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Open Access September 02, 2025

Using materials of radar mapping from spacecrafts as a way to increase reliability, as well as to reduce the cost and time of site selection for extended linear construction projects

Abstract The article describes the use of publicly available materials of radar mapping from spacecraft as a way to increase the reliability, as well as to reduce the cost and time of work to select the site of linear construction projects situated in remote underdeveloped areas. Based on the results of theoretical study and practical application of radar mapping of the Earth's surface from spacecrafts the [...] Read more.
The article describes the use of publicly available materials of radar mapping from spacecraft as a way to increase the reliability, as well as to reduce the cost and time of work to select the site of linear construction projects situated in remote underdeveloped areas. Based on the results of theoretical study and practical application of radar mapping of the Earth's surface from spacecrafts the conclusion is made about the availability of these materials, their reliability (relevance) and accuracy in order to select the site of linear construction projects at the concept design stage.
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Open Access February 24, 2025

Pembrolizumab-induced myelitis in stage 4 renal clear cell carcinoma: a case report

Abstract Pembrolizumab, an immune checkpoint inhibitor targeting the programmed cell death 1 (PD-1) protein, is widely used for renal cell carcinoma but rarely causes central nervous system adverse events such as myelitis. A 58-year-old woman with stage IV renal clear cell carcinoma developed radiating hip pain, paresthesia, hypoesthesia (T10 and below), constipation, urinary retention, and sudden [...] Read more.
Pembrolizumab, an immune checkpoint inhibitor targeting the programmed cell death 1 (PD-1) protein, is widely used for renal cell carcinoma but rarely causes central nervous system adverse events such as myelitis. A 58-year-old woman with stage IV renal clear cell carcinoma developed radiating hip pain, paresthesia, hypoesthesia (T10 and below), constipation, urinary retention, and sudden right-eye blurred vision one month after her sixth cycle of pembrolizumab and lenvatinib. Neurologic examination revealed asymmetrical inferior paraparesis, upper motor neuron signs, and right eye papilledema. MRI demonstrated patchy hyperintensity on C2-C6 and T2-T5, supportive of myelitis. Intravenous methylprednisolone was initiated, leading to pain relief and motor improvement. This is the first reported case of pembrolizumab-induced myelitis in Indonesia, emphasizing the importance of early recognition and corticosteroid therapy for optimal recovery.
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Case Report
Open Access April 25, 2024

Green spaces more adapted and resilient to the current and future climatic conditions in the south of Portugal (Algarve): Xerophytic gardens using xeromorphic succulents

Abstract Considering the current climate conjuncture, it is a consensus that green spaces in large contemporary urban areas should be increasingly more numerous and simultaneously more sustainable, being adapted to the edaphoclimatic conditions of the site, and with reduced maintenance costs. In the case of Algarve, where this research is focused, the current and future water availability, assumes a [...] Read more.
Considering the current climate conjuncture, it is a consensus that green spaces in large contemporary urban areas should be increasingly more numerous and simultaneously more sustainable, being adapted to the edaphoclimatic conditions of the site, and with reduced maintenance costs. In the case of Algarve, where this research is focused, the current and future water availability, assumes a preponderant role in the design of green spaces, where the demands mentioned above can only be achieved if we deviate from conventional landscape practices and develop holistic strategies of management and design of green spaces that integrate different areas of knowledge and not merely aesthetic issues. In this context, this work aims to develop more adapted and resilient landscaping practices to the current and future climatic conditions of the Algarve, thus reinventing the concept of landscaping in the south of Portugal. Thus, it will be of paramount importance to develop more sustainable, resilient and tolerant projects to worsening ecological conditions, particularly limitations associated with water availability. The xeromorphic succulents are a group of plants with mechanisms of tolerance to water stress and with very specific characteristics, being succulence one of the most relevant. Studies on these mechanisms are increasingly frequent, which may prove to be very advantageous in our adaptation to future climatic challenges. In addition, their ornamental potential is enormous, since their bold forms and colours are a veritable sensory explosion, which, combined with their morphological and physiological characteristics, make them the species of choice in the reconversion or creation of xerophytic gardens.
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Open Access October 13, 2023

A Report of Three Cases with Moderate Psoriasis Treated with New Topical Treatment

Abstract Practice guidelines recommend fixed combinations of calcipotriol, a topical vitamin D analogue, and betamethasone dipropionate, a high potency corticosteroid, as first line topical treatment for mild to moderate plaque psoriasis of the body and scalp. A new foaming lotion for treatment of Psoriasis was developed and patented by the Spanish Ministry of Industry, Trade and Tourism (Invention patent [...] Read more.
Practice guidelines recommend fixed combinations of calcipotriol, a topical vitamin D analogue, and betamethasone dipropionate, a high potency corticosteroid, as first line topical treatment for mild to moderate plaque psoriasis of the body and scalp. A new foaming lotion for treatment of Psoriasis was developed and patented by the Spanish Ministry of Industry, Trade and Tourism (Invention patent reference number 202030824). The foaming lotion is composed of clobetasol, papaverine hydrochloride, spironolactone, milk-peptide-complex and propylene glycol. Three cases with moderate Psoriasis aged 34, 36 and 66 years old were treated with our new foaming lotion for 7-8 days. The three patients reported important improvement in the itching sensations and remission of the scaled lesions. Before and after application of the new foaming lotion, Psoriasis Area Severity Index (PASI) scores improved in the first patient from 24.3 to 1.8, in the second patient from 26.1 to 1.8, and in the third patient from 27 to 1.8. Our results show the short-term effectiveness of the new foaming lotion in treating moderate and extensive Psoriasis. Long follow-up is needed to evaluate the remission period of Psoriasis and possible side effects of the new topical treatment.
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Case Report
Open Access September 22, 2023

Bioremediation of Total Polycyclic Aromatic Hydrocarbon in Crude Oil-Contaminated Soil using Costus afer Plant

Abstract Costus afer is a well-known medicinal plant abundant in the Niger Delta region of Nigeria. The successful growth of Costus afer plant on crude oil contaminated soil adds to the list of plants that has potential to get rid of harmful chemical compounds to save human life as well preserve the environment. This study investigates the remediation potential of Costus afer plant at different ages (7, 14, 21, 28, 35, and 42 days old) to decontaminate petroleum hydrocarbon-contaminated soil. To achieve this, contamination of sandy-loam soil was simulated by mixing T0.5, 1.0, and 1.5 L of Bonny-Light crude oil with 48 kg of the soil in three separate reactors to achieve conditions of low, medium, and high contamination, respectively. The reactor with medium-level contaminated soil served as the control. The plants were nursed and transplanted at the stated ages to each reactor except the control. Controlled irrigation was applied, and the setups were housed to shield them from rainfall. After 90 days of treatment, results showed that the 7 days old plants produced the highest amounts of total polycyclic aromatic hydrocarbon (TPAH) reduction of 99.71, 90.10, and 84.06 % in the soil with low, medium, and high contamination, respectively. Furthermore, the sequence of TPAH reduction by the plants was 14 days old > 21 days old > 28 days old > 35 days old > 42-days old. Thus, in addition to its medicinal value, Costus afer [...] Read more.
Costus afer is a well-known medicinal plant abundant in the Niger Delta region of Nigeria. The successful growth of Costus afer plant on crude oil contaminated soil adds to the list of plants that has potential to get rid of harmful chemical compounds to save human life as well preserve the environment. This study investigates the remediation potential of Costus afer plant at different ages (7, 14, 21, 28, 35, and 42 days old) to decontaminate petroleum hydrocarbon-contaminated soil. To achieve this, contamination of sandy-loam soil was simulated by mixing T0.5, 1.0, and 1.5 L of Bonny-Light crude oil with 48 kg of the soil in three separate reactors to achieve conditions of low, medium, and high contamination, respectively. The reactor with medium-level contaminated soil served as the control. The plants were nursed and transplanted at the stated ages to each reactor except the control. Controlled irrigation was applied, and the setups were housed to shield them from rainfall. After 90 days of treatment, results showed that the 7 days old plants produced the highest amounts of total polycyclic aromatic hydrocarbon (TPAH) reduction of 99.71, 90.10, and 84.06 % in the soil with low, medium, and high contamination, respectively. Furthermore, the sequence of TPAH reduction by the plants was 14 days old > 21 days old > 28 days old > 35 days old > 42-days old. Thus, in addition to its medicinal value, Costus afer plant also has the potential to restore crude oil-contaminated soils.
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Open Access August 23, 2023

Determinants and Satisfaction Outcomes of Pregnancy Care in China: The Case of Ghanaian Women in Zhenjiang

Abstract The concept of maternity care satisfaction focuses on women's expectations and results in women having a positive attitude about the care received during pregnancy, childbirth and after birth. The proportion of births to Ghanaian migrant mothers in China is increasing, and there is an increasing demand for information regarding their reproductive health. To reduce maternal and neonatal morbidity [...] Read more.
The concept of maternity care satisfaction focuses on women's expectations and results in women having a positive attitude about the care received during pregnancy, childbirth and after birth. The proportion of births to Ghanaian migrant mothers in China is increasing, and there is an increasing demand for information regarding their reproductive health. To reduce maternal and neonatal morbidity and death rates, it is crucial for foreign women who use maternity services to be satisfied with their care. Ghanaian women's birth experiences in China might be harmed by language and cultural disparities. Little is known about their experiences in China's homogeneous society. A survey of 317 postnatal Ghanaian foreigners in Zhenjiang, China provided the study's data and was analyzed using IBM SPSS Statistics 25. The results showed that (76%) of postnatal foreigners were satisfied with delivery care. Though the satisfaction level was high, respondents raised the issues of poor communication (62.8%) and high cost of delivery care (52.4%) as some of the general experiences they faced. Healthcare providers’ strengthening routine monitoring of maternal and newborn health programs will help deliver more woman-centered care.
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Case Study
Open Access April 28, 2023

Evaluation of the Incidences of Risk Occurrence and Severity in PPP-Procured Mass Housing Projects (PPP-MHPs) in Abuja, Nigeria

Abstract Risks in Public Private Procurement mass housing project (PPP-MHP) initiatives are emerging and this requires early risk identification and allocation to achieve the goal and sustenance of the scheme. The study, being a follow-up of a Delphi survey, elicits the opinion of respondents on the probability of occurrence and severity of identified risks in PPP-MHPs in Nigeria. The study adopts a [...] Read more.
Risks in Public Private Procurement mass housing project (PPP-MHP) initiatives are emerging and this requires early risk identification and allocation to achieve the goal and sustenance of the scheme. The study, being a follow-up of a Delphi survey, elicits the opinion of respondents on the probability of occurrence and severity of identified risks in PPP-MHPs in Nigeria. The study adopts a quantitative research design approach by administering structure questionnaire survey on identified PPP-MHPs partners in Abuja, Nigeria. Data analysis was performed using descriptive and inferential statistical tools such as Mean item score (MIS), standard deviation, and Kruskal Wallis analytical techniques with the aid of SPSS software packages. The findings show that all the listed risk factors were found to be extremely high, very high, high, or moderate in terms of occurrence while all the listed risk factors recorded a very high level of severity on the delivery of PPP-MHPs. The top ten (10) risk factors frequently associated with PPP-MHPs are non-availability of finance, high finance cost, non-involvement of the host community, poor execution of housing policies, corruption and lack of respect for law, wrong perception of housing need by low-income earners, Illegal title to land, land acquisition and site availability, level of demand for the mass housing projects and unstable value of local currency. The respondents differs significantly on 29 risk factors in terms of occurrence and 40 risk factors in term of severity. The study, therefore, recommends that risk management culture should be highly encouraged among the PPP Partners in the sector. The study intends to enumerate the rate of occurrence of some itemized risk factors and their severities on the delivery of PPP – procured mass housing projects in Nigeria and the need to bookmark these risk factors in ensuring the sustainability of the PPP mass housing scheme.
Article
Open Access April 27, 2023

Evaluation of the Critical risk factors in PPP - procured Mass Housing Projects in Abuja Nigeria - A fuzzy synthetic evaluation (FSE) approach

Abstract The study accessed the critical risk factors in public-private partnership (PPP)-procured mass housing project (MHP) delivery in Nigeria. The research design adopts a quantitative approach, using well-structured questionnaires distributed to stakeholders involved in PPP-MHPs i.e. consultants, in-house professionals, contractors, and the organized private sector (OPS) registered with PPP [...] Read more.
The study accessed the critical risk factors in public-private partnership (PPP)-procured mass housing project (MHP) delivery in Nigeria. The research design adopts a quantitative approach, using well-structured questionnaires distributed to stakeholders involved in PPP-MHPs i.e. consultants, in-house professionals, contractors, and the organized private sector (OPS) registered with PPP departments in the Federal Capital Territory Development Authority (FCDA) Abuja, Nigeria. The instrument relates to the background information of respondents and the risk peculiar to PPP-MHP. Sixty-three (63) risk factors were submitted for the respondents to rank using Mean Item score (MIS) for risk occurrence and its severity, while risk significance index (RI) was used to determine the risk impact. Fuzzy Synthetic Evaluation (FSE) method was subsequently applied to determine the risk criticality groups and the overall risk level in the sector. The fuzzy set theory deals with ambiguous, subjective and imprecise judgments peculiar to decision making in construction project risk assessment. It aims to provide a synthetic evaluation of an object relative to a fuzzy decision environment with multiple criteria that requires qualitative linguistic terms. The findings show that thirty-one (31) risk factors were critical in the sector while financial and micro-economic risk group is contributing most significantly to the overall risk level in PPP-MHPs in Nigeria. The top 10 risk factors in the sector include availability of finance, high finance cost, the unstable value of the local currency, lack of creditworthiness, influential economic events (boom/recession), high bidding cost, poor financial market, financial attraction to project investors, interest rate volatility, inflation rate volatility, corruption and lack of respect for the law, non-involvement of the host community and poor execution of housing policies. The implication for practice is that having known the risk group contributing most significantly to the overall risk level in PPP-MHPs, adequate financial and budgetary allocation should be made available before embarking on such venture so as to sustain the scheme in the country. The study is one of the recent researches conducted on housing, since the procurement option is novel in the sector. The study is of immense value to PPP actors in providing necessary information required to formulate risk response methods in minimize the identified risk impact sector.
Article
Open Access November 29, 2022

The Application of Machine Learning in the Corona Era, With an Emphasis on Economic Concepts and Sustainable Development Goals

Abstract The aim of this article is to examine the impacts of Coronavirus Disease -19 (Covid-19) vaccines on economic condition and sustainable development goals. In other words, we are going to study the economic condition during Covid19. We have studied the economic costs of pandemic, benefits in terms of gross domestic product (GDP), public finances and employment, investment on vaccines around the [...] Read more.
The aim of this article is to examine the impacts of Coronavirus Disease -19 (Covid-19) vaccines on economic condition and sustainable development goals. In other words, we are going to study the economic condition during Covid19. We have studied the economic costs of pandemic, benefits in terms of gross domestic product (GDP), public finances and employment, investment on vaccines around the world, progress and totally the economic impacts of vaccines and the impacts of emerging markets (EM) on achieving sustainable development goals (SDGs), including no poverty, good health and well-being, zero hunger, reduced inequality etc. The importance of emerging economies in reducing the harmful effects of the Corona has also been noted. We have tried to do experimental results and forecast daily new death cases from Feb-2020 to Aug-2021 in Iran using Artificial Neural Network (ANN) and Beetle Antennae Search (BAS) algorithm as a case study with econometric models and regression analysis. The findings show that Covid19 has had devastating economic and health effects on the world, and the vaccine can be very helpful in eliminating these effects specially in long-term. We observed that there is inequality in the distribution of Corona vaccines in rich countries compared to poor which EM can decrease the gap between them. The results show that both models (i.e., Artificial intelligence (AI) and econometric models) almost have the same results but AI optimization models can robust the model and prediction. The main contribution of this article is that we have surveyed the impacts of vaccination from socio-economic viewpoint not just report some facts and truth. We have surveyed the impacts of vaccines on sustainable development goals and the role of EM in achieving SDGs. In addition to using the theoretical framework, we have also used quantitative and empirical results that have rarely been seen in other articles.
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Open Access October 28, 2022

Calabrian Native Project: Botanical Education Applied to Conservation and Valorization of Autochthonous Woody Plants

Abstract Calabria is a floristic hotspot just at the center of Mediterranean Sea. Unfortunately, an increasing number of alien plant species threats this natural heritage, exactly while the crucial role of botany in secondary schools of Italy has been definitely dismantled. Calabrian Native Project is an environmental education project planned by Istituto Tecnico Agrario of Catanzaro that, reintroducing [...] Read more.
Calabria is a floristic hotspot just at the center of Mediterranean Sea. Unfortunately, an increasing number of alien plant species threats this natural heritage, exactly while the crucial role of botany in secondary schools of Italy has been definitely dismantled. Calabrian Native Project is an environmental education project planned by Istituto Tecnico Agrario of Catanzaro that, reintroducing some key concepts of botany and biogeography, allowing pupils to experience a botanical excursion in the close-to-the-school Mediterranean Biodiversity Park, gives them the opportunity to become acquainted with both native and alien species. Pupils are asked to collect native plant propagules and to seed or cultivate the material in the school greenhouses, and to take care of these plants until their use. The prevalent outdoor and laboratory approach to the issue of bioinvasions, make the project very effective. This feature, with the low cost and reduced technology inputs, make the project highly replicable in other contexts, just focusing appropriate target species.
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Open Access January 16, 2026

Evaluating the Effectiveness of Occupational Health and Safety Management Practices in Improving Workplace Safety in Nigerian Construction Sites

Abstract The construction industry remains one of the most hazardous sectors globally, with Nigeria experiencing a high incidence of workplace accidents despite the adoption of Occupational Health and Safety Management (OHSM) frameworks. This study evaluated the effectiveness of OHSM practices in improving workplace safety across construction companies in Nigeria’s coastal cities. A cross-sectional design [...] Read more.
The construction industry remains one of the most hazardous sectors globally, with Nigeria experiencing a high incidence of workplace accidents despite the adoption of Occupational Health and Safety Management (OHSM) frameworks. This study evaluated the effectiveness of OHSM practices in improving workplace safety across construction companies in Nigeria’s coastal cities. A cross-sectional design was employed, combining quantitative surveys of construction workers (n = 1,400) with qualitative interviews of 35 managers and supervisors. Quantitative data were analyzed using SPSS version 28, while thematic analysis was applied to qualitative responses. Findings revealed a generally positive perception of OHSM, with 54.4% of workers rating OHS policy effectiveness as “Good” and 52.0% rating health outcomes as “Good.” However, accident frequency remained a concern, with 46.4% reporting accidents occurred “Occasionally” and 31.9% acknowledging them as “Frequent” or “Very Frequent.” Comparative analysis showed indigenous firms were rated higher in policy effectiveness and health outcomes but also reported slightly higher accident frequencies than international firms. Thematic analysis identified five key monitoring and evaluation strategies including routine inspections, regular training, audits, behavioural reinforcement, and access control, Also, five measures of OHSM effectiveness, including compliance observation, incident tracking, KPIs, employee feedback, and benchmarking. OHSM was found to positively influence project outcomes by reducing compensation costs, enhancing reputation, and improving supervision and quality of work. OHSM practices in Nigeria’s construction sector are perceived as effective in policy and health outcomes, yet accident rates remain a critical challenge. The study underscores the importance of continuous training, stricter enforcement, behavioural reinforcement, and systematic performance evaluation.
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Open Access January 23, 2026

Synthesising Stage Blood Using Ghanaian Indigenous Materials: From Material Scarcity to Artistic Self-Reliance

Abstract This study addresses the critical challenge of material scarcity within Ghana’s creative industries by pioneering the synthesis of professional-grade stage blood from indigenous, locally-sourced materials. In the context of Ghanaian theatre and film, practitioners face significant barriers due to the high cost and limited availability of imported special effects products, often resulting in the [...] Read more.
This study addresses the critical challenge of material scarcity within Ghana’s creative industries by pioneering the synthesis of professional-grade stage blood from indigenous, locally-sourced materials. In the context of Ghanaian theatre and film, practitioners face significant barriers due to the high cost and limited availability of imported special effects products, often resulting in the use of inadequate substitutes that compromise aesthetic realism, safety, and narrative authenticity. This paper responds by exploring the potential of cassava starch, tapioca, kenkey dough, and fufu wax. Grounded in Schumacher’s theory of Appropriate Technology, the paper reframes indigenous resources not as inferior alternatives but as technologically and contextually appropriate solutions that align with Ghana’s economic, environmental, and social realities. The study provides detailed, reproducible recipes for both flowing and clotted blood variants, validated through practical application in simulated special effects such as gunshot wounds and deep-tissue scars. These formulations meet key performance criteria: visual fidelity under theatrical and cinematic conditions, controlled viscosity, ease of application and removal, and performer safety. Beyond technical innovation, this research contributes to shifting academic and professional discourse from dependency and scarcity toward resourcefulness, sustainability, and artistic self-reliance. It offers a practical framework for reducing production costs, enhancing the quality of visual storytelling, and fostering local value chains within Ghana’s growing creative economy.
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Open Access September 19, 2025

Effectiveness of Subglottal Suctioning Could Prevent the Develop of VAP in the Patient on Mechanic Ventilator

Abstract VAP, or Ventilator Associated Pneumonia, is a type of pneumonia that arises in patients receiving mechanical ventilation. This condition is a serious complication and can lead to the patient's decline while on a mechanical ventilator, posing a significant risk for secondary complications if not addressed promptly. In particular, VAP is a prevalent issue in intensive care units, where the [...] Read more.
VAP, or Ventilator Associated Pneumonia, is a type of pneumonia that arises in patients receiving mechanical ventilation. This condition is a serious complication and can lead to the patient's decline while on a mechanical ventilator, posing a significant risk for secondary complications if not addressed promptly. In particular, VAP is a prevalent issue in intensive care units, where the healthcare team works to prevent further deterioration of the patient. VAP is associated with a notably high mortality rate, particularly in individuals with weakened immune systems, as well as in younger and older populations. Extended intubation and prolonged sedation can contribute to the onset of VAP. The previous study had found that incidence of VAP accounts for 9 % to 27 % endotracheal intubated patients, whereas VAP has a mortality rate ranging from 25 % to 50 % [1-3]. VAP increased ICU and hospital length of stay, antibiotic consumption, and healthcare cost (Zhi Mao et al, 2016) [4]. While using the subglottic suctioning could prevent and help the intubated patient to decreased the development of VAP. The study shown by Smith et al (2021) [5] SSD is a technique employed to reduce micro aspiration of oropharyngeal secretions in patients with cuffed endotracheal airways. Aspiration of oropharyngeal secretions is the accepted cause of the majority of ventilator-associated pneumonia (VAP), a complication of invasive ventilation with high associated mortality. Another study by Rahul Gujadhur et al (2005) [6], subglottic suction has also been shown to delay the onset of VAP but no benefits in terms of ventilation time, hospital stay or mortality benefit have ever been shown. This investigation into subglottic suctioning may assist the healthcare team, particularly in the intensive care unit, in preventing the development of VAP and shortening the duration of ventilation for patients. The advantages of subglottic suctioning are often debated, particularly regarding its impact on the duration of intubation. However, recent research indicates that implementing subglottic suctioning within a time frame of fewer than three days could help reduce intubation duration and lead to improved patient recovery.
Abstract
Open Access September 04, 2025

Evidence-Based Protocols for the Prevention and Treatment of Prosthetic Joint Infection in Total Hip Arthroplasty: A Systematic Review

Abstract Objective: This systematic review aimed to identify, synthesize, and critically analyze the available evidence on clinical protocols used for the prevention and treatment of prosthetic joint infection (PJI) in total hip arthroplasty (THA), based on studies published between 2000 and 2025. Methods: The review was conducted according to PRISMA guidelines. Electronic searches were performed in PubMed (MEDLINE), Scopus, Web of Science, and Embase between January and April 2025. Eligible studies included clinical trials, cohort studies, case-control studies, systematic reviews, and meta-analyses published in English that addressed either preventive or therapeutic strategies for PJI in THA. Study selection, data extraction, and quality assessment were carried out independently by two reviewers. Due to the heterogeneity of the included studies, a qualitative synthesis was performed. Results: A total of 32 studies were included. Preventive measures identified in the literature comprised combined antibiotic prophylaxis (cefazolin and gentamicin), multimodal perioperative protocols such as ACERTO, nasal decolonization for Staphylococcus aureus [...] Read more.
Objective: This systematic review aimed to identify, synthesize, and critically analyze the available evidence on clinical protocols used for the prevention and treatment of prosthetic joint infection (PJI) in total hip arthroplasty (THA), based on studies published between 2000 and 2025. Methods: The review was conducted according to PRISMA guidelines. Electronic searches were performed in PubMed (MEDLINE), Scopus, Web of Science, and Embase between January and April 2025. Eligible studies included clinical trials, cohort studies, case-control studies, systematic reviews, and meta-analyses published in English that addressed either preventive or therapeutic strategies for PJI in THA. Study selection, data extraction, and quality assessment were carried out independently by two reviewers. Due to the heterogeneity of the included studies, a qualitative synthesis was performed. Results: A total of 32 studies were included. Preventive measures identified in the literature comprised combined antibiotic prophylaxis (cefazolin and gentamicin), multimodal perioperative protocols such as ACERTO, nasal decolonization for Staphylococcus aureus, silver-impregnated dressings, and structured post-discharge surveillance. Treatment strategies included DAIR (Debridement, Antibiotics, and Implant Retention), the DAPRI technique, one-stage and two-stage revision surgeries, muscle flap reconstructions, and protocols without spacers. These interventions were associated with significantly reduced infection rates and improved clinical outcomes when applied appropriately and in accordance with patient-specific factors. Conclusion: Effective prevention and treatment of PJI in total hip arthroplasty require a systematic and evidence-based approach. Integrated protocols—spanning preoperative optimization, meticulous intraoperative techniques, and rigorous postoperative monitoring—have proven effective in reducing infection incidence. In cases of established infection, surgical management must be tailored to the timing of infection, microbial profile, and host conditions. Two-stage revision remains the gold standard for complex infections, while one-stage revision and emerging techniques like DAPRI offer promising results in selected cases. This review contributes to the standardization of clinical practice and supports improved patient outcomes.
Systematic Review
Open Access June 11, 2025

Biomechanical and Functional Performance of Hip Prosthesis Materials in Total Hip Arthroplasty: A Systematic Review

Abstract This systematic review aimed to evaluate the biomechanical properties, functional performance, and clinical outcomes of different hip prosthesis materials and designs used in total hip arthroplasty (THA). A comprehensive search strategy identified 34 peer-reviewed studies published between 2015 and 2024. The materials investigated included cobalt-chromium-molybdenum (CoCrMo), titanium alloys, [...] Read more.
This systematic review aimed to evaluate the biomechanical properties, functional performance, and clinical outcomes of different hip prosthesis materials and designs used in total hip arthroplasty (THA). A comprehensive search strategy identified 34 peer-reviewed studies published between 2015 and 2024. The materials investigated included cobalt-chromium-molybdenum (CoCrMo), titanium alloys, PEEK, ceramics, and advanced surface coatings such as polycrystalline diamond (PCD). In addition, dual mobility systems, lattice structures, and additively manufactured and patient-specific implants were assessed. The studies utilized clinical trials, finite element analysis, and biomechanical testing to compare outcomes such as wear resistance, stress distribution, osseointegration, and range of motion. The findings demonstrated that titanium alloys and porous lattice structures reduce stress shielding, while ceramics and CoCrMo provide superior wear resistance. Dual mobility implants improved joint stability and range of motion, particularly in high-risk patients. PEEK and PCD showed promising properties but lacked robust long-term data. The integration of advanced manufacturing technologies and material innovations has led to more personalized and biomechanically efficient solutions for THA. Further longitudinal studies are needed to validate these developments. This review provides a critical synthesis of the biomechanical, functional, and clinical implications of contemporary hip prosthetic systems.
Systematic Review
Open Access April 30, 2025

An Alternative Renewable Energy Source: Thermal Expansion and Contraction of Materials

Abstract The processes of technical and technological development are unequivocally linked to increasing energy consumption, with a significant portion of energy being produced from fossil fuels worldwide. The reserves of natural energy sources such as petroleum, gas, coal, and turf are finite. The transition to renewable energy sources has been ongoing for a long time, but share in global energy [...] Read more.
The processes of technical and technological development are unequivocally linked to increasing energy consumption, with a significant portion of energy being produced from fossil fuels worldwide. The reserves of natural energy sources such as petroleum, gas, coal, and turf are finite. The transition to renewable energy sources has been ongoing for a long time, but share in global energy consumption remains lower than desired. The main limitations include limited availability, inability to operate continuously throughout the year, high costs, and a lack of materials and devices capable of withstanding high temperatures and pressures. The goal of our research is to create a device that generates electricity using a new type of renewable energy source based on the thermal expansion and contraction of materials. This paper presents the construction, details, and working principles of the new device. The primary focus is on utilizing materials and components that are readily available. The proposed method has own advantages, addresses some of the aforementioned limitations, and can be particularly beneficial for providing electrical energy in remote areas. Calculations indicate that the device built using this new method will be competitive with appliances that utilize other renewable energy sources in terms of features and efficiency.
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Open Access April 10, 2025

Advancements in Pharmaceutical IT: Transforming the Industry with ERP Systems

Abstract The pharmaceutical industry is undergoing a profound transformation driven by advancements in Information Technology (IT), with Enterprise Resource Planning (ERP) systems playing a pivotal role in reshaping operations. These systems offer integrated solutions that streamline key business processes, such as production, inventory management, supply chain optimization, regulatory compliance, and data [...] Read more.
The pharmaceutical industry is undergoing a profound transformation driven by advancements in Information Technology (IT), with Enterprise Resource Planning (ERP) systems playing a pivotal role in reshaping operations. These systems offer integrated solutions that streamline key business processes, such as production, inventory management, supply chain optimization, regulatory compliance, and data integration, contributing significantly to operational efficiency and organizational agility. This paper explores the evolution and impact of ERP systems within the pharmaceutical sector, highlighting their contributions to overcoming the industry’s inherent challenges, including complex regulatory requirements, the need for accurate and real-time data, and the demand for supply chain resilience. The integration of cloud-based ERP solutions, the incorporation of emerging technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), and enhanced data analytics capabilities have revolutionized pharmaceutical IT. These advancements not only reduce operational costs, improve forecasting accuracy, and enhance collaboration but also ensure compliance with stringent global regulations, such as Good Manufacturing Practices (GMP) and FDA guidelines. Moreover, ERP systems have been instrumental in managing the pharmaceutical supply chain, ensuring product traceability, and improving inventory control and order fulfillment processes. This manuscript examines how ERP systems enable pharmaceutical companies to maintain high standards of product quality, improve decision-making, and ensure the safety and efficacy of drugs through robust tracking and auditing mechanisms. A case study of a pharmaceutical company that implemented an ERP system demonstrates the tangible benefits, including increased operational efficiency, improved compliance rates, and enhanced customer satisfaction. However, despite the clear advantages, challenges such as customization complexities, data integration issues, and resistance to change remain. As the pharmaceutical industry continues to evolve, ERP systems will remain a cornerstone of digital transformation, facilitating smarter decision-making, better resource management, and enhanced collaboration across global operations. This paper also identifies future trends, including the potential of AI and blockchain technologies in further strengthening ERP systems and transforming the pharmaceutical landscape.
Review Article
Open Access February 26, 2025

Innovations and Challenges in Pharmaceutical Supply Chain, Serialization and Regulatory Landscape

Abstract The pharmaceutical supply chain has become increasingly complex and vulnerable to various risks, including counterfeit drugs, diversion, and fraud. As these challenges threaten patient safety and the integrity of global healthcare systems, serialization has emerged as a pivotal innovation in pharmaceutical logistics and regulatory compliance. Serialization involves assigning unique identifiers to [...] Read more.
The pharmaceutical supply chain has become increasingly complex and vulnerable to various risks, including counterfeit drugs, diversion, and fraud. As these challenges threaten patient safety and the integrity of global healthcare systems, serialization has emerged as a pivotal innovation in pharmaceutical logistics and regulatory compliance. Serialization involves assigning unique identifiers to individual drug packages, enabling precise tracking and authentication at every stage of the supply chain. This process provides unprecedented transparency, enhances product security, and facilitates real-time monitoring of pharmaceutical products as they move from manufacturers to end consumers. Despite its potential to revolutionize pharmaceutical traceability, the integration of serialization technologies faces numerous obstacles. These include high implementation costs, regulatory inconsistencies across regions, and the technological challenges of managing vast amounts of data. Moreover, the complex, multi-tiered nature of the global supply chain introduces additional risks related to data integrity, cybersecurity, and interoperability between systems. As pharmaceutical companies seek to navigate these challenges, innovations in serialization technology—such as blockchain, artificial intelligence (AI), the Internet of Things (IoT), and radio frequency identification (RFID)—are providing promising solutions to enhance efficiency, reduce fraud, and increase visibility. This manuscript explores both the innovative advancements and the key challenges associated with the integration of serialization in the pharmaceutical supply chain. It delves into the evolving regulatory landscape, highlighting the need for global harmonization of serialization standards, and examines the impact of serialization on securing pharmaceutical distribution networks. Additionally, the paper emphasizes the importance of collaboration among manufacturers, technology providers, and regulatory bodies in overcoming implementation barriers and realizing the full potential of serialization. As the pharmaceutical industry moves towards a more interconnected and data-driven future, serialization promises to play a central role in shaping the next generation of drug safety and supply chain management. By addressing the hurdles to adoption and leveraging emerging technologies, the pharmaceutical sector can create a more secure, transparent, and efficient supply chain that better serves public health and fosters greater trust among consumers and healthcare professionals alike.
Review Article
Open Access February 24, 2025

Socioeconomic Status, Trauma, Cognitive Function, Impulsivity, Reward Salience, and Future Substance Use: Role of Left Caudate Connectivity with the Cingulo-Opercular Network

Abstract Background: While understanding how corticostriatal connectivity is associated with socioeconomic status (SES), trauma exposure, cognitive function, reward salience, impulsivity, and future substance use is essential to identifying neurobiological pathways that contribute to health disparities and behavioral outcomes, very few studies have tested the role of left caudate resting-state [...] Read more.
Background: While understanding how corticostriatal connectivity is associated with socioeconomic status (SES), trauma exposure, cognitive function, reward salience, impulsivity, and future substance use is essential to identifying neurobiological pathways that contribute to health disparities and behavioral outcomes, very few studies have tested the role of left caudate resting-state functional connectivity (rsFC) with the cingulo-opercular network as a proxy of corticostriatal connectivity in social, cognitive, and behavioral processes. Objective: This study investigates the associations between left caudate-cingulo-opercular connectivity and multiple biopsychosocial domains, including low SES, high trauma exposure (financial and life events), cognitive function, reward salience, impulsivity, depression, and future substance use (tobacco and marijuana use). Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data were analyzed to assess connectivity between the left caudate and the cingulo-opercular network. Data on socioeconomic status, trauma exposure, cognitive performance, and mental health were collected from participants. Future substance use behaviors were evaluated through longitudinal follow-ups. Correlation and regression analyses were conducted to examine relationships between corticostriatal connectivity and the targeted domains. Results: Corticostriatal hypoconnectivity was associated with lower SES, higher trauma exposure, poorer cognitive function, heightened reward salience, higher impulsivity, and history of depression. Additionally, corticostriatal hypoconnectivity at baseline predicted future tobacco and marijuana use during follow-up years. Conclusion: Corticostriatal hypoconnectivity, particularly the rsFC between the left caudate and the cingulo-opercular network, may represent a potential mechanism linking a wide range of social, emotional, and behavioral problems in youth. These findings suggest that corticostriatal hypoconnectivity could serve as a neurobiological marker for identifying individuals at risk for depression, low cognitive function, high reward salience, impulsivity, and substance use, emphasizing the interplay between socioeconomic and neurocognitive factors in shaping behavioral health trajectories.
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Open Access February 09, 2025

The Future of Longevity Medicine from the Lens of Digital Therapeutics

Abstract Digital therapeutics (DTx) are emerging as a pivotal tool in promoting longevity by addressing non-communicable diseases (NCDs) such as diabetes, cardiovascular diseases, and mental health disorders. These software-driven interventions offer personalized, evidence-based treatments that can be accessed via digital devices, making healthcare more accessible and scalable. One of the key advancements [...] Read more.
Digital therapeutics (DTx) are emerging as a pivotal tool in promoting longevity by addressing non-communicable diseases (NCDs) such as diabetes, cardiovascular diseases, and mental health disorders. These software-driven interventions offer personalized, evidence-based treatments that can be accessed via digital devices, making healthcare more accessible and scalable. One of the key advancements in DTx is the integration of artificial intelligence (AI) and machine learning (ML) to tailor interventions based on individual health data. This personalization enhances the effectiveness of treatments and supports preventive care by identifying risk factors early. The need for digital therapeutics is underscored by the rising prevalence of NCDs, which are responsible for a significant portion of global mortality and healthcare costs. Traditional healthcare systems often struggle to provide timely and personalized care, especially in low-resource settings. DTx can bridge this gap by offering cost-effective solutions that are easily scalable. Moreover, digital therapeutics can address health inequities by providing low-cost interventions to underserved populations, thereby reducing the burden of NCDs and improving overall health outcomes. As technology continues to evolve, the potential for DTx to enhance longevity and quality of life becomes increasingly promising. Recent advancements in longevity medicine and technology have focused on extending both lifespan and healthspan, ensuring that people not only live longer but also maintain good health throughout their extended years. This review article highlights these advancements that are contributing to this compelling subject of Longevity.
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Review Article
Open Access January 24, 2025

Neurocognitive, Emotional, and Behavioral Costs for Adolescents Due to Diminished Returns of Parental Employment on Trauma

Abstract Background: Parental employment is a significant social determinant of children's developmental outcomes, shaping their cognitive and behavioral trajectories. However, the effects of parental employment may not be equally protective across racial groups. The Minority Diminished Returns (MDRs) framework suggests that socioeconomic status (SES) factors, such as employment, yield fewer [...] Read more.
Background: Parental employment is a significant social determinant of children's developmental outcomes, shaping their cognitive and behavioral trajectories. However, the effects of parental employment may not be equally protective across racial groups. The Minority Diminished Returns (MDRs) framework suggests that socioeconomic status (SES) factors, such as employment, yield fewer protective benefits for Black families compared to White families. Objective: This study investigates the diminished returns of parental employment on trauma and associated neurocognitive and behavioral outcomes in children, with a focus on racial variation in these effects. Methods: Using data from the Adolescent Brain Cognitive Development (ABCD) study, a large and diverse sample of children was analyzed. We applied MDRs theory and social determinants of health frameworks to examine the association between parental employment, trauma, and children's cognitive and behavioral outcomes. The analysis controlled for family SES, neighborhood factors, and racial group differences. Results: Preliminary findings suggest that while parental employment is generally protective against trauma, the strength of this association is diminished for Black children. Black families with employed parents experience higher levels of trauma and stress compared to their White counterparts, which may contribute to racial disparities in cognitive and behavioral outcomes. Conclusion: Parental employment may not equally buffer against trauma-related risks for Black children, reflecting the broader pattern of diminished returns for racially disadvantaged groups. These findings highlight the need for policies addressing the unequal benefits of SES across racial groups.
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Open Access January 22, 2025

Tech Transformations: Modern Solutions for Obstructive Sleep Apnea

Abstract Recent advancements in the screening, diagnosis, and management of obstructive sleep apnea (OSA) have significantly improved patient outcomes. For screening, the use of home sleep apnea testing (HSAT) has become more prevalent, offering a convenient and cost-effective alternative to traditional in-lab polysomnography. HSAT devices have shown good specificity and sensitivity, particularly in [...] Read more.
Recent advancements in the screening, diagnosis, and management of obstructive sleep apnea (OSA) have significantly improved patient outcomes. For screening, the use of home sleep apnea testing (HSAT) has become more prevalent, offering a convenient and cost-effective alternative to traditional in-lab polysomnography. HSAT devices have shown good specificity and sensitivity, particularly in patients with a high pre-test probability of OSA. In terms of diagnosis, advancements in wearable technology and mobile health applications have enabled continuous monitoring of sleep patterns and respiratory parameters. These tools provide valuable data that can be used to identify OSA more accurately and promptly. Additionally, machine learning algorithms are being integrated into diagnostic processes to enhance the accuracy of OSA detection by analyzing large datasets and identifying patterns indicative of the condition. Management of OSA has also seen significant progress. Continuous positive airway pressure (CPAP) therapy remains the gold standard, but new developments include auto-adjusting CPAP devices that optimize pressure settings based on real-time feedback. Mandibular advancement devices and hypoglossal nerve stimulation are emerging as effective alternatives for patients who are CPAP-intolerant. Furthermore, lifestyle interventions such as weight management, positional therapy, and exercise have been shown to complement medical treatments, leading to better overall outcomes. This review article highlights these advancements that collectively contribute to improved patient adherence, reduced symptoms, and enhanced quality of life for individuals with OSA.
Review Article
Open Access January 09, 2025

Advances in the Synthesis and Optimization of Pharmaceutical APIs: Trends and Techniques

Abstract The synthesis and optimization of Active Pharmaceutical Ingredients (APIs) is fundamental to pharmaceutical drug development, directly influencing drug efficacy, safety, and cost-effectiveness. Over recent years, significant advancements in synthetic methodologies and manufacturing technologies have transformed API production. This manuscript provides an overview of the latest innovations in API [...] Read more.
The synthesis and optimization of Active Pharmaceutical Ingredients (APIs) is fundamental to pharmaceutical drug development, directly influencing drug efficacy, safety, and cost-effectiveness. Over recent years, significant advancements in synthetic methodologies and manufacturing technologies have transformed API production. This manuscript provides an overview of the latest innovations in API synthesis, focusing on key techniques such as green chemistry, continuous flow chemistry, biocatalysis, and automation. Green chemistry principles, including solvent substitution and catalytic reactions, have enhanced sustainability by reducing waste and energy consumption. Continuous flow chemistry offers improved reaction control, scalability, and safety, while biocatalysis provides an eco-friendly alternative for synthesizing complex and chiral APIs. Additionally, the integration of automation and advanced process control using machine learning and real-time monitoring has optimized production efficiency and consistency. The manuscript also discusses the challenges associated with regulatory compliance and quality assurance, highlighting the role of advanced analytical techniques such as HPLC, NMR, and mass spectrometry in ensuring API purity. Looking ahead, personalized medicine and smart manufacturing technologies, including blockchain for traceability, are expected to drive further innovation in API production. This review concludes by emphasizing the need for continued advancements in sustainability, efficiency, and scalability to meet the evolving demands of the pharmaceutical industry, ultimately enabling the development of safer, more effective, and environmentally responsible medicines.
Review Article
Open Access November 27, 2024

Bead Jewellery Industry in Ghana: Problems and Solutions

Abstract Bead jewellery is common in all Ghanaian communities. Bead jewellers are well-known for their important bead jewellery production and have advanced to the Master craft level. The industry can be utilized if the industry's difficulties are discovered and remedied. The study area for the research includes Ghana's Eastern, Ashanti, and Greater Accra Regions. The study's population included bead [...] Read more.
Bead jewellery is common in all Ghanaian communities. Bead jewellers are well-known for their important bead jewellery production and have advanced to the Master craft level. The industry can be utilized if the industry's difficulties are discovered and remedied. The study area for the research includes Ghana's Eastern, Ashanti, and Greater Accra Regions. The study's population included bead jewellers, bead jewellery firms, bead dealers, bead aficionados, clients, and bead makers. With a sample size of 30, data was gathered mostly through direct observations, interviews, and document reviews. The study went over the procedure for securing land for a bead jewellery workshop. According to a survey conducted by the Ghanaian Chamber of Commerce and Industry (GCCII), Ghanaian bead jewellers should use qualified designers. Cost pooling in legal services, accounting, and consulting is likely to save money.
Case Study
Open Access November 19, 2024

The Cost of Opportunity: Anti-Black Discrimination in High Resource Settings

Abstract Objective: Inequalities exist in children’s educational outcomes—including reading proficiency, school discrimination, and school disciplinary actions—across zip codes with different levels of educational childhood opportunity index (COI). This study examines the interaction between race and educational environment on children’s educational outcomes. We hypothesize that race, parental [...] Read more.
Objective: Inequalities exist in children’s educational outcomes—including reading proficiency, school discrimination, and school disciplinary actions—across zip codes with different levels of educational childhood opportunity index (COI). This study examines the interaction between race and educational environment on children’s educational outcomes. We hypothesize that race, parental education, and their interaction are associated with perceived school discrimination, which in turn reduces their cognitive, academic, and emotional wellbeing. We also hypothesize that Black children with high socioeconomic status (SES) report high perceived school discrimination in high-COI settings. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study, which measures a wide range of educational, cognitive, and emotional outcomes. At the same time, the ABCD children are sampled across areas with vast differences in COI rankings, that can be classified into these five categories: very high, high, average, low, and very low educational COIs. Our structural equation models (SEM) tested the additive and interactive effects of race and educational attainment on perceived school discrimination, and the effects of school discrimination on various cognitive abilities (reading proficiency, picture vocabulary, and list sorting working memory), school suspension, as well as depressed mood. Our multi-group SEM assessed how these relationships vary across educational COI levels. Results: Our findings showed that high SES Black children report highest school discrimination in residential areas with highest COIs. This is based on the observation that the interaction between race and parental education on experiences of school discrimination were only significant in areas with highest COI. Across residential areas with different COI levels, students who experienced higher school discrimination had higher suspension, worse depression, and worse cognitive performance. Conclusion: While higher COIs are associated with better academic outcomes, Black-White gaps exist in the role of increased COI through increased racial bias that children perceive. These findings underscore the complexity of educational equity, suggesting that improving COI alone is insufficient for eliminating racial disparities in school experiences. Policies should be in place to reduce school-based discrimination against Black students in high COI settings.
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Open Access November 07, 2024

Optimizing Pharmaceutical Supply Chain: Key Challenges and Strategic Solutions

Abstract Pharmaceutical supply chains are critical to ensuring the availability of safe and effective medications, yet they face numerous challenges that can jeopardize public health. This article provides a comprehensive analysis of the key issues impacting pharmaceutical supply chains, including regulatory compliance, demand forecasting, supply chain visibility, quality assurance, and geopolitical risks. [...] Read more.
Pharmaceutical supply chains are critical to ensuring the availability of safe and effective medications, yet they face numerous challenges that can jeopardize public health. This article provides a comprehensive analysis of the key issues impacting pharmaceutical supply chains, including regulatory compliance, demand forecasting, supply chain visibility, quality assurance, and geopolitical risks. Regulatory compliance remains a significant concern due to the stringent guidelines imposed by authorities such as the FDA and EMA, which can lead to increased operational costs and time delays. Additionally, traditional demand forecasting methods often fail to accurately predict fluctuations in drug demand, resulting in stockouts or excess inventory. Limited supply chain visibility further complicates these challenges, hindering timely decision-making and operational efficiency. Quality assurance is paramount, as maintaining the integrity of pharmaceutical products throughout the supply chain is crucial to preventing costly recalls and ensuring patient safety. Moreover, the globalization of supply chains introduces vulnerabilities to geopolitical risks, trade disputes, and natural disasters. In response to these issues, this article outlines strategic recommendations for optimizing pharmaceutical supply chains. These include leveraging advanced analytics and IoT technologies to enhance demand forecasting and visibility, strengthening compliance through automated systems and training, fostering collaboration among stakeholders, implementing robust risk management frameworks, and investing in quality management systems. By adopting these strategies, pharmaceutical companies can enhance the efficiency and resilience of their supply chains, ultimately ensuring the continuous availability of essential medications for patients worldwide. This analysis serves as a critical resource for industry professionals seeking to navigate the complexities of pharmaceutical supply chains in an increasingly dynamic global environment.
Review Article
Open Access November 01, 2024

Impacts of Drug Shortages in the Pharmaceutical Supply Chain

Abstract Drug shortages represent a significant and growing challenge within the pharmaceutical supply chain, with profound implications for patient care, public health, and healthcare costs. This manuscript provides a comprehensive examination of the causes and impacts of drug shortages, highlighting the multifaceted nature of this issue. Key factors contributing to shortages include manufacturing [...] Read more.
Drug shortages represent a significant and growing challenge within the pharmaceutical supply chain, with profound implications for patient care, public health, and healthcare costs. This manuscript provides a comprehensive examination of the causes and impacts of drug shortages, highlighting the multifaceted nature of this issue. Key factors contributing to shortages include manufacturing complications, limited availability of active pharmaceutical ingredients (APIs), market dynamics that discourage the production of less profitable medications, and regulatory challenges that slow down the approval process for new manufacturing capacities. The consequences of these shortages are far-reaching. Patients often face treatment delays, which can lead to adverse health outcomes, increased hospitalization rates, and even mortality. Healthcare providers experience heightened operational costs as they seek alternative therapies and manage complications resulting from inadequate treatment. Furthermore, the frequent occurrence of drug shortages erodes public trust in both the healthcare system and the pharmaceutical industry, leading to decreased patient adherence to prescribed therapies. To mitigate the impacts of drug shortages, this manuscript proposes several strategic solutions, including enhanced communication among stakeholders, diversification of supply sources, increased regulatory flexibility, and collaborative approaches between public and private sectors. Additionally, raising awareness among healthcare providers and patients regarding the causes and potential alternatives can empower stakeholders to navigate shortages effectively. Ultimately, addressing drug shortages necessitates a proactive and coordinated effort from all participants in the pharmaceutical supply chain. By implementing these strategies, stakeholders can enhance the resilience of the supply chain, ensuring that essential medications remain accessible and that patient care is not compromised. The findings of this manuscript underscore the urgent need for ongoing vigilance and collaborative action to tackle the challenges posed by drug shortages, safeguarding public health and improving healthcare outcomes globally.
Review Article
Open Access October 09, 2024

Neuroprotection: at what cost, at what time, at what price?

Abstract Stroke and its disability have deserved the notoriety of a severe and potentially lethal condition, whose treatment is still challenging. The widely craved result of saving as much as possible from the neural tissue and eventually reviving what is thought to be in the ischemic penumbra – if not already dead and gone – is the outcome every clinician is dreaming of. There are several reviews on the [...] Read more.
Stroke and its disability have deserved the notoriety of a severe and potentially lethal condition, whose treatment is still challenging. The widely craved result of saving as much as possible from the neural tissue and eventually reviving what is thought to be in the ischemic penumbra – if not already dead and gone – is the outcome every clinician is dreaming of. There are several reviews on the issue, which have discussed several options of achieving neuroprotection in acute ischemic stroke. Of course, reviews are not and do not pretend to be exhaustive; new drugs enter repeatedly in the scene. We would limit our comments on some of the pharmacological agents, that although seem to be worldwide available, are still looking for obtaining the citizenship in the therapeutic armamentarium of acute ischemic stroke.
Commentary
Open Access September 22, 2024

Societal Perception of New Religious Movements’ Televangelism: A Study of House of Power Ministry International and Gilgal Pentecostal Prayer Ministry International in Dunkwa-On-Offin in the Central Region of Ghana

Abstract This aimed to examine the societal perception of new religious movements' televangelism in Dunkwa-On-Offin, Ghana's Central Region. The study used a sequential explanatory mixed-methods design, using the mixed methods approach to research. The population of this study comprised Women, Regular churchgoers, believers, and those listening to televangelism services by new religious movements, as well [...] Read more.
This aimed to examine the societal perception of new religious movements' televangelism in Dunkwa-On-Offin, Ghana's Central Region. The study used a sequential explanatory mixed-methods design, using the mixed methods approach to research. The population of this study comprised Women, Regular churchgoers, believers, and those listening to televangelism services by new religious movements, as well as clergy, lay leaders, and other male worshippers. Random and purposive sampling techniques were used to select 200 women and 20 men from House of Power Ministry International and GILGAL Pentecostal Prayer Ministry International as the respondents for the study. The instruments used for data collection were questionnaires and interview guides. IBM SPSS statistics software version 23 was used to analyse the quantitative data, while qualitative data was analysed thematically with an interpretative lens. The study has revealed that society perceives the televangelism movements as helpful and encouraging but could also create trouble in fundamental Christian worship principles. The study also indicates that televangelists emphasise material things rather than spiritual matters. Other concerns included that televangelism brings about the separation of family and friends because they always inform members that their friends and family are evil. It is recommended that there is the need to change or improve the credibility perception among Christians in Ghana about televangelism. Televangelists must exhibit accountability and integrity to their worshippers by providing adequate information to encourage viewers to support their ministries.
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Open Access August 30, 2024

Exploring the Benefits of Forgiveness among Adolescents in Junior High Schools in Bimbilla in Ghana: A Comparative Study Based on Age

Abstract This study investigates the benefits of forgiveness among adolescents in Junior High Schools (JHS) in Bimbilla, Ghana, focusing on the influence of age on the effectiveness of forgiveness interventions. The study adopted a mixed-method experimental design, a purposive selection of eight JHSs within the Nanumba North Municipality, from which 60 adolescents were randomly chosen to participate. The [...] Read more.
This study investigates the benefits of forgiveness among adolescents in Junior High Schools (JHS) in Bimbilla, Ghana, focusing on the influence of age on the effectiveness of forgiveness interventions. The study adopted a mixed-method experimental design, a purposive selection of eight JHSs within the Nanumba North Municipality, from which 60 adolescents were randomly chosen to participate. The study employed the Enright Forgiveness Inventory, Depression Mood Scale, and Anger Self-Report items to assess participants' emotional states before and after the intervention. The interventions were structured around the REACH model of forgiveness, which included sessions aimed at helping participants identify sources of hurt, understand the concept of forgiveness, and recognise the emotional costs of holding onto grievances. Qualitative data were analysed into themes using an interpretative lens. A two-way Analysis of Covariance (ANCOVA) was used to analyse the data. The findings revealed that exposure to forgiveness therapies significantly reshaped participants' negative emotions, leading to a marked decrease in feelings of anger and depression. Post-intervention assessments indicated that participants developed a more positive outlook towards their offenders, highlighting the transformative power of forgiveness in fostering emotional well-being. The study's results align with previous research, indicating that forgiveness interventions can effectively reduce negative emotional states and promote psychological resilience. The implications of these findings suggest that integrating forgiveness education into school curricula could be beneficial for enhancing the mental health of adolescents. By fostering an environment that encourages forgiveness, educators and mental health professionals can help mitigate the adverse effects of unresolved emotional conflicts, ultimately contributing to healthier interpersonal relationships and improved overall well-being among young individuals.
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Open Access June 30, 2024

Phytostabilization of Total Monocyclic Aromatic Hydrocarbon in Crude Oil-Contaminated Oxisol using Costus afer Plant

Abstract Costus afer, a known medicinal plant used in the removal of total monocyclic aromatic hydrocarbon (TMAH) in crude oil-contaminated soil add to the list of plant that has the potential to restore the soil quality. This study investigated the potential of Costus afer plant at various ages (7, 14, 21, 28, 35, and 42 days old) to biodegrade crude oil-contaminated soil. The group-balanced block design (GBBD) was used in establishing the experiment. TMAH was quantified by the standard method, according to USEPA method using gas chromatography-mass spectrometry (GC-MS). The contamination of 48kg of sandy loam soil was simulated by mixing 0.5, 1.0, and 1.5L of Bonny-Light crude oil with the soil in three separate vessels to achieve conditions of low (C1), medium(C2), and high(C3) contamination, respectively. An additional vessel with medium-level contaminated soil but no treatment (C4) served as the control. The Costus afer plants were nursed and transplanted at the stated ages to each vessel except the control. Controlled irrigation was applied, and the setups were housed to shield them from rainfall. After 90 days of treatment, results showed that the 7 days old Costus afer plants produced the highest amount of TMAH reduction of 96.5, 39.8, and 32.1%, for C1, C2 and C3, respectively, while the control (C4) was 9.45%. Furthermore, the sequence of TMAH reduction by the plants was 7 days old, 14 days old, 21 days old, 28 days old, 35 days old, and 42 days old. Thus, in addition to its medicinal value, Costus afer [...] Read more.
Costus afer, a known medicinal plant used in the removal of total monocyclic aromatic hydrocarbon (TMAH) in crude oil-contaminated soil add to the list of plant that has the potential to restore the soil quality. This study investigated the potential of Costus afer plant at various ages (7, 14, 21, 28, 35, and 42 days old) to biodegrade crude oil-contaminated soil. The group-balanced block design (GBBD) was used in establishing the experiment. TMAH was quantified by the standard method, according to USEPA method using gas chromatography-mass spectrometry (GC-MS). The contamination of 48kg of sandy loam soil was simulated by mixing 0.5, 1.0, and 1.5L of Bonny-Light crude oil with the soil in three separate vessels to achieve conditions of low (C1), medium(C2), and high(C3) contamination, respectively. An additional vessel with medium-level contaminated soil but no treatment (C4) served as the control. The Costus afer plants were nursed and transplanted at the stated ages to each vessel except the control. Controlled irrigation was applied, and the setups were housed to shield them from rainfall. After 90 days of treatment, results showed that the 7 days old Costus afer plants produced the highest amount of TMAH reduction of 96.5, 39.8, and 32.1%, for C1, C2 and C3, respectively, while the control (C4) was 9.45%. Furthermore, the sequence of TMAH reduction by the plants was 7 days old, 14 days old, 21 days old, 28 days old, 35 days old, and 42 days old. Thus, in addition to its medicinal value, Costus afer plant also has the potential to biodegrade TMAH in crude oil-contaminated sandy loam soil.
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Open Access May 30, 2024

Assessing the Socio-Economic Implications of Free Senior High School (SHS) Policy on Tertiary Institutions in Ghana: A Case Study of the Western Region

Abstract Ghana's Free Senior High School (SHS) policy has been touted as one of the most significant educational reforms in recent years, fueling the nation's achievement of Goal 4 [...] Read more.
Ghana's Free Senior High School (SHS) policy has been touted as one of the most significant educational reforms in recent years, fueling the nation's achievement of Goal 4 of the United Nations Sustainable Development Goals (SDGs). While many studies have been conducted on the policy’s impact on beneficiaries, little is known about its impact on tertiary institutions. The purpose of this study is to evaluate the socioeconomic effects of the Free SHS policy on tertiary institutions in Ghana's Western Region. We also provide suggestions on how to improve the policy's efficacy and lessen any obstacles to its incorporation into higher education. Methodologically, 103 employees of Takoradi Technical University and the University of Mines and Technology were sampled using a purposive sampling technique. According to the report, despite the lack of adequate facilities such as lecture halls, dorms, and residence halls on campus, the Free SHS policy has increased enrollment at the postsecondary level. This has resulted in a high student-to-lecturer ratio, increased utility bills, a high cost of living on campus, and a rise in the opening of businesses on campus. To address some of these socioeconomic impacts, respondents proposed that the government should improve infrastructure in the country's higher institutions, hire more lecturers, boost incentives for lecturers, and foster partnerships with private institutions to support infrastructure development.
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Open Access February 17, 2024

Universal Evaluation of SAP S/4 Hana ERP Cloud System

Abstract Regardless of their traditional ERP Systems, it is essential for every business to acquire a universal advantage in the contemporary international market. When everything is considered, end users in these kinds of businesses have to deal with poorly designed interfaces and unusable technologies. Despite the claims of significant benefits from using S4 Hana cloud ERP software, the possibility of [...] Read more.
Regardless of their traditional ERP Systems, it is essential for every business to acquire a universal advantage in the contemporary international market. When everything is considered, end users in these kinds of businesses have to deal with poorly designed interfaces and unusable technologies. Despite the claims of significant benefits from using S4 Hana cloud ERP software, the possibility of achieving maximum productivity is not fully utilized. One of the causes of this reality is the underfunding of ergonomic measures and the newest technologies. Through the design of S4 Hana cloud ERP software applications, we will demonstrate how important and highly recommended ergonomic research is in order to minimize the financial and human costs that enterprises are currently facing.
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Review Article
Open Access December 23, 2023

Formulation, Characterization and Future Potential of Composite Materials from Natural Resources: the case of Kenaf and Date Palm Fibers

Abstract Thanks to their interesting mechanical properties, recyclability and low production costs, plant fiber-reinforced composites, derived from agricultural residues, are of particular interest to both manufacturers and scientists looking to incorporate new environmentally-friendly and biodegradable materials to replace synthetic fibers, particularly glass fibers. The growing use of these composites in [...] Read more.
Thanks to their interesting mechanical properties, recyclability and low production costs, plant fiber-reinforced composites, derived from agricultural residues, are of particular interest to both manufacturers and scientists looking to incorporate new environmentally-friendly and biodegradable materials to replace synthetic fibers, particularly glass fibers. The growing use of these composites in fields such as the automotive, construction and building industries, and soon in aeronautics, raises concerns about the reliability of the structures with which they are manufactured. This reliability must be guaranteed at the design stage, by a good knowledge of the properties of the material used. In this case, for composites, it is necessary to know the mechanical properties of their constituents, fibers and matrix, etc. In this context, this paper focuses firstly on the economic and industrial recovery of Kenaf (K) and Date Palm (DP) fibers, and secondly on their incorporation as a reinforcing element in cementitious matrix composites, for subsequent use in non-structural applications. This research highlights the development of cementitious matrix bio-composites reinforced with this type of fiber, based on Taguchi's statistical methodology, in order to minimize the cost and number of tests. The bio-composites developed are then mechanically characterized under static loading in compression and 3-point bending after a 30-day drying period.
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Open Access December 06, 2023

Success Factors of Adopting Cloud Enterprise Resource Planning

Abstract The technologies for cloud ERP (Enterprise Resource Planning) have revolutionized the field of information technologies. Any kind of business can benefit from their flexibility, affordability, scalability, adaptation, availability, and customizable data. An advancement of classic ERP, cloud enterprise resource planning (C-ERP) provides the benefits of cloud computing (CC), including resource [...] Read more.
The technologies for cloud ERP (Enterprise Resource Planning) have revolutionized the field of information technologies. Any kind of business can benefit from their flexibility, affordability, scalability, adaptation, availability, and customizable data. An advancement of classic ERP, cloud enterprise resource planning (C-ERP) provides the benefits of cloud computing (CC), including resource elasticity and ease of use. The rise of cloud computing affects on-premise ERP systems in terms of architecture and cost. Cloud-based ERP systems make the claim to be appropriate for digital corporate settings. System quality, security, vendor lock-in, and data accessibility are recognized as the technological issues. Industry 4.0 refers to the re-engineering and revitalization of modern factories through the integration of cloud-based operations, industrial internet connectivity, additive manufacturing, and cybersecurity platforms. One of the four main pillars of Industry 4.0, cloud-based Enterprise Resource Planning (Cloud ERP), is a component of cloud operations that aids in achieving greater standards of sustainable performance.
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Review Article
Open Access October 22, 2023

An Appraisal of Work-Family Conflict on Management Staff of Star-Rated Hotels

Abstract The objective of this research was to investigate work-family conflict among management staff of hotels in the Accra Metropolis of Ghana. The study employs the pragmatism approach and Convergent parallel mixed methods research technique. The population of the study is all-star-rated management staff of star-rated hotels in the Accra metropolis. Stratified, random and convenient sampling techniques [...] Read more.
The objective of this research was to investigate work-family conflict among management staff of hotels in the Accra Metropolis of Ghana. The study employs the pragmatism approach and Convergent parallel mixed methods research technique. The population of the study is all-star-rated management staff of star-rated hotels in the Accra metropolis. Stratified, random and convenient sampling techniques were used to select 182 out of 356 respondents. One hundred (100) were sampled using a formula and a table determination of sample size based on the confidence level needed from a given population as provided by Krejcie and Morgan in 1970 for the study. Ten managers were conveniently interviewed on the issues of work-family conflict. The main instruments for data collection were a questionnaire and a semi-structured interview guide. This study adopted factor analysis and a structural equation model to examine factors that influence work-family conflict. This statistical technique was used in the research to investigate the factorability of the variables of work-related and family-related factors separately and a structural equation model was used to combine both factors to better understand the relationship. Linear regression was used to determine the relationship between work-family conflict. Pearson product-moment Correlation and structural equation model were used to determine the consequences of work-family conflict. It can be concluded that both work-related such as work overload, job type and involvement as well as family-related factors such as life cycle stage, and childcare arrangement predict work-family conflict among managers of hotels in the Accra metropolis. It is also deducted WFC affect managers’ performance on the job, exhaust them emotionally and also influences their intentions to leave the job for another. Managers usually feel fatigued to prepare for work and physically drained after work. They also feel depressed and emotionally drained sometimes. It is recommended that top management of hotels should allocate a budget to build an organisational culture that encourages work-family balance. Frontline managers should be trained to be aware of the benefit of providing support in the work environment that will help staff balance work and family. It is also recommended that hotel jobs be redesigned by the human resource unit to reduce workload and make it more interesting for managers so they may not feel overworked. Overworking of managers will enhance their intentions to quit the job and this will be costly for hotels.
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Article
Open Access October 07, 2023

Emerging Digital Technologies for Pharmaceutical Drug Traceability

Abstract The pharmaceutical supply chain environment has undergone tremendous change in recent decades due to technology, and this shift is intensifying. One of the main concerns of business practitioners is how to cost-effectively integrate, implement, and manage technologies across the supply chain of an organization. Pharmaceutical organizations that produce, ship, and supply goods have trouble tracking [...] Read more.
The pharmaceutical supply chain environment has undergone tremendous change in recent decades due to technology, and this shift is intensifying. One of the main concerns of business practitioners is how to cost-effectively integrate, implement, and manage technologies across the supply chain of an organization. Pharmaceutical organizations that produce, ship, and supply goods have trouble tracking their goods, which makes it easier for counterfeiters to get fake medications into the system. The creation and implementation of a stringent technological system might be a significant step in the arduous battle against the prevalence of fake medications and other healthcare items. In supply chain management, digital technologies have a number of potential advantages. The usage of the Internet of Things in supply chains can make every component visible and create a visible supply chain, making it possible to identify the position and specifications of all the components and materials in the supply chain at any given time.
Review Article
Open Access July 29, 2023

Critical Success Factors of Adopting an Enterprise System for Pharmaceutical Drug Traceability

Abstract For conducting advanced analytics initiatives to acquire in-depth data into usage habits, regional access, sales, and promotional success, etc., unique identification of packaged pharmaceuticals will be a fantastic enabler. The main objective of this study is to prevent and reduce the production of erroneous and counterfeit drugs using the enterprise system, which has become a serious threat [...] Read more.
For conducting advanced analytics initiatives to acquire in-depth data into usage habits, regional access, sales, and promotional success, etc., unique identification of packaged pharmaceuticals will be a fantastic enabler. The main objective of this study is to prevent and reduce the production of erroneous and counterfeit drugs using the enterprise system, which has become a serious threat because it damages the reputation of legitimate drug manufacturers by trying to produce and market placebo medications that are identical to the real thing. Due to federal government procedures and priorities that frequently change over time, the majority of implementation takes time. To achieve compliance with numerous federal regulatory authorities, including drug traceability for patient safety, the pharmaceutical industry must implement a systematic procedure in an ERP environment. The goals would be to guarantee medical drug traceability and provide real-time warnings to supply chain stakeholders and regulatory bodies to maximize the benefit of integrating a drug traceability system into an ERP environment. Additionally, manufacturers are compelled to maintain product costs on the higher side due to a heavy burden of unchecked manufacturing cost spikes. As a result, innovative marketing schemes must be introduced in order to increase the reach to consumers by putting into practice successful strategies.
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Review Article
Open Access February 02, 2023

Quantifying 64 drugs, illicit substances, and D- and L- isomers in human oral fluid with liquid-liquid extraction

Abstract Although human oral fluid has become more routine for quantitative drug detection in pain management, detecting a large scope of medications and substances is costly and technically challenging for laboratories. This paper presents a quantitative assay for 64 pain medications, illicit substances, and drug metabolites in human oral fluid. The novelty of this assay is that it was developed on an [...] Read more.
Although human oral fluid has become more routine for quantitative drug detection in pain management, detecting a large scope of medications and substances is costly and technically challenging for laboratories. This paper presents a quantitative assay for 64 pain medications, illicit substances, and drug metabolites in human oral fluid. The novelty of this assay is that it was developed on an older model AB SCIEX 4000 instrument and renders obscure the need for more technical and expensive laboratory equipment. This method includes addition of internal standard and a 2-step liquid-liquid extraction and dry-down step to concentrate and clean the samples. The samples were suspended in 50% MeOH in water and separation and detection was accomplished using triple quadrupole mass spectrometry (LC-MS/MS). Separation was achieved using reverse-phase liquid chromatography with detection by LC-MS/MS. A second injection was done in negative mode to determine THC-COOH concentration as an indicator of THC. An aliquot of the (already) extracted samples was analyzed for D- and L- isomers of amphetamine and methamphetamine using a chiral column. The standard curve spanned from 5 to 2000 ng/mL for most of the analytes (1 to 2000 ng/mL for fentanyl and THC-COOH) and up to 1000 ng/mL for 13 analytes. Pregabalin and gabapentin ranged from 25 to 2000 ng/mL. The result is a low-cost method for the sensitive detection of a wide-ranging oral fluid menu for pain management. This assay has a high sensitivity, and good precision and accuracy for all analytes with an older model mass spectrometer.
Article
Open Access November 25, 2022

Knowledge for a Better Conservation: Syntaxonomic Review of Caribbean Pine Forests (Cuba, Hispaniola)

Abstract A phytosociological review is carried out of the pine forest formations on the islands of Cuba and Hispaniola (Caribbean), due to the diversity of soils and environments. We collected 10 plant associations belonging to the class Byrsonimo-Pinetea caribaea growing on siliceous, calcareous and sandy substrates and 21 associations on special, serpentine and ophite substrates and on ultramafic rocks belonging to the class Caseario crassinervis-Pinetea cubensis, exclusive to Cuba; while the association of pine forests on serpentines in Hispaniola is included in the class Phyllantho orbicularis-Neobracetea valenzuelanae with a Caribbean distribution. The comparative phytosociological and statistical study reveals phytosociological anomalies in the inclusion of various syntaxa, and in the description of other syntaxa according to the International Code of Phytosociological Nomenclature (ICPN). We therefore propose a change in status for several of the subassociations described: subass. ilicetosum repandae: syn. var. con Ilex repanda; subass. schmidtottietosum shaferi: syn. var. with Schmidtottia shaferi; subass. acrosynanthetosum trachyphylli: syn. var. with Acrosynanthus trachyphyllus; subass. psychotrietosum grandis: var. con Psychotria grandis; subass. notodonetosum roigii: syn. var. with Notodon roigii. We also propose a nomen novum: jaquinietosum oxhyphyllae Reyes & Acosta 2012 ex Cano et al. hoc loco [...] Read more.
A phytosociological review is carried out of the pine forest formations on the islands of Cuba and Hispaniola (Caribbean), due to the diversity of soils and environments. We collected 10 plant associations belonging to the class Byrsonimo-Pinetea caribaea growing on siliceous, calcareous and sandy substrates and 21 associations on special, serpentine and ophite substrates and on ultramafic rocks belonging to the class Caseario crassinervis-Pinetea cubensis, exclusive to Cuba; while the association of pine forests on serpentines in Hispaniola is included in the class Phyllantho orbicularis-Neobracetea valenzuelanae with a Caribbean distribution. The comparative phytosociological and statistical study reveals phytosociological anomalies in the inclusion of various syntaxa, and in the description of other syntaxa according to the International Code of Phytosociological Nomenclature (ICPN). We therefore propose a change in status for several of the subassociations described: subass. ilicetosum repandae: syn. var. con Ilex repanda; subass. schmidtottietosum shaferi: syn. var. with Schmidtottia shaferi; subass. acrosynanthetosum trachyphylli: syn. var. with Acrosynanthus trachyphyllus; subass. psychotrietosum grandis: var. con Psychotria grandis; subass. notodonetosum roigii: syn. var. with Notodon roigii. We also propose a nomen novum: jaquinietosum oxhyphyllae Reyes & Acosta 2012 ex Cano et al. hoc loco.
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Review Article
Open Access October 02, 2022

Thoughts on Pneumococcal Vaccination for the Adult Individuals with Autoimmune Diseases

Abstract Streptococcus pneumoniae [...] Read more.
Streptococcus pneumoniae is an important pathogenic bacteria causing pneumonia and invasive pneumococcal diseases, and the vaccination for pneumococcal vaccination is recommended in patients with RA and other autoimmune disorders. Compared with the immunocompetent individuals, frequency and the mortality rate were higher in the RA patients. The effect of pneumococcal vaccination may not be weakened in people using corticosteroid and biological disease-modifying anti-rheumatic drug (DMARD) currently being used, but mild to relatively inhibition of immunogenicity was suggested in patients using either methotrexate or rituximab. Administration of 13-valent pneumococcal conjugate vaccine (PCV13), rather than 23-valent Pneumococcal polysaccharide vaccine (PPSV23) may be desirable in preventing pneumonia in people with autoimmune disease and sequential administration of PCV13 in people aged ≤64 years and PPSV23 from age ≥65 years may be useful for preventing pneumonia in people with autoimmune disease according to the insurance system. In addition, PCV15 and PCV 20 will be available soon and expected for more clinical efficiency rather than current PCV13 and PPSV23.
Mini Review
Open Access September 01, 2022

Dynamics of Pharmaceutical Drugs Serialization

Abstract The healthcare access is fundamental rights for every human being. It is Governments responsibility to provide good healthcare services and infrastructure to its citizen. Since last few decades, Government and healthcare industries are struggling to minimize the adverse events impacting people health due to fake medicine. The world health organization also predicted that 4 out of 10 medicines in [...] Read more.
The healthcare access is fundamental rights for every human being. It is Governments responsibility to provide good healthcare services and infrastructure to its citizen. Since last few decades, Government and healthcare industries are struggling to minimize the adverse events impacting people health due to fake medicine. The world health organization also predicted that 4 out of 10 medicines in developing and poor countries are either fake or potentially adulterated. Counterfeit drugs cost billions of dollars deficit to world economy and reduce research and development (R&D) funds allocation from organizations. Stopping counterfeit medicine into supply chain is main challenge for Government and regulatory authorities. The Government and regulatory authorities are now making stringent guidelines to prohibit criminals and counterfeiters to supply fake medicine in markets. Healthcare industry need stringent regulations and secure technologies provide sage and authentic drugs to patients. The FDA has published the 10 years roadmap to implement the drug traceability in United States. The Healthcare Distribution Alliance (HDA) has also mandated to print several barcodes and human readable data in product packaging hierarchy. The FDA is participating in pilot project with leading pharmaceutical drug manufacturer and wholesales to use blockchain technology in interoperable digital network for securing digital traceability data transfer between authorized trading partners.
Review Article
Open Access August 08, 2022

Motives of Tourists': Socio-Economic and Challenges of Kwahu Easter Festival (KEF) in Ghana

Abstract The purpose of the study was to examine the Motives of Tourists; Socio-Economic and Challenges of tourism in Kwahu in the Eastern Region of Ghana The study adopted a descriptive survey research design. The population of the study comprised six (6) communities (Mpraeso, Atibie, Obomeng, Obo Oworobong, and Nketepa in Kwahu South District Assembly (KSDA) in the Eastern Region of Ghana. Purposive and [...] Read more.
The purpose of the study was to examine the Motives of Tourists; Socio-Economic and Challenges of tourism in Kwahu in the Eastern Region of Ghana The study adopted a descriptive survey research design. The population of the study comprised six (6) communities (Mpraeso, Atibie, Obomeng, Obo Oworobong, and Nketepa in Kwahu South District Assembly (KSDA) in the Eastern Region of Ghana. Purposive and convenient sampling techniques were employed to select two hundred (200) respondents for the study. The main instrument used for data collection was questionnaires. The study employed the statistical package for social sciences (SPSS) to code and process the collected data. Descriptive and relational statistical techniques involving frequencies, percentages, summations, diagrams, and tables were employed in analysing the data. The Chi-square test analysis was used to explore the relationships and differences in perceptions. The study indicated that every tourist, whether local (Ghanaian) or foreign, had at least one of the following motives in mind for participating in the festival; To socialize; For relaxation; For education to participate and witness the paragliding festivals; To take photographs of festival scenes; Other motives like to sell items, especially souvenirs. The study also revealed that the KEF has had some positive socio-economic impact or implications on the area. These among others include: job creation, income generation for locals of the area, infrastructural development, and projection of the image of the area as the festival has become one of the biggest gatherings of revellers in the country, drawing people from all walks of life, nationally and internationally as a result of the introduction of paragliding since 2005, socialization enhancement, medium for cultural exchange and education, and finally serves as a medium for portraying the cultural identity of the people of Kwahu. The study also indicated that the major challenges encountered by tourists during the event were listed in order of degree of intensity: High cost of living, poor road network in the area, intermitted electricity and water supply, poor sanitary conditions in the area, poor health facilities, and unwelcoming attitude of some local residents of the festival area. It is recommended that, residents must be educated about the potential benefits of tourism as an industry helping to achieve sustainable community development. It is also recommended that Ghana tourism authority and Kwahu District Assembly should collaborate to improve on social amenities in the municipality to attract more foreign and local tourists during the festivity.
Article
Open Access June 27, 2022

Development of Cellulose Nanofibre (CNF) Coating on (1) Metal Surface for Free Standing CNF Film and (2) Paper Substrates for CNF Barrier Laminates

Abstract Paper is widely used in packaging applications and is biodegradable and therefore perfectly safe as green packaging wrap for the environment. The hydrophilic nature of cellulose fibrils limits the water vapour and oxygen barrier properties of paper. To mitigate these limitations, paper is often associated with other materials, such as plastics, wax and aluminum, for achieving their good barrier [...] Read more.
Paper is widely used in packaging applications and is biodegradable and therefore perfectly safe as green packaging wrap for the environment. The hydrophilic nature of cellulose fibrils limits the water vapour and oxygen barrier properties of paper. To mitigate these limitations, paper is often associated with other materials, such as plastics, wax and aluminum, for achieving their good barrier properties. However, these materials suffer from serious environmental issues, as difficult and inefficient to recycle. Recently, cellulose nanofibre (CNF) based materials has been considered as an alternative to produce eco-friendly barrier materials. Existing techniques to prepare cellulose nanofibre films/sheets/composites/ laminates on the paper substrates are commercially not feasible and expensive. Therefore, other cost effective and readily implementable methodologies are required to achieve cellulose nanofibre barrier layers. In the present report, a novel approach is developed using spray coating technique to produce CNF materials with excellent barrier properties. Among many coating techniques, the spray coating has many advantages such as the production of even coating surface on the base sheet and contactless coating with the substrate. A laboratory scale spray coating of cellulose nanofibre suspension on a paper substrate was developed. When the cellulose nanofibre suspension concentration was varied from 0.5 to 1.5 wt. %, coat weight is increased from 2.9±0.7 to 29.3±6.9 g/m2. As a result, the air permeability of composite was decreased 0.78±0.17 to <0.0030 µm/Pa.s. Scanning electron microscopy studies of spray coated CNF laminates on the paper confirms that the surface pores in the paper substrates are filled with sprayed cellulose nanofibre and forms a continuous film on the surface of the substrate. These are the probable reasons for the reduction of air permeability of composites. A rapid preparation technique to prepare free standing cellulose nanofibre films/sheets was also developed using a bench scale spray coating system. Cellulose nanofibre suspension with concentration ranging from 1 to 2 wt% was sprayed onto a stainless steel plate, which is moving on a conveyor at a velocity of 0.32 cm/sec and then air dried. The basis weight of produced cellulose nanofibre films is varied from 52.8±7.4 to 193.1±3.4 g/m2. Processing time taken to prepare films was approximately 1.0 min, which is much less than processing times reported in the previous literature. Thus, the significant reduction in preparation time for producing the cellulose nanofibre sheet recommends that this spray coating technique can be utilized for the development of a scalable process for the fabrication of various cellulose based nanocomposite. Therefore, the laboratory scale spray coating confirms that the spraying could provide a platform for development of films/sheets/nanocomposite and also a CNF barrier layer on the base sheet. The future work is the development of a continuous spray coating of cellulose nanofibre on the base sheet and evaluation of mechanical and barrier properties spray coated barrier layers on the base sheet.
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Project Report
Open Access June 13, 2022

Wireless Technology is Easy to Use

Abstract Wireless networking is the connection of computers, digital communication devices, network equipment, and various other devices via radio waves. It is applied in places where the wired infrastructure cannot be installed or the price of introducing such a structure is too high. In addition, it has some features that are a great advantage over wired networking, such as customer mobility, easy [...] Read more.
Wireless networking is the connection of computers, digital communication devices, network equipment, and various other devices via radio waves. It is applied in places where the wired infrastructure cannot be installed or the price of introducing such a structure is too high. In addition, it has some features that are a great advantage over wired networking, such as customer mobility, easy expandability, and fast and low-cost temporary networking. Wireless technology allows us mobility and ease of use, but most users do not think about security. Users are insufficiently informed about the dangers of the Internet. Many of them do not pay attention to that and access important data such as bank accounts, e-mail, and any other contents that must be preserved and hidden. Today, there are more and more malicious actions, where hackers use various methods and technologies to attack users' accounts, bypassing all protections. Today, the issue of security is one of the priorities for every Internet user. Due to its characteristics, wireless communication is exposed to attacks due to the way they are sent, and there is a possibility of intercepting information.
Review Article
Open Access May 09, 2022

Study for Some Body Weight and Egg Traits in Domyati and Khaki-Campbell Ducks

Abstract The duck industry makes an important contribution to the availability of animal protein sources in Egypt, little known about the genetic parameters, particularly the heritability and genetic correlations of body weight and egg production in ducks. Body weight is the most essential feature for genetic improvement due to its ease of selection, high heredity, and large impact on meat production [...] Read more.
The duck industry makes an important contribution to the availability of animal protein sources in Egypt, little known about the genetic parameters, particularly the heritability and genetic correlations of body weight and egg production in ducks. Body weight is the most essential feature for genetic improvement due to its ease of selection, high heredity, and large impact on meat production costs. The target of this study was to evaluate and explain genetic parameters such as the heritability, the genetic and phenotypic correlations, and sire breeding value in Domyati (local) and Khaki-Campbell (foreign) ducks in order to improve body weight and egg traits. A total of 160 (80 Domyati and 80 Khaki-Campbell ducks utilized to measure body weight at 16 and 20 weeks g), as well as 7000 eggs (2500 Domyati and 4500 Khaki-Campbell) to measure egg traits (the egg number, egg weight, and egg mass are all measured throughout the first 90 days of laying). In Domyati and Khaki-Campbell ducks, the heritability estimated for body weight was moderate to high, ranged from 0.35 to 0.40, and 0.21 to 0.30 for egg production. The genetic correlations among body weight and egg traits were all positive and had high values, also among BW16 and BW20 were stronger (0.90); (0.99). So the genetic improvement in BW16 could be followed by an increase in BW20 weeks. It concluded that, the relatively high value of genetic heritability for body weights and egg traits in Domyati and Khaki-Campbell ducks, indicates that it is possible to genetically increase body weight and egg traits through selection and subsequently inbreeding to divide the herd into groups that are selected among themselves to keep their sons.
Article
Open Access April 18, 2022

Preliminary Survey Analysis on Food Choices among Randomly Selected Social Media Users amidst COVID-19 Pandemic in Nigeria

Abstract A survey on food choices with a randomized sample population of individuals using various social media in Nigeria was conducted during the COVID1-19 pandemic. The data generated was subjected to basic standard statistical analysis. The parameters indicated that 94% of the population is young adults, 58.9 % percent are city dwellers, 63.6% are students, 23.4 % are into business, 86.9% are [...] Read more.
A survey on food choices with a randomized sample population of individuals using various social media in Nigeria was conducted during the COVID1-19 pandemic. The data generated was subjected to basic standard statistical analysis. The parameters indicated that 94% of the population is young adults, 58.9 % percent are city dwellers, 63.6% are students, 23.4 % are into business, 86.9% are graduates; 73.8% consume various diets, 23.4% are vegetarians and only 2.8% fed only on proteins, 30.8% of them go on two meals per day. The most choices on influence on food purchases decision are hunger (26.2%), mood (26.2%), past experience (45.8%), quality of the food products (66.7%), cost of the food products (50.5%) and government approval (28%). Also,other most preferred choices are for self-prepared food (40.21%), enhanced local diets (36 %), and a blend of foreign and local diets purchases (24%). Other highest choices include: easy preparation (37.4%), shelf life (29%); cute packaging (23.4%), swelling property preference (20.6%), minimal cooking time and energy preference (37.4%). The weighted sum, index and rank on factors influencing food choices showed that the influence of quality of food product ranked highest, followed by influence on cost. Also preference for enhanced local healthy diets to foreign ranked highest, minimal cooking time and energy costs ranked highest. These nutritional adaptations have implications to individuals, food scientists, manufacturers in the food industry, food regulatory agencies, government and other decision bodies.
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Article
Open Access September 23, 2021

New Interpretations from Sustainable Economy

Abstract The present work abounds in lathe comments on the ecological, economic policy. The first refers to the layers of thermodynamics and the economic process, but does not describe the importation of analyzing the dynamics of the economic process in terms of the transfer of matter and energy, and it is a natural system. Secondly, it is a revision of the main plant-like portraits by Marx and Engels with [...] Read more.
The present work abounds in lathe comments on the ecological, economic policy. The first refers to the layers of thermodynamics and the economic process, but does not describe the importation of analyzing the dynamics of the economic process in terms of the transfer of matter and energy, and it is a natural system. Secondly, it is a revision of the main plant-like portraits by Marx and Engels with the historical background that plays naturalness in the process of social reproduction. The third radical commentary on reflecting the theory of value, considering that the system can count with a theory of value based on quantities of energy, is limited. The reason is sensible: as long as the capital is valued at no cost from the exploration of the work, it is natural without embargo as a limitation. And as in the last comment, we only see the political economy from a green perspective. Green in the sense that to perform economic analysis, even historical ones, it is necessary to include the natural resource variable and keep the manager accountable with critical info.
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Article
Open Access August 14, 2021

Genes of Gall 200C and Nematode 200C May Develop Biomedical Vaccines Against Plants and COVID-19 Diseases: Advanced Medical Science Technology Agriculture Health Issues

Abstract The outbreaks and quick spread of severe-acute-respiratory-syndrome-coronavirus 2 (SARS-CoV-2), causing the coronavirus disease 2019 (COVID-19), have badly affected the whole world due to continuous emergence-and-transmission of the latest-new viral-genomes forming new-variants revealing patterns of the SARS-CoV-2 outbreak-and-global-pandemic with badly affecting advanced-medical-science-technology-communication-agriculture-agronomy-plant-breeding-horticulture, health-environment-socio-economy, and different-issues. India's emphasis on okra, the ‘Nature's-Gift to Human-Disease-Free-Healthy-Life’ and the most ‘Economically-Important-Number-One-Consumption Vegetable-Crops’ is destroyed by various-diseases causing pathogens like the root-knot (RK)-diseases caused by the nematodes, Meloidogyne incognita [...] Read more.
The outbreaks and quick spread of severe-acute-respiratory-syndrome-coronavirus 2 (SARS-CoV-2), causing the coronavirus disease 2019 (COVID-19), have badly affected the whole world due to continuous emergence-and-transmission of the latest-new viral-genomes forming new-variants revealing patterns of the SARS-CoV-2 outbreak-and-global-pandemic with badly affecting advanced-medical-science-technology-communication-agriculture-agronomy-plant-breeding-horticulture, health-environment-socio-economy, and different-issues. India's emphasis on okra, the ‘Nature's-Gift to Human-Disease-Free-Healthy-Life’ and the most ‘Economically-Important-Number-One-Consumption Vegetable-Crops’ is destroyed by various-diseases causing pathogens like the root-knot (RK)-diseases caused by the nematodes, Meloidogyne incognita (Kofoid & White) Chitwood, and easily checked by many chemical-pesticides. But it causes different carcinogenic effects on the environment and our life. So it is an urgent need to develop potential biomedicines. The pretreatments with ultra-high-diluted-biomedicines (UHDBMs) Gall 200C and Nematode 200C, prepared from okra-root-galls (ORG) and nematode-females (NF) respectively, applied by foliar spray@ 20 ml/plant, are highly effective against the root-knot-disease of okra, Abelmoschus esculentus (L.) Moench Cv. Ankur-40, with the increasing growth of plants and fruits-production. The UHDBMs-Gall 200C is more effective than the Nematode 200C. Both the pretreatments-UHDBMs are responsible for induce-systemic-acquired-defense-response of the pretreated-plants through the expression of pathogenesis-related (PR)-proteins-genes (22-14 numbers), which are more or less similar-molecular-range (295kD-11kD) of many coronavirus, which will be responsible for preventing-RK and COVID-19 like virus-diseases by inducing-defense-resistance or increasing innate-immunity respectively, and advanced in medical-science, technology, communication, agriculture, agronomy, plant breeding, horticulture, health, environment, socio-economy, and different application-issues with pollution-free globe, developing new-preventive typical-biomedical vaccines or treatments methods or drug development and research against the ‘21st-Century Global Pandemic COVID-19 like Any Viral Diseases’ which lead to optimal contributions to the field of policymaking drug and vaccine development emphasizing new or important aspects of the study, and synthetic production of UHDBMs will be more practical implications, and social implications in the future research. And the farmers and the world would be benefitted most; by collecting and uprooting gall-roots after harvesting for cost-effective bio-controlling plant-diseases, and profit from shelling-and-buying of whole plants, fruits, and gall-roots also, and helps for the benefit of global health by developing the most cost-effective, personalized, non-toxic, easily-preparable, easily-maintainable, easily-available and suppliable, vaccines or treatments methods from their own product.
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Article
Open Access August 14, 2021

An Economic Evaluation of the use of Wind Farms in Iran, Taking into Account the Effect of Energy Price Liberalization Policy

Abstract In this study, the effect of energy cost liberalization policies on the cost-effectiveness of wind farms compared to gas power plants has been investigated. To calculate the cost of electricity generation from various sources, including wind energy and fossil fuels, the “levelized cost” method has been used as the most acceptable economic method to compare different types of electricity generation [...] Read more.
In this study, the effect of energy cost liberalization policies on the cost-effectiveness of wind farms compared to gas power plants has been investigated. To calculate the cost of electricity generation from various sources, including wind energy and fossil fuels, the “levelized cost” method has been used as the most acceptable economic method to compare different types of electricity generation technologies. In addition, calculations related to the cost of electricity, different fuel prices, different technologies of wind farms, and different prices of different types of fuel are considered. Based on the results of this research, it was found that by targeting fuel prices in the country, wind farms are quite cost-effective, and considering the cost of the opportunity to use diesel in the country, the construction of these power plants can provide the possibility of exporting this fuel. This cost also increases with the production of valuable equipment in the country. The important point is that the macro policy should localize the wind turbine industry with priority to its valuable parts and components due to fuel price changes. This policy will continue to make this type of power plant cost-effective in the country and the employment of specialists in the country.
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Article
Open Access August 09, 2021

Investigation of the Optimal Model for the Development of Renewable Energy in Iran using a Robust Optimization Approach

Abstract Due to its geographical location, Iran has numerous capacities in renewable energy, and this issue has made the need to develop renewable energy on the authorities’ agenda. This underscores the need to provide an optimal model for developing renewable energy. Therefore, in this study, the main purpose was to provide an optimal renewable energy model. In line with this goal, by choosing the cost [...] Read more.
Due to its geographical location, Iran has numerous capacities in renewable energy, and this issue has made the need to develop renewable energy on the authorities’ agenda. This underscores the need to provide an optimal model for developing renewable energy. Therefore, in this study, the main purpose was to provide an optimal renewable energy model. In line with this goal, by choosing the cost function as the objective function and considering the potential constraints of renewable energy (resource constraints), the amount of electricity consumption in each of the 16 electricity regions (demand constraint) and the limitation of renewable energy production coefficient (Technical constraints), the optimal model of renewable energy use was designed and solved using a solid programming model in LINGO software. The optimal model results show 15.19% small hydropower, 24.30% wind energy, 5.52% biomass energy, 6.13% is geothermal energy, 4.79% is tidal energy, and 44.07% solar energy. The optimum portfolio of renewable energy is estimated in this paper using the robust optimization approach. The results showed which renewable technology has the greater potential to take more share of the energy portfolio. The results of this investigation help policymakers to choose the most suitable renewable technologies to support.
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Article
Open Access August 29, 2022

From Deterministic to Data-Driven: AI and Machine Learning for Next-Generation Production Line Optimization

Abstract The advancement of modern manufacturing is synonymous with the growth of automation. Automation replaces human operators, improves productivity and quality, and reduces costs. However, the initial financial cost and knowledge requirements can be barriers to embracing automation. Manufacturers are now seeking smart manufacturing, known as the fourth industrial revolution. Smart manufacturing goes [...] Read more.
The advancement of modern manufacturing is synonymous with the growth of automation. Automation replaces human operators, improves productivity and quality, and reduces costs. However, the initial financial cost and knowledge requirements can be barriers to embracing automation. Manufacturers are now seeking smart manufacturing, known as the fourth industrial revolution. Smart manufacturing goes beyond automation and utilizes IoT, AI, and big data for optimized production. In a smart factory, production can be linked and controlled innovatively, leading to increased performance, agility, and reduced costs.
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Review Article
Open Access December 27, 2021

Leveraging AI in Urban Traffic Management: Addressing Congestion and Traffic Flow with Intelligent Systems

Abstract Traffic congestion across the globe is a multimodal problem, intertwining vehicular, pedestrian, and bicycle traffic. The relationship between the multimodal traffic flow is a key factor in understanding urban traffic dynamics. The impact of excessive congestion extends to the excessive cost spent on traffic maintenance, as well as the inherent transportation inefficiency and delayed travel times. [...] Read more.
Traffic congestion across the globe is a multimodal problem, intertwining vehicular, pedestrian, and bicycle traffic. The relationship between the multimodal traffic flow is a key factor in understanding urban traffic dynamics. The impact of excessive congestion extends to the excessive cost spent on traffic maintenance, as well as the inherent transportation inefficiency and delayed travel times. From an urban transportation standpoint, an immediate consideration on one hand is monitoring traffic conditions and demand cycles, while on the other hand inducing flow modifications that benefit the traffic network and mitigate congestion. Embedded and centralized control systems that characterize modern traffic management systems extract traffic conditions specific to their regions but lack communication between networks. Moreover, innovative methods are required to provide more accurate up-to-date traffic forecasts that characterize real-world traffic dynamics and facilitate optimal traffic management decisions. In this chapter, we briefly outline the main difficulties and complexities in modeling, managing, and forecasting traffic dynamics. We also compare various conventional and modern Intelligent Transportation Strategies in terms of accuracy and applicability, their performance, and potential opportunities for optimization of multimodal traffic flow and congestion reduction. This chapter introduces various proposed data-driven models and tools employed for traffic flow prediction and management, investigating specific strategies' strengths, weaknesses, and benefits in addressing various real-world traffic management problems. We describe that the design phase of dependable Intelligent Transportation Systems bears unique requirements in terms of the robustness, safety, and response times of their components and the encompassing system model. Furthermore, this architectural blueprint shares similarities with distributed coordinate searching and collective adaptive systems. Town size-independent models induce systemic performance improvements through reconfigurable embedded functionality. These AI techniques feature elaborate anytime planner-engagers ensuring near-optimal performances in an unbiased behavior when the model complexity is varied. Sustainable models minimize congestion during peaks, flooding, and emergency occurrences as they adhere to area-specific regulations. Security-aware and fail-safe traffic management systems relinquish reasonable assurances of persistent operation under various environmental settings, to acknowledge metropolis and complex traffic junctions. The chapter concludes by outlining challenges, research questions, and future research paths in the field of transportation management.
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Open Access December 27, 2021

Financial Implications of Predictive Analytics in Vehicle Manufacturing: Insights for Budget Optimization and Resource Allocation

Abstract Factory owners and vehicle manufacturers increasingly opt for predictive analytics to inform their decisions. While predictive analytics have been proven to provide insights into the initiation of maintenance measures before a machine actually fails, the right models and features could have a significant impact on the budget spent and resources allocated. This means that financially oriented [...] Read more.
Factory owners and vehicle manufacturers increasingly opt for predictive analytics to inform their decisions. While predictive analytics have been proven to provide insights into the initiation of maintenance measures before a machine actually fails, the right models and features could have a significant impact on the budget spent and resources allocated. This means that financially oriented questions need to at least partially guide the decisions in the planning phase of data science projects. Data-driven approaches will play an increasingly important role, but only a few of the firms that were confident performed logistic regression models for predictive maintenance. Also, from the available knowledge, data-driven classification models connecting vehicle component failures and the occurrence of delays at the assembly line have not been published. This paper utilizes a real-world data-driven approach using classification models in predictive analytics by vehicle manufacturers and thereby links the financial implications of such data science projects to their results. We expand the existing literature on predictive maintenance and possess a unique dataset of newly launched series of vehicles, presented as-is. Our research context is of interest to researchers and practitioners in the automotive industry that manage and plan the final vehicle assembly with just-in-time principles, factoring the consequences of component failures on the assembly process. Key findings of this paper highlight that while minor tweaking of the models is possible, their potential input in decision-making processes for budget optimization is limited.
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Open Access November 16, 2023

Innovations in Agricultural Machinery: Assessing the Impact of Advanced Technologies on Farm Efficiency

Abstract Progress in the development and adoption of technological innovations is instrumental in enhancing the efficiency of production systems across the globe. Through the introduction of cost-efficient and high-performing technologies, countries can both reduce the resource use intensity of their economies and boost the global supply of essential products. The focus of this study is to analyze the [...] Read more.
Progress in the development and adoption of technological innovations is instrumental in enhancing the efficiency of production systems across the globe. Through the introduction of cost-efficient and high-performing technologies, countries can both reduce the resource use intensity of their economies and boost the global supply of essential products. The focus of this study is to analyze the application of advanced machinery and mechanisms within the agricultural sector, a primary industry that acts as a major contributor to the gross domestic product (GDP) of many nations. Specifically, this paper provides an in-depth review of the latest impact assessments based on analytical and modeling tools conducted on agricultural machinery and production technologies. Our findings highlight the positive role played by scientific progress and innovation in driving the competitiveness, growth and improved sustainability of the agricultural sector. Over the years, advanced technologies have accelerated the development and modernization of machinery, equipment, and processes in farming. Typically, modern machinery and equipment have enabled large-scale production on farms, enhancing the cost-efficient use of both land and labor, as well as the capacity and timeliness in performing essential agricultural operations. The rapid diffusion of technical advancements has further contributed to resource savings, productivity growth, and the overall transformation of agricultural value chains. Accordingly, the implementation of appropriate enabling conditions is of vital importance in encouraging the widespread integration of technologies in agriculture, not only boosting productivity along the agri-food chain but also yielding widespread social, economic, and environmental benefits.
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Open Access November 05, 2022

Application of Neural Networks in Optimizing Health Outcomes in Medicare Advantage and Supplement Plans

Abstract The growing complexity and variability in healthcare delivery and costs within Medicare Advantage (MA) and Medicare Supplement (Medigap) plans present significant challenges for improving health outcomes and managing expenditures. Neural networks, a subset of artificial intelligence (AI), have shown considerable promise in optimizing healthcare processes, particularly in predictive modeling, [...] Read more.
The growing complexity and variability in healthcare delivery and costs within Medicare Advantage (MA) and Medicare Supplement (Medigap) plans present significant challenges for improving health outcomes and managing expenditures. Neural networks, a subset of artificial intelligence (AI), have shown considerable promise in optimizing healthcare processes, particularly in predictive modeling, personalized treatment recommendations, and risk stratification. This paper explores the application of neural networks in enhancing health outcomes within the context of Medicare Advantage and Supplement plans. We review how deep learning models can be leveraged to predict patient risk, optimize resource allocation, and identify at-risk populations for preventive interventions. Additionally, we discuss the potential for neural networks to improve claims processing, reduce fraud, and streamline administrative burdens. By integrating various data sources, including medical records, claims data, and demographic information, neural networks enable more accurate and efficient decision-making processes. Ultimately, this approach can lead to better patient care, reduced healthcare costs, and improved satisfaction for beneficiaries of these programs. The paper concludes by highlighting the current limitations, ethical considerations, and future directions for AI adoption in the Medicare Advantage and Supplement sectors.
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Open Access December 27, 2023

Leveraging Artificial Intelligence to Enhance Supply Chain Resilience: A Study of Predictive Analytics and Risk Mitigation Strategies

Abstract The management of supply chains is increasingly complex. This study provides a comparative analysis of the cost-benefit analysis for managing various risks. It identifies the financial implications of leveraging artificial intelligence in supply chains to better address risk. Empirical results show a business case for managing some sources of risk more proactively facilitated through predictive [...] Read more.
The management of supply chains is increasingly complex. This study provides a comparative analysis of the cost-benefit analysis for managing various risks. It identifies the financial implications of leveraging artificial intelligence in supply chains to better address risk. Empirical results show a business case for managing some sources of risk more proactively facilitated through predictive modeling techniques offered by AI. Across investigation streams, the use of AI results in an average total cost saving ranging from 41,254 to 4,099,617. Findings from our research can be used to inform managers and theorists about the implications of integrating AI technologies to manage risks in the supply chain. Our work also highlights areas for future research. Given the growing interest in studying sub-second forecasting, our research could be a point of departure for future investigations aimed at considering the impact of forecasting horizons such as an intra-day basis. We formulate a conceptual framework that considers how and to what extent performance evaluation metrics vary according to differences in the fidelity of predictive models and factor importance for identifying risks. We also utilize a mixed-method approach to demonstrate the applicability of our ideas in practice. Our results illustrate the financial implications of integrating AI predictive tools with business processes. Results suggest that real-world companies can circumvent inefficiencies associated with trying to manage many classes of risk via the use of AI-enhanced predictive analytics. As managers need to justify investment to top management, our work supports decision-making by providing a means of conducting a trade-off analysis at the tactical level.
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Open Access December 27, 2023

Ensuring High Availability and Resiliency in Global Deployments: Leveraging Multi-Region Architectures, Auto Scaling, and Traffic Management in Azure and AWS

Abstract Modern organizations leverage highly distributed, global deployments to provide high availability and resiliency for cloud-first applications. By hosting these applications across multiple geographic locations and relying on highly available services, organizations can prevent disruption to their business and reduce complexity by employing the scale of infrastructure offered by major cloud [...] Read more.
Modern organizations leverage highly distributed, global deployments to provide high availability and resiliency for cloud-first applications. By hosting these applications across multiple geographic locations and relying on highly available services, organizations can prevent disruption to their business and reduce complexity by employing the scale of infrastructure offered by major cloud providers. Global deployments in the cloud are built on well-known models such as failover, load balancing, and scalability. However, traditional methods used to recover from regional failure—while effective—can be complex. Typical multi-region recovery and high availability system architectures have latency and cost risks that should be considered when facing other limitations such as deployment models in the cloud. This document describes the different traffic management techniques that can be applied to multi-region strategies, focusing on trade-offs and costs. The introduction of new traffic management techniques being applied to the traditional global architectures now allows organizations to adopt cloud services more efficiently. Traffic management is much more straightforward in some environments, while others have started to leverage their traffic management platform via routing. In multi-region deployments, active-active and active-passive are the most common architectural models, allowing organizations to seamlessly handle failover, scalability, and global distribution based on business goals and requirements. However, traffic management for these infrastructures is critical to ensure just data distribution and efficiency, maintaining costs under control and workloads rerouted when necessary. Using the new traffic management techniques will allow organizations to evolve system architectures easily based on business requirements, taking advantage of cost benefits from multiple infrastructures. In these scenarios, traffic management becomes a crucial backbone of success to ensure that traffic is being efficiently and intelligently distributed [1].
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Open Access December 27, 2023

Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A)

Abstract M&A is a strategic concept of business growth through consolidation, gaining market access, increasing strategic positions, and increasing operational efficiency. To understand the dynamics of M&A, this paper looks at aspects such as targeted firm identification, evaluation, bidding for the target firm, and post-acquisition integration. All forms of M&A, including horizontal, [...] Read more.
M&A is a strategic concept of business growth through consolidation, gaining market access, increasing strategic positions, and increasing operational efficiency. To understand the dynamics of M&A, this paper looks at aspects such as targeted firm identification, evaluation, bidding for the target firm, and post-acquisition integration. All forms of M&A, including horizontal, vertical, conglomerate, and acquisitions, are discussed in terms of goals and values, including synergy, cost reduction, competitive advantages, and access to better technology. However, issues such as cultural assimilation, adhesion to regulations, and calculating an inaccurate value are also resolved. The paper then goes deeper to provide insight into how predictive analytics applies to M&A, using ML to improve decision-making with forecasting benefits. Including healthcare, education, and construction industries, the presented predictive models using regression analysis, neural networks, and ensemble techniques help to make decisions. Through time series and real-time data, PDA enables sound M&A strategies, effective risk management and smooth integration.
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Open Access December 27, 2023

Understanding the Fundamentals of Digital Transformation in Financial Services: Drivers and Strategic Insights

Abstract The current financial services sector is realising considerable changes in its operations due to development in technology and embracing of digital platforms. This evolution is changing the established concepts of business, consumers and channels of delivery of services. Financial services firms are changing the way they work through digital transformation due to developments in technology, [...] Read more.
The current financial services sector is realising considerable changes in its operations due to development in technology and embracing of digital platforms. This evolution is changing the established concepts of business, consumers and channels of delivery of services. Financial services firms are changing the way they work through digital transformation due to developments in technology, changes in customer needs, and an increase in emphasis on sustainability. Understanding the opportunities, risks, and new trends in digital transformation is the focus of this paper. Opportunities include efficient real-time decision-making processes, increased transparency and better process controls, which are balanced by the threats of change management, dubious organization-technology fit, and high implementation costs. The study also examines recent advancements, including the application of machine learning and artificial intelligence, developments in mobile and online banking, integration of blockchain, and increasing focus on security and personalised banking. A literature review yields some findings from different studies on rural financial services, the evolution of the blockchain, drivers of digital transformation, cloud-based learning approaches, and emerging sustainability practices. All of these results suggest that more strategic planning, analytics, and more focus on ensuring that organisational objectives are met with transformations should be pursued. Hence, this research findings add to the existing literature in determining how innovative and digital technologies are likely to transform the financial services sector and advance sustainability.
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Open Access December 27, 2019

Predictive Analytics in Biologics: Improving Production Outcomes Using Big Data

Abstract Biopharmaceuticals, or biologics, are a burgeoning sector in the pharmaceutical industry, predicted to reach $239.4 billion by 2025. This unparalleled growth is often attributed to the enhanced specificity offered by large molecules over small molecules. The large size of the constituent proteins necessitates the continuous implementation of big data predictive analytics to elucidate the most [...] Read more.
Biopharmaceuticals, or biologics, are a burgeoning sector in the pharmaceutical industry, predicted to reach $239.4 billion by 2025. This unparalleled growth is often attributed to the enhanced specificity offered by large molecules over small molecules. The large size of the constituent proteins necessitates the continuous implementation of big data predictive analytics to elucidate the most effective candidates in the lead optimization process. These same methodologies can be applied, and with the advent of machine learning and automated predictive analytics, this is becoming an increasingly facile task, to the augmentation and optimization of the downstream production processes that comprise the majority of the development cost of any biologic. In this work, big data from cell line generation, product and process design, and large-scale lead validation studies have been used to compare the applicability of simple statistical models against these black-box approaches for the rapid acceleration of enzymes to the pilot plant stage. This research can be expanded upon to exploit the big datasets generated as part of the progression of biologics through the development pipeline to further optimize production outcomes. Over the coming months, data from the project will be used to probe which approaches are amenable to which processes and, as a result, more amenable to various economic simulations. The computed optimization objective for the HIT must include the cost of acquiring, storing, and analyzing data to construct these predictive models, alongside the expected commercial reward of choosing an optimally ranked candidate. In this vein, perspective must be taken in the probable future price, capability outputs, and ownership issues of increasingly sophisticated data analysis software as superstructures become more frequent. It is frequently stated that decisions made to reduce production costs are data-driven, but that is not because more economically or energetically costly experiments or production methods are employed; to truly evaluate production steps, dynamic energy, and economic models need to become more commonplace. Conversion of process quality approaches from large questionnaires, risk analysis, and expert opinion-driven methods to statistical and thus more reliable approaches is an area of future research in analytics used herein.
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Open Access December 27, 2019

Data-Driven Innovation in Finance: Crafting Intelligent Solutions for Customer-Centric Service Delivery and Competitive Advantage

Abstract Innovations in computing and communication technologies are reshaping finance. The seismic changes are casting uncertainty about the future of financial services. On one hand, fintech evangelists project a rosy future, asserting that the fast-moving algorithms can deliver low-cost financial services intuitively, customized to meet robust consumer expectations. On the other hand, many finance [...] Read more.
Innovations in computing and communication technologies are reshaping finance. The seismic changes are casting uncertainty about the future of financial services. On one hand, fintech evangelists project a rosy future, asserting that the fast-moving algorithms can deliver low-cost financial services intuitively, customized to meet robust consumer expectations. On the other hand, many finance veterans fret that the traditional banking model could disintermediate, bleeding banks via a ‘death by a thousand cuts’, reducing them to passive portfolio holders with no direct customer relationship, eclipsed by digital giants which use their enormous treasure troves of customer data to offer banking as an added service with nearly free cost. Amidst the upbeat technological promises and apocalyptic forebodings, there are two constant, mostly agreed-upon, truths. The first is the vital importance of data. Advances in the internet, cloud computing, and record-keeping technologies are producing an ‘exponential growth in the volume and detail of data’. Some of this big data are personal information. Smartphones are deployed in almost all developed and emerging economies, serving as little spies; tracking, recording location histories, social networks, and app usage of their unsuspecting owners; often with a great degree of precision. ‘People are walking data-factories’ in this ‘mobile digital society’. Data are the fermentation of these global exchanges, electronic commerce and communication, and financial transactions. To just take Facebook as an example, it shares 30 million people a day through updates and posts, hosting personal information on 2.23 billion users. To the alarm of the uninformed public, much of this information is available for commercial harvest. The second constant is the rise of intelligent solutions. Consumers today—be it disclosed or not—are fed tailored clothes, music, film, holiday packages—almost anything you like, notably dynamic pricing, varying in accordance with individual profiles, or personalized search results. The availability of powerful computers has enabled comparable applications that are intended to make the system more responsive to their customer profiles and desires, or to capitalize competitive business possibilities. Such changes will transform the financial industry and occupy a prominent position among the mechanisms of policy competition, reshaping the way in which financial services are bestowed and led on the demand side.
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Open Access December 27, 2021

Advancing Healthcare Innovation in 2021: Integrating AI, Digital Health Technologies, and Precision Medicine for Improved Patient Outcomes

Abstract Advances of wearables, sensors, smart devices, and electronic health records have generated patient-oriented longitudinal data sources that are analyzed with advanced analytical tools to generate enormous opportunities to understand patient health conditions and needs, transforming healthcare significantly from conventional paradigms to more patient-specific and preventive approaches. Artificial [...] Read more.
Advances of wearables, sensors, smart devices, and electronic health records have generated patient-oriented longitudinal data sources that are analyzed with advanced analytical tools to generate enormous opportunities to understand patient health conditions and needs, transforming healthcare significantly from conventional paradigms to more patient-specific and preventive approaches. Artificial intelligence (AI) with a machine learning methodology is prominently considered as it is uniquely suitable to derive predictions and recommendations from complex patient datasets. Recent studies have shown that precise data aggregation methods exhibit an important role in the precision and reliability of clinical outcome distribution models. There is an essential need to develop an effective and powerful multifunctional machine learning platform to enable healthcare professionals to comprehend challenging biomedical multifactorial datasets to understand patient-specific scenarios and to make better clinical decisions, potentially leading to the optimist patient outcomes. There is a substantial drive to develop the networking and interoperability of clinical systems, the laboratory, and public health. These steps are delivered in concert with efforts at enabling usefully analytic tools and technologies for making sense of the eruption of overall patient’s information from various sources. However, the full efficiency of this technology can only be eliminated when ethical, legal, and social challenges related to reducing the privacy of healthcare information are successfully absorbed. Public and media are to be informed about the capabilities and limitations of the technologies and the paramount to be balanced is juvenile public healthcare data privacy debate. While this is ongoing, the measures have been progressed from patient data protection abuses for progress to realize the full potential of AI technology for hosting the health system, with benefits for all stakeholders. Any protection program should be based on fairness, transparency, and a full commitment to data privacy. On-going innovative systems that use AI to manage clinical data and analyzes are proposed. These tools can be used by healthcare providers, especially in defining specific scenarios related to biomedical data management and analysis. These platforms ensure that the significant and potentially predictive parameters associated with the diagnosis, treatment, and progression of the disease have been recognized. With the systematic use of these solutions, this work can contribute to the realization of noticeable improvements in the provision of real-time, personalized, and efficient medicine at a reduced cost [1].
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Open Access December 27, 2021

Advancements in Smart Medical and Industrial Devices: Enhancing Efficiency and Connectivity with High-Speed Telecom Networks

Abstract Emerging smart medical instruments combined with advanced smart industrial equipment facilitate the collection of vast volumes of critical data. This data not only enables significantly more accurate and cost-effective diagnosis and maintenance but also enriches the datasets available for AI algorithms, leading to improved insights and outcomes. The integration of high-speed and ultra-reliable [...] Read more.
Emerging smart medical instruments combined with advanced smart industrial equipment facilitate the collection of vast volumes of critical data. This data not only enables significantly more accurate and cost-effective diagnosis and maintenance but also enriches the datasets available for AI algorithms, leading to improved insights and outcomes. The integration of high-speed and ultra-reliable telecommunications infrastructure is crucial, as it supports the cloud model. This model allows for off-device aggregation in the cloud, which effectively offloads infrastructure demands and provides an extended runway for future technological improvements before the deployment of the next generation of devices. However, in certain scenarios, latency and bandwidth limitations present significant challenges. These limitations require that a substantial amount of AI and machine learning processing is conducted directly on the transmitted data, which places rigorous demands on both the processing subsystems and the communications links themselves. The current project directly addresses the accelerator side of this multifaceted issue. It will carry out comprehensive end-to-end demonstrations leveraging pilot 5G networks and telemedicine facilities, collaborating closely with major industry participants to showcase the capabilities and potential of this innovative technology. This collaborative effort is essential to pushing the boundaries of what is possible in smart medical instruments and industrial applications [1].
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Open Access December 26, 2021

Deep Learning Applications for Computer Vision-Based Defect Detection in Car Body Paint Shops

Abstract The major automated plants have produced large volumes of high-quality products at low cost by introducing various technologies, including robotics and artificial intelligence. The code of many defects on the surface of products is embedded with economic loss and sometimes functionality loss because products are rarely found with defects. Therefore, most items’ production is done based on [...] Read more.
The major automated plants have produced large volumes of high-quality products at low cost by introducing various technologies, including robotics and artificial intelligence. The code of many defects on the surface of products is embedded with economic loss and sometimes functionality loss because products are rarely found with defects. Therefore, most items’ production is done based on prediction and has an invisible fluctuation in production. The detection process for hidden defect images requires a lot of costs and needs to be supported for better progress and quality enhancement. Paint shop defects should be analyzed from color changes to detect defects effectively by preventing the variability of product demand over time. It is not easy to take visible light images without noise because the paint surfaces are glossy. A few parts of illumination and shadows remain in images, even in larger size and high-resolution images. The various painted surfaces are also needed to reflect both color and texture information in computer vision models to classify defects precisely. Several automated detection systems have been applied to paint shop inspections using lasers, infrared, x-ray, electrical, magnetic, and acoustic sensors. The chance of paint shop defects can be low, unnecessarily low, compared to clouds in the sky, but those chances impact defect functionalities. Thus, they are called as “lessons learned.” Lately, artificial intelligence has been introduced to the field of factory automation, and many defect detection feeds have found footsteps in machine learning and deep learning. Recent attempts at deep learning-based defect detection are proposing simple techniques using specific neural network architectures with big data. However, big data is still in its early stages, and significant challenges exist in normalizing and annotating such data. To get cost-efficient and timely solutions tailored to automotive paint shops, it might be a better consideration to combine deep learning solutions with traditional computer vision and more elaborate machine learning methods.
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Open Access December 27, 2019

Transforming the Retail Landscape: Srinivas’s Vision for Integrating Advanced Technologies in Supply Chain Efficiency and Customer Experience

Abstract Technological advances have had a transformative impact on the retail landscape. Challenges arise with guaranteeing technological changes lead to, rather than detract from, increased efficiency and positive experiences. First, integrating technology into the supply chain in an aggressive way is costly. It requires vast changes to existing systems and developments of cross-industry communication [...] Read more.
Technological advances have had a transformative impact on the retail landscape. Challenges arise with guaranteeing technological changes lead to, rather than detract from, increased efficiency and positive experiences. First, integrating technology into the supply chain in an aggressive way is costly. It requires vast changes to existing systems and developments of cross-industry communication protocols. Secondly, the public is often quick to reject technological changes or slow to become users. Finally, ensuring that technological advancements do not only benefit the top few retailers and are accessible to those of any size poses a challenge, as has been seen in the fate of only a handful of radical changes in retail technology. On the other hand, an integral aspect of technology, particularly that used for big data collection and processing, is that it can account for these and other variables. It can predict the success of ventures into modernizing or developing new systems and can identify more effective and efficient ways to do so. Of course, the concerns of job loss or technological monopoly still loom. But, it would seem, the continued advancement of technology in the retail landscape is inevitable.
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Open Access December 27, 2021

An Analysis of Crime Prediction and Classification Using Data Mining Techniques

Abstract Crime is a serious and widespread problem in their society, thus preventing it is essential. Assignment. A significant number of crimes are committed every day. One tool for dealing with model crime is data mining. Crimes are costly to society in many ways, and they are also a major source of frustration for its members. A major area of machine learning research is crime detection. This paper [...] Read more.
Crime is a serious and widespread problem in their society, thus preventing it is essential. Assignment. A significant number of crimes are committed every day. One tool for dealing with model crime is data mining. Crimes are costly to society in many ways, and they are also a major source of frustration for its members. A major area of machine learning research is crime detection. This paper analyzes crime prediction and classification using data mining techniques on a crime dataset spanning 2006 to 2016. This approach begins with cleaning and extracting features from raw data for data preparation. Then, machine learning and deep learning models, including RNN-LSTM, ARIMA, and Linear Regression, are applied. The performance of these models is evaluated using metrics like Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The RNN-LSTM model achieved the lowest RMSE of 18.42, demonstrating superior predictive accuracy among the evaluated models. Data visualization techniques further unveiled crime patterns, offering actionable insights to prevent crime.
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Open Access December 18, 2020

Intelligent Supply Chain Ecosystems: Cloud-Native Architectures and Big Data Integration in Retail and Manufacturing Operations

Abstract The supply chain ecosystem plays a very important role in the success or failure of organizations, markets, and economies. Supply chain ecosystems are broadly defined as supply chain organizations and their collaborators. Today's combined challenges of pandemic shutdowns, rising internet usage, and skyrocketing climate change concerns demand that the supply chain ecosystem better connect with [...] Read more.
The supply chain ecosystem plays a very important role in the success or failure of organizations, markets, and economies. Supply chain ecosystems are broadly defined as supply chain organizations and their collaborators. Today's combined challenges of pandemic shutdowns, rising internet usage, and skyrocketing climate change concerns demand that the supply chain ecosystem better connect with customers, when and how they want, to provide products and services with high levels of availability and zero defects, yet collaboratively do this to reduce transportation and production risks, often at the same time reducing operational costs and carbon footprints. Addressing these challenges, this work explores the cloud delivery capabilities of cloud-native architectures to enable the big data integrations and analytics that are needed to grow smarter supply chain ecosystems. This work describes what smart supply chain ecosystems are and how they are planning to grow their technology and integration capabilities. Discussing the industry-leading advanced and manufacturing technology producer ecosystems, it is explained how their technology collaboration and investment plans are driven by climate change and job creation goals. With these background models, the work examines the new digital reality of customer-driven experiences and economies that are demanding cloud-native and intelligent technology partnerships to deliver climate objectives, operational responsiveness, and compatibility to avoid trading economies of scale for economies of integration. The final objectives of this paper are to share key ideas about the need to balance the growing customer service direct-to-consumer business models with those for collaborative investment by market and industry. In doing this, it hopes to promote an intelligent supply chain ecosystem foundation for helping its different participating countries survive and thrive in the digital economy.
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Open Access December 27, 2022

Towards the Efficient Management of Cloud Resource Allocation: A Framework Based on Machine Learning

Abstract In the constantly evolving world of cloud computing, appropriate resource allocation is essential for both keeping costs down and ensuring an ongoing flow of apps and services. Because of its adaptability to specific tasks and human behavior, machine learning (ML) is a desirable choice for fulfilling those needs. This study Efficient cloud resource allocation is critical for optimizing performance [...] Read more.
In the constantly evolving world of cloud computing, appropriate resource allocation is essential for both keeping costs down and ensuring an ongoing flow of apps and services. Because of its adaptability to specific tasks and human behavior, machine learning (ML) is a desirable choice for fulfilling those needs. This study Efficient cloud resource allocation is critical for optimizing performance and cost in cloud computing environments. In order to improve the precision of resource allocation, this study investigates the use of Long Short-Term Memory (LSTM). The LSTM model achieved 97% accuracy, 97.5% precision, 98% recall, and a 97.8% F1-score (F1-score: harmonic mean of precision and recall), according to experimental data. The confusion matrix demonstrates strong classification performance across several resource classes, while the accuracy and loss curves verify steady learning with minimal overfitting. The suggested LSTM model performs better than more conventional ML (machine learning) models like Gradient Boosting (GB) and Logistic Regression (LR), according to a comparative study. These findings underscore the LSTM (Long Short-Term Memory) model’s robustness and suitability for dynamic cloud environments, enabling more accurate forecasting and efficient resource management.
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Open Access November 24, 2022

Bridging Traditional ETL Pipelines with AI Enhanced Data Workflows: Foundations of Intelligent Automation in Data Engineering

Abstract Machine Learning (ML) and Artificial Intelligence (AI) are having an increasingly transformative impact on all industries and are already used in many mission-critical use cases in production, bringing considerable value. Data engineering, which combines ETL pipelines with other workflows managing data and machine learning operations, is also significantly impacted. The Intelligent Data [...] Read more.
Machine Learning (ML) and Artificial Intelligence (AI) are having an increasingly transformative impact on all industries and are already used in many mission-critical use cases in production, bringing considerable value. Data engineering, which combines ETL pipelines with other workflows managing data and machine learning operations, is also significantly impacted. The Intelligent Data Engineering and Automation framework offers the groundwork for intelligent automation processes. However, ML/AI are not the only disruptive forces; new Big Data technologies inspired by Web2.0 companies are also reshaping the Internet. Companies having the largest Big Data footprints not only provide applications with a Big Data operational model but also source their competitive advantage from data in the form of AI services and, consequently, impact the cost/performance equilibrium of ETL pipelines. All these technologies and reasons help explain why the traditional ETL pipeline design should adapt to current and emerging technologies and may be enhanced through artificial intelligence.
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Open Access December 24, 2022

Cloud Native ETL Pipelines for Real Time Claims Processing in Large Scale Insurers

Abstract Cloud native ETL pipelines support the extract and transform phases of real time claims processing in large scale insurers. The cloud native approach offers dramatic improvements in scalability, reliability, resiliency and agility as well as seamless integration with the diverse set of data sources, destinations and technologies characteristic of large scale insurers. The ETL process extracts data [...] Read more.
Cloud native ETL pipelines support the extract and transform phases of real time claims processing in large scale insurers. The cloud native approach offers dramatic improvements in scalability, reliability, resiliency and agility as well as seamless integration with the diverse set of data sources, destinations and technologies characteristic of large scale insurers. The ETL process extracts data from source systems such as core transaction, fraud, customer and accounting processes, transforms the data to create a usable format for analytics and other applications, and loads the resulting tables into business intelligence or data lake systems for subsequent storage and analysis. By addressing these two phases of the overall ETL process, cloud native ETL pipelines can provide timely, reliable and consistent data to data scientists, actuaries, underwriters and other analysts. Real time processing represents a key priority within the overall claims process: faster, more accurate claim approvals reduce insurer costs, improve customer service and enhance premium pricing. As a result, a variety of claims related use cases are moving from batch to real time.
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Open Access December 21, 2021

Optimizing Data Warehousing for Large Scale Policy Management Using Advanced ETL Frameworks

Abstract Data warehousing is a technique for collecting, managing, and presenting data to help people analyze and use that data effectively. It involves a large database designed to support management-level staff by providing all the relevant historical data for analysis. This chapter begins with a definition of data warehousing, followed by an overview of large-scale policy management to highlight the [...] Read more.
Data warehousing is a technique for collecting, managing, and presenting data to help people analyze and use that data effectively. It involves a large database designed to support management-level staff by providing all the relevant historical data for analysis. This chapter begins with a definition of data warehousing, followed by an overview of large-scale policy management to highlight the need for data warehousing. Next, an overview of an ETL framework is presented, along with a discussion of advanced ETL techniques. The chapter concludes with an outline of performance optimization techniques for data warehousing. Data warehousing is considered a key enabler for efficient reporting and analysis, with implementation choices ranging from cost-effective desktop systems to large-scale, mission-critical data marts and warehouses containing petabytes of data. Extract, transform, and load (ETL) systems remain one of the largest cost and effort areas within data warehouse development projects, requiring significant planning and resources to build, manage, and monitor the flow of data from source systems into the data warehouse. The technology and techniques used for ETL can greatly influence the success or failure of a data warehouse. Complex business requirements for data cleansing, loading, transformation, and integration have intensified, while operational plans for real-time and near-real-time reporting add additional challenges. Parallel loading mechanisms, incremental data loading, and runtime update and insert strategies not only improve ETL performance but also optimize data warehousing performance, particularly for large-scale policy management.
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Open Access December 22, 2020

Cloud Migration Strategies for High-Volume Financial Messaging Systems

Abstract Key business objectives for digital infrastructure cloud adoption are often framed in terms of reducing cost, improving fault tolerance and resilience, simplifying scale, and enabling innovation. Given the critical nature of the financial sector, however, where timeliness and price can significantly determine an outcome, cloud migration in delivery environments demands greater throughput on the [...] Read more.
Key business objectives for digital infrastructure cloud adoption are often framed in terms of reducing cost, improving fault tolerance and resilience, simplifying scale, and enabling innovation. Given the critical nature of the financial sector, however, where timeliness and price can significantly determine an outcome, cloud migration in delivery environments demands greater throughput on the critical path and, in many enterprise-scale settings, forgoes hybrid complexity and multi-cloud risks. Nevertheless, slack in system designs does exist; financial institutions enable market functionality—trading, clearing/best execution—despite potentially being able to meet such sets with lower service levels than other verticals. A cloud multi-account structure for sensitive data, for example, naturally limits exposure when combined with observed risk. Fulfilling predictions of elasticity during periods of high demand usually requires support from a dedicated environment (or environments) located nearer to the operations. Components can consequently be allocated on a per-account basis or maintained as shared sink systems to which the dedicated streams write. The automation code can similarly be targeted for dedicated accounts, avoiding the resource constraints that beset such operations during industry events like emergency triage/contact desking.
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Open Access December 26, 2021

Scalable Data Warehouse Architecture for Population Health Management and Predictive Analytics

Abstract Scalable architecture principles for data warehousing are introduced to support population health management and predictive analytics. These principles are validated through the design of an accompanying Data Pipeline that allows the integration of non-traditional data sources, the use of real-time data for descriptive analytics dashboards, and support for the generation of supervised Machine [...] Read more.
Scalable architecture principles for data warehousing are introduced to support population health management and predictive analytics. These principles are validated through the design of an accompanying Data Pipeline that allows the integration of non-traditional data sources, the use of real-time data for descriptive analytics dashboards, and support for the generation of supervised Machine Learning models. Several analytical capabilities have been implemented to exemplify the practical application of the principles, including predictive models for Risk Stratification in health care. Optimal cost-effectiveness and performance considerations ensure the practical relevance of the architectural principles and associated Data Pipeline. In recent years, the availability of Low-Cost Data Storage services and the increasing popularity of Streaming technologies opened new possibilities for the storage and processing of Streaming data on a near-real-time basis. These technologies can help Developing Countries in tackling many relevant issues such as Urban Planning, Environmental Management, Migration Policies, etc. A multi-tier approach combining Cloud-based Storage with Data Warehousing and Data Mining technologies can offer an interesting architecture to exploit Big Data related to populations.
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