The decision to choose between onsite and offsite construction is important in the effort toward sustainable construction. Offsite construction is often promoted as an environmentally friendly approach to construction operations. However, previous studies have shown that there is a lack of clarity on the environmental trade-offs between onsite and offsite construction. Factors that can affect the decision to build onsite or offsite include the availability of a local offsite manufacturing facility, the distance of the offsite factory to the final place of use, the proximity of the site to the local supply of material and labor, etc. This study provides a framework to apply the system dynamic modeling technique to evaluate how various factors can affect the environmental impact of the building construction phase (for onsite or offsite construction methods). The system dynamic model (using Vensim software) that was developed provides a platform that allows users to input variables such as the distance that is expected for transportation of labor, material, and equipment to both the onsite facility and the offsite construction location, factors associated with the use of equipment for construction, the distance needed for transportation of building panels or modules from the offsite facility to the final site, etc. Among other things, the model showed that an increase in the distance from the offsite yard to the final construction site increases the total impacts of transportation of completed modules. An increase in the number of trips for the transportation of material to the onsite construction location increases the total impact of onsite construction. In terms of the environmental impact of construction, none of the two methods of construction gives an absolute superiority over the other. The environmental performance of offsite and onsite depends on various associated factors. It is recommended that building practitioners review various factors that are peculiar to their projects to make an informed decision on the best construction methods.

The article's purpose is twofold. First, we wish to draw attention to the insufficiently known field of continuous-time difference equations. These equations are paradigmatic for modeling complexity and chaos. Even the simplest equation , easily leads to complex dynamics, its solutions are perfectly suited to simulate strong nonlinear phenomena such as large-to-small cascades of structures, intermixing, formation of fractals, etc. Second, in the main body of the article we present a small but very important part of the theory behind the above equation marked by . Just as the discrete-time analog of this equation induces the one-dimensional dynamical system on some interval , so the equation induces the infinite-dimensional dynamical system on the space of functions . In the latter case, not only are the long-term behaviours of solutions critically dependent on the limit behaviour of the sequence (as in the discrete case) but also on the internal structure of as . Assuming to be continuous, we consider the iterations of as the semigroup generated by on the space of continuous maps, and introduce the notion of a limit semigroup for in a wider map space in order to investigate asymptotic properties of . We construct a limit semigroup in the space of upper semicontinuous maps. This enables us to describe both of the aforementioned aspects of our interest around the iterations of.

Anthyllis hermanniae subsp. brutia, is an Italian endemic shrub occurring just in one locality by the Calabrian Ionian coast in southern Italy. Objective of this study is to provide data on population numbers, demography and ecology, as well as to identify the main threats on the long term conservation of the target taxon. The survey has been carried out through field census work, sampling biometric and dendrometric data, and applying simple statistics. The population, counting totally 962 individuals, is divided in two stands concentrated in the central part of the distribution area. It is restricted to a narrow belt on the inland part of the dune slope encompassed between an artificial pine forest at the dune top, and the dune-specialized vegetation on the slope. Some biometric insights, such as stem diameter, plant height and number of annual rings, suggest the role of micro-ecology in individual shaping. The most relevant threating factor for the long term conservation of this rare taxon is the rapidly spreading Pinus halepensis subsp. halepensis. Local population of this invasive alien species, deriving from planted individuals, is now invading the A. hermanniae subsp. brutia habitat. Chorological and ecological data here provided should hopefully steer further population dynamics investigation as well as any urgent environment management actions.

The reduction of the native forests coverage in mainland Portugal increased in the past centuries, leading to a marked decrease in biodiversity in general, especially on typical species of mature forest environments. However, urban biodiversity seems to resist more effectively than rural to disturbances due to the lower incidence of fires, as well as to agriculture expansion. Thus, in this work, we analyzed the dynamics of the natural vegetation potential in each biogeographic sector, and selected, based on the evolutionary stages of the vegetation, a set of priority taxa for conservation. The criteria used are intended to highlight plants with ornamental value, but at the same time, some of them have high patrimonial value, belonging to the Red List of Vascular Flora of Mainland Portugal or protected by Annexes II, IV and V of the Sectorial Plan of the Natura 2000 Network at the European level. Our analysis resulted in the identification of 62 plants that can be increased in public spaces in order to improve their conservation status. For each biogeographic sector, the plants best adapted to the local edaphoclimatic conditions are presented. Forest habitats can now, through micro-reserves in urban areas, ensure their long-term conservation and greater awareness among the population. An integrated planning, where the socio-ecological strategy is designed for the long term, will benefit the quality of life of citizens in an urban environment. Furthermore, the creation of micro-reserves in urban parks (gardens) can prevent the extinction of many botanical values in the landscapes of the western Mediterranean Basin.

Background: Coronavirus disease has caused global turmoil especially causing huge impact on human life all over the world. Current reports states more than 3 million people have lost life and more than 160 million people are known to be suspected with the SARS-CoV-2. Transmission and disease incidence rates are indicators to assess the seriousness of COVID-19 pandemic and studies to understand the factors that aid in this direction are very vital to curb the disease. Methods: The study intends to discover the relationship by performing statistical analysis using correlation and multiple linear regression analysis between the variable’s population density, temperature, relative humidity, and active time of virus and find out the parameters that predict the cases reported per million population in 83 countries. Results: Analysis indicates active time of virus in days is very positively associated with the COVID -19 cases in all the countries r = .604, p < .01. Active time of virus shows strong negative correlation with temperature r = -.930, p < .01 revealing that rise in temperature will reduce the virus activity in the population. Together, these variables will account for 36.2% variance in the cases per million population with no significant prediction estimated from any factor. Conclusion: The study outcomes clearly state that population density alone is insufficient to estimate the extent of influence on COVID -19 cases as the number of persons living per sq. km of land is a dynamic quantity tend to fluctuate over time and space due to migration of population. In conjunction to the previous studies reported on the environmental and climatic factors influencing the cases reported, population dynamics does not show much significance on the disease spread and incidence. Contribution: The rise in confirmed cases and the high incidence rate reported in countries can be attributed to the active time of virus life expectancy as there is a positive correlation observed between the COVID-19 cases reported and the virus active time in the examined countries. Also, environment and climatic factors play a role in modulating the infection and transmission rate with less significant influence of population density on the COVID-19.

Objective: The effects of muscle fatigue appear to elicit a transient means of postural instability; however, the recovery of postural stability after fatiguing exercise has not been extensively studied. This study aimed to determine the immediate effect of local vibration applied to fatigued plantar flexor muscles on postural stability in healthy young adults. Design: True Experimental (pre-test - post test design with a control group). Setting: A tertiary care centre. Participations: 42 healthy young adults. Intervention: Fatigue of plantar flexors muscles was induced by repeated dynamic contractions performed to maximum exhaustion. Experimental group (n= 21) received local vibration to fatigued muscles with a handheld vibrator whereas the control group (n = 21) received no intervention (rest). Postural stability was assessed using one leg stance test (OLST) under three different conditions viz. pre-fatigue, post-fatigue and post rest/vibration. Results: Comparative analysis of postural stability within the group was done pre-fatigue, post-fatigue and post rest/vibration condition using Kruskal-Wallis test. A significant decrease from pre-fatigue to post-fatigue condition (p-value < 0.001); and a significant increase from post-fatigue to post rest/vibration condition (p-value < 0.001) was observed in OLST in both - control group and experimental group. However, further comparison of OLST between the groups (using unpaired t test) showed a significant difference in post-fatigue condition versus post rest/vibration condition in favour of the experimental group. Conclusion: Plantar flexors fatigue significantly affects one leg stance time in healthy young adults. Results of this study show that there is an immediate effect of vibration to fatigued muscles on recovery of postural stability in healthy young adults. Recovery of postural stability achieved quickly with such a simple tool may help increase the degree of participation in sports and other similar activities which can cause muscles to fatigue. However, more studies are required to determine this effect using other clinical measures.

The article considers the problems of theoretical substantiation of negative informational and psychological impact evaluation principles, and conducting of relevant researches in this field. At the same time, due to imperfections of theory and practice of negative informational and psychological impact evaluation, previous researches were conducted mainly by “mirroring” the ways of information counteraction, both for our own measures of information and psychological influence, and for the adversary. The rationale for the methodological approaches used in the organization of information and psychological influence is due to inability to access the adversary's target audiences freely and gather the necessary information, as well as the inadequacy of assessing the degree of change in their behaviour. Characteristics mentioned in article classify target audiences according to defined indicators of remote information control of social and individual behaviour of possible objects of influence. Using the formulated conditions and relying on the psychological and psychophysiological characteristics of individuals, a database of target audience behaviour vulnerabilities is forming, that reflects the dependence of indicators of social behaviour perception changes on the intensity of external negative informational and psychological influences. The algorithm of target audience’s information perception is developed based on the model of planned behaviour, in which the subject’s overestimation of small values of probabilities are compared in dynamic with decrease of big ones. The proposed algorithm of evaluation of information-psychological impact allows to receive initial data based on which the model of target audience behaviour will be designed in any environmental conditions.

This Practice-based research explores the innovative application of textiles in the creation of decorative flower vases, positioning them at the intersection of functional design and contemporary art. The study investigates the potential of techniques such as weaving, embroidery, and applique to transcend the conventional boundaries of the medium. Through a methodological framework combining material experimentation interviews with textile artisans and pottery producers in Accra, and critical reflection, the research examines the interplay of materiality, form and aesthetics. It integrates traditional Ghanaian motifs with modern design principles to create culturally resonant, sustainable artworks. The findings demonstrate textiles' significant versatility and creative capacity for producing unique decorative objects. This study contributes to discourses on material innovation and sustainable design by highlighting textiles as a dynamic medium for artistic expression. It offers practical insights for artisans and designers, underscoring the role of textiles in evolving traditional crafts for contemporary contexts.

Mathematical modeling plays a central role in infectious disease epidemiology, shaping outbreak response strategies and informing public health policy. The COVID-19 pandemic demonstrated the value of these models but also exposed persistent limitations related to data fragility, lack of transparency, limited stakeholder engagement, and insufficient consideration of social and political contexts. Rather than critiquing modeling as a discipline, this perspective argues for a reorientation of infectious disease modeling toward a more responsive, equity-centered, and participatory paradigm. We propose a conceptual framework built on three interrelated principles: adaptability through real-time data integration, transparency via open-source and reproducible practices, and relevance through interdisciplinary and co-produced model design. Drawing on illustrative examples from COVID-19 and dengue control efforts, we highlight how integrating behavioral dynamics, local knowledge, and policy feedback can improve model usefulness and public trust. Reconceptualizing models as dynamic systems of inquiry rather than static forecasting tools can enhance decision-making and promote more equitable and effective responses to future public health emergencies.

Introduction: Stroke remains one of the leading causes of death and disability worldwide, with ischemic stroke accounting for most cases. Structural vascular factors such as carotid artery tortuosity have gained attention as potential markers of vascular aging and cerebrovascular risk. The carotid tortuosity index (CTI), defined as the ratio of actual vessel length to the straight-line distance between two fixed points, provides a quantitative measure of arterial curvature. A CTI value of ≥1.2 indicates pathological tortuosity. Although noninvasive modalities such as CTA and MRA are frequently used, digital subtraction angiography (DSA) remains the gold standard for evaluating vessel geometry due to its higher spatial precision. This study aimed to determine the association of age, sex, and hypertension with CTI measured by DSA. Methods: A cross-sectional study was conducted from November to December 2025 at the Neurointervention Clinic, RS Pelni Jakarta, Indonesia, involving 61 adult patients who underwent carotid DSA. CTI was measured bilaterally using digital imaging software and classified as <1.2 (non-tortuous) or ≥1.2 (tortuous). Clinical data, including age, sex, and hypertension status, were collected from medical records and analyzed using bivariate tests. Results: Older age (≥65 years), female sex, and hypertension were significantly associated with higher CTI values on both carotid sides. Tortuosity was more common among hypertensive patients and elderly females, indicating the influence of vascular remodeling and chronic hemodynamic stress. Conclusion: Carotid tortuosity increases with age, hypertension, and female sex. DSA-based CTI measurement provides a reliable and precise approach for evaluating vascular changes associated with cerebrovascular risk.

Background: Tobacco endgame, defined as elimination of commercial tobacco sales The U.S. tobacco control landscape is a complex, adaptive system shaped by diverse stakeholders, evolving products and regulations, shifting social norms, and the strategic countermeasures of a powerful industry. Managing such complexity requires more than isolated interventions—it demands a coordinated, enterprise-wide approach that accounts for dynamic interactions, feedback loops, and emergent risks. Objective: Drawing on complex systems thinking, Zachman enterprise architecture model, and public health best practices, we conceptualize tobacco control as an evolving enterprise progressing through six interconnected phases: (1) Conception & Initiation, (2) Policy & System Design, (3) Implementation & Operation, (4) Evaluation & Adaptation, (5) Consolidation & Endgame Transition, and (6) Sustainment or Sunset. Each phase incorporates governance structures, performance benchmarks, and transition criteria designed to manage interdependence and reduce systemic vulnerabilities. Results: The lifecycle framing emphasizes how tobacco control in the U.S. can evolve as a complex, adaptive enterprise—integrating public health objectives with legal, operational, and cultural change processes. This model supports strategic sequencing, cross-sector alignment, and risk mitigation against emergent industry tactics, enabling a resilient and measurable pathway to the endgame. Conclusions: Seeing tobacco control as a complex enterprise that operates under a lifecycle model may offer a roadmap for achieving and sustaining the tobacco endgame. Using this approach may enhance policy coherence, resource efficiency, and adaptability, ensuring tobacco endgame is achieved.

This work explores the intimate process of creating an acrylic portrait of a long-time friend, guided by photographs. Through a detailed examination of the technical and emotional aspects of portrait painting, this narrative reflects on the deep bond and shared history between the artist and subject. Emphasising the role of mutual understanding, trust, and empathy in the creative process, the paper illustrates how personal experiences and memories shape artistic expression. Drawing on art therapy, narrative identity, and the psychological impact of art, this study offers insights into how portrait painting can facilitate personal reflection, retrospection, and meaningful connection.

Complexity Leadership Theory (CLT) is a new and revolutionary concept in addressing healthcare crises worldwide. Its relevance and applications were tested during the COVID-19 pandemic. However, no definite and encompassing research was done to apply it to nursing leadership. Thus, this study examines CLT integration into nursing leadership to address the challenges posed by the pandemic. Through a systematic review of literature from PubMed, Scopus, and Web of Science, relevant studies were analyzed to determine how complexity leadership theory was defined, conceptualized, and operationalized within nursing leadership context. The findings reveal that traditional hierarchical leadership models are insufficient in a dynamic crisis environment like the pandemic. Instead, CLT’s framework which encompasses adaptive, administrative, and enabling leadership facilitates innovation, resilience, and effective interprofessional collaboration. Nurse leaders employing these strategies are better positioned to manage resources limitation, foster shared decision-making, and implement technological advancements in rapidly changing healthcare settings. Overall, this study underscores the potential of complexity leadership theory to transform nursing leadership practices by promoting continuous learning and empowerment, thereby enhancing crisis response and preparedness for future pandemics.

Preference learning plays a crucial role in AI applications, particularly in recommender systems and personalized services. Traditional pairwise comparisons, while foundational, present scalability challenges in large-scale systems. This study explores alternative elicitation methods such as ranking, numerical ratings, and natural language feedback, alongside a novel hybrid framework that dynamically integrates these approaches. The proposed methods demonstrate improved efficiency, reduced cognitive load, and enhanced accuracy. Results from simulated user studies reveal that hybrid approaches outperform traditional methods, achieving a 40% reduction in user effort while maintaining high predictive accuracy. These findings open pathways for deploying user-centric, scalable preference learning systems in dynamic environments.

Digital therapeutics (DTx) play a transformative role in diabetes management by leveraging technology to provide personalized, data-driven medical interventions. These tools enhance self-management by offering continuous monitoring and real-time feedback on glucose levels, diet, and physical activity. This personalized approach helps patients adhere to treatment plans and make informed lifestyle changes, leading to improved clinical outcomes such as reduced HbA1c levels and better overall diabetes control. The importance of DTx lies in their ability to make diabetes care more accessible and convenient. Mobile apps and telemedicine platforms enable patients to receive support and guidance from anywhere, reducing the need for frequent in-person visits. Additionally, DTx often include behavioral support features like reminders, educational content, and motivational tools, which are crucial for maintaining healthy habits and managing stress. Currently, the dynamics of DTx in diabetes are rapidly evolving, with increasing integration of artificial intelligence and machine learning to further personalize and optimize care. As the adoption of these technologies grows, they hold the potential to significantly improve patient outcomes and revolutionize diabetes management on a global scale. This article will focus on the benefits of novel digital therapeutics for prevention and management of type II diabetes that are currently available in the market.

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.

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.

Intersectionality has significantly enhanced our understanding of how overlapping social identities—such as race, ethnicity, gender, sex, class, and sexual orientation—interact to shape individual experiences. However, despite its theoretical importance, much of the existing literature has relied on qualitative approaches to define and study intersectionality, limiting its application in predictive modeling, comparative analysis, and policy development. This paper introduces the concept of Quantitative Intersectionality Scoring System (QISS), a novel approach that assigns numerical scores to intersecting identities, thereby enabling a more systematic and data-driven analysis of intersectional effects. We argue that QISS can substantially enhance the utility and predictive validity of quantitative models by capturing the complexities of multiple, overlapping social determinants. By presenting concrete examples, such as the varying impacts of socioeconomic mobility on life expectancy among different intersectional groups, we demonstrate how QISS can yield more precise and reliable forecasts. Such a shift would allow policymakers and service providers to dynamically assess economic and health needs, as well as the uncertainties around them, as individuals move through different social and economic contexts. QISS-based models could be more responsive to the complexities of intersecting identities, allowing for a more quantified and nuanced evaluation of policy interventions. We conclude by discussing the challenges of implementing QISS and emphasizing the need for further research to validate these quantifications using robust quantitative methods. Ultimately, adopting QISS has the potential to improve the accuracy of predictive models and the effectiveness of policies aimed at promoting social justice and health equity.

Background: Telomere length is a critical biomarker of cellular aging and overall health. While childhood socioeconomic status (SES) indicators such as education and poverty can have long-lasting effects on biological aging, research has shown contradictory results regarding the impact of adulthood SES on future telomere length, particularly in racially and ethnically diverse individuals. This study investigates the effects of baseline adulthood SES indicators such as education and poverty on telomere length nine years later in women, using data from the Future of Families and Child Wellbeing Study (FFCWS). Methods: We analyzed data from the FFCWS, a longitudinal cohort study. The sample included baseline adulthood SES and follow-up telomere length measure of women (n = 2,421) with varying socioeconomic conditions. Telomere length was measured from saliva samples nine years after the baseline measure of adulthood SES. Education, poverty, and marital status at baseline were assessed. Multivariate linear regression models were used to examine the association between adulthood SES indicators at baseline and future telomere length, controlling for potential confounders. Results: From the total 2,421 women, 675 were Latino White, 1,158 were non-Latino Black, and 588 were non-Latino White. Our findings indicate that for non-Latino White women poverty at certain level, and childbirth weight, and for non-Latino Black maternal age were predictors of telomere lengths nine years later. Conclusion: Poverty at a specific level, maternal age and childbirth weight serve as predictors of telomere lengths nine years later in some women. These findings underscore the importance of socioeconomic factors and early-life influences in understanding telomere dynamics and aging processes among women from varied racial and ethnic backgrounds.

We study a dynamic model of the relationship between two people where the states depend on the “power” in the relationship. We perform a comprehensive analysis of stability of the system, and determine a set of conditions under which stable relationships are possible. In particular, stable relationships can occur if both people are dominant, but the sum of dominances is below a bound determined by the model’s parameters. Stable relationships can also occur if one person is dominant and the other is submissive, provided the level of dominance exceeds the level of submissiveness but not beyond a threshold. We also conclude that a stable relationship is not possible if both people are submissive. While our model is motivated by a social or romantic relationship, it can also be applied to professional or business relationships, diplomatic relationships between nations, and certain biological interactions between organisms and between automated agents or robots.

The intersection of race and place in shaping health disparities presents complex dynamics, as evidenced by studies in cities like Detroit, Baltimore, and Philadelphia, where predominantly Black and economically disadvantaged populations experience high overall rates of health problems. Surprisingly, these cities do not exhibit the most pronounced racial disparities. In contrast, areas with a higher percentage of White residents, indicative of greater income inequality, show stark differences in health outcomes between Black and White populations. This disparity underscores how conditions diverge more sharply between Black and White individuals in wealthier urban areas. This phenomenon suggests a complex and sometimes counterintuitive relationship among race, place, income, and income inequality in shaping racial health disparities. These dynamics have significant policy implications. Addressing health disparities requires nuanced strategies that recognize the multiplicative effects of race and income inequality on health outcomes. Policies focusing on areas with a high disease burden, such as Detroit, Philadelphia, and Baltimore can effectively mitigate disparities both locally and more broadly. Conversely, interventions targeting regions with lower disease prevalence, but higher racial disparities must be approached carefully to avoid exacerbating inequalities. In conclusion, understanding and addressing the complex drivers of health disparities demand comprehensive approaches that acknowledge the intertwined influences of race, income, and place. By prioritizing interventions that address economic disparities alongside health initiatives, policymakers can foster more equitable health outcomes across diverse communities.

The operational performance of Active Pharmaceutical Ingredients (API) supply chains often suffers from significant disruptions attributed to inherent vulnerabilities. Despite theoretical discussions, empirical evidence validating these vulnerabilities remains sparse. This study endeavours to empirically substantiate the vulnerabilities arising from dynamic disruptions within the pharmaceutical supply chain. Its primary goal is to discern actionable insights that can inform the development of robust resilience strategies capable of effectively mitigating such disruptions. This study investigates vulnerabilities within the active pharmaceutical ingredient (API) supply chain in response to disruptions. Despite theoretical insights, empirical evidence validating these vulnerabilities remains limited. Through empirical analysis, this research aims to identify and elucidate the specific vulnerabilities exacerbated by dynamic disruptions in the API supply chain. The findings are intended to inform the development of resilient strategies capable of mitigating the impact of disruptions on pharmaceutical supply chains.

Our lives are becoming more and more digital, and this has an impact on how we work, study, communicate, and interact. Businesses are currently digitally altering their information systems, procedures, culture, and strategy. Existing businesses and economies are severely disrupted by the digital revolution. The Internet of Things, microservices, and mobile services are examples of IT systems with numerous, dispersed, and very small structures that are made possible by digitization. Utilizing the possibilities of cloud computing, mobile systems, big data and analytics, services computing, Internet of Things, collaborative networks, and decision support, numerous new business prospects have emerged throughout the years. The logical basis for robust and self-optimizing run-time environments for intelligent business services and adaptable distributed information systems with service-oriented enterprise architectures comes from biological metaphors of living, dynamic ecosystems. This has a significant effect on how digital services and products are designed from a value- and service-oriented perspective. The evolution of enterprise architectures and the shift from a closed-world modeling environment to a more flexible open-world composition establish the dynamic framework for highly distributed and adaptive systems, which are crucial for enabling the digital transformation. This study examines how enterprise architecture has changed over time, taking into account newly established, value-based relationships between digital business models, digital strategies, and enhanced enterprise architecture.

The emphasis on adapting learner-centric education and inclusive pedagogies to promote learning effectiveness is part of the paradigm shift in teaching. By maximizing variability, differentiated education methodologies ensure individualized instruction and equal academic success for all students. Based on this justification, this study sought to investigate Ghanaian pre-tertiary teachers' adaption of differentiated instruction strategies during the teaching and learning processes. Pre-tertiary teachers within the Kwahu Ridge of the Eastern Region of Ghana were sampled to respond to the close-ended questionnaire. A multi-pronged approach was employed in the data analysis. Respondents possessed knowledge of the differentiated instruction strategies, however, there were some disparities between first and second-cycle teachers. Significant factors influenced the range of diversity in the classroom and knowledge and experience, with the latter showing an unexpected negative influence, possibly due to experienced teachers' preference for traditional methods of teaching. Notwithstanding, a perfect alignment of instructional techniques, activities and assessment practices to accommodate the heterogeneity of students stimulate active participation, interest and readiness to learn. It is recommended that educational stakeholders should recognize the dynamic nature of the learning environment and better provide pre-tertiary teachers with the tools and support needed to employ differentiated instruction techniques successfully to ensure inclusive, individualized and intensive instruction in the classroom.

In the current study, the eight-bar planar mechanism is balanced by reducing variations in shaking force and moments using Minitab and a genetic algorithm. The objective function and constraint equations are taken into consideration, the mathematical model was developed to optimize the balancing of the planar eight-bar mechanism.A set of weighting factors were taken into consideration in order to determine the ideal values for the design parameters based on the contributions of the X and Y components of the shaking force and the shaking moment. A genetic algorithm was used to find the best design parameters. The results showed that the shaking force and moments decreased by 34.5 and 61% from the initial values, respectively.

First, based on the many levels and their cycles in geoscience, we research the hypercycle of geoscience. This is the hypercycle as a tool of self-organization applied to geoscience. It may form from a level to other higher levels. These levels influence each other and the co-evolution. Second, we discuss some possible mathematical methods, which include graph, vector, matrix, some equations, similar theories, etc. This method can be developed and perfected. Third, we propose the nonlinear whole geoscience and its three basic laws. Fourth, we discuss thermodynamics of geoscience, and in which possible entropy decrease under some sates, such as evolution and cycles of Earth, etc. Sustainable development of society must study the mode from high entropy to low entropy. Various cycles in geoscience cannot all be entropy increases, and cannot all be originated from the external interactions.

The study focused on the nature and characteristics of the chieftaincy succession conflict in the Akuapem Traditional Area of Ghana. This study was anchored on an interpretivist philosophical viewpoint. Methodologically, the study employed a qualitative approach with a descriptive phenomenology research design. Thirty-four (34) adults who have lived in the area for the past five years participated in the study. They included members of the traditional council, the Akuapem North Municipal Assembly, the royal gates to the paramountcy and others within the community. Participants were selected using extreme case, critical case and convenience sampling techniques. Data were collected with the use of interview guide, focus-group discussion and observation protocols. The data collected were analysed thematically in line with the research questions and emerged patterns from the dataset. The study found out that the dynamics of the conflict revolved around the nature and frames. The findings showed multiple causes that resulted in the exacerbation of the conflict. A major conclusion drawn from the study was that the chieftaincy institution in Akuapem is hurled with conflict which has complex dynamics and thus, has had multiple implications on the stability and development of the society. It is therefore recommended that all stakeholders to the installation are duly left to perform their duties without any intrusion from external parties or outsiders. Moreover, the grievances of these stakeholders should be addressed to ensure smooth running of the processes. This can be ensured by the traditional council of the area.

Many attempts have been made to repurpose existing and approved drugs for the treatment of COVID-19 infection. This involves anti-malarial drugs such as hydroxychloroquine and chloroquine, which have been shown to be less successful than initially believed, with a substantial risk of often fatal complications and interactions. This also involves Remdesivir, which has been shown to decrease recovery time significantly in hospitalized patients. However, for patients who are not yet hospitalized, there is no currently accepted treatment. Treating patients before they need to be admitted or even prophylactically could greatly decrease the load on hospitals, protect healthcare workers and reduce the spread of COVID-19. An in-vitro study indicated that Ivermectin was dynamic against COVID-19-infected cell. Ivermectin has antimicrobial, antiviral, and anticancer, immunomodulatory properties. This drug could reduce the viral load in COVID-9 infected patients, with potential effect on disease progression and spread. Therefore, Ivermectin may be a therapeutic choice for treatment of COVID-19, however, there is still a lack of evidence-based studies to support ivermectin treatment of patients with COVID-19.

Groundwater geochemistry refers to the general chemical properties of water, particularly groundwater. Precipitation, volatilization, oxidation/reduction, sorption/partition, and complexation are processes involved in the distribution and fate of organic molecules in water. Determining hydrogeochemical facies is a great help for determining relationships and similarities among the chemistry of waters in an aquifer. This study focused on the coastal aquifer of Tripoli (Lebanon) with Mio-Quaternary age. It is considered as a confined aquifer and an important hydraulic reserve for domestic water use in the region. Recently, it underwent an urban development that leads to an increase in water demand causing a decrease in the piezometric level and a high-risk of deterioration to water quality through seawater intrusion and anthropic pollution. To understand the origin of mineralization and the mechanism of water hydro-chemistry variation and to provide a vision to underground water recharge, this study aims to analyze the hydrodynamic, piezometric, and geochemical characteristics of the coastal aquifer. The fluctuation of physicochemical parameters for cool and warm seasons has been studied and monitored for 16 coastal wells during April, May, and June 2020. Results were interpreted by using a statistical analysis called Principal Components Analysis (PCA). Cartographic of groundwater levels and concentrations for nitrate, chloride, sulphate ions, the ratio sulphate/chloride were determined by using SUFFER8 software. It can be noticed that the Mio-Quaternary formation at Tripoli consists of thick sedimentary sandstones and conglomerates with argillaceous roots, which provide significantly high permeability characteristics. It is mainly recharged from precipitations through karstic formations. Chemical analysis shows that bicarbonate ions (HCO₃^-), characterized by dissolution of carbonate rocks from geological upstream formations of Tripoli, means that the aquifer is subjected to intensive recharge of fresh water and snow melting making a hydrostatic equilibrium facing marine intrusion [1]. High contents of chloride and Sodium are due to anthropic contamination or seawater intrusion. However, Magnesium ion concentration assures this intrusion. Meanwhile, nitrates, sulfates and phosphorus high concentrations are related to wastewater leakage or agricultural activities [2].

Skew-symmetric differential forms possess properties that enable one to carry out a qualitative investigation of the equations of mathematical physics and the foundations of field theories. In the paper we call attention to a unique role in field theory of closed exterior skew-symmetric differential forms, which correspond to conservation laws for physical fields (to conservative quantities). At the same time, it was shown that such closed exterior forms can be derived from skew-symmetric differential forms, which follow from the mathematical physics equations describing material media such as thermodynamic, gas-dynamic, cosmic media. This points a connection the field theory equations with the mathematical physics equations. Such connection discloses the properties and specific features of field theory.

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.

Background: Onchocerciasis is a vector-borne neglected tropical disease (NTD) caused by the filarial worm Onchocerca volvulus. Given the high morbidity and mortality, onchocerciasis control gained great attention from many stakeholders both nationally and internationally. However, there are still the need for further solidified commitments and compelling initiatives across concerned stakeholders including regional bodies in the fight toward controlling its burden and risks. Thus, this review briefly appraised the current understanding and dynamics in the control and eradication efforts of Onchocerciasis in Africa. Methods: A rapid scoping review was used for this paper. Key databases used for this study include Web of Science, Scopus, Science Direct, PubMed and Google Scholar to identify a series of relevant peer-reviewed publications. The search contained just English-language articles. In addition, African government websites and specialized organizations such as WHO, UNAIDS, CDC, etc. were accessed and reviewed to gather important data on national and international control programs, related documentation and consultative expert reports. Results: In Africa, long-standing strides toward the control and elimination measures for onchocerciasis were conducted for several decades. Between 1974 to 2002, OCP had actively led the control and containment efforts for onchocerciasis in the context of 11 West Africa. However, endemic regions and states have switched their policies from controlling to eradication, with the ultimate objective of preventing their territories from parasite spread. Some key challenges are the insufficient identification of all endemic areas, high prevalence of both onchocerciasis and loiasis, potential development of resistance to ivermectin, inconsistent initiatives to address cross-border problems, disagreements and social disturbance. Various challenges, however, impede current efforts to eradicate African onchocerciasis. Conclusion: In the last decades, extensive measures have been taken with specialized state programs, largely efficient in high endemic nations, to manage and control onchocerciasis in African regions. The implications of these and other difficulties at country level control programs must therefore be identified and country-specific contextual remedies used to expedite the elimination of onchocerciasis.

The plant leaves used as adsorbent in this study were Guava plant leaves (GPL) and Cashew plant leaves (CPL). The samples were collected within Gombe State. Batch adsorption method was used in determining the adsorption process. Fourier Transform Spectroscopy (FT-IR), Scan-ning Electron Microscopy (SEM) and X-Ray Diffraction (XRD) were used for the characterization. The results show promising signs as they were in agreement with most literatures; various per-centage removals were obtained from Pb²⁺ and Cd²⁺ (GPL and CPL) at optimum conditions. The equilibrium data fitted well with both Langmuir and Freundlich isotherm models. Langmuir mod-el fitted well for Pb²⁺ (CPL) with R² value (0.9855) and Cd²⁺ for (GPL and CPL) with R² values (0.9945 and 0.9948) while Pb²⁺ (GPL) with correlation coefficient at 0.9116 best fits well with Freundlich isotherm model. Pseudo first order and second order were used in testing the kinetics study from which pseudo second order best fitted better than that of the first order kinetics. The thermodynamic study shows that ΔG is negative in most cases except for Cd²⁺ (GPL) where ΔG is positive. Whereas ΔH and ΔS are positive in some cases showing an endothermic and spontane-ous adsorption processes respectively, as well as negative in some. Based on this study, GPL and CPL could be used as a natural adsorbent to remove Pb²⁺ and Cd²⁺ heavy metals from wastewater and environment due to their high removal efficiencies.

The kinetics, equilibrium and thermodynamic study of the adsorption of Ni²⁺, Pb²⁺ and Cu²⁺ions from aqueous solution by the leaf of Mangiferaindica were investigated at different experimental conditions. Optimum conditions of initial metal ion concentration, pH, adsorbent dose, contact time and temperature were determined. The kinetics studies indicate that the adsorption process of the metals ions followed the pseudo second-order model with R² value of 0.9938, 1.00 and 1.00 respectively. Equilibrium studies showed that the adsorption of Ni²⁺, Pb²⁺ and Cu²⁺ ions are well represented by both Langmuir and Freundlich isotherm but the Langmuir model gave a better fit for Pb²⁺ ions with R² value of 0.9950 and Langmuir constant K_L of 4.3383 while Freundlich isotherm model best fit the experimental data of lead(II) and nickel(II) with a R² value of 0.976 and 0.9973 and Freundlich constant K_F value of 4.2677 and 0.0874. The calculated thermodynamics parameters of Ni²⁺, Pb²⁺ and Cu²⁺ ions are ( ΔG^o -1182.49,-5479.1 and 613.48 KJ/mol) showed that the adsorption of Ni²⁺ and Pb²⁺are spontaneous while Cu²⁺ non-spontaneous. The findings indicate that the leaf of Mangiferaindica could be used for the adsorption of Ni²⁺, Pb²⁺ and Cu²⁺ ions from industrial effluents.

The Nigerian Government both previous and present has introduced several policies and programmes to reduce or proffer remedial measures to militate against the negative impact of high inflationary levels on the Nigerian economy. All these measures have not led to a productive result as the inflation rate has continued to sour higher over the years. This paper aimed at examining the economic influence of the determinant factors that influence inflationary trends that are multi-dimensional and dynamic which continue to defy solutions. The data used for this work was sourced from the National Bureau of Statistics and Central Bank of Nigeria, from 1983 to 2020. The ordinary least square approach was used to analyze the data and the result shows that consumer’s price index, interest rate and total export has a positive effect on Nigeria inflation, but only the Consumer’s Price Index (CPI) have a statistically significant effect on the Nigeria inflation at 99% confidence interval. Result also shows that the exchange rate, foreign reserve, money supply, real GDP, real income and total imports has a negative effect though not statistically significant on the Nigeria inflation rate. The result of the granger causality test shows exchange rate and total imports to granger cause Nigeria inflation. It is recommended that Government should improve locally manufacture products to meet international demands to reduce total imports.

Many attempts have been made to improve heat transfer for thermally integrated microchannel reforming reactors. However, the mechanisms for the effects of design factors on heat transfer characteristics are still not fully understood. This study relates to a thermochemical process for producing hydrogen by the catalytic endothermic reaction of methanol with steam in a thermally integrated microchannel reforming reactor. Computational fluid dynamics simulations are conducted to better understand the consumption, generation, and exchange of thermal energy between endothermic and exothermic processes in the reactor. The effects of wall heat conduction properties and channel dimensions on heat transfer characteristics and reactor performance are investigated. Thermodynamic analysis is performed based on specific enthalpy to better understand the evolution of thermal energy in the reactor. The results indicate that the thermal conductivity of the channel walls is fundamentally important. Materials with high thermal conductivity are preferred for the channel walls. Thermally conductive ceramics and metals are well-suited. Wall materials with poor heat conduction properties degrade the reactor performance. Reaction heat flux profiles are considerably affected by channel dimensions. The peak reaction heat flux increases with the channel dimensions while maintaining the flow rates. The change in specific enthalpy is positive for the exothermic reaction and negative for the endothermic reaction. The change in specific sensible enthalpy is always positive. Design recommendations are made to improve thermal performance for the reactor.

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.

The level of business competition in several online shopping sites for fashion products is currently experiencing quite crucial dynamics. Competitive match will indirectly affect consumer purchasing decisions. This research explores what factors are dominantly influencing the level of product purchase decisions on online shopping sites in terms of product variety, price, brand image and promotion aspects. This research design uses a quantitative research design. Determination of the sample in this study using the convenience sampling method with a total of 110 respondents. Data collection uses a questionnaire distributed online during the period from May to June 2021. This study concludes that product variations and brand image have a positive and significant influence on purchasing decisions. Then for the effect of price and promotion on purchasing decisions obtained a positive but not significant impact. This study confirms the importance of paying attention to aspects of pricing and product promotion strategies on the Reebonz online shopping site.

The first visualizations of the structures of the sheep's reproductive system, whether of the uterus or ovaries, were performed through exploratory laparotomies, laparoscopies or through materials obtained in slaughterhouse, being possible to evaluate only what was happening at that moment in the estrous cycle. With the emergence of ultrasound from the 90s, it became possible to dynamically monitor what happened at each moment of the estrous cycle at different times of the year, without having to slaughter the females. Because it is a non-invasive technique and the stress caused by its use is very low, it is increasingly necessary to use ultrasound in sheep, either for pregnancy diagnosis or for multiplying herds using biotechnologies, which the ultrasound examination becomes indispensable to obtain the best results. This review aims to describe the main advances in the study of the estrous cycle of sheep with the help of ultrasonography and its influence on the productive efficiency of the herd.

First, we propose the nonlinear whole seismology and its three basic laws. Next, based on the nonlinear equations of fluid dynamics in Earth’s crust, we obtain a chaos equation, in which chaos corresponds to the earthquake, and shows complexity on seismology. But, combining the Carlson-Langer model and the Gutenberg-Richter relation, a simplified nonlinear solution and corresponding magnitude-period formula of earthquakes may be derived approximately. Further, we research the topological seismology. From these theories some predictions can be calculated quantitatively and are already tested. Combining the Lorenz nonlinear model, we may discuss the earthquake migration to and fro. Finally, if various modern scientific instruments, different scientific theories and some paranormal ways for earthquake are combined each other, the accuracy of multilevel prediction will be increased.

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.

This charge-ahead paper suggests that transitioning the automotive industry towards a zero-carbon ecosystem from material to end-of-life can be accomplished through disruptive zero-carbon manufacturing in the broad area of all-electric vehicle production technology. To accomplish zero carbon emission automotive manufacturing in the vehicle assembly domain, future paradigms must converge on the decoupling of carbon dioxide emissions from automobile manufacturing and use the design, processing, and manufacturing conditions. The envisioned zero carbon emission vehicle manufacturing domain consists of two complementary components: (a) making more efficient use of energy and (b) reducing carbon in energy use. This paper presents the status of key scientific and technological advancements to bring the manufacturing model of today to a zero-carbon ecosystem for the entire automotive industry of tomorrow. This paper suggests the groundbreaking application of dynamic and distributed predictive scheduling algorithms and open sensing and visualization technology to meet the zero carbon emission vehicle manufacturing goals. Power-aware high-performance computing clusters have recently become a viable solution for sustainable production. Advances in scalable and self-adaptive monitoring, predictive analytics, timeline-based machine learning, and digital replica of cyber-physical systems are also seen co-evolving in the zero carbon manufacturing future. These methods are inspired by initiatives to decouple gross domestic product growth and energy-related carbon dioxide emissions. Stakeholders could co-design and implement shared roadmaps to transition the automotive manufacturing sector with relevant societal and environmental benefits. The automated mobility sector offers a program, an industry-leading example of transforming an automotive production facility to carbon neutrality status. The conclusions from this paper challenge automotive manufacturers to engage in industry offsetting and carbon tax programs to drive continuous improvement and circular vehicle flows via a multi-directional zero-carbon smart grid.

The pharmaceutical industry is fundamental to global healthcare, providing essential medicines that improve health outcomes and quality of life. However, the demand and supply dynamics within this sector are highly complex, shaped by various factors including demographic changes, evolving disease burdens, technological advancements, regulatory challenges, and economic pressures. This manuscript explores the intricate relationship between pharmaceutical medicine demand and supply, focusing on key strategies that can help companies effectively navigate these challenges. The demand for pharmaceutical products is driven by several factors, such as population growth, the aging population, the rise of chronic diseases, and the emergence of new health threats. Additionally, healthcare accessibility, affordability, and policy changes significantly impact the consumption of medicines, while innovations in medical technologies and therapies create new treatment needs. On the supply side, pharmaceutical companies face challenges related to manufacturing capacity, raw material availability, distribution logistics, and compliance with ever-evolving global regulatory frameworks. To address these challenges, the manuscript discusses strategic approaches to managing both demand and supply in the pharmaceutical sector. Key strategies include advanced demand forecasting through data analytics, optimizing supply chains for efficiency and resilience, implementing just-in-time inventory models, and investing in flexible manufacturing systems. Furthermore, global collaboration and partnerships, as well as effective risk management practices, are highlighted as essential to ensuring the availability of medicines, particularly in times of crisis or global health emergencies. This manuscript also delves into the role of policy advocacy and regulatory harmonization in stabilizing the pharmaceutical market, ensuring that medicines are accessible to all populations. In conclusion, the pharmaceutical industry must continually adapt to meet the evolving challenges of demand and supply, embracing innovation and collaboration while maintaining a focus on patient access and global healthcare equity. Through strategic planning and adaptive solutions, the pharmaceutical sector can ensure the continuous availability of critical medicines worldwide, meeting both current and future health needs.

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.

To ensure maximum flexibility, service providers offer a variety of computing options with regard to CPU, memory capacity, and network bandwidth. At the same time, the efficient operation of current cloud applications requires an infrastructure that can adjust its configuration continuously across multiple dimensions, which are generally not statically predefined. Our research shows that these requirements are hardly met with today's typical public cloud and management approaches. To provide such a highly dynamic and flexible execution environment, we propose the application-driven autonomic management of data center resources as the core vision for the development of a future cloud infrastructure. As part of this vision and the required gradual progress toward it, we present the concept of composable infrastructure and its impact on resource allocation for multi-cloud environments. We introduce relevant techniques for optimizing resource allocation strategies and indicate future research opportunities [1]. Many cloud service providers offer computing instances that can be configured with arbitrary capacity, depending on the availability of certain hardware resources. This level of configurability provides customers with the desired flexibility for executing their applications. Because of the large number of such prerequisite instances with often varying characteristics, service consumers must invest considerable effort to set up or reconfigure elaborate resource provisioning systems. Most importantly, they must differentiate the loads to be distributed between jobs that need to be executed versus placeholder jobs, i.e., jobs that trigger the automatic elasticity functionality responsible for resource allocator reconfiguration. Operations research reveals that the optimization of resource allocator reconfiguration strategies is a fundamentally difficult problem due to its NP-hardness. Despite these challenges, dynamic resource allocation in multi-clouds is becoming increasingly important since modern Internet-based service settings are dispersed across multiple providers [2].

Deep learning approaches are very useful to enhance cybersecurity protocols for industry-integrated big data enterprise resource planning systems. This research study develops deep learning architectures of variational autoencoder, sparse autoencoder, and deep belief network for detecting anomalies, fraud, and preventing cybersecurity attacks. These cybersecurity issues occur in finance, human resources, supply chain, and marketing in the big data integrated ERP systems or cloud-based ERP systems. The main objectives of this creative research work are to identify the vulnerabilities in various ERP systems, databases, and the interconnected domains; to introduce a conceptual cybersecurity network model that incorporates variational autoencoders, sparse autoencoders, and deep belief networks; to evaluate the performance of the proposed cybersecurity model by employing the appropriate parameters with real-time and synthetic databases and simulated scenarios; and to validate the model performance by comparing it with traditional algorithms. A big data platform with an integrated business management system is known as an integrated ERP system, which plays an instrumental role in conducting business for various organizations in society. In recent times, as uncertainty and disparity increase, the cyber ecosystem becomes more complex, volatile, dynamic, and unpredictable. In particular, the number of cyber-attacks is increasing at an alarming rate; the resultant security breaches have a disruptive and disturbing effect on businesses around the world, with a loss of billions of dollars. To combat these threats, it is essential to develop a conceptual cybersecurity network model to secure systems by functioning as a mutually supporting and strengthening network model rather than working in isolation. In this dynamic and fluid environment, introducing a deep learning approach helps to support and prevent fraud and other illicit activities related to human resources and the supply chain, among others. Some cybersecurity vulnerabilities include, for example, database vulnerabilities, service level vulnerabilities, and system vulnerabilities, among others. The proposed methodology focuses only on database vulnerabilities, with the main aim of detecting and mitigating new potential vulnerabilities in other dependent domains as a future initiative.

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.