Articles

<b>Objective: </b>Kratom (Mitragyna speciosa) has emerged as a widely accessible nonprescription substance that is being utilized in the United States. Kratom is commonly used for self-management of pain, psychiatric symptoms, and opioid withdrawal. Veterans receiving care within the Veterans Health Administration (VHA) represent a high-risk population due to elevated rates of chronic pain, post-traumatic stress disorder (PTSD), and substance use disorders (SUDs). Despite increasing prevalence, kratom use remains underrecognized and is not routinely assessed in clinical practice. This narrative review studies the pharmacology, patterns of use, and clinical implications of kratom among Veterans and proposes a standardized screening framework for implementation within the VHA. This will help to align with the patient centered care delivered to our Veterans related to mental health conditions often concurrent with substance use, pain management, and opioid safety. <b>Methods:</b> A targeted narrative review of the literature was conducted using PubMed, Google Scholar, and relevant federal agency reports. Search terms included “kratom,” “Mitragyna speciosa,” “substance use disorder,” “opioid withdrawal,” and “Veterans.” Articles were selected based on relevance to pharmacology, epidemiology, adverse effects, and clinical implications. Findings were synthesized and interpreted using DSM-5-TR substance use disorder criteria. <b>Results:</b> Kratom exhibits partial agonist activity at μ-opioid receptors, producing dose-dependent stimulant and opioid-like effects. According to the National Institutes of Health's National Library of Medicine, mu-opioid receptors, found in the brain and spinal cord, are primarily responsible for pain relief and other opioid-like effects such as euphoria and respiratory depression. Veterans frequently use kratom to self-manage pain, mood symptoms, and opioid withdrawal (Garcia-Romeu et al., 2020; Grundmann, 2017). Kratom use is associated with dependence, withdrawal, and increased risk of polysubstance use (Post et al., 2019). Detection remains limited due to lack of standardized screening tools and the absence of detection in routine toxicology panels. <b>Conclusions:</b> Given the rising incidence of kratom use among Veterans and associated clinical risks, implementation of a standardized screening within the VHA is an appropriate intervention. Incorporating DSM-5-TR-informed criteria into structured assessments can help improve early identification, enhance patient safety, and support evidence-based treatment strategies.

High-quality collaborative discourse is essential for deep learning in Problem-Based Learning (PBL). However, novice facilitators frequently struggle with topic drift, which occurs when discussions deviate from core learning objectives. Grounded in Cognitive Load Theory and instructional scaffolding, this paper analyzes the cognitive mechanisms behind topic drift in PBL. It identifies three typical deviation patterns: "Premature Resolution" (bypassing mechanistic deduction), "Detail Fixation" (over-engagement with peripheral details), and "Social Avoidance" (stemming from dysfunctional group dynamics). To address these patterns, this paper presents a literature-based facilitation guide offering specific intervention strategies and discursive prompts. These include mechanistic backtracking, metacognitive monitoring, and cognitive visualization. The study argues that effective pedagogical intervention relies on the strategic timing of facilitation rather than the immediate correction of factual errors. Ultimately, built on a foundation of relational trust, this process requires educators to shift their role from "epistemic authorities" to "cognitive coaches."

<b>Background:</b> 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. <b>Objective:</b> 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 &#x26; Initiation, (2) Policy &#x26; System Design, (3) Implementation &#x26; Operation, (4) Evaluation &#x26; Adaptation, (5) Consolidation &#x26; 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. <b>Results:</b> 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. <b>Conclusions:</b> 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.

Smallholder farmers play a pivotal role in global food security; however, they remain exceptionally vulnerable to the impacts of climate change due to their reliance on natural resources and limited adaptive capacities. This narrative review synthesizes a wide range of global sources to explore the intersection of smallholder agriculture and climate adaptation strategies. The review examines adaptation practices, agroecological methods, and the adoption of climate-resilient crop varieties. It reveals that the implementation of these strategies is frequently hindered by systemic barriers such as financial constraints, limited technological access, and institutional inefficiencies. Recognizing that previous studies have addressed isolated aspects of adaptation or relied on secondary data, this review highlights research gaps and offers a comprehensive synthesis of relevant literature. This review uses a narrative synthesis model suitable for integrating evidence from agronomy, economics, and social science to capture the complex challenges faced by smallholder farmers. The review emphasizes the importance of policy frameworks and participatory approaches that empower smallholder communities. This review synthesizes current evidence to inform potential directions for targeted interventions and future field-based studies, while recognizing the limitations of relying on secondary data. These recommendations aim to facilitate integrated policy reforms and drive research initiatives, ultimately strengthening the resilience and adaptability of smallholder agriculture in the face of ongoing climate change.

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.

<b>Background</b>: Type 2 Diabetes Mellitus (T2DM) and Alzheimer’s Disease (AD) are increasingly linked through shared pathophysiological mechanisms, giving rise to the concept of Type 3 Diabetes Mellitus (T3DM). Brain insulin resistance, oxidative stress, and neuroinflammation are central to both conditions, contributing to cognitive decline and AD progression. <b>Aim:</b> This review aims to explore this emerging relationship and its implications for prevention and management. <b>Methods</b>: Using an integrative review, 21 studies were systematically analyzed. The review focused on identifying demographic, genetic, and lifestyle factors contributing to T2DM and AD and examined shared molecular pathways such as insulin dysregulation and amyloid-beta accumulation. <b>Results</b>: The findings reveal that T3DM shares key features with T2DM and AD, including insulin resistance and chronic inflammation. Lifestyle interventions, such as diet and exercise, alongside routine cognitive and metabolic screenings, are critical in mitigating progression. <b>Conclusions</b>: Further research into diagnostic biomarkers and targeted therapies is essential to manage T3DM and its impact on AD. The role of nursing professionals in early detection, education, and holistic management is emphasized as vital in addressing this dual disease burden. This review offers actionable insights into integrated strategies for addressing these interconnected conditions.

Knee osteoarthritis (KOA) is a chronic degenerative joint disorder that significantly impairs mobility and quality of life. While surgical interventions such as total knee arthroplasty (TKA) are effective in severe cases, conservative treatments are critical for early and intermediate disease management. This review evaluates the efficacy, safety, and clinical applications of both conservative and surgical treatment approaches, including lifestyle modifications, physical therapy, pharmacological interventions, regenerative medicine, and surgical procedures. The integration of a multidisciplinary approach is emphasized as a key strategy for optimizing clinical outcomes and tailoring interventions to disease severity.

With an increasing diversity of learners in today’s educational set-ups, there is an insurmountable need to cater for individual differences including the cultural variations among learners. It is therefore necessary for educators to develop culturally responsive teaching that enhances intercultural competencies of learners. As educators strive to provide inclusive learning environments in which learners from diverse cultural backgrounds learn equitably, differentiated instruction becomes a practical tool. This paper explores how differentiated instruction can support and enhance culturally responsive teaching by examining how tailored instructional approaches can bridge cultural gaps and enhance educational outcomes. The aim is to provide a comprehensive understanding of how educators can effectively integrate differentiated instructional methodologies to achieve the goals of Culturally Responsive Teaching. The study used a descriptive survey design to determine the use of differentiated instruction by junior school teachers in Kenya and a systematic review of literature, practical examples, and studies on teachers’ practices in culturally responsive teaching. The study outcomes indicated that teachers used various differentiated instructional strategies with flexible grouping being the most commonly used strategy. However, there arises a concern, that teachers were not very familiar with cultural variations of learners in their classrooms even as they developed their differentiated instructional strategies. Literature provided the principles and practices of culturally responsive teaching. The combination of these results were used to formulate a conceptual framework for Culturally Responsive Differentiated Instruction (CRDI) that provides insights for practitioners to develop and implement culturally responsive differentiated instructional strategies. The study recommends that a framework to support teachers in the implementation of inclusive and equitable curriculum through CRDI be developed, CRDI be integrated into the teaching processes and the teachers be trained on providing for learner differences through CRDI.

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.

<b>Background</b>: 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). <b>Methods: </b>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. <b>Results:</b><b> </b>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. <b>Conclusion:</b><b> </b>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.

Access to and the availability of digital infrastructure remains the most significant issue influencing teachers' use of multimedia technology in teaching and learning processes. Qualitatively, the study focused on a case study research design. The study population consisted of five (5) Social Studies teachers at Presbyterian University College of Education Demonstration Junior High School in the Akuapem North Municipality of the Eastern Region of Ghana. A purposive sampling technique was used to select all the Social Studies teachers for the study. The main instruments for data collection were an interview guide and observation protocols. The data was analysed using the interpretative method based on the themes arrived at during the data collection. The themes were related to the research question and interpreted on the number of issues raised by participants. The study indicated that more resources are needed to use multimedia resources effectively in social studies instruction. Limited access to computers and the internet, unreliable power supply, time constraints for teachers, and a lack of necessary competencies all contribute to this challenge. Although multimedia has become crucial to education, teachers often need more training to utilise these resources fully. The government must collaborate with other organisations to procure ICT resources to address these challenges rather than shouldering the sole responsibility for financing education. Establishing a school-based ICT policy framework to guide technology implementation in teaching and learning is essential.

This study examines concord errors in academic writing among first-year students at Offinso College of Education in Ghana, aiming to identify common errors and propose remedial strategies for improvement. The population sample consists of first-year students at the college, reflecting a gender-sensitive distribution. The study adopts a mixed-methods research design, combining qualitative and quantitative analyses to explore the effects of concord errors on academic writing. Sampling techniques include purposive, quota sampling, and simple random sampling methods. Research instruments include questionnaires, interviews, and writing assessments to evaluate students' language skills. Data analysis involves identifying concord errors in students' writing and assessing the impact on their academic performance. The study concludes by recommending strategies to mitigate concord errors, such as targeted language practice, timely feedback, and awareness of grammatical conventions, to enhance students' writing proficiency and academic success.

A diagnosis of the current state of the crops is made regarding the control of weeds, use of pesticides, fungicides; with an assessment of the state of the plant covers in the crop, and its control by different types of herbicides, and we detected a high loss of biological diversity; and some of these compounds are mentioned due to their high toxicity. Similarly, the use of pesticides and fungicides is discussed due to their repercussions on health. In order to avoid the unhealthiness caused by the applications of these products, phytosanitary and educational control strategies are proposed; promoting the inspection of fruit and vegetable markets, and modifying the contents in higher professional and university education. To this end, we propose an active teaching methodology, through which the student acquires skills and responsibility for the use of chemical agents in agriculture, which serves to prevent the entry of these contaminants into the food chain. Of the different polluting chemical agents, in the case of herbicides we highlight Oxyfluorfen and Glyphosate with high toxicity and whose consumption is very high. In the case of pesticides and fungicides, among others are Organochlorine compounds, which have been detected in blood, and Carbon Tetrachloride and Chloroform, considered potent hepatotoxic and neurotoxic. The basic objective of this study is the awareness and acquisition of knowledge by future teachers about polluting agents, which will subsequently have an impact on society.

Machine learning operations (MLOps) comprises the practices, methods, and tooling that facilitate the deployment of reliable ML models in production environments. While many aspects of cloud data platforms are designed to enable reliability, only some managed ML services support the MLOps goals of continuous integration, continuous delivery, data lineage tracking, associated reproducibility, governance, and security. Furthermore, reliability encompasses not only the fulfillment of service-level objectives, but also systematic monitoring, alerting, and incident response automation. Architectural patterns are proposed to enable reliable deployment in cloud data platforms, focusing on the implementation of continuous integration and testing pipelines for ML models and the formulation of continuous delivery and rollout strategies. Continuous integration pipelines reduce the risk of regressions and ensure sufficient model performance at the time of deployment, while continuous delivery pipelines enable rapid updates to production models within acceptable risk profiles. The landscape of publicly available MLOps frameworks, tools, and services is also examined, emphasizing the pros and cons of established and rising solutions in containerization, orchestration, model serving, and inference. Containerization and orchestration contributes to the building of reliable deployment pipelines in cloud data platforms, whether general-purpose tools (e.g. Docker and Kubernetes) or solutions tailored for ML workloads. Containerized serving frameworks designed for high-throughput, low-latency inference can benefit a wide range of business applications, while auto-scaling and model versioning capabilities enhance the ease of use of cloud-native ML services.

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].

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.

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.

The purpose of this study was to examine coping strategies for managing the effects of work-family conflict on the management staff of hotels in the Accra metropolis of Ghana. The study adopted a 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. multi-stage sampling. The estimation of the sample size for the hotel managers was based on Krejcie and Morgan’s table for the determination of the sample size for a given population. The population of 100 managers were stratified and randomly sampled out of the 182 managers. The main instruments for data collection were questionnaires and an interview. Statistical Package for Social Sciences (SPSS) version 22.0 was used to determine simple percentages and frequencies of responses. Pearson product-moment Correlation and structural equation model were used to determine the consequences of work-family conflict as well as coping strategies adopted by managers. Amos PLS was used to determine the moderating effect of coping strategies on work-family conflict and job performance. Hotel managers in the Accra metropolis combine the strategies of structural role redefinition, personal role redefinition, cognitive restructuring and reactive role redefinition to curb work-family conflict. The study demonstrated a positive relationship between coping strategies and job performance. Coping strategies had a moderating effect on the relationship between work-family conflict and the job performance of hotel managers. Thus, to improve the job performance of hotel managers, there should be the application of coping interventions to help them perform on the job. The study also determined that work-family conflict had a significant positive relationship with job performance. Similarly, the study established that coping strategies significantly moderate the relationship between work-family conflict and job performance among hotel managers in the Accra metropolis. Although coping strategies were employed by hotel managers in the Accra metropolis, it is recommended that training sessions on the use of coping strategies and stress management techniques should be considered by management to address psychological and emotional work environment stressors since they have been proven to reduce stress and WFC. It is also recommended that there should be an inter-hotel collaboration to offer smaller hotels which do not have the resources some leverage the impact of work-family conflict. This platform can be provided by the Ghana hotels association to impact knowledge of coping strategies in smaller hotels. The government must be encouraged to liaise with the Ghana hotels association to enforce the mandatory eight-hour work per day to avoid overworking of hotel managers.

The global pharmaceutical supply chain plays a crucial role in ensuring the timely and safe delivery of medicines to patients worldwide. However, the increasing presence of counterfeit drugs within this supply chain poses a significant and growing risk to public health, patient safety, and the integrity of the pharmaceutical industry. Counterfeit drugs—medications that are fraudulently manufactured, mislabeled, or contain incorrect or harmful ingredients—are a major concern as they can lead to ineffective treatments, adverse health effects, and even death. Despite stringent regulatory frameworks and advanced technological solutions, counterfeit drugs continue to infiltrate legitimate supply chains due to factors such as the complexity of the distribution system, global trade practices, and inadequate enforcement in certain regions. This manuscript explores the primary causes behind the proliferation of counterfeit drugs in pharmaceutical distribution, the associated risks, and the multifaceted approaches required to address this growing threat. It discusses the importance of regulatory measures, including international cooperation and stronger compliance frameworks, as well as the role of emerging technologies like serialization, blockchain, and RFID in ensuring traceability and product authenticity. By focusing on the integration of these technologies, the paper also highlights the potential of innovative solutions to enhance transparency, reduce vulnerabilities, and protect the integrity of pharmaceutical supply chains. Additionally, it emphasizes the importance of public awareness campaigns and collaboration between key stakeholders, including pharmaceutical manufacturers, distributors, regulators, and healthcare providers, in creating a more secure and trustworthy pharmaceutical distribution ecosystem. Through a comprehensive exploration of these strategies, this manuscript aims to provide a roadmap for mitigating the risks posed by counterfeit drugs and ensuring the safety and efficacy of medicines for consumers worldwide.

This study was conducted with beans to determine a protocol that will help reduce the cooking time of beans. It was carried out in the Foods laboratory at the University for Development Studies, Department of Family and Consumer Sciences. A quasi-experimental design was the design tool employed for this study to establish a cause-and-effect relationship between an independent and dependent variable where the independent variable is cooking time and dependent variable is softness of the beans. An experiment was carried out to text the effect of 2 different treatments given to beans during cooking to ascertain which treatment is best for reducing the cooking time for bean. The treatments meted out were addition of blended onion, crushed cassava and no additives. Addition of blended onion had a very significant effect in reducing cooking time with cooking time of 43minutes. Cooking beans with crushed cassava also saw some reduction in the cooking time for beans with 46 minutes. Cooking dry beans with no additive having the highest cooking time (47minutes). With quantity of water, the dry beans sample with crushed cassava used more quantity of water (3.4 liters). Cooking with blended onion and with no treatment both used 2.9 litres per 100grams beans each. The study therefore recommends that crushed onions are added to help reduce the cooking time of dry beans.