“To Be Twice as Good to Get Half” is a common mindset among high aspiration and ambition Black individuals in the U.S., capturing the lived reality of Minorities’ Diminished Returns (MDRs). This paper explains that MDRs reflect how, even with high levels of ambition, self-efficacy, education, and income, Black individuals and other marginalized groups do not experience the same protective benefits for health and well-being as White populations. Systemic obstacles embedded within U.S. society weaken the expected returns on socioeconomic achievements for racialized individuals, creating a reality where “being twice as good” still results in lesser outcomes. High-SES Black individuals, for instance, continue to face significant risks for adverse outcomes, such as depression and chronic disease, due to structural inequities across domains like labor market discrimination, segregation, and accumulated disadvantage from childhood. Our analysis identifies key mechanisms—including interpersonal discrimination, lower-quality education, and structural racism in sectors like banking, policing, and real estate—that erode the protective effects of SES across racial lines. Mediating factors, such as chronic stress, allostatic load, and epigenetic changes over the life course, further compound these diminished returns, weakening the expected physical and mental health benefits. Drawing on extensive evidence from U.S. national and local datasets and corroborated by international studies, this paper underscores the necessity of policies that dismantle structural barriers rather than relying solely on SES improvements. Recommendations include implementing multi-sectoral policies, recognizing the unique challenges of middle-class non-White populations, and approaching policy with humility, acknowledging that achieving equity is a long-term endeavor. By challenging the “bootstraps” narrative, this paper advocates for structural interventions aimed at genuine health and economic equity for all racial and socioeconomic groups. While we provide an in-depth analysis of MDRs’ phenomena, mechanisms, mediators, and policy implications, the experience is often distilled as, “I have to be twice as good to get half.”

Background: Electronic cigarette (e-cigarette) use is increasingly prevalent among youth and young adults, particularly college and university students. This is a population for whom e-cigarette use is not recommended due to potential health risks, including nicotine addiction and long-term respiratory effects. Social networks play a crucial role in shaping attitudes toward e-cigarettes and influencing use behaviors. However, the relative influence of different social ties—parents, siblings, and friends—on e-cigarette attitudes and use remains unclear. Objective: This study utilizes data from the SMOKES study to compare the influence of e-cigarette use within different social network sections—parents, friends, and siblings—on personal e-cigarette attitudes and use among college and university students. Methods: Using a cross-sectional survey of college and university students, we examined the associations between e-cigarette use within different social networks and individual e-cigarette attitudes and use. Multivariate regression models assessed the strength of these associations, adjusting for key demographic and behavioral covariates. Results: Findings indicate that among college and university students, the strongest influence on both e-cigarette attitudes and use comes from friends who use e-cigarettes. In contrast, parental and sibling e-cigarette use showed weak or non-significant effects. These results suggest that peer influence, rather than family influence, plays a dominant role in shaping e-cigarette-related behaviors and perceptions in young adults. Conclusion: This study underscores the importance of peer influence in e-cigarette uptake and attitudes among college and university students. Public health interventions aimed at reducing e-cigarette use in this population should consider targeting peer networks rather than focusing solely on family-based influences.

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.

Background: Tobacco control policies are implemented globally to reduce tobacco-related morbidity and mortality. Emerging evidence suggests that individual tobacco use may influence the level of support for these policies. However, the extent to which personal use affects policy endorsement remains underexplored, particularly among young adults in academic settings. Aims: This study aimed to examine whether college students who use tobacco exhibit lower support for tobacco control policies compared to their non-user counterparts. Methods: We conducted a multi-center, cross-sectional study involving 2403 college students from various provinces in Iran. Tobacco use was ascertained based on self-reported consumption of cigarettes, electronic cigarettes, and hookah. Attitudes toward tobacco control policies were evaluated using a structured survey instrument, and comparative analyses were performed to assess differences in policy support between tobacco users and non-users. Results: The analysis revealed that tobacco users demonstrated significantly lower support for tobacco control policies compared to non-users. This association was consistently observed across users of cigarettes, electronic cigarettes, and hookah, suggesting a systematic pattern irrespective of the type of tobacco product used. Conclusion: These findings indicated a clear association between tobacco use and reduced endorsement of tobacco control policies among Iranian college students. These results have potential implications for public health policy, emphasizing the importance of addressing individual tobacco use behaviors in the development and implementation of tobacco control strategies. Further research is needed to elucidate the underlying mechanisms of this relationship.

Background: Tobacco use remains a major global health concern, and understanding the factors that influence tobacco-related knowledge and support for tobacco control policies is critical for effective development of tobacco control policies that are accepted by the public. Objectives: This study introduces the rationale, design, methodology, and participants of the SMOKES Study (Study of Measurement of Knowledge and Examination of Support for tobacco control policies), which is conducted to evaluate tobacco use, tobacco-related knowledge and attitude, as well as support for tobacco control policies among college and university students. Methods: The SMOKES Study was designed to address significant gaps in literature by focusing on college and university students in a non-Western context. A multi-center, cross-sectional design was employed to collect data from a diverse sample of college and university students across different geographical provinces in Iran. The survey instrument incorporated a range of measures covering socio-demographic characteristics, university-related variables, family tobacco use status, personal tobacco consumption behaviors (including detailed assessments of cigarette, hookah, and electronic cigarette use), and attitudinal as well as knowledge-based assessments related to vaping. Support for tobacco control policies is also measured. Data were collected using an online survey that included self-administered questionnaires, enabling access to a large diverse sample. This study may be used to determine the prevalence of ever and current use of cigarettes, electronic cigarettes, and hookah, as well as examining the correlates of single, dual, and poly-tobacco use. The study also aims to assess the role of social determinants, attitudes, and ethnic/geographic differences in shaping these outcomes. Results: The study sample consisted of 2403 college and university students, including undergraduates enrolled in different academic programs from all faculties and disciplines. Participants were drawn from universities across 15 provinces, and 11 ethnic groups, ensuring a heterogeneous sample with respect to socio-demographic background, ethnicity, and institutional affiliation. This diversity enhances the generalizability of the findings and allows for the exploration of subgroup differences in tobacco use patterns and policy support. Conclusions: The SMOKES Study offers a framework for examining tobacco-related knowledge and the acceptability of tobacco control policies among a key part of the population, being college and university students. By providing detailed insights into the prevalence and correlates of tobacco knowledge, attitude, use, as well as the tobacco control policy support, the study lays the groundwork for tailored public health interventions and more effective tobacco regulation strategies particularly for college campuses in a non-Western setting.

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

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

The study aimed to examine the availability of protective clothing and its usage among workers at the University of Cape Coast in the central region of Ghana. It used the Accident-Proneness Theory and the Theory of Reasoned Action to achieve the study's objectives. The study adopted the positivist research paradigm. The study used a descriptive design with mixed methods. The study population comprised all workers and supervisors whose work demands the use of protective clothing at the University of Cape Coast. The study used multistage sampling techniques (stratified, purposive, proportional and Systematic random sampling techniques) to select one hundred and ninety-six departmental workers and five (5) supervisors in the University. The main instruments for data collection were a Semi-structured questionnaire and an unstructured interview guide. Mean and standard deviation, frequency count, and percentages were used to analyse the quantitative data. The qualitative data was analysed through the development of data categories and themes. The study concluded that “not all the protective clothing for the various departments were available. The University ensured that workers used what was in stock at the department. The protective clothing supplied to the various departments was insufficient, so their continuous use of the existing ones got them defaced, bringing about shortages. The study also revealed that workers used protective clothing most often, but not all used it because safety laws were relaxed. The study recommended that the University ensure a regular and adequate supply of PPC, insist on its usage, and enforce the use of PPC by all workers whose work demands it.

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.

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

Background: In the landscape of education, the decision-making process that leads students to pursue or reject nursing as a career is a multifaceted phenomenon shaped by a plethora of influences ranging from personal experiences to societal norms. Aim: To explore non-nursing students' insights on nursing education, seeking to shed light on the considerations and challenges that influence their views on nursing education. Materials & Methods: A qualitative approach using thematic analysis were utilized. Lincoln and Guba's framework for rigor and trustworthiness directed the validation process. Semi-structured interviews based on vetted questionnaires yielded the data. Results: Analysis of interviews with ten (10) non-nursing college students revealed three key themes: 1) initial insights, 2) factors influencing their insights, and 3) difficulty of nursing education. Non-nursing students view nursing education as multifaceted and rigorous, recognizing the profession's complexity but have reservations about the heavy workload, intense clinical demands, and health risks, particularly highlighted by the pandemic, which contributes to their reluctance to choose nursing as a career path. Implications: Addressing perceptions, enhancing curricula, offering mentorship, and providing emotional support, nursing education can be improved, steering more students towards a career in nursing. Conclusion: Non-nursing students respect the complexity of the nursing profession but are deterred by its demands and risks, indicating a need for educational reforms to better convey the role, value, and opportunities within nursing to encourage more students into the field.

The thrust of this paper is to delve into the cohesive devices of political discourse as it pertains to Nelson Mandela‘s I Am the First Accused. The text was codified and the lexico-grammatical resources were examined in terms of semantic ties through the lens of Discourse analysis. The text was analysed based on Halliday and Hasan’s, 1976 five major cohesion classification categories: reference, demonstrative references, substitution, conjunction and lexical cohesion. The research indicated that there were sufficient phenomenon-example relationships within the text. In other words, there was adequate justification for claim statements within the text. There are also adequate cause-consequential relations in the text. Anaphoric references were commonplace in the text. It was also found out that cataphoric reference was sparingly used in the text. Analysis of the data also revealed that there were 30 instances of personal references, 21 demonstrative references, 3 instances of comparative references, and 6 instances of substitution. There were no instances of ellipsis. There were 7 instances of conjunction as a semantic link. There were 15 instances of repetition, 5 examples of synonyms and 3 instances of antonyms. It is recommended that public speakers and media practitioners take cognisance of cohesive devices and make their write-ups and speeches more cohesive and coherent for their audience and readers to decode meaning. Teachers of English as a second language should give serious attention to the teaching of cohesion as a semantic link within a text since cohesion and coherence aid the readability of a text. Cataphoric references sustain the interest of listeners and readers since they expect information yet to be given. Therefore, it is recommended that teachers of English as a second language should encourage their students to use some cataphors in their essays to create some kind of suspense in their readers. Critical Discourse Analysis (CDA) could also be used as an analytical tool to examine how power plays within the text.

Working on developing geometric coordinates with a special case - in the interest of human engineering - to fit with the humanities or with the famous psychological tests such as the Herman Brain Dominance Instrument Test, which is abbreviated as HBDI, or the Personal Compass test, which is abbreviated as (P.C).

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.

Oncology nurses are more likely to get compassion fatigue (CF) than nurses in other fields because of the emotional stress and poor outlook of cancer patients. Because of this, the care might not be very good, the job might not be very satisfying, and there is a good chance that the patient's pain won't be noticed. Aim. To synthesize empirical evidence on compassion fatigue in order to extract the common, central, and fundamental elements that may improve nursing care. Design. An integrative review Results. Fifteen (15) studies met the eligibility criteria wherein five themes emerged. These are the level of compassion fatigue among oncology nurses, the oncology nurses' perspectives on compassion fatigue, precipitating factors leading to CF with 2 subthemes (work environment and a feeling of lack of support), the influence of compassion fatigue on the personal lives and general well-being of cancer nurses, and the consequences on the quality of oncology nurses' professional lives at work. Conclusion. CF is a significant problem for nurses who work in specialized areas such as cancer units, demonstrated as a basic incapacity to nurture others. The integration of studies provides evidence of clinical practice application which can provide better outcomes and improve nursing care. Implications for Practice. The findings provide understanding into healthcare practice on how to avoid compassion fatigue. Clinical management approaches that can mitigate compassion fatigue and its negative repercussions are presented, as well as the formation of peer support groups that have the ability to ameliorate CF.

The social aspect of education is an important part of the learning process. In this study two research questions were asked to explore this idea. Social network analysis provided multiple measures of AP Physics 1 students’ network centrality. These measures were used to predict physics achievement. Further, survey results measuring extroversion (EPI, alpha=.84-.94), motivation (PGOS, alpha=.64-.83), and self-efficacy (SOSESC, alpha=.94) were used to determine students’ personality characteristics. These personality results were used as moderators for the moderation analysis. The sample consisted of 106 students from a large, Midwestern, suburban high school taking AP Physics 1. Numerous centrality measures significantly correlated with physics achievement. Extroversion and self-efficacy increased the effect of centrality in most cases, whereas motivation did not change the centrality-achievement relationship. In most cases, having many, high quality connections was beneficial to learning physics, but personality characteristics must also be included in pedagogical decisions. Based on the results, teachers are strongly advised to account for personality and student connections when forming groups.

This study aimed to assess the validity and reliability of the dark personality instrument in students of general physical education units of Mashhad universities. The participants include all students of Ferdowsi, Imam Reza, Islamic Azad, and Payame Noor universities who had chosen the units of general physical education and sport in the academic year of 2021-22, using the Morgan table, 196 people were randomly selected as a sample. A standard dark personality questionnaire (Jonason & Webster, 2010) was used to collect data. Cronbach's alpha test was used to confirm the reliability of the questionnaire. To confirm the instrument's validity, exploratory and confirmatory factor analyses were used. Data analysis showed that the factor load of all items is higher than the baseline value (0.4) and the research model has a significant fit. Also, the model fit indices had acceptable values. Finally, it is recommended to sports coaches and teachers of physical education classes and leisure time to use this scale at the beginning of each semester to get to know more about the personality characteristics of students in their class and to measure these people, this can help them a lot in how to manage their classes.

One of the current issues facing humanity is ensuring sustained global food security in the face of devastating effects of climate change; this challenge is particularly pressing on the African continent. Here, I present an opinion piece identifying local animal genetic resources as "African leverage point" that provide the highest chances to cushion rural fork to climate change, enhance environmental sustainability and food security in Africa. When it comes to boosting food production, coping with climate change, or bolstering the delivery of a wide range of ecosystem services, I believe that African animal genetic resources are essential alternatives for the sustainable growth of the livestock industry and its contribution to food security. Africa needs to address the support and development of indigenous animal genetic resources in order to meet the basic food needs of more than 1 billion people, address numerous environmental issues with continental implications, and focus on more effective and resilient food systems with the greatest impact on food security. The indigenous animal resources diversity and support actions to this unique group could provide a boost in protein that is lacking to constitute healthy diets in Africa. The priorities of nonprofit organizations, foundations, governments, citizens' groups, and companies can be influenced by this leverage point in the African food system. Due to continuous food insecurity, which appears to be becoming worse with climate change and makes it even harder to accomplish the SDGs on the continent, Africa has paid a hefty price for being misled about the worth of its own animal genetic resources. To the contrary, it is highly improbable that a strategy to improve food security and rural livelihoods that undermines the utilization of indigenous animal genetic resources will be viable in long-term. If Africa makes an effort, is committed, and fully commits resources to putting indigenous animal genetic resources at the forefront of combating food insecurity and accelerating the achievement of SDGs, it can achieve more under the adverse prevailing climate change induce environmental conditions. Our personal opinion is that we would not have had the ongoing food problems, even in the face of climate change, if Africa had over the years implemented the necessary mechanisms to develop and promote local animal genetic resources. What lies ahead in terms of climate change effect on food security in Africa is anyone's guess – but whatever it is, promoting continental adapted indigenous animal genetic resources portfolio is ready to handle it. Development and promotion of African animal genetic resources should be part of a continental strategy to transform smallholder animal production by 2050, in line with the goals of achieving the SGDs, to improve rural household food security, and bringing rural economy prosperity, resilience, sustainability, and all other desired animal related food outcomes for rural healthy diets. African animal genetic resources are the most important but underutilized resource to address the issue of ongoing food insecurity. The responsible use of local animal genetic resources through climate smart animal husbandry practices also contributes to food security, rural development and increased employment opportunities. African genetic improvement programs involving indigenous animal genetic resources must be considered as regards to local agriculture and livestock development aspirations, appropriateness to local reality and livelihood security, as well as environmental friendliness. Animal agriculture will fill in the enormous gaps in the continent's food supply if this animal group receives adequate attention and is used integrated properly in crop and livestock systems which characterize smallholder farming sector in Africa. Because they have evolved over time to accommodate the various climatic conditions and environmental pressures on the continent, Africa's native animal genetic resources are particularly resilient. Indirectly, the impact of climate change offers a chance to use native animal genetics from Africa. The use of local animal genetic diversity has the potential to substantially improve Africa's food security landscape hence should be given special consideration for sociocultural, environmental, and economic aspects, and with regard for smallholder farmer-specific factors of interest. African animal genetic resources have contributed significantly to the food and nutrition security aspects of the millions of people in their communities of origin and custody in Africa. The purpose of the perception piece is to educate the reader about the fundamental mechanisms that control the use of continental animal genetic resources and how the outlook for these mechanisms can be manipulated in the future for the benefit of improving food security in Africa. The discussion provides in-depth insight into the pertinent literature in understanding the significance of local animal genetic resources in terms of their contribution to food security in Africa.

Police work is mentally demanding and stressful, which takes a heavy toll on the health of police personnel. This study was conducted to assess the eating pattern, physical activity and nutritional status of police personnel in the Tamale Metropolis. A cross-sectional research design was adopted for the study. The population of this study involved all the 1590 police personnel with two years working experience within the Tamale Metropolis in the Northern Region of Ghana. Simple random sampling technique was used to select three hundred and eighty-four (384) respondents for the study. The main instrument for data collection was questionnaire. Data were analyzed using Statistical Package for Social Sciences (SPSS) version 21.0. Chi-square and Fisher’s exact tests were used to test associations. Logistic modeling was used to test the strength of the associations. P<0.05 was used to denote significance. The study revealed that the police eat two main meals, skip breakfast or eat in between meals, consume alcohol, ate foods belonging to the meat, soft drinks, fish, grain and eggs groups and their diet were more moderately diverse. The study also concluded the police personnel had normal BMI while was overweight and obese respectively. It is recommended that the police department should institute health education programs on the benefits of good dietary practices to achieve optimal health, to avoid the practice of police eating two main meals, skipping breakfast, consuming more alcohol but rather consumes diet that is moderately diverse to sustain him or her. It is also recommended that police department should institute a health education and screening exercise policy to examine the personals periodically to warrant their good health in the service.

The rapid spread of COVID 19 outbreak has put a heavy burden on human society and is a great challenge for health care workers. The present study aims to assess the perceptions of nursing personnel regarding challenges in usage of PPE during COVID 19 pandemic and to find out the association between severity of physical symptoms and selected personal variables of nursing personnel. A quantitative approach with descriptive survey research design was used for the study. Web based self-administered questionnaire, rating scale and checklist were developed and distributed among study participants in the “Google forms”. A total of 134 participants were included in the study. Out of the 134 participants, 85(63.4%) nursing personnel were working in the government sector and 49(36.6%) of nursing personnel were working in the private sector. The top five challenges in the usage of PPE ranked based on self-reported data were; 1. difficulty to meet the basic needs such as food and fluids, 2. difficulty to meet elimination needs, 3. Unable to relax, 4. difficulty to meet hygienic needs and 5. disconnected with friends and family during working hours. Analysis of physical symptoms experienced by the nursing personnel showed that 41(30.6%) had mild symptoms, 54(40.3%) had moderate symptoms and 39(29.1%) had severe symptoms experienced owing to PPE usage. The most common physical symptoms reported by nurses were heat stress 124(92.5%), head ache 120(89.6%), exhaustion 117(87.3%) and dryness in throat (86.6%). There were no significant association between physical symptoms of nursing personnel and selected personal variables at 0.05 level of significance.

The purpose of the study was to examine the use of rewards and punishment to improve discipline in Yiadom Boakye Demonstration Junior High School students (JHS) in Berekum of Ghana. A qualitative approach was adopted for the study. A case study research design was used to analyse the study. The population for the study consisted of all the eight (8) teachers in the Yiadom Boakye Demonstration Junior High School (JHS). A purposive sampling technique was used to select the eight teachers and school for the study. The main instrument used for the study was an interview. The study concluded that rewards and punishment lead to a change in the behaviours of the students affecting their academic performance their courses. The study also concluded that reward policies are needed in teaching to improve student learning by fostering enthusiasm in learning; it arouses students’ interest in learning, and change their personality traits and posture in class. The study revealed that a good punishment minimises bad behaviour, once is not having any bases on the student academic life, then it will not worsen the plight of his or her academic life. It is recommended that the colleges of education in Ghana should collaborate with Ghana Education Service and National Teaching Council to organise workshops and seminars on the use of rewards and punishments in the classroom situation.

Most people can't subscribe to every direct-to-consumer platform today, and the number is growing. The platform's content and the user's experience influence the decision to subscribe or buy. Today's consumers anticipate instantaneously curated content exploration, acquisition, and consumption. Media firms actively seek to increase both click-through rate and profitability by enhancing the user experience and enticing customers to subscribe or buy premium content through recommender systems. The direct-to-consumer platforms may maintain user engagement after consumers have visited the contents by providing suggestions that make the most of the site's rich content catalogs. By bringing it to the attention of viewers based on their viewing habits, for instance, effective recommendation systems might boost earnings for underappreciated "long tail" content. This research explores various recommender system types currently in widespread usage with an analysis of some of the fascinating breakthroughs.

Caesarean section is the most common surgical procedure in obstetrics, but also in pregnant women with dystocia. The purpose of this study is to identify factors that contribute to post-caesarean complications in emergency of gynecology-obstetrics service of Saint Joseph Hospital in Kinshasa. This is a descriptive cross-sectional study and was conducted at Saint Joseph Hospital in Kinshasa city for a month (1^st and 30^th July 2021). A questionnaire was used to collect different data namely socio-demographic characteristics and different variables important for the study. Independent variables were factors related to the parturient and the current pregnancy, the surgical procedure and the operational room. While the dependent variable was post-caesarean complications in gynecology-obstetrics service. Descriptive statistical analyses namely frequency and percentage were done to describe the sample profile. To measure the strength of association between different variables were estimated using Pearson's Chi-Square (X²) test and the p-value was 0.05. Data analysis was performed using SPSS version 20 software. The majority of participants are over 33 years of age, have secondary school skills, married and have 3 to 4 children. It was observed that 88.2% of participants have acute respiratory distress prior to caesarean section, 76.6% have a personal history of thromboembolic disease prior to caesarean section. All the participants who underwent caesarean section were victims of external ventilation through the windows of the operating room, which remained open before, during and after the surgery and benefited from antibiotic treatment without any para-clinical analysis before the caesarean section. Furthermore, 82.4% of participants had benefited from the caesarean section with sterilized care materials 48 hours before and after the intervention. While 47.1% of participants had caesarean sections with defective equipment for the operation (use of dry heat sterilization etc.). A better identification of these risk factors can reduce significantly rate of complications and can consequently improve the maternal-infantile prognosis. The obstacles to effective management are related to the provision of quality services.

Resistance exercise is the performance of physical exercises designed to improve strength, muscular, endurance, hypertrophy, and neuromuscular efficiency with the use of weights (Braith & Stewart, 2006)[1]. Resistance exercise has long been utilized for its beneficial health qualities and propensity to elicit certain desired physiological changes (Fry, 2004)[2]. There has been a recent, and significant, increase in resistance exercise activity in American adults (NCHS, 2018)[3] attributable to factors such as autonomous compulsion and self fulfilment to extrinsic factors like health and physical appearance (Fisher et al., 2017; Heinrich et al., 2014; Ingledew & Markland, 2008)[4,5,6]. As such, there is an ever-increasing need for educational material regarding resistance exercise, its benefits, purpose, and manner in which it should be conducted. Purpose- to (a) provide resistance exercise-based educational material regarding the background and rationale behind resistance training; (b) to provide a specific resistance-based exercise program to elicit strength gain; (c) to provide individuals with the knowledge to safely and effectively engage in said program; and (d) to provide the participant with expected physiological adaptations to completing the program. Methods- Two 6-week, 5-day per week resistance exercise programs – with a brief nutritional guide accompaniment – are outlined for a hypothetical participant, age 25-40, of moderate experience with fitness training, and with the goal of strength gain and moderate fat loss as a secondary goal. Results- Anticipated benefits of the program include: increased maximal strength caused by training above 85% 1RM for 2-6 sets of 1-6 reps; increased synergistic muscle groups strength which will contribute to improved prime mover strength; hypertrophy of skeletal muscles throughout the body, induced by lifts of 67-85% 1 rep max (RM) for 3-6 sets of 6-12 reps and increased resting energy expenditure (basal metabolic rate) accompanied by improved body composition. Conclusion- Continued progression though this protocol with modifications to resistance include potential improved running speed, explosive power potential, and other anaerobic sport performance factors, as well as enhanced neuromuscular efficiency associated with increased prime mover force production capabilities.

The purpose of the study was to examine the interactional linguistic resources in concession speeches of Selected Political Leaders in Ghana and the United States of America. The past three decades have witnessed an increasing scholarly interest in political discourse. Despite this, concession speeches have received limited scholarly attention. This study, therefore, comparatively analyzed the concession speeches delivered by John Dramani Mahama and Nana Addo Danquah Akuffo-Addo of Ghana and Hillary Clinton and Al Gore of the United States of America. Speech Act and Metadiscourse Interactionist Theories were used to examine the interpersonal linguistic resources found in the speeches. The speeches, were analyzed qualitatively. The study concluded that speakers of CSs in the two different cultural contexts use similar statements, as has already been discussed earlier in this study. For instance, the four losing candidates used almost the same interpersonal linguistic resources (hedges, boosters, self-mention, attitude markers, and engagement markers) to establish a bond between them and their interlocutors and supporters. It is recommended that, concession speeches (CSs) to be studied from other theoretical perspectives, this will allow for a detailed analysis of a wider range of linguistic resources such as noun phrases, verb phrases, and the use of adjuncts, beyond the SAs in CSs in order not to treat them as mere rhetoric in politics.

The impact of narcissism and self-esteem on academic achievement has long been an important issue in developmental research. The study aimed to explore the students’ narcissism and self-esteem as correlates of academic achievement in Mathematics in Anambra State. Five research questions and five null hypotheses guided the study. The study adopted a correlational approach. The population of the study comprised of 21204 SS2 students from which a sample of 630 was drawn. Multi-stage procedure was used to select the sample. Two standardized research instruments namely; Narcissistic Personality Inventory (NPI), and Self-esteem Questionnaire (SQ), as well as score from students’ promotional examination were used for data collection. Cronbach’s alpha was used to determine the reliability of the items in the instruments. The overall reliability coefficient was 0.75 which shows that the instrument was reliable and good for the study. The Pearson Product Moment Correlation was used to answer research questions 1 to 4 and to test hypotheses 1 to 4, while the research question 5 and hypothesis 5 were answered and tested with multiple correlations. The findings showed that students’ power narcissism recorded a very low positive relationship with academic achievement in mathematics. Findings also revealed that the multiple correlation of these variables is positively non significant with academic achievement in mathematics. Based on these findings, it was recommended that as narcissistic individuals believe strongly that they are better than others, teachers and counsellors should develop a strategy to enhance the confidence and ability in the students as these will help them to become life long learning individuals thereafter.

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

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

There is a growing body of evidence that the number of individuals suffering from chronic and acute pain is under-reported and the burden of the veteran, aging, athletic, and working populations is rising. Current pain management is limited by our capacity to collaborate with individuals continuing normal daily functions and self-administration of pain treatments outside of traditional healthcare appointments and hospital settings. In this review, the current gap in clinical care for real-time feedback and guidance with pain management decision-making for chronic and post-operative pain treatment is defined. We examine the recent and future applications for predictive analytics of opioid use after surgery and implementing real-time neural networks for personalized pain management goal setting for particular individuals on the path to discharge to normal function. Integration of personalized neural networks with longitudinal data may enable the development of future treatment personalizations paired with electrical simulations.

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

In today's fast-changing world, digital has become a way of life in every single field, and it is affecting all industries by providing multi-channel connectivity with people. In the banking industry, moving to the digital age allows for more improvements in customer-related operations and transaction-related operations within a day. These studies are from the perspective of customers. Customers prefer the flexibility of using digital financial services. Banking clients are commonly given technology-related services, whether they are online or not. Now, banks are focused on providing instant credit card issuance and personalized financial solution services to their clients. They are responsible for managing mass affluent clients who conduct transactions approximately the same as mass retail clients. Providing personalized services on time to individual end users will significantly enhance customer value with the banks. Customers who use the bank digitally perform more operations than those who go to the branch. Thus, they become more valuable clients for the banks. This strategic approach to the digitization process takes place in this fast-changing environment, and the major steps of this journey will be explained in the next chapters [1].

Neural networks are bringing a transformation in wearable healthcare technology analytics. These networks are able to analyze a vast amount of data to help in making decisions concerning patient care. Advancements in deep learning have brought neural networks to the forefront, making data analytics a straightforward process. This study will help in unveiling the use of ICT and AI in medical healthcare technology, crawling through some industry giants. Wearable Healthcare Technologies are becoming more popular every day. These technologies facilitate collecting, monitoring, and sharing every vital aspect of the human body necessary for diagnosing and treating an ailment. At the advent of global digitization, health data storage and systematic analysis are taking shape to ensure better diagnostics, preventive, and predictive healthcare. Healthcare analytics powered by neural networks can significantly improve health outcomes, maximizing individuals' potential and quality of life. The breadth and possibilities of connected devices are getting wider. From personal activity monitoring to quantifying every bit of health statistics, connected devices are making an impact in measurement, management, and manipulation. In healthcare, early diagnosis could be a lifesaver. Data analytics can help in a big way to make moves and predictions to save lives. We are in another phase of the digitization era, "Neural Network and Wearable Healthcare Technology Analytics." A neural network could be conceived as an adaptive system made up of a large number of neurons connected in multiple layers. A neural network processes data in a similar way as the human brain does. Using a collection of algorithms, for many neural networks, objects are composed of 'input' and 'output' layers along with the layers of the neural network.

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

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

This paper includes the impacts of the Internet of Things (IoT), Big Data, and other emerging technologies in the vehicle production sector, digital connectivity, and sustainable transport system. Automated and intelligent transportation for safe, efficient, and sustainable transport systems will be stressed. Key factors to promote automated or connected vehicles including connected environment, integration of all transport modes, advanced cooperative systems, and policy enforcement will be discussed. This paper contains the Axiomatic Categorisation Framework (AFS) for the dynamic alignment in a collection of disparate functions in cyber-physical systems (CPS). Developed system is enhanced for breaking the rules within autonomous vehicles (AV). It means the human personal injury is inevitable while the vehicle does not do any rules. Especially in complicated traffic situations, many of the constraints are mutually exclusive, and there is no way to obey all of them at a time. Also, there is no way to ensure that the self-driving vehicle has priority in all situations [1]. Public distrust in AV systems has to be increased and the investment in this technology has to slow down. Instead, a human driver should be partially responsible for operation. The development of a driver-behavior assistant (DBA) system is proposed, which should be able to break the rules for the distances of such slow development. It is intended to be effective in non-deterministic situations while maintaining the safety of the AV and those involved in the event. A driver's actions would not only be acceptable as a driving strategy but also would be predictable, and therefore other road users could unambiguously react.

This study aims to achieve a new understanding of how, why, and when consumer behavior is shaped, enacted, and experienced inside and across integrated digital ecosystems related to large-scale trackable goods, all in service of helping marketers optimize their business performance in the new economy. The pioneering understanding begins by exploring what motivates the choices of a homogeneous group of consumers to organize their consumption of national and store brand varieties of consumer package goods in a certain manner. Thereafter, the essay explores how, if at all, the other digital activities of consumers across various product-related digital spaces and on various platforms build expertise and interest in these products such that they exert an effect on the purchase choices for these products. The essay then advances to asking how online information seeking, in various product-related digital spaces, on various platforms, and from various sources, and taking place at various points in the purchase journey affects online-offline dynamics in purchasing these products. Thereafter, the research examines how paid digital communication in various product-related digital spheres and forms, enabled by consumer advertising engagement on various platforms, boosts the offline sales of these products. Finally, by employing a new methodology that combines consumer scanning data, self-reported online activity data, and transaction data collected from an ad-tech partner, the research presents a fresh set of marketing action levers and performance outcomes on chosen products. Along the way, progress is made on four under-investigated topics in the advertising literature – the role of consumer actors and their expertise in the online-offline purchasing dynamics for ads, advertising engagement, consumer digital spaces, and consumer digital activity investment.