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Background: The use of a Geographic Information System in identifying meningitis hotspots in the Upper West Region (UWR) remains underutilized, making spatial targeting of meningitis hotspots difficult. We therefore utilized surveillance data enabled with GIS technology to target meningitis outbreaks in the UWR. Methods: Secondary data analysis was conducted in the study. The dynamics of bacterial meningitis in space and time were studied using epidemiological data from 2018 to 2020. Spot map and choropleths were used to depict the distribution of cases in the region. Moran's I statistics were used to assess spatial autocorrelation. Getis-Ord Gi*(d) and Anselin Local Moran’s statistics were used to identify hotspots and spatial outliers within the study area. A Geographic Weighted Regression model was also used to examine how socio bio-climatic conditions influence the spread of meningitis. Results: There were 1176 cases of bacterial meningitis, 118 deaths, and 1058 survivors between 2018 and 2020. Nandom municipality had the highest Attack Rate (AR) at 492/100,000 persons, followed by Nadowli-Kaleo district at 314/100,000 persons. Jirapa had the highest case fatality rate (CFR) at 17%. The spatio-temporal analysis showed spatial diffusion of meningitis prevalence from the western half of the UWR to the east with a significant number of hotpots and cluster outliers. Conclusion: Bacterial meningitis does not occur at random. Populations (10.9%) under sub-districts identified as hotspots are exceptionally at higher risk of outbreaks. Targeted interventions should be directed towards clustered hotspots, focusing on zones with low prevalence fenced off by high prevalence zones.

In the ever-changing sector of education, the use of technology has become critical to innovation and increased learning opportunities. This research illustrates the intricate connections that exist between augmented reality [AR] and tremendous educational attributes, thinking about how AR might modify conventional teaching approaches. The important motive is to offer an entire knowledge of how augmented fact influences crucial areas of the educational revel in. Utilizing a quantitative studies method, the study seems at how AR impacts pupil behavior, creativity, and instructional practices, in addition to the mediating and moderating elements that influence these relationships. An online questionnaire was used to collect data from 444 random samples. The relationships between AR, teacher competence, technology acceptance, and educational outcomes were examined. Data shows that augmented reality has a positive effect on creativity, student behavior, and teaching strategies. Teacher competence moderated these relationships, highlighting the critical role of teachers in successfully integrating augmented reality, while technology acceptance emerged as a significant mediator demonstrating the significance of user perceptions. This study has critical implications for educators, administrators, and policymakers interested in using AR to improve instructional development, as well as for the field of generation-infused schooling administration. Additionally, it advances theoretical frameworks through a better understanding of the complicated tactics that impact the uptake and acceptability of AR.

Abstract Coastal cities are at the frontlines of climate change impacts, resulting in an urgent need for substantial adaptation. To understand whether and to what extent cities are on track to prepare for climate risks, this paper systematically assesses the academic literature to evaluate climate change adaptation in 199 coastal cities worldwide. We show that adaptation in coastal cities is rather slow, of narrow scope, and not transformative. Adaptation measures are predominantly designed based on past and current, rather than future, patterns in hazards, exposure, and vulnerability. City governments, particularly in high-income countries, are more likely to implement institutional and infrastructural responses, while coastal cities in lower-middle income countries often rely on households to implement behavioral adaptation. There is comparatively little published knowledge on coastal urban adaptation in low and middle income economies and regarding particular adaptation types such as ecosystem-based adaptation. These insights make an important contribution for tracking adaptation progress globally and help to identify entry points for improving adaption of coastal cities in the future.

The rock slope stability analysis can be performed using deterministic and probabilistic approaches. The deterministic analysis based on the safety concept factor uses fixed representative values for each input parameter involved without considering the variability and uncertainty of the rock mass properties. Probabilistic analysis with the calculation of probability of failure instead of the factor of safety against failure is emerging in practice. Such analyses offer a more rational approach to quantify risk by incorporating uncertainty in the input variables and evaluating the probability of the failure of a system. In rock slope engineering, uncertainty and variability involve a large scatter of geo-structural data and varied geomechanical test results. There has been extensive reliability analysis of rock slope stability in the literature, and different methods of reliability are being employed for assessment of the probability of failure and the reliability of a slope. Probabilistic approaches include Monte Carlo simulation (MCS), the point estimate method (PEM), the response surface method (RSM), first- and second-order reliability methods (FORMs and SORMs), and the first-order second-moment method (FOSM). Although these methods may be complicated, they provide a more complete definition of risk. Probabilistic slope stability analysis is an option in most commercial software; however, the use of this method is not common in practice. This paper provides an overview of the literature on some of the main probabilistic reliability-based methods available for the design of the rock slope in open pit mining. To demonstrate its applicability, the paper investigates the stability of a rock slope in an open pit mine in the Goldfields region, Western Australia. Two different approaches were adopted: deterministic stability analysis using two-dimensional limit equilibrium and finite element shear strength reduction methods using SLIDE and RS2 software, respectively, and probabilistic analysis by applying the MCS and RSM methods in the limit equilibrium method. In this example, the slope stability analysis was performed using the Spencer method with Cuckoo search optimization to locate the critical slip surface. The results obtained were compared and commented on.

Automated Machine Learning (AutoML) tools are revolutionizing the field of machine learning by significantly reducing the need for deep computer science expertise. Designed to make ML more accessible, they enable users to build high-performing models without extensive technical knowledge. This study delves into these tools in the context of time series analysis, which is essential for forecasting future trends from historical data. We evaluate three prominent AutoML tools—AutoGluon, Auto-Sklearn, and PyCaret—across various metrics, employing diverse datasets that include Bitcoin and COVID-19 data. The results reveal that the performance of each tool is highly dependent on the specific dataset and its ability to manage the complexities of time series data. This thorough investigation not only demonstrates the strengths and limitations of each AutoML tool but also highlights the criticality of dataset-specific considerations in time series analysis. Offering valuable insights for both practitioners and researchers, this study emphasizes the ongoing need for research and development in this specialized area. It aims to serve as a reference for organizations dealing with time series datasets and a guiding framework for future academic research in enhancing the application of AutoML tools for time series forecasting and analysis.

Purpose – This paper investigates the moderating role of institutional quality in the relationship between public education financing and educational quality in Sub-Saharan Africa (SSA). Design/methodology/approach – This paper uses a two-step system generalised method of moments (GMM) to investigate the dynamic relationships among the variables using data from the World Bank covering the periods 2002–2020 for 46 SSA countries. Findings – The results show that institutional quality moderates the effect of public education financing on educational quality at SSA’s primary, secondary and tertiary levels. This finding shows that improved institutional quality enhances the effectiveness of public educational investments. Practical implications – The findings of this study imply that policymakers seeking to enhance educational quality must not only increase educational investments but also institute measures to improve institutional quality. Originality/value – Prior studies fail to examine the moderating role of institutional quality in the nexus between public education financing and educational quality. This study analyses the role of institutional quality in the public education financing–educational quality nexus in SSA. The findings of this study contribute to improving the return on public education financing in SSA.

Purpose – This paper examines the short- and long-run effects of foreign direct investment (FDI) on tax revenue in Ghana. Design/methodology/approach – The paper adopts the autoregressive distributed lag approach to estimate FDI’s long-run and short-run effects on tax revenue. The study uses time-series data from 1983 to 2019 for Ghana, mainly obtained from The Bank of Ghana, the World Bank and the IMF. Findings – The results show that, in the short-run, FDI has no significant effect on direct tax revenue and total tax revenue but significantly hurts indirect tax revenue. In the long run, however, the results show that FDI has significant positive effects on indirect tax revenue and total tax revenue but no significant effect on direct tax revenue. Originality/value – Empirical studies often fail to analyse the short-run and long-run effects of FDI on tax revenue. This study contributes to the mixed literature by analysing the short-run and long-run effects of FDI on tax revenue in an emerging market context. Additionally, this study employs three tax revenue measures in analysing the nexus.

Purpose – The objective of this study is to analyze the influence of institutional quality on the attainment of the Sustainable Development Goals (SDGs) using a data set comprising 45 African nations during the timeframe 2000 to 2020. Design/methodology/approach – The data are divided into two periods, with the Millennium Development Goals (MDGs) data covering the years 2000–2015 and the SDGs data spanning from 2015 to 2020. Controlling for other factors, the researcher employs an index of institutional quality and applies the generalized method of moments (GMM) method to analyze the data. Findings – The findings demonstrate a noteworthy inverse relationship between institutional quality and the achievement of both the MDGs and SDGs. The findings reveal a significant and positive link between economic growth and the achievement of the MDGs, while the impact on the SDGs is shown to be insignificant. Population growth significantly drives the SDGs. The results further reveal that trade openness and industrialization contribute positively to the achievement of both the MDGs and SDGs. Practical implications – The findings emphasize the importance of improving institutional quality, promoting economic growth and supporting trade openness and industrialization for sustainable development in African countries. Originality/value – The contribution of the study is twofold. Firstly and to the best of the author’s understanding, this research marks an initial endeavor to empirically investigate the nexus between institutional quality and the SDGs in the context of Africa. Secondly, it adds novelty to the literature by examining how institutional quality influences both the SDGs and their precursor the MDGs, providing insights into the actual contribution of institutions to development within the framework of these two major global compacts.

This study investigates teachers' perceptions on PLC implementation within religious-based secondary schools in the context of Malaysia. Using a pragmatic mixed-method approach, quantitative data were obtained from 610 teachers about principals' implementation and support for PLC implementation. Then, 16 senior teachers who have successfully participated in PLC practices were interviewed. The study reveals that teachers in the religious-based public secondary schools felt satisfied with their principals' implementation of PLC practices. This study is one of few studies explored the practical and theoretical implications of improving principals' initiatives and their strategies which benefit PLC practices across religious-based secondary schools in Malaysia.

Abstract In order to slow the spread of COVID-19, on March 23, 2020, a strict lockdown was implemented in the UK. This was followed by alternating periods of less restrictive lockdowns until most public health restrictions were lifted in the summer of 2021. While these measures were necessary, they significantly affected people’s daily activities, lifestyles, and mental well-being. This paper presents a longitudinal research study that focused on females aged 55 + in the UK, aiming to understand how COVID-19 and the subsequent 15-month period of lockdowns affected their lifestyles and emotions. The study collected data through online surveys, where respondents reported the frequency and mode of access to activities, and their positive and negative emotional experiences during distinct study phases that encompassed both lockdown and less strict periods. In contrast to previous studies highlighting vulnerabilities for females and the elderly during lockdowns, this research found that the studied group maintained an overall positive outlook throughout the study period and successfully adapted to the lockdowns by increasing their engagement in certain activities, in particular, activities like ‘getting active’. In addition, our findings indicate rapid adaptive behaviour change towards many online activities, such as cultural activities. However, the study also revealed negative emotions and a decrease in some activities during the second lockdown in 2020 and the subsequent lockdowns in 2021, underscoring the challenges inherent in prolonged periods of confinement. In addition, the study found negative affect associated with some activities, including working and studying from home. The findings provide valuable insights into how females aged over 55 coped with stressful circumstances, which can inform the development of resilient and mental health-conscious public health policies and responses in preparation for future pandemics or other hazards.

Abstract Objective Routine viral load and drug resistance testing are well supported in most resource-rich settings and provide valuable benefits in the clinical care of PLWH in these communities. Undoubtedly, there exist financial and political constraints for the scale-up of viral load and drug resistance testing in Sub-Saharan Africa. To achieve the global UNAIDS 95/95/95 targets, there is the need to bridge this inequity in patient care and allow for a universal approach that leaves no community behind. Methods Venous blood from 96 PLWH on second-line ART from Korle-Bu Teaching Hospital were collected and processed into plasma for CD4+ T- cell and viral load assessments. Ribonucleic acid (RNA) was extracted from stored plasma and the protease gene amplified, sequenced and analyzed for subtype and drug resistance mutations using the Stanford HIV drug resistance database. Results Out of the 96 PLWH, 37 experienced virological failure with 8 patients’ samples successfully sequenced. The predominant HIV-1 subtype identified was CRF02_AG (6/8, 75.0%) with 12.5% (1/8) each of CFR06_cpx infection and one case unable to subtype. The major PI resistance mutations identified were; M46I, I54V, V82A, I47V, I84V and L90M. Conclusions Persons living with HIV who had experienced virologic failure in this study harboured drug resistance mutations to PI, thus compromise the effectiveness of the drugs in the second line. Resistance testing is strongly recommended prior to switching to a new regimen. This will help to inform the choice of drug and to achieve optimum therapeutic outcome among PLWH in Ghana.

In the new global economy, employee productivity has become a central issue of study. The financial services sector in Ghana has garnered significant attention in recent years. Given the growing inefficiencies in the Ghanaian banking industry, which has resulted in the revocation of operational licenses for some banks, this study aims to examine the impact of compensation, informal organization, and commitment on employee retention and productivity. Additionally, the study seeks to explore the moderating role of job satisfaction in selected private and public banks in the Ashanti region. The study utilized a quantitative research approach, sampling 270 respondents from the selected public and private banks in the Ashanti Region using a simple random sampling technique. For data analysis, the study employed multiple linear regression and utilized the PROCESS MACRO for SPSS version 25. The findings indicate that compensation, commitment, and informal organization exert a positive influence on employee retention, thereby affecting productivity. Furthermore, the study revealed that job satisfaction significantly moderates the relationship between compensation and employee retention, but it does not significantly moderate the relationship between informal organization and employee retention. Similarly, job satisfaction does not significantly moderate the relationship between commitment and employee retention.

One of the crucial issues confronting China is high carbon dioxide (CO2) emissions. Despite the numerous measures outlined to promote the country’s carbon neutrality target, CO2 emissions in the nation continue to increase. This means that more policy options are needed to help improve environmental sustainability (ES) in the nation. Hence, examining the relationship between financial development (FD), foreign direct investment, industrialization, and environmental sustainability in China to provide proper recommendations to drive the carbon neutrality agenda of the nation is deemed fitting. In attaining this goal, time-series data from the period 1990 to 2018 is employed. According to the results, foreign direct investment deteriorates environmental sustainability by promoting more CO2 emissions. This validates the pollution haven hypothesis (PHH). In addition, industrialization and financial development are not friendly to the nation’s environmental quality. Furthermore, economic growth and urbanization escalate environmental pollution in the nation. In addition, the interactions between financial development and foreign direct investment and between financial development and industrialization deteriorate the environment in China. Moreover, foreign direct investment and financial development have an inverted U-shaped association with environmental degradation, but industrialization and environmental pollution are not nonlinearly related. The study advocated for the implementation of measures that could help advance the carbon-neutrality targets of the nation.

Globally, the quality of groundwater has proven to have been affected by some natural and human activities in recent years. To ensure there is good drinking water (Sustainable Development Goal 6.3, there is a need to elucidate the groundwater quality status of the area of interest. The groundwater in the northwestern parts of Ghana is not yet well characterized. Hence, this study employed a multi-method approach of hydrochemistry, water quality index (WQI), multivariate statistics, and machine models: multiple linear regression (MLR), decision tree regression (DTR), random forest regression (RFR), and artificial neural network (ANN), are combined in the characterization and prediction of the water quality in the area. They are robust in providing conclusions on groundwater assessment that can be relied upon for decision-making processes regarding groundwater usage and monitoring. Except for NO3− and TDS exceeding their standard levels in 22 and 2 locations, respectively, the other physicochemical parameters are within acceptable limits. The groundwater is generally good for domestic usage based on the WQI, with 79.2% of excellent to good waters. The groundwater evolved from Na-type, Cl-type, and Cl(SO4)-Ca(Mg) facies. Agricultural activities are the main source of human impact on the groundwater. Silicate mineral dissolution and ion exchange processes are the natural processes that affect groundwater mineralization, with mineral dissolution being the dominant process. Based on the performance metrics: MAE, MSE and RMSE of the ML methods considered in the WQI forecasting, the order of performance of the models is ANN > RFR > DTR > MLR, with the following respective R2 values 0.9974, 0.9193, 0.8966 and 0.8886.

The general argument is that individuals choose those conflict styles that fit their cultural values. The concept of culture fit elucidates why organizational practices are effective with regards to employees work-related performance if these practices fit the cultural values of the workforce. Mismatch of organizational practices with employees’ cultural values may result in dissatisfaction and demotivation to perform well. This present study determined the link between plant turnaround maintenance (TAM) workers culture values, and their preference for a specific method for managing conflict. The research methodology is based on questionnaire survey focusing on plant TAM employees during execution phase. Data was gathered from TAM workers in 13 petrochemical plants in east and west Malaysia. Stated hypotheses were tested using SmartPLS software. Results shows all five cultural dimensions positively predicted integrating, obliging, compromising and avoiding, and negatively predicted dominating conflict management styles. The study concludes that employees will generally favor conflict styles that are consistent with their cultural values. Compared to previous findings, the current results revealed both culture and temperament as predictors of conflict management styles, providing a comprehensive evidence of the predictors of conflict management style preference.

In the ever-changing sector of education, the use of technology has become critical to innovation and increased learning opportunities. This research illustrates the intricate connections that exist between augmented reality [AR] and tremendous educational attributes, thinking about how AR might modify conventional teaching approaches. The important motive is to offer an entire knowledge of how augmented fact influences crucial areas of the educational revel in. Utilizing a quantitative studies method, the study seems at how AR impacts pupil behavior, creativity, and instructional practices, in addition to the mediating and moderating elements that influence these relationships. An online questionnaire was used to collect data from 444 random samples. The relationships between AR, teacher competence, technology acceptance, and educational outcomes were examined. Data shows that augmented reality has a positive effect on creativity, student behavior, and teaching strategies. Teacher competence moderated these relationships, highlighting the critical role of teachers in successfully integrating augmented reality, while technology acceptance emerged as a significant mediator demonstrating the significance of user perceptions. This study has critical implications for educators, administrators, and policymakers interested in using AR to improve instructional development, as well as for the field of generation-infused schooling administration. Additionally, it advances theoretical frameworks through a better understanding of the complicated tactics that impact the uptake and acceptability of AR.

Plant seeds are a source of medicinal components used in human therapeutics. As a result, it is important that extraction methods are developed that can remove the bioactive compounds used for these therapeutics without damaging the plant tissue. In this 'Focus on Environmental Analysis' column, LCGC sat down with Dr. Rabi Ann Musah from the University of Albany, who is currently researching methods to protect seed viability while isolating specific compounds. Musah's team used a technique called laser ablation direct analysis in real-time imaging--mass spectrometry (LADI--MS) to analyze the distribution of molecules, such as alkaloids, in Voacanga africana seeds., PLANTS PLAY AN essential role on Earth. They are critical cogs in several ecosystems that help moderate the planet's climate. Plants have a unique versatility about them that allow them [...]

This study reports on the professional development and school leadership programmes requested by principals in Malaysian schools. A total of 557 principals provided feedback on their preferred school leadership and professional development programmes which they believed as essential to be effective school leaders. Based on their feedback, mentoring was named the most needed leadership development programme as it allowed access to the guidance, knowledge and skills of senior principals. As for school leadership courses mentioned by school principals, financial management was considered as most useful. The study concludes by recommending suggestions to improve principals' professional development programmes in Malaysia.

This study considered the phenomenon of emotional homeostatic disequilibrium that adversely affects individuals, with a view to unveiling factors that instigate it. It was carried out in the area of counselling psychology. The purpose is to determine whether or not sexual spousal abuse is related to EHD among married secondary school teachers in Rivers State of Nigeria. The reason for selecting this topic is because the EHD problem has caused so much damage in the society, which demands investigation. Expost facto correlation design was adopted, while two research questions and two null hypotheses guided the study. Results of the study indicated a significant relationship between sexual spousal abuse and EHD, and a moderating influence of cultural values/beliefs in that relationship among the subjects. Specifically, this study contributes to a deeper understanding of the psychological and emotional toll of sexual spousal abuse and informs more effective support and intervention strategies.

The MHD flow of a blood-based hybrid nanofluid with thermal radiation and stenosis effects is explored in this study. Gold (Au) and Copper (Cu) hybrid nanoparticles are assumed to be distributed in the blood. Relevant governing equations are established and appropriately normalized. The Caputo fractional-order derivative is used to convert the transient terms of normalized equations into time-fractional forms, which are then semi-analytically solved using the Laplace transform method to yield complex forms of modified Bessel functions. The concentrated matrix exponential (CME) approach is used to numerically determine approximate inverse Laplace transforms of the updated equations. The distribution patterns of velocity, temperature, and concentration are evaluated graphically. The results showed that the fractional-order derivative and the height of stenosis greatly influence the velocity, temperature and concentration profiles. We also observed that both velocity and temperature decreased with increasing values of Ha. Temperature rises with increasing values of the thermal radiation parameter (Ra) and the Eckert number (Ec) whilst concentration is enhanced with rising values of the chemical reaction parameter (Cr) and the Schmidt number (Sc). Our numerical results show that relevant parameters have considerable influences on skin friction, Nusselt number, and Sherwood number, which are important for understanding blood mobility, heat and mass transfer dynamics, and treating cardiovascular illnesses. Our results are also essential for controlling blood flow, temperature and delivery of drugs to diseased arteries in the human body.

Background: The successful detection of drug-resistance mutations (DRMs) in HIV-1 infected patients has improved the management of HIV infection. Next-generation sequencing (NGS) to detect low-frequency mutations is predicted to be useful for efficiently testing minority drug resistance mutations, which could contribute to virological failure. This study employed Sanger sequencing and NGS to detect and compare minority and majority drug resistance mutations in HIV-1 strains in treatment-naive patients from Ghana. Method: From a previous study, 20 antiretroviral therapy (ART)-naive participants were selected for a cross-sectional study. Sanger sequencing and NGS techniques were used to detect the majority and minority HIV drug resistance (HIVDR) mutations, respectively, in the protease (PR) and partial reverse transcriptase (RT) genes. NGS detected mutations at 1 % and 5 % frequencies and Sanger sequencing at ≥20 % frequencies. The sequences obtained from NGS and Sanger sequencing platforms were submitted to the Stanford HIV drug resistance database for subtyping, mutation identification, and interpretations. Results: Sequences from the twenty participants where the CRF02_AG was the predominant strain (16, 80 %) were analyzed. NGS detected 25 mutations in the RT and PR genes, compared to 21 mutations by Sanger sequencing. Minority DRMs were detected at the prevalence of 55.0 % with NGS against 35 % DRMs by Sanger sequencing. One of the patients had eight different HIVDR variants, with two minority variants. These mutations were directed against PI (K20I and D30DN), NNRTI (Y181C, M23LM and V108I) and NRTI (K65R, M184I, and D67N). Conclusion: The study affirms the usefulness of genomic sequencing for drug resistance testing in HIV. It further shows that Sanger sequencing alone may not be adequate to detect mutations and that NGS capacity should be developed and deployed in the Ghanaian clinical settings for patients living with HIV.

This study aims to fill a significant knowledge gap by examining the dynamics of sectoral per capita greenhouse gas (GHG) emissions convergence across 54 African countries from 1980 to 2019. Using the log (t) club convergence approach, this study uncovers the presence of multiple local steady-state convergence patterns within each sector. A significant correlation emerges between the classification of countries regarding their total and energy sector emissions. In particular, less industrialized African countries with higher proportions of renewable energy consumption tend to demonstrate elevated convergence rates in both total and per capita energy emissions. Further, the analysis indicates that wealthier countries with greater trade intensity and increased industrialization are associated with a higher rate of convergence in the agriculture sector. By highlighting the heterogeneity in sectoral patterns and the evolving landscape of GHG emissions in Africa, this study provides valuable insight for the formulation of policies that concurrently address the challenges of sustainable development and climate change mitigation.