Findings Of Study Research Articles

Assessment of exchange rate determination in a mono-resource economy: A case of Nigeria

<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Times New Roman,Times,serif"><span dir="ltr" lang="EN-US"><span style="color:black">This study examined the determinants of the exchange rate in a mono-resource economy, during the period of currency and oil price fall in Nigeria. The aim of the study is to ascertain the potentiality of economic diversification (non-oil export) in saving the falling value of the domestic currency, as well as, its stability. The study employed the use of monthly data from the Central Bank of Nigeria and Nigeria National Petroleum Corporation from January 2008 to December 2020 using the ARDL and NARDL models to achieve the stated objectives. In the literature, several empirical studies analyzed the relationship between exchange rates, oil price, and oil export and came to the logical conclusion that a rise in the price of oil would bring about a rise in the exchange rate, all things being equal while the reverse is the case. To add to the existing body of knowledge this study did not only look at the relationship between the variables but also examined the determinants of the exchange rate in a mono-resource economy and ascertained the potentiality of economic diversification in bringing succor to the falling exchange rate in the midst of falling oil price. The NARDL result corroborates the findings of previous studies on the relationship between exchange rate, oil price, and the performance of non-oil export. It maintains that positive changes in oil prices would lead to the appreciation of domestic currency while negative changes in oil prices would lead to the depreciation of the domestic currency. With this analysis, the study recommends the diversification of the economy and revitalization of the non-oil sector. Since import proves to have a negative impact on the exchange rate, the revitalization of the non-oil sector stimulates domestic consumption and thus reduces import bills which raise the demand for the dollar and weakens the naira.</span></span></span></span></p>

An extreme gradient boost based classification and regression tree for network intrusion detection in IoT

Nowadays, modern technology includes various devices, networks, and apps from the internet of things (IoT), which consist of both positive and negative impacts on social, economic, and industrial effects. To address these issues, IoT applications and networks require lightweight, quick, and adaptable security solutions. In this sense, solutions based on artificial intelligence and big data analytics can yield positive outcomes in the realm of cyber security. This study presents a method called extreme gradient boost (XGBoost) based classification and regression tree to identify network intrusions in the IoT. This model is ideally suited for application in IoT networks with restricted resource availability because of its distributed structure and builtin higher generalization capabilities. This approach is thoroughly tested using botnet internet of things (BoT-IoT) new-generation IoT security datasets. All trials are conducted in a range of different settings, and a number of performance indicators are used to evaluate the effectiveness of the proposed method. The suggested study's findings provide recommendations and insights for situations involving binary classes and numerous classes. The suggested XGBoost model achieved 99.53% of accuracy in attack detection and 99.51% in precision for binary class and multiclass classifications, respectively.

A novel framework for analyzing internet of things datasets for machine learning and deep learning-based intrusion detection systems

To generate a machine learning (ML) and deep learning (DL) architecture with good performance, we need a decent dataset for the training and testing phases of the development process. Starting with the knowledge discovery and data mining (KDD) Cup 99 dataset, numerous datasets have been produced since 1998 to be utilized in the ML and DL-based intrusion detection systems (IDS) training and testing process. Because there are so many datasets accessible, it might be challenging for researchers to choose which dataset to employ. Therefore, a framework for evaluating dataset appropriateness with the research to be conducted is becoming increasingly crucial as new datasets are regularly created. Additionally, given the growing popularity of internet of things (IoT) devices and an increasing number of specific datasets for IoT in recent years, it is essential to have a specific framework for IoT datasets. Therefore, this research aims to develop a new framework for evaluating IoT datasets for ML and DL-based IDS. The study's findings include, first, a novel framework for assessing IoT datasets, second, a comparison of this novel framework to other existing frameworks, and third, an analysis of five IoT datasets by using the new framework.

ChatGPT effects on cognitive skills of undergraduate students: Receiving instant responses from AI-based conversational large language models (LLMs)

This study investigated the impact of using ChatGPT, a state-of-the-art generative AI-based model, on the critical, creative, and reflective thinking skills of university students in Ghana. The study utilized a mixed-methods research approach, incorporating quantitative and qualitative data collection instruments, and an experimental procedure with a pretest-posttest control group. The study ultimately enlisted a sample of 125 students randomly allocated to either the experiment group (60 students) or the control group (65 students). The research was conducted in the context of a Research Methodology course, which had adopted the flipped classroom approach. The students in the experiment group engaged with ChatGPT for in-class tasks, while those in the control group used traditional databases and search engines for similar tasks. Data were collected using the Critical Thinking Scale, Creative Thinking Scale, Reflective Thinking Scale, and a student interview guide (semi-structured). The study's findings illustrated that incorporating ChatGPT influenced the students' critical, reflective, and creative thinking skills and their dimensions discernibly. As a result, the study provides suggestions for academics, instructional designers, and researchers working in educational technology.

Evaluating the Antidepressant-like Properties of Melatonin and Vitamin D3 Combination in Mice Subjected to Restraint Stress: Investigating the Involvement of Oxidative Stress

Background: Increased levels of oxidative stress are connected with depression. Due to the melatonin's antioxidant effects and Vitamin D3 (Vit D3)'s regulatory effect on the biosynthesis of neurotransmitters and neurotrophic factors, the present study investigated the possible protective effect of melatonin and Vit D3 combination on restraint stress-induced depression-like behaviors in mice. Methods: After being subjected to restraint stress, mice were divided into six groups using a randomization process. These groups included non-stressed and stressed vehicle-treated groups, as well as groups treated with Vit D3 (25 μg/kg/day), melatonin (10 mg/kg) or fluoxetine. A group also received a combination of both melatonin and Vit D3. The Forced Swimming Test (FST), and Open Field Test (OFT) were conducted to evaluate behavioural changes. The Malondialdehyde (MDA) level and Catalase (CAT), Superoxide Dismutase (SOD) activity, and ADP/ATP ratio were evaluated in the hippocampus of mice. Results: Restraint stress lengthened the immobility period in FST, while melatonin, Vit D3, and their combination all significantly reversed this impact. Co-administration of melatonin and Vit D3 was more effective than melatonin or Vit D3 administration alone at reducing immobility time. The exposure of mice to restraint stress has been linked to an elevation in the ADP/ATP ratio and oxidative stress in their hippocampus; however, these effects are reversed by the administration of melatonin and Vit D3 (10 mg/kg) alone or in combination. Melatonin and Vit D3 combination increased the hippocampus CAT activity compared with melatonin and Vit D3 alone. Conclusion: The current study's findings suggested that Vit D3 may enhance melatonin's potential as an antidepressant in FST.

Comparative analysis of explainable AI models for predicting lung cancer using diverse datasets

Lung cancer prediction is crucial for early detec-tion and treatment, and explainable AI models have gained attention for their interpretability. This study aims to compare various explainable AI models using diverse datasets for lung cancer prediction. Clinical, genomic, and imaging data from multiple sources were collected, prepro-cessed, and used to train models such as Logistic Regression, SVC-Linear, SVC-rbf, Decision Tree, Random Forest, AdaBoost Classifier, and XGBoost Classifier. Preliminary results indicate that Random Forest achieved the highest accuracy of 98.9% across multiple datasets. Evaluation metrics such as accuracy, precision, recall, and F1 score were utilized, along with interpretability techniques like feature importance rankings and rule extraction methods. The study's findings will aid in identifying effective and interpretable AI models, facilitating early detection and treatment decisions for lung cancer.

A study on metrological cross-validation of hydrogen refueling stations using a hybrid metrology evaluation system

Hydrogen refueling stations play a pivotal role in advancing hydrogen fuel cell vehicles. Ensuring the accuracy and reliability of these stations is crucial for their safe and efficient operation. This study proposes a hybrid metrology evaluation system for the comprehensive cross-validation of hydrogen refueling stations. The system combines experimental measurements with computational models to thoroughly assess the stations' performance.The main objectives of this study are to evaluate the precision, accuracy, and reliability of hydrogen refueling stations and to identify potential uncertainties or sources of error in measurements. Six refueling experiments were conducted, varying the refueling pressure from 476bar to 735bar and the refueling rate from 0.601486kg/min to 0.702694kg/min. The maximum refueling capacity was determined to be approximately 6.3kg, based on the specifications of the NEXO vehicle.Throughout the experiments, data on critical parameters such as pressure, weight, and flow rate were collected. These data were meticulously analyzed and compared with expected values derived from computational models. The results convincingly demonstrate that the hybrid metrology evaluation system offers a robust and precise evaluation of hydrogen refueling stations. The system adeptly identifies discrepancies between experimental measurements and computational models, facilitating the correction of potential measurement errors.This study contributes significantly to the enhancement of metrological cross-validation techniques for hydrogen refueling stations, ensuring their precision and dependability. The study findings can inform the development of standardized metrological protocols and guidelines for the certification and calibration of hydrogen refueling stations. By establishing accurate and dependable metrological validation methods, the adoption of hydrogen fuel cell vehicles can be expedited, promoting a sustainable and environmentally friendly transportation system.

Activated nitinol compression staples are associated with favorable biomechanical properties for talonavicular arthrodesis

BackgroundNitinol compression staple use in foot and ankle arthrodesis procedures, including for the talonavicular joint, has gained acceptance. A previous study provided evidence for using nitinol compression staples in talonavicular arthrodesis (TNA) based on functional biomechanical testing comparisons to “gold standard” lag screw fixation. This study aimed to further compare the functional biomechanical properties of nitinol compression staple fixation to lag screw fixation for arthrodesis of the talonavicular joint. Body-temperature incubation and ankle inversion and eversion loading sequences were added to previously reported biomechanical testing. MethodsRobotic testing was performed on cadaveric feet (n = 10; 5 matched pairs) after TNA using either two nitinol compression staples or two fully threaded lag screws. TNA method was randomized, alternating between matched-pairs of left and right feet. After surgical stabilization, specimens were incubated at 38 °C for 24 h to simulate the initial postoperative period in a patient. After plantarflexion and dorsiflexion testing, the specimens underwent inversion and eversion testing, cycling from 20° inversion to 10° eversion for 10 cycles. Displacements were tracked using optical tracking markers. Significant (p < 0.05) differences between staple versus screw fixation cohorts were determined using paired t-Tests. ResultsAll specimens completed testing with none experiencing failure at the TNF. No statistically significant differences in functional biomechanical testing properties were noted between nitinol compression staple fixation and lag screw fixation for TNA. ConclusionThe study findings provide additional support for nitinol compression staple fixation as an option for talonavicular arthrodesis fixation. Taken together, the results of functional biomechanical testing studies have provided sufficient evidence for initiation of a prospective clinical outcomes study using nitinol compression staples for talonavicular arthrodesis fixation at our institution.

Household-level demographic and socio-economic vulnerability in the face of the COVID-19 pandemic in rural Central Vietnam

This study adopted the Social Vulnerability Index (SoVI) method using household-level demographic and socio-economic data to measure the vulnerability of rural households in Central Vietnam to the COVID-19 pandemic. It found that most households suffered from a partial or total loss of employment and a remarkable decrease in household income during the challenging time of the COVID-19 spread. The index scores demonstrated which characteristics and which components were more or less responsible for household-level vulnerability. The findings of the study found that low educational attainment of household heads, low engagement in stable jobs and limited access to the support from local government, grassroots organizations and groups were among the most constructing the vulnerability of the surveyed households to the pandemic.The study suggests that any response and adaptation strategies in short-term or long-term should firstly and ultimately pay special attention to building and enhancing household-level capacities and strengthening local governance so that the households and communities can be more resilient to any disastrous events in the future. It also agreed that the SoVI would be a viable technique in measuring place-based vulnerability and providing empirical evidence for more appropriate responses and prevention measures to crisis and pandemic like COVID-19.

Controversy on the CONVINCE study findings: the PRO take

RESUMO O estudo CONVINCE, publicado recentemente no New England Journal of Medicine, revela uma redução inovadora de 23% no risco relativo de mortalidade por todas as causas entre pacientes renais em estágio terminal submetidos à hemodiafiltração de alto volume de convecção. Esse achado significativo desafia o uso convencional da hemodiálise de alto fluxo e oferece esperança de melhoria dos desfechos em pacientes com doença renal crônica. Embora algumas controvérsias cerquem os achados do estudo, incluindo preocupações sobre a generalização e as causas de óbito, é essencial reconhecer o desenho do estudo e seus principais desfechos. O estudo CONVINCE, parte do projeto HORIZON 2020, inscreveu 1.360 pacientes e demonstrou a superioridade da hemodiafiltração na redução da mortalidade por todas as causas em geral, bem como em subgrupos específicos de pacientes (idosos, HD de curta duração, não diabéticos e aqueles sem problemas cardíacos). Curiosamente, demonstrou-se que a hemodiafiltração teve um efeito protetor contra infecções, incluindo a COVID-19. Pesquisas futuras abordarão sustentabilidade, efeitos de escalonamento da dose, identificação de subgrupos especialmente propensos a se beneficiar e a relação custo-benefício. No entanto, por ora, os achados apoiam fortemente uma adoção mais ampla da hemodiafiltração na terapia renal substitutiva, marcando um avanço significativo na área.

The impact of international trade on economic growth in Somalia

The main objective of this study was to examine the impact of international trade on economic growth in Somalia. This objective was accomplished with the support of four distinct objectives. To investigate the impact of exports on economic growth in Somalia. To examine how imports impact economic growth in Somalia. To discover how the trade openness phenomenon effects economic growth in Somalia. To establish a solid foundation for public policy founded on an innovative international trade approach that considerably boosts the country's economic growth over the long term. In Somalia, international trade has become increasingly important, driven by imports surpassing exports, which underscores the primary objective of this study. Therefore, the study employed the least squares (OLS) method to analyze the determinants of international trade in Somalia from 1960 to 2022. Our analysis predominantly centered on explanatory variables such as exports, imports, and trade openness. According to the study's findings, exports and imports have a positive relationship and have a statistically significant impact on economic growth. This means that a one-unit increase in exports and imports leads to an increase in economic growth in Somalia. The exports and imports have revealed a number of characteristics that are positive for economic growth. Moreover, the study's findings indicate an adverse relationship between trade openness and economic growth. Trade openness has a probability that it is statistically significant with a negative coefficient within the parameter estimation model. A negative coefficient suggests that the dependent variable tends to decrease with an increase in the independent variable. In conclusion, the study's findings contributed to the policy recommendations, which should be taken into account by decision-makers.

Post-traumatic stress disorder symptoms among internally displaced persons: unveiling the impact of the war of Tigray

IntroductionDue to the war in Tigray, 2.1 million people (31% of the total population) were internally displaced. Epidemiological evidence shows that the burden of mental health is higher in war/conflict and post-conflict areas of the world compared to non-conflict places, especially for those who have experienced targeted ethnic violence as a result of civil and political unrest. Post-traumatic stress disorder is one of the common psychiatric disorders experienced during war. Thus, this study aimed to assess the level and aggravating factors of PTSD during the war in Tigray.MethodsA community-based cross-sectional study was conducted among 2132 IDP family heads in Tigray from August 6–30, 2021. Study participants were recruited using a multi-stage sampling technique. Data were collected using a pretested structured questionnaire through face-to-face interviews. The PCL-C checklist, derived from DSM-IV criteria, was used to assess the magnitude of post-traumatic stress disorder. The entered data were exported to the SPSS version 26 statistical package for analysis. Summary statistics were computed, and logistic regression analysis was used to investigate factors associated with developing PTSD.ResultsA total of 2071 IDPs were surveyed with a response rate of 99.7%. The survey revealed that the level of PTSD among community-hosted IDPs was 57.7%; 95% CI 55.5%-59.8%. Older age (> 50) (AOR 3.1, 95% CI 1.497–6.421), primary and secondary school attendance (AOR 2.1, 95% CI 1.344–3.279; and 1.697, 95% CI 1.067–2.7) respectively, internally displaced persons with a family size of > 6 members (AOR 1.821, 95% CI 1.124–2.95), disability due to the war (AOR 1.702, 95% CI 1.077–2.69), and loss of contact with family members (AOR 1.472, 95% CI 1.032–2.099) were significantly associated with PTSD.ConclusionThe overall level of PTSD among cIDPs was found to be high (57.7%). Almost every other IDP developed this serious mental health syndrome. Immediate psycho-social health intervention is needed by local and international organizations in collaboration with governmental and non-governmental institutions based on the study's findings.

Fintech and green finance revolutionizing carbon emission reduction through green energy projects in mineral-rich countries

The primary objective of this study is to examine the impact of green finance, fintech, and renewable energy on the eight mineral-rich countries, namely Russia, the United States, Saudi Arabia, Canada, Iran, China, Brazil, and Australia. In addition to that, the study has also examined the moderating role of renewable energy in the relationship between fintech, green finance, and CO2 emissions. The study is among the pioneers to investigate the issues related to fintech, green finance, renewable energy, and CO2 emissions in eight mineral-rich countries. The study used data from eight mineral-rich countries over a 30-year period, from 1990 to 2019. To achieve the research objectives, the study has employed a robust estimate, namely MMQR. The MMQR approach is a robust technique that determines the impact of green finance, fintech, and renewable energy across different quartiles. The results of the study highlight that an increase in green financial practices, fintech adoption, and the use of renewable energy help mineral-rich countries reduce CO2 emissions. The study's findings provide policymakers with guidelines for making informed decisions in selected economies. In addition to that, the results of the study demonstrate the importance of incorporating renewable energy into the energy mix. The study not only improves our understanding of the interconnections between these factors, but it also establishes a strong foundation for future research and policymaking.

The Students’ Motivation and Grit As Predictors on Reading Achievement

The objective of this study is to examine the relationship between students' reading motivation and their reading achievement, as well as the relationship between students' grit and their reading achievement. Additionally, this study aims to explore the interplay among students' motivation, grit, and reading achievement. In this research, the researcher employed two types of motivation: intrinsic and extrinsic, and two types of grit: consistency of interest and perseverance of effort. This research is a quantitative correlational study with the population consisting of fifty-five students in the sixth semester of the S1 English Study Program Regular A of Tanjungpura University in Pontianak in the academic year of 2021/2022 who already took two reading courses (intensive reading and reading skill development) on their past semesters. Data were collected using questionnaires. The questionnaires consisted of 40 reading motivation items and 8 grit items on a 4 Likert scale ranging from “Very Different from Me” to “A lot Like Me”. Based on the research findings, there is a correlation with reading achievement (r= 0.551). There exists a positive connection (r=0.748) among grit and reading achievement. Additionally, it is noteworthy that there exists a good association between an individual's motivation to read and their level of perseverance and passion towards achieving success in reading (r=0.758). The study's major findings indicate a favorable correlation between the motivation and grit of great performers. There exists a positive correlation between an individual's level of motivation and grit and their level of achievement.

The Influence of CAR, FDR, and BOPO

One metric used to assess how well a business is performing is profitability. An organization's capacity to turn a profit can be used to measure performance. A high profitability level indicates excellent success for the organization. Return On Assets (ROA) is the ratio used to determine the degree of profitability. At the same time, the Capital Adequacy Ratio (CAR), Financing to Deposit Ratio (FDR), and Operating Expenses and Operating Income (BOPO) ratios are known to have an impact on the degree of profitability. This research aims to examine how CAR, FDR, and BOPO affect profitability. This quantitative study utilizes information gathered from Bank Muamalat Indonesia's quarterly financial reports issued between 2013 and 2021. This study employed multiple linear regression with the e-views Nine program as the research method. According to the research's findings, the degree of profitability is significantly impacted by the FDR and BOPO variables but not by the CAR variable. Furthermore, the study's findings indicate that the CAR, FDR, and BOPO variables significantly affect the profitability level simultaneously. The findings of the coefficient of determination (R2) analysis, which indicate that CAR, FDR, and BOPO have an impact on the profitability level, which is 98.60% and 1.40% with the influence of other factors from outside the analysis model, support this.

Dengue fever mapping in Bangladesh: A spatial modeling approach

AbstractBackgroundEpidemics of the dengue virus can trigger widespread morbidity and mortality along with no specific treatment. Examining the spatial autocorrelation and variability of dengue prevalence throughout Bangladesh's 64 districts was the focus of this study.MethodsThe spatial autocorrelation is evaluated with the help of Moran and Geary . Local Moran was used to detect hotspots and cold spots, whereas local Getis Ord G was used to identify only spatial hotspots. The spatial heterogeneity has been detected using various conventional and spatial models, including the Poisson‐Gamma model, the Poisson‐Lognormal Model, the Conditional Autoregressive (CAR) model, the Convolution model, and the BYM2 model, respectively. These models are implemented using Gibbs sampling and other Bayesian hierarchical approaches to analyze the posterior distribution effectively, enabling inference within a Bayesian context.ResultsThe study's findings show that Moran and Geary analysis provides a substantial clustering pattern of positive spatial autocorrelation of dengue fever (DF) rates between surrounding districts at a 90% confidence interval. The Local Indicators of Spatial Autocorrelation cluster mapped spatial clusters and outliers based on prevalence rates, while the local Getis‐Ord G displayed a thorough breakdown of high or low rates, omitting outliers. Although Chattogram had the most dengue cases (15,752), Khulna district had a higher prevalence rate (133.636) than Chattogram (104.796). The BYM2 model, determined to be well‐fitted based on the lowest Deviance Information Criterion value (527.340), explains a significant association between spatial heterogeneity and prevalence rates.ConclusionThis research pinpoints the district with the highest prevalence rate for dengue and the neighboring districts that also have high risk, allowing government agencies and communities to take the necessary precautions to mollify the risk effect of DF.

Transforming abandoned petroleum wells in the Nigerian sector of the Chad basin into triplet borehole heat exchangers for sustainable power generation

This study pioneers a transformative approach to sustainable energy recovery, repurposing abandoned petroleum wells in the Nigerian Chad Basin as a triplet-deep closed-loop heat exchanger. We employed a computational numerical approach to designed two deep closed loop systems, which share a common production well, and to evaluate the thermal performance as well as its sustainability over a period of 25 years. The geometrical configuration consists of two injection wells, which converge to the common production one doubling the flow rate at surface and minimising the heat loss during the ascent of the fluid. The availability of detailed abandoned well specifications enabled us to constrain three-dimensional geological and thermal models of the undisturbed underground and, subsequently, to simulate numerically the production temperature and the thermal disturbance in the surrounding rocks. A comprehensive sensitivity analysis optimized the best operational design for total recovered thermal energy and uninterrupted heat recovery. When the deep close loop heat system operates with a fluid circulation rate of 0.03 m³s⁻1 and an injection temperature of 20 °C, it sustains a production temperature of over 100 °C, which generates total recovered thermal energy of 9730 TWth and 817 TWe over 25 years (9000 days). The average annual thermal and electricity productions of 389 TWth and 33 TWe, respectively, are more than the demand of the entire population of Magumeri district. The study's findings offer practical implications for policymakers, industry stakeholders, and local communities, emphasising the potential for socio-economic development while fostering environmental stewardship in the Nigerian Chad Basin.

Enhancing computational thinking and spatial reasoning skills in gamification programming learning: A comparative study of tangible, block and paper‐and‐pencil tools

AbstractTangible programming tools have become a mainstream teaching aid in gamification programming learning (GPL) due to their interactivity and ability to enhance novice learners' computational thinking and spatial reasoning skills. However, comparing the relative efficacy of different programming tools that simultaneously support these skills was not adequately explored. This study designed and evaluated three programming tools: the tangible programming tool (TPG), which uses real touchable objects; the block programming tool (BPG), which employs virtual programming blocks and 3D game scenarios; and the paper‐and‐pencil programming tool (PPG), which uses paper and pen to draw. The study involved 112 seventh‐grade students from three natural classes: Class A (TPG, n1=37), Class B (BPG, n2=38), and Class C (PPG, n3=37). These students completed four gamification programming tasks and CT skills, spatial reasoning skills, enjoyment, cognitive load and GPL task list measurements. The results indicated that the tangible programming tool led to lower cognitive load, significant improvement in spatial reasoning skills and better abstraction and problem decomposition skills. The block programming tool provided a more enjoyable experience and facilitated students' algorithm design and efficiency. The paper‐and‐pencil programming tool was found to be less effective in improving spatial reasoning skills. This study's findings can help programming educators cultivate students' thinking skills and improve their learning experience by effectively selecting the most appropriate programming tools.

Determinants of the Qualities of Diplomats in African Countries in the Western Context

This article undertakes a comprehensive exploration of the historical evolution of diplomacy in African countries within the Western context, scrutinizing traditional practices, post-colonial transformations, and the enduring impact of milestones like the struggle against apartheid. While diplomacy in this context is vital for international cooperation, economic partnerships, and the projection of national interests, there persist gaps in understanding the determinants shaping diplomats' qualities.The study addresses these gaps by thoroughly examining cultural factors, the impact of educational qualifications, the role of professional experience, and the influence of political challenges on diplomatic effectiveness. Through qualitative methodologies, including purposive sampling and thematic analysis, the research strategically selects cases aligned with the specific focus on diplomatic qualities, ensuring relevance and depth in exploring the nuances of diplomatic effectiveness.Secondary sources, such as academic literature, historical documents, and theoretical frameworks, play a crucial role, contributing to a comprehensive exploration of the subject matter. The combination of purposive sampling and thematic analysis, supported by secondary sources, enhances the robustness of the research design, facilitating a nuanced investigation into the determinants shaping diplomatic effectiveness.The determinants of diplomatic qualities, explored through cultural factors, educational background, and professional experience, offer a holistic understanding of how African diplomats navigate international diplomacy successfully. The study's findings contribute to a robust foundation for policymakers and practitioners to enhance diplomatic strategies, training programs, and educational curricula, ensuring the continued effectiveness of African diplomats in the Western context. Overall, this research provides valuable insights that can inform diplomatic practices, training initiatives, and educational approaches to meet the evolving demands of the African-Western diplomatic landscape.

Financing the future: Asymmetric association between green investment and electric vehicles

Green investment in electric vehicles represents a pivotal shift towards a sustainable future, promising to revolutionize our transportation systems while significantly reducing greenhouse gas emissions. This research aims to probe the linkage between green investment and electric vehicles across the top 10 economies with the highest electric vehicle adoption rates (China, USA, Norway, Germany, UK, France, Portugal, Netherlands, Belgium, and South Korea). Unlike earlier studies that primarily utilized panel data methods and overlooked the individual nuances of each country, our investigation employs the advanced ‘Quantile-on-Quantile’ technique. This novel approach enables us to delve into the relationships between variables within each specific country, thereby improving the precision of our analysis. As a result, this study provides a comprehensive global viewpoint, revealing nuanced findings about each nation's distinct characteristics. The study's findings express a positive connection between green investment and the electric vehicle stock in various segments of the sample economies. Furthermore, this research highlights diverse trends in these connections within different nations. The results emphasize policymakers’ need to conduct comprehensive evaluations and develop effective strategies to address changes in both green investment and electric vehicles.