Peer-reviewed international research papers published open-access with EOI assignment and global indexing across engineering, computer science, environmental science, social sciences, and more.
This research paper examines the transformation of the Taliban’s Policy on the cultivation of opium. It expresses that their active involvement regarding opium cultivation and trading turned into a prohibition policy after this group seized power in August 2021, Afghanistan. The purpose of this study is to reveal that, historically, opium cultivation and the trading of illegal drugs had a very crucial impact on the livelihood of people, the revenue and tax system, and economic development in Afghanistan. A systematic literature review method is used in this research paper to analyze relevant studies. The research paper also depicts that the Taliban’s involvement in illegal drugs was due to their economic necessity, maintaining control of various parts of the country, and other political opportunities and reasons. However, when they seized power, almost one year later, in April 2022, the Taliban altered their policy from supporting opium cultivation and trading to prohibiting it. Several reasons were behind the motivation for the Prohibition of opium cultivation and drug trafficking, such as the immediate and long-term political and economic consequences and international factors. It is necessary to recognize the limitations of this study, which has limited access to reliable data. In conclusion, the study highlights that policy has detrimental impacts on Afghanistan's economic development.
RESUMO
O propósito deste trabalho é analisar a implementação da Agenda 2030 – Os Objetivos de Desenvolvimento Sustentável – ODS, assinada em 1.º de janeiro de 2016, após a Agenda Pós-2015, pelos 193 Países-membros da Organização das Nações Unidas – ONU, tendo como prazo final para sua execução a data de 31 de dezembro de 2030. Além da questão analítica central, busca-se constatar as mazelas sociais históricas transformadas em Objetivos e Metas Globais, apontar os desafios das Nações para a efetivação desse compromisso histórico, identificar as responsabilidades da Administração Pública, representada por Agentes Políticos e Agentes Públicos, da Iniciativa Privada e da Sociedade, e corroborar, por meio da concretização desse desafio mundial, o futuro do planeta. Essa Agenda Global é composta por 17 Objetivos e 169 Metas, além do 18º Objetivo, proposto pelo Governo Brasileiro em setembro de 2023, e seus propósitos centram-se em três pilares do desenvolvimento sustentável: crescimento econômico, inclusão social e proteção ao meio ambiente, abrangendo temas fundamentais como erradicação da pobreza, saúde pública, educação, igualdade de gênero, igualdade étnico-racial, combate às mudanças climáticas, consumo responsável e fortalecimento das instituições democráticas. Para a discussão temática, foi realizada pesquisa qualitativa que, por meio do método histórico-dedutivo, utilizou-se de pesquisa bibliográfica para análise da execução da Agenda 2030 e sobre o futuro do Planeta.
ABSTRACT
Economic hardship is an increasingly important challenge for students in Nigerian tertiary institutions, with potential implications for their academic engagement, psychological well-being, and ability to meet basic educational needs. This study examined students' experiences of economic hardship and its perceived influence on academic performance at Kaduna State College of Education, Nigeria. Guided by Conservation of Resources (COR) Theory, the study adopted a convergent mixed-methods design, combining quantitative questionnaire data with qualitative responses to open-ended questions. Data were obtained from 16 students using a structured questionnaire comprising 24 valid five-point Likert-scale items and open-ended questions addressing economic challenges, academic experiences, coping strategies, and institutional support. Quantitative data were analyzed using frequencies, percentages, means, standard deviations, Cronbach's alpha, and exploratory Spearman's rank-order correlations, while qualitative responses were analyzed using reflexive thematic analysis. Findings indicated a moderate level of economic hardship among participants (M = 3.01, SD = 0.91). Thus, accommodation (M = 3.38, SD = 1.41) and feeding expenses (M = 3.31, SD = 1.49) emerged as the most prominent financial challenges. Qualitative findings highlighted five themes: multidimensional resource shortages, academic disruption and competing demands, psychological and cognitive burden, resource mobilization and coping, and the need for responsive institutional support. The findings suggest that economic hardship extends beyond financial insufficiency to affect students' educational resources, time, concentration, and academic participation. Consistent with COR Theory, students employed various strategies to protect or acquire resources, although some coping strategies created competing academic demands. The study recommends strengthened student financial-support mechanisms, accessible scholarships and bursaries, and skills-development .
Cassava and its processed foods are consumed by over one billion people across the globe, including Argungu Town, due to its high carbohydrate and energy contents. However, these products contain a very dangerous and life threatening chemical compound called hydrocyanic acid (HCN), which when ingested above a threshold limit can be detrimental to humans. Current study investigated ten (10) different cassava products consumed around Argungu town, to determine their levels of cyanide content. The samples were used as purchased, fermented for 36 hours, filtered then titrated against AgNO3 solution. Raw Cassava tubers, Dry White gari and Dry Yellow gari samples recorded the highest HCN contents (mg/kg) of 15.70 ± 0.4, 13.01 ± 0.2 and 12.78 ± 0.4, respectively, while the rest of the seven samples recorded an average of 9.66 ± 0.5. The result revealed that, except for the first three samples, the levels of HCN in the remaining seven sample cassava products evaluated falls within the 10 mg HCN /kg safety limit recommended by the Food and Agriculture Organization (FAO), World Health Organization (WHO), and the Codex Alimentarus (Codex). Resulting cyanide contents of all the samples were attributed to the influence of the processing methods, suggesting the need for constant and periodic evaluation of these products to enhance their safety.
Ebola virus disease (EVD) remains a recurrent health security threat in and around the East African Community (EAC), especially because of cross-border population movement, fragile health systems, and repeated viral haemorrhagic fever alerts linked to eastern Democratic Republic of the Congo. The current Bundibugyo virus disease outbreak centred in DRC, with spillover into Uganda and elevated risk across neighbouring EAC Partner States, demonstrates both the scale of the regional challenge and the importance of timely detection, coordinated response, and digitally enabled surveillance. This article examines how eHealth and telemedicine can strengthen Ebola preparedness, surveillance, diagnosis, case management, and continuity of essential health services in the EAC region. It argues that the EAC’s growing digital and laboratory assets, especially the mobile BSL-3/4 la-boratory network and emerging digital border-health measures, can be integrated into a wider regional strategy for epidemic intelligence and resilient service delivery. Evidence from West Africa and Nigeria further shows the practical value of mobile health tools, digital contact tracing, teleconsultation, and emergency health information systems during Ebola outbreaks, while also warning against fragmented and pilot-driven deployment. The article concludes that the EAC should treat Ebola not only as a recurring emergency but also as a policy window for building interoperable, ethical, and scalable digital health systems that support both outbreak response and long-term health system resilience.
In the modern era of AI, technology or CALL, MALL is the major source of knowledge. The swift digital transformation of education has profoundly altered pedagogical practices, teacher roles and professional identities across global English Language Teaching (ELT) contexts. The expansion of digital education and post-pandemic technology-mediated instruction has led to unprecedented sociocultural, technological and pedagogical transitions for English teachers in Nepal, particularly in government schools. This study investigates the reconstruction of professional identity of English teachers at government schools in Nepal through engagement with digital pedagogy. Using a qualitative narrative inquiry design guided by Sociocultural Theory, Communities of Practice, and the Technological Pedagogical Content Knowledge (TPACK) framework, the study investigates teachers’ lived experiences, identity negotiations, and pedagogical transformations.
Data were generated from ten English teachers in government schools in rural and urban educational contexts, through in-depth semi-structured interviews, reflective narratives, classroom observations and digital teaching artefacts. The results show how the teachers negotiated and reconstructed their professional identity in a constant movement from traditional knowledge transmitters to digitally mediated facilitators of learning. The study also shows that the digital pedagogy transformed the teachers’ classroom authority, professional agency, pedagogical beliefs, emotional experiences, and self-perception as English language educators.
Manual interpretation of computed tomography (CT) images for renal abnormalities is time-consuming and subject to inter-observer variability, motivating automated computer-aided diagnosis. This study directly compares two machine learning paradigms for multi-class classification of kidney CT images (Normal, Cyst, Tumour, Stone) on the public CT-KIDNEY-DATASET: (i) end-to-end fine-tuning of five ImageNet-pretrained convolutional neural network (CNN) backbones — DenseNet121, ResNet50, VGG16, InceptionV3, and EfficientNetB0 — and (ii) a frozen DINOv2 ViT-B/14 embedding pipeline in which four Optuna-tuned classical classifiers (Logistic Regression, SVM, Random Forest, XGBoost) are trained on 768-dimensional embeddings after SMOTE-based class balancing. On a properly deduplicated 11,929-image corpus, VGG16 was the strongest CNN, reaching 99.75% test accuracy and 0.9969 macro-F1. All four DINOv2-based classifiers exceeded 99% test accuracy, with SVM reaching a perfect 1.0000 score; however, forensic inspection of the notebook execution trace showed that the deduplication step in this second pipeline was authored but never executed, so its splits were drawn from a non-deduplicated 12,446-image pool independently confirmed to contain 517 exact-duplicate files. This near-perfect result is therefore assessed as most plausibly explained by train/test duplicate leakage rather than genuine generalization, and is reported with that explicit caveat. The study's principal contributions are a like-for-like comparison of CNN fine-tuning against frozen self-supervised embeddings on a shared renal CT dataset, and a concrete, evidence-based demonstration of how near-perfect medical-imaging benchmark scores should be audited for leakage before being accepted as genuine diagnostic evidence.
Malaria remains a leading cause of morbidity and mortality in sub-Saharan Africa, and Nigeria continues to carry the largest national share of the global burden. This study assessed the prevalence of Plasmodium falciparum malaria infection and the level of community knowledge, attitude, and practice (KAP) regarding malaria among patients attending General Hospital, Ilorin, Kwara State, Nigeria. A hospital-based cross-sectional survey was conducted between October 2021 and February 2022 among 380 respondents, combining a structured knowledge-attitude-practice questionnaire with microscopic examination of Giemsa-stained thick and thin blood films. The overall prevalence of P. falciparum infection was 45.8% (174/380). Infection was highest among children under five years (accounting for 49.4% of all positive cases) and was marginally higher among males (47.1%) than females (44.8%), though the difference was not statistically significant. Awareness that malaria is mosquito-borne was high (76.1%), and 96.8% of respondents knew malaria could be transmitted from an infected to a healthy person; however, reported use of insecticide-treated nets (ITNs) was low (23.7%). Respondents' biomedical knowledge of malaria (χ² = 22.471, p < 0.001) and prior exposure to health education (OR = 0.463, 95% CI: 0.232–0.910, p = 0.031) were significantly associated with reduced odds of infection. The findings confirm that malaria remains holoendemic in this part of North-Central Nigeria and that gaps in preventive practice, particularly low ITN utilization, persist despite generally good disease awareness. Sustained health education and improved access to, and consistent use of, insecticide-treated nets are recommended to reduce the burden of malaria in the study area.
SHA-256 (Secure Hash Algorithm 256 bits), a member of the SHA-2 family developed by the United States National Security Agency (NSA) and standardized by the National Institute of Standards and Technology (NIST), has become one of the most widely used cryptographic mechanisms in contemporary information security. This article presents a narrative review of how SHA-256 works, its main applications — password protection, file integrity verification, message authentication, digital signatures, and support for blockchain structures — and its robustness against cryptanalytic and brute-force attacks. The inadequacy of plain SHA-256 for password storage is discussed, given its processing speed, alongside the superiority of functions such as bcrypt, scrypt, and Argon2 for that specific use case. Finally, the article examines the threat posed by quantum computing, analyzing NIST's position on SHA-256's resilience against Grover's algorithm, as well as its structural role in the SLH-DSA post-quantum signature scheme (FIPS 205), finalized in 2024. It is concluded that SHA-256 remains secure for most current applications, but that its use must be contextualized according to use case, and that its underlying mathematical properties — collision and preimage resistance — remain relevant even in the design of new post-quantum standards.
Accurate land cover classification is crucial for the sustainability of urban planning, environment monitoring, and resource management within cities that are developing at a rapid pace. Traditional methods of land cover classification are known to fail in the representation of heterogeneous land covers and usually result in low interpretability of prediction results. The current paper introduces an explainable multi-source machine learning approach to land cover classification by means of GIS and remote sensing data, where the study site is Lugbe, Abuja, Nigeria. Multi-spectrum images from Sentinel-2 satellites were combined with topographical attributes (elevation, slope, and aspect), population density, and spectral indexes such as NDVI, NDBI, MNDWI, BSI, and SAVI. Four ensemble learners (Random Forest, XGBoost, LightGBM, and CatBoost) have been used together with GridSearchCV hyperparameter tuning. To facilitate the separation between the classes, spectrally similar vegetation classes were consolidated before training. In terms of validation accuracy, the optimized LightGBM model secured the highest value and is quite efficient when it comes to having the least training time. Using the SHapley Additive exPlanations (SHAP), the variables NDVI, population density, and NDBI were found to be highly correlated with the prediction results. With spatial prediction, the generated land cover map indicated vegetation to be the highest class with 37.55%, built-up 25.52%, cropland 14.49%, trees 12.26%, and bare land 10.18%.
The rapid expansion of Internet of Things (IoT) networks has intensified the need for identity management systems that can
authenticate devices, protect privacy and maintain trust without depending on vulnerable centralized authorities. This paper
presents a lightweight blockchain-based security protocol framework for decentralized identity management in IoT networks.
Drawing on a mixed-methods dissertation study involving 92 valid responses from IoT administrators, developers, blockchain
experts and industry practitioners, the article identifies the dominant weaknesses of current identity models, including
unauthorized access, data privacy exposure, weak device authentication, single points of failure and scalability constraints. The
study shows strong support for decentralized identity management, but also confirms that blockchain adoption remains limited
by integration complexity, latency, energy consumption, device resource constraints and lack of standardization. In response, the
paper summarizes the proposed MobiChain IoT Identity Framework, a layered architecture that uses decentralized identifiers,
verifiable credentials, edge-assisted verification, consortium blockchain anchoring, lightweight consensus, off-chain sensitive
attribute storage, scoped capability tokens and blockchain-logged revocation. The article argues that blockchain should function
as a selective trust, verification and audit layer rather than as a heavy fully on-chain identity system. The framework offers a
practical pathway for improving IoT identity security while preserving scalability, interoperability and privacy.
Keywords: Blockchain, Internet of Things, decentralized identity management, IoT security, self-sovereign identity, verifiable credentials,
privacy-preserving protocols, edge-assisted verification.
Objective: This study sought to establish the effect of operational repositioning on the performance of insurance companies in Nairobi City County, Kenya
Methodology: The study was anchored on the Resource-Based View Theory and adopted a descriptive research design. The target population comprised 336 management employees from 56 insurance companies in Nairobi City County. A sample of 179 respondents was selected using stratified random sampling and Krejcie and Morgan’s sample size determination formula. Primary data were collected using structured questionnaires. Data were analyzed using descriptive statistics, Pearson correlation analysis, and simple linear regression analysis at a 95% confidence level. Of the 179 questionnaires administered, 163 were completed and returned, representing a response rate of 91.06%.
Key Findings: The findings established a strong positive and statistically significant relationship between operational repositioning and organizational performance (r = 0.740, p < 0.001). Regression analysis further showed that operational repositioning significantly influenced organizational performance, explaining 54.8% of the variation in performance (R² = 0.548, p < 0.001).
Conclusion: The study concludes that operational repositioning has a positive and significant effect on the performance of insurance companies. The study recommends continuous realignment of operational strategies, improvement of cost efficiency, and appropriate expansion or contraction of operations to enhance organizational performance.
This study analyzes the applicability of Building Information Modeling (BIM) technology as a catalyst for modernization in small-scale design and construction projects. In the contemporary construction industry, digitalization is no longer exclusive to large-scale infrastructure; rather, it has become a necessity for the survival of small firms and contractors. Utilizing a qualitative and analytical approach grounded in a comprehensive literature review and technical standards—such as the Brazilian BIM BR Strategy and related ISO standards—this research evaluates comparative scenarios between traditional CAD-based methods and collaborative BIM workflows. Particular emphasis is placed on the reduction of clash detection errors, precision in quantity surveying, and project schedule control. Consequently, a scalable BIM Implementation Plan is structured, demonstrating that the integration of three-dimensional models minimizes material waste and enhances financial predictability. Ultimately, this study consolidates BIM technology as a fundamental pilar of governance and competitiveness within the small-scale residential and commercial sectors.
Abstract
Background: The quality and competence of the nursing workforce are essential determinants of patient safety, quality of care, and hospital performance. Recruiting nurses with advanced educational preparation and relevant clinical experience may enhance clinical decision-making and reduce preventable errors associated with insufficient knowledge and limited clinical exposure.
Aim: This paper aims to examine the impact of recruiting highly qualified and experienced nurses on hospital performance, patient safety, quality of care, and the reduction of nursing errors associated with inadequate clinical competence and experience.
Methods: A narrative review of scientific literature was conducted to examine evidence related to nurse education, clinical experience, nursing skill mix, staffing, competency, and patient outcomes. Relevant systematic reviews and observational studies were considered to identify relationships between nursing workforce characteristics and patient-safety outcomes.
Results: Evidence indicates that higher levels of nurse educational preparation and an appropriate registered-nurse skill mix are associated with improved patient outcomes, including lower mortality and failure-to-rescue rates. Experienced nurses may contribute through stronger clinical judgment, early recognition of patient deterioration, effective communication, mentoring, and implementation of evidence-based practices. However, years of experience alone do not consistently predict fewer adverse events, highlighting the importance of demonstrated competency rather than seniority alone.
Conclusion: Hospitals should implement competency-based recruitment strategies that integrate educational qualifications, specialty-specific experience, clinical competence, professional development, and patient safety skills. Investing in a highly competent nursing workforce can contribute to safer care, improved clinical outcomes, and stronger organizational performance when combined with supportive leadership, and a positive practice environment.
This study explored and analyzed the effects of administrative directives issued by the Schools Division of Maguindanao del Norte on the teaching effectiveness of its elementary and secondary school teachers. Grounded in the Instructional Leadership Theory and guided by the principles of quality assurance and policy implementation, the research recognized that strong administrative support and clear policy guidance are critical for instructional quality. The study assessed how various administrative mandates affect teachers’ performance in the classroom, acknowledging their core contribution to student learning outcomes and system functionality.
Specifically, the study aimed to determine the extent of implementation of administrative directives in terms of Instructional Mandates (e.g., curriculum supervision, assessment protocols) and Administrative Burden (e.g., reporting, documentation). It also evaluated the current level of teaching effectiveness among teachers based on key indicators from the Philippine Professional Standards for Teachers (PPST) such as instructional strategies, classroom management, and student engagement. Additionally, the research analyzed the relationship between the practice of administrative directives and the resulting level of teaching effectiveness.
The findings revealed that while the directives related to Instructional Mandates were positively correlated and supportive of teaching effectiveness, the heavy burden of non-instructional administrative tasks significantly limited optimal performance. Insufficient policy clarity, excessive documentation requirements, and the resulting time constraints were identified as key challenges. The study emphasized the need for continuous policy review, strategic streamlining of administrative tasks, and enhanced instructional leadership support. These measures are essential to mitigate administrative burden and reinforce an environment where teachers can dedicate maximum time and energy to direct classroom instruction in the Schools Division of Maguindanao del Norte.
Keywords: Administrative Directives, Teaching Effectiveness, Maguindanao del Norte
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