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
Dyslexia is a specific learning disorder associated with persistent difficulties in accurate and fluent word recognition, decoding and spelling. Early identification can support timely educational intervention, but conventional assessment may be resource-intensive and computational prediction models may introduce an additional challenge: highly accurate machine-learning models can be difficult for educators and other stakeholders to interpret. This study develops an explainable ensemble machine-learning framework for early dyslexia detection using behavioural learning data. The study uses the supplied Dyt-desktop dataset containing 3,644 observations, 196 predictors and 392 dyslexia-positive observations. Random Forest (RF), XGBoost and Extra Trees (ET) were evaluated using stratified five-fold cross-validation, followed by Random-Forest Recursive Feature Elimination (RF-RFE) and probability-level logistic-regression stacking. The empirical results show that XGBoost was the strongest base learner, obtaining 90.64% accuracy, 29.08% recall, 40.07% F1-score, 0.8845 ROC-AUC and 0.3912 Matthews Correlation Coefficient (MCC). RF-RFE + XGBoost improved performance to 90.81% accuracy, 31.89% recall, 42.74% F1-score, 0.8858 ROC-AUC and 0.4122 MCC. The proposed heterogeneous stacking ensemble produced the highest recall (71.17%), F1-score (51.71%) and MCC (0.4644), although its accuracy decreased to 85.70%. The findings demonstrate that ensemble learning can substantially improve sensitivity-oriented dyslexia screening. However, because interpretability is essential when predictive outputs may influence educational decisions, the study proposes SHAP-based global and local explanations as an explainability layer for the validated ensemble architecture. The work therefore contributes an empirically grounded framework combining predictive performance, feature reduction and explainability, while recognizing that machine-learning predictions should support rather than replace professional dyslexia assessment
This research investigates the impact of digital marketing and destination competitiveness on selected tourist destinations of Southeastern Nigeria, which are: the National Museum of Unity, Centre for Memories, Akwuke Sand beach, Enugu Golf Course, Opi Lake System and Awhum waterfall. With the increasing reliance on digital platforms for marketing purposes, especially in the tourism industry, it is crucial to understand how these digital platforms affect tourist destinations in Enugu state. Analyzing the effectiveness of digital marketing techniques such as social media campaigns, search engine optimization, and website optimization, this study has provided valuable insights into how Enugu State tourism stakeholders can leverage digital tools to enhance its tourism sector. The study employed mixed method approach through a combination of qualitative and quantitative research methods, including surveys and interviews with key stakeholders, this study sought to identify the strengths and weaknesses of the digital marketing practices employed in the selected destinations and recommend strategies for improvement. The findings of this research contribute to the existing body of knowledge on digital marketing in the tourism industry and provide practical recommendations for policymakers, marketers, and tourism operators in Enugu State, Nigeria.
Kenya’s healthcare sector is rapidly digitizing, with hospitals increasingly adopting electronic medical records (EMRs) and AI-driven diagnostic systems. While these innovations enhance efficiency and clinical outcomes, they also introduce significant risks to patient data privacy. This study investigates the optimal parameters for a secure hybrid deep learning model that integrates convolutional neural networks (CNNs) and recurrent neural networks (RNNs) with cryptographic protocols. To ensure methodological rigor while avoiding bias from real data exposure, a simulated tensor dataset was generated using Torch seeding (seed = 42). The CNN–RNN model served as the experimental environment for protocol evaluation, without direct training on the dataset. Each privacy protocol was applied under controlled conditions, and performance metrics were recorded. The benchmark assessment considered five distinct secure multi-party computation (MPC) protocols: SPDZ, Garbled Circuits, Oblivious Transfer, Shamir’s Secret Sharing, and Fully Homomorphic Encryption (FHE). Results demonstrate that SPDZ, combined with differential privacy, achieves robust security while maintaining predictive performance. The findings established a parameter framework that balances utility and privacy, forming the foundation for subsequent preprocessing and model design using the CBIS‑DDSM dataset for patient data privacy models.
This study analyzes a negotiation case between a Brazilian distributor of orthopedic products and its multinational supplier during the COVID-19 health crisis. The sudden and unexpected suspension of elective surgeries, typical of the healthcare sector, enabled testing of recent Brazilian scholarship on negotiation while applying negotiation theory in a scenario in which the interests of both parties, in conflict, had to be balanced to preserve a long-term commercial relationship. The negotiation became a true test of integrative negotiation strategies, rooted in crisis management and successful negotiation in business relationships, using strategies such as empathy, assertiveness, and credibility. This article furthers negotiation studies by examining crisis negotiations within the scope of integrative bargaining and relational contracting.
The telecommunications industry continues to experience rapid technological and regulatory changes that require effective change management to sustain organizational performance. However, existing studies have largely examined change management practices in isolation, with limited empirical evidence on the effect of leadership practices in change management within the Kenyan telecommunications context. This study therefore examined the influence of leadership practices in change management on organizational performance at Telkom Kenya Limited. The study employed a cross-sectional research design targeting 116 top management personnel across Telkom Kenya’s four regional branches: Nairobi, Mombasa, Kisumu, and Nakuru, from which a sample of 90 respondents was selected using stratified random sampling. A structured questionnaire was used to collect data. Data analysis employed descriptive and inferential statistics using SPSS version 29. The study found that leadership practices had a positive influence on organizational performance (β = 0.613, p < 0.001). The study concluded that leadership practices in change management significantly enhance organizational performance in the telecommunications sector. It is recommended that Telkom Kenya and similar organizations strengthen leadership practices in change management by implementing a formal Leadership Behavioural Accountability Framework and establishing departmental change advisory committees at all business units.
This study explores knowledge, awareness and lifestyle behaviors related to cancer in a sample of undergraduate students. Data were collected through a self-administered questionnaire. 303 students were participating to this study. The majority of participants had a good level of knowledge on most risk factors for cancer. Medical students having received information about cancer prevention from the college curriculum, have good knowledge about the risk factors for cancer. 89.9% of participants believe that the fruit and vegetable can improve the health and prevent cancer, and 84.5% reported the important role of physical activity in reducing the risk of cancer. About the knowledge of the effect smoking cessation on reducing the risk of cancer, only 19% of medical students select the right answer. Also there is a need to increase the awareness about the types of food that has role in developing cancer, and the types of cancer caused by alcohol. There is relevance in providing information/education on cancer risk factors to increase knowledge in the prevention of cancer. This study highlights a need for improved education/information about cancer prevention and lifestyle cancer-related behaviors.
Latar belakang penelitian ini didasarkan pada pemahaman bahwa warna dalam film animasi tidak hanya berfungsi sebagai elemen estetika visual, tetapi juga sebagai sistem tanda yang memiliki kemampuan untuk menyampaikan makna simbolik, emosional, dan kultural kepada penonton. Film animasi Jumbo produksi Visinema Pictures menampilkan penggunaan warna yang kuat dalam membangun suasana, mempertegas karakter tokoh, serta memperkuat pesan naratif yang disampaikan melalui bahasa visual. Oleh karena itu, penelitian ini bertujuan untuk menganalisis makna warna yang digunakan dalam film animasi tersebut serta bagaimana warna berfungsi sebagai tanda visual dalam membangun makna cerita. Penelitian ini menggunakan pendekatan kualitatif dengan metode analisis semiotika untuk mengkaji warna sebagai sistem tanda yang merepresentasikan emosi, kondisi psikologis tokoh, serta nilai-nilai sosial dan budaya yang terkandung dalam film. Data penelitian diperoleh melalui analisis terhadap adegan-adegan dalam film yang menampilkan penggunaan warna secara signifikan dalam mendukung penyampaian pesan visual. Hasil penelitian menunjukkan bahwa penggunaan warna dalam film animasi Jumbo tidak hanya berfungsi sebagai unsur estetika, tetapi juga sebagai simbol visual yang memperkuat atmosfer cerita, menggambarkan dinamika emosional tokoh, serta menyampaikan pesan moral dan nilai budaya kepada penonton secara lebih mendalam.
The study aimed to assess the effectiveness of accounting information as a tool for management decision-making at Harlequin International Ghana Limited. The study revealed a strong, positive relationship between accounting information and effective management decision-making. This indicates that the availability and quality of accounting information significantly enhance the ability of managers to make informed decisions. Managerial experience was found to have a statistically significant and positive impact on decision-making effectiveness. Managers with more experience were better able to interpret and utilize accounting information. The regression model showed that managerial experience positively moderates the relationship between accounting information and decision-making. Experienced managers derive greater benefit from accounting information, enhancing the effectiveness of their decisions. These findings confirm that accounting information plays a vital role in organizational success and that its utility is maximized when interpreted by experienced professionals. The study concludes that accounting information is an indispensable resource for effective managerial decision-making at Harlequin International Ghana Limited. Its contribution is not only significant but is also enhanced when interpreted by experienced managers.
Women diagnosed with breast cancer usually experience moderate to severe psychological symptoms, along with the perception that mirrors the belief that their lives are about to end. Given that this population is more likely to suffer from mental health disorders such as anxiety, depression, and post-traumatic stress disorder (PTSD), stress can be considered among the most com-mon emotions experienced by this population. The current study aims to evaluate the relationship between stress coping strat-egies dimensions and death anxiety among women diagnosed with breast cancer compared with women with no cancer. using mixed methodology. 10 female adult patients from Hassan II university hospital in Fes, Morocco were included in the study. These participants were assessed through clinical interview, brief cope inventory, and death anxiety scale. Regarding the study results, women diagnosed with breast cancer sowed moderate to severe levels of death anxiety, and besides that, death anxiety was significantly associated with certain psychological stress coping strategies among women diagnosed with breast cancer, and more particularly emotion-centered strategies (strong correlation with religion item), while women with no cancer showed mild to moderate levels of death anxiety, and no significant association between specific psychological stress coping strategies and death anxiety was shown.
Abstract
Livestock housing and ranch infrastructure in Nigeria remain, for the most part, informally constructed and poorly adapted to local climatic conditions, a gap that has direct consequences for animal welfare, productivity and long-term facility durability. This paper presents an architectural design framework for a sustainable cattle ranch developed for Ugwolawo, Ofu Local Government Area, Kogi State, derived from a qualitative case-study methodology combining site investigation, climatic analysis and comparative review of local and international ranch precedents. The paper articulates a functional zoning strategy comprising grazing land, freestall housing, residential quarters, and slaughter/milking facilities; details planning data and an indicative schedule of accommodation; and proposes climate-responsive construction and environmental management measures suited to the area's semi-equatorial climate. Findings indicate that facility design decisions — including stall dimensioning, natural ventilation, orientation, and waste management infrastructure — exert a measurable influence on cattle comfort, herd health and operational sustainability, and that these considerations are frequently under-addressed in existing Nigerian ranch and barn developments. The paper concludes with design recommendations intended to guide future livestock facility development in comparable tropical, semi-rural settings.
Keywords: sustainable architecture; livestock housing; ranch design; climate-responsive design; freestall facility; Kogi State
This study assesses major pollutants in Ilaje and Ese-Odo Local Government Areas of Ondo State, Nigeria, to establish baseline data for future environmental monitoring. Prompted by inadequate government policies and weak pollution-health management systems, the research aims to reduce disease burdens in riverine communities through robust laboratory analysis. The methodology employs scientific environmental and medical laboratory testing to determine pollution damage and identify pollutant-induced health risks. Key findings reveal significant concentrations of various metals and minerals across ten mapped communities, directly linking pollution to public health concerns. The study concludes that strategic alliances between environmental and medical laboratories are essential for targeted interventions. It recommends public sensitization, stakeholder training, adoption of international best practices, and private investment in laboratory infrastructure to enhance revenue and sustainability. These actions are critical for effective pollution management and improved health outcomes in the region.
Keywords: Pollution, pollutants, health management systems, government, laboratories, public sensitization, metals, minerals.
This article examines the legal and regulatory conflicts arising from the proposed integration of blockchain-based bidding systems into Nigeria's public procurement framework. While blockchain technology offers unprecedented transparency and immutability for contract award processes, its implementation faces significant constitutional and statutory hurdles. The article analyzes tensions between the decentralized, self-executing nature of smart contracts and the discretionary powers vested in procurement officials under the Public Procurement Act 2007, the constitutional principles of administrative justice, and the evolving regulatory framework of the National Information Technology Development Agency (NITDA). Drawing on institutional theory and empirical studies of blockchain adoption in developing economies, the article argues that technological benefits cannot be realized without fundamental legal framework reconciliation. It proposes a hybrid governance model that preserves constitutional safeguards while enabling blockchain efficiency, contributing to the emerging discourse on digital transformation in African public procurement systems.
Keywords: Block-chain, Public Procurement, Nigeria, Smart Contracts, Constitutional Law, NITDA, Public Procurement Act, Administrative Justice
ABSTRACT
This paper describes the implementation of a scalable, cloud-managed Voice over IP (VoIP) system across the multi-campus environment of the University of Lagos, Nigeria. Using Huawei's Hybrid Power Cloud (HPC) platform, the deployment connects the main Akoka campus and the Idi-Araba College of Medicine campus via existing 10G fibre-optic infrastructure. This implementation meets the critical communication needs between key administrative offices and serves as a model for expanding the system across the institution. Results show notable improvements in internal communication efficiency, cost savings, and operational flexibility. The system is designed to scale from an initial 4 phones to over 400 devices without needing changes to the structure.
Keywords: VoIP, Cloud Computing, Multi-Campus Communication, Huawei HPC, University ICT Infrastructure, Scalable Deployment
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