ISSN:2320-9186
Impact Factor:4.1
ISSN:2320-9186 Impact Factor:4.1
ABSTRACT Generally, this study aimed to find out the changes using high technological and innovative farming system by having mechanize tool and equipment from old and traditional farming practices among area covering three (3) Municipalities of Maguindanao del Norte particularly the demographic profile of participants, the opportunities that may contribute in terms of socio-economic and the lives improvement from low to high yield crop due to modernization systems and technology in farming. The increase in rice production is also considered to be a big factor in order to lift and get rid from poverty among farmers. A qualitative approach of research was applied using a descriptive method in gathering information. The major findings showed that males were more involved with farming, and the females, however, were also responsive, and likewise, they shared opinions and experiences regarding farming. The ages mostly belonged to 45-58 years old. In terms of educational attainment, the majority were elementary, some were secondary, and the rest were no read no write.
Numerous cases and reports of fraudulent financial transactions continue to increase each year. Modern digital economies in the United States experienced losses exceeding $10 billion in 2023 alone, representing a 14% increase from the previous year (As Nationwide Fraud Losses Top $10 Billion in 2023, FTC Steps up Efforts to Protect the Public, 2024). Traditional fraud detection methods, such as rule-based systems and manual inspections, are inadequate when addressing the evolving sophistication of fraudulent activities. This research investigates statistical and advanced machine learning approaches to enhance fraud detection accuracy and efficiency in financial transactions. This study evaluates seven classification algorithms, Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Trees, and three ensemble methods (Bagging, Random Forest, and Boosting), using a Kaggle dataset containing over 6.3 million financial transaction records. It was hypothesized that the implementation of sophisticated classification algorithms/models and ensemble methods would lead to highly accurate and efficient detection of fraudulent behavior in financial transactions. Additionally, it was predicted that the classification models and ensemble methods would lead to accuracies over 95%. The methodology included comprehensive Exploratory Data Analysis (EDA), rigorous data preprocessing such as outlier removal and feature selection, and model evaluation using three key metrics: accuracy, F1 score, and Area Under the ROC Curve (AUC). The research findings indicated exceptional performance across all models, with accuracies surpassing 99%. The Bagging ensemble method achieved the highest accuracy (99.97%), while SVM excelled across multiple metrics with an average performance of 98.94%. Notably, SVM attained a nearly perfect F1 score of 99.89%, and Random Forest recorded an AUC score of 99.44%. These findings validate the hypothesis and prediction, confirming that statistics and advanced machine learning techniques substantially outperform traditional detection methods. The implementation of these models in financial institutions has the potential to significantly reduce fraudulent transactions, potentially decreasing the hundreds of thousands of annual credit card fraud reports. While minor computational constraints and data loss from missing values may present limitations, this research establishes a foundation for developing more sophisticated fraud detection systems. Future work should explore transformer models and neural networks to further enhance detection capabilities in the evolving landscape of financial fraud and fraudulent transactions.
Despite significant progress in HIV treatment access in Kenya, sustained treatment adherence among married women remains uneven and insufficiently understood from a psychosocial perspective. Married women face unique relational, gendered, and community-level dynamics that shape disclosure, support, stigma, and engagement with care. This study examined factors associated with adherence to antiretroviral therapy (ART) among married women living with HIV in Nairobi County, Kenya. Using a cross sectional survey at the PHDA project in Baba Dogo Health Centre, the study explored socio behavioural and health system variables influencing adherence. Data were collected through questionnaires and interviews and analysed using descriptive and inferential statistics. Results showed statistically significant links between adherence and disclosure of HIV status, presence of a treatment buddy, self esteem, societal attitudes, side effects, dietary requirements, regimen simplicity, and quality of patient–provider communication. Adherence measured by self report was 73.6 per cent at one week, 67.9 per cent at two weeks, and 35.8 per cent at four weeks. The study concludes that supportive relationships, reduced stigma, empathetic healthcare, and user friendly regimens are critical to sustaining adherence. It recommends continued counselling, stigma reduction strategies, and patient centred communication to improve ART outcomes among married women.
This study examined the degree of preparation experienced by law enforcers during their reapplication to the Tri-Bureau, which includes the Philippine National Police (PNP), the Bureau of Fire Protection (BFP), and the Bureau of Jail Management and Penology (BJMP), particularly focusing on the experiences of the law enforcers during their attempts of application that caused them to fail, the interventive preparation carried out by the law enforcers during the reapplication, and the challenges encountered by the law enforcers during the interventive preparations. Using a qualitative phenomenological research design, the study gathered data through semi-structured interviews with selected law enforcers from the Tri-Bureau who had experienced failure in their previous attempts of application and later reapplied. Snowball sampling was employed to select participants who met specific criteria, including prior application failure and successful reapplication or continued pursuit of entry into the Tri-Bureau. The data collected were analyzed and interpreted using thematic analysis. The findings revealed that the experiences of the law enforcers during their attempts of application that caused them to fail were largely attributed to documentary deficiencies, physical unpreparedness, neuro-psychological unpreparedness, unguided application practices, and overall preparation shortfalls. During the reapplication, law enforcers demonstrated improved readiness through interventive preparations such as Document Preparation, Physical Conditioning, Practicing Neuro Techniques, Seeking Guidance and Lifestyle Changes. Despite these improvements, participants continued to encounter challenges during interventive preparation, including procedural hurdles, physical strain, neuro barriers, and financial constraints. The study concludes that preparation for Tri-Bureau recruitment is a progressive and holistic process that extends beyond academic qualifications and requires physical, psychological, administrative, and personal discipline.
This study aims to examine the relationship between working memory and social competence among children with autism spectrum disorder (ASD). The study involved 40 children aged between 6 and 11 years, utilizing various working memory tests, including the Forward Digit Span, Backward Digit Span, Modified Digit Span, and Corsi Blocks Test, alongside a multidimensional social competence scale. The results revealed a strong and statistically significant correlation between working memory and various dimensions of social competence. Based on these findings, the study outcomes can guide future research to explore whether working memory training could positively impact the social competence of this population. Keywords: Working Memory; Social Competence; Autism Spectrum Disorder.
Abstract The stabilisation of Somalia was long maintained as a global public good through a multilateral consensus anchored by the African Union (AU) and funded by Western donors, in particular, the European Union. This framework maintained missions like AMISOM and its successor, ATMIS, by a ‘hub and spokes’ security framework. Nonetheless, this consensus had already fractured by January 2025, giving way to AUSSOM a mission that was representative of a post-multilateral world, where ad-hoc, exclusionary, and transactional alliances defined the world. The inability of the United Nations Security Council Resolution 2719 to provide foreseeable funding triggered a financial and operational crisis making AUSSOM a ‘hollow mission’. At the same time, regional tensions, especially between Saudi-Egypt-Somalia axis and Ethiopia-UAE-Somaliland axis, hijacked the security transition and turned Somalia into a proxy theater in the larger Red Sea-power game. This geopolitical division broke apart the internally Egyptian and Ethiopian elements of the AUSSOM and the internal political operations of the Somalia Federal Government further isolated major elements of the federal states and destabilized counter-insurgency operations. Al-Shabaab capitalized on this turmoil and reclaimed land and reestablished control in the rural management. The paper concludes that until there is a renewed multilateral commitment and regional reconciliation, the AUSSOM will not be championing for state consolidation, but the progressive cantonment of the Somali state. Keywords: Post-multilateralism, AUSSOM, Red Sea geopolitics, Al-Shabaab resurgence, Resolution 2719
The excessive use of plastic packaging sacks, becoming a widespread domestic practice in Goma town of North-Kivu Province in DR Congo, is causing significant environmental degradation and public health problems. These plastic sacks contribute to the accumulation of waste, clog sewers and pollute water sources, providing breading grounds for diseases currying insects. The slow degradation of plastic introduces also micro-plastics into the environment, which can harm wildlife and human health. This study examine the household behaviours related to the domestic use and disposal of plastic sacks, and propose mechanisms for sustainable management of the resulting adverse effects. This study applied a semi-structural questionnaire to collect data from 96 respondents (including households and environmental official workers). The results of this study indicate that 100% of households surveyed use plastic sacks as packaging frequently than other plastics products in their households. Large proportion of respondents (61, 75.3%) indicated that plastic sacks are thrown away in disorder; followed by (16, 19.8%) who attested that unsanitary conditions are caused by plastic waste. 54.3% of respondents attested that households commonly use plastic sacks as packaging. As factors promoting the excessive use, 86.67% of respondents mentioned respectively the proliferation of plastic sacks as packaging with cheaper price on the market and the absence of plastic waste management mechanisms. In order to reduce the harmful effects of packaging plastic sacks in Goma town, 45.7% of respondents recommended that the Congolese Government ban the production and importation of non-biodegradable plastic sacks; 29.6% of respondents showed the need to introduce the use of biodegradable eco-friendly packaging and others encouraged plastic sacks recycling initiatives. The findings also recommended that local authorities should focus on awareness campaigns to popularize the potential environment and health problems associated with plastic sacks and other solid waste. Moreover, the central government should encourage people using biodegradable’ eco-friendly materials as an alternative and adopting legislation making the use of plastic sacks less attractive. Key Words: Practice, excessive use, Plastic packaging, Household, sustainable management, effect.
Adsorption of methylene blue dye from aqueous solution onto chitosan was investigated in a batch wise system. The effect of adsorbent dosage, contact time, initial dye concentration, solution pH and temperature were studied. Results obtained indicated that chitosan could be used as a biosorbent in the treatment of water contaminated with this cationic (methylene blue) dye. The results showed that optimum conditions for removal of 99.2% methylene blue dye were; absorbent dose 12 g, pH of 4, initial dye concentration of 2.5 and 3.5 mg/mL, contact time of 120 minutes and temperature of 50oC. The initial dye concentration had the greatest influence on methylene blue adsorption among other variables. Therefore, chitosan can be used as an efficient and eco-friendly adsorbent for the removal of dye from effluents.
The ability of drilling fluids to work in high pressure, high temperature and contaminated conditions is of great importance to wellbore stability, effective cutting transport and overall operational safety. These extreme states result in nonlinear and transient fluid behaviour which cannot be well represented by more empirical model equations such as Bingham Plastic and Herschel- Bulkley The paper combines a hybrid Gradient Boosted Regression (GBR) and Long Short-Term Memory (LSTM) model with multi-objective optimization to build a machine learning-based framework of drilling fluid property prediction and optimization. The lab measurements of viscosity, yield point, gel strength and fluid loss at different pressures (up to 8000 psi), temperatures (up to 180oC) and concentrations of contaminants (NaCl, CaCl2) were made. The Interquartile Range (IQR) approach was used to eliminate outliers and the features normalized and engineered to represent pressure-temperature interactions and shear history effects. The hybrid GBR+LSTM model showed better predictive accuracy and strength compared to standalone GBR with significant improvements in R2 by 10-15% and significant decreases in RMSE by up to 35% of the key fluid properties. Multi-objective optimization with NSGA-II established the additive and nanoparticle combinations that optimized the viscosity loss, maximized the yield point, and optimized the filtrate loss. The optimized formulation made operational improvements of 23-25% in the barite sag, changes in the equivalent circulating density (ECD) and gel recovery of time over baseline fluids. The use of machine learning-based prediction and optimization methods resulted in significant reductions in the trial-and-error formulation process, reduced operational problems associated with drilling at HPHT conditions, and increased the overall efficiency of the drilling operation. Based on the data analysis, an objective and factual methodology for developing high performance drilling fluids in challenging well conditions was developed.
Introduction : La césarienne est une intervention chirurgicale qui consiste à extraire le fœtus à travers une incision sur l’utérus appelée hystérotomie après une laparotomie [1]. L’objectif était d’étudier les aspects épidémiologiques, cliniques et pronostics de la césarienne au centre de santé de référence de Koutiala du 1er octobre 2022 au 30 septembre 2023. Méthode et matériel : Il s’agit d’une étude transversale descriptive et analytique. Résultats : La fréquence de la césarienne était de 18,7%. L’âge moyen des patientes était de 27 ans avec des extrêmes de 13 ans et 48 ans. Environ 78,3% n’étaient pas scolarisées et 26,3% des paucipares. Selon la classification de Robson, les groupes les plus concernés par la césarienne étaient par ordre de fréquences, le groupe 3 (58,3%), le groupe 1(17,7%) et le groupe 5 (16,3%) (Test de Fischer : p= 0,000). Environ 0,9% des césarisées avaient présentées une complication per-opératoire et 17% en post-opératoire. Le décès maternel représentait 0,5%. Environ 85,6% (695/814) des nouveaux nés étaient vivants à la naissance. La mortalité périnatale était de 16,9% (138/814). Les complications maternelles sont statistiquement plus fréquentes (21,20) lorsque la césarienne était réalisée dans un contexte d’urgence [P=0,01 RR 4,2 IC95% (1,576-8,847)]. Les indications obstétricales absolues étaient significativement associées à la mort fœtale [P=0,000 ; RR 11,449 IC95% (6,080-21,558)]. Conclusion : Le pronostic maternel était marqué par l’anémie (15,8%) et le décès maternel (0,5%). La mortalité périnatale était influencée par le mode d’admission des patientes, le caractère absolu de l’indication et le contexte d’urgence de la césarienne. Les groupes 3, 1 et 5 sont les plus concernés par la césarienne selon la classification de Robson. Mots clés : Césarienne, pronostic materno-fœtale, Koutiala.
Proper medical waste management is a cornerstone of public health and environmental sustainability, yet healthcare facilities in Liberia, including John F. Kennedy (JFK) Hospital in Monrovia, face persistent challenges in implementing effective waste handling practices. Inefficient management of medical waste poses serious risks to hospital staff, patients, and the surrounding community, highlighting the need to examine how environmental policies influence operational practices. This study aimed to assess the impact of environmental policies on medical waste management at JFK Hospital, focusing on healthcare waste management guidelines, national solid waste management policy, environmental protection policy, and public health regulations. A descriptive research design was employed, with data collected from 169 hospital staff using structured questionnaires. Data was analyzed using descriptive statistics to assess compliance and perceptions, and regression analysis to examine the relationship between policy awareness and medical waste management practices. Qualitative insights from document reviews and key informant interviews were used to support interpretation of the quantitative results. The regression results indicated a strong positive relationship between environmental policies and medical waste management practices at JFK Hospital, with R = 0.894, showing a very strong correlation between the combined policy variables and operational practices. The R² value of 0.799 implies that approximately 79.9% of the variation in medical waste management practices can be explained by the four policy variables studied, highlighting their critical influence on operational outcomes. Overall, the findings demonstrate that internal hospital guidelines, adherence to national environmental and public health policies, and operational monitoring are key determinants of effective medical waste management. It is recommended that hospital management and policymakers strengthen enforcement of environmental policies, provide adequate treatment facilities, and implement continuous staff training to ensure full compliance and safeguard public health.