University of Science and Technology, Yemen (USTY): Journals / جامعة العلوم والتكنولوجي
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Design of Solar Photovoltaic Energy System to Power a 3 HP Motorised Cassava Shredding Machine in Umudike, Abia State, Nigeria
No full textAbstract— This study presents the finalized design and simulated performance of an autonomous Solar Photovoltaic (SPV) system specifically engineered to power a 3 hp motorized cassava shredding machine at the Ahia Ndoro market in Umudike, Abia State, Nigeria. The machine, which incorporates an electric motor, an internal combustion engine, and a manual winding mechanism, has a maximum input capacity of 16 kg of cassava. The system was designed to meet a total daily energy requirement of 18.7 kWh, corresponding to a maximum operational power output of 2.3 kW. The final component specification requires an array of 20 solar panels (rated at 435 W each), a total of 12 batteries (each with 250 Ah capacity), and an inverter with an input power of 3 kVA. For system integrity, the maximum DC parameters were calculated to be 173 A at 24 V, while the maximum AC parameters were 10.13 A at 230 V. The solar charge controller was specified with an amperage of 97 A. Performance simulations confirmed the system\u27s robust operational capacity: the minimum monthly energy provision of 23.3 kWh per day (recorded in August, the month of lowest solar radiation) comfortably exceeds the required daily energy of 18.7 kWh. The maximum daily production reached 218 kWh per day, yielding an annual average Solar Performance Ratio (SPR) of 75%. Consequently, the proposed SPV system is confirmed to satisfy and secure the energy demands of the Abacha shredding machine, offering a reliable and sustainable power solution
Poetry : A safeguard to Arab Heritage and Past Memories
No full textلقد وجدت الثقافة العربية ، والتاريخ أفضل وسيلة لحفظ تراث ديوان الشعر العربي في كل العصور. فقد كان الشعراء – مشافهة – يوثقون ما يجري وحفظه في أشعارهم قبل أن تظهر السجلات المكتوبة ، فعلى سبيل المثال حفظت المعلقات قديماً، وكذلك شعر المقاومة المعاصر حديثاً الأحداث التاريخية لصراعات القبائل، والتحولات الدينية، والحياة السياسية غير المستقرة ، وتراث الأمة.
يدرس البحث التطور التاريخي للشعر، بدءًا من التقاليد الشفوية قبل الإسلام، مروراً
بالعصر الإسلامي، والعباسي وصولاً الى الادب المعاصر، ويدرس كذلك دور الشعر بوصفه مدوناً تاريخياً، وباني للذاكرة الجمعية العربية، وذلك من خلال تحليل الأعمال
الأدبية البارزة والتقليدية، كالشعر النبطي، والشعر الشعبي اليمني.
ويوضح البحث من خلال هذه الممارسة، أن الشعر يُمثل شكلاً أدبياً، ووسيلة لحفظ الذاكرة الثقافية، ونظاماً مستقلاً لنقل التراث التاريخي العربي من جيل الى اخر. وتتناول الدراسة الشعر العربي من وظيفته بوصفه ذاكرة ثقافية، ودوره في تدوين التاريخ.Arab culture and history have found their best historical documentation through poetry for many centuries. The Arab poetic tradition existed before written records emerged because poets functioned as living historical records through their verse. The Arab poetic tradition has maintained historical records of tribal existence and religious transformation and political instability and communal heritage through its Muʿallaqāt collection and contemporary resistance poetry. The paper examines the historical development of poetry as a historical record starting from pre-Islamic oral traditions through Islamic and Abbasid periods until reaching contemporary literary activism. The research examines how poetry functions as both a historical recorder and builder of Arab collective memory through the analysis of major literary works and traditional forms such as Nabati poetry and Yemeni popular verse. The paper demonstrates through this practice that poetry functions as both a literary form and a method to preserve cultural memory and an independent system for Arab historical transmission from one generation to another.
The study investigates Arab poetry through its function as cultural memory and its role in recording history
Role of Healthcare Professionals in Yemen Toward Reducing Drug Related Problems. A cross-sectional Analysis
Full text linkBackground:Healthcare professionals (HCPs) play a pivotal role in managing drug-related problems (DRPs), which include medication errors, adverse drug reactions, and medication non-adherence. Understanding HCPs\u27 knowledge, attitudes, and practices is essential for designing targeted interventions to mitigate DRPs.
Method:A cross-sectional study was conducted among 120 HCPs in various public and private hospitals in Aden, Yemen, using a validated 20-item survey. The survey was developed from previous study and modified to evaluate HCPs\u27 demographics, knowledge, attitudes, and practices regarding DRP problems. Data was analyzed using SPSS version 26.
Results:The sample included 120 participants, with nearly equal gender distribution (52.5% males and 47.5% females). Most HCPs were under 25 years old (59.2%), and pharmacists represented the largest professional group (48.4%). Private hospitals were the primary workplace for the majority (90.8%), and over half (51.4%) had less than five years of experience.
The findings revealed that 80.49% of HCPs demonstrated adequate knowledge and awareness of DRPs, with 98.33% agreeing that healthcare provider decisions should undergo investigations to reduce errors. However, only 37.5% acknowledged their responsibility to report medication errors, highlighting a gap between knowledge and reporting practices. Additionally, 96.66% supported the role of research in enhancing DRP management.
Conclusion:While Yemeni HCPs exhibited strong knowledge and positive attitudes toward DRPs, discrepancies in medication error reporting practices emphasize the need for targeted educational programs and system-level interventions to foster a culture of accountability and improve medication safety
Impact of Malaria Severity on Selected Liver Function Markers in Aden, Yemen: A Pilot Study
Full text linkBackground: Malaria remains a significant public health concern, with Plasmodium falciparum and P. vivax infections often leading to systemic complications, including hepatic dysfunction.
Objective: This study investigates the relationship between malaria severity and liver function abnormalities, particularly bilirubin and liver enzyme elevations, in malaria patients in Aden, Yemen.
Method: A retrospective observational study was conducted among 150 malaria patients from September to December 2024 in multiple private and public hospitals in Aden, Yemen. Malaria severity was classified based on WHO criteria into severe, moderate and mild. Liver function markers, including (ALT), (AST), (T. Bilirubin), and (D. Bilirubin), were measured using spectrophotometry. Statistical analyses were performed using SPSS version 26 with significance set at p < 0.05.
Results: Males (61%) were more affected than females (39%), with Plasmodium falciparum accounting for 68% of cases. Severe malaria was observed in 56% of patients. Liver enzyme levels were markedly elevated in severe malaria cases, with mean ALT at 80.29 ± 45.11 U/L and ALT at 78.46 ± 46.67 U/L. Bilirubin levels were also significantly increased (T. Bilirubin: 3.00 ± 2.3 mg/dL, D. Bilirubin: 1.19 ± 1.1 mg/dL), with a strong association between disease severity and hepatic dysfunction (p < 0.001). However, no statistical relationship was found between malaria severity and demographic characteristics, including gender (p = 0.318), place of residence (p = 0.438), and participant age (p = 0.869).
Conclusion: Severe malaria is associated with significant hepatic dysfunction, characterized by elevated liver enzyme levels and hyperbilirubinemia. These findings underscore the importance of continuous liver function monitoring in malaria patients to prevent severe hepatic complications. Further research is needed to elucidate the underlying mechanisms and potential long-term impacts of malarial hepatopathy
Therapeutic impact of Serial Plain Local Anesthesia Injections in Myofascial Pain Dysfunction Syndrome: A Prospective Study on Yemeni Patients
Full text linkObjective: This prospective study aimed to evaluate the efficacy of a standardized plain local anesthesia injection protocol in managing pain and functional symptoms in patients diagnosed with Myofascial Pain Dysfunction Syndrome (MPDS), with a secondary focus on outcomes in cases complicated by symptomatic temporomandibular joint (TMJ) dislocation.
Method: A prospective analysis was conducted on 20 patients (17 females, 3 males; mean age 30.2 years) presenting with MPDS symptoms, including radiation pain headaches, active trigger points, and neck & shoulder/otalgia, who underwent a structured treatment regimen. The protocol comprised three plain local anesthesia injections over two weeks (two injections in the first week, one in the second). Patients with TMJ symptomatic subluxation (n=10) received adjunctive ABI therapy. Pain severity was assessed using the Visual Analog Scale (VAS) at baseline, post-treatment, and follow-ups (3 weeks, 3 months, 6 months).
Results: Significant pain reduction was observed across all patients. Initial VAS scores (7–10/10) decreased to 2–3/10 after the first week and further declined to 0–1/10 post-treatment. Complete pain resolution (0/10) was achieved in 90% of cases by the second week, while two patients (10%) reported residual pain (1/10). Patients with TMJ dislocation showed comparable pain reduction but required extended adjunct therapy. Functional outcomes, including mouth opening and mandibular mobility, remained stable or improved in 95% of cases.
Conclusion: Plain local anesthesia injections provide rapid and sustained relief for MPDS-related pain, with high efficacy in uncomplicated cases and in complex cases that are secondary to TMJ involvement. TMJ involvement necessitates adjunct therapies, emphasizing the importance of individualized management. This protocol demonstrates promise as a first-line intervention, though long-term studies are needed to validate durability and compare alternative approaches
Genetic and Demographic Determinants of Diabetes: A Cross-Sectional Analysis of Family History, Gender Differences, and Disease Characteristics in Ghana
Full text linkBackground: The prevalence of diabetes mellitus in Ghana presents an emerging public health issue, being fueled by lifestyle, genetic and demographic factors.
Objective: This study aimed to determine the relationship between family history and the type of diabetes and assess the differences in diabetes onset and duration between genders.
Methods: A cross-sectional survey was conducted with a sample of 1,000 Ghanaians with diabetes selected from various healthcare institutions in Ghana. Participants were chosen using stratified random sampling. Demographic information, type of diabetes, family history, age of onset, and duration of diabetes were gathered using a structured questionnaire. The association between family history and diabetes type was examined through chi-square tests. Age and duration of diabetes between individuals with and without a family history were compared using independent samples t-tests. Demographic characteristics were described using summary measures.
Results: The study revealed that 58% of the participants have a family history of diabetes. Chi-square analysis revealed a considerable interrelation between family history and Type 2 diabetes (χ² = 112.3, p < 0.001). Participants with a family history were diagnosed at a younger age with diabetes (M = 54.2 years vs. 57.8 years, p < 0.001) and had a longer duration of the condition (M = 6.8 years vs. 5.5 years, p < 0.001). More females than males reported having a family history of diabetes (62.4% vs. 52.6%). The rest (61%) were urban residents.
Conclusion: In Ghana, family history is closely related to having Type 2 diabetes, as well as preceding the diagnosis and extending the duration of the disease. The gaps in reporting highlight the need for women-sensitive diabetes care programs. To bridge these gaps, targeted public health interventions, such as community-based screening and educational campaigns, should be implemented to raise awareness and promote early diagnosis, especially among high-risk families
Effectiveness of Health Education in Improving Foot Care Knowledge, Attitudes, and Practices Among Diabetics at an NCD Clinic in Chennai
Full text linkBackground: Proper foot care techniques, a good outlook, and adequate education are necessary for the effective avoidance of diabetic foot problems. The purpose of this study was to assess how health education affected the knowledge, attitudes, and foot self-care practices of diabetic patients.
Methods :This was a quasi-experimental (before and after) study conducted for a study period of 12 weeks (December-February 2023) at the Rural Health Training Centre, Poonamallee Primary Health Care Centre (PHC), among persons with diabetes over the age of 30 years who are on regular follow-up of treatment and willing to participate in the study. We interviewed all the patients in 2 phases, before and after intervention, using a questionnaire. Scores for knowledge, attitudes, and practices were computed both before and after the intervention.
Results: Following the intervention, the knowledge score [median score pre-intervention (pre) = 5.6, median score post-intervention (post) = 6.6] (p-value = 0.021), practice score [median score pre = 3, median score post = 4.8] (p-value = 0.001), and total score (p-value = 0.001) all significantly increased. The increase in attitude score after intervention was marginally non-significant [median score pre = 4.0, median score post = 5.0] (p-value = 0.058).
Conclusion: In order to lower the prevalence of diabetic foot problems, educational initiatives that raise community knowledge of diabetic foot care must actively engage the community
Using an Adaptive Linear Support Vector Machine Algorithm for Predicting Breast Cancer
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سرطان الثدي هو أكثر أنواع السرطانات شيوعاً ويساهم بشكل كبير في ارتفاع معدلات الوفيات بين النساء. يزداد معدل الوفيات عندما يتم تشخيص هذه الحالة يدويًا لأنها تستغرق عدة ساعات ومتخصصين. لذلك، تم اقتراح التشخيص الآلي لسرطان الثدي لتسريع الكشف ووقف المرض من الانتشار. على مر السنين، تم استخدام خوارزميات تصنيف التعلم الآلي للتنبؤ بسرطان الثدي. في الدراسات السابقة، كانت إحدى الخوارزميات الأكثر استخدامًا هي خوارزمية الدعم الالي المتجهة.
ومع ذلك، فإن هذه الدراسات لها نتائج غير متسقة. في هذا العمل، نتحرى تأثير اختيار الميزات، ومعلمات او المتغيرات الخاصة بخوارزمية الدعم الالي المتجهة وكذلك تقسي البيانات على ادء الخوارزمية وبا التالي ، فإننا نبني نموذج واحد للتعلم الالي يحقق نتيجة اعلى تم استخدام مجموعة بيانات ولاية ويسكنسن لتدريب واختبار هذا النموذج. أظهرت النتائج التجريبية أن أداء النموذج قد تأثر باختيار الميزات، معاملات البارامتر الفائق ، وآلية تقسيم البيانات من حيث أفضل ومتوسط .النتائج الثلاثة الأولى. أظهرت نتائج المقارنة تفوق الطريقة المقترحة على الطرق الحديثة الأخرى.Breast cancer is the most common type of cancer and a significant contributor to the high death rates among women. The death rate increases when this condition is manually diagnosed since it takes several hours and specialists. Therefore, an automated breast cancer diagnosis has been suggested to speed up detection and stop the disease from spreading. Over the years, machine learning classification algorithms have been used to predict breast cancer. In the previous studies, one of the most used algorithms is the Support Vector Machine (SVM). However, these studies have inconsistent results. This work, investigates the impact of the features\u27 selection, hyperparameter parameters of SVM, and the mechanism of splitting data on the algorithm performance. Thus, build an SVM, as a single machine learning model, that achieves a higher result. The Wisconsin dataset was used to train and test this model. The experimental results showed that the performance of the model was affected by the features\u27 selection, hyperparameter parameters, and the mechanism of splitting data and random state values in terms of the best top one results and the average of the top three results. The comparison results revealed the superiority of the proposed method over the other state-of-the-art
GENERATIVE AI AND ENGINEERING EDUCATION: MEASURING ACADEMIC PERFORMANCE AMIDST SOCIOECONOMIC CHALLENGES IN YEMEN
Full text linkThis study assessed the impact of generative artificial intelligence (GenAI) usage on the academic outcomes of engineering students within the context of Yemen\u27s unique socioeconomic challenges. This study employed a quantitative approach through a structured 5-point Likert-scale questionnaire, which was distributed to 277 engineering students from Taiz University, Yemen. In a resource-constrained environment, the results exhibited a strong correlation between GenAI usage and engineering students’ overall grades and skills development. Additionally, findings showed that socioeconomic challenges that students face in Yemen have moderately hindered students from the effective usage of GenAI for educational purposes, which is a key finding for higher education institutions (HEIs). Also, statistical results showed that almost all respondents are familiar with GenAI tool usage, while 89.17% use ChatGPT as a fundamental component of learning. Of course, the integration of GenAI into education has become inevitable, compelling HEI policymakers to regulate its use and formally adopt it as a primary source of learning systems. Students and educators should obtain continuous training to effectively benefit from GenAI while conforming to ethics and boosting their intellectual capabilities and skills. Raised concerns that the students overreliance on AI tools could undermine their problem-solving abilities and practical skills development while complicating students’ evaluation process for educators. The outcomes of this study could serve as a foundational reference for policymakers, educators, and students in Yemen and similar settings. It also recommends in-depth studies that cover other educational contexts and respondents from other states, rather than undergraduate engineering students in the present study
Cloud Technology and Cybersecurity: A Literature-Based Study on Threats and Safeguards
Full text linkCloud computing has fundamentally transformed modern IT by offering scalable, cost-effective services. However, its rapid adoption has introduced critical cybersecurity concerns. This study investigates the impact of cloud technology on information security, focusing on key challenges such as data breaches, unauthorized access, and regulatory compliance. Employing a literature-based approach complemented by a quantitative user survey, it evaluates existing security measures, including encryption, multi-factor authentication, and adherence to frameworks like GDPR and HIPAA. The findings highlight that while cloud computing significantly improves accessibility and efficiency, it also necessitates robust security strategies. The study concludes by recommending enhanced encryption, comprehensive user education, and stringent governance policies to strengthen cloud security and ensure the reliability and trustworthiness of cloud-based systems