Islamic Communicative Ethics and the Moral Crisis of Social Media in Nigeria

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The rapid expansion of social media in Nigeria has transformed civic engagement and public communication but has also intensified ethical challenges, including misinformation, cyberbullying, hate speech, political manipulation, and declining public civility. This study examines these developments through the normative framework of Islamic communicative ethics, grounded in Qur’ānic and Prophetic principles of truthfulness, verification, responsible speech, restraint, and harm-avoidance. Employing a multidisciplinary qualitative approach that integrates Islamic ethical theory, media studies, and analysis of Nigeria’s socio-political context, the study interrogates the moral foundations of digital misconduct. The findings indicate that persistent abuses within Nigeria’s online sphere are not merely regulatory or technological failures but manifestations of weakened moral orientation and diminished communicative responsibility. The erosion of ethical speech norms has contributed to ethno-religious tensions, political polarisation, reputational harm, and declining social trust. The study demonstrates that Islamic communicative ethics offers a coherent and contextually resonant framework for reorienting digital behaviour toward accountability, civility, and communal welfare. It concludes that embedding value-driven ethical principles in digital literacy, public discourse, and policy development is essential for fostering a healthier and more socially cohesive online public sphere in Nigeria.​

Analysis And Contemporary Perspectives of Yágodin’s Agrochemistry and its Integration with Current Environmental Principles and Challenges

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Agrochemistry is an essential discipline that studies the chemical composition and biochemical processes of soils and plants in order to optimize agricultural production under sustainability criteria, ensure adequate plant nutrition, and preserve soil fertility. In this context, the work Agrochemistry I and II, edited by B. A. Yagodin and published by Mir Publishers, represents a classical reference in the education and dissemination of this science, particularly in the Spanish-speaking sphere, by integrating theoretical foundations and practical applications. The objective of this research was to analyze the validity, coherence, and relevance of the principles and recommendations contained in both volumes by contrasting them with recent scientific evidence and current environmental regulations, in order to identify areas for improvement and propose guidelines for modern agrochemistry. The methodology included a critical and systematic content analysis, complemented by a bibliometric study of the state of the art using RStudio. A Scopus database comprising 494 publications in the field of agricultural sciences (1980–2025) was used, applying “Agroquímica B. A.” as the search criterion. The results indicate that the foundations proposed by Yagodin remain relevant and are associated with current issues such as soil chemical processes, plant nutrition, fertilizer dynamics, soil acidification, and phosphorus availability. Furthermore, convergence was observed with sustainable nutrient management approaches and emerging technologies such as biochar, controlled-release fertilizers, and digital monitoring. The bibliometric analysis highlighted Italy, France, and Mexico in terms of citation counts, and Japan, the United States, and the United Kingdom in scientific output. It is concluded that integrating Yagodin’s contributions with recent evidence strengthens an updated agrochemical approach capable of addressing contemporary environmental and productive challenges.

Multiclass Diabetes Classification using Multimodal Artificial Intelligence

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Diabetes mellitus is a prevalent metabolic disorder globally. Its primary etiologies encompass socioeconomic determinants, behavioral risk factors, and underlying comorbidities. Numerous epidemiological studies have investigated various diabetes phenotypes, impacting both sexes across the entire age spectrum. This study utilizes a dataset containing clinical profiles of 1,000 subjects assessed on multiple biometric and sociodemographic variables. The objective is to classify diabetes into type 1, type 2, and prediabetes using an array of deep learning and machine learning algorithms. Currently, artificial intelligence-driven diagnostic methods represent a state-of-the-art approach for disease stratification. This research evaluates the performance of six classification algorithms for determining glycemic status: random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), convolutional neural network (CNN), recurrent neural network (RNN), and long short-term memory (LSTM) network. Results demonstrate that the XGBoost classifier attained the highest predictive accuracy of 91% with a training duration of 20 seconds, surpassing the other models. These findings underscore the potential of advanced computational algorithms for precise diabetes phenotyping and risk assessment, offering significant implications for disease management and public health interventions.

Estimation of Fetal Weight by Measuring Umbilical Cord Diameter Using Ultrasonography

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Background and Objectives: Fetal weight assessment is a significant component in obstetric practices. The present study aims to estimate the fetal weight (EFW) by measuring the diameter of the umbalical cord.

Materials and Methods: The cross-sectional study included 153 pregnant women in third trimester. The sonographic evaluation was performed using mindary and Futus Fujifilm, for the examination.  Data were collected by the researcher by measuring the umbilical cord diameter. The data were analyzed using Microsoft Excel and SPSS version 16.

Results and Discussion: The current study closely aligned with findings reported by Benjamin et al. (2020) and Sarwar et al. (2018). Both studies highlighted significant positive correlations between UCD and fetal weight, reinforcing the idea that UCD is an important metric for assessing fetal growth and development. These studies emphasized using UCD as a reliable indicator, linking it effectively to fetal growth patterns, paralleling the findings of the current study in terms of correlations with fetal weight.

Conclusion: The ultrasonographic measurement of fetal weight using the umbilical cord diameter helps predict and estimate fetal birth weight and help in obstetric management. The current study provides valuable insights by demonstrating that umbilical cord diameter is significantly correlated with fetal weight.

Perceived Usefulness and Ease of Use of ICT as Predictors of Faculty Instructional Adaptability

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In higher education, using information and communication technology (ICT) is now essential. Faculty need to adjust their teaching to fit technology-rich classrooms. This study looked at how faculty members’ views on the usefulness and ease of use of ICT affect their ability to adapt in teaching. The research used a quantitative descriptive-correlational design and regression analysis, collecting data from 37 faculty members at a private college in Iligan City through a survey. Data were analyzed using Mann–Whitney, Kruskal–Wallis, Spearman correlation, and multiple regression. Teachers reported very high levels of perceived usefulness, ease of use, and instructional adaptability. There were no major differences in adaptability based on sex, education, or job status. The results showed a weak but significant link between instructional adaptability and perceived usefulness, while perceived ease of use had a strong and significant link. Regression analysis found that effective resource management and teacher readiness and skills are strong predictors of educational outcomes. Overall, practical skills and confidence in using ICT, rather than just seeing its benefits, were most important for improving faculty adaptability and technology use.

The Effect of Moringa (Moringa oleifera) Leaf Soup on Blood Pressure Changes among Overweight Employees at Nusa Cendana University

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Background: Hypertension is a major risk factor for cardiovascular disease and is commonly associated with overweight status. Dietary interventions using functional foods are considered effective non-pharmacological strategies for blood pressure control. Moringa (Moringa oleifera) leaves contain bioactive compounds such as potassium, calcium, magnesium, flavonoids, and antioxidants, which may contribute to blood pressure reduction. However, evidence regarding the effect of Moringa leaf soup on blood pressure among overweight individuals is still limited.

Objective: This study aimed to determine the effect of Moringa leaf soup consumption on changes in blood pressure among overweight employees at Nusa Cendana University.

Methods: This pre-experimental study employed a one-group pretest–posttest design involving 27 overweight employees selected through purposive sampling. Participants consumed 100 grams of Moringa leaf soup daily for seven days. Blood pressure was measured before and after the intervention using a digital sphygmomanometer. Data were analyzed using the Wilcoxon signed-rank test.

Results: A significant reduction in systolic blood pressure was observed after the intervention (p < 0.05). However, no significant change was found in diastolic blood pressure (p > 0.05).

Conclusion: Moringa leaf soup consumption for seven days significantly reduced systolic blood pressure but had no significant effect on diastolic blood pressure. This intervention may serve as a complementary dietary approach for blood pressure management in overweight individuals.

The Effect of E-Trust, E-Service Quality, and Brand Image on Traveloka Application User Satisfaction

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User satisfaction is a crucial factor in determining the sustainability and competitiveness of digital service platforms, particularly in the online travel industry. Increasing competition among online travel applications requires companies to continuously improve service quality, build user trust, and maintain a strong brand image. This study aims to analyze the effects of e-trust, e-service quality, and brand image on user satisfaction of the Traveloka application. A quantitative research approach was employed using a survey method, with 100 Traveloka application users as the research sample, selected through purposive sampling. Data were collected using structured questionnaires and analyzed using multiple linear regression analysis. The results of the instrument tests indicate that all measurement items are valid and reliable. The findings reveal that e-trust has a positive and significant effect on user satisfaction, e-service quality has a positive and significant effect on user satisfaction, and brand image also has a positive and significant effect on user satisfaction. These results suggest that higher levels of trust, superior electronic service quality, and a positive brand image play an important role in enhancing user satisfaction with the Traveloka application. This study emphasizes the importance for online travel service providers to strengthen user trust, improve digital service performance, and maintain a strong brand image in order to increase user satisfaction and sustain competitive advantage in the digital marketplace.

Recurrence of cystic lymphangioma of the forearm in a pediatric patient

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Lymphangioma is a rare, benign neoplasm of vascular origin that presents during childhood and can appear anywhere, with the capacity to spread to adjacent organs. This report presents the case of a 7-year-old male with lymphangioma recurrence one month after resection. Surgical treatment was performed, followed by conservative management. The patient had a satisfactory outcome and was discharged from the angiology service three months later without recurrence.

The Effect of Resistance Training Using Push, Pull, and Leg Methods on Skeletal Muscle Percentage and Body Fat Percentage

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Background: Non-communicable diseases (NCDs) constitute a major global health problem. In Indonesia, the prevalence of NCDs has increased since 2013, influenced by factors such as increased body fat mass and decreased muscle mass. Maintaining a high percentage of skeletal muscle and a low percentage of body fat is essential for health. One effective strategy to achieve this is resistance training using the push, pull, and leg (PPL) method.
Objective: This study aimed to examine the effect of weight training using the push, pull, and leg method on skeletal muscle percentage and body fat percentage.
Methods: This study employed a quasi-experimental design with a pretest–posttest non-equivalent comparison group approach. A total of 40 participants were recruited using non-probability total sampling. Body composition data were measured using bioelectrical impedance analysis (Omron Karada Scan Body Composition Monitor HBF-375). Data were analyzed using the Shapiro–Wilk test, paired sample t-test, and independent t-test.
Results: Weight training using the push, pull, and leg method had a significant effect on increasing skeletal muscle percentage (p = 0.001) and decreasing body fat percentage (p = 0.001).
Conclusion: Weight training using the push, pull, and leg method is effective in increasing skeletal muscle mass and reducing body fat mass.

The Relationship Between Knowledge of Breast Cancer and Breast Self-Examination Behavior Among Women of Reproductive Age in Kupang City, Indonesia

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Background: Breast cancer remains the most common cancer and a leading cause of cancer-related mortality among women worldwide, including women of reproductive age. Early detection through Breast Self-Examination (BSE), locally known as SADARI, is a simple and cost-effective method, particularly relevant in low-resource settings. Knowledge about breast cancer is considered a key cognitive factor influencing women’s engagement in early detection behaviors.

Objective: This study aimed to determine the relationship between the level of knowledge about breast cancer and Breast Self-Examination behavior among women of reproductive age in Kupang City, Indonesia.

Methods: This study employed an observational analytic design with a cross-sectional approach. The research was conducted in six districts of Kupang City from August to October 2025. The study population consisted of women aged 15–49 years. A total of 100 respondents were selected using proportional random sampling. Data were collected using a validated structured questionnaire measuring breast cancer knowledge and BSE behavior. Data analysis included univariate analysis and bivariate analysis using the Chi-square test, with a significance level set at α = 0.05.

Results: Most respondents demonstrated a moderate level of breast cancer knowledge (68.0%), followed by good (27.0%) and poor knowledge (5.0%). The majority of participants reported supportive BSE behavior (70.0%). Statistical analysis revealed a significant association between breast cancer knowledge and BSE behavior (Chi-square test, p = 0.031).

Conclusion: There is a statistically significant relationship between breast cancer knowledge and Breast Self-Examination behavior among women of reproductive age in Kupang City. Higher levels of knowledge are associated with a greater likelihood of engaging in early detection practices through BSE. Strengthening educational interventions may improve early detection behaviors and contribute to breast cancer prevention efforts.