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White matter diffusion metrics for clustering cognitive phenotypes in a preliminary cohort of patients with drug-resistant epilepsy
Introduction: The relationship between white matter microstructural alterations and cognitive phenotypes (CF) in patients with drug-resistant epilepsy (DRE) remains an area requiring further investigation. The objective was to explore the association between white matter diffusion metrics and CF in a small cohort of patients with DRE. Methods: A pilot, analytical, cross-sectional study was conducted in 7 patients with DRE and 3 healthy controls. The International Center for Neurological Restoration (CIREN), Cuba. After identifying statistically significant correlations between FC and white matter diffusion metrics, 3 predictor variables were selected: fractional anisotropy of the corpus callosum of the minor forceps node 41-60 (FACCFMi41-60), mean diffusivity of the left cingulate node 21-40 (DMCCLeft.21-40), and volume of the right fronto-occipital fasciculus node 1-20 (VLFFOIRight.1-20). A Bayesian multinomial generalized linear analysis was performed, calculating the observed variability (R2), likelihood ratio (X2), effect size (ŋ2), odds-change ratio (Exp(B)) and confidence intervals (CI). Results: The model showed: R2=0.99; X2(6)=20.6, p=0.002; ŋ2=0.23 in AFCCFMe41-60 and ŋ2=0.19 in VlFFOIRight.1-20. FC with generalized alterations was associated with lower FACCFMi41-60 (OR: 1.40e-112; p=0.035) and higher MDCCleft.21-40 (OR: 6.75e+21; p=0.019) compared to FC without alterations. Conclusions: This study confirms the feasibility of using white matter metrics and Bayesian analysis to classify cognitive phenotypes, identifying specific trends in patients with drug-resistant epilepsy. Nevertheless, the small cohort size means the results are preliminary and require validation in future studies.
Bayesian multinomial generalized linear analysis
Copyright (c) 2026 Marilyn Zaldivar Bermúdez, Damian Valdés Santiago, Lilia María Morales Chacón (Author) https://creativecommons.org/licenses/by/4.0
Physical, curricular and attitudinal barriers for students with disabilities in higher education
Inclusive education was recognized as an essential component to ensure equal opportunities for students with disabilities; however, physical, curricular, and attitudinal barriers continued to limit their full participation in higher education. The general objective of this study was to empirically analyze how these barriers affected the academic experience of students with disabilities in universities. A mixed-methods approach was employed, combining surveys with 120 students and semi-structured interviews with 12 faculty members. Results revealed that physical barriers, such as inadequate ramps, elevators, and accessible spaces, restricted students' mobility and autonomy. Curricular barriers were evidenced by inconsistent implementation of pedagogical and evaluative adaptations, while attitudinal barriers included negative perceptions and low performance expectations from some faculty and peers. Accessible technological resources were partially available and non-standardized, generating inequalities in learning. Existing institutional policies were perceived as limited, with scarce implementation and monitoring. The study highlighted that effective inclusion required an integrated approach combining accessible infrastructure, adapted curriculum, faculty training, technological resources, and inclusive culture, coordinated among faculty, students, and administrators, to ensure equity, retention, and academic success.
Copyright (c) 2025 Diana Elizabeth Montesdeoca Vera, Janina Consuelo Pérez Cruz, Pedro Arturo Noboa Neira, Isaura Romelia Humanante Serrano (Author) https://creativecommons.org/licenses/by/4.0
Antidiabetic Effect of Raru (Vatica perakensis) Bark Extract and Mocaf Activated Carbon in Streptozotocin-induced Diabetic Ratsntidiabetic Effect of Raru (Vatica perakensis) Bark Extract and Mocaf Activated Carbon in Streptozotocin-induced Diabetic Rats
Introduction: the natural benefits of raru as a natural sweetness reducer. Batak people have practiced for generations, form the basis for exploring raru as a biomedicine ingredient for anti-diabetes. Objective: this study aims to combine the raru's bark extract with tapioca-derived MAC (mocaf activated carbon) to assess its effectiveness and bioactivity as an anti-diabetic agent in male Sprague Dawley rats. Methods: The carbonization technique used was inherently hydrothermal carbonization. For such, the modified tapioca flour was carbonized at a temperature of 250°C for 6 hours. Raru bark powder was extracted using ethanol 70 % by maceration for 72 hours. In vivo antidiabetic activity was used on Sprague Dawley rats, male, aged ± 12 weeks, with a weight of ± 250-350 grams. Results: the result showed that the anti-diabetic activity of the combined raru's extract and MAC exposed to the rats brought about the declines in glucose levels in the rat's blood. The various treatments at different concentration ratios of raru's extract and MAC supposedly efficacious in the experiments showed that the levels of blood level reduction were slightly varied (14-21%). The mixture of raru's extract and MAC with a 75:25 ratio was better than a 50:50 ratio in lowering the blood glucose level. Conclusion: In vivo experiments can reduce blood sugar levels diabetic rats. The involvement of MAC in the alleged anti-diabetic agent did little to induce the glucose level decrease in the rat's blood. However, raru's extract and MAC indicate its potential utilization as an anti-diabetic agent.
Copyright (c) 2025 Gunawan Pasaribu, Novitri Hastuti, Saptadi Darmawan, Gustan Pari, Lisna Efiyanti, Sigit Baktya Prabawa, Totok K. Waluyo, Yelin Adalina, Andianto, Soenarno, Agus Ismanto, Alfonsus H. Harianja (Author) https://creativecommons.org/licenses/by/4.0
Optimization of the Design of a Centrifugal Pump of the Automotive Engine Cooling System
Introduction: The study focused on analyzing the design of a centrifugal pump in vehicle engine cooling systems. Cavitation, a phenomenon that impacts the efficiency and durability of hydraulic components, was examined as a key variable. Based on the geometry of the centrifugal pump impeller, computational fluid dynamics (CFD) simulations and experimental validation were employed. Methods: Three combined strategies were implemented: analysis of hydraulic parameters using equations; precise modeling of flow behavior to evaluate geometric configurations; and comparison of numerical data with actual pressure and flow measurements. Fluctuations in the motor diameter (61 mm, 62 mm, and 63 mm) were analyzed under normal operating conditions and acceleration. Results: Increasing the inlet diameter to 61 mm proved to be the ideal solution, achieving a 5% increase in pump inlet pressure and significantly reducing the risk of cavitation. CFD methods were confirmed as valuable tools for refining designs, demonstrating a high correlation with experimental data. Conclusions: The effective use of tools such as CFD to address critical challenges in automotive engineering is emphasized, optimizing both technical performance and environmental impact. Furthermore, it increases hydraulic efficiency and reduces cavitation in centrifugal pump in vehicle engine cooling systems.
Copyright (c) 2026 Edilberto Antonio Llanes-Cedeño, Édison Argüello Maya, Juan Carlos Quinchuela Paucar , Rodrigo Rigoberto Moreno-Pallares , Lenin Montalvo Ochoa (Author) https://creativecommons.org/licenses/by/4.0
Effects of intradialytic exercise on muscle strength and physical capacity in patients with chronic kidney disease receiving hemodialysis
Introduction: patients with advanced stages of chronic kidney disease present a hypercatabolic state characterized by loss of body proteins, which has a negative impact on physical capacity and muscle strength, particularly in patients undergoing hemodialysis, leading to reduced quality of life and increased mortality. Exercise has been shown to improve muscle function in this population, but remains underutilized due to safety concerns and lack of evidence. Methodology: we conducted a descriptive systematic review of cohort studies and randomized clinical trials published in the last 5 years in English or Spanish whose main intervention is intradialytic physical exercise was conducted. Results: thirteen studies were analyzed that described an improvement in physical and functional capacity of patients who were included in the intradialytic exercise groups, although changes regarding body composition were not significant. Conclusions: the implementation of structured and supervised exercise programs during hemodialysis can mitigate the adverse effects of prolonged inactivity, improve physical function, and ultimately improve the quality of life of CKD patients
Copyright (c) 2025 Melanie Samantha Armas Ingavélez , Jorge Marcelo Morales Solis (Author) https://creativecommons.org/licenses/by/4.0
A Juridical Analysis on the Usage of Artificial Intelligence in Medical Instruments from the Perspective of the Indonesian Law No. 17 of 2023
Introduction: The quick development of artificial intelligence (AI) has spread to various sectors of health, including health technology. However, in line with the development of AI in the medical sector, complex medicolegal (legal and ethical) issues that health professionals, researchers, and policymakers must face start to emerge, such as the lack of legal regulations that govern AI, the issue of patient security and privacy, as well as who must take legal responsibility in case a certain issue occurs. This research aims to analyze how AI is used in health instruments from the perspective of Indonesian Law No. 17 of 2023 using a juridical analysis. Specifically, it aims to analyze the legal position of AI; telehealth and telemedicine in the Indonesian Health Law; the importance of data in the usage of AI in the health sector; risks in Using AI in the medical field; regulations on the use of AI in the medical field; and the implementation of telesurgery with the help of AI. Methods: This research employed the normative juridical research method with a doctrinal characteristic. It employed the statute approach. It means research based on previous research data, library data, systematic reviews and laws and regulations Results: Law No. 17 of 2023 on Health has not regulated the use of artificial intelligence (AI). These unclear regulations may endanger the position of doctors and patients. The lack of regulations that govern medical services between doctors and patients via AI may lead to legal uncertainty. This will certainly lack providing AI service scope for patients and doctors, especially on the safety of utilizing telesurgery in long-distance surgeries. Telesurgery offers certain benefits for patients and doctors but its practice must consider the legal and ethical aspects. Conclusions: There should be regulations that govern the use of AI based on the medical ethical code and the ethical values that apply in society so that its use may always prioritize human interests.
Copyright (c) 2026 Arief Budiono, Onnie Wira Tama , Naeem Allahrakha, Aminuddin Mustaffa , Abdullah Al Mamun , Rizka , Nur Aida Ikrima (Author) https://creativecommons.org/licenses/by/4.0
Regional Collaboration in Public Health Policy: Evaluating Family Assistance Team Involvement in Stunting Reduction
Introduction: The study examined regional collaboration in public health policy by assessing the involvement of Family Assistance Teams (FATs) in accelerating stunting reduction in Lampung Province, Indonesia. It aimed to identify FATs’ roles, performance, and operational challenges in implementing integrated health and nutrition programs under decentralized governance. Methods: A qualitative approach was used through focus group discussions with 23 FAT members from North Lampung, West Lampung, and Way Kanan Regencies. Participants were purposively selected based on program intensity. Data validation was conducted through interviews with family planning field officers to ensure accuracy and policy relevance. Results: The findings revealed variation in role comprehension, sectoral coordination, and digital data use. Key challenges included limited technical skills, scarce resources, and weak integration with Regional Stunting Reduction Teams. Nonetheless, locally driven strategies supported by village funds, structured task allocation, and active engagement in health posts enhanced program performance and outcomes. Conclusions: The study concluded that strengthening institutional capacity, improving digital data management, enhancing coordination mechanisms, and introducing performance-based incentives were vital to increase FAT effectiveness. These insights provided strategic guidance for refining collaborative governance and expanding sustainable stunting reduction initiatives across regions.
Copyright (c) 2026 Yulianto Yulianto, Asnani Asnani, R. Luki Karunia, Johan Hendri Prasetyo (Author) https://creativecommons.org/licenses/by/4.0
Transdisciplinary STEAM and Quality Control Approaches Elevating Vocational Education in Support of SDGs
Introduction: the rapid development of modern industries requires vocational education to equip students with both technical expertise and creative, interdisciplinary competencies. To meet these demands, learning models must integrate scientific and technological knowledge with systematic quality assurance. This study examines the relevance and importance of combining STEAM-based learning with Quality Control (QC) to enhance students’ readiness for industry-standard production. Method: this study employed a Pretest–Posttest Control Group Design involving 32 vocational students divided into experimental and control classes. The experimental class received STEAM-QC–based instruction, integrating scientific concepts, technological tools, engineering design, artistic creativity, and mathematical analysis while applying QC at every production stage. Data were collected through tests, observations, and product assessments, and analyzed using Shapiro–Wilk and Levene tests, N-Gain, and Two-Way ANOVA. A total of 42 scholarly sources supported the theoretical and methodological framework. Results: the STEAM-QC intervention strengthened students’ interdisciplinary understanding, improved their systematic work processes, and enhanced the feasibility of their final products. Learning outcomes showed higher improvement in the experimental group, and product evaluations demonstrated better performance in construction quality, aesthetics, and durability. The model also promoted more consistent decision-making and reflective practice during production. Conclusions: the integration of STEAM and QC provides an effective instructional model for vocational education by aligning academic learning with industrial quality standards. This approach supports the development of competent and innovative graduates and contributes to achieving SDG 4 (Quality Education) and SDG 9 (Industry, Innovation, and Infrastructure).
Copyright (c) 2025 Fani prima, Prof. Dr. Rijal Abdullah, M.T, Dr. Juniman Silalahi, M.Pd, Windry Novalia Jufri, S. Pd., M. Pd, Yuwalitas Gusmareta, S.Pd, M.Pd.T (Author) https://creativecommons.org/licenses/by/4.0
Designing an Android-Based learning media for Javanese Script: A study on student's conceptual understanding and literacy skills
Introduction: javanese script is a traditional writing system with a rich history and philosophy, and it is one of the most endangered forms of cultural heritage. This study aims to determine the effect of understanding the concept of the Javanese script on the literacy skills of students interested in Android-based learning media. Methods: this study uses a mixed-methods approach with quantitative and qualitative analysis stages. A sample of 286 students was selected using purposive random sampling. Quantitative data were obtained by administering student questionnaires, while qualitative data were obtained through observation, interviews and documentation. Quantitative data were analysed using SEM-PLS. Qualitative data analysis was conducted using triangulation of data and sources. Results: the results of the path coefficient calculation show an effect of 0.341, with a t-count of 6.646, and a p-value of 0.000. Understanding the concept of Javanese script influences interest in Android-based media. The path coefficient obtained from the calculation was 0.486, with a t-count of 8.250, and a p-value of 0.000. The results show the influence of children's literacy skills on interest in Android-based media. Conclusions: javaScript learning media based on Android can increase interest in and understanding of the concept of JavaScript. Further research is recommended, with a wider and more diverse sample of participants from different schools and backgrounds, to make the results more generalisable.
Copyright (c) 2025 Much Arsyad Fardani, Ika Ari Pratiwi, Lintang Kironoratri, Indra Ava Dianta, Hilmy Aliriad, Dwiana Asih Wiranti (Author) https://creativecommons.org/licenses/by/4.0
The Effect of Noise, Vibration, Temperature, and Mental Workload on Work Productivity Through Job Stress at PT. Makassar Tene
Introduction: Work stress is one of the common problems faced by workers in both formal and informal sectors. In addition to noise, vibration, temperature and mental workload are also factors that affect employee productivity levels. Method: Quantitative research with a cross-sectional design with path analysis. The sample of this study was 100 respondents selected using the Proportionate Stratified Random Sampling technique. Data were collected through questionnaires and measuring instruments. Results: The results of this study indicate that noise significantly affects work stress (p=0,002) does not affect work productivity (p=0,105) work stress as a significant mediator (p=0,002), vibration (WBV) does not affect work stress (p=0,543) does not affect work productivity (p=0,157), work stress as a mediator is not significant (p=0,547), temperature affects work stress (p=0,002), does not affect work productivity (p=0,918), work stress as a significant mediator (p=0,001), mental workload affects work stress (p=0,012), affects work productivity (p=0,042), work stress as a significant mediator (p=0,012). Conclusion: Noise, temperature and mental workload are important factors influencing work productivity and work stress both directly and through work stress as an intervening variable.
Copyright (c) 2025 Natalia Padalling, Syamsiar S. Russeng, M. Furqaan Naiem (Author) https://creativecommons.org/licenses/by/4.0
The Impact of Visualization Integration and Mason's Theory in Real Analysis Learning on Students' Mathematical Proof Abilitie
Introduction: mathematical proof abilities are crucial for mathematics students because mathematics is full of theories and concepts that must be proven. Mathematical proof is the core of the Real Analysis course. However, most students struggle with this course because the topic consists of abstract concepts and proofs. Providing visualizations of abstract concepts and Mason's framework of thought is expected to be a solution to help students conduct proofs. Methods: this research is a descriptive qualitative study. The research instruments were a mathematical proof test in the form of an essay and a structured interview guide. The research subjects were: one class of 35 students of the Mathematics Education study program, Faculty of Mathematics and Natural Sciences, Padang State University (Indonesia). For the interview, 3 people were taken from the lower group and 3 people from the upper group. Data analysis was carried out using descriptive analysis. Results: the results of the mathematical proof test showed that there was an increase in students' mathematical proofs before and after learning that integrated visualization and Mason's framework of thinking. From the interview results, it was found that: for students in the lower group, the use of visualization could improve their understanding of abstract concepts but they were not yet able to write proofs well. Meanwhile, students in the upper group, the use of visualization could improve their understanding of abstract concepts and write proofs and describe them in the good and very good categories Conclusions: use Mason's visualization and conceptual framework in learning can improve students' mathematical proofs. Although the improvement is not significant, lower-level students saw improvements at the cognitive level of understanding, while higher-level students saw improvements at the application and analysis levels.
Copyright (c) 2025 Yerizon Yerizon, Dewi Murni , Elita Zusti Jamaan, I Made Arnawa, Helma Helma, Mirna Mirna (Author) https://creativecommons.org/licenses/by/4.0
Development of an Augmented Reality-Based Student Attitude Assessment Model (ASSAR) as an Effort to Strengthen the Graduate Profile in the Implementation of Deep Learning in Vocational Schools
Introduction: in[user3.1][AS3.2] the digital era, integrating technology into education has become crucial, particularly for improving student competency assessment. Vocational schools, which aim to prepare work-ready and competitive graduates, require innovative approaches to enhance learning and evaluation processes. Method[user4.1][AS4.2]: this study developed and tested the effectiveness of the Augmented Reality-Based Student Attitude Assessment Model (ASSAR) to support the implementation of deep learning in vocational education. The research employed a Research and Development (R&D) design following the ADDIE model, consisting of Analysis, Design, Development, Implementation, and Evaluation stages. Results: the[user5.1][AS5.2] findings indicated that the ASSAR model was valid, reliable, and practical for use in vocational education. Expert validation demonstrated high content validity (Aiken’s V > 0.80), supported by additional analyses showing strong construct validity and high internal consistency (Cronbach’s Alpha > 0.85). Teachers evaluated the model as feasible and efficient, while students reported increased engagement and authenticity through the AR-based interface. The product also achieved Technology Readiness Level (TRL) 7, confirming its applicability in real educational settings. Further expert evaluation through a Focus Group Discussion reaffirmed these results, with four experts rating both the graduate profile materials and the AR-based learning media as highly eligible (Aiken’s V = 0.81–0.94). Conclusions: the ASSAR model enhanced the objectivity, authenticity, and efficiency of attitude assessment, supporting vocational schools in producing graduates equipped with both technical competence and professional character to meet the challenges of Industry 4.0 and Society 5.0.
Copyright (c) 2025 Ani Widayati, Dian Normalitasari Purnama, Agatha Saputri, Arief Nurrahman (Author) https://creativecommons.org/licenses/by/4.0
Antimicrobial Effects of Aqueous Bark Extracts of Khaya senegalensis, Azadirachta indica and Euclyptus camaldulensis against Different Bacterial Pathogens
Introduction: aqueous bark preparations of Khaya senegalensis, Azadirachta indica, and Eucalyptus camaldulensis are widely employed in traditional medicine for the management of microbial infections in both humans and animals. The present work aimed to investigate the antibacterial potential of these plant extracts against selected Gram-positive bacteria (Staphylococcus aureus and Staphylococcus epidermidis) and Gram-negative bacteria (Klebsiella pneumoniae, Escherichia coli, and Salmonella dublin). Methods: bark materials were extracted with water to obtain concentrations equivalent to 20 g, 40 g, and 50 g per 100 mL. Antibacterial activity was evaluated using the agar well diffusion technique at the Microbiology Laboratory, Faculty of Veterinary Medicine, University of Khartoum. Bacterial susceptibility was determined by measuring inhibition zone diameters around the wells. Results: all tested aqueous extracts demonstrated inhibitory effects against the examined bacterial strains at every tested concentration. Antibacterial activity increased with rising concentration, with the maximum effect observed at 0.5 mg/mL. At this level, inhibition zones against Staphylococcus aureus measured 3.7 ± 0.52 cm for Khaya senegalensis, 3.0 ± 0.24 cm for Azadirachta indica, and 2.8 ± 0.57 cm for Eucalyptus camaldulensis. Conclusion: the findings indicate that bark-derived aqueous extracts from the three studied species possess notable antibacterial activity against both Gram-positive and Gram-negative pathogens, particularly at higher concentrations. These results support their traditional use and suggest the need for further investigations involving other plant organs—such as leaves, fruits, and roots—tested across a wider range of concentrations.
Copyright (c) 2026 Wadah Osman , Haytham Hashim Gibreel , Reem Rabiae Mohammed Salih , Mohamed Mirghani , Alqarni M.H. , Foudah A. I. , Ahmed Ashour, Waggiallah, H. A. , El-Sakhawy, M. A. (Author) https://creativecommons.org/licenses/by/4.0
Integration of Batak Angkola Local Wisdom “Poda Na Lima” In Secondary Stroke Prevention: An Interdisciplinary
Objective: This study aims to explore the integration of Poda Na Lima , a form of local wisdom from the Batak Angkola ethnic group, in the context of secondary stroke prevention. Method: This qualitative study was designed based on an interpretive paradigm using a philosophical hermeneutic approach. Data and information were obtained from ten participants, including health academics, healthcare practitioners, traditional leaders, religious figures, and community leaders. Data collection was conducted through a Focus Group Discussion (FGD) and analyzed using content analysis. Results: The results show five main themes including 1) Maintaining Heart Health ; 2) Maintaining Body Hygiene ; 3) Maintaining Clothing Cleanliness ; 4) Maintaining Home Cleanliness ; and 5) Maintaining Yard/Environment Cleanliness . Conclusions: The findings of this study indicate that the local wisdom of Poda Na Lima can serve as a valuable guide in secondary stroke prevention, contributing to improved health outcomes among stroke survivors.
Copyright (c) 2026 Nanda Masraini Daulay, Hapiz Arlanda Sani, Henniyati Harahap, Haslinah Ahmad, Nanda Suryani Sagala, Siti Zahara Nasution, Anto J. Hadi , Nur Nasry Noor, Shanti Rizkiyani, Lalu Muhammad Saleh , Sukri Palutturi, Anwar Mallongi (Author) https://creativecommons.org/licenses/by/4.0
The Effect of Noise Intensity, Work Climate and Individual Characteristics on Blood Pressure of Workers PT Bungasari Flour Mills
Introduction: K3 is important because workers are exposed to noise of 95.8–87.8 dBA and a working climate of ISBB 31.6°C which exceeds the threshold, so the influence of both and individual characteristics on workers' blood pressure at PT Bungasari Flour Mills Makassar was studied. Methods: Cross-sectional observational analytical quantitative study; population of all PT Bungasari mill workers (100 people) with total sampling (n=100); instruments: characteristic form, SLM Svantek 971, noise dosimeter Svantek 104 (8 hours), Heat Stress Monitor QuesTemp 46 (WBGT), tensiometer, microtoise, digital scales; analysis in SPSS 23 (univariate, Chi-Square, and multiple logistic regression). Results: The majority of workers were aged 26–35 years (37 %) with a high prevalence of smoking (86 %) and dominant obesity nutritional status (48 %), most of whom had worked for ≥4 years (68 %), and 73 % were exposed to noise and 70 % were exposed to hot working climates above the NAB; This condition was followed by an increase in mean blood pressure (systolic +4.90 mmHg; diastolic +4.08 mmHg) and the test results showed a significant relationship with a history of hypertension (p=0.010–0.014), nutritional status (p=0.001–0.002), smoking habits on systolic (p=0.044), work period (p<0.001), noise (p<0.001), and hot work climate (p=0.001–0.041), while age was only related to diastolic (p=0.010), alcohol (p>0.05) and work shifts (p>0.05) were not significant, and multivariate analysis showed that work period ≥4 years was the only significant predictor of systolic blood pressure (Adj-OR=0.022; p=0.002) and diastolic (Adj-OR=0.105; p=0.016). Conclusions: Noise intensity, work climate, and individual characteristics have a significant effect on workers' blood pressure, so it is necessary to strengthen health monitoring and control of the work environment to prevent hypertension.
Copyright (c) 2026 Rizki Ardiansyah , Yahya Thamrin , Syamsiar S. Russeng , Atjo Wahyu, Andi Zulkifli (Author) https://creativecommons.org/licenses/by/4.0
A Review of AI and Deep Transfer Learning Methods for Plant Disease Detection and Classification
The persistent threat of plant disease epidemics poses significant challenges to global agriculture, making crops susceptible to catastrophic diseases that compromise food security and nutritional well-being. This review critically examines the application of deep transfer learning and convolutional neural networks (CNNs) in classifying plant diseases, such as tomato leaf diseases. By synthesizing recent advancements in the field, the article highlights how pre-trained models, trained on large-scale image datasets, can be adapted to recognize disease-specific patterns in agricultural contexts. The discussion encompasses key methodologies, including the integration of custom architectures and shallow classifiers, as exemplified by works such as Fruit and Vegetable Leaf Disease Recognition based on a Novel Custom Convolutional Neural Network and Shallow Classifier and An Integrated Framework of Two-Stream Deep Learning Models Optimal Information Fusion for Fruits Disease Recognition. A critical analysis of existing approaches is provided, addressing their strengths, limitations, and the role of dataset quality and diversity in model performance, including the use of publicly available datasets of labelled plant disease images, such as PlantVillage. The review underscores the transformative potential of automation and robotics in reducing disease spread while emphasizing unresolved challenges, such as the need for cost-effective, scalable frameworks. By identifying gaps in current research and proposing future directions, this article aims to guide the development of sustainable, AI-driven solutions for agricultural productivity.
Copyright (c) 2026 Noredine Hajraoui, Mourade Azrour, Yousef Farhaoui, Ahmad El Allaoui (Author) https://creativecommons.org/licenses/by/4.0
Rational Emotive Behavior Counseling as an Intervention to Strengthen Grit, Growth Mindset, and Academic Resilience in Higher Education
University students frequently encounter substantial academic pressures that may lead to stress, mental fatigue, and procrastination—conditions that negatively affect both academic achievement and psychological well-being. Psychological capacities such as grit, growth mindset, and academic resilience are essential in helping students navigate these challenges; however, structured interventions designed to strengthen these traits remain limited, particularly within the Indonesian higher education context. Therefore, this pilot study sought to evaluate the effectiveness of a structured group counseling intervention aimed at enhancing grit, growth mindset, and academic resilience among first-year university students. Twelve students identified with low baseline levels of these traits participated in six counseling sessions emphasizing cognitive restructuring, emotional regulation, and behavioral development. A time-series design was utilized to monitor changes at multiple points before, during, and after the intervention. The results indicated consistent improvement across all measured variables, with participants demonstrating increased perseverance, stronger beliefs in personal growth, and enhanced resilience in responding to academic challenges. These outcomes suggest that structured cognitive-behavioral counseling holds promise as an effective approach for strengthening essential psychological traits that support student adaptation and academic success. Nevertheless, further investigations employing randomized controlled trials with larger samples and follow-up evaluations are recommended to confirm and extend these preliminary findings.
Copyright (c) 2026 Galuh Adji Pratama, Mazidah Mohd Dagang, Gian Sugiana Sugara (Author) https://creativecommons.org/licenses/by/4.0
Optimization of Tasamuh concept through GESI approach to Fatayat organization to realize inclusive public islam
Introduction: the concept of tasamuh (tolerance) in Indonesia is a fundamental value that is the foundation for people's lives. The concept of tasamuh (tolerance) in Indonesia is a fundamental value that is the foundation for people's lives. This study aims to formulate optimization model tasamuh through GESI approach. Method: this study uses a mixed approach (mixed methods) that combines qualitative and quantitative methods. Research design using a combinative model (convergent parallel design). Data collection techniques were conducted through direct observation, In-Depth Interviews, Questionnaire dissemination, and document analysis. The study sample was 300 people. Results: The results showed that the majority of respondents had a positive perception of the value of Tasamuh and the application of the Gender Equality and Social Inclusion (GESI) principle, with 70–80 % agreeing. Neutral responses ranged from 10-20 %, while negative responses remained below 15 %. These findings suggest that strengthening Tasamuh and applying GESI are effective ways of achieving an inclusive public Islam. Conclusions: fatayat nahdlatul ulama succeeded in internalizing Tasamuh and GESI in building an inclusive and equitable public Islam. Further research could explore the effectiveness of implementing these values at the local level as well as their impact on strengthening the role of women in religious communities.
Copyright (c) 2026 Ifa Khoiria Ningrum, Agus Sholahudin, Mas Tajuddin Ahmad, Nilna Indriana, Nurul Musyafa'ah, Muhammad Afthon Ulin Nuha (Author) https://creativecommons.org/licenses/by/4.0
Technologies for Stakeholder Management in Sustainable Tourism in Manabí, Ecuador
Introduction: Sustainable tourism faces multiple challenges in the efficient management of its stakeholders, requiring the adoption of innovative solutions. In this context, artificial intelligence (AI) and Big Data analytics have proven to be strategic tools for optimizing decision-making and tourism planning. Objective: To analyze the impact of artificial intelligence and Big Data on stakeholder management in the province of Manabí, Ecuador, through the implementation of a predictive analysis and recommendation system. Methods: An AI and Big Data-based system integrating machine learning algorithms and real-time data analysis was developed. A case study was conducted in Manabí, applying inferential statistical analysis tools to assess the system’s effectiveness in stakeholder coordination, resource utilization, and tourist experience enhancement. Results: The integration of AI and Big Data improves stakeholder coordination, optimizes resource utilization, and enhances the tourist experience. Statistical analyses reveal significant differences in response time reduction, resource savings, and stakeholder satisfaction after system implementation. Conclusions: These technologies represent a viable strategy to promote sustainability and efficiency in the tourism sector. Investment in digital infrastructure and training programs is recommended to facilitate adoption.
Copyright (c) 2025 Maritza Sandra Pibaque Pionce, Jose Jorge Tualombo Tituaña, Martha Lorena Figueroa Soledispa, Gloria Pascuala Chiquito Tigua (Author) https://creativecommons.org/licenses/by/4.0
Digital Citizen Participation and Sustainable Development Goals in Ecuadorian Municipalities: An Integrative Review
Digital citizen participation has emerged over the past decade as an essential component of local governance, particularly within the framework of the Sustainable Development Goals (SDGs). In Ecuador, municipalities have progressively incorporated digital technologies with the aim of promoting public consultation processes that are more transparent, inclusive, and efficient. The objective of this study was to analyse, through a systematic review and a bibliometric assessment, the impact of digital citizen participation in Ecuadorian municipalities and its relationship with the fulfilment of the SDGs. The search was conducted in the Scopus database, covering publications from 2015 to 2025. Out of a total of 176 identified documents, 26 met the inclusion criteria established in accordance with the PRISMA protocol. The PICo model was applied to structure the research question, and the Bibliometrix software in R was used to generate thematic maps, collaboration networks, factorial analyses, and co-occurrence structures. The results show a significant increase in scientific production related to digital participation, with a particular focus on governmental transparency, territorial planning, and civic engagement. However, limitations persist, including digital divides, low technological literacy, structural inequalities, and the absence of integrated public policies. The findings indicate that digital citizen participation contributes positively to SDGs 11 and 16, especially in relation to access to public information and institutional strengthening. Nevertheless, its effectiveness depends on factors such as technological infrastructure, political will, the inclusion of vulnerable groups, and citizens’ digital competencies. It is concluded that Ecuadorian municipalities require strategies focused on digital equity, technological interoperability, and the promotion of a participatory culture that enables more inclusive and sustainable governance.
Copyright (c) 2025 Francisco Marcelo Alvarado Porras, Marlon Geovanny Salazar Torres, Vanessa Scarlet Navarro Moreira (Author) https://creativecommons.org/licenses/by/4.0
Effect of Generative Artificial Intelligence Use on Diagnostic Learning in Medical Students: A Quasi-Experimental Study
Generative artificial intelligence (GenAI) has emerged as a transformative tool in medical education, particularly in the development of diagnostic learning and clinical reasoning skills. This study aimed to examine the effect of GenAI use on diagnostic learning among medical students through a quasi-experimental pretest–posttest design. A total of 62 students participated, assigned to an experimental group that used GenAI to solve clinical cases and a control group that relied on traditional study methods. Findings showed a markedly greater improvement in the experimental group, which achieved higher gains in diagnostic accuracy, quality of reasoning and reduced case-resolution time. Students' perceptions were highly positive, emphasising the usefulness, clarity and cognitive support offered by GenAI. Although moderate risks of error were identified, they did not significantly affect the overall evaluation of the tool. The study concludes that generative AI significantly enhances diagnostic learning and strengthens essential clinical competencies, provided its implementation occurs within an appropriate ethical and pedagogical framework. These results open new avenues for research regarding curriculum integration, impact on more complex clinical scenarios and its potential as an intelligent tutoring resource in contemporary medical education.
Copyright (c) 2025 Johanna Nathaly Hidalgo Guevara, Alexander Ismael Hidalgo Guevara (Author) https://creativecommons.org/licenses/by/4.0
Impact of collaborative STEAM learning on the development of metacognitive skills in students
This study was conducted to understand how collaborative learning within a STEAM framework had influenced the development of metacognitive skills among primary and secondary students, considering the persistent challenges of cognitive self-regulation in Latin American educational contexts. The general objective was to determine the impact of this interdisciplinary methodology on students’ planning, monitoring, and self-assessment abilities. A mixed-method sequential explanatory design was applied, including pretest and posttest questionnaires administered to 600 students and semi-structured interviews with 100 teachers. The results showed significant improvements in students’ ability to organize study strategies, evaluate their performance, and reflect on the cognitive processes used. Teachers' interviews supported these findings, describing increased autonomy, active participation, and meaningful engagement in collaborative tasks. Overall, the STEAM intervention enabled students to develop greater metacognitive awareness, demonstrating that disciplinary integration and cooperative work constituted effective pathways for enhancing cognitive self-regulation and promoting deeper learning.
Copyright (c) 2025 José Fabricio Cabrera Toro, María Alejandra Cordero Apolo, María Marcela Cabrera Toro, Daniel Fernando Cabrera Toro (Author) https://creativecommons.org/licenses/by/4.0
Enhancing the Effectiveness of Learning Models: Key Factors Explored Higher Education
Enhancing the effectiveness of learning models remains a challenge in the digital era, making it crucial to understand the factors that influence learning outcomes. This study aims to analyze the factors affecting the effectiveness of learning models in a digital context. A quantitative survey was conducted using questionnaires as the primary data collection instrument, involving 144 students from the Informatics Study Program at the Faculty of Engineering, Universitas Negeri Padang. Data were analyzed using Structural Equation Modeling (SEM) with Smart PLS 4.0 software, and the measurement model was found to be valid and reliable. The results indicate that student characteristics and learning quality have positive but modest effects on learning effectiveness, while the learning environment and learning models show minimal negative correlations. Learning technology was identified as the most influential factor, significantly enhancing the effectiveness of learning models. These findings suggest that prioritizing learning technology can substantially improve the effectiveness of digital learning, whereas other factors have relatively smaller impacts.
Copyright (c) 2025 Ika Parma Dewi, Doni Tri Putra Yanto, Ilmiyati Rahmy Jasri, Afif Rahman Riyanda, Mastri Dihita Sagala, Cherifa Boudia, Dedy Irfan, Asmaa Bengueddach (Author) https://creativecommons.org/licenses/by/4.0
QBD Driven Approach Design and Optimization of Lipid-Based Nanoformulation of Cannabidiol for Enhanced Treatment of Non-Melanoma Skin Cancer
Introduction: The non-melanoma skin cancer (NMSC) is a very commonly detected malignancy globally, contributing significantly to patient morbidity and placing a substantial burden on healthcare systems. Objective: This study aims to develop a stable cannabidiol (CBD)-incorporated nanostructured lipid carrier (NLC) for treating the non-melanoma skin cancer. Methods: In the current study, we report the design, development and characterization of a cannabidiol (CBD)-incorporated nanostructured lipid carrier (NLC) gel formulation (CBD loaded NLC gel), a novel topical therapeutic approach for treating the NMSC. The optimization of the NLC was effectively carried out using a central composite design (CCD), which enabled the systematic evaluation of formulation variables and their impact on key physicochemical parameters. Results: The final optimized CBD-NLC formulation exhibited mean particle size of 154.7 nm and a zeta potential of +30.12 mV, indicating good stability and potential for effective skin interaction. The cumulative drug release and skin permeation studies using Wistar rat skin demonstrated enhanced and sustained delivery of CBD into the epidermal and dermal layers, facilitated by the lipid-based nanocarrier system. Further, the cytotoxic ability of the CBD Loaded NLC formulation was evaluated using A375 human melanoma cells. The MTT assay revealed a significantly lower IC₅₀ value of 3.07 µg/mL for the CBD loaded NLC gel compared to conventional formulations, indicating improved anticancer activity. Conclusion: Cannabidiol (CBD)-incorporated nanostructured lipid carrier (NLC) gel formulation exhibited suitable release, skin permeation and cytotoxic potential for the treatment the non-melanoma skin cancer.
Copyright (c) 2026 Mohammed F. Aldawsari, Md. Khalid Anwer (Author) https://creativecommons.org/licenses/by/4.0
Effective Therapeutic Communication Model in Reducing Stunting in Secanggang District, Langkat Regency, North Sumatra
This research aims to develop and evaluate the effectiveness of a therapeutic communication model in reducing the prevalence of stunting in Secanggang District, Langkat Regency, North Sumatra. Given the high stunting rates ranging from 20-25%, and the need for effective and sustainable intervention, this study designs a model that is responsive to the local social and cultural context. The urgency of this research lies in the pressing need for interventions that not only increase awareness but also change community behaviors related to child care and nutrition practices, aligning with WHO targets and national policies. The methodology employed is qualitative with a phenomenological approach to deeply understand the experiences and perspectives of the community. Primary data was collected through in-depth interviews, participatory observation, and focused group discussions (FGDs) in locations with high stunting prevalence. Data analysis was conducted using Miles, Huberman, and Saldana’s method which includes creating matrices, categorization, coding, visual data presentation, and validating findings through triangulation techniques to strengthen result validity. The findings indicate that the proposed therapeutic communication model—including health education, family support, participatory communication, health service integration, and policy advocacy—has significant potential to improve community nutritional knowledge and behaviors. However, challenges in implementing this model primarily involve limitations in infrastructure, access to services, and sustainability of community participation. Discussion of these results leads to recommendations for adjusting the model to consider specific needs and local conditions, and for enhancing resources and cross-sector collaboration for more effective implementation.
Copyright (c) 2026 Dewi Kurniawati, Nurmaini, Aulia Rahma Ritonga (Author) https://creativecommons.org/licenses/by/4.0
Predictive model of complex networks for geopolitical conflicts in global trade: the case of Ecuador
Introduction: the development of Latin American countries requires clear economic integration strategies that reduce the risks associated with geopolitical conflicts. In an international scenario marked by trade tensions and rivalries between powers, the ability to anticipate risk scenarios becomes a strategic tool for guiding national policies and decisions. The objective is to develop a predictive model based on complex networks to assess geopolitical conflicts arising from global trade, applied in Ecuador. Method: the study relied on the structural-functional systemic method to comprehensively analyze the interactions between economic and political factors. A bibliographic review was conducted in high-impact databases, Scopus and Web of Science, complemented by official reports and statements from heads of state. The model was built using Gephi 1.10.1 software, which allowed for a visual representation of trade and geopolitical networks. To assess its robustness, the Historical Validation (Backtesting) method was applied, comparing the model's predictions with events that occurred during the reference period. Results: the results showed high accuracy in identifying geopolitical conflicts, successfully predicting trade tensions with Ecuador's main trading partners, although discrepancies were observed in the actual intensity of some events. Conclusions: while the model is an effective tool for anticipating risks and guiding trade strategies, it requires adjustments that incorporate qualitative and contextual variables. These findings reinforce the need to complement quantitative approaches with interdisciplinary analysis to increase predictive capacity in complex scenarios.
Copyright (c) 2026 Edwin Santiago Núñez Naranjo, Belky Nerea Orbes Revelo , Julio Ricardo Avendaño Barrera (Author) https://creativecommons.org/licenses/by/4.0
Moving Out Of The Class And Developing Environmental Awareness: Experiential Learning Based Ecopedagogy In Action
Introduction: Integrating experiential learning into ecopedagogy provides a practical framework for fostering students’ ecological intelligence and environmental awareness through authentic, context-based experiences. However, conventional science education in Indonesia remains dominated by classroom-based instruction, limiting students’ engagement with real environmental issues. This study aimed to develop and implement the Experiential Learning–Based Ecopedagogy (ELCoCare) model to bridge theoretical understanding with environmental action. Method: This study employed a descriptive qualitative approach to design, implement, and evaluate an experiential learning-based ecopedagogy model (ELCoCare) to enhance students’ environmental awareness. The model comprised five experiential stages—experiencing, reflecting, constructing, performing, and continuing—integrated with ecopedagogical principles. Data were collected through observations, questionnaires, reflective journals, and interviews, and analyzed using a mixed-methods approach that combined descriptive statistics and thematic analysis. Results: The findings indicated a marked improvement in students’ environmental awareness, reflective thinking, and sense of ecological responsibility. Participants exhibited higher sensitivity to local environmental problems and developed innovative solutions through vertical and straightforward farming projects. The structured ELCoCare cycle effectively linked theoretical knowledge with action-oriented sustainability practices. Conclusions: The ELCoCare model successfully enhanced students’ environmental awareness and ecological intelligence by merging experiential learning with ecopedagogy. The approach promoted critical reflection, problem-solving, and sustainable behavior, preparing students to act as environmentally responsible citizens. The model demonstrates strong potential for integration into higher education curricula to strengthen sustainability-oriented teaching and learning.
Copyright (c) 2026 Dwi Yuniasih Saputri , Sukarmin, Asrowi , Riyadi, Elda Frediana Rety Kartika (Author) https://creativecommons.org/licenses/by/4.0
Body Image Concept of Women's Gym Community in Makassar City
Introduction: An ideal body and an attractive appearance are desired by many women. Method: This research is a qualitative research with a phenomenological approach using an in-depth interview method with 18 informants. Results: Gym members had diverse perceptions of body image, encompassing physical assessments, social perceptions, self-improvement motivation, and self-acceptance. These perceptions were shaped by internal and external factors, with social media being a dominant influence in shaping ideal body standards, along with influences from their immediate environment, the gym community, and work demands. Positive body image was shown to improve self-confidence and social performance, while some women still experienced pressure from unrealistic beauty standards. Conclusion: It is necessary to strengthen the concept of body positivity through education, holistic support, and healthy body diversity campaigns to form a healthier and more sustainable body perception.
Copyright (c) 2026 Irma Payuk, Suriah, Indra Fajarwati Ibnu, Shanty Riskiyani, Apik Indarty Moedjiono (Author) https://creativecommons.org/licenses/by/4.0
Development of BETA learning applications (Balaghah and exploration Tadzawwuq Adabiy) on Balaghah subjects to realize pesantren Revolution 5.0
Introduction: pesantren education faces the greatest challenge of integrating traditional values with technological innovations in order to remain relevant to the needs of the times. This study aims to develop and test the feasibility of BETA learning applications as a balaghah learning medium in line with the concept of pesantren Revolution 5.0. Methods: research was conducted using the Borg & Gall R&D method. The initial trial involved 50 students, followed by a large-scale test with 100 students. The research instruments used were observation, testing, questionnaires and expert validation, as well as statistical and descriptive tests. Results: the study showed that experts declared the BETA application highly viable, with a feasibility rate above 90 %. Students showed over 80% active participation, increasing the average understanding and appreciation of Arabic literature to over 80 %. These findings suggest that using BETA applications effectively improves the quality of Balaghah learning while maintaining student engagement. Conclusions: the BETA application was proven to be a feasible and effective learning medium for Balaghah, increasing student motivation, participation and learning outcomes. Further research will focus on developing application features and adapting them for different levels of education, as well as conducting comparative studies with other digital learning media.
Copyright (c) 2026 Nurul Musyafa'ah, Ulfa Ulfa, Amirul Kholid, Rizka Widayanti, Muhammad Afthon Ulin Nuha, Hilmy Aliriad (Author) https://creativecommons.org/licenses/by/4.0
A Post-Pandemic Management Model for Enhancing Junior High School Teachers’ Professional Competence in Yogyakarta, Indonesia: Development and Validation
The Covid-19 pandemic exposed critical gaps in the professional competence of Indonesian teachers, particularly in digital pedagogy and adaptive instruction. In the Special Region of Yogyakarta, government-led initiatives such as the Zoning-Based Learning Competency Development Program (PKP) and the Teacher Leadership Program (PPGP) were implemented during the pandemic but exhibited systemic weaknesses, including inconsistent execution, weak monitoring, and limited reach to suburban and remote schools. This study investigates the management models applied during the pandemic, identifies their operational shortcomings, and proposes a novel, empirically grounded conceptual model for post-pandemic teacher professional development. Using a mixed-methods research and development design adapted from Borg and Gall, data were collected through observations, semi-structured interviews, and document analysis involving 70 teachers, school principals, supervisors, and education officials in Bantul Regency. Findings reveal that existing models relied on only four classical management functions and suffered from poor planning, inadequate technological integration, and insufficient follow-up. In response, the researchers developed a six-function management model—planning, organizing, facilitating, actuating, controlling, and evaluating—centered on blended collaborative study groups and university–school partnerships. Expert validation (n = 8) and three phases of field trials (n = 10, 20, and 30 teachers) demonstrated high effectiveness (mean = 3.73), efficiency (mean = 3.73), and practicality (mean = 3.67) on a 4-point Likert scale. The model offers a scalable, context-sensitive framework for post-pandemic teacher development in Indonesia and similar Global South contexts.
Copyright (c) 2026 Vezir Ashyrnepesov, Suyanto, Cepi Safruddin Abd Jabar (Author) https://creativecommons.org/licenses/by/4.0