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All Journal Al-Hijr: Journal of Adulearn World Rechtsnormen Journal of Law Journal Neosantara Hybrid Learning Darussalam: Journal of Psychology and Educational Media of Health Research International Journal of Educational Insights and Innovations (IJEDINS) Journal of Computer Science Advancements Journal of Moeslim Research Technik Journal of Selvicoltura Asean Techno Agriculturae Studium of Research Research of Scientia Naturalis Journal of Social Entrepreneurship and Creative Technology Journal of Humanities Research Sustainability Journal of Community Nursing and Primary Care
Li Wei
SuZhou University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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The Relationship Between Gadget Exposure and Musculoskeletal Complaints among Office Workers Ananda, Rizky; Wei, Li; Hafizi, M Zainul
Media of Health Research Vol. 3 No. 3 (2025): Media of Health Research, December 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/mohr.v3i3.316

Abstract

Excessive gadget use has become a significant occupational health concern, particularly among office workers who spend extended hours using computers, smartphones, and other digital devices. Prolonged exposure often leads to poor posture, repetitive movements, and increased risk of musculoskeletal disorders (MSDs). This study aims to investigate the relationship between gadget exposure and musculoskeletal complaints among office workers. A cross-sectional survey was conducted involving 250 office employees in Jakarta, Indonesia, and Beijing, China. Data were collected using a standardized questionnaire that assessed duration of gadget use, ergonomic practices, and musculoskeletal symptoms. The results indicated that office workers who used gadgets for more than 6 hours daily had a significantly higher prevalence of neck pain (62.8%), lower back pain (48.5%), and wrist discomfort (35.4%) compared to those with shorter exposure (p < 0.05). Multivariate analysis confirmed that prolonged gadget use, lack of ergonomic awareness, and absence of rest breaks were independent predictors of musculoskeletal complaints. These findings highlight the urgent need for ergonomic interventions and organizational policies promoting healthy digital habits. This research contributes to occupational health literature by providing cross-cultural evidence of gadget-related musculoskeletal risks and emphasizing preventive workplace strategies.
QUANTUM ADVANTAGE HAS ARRIVED: TANGIBLE IMPACTS ON DRUG DISCOVERY AND NEW MATERIALS Wei, Li; Hui, Zhou; Yang, Liu
Journal of Computer Science Advancements Vol. 3 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v3i5.3325

Abstract

The advancement of computational chemistry is currently stalled by the exponential memory scaling required to simulate strongly correlated electron systems on classical supercomputers. This fundamental barrier significantly impedes the rational design of complex pharmaceuticals and next-generation catalytic materials. This research aims to rigorously validate the immediate utility of Noisy Intermediate-Scale Quantum (NISQ) processors, demonstrating that “Quantum Advantage” has shifted from a theoretical milestone to a practical industrial reality. We employed a comparative research design utilizing the Variational Quantum Eigensolver (VQE) algorithm on the IBM Eagle quantum processor. The study targeted the electronic structure of iron-sulfur clusters and KRAS-G12C inhibitor binding sites, benchmarking quantum outputs against classical Density Functional Theory (DFT) and Full Configuration Interaction (FCI) standards, utilizing Zero-Noise Extrapolation for error mitigation. Results indicate that quantum simulations achieved chemical accuracy (within 1.6 kcal/mol) for these complex systems, whereas classical methods failed with deviations exceeding 8 kcal/mol. The data confirms that quantum hardware can now resolve electronic correlations invisible to classical approximation. We conclude that quantum computing offers a tangible, immediate pathway to accelerate discovery cycles in drug development and material science, necessitating the integration of hybrid quantum workflows into modern R&D pipelines.
MICROBIAL RESILIENCE UNDER ENVIRONMENTAL STRESS: A SYSTEMS-LEVEL ANALYSIS OF METABOLIC AND GENOMIC ADAPTATION Salim, Achmad Agus; Wei, Li; Johnson, Emily
Research of Scientia Naturalis Vol. 3 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v3i2.3630

Abstract

Microbial resilience under environmental stress represents a fundamental aspect of biological survival, shaped by complex interactions between metabolic processes and genomic adaptation. Increasing environmental pressures such as temperature fluctuation, oxidative stress, and nutrient limitation challenge microbial stability, yet existing studies often examine metabolic and genetic responses in isolation. This study aims to develop a systems-level framework that integrates metabolic and genomic dimensions to explain how microorganisms sustain functionality under stress. The research employs a mixed-methods design combining laboratory-based multi-omics data, secondary datasets, and nonlinear computational modeling to analyze adaptive responses across temporal phases. Results indicate that microbial resilience is governed by coordinated mechanisms involving rapid metabolic reprogramming and subsequent genomic modification, with nonlinear dynamics such as threshold effects and multi-stable states shaping system behavior. Gene expression, metabolite flux, and mutation frequency exhibit strong interdependence, revealing feedback-driven adaptation rather than linear response patterns. The findings demonstrate that resilience emerges as a dynamic and context-sensitive process rather than a static trait. The study concludes that integrating ecological, metabolic, and genomic perspectives through nonlinear modeling significantly enhances the understanding of microbial adaptation and provides a robust analytical framework for future research and applied sciences.
The effect of the peer support on stigma among patients with obesity: A quasi-experimental study Wei, Li; Min, Zhang; Jun, Wang
Journal of Community Nursing and Primary Care Vol. 3 No. 1 (2026): January - June
Publisher : Science Center Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63202/jcnpc.v3i1.128

Abstract

Background: Obesity is a growing global public health concern that is frequently accompanied by weight-related stigma, which negatively affects psychological well-being, social participation, and engagement in health services. Stigma represents a critical psychosocial barrier in obesity management that is often insufficiently addressed by conventional interventions focusing primarily on behavioral and clinical outcomes. Peer support has emerged as a promising approach to address psychosocial challenges through shared experiences and mutual support in community settings. Objective: This study aimed to examine the effect of peer support on stigma among patients with obesity in a community-based context. Methods: A quasi-experimental study with a pretest–posttest control group design was conducted among adults with obesity recruited from community health programs. Participants were allocated into an intervention group receiving a structured peer support program and a control group receiving usual community-based health education. Stigma was measured using a validated weight stigma instrument before and after the intervention. Data were analyzed using descriptive and inferential statistics to assess within-group and between-group differences. Results: The intervention group demonstrated a significant reduction in overall stigma scores following the peer support program, whereas the control group showed no significant change. Post-intervention stigma levels were significantly lower in the intervention group compared to the control group. Subdomain analysis revealed substantial improvements in internalized stigma and perceived social rejection, with a moderate improvement in emotional distress. The findings indicate a clinically meaningful and statistically significant effect of peer support on stigma reduction. Conclusion: Peer support is an effective community-based intervention for reducing stigma among patients with obesity. The intervention addresses key psychosocial dimensions of obesity by enhancing self-acceptance, emotional support, and social connectedness.Community obesity programs should integrate peer support as a complementary strategy to conventional interventions, and future research should explore long-term outcomes and scalability across diverse populations.
REAL-TIME LEARNING ANALYTICS: THE ROLE OF AI IN MONITORING STUDENT PROGRESS Mahadjani, Marten; Wei, Li; Yang, Liu
Al-Hijr: Journal of Adulearn World Vol. 5 No. 2 (2026)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/alhijr.v5i2.1269

Abstract

The integration of Artificial Intelligence (AI) in education has significantly transformed how student progress is monitored in real-time, offering valuable insights into individual learning trajectories. Real-time learning analytics powered by AI provide educators with the ability to track and assess students’ performance continuously, facilitating timely interventions and personalized learning experiences. Despite the potential of AI to enhance educational outcomes, its impact on the overall teacher-student dynamic and the challenges associated with its integration into traditional pedagogical frameworks remain underexplored. This study aims to investigate the role of AI in real-time learning analytics and its effect on monitoring student progress, exploring both its benefits and limitations. The research employs a mixed-methods approach, combining quantitative surveys, qualitative interviews, and classroom observations across 10 educational institutions utilizing AI-powered learning tools. The results indicate that AI tools significantly improve student engagement, performance, and the timeliness of feedback, but concerns about the depersonalization of interactions were also raised by both students and teachers. The study concludes that while AI can enhance the monitoring of student progress, it must be integrated in a way that preserves the human aspects of teaching. AI should complement, not replace, the teacher's role in providing emotional and social support in the learning process.
CREATIVE BUSINESS MODELS FOR SOCIAL CHANGE: INTEGRATING TECHNOLOGY, COMMUNITY, AND SUSTAINABILITY Merung, Arteurt Yoseph; Tan, Ethan; Wei, Li; Muller, Johannes
Journal of Social Entrepreneurship and Creative Technology Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v3i1.3297

Abstract

The growing complexity of social and environmental challenges has exposed the limitations of conventional business models that prioritize economic value over societal well-being. In response, creative business models have emerged as alternative approaches that integrate technology, community engagement, and sustainability to generate social change. This study aims to examine how such creative business models are structured and how the integration of technological enablement, community participation, and sustainability principles contributes to long-term social impact. The research employs a qualitative and exploratory design based on secondary data analysis of peer-reviewed literature, policy reports, and documented case studies of social enterprises and community-based ventures. Thematic and cross-case analysis was conducted to identify recurring patterns of value creation, governance, and innovation processes. The findings reveal that social change-oriented business models are most effective when technology functions as an enabling infrastructure, communities act as co-creators rather than beneficiaries, and sustainability is embedded as a core value logic. Integrated models demonstrate greater resilience, legitimacy, and adaptability compared to fragmented approaches. The study concludes that creative business models represent a viable pathway for aligning economic activity with social and environmental objectives. Strengthening integration among technology, community, and sustainability is essential for advancing inclusive and sustainable societal transformation.
ELECTROCHEMICAL SYSTEMS ENGINEERING: MODELING, CONTROL, AND DEGRADATION ANALYSIS Nakamura, Yui; Wei, Li; Arfan, Arfan
Journal of Moeslim Research Technik Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v3i1.3341

Abstract

The global transition toward sustainable energy infrastructure relies heavily on the reliability and longevity of electrochemical energy storage systems. However, conventional management strategies often struggle with the highly non-linear dynamics and unobservable internal degradation mechanisms of these devices. This research addresses the critical need for advanced systems engineering by evaluating a physics-based framework for real-time modeling, state-aware control, and non-invasive degradation analysis. The study aims to optimize the balance between operational performance and capacity retention through the implementation of reduced-order Doyle-Fuller-Newman models. Utilizing a multi-physics experimental design, forty lithium-ion cells were subjected to high-rate cycling while monitored by an adaptive observer-based controller. Results demonstrate that the physics-based approach achieves a 75% reduction in state-of-estimation error compared to empirical models, while significantly mitigating internal resistance growth. Furthermore, the “health-aware” control strategy successfully improved capacity retention by 7.2% over 1,000 cycles by preemptively preventing lithium plating thresholds. This research concludes that internal state visibility is a prerequisite for achieving maximum electrochemical utilization. The findings provide a scalable blueprint for the next generation of resilient battery management systems, asserting that the integration of multi-scale physical models into control architectures is essential for securing the future of global energy storage.
Co-Authors Ananda, Fiqih Ananda, Rizky Arfan Arfan Aulia, Hafidzatul Desmita Desmita Fernandez, Carloz Gonzales, Samnatha Hafizi, M Zainul Hui, Zhou Johannes Muller, Johannes Johnson, Emily Khan, Omar Khasanah, Wirdatul Kumar, Rohan Liu Yang Mahadjani, Marten Mahmuda, Nafila Merung, Arteurt Yoseph Min, Zhang Na, Li Nakamura, Yui Nurhayati Nurhayati Nurlatipah, Nurlatipah Rustiyana, Rustiyana Salim, Achmad Agus Suryani, Ni Kadek Tan, Ethan Wang Jun Widyani, Retno Zhang Li