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All Journal Al-Hijr: Journal of Adulearn World 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 Scientechno: Journal of Science and Technology International Journal of Educational Narratives Rechtsnormen: Journal of Law
Li Wei
Tsinghua University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Physics Other

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MICROBIAL RESILIENCE UNDER ENVIRONMENTAL STRESS: A SYSTEMS-LEVEL ANALYSIS OF METABOLIC AND GENOMIC ADAPTATION Achmad Agus Salim; Li Wei; Emily Johnson
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.
INTEGRATION OF REMOTE SENSING DATA AND GEOGRAPHIC INFORMATION SYSTEM FOR PRECISE MAPPING OF CARBON SEQUESTRATION POTENTIAL IN FOREST Obed Patiung; Nilam Atsirina Krisnaputri; Li Wei
Research of Scientia Naturalis Vol. 3 No. 3 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v3i3.4015

Abstract

Accurate assessment of forest carbon sequestration potential has become increasingly important for climate change mitigation, sustainable forest management, and environmental policy development. Advances in Remote Sensing and Geographic Information System (GIS) technologies offer new opportunities to improve the precision and efficiency of carbon mapping across large and heterogeneous forest landscapes. This study aimed to examine the effectiveness of integrating remote sensing data and GIS techniques for precise mapping of carbon sequestration potential in forest ecosystems and to identify the environmental factors influencing carbon distribution patterns. A quantitative geospatial approach was employed using multisource satellite imagery, vegetation indices, biomass estimates, topographic variables, land-cover data, and field validation measurements. Spatial modeling, statistical analysis, and GIS-based overlay techniques were applied to evaluate carbon sequestration potential across the study area. Results revealed substantial spatial variation in carbon storage capacity, with high-carbon zones concentrated in dense and ecologically intact forests. Vegetation density, biomass accumulation, forest cover percentage, and topographic characteristics showed significant positive relationships with carbon sequestration estimates. Integrated modeling achieved high predictive accuracy and demonstrated strong agreement with field observations. Findings indicate that combining remote sensing and GIS technologies provides a reliable framework for identifying carbon-rich forest areas, supporting evidence-based conservation planning, improving carbon accounting practices, and strengthening climate change mitigation strategies through more accurate spatial assessment of forest carbon resources.
HARNESSING BLOCKCHAIN TECHNOLOGY FOR TRANSPARENT AND SECURE MANAGEMENT OF RESEARCH DATA IN LARGE-SCALE INTERNATIONAL SCIENTIFIC COLLABORATION PROJECTS Faiz Muqorrir Kaaffah; Rachel Chan; Li Wei
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.v3i2.4168

Abstract

Growing reliance on large-scale international scientific collaboration has intensified the need for transparent, secure, and trustworthy research data management to support cross-border data sharing, scientific reproducibility, and institutional accountability. Conventional centralized repositories often face challenges related to data integrity, provenance tracking, interoperability, cybersecurity, and governance consistency. This study evaluated the effectiveness of blockchain technology in strengthening research data management through decentralized governance, immutable provenance, and cryptographic verification. A mixed-methods sequential explanatory design was employed using 3,000 blockchain implementation scenarios across sixty international scientific collaboration projects involving universities, multidisciplinary research institutions, and public research organizations. Quantitative analyses included multivariate statistics, structural equation modeling, hierarchical regression, mediation, and moderation analyses, while qualitative evidence from expert interviews, governance workshops, and institutional document reviews was examined using thematic analysis. The findings demonstrated that consortium and permissioned blockchain architectures consistently outperformed conventional centralized systems by improving research data integrity, provenance accuracy, governance accountability, cybersecurity resilience, interoperability, and collaborative efficiency. Smart contracts and decentralized identity management further enhanced regulatory compliance, automated access control, and scientific reproducibility. Overall, blockchain technology functions as a decentralized governance architecture that integrates technological security with institutional trust, providing a practical framework for universities, research organizations, funding agencies, and policymakers to establish resilient, transparent, accountable, and sustainable global research data governance.
ELECTROCHEMICAL SYSTEMS ENGINEERING: MODELING, CONTROL, AND DEGRADATION ANALYSIS Yui Nakamura; Li Wei; 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.
FOREST-BASED INDUSTRIES AND RURAL DEVELOPMENT IN SOUTHEAST ASIA Li Wei; Zhang Li; Wang Jun
Journal of Selvicoltura Asean Vol. 2 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsa.v2i2.2033

Abstract

Forest-based industries play a crucial role in the economies of Southeast Asia, particularly in rural development. The region is rich in forest resources, which have long been a source of livelihood for many rural communities. However, there is growing concern about the sustainability of these industries, with deforestation and environmental degradation posing challenges to long-term economic development. Understanding the link between forest-based industries and rural development is vital for promoting sustainable practices that benefit both the economy and the environment. This study aims to explore the relationship between forest-based industries and rural development in Southeast Asia, focusing on the economic, social, and environmental impacts. The research seeks to assess how these industries contribute to rural livelihoods, economic growth, and sustainability while addressing the challenges posed by deforestation and unsustainable practices. A mixed-methods approach was used, combining qualitative interviews with stakeholders, including industry representatives, government officials, and rural communities, with quantitative data on economic indicators from forest-based industries in several Southeast Asian countries. The study also includes a comparative analysis of case studies from Indonesia, Malaysia, and Thailand. The study finds that forest-based industries contribute significantly to rural economic growth, providing employment opportunities and improving infrastructure. However, unsustainable logging practices and weak enforcement of environmental regulations have led to environmental degradation and social inequalities. The research concludes that while forest-based industries have the potential to support rural development, their sustainability depends on the adoption of responsible management practices and stronger governance structures.
REAL-TIME LEARNING ANALYTICS: THE ROLE OF AI IN MONITORING STUDENT PROGRESS Marten Mahadjani; Li Wei; Liu Yang
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.
Smart Fertilizing Technologies for Agricultural Efficiency in Canada Nurhayati Nurhayati; Li Wei; Zhang Li
Techno Agriculturae Studium of Research Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v1i4.1595

Abstract

Canada, amid the growing need for sustainable food production. The background of this research focuses on the challenges of modern agriculture in the efficient use of fertilizers and their impact on the environment. The purpose of the study was to examine the extent to which smart fertilization technology can improve agricultural yields while reducing fertilizer use and environmental impact. The research method used is a quantitative approach with field experiments involving farmers in five major Canadian provinces, using soil and weather sensors to collect data in real-time. The results of the study show that smart fertilization technology is able to increase crop yields by up to 22% and reduce fertilizer use by up to 18%, as well as reduce environmental impact by 9-12%. The conclusion of the study is that smart fertilization technology has great potential in improving agricultural efficiency and maintaining environmental sustainability in Canada. However, more research is needed to understand the long-term impact and ensure equitable access to these technologies across the region.
QUANTUM ADVANTAGE HAS ARRIVED: TANGIBLE IMPACTS ON DRUG DISCOVERY AND NEW MATERIALS Li Wei; Zhou Hui; Liu Yang
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.
CREATIVE BUSINESS MODELS FOR SOCIAL CHANGE: INTEGRATING TECHNOLOGY, COMMUNITY, AND SUSTAINABILITY Arteurt Yoseph Merung; Ethan Tan; Li Wei; Johannes Muller
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.
The Philosophy of Consciousness: Understanding the Mind-Body Problem Nurlatipah Nurlatipah; Li Wei; Zhang Li
Journal of Humanities Research Sustainability Vol. 1 No. 5 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jhrs.v1i5.1795

Abstract

Background. The background of this research is based on a long debate between dualism, which separates the mind as a non-physical entity, and materialism, which sees full consciousness as the result of physical processes in the brain. Purpose. The purpose of this study is to explore an integrative approach that tries to bring these two views together to provide a more comprehensive understanding of consciousness.    Method. The research method used is a qualitative approach with in-depth literature analysis, involving the thoughts of leading philosophers and neuroscientists. Results. The results show that the integrative approach has the potential to explain the subjective and physical aspects of consciousness simultaneously, without having to set aside one perspective. Conclusion. The conclusion of this study suggests that mind-body problems require a more cross-disciplinary and inclusive approach, which is able to bridge the gap between philosophy and neuroscience. These findings pave the way for more applicable follow-up research to test the validity of integrative approaches in a variety of practical contexts.
Co-Authors 105120100111001, RAHMAN MALIK Achmad Agus Salim Achmad Hidir Arfan Arfan Arteurt Yoseph Merung Ava Lee Darwan Edyanto Saragih Emily Johnson Ethan Tan Ethan Tan Faiz Muqorrir Kaaffah Fatima Malik Johannes Muller Joni Wilson Sitopu Liu Yang Lucas Lima Mardatillah Mardatillah Marten Mahadjani Muh. Cendekiawan Ainul Haq Nilam Atsirina Krisnaputri Nurhayati Nurhayati Nurlatipah Nurlatipah Patiung, Obed Rachel Chan Retno Widyani Robi Armilus Rustiyana, Rustiyana Sara Hussain Saripuddin M Tiago Costa Wang Jun Wirdatul Khasanah Yui Nakamura Yusuf Krisman Gea Zhang Li Zhou Hui