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Search Results (919)

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Keywords = strategic collaborations

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10 pages, 373 KiB  
Proceeding Paper
Integrating Sustainable Development Goals into Renewable Energy Monopoly: A Generative AI Approach to Sustainable Development Education
by Hung-Cheng Chen
Eng. Proc. 2025, 103(1), 4; https://doi.org/10.3390/engproc2025103004 - 5 Aug 2025
Abstract
This research aims to develop an educational board game, “Sustainable Home: Energy Challenge,” based on Monopoly by integrating sustainable development goals and renewable energy to use ChatGPT in human–computer collaboration. ChatGPT was used for game conceptualization, rule development, board creation, card design, and [...] Read more.
This research aims to develop an educational board game, “Sustainable Home: Energy Challenge,” based on Monopoly by integrating sustainable development goals and renewable energy to use ChatGPT in human–computer collaboration. ChatGPT was used for game conceptualization, rule development, board creation, card design, and simulation in an iterative design. The developed board game demonstrated ChatGPT’s efficiency in educational game design and the benefits of human–computer collaboration. Game simulations validated the board game’s potential as a simulation tool to enhance diversity, cooperation, and strategic depth. The game effectively promoted SDG engagement and sustainable development education in gamified learning. Full article
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28 pages, 2743 KiB  
Article
Unlocking Synergies: How Digital Infrastructure Reshapes the Pollution-Carbon Reduction Nexus at the Chinese Prefecture-Level Cities
by Zhe Ji, Yuqi Chang and Fengxiu Zhou
Sustainability 2025, 17(15), 7066; https://doi.org/10.3390/su17157066 - 4 Aug 2025
Abstract
In the context of global climate governance and the green transition, digital infrastructure serves as a critical enabler of resource allocation in the digital economy, offering strategic value in tackling synergistic pollution and carbon reduction challenges. Using panel data from 280 prefecture-level cities, [...] Read more.
In the context of global climate governance and the green transition, digital infrastructure serves as a critical enabler of resource allocation in the digital economy, offering strategic value in tackling synergistic pollution and carbon reduction challenges. Using panel data from 280 prefecture-level cities, this study employs a multiperiod difference-in-differences (DID) approach, leveraging smart city pilot policies as a quasinatural experiment, to assess how digital infrastructure affects urban synergistic pollution-carbon mitigation (SPCM). The empirical results show that digital infrastructure increases the urban SPCM index by 1.5%, indicating statistically significant effects. Compared with energy and income effects, digital infrastructure can influence this synergistic effect through indirect channels such as the energy effect, economic agglomeration effect, and income effect, with the economic agglomeration effect accounting for a larger share of the total effect. Additionally, fixed-asset investment has a nonlinear moderating effect on this relationship, with diminishing marginal returns on emission reduction when investment exceeds a threshold. Heterogeneity tests reveal greater impacts in eastern, nonresource-based, and environmentally regulated cities. This study expands the theory of collaborative environmental governance from the perspective of new infrastructure, providing a theoretical foundation for establishing a long-term digital technology-driven mechanism for SPCM. Full article
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19 pages, 2280 KiB  
Article
A Swap-Integrated Procurement Model for Supply Chains: Coordinating with Long-Term Wholesale Contracts
by Min-Yeong Ryu and Pyung-Hoi Koo
Mathematics 2025, 13(15), 2495; https://doi.org/10.3390/math13152495 - 3 Aug 2025
Viewed by 109
Abstract
In today’s volatile supply chain environment, organizations require flexible and collaborative procurement strategies. Swap contracts, originally developed as financial instruments, have recently been adopted to address inventory imbalances—such as the 2021 COVID-19 vaccine swap between South Korea and Israel. Despite its increasing adoption [...] Read more.
In today’s volatile supply chain environment, organizations require flexible and collaborative procurement strategies. Swap contracts, originally developed as financial instruments, have recently been adopted to address inventory imbalances—such as the 2021 COVID-19 vaccine swap between South Korea and Israel. Despite its increasing adoption in the real world, theoretical studies on swap-based procurement remain limited. This study proposes an integrated model that combines buyer-to-buyer swap agreements with long-term wholesale contracts under demand uncertainty. The model quantifies the expected swap quantity between parties and embeds it into the profit function to derive optimal order quantities. Numerical experiments are conducted to compare the performance of the proposed strategy with that of a baseline wholesale contract. Sensitivity analyses are performed on key parameters, including demand asymmetry and swap prices. The numerical analysis indicates that the swap-integrated procurement strategy consistently outperforms procurement based on long-term wholesale contracts. Moreover, the results reveal that under the swap-integrated strategy, the optimal order quantity must be adjusted—either increased or decreased—depending on the demand scale of the counterpart and the specified swap price, deviating from the optimal quantity under traditional long-term contracts. These findings highlight the potential of swap-integrated procurement strategies as practical coordination mechanisms across both private and public sectors, offering strategic value in contexts such as vaccine distribution, fresh produce, and other critical products. Full article
(This article belongs to the Special Issue Theoretical and Applied Mathematics in Supply Chain Management)
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23 pages, 2888 KiB  
Review
Machine Learning in Flocculant Research and Application: Toward Smart and Sustainable Water Treatment
by Caichang Ding, Ling Shen, Qiyang Liang and Lixin Li
Separations 2025, 12(8), 203; https://doi.org/10.3390/separations12080203 - 1 Aug 2025
Viewed by 179
Abstract
Flocculants are indispensable in water and wastewater treatment, enabling the aggregation and removal of suspended particles, colloids, and emulsions. However, the conventional development and application of flocculants rely heavily on empirical methods, which are time-consuming, resource-intensive, and environmentally problematic due to issues such [...] Read more.
Flocculants are indispensable in water and wastewater treatment, enabling the aggregation and removal of suspended particles, colloids, and emulsions. However, the conventional development and application of flocculants rely heavily on empirical methods, which are time-consuming, resource-intensive, and environmentally problematic due to issues such as sludge production and chemical residues. Recent advances in machine learning (ML) have opened transformative avenues for the design, optimization, and intelligent application of flocculants. This review systematically examines the integration of ML into flocculant research, covering algorithmic approaches, data-driven structure–property modeling, high-throughput formulation screening, and smart process control. ML models—including random forests, neural networks, and Gaussian processes—have successfully predicted flocculation performance, guided synthesis optimization, and enabled real-time dosing control. Applications extend to both synthetic and bioflocculants, with ML facilitating strain engineering, fermentation yield prediction, and polymer degradability assessments. Furthermore, the convergence of ML with IoT, digital twins, and life cycle assessment tools has accelerated the transition toward sustainable, adaptive, and low-impact treatment technologies. Despite its potential, challenges remain in data standardization, model interpretability, and real-world implementation. This review concludes by outlining strategic pathways for future research, including the development of open datasets, hybrid physics–ML frameworks, and interdisciplinary collaborations. By leveraging ML, the next generation of flocculant systems can be more effective, environmentally benign, and intelligently controlled, contributing to global water sustainability goals. Full article
(This article belongs to the Section Environmental Separations)
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26 pages, 1263 KiB  
Article
Identifying Key Digital Enablers for Urban Carbon Reduction: A Strategy-Focused Study of AI, Big Data, and Blockchain Technologies
by Rongyu Pei, Meiqi Chen and Ziyang Liu
Systems 2025, 13(8), 646; https://doi.org/10.3390/systems13080646 - 1 Aug 2025
Viewed by 193
Abstract
The integration of artificial intelligence (AI), big data analytics, and blockchain technologies within the digital economy presents transformative opportunities for promoting low-carbon urban development. However, a systematic understanding of how these digital innovations influence urban carbon mitigation remains limited. This study addresses this [...] Read more.
The integration of artificial intelligence (AI), big data analytics, and blockchain technologies within the digital economy presents transformative opportunities for promoting low-carbon urban development. However, a systematic understanding of how these digital innovations influence urban carbon mitigation remains limited. This study addresses this gap by proposing two research questions (RQs): (1) What are the key success factors for artificial intelligence, big data, and blockchain in urban carbon emission reduction? (2) How do these technologies interact and support the transition to low-carbon cities? To answer these questions, the study employs a hybrid methodological framework combining the decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) techniques. The data were collected through structured expert questionnaires, enabling the identification and hierarchical analysis of twelve critical success factors (CSFs). Grounded in sustainability transitions theory and institutional theory, the CSFs are categorized into three dimensions: (1) digital infrastructure and technological applications; (2) digital transformation of industry and economy; (3) sustainable urban governance. The results reveal that e-commerce and sustainable logistics, the adoption of the circular economy, and cross-sector collaboration are the most influential drivers of digital-enabled decarbonization, while foundational elements such as smart energy systems and digital infrastructure act as key enablers. The DEMATEL-ISM approach facilitates a system-level understanding of the causal relationships and strategic priorities among the CSFs, offering actionable insights for urban planners, policymakers, and stakeholders committed to sustainable digital transformation and carbon neutrality. Full article
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19 pages, 2528 KiB  
Systematic Review
The Nexus Between Green Finance and Artificial Intelligence: A Systemic Bibliometric Analysis Based on Web of Science Database
by Katerina Fotova Čiković, Violeta Cvetkoska and Dinko Primorac
J. Risk Financial Manag. 2025, 18(8), 420; https://doi.org/10.3390/jrfm18080420 - 1 Aug 2025
Viewed by 237
Abstract
The intersection of green finance and artificial intelligence (AI) represents a rapidly emerging and high-impact research domain with the potential to reshape sustainable economic systems. This study presents a comprehensive bibliometric and network analysis aimed at mapping the scientific landscape, identifying research hotspots, [...] Read more.
The intersection of green finance and artificial intelligence (AI) represents a rapidly emerging and high-impact research domain with the potential to reshape sustainable economic systems. This study presents a comprehensive bibliometric and network analysis aimed at mapping the scientific landscape, identifying research hotspots, and highlighting methodological trends at this nexus. A dataset of 268 peer-reviewed publications (2014–June 2025) was retrieved from the Web of Science Core Collection, filtered by the Business Economics category. Analytical techniques employed include Bibliometrix in R, VOSviewer, and science mapping tools such as thematic mapping, trend topic analysis, co-citation networks, and co-occurrence clustering. Results indicate an annual growth rate of 53.31%, with China leading in both productivity and impact, followed by Vietnam and the United Kingdom. The most prolific affiliations and authors, primarily based in China, underscore a concentrated regional research output. The most relevant journals include Energy Economics and Finance Research Letters. Network visualizations identified 17 clusters, with focused analysis on the top three: (1) Emission, Health, and Environmental Risk, (2) Institutional and Technological Infrastructure, and (3) Green Innovation and Sustainable Urban Development. The methodological landscape is equally diverse, with top techniques including blockchain technology, large language models, convolutional neural networks, sentiment analysis, and structural equation modeling, demonstrating a blend of traditional econometrics and advanced AI. This study not only uncovers intellectual structures and thematic evolution but also identifies underdeveloped areas and proposes future research directions. These include dynamic topic modeling, regional case studies, and ethical frameworks for AI in sustainable finance. The findings provide a strategic foundation for advancing interdisciplinary collaboration and policy innovation in green AI–finance ecosystems. Full article
(This article belongs to the Special Issue Commercial Banking and FinTech in Emerging Economies)
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24 pages, 2982 KiB  
Review
Residual Stresses in Metal Manufacturing: A Bibliometric Review
by Diego Vergara, Pablo Fernández-Arias, Edwan Anderson Ariza-Echeverri and Antonio del Bosque
Materials 2025, 18(15), 3612; https://doi.org/10.3390/ma18153612 - 31 Jul 2025
Viewed by 129
Abstract
The growing complexity of modern manufacturing has intensified the need for precise control of residual stresses to ensure structural reliability, dimensional stability, and material performance. This study conducts a bibliometric review using data from Scopus and Web of Science, covering publications from 2019 [...] Read more.
The growing complexity of modern manufacturing has intensified the need for precise control of residual stresses to ensure structural reliability, dimensional stability, and material performance. This study conducts a bibliometric review using data from Scopus and Web of Science, covering publications from 2019 to 2024. Residual stress research in metal manufacturing has gained prominence, particularly in relation to welding, additive manufacturing, and machining—processes that induce significant stress gradients affecting mechanical behavior and service life. Emerging trends focus on simulation-based prediction methods, such as the finite element method, heat treatment optimization, and stress-induced defect prevention. Key thematic clusters include process-induced microstructural changes, mechanical property enhancement, and the integration of modeling with experimental validation. By analyzing the evolution of research output, global collaboration networks, and process-specific contributions, this review provides a comprehensive overview of current challenges and identifies strategic directions for future research in residual stress management in advanced metal manufacturing. Full article
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18 pages, 2894 KiB  
Article
Technology Roadmap Methodology and Tool Upgrades to Support Strategic Decision in Space Exploration
by Giuseppe Narducci, Roberta Fusaro and Nicole Viola
Aerospace 2025, 12(8), 682; https://doi.org/10.3390/aerospace12080682 - 30 Jul 2025
Viewed by 99
Abstract
Technological roadmaps are essential tools for managing and planning complex projects, especially in the rapidly evolving field of space exploration. Defined as dynamic schedules, they support strategic and long-term planning while coordinating current and future objectives with particular technology solutions. Currently, the available [...] Read more.
Technological roadmaps are essential tools for managing and planning complex projects, especially in the rapidly evolving field of space exploration. Defined as dynamic schedules, they support strategic and long-term planning while coordinating current and future objectives with particular technology solutions. Currently, the available methodologies are mostly built on experts’ opinions and in just few cases, methodologies and tools have been developed to support the decision makers with a rational approach. In any case, all the available approaches are meant to draw “ideal” maturation plans. Therefore, it is deemed essential to develop an integrate new algorithms able to decision guidelines on “non-nominal” scenarios. In this context, Politecnico di Torino, in collaboration with the European Space Agency (ESA) and Thales Alenia Space–Italia, developed the Technology Roadmapping Strategy (TRIS), a multi-step process designed to create robust and data-driven roadmaps. However, one of the main concerns with its initial implementation was that TRIS did not account for time and budget estimates specific to the space exploration environment, nor was it capable of generating alternative development paths under constrained conditions. This paper discloses two main significant updates to TRIS methodology: (1) improved time and budget estimation to better reflect the specific challenges of space exploration scenarios and (2) the capability of generating alternative roadmaps, i.e., alternative technological maturation paths in resource-constrained scenarios, balancing financial and temporal limitations. The application of the developed routines to available case studies confirms the tool’s ability to provide consistent planning outputs across multiple scenarios without exceeding 20% deviation from expert-based judgements available as reference. The results demonstrate the potential of the enhanced methodology in supporting strategic decision making in early-phase mission planning, ensuring adaptability to changing conditions, optimized use of time and financial resources, as well as guaranteeing an improved flexibility of the tool. By integrating data-driven prioritization, uncertainty modeling, and resource-constrained planning, TRIS equips mission planners with reliable tools to navigate the complexities of space exploration projects. This methodology ensures that roadmaps remain adaptable to changing conditions and optimized for real-world challenges, supporting the sustainable advancement of space exploration initiatives. Full article
(This article belongs to the Section Astronautics & Space Science)
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18 pages, 475 KiB  
Article
How Environmental Turbulence Shapes the Path from Resilience to Sustainability: Useful Insights Gathered from Small and Medium Enterprises (SMEs)
by Ahmet Serdar İbrahimcioğlu and Hakan Kitapçı
Sustainability 2025, 17(15), 6938; https://doi.org/10.3390/su17156938 - 30 Jul 2025
Viewed by 182
Abstract
In the context of small and medium-sized enterprises (SMEs), organizational resilience has emerged as a critical capability for navigating dynamic and turbulent environments. The ability of firms to sustain their performance despite external disruptions, particularly those arising from market and technological change, is [...] Read more.
In the context of small and medium-sized enterprises (SMEs), organizational resilience has emerged as a critical capability for navigating dynamic and turbulent environments. The ability of firms to sustain their performance despite external disruptions, particularly those arising from market and technological change, is paramount for achieving long-term sustainability. This study offers a novel contribution by examining how two key dimensions of environmental turbulence—market turbulence and technological turbulence—moderate the relationship between organizational resilience capacity and sustainability performance. Our empirical findings, based on data from 423 SMEs, demonstrate that while organizational resilience positively correlates with sustainability performance, this relationship is significantly weakened under high levels of market and technological turbulence, indicating a negative moderating effect. These results advance resource-based and dynamic capabilities theory by highlighting the contingent nature of resilience in unstable contexts. Furthermore, this study provides practical guidance. SMEs should strategically invest in resilience-building efforts and continuously adapt their strategies in response to environmental fluctuations. Targeted approaches to managing different forms of turbulence and forming resilience-oriented collaborations can enhance sustainability outcomes. This research makes significant contributions to theory and practice; however, there are limitations that future research should take into account in order to appropriately utilize this study’s findings. Full article
(This article belongs to the Section Economic and Business Aspects of Sustainability)
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22 pages, 1248 KiB  
Review
Navigating the Global Regulatory Landscape for Exosome-Based Therapeutics: Challenges, Strategies, and Future Directions
by Nagendra Verma and Swati Arora
Pharmaceutics 2025, 17(8), 990; https://doi.org/10.3390/pharmaceutics17080990 - 30 Jul 2025
Viewed by 377
Abstract
Extracellular vesicle (EV)-based therapies have attracted considerable attention as a novel class of biologics with broad clinical potential. However, their clinical translation is impeded by the fragmented and rapidly evolving regulatory landscape, with significant disparities between the United States, European Union, and key [...] Read more.
Extracellular vesicle (EV)-based therapies have attracted considerable attention as a novel class of biologics with broad clinical potential. However, their clinical translation is impeded by the fragmented and rapidly evolving regulatory landscape, with significant disparities between the United States, European Union, and key Asian jurisdictions. In this review, we systematically analyze regional guidelines and strategic frameworks governing EV therapeutics, emphasizing critical hurdles in quality control, safety evaluation, and efficacy demonstration. We further explore the implications of EVs’ heterogeneity on product characterization and the emerging direct-to-consumer market for EVs and secretome preparations. Drawing on these insights, in this review, we aim to provide a roadmap for harmonizing regulatory requirements, advancing standardized analytical approaches, and fostering ongoing collaboration among regulatory authorities, industry stakeholders, and academic investigators. Such coordinated efforts are essential to safeguard patient welfare, ensure product consistency, and accelerate the responsible integration of EV-based interventions into clinical practice. Full article
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25 pages, 516 KiB  
Article
Exploring a Sustainable Pathway Towards Enhancing National Innovation Capacity from an Empirical Analysis
by Sylvia Novillo-Villegas, Ana Belén Tulcanaza-Prieto, Alexander X. Chantera and Christian Chimbo
Sustainability 2025, 17(15), 6922; https://doi.org/10.3390/su17156922 - 30 Jul 2025
Viewed by 207
Abstract
Innovation is a strategic driver of sustainable competitive advantage and long-term economic growth. This study proposes an empirical framework to support the sustained development of national innovation capacity by examining key enabling factors. Drawing on an extensive review of the literature, the research [...] Read more.
Innovation is a strategic driver of sustainable competitive advantage and long-term economic growth. This study proposes an empirical framework to support the sustained development of national innovation capacity by examining key enabling factors. Drawing on an extensive review of the literature, the research investigates the interrelationships among governmental support (GS), innovation agents (IA), university–industry R&D collaborations (UIRD), and innovation cluster development (ICD), and their influence on two critical innovation outcomes, knowledge creation (KC) and knowledge diffusion (KD). Using panel data from G7 countries spanning 2008 to 2018, sourced from international organizations such as the World Bank, the World Intellectual Property Organization, and the World Economic Forum, the study applies regression analysis to test the proposed conceptual model. Results highlight the foundational role of GS in providing a balanced framework to foster collaborative networks among IA and enhancing the effectiveness of UIRD. Furthermore, IA emerges as a pivotal actor in advancing innovation efforts, while the development of innovation clusters is shown to selectively enhance specific innovation outcomes. These findings offer theoretical and practical contributions for policymakers, researchers, and stakeholders aiming to design supportive ecosystems that strengthen sustainable national innovation capacity. Full article
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28 pages, 3144 KiB  
Review
Artificial Intelligence-Driven and Bio-Inspired Control Strategies for Industrial Robotics: A Systematic Review of Trends, Challenges, and Sustainable Innovations Toward Industry 5.0
by Claudio Urrea
Machines 2025, 13(8), 666; https://doi.org/10.3390/machines13080666 - 29 Jul 2025
Viewed by 612
Abstract
Industrial robots are undergoing a transformative shift as Artificial Intelligence (AI)-driven and bio-inspired control strategies unlock new levels of precision, adaptability, and multi-dimensional sustainability aligned with Industry 5.0 (energy efficiency, material circularity, and life-cycle emissions). This systematic review analyzes 160 peer-reviewed industrial robotics [...] Read more.
Industrial robots are undergoing a transformative shift as Artificial Intelligence (AI)-driven and bio-inspired control strategies unlock new levels of precision, adaptability, and multi-dimensional sustainability aligned with Industry 5.0 (energy efficiency, material circularity, and life-cycle emissions). This systematic review analyzes 160 peer-reviewed industrial robotics control studies (2023–2025), including an expanded bio-inspired/human-centric subset, to evaluate: (1) the dominant and emerging control methodologies; (2) the transformative role of digital twins and 5G-enabled connectivity; and (3) the persistent technical, ethical, and environmental challenges. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, the study employs a rigorous methodology, focusing on adaptive control, deep reinforcement learning (DRL), human–robot collaboration (HRC), and quantum-inspired algorithms. The key findings highlight up to 30% latency reductions in real-time optimization, up to 22% efficiency gains through digital twins, and up to 25% energy savings from bio-inspired designs (all percentage ranges are reported relative to the comparator baselines specified in the cited sources). However, critical barriers remain, including scalability limitations (with up to 40% higher computational demands) and cybersecurity vulnerabilities (with up to 20% exposure rates). The convergence of AI, bio-inspired systems, and quantum computing is poised to enable sustainable, autonomous, and human-centric robotics, yet requires standardized safety frameworks and hybrid architectures to fully support the transition from Industry 4.0 to Industry 5.0. This review offers a strategic roadmap for future research and industrial adoption, emphasizing human-centric design, ethical frameworks, and circular-economy principles to address global manufacturing challenges. Full article
(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)
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20 pages, 1978 KiB  
Review
Banking Profitability: Evolution and Research Trends
by Francisco Sousa and Luís Almeida
Int. J. Financial Stud. 2025, 13(3), 139; https://doi.org/10.3390/ijfs13030139 - 29 Jul 2025
Viewed by 304
Abstract
This study aims to map the scientific knowledge of bank profitability and its determinants. It identifies trends and gaps in existing research through a bibliometric analysis. To this end, 634 documents published in the Web of Science database over the last 54 years [...] Read more.
This study aims to map the scientific knowledge of bank profitability and its determinants. It identifies trends and gaps in existing research through a bibliometric analysis. To this end, 634 documents published in the Web of Science database over the last 54 years were analyzed using the bibliometric package. The results indicate an increase in the volume of publications following the 2008 financial crisis, focusing on analyzing the factors influencing bank profitability and economic growth. The Journal of Banking and Finance is the preeminent publication in this field. The literature reviewed shows that bank profitability depends on internal factors (size, credit risk, liquidity, efficiency, and management) and external factors (such as GDP, inflation, interest rates, and unemployment). In addition to the traditional determinants, the recent literature highlights the importance of innovation and technological factors such as digitalization, mobile banking, and electronic payments as relevant to bank profitability. ESG (environmental, social, and governance) and governance indicators, which are still emerging but have been extensively researched in companies, indicate a need for evidence in this area. This paper also provides relevant insights for the formulation of monetary policy and the strategic formulation of banks, helping managers and owners to improve bank performance. It also provides directions for future empirical studies and research collaborations in this field. Full article
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51 pages, 1874 KiB  
Review
Parkinson’s Disease: Bridging Gaps, Building Biomarkers, and Reimagining Clinical Translation
by Masaru Tanaka
Cells 2025, 14(15), 1161; https://doi.org/10.3390/cells14151161 - 28 Jul 2025
Viewed by 746
Abstract
Parkinson’s disease (PD), a progressive neurodegenerative disorder, imposes growing clinical and socioeconomic burdens worldwide. Despite landmark discoveries in dopamine biology and α-synuclein pathology, translating mechanistic insights into effective, personalized interventions remains elusive. Recent advances in molecular profiling, neuroimaging, and computational modeling have broadened [...] Read more.
Parkinson’s disease (PD), a progressive neurodegenerative disorder, imposes growing clinical and socioeconomic burdens worldwide. Despite landmark discoveries in dopamine biology and α-synuclein pathology, translating mechanistic insights into effective, personalized interventions remains elusive. Recent advances in molecular profiling, neuroimaging, and computational modeling have broadened the understanding of PD as a multifactorial systems disorder rather than a purely dopaminergic condition. However, critical gaps persist in diagnostic precision, biomarker standardization, and the translation of bench side findings into clinically meaningful therapies. This review critically examines the current landscape of PD research, identifying conceptual blind spots and methodological shortfalls across pathophysiology, clinical evaluation, trial design, and translational readiness. By synthesizing evidence from molecular neuroscience, data science, and global health, the review proposes strategic directions to recalibrate the research agenda toward precision neurology. Here I highlight the urgent need for interdisciplinary, globally inclusive, and biomarker-driven frameworks to overcome the fragmented progression of PD research. Grounded in the Accelerating Medicines Partnership-Parkinson’s Disease (AMP-PD) and the Parkinson’s Progression Markers Initiative (PPMI), this review maps shared biomarkers, open data, and patient-driven tools to faster personalized treatment. In doing so, it offers actionable insights for researchers, clinicians, and policymakers working at the intersection of biology, technology, and healthcare delivery. As the field pivots from symptomatic relief to disease modification, the road forward must be cohesive, collaborative, and rigorously translational, ensuring that laboratory discoveries systematically progress to clinical application. Full article
(This article belongs to the Special Issue Exclusive Review Papers in Parkinson's Research)
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20 pages, 1175 KiB  
Article
A Study on the Site Selection of Urban Logistics Centers Utilizing Public Infrastructure
by Jiarong Chen, Jungwook Lee and Hyangsook Lee
Sustainability 2025, 17(15), 6846; https://doi.org/10.3390/su17156846 - 28 Jul 2025
Viewed by 252
Abstract
The COVID-19 pandemic has highlighted critical vulnerabilities in urban logistics systems, particularly in last-mile delivery. To enhance logistics resilience and efficiency, the Korean government has initiated an innovative project that repurposes idle spaces in subway vehicle bases within the Seoul Metropolitan Area into [...] Read more.
The COVID-19 pandemic has highlighted critical vulnerabilities in urban logistics systems, particularly in last-mile delivery. To enhance logistics resilience and efficiency, the Korean government has initiated an innovative project that repurposes idle spaces in subway vehicle bases within the Seoul Metropolitan Area into logistics centers. This study proposes a comprehensive multi-criteria evaluation framework combining the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess the suitability of ten candidate sites. The evaluation criteria span four dimensions, facility, geographical, environmental, and social factors, derived from the literature and expert consultations. AHP results indicate that geographical factors, especially proximity to urban centers and major logistics facilities, hold the highest weight. Based on the integrated analysis using TOPSIS, the most suitable locations identified are Sinnae, Godeok, and Cheonwang. The findings suggest the strategic importance of aligning infrastructure development with spatial accessibility and stakeholder cooperation. Policy implications include the need for targeted investment, public–private collaboration, and sustainable logistics planning. Future research is encouraged to incorporate dynamic data and consider social equity and environmental impact for long-term urban logistics planning. Full article
(This article belongs to the Section Sustainable Transportation)
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