Local Strategies Research Articles

Abstract This article draws on and extends Bechtel’s influential work on the historical and philosophical implications of mechanistic research in cell biology. Beginning in the 1940s, cell biology relied on electron microscopy (EM) and cell fractionation, exemplifying the coupled epistemic strategies of structural decomposition and localization through experimental engagement with component parts and operations (Bechtel and Richardson [1993]2010; Bechtel 2006). In the 1970s, however, fluorescence microscopy (FM) enabled visualization of proteins and macromolecular assemblies in intact cells, which transformed mechanistic studies in cell biology. Through a historical analysis of cell adhesion and migration research, we show how the development and use of FM enabled what we call exposition of mechanisms. Instead of physically de composing cells into component parts, FM allowed researchers to visually ex pose these parts directly in their spatial-functional context in intact and even living cells . This epistemic strategy retained the mechanistic assumption that living systems can be meaningfully studied through localizable parts and operations. Yet, FM allowed for a more holistic approach to investigate structurally integrated components of minimally decomposable systems, such as focal contacts and the cytoskeleton, thus illustrating the importance of preserving the cellular context.

Abstract. Riverbank filtration (RBF), a managed aquifer recharge (MAR) technique utilised at the river–groundwater interface, can enhance groundwater quantity and quality, thus improving water supply security. However, it demands targeted local and regional monitoring strategies to understand how recharge efficiency and water quality benefits may vary with seasonal and short-term, event-based river flow fluctuations, upstream contaminant inputs, and site-specific aquifer heterogeneity. We evaluated river water–groundwater mixing and groundwater residence times to enhance the knowledge of aquifer recharge dynamics at the RBF site near Tarnów, Poland, serving as a critical drinking water source in this region. By coupling environmental tracers (stable water isotopes, chloride concentration, water temperature and specific electrical conductance) with high-resolution hydrological, meteorological and groundwater abstraction records, we show that RBF is the dominant recharge mechanism for the system that constitutes over 90 % of year-round yield from the production wells near the riverbank. Based on this example, we present a transferable and practical methodology for managing RBF systems efficiently: a multi-tracer, Ensemble End-Member Mixing Analysis (EEMMA) based workflow that covers at least one hydrological year, checks for local biases, and combines discrete water samples with continuous monitoring of physicochemical and hydrometeorological data, thus providing a robust and cost-effective template for recharge-source assessment. Such a framework determines both quantitative and qualitative status of abstracted groundwater and facilitates proactive responses to upstream pollution events and/or rapid hydrological shifts, which are crucial for sustainable water resource management internationally.

Abstract This editorial summarizes the 7th Malaysian Audiology Scientific Conference (MASCO) 2025, held in Penang, Malaysia, under the theme “Building Strong Foundations: The Evolution of Evidence-Based Practice in Audiology.” The conference gathered 111 audiologists and 26 students, featuring six plenary sessions by international and local experts on translational practice, auditory processing disorder, tinnitus management, and pediatric hearing loss. Participants presented 14 oral papers, 15 three-minute pitches, and 23 e-posters showcasing innovative diagnostic tools and clinical applications. MASCO 2025 emphasized bridging research and practice through interdisciplinary collaboration and localized strategies to advance audiology service delivery in Malaysia.

Health inequalities in India are significant challenges to achieving Sustainable Development Goal 3, which aspires to achieve healthy lives and well-being for everyone at all ages. Marginalised communities living in remote and tribal areas are disproportionately affected by systemic barriers and socio-economic disparities. This article draws on first-hand reflections and experiences from PhD fieldwork conducted in last-mile areas, exploring the strategic and operational challenges of conducting research in tribal geographies. The study highlights key themes, challenges and mitigation strategies by employing community-based participatory research (CBPR) framework. It emphasises the role of local partnerships and adaptive strategies in crossing these challenges to ensure meaningful conversation with tribal populations. The article also examines the implications of health inequalities through the lens of management education and practice. It calls for businesses, NGOs and policymakers to adopt an integrated approach combining field-level insights with scalable interventions to bridge health disparities. Furthermore, it calls for a paradigm shift in management education pedagogy, emphasising ethical awareness, cultural sensitivity and community engagement to prepare future leaders for addressing health inequities. This study contributes to the discourse on bridging health inequalities in underserved regions by integrating insights from field research, management education and collaborative frameworks.

This research proposes a method based on the greatest and shortest eigen fuzzy sets of fuzzy relations to evaluate the effectiveness of policies and strategies implemented in urban settlements aimed at increasing the livability and well-being of citizens. This assessment is performed by extracting population census data collected at the beginning and end of the analyzed period and grouping them by subzone, that is, for each of the urban areas into which the urban settlement is divided. The greatest eigen fuzzy set (GEFS) and the smallest eigen fuzzy set (SEFS) are determined symmetrically as min-max and max-min solutions of fuzzy relations; they are calculated to estimate the average impact of urban strategies on generating symptoms of growth in citizen well-being during the investigated period. The method is implemented on a GIS (Geographic Information System) platform and was tested to assess the effectiveness of local policies applied between 2011 and 2021 on the growth of employment rates and educational attainment in the city of Naples (Italy), partitioned by neighborhood. Our model, unlike other fuzzy-based models for evaluating the effectiveness of actions and strategies to improve the quality of life in urban settlements, does not allow for subjective interpretations based on the knowledge or experience of different stakeholders, but relies solely on measurements over time of characteristics collected during census activities. Furthermore, it is integrated into a GIS-based platform, providing additional capabilities for identifying the urban areas where the impact of local strategies and policies has been most significant and those most critical. The test results show that the proposed framework can be a valuable tool for supporting decision makers in evaluating the effectiveness of local actions and policies aimed at improving the livability and well-being of citizens.

An alternative approach to estimate mismanaged plastic waste at the sub-national scale.

Despite the rapid progress of robotic surgery, intelligent object recognition and autonomous computer-assisted interventions continues to face limitations. Algorithms designed for the identification and localization of surgical tool tips are pivotal in augmenting the interactive collaboration between the robotic surgical system and its operator. In the present study, our aim to formulate a strategy proficient in recognizing and pinpointing commonly used surgical tools in robotic surgery. A strategy for object detection was conceptualized and validated across two datasets. The first dataset provided by the Medical Image Computing and Computer Assisted Intervention Society (MICCAI) consisted of 24,695 video clips. The second dataset comprised surgical videos from 35 clinical cases in our clinical center, encompassing a total of 392 video clips with 53,128 images. Our approach employs CSPNeXt as the backbone network, incorporates OSTrack for pseudo-labeling and Kalman filtering for data fusion. Our model is openly accessible on GitHub. In the MICCAI test set, our strategy achieved a mean Average Precision of 0.4669. In the second video test set, the recall rate (RR) and precision rate (PR) for seven types of tools ranged from 79.36% to 99.75% and from 57.65% to 97.35%, respectively. RR and PR of bipolar forceps, needle driver and cautery hook all exceeded 94%. An effective strategy for the recognition of surgical tools and tips was successfully developed and validated. This strategy shows promise in actively supporting surgical procedures and has the potential to alleviate the workload on human operators during future algorithm training.

A novel strategy for sparse attack detection and localization in secure state estimation of power systems

Nanocellulose-assisted construction of conductive gradient hydrogel for remote actuated and self-sensing soft actuator.

Duchenne and Becker Muscular Dystrophies in Romania: a 10-year Retrospective Study.

Gradient aware adaptive quantization: Locally uniform quantization with learnable clipping thresholds for globally non-uniform weights.

KGFedRS: Knowledge Graph enhanced Federated Recommender System.

Binocular vision is a core module in humanoid robots, and stereo matching is one of the key challenges in binocular vision, relying on template matching techniques and mathematical optimization methods to achieve precise image matching. However, occlusion significantly affects matching accuracy and robustness in practical applications. To address this issue, we propose a novel hybrid matching strategy. This method does not require network training and has high computational efficiency, effectively addressing occlusion issues. First, we propose the Inverse Template Matching Mathematical Method (ITM), which is based on optimization theory. This method generates multiple new templates from the image to be matched using mathematical segmentation techniques and then matches them with the original template through an inverse optimization process, thereby effectively improving matching accuracy under mild occlusion conditions. Second, we propose the Iterative Matching Mathematical Method (IMM), which repeatedly executes ITM combined with optimization strategies to continuously refine the size of matching templates, thereby further improving matching accuracy under complex occlusion conditions. Concurrently, we adopt a local region selection strategy to selectively target areas related to occlusion regions for inverse optimization matching, significantly enhancing matching efficiency. Experimental results show that under severe occlusion conditions, the proposed method achieves a 93% improvement in accuracy compared to traditional template matching methods and a 37% improvement compared to methods based on convolutional neural networks (CNNs), reaching the current state of the art in the field. Our method introduces a reverse optimization paradigm into the field of template matching and provides an innovative mathematical solution to address occlusion issues.

This study examines the comparative impact of digital marketing on consumer buying behavior in urban and rural areas of Neemuch district. With the rapid growth of internet penetration, mobile usage, and social media adoption, digital marketing has become a critical tool for influencing purchasing patterns. However, lifestyle, infrastructure, and socio-economic status disparities create differing adoption patterns across urban and rural markets. Adopting a descriptive research design, the study employed a quantitative approach using structured questionnaires to collect primary data from 300 respondents (194 urban and 106 rural). A chi-square test of independence was conducted to examine variations in product category preferences and online shopping frequency. Results revealed a statistically significant difference in product category choices between urban and rural consumers (χ² = 13.25, p = .039), suggesting that consumer preferences are influenced by lifestyle, income, and access to digital platforms. However, no significant difference was found in the frequency and pattern of online shopping between the two groups (χ² = 4.896, p = .298), indicating that digital platforms are bridging the gap in shopping behavior across residential contexts. The findings highlight that while urban consumers show greater exposure and preference for branded and convenience-oriented products, rural consumers remain price-sensitive, trust-driven, and community-influenced.This research underscores the need for localized marketing strategies that consider socio-economic conditions, infrastructure gaps, and cultural orientations. The study concludes that digital marketing has transformative potential in bridging the urban-rural divide, provided businesses adopt inclusive, vernacular, and trust-building approaches.

The Business Clinic Program by the Department of Cooperatives, Industry, and Trade (Diskopindag) of Malang City is a strategic initiative aimed at strengthening Micro, Small, and Medium Enterprises (MSMEs) through need-based training, intensive mentoring, financing facilitation, legal assistance, and product promotion. The program not only focuses on improving technical capabilities but also encourages entrepreneurial mindset shifts to adapt with market dynamics and digital technology. One of its main strengths is the tutor system, where each tutor assists five MSMEs intensively for a year. Furthermore, cross-sector collaboration and a data-driven evaluation approach make the program measurable and impactful. As a result, many MSMEs experience increased sales, improved production efficiency, and are able to access modern markets and export opportunities. Despite facing challenges such as limited access to finance and digitalization gaps, this program serves as a comprehensive and inclusive empowerment model that can be replicated by other regions as part of sustainable local economic development strategies.

Motivated by the shift toward sustainable mobility and increased demand for ethically sourced raw materials, this study examines the social sustainability of different sourcing strategies for aluminium and cobalt in electric vehicle (EV) products. These materials are essential components for batteries and lightweight parts in EVs. A Social Life Cycle Assessment (S-LCA) was conducted in conjunction with OpenLCA and the Product Social Impact Life Cycle Assessment (PSILCA) database. The assessment is based on the United Nations Environment Programme (UNEP) Guidelines from 2020 with a focus on key stakeholder categories. In this study, four cradle-to-gate sourcing strategies are evaluated and labelled as Case 1 through Case 4 in the assessment. The results show significant differences across the scenarios. The local sourcing strategy for aluminium in Australia (Case 1) is associated with lower social risks, whereas the local sourcing of cobalt in Russia (Case 2) indicates higher social risks. Global sourcing strategies involving Guinea and Brazil for aluminium (Case 3) and the Democratic Republic of the Congo (DRC) and China for cobalt (Case 4) demonstrate increased social risks. The impacts can be up to 15 times greater, depending on the location. These findings highlight regional variations in social risks associated with the sourcing of raw materials. The results highlight the importance of implementing corporate due diligence and socially responsible procurement practices within raw material supply chains through integrating an S-LCA into sourcing strategies. This approach also supports some of the Sustainable Development Goals. Overall, this study provides practical insights for industry and policymakers, thereby enriching our understanding of social sustainability.

ABSTRACT The successful implementation of industrial strategies relies on high-quality evidence of interventions that work. Yet, there is a lack of such evidence, particularly for local and regional economic policy. While policymakers at all levels of government express a strong desire for better evidence, limited research has addressed the question of why more resources are not devoted to producing better evidence. This article identifies barriers to more and better evaluation of industrial and economic policy more generally. This is a pertinent question in the UK context as a new industrial strategy is launched, while local government is undergoing a reorganisation with new powers for economic policy being devolved. The article makes two contributions. First, it argues that evaluation and evidence should be treated as a public good that will be underprovided without deliberate investment. Second, the lack of a strong ecosystem for evaluation at the local level is identified, which could act as a flexible resource to improve evaluation capacity and capability and support the use of existing evidence. Implications for the design of incentives and institutions for evaluation are considered.

Abstract: This study examines the evolution of Korean migration to Eastern Europe, with particular attention paid to Hungary, Slovakia, and Bulgaria. A comparative analysis of these three countries demonstrates that economic engagement constitutes the primary determinant of migration flows. The findings indicate that migration trajectories are closely associated with patterns of South Korean foreign direct investment in the region. Korean immigration has developed through distinct phases: beginning with isolated diplomatic and entrepreneurial initiatives during the post-Communist transition, advancing to corporate-driven movements connected to large-scale industrial investments, and more recently diversifying to include students, professionals, and families. Based on these findings, the study advances recommendations designed to strengthen the nexus between investment and immigration, to facilitate the sustainable settlement of Korean migrants, and to promote long-term cultural, social, and economic partnerships in Eastern Europe. The proposed measures include expanding intergovernmental cooperation through bilateral agreements, aligning immigration and investment policies, and enhancing the role of corporations in fostering cultural adaptation, social integration, and sustainable localization strategies. Keywords: immigration, European countries, Korea, Bulgaria, Hungary, Slovakia, comparative analysis.

Urban heat islands (UHIs) intensify thermal stress in cities, particularly in arid and semi-arid regions undergoing rapid urban expansion. The main objectives of this study are to quantify and compare UHI intensity in six major Saudi Arabian cities (Dammam, Makkah, Madinah, Jeddah, Riyadh, and Abha) representing diverse climatic zones and to examine how UHI patterns vary between urban, suburban, and rural zones over a 30-year period. Understanding the magnitude and spatial variability of UHIs across different climatic settings is crucial for developing effective urban planning and climate adaptation strategies in Saudi Arabia’s rapidly expanding cities. Except for Abha, these cities are the five most populous cities in the Kingdom. Each city was categorized into urban (>1500 people km−2), suburban (300–1500 people km−2), and rural (<300 people km−2) zones using high-resolution population density data. Two independent temperature datasets (ERA5-land and CHIRTS-ERA5) were analyzed for the years 1994, 2004, 2014, and 2024. Both datasets revealed consistent spatial patterns and a general warming trend across all zones and cities over the 30-year period. The UHI effect was most pronounced for minimum temperatures, with urban zones warmer than rural zones by 0.85 °C (ERA5-land) and 1.10 °C (CHIRTS-ERA5), likely due to greater heat retention and slower cooling rates in built-up areas. Mean temperature differences were smaller but still indicated positive UHI. Conversely, both datasets exhibited a reversed UHI pattern for maximum temperatures, with rural zones warmer than urban zones by 1.73 °C (ERA5-land) and 1.52 °C (CHIRTS-ERA5). This reversed pattern is attributed to the surrounding desert landscapes with minimal vegetation, indicated by low normalized difference vegetation index (NDVI), while urban areas have increasingly benefited from greening and landscaping initiatives. City-level analysis showed the strongest reversed UHI in maximum temperatures in Abha, while Jeddah exhibited the weakest. These findings highlight the need for localized urban planning strategies, particularly the expansion of vegetation cover and sustainable land use, to mitigate extreme thermal conditions in Saudi Arabia.

The hysteresis model can be used to accurately predict the magnetic hysteresis characteristics of ferromagnetic materials. Incorporating the hysteresis model into finite element calculations enables precise prediction of field distributions, voltage or current variations in circuits, and losses, which is essential for electromagnetic transient analysis involving remanent magnetization. When incorporating the hysteresis model into finite element analysis, prohibitively small time-steps are required to resolve hysteresis loops, leading to excessive simulation times compared to simplified BH curve approaches. Furthermore, numerical instabilities arise near zero-crossing points of magnetic flux density, where erroneous negative differential reluctivity values may lead to the divergence of the nonlinear solving process. A finer time resolution needs to be utilized to ensure the convergence of the nonlinear solver. This leads to more time-steps and longer computational time. This work proposes a localized stabilization strategy for regulating the differential reluctivity in instability-prone regions of the hysteresis loop, which can stabilize the nonlinear iteration while avoiding the local refinement of time resolution and thus reduce the overall computation time.