Search Results (1,466)

Since the start of the U.S. Conservation Reserve Program (CRP) in 1985, producers have enrolled environmentally sensitive land in exchange for annual rental payments, supporting multiple dimensions of sustainability through reduced soil loss, improved water quality, enhanced habitat provision, and strengthened climate resilience through land stewardship. Recent declines in enrollment raise concerns about whether participation remains spatially aligned with local environmental need and economic incentives. This study examines regional variation in CRP participation and its sustainability implications by identifying spatial patterns in participation and key drivers using exploratory spatial data analysis (ESDA). We analyze county-level CRP participation rates alongside three key drivers (CRP rental rates, soil erosion risk on cultivated cropland, and farm income) and assess spatial dependence using Global Moran’s I, univariate Local Indicators of Spatial Association (LISA), and bivariate LISA (BiLISA). Framed as an assessment of agri-environmental policy effectiveness for sustainable land management, the framework is applied to counties in the U.S. Midwest, a region with historically substantial CRP enrollment. Global Moran’s I statistics indicate significant positive spatial autocorrelation for CRP participation (I = 0.491), CRP rental rates (I = 0.892), and soil erosion (I = 0.503), confirming pronounced regional clustering across Midwestern counties. LISA results further show that more than 60% of counties fall into high–high (HH) or low–low (LL) clusters for CRP rental rates, while BiLISA results indicate that 22.9% of counties form HH clusters between CRP participation and soil erosion, suggesting only partial alignment between CRP participation and the environmental need. These findings indicate that the environmental benefits of CRP may vary across the region depending on where participation occurs. Overall, the findings support a shift toward a data-driven, spatially explicit CRP strategy that integrates environmental risk, economic incentives, and regional context to strengthen sustainability outcomes and enhance environmental effectiveness, economic efficiency, and the spatial equity of conservation benefits in the United States. Full article

Cultural and natural heritage are increasingly framed as components of territorial governance rather than isolated conservation elements; yet, a structural gap persists between their strategic recognition in planning documents and their measurable integration into statutory land-use systems that guide spatial decision-making. This gap is particularly pronounced in protected areas, where ecological integrity, cultural and symbolic values, tourism functions, and socio-economic expectations converge within environmentally sensitive landscapes. This study develops and empirically applies a compatibility-based analytical framework that embeds Multi-Criteria Decision Analysis (MCDA) within the statutory spatial planning system of Kozara National Park. The framework combines (i) institutional analysis of legally binding planning instruments, (ii) zoning-aligned analytical units derived from the Special-Purpose Spatial Plan and Management Plan, and (iii) a weighted multi-criteria model incorporating ecological integrity, cultural–historical significance, tourism and recreation capacity under controlled use, and socio-economic feasibility. Climate-related disturbance exposure is incorporated as a planning-relevant modifier of ecological compatibility. Composite compatibility scores under the baseline configuration range from 2.55 to 3.85 across analytical units. Rank correlation analysis suggests a high degree of structural consistency across both alternative weighting configurations relative to the baseline scenario (Spearman’s ρ ≈ 0.90), with only limited rank reordering observed, primarily between the two highest-ranked analytical units. Dispersed low-intensity recreational configurations demonstrate the highest structural robustness, whereas infrastructure-intensive zones exhibit management-dependent compatibility. The findings show how spatial planning in protected areas can operationalize compatibility as a measurable decision-support principle without substituting statutory zoning logic. Full article

Titanium dioxide (TiO₂) has evolved from a conventional photocatalyst into a sophisticated nano-platform that bridges environmental sustainability and biomedicine. This paper proposes a unified interfacial redox design framework that links the electronic-structure engineering of the TiO₂ with the spatial control of its reactive oxygen species (ROS). In the environmental sector, we highlight advances in photocatalytic detoxification, such as the cleavage of organophosphates via Ag-modified TiO₂, driven by doping and metal–support interactions. In the biomedical domain, TiO₂ is framed as an active bio-interface capable of coordinative protein binding. We specifically examine the “moonlighting” protein dihydrolipoamide dehydrogenase (DLDH) as a model for stable, oriented biofunctionalization. By integrating RGD-targeting motifs, these hybrid systems enable integrin-directed, localized photodynamic effects. We further address critical toxicological considerations, emphasizing that TiO₂ behavior is context-dependent and governed by particle size, crystallinity, and surface state. By synthesizing insights from catalysis and redox biology, this manuscript outlines principles for the rational design of safer, application-specific TiO₂ technologies. This convergence supports a transition from non-selective oxidation toward predictable, spatially confined redox outcomes in both complex environmental matrices and physiological systems. This review outlines key mechanistic insights and proposes design principles for controlled and context-dependent TiO₂ activity. Full article

The mandatory introduction of tethered caps on plastic beverage bottles under European Directive (EU) 2019/904 aims to reduce plastic litter and improve the collection efficiency of packaging waste. This regulatory change introduced a packaging design modification that directly affects consumer interaction. Consumer acceptance of this packaging innovation, however, remains uncertain. Drawing on research suggesting that product experience is shaped not only by physical interaction but also by expectations and value-based framing, this study examines whether the environmental intent of tethered caps is reflected in consumer perceptions over time. We analyze changes in consumer attitudes toward tethered caps before and after the legal obligation came into force, based on survey data collected in 2024 and 2025. Results indicate that overall consumer perceptions remained predominantly negative in both years, with a slight increase in negative responses following mandatory implementation. Although reported awareness of single-use plastic issues was higher in 2025, this did not correspond to improved evaluations of usability. Skepticism regarding the actual impact on waste reduction, along with ergonomic concerns and discomfort during drinking, were consistently identified as key barriers to acceptance. Socio-demographic analysis showed that age and employment status significantly influenced attitudes, whereas gender and place of residence did not. Contrary to expectations, younger respondents showed a shift toward more negative perceptions after implementation. Overall, the results suggest that the EU Single-Use Plastics Directive, although primarily aimed at achieving positive environmental outcomes, did not produce a comparable effect on consumer perception, as the environmental rationale did not significantly increase the acceptability of the tethered cap among users. This highlights the limits to value-based acceptance of sustainability-driven packaging measures and underscores the importance of integrating user-centered evaluation into regulatory design and communication strategies. These insights contribute to the broader discussion on the effectiveness of regulatory packaging interventions in the beverage sector. Full article

Electric vehicles (EVs) are promoted to decarbonise road transport, yet uptake remains slow in many emerging markets. This study examines consumer resistance to EV adoption in Sri Lanka by modelling status quo bias (SQB) using a Prospect Theory lens. An online survey of urban vehicle owners and near-term buyers yielded 157 responses; after screening and removing influential outliers, 151 cases were analysed using partial least squares structural equation modelling (PLS-SEM). The model tests five Prospect Theory-aligned antecedents, namely, loss aversion, reference dependence, risk perception, framing effects, and uncertainty aversion, and evaluates environmental concern as a moderator. Results indicate that loss aversion has a significant positive effect on SQB (β = 0.216, p = 0.005) and uncertainty aversion is the strongest predictor (β = 0.453, p < 0.001), while reference dependence, risk perception, and framing effects show positive but statistically non-significant direct effects. Moderation tests show that environmental concern significantly moderates the effects of reference dependence (β = 0.181, p = 0.039) and framing effects (β = 0.179, p = 0.037) on SQB, but does not significantly moderate the loss aversion, risk perception, or uncertainty aversion paths. Overall, perceived losses and—especially—ambiguity surrounding EV ownership appear to sustain reliance on internal combustion vehicles in this developing-country context, underscoring the need for interventions that reduce uncertainty (credible infrastructure signals, stable policy, service capability) and mitigate perceived losses (warranties, resale assurances) alongside carefully framed communications. Full article

Invasive plant species frequently dominate contaminated ecosystems and are increasingly reported as accumulators of heavy metals and potentially toxic elements (PTEs). While this phenomenon is widely documented, its functional implications for contaminant dynamics and remediation-oriented management remain insufficiently synthesized. This review provides a comprehensive assessment of heavy metal and PTE accumulation in invasive plants across terrestrial and aquatic environments, with emphasis on tissue-specific partitioning, environmental context, and species-level variability. Based on field surveys, controlled experiments, and biomonitoring studies, we synthesize evidence for the accumulation of key elements (As, Cd, Cr, Cu, Ni, Pb, and Zn) in the roots and above-ground tissues of terrestrial and aquatic invasive plants. The available literature reveals consistent patterns of root-dominated sequestration in many terrestrial invaders, contrasted with enhanced shoot accumulation in fast-growing aquatic species. These patterns underpin divergent functional roles, ranging from contaminant stabilization in soils and sediments to conditional phytoextraction under managed harvesting. Rather than promoting invasive plants as remediation tools, this review frames them as unavoidable functional components of contaminated landscapes. We critically evaluate their advantages, limitations, and ecological risks, identify key research gaps, and propose a context-aware framework for interpreting invasive plant–PTE interactions in environmental management. Full article

Developing electric motors with higher efficiencies for energy savings and environmental protection is crucial. The efficiency of grid-connected induction motors can be measured using various approaches; the preferred method is the indirect approach, which evaluates the separate losses from the additional losses due to residual losses. This approach follows the traditional approach to efficiency determination, introducing experimental procedures to assess additional losses by measuring the torque delivered by the motors. As noted in previous articles, the procedure is complex and requires numerous direct measurements. One area of interest is the determination of measurement uncertainty. This work aims to quantify the sensitivity of the combined uncertainties of losses and efficiency to variations in directly measured input variables: power frequency, rotational speed, torque, power, current, voltage, resistance, coolant temperature, and cold frame temperature. The results presented here help select measurement instrumentation, depending on whether the tests are aimed solely at determining efficiency or whether it is necessary to analyze the trend of the various types of loss, as occurs in optimization and experimental verification processes with high-performance materials, based on a comprehensive analysis of all standard and combined uncertainties, and with experimental data to assign a realistic value to the uncertainties themselves. Full article

The tractor road, as the core scene for autonomous driving of grain transport vehicles, is unstructured, complex, and obstacle-rich, leading to poor real-time performance and accuracy of joint road and obstacle detection with existing YOLOv5s. Furthermore, the reliability of passable area evaluation is low solely based on environmental factors. Therefore, YOLOv5s-C2S is proposed, fusing multi-scale features, attention mechanism, and dynamic features for joint detection. Firstly, YOLOv5s-CC is proposed for road detection by fusing context and spatial details and introducing Criss-Cross attention. Secondly, YOLOv5s-SGA is proposed for obstacle detection by grouped and spatial convolution, parameter-free attention, and adaptive feature fusion. By reusing YOLOv5s-CC weights, YOLOv5s-C2S shares low-level features and decouples high-level specificity. Based on the tractor road and obstacle information, combined with vehicle factors, a weighted scoring–based comprehensive method for passable area evaluation is proposed. Finally, the method was verified through experiments with an intelligent tracked grain transport vehicle using self-constructed datasets, including VOC_Road (11,927 images) and VOC_Obstacle (21,779 images). Compared with existing YOLOv5s, Deeplabv3+, FCN, Unet and SegNet, the mAP₅₀ of road detection by YOLOv5s-CC increased by over 1.2%. Compared with existing YOLOv5s, R-CNN, YOLOv7, SSD and YOLOv8n, the mAP₅₀ of obstacle detection by YOLOv5s-SGA increased by over 2%. Compared with YOLOv5s-SD, the mAP₅₀ of joint detection by YOLOv5s-C2S increased by 9.3%, and the frame rate increased by 7.0 FPS. The proposed passable area evaluation method exhibits strong robustness and reliability in complex environments, meeting the accuracy and real-time requirements in autonomous driving of grain transport vehicles. Full article

Artificial Intelligence (AI) has transitioned from a specialized research area to a ubiquitous socio-technical infrastructure influencing sectors from healthcare and law to manufacturing and defense. In tandem with its transformative promise, AI has created an exponentially expanding ethics literature questioning, fairness, transparency, accountability, and justice. This review synthesizes publications and key policy developments between 2019 and 2025, bringing sectoral discourses together with cross-cutting frameworks. Grounded in a systematic scoping review methodology, we frame the field along four meta-dimensions: trust and transparency, bias and fairness, governance & regulation, and justice, while we investigate their expression across diverse sectors. Special attention is dedicated to healthcare (patient trust and algorithmic bias), education (integrity and authorship), media (misinformation), law (accountability), and the industrial sector (data integrity, intellectual property protection, and environmental safety). We ground abstract principles in concrete case studies to illustrate real-world harms and mitigation strategies. Furthermore, we incorporate pluralistic ethics (e.g., Ubuntu, Islamic perspectives), environmental ethics, and emerging challenges posed by Generative AI and neuro-AI interfaces. To bridge theory and practice, we propose an operational governance framework for organizations. We contend that success involves transitioning from principles toward ethics-by-design, pluralistic governance, sustainability, and adaptive oversight. This review is intended for scholars, practitioners, and policymakers who need a comprehensive and actionable framework for navigating the complex landscape of AI ethics. Full article

Corporate Social Responsibility (CSR) has evolved into a strategic corporate function; however, most reviews continue to frame it primarily through competitiveness and core-business alignment, offering limited analytical differentiation regarding its integration with environmental governance and public health. This study provides a conceptual synthesis of CSR evolution between 2015 and 2024, emphasizing environmental–health integration and emerging hybrid models, particularly in Latin America. A Narrative Systematic Review following PRISMA guidelines was conducted across Scopus, Web of Science, and Google Scholar, resulting in the analysis of 96 publications. Findings are structured into three ideal-typical configurations: Instrumental Competitive CSR, Adaptive Hybrid CSR, and Transformative Health-Centric CSR. The study proposes a complementary environmental health prevention framework in which companies, stakeholders, and governance actors interact to address structural determinants of health. By conceptualizing CSR as a preventive co-governance mechanism rather than a solely competitive strategy, this study advances a more theoretically grounded understanding of corporate responsibility in sustainable and healthy communities. Full article

The retrofit of existing residential buildings plays a critical role in reducing energy consumption and carbon emissions in the building sector. However, previous retrofit evaluations often fail to account for the age-related thermal and lighting requirements of residents in aging residential buildings, thereby overlooking the substantial behavioral heterogeneity that shapes retrofit effectiveness. This study evaluates the comprehensive performance of different building envelope retrofit strategies, considering occupants’ thermal and visual comfort, from the perspectives of energy efficiency, economic feasibility, and environmental sustainability. First, age-specific differences in occupancy patterns, thermal preferences, and lighting requirements between elderly and non-elderly comparison group occupants were systematically extracted from the literature. Then, a typical high-rise residential building was modeled in EnergyPlus to serve as the reference building, within which the differentiated occupant behavior models were implemented, and the pre-retrofit condition was defined as the baseline scenario. Next, six commonly applied exterior wall insulation materials and different glass configurations and window frames were parameterized and evaluated under varying insulation thicknesses and remaining building service life scenarios. Finally, the energy-saving performance, economic benefits, and carbon reduction potential of envelope retrofit measures were quantitatively assessed across three primary functional zones (bedroom, living room, and study), using area-normalized indicators. The results indicate that, in the retrofit of existing residential buildings, bedrooms and study rooms exhibit greater retrofit benefits than living rooms, primarily due to longer occupancy durations and higher heating demand. In terms of retrofit strategies, exterior wall insulation consistently outperforms window retrofitting in energy-saving potential, with energy-saving rates of approximately 3.2–4.3% depending on functional zone, material type, and insulation thickness. Among the evaluated materials, vitrified microbead insulation performs best overall in terms of energy, economic, and carbon benefits at 40–60 mm thickness. These findings support occupant-informed, low-carbon retrofit decision-making for existing residential buildings. Full article

Declining birth rates are reshaping higher education across East Asia, accelerating the large-scale underutilization and, in some contexts, partial abandonment of university campus assets. Although adaptive reuse has been widely discussed, campus transformation is often framed primarily as a programmatic or policy problem, with limited attention to the inherited spatial logic embedded in campus morphology. This study revisits Le Corbusier’s concept of unlimited growth as a generative framework for campus transformation. Rather than treating it as a museum-specific historical typology, the research reinterprets unlimited growth as a scalable spatial logic defined by modular continuity, circulation hierarchy, and open-ended sequencing. To enhance reproducibility and operational clarity, the study formalizes a typo-morphological decoding protocol—modules, circulation, and growth sequence—and applies it through plan-, section-, and diagram-based analysis. Through comparative examination of three museum precedents—Sanskar Kendra Museum, the National Museum of Western Art (Tokyo), and the Chandigarh Museum and Art Gallery—the study extracts a set of transferable spatial mechanisms: modular increment, circulation-centered ordering, directional displacement, and fifth-façade ecological continuity. These mechanisms are then translated into an operational right-sizing model and tested through a design-operational demonstrator on a single anonymized Taiwanese campus experiencing demographic contraction. The findings indicate that unlimited growth functions not merely as a formal principle but as a spatial governance logic that supports phased consolidation, adaptive recomposition, and system-level coherence under long-term uncertainty. Importantly, this framework contributes to sustainability by reducing land consumption through spatial consolidation, minimizing unnecessary new construction, enabling adaptive reuse of existing campus assets, and improving long-term resource-use efficiency through phased right-sizing and ecological continuity. This study further advances a reproducible, mechanism-based methodological framework for institutional spatial transformation, providing a transferable approach for large-scale campus restructuring under conditions of long-term demographic and environmental uncertainty. Full article

The role of Corporate Social Responsibility (CSR) in advancing economic, social, and environmental well-being has been increasingly acknowledged in the broader context of the United Nations Sustainable Development Goals. For instance, CSR in Saudi Arabia is increasingly framed as a mechanism to support Vision 2030—a national strategy aimed at transforming Saudi Arabia to a sustainable economy. However, evidence on how financial institutions disclose and prioritize CSR at the country level remains fragmented. This study examines the extent and patterns of CSR disclosure across the Saudi banking sector by analyzing publicly available documents, e.g., annual reports and ESG/CSR reports (n = 36) from 10 banks (4 Islamic and 6 commercial). Findings indicate that CSR disclosures were primarily clustered into four macro themes—society, economic contribution, internal stakeholders, and environment—with a strong thematic emphasis on philanthropic activities, financial donations, disability support, and financing for Small and Medium Enterprises (SMEs). Environmental initiatives were disclosed less frequently and were generally narrower in scope, focusing on resource efficiency, recycling, and selective green financing. In addition, a comparative analysis between Commercial and Islamic banks revealed that the latter focused on values-based CSR, while commercial ones emphasized governance-oriented CSR. Full article

The 2025–2030 Dietary Guidelines introduce an important shift in public health nutrition, emphasizing minimally processed foods, higher protein intake, greater inclusion of full-fat dairy, and a food-based advice centered on “real food” consumption. While several of these recommendations align with accumulating evidence, particularly the discouragement of ultra-processed foods and added sugars, substantial concerns remain regarding their internal coherence, population-level applicability, risk of misinterpretation, as well as environmental footprint. This critical narrative review evaluates whether the scope, emphasis, and framing of the new guideline components are proportionate to the strength, consistency, and context of the underlying evidence. Using a novel framework that distinguishes between nutritional adequacy, optimization, and therapeutic application, we assess the scientific coherence of key recommendations. A structured literature search was conducted in PubMed, Scopus, and Web of Science focusing on systematic reviews and meta-analyses of randomized controlled trials and large prospective cohort studies relevant to the updated guidelines. Particular attention is given to protein and saturated fat intakes, carbohydrate restriction in chronic disease, and the balance between simplification and scientific precision. Overall, the new guidelines represent a positive shift toward food-based recommendations; however, clearer differentiation between population-level guidance and context-specific interventions is required to preserve scientific rigor, reduce misinterpretation, and enhance public health relevance. Full article

To address the calibration challenge caused by the nonlinear variation in intrinsic parameters during continuous camera zooming in UAV electro-optical pods, this paper proposes an online calibration method based on IMU-visual fusion. Traditional offline calibration cannot adapt to dynamic scenarios, while existing self-calibration methods suffer from slow convergence and insufficient robustness. The proposed method aims to achieve real-time and accurate estimation of camera intrinsic parameters during zooming. Specifically, we first construct a unified state estimation framework that encodes the internal and external parameters of the camera and the 3D positions of scene feature points into a high-dimensional state vector, then establish a camera motion model based on IMU data, construct a visual observation model by combining the pinhole camera and second-order radial distortion model to establish a nonlinear mapping from 3D feature points to 2D pixel coordinates, and adopt an improved ORB algorithm for feature extraction and LK optical flow method to achieve high-precision cross-frame feature matching to enhance the stability of visual observation. Most importantly, we design a tight-coupling fusion strategy based on the Extended Kalman Filter (EKF) prediction-update iteration mechanism, which fuses IMU high-frequency motion constraints and visual geometric constraints in real time to suppress parameter drift induced by focal length changes. Finally, we recursively solve the state vector to complete the online dynamic estimation of intrinsic parameters. Monte Carlo simulation experiments and real UAV flight experiments confirm that the method has both high estimation accuracy and strong environmental adaptability, can meet the high-precision calibration needs of UAVs in dynamic scenarios, and provides reliable technical support for accurate target positioning. Full article