Search Results (59,061)

Numerical magnitude can bias spatial attention, typically facilitating faster responses to the left for small numbers and to the right for large numbers—an effect traditionally attributed to egocentric spatial mappings. However, in everyday environments, individuals often share space with others, raising the question of whether such spatial–numerical associations can spontaneously reorganize based on another person’s visual perspective. To investigate this, we employed a digit-primed visual detection paradigm in which participants judged the location (left, right, up, or down) of a briefly presented peripheral probe following centrally displayed digits. If numerical magnitude implicitly guides attention, probe detection should be faster when its location is congruent with the digit-induced spatial bias. Critically, in the avatar condition, a task-irrelevant avatar was positioned on the participant’s left side, such that the avatar’s horizontal (left–right) axis corresponded to the participant’s vertical (up–down) axis—an axis along which egocentric numerical biases are typically absent. If participants spontaneously adopted the avatar’s perspective, numerical cues might induce attentional biases along this axis. Results revealed two simultaneous effects: a canonical egocentric SNARC-like effect (small–left, large–right) and a novel allocentric effect (small–up, large–down) emerged along the vertical axis, implicitly aligned with the avatar’s left–right spatial orientation. Numerical extremity enhanced the egocentric SNARC-like effect but had no effect in the allocentric case, pointing to a distinct mechanism rooted in embodied spatial perspective. These findings suggest that numerical magnitude can implicitly map onto both egocentric and allocentric spatial frames, reflecting a implicit and embodied mechanism of social understanding. Full article

High dynamic range (HDR) tone mapping techniques have been widely studied to effectively represent the broad dynamic range of real-world scenes. However, generating an HDR image from multiple low dynamic range (LDR) images captured at different exposure levels can introduce ghosting artifacts in dynamic scenes. Moreover, methods that estimate HDR information from a single LDR image often suffer from inherent accuracy limitations. To overcome these limitations, this study proposes a novel image processing technique that extends the dynamic range of a single LDR image. This technique achieves the goal through leveraging a Convolutional Neural Network (CNN) to generate a synthetic Near-Infrared (NIR) image—one that emulates the characteristic of real NIR imagery being less susceptible to diffraction, thus preserving sharper outlines and clearer details. This synthetic NIR image is then fused with the original LDR image, which contains color information, to create a tone-distributed HDR-like image. The synthetic NIR image is produced using a lightweight U-Net-based autoencoder, where the encoder extracts features from the LDR image, and the decoder synthesizes a synthetic NIR image that replicates the characteristics of a real NIR image. To enhance feature fusion, a cardinality structure inspired by Extended-Efficient Layer Aggregation Networks (E-ELAN) in You Only Look Once Version 7 (YOLOv7) and a modified convolutional block attention module (CBAM) incorporating a difference map are applied. The loss function integrates a discriminator to enforce adversarial loss, while VGG, structural similarity index, and mean squared error losses contribute to overall image fidelity. Additionally, non-reference image quality assessment losses based on BRISQUE and NIQE are incorporated to further refine image quality. Experimental results demonstrate that the proposed method outperforms conventional HDR techniques in both qualitative and quantitative evaluations. Full article

In this study, we describe the derivation and evaluation of Top of the Atmosphere (TOA) Shortwave Radiative (SWR) Fluxes from the Advanced Baseline Imager (ABI) sensor on the GOES-18 satellite. The TOA estimates use narrowband observations from ABI that are transformed to broadband (NTB), based on simulations and adjusted to total fluxes using Angular Distribution Models (ADMs). Subsequently, the GOES-18 estimates are evaluated against the Clouds and the Earth’s Radiant Energy System (CERES) data, the only observed SWR broadband flux dataset. The importance of agreement at the TOA is that most methodologies to derive surface SWR start with the satellite observation at the TOA. Moreover, information needed to compute radiative fluxes at both boundaries (TOA and surface) is needed for estimating the energy absorbed by the atmosphere. The methodology described was comprehensively evaluated, and possible sources of errors were identified. The results of the evaluation for the four seasonal months indicate that by using the best available auxiliary data, the accuracy achieved in estimating TOA SWR at the instantaneous scale ranges between 0.55 and 17.14 W m⁻² for the bias and 22.21 to 30.64 W m⁻² for the standard deviation of biases (differences are ABI minus CERES). It is believed that the high bias of 17.14 for July is related to the predominantly cloudless sky conditions, when the used ADMs do not perform as well as for cloudy conditions. Full article

Urban sustainability has become the most important urban development issue globally. Facing the problem of spatial structure optimization during urbanization, how to effectively use public data access to promote urban polycentric development has become a new area of concern for urban planners and policy makers. To quantify how government open-data platforms shape polycentric urban spatial structure across Chinese cities, this study takes the launch of government data platforms as a quasi-natural experiment, constructs the multi-period differences-in-differences model, uses data of 271 Chinese prefectural-level cities from 2010 to 2021, and examines the impact and mechanism of public data access on urban spatial structure. We find that public data access promotes urban polycentric development, especially in large cities, those in urban agglomerations, and resource-abundant cities. The effect follows an inverted ‘N’ trend, which reflects the evolving role of PDA across different urban development stages, highlighting the need for adaptive policies to optimize its benefits. Mechanisms include information process radicalization and industrial structure upgrading, moderated positively by government intervention and regional competition. These insights can inform policies for optimizing urban spatial patterns and advancing sustainable urban development. Full article

This study investigates how local governance actors in northern Taiwan navigate agricultural irrigation coordination under intensifying climate-induced water stress. Although conventional water governance models prioritize structural alignment and centralized integration, they frequently prove to be inadequate under conditions marked by institutional ambiguity and semantic volatility. Focusing on the transitional phase between early drought signaling and the formal implementation of water rationing, this research adopts Situational Grounded Theory (SGT) to examine how actors discursively interpret, negotiate, and adapt to evolving hydrological and institutional constraints. Based on unstructured interviews with irrigation officials, farmers, and public administrators, this study traces how expressions such as “under review” and “adjusting regionally” function as semantic instruments for deferral, alignment, and legitimacy building. These phrases are not merely rhetorical fillers; rather, they operate as situated mechanisms through which actors reposition their roles and recalibrate the meanings of governance. Through iterative coding, semantic clustering, and reflexive mapping grounded in SGT, this study develops the LAWFGS (Local Adaptive Water Governance under Flexible Governance Settings) framework. This tri-axial interpretive framework comprises three interrelated dimensions: (1) governance contexts, which captures the hydrological and institutional phase; (2) actor strategy roles, which reflect how actors adopt and shift their discursive positions; and (3) interpretive flexibility, which denotes the degree of semantic maneuvering exercised in response to governance tensions. The LAWFGS framework offers a situated analytical perspective for understanding how coordination is maintained through meaning-making practices under environmental pressure. The framework emphasizes the relational dynamics through which governance unfolds across shifting and often uncertain contexts. Full article

Value-directed remembering involves two key mechanisms: automatic processing and strategic processing. Automatic processing relies on the brain’s reward system and is associated with midbrain dopaminergic pathways and medial temporal-lobe activity. Strategic processing, in contrast, involves conscious, effortful encoding strategies and engages semantic-processing regions and executive control systems. This article reviews the developmental trajectory of value-directed remembering from childhood to old age through the lens of a dual-process model. Children and adolescents primarily rely on automatic processing; adults are capable of flexibly switching between the two processes; older adults tend to rely more on strategic processing. These findings reflect the dynamic developmental changes in the brain’s reward and executive-control systems. Future research should further investigate the synergistic interplay between dual-processing mechanisms, the moderating role of cultural contexts, and the efficacy of intervention strategies to deepen our understanding of the developmental trajectory of value-directed memory. Full article

The rural border areas of Serbia have been undergoing significant demographic shifts and transformations in land use. Between 2002 and 2022, these regions experienced a continuous population decline, an increase in the average age, and a growing share of single-person households. Simultaneously, there has been a reduction in agricultural land and a noticeable expansion of forested and grassland areas, particularly in hilly and mountainous terrain. This paper aims to explore the interrelationship between demographic indicators and land cover changes in these areas. Pearson’s correlation analysis was applied to data from the national population censuses and the CORINE Land Cover datasets for 1990 and 2018. The strongest positive correlation was found between the decline in the number of households and the reduction in agricultural land. Conversely, the expansion of forested areas showed a negative correlation with most demographic indicators. The findings reflect trends similar to those observed in other Eastern European countries but also reveal specific patterns of spatial marginalization unique to Serbia. In the study, the conclusion leads to the idea that depopulated border areas are in transition between past and future functions that will be influenced by their resource base. Full article

The accelerating pace of urbanization and population growth has increasingly disrupted the relationship between the built environment and nature, contributing to a decline in individuals’ psychological and spiritual well-being. Religious buildings—particularly mosques—have the potential to serve as restorative environments that support spiritual reflection and emotional balance. Within this context, the integration of biophilic design principles into sacred architecture has emerged as a significant area of contemporary research. This study investigates how biophilic elements in mosque interiors influence individuals’ perceptions of spirituality and the restorative quality of the space. Mosque interior images were generated using artificial intelligence tools (Midjourney V6.1 and DALL·E 3), informed by biophilic design theory. Grounded in Attention Restoration Theory (ART), the study utilized a quantitative research framework to explore how biophilic elements influence spiritual and restorative perceptions in sacred architectural spaces. Data were collected from 390 individuals in Türkiye with prior worship experience in Republican-era mosques—structures marked by ideological and spatial transformations. Two instruments were used, the Perceived Restorativeness Scale (PRS) and the newly developed Biophilic Spiritual Perception Scale (BSPS), which demonstrated high internal consistency (Cronbach’s α = 0.981). Analyses included exploratory and confirmatory factor analyses, as well as parametric and non-parametric statistical tests. Findings suggest that biophilic design in mosque interiors positively influences both spiritual experience and perceived environmental restorativeness. These results support the view that biophilic design should not be seen merely as an esthetic or ecological approach but as a multidimensional strategy that enhances the emotional and spiritual quality of sacred spaces. Implications for future mosque design in Türkiye are discussed. Full article

Higher education is increasingly focused on developing competencies beyond traditional academic content. Collaborative learning fosters academic achievement and promotes sustainable educational practices, helping students thrive in a dynamic and interconnected world. Professors now play a key role in creating environments where students actively engage in their own learning and development. This shift is especially evident when collaborative learning is used as a strategy for sustainability, encouraging lifelong learning and responsible citizenship. This study compared two teaching methodologies in a university business administration course. The results show that, in all cases, students in the collaborative group obtained higher averages. They also perceived greater teacher involvement in their learning process. These findings suggest that collaborative learning allows students to better assess the professor’s role and engagement. Collaborative learning is not merely a collection of techniques but a pedagogical philosophy that redefines the teacher’s role. As such, teacher training and institutional leadership must support long-term, reflective processes that foster student-centered attitudes and cultural change in universities. Faculty mindsets take time to evolve, and institutional culture plays a vital role in enabling or hindering change. Moreover, this study contributes to the literature by showing how collaborative learning, interpreted through the lens of transactional theory, enhances student perception of teacher involvement—highlighting the importance of mutual engagement and co-responsibility in business education settings. Full article

Accurate and spatially detailed soil information is essential for supporting sustainable land use planning, particularly in data-scarce regions such as Cyprus, where soil degradation risks are intensified by land fragmentation, water scarcity, and climate change pressure. This study aimed to generate national-scale predictive maps of key soil health descriptors by integrating satellite-based indicators with a recently released geo-referenced soil dataset. A machine learning model was applied to estimate a suite of soil properties, including organic carbon, pH, texture fractions, macronutrients, and electrical conductivity. The resulting maps reflect spatial patterns consistent with previous studies focused on Cyprus and provide high resolution insights into degradation processes, such as organic carbon loss, and salinization risk. These outputs provide added value for identifying priority zones for soil conservation and evidence-based land management planning. While predictive uncertainty is greater in areas lacking ground reference data, particularly in the northeastern part of the island, the modeling framework demonstrates strong potential for a national-scale soil health assessment. The outcomes are directly relevant to ongoing soil policy developments, including the forthcoming Soil Monitoring Law, and provide spatial prediction models and indicator maps that support the assessment and mitigation of soil degradation. Full article

This study provides a comprehensive assessment of the population structures, anatomical adaptations, and chloroplast genome organizations of three rare tree species—Fraxinus sogdiana Bunge, Celtis caucasica Willd., and Betula jarmolenkoana Golosk.—from the Northern Tien Shan region of Kazakhstan. Field surveys revealed species-specific demographic patterns, with F. sogdiana and B. jarmolenkoana populations displaying a complete age spectrum and signs of ongoing regeneration, while C. caucasica exhibited a lack of juvenile stages, indicating regeneration failure. Anatomical analysis of leaf and stem tissues highlighted adaptive features aligned with habitat conditions: F. sogdiana showed mesophytic traits suited for riparian environments, C. caucasica displayed xeromorphic structures reflecting drought tolerance, and B. jarmolenkoana demonstrated structural reinforcement adapted to high-altitude stressors. Whole chloroplast genome sequencing revealed conserved quadripartite architecture across species, with minor variations in gene content and inverted repeat boundaries suggesting lineage-specific evolution. The findings underscore the ecological sensitivity and conservation priority of these species and provide foundational data for future ecological monitoring, restoration efforts, and phylogenomic research in Central Asian montane ecosystems. Full article

Understanding human perceptual strategies in high-stakes environments, such as crime scene investigations, is essential for developing cognitive models that reflect expert decision-making. This study presents an immersive experimental framework that utilizes virtual reality (VR) and eye-tracking technologies to capture and analyze visual attention during simulated forensic tasks. A${360}^{\circ }$ panoramic crime scene, constructed using the Nikon KeyMission 360 camera, was integrated into a VR system with HTC Vive and Tobii Pro eye-tracking components. A total of 46 undergraduate students aged 19 to 24–23, from the National University of Singapore in Singapore and 23 from the Central Police University in Taiwan—participated in the study, generating over 2.6 million gaze samples (IRB No. 23-095-B). The collected eye-tracking data were analyzed using statistical summarization, temporal alignment techniques (Earth Mover’s Distance and Needleman-Wunsch algorithms), and machine learning models, including K-means clustering, random forest regression, and support vector machines (SVMs). Clustering achieved a classification accuracy of 78.26%, revealing distinct visual behavior patterns across participant groups. Proficiency prediction models reached optimal performance with a random forest regression ($R^2$ = 0.7034), highlighting scan-path variability and fixation regularity as key predictive features. These findings demonstrate that eye-tracking metrics—particularly sequence-alignment-based features—can effectively capture differences linked to both experiential training and cultural context. Beyond its immediate forensic relevance, the study contributes a structured methodology for encoding visual attention strategies into analyzable formats, offering valuable insights for cognitive modeling, training systems, and human-centered design in future perceptual intelligence applications. Furthermore, our work advances the development of autonomous vehicles by modeling how humans visually interpret complex and potentially hazardous environments. By examining expert and novice gaze patterns during simulated forensic investigations, we provide insights that can inform the design of autonomous systems required to make rapid, safety-critical decisions in similarly unstructured settings. The extraction of human-like visual attention strategies not only enhances scene understanding, anomaly detection, and risk assessment in autonomous driving scenarios, but also supports accelerated learning of response patterns for rare, dangerous, or otherwise exceptional conditions—enabling autonomous driving systems to better anticipate and manage unexpected real-world challenges. Full article

Aiming at the incentive effect of real-time electricity prices on load demand response in the context of the electricity market, this paper proposed a dual layer optimization operation method for regional energy storage considering dynamic electricity prices and battery capacity degradation. The innovation of the proposed method lies in introducing user satisfaction and establishing real-time electricity price models based on fuzzy theory and consumer satisfaction, making dynamic electricity prices more realistic. At the same time, the proposed dual layer optimization operation model for regional energy storage has modeled the capacity degradation performance of energy storage batteries, which more accurately reflects the practicality of energy storage batteries. Finally, the particle swarm optimization (PSO) algorithm is utilized to efficiently optimize charging/discharging strategies, balancing economic benefits with battery longevity. The correctness of the proposed method is verified through simulation examples using MATLAB. Simulation results demonstrate that real-time electricity prices based on consumer satisfaction increase load demand response resources, resulting in stronger absorption of new energy sources, improving by 73.7%, albeit with reduced economic efficiency by 11.27%. While the real-time electricity prices based on fuzzy theory exhibit weaker absorption of new energy sources improving by only 36.4%, but achieve the best overall economic performance. Full article

As vital outcomes of agricultural technological innovation, new animal breeds are not only foundational to rural revitalization but also central to preserving ecological diversity. At present, China lacks a clear and coherent legal framework of protection for new animal breeds, making it difficult to accommodate practical demands posed by modern breeding technologies such as gene editing. The results show that international models for protecting intellectual property in new animal breeds generally fall into three categories: granting patents for animal breeds, granting patents for breeding methods, and establishing sui generis rights for animal breeds. The sui generis protecting model of animal breed rights provides stronger protection and better reflects genetic specificity of such breeds. This research recommends that, on ethical review, stricter oversight of animal welfare and genetic data usage should be implemented to promote responsible innovation. On safety assessment, detailed standards should be developed for food and environmental risk assessment to ensure biodiversity and ecological sustainability. On risk balance evaluation, efforts should be made to ensure effective alignment among animal breed rights, animal welfare, and fair competition in the market, while also striking an appropriate balance of interests between breeders and other stakeholders such as farmers, who act as conservers and providers of germplasm resources. Full article

Both behavioral intentions and structural constraints shape household waste disposal in low-resource settings. This study integrates the Theory of Planned Behavior (TPB) with Environmental Justice (EJ) to examine informal waste disposal in Vhembe District, South Africa, a region marked by infrastructural deficits and uneven municipal services. A cross-sectional survey of 399 households across four municipalities assessed five disposal behaviors, including river dumping and domestic burial. Only 8% of households used formal bins, while over 50% engaged in open or roadside dumping. Although education and income were inversely associated with harmful practices, inadequate service access was the most significant constraint on formal disposal. Logistic regression revealed that rural residents and households in underserved municipalities were significantly more likely to engage in hazardous methods, regardless of socioeconomic status. These findings extend TPB by showing that perceived behavioral control reflects not only psychological agency but also material and institutional limitations. By reframing informal disposal as a structurally conditioned response rather than a behavioral deficit, the study advances EJ theory and provides a transferable TPB–EJ framework for decentralized, justice-oriented waste governance. The results underscore the need for Sustainable Development Goal (SDG)-aligned interventions that integrate equitable infrastructure with context-sensitive behavioral strategies. Full article