Search Results (567)

Reconciling hydropower development with aquatic biodiversity conservation is a central challenge for sustainable river management worldwide. Cascade dam configurations, in which multiple impoundments are arranged in series along a single channel, impose longitudinal environmental gradients that restructure biological communities across trophic levels. Whether the resulting multi-trophic responses are independently driven by shared abiotic gradients (environmental filtering) or mechanistically coupled through direct food-web interactions (trophic cascading) remains unresolved. We surveyed phytoplankton, zooplankton, and benthic macroinvertebrates simultaneously at seven stations along a 430 km gradient downstream of Danjiangkou Dam in the Hanjiang River, the largest tributary of the Yangtze River and the source of China’s South-to-North Water Diversion Middle Route, over eight seasonal campaigns (2015–2017). Variance partitioning, piecewise structural equation modeling, Mantel tests, and co-occurrence network analysis were applied to partition environmental and trophic pathways. Environmental filtering dominated community restructuring at all three trophic levels, while the biotic proxy for direct trophic interactions explained less than 0.4% of community variation, consistent with weak detectable trophic coupling at seasonal resolution. Distance from Danjiangkou Dam shaped downstream transparency and turbidity gradients that mediated trophic-level-specific responses along distinct environmental axes (pH and water temperature for phytoplankton, conductivity for zooplankton, and transparency for benthic macroinvertebrates). Benthic macroinvertebrates were systematically decoupled from the pelagic analytical framework, absent from the cross-trophic co-occurrence network and structured more by spatial configuration than by water-column variables. Hub species in the network were associated with downstream mineralized conditions, confirming that network architecture reflects shared environmental preferences rather than biotic interactions. These findings support a management shift from single-dam mitigation toward cascade-scale coordination of environmental flow regimes, sediment connectivity, and substrate restoration as integrated strategies for sustaining multi-trophic biodiversity in regulated rivers. Full article

Against the background of highly interconnected global capital markets and rapidly propagating cross-lingual information streams, traditional anomaly detection paradigms based solely on single-modality numerical time-series sensors are insufficient for forward-looking risk sensing. From the perspective of artificial intelligence-driven sensing, this study proposes a multilingual semantic–numerical collaborative Transformer framework to construct a unified multimodal financial sensing architecture for intelligent anomaly sensing and risk perception. Within the proposed sensing paradigm, multilingual texts are conceptualized as semantic sensors that continuously emit event-driven sensing signals, while market prices, trading volumes, and order book dynamics are modeled as heterogeneous numerical sensor streams reflecting behavioral market sensing responses. These heterogeneous sensors are jointly integrated through a cross-modal sensor fusion architecture. A cross-modal temporal alignment attention mechanism is designed to explicitly model dynamic lag structures between semantic sensing signals and numerical sensor responses, enabling temporally adaptive sensor-level alignment and fusion. To enhance sensing robustness, a multilingual semantic noise-robust encoding module is introduced to suppress unreliable textual sensor noise and stabilize cross-lingual semantic sensing representations. Furthermore, a semantic–numerical collaborative risk fusion module is constructed within a shared latent sensing space to achieve adaptive sensor contribution weighting and cross-sensor feature coupling, thereby improving anomaly sensing accuracy and robustness under complex multimodal sensing environments. Extensive experiments conducted on real-world multi-market financial sensing datasets demonstrate that the proposed artificial intelligence-driven sensing framework significantly outperforms representative statistical and deep learning baselines. The framework achieves a Precision of $0.852$, Recall of $0.781$, F1-score of $0.815$, and an AUC of $0.892$, while substantially improving early warning time in practical risk sensing scenarios. In cross-market transfer settings, the proposed sensing architecture maintains stable anomaly sensing performance under bidirectional domain shifts, with AUC consistently exceeding $0.86$, indicating strong structural generalization across heterogeneous sensing environments. Ablation analysis further verifies that temporal sensor alignment, semantic sensor denoising, and collaborative cross-sensor risk coupling contribute independently and synergistically to the overall sensing performance. Overall, this study establishes a scalable multimodal intelligent sensing framework for dynamic financial anomaly sensing, providing an effective artificial intelligence-driven sensing solution for cross-market risk surveillance and adaptive financial signal sensing. Full article

This study examines the impact of environmental assessment on corporate financialization in China. Using panel data of A-share listed firms from 2008 to 2023, we exploit the staggered implementation of the Natural Resource Asset Audit for Leading Cadres as a quasi-natural experiment and employ a difference-in-differences (DID) model to identify the causal effects. The empirical results show that environmental assessment significantly promotes corporate financialization, and the findings remain robust after a series of robustness and endogeneity tests. Further analysis reveals that the policy reduces firms’ financing constraints, thereby encouraging a shift in resources from real investment to financial assets. Moreover, regional financial development and corporate digital transformation positively moderate this relationship, while the effect is more pronounced in eastern regions and among smaller firms. Full article

Spatial qualities are central to architectural reasoning; yet, in studio-based education, they often remain implicit rather than structured as a shared analytical framework. This study examines how a multi-scalar taxonomy of spatial qualities can function as a collaborative analytical language in studio-based architectural education. Situated in Košanćićev venac and Dorćol, two historically layered areas of Belgrade’s old town, this study integrates expert spatial analysis with a student questionnaire administered across bachelor and master study levels. Empirical testing was conducted to evaluate structural coherence, conceptual differentiation and the distribution of spatial qualities across detail, architectural and urban drawing scales. The findings indicate consistent internal stability, clear differentiation among constructs and statistically significant cross-scale articulation. Form- and composition-related qualities showed high usability, while interpretative constructs were more variable. Master-level students demonstrated greater engagement with cognitive and interpretative constructs, indicating a shift toward more conceptually grounded design reasoning without affecting overall structural coherence. These results suggest that spatial qualities can operate as a level-independent analytical language, supporting inclusive participation, shared interpretation and structured dialogue within the design studio. By positioning spatial qualities as a collaborative pedagogical framework, this study contributes to interdisciplinary communication and more equitable engagement in architectural education. Full article

Horizontal Gene Transfer (HGT) is a hallmark of the evolution of parasitic plants, facilitated by the haustorial connection. While mitochondrial HGT is widespread, the extent of nuclear HGT and the long-term retention of foreign genetic material in holoparasitic lineages remain poorly understood. This study explores the genomic architecture of Prosopanche americana (Hydnoraceae), a non-photosynthetic holoparasite currently specialized on Fabaceae. Through a comparative phylogenomic approach integrating draft mitochondrial genomes (mtDNA) and nuclear transcriptomes of P. americana, we identified a multi-layered landscape of foreign DNA. The mtDNA of P. americana contains 18 foreign regions (>500 bp) primarily derived from Solanales, Malvales, and Fabales. Notably, 13 of these regions are shared with P. panguanensis, indicating they were acquired in their common ancestor before speciation and ecological shift. In the nuclear genome, we identified 303 horizontally acquired transcripts (99 orthogroups) with high confidence. Functional analysis revealed an enrichment of foreign genes involved in metabolic pathways and plastid functions (e.g., photosystems and thylakoids) exclusively derived from the ancestral host order Solanales. Our results demonstrate that the genome of P. americana acts as a “molecular fossil,” preserving evidence of past ecological interactions with diverse host lineages. The disparity in HGT footprints between the current host (Fabaceae) and ancestral hosts suggests a period of high genomic plasticity followed by host specialization, providing new insights into the timing and dynamics of horizontal gene flow in holoparasitic Piperales. Full article

Background/Objectives: Parkinson’s disease (PD) is a progressive neurodegenerative disorder that affects both motor and non-motor functioning, leading to increasing dependency and long-term psychosocial consequences. As the disease progresses, partners often assume caregiving roles, resulting in shifts in responsibilities, communication patterns, and emotional dynamics within marital relationships. The aim of this study was therefore to explore the impact of Parkinson’s disease on marital relationships. Methods: A qualitative interview study with a retrospective design was conducted. Six couples were recruited through a movement disorders clinic and a lay organization in Sweden. Semi-structured, face-to-face interviews were conducted separately with each partner. Interviews were transcribed verbatim and analyzed using conventional content analysis with an inductive design. Results: Four main themes emerged: managing the disease together in partnership, nurturing the relationship, facing marital hardship, and planning an uncertain future. Couples who adopted a positive and pragmatic outlook, shared responsibilities, and maintained open communication seemed to be better able to manage the disease. Engaging in joint activities and reciprocal communication strengthened emotional closeness. In contrast, changes in roles, emotional distress, loss of intimacy, and communication avoidance challenged relationships. Thinking about the future evoked feelings of ambivalence, as couples balanced uncertainty with a need for security. Conclusions: Parkinson’s disease affects marital relationships, reshaping roles, emotional bonds, and future perspectives. The ability of nurses to address both partners’ needs and promote communication and shared coping strategies is essential to strengthening couples’ well-being. Full article

Corporate sustainability programs in agri-food systems have expanded dramatically, yet emissions, deforestation, hunger, and land concentration intensify. Why does corporate sustainability systematically fail to deliver transformation? This paper applies Commonist Value Theory (CVT) to show that this failure is structural, not contingent. CVT distinguishes between True Value, the life-supporting qualities that sustain human and more-than-human flourishing, and Fetish Value, abstracted forms oriented toward capital accumulation. CVT traces how corporate sustainability programs convert the former into the latter through ‘decommonization’: the perversion and enclosure of shared life-supporting relations. Drawing on investor analyses, carbon market assessments, and critical scholarship, this paper demonstrates that corporate sustainability programs function as civilizing meta-mechanisms. Rather than transforming food systems, they stabilize existing arrangements by absorbing critique and redirecting transformative energies into regime-compatible forms. Farmers’ knowledge is captured as proprietary data, living ecosystems are reduced to tradeable metrics, collaborative relationships are fragmented by corporate platforms, and movements for genuine alternatives are channeled into supply chain optimization. The analysis concludes that corporate sustainability cannot deliver genuine transformation because its structural function is to stabilize rather than supersede the current value regime. Genuine transformation requires commons-based alternatives from below and political–legislative shifts from above that structurally constrain decommonization. Full article

Rural property rights reform is considered paramount for mobilizing land resources and promoting rural entrepreneurship. However, the outcomes of tenure clarification depend on the role of the land in household livelihoods. The study focuses on China’s homestead rights confirmation and examines its effects on farmer entrepreneurship. The analysis is based on data from 2337 households in Jiangsu Province from the 2020 China Land Economic Survey. The application of Probit and endogenous switching Probit models yielded the following finding: confirming homestead rights reduces the probability of farmer entrepreneurship by approximately 11.4 percentage points. This decline can be attributed to several factors, including a decrease in homestead utilization, a shift towards lower-investment-risk preferences, an increase in entrepreneurial risk perception, and a contraction in entrepreneurial social networks. Collectively, these factors contribute to a reshaping of households’ risk evaluation and asset allocation. The negative impact is primarily observed among households with higher dependency ratios, poorer housing conditions, older heads of household, and those residing in less developed areas. The findings indicate that the consequences of property rights confirmation are characterized by institutional and functional specificity, thereby underscoring the necessity for measures that promote land transfer, exit, and risk-sharing to harmonize tenure reform with entrepreneurship. Full article

Background/Objectives: Social rejection during the latency stage is a significant risk factor for children’s emotional and social development. Whereas earlier research focused primarily on individual characteristics of rejected children, contemporary perspectives emphasize peer-group processes, including norm formation, hierarchies, and social status structures. Although autonomy has been widely examined as an individual developmental construct, less attention has been given to its possible collective expression within the classroom peer group. This study aimed to explore how children understand and experience group autonomy and to clarify its role in social status and peer rejection. Methods: Twelve classroom-based focus groups were conducted with 140 fifth-grade children from five public elementary schools in Israel. Discussions were initiated using a projective narrative describing ambiguous peer exclusion. Data were audio-recorded, transcribed verbatim, and analyzed using thematic analysis. Coding was conducted independently by two researchers and refined through iterative comparison and reflexive procedures. Results: Three themes emerged: (1) a shared longing for classroom-based group autonomy and collective decision-making; (2) group autonomy as an implicit hierarchical criterion shaping social status, whereby reduced reliance on adults and alignment with peer norms were associated with higher status, while adult dependence was linked to marginalization; and (3) an ambivalent structure of autonomy, as children valued peer independence yet expressed fear of adult punishment and responsibility. Conclusions: Findings suggest that during the latency stage autonomy shifts toward a collectively organized peer-group process. Recognizing group autonomy as a developmental dimension may deepen understanding of social status and peer rejection within classroom contexts. Full article

Empty Container Management (ECM) represents a cost-intensive and environmentally impactful component of global container logistics, with its effects most visibly manifested in inland transport systems. Despite extensive academic attention, research on ECM remains fragmented across optimisation, coordination, sustainability, and technology-oriented approaches, often addressing isolated processes or decision problems. As a result, persistent costs, inefficiencies, and emissions continue to characterise inland container logistics. This study applies PRISMA guidelines to systematically review the ECM literature. The analysis focuses on three aspects: the structural causes of container imbalances, the operational activities generating costs and emissions, and the stakeholders influencing ECM decisions. The findings show that empty container imbalances do not arise from a single source. Instead, they result from the interaction of global trade asymmetries, demand uncertainty, fragmented inland operations, and diverse regulatory and institutional environments. The answers to the research questions reveal three fundamental research gaps in the existing literature. First, optimising locally does not always improve the entire system, as it might simply shift costs to other parts of the empty container management (ECM) system. Second, technological solutions cannot operate effectively without appropriate governance mechanisms and data-sharing arrangements. Third, the actors responsible for setting rules and controlling equipment availability often do not bear the full consequences of empty container movements. This review provides a structured foundation for developing integrative decision-support approaches capable of addressing inland ECM under real-world structural constraints. Full article

Kazakhstan is one of the world’s major wheat producers and exporters, playing an important role in regional and global food security. However, increasing quality requirements in domestic and export markets have exposed limitations in the country’s capacity to consistently supply high-quality spring bread wheat (Triticum aestivum L.). This review aims to assess the current status of spring wheat grain quality in Northern Kazakhstan, identify the main factors driving its variation, and outline pathways for quality improvement. The analysis is based on published literature, official statistics, national quality standards, and recent data on wheat production, grading, breeding systems, agronomic practices, and trade patterns. The review reveals that wheat production is dominated by medium-quality grain (primarily class 3), while high-quality classes suitable for premium and improver markets represent a small share. Compared with major exporters such as Canada, the United States, and Australia, Kazakh wheat is generally inferior across key quality parameters. Structural constraints include the limited integration of quality assessments within breeding programs, insufficient laboratory infrastructure, weak agroecological zoning by quality classes, and suboptimal agronomic management, particularly regarding nitrogen use. Environmental heterogeneity and climate change further influence the yield–quality balance. Overall, the findings suggest that improving wheat grain quality in Kazakhstan will require coordinated advances in breeding, agronomy, institutional capacity, and market alignment, enabling a gradual shift toward a more competitive, quality-oriented wheat production system. Full article

With the wave of new campus construction gradually receding, the focus of green campus planning and design is shifting toward the low-carbon retrofitting of the existing built environment. University campuses often face challenges such as dispersed land use, inadequate spatial planning, disorganized road layouts, suboptimal landscape design, and low energy efficiency. Grounded in a review of current research on campus carbon emissions, this study integrates green technology indicators with planning and design approaches to establish a multi-scale, context-adaptive planning framework for carbon control, spanning five dimensions: intensive land use, spatial layout, transportation systems, landscape development, and facility integration. Employing a combined approach of bibliometric analysis and case studies, this research examines and compares typical university campuses both domestically and internationally to validate the effectiveness of the synergistic “technology-system-behavior” pathway in mitigating high-carbon lock-in. Through a systematic comparative analysis of representative low-carbon campuses, the synthesized results indicate that under optimal operational conditions, the clustered reorganization of functional zones demonstrates the potential to reduce transportation carbon emissions by approximately 25%; comprehensive retrofitting of building envelopes can decrease building energy consumption intensity by an estimated 30%; a multimodal coordinated transport system can increase the share of non-motorized travel to around 65%; establishing high carbon-sequestration plant communities can enhance carbon sink capacity by up to 30%; and smart facility integration can reduce overall campus carbon emissions by a projected range of 25–40%. It should be noted that these quantitative outcomes represent high-probability potential ranges, with actual performance subject to behavioral and operational fluctuations. This study provides theoretical support and practical pathways for achieving “near-zero carbon campuses” and underscores the important demonstrative role that higher education institutions can play in addressing climate change. Full article

The stability of solar-dependent energy systems is vital for urban sustainability, but it is increasingly threatened by compound energy risks (CERs), events where low photovoltaic generation coincides with high electricity demand. This study addresses a critical knowledge gap by disentangling the co-evolving structural and magnitude drivers of these events to identify their propagation pathways and the most vulnerable districts. To achieve this, a novel hybrid framework was developed to provide a high-resolution, spatiotemporal assessment of both risk dimensions across Singapore’s 41 districts. Structural risk was mapped by integrating an undirected co-occurrence network, quantified using Mutual Information (MI), with a directed influence network derived from Bayesian Network Theory (BNT). Concurrently, magnitude risk was assessed through a copula-based analysis of joint probabilities for historical and future climate conditions, using Singapore’s new V3 dataset under multiple Shared Socioeconomic Pathways (SSPs). The results reveal a significant shift in the compound energy risk landscape. Structurally, the network of risk propagation evolves from a historically diffuse configuration to a consolidated system dominated by clusters of 8 to 9 highly interconnected districts under the SSP245 scenario. Under the high-diffusion SSP585 scenario, this evolution is expanded by the addition of 4 more districts. At the same time, the magnitude of risk intensifies across identified hotspot districts. This synthesis uncovers a critical feedback dynamic: districts such as 29, 36, and 40 not only serve as key structural hubs but also experience sharp increases in event probability, with their return periods for extreme compound events collapsing from over 50 years historically to the 10–20-year range. This forms a self-reinforcing loop of systemic vulnerability. These findings indicate that Singapore’s energy security will become increasingly exposed to climate-driven risks that propagate through this consolidated network, requiring targeted spatial adaptation to ensure long-term grid sustainability. Full article

The rapid increase in point density and acquisition rate of UAV laser scanning (ULS) systems has shifted the primary bottleneck of LiDAR workflows from data acquisition to post-processing, particularly during direct georeferencing of massive LiDAR measurements. This study presents a systematic evaluation of parallel computing strategies for accelerating ULS direct georeferencing while preserving geodetic accuracy. Two georeferencing models are investigated: (1) a rigorous model that strictly follows the full geodetic transformation chain from sensor owned coordinates system (SOCS) to projected map coordinates, and (2) an approximate model that incorporates meridian convergence angle compensation and preprocessing of platform trajectories to reduce per-point computational complexity. For each model, a shared-memory multicore CPU implementation based on OpenMP and a heterogeneous GPU implementation based on CUDA are designed. Experiments were conducted on seven real-world ULS datasets, ranging from 2.9 × 10⁷ to 7.0 × 10⁸ points and covering diverse terrain types. Accuracy analysis shows that, in typical urban, plain, and industrial scenarios, the approximate model achieves millimeter-level mean errors and centimeter-level RMSEs relative to the rigorous model, satisfying the requirements of most engineering surveying applications. Performance evaluation demonstrates that parallelization yields substantial speedups: OpenMP-based method achieves 7–9 times acceleration, while GPU computing attains up to 24.6 times acceleration for the rigorous model and up to 16.7 times for the approximate model. The results highlight the complementary strengths of the two models and provide practical guidance for selecting accuracy-efficiency trade-offs in large-scale ULS production workflows. Full article

The intricate relationships between humans and animals have long shaped philosophical, cultural and scientific inquiry. This narrative review examines evolving conceptions of animal consciousness, agency and sentience within broader historical, ethical and epistemological contexts. Drawing on philosophy, ethology, neuroscience, psychology and animal studies, it critically engages debates on anthropocentrism, cognitive ethology, moral considerability and relational ontology. By tracing the shift from mechanistic models of animality to embodied and affective accounts of consciousness, the analysis highlights how contemporary scholarship destabilises traditional forms of human exceptionalism. Building on this interdisciplinary synthesis, the article advances a symbiotic humanist orientation that integrates evolutionary continuity with multidimensional models of consciousness and differentiated normative responsibility. The argument culminates in the articulation of a Stratified Relational Responsibility Model (SRRM), which reconciles ontological continuity with asymmetrical accountability. Within this framework, shared evolutionary conditions ground moral considerability, while the emergence of reflexive and institutional normativity intensifies human ethical obligation. The model offers a non-anthropocentric yet normatively robust account of human–animal relations, situating human distinctiveness not in metaphysical superiority but in heightened responsibility within multispecies ecological systems. Full article