Search Results (7,563)

Hot dry rock (HDR) is a promising renewable energy resource whose vast reserves and wide distribution have attracted extensive attention in recent years. However, exploiting HDR resources requires hydraulic stimulation, which is typically accompanied by substantial microseismic activity, posing significant risks to project safety and public acceptance. Current understanding of microseismic mechanisms, particularly the role of fracture geometry under varying injection schemes, remains inadequate. This study employs a three-dimensional block-based discrete element method to construct a fluid–mechanics coupled model founded on a discrete fracture network, aimed at investigating the mechanical behavior of fractures and the spatial distribution of microseismicity during hydraulic stimulation. Our results quantitatively demonstrate that fractures oriented at 45° to the maximum principal stress are most susceptible to shear reactivation and microseismic clustering, with event magnitudes strongly correlated to both fracture orientation and intra-fracture fluid pressure. Consequently, preventing critically high fluid pressures in natural fractures near the injection well, particularly those at approximately 45° to the maximum principal stress direction, is essential for risk mitigation. Cyclic injection can shear more fractures and slightly reduce magnitudes via staged pressure relaxation, but its effectiveness in controlling microseismic magnitude is limited. Therefore, it is recommended to implement measures to control the entry of fracturing fluid into these high-risk fissures, such as segmented fracturing or temporary plugging techniques. This strategy is expected to enhance seismic risk mitigation, thereby contributing to the safe and efficient exploitation of deep geothermal resources. Full article

Integrated urban–rural development is of great significance in promoting coordinated development in underdeveloped areas across provinces and advancing common prosperity. Previous studies have mostly focused on typical counties in single or developed areas, with insufficient exploration of integrated urban–rural development in underdeveloped areas. A total of 71 counties in Wuling Mountain area were taken as the research object, and a conceptual model of “element–structure–function” was constructed based on the theory of the urban–rural integration system. The entropy weight ideal point method, variation coefficient method, coupling coordination model, and obstacle model were employed to analyze the integrated urban–rural development in counties of the Wuling Mountain area during 2010 and 2023 from the five dimensions of population, economy, space, society, and ecology, and to explore their coupling coordination relationship and key obstacle factors. The research results indicate the following: (1) During the study period, the average annual growth rate of integrated urban–rural development was only 1.213%, showing a relatively low level. The spatial evolution exhibited a trend of “overall optimization–gap convergence–multipolar linkage–hot in the south and cold in the north”. (2) The comprehensive coupling coordination increased from 0.6380 in 2010 to 0.7016 in 2023, and the coupling coordination of “population–space” became the dominant mode. Nearly 60% of counties achieved a level upgrade from the transition stage to the coordination stage, and the multidimensional coordination relationship was mainly affected by the dual effects of spatial polarization and ecological constraints. (3) The obstacle of spatial integration ranked first and the mismatch of factors was severe. Land urbanization and population distribution imbalance were key obstacles, and their core contradictions were concentrated in the tripartite dilemma of “extensive land utilization–factor blockage–ecological antagonism”. It is urgent to achieve coordinated and sustainable development of urban and rural integration through market-oriented reforms of two-way factor flow. The conceptual model of “element–structure–function” constructed by the research results can provide a theoretical tool for analyzing the integrated development of urban and rural areas in counties, and can provide decision support for solving the dilemma of element mismatch. Full article

This paper presents the theoretical and methodological foundations of Living a Life of Meaning and Purpose-C (LAMP-C), a novel quantitative instrument designed to assess meaning-making capacity among emerging adults to be used as part of a battery of assessments for religiosity. Drawing on Constructive-Developmental Theory (CDT) as articulated by Robert Kegan, Sharon Daloz Parks, and Marcia Baxter Magolda, LAMP-C operationalizes complex developmental constructs such as cognitive, interpersonal, and intrapersonal growth. LAMP-C integrates CDT with the Rasch/Guttman Scenario (RGS) methodology, which systematically structures items to reflect incremental developmental complexity. An instrument for assessing meaning-making contributes to the comprehensive interpretation of assessments of religiosity among emerging adults. By framing meaning-making through four facets—ideation, relational awareness, conflict resolution, and sense of responsibility—this paper provides a comprehensive conceptual foundation for measuring growth in meaning-making. The RGS methodology further enhances construct validity by enabling precise, context-specific, and developmentally sensitive assessments across three contexts. LAMP-C bridges the gap between qualitative depth and quantitative breadth in assessing developmental constructs, offering a tool that supports both large-scale applications and nuanced theoretical alignment. LAMP-C establishes a framework for assessing meaning-making while setting the stage for future empirical research (e.g., longitudinal studies) to evaluate religiosity in emerging adults. Full article

An accurate topology of low-voltage distribution grids (LVDGs) serves as the foundation for advanced applications such as line loss analysis, fault location, and power supply planning. This paper proposes a two-stage topology identification strategy for LVDGs based on Contrastive Learning. Firstly, the Dynamic Time Warping (DTW) algorithm is utilized to align the time series of measurement data and evaluate their similarity, yielding the DTW similarity coefficient of the sequences. The Prim algorithm is then employed to construct the initial topology framework. Secondly, aiming at the topology information obtained from the initial identification, an Unsupervised Graph Attention Network (Unsup-GAT) model is proposed to aggregate node features, enabling the learning of complex correlation patterns in unsupervised scenarios. Subsequently, a loss function paradigm that incorporates both InfoNCE loss and power imbalance loss is constructed for updating network parameters, thereby realizing the identification and correction of local connection errors in the topology. Finally, case studies are conducted on 7 LVDGs of different node scales in a certain region of China to verify the effectiveness of the proposed two-stage topology identification strategy. Full article

As an advanced form of community development, Future Communities (Weilai Shequ) is a policy-led urban initiative launched in Zhejiang, China, that prioritizes human-centered development. However, it is currently confronted with an inherent contradiction: the expansion of technological rationality is encroaching upon humanistic values. Centering on the core “technology–human” relationship, this study is dedicated to exploring development measures for Future Community that synergistically integrate technological empowerment and humanistic care. Using natural language processing techniques (LDA topic modeling), we conducted an exploration and analysis of the thematic characteristics and evolution of 40 policy documents related to future communities issued by the central and local governments of China from 2014 to 2024. The study identifies six core topics: Quality Enhancement, Technical Foundation, Intelligent Operations and Maintenance, Green and Low-Carbon, All-Age Friendliness, and Community Services. Analysis revealed that each theme embodies a dual connotation of both technological and humanistic dimensions. Furthermore, the study revealed that the evolution of policy semantics follows a three-stage developmental pattern: technology dominance and nascent human-centered values; human-centered rise and technology empowerment; and human-centered deepening and technological embeddedness. Based on the above findings, and grounded in a phenomenological perspective, this study integrates Alexander’s human-centered architectural philosophy with Ihde’s theory of technological mediation to propose a future community construction pathway jointly driven by “technological mediation” and “human presence.” Theoretically, this research transcends the binary narrative of technology versus humanism. In practice, it provides policymakers with tools to avoid technological pitfalls. It establishes fundamental principles for planners and designers to implement humanistic values, ultimately aiming to realize, at the community level, the vision of technology serving humanity’s aspiration for a better life. Full article

Spinach is a beloved vegetable crop and widely cultivated worldwide. It is dioecious with male and female plants, although monoecious mutations exist. Female spinach exhibits two distinct sepal morphologies—thorn-shaped and round-shaped determine seed shape and strongly influence seed handling, mechanized sowing, and cultivar classification. To dissect the genetic basis of this trait, we developed an F₂ population from contrasting parental lines and constructed a high-density linkage map with ~1615 bin markers spanning ~994.04 cm. A major 4.31 Mb genomic interval on chromosome 4, flanked by tightly linked markers, was consistently associated with sepal morphology. Transcriptome profiling across early and mature sepal developmental stages revealed significant enrichment of cell cycle-related pathways, including DNA replication, repair, mitosis, and cytokinesis. By integrating differential expression analysis with weighted gene co-expression network analysis, we identified 25 DEGs within the mapped interval, 11 of which showed strong co-expression with hub genes in trait-associated modules. Structural variation analysis further uncovered promoter and coding sequence polymorphisms in a subset of candidate genes. This study highlights 11 promising candidate genes potentially regulating sepal-derived seed morphology in spinach, rather than confirming definitive causal genes, providing valuable targets for functional validation and new insights into the genetic regulation of sepal development. Full article

To address the pronounced asymmetry and strong nonlinearity exhibited by the tractor electro-hydraulic hitch system during lifting and lowering operations, this study proposes a distributed parameter identification method based on a dual-mode grey-box modelling approach. Following a mode decomposition strategy, the lifting and lowering processes are regarded as two independent subsystems. Benchmark transfer function models are established for each subsystem through theoretical derivation. Considering the nonlinear characteristics and unmodeled dynamics that cannot be accurately captured by the benchmark model, a long short-term memory (LSTM) neural network compensator is introduced to enhance the model performance. Ultimately, a series-compensated dual-channel grey-box model is established, which effectively integrates mechanistic interpretability with high modelling accuracy. Then, to cope with the high-dimensional and heterogeneous parameter space of the constructed grey-box structure, a distributed parameter identification framework is proposed. This framework employs a staged optimization process that combines the whale optimization algorithm (WOA) with the gradient descent (GD) method to efficiently identify the hybrid parameter set. The identified models are validated through bench experiments. The results show that the proposed grey-box models achieve root mean square errors (RMSEs) of 0.33 mm and 0.48 mm, and mean absolute errors (MAEs) of 0.24 mm and 0.40 mm for the lifting and lowering processes, respectively. Compared with a single transfer function model, the RMSE is reduced by 57.6% and 87.3%, and the MAE is reduced by 59.2% and 87.9%, respectively. The proposed method substantially improves the modelling accuracy of the electro-hydraulic hitch system, providing a reliable foundation for system characterization and the design of high-performance control strategies for tractor electro-hydraulic hitch systems. Full article

Despite the growing use of collaborative robots in high-rise construction, ensuring safe human–robot collaboration (HRC) in hazardous environments remains a critical challenge. Addressing the gap that previous studies optimized human, robot, or task factors in isolation without a systemic coordination perspective, this study develops and empirically validates a Human–Task–Robot Alignment (HTRA) framework to explain how alignment mechanisms enhance safety performance in the construction of HRC. Data from 84 high-rise HRC projects were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that HTRA serves as a pivotal mechanism for safety improvement, where Human–Robot Alignment (HRA) and Task–Human Alignment (THA) exert stronger effects on bilateral safety perception than Task–Robot Alignment (TRA), underscoring the centrality of human factors at the current stage of HRC development. Moreover, this study identifies a sequential cognitive–behavioral path from safety perception to safety intention and safety behavior performance, explaining how alignment enhances safety performance. Standardized HRC guidelines further strengthen HRA, facilitating safer and more efficient collaboration. This study extends Task–Technology Fit theory to a triadic human–task–robot context and advances the concept of bilateral safety, providing theoretical and managerial guidance for developing next-generation safe collaboration systems in construction. Full article

Different Digital Governance maturity models are established; however, limited research has examined their applicability at the local government level, particularly concerning the interrelations among dimensions such as Strategy, Employees, and Processes. Understanding these connections is vital for municipalities striving to enhance resilience through Digital Governance amidst uncertainties. This study aims to develop, justify, and empirically test a Triadic Model capturing the relationships among its dimensions, assessing Digital Governance maturity in local governments during crisis response. To achieve this, a quantitative survey was conducted across all 60 Lithuanian municipalities, and the collected data were analyzed using Confirmatory Factor Analysis (CFA) to validate the factor structure and Structural Equation Modeling (SEM) to test the hypothesized relationships among variables and latent constructs. The findings reveal significant interrelations among the model’s dimensions in enhancing municipal resilience. Research proposes a comprehensive framework for assessing Digital Governance maturity at three levels—Digital Consistency, Digital Adaptation, and Digital Transformation—and examines their interactive influence during crises. The results highlight how the dimensions of the Triadic Model collectively reflect municipal responses, emphasizing the importance of an integrated, staged approach to digitalization. This validated framework advances understanding of Digital Governance in local authorities and underscores the relevance of interrelated key dimensions for fostering resilience in uncertain contexts. In addition to model validation, the study also explores practical variations in Digital Governance maturity among Lithuanian municipalities, demonstrating the model’s applicability as a diagnostic tool for local governments. Full article

The development of a geomechanical model is aimed at enhancing the safety of mining operations through the determination of optimal slope angles and the probabilistic assessment of pit wall stability. For the conditions of open-pit mining, three-dimensional geomechanical models were constructed based on the calculation of the slope stability factor using the Rocscience Slide2/Slide3 (v.9.027, 2023) software package. The stress–strain state of the rock mass at the final stage of extraction was evaluated using the finite element method. Strength reduction factors (SRF) were determined considering the physico-mechanical properties of the rocks forming the near-contour zone of the massif. The stability of the pit slopes was assessed along individual geological cross-sections in accordance with the design contours of the Northern Katpar open pit. Calculations performed using several methods confirmed the overall stability of the pit walls. The final design parameters of the projected open pit were determined. For the first time, it was established that in the southern and southwestern sectors of the Northern Katpar pit, within the elevation range of +700 to +400 m, a reduction in the SFR (from 1.18 to 1.41) occurs due to the predominance of siltstones and the presence of tectonic disturbances. The generalized results of numerical slope stability analyses for the design pit contour, together with the developed geological–structural model of the deposit, provide a basis for ensuring the safe conduct of mining operations at the site. Full article

The development of epidermis plays a central role in driving the morphogenesis of the Caenorhabditis elegans embryo. However, current research on epidermal morphogenesis focuses disproportionately on overt phenotypic abnormalities, potentially overlooking the crucial role of developmental timing. In this study, we developed a modular two-step deep learning-based image analysis pipeline. First, we used ResU-Net to extract completely developed embryos and suppress noise; second, ResNet was used to predict the corresponding embryonic stage. The predicted probabilities and their corresponding embryonic time points were subsequently utilized to construct a developmental timeline. Combining this pipeline with differential interference contrast time-lapse microscopy, we dynamically tracked the timeline of epidermal morphogenesis in RNAi-treated embryos (ajm-1, tes-1, leo-1) and mutant embryos (clk-1). By statistically comparing the duration of each embryonic stage, our approach enabled the detection of stage-specific developmental timing without relying on overt phenotypic abnormalities or fluorescent markers, successfully recapitulating and extending the known roles of these genes from a temporal perspective. Our work underscores the importance of incorporating developmental timing into morphogenetic analysis, offering a novel framework for revealing subtle developmental processes, deepening the understanding of morphogenetic dynamics, and bridging the methodological gap in C. elegans embryology. Full article

Carbon emission efficiency plays a vital role in the realization of the “dual carbon” goals. Taking land resource allocation as the entry point, this paper explores how land resource misallocation (LRM) affects carbon emission efficiency (CEE) to support the enhancement of CEE and the optimal allocation of land resources. Using 108 cities in the Yangtze River Economic Belt from 2003 to 2021 as an example, this paper constructs a panel smooth transition model (PSTR), with industrial structure as the transition variable, to examine the nonlinear impact effects of LRM on CEF and its regional heterogeneity. The research results show that the LRM index as a whole presents a fluctuating downward trend, while CEF shows a fluctuating but slow upward trend, and the regional differences in both LRM and CEF continue to expand. There exists a significant nonlinear relationship between LRM and CEF. When the advancement of industrial structure index shifts from the low regime to the high regime, the impact of LRM on CEF presents an inverted “U”-shaped curve characteristic. The nonlinear impact of LRM on CEF exhibits regional heterogeneity, and the threshold effect of industrial structure is the main reason for the regional differences in the nonlinear impact. Therefore, it is necessary to accelerate the market-oriented reform of land factor allocation, and to formulate phased and differentiated land resource allocation policies adapted to the stages of industrial structure development, so as to effectively serve the goals of green, low-carbon, and high-quality development. Full article

Water inrush disasters pose a serious threat during tunnel construction. Accurately evaluating their evolution process is essential for timely prevention and risk mitigation. Given the staged nature of seepage-instability-induced inrushes and the sensitivity of borehole resistivity imaging to water-bearing anomalies, this study explores the use of borehole resistivity methods to monitor the evolution of such events. A four-stage geoelectrical evolution model is developed based on the characteristics of inclined fault-related water inrushes. A time-lapse evaluation method combining least squares inversion and resistivity ratio analysis is proposed to assess the inrush process. Numerical simulations show that this method achieves a localization error below 2 m for inclined water-conducting channels. Across the four stages, the resistivity ratio of the channel ranges from 0.65 to 1.40, capturing the three-dimensional expansion of the inrush pathway. These findings confirm that borehole resistivity imaging effectively characterizes the evolution of water inrush disasters and supports early warning and mitigation strategies. Full article

This article develops a conceptual framework of Sustainable Human Resource Management (Sustainable HRM) by integrating three critical dimensions: Green HRM practices, ethical and responsible leadership, and digital resilience in HR systems. Positioned within the United Nations Sustainable Development Goals (SDGs), the study addresses the lack of theoretical integration across the fragmented literature. The framework highlights employee well-being as the central mediating construct linking HRM practices to sustainability outcomes, connecting micro-level engagement, meso-level HR systems and leadership ethics, and macro-level policy and ESG alignment. This explicitly demonstrates the multi-level (micro–meso–macro) nature of the framework. The proposed model advances theory by extending HRM beyond organizational boundaries, offering Sustainable HRM as a boundary-spanning and original perspective that links people management to global sustainability agendas. Using a five-stage conceptual development process including literature synthesis, construct definition, integrative framework building, formulation of conceptual propositions, and the design of a future research agenda—this study explicitly acknowledges its conceptual nature to set appropriate reader expectations and ensures methodological transparency in framework development. The study further contributes (1) to theory by clarifying how Green HRM, ethical leadership, and digital resilience interact through employee well-being to advance sustainability; (2) to practice by providing HR leaders with pathways to embed sustainability into core processes; and (3) to policy by informing regulators on HRM’s role in achieving SDGs. Ultimately, the framework positions HRM as a strategic enabler of sustainable development. Full article

Excavation is a common requirement in engineering construction within rock masses. While excavation volumes are generally limited in road slope projects, they may become substantial in large-scale operations such as deep open pit mines. The interaction between time and cost in excavation processes is strongly controlled by rock mass excavatability, which has been recognized as a key factor in project budgets. Since the 1970s, excavatability assessment has therefore attracted considerable research interest in rock mechanics. In this study, the excavatability cases previously plotted on the Geological Strength Index (GSI) versus Uniaxial Compressive Strength of the Rock Mass (σ_{c_rm}) diagram in the literature were improved by employing an Artificial Neural Network (ANN). The ANN approach was used to investigate the boundaries between digger, ripper, and hammer+blasting excavation classes within the available case zones defined by GSI–σ_{c_rm} data pairs. The prediction performance of the developed rock mass excavatability chart is highly acceptable, with correct classification rates of 91.1% for blasting+hammer and ripper classes, and 87.2% for the ripper class. Considering GSI and σ_{c_rm} as the main input parameters, the proposed ANN-oriented excavatability chart is highly acceptable for preliminary equipment selection during the design stage of surface rock mass excavations, including slope cases. Full article