Search Results (37,696)

Energy-efficient renovation of existing buildings is one of the important approaches to achieving sustainable development. This study takes a naturally ventilated sports hall (without heating or air conditioning systems) at a university in Weifang, Shandong Province, as the research object, where indoor thermal comfort levels remain low throughout most of the year. Adopting passive optimization as the core approach, the study aims to improve natural daylighting and winter thermal environment by adjusting window-to-wall ratio (WWR), window-to-floor ratio (WFR), skylight height, and glass thermal–optical parameters. The research methodology consists of two main stages: field measurement and multi-scenario simulation. On-site measurements were first conducted to ascertain the building’s actual usage patterns, existing daylighting conditions, and temperature distribution characteristics. Subsequently, six scenarios—including the original design, the current condition, and four differentiated optimization schemes (Schemes A, B, C, and D)—were quantitatively evaluated for indoor daylighting and thermal performance using Ecotect Analysis 2011 and eQUEST 3.65. The simulation models were calibrated against field measurement data to ensure result reliability. Key findings are as follows. In terms of daylighting, daylight factor and indoor average illuminance increase significantly with higher WFR, with this growth trend noticeably plateauing around a WFR of 0.7. Illuminance uniformity should be comprehensively assessed using both of its calculation methods; skylights provide more balanced daylighting than side windows, and combined side-window and skylight schemes yield far superior illuminance uniformity compared to single-type window arrangements. Regarding thermal performance, in schemes incorporating skylights, indoor temperature rises with increasing glazing area when WFR is below 0.7; however, when WFR exceeds 0.7, building heat dissipation surpasses solar heat gain, causing indoor temperature to decrease. Considering annual thermal comfort performance, Scheme C achieves the longest cumulative comfort hours and the most balanced year-round thermal performance, making it suitable for renovation projects pursuing stable indoor environments. Scheme A demonstrates significant winter warming effects but suffers from overheating defects during summer and transition seasons, thus requiring enhanced ventilation measures. After implementing increased ventilation (5 air changes per hour), Schemes A and C achieve 36.7% and 37.2% more comfortable hours during the building’s 10-month usage period, respectively, compared to the current condition. In conclusion, for large-space buildings such as sports halls, relying solely on increasing WFR and WWR for passive winter warming yields limited effects, and coordinated optimization of glass thermal–optical properties and ventilation strategies should be adopted. Full article

Faults in high-permeability fault-block reservoirs may act as sealing boundaries, partial flow baffles, or hydraulically communicating interfaces. In this study, a field-constrained pressure-transient workflow is developed for diagnosing fault-related flow baffling in long-horizontal-well reservoir systems. Finite cross-fault transmissibility is represented by a leakage coefficient, $L_f$, and numerical models are used to examine the evolution of middle- and late-time pressure-derivative responses. The model is benchmarked against KAPPA Saphir and reproduces the principal derivative-shape evolution, anomaly timing, and peak attenuation, with average errors of 9.66% for the pressure derivative and 10.36% for pressure drawdown over the comparison interval. As $L_f$ increases, the response evolves from sustained late-time uplift to finite humps, broadened transitions, weak platform distortion, and connected-like behavior. For finite anomalies, the relative intensity $I_h$, occurrence time $t_h$, and transition width $W_h$ describe anomaly magnitude, timing, and broadness; sustained-uplift and connected-like responses are interpreted qualitatively. The workflow is applied to three anonymized long horizontal wells: Well A shows strong boundary control, Well B shows a broadened transitional anomaly with $I_h^{*}=0.61$ and $t_h=27.17$h, and Well C shows a smooth, connected-like response. The results indicate that fault diagnosis is inherently non-unique and should combine derivative characteristics with well–fault geometry, test quality, reservoir properties, production dynamics, and geological constraints. The framework provides a practical dynamic complement to static fault-seal interpretation. Full article

Reading comprehension is a critical cognitive competency in higher education, although learners demonstrate substantial variability in responsiveness to metacognitive instructional interventions. The study focused on individual cognitive-response processes within the framework of the adaptive metacognitive reading system, which was realized through precision-learning architecture, which integrates latent learner-response phenotyping, explainable machine learning, Markov transition analysis, Bayesian adaptive inference, and reinforcement-learning optimization. The study employed a quasi-experimental longitudinal design involving an eight-week structured metacognitive reading intervention delivered through planning, monitoring, evaluation, strategic flexibility, and reading self-regulation activities. The psychometric analyses demonstrated satisfactory reliability of the adapted Metacognitive Awareness Inventory (MAI), with Cronbach’s α ranging from 0.83 to 0.89. A latent-profile model revealed significant heterogeneity of learner-response patterns among learners, with four learner-response phenotypes: High Responders, Strategic Improvers, Monitoring-Dependent Learners, and Low Responders. Explainable machine-learning models performed well in predicting individualized comprehension gains, with the model with the highest predictive accuracy being XGBoost (R² = 0.61). Markov transition modeling identified exploratory learner-state redistribution patterns following the intervention. Bayesian adaptive inference and reinforcement-learning optimization were subsequently conducted as post hoc simulation procedures to estimate hypothetical adaptive instructional calibration scenarios rather than as real-time instructional decision systems. Overall, the proposed Adaptive Cognitive Intervention Architecture (ACIA) should be interpreted as an exploratory computational framework for modeling learner heterogeneity, predicting comprehension gains, and simulating post hoc computational optimization in higher-education learning environments. Full article

Backfill mining is a key technique for achieving mine stratum control and synergistic disposal of solid waste. Cemented backfill, as the core bearing structure of the mined area, plays an essential role in ensuring engineering safety and promoting green mining practices. This review systematically explains the multiscale mechanisms of strength development in backfill and establishes a three-tier analytical framework based on “Materials–Environment–Structure”. At the material level, previous research has revealed the microscopic mechanisms involving hydration products and the interfacial transition zone (ITZ); at the environmental level, the coupling of multiphysical fields during strength evolution has become a focal point of study. The core challenge lies in the fact that large-volume backfill under field conditions, which forms layered structures, is anisotropic and exhibits size effects during sedimentation and processing stages, significantly controlling the macroscopic mechanical behavior. This is difficult to fully reveal through laboratory research focused on homogeneous materials. The authors provide a comprehensive review of experimental, simulation, and theoretical results, with a focus on revealing the controlling mechanisms of factors such as layered weak interfaces, inclined interfaces, and structural scale for backfill strength and failure modes. Moreover, the proposed “Materials–Environment–Structure” framework offers predictive potential for linking multiscale strength formation mechanisms with field-scale structural performance. The goal is to advance the understanding of strength from material constitutive models to structural responses, providing theoretical support for the development of strength prediction methods and structural designs suitable for engineering practice. Full article

Existing residential buildings constructed under earlier thermal-design standards often lack effective external solar control systems. Building envelope retrofits must extend beyond mere cooling load reductions; instead, they require a holistic evaluation of summer heat rejection, winter solar gain preservation, transmitted solar exposure, and retrofit-induced embodied carbon. This study develops a screening-level method for climate-adaptive passive shading retrofits. The workflow integrates hourly solar-position reconstruction, facade irradiance mapping, shading geometry interception, and a reduced-order 2R2C thermal network. NSGA-II is used to generate Pareto-optimal alternatives, CV-TOPSIS is applied to identify representative trade-off solutions, and a life-cycle-informed carbon payback check within an A1–A4 + B6 boundary is used to test whether operational carbon savings can offset the upfront carbon of shading components and glazing replacement. Five Chinese cities—Haikou, Shanghai, Beijing, Lhasa, and Urumqi—are selected to represent the transition from cooling- to heating-dominated climates. For comparative screening, the reduced-order model shows acceptable agreement with an EnergyPlus benchmark, with NMBE, CV(RMSE), and $R^2$ values of +2.11%, 28.25%, and 0.804, respectively. The selected solutions reveal strong climate dependence in both shading morphology and carbon performance. For instance, Haikou exhibits the largest annual electricity savings (2030.3 kWh/yr) and the shortest Carbon Payback Period (1.8 years). In Lhasa, by contrast, the CV-TOPSIS-selected compromise scheme reduces the transmitted solar exposure proxy but increases annual energy use by 706.1 kWh/yr, indicating that this selected compromise, rather than fixed shading in general, is not carbon-effective within the defined boundary. The proposed method supports climate-specific retrofit screening by jointly considering heating–cooling balance, solar radiation conditions, and regional grid carbon intensity. Full article

Cu–Fe alloys combine the high electrical conductivity of Cu with the strengthening and magnetic contributions of Fe, making them promising high-strength, electrically conductive functional materials. However, for high-Fe Cu–Fe alloys with Fe contents exceeding 10 wt.%, the microstructural response, texture evolution, and two-phase deformation partitioning during warm rolling remain insufficiently understood. In this study, Cu–10Fe, Cu–15Fe, and Cu–20Fe alloys were investigated to clarify the effect of Fe content on microstructure evolution, texture characteristics, deformation behavior, and property balance after single-pass warm rolling at 500 °C with a 50% reduction. The results show that, as the Fe content increased from 10% to 20%, the Fe-rich phase became progressively denser after warm rolling and gradually transformed from discrete spherical/spindle-like particles into fibrous structures distributed along the rolling direction, while the average grain size of the alloy decreased. EBSD analysis indicates that increasing Fe content weakened the preferred orientation of the Cu matrix. The maximum texture intensity of the Cu matrix decreased from 5.08 to 4.21, and texture showed a weakening trend. The mechanical properties show that, with increasing Fe content, the ultimate tensile strength increased from 434 MPa to 514 MPa, whereas the elongation decreased from 10.7% to 5.1%. This indicates that the increased amount of Fe-rich phase enhanced strength but reduced plasticity; nevertheless, dynamic recovery and local recrystallization induced by warm rolling helped maintain a certain degree of ductility. The electrical conductivity decreased from 19.43% IACS to 16.71% IACS with increasing Fe content, corresponding to a decrease of only approximately 2.7% IACS, suggesting that warm rolling partially mitigated the negative effect of increasing Fe content on electrical conductivity. Based on the combined microstructural, texture, and KAM/GND analyses, the deformation behavior of the alloys with increasing Fe content exhibited a transition from heterogeneous deformation dominated by the Cu matrix/interface to cooperative deformation involving the Fe-rich phase. Full article

Nanoglasses (NGs) have received much attention due to their superior ductility and well-retained strength compared to their metallic glass counterparts. However, few studies have examined how notch geometry affects the mechanical behavior and deformation mode of NGs. In this work, molecular dynamics simulations are performed on un-notched and symmetric double-edge notched Mg₃₃Cu₆₇ NGs under tensile loading, with focus on the roles of notch depth, height, and sharpness in determining their mechanical properties and failure modes. Our simulation results show that symmetric double-notched specimens exhibit higher strength and plasticity than un-notched counterparts. The improved plasticity is attributed to a transition in the deformation mode. Furthermore, the deformation mode and strength of notched specimens strongly depend on the notch depth and sharpness. The strengthening effect is enhanced with increasing notch depth or sharpness. This enhancement is likely related to the constrained growth of the plastic zone, which requires a higher stress for continued propagation. In addition, by altering notch depth and sharpness, the deformation mode is observed to change from shear banding-dominated to mixed-mode and then to necking-governed behavior. The mixed mode, characterized by the intersection of V-shaped shear bands, can accommodate substantial additional plastic deformation. Our key finding is that the mixed deformation mode, enabled by proper notch geometry, leads to a remarkable enhancement in both strength and plasticity. This work aims to provide significant insights into the deformation and failure mechanisms of notched NGs, offering an effective design strategy for optimizing their strength and ductility. Full article

This study investigates the impact of liquidity risk on asset quality and financial stability in Uzbekistan’s commercial banking sector. Using quarterly time-series data from 2016 to 2024, the study employs Ordinary Least Squares (OLS) regression with quadratic specifications to capture potential non-linear effects of liquidity. Two models are estimated to examine (i) the relationship between liquidity risk and asset quality, and (ii) the impact of liquidity risk on financial stability, proxied by net profit. The results indicate that liquidity risk does not have a statistically significant effect on asset quality, suggesting that credit performance is primarily driven by structural and macroeconomic factors rather than liquidity conditions. In contrast, the financial stability model demonstrates high explanatory power (R² = 0.883), although individual coefficients are statistically insignificant due to severe multicollinearity among banking sector variables. The findings do not support the conventional liquidity–profitability trade-off hypothesis, as no evidence of a linear or non-linear relationship between liquidity and profitability is observed. Regulatory capital emerges as the most influential variable, indicating the importance of capital strength in supporting banking stability. This study contributes to the literature by providing novel empirical evidence from a transition economy, highlighting the limitations of isolating liquidity effects in rapidly expanding banking systems. The results suggest that in reform-oriented financial environments, banking stability is shaped more by structural growth and capital adequacy than by liquidity trade-offs, offering important implications for macroprudential policy design. Full article

The Yellow River Basin is a vital ecological security barrier for China, as well as a region rich in cultural and tourism resources. Tourism has emerged as a core industry underpinning both ecological conservation and sustainable, high-quality regional development within the basin. As the tourism industry transitions toward sustainable and high-quality development, tourism efficiency serves not only as a core indicator for measuring the quality of tourism development but also as a critical basis for assessing regional tourism sustainability. Taking 68 Outstanding Tourism Cities in the Yellow River Basin from 2009 to 2023 as research samples, this study employs the Super-Slack-Based Measure (Super-SBM) model to measure tourism efficiency. It depicts the spatiotemporal evolution through trend surface analysis, spatial autocorrelation analysis, hotspot analysis, and standard deviation ellipses and utilizes the Geographically and Temporally Weighted Regression (GTWR) model to identify the determinants of spatiotemporal heterogeneity. Tourism efficiency in the basin’s Outstanding Tourism Cities is generally low but has a variably increasing trend with a pronounced spatial gradient of upstream > midstream > downstream. The efficiency of tourism is highly interdependent spatially and highly clustered, as the regional high and low values are mostly situated up- and downstream, respectively. In general, the center of tourism efficiency has changed to the southwest instead of the northeast. The infrastructure, industrial structure and human capital characterize the efficiency of tourism, but the openness to the external world is the most significant factor, and the impact of these factors also varies sharply in terms of their strength. This study systematically reveals the spatiotemporal evolution patterns and heterogeneous driving mechanisms of tourism efficiency in Outstanding Tourism Cities within the Yellow River Basin. It not only expands the research perspectives and empirical analytical frameworks for sustainable tourism development at the basin scale but also provides a precise decision-making basis for the coordinated advancement of sustainable and high-quality tourism development in the region. Full article

Rapid urban expansion has increasingly reshaped the carbon budgets of urban agglomerations through land use change. However, the role of functional heterogeneity within construction land remains insufficiently considered when examining the spatial differentiation of construction expansion-related carbon increases. Using the Pearl River Delta Urban Agglomeration in China as the study area, this research traced the spatiotemporal changes in land use carbon budgets between 2000 and 2024, evaluated how the expansion of construction land contributed to the growth of regional carbon emissions, and further examined the spatial associations between six construction land functional categories and expansion-related carbon increases over the period of 2010–2024. The results show the following. (1) During 2000–2024, approximately 15,200 km² of land experienced use transitions, representing 28.2% of the regional land area. These transitions generated an accumulated increase of 15.46 million t in net carbon emissions, largely driven by the conversion of cultivated land, forest land, and other non-construction land into construction land. (2) Approximately 96.2% of the carbon increase from land use transitions was attributed to the conversion of other land use types into construction land, confirming construction land expansion as the dominant pathway of regional carbon increases. (3) From 2010 to 2024, expansion-related carbon increases showed significant spatial clustering, with high-value clusters mainly concentrated in the Guangzhou–Foshan–Dongguan–Shenzhen corridor and low-value clusters in peripheral areas. (4) Functional space variables were further associated with the spatial differentiation of carbon increases. Industrial and transportation spaces showed the strongest spatial associations, and their interaction showed the strongest explanatory effect, while GWR results revealed stronger local associations in peripheral areas and weaker associations in core areas. These findings provide empirical support for carbon-focused land use governance, functional optimization of construction land, and differentiated territorial spatial regulation in rapidly urbanizing urban agglomerations. Full article

Urban intersection design generally assumes that drivers follow idealised turning paths defined by circular arcs and, in some cases, transition curves. In practice, however, observed left-turn trajectories often depart from these theoretical paths. This study proposes a curvature-based framework for quantifying such deviations at the movement level by directly comparing observed vehicle paths with theoretical design arcs derived from intersection geometry. Naturalistic traffic data were collected at five urban intersections in Thessaloniki, Greece, using elevated video cameras. Left-turn passenger-vehicle trajectories were extracted, georeferenced, and compared with corresponding theoretical paths. For each trajectory, a best-fit circular arc was estimated, and the deviation between observed and theoretical path geometry was quantified through radius- and curvature-based percentage indicators. These indicators were then aggregated at the intersection and movement level using medians, deciles and the relative shares of flatter-than-theoretical and tighter-than-theoretical trajectories. The results show that deviations from theoretical geometry are strongly movement-specific and that the strongest flattening and tightening patterns were statistically supported by movement-level Wilcoxon signed-rank tests. In some cases, drivers systematically opened the turn relative to the design path, with median curvature deviations reaching about −14% and flatter-than-theoretical shares as high as 94%. In other cases, the opposite pattern was observed, with median curvature deviations exceeding +37% and tighter-than-theoretical shares reaching 100%. Other movements remained close to the theoretical path or displayed substantial internal heterogeneity. Overall, the proposed framework offers a practical and interpretable way to screen left-turn movements for systematic departure from design intent. This is important because it allows the analysis to move from individual path overlays to a movement-level geometric reading that can support consistency checks, intersection review and future integration with speed- and conflict-based safety analyses. These results should nonetheless be regarded as exploratory and descriptive: neither the circle-fitting residuals nor the coordinate-level geometric accuracy of the extracted trajectories were formally validated in the present study, and the reported RDP/CDP values are, therefore, not intended for use as precision-survey quantities or as a stand-alone design basis. Full article

Emerging adulthood may be particularly challenging for young people who have graduated from educational frameworks for adolescents at risk, many of whom have faced complex social, emotional, or familial hardships, alongside academic challenges such as school dropout, yet the mechanisms linking such adversity to well-being remain insufficiently understood. Drawing on Self-Determination Theory, this study examined whether satisfaction of three basic psychological needs (autonomy, competence, and relatedness) mediates the association between negative life events and mental well-being among emerging adults from at-risk educational backgrounds. Participants were 256 Israeli emerging adults (aged 18–25; 48.8% female) who had completed their secondary education in frameworks for youth at risk. Mental well-being was assessed across emotional, social, and psychological dimensions, alongside measures of negative life events and need satisfaction. Parallel mediation analyses indicated that exposure to a greater number of negative life events was associated with lower psychological need satisfaction. Direct effects of negative life events on well-being became nonsignificant once need satisfaction was included, whereas total indirect effects remained significant across outcomes. Competence emerged as the most consistent mediator, while autonomy was specific to emotional well-being and relatedness to social and psychological well-being. These findings identify need satisfaction as a key mechanism linking adversity to well-being and highlight the importance of maintaining supportive relational and developmental structures for young adults transitioning out of at-risk educational frameworks. Full article

Traditional villages and intangible cultural heritage (ICH) are interrelated components of rural heritage landscapes, linking material spatial carriers with living cultural practices. Yet their spatial matching, mismatch-formation mechanisms, and translation into collaborative conservation zoning remain insufficiently understood. Taking Anhui Province, China, a north–south transitional region, this study examines 836 traditional villages and 685 ICH items at or above the provincial level. We develop a stepwise spatial diagnostic framework that connects clustering identification, positional and quantity–structure mismatch diagnosis, corridor and multi-factor association interpretation, and strategy-oriented conservation zoning. The results show that traditional villages form a strong southern Anhui core (83.01%), whereas the officially attributed locations of listed ICH items are more widely distributed across southern, central, and northern Anhui (43.21%, 26.42%, and 30.36%). The provincial centroid mismatch distance reaches 160.15 km, and prefecture-level cities are classified into ICH-advantaged, traditional-village-advantaged, and relatively matched types. Huangshan further demonstrates that positional proximity does not necessarily imply quantity-structure matching. Mechanism analysis suggests two scale-dependent association patterns: an environmental preservation pattern for traditional villages and a social-transmission and institutional-attribution pattern for listed ICH items. Based on this provincial-scale diagnosis, the study delineates key, secondary, and general conservation zones as strategy-oriented diagnostic zones and proposes differentiated collaborative conservation strategy orientations. Full article

The global proliferation of microplastics demands sustainable remediation alternatives to energy-intensive conventional disposal methods, shifting research focus toward polymer-degrading microbial communities within the “plastisphere.” The primary objectives of this study are twofold: first, to systematically decode the sequential biophysical mechanisms underlying microplastic colonization and enzymatic degradation; and second, to establish an empirically validated, scalable treatment framework that employs both a novel biological isolate and a hybrid engineering architecture. Experimentally, we investigate the multi-stage colonization process and demonstrate that “Phase Zero” conditioning films modulate the surface zeta potential (ζ) to anchor pioneer r-strategists. To evaluate degradative efficacy under accelerated conditions without abiotic pretreatment, the newly isolated carp gut strain Hafnia paralvei UUNT_MP29 was exposed to pristine low-density polyethylene (LDPE) and polystyrene (PS). Over a 16-day biotic incubation period, structural and chemical alterations were distinctly polymer-specific: bacterial action on the polyolefin LDPE yielded a Carbonyl Index of 0.4594 and a 10.95 °C reduction in thermal stability (T_max), whereas the aromatic PS matrix exhibited a Carbonyl Index of 0.3235 alongside a 10.80 °C decrease in T_max, with both substrates showing intense surface pitting. To standardize these complex tracking metrics across the field, a universal four-pillar Biodegradability Index (BI) was formulated. Based on these findings, we recommend an immediate transition from passive waste containment to a closed-loop engineering approach. Specifically, we propose integrating an artificial intelligence (AI)-managed hybrid bioprocess configuration that couples Advanced Oxidation Processes (AOPs) with Membrane Bioreactors (MBRs). This dual-stage configuration is recommended to overcome polyolefin crystallinity, accelerate stoichiometric mineralization, and actively mitigate additive-mediated toxicity at the industrial scale, providing a vital blueprint for the circular bio-economy. Full article

This exploratory pilot study analyzes the organizational and environmental determinants associated with stated intention to adopt biogas-solar microgrids within a circular bioeconomy framework. A quantitative, applied, cross-sectional design was used with 71 valid individual responses from participants linked to productive, agro-industrial, livestock, energy, and waste management organizations or projects, selected through nonprobabilistic convenience sampling. The analysis does not measure actual investment, implementation, or use; therefore, the results refer only to declared adoption intention and should not be generalized beyond the sample. The questionnaire measured perceived benefits, barriers, institutional conditions, financial feasibility, environmental value, organizational capabilities, and adoption intention. Content validity was supported by expert judgment, and psychometric reliability was assessed using Cronbach’s alpha and McDonald’s omega. Predictive modeling compared supervised classification, regression, and unsupervised segmentation techniques using train-test validation, cross-validation, and interpretability analyses. ExtraTrees achieved the best exploratory classification performance, with a test ROC-AUC of 0.889, while RandomForestRegressor showed the best regression performance; however, these values should be interpreted as sample-specific evidence rather than as a validated predictive tool. Organizational capabilities and environmental criteria emerged as the most influential predictors, and K-Means suggested two tentative readiness profiles with weak separation. The findings suggest that stated adoption intention is associated with a systemic configuration of organizational maturity, environmental legitimacy, financial feasibility, and institutional support, providing preliminary evidence for future larger sample validation and for decision-support discussions in sustainable energy transitions. Full article