Search Results (7,564)

Expansive mudstone tunnels often suffer long-term convergence and support damage because excavation-induced unloading is coupled with water-induced swelling. This study proposes a particle flow modeling framework for expansive mudstone tunnels by linking tunnel-wall displacement, swelling pressure, and the equivalent particle radius expansion coefficient. Constant-volume swelling pressure tests were first conducted to determine the representative swelling pressure of the mudstone. An independent confined particle model was then established to calibrate the relationship between macroscopic swelling pressure and microscopic particle expansion. The results show that a stable swelling pressure of 300 kPa corresponds to an equivalent particle radius expansion coefficient of 3.11%. Incorporating this calibrated swelling mechanism into the tunnel model indicates that swelling intensifies excavation-induced damage, increasing the final crack number from 1566 to 1852 and enlarging the equivalent damage-zone diameter from 21.6 m to 22.8 m. Under the original support scheme, the damage depth reaches 5.45 m, and the final crown settlement reaches 177.6 mm. After reinforcement, these values decrease to 3.40 m and 81.1 mm, respectively. Field monitoring confirms the predicted deformation-control trend. The proposed framework provides a practical approach for simulating swelling-induced damage evolution and optimizing support design in expansive mudstone tunnels. Full article

Background/Objective: Web-delivered psychoeducational tools offer scalable options for managing elevated stress. Passive psychoeducation that delivers self-guided content without active psychotherapy techniques or homework may be particularly accessible at low costs. The present study examined the acceptability and preliminary effectiveness of a seven-week app-based passive psychoeducational stress-management program in an unselected cohort of nursing students. Methods: In this parallel-group randomized controlled trial (preregistered at the German Clinical Trials Register), 154 nursing students were randomized to either a psychoeducation group (n = 77) or a waitlist control (n = 77). Outcomes were assessed at baseline and post-intervention using the Depression Anxiety Stress Scales–21 (DASS-21). A total of 56 completed the post-test assessment. The intervention group received a new psychoeducational module each week for seven weeks. After each module, participants rated satisfaction and reported adherence and application of content in daily life. The control group received no intervention. Results: Compared with the waitlist control, the intervention group showed a statistically significant reduction in perceived stress from pre- to post-test. Depressive symptoms demonstrated a trend toward improvement, whereas anxiety scores did not change significantly. Acceptability ratings were high and participants reported moderate uptake of strategies and perceived relief. Conclusions: A brief, app-based passive psychoeducational program appears feasible and acceptable for nursing students and can reduce perceived stress. However, the findings of the current study should be interpreted cautiously given the high attrition rate and the absence of long-term follow-up. Further studies with larger samples and replication under conditions of better retention are warranted. Full article

Traditional grid-forming converter (GFC) control faces fundamental challenges in maintaining DC bus stability during rapid power transients, primarily due to the limited dynamic response capability of source-side energy storage devices. To address this, this paper proposes a hybrid control strategy integrating long short-term memory (LSTM) networks with a joint GFC and storage converter (SC) control scheme. The LSTM detects short-term voltage trends from historical DC bus data to generate a feedforward compensation signal, while the joint SC-GFC control dynamically incorporates the GFC’s inertial power demand into the SC’s power reference. Hardware-in-the-loop experiments show that, compared to traditional independent control under the same step transient conditions, the proposed method can reduce power overshoot by approximately 79.2%. The LSTM-enhanced joint control maintains stable power flow and significantly suppresses low-frequency oscillations, validating the necessity of data-driven trend prediction for achieving superior inertial support in practical constrained environments. This work provides a communication-free, practical solution for enhancing GFC performance. Full article

Ornamental palm pruning residues represent a locally abundant, underutilized lignocellulosic waste stream with potential as a waste-valorized epoxy reinforcement. This study investigates the flexural behavior of particulate epoxy composites reinforced with Washingtonia robusta leaf stalk residue, evaluating the influence of reinforcement granulometry on mechanical and microstructural response. Four specimen families were fabricated from a Bisphenol A/F epoxy resin cured with a cycloaliphatic amine hardener: neat resin (RS, reference) and composites reinforced with fine (RF), coarse (RG) and mixed-fraction (RM) particles at 20 vol.% loading. Flexural properties were assessed by three-point bending and fracture surfaces were characterized by SEM. The neat resin exhibited a non-monotonic, viscoelastic-dominated response with no fracture within the extended deformation range tested, whereas all reinforced systems fractured within a substantially narrower window (~8–14.5 mm). RF showed the highest observed flexural modulus (≈15.8 GPa), followed by RM (≈15.4 GPa) and RG (≈14.2 GPa). These differences were not statistically significant (one-way ANOVA, p > 0.05). Damage tolerance followed a similar descriptive trend: RG failed earliest, linked to large interfacial pull-out cavities; RF delayed fracture through crack deflection; and RM showed the most favorable overall balance, combining a modulus comparable to RF with superior crack path tortuosity. These results indicate the potential of Washingtonia robusta, particularly in mixed-granulometry form, as a candidate reinforcement for semi-structural epoxy biocomposites, pending further characterization of properties such as tensile strength, impact resistance, moisture absorption, and long-term durability. Full article

Araucaria angustifolia (Bertol.) Kuntze, a critically endangered tree species, plays an irreplaceable ecological role in its native habitats. Under global climate change, identifying the drivers governing its geographic distribution and assessing climate-related threats can provide scientific guidance for the long-term conservation and habitat restoration of this species. In this study, a total of 287 valid occurrence records from 27 countries were compiled. Combined with 14 screened environmental variables, an optimized Maximum Entropy (MaxEnt) model was used to predict the potential suitable habitats of A. angustifolia under historical climate conditions (1970–2000), as well as under low-emission (SSP126) and high-emission (SSP585) scenarios for the future periods of 2050, 2070, and 2090. Under historical climatic conditions, the average training AUC value from 10 replicate model runs was 0.979, indicating excellent and reliable model performance. Globally, the species has 1.91 × 10⁶ km² of moderately suitable habitat and 0.95 × 10⁶ km² of highly suitable habitat, with a total suitable habitat area of 2.86 × 10⁶ km², accounting for only 1.92% of the global terrestrial area. Mean annual temperature (bio1), mean temperature of the coldest quarter (bio11), and annual temperature range (bio7) are the dominant environmental variables shaping the distribution of A. angustifolia, followed by annual precipitation (bio12). Under future climate scenarios, the overall suitable habitats of A. angustifolia exhibit a slight contracting trend, whereas their spatial distribution patterns remain relatively stable. Full article

To address the critical challenge of extracting short-period surface deformation signals induced by extreme floods from InSAR time series, this study focuses on the catastrophic flood that struck the Haihe River Basin in July 2023 (hereinafter referred to as the “23·7” flood, with a total duration of approximately 65 days) and proposes a novel method for transient deformation signal extraction. Using Sentinel-1A satellite data and the PS-InSAR technique, we constructed a multivariate composite fitting function comprising a linear trend term, annual and semi-annual seasonal terms, a step term, and a logarithmic decay term. Through nonlinear least-squares fitting, this approach achieves effective separation of long-term tectonic deformation, seasonal fluctuations, high-frequency noise, and transient flood-related signals. The results show that the W-shaped floodplain east of Xiong’an New Area does not exhibit the expected subsidence induced by water loading but instead features pronounced surface uplift of up to 30 mm. Multi-physics forward modeling reveals the underlying mechanism: the elastic subsidence caused by surface water loading, calculated via the LoadDef spherical loading theory, amounts to only ~2 mm. In contrast, forward modeling based on the GMS three-dimensional groundwater seepage model and the principle of effective stress indicates that the pore water rebound effect can produce surface uplift of up to ~36 mm. The superposition of these two effects is highly consistent with InSAR observations in terms of magnitude, direction, and spatial distribution, confirming that the flood-induced surface deformation is dominated by the pore water rebound effect driven by rapid groundwater recharge, rather than subsidence from water loading. The proposed framework extends the application potential of geodetic techniques for monitoring short-period extreme hydrological events. Full article

Long-term exploitation of ion-adsorption rare earth deposits has played a vital role in ensuring the supply of strategic mineral resources. However, intensive mining activities have also resulted in severe ecological degradation, including vegetation loss, land degradation, and soil erosion. Although the Remote Sensing Ecological Index has been widely used for ecological environment assessment, it inadequately characterizes land degradation in ion-adsorption rare earth mining areas, while its fixed-weight framework is unable to effectively capture the influence of localized ecological limiting factors. To address these limitations, this study selected a typical ion-adsorption rare earth mining area in southern Jiangxi, China, as the study area. A Desertification Difference Index was incorporated into the conventional RSEI framework to establish a five-dimensional evaluation system consisting of greenness, wetness, dryness, heat, and desertification. Furthermore, a Dynamic Variable-Weight Remote Sensing Ecological Index (DV-RSEI) was developed by integrating variable-weight theory, enabling adaptive adjustment of indicator weights according to local ecological conditions. Using Landsat imagery from 2000, 2005, 2010, 2016, 2020, and 2023, the spatiotemporal evolution and spatial heterogeneity of ecological environmental quality were systematically investigated. The results indicate that: (1) ecological environmental quality exhibited a characteristic evolution process of mining disturbance–ecological degradation–comprehensive restoration–ecological recovery during 2000–2023, with an overall trend dominated by stability and improvement; (2) ecological environmental quality showed significant spatial clustering, with High–High clusters mainly distributed in areas with favorable ecological conditions, whereas Low–Low clusters were concentrated in regions strongly affected by mining activities; and (3) compared with the conventional RSEI, the DV-RSEI better characterized mining-related ecological degradation patterns and the spatial heterogeneity of ecological environmental quality. The proposed approach provides a scientific basis for dynamic ecological monitoring, evaluation of ecological restoration effectiveness, and the construction of green mines in ion-adsorption rare earth mining areas. Full article

Quantifying the impacts of climate change and extreme climatic events on crop yields is essential for safeguarding global food security. The rapid growth of data availability and advances in computational capacity have established machine learning (ML) as a critical tool for unraveling the complex, nonlinear relationships between climatic factors and agricultural productivity. This systematic review synthesizes evidence from 137 peer-reviewed studies published between 2015 and 2025 that applied ML models to assess the effects of both long-term climate trends and discrete extreme events on crop yields worldwide. Bibliometric and thematic analyses reveal a rapidly evolving field, with over 85% of studies published since 2020, and a strong concentration on staple cereals—wheat, maize, and rice—in major agricultural regions including China, the United States, and India. Random Forest (RF) was the most commonly used algorithm; ensemble and deep-learning models achieved high predictive accuracy within well-resourced study contexts. Temperature and precipitation extremes emerged as the most frequently examined stressors, with distinct methodological patterns: studies focusing on climate change trends predominantly employed RF and LSTM models, whereas those investigating extreme events increasingly adopted hybrid approaches that integrate ML with process-based crop models. This review highlights the transformative potential of ML while identifying persistent challenges, such as geographical imbalances in research coverage, the need for enhanced interpretability in extreme event attribution, and the critical importance of modeling compound extremes. Future research should prioritize the development of explainable, causally informed, and transferable ML frameworks to support equitable climate adaptation strategies in global agriculture. Full article

Background/Objectives: Hematological malignancies (HMs) are an important component of the cancer burden in adolescents and young adults (AYA, 15–39 years), requiring long-term specialized care. In Poland, recent healthcare reforms under the National Oncology Network (KSO) have not formally included haemato-oncology or AYA-specific needs. Methods: A population-based study was conducted using data from the Polish National Cancer Registry. AYAs diagnosed with HM between 2000 and 2022 were included. Descriptive analyses and projections were based on cases diagnosed between 2000 and 2022, whereas age-specific incidence trend analyses were restricted to the 2015–2022 period. Tumours were classified according to the HAEMCARE framework. Age-standardized incidence rates (ASIRs), annual percentage changes (APCs), and short-term projections through 2028 were estimated using generalized linear models. Additionally, data from the National Health Fund (NFZ) were analyzed to assess the geographical distribution of reimbursed drug programmes dedicated to selected HMs. Results: A total of approximately 23,000 AYA patients diagnosed with HMs were identified. Hodgkin lymphomas (HL) were the predominant tumour type across all age groups, while lymphoblastic leukemia/lymphoma was most common among younger AYAs and diffuse large B-cell lymphoma (DLBCL) increased in relative importance with age. Between 2015 and 2022, ASIRs remained stable only in two age groups (20–24 and 25–29), whereas statistically significant increases were observed among individuals aged 15–19, 30–34 and 35–39 years. Despite largely stable incidence patterns, projections indicated a growing absolute number of cases for DLBCL and follicular lymphomas. Analysis of NFZ data revealed substantial regional variation in the availability of reimbursed drug programmes, with up to six-fold differences in facility density between voivodships. Conclusions: HM epidemiology among AYAs in Poland is characterized by increasing incidence in selected lymphoma subtypes alongside declining mortality. Incorporating haemato-oncology and AYA-specific needs into national cancer planning frameworks should therefore be considered essential for future healthcare system preparedness. Full article

Climate risk has become a defining challenge for businesses, influencing strategic decision-making, organisational resilience, and long-term performance. Despite the rapid growth of research in this area, the intellectual development and thematic evolution of climate-related corporate studies remain fragmented. This study provides a comprehensive synthesis of the literature through a bibliometric analysis and systematic review of 643 Scopus-indexed, peer-reviewed articles published between 1993 and 2025, with a systematic thematic synthesis of 23 empirical studies. Using Biblioshiny and VOSviewer, science-mapping techniques, including co-citation analysis and bibliographic coupling, were employed to examine publication trends, intellectual foundations, and major research themes. The findings indicate a shift from environmental measurement and compliance toward climate-risk management, carbon disclosure, and sustainable finance. Financial outcomes are heterogeneous, and context-dependent carbon exposure is generally associated with valuation penalties and downside risk, while the relevance of disclosure and climate strategies depends on credibility, substantive implementation, and organisational and institutional conditions. The integrated review shows that the financial implications of climate-related corporate actions are contingent upon climate-risk exposure, disclosure credibility, organisational capabilities, and institutional context. It further explains the coexistence of mixed empirical findings and identifies priorities for future research and policy. The findings offer valuable implications for researchers, corporate managers, investors, and policymakers seeking to strengthen sustainable business practices under an evolving climate risk landscape. Full article

This study proposes an innovative framework that combines hydroclimatic and agro-environmental predictors, including nitrate concentration and NDVI, with climatic factors such as Rainfall, temperature, and evapotranspiration to forecast piezometric level variations in the Saïss Basin, Morocco. Eight Machine Learning (ML) models were benchmarked, and feature importance was assessed using Shapley Additive exPlanations (SHAP) to ensure model transparency and interpretability. In parallel, the PELT algorithm was applied to detect structural change points, while Sen’s slope estimator and the Mann–Kendall test were used to quantify long-term trends. The Extra Trees (ET) model achieved the best performance (R² = 0.92), with Rainfall emerging as the most influential predictor, followed by nitrate concentration, confirming the added value of hydrochemical indicators for groundwater forecasting. Change-point analysis revealed significant declines during the 1980s and 1990s, followed by lower-amplitude fluctuations since the late 2000s. Projections toward 2050 suggest partial stabilization in the central part of the basin under favorable recharge conditions, whereas persistent declines are expected to continue in peripheral areas subjected to sustained groundwater abstraction pressure. These findings provide a robust and transferable decision-support tool for the sustainable management of groundwater resources in semi-arid agricultural area. Full article

Objectives: Initial caries lesions (ICLs) are the earliest manifestation of dental caries, characterized by subsurface porosity that affects enamel’s optical properties while maintaining its surface integrity. Resin infiltration is a minimally invasive approach to managing these lesions by penetrating and sealing pores with low-viscosity resin, potentially modifying their visual appearance. In order to provide a quantifiable, objective assessment of this optical behavior, this study aimed to evaluate the modulation of color coordinates and VITA Classical shade transitions within the initial lesions immediately following infiltration with Icon Smooth Surface (DMG, Hamburg, Germany). Materials and Methods: Forty-nine extracted human premolars with naturally occurring proximal ICLs (subsurface demineralization) were selected. Lesions were assessed for fluorescence level using 655 nm laser fluorescence (DIAGNOdent pen). Reflectance spectrophotometry (SpectroShade Micro) was employed to record color coordinates in the CIELab and CIELCh spaces, alongside VITA Classical shades, before and after resin infiltration. Results: The infiltration procedure resulted in a statistically significant increase in b* (yellowness) and subsequent C* (chroma) parameters (p < 0.05). VITA Classical shade guide analysis showed an insignificant shift in color distribution according to value (p > 0.05). Conclusions: The present exploratory study provides quantitative insights into the immediate color-modifying effects of a resin infiltration procedure on natural initial proximal caries lesions, complementing the existing literature with objective CIELab/CIELCh and VITA Classical measurements. The p-values should be interpreted as descriptive indicators of potential trends rather than definitive statistical proof. Further research with larger cohorts and long-term follow-up is needed to validate the durability and clinical relevance of these esthetic outcomes. Full article

Background: The development of osteoarthritis (OA), a whole-joint disorder that is increasingly recognized, depends on subchondral trabecular bone. Variations in the viscoelastic characteristics of trabecular bone have been proposed to affect load distribution and potentially lead to joint degradation. The viscoelastic response of human trabecular bone in both healthy and osteoarthritic situations was investigated using constitutive modeling and stress-relaxation testing. Fifteen tibial trabecular bone specimens were evaluated using Standard Linear Solid (SLS) models and two-branch generalized Maxwell models following uniaxial stress-relaxation testing. Mechanical, energy, and relaxation-related traits were retrieved and compared between groups. Results: Healthy bone tended to relax stress more slowly and to bear mechanical loads over time to a slightly greater extent than osteoarthritic bone, which tended to relax stress more quickly and had poorer mechanical endurance; these differences were not statistically significant. The Generalized Maxwell model suited the experimental data better than the SLS model (R² > 0.98), capturing both short- and long-term relaxation mechanisms. Sensitivity analysis revealed higher parameter variability in OA specimens, suggesting possible differences in mechanical heterogeneity and load-dissipation behavior that require further investigation. Conclusions: Although the observed differences were not statistically significant in this exploratory study, the results suggest potential trends toward altered viscoelastic behavior between healthy and osteoarthritic trabecular bone. Future studies with larger cohorts are needed to further investigate osteoarthritis-related biomechanical alterations. Multi-branch viscoelastic modeling may provide sensitive mechanical descriptors for characterizing the relaxation behavior of subchondral bone. Full article

We examine the impact of board gender diversity on the financial and operating performance of the banking sector in Egypt over the period 2016–2024. We document a clear upward trend in female board representation, particularly following regulatory reforms introduced in 2019 and beyond. Our results show that board gender diversity is positively associated with bank performance, including profitability, efficiency, asset quality, and capital adequacy. However, this relationship becomes economically and statistically meaningful only after a critical mass of female directors is reached. Within the limited range of female board representation observed in the sample, we do not observe a declining or inverted U-shaped pattern. We further show that the positive role of gender-diverse boards is amplified under stronger governance structures—particularly where board independence is high, state ownership is limited, and CEO–chairman roles are separated. These findings provide support for regulatory initiatives aimed at increasing female representation on corporate boards, including Egypt’s Vision 2030 target of 30% female leadership representation. At the same time, the results highlight that the effectiveness of such policies depends on institutional readiness, governance quality, and meaningful participation beyond symbolic compliance. These results suggest that compliance-driven board gender diversity mandates can contribute to sustainable governance, supporting SDG 5 objectives and the long-term institutional resilience of the banking sector in emerging economies. Full article

Freshwater scarcity can weaken water governance when hydrological pressure interacts with intensive agricultural demand, regulatory weakness, and political conflict. This research evaluates whether Irrigation District 005 (IR 005) in Chihuahua, northern Mexico, demonstrates local water-governance fragility across three domains: public security, the rule of law, and the ability to sustain water access and food production. A mixed-methods approach integrates legal and human rights documentation, institutional records, published studies, and a structured media review with hydrological, agricultural, climatic, and reservoir data. Water balances were analysed for 1998–2023, precipitation trends for 1980–2020, and crop water requirements were estimated using the Food and Agriculture Organization’s Irrigation and Drainage Paper No. 56 (FAO-56) Penman–Monteith framework, the crop coefficient (Kc), the water-stress coefficient (Ks), the United States Soil Conservation Service (SCS) Curve Number method, and application-efficiency assumptions. The 2020 water conflict resulted in fatalities, injuries, arrests, and documented human rights violations. Rule-of-law capacity was further diminished by unauthorised withdrawals, cultivation beyond authorised irrigation plans, and limited enforcement. The annual water balance shifted to persistent deficits after 2016, reaching an estimated deficit of 2268 cubic hectometres (hm³) in 2020. Annual precipitation did not exhibit a statistically significant monotonic decline during 1980–2020 (Mann–Kendall Z = −0.79, τ = −0.0878, p = 0.4251; Sen’s slope = −1.1628 mm yr⁻¹; Mann–Whitney p = 0.5313), indicating that recent stress is more closely linked to production scale, crop mix, governance conditions, and irrigation efficiency than to a long-term reduction in rainfall. Sensitivity analysis revealed that ±15% changes in Kc and Ks altered gross water requirements by approximately ±16–17%, while equivalent changes in effective precipitation produced changes of only 1–3%. These results demonstrate heightened water-governance fragility resulting from mutually reinforcing hydrological, institutional, and conflict-related pressures. Future research should refine locally calibrated water-demand parameters and develop reproducible monitoring systems that combine hydrological, institutional, satellite, and participatory data to support anticipatory, transparent, and rights-based water governance. Full article