Search Results (3,599)

The purpose of this study is to explore how Zimbabwean firms use Environmental Management Accounting (EMA) and climate risk disclosure amid climate policy uncertainty and how managers perceive these practices as relevant to organisational resilience and long-term sustainability within a volatile institutional and macroeconomic context. The study was couched in the interpretivist research philosophy and adopted the inductive research approach. A case study research design, which aligns with a qualitative research design, was chosen for the study. The study employed in-depth interviews with management accountants, finance executives, and industry leaders across firms in Harare. The study adopted the cross-sectional time horizon and analysed data using thematic analysis to develop insights into the role of EMA and climate risk disclosure in times of policy uncertainty. The findings suggest that participants perceived climate policy uncertainty as influencing organisational efforts to reconfigure management accounting practices through greater environmental performance monitoring, adaptive budgeting, and scenario-based planning. The findings of this study suggest that organisational actors interpreted climate policy uncertainty as a condition requiring greater flexibility in budgeting, environmental monitoring, and strategic planning. Participants in this study associated EMA with improved environmental cost visibility and more adaptive approaches to investment appraisal and risk management under uncertain policy conditions. Similarly, participants perceived climate risk disclosure as increasingly crucial for strengthening organisational legitimacy, stakeholder confidence, and institutional credibility. While respondents linked sustainability-oriented accounting adaptation to broader organisational resilience and long-term sustainable growth aspirations, these relationships were understood through managerial perceptions and organisational experiences rather than as directly measurable macroeconomic outcomes. The study contributes to the sustainability accounting literature by providing qualitative, context-sensitive insights into how managers in an emerging economy interpret climate policy uncertainty and adapt EMA and climate risk disclosure practices within volatile institutional conditions. The study further contributes by integrating sensemaking theory and institutional theory to explain how organisational interpretations of uncertainty shape sustainability-oriented accounting adaptation and perceptions of organisational resilience. It is therefore recommended that the regulatory institutional pillar be strengthened to reduce uncertainty and enhance the EMA’s strategic adaptation. Full article

The development of digital learning technologies has introduced innovative tools to enhance science and chemistry education, including PhET simulations. This study aims to evaluate the effectiveness of PhET simulations on students’ learning outcomes through a systematic literature review following the PRISMA 2020 guidelines. A systematic search of Scopus and Crossref databases was conducted (last search: January 2026) using predefined keywords. Eligible studies were empirical research published between 2020 and 2026 that investigated PhET simulations in science-related education and reported learning outcomes, while non-empirical studies and non-Scopus-indexed articles were excluded. Risk of bias was assessed using an adapted Joanna Briggs Institute critical appraisal tool. Due to heterogeneity in study designs and outcome measures, the results were synthesized using a narrative approach. A total of 14 studies across elementary to higher education levels were included. The findings indicate that PhET simulations consistently improve learning outcomes, particularly academic achievement and conceptual understanding, with effects generally favoring simulation-based instruction over traditional methods. However, higher-order skills and affective outcomes such as motivation and attitude remain less frequently investigated. The evidence is limited by variability in study designs, incomplete reporting of non-cognitive outcomes, and the absence of quantitative synthesis. Overall, PhET simulations demonstrate strong potential as an effective interactive learning medium, although their impact depends on instructional design, teacher facilitation, and technological accessibility. Full article

This paper proposes an integrated attitude control framework for flexible spacecraft subject to external disturbances, rigid–flexible dynamic coupling, and actuator faults. The control framework combines the Twin Delayed Deep Deterministic Policy Gradient (TD3) reinforcement learning algorithm with an adaptive fault-tolerant (AFT) compensator. First, a rigid–flexible coupling dynamic model is formulated using Modified Rodrigues Parameters. Second, an observer-based TD3 attitude controller is designed, where a hierarchical reward function incorporating the observer-estimated flexible modal displacement $\widehat{\mathit{\eta }}$ is constructed to train the agent for simultaneous attitude convergence and vibration suppression. Third, a composite fault-tolerant control structure is developed by integrating the trained TD3 policy with an adaptive sliding mode compensator that handles both partial loss-of-effectiveness faults and time-varying additive faults. The proposed framework is evaluated under a progressive five-scenario uncertainty evaluation framework encompassing measurement noise, parameter mismatch, external disturbances, and actuator faults. Simulation results demonstrate that (i) the $\widehat{\mathit{\eta }}$-augmented reward enables substantial improvements in vibration suppression over the baseline reward, achieving a better balance between pointing accuracy and vibration attenuation; (ii) under the most demanding fault scenario, the AFT compensator proves essential for precise convergence, and the composite TD3+AFT architecture achieves the best overall performance among the four compared control schemes. Full article

Aiming at the problem that complex underwater environments induce outliers in Doppler Velocity Log (DVL) measurements, which degrade the navigation accuracy of the Strapdown Inertial Navigation System (SINS)/DVL integrated system, this paper proposes a soft-gating Gaussian–Student’s t mixture robust Kalman filter (MRKF). Firstly, the measurement noise is modeled as a mixture of Gaussian and Student’s t distributions to adapt to normal stationary noise and abrupt outliers, respectively. Secondly, a logistic soft-gating weight is constructed based on the innovation Mahalanobis distance to adaptively balance the output contributions of the standard Kalman Filter (KF) and the variational Bayesian Student’s t filter. Finally, moment matching is adopted to realize the weighted fusion of two-branch posterior distributions, and an equivalent Gaussian posterior estimation is obtained. Simulation results under the considered SINS/DVL integrated navigation scenarios show that the proposed MRKF maintains estimation accuracy close to the standard KF under nominal Gaussian measurement noise. In the designed DVL outlier-injection scenario, the proposed MRKF achieves a position RMSE of $53.39\mathrm{m}$, compared with $878.75\mathrm{m}$, $58.84\mathrm{m}$, and $56.49\mathrm{m}$ for the nominal KF, Huber KF (HKF), and Student’s-t variational Bayesian KF (STVBKF), respectively. These results indicate that the proposed MRKF can improve robustness against DVL outliers while maintaining competitive estimation accuracy under the simulated conditions. Full article

Introduction/Objectives: Patient-centered communication is essential in oncology care, where healthcare professionals often manage emotionally demanding conversations, uncertainty, complex decisions, and patient involvement in care. However, the relationship between communication knowledge, empathic listening, and practical communication skills remains insufficiently examined. This study aimed to examine the associations between communication knowledge, empathic listening, and interpersonal communication skills among healthcare professionals involved in oncology care. Methods: A cross-sectional study was conducted in Croatia from May to November 2025 on a convenience sample of 138 healthcare professionals involved in oncology care. Communication knowledge was assessed using a study-specific questionnaire, empathic listening using an adapted Active Empathic Listening Scale, and interpersonal communication skills using an adapted Interpersonal Communication Skills Inventory. Because the instruments were adapted to the oncology care context, their dimensions were examined using exploratory factor analysis and interpreted as sample-specific exploratory constructs. Descriptive statistics, correlation analyses, and multiple linear regression analyses were performed. Results: Clear message delivery and assertiveness had the highest self-reported score, whereas emotional interaction management had the lowest. Communication knowledge was not an independent predictor of communication skills dimensions. Processing and responding positively predicted clear message delivery and assertiveness (β = 0.361; p = 0.001; R² = 13.4%), while noticing emotional and nonverbal cues negatively predicted emotional interaction management (β = −0.234; p = 0.032; R² = 7.6%). The explained variance of the models was low. Conclusions: The findings suggest limited but potentially relevant associations between selected dimensions of empathic listening and self-reported communication skills in oncology care. Communication knowledge, measured using a study-specific exploratory instrument, was not independently associated with communication skills. Because of the exploratory design, self-report measures, adapted instruments, and convenience sampling, the results should be interpreted with caution. Full article

Indian metropolitan cities such as Mumbai grapple with rapid urbanisation, extreme urban density, high built-up areas, loss of green cover, and shrinking open spaces, resulting in increased impermeable surfaces, urban heat island effects, and frequent flooding occurrences. Modern stormwater management has increasingly been characterised by integrated grey-green approaches; however, cities in the Global North benefit from established policies, technical expertise, and financial resources that enable the systematic and large-scale integration of Blue-Green Infrastructure (BGI) through district-wide geospatial assessment frameworks, unlike many cities in the Global South. Despite growing interest in nature-based stormwater solutions, there remains a dearth of geospatial empirical research from India examining the placement, distribution, performance, and functionality of BGI integrated with existing stormwater management systems in cities such as Mumbai. Furthermore, hydrological modelling using tools such as the Storm Water Management Model (SWMM) for the design, planning, and implementation of BGI in Indian cities remains largely unexplored. This study explores the role of BGI strategies in improving urban stormwater management within high-density Indian cities under a 25-year return period extreme rainfall scenario. Using an integrated approach that combines QGIS-based spatial analysis with EPA-SWMM hydrologic-hydraulic modelling, the research examines runoff behaviour, identifies flooding hotspots, and evaluates the effectiveness of Low Impact Development (LID)-based BGI measures such as permeable pavements, infiltration trenches, and green roofs applied at the ward level in Mumbai’s F/North and G/North Wards. Detailed land use classification, spatial mapping, and rainfall simulation corresponding specifically to a 25-year return period rainfall event was used to assess pre- and post-intervention conditions. The findings indicate that the applied BGI measures led to a 12.6% reduction in peak runoff (137.6 m³/s to 120.2 m³/s) and a 5.5% decrease in total runoff volume (783,510 m³ to 740,410 m³). More importantly, the peak flooding flow rate decreased by 45% (94.1 m³/s to 51.7 m³/s), demonstrating that BGI measures can efficiently reduce peak flooding flows by extending runoff hydrographs during extreme rainfall events. These findings are specifically applicable to the simulated 25-year return period extreme rainfall scenario and may vary under different rainfall intensities or return periods. Less extreme events could potentially experience even greater relative reductions or prevent flooding altogether, while also easing downstream hydraulic loads. Overall, strategically placed BGI interventions can significantly reduce surface runoff and peak flow, thereby enhancing stormwater resilience within spatially constrained urban environments. This study provides a replicable, data-driven framework for catchment-scale stormwater planning in dense Indian cities under extreme rainfall conditions, offering practical insights into methods, local contextual considerations, and spatial planning strategies for policymakers and urban planners seeking to retrofit and adapt existing infrastructure under increasing hydrologic stress and climate variability. Full article

Farmers’ investment decisions can shape their capacity to implement practices consistent with sustainable development objectives. The article identifies the declarative structure of investment decisions on Polish dairy farms based on a survey and diverse theoretical frameworks (resource-based view, institutional approach, real options theory, behavioural theory, and the theory of planned behaviour). The purpose is to identify the determinants of the extent and structure of declared agricultural investments. The authors determined the relationships between declared investments and groups of variables and identified investment axes and interdependencies. Investment decision predictions are founded on logistic regression, an SEM model for relationship structuring, and residual correlation analysis for mapping relationships and evaluating the correlation demasking effect, according to which raw correlations between investment axes may hide underlying residual associations between them. We found that declared farmland investments were associated with milk production volume and appeared to be linked to long-term farm development objectives. The respondents became less keen on investing in livestock production as they aged, whereas older farmers showed a greater propensity to undertake energy-related investments. These results suggest that farmers’ declared investment intentions may be consistent with conditions conducive to achieving sustainable development objectives through their potential association with farm viability, resource-use efficiency, and rural economic development. Our findings may have potential policy relevance by informing the design of public measures aimed at strengthening farms’ adaptive capacity in the context of sustainability transitions. Full article

Neighbourhood-scale sustainable urban mobility assessment requires analytical tools that evaluate walking, cycling, and public transport together rather than as separate modes. Existing studies often rely on single-mode indicators or aggregated urban-scale measures, which limit their ability to reveal micro-scale spatial inequalities and multimodal performance imbalances. This study addresses this gap by developing an integrated Geographic Information Systems (GIS)–Analytic Hierarchy Process (AHP)–correlation–clustering framework for six sample areas in Kayseri, Türkiye. The framework evaluates three main criteria—walkability, bikeability, and public transport accessibility—through ten sub-criteria. In addition, seven land-use and urban design variables are used to examine built environment relationships. A 100 × 100 m grid-based spatial database was created; criteria weights were determined using AHP; mobility scores were examined through correlation analysis; and spatial mobility typologies were identified using K-means clustering. The findings indicate that development density and land-use diversity support walkability. However, similar density patterns do not automatically improve cycling performance or public transport integration. The clustering results reveal persistent modal imbalances, even in areas with medium-to-high overall performance. The study demonstrates that density alone is insufficient for multimodal sustainability and offers an adaptable decision-support framework for context-sensitive neighbourhood planning. Full article

Uniaxial compressive strength (UCS) is a fundamental parameter for rock engineering design and stability assessment, but direct laboratory testing is costly, time-consuming, and often difficult for weak or fractured rocks. To improve predictive accuracy while preserving mechanical interpretability, this study proposes a Gated Empirical-Law LightGBM model (GEL-LightGBM). The framework embeds three representative rock-strength priors, including point-load strength, multi-index strength, and porosity-degradation relationships, as empirical-law experts. A sample-adaptive gating mechanism dynamically assigns its contributions for different rock states, while a controlled residual corrector captures nonlinear deviations between empirical estimates and measured UCS. Using 344 published rock-mechanics samples, porosity, Schmidt rebound hardness, P-wave velocity, and point-load strength index were used as predictors. GEL-LightGBM outperformed LightGBM, XGBoost, random forest, MLP, CNN, SVR, and BPNN, achieving a testing R2 of 0.9790 and an RMSE of 7.5623 MPa. SHAP analysis identified porosity as the dominant factor, contributing 49.0%, followed by rebound hardness (32.2%) and P-wave velocity (17.2%). The strongest interaction occurred between porosity and rebound hardness (2.31 MPa). These findings indicate that GEL-LightGBM provides accurate, stable, and physically interpretable UCS prediction for heterogeneous rock datasets. Full article

The sustainable transformation of idle built environments represents a critical pathway for advancing low-carbon development and achieving carbon neutrality targets. This study examines how idle rural building stocks may contribute to sustainable built environment systems through rural building repurposing and regeneration strategies. It introduces the concept of Green Rural Centers (GRCs), multifunctional facilities formed through the adaptive reuse of idle buildings that integrate low-carbon design, community services, and local economic functions. Within the proposed framework, GRCs are conceptually characterized as facilities that may: (1) achieve 50–70% reductions in operational energy demand through passive and renewable measures, (2) incorporate two or more community-oriented functions (e.g., education, governance, cultural services), and (3) demonstrate embodied carbon savings of ≥40% compared to demolition-and-rebuild scenarios. Grounded in fieldwork from Fujian Province, China, and aligned with national policies, the study evaluates spatial transformation, carbon mitigation, and institutional integration. Using a mixed-methods approach that combines scenario-based carbon-reduction estimation and appraisal, spatial analysis, comparative case studies, and policy evaluation, the findings indicate that retrofitting 30% of approximately 68,000 idle rural schools could achieve approximately 734,400 metric tons of cumulative CO₂ reduction by 2060 under the baseline scenario. Under conservative and ambitious implementation conditions, the estimated cumulative reductions are approximately 408,000 and 1,224,000 metric tons of CO₂, respectively. Sensitivity analysis shows that moderate improvements in retrofit quality or implementation rates significantly amplify emissions reduction outcomes. Beyond environmental performance, the proposed framework may also support community resilience, decentralized service provision, and socio-economic revitalization. This research reframes idle building stock as a strategic asset within sustainable built environment systems, policy-relevant exploratory framework potentially adaptable to comparable rural contexts. This study contributes to the sustainable built environment discourse by demonstrating how underutilized rural building stocks can function as broader low-carbon rural regeneration systems. Full article

Traditional acupoint localization methods rely heavily on manual operation, resulting in high subjectivity and limited accuracy. To improve the precision and stability of acupoint detection, this study integrates machine vision technology with in situ projection to achieve automated recognition and real-time visualization of human acupoints. First, an automatic calibration method based on image processing is proposed for back acupoints. Spinal features are extracted from the blue channel, enhanced using adaptive histogram equalization, and processed through region of interest extraction, minimum-threshold binarization, and morphological operations. Key spinal curve points are then fitted using Bézier functions. Canny edge detection is used to extract the human silhouette, locate the acromion, and derive the pixel scale of the “cun” measurement, enabling coordinate computation for 141 back acupoints. In the deep learning component, an improved YOLOv8-Pose model is developed for acupoint localization. Unlike existing methods that use local attention or the original Object Keypoint Similarity (OKS) loss, we introduce two innovations: a non-local attention module for global dependency modeling, and a novel Efficient Object Keypoint Similarity (EOKS) loss function that incorporates geometric constraints—namely, width, height, and center distance—in addition to Euclidean distance. A non-local attention mechanism is incorporated into the backbone to enhance global feature extraction, and the EOKS loss function is designed to improve spatiogeometric regression accuracy. An inference mechanism is further introduced to derive the remaining acupoints from 49 detected keypoints; experiments demonstrate that the improved model achieves 95.0% detection accuracy, outperforming the baseline by 2.62%, with an inference time of 14.5 ms. Finally, an in situ projection platform is constructed, combining camera calibration, four-point proportional scaling, and an OpenCV 4.5.4-based interactive interface. The system supports real-time translation, rotation, and scaling, enabling accurate projection of detected acupoints onto the human body. Full article

The dimensional accuracy of the bearing inner ring is critical for the operational performance and reliability of high-end equipment. However, nonlinear deformation of the measurement mechanism caused by temperature variations and temperature drift of the sensor significantly affect the measurement accuracy. In this study, a novel online measurement system for bearing inner diameter was designed, which integrates a two-degree-of-freedom motion mechanism and an adaptive elastic measurement probe. To compensate for the measurement errors caused by temperature effects in the proposed system, an intelligent compensation method based on a CNN-LSTM–Attention hybrid model was proposed. The raw sensor signals and ambient temperature were used as the model inputs, and an end-to-end nonlinear mapping relationship for the actual bearing inner diameter deviation was established without the need to construct complex explicit physical equations. The experimental results show that, within the investigated temperature interval of 11–21 °C, the proposed method controls the measurement error within 1.87 μm, thereby satisfying the dimensional measurement requirement for P4-grade bearings with a tolerance of 0 to −4 μm. Full article

This study investigated the effects of therapeutic climbing on pain, function, and rotator cuff muscle thickness in sport climbers with shoulder pain using a prospective, single-blind randomized controlled trial design. Forty-five participants were randomly assigned to three groups: therapeutic climbing combined with sport climbing (EG1), shoulder stabilization exercise combined with sport climbing (EG2), and sport climbing alone (CG). Interventions were performed three times per week for six weeks, with assessments conducted at baseline, 3 weeks, and 6 weeks. Pain and disability were measured using the Shoulder Pain and Disability Index (SPADI), and muscle thickness of the supraspinatus and infraspinatus was assessed using ultrasound imaging. Both EG1 and EG2 demonstrated significantly greater improvements in pain and function compared to the control group (p < 0.05), with EG1 showing more consistent and progressive improvement over time. Changes in muscle thickness varied by muscle and intervention: supraspinatus thickness decreased over time in EG1, whereas it increased in EG2 and CG; in contrast, infraspinatus thickness remained stable in EG1 and EG2 but decreased in CG. These findings suggest that therapeutic climbing may promote more favorable neuromuscular adaptations, contributing to improved shoulder function. Therefore, therapeutic climbing may serve as an effective, sport-specific rehabilitation strategy for reducing pain and facilitating functional recovery in climbers with shoulder pain. Full article

Developing critical thinking is a central aim of contemporary higher education, yet conventional instructional approaches often underuse authentic, real-world materials that stimulate higher-order reasoning and reflective judgment. The study examines the effectiveness of case-based socio-legal pedagogy in fostering critical thinking within contexts of legal pluralism and social complexity. A quasi-experimental mixed-methods pre–post design was conducted with 62 undergraduate students enrolled in a course on Islamic law and society. Over a four-week intervention, students engaged with six socio-legal cases drawn from Muslim women’s legal experiences in Israel, focusing on divorce, maintenance (nafaka), and child custody. Quantitative data were collected using a validated Critical Thinking Rubric assessing argumentation, evaluation of multiple perspectives, and legal reasoning. Results showed significant improvement in overall critical thinking, with gains across all measured dimensions. Qualitative analysis of written assignments and student reflections revealed greater recognition of legal ambiguity, more structured and evidence-based argumentation, and deeper engagement with competing normative and social frameworks. Overall, the findings highlight the pedagogical value of integrating socio-legal complexity into case-based learning as an adaptable model for strengthening critical thinking across disciplines involving interpretive, contested, and context-dependent knowledge in higher education and other fields requiring careful judgment under conditions of uncertainty and change. Full article

Heart rate variability (HRV) is an established biomarker of autonomic nervous system activity, yet its profile in miniature cattle remains poorly understood despite their growing importance in sustainable farming. This study compared HRV parameters between miniature and Holstein cows and assessed the influence of age on these profiles. Eighty clinically healthy female cattle (40 miniature, 40 Holstein), aged 2 to 8 years, were evaluated under field conditions using a Polar H10 heart rate monitor. RR intervals were analyzed using Kubios HRV software to obtain time- and frequency-domain indices. Miniature cows exhibited significantly lower heart rates and higher time-domain measures (RMSSD and SDNN) compared to Holsteins, while frequency-domain analysis revealed significant differences in LF, HF, and LF/HF ratio, suggesting group-associated differences in proportional autonomic balance. Age-stratified analysis revealed that these physiological distinctions were more pronounced in older cows (6–8 years). However, given the observational cross-sectional design of this study, confounding factors—specifically the different farm environments, management systems, and the active lactation status of the Holstein group—preclude attributing these differences solely to breed or body size. Therefore, these results suggest an associative physiological pattern rather than a definitive autonomic adaptation. Despite these limitations, portable HRV monitoring proved feasible under farm conditions, providing valuable preliminary baseline data that can inform future controlled studies on bovine cardiovascular welfare. Full article