Search Results (17,919)

This systematic review maps the landscape of microlearning research within software engineering education, critically examining how this pedagogical approach is being applied to develop the multifaceted competencies required of modern software professionals. Following PRISMA-ScR guidelines, the review synthesized 21 empirical studies from 2015 to 2026, analyzing their pedagogical approaches, technological integrations, curriculum coverage, and evidence of effectiveness. The findings reveal a field marked by creative experimentation yet significant fragmentation: while microlearning effectively engages students and conveys discrete programming and project management knowledge through gamified, mobile, and project-based formats, its application remains narrowly concentrated on introductory coding, leaving advanced competencies such as software architecture, requirements engineering, and testing strategies virtually unexplored. The review further exposes critical gaps in the evidence base, including the absence of longitudinal and transfer studies, the conflation of platform engagement with learning, and methodologically fragile claims of effectiveness. Enthusiasm for microcredentials and AI-personalized learning considerably outstrips empirical support, with implemented systems relying on rule-based logic rather than adaptive intelligence and credentialing frameworks lacking validation of employer recognition or employment outcomes. This review concludes that while microlearning holds genuine potential for just-in-time skill development in a rapidly evolving discipline, its role in software engineering education must be strategic and supplemental rather than comprehensive. The field must urgently move from promotional advocacy toward rigorous, comparative, and longitudinal research that assesses higher-order competencies and authentic professional capability, lest its promise remain unfulfilled. Full article

Grey plastic is a representative traditional architectural decoration craft in the Lingnan region in China, carrying rich historical and cultural values as well as distinctive regional artistic characteristics. However, the grey plastic craft is currently facing problems such as inheritance gaps and a shortage of craftsmen, and its restoration projects impose extremely high professional requirements on contractors. Existing contractor selection methods are mostly applicable to ordinary construction projects and are difficult to adapt to its particularity, which may easily lead to risks such as substandard restoration quality. Therefore, this paper proposes a contractor selection method for grey plastic decoration projects of cultural relic buildings based on the BWM-TODIM method. Firstly, an evaluation system covering six core criteria is constructed; secondly, the BWM is adopted to determine the criteria weights; thirdly, the TODIM method is used to characterize the decision-makers’ loss aversion psychology and rank the candidate contractors; finally, an empirical analysis is conducted with a grey plastic restoration project in Lingnan as a case to verify the feasibility and effectiveness of the method. This study can provide decision support for the scientific selection of contractors for grey plastic decoration projects and contribute to the sustainable protection of cultural heritage. The scope of this study is limited to contractor selection for grey plaster decoration engineering of cultural relic buildings. Full article

Background and Objectives: Hip and knee replacement joint surgeries are experiencing constant growth, and anticipating future needs allows decision-makers and stakeholders involved in the healthcare system to allocate the necessary resources for safe and effective services. The objective of this study is to estimate the volumes of primary and revision hip and knee surgeries expected to be performed in Romania by 2060. Materials and Methods: We used data from the Romanian Arthroplasty Register regarding the total volume of primary hip replacement surgery (cumulative n = 51,252 across five years), hip revision surgery (cumulative n = 3579), primary knee replacement surgery (cumulative n = 32,283), and knee revision surgery (cumulative n = 943) performed in 2017–2019, 2023 and 2024—the last five years of complete registrations, excluding the pandemic period. We projected future numbers of hip and knee primary and revision surgeries using the arithmetic mean of annual procedure rates observed during the study period, combined with the average annual trend in these rates. Projections were stratified by age group (0–39, 40–49, 50–59, 60–69, 70–79, and ≥80 years) and sex and were applied to population forecasts from the National Institute of Statistics of Romania up to 2060. Results: By 2060, primary hip replacement surgery volumes will increase by 40.14% relative to 2024 levels (from 13,526 in 2024 to 18,965 in 2060), and primary knee replacement surgery volumes will increase by 79.78% (from 9003 in 2024 to 16,186 in 2060). Revision hip surgery volumes will increase by 42.02% (from 759 in 2024 to 1078 in 2060), and revision knee surgery volumes will increase by 109.25% (from 227 in 2024 to 475 in 2060). The largest relative increases are concentrated in patients aged ≥80 years, with projected growth substantially exceeding those in younger age groups across all procedure types and both sexes. These percentages represent the projected growth in procedure volumes for this age group compared with 2024 baseline volumes. Conclusions: By 2060, we project substantial increases in all arthroplasty procedure types in Romania, with the most pronounced growth among patients aged ≥80 years. Given that resource utilization and morbidity are higher in this population, the increased demand for medical interventions requires advance planning, which will have significant implications for the healthcare system. Full article

This study introduces a novel risk detection and control system to enhance social stability in major construction projects. Utilizing a heterogeneous cellular automaton model, the system simulates complex interactions among project stakeholders to identify and mitigate Social Stability Risks (SSR). Integrating the Ignorant–Latent–Malcontent–Recovered (ILMR) framework, the model applies principles from epidemiology to predict and manage the spread of social stability risks. Simulation results demonstrate the model’s effectiveness in reducing the number of malcontent and ignorant individuals while increasing the recovered category, stabilizing the social environment around large projects. This approach helps manage immediate risks and improves long-term social acceptance and sustainability of engineering projects. By bridging risk management with advanced simulation techniques, this research contributes to major construction projects by providing a robust framework for managing complex social dynamics, thereby enhancing project success and stakeholder satisfaction. The findings underscore the potential of integrating innovative technological tools with traditional risk management strategies to address the socio-technical challenges of large-scale engineering projects. Full article

Indoor pedestrian navigation tasks, as a key part of smart cities and navigation services, face dual challenges of accuracy and cost under complex building environments. Currently, neural inertial navigation is at the vanguard of current research in indoor pedestrian navigation, and existing related studies have achieved positive results. However, the exploration of deep learning solutions is still not sufficient, mainly reflected in the lack of explorations of model training configurations. Based on testing results under different deep learning schemes, this paper proposes EDIN, an enhanced deep inertial navigation approach. This method benefits from a proprietary neural network based on ResNeXt with Convolutional Block Attention Module (CBAM) to predict the relationship between inertial data and motion trajectory. Compared to existing projects, this paper also makes improvements in the model training process, thereby improving the predictive effect of the trained model. Specifically, this paper innovatively uses Logcosh as the loss function and combines data rotation and additional noise as data augment methods. To assess EDIN’s performance, extensive tests were conducted using three publicly available datasets: RoNIN, OXIOD, and RIDI. The results clearly indicate EDIN’s superior performance relative to other neural inertial navigation systems. Notably, localization accuracy improved significantly, with an average enhancement of 16.06% compared to the RoNIN-ResNet method. Full article

The objective of this scientific study is to examine whether the climate change attention of the chief executive officer promotes corporate social responsibility. To perform the extensive calculations required for this analysis, the study utilizes comprehensive panel data sourced from Carbon Disclosure Project, KLD, and financial databases. The scientific research methods used include two-stage instrumental variable estimation and difference-in-differences approaches to rigorously establish a causal relationship. The results identify a significant positive correlation between chief executive officer climate change attention and overall corporate social responsibility. Specifically, this executive focus significantly improves external and internal corporate social responsibility while reducing socially irresponsible performance; however, it does not enhance material corporate social responsibility. Furthermore, the findings indicate that this positive effect is significantly amplified when chief executive officers are in the early stages of their careers or receive high compensation, particularly equity-based compensation. Additionally, the implementation of a corporate low-carbon strategy serves as an important mediating channel for improving social performance. In conclusion, executive cognitive attention is a fundamental determinant of a firm’s strategic behaviors. It is recommended that corporate boards structure equity-based compensation to align with sustainability goals and actively support low-carbon strategies to maximize the positive impact of executive attention on sustainable development. Full article

Environmental regulations, rapid technological advancements, and evolving mobility trends have led to a significant transformation of the automotive industry in recent years. The adoption of battery-electric vehicles (BEVs) has been accelerated by these developments, which are becoming increasingly efficient and widely deployed. Evaluating BEV energy consumption and performance is essential for optimizing energy efficiency, extending driving range, and developing effective control strategies under real-world operating conditions. The analysis is based on the WLTP Class 3 driving cycle, in which the vehicle operating points are projected onto the motor efficiency map to evaluate the influence of real-world operating conditions on overall propulsion efficiency. Two operating scenarios are considered: with regenerative braking and without regenerative braking. The inverter and battery are modeled using quasi-static energy-based representations to ensure system-level energetic consistency while maintaining computational efficiency. The results show that rotor topology significantly influences vehicle-level energy consumption. The dual-layer IPM configuration reduces net WLTP energy demand by approximately 9% and increases the estimated driving range from about 489 km to 535 km compared to the single-layer V-shaped configuration. Variations in rotor topology led to different efficiency distributions, which leads to systematic differences in battery energy demand and achievable driving range. The results highlight the importance of aligning traction motor design with realistic operating-point distributions rather than optimizing solely for peak efficiency or marginal improvements in regenerative braking performance. Full article

The accurate measurement and optimization of spatial vitality inside commercial complexes has become crucial for sophisticated urban governance as urban growth moves from rapid expansion to quality-oriented stock augmentation. This research creates a multifaceted assessment methodology that incorporates systemic connectedness (transportation synergy), spatial performance (public activity and social efficacy), and spatial supply (human–land linkages and arrangement). We used a stratified purposive sample of 20 business complexes spread across eight districts in Guangzhou, a typical high-density megacity. In order to understand the underlying mechanisms of spatial vitality, we measured important indicators including the Polycentricity Index (α) and the Spatial Performance Index (β) using a mixed-methods approach that included K-means clustering, multinomial logit regression, and Structural Equation Modeling (SEM). Four important insights are shown by our findings. 1. The paradox of density and efficiency: The notion that high-density development inevitably ensures lively public space is called into question by the lack of a significant linear correlation between the Floor Area Ratio (FAR) and spatial performance (r = 0.32, p > 0.05), despite a core–periphery gradient in development intensity. 2. Structural Supply Demand Mismatch: Although overall spatial performance is strong (β = 0.81 ± 0.07), there is a notable shortfall in cultural and artistic venues, where young adults’ demand (0.27) is 145% greater than supply (0.11). 3. Polycentric Networking vs. Transport Polarization: While spatial structures show a networked polycentric pattern (mean α = 6.40), transportation synergy is affected by core–periphery polarization, which results in “vitality islands” in the periphery. 4. Dual-Path Driving Mechanisms: According to SEM results, cultural spaces have a considerable indirect impact (39.7% mediation) by boosting brand uniqueness and “cultural capital,” while composite plaza spaces have a strong direct effect on commercial performance (γ = 0.682). Based on these findings, we suggest distinct optimization strategies: aging projects need climate-responsive design interventions; growing areas should create family-oriented consumption ecosystems; and core districts should give priority to cultural “IP” integration. For the planning and revitalization of commercial land use in high-density global environments, this study offers a solid analytical framework and practical insights. Full article

Construction projects are prone to conflicts and disputes due to differing stakeholder interests, which can adversely affect their successful completion in terms of time, cost, and quality. Thus, implementing effective conflict management methods is essential to reduce negative outcomes and capitalize on the positive outcomes of conflicts. However, there is still limited understanding of the status and trends of stakeholder conflicts, and critical conflict causes and management strategies identified by previous studies. Thus, a systematic literature review was conducted, complemented by a scientometric analysis using the VOSviewer bibliographic tool and Pareto analysis to systematically identify critical factors within literature. A total of 63 studies published between 1993 and 2025 were analyzed. Findings indicate that most recent studies have focused more on human, contractual, and technological aspects of conflict. Overall, this study identified 46 conflict causes and 58 management strategies, which were categorized into different groups based on their characteristics. Among these, 23 and 31 were identified as most critical causes and management strategies based on Pareto analysis, with most factors linked to stakeholder relationships. The study offers a systematic understanding of the status quo and emerging themes in stakeholder conflicts research in construction industry. The findings of this study will be beneficial for researchers in identifying future research directions and project stakeholders to understand the most common conflicts and effective management methods for handling conflicts in construction projects. Full article

Large depth of field (DOF) is a core pursuit in integral imaging (InIm). In this paper, we propose a DOF-enhanced InIm display system comprising a transmissive mirror device (TMD), a semi-transparent mirror (STM), two 2D displays, and a micro-lens array (MLA). The two 2D displays pre-render two sets of elemental image arrays (EIAs), each corresponding to a distinct depth plane. The STM spatially coaxializes the two EIAs emitted by the two 2D displays. At the same time, the TMD collaborates with the STM to adjust the effective projection distances of the coaxialized EIAs onto the MLA to different values. The MLA couples with the two EIAs projected at different effective distances, enabling the reconstruction of three-dimensional (3D) images at two separate central depth planes (CDPs). This system solves the narrow DOF issue in conventional InIm displays by reconstructing 3D images at two separate CDPs, thus enhancing the DOF. Notably, the proposed system achieves an approximate two-fold increase in DOF compared to a conventional one. A prototype of the DOF-enhanced InIm display system is constructed, and experimental results verify its feasibility. Full article

External defects considerably reduce the quality, consumer acceptance, and market value of citrus fruits. Therefore, a rapid and reliable, non-destructive inspection method is necessary for postharvest processing. In this study, a non-destructive approach for external defect classification of citrus fruits is developed by combining visible–near infrared hyperspectral imaging (HSI) with effective wavelength selection (EWS) algorithms. First, 1702 spectral samples of normal and defective regions on citrus fruit surfaces were collected. A partial least squares discriminant analysis (PLS-DA) model was developed using the full wavelength range (400–1000 nm), which achieved 99.02% prediction accuracy. Four EWS algorithms—weighted regression coefficients, variable importance in projection, sequential forward selection (SFS(5, 10, 15)), and random frog—were evaluated for optimal spectral dimensionality and computational efficiency. The SFS15-PLS-DA model, which selected 15 optimal variables out of the initial 300 and used maximum normalization preprocessing, achieved the highest prediction accuracy of 99.80%. This model demonstrated near-perfect classification while reducing the total number of wavelengths by 95.0% (from 300 to 15 wavelengths). Further, a pixel-wise image classification algorithm was implemented using the optimal model, which effectively detected physical damage, pest infestation, and fungal decay. These results demonstrate that combining HSI with EWS enables compact, interpretable, and high-performance models suitable for real-time postharvest sorting. This approach has strong potential to enhance automation, speed, and reliability in commercial citrus quality assessment. Full article

Floodplain disconnection caused by channel incision and/or levee construction has led to widespread loss of riparian habitats and ecosystem functions globally. Restoring full stream–floodplain connectivity is increasingly promoted, yet evidence of ecological outcomes remains limited. This study evaluates the initial performance of two Stage 0 restoration projects on Whychus Creek, Oregon, which reconnected incised channels to their historical floodplains in 2012 and 2016. We combined pre- and post-restoration vegetation surveys along fixed transects with hydrogeomorphic-based riparian and wetland function assessments and applied quantitative analyses, including Kruskal–Wallis tests, Jaccard correlations, Sorensen similarity indices, and factor analysis, to compare changes in plant assemblages and ecosystem functions across restored, transitional, and unrestored reaches. Our research results indicate that two years post-restoration, the active riparian area expanded 2.5-fold, species richness and structural diversity increased significantly, and riparian and wetland functions such as water storage, sediment retention, and habitat support for fish and amphibians improved markedly. Numbers of anadromous salmonids also increased markedly. This is important as salmon recovery is a regional stream restoration goal. Comparisons with a reach restored six years earlier suggest a positive trajectory toward mature, resilient ecosystems. These findings demonstrate that Stage 0 restoration can rapidly reestablish complex habitat mosaics and enhance ecosystem services critical for biodiversity, water quality, and flood resilience. Practically, this evidence supports process-based restoration strategies that prioritize full floodplain reconnection as a cost-effective approach to reversing long-term ecological degradation. Continued monitoring is essential to guide adaptive management and strengthen the evidence base for the wide-scale implementation of valley-floor wide stream restoration. Full article

In highway widening projects, the wet–dry cycling effect of weakly expansive soil fill under seasonal groundwater fluctuations exacerbates differential settlement. This study establishes a three-dimensional numerical model for a widened road with weakly expansive soil, based on a redeveloped numerical method and actual engineering projects. Through multi-scenario numerical simulations, the influence patterns and weighting factors of widening methods, road height, and water level on differential settlement were clarified. Three safety levels for differential settlement were defined using 6 cm and 12 cm as thresholds. A prediction model based on support vector machines was established to determine the combined threshold limits of key parameters under different differential settlement boundaries. The control effectiveness of sand replacement, water-blocking layers, and wicking geotextiles was comparatively evaluated: sand replacement reduces differential settlement by approximately 70% on average and is applicable to all scenarios; water-blocking layers reduce settlement by about 50% and are more suitable for bilateral widening or unilateral widening of low embankments; wicking geotextiles are unsuitable for controlling differential settlement in high-water-level areas. Selection principles for control methods under different conditions were proposed based on engineering requirements, and field tests validated the effectiveness of the proposed solutions. Full article

Variations in terrestrial carbon flux influence atmospheric CO₂ exchange and related climate feedback, with Net ecosystem productivity (NEP) serving as a key metric for assessing ecosystem carbon source–sink dynamics. Given the vital ecological barrier function of the Tibetan Plateau (TP), understanding the spatiotemporal variability of NEP and its climatic controls is essential for elucidating carbon sink and climate interactions under ongoing climate change. The spatiotemporal dynamics of NEP across the TP from 1979 to 2018 are investigated using the process-based Community Land Model version 5.0 (CLM5.0). And climate sensitivity experiments are conducted to quantify the relative contributions of different climate factors to NEP variability. Furthermore, future changes in NEP for the period 2025–2100 under multiple Shared Socioeconomic Pathway (SSP) scenarios are projected. The results indicate that the TP functioned predominantly as a net carbon sink during the historical period, with a multi-year mean NEP of 23.96 g C m² yr⁻¹. Spatially, NEP showed a significantly increasing gradient from the northwest to the southeast. During 1979–2018, NEP exhibited an overall decreasing trend across most regions of the TP. Air temperature was identified as the dominant controlling factor, accounting for approximately 68% of the interannual NEP variability, followed by solar radiation (21%) and precipitation (11%). The dominant climatic drivers of NEP variation differ among regions: air temperature predominates in the southwestern and southeastern regions, radiation dominates in the northwestern and central areas, and precipitation exerts a controlling effect in the northern and western regions. Future projections suggest that NEP remains positive under all SSP scenarios, indicating that the TP is likely to persist as a carbon sink throughout the 21st century. This study provides important reference for the development of ecological protection, restoration planning, and regional carbon neutrality strategies. Full article

Serving students with special educational needs (SENs) involves recognising that their learning is closely linked to their emotional needs. Self-esteem and socio-emotional well-being play a key role in their motivation and adaptation to school. In this context, physical activity-based interventions at school emerge as a possible way to strengthen their self-esteem and socio-emotional well-being. The aim of this study was to analyse the effects of a web-based active break programme on self-esteem in students aged 6 to 10 years with SENs and on socio-emotional well-being in the subgroup of first–second-grade students. A pre-specified sub-analysis was conducted of a multicentre randomised controlled trial with a sample of 161 students with special educational needs (7.8 ± 1.1 years, 32% girls), divided into a control group (85 students) and an experimental group (76 students). A programme of video-guided active breaks was implemented in the classroom, applied twice a day, five days a week for 12 weeks, via a web platform. Self-esteem was assessed using the School Self-Esteem Test (SSET), and socio-emotional well-being was assessed using the Self-Report of Socio-Emotional Well-Being (SRSEWB). A significant Time × Group interaction was observed for self-esteem, F_{(1, 157)} = 5.43, p = 0.021, η²_p = 0.033, but no statistically significant effects were detected for socio-emotional well-being. These findings suggest that active break interventions may help strengthen self-esteem in students with SENs. Future research should examine the temporal stability of these improvements, determine the optimal intervention duration required to generate sustained changes, and evaluate longer-term socio-emotional outcomes. Full article