Search Results (12,848)

Conventional academic warning systems in higher education often rely on end-of-semester grades, which severely limits opportunities for timely intervention. To address this, our interdisciplinary study developed and validated a comprehensive socio-technical framework that integrates social-cognitive theory with learning analytics. The framework combines educational data mining with culturally responsive, personalized interventions tailored to a non-Western context. A two-phase mixed-methods design was employed: first, predictive models were built using Learning Management System (LMS) data from 2,856 students across 64 courses. Second, a quasi-experimental trial (n = 48) was conducted to evaluate intervention efficacy. Historical academic performance, attendance, and assignment submission patterns were the strongest predictors, achieving a Balanced Area Under the Curve (AUC) of 0.85. The intervention, specifically adapted to Confucian educational values, yielded remarkable results: 73% of at-risk students achieved passing grades, with a large effect size for academic improvement (Cohen’s d = 0.91). These findings empirically validate a complete prediction–intervention–evaluation cycle, demonstrating how algorithmic predictions can be effectively integrated with culturally informed human support networks. This study advances socio-technical systems theory in education by bridging computer science, psychology, and educational research. It offers an actionable model for designing ethical and effective early warning systems that balance technological innovation with human-centered pedagogical values. Full article

High-precision semantic segmentation of remote sensing imagery is crucial in geospatial analysis. It plays an immeasurable role in fields such as urban governance, environmental monitoring, and natural resource management. However, when confronted with complex objects (such as winding roads and dispersed buildings), existing semantic segmentation methods still suffer from inadequate target recognition capabilities and multi-scale representation issues. This paper proposes a neural network model, LMVMamba (LoRA Multi-scale Vision Mamba), for semantic segmentation of remote sensing images. This model integrates the advantages of convolutional neural networks (CNNs), Transformers, and state-space models (Mamba) with a multi-scale feature fusion strategy. It simultaneously captures global contextual information and fine-grained local features. Specifically, in the encoder stage, the ResT Transformer serves as the backbone network, employing a LoRA fine-tuning strategy to effectively enhance model accuracy by training only the introduced low-rank matrix pairs. The extracted features are then passed to the decoder, where a U-shaped Mamba decoder is designed. In this stage, a Multi-Scale Post-processing Block (MPB) is introduced, consisting of depthwise separable convolutions and residual concatenation. This block effectively extracts multi-scale features and enhances local detail extraction after the VSS block. Additionally, a Local Enhancement and Fusion Attention Module (LAS) is added at the end of each decoder block. LAS integrates the SimAM attention mechanism, further enhancing the model’s multi-scale feature fusion capability and local detail segmentation capability. Through extensive comparative experiments, it was found that LMVMamba achieves superior performance on the OpenEarthMap dataset (mIoU 52.3%, OA 69.8%, mF1: 68.0%) and LoveDA (mIoU 67.9%, OA 80.3%, mF1: 80.5%) datasets. Ablation experiments validated the effectiveness of each module. The final results indicate that this model is highly suitable for high-precision land-cover classification tasks in remote sensing imagery. LMVMamba provides an effective solution for precise semantic segmentation of high-resolution remote sensing imagery. Full article

Cultural heritage is important for every group and society, as it represents a part of their identity and helps preserve traditions, along with significant tangible and intangible elements. These elements are not only passed on to future generations but also play a role in education today. Many studies have examined digital applications that promote cultural heritage, particularly those that use Augmented Reality (AR) technology. However, few have systematically examined the methodologies used in the design, development and evaluation of AR applications for cultural heritage. This narrative review addresses that gap by analyzing 45 papers published between 2008 and 2024 from the Scopus and Web of Science databases. The review identifies the main motivations for AR applications, such as enhancing the learning experience, promoting tourism and the use of gamification. The majority of these applications concentrate on tangible cultural heritage, such as historical buildings and cultural routes, while intangible heritage remains less explored. In most cases, AR applications were developed with a focus on user experience, using various development tools and showing different levels of technical complexity. Although many applications initiated evaluation processes, few completed them thoroughly. These evaluations vary widely, ranging from usability tests to pre-/post-tests. The results generally report positive impacts in terms of learning and user experience. This review offers a structured framework and useful insights for researchers regarding the design and evaluation of AR applications and helps identify research gaps and limitations for future work. Full article

Competitive programming has emerged as a critical benchmark for evaluating large language models (LLMs) in solving algorithmic problems under competitive conditions. Existing methods, such as the Sequential One-Agent Pipeline (SOP) approach, suffer from significant limitations, including the inability to effectively manage semantic drift across multiple stages, a lack of coordinated adversarial testing, and suboptimal final solutions. These issues lead to high rates of wrong answer (WA) and time-limit exceeded (TLE) errors, especially on complex problems. In this paper, we propose the Cross-Verification Collaboration Protocol (CVCP), a multi-agent framework that integrates symmetry detection, symmetry-guided adversarial testing, Round-Trip Review Protocol (RTRP), and Asynchronous Voting Resolution (AVR) to address these shortcomings. We evaluate our method on the CodeELO dataset, showing significant improvements in performance, with Elo Ratings increasing by up to 7.1% and Pass Rates for hard problems improving by as much as 1.8 times compared to the SOP baseline. Full article

In this research, precision temperature sensing for electromagnetically harsh environments was achieved utilizing a low-threshold frequency-stable optoelectronic oscillator (OEO) leveraging stimulated Brillouin scattering (SBS). The sensing mechanism relied on the temperature-dependent frequency shift in the SBS-induced notch filter. By embedding this filter in the OEO feedback loop, the oscillator’s output frequency was locked to the difference between the optical carrier frequency and the SBS notch center frequency. The temperature variations were translated into microwave frequency shifts through OEO oscillation, which was quantified with heterodyne detection. To suppress environmental perturbations, a Faraday rotation mirror (FRM) was integrated at the fiber end, creating a dual-pass SBS interaction that simultaneously enhanced the vibration immunity and reduced the SBS power threshold by 2.7 dB. The experimental results demonstrated a sensitivity of 1.0609 MHz/°C (R² = 0.999) and a long-term stability of ±0.004 °C. This innovative scheme demonstrated significant advantages over conventional SBS-OEO temperature sensing approaches, particularly in terms of threshold reduction and environmental stability enhancement. Full article

This manuscript presents a study on the dynamics of fiber Bragg grating formation using femtosecond radiation in the point-by-point inscription regime. By employing a multi-pass inscription technique, the dynamics of the photoinduced formation of modified regions (strokes) were investigated through an analysis of the evolution of the Bragg grating’s parameters. The results demonstrate a decrease in the average effective refractive index during the grating inscription. This study highlights the complexity of the structural transformations induced in the optical fiber core material by femtosecond laser radiation. Full article

Crude oil and grain, as two pivotal global commodities, exhibit significant price co-movement that profoundly affects national economic stability and food security. From the perspective of systems theory, the energy and grain markets do not exist in isolation but rather form a highly coupled complex system, characterized by nonlinear feedback, cross-market risk contagion, and cascading effects. This study systematically investigates the transmission mechanisms from international crude oil prices to the domestic prices of Chinese four major grains, employing the DY spillover index, Vector Error Correction Model (VECM), and a mediation effect framework. The empirical findings reveal three key insights. First, rising international crude oil prices significantly strengthen the pass-through of global grain prices to domestic markets, while simultaneously weakening the effectiveness of domestic price stabilization policies. Second, higher crude oil prices amplify international-to-domestic price spillovers by increasing maritime freight costs, a key channel in global grain trade logistics. Third, elevated oil prices stimulate demand for renewable biofuels, including biodiesel and ethanol, thereby boosting international demand for corn and soybeans and intensifying the transmission of price fluctuations in these commodities to the domestic market. These findings reveal the key pathways through which shocks in the energy market affect food security and highlight the necessity of studying the “energy–food” coupling mechanism within a systems framework, enabling a more comprehensive understanding of cross-market risk transmission. Full article

The southeastern Tibet region is characterized by rugged terrain and relative isolation, which has significantly constrained the development of agriculture. However, due to the extremely limited archaeological and historical records available, its important role in the history of agricultural development in Tibet has been overlooked. This study focuses on the Linzhi and Changdu regions of southeastern Tibet, integrating limited archival, historical, and documentary data. By reconstructing historical settlement patterns and population data, this study estimates the arable land area during the Tubo, Yuan, Ming, and Qing dynasties. Using a grid-based model, it reconstructs the distribution patterns of arable land during these periods, aiming to provide a reference for the development of agriculture in Tibet. The research findings indicate the following: (1) During historical periods, settlements in southeastern Tibet were primarily distributed in flat, resource-rich alluvial plains at medium to high altitudes. Settlement types exhibited spatial differentiation: Post stations were primarily situated along major transportation routes that connected river valleys, as well as at high mountain passes. Temples tended to occupy moderately steep slopes, while manors were concentrated in low-lying valleys. (2) During the Tubo, Yuan, Ming, and Qing periods, the total arable land area and cultivation rate in southeastern Tibet were generally low, with total arable land areas of 28,085 hm², 29,449 hm², 25,319 hm², and 24,371 hm², respectively, and cultivation rates of 0.12%, 0.13%, 0.11%, and 0.11%, respectively. (3) Farmland was predominantly distributed along the Yarlung Zangbo, Jinsha, Lancang, and Nu Rivers and their broader tributary valleys. Natural constraints resulted in a highly fragmented farmland distribution. Full article

In low-risk and open environments, such as farms and mining sites, efficient cargo transportation is essential. Despite the suitability of autonomous driving for these environments, its high deployment and maintenance costs limit large-scale adoption. To address this issue, a modular unmanned ground vehicle (UGV) system is proposed, which is adapted from existing platforms and supports both autonomous and manual control modes. The autonomous mode uses environmental perception and trajectory planning algorithms for efficient transport in structured scenarios, while the manual mode allows human oversight and flexible task management. To mitigate the control latency and execution delays caused by platform modifications, an enhanced transformer-based general dynamics model is introduced. Specifically, the model is trained on a custom-built dataset and optimized within a bicycle kinematic framework to improve control accuracy and system stability. In road tests allowing a positional error of up to 0.5 m, the transformer-based trajectory estimation method achieved 94.8% accuracy, significantly outperforming non-transformer baselines (54.6%). Notably, the test vehicle successfully passed all functional validations in autonomous driving trials, demonstrating the system’s reliability and robustness. The above results demonstrate the system’s stability and cost-effectiveness, providing a potential solution for scalable deployment of autonomous transport in low-risk environments. Full article

Signs of the passage of time can come as an unwelcome reminder of our own eventual passing. Historically, many cultures have sought refuge from the march of time in the notion of a timeless present. More recently, studies have shown that presence achieved through meditation lowers stress. This essay explores how the built environments where we spend most of our lives might help us to be more fully present. Rather presenting a comprehensive theory of the present in architecture, its intent is to make a series of design suggestions. Full article

This study evaluates the competency-based performance of Initial Incident Commander (IIC) candidates—fire officers who serve as first-arriving, on-scene incident commanders—in South Korea and identifies sub-competency deficits to inform training improvements. Using evaluation data from 92 candidates tested between 2022 and 2024—of whom 67 achieved certification and 25 did not—we analyzed counts and mean scores for each sub-competency and integrated transcribed radio communications to contextualize deficiencies. Results show that while a majority (72.8%) passed, a significant proportion (27.2%) failed, with recurrent weaknesses in crisis response, progress management, and decision-making. For example, “Responding to Unexpected or Crisis Situations 3-3” recorded 27 unsuccessful cases with a mean score of 68.8. Candidates also struggled with resource allocation, situational awareness and radio communications. The study extends recognition-primed decision-making theory by operationalizing behavioral marker frameworks and underscores the need for predetermined internal alignment, scalability and teamwork synergy. Practical implications recommend incorporating high-fidelity simulation and VR scenarios, competency frameworks and reflective debriefs in training programs. Limitations include the single-country sample, reliance on predetermined scoring rubrics and absence of team-level analysis. Future research is indispensable to adopt multi-jurisdictional longitudinal designs, evaluate varied training interventions, assess skill retention and explore the interplay between physical and cognitive training over time. Full article

This study evaluates media-level filtration behaviour and short-term fuel consumption outcomes for five spin-on lubricating oil filters operated under real driving conditions at high altitude. To improve interpretability, filters are reported using parameter-based identifiers (media descriptors and equivalent circular diameter, ECD) rather than internal codes. Pore-scale morphology was quantified by microscopy and expressed as ECD, and bulk fluid cleanliness was summarised using ISO 4406 codes. Trials were conducted over representative urban and extra-urban routes at altitude; fuel consumption was analysed using ANCOVA. The results indicated clear media-level differences (tighter pore envelopes and cleaner ISO codes, particularly for two OEM units). However, fuel-consumption differences were not statistically significant (ANCOVA, p = 0.29). Accordingly, findings are reported as short-term cleanliness and media characterisation under high-altitude duty rather than durability or efficiency claims. The parameter-based framing clarifies trade-offs across metrics and avoids over-generalisation from brand or part numbers. The work highlights the value of ECD as a comparative pore metric and underscores limitations of microscopy/cleanliness data for inferring engine wear or long-term consumption. Future work will incorporate formal multi-pass testing (ISO 4548-12), direct differential-pressure instrumentation, used-oil viscosity tracking, and wear-metal spectrometry to enable cross-vendor benchmarking and causal interpretation. Findings are presented as short-term cleanliness and media characterisation; no durability claims are made in the absence of direct wear measurements. Full article

In order to form a solid electrolyte interphase (SEI) layer using aqueous processes, a graphite anode called MG-AQP was designed by wrapping and crosslinking graphite particles with aqueous composites (AQCs), which contained zwitterionic polymer, zwitterion molecules, and lithium salts. First, MG-AQP was used to fabricate a full lithium-ion battery (LIB) cell with Li[Ni_0.8Mn_0.1Co_0.1]O₂ (NMC811) as the cathode, denoted as LIB-MG-AQP//NMC811, to demonstrate its performance via a 0.5 C-rate break-in and 1 C-rate cycling. Accordingly, this showed that LIB-MG-AQP exhibits outstanding cyclic stability. To evaluate its electrochemical performance, MG-AQP and lithium metal were used to fabricate a half cell named LIBs-MG-AQP. According to the initial cyclic voltammetry curve, almost no surface reaction for forming an SEI layer exists in LIBs-MG-AQP, illustrating its high initial coulombic efficiency of 92% at a 0.5 C-rate break-in. These outstanding results are due to the fact that the AQC has fewer cracks, thus blocking solvent molecules from passing from the electrolyte into the graphite anode. This study provides new insights to optimize graphite anodes via 0.5 C-rate break-in rather than conventional SEI formation to save time and energy. Full article

Non-small cell lung carcinoma (NSCLC) is a prominent type, with an 85–90% incidence in all lung cancer cases. The evidence for a particular therapy strategy for people with NSCLC is still inadequate. This review evaluates NSCLC therapies that have passed phase IV trials, emphasizing their efficiency and adverse effects. Crucial therapeutic approaches, including dacomitinib, lorlatinib, durvalumab, osimertinib, and rivaroxban, are discussed, highlighting their mechanisms of action, uses, and adverse effects. Immune checkpoint medications are recommended because of their specific activity and minimal adverse reactions. The review also investigates cooperation therapies, such as targeting immune checkpoint inhibitors and hemostasis, alongside chemotherapy, as they offer potential for future therapies. However, further research is needed to improve the safety and efficacy of current treatments, and to explore novel ways to achieve better long-term outcomes. Full article

Background: Liberation from mechanical ventilation is a major objective in critically ill patients. Various criteria for extubation are used with different success rates. We developed a novel, simple bedside maneuver and index that involves measuring breath-hold duration and forced vital capacity (FVC). We named it the Respiratory Breath Hold Index (RBHI). Methods: We enrolled 225 mechanically ventilated intensive care unit (ICU) patients who were candidates for extubation. At the end of a spontan eous breathing trial (SBT), and just prior to extubation, patients were asked to hold their breath and perform a stalked FVC maneuver. The ability to perform a breath-hold maneuver and its duration were recorded and compared with a standard SBT. Results: 171 patients (76%) were successfully extubated, while 54 patients (24%) failed extubation. A successful SBT alone did not predict extubation, as 80.1% of passed SBT and 81.5% of failed SBT patients were extubated successfully (p = 1.00). However, a higher RBHI, together with the ability to hold breath and breath-hold duration, was highly associated with a successful extubation (p < 0.0001). Logistic regression analysis showed that RBHI over 3 was correlated with higher rates of successful extubation (OR 4.252, p < 0.001). Overall, 89% of patients who passed SBT and were able to hold breath were successfully extubated. (p < 0.0001). Whereas, among patients who passed SBT but failed to hold breath, only 24% were successfully extubated (p < 0.0001). Conclusion: Higher RBHI, together with the ability to hold a breath just prior to extubation in mechanically ventilated patients, is more sensitive and specific, and may be superior to standard SBT in predicting a successful extubation. Full article