Search Results (39,403)

Mobile learning (m-learning) technologies are gaining popularity in universities but not uniformly across institutions because of cognitive, affective, and behavior obstacles. This research tested and applied an expansion of the Technology Acceptance Model (TAM) with technostress (TECH) and resistance to change (RTC) as affective obstacles, as well as the core predictors of perceived usefulness (PU), perceived ease of use (PE), and perceived risk (PR). By employing a cross-sectional survey of Greek university students (N = 608) and partial least squares structural equation modeling (PLS-SEM), we tested direct and indirect impacts on behavioral intention (BI) to apply m-learning applications. The results affirm that PU and PE are direct predictors of BI, while PR has no direct impact on BI but acts indirectly through TECH and RTC. Mediation is partial in terms of PE and PU and indirect-only (complete) in terms of PR with respect to the impact of affective states on adoption. Multi-group comparisons found differences in terms of gender, age, confidence, and years of use but not frequency of use, implying that psychological and experiential characteristics have a greater impact on intention than habitual patterns. These results offer theory-driven and segment-specific guidelines for psychologically aware, user-focused m-learning adoption in higher education. Full article

The prediction of thin-bedded, favorable sand bodies within the Triassic Baikouquan Formation fan delta on the western slope of the Mahu Sag is challenging due to their strong spatial heterogeneity. To address this, we propose an integrated workflow that synergizes seismic sedimentology with geologically constrained seismic inversion. This study leverages well logging, core data, and 3D seismic surveys. Initially, seismic attribute analysis and stratal slicing were employed to delineate sedimentary microfacies, revealing that the fan delta front subfacies comprises subaqueous distributary channels, interdistributary bays, and distal bars. Subsequently, the planform distribution of these microfacies served as a critical constraint for the Seismic Waveform Indicative Inversion (SWII), effectively enhancing the resolution for thin sand body identification. The results demonstrate the following: (1). Two NW-SE trending subaqueous distributary channel systems, converging near the BAI65 well, form the primary reservoirs. (2). The SWII, optimized by our workflow, successfully predicts high-quality sand bodies with a cumulative area of 159.2 km², primarily located in the MAXI1, AIHU10, and AICAN1 well areas, as well as west of the MA18 well. This study highlights the value of integrating sedimentary facies boundaries as a geological constraint in seismic inversion, providing a more reliable method for predicting heterogeneous thin sand bodies and delineating future exploration targets in the Mahu Sag. Full article

The air-conditioner noise in a rehabilitation room can seriously affect the mental state of patients. However, the existing single-layer active noise control (ANC) filters may fail to attenuate the complicated harmonic noise, and the deep recursive ANC method may fail to work in real time. To solve the problem, in a bending-pipe model, a new hybrid adaptive self-loading filtered-x least-mean-square (ASL-FxLMS) and convolutional neural network-gate recurrent unit (CNN-GRU) network is proposed. At first, based on the recursive GRU translation core, an improved CNN-GRU network with multi-head attention layers is proposed. Especially for complicated harmonic noises with more or fewer frequencies than harmonic models, the attenuation performance will be improved. In addition, its structure is optimized to decrease the computing load. In addition, an improved time-delay estimator is applied to improve the real-time ANC performance of CNN-GRU. Meanwhile, an adaptive self-loading FxLMS algorithm has been developed to deal with the uncertain components of complicated harmonic noise. Moreover, to achieve balance attenuation, robustness, and tracking performance, the ASL-FxLMS and CNN-GRU are connected by a convex combination structure. Furthermore, theoretical analysis and simulations are also conducted to show the effectiveness of the proposed method. Full article

The traditional continuous, quantitative spraying technology ignores the severity of pests, diseases and grasses, spatial distribution and other differences, resulting in low effective utilization of pesticides, environmental pollution and other problems. Variable-rate spray technology has become an important development direction in the field of precision agriculture by dynamically sensing crop canopy morphology, pest and disease distribution, and environmental parameters, adjusting the application amount in real time, and significantly improving pesticide utilization. In this study, we systematically review the core progress of variable-rate spray technology; focus on the technical system of information detection, spray volume model, and control system; analyze the current bottlenecks; and propose an optimization path to adapt to the complex agricultural conditions. At the level of information perception, LiDAR, machine vision, and multi-source sensor fusion technology constitute the main perception architecture, and infrared and ultrasonic sensors assist target recognition in complex scenes. In the construction of the spray volume model, models based on canopy volume, leaf area density, etc., are used to realize dynamic application decision by fusing equipment operating parameters, pest and disease levels, meteorological conditions, and so on. The control system takes the solenoid valve + PID control as the core program, and improves the response speed through PWM regulation and closed-loop feedback. The current technical bottlenecks are mainly concentrated in the sensor dynamic detection accuracy, model environmental adaptability, and the reliability of the execution parts. In the future, it is necessary to further promote anti-jamming multi-source heterogeneous sensor data fusion, multi-factor adaptive spray model development, lightweight edge computing deployment, and solenoid valve structural parameter optimization and other technical research, with a view to promoting the application of variable-rate spray technology to the field on a large scale and providing a theoretical reference and technological support for the green transformation of agriculture. Full article

Obsessive–compulsive disorder (OCD) is a multifactorial condition, and interest in gut–brain interactions is increasing. We conducted a systematic two-step review, registered in PROSPERO (CRD420251083936). Step 1 mapped core OCD biology to gut-relevant pathways, including neuroimmune activation, epithelial barrier function, microbial metabolites, and stress circuitry, to clarify plausible mechanisms. Step 2 synthesized evidence from human and preclinical studies that measured or manipulated microbiota. Searches across PubMed, EMBASE, Web of Science, PsycINFO, and Cochrane (September 2025) yielded 357 biological and 20 microbiota-focused studies. Risk of bias was assessed using the Joanna Briggs Institute checklist for human studies and SYRCLE’s tool for animal studies. Although taxonomic findings in human cohorts were heterogeneous, functional patterns converged: reduced short-chain fatty acid capacity, enrichment of pro-inflammatory pathways, and host markers of barrier disruption and inflammation correlating with OCD severity. Transferring patient microbiota to mice induced OCD-like behaviors with neuroinflammatory changes, partly rescued by metabolites or barrier-supporting strains. Mendelian randomization suggested possible causal contributions at higher taxonomic levels. Diet, especially fiber intake, and psychotropic exposure were major sources of heterogeneity. Evidence supports the microbiota as a modifiable co-factor in a subset of OCD, motivating diet-controlled, stratified clinical trials with composite host–microbe endpoints. Full article

To address the challenges of short dwell time near top dead center (TDC) and uneven heat release, this paper presents a comprehensive analysis of the effects of different ignition schemes on combustion characteristics, flame formation and development, and emissions. A three-dimensional model of coupled reaction’s kinetic mechanism was established using Converge 3.0 and validated by experimental data. The results show that ignition position, whether synchronous or asynchronous changes, significantly influence pressure. The pressure in synchronous cases can reach up to 62.5 bar, representing a 10.8% increase, exhibiting a distinct upward trend with advanced ignition position. In asynchronous cases, the pressure variation shows a distinct nonlinear characteristic due to the negative effects of in-cylinder airflow and flame core collision. When the ignition position is advanced, the ignition delay increases for both synchronous and asynchronous strategies. However, for synchronous cases, the combustion duration is reduced by up to 1.5 ms, whereas for asynchronous cases, the reduction is only 0.135 ms. Regardless of the schemes, the layout and the strong counterclockwise swirl lead to the flame core gradually developing from right to left, ultimately engulfing the left-side flame core. Compared then to that case, the left and right flame kernels may collide prematurely, leading to incomplete local combustion and consequently reducing combustion efficiency. Compared to synchronous changes, the emission differences during asynchronous changes are smaller and maintained at a relatively low level. Full article

The aryl hydrocarbon receptor (AHR), a ligand-activated transcription factor, plays a crucial role in regulating immune homeostasis, inflammatory responses, and intestinal barrier function. Indole compounds and their derivatives are ligands of AHR, which can activate the AHR signal transduction pathway and show significant regulatory potential in various inflammatory and immune diseases. Cystic fibrosis (CF) is a life-threatening autosomal recessive genetic disorder. Cystic fibrosis transmembrane conductance regulator (CFTR) dysfunction affects multiple systems throughout the body. The core of its pathological process is chronic infection, abnormal inflammation, and tissue damage caused by mucus accumulation. Exploring alternative or adjunctive therapeutic strategies targeting pathological pathways downstream of CFTR is of significant importance. The aim of the present study is to explore the multiple beneficial effects that indole compounds may exert in regulating pulmonary infection and inflammation, repairing intestinal barrier function, and regulating immune homeostasis in CF patients by activating the AHR signaling pathway. Additionally, this study discusses the risks and challenges associated with developing indole compounds as CF drugs, offering a novel research approach distinct from traditional CFTR modulators for creating new CF therapeutics. Full article

Reinforced composite prestressed concrete hollow square (RCPHS) piles, installed through pre-drilling, grouting, and static jacking, integrate the large lateral contact area of cement–soil casings with the high strength and stiffness of prestressed concrete cores. This study combines full-scale vertical static load tests and finite-element (FE) simulations to explore the interaction among the core pile, plain-concrete casing, and surrounding soil. Results show that, at 3600 kN, RCPHS piles exhibit 76% less pile-head settlement compared to PHS piles, and a 36.5% reduction in pile-material expenditure is achieved using the RCPHS scheme. At the same settlement of 23 mm, RCPHS piles carry 87% more load than PHS piles. A 3D FE model developed in ABAQUS reveals that the core pile carries approximately 94% of the applied load. When the load exceeds 4180 kN, the axial force in the casing sharply increases at depths of 7–10 m. The simulated P–s curves align well with field measurements, confirming model accuracy. The superior performance of RCPHS piles is attributed to the graded elastic modulus and coordinated stress distribution of the core–casing–soil system, which enhances interface friction and overall load capacity. These findings provide a foundation for the design optimization of RCPHS piles in dense sandy foundations. Full article

To meet the increasing demands of energy efficiency and real-time performance in autonomous driving systems, this paper presents a lightweight and robust LiDAR SLAM framework designed with power-aware considerations. The proposed system introduces three core innovations. First, it replaces traditional ordered point cloud indexing with a 2D range image projection, significantly reducing memory usage and enabling efficient feature extraction with curvature-based criteria. Second, a multi-stage outlier rejection mechanism is employed to enhance feature robustness by adaptively filtering occluded and noisy points. Third, we propose a dynamically filtered local mapping strategy that adjusts keyframe density in real time, ensuring geometric constraint sufficiency while minimizing redundant computation. These components collectively contribute to a SLAM system that achieves high localization accuracy with reduced computational load and energy consumption. Experimental results on representative autonomous driving datasets demonstrate that our method outperforms existing approaches in both efficiency and robustness, making it well-suited for deployment in low-power and real-time scenarios within intelligent transportation systems. Full article

Driven by the green and low-carbon transformation of urban logistics, the integration of crowdsourced delivery and green transportation is considered an important pathway to achieving sustainable last-mile delivery. This study focuses on urban crowdsourced delivery using cargo bikes and develops an extended behavioral model based on the Theory of Planned Behavior (TPB). The model systematically examines the key factors influencing the public’s behavioral intention (BI) to participate as crowdshippers. While retaining the core structure of TPB, the model incorporates external variables—perceived risk (PR), policy support (PS), and infrastructure conditions (IC)—to improve its explanatory power and applicability to real-world delivery scenarios. A questionnaire survey was conducted in South Korea, yielding 600 valid responses. The results indicate that usage attitude and perceived behavioral control exert significant positive effects on BI. PR has a significant negative effect on both attitude and BI. PS indirectly enhances BI by improving attitudes, whereas IC primarily influences BI by strengthening the public’s sense of control. This study not only expands the theoretical explanatory power of the TPB model in the context of green crowdsourced delivery but also provides empirical evidence for policymakers and platform operators. Full article

This study was focused on addressing the performance degradation in core microstructures of ultra-heavy steel plates (thickness ≥ 50 mm) caused by non-uniform cooling during thermo-mechanical controlled processing. Using microalloyed DH36 steel as the research subject, we systematically investigated the effects of cooling rate on the nucleation and growth of acicular ferrite and its consequent microstructure-property relationships through an integrated approach combining in situ observation via high-temperature laser scanning confocal microscopy with multiscale characterization techniques. Results demonstrate that the cooling rate significantly affects acicular ferrite formation, with the range of 3–7 °C/s being most conducive to acicular ferrite formation. At 5 °C/s, the acicular ferrite volume fraction reached a maximum of 74% with an optimal aspect ratio (5.97). Characterization confirmed that TiOx-Al₂O₃·SiO₂-MnO-MnS complex inclusions act as effective nucleation sites for acicular ferrite, where the MnS outer layer plays a key role in reducing interfacial energy and promoting acicular ferrite radial growth. Furthermore, the interlocking acicular ferrite structure was shown to enhance microhardness by 14% (HV0.1 = 212.5) compared to conventional ferrite through grain refinement strengthening and dislocation strengthening (with a dislocation density of 2 × 10⁸ dislocations/mm²). These results provide crucial theoretical insights and a practical processing window for strengthening-toughening control of heavy plate core microstructures, offering a viable pathway for improving the comprehensive performance of ultra-heavy plates. Full article

In a significant transition from classical theories of efficient markets and perfectly rational investors, the recent literature has increasingly acknowledged the importance of the human element and external market conditions in decision-making. However, the application of adaptive market frameworks in the property sector remains underexplored. This gap is particularly pronounced in the commercial property market, where structural inefficiencies, such as information asymmetry and illiquidity, amplify decision-making complexity. Given that investor rationality tends to diminish as uncertainty and complexity increase, this study explored how private commercial property investors adapt their strategies amid heightened uncertainty. The perspectives of seven experienced property experts were thematically analysed to highlight recurring patterns, which were then integrated into a conceptual mind map. The findings reveal that while economic fundamentals are the constant drivers of capital allocation decisions, investors process these signals through the lens of adaptive behaviour based on intuition, experience, risk perceptions, and herding. This relationship becomes more pronounced under conditions of heightened uncertainty, where investors seek to supplement available information with sentiment due to weaker signals and declining confidence in fundamentals. Sustainable investing and technology integration also emerged as core considerations, but interest among private investors is subdued due to ambiguous value propositions regarding the long-term economic benefits of a green premium. These findings offer practical insights into how external market conditions influence property investment decisions and provide a platform for operational models of investment decision-making that integrate adaptive behaviour. Full article

The influence of stress on gas sorption behavior and sorption-induced swelling in coal is critical for the success of CO₂-enhanced coalbed methane recovery (CO₂-ECBM) and geological carbon sequestration—a key strategy for mitigating climate change and promoting clean energy transitions. However, this influence remains insufficiently understood, largely due to experimental limitations (e.g., overreliance on powdered coal samples) and conflicting theoretical frameworks in existing studies. To address this gap, this study systematically investigates the effects of two distinct stress constraints—constant confining pressure and constant volume—on CO₂ adsorption capacity, adsorption kinetics, and associated swelling deformation of intact anthracite coal cores. An integrated experimental apparatus was custom-designed for this study, combining volumetric sorption measurement with high-resolution strain monitoring via the confining fluid displacement (CFD) method and the confining pressure response (CPR) method. This setup enables the quantification of CO₂–coal interactions under precisely controlled stress environments. Key findings reveal that stress conditions exert a regulatory role in shaping CO₂–coal behavior: constant confining pressure conditions enhance CO₂ adsorption capacity and sustain adsorption kinetics by accommodating matrix swelling, thereby preserving pore accessibility for continuous gas uptake. In contrast, constant volume constraints lead to rapid internal stress buildup, which inhibits further gas adsorption and accelerates the attainment of kinetic saturation. Sorption-induced swelling exhibits clear dependence on both pressure and constraint conditions. Elevated CO₂ pressure leads to increased strain, while constant confining pressure facilitates more gradual, sustained expansion. This is particularly evident at higher pressures, where adsorption-induced swelling prevails over mechanical constraints. These results help resolve key discrepancies in the existing literature by clarifying the dual role of stress in modulating both pore accessibility (for gas transport) and mechanical response (for matrix deformation). These insights provide essential guidance for optimizing CO₂ injection strategies and improving the long-term performance and sustainability of CO₂-ECBM and geological carbon storage projects, ultimately supporting global efforts in carbon emission reduction and sustainable energy resource utilization. Full article

An integrative approach combining network pharmacology, molecular docking, and cellular assays was used to elucidate the potential mechanisms by which the n-butanol extract of Biebersteinia heterostemon ameliorates type 2 diabetes mellitus (T2DM). Chemical constituents of the n-butanol extract were identified via ultra-high-performance liquid chromatography coupled with Q-Exactive Orbitrap mass spectrometry. Active compounds and T2DM-related targets were retrieved from public databases, and intersecting targets were identified. Protein–protein interaction (PPI) networks were constructed using the STRING database, while Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed via the DAVID database. A comprehensive “drug–compound–target–disease–pathway” network was established, and molecular docking was conducted to evaluate binding affinities of key compounds to core targets. Functional validation was performed in insulin-resistant cell models. Network pharmacology analysis identified 37 active constituents within the extract and 222 overlapping targets associated with T2DM. GO enrichment indicated involvement in protein phosphorylation, MAPK cascade activation, and negative regulation of apoptosis. Key signaling pathways included PI3K/AKT and lipid and atherosclerosis pathways. Molecular docking revealed strong binding affinities (binding energies ≤ −9.3 kcal·mol⁻¹) between core compounds—such as cheilanthifoline, glabridin, acetylcorynoline, skullcapflavone II, liquiritigenin, and dinatin—and pivotal targets including GAPDH, AKT1, TNF, SRC, EGFR, and PPARγ. In vitro experiments demonstrated that the extract significantly enhanced glucose uptake and glycogen synthesis in insulin-resistant cells, while suppressing oxidative stress and the expression of pro-inflammatory mediators such as TNF-α, MMP9, and IL-6. Collectively, B. heterostemon shows potential as an effective intervention for T2DM by targeting key molecular pathways, improving insulin sensitivity, and mitigating oxidative stress and inflammation in insulin-resistant cells. Full article

In the context of sustainable forest resource development, balancing ecological conservation with rational utilization is essential to achieving forest multifunctionality. Longyuwan National Forest Park, located in Luanchuan County, Henan Province, serves as a transitional zone between rural mountainous ecosystems and nearby urban settlements. Increasingly, this area faces urbanization pressures such as tourism expansion, infrastructure development, and intensified land use, which may threaten ecological stability. This study aims to evaluate the ecological sensitivity of the park and optimize its spatial functional zoning. Using the Analytic Hierarchy Process (AHP), we followed four key steps: constructing the hierarchical model, generating the pairwise judgment matrices, computing the weights and conducting the consistency check, and determining the final weights. A hierarchical evaluation framework was constructed using the AHP, incorporating twelve ecological indicators across geomorphological, hydrological, atmospheric, biological, and anthropogenic dimensions. Spatial analysis tools in ArcGIS 10.2, including reclassification and weighted overlay, were employed for single-factor and integrated sensitivity assessments. The results indicated that land-use type, elevation, and water-body distribution were the most influential indicators. Ecological sensitivity across the park was categorized into five levels: extremely high (0.02%), high (11.99%), moderate (73.53%), low (14.19%), and extremely low (0.28%). Based on these findings, four functional zones were delineated: ecological conservation (50.99%), core landscape (22.86%), general recreation (23.94%), and management and service (2.21%). This research provides spatially explicit insights into forest management under anthropogenic stress, offering theoretical support for the sustainable governance of forest–urban interface landscapes. Full article