Search Results (371)

This study investigates the factors influencing school trip mode choice among senior high school students in the Chiang Rai urban area, Chiang Rai, Thailand, under normal and adverse weather conditions. Utilizing data from 472 students across six extra-large urban schools, a Multinomial Logit (MNL) regression model was applied to examine the effects of socio-demographic attributes, household vehicle ownership, travel distance, and spatial variables on mode selection. The results revealed notable modal shifts during adverse weather, with motorcycle usage decreasing and private vehicle reliance increasing, while school bus usage remained stable, highlighting its role as a resilient transport option. Car ownership emerged as a strong enabler of modal flexibility, whereas students with limited access to private transport demonstrated reduced adaptability. Additionally, increased waiting and travel times during adverse conditions underscored infrastructure and service vulnerabilities, particularly for mid-distance travelers. The findings suggest an urgent need for transport policies that promote inclusive and climate-resilient mobility systems, particularly in the context of Chiang Rai, including expanded school bus services, improved first-mile connectivity, and enhanced pedestrian infrastructure. This study contributes to the literature by addressing environmental variability in school travel behavior and offers actionable insights for sustainable transport planning in secondary cities and border regions. Full article

In the design of multiprocessor systems, evaluating the reliability of interconnection networks is a critical aspect that significantly impacts system performance and functionality. When quantifying the reliability of these networks, extra connectivity and extra diagnosability serve as fundamental metric parameters, offering valuable insights into the network’s resilience and fault-handling capabilities. In this paper, we investigate the 1-extra connectivity and 1-extra diagnosability of the n-dimensional enhanced folded hypercube-like network. Through analysis, we show that the 1-extra connectivity of this network is $2n+2$. Moreover, for $n>5$, we determine its 1-extra diagnosability under both the PMC model and the MM${}^{\ast }$ model to be $2n+3$. These results show that as the dimension n increases, both the 1-extra connectivity and 1-extra diagnosability of the network approach approximately twice the value of traditional diagnosability metrics. This provides quantitative insights into the reliability properties of the enhanced folded hypercube-like network, contributing to a better understanding of its performance in terms of connectivity and fault diagnosis. Full article

To study the optimization of construction parameters and schemes for complex connecting tunnels in extra-long highway tunnels in granite strata, the research team, relying on the construction project of the complex connecting tunnel between the Xiaolongmen Extra-long Highway Tunnel and the ultra-deep shaft, established an on-site monitoring scheme and a refined numerical simulation model. It systematically analyzed the impact of various construction parameters on the construction process of connecting tunnels and the main tunnel, and on this basis, optimized the construction scheme, improving construction efficiency. The research results show that (1) after the excavation of the connecting tunnel, the confining pressure at the top of the working face decreases rapidly, while the confining pressure on both sides increases rapidly; the extreme point of the confining pressure decrease is located at the central point at the top of the excavated working face. (2) For Class III surrounding rock excavated using the full-face blasting method, the maximum influence range of working face excavation on the stratum along the tunneling direction is approximately 4D (where D represents the excavation step). (3) The larger the excavation step of the connecting tunnel, the more obvious the stress concentration phenomenon at the central point of the working face arch crown, and the excavation step should be optimally controlled within the range of 2–3 m. (4) When explosives in the blast hole adopt decoupled charging, the ratio of borehole diameter to charge diameter can be increased to utilize the air gap to buffer the energy generated by the explosion. Full article

Federated learning (FL) has emerged as a powerful approach for privacy-preserving model training in autonomous vehicle networks, where real-world deployments rely on multiple roadside units (RSUs) serving heterogeneous clients with intermittent connectivity. While most research focuses on single-server or hierarchical cloud-based FL, multi-server FL can alleviate the communication bottlenecks of traditional setups. To this end, we propose an edge-based, multi-server FL (MS-FL) framework that combines performance-driven aggregation at each server—including statistical weighting of peer updates and outlier mitigation—with an application layer handover protocol that preserves model updates when vehicles move between RSU coverage areas. We evaluate MS-FL on both MNIST and GTSRB benchmarks under shard- and Dirichlet-based non-IID splits, comparing it against single-server FL and a two-layer edge-plus-cloud baseline. Over multiple communication rounds, MS-FL with the Statistical Performance-Aware Aggregation method and Dynamic Weighted Averaging Aggregation achieved up to a 20-percentage-point improvement in accuracy and consistent gains in precision, recall, and F1-score (95% confidence), while matching the low latency of edge-only schemes and avoiding the extra model transfer delays of cloud-based aggregation. These results demonstrate that coordinated cooperation among servers based on model quality and seamless handovers can accelerate convergence, mitigate data heterogeneity, and deliver robust, privacy-aware learning in connected vehicle environments. Full article

Background/Objectives: Despite extensive research, the underlying causes of amyotrophic lateral sclerosis (ALS) remain unclear. This umbrella review aims to synthesize a vast body of evidence from advanced magnetic resonance imaging (MRI) studies of ALS, encompassing a wide range of neuroimaging techniques and patient cohorts. Methods: Following the PRISMA guidelines, we conducted an extensive search of four databases (PubMed, Scopus, Web of Science, and Embase) for articles published until 3 December 2024. Data extraction and quality assessment were independently performed using the AMSTAR2 tool. Results: This review included 18 studies that incorporated data from over 29,000 ALS patients. Structural MRI consistently showed gray matter atrophy in the motor and extra-motor regions, with significant white matter (WM) atrophy in the corticospinal tract and corpus callosum. Magnetic resonance spectroscopy revealed metabolic disruptions, including reduced N-acetylaspartate and elevated choline levels. Functional MRI studies have demonstrated altered brain activation patterns and functional connectivity, reflecting compensatory mechanisms and neurodegeneration. fMRI also demonstrated disrupted motor network connectivity and alterations in the default mode network. Diffusion MRI highlighted microstructural changes, particularly reduced fractional anisotropy in the WM tracts. Susceptibility-weighted imaging and quantitative susceptibility mapping revealed iron accumulation in the motor cortex and non-motor regions. Perfusion MRI indicated hypoperfusion in regions associated with cognitive impairment. Conclusions: Multiparametric MRI consistently highlights widespread structural, functional, and metabolic changes in ALS, reflecting neurodegeneration and compensatory mechanisms. Full article

Agrobiodiversity decline depends on wider-scale landscape ecological traits. Studying inter-scale patterns helps in understanding context-specific farm-scale biodiversity issues and needs. In this study, we investigated the drivers of agrobiodiversity in four Po Plain sites (northern Italy), an intensively impacted agricultural district. Farm-scale floristic–vegetational indicators reflecting anthropic disturbance (biological forms, chorological traits, and maturity traits) were studied for their relationship with species richness and phytocoenosis α-diversity values. Their correlation with local- and extra-local-scale landscape ecology traits was also studied. Species richness and α-diversity were negatively related to floristic contamination and therophytes; they tended to increase with the Eurasiatic and phanerophyte ratio, suggesting a role of disturbance conditions on diversity values. Extra-local/local scale showed similar relationships with farm-scale floristic–vegetational traits; correlation was higher for local scale. Species richness and α-diversity tended to increase with higher landscape natural components, landscape diversity, biological territorial capacity, and connectivity. These landscape traits also tended to be positively related to Eurasiatic, hemicryptophyte, chamaephyte, phanerophyte, and maturity values, while they were negatively related to adventitious, wide distribution, aliens, and therophytes. Corridors’ ecological quality apparently influenced disturbance-related species amount. Maps representing these inter-scale biodiversity facets are provided (land-use-based support ecosystem service maps integrated with landscape diversity maps). The detected patterns orient context-specific multi-scale biodiversity support. They confirm the theoretical frameworks and should be validated on wider datasets to strengthen their representativeness. Full article

The dual effects of work connectivity behavior after-hours (WCBA) on employees’ in-role and extra-role behaviors were investigated using the framework of the Job Demands–Resources (JD-R) model. A two-wave cross-sectional design with a one-week interval was employed, and data were acquired from a survey of 402 Chinese employees. The results showed that WCBA positively influenced in-role and extra-role behaviors through enhanced psychological job control (β = 0.1908 and β = 0.1356, respectively), while also exerting negative effects via increased ICT anxiety (β = −0.0190 and β = −0.0434, respectively). The findings indicate that although WCBA can foster work outcomes through increased job control, it also carries the risk of undermining these benefits due to the psychological strain from ICT-related stress. Therefore, organizations should support employees in managing WCBA effectively by balancing potential productivity gains with an awareness of its psychological costs. This research uniquely provides a simultaneous investigation of both behavior types within a unified dual-pathway framework based on the Job Demands–Resources (JD-R) model. This research also extends our knowledge of the nuanced influence of after-hours connectivity and has potential application in the optimization of the performance and welfare of employees in digitally connected work environments. Full article

Extra edge connectivity is an important parameter for measuring the reliability of interconnection networks. Given a graph G and a non-negative integer h, the h-extra edge connectivity of G, denoted by ${\lambda }_h\left(G\right)$, is the minimum cardinality of a set of edges in G (if it exists) whose deletion disconnects G such that each remaining component contains at least $h+1$ vertices. In this paper, we obtain the h-extra edge connectivity of Cayley graphs generated by transposition trees for $h\le 5$. As byproducts, we derive the h-extra edge connectivity of the star graph $S_n$ and the bubble-sort graph $B_n$ for $h\le 5$. Full article

Analyzing network connectivity is important for evaluating the robustness, efficiency, and overall performance of various architectural designs. By examining the intricate interactions among nodes and their connections, researchers can determine a network’s resilience to failures, its capacity to support efficient information flow, and its adaptability to dynamic conditions. These insights are critical across multiple domains—such as telecommunications, computer science, biology, and social networks—where optimizing connectivity can significantly enhance functionality and reliability. In the literature, there are many variations of connectivity to measure network resilience and fault tolerance. In this survey, we focus on connectivity, tightly super connectivity, and h-extra connectivity within DVcube networks—a compound architecture combining disk-ring and hypercube-like topologies. Additionally, we identify several open problems to encourage further exploration in future research. Full article

Understanding population genetic connectivity is crucial for the sustainability and persistence of marine biodiversity. As a fundamental reef-building macroalga of the coastal ecosystem, Halimeda macroloba Decaisne is one of the dominant intertidal seaweeds in the Indo-Pacific region. However, its genetic structure and population connectivity have been poorly recognized. Here, we explored the population genetic structure and genetic connectivity of H. macroloba using chloroplast tufA, rps3-rpl14, and rbcL. Our results indicated low genetic diversity and shallow population genetic structure at the intraspecific level, uncovering five genetic groups with six subdivided lineages in tufA and two genetic clusters in rps3-rpl14. We detected demographic expansion in the last glacial period of the Pleistocene and significantly asymmetric gene flow among different geographical units. We suggest that the southwestward ocean currents under the influence of northeast monsoon in the Indo-Pacific region are the main factor in shaping the present genetic structure, and the asexual reproduction of H. macroloba also plays an important role of the low genetic diversity pattern; in addition, the divergence between genetic clusters might be related to the historical isolation led by the paleoclimate oscillation in the Pleistocene. The Xisha Islands in the northern South China Sea might serve as a potential refugium of H. macroloba, which needs extra attention to conservation management. Given the limitation of sample size, we need to conduct more field work and carry out further research at a larger scale in the future. Our study provided new insights into the theory of population connectivity in the Indo-Pacific region and provided scientific basis for tropical costal seaweed conservation. Full article

Maritime relay communication has emerged as a critical application scenario for non-terrestrial networks (NTNs), providing beyond-line-of-sight (BLOS) connectivity for offshore terminals. Unlike terrestrial environments, the complex marine propagation conditions lead to signal instability. To enhance the robustness of maritime two-way relay networks (TWRNs), we propose a novel physical-layer network coding (PNC) scheme based on block Markov superposition transmission (BMST). The proposed scheme introduces a novel co-design framework that achieves dual breakthroughs: (1) robust error correction via BMST’s spatially coupled coding architecture and (2) spectral efficiency maximization through PNC’s spatial-domain signal superposition. Moreover, we develop a decoding–computing (DC) algorithm that sequentially performs iterative decoding followed by computing. Compared to the computing–decoding (CD) algorithm, the proposed DC algorithm mitigates useful information loss at relay nodes, achieving a 2.9 dB coding gain at a bit error rate (BER) of ${10}^{-5}$. Owing to the DC algorithm’s dual-layer decoding architecture, we can further improve the overall system performance through targeted optimization of either the code rate or memory size for communication sides with poor channel conditions, yielding an extra 0.2 dB gain at a BER of ${10}^{-5}$ compared to non-optimized configurations. The simulation results demonstrate that the proposed scheme significantly enhances maritime relay communication performance under harsh oceanic channel conditions while providing actionable insights for optimizing next-generation maritime communication system designs. Full article

An interconnection network is usually modeled by a graph, and fault tolerance of the interconnection network is often measured by connectivity of the graph. Given a connected subgraph L of a graph G and non-negative integer t, the t-extra connectivity ${\kappa }_t\left(G\right)$, the L-structure connectivity $\kappa (G;L)$ and the t-extra L-structure connectivity ${\kappa }_g(G;L)$ of G can provide new metrics to measure the fault tolerance of a network represented by G. Fully connected cubic networks ${\mathcal{FC}}_n$ are a class of hierarchical networks which enjoy the strengths of a constant vertex degree and good expansibility. In this paper, we determine ${\kappa }_t\left({\mathcal{FC}}_n\right)$, $\kappa ({\mathcal{FC}}_n;L)$ and ${\kappa }_t({\mathcal{FC}}_n;L)$ for $t=1$ and $L\in \{K_{1,1},K_{1,2},K_{1,3}\}$. We also establish the edge versions ${\lambda }_t\left({\mathcal{FC}}_n\right)$, $\lambda ({\mathcal{FC}}_n;L)$ and ${\lambda }_t({\mathcal{FC}}_n;L)$ for $t=1$ and $L\in \{K_{1,1},K_{1,2}\}$. Full article

Bicuspid aortic valve (BAV) and thoracic aortic aneurysms and dissections (TAAD) are recognized in syndromic connective tissue diseases (CTD), but most cases occur sporadically. The extent to which non-syndromic BAV or TAAD predisposes to additional arteriopathies, particularly in younger individuals, remains unclear. We retrospectively analyzed 1438 patients (mean age = 48.0, 67.7% female), excluding those with CTDs. Participants were ≤60 years old and categorized by the presence of BAV and/or TAAD. We examined co-existing arterial pathologies, including fibromuscular dysplasia, spontaneous coronary artery dissection, abdominal aortic aneurysms (AAA), mesenteric, peripheral extremity, and carotid/cerebral arteriopathies. Overall, 44.6% had either BAV or TAAD, and 27.2% had multiple arteriopathies. While vascular diseases were frequently noted, odds ratios demonstrated no significantly increased risk of extra-aortic arteriopathies in the BAV or TAAD cohorts. AAA exhibited a non-significant trend toward higher prevalence in TAAD patients. These findings support current guidelines recommending targeted imaging (transthoracic echocardiography of the aortic root and ascending aorta) over comprehensive “head-to-pelvis” screening for non-syndromic BAV or TAAD patients without additional risk factors. Ongoing genetic analyses may elucidate whether particular variants predispose to multi-site aneurysms or dissections. Consequently, targeted surveillance remains appropriate, with broader imaging reserved for patients with genetic or clinical indicators of higher risk. Full article

Background/Objectives: The structural integrity and strength of the transgingival soft tissue seal around dental implant surfaces remain critical challenges. Therefore, animal models should include all three implant/tissue interfaces: bone, connective tissue, and epithelium. Thus, we sought to explore the rabbit mandibular diastema as a site for candidate intra-oral implant placement. Methods: Ninety-six custom mini-implants (with one of four different surfaces: machined, acid-etched, and with or without a nanotube coating) made from titanium 6/4 alloy were placed in the mandibular diastemas of twenty-four 16-week-old New Zealand white rabbits, with the implant collar above the alveolar crest. After 7, 21, and 42 days, the bony and connective tissue/implant interfaces were examined by light and scanning electron microscopy (SEM). Results: Of ninety-six implants, eight implants were found exposed to the oral cavity, with no evidence of soft tissue inflammation, suggesting that transmucosal implant placement would have been feasible. No significant differences were observed in collagen fiber orientation and fibrous tissue thickness by polarized light microscopy. However, SEM images showed that at all three time points, topographically complex nanotube surfaces had a profound effect on soft tissue peri-implant deposition, although functionally oriented collagen fibers were not identified attached to the implant surface. These surfaces also showed reparative peri-implant bone in the collar region. An intramembranous form of de novo bone formation was observed, together with tartrate-resistant acid-phosphatase-positive osteoclasts and multinucleate giant cells in the peri-implant endosseous compartment. Conclusions: Our results demonstrate that the rabbit mandibular diastema provides an intra-oral method of implant placement without the necessity of an extra-oral approach, tooth extractions, or bone augmentation procedures. Furthermore, given that three implant tissue interfaces can potentially be studied (bone, connective tissue, and epithelium) this model provides advantages over more traditional implant placement sites in the appendicular skeleton. Full article

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as mean absolute error (MAE), root mean square error (RMSE), and R-squared. The future forecast is compared with an outcome of a previous physical model that integrates wells and reservoir properties to simulate gas production using regressions and forecasts based on empirical and theoretical relationships. Regression analysis ensures alignment between historical data and model predictions, forming a baseline for hybrid model performance evaluation. The results reveal the complementary attributes of these methodologies, providing insights into integrating data-driven and physics-based approaches for optimal reservoir management. The hybrid model captured the production rate conservatively with an extra margin of three years in favor of the physical model. Full article