Dongyang University

Resilience pads provide elastic behavior and reduce impact and vibration loads in sleeper floating tracks, but their long-term degradation affects critical track components. Their performance is currently measured using labor-intensive, expensive restricted field sampling and indoor static stiffness testing, which cannot reliably measure entire track sections. The objective of this study was to measure and analyze a rail’s supporting-point reaction force (pressure) using a skin sensor according to the train load (as the force changes with spring stiffness) and the resilience pad spring stiffness of the sleeper floating track. To evaluate the rail-supporting-point reaction force of the sleeper floating track, a skin sensor was installed at the bottom of the concrete sleeper, and the reaction force was measured according to the train load. Laboratory testing demonstrated that resilience pad spring stiffness affects the rail-supporting-point reaction force. Field measurements of the train load were used to examine the sleeper floating track’s supporting-point reaction force and the resilience pad’s spring stiffness, confirming field applicability. Therefore, this innovative skin-sensor-based assessment technique for reaction forces at rail-support points may predict resilience pad replacement and identify anomalies in real time, making it easier to assess performance and diagnose sleeper floating tracks.

This study aimed to develop a methodology to strengthen coordination between ground ambulances and helicopter emergency medical services (EMS) for rapid patient transport. Using data on helicopter EMS infrastructure, crash locations, and prehospital EMS times, safety assessments and geographic information system (GIS)-based network analyses were conducted to identify service gaps and prioritize infrastructure expansion. Results showed that EMS stations and heliports near high-fatality crash locations were insufficient to meet prehospital EMS time thresholds. To address this, a three-dimensional virtual space platform combining GIS-based spatial modeling with real-time visualization was developed for training ground and air ambulance operators. This platform realistically simulates patient transport scenarios, enhancing decision-making, and collaboration. The findings provide a data-driven framework for optimizing helicopter EMS infrastructure and developing practical training tools, offering policymakers quantitative evidence to improve EMS accessibility and promote effective strategies for timely patient transport.

Tomato spotted wilt virus (TSWV) is a highly destructive plant pathogen transmitted by thrips, including Frankliniella occidentalis, in a circulative and propagative manner. To counter viral infections, thrips activate antiviral defences through C20 oxygenated polyunsaturated fatty acids (PUFAs), known as eicosanoids. However, at later stages of infection, C18 PUFAs, including epoxyoctadecamonoenoic acids (EpOMEs), modulate immune responses by preventing excessive and unnecessary activation. Our previous study demonstrated that TSWV elevates EpOME levels in thrips to suppress antiviral responses and enhance viral replication, with its nonstructural protein S (NSs) playing a key role in this process. In this study, we investigated the impact of NSs protein variation on vector immunity and virus–vector interactions. We assessed relative TSWV titres in thrips larvae and examined the role of eicosanoids, specifically 12,13-EpOME and PGE2, in regulating viral load and apoptosis. Our results revealed that 12,13-EpOME significantly increased viral titres, whereas PGE2 reduced the viral accumulation by promoting apoptosis in the vector insect. Phylogenetic analysis identified distinct NSs variations among TSWV isolates, with resistance-breaking (RB) and WT strains, which modulated differential infection patterns in thrips gut tissues, as visualized through fluorescence in situ hybridization. RB strains exhibited significantly higher viral titres, along with increased expression of EpOME biosynthetic gene (Fo-CYP24) and decreasing expression of EpOME degradation gene (Fo-sEH2). Apoptosis assays using the terminal deoxynucleotidyl transferase dUTP nick-end labelling assay further indicated that RB strains suppressed the gut epithelial cell death in thrips by antagonizing a process regulated by PGE2. Additionally, in vivo transient expression of the NSs gene in a nontarget insect, Spodoptera exigua, demonstrated the immunosuppressive effects by inducing EpOME level through upregulation of Se-CYP expression and downregulation of Se-sEH expression. Indeed, RB strains suppressed cellular immune responses more effectively than WT strains in S. exigua. These findings provide novel insight into the role of NSs genetic variation in TSWV transmission in the insect vector as well as in the host plants.

Background and Objectives: The prognostic immune and nutritional index (PINI) was reported to be clinically relevant for colorectal cancer prognosis. Herein, the utility of PINI as a prognostic factor for the survival of patients with gastric cancer (GC) was investigated. Materials and Methods: We retrospectively analyzed 492 patients with stage I–III GC, predominantly of Asian descent, who underwent curative-intent gastrectomy. Multivariate Cox regression analysis identified independent predictors of overall survival (OS). Model performance was evaluated using the concordance index (C-index), integrated area under the curve (iAUC), time-dependent AUC, integrated discrimination improvement (IDI), and continuous net reclassification improvement (cNRI). Results: The PINI score—calculated as [albumin (g/dL) × 0.9] − [absolute monocyte count (/μL) × 0.0007]—was found to be independently associated with OS (p < 0.001). Additional independent prognostic factors included age, body mass index, 5-factor modified frailty index, tumor–node–metastasis (TMN) stage, gastrectomy type, and anemia. The full model that included all significant covariates outperformed the baseline TNM model, showing significantly higher C-index and iAUC values (both p < 0.001). Compared with an intermediate model, which excluded PINI, the full model demonstrated a superior C-index and iAUC (both p = 0.004). Although the observed improvements in AUC, IDI, and cNRI at 3 years were not statistically significant, the full model achieved significant gains in all three metrics at 5 years, underscoring the added long-term prognostic value of the PINI. Conclusions: PINI is a significant independent predictor of survival in patients with GC who underwent curative-intent surgery. Its inclusion in prognostic models enhances the long-term predictive accuracy for survival, supporting its potential role in guiding personalized postoperative management. External validation in larger multi-ethnic prospective cohorts is essential to confirm its generalizability and to establish its role in routine clinical practice.

BackgroundHeat-related illness is a significant occupational hazard requiring effective prevention. The World Health Organization emphasizes that reducing a worker's ability to perform tasks due to extreme heat or cold is a "health effect" of climate conditions. This study proposes a novel safety management approach in construction to prevent heatstroke among workers using thermochromic fibers that change color in response to body temperature, enabling the visual detection of rising heat levels.ObjectiveThis study evaluated the visibility and contrast of blue and pink (red spectrum) fibers at different distances. The hypothesis was that workers could help prevent heat-related illnesses by monitoring the color changes in their clothing.MethodsThe study involved visibility and contrast tests of garments dyed with thermochromic pigments, observed at different distances. Data analysis was conducted using ANOVA and regression analysis.ResultsThe findings indicate that while blue fibers initially have higher visibility, their visibility diminishes more rapidly with distance than pink fibers. Owing to psychological associations, pink fiber may be more effective in heat stroke safety management.ConclusionsSelecting appropriate colors for thermochromic fibers enhances their effectiveness as safety indicators. Additionally, empowering workers to monitor each other through visual cues may improve safety outcomes, representing a shift from traditional management methods.

In convolutional neural networks (CNN), the problem of heat generation is becoming a significant issue. This challenge can be mitigated through both hardware and software methods. This study focuses on drastically reducing the amount of computations and, consequently, the heat generation. Specifically, the proposed approach reduces computations by approximately $m \times 2^n$, where $m$ is the number of layers and $n$ is the size of the node.

Colorectal cancer (CRC) is a form of cancer that impacts both the rectum and colon. Typically, it begins with a small abnormal growth known as a polyp, which can either be non-cancerous or cancerous. Therefore, early detection of colorectal cancer as the second deadliest cancer after lung cancer, can be highly beneficial. Moreover, the standard treatment for locally advanced colorectal cancer, which is widely accepted around the world, is chemoradiotherapy. Then, in this study, seven artificial intelligence models including decision tree, K-nearest neighbors, Adaboost, random forest, Gradient Boosting, multi-layer perceptron, and convolutional neural network were implemented to detect patients responder and non-responder to radiochemotherapy. For finding the potential predictors (genes), three feature selection strategies were employed including mutual information, F-classif, and Chi-Square. Based on feature selection models, four different scenarios were developed and five, ten, twenty and thirty features selected for designing a more accurate classification paradigm. The results of this study confirm that random forest, Gradient Boosting, decision tree, and K-nearest neighbors provided more accurate results in terms of accuracy, by 93.8%. Moreover, Among the feature selection methods, mutual information and F-classif showed the best results, while Chi-Square produced the worst results. Therefore, the suggested artificial intelligence models can be successfully applied as a robust approach for classification of colorectal cancer response to radiochemotherapy for medical studies.

In this study, numerical analysis using FDS was conducted to analyze the effect of the opening configuration of the compartment on the formation of the ejected flame and thermal radiation characteristics outside the compartment. After validating the analysis by comparisons with previous experimental results for the 2/5 scaled ISO 9705 standard compartment, numerical calculations were performed by altering the aspect ratio of the opening and the position from the bottom surface. At a fire heat release rate of 341 kW, the flame ejected from the standard-sized opening generated a heat flux that exceeded the critical value of general combustibles on a wall 1 m away. When the width of the opening was reduced to 1/4, the flow of the ejected flame bent toward the upper wall, generating a maximum heat flux that was more than three times higher than that of the standard opening.