Search Results (33,735)

As urbanization advances, rural construction and resource development in China encounter significant challenges, leading to the widespread adoption of standardized planning and design methods to manage increasing population pressure. These uniform approaches often prioritize economic benefits over climate adaptability and energy efficiency. This paper addresses this issue by focusing on traditional mountain villages in northern regions, particularly examining the wind and thermal environments of courtyards and street networks. This study integrates energy consumption and comfort performance analysis early in the planning and design process, utilizing Genetic and XGBoost algorithms to enhance efficiency. This study began by selecting a benchmark model based on simulations of courtyard PET (Physiological Equivalent Temperature) and MRT (mean radiant temperature). It then employed the Wallacei_X plugin, which uses the NSGA-II algorithm for multi-objective genetic optimization (MOGO) to optimize five energy consumption and comfort objectives. The resulting solutions were trained in the Scikit-learn machine learning platform. After comparing machine learning models like RandomForest and XGBoost, the highest-performing XGBoost model was selected for further training. Validation shows that the XGBoost model achieves an average accuracy of over 80% in predicting courtyard performance. In the project’s validation phase, the overall street network framework of the block was first adjusted based on street performance prediction models and related design strategies. The optimized model prototype was then integrated into the planning scheme according to functional requirements. After repeated validation and adjustments, the performance prediction of the village planning scheme was conducted. The calculations indicate that the optimized planning scheme improves overall performance by 36% compared with the original baseline. In conclusion, this study aimed to integrate performance assessment and machine learning algorithms into the decision-making process for optimizing traditional village environments, offering new approaches for sustainable rural development. Full article

Background/Objectives: The prolonged time to reach investigation and management decisions in non-small cell lung cancer (NSCLC) patients can negatively impact long-term outcomes. This retrospective cohort study aims to assess the impact of a multidisciplinary team conference (MDT) on NSCLC care quality and outcomes. Methods: This retrospective study included resectable NSCLC patients who underwent pulmonary resection at Chiang Mai University Hospital, Thailand, from 1 January 2009 to 31 December 2021. Patients were divided into two groups: non-MDT and MDT groups, based on the initiation of MDT on 1 March 2018. The study compared overall survival, disease-free survival, and waiting times for investigation and surgery between the two groups. The effect of MDT on these outcomes was analyzed using multivariable analysis with inverse-probability weighting propensity scores. Results: The study included 859 patients, with 583 in the non-MDT group and 276 in the MDT group. MDT groups had a higher proportion of stage I and II NSCLC patients undergoing pulmonary resection (78.6% vs. 59.69%, p < 0.001). In multivariable analysis, patients in the MDT group had a significantly higher likelihood of longer survival compared to the non-MDT group (adjusted HR 0.23, 95% CI 0.09–0.55). Median waiting times for bronchoscopy (3 days vs. 12 days, p = 0.012), pathologic report (7 days vs. 13 days, p < 0.001), and surgery scheduling (18 days vs. 25 days, p = 0.001) were significantly shorter in the MDT group. Conclusions: An MDT has a survival benefit in NSCLC care and improves waiting times for investigation and treatment steps. Further studies are needed to validate these results. Full article

The implementation of morphing wing mechanisms shows significant potential for improving aircraft performance, as highlighted in the recent literature. The Clean Sky 2 AirGreen 2 European project team is currently performing ground and wind tunnel tests to validate improvements in morphing wing structures. The project aims to demonstrate the effectiveness of these morphing designs on a full-scale flying prototype. This article describes the design methodology and structural testing of a scaled morphing-flap structure, which can adapt to three different morphing modes for various flight conditions: low-speed (take-off and landing) and high-speed (cruise). A scale factor of 1:3 was selected for the wind tunnel test campaign. Due to challenges in scaling the embedded mechanisms and actuators necessary for shape-changing, a full geometrical scale of the real flap prototype was not feasible. Static analyses were performed using the finite element method to address critical load conditions determined through three-dimensional computational fluid dynamic (CFD) analysis. The finite element (FE) analysis was conducted and the results were compared with the empirical data from the structural test. Good correlations were found between the structural testing results and numerical predictions, including static deflections and elastic deformations under applied loads. This indicates that the modeling approaches used during the design and testing phases were highly successful. Based on simulations for the ultimate load conditions tested during the wind tunnel tests, the scaled flap prototype has been deemed suitable for further testing. Full article

Vehicle scanning methods are gaining popularity because of their ability to identify modal properties of several bridges with only one instrumentation setup, and several methods have been proposed in the last decade. In the numerical models used to develop and validate such methods, bridge damping is often overlooked, and its impact on the efficacy of vehicle scanning methods remains unknown. The present article addresses this knowledge gap by systematically investigating the effects of bridge damping on the efficacy of vehicle scanning methods in identifying the modal properties of bridges. For this, acceleration responses obtained from a numerical model of a bridge and vehicle are used. Four different scenarios are considered where vehicle damping, presence of road roughness, and traffic on the bridge are varied. Bridge damping is modeled using mass-proportional, stiffness-proportional, and Rayleigh damping models. The impacts of ignoring bridge damping or considering one of these damping models on the modal frequencies and mode shapes identified using the vehicle response are investigated by comparing the results. The outcomes of the numerical analysis show that ignoring bridge damping in vehicle scanning applications can significantly increase the efficacy of these methods. They also show that the identifiability of the bridge frequencies and bridge mode shapes from the vehicle response decreases significantly when bridge damping is considered. Further, the damping model used impacts which bridge modes can be identified because different damping models provide different modal damping ratios for each mode. The results highlight the importance of correctly simulating damping behavior of bridges, which is often ignored, to be able to correctly evaluate the efficacy of vehicle scanning methods, and they provide an important stepping stone for future studies in this field. Full article

The purpose of this paper is to accurately establish a model of a special vehicle driven by in-wheel motors (IWMs) and investigate its dynamic characteristics. This study proposes a novel integrated vehicle modeling strategy, focusing on the IWM and other key subsystems. Based on this strategy, the vehicle model is developed and simulated in ADAMS. The natural frequencies of the vehicle and transmission characteristics of key components are compared with MATLAB simulation results to validate the accuracy of the model. In the time-domain analysis, the vehicle system’s time-domain characteristics are obtained by using random road spectra of different road grades as excitations. Our simulation results demonstrate that vibration input can be reduced by between 97% and 99% after multi-stage vibration reduction. This work will provide relevant parameters for the design of special vehicles driven by IWMs. Full article

Reanalysis and satellite retrieval are two primary approaches for obtaining large-scale and long-term Aerosol Optical Depth (AOD) datasets. This study evaluates and compares the accuracy, long-term stability, and error characteristics of the MERRA-2, MODIS combined Dark Target and Deep Blue (DT&DB), and VIIRS DB AOD products globally and regionally. The results indicate that the MERRA-2 AOD exhibits the highest accuracy with an expected error (EE, ±0.05 ± 20%) of 83.24% and mean absolute error (MAE) of 0.056, maintaining a stability of 0.010 per decade. However, since the MERRA-2 AOD ceased assimilating observations other than the MODIS AOD in 2014, its accuracy decreased by approximately 5.6% in the EE metric after 2014. The VIIRS Deep Blue (DB) AOD product, with an EE of 79.43% and stability of 0.016 per decade, is slightly less accurate and stable compared to the MERRA-2 AOD. The MODIS DT&DB AOD demonstrates an EE of 76.75% and stability of 0.011 per decade. Regionally, the MERRA-2 AOD performs acceptably in most areas, especially in low-aerosol-loading regions, with an EE > 86% and stability ~0.02 per decade. The VIIRS DB AOD excels in high-aerosol-loading regions, such as the Indian subcontinent, with an EE of 69.14% and a stability of 0.049 per decade. The performance of the MODIS DT&DB AOD falls between that of VIIRS DB and MERRA-2 across most regions. Overall, each product meets the accuracy and stability metrics globally, but users need to select the appropriate product for analysis based on the validation results of the accuracy and stability in different regions. Full article

Anoikis is a distinct type of programmed cell death and a unique mechanism for tumor progress. However, its exact function in gastric cancer (GC) remains unknown. This study aims to investigate the function of anoikis-related lncRNA (ar-lncRNA) in the prognosis of GC and its immunological infiltration. The ar-lncRNAs were derived from RNA sequencing data and associated clinical information obtained from The Cancer Genome Atlas. Pearson correlation analysis, differential screening, LASSO and Cox regression were utilized to identify the typical ar-lncRNAs with prognostic significance, and the corresponding risk model was constructed, respectively. Comprehensive methods were employed to assess the clinical characteristics of the prediction model, ensuring the accuracy of the prediction results. Further analysis was conducted on the relationship between immune microenvironment and risk features, and sensitivity predictions were made about anticancer medicines. A risk model was built according to seven selected ar-lncRNAs. The model was validated and the calibration plots were highly consistent in validating nomogram predictions. Further analyses revealed the great accuracy of the model and its ability to serve as a stand-alone GC prognostic factor. We subsequently disclosed that high-risk groups display significant enrichment in pathways related to tumors and the immune system. Additionally, in tumor immunoassays, notable variations in immune infiltrates and checkpoints were noted between different risk groups. This study proposes, for the first time, that prognostic signatures of ar-lncRNA can be established in GC. These signatures accurately predict the prognosis of GC and offer potential biomarkers, suggesting new avenues for basic research, prognosis prediction and personalized diagnosis and treatment of GC. Full article

Background/Objectives: The purpose of this study was to analyze relevant areas in acute-stage fluorescein angiography (FA) images, predicting the long-term visual prognosis of branch retinal vein occlusion (BRVO) based on gradient-weighted class activation mapping (Grad-CAM). Methods: This retrospective observational study included 136 eyes with BRVO that were followed up for more than a year post-FA. Cropped grayscale images centered on the fovea (200 × 200 pixels) were manually pre-processed from early-phase FA at the acute phase. Pairs of the cropped FA images and the best-corrected visual acuity (BCVA) in remission at least one year post-FA were used to train a 38-layer ResNet with five-fold cross-validation. Correlations between the ResNet-predicted and true (actually measured) logMAR BCVAs in remission, and between the foveal avascular zone (FAZ) area measured by ImageJ (version 1.52r) from FA images and true logMAR BCVA in remission were evaluated. The heat maps generated by Grad-CAM were evaluated to determine which areas were consumed as computational resources for BCVA prediction. Results: The correlation coefficient between the predicted and true logMAR BCVAs in remission was 0.47, and that between the acute-stage FAZ area and true logMAR BCVA in remission was 0.42 (p < 0.0001 for both). The Grad-CAM-generated heat maps showed that retinal vessels adjacent to the FAZ and the FAZ per se had high selectivity (95.7% and 62.2%, respectively). Conclusions: The Grad-CAM-based analysis demonstrated FAZ-neighboring vessels as the most relevant predictor for the long-term visual prognosis of BRVO. Full article

RaTG13 is phylogenomically the closest related coronavirus to SARS-CoV-2; consequently, understanding the provenance of this high-value genome sequence is important in understanding the origin of SARS-CoV-2. While RaTG13 was described as being generated from a Rhinolophus affinis fecal swab obtained from a mine in Mojiang, Yunnan, numerous investigators have pointed out that this is inconsistent with the low proportion of bacterial reads in the sequencing dataset. Metagenomic analysis confirms that only 10.3% of small-subunit (SSU) rRNA sequences in the dataset are bacterial, which is inconsistent with a fecal sample. In addition, the bacterial taxa present in the sample are shown to be inconsistent with fecal material. The assembly of mitochondrial SSU rRNA sequences in the dataset produces a sequence 98.7% identical to R. affinis mitochondrial SSU rRNA, indicating that the sample was generated from R. affinis or a closely related species. In addition, 87.5% of the reads in the dataset map to the Rhinolophus ferrumequinum genome, and 62.2% of these map to protein-coding genes, indicating that the dataset represents a Rhinolophus sp. transcriptome rather than a fecal swab sample. Differential gene expression analysis reveals that the pattern of expressed genes in the RaTG13 dataset is similar to that of RaTG15, which was also collected from the Mojiang mine. GO enrichment analysis reveals the overexpression of spermatogenesis- and olfaction-related genes in both datasets. This observation is consistent with a mating plug found in female Rhinolophid bats and suggests that RaTG13 was mis-sampled from such a plug. A validated natural provenance of the RaTG13 dataset throws into relief the unusual features of the SARS-CoV-2 genome. Full article

The composite blade is integral to megawatt-class wind turbines and frequently incurs interlaminar damages such as adhesive failures, cracks, and fractures, which may originate from manufacturing flaws or sustained external fatigue loads. Notably, adhesive joint failure in the spar–web and trailing edge (TE) represents a predominant damage mode. This study systematically explores the failure mechanism in these regions, using mode I fracture toughness tests for an in-depth, quantitative analysis of the adhesive joint’s fatigue crack growth characteristics. Additionally, we conducted extensive material and technical evaluations on specimen units, aiming to validate the reliability of techniques employed for wind blade damage modeling. A damage model, inspired by the NREL 5 MW wind generator’s composite blade structure, meticulously considers the interactions between the TE and spar–web. Utilizing the virtual crack closure technique (VCCT), this model effectively simulates crack growth dynamics in wind blade adhesive joints, while the extended finite element method (XFEM) aids in analyzing crack propagation trajectories under repetitive fatigue loading. By applying this integrated methodology, we successfully determined the lifespan of the spar–web adhesive joint under constant load amplitudes, providing crucial insights into the resilience and longevity of critical wind turbine components. Full article

This study explores the inhibitory potential of the flavonoids resokaempferol and tectochrysin against both wild-type and H1047R mutant forms of PI3Kα, aiming to expand the repertoire of targeted cancer therapies. Employing an array of computational techniques, including Density Functional Theory (DFT), calculations of electronic parameters such as the energies of the frontier molecular orbitals, Molecular Electrostatic Potential (MEP) mapping, and Molecular Docking, we investigate in detail the molecular interactions of these compounds with the PI3Kα kinase. Our findings, corroborated by DFT calculations performed based on the B3LYP (Becke, three-parameter, Lee-Yang-Parr) hybrid functional and the 6-311G++(d,p) basis set, align well with experimental benchmarks and indicate substantial inhibitory efficacy. Further analysis of chemical potential and bioavailability confirmed the drug-like attributes of these flavonoids. Binding affinity and selectivity were rigorously assessed through self-docking and cross-docking against the PIK3CA PDB structures 7K71 and 8TS9. The most promising interactions were validated using Pairwise Structure Alignment and MolProbity analysis of all-atom contacts and geometry. Collectively, these results highlight the flavonoids’ potential as PI3Kα inhibitors and exemplify the utility of natural compounds in the development of precise anticancer treatments. Full article

DnaJ proteins, also known as HSP40s, play a key role in plant growth and development, and response to environmental stress. However, little comprehensive research has been conducted on the DnaJ gene family in maize. Here, we identify 91 ZmDnaJ genes from maize, which are likely distributed in the chloroplast, nucleus, and cytoplasm. Our analysis revealed that ZmDnaJs were classified into three types, with conserved protein motifs and gene structures within the same type, particularly among members of the same subfamily. Gene duplication events have likely contributed to the expansion of the ZmDnaJ family in maize. Analysis of cis-regulatory elements in ZmDnaJ promoters suggested involvement in stress responses, growth and development, and phytohormone sensitivity in maize. Specifically, four cis-acting regulatory elements associated with stress responses and phytohormone regulation indicated a role in adaptation. RNA-seq analysis showed constitutive expression of most ZmDnaJ genes, some specifically in pollen and endosperm. More importantly, certain genes also responded to salt, heat, and cold stresses, indicating potential interaction between stress regulatory networks. Furthermore, early responses to heat stress varied among five inbred lines, with upregulation of almost tested ZmDnaJ genes in B73 and B104 after 6 h, and fewer genes upregulated in QB1314, MD108, and Zheng58. After 72 h, most ZmDnaJ genes in the heat-sensitive inbred lines (B73 and B104) returned to normal levels, while many genes, including ZmDnaJ55, 79, 88, 90, and 91, remained upregulated in the heat-tolerant inbred lines (QB1314, MD108, and Zheng58) suggesting a synergistic function for prolonged protection against heat stress. In conclusion, our study provides a comprehensive analysis of the ZmDnaJ family in maize and demonstrates a correlation between heat stress tolerance and the regulation of gene expression within this family. These offer a theoretical basis for future functional validation of these genes. Full article

Simulation technology has been extensively utilized in the study of ship entry and exit from ports, as well as navigation through waterways. It effectively mirrors the stochastic dynamic changes and interrelationships among various elements within the port system. This paper provides a comparative analysis of the advantages and disadvantages of various modeling methods used in ship navigation simulations. It proposes a simulation modeling approach for ship–port systems based on multi-agent information interaction, which simulates the entire process of ships entering and exiting ports and navigating through complex waterways, achieving a precise and detailed simulation of the entire port entry and exit process in complex waters. Using the Qiongzhou Strait as a case study, the validity and accuracy of the model are verified. The model is employed to quantitatively identify port navigation elements, assess waterway capacity, and evaluate port operational capability. Furthermore, the model enables the analysis of coordination among port channels, berths, and anchorages. Based on simulation results and port development plans, recommendations are provided to enhance port service levels and promote scientific, rational development and efficient operation of ports. Full article

As urban design increasingly emphasizes livable environments, research on pedestrians and walking environments has been revisited at the street level. Although existing studies have shown that street environments impact pedestrians, there remains a significant gap in our knowledge regarding which street elements affect pedestrian walking behavior, to what degree, and which walking characteristics are influenced. This study aims to validate the close relationship between street elements and pedestrian stopping behavior by measuring the influence of different street element environments on walking characteristics. Research methods include a literature review and field research, categorizing street elements into 32 types and pedestrian stopping behaviors into 10 characteristics. By collecting effective walking data from 1587 pedestrians and conducting data processing and regression analysis, we found that rational street design can effectively promote commercial activity and enhance street vitality. Based on the experimental conclusions, we propose urban design recommendations to further enhance the vitality of commercial pedestrian streets, including optimizing street landscape design, improving pedestrian facilities, and increasing leisure spaces. This research provides valuable references for further exploring how to enhance the vitality of commercial pedestrian streets, helping urban planners and designers better understand the relationship between street elements and urban vitality, thereby creating more attractive and vibrant urban spaces and promoting sustainable urban development. Full article

Wave-induced mixing can enhance vertical mixing in the upper ocean, facilitating the exchange of heat and momentum between the surface and deeper layers, thereby influencing ocean circulation and climate patterns. Building on previous research, this study proposes a wave-induced mixing parameterization scheme (referred to as EXP3) specifically designed for typhoon periods. This scheme was integrated into the fully coupled ocean–wave–atmosphere model COAWST and applied to analyze Typhoon In-Fa (2021) as a case study. The simulation results were validated against publicly available data, demonstrating a good overall match with observed phenomena. Subsequently, a comparative analysis was conducted between the EXP3 scheme, the previous scheme (EXP2) and the original model scheme (EXP1). Validation against Argo and Drifter buoy data revealed that both EXP2 and EXP3, which include wave-induced mixing effects, resulted in a decrease in the simulated mixed layer depth (MLD) and mixed layer temperature (MLT), with EXP3 showing closer alignment with the observed data. Compared to the other two experiments, EXP3 enhanced vertical motion in the ocean due to intensified wave-induced mixing, leading to increased upper-layer water divergence and upwelling, a decrease in sea surface temperature and accelerated rightward deflection of surface currents. This phenomenon not only altered the temperature structure of the ocean surface layer but also significantly impacted the regional ocean dynamics. Full article