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关键词： Eye-tracking   Concurrent reader   Chest radiography   Bounding-box display   Interpretation time  

摘要： Computer-aided detection (CAD) systems for chest radiographs are widely used; however, concurrent reader displays such as bounding-box (BB) highlights may influence interpretation. This pilot study used eye tracking to examine which aspects of visual search were affected by these factors.

关键词： Conceptual design  

摘要： With the advancement of transplanting theory and increasing agronomic requirements, gear–linkage/cam mechanisms (GLCMs) have emerged as a feasible solution for achieving complex operational trajectories by introducing transmission ratio variation characteristics. However, systematic design methodologies for such mechanisms remain limited. In this study, a structural synthesis method for GLCMs based on gear pair substitution is proposed, and suitable configurations are selected in combination with kinematic synthesis to design vegetable plug seedling transplanting mechanisms. First, similar edges are identified using the minimum distance matrix constant and the power matrix constant, with verification against established databases to ensure recognition accuracy. Second, a structural synthesis approach for special GLCMs is developed by gradually adding components and kinematic pairs. Through gear pair substitution, structural synthesis of GLCMs with up to three degrees-of-freedom is achieved, while similarity information is employed to avoid generating isomorphic configurations. Finally, an optimal configuration is selected and combined with kinematic synthesis to design a vegetable plug seedling transplanting mechanism, whose feasibility is validated through simulation experiments. Copyright © 2025 by ASME.

摘要： Ultrasound imaging is vital for the early detection of breast cancer, where accurate lesion segmentation supports clinical diagnosis and treatment planning. However, existing deep learning-based methods rely on pixel-level annotations, which are costly and labor-intensive to obtain. This study presents a weakly supervised framework for breast lesion segmentation in ultrasound images. The framework combines morphological enhancement with Class Activation Map (CAM)-guided lesion localization and utilizes the Segment Anything Model (SAM) for refined segmentation without pixel-level labels. By adopting a lightweight region synthesis strategy and relying solely on SAM inference, the proposed approach substantially reduces model complexity and computational cost while maintaining high segmentation accuracy. Experimental results on the BUSI dataset show that our method achieves a Dice coefficient of 0.7063 under five-fold cross-validation and outperforms several fully supervised models in Hausdorff distance metrics. These results demonstrate that the proposed framework effectively balances segmentation accuracy, computational efficiency, and annotation cost, offering a practical and low-complexity solution for breast ultrasound analysis. The code for this study is available at: https://***/YueXin18/MorSeg-CAM-SAM-Segmentation.

关键词： Acute myocardial infarction(AMI)   Coronary artery disease(CAD)   Machine learning algorithms   Mitochondrial energy metabolism   Molecular docking   Therapeutic agents  

摘要： Coronary artery disease (CAD) is a leading cause of acute myocardial infarction (AMI), a condition characterized by the sudden blockage of blood flow to the heart muscle, resulting in significant morbidity and mortality worldwide. Despite advances in treatment, early prediction and diagnosis remain challenging. This study aims to construct a predictive model for CAD in AMI patients by focusing on mitochondrial energy metabolism(MME), a critical factor in cardiac function and disease progression. We employed an integrative WGCNA and machine learning algorithm combinations (RF, Lasso and SVM), utilizing 5 distinct CAD and AMI peripheral blood bulk profiles for the elucidation of potential diagnostic biomarkers for CAD patients with AMI. Finally, we discovered that CLPX can be recognized as diagnostic biomarkers, which is related to the molecular and immune pathogenesis of AMI among CAD patients. Meanwhile, we also discovered that MME-related genes can divide CAD and AMI into 2 different molecular subgroups via consensus clustering. Besides, Troglitazone can be regarded as potential therapeutic agents for AMI of CAD patients targeting CLPX via molecular docking. This study underscores the importance of mitochondrial function in cardiovascular diseases and highlights the potential of bioinformatics in advancing precision medicine.

关键词： Partially saturated soils   Cyclic loading   Hydro-mechanical modelling   Hydro-mechanical loading   Historiotropic surface  

摘要： Partially saturated soils are gaining prominence in geotechnical engineering and engineering geology, particularly in the context of extreme climate phenomena. Their intricate response to changing moisture conditions significantly impacts slope stability, foundation design, and infrastructure resilience against climate’s extreme phenomena in geotechnical engineering applications. Current constitutive models mainly focused on predicting monotonic hydro-mechanical (HM) processes, lacking accuracy in predicting soil behaviour under cyclic loading and moisture variations. However, infrastructures like railway tracks impose cyclic loading on the subsoil, while the soil undergoes seasonal moisture variations. This study aims to contribute to this topic by proposing a new HM constitutive model based on the Constitutive Anamnesis Model (CAM) for saturated soils, extending its application to partially saturated conditions. The original CAM effectively predicts the behaviour of fully saturated fine-grained soils under monotonic and cyclic loading, considering soil preloading history. By incorporating partial saturation effects, the extended model offers improved accuracy in simulating the behaviour of low and high plasticity clays under cyclic hydro-mechanical loading, providing a more comprehensive tool for geotechnical engineering applications.

关键词： CAM   CLIP   Image-level labels   WSSS  

摘要： Weakly supervised semantic segmentation (WSSS) using image-level labels aims to create pseudo-labels leveraging Class Activation Maps (CAM) to train a separate segmentation model. Recent methods that utilize Contrastive Language-Image Pre-training (CLIP) models have achieved significant advancements. These approaches take advantage of CLIP’s capability to identify various categories without requiring additional training. However, due to the limited local information of the final embedding layer, the CAM generated by the CLIP model is still a rough region with an under-activated or over-activated issue. Furthermore, the abundant multi-layer information of CLIP, which plays a vital role in dense prediction, has been ignored. In this paper, we proposed a LayerCLIP model for a fine-grained CAM generation via hierarchical features, which consists of two consecutive components: a dynamic hierarchical CAMs module and an adaptive affinity module. Specifically, the dynamic hierarchical CAMs module utilizes the hierarchical features to produce two complementary CAMs, along with a dynamic strategy to fuse these CAMs. Subsequently, the affinity based on multi-head self-attention is adaptively reweighted to refine CAM by the CAM itself in the adaptive affinity module. LayerCLIP significantly enhances the quality of CAM. Our method achieves a new state-of-the-art performance on PASCAL VOC 2012 (75.1 % mIoU) and MS COCO 2014 (46.9 % mIoU) through extensive benchmark experiments.

关键词： Simulation framework   Distributed CAD system   Thermal performance   Simulation efficiency  

摘要： This study develops a distributed Computer-Aided Design (CAD) system for scalable thermal performance simulation in clothing engineering, overcoming key limitations of conventional single-server architectures. The proposed framework incorporates three core innovations: (1) a multiphysics coupling engine that models the human–clothing–environment system as a thermal system, integrating Stolwijk’s 25-node human thermoregulation model with dynamic fabric transfer equations via finite-volume discretization; (2) a distributed architecture that improves processing efficiency under multi-user concurrent scenarios; and (3) a five-stage scenario definition workflow supporting parametric modeling of activity-dependent metabolic rates, multi-layer garment configurations (across up to six segments), and environmental boundary conditions. Six simulation cases were tested–running at 8, 10, and 12 km/h under 20°C and 60 % relative humidity for 30 minutes each–demonstrating that the distributed CAD system significantly reduces simulation and user waiting times compared to a legacy Browser/Server system. It also enables visualization of human skin temperature and fabric properties on the trunk during simulated running. This distributed approach facilitates faster, large-scale simulations for designing sportswear and protective clothing, thereby reducing reliance on costly physical prototypes and accelerating the development of more comfortable and functional apparel.

关键词： Tropane alkaloids   Atropine   Scopolamine   Stability   Degradation   Charged Aerosol Detection   Mixed Mode Column  

摘要： Medicines often have a much longer shelf life than stated by the manufacturer. Due to the high costs of emergency stockpiling, but also due to supply shortages, an extended shelf life can offer many advantages. In this study, three injection solutions containing atropine, scopolamine and belladonna total alkaloids, respectively, manufactured between 1940 and 1960 and stored under uncontrolled conditions, were tested, to show that pharmaceutical products, containing tropane alkaloids, are significantly more stable than expected after some 80 years. To analyze the stability of the main alkaloids atropine and scopolamine, a method using charged aerosol detection (CAD) was developed and validated. CAD enables the detection of degradation products that lack a chromophore and cannot be detected using pharmacopoeial (UV) methods. For separation a SIELC Primesep 200 column (4.6 ×150 mm; 100 Å; 3 µm) and gradient elution with water, acetonitrile and formic acid were used. The results indicated a high stability of atropine, with a determined content of 101.9 % and a small amount of degradation products. Scopolamine, however, showed higher degree of degradation with a remaining content of 68 %.

摘要： The structure integrating the advantages of convolutional local feature extraction and Transformer-based global feature analysis exhibits distinct strengths in bearing fault diagnosis. However, there is often noise interference in actual working conditions, and such structures typically require large-scale training datasets to maintain performance, which poses a significant limitation in fault diagnosis scenarios. Additionally, the decision principles of these structures cannot be explored, and interpretability remains insufficient. To address these challenges, an interpretable fault diagnosis framework is proposed, wherein channel-level and region-level feature information are jointly optimized. A variable bandwidth filter module is first designed for signal preprocessing, with spectral attention heat maps generated via filter channel weight mapping. Joint distributed self-attention is employed to perform interactive weighting across regional and channel dimensions, thereby reducing model parameters. A multi-head weighted link classification layer is developed for feature classification, with inherent interpretability embedded. Based on this, Weight-CAM method is designed to obtain accurate post-hoc activation maps without invoking original model computations. Experimental results show that the proposed model can maintain classification accuracy in the presence of noise, limited samples, and the need to cross speeds. Through the incorporation of variable bandwidth filtering and weighted link layers, spectral heat maps and post-hoc activation maps are utilized to cross-locate model focus in both time and frequency domains, validating the interpretability of the framework.