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The detection of objects concealed under people’s clothing is a very challenging task, which has crucial applications for security. When testing the human body for metal contraband, the concealed targets are usually small in size and are required to be detected within a few seconds. Focusing on weapon detection, this paper proposes using a real-time detection method for detecting concealed metallic weapons on the human body applied to passive millimeter wave (PMMW) imagery based on the You Only Look Once (YOLO) algorithm, YOLOv3, and a small sample dataset. The experimental results from YOLOv3-13, YOLOv3-53, and Single Shot MultiBox Detector (SSD) algorithm, SSD-VGG16, are compared ultimately, using the same PMMW dataset. For the perspective of detection accuracy, detection speed, and computation resource, it shows that the YOLOv3-53 model had a detection speed of 36 frames per second (FPS) and a mean average precision (mAP) of 95% on a GPU-1080Ti computer, more effective and feasible for the real-time detection of weapon contraband on human body for PMMW images, even with small sample data.

This paper takes the impact of economic growth on environmental pollution in Liaoning Province as the research object. After analyzing the status quo of economic growth and environmental pollution in Liaoning Province, four environmental pollution indicators (industrial wastewater discharge, industrial waste gas emissions, industrial sulfur dioxide emissions, and industrial dust emissions) and an economic growth indicator (per capita GDP) are selected. After an economic model is established to focus on the real impact of Liaoning’s economic growth on environmental pollution, it is found that the impact of Liaoning’s economic growth on environmental pollution does not conform to the traditional Environmental Kuznets Curve. Through analysis, it is concluded that economic growth has affected the four environmental indicators to varying degrees. Among them, industrial wastewater discharge, industrial sulfur dioxide emissions, and industrial dust emissions drop after rising, and industrial dust emissions have been on the rise all the time. Considering the realities and characteristics of Liaoning Province, the author has proposed five countermeasures and suggestions for coordinating the relationship between economic growth and environmental protection in Liaoning Province, which are, optimize the industrial structure to promote economic development in the direction of environmental protection; focus on pollution prevention to take a new road to industrialization of circular economy; tap the full potential of market mechanism to realize the innovation of environmental protection system; actively promote the application of low-carbon energy to increase its proportion in total energy consumption; increase investment in environmental protection to improve investment structure and efficiency of environmental protection.

To survive under adverse conditions, plants form stress granules (SGs) to temporally store mRNA and halt translation as a primary response. Dysregulation in SG disassembly can have detrimental effects on plant survival after stress release, yet the underlying mechanism remains poorly understood. Using Arabidopsis as a model system, we demonstrate that the β subunit of adaptor protein (AP) -3 complex (AP-3β) interacts with the SG core RNA-binding proteins Tudor staphylococcal nuclease 1/2 (TSN1/2) both in vitro and in vivo. We also show that AP-3β is rapidly recruited to SGs upon heat induction and plays a key role in disassembling SGs during stress recovery. Genetic evidences support that AP-3β serves as an adaptor to recruit the 19S regulatory particle (RP) of the proteasome to SGs. Notably, the 19S RP promotes SG disassembly through RP-associated deubiquitylation, independent of its proteolytic activity. This deubiquitylation process of SG components is crucial for translation reinitiation and growth recovery after heat release. Our findings uncover a previously unexplored role of the 19S RP in regulating SG disassembly and highlights the importance of endomembrane proteins in supporting RNA granule dynamics in plants. This study demonstrates that the adaptor protein AP-3β recruits the 19S regulatory particle (RP) of the proteasome to stress granules (SGs) after heat stress and promotes SG disassembly through RP-associated deubiquitylation process.

Diabetic neuropathy is one of the clinical syndromes characterized by pain and substantial morbidity primarily due to a lesion of the somatosensory nervous system. The burden of diabetic neuropathy is related not only to the complexity of diabetes but also to the poor outcomes and difficult treatment options. There is no specific treatment for diabetic neuropathy other than glycemic control and diligent foot care. Although various metabolic pathways are impaired in diabetic neuropathy, enhanced cellular oxidative stress is proposed as a common initiator. A mechanism-based treatment of diabetic neuropathy is challenging; a better understanding of the pathophysiology of diabetic neuropathy will help to develop strategies for the new and correct diagnostic procedures and personalized interventions. Thus, we review the current knowledge of the pathophysiology in diabetic neuropathy. We focus on discussing how the defects in metabolic and vascular pathways converge to enhance oxidative stress and how they produce the onset and progression of nerve injury present in diabetic neuropathy. We discuss if the mechanisms underlying neuropathy are similarly operated in type I and type II diabetes and the progression of antioxidants in treating diabetic neuropathy.

Unlike optical satellites, synthetic aperture radar (SAR) satellites can operate all day and in all weather conditions, so they have a broad range of applications in the field of ocean monitoring. The ship targets’ contour information from SAR images is often unclear, and the background is complicated due to the influence of sea clutter and proximity to land, leading to the accuracy problem of ship monitoring. Compared with traditional methods, deep learning has powerful data processing ability and feature extraction ability, but its complex model and calculations lead to a certain degree of difficulty. To solve this problem, we propose a lightweight YOLOV5-MNE, which significantly improves the training speed and reduces the running memory and number of model parameters and maintains a certain accuracy on a lager dataset. By redesigning the MNEBlock module and using CBR standard convolution to reduce computation, we integrated the CA (coordinate attention) mechanism to ensure better detection performance. We achieved 94.7% precision, a 2.2 M model size, and a 0.91 M parameter quantity on the SSDD dataset.

The long-term operation performance of HVDC transmission systems is significantly influenced by the reliability of thyristors. However, the current reliability research of thyristors is mainly based on the leakage current and there is no comprehensive degradation characteristics of thyristors. In this article, the degradation characteristics of thyristors under voltage and temperature accelerated ageing tests are obtained, including the reverse recovery characteristic, on-state characteristic, blocking characteristic and gate characteristic. The reverse recovery characteristic obviously degrades under the voltage accelerated ageing tests. The reverse recovery charge and reverse recovery time decrease by over 10% after the tests. Seven thyristors operating for a certain number of years from two HVDC stations are tested, and the results verify the thyristor degradation characteristics obtained from the ageing tests. Moreover, the mechanisms of the leakage current and reverse recovery characteristic are analyzed in detail.

Building reconstruction using high-resolution satellite-based synthetic SAR tomography (TomoSAR) is of great importance in urban planning and city modeling applications. However, since the imaging mode of SAR is side-by-side, the TomoSAR point cloud of a single orbit cannot achieve a complete observation of buildings. It is difficult for existing methods to extract the same features, as well as to use the overlap rate to achieve the alignment of the homologous TomoSAR point cloud and the cross-source TomoSAR point cloud. Therefore, this paper proposes a robust alignment method for TomoSAR point clouds in urban areas. First, noise points and outlier points are filtered by statistical filtering, and density of projection point (DoPP)-based projection is used to extract TomoSAR building point clouds and obtain the facade points for subsequent calculations based on density clustering. Subsequently, coarse alignment of source and target point clouds was performed using principal component analysis (PCA). Lastly, the rotation and translation coefficients were calculated using the angle of the normal vector of the opposite facade of the building and the distance of the outer end of the facade projection. The experimental results verify the feasibility and robustness of the proposed method. For the homologous TomoSAR point cloud, the experimental results show that the average rotation error of the proposed method was less than 0.1°, and the average translation error was less than 0.25 m. The alignment accuracy of the cross-source TomoSAR point cloud was evaluated for the defined angle and distance, whose values were less than 0.2° and 0.25 m.

Dynamic oxygen uptake (VO2) reflects moment-to-moment changes in oxygen consumption during exercise and underpins training design, performance enhancement, and clinical decision-making. We tackled two key obstacles—the limited fusion of heterogeneous sensor data and inadequate modeling of long-range temporal patterns—by integrating wearable accelerometer and heart-rate streams with a convolutional neural network–LSTM (CNN-LSTM) architecture and optional attention modules. Physiological signals and VO2 were recorded from 21 adults through resting assessment and cardiopulmonary exercise testing. The results showed that pairing accelerometer with heart-rate inputs improves prediction compared with considering the heart rate alone. The baseline CNN-LSTM reached R2 = 0.946, outperforming a plain LSTM (R2 = 0.926) thanks to stronger local spatio-temporal feature extraction. Introducing a spatial attention mechanism raised accuracy further (R2 = 0.962), whereas temporal attention reduced it (R2 = 0.930), indicating that attention success depends on how well the attended features align with exercise dynamics. Stacking both attentions (spatio-temporal) yielded R2 = 0.960, slightly below the value for spatial attention alone, implying that added complexity does not guarantee better performance. Across all models, prediction errors grew during high-intensity bouts, highlighting a bottleneck in capturing non-linear physiological responses under heavy load. These findings inform architecture selection for wearable metabolic monitoring and clarify when attention mechanisms add value.

Solid‐state transformers (SSTs) have applications in medium‐voltage direct current (MVDC) grids and compact power systems. High‐frequency transformer (HFT) is the core component of SSTs. High levels of high frequency high dv/dt voltage stresses challenged the integrity of the galvanic insulation of HFTs. However, dielectric thermal runaway and resultant electrical failure mechanisms in epoxy resin (EP) cast insulation remain unclear. Dielectric heating of EP across varying voltages, frequencies, rising edges, duty cycles and DC biases were measured and corroborated by simulation. The thermal runaway threshold mainly depends on the tangency point of the loss generation and heat dissipation curves below the glass transition temperature. Observations reveal that thermal runaway does not directly cause breakdown; instead, thermal decomposition above 200°C triggers discharge and eventual failure. Simulations demonstrate that temperature rise mainly depends on the average field within the electrode region and inter‐segment and inter‐layer distances within the HFT winding definitively impact insulation thermal runaway. By applying different criteria for MV and high‐voltage (HV) transformers, the reference electric fields for insulation design with unfilled and filled EP were obtained. For instance, limiting dielectric heating below 5 K at 50 kHz necessitates an RMS average field less than 0.44 V/mm, which is much lower than dry‐type transformer conventions. The authors prove the necessity of re‐evaluating the permissible field strength in HFT insulation design.

Objective To explore the potential mechanisms of interstitial cystitis (IC), we employed a cyclophosphamide (CYP)-induced cystitis rat model, a well-established tool for studying IC-like bladder inflammation and dysfunction. This study aimed to investigate the role of rhythmic genes and immune microenvironment remodeling in this model, focusing on TOP2A and its impact on T-cell infiltration. Methods CYP-induced cystitis rat models were established using cyclophosphamide. Single-cell RNA sequencing was performed on bladder tissues to analyze cellular heterogeneity. Differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) identified rhythmic and immune-related gene clusters. TOP2A was validated via RT-PCR, Western blot, and immunohistochemistry (IHC). Statistical analyses assessed correlations between TOP2A, CD4 + T cells, and CD8 + T cells. Results Single-cell sequencing revealed elevated T-cell infiltration in a CYP-induced cystitis rat model. TOP2A was the sole overlapping gene between rhythmic and immune clusters and showed significant upregulation in IC tissues ( P  < 0.05). IHC confirmed increased TOP2A, CD4 + T, and CD8 + T cell levels, with strong positive correlations ( r  = 0.89 and 0.64, respectively). Functional enrichment linked TOP2A to oxidative phosphorylation and ribosomal pathways. Conclusions Our findings demonstrate that TOP2A drives immune dysregulation in CYP-induced cystitis by modulating T-cell infiltration. As T-cell infiltration is a hallmark of human IC, our findings in this CYP-induced model suggest that TOP2A may represent a novel therapeutic target worthy of further investigation in human IC tissues.