Search

Supercapacitors (SCs) are widely recognized as competitive power sources for energy storage. The hierarchical structure of nickel vanadium sulfide nanoparticles encapsulated on graphene nanosheets (NVS/G) was fabricated using a cost-effective and scalable solvothermal process. The reaction contents of the composites were explored and optimized. TEM images displayed the nickel vanadium sulfide nanoparticles (NVS NPs) with 20–30 nm average size anchored to graphene nanosheets. The interconnection of graphene nanosheets encapsulating NVS nanoparticles effectively reduces the ion diffusion path between the electrode and electrolyte, thereby enhancing electrochemical performance. The NVS/G composite demonstrated improved electrochemical performance, achieving a maximum of 1437 F g−1 specific capacitance at 1 A g−1, remarkable rate capability retaining of 1050 F g−1 at 20 A g−1, and exceptional cycle stability with 91.2% capacitance retention following 10,000 cycles. The NVS/G composite was employed as a cathode, and reduced graphene oxide (rGO) was used as an anode material to assemble a device. Importantly, asymmetric SCs using NVS/G//rGO achieved 74.7 W h kg−1 energy density at 0.8 kW kg−1 power density, along with outstanding stability with 88.2% capacitance retention following 10,000 cycles. These superior properties of the NVS/G electrode highlight its significant potential in energy storage applications. [ABSTRACT FROM AUTHOR]

Distinguishing humans from animals using ultra-wideband (UWB) radar is necessary in post-disaster emergency rescues to prioritize and thereby optimize the distribution of labor and material resources. However, current studies are few and have only been implemented in simple laboratory environments, such that the effectiveness of these approaches cannot be guaranteed in rescue situations. This study describes experiments under actual post-disaster emergency rescue scenarios, for which the signal-to-noise ratio of UWB radar is seriously degraded owing to multipath effects and a complicated ruin environment. Four distinguishing features are extracted from aspects of wavelet entropy, correlation coefficient, and energy to classify humans from animals. Analysis of feature effectiveness showed that each feature could identify humans from animals individually. The largest difference between humans and animals was found in a feature which combines advantages of the correlation coefficient and energy simultaneously. There was no overlap between the human and animal values for this feature among the 20 sets of radar data collected. This is the first attempt to distinguish humans from animals in an actual post-disaster trapped condition, and it yielded four features of strong classification ability. We envision this study to advance real-world applicability of UWB radar in post-disaster emergency rescue.

Traditional digital image processing techniques face problems such as complex feature extraction and weak robustness when dealing with surface defects of multiple categories of electronic components. Deep learning is widely used in industrial defect detection. However, the performance of electronic component defect detection at the pixel segmentation level needs to be improved. For pixel-level defect detection, this paper constructs a defect detection model (ECSDDNet) for electronic component surface defects in computer vision engineering management system. To improve the segmentation accuracy and detection effect, three stages of experiments are conducted to address mis-segmentation problems and the shortcomings of the Unet network structure. Firstly, a classification network that can perform weight transfer is used to replace the encoding structure in the Unet network. Secondly, a simplified version of the feature fusion is proposed and added to the skip connection of the Unet network. Finally, label smoothing is used to optimize the loss and improve the generalization of the network. After the optimization experiment, some noisy contours and small defect contours that are mis-segmented are removed. Experimental results show that ECSDDNet has good segmentation effects on electronic component surface defects and can meet the segmentation and detection needs of electronic component surface defects. [ABSTRACT FROM AUTHOR]

Hole repair processing is an important part of point cloud data processing in airborne 3-dimensional (3D) laser scanning technology. Due to the fragmentation and irregularity of the surface morphology, when applying the 3D laser scanning technology to mountain mapping, the conventional mathematical cloud-based point cloud hole repair method is not ideal in practical applications. In order to solve this problem, we propose to repair the valley and ridge line first, and then repair the point cloud hole. The main technical steps of the method include the following points: First, the valley and ridge feature lines are extracted by the GIS slope analysis method; Then, the valley and ridge line missing from the hole are repaired by the mathematical interpolation method, and the repaired results are edited and inserted to the original point cloud; Finally, the traditional repair method is used to repair the point cloud hole whose valley line and ridge line have been repaired. Three experiments were designed and implemented in the east bank of the Xiaobaini River to test the performance of the proposed method. The results showed that compared with the direct point cloud hole repair method in Geomagic Studio software, the average repair accuracy of the proposed method, in the 16m buffer zone of valley line and ridge line, is increased from 56.31cm to 31.49cm. The repair performance is significantly improved.

Objective: To investigate the effects of desmoglein 3 (DSG3) gene mediating epidermal growth factor/epidermal growth factor receptor (EGF/EGFR) signaling pathway on inflammatory response and immune function of anaphylactic rhinitis (AR). Methods: Ten of the seventy male BALB/c mice were randomly selected as the normal control group, and the remaining 60 were used to construct the AR mice model. AR model mice were divided into 6 groups: model group (instilled with 5 μL saline), empty vector group (instilled with 5 μL of liposome and empty vector mixture), siRNA-DSG3 group (instilled with 5 μL of liposome and siRNA-DSG3 carrier mixture), AG1478 group (instilled with 5 μL of EGF/EGFR inhibitor AG1478), siRNA-DSG3+AG1478 group (instilled with 5 μL of liposome and siRNA-DSG3 carrier and EGF/EGFR inhibitor AG1478 mixture) and oe-DSG3 group, 10 in each group. After taking serum, each group of mice was sacrificed to get nasal mucosa tissues. HE staining was used to observe the pathological changes of nasal mucosa tissues in each group. The expression levels of DSG3, EGF and EGFR in nasal mucosa tissues of mice in each group were detected by qRT-PCR and western blot methods respectively. TUNEL staining was used to observe the apoptosis of nasal mucosa cells in mice. The expression of IgE, INF-γ, TNF-α, IL-2, IL-4 and IL-6 in serum of mice was determined by ELISA method. The immune adhesion function of red blood cells was detected by complement sensitization yeast hemagglutination method. Results: All the mice with AR showed different degrees of nasal mucosa injury and inflammatory cell infiltration, and silencing DSG3 or inhibiting the activity of EGF signaling pathway could alleviate the nasal mucosa injury. Compared with control group, the INF-γ and IL-2 levels of serum in AR model mice were significantly decreased; IgE, TNF-α, IL-4 and IL-6 levels were significantly increased (all P

Speech signal acquisition is of great significance for human communication. Bio-radar technology has many advantages, such as it is noncontact, noninvasive, safe, highly directional, highly sensitivity, immune to strong acoustical disturbance and penetrable. This technology has important applications in the field of speech detection. In this paper, we first review the developmental history of speech detection technology, and then summarize the status of bio-radar speech detection technology. The basic principles of a bio-radar in detecting speech signals are given, and the performance of three types of bio-radar speech detection systems are compared in this paper. Finally, the potential applications of bio-radar speech signal detection technology are prospected.

Because of the mutual interference between multiple stationary humans, distinguishing individuals via the range profile of a single-channel bioradar is difficult. To solve this problem, we used an Ultra-WideBand Multiple-Input Multiple-Output (UWB MIMO) bioradar to compose high-resolution two-dimensional images. These images allow multiple stationary humans to be separated from space. Then, vital signs are enhanced on the basis of the UWB MIMO image sequence, thereby leading to effective suppression of interference. The experimental results demonstrate that the proposed method can compose high-resolution images of multiple stationary humans. Thus, high-performance detection and localization of multiple stationary humans can be expected.

Introduction: Inflammasome and pyroptosis play important roles in periodontitis. Gasdermin D (GSDMD), a key factor in pyroptosis, is cleaved by caspase‐1 and regulated by ubiquitination. Synoviolin is a ubiquitin E3 ligase that interacts with GSDMD. In this study, the effects of Synoviolin on inflammasome activation and periodontitis were explored. Methods: The expression of IL‐1β, GSDMD, and Synoviolin in peripheral blood mononuclear cells from patients with periodontitis was determined. The interaction between GSDMD and Synoviolin was studied. The cytokine level in gingival tissues and the distance from the cementoenamel junction to the alveolar bone crest were measured in mice with Synoviolin deficiency in myeloid cells. Results: We reported that elevated mRNA and protein levels of IL‐1β and GSDMD, decreased levels of Synoviolin mRNA and protein, and decreased ubiquitination of GSDMD were associated with periodontitis. Synoviolin interacted with GSDMD. Synoviolin‐deficient bone marrow‐derived macrophages had increased IL‐1β and IL‐18 secretion after ATP stimulation. Mice with Synoviolin deficiency in myeloid cells had more severe periodontitis and upregulated IL‐1β and IL‐18. Conclusions: Therefore, we conclude that Synoviolin suppresses inflammasome activation and periodontitis by regulating GSDMD stability. [ABSTRACT FROM AUTHOR]