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Investigating the 3D structures and rearrangements of organelles within a single cell is critical for better characterizing cellular function. Imaging approaches such as soft X-ray tomography have been widely applied to reveal a complex subcellular organization involving multiple inter-organelle interactions. However, 3D segmentation of organelle instances has been challenging despite its importance in organelle characterization. Here we propose an intensity-based post-processing tool to identify and separate organelle instances. Our tool separates sphere-like (insulin vesicle) and columnar-shaped organelle instances (mitochondrion) based on the intensity of raw tomograms, semantic segmentation masks, and organelle morphology. We validate our tool using synthetic tomograms of organelles and experimental tomograms of pancreatic β-cells to separate insulin vesicle and mitochondria instances. As compared to the commonly used connected regions labeling, watershed, and watershed + Gaussian filter methods, our tool results in improved accuracy in identifying organelles in the synthetic tomograms and an improved description of organelle structures in β-cell tomograms. In addition, under different experimental treatment conditions, significant changes in volumes and intensities of both insulin vesicle and mitochondrion are observed in our instance results, revealing their potential roles in maintaining normal β-cell function. Our tool is expected to be applicable for improving the instance segmentation of other images obtained from different cell types using multiple imaging modalities.

In current construction waste resource management processes, the effect of government supervision is unclear, and illegal treatment and low-quality reproduction of recycling and reprocessing enterprises by construction units are common. To improve the degree of resource utilization of construction waste and deeply explore the role of its key influencing factors, a tripartite evolutionary game model of construction waste resource treatment in which the government, construction units, and recycling and reprocessing enterprises are the research objects that considers public participation factors to be established. MATLAB is used to simulate the sensitivity of relevant parameters. The results show that: (1) An increase in government fines can regulate the behavior of enterprises; (2) Low government subsidies are conducive to the development of a tripartite stability strategy; and (3) An increase in the cost difference between the two strategies of the enterprise will weaken its willingness to carry out green operations (and after the cost difference exceeds the threshold, the enterprise will refuse to carry out green operations); (4) The reputation value brought by the public and the additional value added by reputation under the contrast effect have an incentive effect on the enterprise and the government; and (5) The peak value of the inverted U-shaped curve of government strategy choice is affected by the degree of public participation. Therefore, the government should propose rectifications in terms of fines and subsidies, and both companies can use technological innovation to reduce costs. At the same time, it is necessary to raise stakeholders' awareness of resource utilization and encourage the public to actively participate in supervision. The research conclusions can provide a decision-making reference for improving the utilization of construction waste resources and the efficient treatment of construction waste resources. [ABSTRACT FROM AUTHOR]

Antennas play a crucial role in designing an efficient communication system. However, reducing the maximum sidelobe level (SLL) of the beam pattern is a crucial challenge in antenna arrays. Pattern synthesis in smart antennas is a major area of research because of its widespread application across various radar and communication systems. This paper presents an effective technique to minimize the SLL and thus improve the radiation pattern of the linear antenna array (LAA) using the chaotic inertia-weighted Wild Horse optimization (IERWHO) algorithm. The wild horse optimizer (WHO) is a new metaheuristic algorithm based on the social behavior of wild horses. The IERWHO algorithm is an improved Wild Horse optimization (WHO) algorithm that combines the concepts of chaotic sequence factor, nonlinear factor, and inertia weights factor. In this paper, the method is applied for the first time in antenna array synthesis by optimizing parameters such as inter-element spacing and excitation to minimize the SLL while keeping other constraints within the boundary limits, while ensuring that the performance is not affected. For performance evaluation, the simulation tests include 12 benchmark test functions and 12 test functions to verify the effectiveness of the improvement strategies. According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization. [ABSTRACT FROM AUTHOR]

Acute compartment syndrome (ACS) is a syndrome in which local circulation is affected due to increased pressure within the compartment. We previously found in patients with calf fractures, the pressure of fascial compartment could be sharply reduced upon the appearance of tension blisters. Deep fascia, as the important structure for compartment, might play key role in this process. Therefore, the aim of the present study was to examine the differences in gene profile in deep fascia tissue in fracture patients of the calf with or without tension blisters, and to explore the role of fascia in pressure improvement in ACS. Patients with lower leg fracture were enrolled and divided into control group (CON group, n = 10) without tension blister, and tension blister group (TB group, n = 10). Deep fascia tissues were collected and LC-MS/MS label-free quantitative proteomics were performed. Genes involved in fascia structure and fibroblast function were further validated by Western blot. The differentially expressed proteins were found to be mainly enriched in pathways related to protein synthesis and processing, stress fiber assembly, cell-substrate adhesion, leukocyte mediated cytotoxicity, and cellular response to stress. Compared with the CON group, the expression of Peroxidasin homolog (PXDN), which promotes the function of fibroblasts, and Leukocyte differentiation antigen 74 (CD74), which enhances the proliferation of fibroblasts, were significantly upregulated (p all <0.05), while the expression of Matrix metalloproteinase-9 (MMP9), which is involved in collagen hydrolysis, and Neutrophil elastase (ELANE), which is involved in elastin hydrolysis, were significantly reduced in the TB group (p all <0.05), indicating fascia tissue underwent microenvironment reconstruction during ACS. In summary, the ACS accompanied by blisters is associated with the enhanced function and proliferation of fibroblasts and reduced hydrolysis of collagen and elastin. The adaptive alterations in the stiffness and elasticity of the deep fascia might be crucial for pressure release of ACS. [ABSTRACT FROM AUTHOR]

Purpose: The resurgence of pertussis has occurred around the world. However, the epidemiological profiles of pertussis cannot be well understood by current diseases surveillance. This study was designed to understand the seroepidemiological characteristics of pertussis infection in the general population of Huzhou City, evaluate the prevalence infection of pertussis in the population, and offer insights to inform adjustments in pertussis prevention and control strategies. Methods: From September to October 2023, a cross-sectional serosurvey was conducted in Huzhou City, involving 1015 permanent residents. Serum samples were collected from the study subjects, and pertussis toxin IgG antibodies (Anti-PT-IgG) were quantitatively measured using enzyme-linked immunosorbent assay (ELISA). The analysis included the geometric mean concentration (GMC) of Anti-PT-IgG, rates of GMC≥40IU/mL, ≥100IU/mL, and <5IU/mL. Stratified comparisons were made based on age, vaccination history, and human categories. Results: Among the 1015 surveyed individuals, the geometric mean concentration (GMC) of Anti-PT-IgG was 10.52 (95% CI: 9.96–11.11) IU/mL, with a recent infection rate of 1.58%, a serum positivity rate of 11.43%, and a proportion with <5IU/mL of 40.49%. Among 357 children with clear vaccination history, susceptibility decreased with an increasing number of vaccine doses (Z = -6.793, P < 0.001). The concentration of Anti-PT-IgG exhibited a significant post-vaccination decline over time (Z = -5.143, P < 0.001). In women of childbearing age, the GMC of Anti-PT-IgG was 7.71 (95% CI: 6.90–8.62) IU/mL, with no significant difference in susceptibility among different age groups (χ2 = 0.545, P = 0.909). The annual pertussis infection rate in individuals aged ≥3 years was 9321 (95%CI: 3336–16039) per 100,000, with peak infection rates in the 20–29, 40–49, and 5–9 age groups at 34363 (95%CI: 6327–66918) per 100,000, 22307.72 (95%CI: 1380–47442) per 100,000, and 18020(95%CI: 1093–37266) per 100,000, respectively. Conclusions: In 2023, the actual pertussis infection rate in the population of Huzhou City was relatively high. Vaccine-induced antibodies exhibit a rapid decay, and the estimated serum infection rate increases rapidly from post-school age, peaking in the 20–29 age group. It is recommended to enhance pertussis monitoring in adolescents and adults and refine vaccine immunization strategies. [ABSTRACT FROM AUTHOR]

The continuous development of science and technology has led to the gradual digitization and intelligence of campus construction. To apply facial recognition technology to construct smart libraries in higher education, this study optimizes traditional facial recognition algorithm models. Firstly, a smart management system for university libraries is designed with facial recognition as the core, and secondly, the traditional FaceNet network is optimized. Combined with MobileNet, Attention mechanism, Receptive field module and Mish activation function, the improved multitask face recognition convolutional neural network is built and used in the construction of university smart library. The performance verification of the constructed model shows that the feature matching error value of the model in a stable state is only 0.04. The recognition accuracy in the dataset is as high as 99.05%, with a recognition error as low as 0.51%. The facial recognition model used in university smart libraries can achieve 97.6% teacher satisfaction and 96.8% student satisfaction. In summary, the facial recognition model constructed by this paper has good recognition performance and can provide effective technical support for the construction of smart libraries. [ABSTRACT FROM AUTHOR]