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The acceptance check is a key step to decide whether an overhead transmission line can be put into use. However, for the acceptance check of towers, the manual means is still adopted mostly nowadays, which is dangerous and inefficient. The main challenges for intelligent check technique are the automatic tower segmentation and intelligent requirements of some detection items. Here, based on point clouds from lidars, some intelligent methods are proposed for tower related acceptance check items. The geometric structural changing rules for towers are found and analyzed to identify and segment towers from the scene point cloud automatically. A model‐constrained method is proposed for fine filtering of towers. With point cloud registration strategies, the tilt angle of a tower is calculated intelligently and the defect detection of a tower is conducted successfully. Experiments show that the results of the proposed methods are accurate, efficient and automatic, which have potential for real applications. [ABSTRACT FROM AUTHOR]

Human-machine interactive systems show increasing demand for analysing fast moving objects in high-frame-rate videos. Robust foreground detection, which is able to reduce large amount of redundant background data from high-frame-rate video, becomes the essence to achieve ultra-high-speed human-machine interactions. This paper proposes a local spatial propagation based background model generation, a local linear illumination correction based background model update, and a regional central coordinates and edge keypoints constrained foreground region reselection. The three proposals make up a robust and hardware-friendly foreground detection method. Experimental results prove that the proposed hardware-friendly algorithm achieves high accuracy and robustness on various kinds of challenging cases. Meanwhile, the hardware implementation utilizes little hardware resources and achieves realtime processing of high-frame-rate (784 frame/second) video with the delay less than 1 ms/frame in image processing core. In addition, a practical system is implemented by combing a PC, a high-speed camera and a field programmable gate array (FPGA) for realworld applications. This work will significatively promote the development and application of high-speed human machine interaction. A demo of the proposed vision system working at 784 FPS is available at https://wcms.waseda.jp/em/5f84f75136a6. Note to Practitioners—This paper was motivated by the problem of high-frame-rate video contains large amount of redundant background pixels which makes ultra-high-speed human-machine interactions inaccessible. Existing approaches are mainly focused on designing complex background models, but processing speed, which is the most important issue for ultra-high-speed human-machine interactions, has received relatively little attention. This paper suggests a robust and hardware-friendly foreground detection algorithm which has been implemented as a hardware system by using an FPGA, a high-frame-rate camera, and a PC. We show that the hardware implementation utilizes less hardware resources and achieves real-time processing speed of 784 FPS with the delay less than 1 ms/frame in the image processing core. This work is a pioneering attempt of ultra-high-speed foreground detection, which will significatively speed up the wide applications of ultra-high-speed human machine interactions. [ABSTRACT FROM AUTHOR]

The invasive weed algorithm (IWO) is a meta-heuristic algorithm, which is an effective and promising optimiser to address the optimisation problems. In this study, a hybrid algorithm based on the self-adaptive invasive weed algorithm (IWO) and differential evolution algorithm (DE), named SIWODE, is proposed to address the continuous optimisation problems. In the proposed SIWODE, first, the two parameters are adaptively proposed to improve the convergence speed of the algorithm. Second, the crossover and mutation operations are introduced in SIWODE to improve the population diversity and increase the exploration capability during the iterative process. Furthermore, a local perturbation strategy is presented to improve exploitation ability during the late process. The exploration and exploitation ability of the algorithm is effectively balanced by cooperative mechanisms. The experiment results of SIWODE show that the SIWODE has the superior searching quality and stability than other mentioned approaches. [ABSTRACT FROM AUTHOR]

Toughening modification of poly(l‐lactide) (PLLA) with rubber particles is often realized at the cost of transparency, mechanical strength, and modulus because high rubber loadings are generally required for toughening. In this work, a promising strategy to simultaneously improve the transparency and stiffness–toughness performance of poly(butyl acrylate)‐poly(methyl methacrylate) (BAMMA) core‐shell rubber nanoparticles toughened PLLA blends by utilizing the stereocomplex (SC) crystallization between PLLA and poly(d‐lactide) (PDLA) is devised. The results reveal that the construction of SC crystallites in PLLA matrix via melt‐mixing PLLA/BAMMA blends with PDLA can prevent BAMMA nanoparticles from aggregation and promote them to form network‐like structure at lower contents. As a result, not only higher toughening efficiency with less rubber contents but also superior transparency is achieved in the PLLA/PDLA/BAMMA blends as compared with the PLLA/BAMMA ones where large aggregated BAMMA clusters are formed. Moreover, the outstanding reinforcement of SC crystallites network for PLLA can impart an enhanced tensile strength and modulus to PLLA/PDLA/BAMMA blends, thus improving the stiffness–toughness performance of PLLA/PDLA/BAMMA blends to a higher degree. This work demonstrates that SC crystallization is a promising solution to solve the contradiction between transparency and mechanical properties and then obtain superior comprehensive performances in rubber toughened PLLA blends. [ABSTRACT FROM AUTHOR]

As multipath is one of the dominating error sources for high accuracy Global Navigation Satellite System (GNSS) applications, multipath mitigation approaches are employed to minimize this hazardous error in receivers. Binary offset carriermodulation (BOC), as a modernized signal structure, is adopted to achieve significant enhancement. However, because of its multi-peak autocorrelation function, conventional multipath mitigation techniques for binary phase shift keying (BPSK) signal would not be optimal. Currently, non-parametric and parametric approaches have been studied specifically aiming at multipath mitigation for BOC signals. Non-parametric techniques, such as Code Correlation ReferenceWaveforms (CCRW), usually have good feasibility with simple structures, but suffer from low universal applicability for different BOC signals. Parametric approaches can thoroughly eliminate multipath error by estimating multipath parameters. The problems with this category are at the high computation complexity and vulnerability to the noise. To tackle the problem, we present a practical parametric multipath estimation method in the frequency domain for BOC signals. The received signal is transferred to the frequency domain to separate out the multipath channel transfer function for multipath parameter estimation. During this process, we take the operations of segmentation and averaging to reduce both noise effect and computational load. The performance of the proposed method is evaluated and compared with the previous work in three scenarios. Results indicate that the proposed averaging-Fast Fourier Transform (averaging-FFT) method achieves good robustness in severe multipath environments with lower computational load for both low-order and high-order BOC signals. [ABSTRACT FROM AUTHOR]

Local structural information is crucially important for human visual system to perceive natural scenes. Recent years, a variety of local image structure description methods have been proposed for the artificial modeling of visual perception. Although existing local image structure descriptors have shown successful performances, one general limitation is their numerical instability caused by ignoring the information of the spatial correlation of local orientation. In this paper, we propose a local image structure descriptor by modeling the anisotropic mechanism in the primary visual cortex. In particular, the pixel-wise anisotropy values of a given image are calculated by pseudo-Wigner-Ville distribution (PWVD) and Rényi entropy. Then the excitatory/inhibitory interactions among visual neurons in the local receptive field are modeled by measuring the similarities between their anisotropies. By mapping visual neurons to image pixels, the correlation between a central pixel and its local neighbors can be represented by a binary pattern which is named as local anisotropic pattern (LAP). Experimental results on texture classification verified that the proposed LAP has satisfactory texture classification accuracy, rotation invariance, and noise robustness; experimental results on no-reference image quality assessment demonstrated that the proposed LAP achieves state-of-the-art performance in objective evaluation of the perceptual quality of natural image, and this reflects that LAP can accurately represent the degradation of local image structure. [ABSTRACT FROM AUTHOR]

Blind image quality assessment (BIQA), which aims to estimate the perceptual quality of images without any reference information, is a very important yet challenging task. Although human visual system is sensitive to degradations on both spatial contrast and spatial distribution, most of the existing structural degradation based BIQA models consider only one of them. This study introduces a novel BIQA model by taking into account degradations on both contrast and spatial distribution. First, the authors construct a multi‐threshold local tetra pattern (MTLTrP) instead of local binary pattern to measure the changes on spatial distribution. Second, Weber–Laplacian of Gaussian (WLOG) operator, which responds to intensity contrast in a small spatial neighbourhood, is proposed to extract local contrast features. Finally, the joint statistics of MTLTrP and WLOG are utilised for BIQA model learning. Experimental results on three large benchmark databases demonstrate that the proposed model outperforms state‐of‐the‐art BIQA models, as well as with several well‐known full reference quality assessment methods. [ABSTRACT FROM AUTHOR]

As a matter of fact, mammalian visual system do not pay an equivalent attention to different regions in an image, the visual cortex is less sensitive to textures than non-textures. Therefore, to obtain the optimal visual quality and the perfect compression ratio simultaneously in image quantization, textures should be quantized coarsely, and non-textures should be quantized finely. The pulse-coupled neural networks (PCNN) is a model of synchronous pulse bursts in mammalian visual cortex, which has been proved to be extremely effective in image processing because of its biological background. In this work, a mammalian visual characteristics inspired perceptual image quantization strategy is proposed. It employs PCNN to extract textures from original image. Then, pixels in textures are quantized into less gray scale layers than pixels in non-textures. After that, quantized textures and quantized non-textures are consolidated. Experimental results prove validity and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a high sensitivity optical pressure sensor based on a graphene/molybdenum disulfide (MoS 2 ) composite film is proposed. The sensor is composed of a polydimethylsiloxane (PDMS) pyramid structure, graphene/MoS 2 composite film, and lithium niobate waveguide. The pressure deforms the PDMS pyramid structure, which leads to the change of the refractive index of the graphene/MoS 2 composite film, and finally be detectable sensitively by the variation of the interference spectrum. Experiments have been carried out using our sensor prototype, and the sensitivity is up to 575.233 nm/kPa in the pressure range of 0 kPa-0.123 kPa, which is much higher than that of typical optical pressure sensors. This shows the advantages of high sensitivity optical pressure sensors based on the graphene/MoS 2 composite film, which is expected to be applied in highly sensitive pressure detection environments.

Atherosclerosis, a chronic inflammatory condition primarily affecting large and medium arteries, is the main cause of cardiovascular diseases. Macrophages are key mediators of inflammatory responses. They are involved in all stages of atherosclerosis development and progression, from plaque formation to transition into vulnerable plaques, and are considered important therapeutic targets. Increasing evidence suggests that the modulation of macrophage polarization can effectively control the progression of atherosclerosis. Herein, we explore the role of macrophage polarization in the progression of atherosclerosis and summarize emerging therapies for the regulation of macrophage polarization. Thus, the aim is to inspire new avenues of research in disease mechanisms and clinical prevention and treatment of atherosclerosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wu, He, Song, Chen, Lin, Sun, Zhou, Peng, Du, Zheng and Liu.)

Background Extracellular vesicles (EVs) are a popular treatment candidate for myocardial injury. This work investigated the effects of mesenchymal stem cells (MSCs)-secreted EVs-derived miR-200b-3p on cardiomyocyte apoptosis and inflammatory response after myocardial infarction (MI) through targeting BCL2L11 (Bcl-2-like protein 11) . Methods and Results EVs from MSCs were isolated and identified. EVs from MSCs with transfection of miR-200b-3p for overexpression were injected into MI mice. The effect of miR-200b-3p on cardiac function, infarction area, myocardial fibrosis, cardiomyocyte apoptosis, and inflammatory response was determined in MI mice. The targeting relationship between miR-200b-3p and BCL2L11 was verified, and the interaction between BCL2L11 and NLR family pyrin domain containing 1 (NLRP1) was also verified. MI mice were injected with an overexpressing BCL2L11 lentiviral vector to clarify whether BCL2L11 can regulate the effect of miR-200b-3p on MI mice. EVs from MSCs were successfully extracted. MSCs-EVs improved cardiac function and reduced infarction area, apoptosis of cardiomyocytes, myocardial fibrosis, and inflammation in MI mice. Upregulation of miR-200b-3p further enhanced the effects of MSCs-EVs on the myocardial injury of MI mice. BCL2L11 was targeted by miR-200b-3p and bound to NLRP1. Upregulation of BCL2L11 negated the role of miR-200b-3p-modified MSCs-EVs in MI mice. Conclusions A summary was obtained that miR-200b-3p-encapsulated MSCs-EVs protect against MI-induced apoptosis of cardiomyocytes and inflammation via suppressing BCL2L11.

Background: The aim of present study is to investigate the role of lymphotoxin beta receptor (Ltβr) in lipopolysaccharides (LPS)-induced inflammation in vascular smooth muscle cells (VSMCs) and whether its effects are mediated by modulating microRNAs (miRNAs) and nuclear factor-kappa B (NF-κB)., Methods: Mouse aortic smooth muscle cell (SMC) line (MOVAS cells) were transduced with short hairpin Ltβr (shLtβr) and mRNA and protein expression level of Ltβr were measured by qPCR and Western blot in shLtβr-transduced cells. Lentiviral vector-transduced (control) and lentiviral vector/shLtβr-transduced MOVAS cells were stimulated with LPS (1 μg/mL) for 0, 16, or 24 h. Then the mRNA and protein levels of Ltβr, interleukin-18 (IL-18), p-p65, p65 and vascular cell adhesion molecule 1 (VCAM-1) were measured by real-time quantitative polymerase chain reaction (qPCR), Western blot and enzyme-linked immunosorbent assay (ELISA). Different miRNAs expression in LPS-stimulated normal and shLtβr-transduced cells were detected by small RNA sequencing (smRNA-seq)., Results: The mRNA and protein expression of Ltβr was significantly downregulated in shLtβr-transduced cells. LPS-increased the mRNA and protein levels of Ltβr, IL-18, p-p65 and VCAM-1 in were attenuated by shLtβr transducing compared with LPS-stimulated control group. Moreover, LPS treatment induced 10 upregulated and 64 downregulated miRNAs in shLtβr-transduced cells compared with control cells. Moreover, miR-146b-5p and miR-27a-5p levels were significantly decreased in shLtβr-transduced cells., Conclusions: Our results show for the first time that the role of Ltβr in regulating inflammatory response in LPS-stimulated VSMCs via modulating miRNAs and NF-κB pathway. Our findings might provide valuable information with respect to better understanding in the treatment of cardiovascular diseases, such as atherosclerosis.

Background: Human alpha 1-antitrypsin (A1AT) is involved in the pathophysiological process underlying ischemic acute kidney injury (AKI). To test the hypothesis that serum A1AT (sA1AT) is a predictor for severe AKI after cardiopulmonary bypass (CPB), we conducted a prospective cohort study in 201 patients undergoing cardiac surgery., Methods: We collected blood and urine samples, and analyzed the sA1AT and other injury biomarkers during the perioperative period. Severe AKI is defined as Kidney Disease Improving Global Outcomes (KDIGO) stage 2 or 3, and overall AKI is defined as KDIGO stage 1, 2, or 3., Results: Ninety-one (45.3%) patients developed overall AKI, and 22 (10.9%) among them developed severe AKI after operation. sA1AT level spiked 2 hours after surgery in patients who subsequently developed severe AKI, while serum creatinine peaked 12 hours after operation. Higher postoperative sA1AT independently correlated to the development of severe AKI [OR, 1.54 (1.17-2.03); P=0.002]. The highest quartile of postoperative sA1AT level was associated with 6-fold higher hazards of severe AKI compared to the lowest quartile. Higher sA1AT levels were correlated with longer stays in the intensive care unit and the hospital. For predicting severe AKI, the AUC of sA1AT 2 hours after CPB reached 0.814. After combining with urine T cell immunoglobulin mucin-1 and clinical model, the AUC improved to 0.923., Conclusions: In summary, sA1AT is a valuable predictor of severe AKI development and prolonged ICU and hospital stays in patients after cardiac surgery., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest to declare., (2019 Journal of Thoracic Disease. All rights reserved.)

Background: Dyslipidemia is commonly observed in various kidney diseases, renal specific secreted erythropoietin (EPO) may participate in this process. However, how this process is regulated remains elusive., Method: Dyslipidemia was evaluated in chronic kidney disease and ischemia kidney injury animal model. Primary cultured adipocytes were harvested to investigate the lipid metabolic effect of EPO. Lipidemia was evaluated in EPO treated animals. Blood samples from cardiac surgery-induced kidney injury patient were collected to assess correlationship between EPO and lipidemia., Findings: We found a decrease in secreted EPO and hypertriglyceridemia in chronic kidney disease (CKD) mice. In contrast, in renal ischemia animal model, increased EPO triggered by hypoxia signaling activation, was accompanied by decreased triglyceride (TG) in serum. Mechanistically, circulating EPO modulated JAK2-STAT5 signaling, which in turn enhanced lipid catabolism in peripheral adipose tissue and contributed to dysregulated lipidemia. Delivering of recombinant EPO into both wild type and CKD mice suppressed TG in serum by accelerating lipid catabolism in adipose tissue. In a cohort of patients diagnosed with acute kidney injury after cardiopulmonary bypass surgery, the decreased TG and cholesterol negatively correlated with increased EPO in serum., Interpretation: This study depicted a new mechanism by which renal secreted EPO controlled lipidemia in kidney diseases including chronic kidney disease. Circulating EPO stimulated lipid catabolism by targeting JAK2-STATA5 signaling in peripheral adipose tissue, providing new therapeutic target for dyslipidemia treatment., Funding: This work was supported by grants from the National Natural Science Foundation of China (Nos. 81700640 and 81970608)., (Copyright © 2019 The Author(s). Published by Elsevier B.V. All rights reserved.)

This study was designed to test the hypothesis that whether the plasma level of advanced oxidant protein products (AOPPs) would be useful for the clinical diagnosis of acute lung injury (ALI) following cardiac surgery with the technique of cardiopulmonary bypass (CPB). In this prospective study, seventy consecutive adults undergoing open heart surgery with CPB were included and assigned into the ALI (n = 18) and non-ALI (n = 52) groups according to the American-European Consensus Criteria. Plasma concentrations of AOPPs were measured at baseline, postoperative 1 h, 12 h, 24 h, and 48 h. Eighteen patients (25.7 %) developed ALI after surgery. The plasma levels of AOPPs in the ALI group were significantly increased and remained considerably higher at all time points after operation (all P < 0.05). Multivariate logistic regression analysis revealed that the plasma level of AOPPs at 1 h after operation was an independent predictor for the diagnosis of ALI (OR 1.164; 95 % CI 1.068-1.269; P = 0.001). Plasma level of AOPPs could serve as an early biomarker of the incidence of ALI in adult patients who underwent open cardiac surgery with the technique of CPB.