881 research outputs found

    Diagnosis for topological semimetals in the absence of spin-orbital coupling

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    Topological semimetals are under intensive theoretical and experimental studies. The first step of these studies is always the theoretical (numerical) predication of one of several candidate materials, starting from first principles. In these calculations, it is crucial that all topological band crossings, including their types and positions in the Brillouin zone, are found. While band crossings along high-symmetry lines, which are routinely scanned in numerics, are simple to locate, the ones at generic momenta are notoriously time-consuming to find, and may be easily missed. In this paper, we establish a theoretical scheme of diagnosis for topological semimetals where all band crossings are at generic momenta in systems with time-reversal symmetry and negligible spin-orbital coupling. The scheme only uses the symmetry (inversion and rotation) eigenvalues of the valence bands at high-symmetry points in the BZ as input, and provides the types, numbers and configurations of all topological band crossings, if any, at generic momenta. The nature of new diagnosis scheme allows for full automation and parallelizations, and paves way to high throughput numerical predictions of topological materials.Comment: 21 pages, 5 figures, 1 table; v4: accepted in PRX, a "PRELIMINARIES" section adde

    Analysis of the Impact of Central bank Digital Currency on the Demand for Transactional Currency

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    This paper takes the development of Central bank digital currencies as a perspective, introduces it into the Baumol-Tobin money demand theoretical framework, establishes the transactional money demand model under Central bank Digital Currency, and qualitatively analyzes the influence mechanism of Central bank digital currencies on transactional money demand; meanwhile, quarterly data from 2010-2022 are selected to test the relationship between Central bank digital currencies and transactional money demand through the ARDL model. The long-run equilibrium and short-run dynamics between the demand for Central bank digital currencies and transactional currency are examined by ARDL model. The empirical results show that the issuance and circulation of Central bank digital currencies will reduce the demand for transactional money. Based on the theoretical analysis and empirical test, this paper proposes that China should explore a more effective Currency policy in the context of Central bank digital currencies while promoting the development of Central bank digital currencies in a prudent manner in the future.Comment: Central bank digital currencies; transactional money demand; ARDL model. arXiv admin note: text overlap with arXiv:2310.0732

    Scale Estimation with Dual Quadrics for Monocular Object SLAM

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    The scale ambiguity problem is inherently unsolvable to monocular SLAM without the metric baseline between moving cameras. In this paper, we present a novel scale estimation approach based on an object-level SLAM system. To obtain the absolute scale of the reconstructed map, we derive a nonlinear optimization method to make the scaled dimensions of objects conforming to the distribution of their sizes in the physical world, without relying on any prior information of gravity direction. We adopt the dual quadric to represent objects for its ability to fit objects compactly and accurately. In the proposed monocular object-level SLAM system, dual quadrics are fastly initialized based on constraints of 2-D detections and fitted oriented bounding box and are further optimized to provide reliable dimensions for scale estimation.Comment: 8 pages, 6 figures, accepted by IROS202

    Knowledge, attitudes, and practices associated with bioterrorism preparedness in healthcare workers: a systematic review

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    IntroductionBioterrorism is an important issue in the field of biosecurity, and effectively dealing with bioterrorism has become an urgent task worldwide. Healthcare workers are considered bioterrorism first responders, who shoulder essential responsibilities and must be equipped to deal with bioterrorism. This study aims to extract and summarize the main research components of the bioterrorism knowledge, attitude, and practice dimensions among healthcare workers.MethodThis study utilized a systematic review research design based on the PRISMA 2020 guidelines. A literature search was conducted in the PubMed, Web of Science, and Scopus databases for peer-reviewed literature, and the Mixed Methods Appraisal Tool (MMAT) version 2018 was used to assess the quality of the literature.ResultA total of 16 studies were included in the final selection. Through the analysis and summary of the included studies, three main aspects and 14 subaspects of the knowledge dimension, three main aspects and 10 subaspects of the attitude dimension, and two main aspects and six subaspects of the practice dimension were extracted.ConclusionThis study conducted a literature review on bioterrorism knowledge, attitudes, and practices for healthcare workers based on the PRISMA 2020 guidelines. The findings can guide improvements in health literacy and provide beneficial information to professional organizations that need to respond effectively to bioterrorism

    On the use of thermal forces to probe kinesin’s response to force

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    The stepping dynamics of cytoskeletal motor proteins determines the dynamics of cargo transport. In its native cellular environment, a molecular motor is subject to forces from several sources including thermal forces and forces ensuing from the interaction with other motors bound to the same cargo. Understanding how the individual motors respond to these forces can allow us to predict how they move their cargo when part of a team. Here, using simulation, we show that details of how the kinesin motor responds to small assisting forces–which, at the moment, are not experimentally constrained-can lead to significant changes in cargo dynamics. Using different models of the force-dependent detachment probability of the kinesin motor leads to different predictions on the run-length of the cargo they carry. These differences emerge from the thermal forces acting on the cargo and transmitted to the motor through the motor tail that tethers the motor head to the microtubule. We show that these differences appear for cargo carried by individual motors or motor teams, and use our findings to propose the use of thermal forces as a probe of kinesin’s response to force in this otherwise inaccessible force regime

    Downregulation of hypoxia-inducible factor-1α by RNA interference alleviates the development of collagen-induced arthritis in rats

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    Rheumatoid arthritis (RA) is the most common type of autoimmune arthritis. Hypoxia-inducible factor-1α (HIF-1α) as a transcription factor in response to hypoxia suggests that it could be a potential therapeutic target for the treatment of RA. In this study, we assessed whether the HIF pathway blockade attenuates the manifestations of RA in the collagen-induced arthritis (CIA) rat model. We constructed a short hairpin RNA (shRNA) lentiviral expression vector targeting HIF-1α (pLVX-shRNA-HIF-1α) and to achieve HIF-1α RNA interference. Quantitative RT-PCR, immunofluorescence staining, and western blot were used to detect the expressions of HIF-1α, vascular endothelial growth factor (VEGF), phsopho (p)-p65, and p-IКBɑ mRNA and protein, respectively. Micro-computed tomography was used to investigate joint morphology at different time points after CIA induction. Moreover, enzyme-linked immunosorbent assay (ELISA) was used to monitor the expression of inflammatory cytokines. In vitro analyses revealed that pLVX-shRNA-HIF-1α effectively inhibited the expression of HIF-1α and VEGF and led to the activation of p-65 and p-IКBɑ, as well as decreased proinflammatory cytokine expression in cell culture. Inhibition of HIF-1α in rats decreased signs of a systemic inflammatory condition, together with decreased pathological changes of RA. Moreover, downregulation of HIF-1α expression markedly reduced the synovitis and angiogenesis. In conclusion, we have shown that pharmacological inhibition of HIF-1 may improve the clinical manifestations of RA

    Genome-wide analysis of soybean hypoxia inducible gene domain containing genes: a functional investigation of GmHIGD3

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    The response of Hypoxia Inducible Gene Domain (HIGD) proteins to hypoxia plays a crucial role in plant development. However, the research on this gene family in soybean has been lacking. In this study, we aimed to identify and comprehensively analyze soybean HIGD genes using the Glycine max genome database. As a result, six GmHIGD genes were successfully identified, and their phylogeny, gene structures, and putative conserved motifs were analyzed in comparison to Arabidopsis and rice. Collinearity analysis indicated that the HIGD gene family in soybean has expanded to some extent when compared to Arabidopsis. Additionally, the cis-elements in the promoter regions of GmHIGD and the transcription factors potentially binding to these regions were identified. All GmHIGD genes showed specific responsiveness to submergence and hypoxic stresses. Expression profiling through quantitative real-time PCR revealed that these genes were significantly induced by PEG treatment in root tissue. Co-expressed genes of GmHIGD were primarily associated with oxidoreductase and dioxygenase activities, as well as peroxisome function. Notably, one of GmHIGD genes, GmHIGD3 was found to be predominantly localized in mitochondria, and its overexpression in Arabidopsis led to a significantly reduction in catalase activity compared to wild-type plants. These results bring new insights into the functional role of GmHIGD in terms of subcellular localization and the regulation of oxidoreductase activity

    Mobile Robot Tracking with Deep Learning Models under the Specific Environments

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    Visual-based target tracking is one of the critical methodologies for the control problem of multi-robot systems. In dynamic mobile environments, it is common to lose the tracking targets due to partial visual occlusion. Technologies based on deep learning (DL) provide a natural solution to this problem. DL-based methods require less human intervention and fine-tuning. The framework has flexibility to be retrained with customized data sets. It can handle massive amounts of available video data in the target tracking system. This paper discusses the challenges of robot tracking under partial occlusion and compares the system performance of recent DL models used for tracking, namely you-only-look-once (YOLO-v5), Faster region proposal network (R-CNN) and single shot multibox detector (SSD). A series of experiments are committed to helping solve specific industrial problems. Four data sets are that cover various occlusion statuses are generated. Performance metrics of F1 score, precision, recall, and training time are analyzed under different application scenarios and parameter settings. Based on the metrics mentioned above, a comparative metric P is devised to further compare the overall performance of the three DL models. The SSD model obtained the highest P score, which was 13.34 times that of the Faster RCNN model and was 3.39 times that of the YOLOv5 model with the designed testing data set 1. The SSD model obtained the highest P scores, which was 11.77 times that of the Faster RCNN model and was 2.43 times that of the YOLOv5 model with the designed testing data set 2. The analysis reveals different characteristics of the three DL models. Recommendations are made to help future researchers to select the most suitable DL model and apply it properly in a system design.</jats:p

    Axitinib targets cardiac fibrosis in pressure overload-induced heart failure through VEGFA-KDR pathway

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    BackgroundThere are no specific clinical medications that target cardiac fibrosis in heart failure (HF). Recent studies have shown that tyrosine kinase inhibitors (TKIs) may benefit fibrosis in various organs. However, there is limited research on their application in cardiac fibrosis. Axitinib, an FDA-approved tyrosine kinase inhibitor, was used to evaluate its effects on cardiac fibrosis and function in pressure overload-induced heart failure.MethodsTo build a pharmacological network, the pharmacological targets of axitinib were first retrieved from databases and coupled with key heart failure gene molecules for analysis and prediction. To validate the results outlined above, 8-week-old male C57BL/6 J mice were orally administrated of axitinib (30 mg/kg) daily for 8 weeks after Transverse Aortic Constriction (TAC) surgery. Mouse cardiomyocytes and cardiac fibroblasts were used as cell lines to test the function and mechanism of axitinib.ResultsWe found that the pharmacological targets of axitinib could form a pharmacological network with key genes involved in heart failure. The VEGFA-KDR pathway was found to be closely related to the differential gene expression of human heart-derived primary cardiomyocyte cell lines treated with axitinib, based on analysis of the publicly available dataset. The outcomes of animal experiments demonstrated that axitinib therapy greatly reduced cardiac fibrosis and improved TAC-induced cardiac dysfunction. Further research has shown that the expression of transforming growth factor-β(TGF-β) and other fibrosis genes was significantly reduced in vivo and in vitro.ConclusionOur study provides evidence for the repurposing of axitinib to combat cardiac fibrosis, and offers new insights into the treatment of patients with HF
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