Institution
Wuhan University
Education•Wuhan, China•
About: Wuhan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Computer science & Population. The organization has 92849 authors who have published 92882 publications receiving 1691049 citations. The organization is also known as: WHU & Wuhan College.
Topics: Computer science, Population, Catalysis, Feature extraction, Apoptosis
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a seafood waste (chitin)-derived hierarchically porous nitrogen-doped carbon microsphere (NCS) electrode with a surface-driven potassium storage mechanism is developed.
371 citations
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TL;DR: In this article, a new sorbent comprising silica-coated magnetic nanoparticles (SCMNPs) modified with γ-mercaptopropropyltrimethoxysilane (γ-MPTMS) was used for solid phase extraction of trace amounts of Cd, Cu, Hg, and Pb from biological and environmental samples.
371 citations
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TL;DR: The aim of this study was to analyze the expression of known and potential SARS‐CoV‐2 receptors and related molecules in the extensive collection of primary human cells and tissues from healthy subjects of different age and from patients with risk factors and known comorbidities of COVID‐19.
Abstract: Background: Morbidity and mortality from COVID-19 caused by novel coronavirus SARS-CoV-2 is accelerating worldwide, and novel clinical presentations of COVID-19 are often reported. The range of human cells and tissues targeted by SARS-CoV-2, its potential receptors and associated regulating factors are still largely unknown. The aim of our study was to analyze the expression of known and potential SARS-CoV-2 receptors and related molecules in the extensive collection of primary human cells and tissues from healthy subjects of different age and from patients with risk factors and known comorbidities of COVID-19.
Methods: We performed RNA sequencing and explored available RNA-Seq databases to study gene expression and co-expression of ACE2, CD147 (BSG), and CD26 (DPP4) and their direct and indirect molecular partners in primary human bronchial epithelial cells, bronchial and skin biopsies, bronchoalveolar lavage fluid, whole blood, peripheral blood mononuclear cells (PBMCs), monocytes, neutrophils, DCs, NK cells, ILC1, ILC2, ILC3, CD4+ and CD8+ T cells, B cells, and plasmablasts. We analyzed the material from healthy children and adults, and from adults in relation to their disease or COVID-19 risk factor status.
Results: ACE2 and TMPRSS2 were coexpressed at the epithelial sites of the lung and skin, whereas CD147 (BSG), cyclophilins (PPIA andPPIB), CD26 (DPP4), and related molecules were expressed in both epithelium and in immune cells. We also observed a distinct age-related expression profile of these genes in the PBMCs and T cells from healthy children and adults. Asthma, COPD, hypertension, smoking, obesity, and male gender status generally led to the higher expression of ACE2- and CD147-related genes in the bronchial biopsy, BAL, or blood. Additionally, CD147-related genes correlated positively with age and BMI. Interestingly, we also observed higher expression of CD147-related genes in the lesional skin of patients with atopic dermatitis.
Conclusions: Our data suggest different receptor repertoire potentially involved in the SARS-CoV-2 infection at the epithelial barriers and in the immune cells. Altered expression of these receptors related to age, gender, obesity and smoking, as well as with the disease status, might contribute to COVID-19 morbidity and severity patterns.
Keywords: COPD; COVID-19; COVID-19 children; SARS receptor; asthma; hypertension; obesity.
371 citations
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TL;DR: The quantitative structure-activity relationships (QSARs) were established and correlated to the Tafel equation, suggesting that the nonradical oxidation by the CNT-PDS* undergoes a mechanism analogous to anodic oxidation.
Abstract: Carbon-driven advanced oxidation processes are appealing in wastewater purification because of the metal-free feature of the carbocatalysts. However, the regime of the emerging nonradical pathway i...
371 citations
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TL;DR: An algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel- separation fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localization with BLE beacons is proposed.
Abstract: Indoor wireless localization using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel-separate fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localization with BLE beacons. The proposed algorithm uses FP and PRM to estimate the target’s location and the distances between the target and BLE beacons respectively. We compare the performance of distance estimation that uses separate PRM for three advertisement channels (i.e., the separate strategy) with that use an aggregate PRM generated through the combination of information from all channels (i.e., the aggregate strategy). The performance of FP-based location estimation results of the separate strategy and the aggregate strategy are also compared. It was found that the separate strategy can provide higher accuracy; thus, it is preferred to adopt PRM and FP for each BLE advertisement channel separately. Furthermore, to enhance the robustness of the algorithm, a two-level outlier detection mechanism is designed. Distance and location estimates obtained from PRM and FP are passed to the first outlier detection to generate improved distance estimates for the EKF. After the EKF process, the second outlier detection algorithm based on statistical testing is further performed to remove the outliers. The proposed algorithm was evaluated by various field experiments. Results show that the proposed algorithm achieved the accuracy of <2.56 m at 90% of the time with dense deployment of BLE beacons (1 beacon per 9 m), which performs 35.82% better than <3.99 m from the Propagation Model (PM) + EKF algorithm and 15.77% more accurate than <3.04 m from the FP + EKF algorithm. With sparse deployment (1 beacon per 18 m), the proposed algorithm achieves the accuracies of <3.88 m at 90% of the time, which performs 49.58% more accurate than <8.00 m from the PM + EKF algorithm and 21.41% better than <4.94 m from the FP + EKF algorithm. Therefore, the proposed algorithm is especially useful to improve the localization accuracy in environments with sparse beacon deployment.
371 citations
Authors
Showing all 93441 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jing Wang | 184 | 4046 | 202769 |
Jiaguo Yu | 178 | 730 | 113300 |
Lei Jiang | 170 | 2244 | 135205 |
Gang Chen | 167 | 3372 | 149819 |
Omar M. Yaghi | 165 | 459 | 163918 |
Xiang Zhang | 154 | 1733 | 117576 |
Yi Yang | 143 | 2456 | 92268 |
Thomas P. Russell | 141 | 1012 | 80055 |
Jun Chen | 136 | 1856 | 77368 |
Lei Zhang | 135 | 2240 | 99365 |
Chuan He | 130 | 584 | 66438 |
Han Zhang | 130 | 970 | 58863 |
Lei Zhang | 130 | 2312 | 86950 |
Zhen Li | 127 | 1712 | 71351 |
Chao Zhang | 127 | 3119 | 84711 |