Wuhan University

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.

On-Demand Dissolvable Self-Healing Hydrogel Based on Carboxymethyl Chitosan and Cellulose Nanocrystal for Deep Partial Thickness Burn Wound Healing.

Abstract: Deep partial thickness burn wounds present big challenges due to the long healing time, large size and irregular shape, pain and reinjury at wound dressing changes, as well as scarring. The clinically effective therapy to alleviate pain at wound dressing changes, and the scar left on the skin after the healing of wound is still unavailable. To combat this, we develop a nanocomposite self-healing hydrogel that can be injected into irregular and deep burn wound beds and subsequently rapidly self-heal to reform into an integrated piece of hydrogel that thoroughly fills the wound area and protects the wound site from external environment, finally being painlessly removed by on-demand dissolving using amino acid solution at wound dressing changes, which accelerates deep partial thickness burn wound healing and prevents scarring. The hydrogel is made out of naturally occurring polymers, namely, water-soluble carboxymethyl chitosan (CMC) and rigid rod-like dialdehyde-modified cellulose nanocrystal (DACNC). They are cross-linked by dynamic Schiff-base linkages between amines from CMC and aldehydes from DACNC. The large aspect ratio and specific surface area of DACNC raise massive active junctions within the hydrogel, which can be readily broken and reformed, allowing hydrogel to rapidly self-heal. Moreover, DACNC serves as nanoreinforcing fillers to improve the hydrogel strength, which also restricts the "soft" CMC chains' motion when soaked in aqueous system, endowing high fluid uptake capacity (350%) to hydrogel while maintaining integrity. Cytotoxicity assay and three-dimensional cell culture demonstrate excellent biocompatibility of the hydrogel and capacity as extracellular matrix to support cell growth. This work opens a novel pathway to fabricate on-demand dissolvable self-healing hydrogels to speed deep partial thickness burn wound healing and eliminate pain at wound dressing changes and prevent scar formation.

Review on Estimation of Land Surface Radiation and Energy Budgets From Ground Measurement, Remote Sensing and Model Simulations

Abstract: Land surface radiation and energy budgets are critical components of any land surface models that characterize hydrological, ecological and biogeochemical processes. The estimates of their components generated from remote sensing data or simulations from numerical models have large uncertainties. This paper provides a comprehensive review of recent advances in estimating insolation, albedo, clear-sky longwave downward and upwelling radiation, all-wave net radiation and evapotranspiration from ground measurements, remote sensing algorithms and products, as well as numerical model simulations. The decadal variations of these components are also discussed.

Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan, China.

Abstract: In December 2019, coronavirus disease 2019 (COVID-19) outbreak was reported from Wuhan, China. Information on the clinical course and prognosis of COVID-19 was not thoroughly described. We described the clinical courses and prognosis in COVID-19 patients. Retrospective case series of COVID-19 patients from Zhongnan Hospital of Wuhan University in Wuhan and Xishui Hospital, Hubei Province, China, up to February 10, 2020. Epidemiological, demographic, and clinical data were collected. The clinical course of survivors and non-survivors were compared. Risk factors for death were analyzed. A total of 107 discharged patients with COVID-19 were enrolled. The clinical course of COVID-19 presented as a tri-phasic pattern. Week 1 after illness onset was characterized by fever, cough, dyspnea, lymphopenia, and radiological multi-lobar pulmonary infiltrates. In severe cases, thrombocytopenia, acute kidney injury, acute myocardial injury, and adult respiratory distress syndrome were observed. During week 2, in mild cases, fever, cough, and systemic symptoms began to resolve and platelet count rose to normal range, but lymphopenia persisted. In severe cases, leukocytosis, neutrophilia, and deteriorating multi-organ dysfunction were dominant. By week 3, mild cases had clinically resolved except for lymphopenia. However, severe cases showed persistent lymphopenia, severe acute respiratory dyspnea syndrome, refractory shock, anuric acute kidney injury, coagulopathy, thrombocytopenia, and death. Older age and male sex were independent risk factors for poor outcome of the illness. A period of 7–13 days after illness onset is the critical stage in the COVID-19 course. Age and male gender were independent risk factors for death of COVID-19.

Measurements of POI-based mixed use and their relationships with neighbourhood vibrancy

Abstract: Although mixed use is an emerging strategy that has been widely accepted in urban planning for promoting neighbourhood vibrancy, there is no consensus on how to quantitatively measure the mix and the effects of mixed use on neighbourhood vibrancy. Shannon entropy, the most commonly used diversity measurement in assessing mixed use, has been found to be inadequate in measuring the multifaceted, multidimensional characteristics of mixed use. And lack of data also makes it difficult to find the relationship between mixed use and neighbourhood vibrancy. However, the recent availability of new sources including mobile phone data and Point of Interest POI data have made it possible to develop new indices of mixed use and neighbourhood vibrancy to analyse their relationships. Taking advantage of these emerging new data sources, this study used the numbers of mobile phone users in a 24-hour period as a proxy of neighbourhood vibrancy and used POIs from a navigation database to develop a series of mixed-use indicators that can better reflect the multifaceted, multidimensional characteristics of mixed-use neighbourhoods. The Hill numbers, a unified form of diversity measurement used in ecological literature that includes richness, entropy, and the Simpson index, are used to measure the degrees of mixed use. Using such fine-grained data sets and the Hill numbers allowed us to obtain better insights into the relationship between mixed use and neighbourhood vibrancy. Four models varying in POI measurements that reflect different dimensions of mixed use were presented. The results showed that either POI density or entropy can explain approximately 1% of neighbourhood vibrancy, while POI richness contributes significantly in improving neighbourhood vibrancy. The results also revealed that the entropy has limitations as a measure for representing mixed use and demonstrated the necessity of adopting a set of more appropriate measurements for mixed use. Increasing the number of POIs has limited power to improve neighbourhood vibrancy compared with encouraging the mixing of complementary POIs. These exploratory findings may be useful for adjusting mixed-use assessments and to help guide urban planning and neighbourhood design.

Align Deep Features for Oriented Object Detection

Abstract: The past decade has witnessed significant progress on detecting objects in aerial images that are often distributed with large-scale variations and arbitrary orientations. However, most of existing methods rely on heuristically defined anchors with different scales, angles, and aspect ratios, and usually suffer from severe misalignment between anchor boxes (ABs) and axis-aligned convolutional features, which lead to the common inconsistency between the classification score and localization accuracy. To address this issue, we propose a single-shot alignment network (S²A-Net) consisting of two modules: a feature alignment module (FAM) and an oriented detection module (ODM). The FAM can generate high-quality anchors with an anchor refinement network and adaptively align the convolutional features according to the ABs with a novel alignment convolution. The ODM first adopts active rotating filters to encode the orientation information and then produces orientation-sensitive and orientation-invariant features to alleviate the inconsistency between classification score and localization accuracy. Besides, we further explore the approach to detect objects in large-size images, which leads to a better trade-off between speed and accuracy. Extensive experiments demonstrate that our method can achieve the state-of-the-art performance on two commonly used aerial objects' data sets (i.e., DOTA and HRSC2016) while keeping high efficiency.