University of Electronic Science and Technology of China

About: University of Electronic Science and Technology of China is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Antenna (radio) & Dielectric. The organization has 50594 authors who have published 58502 publications receiving 711188 citations. The organization is also known as: UESTC.

Prospects and challenges of extracellular vesicle-based drug delivery system: considering cell source

Abstract: Extracellular vesicles (EVs), including exosomes, microvesicles, and apoptotic bodies, are nanosized membrane vesicles derived from most cell types. Carrying diverse biomolecules from their parent cells, EVs are important mediators of intercellular communication and thus play significant roles in physiological and pathological processes. Owing to their natural biogenesis process, EVs are generated with high biocompatibility, enhanced stability, and limited immunogenicity, which provide multiple advantages as drug delivery systems (DDSs) over traditional synthetic delivery vehicles. EVs have been reported to be used for the delivery of siRNAs, miRNAs, protein, small molecule drugs, nanoparticles, and CRISPR/Cas9 in the treatment of various diseases. As a natural drug delivery vectors, EVs can penetrate into the tissues and be bioengineered to enhance the targetability. Although EVs' characteristics make them ideal for drug delivery, EV-based drug delivery remains challenging, due to lack of standardized isolation and purification methods, limited drug loading efficiency, and insufficient clinical grade production. In this review, we summarized the current knowledge on the application of EVs as DDS from the perspective of different cell origin and weighted the advantages and bottlenecks of EV-based DDS.

High-Performance Electrohydrogenation of N2 to NH3 Catalyzed by Multishelled Hollow Cr2O3 Microspheres under Ambient Conditions

Abstract: Electrohydrogenation of N2 to NH3 is emerging as an environmentally benign strategy to tackle the issues associated with the energy-intensive, CO2-emitting Haber–Bosch process. However, the method is severely challenged by N2 activation and needs efficient N2 reduction reaction (NRR) catalysts. Here, we report that multishelled hollow Cr2O3 microspheres (MHCMs), which are synthesized by a facile synthetic route, can serve as efficient and selective non-noble metal electrocatalysts for NRR. In 0.1 M Na2SO4 solution, the MHCMs achieve a high Faradaic efficiency (6.78%) and a large NH3 yield (25.3 μg h–1 mgcat–1) at −0.9 V vs reversible hydrogen electrode. The MHCMs also exhibit high stability during the reaction. Density functional theory calculations suggest that NRR over MHCMs occurs via both distal associative and partially alternative routes.

Efficient and Accurate Arbitrary-Shaped Text Detection With Pixel Aggregation Network

Abstract: Scene text detection, an important step of scene text reading systems, has witnessed rapid development with convolutional neural networks. Nonetheless, two main challenges still exist and hamper its deployment to real-world applications. The first problem is the trade-off between speed and accuracy. The second one is to model the arbitrary-shaped text instance. Recently, some methods have been proposed to tackle arbitrary-shaped text detection, but they rarely take the speed of the entire pipeline into consideration, which may fall short in practical applications. In this paper, we propose an efficient and accurate arbitrary-shaped text detector, termed Pixel Aggregation Network (PAN), which is equipped with a low computational-cost segmentation head and a learnable post-processing. More specifically, the segmentation head is made up of Feature Pyramid Enhancement Module (FPEM) and Feature Fusion Module (FFM). FPEM is a cascadable U-shaped module, which can introduce multi-level information to guide the better segmentation. FFM can gather the features given by the FPEMs of different depths into a final feature for segmentation. The learnable post-processing is implemented by Pixel Aggregation (PA), which can precisely aggregate text pixels by predicted similarity vectors. Experiments on several standard benchmarks validate the superiority of the proposed PAN. It is worth noting that our method can achieve a competitive F-measure of 79.9% at 84.2 FPS on CTW1500.

Measuring Economic Impacts of Drought: A Review and Discussion

Abstract: Purpose – The purpose of this paper is to provide useful information for members of the weather community and policy makers, to help them understand the full scope of drought economic impacts and assessment methodologies, and to help determine the feasibility of future drought mitigation programs.Design/methodology/approach – To accomplish the objective, the paper reviews the literature of drought economic impact studies in both agricultural and non‐agricultural sectors, summarizes the methods and data employed, compares the various results, and investigates the problems and limitations of previous studies.Findings – The paper concludes with a discussion of the challenges and directions of future improvement on drought economic impact assessment.Originality/value – This paper gives a comprehensive review of drought economic impacts and the associated quantitative assessment methodologies, which provides valuable information to rational decisions supporting drought mitigation policies and programs.