Nanjing University of Science and Technology

About: Nanjing University of Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 31581 authors who have published 36390 publications receiving 525474 citations. The organization is also known as: Nánjīng Lǐgōng Dàxué & Nánlǐgōng.

Gated Fusion Network for Single Image Dehazing

Abstract: In this paper, we propose an efficient algorithm to directly restore a clear image from a hazy input. The proposed algorithm hinges on an end-to-end trainable neural network that consists of an encoder and a decoder. The encoder is exploited to capture the context of the derived input images, while the decoder is employed to estimate the contribution of each input to the final dehazed result using the learned representations attributed to the encoder. The constructed network adopts a novel fusion-based strategy which derives three inputs from an original hazy image by applying White Balance (WB), Contrast Enhancing (CE), and Gamma Correction (GC). We compute pixel-wise confidence maps based on the appearance differences between these different inputs to blend the information of the derived inputs and preserve the regions with pleasant visibility. The final dehazed image is yielded by gating the important features of the derived inputs. To train the network, we introduce a multi-scale approach such that the halo artifacts can be avoided. Extensive experimental results on both synthetic and real-world images demonstrate that the proposed algorithm performs favorably against the state-of-the-art algorithms.

Pathogen blockade of TAK1 triggers caspase-8-dependent cleavage of gasdermin D and cell death.

Abstract: Limited proteolysis of gasdermin D (GSDMD) generates an N-terminal pore-forming fragment that controls pyroptosis in macrophages. GSDMD is processed via inflammasome-activated caspase-1 or -11. It is currently unknown whether macrophage GSDMD can be processed by other mechanisms. Here, we describe an additional pathway controlling GSDMD processing. The inhibition of TAK1 or IκB kinase (IKK) by the Yersinia effector protein YopJ elicits RIPK1- and caspase-8-dependent cleavage of GSDMD, which subsequently results in cell death. GSDMD processing also contributes to the NLRP3 inflammasome-dependent release of interleukin-1β (IL-1β). Thus, caspase-8 acts as a regulator of GSDMD-driven cell death. Furthermore, this study establishes the importance of TAK1 and IKK activity in the control of GSDMD cleavage and cytotoxicity.

Versatile ternary organic solar cells: a critical review

Abstract: The power conversion efficiency (PCE) of organic solar cells has been constantly refreshed in the past ten years from 4% up to 11% due to the contribution from the chemists on novel materials and the physicists on device engineering. For practical applications, a single bulk heterojunction structure may be the best candidate due to the cell with a high PCE, easy fabrication and low cost. Recently, ternary solar cells have attracted much attention due to enhanced photon harvesting by using absorption spectral or energy level complementary materials as the second donor or acceptor based on a single bulk heterojunction structure. For better promoting the development of ternary solar cells, we summarize the recent progress of ternary solar cells and try our best to concise out the scientific issues in preparing high performance ternary solar cells.

Federated Learning With Differential Privacy: Algorithms and Performance Analysis

Abstract: Federated learning (FL), as a type of distributed machine learning, is capable of significantly preserving clients’ private data from being exposed to adversaries. Nevertheless, private information can still be divulged by analyzing uploaded parameters from clients, e.g., weights trained in deep neural networks. In this paper, to effectively prevent information leakage, we propose a novel framework based on the concept of differential privacy (DP), in which artificial noise is added to parameters at the clients’ side before aggregating, namely, noising before model aggregation FL (NbAFL). First, we prove that the NbAFL can satisfy DP under distinct protection levels by properly adapting different variances of artificial noise. Then we develop a theoretical convergence bound on the loss function of the trained FL model in the NbAFL. Specifically, the theoretical bound reveals the following three key properties: 1) there is a tradeoff between convergence performance and privacy protection levels, i.e., better convergence performance leads to a lower protection level; 2) given a fixed privacy protection level, increasing the number $N$ of overall clients participating in FL can improve the convergence performance; and 3) there is an optimal number aggregation times (communication rounds) in terms of convergence performance for a given protection level. Furthermore, we propose a $K$ -client random scheduling strategy, where $K$ ( $1\leq K ) clients are randomly selected from the $N$ overall clients to participate in each aggregation. We also develop a corresponding convergence bound for the loss function in this case and the $K$ -client random scheduling strategy also retains the above three properties. Moreover, we find that there is an optimal $K$ that achieves the best convergence performance at a fixed privacy level. Evaluations demonstrate that our theoretical results are consistent with simulations, thereby facilitating the design of various privacy-preserving FL algorithms with different tradeoff requirements on convergence performance and privacy levels.

All Inorganic Halide Perovskites Nanosystem: Synthesis, Structural Features, Optical Properties and Optoelectronic Applications.

Abstract: The recent success of organometallic halide perovskites (OHPs) in photovoltaic devices has triggered lots of corresponding research and many perovskite analogues have been developed to look for devices with comparable performance but better stability. Upon the preparation of all inorganic halide perovskite nanocrystals (IHP NCs), research activities have soared due to their better stability, ultrahigh photoluminescence quantum yield (PL QY), and composition dependent luminescence covering the whole visible region with narrow line-width. They are expected to be promising materials for next generation lighting and display, and many other applications. Within two years, a lot of interesting results have been observed. Here, the synthesis of IHPs is reviewed, and their progresses in optoelectronic devices and optical applications, such as light-emitting diodes (LEDs), photodetectors (PDs), solar cells (SCs), and lasing, is presented. Information and recent understanding of their crystal structures and morphology modulations are addressed. Finally, a brief outlook is given, highlighting the presently main problems and their possible solutions and future development directions.