Nanjing University

About: Nanjing University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 85961 authors who have published 105504 publications receiving 2289036 citations. The organization is also known as: NJU & Nanking University.

Appearance-and-Relation Networks for Video Classification

Abstract: Spatiotemporal feature learning in videos is a fundamental problem in computer vision. This paper presents a new architecture, termed as Appearance-and-Relation Network (ARTNet), to learn video representation in an end-to-end manner. ARTNets are constructed by stacking multiple generic building blocks, called as SMART, whose goal is to simultaneously model appearance and relation from RGB input in a separate and explicit manner. Specifically, SMART blocks decouple the spatiotemporal learning module into an appearance branch for spatial modeling and a relation branch for temporal modeling. The appearance branch is implemented based on the linear combination of pixels or filter responses in each frame, while the relation branch is designed based on the multiplicative interactions between pixels or filter responses across multiple frames. We perform experiments on three action recognition benchmarks: Kinetics, UCF101, and HMDB51, demonstrating that SMART blocks obtain an evident improvement over 3D convolutions for spatiotemporal feature learning. Under the same training setting, ARTNets achieve superior performance on these three datasets to the existing state-of-the-art methods.1

Visible light-driven organic photochemical synthesis in China

Abstract: In recent years, visible light-driven organic photochemical synthesis has attracted wide research interest from academic and industrial communities due to its features of green and sustainable chemistry. In this flourishing area, Chinese chemists have devoted great efforts to different aspects of synthetic chemistry. This review will summarize their representative work according to the following categories: C–H functionalization, synthesis of aromatic aza-heterocycles, asymmetric organic photochemical synthesis, transformations of small molecules and biomolecule-compatible reactions.

Fine-Tuning Pore Size by Shifting Coordination Sites of Ligands and Surface Polarization of Metal–Organic Frameworks To Sharply Enhance the Selectivity for CO2

Abstract: Based upon the (3,6)-connected metal–organic framework {Cu(L1)·2H2O·1.5DMF}∞ (L1 = 5-(pyridin-4-yl)isophthalic acid) (SYSU, for Sun Yat-Sen University), iso-reticular {Cu(L2)·DMF}∞ (L2 = 5-(pyridin-3-yl)isophthalic acid) (NJU-Bai7; NJU-Bai for Nanjing University Bai group) and {Cu(L3)·DMF·H2O}∞ (L3 = 5-(pyrimidin-5-yl)isophthalic acid) (NJU-Bai8) were designed by shifting the coordination sites of ligands to fine-tune pore size and polarizing the inner surface with uncoordinated nitrogen atoms, respectively, with almost no changes in surface area or porosity. Compared with those of the prototype SYSU, both the adsorption enthalpy and selectivity of CO2 for NJU-Bai7 and NJU-Bai8 have been greatly enhanced, which makes NJU-Bai7 and NJU-Bai8 good candidates for postcombustion CO2 capture. Notably, the CO2 adsorption enthalpy of NJU-Bai7 is the highest reported so far among the MOFs without any polarizing functional groups or open metal sites. Meanwhile, NJU-Bai8 exhibits high uptake of CO2 and good CO2/CH4 s...

Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment

Abstract: Failure mode and effects analysis (FMEA) is a widely used risk assessment tool for defining, identifying, and eliminating potential failures or problems in products, process, designs, and services In traditional FMEA, the risk priorities of failure modes are determined by using risk priority numbers (RPNs), which can be obtained by multiplying the scores of risk factors like occurrence (O), severity (S), and detection (D) However, the crisp RPN method has been criticized to have several deficiencies In this paper, linguistic variables, expressed in trapezoidal or triangular fuzzy numbers, are used to assess the ratings and weights for the risk factors O, S, and D For selecting the most serious failure modes, the extended VIKOR method is used to determine risk priorities of the failure modes that have been identified As a result, a fuzzy FMEA based on fuzzy set theory and VIKOR method is proposed for prioritization of failure modes, specifically intended to address some limitations of the traditional FMEA A case study, which assesses the risk of general anesthesia process, is presented to demonstrate the application of the proposed model under fuzzy environment