Shanghai University

About: Shanghai University is a education organization based out in Shanghai, Shanghai, China. It is known for research contribution in the topics: Microstructure & Catalysis. The organization has 59583 authors who have published 56840 publications receiving 753549 citations. The organization is also known as: Shànghǎi Dàxué.

Local and Nonlocal Preserving Projection for Bearing Defect Classification and Performance Assessment

Abstract: The sensitivity of various physical features that are characteristics of bearing performance may vary significantly under different working conditions. Thus, it is critical to extract the most effective information from the original physical features generated from vibration signals for bearing defect classification and performance degradation assessment. This paper proposes a local and nonlocal preserving projection (LNPP)-based feature extraction algorithm, which is different from principal component analysis that aims to discover the global structure of Euclidean space and regular manifold learning algorithms that attempt to preserve local structure in data. LNPP is capable of discovering both local and nonlocal structures of data manifold. This may enable LNPP to find the meaningful low-dimensional information hidden in the high-dimensional feature set and then to serve as a preprocessor for defect classification. Furthermore, an LNPP-based quantification index is proposed for the assessment of bearing performance degradation. An LNPP-based contribution plot for feature selection is developed to improve the degradation detection sensitiveness and to reduce false alarms. A dynamic LNPP for bearing performance assessment is further developed to consider inherent autocorrelation existing in vibration data. Detailed results are very promising and are reported in this paper. This paper will provide guidance for the applications of manifold learning algorithms (e.g., LNPP) in machine fault diagnosis and performance prognostics.

Function of PM2.5 in the pathogenesis of lung cancer and chronic airway inflammatory diseases (Review)

Abstract: Previous research has identified that air pollution is associated with various respiratory diseases, but few studies have investigated the function served by particulate matter 2.5 (PM2.5) in these diseases. PM2.5 is known to cause epigenetic and microenvironmental alterations in lung cancer, including tumor-associated signaling pathway activation mediated by microRNA dysregulation, DNA methylation, and increased levels of cytokines and inflammatory cells. Autophagy and apoptosis of tumor cells may also be detected in lung cancer associated with PM2.5 exposure. A number of mechanisms are involved in triggering and aggravating asthma and COPD, including PM2.5-induced cytokine release and oxidative stress. The present review is an overview of the underlying molecular mechanisms of PM2.5-induced pathogenesis in lung cancer and chronic airway inflammatory diseases.

The impact of low-carbon city pilot policy on the total factor productivity of listed enterprises in China

Abstract: In recent years, the low-carbon city pilot policy has been important work in China It aims to control the city's greenhouse gas emissions, find a "win-win" path of low-carbon and economy and drive the innovation and development of cities through low-carbon goals In this context, we consider the low-carbon city pilot policy as the starting point Based on the data of A-share listed companies in Shanghai and Shenzhen from 2005 to 2015 in 285 prefecture-level cities, the OP and LP methods are used to calculate total factor productivity (TFP) In this paper, using PSM-DID and other methods, we empirically test whether and how the low-carbon city pilot policy affects enterprise TFP The results indicate that the construction of low-carbon cities significantly promotes an increase in the TFP of local enterprises In addition, improving technological innovation and optimizing the efficiency of resource allocation are two important transmission mechanisms The above conclusions are robust to a series of tests Therefore, the implementation of a low-carbon city pilot policy can help achieve the "win-win" goal of emission reduction and high-quality enterprise development This study provides strong support for further expanding the scope of low-carbon city pilot policy projects and the scientific implementation of climate change policies, and it provides beneficial policy enlightenment for the scientific implementation of urban emission reduction control to win the battle against climate change

2D vanadium carbide MXenzyme to alleviate ROS-mediated inflammatory and neurodegenerative diseases.

Abstract: Reactive oxygen species (ROS) are generated and consumed in living organism for normal metabolism. Paradoxically, the overproduction and/or mismanagement of ROS have been involved in pathogenesis and progression of various human diseases. Here, we reported a two-dimensional (2D) vanadium carbide (V2C) MXene nanoenzyme (MXenzyme) that can mimic up to six naturally-occurring enzymes, including superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), glutathione peroxidase (GPx), thiol peroxidase (TPx) and haloperoxidase (HPO). Based on these enzyme-mimicking properties, the constructed 2D V2C MXenzyme not only possesses high biocompatibility but also exhibits robust in vitro cytoprotection against oxidative stress. Importantly, 2D V2C MXenzyme rebuilds the redox homeostasis without perturbing the endogenous antioxidant status and relieves ROS-induced damage with benign in vivo therapeutic effects, as demonstrated in both inflammation and neurodegeneration animal models. These findings open an avenue to enable the use of MXenzyme as a remedial nanoplatform to treat ROS-mediated inflammatory and neurodegenerative diseases.