The Impact of ESG on the Financial Performance of Listed Companies: Empirical Analysis Based on A-share Listed Companies

As China’s ecological civilization advances, ESG (Environmental, Social, and Governance) has emerged as a focal point for market participants and investors. Based on the data of Shanghai and Shenzhen A-share listed companies from 2014 to 2022 and Bloomberg ESG score, this paper explores the impact of ESG performance on corporate value and its mechanism through multiple regression analysis. The results indicate that an enhancement in ESG performance significantly boosts the financial performance of listed companies, particularly in non-polluting industries, enterprises with low information transparency, and foreign-controlled enterprises. In response to these conclusions, the article makes recommendations for policy formulation and business management aimed at promoting sustainable development of enterprises, enhancing market competitiveness, and responding to the growing concern of investors about ESG

iCare: A Mobile Health Monitoring System for the Elderly

This paper describes a mobile health monitoring system called iCare for the elderly. We use wireless body sensors and smart phones to monitor the wellbeing of the elderly. It can offer remote monitoring for the elderly anytime anywhere and provide tailored services for each person based on their personal health condition. When detecting an emergency, the smart phone will automatically alert pre-assigned people who could be the old people's family and friends, and call the ambulance of the emergency centre. It also acts as the personal health information system and the medical guidance which offers one communication platform and the medical knowledge database so that the family and friends of the served people can cooperate with doctors to take care of him/her. The system also features some unique functions that cater to the living demands of the elderly, including regular reminder, quick alarm, medical guidance, etc. iCare is not only a real-time health monitoring system for the elderly, but also a living assistant which can make their lives more convenient and comfortable.Comment: The 3rd IEEE/ACM Int Conf on Cyber, Physical and Social Computing (CPSCom), IEEE, Hangzhou, China, December 18-20, 201

ECM-OPCC: Efficient Context Model for Octree-based Point Cloud Compression

Recently, deep learning methods have shown promising results in point cloud compression. For octree-based point cloud compression, previous works show that the information of ancestor nodes and sibling nodes are equally important for predicting current node. However, those works either adopt insufficient context or bring intolerable decoding complexity (e.g. >600s). To address this problem, we propose a sufficient yet efficient context model and design an efficient deep learning codec for point clouds. Specifically, we first propose a window-constrained multi-group coding strategy to exploit the autoregressive context while maintaining decoding efficiency. Then, we propose a dual transformer architecture to utilize the dependency of current node on its ancestors and siblings. We also propose a random-masking pre-train method to enhance our model. Experimental results show that our approach achieves state-of-the-art performance for both lossy and lossless point cloud compression. Moreover, our multi-group coding strategy saves 98% decoding time compared with previous octree-based compression method

A Local Signal based Inter-area Damping Controller via Dynamic State Estimation Approach

To suppress inter-area oscillations and enhance small-signal stability of power systems, wide-area damping controllers (WADC) have been used by utilising wide-area signals with high observabilities to inter-area modes. However, the requirement of the wide-area signal makes communication systems involved in the control loops of the power systems and therefore, the damping performance of the conventional WADC suffers from time-delay, data dropout and cyber-attacks. This paper proposes a local signal based inter-area damping controller (LSIADC) to suppress inter-area oscillation without using wide-area signals. The LSIADC extracts a signal with high observability to the inter-area mode from the local signal by dynamic state estimation (DSE) technique and the control signal is obtained by adding a proper phase shift to the extracted signal. The simulation results show that the proposed controller can effectively suppress inter-area oscillation using the local signal only