A Survey on Fairness-aware Recommender Systems

As information filtering services, recommender systems have extremely enriched our daily life by providing personalized suggestions and facilitating people in decision-making, which makes them vital and indispensable to human society in the information era. However, as people become more dependent on them, recent studies show that recommender systems potentially own unintentional impacts on society and individuals because of their unfairness (e.g., gender discrimination in job recommendations). To develop trustworthy services, it is crucial to devise fairness-aware recommender systems that can mitigate these bias issues. In this survey, we summarise existing methodologies and practices of fairness in recommender systems. Firstly, we present concepts of fairness in different recommendation scenarios, comprehensively categorize current advances, and introduce typical methods to promote fairness in different stages of recommender systems. Next, after introducing datasets and evaluation metrics applied to assess the fairness of recommender systems, we will delve into the significant influence that fairness-aware recommender systems exert on real-world industrial applications. Subsequently, we highlight the connection between fairness and other principles of trustworthy recommender systems, aiming to consider trustworthiness principles holistically while advocating for fairness. Finally, we summarize this review, spotlighting promising opportunities in comprehending concepts, frameworks, the balance between accuracy and fairness, and the ties with trustworthiness, with the ultimate goal of fostering the development of fairness-aware recommender systems.Comment: 27 pages, 9 figure

Graph Self-Supervised Learning: A Survey

Deep learning on graphs has attracted significant interests recently. However, most of the works have focused on (semi-) supervised learning, resulting in shortcomings including heavy label reliance, poor generalization, and weak robustness. To address these issues, self-supervised learning (SSL), which extracts informative knowledge through well-designed pretext tasks without relying on manual labels, has become a promising and trending learning paradigm for graph data. Different from SSL on other domains like computer vision and natural language processing, SSL on graphs has an exclusive background, design ideas, and taxonomies. Under the umbrella of graph self-supervised learning, we present a timely and comprehensive review of the existing approaches which employ SSL techniques for graph data. We construct a unified framework that mathematically formalizes the paradigm of graph SSL. According to the objectives of pretext tasks, we divide these approaches into four categories: generation-based, auxiliary property-based, contrast-based, and hybrid approaches. We further describe the applications of graph SSL across various research fields and summarize the commonly used datasets, evaluation benchmark, performance comparison and open-source codes of graph SSL. Finally, we discuss the remaining challenges and potential future directions in this research field.Comment: 25 pages, 9 figures, 9 table

Health State Estimation of On-Board Lithium-Ion Batteries Based on GMM-BID Model

As a single feature parameter cannot comprehensively evaluate the health status of a battery, a multi-source information fusion method based on the Gaussian mixture model and Bayesian inference distance is proposed for the health assessment of vehicle batteries. The missing and abnormal data from real-life vehicle operations are preprocessed to extract the sensitive characteristic parameters which determine the battery performance. The normal state Gaussian mixture model is established using the fault-free state data, whereas the Bayesian inference distance is constructed as an index to quantitatively evaluate the battery performance state. In order to solve the problem that abnormal data may exist in the measured data and introduce errors into evaluation results, the determination rules of abnormal data are formulated. The verification of real-life vehicle operation data reveals that the proposed method can accurately evaluate the onboard battery state and reduce safety hazards of electric vehicles during the normal operation process

Research on dead-time compensation of common DC bus OW-PMSM based on 120°decoupling modulation

To suppress the switching dead-band in the Open-End Winding Permanent Magnet Synchronous Machine with Common DC bus (OW-PMSM-CDCB) drive system, the dual-inverter switch dead-band generates zero-sequence voltage and current during 120°decoupling modulation. The generation mechanism of dead-band voltage is analyzed with the help of Matlab/Simulink and a method to compensate for the zero-sequence voltage resulting from the dead-band of dual-inverter switches is discussed in this study. With the help of current polarity detection, the zero-sequence voltage resulting from the dead-band of the switch is offset by solving the dead-band voltage compensation amount, and an OW-PMSM-CDCB drive system experimental platform is built for experimental verification. Simulation and experimental show that the proposed compensation method can effectively suppress the zero-sequence current of OW-PMSM-CDCB

Multi-genome comprehensive identification of SSR/SV and development of molecular markers database to serve Sorghum bicolor (L.) breeding

Abstract Background As an important food and cash crop, identification of DNA molecular markers is of great significance for molecular marker-assisted breeding of Sorghum (Sorghum bicolor (L.) moench). Although some sorghum-related mutation databases have been published, the special SSR and SV databases still need to be constructed and updated. Results In this study, the quality of 18 different sorghum genomes was evaluated, and two genomes were assembled at chromosome level. Through the identification and comparative analysis of SSR loci in these genomes, the distribution characteristics of SSR in the above sorghum genomes were initially revealed. At the same time, five representative reference genomes were selected to identify the structural variation of sorghum. Finally, a convenient SSR/SV database of sorghum was constructed by integrating the above results ( http://www.sorghum.top:8079/ ; http://43.154.129.150:8079/ ; http://47.106.184.91:8079/ ). Users can query the information of related sites and primer pairs. Conclusions Anyway, our research provides convenience for sorghum researchers and will play an active role in sorghum molecular marker-assisted breeding

Research on speed loop control of IPMSM based on Fuzzy linear active disturbance rejection control

Interior Permanent Magnet Synchronous Motor (IPMSM) significantly speed fluctuations under load change suddenly conditions. With the help of MATLAB/Simulink simulation software, a novel IPMSM speed loop control strategy is studied. A Fuzzy linear active disturbance rejection (Fuzzy-LADRC) speed controller is designed, and the LADRC parameters are dynamically adjusted by Fuzzy control to reduce the speed fluctuations of IPMSM in this paper. Finally, the dSPACE experimental platform is used to conduct simulations and experiments. The simulation and experimental results show that the Fuzzy-LADRC has stronger anti-disturbance than the conventional LADRC controlled IPMSM drive system, and the motor speed fluctuations are small

Ripa-56 protects retinal ganglion cells in glutamate-induced retinal excitotoxic model of glaucoma

Abstract Glaucoma is a prevalent cause of blindness globally, characterized by the progressive degeneration of retinal ganglion cells (RGCs). Among various factors, glutamate excitotoxicity stands out as a significant contributor of RGCs loss in glaucoma. Our study focused on Ripa-56 and its protective effect against NMDA-induced retinal damage in mice, aiming to delve into the potential underlying mechanism. The R28 cells were categorized into four groups: glutamate (Glu), Glu + Ripa-56, Ripa-56 and Control group. After 24 h of treatment, cell death was assessed by PI / Hoechst staining. Mitochondrial membrane potential changes, apoptosis and reactive oxygen species (ROS) production were analyzed using flow cytometry. The alterations in the expression of RIP-1, p-MLKL, Bcl-2, BAX, Caspase-3, Gpx4 and SLC7A11 were examined using western blot analysis. C57BL/6j mice were randomly divided into NMDA, NMDA + Ripa-56, Ripa-56 and control groups. Histological changes in the retina were evaluated using hematoxylin and eosin (H&E) staining. RGCs survival and the protein expression changes of RIP-1, Caspase-3, Bcl-2, Gpx4 and SLC7A11 were observed using immunofluorescence. Ripa-56 exhibited a significant reduction in the levels of RIP-1, p-MLKL, Caspase-3, and BAX induced by glutamate, while promoting the expression of Bcl-2, Gpx-4, and SLC7A1 in the Ripa-56-treated group. In our study, using an NMDA-induced normal tension glaucoma mice model, we employed immunofluorescence and H&E staining to observe that Ripa-56 treatment effectively ameliorated retinal ganglion cell loss, mitigating the decrease in retinal ganglion cell layer and bipolar cell layer thickness caused by NMDA. In this study, we have observed that Ripa-56 possesses remarkable anti- necroptotic, anti-apoptotic and anti-ferroptosis properties. It demonstrates the ability to combat not only glutamate-induced excitotoxicity in R28 cells, but also NMDA-induced retinal excitotoxicity in mice. Therefore, Ripa-56 could be used as a potential retinal protective agent

The Impact of Alternative Fuels on Ship Engine Emissions and Aftertreatment Systems: A Review

Marine engines often use diesel as an alternative fuel to improve the economy. In recent years, waste oil, biodiesel and alcohol fuel are the most famous research directions among the alternative fuels for diesel. With the rapid development of the shipping industry, the air of coastal areas is becoming increasingly polluted. It is now necessary to reduce the emission of marine engines to meet the strict emission regulations. There are many types of alternative fuels for diesel oil and the difference of the fuel may interfere with the engine emissions; however, PM, HC, CO and other emissions will have a negative impact on SCR catalyst. This paper reviews the alternative fuels such as alcohols, waste oils, biodiesel made from vegetable oil and animal oil, and then summarizes and analyzes the influence of different alternative fuels on engine emissions and pollutant formation mechanism. In addition, this paper also summarizes the methods that can effectively reduce the emissions of marine engines; it can provide a reference for the study of diesel alternative fuel and the reduction of marine engine emissions