EXECUTIVE COMPENSATION DISPERSION AND FIRM PERFORMANCE

In this study, we examine the correlation between managerial pay dispersion and firm performance. We conduct a horse race between two different theories---tournament theory versus behavioral theory. We come to the conclusion that firm performance, measured by abnormal return, is positively associated wtih managerial compensation dispersion.  The result is in consistent with the tournament theory

Artificial intelligence-based human–computer interaction technology applied in consumer behavior analysis and experiential education

In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce (E-commerce) has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes to use artificial intelligence (AI) image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction (HCI) in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network (DNN) is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce

On the Sweet Spot of Contrastive Views for Knowledge-enhanced Recommendation

In recommender systems, knowledge graph (KG) can offer critical information that is lacking in the original user-item interaction graph (IG). Recent process has explored this direction and shows that contrastive learning is a promising way to integrate both. However, we observe that existing KG-enhanced recommenders struggle in balancing between the two contrastive views of IG and KG, making them sometimes even less effective than simply applying contrastive learning on IG without using KG. In this paper, we propose a new contrastive learning framework for KG-enhanced recommendation. Specifically, to make full use of the knowledge, we construct two separate contrastive views for KG and IG, and maximize their mutual information; to ease the contrastive learning on the two views, we further fuse KG information into IG in a one-direction manner.Extensive experimental results on three real-world datasets demonstrate the effectiveness and efficiency of our method, compared to the state-of-the-art. Our code is available through the anonymous link:https://figshare.com/articles/conference_contribution/SimKGCL/2278338

Design of the Tsinghua Tabletop Kibble Balance

The Kibble balance is a precision instrument for realizing the mass unit, the kilogram, in the new international system of units (SI). In recent years, an important trend for Kibble balance experiments is to go tabletop, in which the instrument's size is notably reduced while retaining a measurement accuracy of $10^{-8}$. In this paper, we report a new design of a tabletop Kibble balance to be built at Tsinghua University. The Tsinghua Kibble balance aims to deliver a compact instrument for robust mass calibrations from 10 g to 1 kg with a targeted measurement accuracy of 50 $\mu$g or less. Some major features of the Tsinghua Kibble balance system, including the design of a new magnet, one-mode measurement scheme, the spring-compensated magnet moving mechanism, and magnetic shielding considerations, are discussed.Comment: 8 pages, 9 figure

KBioXLM: A Knowledge-anchored Biomedical Multilingual Pretrained Language Model

Most biomedical pretrained language models are monolingual and cannot handle the growing cross-lingual requirements. The scarcity of non-English domain corpora, not to mention parallel data, poses a significant hurdle in training multilingual biomedical models. Since knowledge forms the core of domain-specific corpora and can be translated into various languages accurately, we propose a model called KBioXLM, which transforms the multilingual pretrained model XLM-R into the biomedical domain using a knowledge-anchored approach. We achieve a biomedical multilingual corpus by incorporating three granularity knowledge alignments (entity, fact, and passage levels) into monolingual corpora. Then we design three corresponding training tasks (entity masking, relation masking, and passage relation prediction) and continue training on top of the XLM-R model to enhance its domain cross-lingual ability. To validate the effectiveness of our model, we translate the English benchmarks of multiple tasks into Chinese. Experimental results demonstrate that our model significantly outperforms monolingual and multilingual pretrained models in cross-lingual zero-shot and few-shot scenarios, achieving improvements of up to 10+ points. Our code is publicly available at https://github.com/ngwlh-gl/KBioXLM

SD-GAN: Semantic Decomposition for Face Image Synthesis with Discrete Attribute

Manipulating latent code in generative adversarial networks (GANs) for facial image synthesis mainly focuses on continuous attribute synthesis (e.g., age, pose and emotion), while discrete attribute synthesis (like face mask and eyeglasses) receives less attention. Directly applying existing works to facial discrete attributes may cause inaccurate results. In this work, we propose an innovative framework to tackle challenging facial discrete attribute synthesis via semantic decomposing, dubbed SD-GAN. To be concrete, we explicitly decompose the discrete attribute representation into two components, i.e. the semantic prior basis and offset latent representation. The semantic prior basis shows an initializing direction for manipulating face representation in the latent space. The offset latent presentation obtained by 3D-aware semantic fusion network is proposed to adjust prior basis. In addition, the fusion network integrates 3D embedding for better identity preservation and discrete attribute synthesis. The combination of prior basis and offset latent representation enable our method to synthesize photo-realistic face images with discrete attributes. Notably, we construct a large and valuable dataset MEGN (Face Mask and Eyeglasses images crawled from Google and Naver) for completing the lack of discrete attributes in the existing dataset. Extensive qualitative and quantitative experiments demonstrate the state-of-the-art performance of our method. Our code is available at: https://github.com/MontaEllis/SD-GAN.Comment: 16 pages, 12 figures, Accepted by ACM MM202

Current status and influencing factors of activation of older patients with chronic disease

ObjectiveWe aimed to investigate the status and influencing factors of activation of older patients with chronic disease.MethodsWe conducted a cross-sectional study, using the general information questionnaire, Patient Activation Measure, the Chinese version of the e-Health Literacy Scale, and the Health Empowerment Scale for the Elderly with Chronic Disease. By the convenience sampling method, 289 older patients with chronic disease were selected from January to April 2023 in a Class A tertiary hospital in Zhengzhou.ResultsThe mean score of the Patient Activation Measure for older patients with chronic disease was 65.94 ± 13.35. The association of influencing factors such as religion, family income, health empowerment, e-health literacy, and patient activation was investigated.ConclusionThe patient activation of older patients with chronic disease was at a middle level. Patients without religion and from high-income families tended to have a higher level of patient activation. Improving health empowerment and e-health literacy levels promotes patient activation and enhances their self-health management ability

Effect of blocking Ras signaling pathway with K-Ras siRNA on apoptosis in esophageal squamous carcinoma cells

AbstractObjectiveTo study the effect of RNAi silencing of the K-Ras gene on Ras signal pathway activity in EC9706 esophageal cancer cells.MethodsEC9706 cells were treated in the following six groups: blank group (no transfection), negative control group (transfection no-carrier), transfection group (transfected with pSilencer-siK-ras), taxol chemotherapy group, taxol chemotherapy plus no-carrier group, taxol chemotherapy plus transfection group. Immunocytochemistry, Reverse transcription-polymerase chain reaction and western blotting were used to analyze the expression of MAPK1 (mitogen-activated protein kinases 1) and cyclin D1 in response to siRNA (small interfering RNA) transfection and taxol treatment.ResultsK-Ras (K-Ras gene) siRNA transfection of EC9706 esophageal squamous carcinoma cells decreased the expression of K-Ras, MAPK1 and cyclin D1 at the mRNA and protein level. Reverse transcription-polymerase chain reaction indicated that the expression levels of MAPK1 and cyclin D1 mRNAs were significantly lower in the transfection group than in the blank group (P<0.05). Western blotting showed that 72 h after EC9706 cell transfection, the expression levels of MAPK1 and cyclin D1 proteins had decreased in all groups, and the expression levels in the transfection group were significantly inhibited as compared with the blank group. Apoptosis increased significantly in the transfection group or after addition of taxol as compared with the blank group and the no-carrier group. The degree of apoptosis in the taxol plus transfection group was more severe.ConclusionApoptosis increased significantly in EC9706 esophageal carcinoma cells after siRNA-mediated inhibition of Ras signaling, with the most obvious increase observed in the transfection plus taxol chemotherapy group. Ras knockdown therefore increased cellular sensitivity to the chemotherapeutic agent, taxol. Ras knockdown also down-regulated the expression of the downstream genes, MAPK1 and cyclin D1, thus inhibiting the growth, proliferation and metabolism of esophageal cancer cells

A review of microplastics aggregation in aquatic environment: Influence factors, analytical methods, and environmental implications

A large amount of plastic waste released into natural waters and their demonstrated toxicity have made the transformation of microplastics (MPs; < 5 mm) and nanoplastics (NPs; < 100 nm) an emerging environmental concern. Aggregation is one of the most important environmental behaviors of MPs, especially in aquatic environments, which determines the mobility, distribution and bioavailability of MPs. In this paper, the sources and inputs of MPs in aquatic environments were first summarized followed by the analytical methods for investigating MP aggregation, including the sampling, visualization, and quantification procedures of MP’ particle sizes. We critically evaluated the sampling methods that still remains a methodological gap. Identification and quantification of MPs were mostly carried out by visual, spectroscopic and spectrometric techniques, and modeling analysis. Important factors affecting MP aggregation in natural waters and environmental implications of the aggregation process were also reviewed. Finally, recommendations for future research were discussed, including (1) conducting more field studies; (2) using MPs in laboratory works representing those in the environment; and (3) standardizing methods of identification and quantification. The review gives a comprehensive overview of current knowledge for MP aggregation in natural waters, identifies knowledge gaps, and provides suggestions for future research