Research on the Impact of Executive Shareholding on New Investment in Enterprises Based on Multivariable Linear Regression Model

Based on principal-agent theory and optimal contract theory, companies use the method of increasing executives' shareholding to stimulate collaborative innovation. However, from the aspect of agency costs between management and shareholders (i.e. the first type) and between major shareholders and minority shareholders (i.e. the second type), the interests of management, shareholders and creditors will be unbalanced with the change of the marginal utility of executive equity incentives.In order to establish the correlation between the proportion of shares held by executives and investments in corporate innovation, we have chosen a range of publicly listed companies within China's A-share market as the focus of our study. Employing a multi-variable linear regression model, we aim to analyze this relationship thoroughly.The following models were developed: (1) the impact model of executive shareholding on corporate innovation investment; (2) the impact model of executive shareholding on two types of agency costs; (3)The model is employed to examine the mediating influence of the two categories of agency costs. Following both correlation and regression analyses, the findings confirm a meaningful and positive correlation between executives' shareholding and the augmentation of corporate innovation investments. Additionally, the results indicate that executive shareholding contributes to the reduction of the first type of agency cost, thereby fostering corporate innovation investment. However, simultaneously, it leads to an escalation in the second type of agency cost, thus impeding corporate innovation investment.Comment: Accepted by the 7th APWeb-WAIM International Joint Conference on Web and Big Data. (APWeb 2023

Severe acute respiratory syndrome coronavirus 2 pathology and cell tropism in tongue tissues of COVID-19 autopsies

Since 2019, Coronavirus Disease 2019(COVID-19) has affected millions of people worldwide. Except for acute respiratory distress syndrome, dysgeusis is also a common symptom of COVID-19 that burdens patients for weeks or permanently. However, the mechanisms underlying taste dysfunctions remain unclear. Here, we performed complete autopsies of five patients who died of COVID-19. Integrated tongue samples, including numerous taste buds, salivary glands, vessels, and nerves were collected to map the pathology, distribution, cell tropism, and receptor distribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the tongue. Our results revealed that all patients had moderate lymphocyte infiltration around the salivary glands and in the lamina propria adjacent to the mucosa, and pyknosis in the epithelia of taste buds and salivary glands. This may be because the serous acini, salivary gland ducts, and taste buds are the primary sites of SARS-CoV-2 infection. Multicolor immunofluorescence showed that SARS-CoV-2 readily infects Keratin (KRT)7+ taste receptor cells in taste buds, secretory cells in serous acini, and inner epithelial cells in the ducts. The major receptors, angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine subtype 2 (TMPRSS2), were both abundantly expressed in these cells. Viral antigens and receptor were both rarely detected in vessels and nerves. This indicates that SARS-CoV-2 infection triggers pathological injury in the tongue, and that dysgeusis may be directly related to viral infection and cellular damage

Insight into over Repair of Hot Carrier Degradation by GIDL Current in Si p-FinFETs Using Ultra-Fast Measurement Technique

In this article, an experimental study on the gate-induced drain leakage (GIDL) current repairing worst hot carrier degradation (HCD) in Si p-FinFETs is investigated with the aid of an ultra-fast measurement (UFM) technique (~30 μs). It is found that increasing GIDL bias from 3 V to 4 V achieves a 114.7% VT recovery ratio from HCD. This over-repair phenomenon of HCD by UFM GIDL is deeply discussed through oxide trap behaviors. When the applied gate-to-drain GIDL bias reaches 4 V, a significant electron trapping and interface trap generation of the fresh device with GIDL repair is observed, which greatly contributes to the approximate 114.7% over-repair VT ratio of the device under worst HCD stress (−2.0 V, 200 s). Based on the TCAD simulation results, the increase in the vertical electric field on the surface of the channel oxide layer is the direct cause of an extraordinary electron trapping effect accompanied by the over-repair phenomenon. Under a high positive electric field, a part of channel electrons is captured by oxide traps in the gate dielectric, leading to further VT recovery. Through the discharge-based multi-pulse (DMP) technique, the energy distribution of oxide traps after GIDL recovery is obtained. It is found that over-repair results in a 34% increment in oxide traps around the conduction energy band (Ec) of silicon, which corresponds to a higher stabilized VT shift under multi-cycle HCD-GIDL tests. The results provide a trap-based understanding of the transistor repairing technique, which could provide guidance for the reliable long-term operation of ICs

Deep spatial proteomics reveals region-specific features of severe COVID-19-related pulmonary injury

Summary: As a primary target of severe acute respiratory syndrome coronavirus 2, lung exhibits heterogeneous histopathological changes following infection. However, comprehensive insight into their protein basis with spatial resolution remains deficient, which hinders further understanding of coronavirus disease 2019 (COVID-19)-related pulmonary injury. Here, we generate a region-resolved proteomic atlas of hallmark pathological pulmonary structures by integrating histological examination, laser microdissection, and ultrasensitive proteomics. Over 10,000 proteins are quantified across 71 post-mortem specimens. We identify a spectrum of pathway dysregulations in alveolar epithelium, bronchial epithelium, and blood vessels compared with non-COVID-19 controls, providing evidence for transitional-state pneumocyte hyperplasia. Additionally, our data reveal the region-specific enrichment of functional markers in bronchiole mucus plugs, pulmonary fibrosis, airspace inflammation, and alveolar type 2 cells, uncovering their distinctive features. Furthermore, we detect increased protein expression associated with viral entry and inflammatory response across multiple regions, suggesting potential therapeutic targets. Collectively, this study provides a distinct perspective for deciphering COVID-19-caused pulmonary dysfunction by spatial proteomics

Sequencing of 19,219 exomes identifies a low-frequency variant in FKBP5 promoter predisposing to high myopia in a Han Chinese population

Summary: High myopia (HM) is one of the leading causes of visual impairment and blindness worldwide. Here, we report a whole-exome sequencing (WES) study in 9,613 HM cases and 9,606 controls of Han Chinese ancestry to pinpoint HM-associated risk variants. Single-variant association analysis identified three newly identified -genetic loci associated with HM, including an East Asian ancestry-specific low-frequency variant (rs533280354) in FKBP5. Multi-ancestry meta-analysis with WES data of 2,696 HM cases and 7,186 controls of European ancestry from the UK Biobank discerned a newly identified European ancestry-specific rare variant in FOLH1. Functional experiments revealed a mechanism whereby a single G-to-A transition at rs533280354 disrupted the binding of transcription activator KLF15 to the promoter of FKBP5, resulting in decreased transcription of FKBP5. Furthermore, burden tests showed a significant excess of rare protein-truncating variants among HM cases involved in retinal blood vessel morphogenesis and neurotransmitter transport

A resource-efficient tool for mixed model association analysis of large-scale data

The genome-wide association study (GWAS) has been widely used as an experimental design to detect associations between genetic variants and a phenotype. Two major confounding factors, population stratification and relatedness, could potentially lead to inflated GWAS test statistics and hence to spurious associations. Mixed linear model (MLM)-based approaches can be used to account for sample structure. However, genome-wide association (GWA) analyses in biobank samples such as the UK Biobank (UKB) often exceed the capability of most existing MLM-based tools especially if the number of traits is large. Here, we develop an MLM-based tool (fastGWA) that controls for population stratification by principal components and for relatedness by a sparse genetic relationship matrix for GWA analyses of biobank-scale data. We demonstrate by extensive simulations that fastGWA is reliable, robust and highly resource-efficient. We then apply fastGWA to 2,173 traits on array-genotyped and imputed samples from 456,422 individuals and to 2,048 traits on whole-exome-sequenced samples from 46,191 individuals in the UKB