Goal Pursuit of Sellers in Hierarchical Online Reputation Systems

To understand sellers’ reputation status more intuitively and quickly, a hierarchical reputation system is routinely deployed by online C2C marketplaces, where reputation scores are divided into several grades shown in badges. It not only helps the consumers but also unintentionally introduces the incentive hierarchies to motivate sellers to pursuit the reputation goals. Yet the existing literature remains largely unclear whether sellers’ goal pursuit behavior exists in the context of electronic commerce. We gathered data from a large online marketplace to answer this question. The results show that sellers will exert more efforts (i.e., take discounts) when their absolute reputation scores are closer to the threshold of next grade. Moreover, low value products and high value products decrease more than median value products. This relationship is moderated by sellers’ relative position in their current grade. Our findings contribute both goal pursuit and online market literature and have direct managerial implications

Identifying Subgroups of ICU Patients Using End-to-End Multivariate Time-Series Clustering Algorithm Based on Real-World Vital Signs Data

This study employed the MIMIC-IV database as data source to investigate the use of dynamic, high-frequency, multivariate time-series vital signs data, including temperature, heart rate, mean blood pressure, respiratory rate, and SpO2, monitored first 8 hours data in the ICU stay. Various clustering algorithms were compared, and an end-to-end multivariate time series clustering system called Time2Feat, combined with K-Means, was chosen as the most effective method to cluster patients in the ICU. In clustering analysis, data of 8,080 patients admitted between 2008 and 2016 was used for model development and 2,038 patients admitted between 2017 and 2019 for model validation. By analyzing the differences in clinical mortality prognosis among different categories, varying risks of ICU mortality and hospital mortality were found between different subgroups. Furthermore, the study visualized the trajectory of vital signs changes. The findings of this study provide valuable insights into the potential use of multivariate time-series clustering systems in patient management and monitoring in the ICU setting.Comment: Proceedings of Beijing Health Data Science Summit (HDSS) 202

Three-dimensional petrographical investigations on borehole rock samples: a comparison between X-ray computed- and neutron tomography

Technical difficulties associated with excavation works in tectonized geological settings are frequent. They comprise instantaneous and/or delayed convergence, sudden collapse of gallery roof and/or walls, outpouring of fault-filling materials and water inflows. These phenomena have a negative impact on construction sites and their safety. In order to optimize project success, preliminary studies on the reliability of rock material found on site are needed. This implies in situ investigations (surface mapping, prospective drilling, waterflow survey, etc.) as well as laboratory investigations on rock samples (permeability determination, moisture and water content, mineralogy, petrography, geochemistry, mechanical deformation tests, etc.). A set of multiple parameters are then recorded which permit better insight on site conditions and probable behavior during excavation. Because rock formations are by nature heterogeneous, many uncertainties remain when extrapolating large-scale behavior of the rock mass from analyses of samples order of magnitudes smaller. Indirect large-scale field investigations (e.g. geophysical prospecting) could help to better constrain the relationships between lithologies at depth. At a much smaller scale, indirect analytical methods are becoming more widely used for material investigations. We discuss in this paper X-ray computed tomography (XRCT) and neutron tomography (NT), showing promising results for 3D petrographical investigations of the internal structure of opaque materials. Both techniques record contrasts inside a sample, which can be interpreted and quantified in terms of heterogeneity. This approach has the advantage of combining genetic parameters (physico-chemical rock composition) with geometric parameters resulting from alteration or deformation processes (texture and structure). A critical analysis of such 3D analyses together with the results of mechanical tests could improve predictions of short- and long-term behavior of a rock unit. Indirect methods have the advantage of being non-destructive. However, as it is the case with large-scale geophysical surveying, XRCT and NT are affected by several error factors inherent to the interaction of a radiation modality (X-ray or neutron beam) with the atomic structure of the investigated materials. Recorded signals are therefore in particular cases not artifact-free and need to be corrected in a subsequent stage of data processin

Based on Network Pharmacology and Molecular Docking to Discuss the Mechanism of Antitussive and Expectorant Action of Ruanerli

The antitussive and expectorant effects of Ruanerli and its mechanism were investigated by methods of network pharmacology. The outcomes predicted were verified by molecular docking and animal experiments. The components and targets of Ruanerli were obtained by literature investigation and TCMSP database screen. Mapping with two groups of genes related to "cough" and "sputum" from GeneCards database, the target genes of antitussive and expectorant effects of Ruanerli were obtained. GO and KEGG enrichment analysis of the target genes was performed by Metascape platform. The PPI network among the target genes was constructed through STRING data platform. Cytoscape plugin CytoHubba was used to screen the Top10 genes related to antitussive and expectorant effects of Ruanerli, and KEGG pathway enrichment was performed on the Top10 genes through Metascape data platform to predict the possible signal pathways involved in antitussive and expectorant effects of Ruanerli. Autodock Vina was used for molecular docking between the predicted Top10 gene proteins and the Top 3 active ingredients of Ruanerli. Finally, the predicted results were verified by ammonia induced cough test and phenol red excretion test. According to the analysis of multiple databases, 51 chemical components and 282 corresponding targets have been reported, eighty of them were related to the antitussive and expectorant effects of Ruanerli. The Top10 genes selected by Degree value were mainly concentrated in infection and immune-related pathways. Molecular docking test showed that the Top10 genes had strong binding activity with the Top3 chemical components (Caffeic acid, Rutin and Valeraldehyde) in PPI network. Animal experiments showed that the cough induced by ammonia was significantly inhibited when treated with Ruanerli in mice. The levels of IL-6 and IL-13 in serum were reduced and the excretion of phenol red in mice trachea was increased. PCR and WB detection showed that the mRNA levels and protein expressions of inflammatory genes IL6, IL1B, VEGFA, PTGS2 and MAPK3 were decreased, suggesting that the antitussive and expectorant effects of Ruanerli might be related to decreasing the expression of inflammatory genes and the release of inflammatory factors

Pharmacokinetics/pharmacodynamics of polymyxin B in patients with bloodstream infection caused by carbapenem-resistant Klebsiella pneumoniae

Introduction: Polymyxin B is a last-line therapy for carbapenem-resistant microorganisms. However, a lack of clinical pharmacokinetic/pharmacodynamic (PK/PD) data has substantially hindered dose optimization and breakpoint setting.Methods: A prospective, multi-center clinical trial was undertaken with polymyxin B [2.5 mg/kg loading dose (3-h infusion), 1.25 mg/kg/12 h maintenance dose (2-h infusion)] for treatment of carbapenem-resistant K. pneumoniae (CRKP) bloodstream infections (BSI). Safety, clinical and microbiological efficacy were evaluated. A validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was applied to determine the concentrations of polymyxin B in blood samples. Population pharmacokinetic (PK) modeling and Monte Carlo simulations were conducted to examine the susceptibility breakpoint for polymyxin B against BSI caused by CRKP.Results: Nine patients were enrolled and evaluated for safety. Neurotoxicity (5/9), nephrotoxicity (5/9), and hyperpigmentation (1/9) were recorded. Blood cultures were negative within 3 days of commencing therapy in all 8 patients evaluated for microbiological efficacy, and clinical cure or improvement occurred in 6 of 8 patients. Cmax and Cmin following the loading dose were 5.53 ± 1.80 and 1.62 ± 0.41 mg/L, respectively. With maintenance dosing, AUCss,24 h was 79.6 ± 25.0 mg h/L and Css,avg 3.35 ± 1.06 mg/L. Monte Carlo simulations indicated that a 1 mg/kg/12-hourly maintenance dose could achieve >90% probability of target attainment (PTA) for isolates with minimum inhibitory concentration (MIC) ≤1 mg/L. PTA dropped substantially for MICs ≥2 mg/L, even with a maximally recommended daily dose of 1.5 mg/kg/12-hourly.Conclusion: This is the first clinical PK/PD study evaluating polymyxin B for BSI. These results will assist to optimize polymyxin B therapy and establish its breakpoints for CRKP BSI

Screening of potentially active compounds against rheumatoid arthritis in the Juan-Bi decoction using systems pharmacology and animal experiments

Background: The Juan-Bi decoction (JBD) is a classic traditional Chinese medicines (TCMs) prescription for the treatment of rheumatoid arthritis (RA). However, the active compounds of the JBD in RA treatment remain unclear.Aim: The aim of this study is to screen effective compounds in the JBD for RA treatment using systems pharmacology and experimental approaches.Method: Botanical drugs and compounds in the JBD were acquired from multiple public TCM databases. All compounds were initially screened using absorption, distribution, metabolism, excretion, and toxicity (ADMET) and physicochemical properties, and then a target prediction was performed. RA pathological genes were acquired from the DisGeNet database. Potential active compounds were screened by constructing a compound–target–pathogenic gene (C-T-P) network and calculating the cumulative interaction intensity of the compounds on pathogenic genes. The effectiveness of the compounds was verified using lipopolysaccharide (LPS)-induced RAW.264.7 cells and collagen-induced arthritis (CIA) mouse models.Results: We screened 15 potentially active compounds in the JBD for RA treatment. These compounds primarily act on multiple metabolic pathways, immune pathways, and signaling transduction pathways. Furthermore, in vivo and in vitro experiments showed that bornyl acetate (BAC) alleviated joint damage, and inflammatory cells infiltrated and facilitated a smooth cartilage surface via the suppression of the steroid hormone biosynthesis.Conclusion: We screened potential compounds in the JBD for the treatment of RA using systems pharmacology approaches. In particular, BAC had an anti-rheumatic effect, and future studies are required to elucidate the underlying mechanisms

Submicron and Nanometer Structures Technology and Research

Contains reports on twenty research projects and a list of publications.Defense Advanced Research Projects Agency Contract N00019-92-K-0021Joint Services Electronics Program Contract DAAL03-92-C-0001National Science Foundation Grant ECS 90-16437U.S. Army Research Office Grant DAAL03-92-G-0291IBM CorporationU.S. Air Force - Office of Scientific Research Grant F49620-92-J-0064National Science Foundation Grant DMR 87-19217National Science Foundation Grant DMR 90-22933Defense Advanced Research Projects Agency Consortium for Superconducting ElectronicsNational Aeronautics and Space Administration Contract NAS8-36748National Aeronautics and Space Administration Grant NAGW-200

The Effect of Perceived vs. Factual Knowledge on Exploration

Exploration and exploitation decision-making are crucial cognitive processes, often guided by an individual’s knowledge state. The information gap theory posits that lesser knowledge enhances exploration, yet the differential impacts of factual versus perceived knowledge on exploration preferences are not thoroughly understood. This research aims to bridge this gap by independently manipulating factual and perceived knowledge to assess their separate effects on exploration behaviors. Through three studies, we discovered that individuals with less factual knowledge explored more intensely and for longer durations, but only when they were explicitly aware of their information gaps. Furthermore, our findings reveal that the perception of insufficient knowledge can trigger increased exploration, independent of the factual knowledge possessed. Our studies illuminate the significant impact of metacognitive states on exploration preferences, advancing our understanding of how people decide whether to explore or exploit

Bioinformatics in Plant Breeding and Research on Disease Resistance

In the context of plant breeding, bioinformatics can empower genetic and genomic selection to determine the optimal combination of genotypes that will produce a desired phenotype and help expedite the isolation of these new varieties. Bioinformatics is also instrumental in collecting and processing plant phenotypes, which facilitates plant breeding. Robots that use automated and digital technologies to collect and analyze different types of information to monitor the environment in which plants grow, analyze the environmental stresses they face, and promptly optimize suboptimal and adverse growth conditions accordingly, have helped plant research and saved human resources. In this paper, we describe the use of various bioinformatics databases and algorithms and explore their potential applications in plant breeding and for research on plant disease resistance

Environmental tax and highly polluting firms' green transformation : evidence from green mergers and acquisitions

Taking China's Environmental Protection Tax Law, implemented in 2018, as an exogenous shock, this study investigates the effect of an environmental tax on firms' green transformation behaviors. Our baseline results show that this environmental tax policy has a positive impact on promoting highly polluting firms' green mergers and acquisitions (M&As). Heterogeneity analyses show that the effect of the environmental tax on green M&As is moderated by firm characteristics (state ownership, innovation capacity, and reputation), industry ones (competition and barriers to entry), and regional ones (legal system strength, environmental pollution severity, and pollution tax rates). Finally, we find that the capital market responds more positively to green M&As in highly polluting firms after the implementation of the environmental tax. This study has important policy implications, providing empirical evidence that may be useful for corporate green transformation