Analysis of Influencing Factors of Tablet Consumer Satisfaction Based on Online Comment Mining

How to extract effective information that affects consumer satisfaction from online comments has become a hot issue for customer behavior. This article is based on the data mining of online comments and the research object are the top-selling tablets on the JD platform from October to December 2018. We started by analyzing influential factors such as goods, after-sales service, and logistics, and crawled online review information of nearly 3,000 tablet computers from five major brands. We first use the jieba word segmentation tool to process the user comments, and use TF-IDF to calculate the frequency of different words in the comments to determine the main keywords of the comments. Secondly, we set up a user\u27s sentiment dictionary to determine the sentiment index of the review, and combined the keywords and sentiment index to get the degree of consumer satisfaction on different influencing factors. Finally, we imported the quantified characteristic factors into Clementine 12.0, and established a Bayesian network model of customer satisfaction, thereby obtaining a ranking table of the importance of each factor to product sales. To improve the model robustness, we adopt a multivariate linear model to check the accuracy of the output results. Our research can not only formulate effective product service sales strategies for merchants, but also guarantee customers to experience better products and services

Protective Effect of Danhong Injection on Acute Hepatic Failure Induced by Lipopolysaccharide and D-Galactosamine in Mice

Acute hepatic failure (AHF), which leads to an extremely high mortality rate, has become the focus of attention in clinic. In this study, Danhong injection (DHI) was investigated to evaluate the preventive and protective effect on AHF induced by lipopolysaccharide (LPS) and D-galactosamine (GalN) in mice. For AHF induction, ICR mice were intraperitoneally injected with D-GalN (700 mg/kg) and LPS (20 μg/kg). DHI was administrated twice, at 12 and 1 h, respectively, before D-GalN/LPS injection. After stimulation with D-GalN/LPS for 1 and 6 h, serum and livers were collected for analysis. We found that mice administrated with DHI displayed a higher survival rate, lower serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBil), glutathione S-transferase (GST), and tumor necrosis factor (TNF)-α. DHI inhibited the elevations of hepatic lipid peroxidation (malondialdehyde), caspase-8 activity, and mRNA expression levels of inflammatory cytokines (interleukin-1β and interleukin-6) increased by D-GalN/LPS in the liver. Furthermore, liver histopathological analysis indicated that the DHI group showed markedly fewer apoptotic (TUNEL positive) cells and less pathological changes than those in the AHF model group. These results provide a novel insight into the pharmacological actions of DHI as a potential candidate for treating AHF

Investigation for the puzzling abundance pattern of the neutron-capture elements in the ultra metal-poor star: CS 30322-023

The s-enhanced and very metal-poor star CS 30322-023 shows a puzzling abundance pattern of the neutron-capture elements, i.e. several neutron-capture elements such as Ba, Pb etc. show enhancement, but other neutron-capture elements such as Sr, Eu etc. exhibit deficient with respect to iron. The study to this sample star could make people gain a better understanding of s- and r-process nucleosynthesis at low metallicity. Using a parametric model, we find that the abundance pattern of the neutron-capture elements could be best explained by a star that was polluted by an AGB star and the CS 30322-023 binary system formed in a molecular cloud which had never been polluted by r-process material. The lack of r-process material also indicates that the AGB companion cannot have undergone a type-1.5 supernova, and thus must have had an initial mass below 4.0M$_\odot$, while the strong N overabundance and the absence of a strong C overabundance indicate that the companion's initial mass was larger than 2.0M$_\odot$. The smaller s-process component coefficient of this star illustrates that there is less accreted material of this star from the AGB companion, and the sample star should be formed in the binary system with larger initial orbital separation where the accretion-induced collapse (AIC) mechanism can not work.Comment: 13 pages, 2 figure

Video-Bench: A Comprehensive Benchmark and Toolkit for Evaluating Video-based Large Language Models

Video-based large language models (Video-LLMs) have been recently introduced, targeting both fundamental improvements in perception and comprehension, and a diverse range of user inquiries. In pursuit of the ultimate goal of achieving artificial general intelligence, a truly intelligent Video-LLM model should not only see and understand the surroundings, but also possess human-level commonsense, and make well-informed decisions for the users. To guide the development of such a model, the establishment of a robust and comprehensive evaluation system becomes crucial. To this end, this paper proposes \textit{Video-Bench}, a new comprehensive benchmark along with a toolkit specifically designed for evaluating Video-LLMs. The benchmark comprises 10 meticulously crafted tasks, evaluating the capabilities of Video-LLMs across three distinct levels: Video-exclusive Understanding, Prior Knowledge-based Question-Answering, and Comprehension and Decision-making. In addition, we introduce an automatic toolkit tailored to process model outputs for various tasks, facilitating the calculation of metrics and generating convenient final scores. We evaluate 8 representative Video-LLMs using \textit{Video-Bench}. The findings reveal that current Video-LLMs still fall considerably short of achieving human-like comprehension and analysis of real-world videos, offering valuable insights for future research directions. The benchmark and toolkit are available at: \url{https://github.com/PKU-YuanGroup/Video-Bench}.Comment: Benchmark is available at https://github.com/PKU-YuanGroup/Video-Benc

Waveform Design for Communication-Assisted Sensing in 6G Perceptive Networks

The integrated sensing and communication (ISAC) technique has the potential to achieve coordination gain by exploiting the mutual assistance between sensing and communication (S&C) functions. While the sensing-assisted communications (SAC) technology has been extensively studied for high-mobility scenarios, the communication-assisted sensing (CAS) counterpart remains widely unexplored. This paper presents a waveform design framework for CAS in 6G perceptive networks, aiming to attain an optimal sensing quality of service (QoS) at the user after the target's parameters successively ``pass-through'' the S$\&$C channels. In particular, a pair of transmission schemes, namely, separated S&C and dual-functional waveform designs, are proposed to optimize the sensing QoS under the constraints of the rate-distortion and power budget. The first scheme reveals a power allocation trade-off, while the latter presents a water-filling trade-off. Numerical results demonstrate the effectiveness of the proposed algorithms, where the dual-functional scheme exhibits approximately 12% performance gain compared to its separated waveform design counterpart

2-(2,3-Difluoro­phen­yl)ethyl toluene-4-sulfonate

In the title compound, C15H14F2O3S, the dihedral angle between the aromatic rings is 6.19 (13)°. In the crystal, mol­ecules are linked by C—H⋯O hydrogen bonds, generating [110] chains