7,321 research outputs found
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 (700âmg/kg) and LPS (20âÎŒg/kg). DHI was administrated twice, at 12 and 1âh, respectively, before D-GalN/LPS injection. After stimulation with D-GalN/LPS for 1 and 6âh, 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-1ÎČ 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, 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. 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 SC 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-DifluoroÂphenÂyl)ethyl toluene-4-sulfonate
In the title compound, C15H14F2O3S, the dihedral angle between the aromatic rings is 6.19â
(13)°. In the crystal, molÂecules are linked by CâHâŻO hydrogen bonds, generating [110] chains
- âŠ