The Long-Term Effectiveness of Eco-Driving Training: A Pilot Study

Eco-driving has been proven to have a great benefit in reducing vehicle fuel consumption in many developed countries. However, the potential of ecodriving on energy-saving in China is not very clear. Taking three taxi drivers from Beijing Beiqi Taxi Group Company as examples, the petrol consumption, travel distance and many other factors influencing vehicle fuel use before and after ecodriving training were collected through survey forms. The short-term and long-term effect of eco-driving was compared. The results showed that, taking one month as the statistical cycle, the benefit of eco-driving in saving fuel consumption averaged is 19.04%; while it reduced to 14.41% after four months from taking eco-driving training. Thus, drivers would partially regressed back to less economically driving behaviors and thus resulting in lower fuel savings after sometime. This study laid a foundation to evaluate the benefit of eco-driving in saving energy use

Eisenia fetida Protease-III-1 Functions in Both Fibrinolysis and Fibrogenesis

The fibrinolytic function of earthworm protease-III-1 (Ef P-III-1) has been studied in recent years. Here, we found that Ef P-III-1 acted not only in fibrinogenolysis, but also in fibrogenesis. We have used Ef P-III-1 to hydrolyze fibrinogen, and to activate plasminogen and prothrombin. Based on the N-terminal sequences of the hydrolytic fragments, Ef P-III-1 was showed to specifically recognize the carboxylic sites of arginine and lysine. Analyses by fibrinogenolysis mapping and amino acid sequencing revealed that the isozyme could cleave the alpha, beta, and gamma chains of fibrinogen, showing a high α-fibrinogenase, moderate β-fibrinogenase, and low γ-fibrinogenase activities. Interestingly, Ef P-III-1 activated plasminogen and released active plasmin, suggesting a tPA-like function. Furthermore, Ef P-III-1 showed a factor Xa-like function on prothrombin, producing alpha-thrombin. The function in both activating prothrombin and catalyzing fibrinogenolysis suggests that Ef P-III-1 may play a role in the balance between procoagulation and anticoagulation

Synthesis, crystal structure of and DFT calculations on bisglycinato-bis[p-(hydroxymethyl)pyridine]nickel(II)

The main aim of this study was to investigate the relationship between mIn tA new Ni(II) complex of bisglycinato-bis[p-(hydroxylmethyl)py-ridine] was synthesized and characterized by elemental analysis, IR, UV–Vis spectroscopy and X-ray single crystal diffraction analysis. The thermal stability of the title complex was also determined. The complex adopts a distorted octahedral geometry and possesses inversion symmetry with the Ni(II) ion as the center of inversion. Density function theory (DFT) calculations of the structure, electronic absorption spectra, electron structure and natural population analysis (NPA) at the B3LYP/LANL2DZ level of theory were performed. The predicted geometric parameters and electronic spectra were compared with the experimental values and they supported each other. The NPA results indicate that the electronic transitions were mainly derived from the contribution of an intra-ligand (IL) transition, a ligand-to-metal charge transfer (LMCT) transition and a d-d transition. The electron structure calculations suggest that the central Ni(II) ion uses its 4s and 3d orbitals to form covalent bonds with coordinated N and O atoms. The calculated bond orders are also consistent with the thermal decomposition results. Based on vibrational analysis, the thermodynamic properties of the title complex were predicted and the correlative equations between these thermodynamic properties and temperature are also reported

Characterizing and Predicting Early Reviewers for Effective Product Marketing on E-Commerce Websites

Online reviews have become an important source of information for users before making an informed purchase decision. Early reviews of a product tend to have a high impact on the subsequent product sales. In this paper, we take the initiative to study the behavior characteristics of early reviewers through their posted reviews on two real-world large e-commerce platforms, i.e., Amazon and Yelp. In specific, we divide product lifetime into three consecutive stages, namely early, majority and laggards. A user who has posted a review in the early stage is considered as an early reviewer. We quantitatively characterize early reviewers based on their rating behaviors, the helpfulness scores received from others and the correlation of their reviews with product popularity. We have found that (1) an early reviewer tends to assign a higher average rating score; and (2) an early reviewer tends to post more helpful reviews. Our analysis of product reviews also indicates that early reviewers' ratings and their received helpfulness scores are likely to influence product popularity. By viewing review posting process as a multiplayer competition game, we propose a novel margin-based embedding model for early reviewer prediction. Extensive experiments on two different e-commerce datasets have shown that our proposed approach outperforms a number of competitive baselines

HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models

Large language models (LLMs), such as ChatGPT, are prone to generate hallucinations, i.e., content that conflicts with the source or cannot be verified by the factual knowledge. To understand what types of content and to which extent LLMs are apt to hallucinate, we introduce the Hallucination Evaluation benchmark for Large Language Models (HaluEval), a large collection of generated and human-annotated hallucinated samples for evaluating the performance of LLMs in recognizing hallucination. To generate these samples, we propose a ChatGPT-based two-step framework, i.e., sampling-then-filtering. Besides, we also hire some human labelers to annotate the hallucinations in ChatGPT responses. The empirical results suggest that ChatGPT is likely to generate hallucinated content in specific topics by fabricating unverifiable information (i.e., about $19.5\%$ responses). Moreover, existing LLMs face great challenges in recognizing the hallucinations in texts. However, our experiments also prove that providing external knowledge or adding reasoning steps can help LLMs recognize hallucinations. Our benchmark can be accessed at https://github.com/RUCAIBox/HaluEval.Comment: Accepted to EMNLP 2023 Main Conference (Long Paper

Structure and superconductivity of Mg(B1-xCx)2 compounds

In this paper, we reported the structural properties and superconductivity of Mg(B1-xCx)2 compounds. Powder x-ray diffraction results indicate that the samples crystallize in a hexagonal AlB2-type structure. Due to the chemical activity of Mg powders, a small amount of MgO impurity phase was detected by x-ray diffraction. The lattice parameters decrease slightly with increasing carbon content. Magnetization measurements indicate the non-stoichiometry of MgB2 has no influence on the superconducting transition temperature and the transition temperature width. The addition of carbon results in a decrease of Tc and an increase in the superconducting transition width, implying the loss of superconductivity.Comment: PDF files, 5 pages,3 figures, Accepted by Chinese Physics on Feb. 26, 2001(in press