Insight into Biomass Upgrade: A Review on Hydrogenation of 5-Hydroxymethylfurfural (HMF) to 2,5-Dimethylfuran (DMF)

Recent developments in the transformation of biobased 5-hydroxymethylfurfural (HMF) into a potential liquid fuel, 2,5-dimethylfuran (DMF), are summarised. This review focuses briefly on the history of HMF conversion to DMF in terms of the feedstock used and emphasises the ideal requirements in terms of the catalytic properties needed in HMF transformation into DMF. The recent state of the art and works on HMF transformation into DMF are discussed in comparison to noble metals and non-noble metals as well as bimetallic catalysts. The effect of the support used and the reaction conditions are also discussed. The recommendations for future work and challenges faced are specified.

Perception, Attitude and Support of Society Towards Drug Abuse: Do Gender, Age and Education Matter?

This article highlights the support, attitude and perception of the general public towards drug abuse so that appropriate policies can be framed for the prevention of drug abuse among youth. The study aims to understand the relationship among variables influencing behaviour change with respect to drug abuse. Questionnaire from 1,159 respondents was administered comprising of 39 items exploring Perception, Attitude, Support pertaining to illicit drugs. Positive or negative attitude towards drug abuse is evolved out of the perception of problems associated with drug abuse and the support provided to dissuade drug-abusing behaviour, and relationship among these variables was tested using SEM-Path analysis. The perception of problems related to drug addiction significantly influences the attitude towards drug addiction. The perceived nature of the support structure augments the influence further (partial mediation). The augmenting effect of the support structure can be seen among gender, age and education. Moderator effects of age, gender and education were studied by estimating multi-group path coefficients. This article is useful to local government as they may take some of the findings of this article for framing policy related to educating youth related to drugs, creating a campaign regarding the harm of drug abuse and involving those volunteers in drug assistance programmes that are more supportive of drug addicts. This article is helpful for society to make them understand that their positive attitude and support towards drug abuse will give a second chance to drug addicts to leave drugs and live a normal life again.

Ni, Mo-containing catalysts for the single-step synthesis of propylene from ethylene: the effect of the support nature

Polyfunctional Ni, Mo-containing catalysts were synthesized by sequential impregnation of the support (SiO2, Al2O3, B2O3-Al2O3, SO42–/Al2O3,SO42–/ZrO2) with solutions of the corresponding salts with intermediate drying at 120 °C and calcination at 500–550 °C. Physicochemical properties of the synthesized catalysts were studied by XRD, H2-TPR, UV-vis spectroscopy and EPR; the catalysts were tested in the singlestep synthesis of propylene from ethylene at atmospheric pressure, temperature 200 °С, and ethylene mass flow rate 0.5 h–1. The maximum values of ethylene conversion and propylene yield were observed for the sample synthesized from borate-containing alumina; this is related to the formation of active sites of ethylene dimerization – the Ni2+ cations bound to acid sites of the support, and active sites of metathesis – the surface monomolybdate compounds.

Data Mining Technology Application in False Text Information Recognition

False information on the Internet is being heralded as serious social harm to our society. To recognize false text information, in this paper, an effective method for mining text features is proposed in the field of false drug advertisements. Firstly, the data of false drug advertisements and real drug advertisements were collected from the official websites to build a database of false and real drug advertisements. Secondly, by performing feature extraction on the text of drug advertisements, this work built a characteristic matrix based on the effective features and assigned positive or negative labels to the feature vector of the matrix according to whether it is a fake medical advertisement or not. Thirdly, this study trained and tested several different classifiers, selected the classification model with the best performance in identifying false drug advertisements, and found the key characteristics that can determine the classification. Finally, the model with the best performance was used to predict new false drug advertisements collected from Sina Weibo. In the case of identifying false drug advertisements, the classification effect of the support vector machine (SVM) classifier established on the feature set after feature selection was the most effective. The findings of this study can provide an effective method for the government to identify and combat false advertisements. This study has a certain reference significance in demonstrating the use of text data mining technology to identify and detect information fraud behavior.