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Titanium dioxide (TiO2) could improve the self-cleaning performances of cotton fabric owing to its good photocatalytic performances. However, the fast recombination rate of the photogenerated electron-hole pairs and narrow photoresponse range of TiO2 limit its wide application. In this work, Ag2S and reduced graphene oxider (rGO) were compounded with TiO2, and the composite was loaded on the surface of cotton fabric by hydrothermal method to enhance the self-cleaning performance of cotton fabric. The close contact between Ag2S and TiO2 increases the light response range. Then, rGO could effectively transfer photogenerated electrons, prolong the recombination time of carriers and improve the photocatalytic efficiency. The cotton fabric was characterized by XRD, SEM, Raman and fluorescence spectra. The photocatalytic degradation of methylene blue under visible light was studied. The results showed that TiO2/Ag2S/rGO adhered uniformly on the surface of cotton fabric and had good adhesion properties. In addition, under visible light irradiation, cotton fabric has excellent photocatalytic self-cleaning performance, washing resistance and rub resistance.

Transition metal carbides (TMCs) have attracted great interest owing to their potential applications for energy storage and electrocatalysis. But the synthesis of high-quality TMCs usually needs high energy consumption, long reaction times, or dangerous chemical reagents, limiting their practical application. Here, a microwave combustion method is developed to rapidly (∼2 min) produce transition metal carbides under ambient conditions. The as-synthesized TMCs (W2C, VC, Fe3C, NbC, TaC, and Mo2C) and rGO composites exhibit outstanding catalytic performance for the hydrogen evolution reaction (HER) over a broad range of pH values. This work highlights a novel strategy for the design and synthesis of transition metal carbides.

With the development of technology, the requirements of hardware equipment and user expectations of visual enjoyment are increasingly gradually. The Joint Video Exploration Team (JVET) has established the latest video compression standard, Future Video Coding (FVC). FVC adopts QuadTree plus Binary Tree (QTBT) based Coding Unit (CU) structure, which not only removes the complex hierarchical structure of the CU, Prediction Unit (PU), and Transform Unit (TU) but also supports square and rectangular coding blocks based on the texture of the video content. Although the QTBT structure can provide superior coding performance, it significantly increases the encoding time, particularly in intra coding. Therefore, developing a fast intra CU partition decision algorithm is essential. In this paper, a fast CU partition decision algorithm in FVC intra coding based on spatial features is proposed. Different spatial features in the pixel domain are proposed in the binary tree and quadtree decision processes. Spatial features for the binary tree are employed for early skipping of the encoding process of CUs with binary tree depth and for early determination of binary tree split mode. Spatial features for the quadtree are employed for early splitting or termination of CUs with quadtree depth. Compared with JEM 5.0, the proposed method can save 23% encoding time on average with a slight increase of 0.62% in the Bjontegaard delta bitrate (BDBR).

Natural dyes have been the focus of textile industry for their environmental protection properties. However, some limitations such as poor photostability has limited their wide application, and the researches of the discoloration mechanism of fabric with natural dye are relatively limited. As one of the most important natural dye, madder has been widely used in textile field. Herein, as the main pigment of madder, alizarin was selected as the model natural dye to explore the photo-fading progress of alizarin-dyed fabrics. The photodegradation progress of alizarin was explored by UV, HPLC, HPLC-MS and Datacolor (computer color matching system). When exposed to light, alizarin could be oxidized into colorless small molecules through ·OH radical-mediated route, and finally resulting in the fading of alizarin. In addition, the influence of pre-mordant and the liquid rate has also been studied. These results provide us a good insight into the photo-fading progress of natural dyes, and our work could help to open the way to further studies aiming at improving the photostability of natural dyes or developing new photo-stable dyes.

Water silicon sol was prepared in this paper using sol-gel technology, which tetraethoxysilane (TEOS) was used as precursor. And the sol-Si/direct dye was prepared by doping dyes into sol-Si, then the sol-Si/direct dye was used to dye cotton woven fabric. The particle sizes of sol-Si and sol-Si/direct dye, the effects of sol-Si dosage, electrolyte dosage on the dyeing performance of sol-Si/direct dye were discussed. It showed that the particle sizes was really stable and under the influence of sol-Si the fastness were improved evidently, and the K/S value can be able to meet the requirements.

The Joint Video Exploration Team (JVET) has established the latest video compression standard, Future Video Coding (FVC). However, quadtree plus binary tree (QTBT) based coding unit (CU) structure increases noticeable computational complexity in FVC intra coding. In this paper, a fast intra CU binary tree partition decision algorithm based on spatial features is proposed. The proposed method compared to JEM5.0 can save 23% encoding time with only 0.55% BDBR increment.

Acrylonitrile (AN) and itaconic acid (IA) were used to synthesize UHMWPAN by aqueous suspension method with 2,2’-azobisisobutyronitrile (AIBN) as the initiator and polyvinylalcohol (PVA) as the disperser at different temperatures (55°C~75°C) for different timings (1.0h~3.0h). The usage amounts of AN, IA, AIBN and PVA were also technical polymerization parameters used to obtain the optimal polymerization process. We found that the conversion and the viscosity average molecular weight both achieved the optimum levels when the conditions were as follows: the total monomer concentration (21wt%), the monomer ratio (AN: IA=98:2), the usage amount of the initiator (AIBN, 0.01wt%), the usage amount of the disperser (PVA, 0.1wt%), the polymerization temperature (70°C) and the polymerization time (2h).

This paper proposes an efficient method for accelerating Transform Unit (TU) depth decisions based on the rough mode cost (RMC), which is the simplified rate-distortion (RD) cost during the rough mode decision (RMD), in HEVC intra coding. The TU partition of the mode with the minimal RMC is used to determine the TU partitions of remaining intra modes. The proposed TU partitioning method improves RD performance as well as reduces the encoding time; it demonstrates greater performance than the default method in reference software.

The effects of ultra high molecular weight Polyacrylonitrile (UHMW-PAN) on the rheological behavior of PAN/DMSO solution have been investigated using a cone-plate rheometer in this work. The rheological behavior was characterized by steady shear and oscillation test It is observed from the measurements that, the rheological behavior of the polymer mixture of UHMW-PAN and AMW-PAN makes a difference to the AMW-PAN solution due to macromolecular entanglements, the viscosities of the solutions decreased with the rising of shear rate, shear viscosity rise with the increase of the molecular weight of the UHMW-PAN. For dynamic experiments, a steady increase of both and with the increase of oscillation frequency and molecular weight of UHMW-PAN was seen for all samples. The and increase with the decrease of the temperature or with the increase of the contents of the UHMW-PAN.

At present, using a computer to fabric defect detection is a hot method in textile quality assess. The contrast of fabric defects images is not high and effects of tradition processing methods are not particularly good. In this paper, therefore, based on Rough Set and Pulse Coupled Neural Networks, a filtering algorithm is proposed and good results have been achieved.

The octanol / water partition coefficient (Kow) is an important physical parameters to describe their behavior in the environment. However, because of some reasons, it is difficult to determine the octanol / water partition coefficient of each compound accurately. In this paper, we will introduce RBF neural network and molecular bond connectivity index to forecast the solubility of organic compounds in water. The result is better using the BP network to predict, the correlation coefficient has achieved 0.998, the prediction error in the permission scope.

Forecast model of the nitrobenzene compound biological toxicity has been established based on the RBF neural network, the correlation coefficient between the predicted value and the actual value reaches 0.993. Prediction errorpsilas biggest absolute value is 0.34, the rest is under 0.20.So it is a good forecast mode of the nitrobenzene compound biological activity.