Antibacterial activity of V- doped rod-like MgO crystals decorated with nanoflake layer

In present study, we report a V doping fabrication method for obtaining rod-like MgO crystals decorated with a nanoflake layer. This novel structure has only been minimally reported in literature. Pure MgO and Mg₂V₂O₇–MgO composite materials were obtained by precipitation and impregnation methods, with vanadium added concentrations of 0–9%. The influence of V doping on crystal structure and particle morphology of MgO was investigated by scanning electron microscopy (SEM). X-ray diffraction (XRD) analysis demonstrated that MgO has a cubic structure, while X-ray photoelectron spectroscopy (XPS) revealed that V⁵⁺ exists on the surface of MgO. The specific surface areas and pore sizes of MgO composites were calculated by BET and BJH analysis. These techniques revealed that specific surface area and pore size of MgO increased due to vanadium doping. The antibacterial effects of Mg₂V₂O₇–MgO composite materials against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) were assessed using a bacterial killing/colony-forming unit (CFU) assay and bacteriostatic ring method. Our results demonstrate that V doping dramatically improved antimicrobial properties of MgO, with 7 mol% doping inducing the best antibacterial activity. The antibacterial mechanisms of Mg₂V₂O₇–MgO composite material were also proposed.     

Multi-skeletal PtPdNi nanodendrites as efficient electrocatalyst with high activity and durability towards oxygen reduction reaction

Engineering alloy nanostructures with a combination of highly active noble metals (Pt and Pd) and less electronegative non-noble metal (Ni) is found to be crucial for improving surface reactivity by enriching with active Pt sites. Herein, a multi-skeletal PtPdNi nanodendrites (NDs) was successfully formed by a simple one-pot method with structure directing agent. The modification of Pt electronic structure and their interaction due to compressive strain were explored using benchmark characterization techniques, which showed that the PtPdNi NDs possess Pt-enriched surface, corroborating to more active catalyst sites for oxygen reduction reaction (ORR) in acidic medium. The PtPdNi NDs have a higher electrochemical surface area (63 m² g^?1) and an earlier onset potential (1.01 V) than PtPd NDs, PtNi NDs, and commercial Pt/C catalysts, indicating the outstanding ORR performance. The high mass and specific activities, as well as superior durability after accelerated degradation test (ADT), highlight the remarkable electrocatalytic performance of PtPdNi NDs over others. As a result, enhancing Pt utilization through the formation of PtPdNi NDs could be a reliable strategy to improve ORR electrocatalysis for polymer electrolyte membrane fuel cell (PEMFC) applications.     

Image sequence-based risk behavior detection of power operation inspection personnel

A novel image sequence-based risk behavior detection method to achieve high-precision risk behavior detection for power maintenance personnel is proposed in this paper. In this method, the original image sequence data is first separated from the foreground and background. Then, the free anchor frame detection method is used in the foreground image to detect the personnel and correct their direction. Finally, human posture nodes are extracted from each frame of the image sequence, which are then used to identify the abnormal behavior of the human. Simulation experiment results demonstrate that the proposed algorithm has significant advantages in terms of the accuracy of human posture node detection and risk behavior identification.     

Cornus officinalis vinegar reduces body weight and attenuates hepatic steatosis in mouse model of nonalcoholic fatty liver disease

This study aimed to determine the main bioactive components of Cornus officinalis vinegar (COV) and assess the effects of COV on the body weight (BW) and hepatic steatosis in a nonalcoholic fatty liver disease (NAFLD) mouse model. Seven-week-old KM female mice were divided into five treatment groups: (1) Normal control (NC) group, (2) high fat diet (HFD) group, (3) low concentration treatment group (3.5% COV), (4) medium concentration treatment group (5.0% COV), and (5) high concentration treatment group (6.5% COV). Mice in the NC group were fed with a normal chow diet, and those in the other four groups were fed with a HFD known for causing obesity for 10 weeks. Then, mice in the three COV treatment groups were orally administered with COV once a day for 6 weeks. Results showed that the contents of loganin and morroniside in COV reached 16.82 and 51.17 µg/ml, respectively, and COV also contained multiple organic acids. COV significantly reduced BW, abdominal fat weight, liver weight, and the levels of glucose, triglyceride, and low-density lipoprotein cholesterol of serum and increased the levels of high-density lipoprotein cholesterol of serum (p < 0.05). COV also improved the liver function and anti-oxidant activity of liver (p < 0.05). COV treatments increased the interleukin-10 expression and reduced the tumor necrosis factor-α expression in the liver tissue of NAFLD mice (p < 0.05). Histopathological observation revealed that COV suppressed hepatic lipid accumulation and steatosis. The results suggest that COV may contribute to the alleviation of NAFLD and obesity.     

Preparation,structural and photocatalytic activity of Sn/Fe co-doped TiO2 nanoparticles by sol-gel method

Pure and Sn/Fe co-doped (0.2 at.% Sn and 0.6 at.% Fe, 0.6 at.% Sn and 0.2 at.% Fe, 1.0 at.% Sn and 1.0 at.% Fe) TiO₂ nanoparticles were synthesized via a sol-gel method and subsequently calcined at different temperatures. Furthermore, the particles were analyzed by TG-DSC, XRD, TEM, HRTEM, EDS, SAED and UV–Vis for investigating the influences of dopant and calcination temperature on the thermal effect, composition, morphology, energy band gap (E_g) and the degradation efficiency of methyl orange (MO) under various light irradiations respectively. Results indicated that Sn/Fe co-doping inhibited the crystallization transformation from anatase to rutile phase of TiO₂ and decreased the E_g. The increased calcination temperature and Sn/Fe co-doped effect brought about the abnormal grain growth of TiO₂ nanoparticles. 0.6 at.% Sn/0.2 at.% Fe and 1.0 at.% Sn/1.0 at.% Fe co-doped TiO₂ nanoparticles presented better photocatalytic performance than pure and 0.2 at.% Sn/0.6 at.% Fe co-doped TiO₂ nanoparticles under visible light irradiation mainly due to the decreased E_g. On the contrary, 0.2 at.% Sn and 0.6 at.% Fe co-doped TiO₂ nanoparticles calcined at 650 °C showed the most excellent photocatalytic performance under UV light irradiation, which was about twice as large as that of pure TiO₂ possibly due to the formed hybrid structure of anatase and rutile phase as well as the h⁺-mediated decomposition pathway.     

Effects of non-thermal plasma treating wheat kernel on the physicochemical properties of wheat flour and the quality of fresh wet noodles

The effects of non-thermal plasma (NTP) on the physicochemical properties of wheat flour and the quality of fresh wet noodles ( FWN) were investigated. The results showed that NTP effectively decreased the total plate count (TPC), yeast and mould count (YMC) and Bacillus spp. in wheat flour. Wet gluten contents and the stability time reached the maximum when treated for 20 s. The viscosity of starch increased significantly after treatment due to the increased of damaged starch. The contents of secondary structure were altered to some extent, which was because that the ordered network structure of gluten protein broken. Furthermore, compared with the control, texture properties of FWN were enhanced significantly at 20 s, and the darkening rate of FWN was greatly inhibited due to the low polyphenol oxidase (PPO) activity. Consequently, the most suitable treatment was 500 W for 20 s, providing a basis for the application of NTP in flour products.     

No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.