Genetic Diversity of the ORF5 Gene of Porcine Reproductive and Respiratory Syndrome Virus Isolates in Southwest China from 2007 to 2009

To gain insight into the molecular epidemiology and possible mechanisms of genetic variation of porcine reproductive and respiratory syndrome (PRRS) in Yunnan Province of China, the ORF5 gene of 32 PRRSV isolates from clinical samples collected from 2007 to 2009 were sequenced and analyzed. Nucleotide and amino acid analyses were carried out on 32 isolates and representative strains of the North American genotype, European genotype and two representative Chinese isolates. Results revealed that these isolates share 86.9–99.0% nucleotide and 87.5–98.0% amino acid identity with VR-2332 the prototypical North American PRRSV, 61.7–62.9% and 54.3–57.8% with Lelystad virus (LV) the representative strain of European genotype, 91.2–95.4% and 90.0–94.5% with CH-1a that was isolated in mainland China in 1996, 88.1–99.3% and 85.5–99.0% with JX-A1 the representative strain of High pathogenic PRRSV in China, and 86.2–99.8% and 85.5–100.0% between isolated strains of different years, respectively. Phylogenetic analysis revealed that all 32 PRRSV isolates belonged to the North American genotype and were further divided into two different subgenotypes. Subgenotype 1 comprised twenty two Yunnan isolates which divided into two branches. Subgenotype 2 comprised ten isolates which closely related to the RespPRRS vaccine and its parent strain VR-2332. The functional domains of GP5 such as the signal peptide, ectodomain, transmembrane regions and endodomain were identified and some motifs in GP5 with known functions, such as primary neutralizing epitope (PNE) and decoy epitope were also further analyzed. Our study shown the great genetic diversity of PRRSV in southwest China, rendering the guide for control and prevention of this disease

Reconstructed covalent organic frameworks

Covalent organic frameworks (COFs) are distinguished from other organic polymers by their crystallinity1–3, but it remains challenging to obtain robust, highly crystalline COFs because the framework-forming reactions are poorly reversible4,5. More reversible chemistry can improve crystallinity6–9, but this typically yields COFs with poor physicochemical stability and limited application scope5. Here we report a general and scalable protocol to prepare robust, highly crystalline imine COFs, based on an unexpected framework reconstruction. In contrast to standard approaches in which monomers are initially randomly aligned, our method involves the pre-organization of monomers using a reversible and removable covalent tether, followed by confined polymerization. This reconstruction route produces reconstructed COFs with greatly enhanced crystallinity and much higher porosity by means of a simple vacuum-free synthetic procedure. The increased crystallinity in the reconstructed COFs improves charge carrier transport, leading to sacrificial photocatalytic hydrogen evolution rates of up to 27.98 mmol h−1 g−1. This nanoconfinement-assisted reconstruction strategy is a step towards programming function in organic materials through atomistic structural control

l-Leaks: Membership Inference Attacks with Logits

Machine Learning (ML) has made unprecedented progress in the past several decades. However, due to the memorability of the training data, ML is susceptible to various attacks, especially Membership Inference Attacks (MIAs), the objective of which is to infer the model's training data. So far, most of the membership inference attacks against ML classifiers leverage the shadow model with the same structure as the target model. However, empirical results show that these attacks can be easily mitigated if the shadow model is not clear about the network structure of the target model. In this paper, We present attacks based on black-box access to the target model. We name our attack \textbf{l-Leaks}. The l-Leaks follows the intuition that if an established shadow model is similar enough to the target model, then the adversary can leverage the shadow model's information to predict a target sample's membership.The logits of the trained target model contain valuable sample knowledge. We build the shadow model by learning the logits of the target model and making the shadow model more similar to the target model. Then shadow model will have sufficient confidence in the member samples of the target model. We also discuss the effect of the shadow model's different network structures to attack results. Experiments over different networks and datasets demonstrate that both of our attacks achieve strong performance.Comment: 10pages,6figure

Research on Carbonation Characteristics and Frost Resistance of Iron Tailings Powder Concrete under Low-Cement Clinker System

The accelerated carbonation, natural carbonation, fast freeze-thaw test, and pore structure analysis of C30 and C50 concrete with different proportions of iron tailings powder and slag powder were tested, respectively. The results show that the accelerated carbonation depth and natural carbonation depth of concrete increase with the increase of iron tailings powder content. The prediction model of carbonation depth of iron tailings powder concrete is established by introducing the iron tailings content coefficient and strength influence coefficient. The error between the calculated value of the model and the test value of 28 d curing concrete natural carbonation depth is small, which proves that the model is completely feasible. When iron tailings powder accounts for 50% of mineral admixture, it is helpful to improve the frost resistance of concrete. According to the pore structure analysis, the introduction of iron tailings powder can optimize the pore structure, improve the porosity of harmless and less harmful pores, and thus improve the frost resistance

Modelling the heat transfer of an antioxidant coating heating system in wide temperature and simulation

MoSi2 is regarded as the most potential coating material in high-temperature application. The present aims to explore a feasible resistance direct heating technique for thermogravimetric heating in the wide-temperature range (773–2573 K) of MoSi2 coating. The physical heat transfer model is derived for the first time. Furthermore, based on the method of finite element analysis, heat distribution and heat transfer mechanism of the surface of MoSi2 coating material before and after oxidation are discussed. The research indicates that surface heat distribution is non-uniform, and coupling effect results in the maximum heat occurs in the center area of MoSi2 coating surface. When electric voltage increases ranging from 1.4 V to 1.7 V, the maximum temperature of surface increase from 2073 K (service temperature) to 2303 K (melting temperature) before the oxidation. During oxidation, the maximum temperature of surface quasi-linearly increases with the increasing of oxidated thickness. When the defects occur (the defect diameter is 1 × 10−3 to 3 × 10−3 m and the thickness is 0.05 × 10−3 to 0.5 × 10−3 m), the maximum temperature of MoSi2 coating surface is positively related to the defective diameter, and negatively related to the defect thickness. Especially, this paper reveals the heat transfer mechanisms and law of the MoSi2 coating, which will have a positive effect on the evaluating of fatigue failure and reliability of MoSi2 coating materials. Keywords: MoSi2 coating, Thermogravimetric heating, Heating model, Heat transfe

A Highly Conductive COF@CNT Electrocatalyst Boosting Polysulfide Conversion for Li–S Chemistry

The catalysis of covalent organic frameworks (COFs) in Li–S chemistry is largely blocked by a weak chemical interaction and low conductivity. Herein, a new kind of diketopyrrolopyrrole (DPP)-based COF is in situ fabricated onto the carbon nanotube (CNT) surface (denoted as COF@CNT) to uncover the electrocatalysis behavior by its strong chemical interaction and highly conductive property. We declare that the electrocatalytic activity of DPP-COF can be maximized by introducing an appropriate content of CNT (66 wt %); the analyses including density functional theory calculations, X-ray photoelectron spectroscopy, Fourier transform infrared, and Raman show that the DPP moiety can mediate the conversion of polysulfides contributed by a CO/C–O bonding conversion. Hence, the modified battery shows a 0.042% decay rate over 1000 cycles and achieves a desirable capacity of 8.7 mAh cm–2 with 10 mg cm–2 sulfur loading and lean electrolyte (E/S = 5). This work will inspire the rational design of COF@support hybrids for various electrocatalysis applications

Benzotriazole-Containing Planar Conjugated Polymers with Noncovalent Conformational Locks for Thermally Stable and Efficient Polymer Field-Effect Transistors

We report a series of benzotriazole-based semicrystalline π-conjugated polymers with noncovalent conformational locks for applications in polymer field-effect transistors. The benzotriazole moiety is a versatile electron-deficient building block that offers two chemically functionalizable sites, 2­(N) and 5, 6­(C) positions, allowing easy modulation of the solution processability and electronic structures of the resulting polymers. Fluorine or alkoxy substituents were introduced to the benzotriazole unit to enhance the molecular ordering through intra- and intermolecular F···S, F···H–C, C–F···π_F, or S···O attractive interactions. The fluorinated polymer (<b>PTBTz-F</b>) showed remarkably enhanced hole mobility (μ_h = 1.9 cm²/(V·s), on/off ratio = 8 × 10⁷) upon thermal annealing at 305 °C, compared to the unsubstituted one (<b>PTBTz</b>) (μ_h = 7.0 × 10^–3 cm²/(V·s), on/off ratio = 3 × 10⁶). Alkoxy unit substitution (<b>PTBTz-OR</b>) also improved the carrier mobility up to 0.019 cm²/(V·s) with an on/off ratio of 4 × 10⁵. Fluorine or alkoxy substitution induced tight interchain ordering with edge-on orientation, as confirmed by X-ray diffraction measurements. In particular, fluorinated <b>PTBTz-F</b> showed high thermal stability (<i>T</i>_d 453 °C) and the remarkable device characteristics with deep frontier orbital levels