Synthesis and characterization of carborane-containing poly(hydroxy ethers) with excellent thermal stability

o-Carborane-containing poly(hydroxy ethers)(P1, P2 and P3) were synthesized via "advancement reaction" of o-carborane-containing bisphenol(4) and diglycidyl ether of bisphenols(DGEBA and 1). FTIR and ~(1) H-, ~(13)C-, and ~(11) B-NMR were utilized to characterize the obtained polymers. TGA test was conducted under nitrogen and air. It is found that the shielding effect of carborane moiety on its adjacent aromatic structures contributes to high initial decomposition temperatures, while oxygen in air has an adverse effect on the initial decomposition temperature. The oxygen can combine with polymer chain to form peroxide and hydroperoxide groups, which are more reactive during the degradation process. Besides, o-carborane-containing poly(hydroxy ethers) have high char yield at elevated temperatures. The boron atom combines with oxygen from the polymer structure or/and from air, thus to form a three-dimensional network linked with B―O―B and B―C bonds, and retain the polymer weight to a large extent.     

Protective Effects of Cinnamaldehyde on the Inflammatory Response,Oxidative Stress,and Apoptosis in Liver of Salmonella typhimurium-Challenged Mice

Salmonella typhimurium infection is associated with gastrointestinal disorder and cellular injury in the liver of both humans and animals. Cinnamaldehyde, the main component of essential oil from cinnamon, has been reported to have anti-inflammatory, anti-oxidative, and anti-apoptotic effects. However, it remains unknown whether cinnamaldehyde can alleviate Salmonella typhimurium infection-induced liver injury in mice. In the present study, we found that cinnamaldehyde attenuated Salmonella typhimurium-induced body weight loss, the increase of organ (liver and spleen) indexes, hepatocyte apoptosis, and the mortality rate in mice. Further study showed that cinnamaldehyde significantly alleviated Salmonella typhimurium-induced liver injury as shown by activities of alanine transaminase, aspartate transaminase, and myeloperoxidase, as well as malondialdehyde. The increased mRNA level of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α, and IFN-γ) and chemokines (CCL2 and CCL3) induced by Salmonella typhimurium were significantly abolished by cinnamaldehyde supplementation. These alterations were associated with a regulatory effect of cinnamaldehyde on TLR2, TLR4, and MyD88. 16S rDNA sequence analysis showed that Salmonella typhimurium infection led to upregulation of the abundances of genera Akkermansia, Bacteroides, Alistipes, Muribaculum, and Prevotellaceae UCG-001, and downregulation of the abundances of genera Lactobacillus, Enterorhabdus, and Eggerthellaceae (unclassified). These alterations were reversed by cinnamaldehyde supplementation. In conclusion, cinnamaldehyde attenuated the inflammatory response, oxidative stress, and apoptosis in the liver of Salmonella typhimurium-infected mice. Supplementation of cinnamaldehyde might be a preventive strategy to alleviate liver injury caused by Salmonella typhimurium infection in humans and animals.     

Sensitivity of energy eigenstates to perturbation in quantum integrable and chaotic systems

We study the sensitivity of energy eigenstates to small perturbation in quantum integrable and chaotic systems.It is shown that the distribution of rescaled components of perturbed states in unperturbed basis exhibits qualitative difference in these two types of systems:being close to the Gaussian form in quantum chaotic systems,while,far from the Gaussian form in integrable systems.     

Sensor and Actuator Fault Diagnosis for Robot Joint Based on Deep CNN

This paper proposes a data-driven method-based fault diagnosis method using the deep convolutional neural network (DCNN). The DCNN is used to deal with sensor and actuator faults of robot joints, such as gain error, offset error, and malfunction for both sensors and actuators, and different fault types are diagnosed using the trained neural network. In order to achieve the above goal, the fused data of sensors and actuators are used, where both types of fault are described in one formulation. Then, the deep convolutional neural network is applied to learn characteristic features from the merged data to try to find discriminative information for each kind of fault. After that, the fully connected layer does prediction work based on learned features. In order to verify the effectiveness of the proposed deep convolutional neural network model, different fault diagnosis methods including support vector machine (SVM), artificial neural network (ANN), conventional neural network (CNN) using the LeNet-5 method, and long-term memory network (LTMN) are investigated and compared with DCNN method. The results show that the DCNN fault diagnosis method can realize high fault recognition accuracy while needing less model training time.     

Solving linear optimization over arithmetic constraint formula

Since Balas extended the classical linear programming problem to the disjunctive programming (DP) problem where the constraints are combinations of both logic AND and OR, many researchers explored this optimization problem under various theoretical or application scenarios such as generalized disjunctive programming (GDP), optimization modulo theories (OMT), robot path planning, real-time systems, etc. However, the possibility of combining these differently-described but form-equivalent problems into a single expression remains overlooked. The contribution of this paper is two folded. First, we convert the linear DP/GDP model, linear-arithmetic OMT problem and related application problems into an equivalent form, referred to as the linear optimization over arithmetic constraint formula (LOACF). Second, a tree-search-based algorithm named RS-LPT is proposed to solve LOACF. RS-LPT exploits the techniques of interval analysis and nonparametric estimation for reducing the search tree and lowering the number of visited nodes. Also, RS-LPT alleviates bad construction of search tree by backtracking and pruning dynamically. We evaluate RS-LPT against two most common DP/GDP methods, three state-of-the-art OMT solvers and the disjunctive transformation based method on optimization benchmarks with different types and scales. Our results favor RS-LPT as compared to existing competing methods, especially for large scale cases.     

Transparent Electronic Skin Device Based on Microstructured Silver Nanowire Electrode

Transparent, flexible electronic skin holds a wide range of applications in robotics, humanmachine interfaces, artificial intelligence, prosthetics, and health monitoring. Silver nanowire are mechanically flexible and robust, which exhibit great potential in transparent and electricconducting thin film. Herein, we report on a silver-nanowire spray-coating and electrodemicrostructure replicating strategy to construct a transparent, flexible, and sensitive electronic skin device. The electronic skin device shows highly sensitive piezo-capacitance response to pressure. It is found that micropatterning the surface of dielectric layer polyurethane elastomer by replicating from microstructures of natural-existing surfaces such as lotus leaf, silk, and frosted glass can greatly enhance the piezo-capacitance performance of the device. The microstructured pressure sensors based on silver nanowire exhibit good transparency, excellent flexibility, wide pressure detection range (0-150 kPa), and high sensitivity (1.28 kPa^-1).     

In situ NMR diffusion coefficients assessment of lithium ion conductor using electrochemical priors and Arrhenius constraint——A computational study

In situ NMR measurements of the diffusion coefficients,including an estimate of signal strength,of lithium ion conductor using diffusion-weighting pulse sequence are performed in this study.A cascade bilinear model is proposed to estimate the diffusion sensitivity factors of pulsed-field gradient using prior information of the electrochemical performance and Arrhenius constraint.The model postulates that the active lithium nuclei participating electrochemical reaction are relevant to the NMR signal intensity,when discharge rate or temperature condition is varying.The electrochemical data and the NMR signal strength show a highly fit with the proposed model according our simulation and experiments.Furthermore,the diffusion time is constrained by temperature based on Arrhenius equation of reaction rates dependence.An experimental calculation of Li_4Ti_5O_(12)(LTO)/carbon nanotubes(CNTs) with the electrolyte evaluating at 20 ℃ is presented,which the b factor is estimated by the discharge rate.     

基于核酸适配体信号置换结合循环扩增的液相色谱法检测4种生物胺

生物胺的含量是衡量食品卫生状况和药物纯度的重要标志之一,建立食品药品中生物胺的精准、灵敏检测具有重要的实际意义。该文基于核酸适配体置换生物胺信号源并结合荧光信号循环扩增的策略,建立了一种新型的同时检测鱼肉、猪肉和抗生素中4种生物胺的高效液相色谱法(HPLC)。首先通过两步信号置换,将无荧光信号的目标物转换为有荧光信号的核酸探针;再结合双链特异性核酸酶辅助信号扩增策略,获取大量不同长度和碱基序列的核酸探针;最后借助HPLC平台实现实际样品中多种生物胺信号的精确识别。文章研究了核酸探针的碱基序列和长度对出峰时间和前后顺序的影响,以提高荧光信号的区分度。通过正交实验探讨了柱温、流速和梯度洗脱过程、反应温度、孵化时间等对信号分离的影响,确定最优条件,提高信号的分离效率。该方法对目标物酪胺、组胺、精胺和色胺的检出限分别为0.25、0.21、0.27和0.19 pmol/L,线性范围为1 pmol/L~1 μmol/L。通过对硫酸大庆霉素、鱼肉和猪肉样品中生物胺含量进行检测,研究了该方法检测实际样品的可行性。该方法可精准识别、捕获和分离复杂基质样品中的生物胺组分,能有效提高对目标分析物的选择性,并降低实际样品中的基质干扰,有望为食品药品分析领域提供一种新的思路。     

Aptamer-functionalized Ti3C2-MXene Nanosheets with One-step Potentiometric Detection of Programmed Death-ligand 1

This communication describes a simple sensitive one-step potentiometric aptasensing method for quantitative detection of a referenced therapeutic biomarker (programmed death-ligand 1, PD−L1). The aptasensor is constructed by modifying PD−L1-specific aptamer on Ti₃C₂-MXene nanosheets-functionalized electrode. Introduction of PD−L1 induces the specific reaction between PD−L1 and aptamer, thereby resulting in the change of spatial structures. The surface electric potential of modified electrode is shifted upon addition of PD−L1 proteins before and after the reaction of aptamer with the analyte. Interestingly, potentiometric aptamer with Ti₃C₂-MXene nanosheets can achieve a higher sensitivity and a lower detection limit toward target PD−L1 relative to aptamer-modified electrode. Experimental results indicated that the linear range and detection limit of using Ti₃C₂-MXene nanosheets were 0.01–100 ng mL⁻¹ and 7.8 pg mL⁻¹ PD−L1, respectively. Meanwhile, the specificity, reproducibility, storing stability and accuracy of potentiometric aptasensor are acceptable for the screening of PD−L1 in human serum samples.