Visible Light-Driven Alkyne-Grafted Ethylene-Bridged Azobenzene Chromophores for Photothermal Utilization

Molecular photoswitches are considered to be important candidates in the field of solar energy storage due to their sensitive and reversible bidirectional optical response. Nevertheless, it is still a daunting challenge to design a molecular photoswitch to improve the low solar spectrum utilization and quantum yields while achieving charging and discharging of heat without solvent assistance. Herein, a series of visible-light-driven ethylene-bridged azobenzene (b-Azo) chromophores with different alkyne substituents which can undergo isomerization reactions promoted in both directions by visible light are reported. Their visible light responsiveness improves their solar spectrum utilization while also having high quantum yields. In addition, as the compounds are liquids, there is no need to dissolve the compounds in order to exploit this switching. The photoisomerization of b-Azo can be adjusted by alkyne-related substituents, and hexyne-substituted b-Azo is able to store and release photothermal energy with a high density of 106.1 J·g⁻¹, and can achieve a temperature increase of 1.8 °C at a low temperature of −1 °C.     

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.     

蝙蝠喉部发声组织建模及发声机理*

建立蝙蝠发声组织模型对超声机理研究及在智能设备的应用具有重要意义。根据蝙蝠喉部发声组织结构特点,通过有限元方法构建了蝙蝠的3种不同发声组织模型,分析了尺寸、材料力学参数、组织结构和张力4个因素对发声组织特征频率的影响。结果表明,如果用人类声带,按比例缩小构建蝙蝠喉部组织模型,蝙蝠无法发出超声波。构建组织结构含甲状软骨和声带的半鼓状模型和只含声带的条状模型,两种模型的特征频率相近且在合理的参数域内均无法达到超声范围。而含膜条状模型的特征频率可以通过张力进行超声频率的调节,这与文献的实验结果一致。因此,可基于含膜条状模型对蝙蝠喉管发声组织进行建模及其发声机理研究。     

初始溶液中钴铁摩尔比对钴取代Fe3O4中铁的影响

从实际应用的角度出发,研究了初始溶液中钴铁摩尔比对室温下Co2 进入尖晶石结构的速率和程度的影响,过程中的氧化-还原电位和产物的化学分析、XRD以及IR等光谱分析的结果表明:初始溶液中较小的钴铁摩尔比有利于钴铁酸盐的生成.另外,随Co2 进入尖晶石结构,产物的晶面间距和晶格常数增加,红外振动吸收峰向高波数移动.     

Microwave Pyrolysis and Electrochemical Supercapacitor of S-doped g-C_3N_4 Nanoparticles

In this study, S-doped g-C_3N_4 nanoparticles were successfully prepared by one-step solid-state microwave synthesis. The detailed characterizations through XRD, FT-IR, SEM and XPS were studied. In addition, the electrochemical properties as supercapacitor of the sample were tested by cyclic voltammetry(CV), galvanostatic charge-discharge(GCD) and electrochemical impedance spectroscopy(EIS) techniques. The results showed a high specific capacitance of 691 F/g at current density of 4 A/g in 2 M KOH + 0.15 M K_3[Fe(CN)_6] electrolyte. This study shows that the microwave synthesis is a promising way to design carbon-based electrodes for supercapacitor.     

Role of Natural Compounds and Target Enzymes in the Treatment of Alzheimer’s Disease

Alzheimer’s disease (AD) is a progressive neurological condition. The rising prevalence of AD necessitates the rapid development of efficient therapy options. Despite substantial study, only a few medications are capable of delaying the disease. Several substances with pharmacological activity, derived from plants, have been shown to have positive benefits for the treatment of AD by targeting various enzymes, such as acetylcholinesterase (AChE), butyrylcholinesterase (BuChE), β-secretase, γ-secretase, and monoamine oxidases (MAOs), which are discussed as potential targets. Medicinal plants have already contributed a number of lead molecules to medicine development, with many of them currently undergoing clinical trials. A variety of medicinal plants have been shown to diminish the degenerative symptoms associated with AD, either in their raw form or as isolated compounds. The aim of this review was to provide a brief summary of AD and its current therapies, followed by a discussion of the natural compounds examined as therapeutic agents and the processes underlying the positive effects, particularly the management of AD.     

Single-Stage Extraction and Separation of Co2+ from Ni2+ Using Ionic Liquid of [C4H9NH3][Cyanex 272]

The purpose of this study was to optimize the extraction conditions for separating Co²⁺ from Ni²⁺ using N-butylamine phosphinate ionic liquid of [C₄H₉NH₃][Cyanex 272]. A Box–Behnken design of response surface methodology was used to analyze the effects of the initial pH, extraction time, and extraction temperature on the separation factor of Co²⁺ from sulfuric acid solution containing Ni²⁺. The concentrations of Co²⁺ and Ni²⁺ in an aqueous solution were determined using inductively coupled plasma-optical emission spectrometry. The optimized extraction conditions were as follows: an initial pH of 3.7, an extraction time of 55.8 min, and an extraction temperature of 330.4 K. The separation factor of Co²⁺ from Ni²⁺ under optimized extraction conditions was 66.1, which was very close to the predicted value of 67.2, and the error was 1.7%. The equation for single-stage extraction with high reliability can be used for optimizing the multi-stage extraction process of Co²⁺ from Ni²⁺. The stoichiometry of chemical reaction for ion-exchange extraction was also investigated using the slope method.     

两种群随机模型的两种解法

考虑一个具体的关于两个竞争种群的模型,理论推导出两种群的种群期望的微分方程组.利用微分方程法和随机模拟法得到10,20,40 a后两种群的数量概率,分析并比较了微分方程法和随机模拟法得到的稳定性结果与确定性模型中的稳定性结果.     

新丰江水库大坝地震反应专用台阵介绍

对水库诱发地震的监测、预测和大型水利枢纽或大型水电站如何防震减灾是我国政府、水利水电项目的投资者和建设者、地震科技人员一直密切关注的问题。新丰江水库大坝地震反应专用台阵的布设,为大坝抗震设防提供了科学准确的数据资料,在国内水库大坝监测与防震减灾领域具有重要的科学意义。     

油田废水余热发电的可行性分析

分析了某油田废水的特性,提出特油污水热能综合利用的方案,并设计了工艺流程图．结果表明,该工艺不但可以充分利用污水的低温余热,每天产生10．2×104kW·h的电能．该系统还有助于削减二氧化硫和二氧化碳污染物的排放．关于油田废水污水对换热设备造成的腐蚀问题,可将涂层或者镀层应用于金属表面是比较方便和经济的．