从知识传授到育人:高职“生活中的化学”教学实践*

深挖高职院校公选课“生活中的化学”的育人元素,精心设计教学内容,运用课堂主题辩论、趣味生活实验的设计与展示、探秘生活中的化学等理论知识传授与课内外实践相结合的教学方式,实现全过程育人,充分展现了公选课在立德树人方面的价值。     

Regularity of optimal sets for some functional involving eigenvalues of an operator in divergence form

In this paper we consider minimizers of the functional$\min \{{\lambda }_1(\mathrm{\Omega })+\cdots +{\lambda }_k(\mathrm{\Omega })+\mathrm{\Lambda }|\mathrm{\Omega }|,:\mathrm{\Omega }\subset D\text{ open}\}$ where $D\subset {\mathbb{R}}^d$ is a bounded open set and where $0<{\lambda }_1(\mathrm{\Omega })\le \cdots \le {\lambda }_k(\mathrm{\Omega })$ are the first k eigenvalues on Ω of an operator in divergence form with Dirichlet boundary condition and with Hölder continuous coefficients. We prove that the optimal sets ${\mathrm{\Omega }}^{⁎}$ have finite perimeter and that their free boundary $\partial {\mathrm{\Omega }}^{⁎}\cap D$ is composed of a regular part, which is locally the graph of a $C^{1,\alpha }$-regular function, and a singular part, which is empty if $d<d^{⁎}$, discrete if $d=d^{⁎}$ and of Hausdorff dimension at most $d-d^{⁎}$ if $d>d^{⁎}$, for some $d^{⁎}\in \{5,6,7\}$.     

游客情感计算的文本大数据挖掘方法比较研究

旅游文本大数据以其方便、快捷和低门槛的特点为游客情感计算提供了极大便利，已经成为旅游大数据的主要来源之一。基于大数据理论和情感理论，以文本大数据为数据源，在全面梳理国内外情感计算相关成果的基础上，利用人工智能中的逻辑/算法编程方法、机器学习方法、深度学习方法对旅游文本大数据进行挖掘，探索最佳的基于文本大数据的游客情感计算方法。研究发现：（1）基于情感词典的游客情感计算模型，其核心是构建情感词典和设计情感计算规则，方法简单，容易实现，适用语料范围广。（2）机器学习，用统计学方法抽取文本中的特征项，具有非线性特征，可靠性较线性特征的情感词典方法高。（3）基于深度学习技术的游客情感计算，效果良好，准确率在85%以上。训练多领域的文本语料易于移植，实用性强，且泛化能力好，较适合大数据时代游客情感计算研究。     

A Far-Red Emitting Fluorescent Chemogenetic Reporter for In Vivo Molecular Imaging

Far-red emitting fluorescent labels are highly desirable for spectral multiplexing and deep tissue imaging. Here, we describe the generation of frFAST (far-red Fluorescence Activating and absorption Shifting Tag), a 14-kDa monomeric protein that forms a bright far-red fluorescent assembly with (4-hydroxy-3-methoxy-phenyl)allylidene rhodanine (HPAR-3OM). As HPAR-3OM is essentially non-fluorescent in solution and in cells, frFAST can be imaged with high contrast in presence of free HPAR-3OM, which allowed the rapid and efficient imaging of frFAST fusions in live cells, zebrafish embryo/larvae, and chicken embryos. Beyond enabling the genetic encoding of far-red fluorescence, frFAST allowed the design of a far-red chemogenetic reporter of protein–protein interactions, demonstrating its great potential for the design of innovative far-red emitting biosensors.     

Molecular design of ambipolar redox-active molecules II: closed-shell systems

This mini-review highlights key structural features that should be taken into account when creating ambipolar redox-active closed-shell metal-free molecules. This type of compound is strongly required for the fabrication of all-organic ‘poleless’ batteries and semiconductors. The suggested strategies aimed at stabilization of both oxidized (cationic) and reduced (anionic) redox-states are based on the comprehensive analysis of the most successful structures taken from the recent publications.     

煤直接液化油中混合酚的分离研究

利用分子筛择形特点，对煤直接液化油中的混合酚实施高效分离。本研究选取间甲酚和对甲酚作为分离煤直接液化油馏分段混合酚的模型化合物，采用化学液相沉积法对HZSM-5吸附剂的孔口结构进行改变，分析分子筛硅铝比及颗粒粒径对模型化合物间甲酚和对甲酚吸附分离性能的影响，以获得高性能固相吸附剂，并将其应用于180-190℃馏分段混合酚分离。结果表明，当分子筛硅铝比为25、粒径为3-5 μm时，分子筛的孔口结构调节效果最优；当正硅酸乙酯的最小用量为0.2 mL/g时，固相吸附剂的吸附量为0.03 g/g，对甲酚选择性高于95%。由于外表面沉积物对吸附剂的孔口结构变化，导致对甲酚选择性的提高。进一步采用HZSM-5（1）吸附剂对真实煤直接液化油混合酚的分离中发现，苯酚和对甲酚的选择性均达到100%。     

Computational Design of Novel Allosteric Inhibitors for Plasmodium falciparum DegP

The serine protease, DegP exhibits proteolytic and chaperone activities, essential for cellular protein quality control and normal cell development in eukaryotes. The P. falciparum DegP is essential for the parasite survival and required to combat the oscillating thermal stress conditions during the infection, protein quality checks and protein homeostasis in the extra-cytoplasmic compartments, thereby establishing it as a potential target for drug development against malaria. Previous studies have shown that diisopropyl fluorophosphate (DFP) and the peptide SPMFKGV inhibit E. coli DegP protease activity. To identify novel potential inhibitors specific to PfDegP allosteric and the catalytic binding sites, we performed a high throughput in silico screening using Malaria Box, Pathogen Box, Maybridge library, ChEMBL library and the library of FDA approved compounds. The screening helped identify five best binders that showed high affinity to PfDegP allosteric (T0873, T2823, T2801, {"type":"entrez-protein","attrs":{"text":"RJC02337","term_id":"1480409465","term_text":"RJC02337"}}RJC02337, CD00811) and the catalytic binding site (T0078L, T1524, T2328, BTB11534 and 552691). Further, molecular dynamics simulation analysis revealed {"type":"entrez-protein","attrs":{"text":"RJC02337","term_id":"1480409465","term_text":"RJC02337"}}RJC02337, BTB11534 as the best hits forming a stable complex. WaterMap and electrostatic complementarity were used to evaluate the novel bio-isosteric chemotypes of {"type":"entrez-protein","attrs":{"text":"RJC02337","term_id":"1480409465","term_text":"RJC02337"}}RJC02337, that led to the identification of 231 chemotypes that exhibited better binding affinity. Further analysis of the top 5 chemotypes, based on better binding affinity, revealed that the addition of electron donors like nitrogen and sulphur to the side chains of butanoate group are more favoured than the backbone of butanoate group. In a nutshell, the present study helps identify novel, potent and Plasmodium specific inhibitors, using high throughput in silico screening and bio-isosteric replacement, which may be experimentally validated.     

A Structural Entropy Measurement Principle of Propositional Formulas in Conjunctive Normal Form

The satisfiability (SAT) problem is a core problem in computer science. Existing studies have shown that most industrial SAT instances can be effectively solved by modern SAT solvers while random SAT instances cannot. It is believed that the structural characteristics of different SAT formula classes are the reasons behind this difference. In this paper, we study the structural properties of propositional formulas in conjunctive normal form (CNF) by the principle of structural entropy of formulas. First, we used structural entropy to measure the complex structure of a formula and found that the difficulty solving the formula is related to the structural entropy of the formula. The smaller the compressing information of a formula, the more difficult it is to solve the formula. Secondly, we proposed a λ-approximation strategy to approximate the structural entropy of large formulas. The experimental results showed that the proposed strategy can effectively approximate the structural entropy of the original formula and that the approximation ratio is more than 92%. Finally, we analyzed the structural properties of a formula in the solution process and found that a local search solver tends to select variables in different communities to perform the next round of searches during a search and that the structural entropy of a variable affects the probability of the variable being flipped. By using these conclusions, we also proposed an initial candidate solution generation strategy for a local search for SAT, and the experimental results showed that this strategy effectively improves the performance of the solvers CCAsat and Sparrow2011 when incorporated into these two solvers.