The Interfacial Interactions of Glycine and Short Glycine Peptides in Model Membrane Systems

The interactions of amino acids and peptides at model membrane interfaces have considerable implications for biological functions, with the ability to act as chemical messengers, hormones, neurotransmitters, and even as antibiotics and anticancer agents. In this study, glycine and the short glycine peptides diglycine, triglycine, and tetraglycine are studied with regards to their interactions at the model membrane interface of Aerosol-OT (AOT) reverse micelles via ¹H NMR spectroscopy, dynamic light scattering (DLS), and Langmuir trough measurements. It was found that with the exception of monomeric glycine, the peptides prefer to associate between the interface and bulk water pool of the reverse micelle. Monomeric glycine, however, resides with the N-terminus in the ordered interstitial water (stern layer) and the C-terminus located in the bulk water pool of the reverse micelle.     

Physiochemical structure of semicoke derived from co-carbonization of coal and sawdust blends

The substitution of coal blending with sawdust had been widely investigated for metallurgical coke production. In this paper, the physiochemical structures of the semicoke derived from sawdust/coals blends co-coking were characterized by several analytical techniques including FTIR-ATR, XPS, NMR, OM, and SEM. Meanwhile, the influence of the sawdust on the physicochemical properties of the sawdust/coals blends were also investigated. Results indicated that partial substitution of coal blending with sawdust benefited from the formation of colloid and optical anisotropy due to the positive synergetic effect, whereas high proportion of sawdust (>10 wt%) inhibited the agglomeration of semi-coke. On the other hand, the semicoke consisted primarily of aromatic carbons replaced by the oxygen linked to carbons and aliphatic carbons when the coal blending was replaced by high proportion of sawdust, causing a less polyaromatic graphite-like structure formation in the semicoke.     

基于多通道的ICU脑血管疾病死亡风险预测模型

死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患，通过死亡风险预测可以有针对性地对病人做出临床诊断，以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表，针对ICU病人临床监测的17项生理参数，提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型，用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库，从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究，除了六组超参数实验之外，将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归（logistic regression）和支持向量机（support vector machine, SVM）四种模型进行了对比分析，准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标，实验结果表明，所提模型性能优于其他模型，AUC值达到94.3%。     

改进的CAGAN在虚拟试衣中的应用

针对CAGAN（Conditional Analogy GAN）换衣后效果模糊，在目标衣服与原始衣服长短不一致时效果一般，相对目标衣服保留过少的细节等问题做了相关研究并对CAGAN进行了改进，提出了新的虚拟试衣方式。经过改进的CAGAN生成一个粗糙的结果，由该结果得到目标衣服穿在模特身上改变形状后的mask，接下来利用mask对目标衣服进行变形，综合变形的衣服和第一步的结果便得到最终的试衣图像。实验结果表明，该方法解决了前面存在的问题，而且取得了非常好的效果。     

改性聚乳酸发泡技术研究进展

综述了近几年国内外改性聚乳酸（PLA）发泡技术的研究进展，针对PLA在发泡方面熔体强度和结晶性能的不足，介绍了通过加入扩链剂、交联剂、成核剂、纤维和其他聚合物等物质来改善PLA发泡性能的方法、效果和机理；最后，对改性聚乳酸发泡技术的未来发展进行了展望。     

Structure and crystallization behavior of complex mold flux glasses in the system CaO-Na2O-Li2O-CaF2-B2O3-SiO2: A multi-nuclear NMR spectroscopic study

The structure of mold flux glasses in the system CaO-(Na,Li)₂O-SiO₂-CaF₂ with unusually high modifier contents, stabilized by the addition of ∼4 mol% B₂O₃, is studied using ⁷Li, ²³Na, ¹⁹F, ¹¹B, and ²⁹Si magic-angle-spinning (MAS), and ⁷Li{¹⁹F} and ²³Na{¹⁹F} rotational echo double-resonance (REDOR) nuclear magnetic resonance (NMR) spectroscopy. When taken together, the spectroscopic results indicate that the structure of these glasses consists primarily of dimeric [Si₂O₇]⁻⁶ units that are linked to the (Ca,Na,Li)-O coordination polyhedra, and are interspersed with chains of corner-shared BO₃ units. The F atoms in the structure are exclusively bonded to Ca atoms, forming Ca(O,F)_n coordination polyhedra. This structural scenario is shown to be consistent with the crystallization of cuspidine (3CaO·2SiO₂·CaF₂) from the parent melts on slow supercooling. The progressive addition of Li to a Na-containing base composition results in a corresponding increase in the undercooling required for the nucleation of cuspidine in the melt, which is attributed to the frustrated local structure caused by the mixing of alkali ions.     

Proton Nuclear Magnetic Resonance-Based Method for the Quantification of Epoxidized Methyl Oleate

Epoxidized methyl esters (EMO) with their high oxirane ring reactivity, acts as a raw material in the synthesis of various industrial chemicals including polymers, stabilizers, plasticizers, glycols, polyols, carbonyl compounds, biolubricants etc. EMO has been generally quantified by the gas chromatography (GC) and high-performance liquid chromatography (HPLC) techniques. Taking into the account of the limitations of these techniques, two qHNMR-based equations have been proposed for the quantification of EMO in the mixture of EMO and methylesters (MO). The validity of the proposed method was determined using standard mixtures of MO and EMO having different molar concentrations. The developed equations have been applied on the samples of EMO prepared from oleic acid in two-step process viz., esterification followed by epoxidation. The qHNMR-based EMO quantification showed acceptable agreement with the results obtained from HPLC analysis.     

3D Structural Insights into β-Glucans and Their Binding Proteins

β(1,3)-glucans are a component of fungal and plant cell walls. The β-glucan of pathogens is recognized as a non-self-component in the host defense system. Long β-glucan chains are capable of forming a triple helix structure, and the tertiary structure may profoundly affect the interaction with β-glucan-binding proteins. Although the atomic details of β-glucan binding and signaling of cognate receptors remain mostly unclear, X-ray crystallography and NMR analyses have revealed some aspects of β-glucan structure and interaction. Here, we will review three-dimensional (3D) structural characteristics of β-glucans and the modes of interaction with β-glucan-binding proteins.     

变分自编码器模型综述

变分自编码器（VAE）作为深度隐空间生成模型的一种，近年来其表现性能取得了极大的成功，尤其是在图像生成方面。变分自编码器模型作为无监督式特征学习的重要工具之一，可以通过学习隐编码空间与数据生成空间的特征映射，进而在输出端重构生成输入数据。梳理了传统变分自编码器模型及其衍生变体模型的发展与研究现状，并就此做了总结和对比，最后分析了变分自编码器模型存在的问题与挑战，并就可能的发展趋势做了展望。