The effects of washing a collagen sample prior to TEM examination

Transmission electron microscopy (TEM) is an important analysis technique to visualize (bio)macromolecules and their assemblies, including collagen fibers. Many protocols for TEM sample preparation of collagen involve one or more washing steps to remove excess salts from the dispersion that could hamper analysis when dried on a TEM grid. Such protocols are not standardized and washing times as well as washing solvents vary from procedure to procedure, with each research group typically having their own protocol. Here, we investigate the influence of washing with water, ethanol, but also methanol and 2-propanol, for both mineralized and unmineralized collagen samples via a protocol based on centrifugation. Washing with water maintains the hydrated collagen structure and the characteristic banding pattern can be clearly observed. Conversely, washing with ethanol results in dehydration of the fibrils, often leading to aggregation of the fibers and a less obvious banding pattern, already within 1 min of ethanol exposure. As we show, this process is fully reversible. Similar observations were made for methanol and propanol. Based on these results, a standardized washing protocol for collagenous samples is proposed.     

Machine fault diagnosis with small sample based on variational information constrained generative adversarial network

In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches.     

生物预处理技术在天然产物提取中的应用研究进展

生物预处理技术运用于天然产物提取是借助微生物或生物酶的作用，在适当条件下对天然资源进行处理，破坏植物原料的细胞壁，促进天然产物释放到提取介质中，以提高分离效率，有助于保证天然产物活性。生物预处理技术按形式可以分为微生物发酵技术和生物酶处理技术。针对2种生物预处理技术的作用机制和应用进行综述，旨在为天然产物开发利用提供参考。     

Insights into biological delignification of rice straw by Trametes hirsuta and Myrothecium roridum and comparison of saccharification yields with dilute acid pretreatment

Rice straw is the most abundant agricultural residue on a global scale and is widely available as feedstock for cellulosic fuel production. However, it is highly recalcitrant to biochemical deconstruction and also generates inhibitors that affect enzymatic saccharification. Rice straw from eastern Arkansas was subjected to dilute acid pretreatment (160 °C, 48 min and 1.0% sulfuric acid) and solid-state fermentation with two lignocellulolytic fungi, Trametes hirsuta and Myrothecium roridum, and their saccharification efficacies were compared. T. hirsuta and M. roridum were tested separately; pretreatment of rice straw with either strain for seven days resulted in 19 and 70% enrichment of its holocellulose content, respectively. However, liquid chromatography analysis of the alkali extracts showed significant differences in cell wall degradation by T. hirsuta and M. roridum. T. hirsuta removed 15% more phenolic compounds and 38% more glucan than M. roridum, while M. roridum removed 77% more xylan than T. hirsuta. Fungal and dilute acid pretreated biomass was then hydrolyzed using Accellerase^® 1500, a saccharification cocktail. Saccharification efficiency of M. roridum was 37% higher than that of dilute acid pretreatment of rice straw, requiring 8% lower enzyme loading and 50% shorter enzymatic hydrolysis duration. Alkali extraction of fungal pretreated biomass also yielded 10–15 g kg⁻¹ of acid precipitable polymeric lignin (APPL), which is a valuable co-product for biorefineries. In comparison to dilute acid pretreatment, fungal pretreatment could be a cost-effective alternative for the degradation of recalcitrant biomass, such as rice straw.     

不同制样方法对直流辉光放电质谱法测定氮化硼中27种杂质元素的影响

讨论了3种制样方法对直流辉光放电质谱法(dc-GDMS)检测氮化硼中的Na、Mg、Al、Si等27种杂质元素的影响。3种制样方法分别如下所示:方法1,直接把氮化硼压在铟薄片上;方法2,把氮化硼压在铟薄片上后,再盖上一层铟罩;方法3,把压碎后的氮化硼放在针状钽勺上。在优化的辉光放电参数下对比了3种不同制样方法对基体信号强度的影响。试验表明:在方法1中,当氮化硼尺寸约为3mm×3mm,厚度小于1mm时,基体¹¹B的信号可达1.8×10⁷ cps;在方法2中,选择铟孔大小合适的铟罩,基体¹¹B的信号可达1.0×10⁷ cps;方法3获得基体信号强度比方法1、方法2高一个数量级。大部分元素在中分辨率下可获得较好的结果,而对于在高分辨率下也较难分离的元素,可选择丰度较低的同位素在中分辨率下进行测定,如Ge选择⁷⁰Ge⁺,Se选择⁸²Se⁺,Cd选择¹¹¹Cd⁺,Sn选择¹¹⁹Sn⁺,Ag选择¹⁰⁹Ag⁺,Pt选择¹⁹⁴Pt⁺。氮化硼中的杂质元素含量可通过样品片中待测元素含量减去来自于铟薄片或钽勺中该元素贡献的含量来计算获得。将样品平行测定5次,相对标准偏差均在20%以内。对于Al、Si、Ti等元素的测定,3种制样方法的测定结果基本一致;方法1、方法2中检测到的In含量较大,使得铟中的Ni、Cu对氮化硼的测定值影响较大;方法3由于钽中Fe、Cu的贡献导致氮化硼中Fe、Cu的检测值较大,但方法3获得的基体信号强度大,可降低部分元素的检出限,如Cr、Mn、Ga、Ge等。综上所述,方法3为优选方法。     

硫化物预处理方法研究及测定中的质量保证

针对水和废水中硫离子的特点,设计制作了测定硫化物的酸化—吹气—吸收预处理装置,并验证了该装置对硫化物的回收效果,简化了原来的预处理方法。总结分光测定过程中注意的若干事项,确定了最佳实验条件,使该方法具有更准确、简便、快速的特点。     

对空监视雷达探测威力检飞的几个问题

以新的观点论证了对空监视雷达探测威力检验飞行中所需的采样点数和飞行架次，讨论了预警机雷达威力检飞的特殊问题，包括地区选择、航线设计和目标机标定等。     

基于自适应加权Fisherface算法的人脸识别

提出了一种改进的Fisherface算法。算法首先利用Karhunen-Loeve（K-L）变换降维，在降维的子空间内，根据样本与同类样本间的距离赋予该样本一权值，再用加权后的样本求取类均值，以新的类均值重建类内散布矩阵和类间散布矩阵，从而改进Fisher判别函数。在ORL和Yale人脸库上的实验结果表明，该算法优于传统的主成分分析（PCA）方法和Fisherface方法，并能有效解决小样本情况下训练样本类均值偏离类中心的问题。