Uranium Superconductivity Redux

Since the discovery of heavy-fermion superconductivity in uranium compounds in the early 1980s, other uranium compounds have been discovered that are fully as interesting to study. However, as we look forward in the year 2000, we now have higher-purity, single crystals of the element itself. Preliminary resistivity and ac susceptibility measurements show the improved quality of the samples and thus hold the promise of understanding many aspects of its superconductivity, which have remained untouched for almost 25 years.     

产电微生物对SMFC产电及降解性能的影响

目的在以含油污泥为阳极底泥的沉积型微生物燃料电池(SMFC)体系中,通过改变产电微生物种类和分布方式,探究产电微生物对SMFC产电及降解性能的影响。 方法通过采集输出电压、功率密度、表观内阻来检测石油去除率,比较了不同单菌-SMFC、不同混合菌-SMFC的产电性能和降解性能,考查了菌种分布对SMFC性能的影响。 结果在单菌-SMFC中,弗氏柠檬酸杆菌-SMFC的产电及降解性能均优于其他5种单菌构筑的SMFC;混合菌-SMFC的产电及降解性能较单菌-SMFC有较大提升,且其中蜡样芽孢杆菌+中间苍白杆菌-SMFC的产电及降解性能最优,输出电压可达到515.30 mV;菌种分布在阳极材料中和阳极底泥中都可以降解含油污泥中的有机物,但是菌种分布在阳极材料中更有利于SMFC产电性能及降解性能的发挥。 结论混合菌相对于单菌能够显著提升SMFC的产电及降解性能,而且菌种分布在阳极材料中更有益于SMFC产电性能及降解性能的发挥。      

Structural Insights into Iron Ions Accumulation in Dps Nanocage

Dps (DNA-binding protein from starved cells) is well known for the structural protection of bacterial DNA by the formation of highly ordered intracellular assemblies under stress conditions. Moreover, this ferritin-like protein can perform fast oxidation of ferrous ions and subsequently accumulate clusters of ferric ions in its nanocages, thus providing the bacterium with physical and chemical protection. Here, cryo-electron microscopy was used to study the accumulation of iron ions in the nanocage of a Dps protein from Escherichia coli. We demonstrate that Fe²⁺ concentration in the solution and incubation time have an insignificant effect on the volume and the morphology of iron minerals formed in Dps nanocages. However, an increase in the Fe²⁺ level leads to an increase in the proportion of larger clusters and the clusters themselves are composed of discrete ~1–1.5 nm subunits.     

基于属性变化的增量关联规则挖掘

关联规则的挖掘是数据挖掘研究中的一个重要课题,目前已经提出了许多用于发现海量事务库中关联规则的算法以及更新已经发现的关联规则的算法。但是在关联规则的更新算法中,都是基于支持度变化和事务库变化的研究,目前没有人研究当事务库中的属性发生变化时,如何高效地更新关联规则的问题。针对这种情况,提出了三种基于属性变化的增量关联规则挖掘算法ACA+（Attribute Change Algorithm）和ACA-（ACA1-）,从而解决了该问题。     

基于“双芯”51内核的学习机设计

嵌入式系统在教育领域的应用产生了各种类型的学习机,重点论述了一种基于M CS-51内核的“双芯”的嵌入式学习机系统,满足了职业学校学生录入练习的需求。通过对这个系统的分析和论述提出一种在51内核上运行复杂系统的方法。     

施威德勒型单层球面网壳结构抗火的非线性有限元分析

根据ISO-834标准升温曲线与结构钢强度和刚度随温度的变化曲线,采用非线性有限元法对不同的矢跨比的施威德勒型单层球面网壳结构进行了抗火分析,得到了一些结果,可为经济、科学的结构综合防火设计提供理论依据.     

Genetic LGALS1 Variants Are Associated with Heterogeneity in Galectin-1 Serum Levels in Patients with Early Arthritis

Galectin 1 (Gal1) exerts immunomodulatory effects leading to therapeutic effects in autoimmune animal models. Patients with rheumatoid arthritis have been reported to show higher Gal1 serum levels than the healthy population. Our study aimed to find genetic variants on the Gal1 gene (LGALS1) modulating its expression and/or clinical features in patients with early arthritis (EA). LGALS1 was sequenced in 53 EA patients to characterize all genetic variants. Then, we genotyped rs9622682, rs929039, and rs4820293, which covered the main genetic variation in LGALS1, in 532 EA patients. Gal1 and IL-6 serum levels were measured by ELISA and Gal1 also by western blot (WB) in lymphocytes from patients with specific genotypes. Once disease activity improved with treatment, patients with at least one copy of the minor allele in rs9622682 and rs929039 or those with GG genotype in rs4820293 showed significantly higher Gal1 serum levels (p < 0.05). These genotypic combinations were also associated with higher Gal1 expression in lymphocytes by WB and lower IL-6 serum levels in EA patients. In summary, our study suggests that genetic variants studied in LGALS1 can explain heterogeneity in Gal1 serum levels showing that patients with higher Gal1 levels have lower serum IL-6 levels.     

基于改进VGG网络的单体热电池X光图像无损检测方法研究

为解决单体热电池生产中出现的安装错误、人工检测耗时耗力的问题,提出一个结合迁移学习和卷积 神 经网络(convolutional neural network,CNN) 的单体热电池缺陷检测模型。首先,对数据集图像进行裁剪、加噪等预处理,以VGG16(visual geometry group 16) 网络作为 模型的骨干架构,在瓶颈层后增添选择性核(selective kernel,SK) 卷积;然后,增添全局平均池化(global average pooling,GAP) 层, 增加Dropout层及添加 L2 正则化等微调操作,得到单体热电池缺陷检测模型Q-VGGNet;最后,在大型公开数据集ImageNet上进 行预训练学习,将获得的权重参数迁移到单体热电池图像识别模型Q-VGGNet上。测试实验表明:6种 网络模型对数据集缺陷图像的总体识别准确率分别达到了98.39%、94.44%、97.27%、96.34%、93.71%、 95.61%,Q-VGGNet网 络模型 对合格图像和 漏装负极、极耳断裂、漏装集流片3种缺陷图像 识别准确率 分别达到了99.6%,95.9%,99.6%和98.4%。检测结果表明:该方法能够更准确、快速地检测热电池缺陷, 拥有良好的缺陷诊断能力,较传统方法提高近3%,为人工检测单体热电池缺陷提供了良好的解决途径。     

Gene Variants Related to Cardiovascular and Pulmonary Diseases May Correlate with Severe Outcome of COVID-19

Background: Severe outcomes of COVID-19 account for up to 15% of all cases. The study aims to check if any gene variants related to cardiovascular (CVD) and pulmonary diseases (PD) are correlated with a severe outcome of COVID-19 in a Polish cohort of COVID-19 patients. Methods: In this study, a subset of 747 samples from unrelated individuals collected across Poland in 2020 and 2021 was used and whole-genome sequencing was performed. Results: The GWAS analysis of SNPs and short indels located in genes related to CVD identified one variant significant in COVID-19 severe outcome in the HADHA gene, while for the PD gene panel, we found two significant variants in the DRC1 gene. In this study, both potentially protective and risk variants were identified, of which variants in the HADHA gene deserve the most attention. Conclusions: This is the first study reporting the association between the HADHA and DRC1 genetic variants and COVID-19 severe outcome based on the cohort WGS analysis. Although all the identified variants are localised in introns, they may be correlated and therefore inherited along with other risk variants, potentially causative to severe outcome of COVID-19 but not discovered yet.