Simplified model for the evaluation of the effects of explosions on industrial target

The evaluation of vulnerability of process equipment to explosion is a central issue in the analysis of industrial risks. In this work, we have developed a simplified model, however based on fundamental equations, which includes structural and fluid–dynamic parameters for the target (the industrial equipment) and for the impacting pressure wave (shock waves) or object (fragment, debris) produced by different type of chemical explosions.The validity of methodology has been assessed by case histories. Several insights on the dynamic of structural interaction of the explosion with the target have been obtained, with specific reference to escalation effects.The model derives from the well-known Johnson's number, often adopted in impact engineering.     

An Analysis of Spatial Clustering and Implications for Wildlife Management: A Burrowing Owl Example

Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl (Athene cunicularia). We assessed the ability of Ripley’s K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley’s K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses.     

An integrative analysis of miRNA and mRNA expression in the brains of Alzheimer's disease transgenic mice after real-world PM2.5 exposure

Fine particulatematter (PM2.5) is associated with increased risks of Alzheimer’s disease (AD),yet the toxicologicalmechanisms of PM2.5 promoting AD remain unclear. In this study,wildtype and APP/PS1 transgenic mice (AD mice) were exposed to either filtered air (FA) or PM2.5 for eight weeks with a real-world exposure system in Taiyuan, China (mean PM2.5 concentration in the cage was 61 μg/m3). We found that PM2.5 exposure could remarkably aggravate AD mice’s ethological and brain ultrastructural damage, along with the elevation of the pro-inflammatory cytokines (IL-6 and TNF-α), Aβ-42 and AChE levels and the decline of ChAT levels in the brains. Based on high-throughput sequencing results, some differentially expressed (DE) mRNAs and DE miRNAs in the brains of AD mice after PM2.5 exposure were screened.Using RT-qPCR, seven DEmiRNAs (mmu-miR-193b-5p, 122b-5p, 466h-3p, 10b-5p, 1895, 384–5p, and 6412) and six genes (Pcdhgb8, Unc13b, Robo3, Prph, Pter, and Tbata) were evidenced the and verified. Two miRNA-target gene pairs (miR-125b-Pcdhgb8 pair and miR-466h-3p-IL-17Rα/TGF-βR2/Aβ-42/AChE pairs) were demonstrated that they were more related to PM2.5-induced brain injury. Results of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways predicted that synaptic and postsynaptic regulation, axon guidance, Wnt, MAPK, and mTOR pathways might be the possible regulatory mechanisms associated with pathological response. These revealed that PM2.5- elevated pro-inflammatory cytokine levels and PM2.5-altered neurotransmitter levels in AD mice could be the important causes of brain damage and proposed the promising miRNA andmRNA biomarkers and potentialmiRNA-mRNA interaction networks of PM2.5-promoted AD.     

车用高分子材料不同地区户外曝晒试验相关性研究

目的将3种高分子材料以及3种车用外饰材料分别投放在中国海南琼海和美国佛罗里达州2种典型湿热环境中进行户外曝晒试验,研究气候相似的2种地区的试验相关性。方法通过测试相同时间间隔下不同材料在2处试验场曝晒过程中的黄变程度,表征材料的老化现象。采用斯皮尔曼等级相关系数的统计方法,研究材料在2个地区相同时间节点的试验结果的相关性,并利用时间同轴的作图方法比较2个地区严酷度的差异。结果琼海与佛罗里达州2个地区在各个时间节点的相关系数接近于1,且在材料黄变方面呈现一定比例关系。结论琼海和佛罗里达州2个地区的试验结果呈现出较好的相关性,且严酷度比值约为琼海︰佛罗里达=1︰1.19。