A TEM study on the microstructure of spark plasma sintered ZrB_2-based composite with nano-sized SiC dopant

Sintering behavior of ZrB_2 ceramic with nano-sized SiC dopant was studied. ZrB_2-25 vol% nano-sized SiC was selected as the starting mixture to fabricate the composite. The manufacturing process was accomplished at 1800℃ for 5 min under 25 MPa via spark plasma sintering(SPS). The as-sintered sample reached a relative density of 99%. Besides the initial phases, namely ZrB_2 and SiC, the high-resolution X-ray diffraction(HRXRD) was used to study the formation of an in-situ ZrC phase. The possible chemical interactions during the ZrC phase formation were scrutinized. The microstructure of the composite was studied by the field emission scanning electron microscopy(FESEM) and transmission electron microscopy(TEM). Elemental analysis through FESEM evaluations revealed the formation of amorphous phases, rich in Zr, C, Si, B, and O elements, which was in harmony with the thermodynamical assessments. TEM studies endorsed the formation of such phases, containing a glassy bed of Si–B–O with ZrC and C islands dispersed therein.     

The Study of the Grit-blasting Parameters and Their Effects on the Adhesive Strength of the Plasma Sprayed Coatings

Surface Preparation is very important in adhesive b on ding of spray coatings to the surface of a work piece. The common practice is gr it-blasting of the surface before subjecting it to the spray coating process. In this study, grit-blasting of an AISI 4130 steel (of different heat treatmen ts) with Al 2O 3 particles was studied. Various grit-blasting parameters such as blasting particle size, the distance between blasting nozzle and the work pi ece (25, 30 and 40 cm.), blasting pressure (3,4,5,6 and ...     

Cooperative Sensor Anomaly Detection Using Global Information

Sensor networks are deployed in many application areas nowadays ranging from environment monitoring, industrial monitoring, and agriculture monitoring to military battlefield sensing. The accuracy of sensor readings is without a doubt one of the most important measures to evaluate the quality of a sensor and its network. Therefore, this work is motivated to propose approaches that can detect and repair erroneous (i.e., dirty) data caused by inevitable system problems involving various hardware and software components of sensor networks. As information about a single event of interest in a sensor network is usually reflected in multiple measurement points, the inconsistency among multiple sensor measurements serves as an indicator for data quality problem. The focus of this paper is thus to study methods that can effectively detect and identify erroneous data among inconsistent observations based on the inherent structure of various sensor measurement series from a group of sensors. Particularly, we present three models to characterize the inherent data structures among sensor measurement traces and then apply these models individually to guide the error detection of a sensor network. First, we propose a multivariate Gaussian model which explores the correlated data changes of a group of sensors. Second, we present a Principal Component Analysis (PCA) model which captures the sparse geometric relationship among sensors in a network. The PCA model is motivated by the fact that not all sensor networks have clustered sensor deployment and clear data correlation structure. Further, if the sensor data show non-linear characteristic, a traditional PCA model can not capture the data attributes properly. Therefore, we propose a third model which utilizes kernel functions to map the original data into a high dimensional feature space and then apply PCA model on the mapped linearized data. All these three models serve the purpose of capturing the underlying phenomenon of a sensor network from its global view, and then guide the error detection to discover any anomaly observations. We conducted simulations for each of the proposed models, and evaluated the performance by deriving the Receiver Operating Characteristic (ROC) curves.     

硬脂酸改性处理TC4钛合金微弧氧化膜层耐蚀性的研究

在Ti₆Al₄V合金微弧氧化膜层上采用硬脂酸改性处理实现了陶瓷膜层的疏水化转变，显著提高了钛合金的耐蚀性能。利用接触角测试仪、扫描电子显微镜（SEM）、能谱仪（EDS）和傅里叶变换红外光谱仪（FT-IR）对膜层的润湿性、稳定性、微观结构和化学组成进行了分析，并通过动电位极化曲线和电化学阻抗分析了其腐蚀行为。结果表明，改性处理得到的疏水微弧氧化膜层试样能有效修复微弧氧化膜层缺陷，提高钛合金的耐蚀性能，说明硬脂酸改性处理与微弧氧化技术相结合有助于拓宽微弧氧化技术在钛合金上的应用。     

Dicer generates a regulatory microRNA network in smooth muscle cells that limits neointima formation during vascular repair

MicroRNAs (miRNAs) coordinate vascular repair by regulating injury-induced gene expression in vascular smooth muscle cells (SMCs) and promote the transition of SMCs from a contractile to a proliferating phenotype. However, the effect of miRNA expression in SMCs on neointima formation is unclear. Therefore, we studied the role of miRNA biogenesis by Dicer in SMCs in vascular repair. Following wire-induced injury to carotid arteries of Apolipoprotein E knockout (Apoe ^?/?) mice, miRNA microarray analysis revealed that the most significantly regulated miRNAs, such as miR-222 and miR-21-3p, were upregulated. Conditional deletion of Dicer in SMCs increased neointima formation by reducing SMC proliferation in Apoe ^?/? mice, and decreased mainly the expression of miRNAs, such as miR-147 and miR-100, which were not upregulated following vascular injury. SMC-specific deletion of Dicer promoted growth factor and inflammatory signaling and regulated a miRNA–target interaction network in injured arteries that was enriched in anti-proliferative miRNAs. The most connected miRNA in this network was miR-27a-3p [e.g., with Rho guanine nucleotide exchange factor 26 (ARHGEF26)], which was expressed in medial and neointimal SMCs in a Dicer-dependent manner. In vitro, miR-27a-3p suppresses ARHGEF26 expression and inhibits SMC proliferation by interacting with a conserved binding site in the 3′ untranslated region of ARHGEF26 mRNA. We propose that Dicer expression in SMCs plays an essential role in vascular repair by generating anti-proliferative miRNAs, such as miR-27a-3p, to prevent vessel stenosis due to exaggerated neointima formation.     

Earliest date for milk use in the Near East and southeastern Europe linked to cattle herding

The domestication of cattle, sheep and goats had already taken place in the Near East by the eighth millennium bc. Although there would have been considerable economic and nutritional gains from using these animals for their milk and other products from living animals-that is, traction and wool-the first clear evidence for these appears much later, from the late fifth and fourth millennia bc. Hence, the timing and region in which milking was first practised remain unknown. Organic residues preserved in archaeological pottery have provided direct evidence for the use of milk in the fourth millennium in Britain, and in the sixth millennium in eastern Europe, based on the delta(13)C values of the major fatty acids of milk fat. Here we apply this approach to more than 2,200 pottery vessels from sites in the Near East and southeastern Europe dating from the fifth to the seventh millennia bc. We show that milk was in use by the seventh millennium; this is the earliest direct evidence to date. Milking was particularly important in northwestern Anatolia, pointing to regional differences linked with conditions more favourable to cattle compared to other regions, where sheep and goats were relatively common and milk use less important. The latter is supported by correlations between the fat type and animal bone evidence.