静压循环膨胀挤压后超细/纳米晶粒纯铜管的织构演化与力学各向异性

采用静压循环膨胀挤压工艺(HTCEE)加工超细粒纯铜管,研究了其织构演化和力学各向异性行为。对于超细晶铜（UFG）管,在纵向和周向记录了不同的变形行为和显著的拉伸性能各向异性。研究结果表明HTCEE工艺使材料轴向的屈服强度和极限强度分别提高了3.6倍和1.67倍。同时,这一过程使周向的屈服强度和极限强度分别提高了1.15倍和1.12倍。作为力学各向异性判据的周向极限抗拉强度与轴向极限抗拉强度之比,对于退火粗晶粒和热处理后的UFG管分别为1.7和1.16。因此,结果表明HTCEE过程对力学各向异性有降低作用。此外,HTCEE工艺在两个方向上的延性损失都很低,这是HTCEE工艺的另一个优点。硬度测量显示,周向硬度值略有增加,这与拉伸试验的趋势一致。进行织构分析,以确定晶粒的分布,得到的111极点图证明了织构的演化,并证实了力学性能的各向异性。扫描电镜(SEM)显示,在两个正交方向拉伸试验后,出现了不同的断裂模式。     

Preparation,characterization, and antibacterial activity of γ-irradiated silver nanoparticles in aqueous gelatin

Colloidal silver nanoparticles (Ag-NPs) were obtained through γ-irradiation of aqueous solutions containing AgNO₃ and gelatin as a silver source and stabilizer, respectively. The absorbed dose of γ-irradiation influences the particle diameter of the Ag-NPs, as evidenced from surface plasmon resonance (SPR) and transmission electron microscopy (TEM) images. When the γ-irradiation dose was increased (from 2 to 50 kGy), the mean particle size was decreased continuously as a result of γ-induced Ag-NPs fragmentation. The antibacterial properties of the Ag-NPs were tested against Methicillinresistant Staphylococcus aureus (MRSA) (Gram-positive) and Pseudomonas aeruginosa (P.a) (Gram-negative) bacteria. This approach reveals that the γ-irradiation-mediated method is a promising simple route for synthesizing highly stable Ag-NPs in aqueous solutions with good antibacterial properties for different applications.     

Production planning problem with pricing under random yield: CVaR criterion

In this paper, we address a basic production planning problem with price dependent demand and stochastic yield of production. We use price and target quantity as decision variables to lower the risk of low yield. The value of risk control becomes more important especially for products with short life cycle. This is because, the profit implications of low yield might be unbearable in the short run. We apply Conditional Value at Risk （CVaR） to model the, risk. CVaR measure is a coherent risk measure and thereby having nice conceptual and mathematical underpinnings. It is also widely used in practice. We consider the problem under general demand function and general distribution function of yield and find sufficient conditions under which the problem has a unique local maximum. We also both analytically and numerically analyze the impact of parameter change on the optimal solution. Among our results, we analytically show that with increasing risk aversion, the optimal price increases. This relation is opposite to that of in Newsvendor problem where the uncertainty lies in demand side.     

Application of SSM in tackling problematical situations from academicians’ viewpoints

In recent years, a wide variety of studies have applied soft systems methodology (SSM) to address the complexities of the messy situations. This paper seeks to identify 1) application areas and 2) application levels of the use of SSM in dealing with problematical situations. To do so, 149 articles published between 2000 and 2015 were studied. The findings revealed the application of SSM in new application areas such as sustainable development, knowledge management and project management. The results of this study also indicated that researchers applied SSM at three levels: SSM as a process of inquiry, SSM as an action-oriented methodology, and the hybrid use of SSM. Based on the findings, SSM at the level of a single methodology for bringing out changes has been less welcomed by researchers, but the application levels of inquiry processes and hybrid approaches have been more utilized. This suggests that in the correspondence of SSM with the nature or situation of problems, a sort of incommensurability is witnessed. Factors arising from the nature of the problem, inadequate mastery of the researcher over SSM or the limitations of SSM can exert an influence on this incommensurability.     

CT Brain Image: Abnormalities Recognition and Segmentation

In order to develop an automated segmentation system for Computed Tomography (CT) brain images, a new approach which consists of several unsupervised segmentation techniques was introduced. The system segments the CT brain images into three partitions, i. e., abnormalities, cerebrospinal fluid (CSF), and brain matter. Our approach consists of two phase-segmentation methods. In the first phase segmentation, k-means and fuzzy c-means (FCM) methods were implemented to segment and transform the images into the binary images. Based on the connected component in binary images, a decision tree was employed for the annotation of normal or abnormal regions, In the second phase segmentation, the modified FCM with population-diameter independent (PDI) segmentation was applied to segment the images into CSF and brain matter. The experimental results have shown that our proposed system is feasible and yield satisfactory results.