Local cohomology modules and Gorenstein injectivity with respect to a semidualizing module

Let (R,\fm) be a local ring and let $C$ be a semidualizing $R$--module. In this paper, we are concerned in $C$--injective and $G_{C}$--injective dimensions of certain local cohomology modules of $R$. Firstly, the injective dimension of $C$ and the above quantities of dimensions is compared. Then, as an application of the above comparisons, a characterization of a dualizing module of $R$ is given. Finally, it is shown that if $R$ is Cohen-Macaulay of dimension $d$ such that \H_{\fm}^{d}(C) is $C$--injective, then $R$ is Gorernstein. This is an answer to the question which was recently presented.Comment: 9 pages, published in Archive der Mathematik. 100 (2013) 25-3

Vogt-Koyanagi-Harada Syndrome in a 10 Years Old Child

The Vogt-Koyanagi-Harada (VKH) syndrome is a rare systemic disorder of uveitis, dysacousia, vitiligo, premature graying of the hair, eyebrows and eyelashes, and meningoencephalitis. Although frequently unrecognised,VKH may affect children. We report a case of a 10 year old girl who presented with headache and dimness of vision and was diagnosed as papillitis on the basis of bilateral disc edema. However over the course of time developed skin changes (poliosis, vitiligo over lower back) and depigmented patches in inferior fundus suggesting diagnosis of VKH disease. Thus the diagnosis is difficult in the absence of extraocular manifestations. In such cases the diagnosis is based on clinical evolution of the disease

DCDIDP: A distributed, collaborative, and data-driven intrusion detection and prevention framework for cloud computing environments

With the growing popularity of cloud computing, the exploitation of possible vulnerabilities grows at the same pace; the distributed nature of the cloud makes it an attractive target for potential intruders. Despite security issues delaying its adoption, cloud computing has already become an unstoppable force; thus, security mechanisms to ensure its secure adoption are an immediate need. Here, we focus on intrusion detection and prevention systems (IDPSs) to defend against the intruders. In this paper, we propose a Distributed, Collaborative, and Data-driven Intrusion Detection and Prevention system (DCDIDP). Its goal is to make use of the resources in the cloud and provide a holistic IDPS for all cloud service providers which collaborate with other peers in a distributed manner at different architectural levels to respond to attacks. We present the DCDIDP framework, whose infrastructure level is composed of three logical layers: network, host, and global as well as platform and software levels. Then, we review its components and discuss some existing approaches to be used for the modules in our proposed framework. Furthermore, we discuss developing a comprehensive trust management framework to support the establishment and evolution of trust among different cloud service providers. © 2011 ICST

EXPERIMENTAL AND NUMERICAL FAILURE ANALYSIS OF DEEP STEEL COLUMN SECTIONS

The availability of reliable numerical models is essential to reduce the uncertainties present in the prediction of structural behavior. Experimental studies allow the calibration and development of numerical models capable of characterizing the realistic behavior of structural elements and components until the limit state of collapse is approached. Exterior columns in perimeter steel moment-resisting frame structures that are exposed to strong earthquakes experience bending moment demands with high levels of axial load due to overturning. Deep wide flange sections can be used as exterior columns to increase the lateral stiffness of moment frames without significantly increasing the overall weight of the structure. However, experimental data on the cyclic response of deep steel wide flange sections subjected to large drift, rotation, and axial load demands are scarce. To address this need, this research presents results from an experimental program that deals with studying and quantifying the behavior of 1:8 scaled W36X652 column sections exposed to different monotonic and cyclic loading histories consisting of large drift ratios of up to 0.1 rad, rotations at the tip of the column of up to 0.1 rad, and variable levels of axial loads up to 60% (in compression) of the column axial load carrying capacity that vary between tension and compression are used. The experiments consist of quasi-static experiments and hybrid simulations. The influence of member behavior and axial load on the parameters that control the collapse of the structure was studied. Column plastic rotations from 0.012 to 0.08 rad and post-capping rotations from 0.03 to 0.37 rad were observed depending on the loading history and level of axial load. Further, numerical models of the column were calibrated utilizing the experimental results performed in this research. These models can be used for design and performance prediction of deep column section, especially valued in seismic design and assessment