Enabling Location-Based Services in Data Centers

In this article, we explore services and capabilities that can be enabled by the localization of various assets in a data center or IT environment. We also describe the underlying location estimation method and the protocol to enable localization. Finally, we present a management framework for these services and present a few case studies to assess benefits of location-based services in data centers

A Simple Algorithm that Adapts one of Two Packet Sizes in a Wireless ARQ Protocol

A recent algorithm of Modiano selects packet sizes in a selective repeat ARQ protocol based on the acknowledgement history of the most recently transmitted packets. In this paper we modify this algorithm so that the choice of packet size is restricted to one of two pre-specified values. We provide a strategy for switching between these packet sizes and show that is optimal in the sense of maximizing the one step efficiency. The throughput efficiency of the proposed adaptive scheme is analyzed for a constant bit-error-rate channel and for two state Gilbert-Elliot channel. The results show that the throughput efficiencies of this scheme under high and moderate bit-error-rates are slightly less than that of Modiano\u27s algorithm. However the scheme is attractive because of its simplicity

Ultra Wideband Channel Characterization and Ranging in Data Centers

This paper presents a detailed measurement based characterization of the Ultra Wideband (UWB) channels in a data center environment and examines the accuracy of direct ranging using Time of Arrival (ToA) measurements. Modern data centers present a unique indoor environment that to our knowledge has not yet been characterized. Our ranging experiments indicate that it is possible to achieve an accuracy of fraction of a meter via direct ranging and point to the feasibility of locating individual servers using more sophisticated cooperative ranging

A Weighted Sum of Gaussian-Derived Pulse Design for UWB

With 7.5 GHz of spectrum, ultra wide band (UWB) is an ideal candidate for achieving high data rates over short distances with low cost and low power consumption. In this paper, we propose a simple pulse design method that uses a linear combination of two Gaussian derivatives to meet the FCC spectral mask requirements. With distance and data rate analysis, it is demonstrated that the proposed pulse design is efficient as compared to previously proposed standard Gaussian monocycles. In quest of making UWB a universal standard, the proposed pulse is shown to satisfy the ETSI proposed UWB spectral requirements

European mtDNA Variants Are Associated With Differential Responses to Cisplatin, an Anticancer Drug: Implications for Drug Resistance and Side Effects.

Background: Cisplatin, a powerful antitumor agent, causes formation of DNA adducts, and activation of apoptotic pathways. Presently, cisplatin resistance develops in up to 70% of patients but the underlying molecular mechanism(s) are unclear and there are no markers to determine which patients will become resistant. Mitochondria play a significant role not only in energy metabolism but also retrograde signaling (mitochondria to nucleus) that modulates inflammation, complement, and apoptosis pathways. Maternally inherited mitochondrial (mt) DNA can be classified into haplogroups representing different ethnic populations that have diverse susceptibilities to diseases and medications. Methods: Transmitochondrial cybrids, where all cell lines possess identical nuclear genomes but either the H (Southern European) or J (Northern European) mtDNA haplogroups, were treated with cisplatin and analyzed for differential responses related to viability, oxidative stress, and expression levels of genes associated with cancer, cisplatin-induced nephrotoxicity and resistance, apoptosis and signaling pathways. Results: The cisplatin-treated-J cybrids showed greater loss of cell viability along with lower levels of reactive oxygen species and mitochondrial membrane potential compared to cisplatin-treated-H cybrids. After cisplatin treatment, J cybrids showed increased gene expression of BAX, CASP3, and CYP51A, but lower levels of SFRP1 compared to untreated-J cybrids. The cisplatin-treated-H cybrids had elevated expression of CDKN1A/P21, which has a role in cisplatin toxicity, compared to untreated-H cybrids. The cisplatin-treated H had higher transcription levels of ABCC1, DHRS2/HEP27, and EFEMP1 compared to cisplatin-treated-J cybrids. Conclusions: Cybrid cell lines that contain identical nuclei but either H mtDNA mitochondria or J mtDNA mitochondria respond differently to cisplatin treatments suggesting involvement of the retrograde signaling (from mitochondria to nucleus) in the drug-induced cell death. Varying toxicities and transcription levels of the H vs. J cybrids after cisplatin treatment support the hypothesis that mtDNA variants play a role in the expression of genes affecting resistance and side effects of cisplatin

Functional Annotation and Identification of Candidate Disease Genes by Computational Analysis of Normal Tissue Gene Expression Data

Background: High-throughput gene expression data can predict gene function through the ‘‘guilt by association’ ’ principle: coexpressed genes are likely to be functionally associated. Methodology/Principal Findings: We analyzed publicly available expression data on normal human tissues. The analysis is based on the integration of data obtained with two experimental platforms (microarrays and SAGE) and of various measures of dissimilarity between expression profiles. The building blocks of the procedure are the Ranked Coexpression Groups (RCG), small sets of tightly coexpressed genes which are analyzed in terms of functional annotation. Functionally characterized RCGs are selected by means of the majority rule and used to predict new functional annotations. Functionally characterized RCGs are enriched in groups of genes associated to similar phenotypes. We exploit this fact to find new candidate disease genes for many OMIM phenotypes of unknown molecular origin. Conclusions/Significance: We predict new functional annotations for many human genes, showing that the integration of different data sets and coexpression measures significantly improves the scope of the results. Combining gene expression data, functional annotation and known phenotype-gene associations we provide candidate genes for several geneti

ATM variants 7271T>G and IVS10-6T>G among women with unilateral and bilateral breast cancer

Recent reports suggest that two ATM gene mutations, 7271T>G and IVS10-6T>G, are associated with a high risk of breast cancer among multiple-case families. To assess the importance of these two mutations in another 'high-risk' group, young women (under age 51) with multiple primaries, we screened a large population-based series of young women with bilateral breast cancer and compared the frequency of these mutations among similar women diagnosed with unilateral breast cancer. The 1149 women included were enrolled in an ongoing population-based case-control study of the genetic factors that contribute to bilateral breast cancer; they were not selected on the basis of family history of cancer. Screening for 7271T>G and IVS10-6T>G ATM gene mutations was conducted using DHPLC followed by direct sequencing. The 7271T>G mutation was detected in one out of 638 (0.2%) women with unilateral breast cancer and in none of the bilateral cases, and the IVS10-6T>G mutation in one out of 511 (0.2%) bilateral and in eight out of 638 (1.3%) unilateral breast cancer cases. Carriers of either mutation were not limited to women with a family history. Given the likelihood that young women with bilateral breast cancer have a genetic predisposition, the observed mutation distribution is contrary to that expected if these two mutations were to play an important role in breast carcinogenesis among individuals at high risk

Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

One of the most limiting aspects of biological research in the post-genomic era is the capability to integrate massive datasets on gene structure and function for producing useful biological knowledge. In this report we have applied an integrative approach to address the problem of identifying likely candidate genes within loci associated with human genetic diseases. Despite the recent progress in sequencing technologies, approaching this problem from an experimental perspective still represents a very demanding task, because the critical region may typically contain hundreds of positional candidates. We found that by concentrating only on genes sharing similar expression profiles in both human and mouse, massive microarray datasets can be used to reliably identify disease-relevant relationships among genes. Moreover, we found that integrating the coexpression criterion with systematic phenome analysis allows efficient identification of disease genes in large genomic regions. Using this approach on 850 OMIM loci characterized by unknown molecular basis, we propose high-probability candidates for 81 genetic diseases