Lower bounds for dilation, wirelength, and edge congestion of embedding graphs into hypercubes

Interconnection networks provide an effective mechanism for exchanging data between processors in a parallel computing system. One of the most efficient interconnection networks is the hypercube due to its structural regularity, potential for parallel computation of various algorithms, and the high degree of fault tolerance. Thus it becomes the first choice of topological structure of parallel processing and computing systems. In this paper, lower bounds for the dilation, wirelength, and edge congestion of an embedding of a graph into a hypercube are proved. Two of these bounds are expressed in terms of the bisection width. Applying these results, the dilation and wirelength of embedding of certain complete multipartite graphs, folded hypercubes, wheels, and specific Cartesian products are computed

Analysis of airborne Doppler lidar, Doppler radar and tall tower measurements of atmospheric flows in quiescent and stormy weather

The first experiment to combine airborne Doppler Lidar and ground-based dual Doppler Radar measurements of wind to detail the lower tropospheric flows in quiescent and stormy weather was conducted in central Oklahoma during four days in June-July 1981. Data from these unique remote sensing instruments, coupled with data from conventional in-situ facilities, i.e., 500-m meteorological tower, rawinsonde, and surface based sensors, were analyzed to enhance understanding of wind, waves and turbulence. The purposes of the study were to: (1) compare winds mapped by ground-based dual Doppler radars, airborne Doppler lidar, and anemometers on a tower; (2) compare measured atmospheric boundary layer flow with flows predicted by theoretical models; (3) investigate the kinematic structure of air mass boundaries that precede the development of severe storms; and (4) study the kinematic structure of thunderstorm phenomena (downdrafts, gust fronts, etc.) that produce wind shear and turbulence hazardous to aircraft operations. The report consists of three parts: Part 1, Intercomparison of Wind Data from Airborne Lidar, Ground-Based Radars and Instrumented 444 m Tower; Part 2, The Structure of the Convective Atmospheric Boundary Layer as Revealed by Lidar and Doppler Radars; and Part 3, Doppler Lidar Observations in Thunderstorm Environments

A Case Matched Gender Comparison Transcriptomic Screen Identifies eIF4E and eIF5 as Potential Prognostic and Tractable Biomarkers in Male Breast Cancer

Purpose: Breast cancer (BC) affects both genders, but is understudied in men. Although still rare, male BC is being diagnosed more frequently. Treatments are wholly informed by clinical studies conducted in women, based on assumptions that underlying biology is similar. Experimental design: A transcriptomic investigation of male and female BC was performed, confirming transcriptomic data in silico. Biomarkers were immunohistochemically assessed in 697 MBCs (n=477, training; n=220, validation set) and quantified in pre- and post-treatment samples from a male BC patient receiving Everolimus and PI3K/mTOR inhibitor. Results: Gender-specific gene expression patterns were identified. eIF transcripts were up-regulated in MBC. eIF4E and eIF5 were negatively prognostic for overall survival alone (Log rank; p=0.013; HR=1.77, 1.12-2.8 and p=0.035; HR=1.68, 1.03-2.74, respectively), or when co-expressed (p=0.01; HR=2.66, 1.26-5.63), confirmed in the validation set. This remained upon multivariate Cox regression analysis (eIF4E p=0.016; HR 2.38 (1.18-4.8), eIF5 p=0.022; HR 2.55 (1.14-5.7); co-expression p=0.001; HR=7.04 (2.22-22.26)). Marked reduction in eIF4E and eIF5 expression was seen post BEZ235/Everolimus, with extended survival. Conclusions: Translational initiation pathway inhibition could be of clinical utility in male BC patients overexpressing eIF4E and eIF5. With mTOR inhibitors which target this pathway now in the clinic, these biomarkers may represent new targets for therapeutic intervention, although further independent validation is required

A Brokering Framework for Assessing Legal Risks in Big Data and the Cloud

“Cloud computing” and “Big Data” are amongst the most hyped-up terms and buzzwords of the moment. After decades in which individuals and companies used to host their data and applications using their own IT infrastructure, the world has seen the stunning transformation of the Internet. Major shifts occurred when these infrastructures began to be outsourced to public Cloud providers to match commercial expectations. Storing, sharing and transferring data and databases over the Internet is convenient, yet legal risks cannot be eliminated. Legal risk is a fast-growing area of research and covers various aspects of law. Current studies and research on Cloud computing legal risk assessment have been, however, limited in scope and focused mainly on security and privacy aspects. There is little systematic research on the risks, threats and impact of the legal issues inherent to database rights and “ownership” rights of data. Database rights seem to be outdated and there is a significant gap in the scientific literature when it comes to the understanding of how to apply its provisions in the Big Data era. This means that we need a whole new framework for understanding, protecting and sharing data in the Cloud. The scheme we propose in this chapter is based on a risk assessment-brokering framework that works side by side with Service Level Agreements (SLAs). This proposed framework will provide better control for Cloud users and will go a long way to increase confidence and reinforce trust in Cloud computing transactions