Flexible Power Modeling of LTE Base Stations

With the explosion of wireless communications in number of users and data rates, the reduction of network power consumption becomes more and more critical. This is especially true for base stations which represent a dominant share of the total power in cellular networks. In order to study power reduction techniques, a convenient power model is required, providing estimates of the power consumption in different scenarios. This paper proposes such a model, accurate but simple to use. It evaluates the base station power consumption for different types of cells supporting the 3GPP LTE standard. It is flexible enough to enable comparisons between state-of-the-art and advanced configurations, and an easy adaptation to various scenarios. The model is based on a combination of base station components and sub-components as well as power scaling rules as functions of the main system parameters

On the complexity of computing the kk-restricted edge-connectivity of a graph

The \emph{$k$-restricted edge-connectivity} of a graph $G$, denoted by $\lambda_k(G)$, is defined as the minimum size of an edge set whose removal leaves exactly two connected components each containing at least $k$ vertices. This graph invariant, which can be seen as a generalization of a minimum edge-cut, has been extensively studied from a combinatorial point of view. However, very little is known about the complexity of computing $\lambda_k(G)$. Very recently, in the parameterized complexity community the notion of \emph{good edge separation} of a graph has been defined, which happens to be essentially the same as the $k$-restricted edge-connectivity. Motivated by the relevance of this invariant from both combinatorial and algorithmic points of view, in this article we initiate a systematic study of its computational complexity, with special emphasis on its parameterized complexity for several choices of the parameters. We provide a number of NP-hardness and W[1]-hardness results, as well as FPT-algorithms.Comment: 16 pages, 4 figure

The 4q12 Amplicon in Malignant Peripheral Nerve Sheath Tumors: Consequences on Gene Expression and Implications for Sunitinib Treatment

Malignant peripheral nerve sheath tumors (MPNST) are highly aggressive tumors which originate from Schwann cells and develop in about 10% of neurofibromatosis type 1 (NF1) patients. The five year survival rate is poor and more effective therapies are needed. Sunitinib is a drug targeting receptor tyrosine kinases (RTK) like PDGFRα, c-Kit and VEGFR-2. These genes are structurally related and cluster on chromosomal segment 4q12.) was present in MPNST cell lines suggesting an autocrine loop. We show that VEGF triggered signal transduction via the MAPK pathway, which could be blocked by sunitinib. might serve as predictive markers for efficacy of sunitinib

Status of Flat Electron Beam Production

Last year at LINAC2000 [1] we reported our initial verification of the round beam (comparable transverse emittances) to flat beam (high transverse emittance ratio) transformation described by Brinkmann, Derbenev, and Flöttmann [2]. Further analysis of our data has confirmed that a transverse emittance ratio of approximately 50 was observed. Graphics representing observational detail are included here, and future plans outlined

High-gradient normal-conducting RF structures for muon cooling channels

We present a status report on the research and development of high-gradient normal-conducting RF structures for the ionization cooling of muons in a neutrino factory or muon collider. High-gradient RF structures are required in regions enclosed in strong focusing solenoidal magnets, precluding the application of superconducting RF technology [1]. We propose using linear accelerating structures, with individual cells electromagnetically isolated, to achieve the required gradients of over 15 MV/m at 201 MHz and 30 MV/m at 805 MHz. Each cell will be powered independently, and cell length and drive phase adjusted to optimize shunt impedance of the assembled structure. This efficient design allows for relatively small field enhancement on the structure walls, and an accelerating field approximately 1.7 times greater than the peak surface field. The electromagnetic boundary of each cell may be provided by a thin Be sheet, or an assembly of thin-walled metal tubes. Use of thin, low-Z materials will allow passage of the muon beams without significant deterioration in beam quality due to scattering. R and D in design and analysis of robust structures that will operate under large electric and magnetic fields and RF current heating are discussed, including the experimental program based in a high-power test laboratory developed for this purpose

Status of Muon Collider Research and Development and Future Plans

The status of the research on muon colliders is discussed and plans are outlined for future theoretical and experimental studies. Besides continued work on the parameters of a 3-4 and 0.5 TeV center-of-mass (CoM) energy collider, many studies are now concentrating on a machine near 0.1 TeV (CoM) that could be a factory for the s-channel production of Higgs particles. We discuss the research on the various components in such muon colliders, starting from the proton accelerator needed to generate pions from a heavy-Z target and proceeding through the phase rotation and decay ($\pi \to \mu \nu_{\mu}$) channel, muon cooling, acceleration, storage in a collider ring and the collider detector. We also present theoretical and experimental R & D plans for the next several years that should lead to a better understanding of the design and feasibility issues for all of the components. This report is an update of the progress on the R & D since the Feasibility Study of Muon Colliders presented at the Snowmass'96 Workshop [R. B. Palmer, A. Sessler and A. Tollestrup, Proceedings of the 1996 DPF/DPB Summer Study on High-Energy Physics (Stanford Linear Accelerator Center, Menlo Park, CA, 1997)].Comment: 95 pages, 75 figures. Submitted to Physical Review Special Topics, Accelerators and Beam

Gigahertz (GHz) hard x-ray imaging using fast scintillators

Gigahertz (GHz) imaging technology will be needed at high-luminosity X-ray and charged particle sources. It is plausible to combine fast scintillators with the latest picosecond detectors and GHz electronics for multi-frame hard Xray imaging and achieve an inter-frame time of less than 10 ns. The time responses and light yield of LYSO, LaBr_3, BaF_2 and ZnO are measured using an MCP-PMT detector. Zinc Oxide (ZnO) is an attractive material for fast hard X-ray imaging based on GEANT4 simulations and previous studies, but the measured light yield from the samples is much lower than expected

Fat Mass and Obesity-Associated Gene (FTO) in Eating Disorders: Evidence for Association of the rs9939609 Obesity Risk Allele with Bulimia nervosa and Anorexia nervosa

Objective: The common single nucleotide polymorphism (SNP) rs9939609 in the fat mass and obesity-associated gene (FTO) is associated with obesity. As genetic variants associated with weight regulation might also be implicated in the etiology of eating disorders, we evaluated whether SNP rs9939609 is associated with bulimia nervosa (BN) and anorexia nervosa (AN). Methods: Association of rs9939609 with BN and AN was assessed in 689 patients with AN, 477 patients with BN, 984 healthy non-population-based controls, and 3,951 population-based controls (KORA-S4). Based on the familial and premorbid occurrence of obesity in patients with BN, we hypothesized an association of the obesity risk A-allele with BN. Results: In accordance with our hypothesis, we observed evidence for association of the rs9939609 A-allele with BN when compared to the non-population-based controls (unadjusted odds ratio (OR) = 1.142, one-sided 95% confidence interval (CI) 1.001-infinity; one-sided p = 0.049) and a trend in the population-based controls (OR = 1.124, one-sided 95% CI 0.932-infinity; one-sided p = 0.056). Interestingly, compared to both control groups, we further detected a nominal association of the rs9939609 A-allele to AN (OR = 1.181, 95% CI 1.027-1.359, two-sided p = 0.020 or OR = 1.673, 95% CI 1.101-2.541, two-sided p = 0.015,). Conclusion: Our data suggest that the obesity-predisposing FTO allele might be relevant in both AN and BN. Copyright (C) 2012 S. Karger GmbH, Freibur

Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery

<p>Abstract</p> <p>Background</p> <p>Although high-throughput microarray based molecular diagnostic technologies show a great promise in cancer diagnosis, it is still far from a clinical application due to its low and instable sensitivities and specificities in cancer molecular pattern recognition. In fact, high-dimensional and heterogeneous tumor profiles challenge current machine learning methodologies for its small number of samples and large or even huge number of variables (genes). This naturally calls for the use of an effective feature selection in microarray data classification.</p> <p>Methods</p> <p>We propose a novel feature selection method: multi-resolution independent component analysis (MICA) for large-scale gene expression data. This method overcomes the weak points of the widely used transform-based feature selection methods such as principal component analysis (PCA), independent component analysis (ICA), and nonnegative matrix factorization (NMF) by avoiding their global feature-selection mechanism. In addition to demonstrating the effectiveness of the multi-resolution independent component analysis in meaningful biomarker discovery, we present a multi-resolution independent component analysis based support vector machines (MICA-SVM) and linear discriminant analysis (MICA-LDA) to attain high-performance classifications in low-dimensional spaces.</p> <p>Results</p> <p>We have demonstrated the superiority and stability of our algorithms by performing comprehensive experimental comparisons with nine state-of-the-art algorithms on six high-dimensional heterogeneous profiles under cross validations. Our classification algorithms, especially, MICA-SVM, not only accomplish clinical or near-clinical level sensitivities and specificities, but also show strong performance stability over its peers in classification. Software that implements the major algorithm and data sets on which this paper focuses are freely available at <url>https://sites.google.com/site/heyaumapbc2011/</url>.</p> <p>Conclusions</p> <p>This work suggests a new direction to accelerate microarray technologies into a clinical routine through building a high-performance classifier to attain clinical-level sensitivities and specificities by treating an input profile as a ‘profile-biomarker’. The multi-resolution data analysis based redundant global feature suppressing and effective local feature extraction also have a positive impact on large scale ‘omics’ data mining.</p