Embedded Fiber Optic Probes to Measure Detonation Velocities Using the Photonic Doppler Velocimeter

Detonation velocities for high explosives can be in the 7 to 8 km/s range. Previous work has shown that these velocities may be measured by inserting an optical fiber probe into the explosive assembly and recording the velocity time history using a Fabry-Perot velocimeter. The measured velocity using this method, however, is the actual velocity multiplied times the refractive index of the fiber core, which is on the order of 1.5. This means that the velocimeter diagnostic must be capable of measuring velocities as high as 12 km/s. Until recently, a velocity of 12 km/s was beyond the maximum velocity limit of a homodyne-based velocimeter. The limiting component in a homodyne system is usually the digitizer. Recently, however, digitizers have come on the market with 20 GHz bandwidth and 50 GS/s sample rate. Such a digitizer coupled with high bandwidth detectors now have the total bandwidth required to make velocity measurements in the 12 km/s range. This paper describes measurements made of detonation velocities using a high bandwidth homodyne system

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

Embedded Fiber Optic Probes to Measure Detonation Velocities Using the PDV

Author Institution: Lawrence Livermore National LaboratoryAuthor Institution: Los Alamos National LaboratorySlides presented at the 5th Annual Photonic Doppler Velocimetry (PDV) Users Conference held at The Ohio State University, Columbus, Ohio, September 8-9, 2010

Free-Surface Optical Scattering as an Indicator of the Shock-Induced Solid-Liquid Phase Transition in Tin

When highly polished metal surfaces melt upon release after shock loading, they exhibit features that suggest significant surface changes accompany the phase transition. The reflection of light from such surfaces changes from specular (pre-shock) to diffuse upon melting. A familiar manifestation of this phenomenon is the loss of signal light in VISAR measurements, which occurs at pressures high enough to melt the free surface. Unlike many other potential material phase-sensitive diagnostics (e.g., reflectometry, conductivity) that show relatively small (1%–10%) changes, the specularity of reflection provides a more sensitive and definitive indication of the solid-liquid phase transition. Data will be presented that support the hypothesis that specularity changes indicate melt in a way that can be measured easily and unambiguously

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

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

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

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