Heavy Quark Radiative Energy Loss - Applications to RHIC

Heavy quark energy loss in a hot QCD plasma is computed taking into account the competing effects due to suppression of zeroth order gluon radiation bellow the plasma frequency and the enhancement of gluon radiation due to transition energy loss and medium induced Bremsstrahlung. Heavy quark medium induced radiative energy loss is derived to all orders in opacity, $(L/\lambda_g)^n$. Numerical evaluation of the energy loss suggest small suppression of high $p_\perp$ charm quarks, and therefore provide a possible explanation for the null effects observed by PHENIX in the prompt electron spectrum in $Au+Au$ as $\sqrt{s}=130$ and 200 AGeV.Comment: 4 pages, 4 figures, Contributed to 17th International Conference on Ultra Relativistic Nucleus-Nucleus Collisions (Quark Matter 2004), Oakland, California, 11-17 Jan 200

On Finite Noncommutativity in Quantum Field Theory

We consider various modifications of the Weyl-Moyal star-product, in order to obtain a finite range of nonlocality. The basic requirements are to preserve the commutation relations of the coordinates as well as the associativity of the new product. We show that a modification of the differential representation of the Weyl-Moyal star-product by an exponential function of derivatives will not lead to a finite range of nonlocality. We also modify the integral kernel of the star-product introducing a Gaussian damping, but find a nonassociative product which remains infinitely nonlocal. We are therefore led to propose that the Weyl-Moyal product should be modified by a cutoff like function, in order to remove the infinite nonlocality of the product. We provide such a product, but it appears that one has to abandon the possibility of analytic calculation with the new product.Comment: 13 pages, reference adde

Color Diffusion and Conductivity in a Quark-Gluon Plasma

Color diffusion is shown to be an important dissipative property of quark-gluon plasmas that rapidly damps collective color modes. We derive the characteristic color relaxation time scale, $t_c\approx (3\alpha_s T \log(m_E/m_M ))^{-1}$, showing its sensitivity to the ratio of the static color electric and magnetic screening masses. This leads to a surprisingly small color conductivity, $\sigma_c\approx 2 T/\log(m_E/m_M)$, which in fact vanishes in the semi-classical (1-loop) limit.Comment: 11 pages, Columbia University Preprint CU-TP-59

Small-Size Resonant Photoacoustic Cell of Inclined Geometry for Gas Detection

A photoacoustic cell intended for laser detection of trace gases is represented. The cell is adapted so as to enhance the gas-detection performance and, simultaneously, to reduce the cell size. The cell design provides an efficient cancellation of the window background (a parasite response due to absorption of laser beam in the cell windows) and acoustic isolation from the environment for an acoustic resonance of the cell. The useful photoacoustic response from a detected gas, window background and noise are analyzed in demonstration experiments as functions of the modulation frequency for a prototype cell with the internal volume ~ 0.5 cm^3. The minimal detectable absorption for the prototype is estimated to be ~ 1.2 10^{-8} cm^{-1} W Hz^{-1/2}.Comment: 11 pages, 5 figure

Platelet Counts and Postoperative Stroke After Coronary Artery Bypass Grafting Surgery

BACKGROUND: Declining platelet counts may reveal platelet activation and aggregation in a postoperative prothrombotic state. Therefore, we hypothesized that nadir platelet counts after on-pump coronary artery bypass grafting (CABG) surgery are associated with stroke. METHODS: We evaluated 6130 adult CABG surgery patients. Postoperative platelet counts were evaluated as continuous and categorical (mild versus moderate to severe) predictors of stroke. Extended Cox proportional hazard regression analysis with a time-varying covariate for daily minimum postoperative platelet count assessed the association of day-to-day variations in postoperative platelet count with time to stroke. Competing risks proportional hazard regression models examined associations between day-to-day variations in postoperative platelet counts with timing of stroke (early: 0-1 days; delayed: ≥2 days). RESULTS: Median (interquartile range) postoperative nadir platelet counts were 123.0 (98.0-155.0) × 10/L. The incidences of postoperative stroke were 1.09%, 1.50%, and 3.02% for platelet counts >150 × 10/L, 100 to 150 × 10/L, and 150 × 10/L. Importantly, such thrombocytopenia, defined as a time-varying covariate, was significantly associated with delayed (≥2 days after surgery; adjusted HR, 2.83; 95% CI, 1.48-5.41; P= .0017) but not early postoperative stroke. CONCLUSIONS: Our findings suggest an independent association between moderate to severe postoperative thrombocytopenia and postoperative stroke, and timing of stroke after CABG surgery

Testing the Resolving Power of 2-D K^+ K^+ Interferometry

Adopting a procedure previously proposed to quantitatively study two-dimensional pion interferometry, an equivalent 2-D chi^2 analysis was performed to test the resolving power of that method when applied to less favorable conditions, i.e., if no significant contribution from long lived resonances is expected, as in kaon interferometry. For that purpose, use is made of the preliminary E859 K^+ K^+ interferometry data from Si+Au collisions at 14.6 AGeV/c. As expected, less sensitivity is achieved in the present case, although it still is possible to distinguish two distinct decoupling geometries. The present analysis seems to favor scenarios with no resonance formation at the AGS energy range, if the preliminary K^+ K^+ data are confirmed. The possible compatibility of data with zero decoupling proper time interval, conjectured by the 3-D experimental analysis, is also investigated and is ruled out when considering more realistic dynamical models with expanding sources. These results, however, clearly evidence the important influence of the time emission interval on the source effective transverse dimensions. Furthermore, they strongly emphasize that the static Gaussian parameterization, commonly used to fit data, cannot be trusted under more realistic conditions, leading to distorted or even wrong interpretation of the source parameters!Comment: 11 pages, RevTeX, 4 Postscript figures include

Machine Learning to Identify Dialysis Patients at High Death Risk.

IntroductionGiven the high mortality rate within the first year of dialysis initiation, an accurate estimation of postdialysis mortality could help patients and clinicians in decision making about initiation of dialysis. We aimed to use machine learning (ML) by incorporating complex information from electronic health records to predict patients at risk for postdialysis short-term mortality.MethodsThis study was carried out on a contemporary cohort of 27,615 US veterans with incident end-stage renal disease (ESRD). We implemented a random forest method on 49 variables obtained before dialysis transition to predict outcomes of 30-, 90-, 180-, and 365-day all-cause mortality after dialysis initiation.ResultsThe mean (±SD) age of our cohort was 68.7 ± 11.2 years, 98.1% of patients were men, 29.4% were African American, and 71.4% were diabetic. The final random forest model provided C-statistics (95% confidence intervals) of 0.7185 (0.6994-0.7377), 0.7446 (0.7346-0.7546), 0.7504 (0.7425-0.7583), and 0.7488 (0.7421-0.7554) for predicting risk of death within the 4 different time windows. The models showed good internal validity and replicated well in patients with various demographic and clinical characteristics and provided similar or better performance compared with other ML algorithms. Results may not be generalizable to non-veterans. Use of predictors available in electronic medical records has limited the assessment of number of predictors.ConclusionWe implemented and ML-based method to accurately predict short-term postdialysis mortality in patients with incident ESRD. Our models could aid patients and clinicians in better decision making about the best course of action in patients approaching ESRD

A two-layer approach to the coupled coherent states method

In this paper a two-layer scheme is outlined for the coupled coherent states (CCS) method, dubbed two-layer CCS (2L-CCS). The theoretical framework is motivated by that of the multiconfigurational Ehrenfest (MCE) method, where different dynamical descriptions are used for different subsystems of a quantum mechanical system. This leads to a flexible representation of the wavefunction, making the method particularly suited to the study of composite systems. It was tested on a 20-dimensional asymmetric system-bath tunnelling problem, with results compared to a benchmark calculation, as well as existing CCS, MP/SOFT and CI expansion methods. The two-layer method was found to lead to improved short and long term propagation over standard CCS, alongside improved numerical efficiency and parallel scalability. These promising results provide impetus for future development of the method for on-the-fly direct dynamics calculations

Hypoglycemia-Related Hospitalizations and Mortality Among Patients With Diabetes Transitioning to Dialysis.

Rationale & objectiveDiabetic patients with declining kidney function are at heightened risk for hypoglycemia. We sought to determine whether hypoglycemia-related hospitalizations in the interval before dialysis therapy initiation are associated with post-end-stage renal disease (ESRD) mortality among incident patients with ESRD with diabetes.Study designObservational cohort study.Setting & participantsUS veterans from the national Veterans Affairs database with diabetes and chronic kidney disease transitioning to dialysis therapy from October 2007 to September 2011.ExposureHypoglycemia-related hospitalizations during the pre-ESRD period and antidiabetic medication regimens.OutcomeThe outcome of post-ESRD all-cause mortality was evaluated relative to pre-ESRD hypoglycemia. The outcome of pre-ESRD hypoglycemia-related hospitalization was evaluated relative to antidiabetic medication regimens.Analytic approachWe examined whether the occurrence and frequency of pre-ESRD hypoglycemia-related hospitalizations are associated with post-ESRD mortality using Cox regression models adjusted for case-mix covariates. In a subcohort of patients prescribed 0 to 2 oral antidiabetic drugs and/or insulin, we examined the 12 most commonly prescribed antidiabetic medication regimens and risk for pre-ESRD hypoglycemia-related hospitalization using logistic regression models adjusted for case-mix covariates.ResultsAmong 30,156 patients who met eligibility criteria, the occurrence of pre-ESRD hypoglycemia-related hospitalization(s) was associated with higher post-ESRD mortality risk: adjusted HR (aHR), 1.25; 95% CI, 1.17-1.34 (reference group: no hypoglycemia hospitalization). Increasing frequency of hypoglycemia-related hospitalizations was independently associated with incrementally higher mortality risk: aHRs of 1.21 (95% CI, 1.12-1.30), 1.47 (95% CI, 1.19-1.82), and 2.07 (95% CI, 1.46-2.95) for 1, 2, and 3 or more hypoglycemia-related hospitalizations, respectively (reference group: no hypoglycemia hospitalization). Compared with patients who were prescribed neither oral antidiabetic drugs nor insulin, medication regimens that included sulfonylureas and/or insulin were associated with higher risk for hypoglycemia.LimitationsResidual confounding cannot be excluded.ConclusionsAmong incident patients with ESRD with diabetes, a dose-dependent relationship between frequency of pre-ESRD hypoglycemia-related hospitalizations and post-ESRD mortality was observed. Further study of diabetic management strategies that prevent hypoglycemia as patients with chronic kidney disease transition to ESRD are warranted

Parallel iterative solvers for real-time elastic deformations

Physics-based animation of elastic materials allows to simulate dynamic deformable objects such as fabrics, human tissue, hair, etc. Due to their complex inner mechanical behaviour, it is difficult to replicate their motions interactively and accurately at the same time. This course introduces students and practitioners to several parallel iterative techniques to tackle this problem and achieve elastic deformations in real-time. We focus on techniques for applications such as video games and interactive design, with\ua0fixed and small hard time budgets\ua0available for physically-based animation, and where responsiveness and stability are often more important than accuracy, as long as the results are believable. The course focuses on solvers able to fully exploit the computational capabilities of modern GPU architectures, effectively solving systems of hundreds of thousands of nonlinear equations in a matter of few milliseconds. The course introduces the basic concepts concerning physics-based elastic objects, and provide an overview of the different types of numerical solvers available in the literature. Then, we show how some variants of traditional solvers can address real-time animation and assess them in terms of accuracy, robustness and performance. Practical examples are provided throughout the course, in particular how to apply the depicted solvers to Projective Dynamics and Position-based Dynamics, two recent and popular physics models for elastic materials