Trapping of Projectiles in Fixed Scatterer Calculations

We study multiple scattering off nuclei in the closure approximation. Instead of reducing the dynamics to one particle potential scattering, the scattering amplitude for fixed target configurations is averaged over the target groundstate density via stochastic integration. At low energies a strong coupling limit is found which can not be obtained in a first order optical potential approximation. As its physical explanation, we propose it to be caused by trapping of the projectile. We analyse this phenomenon in mean field and random potential approximations. (PACS: 24.10.-i)Comment: 15 page

More is the Same; Phase Transitions and Mean Field Theories

This paper looks at the early theory of phase transitions. It considers a group of related concepts derived from condensed matter and statistical physics. The key technical ideas here go under the names of "singularity", "order parameter", "mean field theory", and "variational method". In a less technical vein, the question here is how can matter, ordinary matter, support a diversity of forms. We see this diversity each time we observe ice in contact with liquid water or see water vapor, "steam", come up from a pot of heated water. Different phases can be qualitatively different in that walking on ice is well within human capacity, but walking on liquid water is proverbially forbidden to ordinary humans. These differences have been apparent to humankind for millennia, but only brought within the domain of scientific understanding since the 1880s. A phase transition is a change from one behavior to another. A first order phase transition involves a discontinuous jump in a some statistical variable of the system. The discontinuous property is called the order parameter. Each phase transitions has its own order parameter that range over a tremendous variety of physical properties. These properties include the density of a liquid gas transition, the magnetization in a ferromagnet, the size of a connected cluster in a percolation transition, and a condensate wave function in a superfluid or superconductor. A continuous transition occurs when that jump approaches zero. This note is about statistical mechanics and the development of mean field theory as a basis for a partial understanding of this phenomenon.Comment: 25 pages, 6 figure

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Copyright © 2014 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Environmental Modelling and Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environmental Modelling and Software Vol. 62 (2014), DOI: 10.1016/j.envsoft.2014.09.013The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g. model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts

Plasma Metabolomics Implicate Modified Transfer RNAs and Altered Bioenergetics in the Outcome of Pulmonary Arterial Hypertension.

BACKGROUND: -Pulmonary arterial hypertension (PAH) is a heterogeneous disorder with high mortality. METHODS: -We conducted a comprehensive study of plasma metabolites using ultra-performance liquid chromatography mass-spectrometry to (1) identify patients at high risk of early death, (2) identify patients who respond well to treatment and (3) provide novel molecular insights into disease pathogenesis. RESULTS: -53 circulating metabolites distinguished well-phenotyped patients with idiopathic or heritable PAH (n=365) from healthy controls (n=121) following correction for multiple testing (p<7.3e-5) and confounding factors, including drug therapy, renal and hepatic impairment. A subset of 20/53 metabolites also discriminated PAH patients from disease controls (symptomatic patients without pulmonary hypertension, n=139). 62 metabolites were prognostic in PAH, with 36/62 independent of established prognostic markers. Increased levels of tRNA-specific modified nucleosides (N2,N2-dimethylguanosine, N1-methylinosine), TCA cycle intermediates (malate, fumarate), glutamate, fatty acid acylcarnitines, tryptophan and polyamine metabolites and decreased levels of steroids, sphingomyelins and phosphatidylcholines distinguished patients from controls. The largest differences correlated with increased risk of death and correction of several metabolites over time was associated with a better outcome. Patients who responded to calcium channel blocker therapy had metabolic profiles similar to healthy controls. CONCLUSIONS: -Metabolic profiles in PAH are strongly related to survival and should be considered part of the deep phenotypic characterisation of this disease. Our results support the investigation of targeted therapeutic strategies that seek to address the alterations in translational regulation and energy metabolism that characterize these patients

Regulatory T cell DNA methyltransferase inhibition accelerates resolution of lung inflammation

Acute respiratory distress syndrome (ARDS) is a common and often fatal inflammatory lung condition without effective targeted therapies. Regulatory T cells (Tregs) resolve lung inflammation, but mechanisms that enhance Tregs to promote resolution of established damage remain unknown. DNA demethylation at the forkhead box protein 3 (Foxp3) locus and other key Treg loci typify the Treg lineage. To test how dynamic DNA demethylation affects lung injury resolution, we administered the DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine (DAC) to wild-type (WT) mice beginning 24 hours after intratracheal LPS-induced lung injury. Mice that received DAC exhibited accelerated resolution of their injury. Lung CD4+CD25hi Foxp3+ Tregs from D AC-treated WT mice increased in number and displayed enhanced Foxp3 expression, activation state, suppressive phenotype, and proliferative capacity. Lymphocyte-deficient recombinase activating gene-1-null mice and Treg-depleted (diphtheria toxin-treated Foxp3DTR) mice did not resolve their injury in response to DAC. Adoptive transfer of 2 ×105 DAC-treated, but not vehicle-treated, exogenous Tregs rescued Treg-deficient mice from ongoing lung inflammation. In addition, in WT mice with influenza-induced lung inflammation, DAC rescue treatment facilitated recovery of their injury and promoted an increase in lung Treg number. Thus, DNA methyltransferase inhibition, at least in part, augments Treg number and function to accelerate repair of experimental lung injury. Epigenetic pathways represent novel manipulable targets for the treatment of ARDS

Temporal fluctuations of waves in weakly nonlinear disordered media

We consider the multiple scattering of a scalar wave in a disordered medium with a weak nonlinearity of Kerr type. The perturbation theory, developed to calculate the temporal autocorrelation function of scattered wave, fails at short correlation times. A self-consistent calculation shows that for nonlinearities exceeding a certain threshold value, the multiple-scattering speckle pattern becomes unstable and exhibits spontaneous fluctuations even in the absence of scatterer motion. The instability is due to a distributed feedback in the system "coherent wave + nonlinear disordered medium". The feedback is provided by the multiple scattering. The development of instability is independent of the sign of nonlinearity.Comment: RevTeX, 15 pages (including 5 figures), accepted for publication in Phys. Rev.

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Abstract not availableH.R. Maier, Z. Kapelan, Kasprzyk, J. Kollat, L.S. Matott, M.C. Cunha, G.C. Dandy, M.S. Gibbs, E. Keedwell, A. Marchi, A. Ostfeld, D. Savic, D.P. Solomatine, J.A. Vrugt, A.C. Zecchin, B.S. Minsker, E.J. Barbour, G. Kuczera, F. Pasha, A. Castelletti, M. Giuliani, P.M. Ree