Limitations of the Standard Gravitational Perfect Fluid Paradigm

We show that the standard perfect fluid paradigm is not necessarily a valid description of a curved space steady state gravitational source. Simply by virtue of not being flat, curved space geometries have to possess intrinsic length scales, and such length scales can affect the fluid structure. For modes of wavelength of order or greater than such scales eikonalized geometrical optics cannot apply and rays are not geodesic. Covariantizing thus entails not only the replacing of flat space functions by covariant ones, but also the introduction of intrinsic scales that were absent in flat space. In principle it is thus unreliable to construct the curved space energy-momentum tensor as the covariant generalization of a geodesic-based flat spacetime energy-momentum tensor. By constructing the partition function as an incoherent average over a complete set of modes of a scalar field propagating in a curved space background, we show that for the specific case of a static, spherically symmetric geometry, the steady state energy-momentum tensor that ensues will in general be of the form $T_{\mu\nu}=(\rho+p)U_{\mu}U_{\nu}+pg_{\mu\nu}+\pi_{\mu\nu}$ where the anisotropic $\pi_{\mu\nu}$ is a symmetric, traceless rank two tensor which obeys $U^{\mu}\pi_{\mu\nu}=0$. Such a $\pi_{\mu\nu}$ type term is absent for an incoherently averaged steady state fluid in a spacetime where there are no intrinsic length scales, and in principle would thus be missed in a covariantizing of a flat spacetime $T_{\mu\nu}$. While the significance of such $\pi_{\mu\nu}$ type terms would need to be evaluated on a case by case basis, through the use of kinetic theory we reassuringly find that the effect of such $\pi_{\mu\nu}$ type terms is small for weak gravity stars where perfect fluid sources are commonly used.Comment: Final version to appear in General Relativity and Gravitation (the final publication is available at http://www.springerlink.com). 29 pages, 1 figur

Reply to “Comments on ‘Monitoring and Understanding Trends in Extreme Storms: State of Knowledge’”

We welcome the comments of Landsea (2015, hereafter L15) and we1 applaud his efforts toward reanalyzing past tropical cyclone data in the Atlantic (Landsea et al. 2008, 2012, 2014; Hagen et al. 2012). However, L15 does not substantially change the conclusions stated in Kunkel et al. (2013, hereafter K13). L15 voices two main concerns: 1. The U.S. landfalling hurricane time series considered by K13 is dated. 2. The U.S. landfall record exhibits multidecadal variability that places the changes since 1970 into a larger perspective than K13 provided. Related to this concern, L15 introduces assertions about the relationship between U.S. landfall variability and basinwide North Atlantic variability

Assessing Predictability of Cotton Yields in the Southeastern United States Based on Regional Atmospheric Circulation and Surface Temperatures

The potential to predict cotton yields up to one month before planting in the southeastern United States is assessed in this research. To do this, regional atmospheric variables that are related to historic summer rainfall and cotton yields were identified. The use of simulations of those variables from a global circulation model (GCM) for estimating cotton yields was evaluated. The authors analyzed detrended cotton yields (1970–2004) from 48 counties in Alabama and Georgia, monthly rainfall from 53 weather stations, monthly reanalysis data of 850- and 200-hPa winds and surface temperatures over the southeast U.S. region, and monthly predictions of the same variables from the ECHAM 4.5 GCM. Using the reanalysis climate data, it was found that meridional wind fields and surface temperatures around the Southeast were significantly correlated with county cotton yields (explaining up to 52% of the interannual variability of observed yields), and with rainfall over most of the region, especially during April and July. The tendency for cotton yields to be lower during years with atmospheric circulation patterns that favor higher humidity and rainfall is consistent with increased incidence of disease in cotton during flowering and harvest periods under wet conditions. Cross-validated yield estimations based on ECHAM retrospective simulations of wind and temperature fields forced by observed SSTs showed significant predictability skill (up to 55% and 60% hit skill scores based on terciles and averages, respectively). It is concluded that there is potential to predict cotton yields in the Southeast by using variables that are forecast by numerical climate models

Cis-effects on gene expression in the human prenatal brain associated with genetic risk for neuropsychiatric disorders

The majority of common risk alleles identified for neuropsychiatric disorders reside in non-coding regions of the genome and are therefore likely to impact gene regulation. However, the genes that are primarily affected and the nature and developmental timing of these effects remain unclear. Given the hypothesised role for early neurodevelopmental processes in these conditions, we here define genetic predictors of gene expression in the human fetal brain with which we perform transcriptome-wide association studies (TWASs) of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder, bipolar disorder, major depressive disorder and schizophrenia. We identify prenatal cis-regulatory effects on 63 genes and 166 individual transcripts associated with genetic risk for these conditions. We observe pleiotropic effects of expression predictors for a number of genes and transcripts, including those of decreased DDHD2 expression in association with risk for schizophrenia and bipolar disorder, increased expression of a ST3GAL3 transcript with risk for schizophrenia and ADHD, and increased expression of an XPNPEP3 transcript with risk for schizophrenia, bipolar disorder and major depression. For the protocadherin alpha cluster genes PCDHA7 and PCDHA8, we find that predictors of low expression are associated with risk for major depressive disorder while those of higher expression are associated with risk for schizophrenia. Our findings support a role for altered gene regulation in the prenatal brain in susceptibility to various neuropsychiatric disorders and prioritize potential risk genes for further neurobiological investigation

Re-imagining the data collection and analysis research process by proposing a rapid qualitative data collection and analytic roadmap applied to the dynamic context of precision medicine

Our implementation science study focuses on implementing a new way of practice and offers methodological specificity about how to rapidly investigate an individually tailored precision medicine intervention. A qualitative study advancing a new methodology for speedily identifying barriers and enablers to implementation in the context of childhood cancer. Data were collected through rapid ethnography, coded using the Consolidated Framework for Implementation Research, and analysed by Sentiment Analysis. Thirty-eight data collection events occurred during 14 multidisciplinary tumour board meetings, 14 curation meetings, and 10 informal conversations. Sentiment Analysis distilled Consolidated Framework for Implementation Research codes to reveal key barriers and enablers to implementation. A traffic light labelling system has been used to present levels of positivity and negativity (green for strong enablers and red for strong barriers), highlighting levels of concern regarding implementation. Within the intervention design characteristics, “Adaptability” was the strongest enabler and “Design quality and safety” the strongest barrier. Among the contextual factors: “Networks and communication” were the strongest enabler, and “Available resources” were the strongest barrier. Overall, there was a higher percentage of negative sentiment towards intervention design characteristics and contextual factors than positive sentiment, while more concerns were raised about intervention design factors than contextual factors. This study offers a rapid qualitative data collection and analytic methodological roadmap for establishing barriers and enablers to a paediatric precision medicine intervention

Developing a multidisciplinary syndromic surveillance academic research programme in the United Kingdom: benefits for public health surveillance

Syndromic surveillance is growing in stature internationally as a recognised and innovative approach to public health surveillance. Syndromic surveillance research uses data captured by syndromic surveillance systems to investigate specific hypotheses or questions. However, this research is often undertaken either within established public health organisations or the academic setting, but often not together. Public health organisations can provide access to health-related data and expertise in infectious and non-infectious disease epidemiology and clinical interpretation of data. Academic institutions can optimise methodological rigour, intellectual clarity and establish routes for applying to external research funding bodies to attract money to fund projects. Together, these competencies can complement each other to enhance the public health benefits of syndromic surveillance research. This paper describes the development of a multidisciplinary syndromic surveillance academic research programme in England, United Kingdom, its aims, goals and benefits to public health

Laser Welding of a Stent

We consider the problem of modelling the manufacture of a cylindrical Stent, in which layers of a plastic material are welded together by a Laser beam. We firstly set up the equations for this system and solve them by using a Finite Element method. We then look at various scalings which allow the equations to be simplified. The resulting equations are then solved analytically to obtain approximate solutions to the radial temperature profile and the averaged axial temperature profile

Analysis of Elliptically Polarized Maximally Entangled States for Bell Inequality Tests

When elliptically polarized maximally entangled states are considered, i.e., states having a non random phase factor between the two bipartite polarization components, the standard settings used for optimal violation of Bell inequalities are no longer adapted. One way to retrieve the maximal amount of violation is to compensate for this phase while keeping the standard Bell inequality analysis settings. We propose in this paper a general theoretical approach that allows determining and adjusting the phase of elliptically polarized maximally entangled states in order to optimize the violation of Bell inequalities. The formalism is also applied to several suggested experimental phase compensation schemes. In order to emphasize the simplicity and relevance of our approach, we also describe an experimental implementation using a standard Soleil-Babinet phase compensator. This device is employed to correct the phase that appears in the maximally entangled state generated from a type-II nonlinear photon-pair source after the photons are created and distributed over fiber channels.Comment: 8 page

Disorder-Induced Critical Phenomena in Hysteresis: Numerical Scaling in Three and Higher Dimensions

We present numerical simulations of avalanches and critical phenomena associated with hysteresis loops, modeled using the zero-temperature random-field Ising model. We study the transition between smooth hysteresis loops and loops with a sharp jump in the magnetization, as the disorder in our model is decreased. In a large region near the critical point, we find scaling and critical phenomena, which are well described by the results of an epsilon expansion about six dimensions. We present the results of simulations in 3, 4, and 5 dimensions, with systems with up to a billion spins (1000^3).Comment: Condensed and updated version of cond-mat/9609072,``Disorder-Induced Critical Phenomena in Hysteresis: A Numerical Scaling Analysis'