Extending the behavioral immune system to political psychology: Are political conservativism and disgust sensitivity really related

Previous research suggests that several individual and cultural level attitudes, cognitions, and societal structures may have evolved to mitigate the pathogen threats posed by intergroup interactions. It has been suggested that these anti-pathogen defenses are at the root of conservative political ideology. Here, we test a hypothesis that political conservatism functions as a pathogen-avoidance strategy. Across three studies, we consistently find no relationship between sensitivity to pathogen disgust and multiple measures of political conservatism. These results are contrasted with theoretical perspectives suggesting a relationship between conservatism and pathogen avoidance, and with previous findings of a relationship between conservatism and disgust sensitivity

Treatment of Advanced Emphysema with Emphysematous Lung Sealant (AeriSeal (R))

Background: This report summarizes initial tests of an emphysematous lung synthetic polymer sealant (ELS) designed to reduce lung volume in patients with advanced emphysema. Objectives: The primary study objective was to define a therapeutic strategy to optimize treatment safety and effectiveness. Methods: ELS therapy was administered bronchoscopically to 25 patients with heterogeneous emphysema in an open-label, noncontrolled study at 6 centers in Germany. Treatment was performed initially at 2-4 subsegments. After 12 weeks, patients were eligible for repeat therapy to a total of 6 sites. Safety and efficacy were assessed after 6 months. Responses were evaluated in terms of changes from baseline in lung physiology, functional capacity, and health-related quality of life. Follow-up is available for 21 of 25 patients. Results: Treatment was well tolerated. There were no treatment-related deaths (i.e. within 90 days of treatment), and an acceptable short-and long-term safety profile. Physiological and clinical benefits were observed at 24 weeks. Efficacy responses were better among Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage III patients {[}n = 14; change in residual volume/total lung capacity (Delta RV/TLC) = -7.4 +/- 10.3%; Delta forced expiratory volume in 1 s (Delta FEV(1)) = +15.9 +/- 22.6%; change in forced vital capacity (Delta FVC) = +24.1 +/- 22.7%; change in carbon monoxide lung diffusion capacity (Delta DLCO) = +19.3 +/- 34.8%; change in 6-min walk test (Delta 6MWD) = +28.7 +/- 59.6 m; change in Medical Research Council Dyspnea (Delta MRCD) score = -1.0 +/- 1.04 units; change in St. George's Respiratory Questionnaire (Delta SGRQ) score = -9.9 +/- 15.3 units] than for GOLD stage IV patients (n = 7; Delta RV/TLC = -0.5 +/- 6.4%; Delta FEV 1 = +2.3 +/- 12.3%; Delta FVC = +2.6 +/- 21.1%; Delta DLCO = -2.8 +/- 17.2%; Delta 6MWD = +28.3 +/- 58.4 m; Delta MRCD = 0.3 +/- 0.81 units; Delta SGRQ = -6.7 +/- 7.0 units). Conclusions: ELS therapy shows promise for treating patients with advanced heterogeneous emphysema. Additional studies to assess responses in a larger cohort with a longer follow-up are warranted. Copyright (C) 2011 S. Karger AG, Base

The ZEUS Forward Plug Calorimeter with Lead-Scintillator Plates and WLS Fiber Readout

A Forward Plug Calorimeter (FPC) for the ZEUS detector at HERA has been built as a shashlik lead-scintillator calorimeter with wave length shifter fiber readout. Before installation it was tested and calibrated using the X5 test beam facility of the SPS accelerator at CERN. Electron, muon and pion beams in the momentum range of 10 to 100 GeV/c were used. Results of these measurements are presented as well as a calibration monitoring system based on a $^{60}$Co source.Comment: 38 pages (Latex); 26 figures (ps

Real-Time Profiling of Respiratory Motion: Baseline Drift, Frequency Variation and Fundamental Pattern Change

To precisely ablate tumor in radiation therapy, it is important to locate the tumor position in real time during treatment. However, respiration-induced tumor motions are difficult to track. They are semi-periodic and exhibit variations in baseline, frequency and fundamental pattern (oscillatory amplitude and shape). In this study, we try to decompose the above-mentioned components from discrete observations in real time. Baseline drift, frequency (equivalently phase) variation and fundamental pattern change characterize different aspects of respiratory motion and have distinctive clinical indications. Furthermore, smoothness is a valid assumption for each one of these components in their own spaces, and facilitates effective extrapolation for the purpose of estimation and prediction. We call this process 'profiling' to reflect the integration of information extraction, decomposition, processing and recovery. The proposed method has three major ingredients: (1) real-time baseline and phase estimation based on elliptical shape tracking in augmented state space and Poincaré sectioning principle; (2) estimation of the fundamental pattern by unwarping the observation with phase estimate from the previous step; (3) filtering of individual components and assembly in the original temporal-displacement signal space. We tested the proposed method with both simulated and clinical data. For the purpose of prediction, the results are comparable to what one would expect from a human operator. The proposed approach is fully unsupervised and data driven, making it ideal for applications requiring economy, efficiency and flexibility.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85908/1/Fessler14.pd

Large scale cosmic-ray anisotropy with KASCADE

The results of an analysis of the large scale anisotropy of cosmic rays in the PeV range are presented. The Rayleigh formalism is applied to the right ascension distribution of extensive air showers measured by the KASCADE experiment.The data set contains about 10^8 extensive air showers in the energy range from 0.7 to 6 PeV. No hints for anisotropy are visible in the right ascension distributions in this energy range. This accounts for all showers as well as for subsets containing showers induced by predominantly light respectively heavy primary particles. Upper flux limits for Rayleigh amplitudes are determined to be between 10^-3 at 0.7 PeV and 10^-2 at 6 PeV primary energy.Comment: accepted by The Astrophysical Journa

Sparse Matrix-Based HPC Tomography

Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, larger fields of view or higher resolution, so high performance solutions are currently widely used for analysis. Tomographic instruments can vary significantly from one to another, including the hardware employed for reconstruction: from single CPU workstations to large scale hybrid CPU/GPU supercomputers. Flexibility on the software interfaces and reconstruction engines are also highly valued to allow for easy development and prototyping. This paper presents a novel software framework for tomographic analysis that tackles all aforementioned requirements. The proposed solution capitalizes on the increased performance of sparse matrix-vector multiplication and exploits multi-CPU and GPU reconstruction over MPI. The solution is implemented in Python and relies on CuPy for fast GPU operators and CUDA kernel integration, and on SciPy for CPU sparse matrix computation. As opposed to previous tomography solutions that are tailor-made for specific use cases or hardware, the proposed software is designed to provide flexible, portable and high-performance operators that can be used for continuous integration at different production environments, but also for prototyping new experimental settings or for algorithmic development. The experimental results demonstrate how our implementation can even outperform state-of-the-art software packages used at advanced X-ray sources worldwide

Mathematical Properties of a New Levin-Type Sequence Transformation Introduced by \v{C}\'{\i}\v{z}ek, Zamastil, and Sk\'{a}la. I. Algebraic Theory

\v{C}\'{\i}\v{z}ek, Zamastil, and Sk\'{a}la [J. Math. Phys. \textbf{44}, 962 - 968 (2003)] introduced in connection with the summation of the divergent perturbation expansion of the hydrogen atom in an external magnetic field a new sequence transformation which uses as input data not only the elements of a sequence $\{s_n \}_{n=0}^{\infty}$ of partial sums, but also explicit estimates $\{\omega_n \}_{n=0}^{\infty}$ for the truncation errors. The explicit incorporation of the information contained in the truncation error estimates makes this and related transformations potentially much more powerful than for instance Pad\'{e} approximants. Special cases of the new transformation are sequence transformations introduced by Levin [Int. J. Comput. Math. B \textbf{3}, 371 - 388 (1973)] and Weniger [Comput. Phys. Rep. \textbf{10}, 189 - 371 (1989), Sections 7 -9; Numer. Algor. \textbf{3}, 477 - 486 (1992)] and also a variant of Richardson extrapolation [Phil. Trans. Roy. Soc. London A \textbf{226}, 299 - 349 (1927)]. The algebraic theory of these transformations - explicit expressions, recurrence formulas, explicit expressions in the case of special remainder estimates, and asymptotic order estimates satisfied by rational approximants to power series - is formulated in terms of hitherto unknown mathematical properties of the new transformation introduced by \v{C}\'{\i}\v{z}ek, Zamastil, and Sk\'{a}la. This leads to a considerable formal simplification and unification.Comment: 41 + ii pages, LaTeX2e, 0 figures. Submitted to Journal of Mathematical Physic

Theoretical Evaluation of the Detectability of Random Lesions in Bayesian Emission Reconstruction

Detecting cancerous lesion is an important task in positron emission tomography (PET). Bayesian methods based on the maximum a posteriori principle (also called penalized maximum likelihood methods) have been developed to deal with the low signal to noise ratio in the emission data. Similar to the filter cut-off frequency in the filtered backprojection method, the prior parameters in Bayesian reconstruction control the resolution and noise trade-off and hence affect detectability of lesions in reconstructed images. Bayesian reconstructions are difficult to analyze because the resolution and noise properties are nonlinear and object-dependent. Most research has been based on Monte Carlo simulations, which are very time consuming. Building on the recent progress on the theoretical analysis of image properties of statistical reconstructions and the development of numerical observers, here we develop a theoretical approach for fast computation of lesion detectability in Bayesian reconstruction. The results can be used to choose the optimum hyperparameter for the maximum lesion detectability. New in this work is the use of theoretical expressions that explicitly model the statistical variation of the lesion and background without assuming that the object variation is (locally) stationary. The theoretical results are validated using Monte Carlo simulations. The comparisons show good agreement between the theoretical predications and the Monte Carlo results

Metabolic state alters economic decision making under risk in humans

Background: Animals' attitudes to risk are profoundly influenced by metabolic state (hunger and baseline energy stores). Specifically, animals often express a preference for risky (more variable) food sources when below a metabolic reference point (hungry), and safe (less variable) food sources when sated. Circulating hormones report the status of energy reserves and acute nutrient intake to widespread targets in the central nervous system that regulate feeding behaviour, including brain regions strongly implicated in risk and reward based decision-making in humans. Despite this, physiological influences per se have not been considered previously to influence economic decisions in humans. We hypothesised that baseline metabolic reserves and alterations in metabolic state would systematically modulate decision-making and financial risk-taking in humans. Methodology/Principal Findings: We used a controlled feeding manipulation and assayed decision-making preferences across different metabolic states following a meal. To elicit risk-preference, we presented a sequence of 200 paired lotteries, subjects' task being to select their preferred option from each pair. We also measured prandial suppression of circulating acyl-ghrelin (a centrally-acting orexigenic hormone signalling acute nutrient intake), and circulating leptin levels (providing an assay of energy reserves). We show both immediate and delayed effects on risky decision-making following a meal, and that these changes correlate with an individual's baseline leptin and changes in acyl-ghrelin levels respectively. Conclusions/Significance: We show that human risk preferences are exquisitely sensitive to current metabolic state, in a direction consistent with ecological models of feeding behaviour but not predicted by normative economic theory. These substantive effects of state changes on economic decisions perhaps reflect shared evolutionarily conserved neurobiological mechanisms. We suggest that this sensitivity in human risk-preference to current metabolic state has significant implications for both real-world economic transactions and for aberrant decision-making in eating disorders and obesity