Detecting Sunyaev-Zel'dovich clusters with PLANCK: I. Construction of all-sky thermal and kinetic SZ-maps

All-sky thermal and kinetic Sunyaev-Zel'dovich (SZ) maps are presented for assessing how well the PLANCK-mission can find and characterise clusters of galaxies, especially in the presence of primary anisotropies of the cosmic microwave background (CMB) and various galactic and ecliptic foregrounds. The maps have been constructed from numerical simulations of structure formation in a standard LCDM cosmology and contain all clusters out to redshifts of z = 1.46 with masses exceeding 5e13 M_solar/h. By construction, the maps properly account for the evolution of cosmic structure, the halo-halo correlation function, the evolving mass function, halo substructure and adiabatic gas physics. The velocities in the kinetic map correspond to the actual density environment at the cluster positions. We characterise the SZ-cluster sample by measuring the distribution of angular sizes, the integrated thermal and kinetic Comptonisations, the source counts in the three relevant PLANCK-channels, and give the angular power-spectra of the SZ-sky. While our results are broadly consistent with simple estimates based on scaling relations and spherically symmetric cluster models, some significant differences are seen which may affect the number of cluster detectable by PLANCK.Comment: 14 pages, 16 figures, 3 tables, submitted to MNRAS, 05.Jul.200

Measuring cluster peculiar velocities with the Sunyaev-Zeldovich effects: scaling relations and systematics

The fluctuations in the Cosmic Microwave Background (CMB) intensity due to the Sunyaev-Zeldovich (SZ) effect are the sum of a thermal and a kinetic contribution. Separating the two components to measure the peculiar velocity of galaxy clusters requires radio and microwave observations at three or more frequencies, and knowledge of the temperature T_e of the intracluster medium weighted by the electron number density. To quantify the systematics of this procedure, we extract a sample of 117 massive clusters at redshift z=0 from an N-body hydrodynamical simulation, with 2x480^3 particles, of a cosmological volume 192 Mpc/h on a side of a flat Cold Dark Matter model with Omega_0=0.3 and Lambda=0.7. Our simulation includes radiative cooling, star formation and the effect of feedback and galactic winds from supernovae. We find that (1) our simulated clusters reproduce the observed scaling relations between X-ray and SZ properties; (2) bulk flows internal to the intracluster medium affect the velocity estimate by less than 200 km/s in 93 per cent of the cases; (3) using the X-ray emission weighted temperature, as an estimate of T_e, can overestimate the peculiar velocity by 20-50 per cent, if the microwave observations do not spatially resolve the cluster. For spatially resolved clusters, the assumptions on the spatial distribution of the ICM, required to separate the two SZ components, still produce a velocity overestimate of 10-20 per cent, even with an unbiased measure of T_e. Thanks to the large size of our cluster samples, these results set a robust lower limit of 200 km/s to the systematic errors that will affect upcoming measures of cluster peculiar velocities with the SZ effect.Comment: 14 pages, 12 figures, MNRAS, in press. Figures 3 and 4 now contain more recent observational data. Other minor revisions according to referee's comment

A Chandra and XMM View of the Mass & Metals in Galaxy Groups and Clusters

X-ray observations with Chandra and XMM are providing valuable new measurements of the baryonic and dark matter content of groups and clusters. Masses of cD clusters obtained from X-ray and gravitational lensing studies generally show good agreement, therefore providing important validation of both methods. Gas fractions have been obtained for several clusters that verify previous results for a low matter density (Omega_m ~0.3). Chandra has also provided measurements of the mass profiles deep down into several cluster cores and has generally found no significant deviations from CDM predictions in contrast to the flat core density profiles inferred from the rotation curves of low-surface brightness galaxies and dwarf galaxies; i.e., there is no evidence for self-interacting dark matter in cluster cores. Finally, initial studies of the iron and silicon abundances in centrally E-dominated groups show that they have pronounced gradients from 1-2 solar values within the central 30-50 kpc that fall to values of 0.3-0.5 solar at larger radii. The Si/Fe ratios are consistent with approximately 80% of the metals originating from Type Ia supernovae. Several cD clusters also display central Fe enhancements suggestive of Type Ia supernova enrichment, though some have central dips that may provide a vital clue for solving the cooling flow mystery

Grand challenges in social physics: in pursuit of moral behavior

Methods of statistical physics have proven valuable for studying the evolution of cooperation in social dilemma games. However, recent empirical research shows that cooperative behavior in social dilemmas is only one kind of a more general class of behavior, namely moral behavior, which includes reciprocity, respecting others' property, honesty, equity, efficiency, as well as many others. Inspired by these experimental works, we here open up the path toward studying other forms of moral behavior with methods of statistical physics. We argue that this is a far-reaching direction for future research that can help us answer fundamental questions about human sociality. Why did our societies evolve as they did? What moral principles are more likely to emerge? What happens when different moral principles clash? Can we predict the break out of moral conflicts in advance and contribute to their solution? These are amongst the most important questions of our time, and methods of statistical physics could lead to new insights and contribute toward finding answers

Lactobacillus plantarum displaying CCL3 chemokine in fusion with HIV-1 Gag derived antigen causes increased recruitment of T cells

Background Chemokines are attractive candidates for vaccine adjuvants due to their ability to recruit the immune cells. Lactic acid bacteria (LAB)-based delivery vehicles have potential to be used as a cheap and safe option for vaccination. Chemokine produced on the surface of LAB may potentially enhance the immune response to an antigen and this approach can be considered in development of future mucosal vaccines. Results We have constructed strains of Lactobacillus plantarum displaying a chemokine on their surface. L. plantarum was genetically engineered to express and anchor to the surface a protein called CCL3Gag. CCL3Gag is a fusion protein comprising of truncated HIV-1 Gag antigen and the murine chemokine CCL3, also known as MIP-1α. Various surface anchoring strategies were explored: (1) a lipobox-based covalent membrane anchor, (2) sortase-mediated covalent cell wall anchoring, (3) LysM-based non-covalent cell wall anchoring, and (4) an N-terminal signal peptide-based transmembrane anchor. Protein production and correct localization were confirmed using Western blotting, flow cytometry and immunofluorescence microscopy. Using a chemotaxis assay, we demonstrated that CCL3Gag-producing L. plantarum strains are able to recruit immune cells in vitro. Conclusions The results show the ability of engineered L. plantarum to produce a functional chemotactic protein immobilized on the bacterial surface. We observed that the activity of surface-displayed CCL3Gag differed depending on the type of anchor used. The chemokine which is a part of the bacteria-based vaccine may increase the recruitment of immune cells and, thereby, enhance the reaction of the immune system to the vaccine

Direct Simulation of a Solidification Benchmark Experiment

International audienceA solidification benchmark experiment is simulated using a three-dimensional cellular automaton-finite element solidification model. The experiment consists of a rectangular cavity containing a Sn-3 wt pct Pb alloy. The alloy is first melted and then solidified in the cavity. A dense array of thermocouples permits monitoring of temperatures in the cavity and in the heat exchangers surrounding the cavity. After solidification, the grain structure is revealed by metallography. X-ray radiography and inductively coupled plasma spectrometry are also conducted to access a distribution map of Pb, or macrosegregation map. The solidification model consists of solutions for heat, solute mass, and momentum conservations using the finite element method. It is coupled with a description of the development of grain structure using the cellular automaton method. A careful and direct comparison with experimental results is possible thanks to boundary conditions deduced from the temperature measurements, as well as a careful choice of the values of the material properties for simulation. Results show that the temperature maps and the macrosegregation map can only be approached with a three-dimensional simulation that includes the description of the grain structure

The relationship between perceived service quality and patient willingness to recommend at a national oncology hospital network

<p>Abstract</p> <p>Background</p> <p>"Willingness to recommend" questions are being increasingly used to measure and manage patient loyalty. Yet, there is little data in the literature correlating the "willingness to recommend" question with commonly used perceived service quality items in surveys to identify the key drivers of the optimal patient experience. We therefore evaluated the relationship between perceived service quality and subsequent single top box "willingness to recommend" scores among oncology patients.</p> <p>Methods</p> <p>A total of 2018 returning cancer patients treated at Cancer Treatment Centers of America^®(CTCA) responded to an internally developed service quality questionnaire, which covered the following dimensions: operations and services, treatment and care with a multidisciplinary team and patient endorsements. Items were measured on a 7-point Likert-type scale ranging from "completely dissatisfied" to "completely satisfied." Patient willingness to, "recommend this facility to friends and associates" was measured on an 11-point scale ranging from "not at all likely" to "extremely likely", which was subsequently dichotomized into two categories: top box response (10) versus all others (0-9). The relationship between perceived service quality and "willingness to recommend" was assessed via Kendall's tau b correlation and univariate and multivariate logistic regression.</p> <p>Results</p> <p>Of the 2018 patients, 959 were newly diagnosed while 1059 were previously treated. 902 were males and 1116 females. The mean age was 54.2 years and the most frequent diagnoses were breast (412), lung (294), prostate (260), colorectal (179) and pancreas (169). 1553 patients said they were "extremely likely" to recommend CTCA to friends and associates, resulting in 77% "top box" responses while 465 (23%) responded in all other categories. The key service quality drivers that were statistically significant in the final logistic model were "team helping you understand your medical condition", "staff genuinely caring for you as an individual", "whole person approach to patient care" and "CTCA medical oncologist."</p> <p>Conclusions</p> <p>In this multi-center study, we demonstrate the predictive significance of perceived service quality as it relates to patient willingness to recommend an oncology service provider. This study is unique in reporting on the role of perceived service quality as a predictor of patient willingness to recommend in a large sample of cancer patients.</p