Do cardiovascular risk factors explain the relation between socioeconomic status, risk of all-cause mortality, cardiovascular mortality, and acute myocardial infarction?

Much remains to be understood about how low socioeconomic status (SES) increases cardiovascular disease and mortality risk. Data from the Kuopio Ischemic Heart Disease Risk Factor Study (1984-1993) were used to estimate the associations between acute myocardial infarction and income, all-cause mortality, and cardiovascular mortality in a population-based sample of 2,272 Finnish men, with adjustment for 23 biologic, behavioral, psychologic, and social risk factors. Compared with the highest income quintile, those in the bottom quintile had age-adjusted relative hazards of 3.14 (95% confidence interval (CI) 1.77-5.56), 2.66 (95% CI 1.25-5.66), and 4.34 (95% CI 1.95-9.66) for all-cause mortality, cardiovascular mortality, and AMI, respectively. After adjustment for risk factors, the relative hazards for the same comparisons were 1.32 (95% CI 0.70-2.49), 0.70 (95% CI 0.29-1.69), and 2.83 (95% CI 1.14-7.00). In the lowest income quintile, adjustment for risk factors reduced the excess relative risk of all-cause mortality by 85%, that of cardiovascular mortality by 118%, and that of acute myocardial infarction by 45%. These data show how the association between SES and cardiovascular mortality and all-cause mortality is mediated by known risk factor pathways, but full "explanations" for these associations will need to encompass why these biologic, behavioral, psychologic, and social risk factors are differentially distributed by SES.     

Insult, aggression, and the southern culture of honor: An "experimental ethnography."

Three experiments examined how norms characteristic of a "culture of honor" manifest themselves in the cognitions, emotions, behaviors, and physiological reactions of southern White males. Participants were University of Michigan students who grew up in the North or South. In 3 experiments, they were insulted by a confederate who bumped into the participant and called him an "asshole." Compared with northerners (who were relatively unaffected by the insult) southerners were more likely to think their masculine reputation was threatened, more upset (as shown by a rise in cortisol levels), more physiologically primed for aggression (as shown by a rise in testosterone levels), more cognitively primed for aggression, and more likely to engage in aggressive and dominant behavior. Findings highlight the insult–aggression cycle in cultures of honor, in which insults diminish a man's reputation and he tries to restore his status by aggressive or violent behavior. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

EPW: A program for calculating the electron–phonon coupling using maximally localized Wannier functions

EPW (Electron–Phonon coupling using Wannier functions) is a program written in Fortran90 for calculating the electron–phonon coupling in periodic systems using density-functional perturbation theory and maximally localized Wannier functions. EPW can calculate electron–phonon interaction self-energies, electron–phonon spectral functions, and total as well as mode-resolved electron–phonon coupling strengths. The calculation of the electron–phonon coupling requires a very accurate sampling of electron–phonon scattering processes throughout the Brillouin zone, hence reliable calculations can be prohibitively time-consuming. EPW combines the Kohn–Sham electronic eigenstates and the vibrational eigenmodes provided by the Quantum ESPRESSO package (see Giannozzi et al., 2009 [1]) with the maximally localized Wannier functions provided by the wannier90 package (see Mostofi et al., 2008 [2]) in order to generate electron–phonon matrix elements on arbitrarily dense Brillouin zone grids using a generalized Fourier interpolation. This feature of EPW leads to fast and accurate calculations of the electron–phonon coupling, and enables the study of the electron–phonon coupling in large and complex systems.

Program summary

Program title: EPWCatalogue identifier: AEHA_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHA_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: GNU Public LicenseNo. of lines in distributed program, including test data, etc.: 304 443No. of bytes in distributed program, including test data, etc.: 1 487 466Distribution format: tar.gzProgramming language: Fortran 90Computer: Any architecture with a Fortran 90 compilerOperating system: Any environment with a Fortran 90 compilerHas the code been vectorized or parallelized?: Yes, optimized for 1 to 64 processorsRAM: Heavily system dependent, as small as a few MBSupplementary material: A copy of the “EPW/examples” directory containing the phonon binary files can be downloadedClassification: 7External routines: MPI, Quantum-ESPRESSO package [1], BLAS, LAPACK, FFTW. (The necessary Blas, Lapack and FFTW routines are included in the Quantum-ESPRESSO package [1].)Nature of problem: The calculation of the electron–phonon coupling from first-principles requires a very accurate sampling of electron–phonon scattering processes throughout the Brillouin zone; hence reliable calculations can be prohibitively timeconsuming.Solution method: EPW makes use of a real-space formulation and combines the Kohn–Sham electronic eigenstates and the vibrational eigenmodes provided by the Quantum-ESPRESSO package with the maximally localized Wannier functions provided by the wannier90 package in order to generate electron–phonon matrix elements on arbitrarily dense Brillouin zone grids using a generalized Fourier interpolation.Running time: Single processor examples typically take 5–10 minutes.References:

• [1] 

  P. Giannozzi, et al., J. Phys. Condens. Matter 21 (2009), 395502, http://www.quantum-espresso.org/.

     

Evaluating improvements to a meta-heuristic search for constrained interaction testing

Combinatorial interaction testing (CIT) is a cost-effective sampling technique for discovering interaction faults in highly-configurable systems. Constrained CIT extends the technique to situations where some features cannot coexist in a configuration, and is therefore more applicable to real-world software. Recent work on greedy algorithms to build CIT samples now efficiently supports these feature constraints. But when testing a single system configuration is expensive, greedy techniques perform worse than meta-heuristic algorithms, because greedy algorithms generally need larger samples to exercise the same set of interactions. On the other hand, current meta-heuristic algorithms have long run times when feature constraints are present. Neither class of algorithm is suitable when both constraints and the cost of testing configurations are important factors. Therefore, we reformulate one meta-heuristic search algorithm for constructing CIT samples, simulated annealing, to more efficiently incorporate constraints. We identify a set of algorithmic changes and experiment with our modifications on 35 realistic constrained problems and on a set of unconstrained problems from the literature to isolate the factors that improve performance. Our evaluation determines that the optimizations reduce run time by a factor of 90 and accomplish the same coverage objectives with even fewer system configurations. Furthermore, the new version compares favorably with greedy algorithms on real-world problems, and, though our modifications were aimed at constrained problems, it shows similar advantages when feature constraints are absent.     

Context‐Dependent Crowd Evaluation

Many times, even if a crowd simulation looks good in general, there could be some specific individual behaviors which do not seem correct. Spotting such problems manually can become tedious, but ignoring them may harm the simulation's credibility. In this paper we present a data‐driven approach for evaluating the behaviors of individuals within a simulated crowd. Based on video‐footage of a real crowd, a database of behavior examples is generated. Given a simulation of a crowd, an analog analysis is performed on it, defining a set of queries, which are matched by a similarity function to the database examples. The results offer a possible objective answer to the question of how similar are the simulated individual behaviors to real observed behaviors. Moreover, by changing the video input one can change the context of evaluation. We show several examples of evaluating simulated crowds produced using different techniques and comprising of dense crowds, sparse crowds and flocks.     

Edge detection insensitive to changes of illumination in the image

In this paper we present new edge detection algorithms which are motivated by recent developments on edge-adapted reconstruction techniques [F. Aràndiga, A. Cohen, R. Donat, N. Dyn, B. Matei, Approximation of piecewise smooth functions and images by edge-adapted (ENO-EA) nonlinear multiresolution techniques, Appl. Comput. Harmon. Anal. 24 (2) (2008) 225–250]. They are based on comparing local quantities rather than on filtering and thresholding. This comparison process is invariant under certain transformations that model light changes in the image, hence we obtain edge detection algorithms which are insensitive to changes in illumination.     

Anisotropic Smoothness Classes: From Finite Element Approximation to Image Models

We propose and study quantitative measures of smoothness f ? A(f) which are adapted to anisotropic features such as edges in images or shocks in PDE’s. These quantities govern the rate of approximation by adaptive finite elements, when no constraint is imposed on the aspect ratio of the triangles, the simplest example being \(A_{p}(f)=\|\sqrt{|\mathrm{det}(d^{2}f)|}\|_{L^{\tau}}\) which appears when approximating in the L ^p norm by piecewise linear elements when \(\frac{1}{\tau}=\frac{1}{p}+1\). The quantities A(f) are not semi-norms, and therefore cannot be used to define linear function spaces. We show that these quantities can be well defined by mollification when f has jump discontinuities along piecewise smooth curves. This motivates for using them in image processing as an alternative to the frequently used total variation semi-norm which does not account for the smoothness of the edges.     

Labeling Schemes for Tree Representation

This paper deals with compact label-based representations for trees. Consider an n-node undirected connected graph G with a predefined numbering on the ports of each node. The all-ports tree labeling ℒ _all gives each node v of G a label containing the port numbers of all the tree edges incident to v. The upward tree labeling ℒ _up labels each node v by the number of the port leading from v to its parent in the tree. Our measure of interest is the worst case and total length of the labels used by the scheme, denoted M _up (T) and S _up (T) for ℒ _up and M _all (T) and S _all (T) for ℒ _all . The problem studied in this paper is the following: Given a graph G and a predefined port labeling for it, with the ports of each node v numbered by 0,…,deg (v)−1, select a rooted spanning tree for G minimizing (one of) these measures. We show that the problem is polynomial for M _up (T), S _up (T) and S _all (T) but NP-hard for M _all (T) (even for 3-regular planar graphs). We show that for every graph G and port labeling there exists a spanning tree T for which S _up (T)=O(nlog log n). We give a tight bound of O(n) in the cases of complete graphs with arbitrary labeling and arbitrary graphs with symmetric port labeling. We conclude by discussing some applications for our tree representation schemes. A preliminary version of this paper has appeared in the proceedings of the 7th International Workshop on Distributed Computing (IWDC), Kharagpur, India, December 27–30, 2005, as part of Cohen, R. et al.: Labeling schemes for tree representation. In: Proceedings of 7th International Workshop on Distributed Computing (IWDC), Lecture Notes of Computer Science, vol. 3741, pp. 13–24 (2005). R. Cohen supported by the Pacific Theaters Foundation. P. Fraigniaud and D. Ilcinkas supported by the project “PairAPair” of the ACI Masses de Données, the project “Fragile” of the ACI Sécurité et Informatique, and by the project “Grand Large” of INRIA. A. Korman supported in part by an Aly Kaufman fellowship. D. Peleg supported in part by a grant from the Israel Science Foundation.     

Fast Object Segmentation by Growing Minimal Paths from a Single Point on 2D or 3D Images

In this paper, we present a new method for segmenting closed contours and surfaces. Our work builds on a variant of the minimal path approach. First, an initial point on the desired contour is chosen by the user. Next, new keypoints are detected automatically using a front propagation approach. We assume that the desired object has a closed boundary. This a-priori knowledge on the topology is used to devise a relevant criterion for stopping the keypoint detection and front propagation. The final domain visited by the front will yield a band surrounding the object of interest. Linking pairs of neighboring keypoints with minimal paths allows us to extract a closed contour from a 2D image. This approach can also be used for finding an open curve giving extra information as stopping criteria. Detection of a variety of objects on real images is demonstrated. Using a similar idea, we can extract networks of minimal paths from a 3D image called Geodesic Meshing. The proposed method is applied to 3D data with promising results.

Rapid building detection using machine learning

This work describes algorithms for performing discrete object detection, specifically in the case of buildings, where usually only low quality RGB-only geospatial reflective imagery is available. We utilize new candidate search and feature extraction techniques to reduce the problem to a machine learning (ML) classification task. Here we can harness the complex patterns of contrast features contained in training data to establish a model of buildings. We avoid costly sliding windows to generate candidates; instead we innovatively stitch together well known image processing techniques to produce candidates for building detection that cover 80–85 % of buildings. Reducing the number of possible candidates is important due to the scale of the problem. Each candidate is subjected to classification which, although linear, costs time and prohibits large scale evaluation. We propose a candidate alignment algorithm to boost classification performance to 80–90 % precision with a linear time algorithm and show it has negligible cost. Also, we propose a new concept called a Permutable Haar Mesh (PHM) which we use to form and traverse a search space to recover candidate buildings which were lost in the initial preprocessing phase. All code and datasets from this paper are made available online (http://kdl.cs.umb.edu/w/datasets/ and https://github.com/caitlinkuhlman/ObjectDetectionCLUtility).