Particle displacements in the elastic deformation of amorphous materials: local fluctuations vs. non-affine field

We study the local disorder in the deformation of amorphous materials by decomposing the particle displacements into a continuous, inhomogeneous field and the corresponding fluctuations. We compare these fields to the commonly used non-affine displacements in an elastically deformed 2D Lennard-Jones glass. Unlike the non-affine field, the fluctuations are very localized, and exhibit a much smaller (and system size independent) correlation length, on the order of a particle diameter, supporting the applicability of the notion of local "defects" to such materials. We propose a scalar "noise" field to characterize the fluctuations, as an additional field for extended continuum models, e.g., to describe the localized irreversible events observed during plastic deformation.Comment: Minor corrections to match the published versio

Digital Collaboration and Classroom Practice: Educator Use of ARIS Connect

A major focus of the booming education technology sector is on products that aim to help teachers improve classroom practice. For their part, districts must figure out which of these resources will be most useful to schools. In New York City, the Department of Education developed its own Achievement Reporting and Innovation System (ARIS), which was rolled out in 2008. ARIS was an early effort at a system-wide data and teacher collaboration platform, and a major undertaking for the nation's largest school district. In 2011, the Research Alliance received a grant from the Spencer Foundation to investigate how this ambitious initiative played out in schools. Our first report focused on overall use and perceptions of ARIS. In the current phase of our study, we honed our focus onto ARIS Connect -- a component designed specifically to help educators improve their practice by sharing resources, posting questions, and giving one another feedback, both within schools and across the district. Our investigation sought to understand what educators thought of Connect, and whether, as its designers intended, Connect supported their ability to communicate with other educators and improve classroom practice. The study is based on two years of "clickstream" data, which tracks user visits to and navigation through ARIS. We also visited nine middle schools that recorded higher-than-average use of Connect, where we interviewed administrators and held focus groups with teachers. This report presents our findings, including insights on why educators did or did not use Connect; what might have made Connect more useful; and what external tools educators use for similar purposes

Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities

New technologies have enabled the investigation of biology and human health at an unprecedented scale and in multiple dimensions. These dimensions include a myriad of properties describing genome, epigenome, transcriptome, microbiome, phenotype, and lifestyle. No single data type, however, can capture the complexity of all the factors relevant to understanding a phenomenon such as a disease. Integrative methods that combine data from multiple technologies have thus emerged as critical statistical and computational approaches. The key challenge in developing such approaches is the identification of effective models to provide a comprehensive and relevant systems view. An ideal method can answer a biological or medical question, identifying important features and predicting outcomes, by harnessing heterogeneous data across several dimensions of biological variation. In this Review, we describe the principles of data integration and discuss current methods and available implementations. We provide examples of successful data integration in biology and medicine. Finally, we discuss current challenges in biomedical integrative methods and our perspective on the future development of the field

Sex workers perspectives on strategies to reduce sexual exploitation and HIV risk: a qualitative study in Tijuana, Mexico.

Globally, female sex workers are a population at greatly elevated risk of HIV infection, and the reasons for and context of sex industry involvement have key implications for HIV risk and prevention. Evidence suggests that experiences of sexual exploitation (i.e., forced/coerced sex exchange) contribute to health-related harms. However, public health interventions that address HIV vulnerability and sexual exploitation are lacking. Therefore, the objective of this study was to elicit recommendations for interventions to prevent sexual exploitation and reduce HIV risk from current female sex workers with a history of sexual exploitation or youth sex work. From 2010-2011, we conducted in-depth interviews with sex workers (n = 31) in Tijuana, Mexico who reported having previously experienced sexual exploitation or youth sex work. Participants recommended that interventions aim to (1) reduce susceptibility to sexual exploitation by providing social support and peer-based education; (2) mitigate harms by improving access to HIV prevention resources and psychological support, and reducing gender-based violence; and (3) provide opportunities to exit the sex industry via vocational supports and improved access to effective drug treatment. Structural interventions incorporating these strategies are recommended to reduce susceptibility to sexual exploitation and enhance capacities to prevent HIV infection among marginalized women and girls in Mexico and across international settings

International study into the use of intermittent hormone therapy in the treatment of carcinoma of the prostate : A meta-analysis of 1446 patients

OBJECTIVE: To review pooled phase II data to identify features of different regimens of intermittent hormone therapy (IHT), developed to reduce the morbidity of treating metastatic prostate cancer, and which carries a theoretical advantage of delaying the onset of androgen-independent prostate cancer, (AIPC) that are associated with success, highlighting features which require exploration with prospective trials to establish the best strategies for using this treatment. METHODS: Individual data were collated on 1446 patients with adequate information, from 10 phase II studies with >50 cases, identified through Pubmed. RESULTS: Univariate and multivariate Cox proportional hazard models were developed to predict treatment success with a high degree of statistical success. The prostate-specific antigen (PSA) nadir, the PSA threshold to restart treatment, and medication type and duration, were important predictors of outcome. CONCLUSIONS: The duration of biochemical remission after a period of HT is a durable early indicator of how rapidly AIPC and death will occur, and will make a useful endpoint in future trials to investigate the best ways to use IHT based on the important treatment cycling variables described above. Patients spent a mean of 39% of the time off treatment. The initial PSA level and PSA nadir allow the identification of patients with prostate cancer in whom it might be possible to avoid radical therapy.Peer reviewe

Force Chains, Microelasticity and Macroelasticity

It has been claimed that quasistatic granular materials, as well as nanoscale materials, exhibit departures from elasticity even at small loadings. It is demonstrated, using 2D and 3D models with interparticle harmonic interactions, that such departures are expected at small scales [below O(100) particle diameters], at which continuum elasticity is invalid, and vanish at large scales. The models exhibit force chains on small scales, and force and stress distributions which agree with experimental findings. Effects of anisotropy, disorder and boundary conditions are discussed as well.Comment: 4 pages, 11 figures, RevTeX 4, revised and resubmitted to Phys. Rev. Let

Stress response inside perturbed particle assemblies

The effect of structural disorder on the stress response inside three dimensional particle assemblies is studied using computer simulations of frictionless sphere packings. Upon applying a localised, perturbative force within the packings, the resulting {\it Green's} function response is mapped inside the different assemblies, thus providing an explicit view as to how the imposed perturbation is transmitted through the packing. In weakly disordered arrays, the resulting transmission of forces is of the double-peak variety, but with peak widths scaling linearly with distance from the source of the perturbation. This behaviour is consistent with an anisotropic elasticity response profile. Increasing the disorder distorts the response function until a single-peak response is obtained for fully disordered packings consistent with an isotropic description.Comment: 8 pages, 7 figure captions To appear in Granular Matte

A survey of statistical network models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Comment: 96 pages, 14 figures, 333 reference