Lower Bounds for Sparse Recovery

We consider the following k-sparse recovery problem: design an m x n matrix A, such that for any signal x, given Ax we can efficiently recover x' satisfying ||x-x'||_1 <= C min_{k-sparse} x"} ||x-x"||_1. It is known that there exist matrices A with this property that have only O(k log (n/k)) rows. In this paper we show that this bound is tight. Our bound holds even for the more general /randomized/ version of the problem, where A is a random variable and the recovery algorithm is required to work for any fixed x with constant probability (over A).Comment: 11 pages. Appeared at SODA 201

Lower bounds for sparse recovery

We consider the following k-sparse recovery problem: design an m x n matrix A, such that for any signal x, given Ax we can efficiently recover ^x satisfying x|| ^x||1 [less than or equal to] C min[subscript k]-sparse x'||x - x'||1. It is known that there exist matrices A with this property that have only O(k log(n=k)) rows. In this paper we show that this bound is tight. Our bound holds even for the more general random- ized version of the problem, where A is a random variable, and the recovery algorithm is required to work for any fixed x with constant probability (over A).David & Lucile Packard FoundationDanish National Research FoundationDanish National Research Foundation (MADALGO (Center for Massive Data Algorithmics))National Science Foundation (U.S.) (grant CCF-0728645)Cisco Community Fellowship Progra

The effects of socioeconomic status and indices of physical environment on reduced birth weight and preterm births in Eastern Massachusetts

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Air pollution and social characteristics have been shown to affect indicators of health. While use of spatial methods to estimate exposure to air pollution has increased the power to detect effects, questions have been raised about potential for confounding by social factors.Methods: A study of singleton births in Eastern Massachusetts was conducted between 1996 and 2002 to examine the association between indicators of traffic, land use, individual and area-based socioeconomic measures (SEM), and birth outcomes ( birth weight, small for gestational age and preterm births), in a two-level hierarchical model.Results: We found effects of both individual ( education, race, prenatal care index) and area-based ( median household income) SEM with all birth outcomes. The associations for traffic and land use variables were mainly seen with birth weight, with an exception for an effect of cumulative traffic density on small for gestational age. Race/ethnicity of mother was an important predictor of birth outcomes and a strong confounder for both area-based SEM and indices of physical environment. The effects of traffic and land use differed by level of education and median household income.Conclusion: Overall, the findings of the study suggested greater likelihood of reduced birth weight and preterm births among the more socially disadvantaged, and a greater risk of reduced birth weight associated with traffic exposures. Results revealed the importance of controlling simultaneously for SEM and environmental exposures as the way to better understand determinants of health.This work is supported by the Harvard Environmental Protection Agency (EPA) Center, Grants R827353 and R-832416, and National Institute for Environmental Health Science (NIEHS) ES-0002

Dopamine transporter (DAT1) and dopamine receptor D4 (DRD4) genotypes differentially impact on electrophysiological correlates of error processing

Peer reviewedPublisher PD

Old and new cluster designs in emergency field surveys: in search of a one-fits-all solution

<p>Abstract</p> <p>Introduction</p> <p>Cluster surveys are frequently used to measure key nutrition and health indicators in humanitarian emergencies. The survey design of 30 clusters of 7 children (30 × 7) was initially proposed by the World Health Organization for measuring vaccination coverage, and later a design of 30 clusters of 30 children (30 × 30) was introduced to measure acute malnutrition in emergency settings. Recently, designs of 33 clusters of 6 children (33 × 6) and 67 clusters of 3 children (67 × 3) have been proposed as alternatives that enable measurement of several key indicators with sufficient precision, while offering substantial savings in time. This paper explores expected effects of using 67 × 3, 33 × 6, or 30 × 7 designs instead of a "standard" 30 × 30 design on precision and accuracy of estimates, and on time required to complete the survey.</p> <p>Analysis</p> <p>The 67 × 3, 33 × 6, and 30 × 7 designs are expected to be more statistically efficient for measuring outcomes having high design effects (e.g., vaccination coverage, vitamin A distribution coverage, or access to safe water sources), and less efficient for measuring outcomes with more within-cluster variability, such as global acute malnutrition or anemia. Because of small sample sizes, these designs may not provide sufficient levels of precision to measure crude mortality rates. Given the small number (3 to 7) of survey subjects per cluster, it may be hard to select representative samples of subjects within clusters.</p> <p>The smaller sample size in these designs will likely result in substantial time savings. The magnitude of the savings will depend on several factors, including the average travel time between clusters. The 67 × 3 design will provide the least time savings. The 33 × 6 and 30 × 7 designs perform similarly to each other, both in terms of statistical efficiency and in terms of time required to complete the survey.</p> <p>Conclusion</p> <p>Cluster designs discussed in this paper may offer substantial time and cost savings compared to the traditional 30 × 30 design, and may provide acceptable levels of precision when measuring outcomes that have high intracluster homogeneity. Further investigation is required to determine whether these designs can consistently provide accurate point estimates for key outcomes of interest. Organizations conducting cluster surveys in emergency settings need to build their technical capacity in survey design to be able to calculate context-specific sample sizes individually for each planned survey.</p

Climate change: what competencies and which medical education and training approaches?

<p>Abstract</p> <p>Background</p> <p>Much research has been devoted to identifying healthcare needs in a climate-changing world. However, while there are now global and national policy statements about the importance of health workforce development for climate change, little has been published about what competencies might be demanded of practitioners in a climate-changing world. In such a context, this debate and discussion paper aims to explore the nature of key competencies and related opportunities for teaching climate change in medical education and training. Particular emphasis is made on preparation for practice in rural and remote regions likely to be greatly affected by climate change.</p> <p>Discussion</p> <p>The paper describes what kinds of competencies for climate change might be included in medical education and training. It explores which curricula, teaching, learning and assessment approaches might be involved. Rather than arguing for major changes to medical education and training, this paper explores well established precedents to offer practical suggestions for where a particular kind of literacy--eco-medical literacy--and related competencies could be naturally integrated into existing elements of medical education and training.</p> <p>Summary</p> <p>The health effects of climate change have, generally, not yet been integrated into medical education and training systems. However, the necessary competencies could be taught by building on existing models, best practice and innovative traditions in medicine. Even in crowded curricula, climate change offers an opportunity to reinforce and extend understandings of how interactions between people and place affect health.</p

Synthetic asters as elastic and radial skeletons

The radial geometry with rays radiated from a common core occurs ubiquitously in nature for its symmetry and functions. Herein, we report a class of synthetic asters with well-defined core-ray geometry that can function as elastic and radial skeletons to harbor nano- and microparticles. We fabricate the asters in a single, facile, and high-yield step that can be readily scaled up; specifically, amphiphilic gemini molecules self-assemble in water into asters with an amorphous core and divergently growing, twisted crystalline ribbons. The asters can spontaneously position microparticles in the cores, along the radial ribbons, or by the outer rims depending on particle sizes and surface chemistry. Their mechanical properties are determined on single- and multiple-aster levels. We further maneuver the synthetic asters as building blocks to form higher-order structures in virtue of aster-aster adhesion induced by ribbon intertwining. We envision the astral structures to act as rudimentary spatial organizers in nanoscience for coordinated multicomponent systems, possibly leading to emergent, synergistic functions

An Integrated Decision Making Approach for Adaptive Shared Control of Mobility Assistance Robots

© 2016, Springer Science+Business Media Dordrecht. Mobility assistance robots provide support to elderly or patients during walking. The design of a safe and intuitive assistance behavior is one of the major challenges in this context. We present an integrated approach for the context-specific, on-line adaptation of the assistance level of a rollator-type mobility assistance robot by gain-scheduling of low-level robot control parameters. A human-inspired decision-making model, the drift-diffusion Model, is introduced as the key principle to gain-schedule parameters and with this to adapt the provided robot assistance in order to achieve a human-like assistive behavior. The mobility assistance robot is designed to provide (a) cognitive assistance to help the user following a desired path towards a predefined destination as well as (b) sensorial assistance to avoid collisions with obstacles while allowing for an intentional approach of them. Further, the robot observes the user long-term performance and fatigue to adapt the overall level of (c) physical assistance provided. For each type of assistance a decision-making problem is formulated that affects different low-level control parameters. The effectiveness of the proposed approach is demonstrated in technical validation experiments. Moreover, the proposed approach is evaluated in a user study with 35 elderly persons. Obtained results indicate that the proposed gain-scheduling technique incorporating ideas of human decision-making models shows a general high potential for the application in adaptive shared control of mobility assistance robots

The Demographic and Socioeconomic Factors Predictive for Populations at High-Risk for La Crosse Virus Infection in West Virginia

Although a large body of literature exists for the environmental risk factors for La Crosse virus (LACV) transmission, the demographic and socioeconomic risk factors for developing LACV infection have not been investigated. Therefore, this study investigated the demographic and socioeconomic risk factors for LACV infection in West Virginia from 2003 to 2007, using two forward stepwise discriminant analyses. The discriminant analyses were used to evaluate a number of demographic and socioeconomic factors for their ability to predict: 1) those census tracts with at least one reported case of LACV infection versus those census tracts with no reported cases of LACV infection and 2) to evaluate significantly high-risk clusters for LACV infection versus significantly low-risk clusters for LACV infection. In the first model, a high school education diploma or a general education diploma or less and a lower housing densit