Animal models of fetal growth restriction: Considerations for translational medicine.

Fetal growth restriction (FGR) is the failure of a fetus to reach its full genetic growth potential. It occurs in up to 8% of pregnancies, and after premature birth is the second leading cause of infant mortality and morbidity. There is no treatment currently available for FGR. Its primary cause, when not attributable to structural or genetic defects of the fetus, is 'placental insufficiency'. This broad definition covers the inability of the fetus to acquire sufficient nutrients and oxygen, and is influenced by a number of factors including altered maternal or fetal blood flow, reduced nutrient transport or changes in the placenta such as increased barrier thickness inhibiting nutrient transfer. For those researchers studying FGR and developing new therapies, choosing an animal model is a crucial consideration. It is vital to clearly frame the question being asked, as this will impact the factor influencing fetal nutrient delivery in the model, and will also affect the applicability of the results to the human condition. This review examines the range of in vivo models of FGR available for those engaged in translational research

New insights on the impact of coefficient instability on ratio-correlation population estimates

In this study we examine the regression-based ratio-correlation method and suggest some new tools for assessing the magnitude and impact of coefficient instability on population estimation errors. We use a robust sample of 904 counties from 11 states and find that: (1) coefficient instability is not a universal source of error in regression models for population estimation and its impact is less than commonly assumed; (2) coefficient instability is not related to bias, but it does decrease precision and increase the allocation error of population estimates; and (3) unstable coefficients have the greatest impact on counties under 20,000 in population size. Our findings suggest that information about the conditions that affect coefficient instability and its impact on estimation error might lead to more targeted and efficient approaches for improving population estimates developed from regression models

Discovering Job Preemptions in the Open Science Grid

The Open Science Grid(OSG) is a world-wide computing system which facilitates distributed computing for scientific research. It can distribute a computationally intensive job to geo-distributed clusters and process job's tasks in parallel. For compute clusters on the OSG, physical resources may be shared between OSG and cluster's local user-submitted jobs, with local jobs preempting OSG-based ones. As a result, job preemptions occur frequently in OSG, sometimes significantly delaying job completion time. We have collected job data from OSG over a period of more than 80 days. We present an analysis of the data, characterizing the preemption patterns and different types of jobs. Based on observations, we have grouped OSG jobs into 5 categories and analyze the runtime statistics for each category. we further choose different statistical distributions to estimate probability density function of job runtime for different classes.Comment: 8 page

The Impact of Digitization on Product Offerings: Using Direct Digital Manufacturing in the Supply Chain

To remain competitive, supply chain managers must constantly improve their processes and react to ever-growing and evolving customer preferences in a changing business environment. However, many companies have reached diminishing returns for many of their business processes. Digitization has begun to change product offerings and these changes could be the next great source of competitive advantage for supply chain managers. This research uses a demand supply integration framework to examine direct digital manufacturing (DDM) applications being used to change product delivery to consumers. To test hypotheses, press announcements were collected and analyzed with content analysis. We find that, of the implementations of DDM for delivering products to consumers using digitization, 61% are demand-side focused innovations, 39% are supply-side focused innovations, and 9% are both demand-supply integrated innovations

Charting the Course for Energy Efficiency in New York: Lessons from Existing Programs

This report examines the performance of the existing suite of energy efficiency efforts run by the New York State Energy Research and Development Authority and the state’s investor owned utilities. The latest data shows that through 2014 EEPS program administrators had achieved 79 percent of their to-date savings goals. The report focuses on the best ways to transition from the EEPS program model to the emerging REV model. Reviewing publicly available information, this analysis takes stock of what the EEPS has achieved and calls for a REV planning and delivery program that builds upon lessons learned from decades of past efforts to achieve self-sustaining efficiency markets. It 1) describes the proposed changes to energy efficiency delivery currently under consideration by the Cuomo Administration, 2) reviews overall EEPS performance through the third quarter of 2014, 3) recommends a framework to serve as the basis for future decision-making, and 4) makes additional recommendations for the future of energy efficiency efforts in New York State

Hypothesis Testing in GWAS and Statistical Issues with Compensation in Clinical Trials

We first show theoretically and in simulation how power varies as a function of SNP correlation structure with currently-implemented gene-based testing methods. We propose alternative testing methods whose power does not vary with the correlation structure. We then propose hypothesis tests for detecting prevalence-incidence bias in case-control studies, a bias perhaps overrepresented in GWAS due to currently used study designs. Lastly, we hypothesize how different incentive structures used to keep clinical trial participants in studies may interact with a background of dependent censoring and result in variation in the bias of the Kaplan-Meier survival curve estimator

EFFECTS OF MANAGEMENT PRACTICES ON GRASSLAND BIRDS: SAVANNAH SPARROW

Information on the habitat requirements and effects of habitat management on grassland birds were summarized from information in more than 4,000 published and unpublished papers. A range map is provided to indicate the relative densities of the species in North America, based on Breeding Bird Survey (BBS) data. Although birds frequently are observed outside the breeding range indicated, the maps are intended to show areas where managers might concentrate their attention. It may be ineffectual to manage habitat at a site for a species that rarely occurs in an area. The species account begins with a brief capsule statement, which provides the fundamental components or keys to management for the species. A section on breeding range outlines the current breeding distribution of the species in North America, including areas that could not be mapped using BBS data. The suitable habitat section describes the breeding habitat and occasionally microhabitat characteristics of the species, especially those habitats that occur in the Great Plains. Details on habitat and microhabitat requirements often provide clues to how a species will respond to a particular management practice. A table near the end of the account complements the section on suitable habitat, and lists the specific habitat characteristics for the species by individual studies. A special section on prey habitat is included for those predatory species that have more specific prey requirements. The area requirements section provides details on territory and home range sizes, minimum area requirements, and the effects of patch size, edges, and other landscape and habitat features on abundance and productivity. It may be futile to manage a small block of suitable habitat for a species that has minimum area requirements that are larger than the area being managed. The Brown-headed Cowbird (Molothrus ater) is an obligate brood parasite of many grassland birds. The section on cowbird brood parasitism summarizes rates of cowbird parasitism, host responses to parasitism, and factors that influence parasitism, such as nest concealment and host density. The impact of management depends, in part, upon a species’ nesting phenology and biology. The section on breeding-season phenology and site fidelity includes details on spring arrival and fall departure for migratory populations in the Great Plains, peak breeding periods, the tendency to renest after nest failure or success, and the propensity to return to a previous breeding site. The duration and timing of breeding varies among regions and years. Species’ response to management summarizes the current knowledge and major findings in the literature on the effects of different management practices on the species. The section on management recommendations complements the previous section and summarizes specific recommendations for habitat management provided in the literature. If management recommendations differ in different portions of the species’ breeding range, recommendations are given separately by region. The literature cited contains references to published and unpublished literature on the management effects and habitat requirements of the species. This section is not meant to be a complete bibliography; a searchable, annotated bibliography of published and unpublished papers dealing with habitat needs of grassland birds and their responses to habitat management is posted at the Web site mentioned below