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

Constitutional Law - Church and State - Statute Requiring Religion to be Taken Into Consideration in Adoption

ln 1951, a Jewish couple obtained custody of illegitimate twins who were then two weeks old. In 1954, the couple formally sought to adopt the children. Although petitioners were otherwise qualified to act as parents, a Massachusetts statute provides that in making orders for adoption, the judge when practicable must give custody only to persons of the same religious faith as that of the child. The twins\u27 natural mother was Catholic but had consented in writing to adoption by the petitioners and to rearing of the children in the Jewish faith. The lower court found that several Catholic couples had filed applications with the Catholic Charities Bureau to adopt Catholic children of the age of the twins, and thus that it was practicable to give custody only to persons of Catholic faith. On appeal, held, affirmed. The statute does not violate the First Amendment since it treats all religions alike and does not require, prevent or hamper any exercise of religion. The mother\u27s interest was only that the babies were in a good home; she permitted rather than commanded the adoption. Petitions of Goldman, (Mass. 1954) 121 N.E. (2d) 843, cert. den. 348 U.S. 942, 75 S.Ct. 363 (1955)