Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration.

Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today's sequencing and array-based profiling methods present major challenges to visualization tools. The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution. A key characteristic of IGV is its focus on the integrative nature of genomic studies, with support for both array-based and next-generation sequencing data, and the integration of clinical and phenotypic data. Although IGV is often used to view genomic data from public sources, its primary emphasis is to support researchers who wish to visualize and explore their own data sets or those from colleagues. To that end, IGV supports flexible loading of local and remote data sets, and is optimized to provide high-performance data visualization and exploration on standard desktop systems. IGV is freely available for download from http://www.broadinstitute.org/igv, under a GNU LGPL open-source license

Generation and characterisation of graphite and bio-oil from the pyrolysis of woody biomass

The thermal conversion of biomass to biochar has been studied for over 100 years (Laboratory et al., 1978). Over the past two decades it has gained momentum in environmental and energy research (Stavi & Lal, 2013). Concerns over climate change, poverty, declining agricultural production, fertiliser shortage, and fuel generation are all topics that biochar and bio-oils have aimed to address. Optimisation of biochar and bio-oils production, however, has received relatively little attention from a whole-of-system approach. The work undertaken in this thesis aims to address these limitations and provide a system that maximises the conversion of woody biomass to biochar and bio-oils

Decision-Making Factors of School Superintendents Related to the New York State Tax Levy Cap and its Impact on Budgeting for Public Education

The purpose of the study was to examine decision-making factors among school superintendents related to the impact the New York State tax levy cap is having on public school budgeting. Revenue limitations resulting from the 2012 tax levy cap legislation created concerns of a funding cliff forecast to happen within 4-5 years. The cliff was expected to threaten and affect the school districts’ ability to provide quality programs, meet their expenses, or risk insolvency. Now, 7 years after the implementation of this tax levy cap legislation, school districts have not become insolvent. This qualitative study used personal interviews of a sample of school superintendents in Nassau County, New York from high need/low wealth, and low need/high wealth districts to determine the impact of the tax levy cap on budgeting. Results of this study suggest that superintendents are more cognizant of district finances and have focused greater attention on long range financial analysis and planning. The results also suggest that what superintendents once thought was a leverage opportunity to negotiate more favorable terms with collective bargaining units now appears to be a limitation to a district’s ability to attract and retain talented staff. Lastly, the results suggest that inequities are prevalent in Nassau County, NY when comparing high need/low wealth districts with their low need/high wealth counterparts. This study provides recommendations and insight to aid future superintendents, administrators, legislators, and policy makers to better understand the pressures on the educational system experienced by current school leaders

Simulation of Alternative Marketing Strategies for U.S. Cotton

Three marketing strategies (selling a put option, cash sale at harvest, and cash sale in June) are simulated based on historical values and ranked based on certainty equivalents for a representative irrigated and dryland cotton farm Scenario analysis is also used to compare varying yield values.Simulation, Marketing, Cotton, Risk, Marketing, Research Methods/ Statistical Methods,

Supersolutions for a class of semilinear heat equations

A semilinear heat equation $u_{t}=\Delta u+f(u)$ with nonnegative initial data in a subset of $L^{1}(\Omega)$ is considered under the assumption that $f$ is nonnegative and nondecreasing and $\Omega\subseteq \R^{n}$. A simple technique for proving existence and regularity based on the existence of supersolutions is presented, then a method of construction of local and global supersolutions is proposed. This approach is applied to the model case $f(s)=s^{p}$, $\phi\in L^{q}(\Omega)$: new sufficient conditions for the existence of local and global classical solutions are derived in the critical and subcritical range of parameters. Some possible generalisations of the method to a broader class of equations are discussed.Comment: Expanded version of the previous submission arXiv:1111.0258v1. 14 page

Whole-genome sequence analysis shows that two endemic species of North American wolf are admixtures of the coyote and gray wolf.

Protection of populations comprising admixed genomes is a challenge under the Endangered Species Act (ESA), which is regarded as the most powerful species protection legislation ever passed in the United States but lacks specific provisions for hybrids. The eastern wolf is a newly recognized wolf-like species that is highly admixed and inhabits the Great Lakes and eastern United States, a region previously thought to be included in the geographic range of only the gray wolf. The U.S. Fish and Wildlife Service has argued that the presence of the eastern wolf, rather than the gray wolf, in this area is grounds for removing ESA protection (delisting) from the gray wolf across its geographic range. In contrast, the red wolf from the southeastern United States was one of the first species protected under the ESA and was protected despite admixture with coyotes. We use whole-genome sequence data to demonstrate a lack of unique ancestry in eastern and red wolves that would not be expected if they represented long divergent North American lineages. These results suggest that arguments for delisting the gray wolf are not valid. Our findings demonstrate how a strict designation of a species under the ESA that does not consider admixture can threaten the protection of endangered entities. We argue for a more balanced approach that focuses on the ecological context of admixture and allows for evolutionary processes to potentially restore historical patterns of genetic variation

NURBS modeling and structural shape optimization of cardiovascular stents

Cardiovascular stents have been used since the 1990s to treat atherosclerosis, one of leading causes of death in the western world, and structural optimization has led to significant improvements in stent performance. Much of the potential variation in stent geometry, however, has remained unconsidered. This paper presents a non-uniform rational basis spline (NURBS) parameterization of a stent, the inclusion of structural fatigue resistance as a design consideration, and the results of a design optimization based on response surface techniques. Results show the feasibility and merits of the NURBS approach, which models a much broader range of shapes than was previously possible. Multi-objective optimization produces a range of geometrically diverse Pareto-optimal designs; these can be used to develop future clinical design guides, accounting for the variation observed across patients. We conclude by motivating future work with increasingly complex physical modeling and optimization capabilities