Sustainable Software Ecosystems for Open Science

Sustainable software ecosystems are difficult to build, and require concerted effort, community norms and collaborations. In science it is especially important to establish communities in which faculty, staff, students and open-source professionals work together and treat software as a first-class product of scientific investigation-just as mathematics is treated in the physical sciences. Kitware has a rich history of establishing collaborative projects in the science, engineering and medical research fields, and continues to work on improving that model as new technologies and approaches become available. This approach closely follows and is enhanced by the movement towards practicing open, reproducible research in the sciences where data, source code, methodology and approach are all available so that complex experiments can be independently reproduced and verified.Comment: Workshop on Sustainable Software: Practices and Experiences, 4 pages, 3 figure

RANKL-independent osteoclastogenesis in the SH3BP2 cherubism mice

Even though the receptor activator of the nuclear factor-κB ligand (RANKL) and its receptor RANK have an exclusive role in osteoclastogenesis, the possibility of RANKL/RANK-independent osteoclastogenesis has been the subject of a long-standing debate in bone biology. In contrast, it has been reported that calvarial injection of TNF-ɑ elicits significant osteoclastogenesis in the absence of RANKL/RANK in NF-κB2- and RBP-J-deficient mice, suggesting that inflammatory challenges and secondary gene manipulation are the prerequisites for RANKL/RANK-deficient mice to develop osteoclasts in vivo. Here we report that, even in the absence of RANKL (Rankl−/−), cherubism mice (Sh3bp2KI/KI) harboring the homozygous gain-of-function mutation in SH3-domain binding protein 2 (SH3BP2) develop tartrate-resistant acid phosphatase (TRAP)-positive multinucleated osteoclasts spontaneously. The Sh3bp2KI/KIRankl−/− mice exhibit an increase in tooth exposure and a decrease in bone volume/total volume compared to Sh3bp2+/+Rankl−/− mice. The multinucleated cells were stained positively for cathepsin K. Osteoclastic marker gene expression in bone and serum TRAP5b levels were elevated in Sh3bp2KI/KIRankl−/− mice. Elevation of the serum TNF-ɑ levels suggested that TNF-ɑ is a driver for the RANKL-independent osteoclast formation in Sh3bp2KI/KI mice. Our results provide a novel mutant model that develops osteoclasts independent of RANKL and establish that the gain-of-function of SH3BP2 promotes osteoclastogenesis not only in the presence of RANKL but also in the absence of RANKL

Creating Sustainable Neighborhood Design for Legacy Cities: A New Framework for Sustainability Assessment

Highly vacant neighborhoods present challenges for balancing social, environmental, and economic considerations for land reuse. Since the 1960’s, many post-Industrial cities such as Detroit have seen extreme population decline, creating severe economic loss and disinvestment in their communities. Strategies and opportunities for stabilization and revitalization, especially those that can be created and implemented by community groups, have become particularly important in these legacy (shrinking) cities. This report uses a case study site on the Lower East Side of Detroit to examine how the Community Development Advocates of Detroit (CDAD) Strategic Framework, a new land use and development framework for highly vacant cities, can be used to influence the Leadership in Energy and Environmental Design for Neighborhood Development (LEED-ND) criteria to allow it to better consider the social, economic, and environmental context of a legacy city. The land use typology described in CDAD’s Strategic Framework inform the criteria in the LEED-ND valuation tool measuring the sustainability of a neighborhood in order to create a new framework: Sustainable Neighborhood Development for Legacy Cities (SND-LC). SND-LC provides recommendations to further integrate social capital, social equity, and ecological considerations into the two frameworks through various planning and design techniques. Joan Nassauer’s concept of “cues to care” is instrumental for examining social capital in vacant neighborhoods and in identifying opportunities to grow social networks. Recommendations for land use reconsiderations call for the integration of social variables such as neighborhood cohesion and access to resources, as well as ecological variables such as stormwater and green space connectivity. Recommendations in SND-LC encourage retrofitting and illustrate how sustainability can be achieved through a more strategic use of vacant land areas rather than through compactness or new development. The new credit rating system applies the economic and social conditions of a legacy city to a new valuation system that can allow highly vacant neighborhoods across the country to achieve a sustainable neighborhood status.Master of Landscape ArchitectureMaster of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/90939/1/Final OAP Completed Project 4.26.pd

The Welcome Project Brochure 2009

The Welcome Project is a diverse group of URI students, faculty, and staff organized to examine and address the climate for Gay, Lesbian, Bisexual, Transgender, Queer, and Questioning (GLBT) individuals on the URI campuses and beyond. The purpose of the Welcome Project is to affirm the dignity of all members of the URI community regardless of sexual orientation and gender identity/ expression, as well as to promote a safe, comfortable, and inclusive environment for all. The Welcome Project strives to identify and eliminate various forms of discrimination based on sexual orientation and gender identity/expression, and works toward developing a tradition of visibility and respect for GLBT people within our community. This is the 2009 edit of the brochure and its Ms Publisher file

Association between celiac sprue and cryopyrin associated autoinflammatory disorders: a case report

Cryopyrin-associated diseases may be characterized by rashes, fever, and sensorineural deafness, while celiac disease may present with symptoms of malabsorption and fatigue. Arthritis is seen in both conditions. We report a young child with histologically diagnosed celiac disease and a cryopyrinopathy

Stan: A Probabilistic Programming Language

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting

Evaluation of Methods for Estimating Time to Steady State with Examples from Phase 1 Studies

An overview is provided of the methodologies used in determining the time to steady state for Phase 1 multiple dose studies. These methods include NOSTASOT (no-statistical-significance-of-trend), Helmert contrasts, spline (quadratic) regression, effective half life for accumulation, nonlinear mixed effects modeling, and Bayesian approach using Markov Chain Monte Carlo (MCMC) methods. For each methodology we describe its advantages and disadvantages. The first two methods do not require any distributional assumptions for the pharmacokinetic (PK) parameters and are limited to average assessment of steady state. Also spline regression which provides both average and individual assessment of time to steady state does not require any distributional assumptions for the PK parameters. On the other hand, nonlinear mixed effects modeling and Bayesian hierarchical modeling which allow for the estimation of both population and subject-specific estimates of time to steady state do require distributional assumptions on PK parameters. The current investigation presents eight case studies for which the time to steady state was assessed using the above mentioned methodologies. The time to steady state estimates obtained from nonlinear mixed effects modeling, Bayesian hierarchal approach, effective half life, and spline regression were generally similar