NASA Lewis Wind Tunnel Model Systems Criteria

This report describes criteria for the design, analysis, quality assurance, and documentation of models or test articles that are to be tested in the aeropropulsion facilities at the NASA Lewis Research Center. The report presents three methods for computing model allowable stresses on the basis of the yield stress or ultimate stress, and it gives quality assurance criteria for models tested in Lewis' aeropropulsion facilities. Both customer-furnished model systems and in-house model systems are discussed. The functions of the facility manager, project engineer, operations engineer, research engineer, and facility electrical engineer are defined. The format for pretest meetings, prerun safety meetings, and the model criteria review are outlined Then, the format for the model systems report (a requirement for each model that is to be tested at NASA Lewis) is described, the engineers that are responsible for developing the model systems report are listed, and the time table for its delivery to the facility manager is given

The Influence on Climate Change of Differing Scenarios for Future Development Analyzed Using the MIT Integrated Global System Model

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).A wide variety of scenarios for future development have played significant roles in climate policy discussions. This paper presents projections of greenhouse gas (GHG) concentrations, sea level rise due to thermal expansion and glacial melt, oceanic acidity, and global mean temperature increases computed with the MIT Integrated Global Systems Model (IGSM) using scenarios for 21st century emissions developed by three different groups: intergovernmental (represented by the Intergovernmental Panel on Climate Change), government (represented by the U.S. government Climate Change Science Program) and industry (represented by Royal Dutch Shell plc). In all these scenarios the climate system undergoes substantial changes. By 2100, the CO2 concentration ranges from 470 to 1020 ppm compared to a 2000 level of 365 ppm, the CO2-equivalent concentration of all greenhouse gases ranges from 550 to 1780 ppm in comparison to a 2000 level of 415 ppm, sea level rises by 24 to 56 cm relative to 2000 due to thermal expansion and glacial melt, oceanic acidity changes from a current pH of around 8 to a range from 7.63 to 7.91. The global mean temperature increases by 1.8 to 7.0 degrees C relative to 2000.The IGSM model used here is supported by the U.S. Department of Energy, U.S. Environmental Protection Agency, U.S. National Science Foundation, U.S. National Aeronautics and Space Administration, U.S. National Oceanographic and Atmospheric Administration and the Industry and Foundation Sponsors of the MIT Joint Program on the Science and Policy of Global Change

Use of smartphones, mobile apps and wearables for health promotion by people with anxiety or depression:An analysis of a nationally representative survey data

People with mental illness have increased cardiovascular risk factors, which contributes significantly to mortality in this population. Digital interventions have emerged as promising models to promote physical health, although their potential for use in mental health populations is relatively unexplored. We examined the potential for using digital tools for health promotion by people with common mental disorders like anxiety or depression. Using data from the 2019 edition of the Health Information National Trends Survey (HINTS 5), we evaluated differences between individuals with self-reported history of diagnosed depression/anxiety and the general population with respect to ownership, usage, and perceived usefulness of digital tools for managing their health. Overall, individuals with anxiety or depression were as likely as the general population to use digital devices for their care. Those with anxiety or depression who had health apps were more likely to report intentions to lose weight than those without health apps. Significant sociodemographic predictors of digital tools usage included gender, age, income, and education level. People with anxiety or depression own and use digital health tools at similarly high rates to the general population, suggesting that these tools present a novel opportunity for health promotion among people with these disorders

Intergalactic Globular Clusters

We confirm and extend our previous detection of a population of intergalactic globular clusters in Abell 1185, and report the first discovery of an intergalactic globular cluster in the nearby Virgo cluster of galaxies. The numbers, colors and luminosities of these objects can place constraints on their origin, which in turn may yield new insights to the evolution of galaxies in dense environments.Comment: 2 pages, no figures. Talk presented at JD6, IAU General Assembly XXV, Sydney, Australia, July 2003, to appear in Highlights of Astronomy, Vol. 1

Influence of Soybean Maturity Group and Row Width on Bean Leaf Beetle (Coleoptera: Chrysomelidae) and Bean Pod Mottle Disease in an Early Season Production System

ABSTRACT The influence of narrow and wide-row soybeans on infestations of bean leaf beetle (BLB), Cerotoma trifurcata (Forster) (Coleoptera: Chrysomelidae) adults, a vector of bean pod mottle virus (BPMV), and associated incidence of bean pod mottle (BPM) disease were investigated in maturity groups IV and V soybeans in Mississippi. Maturity group IV soybeans had greater cumulative BLB numbers and greater incidence of BPM than maturity grou

Safety and preliminary efficacy of vorinostat with R-EPOCH in high-risk HIV-associated non-Hodgkin\u27s lymphoma (AMC-075)

We performed a phase I trial of vorinostat (VOR) given on days 1 to 5 with R-EPOCH (rituximab plus etoposide, prednisone, vincristine, cyclophosphamide, and doxorubicin hydrochloride) in patients with aggressive HIV-associated non-Hodgkin lymphoma. VOR was tolerable at 300 mg and seemingly efficacious with chemotherapy with complete response rate of 83% and 1-year event-free survival of 83%. VOR did not significantly alter chemotherapy steady-state concentrations, CD4+ cell counts, or HIV viral loads. Vorinostat (VOR), a histone deacetylase inhibitor, enhances the anti-tumor effects of rituximab (R) and cytotoxic chemotherapy, induces viral lytic expression and cell killing in Epstein-Barr virus-positive (EBV+) or human herpesvirus-8-positive (HHV-8+) tumors, and reactivates latent human immunodeficiency virus (HIV) for possible eradication by combination antiretroviral therapy (cART). We performed a phase I trial of VOR given with R-based infusional EPOCH (etoposide, prednisone, vincristine, cyclophosphamide, and doxorubicin hydrochloride) (n = 12) and cART in aggressive HIV-associated B-cell non-Hodgkin lymphoma (NHL) in order to identify safe dosing and schedule. VOR (300 or 400 mg) was given orally on days 1 to 5 with each cycle of R-EPOCH for 10 high-risk patients with diffuse large B-cell lymphoma (1 EBV+), 1 EBV+/HHV-8+ primary effusion lymphoma, and 1 unclassifiable NHL. VOR was escalated from 300 to 400 mg using a standard 3 + 3 design based on dose-limiting toxicity observed in cycle 1 of R-EPOCH. The recommended phase II dose of VOR was 300 mg, with dose-limiting toxicity in 2 of 6 patients at 400 mg (grade 4 thrombocytopenia, grade 4 neutropenia), and 1 of 6 treated at 300 mg (grade 4 sepsis from tooth abscess). Neither VOR, nor cART regimen, significantly altered chemotherapy steady-state concentrations. VOR chemotherapy did not negatively impact CD4+ cell counts or HIV viral loads, which decreased or remained undetectable in most patients during treatment. The response rate in high-risk patients with NHL treated with VOR(R)-EPOCH was 100% (complete 83% and partial 17%) with a 1-year event-free survival of 83% (95% confidence interval, 51.6%-97.9%). VOR combined with R-EPOCH was tolerable and seemingly efficacious in patients with aggressive HIV-NHL

Analysis of Climate Policy Targets under Uncertainty

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).Although policymaking in response to the climate change is essentially a challenge of risk management, most studies of the relation of emissions targets to desired climate outcomes are either deterministic or subject to a limited representation of the underlying uncertainties. Monte Carlo simulation, applied to the MIT Integrated Global System Model (an integrated economic and earth system model of intermediate complexity), is used to analyze the uncertain outcomes that flow from a set of century-scale emissions targets developed originally for a study by the U.S. Climate Change Science Program. Results are shown for atmospheric concentrations, radiative forcing, sea ice cover and temperature change, along with estimates of the odds of achieving particular target levels, and for the global costs of the associated mitigation policy. Comparison with other studies of climate targets are presented as evidence of the value, in understanding the climate challenge, of more complete analysis of uncertainties in human emissions and climate system response.This study received support from the MIT Joint Program on the Science and Policy of Global Change, which is funded by a consortium of government, industry and foundation sponsors

Reconciling gene expression data with regulatory network models

The reconstruction of genome-scale metabolic models from genome annotations has become a routine practice in Systems Biology research. The potential of metabolic models for predictive biology is widely accepted by the scientific community, but these same models still lack the capability to account for the effect of gene regulation on metabolic activity. Our focus organism, Bacillus subtilis is most commonly found in soil, being subject to a wide variety of external environmental conditions. This reinforces the importance of the regulatory mechanisms that allow the bacteria to survive and adapt to such conditions. We introduce a manually curated regulatory network for Bacillus subtilis, tapping into the notable resources for B. subtilis regulation. We propose the concept of Atomic Regulon, as a set of genes that share the same ON and OFF gene expression profile across multiple samples of experimental data. Atomic regulon inference uses prior knowledge from curated SEED subsystems, in addition to expression data to infer regulatory interactions. We show how atomic regulons for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how atomic regulons can be used to help expand/ validate the knowledge of the regulatory networks and gain insights into novel biology

Reconciling gene expression data with regulatory network models – a stimulon-based approach for integrated metabolic and regulatory modeling of Bacillus subtilis

The reconstruction of genome-scale metabolic models from genome annotations has become a routine practice in Systems Biology research. The potential of metabolic models for predictive biology is widely accepted by the scientific community, but these same models still lack the capability to account for the effect of gene regulation on metabolic activity. Our focus organism, Bacillus subtilis is most commonly found in soil, being subject to a wide variety of external environmental conditions. This reinforces the importance of the regulatory mechanisms that allow the bacteria to survive and adapt to such conditions. Existing integrated metabolic regulatory models are currently available for only a small number of well-known organisms (e.g E. coli and B. subtilis). The E. coli integrated model was proposed by Covert et al in 2004 and has slowly improved over the years. Goelzer et al. introduced the B. subtilis integrated model in 2008, covering only the central metabolic pathways. Different strategies were used in the two modeling efforts. The E. coli model is defined by a set of Boolean rules (turning genes ON and OFF) accounting mostly for transcription factors, gene interactions, involved metabolites, and some external conditions such as heat shock. The B. subtilis model introduces a set of more complex rules and also incorporates sigma factor activity into the modeling abstraction. Here we propose a genome-scale model for the regulatory network of B. subtilis, using a new stimulon-based approach. A stimulon is defined as the set of genes (that can be a part of the same operon(s) and regulon(s)) that respond in the same set of stimuli. The proposed stimulon-based approach allows for the inclusion of more types of regulation in the model. This methodology also abstracts away much of the complexity of regulatory mechanisms by directly connecting the activity of genes to the presence or absence of associated stimuli, a necessity in the many cases where details of regulatory mechanisms are poorly understood. Our model integrates regulatory network data from the Goelzer et al model, in addition to other available literature data. We then reconciled our model against a large set of high-quality gene expression data (tiled microarrays for 104 different conditions). The stimulons in our model were split or extended to improve consistency with our expression data, and the stimuli in our model were adjusted to improve consistency with the conditions of our expression experiments. The reconciliation with gene expression data revealed a significant number of exact or nearly exact matches between the manually curated regulons/stimulons and pure correlation-based regulons. Our reconciliation analysis of the 2011 SubtiWiki regulon release suggested many gene candidates for regulon extension that were subsequently included in the 2013 SubtiWiki update. Our enhanced model also includes an improved coverage of a wide range of different stress conditions. We then integrated our regulatory model with the latest metabolic reconstruction for B. subtilis, the iBsu1103V2 model (Tanaka et al. 2012). We applied this integrated metabolic regulatory model to the simulation of all growth phenotype data currently available for B. subtilis, demonstrating how the addition of regulatory constraints improved consistency of model predictions with experimentally observed phenotype data. This analysis of growth phenotype data unveiled phenotypes that could only be characterized with the addition of regulatory network constraints. All tools applied in the reconstruction, simulation, and curation of our new regulatory model are now publicly available as a part of the KBase framework. These tools permit the direct simulation of gene expression data using the regulon model alone, as well as the simulation of phenotypes and growth conditions using an integrated metabolic and regulatory model. We will highlight these new tools in the context of our reconstruction and analysis of the B. subtilis regulatory model