MAARSS: Magnet Architectures and Active Radiation Shielding Study

Protecting humans from space radiation is a major hurdle for human exploration of the solar system and beyond. Like on Earth, large magnetic fields surrounding a spaceship would deflect charged particles away from the habitat region and reduce the radiation dose to acceptable limits. The objective of this study is to determine the feasibility of current state of the art (SOA) high temperature superconducting (HTS) magnets as a means to protect crew from space radiation exposure on long duration missions beyond Low Earth Orbit (LEO). The study will look at architecture concepts to deflect high energy Galactic Cosmic Radiation (GCR) and Solar Proton Events (SPEs). Mass, power, and shielding efficiency will be considered and compared with current passive shielding capabilities. This report will walk the reader through several designs considered over the one year study and discuss the multiple parameters that should be evaluated for magnetic shielding. The study team eventually down-selects to a scalable light weight solenoid architecture that is launchable and then deployable using magnetic pressure to expand large diameter coils. Benefitting from the low temperature and high vacuum environment of deep space, existing high-temperature superconductors make such radiation shields realistic, near-term technical developments

Magnet Architectures and Active Radiation Shielding Study - SR2S Workshop

Analyze new coil configurations with maturing superconductor technology -Develop vehicle-level concept solutions and identify engineering challenges and risks -Shielding performance analysis Recent advances in superconducting magnet technology and manufacturing have opened the door for re-evaluating active shielding solutions as an alternative to mass prohibitive passive shielding.Publications on static magnetic field environments and its bio-effects were reviewed. Short-term exposure information is available suggesting long term exposure may be okay. Further research likely needed. center dotMagnetic field safety requirements exist for controlled work environments. The following effects have been noted with little noted adverse effects -Magnetohydrodynamic (MHD) effects on ionized fluids (e.g. blood) creating an aortic voltage change -MHD interaction elevates blood pressure (BP) center dot5 Tesla equates to 5% BP elevation -Prosthetic devises and pacemakers are an issue (access limit of 5 gauss)

Rainfall variability at decadal and longer time scales: signal or noise?

Rainfall variability occurs over a wide range of temporal scales. Knowledge and understanding of such variability can lead to improved risk management practices in agricultural and other industries. Analyses of temporal patterns in 100 yr of observed monthly global sea surface temperature and sea level pressure data show that the single most important cause of explainable, terrestrial rainfall variability resides within the El Nino-Southern Oscillation (ENSO) frequency domain (2.5-8.0 yr), followed by a slightly weaker but highly significant decadal signal (9-13 yr), with some evidence of lesser but significant rainfall variability at interclecadal time scales (15-18 yr). Most of the rainfall variability significantly linked to frequencies tower than ENSO occurs in the Australasian region, with smaller effects in North and South America, central and southern Africa, and western Europe. While low-frequency (LF) signals at a decadal frequency are dominant, the variability evident was ENSO-like in all the frequency domains considered. The extent to which such LF variability is (i) predictable and (ii) either part of the overall ENSO variability or caused by independent processes remains an as yet unanswered question. Further progress can only be made through mechanistic studies using a variety of models

An ontology approach to comparative phenomics in plants

BACKGROUND: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. RESULTS: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. CONCLUSIONS: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics that enhances the utility of model genetic organisms and can be readily applied to species with fewer genetic resources and less well-characterized genomes. In addition, these tools should enhance future efforts to explore the relationships among phenotypic similarity, gene function, and sequence similarity in plants, and to make genotype-to-phenotype predictions relevant to plant biology, crop improvement, and potentially even human health.This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at [email protected]

Interactive Actor Analysis for Rural Water Management in The Netherlands

Recent developments in the policy sciences emphasize the social environment in which decisions are made. The ‘network metaphor’ is often used to describe the key role of interactions between interdependent actors involved in decision making. These interactions take place in a policy arena drawn up by actors with an interest in and control over decisions on the issues addressed. Interdependencies, caused by the need for actors to increase their means of realizing objectives, are the driving force behind these interactions. Dependency relations are of special interest to water management and river basin management because of the fundamental asymmetrical interdependencies that exist in river basins between upstream and downstream stakeholders. Coleman’s linear system of action models decision making process involving dependencies between multiple stakeholders as exchange of control over issues, while interactions are required to negotiate exchanges of control. We developed an interactive method for actor analysis based on Coleman’s linear system of action and applied it to the national rural water management policy domain in The Netherlands. The method is firmly rooted in mathematical sociology and defies the criticism that methods for actor and stakeholder analysis do not specify a theoretical basis explaining the causal relations between the variables analyzed and policy change. With the application to the rural water management policy arena we intended to increase our insight into the practical applicability of this analyticmethod in an interactive workshop, the acceptability of the approach for the participating actors, its contribution to the process of decision making and our understanding of the rural water management policy arena in The Netherlands. We found that the Association of Water Authorities, the Ministry of Public Works and the Ministry of Agriculture are the most powerful actor in the policy domain, while governance and cost and benefits of rural water management are the most salient issues. Progress in policy development for rural water management is probably most promising for the issues governance, costs and benefits, safety and rural living conditions through improved interaction between the Association of Water Authorities, the Ministry of Agriculture and the Rural Credit Bank. Besides these analytic results the interactive approach implemented increased the participants understanding of their dependency on other actors in the rural water management policy domain and supported them in developing a sound perspective on their dependency position. We concluded that the method developed is acceptable to real-world policy decision makers, can successfully be applied in an interactive setting, potentially contributes to the process of decision making by increasing the participants understanding of their dependency position, has the potential to delivers valuable advice for future decision-making and increases our understanding of policy development for rural water management in general

An ontology approach to comparative phenomics in plants

BACKGROUND: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework. RESULTS: We developed a workflow to curate and standardize existing phenotype datasets for six plant species, encompassing both model species and crop plants with established genetic resources. Our effort focused on mutant phenotypes associated with genes of known sequence in Arabidopsis thaliana (L.) Heynh. (Arabidopsis), Zea mays L. subsp. mays (maize), Medicago truncatula Gaertn. (barrel medic or Medicago), Oryza sativa L. (rice), Glycine max (L.) Merr. (soybean), and Solanum lycopersicum L. (tomato). We applied the same ontologies, annotation standards, formats, and best practices across all six species, thereby ensuring that the shared dataset could be used for cross-species querying and semantic similarity analyses. Curated phenotypes were first converted into a common format using taxonomically broad ontologies such as the Plant Ontology, Gene Ontology, and Phenotype and Trait Ontology. We then compared ontology-based phenotypic descriptions with an existing classification system for plant phenotypes and evaluated our semantic similarity dataset for its ability to enhance predictions of gene families, protein functions, and shared metabolic pathways that underlie informative plant phenotypes. CONCLUSIONS: The use of ontologies, annotation standards, shared formats, and best practices for cross-taxon phenotype data analyses represents a novel approach to plant phenomics that enhances the utility of model genetic organisms and can be readily applied to species with fewer genetic resources and less well-characterized genomes. In addition, these tools should enhance future efforts to explore the relationships among phenotypic similarity, gene function, and sequence similarity in plants, and to make genotype-to-phenotype predictions relevant to plant biology, crop improvement, and potentially even human health

The Rise of Multiple-Measures Rules in the House of Representatives

Through most of the modern partisan era, the House Rules Committee adhered to a norm of One Measure, One Rule. Starting in the 1990s, majorities violated this norm on rare occasions, but after 2010, multiple-measures rules became commonplace. This paper argues that multiple, sometimes competing objectives—majority messaging, member position-taking opportunities, and managing limited floor time—motivate the majority’s use of this creative rule. Bills in multiple-measures rules since 2010 have been more majority-unifying and divisive between the parties, and bills appear more in these rules as some time constraints increase. Bills sponsored by rank-and-file members, as compared to committee chairs, are also more likely to be included in multiple-measures packages. A special case of the multiple-measures rule, the bifurcated rule, also governs measures with heightened partisan conflict, and it allows the majority to navigate coalition problems creatively under certain conditions. The multiple-measures trend highlights how the majority continues to evolve special rules to pursue multiple goals under constraints, and it raises important questions about the way these tactics limit floor consideration of procedure

How Congressional Leaders Define Loyalty: Validating US House Party Voting Scores with Party Leadership Records

Measures of party unity are commonplace in the study of legislative voting, particularly in assessments of party influence. Scholars have employed a range of measures in studying loyalty and reward in the U.S. House, but all are proxies for the scores that House party leaders construct for their own processes. These loyalty scores have never been examined in empirical scholarship. Drawing on archived leadership records, I construct leader loyalty scores for House Democrats in the 1970s and 1980s based on leadership-selected key votes in each session. I show that the content of the leader lists was very sensitive to political context as the leadership responded to short-term challenges, but in the aggregate, leader loyalty scores are closely related over time to other indicators. As predictors of party rewards—in the form of committee posts and legislative success—the leadership’s measure provides some clearer evidence of reward, particularly in comparison to conventional party unity scores