Diversity in the Heartland of America: The Impact on Human Development in Indiana

This article is the third in a series of studies measuring the impact of cultural diversity on human development. We disaggregate cultural diversity into three components: ethnicity, language, and religion. The first study examined the impact of diversity internationally. We found that countries are worse off with greater diversity, especially religious diversity; however, we found that more-prosperous countries with strong institutions benefited from increased diversity. We concluded that strong institutions are essential to maximize the benefits of diversity while mitigating the associated costs. The second study examined the impact of diversity within the United States, where institutional strength was assumed to be relatively great and similar between states. We found an overall negative impact from diversity. Ethnic diversity was negatively associated with human development, while religious and language diversity had a positive impact. We concluded that in the United States, there is more tolerance for religious and language differences compared to ethnic differences. In this third study, we examine the impact of diversity within the state of Indiana. As with our national results, we find a generally negative relationship between human development and diversity. Ethnic diversity has a negative impact, while religious and language diversity are generally positive influences. Strong political and legal institutions may not be sufficient to extract net benefits from diversity if social attitudes that guide behavior are not supportive. The results suggest that net benefits from diversity in Indiana may depend on improvement of social attitudes and in commitment to social services that support historically disadvantaged minority groups

Data-Mining a Large Digital Sky Survey: From the Challenges to the Scientific Results

The analysis and an efficient scientific exploration of the Digital Palomar Observatory Sky Survey (DPOSS) represents a major technical challenge. The input data set consists of 3 Terabytes of pixel information, and contains a few billion sources. We describe some of the specific scientific problems posed by the data, including searches for distant quasars and clusters of galaxies, and the data-mining techniques we are exploring in addressing them. Machine-assisted discovery methods may become essential for the analysis of such multi-Terabyte data sets. New and future approaches involve unsupervised classification and clustering analysis in the Giga-object data space, including various Bayesian techniques. In addition to the searches for known types of objects in this data base, these techniques may also offer the possibility of discovering previously unknown, rare types of astronomical objects.Comment: Invited paper, to appear in Applications of Digital Image Processing XX, ed. A. Tescher, Proc. S.P.I.E. vol. 3164, in press; 10 pages, a self-contained TeX file, and 3 separate postscript figure

Cultural Diversity in the United States and Its Impact on Human Development

Previous studies have yielded mixed results on the impact of cultural diversity on economic performance. We find a positive relationship in the United States between cultural diversity and a comprehensive measure of human development that incorporates health, education, and income. We also disaggregate cultural diversity into three components including ethnicity, language, and religion. We find a positive relationship between human development and both religious and language diversity, and a negative relationship with ethnic diversity. These relationships are robust, using several alternative mathematical measures of diversity. Our results are consistent with diversity generating benefits from exposure to a variety of experiences, ideas, and skills while introducing costs due to difficulty in communication, difference in preferences, and conflict between polarized groups. We conclude that strong institutions are essential to maximize the benefits of diversity while mitigating the associated costs

Using machine learning techniques to automate sky survey catalog generation

We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomar Observatory Sky Survey provides comprehensive photographic coverage of the northern celestial hemisphere. The photographic plates are being digitized into images containing on the order of 10(exp 7) galaxies and 10(exp 8) stars. Since the size of this data set precludes manual analysis and classification of objects, our approach is to develop a software system which integrates independently developed techniques for image processing and data classification. Image processing routines are applied to identify and measure features of sky objects. Selected features are used to determine the classification of each object. GID3* and O-BTree, two inductive learning techniques, are used to automatically learn classification decision trees from examples. We describe the techniques used, the details of our specific application, and the initial encouraging results which indicate that our approach is well-suited to the problem. The benefits of the approach are increased data reduction throughput, consistency of classification, and the automated derivation of classification rules that will form an objective, examinable basis for classifying sky objects. Furthermore, astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems given automatically cataloged data

Issues in knowledge representation to support maintainability: A case study in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and runtime estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks. Because the scientific data processing modules (called fittings) evolve to match scientists' needs, issues regarding maintainability are of prime importance in PIPE. This paper describes the PIPE system and describes how issues in maintainability affected the knowledge representation used in PIPE to capture knowledge about the behavior of fittings

Intelligent assistance in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and run time estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks

Discovery Prospects for a Supernova Signature of Biogenic Origin

Approximately 2.8 Myr before the present our planet was subjected to the debris of a supernova explosion. The terrestrial proxy for this event was the discovery of live atoms of 60Fe in a deep-sea ferromanganese crust. The signature for this supernova event should also reside in magnetite Fe3O4 microfossils produced by magnetotactic bacteria extant at the time of the Earth-supernova interaction, provided the bacteria preferentially uptake iron from fine-grained iron oxides and ferric hydroxides. Using estimates for the terrestrial supernova 60Fe flux, combined with our empirically derived microfossil concentrations in a deep-sea drill core, we deduce a conservative estimate of the ^{60}{Fe} fraction as 60Fe/Fe ~ 3.6 x 10^{-15}. This value sits comfortably within the sensitivity limit of present accelerator mass spectrometry capabilities. The implication is that a biogenic signature of this cosmic event is detectable in the Earth's fossil record.Comment: As it appears in Icaru

Bright Spots: Physical activity investments that work : Active for health Rotherham; Be active to stay healthy

Programme card: Active for Health Rotherham, Be active to stay healthy Country/locality/coverage Rotherham, South Yorkshire, United Kingdom which has an estimated population over 262,000. Target population People living in Rotherham with one or more of the following seven long term conditions; Cardiac, heart failure, stroke, COPD, cancer, lower back pain and a recent fall and/or fracture. What modes/types/domains of physical activity does the program promote? Functional physical activity delivered in community venues aimed at improving rehabilitation and recovery. Which of the 7 best investments the program addresses? Community wide programs and Healthcare What sectors does it involve? The project involves health professionals and exercise specialists by developing a pathway that bridges the gap between National Health Service (NHS) rehabilitation and community physical activity opportunities. Estimated program reach The programme reaches over 1000 patients a year, improving their health and wellbeing. At the time of this publication, 695 patients had registered for the programme and consented to participate in the evaluation. What is special about this program? The programme aims to revolutionise the role that physical activity plays in rehabilitation and recovery, by providing safe, effective and quality assured services in local communities resulting in notable improvements in health and wellbeing. Key programme details Programme website www.rotherhamgetactive.co.uk/activeforhealth #activeforhealth www.facebook.com/activeforhealth

Long-range energy transport in photosystem II.

We simulate the long-range inter-complex electronic energy transfer in photosystem II-from the antenna complex, via a core complex, to the reaction center-using a non-Markovian (ZOFE) quantum master equation description that allows the electronic coherence involved in the energy transfer to be explicitly included at all length scales. This allows us to identify all locations where coherence is manifested and to further identify the pathways of the energy transfer in the full network of coupled chromophores using a description based on excitation probability currents. We investigate how the energy transfer depends on the initial excitation-localized, coherent initial excitation versus delocalized, incoherent initial excitation-and find that the overall energy transfer is remarkably robust with respect to such strong variations of the initial condition. To explore the importance of vibrationally enhanced transfer and to address the question of optimization in the system parameters, we systematically vary the strength of the coupling between the electronic and the vibrational degrees of freedom. We find that the natural parameters lie in a (broad) region that enables optimal transfer efficiency and that the overall long-range energy transfer on a ns time scale appears to be very robust with respect to variations in the vibronic coupling of up to an order of magnitude. Nevertheless, vibrationally enhanced transfer appears to be crucial to obtain a high transfer efficiency, with the latter falling sharply for couplings outside the optimal range. Comparison of our full quantum simulations to results obtained with a "classical" rate equation based on a modified-Redfield/generalized-Förster description previously used to simulate energy transfer dynamics in the entire photosystem II complex shows good agreement for the overall time scales of excitation energy transport

Procedural personas as critics for dungeon generation

This paper introduces a constrained optimization method which uses procedural personas to evaluate the playability and quality of evolved dungeon levels. Procedural personas represent archetypical player behaviors, and their controllers have been evolved to maximize a specific utility which drives their decisions. A “baseline” persona evaluates whether a level is playable by testing if it can survive in a worst-case scenario of the playthrough. On the other hand, a Monster Killer persona or a Treasure Collector persona evaluates playable levels based on how many monsters it can kill or how many treasures it can collect, respectively. Results show that the implemented two-population genetic algorithm discovers playable levels quickly and reliably, while the different personas affect the layout, difficulty level and tactical depth of the generated dungeons.The research was supported, in part, by the FP7 ICT project C2Learn (project no: 318480) and by the FP7 Marie Curie CIG project AutoGameDesign (project no: 630665).peer-reviewe