48 research outputs found

    The CIA : the struggle between national security and democracy

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    RMP Capital Corp- an In-House IT Solution

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    MBAT: A scalable informatics system for unifying digital atlasing workflows

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    Abstract Background Digital atlases provide a common semantic and spatial coordinate system that can be leveraged to compare, contrast, and correlate data from disparate sources. As the quality and amount of biological data continues to advance and grow, searching, referencing, and comparing this data with a researcher's own data is essential. However, the integration process is cumbersome and time-consuming due to misaligned data, implicitly defined associations, and incompatible data sources. This work addressing these challenges by providing a unified and adaptable environment to accelerate the workflow to gather, align, and analyze the data. Results The MouseBIRN Atlasing Toolkit (MBAT) project was developed as a cross-platform, free open-source application that unifies and accelerates the digital atlas workflow. A tiered, plug-in architecture was designed for the neuroinformatics and genomics goals of the project to provide a modular and extensible design. MBAT provides the ability to use a single query to search and retrieve data from multiple data sources, align image data using the user's preferred registration method, composite data from multiple sources in a common space, and link relevant informatics information to the current view of the data or atlas. The workspaces leverage tool plug-ins to extend and allow future extensions of the basic workspace functionality. A wide variety of tool plug-ins were developed that integrate pre-existing as well as newly created technology into each workspace. Novel atlasing features were also developed, such as supporting multiple label sets, dynamic selection and grouping of labels, and synchronized, context-driven display of ontological data. Conclusions MBAT empowers researchers to discover correlations among disparate data by providing a unified environment for bringing together distributed reference resources, a user's image data, and biological atlases into the same spatial or semantic context. Through its extensible tiered plug-in architecture, MBAT allows researchers to customize all platform components to quickly achieve personalized workflows

    Adding Value to Crop Production Systems by Integrating Forage Cover Crop Grazing

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    In addition to their value as cereal grains, wheat (Triticum aestivum L.) and triticale (× Triticosecale Wittmack) are important cool-season annual forages and cover crops. Yearling steer (Bos taurus) performance was compared in the spring following autumn establishment as for age cover crops after soybean [Glycine max (L.) Merr.] grain harvest. Replicated pastures (0.4 ha) were no-till seeded in three consecutive years into soybean stubble in autumn, fertilized, and grazed the following spring near Ithaca, Nebraska, USA. Each pasture (n = 3) was continuously stocked in spring with four yearling steers (380 ± 38 kg) for 17, 32, and 28 d in 2005, 2006, and 2007, respectively. In 2005, average daily gain (ADG) for steers grazing triticale exceeded the ADG for wheat by 0.31 kghd−1d−1. In 2006, wheat ADG exceeded that for triticale by 0.12 kghd−1d−1. In 2007, steers grazing wheat lost weight, while steers grazing triticale gained 0.20 kghd−1d−1. Based on the 3-year average animal gains valued at 1.32kg−1,meannetreturn(1.32 kg−1, mean net return ( ha−1yr−1) was 62.15fortriticaleand62.15 for triticale and 22.55 for wheat. Since these grazed cover crops provide ecosystem services in addition to forage, grazing could be viewed as a mechanism for recovering costs and adds additional value to the system. Based on this 3-year grazing trial, triticale was superior to wheat and likely will provide the most stable beef yearling performance across years with variable weather for the western Cornbelt USA

    Variation and Change Over Time in PROMIS-29 Survey Results Among Primary Care Patients With Type 2 Diabetes

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    Purpose: We sought to describe results of patient-reported outcome measures implemented among primary care patients with diabetes and explore factors associated with changes in scores over time. Methods: Two organizations serving diverse patient populations collected the PROMIS-29 survey at baseline and 3-month follow-up for patients with type 2 diabetes. Bayesian regression analysis was used to examine the relationship between patient characteristics and changes in PROMIS-29 scores. Exploratory analyses assessed relationships between goal-setting and changes in scores. Results: The study population reported substantially more problems with physical functioning (mean: 42.5 at Site 1 and 38.9 at Site 2) and pain interference (mean: 58.0 at Site 1 and 61.1 at Site 2) compared to the general population (mean: 50; standard deviation: 10). At least 33% of patients had a clinically meaningful change (ie, at least half the standard deviation, or 5 points) in each PROMIS domain. For pain interference, 55% had no change, 22% improved by 5 or more points, and 23% worsened by 5 or more points. Bayesian regression analyses suggest that chronic conditions, insurance status, and Hispanic ethnicity are likely associated with decreased functioning over time. Exploratory analyses found that setting a mental health goal did not appear to be associated with improvement for anxiety or depression. Conclusions: Use of patient-reported outcome measures in routine clinical care identified areas of functional limitations among people with diabetes. However, changes in participants’ PROMIS-29 scores over time were minimal. Research is needed to understand patterns of change in global and domain-specific functioning, particularly among racial/ethnic minorities
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