2,591 research outputs found

    Geometric Phase in Eigenspace Evolution of Invariant and Adiabatic Action Operators

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    The theory of geometric phase is generalized to a cyclic evolution of the eigenspace of an invariant operator with NN-fold degeneracy. The corresponding geometric phase is interpreted as a holonomy inherited from the universal connection of a Stiefel U(N)-bundle over a Grassmann manifold. Most significantly, for an arbitrary initial state, this geometric phase captures the inherent geometric feature of the state evolution. Moreover, the geometric phase in the evolution of the eigenspace of an adiabatic action operator is also addressed, which is elaborated by a pullback U(N)-bundle. Several intriguing physical examples are illustrated.Comment: Added Refs. and corrected typos; 4 page

    High-throughput profiling and analysis of plant responses over time to abiotic stress

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    Sorghum (Sorghum bicolor (L.) Moench) is a rapidly growing, high-biomass crop prized for abiotic stress tolerance. However, measuring genotype-by-environment (G x E) interactions remains a progress bottleneck. We subjected a panel of 30 genetically diverse sorghum genotypes to a spectrum of nitrogen deprivation and measured responses using high-throughput phenotyping technology followed by ionomic profiling. Responses were quantified using shape (16 measurable outputs), color (hue and intensity), and ionome (18 elements). We measured the speed at which specific genotypes respond to environmental conditions, in terms of both biomass and color changes, and identified individual genotypes that perform most favorably. With this analysis, we present a novel approach to quantifying colorbased stress indicators over time. Additionally, ionomic profiling was conducted as an independent, low-cost, and high-throughput option for characterizing G x E, identifying the elements most affected by either genotype or treatment and suggesting signaling that occurs in response to the environment. This entire dataset and associated scripts are made available through an open-access, user-friendly, web-based interface. In summary, this work provides analysis tools for visualizing and quantifying plant abiotic stress responses over time. These methods can be deployed as a time-efficient method of dissecting the genetic mechanisms used by sorghum to respond to the environment to accelerate crop improvement

    Recent Developments in the Design, Capabilities and Autonomous Operations of a Lightweight Surface Manipulation System and Test-bed

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    The first generation of a versatile high performance device for performing payload handling and assembly operations on planetary surfaces, the Lightweight Surface Manipulation System (LSMS), has been designed and built. Over the course of its development, conventional crane type payload handling configurations and operations have been successfully demonstrated and the range of motion, types of operations and the versatility greatly expanded. This enhanced set of 1st generation LSMS hardware is now serving as a laboratory test-bed allowing the continuing development of end effectors, operational techniques and remotely controlled and automated operations. This paper describes the most recent LSMS and test-bed development activities, that have focused on two major efforts. The first effort was to complete a preliminary design of the 2nd generation LSMS that has the capability for limited mobility and can reposition itself between lander decks, mobility chassis, and fixed base locations. A major portion of this effort involved conducting a study to establish the feasibility of, and define, the specifications for a lightweight cable-drive waist joint. The second effort was to continue expanding the versatility and autonomy of large planetary surface manipulators using the 1st generation LSMS as a test-bed. This has been accomplished by increasing manipulator capabilities and efficiencies through both design changes and tool and end effector development. A software development effort has expanded the operational capabilities of the LSMS test-bed to include; autonomous operations based on stored paths, use of a vision system for target acquisition and tracking, and remote command and control over a communications bridge

    Early Stage Breast Cancer and Its Association with Diet and Exercise-Related Perceptions and Behaviors to Prevent Recurrence

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    Background The favorable prognosis for early stage breast cancer survivors may be a reason for the minimal research regarding their quality of life. Prior research has observed more long-term weight gain among early stage survivors compared to cancer-free women of a similar age. It would be useful to study survivors’ perceptions and reported behaviors regarding diet and exercise to see if there is a correlation with previous studies. Methods A sample of 700 breast cancer survivors from Ohio and Michigan was randomly selected from the Northwest Ohio affiliate of the Susan G. Komen For the Cure mailing list and sent a survey for completion. Results 389 survivors completed the survey and among Stage 1 (50/197 = 25.4%) and Stage 2 survivors (24/105 = 22.9%), a small proportion had a positive correlation between self-reported dietary behaviors and their perceived benefits of eating fruits and vegetables. Similar correlations were observed between their self-reported exercise behaviors and their perceived benefits of exercise (Stage 1: 36/197 = 18.3%, Stage 2: 18/105 = 17.1%). Conclusions Regardless of stage, a small proportion of survivors’ self-reported dietary and exercise behaviors match their perceived benefits of diet and exercise. Factors such as access, motivation, and lack of co-morbidities among early stage survivors may prevent them from living healthier post-diagnosis. More thorough dietary and clinical measurements will provide greater certainty. Thus, innovative, sustainable programs must be accessible and provide motivation and social support from family, friends, and other survivors to truly improve quality of life

    Increased signal-to-noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components

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    Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is deter-mined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create microtreatments throughout the field. In addition, the variation within different soil properties is often nonrandomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome, and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a method with which sources of environmental variation in field data can be identified and adjusted, improving our ability to resolve effects of interest and to quantify subtle phenotypes

    Prevalence of filarioid nematodes and trypanosomes in American robins and house sparrows, Chicago USA

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    AbstractHosts are commonly infected with a suite of parasites, and interactions among these parasites can affect the size, structure, and behavior of host–parasite communities. As an important step to understanding the significance of co-circulating parasites, we describe prevalence of co-circulating hemoparasites in two important avian amplification hosts for West Nile virus (WNV), the American robin (Turdus migratorius) and house sparrow (Passer domesticus), during the 2010–2011 in Chicago, Illinois, USA. Rates of nematode microfilariemia were 1.5% of the robins (n=70) and 4.2% of the house sparrows (n=72) collected during the day and 11.1% of the roosting robins (n=63) and 0% of the house sparrows (n=11) collected at night. Phylogenetic analysis of nucleotide sequences of the 18S rRNA and cytochrome oxidase subunit I (COI) genes from these parasites resolved two clades of filarioid nematodes. Microscopy revealed that 18.0% of American robins (n=133) and 16.9% of house sparrows (n=83) hosted trypanosomes in the blood. Phylogenetic analysis of nucleotide sequences from the 18s rRNA gene revealed that the trypanosomes fall within previously described avian trypanosome clades. These results document hemoparasites in the blood of WNV hosts in a center of endemic WNV transmission, suggesting a potential for direct or indirect interactions with the virus

    An automated, high-throughput method for standardizing image color profiles to improve image-based plant phenotyping

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    High-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up of tuples of data called pixels, which consist of R, G, and B values, arranged in a grid. Many factors, for example image brightness, can influence the quality of the image that is captured. These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. Here, we provide an automated method to adjust an image-based dataset so that brightness, contrast, and color profile is standardized. The correction method is a collection of linear models that adjusts pixel tuples based on a reference panel of colors. We apply this technique to a set of images taken in a high-throughput imaging facility and successfully detect variance within the image dataset. In this case, variation resulted from temperature-dependent light intensity throughout the experiment. Using this correction method, we were able to standardize images throughout the dataset, and we show that this correction enhanced our ability to accurately quantify morphological measurements within each image. We implement this technique in a high-throughput pipeline available with this paper, and it is also implemented in PlantCV

    LitMiner: integration of library services within a bio-informatics application

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    BACKGROUND: This paper examines how the adoption of a subject-specific library service has changed the way in which its users interact with a digital library. The LitMiner text-analysis application was developed to enable biologists to explore gene relationships in the published literature. The application features a suite of interfaces that enable users to search PubMed as well as local databases, to view document abstracts, to filter terms, to select gene name aliases, and to visualize the co-occurrences of genes in the literature. At each of these stages, LitMiner offers the functionality of a digital library. Documents that are accessible online are identified by an icon. Users can also order documents from their institution's library collection from within the application. In so doing, LitMiner aims to integrate digital library services into the research process of its users. METHODS: Case study RESULTS: This integration of digital library services into the research process of biologists results in increased access to the published literature. CONCLUSION: In order to make better use of their collections, digital libraries should customize their services to suit the research needs of their patrons
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