3,311 research outputs found

    \u3ci\u3eIxodes Dentatus\u3c/i\u3e (Acari: Ixodidae) in Michigan: First State Records and Occurrence on a Human

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    An Ixodes dentatus adult female was taken from a cottontail rabbit in Kalamazoo County, and a nymph from a child in Berrien County, in 1992 in Michigan. These findings represent the first records of I.dentatus in the state, and document an unusual parasitization of a human being by this species of tick

    Actor-Critic Policy Learning in Cooperative Planning

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    In this paper, we introduce a method for learning and adapting cooperative control strategies in real-time stochastic domains. Our framework is an instance of the intelligent cooperative control architecture (iCCA)[superscript 1]. The agent starts by following the "safe" plan calculated by the planning module and incrementally adapting its policy to maximize the cumulative rewards. Actor-critic and consensus-based bundle algorithm (CBBA) were employed as the building blocks of the iCCA framework. We demonstrate the performance of our approach by simulating limited fuel unmanned aerial vehicles aiming for stochastic targets. In one experiment where the optimal solution can be calculated, the integrated framework boosted the optimality of the solution by an average of %10, when compared to running each of the modules individually, while keeping the computational load within the requirements for real-time implementation.Boeing Scientific Research LaboratoriesUnited States. Air Force Office of Scientific Research (Grant FA9550-08-1-0086

    ACATALASEMIC MICE

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    Independent evaluation of a simple clinical prediction rule to identify right ventricular dysfunction in patients with shortness of breath

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    BACKGROUND: Many patients have unexplained persistent dyspnea after negative computed tomographic pulmonary angiography (CTPA). We hypothesized that many of these patients have isolated right ventricular (RV) dysfunction from treatable causes. We previously derived a clinical decision rule (CDR) for predicting RV dysfunction consisting of persistent dyspnea and normal CTPA, finding that 53% of CDR-positive patients had isolated RV dysfunction. Our goal is to validate this previously derived CDR by measuring the prevalence of RV dysfunction and outcomes in dyspneic emergency department patients. METHODS: A secondary analysis of a prospective observational multicenter study that enrolled patients presenting with suspected PE was performed. We included patients with persistent dyspnea, a nonsignificant CTPA, and formal echo performed. Right ventricular dysfunction was defined as RV hypokinesis and/or dilation with or without moderate to severe tricuspid regurgitation. RESULTS: A total of 7940 patients were enrolled. Two thousand six hundred sixteen patients were analyzed after excluding patients without persistent dyspnea and those with a significant finding on CTPA. One hundred ninety eight patients had echocardiography performed as standard care. Of those, 19% (95% confidence interval [CI], 14%-25%) and 33% (95% CI, 25%-42%) exhibited RV dysfunction and isolated RV dysfunction, respectively. Patients with isolated RV dysfunction or overload were more likely than those without RV dysfunction to have a return visit to the emergency department within 45 days for the same complaint (39% vs 18%; 95% CI of the difference, 4%-38%). CONCLUSION: This simple clinical prediction rule predicted a 33% prevalence of isolated RV dysfunction or overload. Patients with isolated RV dysfunction had higher recidivism rates and a trend toward worse outcomes

    Examining Periodic Solar Wind Density Structures Observed in the SECCHI Heliospheric Imagers

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    We present an analysis of small-scale, periodic, solar-wind density enhancements (length-scales as small as \approx 1000 Mm) observed in images from the Heliospheric Imager (HI) aboard STEREO A. We discuss their possible relationship to periodic fluctuations of the proton density that have been identified at 1 AU using in-situ plasma measurements. Specifically, Viall, Kepko, and Spence (2008) examined 11 years of in-situ solar-wind density measurements at 1 AU and demonstrated that not only turbulent structures, but also non-turbulent periodic density structures exist in the solar wind with scale sizes of hundreds to one thousand Mm. In a subsequent paper, Viall, Spence, and Kasper (2009) analyzed the {\alpha} to proton solar-wind abundance ratio measured during one such event of periodic density structures, demonstrating that the plasma behavior was highly suggestive that either temporally or spatially varying coronal source plasma created those density structures. Large periodic density structures observed at 1 AU, which were generated in the corona, can be observable in coronal and heliospheric white-light images if they possess sufficiently high density contrast. Indeed, we identify such periodic density structures as they enter the HI field of view and follow them as they advect with the solar wind through the images. The smaller periodic density structures that we identify in the images are comparable in size to the larger structures analyzed in-situ at 1 AU, yielding further evidence that periodic density enhancements are a consequence of coronal activity as the solar wind is formed.Comment: 15 pages, 12 figures. The final publication is available at http://www.springerlink.co

    Towards Emotion Recognition: A Persistent Entropy Application

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    Emotion recognition and classification is a very active area of research. In this paper, we present a first approach to emotion classification using persistent entropy and support vector machines. A topology-based model is applied to obtain a single real number from each raw signal. These data are used as input of a support vector machine to classify signals into 8 different emotions (calm, happy, sad, angry, fearful, disgust and surprised)

    Systems pharmacology assessment of the 5-fluorouracil pathway

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    To assess the impact of the 5-fluorouracil (5-FU) drug-pathway genes on cytotoxicity, and determine whether loss-of-function analyses coupled with functional assays can help prioritize pharmacogenomic candidate genes

    Does BCR/ABL1 positive Acute Myeloid Leukaemia Exist?

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    The BCR/ABL1 fusion gene, usually carried by the Philadelphia chromosome (Ph) resulting from t(9;22)(q34;q11) or variants, is pathognomonic for chronic myeloid leukaemia (CML). It is also occasionally found in acute lymphoblastic leukaemia (ALL) mostly in adults and rarely in de novo acute myeloid leukaemia (AML). Array Comparative Genomic Hybridization (aCGH) was used to study six Ph(+)AML, three bi-lineage and four Ph(+)ALL searching for specific genomic profiles. Surprisingly, loss of the IKZF1 and/or CDKN2A genes, the hallmark of Ph(+)ALL, were recurrent findings in Ph(+)AML and accompanied cryptic deletions within the immunoglobulin and T cell receptor genes. The latter two losses have been shown to be part of 'hot spot' genome imbalances associated with BCR/ABL1 positive pre-B lymphoid phenotype in CML and Ph(+)ALL. We applied Significance Analysis of Microarrays (SAM) to data from the 'hot spot' regions to the Ph(+)AML and a further 40 BCR/ABL1(+) samples looking for differentiating features. After exclusion of the most dominant markers, SAM identified aberrations unique to de novo Ph(+)AML that involved relevant genes. While the biological and clinical significance of this specific genome signature remains to be uncovered, the unique loss within the immunoglobulin genes provides a simple test to enable the differentiation of clinically similar de novo Ph(+) AML and myeloid blast crisis of CML. © 2013 John Wiley & Sons Ltd and Crown

    Active Learning in Persistent Surveillance UAV Missions

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    The performance of many complex UAV decision-making problems can be extremely sensitive to small errors in the model parameters. One way of mitigating this sensitivity is by designing algorithms that more effectively learn the model throughout the course of a mission. This paper addresses this important problem by considering model uncertainty in a multi-agent Markov Decision Process (MDP) and using an active learning approach to quickly learn transition model parameters. We build on previous research that allowed UAVs to passively update model parameter estimates by incorporating new state transition observations. In this work, however, the UAVs choose to actively reduce the uncertainty in their model parameters by taking exploratory and informative actions. These actions result in a faster adaptation and, by explicitly accounting for UAV fuel dynamics, also mitigates the risk of the exploration. This paper compares the nominal, passive learning approach against two methods for incorporating active learning into the MDP framework: (1) All state transitions are rewarded equally, and (2) State transition rewards are weighted according to the expected resulting reduction in the variance of the model parameter. In both cases, agent behaviors emerge that enable faster convergence of the uncertain model parameters to their true values
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