3,552 research outputs found

    Super-Resolution for Overhead Imagery Using DenseNets and Adversarial Learning

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    Recent advances in Generative Adversarial Learning allow for new modalities of image super-resolution by learning low to high resolution mappings. In this paper we present our work using Generative Adversarial Networks (GANs) with applications to overhead and satellite imagery. We have experimented with several state-of-the-art architectures. We propose a GAN-based architecture using densely connected convolutional neural networks (DenseNets) to be able to super-resolve overhead imagery with a factor of up to 8x. We have also investigated resolution limits of these networks. We report results on several publicly available datasets, including SpaceNet data and IARPA Multi-View Stereo Challenge, and compare performance with other state-of-the-art architectures.Comment: 9 pages, 9 figures, WACV 2018 submissio

    Tracking system study

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    A digital computer program was generated which mathematically describes an optimal estimator-controller technique as applied to the control of antenna tracking systems used by NASA. Simulation studies utilizing this program were conducted using the IBM 360/91 computer. The basic ideas of applying optimal estimator-controller techniques to antenna tracking systems are discussed. A survey of existing tracking methods is given along with shortcomings and inherent errors. It is explained how these errors can be considerably reduced if optimal estimation and control are used. The modified programs generated in this project are described and the simulation results are summarized. The new algorithms for direct synthesis and stabilization of the systems including nonlinearities, are presented

    Neural Circuitry of Novelty Salience Processing in Psychosis Risk: Association With Clinical Outcome

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    Psychosis has been proposed to develop from dysfunction in a hippocampal-striatal-midbrain circuit, leading to aberrant salience processing. Here, we used functional magnetic resonance imaging (fMRI) during novelty salience processing to investigate this model in people at clinical high risk (CHR) for psychosis according to their subsequent clinical outcomes. Seventy-six CHR participants as defined using the Comprehensive Assessment of At-Risk Mental States (CAARMS) and 31 healthy controls (HC) were studied while performing a novelty salience fMRI task that engaged an a priori hippocampal-striatal-midbrain circuit of interest. The CHR sample was then followed clinically for a mean of 59.7 months (~5 y), when clinical outcomes were assessed in terms of transition (CHR-T) or non-transition (CHR-NT) to psychosis (CAARMS criteria): during this period, 13 individuals (17%) developed a psychotic disorder (CHR-T) and 63 did not. Functional activation and effective connectivity within a hippocampal-striatal-midbrain circuit were compared between groups. In CHR individuals compared to HC, hippocampal response to novel stimuli was significantly attenuated (P = .041 family-wise error corrected). Dynamic Causal Modelling revealed that stimulus novelty modulated effective connectivity from the hippocampus to the striatum, and from the midbrain to the hippocampus, significantly more in CHR participants than in HC. Conversely, stimulus novelty modulated connectivity from the midbrain to the striatum significantly less in CHR participants than in HC, and less in CHR participants who subsequently developed psychosis than in CHR individuals who did not become psychotic. Our findings are consistent with preclinical evidence implicating hippocampal-striatal-midbrain circuit dysfunction in altered salience processing and the onset of psychosis

    Comparative analysis reveals the long-term co-evolutionary history of parvoviruses and vertebrates [preprint]

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    Parvoviruses (family Parvoviridae) are small, non-enveloped DNA viruses that infect a broad range of animal species. Comparative studies, supported by experimental evidence, show that many vertebrate species contain sequences derived from ancient parvoviruses embedded in their genomes. These ‘endogenous parvoviral elements’ (EPVs), which arose via recombination-based mechanisms in infected germline cells of ancestral organisms, constitute a form of ‘molecular fossil record’ that can be used to investigate the origin and evolution of the parvovirus family. Here, we use comparative approaches to investigate 198 EPV loci, represented by 470 EPV sequences identified in a comprehensive in silico screen of 752 published vertebrate genomes. We investigated EPV loci by constructing an open resource that contains all of the data items required for comparative sequence analysis of parvoviruses and uses a relational database to represent the complex semantic relationships between them. We used this standardised framework to implement reproducible comparative phylogenetic analysis of combined EPV and virus data. Our analysis reveals that viruses closely related to contemporary parvoviruses have circulated among vertebrates since the Late Cretaceous epoch (100-66 million years ago). We present evidence that the subfamily Parvovirinae, which includes ten vertebrate-specific genera, has evolved in broad congruence with the emergence and diversification of major vertebrate groups. Furthermore, we infer defining aspects of evolution within individual parvovirus genera - mammalian vicariance for protoparvoviruses (genus Protoparvovirus), and inter-class transmission for dependoparvoviruses (genus Dependoparvovirus) - thereby establishing an ecological and evolutionary perspective through which to approach analysis of these virus groups. We also identify evidence of EPV expression at RNA level and show that EPV coding sequences have frequently been maintained during evolution, adding to a growing body of evidence that EPV loci have been co-opted or exapted by vertebrate species, and especially by mammals. Our findings offer fundamental insights into parvovirus evolution. In addition, we establish novel genomic resources that can advance the development of parvovirus-related research - including both therapeutics and disease prevention efforts - by enabling more efficient dissemination and utilisation of relevant, evolution-related domain knowledge

    Exploring the interplay between Buddhism and career development : a study of highly skilled women workers in Sri Lanka

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    This article adopts a socio cultural lens to examine the role of Buddhism in highly skilled women workers’ careers in Sri Lanka. While Buddhism enabled women’s career development by giving them strength to cope with difficult situations in work, it also seemed to restrict their agency and constrain their career advancement. Based on our findings, we argue that being perceived as a good Buddhist woman worked as a powerful form of career capital for the respondents in our sample, who used their faith to combat gender disadvantage in their work settings

    Experiential learning in public health: evaluation of a health promotion campaign assessment for pharmacy students

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    Description: Students in small groups designed, delivered and evaluated real-life health promotion campaigns in the local community. A peer assessed component was included from the fifth cohort onwards. Evaluation: Six successive cohorts of pharmacy students anonymously completed an evaluation questionnaire after finishing the assessment. Descriptive and inferential statistical analyses were undertaken on the data. The results showed that consistently more respondents reported the assessment as a positive experience than a negative experience. Significantly more respondents reported peer assessment as being useful and group members equally contributing to campaign planning in the cohorts with peer assessment compared to the pre-peer assessment cohorts, but peer assessment did not significantly affect enjoyment ratings. Respondents’ reported enjoyment of the assessment was significantly associated with agreement that it prepared them for health promotion in practice. Conclusions: Pharmacy students perceived the health promotion campaign assessment as appropriately challenging and enjoyable preparation for health promotion in practice

    Modeling the Distance-Dependent Blurring in Transmission Imaging in the Ordered-Subset Transmission (OSTR) Algorithm by Using an Unmatched Projector/Backprojector Pair

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    In SPECT, accurate emission reconstruction requires attenuation compensation with high-quality attenuation maps. Resolution loss in transmission maps could cause blurring and artifacts in emission reconstruction. For a transmission system employing parallel-hole collimators and a sheet source, distance-dependent blurring is caused by the non-ideal source and camera collimations, and the finite intrinsic resolution of the detector. These can be approximately modeled by an incremental-blurring model. To compensate for this blurring in iterative transmission reconstruction, we incorporated the incremental blurring model in the forward projector of the OSTR algorithm but did not include the blur in the backprojector. To evaluate our approach, we simulated transmission projections of the MCAT phantom using a ray-tracing projector, in which the rays coming out from a source point form a narrow cone. The geometric blurring due to the non-ideal source and camera collimations was simulated by multiplying the counts along each cone-beam ray with a weight calculated from the overall geometric response function (assumed a two-dimensional Gaussian function), and then summing the weighted counts into projections. The resulting projections were convolved with the intrinsic response (another two-dimensional Gaussian) to simulate the total system blurring of transmission imaging. Poisson noise was then added to the projection data. We also acquired two sets of transmission measurements of an air-filled Data Spectrum Deluxe SPECT phantom on a Prism 2000 scanning-line-source transmission system. We reconstructed the simulations using the OSTR algorithm, with and without modeling of the incremental blur in the projector. The scaling parameter of the penalty prior was optimized in each case by minimizing the root-mean-square error (RMSE). Reconstructions showed that modeling the incremental blur improved the resolution of the attenuation map and quantitative accuracy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85829/1/Fessler211.pd
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