696 research outputs found

    Utilizing hyperspectral remote sensing for soil gradation

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    Soil gradation is an important characteristic for soil mechanics. Traditionally soil gradation is performed by sieve analysis using a sample from the field. In this research, we are interested in the application of hyperspectral remote sensing to characterize soil gradation. The specific objective of this work is to explore the application of hyperspectral remote sensing to be used as an alternative to traditional soil gradation estimation. The advantage of such an approach is that it would provide the soil gradation without having to obtain a field sample. This work will examine five different soil types from the Keweenaw Research Center within a laboratory-controlled environment for testing. Our study demonstrates a correlation between hyperspectral data, the percent gravel and sand composition of the soil. Using this correlation, one can predict the percent gravel and sand within a soil and, in turn, calculate the remaining percent of fine particles. This information can be vital to help identify the soil type, soil strength, permeability/hydraulic conductivity, and other properties that are correlated to the gradation of the soil

    Characterizing soil stiffness using thermal remote sensing and machine learning

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    Soil strength characterization is essential for any problem that deals with geomechanics, including terramechanics/terrain mobility. Presently, the primary method of collecting soil strength parameters through in situ measurements but sending a team of people out to a site to collect data this has significant cost implications and accessing the location with the necessary equipment can be difficult. Remote sensing provides an alternate approach to in situ measurements. In this lab study, we compare the use of Apparent Thermal Inertia (ATI) against a GeoGauge for the direct testing of soil stiffness. ATI correlates with stiffness, so it allows one to predict the soil strength remotely using machine-learning algorithms. The best performing regression algorithm among the ones tested with different predictor variable combinations was found to be KNN with an R2 of 0.824 and a RMSE of 0.141. This study demonstrates the potential for using remote sensing to acquire thermal images that characterize terrain strength for mobility utilizing different machine-learning algorithms

    Radio Galaxy Zoo: Knowledge Transfer Using Rotationally Invariant Self-Organising Maps

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    With the advent of large scale surveys the manual analysis and classification of individual radio source morphologies is rendered impossible as existing approaches do not scale. The analysis of complex morphological features in the spatial domain is a particularly important task. Here we discuss the challenges of transferring crowdsourced labels obtained from the Radio Galaxy Zoo project and introduce a proper transfer mechanism via quantile random forest regression. By using parallelized rotation and flipping invariant Kohonen-maps, image cubes of Radio Galaxy Zoo selected galaxies formed from the FIRST radio continuum and WISE infrared all sky surveys are first projected down to a two-dimensional embedding in an unsupervised way. This embedding can be seen as a discretised space of shapes with the coordinates reflecting morphological features as expressed by the automatically derived prototypes. We find that these prototypes have reconstructed physically meaningful processes across two channel images at radio and infrared wavelengths in an unsupervised manner. In the second step, images are compared with those prototypes to create a heat-map, which is the morphological fingerprint of each object and the basis for transferring the user generated labels. These heat-maps have reduced the feature space by a factor of 248 and are able to be used as the basis for subsequent ML methods. Using an ensemble of decision trees we achieve upwards of 85.7% and 80.7% accuracy when predicting the number of components and peaks in an image, respectively, using these heat-maps. We also question the currently used discrete classification schema and introduce a continuous scale that better reflects the uncertainty in transition between two classes, caused by sensitivity and resolution limits

    Elevated glutamatergic compounds in pregenual anterior cingulate in pediatric autism spectrum disorder demonstrated by 1H MRS and 1H MRSI.

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    Recent research in autism spectrum disorder (ASD) has aroused interest in anterior cingulate cortex and in the neurometabolite glutamate. We report two studies of pregenual anterior cingulate cortex (pACC) in pediatric ASD. First, we acquired in vivo single-voxel proton magnetic resonance spectroscopy ((1)H MRS) in 8 children with ASD and 10 typically developing controls who were well matched for age, but with fewer males and higher IQ. In the ASD group in midline pACC, we found mean 17.7% elevation of glutamate + glutamine (Glx) (p<0.05) and 21.2% (p<0.001) decrement in creatine + phosphocreatine (Cr). We then performed a larger (26 subjects with ASD, 16 controls) follow-up study in samples now matched for age, gender, and IQ using proton magnetic resonance spectroscopic imaging ((1)H MRSI). Higher spatial resolution enabled bilateral pACC acquisition. Significant effects were restricted to right pACC where Glx (9.5%, p<0.05), Cr (6.7%, p<0.05), and N-acetyl-aspartate + N-acetyl-aspartyl-glutamate (10.2%, p<0.01) in the ASD sample were elevated above control. These two independent studies suggest hyperglutamatergia and other neurometabolic abnormalities in pACC in ASD, with possible right-lateralization. The hyperglutamatergic state may reflect an imbalance of excitation over inhibition in the brain as proposed in recent neurodevelopmental models of ASD

    Advanced information processing system: The Army fault tolerant architecture conceptual study. Volume 1: Army fault tolerant architecture overview

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    Digital computing systems needed for Army programs such as the Computer-Aided Low Altitude Helicopter Flight Program and the Armored Systems Modernization (ASM) vehicles may be characterized by high computational throughput and input/output bandwidth, hard real-time response, high reliability and availability, and maintainability, testability, and producibility requirements. In addition, such a system should be affordable to produce, procure, maintain, and upgrade. To address these needs, the Army Fault Tolerant Architecture (AFTA) is being designed and constructed under a three-year program comprised of a conceptual study, detailed design and fabrication, and demonstration and validation phases. Described here are the results of the conceptual study phase of the AFTA development. Given here is an introduction to the AFTA program, its objectives, and key elements of its technical approach. A format is designed for representing mission requirements in a manner suitable for first order AFTA sizing and analysis, followed by a discussion of the current state of mission requirements acquisition for the targeted Army missions. An overview is given of AFTA's architectural theory of operation

    Advanced information processing system: The Army fault tolerant architecture conceptual study. Volume 2: Army fault tolerant architecture design and analysis

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    Described here is the Army Fault Tolerant Architecture (AFTA) hardware architecture and components and the operating system. The architectural and operational theory of the AFTA Fault Tolerant Data Bus is discussed. The test and maintenance strategy developed for use in fielded AFTA installations is presented. An approach to be used in reducing the probability of AFTA failure due to common mode faults is described. Analytical models for AFTA performance, reliability, availability, life cycle cost, weight, power, and volume are developed. An approach is presented for using VHSIC Hardware Description Language (VHDL) to describe and design AFTA's developmental hardware. A plan is described for verifying and validating key AFTA concepts during the Dem/Val phase. Analytical models and partial mission requirements are used to generate AFTA configurations for the TF/TA/NOE and Ground Vehicle missions

    The utility of the alvarado score in the diagnosis of acute appendicitis in the elderly

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    Clinical scores determining the likelihood of acute appendicitis (AA), including the Alvarado score, were devised using a younger population, and their efficacy in predicting AA in elderly patients is not well documented. This study's purpose is to evaluate the utility of Alvarado scores in this population. A retrospective chart review of patients >65 years old presenting with pathologically diagnosed AA from 2000 to 2010 was performed. Ninety-six patients met inclusion criteria. The average age was 73.7 ± 1.5 years and our cohort was 41.7 per cent male. The average Alvarado score was 6.9 ± 0.33. The distribution of scores was 1 to 4 in 3.7 per cent, 5 to 6 in 37.8 per cent, and 7 to 10 in 58.5 per cent of cases. There was a statistically significant increase in patients scoring 5 or 6 in our cohort versus the original Alvarado cohort (P < 0.01). Right lower quadrant tenderness (97.6%), left shift of neutrophils (91.5%), and leukocytosis (84.1%) were the most common symptoms on presentation. In conclusion, our data suggest that altering our interpretation of the Alvarado score to classify elderly patients presenting with a score of ‡5 as high risk may lead to earlier diagnosis of AA. Physicians should have a higher clinical suspicion of AA in elderly patients presenting with right lower quadrant tenderness, left shift, or leukocytosis

    Long-Term Potentiation: One Kind or Many?

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    Do neurobiologists aim to discover natural kinds? I address this question in this chapter via a critical analysis of classification practices operative across the 43-year history of research on long-term potentiation (LTP). I argue that this 43-year history supports the idea that the structure of scientific practice surrounding LTP research has remained an obstacle to the discovery of natural kinds

    Predictors of CNS Injury as Measured by Proton Magnetic Resonance Spectroscopy in the Setting of Chronic HIV infection and CART

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    The reasons for persistent brain dysfunction in chronically HIV-infected persons on stable combined antiretroviral therapies (CART) remain unclear. Host and viral factors along with their interactions were examined in 260 HIV-infected subjects who underwent magnetic resonance spectroscopy (MRS) Metabolite concentrations (NAA/Cr, Cho/Cr, MI/Cr and Glx/Cr) were measured in the basal ganglia, the frontal white matter and grey matter and the best predictive models were selected using a bootstrap-enhanced Akaike Information Criterion (AIC). Depending on the metabolite and brain region, age, race, HIV RNA concentration, ADC stage, duration of HIV infection, nadir CD4, and/or their interactions were predictive of metabolite concentrations, particularly the basal ganglia NAA/Cr and the mid-frontal NAA/Cr and Glx/Cr whereas current CD4 and the CPE index rarely or did not predict these changes. These results show for the first time that host and viral factors related to both current and past HIV status contribute to persisting cerebral metabolite abnormalities and provide a framework for further understanding neurological injury in the setting of chronic and stable disease

    Endocannabinoids Generated by Ca2+ or by Metabotropic Glutamate Receptors Appear to Arise from Different Pools of Diacylglycerol Lipase

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    The identity and subcellular sources of endocannabinoids (eCBs) will shape their ability to affect synaptic transmission and, ultimately, behavior. Recent discoveries support the conclusion that 2-arachidonoyl glycerol, 2-AG, is the major signaling eCB, however, some important issues remain open. 2-AG can be synthesized by a mechanism that is strictly Ca2+-dependent, and another that is initiated by G-protein coupled receptors (GPCRs) and facilitated by Ca2+. An important question is whether or not the 2-AG in these cases is synthesized by the same pool of diacylglycerol lipase alpha (DAGLα). Using whole-cell voltage-clamp techniques in CA1 pyramidal cells in acute in vitro rat hippocampal slices, we investigated two mechanistically distinct eCB-mediated responses to address this issue. We now report that pharmacological inhibitors of DGLα have quantitatively different effects on eCB-mediated responses triggered by different stimuli, suggesting that functional, and perhaps physical, distinctions among pools of DAGLα exist
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