629 research outputs found

    An automated 3D modeling of topological indoor navigation network

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    Ā© 2015, Springer Science+Business Media Dordrecht. Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigation. In this research, an automated method for 3D modeling of indoor navigation network has been presented. 3D indoor navigation modeling requires a valid 3D model that can be represented as a cell complex: a model without any gap or intersection such that two cells (e.g. room, corridor) perfectly touch each other. This research investigates an automated method for 3D modeling of indoor navigation network using a geometrical model of indoor building environment. In order to reduce time and cost of surveying process, Trimble LaserAce 1000 laser rangefinder was used to acquire indoor building data which led to the acquisition of an inaccurate geometry of building. The connection between surveying benchmarks was established using Delaunay triangulation. Dijkstra algorithm was used to find shortest path in between building floors. The modeling results were evaluated against an accurate geometry of indoor building environment which was acquired using highly-accurate Trimble M3 total station. This research intends to investigate and propose a novel method of topological navigation network modeling with a less accurate geometrical model to overcome the need of required an accurate geometrical model. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation will be investigated in the near future

    Normative Evidence Accumulation in Unpredictable Environments

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    In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals

    From aptamer-based biomarker discovery to diagnostic and clinical applications: an aptamer-based, streamlined multiplex proteomic assay

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    Recently, we reported an aptamer-based, highly multiplexed assay for the purpose of biomarker identification. To enable seamless transition from highly multiplexed biomarker discovery assays to a format suitable and convenient for diagnostic and life-science applications, we developed a streamlined, plate-based version of the assay. The plate-based version of the assay is robust, sensitive (sub-picomolar), rapid, can be highly multiplexed (upwards of 60 analytes), and fully automated. We demonstrate that quantification by microarray-based hybridization, Luminex bead-based methods, and qPCR are each compatible with our platform, further expanding the breadth of proteomic applications for a wide user community

    Clinically Silent Alzheimer\u27s and Vascular Pathologies Influence Brain Networks Supporting Executive Function in Healthy Older Adults

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    Aging is associated with declines in executive function. We examined how executive functional brain systems are influenced by clinically silent Alzheimerā€™s disease (AD) pathology and cerebral white matter hyperintensities (WMHs). Twenty-nine younger adults and thirty-four cognitively normal older adults completed a working memory paradigm while functional magnetic resonance imaging (fMRI) was performed. Older adults further underwent lumbar cerebrospinal fluid (CSF) draw for assessment of AD pathology and FLAIR imaging for assessment of WMHs. Accurate working memory performance in both age groups was associated with high fronto-visual functional connectivity (fC). However, in older adults, higher expression of fronto-visual fC was linked with lower levels of clinically silent AD pathology. In addition, AD pathology and WMHs were each independently related to increased fMRI response in the left dorsolateral prefrontal cortex, a pattern associated with slower task performance. Our results suggest that clinically silent AD pathology is related to lower expression of a fronto-visual fC pattern supporting executive task performance. Further, our findings suggest that AD pathology and WMHs appear to be linked with ineffective increases in frontal response in CN older adults

    2014 dDocent: a RADseq, variantcalling pipeline designed for population genomics of non-model organisms

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    ABSTRACT 14 Restriction-site associated DNA sequencing (RADseq) has become a powerful and useful 15 approach for population genomics. Currently, no software exists that utilizes both paired-end 16 reads from RADseq data to efficiently produce population-informative variant calls, 17 especially for organisms with large effective population sizes and high levels of genetic 18 polymorphism but for which no genomic resources exist. dDocent is an analysis pipeline with 19 a user-friendly, command-line interface designed to process individually barcoded RADseq 20 data (with double cut sites) into informative SNPs/INDELs for population-level analyses. The 21 pipeline, written in BASH, uses data reduction techniques and other stand-alone software 22 packages to perform quality trimming and adapter removal, de novo assembly of RAD loci, 23 read mapping, SNP and INDEL calling, and baseline data filtering. Double-digest RAD data 24 from population pairings of three different marine fishes were used to compare dDocent with 25 Stacks, the first generally available, widely used pipeline for analysis of RADseq data. 26 dDocent consistently identified more SNPs shared across greater numbers of individuals and 27 with higher levels of coverage. This is most likely due to the fact that dDocent quality trims 28 instead of filtering and incorporates both forward and reverse reads in assembly, mapping, 29 and SNP calling, thus enabling use of reads with INDEL polymorphisms. The pipeline and a 30 comprehensive user guide can be found at (http://dDocent.wordpress.com). 31 32 PeerJ PrePrints | http://dx.doi.org/10.7287/peerj.preprints.314v1 | CC-BY 4.

    Enlarged Perivascular Spaces are Negatively Associated with Montreal Cognitive Assessment Scores in Older Adults

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    Emerging evidence suggests that enlarged perivascular spaces (ePVS) may be a clinically significant neuroimaging marker of global cognitive function related to cerebral small vessel disease (cSVD). We tested this possibility by assessing the relationship between ePVS and both a standardized measure of global cognitive function, the Montreal Cognitive Assessment (MoCA), and an established marker of cSVD, white matter hyperintensity volume (WMH) volume. One hundred and eleven community-dwelling older adults (56ā€“86) underwent neuroimaging and MoCA testing. Quantification of region-specific ePVS burden was performed using a previously validated visual rating method and WMH volumes were computed using the standard ADNI pipeline. Separate linear regression models were run with ePVS as a predictor of MoCA scores and whole brain WMH volume. Results indicated a negative association between MoCA scores and both total ePVS counts (P ā‰¤ 0.001) and centrum semiovale ePVS counts (P ā‰¤ 0.001), after controlling for other relevant cSVD variables. Further, WMH volumes were positively associated with total ePVS (P = 0.010), basal ganglia ePVS (P ā‰¤ 0.001), and centrum semiovale ePVS (P = 0.027). Our results suggest that ePVS burden, particularly in the centrum semiovale, may be a clinically significant neuroimaging marker of global cognitive dysfunction related to cSVD

    Microscale to Manufacturing Scale-up of Cell-Free Cytokine Productionā€”A New Approach for Shortening Protein Production Development Timelines

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    Engineering robust protein production and purification of correctly folded biotherapeutic proteins in cell-based systems is often challenging due to the requirements for maintaining complex cellular networks for cell viability and the need to develop associated downstream processes that reproducibly yield biopharmaceutical products with high product quality. Here, we present an alternative Escherichia coli-based open cell-free synthesis (OCFS) system that is optimized for predictable high-yield protein synthesis and folding at any scale with straightforward downstream purification processes. We describe how the linear scalability of OCFS allows rapid process optimization of parameters affecting extract activation, gene sequence optimization, and redox folding conditions for disulfide bond formation at microliter scales. Efficient and predictable high-level protein production can then be achieved using batch processes in standard bioreactors. We show how a fully bioactive protein produced by OCFS from optimized frozen extract can be purified directly using a streamlined purification process that yields a biologically active cytokine, human granulocyte-macrophage colony-stimulating factor, produced at titers of 700 mg/L in 10 h. These results represent a milestone for in vitro protein synthesis, with potential for the cGMP production of disulfide-bonded biotherapeutic proteins. Biotechnol. Bioeng. 2011; 108:1570ā€“1578. Ā© 2011 Wiley Periodicals, Inc

    White Matter Hyperintensity Regression: Comparison of Brain Atrophy and Cognitive Profiles with Progression and Stable Groups

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    Subcortical white matter hyperintensities (WMHs) in the aging population frequently represent vascular injury that may lead to cognitive impairment. WMH progression is well described, but the factors underlying WMH regression remain poorly understood. A sample of 351 participants from the Alzheimerā€™s Disease Neuroimaging Initiative 2 (ADNI2) was explored who had WMH volumetric quantification, structural brain measures, and cognitive measures (memory and executive function) at baseline and after approximately 2 years. Selected participants were categorized into three groups based on WMH change over time, including those that demonstrated regression (n = 96; 25.5%), stability (n = 72; 19.1%), and progression (n = 209; 55.4%). There were no significant differences in age, education, sex, or cognitive status between groups. Analysis of variance demonstrated significant differences in atrophy between the progression and both regression (p = 0.004) and stable groups (p = 0.012). Memory assessments improved over time in the regression and stable groups but declined in the progression group (p = 0.003; p = 0.018). WMH regression is associated with decreased brain atrophy and improvement in memory performance over two years compared to those with WMH progression, in whom memory and brain atrophy worsened. These data suggest that WMHs are dynamic and associated with changes in atrophy and cognition

    A refined model for spinning dust radiation

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    We present a comprehensive treatment of the spectrum of electric dipole emission from spinning dust grains, updating the commonly used model of Draine and Lazarian. Grain angular velocity distributions are computed using the Fokker-Planck equation; we revisit the drift and diffusion coefficients for the major torques on the grain, including collisions, grain-plasma interactions, and infrared emission. We use updated grain optical properties and size distributions. The theoretical formalism is implemented in the companion code, SPDUST, which is publicly available. The effect of some environmental and grain parameters on the emissivity is shown and analysed.Comment: Minor corrections. Matches the MNRAS published version (except for a typo in Eq.(74) corrected here). The companion code, SPDUST, can be downloaded from http://www.tapir.caltech.edu/~yacine/spdust/spdust.htm
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