944 research outputs found

    Micro-IPOs: An Analysis of the Small Corporate Offering Registration (SCOR) Procedure with National Data

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    In this study we examine every Small Corporate Offering Registration available from the United States. Using 339 micro-IPOs from 33 states, we find support for the relevance of (1)offering marketing mechanisms and expenses; (2)geographic characteristics; (3)offering characteristics; (4)ownership and governance characteristics; (5)business characteristics; (6)firm marketing mechanisms; and (7)signaling factors

    Elastically Deforming a Three-Dimensional Atlas to Match Anatomical Brain Images

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    To evaluate our system for elastically deforming a three-dimensional atlas to match anatomical brain images, six deformed versions of an atlas were generated. The deformed atlases were created by elastically mapping an anatomical brain atlas onto different MRI brain image volumes. The mapping matches the edges of the ventricles and the surface of the brain; the resultant deformations are propagated through the atlas volume, deforming the remainder of the structures in the process. The atlas was then elastically matched to its deformed versions. The accuracy of the resultant matches was evaluated by determining the correspondence of 32 cortical and subcortical structures. The system on average matched the centroid of a structure to within 1 mm of its true position and fit a structure to within 11% of its true volume. The overlap between the matched and true structures, defined by the ratio between the volume of their intersection and the volume of their union, averaged 66%. When the gray-white interface was included for matching, the mean overlap improved to 78%; each structure was matched to within 0.6 mm of its true position and fit to within 6% of its true volume. Preliminary studies were also made to determine the effect of the compliance of the atlas on the resultant match

    Reproducibility of graph metrics of human brain structural networks

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    Recent interest in human brain connectivity has led to the application of graph theoretical analysis to human brain structural networks, in particular white matter connectivity inferred from diffusion imaging and fiber tractography. While these methods have been used to study a variety of patient populations, there has been less examination of the reproducibility of these methods. A number of tractography algorithms exist and many of these are known to be sensitive to user-selected parameters. The methods used to derive a connectivity matrix from fiber tractography output may also influence the resulting graph metrics. Here we examine how these algorithm and parameter choices influence the reproducibility of proposed graph metrics on a publicly available test-retest dataset consisting of 21 healthy adults. The dice coefficient is used to examine topological similarity of constant density subgraphs both within and between subjects. Seven graph metrics are examined here: mean clustering coefficient, characteristic path length, largest connected component size, assortativity, global efficiency, local efficiency, and rich club coefficient. These reproducibility of these network summary measures is examined using the intraclass correlation coefficient (ICC). Graph curves are created by treating the graph metrics as functions of a parameter such as graph density. Functional data analysis techniques are usedto examine differences in graph measures that result from the choice of fiber tracking algorithm. The graph metrics consistently showed good levels of reproducibility as measured with ICC, with the exception of some instability at low graph density levels. The global and local efficiency measures were the most robust to the choice of fiber tracking algorithm

    Segregation and linkage analysis for longitudinal measurements of a quantitative trait

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    We present a method for using slopes and intercepts from a linear regression of a quantitative trait as outcomes in segregation and linkage analyses. We apply the method to the analysis of longitudinal systolic blood pressure (SBP) data from the Framingham Heart Study. A first-stage linear model was fit to each subject's SBP measurements to estimate both their slope over time and an intercept, the latter scaled to represent the mean SBP at the average observed age (53.7 years). The subject-specific intercepts and slopes were then analyzed using segregation and linkage analysis. We describe a method for using the standard errors of the first-stage intercepts and slopes as weights in the genetic analyses. For the intercepts, we found significant evidence of a Mendelian gene in segregation analysis and suggestive linkage results (with LOD scores ≥ 1.5) for specific markers on chromosomes 1, 3, 5, 9, 10, and 17. For the slopes, however, the data did not support a Mendelian model, and thus no formal linkage analyses were conducted

    Multivariate Normalization with Symmetric Diffeomorphisms for Multivariate Studies

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    Current clinical and research neuroimaging protocols acquire images using multiple modalities, for instance, T1, T2, diffusion tensor and cerebral blood flow magnetic resonance images (MRI). These multivariate datasets provide unique and often complementary anatomical and physiological information about the subject of interest. We present a method that uses fused multiple modality (scalar and tensor) datasets to perform intersubject spatial normalization. Our multivariate approach has the potential to eliminate inconsistencies that occur when normalization is performed on each modality separately. Furthermore, the multivariate approach uses a much richer anatomical and physiological image signature to infer image correspondences and perform multivariate statistical tests. In this initial study, we develop the theory for Multivariate Symmetric Normalization (MVSyN), establish its feasibility and discuss preliminary results on a multivariate statistical study of 22q deletion syndrome

    POPULATION RECOVERY OF THE WHOOPING CRANE WITH EMPHASIS ON REINTRODUCTION EFFORTS: PAST AND FUTURE

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    The U.S. Fish and Wildlife Service (USFWS) began building a captive whooping crane (Grus americana) colony at Patuxent Wildlife Research Center (patuxent), Maryland, in 1966. From 1976 to 1984, 73 eggs from this colony and 216 eggs from Wood Buffalo National Park (Wood Buffalo), Canada, nests were placed in sandhill crane (G. canadensis) nests at Grays Lake National Wildlife Refuge (Grays Lake), Idaho, the site of the first whooping crane reintroduction attempt. Although 84 chicks fledged from the 289 eggs, the egg transfer program has been discontinued because of inordinately high mortality (only ca. 13 birds remain in the wild in 1991) and lack of breeding in survivors. In recent decades new methods have emerged for introducing captive-produced offspring to the wild. Surrogate studies with sandhill cranes, particularly the endangered Mississippi sandhill cranes (G. c. pulla), have shown that young cranes, raised either by captive, conspecific foster parents, or by costumed humans and in close association with live cranes and lifelike crane taxidermic dummies, have high post-release survival rates. These techniques will likely be used in future Whooping crane reintroduction programs. Current recovery objectives for the Whooping crane include expansion of the 2 captive colonies, establishment of a third captive colony in Canada, and reintroduction of 2 additional wild populations. The Kissimmee Prairie in central Florida has been selected for the next release experiment. Evaluation of this site began in 1984, and risk assessment is expected to begin in 1992 with the transfer and monitoring of a group of captivereared, juvenile whooping cranes. These tests of the environment will, if results are favorable, be followed by a full-scale reintroduction effort of at least 20 birds/year beginning in 1994 or 1995

    The Role of Chain-of-Thought in Complex Vision-Language Reasoning Task

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    The study explores the effectiveness of the Chain-of-Thought approach, known for its proficiency in language tasks by breaking them down into sub-tasks and intermediate steps, in improving vision-language tasks that demand sophisticated perception and reasoning. We present the "Description then Decision" strategy, which is inspired by how humans process signals. This strategy significantly improves probing task performance by 50%, establishing the groundwork for future research on reasoning paradigms in complex vision-language tasks

    Efficient Generation of Shape-Based Reference Frames for the Corpus Callosum for DTI-based Connectivity Analysis

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    Yushkevich et.al. [17, 18] established a PDE-based deformable modeling approach called continuous medial representation (cm-rep), in which the geometric relationship between the medial axis of a 3D object and its boundary is captured. Continuous medial description of an object not only provides useful shape features for object characterization and comparison; it also imposes a shape-based reference frame on the interior of that object. Such a reference frame provides a useful means of representing different instances of an anatomical structure using a common canonical parametrization domain. This paper presents an efficient method to construct continuous medial shape models for 2D objects. A closed form solution for the ordinary differential equation (ODE) is derived via Pythagorean hodograph (PH) curves. That closed form solution reduces the computation complexity from solving an ODE system to pure algebraic manipulation. Using this method, we generate shape-based reference frames, and demonstrate how they can be applied to the analysis of anatomical connectivity of corpora callosa, obtained by fiber tracking in diffusion tensor magnetic resonance imaging (DTI) in a chromosome 22q11.2 deletion syndrome study

    Atypical cortical connectivity and visuospatial cognitive impairments are related in children with chromosome 22q11.2 deletion syndrome

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    BackgroundChromosome 22q11.2 deletion syndrome is one of the most common genetic causes of cognitive impairment and developmental disability yet little is known about the neural bases of those challenges. Here we expand upon our previous neurocognitive studies by specifically investigating the hypothesis that changes in neural connectivity relate to cognitive impairment in children with the disorder.MethodsWhole brain analyses of multiple measures computed from diffusion tensor image data acquired from the brains of children with the disorder and typically developing controls. We also correlated diffusion tensor data with performance on a visuospatial cognitive task that taps spatial attention.ResultsAnalyses revealed four common clusters, in the parietal and frontal lobes, that showed complementary patterns of connectivity in children with the deletion and typical controls. We interpreted these results as indicating differences in connective complexity to adjoining cortical regions that are critical to the cognitive functions in which affected children show impairments. Strong, and similarly opposing patterns of correlations between diffusion values in those clusters and spatial attention performance measures considerably strengthened that interpretation.ConclusionOur results suggest that atypical development of connective patterns in the brains of children with chromosome 22q11.2 deletion syndrome indicate a neuropathology that is related to the visuospatial cognitive impairments that are commonly found in affected individuals
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