173 research outputs found
Supplementary Table 1 -Supplemental material for Cerebellar and Prefrontal Cortical Alterations in PTSD: Structural and Functional Evidence
No full textSupplemental material, Supplementary Table 1 for Cerebellar and Prefrontal Cortical Alterations in PTSD: Structural and Functional Evidence by Sophie E. Holmes, Dustin Scheinost, Nicole DellaGioia, Margaret T. Davis, David Matuskey, Robert H. Pietrzak, Michelle Hampson, John H. Krystal and Irina Esterlis in Chronic Stress</p
Supplementary Figures -Supplemental material for Cerebellar and Prefrontal Cortical Alterations in PTSD: Structural and Functional Evidence
No full textSupplemental material, Supplementary Figures for Cerebellar and Prefrontal Cortical Alterations in PTSD: Structural and Functional Evidence by Sophie E. Holmes, Dustin Scheinost, Nicole DellaGioia, Margaret T. Davis, David Matuskey, Robert H. Pietrzak, Michelle Hampson, John H. Krystal and Irina Esterlis in Chronic Stress</p
Assessment of solid/liquid equilibria in the (U, Zr)O2+y system
No full textSolid/liquid equilibria in the system UO2eZrO2 are revisited in this work by laser heating coupled with
fast optical thermometry. Phase transition points newly measured under inert gas are in fair agreement
with the early measurements performed by Wisnyi et al., in 1957, the only study available in the literature
on the whole pseudo-binary system. In addition, a minimum melting point is identified here for
compositions near (U0.6Zr0.4)O2þy, around 2800 K. The solidus line is rather flat on a broad range of
compositions around the minimum. It increases for compositions closer to the pure end members, up to
the melting point of pure UO2 (3130 K) on one side and pure ZrO2 (2970 K) on the other. Solid state phase
transitions (cubic-tetragonal-monoclinic) have also been observed in the ZrO2-rich compositions X-ray
diffraction. Investigations under 0.3 MPa air (0.063 MPa O2) revealed a significant decrease in the melting
points down to 2500 Ke2600 K for increasing uranium content (x(UO2)> 0.2). This was found to be
related to further oxidation of uranium dioxide, confirmed by X-ray absorption spectroscopy. For
example, a typical oxidised corium composition U0.6Zr0.4O2.13 was observed to solidify at a temperature
as low as 2493 K.
The current results are important for assessing the thermal stability of the system fuel e cladding in an
oxide based nuclear reactor, and for simulating the system behaviour during a hypothetical severe
accident
Smooth graph learning for functional connectivity estimation
No full textFunctional connectivity (FC) estimated from functional magnetic resonance imaging (fMRI) signals is important in understanding neural representation and information processing in cortical networks. However, due to a lack of ”ground truth” FC pattern, the reliability and robustness of FC estimates are usually examined in downstream FC analysis tasks, such as performing participant’s identification (also known as ”fingerprinting”). In this paper, we propose to learn FC via a smooth graph learning framework. In particular, we treat each time frame of the fMRI time series as a graph signal on an underlying functional brain graph, and estimate the smooth graph functional connectivity (SGFC) by learning the weighted graph adjacency matrix based on graph signal smoothness assumption. We demonstrate that our approach gives rise to a natural and sparse graph representation of FC from which reliable graph measures can be extracted. Reliability of SGFC is evaluated in the context of fingerprinting and compared to correlation FC (CFC). SGFC achieves higher fingerprinting accuracy across several different experiment settings; the improvement is even more significant when a shorter fMRI scanning length is used for FC estimation. In addition to being reliable, we also validate the cognitive relevance of SGFC by using it to predict fluid intelligence. Finally, in evaluating topological measures of the sparse graph, SGFC reveals a more small-world and modular structure compared to CFC. Together, our results suggest that the smooth graph learning framework produces a naturally sparse, reliable, and cognitive-relevant representation of functional connectivity
A guide to the measurement and interpretation of fMRI test-retest reliability
No full textThe test-retest reliability of functional neuroimaging data has recently been a topic of much discussion. Despite early conflicting reports, converging reports now suggest that test-retest reliability is poor for standard univariate measures—namely, voxel- and region-level task-based activation and edge-level functional connectivity. To better understand the implications of these recent studies requires understanding the nuances of test-retest reliability as commonly measured by the intraclass correlation coefficient (ICC). Here we provide a guide to the measurement and interpretation of test-retest reliability in functional neuroimaging and review major findings in the literature. We highlight the importance of making choices that improve reliability so long as they do not diminish validity, pointing to the potential of multivariate approaches that improve both. Finally, we discuss the implications of recent reports of low test-retest reliability in the context of ongoing work in the field
Nonlinear manifold learning in functional magnetic resonance imaging uncovers a low‐dimensional space of brain dynamics
No full textLarge-scale brain dynamics are believed to lie in a latent, low-dimensional space. Typically, the embeddings of brain scans are derived independently from different cognitive tasks or resting-state data, ignoring a potentially large-and shared-portion of this space. Here, we establish that a shared, robust, and interpretable low-dimensional space of brain dynamics can be recovered from a rich repertoire of task-based functional magnetic resonance imaging (fMRI) data. This occurs when relying on nonlinear approaches as opposed to traditional linear methods. The embedding maintains proper temporal progression of the tasks, revealing brain states and the dynamics of network integration. We demonstrate that resting-state data embeds fully onto the same task embedding, indicating similar brain states are present in both task and resting-state data. Our findings suggest analysis of fMRI data from multiple cognitive tasks in a low-dimensional space is possible and desirable
Thieves in law - post-soviet criminal world leaders (from "perestroica" until today)
No full textThe work deals with thieves in law as chiefs of Russian-language criminal organizations. On the basis of an analysis of available sources, and their historical, criminologically focused processing, there is examined a hypothesis that criminality represented by the thieves in law creates in its fight against the society a specific form of self-defence. Part of the work being also an answer to a question to what extent today's division into old and new vors is topical, and whether this world has modernized in permanent relation to the environment surrounding it. The author proceeds in his analysis from the role of the thief in law as the individuality acting in constant tension with the society to the characterization of the thieves in law and to relations by which they are connected. He also focuses on power structures to which the thieves in law are subordinated. Thus, the author pursues an overall picture of chiefs of the Vor world and its possible modernization. Powered by TCPDF (www.tcpdf.org
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