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Schizophrenia is a mental disorder characterized by social problems and disorders of thought, behaviour and cognitive functions. These impaired cognitive functions may be associated with alterations in resting state functional connectivity in schizophrenia. Therefore, the present study has been carried out to determine the resting state functional brain connectivity changes associated with schizophrenia in all the resting state networks (RSNs) using independent component analysis approach (ICA) and dual-regression based approach.
The objective of this study was to investigate the aberrant resting-state functional connectivity patterns in schizophrenia patients as compared to healthy controls.
35 schizophrenia patients and 31 healthy controls were recruited for the study and scanned by using resting state functional magnetic resonance (rsfMRI). Pre-processing and post-processing of the resting state functional data were performed using the FMRI Expert Analysis Tool (FEAT), which is a part of FSL (FMRIB's Software Library, www.fmrib. ox.ac.uk/fsl).
Our results showed significantly decreased functional connectivity in the regions of left fronto-parietal network, lateral visual network, medial visual network, motor network and default mode network (DMN) in schizophrenia patients as compared with healthy controls.
The overall findings suggest that the alterations in these resting state network connectivity may, in part, contribute to the impairments in cognitive functions associated with schizophrenia. These findings also suggest that aberrant resting state network connectivity contributes to regional functional pathology in schizophrenia and bears significance for core symptoms.
Schizophrenia is one of the psychotic mental disorders, characterized by social problems and disorders of thought, behaviour, motor and cognitive functions such as long-term memory, verbal memory, executive functioning and vigilance etc. However, the relation between structural and functional alterations in schizophrenia remains unclear. Therefore, the present study sought to investigate whether functional alterations in schizophrenia are also associated with structural brain aberrations directly in related brain regions or in anatomically closely connected areas.
The current study was conducted to investigate the possible relationship between functional and structural changes for a simple motor task in schizophrenics.
16 controls and 16 schizophrenic patients were chosen for the study. The structural and functional MRI scans were acquired using 3 Tesla whole-body MRI system with a 16 channel head array coil. For fMRI, a block paradigm with alternating blocks of motor task (right finger tapping; 120 taps/min) and rest was carried out. Pre-processing and post-processing of MRI scans were performed using SPM8 software.
The fMRI study showed relatively less activation in the left precentral and postcentral gyrus and right cerebellum in schizophrenic patients as compared to controls during finger tapping task. Voxel-based morphometry (VBM) revealed grey matter decreases in the left precentral and postcentral gyrus and left middle frontal gyrus while white matter decreases in the right cerebellum and right inferior temporal gyrus of schizophrenics as compared to controls.
The present study provides strong evidence for an association between motor functional deficits and structural alterations in schizophrenic patients as compared to controls.
In this paper, we present the two-dimensional (2-D) energy cross-spectrum of the streamwise velocity (
) component and use it to test the notion of self-similarity in turbulent boundary layers. The primary focus is on the cross-spectrum (
) measured across the logarithmic (
) and near-wall (
) wall-normal locations, providing the energy distribution across the range of streamwise (
) and spanwise (
) wavelengths (or length scales) that are coherent across the wall-normal distance.
may thus be interpreted as a wall-filtered subset of the full 2-D
), the latter providing information on all coexisting eddies at
. To this end, datasets comprising synchronized two-point
, across the friction Reynolds number range
, are analysed. The published direct numerical simulation (DNS) dataset of Sillero et al. (Phys. Fluids, vol. 26 (10), 2014, 105109) is considered for low-
analysis, while the high-
dataset is obtained by conducting synchronous multipoint hot-wire measurements. High-
cross-spectra reveal that the wall-attached large scales follow a
relationship more closely than seen for
, where this self-similar trend is obscured by coexisting scales. The present analysis reaffirms that a self-similar structure, conforming to Townsend’s attached eddy hypothesis, is ingrained in the flow.
This article examines two intertwined topics on architected materials with imperfections—their mechanics and optimum design. We first discuss the main factors that control defect sensitivity along with a range of strategies for defect characterization. The potency of both as-designed and as-manufactured defects on their macroscopic response is highlighted with an emphasis on those caused by additive manufacturing technology. As a natural extension of defect sensitivity, we describe the design approaches for architected materials with particular focus on systematic tools of topology optimization. Recent extensions to formally incorporate imperfections in the optimization formulation are discussed, where the ultimate goal is to generate architectures that are flaw-tolerant and perform robustly in the presence of imperfections. We conclude with an outlook on the field, highlighting potential areas of future research.
Architected materials are a unique and emerging class of materials where performance is fundamentally controlled by geometry at multiple length scales, from the nano- to the macroscale, rather than chemical composition alone. As a result, the realization of these remarkable materials is contingent upon the ability to faithfully reproduce the designed architecture. This presents fundamental challenges in fabrication due to the required three-dimensional complexity, multiple length scales, range of material constituents, possibility of multiple materials in a single architecture, and overall manufacturing throughput. Additive manufacturing (AM) processes can provide solutions to some of these challenges and are discussed in this article. Specifically, light-based and extrusion-based processes and associated materials are presented with an emphasis on recent developments, including volumetric additive manufacturing, and on-the-fly mixing of materials in extrusion-based printing systems. While remarkable advancements have been made in AM for architected materials, bringing these materials and processes to industrial realization remains a significant challenge.
The integration of materials and architectural features at multiple length scales into structural mechanics has shifted the paradigm of structural design toward optimally engineered structures, which resulted in, for example, the Eiffel Tower. This structural revolution paved the way for the development of computational design approaches used in modern-day construction. Similar principles are now being applied to the design and manufacture of architected materials with a suite of properties determined a priori and attained through multiscale approaches. These new material classes potentially offer breakthrough advances in almost every branch of technology: from ultra-lightweight and damage-tolerant structural materials to safe and efficient energy storage, biomedical devices, biochemical, and micromechanical sensors and actuators, nanophotonic devices, and textiles. When reduced to the microscale, such materials embody the characteristics of both the constituent material, which brings the effects of its microstructure and ensuing properties at the relevant characteristic length scales, as well as the structure, which is driven by architected design. This issue gives an overview of the current state of the art of this new class of materials.
We present a survey of modeling techniques used to describe and predict architected cellular metamaterials, and to optimize their topology and geometry toward tailoring their mechanical properties such as stiffness, strength, fracture toughness, and energy absorption. Architectures of interest include truss-, plate-, and shell-based networks with and without periodicity, whose effective mechanical behavior is simulated by tools such as classical finite elements, further scale-bridging techniques such as homogenization and concurrent scale-coupling, and effective continuum descriptions of the underlying discrete networks. In addition to summarizing advances in applying the latter techniques to improve the properties of metamaterials and featuring prominent examples of structure–property relations achieved this way, we also present recently introduced techniques to improve the optimization process toward a full exploitation of the available design space, accounting for both linear and nonlinear material behavior.