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Abstract High‐gain converters play a vital role in all industrial applications such as automobiles, motor drives, renewable energy systems, and railway transportation sectors. The conventional converters have low gain owing to high‐voltage stress on active MOSFET, diode and low efficiency related with high operating pulse ratio. To overcome the limitations associated with the conventional converters, this study proposes a non‐isolated configuration of multiport quasi‐resonant converter (MP‐QRC) with high gain. The proposed MP‐QRC has the merits of high‐voltage gain, reduced number of components, minimum conduction losses, realization of soft switching in the devices and improved reliability. Moreover, the proposed converter is scalable and can serve as a good candidate in microgrid environment where the integration of more than one input is essential. In this paper, first a comprehensive analysis of various operation modes and design constraints are presented. Further, the study is supported with a reliability evaluation of proposed converter based on component failure. Also, the futuristic behaviour of MP‐QRC under continuous conduction mode as a function of operational and environmental variables is investigated to ascertain the reliability. The steady‐state operation of the converter is demonstrated for off‐board electric vehilce (EV) charging using MATLAB/SIMULINK and experiments performed on a 300‐W test rig.

Cognitive deficits contribute to functional disability in patients with schizophrenia and may be related to altered functional networks that serve cognition. We evaluated the integrity of major functional networks and assessed their role in supporting two cognitive functions affected in schizophrenia: processing speed (PS) and working memory (WM). Resting-state functional magnetic resonance imaging (rsfMRI) data, N = 261 patients and 327 controls, were aggregated from three independent cohorts and evaluated using Enhancing NeuroImaging Genetics through Meta Analysis rsfMRI analysis pipeline. Meta- and mega-analyses were used to evaluate patient-control differences in functional connectivity (FC) measures. Canonical correlation analysis was used to study the association between cognitive deficits and FC measures. Patients showed consistent patterns of cognitive and resting-state FC (rsFC) deficits across three cohorts. Patient-control differences in rsFC calculated using seed-based and dual-regression approaches were consistent (Cohen's d: 0.31 ± 0.09 and 0.29 ± 0.08, p < 10 -4 ). RsFC measures explained 12-17% of the individual variations in PS and WM in the full sample and in patients and controls separately, with the strongest correlations found in salience, auditory, somatosensory, and default-mode networks. The pattern of association between rsFC (within-network) and PS (r = .45, p = .07) and WM (r = .36, p = .16), and rsFC (between-network) and PS (r = .52, p = 8.4 × 10 -3 ) and WM (r = .47, p = .02), derived from multiple networks was related to effect size of patient-control differences in the functional networks. No association was detected between rsFC and current medication dose or psychosis ratings. Patients demonstrated significant reduction in several FC networks that may partially underlie some of the core neurocognitive deficits in schizophrenia. The strength of connectivity-cognition relationships in different networks was strongly associated with network's vulnerability to schizophrenia., (© 2019 Wiley Periodicals, Inc.)

Background: Altered brain connectivity is implicated in the development and clinical burden of schizophrenia. Relative to matched controls, schizophrenia patients show (1) a global and regional reduction in the integrity of the brain's white matter (WM), assessed using diffusion tensor imaging (DTI) fractional anisotropy (FA), and (2) accelerated age-related decline in FA values. In the largest mega-analysis to date, we tested if differences in the trajectories of WM tract development influenced patient-control differences in FA. We also assessed if specific tracts showed exacerbated decline with aging., Methods: Three cohorts of schizophrenia patients (total n = 177) and controls (total n = 249; age = 18-61 years) were ascertained with three 3T Siemens MRI scanners. Whole-brain and regional FA values were extracted using ENIGMA-DTI protocols. Statistics were evaluated using mega- and meta-analyses to detect effects of diagnosis and age-by-diagnosis interactions., Results: In mega-analysis of whole-brain averaged FA, schizophrenia patients had lower FA (P = 10 -11 ) and faster age-related decline in FA (P = 0.02) compared with controls. Tract-specific heterochronicity measures, that is, abnormal rates of adolescent maturation and aging explained approximately 50% of the regional variance effects of diagnosis and age-by-diagnosis interaction in patients. Interactive, three-dimensional visualization of the results is available at www.enigma-viewer.org., Conclusion: WM tracts that mature later in life appeared more sensitive to the pathophysiology of schizophrenia and were more susceptible to faster age-related decline in FA values. Hum Brain Mapp 37:4673-4688, 2016. © 2016 Wiley Periodicals, Inc., Competing Interests: Authors declare no conflict of interest., (© 2016 Wiley Periodicals, Inc.)