Railway switch machine is essential for maintaining the safety and punctuality of train operations.A data-driven fault diagnosis scheme for railway switch machine using tensor machine and multi-representation monitori...
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Railway switch machine is essential for maintaining the safety and punctuality of train operations.A data-driven fault diagnosis scheme for railway switch machine using tensor machine and multi-representation monitoring data is developed *** existing methods,this approach takes into account the spatial information of the time series monitoring data,aligning with the domain expertise of on-site manual ***,a multi-sensor fusion tensor machine is designed to improve single signal data’s limitations in insufficient ***,one-dimensional signal data is preprocessed and transformed into two-dimensional ***,the fusion feature tensor is created by utilizing the images of the three-phase current and employing the CANDE-COMP/PARAFAC(CP)decomposition ***,the tensor learning-based model is built using the extracted fusion feature *** developed fault diagnosis scheme is valid with the field three-phase current *** experiment indicates an enhanced performance of the developed fault diagnosis scheme over the current approach,particularly in terms of recall,precision,and F1-score.
The goals of the current study were to use behavioral and pupillary measures to examine working memory on a spatial n-back task in 8-20-year-olds with youth-onset psychosis or ADHD (Combined subtype) and healthy contr...
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The goals of the current study were to use behavioral and pupillary measures to examine working memory on a spatial n-back task in 8-20-year-olds with youth-onset psychosis or ADHD (Combined subtype) and healthy controls to determine the contribution of different attentional factors to spatial working memory impairments, and to examine if age-related changes in performance differed across groups. Although both clinical groups had lower perceptual sensitivity on both 0- and 1-back, there was no evidence of an impairment in spatial working memory or differential order effects on the 0-back. Instead, results suggest that both clinical groups had difficulty encoding the stimuli. They also appeared to have difficulty maintaining attention and/or readiness to respond, and, to a lesser extent, recruiting resources on a trial-to-trial basis. It is likely that these attentional problems prevented the clinical groups from encoding the stimuli effectively and contributed to their general performance deficits. (c) 2009 Elsevier B.V. All rights reserved.
A quantum mechanics/molecular mechanics (QM/MM) approach is a broadly used tool in computational enzymology. Treating the QM region with a high-level DFT method is one of the important branches. Here, taking leaf-bran...
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A quantum mechanics/molecular mechanics (QM/MM) approach is a broadly used tool in computational enzymology. Treating the QM region with a high-level DFT method is one of the important branches. Here, taking leaf-branch compost cutinase-catalyzed polyethylene terephthalate depolymerization as an example, the convergence behavior of energy barriers as well as key structural and charge features with respect to the size of the QM region (up to 1000 atoms) is systematically investigated. BP86/6-31G(d)//CHARMM and M06-2X/6-311G(d,p)//CHARMM level of theories were applied for geometry optimizations and single-point energy calculations, respectively. Six independent enzyme conformations for all the four catalytic steps (steps (i)-(iv)) were considered. Most of the twenty-four cases show that at least 500 QM atoms are needed while only two rare cases show that similar to 100 QM atoms are sufficient for convergence when only a single conformation was considered. This explains why most previous studies showed that 500 or more QM atoms are required while a few others showed that similar to 100 QM atoms are sufficient for DFT/MM calculations. More importantly, average energy barriers and key structural/charge features from six conformations show an accelerated convergence than that in a single conformation. For instance, to reach energy barrier convergence (within 2.0 kcal mol-1) for step (ii), only similar to 100 QM atoms are required if six conformations are considered while 500 or more QM atoms are needed with a single conformation. The convergence is accelerated to be more rapid if hundreds and thousands of conformations were considered, which aligns with previous findings that only several dozens of QM atoms are required for convergence with semi-empirical QM/MM MD simulations. Both QM region sizes and conformation numbers have an impact on modelling enzyme reactions. The convergence behavior of energy barriers and features with respect to the QM region size can be acceler
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