Inverse Problem Solution and Regularization Parameter Selection for Current Distribution Reconstruction in Switching Arcs by Inverting Magnetic Fields

Current density distribution in electric arcs inside low voltage circuit breakers is a crucial parameter for us to understand the complex physical behavior during the arcing process. In this paper, we investigate the inverse problem of reconstructing the current density distribution in arcs by inverting the magnetic fields. A simplified 2D arc chamber is considered. The aim of this paper is the computational side of the regularization method, regularization parameter selection strategies, and the estimation of systematic error. To address the ill-posedness of the inverse problem, Tikhonov regularization is analyzed, with the regularization parameter chosen by Morozov’s discrepancy principle, the L-curve, the generalized cross-validation, and the quasi-optimality criteria. The provided range of regularization parameter selection strategies is much wider than in the previous works. Effects of several features on the performance of these criteria have been investigated, including the signal-to-noise ratio, dimension of measurement space, and the measurement distance. The numerical simulations show that the generalized cross-validation and quasi-optimality criteria provide a more satisfactory performance on the robustness and accuracy. Moreover, an optimal measurement distance can be expected when using a planner sensor array to perform magnetic measurements

MOOCs as an Alternative for Teacher Professional Development. Examining Learner Persistence in One Chinese MOOC

Massive Open Online Courses (MOOCs) have developed into a significant international movement, showing great promise in addressing equity, quality, and efficiency issues in global education. To date, many MOOCs have been developed specifically for teacher professional development (TPD). In this regard, an important empirical question remains to be addressed: How and to what extent can MOOCs support equity, quality, and efficiency in teacher professional development? To help fill this knowledge gap, this study, conducted from 2014 to 2016, focused on persistent teacher-learners in a TPD MOOC that was offered for seven consecutive rounds by the X-Learning Center of Peking University. The study found that more than 15% of the 105,383 teachers who enrolled in this MOOC were persistent teacher-learners, defined as learners who enrolled in multiple rounds. Data analysis showed that these persistent Keywords: MOOC, teacher professional development, persistent teacher-learners, self-regulated learning teacher-learners had diverse motivations for re-enrollment, including refreshing conceptual understanding, achieving higher scores, earning course certification, and discussing practical problems. The study also found that the persistent teacher learners developed self-regulated learning skills in the course of multiple rounds of the MOOC and showed significantly higher learning achievement than one-time enrollees. Qualitative and quantitative analysis of both clicklog data and interview data revealed additional insights into the persistent teacherlearners’ learning within the MOOC and their real-world teaching practice beyond the MOOC. Overall, this study contributes to an improved understanding of the potential of MOOCs as an alternative TPD delivery mode in developing countries and sheds light on the future design of effective TPD through MOOCs.This work was created with financial support from the UK Government’s Department for International Development and the International Development Research Centre, Canada. The views expressed in this work are those of the authors and do not necessarily represent those of the UK Government’s Department for International Development; the International Development Research Centre, Canada or its Board of Governors; or the Foundation for Information Technology Education and Developmen

EFFECT OF THE Si POWDER ADDITIONS ON THE PROPERTIES OF SiC COMPOSITES

By means of transient plastic phase process, the SiC silicon carbide kiln furniture materials were produced through adding Si powder to SiC materials. At the condition of the same additions of SiO2 powder, the effect of the Si powder additions on properties of silicon carbide materials after sintered at 1450°C for 3 h in air atmosphere was studied by means of SEM and other analysis methods. The results showed that silicon powder contributes to both sintering by liquid state and plastic phase combination to improve the strength of samples. When the Si powder additions is lower than 3.5 %, the density and strength of samples increase and porosity decrease with increasing Si powder additions. However when the Si powder additions is higher than 3.5 %, the density and strength of samples decrease and porosity increase with increasing Si powder additions. With increasing of Si additions, the residual strength of sample after thermal shocked increased and linear change rate decreased, and get to boundary value when Si additions is 4.5 %. The results also indicated that at the same sintering temperature, the sample with 3.5 % silicon powder has maximum strength

Cognitive deficits induced by multi-walled carbon nanotubes via the autophagic pathway

This document is the Accepted Manuscript version, made available under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License CC BY NC-ND 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.Multi-walled carbon nanotubes (MWCNTs) have shown potential applications in many fields, especially in the field of biomedicine. Several studies have reported that MWCNTs induce apoptosis and oxidative damage in nerve cells during in vitro experiments. However, there are few studies focused on the neurotoxicity of MWCNTs used in vivo. Many studies have reported that autophagy, a cellular stress response to degrade damaged cell components, can be activated by diverse nanoparticles. In this study, we investigated the neurotoxic effects of MWCNTs on hippocampal synaptic plasticity and spatial cognition in rats. Then, we used an inhibitor of autophagy called chloroquine (CQ) to examine whether autophagy plays an important role in hippocampal synaptic plasticity, since this was damaged by MWCNTs. In this study, adult male Wister rats were randomly divided into three groups: a control group, a group treated with MWCNTs (2.5mg/kg/day) and a group treated with MWCNTs+CQ (20mg/kg/day). After two-weeks of intraperitoneal (i.p.) injections, rats were subjected to the Morris water maze (MWM) test, and the long-term potentiation (LTP) and other biochemical parameters were determined. Results showed that MWCNTs could induce cognitive deficits, histopathological alteration and changes of autophagy level (increased the ratio of LC3 II /LC3 I and the expression of Beclin-1). Furthermore, we found that CQ could suppress MWCNTs-induced autophagic flux and partly rescue the synapse deficits, which occurred with the down-regulation of NR2B (a subunit of NMDA receptor) and synaptophysin (SYP) in the hippocampus. Our results suggest that MWCNTs could induce cognitive deficits in vivo via the increased autophagic levels, and provide a potential strategy to avoid the adverse effects of MWCNTs.Peer reviewedFinal Accepted Versio

Effects of nanoparticle zinc oxide on spatial cognition and synaptic plasticity in mice with depressive-like behaviors

Background: Nanomaterials, as a new kind of materials, have been greatly applied in different fields due to their special properties. With the industrialization of nanostructured materials and increasing public exposure, the biosafety and potential influences on central nervous system (CNS) have received more attention. Nanosized zinc oxide (nanoZnO) was suggested to up-regulate neuronal excitability and to induce glutamate release in vitro. Therefore, we hypothesized nanoparticles of nanoZnO may lead to changes in balance of neurotransmitter or neuronal excitability of CNS. This study was to investigate if there were effects of nanoZnO on animal model of depression. Methods: Male Swiss mice were given lipopolysaccharides (LPS, 100 mu g/kg, 100 mu g/ml, every other day, 8 times, i.p.) from weaning to induce depressive-like behaviors. NanoZnO (5.6 mg/kg, 5.6 mg/ml, every other day, 8 times, i.p.) was given as the interaction. The mouse model was characterized using the methods of open field test, tail suspension test and forced swim test. Furthermore, the spatial memory was evaluated using Morris water maze (MWM) and the synaptic plasticity was assessed by measuring the long-term potentiation (LTP) in the perforant pathway (PP) to dentate gyrus (DG) in vivo. Results: Results indicated that model mice showed disrupted spatial memory and LTP after LPS injections and the behavioral and electrophysiological improvements after nanoZnO treatment. Conclusion: Data suggested that nanoZnO may play some roles in CNS of mental disorders, which could provide some useful direction on the new drug exploring and clinical researches.Peer reviewe

A novel coping metal material CoCrCu alloy fabricated by selective laser melting with antimicrobial and antibiofilm properties

This document is the Accepted Manuscript version of the following article: Ling Ren, Kaveh Memarzadeh, Shuyuan Zhang, Ziqing Sun, Chunguang Yang, Guogang Ren, Robert T. Allaker, Ke Yang, ‘A novel coping metal material CoCrCu alloy fabricated by selective laser melting with antimicrobial and antibiofilm properties’, Vol. 67: 461-467, October 2016, doi: http://dx.doi.org/10.1016/j.msec.2016.05.069. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ .OBJECTIVE: The aim of this study was to fabricate a novel coping metal CoCrCu alloy using a selective laser melting (SLM) technique with antimicrobial and antibiofilm activities and to investigate its microstructure, mechanical properties, corrosion resistance and biocompatibility. METHODS: Novel CoCrCu alloy was fabricated using SLM from a mixture of commercial CoCr based alloy and elemental Cu powders. SLM CoCr without Cu served as control. Antibacterial activity was analyzed using standard antimicrobial tests, and antibiofilm properties were investigated using confocal laser scanning microscope. Cu distribution and microstructure were determined using scanning electron microscope, optical microscopy and X-ray diffraction. Corrosion resistance was evaluated by potential dynamic polarization and biocompatibility measured using an MTT assay. RESULTS: SLM CoCrCu alloys were found to be bactericidal and able to inhibit biofilm formation. Other factors such as microstructure, mechanical properties, corrosion resistance and biocompatibility were similar to those of SLM CoCr alloys. SIGNIFICANCE: The addition of appropriate amounts of Cu not only maintains normal beneficial properties of CoCr based alloys, but also provides SLM CoCrCu alloys with excellent antibacterial and antibiofilm capabilities. This material has the potential to be used as a coping metal for dental applications.Peer reviewe

Learning List-wise Representation in Reinforcement Learning for Ads Allocation with Multiple Auxiliary Tasks

With the recent prevalence of reinforcement learning (RL), there have been tremendous interests in utilizing RL for ads allocation in recommendation platforms (e.g., e-commerce and news feed sites). For better performance, recent RL-based ads allocation agent makes decisions based on representations of list-wise item arrangement. This results in a high-dimensional state-action space, which makes it difficult to learn an efficient and generalizable list-wise representation. To address this problem, we propose a novel algorithm to learn a better representation by leveraging task-specific signals on Meituan food delivery platform. Specifically, we propose three different types of auxiliary tasks that are based on reconstruction, prediction, and contrastive learning respectively. We conduct extensive offline experiments on the effectiveness of these auxiliary tasks and test our method on real-world food delivery platform. The experimental results show that our method can learn better list-wise representations and achieve higher revenue for the platform.Comment: arXiv admin note: text overlap with arXiv:2109.04353, arXiv:2204.0037