The Benefits of the Suzuki Method for Children’s Cognitive and Physical Development: A Descriptive Phenomenological Study of Suzuki Specialists

This descriptive phenomenological study aimed to explore the experiences and perceptions of Suzuki specialists regarding the cognitive and physical development of children participating in the Suzuki method of music instruction. Music educators recognize the Suzuki method as a successful approach for delivering content and meeting music students’ needs. This study may provide a roadmap for conducting the Suzuki method with young students aged five to twelve. The lived experiences of Suzuki teachers provided a unique perspective for understanding how Suzuki instruction contributes to children’s physical and cognitive development. This study explored the following central research question: How do Suzuki specialists describe their teaching experiences? The research sub-questions concerned how Suzuki specialists described their experiences teaching elements related to physical and cognitive development. Data were collected through focus group interviews, and epoché and horizontalization were employed for the data collection and analysis. Music teachers could enhance children’s cognitive and physical development by considering and applying this study’s findings, which provide practical information describing how Suzuki specialists used the method to enhance children’s development. This research on Suzuki specialists’ lived experiences identified five distinct themes: 1) parental involvement, 2) encouragement with a positive mindset, 3) play by ear, 4) group play, and 5) fine muscle development. The findings may also contribute to the literature that describes the theories and practices involved in the effective teaching and learning of instrumental music

Mothers’ experience of caring for home-quarantined children after close contact with COVID-19 in Korea: an exploratory qualitative study

Purpose The world saw a shift into a new society consequent to the coronavirus disease 2019 (COVID-19), which made home quarantine mandatory for a person in close contact with those who tested positive. For children, however, home quarantine was not limited only to themselves but parents, especially mothers were involved and required to quarantine. This qualitative study aimed to explore and understand mothers’ experience and their related psychosocial issues while caring for their school-aged children in Korea, who had to home quarantine after coming in close contact with COVID-19 positive individuals. Methods Data were collected from October 2020 to January 2021 via in-depth, semi-structured interviews with nine mothers of children who had to home quarantine. Interviews were conducted face-to-face in an independent space near the participant’s home or workplace (n=5) or via online platforms or telephone (n=4). The data were analyzed using thematic analysis through several iterative team meetings. Results Thematic analysis revealed the following four themes: “Unable to be relieved due to uncertain situations surrounding me,” “Blame and hurt toward me, others, and one another,” “Pulling myself together for my children in my broken daily life,” and “Changes in the meaning of life amid COVID-19.” Conclusion The narratives show that mothers experienced psychosocial difficulties while caring for their children during home quarantine. It is necessary to reduce the social stigma toward individuals in home quarantine and establish policies to ensure work-family compatibility for such mothers

Renormalization group theory for percolation in time-varying networks

Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether a given source node can communicate with a destination node along paths of active links is equivalent to a percolation problem. Our theory maps the temporal existence of multi-hop paths on an effective two-state Markov process. We show analytically how this Markov process converges towards a memory-less Bernoulli process as the hop distance between source and destination node increases. Our work extends classical percolation theory to the dynamic case and elucidates temporal correlations of message losses. Quantification of temporal correlations has implications for the design of wireless communication and control protocols, e.g. in cyber-physical systems such as self-organized swarms of drones or smart traffic networks.Comment: 8 pages, 3 figure

Develmental patterns of Korean EFL learners' English argument structure constructions

The present study aims to explore developmental patterns of constructional knowledge of Korean EFL learners. The study asked120 Korean learners of English to carry out a sentence sorting and a translation task, and investigated how the participants atthree different proficiency levels use their constructional knowledge to comprehend English sentences. The results from thesorting task showed that the learners in the beginner group relied more heavily on verb-centered sorting than the learners in theintermediate group. The results from the translation task revealed that the L2 learners ability to comprehend complexconstructions is highly correlated with their proficiency in the target language. The study suggests that L2 learners' constructionalknowledge is acquired incrementally as their exposure to the target language extends, supporting one of the main premises of theusage-based approach to language and language acquisition.OAIID:oai:osos.snu.ac.kr:snu2013-01/102/0000001658/1SEQ:1PERF_CD:SNU2013-01EVAL_ITEM_CD:102USER_ID:0000001658ADJUST_YN:NEMP_ID:A002679DEPT_CD:707CITE_RATE:0FILENAME:developmental patterns of korean efl learners english argument structure constructions.docDEPT_NM:영어교육과EMAIL:[email protected]:

Automated Brittle Fracture Rate Estimator for Steel Property Evaluation Using Deep Learning After Drop-Weight Tear Test

This study proposes an automated brittle fracture rate (BFR) estimator using deep learning. As the demand for line-pipes increases in various industries, the need for BFR estimation through dropweight tear test (DWTT) increases to evaluate steel's property. Conventional BFR or ductile fracture rate (DFR) estimation methods require an expensive 3D scanner. Alternatively, a rule-based approach is used with a single charge-coupled device (CCD) camera. However, it is sensitive to the hyper-parameter. To solve these problems, we propose an approach based on deep learning that has recently been successful in the fields of computer vision and image processing. The method proposed in this study is the first to use deep learning approach for BFR estimation. The proposed method consists of a VGG-based U-Net (VU-Net) which is inspired by U-Net and fully convolutional network (FCN). VU-Net includes a deep encoder and a decoder. The encoder is adopted from VGG19 and transferred with a pre-trained model with ImageNet. In addition, the structure of the decoder is the same as that of the encoder, and the decoder uses the feature maps of the encoder through concatenation operation to compensate for the reduced spatial information. To analyze the proposed VU-Net, we experimented with different depths of networks and various transfer learning approaches. In terms of accuracy used in real industrial application, we compared the proposed VU-Net with U-Net and FCN to evaluate the performance. The experiments showed that VU-Net was the accuracy of approximately 94.9 %, and was better than the other two, which had the accuracies of about 91.8 % and 93.7 %, respectively.11Ysciescopu

Cerebral perfusion simulation using realistically generated synthetic trees for healthy and stroke patients

Background and objective Cerebral vascular diseases are among the most burdensome diseases faced by society. However, investigating the pathophysiology of diseases as well as developing future treatments still relies heavily on expensive in-vivo and in-vitro studies. The generation of realistic, patient-specific models of the cerebrovascular system capable of simulating hemodynamics and perfusion promises the ability to simulate diseased states, therefore accelerating development cycles using in silico studies and opening opportunities for the individual assessment of diseased states, treatment planning, and the prediction of outcomes. By providing a patient-specific, anatomically detailed and validated model of the human cerebral vascular system, we aim to provide the basis for future in silico investigations of the cerebral physiology and pathology. Methods In this retrospective study, a processing pipeline for patient-specific quantification of cerebral perfusion was developed and applied to healthy individuals and a stroke patient. Major arteries are segmented from 3T MR angiography data. A synthetic tree generation algorithm titled tissue-growth based optimization (GBO) is used to extend vascular trees beyond the imaging resolution. To investigate the anatomical accuracy of the generated trees, morphological parameters are compared against those of 7 T MRI, 9.4 T MRI, and dissection data. Using the generated vessel model, hemodynamics and perfusion are simulated by solving one-dimensional blood flow equations combined with Darcy flow equations. Results Morphological data of three healthy individuals (mean age 47 years ± 15.9 [SD], 2 female) was analyzed. Bifurcation and physiological characteristics of the synthetically generated vessels are comparable to those of dissection data. The inability of MRI based segmentation to resolve small branches and the small volume investigated cause a mismatch in the comparison to MRI data. Cerebral perfusion was estimated for healthy individuals and a stroke patient. The simulated perfusion is compared against Arterial-Spin-Labeling MRI perfusion data. Good qualitative agreement is found between simulated and measured cerebral blood flow (CBF). Ischemic regions are predicted well, however ischemia severity is overestimated. Conclusions GBO successfully generates detailed cerebral vascular models with realistic morphological parameters. Simulations based on the resulting networks predict perfusion territories and ischemic regions successfully

Enhanced efficiency of crystalline Si solar cells based on kerfless-thin wafers with nanohole arrays

Several techniques have been proposed for kerfless wafering of thin Si wafers, which is one of the most essential techniques for reducing Si material loss in conventional wafering methods to lower cell cost. Proton induced exfoliation is one of promising kerfless techniques due to the simplicity of the process of implantation and cleaving. However, for application to high efficiency solar cells, it is necessary to cope with some problems such as implantation damage removal and texturing of (111) oriented wafers. This study analyzes the end-of-range defects at both kerfless and donor wafers and ion cutting sites. Thermal treatment and isotropic etching processes allow nearly complete removal of implantation damages in the cleaved-thin wafers. Combining laser interference lithography and a reactive ion etch process, a facile nanoscale texturing process for the kerfless thin wafers of a (111) crystal orientation has been developed. We demonstrate that the introduction of nanohole array textures with an optimal design and complete damage removal lead to an improved efficiency of 15.2% based on the kerfless wafer of a 48 mu m thickness using the standard architecture of the Al back surface field

SALM4 suppresses excitatory synapse development by cis-inhibiting trans-synaptic SALM3-LAR adhesion

Synaptic adhesion molecules regulate various aspects of synapse development, function and plasticity. These functions mainly involve trans-synaptic interactions and positive regulations, whereas cis-interactions and negative regulation are less understood. Here we report that SALM4, a member of the SALM/Lrfn family of synaptic adhesion molecules, suppresses excitatory synapse development through cis inhibition of SALM3, another SALM family protein with synaptogenic activity. Salm4-mutant (Salm4) mice show increased excitatory synapse numbers in the hippocampus. SALM4 cis-interacts with SALM3, inhibits trans-synaptic SALM3 interaction with presynaptic LAR family receptor tyrosine phosphatases and suppresses SALM3-dependent presynaptic differentiation. Importantly, deletion of Salm3 in Salm4 mice (Salm3, Salm4) normalizes the increased excitatory synapse number. These results suggest that SALM4 negatively regulates excitatory synapses via cis inhibition of the trans-synaptic SALM3-LAR adhesion. © The Author(s) 2016110101sciescopu

Calsyntenin-3 Interacts With Both α- And β-Neurexins in the Regulation of Excitatory Synaptic Innervation in Specific Schaffer Collateral Pathways

Calsyntenin-3 (Clstn3) is a postsynaptic adhesion molecule that induces presynaptic differentiation via presynaptic neurexins (Nrxns), but whether Nrxns directly bind to Clstn3 has been a matter of debate. Here, using LC-MS/MS-based protein analysis, confocal microscopy, RNAscope assays, and electrophysiological recordings, we show that β-Nrxns directly interact via their LNS domain with Clstn3 and Clstn3 cadherin domains. Expression of splice site 4 (SS4) insert-positive β-Nrxn variants, but not insert-negative variants, reversed the impaired Clstn3 synaptogenic activity observed in Nrxn-deficient neurons. Consistently, Clstn3 selectively formed complexes with SS4-positive Nrxns in vivo Neuron-specific Clstn3 deletion caused significant reductions in number of excitatory synaptic inputs. Moreover, expression of Clstn3 cadherin domains in CA1 neurons of Clstn3 conditional knockout mice rescued structural deficits in excitatory synapses, especially within the stratum radiatum layer. Collectively, our results suggest that Clstn3 links to SS4-positive Nrxns to induce presynaptic differentiation and orchestrate excitatory synapse development in specific hippocampal neural circuits, including Schaffer collateral afferents. © 2020 Kim et al.1