Teachers’ perceptions and practices in relation to the integration of digital technologies in kindergartens in China: an interpretive multi-method study

The present study aimed to provide insights into the integration of digital technologies in the kindergartens of China from the perspectives of teachers, with a specific focus on teachers’ perceptions, pedagogical practices and the multiple contextual factors behind them. Given the focus of the study on the particular context of China, this study did not intend to be representative. The sociocultural ideas developed by Vygotsky were adopted to provide the theoretical bases for this study, whilst the TPACK model (Mishra & Koehler, 2006) and its context framework (Porras-Hernandez & Salinas-Amescua, 2013) were employed to conceptualise some of the research findings. In order to empirically address the research questions regarding participants’ perceptions, practices and their relationships with contexts, this study employed the two-phase interpretive qualitative research design, which included individual interviews of fourteen kindergarten teachers and five case studies with kindergarten teachers and their classrooms in China. In specific, I adopted the case study to deeply understand participating teachers’ pedagogical approaches when integrating digital technologies. The data were generated from individual interviews, classroom observations and document reviews, and then were analysed through the thematic approach and multimodal approach. In particular, both inductive and deductive approach were applied to analyse the data in a reflexive way. This thesis made several empirical and theoretical contributions to the existent knowledge base. Firstly, the findings indicated that the participating teachers tended to foster a greater use of digital technologies for consumption purposes, rather than for creative functions. Secondly, the pedagogical practices of teachers in the present study were interconnected with their understandings of digital technologies and pedagogical beliefs. Thirdly, it was found that teachers’ perceptions and practices were shaped by multiple and interrelated contextual factors, among which the meso-level kindergarten context played a more important role than micro- and macro-level forces. Lastly, the thesis theoretically adapted the context framework for TPACK developed by Porras-Hernandez and Salinas-Amescua (2013) to a networked framework, providing the basis for researchers to study more complex interrelationships between contextual systems in the future

Diffraction-Free Bloch Surface Waves

In this letter, we demonstrate a novel diffraction-free Bloch surface wave (DF-BSW) sustained on all-dielectric multilayers that does not diffract after being passed through three obstacles or across a single mode fiber. It can propagate in a straight line for distances longer than 110 {\mu}m at a wavelength of 633 nm and could be applied as an in-plane optical virtual probe, both in air and in an aqueous environment. The ability to be used in water, its long diffraction-free distance, and its tolerance to multiple obstacles make this DF-BSW ideal for certain applications in areas such as the biological sciences, where many measurements are made on glass surfaces or for which an aqueous environment is required, and for high-speed interconnections between chips, where low loss is necessary. Specifically, the DF-BSW on the dielectric multilayer can be used to develop novel flow cytometry that is based on the surface wave, but not the free space beam, to detect the surface-bound targets

Extending the Propagation Distance of a Silver Nanowire Plasmonic Waveguide with a Dielectric Multilayer Substrate

Chemical synthesized silver nanowires have been proved to be the efficient architecture for Plasmonic waveguides, but the high propagation loss prevents their widely applications. Here, we demonstrate that the propagation distance of the plasmons along the Ag NW can be extended if the Ag NW was placed on a dielectric multilayer substrate containing a photonic band gap, but not placed on a commonly used glass substrate. The propagation distance at 630 nm wavelength can reach 16 um even that the Ag NW is as thin as 90 nm in diameter. Experimental and simulation results further show that the polarization of this propagating plasmon mode was nearly parallel to the surface of the dielectric multilayer, so it was excited by a transverse-electric polarized Bloch surface wave propagating along a polymer nanowire with diameter at only about 170 nm on the same dielectric multilayer. Numerical simulations were also carried out and consistent with the experiment results. Our work provides a platform to extend the propagation distance of plasmonic waveguide and also for the integration between photonic and plasmonic waveguides on the nanometre scale.Comment: 5 pages, 4 figure

A Genome-Scale Model of \u3cem\u3eShewanella piezotolerans\u3c/em\u3e Simulates Mechanisms of Metabolic Diversity and Energy Conservation

Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea

Design, Fabrication, Simulation and Characterization of a Novel Dual-Sided Microelectrode Array for Deep Brain Recording and Stimulation

In this paper, a novel dual-sided microelectrode array is specially designed and fabricated for a rat Parkinson’s disease (PD) model to study the mechanisms of deep brain stimulation (DBS). The fabricated microelectrode array can stimulate the subthalamic nucleus and simultaneously record electrophysiological information from multiple nuclei of the basal ganglia system. The fabricated microelectrode array has a long shaft of 9 mm and each planar surface is equipped with three stimulating sites (diameter of 100 μm), seven electrophysiological recording sites (diameter of 20 μm) and four sites with diameter of 50 μm used for neurotransmitter measurements in future work. The performances of the fabricated microelectrode array were characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS) and cyclic voltammetry. In addition, the stimulating effects of the fabricated microelectrode were evaluated by finite element modeling (FEM). Preliminary animal experiments demonstrated that the designed microelectrode arrays can record spontaneous discharge signals from the striatum, the subthalamic nucleus and the globus pallidus interna. The designed and fabricated microelectrode arrays provide a powerful research tool for studying the mechanisms of DBS in rat PD models

A Design Method for Gammachirp Filterbank for Loudness Compensation in Hearing Aids

Because the hearing impaired often experience different degrees of hearing loss along with the loss of frequencies, the loudness compensation algorithm in hearing aids decomposes the speech signal and compensates with different frequency bands based on their audiograms. However, the speech quality of the compensated signal is unsatisfactory because the traditional filterbanks fail to fully consider the characteristics of human hearing and personalized hearing loss. In this study, an effective design for the gammachirp filterbank for the loudness compensation algorithm was proposed to improve the speech quality of hearing aids. Firstly, a multichannel gammachirp filterbank was employed to decompose the signals. Then, the adjacent bands were merged into one channel, guided by the proposed combination method. After obtaining the personalized filterbank, each band conducted a loudness compensation to match the requirements of the audiograms. The excellent advantage of the gammachirp filterbank is that it can simulate the characteristics of the basilar membrane. Furthermore, the novel channel combination method considers the information from the audiograms and the relationship between frequency ranges and speech intelligibility. The experimental results showed that the proposed multichannel gammachirp filterbank achieves better speech signal decomposition and synthesis, and good performance can be gained with fewer channels. The loudness compensation algorithm based on the gammachirp filterbank effectively improves sentence intelligibility. The sentence recognition rate of the proposed method is higher than that of a system with a gammatone filterbank by approximately 13%

Sustainability Assessment of Autonomous Regions in China Using GRA-SPA Method

Sustainability development is a core issue in autonomous regions’ construction and development. The paper evaluated the sustainability development of the five autonomous regions in Western China from 2010 to 2019. In order to further analyze the sustainable development level of the autonomous regions, it is compared with the three provinces with the largest GDP in Central China in the past three years, and similarly, with the three provinces in Eastern China. A new weighting method was proposed by combining the grey relational analysis (GRA) and set pair analysis (SPA) methods that not only analyze the correlation between indicators and ideal points but also analyze the status and development trend. The method can ensure the objectivity of indicator weight. Firstly, the ideal reference point is determined by the grey correlation degree between the indicator and the ideal positive point. Secondly, the indicator and the ideal reference point constitute a set pair system, and the relation number is used further to analyze the status and development trend of the indicator to determine the weight objectively. The sustainability results showed that the progress of the autonomous regions’ sustainable development in China was increased slowly in 2010–2019. For example, Ningxia and Xinjiang saw the slowest growth. The prime reason is that economic sustainability has declined severely. Although Inner Mongolia presented the highest increasing trends, the growth rate value was 0.75%. In contrast, other autonomous regions showed a negative growth trend. Regarding sustainable development in three dimensions, the economic sustainability performance of autonomous regions is not ideal, but the environmental sustainability performance is the most ideal. This conclusion implicates the necessity and urgency of improving the coordinated development of the three dimensions of autonomous regions in China

Traffic Flow Prediction Method Based on Seasonal Characteristics and SARIMA-NAR Model

Traffic flow is used as an essential indicator to measure the performance of the road network and a pivotal basis for road classification. However, the combined prediction model of traffic flow based on seasonal characteristics has been given little attention at present. Because the seasonal autoregressive integrated moving average model (SARIMA) has superior linear fitting characteristics, it is often used to process seasonal time series. In contrast, the non-autoregressive dynamic neural network (NAR) has a vital memory function and nonlinear interpretation capabilities. They are suitable for constructing combined forecasting models. The traffic flow time series of a highway in southwest China is taken as the research object in this paper. Combining the SARIMA (0,1,2) (0,1,2)12 model and the NAR model with 15 hidden layer neurons and fourth-order delay, two combined models are constructed: the linear and nonlinear component combination method is realized by the SARIMA-NAR combination model 1, and the MSE weight combination method is used by the SARIMA-NAR combination model 2. We calculated that the prediction accuracy of SARIMA-NAR combined model 1 is as high as 0.92, and the prediction accuracy of SARIMA-NAR combined model 2 is 0.90. In addition, the traffic flow forecast under the influence of the epidemic is also discussed. Through a comprehensive comparison of multiple indicators, the results show that the SARIMA-NAR combined model 1 has better road traffic flow fitting and prediction effects and is suitable for the greater volatility of traffic flow during the epidemic. This model improves the effectiveness and reliability of traffic flow forecasting, and the forecasting process is more convenient and efficient

Baicalin Attenuates Alcoholic Liver Injury through Modulation of Hepatic Oxidative Stress, Inflammation and Sonic Hedgehog Pathway in Rats

Background/Aims: Lipid accumulation, inflammatory responses and oxidative stress have been implicated in the pathology of alcoholic liver disease (ALD). Targeting inhibition of these features may provide a promising therapeutic strategy for ALD. Baicalin, a flavonoid isolated from Scutellaria baicalensis Georgi, has been shown to exert a hepatoprotective effect. However, its effects on ALD remain obscure. This study was aimed to investigate the effects of baicalin on alcohol-induced liver injury and its related mechanisms. Methods: For in vivo experiments, rats were supplied intragastrical administration of alcohol continuously for 4 or 8 weeks, and then received baicalin treatment in the latter 4 weeks in the presence / absence of alcohol intake. Liver histology and function, inflammatory cytokines, oxidative mediators, and the components of the Sonic hedgehog pathway were evaluated. For in vitro experiments, alcohol-stimulated human normal liver cells LO2 were used. Results: Baicalin treatment significantly alleviated alcoholic liver injury, improved liver function impaired by alcohol, and inhibited hepatocytes apoptosis. In addition, baicalin decreased the expression levels of proinflammatory cytokines TNF-α, IL-1β, IL-6) and malonyldialdehyde (MDA), and increased the activities of antioxidant enzymes SOD and GSH-Px. Furthermore, baicalin modulated the activation of Sonic hedgehog (Shh) pathway. Administration of baicalin upregulated the expression of sonic hedgehog (Shh), patched (Ptc), Smoothened (Smo), and Glioblastoma-1(Gli-1). Blockade of the Shh pathway in cyclopamine abolished the effects of baicalin in vitro. Conclusion: Both in vivo and in vitro experimental results indicate that baicalin exerts hepatoprotective roles in alcohol-induced liver injury through inhibiting oxidative stress, inflammatory response, and the regulation of the Shh pathway

In Vivo Neural Recording and Electrochemical Performance of Microelectrode Arrays Modified by Rough-Surfaced AuPt Alloy Nanoparticles with Nanoporosity

In order to reduce the impedance and improve in vivo neural recording performance of our developed Michigan type silicon electrodes, rough-surfaced AuPt alloy nanoparticles with nanoporosity were deposited on gold microelectrode sites through electro-co-deposition of Au-Pt-Cu alloy nanoparticles, followed by chemical dealloying Cu. The AuPt alloy nanoparticles modified gold microelectrode sites were characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and in vivo neural recording experiment. The SEM images showed that the prepared AuPt alloy nanoparticles exhibited cauliflower-like shapes and possessed very rough surfaces with many different sizes of pores. Average impedance of rough-surfaced AuPt alloy nanoparticles modified sites was 0.23 MΩ at 1 kHz, which was only 4.7% of that of bare gold microelectrode sites (4.9 MΩ), and corresponding in vitro background noise in the range of 1 Hz to 7500 Hz decreased to 7.5 μ V rms from 34.1 μ V rms at bare gold microelectrode sites. Spontaneous spike signal recording was used to evaluate in vivo neural recording performance of modified microelectrode sites, and results showed that rough-surfaced AuPt alloy nanoparticles modified microelectrode sites exhibited higher average spike signal-to-noise ratio (SNR) of 4.8 in lateral globus pallidus (GPe) due to lower background noise compared to control microelectrodes. Electro-co-deposition of Au-Pt-Cu alloy nanoparticles combined with chemical dealloying Cu was a convenient way for increasing the effective surface area of microelectrode sites, which could reduce electrode impedance and improve the quality of in vivo spike signal recording