Attitudes towards Digital Game-based Learning of Chinese Primary School English Teachers

As a result of technological advancement, the educational landscape in the field of language education has been experiencing a significant evolution. Educational gaming, as a newly emerged paradigm of online learning, has been explored for its potential in language teaching. Teachers’ attitudes and needs are crucial in the implementation of digital gaming into the classroom. However, few previous attitude studies have focused on English Language Teaching (ELT) and young learners, with even less conducted in the context of China, where the potential market for ELT is massive. Having identified the potential of Digital Game-based Learning (DGBL) in China, the Knowledge Transfer Partnership (KTP) project was undertaken, in order to develop a DGBL platform to help Chinese young learners to learn English. This current study, focusing on the attitudes of teachers, constitutes a part of a large scale needs analysis regarding the implementation of DGBL in the context of China. In aiming to broaden the scope of understanding, a mixed methods design was employed to measure the attitudes of teachers in both a qualitative and quantitative manner. A total of 76 Chinese primary school English teachers completed the survey, and 3 of them were interviewed. The results revealed that, generally, the teachers hold positive attitudes towards using digital gaming to assist their English teaching. The potential of DGBL in motivating students and teaching vocabulary was highlighted in the investigation. Parallel with potential barriers identified, teachers also suggested a number of facilitative approaches for the implementation, among which the integration of digital games with the syllabus was raised as the first concern by most of the teachers. It was also concluded that administrative and financial support is a prerequisite for the implementation of DGBL, and that equality of participation in the games is a key factor in ensuring the efficiency of DGBL in classroom practices

Whole-genome shotgun sequencing unravels the influence of environmental microbial co-infections on the treatment efficacy for severe pediatric infectious diseases

BackgroundThe microbiome plays a pivotal role in mediating immune deviation during the development of early-life viral infections. Recurrent infections in children are considered a risk factor for disease development. This study delves into the metagenomics of the microbiome in children suffering from severe infections, seeking to identify potential sources of these infections.AimsThe aim of this study was to identify the specific microorganisms and factors that significantly influence the treatment duration in patients suffering from severe infections. We sought to understand how these microbial communities and other variables may affect the treatment duration and the use of antibiotics of these patients with severe infections.MethodWhole-genome shotgun sequencing was conducted on samples collected from children aged 0–14 years with severe infections, admitted to the Pediatrics Department of Xiamen First Hospital. The Kraken2 algorithm was used for taxonomic identification from sequence reads, and linear mixed models were employed to identify significant microorganisms influencing treatment duration. Colwellia, Cryptococcus, and Citrobacter were found to significantly correlate with the duration of clinical treatment. Further analysis using propensity score matching (PSM) and rank-sum test identified clinical indicators significantly associated with the presence of these microorganisms.ResultsUsing a linear mixed model after removed the outliers, we identified that the abundance of Colwellia, Cryptococcus, and Citrobacter significantly influences the treatment duration. The presence of these microorganisms is associated with a longer treatment duration for patients. Furthermore, these microorganisms were found to impact various clinical measures. Notably, an increase in hospitalization durations and medication costs was observed in patients with these microorganisms. In patients with Colwellia, Cryptococcus, and Citrobacter, we discover significant differences in platelets levels. We also find that in patients with Cryptococcus, white blood cells, hemoglobin, and neutrophils levels are lower.ConclusionThese findings suggest that Colwellia, Cryptococcus, and Citrobacter, particularly Cryptococcus, could potentially contribute to the severity of infections observed in this cohort, possibly as co-infections. These microorganisms warrant further investigation into their pathogenic roles and mechanisms of action, as their presence in combination with disease-causing organisms may have a synergistic effect on disease severity. Understanding the interplay between these microorganisms and pathogenic agents could provide valuable insights into the complex nature of severe pediatric infections and guide the development of targeted therapeutic strategies

SC-Track: a robust cell tracking algorithm for generating accurate single-cell lineages from diverse cell segmentations

Computational analysis of fluorescent timelapse microscopy images at the single-cell level is a powerful approach to study cellular changes that dictate important cell fate decisions. Core to this approach is the need to generate reliable cell segmentations and classifications necessary for accurate quantitative analysis. Deep learning-based convolutional neural networks (CNNs) have emerged as a promising solution to these challenges. However, current CNNs are prone to produce noisy cell segmentations and classifications, which is a significant barrier to constructing accurate single-cell lineages. To address this, we developed a novel algorithm called Single Cell Track (SC-Track), which employs a hierarchical probabilistic cache cascade model based on biological observations of cell division and movement dynamics. Our results show that SC-Track performs better than a panel of publicly available cell trackers on a diverse set of cell segmentation types. This cell-tracking performance was achieved without any parameter adjustments, making SC-Track an excellent generalised algorithm that can maintain robust cell-tracking performance in varying cell segmentation qualities, cell morphological appearances and imaging conditions. Furthermore, SC-Track is equipped with a cell class correction function to improve the accuracy of cell classifications in multi-class cell segmentation time series. These features together make SC-Track a robust cell-tracking algorithm that works well with noisy cell instance segmentation and classification predictions from CNNs to generate accurate single-cell lineages and classifications

Can Philanthropy be Taught?

In recent years, colleges and universities have begun investing significant resources into an innovative pedagogy known as experiential philanthropy. The pedagogy is considered to be a form of service-learning. It is defined as a learning approach that provides students with opportunities to study social problems and nonprofit organizations and then make decisions about investing funds in them. Experiential philanthropy is intended to integrate academic learning with community engagement by teaching students not only about the practice of philanthropy but also how to evaluate philanthropic responses to social issues. Despite this intent, there has been scant evidence demonstrating that this type of pedagogic instruction has quantifiable impacts on students\u27 learning or their personal development. Therefore, this study explores learning and development outcomes associated with experiential philanthropy, and examines the efficacy of experiential philanthropy as a pedagogic strategy within higher education. Essentially, we seek to answer the question: Can philanthropy be taught

Pores Structure Change Induced by Heat Treatment in Cold-Sprayed Ti6Al4V Coating

In this study, the evolution of pores structure in cold-sprayed Ti6Al4V coating (TC4) was analyzed before and after 600-1100 °C heat treatment. It was found that almost no change happened to pores under the heat treatment temperature below 600 °C. When the heat treatment temperature was increased to 700 °C, the coating recrystallized, and pores turned to spheroid and healed because of the “bridging” effect. Some of the pores coarsened after 800 °C and 900 °C heat treatment. This kind of phenomenon grew severer when the heat treatment temperature increased to 1000 °C and 1100 °C. On the whole, with the increment of temperature, for the coating prepared at relatively low temperature, apparent porosity measured by image analysis method tended to go down first and then up, but it decreased all the time for the coating prepared at relatively high temperature. The reason for this phenomenon was contributed to the bonding state of particles in the coating. Only when there were fewer weakly bonded interfaces, the detachment between the particle interfaces which may be caused by release of residual stress did not occur, and there was no pores expansion and internal connectivity, so the porosity continuously decreased

Preparation of ZrB2-ZrC-SiC-ZrO2 nanopowders with in-situ grown homogeneously dispersed SiC nanowires

To explore the application of SiC nanowires (SiCnws) in ZrB2 based ceramic materials, a facile approach is reported to in situ synthesize homogeneously dispersed SiCnws in ZrB2-ZrC-SiC-ZrO2 nanopowders by pyrolyzing a B-Si-Zr containing sol precursor impregnated in polyurethane sponge. The sponge was used to provide porous skeletons for the growth of SiC nanowires and facilitate their uniform distribution in the powders. After heat-treatment of the precursor with a Si/Zr atomic ratio of 10 at 1500 °C for 2 h, ZrB2-ZrC-SiC-ZrO2 ceramic powders were obtained with an even and fine particle size of ~100 nm. The SiCnws were in a diameter of ~100 nm with a controllable length varying from tens to hundreds of microns by increasing the silicon content in the precursor. Moreover, the produced SiCnws were in high purity, and homogeneously dispersed in the hybrid nanopowders. The study can open up a feasible route to overcome the critical fabrication process in SiCnws reinforced ceramic matrix composites

Source localization of epileptic spikes using Multiple Sparse Priors

Objective: To evaluate epileptic source estimation using multiple sparse priors (MSP) inverse method and high-resolution, individual electrical head models. Methods: Accurate source localization is dependent on accurate electrical head models and appropriate inverse solvers. Using high-resolution, individual electrical head models in fifteen epilepsy patients, with surgical resection and clinical outcome as criteria for accuracy, performance of MSP method was compared against standardized low-resolution brain electromagnetic tomography (sLORETA) and coherent maximum entropy on the mean (cMEM) methods. Results: The MSP method performed similarly to the sLORETA method and slightly better than the cMEM method in terms of success rate. The MSP and cMEM methods were more focal than sLORETA with the advantage of not requiring an arbitrary selection of a hyperparameter or thresholding of reconstructed current density values to determine focus. MSP and cMEM methods were better than sLORETA in terms of spatial dispersion. Conclusions: Results suggest that the three methods are complementary and could be used together. In practice, the MSP method will be easier to use and interpret compared to sLORETA, and slightly more accurate and faster than the cMEM method. Significance: Source localization of interictal spikes from dense-array electroencephalography data has been shown to be a reliable marker of epileptic foci and useful for pre-surgical planning. The advantages of MSP make it a useful complement to other inverse solvers in clinical practice.Fil: Fernandez Corazza, Mariano. Universidad Nacional de La Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales. Universidad Nacional de La Plata. Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales; ArgentinaFil: Feng, Rui. Huashan Hospital; ChinaFil: Ma, Chengxin. Huashan Hospital; ChinaFil: Hu, Jie. Huashan Hospital; ChinaFil: Pan, Li. Huashan Hospital; ChinaFil: Luu, Phan. Brain Electrophysiology Laboratory Company; Estados Unidos. Huashan Hospital; ChinaFil: Tucker, Don. University of Oregon; Estados Unidos. Brain Electrophysiology Laboratory Company; Estados Unido

MONITORING DYNAMIC GLOBAL DEFLECTION OF A BRIDGE BY MONOCULAR DIGITAL PHOTOGRAPHY

This study uses MDP (monocular digital photography) to monitor the dynamic global deflection of a bridge with the PST-TBP (Photographing scale transformation-time baseline parallax) method in which the reference system set near the camera is perpendicular to the photographing direction and does not need parallel to the bridge plane. A SONY350 camera was used to shoot the bridge every two seconds when the excavator was moving on the bridge and produced ten image sequences. Results show that the PST-TBP method is effective in solving the problem of the photographing direction being perpendicular to the bridge plane in monitoring the bridge by MDP. The PST-TBP method can achieve sub-pixel matching accuracy (0.3 pixels). The maximal deflection of the bridge is 55.34 mm which is within the bridge’s allowed value of 75mm. The MDPS (monocular digital photography system) depicts deflection trends of the bridge in real time, which can warn the possible danger of the bridge in time. It provides key information to assess the bridge health on site and to study the dynamic global deformation mechanism of a bridge caused by dynamic vehicle load. MDP is expected to be applied to monitor the dynamic global deflection of a bridge