METHODS: We collected and analyzed functional near-infrared spectroscopy data of 38 participants while performing the revised lateralized attention network tast.
RESULTS: Elite players were significantly faster than novices (p = .005), and the experts' overall accuracy rate (ACC) was higher than that of novices (p = .001). The effect of the executive network on reaction time was higher in novices than in elite players (p = .008) and experts (p = .004). The effect of the executive network on the ACC was lower in elite players than in experts (p = .009) and novices (p = .010). Finally, elite player had higher flanker conflict effects on RT (p = .005) under the invalid cue condition. the effect of the alertness network and orientation on the ACC was lower in elite players than in novices (p = .000) and experts (p = .022). Changes in the blood oxygen level-dependent signal related to the flanker effect were significantly different in the right dorsolateral prefrontal cortex (F=3.980, p = .028) and right inferior frontal gyrus (F=3.703, p = .035) among the three groups. Elit players showed more efficient executive control (reduced conflict effect on ACC) (p = .006)in the RH.The changes related to the effect of blood oxygen level on orienting were significantly different in the right frontal eye fields (F=3.883, p = .030) among the three groups, Accompanied by significant activation of the right dorsolateral prefrontal cortex(p = .026).
CONCLUSION: Our findings provide partial evidence of the superior cognitive performance and high neural efficiency of elite ice hockey players during cognitive tasks. These results demonstrate the right hemisphere superiority for executive control.We also found that specific brain activation in hockey players does not show a clear and linear relationship with skill level.
METHODS: In this study, we propose a multi-view secondary input residual (MV-SIR) convolutional neural network model for 3D lung nodule segmentation using the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) dataset of chest computed tomography (CT) images. Lung nodule cubes are prepared from the sample CT images. Further, from the axial, coronal, and sagittal perspectives, multi-view patches are generated with randomly selected voxels in the lung nodule cubes as centers. Our model consists of six submodels, which enable learning of 3D lung nodules sliced into three views of features; each submodel extracts voxel heterogeneity and shape heterogeneity features. We convert the segmentation of 3D lung nodules into voxel classification by inputting the multi-view patches into the model and determine whether the voxel points belong to the nodule. The structure of the secondary input residual submodel comprises a residual block followed by a secondary input module. We integrate the six submodels to classify whether voxel points belong to nodules, and then reconstruct the segmentation image.
RESULTS: The results of tests conducted using our model and comparison with other existing CNN models indicate that the MV-SIR model achieves excellent results in the 3D segmentation of pulmonary nodules, with a Dice coefficient of 0.926 and an average surface distance of 0.072.
CONCLUSION: our MV-SIR model can accurately perform 3D segmentation of lung nodules with the same segmentation accuracy as the U-net model.
METHODS: A rapid online survey comprising 22 items was administered during the rapid outbreak of COVID-19 in Pakistan. Questions were focused on the prevention, transmission, clinical features, and control of COVID-19. In addition, the attitudes and practices of the participants were explored. Descriptive statistics, Mann-Whitney tests, Kruskal-Wallis tests, and regression analysis were carried out during data analysis.
RESULTS: A total of 1257 respondents participated in this study. Most of the respondents had good knowledge (good = 64.8%, average = 30.5%, poor = 4.7%) of COVID-19. Gender, marital status, education, and residence were observed to have a significant association with the knowledge score. A vast majority of the survey respondents (77.0%) believed that COVID-19 would be controlled successfully in Pakistan. The practices of wearing a mask (85.8%) and handwashing (88.1%) were common among the participants.
CONCLUSION: The participants demonstrated good knowledge and reasonable attitudes and practices toward most aspects of the COVID-19 outbreak. Improvements in certain areas could be made by mass-level education.
METHODS: A total of 2231 higher vocational students from Shandong Province were surveyed by means of Academic Self-efficacy Questionnaire, Meaning in Life Questionnaire, and Test Anxiety Scale.
RESULTS: There were significant negative correlations among academic self-efficacy, sense of life meaning, and test anxiety. Fear of failure was positively correlated with test anxiety. Sense of life meaning and fear of failure played a mediating role in the relationship between academic self-efficacy and test anxiety. The chain mediating effect was significant only in the female group, not in the male group. In contrast, academic self-efficacy indirectly predicted test anxiety by the independent mediating effect of sense of life meaning or fear of failure in the male group.
CONCLUSION: Academic self-efficacy may influence test anxiety through the independent mediating effect of sense of life meaning, fear of failure, and the chain mediating effect, and there is a gender difference in these effects.