中国における保育者のメンタルヘルスに関する研究 : レジリエンスとコーピングに着目して

内容の要約広島大学(Hiroshima University)博士(教育学)Doctor of Philosophy in Educationdoctora

A Study of Chinese Preschool Teachers' Mental Health with a Focus on Resilience

This study examines the resilience of preschool teachers and suggests ways to improve their mental health. These suggestions relate to teachers' years of experience and educational background, and focussed on 200 Chinese preschool teachers. The study found that the resilience of veteran Chinese preschool teachers, especially in terms of social support and self-efficacy, is lower than new and mid-career teachers. The study also found that preschool teachers with university degrees have lower self-efficacy than teachers who graduated from training colleges. Based on these results, it is necessary to enrich the veteran preschool teachers' social support and construct a system to enhance their self-efficacy. There is also a need to reinforce the knowledge and skills of preschool teachers with college degrees

Near-Field Channel Estimation for Extremely Large-Scale Array Communications: A model-based deep learning approach

Extremely large-scale massive MIMO (XL-MIMO) has been reviewed as a promising technology for future wireless communications. The deployment of XL-MIMO, especially at high-frequency bands, leads to users being located in the near-field region instead of the conventional far-field. This letter proposes efficient model-based deep learning algorithms for estimating the near-field wireless channel of XL-MIMO communications. In particular, we first formulate the XL-MIMO near-field channel estimation task as a compressed sensing problem using the spatial gridding-based sparsifying dictionary, and then solve the resulting problem by applying the Learning Iterative Shrinkage and Thresholding Algorithm (LISTA). Due to the near-field characteristic, the spatial gridding-based sparsifying dictionary may result in low channel estimation accuracy and a heavy computational burden. To address this issue, we further propose a new sparsifying dictionary learning-LISTA (SDL-LISTA) algorithm that formulates the sparsifying dictionary as a neural network layer and embeds it into LISTA neural network. The numerical results show that our proposed algorithms outperform non-learning benchmark schemes, and SDL-LISTA achieves better performance than LISTA with ten times atoms reduction.Comment: 4 pages, 5 figure

Higher phagocytic activity of thioglycollate-elicited peritoneal macrophages is related to metabolic status of the cells

BACKGROUND: Peritoneal macrophages are widely used in immunological studies. The cells can be collected under non-elicited (resident) or elicited (e.g., with Brewer thioglycollate broth injection) conditions, and their phenotype and functions differ. Recent studies have shown that macrophage phenotype and function are related to their metabolic states, and metabolic reprogramming has been an emerging concept for controlling macrophage function. In this study, we examined the metabolic state of resident and elicited macrophages and investigated how their metabolic state may affect cell function, including phagocytosis. FINDINGS: Flow cytometry showed that elicited macrophages expressed higher levels of MHC-II, LFA-1 and CD64 but lower levels of F4/80 compared to naïve resident peritoneal macrophages, suggesting a more mature and active phenotype. Elicited macrophages had significantly higher levels of phagocytic activity compared to that of resident macrophages. Metabolic studies showed that the Extracellular Acidification Rates (ECAR) and Oxygen Consumption Rates (OCR) were both significantly higher in elicited macrophages than those in resident macrophages. The treatment of macrophages with 2-Deoxy-D-glucose suppressed glycolysis and reduced phagocytosis, whereas treatment with oligomycin enhanced glycolysis and increased phagocytosis in elicited macrophages. CONCLUSION: Naïve resident peritoneal macrophages are less metabolically active compared to elicited macrophages. Elicited macrophages had higher levels of glycolysis and oxidative phosphorylation, which may be related to their increased phagocytic capacity and higher levels of maturation and activation. Further understanding of the molecular links between metabolic pathways and cell function would be crucial to develop strategies to control macrophage function through metabolic reprogramming

Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions

Machine learning (ML) models can underperform on certain population groups due to choices made during model development and bias inherent in the data. We categorize sources of discrimination in the ML pipeline into two classes: aleatoric discrimination, which is inherent in the data distribution, and epistemic discrimination, which is due to decisions made during model development. We quantify aleatoric discrimination by determining the performance limits of a model under fairness constraints, assuming perfect knowledge of the data distribution. We demonstrate how to characterize aleatoric discrimination by applying Blackwell's results on comparing statistical experiments. We then quantify epistemic discrimination as the gap between a model's accuracy when fairness constraints are applied and the limit posed by aleatoric discrimination. We apply this approach to benchmark existing fairness interventions and investigate fairness risks in data with missing values. Our results indicate that state-of-the-art fairness interventions are effective at removing epistemic discrimination on standard (overused) tabular datasets. However, when data has missing values, there is still significant room for improvement in handling aleatoric discrimination

Observation of the Effect of Gait-induced Functional Electrical Stimulation on Stroke Patients with Foot Drop

Objective: To explore the effects of functional electrical stimulation and functional mid frequency electrical stimulation on lower limb function and balance function in stroke patients. Methods: 20 cases of stroke patients with foot drop after admission were randomly divided into the observation group and the control group, 10 cases in each group. On the basis of the two groups of patients, the observation group used the gait induced functional electrical stimulation to stimulate the peroneal nerve and the pretibial muscle in the observation group. The control group used the computer medium frequency functional electrical stimulation to stimulate the peroneal nerve and the anterior tibial muscle for 2 weeks. Before and after treatment, the lower extremity simple Fugl-Meyer scale (FMA), the Berg balance scale (BBS) and the improved Ashworth scale were evaluated respectively, and the comparative analysis was carried out in the group and between the groups. Results: After 2 weeks of treatment, the scores of FMA and BBS in the two groups were significantly higher than those before the treatment (P < 0.05), and the scores of FMA and BBS in the observation group were higher than those in the control group (P < 0.05), and the flexor muscle tension of the ankle plantar flexor muscle of the observed group was lower than that of the control group (P < 0.05). Conclusions: Exercise therapy combined with gait induced functional electrical stimulation or computer intermediate frequency functional electrical stimulation can significantly improve lower limb function and balance function in patients with ptosis, and the therapeutic effect of functional electrical stimulation combined with gait is better.