TransY-Net:Learning Fully Transformer Networks for Change Detection of Remote Sensing Images

In the remote sensing field, Change Detection (CD) aims to identify and localize the changed regions from dual-phase images over the same places. Recently, it has achieved great progress with the advances of deep learning. However, current methods generally deliver incomplete CD regions and irregular CD boundaries due to the limited representation ability of the extracted visual features. To relieve these issues, in this work we propose a novel Transformer-based learning framework named TransY-Net for remote sensing image CD, which improves the feature extraction from a global view and combines multi-level visual features in a pyramid manner. More specifically, the proposed framework first utilizes the advantages of Transformers in long-range dependency modeling. It can help to learn more discriminative global-level features and obtain complete CD regions. Then, we introduce a novel pyramid structure to aggregate multi-level visual features from Transformers for feature enhancement. The pyramid structure grafted with a Progressive Attention Module (PAM) can improve the feature representation ability with additional inter-dependencies through spatial and channel attentions. Finally, to better train the whole framework, we utilize the deeply-supervised learning with multiple boundary-aware loss functions. Extensive experiments demonstrate that our proposed method achieves a new state-of-the-art performance on four optical and two SAR image CD benchmarks. The source code is released at https://github.com/Drchip61/TransYNet.Comment: This work is accepted by TGRS2023. It is an extension of our ACCV2022 paper and arXiv:2210.0075

Review on the Formulation, Existing Problems, and Practical Effects of Fitness Exercise Prescriptions for People With Intellectual Disabilities

Compared with normal people, patients with intellectual disability have poor cardiopulmonary and muscle fitness levels, and their daily physical activity generally cannot reach the “guideline-recommended amount,” which increases the risk of obesity and cardiovascular disease in this group. From the perspective of six elements of exercise prescription (frequency, intensity, time, form of exercise, amount of exercise, and progressive rate), this paper systematically reviews the current situation of the formulation and implementation of exercise prescription for patients with intellectual disabilities. The results show that the design idea of aerobic fitness exercise prescription for patients with intellectual impairment follows the six-element 5paradigm, but the insufficient recommended amount of each element is a common problem. In the design of muscle fitness exercise prescription, due to the differences of different exercise forms, the description of the six elements is very inconsistent. Although most prescription execution effects show that it is beneficial to improve cardiopulmonary and muscle fitness, there is a great debate on whether it is beneficial to improve body composition. People with intellectual disabilities are highly heterogeneous groups. In the initial stage of exercise intervention, the elements of exercise prescription need to be adjusted individually to obtain sustainable positive benefits

Multiresolution Feature Guidance Based Transformer for Anomaly Detection

Anomaly detection is represented as an unsupervised learning to identify deviated images from normal images. In general, there are two main challenges of anomaly detection tasks, i.e., the class imbalance and the unexpectedness of anomalies. In this paper, we propose a multiresolution feature guidance method based on Transformer named GTrans for unsupervised anomaly detection and localization. In GTrans, an Anomaly Guided Network (AGN) pre-trained on ImageNet is developed to provide surrogate labels for features and tokens. Under the tacit knowledge guidance of the AGN, the anomaly detection network named Trans utilizes Transformer to effectively establish a relationship between features with multiresolution, enhancing the ability of the Trans in fitting the normal data manifold. Due to the strong generalization ability of AGN, GTrans locates anomalies by comparing the differences in spatial distance and direction of multi-scale features extracted from the AGN and the Trans. Our experiments demonstrate that the proposed GTrans achieves state-of-the-art performance in both detection and localization on the MVTec AD dataset. GTrans achieves image-level and pixel-level anomaly detection AUROC scores of 99.0% and 97.9% on the MVTec AD dataset, respectively

Research Progress of Vitamin D and Autoimmune Diseases

As a fat-soluble vitamin, Vitamin D is a necessary hormone to maintain normal physiological activities of the body. In recent years, vitamin D has been considered as a new neuroendocrine-immunomodulatory hormone, and researchers have paid more attention to the study of immune regulatory mechanism. It is not only related to calcium and phosphorus metabolism, bone metabolism and other important metabolic mechanisms of the body, but also closely related to the immune regulation mechanism of the body. Vitamin D deficiency caused by many factors can play a certain role in the development of autoimmune diseases. In this paper, the related mechanisms of vitamin D affecting autoimmune diseases were reviewed, with a view to expound the close correlation between vitamin D and autoimmune diseases, so as to find new diagnosis and treatment approaches for clinical autoimmune diseases and improve the quality of life of patients with autoimmune diseases

A Research on the Relationship between Intestinal Flora and Human Longevity

The exploration of human life and health is advancing with the changes of the times. With the growth of age, the occurrence of chronic diseases of human immunity and organ system is frequent, which has a serious impact on human health. Genes, environment and other random factors determine the outcome of longevity, and intestinal flora is considered to be a decisive factor affecting human health and longevity, mainly because of its huge impact on human immunity, growth and development. The study of the relationship between intestinal flora and longevity is beneficial to improve the health status of the elderly and improve the overall life level of human beings, which has great scientific research value. This review will review the role of intestinal flora in longevity

Metformin and Lactic Acidosis in Diabetic Patients

Metformin is the basic drug in the clinical treatment of Diabetes, often used in the treatment of Type 2 Diabetes Mellitus (T2DM).Its effect has been fully verified in the clinical treatment of T2DM. However, in the treatment of T2DM with metformin, there is still a certain probability of related lactic acidosis, and the fatality rate is high. Therefore, is the use of metformin drug treatment a direct risk factor for lactic acidosis in diabetic patients? This paper will review the hypoglycemic mechanism of metformin and related studies on lactic acidosis, so as to further explore the relationship between metformin and lactic acidosis in diabetic patients, and provide help and reference for metformin drugs in the clinical treatment of T2DM