In this study, optical and microwave satellite observations are integrated to estimate soil moisture at the same spatial resolution as the optical sensors (5km here) and applied for drought analysis in the continental United States. A new refined model is proposed to include auxiliary data like soil texture, topography, surface types, accumulated precipitation, in addition to Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) used in the traditional universal triangle method. It is found the new proposed soil moisture model using accumulated precipitation demonstrated close agreements with the U.S. Drought Monitor (USDM) spatial patterns. Currently, the USDM is providing a weekly map. Recently, “flash” drought concept appears. To obtain drought map on daily basis, LST is derived from microwave observations and downscaled to the same resolution as the thermal infrared LST product and used to fill the gaps due to clouds in optical LST data. With the integrated daily LST available under nearly all weather conditions, daily soil moisture can be estimated at relatively higher spatial resolution than those traditionally derived from passive microwave sensors, thus drought maps based on soil moisture anomalies can be obtained on daily basis and made the flash drought analysis and monitoring become possible.

This article aims to explore the training model of preschool physical education teachers based on the theory of "space, capital, and habits". Preschool physical education plays an important role in the development of children's physical fitness and cognitive abilities. This article first introduces the theory of "space, capital, and habits", including its definition and core concepts, as well as its application value in teacher training. Subsequently, a training model for preschool physical education teachers based on this theory was proposed, which includes three elements: space, capital, and habits. In terms of space, it is emphasized to create an environment and place conducive to the professional development of preschool physical education teachers, such as the construction of training institutions and internship bases, and the support of teaching environment and resources. In terms of capital, emphasis is placed on cultivating the professional knowledge and abilities of preschool physical education teachers, including curriculum design and teaching methods, teacher team construction, and professional development mechanisms. In terms of habits, emphasis is placed on cultivating the professional literacy and educational attitude of preschool physical education teachers, including practical links and social participation, evaluation and feedback mechanisms. This training model aims to improve the quality and effectiveness of preschool physical education teacher training, and provide theoretical guidance and practical suggestions for preschool physical education teacher training.

Previous studies support the direct relationship between outdoor physical activity and natural spaces in cities. The Active City and Nature concept explores the relationship between urban, green and active environments; it aims to demonstrate the scientific evidence for the need for action to be taken to increase participation in active living and sport, leading to healthier cities and communities. Our research seeks to analyse the city’s natural spaces as scenarios to encourage physical activity and sport, through a combined study of qualitative research techniques: the use of a digital webGIS platform, collaborative maps made by citizens, and surveys conducted with citizens and the local government. This methodology has been tested in the city of Malaga, the European City of Sport 2020. The study of the city’s main sport areas, the waterfront and natural green spaces provided data on the types of physical activity taking place in each of these areas and the physical activity needs of citizens. This research argues that it is important to know the criteria of local communities for physical activity and/or sport in natural environments, as well as the main demands expressed. This will provide valuable information to design and manage natural public spaces as a means of promoting physical activity and healthy habits.

Understanding the factors that influence early science achievement is crucial for developing effective educational policies and ensuring equity within the education system. Despite its importance, research on the patterns of young children achieving science learning milestones and the factors that can reduce disparities between students with and without disabilities remains limited. This study analyzes data from the Early Childhood Longitudinal Study of Kindergarten Cohort 2011 (ECLS-K: 2011), which includes 18,174 children from 1328 schools across the United States, selected through a complex sampling process and spanning kindergarten to 5th grade. Utilizing survival analysis, the study finds that children with disabilities achieve science milestones later than their peers without disabilities, with these disparities persisting from early grades. The research highlights the effectiveness of center-based programs in enhancing science learning, particularly in narrowing the achievement gap between children with and without disabilities. These findings contribute to the broader discourse on equity in the education system and policy by introducing novel methodologies for assessing the frequency and duration of science learning milestones, and by providing insights into effective strategies that support equitable science education.

In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.