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Geospatial thinking is crucial for understanding the spatial order of the world. The factors influencing geospatial thinking deserve attention in geography education. Utilizing correlation analysis, we found that general intelligence, geographic knowledge, and geographic learning interest had a significant influence on geospatial thinking. This article attempts to understand how these factors affect geospatial thinking by using structural equation modeling. The results indicate that they impacted geospatial thinking directly. In addition, general intelligence and geographic learning interest had an indirect impact on geospatial thinking.

Injury to the peripheral nervous system disconnects targets to the central nervous system, disrupts signal transmission, and results in functional disability. Although surgical and therapeutic treatments improve nerve regeneration, it is generally hard to achieve fully functional recovery after severe peripheral nerve injury. A better understanding of pathological changes after peripheral nerve injury helps the development of promising treatments for nerve regeneration. Single-cell analyses of the peripheral nervous system under physiological and injury conditions define the diversity of cells in peripheral nerves and reveal cell-specific injury responses. Herein, we review recent findings on the single-cell transcriptome status in the dorsal root ganglia and peripheral nerves following peripheral nerve injury, identify the cell heterogeneity of peripheral nerves, and delineate changes in injured peripheral nerves, especially molecular changes in neurons, glial cells, and immune cells. Cell-cell interactions in peripheral nerves are also characterized based on ligand-receptor pairs from coordinated gene expressions. The understanding of cellular changes following peripheral nerve injury at a single-cell resolution offers a comprehensive and insightful view for the peripheral nerve repair process, provides an important basis for the exploration of the key regulators of neuronal growth and microenvironment reconstruction, and benefits the development of novel therapeutic drugs for the treatment of peripheral nerve injury. [ABSTRACT FROM AUTHOR]

Gas detection and monitoring are critical to protect human health and safeguard the environment and ecosystems. Chemiresistive sensors are widely used in gas monitoring due to their ease of fabrication, high customizability, mechanical flexibility, and fast response time. However, with the rapid development of industrialization and technology, the main challenges faced by chemiresistive gas sensors are poor selectivity and insufficient anti-interference stability in complex application environments. In order to overcome these shortcomings of chemiresistive gas sensors, the pattern recognition method is emerging and is having a great impact in the field of sensing. In this review, we focus systematically on the advancements in the field of data processing methods for feature extraction, such as the methods of determining the characteristics of the original response curve, the curve fitting parameters, and the transform domain. Additionally, we emphasized the developments of traditional recognition algorithms and neural network algorithm in gas discrimination and analyzed the advantages through an extensive literature review. Lastly, we summarized the research on chemiresistive gas sensors and provided prospects for future development. [ABSTRACT FROM AUTHOR]

Thermally activated delayed fluorescence (TADF)‐based materials are attracting widespread attention for different applications owing to their ability of harvesting both singlet and triplet excitons without noble metals in their structures. As compared to the conventional fluorescence and room‐temperature phosphorescence pathways, TADF originates from the reverse intersystem crossing process from the excited triplet state (T1) to the singlet state (S1). Therefore, TADF emitters enabling activated and long lifetime T1 excitons are potential candidates for generating long‐lived afterglow emission, an effect that can still be observed for a while by the naked eye after the removal of the excitation light source. Recently, TADF‐based organic afterglow materials featuring high photoluminescence quantum yields and long lifetimes above 100 ms under ambient conditions, have emerged for advanced information security, high‐contrast biological imaging, optoelectronic devices, and intelligent sensors, whereas the related systematic review is still lacking. Herein, the recent progress in TADF‐based organic afterglow materials is summarized and an overview of the photophysical mechanism, design strategies, and the performances for relevant applications is given. In addition, the challenge and perspective of this area are given at the end of the review. [ABSTRACT FROM AUTHOR]

In this article, we use eye-tracking technology to analyze the eye movement differences in cognitive maps between high and low level map-based spatial ability participants, revealing key factors of superior spatial ability. It is found that focusing on the perception of spatial structure information, constructing and manipulating complex images psychologically, and positioning by spatial relationship with reference objects are three key factors of superior spatial ability. Based on this, we developed the teaching strategies of geospatial ability to provide reference and suggestions for the education and evaluation of senior high school students' spatial ability.

Spinal cord injury (SCI) is one of the most severe injuries, characterized by multiple positive feedback regulatory signaling networks formed by oxidative stress and inflammation in the injury microenvironment, leading to neuronal cell damage and even death. Here, astragaloside IV (AS), known for its regulatory role in ferroptosis, was encapsulated in the cavity of apoferritin (HFn) after an in situ biomineralization process involving MnO2, resulting in the synthesis of HFn@MnO2/AS nanoparticles. These nanoparticles were then dispersed in chitosan/polyvinyl alcohol/glutaraldehyde/sodium β-glycerophosphate (CGPG) hydrogels to form CGPG-HFn@MnO2/AS injectable thermosensitive hydrogels that can scavenge reactive oxygen species (ROS) in the microenvironment. Our findings indicated that the prepared CGPG-HFn@MnO2/AS hydrogel exhibited remarkable efficacy in scavenging ROS in vitro, effectively ameliorating the oxidative stress microenvironment post-SCI. Furthermore, it inhibited oxidative stress-induced ferroptosis in vitro and in vivo by regulating SIRT1 signaling, thereby promoting neuronal cell migration and repair. Hence, the developed hydrogel combining MnO2 and AS exhibited multifaceted abilities to modulate the pathological microenvironment, providing a promising therapeutic strategy for central nervous system (CNS) diseases. [ABSTRACT FROM AUTHOR]

This study explores the relationship between vicarious experiences of nature, environmental behavioral beliefs, environmental attitudes and adolescents' environmental behavior. Based on a sample of 1476 adolescents from five high schools in Jiangsu Province, China, we proposed a model that was supported by structural equation modelling analysis. The model suggests that vicarious experiences of nature are positively associated with adolescents' environmental behavior. Environmental attitudes and environmental behavioral beliefs play partial mediator roles in the relationship of vicarious experiences of nature and environmental behavior. In addition to the significant direct impact of vicarious experiences of nature on environmental behavior, indirect effects are also achieved through behavioral beliefs, environmental attitudes and the serial multiple mediation effect of the two variables. These research results imply that we must pay attention to the important role of vicarious experiences of nature in cultivating adolescents' environmental behavior. In addition, the theoretical and practical implications of this research are discussed, as well as the limitations and potential for future research. [ABSTRACT FROM AUTHOR]

A metabolic bone disease characterized by decreased bone formation and increased bone resorption is osteoporosis. It can cause pain and fracture of patients. The elderly are prone to osteoporosis and are more vulnerable to osteoporosis. In this study, radiomics are extracted from computed tomography (CT) images to screen osteoporosis in the elderly. Collect the plain scan CT images of lumbar spine, cut the region of interest of the image and extract radiomics features, use Lasso regression to screen variables and adjust complexity, use python language to model random forests, support vector machines, K nearest neighbor, and finally use receiver operating characteristic curve to evaluate the performance of the model, including precision, recall, accuracy and area under the curve (AUC). For the model, 14 radiolomics features were selected. The diagnosis performance of random forest model and support vector machine is good, all around 0.9. The AUC of K nearest neighbor model in training set and test set is 0.828 and 0.796, respectively. We selected the plain scan CT images of the elderly lumbar spine to build radiomics features model, which has good diagnostic performance and can be used as a tool to assist the diagnosis of osteoporosis in the elderly. [ABSTRACT FROM AUTHOR]