In recent years, incidents of school bullying have been on the rise, attracting increasing attention from society. School bullying refers to the repeated and sustained use of force or coercion by individual or group of students to oppress other students in terms of power or status, resulting in many physical and psychological problems for the victims. This paper introduces the definition, classification, role types, and the impact on victims, as well as interventions for school bullying. Studies have shown that school bullying can have negative psychological consequences for victims, such as anxiety and depression, making timely intervention extremely important. Intervention measures include educating the active perpetrators, victims, and bystanders. In particular, the "STAC" course is an effective way to educate bystanders. In summary, school bullying is a problem that requires timely intervention, and it requires joint efforts from schools, families, and society to solve.

Problem: in recent years, new studies have been published on biological effects of strong static magnetic fields and on thermal effects of high-frequency electromagnetic fields as used in magnetic resonance imaging (MRI). Many of these studies have not yet been incorporated into current safety recommendations. Method: scientific publications from 2010 onwards on the biological effects of static and electromagnetic fields of MRI were searched and evaluated. Results: new studies confirm older work that has already described effects of static magnetic fields on sensory organs and the central nervous system accompanied by sensory perception. A new result is the direct effect of Lorentz forces on ionic currents in the semicircular canals of the vestibular organ. Recent studies on thermal effects of radiofrequency fields focused on the development of anatomically realistic body models and more accurate simulation of exposure scenarios. Recommendation for practice: strong static magnetic fields can cause unpleasant perceptions, especially dizziness. In addition, they can impair the performance of the medical personnel and thus potentially endanger patient safety. As a precaution, medical personnel should move slowly in the field gradient. High-frequency electromagnetic fields cause tissues and organs to heat up in patients. This must be taken into account in particular for patients with impaired thermoregulation as well as for pregnant women and newborns; exposure in these cases must be kept as low as possible.

An image adaptive noise reduction enhancement algorithm based on NSCT is proposed to perform image restoration preprocessing on the defocused image obtained under the microscope. Defocused images acquired under micro-nano scale optical microscopy, usually with inconspicuous details, edges and contours, affect the accuracy of subsequent observation tasks. Due to its multi-scale and multi-directionality, the NSCT transform has superior transform functions and can obtain more textures and edges of images. Combined with the characteristics of micro-nanoscale optical defocus images, the NSCT inverse transform is performed on all sub-bands to reconstruct the image. Finally, the experimental results of the standard 500 nm scale grid, conductive probe and triangular probe show that the proposed algorithm has a better image enhancement effect and significantly improves the quality of out-of-focus images.

The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI’s capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.

The Middle East and North Africa (MENA) region faces unique challenges and opportunities in integrating sustainability into sovereign credit assessments. This research study examines environmental, social, and governance (ESG) factors embedded in the lending policies of jurisdictional institutions in MENA. By analyzing existing literature and case studies, we identify key drivers and barriers to ESG integration in sovereign lending. Our findings suggest a growing recognition of sustainability’s importance in financial stability and credit, driven by global climate guarantees and local socio-economic development. However, challenges such as data availability, regulatory frameworks, and market acceptance persist. This paper provides an overview of current practices, highlights best practices, and offers recommendations to enhance ESG integration in sovereign debt reviews in the MENA region. The study concludes that a robust ESG framework is necessary to accurately reflect the long-term risks and opportunities associated with sovereign debt, ultimately contributing to sustainable economic growth regionally.