This review provides an overview of the importance of nanoparticles in various fields of science, their classification, synthesis, reinforcements, and applications in numerous areas of interest. Normally nanoparticles are particles having a size of 100 nm or less that would be included in the larger category of nanoparticles. Generally, these materials are either 0-D, 1-D, 2-D, or 3-D. They are classified into groups based on their composition like being organic and inorganic, shapes, and sizes. These nanomaterials are synthesized with the help of top-down bottom and bottom-up methods. In case of plant-based synthesis i.e., the synthesis using plant extracts is non-toxic, making plants the best choice for producing nanoparticles. Several physicochemical characterization techniques are available such as ultraviolet spectrophotometry, Fourier transform infrared spectroscopy, the atomic force microscopy, the scanning electron microscopy, the vibrating specimen magnetometer, the superconducting complex optical device, the energy dispersive X-ray spectrometry, and X-ray photoelectron spectroscopy to investigate the nanomaterials. In the meanwhile, there are some challenges associated with the use of nanoparticles, which need to be addressed for the sustainable environment.

The article examines the modern vectors of implementation of measures to achieve results in the field of Sustainable Development Goals (SDGs), both at the level of national priorities and at the level of Central Asian countries. The purpose of this study is a multidimensional analysis of actions that make it possible to develop solutions to stabilize the environmental situation in Central Asian countries based on global international trends. The scientific novelty of the research lies in the integrated use of thematic modeling methods, as well as sociological surveys used to improve the efficiency of business processes in the field of environmental protection. The methodological basis for conducting a comparative assessment of the impact of environmental policy instruments used on regional development is the concept of sustainable development. In conclusion, conclusions are drawn about the need to develop effective mechanisms for the implementation of environmental policy in the studied countries.

Hospital waste containing antibiotics is toxic to the ecosystem. Ciprofloxacin is one of the essential, widely used antibiotics and is often detected in water bodies and soil. It is vital to treat these medical wastes, which urge new research towards waste management practices in hospital environments themselves. Ultimately minimizes its impact in the ecosystem and prevents the spread of antibiotic resistance. The present study highlights the decomposition of ciprofloxacin using nano-catalytic ZnO materials by reactive oxygen species (ROS) process. The most effective process to treat the residual antibiotics by the photocatalytic degradation mechanism is explored in this paper. The traditional co-precipitation method was used to prepare zinc oxide nanomaterials. The characterization methods, X-Ray diffraction analysis (XRD), Fourier Transform infrared spectroscopy (FTIR), Ulraviolet-Visible spectroscopy (UV-Vis), Scanning Electron microscopy (SEM) and X-Ray photoelectron spectroscopy (XPS) have done to improve the photocatalytic activity of ZnO materials. The mitigation of ciprofloxacin catalyzed by ZnO nano-photocatalyst was described by pseudo-first-order kinetics and chemical oxygen demand (COD) analysis. In addition, ZnO materials help to prevent bacterial species, S. aureus and E. coli, growth in the environment. This work provides some new insights towards ciprofloxacin degradation in efficient ways.

This study aims at exploring the direct impact of positive mental health through 6 factors on quality of life among students with disabilities and diabetes at Saudi universities, as well as the moderating impact of physical fitness on all direct relationships among all variables of the study. Employing a quantitative research methodology, using self-administered surveys distributed to a sample of students with disabilities and diabetes at numerous Saudi Arabian universities. 468 completed surveys were received and subjected to statistical analysis, using PLS-SEM, and the study uncovered significant positive direct relationships between all positive mental health sub factors and quality of life among students. Additionally, the study revealed that physical fitness acts as a moderator in all direct relationships These findings offer valuable insights for universities, in order to develop and implement psychological support and academic adjustments policies ensuring students have access to health and wellness programs, and engage local communities in the creation of policies that can help students with disabilities.

The power of Artificial Intelligence (AI) combined with the surgeons’ expertise leads to breakthroughs in surgical care, bringing new hope to patients. Utilizing deep learning-based computer vision techniques in surgical procedures will enhance the healthcare industry. Laparoscopic surgery holds excellent potential for computer vision due to the abundance of real-time laparoscopic recordings captured by digital cameras containing significant unexplored information. Furthermore, with computing power resources becoming increasingly accessible and Machine Learning methods expanding across various industries, the potential for AI in healthcare is vast. There are several objectives of AI’s contribution to laparoscopic surgery; one is an image guidance system to identify anatomical structures in real-time. However, few studies are concerned with intraoperative anatomy recognition in laparoscopic surgery. This study provides a comprehensive review of the current state-of-the-art semantic segmentation techniques, which can guide surgeons during laparoscopic procedures by identifying specific anatomical structures for dissection or avoiding hazardous areas. This review aims to enhance research in AI for surgery to guide innovations towards more successful experiments that can be applied in real-world clinical settings. This AI contribution could revolutionize the field of laparoscopic surgery and improve patient outcomes.

Hospital performance possesses strategic significance in achieving an essential completive advantage for the public hospitals. This study aimed to examine the relationship between patient safety culture (PSC) and the performance of traditional Chinese medicine (TCM) public hospitals in Sichuan, China. To address the research purpose, this study analyses the hospital performance and Patient safety culture in traditional Chinese medicine public hospital in China. We examine the propose model by analyzing cross-sectional survey data from 194 clinical directors at 194 public traditional Chinese medicine hospitals using the Partial least squares structural equation model in Smart PLS 4.0. This study provides predictive evidence that PSC in unit management and management support can lead to better patient safety outcomes. The results revealed patient safety outcomes significantly and positively effects of patient safety related to unit management and management support on overall hospital performance (p-value: 0.000–0.003).