[Objective]In order to explore the sustainable food security level in the Yangtze River Economic Belt, ensure food security and sustainable development of agricultural modernization, it is necessary to establish a scientific food security evaluation system to safeguard local food security.[Methods]This paper takes the food system of the Yangtze River Economic Belt in China as the research object, based on the food security research results at home and abroad, based on sustainable development thinking, combined with a new perspective of dynamic equilibrium research: Beginning with food normalcy, a comprehensive analysis of food production, food economy, social development, ecological security, and technical support for sustainable development is presented using the entropy-weighted TOPSIS model to build a food security evaluation system for sustainable development. [Conclusion]After systematic analysis, it is concluded that (1) the average value of food security score of the Yangtze River Economic Belt from 2008 to 2021 is 0.429, and the overall food in the Yangtze River Economic Belt is in general security level (0.400 ≤ Q1 ≤ 0.600), and the overall situation of food security is not optimistic, (2) from the segmentation of the Yangtze River Economic Belt, the high and low level of food security are divided into sections: midstream > downstream > upstream, and each province and city is slowly rising to different degrees. In this way, we propose general countermeasures to ensure local food security from the perspective of sustainable development.

Vehicle detection stands out as a rapidly developing technology today and is further strengthened by deep learning algorithms. This technology is critical in traffic management, automated driving systems, security, urban planning, environmental impacts, transportation, and emergency response applications. Vehicle detection, which is used in many application areas such as monitoring traffic flow, assessing density, increasing security, and vehicle detection in automatic driving systems, makes an effective contribution to a wide range of areas, from urban planning to security measures. Moreover, the integration of this technology represents an important step for the development of smart cities and sustainable urban life. Deep learning models, especially algorithms such as You Only Look Once version 5 (YOLOv5) and You Only Look Once version 8 (YOLOv8), show effective vehicle detection results with satellite image data. According to the comparisons, the precision and recall values of the YOLOv5 model are 1.63% and 2.49% higher, respectively, than the YOLOv8 model. The reason for this difference is that the YOLOv8 model makes more sensitive vehicle detection than the YOLOv5. In the comparison based on the F1 score, the F1 score of YOLOv5 was measured as 0.958, while the F1 score of YOLOv8 was measured as 0.938. Ignoring sensitivity amounts, the increase in F1 score of YOLOv8 compared to YOLOv5 was found to be 0.06%.

Malaria is a mosquito-borne infectious disease that affects humans and poses a severe public health problem. Nigeria has the highest number of global cases. Geospatial technology has been widely used to study the risks and factors associated with malaria hazards. The present study is conducted in Ibadan, Oyo State, Nigeria. The objective of this study is to map out areas that are at high risk of the prevalence of malaria by considering a good number of factors as criteria that determine the spread of malaria within Ibadan using open-source and Landsat remote sensing data and further analysis in GIS-based multi-criteria evaluation (MCE). This study considered factors like climate, environmental, socio-economic, and proximity to health centers as criteria for mapping malaria risk. The MCE used a weighted overlay of the factors to produce an element at-risk map, a malaria hazard map, and a vulnerability map. These maps were overlaid to produce the final malaria risk map, which showed that 72% of Ibadan has a risk of malaria prevalence. Identification and delineation of risk areas in Ibadan would help policymakers and decision-makers mitigate the hazards and improve the health status of the state.

The high demand for quality healthcare services in Portugal is generating concerns about meeting the optimum number of healthcare professionals in the private sector, such as doctors and clinicians. Critical interventions are currently in progress, aiming to provide quality healthcare that will be accessible and sustainable through actionable retention strategies such as investing and developing human capital, introducing better conditions of service to attract and retain talent in the private healthcare sector, and prioritizing the needs of patients. The objective of this study is to understand which factors promote the migration of physicians from the public to the private sector according to the theoretical assumptions of incentives. In this context, a phenomenological study was carried out, using semi-structured interviews with fifteen physicians working in the private health network. Content analysis was done using NVivo 12. The results indicate that performance evaluation in the private sector exists but has no alignment with incentives. The condition makes the private healthcare sector unattractive, however, other policies of remuneration remain promising. Current proposals that could revive the image of the sector include collective decision-making and strong labour relations advocacy for physicians in the private sector.

In this study, the enrichment of the major oxide, trace element/heavy metal and rare earth element contents of the rocks outcropping in Kısacık and its vicinity (Ayvacık-Çanakkale/Türkiye) were investigated. The rocks in the field were handled in 5 groups, and whole rock analyses were carried out for 22 samples collected representing these rock groups and Element Enrichment Factor (EEF) of the major oxide, trace element/heavy metal and rare earth element contents of the rocks were calculated. As a result, it was determined that the Kısacık volcanics were enriched in SiO₂, Fe₂O₃, K₂O, Be, Co, Cs, Th, U, W, La, Eu, Tm, Yb, Lu, Mo, As, Cd, Sb, Bi and Hg elements at a rate of >1 to >150 according to the upper crust values, and the Fe₂O₃, MgO, CaO, TiO₂, P₂O₅, MnO, Cr, Sc, Co, Nb, Sr, Mo, Cu, Ni, Cad, Sb, Bi, V, Cu and Cd concentrations of the Ophiolitic Mélange were enriched in ratios ranging from >1 to >36 according to the upper crust values. It has been also observed that the listvenitic rocks in the Ophiolitic Mélange are enriched in Cr, Co, Ni, As and Hg elements compared to the upper crust. As to Kazdağ Group, MgO, CaO, K₂O, MnO, Cr, Co, Ta, U, W, Mo, Cu, Ni, As and Cd were enriched. Listvenite were enriched in SiO₂, Fe₂O₃, MgO, Mn, Cr, Co, Ni, As, Sb and Hg at a rate of >1 to >32 according to the upper crust values. When the rocks in the area were evaluated together, some oxides (e.g., CaO, MgO, Fe₂O₃, TiO₂) and elements (e.g., Cr, Ni, Co) were enriched due to parental rock, while some oxides (e.g., SiO₂, K₂O and MnO) and elements (As, Sb, Hg) were enriched due to epigenic processes such as hydrothermal alteration and weathering.

Nanoparticle drug delivery systems are engineered technologies that use nanoparticles for the targeted delivery and controlled release of therapeutic agents. Cisplatin-loaded nanoparticle formulations were optimized utilizing response surface methods and the central composite rotating design model. This study employed a central composite rotatable design with a three-factored factorial design with three tiers. Three independent variables namely drug polymer ratio, aqueous organic phase ration, and stabilizer concentration were used to examine the particle size, entrapment efficiency, and drug loading of cisplatin PLGA nanoparticles as responses. The results revealed that this response surface approach might be able to be used to find the best formulation for the cisplatin PLGA nanoparticles. A polymer ratio of 1:8.27, organic phase ratio of 1:6, and stabilizer concentration of 0.15 were found to be optimum for cisplatin PLGA nanoparticles. Nanoparticles made under the optimal conditions found yielded a 112 nm particle size and a 95.4 percent entrapment efficiency, as well as a drug loading of 9 percent. The cisplatin PLGA nanoparticles tailored for scanning electon microscopy displayed a spherical form. A series of in vitro tests showed that the nanoparticle delivered cisplatin progressively over time. According to this work, the Response Surface Methodology (RSM) employing the central composite rotatable design may be successfully used to simulate cisplatin-PLGA nanoparticles.