Gustavsenclayton0672

Crack detection on dam surfaces is an important task for safe inspection of hydropower stations. More and more object detection methods based on deep learning are being applied to crack detection. However, most of the methods can only achieve the classification and rough location of cracks. Pixel-level crack detection can provide more intuitive and accurate detection results for dam health assessment. To realize pixel-level crack detection, a method of crack detection on dam surface (CDDS) using deep convolution network is proposed. First, we use an unmanned aerial vehicle (UAV) to collect dam surface images along a predetermined trajectory. Second, raw images are cropped. Then crack regions are manually labelled on cropped images to create the crack dataset, and the architecture of CDDS network is designed. Finally, the CDDS network is trained, validated and tested using the crack dataset. To validate the performance of the CDDS network, the predicted results are compared with ResNet152-based, SegNet, UNet and fully convolutional network (FCN). In terms of crack segmentation, the recall, precision, F-measure and IoU are 80.45%, 80.31%, 79.16%, and 66.76%. The results on test dataset show that the CDDS network has better performance for crack detection of dam surfaces.Mosquito-borne arboviruses are increasing due to human disturbances of natural ecosystems and globalization of trade and travel. These anthropic changes may affect mosquito communities by modulating ecological traits that influence the "spill-over" dynamics of zoonotic pathogens, especially at the interface between natural and human environments. Particularly, the global invasion of Aedes albopictus is observed not only across urban and peri-urban settings, but also in newly invaded areas in natural settings. This could foster the interaction of Ae. albopictus with wildlife, including local reservoirs of enzootic arboviruses, with implications for the potential zoonotic transfer of pathogens. To evaluate the potential of Ae. albopictus as a bridge vector of arboviruses between wildlife and humans, we performed a bibliographic search and analysis focusing on three components (1) The capacity of Ae. albopictus to exploit natural larval breeding sites, (2) the blood-feeding behaviour of Ae. albopictus, and (3) Ae. albopictus' vector competence for arboviruses. EGFR tumor Our analysis confirms the potential of Ae. albopictus as a bridge vector based on its colonization of natural breeding sites in newly invaded areas, its opportunistic feeding behaviour together with the preference for human blood, and the competence to transmit 14 arboviruses.The current situation with the problems associated with the removal of oil from wastewaters by membranes is being explored. Many types of membranes have been investigated-organic polymers, inorganic or ceramic species and hybrids of the two. Polymeric membranes can be designed to facilitate the passage of oil, but the more successful approach is with hydrophilic types that encourage the passage of water. Ceramic membranes have an advantage here as they are less often irreversibly fouled and give a higher recovery of oil, with a lower flux decline. Furthermore, they can be cleaned up by a simple heating procedure. More attention should be given to understanding the mechanism of fouling so that operating conditions can be optimised to further reduce fouling and further decrease the flux decline, as well as assisting in the design of antifouling membranes. Another obstacle to ceramic membrane use is the high cost of manufacture. Cheaper starting materials such as clays have been surveyed.Autonomous navigation requires both a precise and robust mapping and localization solution. In this context, Simultaneous Localization and Mapping (SLAM) is a very well-suited solution. SLAM is used for many applications including mobile robotics, self-driving cars, unmanned aerial vehicles, or autonomous underwater vehicles. In these domains, both visual and visual-IMU SLAM are well studied, and improvements are regularly proposed in the literature. However, LiDAR-SLAM techniques seem to be relatively the same as ten or twenty years ago. Moreover, few research works focus on vision-LiDAR approaches, whereas such a fusion would have many advantages. Indeed, hybridized solutions offer improvements in the performance of SLAM, especially with respect to aggressive motion, lack of light, or lack of visual features. This study provides a comprehensive survey on visual-LiDAR SLAM. After a summary of the basic idea of SLAM and its implementation, we give a complete review of the state-of-the-art of SLAM research, focusing on solutions using vision, LiDAR, and a sensor fusion of both modalities.Biological molecules can be obtained from natural sources or from commercial waste streams and can serve as effective feedstocks for a wide range of polymer products. From foams to epoxies and composites to bulk plastics, biomolecules show processability, thermal stability, and mechanical adaptations to fulfill current material requirements. This paper summarizes the known bio-sourced (or bio-derived), environmentally safe, thermo-oxidative, and flame retardant (BEST-FR) additives from animal tissues, plant fibers, food waste, and other natural resources. The flammability, flame retardance, and-where available-effects on polymer matrix's mechanical properties of these materials will be presented. Their method of incorporation into the matrix, and the matrices for which the BEST-FR should be applicable will also be made known if reported. Lastly, a review on terminology and testing methodology is provided with comments on future developments in the field.(1) Background Identifying and measuring adverse events (AE) is a priority for patient safety, which allows us to define and prioritise areas for improvement and evaluate and develop solutions to improve health care quality. The aim of this work was to determine the prevalence of AEs in surgical and medical-surgical departments and to know the health impact of these AEs. (2) Methods A cross-sectional study determining the prevalence of AEs in surgical and medical-surgical departments was conducted and a comparison was made among both clinical areas. A total of 5228 patients were admitted in 58 hospitals in Argentina, Colombia, Costa Rica, Mexico, and Peru, within the Latin American Study of Adverse Events (IBEAS), led by the Spanish Ministry of Health, the Pan American Health Organization, and the WHO Patient Safety programme. (3) Results The global prevalence of AEs was 10.7%. However, the prevalence of AEs in surgical departments was 11.9%, while in medical-surgical departments it was 8.9%. The causes of these AEs were associated with surgical procedures (38.