High resolution meltcurve polymerase chain reaction assay for detection of salmonella and e. coli O157:H7 in foods

Foodborne illnesses associated with Salmonella and Escherichia coli O157:H7 have become world-wide public-health problems. Conventional methods for the identification of foodborne pathogens are tedious, expensive, and time-consuming. Alternatively, real-time PCR (RT-PCR) as a promising method to detect pathogens in food samples, has recently been widely applied in food safety areas. High Resolution Meltcurve (HRM) analysis, performed immediately at the end of a real-time PCR, is able to yield a higher resolution plot compared with SYBR Green I PCR. HRM dyes completely saturate all amplicons without showing preferential bindings, making the results more clear and distinct. In this research, a multiplex real-time PCR targeting the invA, fimA and stn genes were developed to efficiently detect Salmonella in foods. Furthermore, HRM analysis is sensitive to any single mutation in PCR products, thus it was also applied in this study to distinguish E. coli O157 from other serogroups of E. coli by targeting the uidA gene. The specificity of primers used in this study was checked using many different strains. Results of artificially contaminated foods presented a high sensitivity of the HRM detection methods. Due to its low cost, simplicity of the approach and rapidness, HRM technology is highly competitive with relaxed-condition PCR and probe-based PCR. Besides, an HRM assay can be performed on generic real-time PCR instrumentations found in many laboratories. In conclusion, HRM-based PCR assay are proved to be efficient methods in foodborne pathogen detections.Dr. Azlin Mustapha, Thesis Supervisor.|Includes vita.Includes bibliographical references (pages 58-66)

Ultimate bearing capacity of circular shallow foundations in frozen clay

This paper presents a study on the ultimate bearing capacity of circular shallow foundation in frozen clay. The bearing capacity were determined by model test, numerical simulation and analytical solution. In numerical simulation, the temperature field considering the phase transition was transformed into a temperature load and applied to a three-dimensional solid model. The generalized Kelvin model was used to describe the creep of frozen clay, and step loading was used. Based on the tests results that frozen soil fails because of local shear, we proposed an analytical model to estimate the ultimate bearing capacity of circular shallow foundation with local shear failure mechanisms. Based on the limit equilibrium theory, it was assumed that the fracture plane of the model only develops to the boundary between the transition zone and the passive zone. The results from present study and some other method are presented and compared, which has shown and verified the feasibility of our method. And the analytical solution is in good consistent with the results of the model test and numerical simulation

The Test of torrential rains—— Analysis of factors influencing the credibility of government microblogs in major natural disasters

Social media has become an important platform for the government to release information, publicize policies, and communicate with the public due to its instantaneous, synchronized, interactive advantages. And it plays an irreplaceable role in the rescue and relief process of major natural disasters. It is because of the special attributes and unique effectiveness of government social media that it has also become a visible window to reflect and evaluate the credibility of the Government. This research focuses on the rare and extremely heavy rainstorm that oc-curred in Zhengzhou City, Henan Province, China in July 2021, and uses it as a scenario. By collecting and analyzing the information release data and public interaction information of governments’ microblog accounts in Zhengzhou City, the research is carried out from three dimensions: government information supply, public information demand, and the deviations between the them. After that we will examine the credibility and effectiveness of government social media during the "720" Zhengzhou heavy rainstorm, and try to create a model of the factors which influence the credibility of government social media in major natural disasters, and then propose strategies to improve it

Optimal Feature Transport for Cross-View Image Geo-Localization

This paper addresses the problem of cross-view image geo-localization, where the geographic location of a ground-level street-view query image is estimated by matching it against a large scale aerial map (e.g., a high-resolution satellite image). State-of-the-art deep-learning based methods tackle this problem as deep metric learning which aims to learn global feature representations of the scene seen by the two different views. Despite promising results are obtained by such deep metric learning methods, they, however, fail to exploit a crucial cue relevant for localization, namely, the spatial layout of local features. Moreover, little attention is paid to the obvious domain gap (between aerial view and ground view) in the context of cross-view localization. This paper proposes a novel Cross-View Feature Transport (CVFT) technique to explicitly establish cross-view domain transfer that facilitates feature alignment between ground and aerial images. Specifically, we implement the CVFT as network layers, which transports features from one domain to the other, leading to more meaningful feature similarity comparison. Our model is differentiable and can be learned end-to-end. Experiments on large-scale datasets have demonstrated that our method has remarkably boosted the state-of-the-art cross-view localization performance, e.g., on the CVUSA dataset, with significant improvements for top-1 recall from 40.79% to 61.43%, and for top-10 from 76.36% to 90.49%. We expect the key insight of the paper (i.e., explicitly handling domain difference via domain transport) will prove to be useful for other similar problems in computer vision as well