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- Creators: Barrett, The Honors College
Geology and its tangential studies, collectively known and referred to in this thesis as geosciences, have been paramount to the transformation and advancement of society, fundamentally changing the way we view, interact and live with the surrounding natural and built environment. It is important to recognize the value and importance of this interdisciplinary scientific field while reconciling its ties to imperial and colonizing extractive systems which have led to harmful and invasive endeavors. This intersection among geosciences, (environmental) justice studies, and decolonization is intended to promote inclusive pedagogical models through just and equitable methodologies and frameworks as to prevent further injustices and promote recognition and healing of old wounds. By utilizing decolonial frameworks and highlighting the voices of peoples from colonized and exploited landscapes, this annotated syllabus tackles the issues previously described while proposing solutions involving place-based education and the recentering of land within geoscience pedagogical models. (abstract)
The ASU COVID-19 testing lab process was developed to operate as the primary testing site for all ASU staff, students, and specified external individuals. Tests are collected at various collection sites, including a walk-in site at the SDFC and various drive-up sites on campus; analysis is conducted on ASU campus and results are distributed virtually to all patients via the Health Services patient portal. The following is a literature review on past implementations of various process improvement techniques and how they can be applied to the ABCTL testing process to achieve laboratory goals. (abstract)
can also infect people. In recent decades, and especially since the emergence of highly pathogenic avian influenza (HPAI) H5N1 in 1996, these diseases have become a significant threat to animal and public health across the world. HPAI H5N1 has caused severe damage to poultry populations, killing, or prompting the culling of, millions of birds in Asia, Africa, and Europe. It has also infected hundreds of people, with a mortality rate of approximately 50%. This dissertation focuses on the ecological and socioeconomic drivers of avian influenza risk, particularly in China, the most populous country to be infected. Among the most significant ecological risk factors are landscapes that serve as “mixing zones” for wild waterfowl and poultry, such as rice paddy, and nearby lakes and wetlands that are important breeding and wintering habitats for wild birds. Poultry outbreaks often involve cross infections between wild and domesticated birds. At the international level, trade in live poultry can spread the disease, especially if the imports are from countries not party to trade agreements with well-developed biosecurity standards. However, these risks can be mitigated in a number of ways. Protected habitats, such as Ramsar wetlands, can segregate wild bird and poultry populations, thereby lowering the chance of interspecies transmission. The industrialization of poultry production, while not without ethical and public health problems, can also be risk-reducing by causing wild-domestic segregation and allowing for the more efficient application of surveillance, vaccination, and other biosecurity measures. Disease surveillance is effective at preventing the spread of avian influenza, including across international borders. Economic modernization in general, as reflected in rising per-capita GDP, appears to mitigate avian influenza risks at both the national and sub-national levels. Poultry vaccination has been effective in many cases, but is an incomplete solution because of the practical difficulties of sustained and widespread implementation. The other popular approach to avian influenza control is culling, which can be highly expensive and raise ethical concerns about large-scale animal slaughter. Therefore, it is more economically efficient, and may even be more ethical, to target the socio-ecological drivers of avian influenza risks, including by implementing the policies discussed here.
Non-destructive testing (NDT) and structural health monitoring (SHM) are widely used for this purpose. Different types of NDT techniques have been proposed for the damage detection, such as optical image, ultrasound wave, thermography, eddy current, and microwave. The focus in this study is on the wave-based detection method, which is grouped into two major categories: feature-based damage detection and model-assisted damage detection. Both damage detection approaches have their own pros and cons. Feature-based damage detection is usually very fast and doesn’t involve in the solution of the physical model. The key idea is the dimension reduction of signals to achieve efficient damage detection. The disadvantage is that the loss of information due to the feature extraction can induce significant uncertainties and reduces the resolution. The resolution of the feature-based approach highly depends on the sensing path density. Model-assisted damage detection is on the opposite side. Model-assisted damage detection has the ability for high resolution imaging with limited number of sensing paths since the entire signal histories are used for damage identification. Model-based methods are time-consuming due to the requirement for the inverse wave propagation solution, which is especially true for the large 3D structures.
The motivation of the proposed method is to develop efficient and accurate model-based damage imaging technique with limited data. The special focus is on the efficiency of the damage imaging algorithm as it is the major bottleneck of the model-assisted approach. The computational efficiency is achieved by two complimentary components. First, a fast forward wave propagation solver is developed, which is verified with the classical Finite Element(FEM) solution and the speed is 10-20 times faster. Next, efficient inverse wave propagation algorithms is proposed. Classical gradient-based optimization algorithms usually require finite difference method for gradient calculation, which is prohibitively expensive for large degree of freedoms. An adjoint method-based optimization algorithms is proposed, which avoids the repetitive finite difference calculations for every imaging variables. Thus, superior computational efficiency can be achieved by combining these two methods together for the damage imaging. A coupled Piezoelectric (PZT) damage imaging model is proposed to include the interaction between PZT and host structure. Following the formulation of the framework, experimental validation is performed on isotropic and anisotropic material with defects such as cracks, delamination, and voids. The results show that the proposed method can detect and reconstruct multiple damage simultaneously and efficiently, which is promising to be applied to complex large-scale engineering structures.