79717 research outputs found
Sort by
FUBAR: A Narrative Analysis of War Remains
Get PDFThe virtual reality (VR) experience War Remains created by Dan Carlin claims that it is an immersive memory in attempt to give its audience the “tiniest taste of” what-it-was-like to experience a WWI battle (Carlin, 2020). This claim aligns with the growing belief that VR can be the ultimate empathy machine (Milk, 2016). The following is a work of rhetorical criticism. This thesis analyzes War Remains using the narrative paradigm, developed by the rhetorician and literary critic Walter Fisher, in order to assess if War Remains is a rhetorically effective narrative. Through the use of War Remains as a case study, this analysis demonstrates the importance of developing a robust narrative structure in order to deliver on VR marketing material that claims VR programs create empathy
A 1V 40mA Fast Transient Capless LDO with 7uA Quiescent Current in 180nm CMOS using Ring Amplifier with Adaptive Damping
Get PDFRing amplification has emerged as an efficient technique to drive large capacitive loads in switched capacitor circuits. We propose circuit techniques to demonstrate the first application of a ring amplifier in a non-capacitive feedback system of a LDO. These techniques enable a simple cap-less LDO structure in 180nm CMOS that can achieve less than 700ns settling time for load transitions between 100uA-40mA with a quiescent current of 6.5uA while regulating a 1V output with a 80mV drop out voltage
Competing Food Sovereignties: Food Democracy and GMO-free Activism in Southern Oregon
Get PDFFood sovereignty is increasingly being conceptualized as a human rights issue. This is evidenced in the growth of local actors, communities, and nation-states that are working towards a food sovereignty agenda. Indicators of food sovereignty center on people having the right and ability to define their food polices. One of the most highly contested food policy issues worldwide is the use of genetically-modified organisms (GMO/GEs) in agricultural production. The dissertation focuses on the human right to food and food sovereignty through an ethnographic account of local food system activism in Southern Oregon. It assesses the present status of the human right to food within civic society and state/local governance by identifying the mechanisms of and hurdles to food sovereignty and food democracy in the era of corporate agrifood. Specifically, this dissertation examines local GMO-free activism and participatory food democracy in Southern Oregon that occurred between 2012 and 2017. Data collection was undertaken during 2016 and 2017. Standard ethnographic methods were utilized including semi-structured interviews and participant-observation. In addition, archival research was conducted on the GMO-free Jackson County campaign and Oregon legislation relating to the use of GMOs in agriculture and the preemptive seed law. The research results indicate that from its inception, the GMO/GE-free movement in Southern Oregon was in the process of negotiating multiple sovereignties at the local and state levels, including concerned citizens in the community, conventional and organic farmers and seed growers, GMO/GE farmers and the State of Oregon. The research identifies and documents the effects of socio-political power dynamics and tensions that exist between civil society and State of Oregon acts of food sovereignty, democracy and agrifood policy in rural Southern Oregon where priorities regarding the use of GMO crops are in conflict. In passing a GMO-free law, Jackson County Oregon has obtained some measure of food sovereignty, however, the State of Oregon’s seed preemptive law enacted in 2013 curtailed efforts for citizens of other counties in the state to enact a similar GMO-free law. By mapping and comparing successful and unsuccessful real-world negotiations of multiple and contested sovereignties, this study historicizes local food activism and provides evidence for the possible emergence of a third global (corporate) food regime
Multi-objective Resilience Optimization of Interdependent Critical Infrastructure Networks
Get PDFCritical Infrastructures (CIs) such as energy, water supply, telecommunications, and transportation are highly vulnerable to cascading failures due to their interdependent operations. A resilient network is crucial to withstand the impact of functionality loss in disruptive events. This research evaluates network expansion as a proactive resilience strategy in which new network components are added to improve redundancy and increase the service level of the network. We present a multi-objective resilience optimization model to evaluate network expansion decisions for interdependent CIs under disruption uncertainty. A network-based graph is developed to model the geographical and functional relationships of two interacting CIs. A resilience score for interdependent CIs is determined from network complexity and unmet demand metrics to represent the topology-based and service-based network performance metrics. The multi-objective approach is used to develop solutions showing the trade-off between increasing the investment and improving resilience.
Later, the resilience optimization model is formulated as a two-stage stochastic mixed-integer program with the expected total cost and the expected resilience score as competing objectives. The first-stage decisions involve the optimal selection of candidate nodes and links to add to the network. The second-stage decisions comprise the optimal flow allocation, the unmet demand, and the unused supply of CI commodities post-disruption. The disruption uncertainty is introduced as a set of random parameters corresponding to each disruption scenario. The physical interdependencies between CIs are enforced through the demand constraints. We consider a real-world case study of the interdependent power-water networks in Shelby County, TN under earthquake scenarios with varying degrees of severity. The electrical flow in the power grid is modeled using linear DC power flow equations. The model is solved using the augmented epsilon-constraint method to generate sets of Pareto optimal frontiers. This study confirms that network expansion can improve resilience significantly with low total costs, but the improvement diminishes at higher total costs.
Finally, we further evaluate the effect of network topology on resilience through five synthetic interdependent networks having a combination of random and hub-and-spoke topologies with different network sizes and expansion opportunities. We develop a method to generate a manageable number of critical node disruption scenarios. After applying the stochastic resilience optimization model to the synthetic problem instances, the expanded network designs are characterized according to their graph metrics. Random interdependent networks are found to be better connected than the ones with hub-and-spoke structure due to their higher average node degree, higher average clustering coefficient, and lower average shortest path length. Hub-and-spoke structures exhibit scale-free characteristics which make them less tolerant to targeted attacks on the hub nodes. In addition, expansion should be prioritized on the single network with a larger size due to their stronger contribution to the overall resilience. Our study demonstrates the importance of interdependent relationships, network topologies, and disruption types when planning for resilience
Tsunami Loading on Coastal Infrastructure
No full textThe safety of coastal infrastructure has been a concern after the Indian Ocean Tsunami in 2004 and the Great East Japan Tsunami in 2011. The western coast of the United States is also exposed to tsunami hazards due to the Cascadia subduction zone. Therefore, it is critical to design coastal infrastructure, bridges and buildings in particular, for tsunami loading. After a tsunami event, coastal bridges are critical to the transportation in securing the evacuation of people, sending equipment to destroyed area, and reconstructing essential facilities. However, general loading equations to design bridges are not available. Although loading equations for buildings are available, current research on tsunami loading on buildings is based on the assumption that buildings are rigid.
To refine tsunami loading equations and investigate mitigation strategies, it is necessary to use numerical simulation in addition to experiments. An all-encompassing source-to-bridge simulation to determine bridge forces is not realistic due to the different scales between ocean shallow wave flow and localized bridge geometry. Thus, it is desirable to have an efficient approach to impart a wave of given height and velocity on a bridge model.
In this research, a simplified numerical tsunami bore is proposed and validated. In order to provide enough samples to generate loading equations, the simplified bore is used to test bridge scenarios with different wave heights, bridge to standing water level (SWL) clearance and bridge configuration. In turn, loading equations on bridges are proposed with empirical coefficients. Good prediction of the tsunami loading equations to numerical bridge simulations is observed. Other factors that affect the tsunami loading on bridges such as superelevation, rail, and inclined surface of the bridge are considered as extra coefficients applied to the loading equations.
To further examine the role of structural flexibility, a two-story flexible building model is tested with different inundation height and imparted with broken solitary waves while inundated in the OSU wave flume laboratory. It is found that as the inundation height increases, the fundamental period and damping ratio of the structure increases
Process Optimization in the Chemical Life Cycle of Accelerator-Produced, Low Specific Activity 99Mo
Get PDFGlobal efforts to support non-uranium approaches for 99Mo production, due to the proliferation risks associated with 235U fission-based production methods, have recently taken huge strides towards fruition. Several linear accelerator-based methods are currently in late-stage development that can produce low specific activity 99Mo from enriched 98/100Mo targets. The development of these technologies requires new chemical processing and purification schemes that emphasize low-waste recycling of the expensive, enriched Mo material. This dissertation arranges the results from three studies investigating parts of Mo chemical life cycle during accelerator-production of 99Mo.
The first chapter of this work provides background information to some of the work that has already been accomplished towards production of commerical 99Mo, with an emphasis on acclerator-production strategies. This chapter contextualizes the individual objectives of the dissertation within the full chemical cycle of 99Mo. The subsequent chapters discuss results from three studies aimed at specific parts of this chemical cycle while including additional background information where needed for perspective. The first of these studies is a fundamental exploration into the chemical thermodynamics of Mo(VI) in aqueous solutions where high Mo concentrations are present. In this work, three polyoxometalate Mo species were identified and their thermodynamic formation constants were calculated using spectrophotometric data and equilibrium modeling. These results provide new knowledge about Mo speciation during
molybdenum recycling and purification schemes that are currently used during the recycling of enriched Mo targets.
The second and third projects of this dissertation deliver chemical flowsheets based on laboratory-scale experiments for the purification and recycling of Mo targets. In the first of these studies, two separation methods are introduced for the purification of Mo-oxide target material. Rhenium (Re), a frequent contaminant in Mo, is an especially critical element to detect and separate due the neutron activation of short-lived radioisotopes 186/188Re that interfere with the radiopurity of the 99mTc product eluted from low specific activity generators. These methods are based on solvent extraction or chromatographic extraction of Re from the dense Mo matrix. Instrument detection limits investigated and optimized to enable detection of ultratrace quantities of Re. The final project offers a strategy to recycle Mo from the solidified waste stream of some low specific activity generator designs. Recovering Mo from superabsorbant polymer waste of is crucial for maintaining the economic feasability accelerator-produced 99Mo. The results of this work provide a simplified procedure for near-quantitative recovery of Mo as well as some preliminary data on its purification from organic contaminants
An Agent-based Dynamic Network Model
Get PDFAgent-based models (ABM) are widely used in network data analysis, and due to their simple structures and sophisticated outcomes, they serve as good tools in understanding the dynamics in networks. In this thesis, we develop an agent-based dynamic network model, and show that it can replicate the expected degree distribution of a static counterpart at the end of a time duration with both theoretical derivations and simulations
Design Techniques for Wide-bandwidth Continuous-time Delta-sigma Modulators with Noise-shaping Quantizers
Get PDFNoise-shaping multibit quantizers in a ΔΣ modulator offer extra orders of noise shaping without increasing the loop-filter order and without compromising the stability of the modulator. This dissertation presents two new architectures for improving the overall performance of continuous-time ΔΣ modulators using noise-shaped quantizers.
The first modulator architecture is motivated towards achieving high sampling frequencies using a VCO quantizer. The VCO based quantizer provides the benefits of first-order noise shaping, inherent DWA, and high sampling frequencies but suffers from a highly nonlinear voltage-to-frequency transfer characteristic leading to performance degradation. In this work, a dual-path VCO quantizer nonlinearity cancellation technique is proposed that improves the overall modulator performance by cancelling the VCO quantizer non-linearity. The prototype modulator fabricated in a 65 nm CMOS technology achieves 76.1 dB DR, 73.5 dB SNDR and 88 dB SFDR over a 50 MHz signal bandwidth with an OSR of 15 and 51.8 mW of power.
The second modulator architecture, on the other hand, achieves 2nd order noise shaping from the quantizer itself, thus, reducing the needed loop-filter order by two and saving on active RC-OTA based integrator power. This new SAR-VCO based hybrid quantizer solves the VCO quantizer nonlinearity issue and also provides second order noise shaping. By using this SAR-VCO quantizer as an internal quantizer in a 2nd order ΔΣ loop, 4th order noise shaping is achieved using only two OTAs. The pipeline operation of the SAR quantizer and the VCO quantizer makes the delay of the hybrid quantizer equal to the delay of the SAR quantizer only. This reduces the excess-loop-delay introduced by the quantizer when used in a ΔΣ loop. Also, the quantization error leakage due to gain mismatch between the SAR path and the VCO path in the quantizer is noise shaped. The prototype modulator fabricated in a 65 nm CMOS process achieves 83 dB DR, 80 dB SNDR and 84 dB SFDR for a 12 MHz signal bandwidth with an OSR of 25 and 16.5 mW of power
Effect of Agronomically Selenium Biofortified Hay on Oxidative Status, Metabolic and Inflammatory Biomarkers, and Immune Response of Transition Primiparous Dairy Cows and Se Transfer and Glutathione Peroxidase Activity in their Calves
Get PDFDuring the peripartum period (3 weeks before through 3 weeks after calving, a.k.a. “transition”), high producing dairy cows experience, among others, , oxidative stress and immune suppression that compromise performance and increased incidence of diseases.Among trace minerals, supplementation of Selenium (Se) can help to improve the transition by enhancing glutathione peroxidase (GPx) activity and boosting the immune system. Thus, cows during the transition period would benefit from a high amount of Se. Among ways to supplement Se to dairy cows, use of biofortified plants (i.e., the soil is fertilized by inorganic Se that is then incorporated in plant proteins as Se-methionine and Se-cysteine) has proven to be effective in increasing the Se status and improve animals’ health and performance, including their offspring, when fed topregnant beef cows at 2.5 % BW. Different from beef cows, high-producing dairy cows need a more precisely balanced ration that requires a more complex diet; thus, it is not possible to feed only hay. Thus, it remains to be determined if feeding an increased level of Se biofortified hay can be effective in improving the Se status in peripartum high-producing dairy cows.
The present dissertation aimed to assess if feeding Se biofortified hay at a level that is more typical for a ration of high-producing dairy cows is an effective way to improve the transition from pregnancy to lactation in high-producing dairy cows. To accomplish the aim, we tested if supplementing high producing dairy cows with 1 kg/100 kg BW (1% BW) of Se biofortified hay was effective in improving 1) Se status (Part 1) and 2) the transition from pregnancy to lactation (Part 2). For the experiment, we used 10 Jersey and 8 Holstein pregnantdairy heifers that were supplemented with 1% BW of Se biofortified (TRT; n=9; 3.2 mg/kg DM Se) or non-biofortified (CTR; n=9; 0.4 mg/kg DM Se) alfalfa hay mixed with the TMR from approx. 40 days prior- to 2 weeks post-partum.
The objectives of Part 1 of the experiment were to assess if the aforementioned treatment improved 1) the Se concentration in whole blood, liver, milk, and colostrum; 2) the amount of Se that is transferred into the calves; and 3) the antioxidant activity of cows and calves through the determination of GPx activity. For Part 1, we hypothesized that supplementing primiparous dairy cows with a relatively low amount of Se biofortified hay during the dry period and early lactation enhances the Se concentration and antioxidant status in cows and their calves. Se concentration and other trace minerals in whole blood of cows and claves and liver, milk, and colostrum of cows were measured by using ICP-MS, and GPx activity in samples was measured via a commercial kit. Se concentration in blood was 2-fold higher (P<0.05) in TRT vs. CTR (204.5 vs. 95.0 ng/ml) which resulted in higher Se in liver (1.24 vs 0.62 µg/g dry weight) and colostrum (99.1 vs. 27.2 ng/ml) but not milk. Higher GPx activity in plasma (92.8 vs. 77.9 nmol/min/ml) and erythrocytes (549.2 vs. 260.0 nmol/min/ml) were detected, but not in milk. GPx activity in plasma samples was also higher in TRT vs. CTR (92.8 vs. 77.9 nmol/min/ml) and erythrocytes (549.2 vs. 260.0 nmol/min/ml) but not in milk. Compared to CTR, calves from TRT had higher Se in the blood (215.5 vs. 161.22 ng/ml) but only a numerically (P=0.09) larger GPx activity in plasma. A positive correlation was detected between Se in blood and GPx activity in erythrocytes and plasma in cows. Our results proved that feeding pregnant primiparous dairy heifers with one % BW of Se biofortified alfalfa hay is an efficient way to improve Se status in cows and their calves. Se supplementation increased antioxidant activity via GPx in cows and, numerically, in calves. Feeding Se biofortified hay raised Se level in colostrum but not in milk.
Part 2 of the experiment aimed to examine the effect of the treatment on performance, metabolism, oxidative status, and immune response of transition primiparous dairy cows. We hypothesized that supplementing primiparous dairy cows with a relatively small amount of Se biofortified hay during the dry period and early lactation improves performance, metabolism, oxidative status, and immune response. Cows were monitored daily for health status, dry matter intake (DMI), activity, weekly for body weight, and body condition score (BCS). Blood samples were also collected to measure hematocrit (HMC) and metabolic, oxidative, and inflammatory biomarkers. Phagocytosis, white blood cell differential count, and carrageenan skin test (CST) were measured in primiparous cows. Milk yield and components, including fatty acid profile (FA), were determined. Supplementation of primiparous cows with 1% BW of Se-biofortified hay did not affect milk yield or milk components, including fatty acid profile, body weight or DMI. Se biofortified hay affected only a few of the measured parameters in the blood. Albumin level increased, and haptoglobin and urea tended to be increased by supplementation of Se-biofortified hay, indicating a better liver status, especially post-partum. The treatment increased advanced oxidation protein products (AOPP), which is a marker of protein oxidation. An improved antioxidative function of albumin by Se-biofortified hay supplementation was supported by the negative correlation of AOPP with myeloperoxidase and parameters related to inflammation but a positive association with albumin. Se biofortified hay increased hematocrit indicating either a positive effect on erythropoiesis or in lifetime of erythrocytes that could be reduced around calving and/or per effect of severe inflammations. Treatment did not affect any of the measured parameters associated with the immune system. Feeding 1% BW of Se biofortified hay had little effect on metabolic, inflammatory, and oxidative status parameters with no effect on cow’s performance or immune response. Supplementation with Se biofortified hay possibly enhanced liver function, promoted the antioxidant role of albumin, and improved level of red blood cells
Data-Driven Environmentally Sustainable Product Design: A Shift Toward Increased use of Sustainable Design Activities in the Early Design Phase
Get PDFModern product design drives the boundaries of innovation by encompassing complex Design-for-X objectives, and the inclusion of multidimensional stakeholders. This growing complexity in product design has left design teams unequipped, as classical design theory is bounded by designer experience, expertise, and cognition. One novel approach to tackling product complexity is to leverage data into improved design processes through data-driven design methods.
In this dissertation, data-driven design approaches are presented as a means to explore applied knowledge discovery in product data, with a particular focus on function-based design, life cycle inventory, and life cycle assessment data. Using artificial intelligence approaches ranging from decision trees to graph neural networks, and statistical methods such as kernel density estimation, function-based sustainable design is more readily achievable. This dissertation presents methods for introducing sustainable design knowledge in the early stages of product design through the use of data-driven approaches on historic LCA product data. Here, functional modeling is identified as the entry point to the early design phase that can be altered to meet sustainable design objectives. By using data-driven design methods, components are related to functional performance and estimated environmental impact. The culmination of this work is the creation of a probabilistic data-driven methodology that assesses the environmental impact of functional chains and provides component suggestions that reduce potential environmental impact.
The research presented in this dissertation begins with an introduction to data-driven design literature and research opportunities (manuscript one). From these opportunities, manuscripts two and three introduce two function-based design methods for aiding in component function assignment and automated functional modeling. Manuscripts four and five introduce novel sustainable methods that realize the goals of this dissertation to create data-driven sustainable design methods applicable to the early design phase. Expanding on this work, the disparity in product data encourages the exploration of richer data sets. By leveraging multiple data sources, including manufacturing, digital, and other life cycle data, we can look forward to novel approaches in data-driven design for knowledge enrichment in function-based sustainable design