Diffuse traumatic brain injury (TBI) represents the most common form of brain injury, yet conventional magnetic resonance imaging (MRI) fails to detect neuroinflammatory pathophysiology without overt structural abnormalities. Diffusion MRI (dMRI) offers sensitivity to microscale pathophysiological changes, but imaging signatures, characteristic patterns on scans, require validation against histopathological markers. This study established radiologic-pathologic correspondence between dMRI signatures and histopathologic targets in experimental diffuse TBI. Ex vivo dMRI was performed on adult Sprague Dawley rats (n = 4) 7 days post-injury using a 7T system with mean apparent propagator metrics including Return-to-Axis Probability (RTAP) and Return-to-Origin Probability (RTOP). Immunohistochemical analysis used markers for microglia (Iba1+, CD83), astrocytes (GFAP, AQP4), and neuronal integrity (MAP2). Receiver operating characteristic (ROC) analysis evaluated the diagnostic performance of each marker using skeleton analysis protocols. Quantitative morphological analysis compared the primary somatosensory barrel field cortex (S1BF) and the motor cortex (control). Spatial correspondence was established between dMRI hyperintensity in RTAP and RTOP maps, where qualitative analysis identified high concentrations of microglial (Iba1+) pathology in the S1BF. Iba1+ quantitative analysis revealed significantly lower microglial endpoints and higher process length in S1BF regions compared to motor cortex, representative of injured pathology. CD83 showed contrasting endpoint patterns to Iba1+ but similar process length increase, providing complementary validation of microglial activation. CD83 endpoints demonstrated the strongest diagnostic performance (AUC = 0.750), while Iba1+ endpoints revealed an inverse relationship requiring reinterpretation (AUC = 0.816). GFAP, AQP4, and MAP2 showed minimal regional differences and poor diagnostic performance, suggesting limited utility as biomarkers at this timepoint. Imaging confusion matrix analysis demonstrated perfect specificity in control regions but limited sensitivity (33.3%) in injury regions. This study provides verification of radiologic-pathologic correspondence between dMRI signatures and microglial activation in experimental diffuse TBI.

Intense, ultrashort-pulse laser sources (USPLs) enable a wide range of applications in remote sensing, laser wakefield acceleration, and directed energy. The extremity of the underlying physical phenomena scales favorably with the wavelength of the laser driver, yet, to-date, most of the investigations in intense light-matter interactions used high-power USPLs operating in the relatively narrow wavelength range in the near infrared (NIR). This applies to the nonlinear self-channeling of USPL pulses in air, known as laser filamentation, the primary motivator for the work discussed in this dissertation. Like several other metrics in intense light-matter interactions, the threshold for self-focusing, which is the prerequisite to filamentation, and the optical power carried by an individual laser filament, both scale in proportion to the wavelength of the laser squared. Recent developments in the ultrafast laser technology have enabled the extension of the studies of air filamentation from the familiar NIR spectral range to the short-wave and mid-wave infrared (SWIR and MWIR, respectively). An interesting effect accompanying MWIR filamentation is the efficient and non-perturbation generation of low odd-order harmonics of the optical driver. As the results of our experiments show, spectral interference of the neighboring harmonics carries information about the carrier-envelope phase (CEP) of the MWIR driver pulses and can be used for the single-shot CEP characterization. Contrary to intuition, the carrier-phase information is preserved through the highly nonlinear propagation through the interaction region in the presence of ionization. The natural extension of these and other studies in strong-field science to LWIR is hindered by the lack of practical optical sources in that wavelength range. To address this shortcoming, we have designed and constructed a source of ultrashort optical pulses operating at the center wavelength of 8.5 um. The source is based on optical parametric chirped-pulse amplification (OPCPA) and currently generates one-millijoule pulses at the repetition rate of ten pulses per second. The optical bandwidth of the generated LWIR emission supports one hundred femtosecond pulse duration, corresponding to multi-gigawatt peak optical power. In this dissertation, I will discuss the principle of operation of this OPCPA source, and the major trade-offs involved in its design.

The United States-Mexico transboundary region comprises myriad land covers withdistinct ecosystems, with the desert biome characterized by limited water resources. Water availability plays a vital role in evapotranspiration (ET) and is essential for determining environmental conservation strategies and sustainable management decisions. This study quantifies ET across his diverse landscape using a decade of Landsat 8 Operational Land Imager (OLI) data (2013–2022) at 30-m resolution, and climatological data from the 1-km resolution DAYMET dataset to compute ET. The empirical Nagler ET model developed using the Moderate Imaging Spectroradiometer (MODIS) was applied with Landsat to estimate ETa. A newly developed regional land cover map was used in this study to constrain the analysis of Eta patterns for six selected land cover class types as an initial proof-of-concept methodology. The results showed the highest ETa rates in the higher-elevation land cover classes (The Madrean Upper Conifer Woodland and Shrubland) and land cover classes along the riparian corridors (North American Arid West Emergent Marsh, the North American Warm Desert Lower Montane Riparian Woodland and Shrubland), while the lowest are in drier areas (The Sonoran-Mojave Creosotebush–White Bursage Desert Scrub), which reflects the capacity of each land cover class to retain and transpire water. ETa patterns aligned with vegetation indices; an indication that Eta may be considered a reliable metric for estimating land cover conditions to determine general health, habitat quality, and resilience in the face of environmental disturbance and pressures.

The senior immigrant population in the United States continues to grow. More than ten percent of seniors in the U.S. who are 65 and older were born outside of the U.S. (Elderly Immigrants in the United States," n.d.). The increase in the senior immigrant population in the U.S. is primarily due to the aging of the foreign-born population and immigrants or refugees entering the U.S. to reunite with their families (ASA Generations, 2022). It is projected that by 2060, immigrants 60 years of age and older will make up about a quarter of the elderly population in the U.S. (New Old Immigrants in the U.S., 2022). This includes a large number of older Asian immigrants. Some researchers have proposed that music, as a universal language, contributes to older adults' health and quality of life and promotes the ability to foster cultural understanding and social interaction (MacDonald et al., 2012; Fung & Lehmberg, 2016). However, while there is a large amount of literature on immigrant communities, there is limited research on the link between music and immigration. More in-depth research is necessary to fill this gap. In addition, how to provide culturally sensitive social services or multicultural music programs to ameliorate loneliness and social isolation among senior immigrant Chinese Americans continues to be a common challenge for the public (Stewart et al., 2011). This research aims to build a sustainable, innovative, and inclusive music program that meets Chinese immigrant older adults' diverse needs and expectations while providing hands-on and community-engaged learning opportunities for pre-service teachers. It seeks to be a culturally resonant space that promotes cultural respect and social inclusion while utilizing the power of music as a tool for lifelong learning, social connection, and enhanced emotional and cognitive health. The study found that music participation can evoke deep cultural memories among senior immigrants and promote identity reconstruction, while collective music activities strengthen social connections. Pre-service teachers also experienced a shift in their educational philosophy during this process. This study reveals the role of music in the cultural empowerment and emotional health of immigrant seniors and provides cross-cultural and community-oriented practical references for music education teacher training.

Effective use of additive manufacturing (AM) design freedom and rapid manufacturing capabilities requires designers to promptly address geometry-related quality issues, such as distortion, to ensure part accuracy. To date, AM part design has been a challenging and expensive process, given the complexity and cost of the AM process, the design freedom, and the limited availability of AM data. As a result, ensuring part design for improved quality hinders the broader adoption of AM technologies and may discourage designers from engaging with AM. The trial-and-error design process, based on time-consuming simulations, experiments, and ad-hoc rules, highlights the need for more efficient, data-driven design frameworks. Data-driven models can provide faster predictions of AM process-induced distortion, generate design guidelines by analyzing critical geometric features, and perform design compensation based on these distortion predictions. My research has three distinct aims focused on improving AM design processes and preparation of students for AM: (1) compensate part designs for minimizing part quality issues for the metal AM process, particularly laser powder bed fusion (LPBF), (2) efficiently predict AM part quality and provide design modifications based on the critical geometric features, and (3) explore engineering students experience in engineering, their engineering identity formation and engagement in makerspace to provide a scalable solution that increase students engagement in design and making activities like AM. To address the first aim, a key dimensional characteristics-based geometry compensation integrated remanufacturing framework for reverse engineering (RE) and AM was proposed. The proposed two distortion compensation algorithms utilized the 3D CAD model and the STL model. Findings indicated that STL-based compensation underperformed the CAD-based approach. The deviation distributions of the four remanufactured parts (two case study parts with two compensation methods) and their corresponding nominal geometries had mean values ranging from 30.0 μm to 48.9 μm and standard deviations ranging from 66.2 μm to 78.6 μm. The second aim is to develop a machine learning-based geometry-driven distortion risk (low, medium, or high risk) prediction model for a broad range of axisymmetric geometries. This model identified critical geometric features of parts that contribute to geometrical deviations and quality prediction, and provided targeted design modification recommendations for parts based on their predicted quality measures. This approach can deliver fast and high-quality predictions for a wide range of parts. Shape descriptors accurately classified distortion risk (with an accuracy of 86.4% for 81 test parts) and recommended design modifications to reduce distortion risks based on the key geometric feature trends for distortion risk classes. The third aim of understanding diverse students' engagement in making, makerspaces, and engineering, as well as their engineering identity formation, revealed emergent themes on making. For example, men and womxn (students who identified as women as one of their gender identities) may hold differing perspectives or exhibit varying interests in makerspace engagement, with men focused on specific technologies in the makerspace, while womxn are focused on space, community, and projects, and students feel more like engineers by the end of the semester. These findings can help develop more inclusive and engaging engineering courses, as well as support the development of the AM curriculum. The ML-based part distortion prediction and design recommendation, as well as the geometric feature-based design compensation model and the exploration of differences in engineering students' experiences and engagement in design and manufacturing, can support the broader goal of transitioning seamlessly from design and geometry capture to AM parts with reduced distortion. Model-based methods can capture the interactions among geometric features that impact part distortions, providing accurate and rapid predictions of distortion, design modifications, and compensation. Taken together, this dissertation reinforces the need for model-based methods and workforce training on design for quality that ensures both design intent and part quality in metal AM.

This dissertation explores the incentives of manufacturers to communicate product attribute information to consumers strategically. Two essays examine how firms shape consumer knowledge and search behavior to create favorable competitive conditions, either in horizontal competition with rivals or in vertical relationships with suppliers.Essay 1 outlines how vertical interactions between the manufacturer and suppliers and the horizontal competition between suppliers determine a manufacturer’s incentives for information disclosure. Contrary to the classic literature on quality disclosure, which suggests that manufacturers of all quality levels should voluntarily disclose their private quality information to buyers, recent theoretical advances indicate that mechanisms such as vertical channel interactions may lead manufacturers to withhold high-quality levels. In contrast, empirical evidence and anecdotal observations show that many nonintegrated firms do disclose high-quality levels. This essay addresses this discrepancy by providing a theoretical explanation of how the nature and intensity of supplier-level competition influence manufacturers' incentives to disclose quality. I show that when suppliers are vertically differentiated, the manufacturer discloses all quality levels, regardless of the intensity of upstream competition. Moreover, when suppliers are homogeneous with asymmetric costs or horizontally differentiated, full disclosure can arise if competition is sufficiently intense. Otherwise, partial disclosure emerges, where the manufacturer discloses high and medium-low quality levels but avoids disclosing low and medium-high levels. Additionally, this essay identifies conditions under which channel instruments, such as side payments and pre-commitment to wholesale prices, can encourage manufacturers to disclose quality, thereby improving system profits. The results highlight the impact of disclosure on consumer welfare and product line decisions. Finally, in contrast with the channels’ literature, this essay demonstrates that when consumers are uncertain of quality, introducing upstream competition to a bilateral monopoly may hurt channel efficiency. Essay 2 provides a rationale for the use of product comparison tools and identifies the conditions under which this strategy is profitable. Some firms offer unbiased comparison tools on their websites, even when doing so reveals weaknesses in certain product attributes and risks losing customers already familiar with the firm. Using a game-theoretic framework, we conceptualize comparison tools as a strategic means of influencing the consumer search process by disclosing competing products’ attributes. The model considers manufacturer comparative disclosure and consumer search as two parallel information channels. Contrary to the expectations of regulators and policymakers, this essay shows that comparison tools can decrease competition and lead to higher market prices. It argues that by increasing consumer knowledge about competing products, comparison tools enable marketers to segment the market more effectively based on consumer fit, resulting in less elastic demand. Surprisingly, when firms are symmetric in quality, mutual comparison not only benefits them but also may increase consumer welfare. With firms asymmetric in quality, mutual comparison benefits those with closer quality levels; however, when the quality gap is wide, only the lower-quality firm benefits from comparison. The findings suggest that comparison by a higher-quality product is more likely to be profitable if it is more familiar to consumers or if consumer search costs are higher.

Food security exists when " all people, at all times, have physical and economic access to sufficient, safe, and nutritious food to meet their dietary needs and food preferences for an active and healthy life"(FAO 1996, p.1083). Achieving Sustainable food security in Sub-Saharan Africa (SSA) could be quite a challenge to the ultimate objective of a "hunger free" World. Food security is certainly one of the most complex and multi-dimensional issues of our times in the region, and it is an important measure of development. The general topic of this thesis is the measurement of food security. The general question this thesis asks is: if we include both diet quantity and diet quality in a set of food security indicators, what difference does it make for targeting food-insecure populations and the types of policies needed to reduce food insecurity? Specifically, this thesis investigates two indicators of food security using data from national Household Expenditure Surveys (HESs) conducted in three Sub-Saharan Africa countries in the late 1990s: Ghana, Malawi and Uganda. The two indicators are: household calorie availability, a measure of the quantity of food people eat, and diet diversity, a measure of the quality of that food. Two questions are explored: (1) Do the indicators tell us different things about who in a population is food insecure and the prevalence of food insecurity? And (2) Do they have different determinants? To answer the first question, correlation analysis and contingency tables are employed. To answer the second, community fixed-effects regression analysis (Ordinary Least Squares and Two-stage Least Squares) is employed.

Since precipitation is a crucial component for forage production in the southeastern rangelands of Arizona, ranching operations m this region are highly vulnerable to fluctuations in climate patterns. If crude ENSO forecasts are the only type of climate information available to a rancher, can this information improve resource management strategies and influence the stocking decision? The stocking decision is modeled for the San Carlos cow-calf ranching operation through a stylized dynamic stochastic framework utilizing El Nino Southern Oscillation (ENSO) forecasts that represent qualitatively different types of climate activity such as El Nino and La Nina events to determine the value of climate forecast information in the range cattle stocking decision. ENSO forecasts can lead to improved ranch profits as well as lower average stocking rates.

Existing literature analyzing consumer demand for organically grown produce has primarily consisted of studies that contain self- reported data from a specific region in the US. Research utilizing direct purchasing behavior of organic produce at the household level is almost non-existent. With the use of ACNielsen household scanner data, consumer demand and loyalty to organic fresh products are analyzed as a function of own price, income, conventional prices, household composition, and demographic attributes. While organic products still maintain a small market share in the produce industry, an empirical model must correctly account for corner solutions where a high percentage of households choose conventional over organic items. In controlling for unobserved heterogeneity of households in a panel model, empirical estimates suggest that price effects, the presence of adolescent children, larger households, income levels, and female head of household demographics are statistically significant influences on organic produce purchase decisions at the household level.

This study examines diffusion of Bt cotton in 27 U.S. cotton-producing regions from 1996 to 1999. First, a dynamic logistic diffusion function is estimated to explain regional differences in both the rate and extent of Bt cotton adoption. The function's flexible specification allows for accelerated adoption as well as deadoption. Second, a pesticide use equation is estimated to test whether or not Bt cotton has reduced traditional pesticide use. The two equations are estimated independently and then as part of a simultaneous system to account for potential endogeneity of Bt adoption in the pesticide use equation. Results suggest that demand-side factors, such as pest damage, input costs, output price and government policy significantly influence diffusion, as do supply-side constraints on Bt seed variety availability. The hypothesis that use of Bt cotton does not reduce the use of traditional pesticides is solidly rejected in all of the econometric specifications tested. Results concerning farmers' overall costs, however, are more ambiguous. Estimates suggest that, in many regions, overall costs have not decreased and in several regions, may have increased, Cost-savings alone may not explain the widespread adoption of Bt cotton. Future research on the impacts of Bt cotton on yields would be useful.