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Customer Visitation Pattern: A Robust Heterogenous Network Model of Human Mobility
No full textStudying human mobility across time and space has significant implications for urban planning, business management, and disaster studies. However, previous research in this area has identified several gaps, including a lack of detailed understanding of the connection between location characteristics and visit frequencies, a lack of suitable spatial-temporal network models, and limitations in applying existing models to various scenarios. To address these gaps, this doctoral dissertation research aims to provide a general framework from a network perspective to model customer visit patterns, particularly before and after natural disasters. This research will develop a Geospatial Artificial Intelligence (GeoAI) based framework to derive the visitation pattern from heterogeneous data sources, such as mobile phone trajectories, online reviews, and official census data. The proposed research will address the following research questions: How to quantitatively delineate customer visitation patterns based on mobility data and deep learning? What is the typical visitation pattern, and how does it change after a natural disaster? What would the visitation pattern be if the business changed some strategies? The proposed research will model heterogenous data in a network and use deep learning methods to validate and derive knowledge from it. This knowledge can guide business management and support spatial decision-making. Overall, this research will contribute to the development of a network perspective framework for modeling customer visit patterns, which can be applied to various scenarios and guide urban planning and business management decisions
Applied and Theoretical Approaches to Decision Making in Agriculture
No full textThis work consists of three essays, each demonstrating economic approaches to decision making.
In the first essay, the choice of which Title I farm program to enroll in is modelled as a quadratic integer programming problem. This framework is used to determine optimum program selection for upland cotton producers in Hale County Texas with average risk aversion.
The second essay quantifies the gains in efficiency resulting from recent infrastructure development in the Southern Plains region of Texas. The transportation of agricultural commodities on public roads imposes a number of costs on the state. These include increased road maintenance, ecological damage and traffic congestion in urban centers. The presence of these externalities can lead to inefficient market outcomes. This paper uses a linear programming model to study recent changes to the supply chain of cottonseed and lint and the associated improvement in efficiency.
The third essay is a theoretical piece that expands traditional consumer theory, allowing it to be used in new contexts. It uses this framework to explore and reconcile opposing viewpoints on the value of work. It demonstrates that the process of producing commodities is a potentially important source of utility and failing to account for this results in a misleading evaluation of welfare changes associated with a modification of manufacturing methods
Quantifying Complex Grazing Management Practices and Producer Systems Thinking Skills
No full textThe capacity of alternative grazing management strategies to maintain or enhance the production of ecosystem services and ranch profitability continues to be vigorously debated. However, the parameters used to differentiate among alternative grazing systems are inadequate, and standardized methods for comprehensively characterizing grazing systems are lacking. Inconsistent approaches to, and definitions of, adaptive management have likely contributed to the inconsistent findings in grazing management research. Systems thinking has been promoted to enhance decision making in complex natural resource systems but there is a lack of research evaluating the relationship between adaptive management implementation and systems thinking skills. This dissertation (1) develops a rigorous weighted composite index to serve as a standardized approach for more accurately classifying the grazing intensity implemented in grazing management systems; (2) develops an instrument that thoroughly measures the implementation of adaptive management at the ranch level, and; (3) tests the hypothesis that the level of adaptive management is positively associated with a producer���s level of systems thinking skills. The Grazing Intensity Index (GII) characterizes grazing systems differently than characterization efforts that rely on only a few descriptors, which suggests that the GII more objectively and comprehensively captures the cumulative effect of the spatiotemporal distribution of grazing and rest within a grazing system. The Adaptive Management Index (AMI) is positively correlated with perceptions of increased connectedness between grazing system elements, which suggests that the AMI effectively measures the implementation of adaptive management in livestock grazing systems. Gross livestock sales and gender, rather than the AMI, are primary drivers of systems thinking as measured by the systems thinking skills instrument, suggesting that producers who generate a larger volume of sales from their operation have a greater tendency for viewing systems holistically. Implementing the GII and AMI in future grazing management research studies will enable researchers to more precisely characterize contrasting grazing management strategies resulting in more robust findings and enhanced communication among researchers, and between researchers, extension personnel, and producers. Additional research is needed to evaluate the relationship between adaptive management implementation and systems thinking skills
Antimicrobial Resistance Dynamics in Poultry Environment and the Role of Insects as Vectors of Resistance
No full textThis study investigated the potential role of insects in the spread of antimicrobial resistance (AMR) within and around broiler-rearing facilities, specifically focusing on antimicrobial resistance genes (ARGs). By evaluating spatial patterns of AMR, defining the diversity and presence of ARGs, and analyzing the implications for animal and human health, we aimed to better understand AMR dynamics in broiler production environments. We employed multiple sampling techniques to collect insect and environmental samples. Shotgun sequencing was performed to examine the microbial communities and determine the presence of antimicrobial-resistant genes. Spatial variations in AMR and evaluation of elements influencing AMR dissemination were assessed by statistical analysis. Results from this research uncovered a diverse assortment of pathogens and AMR genes within the livestock environment, and highlighted insects as potential vectors for the transmission of resistant bacteria. Variations in AMR occurrence were found among the sampling sites, emphasizing the need for directed surveillance and intervention protocols. The findings of AMR in broiler farms indicated that antibiotic-resistant bacteria pose risks to food safety, human and animal health, and animal welfare, highlighting the necessity of dynamic management practices. Altogether, this study expands upon the understanding of AMR dynamics in broiler facility landscapes and showcases the significance of managing AMR in livestock environments to protect human and animal health. Additionally, our findings highlight the need for integrated management strategies considering the intricate interactions between microbes, arthropod vectors, livestock, and the environment in limiting the spread of AMR
Effects of Horizontal Resolution on Precipitation Simulations
No full textPrecipitation simulated by climate models in different resolutions, including the mean state of global precipitation, regional precipitation response to mesoscale SST variability, global extreme precipitation in present-day and its future projections, are investigated using both observational (reanalysis) data and global climate model simulations.
The hydrological cycle and its anticipated alterations in the face of global warming are analyzed and compared based on observations, reanalysis datasets, and climate models with different horizontal resolution. Notably, CESM-HR demonstrates a remarkably more robust oceanic water cycle than CESM-LR, a difference possibly stemming from the warmer SSTs in CESM-HR in contrast to CESM-LR. Under global warming, the impact of increased horizontal resolution on future projected changes in the hydrological cycle becomes apparent. Specifically, CESM-HR exhibits a slightly higher percentage increase in ocean-to-land water vapor transport. Therefore, it plays a role in the amplified increase in precipitation over land under climate change.
Precipitation and associated atmospheric response to mesoscale SST forcing is explored. By filtering out mesoscale SST variability, CESM-HR produces a realistic precipitation response as observed, while CESM-LR fails to capture such a response because of absent mesoscale SST variability. Further analyses in CESM-HR and ERA5 reveal a similar vertical velocity response extending up to 500hPa, suggesting a possible free-atmosphere response to mesoscale SST anomalies. Composite analysis further validates this local deep response. The poor representation of mesoscale SST variability in CESM-LR hampers model���s ability to simulate precipitation and associated circulation response.
A comprehensive overview of the impact of horizontal resolution on presenting extreme precipitation shows that, CESM-HR not only replicates the observed spatial distribution of extreme precipitation but also accurately captures the intensity across the global land. Significantly, the discernible influence of horizontal resolution on precipitation extremes predominantly manifests itself through its effect on the representation of resolved large-scale precipitation. Under global warming, extreme precipitation over most of the global land is shown to be intensified. After decomposing projected changes of extreme precipitation by moisture budget analysis in CESM-HR, we find that across most of the global land area, the projected changes are predominantly attributed to shifts in atmospheric circulation features, rather than contributions from thermodynamics
Inducing Potential Mutants in Industrial Hemp (Cannabis sativa L.) via Physical and Chemical Mutagenesis
No full textCannabis sativa is a multi-use crop with applications in food, fiber, construction, and medicinal industries. Cannabis plants with low THC concentrations (hemp) have recently been decriminalized by multiple nations across the globe, but farmers are still on the fence about its legality. To avert the risk and constant regulatory pressures due to potential THC contents, we aim to develop a Cannabis variety with zero cannabinoids - Type V Cannabis, using physical and chemical mutagenesis. We selected EMS as the chemical mutagen and E-beam radiation as the physical mutagen and identified the LD50 doses for three hemp varieties ��� HT, 4X, and HCP. The variations in seed germination percentages among mutagen treatments were found to be highly significant (P < 0.05). The M0 seeds were treated with the LD50 dosage of the mutagen to produce mutant M1 populations. The M1 plants displayed a wide array of mutant phenotypes and were tested for their trichome profiles. Selection of M1 plants was done based on mutant phenotypic traits and trichome production, followed by self-hybridizations to produce M2 seeds. The obtained line- Type V is expected to be 100% compliant with all regulations. This promising line presents a new, versatile, and sustainable crop with applications in food, fiber, and construction industries, addressing the growing needs of the nation
Development of an Active Barium Vapor Notch Filter for Ultraviolet Scattering Based Diagnostics
No full textAtomic and molecular filters are proven tools in laser-based diagnostics. Their use as notch filters has greatly expanded the usefulness of scattering phenomena in both ground testing and remote sensing applications. However, current filtering technology limits researchers to the use of the frequency doubled Nd:YAG signal (532 nm) or more rare and complicated lasers such as Ti:Sapphire and Dye lasers. The visible spectrum presents eye safety issues and lacks the molecular scattering signal strength found in the UV. This work aims to develop a vapor filter functioning at the near UV wavelength of the Nd:YAG third harmonic (355 nm). The frequency required for this filter, which utilizes an excited state transition in atomic barium vapor, falls between the ozone absorption region and the retinal hazard region, provides a stronger backscattered signal than visible light, and can be easily attained with the robust and commonly used high-power Nd:YAG laser. These benefits have significant implications for atmospheric measurements, including the aerosol profiling technique of High Spectral Resolution Lidar (HSRL). Through a combined theoretical and experimental effort, a barium vapor filter has been fabricated and characterized for a variety of filter conditions. The results for low vapor pressures of barium are particularly notable and represent the first reported measurements of the absorption feature of interest in the absence of a neutral buffer gas. The addition of a weak argon buffer gas reduced spatial diffusion, resulting in a more stable and deep absorption feature, capable of implementation in scattering based diagnostics. The AURa (Aggie Ultraviolet Rayleigh) Lidar facility has been developed to serve as a testbed for this and other lidar techniques. Aerosol backscatter and extinction results using the novel filter, which mark the first HSRL measurements at 355 nm with a vapor-based filter, will be presented alongside a discussion of the measurement errors and suggested improvements to this system. Finally, a few other applications of the novel filtering approach will be examined
Optimization-based Scheduling in Multi-service Appointment Systems with Application to College Counseling Centers
No full textAppointment scheduling is a crucial problem in various domains such as healthcare and logistics. In practice, several complicating factors make the decision-making process challenging. In this work, we study multi-service appointment scheduling systems having non-stationary arrival processes, with a special focus on college Counseling and Psychological Service (CAPS) centers. Given the increasing prevalence of mental health issues among college students and the resource constraints faced by CAPS centers in addressing the rise in demand, our goal is to propose data-driven solutions that improve students��� access to these vital services.
To achieve this, we adopt a two-step methodology. First, we develop a comprehensive discrete-event simulation (DES) model that accurately reflects the complexities of CAPS center operations. This model acts as a testing ground for evaluating the performances of different scheduling-related policies. Second, we construct optimization-based frameworks that leverage historical demand to identify data-driven schedules that lead to good-performing systems, while incorporating several realistic factors like multiple customer classes and their associated importance, time-varying demands, resource limitations, and implementability. To address the challenge of characterizing system performance for such complex stochastic systems, we develop stylized optimization models based on approximation schemes that capture the transient behavior of the original system. Further analysis leads to key structural properties, which we use to devise efficient globally convergent solution schemes for the stylized models. Our numerical experiments, based on data obtained from Texas A&M University���s CAPS center, demonstrate the benefits of the proposed scheduling methodologies, leading to policies that significantly enhance system performance compared to current scheduling practices
John Bickham field notebook: AK12125-AK12391_assorted_Derr.pdf
No full textEach page/AK number corresponds to a karyotype slide data and/or unique specimen.Data pages for AK12125-AK12391_assorted_Derr corresponding to unique identifiers of specimens/samples examined for biological research. Specimens are primarily housed at Texas A&M University; Biodiverstiy Research and Teaching Collection
The Role of Auditors in Classification of Debt Securities: Evidence From Banks
No full textFirms that hold debt securities can exploit the discretion in security classification and classify securities as held-to-maturity when the classification provides a more favorable accounting treatment (hereby referred to as security classification shifting). In this study, I utilize the banking industry to examine whether auditors are associated with their clients��� security classification shifting strategies. I find a positive association between a bank-client���s security classification shifting and the classification shifting at other bank-clients audited by the same audit office. This finding is consistent with auditors influencing their clients��� security classification strategies. The effect of auditors is concentrated in banks engaging an audit office with a greater emphasis on bank-specific non-audit services and in smaller banks which suggests that auditors are more likely to influence their clients��� financial reporting strategies when the auditor has a greater proclivity to provide advice and when clients have a greater need for financial reporting expertise. Finally, I find evidence suggesting that industry-expert auditors limit security classification shifting in resource-constrained banks; however, non-expert auditors do not appear to have a similar effect