136879 research outputs found
Sort by
Essays in Climate Risk, Residential Mobility, and Housing Security
No full textThe combination of climate change and economic growth in disaster-prone regions increasingly exposes the population to extreme weather events. In Chapter 1, I use property-level data to quantify the magnitude of climate risk across Texas, highlighting regional variation in exposure that challenges individuals, businesses, and industries across the state.
While the aggregate impacts of natural disasters are well documented, much less is known about the individual responses to these environmental shocks. In Chapter 2, I estimate the average treatment effects of flood damage using a fuzzy regression discontinuity design in the context of Hurricane Harvey, which damaged more than 200,000 homes in Houston, Texas in 2017. I leverage the relationship between flooding and a home���s elevation, exploiting a discontinuous increase in damage from 48,000 once water reaches the first floor. I provide evidence that disaster damage induces homeowners to relocate from their pre-storm residence while simultaneously preventing their decision to sell their property. The impacts on residential mobility attenuate over time, but I document a persistent divergence in the location and type of housing selected by damage-induced movers. My results indicate that flood damage makes people more likely to move shorter distances, and damage-induced movers are more likely to transition out of homeownership. Despite the combined shock to shelter and wealth, I find that flooded households are more likely to sort into higher-income census tracts in the aftermath of Hurricane Harvey.
Housing security is a critical component to wellbeing that extends beyond the context of environmental shocks. In Chapter 3, I explore how housing security relates to tenants��� criminal activity by analyzing the final stage of the eviction process. In particular, I exploit quasi-random variation in eviction executions to identify the impact of extending or shortening the enforcement process on tenants��� arrest propensity. I find no evidence that extending this process affects the likelihood of arrest, but statistical noise from data constraints may contribute to the uncertainty
Applying Topology-Based Machine Learning to Risk Stratification in Pulmonary Arterial Hypertension
No full textRisk assessment instruments such as REVEAL Lite 2 can identify patients at high risk for events related to Pulmonary Arterial Hypertension (PAH). However, some patients classified as low or intermediate risk can still experience disease-worsening events, suggesting that these patients are at increased risk beyond that specified by traditional risk stratification tools.
We utilized a dataset of 109 consecutive PAH patients seen between January 2016 and December 2019. PAH-related worsening events occurred in 22 patients. An event was defined as the initiation of parenteral prostacyclin, lung transplantation referral, or death. The 87 patients without an event were used as controls. Echocardiography and REVEAL Lite 2 variables were obtained 4-8 months prior to an event. Topological Data Analysis (TDA), a machine-learning method well-suited to finding hidden patterns in high-dimensional datasets, was used to analyze the dataset. The TDA results then guided Kolmogorov-Smirnov Two-Sample Tests to identify variables differentiating event-prone patients from low-event patients.
Kolmogorov-Smirnov Two Sample Testing of event-prone and low-event patients across all three risk levels showed REVEAL Lite 2 had a KS-Score of 0.303, putting it below echocardiographic variables such as end-systolic eccentricity index (0.625) in terms of differentiating between the two groups.
In this single center machine learning-based study, TDA was able to identify a unique phenotype of patients defined by worsened echocardiographic parameters who were at high-risk of PAH-related events even when deemed low-risk by traditional risk assessment scoring methods. Future risk stratification studies should consider TDA and other machine learning methods
Thrifted Religion: Finding Religion in Texas Thrift Stores, Volume 2
Get PDFThrifted Religion: Finding Religion in Texas Thrift Stores is a collection of essays written by students from Dr Heidi A Campbell's Comm 480: Religious Communication classes in Spring and Fall 2024. These essays provide descriptions and analysis of selected item included in an exhibition called "Thrifted Religion" held in Fall 2024 at the J Wayne Stark Galleries on the campus of Texas A&M University. The aim of this exhibition was to showcase what religion looks like in East Texas from the standpoint of religious object that show up in second hand and resales stores. The exhibition included over 500 items representing Buddhism, Christianity, Hinduism, Islam, Judaism and various New Religious Movements. This eBook is part of a research study called the ���Thrifting Religion Project,��� which for three years has documented and studied the different forms of ���religious material culture��� found throughout secondhand sales and resale shops in the Bryan-College Station area. Religious material culture refers to the study of physical objects related to various religions' beliefs and practices. It is argued that exploring the types religious objects that show up for resale and their use, can provide a unique perspective into understanding current and changing religious identities, institutions, and beliefs in Texas.Academy of Visual and Performing Arts (AVPA) at Texas A&M University and the Luce Foundation-American Academy of Religion Advancing Public Scholarship Gran
Evaluating the Attentional Demand of Visual and Auditory Stimuli on Adolescents with ADHD Using a Dual Task Paradigm
No full textAttention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder defined by impaired levels of inattention and/or hyperactivity ��� characterized by being unable to stay focused in the face of distraction or think flexibly when presented more than one stimulus. This inability to remain focused may make it difficult to do two things at one time, or dual task.
Dual task is a paradigm used to quantify allocation of attention by asking subjects to perform two tasks consecutively and measuring the difference in their performance individually to completing them together. Usually done with walking and a cognitive task. The type of cognitive task may be important in ADHD because of poorer responses to visual vs auditory stimuli.
This study sought out to examine the difference in dual task cost (DTC) between auditory and visual stimuli-based tasks in older adolescents with ADHD tendencies. The hypothesis was people with ADHD tendencies would experience a higher DTC under visual than the auditory tasks.
Nineteen subjects completed five randomized, one-minute collections of single task (ST) walking, ST visual, ST auditory, dual task (DT) visual (walking while performing the test), and DT auditory. The cognitive DTC was calculated using the percent correct answer difference. The gait DTC was calculated for step width and gait speed. Both the signed and absolute DTC values were analyzed to examine both the direction of the cost as well as the magnitude of the change. Comparisons were made between visual and auditory DTC for percent correct, gait speed, and step width. The absolute value of the cognitive DTC was found to have significance (p<0.001), with the auditory having a higher magnitude of DTC than the visual. Other comparisons were not significant.
Little to no evidence was found to support the hypothesis. This was likely due to the use of preferred gait speed, which may not have challenged attentional resources. Further, it is feasible that there is a cognitive benefit of walking on working memory. Future studies should investigate or control for subtypes or comorbidities of ADHD, the mechanisms of auditory processing in those with ADHD, and the cognitive benefits associated with walking
Thermal Lethality Validation for Human Pathogenic Salmonella enterica on Chicken Feathers and Blood During Simulated Low-Temperature Rendering
No full textPoultry carcass offal rendering is the process in which poultry inedible and carcass waste materials are converted into high-quality protein meals such as poultry, feather, and blood meal, and other commercial byproducts through physical and chemical transformation using sustained heat application, moisture extraction, and fat separation. Nevertheless, the presence of pathogens in animal feed that have been linked to ingredients obtained from rendered products has raised concerns over the process���s capability to reduce food safety hazards to acceptable levels that might be transmitted to animal feeds. This study was conducted to validate the inactivation, and determine the death kinetics, of a thermotolerant human pathogenic Salmonella enterica in chicken feathers and blood during simulated low-temperature dry rendering conditions. Chicken feathers and blood were inoculated with Salmonella enterica serovar Senftenberg 775W and heated to 60, 70, or 80 ��C for 60, 20, and 5 min, respectively. Complete block design experiments were conducted and three samples for each product were processed at each time point and replicated three times (N=3). After thermal treatment, samples were serially diluted and selectively enumerated after incubating for 24 h at 37��C. Experimental data were log-transformed and the Geeraerd non-linear inactivation model was used for curve and data fitting with the Microsoft Excel Add-In software toolkit GInaFiT. The data analysis showed D-values and observed shoulder periods decreased with increase in processing temperature for both feathers and blood. D-values were 2.23��0.045, 0.66��0.135, and 0.29��0.0225 min for chicken feathers and 2.22��0.2, 0.46��0.0175, and 0.27��0.05 min for chicken blood at 60,70, and 80 ��C respectively. Secondary model analysis showed that the maximum inactivation rate was positively correlated with the processing temperature. Model predicted Kmax values calculated per minute were 1.05��0.07, 3.63��0.20, and 8.37��0.67 for chicken feathers, and 1.06��0.10, 5.06��0.20, and 8.53��1.10 for chicken blood at 60, 70, and 80 oC respectively. Study findings validated ability of low-temperature rendering conditions to significantly reduce Salmonella in poultry rendered product to below detectable values. They also provide rendering industry a supporting tool for food safety validation and food safety regulatory standards compliance
An Innovative Algorithm for Assessing Instance Segmentation in Autofluorescence Microscopy Images
No full textNumerous methods have been created to segment individual cells in microscopy images, highlighting the need for an effective way to evaluate segmented results. Traditionally, the comparison of segmented images with their corresponding ground-truth images is conducted on a pixel-by-pixel basis. However, this approach often overlooks the misallocation of pixels between adjacent objects. In response, we introduce a per-object segmentation evaluation algorithm (POSEA), which assesses the accuracy of segmentation for each object in comparison to a ground truth image. The efficacy of POSEA is validated through the analysis of precision, recall, and f-measure scores, contrasting these with those derived from traditional pixel-based assessments across simulated and segmented fluorescence microscopy images of three distinct cell types. Notably, POSEA identifies a higher rate of segmentation errors due to its accurate recognition of pixels misattributed to adjacent objects. As a result, POSEA offers precise metrics for evaluating the segmentation of adjacent objects, proving its effectiveness for evaluating segmentation algorithms for autofluorescence microscopy images
Investigation of Co-resident Attacks in Serverless Cloud Environment
No full textIn the rapidly evolving landscape of cloud computing, serverless environments have gained prominence for their scalability and efficiency. However, the security of such environments re-mains a critical concern given how ubiquitous their implementation is in both academic and industrial settings. This study delves into the realm of co-resident attacks within serverless cloud con-texts, aiming to exploit the weak isolation within software infrastructure implementation. Specifically, this research investigates the potential flaws in the Function as a Service (FaaS) framework and sheds light on the vulnerabilities that arise when multiple tenants share the same underlying hardware. By identifying these vulnerabilities, this research aims to improve the security of serverless cloud domain and explores avenues to protect against co-resident attacks. This work specifically investigates the feasibility of cache covert channel attacks within serverless environments deployed on commercial cloud platforms. In this study, the open-source Apache OpenWhisk function-as-a-service (FaaS) is deployed on top of a Kubernetes (K8s) cluster. The cluster is pro-visioned and managed using Google Kubernetes Engine (GKE) on the Google Cloud Platform (GCP) to emulate a real-world scenario. With this, the potential of malicious actors establishing covert communication channel across co-resident functions is investigated. The research is conducted in a shared host environment within GCP, emphasizing on virtual CPU (vCPU) resource sharing. Dedicated hosts are intentionally avoided to simulate real-world cloud deployment scenarios. Our findings indicate that commercial-grade clouds like GCP inherently provide a degree of security obfuscation, making covert channel establishment more challenging. While attacks may be more feasible on dedicated single-tenant machines, the shared nature of commercial cloud environments adds a layer of complexity. Serverless frameworks, while introducing new abstractions, ultimately rely on the same underlying infrastructure; therefore, they introduce additional noise rather than fundamentally altering the attack surface. While effective defense mechanisms can be implemented, they invariably introduce performance overheads
The Reconstruction of Riesman's Social Character Social Types: Loss of Indigenous Cultural Identity
No full textThe Navajo tribe is one of the largest Indigenous tribes in the United States. With the continuous issues that the Navajo population faces, the loss of cultural identity is a primary concern. Applying David Riesman's theory of social characters, the three recontextualizations: tradition-directed, inner-directed, and other-directed, have yet to be done. Applying and recontextualizing David Riesman's theory will continue to identify and explore Indigenous cultural identity. David Riesman writes mainly about white American suburban society (other-directed) and applies his neglected concepts on traditional directedness. Applying ancestral traditions through the recontextualization of tradition-directed and inner-directed can cause the loss of connection between the Navajo tribe, cultural roots, and cultural identity. Applying Riesman theory to Indigenous tribes will reflect that the difference between the white population (other-directedness) and the Indigenous tribes (traditional-directedness) continues to fit even today. It will return to full circle and follow Riesman's concepts to a certain extent. The other recontextualization is the struggle between each type of social character's three social traits and the direction of modernization
Becoming the (Invisible) Sixth Resident: Cultural Myths and Parasocial Engagement in the Medical Drama Grey's Anatomy
No full textGrey���s Anatomy is one of the longest-running and most successful television medical dramas of all time. Some scholars have investigated the show���s representations of gender, depictions of medical professionalism, and reception of viewers. However, it is still unclear why Grey���s Anatomy resonates with so many viewers, and what cultural messages it may convey.
To address these gaps, I explored the sociohistorical context, cinematic crafting, narrative content, and audience reception of Grey���s Anatomy. Methods include textual and interpretive analysis along with thematic content analysis, structuralist film analysis, narrative discourse analysis, and audience reception analysis of 20 semi-structured interviews.
My results suggest that Grey���s Anatomy is especially immersive when compared to other American medical dramas, partly due to cinematic crafting that encourages viewers to feel immersed within the daily lives of flawed yet glamorous medical professionals. Patient-doctor interactions may effectively portray positive interpersonal communication skills for medical professionals, particularly when navigating patient experiences with suffering and trauma. Complicated and nuanced representations of gender roles and sexual orientation appear to resonate with many viewers. Some dedicated viewers also appear to form parasocial bonds with main characters who function as peer role models for navigating gender identity and sexual orientation.
Overall, I conclude that Grey���s Anatomy encourages parasocial bonds that may provide educational and vicarious emotional support to viewers as they adopt new cultural models related to constructing new personal and professional identities. This research adds to the body of anthropological knowledge by highlighting that parasocial interactions with mass media texts may reflect or reinforce cultural gender values while conveying feelings of friendship, familiarity, and belonging
Computational Biomechanics for a Standing Human Body: Modal Analysis and Simulation
No full textWe develop computational mechanical modeling and methods for the analysis and simulation of the motions of a human body. This type of work is crucial in many aspects of human life, ranging from comfort in riding, the motion of aged persons, sports performance and injuries, and many ergonomic issues.
A prevailing approach for human motion studies is through lumped parameter models containing discrete masses for the parts of the human body with empirically determined spring, mass, damping coefficients. Such models have been effective to some extent; however, a much higher-fidelity modeling method is to model the human body as it is, namely, as a continuum.
We present this approach, and for comparison, we choose two digital CAD models of mannequins for a standing human body, one from the versatile software package LS-DYNA and another from open resources with some of our own adaptations. Our basic view in this paper is to regard human motion as a perturbation and vibration from an equilibrium position which is upright standing. A linear elastodynamic model is chosen for modal analysis, but a full nonlinear viscoelastoplastic extension is possible for full-body simulation.
The motion and vibration of these two mannequin models is analyzed by modal analysis, where the normal modes of motion are determined. LS-DYNA is used as the supercomputing and simulation platform. Four sets of low-frequency modes are tabulated, discussed, visualized, and compared. Higher frequency modes are also selectively displayed. We have found that these modes of motion and vibration form intrinsic basic modes of biomechanical motion of the human body. This view is supported by our finding of the upright walking motion as a low-frequency mode in modal analysis. Dynamic motions of CAD mannequins are also simulated by drop tests for comparisons and the validity of the models is discussed through Fourier frequency analysis. In the low-frequency range, our numerical results have provided a satisfactory self-consistent match as validation. All computed modes of motion are collected in several sets of video animations for ease of visualization. Samples of LSDYNA computer codes are also included for possible use by other researchers