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An Empirical Investigation of Afghanistan���s Organizational Culture
No full textThe purpose of this study was to examine Afghanistan culture using Geert Hofstede's Value Survey Module (VSM-2013). This research aimed to uncover and interpret the VSM profiles for Afghanistan, particularly focusing on differences across gender, ethnicities, languages, and religions in relation to Hofstede���s six cultural dimensions: power distance (PD), individualism���collectivism (IC), masculinity���femininity (MF), uncertainty avoidance (UA), long-term���short-term orientation (LSO), and indulgence���restraint (IR). Survey data were collected from 2,071 students across 15 universities in five provinces ���Kabul, Kandahar, Herat, Balkh, and Nangarhar. After ensuring the reliability and validity of the data, the study employed two main analytical techniques: Multivariate Analysis of Variance (MANOVA) to explore cultural variances across groups (e.g., gender, ethnicity, language, and religion) and Hofstede���s Classic VSM-2013 technique to compute VSM indices for Afghanistan as well as those groups. The results revealed insightful distinctions and similarities in cultural dimensions among Afghan men and women, as well as across various ethnic, linguistic, and religious groups. The study's findings are particularly valuable for addressing the need for empirical evidence on Afghanistan���s national culture. Understanding these cultural contexts is critical for the effective management of human resources in Afghanistan
On the Security of End-to-End Encrypted Messaging and Calling Applications
No full textIn recent years, the use of end-to-end encrypted messaging and calling applications has risen, driven by the need for secure communications. While these applications protect against unauthorized access, concerns about potential vulnerabilities have emerged. End-to-end encryption (E2EE) aims to safeguard private communications, yet fears of eavesdropping and communication manipulation linger, especially from government entities or attackers. Despite its effectiveness, E2EE integrity can be compromised, like through key substitution attacks. Worries center on authentication ceremonies and potential user errors leading to man-in-the-middle (MitM) attacks. Additionally, the introduction of client-side scanning (CSS) in secure applications to detect harmful content raises privacy concerns. CSS���s local processing or endpoint filtering could undermine the promised encryption guarantees.
In this dissertation, we delve into the complexities surrounding the use of end-to-end encrypted messaging and calling applications, addressing issues of impersonations, MitM attacks, authenti-cation ceremonies, and the topic of CSS technology. Our work provides a systematic analysis of E2EE functionality and authentication ceremonies in popular applications. We propose an auto-mated approach to enhance and streamline the authentication ceremony within encrypted applications. Our work highlights vulnerabilities in voice-based authentication and stresses the need for stronger security measures. Additionally, we investigate the risks of using social media networks in the authentication ceremony and examine potential threats related to CSS technologies and their impact on E2EE principles.
Our dissertation provides the following contributions: First, we conduct a comprehensive security analysis of existing studies, identifying flaws and vulnerabilities in widely used encrypted applications, particularly focusing on authentication ceremonies. Second, we explore automated methods to enhance the authentication ceremony and reduce reliance on user interaction. Third, we undertake simulated investigations to identify potential vulnerabilities arising from exclusive reliance on a voice channel for the authentication ceremony in a real-world end-to-end encrypted application. This could compromise the security of static media and textual communications. The insights from our study suggest enhancing the security of end-to-end encrypted apps by using phonetically distinct words for codes, implementing warnings for suspicious voice code usage, employing multiple authentication channels, and prioritizing ongoing research for stronger security measures. Fourth, we introduce a novel investigation targeting social media authentication ceremonies, illustrating potential risks associated with user impersonation through counterfeit ac-counts. Our study suggests enhancing social media authentication security by displaying comprehensive user details, promoting hands-on user verification, using visual cues for unique identifiers, advocating continuous monitoring and adaptation, and fortifying end-to-end encrypted applications with multi-channel authentication. Lastly, we introduce an encrypted keyboard to address concerns related to CSS technology
Phase Field Fracture Simulations of High Burn-Up Uranium Dioxide Under Accident Transients
No full textUranium dioxide stands as the predominant fuel type in contemporary nuclear reactors. Despite its notable utility, there is a desire to enhance its performance in high burn-up scenarios. Such advancements would not only mitigate operational costs within existing reactor fleets but also ensure the long-term sustainability of global nuclear programs. To this end, significant progress has been made concerning the thermal performance of uranium dioxide. One notable advancement has been the use of computer simulations to test the fuel in ways that are difficult to replicate in traditional experiments.
This research introduces a novel variant of the cohesion phase-field fracture model within the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. This model was used to simulate high burn-up uranium dioxide under two specific transient scenarios. The first involves a transient representative of reactor start-up, serving to verify the model and establish a performance baseline. The second scenario involves a high-power ramp transient, simulating an unforeseen accident that could potentially occur at any point during operation. The resulting crack patterns from these transients were systematically studied and subsequently compared with existing literature.
The study of these transients has yielded several significant results. During reactor start-up, a limited number of discrete radial cracks would form at the edge and propagate toward the center of the fuel pellet. Characteristics of these cracks, such as their length and quantity, exhibit correlations with start-up power and fuel heat rate. Additional cracking was observed later in the transient when the fuel temperature was increased. These additional cracks would branch off existing cracks and move in the circumferential direction.
The morphological features of the cracks generated in these simulations are consistent with observations from historical and contemporary experiments. Moreover, the model employed in these simulations demonstrates competitiveness with contemporary counterparts, distinguishing itself by offering greater flexibility and fewer artificial restrictions
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
Posttraumatic Stress, Alcohol Use, and Alcohol Use Motives Among Latina Survivors of Interpersonal Trauma: Examining Associations with Anxiety Sensitivity and Distress Tolerance
No full textHazardous alcohol use, interpersonal trauma, and posttraumatic stress disorder (PTSD) symptomatology are prevalent among college students, especially women who identify as Hispanic/Latinx. However, a dearth of literature has focused on alcohol use and PTSD relations among Hispanic/Latinx college student women, specifically. Thus, research is needed to investigate malleable transdiagnostic psychological factors involved in PTSD symptoms and alcohol use and motivations for alcohol use among Hispanic/Latinx students to inform culturally-tailored, evidence-based interventions. A growing body of literature has demonstrated that anxiety sensitivity (i.e., fear of anxiety-related bodily sensations) and distress tolerance (i.e., ability to tolerate negative emotional states) are two malleable transdiagnostic mechanisms with relevance to both alcohol use and PTSD. The current project examined, among 288 Hispanic/Latina college students (Mage = 23.3, SD = 5.4) with interpersonal trauma histories, the indirect effects of PTSD symptom severity on (1) alcohol use and (2) alcohol use motives (i.e., coping, conformity, enhancement, social) through distress tolerance and anxiety sensitivity, evaluated as parallel statistical mediators. Covariates included subjective social status, country of origin, and trauma load. Results revealed anxiety sensitivity, but not distress tolerance, mediated the link between PTSD symptom severity and a) alcohol use severity; b) conformity motives for alcohol use; and c) social motives for alcohol use. Further, PTSD symptom severity was associated with coping motives for alcohol use via both anxiety sensitivity and distress tolerance. This line of research has the potential to inform and advance culturally-informed literature focused on factors that may impact co-occurring PTSD symptoms and alcohol use among an understudied population
Biological Ecosystem Inspired Approaches for Circular Economy Design and Quantification
No full textA cornerstone of sustainable development is the idea of a circular economy, a closed loop system where resources are cycled through a system and waste generated and virgin resource use are minimized. This thesis proposes a new of design tools based on environmental network analysis (ENA) and new design metrics, Ns* and NS, as tools which can be used to design systems in accordance with circular economy principles. NS is the number of nodes which strongly connect to a cycle, thus participating in both donation and acceptance, and Ns* is the proportion of total actors connected to a cycle that have a strong connection to that cycle. To explore these tools, multiple engineered systems were evaluated to benchmark their performance against the performance of biological ecosystems and to investigate the ties between ENA metrics and circular economy strategies. Manufacturing floors were also assessed in their ability to be easily reconfigured and their performance based on ENA metrics. The manufacturing floors with the closest values to biological ecosystems also performed the best at reconfigurabilty. The results showed how the low data metrics were able to guide design decisions of an emerging technology through exploring the potential resource cycling routes in a hypothetical economy. Additionally, a carpet network model was used to understand how the design tools related to circular economy strategies. Ns* and NS were found to be integral in assessing collaboration between industries participating in cycling, while FCI showed to be a good indicator of resource cycling, waste diversion and a decreased reliance on raw materials
Ira Greenbaum field notebook: GK6001-GK6500.pdf
No full textBound book, each page corresponds to a karyotype slide data.Data pages for GK6001-GK6500 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
San Giacomo di Galizia: The Digital Reconstruction of a Galleon of the Anglo-Spanish War of 1585 ��� 1604
No full textThe San Giacomo di Galizia was a late-16th century galleon employed by Spain during the Anglo-Spanish War that took place between 1585 and 1604. After a failed attempt to capture the English port of Falmouth, the ship returned to Ribadeo on the north coast of Spain, where it sunk due to the damage received in foul weather. The purpose of the thesis was to digitally reconstruct the vessel based on the archaeological evidence, primary historical sources, and contemporary naval treatises in order to analyze the hydrostatic features of the galleon to comprehend the seagoing performance of similar ships of this period. Likewise, the project aimed to determine the efficiency of this new methodology as a digital tool for nautical archaeology and historical research
Geometric Deep Learning for Science: Prediction, Generation, and Symmetries
No full textDeep learning has significant potentials in accelerating the progress of science research. However, the data in most science problems are geometric data, or graph data, which brings many unique challenges. First, designing label-invariant data augmentations for geometric data is challenging. Second, regular deep generative models need to be dramatically modified to suit for 2D molecular graphs, 3D molecular geometries, and periodic materials. In this dissertation, we study these challenges and propose several novel methods to tackle them.
We first propose GraphAug, a novel automated data augmentation method aiming at computing label-invariant augmentations for graph classification. GraphAug uses an automated augmentation model to avoid compromising critical label-related information of the graph, thereby producing label-invariant augmentations at most times. To ensure label-invariance, we develop a training method based on reinforcement learning to maximize an estimated label-invariance probability. Second, we propose GraphDF, a novel discrete latent variable model for 2D molecular graph generation based on normalizing flow methods. GraphDF uses invertible modulo shift transforms to map discrete latent variables to graph nodes and edges. We show that the use of discrete latent variables reduces computational costs and eliminates the negative effect of dequantization.
Third, we propose G-SphereNet, a novel autoregressive flow model for generating 3D molecular geometries. G-SphereNet employs a flexible sequential generation scheme by placing atoms in 3D space step-by-step. We propose to determine 3D positions of atoms by generating distances, angles and torsion angles, thereby ensuring both invariance and equivariance. In addition, we propose to use spherical message passing and attention mechanism for conditional information extraction.
Finally, we propose SyMat, a novel symmetry-aware periodic material generation method. SyMat generates atom types and lattices with a variational auto-encoder model. In addition, SyMat employs a score-based diffusion model to generate atom coordinates based on a novel coordinate diffusion process. We show that SyMat is theoretically invariant to all symmetry transformations of materials.
We demonstrate the effectiveness of our proposed methods with comprehensive benchmark experiments. In the future, we will explore developing novel predictive models for the prediction of Hamiltonian matrices and accelerating the generation of SyMat by stochastic differential equation based diffusion models
Integrated Protein Turnover: Toward a New Understanding of Cellular Protein Metabolism
No full textProtein metabolism lies at the heart of cellular health. However, the intersections between protein anabolism and catabolism are not completely understood. Here we propose a new view on cellular protein metabolism, the integrated protein turnover model, which we argue better explains the events and evidence underlying anabolic and catabolic states in cells. Instead of viewing protein synthesis and breakdown as separate pathways, we argue that these processes are fundamentally and inextricably linked, and that overall anabolism and catabolism are the result of simultaneous and coordinated action of all the protein metabolic machinery, encompassing the mTOR, autophagic, and ubiquitin-proteasome pathways. We provide the first direct evidence that autophagy is required for protein synthesis in muscle, such that mTORC1-mediated anabolism cannot occur without input from the autophagic pathway. We further show that expression of a select autophagy gene, ATG4B is high in lung and pancreatic cancers and its expression is associated with mortality. Inhibiting ATG4B suppresses cancer cell growth and protein synthesis, allowing for targeting of both autophagic and anabolic markers of metabolism. Finally, we demonstrate that microRNA are a viable candidate for the regulation of the overall proteostatic network, and that removing select microRNA (mir15a/16) from skeletal muscle activates muscle anabolic signaling, while restoring these same microRNA slows anabolism and growth in cancer. Our results demonstrate the strength of the integrated protein turnover model, and indicate new avenues for both the understanding and targeting of protein metabolism in health and disease