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De Novo Design Of Ablative Polymers For Aerospace Thermal Protection Systems Through An Integrated AI-Theory-Experiment Approach
No full textNovolac phenolic resin (NPR) is a widely used polymeric ablative material (PAM) for thermal protection systems (TPS) due to its high thermal decomposition temperature (TD, 500�°C) and char yield (YC, 55�wt%). However, its drawbacks (including high thermal conductivity, low mechanical properties and water uptake) prompt the need for improved PAMs. This study explores the pyrolysis behavior and char-forming capabilities of NPR and a potential alternative PAM, poly(1,6-dimethyl phenol) (PPO), through both theoretical and experimental approaches. A graph neural network (GNN) was developed to predict structure-property relationships, revealing that benzyl group positioning and oxygen atom placement significantly influence YC. PPO\u27s para-positioned chains and second methyl group also hinder its char formation. Pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) confirmed distinct decomposition products between NPR and PPO, correlating with their TD differences. Density functional theory (DFT) showed NPR requires higher energy for initial dissociation (92.4 vs. 76.4�kcal/mol), contributing to its superior thermal resistance and TD. The experimental study and molecular dynamics (MD) simulations revealed that NPR forms large polycyclic structures, while PPO forms smaller ones, limiting char formation. DFT mechanistic analysis indicated that NPR undergoes intramolecular cyclization to tricyclic intermediates regardless of the initiation pathway (bond fission or H-abstraction). On the other hand, PPO forms similar structures only under H-abstraction due to higher bond energy barriers encountered through bond fission. The key to the formation of polycyclic compounds is the radical center to the adjacent aromatic ring distance. Finally, poly(diphenyl phenol) (PPPO), a PPO analog, demonstrated better thermal properties (TD 530�°C, YC 45�wt%) by enabling cyclization through phenyl substitution. Overall, the study underscores that char yield depends on a polymer\u27s ability to generate radicals capable of cyclization, providing valuable insights for the rational design of next-generation PAMs
Modeling And Characterization Of Additively Manufactured Barium Titanate Ceramic
No full textThis dissertation investigates the influence of geometric design on the mechanical properties of BTO structures fabricated via 3D printing. Using finite element modeling (FEM), we simulate mechanical stress responses across a range of architected designs. Results reveal that specific design strategies can significantly enhance performance by promoting favorable stress distributions. This work highlights the critical role of structural design in optimizing functional ceramics and provides a computational framework for the design of next-generation piezoelectric devices
Technology-Enabled Foreign Object (FO) Prevention
No full textThe aviation industry incurs $14 billion per year in cost due to Foreign Object (FO) damage and the prevention and resolution techniques associated with foreign object debris. While aircraft loss, material scrap and rework contribute to that cost impact, a traditional approach to aircraft design and manufacturing which is based on human performance is also a significant driver. Failure modes and effects analysis of human based aircraft manufacturing reveals that two of the largest risks are associated with unknown potential for FO creation and the inability to recall or objectively provide evidence of FO conformity for cases of inquiry, learning, and sharing. These two main risks present an opportunity for digital technology insertion to confirm the hypothesis that 1) not all FO pose the same risk to an aircraft, 2) a Human-Machine (digital technology) approach can be more effective than solely human approaches, and 3) digital design and manufacturing process techniques can be utilized to prevent FO risk. The research shown in this dissertation will evaluate the hypothesis and address digital twin characterization of the human-machine approach, optimization for humans and machine-based roles in FO prevention, experimentation to evaluate design for FO risk, and validation testing for confirmation
Sustainable Agriculture Through Data-Driven Land And Soil Management For Rural Farming Communities
No full textThis thesis aims to investigate sustainable farming practices by utilizing a database containing soil, weather, and water data. Additionally, it evaluates cropping strategies using a system that incorporates nutrient dynamics and environmental values. The objective is to monitor, develop predictive models, and assess the impact of both controlled and uncontrolled nutrient variables. This is achieved through the development of an algorithm that provides information on soil health based on datasets and land use, with a particular focus on residual values after harvesting for deeper analytical insights and interpretation. This study focuses on key nutrients, including pH levels, water availability, and temperature forecasts. Utilizing the available dataset, machine learning algorithms are applied to evaluate and compare two main scenarios: pure cropping and intercropping. Additionally, the proposed model assesses the selection process for these features using three methodologies, which guide the identification of either a primary crop or a companion crop, depending on the scenario. This approach optimizes rural farming operations by providing farmers with predictive insights into soil health and nutrient availability, thereby promoting the long-term sustainability impact for both farmers and their communities
Investigating the E74-mediated regulation of a GATA factor in Aedes aegypti mosquitoes
No full textThe mosquito species Aedes aegypti has a significant impact on public health as a vector for multiple pathogens. Its ability to transmit deadly diseases, including Yellow Fever, Dengue Fever, and Zika, emphasizes the urgency of understanding its reproductive biology. In female mosquitoes, reproductive success hinges on obtaining a vertebrate blood meal, which triggers vitellogenesis - the synthesis of yolk protein precursors (YPPs) necessary for egg development. Without a blood meal, female Ae. aegypti remain in a state of previtellogenic arrest, where the YPP gene vitellogenin (Vg) is repressed by a type of transcriptional factor, GATAr (AaGATAr) (Attardo et al., 2003). In the post-blood meal (PBM) period, mosquitoes exhibit differential gene expression. The steroid hormone 20-Hydroxyecdysone (20E) is a key regulator of PBM events, with its signaling being mediated by the ecdysone receptor (EcR). The 20E-EcR complex activates several early genes , including E74, which subsequently acts as a transcription factor for late genes, like vitellogenin (Vg). To investigate the role of E74 in regulating AaGATAr gene expression, the knockdown of E74 isoforms can be achieved by RNA interference-mediated techniques. By analyzing the expression of GATAr following E74 isoform knockdowns, we can assess whether the AaGATAr gene is directly regulated by E74A/B in this pathway. The findings of this study can shed light on the molecular mechanisms underlying mosquito reproductive processes, as well as provide potential targets for controlling mosquito populations and mitigating disease transmission. By exploring the interaction between E74 isoforms and the GATAr factor, we can contribute insight into the scope of vector biology and public health
Development Of A Behavioral Paradigm To Monitor Seizure Susceptibility And Severity In A Zebrafish Model Of Cblx Syndrome
No full textMethylmalonic acidemia and homocysteinemia cblX type (cblX) (MIM#309541) is a rare, X-linked recessive disorder caused by a mutation in the HCFC1 gene. This disorder is characterized by multiple congenital anomalies which include intellectual disability, brain malformations, intractable epilepsy, microcephaly, and facial dysmorphia. The most severe symptom of cblX is intractable epilepsy which is 100% penetrant. Our lab developed a zebrafish model with a mutation in the zebrafish hcfc1a ortholog to study the mechanisms underlying seizure phenotypes in cblX. Our laboratory previously showed that mutation of hcfc1a results in increased number and proliferation of neural precursor cells (NPCs) and an increase in AKT/mTOR signaling. Previous studies in the field have confirmed that hyperactivation of mTOR signaling (mammalian target of rapamycin) is associated with seizures. Therefore, we hypothesized that zebrafish with a mutation in hcfc1a are more susceptible to seizures with increased severity relative to their wild-type siblings. To test this, we exposed mutant and wildtype type larvae to pentylenetetrazole (PTZ), a GABA antagonist, with and without inhibition of mTOR. We used Zebrabox technology to record behavioral parameters associated with seizure-like behavior. Suboptimal doses of PTZ did not lead to increased susceptibility in mutant animals, but treatment with mTOR inhibitors was able to reduce the severity of PTZ. We used western blot technology to verify the effects of mTOR inhibition. Our results suggest that hyperactivation of mTOR is partially responsible for seizure severity in hcfc1a mutant larvae but does not enhance seizure susceptibility
The Origin And Geologic History Of Dolostones Associated With The Moab Valley Salt Wall, Paradox Basin, Utah
No full textThis thesis investigates the origin and geologic context of dolostones associated with the Moab Valley salt wall in southeastern Utah, a feature within the broader Paradox Basin that offers an exceptional opportunity to study the interplay between carbonate sedimentation, diagenesis, and salt diapirism. The fundamental research question focuses on evaluating whether dolostones observed in the Moab Valley are all depositional, diagenetic or structurally reworked components of deeper stratigraphy, and how their presence and geometry relate to the halokinetic processes that shaped sedimentation across the Moab Valley. This study tested the hypothesis that dolostones within Moab Valley represent a mixed assemblage derived from various temporal and environmental origins, subsequently reconfigured by salt movement. Fieldwork, petrographic analysis, carbon and oxygen isotopes, and stratigraphic relationships are used to distinguish between carbonates formed in situ during deposition versus those mobilized (inclusions) or folded (megaflap) into younger strata via diapiric processes. Understanding the genesis of these dolostones provides important insights into the depositional and deformational history of the Moab Valley and the broader Paradox Basin. Beyond academic interest, accurately distinguishing between depositional and structural origins of such carbonates is critical. Misinterpretations can lead to flawed basin models, misdirected resource exploration, and incorrect assessments of CO2 sequestration potential. This research concludes that the dolostones in Moab Valley can be classified into 4 distinct lithofacies, each reflecting distinct depositional origins, ages, and relationships to the Moab Valley salt wall. These lithofacies represent three major episodes of carbonate formation in the Paradox Basin, driven by various combinations of glacio-eustatic, climatic, and diagenetic processes, as well as halokinetic influences. The Massive Silty Dolomudstone and Black Laminated Peloidal Dolomudstone lithofacies were deposited in the Pennsylvanian in the Paradox Formation layered evaporite sequence and subsequently dislocated and diapirically carried upward as non-evaporite inclusions in the Moab Valley Salt Wall. The Tan Laminated Sandy Dolomudstone lithofacies was deposited in a shallow hypersaline lake during deposition of the Triassic Chinle Formation. The Breccia Dolostone lithofacies formed post-Triassic in association with basinal fluid migration and diagenesis. Overall, the results support a model in which both depositional environments and salt-related structural processes must be considered together to accurately interpret carbonate occurrences near salt walls
Towards Mitigation of the Light Network Load Performance Penalty of the Network Link Outlier Factor (NLOF)
No full textDetecting and localizing faults in communication networks is critical to maintaining reliable and efficient network operations. The Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm has demonstrated its potential to automate this task but suffers from significant performance degradation under low network load conditions, where limited network flow data reduces its ability to localize faults. This thesis proposes and evaluates the performance of a synthetic traffic generation algorithm to be used with NLOF:MLL. This algorithm strategically injects synthetic flows that supplement the insufficient real network flows, thereby improving NLOF:MLL\u27s performance under low-load conditions. Specifically, we select network flow host pairs such that core network link coverage is heuristically maximized. We use a set of Mininet experiments to evaluate the performance of our synthetic traffic generation algorithm. While our findings are not conclusive, they suggest that synthetic traffic generation may provide a promising avenue for improving NLOF\u27s performance. Further work is needed to isolate the effects of different traffic parameters and to determine how synthetic flows can best support accurate fault localization across varying network conditions
Clinicogenomic Insights For Prostate Cancer Progression
No full textProstate cancer (PrCa) remains a critical challenge in precision oncology due to several reasons including its apparent heterogenous condition, recurrence following treatment and rapid progressive forms. Therefore, identifying patients at risk of progression is essential to fast-track therapeutic decisions and improve outcomes. Despite recent advances in genomic and molecular profiling, conventional PrCa risk assessment tools heavily rely on a few clinical parameters, neglecting the prognostic potential of genomic biomarkers in the presence of clinical biomarkers. This study presents a computational pipeline to harmonize and evaluate the prognostic value of clinicogenomic profiles of patients in modelling progression free survival (PFS). PFS, defined as the time from treatment initiation to disease progression or death whichever comes first, offers a meaningful proxy for overall survival (OS). Since PFS is convenient in cases where long term follow-up is impractical, it is considered useful for speeding up insights into treatment effect and the drug development process. We deployed several existing survival models with extensive tuning strategies across different clinicogenomic data experimental settings, taking into consideration the interplay of relevant and highly ranked clinicogenomic features in all models as well as their discriminative accuracy in ranking patient risks. These models revealed distinct dynamics but consistent multifactorial relevance of clinical and genomic factors to determine association with PrCa progression with good discrimination ability. This study reinforced the use of PFS as a surrogate for OS in PrCa research. Also, the recurrence of specific clinicogenomic biomarkers across different settings highlighted the relevance for further wet lab investigation. Ultimately, these findings upvotes the incorporation of genomics data into survival modelling pipelines, thereby strengthening the case for clinicogenomic risk stratification insights for precision oncology
Low-Cost Electron Donors For Hydrogen Fuel From Water Photolysis
No full textThis work explores strategies for the production of low-cost hydrogen gas, which is a low polluting renewable storable fuel that also can serve as an energy carrier. By lowering the cost of hydrogen, the research presented here can enable its adoption by making it more competitive with fossil fuel and other options. The present work shows that biomass, such as cellulose and starch, can be reformed into hydrogen using water and special metal oxide catalysts in a photocatalytic process. This field of study promises an economically viable solution for sustainable hydrogen production. Natural biomass is energy-rich, widely available, and very low-cost. Photocatalytic water photolysis is based on a redox reaction, that simultaneously oxidizes the oxygen anions in water into molecular oxygen gas, and it reduces hydrogen cations in water to form molecular hydrogen gas. This work takes advantage organic biomass\u27s ability to donate electrons, and in the process become irreversibly oxidized. As such they are called sacrificial electron donors. With the proper catalyst, biomass is easily oxidized to supply electrons for the photocatalytic reduction of water into hydrogen gas. Here, we explore the parameters that optimize the use of cellulosic and starch materials as sacrificial electron donors, and prove that they are viable alternatives compared to expensive molecular organic donors such as alcohols. Comparison of starch and cellulose as sacrificial electron donors reveals that both biopolymers can drive sustained with excellent catalyst stability and reproducibility. However, cellulose markedly outperforms starch when normalized to mass loading. Starch requires 6 mg/mL concentrations to approach its maximum hydrogen-production rate of 0.109 µmol/min. In contrast, cellulose reaches a rate of 0.115 µmol/min at only 1.5 mg/mL, which is one-quarter of the starch concentration. This laboratory has also pioneered a new class of porous, high surface area photocatalysts, derived from potassium triniobate (KNb3O8). With metallic platinum deposited on the surface as a co-catalyst, under UV light these wide-bandgap semiconductor materials exhibit exceptional stability and good photocatalytic activity for hydrogen generation. This new triniobate catalyst was synthesized and used to evaluate both cellulosic and starch electron donors for water photolysis. It is clearly demonstrated that these biomass materials can function effectively as sacrificial electron donors for water photolysis, and reduce the cost of photocatalytic hydrogen by lowering the cost of a major component, the electron donor. This work also shows, for the first time, the feasibility of using alkane oils as electron donors. Due to their hydrophobic nature, oils do not dissolve in water, making them incompatible with water-based photoreactions, since they struggle to mix with other reactants in an aqueous solution. To overcome this challenge, this work presents a method to render these oils chemically accessible in water, by emulsifying them into nano-sized droplets, or oil-in-water emulsions. Various straight-chain alkanes, C6, C7, C10, C13, C16, and C20 are used as models to investigate the effect of oil type on droplet formation in the emulsions and as electron donors. As C20 solidifies at room temperature, these emulsions were made in heated solutions to liquify the wax and were allowed to cool before use. The behavior of the C20 solid nanoparticle emulsions sheds light on the potential future issues, when using solid organic particles as donors. All of the results reported here use UV light to excite wide band gap semiconductor photocatalysts, because this simplifies and provides faster method optimizations, which can then be applied to visible light-activated photocatalytic systems