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Nanoscale Functionalization of Graphene-Based and Molybdenum Disulphide Samples via Electrochemical and Thermochemical Methods
No full textOur primary objective was to try to functionalize Graphene-based and Molybdenum Disulphide samples through electrochemical and thermochemical methods. The samples that we experimented with were Graphene, Graphene Oxide, and Molybdenum Disulphide on gold substrates. We chemically functionalized Graphene Oxide with Cyanuric Chloride (2,4,6- trichloro-1,3,5-triazine), assisted by an external heater source to covalently bond the compounds (thermochemical means), which was confirmed by X-ray Photoelectron Spectroscopy (XPS) results.
In the electrochemical method, we attempted to locally functionalize Graphene and Molybdenum Disulphide (MoS2) samples fabricated on a gold substrate via tip-based Local Anodic Oxidation (LAO) using a Conductive Atomic Force Microscope, where the AFM tip is connected to the positive terminal of the source meter and sample connected to the negative terminal. The local chemical changes were analyzed by measuring and comparing scan heights before the LAO. Platinum-coated Silicon tips were used due to their hardness and local corrosion resistance to pattern the 2D materials. Analysis of results and a proposed future work on the chemical functionalization of Molybdenum Disulphide were also discussed due to its surface properties akin to Graphene samples
Shell Designs for Tailoring Dissolution Rates of Selective Laser Sintered Pharmaceutical Printlets
No full textWith the advent of personalized medicine, 'Just In Time' manufacturing of solid dosage pharmaceutical formulations is necessary, especially for a pediatric population that has a rapidly changing physiology. Solvent-free additive manufacturing is a promising approach that lends geometric and compositional flexibility to the process. The objective of this study is to investigate the behavior of shell-based designs, predominantly in their ability to affect dissolution rates of additively manufactured (AM) pharmaceutical pills/tablets (printlets). The primary motivation for this work lies in being able to leverage the tailorability of the AM process to control the geometric design of printlets and thus ���tune��� the eventual dissolution rates of these pills in a biological medium. For this, Selective Laser Sintering (SLS) was used to manufacture tablets using a powder mixture consisting of Carbamazepine (CBZ) as the active ingredient (drug), Kollidon VA64 as the excipient (polymer), and gold sheen as the agent with high laser absorptivity. A design of experiments was implemented to investigate the influence of compositional variance (% drug fraction) and geometrical differences (shell thickness) on the manufacturability and mechanical/pharmacokinetic performance of the printlets. Results show a general inverse relationship between structural integrity (as measured by pharmaceutical 'hardness' tests) and drug dissolution rates, as expected. Further, certain shell-breakup events were detectable via dissolution tests, as evidenced by sudden increases in dissolution magnitudes. FTIR and XRD analyses confirmed that there was no appreciable drug degradation. Altogether, this effort yielded a viable approach to 'tune' dissolution rates of certain solid dosage formulations
The Hepatic Biotransformation Capability and Occurrence of Emerging Contaminants in American Alligators (Alligator Mississippiensis)
No full textRecently, emerging contaminants (ECs) have been drawing more attention due to health concerns in exposed organisms. Pharmaceuticals and per- and polyfluorinated substances (PFAS) are representative ECs that are ubiquitous and persistent in aquatic environments. American alligators (Alligator mississippiensis) are often considered a sentinel species in coastal aquatic ecosystems along the Gulf of Mexico as they are susceptible to the bioaccumulation of contaminants due to their high trophic position and longevity. However, the biotransformation capability of alligators for ECs and EC exposure impact in wild alligators are yet to be understood. Therefore, this study aimed to address these knowledge gaps.
For the evaluation of biotransformation capability, a novel in situ liver perfusion system was developed using juvenile alligators. The operativity of perfused livers was tested with normoxic and hypoxic treatments. Under normoxia, the aspartate transferase (AST) and lactate/pyruvate ratio in effluent perfusate remained stable for 6 hours whereas hypoxia significantly increased the lactate/pyruvate ratio after 2 hours. The elevation of lactate suggests the induction of anaerobic metabolism indicating the viability of the organ. With the establishment of operable perfused livers, alligator biotransformation capability for carbamazepine (CBZ) and nicotine (NCT) was investigated by measuring the formation of their primary metabolites. Additionally, the in vitro S9 assay was performed to compare its metabolic potential with perfused livers. For CBZ, perfused livers exhibited only 30% intrinsic formation clearance (CLf,int) relative to the S9 assay. The NCT metabolism was only observed in perfused livers. Compared to the corresponding rat models (S9 or perfused livers), alligators��� CLf,int was 20-60% for CBZ and 50% for NCT of rats. Lastly, wild alligator plasma was analyzed for select ECs and biochemistry parameters. The detected ECs included amphetamine, atenolol, ketoprofen, naproxen, nicotine, and perfluorooctane sulfonic acid. Statistical analyses showed positive correlations between the plasma EC levels and biochemistry indicating potential physiological stress associated with organ injury and endocrine disruption. While this study provides invaluable insight into the metabolic capability and vulnerability to EC exposure in alligators, the methods developed in this study can also serve as an effective toolbox for future studies to protect this ecologically important species
Integrated Techno-Economic and Life-Cycle Assessment of Subsurface Energy-Storage Technologies for Renewable Energy
No full textThe Electric Reliability Council of Texas (ERCOT) has encountered significant renewable energy losses, known as curtailments, due to the fluctuating nature of wind and solar energy, which strains the electric grid. Although energy storage technologies have the potential to alleviate this issue by managing the energy supply, the lack of efficient methods and understanding of their impact has limited their integration into the electric grid. This thesis aims to provide an integrated
techno-economic and life-cycle assessment of two emerging storage technologies, namely subsurface hydrogen (H���) storage and synthetic geothermal storage, to determine the optimal storing option based on estimated efficiency, levelized cost, and greenhouse gas (GHG) emissions. Various phases were analyzed for H��� storage, including H��� production through electrolysis, compression, pumping, subsurface storage, withdrawal, and power generation through a fuel cell. Geothermal storage phases included water heating through an electric-powered hot water/steam
boiler or concentrated solar power (CSP), pumping, storage in geological porous media, withdrawal, and power generation through steam turbines. The monthly averages of ERCOT���s curtailed energy from 2017 to 2021 were used in this study and projected for the next 5 years. Additionally, a reservoir simulation model was utilized to determine the withdrawal efficiency of the geothermal storage. Results showed that around 32-49% of curtailed energy can be recovered through subsurface H��� storage at a minimal levelized cost of 31-50/MWh. Synthetic geothermal storage exhibited higher life-cycle annual emissions and energy consumption, compared to subsurface H��� storage. Results suggest that subsurface H��� storage holds more promise for mitigating renewable energy curtailments
Bayesian Optimization of Coupled Systems
No full textThe field of multidisciplinary design optimization (MDO) addresses the complex challenge of optimizing systems characterized by interconnections or couplings, which significantly increases the computational burden for ensuring reliability in optimization outcomes. Particularly, design challenges involving feedback-coupled systems are notorious for their substantial demands on computational resources. In response to this issue, substantial efforts have been directed towards developing surrogate models that accurately replicate the intricate interconnected nature of these systems. Such models promise to drastically reduce computational expenses while maintaining effectiveness. Although Bayesian Optimization (BO) is traditionally celebrated for its efficiency in querying surrogate models, it encounters significant limitations when applied to constructing surrogate models for interconnected systems. Specifically, the black-box nature of BO struggles to capture the complexities of these systems, often necessitating frequent queries to the actual functions for training set updates. This approach, while potentially reliable, results in prohibitive computational costs.
To address these challenges and enhance the efficiency and reliability of optimization in the context of interconnected systems, we propose a novel methodology. This methodology focuses on the construction and querying of interconnected surrogate models, designed to more effectively and efficiently replicate the behavior of the target systems. By overcoming the limitations of traditional black-box models, our approach aims to provide a viable solution to the computational and practical challenges inherent in multidisciplinary design optimization of feedback-coupled systems. This advancement represents a significant leap forward in the pursuit of computationally efficient and reliable optimization techniques for complex, interconnected systems
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
Common Operating Picture Enhancement for Cyber-Physcial Data and Under Contingencies
No full textThe power grid is the foundation of contemporary society���s infrastructure, so it is crucial to take strong cybersecurity precautions to guard against potential disruptions that could have a significant impact on the stability and functionality of society. The power grid is particularly vulnerable to new cyber threats that pose a growing threat to its resilience.
This research explores the crucial role of common operating pictures in bolstering the cybersecurity of critical infrastructure with easily understandable data. The primary approach to depicting the common operating picture involves the utilization of Graphical User Interfaces (GUIs), which serve as digital platforms enabling operators to engage with physical equipment via visual graphics and graphical icons. The study investigates the Cyber-Physical Resilient Energy Systems Energy Management System (CYPRES EMS) and places a significant emphasis on Cyber-Physical Situational Awareness (CyPSA).
Furthermore, the study illuminates the advantages of integrating a risk matrix graph within and environment called CYPSA live environment. This integration utilizes data on common vulnerabilities and exposures sourced from the National Vulnerabilities Database (NVD). The inclusion of the risk matrix graph provides heightened clarity on the intricacies of the risk landscape, equipping users with discerning options for informed decision-making.
This study builds upon established analytical methodologies, such as attack tree graphs and a method called Failure Modes, Effects, and Criticality Analysis (FMECA), to comprehensively identify and address potential risks and threats to the system.
In conclusion, the results underscore the potential insights derived from combining these technologies, offering a more effective means to protect critical infrastructure from evolving cyber threats and vulnerabilities. The findings contribute to the growing body of knowledge aimed at bolstering cybersecurity measures for vital systems
Influence of Saccharomyces cerevisiae CNCM I-1077 on the Intestinal Environment, Gut Permeability, and Markers of Systemic Inflammation in Horses Fed a High-Starch Diet
No full textThirty mature Quarter Horse geldings were used in a completely randomized 32-d study to test the hypotheses that supplemental live Saccharomyces cerevisiae CNCM I-1077 improves apparent digestion, stabilizes the intestinal environment, reduces gut permeability, and decreases inflammation in horses fed a high-starch diet. Horses were stratified by BW, age, and body condition score (BCS) to one of two treatments (n=15/treatment): concentrate formulated with 2g starch ��� kg BW^-1 ��� meal^-1 (CON) or the same concentrate top-dressed with 25 g/d Saccharomyces cerevisiae (SC; 20 billion CFU). Horses were fed individually in stalls every 12h. Between meals, horses were housed in dry-lots with ad libitum access to Coastal bermudagrass hay. On d 0 and 32, BW and BCS were recorded, and blood was collected prior to feeding at 2, 8, 16, and 24h post meal. Samples were analyzed for serum D-lactate, chemokine (CCL2) and cytokine (TNF��) concentrations. Whole blood 16s rRNA sequencing was performed. Fecal samples were obtained on d 0, 16, and 32 prior to feeding and at 8, 16, and 24h post meal; fecal pH and fecal starch were measured. Beginning d 28, intake and total fecal production were recorded over 4-d. There was an effect of treatment on ���BW (P=0.03), with no change in BCS (P=0.97). D-lactate peaked at h 8 on d 0, and CON was greater than SC (P���0.01). On d 32, D-lactate tended to be higher in SC at 16h compared to CON (P<0.10). LogCCL2 and TNF�� declined (P���0.02) across treatments to d 32. Fold change of percent reads from d 0 in bacterial 16s rRNA was not different between treatment groups. On d 0, fecal pH declined to h 16 (P���0.01) in both groups but returned to baseline by 24h. At h 0, CON had lower fecal pH on d 32 than d 0 (P���0.01). Fecal starch was undetectable indicating nearly complete dietary starch digestion. There was no effect of treatment for any measure of intake (P���0.25) or digestibility (P���0.77). High-starch diet reduced fecal pH and increased BW but after 32-d, there was no difference in digestibility, intestinal inflammation, or gut permeability, regardless of SC supplementation
Exploring the Impact of Catalyst Supports on Hydrogenolysis of Polyolefins over Cobalt-Based Catalyst
No full textThe persistent utilization of plastics and inadequate disposal methods post-consumption are responsible for causing numerous ecological challenges on a global scale. In recent years, hydrogenolysis has been studied as a promising route to chemically repurpose polypropylene and polyethylene, which are some of the most widely used plastics. In this study, polyethylene is subjected to hydrogenolysis, utilizing cobalt-based catalysts on three supports: Zinc Zirconium Oxide (ZnZrO), Cerium Oxide (CeO2), and Titania (TiO2). The reaction is conducted under batch conditions at 275��C and 30 bar H2 pressure, with reactions performed for periods ranging from 30 minutes to 32 hours. Our findings reveal that cobalt supported on ZnZrO exhibits a high yield of liquid phase alkanes (C5-C30) up to 67%. The evolution of products over time also aids us in understanding the influence of the support material on catalyst performance, we propose likely reaction routes followed for hydrogenolysis carried out in the case of Co/ZnZrO and Co/TiO2. A loading study is also carried out to assess the impact of active metal density on reaction product yield and selectivity. Further, the efficacy of Co/ZnZrO is examined by using it to carry out hydrogenolysis of a post-consumer LDPE bottle, yielding results largely consistent with those obtained from the model PE substrate employed in our investigation. These outcomes underscore the pivotal role of support materials in the hydrogenolysis reaction and contribute to the mitigation of challenges stemming from inefficient plastic disposal, providing a more feasible way of upcycling plastics
Transparency, Accuracy, & Uncertainty in Human-AI Collaborative Decision-Making for Spacecraft Anomaly Diagnosis
No full textAI agents are becoming increasingly ubiquitous in a variety of domains, from safety-critical environments to day-to-day activities. These days they are being considered more as a virtual peer rather than a decision-making tool. In the coming years, AI agents will have a key role to play in spaceflight missions that will voyage beyond low earth orbit, where communication delays with the ground control will become longer and more frequent. On-board AI agents can help the crewmembers detect, diagnose, and treat spacecraft anomalies faster, giving them more autonomy and allowing them to respond faster to emergencies, or to focus on other critical aspects of their mission.
In order for any technology to be accepted and used by the operators, a sufficient amount of trust needs to be established first. Trust in automation is a key factor that determines willingness of a human operator to rely on an AI agent. Previous research on trust in an AI agent highlights some key elements that influence its development, such as its transparency, accuracy, and reliability. However, having perfectly accurate and reliable agents may not be possible or even enough to establish trust, especially in scenarios where there is significant uncertainty in the agent���s recommendations. In light of this fact, the link between trust, accuracy, and uncertainty merits further examination. This dissertation aims to elucidate this potential link in an agent that provides explanations for its recommendations compared to one that does not explain its decisions to the user.
This thesis presents the development and use of an AI-agent, Daphne, for detecting, diagnosing, and treating spacecraft anomalies related to the Environment Control and Life Support Systems (ECLSS). We present an experiment where human operators rely on Daphne���s recommendations induced with various levels of inaccuracies and uncertainties to detect and diagnose ECLSS-based anomalies. Human performance (number of anomalies correctly diagnosed and time to diagnosis), trust, situational awareness, cognitive workload, satisfaction, and confidence in their response were measured using both objective and subjective techniques.
Our results show that the effects of automation transparency can influence operator task performance, trust, situational awareness, workload, user confidence, satisfaction, and appropriate reliance positively. Results also suggested that agent accuracy improved task performance, appropriate reliance, and partially improved user confidence, while trust, workload, and SA were not significantly affected. Results also showed that uncertainty in agent���s recommendations reduces task performance, trust, situational awareness, user confidence, satisfaction, and appropriate reliance, and increases mental workload.
Overall, this work sheds light on under-investigated issues in Human-AI Collaboration by providing insights on factors that are most likely to effect the human-AI relationship during long duration exploration missions for spacecraft anomaly diagnosis. Further, this work provides recommendations and guidelines for designers and developers of XAI systems for developing transparent AI agents to support operators in time- and safety-critical tasks and environments, such as crew members during long-duration exploration missions