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Design Attributes to Support Astronaut’s Psychological Well Being in Long Duration Missions
No full textDesigning habitation for long duration missions has many challenges including: maintaining physical health, psychological health, operational functions and many more. This thesis is an exploration between the physical habitat design and psychological function of crew members. Its focus is on the visual elements implemented into the spaces, and integration of environmental features that can enhance the mental wellbeing of astronauts. The study examined and analyzed previous research done in analog missions on the effects of long duration missions on humans. While previous research looked at the effects of the mission on humans very little addresses the design of the habitats as a cause for the stressors. This psychological research was synthesized with research done on current transit habitat designs. The focus was on optimizing the transit spaces but often overlooked strategies to minimize psychological stressors. From the two research studies there are four design attributes that are being proposed to mitigate the psychological stressors in long duration missions. The recommendations aim to improve the quality of life for astronauts by mimicking earth’s key conditions needed to regulate the astronaut’s mental wellbeing. Lighting, virtual windows and skylights, display screens and open spaces all can be implemented i a variety of mission scenarios. The goal is to ultimately optimize the psychological wellbeing of astronauts in the in-transit period of the long duration of missions to ensure success of their missions
Hardware Optimized Modular Reduction
No full textWe introduce a modular reduction method that is optimized for hardware and outperforms conventional approaches. By leveraging calculated reduction cycles and combinatorial logic, we achieve a remarkable 30% reduction in power usage, 27% reduction in Configurable Logic Blocks (CLBs), and 42% fewer look-up tables (LUTs) than the conventional implementation. Our Hardware-Optimized Modular Reduction (HOM-R) system can condense a 256-bit input to a four-bit base within a single 250 MHz clock cycle. Further, our method stands out from prevalent techniques, such as Barrett and Montgomery reduction, by eliminating the need for multipliers or dividers, and relying solely on addition and customizable LUTs. This innovative method frees up FPGA resources typically consumed by power-intensive DSPs, offering a compelling low-power, low-latency alternative for diverse design needs
In My Football Era: Exploring the Impact of Parasocial Interactions in Shaping Football Viewership and Attitudes Among Swifties
No full textThis research examines the influence of parasocial interaction on the development of endorsed brand attitudes by looking at the effects of parasocial interactions between Taylor Swift fans who were influenced to watch her appearances at NFL games during the 2023-2024 season. Using the Dual Entertainment Path Model (Hung, 2014) as a framework to understand this process, relationships were tested between fans’ companionship motives, parasocial interaction, and the entertainment motives and experiences that create endorsed brand attitudes; the relationship between endorsed brand attitude and influenced behavior was also tested. A quantitative survey collected responses from 148 people through social media, snowballing, and undergraduate and graduate classes in the Jack J. Valenti School of Communication at the University of Houston. Findings showed that parasocial interaction positively relates to companionship motives and lighthearted/playful entertainment motives. However, findings also showed that endorsed brand attitude negatively correlates with influenced behavior. The research has practical implications for celebrity-fan relationships in the sports industry while identifying limitations to celebrity endorsements. It also opens the door for further research into parasocial interactions and relationships induced by celebrity media engagement
Novel Design Strategy for Potent and Selective CDPK1 Inhibitors for Cryptosporidiosis
No full textCalcium – dependent protein kinase 1 (CDPK1) is a key enzyme functioning in cell motility of Cryptosporidium parvum (Cp) and C. hominis, the parasitic protozoa accountable for life-threatening diarrhea in young children and immunocompromised individuals worldwide. The unmet clinical need for the treatment of cryptosporidiosis due to the shortage of effective therapeutics has provoked the pursuit of several anti-cryptosporidium approaches. Among those, small molecules targeting the ATP-binding site of CDPK1 have held promise; however, none of the original series of CDPK1 inhibitors has successfully been used in humans due to various toxicities. Recently, UH15-16 that contains a pyridopyrimidinone scaffold, was reported as a novel class of CDPK1 inhibitors showing good Cp growth inhibition (IC50 = 0.04 μM) in HCT-8 host cells and no acute toxicity in mice. However, UH15-16 also moderately inhibited human Src kinase (IC50 = 0.28 μM), which raises a toxicity concern. Thus, enhancement of kinase selectivity was needed. Herein, we demonstrated that targeting a back pocket created by a distinct feature of the CDPK1 αC-helix efficiently enables enhancement of selectivity over human kinases. The structure-activity relationship (SAR) study of pyridopyrimidinone analogs also provided insights into CDPK1 inhibitor optimization. These efforts produced WIN1-158 as a 2nd - generation pyridopyrimidinone based CDPK1 inhibitor that provided greater selectivity (> 1,000-fold) against human Src kinase as well as other human kinases while retaining Cp growth inhibition (IC50 <10 nM) in HCT-8 host cells. This study will pave a new way to develop potent and selective CDPK1 inhibitors to fight against cryptosporidiosis
Machine-Learning-Powered Information Systems: A Systematic Literature Review for Developing Multi-Objective Healthcare Management
No full textThe incorporation of machine learning (ML) into healthcare information systems (IS) has transformed multi-objective healthcare management by improving patient monitoring, diagnostic accuracy, and treatment optimization. Notwithstanding its revolutionizing capacity, the area lacks a systematic understanding of how these models are divided and analyzed, leaving gaps in normalization and benchmarking. The present research usually overlooks holistic models for comparing ML-enabled ISs, significantly considering pivotal function criteria like accuracy, precision, sensitivity, and specificity. To address these gaps, we conducted a broad exploration of 306 state-of-the-art papers to present a novel taxonomy of ML-enabled IS for multi-objective healthcare management. We categorized these studies into six key areas, namely diagnostic systems, treatment-planning systems, patient monitoring systems, resource allocation systems, preventive healthcare systems, and hybrid systems. Each category was analyzed depending on significant variables, uncovering that adaptability is the most effective parameter throughout all models. In addition, the majority of papers were published in 2022 and 2023, with MDPI as the leading publisher and Python as the most prevalent programming language. This extensive synthesis not only bridges the present gaps but also proposes actionable insights for improving ML-powered IS in healthcare management
Impact of Artificial Intelligence in Accounting
No full textThe field of accounting has witnessed significant transformations in recent years due to advancements in artificial intelligence (AI) technologies. In today's digital age, AI has become an integral tool in the accounting industry, with firms increasingly incorporating AI into their practices. This research aims to investigate the impact of AI in the accounting industry, specifically focusing on the tax and audit fields. The study is of paramount importance within the discipline of accounting as it addresses a critical question facing the profession: whether AI is replacing accountants or enhancing their productivity. To gain insights, public accounting professionals were surveyed, gathering firsthand perspectives on how AI is influencing their work and the profession as a whole.Accountancy and Taxation, Department ofHonors Colleg
Prolonged Survival Outcome in a Patient with Refractory Metastatic Colorectal Cancer Treated with Regorafenib Plus 5-Fluorouracil: A Case Report and Literature Review
No full text<b>Background:</b> The use of regorafenib and 5-fluorouracil in the management of refractory metastatic colorectal cancer has gained increasing attention due to their demonstrated efficacy in extending the survival of patients with colorectal cancer. This study aims to discuss the effect of using regorafenib and 5-fluorouracil combination therapy in refractory metastatic colorectal cancer patients. <b>Case Presentation:</b> We present a case report of a 68-year-old female patient with KRAS G12D and PIK3CA mutations who was diagnosed with stage IV-C colon cancer. She was referred to hospice care and subsequently received therapeutic intervention with 56 cycles of regorafenib and 5-fluorouracil for 31 months while maintaining stable disease (SD). The patient exhibited good tolerance with minimal adverse effects, including Grade I-II Hand&ndash;Foot Syndrome. <b>Conclusions:</b> Our case showed the feasibility of using Regorafenib and 5-fluorouracil combination therapy in stage IV refractory metastatic colorectal cancer treatment, which resulted in an improvement in the overall survival after she was referred to Hospice care. Utilizing this case report may provide valuable input in managing refractory metastatic colorectal cancer, given the prolonged survival and the clinical meaningfulness of this regimen in our patient
A Place-Based County-Level Study of Air Quality and Health in Urban Communities
No full textThis study investigates the relationships between air quality, social vulnerability, and health outcomes at the census tract-level in Harris County, Texas. Spatial and regression analyses were conducted using sociodemographic data, air quality indicators, including PM2.5, diesel particulate matter (DPM), nitrogen dioxide (NO<sub>2</sub>), and ozone, and health metrics, such as coronary heart disease, chronic obstructive pulmonary disease (COPD), asthma, and stroke prevalence. The results indicated variability in sociodemographic challenges, air pollution, and health outcomes. Social vulnerability strongly correlated with increased prevalence of respiratory and cardiovascular diseases, notably COPD, asthma, and stroke. The air quality metrics showed significant geospatial variability: PM2.5 and NO<sub>2</sub> were concentrated centrally near transportation corridors, DPM was elevated near eastern industrial regions, and ozone peaked in western parts of the county, potentially due to atmospheric transport and photochemical processes. PM2.5 exposure significantly correlated with increased cardiovascular and respiratory health outcomes, particularly at elevated concentrations. In contrast, ozone demonstrated a plateauing effect, increasing the health risks but with a diminishing impact at higher concentrations. The correlations between social vulnerability and air quality were modest, suggesting homogenous distributions of PM2.5, NO<sub>2</sub>, and DPM across socioeconomically diverse areas, whereas ozone exposure slightly increased with higher social vulnerability. The findings pointed to the complexity of spatial relationships between socioeconomic status, air pollution, and health, highlighting the need for additional monitoring and targeted interventions to improve health outcomes in socio-demographically and economically challenged communities
A Simple Mathematical Model to Determine Pressure Drop Throughout the Bronchial Tree
No full textUnderstanding the deformation of the human diaphragm can have significant medical applications. Being able to predict the deformation requires a modelling of the elastic properties of the diaphragm. Values for pressure throughout the respiratory tract help the effort of determining the elastic properties. One of the biggest contributors to pressure drop is the friction from the respiratory tract wall. A simplified geometry of up to the 4th generation of branching was used to model the pressure drop in the respiratory tract. It was determined that all branches in the model lie within their hydrodynamic entrance region in terms of length. An equation accounting for the hydrodynamic entrance region was used to determine the pressure drop across all generations. Comparing the results to a study using CFD and real experiments showed that accounting for bifurcation is crucial for accounting for the pressure drop throughout the respiratory tract. The study was compared without its acknowledgement of the bifurcation and its value for pressure drop was within 2 [Pa] of the model developed here, a much better agreement. This model has possible use in future research as a basis for developing more complex models that account for bifurcation and other factors contributing to pressure drop.Mechanical and Aerospace Engineering, Department ofHonors Colleg
Effects of Two Weeks of Red Light Therapy on Choroidal Thickness and Axial Length in Young Adults
No full textPurpose: Red light therapy has recently emerged as a treatment for myopia in children. However, the mechanism remains unknown. The purpose of this study was to determine the effects of two weeks of red light therapy on choroidal thickness and axial length in young adults. Methods: Twenty participants, ages 24.6 ± 2.4 years, underwent long wavelength “red” light therapy for 5 minutes twice a day for 2 weeks. Red light was presented binocularly and consisted of full field exposure to long wavelength LEDs (Color Dome, Espion, Diagnosys, LLC) via narrowband LEDs with a peak wavelength of 626 ± 10 nm and irradiance of 0.14 mW/cm2. At eye level, the illuminance is approximately 1000 lux (Mr. Meter), which is equal to 0.8 mW/cm2. Non-cycloplegic autorefraction (WAM-5500) was measured. Before and after 14 consecutive days of twice-daily red light therapy, ocular measurements of the right eye were captured over one day, every three hours from 9:00 am to 9:00 pm. At each time point, axial length was measured (LenStar) and optical coherence tomography (OCT) imaging (Spectralis) was performed. OCT scans were analyzed for choroidal thickness using a custom MATLAB program. Data were analyzed using two-factor repeated measures ANOVAs. Results: Mean SER was -0.97 ± 1.77 D and included 10 myopes (SER range -0.5 to -4.5D) and 10 emmetropes (SER range -0.38 to +0.75 D). Regardless of the treatment, axial length and choroidal thickness demonstrated significant diurnal variation across the 12-hour measurement period (P < 0.005 for both). There were no effects of condition on axial length (P = 0.71) or choroidal thickness (P = 0.49). Mean axial length before red light therapy was 23.95 ± 0.28 mm and after red light therapy was 23.96 ± 0.28 mm. Mean choroidal thickness before red light therapy was 360.5 ± 16.4 μm, and after red-light therapy was 358.5 ± 17.4 μm. Conclusion: Two weeks of twice daily red-light therapy using a full-field LED light source did not result in significant changes in axial length or choroidal thickness in young adults. These findings contrast with studies using a red laser light source for myopia control