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Integer Programming Approaches for Network Optimization and Chance-Constrained Combinatorial Problems
No full textInteger Programming (IP), a critical branch of optimization, serves as a powerful and fundamental mathematical tool for formulating and solving discrete decision-making problems that are prevalent across various fields of study and real-world applications. Typically, IP is about ways to solve combinatorial optimization problems with discrete or integer variables. By formulating problems as IP models, decision-makers can derive advanced solution techniques to find optimal or near-optimal solutions within complex environments. In this dissertation, we explore several techniques of IP: modeling, lifting, relaxation, convexification and enumeration, with two significant application domains in the context of network optimization and chance-constrained combinatorial problems.
First, we apply IP approaches to studying the spread of influence over networks, a phenomenon with significant implications in diverse areas such as viral marketing, rumor control, epidemiology, social recommendation, etc. Understanding and modeling the spread of influence in social networks are crucial for predicting individual impacts and managing collective dynamics. In this dissertation, we focus on minimizing the spread of influence by removing a subset of nodes from a network. We study the complexity of this problem and develop a novel delayed constraint generation (DCG) algorithm based on an IP model to identify the most critical nodes in the influence propagation process. Furthermore, we derive lifting inequalities for minimal activation sets to enhance our understanding of the dynamics involved. Experiments conducted on the connected Watts-Strogatz small-world networks and real-world networks validate the effectiveness of our methodology. Additionally, we apply techniques to model the spread of infectious diseases over networks through influence maximization. This involves analyzing network structures, modeling connections among individuals with infected probabilities, and incorporating evolving individual behaviors that influence the spread process over time. Simulation results on random networks and a local community network during the COVID-19 pandemic validate the proposed models and their relationships with classic compartmental models.
Second, we apply IP approaches to several chance-constrained problems. Uncertainty poses a significant challenge in decision-making processes, especially when the random vector is high-dimensional. Chance-constrained optimization (CCO) has emerged as a powerful paradigm to model uncertainty in optimization problems. In this dissertation, we first consider a variant of the set covering problem with uncertain data, which we refer to as the chance-constrained set multicover problem (CC-SMCP). We develop exact deterministic reformulations and propose an outer-approximation (OA) algorithm for CC-SMCP using some combinatorial methods. Our methods combine enumerative combinatorics, discrete probability distributions and combinatorial optimization, representing a novel and intriguing direction for future research in combinatorial chance-constrained problems. Additionally, we explore strategies to reduce the number of chance constraints by considering vector dominance relations defined in an appropriate partially ordered set. Some theoretical results on sampling-based methods, sample average approximation (SAA) and importance sampling (IS), to approximate the optimal value of CC-SMCP are also presented. Numerical experiments are conducted to validate the effectiveness of our OA method compared to the SAA and IS approaches. In addition to CC-SMCP, we also investigate the maximum probabilistic clique problem (MPCP) and derived its exact MIP reformulation by considering the complement of random graphs. We proposed two exact algorithms, DCG and Branch-and-Bound (BnB), as well as two approximation algorithms, SAA and Reinforcement learning (RL), to address the problem.Release after 08/22/202
First Description of the Male Ageniella evansi
No full textThe Pompilidae is a large family of aculeate wasps with a global distribution and over 5,000 valid taxa. Pompilid wasps are ectoparasitoids of spiders, and a wide variety of spider families are used as food for the larvae of this family. The genus Ageniella Banks 1912 is strictly a New World group that currently consists of 112 recognized species, and 36 of them occur in the United States. Ageniella evansi Townes, 1957 (Hymenoptera: Pompilidae) was originally described by Townes in his monograph of the Nearctic wasps of the pompilid subfamilies Pepsinae and Ceropalinae (Townes 1957). The original description was based only on female specimens. The male A. evansi is described here for the first time. This description is an adjunct to an ongoing, long-term study of the populations of the species that nest deep within the caves at Colossal Cave Mountain Park at Vail, Arizona, USA.Immediate accessThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
THE RELATIONSHIP BETWEEN EXERCISE AND COGNITIVE HEALTH
No full textDue to an aging population, it is expected for there to be a higher incidence of neurological diseases. It is thus important to understand how to maximize one's healthy years while minimizing one's years living with disease. Exercise is a key component in maintaining a healthy lifestyle. It is known that exercise has numerous benefits regarding physical health, but it is important to also understand its effects on cognitive health in the pursuit of longevity. This literature review examines the relationship between exercise and cognitive health. Exercise reduces the risk of cognitive decline and dementia, enhances physical and cognitive health, and has varying effects on physical and cognitive health depending on the type of exercise as well as intensity, duration, and frequency of exercise. While it may possibly improve cognitive health in cases of dementia, exercise seems to be better as a preventative measure as opposed to a treatment measure. Consistent physical activity seems to improve cognitive health and slow the aging process via stimulation of metabolic pathways that are typically associated with younger populations. Aerobic and resistance exercise should ideally be implemented together to improve cognitive health outcomes. It is important to find the proper balance to challenge without overworking oneself. Exercise improves cognitive health and is essential in sustaining positive health outcomes
CHARACTERIZING INTRINSIC AGE-RELATED DIFFERENCES IN THE CIRCUIT RESPONSIBLE FOR SPATIAL WORKING MEMORY
No full textAs the population of individuals aged 65 and older continues to expand worldwide, it becomes increasingly important to characterize the physiological changes associated with the aging process, especially with regards to brain health and cognitive function. Spatial working memory, a complex cognitive process important to navigation, has proven to be exceptionally vulnerable to age-related cognitive decline (Kapellusch et. al, 2018). In this study we aimed to identify differences in the activity of the hippocampal-prefrontal circuit, which is responsible for spatial working memory, across young and old age groups in order to characterize intrinsic changes to this circuit which occur with age. To do this, a biphasic stimulation probe was used to deliver pulses to the ventral and intermediate hippocampus of anesthetized male F344 rats. Evoked potentials in the mPFC were then recorded along the dorsoventral axis (including the infralimbic and prelimbic layers) using a neuropixels 2.0 probe. When comparing the evoked activity in the medial prefrontal cortex in response to ventral hippocampal stimulation between young and old rats, we found that younger rats exhibited more total active neurons and more spiking activity per neuron compared to their older counterparts. These results were shown to be directly related to hippocampal stimulation. Overall, these results suggest that age-dependent physiological changes to the hippocampal-prefrontal projection may underlie observed age-related differences in spatial working memory capability
USING FAMILY SCIENCE TO PREDICT RESILIENCE OR CRISIS OUTCOMES IN THE MENTAL HEALTH OF MOTHERS RAISING CHILDREN WITH AUTISM
No full textRaising a child with symptoms of Autism Spectrum Disorder (ASD) can be stressful in any family. Due to the high caregiving demands and the persistence of symptoms across the lifespan, mothers in particular are at risk for mental health issues such as depression, anxiety, and negative emotions. Treatments and interventions for ASD are typically geared toward the child as an individual. However, family systems theory tells us that the effects of a child's diagnosis of ASD can ripple through the entire family unit. The ABC-X Stress Model is a tool used to evaluate how families cope with stress by analyzing (A) the stressor, (B) resources available, and (C) family perceptions, which lead to (X) our outcomes of crisis or resilience. My aim in this paper was to adapt the ABC-X Stress Model to examine factors of maternal stress when raising children with ASD. This allows us to analyze risks of crisis and resilience within mothers' mental health. A literature review of 30 peer-reviewed articles was used to analyze what research has already been done in this area. The results imply that addressing one factor alone is not sufficient for significantly improving mental health in mothers. The findings show how mental health promotion and prevention for mothers of children with ASD can be analyzed through identifying the personal, societal, and social structures that act as preventative factors or put mothers at risk. This allows researchers, policy makers, as well as therapists, to identify ways to reduce stress, social disparities, and encourage resilience by creating programs that support mental health promotion
SYNTAX OF ADVERBIAL PARTICLES IN O'ODHAM: AN ANALYSIS OF HAB
No full textO'odham is a language of the Tepiman branch of the Uto-Aztecan language family. It is spoken
across southern Arizona and northern Mexico. O'odham contains a plethora of particles, that is
small, typically cliticized, functional elements of an indeterminate syntactic category. Despite
O'odham containing so many particles and these particles occurring so frequently (Hale 2001),
there has been little pedagogical, descriptive, or theoretical work done about these particles. This
is a topic mutually interesting to both linguists (who will need to account for these particles
while developing theories that can better encompass languages like O'odham) and the O'odham
community (as these particles can be difficult to explain). This project set out to create an
syntactic analysis for the O'odham particles hab, cem, "˜ep, "˜i (inceptive), and "˜i (correlative).
Hale's Preliminary Remarks on the Syntax and Semantics O'odham Particles (2001) provided
the framework for these particles in which this project is situated in. It also provided some
hypotheses as to the ordering of these particles which were used as a starting point for this
project. This project analyzed sentences containing these particles from A Dictionary of Papago
Usage by Madeleine Mathiot (1973) and Legends and Lore of the Papago and Pima Indians by
Dean and Lucille Saxton (1969). Based on my analysis, I will present some generalizations about
the particle hab
SCIENTIFIC VISUALIZATION OF PHOTON RING FORMATION AND IMAGING
No full textThe photon ring is a key feature predicted by general relativity. It is a narrow ring formed of multiple images of the matter orbiting the black hole. Recent advances in radio astronomy, such as the Event Horizon Telescope (EHT), have made imaging the regions where the photon rings form increasingly relevant. This thesis aims to develop a scientifically accurate and pedagogically effective visualization of physics underlying the photon ring, utilizing ray-tracing simulations to model photon trajectories around rotating black holes. Emphasis is placed on clarity and accuracy to support public outreach and educational contexts. These renderings provide intuitive insights into relativistic light bending and observational challenges of detecting such features. The visualizations developed here serve as tools for science communication and a foundation for future interactive platforms exploring black hole imaging
GENRE GAME SHOW
No full textMy Honors Thesis is a combination of both my major in Psychology and my minor in Film & Television. To utilize both disciplines, I decided to create a video based on the survey data I gathered about audiences' movie genre preferences. In the film industry, we have been trying to figure out audiences' preferences for centuries, and most of the data now is collected illegally through streaming services. I used a public Google Forms survey to collect this data legally from volunteer survey takers, via QR-coded posters & social media posts. Posters were distributed throughout Arizona, and before the survey was closed in April 2025, there were 340 survey entries. The ultimate goal was to find the best movie genre combo, with a variety of 8 selected genres and 3 combo add-ins. These add-ins are comedies, animation, and musicals; they are labeled as such since they can fit into any of the 8 genre categories. Through a 3 round game show, contestants earn points by guessing which genre is being referenced in each interview. Each interviewee has signed a legal consent form before being recorded. Interviews were used for the 5 worst-ranking genres and were divided into 2 guessing rounds, while the final round is the reveal of the top 3 best genre combos
IMPROVING ENERGY EFFICIENCY IN SEMICONDUCTOR HVAC SYSTEMS
No full textThe semiconductor industry plays a major role in modern technology, including consumer electronics and advancing computing systems. As demand for semiconductors continues to grow, the need for efficient and sustainable processes has increased. A critical focus within the industry is optimizing cleanroom environments, which are essential for contamination-free production. Cleanrooms must meet strict standards for air quality, temperature, and humidity, but maintaining these conditions requires significant financial investment, energy consumption, and water usage. Addressing these challenges is essential to improving operational efficiency and reducing environmental impact.
Optimizing HVAC systems in semiconductor cleanrooms provides an opportunity to address these issues. This project focuses on developing and analyzing various HVAC airflow configurations tailored for different cleanroom classifications. The primary objective is to identify the optimal configuration that balances energy usage, cost-effectiveness, water consumption, and environmental responsibility. Through modeling and analysis, various cleanroom HVAC systems were created and evaluated for their ability to supply clean air efficiently while maintaining compliance with air quality, temperature, and humidity standards. Emphasis was placed on reducing energy usage and emissions without compromising cleanroom integrity. This initiative is driven by the growing demand for sustainable manufacturing practices and the continuous expansion of the semiconductor sector. With rising global energy costs and tightening environmental regulations, HVAC optimization can reduce operational expenses and support sustainability goals. Innovative airflow configurations and energy-efficient designs can also help establish new industry standards for cleanroom operation. This report analyzes four airflow configurations, labeled Exhibits A through D, using ISO 4, ISO 5, and ISO 7 cleanrooms to simulate different manufacturing processes. Exhibit A models fully independent cleanrooms with no air reuse. Exhibit B connects the cleanrooms in sequence, recycling air between different classifications. Exhibit C mirrors A but incorporates return air into the feed stream. Exhibit D combines both return and recycled air strategies across interconnected cleanrooms. In Stage 1, all configurations were modeled under extreme hot and cold dry conditions over a six-month period. In Stage 2, daily temperature and humidity data from Chandler, Arizona were used for a more realistic, year-round cost comparison. The economic analysis evaluated financial feasibility using cash flow diagrams that included capital costs, utility expenses (electricity, municipal water, R-32, and ultra-pure water), maintenance, and equipment depreciation. Utility rates were sourced from the City of Phoenix (2024), and water costs from Whitehead (2020). A 12-year Net Present Value (NPV) analysis using a 20 percent minimum acceptable return rate was conducted. In Stage 1, Exhibit D was the most cost-efficient option (NPV: 389,298,169). In Stage 2, Exhibit D again performed best (NPV: 133,110,000). The use of real daily data in Stage 2 resulted in lower projected losses overall. In Stage 1, heating and cooling dominated electricity usage due to the modeled extremes. Assumptions in equipment sizing and weather profiles introduced uncertainty. Stage 2 results, based on daily climate data, showed greater accuracy, with humidifier operation emerging as a key cost driver. However, using daily averages may obscure fluctuations in heating and cooling demands, especially when temperatures hover near the cleanroom setpoint. This limitation can affect the accuracy of utility cost estimates. Despite these uncertainties, the relative rankings of configurations in the decision matrix are unlikely to change. Refining equipment sizing and incorporating more detailed weather data could improve future modeling. Additional considerations, such as varying air change rates and fan filter efficiencies, may provide further optimization opportunities. Based on this study, Exhibit D is expected to remain the most effective configuration. This work highlights key cost drivers and areas for future refinement in cleanroom HVAC system design
COMPARISON OF PAIN MANAGEMENT IN PATIENTS CARED FOR BY BASIC VERSUS ADVANCED LIFE SUPPORT (BLS VS. ALS) FIRE ENGINE FIRST RESPONSE CREWS
No full textObjective: In 2023, a single large fire-based EMS agency, transitioned from a Basic Life Support (BLS) fire engine and dual paramedic Advanced Life Support (ALS) ambulance system, to an all ALS response model, with a paramedic on both the engine and ambulance transport. The impact of this transition from a dual medic (DM) ambulance to a one and one (1:1) system on patient care is unknown. In this same system, administration of morphine and transport by Basic Life Support (BLS) ambulance is encouraged as a method to improve ALS ambulance resource utilization. The aim of this study is to describe the impact of this system change on pain management. Methods: This study involved a retrospective analysis of quality improvement (QI) data gathered by the fire-based EMS agency on an ongoing basis. QI data referencing pain management was compared from the DM period (June 1, 2022, to May 31, 2023) to the 1:1 period (June 1, 2023, to May 31, 2024). Cases during the implementation of the 1:1 system (April 1, 2023, to May 30, 2024) were excluded. Key outcome measures included rates of ketamine and morphine administration, frequency of IV access and rate of ALS and BLS transports in reference to morphine administration. Statistical analysis was conducted to evaluate the association between system design change and outcomes. Statistical significance was set at p < 0.05. Results: There were 893 patients who received pain management during the DM period and 1054 during the 1:1 period. The median age / percent female was 62 years / 54% and 63 years / 54%. The frequency of ALS transports (Before: 51%, After: 51%; OR = 0.99 95% CI: 1.97, 0.51) did not change. Patients without an IV placed, despite complaints of pain, decreased from 35% to 28% (OR = 0.72, 95% CI: 0.88, 0.60). Patients who received only ketamine increased from 13% to 22% (OR = 1.94 95% CI: 2.48, 1.52), while patients the number of patients who received only morphine (Before: 50%, After: 48%; OR = 0.92, 95% CI: 1.09, 0.78) or morphine and ketamine (Before: 2%, After: 2%; OR = 1.01, 95% CI: 1.97, 0.51) showed no significant change. Among patients who received morphine, frequency of BLS transports increased from 38% to 52% (OR = 1.78 95% CI: 2.30, 1.39). Conclusion: In this single agency, the transition from a DM transport to the 1:1 system was associated with higher rates of IV insertion, increased use of ketamine and increased rates of BLS transport after morphine administration. All suggesting that the presence of a paramedic on every call allows for more aggressive pain management. Further research is necessary to determine if these single systems observations can be applied more broadly