Statistics and Probability Commons^™

Physician Remuneration Schemes, Psychiatric Hospitalizations And Follow-Up Care: Evidence From Blended Fee-For-Service And Capitation Models., Thyna Vu, Kelly K Anderson, Rose Anne Devlin, Nibene H Somé, Sisira Sarma

Epidemiology and Biostatistics Publications

Psychiatric hospitalizations could be reduced if mental illnesses were detected and treated earlier in the primary care setting, leading to the World Health Organization recommendation that mental health services be integrated into primary care. The mental health services provided in primary care settings may vary based on how physicians are incentivized. Little is known about the link between physician remuneration and psychiatric hospitalizations. We contribute to this literature by studying the relationship between physician remuneration and psychiatric hospitalizations in Canada's most populous province, Ontario. Specifically, we study family physicians (FPs) who switched from blended fee-for-service (FFS) to blended capitation remuneration …

Incorporating Animal Movement Into Distance Sampling, R. Glennie, S. T. Buckland, R. Langrock, Tim Gerrodette, Susan Chivers, M. D. Scott

United States Department of Commerce: Staff Publications

Distance sampling is a popular statistical method to estimate the density of wild animal populations. Conventional distance sampling represents animals as fixed points in space that are detected with an unknown probability that depends on the distance between the observer and the animal. Animal movement can cause substantial bias in density estimation. Methods to correct for responsive animal movement exist, but none account for nonresponsive movement independent of the observer. Here, an explicit animal movement model is incorporated into distance sampling, combining distance sampling survey data with animal telemetry data. Detection probability depends on the entire unobserved path the animal …

A Unified Approach For Constructing Confidence Intervals And Hypothesis Tests Using H-Function, Weizhen Wang

Mathematics and Statistics Faculty Publications

We introduce a general method, named the h-function method, to unify the constructions of level-a exact test and 1-a exact confidence interval. Using this method, any confidence interval is improved as follows: i) an approximate interval, including a point estimator, is modified to an exact interval; ii) an exact interval is refined to be an interval that is a subset of the previous one. Two real datasets are used to illustrate the method.

Count Data Time Series Models And Their Applications, Yi Zhang

Doctoral Dissertations

“Due to fast developments of advanced sensors, count data sets have become ubiquitous in many fields. Modeling and forecasting such time series have generated great interest. Modeling can shed light on the behavior of the count series and to see how they are related to other factors such as the environmental conditions under which the data are generated. In this research, three approaches to modeling such count data are proposed.

First, a periodic autoregressive conditional Poisson (PACP) model is proposed as a natural generalization of the autoregressive conditional Poisson (ACP) model. By allowing for cyclical variations in the parameters of …

Carbon Dioxide And Particulate Matter Concentration On Hampton Roads Air Quality, Gregory Hubbard

OUR Journal: ODU Undergraduate Research Journal

Hampton Roads has been a maritime crossroads for the last 400 years. Industrialization has impacted the coastal region for the last 250 years. The expansion of the Port of Virginia in 2019 has created dense traffic in the region resulting in impacts to air quality. Two waste products that affect humans are particulate matter and carbon dioxide. Both respective emissions can cause adverse effects on humans, such as asthma, some lung cancers, and other respiratory distress. Scientists and health practitioners are studying the effects of particulate matter on human health. Hampton Roads, in particular, because of its unique location on …

Maternal Proximity To Mountaintop Removal Mining And Birth Defects In Appalachian Kentucky, 1997-2003, Daniel B. Cooper

Theses and Dissertations--Public Health (M.P.H. & Dr.P.H.)

Background: Extraction of coal through mountaintop removal mining (MTR) alters many dimensions of the landscape, and explosive blasts, exposed rock, and coal washing have the potential to pollute air and water with substances known to increase risk of developmental and birth anomalies. Previous research suggests that infants born to mothers living in MTR coal mining counties have higher prevalence of most types of birth defects.

Objectives: This study seeks to examine further the relationship between MTR activity and birth defects by employing individual level exposure estimation through precise satellite data of MTR activity in the Appalachian region and maternal residence …

Is Technological Progress A Random Walk? Examining Data From Space Travel, Michael Howell, Daniel Berleant, Hyacinthe Aboudja, Richard Segall, Peng-Hung Tsai

Journal of the Arkansas Academy of Science

Improvement in a variety of technologies can often be successful modeled using a general version of Moore’s law (i.e. exponential improvements over time). Another successful approach is Wright’s law, which models increases in technological capability as a function of an effort variable such as production. While these methods are useful, they do not provide prediction distributions, which would enable a better understanding of forecast quality

Farmer and Lafond (2016) developed a forecasting method which produces forecast distributions and is applicable to many kinds of technology. A fundamental assumption of their method is that technological progress can be modeled as a …

Biofilm And Cell Adhesion Strength On Dental Implant Surfaces Via The Laser Spallation Technique, James D. Boyd, Arnold J. Stromberg, Craig S. Miller, Martha E. Grady

Statistics Faculty Publications

OBJECTIVE: The aims of this study are to quantify the adhesion strength differential between an oral bacterial biofilm and an osteoblast-like cell monolayer to a dental implant-simulant surface and develop a metric that quantifies the biocompatible effect of implant surfaces on bacterial and cell adhesion.

METHODS: High-amplitude short-duration stress waves generated by laser pulse absorption are used to spall bacteria and cells from titanium substrates. By carefully controlling laser fluence and calibration of laser fluence with applied stress, the adhesion difference between Streptococcus mutans biofilms and MG 63 osteoblast-like cell monolayers on smooth and rough titanium substrates is obtained. The …

Fourth Down Decision Making: Challenging The Conservative Nature Of Nfl Coaches, Will Palmquist, Ryan Elmore, Benjamin Williams

DU Undergraduate Research Journal Archive

This thesis analyzes the hypothesis that coaches in the National Football League are often too conservative in their decision making on fourth downs. I used R Studio and NFL play-by-play data to simulate actual football plays and drives according to different fourth down strategies. By measuring expected points per drive over thousands of simulated drives, we are able to evaluate the effectiveness of different fourth down strategies. This research points to a number of conclusions regarding the nature of NFL coaches on fourth downs as well as the complexity of modeling and simulating decision making in a complex sport such …

Statistical Approaches For Estimation And Comparison Of Brain Functional Connectivity, Jifang Zhao

Theses and Dissertations

Drug addiction can lead to many health-related problems and social concerns. Functional connectivity obtained from functional magnetic resonance imaging (fMRI) data promotes a variety of fundamental understandings in such association. Due to its complex correlation structure and large dimensionality, the modeling and analysis of the functional connectivity from neuroimage are challenging. By proposing a spatio-temporal model for multi-subject neuroimage data, we incorporate voxel-level spatio-temporal dependencies of whole-brain measurements to improve the accuracy of statistical inference. To tackle large-scale spatio-temporal neuroimage data, we develop a computationally efficient algorithm to estimate the parameters. Our method is used to identify functional connectivity and …

Investigations Into The Genetics Of Mixed Pathologies In Dementia, Adam Dugan

Theses and Dissertations--Epidemiology and Biostatistics

Alzheimer’s disease (AD) is an irreversible, progressive brain disorder that leads to a loss of memory and thinking skills. While tremendous progress has been made in our understanding of the genetics underlying AD, currently known genetic variants explain only approximately 30% of the heritable risk of developing AD. One hurdle to AD research is that it can only be definitively diagnosed at autopsy, making cruder, clinic-based diagnoses more common. In recent years, several brain pathologies that mimic AD’s clinical presentation have been identified including brain arteriolosclerosis, hippocampal sclerosis (HS), and, most recently, limbic-predominant age-related TDP-43 encephalopathy (LATE). It has become …

A Glm Approach To Decomposing Wage Differential: Evidence From The Psid., Kassahun Mamo Geleta

Graduate Research Theses & Dissertations

The persistent gender wage differential, though declining through time, is the source of motivation to study the subject.A notable method to deal with the disparity is Oaxaca Blinder decomposition in combination with OLS estimation. This study follows a different approach that does not require the normality assumption and the log transformation of the wage variable. The study employs a generalized linear model (GLM) approach to estimate determinants of wage (measured in level) and combines the results with the Oaxaca Blinder decomposition method. The latter method quantifies the proportion of the wage gap which emanates from characteristics difference between men and …

Coloring Permutation-Gain Graphs, Daniel Slilaty

Mathematics and Statistics Faculty Publications

Correspondence colorings of graphs were introduced in 2018by Dvoˇr ́ak and Postle as a generalization of list colorings of graphswhich generalizes ordinary graph coloring. Kim and Ozeki observed thatcorrespondence colorings generalize various notions of signed-graph col-orings which again generalizes ordinary graph colorings. In this notewe state how correspondence colorings generalize Zaslavsky’s notionof gain-graph colorings and then formulate a new coloring theory ofpermutation-gain graphs that sits between gain-graph coloring and cor-respondence colorings. Like Zaslavsky’s gain-graph coloring, our newnotion of coloring permutation-gain graphs has well defined chromaticpolynomials and lifts to colorings of the regular covering graph of apermutation-gain graph

Physical Activity, Dietary Patterns, And Glycemic Management Of Active Individuals With Type 1 Diabetes: An Online Survey, Sheri Colberg, Jihan Kannane, Norou Diawara

Human Movement Studies & Special Education Faculty Publications

Individuals with type 1 diabetes (T1D) are able to balance their blood glucose levels while engaging in a wide variety of physical activities and sports. However, insulin use forces them to contend with many daily training and performance challenges involved with fine-tuning medication dosing, physical activity levels, and dietary patterns to optimize their participation and performance. The aim of this study was to ascertain which variables related to the diabetes management of physically active individuals with T1D have the greatest impact on overall blood glucose levels (reported as A1C) in a real-world setting. A total of 220 individuals with T1D …

The Impact Of Covid-19 On Volunteering:Results Of A Survey Of Maine Non-Profits, Sarah Goan

Publications

In response to the disruptions caused by the COVID-19 pandemic, particularly within the nonprofit sector that relies heavily on volunteers, Volunteer Maine sought to assess how volunteer capacity had been affected and what types of support organizations needed to rebuild. To accomplish this, the organization partnered with DIP and SRC to design and administer a statewide survey of nonprofit organizations. The purpose of the study was to understand the pandemic’s impact on the volunteer base, document organizational adjustments to changing conditions, identify innovative responses, and determine how Volunteer Maine and its affiliates could best assist in community recovery efforts. The …

Satellite-Based Phenology Analysis In Evaluating The Response Of Puerto Rico And The United States Virgin Islands' Tropical Forests To The 2017 Hurricanes, Melissa Collin

Cal Poly Humboldt theses and projects

The functionality of tropical forest ecosystems and their productivity is highly related to the timing of phenological events. Understanding forest responses to major climate events is crucial for predicting the potential impacts of climate change. This research utilized Landsat satellite data and ground-based Forest Inventory and Analysis (FIA) plot data to investigate the dynamics of Puerto Rico and the U.S. Virgin Islands’ (PRVI) tropical forests after two major hurricanes in 2017. Analyzing these two datasets allowed for validation of the remote sensing methodology with field data and for the investigation of whether this is an appropriate approach for estimating forest …

การพยากรณ์ปริมาณน้ำฝนระยะสั้นในบริเวณพื้นที่สนามบินสุวรรณภูมิด้วยโครงข่ายระบบประสาทแบบย้อนกลับ, รักษ์คณา ภูสีเขียว

Chulalongkorn University Theses and Dissertations (Chula ETD)

ปริมาณน้ำฝนนับเป็นปัจจัยสำคัญอย่างหนึ่งที่มีผลต่อการดำเนินชีวิตของมนุษย์ การพยากรณ์ปริมาณน้ำฝนที่มีความแม่นยำช่วยให้มนุษย์เตรียมพร้อมสำหรับกิจกรรมต่างๆ ที่จะเกิดขึ้นในอนาคตได้ดี อย่างไรก็ตามในบางสถานการณ์ความพร้อมใช้งานของข้อมูลสภาพอากาศมีจำกัด ทำให้การพยากรณ์ปริมาณน้ำฝนอย่างแม่นยำนั้นเป็นเรื่องที่ยาก ปัจจุบันหลายๆ งานวิจัยที่เกี่ยวข้องได้เลือกโครงข่ายประสาทเทียมเชิงลึกเป็นอัลกอริทึมในการฝึกแบบจำลองเพื่อใช้ในการพยากรณ์ แนวคิดหลักคือการสร้างตัวแปรคุณลักษณะ (Feature) ที่เกี่ยวข้องในระดับสถาปัตยกรรม จากหลักการนี้สถาปัตยกรรมโครงข่ายประสาทเทียมเชิงลึกที่เหมาะสมสามารถผสมผสานและจับคู่คุณลักษณะที่เกี่ยวข้องในการพยากรณ์ได้อย่างเหมาะสม ผลที่ตามมางานวิจัยที่มีอยู่ส่วนใหญ่จึงมุ่งเน้นไปที่เทคนิคบางอย่างเพื่อปรับปรุงประสิทธิภาพของแบบจำลองโดยไม่ได้ให้ความสำคัญกับการเพิ่มคุณลักษณะให้กับตัวแบบมากนัก อย่างไรก็ตามเมื่อข้อมูลการฝึกฝนมีจำนวนจำกัดโครงข่ายประสาทเทียมเชิงลึกอาจจะทำงานได้ไม่เต็มประสิทธิภาพมากนัก ทำให้การผสมผสานและจับคู่คุณลักษณะที่เกี่ยวข้องในการพยากรณ์ทำได้ไม่ดีตามไปด้วย สิ่งนี้ทำให้เกิดคำถามงานวิจัยว่าแบบจำลองการพยากรณ์ปริมาณน้ำฝนที่ได้ถูกนำเสนอมีประสิทธิภาพที่ดีเพียงพอหรือไม่ เมื่อไม่ได้มีการเพิ่มคุณสมบัติที่เกี่ยวข้องให้กับแบบจำลอง งานวิจัยนี้จึงมีวัตถุประสงค์เพื่อพัฒนาและเปรียบเทียบประสิทธิภาพของแบบจำลองต่างๆ ในการพยากรณ์ปริมาณน้ำฝนสะสมในระยะสั้นที่มีและไม่มีการเพิ่มตัวแปรคุณสมบัติที่เกี่ยวข้อง โดยได้แบ่งการทดลองออกเป็น 2 ส่วนเพื่อวัดประสิทธิภาพ คือ 1) การเปรียบเทียบประสิทธิภาพของตัวแบบที่มีการเพิ่มตัวแปรคุณลักษณะที่เกี่ยวข้องว่ามีความถูกต้องแม่นยำดีขึ้นหรือไม่เมื่อเทียบกับแบบจำลองที่ไม่ได้มีการเพิ่มตัวแปรคุณลักษณะในสภาพแวดล้อมที่เทียบเท่ากัน และ 2) การเปรียบเทียบประสิทธิภาพในการพยากรณ์ปริมาณน้ำฝนสะสมของแบบจำลองที่สนใจศึกษา ได้แก่ ARIMA ARIMAX RNN LSTM และ GRU ข้อมูลที่นำมาใช้ในงานวิจัยนี้เป็นข้อมูลสภาพอากาศและปริมาณน้ำฝนสะสมที่รวบรวบมาจากพื้นที่สนามบินสุวรรณภูมิ จากผลการศึกษาทั้ง 2 ส่วนพบว่าการเพิ่มตัวแปรคุณลักษณะสามารถเพิ่มประสิทธิภาพการพยากรณ์ให้กับตัวแบบได้ในกรณีที่ข้อมูลที่นำมาฝึกฝนตัวแบบมีจำนวนจำกัด โดย แบบจำลอง GRU ให้ประสิทธิภาพในการพยากรณ์มากที่สุด

Topics In Design And Analysis Of Experiments: Calibration, Sequential Experimentation, And Model Selection, Christine Miller

Theses and Dissertations

Experiments are widely used across multiple disciplines to uncover information about a system or processes. Experimental design is a statistical technique devoted to the methodology of selecting the appropriate samples to aid in the subsequent analysis. We research three open problems in experimental designs regarding calibration, sequential experimentation, and model selection. First, we focus on calibration; the impact of experimental design choice on the performance of statistical calibration is largely unknown. We investigate the performance of several experimental designs with regards to inverse prediction via a comprehensive simulation study. Specifically, we compare several design types including traditional response surface designs, …

การทดสอบประสิทธิภาพการแบ่งข้อมูลตัวแปรเดียวด้วยการใช้การแบ่งช่วงธรรมชาติเจงค์แบบซ้ำ, วิชญ์ยุตม์ สุขแพทย์

Chulalongkorn University Theses and Dissertations (Chula ETD)

การแบ่งช่วงธรรมชาติเจงค์เป็นวิธีการจัดกลุ่มข้อมูลที่ได้รับความนิยม งานวิจัยนี้ได้นำการแบ่งช่วงธรรมชาติเจงค์มาปรับใช้ด้วยการเพิ่มจำนวนกลุ่มที่ใช้แบ่งเรื่อย ๆ จนกว่าจุดแบ่งแรกของการแบ่งช่วงธรรมชาติเจงค์จะเปลี่ยนแปลงไปน้อยกว่าค่าร้อยละที่กำหนดและใช้จุดแบ่งแรกนั้นในการแบ่งข้อมูลออกเป็น 2 กลุ่ม จากการทดสอบประสิทธิภาพด้วยการจำลองข้อมูลตัวแปรเดียวที่มีการแจกแจงในรูปแบบการแจกแจงปกติแบบผสมและการแจกแจงล็อกปกติแบบผสม 2 กลุ่มและเปรียบเทียบกับวิธีการแบ่งกลุ่มข้อมูลอื่น ๆ พบว่าการแบ่งช่วงธรรมชาติเจงค์แบบซ้ำนั้นไม่มีประสิทธิภาพในการแบ่งข้อมูลแจกแจงปกติแบบผสมเมื่อต้องการให้ได้ความแม่นยำสูงสุด และเหมาะสมกับการใช้ในข้อมูลแจกแจงล็อกปกติแบบผสมเมื่อข้อมูล 2 กลุ่มมีจำนวนใกล้เคียงกันหรือกลุ่มที่ค่าเฉลี่ยสูงกว่ามีจำนวนมากกว่า นอกจากนี้การแบ่งช่วงธรรมชาติเจงค์แบบซ้ำใช้เวลาในการแบ่งกลุ่มกว่าวิธีอื่นมาก จึงไม่เหมาะสมที่จะนำมาใช้หากข้อมูลมีจำนวนมาก

Comparison Of Software Packages For Detecting Differentially Expressed Genes From Single-Sample Rna-Seq Data, Rong Zhou

Electronic Theses and Dissertations

RNA-sequencing (RNA-seq) has rapidly become the tool in many genome-wide transcriptomic studies. It provides a way to understand the RNA environment of cells in different physiological or pathological states to determine how cells respond to these changes. RNA-seq provides quantitative information about the abundance of different RNA species present in a given sample. If the difference or change observed in the read counts or expression level between two experimental conditions is statistically significant, the gene is declared as differentially expressed. A large number of methods for detecting differentially expressed genes (DEGs) with RNA-seq have been developed, such as the methods …

Development Of A Probabilistic Multi-Class Model Selection Algorithm For High-Dimensional And Complex Data, Madeline Anne Ausdemore

Electronic Theses and Dissertations

The development of quantifiable measures of uncertainty in forensic conclusions has resulted in the debut of several ad-hoc methods for approximating the weight of evidence (WoE). In particular, forensic researchers have attempted to use similarity measures, or scores, to approximate the weight of evidence characterized by highdimensional and complex data. Score-based methods have been proposed to approximate theWoE for numerous evidence types (e.g., fingerprints, handwriting, inks, voice analysis). In general, scorebased methods consider the score as a projection onto the real line. For example, the score-based likelihood ratio evaluates and compares the likelihoods of a score calculated between two objects …

Predictability Of Missing Data Theory To Improve U.S. Estimator’S Unreliable Data Problem, Tomeka S. Williams

Walden Dissertations and Doctoral Studies

Since the topic of improving data quality has not been addressed for the U.S. defense cost estimating discipline beyond changes in public policy, the goal of the study was to close this gap and provide empirical evidence that supports expanding options to improve software cost estimation data matrices for U.S. defense cost estimators. The purpose of this quantitative study was to test and measure the level of predictive accuracy of missing data theory techniques that were referenced as traditional approaches in the literature, compare each theories’ results to a complete data matrix used in support of the U.S. defense cost …

Assessing And Forecasting Chlorophyll Abundances In Minnesota Lake Using Remote Sensing And Statistical Approaches, Ben Von Korff

All Graduate Theses, Dissertations, and Other Capstone Projects

Harmful algae blooms (HABs) can negatively impact water quality, lake aesthetics, and can harm human and animal health. However, monitoring for HABs is rare in Minnesota. Detecting blooms which can vary spatially and may only be present briefly is challenging, so expanding monitoring in Minnesota would require the use of new and cost efficient technologies. Unmanned aerial vehicles (UAVs) were used for bloom mapping using RGB and near-infrared imagery. Real time monitoring was conducted in Bass Lake, in Faribault County, MN using trail cameras. Time series forecasting was conducted with high frequency chlorophyll-a data from a water quality sonde. Normalized …

Design And Analyses Of School-Based Violence Prevention Cluster Randomized Trials, Md. Tofial Azam

Theses and Dissertations--Epidemiology and Biostatistics

Interpersonal violence such as teen dating violence is a severe public health problem. Teen dating violence, including sexual violence (unwanted sexual contacts or activities), physical and psychological dating violence, sexual harassment, and stalking, affects high school students' physical and mental health and academic achievement in the United States. Dating violence is linked to psychological abuse perpetration in the future, depression, anxiety, and hostility. The teen dating violence victimization experience was related to antisocial behavior, drug abuse, increased heavy drinking, depression, suicidal ideation, smoking, and adult interpersonal violence victimization during adolescence. The detrimental effects of interpersonal violence demonstrate the critical importance …

Finite Mixture Models : Applications To Length Of Stay For Delivery Hospitalizations, Eva Williford

Legacy Theses & Dissertations (2009 - 2024)

In the United States (U.S.), childbirth is the most common reason for hospitalization, and the maternal mortality rate per 100,000 (2017-2018) is markedly elevated in the U.S. (17.4) compared to neighboring Canada (10), the United Kingdom (7), and Japan (5) (Trends in Maternal Mortality, 2000 to 2017: Estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division). These data, the increased focus on addressing severe maternal morbidity and mortality to improve patient outcomes and reduce healthcare costs is well deserved. These women often have a longer delivery length of stay (LOS) and experience complications of varying …

Evaluating The Incidence Of Melanoma And Lung Cancer Of Current And Former Active-Duty U.S. Military Who Were Deployed In Support Of Operation Enduring Freedom And Operation Iraqi Freedom, Brian Kovacic

Theses and Dissertations--Epidemiology and Biostatistics

The incidence of melanoma and lung cancer has been gradually increasing in the United States over the past three decades with the reputed causes due to etiological and environmental exposures, and tobacco usage. There has been concern that melanoma and lung cancer incidence among military personnel may be associated with deployment to environments with intense sun exposure and increased smoking rates due to post-traumatic stress disorder. The aim of this study was to examine associations between deployment in support of Operation Enduring Freedom (OEF) or Operation Iraqi Freedom (OIF), from 2001 through 2015, with subsequent melanoma and lung cancer incidence. …

Sexual Behaviors Associated With Online Partner-Seeking Among Men Who Have Sex With Men From Small/Midsized Towns Or Rural Areas In Kentucky, Vira Pravosud

Theses and Dissertations--Epidemiology and Biostatistics

The HIV epidemic remains one of the most significant public health issues in the United States, particularly among men who have sex with men (MSM). New avenues for partner-seeking have emerged over the past three decades, including through the Internet, social media, and geosocial networking applications. Consisting of three cross-sectional studies, this dissertation research aimed to determine associations between the use of various online tools for partner-seeking (hereafter collectively referred to as “apps”) and HIV-related sexual behaviors among 252 young adult MSM residing in small/midsized towns or rural areas in Central Kentucky, a group that has been under-represented in the …

Parametric, Nonparametric, And Semiparametric Linear Regression In Classical And Bayesian Statistical Quality Control, Chelsea L. Jones

Theses and Dissertations

Statistical process control (SPC) is used in many fields to understand and monitor desired processes, such as manufacturing, public health, and network traffic. SPC is categorized into two phases; in Phase I historical data is used to inform parameter estimates for a statistical model and Phase II implements this statistical model to monitor a live ongoing process. Within both phases, profile monitoring is a method to understand the functional relationship between response and explanatory variables by estimating and tracking its parameters. In profile monitoring, control charts are often used as graphical tools to visually observe process behaviors. We construct a …

Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman

Pitzer Senior Theses

This thesis investigates the unique interactions between pregnancy, substance involvement, and race as they relate to the War on Drugs and the hyper-incarceration of women. Using ordinary least square regression analyses and data from the Bureau of Justice Statistics’ 2016 Survey of Prison Inmates, I examine if (and how) pregnancy status, drug use, race, and their interactions influence two length of incarceration outcomes: sentence length and amount of time spent in jail between arrest and imprisonment. The results collectively indicate that pregnancy decreases length of incarceration outcomes for those offenders who are not substance-involved but not evenhandedly -- benefitting white …

A Deep Learning Model To Predict Traumatic Brain Injury Severity And Outcome From Mr Images, Dacosta Yeboah, Hung Nguyen, Daniel B. Hier, Gayla R. Olbricht, Tayo Obafemi-Ajayi

Chemistry Faculty Research & Creative Works

For Many Neurological Disorders, Including Traumatic Brain Injury (TBI), Neuroimaging Information Plays a Crucial Role Determining Diagnosis and Prognosis. TBI is a Heterogeneous Disorder that Can Result in Lasting Physical, Emotional and Cognitive Impairments. Magnetic Resonance Imaging (MRI) is a Non-Invasive Technique that Uses Radio Waves to Reveal Fine Details of Brain Anatomy and Pathology. Although MRIs Are Interpreted by Radiologists, Advances Are Being Made in the Use of Deep Learning for MRI Interpretation. This Work Evaluates a Deep Learning Model based on a Residual Learning Convolutional Neural Network that Predicts TBI Severity from MR Images. the Model Achieved a …