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Experiences Of Parents With Opioid Use Disorder During Their Attempts To Seek Treatment: A Qualitative Analysis, Christine Bakos-Block, Angela J Nash, A Sarah Cohen, Tiffany Champagne-Langabeer 2022 The Texas Medical Center Library

Experiences Of Parents With Opioid Use Disorder During Their Attempts To Seek Treatment: A Qualitative Analysis, Christine Bakos-Block, Angela J Nash, A Sarah Cohen, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

In the U.S., 12.3% of children live with at least one parent who has a substance use disorder. Prior research has shown that men are more likely to seek treatment than women and that the barriers are different; however, there is limited research focusing specifically on opioid use disorder (OUD). We sought to understand the barriers and motivators for parents with OUD. We conducted a qualitative study by interviewing parents with OUD who were part of an outpatient treatment program. Interviews followed a semi-structured format with questions on access to and motivation for treatment. The interviews were recorded and transcribed …


Investigating Applications Of Deep Learning For Diagnosis Of Post Traumatic Elbow Disease, Hugh James 2022 Washington University in St. Louis

Investigating Applications Of Deep Learning For Diagnosis Of Post Traumatic Elbow Disease, Hugh James

McKelvey School of Engineering Graduate Student Theses & Dissertations

Traumatic events such as dislocation, breaks, and arthritis of musculoskeletal joints can cause the development of post-traumatic joint contracture (PTJC). Clinically, noninvasive techniques such as Magnetic Resonance Imaging (MRI) scans are used to analyze the disease. Such procedures require a patient to sit sedentary for long periods of time and can be expensive as well. Additionally, years of practice and experience are required for clinicians to accurately recognize the diseased anterior capsule region and make an accurate diagnosis. Manual tracing of the anterior capsule is done to help with diagnosis but is subjective and timely. As a result, there is …


Effect Of Temperature Cycling Pretreatment On The Thermal Stability Of Sm2(Co, Fe, Zr, Cu)17 Magnets In The Mild Temperature Range, Hulin Wu, Zhimei Long, Zhongsheng Li, Kaiqiang Song, Chaoqun Li, Dalong Cong, Bin Shao, Xiaowei Liu, Jianchun Sun, Yilong Ma 2022 The Texas Medical Center Library

Effect Of Temperature Cycling Pretreatment On The Thermal Stability Of Sm2(Co, Fe, Zr, Cu)17 Magnets In The Mild Temperature Range, Hulin Wu, Zhimei Long, Zhongsheng Li, Kaiqiang Song, Chaoqun Li, Dalong Cong, Bin Shao, Xiaowei Liu, Jianchun Sun, Yilong Ma

Faculty, Staff and Student Publications

The irredeemable magnetic losses of Sm(Co, Fe, Zr, Cu)7.8 permanent magnets caused by oxidation are very important for their practical application. In this work, the simulated results with R2 ≥ 98% based on the data of the temperature cycling test and the long-term isothermal test for the original samples confirmed that the magnetic flux losses reached 9.38% after the 5000th cycle in range R.T.–300 °C, and 7.15% after oxidated at 180 °C for 10 years, respectively. Demagnetization curves showed that the low-temperature oxidation mainly led to the remanence attenuation, while the coercivity remained relatively stable. SEM observation and EDS …


High-Frequency Ultrasound In Patients With Seronegative Rheumatoid Arthritis, Junkui Wang, Miao Wang, Qinghua Qi, Zhibin Wu, Jianguo Wen 2022 The Texas Medical Center Library

High-Frequency Ultrasound In Patients With Seronegative Rheumatoid Arthritis, Junkui Wang, Miao Wang, Qinghua Qi, Zhibin Wu, Jianguo Wen

Faculty, Staff and Student Publications

This study aimed to investigate the value of high-frequency ultrasound (HFUS) in differentiation of the seronegative rheumatoid arthritis (SNRA) and osteoarthritis (OA) and in the diagnosis of SNRA. 83 patients diagnosed with SNRA (SNRA group) and 40 diagnosed with OA (OA group) who received HFUS were retrospectively analyzed. The grayscale (GS) scores, power Doppler (PD) scores, and bone erosion (BE)scores were recorded, and added up to calculate the total scores of US variables. The correlations of the total scores of US variables with the 28-joint disease activity score (DAS28), erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were analyzed. The …


Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss 2022 Nova Southeastern University

Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss

All HCAS Student Capstones, Theses, and Dissertations

Trait-based ecology characterizes individuals’ functional attributes to better understand and predict their interactions with other species and their environments. Utilizing morphological traits to describe functional groups has helped group species with similar ecological niches that are not necessarily taxonomically related. Within the deep-pelagic fishes, the Order Stomiiformes exhibits high morphological and species diversity, and many species undertake diel vertical migration (DVM). While the morphology and behavior of stomiiform fishes have been extensively studied and described through taxonomic assessments, the connection between their form and function regarding their DVM types, morphotypes, and daytime depth distributions is not well known. Here, three …


Transfer Of Personality Through Text Style, Michael O'Mahony, Robert Ross 2022 Technological University Dublin

Transfer Of Personality Through Text Style, Michael O'Mahony, Robert Ross

Other resources

The style of generated text is how something is said rather than what is said. We hypothesize that changing the style of generated text can change the perceived personality of the text generation agent. Dialogue systems that aim to imitate a human agent can appear to have a consistent personality through a consistent, controllable style of conversation. Some recent work on the style of generated text [1] performs impressively in the small number of domains selected for their experiments using transformer and LSTM-based models. Lin et al. [1] used weak supervised learning as their data set lacks parallel data. The …


A Maturity Model Of Data Modeling In Self-Service Business Intelligence Software, Anna Kurenkov 2022 Kennesaw State University

A Maturity Model Of Data Modeling In Self-Service Business Intelligence Software, Anna Kurenkov

Master of Science in Information Technology Theses

Although Self-Service Business Intelligence (SSBI) is continually being adopted in various industries, there is a lack of research focused on data modeling in SSBI. This research aims to fill that research gap and propose a maturity model for SSBI data modeling which is generalizeable between different software and applicable for users of all technical backgrounds. Through extensive literature review, a five-tier maturity model was proposed, explained, and instantiated in PowerBI and Tableau. The testing of the model was found to be simple and intuitive, and the research concludes that the model is applicable to enterprise SSBI environments. This research is …


Open-Source Benchmarking Of Ibd Segment Detection Methods For Biobank-Scale Cohorts, Kecong Tang, Ardalan Naseri, Yuan Wei, Shaojie Zhang, Degui Zhi 2022 The Texas Medical Center Library

Open-Source Benchmarking Of Ibd Segment Detection Methods For Biobank-Scale Cohorts, Kecong Tang, Ardalan Naseri, Yuan Wei, Shaojie Zhang, Degui Zhi

Faculty, Staff and Student Publications

In the recent biobank era of genetics, the problem of identical-by-descent (IBD) segment detection received renewed interest, as IBD segments in large cohorts offer unprecedented opportunities in the study of population and genealogical history, as well as genetic association of long haplotypes. While a new generation of efficient methods for IBD segment detection becomes available, direct comparison of these methods is difficult: existing benchmarks were often evaluated in different datasets, with some not openly accessible; methods benchmarked were run under suboptimal parameters; and benchmark performance metrics were not defined consistently. Here, we developed a comprehensive and completely open-source evaluation of …


Industry 4.0, Zachary Zeitler 2022 Western Michigan University

Industry 4.0, Zachary Zeitler

Honors Theses

The ultimate goal of this project is to automate quality control processes on various machines which include 3D printers, welders, routers, CNCs, and more. Using the “Digital Twin” approach, we want to automate monitoring, data collection, data analysis, and corrective action. Our involvement begins with building a new piece of software that can perform two specific functions and collect data from cameras. We are not attempting to analyze the data, make corrective action, or design a final version of the physical attributes. Our software provides the user with the ability to capture an image set or a 3D scan and …


Critically Observing The Challenges And Changes: An Analysis On Covid-19’S Impact With An Emphasis On Students In Higher Education, Landon Perkins 2022 University of Mississippi

Critically Observing The Challenges And Changes: An Analysis On Covid-19’S Impact With An Emphasis On Students In Higher Education, Landon Perkins

Honors Theses

This project involves comparing different visualizations related to COVID-19 and higher education in order to determine key impacts of the COVID-19 pandemic on students in higher education, as well as higher education as a whole. The main metrics used to determine the impact were mental health indicators for anxiety or depressive disorders, enrollment numbers by control type (public, private non-profit, or private for-profit) and state for 2020 and 2021, and state mandate lift dates for a variety of mandates implemented across the United States. These metrics were analyzed both individually and against each other to determine if they had any …


The Interaction Of Normalisation And Clustering In Sub-Domain Definition For Multi-Source Transfer Learning Based Time Series Anomaly Detection, Matthew Nicholson, Rahul Agrahari, Clare Conran, Haythem Assem, John D. Kelleher 2022 ADAPT Centre, Trinity College Dublin

The Interaction Of Normalisation And Clustering In Sub-Domain Definition For Multi-Source Transfer Learning Based Time Series Anomaly Detection, Matthew Nicholson, Rahul Agrahari, Clare Conran, Haythem Assem, John D. Kelleher

Articles

This paper examines how data normalisation and clustering interact in the definition of sub-domains within multi-source transfer learning systems for time series anomaly detection. The paper introduces a distinction between (i) clustering as a primary/direct method for anomaly detection, and (ii) clustering as a method for identifying sub-domains within the source or target datasets. Reporting the results of three sets of experiments, we find that normalisation after feature extraction and before clustering results in the best performance for anomaly detection. Interestingly, we find that in the multi-source transfer learning scenario clustering on the target dataset and identifying subdomains in the …


Artificial Intelligence In The Medical Field: Medical Review Sentiment Analysis, Nicholas Podlesak 2022 Northern Illinois University

Artificial Intelligence In The Medical Field: Medical Review Sentiment Analysis, Nicholas Podlesak

Honors Capstones

In this research project, natural language processing techniques’ ability to accurately classify medical text was measured to reinforce the relevance of artificial intelligence in the medical field. Sentiment analyses (analyses to determine whether the text was positive or negative) were performed on the prescription drug reviews in an open-source dataset using four different models: lexical, a neural network, a support vector machine, and a logistic regression model. Each model’s effectiveness was gauged by its ability to correctly classify unlabeled drug reviews (i.e., a percentage representing accuracy). The machine learning models were able to accurately classify the text, while the lexical …


Safe Sharing For Sensitive Data, Kristi Thompson 2022 Western University

Safe Sharing For Sensitive Data, Kristi Thompson

Western Libraries Presentations

This workshop focused on the question of when and how human subjects' data can be safely shared. It introduced the basics of data anonymization and discussed how to tell if a dataset has been de-identified. Case studies of successful anonymization and some spectacular failures were shared


From Computer Curriculum That Works For The Use Of Computer Intellignece Computer Science, Malachi B. Bacchus 2022 CUNY New York City College of Technology

From Computer Curriculum That Works For The Use Of Computer Intellignece Computer Science, Malachi B. Bacchus

Publications and Research

Computer interconnection can link different networks by using electrical artificial flow ways that can travel through different connections. these are called data network which travels through different sectors of the network simulation of service computer network using artificial intelligence to enhanced further understanding the computations, I've also demonstrated knowing by using the network to get better understanding of how ethical computing can be learned through universities and collegiate that can help established knowledge and healthy computer information. The main tools for the research are using data networking, ethical learning and translation towards different computer systems.


Identity Term Sampling For Measuring Gender Bias In Training Data, Nasim Sobhani, Sarah Jane Delany 2022 Technological University Dublin

Identity Term Sampling For Measuring Gender Bias In Training Data, Nasim Sobhani, Sarah Jane Delany

Conference Papers

Predictions from machine learning models can reflect biases in the data on which they are trained. Gender bias has been identified in natural language processing systems such as those used for recruitment. The development of approaches to mitigate gender bias in training data typically need to be able to isolate the effect of gender on the output to see the impact of gender. While it is possible to isolate and identify gender for some types of training data, e.g. CVs in recruitment, for most textual corpora there is no obvious gender label. This paper proposes a general approach to measure …


Denoising And Deconvolving Sperm Whale Data In The Northern Gulf Of Mexico Using Fourier And Wavelet Techniques, Kendal McCain Leftwich 2022 University of New Orleans, New Orleans

Denoising And Deconvolving Sperm Whale Data In The Northern Gulf Of Mexico Using Fourier And Wavelet Techniques, Kendal Mccain Leftwich

LSU New Orleans Theses and Dissertations

The use of underwater acoustics can be an important component in obtaining information from the oceans of the world. It is desirable (but difficult) to compile an acoustic catalog of sounds emitted by various underwater objects to complement optical catalogs. For example, the current visual catalog for whale tail flukes of large marine mammals (whales) can identify even individual whales from their individual fluke characteristics. However, since sperm whales, Physeter microcephalus, do not fluke up when they dive, they cannot be identified in this manner. A corresponding acoustic catalog for sperm whale clicks could be compiled to identify individual …


The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Naglah 2022 University of Louisville

The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Naglah

Electronic Theses and Dissertations

Computational technologies can contribute to the modeling and simulation of the biological environments and activities towards achieving better interpretations, analysis, and understanding. With the emergence of digital pathology, we can observe an increasing demand for more innovative, effective, and efficient computational models. Under the umbrella of artificial intelligence, deep learning mimics the brain’s way in learn complex relationships through data and experiences. In the field of bioimage analysis, models usually comprise discriminative approaches such as classification and segmentation tasks. In this thesis, we study how we can use generative AI models to improve bioimage analysis tasks using Generative Adversarial Networks …


A Multistate Competing Risks Framework For Preconception Prediction Of Pregnancy Outcomes, Kaitlyn Cook, Neil J. Perkins, Enrique Schisterman, Sebastien Haneuse 2022 Harvard Pilgrim Health Care Institute

A Multistate Competing Risks Framework For Preconception Prediction Of Pregnancy Outcomes, Kaitlyn Cook, Neil J. Perkins, Enrique Schisterman, Sebastien Haneuse

Statistical and Data Sciences: Faculty Publications

Background: Preconception pregnancy risk profiles—characterizing the likelihood that a pregnancy attempt results in a full-term birth, preterm birth, clinical pregnancy loss, or failure to conceive—can provide critical information during the early stages of a pregnancy attempt, when obstetricians are best positioned to intervene to improve the chances of successful conception and full-term live birth. Yet the task of constructing and validating risk assessment tools for this earlier intervention window is complicated by several statistical features: the final outcome of the pregnancy attempt is multinomial in nature, and it summarizes the results of two intermediate stages, conception and gestation, whose outcomes …


A Systematic Approach To Configuring Metamap For Optimal Performance, Xia Jing, Akash Indani, Nina Hubig, Hua Min, Yang Gong, James J Cimino, Dean F Sittig, Lior Rennert, David Robinson, Paul Biondich, Adam Wright, Christian Nøhr, Timothy Law, Arild Faxvaag, Ronald Gimbel 2022 The Texas Medical Center Library

A Systematic Approach To Configuring Metamap For Optimal Performance, Xia Jing, Akash Indani, Nina Hubig, Hua Min, Yang Gong, James J Cimino, Dean F Sittig, Lior Rennert, David Robinson, Paul Biondich, Adam Wright, Christian Nøhr, Timothy Law, Arild Faxvaag, Ronald Gimbel

Faculty, Staff and Student Publications

BACKGROUND: MetaMap is a valuable tool for processing biomedical texts to identify concepts. Although MetaMap is highly configurative, configuration decisions are not straightforward.

OBJECTIVE: To develop a systematic, data-driven methodology for configuring MetaMap for optimal performance.

METHODS: MetaMap, the word2vec model, and the phrase model were used to build a pipeline. For unsupervised training, the phrase and word2vec models used abstracts related to clinical decision support as input. During testing, MetaMap was configured with the default option, one behavior option, and two behavior options. For each configuration, cosine and soft cosine similarity scores between identified entities and gold-standard terms were …


Intraoperative Localization And Preservation Of Reading In Ventral Occipitotemporal Cortex, Oscar Woolnough, Kathryn M Snyder, Cale W Morse, Meredith J McCarty, Samden D Lhatoo, Nitin Tandon 2022 The Texas Medical Center Library

Intraoperative Localization And Preservation Of Reading In Ventral Occipitotemporal Cortex, Oscar Woolnough, Kathryn M Snyder, Cale W Morse, Meredith J Mccarty, Samden D Lhatoo, Nitin Tandon

Faculty, Staff and Student Publications

OBJECTIVE: Resective surgery in language-dominant ventral occipitotemporal cortex (vOTC) carries the risk of causing impairment to reading. Because it is not on the lateral surface, it is not easily accessible for intraoperative mapping, and extensive stimulation mapping can be time-consuming. Here the authors assess the feasibility of using task-based electrocorticography (ECoG) recordings intraoperatively to help guide stimulation mapping of reading in vOTC.

METHODS: In 11 patients undergoing extraoperative, intracranial seizure mapping, the authors recorded induced broadband gamma activation (70-150 Hz) during a visual category localizer. In 2 additional patients, whose pathologies necessitated resections in language-dominant vOTC, task-based functional mapping was …


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