Digital Commons Network^™

“You Could Have Did Us Better Than This”: Reparative Housing Policies And The Struggle To Right Harms To Black Communities, Amie Thurber, Lisa K. Bates, Susan Halverson, Keisha Muia

School of Social Work Faculty Publications and Presentations

This paper contributes to the burgeoning literature related to reparative planning, with an emphasis on housing policy. After exploring the state of theorizing related to reparative planning, this paper describes its three central dimensions: public recognition, material redistribution, and social/spatial transformation. The authors use these dimensions to evaluate a housing policy designed to repair harms to Black residents in Portland, Oregon. This in-depth analysis draws on survey, interview, and focus group data to explore the degree to which residents’ experiences of the policy reflect these three dimensions. The paper concludes with implications for other municipalities considering reparative housing policies, namely …

Uab Startup Company Focuses On Ai To Help Identify Cardiovascular Disease, Staff

Browse All News

No abstract provided.

Regards Study Secures Nih Funding For Another Five Years, Expands Research On Stroke And Brain Health Risks, Staff

Browse All News

No abstract provided.

Adjunctive Middle Meningeal Artery Embolization For Subdural Hematoma, Jason M. Davies, Jared Knopman, Maxim Mokin, Ameer E. Hassan, Robert E. Harbaugh, Alexander Khalessi, Jens Fiehler, Bradley A. Gross, Ramesh Grandhi, Jason Tarpley

School of Medicine Publications

Background Subacute and chronic subdural hematomas are common and frequently recur after surgical evacuation. The effect of adjunctive middle meningeal artery embolization on the risk of reoperation remains unclear.

Methods In a prospective, multicenter, interventional, adaptive-design trial, we randomly assigned patients with symptomatic subacute or chronic subdural hematoma with an indication for surgical evacuation to undergo middle meningeal artery embolization plus surgery (treatment group) or surgery alone (control group). The primary end point was hematoma recurrence or progression that led to repeat surgery within 90 days after the index treatment. The clinical secondary end point was deterioration of neurologic function …

Fs Transcript 2024-11-20, Northern Illinois University

Faculty Senate Archives

No abstract provided.

Rooted In Nature: Pre-Service Teachers' Development Of Nature-Based Pedagogical Insights Through A Forest School Field Experience, Janet Vanlone, Lauren Shearer, Makenna Luzenski, Ellen Amarante, Susan Chlebowski, Chris Boyatzis

Faculty Journal Articles

Outdoor education programs, such as Forest School, have physical, social-emotional, and academic benefits for children, and teachers trained in nature-based pedagogy are more likely to provide outdoor education opportunities for their students. Incorporating outdoor field experiences in teacher preparation may teach new teachers how to implement nature-based programming. However, little is known about how outdoor field experiences affect pre-service teacher development. Grounded in self-efficacy theory (Bandura, 1977), this mixed-methods study examined in a pretest-posttest design how participating in a 12-week outdoor field experience contributed to pre-service teachers’ (N = 9) knowledge of nature-based pedagogy and their self-efficacy. Participants also completed …

Fostering Systems Thinking Through Engineering Study Abroad Programs, Desen S. Ozkan, Kirsten A. Davis, James C. Davis, Jessica Deters, Homero Murzi

School of Engineering Education Faculty Publications

Engineering study abroad programs are a novel setting for students to develop systems thinking, which has primarily been taught in formal learning environments. Through a situated learning perspective, we examined the impact of two engineering-focused study abroad experiences on developing students’ systems thinking skills. We conducted secondary data analysis to examine how first-year engineering students (n = 47) at a technical university in the United States (US) connect technical and contextual aspects of engineering in China and the UK/Ireland. The students on the China track drew connections more frequently (81% of excerpts) than those on the UK/Ireland track (49% …

Phase I Dose Escalation Study Of Io-108, An Anti-Lilrb2 Antibody, In Patients With Advanced Solid Tumors, Matthew H Taylor, Aung Naing, John Powderly, Paul Woodard, Luke Chung, Hongyu Tian, Hong Xiang, Rong Deng, Kyu Hong, Donna Valencia, Tao Huang, Ying Zhu, X Charlene Liao, Xiao Min Schebye, Manish R Patel

Faculty, Staff and Student Publications

Purpose: In this first-in-human dose escalation study, the safety and efficacy of IO-108, a fully human monoclonal antibody targeting leukocyte immunoglobulin-like receptor B2 (LILRB2), was investigated in patients with advanced solid tumors as monotherapy and in combination with pembrolizumab, an anti-programmed cell death protein 1 (PD-1) antibody.

Methods: The study included patients with histologically or cytologically confirmed advanced and relapsed solid tumors, with measurable disease by Response Evaluation Criteria In Solid Tumors (RECIST) V.1.1. Patients were treated with escalating doses of IO-108 every 3 weeks (Q3W) as monotherapy and in combination with pembrolizumab. Safety and tolerability were the primary objectives. …

Mitigating Neuroinflammation In Cognitive Areas: Exploring The Impact Of Hmg-Coa Reductase Inhibitor, Carlos Henrique Rocha Catalão, Luis Henrique Angenendt Da Costa, Jonathas Rodrigo Dos Santos, Luciane Carla Alberici, Luiz Luciano Falconi-Sobrinho, Diogo Dominguini, Tatiana Barichello, Maria José Alves Rocha

Faculty, Staff and Student Publications

Existing literature suggests that infection-specific mechanisms may play a significant role in the onset and progression of dementia, as opposed to the broader phenomenon of systemic inflammation. In addition, 3-hydroxy-3-methylglutaryl (HMG)-coenzyme A (CoA) reductase inhibitors have been proposed as a potential therapeutic approach for sepsis, given their anti-inflammatory and antioxidant properties. We investigated the neuroprotective effect of an HMG-CoA reductase inhibitor (simvastatin) by analyzing neurodegenerative markers, mitochondrial respiration, and neuronal tracing in the prefrontal cortex (PFC) and thalamic nucleus reuniens (RE) of sepsis survivor animals. Adult Wistar rats were subjected to sepsis by cecal ligation and puncture or left non-manipulated. …

Cladribine-Based Therapy For Acute Myeloid Leukemia In Child, Adolescent, And Early Young Adult Patients: The Md Anderson Cancer Center Experience, David Mccall, Shaikha Alqahtani, Moriah Budak, Irtiza Sheikh, Aaron E Fan, Cesar Nunez, Miriam B Garcia, Amber Gibson, Naval Daver, Sofia Garces, Nicholas J Short, Ghayas C Issa, Farhad Ravandi, Courtney D Dinardo, Guillermo Montalban Bravo, Guillermo Garcia-Manero, Branko Cuglievan, Tapan Kadia

Faculty, Staff and Student Publications

Background: Cladribine-based combination chemotherapy has demonstrated promising efficacy in patients with relapsed/refractory adult acute myeloid leukemia (AML), prompting its increased utilization in the frontline; in pediatrics, it has been typically reserved for relapsed or refractory cases. While fludarabine has been used more commonly as a purine analog in intensive regimens, cladribine may be an important alternative.

Methods: We performed a retrospective study at MD Anderson Cancer Center from January 2015 to July 2023, which included patients aged 1-21 years with refractory or relapsed AML who received cladribine outside of a transplant conditioning.

Results: A total of 30 patients were included, …

2024-11-20 Pnw Students Congregate At Vsa Turkey Bowl, Maude Miles

The Spectator Online

No abstract provided.

Construction And Evaluation Of A New Rat Reference Genome Assembly, Grcr8, From Long Reads And Long-Range Scaffolding, Jonathan M D Wood, Hao Chen, Julia L Ciosek, Patrick Masterson, Terence D Murphy, Theodore S Kalbfleisch, Peter A Doris

Faculty, Staff and Student Publications

We report the construction and analysis of a new reference genome assembly for Rattus norvegicus, the laboratory rat, a widely used experimental animal model organism. The assembly has been adopted as the rat reference assembly by the Genome Reference Consortium and is named GRCr8. The assembly has employed 40× Pacific Biosciences (PacBio) HiFi sequencing coverage and scaffolding using optical mapping and Hi-C. We used genomic DNA from a male BN/NHsdMcwi (BN) rat of the same strain and from the same colony as the prior reference assembly, mRatBN7.2. The assembly is at chromosome level with 98.7% of the sequence assigned …

Professional Development For Library Interns: Creation Of A Guide And Program, Rebecca Hedreen, Jessica Bernier, Alexis Haakonsen, Jennifer Mottolese, Ariss Tiu

Journal of Graduate Librarianship

Seeing a need for more structured mentorship in library professional development, an internship supervisor created a reading guide for her interns at a mid-sized public university. The librarian and the first four interns who used the guide as part of their internship describe their experiences with this new reading program. Besides enabling the discovery of interesting articles and videos, we hope that the focus on professional development will encourage internship supervisors to include explicit mentorship in professional development and encourage interns to ask for more support in developing this crucial practice.

What Is In Your Drink? How Ingredient Lists For Alcoholic Beverages Would Protect Persons With Food Allergies, Benjamin Leraris

DePaul Law Review

No abstract provided.

Upstream Lawyering: A Framework For Poverty Law, L. Kate Mitchell

DePaul Law Review

No abstract provided.

Table Of Contents

DePaul Law Review

No abstract provided.

Gpr-1194 Computer Vision-Enhanced Spectroscopy For Glucose Prediction: An In Vitro Validation Study, El Arbi Belfarsi

C-Day Computing Showcase

This study introduces a novel computer vision-based spectral approach for non-invasive glucose detection using synthetic blood samples. We developed an experimental setup with glucose concentrations from 70 to 120 mg/dL, using two dye methods. Light sources tested included an 850 nm LED, 850 nm laser, 808 nm laser, and 650 nm laser, with image capture via a 1080p IR camera. Data augmentation, including Gaussian noise, contrast and brightness adjustments, rotations, and zooming, produced seven variants per image. Three machine learning models—CNN, AdaBoost, and ResNet—were evaluated, with the 850 nm light source yielding the best results: 87.5% of predictions fell within …

Ur-172 A Comparative Study Of Llm Effectiveness In Mental Health Assistance​, Kris Prasad

C-Day Computing Showcase

This study evaluates the effectiveness of LLMs in supporting mental health applications by analyzing their performance in understanding and categorizing user (mental health-related) inputs. We collected data from various mental health apps on the Google Play Store, including user reviews and app descriptions, and filtered content using a targeted mental health keyword bank. Sentiment analysis and keyword similarity scores were generated for reviews using RoBERTa-based models, this showed us how each review aligned with the mental health keywords advertised by the app and how users felt about the app. We prompted four modern LLMs: GPT-4o, Claude 3.5 Sonnet, Gemma 2, …

Gmc-130 School Bus Monitoring Simulation W/ Apache Kafka, John Blake, Hudson Topping, Eun Sik Kim, Tiep Bui, Julio Lois

C-Day Computing Showcase

Our project is a proof-of-concept of event-streaming bus telemetry data using Apache Kafka (Kafka), as requested by our client, Gwinnett County Public Schools (GCPS). The Kafka event stream is more efficient than GCPS’s current process of pulling bus telemetry data: calling APIs every 5 seconds. Moving to Kafka will provide GCPS near real-time insights into bus locations and speeds, giving visibility to whether buses drive safely and punctually. Our simulation produces synthetic bus data to be passed through Kafka and consumed. It features two UIs for system monitoring and data visualization.

Gmr-216 Ai/Ml-Based Water Quality Monitoring Mobile App For Predicting E.Coli In Surface Waters, Keerthi Priya Karumanchi

C-Day Computing Showcase

E.coli contamination in surface waters has proven to be a significant public health concern, requiring innovative monitoring solutions. This paper presents the design of an AI-driven mobile application to predict whether E.coli bacteria are present at levels exceeding acceptable thresholds in surface waters. The methodology employs sensor devices to collect water quality data parameters, such as water temperature, pH, dissolved oxygen, and turbidity. A dataset is generated based on these parameters, and machine learning (ML) algorithms are applied to evaluate accuracy, precision, recall, and processing time. Additionally, our ML algorithms establish a correlation matrix among water quality parameters to identify …

Gmr-7175 Enhancing Alzheimer’S Diagnosis Through Spontaneous Speech Recognition: A Deep Learning Approach With Data Augmentation, Venkata Sai Bhargav Mutala

C-Day Computing Showcase

Alzheimer’s disease (AD) is a growing public health issue due to its progressive nature and rising prevalence. This study explores a neural network model trained on speech data from the ADReSS2020 Challenge dataset to distinguish AD patients from healthy individuals, using log-Mel spectrogram features. To improve accuracy, five data augmentation methods, including pitch and time shifting, were used. The results highlight deep learning, combined with data augumentation, as a promising, scalable, and noninvasive approach for early AD diagnosis

Gpr-2212 Explainable Multi-Label Classification Framework For Behavioral Health Based On Domain Concepts, Francis E Nweke, Abm Adnan Azmee

C-Day Computing Showcase

Behavioral health, which covers mental health, lifestyle choices, addictions, and crises, poses serious issues in the community. Thus, appropriately analyzing and classifying behavioral health data is crucial for making informed healthcare decisions. Traditional deep learning and natural language processing approaches struggle to effectively identify behavioral health issues because the data is unstructured, complex, and lacks sufficient context. Furthermore, subject matter experts must be consulted to ensure effective identification. In this work, we proposed a deep learning-based framework consisting of several modules: A) domain concept encoder converts the keywords and their evidence types to vectors, which were predefined by a subject …

Uc-166 The Eternal Guest - A 2d Hack-And-Slash Game, Luke H Gamage, Zion Johnson, Benjamin J Hedges, Bryanna N Walker, Avis A. Ewing

C-Day Computing Showcase

The Eternal Guest is a narrative-driven, hack-and-slash combat and exploration game where you make meaningful friendships, battle enemies, and regain lost memories as you traverse a strange, non-euclidian hotel. Use a wide array of weapons and abilities alongside the knowledge you gain from other guests to attempt to escape the bloodlust of a homicidal vampire. The Eternal Guest emphasizes 2D, top-down, melee combat in combination with ranged abilities, offering an exciting dynamic to gameplay. Our game also presents a unique spin on randomized exploration through its unique D.R.E.A.D. system, creating a sense of unease and uncertainty when exploring. This unique …

Uc-173 Leveraging Large Language Models To Empower Caretakers Of People With Dementia, Mercy Olaniran, Emily A Centeno

C-Day Computing Showcase

Behavioral symptoms of Alzheimer's Disease and Related Dementias (ADRD) are detrimental to the quality of life for individuals with ADRD and their caregivers. Symptoms such as wandering, agitation, and confusion can often overwhelm caregivers leading to stress, depression, or burnout which can lead to a decrease in the quality of care. These challenges often result in increased hospitalizations and care costs, creating a need for a solution to support informal caregivers. This project proposes the development of an AI-based Dementia Care Voice Assistant application to meet the needs of caregivers. Using large language models, the application will provide real-time and …

Gmr-159 Llm Enabled Synthetic Dataset Generation For Human-Ai Teaming Algorithm, Sai Sanjay Potluri

C-Day Computing Showcase

This research explores using Large Language Models (LLMs) to generate synthetic datasets for Human-AI teaming algorithms, focusing on mental health assessments. We create a diverse dataset simulating human-AI collaboration scenarios in diagnostic processes. The synthetic data is labeled through an innovative approach involving two human annotators and three LLMs, using majority voting for consensus-based annotations. This dataset serves as a resource for training and evaluating Human- AI teaming algorithms, enabling exploration of collaboration dynamics between human expertise and AI in complex decision-making. Our approach addresses the scarcity of real-world data in Human-AI teaming scenarios and provides a controlled environment for …

Gmr-208 Automatic Categorization Of Behavioral Health Issues In Police Reports, Mason V Pederson, Abm Adnan Azmee, Francis E Nweke

C-Day Computing Showcase

911 is often the first place contacted for dealing with behavioral health related (BHR) issues. Its estimated at least a fifth of all calls are related to behavioral health, and with BHR affected convicts having a recidivism rate of around 30%, its not hard to see how straining these issues can become on systems already stretched thin, where chronic understaffing is often a reality. A great solution would be if we could intervene as soon as possible to get people the treatment they need, police reports would be excellent for identifying and treating these individuals, but annotation is a long …

Gpr-151 Compassionate Digital Assistant: Anchor, Christopher M Regan, Navneet Verma

C-Day Computing Showcase

Mental health support is crucial, but access to professional care can be limited by cost, availability, and social stigma. Digital solutions, particularly chatbots, offer an accessible and scalable approach to providing mental health support. However, current chatbot solutions may not always reflect the diversity of users' emotional experiences, and they may lack the specialized domain knowledge and adaptability required for effective mental health counseling. This research project aims to address these challenges by developing a compassionate AI digital assistant that can use specialized natural language processing (NLP) models to provide empathetic and targeted responses based on the nature of the …

Gpr-233 Human-Assisted Ai For Detecting Mental Health Indicators In Social Media, Abm Adnan Azmee, Francis E Nweke, Mason V Pederson

C-Day Computing Showcase

Mental health is essential to overall well-being, and mental illness includes conditions that affect a person’s psychological health, causing significant distress and limiting daily functioning. With advancements in technology, social media has become a platform where individuals openly share their emotions and thoughts, offering a unique window into their psychological states. However, traditional machine learning models struggle to interpret social media data's wide range of linguistic nuances. To analyze this data effectively, collaboration with human experts is crucial. This study proposes an innovative human-AI teaming framework that integrates human expertise with artificial intelligence (AI) to address these challenges. Our framework …

Uc-140 Streamlining School Bus Monitoring: Gcps's Transition To Real-Time Kafka Event Processing​, Sarah Fashinasi, Tyler J Hood, Jeffrey Sanderson, Amali B Mchie, Alexandra Baker

C-Day Computing Showcase

This project develops a prototype real-time bus monitoring system for Gwinnett County Public Schools using simulated Kafka event streaming to replace current API polling methods. The system processes simulated Asset Location and Speed events, mimicking Samsara's Kafka Connector, performing data validation before storing in SQL Server. The containerized solution demonstrates the potential for near real-time visibility into school bus operations.

Uc-247 Using Dynamic Difficulty Adjustment (Dda) To Improve Health And Wellness Apps And Programs, Fernando Orfila

C-Day Computing Showcase

Physical inactivity, obesity and Type 2 Diabetes cost the United States’ economy more than $700 billion a year (CDC). Yet, individuals spend $137 billion dollars a year on gym memberships to get in shape and feel better, without attaining results and dropping out. “…63% of new members will abandon activities before the third month, and less than 4% will remain for more than 12 months of continuous activity.” (Sperandei et al). The personal training apps don’t fare better, with 71% of users disengaging within 90 days (Amagai et al). The higher chances of people dropping out are due to "a …