Digital Commons Network^™

The Ubiquity Of Time In Latent-Cause Inference, Dan-Mircea Mirea, Yeon Soon Shin, Sarah Dubrow, Yael Niv

Psychology Faculty Research and Scholarship

Humans have an outstanding ability to generalize from past experiences, which requires parsing continuously experienced events into discrete, coherent units, and relating them to similar past experiences. Time is a key element in this process; however, how temporal information is used in generalization remains unclear. Latent-cause inference provides a Bayesian framework for clustering experiences, by building a world model in which related experiences are generated by a shared cause. Here we examine how temporal information is used in latent-cause inference,using a novel task in which participants see ‘microbe’ stimuli and explicitly report the latent cause (‘strain’) they infer for each …

Emphasizing Self-Regulation In Teaching: Reducing Disruption To Students’ Learning During Unplanned Instructional Mode Transition, Somesh Roy, Amber Young-Brice, Jenna Lassila, Brandon Kyle Johnson

College of Nursing Faculty Research and Publications

In Spring 2020, engineering faculty transitioned to emergency remote instruction due to COVID-19. This mixed-methods study was done to understand the correlation between self-regulated learning and how students experienced the emergency transition to remote learning. The participants were from an upper-level engineering course, with 33 students surveyed four times during the semester. Seven students were interviewed after the semester. Findings revealed that during the transition to remote learning, students perceived less change if they had higher degrees of self-regulation. The qualitative analysis also revealed that transparency in learning and teaching also played an important role in students’ perceptions.

Prevalence And Determinants Of Diarrhoea And Acute Respiratory Infections Among Children Aged Under Five Years In West Africa: Evidence From Demographic And Health Surveys, Derrick Nyantakyi Owusu, Henry Ofori Duah, Duah Dwomoh, Yakubu Alhassan

College of Nursing Faculty Research and Publications

Background Diarrhoea and pneumonia are the leading causes of morbidity and mortality in children aged < 5 y (under five) globally. This study sought to investigate the prevalence and determinants of diarrhoea and acute respiratory infections (ARIs) among children under five in West Africa. Methods The most recent demographic and health survey (DHS) standard for 13 West African countries was used in the study. We calculated the prevalence of diarrhoea and ARIs (2 wk prior to the survey) and performed multivariable complex logistic regression analysis to identify possible predictors of diarrhoea and ARIs. Results The weighted prevalence of diarrhoea and ARI was 13.7% and 15.9%, respectively. The prevalence of comorbid diarrhoea and ARI was 4.4%. Children aged < 2 y (p< 0.001), mothers aged < 30 y (p< 0.003), mothers without formal education (p< 0.001), poor households (p< 0.001) and poor nutritional status, wasting (p=0.005) and underweight (p< 0.001), were the independent predictors of diarrhoea. The independent predictors of ARIs were children with no childhood vaccinations (p=0.002), use of solid fuel in the household (p=0.007), being underweight (p=0.05) and diarrhoea (p< 0.001). Conclusions The findings imply the need for holistic public health interventions such as increased vaccination coverage, population-based nutritional programmes and campaigns on the use of cleaner cooking fuel targeted at high-risk subgroups in the population to reduce the burden and adverse effects of diarrhoea and ARIs in the West African region.

Conduction System Pacing For Heart Failure, Nathan R Smith, Patrick Lynch, Mihail G Chelu

The Texas Heart Institute Journal

No abstract provided.

Tfeb-Vacuolar Atpase Signaling Regulates Lysosomal Function And Microglial Activation In Tauopathy, Baiping Wang, Heidi Martini-Stoica, Chuangye Qi, Tzu-Chiao Lu, Shuo Wang, Wen Xiong, Yanyan Qi, Yin Xu, Marco Sardiello, Hongjie Li, Hui Zheng

Center on Aging Staff Publications

Transcription factor EB (TFEB) mediates gene expression through binding to the coordinated lysosome expression and regulation (CLEAR) sequence. TFEB targets include subunits of the vacuolar ATPase (v-ATPase), which are essential for lysosome acidification. Single-nucleus RNA sequencing of wild-type and PS19 (Tau) transgenic mice expressing the P301S mutant tau identified three unique microglia subclusters in Tau mice that were associated with heightened lysosome and immune pathway genes. To explore the lysosome-immune relationship, we specifically disrupted the TFEB-v-ATPase signaling by creating a knock-in mouse line in which the CLEAR sequence of one of the v-ATPase subunits, Atp6v1h, was mutated. CLEAR mutant exhibited …

Stroke Survivors’ Telemedicine Experiences During The Covid-19 Pandemic: A Phenomenological Investigation, Barbara Kimmel, Annette Walder, Anette Ovalle, Chethan P Venkatasubba Rao, Sean I Savitz, Mark Goldberg, Steven Warach, Salvador Cruz-Flores, Daiwai M Olson, Jane A Anderson

Faculty, Staff and Student Publications

PURPOSE: This study aimed to describe stroke survivors' experiences receiving telemedicine visits at the Lone Star Stroke Consortium during the COVID-19 pandemic.

MATERIALS AND METHODS: A qualitative descriptive phenomenological design was applied to gather patients' telemedicine experiences through in-depth interviews, using a study guide. Audio-recorded interviews were conducted via ZOOM and transcribed verbatim. Two independent reviewers used the Giorgi descriptive method to analyze the data and search for the essence of stroke survivors' follow-up telemedicine experiences during the COVID-19 pandemic.

RESULTS: Fifteen underserved patients were recruited: mean age, 51.8 (15.7), and 9 (60%) females. Three themes emerged: (1) vivid memory …

Insights From Social Media Into Public Perspectives On Investigative Genetic Genealogy, Sara Huston, Diana Madden, Andrea Villanes, Nathan Reed, Whitney Bash Brooks, Christopher Healey, Christi Guerrini

Center for Medical Ethics and Health Policy Staff Publications

Social media sites like X (formerly Twitter) increasingly serve as spaces for the public to discuss controversial topics. Social media can spark extreme viewpoints and spread biased or inaccurate information while simultaneously allowing for debate around policy-relevant topics. The arrest of Joseph J. DeAngelo in April 2018 ignited a barrage of social media conversations on how DNA and genetic genealogy led to the suspect. These conversations continued over the following years as policies changed and as the use of the approach expanded. We examined social media coverage of investigative genetic genealogy (IGG) to characterize the volume and temporal patterns in …

Title: I: L1-Norm Matrix Completion For Recommender Systems Ii: Conjecturing-Based Classification, Fatemeh Valizadeh Gamchi

Theses and Dissertations

Recommendation systems are essential for providing personalized user experiences, but their performance can be affected by outliers especially in traditional collaborative filtering methods that use the L2-norm. To address this challenge, we developed two new algorithms, SharpEl1rs and SharpEl1rs-Impute, based on the L1-norm to improve resistance against extreme values and effectively handle missing data. Our experimental setting was designed to compare these proposed methods with existing techniques. Then our algorithms are applied to real datasets to assess their performance, with findings indicating that our proposed models offer improved accuracy in some cases and solid performance in others for industrial-scale recommendation …

External Runtime Execution Monitoring Of A Cyber Physical System Via Trace Interfaces, Peter Vaughan Truslow

Theses and Dissertations

In the past two decades, Unmanned Aerial Systems have progressed from expensive military hardware or one-off custom builds, to include off-the-shelf drones that can be purchased for a rather affordable price and flown by nearly anyone. As the technology and performance have improved, the door is opened to applications that require operation in environments where the consequences for failure are high, such as operating in the navigable airspace or in urban environments, or with human passengers. This requires a great deal of trust in the reliability and integrity of the control systems of the aircraft. A method of monitoring the …

Direct Measurement Of Microwave Loss In Nb Films For Superconducting Qubits, B. Abdisatarov, D. Bafia, A. Murthy, G. Eremeev, H. E. Elsayed-Ali, J. Lee, A. Netepenko, C. P. A. Carlos, S. Leith, G. J. Rosaz, A. Romanenko, A. Grassellino

Electrical & Computer Engineering Faculty Publications

Niobium films are a key component in modern two-dimensional superconducting qubits, yet their contribution to the total qubit decay rate is not fully understood. The presence of different layers of materials and interfaces makes it difficult to identify the dominant loss channels in present two-dimensional qubit designs. In this paper, we present the study that directly correlates measurements of RF losses in such films to material parameters by investigating a high-power impulse magnetron sputtered (HiPIMS) film atop a three-dimensional niobium superconducting radio frequency (SRF) resonator. By using a 3D SRF structure, we are able to isolate the niobium film loss …

Hack24f: Ai And Mental Health: Addressing The Therapy Gap, Samatrai Piam, Digvijay Mahawar, Meric Kinali, Luxman Surentha, Jackson Comeau, Gail Rauch, Cody Turner

Paul English Applied Artificial Intelligence (AI) Institute Publications

Real-World Problem: There is a global shortage of mental health professionals, especially in underserved areas. AI-based chatbots could help fill this gap, but there are serious ethical concerns about the quality of care and efficacy of such chatbots.

Solution: This is a non-technical project that involved conversing with existing chatbots in an effort to develop a normative framework that could be used by future AI therapy bot developers. This framework seeks to build on, and operationalize, some of the insights from the recently published whitepaper on the ethics of chatbot therapy by the UMass Boston Applied Ethics Center. This presentation …

Hack24f: Beacon Pathway, Michael Agbesi, Ciara Santiago, David Martinez, Olivia Moos, Mohammed Mustafa

Paul English Applied Artificial Intelligence (AI) Institute Publications

The problem: There are a multitude of students from different backgrounds who are feeling lost in their academic journey at UMass Boston & need help with finding opportunities that fit their needs.

The solution: Developing Beacon Pathway, a user-centered platform designed to empower UMass Boston students from diverse backgrounds by streamlining their academic journey. This solution focuses on providing personalized resources, tailored opportunities, and community engagement, ensuring every student feels supported and connected as they navigate their unique paths to success

Hack24f: Examine The Human Creativity And Productivity In Ai Generated Content, Jongsoo Ha, Dante Barton, Onkar Khedkar, Neeti Shah, Yash Gondkar, Youxiang Zhu, Xiaohui Liang

Paul English Applied Artificial Intelligence (AI) Institute Publications

This project, presented at the Fall 2024 Hackathon, explores the balance between human creativity and productivity in the age of AI-generated content. With tools such as ChatGPT and Grammarly becoming integral to students’ academic workflows, questions surrounding originality, intellectual property, and academic integrity have grown increasingly urgent. The team addresses the challenge of distinguishing between human and AI contributions in content creation, particularly as current AI detection tools prove unreliable. Their proposed solution involves a system that not only detects AI-generated text using watermarking techniques but also quantifies contributions from humans and AI throughout the writing process.

Hack24f: Llms And World Knowledge Problems, Chengtaon Lin, Joseph Lobo, Huuthanhvy Nguyen, Brian Santos, Ting Xu

Paul English Applied Artificial Intelligence (AI) Institute Publications

While AI “hallucinations” have been widely publicized by the media as shortcomings of Large Language Models (LLMs), there is much less awareness about shortcomings that derive from the potential lack of understanding of the world, from a potential lack of commonsense knowledge. We want to raise awareness among our student body about the potential fallibility of LLMs when they the problems that they need to solve require a basic understanding of the world. We hope that this awareness will prompt everyone to question more carefully the outputs generated by LLMs.

Hack24f: Tori Project: An Llm Powered Personal Assistant That Speaks, Inal Mashukov, Avi Felzenstein

Paul English Applied Artificial Intelligence (AI) Institute Publications

The problem: remember Jarvis from Iron Man? If not, Jarvis is an AI personal assistant to Tony Stark, aka Iron Man, which can speak in a human-like manner, and is in charge of the systems of the Iron Man suit. Tony Stark also relies on Jarvis for direct access to information, automation of his projects, and helping with work in general. Currently, the “best” real-world alternatives to Jarvis are Siri and Alexa. These are NOT particularly intelligent. Wouldn't it be nice to have a Jarvis-like assistant that is: actually intelligent and resourceful, sounds human, runs locally/offline on your phone or …

Underlying Substrate Effect On Electrochemical Activity For Hydrogen Evolution Reaction With Low-Platinum-Loaded Catalysts, Baleeswaraiah Muchharla, Peter V. Sushko, Kishor K. Sadasivuni, Wei Cao, Akash Tomar, Hani Elsayed-Ali, Adetayo Adedeji, Abdennaceur Karoui, Joshua M. Spurgeon, Bijandra Kumar

Electrical & Computer Engineering Faculty Publications

Platinum is known as the best catalyst for the hydrogen evolution reaction (HER) but the scarcity and high cost of Pt limit its widespread applicability. Herein, the role of the underlying substrate on the HER activity of dispersed Pt atoms is uncovered. A direct current magnetron sputtering technique is utilized to deposit transition metal (TM) thin films of W, Ti, and Ta as underlying substrates for extremely low loading of Pt (

Using Feature Selection Enhancement To Evaluate Attack Detection In The Internet Of Things Environment, Khawlah Harahsheh, Rami Al-Naimat, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The rapid evolution of technology has given rise to a connected world where billions of devices interact seamlessly, forming what is known as the Internet of Things (IoT). While the IoT offers incredible convenience and efficiency, it presents a significant challenge to cybersecurity and is characterized by various power, capacity, and computational process limitations. Machine learning techniques, particularly those encompassing supervised classification techniques, offer a systematic approach to training models using labeled datasets. These techniques enable intrusion detection systems (IDSs) to discern patterns indicative of potential attacks amidst the vast amounts of IoT data. Our investigation delves into various aspects …

Quest For An Optimal Spin-Polarized Electron Source For The Electron-Ion Collider, J. Biswas, E. Wang, O. Rahman, J. Sharitka, K. Kisslinger, Adam Masters, S. Marsillac, T. Lee

Electrical & Computer Engineering Faculty Publications

Superlattice GaAs photocathodes play a crucial role as the primary source of polarized electrons in various accelerator facilities, including the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson National Laboratory and the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. To increase the quantum efficiency (QE) of GaAs/GaAsP superlattice photocathodes, a Distributed Bragg Reflector (DBR) is grown underneath using metal-organic chemical vapor deposition (MOCVD). There are several challenges associated with DBR photocathodes: the resonance peak may not align with the emission threshold of around 780 nm, non-uniform doping density in the top 5 nm may significantly impact QE and spin polarization, …

Real-Time Spectroscopic Ellipsometry For Flux Calibrations In Multi-Source Co-Evaporation Of Thin Films: Application To Rate Variations In Cuinse₂ Deposition, Dhurba R. Sapkota, Balaji Ramanujam, Puja Pradhan, Mohammed A. Razooqi Alaani, Ambalanath Shan, Michael J. Heben, Sylvain Marsillac, Nikolas J. Podraza, Robert W. Collins

Electrical & Computer Engineering Faculty Publications

Flux calibrations in multi-source thermal co-evaporation of thin films have been developed based on real-time spectroscopic ellipsometry (RTSE) measurements. This methodology has been applied to fabricate CuInSe₂ (CIS) thin film photovoltaic (PV) absorbers, as an illustrative example, and their properties as functions of deposition rate have been studied. In this example, multiple Cu layers are deposited step-wise onto the same Si wafer substrate at different Cu evaporation source temperatures (TCu). Multiple In₂Se₃ layers are deposited similarly at different In source temperatures (TIn). Using RTSE, the Cu and In₂Se₃ deposition rates are determined as …

A Fresh Revisit Of The Issues And Improvements In Impulse Invariance Filter Design For Infinite Impulse Response Filters, Chiman Kwan, Hal Ferguson

Electrical & Computer Engineering Faculty Publications

The objective of this paper is to first present some issues with impulse invariance filter (IIF) design during the design of digital infinite impulse response (IIR) filters. Engineers are often confused about some inconsistent observations. For instance, if the impulse response of a digital filter is designed using the impulse invariance procedure, then the analog and digital filters’ frequency and step responses are very different. Two simple remedies are presented in this paper. One is a post-processing approach that scales the frequency and step responses of the digital filter by the sampling interval T. Another one is a pre-processing approach …

Skipresnet: Crop And Weed Recognition Based On The Improved Resnet, Wenyi Hu, Tian Chen, Chunjie Lan, Shan Liu, Lirong Yin

Electrical & Computer Engineering Faculty Publications

Weeds have a detrimental effect on crop yield. However, the prevailing chemical weed control methods cause pollution of the ecosystem and land. Therefore, it has become a trend to reduce dependence on herbicides; realize a sustainable, intelligent weed control method; and protect the land. In order to realize intelligent weeding, efficient and accurate crop and weed recognition is necessary. Convolutional neural networks (CNNs) are widely applied for weed and crop recognition due to their high speed and efficiency. In this paper, a multi-path input skip-residual network (SkipResNet) was put forward to upgrade the classification function of weeds and crops. It …

Parametrization Of Fluid Models For Electrical Breakdown Of Nitrogen At Atmospheric Pressure, Shirshak K. Dhali

Electrical & Computer Engineering Faculty Publications

In the transient phase of an atmospheric pressure discharge, the avalanche turns into a streamer discharge with time. Hydrodynamic fluid models are frequently used to describe the formation and propagation of streamers, where charge particle transport is dominated by the creation of space charge. The required electron transport data and rate coefficients for the fluid model are parameterized using the local mean energy approximation (LMEA) and the local field approximation (LFA). In atmospheric pressure applications, the excited species produced in the electrical discharge determine the subsequent conversion chemistry. We performed the fluid model simulation of streamers in nitrogen gas at …

Scene Classification Of Remote Sensing Image Based On Multi-Path Reconfigurable Neural Network, Wenyi Hu, Chunjie Lan, Tian Chen, Shan Liu, Lirong Yin, Lei Wang

Electrical & Computer Engineering Faculty Publications

Land image recognition and classification and land environment detection are important research fields in remote sensing applications. Because of the diversity and complexity of different tasks of land environment recognition and classification, it is difficult for researchers to use a single model to achieve the best performance in scene classification of multiple remote sensing land images. Therefore, to determine which model is the best for the current recognition classification tasks, it is often necessary to select and experiment with many different models. However, finding the optimal model is accompanied by an increase in trial-and-error costs and is a waste of …

Integrated Machine Learning And Deep Learning Models For Cardiovascular Disease Risk Prediction: A Comprehensive Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran

Electrical & Computer Engineering Faculty Publications

Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study explores the performance of traditional Machine Learning (ML) and Deep Learning (DL) models in predicting CVD risk, utilizing a meticulously curated dataset derived from health records. Rigorous preprocessing, including normalization and outlier removal, enhances model robustness. Diverse ML models (Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbor, Decision Tree, and Gradient Boosting) are compared with a Long Short-Term Memory (LSTM) neural network for DL. Evaluation metrics include accuracy, ROC AUC, computation time, and memory usage. Results identify the …

Verification And Validation Of Pavement Models, Jaime Hernandez, Angeli Jayme, Hasan Ozer, Eyal Levenberg, Lev Khazanovich, Emin M. Kutay

Civil and Environmental Engineering Faculty Research and Publications

Model development activities are increasing in pavement research and engineering applications. At the same time, there is ambiguity and a lack of consistency with regard to checking and quantifying credibility and suitability for the intended application. Specifically, usage of the terms Verification and Validation (V&V) is seen to vary across contributions. In this context, this paper was motivated by the desire to provide a best-practice reference that underlines the significance of the V&V terms, clarifies their definition, and promotes a more unified usage. Accordingly, the objective was to offer examples that introduce the V&V jargon, demonstrate basic V&V concepts and …

Diminished Tmem100 Expression In A Newborn With Acinar Dysplasia And A Novel Tbx4 Variant: A Case Report, Przemyslaw Szafranski, Silvia Patrizi, Tomasz Gambin, Bushra Afzal, Emily Schlotterbeck, Justyna A Karolak, Gail Deutsch, Drucilla Roberts, Paweł Stankiewicz

Faculty, Staff and Students Publications

Acinar dysplasia (AcDys) of the lung is a rare lethal developmental disorder in neonates characterized by severe respiratory failure and pulmonary arterial hypertension refractory to treatment. Recently, abnormalities of TBX4-FGF10-FGFR2-TMEM100 signaling regulating lung development have been reported in patients with AcDys due to heterozygous single-nucleotide variants (SNVs) or copy-number variant (CNV) deletions involving TBX4, FGF10, or FGFR2. Here, we describe a female neonate who died at 4 hours of life due to severe respiratory distress related to AcDys diagnosed by postmortem histopathologic evaluation. Genomic analyses revealed a novel deleterious heterozygous missense variant c.728A>C (p.Asn243Thr) in TBX4 that arose …

‘Routines’ And ‘Formulaic Language’ In Conversation Analysis (Author's Extended Data), Danielle M. Pillet-Shore

Faculty Publications

Though the field of conversation analysis (CA) was founded upon examinations of interactional “routines” such as conversation openings and closings, conceptualizing and categorizing communicative phenomena as “formulaic” is anathema to CA. This chapter details how, since its inception, CA work has empirically elucidated how participants to recorded episodes of naturally occurring social interaction actively and collaboratively accomplish conversational activities as ‘routine’ or not by selecting from available action alternatives, spontaneously coordinating their selections vis-à-vis one another. Taking a multimodal CA approach, this chapter reviews state-of-the art literature on how people open and close in-person and telephone conversations, showing the immense …

Leveraging Information Forcing In Good Faith, Hillary A. Sale

Georgetown Law Faculty Publications and Other Works

Leveraging Information Forcing in Good Faith, a chapter in Research Handbook on Law and Time, argues that the information-forcing-substance theory has a significant role to play both in how courts decide duty of good faith and oversight matters and in how active and engaged directors can add value in the boardroom. As explored in the chapter, by deploying the theory in corporate-law matters, the courts can reveal the information gaps between officers and directors and create pressure for better processes and discourse within the corporation. In turn, this can impact both the way in which fiduciaries interact with …

The Lawlessness Of Sackett V. Epa, William W. Buzbee

Georgetown Law Faculty Publications and Other Works

When the Supreme Court speaks on a disputed statutory interpretation question, its words and edicts undoubtedly are the final judicial word, binding lower courts and the executive branch. Its majority opinions are the law. But the Court’s opinions can nonetheless be assessed for how well they hew to fundamental elements of respect for the rule of law. In particular, law-respecting versus law-neglecting or lawless judicial work by the Court can be assessed in the statutory interpretation, regulatory, and separation of power realms against the following key criteria, which in turn are based on some basic rule of law tenets: analysis …

Updating Senator Borah: A Nuclear Kellogg-Briand Pact, David A. Koplow

Georgetown Law Faculty Publications and Other Works

In recognizing the legacy of Senator William E. Borah, the author shares his remarks from the Borah Symposium at the University of Idaho, about the Senator's personality and character, his contribution and later characterization to international law and national security, specifically the 1928 Kellogg-Briand Pact, and finally, a proposal to a modern reincarnation to the Kellogg-Briand Pact and the newer threats of this era.