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Keyframe Selection From Motion Capture Data With Dual-Agent Reinforcement Learning, Kun Hu, Wang, Clinton Mo, Mingyang Ma, Shaohui Mei, Zebin Chen, Zhiyong Wang

Research outputs 2022 to 2026

Animation production workflows centered around motion capture techniques require animators to edit motions based on a set of keyframes. However, most existing keyframe selection methods are optimization-based, which suffer from the issues of flexibility and efficiency. In this paper, a novel deep reinforcement learning method with dual agents are proposed for unsupervised keyframe selection. First, an S-Agent and an R-Agent evaluate the actions of selection and refinement, respectively. A deep spatio-temporal network, namely graph keyframe evaluation network (GKEN), is proposed for the agents. Then, an animation specified reward is devised based on reconstruction, which fulfills three important properties of the …

Glomalin-Related Soil Protein In Colluvial Soils As A Proxy For Reconstructing Millenary Changes In Landscape And Soil Health, Axel Werner, Lourdes López-Merino, Joeri Kaal, Cruz Ferro-Vázquez, Oscar Serrano

Research outputs 2022 to 2026

Glomalin-related soil protein (GRSP) is an operationally defined soil organic matter pool that includes a heat shock protein linked to arbuscular mycorrhizal fungi (AMF) living in symbiosis with most vascular plants and plays a key role in soil health. However, the potential of GRSP as a palaeoecological proxy remains unexplored. We analysed the GRSP content in a North-western Iberian colluvial soil profile encompassing the last 14,000 years. We aimed to 1) identify whether GRSP is preserved, and 2) investigate whether GRSP could be used as a palaeoecological proxy after comparing its record with palynological and pedoanthracological records that account for …

Effects Of Demineralization Protocols On Hydrogen And Oxygen Isotope Ratios In Fossil Bone Collagen, Linda M. Reynard

Boise State University Publications and Presentations

The effect of three commonly used preparation protocols on bone collagen δ2H and δ18O values was investigated, using six generally well-preserved faunal bones (cattle, bison, horse) ranging in age from the Holocene to Late Pleistocene. The treatments tested were ethylene diamine tetraacetic acid demineralization without gelatinization and hydrochloric acid demineralization with and without gelatinization. There are significant shifts in δ18O values among preparation methods. No systematic shifts in bone collagen δ2H values were noted among the three treatments, and most offsets were low (< 2–3 ‰) and smaller than typical measurement uncertainties. A few sample/treatment combinations yielded slightly higher inter-treatment δ2H differences (∼ 5–7 ‰). Lower mass fraction of hydrogen in …

Reliability And Validity Of Upper Extremity Neurocognitive Reactive Tests In Collegiate Athletes, Matthew L. Gauthier, Marisa Pontillo, George J. Davies

Physical Therapy Faculty Publications

Objectives: Neurocognitive function is vital in sports, but evidence supporting neurocognitive reaction testing in upper extremity return-to-sport testing is limited. This study's purpose was to quantify measurement properties of upper extremity reactive testing in collegiate athletes, hypothesizing acceptable measurement properties for clinical use.

Design: Cross-Sectional Study.

Setting: Collegiate athletics.

Participants: Sixty-three healthy athletes (25 females, age = 20.8 ± 1.6 years, BMI = 25.6 ± 2.6 kg/m2; 38 males, age = 20.8 ± 1.6, BMI = 25.7 ± 2.6 kg/m2).

Main outcome measure(s): Successful touches and average reaction time on the Upper Extremity Reactive Closed Kinetic Chain Test (UERCKCT) and …

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A Review Of Gallium And Germanium Recovery From Industrial Solid Residues, Ernest V. Oteng, Marthias Silwamba, Lana Alagha, Alex Luyima

Mining Engineering Faculty Research & Creative Works

The global demand for critical elements such as gallium (Ga) and germanium (Ge), and the shift toward circular mining has accelerated the development of new extraction and recovery processing these metals from industrial solid residues. This transition is driven by a substantial surge in demand for advanced technologies and the depletion of primary ore. Consequently, industrial solid residues, particularly zinc processing residues, smelter slags, flue dusts, and coal fly ash, are emerging as viable alternative sources. These residues incorporate Ga and Ge through isomorphic substitution in phases such as ferrites, silicates, and glassy aluminosilicates, and are enriched by industrial processes, …

Prototyping Pinhole Collimators For Imaging Irradiated Nuclear Fuel, Narrie Loftus, Ashish Avachat, Joseph T. Graham, Ryan Fronk, Jordan Fox, Rachel Shaffer, Seth Kilby

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

Collimator design and fabrication is a costly and time-consuming process that does not lend itself to simplified testing. This manuscript presents an approach for the rapid prototyping of sub-millimeter pinhole collimators for nuclear fuel applications using low-melting-point, high-mass-density materials. Multiple collimators were fabricated to test collimator parameters and properties, including acceptance angle, aperture diameter, and magnification. The fabricated collimators were paired with a position-sensitive CdZnTe detector to determine the detector response convolved with the collimator. Preliminary analysis using these collimators showed that they were effective in collimating multi-energy gamma laboratory sources. Radiography was performed to confirm magnification and determine coarse …

Differences In Infection Prevention And Control Staffing Between Free-Standing And System-Affiliated Hospitals: A National Survey., Lucas Philip, Vittorio Maio, Pamela De Cordova, Elizabeth Monsees, Raegan Davis, Pat Moeller, Andrew Dick, Scott W Keith, Monika Pogorzelska-Maziarz

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND: Infection prevention and control (IPC) staffing varies across US hospitals, and traditional bed-based benchmarks may no longer reflect contemporary workloads or organizational structures. With most hospitals now system-affiliated, understanding how affiliation influences infection preventionist (IP) staffing is critical for modernizing guidance.

METHODS: A national survey was distributed to US acute care hospitals participating in the National Healthcare Safety Network (NHSN) from August to December 2023, assessing IPC staffing, resource availability, and organizational structure. Hospitals were categorized as free-standing or system-affiliated; differences were assessed with Wilcoxon rank-sum and chi-square tests.

RESULTS: Of 741 responding hospitals, 550 (74%) were system-affiliated and …

Lrq-Solver: A Transformer-Based Neural Operator For Fast And Accurate Solving Of Large-Scale 3d Pdes, Peijian Zeng, Guan Wang, Haohao Gu, Xiaoguang Hu, Tiezhu Gao, Zhuowei Wang, Aimin Yang, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

Solving large-scale PDEs on complex three-dimensional geometries remains a central challenge in scientific and engineering computing, often due to expensive pre-processing stages and high computational overhead. We present Low-Rank Query-based PDE Solver (LRQ-Solver), a physics-integrated deep learning framework for efficient CAE simulations of complex three-dimensional geometries in CAD-driven design analysis. Built upon the Parameter-Conditioned Lagrangian Modeling (PCLM) that embeds physical consistency into the learning process and the Low-Rank Query Attention (LR-QA) module that reduces attention complexity from O(N2) to O(NC2+C3) via covariance decomposition, LRQ-Solver supports multi-configuration analysis within iterative design workflows. On two benchmark datasets, it achieves a 28.6% error …

Mind The Hazard: Modeling And Interpreting Comfort With Personalized Sensing, Yufei Zhang, Matteo Favero, Patrick Chwalek, Sailin Zhong, Denis Lalanne, A. Joseph Paradiso, Clayton Miller, Andrew Sonta

Research Collection College of Integrative Studies

Recent advances in personalized sensing and comfort feedback have spurred the development of data-driven comfort models tailored to individual needs. However, because current models treat sequential comfort feedback independently, they are subject to unstable predictions and limited interpretability, hindering their deployment in building management. This study introduces a dynamic modeling framework that utilizes a Neural Ordinary Differential Equations-based Continuous-time Markov Chain to model the transitions in comfort states over time. Our modeling approach, developed through a field study utilizing smart glasses and mobile app feedback, tracks occupants' comfort transitions across daily activities and contexts. The results demonstrate that this model …

Emotional Urgency And Lack Of Perseverance Are Linked To Anxiety Sensitivity And Improve During Early Recovery From Opioid Use Disorder., Breanna A. Mcnaughton-Long, Abigail J. Pleiman, Carmen Buchfink, Chrysantha B. Davis, Rayus Kuplicki, Martin P. Paulus, Hung-Wen Yeh, Maëlle C M Gueguen, Jennifer L. Stewart

Manuscripts, Articles, Book Chapters and Other Papers

Few studies have identified how facets of impulsivity relate to recovery in opioid use disorder (OUD). Treatment-enrolled individuals with OUD (n = 167) and healthy controls (CTL; n = 46) completed the Urgency, Premeditation, Perseverance, Sensation Seeking, Positive Urgency (UPPS-P) Impulsive Behavior Scale along with demographic and clinical measures at visit 1. Over the next three months, abstinence and return to use were documented for participants with OUD (via self-report, alcohol breathalyzer, urine drug screen, and secondary contact communication). Participants with OUD who returned to use (n = 59) did not complete further study visits, whereas those who remained abstinent …

Climate Transition Stress Testing For Corporate Credit Risk: A Replicable Data-Mining Pipeline Using Esg Risk Scores, Huynh Long Hung Nguyen, Alan @ Ali Madjelisi Megargel, Rajesh Krishna Balan, Paul Robert Griffin

Research Collection School Of Computing and Information Systems

We present a replicable data-mining pipeline for illustrative, scenario-conditioned corporate distress analysis under feature decoupling. The pipeline links Compustat financial statements with Sustainalytics ESG Risk Rating records for 2,144 U.S. non-financial public firms, constructs a standardized Transition Risk Index (TRI), estimates a contemporaneous accounting-distress classifier, and applies transparent transition-cost sensitivities. Distress is defined as annual operating income insufficient to cover annual interest expense; interest coverage itself is excluded from the predictors. The resulting model is not a forward default forecast or a regulatory probability-of-default model. On a held-out cross-sectional test set, the logistic specification obtains AUC 0.909, PR-AUC 0.822, and …

Tiny Large Language Models For Iot Networks: Potentials And Challenges, Muhammed Golec, Suhib Bani Melhem, Yaser Khamayseh, Abdulmalik Alwarafy, Naofal Al-Dhahir

All Works

Large Language Models (LLM), which have gained great momentum in recent years, have revolutionized the field of Artificial Intelligence (AI); while their applicability for hardware-constrained Internet of Things (IoT) environments has begun to be questioned. This has led to the emergence of compact architecture and resource-efficient Tiny LLM models. This survey paper systematically examines Tiny LLMs for IoT networks and classifies existing approaches in five basic dimensions: model architectures, optimization strategies, transfer learning methods, deployment paradigms, and explainability-security integration. By applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, 139 related studies published between 2020 and 2025 …

Semiconductor Supply Chain Risk Monitoring And Forecasting: A Hybrid Big Data Architecture And Empirical Validation, Ming Gong, Sangwhan Cha

Harrisburg University Other Works

Global semiconductor manufacturing networks are characterized by deep geographical concentration, high capital intensity, and acute vulnerability to regional supply disruptions. While public merchandise trade statistics provide transparent, reproducible empirical records, transforming these raw macroeconomic streams into actionable supply chain risk intelligence requires both rigorous analytical framing and scalable computational architecture. In this paper, we propose an enterprise-grade cloud data architecture designed for semiconductor risk monitoring, combining scheduled distributed batch processing on Google Cloud (Dataproc/PySpark, BigQuery) with an event-driven streaming ingestion lane (Pub/Sub, Dataflow/Apache Beam). To rigorously evaluate the underlying scoring and forecasting logic without premature distributed deployment costs, we implement …

A Finite Element Model For Thermomechanical Stress-Strain Fields In Transversely Isotropic Strain-Limiting Materials, Saugata Ghosh, Dambaru Bhatta, S. M. Mallikarjunaiah

School of Mathematical & Statistical Sciences Faculty Publications

This paper presents a comprehensive computational framework for investigating thermo-elastic fracture in transversely isotropic materials, where classical linear elasticity fails to predict physically realistic behavior near stress concentrations. We address the challenge of unphysical strain singularities at crack tips by employing a strain-limiting theory of elasticity. This theory is characterized by an algebraically nonlinear constitutive relationship between stress and strain, which intrinsically enforces a limit on the norm of the strain tensor. This approach allows the development of very large stresses, as expected near a crack tip, while ensuring that the corresponding strains remain physically bounded. A loosely coupled system …

Pattern Formation In Quantum Hierarchical Cellular Neural Networks, Wilson A. Zuniga-Galindo, B. A. Zambrano-Luna, Chayapuntika Indoung

School of Mathematical & Statistical Sciences Faculty Publications

We present a new class of quantum neural networks (QNNs) whose states are solutions of p -adic Schrödinger equations with a non-local potential that controls the interaction between the neurons. These equations are obtained as Wick rotations of the state equations of p -adic cellular neural networks (CNNs). The p -adic CNNs arise as continuous limits of large discrete hierarchical neural networks (NNs). The CNNs are bio-inspired by the Wilson–Cowan model, which describes the macroscopic dynamics of large populations of neurons. We provide a detailed study of the discretization of the new p -adic Schrödinger equations, which allows the construction …

Life Participation In Parents Of Children With Ckd., Anastasia Hughes, Andrea Matus Gonzalez, Anita Van Zwieten, Chandana Guha, Simon Carter, Germaine Wong, Dale Coghlan, Amanda Dominello, Jonathan C. Craig, Martin Howell, Siah Kim, Karine Manera, Colm O'Reilly, Javier Recabarren Silva, Angela Rejuso, Benedicte Sautenet, Nicole Scholes-Robertson, Amanda Sluiter, Rebecca Wu, Mignon Mcculloch, Natalia Armijo, Ximena Atilano-Carsi, Patricia De La Cerda, Gabriel Alexis Gallardo Letelier, Carla Galvez, Nicole Gonzalez-Agüero, Maria Maldonado, Viola Pinto, Lilian Reyes, Lena Rodriguez, Angelica Rojo, Alejandro Sepúlveda, Luca G. Torrisi, Andrea K. Viecelli, Bashir Admani, Bethany J. Foster, Alexander J. Hamilton, Augustina Jankauskiene, Rebecca J. Johnson, Jasmijn Kerklaan, Isaac Liu, Stephen D. Marks, Cozumel S. Pruette, Franz Schaefer, Sebastian Wolfenden, Allison Jaure, Song-Kids Life Participation Workshop Investigators

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND: The caregiver burden among parents of children with chronic kidney disease (CKD) is high and can impair their life participation, which may in turn have negative consequences on their children's care and outcomes. We aim to describe effects on life participation in parents of children with CKD, from the perspectives of their children, health professionals, and the parents themselves.

METHODS: We thematically analyzed data from the Standardized Outcomes in Nephrology-Children and Adolescents Initiative (SONG-Kids) life participation workshops involving children with childhood CKD, parents or caregivers, and health professionals, for content related to perspectives on life participation among parents of …

Machine Learning Local Potentials For Accelerated Electron-Phonon Interactions Calculations Within The Projector Augmented-Wave Framework, Yi Xia

Mechanical and Materials Engineering Faculty Publications and Presentations

Electron–phonon interactions govern carrier dynamics, transport, and many optical and quantum phenomena in solids, but finite-displacement calculations within the projector augmented-wave (PAW) framework require up to 6N self-consistent supercell calculations for an N-atom system, making them costly for large, low-symmetry, and disordered materials. We introduce MLLocP, a machine learning (ML) strategy that learns the self-consistent local potential (LocP) on real-space grids and supplies its displacement derivatives to the evaluation of all-electron PAW electron–phonon matrix elements. Analysis of the PAW decomposition identifies the local-potential contribution as a natural target for machine learning, while the remaining PAW quantities are retained within the …

Organic Solvent-Assisted Pore Structure Modulation In Porous Carbons For Superior Energy Storage Performance In Supercapacitors, Jibi Kunjumon, Gurwinder Singh, Ajanya M. Ruban, Harleen Kaur, Alan Larson, Ranjit Pati, Et Al.

Michigan Tech Publications

The pore structure is a significant feature of porous carbons that accounts for their excellent performance in supercapacitors; however, the literature on pore modulation and cleansing is scarce. Here, a novel approach based on organic solvent-assisted pore modulation is reported to tune the pore hierarchy and local carbon-layer arrangement in porous carbons derived from waste biomass. The strategy involves adsorbing n-heptane into porous carbon at room temperature, thereby facilitating realignment of the carbon layers, improving pore hierarchy, and generating short-range graphitic domains. The solvent-assisted pore modulation, together with the high surface area and graphitization, led to a significant increase of …

The Influence Of Childhood Experiential History On Elon Musk’S Personality, Amelia Brower, Aubrey Immelman

Psychology Faculty Publications

This paper presents the results of a developmental causal analysis of the adult personality of innovative entrepreneur and business leader Elon Musk, from the conceptual perspective of personologist Theodore Millon.

Psychodiagnostically relevant data relating to Musk’s personality were collected from biographical sources and media reports and synthesized into a personality profile using the Millon Inventory of Diagnostic Criteria (MIDC), which yields 34 normal and maladaptive personality classifications congruent with DSM-III-R, DSM-IV, and DSM-5-TR.

The findings of the personality assessment were previously reported in a separate paper. Musk’s primary personality patterns were found to be Ambitious/self-serving and Dominant/controlling, …

Inclusive Education In Diverse Societies: Three Decades After The Salamanca Statement, From Disability Inclusion To The Recognition Of Student Diversity, Farida Kurniawati

Psychological Research on Urban Society

Inclusive Education in Diverse Societies: Three Decades after the Salamanca Statement, from Disability Inclusion to the Recognition of Student Diversity

Performing Proficiency: Ethnodrama As Arts-Based Research In An Esl Acting Classroom, Angel M. Morales

Journal of English Learner Education

This study explores the use of ethnodrama as an arts-based research method and pedagogical tool in English as a Second Language (ESL) education. Drawing on the work of Saldaña, Salvatore, and Denzin, the project examines how performance can communicate lived experiences, foster language development, and promote social justice in multicultural classrooms. Based on interviews and observations of ESL students in an Acting I course, the resulting ethnodrama, What?! Acting?!, presents verbatim narratives that reveal learners’ identities, struggles, and resilience. The findings highlight how theatrical practice enhances linguistic fluency, self-expression, and cultural understanding, demonstrating the transformative potential of performance in …

A Franco-American University Collaboration: Oral Assessment With Cefr And Star, Nadia Yassine-Diab, Christina Torres University Of Central Florida, Aimee Schoonmaker

Journal of English Learner Education

This article describes the collaboration between faculty at two international
universities, one in France and one in the U.S., who partnered their students to practice and assess oral skills. Using computer-mediated communication with both synchronous and asynchronous elements, the collaboration provided a valuable opportunity for both groups to engage in pedagogically meaningful and structured exchanges integrated into coursework that mirror their future professional situations (O’Dowd et. al., 2020). More specifically, each semester, the U.S. TESOL students interview and assess French speaking English language learners using the Common European Framework of Reference (CEFR) and the Situation Task Action Results (STAR) interview …

Making The Implicit Explicit For Multilingual Learners: A Language-Based Framework For Literacy Development, Luciana C. De Oliveira

Journal of English Learner Education

Literacy is fundamentally an act of meaning-making that requires bridging micro-level linguistic choices with macro-level text structures across genres. Current literacy policies dominated by Science of Reading (SoR) mandates often overemphasize isolated, word-level foundational skills. This narrow focus creates a one-size-fits-all model that reduces reading to the level of individual words, not appropriate for multilingual learners (MLs) who require access to dense, specialized disciplinary discourse. This article proposes an intentional, language-based literacy framework designed to build high-challenge, high-support classrooms for MLs without lowering academic expectations. Integrating genre-based pedagogy through the Teaching and Learning Cycle (TLC) with the mode continuum, the …

Race, Embodiment, And Professionalism: A Critical Intersectional Analysis Of Brazilian Sign Language Interpreting, Roberto César Reis Da Costa, Sheila Santos

Journal of Interpretation

This paper investigates the intersections of race, corporate professionalism, and somatic regulation within Brazilian Sign Language (Libras) translation and interpretation. While traditional translation scholarship prioritizes linguistic neutrality, this study employs an interdisciplinary critical methodology combining Critical Race Theory (CRT), Critical Discourse Analysis (CDA), and Translation and Interpreting Studies (TIS) to deconstruct how standard professional aesthetics inadvertently sustain systemic racism and Eurocentric cultural erasure. Utilizing a textual deconstruction of Article 5 of the National Libras Code of Ethics alongside an autoethnographic mapping of workplace visual ergonomics, we examine how racialized aesthetic expectations regulate and pathologize cultural markers such as braided hairstyles, …

Toward Cross-Cultural Assessment Of Career Anxiety: Psychometric Validation Of The Career Anxiety Scale In Indonesia, Arifah Wulandari, Raudha Nur Hidayah Al Jannah, Gracianus Edwin Tue P. Lejap, Elwas Berdha Krismona, Santy Andrianie, Anisah Muflihatul Latifah, Merikan Aren

Buletin Konseling Inovatif

Career anxiety has become an important psychological concern among university students amid rapid technological transformation, labor market uncertainty, and increasingly complex school-to-work transitions. However, evidence regarding the factor structure of the Career Anxiety Scale (CAS) in the Indonesian context remains limited. This study aimed to examine the factor structure and psychometric properties of the Indonesian Version of the Career Anxiety Scale (CAS-IV). A cross-sectional survey was conducted with 287 Indonesian university students aged 18–25 years. The instrument was translated in accordance with International Test Commission guidelines and evaluated using Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), inter-factor correlations, and …

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Thin Sections

No abstract provided.

Llm-Driven Simulation Method For Mobilization Decision-Making In Weapons And Equipment Supply Chain, Qichang Guo, Jihai Zhang, Zichu Qin

Journal of System Simulation

Abstract: A LLM-driven multi-agent simulation model for production mobilization in the weapons and equipment supply chain is developed to address the practical challenge of transitioning the supply chain from peacetime to wartime production in response to surging wartime demand. The model consists of a military demand layer, a supply chain execution layer, and a mobilization decision-making layer. An LLM is incorporated as a mobilization decision generation module to represent the dynamic regulation of production conversion and expansion under war-readiness budget and production safety constraints. The simulation results show that compared with the no-mobilization and rule-based mobilization strategies, the LLM-based strategy …

Chemical Plant Control Based On Dynamic Simulation And Reinforcement Learning, Yuxin Li, Haijie Li, Shangbo Han, Kai Gao, Qingyuan Zhang, Yanwen Xiao, Zhengcai Liu

Journal of System Simulation

Abstract: An intelligent control strategy framework combining offline training and on-site deployment for regenerative thermal oxidizer (RTO) operation control based on RL is proposed to solve the problem that fluctuations in exhaust gas concentration and flow, as well as changes in working conditions, make it difficult for RTO to maintain the system operating parameters within the economically optimal range in practical applications. In the offline phase, RL is employed to enable autonomous policy learning and global optimization. In the online phase, an adaptive policy correction mechanism based on real-time data is introduced. RL control strategy is integrated with the operation …

Five-Dimensional Digital Twin System For Closed-Loop Gasoline Blending Optimization, Yaning Fang, Renchu He

Journal of System Simulation

Abstract: An adaptive blending optimization system based on five-dimensional digital twin theory is designed and developed to address the challenges of strict nonlinear constraints and frequent raw material fluctuations. A five-dimensional model architecture is constructed to achieve virtual-real mapping and synergy throughout the blending process. A closed-loop control strategy of "online model correction and dynamic recipe optimization" is proposed. The constrained recursive least squares (RLS) algorithm is adopted to update the octane blending effect model parameters, resolving the model mismatch caused by raw material fluctuations. The linear decreasing weight particle swarm optimization algorithm (LDW-PSO) is combined to determine the optimal …