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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 …

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, …

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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, …

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 …

Codee Expects That Every Mathematician Will Do Their Odes: From The Battle Of Trafalgar To Calculus (Or Nelson To Newton), Steven Miller

CODEE Journal

Using the historical Battle of Trafalgar as a case study, we introduce students to mathematical modeling to describe and explore real-world systems. Starting with the question—how do force sizes and combat effectiveness determine which side wins?—we show how to use a blend of mathematics and computational tools to investigate the answer. Beginning by defining a simple differential equation model for combat dynamics, we analyze its behavior using differential equations and accessible algebraic techniques. We show how computational methods and simulations can support systematic, visual exploration and suggest conjectures that mathematical analysis can then establish. This material could serve as 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 …

Nonhuman Speakers And The Constitution, Helen Norton

Fordham Law Review

Long-standing free speech law sometimes does—and sometimes does not—turn on speakers’ human character. This Essay explores how these doctrinal threads might shape the constitutional doctrine applied to generative artificial intelligence’s (AI) speech outputs if we assume that a human speaker cannot be identified as the creator of those words and images—and that those words and images are nevertheless considered “speech” for First Amendment purposes.

For example, First Amendment doctrine sometimes requires proof of a speaker’s culpable mental state before that speaker can be held liable for what would otherwise be unprotected speech. These requirements seek to prevent the chilling of …

Digital Gaze And Constitutional Democracy At 250, Catherine Powell

Fordham Law Review

The panopticon of digital surveillance undermines identity formation and realization of our authentic selves. This Essay offers a new insight by conceptualizing alienation from genuine selfhood as a form of “double consciousness.” W.E.B. Du Bois formulated the notion of double consciousness—the dual awareness inherent in negotiating between a self-defined identity and an externally imposed one. Just as Du Bois speaks of “double consciousness” for African Americans, the ever-present digital gaze to which we are now all subject—regardless of our race—creates a similar duality. I call this duality “online double consciousness,” which is compounded for people of color and other historically …

Clickwrap Accountability, Alicia Solow-Niederman

Fordham Law Review

Picture a public‑facing generative artificial intelligence (AI) chatbot on a government website that can answer questions about benefits eligibility. Systems like these expose a sociotechnical-legal divide: They route around the standard due process framework because there has been no formal government determination, yet they induce reliance from users, above and beyond past rounds of automated legal guidance. Moreover, if there is an error, current doctrine on government errors and equitable estoppel makes relief unlikely.

This Essay focuses on government deployment of public‑facing generative AI chatbots and critically assesses the front‑end power dynamics that determine who is filtered out of government …

Algorithmic Models And The Freedom Of Speech, Alexander Tsesis

Fordham Law Review

Intentionality and reason are intrinsic features of the human mind that large language models (LLMs) entirely lack. Although LLMs generate natural-language sentences through algorithmic processes, autonomously produced machine speech lacks the consciousness of human speakers. This intrinsic distinction between natural persons and artificial machines is consequential to whether LLM-generated outputs are covered by the First Amendment. Scholars who equate the constitutional value of human speech with algorithmic outputs tend to emphasize the informational value of those outputs to audiences while giving insufficient attention to the absence of machine consciousness. The conscious underpinnings of thought and their relation to constitutional protections …

Climate Change Under Customary International Law: Must The United States Protect The Climate System?, Daniel Rees

Fordham Law Review

On July 23, 2025, the International Court of Justice (ICJ) issued its “Advisory Opinion on Obligations of States in Respect of Climate Change,” concluding that “the full gamut of international law applies to climate change.” Beyond treaty-based duties, the ICJ recognized that customary international law imposes obligations on all states to protect the climate. The advisory opinion emerged from unprecedented participation by states and international organizations, reflecting a growing consensus that addressing climate change is a legal obligation. This Note explores the legal implications of recognizing a customary international law duty to protect the climate system. It posits that these …

Quality Reveals What Quantity Conceals: Deceptive Equity Patterns In Urban Green Space Distribution, Zheng Xian, Yoshiharu Suzuki, Kun Liu, Clive E. Sabel, Naoki Nakaya, Atsushi Hozawa, Tomoki Nakaya

School of Geography, Earth and Environmental Sciences

Equitable provision of urban green space depends on how green space exposure is measured, yet aggregate, quantity-focused metrics can mask disparities in quality. We introduce the concept of deceptive equity, in which apparent distributional fairness conceals substantive inequality, and test it across 344 postcode areas in Sendai, Japan. Across three dimensions — ecological (NDVI), perceptual (Green View Index) and service provision (accessible park count) — we paired a quantity indicator with a quality indicator. A quantity–quality divergence emerged in every dimension: wherever a quality indicator showed a significant socioeconomic gradient it favoured affluent areas, whereas the corresponding quantity indicators were …

Multilayered Childhood Adversity And Mortality: A Population-Based Cohort Study Of 1.2 Million Individuals, Naja Hulvej Rod, Signe Kær Bennetsen, Leonie K. Elsenburg, Clive E. Sabel, David Taylor–Robinson, Dora Kovacs, Adrian G. Zucco, Tjeerd Rudmer De Vries

School of Geography, Earth and Environmental Sciences

Background: Childhood adversity is multi-layered, extending beyond the family to include broader neighbourhood and health contexts. We aimed to investigate how these multiple layers of childhood adversity relate to the risk of death in young adulthood. Methods: Children were followed from birth into young adulthood (16–42 years) using nationwide register data on multi-layered childhood adversity and mortality. Individual adversity included perinatal adversity (preterm or small-for-gestational-age) and mental and physical health-service use. Family adversity included five distinct groups using group-based multi-trajectory modelling based on 12 adversities. Neighbourhood adversity included material deprivation in small-area geographical zones. We evaluated associations of these layers …

Decades Of National Health Strategy In England On Intellectual Disability And The Drift From Evidence-Based Practice, Rohit Shankar

Peninsula Medical School

No abstract provided.

A Review Of Bast Fibres And Their Composites: Part 5 ~ Sustainability, Luke Branca, Badr Moutik, John Summerscales

School of Engineering, Computing and Mathematics

Life Cycle Assessment (LCA) is a methodology for the evaluation of the (relative) potential environmental impacts of a product system throughout its life cycle. It is standardised under the ISO14040 and ISO14044 series. When conducted rigorously, LCA provides a quantitative framework for comparing environmental impact and can challenge or substantiate common assumptions regarding environmental performance of the system. However, it is essential that any reported results are read in combination with the defined goal and scope, as the choice of the system boundary and/or the allocation of burdens and other methodological choices can influence the outcome presented. This review will …

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 …

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 …

Meeting Survivors Where They Are: Gbv Service Fit And Mismatch In Rural Communities, Ziwei Qi, Rachel Dolechek, Naishuo Sun

Social Work Faculty Publications

Gender-based violence (GBV) poses ongoing challenges in rural communities, where structural and cultural barriers often hinder effective support. This qualitative study analyzed six listening sessions and two survivor panels with over 50 participants in a Midwestern state. Using trauma-informed care and cultural humility frameworks, we conducted reflexive thematic analysis to explore service alignment with local values and survivor needs. Two themes emerged: service fits, marked by adaptive, trust-based practices; and service mismatches, involving rigid systems and cultural isolation. Findings highlight the need for survivor-led, flexible, and culturally grounded responses to enhance rural GBV service delivery and promote long-term well-being.

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 …

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 …