Digital Commons Network^™

Nh State Shoreland Water Quality Protection Act (Landscaping For Water Quality Workshop - 2026), Jay Aube

UNH Cooperative Extension

No abstract provided.

Computational Regolith Mechanics And Instrumentation Development For Lunar Exploration And Resource Utilization, Jared M. Long-Fox

Graduate Studies Theses and Dissertations 2026

Sustained exploration of the Moon requires quantitative understanding of lunar regolith properties to support scientific investigation, in situ resource utilization, excavation, and infrastructure development. This dissertation examines the mechanical interaction between robotic excavation systems and lunar regolith, emphasizing how regolith behavior both enables and constrains exploration-focused and exploration-enabled science. Computational excavation models were compared to laboratory data to evaluate prediction of excavation forces and to develop metrics of excavation efficiency. Laboratory experiments using high-fidelity lunar regolith simulants were conducted to characterize pressure-sinkage behavior, shear strength, and angle of repose across a range of material states. Common analytical excavation and terramechanics …

An Investigation Into The Impact Of Open Educational Resources (Oer) On Postsecondary Student Outcomes, Amber Mullens

Graduate Studies Theses and Dissertations 2026

Increasing higher education costs are a concern for policymakers and the American public. In 2024-25, undergraduate students paid on average $1,290 for books and supplies (College Board, 2024). These costs have led policymakers and educators to advocate for the use of open educational resources (OER). OER are teaching and learning materials that are in the public domain or licensed under copyright allowing no cost access, reuse, repurpose, adaptation, and redistribution (UNESCO, 2019, p. 5). While research has demonstrated OER use significantly reduces costs for students, less is known about OER's impact on student academic outcomes. Despite significant research on these …

Design And Characterization Of A Jet Nozzle Using Particle Image Velocimetry, Valerie K. Rodriguez

Graduate Studies Theses and Dissertations 2026

This paper presents the design and experimental characterization of the jet exit velocity from a supersonic nozzle injecting into a low-pressure vacuum chamber using Particle Image Velocimetry (PIV). The PIV method is employed to overcome limitations encountered in prior experiments characterizing a jet-in-crossflow, such as qualitative shock visualization and insufficient data on jet exit properties. The previous set of experiments used Classical Schlieren to visualize the flow as well as emission measurement with IR detectors. For the fuel injection cases, particular emphasis is placed on preventing condensation within the injection line and at the nozzle exit due to under expanded …

Lessons Learned From Clinical Trials Of Thymic Stromal Lymphopoietin (Tslp) Inhibition, Jonathan Corren, Larry Borish, Christopher Brightling, Joseph K. Han, Emma Guttman-Yassky, Steven Ziegler, Jean Publicover, Jyotsna Gulati, Nestor Molfino, Christopher S. Ambrose, Jean-Pierre Llanos, Lang Chen, Jane R. Parnes, Joseph Spahn, Andrew Lindsley

Department of Otolaryngology (ENT) Faculty Publications

Type 2 (T2) immune–mediated epithelial-driven diseases are characterized by dysregulated immune responses at epithelial barrier surfaces. A key mediator of these diseases is thymic stromal lymphopoietin (TSLP), an epithelial cytokine that acts as a regulator of both T2 and non-T2 inflammation. TSLP activates dendritic cells and other immune cells, promoting the release of proinflammatory cytokines, including IL-4, IL-5, and IL-13. Given its central role in initiating and amplifying T2 inflammation, TSLP has emerged as a promising therapeutic target in multiple epithelial-driven inflammatory diseases. Tezepelumab is a human monoclonal antibody that selectively blocks TSLP from interacting with its receptor complex, thereby …

Absolute Quantification And Identification Of Rna From Rna-Lipid Nanoparticles Using High Resolution Mass Spectrometry, Jason C. Funderburk, Yasir A. Alshehry, Matthew S. Halquist Phd, Sandro R.P. Da Rocha Phd

Graduate Research Posters

Background

RNA therapeutics are a rising drug category with potential use for a range of conditions encompassing infectious diseases to therapies for cancer, diseases, and genetic disorders. RNA-lipid nanoparticles (RNA-LNPs) are the prominent delivery method for these therapeutics approved products include mRNA vaccines and polyneuropathy treatments. The emergency use authorizations and orphan drug status of current RNA-LNP drugs has allowed approval without finalization of the regulatory analytical procedures for quality monitoring. The objective of the study was to develop an LC-MS assay to simultaneously measure identity and concentration of two therapeutically relevant intact RNA constructs extracted from RNA-LNPs to enhance …

Watch Your Step, Mind The Crowd: Socially Compliant Navigation In Unstructured Environments, Jack Vice

Graduate Studies Theses and Dissertations 2026

Autonomous mobile robots increasingly operate in complex real-world environments characterized by uneven terrain, dynamic obstacles, and human presence. This dissertation addresses the fundamental challenge of developing adaptive navigation strategies that enable robots to safely and effectively traverse unstructured outdoor environments including construction sites, agricultural fields, and disaster areas while maintaining social compliance around people. We advance this capability through five complementary contributions that collectively target dynamic, unstructured, human-occupied environments. First, we demonstrate evolutionary optimization of legged mobility for uneven terrain. Second, we propose using a spatiotemporal autoencoder to learn the temporal dynamics of moving people and objects. Third, we introduce …

Federated Learning In The Era Of Foundation Models, Guangyu Sun

Graduate Studies Theses and Dissertations 2026

The emergence of large-scale foundation models has reshaped computer vision and multi-modal learning, but their substantial computational and communication demands pose significant challenges for deployment in federated learning (FL) systems. Federated learning enables collaborative model training across decentralized clients without sharing raw data, offering strong privacy guarantees. However, adapting foundation models in FL remains difficult due to communication bottlenecks, heterogeneous data distributions, limited device resources, and scarce labeled data. This dissertation presents a unified line of research that addresses these challenges through four complementary frameworks, progressively advancing the efficiency, personalization, and practicality of foundation model adaptation in federated settings.

First, …

Non-Destructive Characterization Of Variously Colored Gypsum And Aragonite/Calcite Speleothems From The Cigalère Cave (Ariège, France), Martin Vlieghe, Johan Wouters, Gérald Fanuel, Jean-François Drion Du Chapois, Anne Gallez, Stéphane Pire-Stevenne, Gaëtan Rochez, Johan Yans

International Journal of Speleology

The Cigalère Cave is a 21 km-long karstic cave located in the Ariège Department, in the French Pyrenees, and underlies directly the Bentaillou Pb-Zn-Fe sulfide ores. The cave hosts abundant gypsum mineralizations, some of them exhibiting various colorations including blue, yellow, purple, orange and black. Due to strict preservation policies, these colored mineralizations have not been studied much. Here we propose a non-destructive characterization of five distinct gypsum or carbonate speleothem structures from the Cigalère, exhibiting different colorations. To comply with the preservation policies, no sample was taken from the cave, and all speleothems were analyzed in situ using portable …

Lorawan-Based Asset Tracking System Development And Performance Analysis Within Stem-Pbl Framework: A Mixed-Method Study, Yousef Alfarraj, Ghada Abdelhady, Abdelrahman Ahmed, Mahmoud Elaasar, Jair J. Aguilar

Teaching and Learning Faculty Publications

This study examines the integration of project-based learning (PBL) within the integrative STEM framework to advance practical problem-solving skills and investigate students' perceptions of the STEM-PBL approach through developing an IoT-enabled asset tracking system using Long-Range Wide Area Network (LoRaWAN) technology to tackle real-world logistical challenges. Adopting a mixed-methods approach, the study combines an experimental approach utilizing quantitative system performance analysis with qualitative insights gathered through participant interviews with ten graduate students. Results reveal that the LoRaWAN system demonstrated high reliability with only 0.437% downtime, validating the technical feasibility of the educational project. Furthermore, participants perceived the STEM-PBL approach positively, …

Ftc Titans #17576 2026 Engineering Portfolio, Andrew Sun '27, Ian Wang '27, Noah David '26, Aparna Sadhanagiri '26, Adam Park '28, Ajay Srinivasan '28

Distinguished Student Work

FTC Robotics is a program for students to engage with designing, assembling, and driving an 18x18x18' robot to compete in local, regional, and state competitions. During the 25/26 season, we reached over 150k+ individuals, connected with 36 STEM professionals, helped mentor 11 robotics teams, and curated an Instagram page with over 360k+ views. The team was the Reach award winner at the regional level and was first pick on the Winning Alliance. Then, at the Illinois State Championship, we were 3rd place in qualification matches and reached Semifinalist in the elimination rounds. The 25/26 season, in terms of overall OPR …

Advancing Culturally Sustaining Stem Instruction For Latinx Secondary Students: From Research To Practice Through The Monarch Migration, Maryam Saberi, Noushin Nouri

Teaching and Learning Faculty Publications

This chapter presents the development of a research-based STEM curriculum for Latinx students using Monarch butterfly migration phenomenon as context. Based on a systematic review of 196 articles, the study first maps eight STEM research categories for Latinx populations. It then conducts a meta-synthesis of 23 successful interventions to create a Latinx-Affirming STEM (La-STEM) curriculum framework organized around Akker's ten curriculum elements. Finally, it translates these theoretical foundations into practical implementation through a detailed Monarch butterfly migration curriculum. The Monarch phenomenon, chosen for its deep cultural resonance and scientific richness, demonstrates how each curriculum element can integrate STEM concepts with …

Teaching Nature Of Science (Nos) Through Cultural Windows: A Framework For Latinx Preservice Science Teachers, Noushin Nouri, Maryam Saberi

Teaching and Learning Faculty Publications

This chapter presents a comprehensive framework for teaching Nature of Science (NOS) to preservice science teachers through cultural windows, implemented through six targeted activities. The framework, developed through rigorous meta-synthesis of NOS literature and analysis of Latinx preservice teachers' autobiographies, integrates Culturally Sustaining Pedagogy (CSP) and Rightful Presence (RP) theories with NOS curriculum elements. This theoretical foundation informs the design of activities: Dolores Huerta environmental justice, Tangram exploration, historical cases, cultural picture analysis, nixtamalization black box, and family-scientist interactions. Each activity systematically maps to curriculum elements while demonstrating how the framework enables cultural knowledge integration in NOS instruction for meaningful, …

Department Of English Newsletter, Winter 2025-2026, Illinois State University, Department Of English

Department of English Newsletter

Newsletter of the Illinois State University Department of English

Parent And Family Guide, 2026-2027, Illinois State University, Dean Of Students Office, Parent And Family Services

Parent and Family Guide

Campus guide prepared by the Illinois State University Dean of Students Office's Parent and Family Services Department

Defining Clinically Meaningful Within-Patient Changes In Heart Failure: Jacc Heart Failure Position Statement, Amin Yehya, Rebecca Hahn, Barry Borlaug, Victoria Delgado, Andrew Ambrosy, Ross Arena, Nosheen Reza, Gregory Lewis, Natalie Tapaskar, Salvatore Carbone, Cynthia Chauhan, Mitchell A. Psotka, Norman Stockbridge, James Januzzi, Javed Butler, Jennifer Cowger, Biykem Bozkurt, John Spertus

Department of Medicine Faculty Publications

Heart failure (HF) clinical trials increasingly rely on diverse endpoints beyond mortality, including hospitalizations, imaging, hemodynamic status, biomarkers, functional capacity, and patient-reported outcomes. Although statistically significant differences between treatment groups are commonly reported, interpreting whether these changes are clinically meaningful for individual patients remains challenging. This JACC: Heart Failure position statement proposes a pragmatic framework for defining clinically meaningful within-patient change across commonly used HF outcomes by integrating measurement variability, prognostic associations, and patient-anchored evidence where available. Relative and absolute risk reductions should both inform interpretation of clinical events, while imaging, hemodynamic, biomarker, and functional measures require changes exceeding measurement …

High-Resolution Mapping Of Soil Moisture Variation Using Uas Thermal And Multispectral Imagery, Jackline Amma Timah

Theses and Dissertations

In agricultural landscapes, soil moisture regulates hydrologic partitioning, nutrient transport and water quality, land-atmosphere energy exchange that shapes local climate, and ecosystem resilience. However, traditional monitoring approaches, such as in-situ sensors and satellite imagery, often lack the spatial resolution required to capture fine-scale soil moisture variability. This study evaluated whether unmanned aerial system (UAS)-derived thermal, multispectral, and terrain variables can capture fine-scale spatial variability in volumetric water content (VWC) within an SRB in central Illinois.

High-resolution imagery was collected and paired with 50 field-measured VWC observations. Land surface temperature (LST), vegetation indices (NDVI and NDRE), spectral bands, and slope were …

Success Criteria: Sustainable Efficacy In Australian Farmer Groups, David K. Mckenzie, Janine Joyce, Kerstin K. Zander, Penelope A.S. Wurm, Kim M. Caudwell

Research outputs 2022 to 2026

Purpose: To examine the factors and processes that sustain the efficacy of farmer groups as extension intermediaries for influencing collective innovation, and knowledge co-creation and exchange. Design/Methodology/Approach: Data was collected from farmer interviews, focus groups, and the published digital documents of five farmer groups across SE Australia. A grounded theory mixed-methods approach was used for data collection and analysis, aided by Atlas software in constructing concepts and a concept map representing group processes. Findings: The ability of groups to influence farm innovation, and farmer learning and knowledge co-creation, depends on the group efficacy. Group identity in advancing farmer interests and …

Reflecting On Themes From Telehealth Consultations Early In The Pandemic: An Opportunity To Learn From Multiprofessional Colleagues, Maggie Meeks, Laura R. Joyce, John Dean, Lorna Davies, Tika Ormond, Philippa Seaton, Dale Sheehan, Dean Sutherland, Melanie Welfare, Arindam Basu

Research outputs 2022 to 2026

Aims: This study is aimed at documenting the reflections of New Zealand healthcare professionals on the use of synchronous telehealth consultations. Methods: A qualitative narrative inquiry was conducted to explore the practice of telehealth in New Zealand. Purposive sampling was used to identify clinicians from multiple professions who used telehealth during the initial phase of the COVID-19 pandemic. Fifteen semistructured interviews were conducted between October 2020 and May 2021 with clinicians from primary and secondary care, including multiple professional backgrounds. Interview transcripts were analysed thematically. Results: Six themes were identified: (1) equitable access: There were concerns regarding equitable access to …

Optimizing Subgroup Selection In Petrochemical Industries: A Robust Data Envelopment Analysis Approach For Uncertainty Management, Sadegh Niroomand, Hilda Saleh, Morteza Shafiee, Dragan Pamucar, Ali Mahmoodirad

Research outputs 2022 to 2026

This study addresses the critical challenge faced by organizations in selecting an optimal subgroup of decision-making units (DMUs). Such a selection procedure can significantly influence efficiency, profitability, and strategic development. Recognizing the limitations of existing methods in handling inexact data and incorporating managerial preferences, this study proposes a novel framework that integrates data envelopment analysis (DEA) with binary linear programming models. The model applies belief-degree–based representations of uncertainty to capture imprecise inputs and outputs. For this model, two solution approaches—namely, chance-constrained programming and expected value approaches—were developed. These approaches are suitable for real-world applications using standard optimization software. The effectiveness …

Multi-Scale Sensor-Aware Variational Autoencoders For Adaptive Iot Security: Integrating Drift Calibration And Cyberattack Detection, Md Kamal Hossain, Iftekhar Ahmad, Daryoush Habibi

Research outputs 2022 to 2026

Existing approaches to Industrial Internet of Things (IoT) anomaly detection treat sensor drift calibration and cyberattack detection as separate problems, overlooking their strong interdependence and the compound failure modes that arise when drift dynamics are exploited by stealthy adversaries. Industrial Internet of IoT sensor networks therefore require a unified framework that jointly models both phenomena. This paper proposes the first unified multi-scale sensor-aware variational autoencoder (MS-VAE) framework that jointly models sensor drift and malicious activity within shared latent representations, enabling integrated calibration and security monitoring. The framework introduces three key components: (i) a multi-scale latent architecture that captures short-term anomalies …

Rrto: A High-Performance Transparent Offloading System For Model Inference In Mobile Edge Computing, Zekai Sun, Xiuxian Guan, Zheng Lin, Yuhao Qing, Haoze Song, Zihan Fang, Zhe Chen, Fangming Liu, Heming Cui, Wei Ni, Jun Luo

Research outputs 2022 to 2026

Deploying Machine Learning (ML) applications on resource-constrained mobile devices remains challenging due to limited computational resources and poor platform compatibility. While Mobile Edge Computing (MEC) offers an offloading-based inference paradigm using GPU servers, existing approaches can be divided into non-transparent and transparent methods, with the former necessitating source-code modifications. Non-transparent offloading achieves high performance but requires intrusive code changes, limiting compatibility with diverse applications. Transparent offloading, in contrast, offers wide compatibility but introduces two challenges: performance degradation under MEC's low and fluctuating bandwidth, where per-operator remote procedure calls (RPCs) inflate end-to-end latency and energy consumption; and black-box logic reconstruction, which …

Bitcoin Halving: How Effective Is It In Driving Cryptocurrency Market Dynamics?, Nyoman Sri Subawa, Caren Angellina Mimaki, I. Made Oka Mahendra, Made Srinitha Millinia Utami

Research outputs 2022 to 2026

Bitcoin halving is a quadrennial event that halves mining rewards and is believed to influence cryptocurrency prices and cryptocurrency market dynamics. This study examines the effect of Bitcoin halving on Cryptocurrency Prices, with Government Regulations, Market Sentiment, and Cryptocurrency Performance as mediating variables. A quantitative research approach was employed, gathering original data via survey instruments from 294 participants within the cryptocurrency community in Bali, which were analyzed using PLS-SEM. The findings indicate that Bitcoin halving exerts a favorable and statistically meaningful influence on Government Regulations, Market Sentiment, Cryptocurrency Performance, and Cryptocurrency Prices. Market Sentiment fully mediates the influence of Government …

Sparse Gradient Training For Recommender Systems, Yunke Qu, Liang Qu, Tong Chen, Xiangyu Zhao, Jianxin Li, Hongzhi Yin

Research outputs 2022 to 2026

Recommender systems are widely applied in numerous online platforms such as shopping and social media platforms. They typically utilize large embedding tables that map users and items to dense vectors of uniform sizes. As the number of users and items continues to grow, this design leads to significant memory consumption and computational inefficiencies. This challenge is particularly pronounced in scenarios such as federated learning, where model parameters are updated locally on edge devices with limited computational resources before being transmitted to a central server for aggregation. Numerous approaches have been proposed to address this issue, among which embedding pruning methods …

Sensing-Then-Beamforming: Robust Transmission Design For Ris-Empowered Integrated Sensing And Covert Communication, Xingyu Zhao, Min Li, Ming Min Zhao, Shihao Yan, Min Jian Zhao

Research outputs 2022 to 2026

Traditional covert communication often relies on the knowledge of the warden's channel state information, which is inherently challenging to obtain due to the non-cooperative nature and potential mobility of the warden. The integration of sensing and communication technology provides a promising solution by enabling the legitimate transmitter to sense and track the warden, thereby enhancing transmission covertness. In this paper, we develop a framework for sensing-then-beamforming in reconfigurable intelligent surface (RIS)-empowered integrated sensing and covert communication (ISACC) systems, where the transmitter (Alice) estimates and tracks the mobile aerial warden's channel using sensing echo signals while simultaneously sending covert information to …

Experimental Investigation And Performance Optimization Of A Double Slope Solar Still Integrated With Nanoparticles In Phase Change Materials, Pronob Das, Md Shahriar Mohtasim, Utpol K. Paul, Md Sanowar Hossain, Barun K. Das, Anik Saha, Md Golam Kibria

Research outputs 2022 to 2026

By utilizing solar energy for desalination, solar stills offer a sustainable and cost-effective means of providing fresh drinking water in remote and arid regions. Existing studies have primarily focused on improving freshwater productivity while considering economic and environmental feasibility. The present work offers an in-depth assessment of solar still (SS) systems by analyzing energy and exergy performance, exergoeconomic factors (energy-economic factor, exergoeconomic factor, and cost of water), environmental impacts (CO2 emissions, exergo-environmental factor, and carbon credit gained), and sustainability indicators (energy payback time and sustainability index). Five different cases were examined: (I) a conventional solar still (CSS), (II) CSS with …

Rapid Classification And Quality Assessment Of Citrus Essential Oils Via Machine-Learning-Assisted Raman Spectroscopy, Yong Xuan Hong, Jia Wei Tang, Jie Chen, Yun Yun Xie, Zhang Wen Ma, Qing Hua Liu, Liang Wang

Research outputs 2022 to 2026

Citrus essential oils (EOs) require accurate identification and assessment to ensure authenticity and consistency. However, conventional techniques such as gas chromatography (GC) and mass spectrometry (MS) are time-consuming and expensive, highlighting the need for novel analytical methods. This study proposes an approach for EOs detection using Raman spectroscopy (RS) combined with machine learning (ML) algorithms. Six citrus EOs underwent an evaporation experiment, with Raman spectra collected at five time points and GC-MS was used to analyze compositional changes at the starting and ending points of evaporation as a standard reference. Five ML algorithms were developed to identify differences among EOs …

Sexisms And Gender-Washing In Australian Academia: Public Front, Private Realities, Jacqueline Ullman, Emily Gray, Mindy Blaise, Lucy Hobby

Research outputs 2022 to 2026

This paper offers an analysis of selected survey findings from a mixed methods research project, entitled Understanding and Addressing Everyday Sexisms in Australian Universities. The project is situated within the context of the negative impact of gender-based discrimination upon the higher education sector in Australia and internationally. The findings discussed in this paper relate to quantitative analyses of selected items from a national survey of over 1200 Australian academics, recruited through 12 public universities. In this paper, the ways in which different participant groups responded to items designed to explore their attitudes towards sexism in the academic workplace, both broadly …

The Strategic Competence Of Secondary Mathematics Teachers Solving Algebraic Word Problems, Vesife Hatisaru, Steven Richardson, Helen Chick, John Sevier

Research outputs 2022 to 2026

We examined the strategic competence of 22 secondary mathematics teachers by considering their solutions to an algebraic word problem involving simultaneous equations. The analyses have shown that although the majority could solve the problem, the strategic competence of the participants varied, with some teachers having greater fluency with an algebraic solution, and the others less likely to address simultaneity. Overall, many of the teachers had relatively limited capacity to identify additional solution approaches. The study highlights the usefulness of a strategic competence scheme with key indicators that may reveal areas for further teacher development, with the specific findings suggesting the …

A Novel Hybrid Robust Transfer Learning-Based Adaptive Fractional-Order Super-Twisting Sliding Mode Controller Enhanced For Speed Regulation Of Brushless Dc Motor, Seyyed Morteza Ghamari, Asma Aziz, Daryoush Habibi

Research outputs 2022 to 2026

Brushless DC (BLDC) motors are widely used in applications that are highly-efficient, reliable, and compact, such as electric vehicles, robotics, and medical devices. However, the inherent nonlinearities and load sensitivity of BLDC motors require a robust and adaptive control strategy to ensure satisfactory performance under various operating conditions. Sliding mode control (SMC) has been widely used for the BLDC drives. However, because of its simplicity and robustness, the control effectiveness of the control is limited by the sensitivity to the disturbances and the chattering phenomenon. To remedy this, super-twisting (ST) technique has been proposed to achieve smoother response and better …