Digital Commons Network^™

Detection And Monitoring Of Stress Using Wearables: A Systematic Review, Anuja Pinge, Vinaya Gad, Dheryta Jaisinghani, Surjya Ghosh, Sougata Sen

Faculty Publications

Over the last few years, wearable devices have witnessed immense changes in terms of sensing capabilities. Wearable devices, with their ever-increasing number of sensors, have been instrumental in monitoring human activities, health-related indicators, and overall wellness. One health-related area that has rapidly adopted wearable devices is the mental health monitoring and well-being area, which covers problems such as psychological distress. The continuous monitoring capability of wearable devices allows the detection and monitoring of stress, thus enabling early detection of mental health problems. In this paper, we present a systematic review of the different types of sensors and wearable devices used …

Mental Health Care Disparities Among Us Pregnant Individuals In 2020–2021: A Cross-Sectional Study, Julisa Tindall, Monique J. Brown Ph.D., Mph, Peiyin Hung

Faculty Publications

Purpose

To examine maternal characteristics associated with perceived unmet mental health needs and mental health care settings, focusing on residential rurality and race/ethnicity.

Methods

This cross-sectional study analyzed self-reported unmet mental health needs and mental health care settings among 1097 pregnant respondents in the 2020–2021 National Survey on Drug Use and Health, incorporating the complex sampling weights for national representativeness.

Findings

Non-Hispanic Black pregnant individuals and those living in nonmetro rural areas reported lower odds of unmet mental health needs compared to those in large metro areas and non-Hispanic White individuals. Pregnant individuals in nonmetro rural areas and non-Hispanic other …

Organic Alkalinity Distributions, Characteristics, And Application To Carbonate System Calculations In Estuarine And Coastal Systems, Christopher W. Hunt, Joseph Salisbury, Xuewu Liu, Robert H. Byrne

Faculty Publications

The capacity of aquatic systems to buffer acidification depends on the sum contributions of various chemical species to total alkalinity (TA). Major TA contributors are inorganic, with carbonate and bicarbonate considered the most important. However, growing evidence shows that many rivers, estuaries, and coastal waters contain dissolved organic molecules with charge sites that create organic alkalinity (OrgAlk). This study describes the first comparison of (1) OrgAlk distributions and (2) acid–base properties in contrasting estuary-plume systems: the Pleasant (Maine, USA) and the St. John (New Brunswick, CA). The substantial concentrations of OrgAlk in each estuary were sometimes not conservative with salinity …

Verbal Working Memory And Syntactic Comprehension Segregate Into The Dorsal And Ventral Streams, Respectively, William Matchin, Zeinab K. Mollasaraei, Leonardo Bonilha, Chris Rorden, Gregory Hickok, Dirk Den Ouden, Julius Fridriksson Ph.D.

Faculty Publications

Syntactic processing and verbal working memory are both essential components to sentence comprehension. Nonetheless, the separability of these systems in the brain remains unclear. To address this issue, we performed causal-inference analyses based on lesion and connectome network mapping using MRI and behavioural testing in two groups of individuals with chronic post-stroke aphasia. We employed a rhyme judgement task with heavy working memory load without articulatory confounds, controlling for the overall ability to match auditory words to pictures and to perform a metalinguistic rhyme judgement, isolating the effect of working memory load (103 individuals). We assessed non-canonical sentence comprehension, isolating …

New Insights Into Supradense Matter From Dissecting Scaled Stellar Structure Equations, Bao-Jun Cai, Bao-An Li

Faculty Publications

The strong-field gravity in general relativity (GR) realized in neutron stars (NSs) renders the equation of state (EOS) P(ε) of supradense neutron star matter to be essentially nonlinear and refines the upper bound for ϕ≡P/ε to be much smaller than the special relativity (SR) requirement with linear EOSs, where P andεare respectively the pressure and energy density of the system considered. Specifically, a tight bound ϕ ≲ 0.374 is obtained by perturbatively anatomizing the intrinsic structures of the scaled Tolman–Oppenheimer–Volkoff (TOV) equations without using any input nuclear EOS. New insights gained from this novel analysis provide EOS-model-independent constraints on the …

Na2B12Si6Se18: A Novel B12-Cluster-Containing Quaternary Selenoborate Framework Material, Gopabandhu Panigrahi, Hunter B. Tisdale, Gregory Morrison, Hans Conrad Zur Loye

Faculty Publications

We report the successful synthesis of the new quaternary, three-dimensional Na₂B₁₂Si₆Se₁₈ material using a solid-state synthesis route. This compound is characterized by a unique framework structure that features the rare icosahedral [B₁₂]¹⁰⁺ cation which is connected via Si2Se6 polyhedral units into a 3D framework structure with Na+ ions located inside the channels. The Na₂B₁₂Si₆Se₁₈ compound crystallizes in the cubic crystal system in the space group Im, with lattice parameter a = 11.91110(10) Å and unit cell volume of 1689.88(4) ų. …

How Should Scientists Act? Assessing Public Perceptions Of Scientists And Scientific Practices And Their Implications For Science Communication, Thomas G. Safford, Emily H. Whitmore

Faculty Publications

Is how science is conducted legitimate? Are scientists trustworthy? Whether the public answers “yes” to these questions is critical for science communicators. We explore how social factors affect public perceptions of the practice of science, and then test how those beliefs relate to views about how scientists engage with the public and policy making. Our results show that political ideology and religiosity affect these views. However, more importantly, respondents’ concerns about the integrity of the scientific process are the strongest predictor of views about scientists’ behavior, providing a focus area for future communication efforts in support of science-based decision making.

Ultraviolet And Blue Stimulated Emission From Cs Alkali Vapor Pumped Using Two-Photon Absorption And Four-Wave Mixing, Ricardo C. Davila, Christopher A. Rice, Nathan B. Terry, Glen P. Perram

Faculty Publications

Stimulated emission on the ultraviolet and blue transitions in Cs has been achieved by pumping via two-photon absorption and four-wave mixing for the pump transition 6²S½ → 8²D_3/2,5/2. The emission performance of the optically pumped cesium vapor laser operating in ultraviolet and blue has been extended to 650 nJ/pulse for 387 nm, 1 to 3 μ J / pulse for 388 nm, 200 nJ/pulse for 455 nm, and 500 nJ/pulse for 459 nm. Emission performance improves dramatically as the cesium vapor density is increased, and no scaling limitations associated with energy pooling or …

Machine Visual Perception From Sim-To-Real Transfer Learning For Autonomous Docking Maneuvers, Derek Worth, Jeffrey Choate, Ryan M. Raettig, Scott L. Nykl, Clark N. Taylor

Faculty Publications

This paper presents a comprehensive approach to enhancing autonomous docking maneuvers through machine visual perception and sim-to-real transfer learning. By leveraging relative vectoring techniques, we aim to replicate the human ability to execute precise docking operations. Our study focuses on autonomous aerial refueling as a use case, demonstrating significant advancements in relative navigation and object detection. We introduce a novel method for aligning digital twins using fiducial targets and motion capture data, which facilitates accurate pose estimation from real-world imagery. Additionally, we develop cost-efficient annotation automation techniques for generating high-quality You Only Look Once training data. Experimental results indicate that …

The Impacts Of Co-Occurring Developmental Language Disorder On The Academic, Interpersonal, And Behavioral Profiles Of Children With Adhd, Kirsten M. Hannig Russell, Sean M. Redmond

Faculty Publications

Purpose: Attention-deficit/hyperactivity disorder (ADHD) is a multifactorial disorder that has been linked to increased risk for behavioral, academic, and interpersonal problems. Developmental language disorder (DLD) has also been linked to poor outcomes in these areas. The presence of co-occurring disorders in children’s profiles is generally associated with poorer outcomes relative to profiles consisting of only one disorder. This study investigated the extent to which co-occurring DLD in children already identified with ADHD presented increased risk for severity of their primary ADHD symptoms, the presence of secondary behavioral problems, and/or increased problems in the tertiary areas of academic performance and interpersonal …

Everyone Brings Something To The Table: A Culturally Sustaining Analysis Of Teacher Candidates’ Mixed Reality Teaching Simulations, Erin Scott

Faculty Publications

Discussions of HBCU students’ content knowledge have centered around developing high impact, asset-based approaches to learning (Williams et al, 2022). So, HBCU teacher preparation providers (TPPs) can also focus efforts on culturally sustaining approaches to developing candidates’ content knowledge and researching how high impact practices, like teaching simulations, can help prepare candidates for classrooms. This exploratory case study uses critical cases (n=2); findings suggest candidates have a developing understanding of content, which forms a solid basis for increasing their knowledge. MRTSs are addressed as a potential high impact, culturally sustaining practice for building candidates’ content knowledge. Further, HBCU TPPs can …

Net Evaporation-Induced Mangrove Area Loss Across Low-Lying Caribbean Islands, Isamar M. Cortés, Jorge Lorenzo-Trueba, Andre S. Rovai, Robert R. Twilley, Mark Chopping, Temilola Fatoyinbo

Faculty Publications

Although mangroves provide many beneficial ecosystem services, such as blue carbon storage and coastal protection, they are currently under threat due to changes in climate conditions, such as prolonged drought exposure. Under drought conditions, evaporation exceeds precipitation and high soil salinities can lead to stunted growth and die-back. To quantify this interplay, we developed a database for low-lying and uninhabited mangrove islands in the Caribbean under various evaporation and precipitation regimes. We extracted physical and biological information from each island using remote sensing techniques and coupled it with a process-based model. We used this database to develop a model that …

A Temperature Tipping Point In Hypoxic Zone Size, R. Eugene Turner, Nancy N. Rabalais, Cassandra N. Glaspie

Faculty Publications

Temperature increases will have ubiquitous effects on aquatic food webs, from microbes to consumers, and affect the quality and quantity of carbon flows within and between water layers. A decline in the biological pump moving carbon from surface to lower layers is anticipated. We reviewed 37 years of data on hypoxic zone size and water quality in the northern Gulf of Mexico to determine if air and bottom water temperature increases (0.5°C decade⁻¹) are significantly related to variations in its areal size. There was no significant decline in important river water quality in the 24 years since the …

Detecting, Attributing, And Projecting Global Marine Ecosystem And Fisheries Change: Fishmip 2.0, Julia L. Blanchard, Camilla Novaglio, Olivier Maury, Cheryl S. Harrison, Colleen M. Petrik, Denisse Fierro-Arcos, Kelly Ortega-Cisneros, Andrea Bryndum-Buchholz, Tyler D. Eddy, Ryan Heneghan, Kelsey Roberts, Jacob Schewe, Daniele Bianchi, Jerome Guiet, P. Daniel Van Denderen, Juliano Palacios-Abrantes, Xiao Liu, Charles A. Stock, Yannick Rousseau, Matthias Büchner, Ezekiel O. Adekoya, Cathy Bulman, William Cheung, Villy Christensen, Marta Coll, Leonardo Capitani, Samik Datta, Elizabeth A. Fulton, Alba Fuster, Victoria Garza, Matthieu Lengaigne, Max Lindmark, Kieran Murphy

Faculty Publications

There is an urgent need for models that can robustly detect past and project future ecosystem changes and risks to the services that they provide to people. The Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) was established to develop model ensembles for projecting long-term impacts of climate change on fisheries and marine ecosystems while informing policy at spatio-temporal scales relevant to the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) framework. While contributing FishMIP models have improved over time, large uncertainties in projections remain, particularly in coastal and shelf seas where most of the world's fisheries occur. Furthermore, previous FishMIP climate …

Periodic Gamma-Ray Modulation Of The Blazar Pg 1553+113 Confirmed By Fermi-Lat And Multiwavelength Observations, S. Abdollahi, L. Baldini, G. Barbiellini, R. Bellazzini, B. Berenji, E. Bissaldi, R. D. Blandford, R. Bonino, P. Bruel, S. Buson, R. A. Cameron, P. A. Caraveo, F. Casaburo, E. Cavazzuti, C. C. Cheung, G. Chiaro, S. Ciprini, G. Cozzolongo, P. Cristarella Orestano, S. Cutini, F. D’Ammando, N. Di Lalla, F. Dirirsa, L. Di Venere, A. Domínguez, S. J. Fegan, E. C. Ferrara, A. Fiori, Y. Fukazawa, S. Funk, P. Fusco, F. Gargano, S. Garrappa

Faculty Publications

A 2.1 yr periodic oscillation of the gamma-ray flux from the blazar PG 1553+113 has previously been tentatively identified in ∼7 yr of data from the Fermi Large Area Telescope. After 15 yr of Fermi sky-survey observations, doubling the total time range, we report >7 cycle gamma-ray modulation with an estimated significance of 4σ against stochastic red noise. Independent determinations of oscillation period and phase in the earlier and the new data are in close agreement (chance probability < 0.01). Pulse timing over the full light curve is also consistent with a coherent periodicity. Multiwavelength new data from Swift X-Ray Telescope, Burst Alert Telescope, and UVOT, and from KAIT, Catalina Sky Survey, All-Sky Automated Survey for Supernovae, and Owens Valley Radio Observatory ground-based observatories as well as archival Rossi X-Ray Timing Explorer satellite-All Sky Monitor data, published optical data of Tuorla, and optical historical Harvard plates data are included in our work. Optical and radio light curves show clear correlations with the gamma-ray modulation, possibly with a nonconstant time lag for the radio flux. We interpret the gamma-ray periodicity as possibly arising from a pulsational accretion flow in a sub-parsec binary supermassive black hole system of elevated mass ratio, with orbital modulation of the supplied material and energy in the jet. Other astrophysical scenarios introduced include instabilities, disk and jet precession, rotation or nutation, and perturbations by massive stars or intermediate-mass black holes in polar orbit.

Global Well-Posedness For Supercritical Sqg With Perturbations Of Radially Symmetric Data, Aynur Bulut, Hongjie Dong

Faculty Publications

We study the global well-posedness of the supercritical dissipative surface quasi-geostrophic (SQG) equation, a key model in geophysical fluid dynamics. While local well-posedness is known, achieving global well-posedness for large initial data remains open. Motivated by enhanced decay in radial solutions, we aim to establish global well-posedness for small perturbations of potentially large radial data. Our main result shows that for small perturbations of radial data, the SQG equation admits a unique global solution.

Introducing The Second-Order Features Adjoint Sensitivity Analysis Methodology For Neural Ordinary Differential Equations—Ii: Illustrative Application To Heat And Energy Transfer In The Nordheim–Fuchs Phenomenological Model For Reactor Safety, Dan Gabriel Cacuci

Faculty Publications

This work presents an illustrative application of the newly developed “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-FASAM-NODE)” methodology to determine most efficiently the exact expressions of the first- and second-order sensitivities of NODE decoder responses to the neural net’s underlying parameters (weights and initial conditions). The application of the 2nd-FASAM-NODE methodology will be illustrated using the Nordheim–Fuchs phenomenological model for reactor safety, which describes a short-time self-limiting power transient in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted. The representative model responses that will …

Introducing The Second-Order Features Adjoint Sensitivity Analysis Methodology For Neural Ordinary Differential Equations—I: Mathematical Framework, Dan Gabriel Cacuci

Faculty Publications

This work introduces the mathematical framework of the novel “First-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations” (1st-FASAM-NODE). The 1st-FASAM-NODE methodology produces and computes most efficiently the exact expressions of all of the first-order sensitivities of NODE-decoder responses with respect to the parameters underlying the NODE’s decoder, hidden layers, and encoder, after having optimized the NODE-net to represent the physical system under consideration. Building on the 1st-FASAM-NODE, this work subsequently introduces the mathematical framework of the novel “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-FASAM-NODE)”. The 2nd-FASAM-NODE methodology efficiently computes the exact expressions …

Cgbi_Yolo: Lightweight Land Target Detection Network, Ruiyang Wang, Siyu Lu, Jiawei Tian, Lirong Yin, Lei Wang, Xiaobing Chen, Wenfeng Zheng

Faculty Publications

Object detection algorithms for optical remote sensing images often face challenges in computational efficiency, particularly when detecting small and densely packed targets. This paper introduces CGBi_YOLO, a novel lightweight land target detection network designed to optimize computational resource utilization while maintaining detection capabilities for small-scale targets. Our approach incorporates an innovative lightweight optimization strategy featuring a new lightweight backbone feature extraction network: CSPGhostNet. This model significantly enhances the detection ability of small objects within optical remote sensing images without increasing computational demands. The efficacy of the proposed model is validated through rigorous experimentation on the DOTA dataset. Compared to the …

Research Overview On Urban Heat Islands Driven By Computational Intelligence, Chao Liu, Siyu Lu, Jiawei Tian, Lirong Yin, Lei Wang, Wenfeng Zheng

Faculty Publications

In recent years, the intensification of the urban heat island (UHI) effect has become a significant concern as urbanization accelerates. This survey comprehensively explores the current status of surface UHI research, emphasizing the role of land use and land cover changes (LULC) in urban environments. We conducted a systematic review of 8260 journal articles from the Web of Science database, employing bibliometric analysis and keyword co-occurrence analysis using CiteSpace to identify research hotspots and trends. Our investigation reveals that vegetation cover and land use types are the two most critical factors influencing UHI intensity. We analyze various computational intelligence techniques, …

Investigation Of Magnesium-Potassium Phosphates As Potential Nuclear Waste Form For The Immobilization Of Minor Actinides, Hans Conrad Zur Loye, Petr Vecernik, Monika Kiselova, Vlastislav Kašpar, Hana Korenkova, Vlastimil Miller, Petr Bezdicka, Jan Šubrt, Natalija Murafa, Volodymyr Shkuropatenko, Sergey Sayenko

Faculty Publications

Several recent studies have evaluated technologies of spent nuclear fuel processing specifically for solidifying transuranic (TRU) waste as a by-product of fission. Of the TRU group, plutonium and the minor actinides will be responsible for the bulk of the radiotoxicity and heat generation of spent nuclear fuel in the long term (300 to 20,000 years). In this study, we investigated magnesium potassium phosphate (MKP)-based compounds as host waste forms for the encapsulation of inactive trivalent Nd and Sm as analogues of the minor trivalent actinides, Am and Cm. Waste forms were fabricated under ambient atmospheric conditions by adding 5 wt.% …

Temporal Metadata Analysis: A Learning Classifier System Approach, Michael C. Todd, Gilbert L. Peterson

Faculty Publications

Digital forensics is a complex field that requires expert knowledge (EK) and specialized tools to collect, analyze, and report on digital evidence. Temporal metadata analysis is particularly challenging, requiring expert knowledge to understand and interpret underlying traces and associate them with their source. This paper introduces Digital Trace Inspector (DTI), a Learning Classifier System (LCS)-based decision support tool for temporal metadata analysis. DTI leverages a binary Michigan-style LCS to locate and group corroborating temporal digital traces of targeted user activity. Rules are built from expert-created atomics encoded as feature vectors using patterns defined in a structured EK rule framework. The …

A Study Of The Near-Surface Vertical Distribution And Chemistry Of Pollutants In Cold-Climate Urban Areas With The Novel Pact-1d Model, Jonas Kuhn, Jochen Stutz, Meeta Cesler-Maloney, William R. Simpson, Thorsten Bartels-Rausch, Tjarda J. Roberts, Jennie L. Thomas, Jack E. Dibb, Laura Heinlein, Michael O. Sunday, Cort Anastasio, Kathleen Fahey, James H. Flynn, Fangzhou Guo

Faculty Publications

Cold-climate urban areas often face severe air pollution events in wintertime because of residential heating and vehicle emissions into shallow surface inversion layers. Many state-of-the-art regional chemistry-transport models cannot capture the small spatio-temporal scale of the transport and chemical processes occurring in these environments.Here we introduce a new version of our one-dimensional atmospheric chemistry and transport model, PACT-1D that includes continuous exchange of atmospheric air with the interstitial air of a snow layer and a kinetic treatment of multi-phase chemical processes in air and snow. PACT-1D allows modeling and assessment of the interaction of transport, chemistry, and emissions on the …

Monte Carlo Error Analysis Of Lightning Interferometry With Lofar, Paulina Turekova, Brian Hare, Olaf Scholten, Steven Cummer, Joseph Dwyer, Ningyu Liu, Chris Sterpka, Sander Ter Veen

Faculty Publications

The LOFAR radio telescope works on a principle of radio interferometric imaging. It coherently sums the signal of hundreds of antennas in northern Netherlands, covering the 30-80 MHz window of the very high frequency (VHF) band of 30-300 MHz. We are using the TRI-D algorithm to extract 3-D polarization data of a lightning flash observed by LOFAR. TRI-D functions by coherently summing recorded voltages, accounting for the antenna function, polarization, and geometric time delay for each voxel. The result is split into time slices. A coherent intensity is calculated for each time slice, and the maximum of this value is …

Spatial Pattern And Differential Expression Analysis With Spatial Transcriptomic Data, Fei Qin, Xizhi Luo, Bo Cai Ph.D., Feifei Xiao, Guoshuai Cai

Faculty Publications

The emergence of spatial transcriptomic technologies has opened new avenues for investigating gene activities while preserving the spatial context of tissues. Utilizing data generated by such technologies, the identification of spatially variable (SV) genes is an essential step in exploring tissue landscapes and biological processes. Particularly in typical experimental designs, such as case-control or longitudinal studies, identifying SV genes between groups is crucial for discovering significant biomarkers or developing targeted therapies for diseases. However, current methods available for analyzing spatial transcriptomic data are still in their infancy, and none of the existing methods are capable of identifying SV genes between …

A Study Of The Near-Surface Vertical Distribution And Chemistry Of Pollutants In Cold-Climate Urban Areas With The Novel Pact-1d Model, Jonas Kuhn, Jochen Stutz, Meeta Cesler-Maloney, William R. Simpson, Thorsten Bartels-Rausch, Tjarda J. Roberts, Jennie L. Thomas, Jack E. Dibb, Laura Heinlein, Michael O. Sunday, Cort Anastasio, Kathleen Fahey, James H. Flynn, Fangzhou Guo

Faculty Publications

Cold-climate urban areas often face severe air pollution events in wintertime because of residential heating and vehicle emissions into shallow surface inversion layers. Many state-of-the-art regional chemistry-transport models cannot capture the small spatio-temporal scale of the transport and chemical processes occurring in these environments.Here we introduce a new version of our one-dimensional atmospheric chemistry and transport model, PACT-1D that includes continuous exchange of atmospheric air with the interstitial air of a snow layer and a kinetic treatment of multi-phase chemical processes in air and snow. PACT-1D allows modeling and assessment of the interaction of transport, chemistry, and emissions on the …

Monte Carlo Error Analysis Of Lightning Interferometry With Lofar, Paulina Turekova, Brian Hare, Olaf Scholten, Steven Cummer, Joseph Dwyer, Ningyu Liu, Chris Sterpka, Sander Ter Veen

Faculty Publications

The LOFAR radio telescope works on a principle of radio interferometric imaging. It coherently sums the signal of hundreds of antennas in northern Netherlands, covering the 30-80 MHz window of the very high frequency (VHF) band of 30-300 MHz. We are using the TRI-D algorithm to extract 3-D polarization data of a lightning flash observed by LOFAR. TRI-D functions by coherently summing recorded voltages, accounting for the antenna function, polarization, and geometric time delay for each voxel. The result is split into time slices. A coherent intensity is calculated for each time slice, and the maximum of this value is …

Bound States And Particle Production By Breather-Type Background Field Configurations, Abhishek Rout, Brett Altschul

Faculty Publications

We investigate the interaction of fermion fields with oscillating domain walls, inspired by breather-type solutions of the sine-Gordon equation, a nonlinear system of fundamental importance. Our study focuses on the fermionic bound states and particle production induced by a time-dependent scalar background field. The fermions couple to two domain walls undergoing harmonic motion, and we explore the resulting dynamics of the fermionic wave functions. We demonstrate that while fermions initially form bound states around the domain walls, the energy provided by the oscillatory motion of the scalar field induces an outward flux of fermions and antifermions, leading to particle production …

Effective Support Strategies Serving Diverse Teacher Candidates In Paraprofessional Teacher Education Programs, Angela Christine Griner, Debra K. Wellman

Faculty Publications

Paraprofessionals remain a rich resource for our children and our school communities. Teacher education programs that have sought to provide pathways to teaching certification for paraprofessionals recognize this. Over the last 25 years, research has shown well-documented models for programs and strategies that support candidates in these programs, as well as the obstacles and challenges those programs and participants face. This article presents a descriptive case study of the first three years of a para-to-teacher program, across three cohorts of participants at a small liberal arts institution. Implications for best practices tied to collaborative leadership, relational approaches, and collaborative program …

Applying Machine‐Learning Methods To Laser Acceleration Of Protons: Lessons Learned From Synthetic Data, Ronak Desai, Thomas Zhang, J. J. Felice, Ricky Oropeza, Joseph R. Smith, Alona Kryshchenko, Chris Orban, Michael L. Dexter, Anil K. Patnaik

Faculty Publications

In this study, we consider three different machine-learning methods—a three-hidden-layer neural network, support vector regression, and Gaussian process regression—and compare how well they can learn from a synthetic data set for proton acceleration in the Target Normal Sheath Acceleration regime. The synthetic data set was generated from a previously published theoretical model by Fuchs et al. 2005 that we modified. Once trained, these machine-learning methods can assist with efforts to maximize the peak proton energy, or with the more general problem of configuring the laser system to produce a proton energy spectrum with desired characteristics. In our study, we focus …