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- Creator:
- Chen, Hongfan, Sachdeva, Nishtha, Huang, Zhenguang, van der Holst, Bart, Manchester, Ward, Jivani, Aniket, Zou, Shasha, Chen, Yang, Huan, Xun, and Toth, Gabor
- Description:
- In this study, we show that coronal mass ejection (CME) simulations conducted with the Space Weather Modeling Framework (SWMF) can be assimilated with SOHO LASCO white-light (WL) coronagraph observations and solar wind observations at L1 prior to the CME eruption to improve the prediction of CME arrival time. L1 observations are used to constrain the background solar wind, while LASCO coronagraph observations filter the initial ensemble simulations by constraining the simulated CME propagation speed. We then construct probabilistic predictions for CME arrival time using the data-assimilated ensemble. Scripts in this work are written in R, Python and Julia.
- Keyword:
- Data Assimilation, Uncertainty Quantification, and Space Weather
- Discipline:
- Engineering
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- Creator:
- Sulkowski, Brendan and Collette, Matthew
- Description:
- This data set supports the published four-component integration problem using real-world weather forecasts from the European Centre for Medium-Range Weather Forecast and a simulated linear spring--mass--damper system excited by wave elevation. Each component in the spring--mass--damper system is monitored with techniques of differing accuracies representative of marine-type health uncertainties. Weather forecast uncertainty is included using weather predictions of significant wave height and peak period up to 10 days out. As well as their exact values, different test cases include the spring, mass, and damper being modeled as noisy sensors representative of sensors onboard a vessel, as well as the spring being modeled as a visually-inspected system component reflective of human impact onboard a vessel. Complete details are given in the referenced paper; this data set represents the inputs to the machine learning classifiers discussed.
- Keyword:
- Machine Learning, Inspection, Marine system, and Weather forecast
- Citation to related publication:
- Sulkowski, B and M. Collette. (2025) A comparison of machine learning classifiers in predicting safety for a multi-component dynamic system representation of an autonomous vessel. Applied Ocean Research, 154 (104368), https://doi.org/10.1016/j.apor.2024.104368
- Discipline:
- Engineering
-
- Creator:
- Teague, Seth, Yu, Zhiyuan, and Heemskerk, Idse
- Description:
- Images were collected as part of a project investigating the interpretation of BMP signaling dynamics by differentiating human pluripotent stem cells. Image files are in the proprietary Imaris (.ims) file format. MATLAB and Python code for image processing and quantification is provided with the data and at https://github.com/seth414/HeemskerkLabMethods. Processed data originally published in Teague et al., 2024 (see below).
- Keyword:
- cell tracking, human pluripotent stem cells, immunofluorescence, and signaling dynamics
- Citation to related publication:
- Teague, S., Primavera, G., Chen, B. et al. Time-integrated BMP signaling determines fate in a stem cell model for early human development. Nat Commun 15, 1471 (2024). https://doi.org/10.1038/s41467-024-45719-9
- Discipline:
- Health Sciences and Engineering
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- Creator:
- Burgin, Tucker and Mayes, Heather B.
- Description:
- This project aimed to discover and analyze the molecular mechanism of synthesis of two particular fucosylated oligosaccharide products in a mutant enzyme, Thermatoga maratima Alpha-L-Fucosidase D224G, whose wild type performs the opposite reaction (cleavage of fucosyl glycosidic bonds). Discovery of the mechanism was performed using an unbiased simulations method known as aimless shooting, whereas analysis of the mechanism in terms of the energy profile was performed using a separate method known as equilibrium path sampling. The data here concerns the latter method. and The contents of the atesa_master.zip are the ATESA GitHub project. A Python program for automating transition path sampling with aimless shooting using Amber. https://github.com/team-mayes/atesa
- Keyword:
- Equilibrium Path Sampling, Transition Path Sampling, Enzymatic Mechanism, and GH29
- Citation to related publication:
- Burgin, T., & Mayes, H. B. (2019). Mechanism of oligosaccharide synthesis via a mutant GH29 fucosidase. Reaction Chemistry & Engineering, 4(2), 402–409. https://doi.org/10.1039/C8RE00240A
- Discipline:
- Engineering
-
- Creator:
- Ruas, Terry, Ferreira, Charles H. P., Grosky, William, França, Fabrício O., and Medeiros, Débora M. R,
- Description:
- The relationship between words in a sentence often tell us more about the underlying semantic content of a document than its actual words, individually. Recent publications in the natural language processing arena, more specifically using word embeddings, try to incorporate semantic aspects into their word vector representation by considering the context of words and how they are distributed in a document collection. In this work, we propose two novel algorithms, called Flexible Lexical Chain II and Fixed Lexical Chain II that combine the semantic relations derived from lexical chains, prior knowledge from lexical databases, and the robustness of the distributional hypothesis in word embeddings into a single decoupled system. In short, our approach has three main contributions: (i) unsupervised techniques that fully integrate word embeddings and lexical chains; (ii) a more solid semantic representation that considers the latent relation between words in a document; and (iii) lightweight word embeddings models that can be extended to any natural language task. Knowledge-based systems that use natural language text can benefit from our approach to mitigate ambiguous semantic representations provided by traditional statistical approaches. The proposed techniques are tested against seven word embeddings algorithms using five different machine learning classifiers over six scenarios in the document classification task. Our results show that the integration between lexical chains and word embeddings representations sustain state-of-the-art results, even against more complex systems. Github: https://github.com/truas/LexicalChain_Builder
- Keyword:
- document classification, lexical chains, word embeddings, synset embeddings, chain2vec, and natural language processing
- Citation to related publication:
- Terry Ruas, Charles Henrique Porto Ferreira, William Grosky, Fabrício Olivetti de França, Débora Maria Rossi de Medeiros, "Enhanced word embeddings using multi-semantic representation through lexical chains", Information Sciences, 2020, https://doi.org/10.1016/j.ins.2020.04.048
- Discipline:
- Other, Science, and Engineering
-
- Creator:
- Dorman, Cole J
- Description:
- CHIME provides accurate measurements while enabling inter-spacecraft calibration in constellation missions, offering a significantly more affordable alternative to traditional magnetometers without compromising measurement quality. The development of CHIME is motivated by the high number of magnetometers needed in spacecraft constellations that require a cost-effective commercial solution, as traditional, precise magnetometers are expensive and require complex ground and on-orbit calibration methods that depend on geomagnetic models or special conditions. CHIME Accuracy Calibration: - Various PNI RM3100s were used for data collection, each specified when used and how - Ground CHIME was used for experiments (50 turns per axis, hand wound) - Bartington HC1 500 mm Helmholtz coil was used for calibration baseline experiments. - Python 3.7+ Coil Homogeneity Simulations: - Python 3.7+ Optimal Calibration Pulse Parameters: - Python 3.7+ - ESA Swarm Simulation Data 50 Hz: Level 1B MAGx_HR ( https://swarm-diss.eo.esa.int). - ESA Swarm Simulation Data 1 Hz: Level 1B MAGx_LR. CHIME Calibration Accuracy Across Orbital Environments: - Python 3.7+ - ESA Swarm Simulation Data 50 Hz: Level 1B MAGx_HR ( https://swarm-diss.eo.esa.int). Comparison Simulations of Single Sensor Attitude Indepedent Calibration Methods: - Python 3.7+ - ESA Swarm Simulation Data 50 Hz: Level 1B MAGx_HR ( https://swarm-diss.eo.esa.int). Definitions: CHIME- protagonist of the dataset and accompanying manuscript, the self-calibrating magnetometer Scale Factor (SF), Non-Orthogonality (NO)- forms of magnetic sensor error PNI RM3100- internal magnetic sensor in CHIME Bartington HC1 Coil- calibration tool for the RM3100 and CHIME, a Helmholtz coil itself. ESA - European Space Agency
- Keyword:
- magnetometer, calibration, Helmholtz, spacecraft, and remote sensing
- Citation to related publication:
- Dorman, C.J., Vata, J., Ojeda, L. V., Moldwin, M.B., The CHIME Magnetometer: A Self-Calibrating Approach for Enhanced Accuracy in Spaceborne Applications, Forthcoming.
- Discipline:
- Engineering
-
- Creator:
- Renno, Nilton O., Mohan, Paul, Musko, Stephen, and Madathil, Rohan
- Description:
- The file named "Raw_Reference+OIDU_Data.xlsx" contains both raw data from the Phenom 300 reference scientific measurements and raw data from measurements by the Icing Detection System (IDS) Optical Icing Detection Unit (OIDU) installed in the Phenom 300. Each tab of the file named "Raw_Reference+OIDU_Data.xlsx" contains data from a specific flight with the flight number in the tab. Each tab contains columns for measurement time (in seconds of the UTC day), 905 nm OIDU signal (in counts), 1525 nm signal (in counts), 1635 nm signal (in counts), flight altitude (in ft), air temperature (in degrees C), liquid water content -LWC (in g/m^3), total water content -TWC (in g/m^3), ice water content -ICW (in g/m^3), and median volume diameter -MVD (in micron)., The file named "Raw_MRU_Data.xlsx" contains raw data from measurements made by the microwave resonator unit (MRU). The various columns contain data from engineering measurements and icing detection measurements. The data scientific relevant are in column A -the time stamp in UNIX time, column B -the time stamp in seconds of the GMT day, column G -the peak resonator frequency (Hz), and column H -the resonance quality factor (non-dimensional)., and The file named "Appendix-C-O_Data_Explained.xlsx" contains processed data from measurements by the Phenom 300 reference scientific measurements and processed data from measurements by the Icing Detection System (IDS) Optical Icing Detection Unit (OIDU) installed in the Phenom 300. As explained in Renno et al. (2025), the raw data was reduced by removing data points reported to contain measurement errors (identified by the NAN code in the data) and in-cloud measurements in which TWC ≤ 0 or MVD ≤ 0 before being analyzed. Each data column is described in the first tab.
- Keyword:
- aircraft icing
- Citation to related publication:
- Renno et al. (2025), A New Type of Aircraft Icing Detection System, Nature Scientific Research.
- Discipline:
- Engineering
-
- Creator:
- Esquivel, Amanda and Ajdaroski, Mirel
- Description:
- The ability to accurately measure tibiofemoral angles during various dynamic activities is of clinical interest. The purpose of this study was to determine if inertial measurement units (IMUs) can provide accurate and reliable angle estimates during dynamic actions. A tuned quaternion conversion (TQC) method tuned to dynamics actions was used to calculate Euler angles based on IMU data and these calculated angles were compared to a motion capture system (our “gold” standard) and a commercially available sensor fusion algorithm. Nine healthy athletes were in-strumented with APDM Opal IMUs and asked to perform nine dynamic actions; five participants were used in training the parameters of the TQC method with the remaining four used to test validity.
- Keyword:
- wearable sensors
- Citation to related publication:
- Ajdaroski M, Esquivel A. Can Wearable Sensors Provide Accurate and Reliable 3D Tibiofemoral Angle Estimates during Dynamic Actions? Sensors. 2023; 23(14):6627. https://doi.org/10.3390/s23146627
- Discipline:
- Engineering
-
- Creator:
- A. Abeid, Bachir , L. Fabiilli, Mario , Aliabouzar, Mitra, and Estrada, Jon B.
- Description:
- Images of droplet dynamics during and after optical excitation experiments were recorded in the ultra-fast regime at 1 million frames per second (fps) while the low-speed, quasi-static evolution was carried at 1 fps. During both the inertial and quasi-static phases, we record 1–3 frames in the reference configuration prior to the arrival of the laser-pulse to distinguish the bubble from the background. Lastly, due to the complex physics of plasma formation and chemistry, forward simulations begin at the time when the bubble reaches its maximum expansion
- Keyword:
- optical droplet vaporization, cavitation, viscoelasticity, ultra-high-speed imaging, hydrogel, numerical modeling.
- Citation to related publication:
- Abeid, Bachir A, et al. (2024). Experimental and numerical investigations of ultra-high-speed dynamics of optically induced droplet cavitation in soft materials
- Discipline:
- Science and Engineering
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- Creator:
- Wu, Wenbing, Kadar, Alain, Lee, Sang Hyun, Jung, Hong Ju, Park, Bum Chul, Raymond, Jeffery, Tsotsis, Thomas, Cesnik, Carlos, Glotzer, Sharon, Goss, Valerie, and Kotov, Nicholas
- Description:
- The goal of this project is to relate properties of nanowire networks to their structure. The structure of these networks was determined from electron and atomic force microscopy, which were used as the basis for property predictions. Properties include sheet resistance, conductive anisotropy, absorption spectra, and current capacity.
- Keyword:
- structural complexity, nanowires, graph theory (GT), complex particle systems, complex composites, correlated disorder
- Citation to related publication:
- Preprint: https://arxiv.org/pdf/2310.15369
- Discipline:
- Engineering