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.
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
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
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
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
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
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
Abeid, Bachir A, et al. (2024). Experimental and numerical investigations of ultra-high-speed dynamics of optically induced droplet cavitation in soft materials
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.
The SID dataset was curated to support advanced research in autonomous driving systems, particularly focusing on perception under adverse weather and lighting conditions. This dataset encompasses over 178k high-resolution stereo image pairs organized into 27 sequences, reflecting a rich variety of conditions such as snow, rain, fog, and low light. It covers dynamic changes in driving scenarios and environmental backgrounds, including university campuses, residential streets, and urban settings. The dataset is designed to challenge perception algorithms with scenarios such as partially obscured camera lenses and varying visibility, promoting the development of robust computer vision models. No specialized software or scripts are necessary for accessing the image data, as the files are provided in standard PNG format. However, researchers and developers may require their image processing and computer vision toolkits to utilize the dataset effectively in their work.
El-Shair, Z.A., Abu-raddaha, A., Cofield, A., Alawneh, H., Aladem, M., Hamzeh, Y. and Rawashdeh, S.A., 2024, July. SID: Stereo Image Dataset for Autonomous Driving in Adverse Conditions. In NAECON 2024-IEEE National Aerospace and Electronics Conference (pp. 403-408). IEEE.
This investigation utilizes a new and more accurate multiscale analysis that combines molecular dynamics and polycrystalline theory with micromechanics to capture the influence of the amorphous boron nitride interphase thickness on the mechanical properties of the SiC/SiC composites.
We have ported our MHD code, BATSRUS ( https://github.com/SWMFsoftware/BATSRUS), to the GPU. This dataset contains the input parameters and raw timing results for the Paper (being revised). To reproduce the results on the supercomputers Frontera and Pleiades, the user need to load modules nvhpc 20.7 for compiling on frontera, nvhpc 24.3-nompi + mpi-hpe/mpt for compiling on Pleiades. and Abstract: BATSRUS, our state-of-the-art extended magnetohydrodynamic code, is the most used and one of the most resource-consuming model in the Space Weather Modeling Framework. It is ever our objective to improve its efficiency and speed with emerging techniques, such as GPU acceleration. To utilize the GPU nodes on modern supercomputer, we port BATSRUS to GPUs with the OpenACC API. Porting the code to a single GPU requires to rewrite and optimize the most used functionalities of the original code into a new solver, which accounts for around 1% of the entire program. To port it to multiple GPUs, we implement a new message passing algorithm to support its unique block adaptive grid feature. We conduct weak scaling tests on as many as 64 GPUs on two supercomputers, and find good performance for up to 16 GPUs. The program is able to retain 65-80% parallel efficiency within one node (up to 4 GPUs), and 40-60% efficiency for 16 GPUs. Applications on more GPUs have reduced efficiency but remain operationally meaningful. Profiling shows that the loss of efficiency is due to the communication latency between supercomputer nodes. We also demonstrate our ability to run representative magnetosphere simulations on GPUs. The performance for a single V100 GPU is about the same as 140 Intel Xeon E5-2680v4 ''Broadwell'' CPU cores, and it runs about twice as fast as real time. The code can run 4 times faster than real time on 4 V100 or 16 RTX 5000 GPUs.
An, Y., Chen, Y., Zhou, H. and Toth, G. (2024). BATSRUS GPU: Faster than Real Time Magnetospheric Simulations with a Block Adaptive Grid Code. Being revised.
Passive flow control devices, such as vortex generators (VGs), can effectively modulate the turbulent boundary layer flow near regions of adverse pressure gradients, but the interactions between the salient flow structures produced by VGs and those of the separated flow are not fully understood. In this study, a spatially evolving turbulent boundary layer interacting with a wall-mounted cube ahead of a backward-facing ramp is investigated using wall-resolved large-eddy simulations for a Reynolds number of 19,600, based on the inlet boundary layer thickness and freestream velocity. Different cube configurations are examined to isolate the effects of cube height and streamwise position.
Suyash Tandon, Kevin J. Maki, and Eric Johnsen, "Large-Eddy Simulations of Flow over a Backward-Facing Ramp with a Wall-Mounted Cube, " AIAAJ, Vol. 62, No. 9 (2024), pp. 3403-3417 doi: doi/abs/10.2514/1.J063803
This dataset contains data from two direct numerical simulations of a turbulent zero-pressure-gradient flat-plate boundary layer spanning friction Reynolds numbers from 292 to 728 (BL1) and 488 to 1024 (BL2). The dataset contains time-resolved snapshots of the three-dimensional velocity field for both cases: roughly 10,000 snapshots spanning 20 eddy-turnover times for BL1 and 7,500 snapshots spanning 7 eddy-turnover times for BL2 . Also included for both cases are pre-processed correlations at several wall-normal distances, mean and root-mean-squared velocity and vorticity profiles, several boundary-layer metrics, and time-resolved velocity data in the streamwise-wall-normal plane. All data are stored within hdf5 files, and a Matlab script showing how the data can be read and manipulated is provided. Please see the ‘BLdns_README.pdf’ file for more information. We recommend using the ‘BLdns_example.zip’ file as an entry point to the dataset. and The dataset is part of “A database for reduced-complexity modeling of fluid flows” (see references below) and is intended to aid in the conception, training, demonstration, evaluation, and comparison of reduced-complexity models for fluid mechanics. The paper introduces the flow setup and computational methods, describes the available data, and provides an example of how these data can be used for reduced-complexity modeling. Users of these data should cite the paper listed below.
Towne, A., Dawson, S., Brès, G. A., Lozano-Durán, A., Saxton-Fox, T., Parthasarthy, A., Biler, H., Jones, A. R., Yeh, C.-A., Patel, H., Taira, K. (2022). A database for reduced-complexity modeling of fluid flows. AIAA Journal 61(7): 2867-2892.