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29 results for “Mechanical Engineering”
Raw data corresponding to the scientific paper: "A modular telerehabilitation architecture for upper limb robotic therapy" (Advances in Mechanical Engineering 2017, Vol. 9(1) 1-13)
<p>Acquired raw data necessary to implement the adaptive control strategy grounded on multimodal information.<br> In addition, raw data for the computation of the communication parameters needed for the assessment of the implemented telerehabilitation architecture are provided.</p> <p>a) End-effector positions and velocities (x, y, vx, vy) in three conditions: healthy (Fig 9) and constraint simulated stroke behaviour (Fig 10) without robotic assistance and simulated stroke behavior with robotic assistance (Fig 11)</p> <p>b) Performance indicators and control parameters for all the recruited subjects in both conditions healthy behaviour and simulated stroke behaviour (Fig 12a and Fig 12b)</p> <p>c) Computational values for evaluating telerehabilitation performance (Table 1)</p> <p> </p> <p> </p>
Acquired data necessary to perform the control algorithm introduced in the scientific paper: "Multilevel control of an anthropomorphic prosthetic hand for grasp and slip prevention" (Advances in Mechanical Engineering, 2016, vol. 8, pp. 1-13)
<p>Acquired data necessary to perform the control algorithm introduced in this paper.</p> <p>a) Figure 6: Calibration data for the three FSRs placed on the prosthetic hand and covered with silicon caps.<br> b) Figure 9: Data for the cost during the learning of two grasping tasks of an egg: bi-digital grasp and tri-digital grasp.<br> c) Figure 10 and Figure 11: Data for the experimental results with the plastic cup and with the highlighter shown in the paper.<br> </p> <p> </p>
Dataset of the scientific paper " Multimodal robotic system for upper-limb rehabilitation in physical environment" (Advances in Mechanical Engineering)
<p>There are eight files with the following information:<br> - pos_stateXX.bin, binary file with information of the end effector position of the robot device in meters along the three axis (X, Y, Z) during state XX of the experiment<br> - target_stateXX.bin, binary file with information of the target position for the robot device in meters along the three axis (X, Y, Z) during state XX of the experiment<br> - emg_channelXX.bin, binary file with information of channel 1 of the EMG sensor in mV during during the whole time of the experiment<br> - color_stateXX.bin, binary file with information of color filter information during state XX of the experiment. This information is the percentage of pixels with the correct color (yellow, cyan or magenta) inside the region of interest</p> <p> </p>
Dataset for publication Cuevas K., Chougan M., Martin F., Ghaffar SH, Stephan D., Sikora P. 3D printable lightweight cementitious composites with incorporated waste glass aggregates and expanded microspheres – Rheological, thermal and mechanical properties. Journal of Building Engineering (2021) 44, 102718
<p>Dataset consisting of G-code for 3D mortar specimen's printing path and particle size distribution (Origin file) of materials used in the study Cuevas K., Chougan M., Martin F., Ghaffar SH, Stephan D., Sikora P. 3D printable lightweight cementitious composites with incorporated waste glass aggregates and expanded microspheres – Rheological, thermal and mechanical properties. Journal of Building Engineering (2021) 44, 102718. <a href="https://doi.org/10.1016/j.jobe.2021.102718">https://doi.org/10.1016/j.jobe.2021.102718</a></p>
Supplementary data for "ENGINEERED ADAPTATION MECHANISMS BETWEEN MARINE AND FRESHWATER ENVIRONMENTS IN FISH AFTER THE FLOOD" for the ICC 2023 in Cedarville, Ohio
<p>Supplementary data for "ENGINEERED ADAPTATION MECHANISMS BETWEEN MARINE AND FRESHWATER ENVIRONMENTS IN FISH AFTER THE FLOOD" for the ICC 2023 in Cedarville, Ohio.</p> <p>These include FishBase annotation, mtDNA sequence similarity matrixes, clustering, and statistics for nine fish orders:</p> <p>1. Acipenseriformes</p> <p>2. Angulliformes</p> <p>3. Beloniformes</p> <p>4. Characiformes</p> <p>5. Clupeiformes</p> <p>6. Cyprinodontiformes</p> <p>7. Elasmobranchii</p> <p>8. Pleuronectiformes</p> <p>9. Salmoniformes</p>
Dataset for "Engineering defect clustering in diamond-based materials for technological applications via quantum mechanical descriptors"
<p>The unique set of extreme physical properties makes diamond an ideal candidate for applications in the energy industry such as in high-power and high-frequency electronics as well as in electrochemistry and photovoltaics. Furthermore, dopant-vacancy complexes in diamond can be exploited for further development of quantum computers, single-photon emitters, high-precision magnetic field sensing and nanophotonic devices. While certain dopant-vacancy complexes are well-studied, studies of other dopant/vacancy clusters are focused mostly on defect detection while investigations on how to tune their electronic and optical properties for specific applications is mostly omitted. To this aim, we attempted to reveal coupled structural-electronic features and their effect on the band gap of such defects through first principle calculations. We investigated four different defect types: a) dopant-vacancy complexes (X-V), b) two dopants as nearest neighbours (X-X), c) two dopants separated by one carbon atom (X-C-X) and d) two dopants separated by a vacancy (X-V-X). For each of these configurations, we considered Al, B, N, P and Si as dopant atoms. This dataset contains input files needed to reproduce every ground state geometry used in our study.</p>
Data for the paper: The Role of Glycerol in Manufacturing Freeze-Dried Chitosan and Cellulose Foams for Mechanically Stable Scaffolds in Skin Tissue Engineering
<p>The Dataset contains all the data, described in the article "<strong>The Role of Glycerol in Manufacturing Freeze-Dried Chitosan </strong><br><strong>and Cellulose Foams for Mechanically Stable Scaffolds in Skin Tissue Engineering</strong>."</p> <p><strong><em>Abstract</em></strong><br>Various strategies have extensively explored enhancing the physical and biological properties of chitosan and cellulose scaffolds for skin tissue engineering. This study presents a straightforward method involving the addition of glycerol into highly porous structures of two polysaccharide complexes: chitosan/carboxymethyl cellulose (Chit/CMC) and chitosan/oxidized cellulose (Chit/OC); during a one-step freeze-drying process. Adding glycerol, especially to Chit/CMC, significantly increased stability, prevented degradation, and improved mechanical strength by nearly 50%. Importantly, after 21 days of incubation in enzymatic medium Chit/CMC scaffold has almost completely decomposed, while foams reinforced with glycerol exhibited only 40% mass loss. It is possible due to differences in multivalent cations and polymer chain contraction, resulting in varied hydrogen bonding <br>and, consequently, distinct physicochemical outcomes. Additionally, the scaffolds with glycerol improved the cellular activities resulting in over 40% higher proliferation of fibroblast after 21 days of incubation. It was achieved by imparting water resistance to the highly absorbent material and aiding in achieving a balance between hydrophilic and hydrophobic properties. This study clearly indicates the possible elimination of additional crosslinkers and multiple fabrication steps that can reduce the cost of scaffold production for skin tissue engineering applications while tailoring mechanical strength and degradation.</p> <p><strong>Figure 2.</strong> Morphology. SEM micrographs of the internal structure of the freeze-dried scaffolds. Results of porosity analysis. The methodology and data are described in the README file in the folder.</p> <p><strong>Figure 3.</strong> Mechanical test results. Representative stress-strain curves from the tensile test of all freeze-dried scaffolds, where (A)<br>– measurement performed in dry conditions, (B) – measurement performed in wet conditions. All are described in the README file in the folder.</p> <p><strong>Figure 4. </strong>Swelling behavior of all scaffolds. B – Two representative vials with a visual demonstration of swelling, samples marked with circles: Chit/CMC sample submerged in the PBS (blue circle) and Chit/CMC/Glyc sample floating on the surface (green circle). The arrows lead to photos of scaffolds taken from vials directly after swelling. C – Gel fraction analysis in aqueous solution after 24 <br>6 h. D – Time after which the water droplet is absorbed into the scaffold. E – Photographs of water droplet shape changes on Chit/CMC and Chit/CMC/Glyc scaffolds over time. All are described in the README file in the folder.</p> <p><strong>Figure 5</strong>. Fourier Transform Infrared Spectroscopy (ATR-FTIR) analysis results. Details are in the README file in the folder.</p> <p><strong>Figure 6.</strong> The FTIR spectra of eluates from degraded scaffolds collected on a microscopic glass slide. Details are in the README file in the folder.</p> <p><strong>Figure 7.</strong> The degradation studies of all scaffolds over 21 days of experiments in A – enzymatic medium. B – cell culture medium. Details are in the README file in the folder.</p> <p><strong>Figure 9. </strong>Cell experiments and toxicity analysis. Cytotoxicity of eluates taken from degraded scaffolds. B – Direct fibroblast seeding on scaffolds during 14 days of culture period. C – Direct fibroblast seeding on scaffolds during 14 days of culture period without control to better see the effect of glycerol. Details are in the README file in the folder.</p>
Mechanical Engineering: An International Journal ( MEIJ)
<pre>Mechanical Engineering: An International Journal is a peer-reviewed, open access journal that addresses the impacts and challenges of Mechanical Engineering. The journal documents practical and theoretical results which make a fundamental contribution for the development of Mechanical Engineering.</pre>
Mechanical Engineering: An International Journal (MEIJ)
<p>CALL FOR PAPERS...!!!!</p> <p> </p> <p><strong>Mechanical Engineering: An International Journal (MEIJ)</strong></p> <p> </p> <p><a href="http://airccse.com/meij/index.html"><strong>http://airccse.com/meij/index.html</strong></a></p> <p> </p> <p><strong>ISSN: 2349 – 2651</strong></p> <p> </p> <p><strong>Submission Deadline:</strong> <strong>January 30</strong> <strong>, 2021</strong></p> <p> </p> <p><strong>CONTACT US : </strong><a href="mailto:meijjournal@yahoo.com"><strong>meijjournal@yahoo.com</strong></a><strong> or </strong><a href="mailto:meij@airccse.com"><strong>meij@airccse.com</strong></a></p> <p> </p> <p><strong>Submission Link</strong> : <a href="https://airccse.com/submission/home.html"><strong>https://airccse.com/submission/home.html</strong></a></p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Supplemental Material to Doctoral Thesis "Engineering approach for predicting tunneling crack initiation in trailing-edge adhesive joints of wind turbine blades under mechanical fatigue and thermal residual stresses"
<p>This set supplements the figure data to the doctoral thesis "Engineering approach for predicting tunneling crack initiation in trailing-edge adhesive joints of wind turbine blades under mechanical fatigue and thermal residual stresses", DOI: <a href="https://doi.org/10.14279/depositonce-19144">10.14279/depositonce-19144</a></p>
Input data of the multi-patch geometries used in: A. Farahat, H. M. Verhelst, J. Kiendl, M. Kapl, Isogeometric analysis for multi-patch structured Kirchhoff–Love shells, Computer Methods in Applied Mechanics and Engineering 411 (2023) 116060 DOI: 10.1016/j.cma.2023.116060
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Datasets and geometries for "MORE-Q, Dataset for molecular olfactorial receptor engineering by quantum mechanics"
<p>We introduce the MORE-Q dataset, a quantum-mechanical (QM) dataset encompassing the structural and electronic data of non-covalent molecular sensors formed by combining 18 mucin-derived olfactorial receptors with 102 body odor volatilome (BOV) molecules. To have a better understanding of their intra- and inter-molecular interactions, we have performed accurate QM calculations in different stages of the sensor design and, accordingly, MORE-Q splits into three subsets: i) MORE-Q-G1: QM data of 18 receptors and 102 BOV molecules, ii) MORE-Q-G2: QM data of 23, 838 BOV-receptor configurations, and iii) MORE-Q-G3: QM data of 1, 836 BOV-receptor-graphene systems. Each subset involves geometries optimized using GFN2-xTB with D4 dispersion correction and up to 39 physicochemical properties, including global and local properties as well as binding features, all computed at the tightly converged PBE+D3 level of theory. By addressing BOV-receptor-graphene systems from a QM perspective, MORE-Q can serve as a benchmark dataset for state-of-the-art machine learning methods developed to predict binding features. This, in turn, can provide valuable insights for developing the next-generation mucin-derived olfactory receptor sensing devices.</p> <p>The dataset is provided in 3 HDF5 based files. One can also find here a README file with technical usage details and examples of how to access the information stored in the dataset (see createDF.py). We also offer a Github repository for user guide, see https://github.com/LiC1117/MORE-Q.</p> <p>For more details, one can refer to the manuscript doi: <a href="https://doi.org/10.1038/s41597-025-04616-6" rel="nofollow">https://doi.org/10.1038/s41597-025-04616-6</a></p>
Dataset for article "Prediction of thermal shock induced cracking in multi-material ceramics using a stress-energy criterion" published in Engineering Fracture Mechanics
<p>Dataset contains graphical outputs of the numerical analysis performed using Finite element method in finite elements software Ansys Mechanical. It contains also photoes of the tested specimens. Further, material data used for the numerical analysis and measured by authors are included in the csv file and all necessary input codes for the FE system Ansys creating data for graphs in the publication are provided in the subfolder "Models-Ansys" within "Data" directory.</p> <p> </p>
Evaluating Mechanically Engineered Stem Cell Exosomes for Treating Endometrial Injury: A Clinical Study
ClinicalTrials.gov study NCT06896747. IPD Sharing: YES. Countries: 1. Publications: 6.
Keyword-Matching-for-Canadian-Mechanical-Engineering-Programs-2023-2024
<p>This data repository contributed to the survey of the prevalence of Artificial Intelligence (AI) in current Canadian engineering curricula, which will be published in the proceedings of IDETC2024:</p> <ol> <li>Web-scraping course information (course codes, names, and descriptions) from the webites of engineering programs</li> <li>List of AI keywords</li> <li>Developing a keyword-matching algorithm to look for the keywords within every web-scraped course description and to generate a list of courses whose descriptions matched with at least one keyword</li> </ol> <p>The final results and scripts for each of these projects can be found in their respective folders in this repository</p> <p>The keyword-matching script can be directly run on the commandline and the webscraping scripts can be opened via Jupyter Notebooks or Google Colab.</p>
The input data of the multi-patch geometries used in: M. Kapl, A. Kosmač, V. Vitrih, Isogeometric collocation for solving the biharmonic equation over planar multi-patch domains, Computer Methods in Applied Mechanics and Engineering 424 (2024) 116882; DOI: 10.1016/j.cma.2024.116882
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Data for the article "Elastic strain engineering for ultralow mechanical dissipation"
<p>Device fabrication masks, raw experimental data and data processing scripts</p>
Evolution of Escherichia coli to 42 °C and Subsequent Genetic Engineering Reveals Adaptive Mechanisms and Novel Mutations
GEO Series GSE132442. Escherichia coli str. K-12 substr. MG1655. 10 samples. Type: Expression profiling by high throughput sequencing.
Mechanical Unloading of Engineered Human Meniscus Models Under Simulated Microgravity
GEO Series GSE192983. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
Dataset for publication 7. Eslam El-Seidy, Mehdi Chougan, Yazeed A. AI-Noaimat, Mazen J. Al-Kheetan, Seyed Hamidreza Ghaffar. (2024). The impact of waste brick and geo-cement aggregates as sand replacement on the mechanical and durability properties of alkali–activated mortar composites, Results in Engineering, doi: https://doi.org/10.1016/j.rineng.2024.101797
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.