Replication Data for: Protein Secondary Structure in Spider Silk Nanofibrils
Abstract
This dataset contains raw data, processed data, and the codes used for data processing in our manuscript from our Fourier-transform infrared (FTIR) spectroscopy, Nuclear magnetic resonance (NMR), Raman spectroscopy,- Publisher:
- Harvard Dataverse
- Publication Year:
- NSF-PAR ID:
- 10383121
- Sponsoring Org:
- National Science Foundation
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Abstract
Raw data of optical microscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), and diameter measurements of the exfoliated and self-assembled nanofibrils for our manuscript. File Formats AFM raw data is provided in Gwyddion format, which can be viewed using the Gwyddion AFM viewer, which has been released under the GNU public software licence GPLv3 and can be downloaded free of charge at http://gwyddion.net/ Optical microscopy data is provided in JPEG format SEM raw data is provided in TIFF format Data analysis codes were written in MATLAB (https://www.mathworks.com/products/matlab) and stored as *.m files Data analysis results were stored as MATLAB multidimensional arrays (MATLAB “struct” data format, *.mat files) Data (Folder Structure) The data in the dataverse is best viewed in Tree mode. ReadMe.md This description in Markdown format. Figure 2 - Microscopy Raw Data Figure 2 - panel a.jpg (7.2 MB) Optical micrograph (JPEG format) Figure 2 - panel b.jpg (6.1 MB) Optical micrograph (JPEG format) Figure 2 - panel c f.tif (1.2 MB) SEM raw data (TIFF format) Figure 2 - panel d.tif (1.2 MB) SEM raw data (TIFF format) Figure 2 - panel e - Exfoliated Fibrils.gwy (32.0 MB) AFM raw data (Gwyddion format) Figure 3 - -
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Raw data of scanning electron microscopy (SEM), atomic force microscopy (AFM), force spectroscopy, data analysis and plotting, optical microscopy, and finite element simulations (FEA) for our manuscript. File Formats AFM raw data is provided in Gwyddion format, which can be viewed using the Gwyddion AFM viewer, which has been released under the GNU public software licence GPLv3 and can be downloaded free of charge at http://gwyddion.net/ Optical microscopy data is provided in JPEG format SEM raw data is provided in TIFF format Data analysis codes were written in MATLAB (https://www.mathworks.com/products/matlab) and stored as *.m files Imported raw data to MATLAB and saved MATLAB data were stored as MATLAB multidimensional arrays (MATLAB “struct” data format, *.mat files) FEA results were saved as text files, .txt files) Data (Folder Structure) The data in the dataverse is best viewed in Tree mode. Read me file.docx More Explanations of analysis in docx format. Figure 1 Figure 1 - panel b.jpg (5.5 MB) Optical micrograph (JPEG format) Figure 1 - panel c - AFM Raw Data.gwy (8.0 MB) AFM raw data (Gwyddion format) Figure 1 - panel e - P0_Force-curve_raw_data.txt (3 KB) Raw force-displacement data at P0 (text format) Figure 1 - panel e -
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<p>Data files were used in support of the research paper titled “<em>Mitigating RF Jamming Attacks at the Physical Layer with Machine Learning</em>" which has been submitted to the IET Communications journal.</p> <p>---------------------------------------------------------------------------------------------</p> <p>All data was collected using the SDR implementation shown here: https://github.com/mainland/dragonradio/tree/iet-paper. Particularly for antenna state selection, the files developed for this paper are located in 'dragonradio/scripts/:'</p> <ul><li>'ModeSelect.py': class used to defined the antenna state selection algorithm</li><li>'standalone-radio.py': SDR implementation for normal radio operation with reconfigurable antenna</li><li>'standalone-radio-tuning.py': SDR implementation for hyperparameter tunning</li><li>'standalone-radio-onmi.py': SDR implementation for omnidirectional mode only</li></ul> <p>---------------------------------------------------------------------------------------------</p> <p>Authors: Marko Jacovic, Xaime Rivas Rey, Geoffrey Mainland, Kapil R. Dandekar<br /> Contact: krd26@drexel.edu</p> <p>---------------------------------------------------------------------------------------------</p> <p>Top-level directories and content will be described below. Detailed descriptions of experiments performed are provided in the paper.</p> <p>---------------------------------------------------------------------------------------------</p> <p>classifier_training: files used for training classifiers that are integrated into SDR platform</p> <ul><li>'logs-8-18' directory contains OTA SDR collected log files for each jammer type and under normal operation (including congested and weaklink states)</li><li>'classTrain.py' is the main parser for training the classifiers</li><li>'trainedClassifiers' contains the output classifiers generated by 'classTrain.py'</li></ul> <p>post_processing_classifier: contains logs of online classifier outputs and processing script</p> <ul><li>'class' directory contains .csv logs of each RTE and OTA experiment for each jamming and operation scenario</li><li>'classProcess.py' parses -
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<p>Data files were used in support of the research paper titled "“Experimentation Framework for Wireless<br /> Communication Systems under Jamming Scenarios" which has been submitted to the IET Cyber-Physical Systems: Theory & Applications journal. </p> <p>Authors: Marko Jacovic, Michael J. Liston, Vasil Pano, Geoffrey Mainland, Kapil R. Dandekar<br /> Contact: krd26@drexel.edu</p> <p>---------------------------------------------------------------------------------------------</p> <p>Top-level directories correspond to the case studies discussed in the paper. Each includes the sub-directories: logs, parsers, rayTracingEmulation, results. </p> <p>--------------------------------</p> <p>logs: - data logs collected from devices under test<br /> - 'defenseInfrastucture' contains console output from a WARP 802.11 reference design network. Filename structure follows '*x*dB_*y*.txt' in which *x* is the reactive jamming power level and *y* is the jaming duration in samples (100k samples = 1 ms). 'noJammer.txt' does not include the jammer and is a base-line case. 'outMedian.txt' contains the median statistics for log files collected prior to the inclusion of the calculation in the processing script. <br /> - 'uavCommunication' contains MGEN logs at each receiver for cases using omni-directional and RALA antennas with a 10 dB constant jammer and without the jammer. Omni-directional folder contains multiple repeated experiments to provide reliable results during each calculation window. RALA directories use s*N* folders in which