3594064 research outputs found
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UCB-6B36-B-14-2-15907-Mandible
No full textMesolithic mandible UCB-6B36-B-14-2-15907 from Sudan; curated in the collections at the University of Colorado at Boulder. Data were collected with a Creaform GoSCAN20.
Many thanks to Dr. Dennis Van Gerven and the University of Colorado at Boulder for the requisite permissions and access needed to scan this collection
UCB-6B36-B-27-2-15920-Mandible
No full textMesolithic mandible UCB-6B36-B-24-1-15920 from Sudan; curated in the collections at the University of Colorado at Boulder. Data were collected with a Creaform GoSCAN20.
Many thanks to Dr. Dennis Van Gerven and the University of Colorado at Boulder for the requisite permissions and access needed to scan this collection
Human iPSC-derived microglia carrying LRRK2-G2019 mutation show Parkinson's disease related transcriptional profile and functions
No full text<p>This repository contains the data and the code used in Ohtone Sohvi's project.</p>
<p>A folder can contain the starting raw data in "data", the R scripts in order of execution (op1, op2 ..) and the "output" folder that contains the final processed data of each operation.</p>
<ul>
<li>"PD_bulk_analysis" contains the processing and analysis of the bulk RNA sequencing data</li>
<li>"PD_bulk_fastq" contains the raw fastq sequences of the bulk RNA sequencing</li>
<li>"PD_bulk_nfcore" contains the results of processing the fasta sequences with nfcore rnaseq workflow </li>
<li>"PD_scRNA_analysis" contains the analysis of the snRNA sequencing dataset</li>
<li>"PD_spatial" contains the raw data of the spatial sequencing, the assempbly of the spatial expression profiles starting from the DAPI images and the transcripts coordinates, the analysis performed on the data</li>
</ul>
Egyptian mummies in Ukrainian museums: an Overview
No full textThe collections of ancient Egyptian artifacts in Museums of Ukraine include various types of objects. An integral part of these collections are human and animal mummies, but they have never been studied or even reviewed by Egyptologists or Anthropologists. In this short paper a short overview of these objects and their museological history is proposed
New species of Pruvotininae (Solenogastres, Cavibelonia) from bathyal bottoms off the NW Iberian Peninsula, with a taxonomical discussion about the family Pruvotinidae
No full textThe family Pruvotinidae (Solenogastres, Cavibelonia) comprises 34 species grouped in 15 genera, five subfamilies and one uncertain subfamily. Three genera with 15 species make up the subfamily Pruvotininae characterized by hook-shaped, hollow acicular sclerites, dorso-pharyngeal gland and ventrolateral foregut glands type A or type Pararrhopalia. Seven species of this subfamily new to science are described in this paper: Pararrhopalia
oscari Pedrouzo & Urgorri n. sp., Pruvotina glandulosa n. sp., Pruvotina bathyalis n. sp., Pruvotina zamarroae n. sp., Pruvotina harpagone n. sp., Labidoherpia vitucoi Pedrouzo & García-Álvarez n. sp. and Labidoherpia lucus n. sp. from hard substrata of bathyal bottoms of NW Iberian Peninsula at a depth of 438 - 2516 m. In addition, the midgut with regular constrictions of Pararrhopalia pruvoti Simroth, 1893 and Pararrhopalia oscari n. sp. and the harpoon-shaped sclerites of Pruvotina harpagone n. sp. have led to modify
the diagnosis of the genera Pararrhopalia, Pruvotina and Labidoherpia. Pararrhopalia pruvoti Simroth, 1893 is redescribed. In the taxonomical discussion about the family Pruvotinidae, the classification of the genus Forcepimenia Salvini-Plawen, 1969 in the subfamily Halomeniinae Salvini-Plawen, 1978 and of the genus Scheltemaia Salvini-Plawen, 2003 in the new subfamily Scheltemaiinae is proposed. The classification of the family
Pruvotinidae is summarized
The Athens Mummy Project in Context: Exciting and Unexpected Results from the CT–Scanning of Five Mummies of the National Archaeological Museum
No full textThe Hellenic Institute of Egyptology —in close collaboration with the National Archaeological Museum of Athens and the Athens Medical Centre— performed a joint Research Project (= Athens Mummy Project), an original and unique up to now endeavour for Hellas. Five out of the ten Ptolemaic mummies coming from Panopolis, the sarcophagi of which have been studied earlier egyptologically [Maravelia & Cladaki–Manoli 2004; Maravelia 2005] have been examined with a non–invasive method, using Computed Tomography (CT) with up–to–date techniques and Scanners, in order to examine and study them also from a medical, anthropological and forensic perspective. The results of this study are not only encouraging [Maravelia, Bontozoglou, Kalogerakou et al. 2019], but very interesting too, some of them being unique and unexpected [Michailidis, Kyriazi, Maravelia et al. 2019; Kalampoukas, Kyriazi, Maravelia et al. 2020; Pantazis, Tourna, Maravelia et al. 2020]. In this paper, after a short introduction to the Research Project, we shall summarize the context as well as the principal results of our study, presenting more exciting results
PhenoCam data processing library
No full text<div>
<p>under development (pending major updates)</p>
<h3>Short description:</h3>
</div>
<p>Python Library for processing StarDot SC 5MP (RGB+IR) phenocam data.<br>Author/troubleshooting contact: Dimitris Tsirantonakis<br>rslab.gr<br>version 0.1<br>Documentation in development</p>
<p>Basic functions are largely based on: https://nbviewer.org/github/tmilliman/phenocam_notebooks/blob/master/Standard_Processing_ROI_Stats/PhenoCam_ROI_stats.ipynb</p>
<p> </p>
<p>Acknowledgements:<br>PhenoCam Network https://phenocam.nau.edu/webcam/<br>python-vegindex package https://github.com/tmilliman/python-vegindex</p>
<div>
<h3>Current functionalities</h3>
</div>
<ol>
<li>Create database of RGB + IR images (coupled RGB + IR images + paths + datetimes)</li>
<li>Add image metadata to database (exposure settings, local time + utc offset)</li>
<li>Create 4-band (R-G-B-IR) image stacks for available image pairs.</li>
<li>Compute exposure adjustments adapted from <a href="https://harvardforest1.fas.harvard.edu/publications/pdfs/Petach_AgriForestMeteor_2014.pdf" rel="nofollow">Petach et al.(2014)</a>.</li>
<li>Compute mean Green Chromatic Coordinate (GCC) + std GCC + mean NDVI for multiple Regions Of Interest (ROI) +std.</li>
</ol>
Optris thermal data processing library
No full text<div>
<p>This work is under development.</p>
<h3>Short description:</h3>
</div>
<p>Python Library for data processing from <em>Optris 640 Pi</em> and <em>Sony RX100 iii</em> cameras mounted on a UAV system (<a href="http://rslab.gr/uas_thermal.html" rel="nofollow">http://rslab.gr/uas_thermal.html</a>).<br>Author/troubleshooting contact: Dimitris Tsirantonakis<br>rslab.gr<br>version 0.1<br>under development Latest update: 12/2/23<br><a href="https://drive.google.com/drive/folders/10R_VeBw5YleZLx1f8tyBVojLDKJENuLJ?usp=sharing" rel="nofollow">Test data link</a></p>
<div>
<h3>Requirements:</h3>
</div>
<p>Check below</p>
<div>
<h3>Setup guide:</h3>
</div>
<p>Using a virtual environment is strongly suggested. After installing <a href="https://docs.anaconda.com/anaconda/install/windows/" rel="nofollow">anaconda</a>, open the anaconda prompt and create new environment by typing:<br><code>conda create -n thermal_env python=3.10</code><br>Then, type 'conda activate thermal_env` to launch the conda environment and run the following:</p>
<ol>
<li><code>pip install rasterio</code></li>
<li><code>python -m pip install -U scikit-image</code></li>
<li><code>conda install matplotlib</code></li>
<li><code>conda install pandas</code></li>
<li><code>conda install spyder-kernels=2.2</code> (this is optional but has to be installed if you want to use Spyder (recommended) to run the scripts.</li>
</ol>
<div>
<h3>How to run:</h3>
</div>
<p>The library can be loaded and used using any python IDE, but Spyder is where it has been tested, and the virtual environment contains the packages needed to run the script in a virtual environment in Spyder. Adjustments will be required for different IDEs. The optris_lib_demo.py file contains examples of all function uses using the test data. So the steps to run this are:</p>
<ol>
<li>Open Spyder</li>
<li>Go to Preferences > Python Interpreter and change to the python.exe file path in the virtual environment, i.e. “C:\Users\RSLab2022z\anaconda3\envs\thermal\python.exe” or similar.</li>
<li>Open, edit according to needs and run optris_lib_demo.py.</li>
</ol>
<div>
<h3>Current optris_lib.py functions:</h3>
</div>
<div>
<h4>csv_to_tiff(thermal_csv_path)</h4>
</div>
<p>Inputs:<br><em>thermal_csv_path</em>: path to folder of .csv files.<br>The function converts the files to geotiffs (with lzw compression, no geotags).<br>Note: The function works only with the default naming convention of the .csv files coming from the OPTRIS PIX Connect software. Check test data for insight.</p>
<div>
<h4>geotag_thermal_from_opt(thermal_tif_path,optical_path)</h4>
</div>
<p>Inputs:<br><em>thermal_tif_path</em>: path to folder of thermal geotiffs.<br><em>optical_path</em>: path to folder of Optical geotagged images (.jpg format)</p>
<p>The function copies the gps tags from the optical images and assigns them to the corresponding thermal images.<br>Note: This function uses the <a href="https://exiftool.org/" rel="nofollow">exiftool.exe</a> to geotag the thermal images, hence the exiftool.exe file needs to be present in the same folder as the optris_lib.py file so that the function works. Also, exiftool edits the names of the original un-geotagged .tif files. No workaround has been found for this</p>
<div>
<h4>thermal_animation(thermal_tif_path)</h4>
</div>
<p>Inputs:<br><em>thermal_tif_path</em>: path to thermal geotiffs.</p>
<p>This function creates an .mp4 movie file displaying the thermal images so that a quick quality check of the data can be done.<br>Note: This function requires the FFmpeg codec to be present in the pc to work. <a href="https://www.geeksforgeeks.org/how-to-install-ffmpeg-on-windows/" rel="nofollow">How to get FFmpeg codecs link</a>.</p>
<div> </div>
Monitoring data from Historical Building in La Valletta (MALTA)
No full text<p>This dataset includes a selection of energy data coming from the monitoring of the demonstration site of La Valletta (MALTA) during both heating and cooling operations. The data were used to calculate the energy performance of the geothermal system that was implemented within GEO4CIVHIC demonstration activities. </p>
<p> </p>
UCB-6B36-B-30-2-15923-Mandible
No full textMesolithic mandible UCB-6B36-B-24-1-15923 from Sudan; curated in the collections at the University of Colorado at Boulder. Data were collected with a Creaform GoSCAN20.
Many thanks to Dr. Dennis Van Gerven and the University of Colorado at Boulder for the requisite permissions and access needed to scan this collection