Find research datasets worth reusing

opencc-by-4.0Nov 2018View details →

Fig. 1 in The Influence Of Fixatives On The Validity Of Histological Preparations Of Olfactory Organ In Teleostei

Fig. 1. Section levels through the olfactory organ of European weatherfish Misgurnus fossilis: A — cross-section (prolarva); B — frontal section (larva).

opencc-by-4.0Jul 2022View details →

Magnetoencephalographic spectral fingerprints differentiate evidence accumulation from saccadic motor preparation in perceptual decision-making

This repository contains the dataset of the paper "Magnetoencephalographic spectral fingerprints differentiate evidence accumulation from saccadic motor preparation in perceptual decision-making". The dataset contains the MEG power spectrum of 16 subjects in the source space of a perceptual decision making experiment.

opencc-by-4.0Aug 2022View details →

A multicenter randomized phase 4 trial comparing Sodium Picosulphate plus Magnesium Citrate vs Polyethylene Glycol plus Ascorbic Acid for bowel PREparation before COLonoscopy. The PRECOL trial.

This is the database for final analysis of the PRECOL clinical trial, whose abstract follows Background. Adequate bowel preparation before colonoscopy is crucial. Unfortunately, up to 25% of all colonoscopies have inadequate bowel cleansing.  From a patient perspective, bowel preparation is a main obstacle for colonoscopy. Several low-volume bowel preparations have been formulated to provide more tolerable purgative solutions without loss of efficacy. Methods: In this phase 4, randomized, multicenter, two-arm trial, adult outpatients undergoing colonoscopy received either Sodium Picosulphate plus Magnesium Citrate (SPMC) or Polyethylene Glycol plus Ascorbic Acid (PEG-ASC) for bowel preparation. The primary aims were to test quality of bowel cleansing (primary endpoint, scored according the Boston Bowel Preparation Scale) and patient’s acceptance (measured with 6 visual analogue scales). The study was open as for treatment assignment, and blinded for primary endpoint assessment that was done independently on videotaped colonoscopies by 2 endoscopists not aware of study arm. A sample size of 525 patients was calculated to recognize a difference of 10% in the proportion of successes between the arms with a two-sided alpha error of 0·05 and 90% statistical power. Findings: overall 550 subjects (279 assigned to PEG-ASC and 271 assigned to SPMC) represented the analysis population. There was no statistically significant difference in the success rate according to BBPS: 94·4% with PEG-ASC and 95·7% with SPMC (P=0·49). Acceptance and willing to repeat were significantly better for SPMC with all the scales. Compliance was less than full in 6·6% and 9·9% of cases with PEG-ASC and SPMC, respectively (P=0·17). Nausea and meteorism were significantly more bothersome with PEG-ASC than SPMC. There were no serious adverse events in either group. Interpretation. SPMC and PEG-ASC are not different in terms of efficacy, but SPMC is better tolerated than PEG-ASC. SPMC could be used as alternative to low-volume PEG based purgative solutions for bowel preparation. Funding. This research had no financial support. ClinicalTrials.gov NCT01649674; EudraCT 2011—000587—10.

opencc-by-4.0Sep 2022View details →

Subset of 300 out of 3000 Prepared Sentinel 2 Scenes for Transfer Learning and Super-sampling.

This dataset contains a random subset of 300 out of 3000 Sentinel 2 scenes prepared for Transfer Learning and Super-sampling. It comes in the form of zipped NumPy arrays in the npz format. The files have are named in the following fashion: latutide+latitude_decimals_longitude+longitude_decimals_month_of_the_year_for_mosaic.  Each file contains: bands.npy: The Sentinel 2 bands in 10m resolution uint10: B02, B03, B04, B08, B05, B06, B07, B8A, B11, B12. The 20m bands have been resampled using bilinear resampling. nir.npy: B08 Resampled to 20m using average resampling and then resampled to 10m using bilinear. Useful for training super-sampling models. scl.npy: The Sentinel 2 Scene Classification file. Contains information on cloud cover and land cover. sincos.npy: Contains the latitude, longitude, and time of capture for each pixel encoded to sine and cosine waves in the [0,1] interval. The is useful when training a model to predict where on the globe an image was captured. The images can be processed to patches using the buteo toolbox:  `pip install buteo --upgrade `import buteo as beo` `beo.get_patches(beo.raster_to_array("path_to_bands"))`

opencc-by-4.0Sep 2022View details →

Python scripts / Jupyter Notebooks and data for training segmentation models on slide scans of diatom preparations from river Menne

This archive contains the Jupyter Notebooks and data used for the deep learning experiments published in Kloster et al. 2022: Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint. The notebooks are numbered according to the order in which they are to execute. Please refer to the comments and documentation within the notebooks as well as to the manuscript for details. The data (image data, mask data & segmentation ground truth in COCO format for several different tiling strategies) is stored in separate subfolders corresponding with data usage (model training, validation, test) and tiling strategy. Please refer to the "readme" files for detailed information.

opencc-by-4.0Sep 2022View details →

Segmentation models and experimental results on segmenting slide scans of diatom preparations from river Menne

This archive contains the models and the results of the deep learning experiments published in Kloster et al. 2022: Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint. The folders contain models and results of each of the 24 training runs, the files “metrics.experiments.pt[prediction score threshold].csv contain segmentation score thresholds the models obtained on unknown evaluation data. The data pertaining to each model is stored in a separate folder. Its name follows the convention “experiment.[model architecture].[tiling method].[dataset size].[timestamp]”. Please note that the naming of the tiling method differs from the manuscript; “fixed” refers to fixed-stride tiling, “objectcentred” object-based positioning, and “objectcentred_with_cropped” to object-based positioning + object integrity constraint. Dataset size “10p” refers to a 10% subsample of the complete training data set, “25p” to a 25% subsample and so on. Each folder contains the best performing model of the corresponding training run as pth (Mask R-CNN, PyTorch) or h5 (U-Net, Tensorflow/Keras) file, along with a files describing setup and conduction of the training. Subfolders “test_images_segmented*” contain the segmentation predicted by the models on the evaluation data. These are supplied as 1.) mask image either with the intensity value representing the prediction score (score 0.0 – 1.0 = intensities 0 – 255) or thresholded by the prediction score threshold given in the folder name; 2.) input image overlayed with ground truth (red) and segmentation mask (green), resulting in TP marked in yellow; 3.) a CSV file giving info on the filenames and the segmentation performance metrics. Please refer to the manuscript for further details.

opencc-by-4.0May 2022View details →

Data for FEgrow: An Open-Source Molecular Builder and Free Energy Preparation Workflow

Data illustrating the use of de novo design in building and scoring protein-ligand complexes. This is relationship to the FEgrow publication with the intiial preprint here:  https://chemrxiv.org/engage/chemrxiv/article-details/6287bb98a42e9c78d34769f6   The FEgrow software snapshot used can be found here: https://zenodo.org/record/7105647#.YzFwINLMIUE

opencc-by-4.0Apr 2022View details →

Figure 1 in Use of homeophathic preparations for red spider mite, Tetranychus urticae (Acari: Tetranychidae) control in strawberry plants

Figure 1. Degree of a) Incidence, and b) severity caused by T. urticae in strawberry plants 30 and 60 days after applying the treatments: Distilled water (Ctl); 6 and 30 CH Strawberry leaves homeopathic (Agroh); 6 and 30 CH Bovista (Bov); 6 and 30 CH Belladonna (Bellad); 6 and 30 CH Arnica (Árni) and 6 and 30 CH Ferrum sulphuricum (FS). Treatments with the same letter are not significantly different between them (p <0.05) (n = 8).

Figure 4: Spectro°uorimetric spectra of TiO2/CdS composites samples with a di®erent mass proportion-PREPARATION AND CHARACTERIZATION OF TIO2/CDS LAYERS AS POTENTIAL PHOTOELECTROCATALYTIC MATERIALS

Fig. 4 illustrates the fluorescence emission spectra of TiO2/CdS nanostructured ¯lm at the exciting wavelength of 340 nm. The curves for TC 1, TC 2, TC 3 and TC 4 exhibited the clear photoemission peaks at about 375 nm, and compared with emission of bulk CdS (520 nm), 145 nm of blue shift was observed. These features indicate the quantum-con¯ned e®ect of the TiO2/CdS nanocomposite ¯lms [25].

PREPARATION AND CHARACTERIZATION OF TIO2/CDS LAYERS AS POTENTIAL PHOTOELECTROCATALYTIC MATERIALS-Figure 2: The FT/IR microscopy images of the TiO2/CdS composites

The microstructural properties of the deposited TiO2/CdS layers depend on the mass proportions of TiO2:CdS. The proportion of CdS phase is di- rect proportional with the CdS powder used in the preparation process. The FT/IR microscopy images of the TiO2/CdS composites upon annealing at high temperatures, are shown in Fig.2 The micrograph shows agglomerates with irregular morphology and size ranging from few micrometers down to hundreds of nanometer.

Figure 1: X-ray di®raction pattern for TiO2/CdS composites samples-PREPARATION AND CHARACTERIZATION OF TIO2/CDS LAYERS AS POTENTIAL PHOTOELECTROCATALYTIC MATERIALS

Fig. 1 shows the X-ray di®raction pattern for TiO2/CdS composites (sample TC 1, TC 2, TC 3 and TC 4). The di®raction pattern of the TiO2/CdS composites exhibits the di®raction peaks owning to CdS phase (hexagonal and cubic). TiO2 (rutile and anatase) phases were also detected.

Figure 3: Absorption spectra of TiO2/CdS composites samples with a di®erent mass proportion-PREPARATION AND CHARACTERIZATION OF TIO2/CDS LAYERS AS POTENTIAL PHOTOELECTROCATALYTIC MATERIALS

Optical properties of TiO2/CdS semi- conductor composites have been investigated using optical absorption and pho- toluminescence spectroscopy. UV-VIS absorption spectra of the as-prepared photocatalysts were taken on a JASCO V-550 spectrometer. The °uorescence spectra were obtained using an ABL&Jasco V 6500 spectro°uorimeter with xenon lamp. The optical studies of the TiO2/CdS composites were performed using the absorption spectra observed in the wavelength range 200-900 nm. Fig. 3 shows the UV-Vis spectra of TiO2/CdS samples.

opencc-by-4.0Mar 2024View details →

Data for a publication "The role of the preparation route on microstructure and mechanical properties of AlCoCrFeNi high entropy alloy"

A dataset containing data for the published article "The role of the preparation route on microstructure and mechanical properties of AlCoCrFeNi high entropy alloy".   For more details, please read the README Description of data and analysis.txt file.

opencc-by-4.0May 2024View details →

Medical Students use Online Study Materials more than School-Provided Resources when preparing for USMLE Step 1

In this excel file contains the raw data collected from a survery sent out to students attend ULSOM and UNRSOM. The raw data was processed and analyzed in the sheet titled "graphs".

opencc-by-4.0Dec 2023View details →

FIGURE A3-2. m1 images preparation protocol. A in Morphospace dynamics and intraspecies variety of Sorex araneus and S. tundrensis according to recent and fossil data

FIGURE A3-2. m1 images preparation protocol. A, Two-dimensional images of m1 give from three-dimensional model of a hemimandible. B, Interface MorphoDig software (Lebrun, 2020) for work with the models. C, Model alignment to the 'Functional View' in sense to Polly (2003), see details in Figure A3-3. D, Obtaining separate images via 'Snipping Tool' for three repeats, A, B, and C. E, Landmarking ready images via tpsDig software (Rohlf, 2007). F, Obtaining three separate data sets required for assessing the 'metering error' influence or obtaining a final work data set as a mean between repeats. Abbreviations: a, b — rotation along of the space planes for a model alignment.

FIGURE S1 in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle

FIGURE S1. The prototype of the Wada air scribe. The short air scribe and the cylinder were welded together, at an L-shaped configuration. The impact angle remained fixed at 90 degrees and could not be adjusted.

FIGURE S4. The production flow for a in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle

FIGURE S4. The production flow for a bushing. Schematic diagrams in lateral (upper row) and front (middle row) views and cross-sections (lower row) are shown.

FIGURE 11 in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle

FIGURE 11. Usage example of the Wada air scribe. A, fossil preparation inside of the deep cavity; B, preparation under a microscope using the Wada air scribe.

FIGURE 8 in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle

FIGURE 8. The assembly drawing of the Wada air scribe and the handle form 1 (A-C) and 2 (D-F). A, insert the air scribe between the left and right arm; B, angle adjustment of the Wada air scribe; C, the Wada air scribe with the handle form 1 in right lateral view; D, insert the air scribe into the body holder and attach them to the support rod; E, angle adjustment of the Wada air scribe; F, the Wada air scribe with the handle form 2.

FIGURE 6. The handle form 1. A in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle

FIGURE 6. The handle form 1. A, production process. The component numbers correspond to those in Figure 2; B, the handle in right lateral view; C, the handle in top view; D, the handle with the socket head screw (M4) in bottom view; E, the handle in left lateral view.