cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3271648
title: Flashlight-fish-dataset

description: Dataset frames of flashlight fish collected using Hamamatsu camera. Paper title: <strong>Bioluminescent Flashes Drive Nighttime Schooling Behavior and Synchronized Swimming Dynamics in Flashlight Fish</strong> Authors: David F. Gruber<sup>1,2</sup>, Brennan T. Phillips<sup>3</sup>, Rory O’Brien<sup>4</sup>, Vivek Boominathan<sup>5</sup>, Ashok Veeraraghavan<sup>5</sup>, Ganesh Vasan<sup>4</sup>, Peter O’Brien<sup>4</sup>, Vincent A. Pieribone<sup>4</sup> and John S. Sparks<sup>6</sup> <sup>1</sup>Baruch College, City University of New York, Department of Natural Sciences, New York, NY 10010, USA <sup>2</sup>City University of New York The Graduate Center Program in Biology, New York, NY 10016, USA <sup>3</sup>University of Rhode Island, Department of Ocean Engineering, Narragansett, RI 02882, USA <sup>4</sup>The John B. Pierce Laboratory Cellular and Molecular Physiology Yale University School of Medicine, New Haven, CT 06519, USA <sup>5</sup>Rice University, Department of Electrical and Computer Engineering, Houston, Texas, USA <sup>6</sup>American Museum of Natural History, Division of Vertebrate Zoology, Department of Ichthyology, New York, NY 10024, USA Correspondence: David.Gruber@Baruch.cuny.edu
DOI: 10.5281/zenodo.3271649
title: Flashlight-fish-dataset

description: Dataset frames of flashlight fish collected using Hamamatsu camera. Paper title: <strong>Bioluminescent Flashes Drive Nighttime Schooling Behavior and Synchronized Swimming Dynamics in Flashlight Fish</strong> Authors: David F. Gruber<sup>1,2</sup>, Brennan T. Phillips<sup>3</sup>, Rory O’Brien<sup>4</sup>, Vivek Boominathan<sup>5</sup>, Ashok Veeraraghavan<sup>5</sup>, Ganesh Vasan<sup>4</sup>, Peter O’Brien<sup>4</sup>, Vincent A. Pieribone<sup>4</sup> and John S. Sparks<sup>6</sup> <sup>1</sup>Baruch College, City University of New York, Department of Natural Sciences, New York, NY 10010, USA <sup>2</sup>City University of New York The Graduate Center Program in Biology, New York, NY 10016, USA <sup>3</sup>University of Rhode Island, Department of Ocean Engineering, Narragansett, RI 02882, USA <sup>4</sup>The John B. Pierce Laboratory Cellular and Molecular Physiology Yale University School of Medicine, New Haven, CT 06519, USA <sup>5</sup>Rice University, Department of Electrical and Computer Engineering, Houston, Texas, USA <sup>6</sup>American Museum of Natural History, Division of Vertebrate Zoology, Department of Ichthyology, New York, NY 10024, USA Correspondence: David.Gruber@Baruch.cuny.edu
DOI: 10.5281/zenodo.2580023
title: Dataset: Decay of Torsional Stiffness of RC U-shaped Walls When Subjected Simultaneously to In-Plane Loading

description: Reinforced concrete U-shaped walls are a popular construction choice, commonly used to resist the lateral loads from wind and earthquakes. When subjected to earthquake ground motions, it is likely that these structural elements will not only bend in flexure but twist due to asymmetries of the building plan layout and the location of the shear center outside of the section. This research investigates the dependency of the torsional stiffness of U-shaped walls on the in-plane translational displacement demands using novel experimental evidence and advanced numerical models. The experimental results show that for a given flexural position, the torsional stiffness decreases with increasing in-plane translational displacement. Furthermore, the numerical and experimental results indicate that when the wall is centered the torsional stiffness degrades at the same rate at the translational stiffness of the walls. Thus, the torsional stiffness of a U-shaped wall as a function of ductility can be estimated using the translational secant stiffness. The numerical results also show that the torsional stiffness increases as a function of the axial load ratio of the wall. The experimental and numerical dataset from this research investigation can be downloaded from a publicly accessible repository.
DOI: 10.5281/zenodo.2580024
title: Dataset: Decay of Torsional Stiffness of RC U-shaped Walls When Subjected Simultaneously to In-Plane Loading

description: Reinforced concrete U-shaped walls are a popular construction choice, commonly used to resist the lateral loads from wind and earthquakes. When subjected to earthquake ground motions, it is likely that these structural elements will not only bend in flexure but twist due to asymmetries of the building plan layout and the location of the shear center outside of the section. This research investigates the dependency of the torsional stiffness of U-shaped walls on the in-plane translational displacement demands using novel experimental evidence and advanced numerical models. The experimental results show that for a given flexural position, the torsional stiffness decreases with increasing in-plane translational displacement. Furthermore, the numerical and experimental results indicate that when the wall is centered the torsional stiffness degrades at the same rate at the translational stiffness of the walls. Thus, the torsional stiffness of a U-shaped wall as a function of ductility can be estimated using the translational secant stiffness. The numerical results also show that the torsional stiffness increases as a function of the axial load ratio of the wall. The experimental and numerical dataset from this research investigation can be downloaded from a publicly accessible repository.
DOI: 10.5281/zenodo.3271411
title: SRTM y WorldClim para Curso de mapeo digital de suelos

description: Datos requeridos para Curso Introductorio al Mapeo digital de suelos https://github.com/angelini75/Curso-introductorio-a-MDS
DOI: 10.5281/zenodo.3271412
title: SRTM y WorldClim para Curso de mapeo digital de suelos

description: Datos requeridos para Curso Introductorio al Mapeo digital de suelos https://github.com/angelini75/Curso-introductorio-a-MDS
DOI: 10.21227/yexn-cd06
title: Health_Care_and_Insurance

description: The data set with 20,936 data records and 525 attributes concerns Chinese healthcare and insurance.
DOI: 10.17632/myvr4dpvk7.3
title: The content of 43 elements as determined by INAA in 29 mosse samples from Western Tajikistan

description: The data-set contains numerical values of 43 major as well as trace elements in Hylocomium splendens mosses as determined by Epithermal Neutron Activation Analysis for 29 collecting points located in the Western Tajikistan. All measurements were performed at the IBR 2 reactor of the Frank Neutron Physics Laboratory of the Joint Institute for Nuclear Research in Dubna, Russian Federation. For each collecting points longitude, latitude as well as altitude are provided.
DOI: 10.5445/ir/1000095498
title: Datasets from MIPAS and GLORIA infrared limb-sounding instruments, from AIDA cloud-chamber observations and from ATLAS and TRACZILLA trajectory calculations as used in the paper 'M. Höpfner et al., Ammonium nitrate particles formed in upper troposphere from ground ammonia sources during Asian monsoons', Nature Geoscience, 2019.
DOI: 10.21227/865v-9y24
title: iChallenge-PALM: PAthoLogic Myopia Challenge

description: Pathologic Myopia Challenge (PALM), as a part of the serial challenge iChallenge, is organized as a half day Challenge, a Satellite Event of the ISBI 2019 conference in Venice, Italy. The PALM challenge focuses on the investigation and development of algorithms associated with the diagnosis of Pathological Myopia (PM) and segmentation of lesions in fundus photos from PM patients. The goal of the challenge is to evaluate and compare automated algorithms for the detection of pathological myopia on a common dataset of retinal fundus images. In PALM challenge, we provide 1200 images with annotations as 400 training images, 400 validation images, and 400 test images.Challenge Homepage: https://palm.grand-challenge.org
DOI: 10.21227/e4dd-ez82
title: iChallenge-PALM: PAthoLogic Myopia Challenge

description: Pathologic Myopia Challenge (PALM), as a part of the serial challenge iChallenge, is organized as a half day Challenge, a Satellite Event of the ISBI 2019 conference in Venice, Italy. The PALM challenge focuses on the investigation and development of algorithms associated with the diagnosis of Pathological Myopia (PM) and segmentation of lesions in fundus photos from PM patients. The goal of the challenge is to evaluate and compare automated algorithms for the detection of pathological myopia on a common dataset of retinal fundus images. In PALM challenge, we provide 1200 images with annotations as 400 training images, 400 validation images, and 400 test images.Challenge Homepage: https://palm.grand-challenge.org
DOI: 10.17638/datacat.liverpool.ac.uk/908
title: In vitro and computational modelling of drug delivery across the outer blood retinal barrier

description: Simulation data obtianed using COMSOL Multiphysics software.
DOI: 10.5281/zenodo.3266059
title: Gradient Boosting Machine Learning to Improve Satellite-Derived Column Water Vapor Measurement Error

description: <strong>The atmospheric products of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm include column water vapor (CWV) at 1 km resolution, derived from daily overpasses of NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the Aqua and Terra satellites. We have recently shown that machine learning using extreme gradient boosting (XGBoost) can improve the estimation of MAIAC aerosol optical depth (AOD). Although MAIAC CWV is generally well validated (Pearson’s R &gt;0.97 versus CWV from AERONET sun photometers), it has not yet been assessed whether machine-learning approaches can further improve CWV. Using a novel spatiotemporal cross-validation approach to avoid overfitting, our XGBoost model with nine features derived from land use terms, date, and ancillary variables from the MAIAC retrieval, quantifies and can correct a substantial portion of measurement error relative to collocated measures at AERONET sites (27.8% and 15.5% decrease in Root Mean Square Error (RMSE) for Terra and Aqua datasets, respectively) in the Northeastern USA, 2000-2015. We use machine-learning interpretation tools to illustrate complex patterns of measurement error and describe a positive bias in MAIAC Terra CWV worsening in recent summertime conditions. We validate our predictive model on MAIAC CWV estimates at independent stations from the SuomiNet GPS network where our corrections decrease the RMSE by 17% and 8% for Terra and Aqua MAIAC CWV. Empirically correcting for measurement error with machine-learning algorithms is a post-processing opportunity to improve satellite-derived CWV data for Earth science and remote sensing applications.</strong>
description: The datasets in the zip file are JSON files that can be opened directly in browsers, text editor, or R using functions like `jsonlite::fromJSON`.
DOI: 10.25345/c5d656
title: MassIVE MSV000084065 - A novel translocon for biogenesis of multi-pass membrane proteins
title: A novel 370 kDa translocon comprising Sec61 and five accessory factors acting co-translationally with ribosomes to fold and insert multi-pass membrane proteins was identified, purified and analyzed structurally by single particle cryo-EM and cross-linking mass spectrometry. The purified ribosome-translocon complex was cross-linked with DSS, trypsin digested, and size-exclusion enriched (SEC) cross-link containing fractions were analyzed by sequential HCD/ETD of the same precursor ion. The four LC-MS runs corresponding to SEC fractions eluting between 0.9-1.4 ml are deposited here.
DOI: 10.5281/zenodo.3271792
title: BARCAN data base

description: The BARCAN project aimed at studying the morphodynamics of a near-shore bar. Special attention was devoted to the effects of infragravity waves. Experiments in a small-scale physical model with light-weight sediment were conducted, and the hydrodynamics was simulated with a Boussinesq-type numerical model (SERR1D). The data base is the set of measurements (including water surface elevation, flow velocities and bed profile changes) and results of numerical simulations, see details in the accompanying note and paper submitted to JGR.
DOI: 10.5061/dryad.7ht92p7/1
title: Dryad Item 10.5061/DRYAD.7HT92P7/1

description: (:tba)
DOI: 10.5061/dryad.7ht92p7/2
title: Dryad Item 10.5061/DRYAD.7HT92P7/2

description: (:tba)
DOI: 10.5061/dryad.7ht92p7/3
title: Dryad Item 10.5061/DRYAD.7HT92P7/3

description: (:tba)
DOI: 10.5061/dryad.7ht92p7/4
title: Dryad Item 10.5061/DRYAD.7HT92P7/4

description: (:tba)
DOI: 10.5281/zenodo.3271624
title: Hand gestures raw images

description: This dataset includes 4 categories of hand gestures: open hand, fist, right hand, left hand + one negative class
DOI: 10.5281/zenodo.3271625
title: Hand gestures raw images

description: This dataset includes 4 categories of hand gestures: open hand, fist, right hand, left hand + one negative class
DOI: 10.5281/zenodo.3241876
title: FT25 Savary Jeune (2) 13-key fagottino: measurements, photos, endoscopic video

description: Dataset of FT25 Savary Jeune (2)13-key fagottino containing detailed external and internal measurements, photos, and an endoscopic video.
DOI: 10.5281/zenodo.3241877
title: FT25 Savary Jeune (2) 13-key fagottino: measurements, photos, endoscopic video

description: Dataset of FT25 Savary Jeune (2)13-key fagottino containing detailed external and internal measurements, photos, and an endoscopic video.
DOI: 10.13012/b2idb-4551278_v1
title: Wikipedia category embeddings - Node2Vec, Poincare, Elmo

description: Wikipedia category tree embeddings based on wikipedia SQL dump dated 2017-09-20 (https://archive.org/download/enwiki-20170920) created using the following algorithms: * Node2vec * Poincare embedding * Elmo model on the category title The following files are present: * wiki_cat_elmo.txt.gz (15G) - Elmo embeddings. Format: category_name (space replaced with "_") 300 dim space separated embedding. * wiki_cat_elmo.txt.w2v.gz (15G) - Elmo embeddings. Format: word2vec format can be loaded using Gensin Word2VecKeyedVector.load_word2vec_format. * elmo_keyedvectors.tar.gz - Gensim Word2VecKeyedVector format of Elmo embeddings. Nodes are indexed using * node2vec.tar.gz (3.4G) - Gensim word2vec model which has node2vec embedding for each category identified using the position (starting from 0) in category.txt * poincare.tar.gz (1.8G) - Gensim poincare embedding model which has poincare embedding for each category identified using the position (starting from 0) in category.txt * wiki_category_random_walks.txt.gz (1.5G) - Random walks generated by node2vec algorithm (https://github.com/aditya-grover/node2vec/tree/master/node2vec_spark), each category identified using the position (starting from 0) in category.txt * categories.txt - One category name per line (with spaces). The line number (starting from 0) is used as category ID in many other files. * category_edges.txt - Category edges based on category names (with spaces). Format from_category to_category * category_edges_ids.txt - Category edges based on category ids, each category identified using the position (starting from 1) in category.txt * wiki_cats-G.json - NetworkX format of category graph, each category identified using the position (starting from 1) in category.txt Software used: * https://github.com/napsternxg/WikiUtils - Processing sql dumps * https://github.com/napsternxg/node2vec - Generate random walks for node2vec * https://github.com/RaRe-Technologies/gensim (version 3.4.0) - generating node2vec embeddings from random walks generated usinde node2vec algorithm * https://github.com/allenai/allennlp (version 0.8.2) - Generate elmo embeddings for each category title Code used: * wiki_cat_node2vec_commands.sh - Commands used to * wiki_cat_generate_elmo_embeddings.py - generate elmo embeddings * wiki_cat_poincare_embedding.py - generate poincare embeddings
DOI: 10.5066/p986q3yt
title: Estimates of discharge from wastewater treatment plants for 1,518 U.S. Geological Survey study watersheds, 1978 through 2012

description: This product consists of a table of annual discharge estimates in millions of gallons per day from wastewater treatment plants (WWTPs) for 1,518 watersheds in the conterminous United States. The data are based on information extracted from the U.S. Environmental Protection Agency's Clean Watersheds Needs Survey. The data are for 13 time periods, beginning in 1978 and ending in 2012. Total nitrogen and phosphorus loads from WWTPs per watershed for each year are also provided, based on previously published data (Falcone, 2017). Falcone, J.A., 2017, Watershed characteristics for study sites of the Surface Water Trends project, National Water Quality Program: U.S. Geological Survey data release, https://doi.org/10.5066/F7TX3CKP. Oelsner, G.P., Sprague, L.A., Murphy, J.C., Zuellig, R.E., Johnson, H.M., Ryberg, K.R., Falcone, J.A., Stets, E.G., Vecchia, A.V., Riskin, M.L., De Cicco, L.A., Mills, T.J., and Farmer, W.H., 2017, Water-quality trends in the Nation's rivers and streams, 1972-2012 -- Data preparation, statistical methods, and trend results: U.S. Geological Survey Scientific Investigations Report 2017-5006, 136 p., https://doi.org/10.3133/sir20175006.
DOI: 10.14457/cu.the.2013.1868
title: Prevalence of potentially inappropriate medication (PIM) and factors associated with PIM in elderly outpatient prescriptions at a district hospital in the Southern region of Thailand

description: The aims of study are to know the prevalence of, and to describe factors associated with prescribing PIM at a district hospital in the south of Thailand. In this cross-sectional study, the elderly patients were a ≥ 65-year outpatient and had at least 1 prescribed medication from the hospital. Overall patients were 430 with 2,128 prescriptions. 2012 Beers criteria were applied to detect PIM. Prevalence of PIM was calculated by their total prescriptions. Prescription, patient, and prescriber characteristics associated with PIM were analyzed by logistic regression. Results showed that 28% of total prescriptions had at least 1 PIM. There was the more likelihood of PIM prescription at outpatient department increased significantly when that prescription comprised of more than 5 medications (p&lt;0.001). The positive association between age of participant and the presence of PIM prescription was observed (OR=1.018, p= 0.040, CI=1.001-1.035). Interestingly, the elderly outpatients who had more frequent outpatient visits had less PIM prescription as compared to reference group, who had 1-3 visits. (4-6 vs. ≥7: OR = 0.581 [95%CI=0.408-0.828], p=0.003 vs. OR=0.704 [95%CI=0.526-0.943], p=0.019) No statistically significant association between the presence of PIM and patient's gender, number of diagnoses, Types of health insurance schemes, hospitalizations, prescriber's gender, ages, types of prescriber and length of prescriber's years work was observed.
DOI: 10.14457/cu.the.2013.1869
title: Health seeking behaviors in influenza-like illness among healthcare providers in Angthong Province, Thailand

description: This cross-sectional study aimed to describe and determine relationship betweeninfluencing factors and health seeking behaviors (HSB) in influenza-like illness (ILI) among 290 of physicians, dentists, and nurses in 7 hospital in Angthong. The most were 35 - 50 years old and 92.8% were female. They were nurses 84.8%, physicians and dentists7.6% for each group. Only 65,22.4% had underlying disease and 38.3% got ILI during 1-3 months ago. Hand washing was the most way they behave (97.6%) and gloves were always used 74.5%. Annual checkup was performed 92.4%. Television was a mass media which used the most (205, 70.7%). 42.5% were confidence to take care themselves when they got ILI 67.9% got influenza vaccination in 2012. They were aware more about influenza transmission to their patients (228, 78.6%) and 233 (80.3%) thought influenza vaccination was a part of their responsibility. 55.2% had basic knowledge about influenza Inappropriate behavior; These influencing factors including male, more awareness of influenza transmission to patient, using PPE, and time since the most recent ILI were influencing factors of do nothing HSB. Male was more likely to do this HSB than female (OR= 10.09, p-value&lt;0.001, 95%CI 3.122-32.612). And high score of knowing reason for staying at home was less likely to do self-medication without suggestion (OR= 0.86, p-value&lt;0.015, 95%CI 0.764-0.971). Appropriate behavior; Influencing factors of self-medication with suggestion were using PPE, perception score and time since the most recent ILI. Using PPE was more likely to do this HSB than less use (OR= 1.29, p-value&lt;0.016, 95%CI 1.049-1.582). Influencing factor of see doctor were male, married (ref=single), knowing cause of ILI, exposed to mass media, and perception score. Exposed to mass media was more likely to see doctor than unexposed (OR= 2.89, p-value&lt;0.011, 95%CI 1.279-6.521). Influencing factor of rest at home were knowing how to prevent seasonal influenza and dentist (ref= doctor). Dentist was more likely to rest at home than doctor (OR= 8.50, p-value &lt;0.014, 95%CI 1.549-46.611). *Very few of the study factors were significant with health seeking behaviour, suggesting that more researches needed to understand the determinate of the these behaviours.
DOI: 10.5281/zenodo.3272764
title: Supporting Multiscale Maritime Governance through Maritime Spatial Planning Relevant Tools and Assessment Techniques in the Adriatic-Ionian Macroregion

description: The dataset included in the database were developed according to the mentioned Maritime Spatial Planning relevant governance schemes for the Adriatic-Ionian Macroregion. All spatial data were projected to the UTM33 north. The spatial and non-spatial databases were developed for the specific research entitled "Supporting Multiscale Maritime Governance Through Maritime Spatial Planning Relevant Tools and Assessment Techniques in the Adriatic-Ionian Macroregion".
DOI: 10.5281/zenodo.3272765
title: Supporting Multiscale Maritime Governance through Maritime Spatial Planning Relevant Tools and Assessment Techniques in the Adriatic-Ionian Macro Region

description: The datasets included in the database were developed according to the mentioned Maritime Spatial Planning relevant governance schemes for the area of Adriatic-Ionian macro region. All spatial data were projected to the UTM33 north. These datasets were developed for the specific research entitled "Supporting Multiscale Maritime Governance Through Maritime Spatial Planning Relevant Tools and Assessment Techniques in the Adriatic-Ionian Macro Region".
DOI: 10.17632/6b296z3dg3.1
title: Data for: Complex diffusion-weighted image estimation via matrix recovery under general noise models

description: Tools for complex DWI denoising using SVD shrinkage, adult and neonatal examples