cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/dwnb9fspdn.1
title: Data for: Banking Crises and Exports: Lessons from the Past

description: This dataset and do file allow replicating the results of the paper Banking Crises Banking Crises and Exports: Lessons from the Past. This paper analyzes the impact of banking crises on manufacturing exports, exploiting the fact that sectors differ in their needs for external financing. Relying on data from 160 developed and developing countries during 1970-2012, we analyze 147 banking crisis episodes and separate their impact on export growth from the impact of other exogenous shocks (e.g., demand shocks, exchange rate shocks). Our findings show that during a crisis, the exports of sectors more dependent on external finance grow significantly less than other sectors. However, this result holds only for sectors that depend on banking finance as opposed to interfirm finance (i.e., trade finance or trade credit). For sectors that depend heavily on banking finance, the effect of banking crises on exports is robust, additional to external demand shocks, and not driven by exchange rate shocks. The database includes trade data from WITS for 1976-2012 and from NBER for 1970-1975 at the ISIC rev. 2 3-digits level, crisis data from Laeven and Valencia (2013), a measure of external dependence based on Rajan and Zingales (1998), Trade Credit from Fisman and Love (2003) and Tangibility from Kroszner et al. (2007). A README file is included, explaining how to obtain the results.
DOI: 10.17632/my294r2pgb.1
title: A multiresolution noise-removal algorithm for visual pattern recognition in imaging detectors

description: Abstract An algorithm to process data from imaging detectors is proposed. It performs the preprocessing phase for pattern-recognition tasks to remove noise from input images based on a computer vision model. As an example, the program was applied to reconstruct the pattern of Cherenkov light distributed on a single circle produced and detected by a RICH device at CERN. Title of program: PRIP_ENHANCE Catalogue Id: ACBJ_v1_0 Nature of problem High multiplicity events, generated by recent physics experiments require high granularity detectors in particular those read out by CCD's. These devices produce unambiguous bidimensional representations of spot-composed events thus involving the use of digital image process- ing techniques for data analysis. Random noise from light reflections and CCD noise arise in such a way to elude traditional noise removal methods making unreliable further event pattern recognition strategies. Versions of this program held in the CPC repository in Mendeley Data ACBJ_v1_0; PRIP_ENHANCE; 10.1016/0010-4655(91)90078-Y This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.15468/dl.qfv6xt
title: Occurrence Download

description: A dataset containing 1258 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pinus densiflora Siebold & Zucc.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 1258 records from 102 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009210-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/sxgymx5xjm.1
title: Anthropometric-Data-Aged-2-19-Pak

description: The dataset is of 10,782 children and adolescents, aged 2 to 19 years, who belonged to four major cities of Pakistan including Lahore, Multan, Rawalpindi/Islamabad. The dataset consists of data about variables age (years), gender status (boys/girls), residential city (Multan/ Lahore/ Rawalpindi or Islamabad) and anthropometric measurements i.e., height (0.1cm), weight (kg.), WC (0.1cm), HpC (0.1cm), MUAC (0.1cm), NC (0.1cm) and WrC (0.1cm).
DOI: 10.17632/7grhw5tv7n.4
title: ERCPMPv4: An Endoscopic Image and Video Dataset for Recognition of Colorectal Polyps Morphology and Pathology

description: ERCPMPv4 is an Endoscopic Image and Video Dataset for Recognition of Colorectal Polyps Morphology and Pathology. This dataset contains demographic, morphological and pathological data, endoscopic images and videos of 191 patients with colorectal polyps. Morphological data is included based on the latest international gastroenterology classification references such as Paris, Pit and JNET classification. Pathological data includes the diagnosis of the polyps including Tubular, Villous, Tubulovillous, Hyperplastic, Serrated, Inflammatory and Adenocarcinoma with Dysplasia Grade & Differentiation. ERCPMPv4 is prepared and organized by a team of Gastroenterology, Hematology, Oncology and Artificial Intelligence Experts. ERCPMPv4 is the first version of this dataset and in the later versions, the morphological and pathological data, images and videos will be completed.
DOI: 10.17632/dvgmbh7z3z.1
title: Data for: On the Relation between Financial Reporting Quality and Country Attributes: Research Challenges and Opportunities

description: Dataset with data and variable definitions used in Isidro, Nanda and Wysocki (2019) On the Relation between Financial Reporting Quality and Country Attributes: Research Challenges and Opportunities.
DOI: 10.17632/745w6cxkpz
title: Core code for hw_wpd

description: Core code for hw_wpd
DOI: 10.17632/rgwpd4m785.3
title: Bajwa Hospital (Multi Eye Disease Dataset)

description: This Multi Disease Dataset was created for the study entitled "A Novel Hybrid Algorithm for Feature Selection Based On Optimization." The dataset was collected and compiled on April 20, 2022, at the "Bajwa Hospital, Dina Nagar, Gurdaspur, India". The dataset was created using image assets from three different eye modalities. It contains images of the eye categorised into four distinct categories: normal, cataract, glaucoma, and retinal disease. The dataset consists of  100 fundus images of cataract,  glaucoma, retinal diseases each. The fourth class of images are healthy fundus eye images and 300 is the total number. 
The process of data fusion was used to finally construct the full dataset volume.  Since, Image data is anonymized, and none of the individuals' private information is distributed.
DOI: 10.17632/8chk8vdn2z.1
title: Road Anomaly Detection

description: The dataset for this study was compiled from various sources to ensure a diverse and representative collection of road anomalies. Primary data were gathered by recording videos and capturing images using mobile cameras and surveillance systems in different cities across Pakistan. Additionally, footages were obtained through collaboration with friends, who provided videos from social media platforms and other online sources, including contributions from different countries. This comprehensive approach allowed for the creation of a dataset that encompasses a wide range of scenarios and conditions pertinent to the study's focus on road anomalies.
DOI: 10.17632/fd5wd6wmdj.1
title: Parkinson’s Disease Detection Using Spiral Images (Hand Drawings)

description: Parkinson’s disease (PD), or simply Parkinson’s, is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms usually emerge slowly, and as the disease worsens, non-motor symptoms become more common. The most obvious early symptoms are tremor, rigidity, slowness of movement, and difficulty with walking. Parkinson’s Disease can cause slow motor movements, depression, anxiety, sleep and sensory system disorders, behaviour changes etc. Environmental factors and Genetic Inheritance are amongst the major contributing factors for Parkinson’s disease. Spiral drawing is a skilled and complex coordinated motor activity. Therefore, it is treated as a sensitive motor assessment and a preliminary test for early symptoms of Parkinson’s disease. This article presents a solution for detecting Parkinson’s disease using Spiral Drawings and Convolutional Neural Networks (CNN). The Cainvas Platform is used for implementation, which provides seamless execution of python notebooks for building AI systems that can eventually be deployed on edge (i.e. an embedded system such as compact MCUs). The notebook can be found here. The flow of the article is as follows — Description of the Problem Statement The Dataset Data Augmentation CNN Model Architecture Training the Model Performance of Model Testing models on Images Conclusion Description of the Problem Statement The project aims at presenting a solution for Parkinson’s disease detection using Spiral Drawings and CNN. The main idea behind the implementation is to classify a person as Healthy or having Parkinson’s disease by looking at the Spiral Drawing made by the person. The Spiral Drawing created by a healthy person will look almost similar to a standard spiral shape. However, a spiral drawn by a person with Parkinson’s disease will highly deviate from a perfect spiral shape and look distorted due to slow motor movements and decreased coordination between hand and brain. The Dataset The dataset used here is the Parkinson’s Drawing Dataset present on Kaggle. The dataset can be accessed through this link. The dataset contains Spiral and Waves drawings made by healthy people and Parkinson’s disease infected people. In this article, only Spiral Drawings are used for classification. The dataset already contains the Train Set and the Test Set, so no need to manually split the dataset.
DOI: 10.17632/3s368jpdx2.1
title: Open-source modelling of aerosol dynamics and computational fluid dynamics: Nodal method for nucleation, coagulation, and surface growth

description: Understanding formation, growth and transport of aerosols is critical to processes ranging from cloud formation to disease transmission. In this work, a numerical algorithm of aerosol dynamics including nucleation, coagulation, and surface growth was coupled with flow and heat transfer equations enabling the solution of three-dimensional multi-physics aerosol processes in an open-source platform. The general dynamic equation was solved by a nodal method where the particle size distribution was represented by a finite number of nodes. The models were verified by comparing four test cases, (1) pure coagulation, (2) nucleation and coagulation, (3) pure surface growth, and (4) a general dynamic equation that includes the three mechanisms provided in literature. A high temperature aerosol flow in a cooled pipe is chosen as a tutorial case of coupled computational aerosol and fluid dynamics. The aerosolGDEFoam code is available at https://openaerosol.sourceforge.io and can be further modified under GNU general public licence.
DOI: 10.17632/jxj2r45t2x.1
title: Honeys biological origin by GC-IMS

description: GC-IMS data set of authentic honeys from 3 biological origins: canola, acacia and honeydew. The files are in native .mea format and can e.g. be analyzed by our open source toolbox gc-ims-tools. An exemplary workflow can be found here: http://dx.doi.org/10.1016/j.foodres.2022.111779
DOI: 10.17632/59xmzmcsjz.1
title: deforestation dataset

description: This is a Dataset about deforestation. there is 2010 images from south America rainy forest that we gathered for our research. all images have been extracted from Google Earth.
DOI: 10.17632/5xth87zwb5.1
title: Sanadset: Data on Hadith narrators

description: Sanadset is a full hadith dataset that contains over 368,683 records collected from 926 historical Arabic books of hadith. This dataset can be used for further investigation and classification of hadiths (Strong/Weak), and narrators (trustworthy/not) using AI techniques, and also it can be used as a linguistic resource tool for Arabic Natural Language Processing.
DOI: 10.17632/6jcmyhfhpb.1
title: Data for: High resolution crustal model of SE Tibet from joint inversion of seismic P-wave travel-times and Bouguer gravity anomalies and its implication for the crustal channel flow

description: Crustal P-wave velocity model of SE Tibet from seismic P-wave travel-times
DOI: 10.17632/dvzvr3k9tw.1
title: TREM2 receptor protects against complement-mediated synaptic loss by binding to complement C1q during neurodegeneration

description: By utilizing C3 and C1qa KO mouse models, we evaluated the specificity of the antibodies targeting these proteins by using Western blotting and immunofluorescence staining methods.
DOI: 10.17632/kphtgxn3ff.4
title: A Real-Time Shelf-Life Estimation Model

description: A Shelf-Life Estimation Model built in MATLAB for fresh fruits and vegetables. The model can accept any temperature history, whether simulated or provided by a temperature sensor,  and can account for passively-created modified atmospheres. It has been validated experimentally and found to be most accurate for unsealed non-climacteric products. Much effort has been put into making the model setup process as user-friendly as possible as a user manual has been provided.
DOI: 10.17632/26cgxd9pgz.1
title: Undulating Relativity + § 37 +§ 38

description: Undulating Relativity 
§ 37 Relativistic Transformations
§ 38 Hyperbolic average kinetic energy (Ec ) 
212Pg
DOI: 10.17632/x6vr3sdm75.1
title: DDOS ATTACKS DATASET FOR SOFTWARE DEFINED NETWORK

description: The dataset is made up of 12 features of normal and malicious UDP, ICMP, and TCP traffic from an SDN-emulated network. The features were extracted and computed from the Switch statistics. The dataset can be used for Traffic classification and DDOS attack detection in SDN using various machine learning, neural network, and statistical-based approaches.
DOI: 10.17632/f3bdjxcb4b.1
title: Tourism Recommendation Dataset

description: The reviews are scraped from Trip Advisor using Selenium tool. These are reviews about TajMahal and Periyar Tiger Reserve.
DOI: 10.17632/w4ttp6d7pb.1
title: Spatio-temporal graffiti in Belfast

description: To capture the multidimensional aspects of Belfast’s evolving muralscape we created an original dataset of graffiti images organised by the ‘site’ (general spatial area in which data collection was bound) in which they were collected and the ‘set’ (the entire range of temporal data collected in relation to a precise spatial location) to which they belong. We collated a total of 147 graffiti sets, spanning six predefined data collection sites within the database. Each set contains anywhere from two to 24 pieces of visual data, with a total of 680 individual pieces collected. The dataset is organised along axis of space and time to generate a visual record. Each mural set is geotagged by its Global Positioning System (GPS) coordinates. To construct the dataset, we defined temporal and spatial bounds. We limited the data collection to the years 1998 to 2022. These temporal bounds were set in line with the signing of the Good Friday Agreement, which marked a significant will to alter attitudes and ideologies for the sake of peace. We stopped recording new pieces in November 2022. The six sites are: the divided estates surrounding the Unionist Shankill and Nationalist Falls Roads, the interface area between them, a shared area surrounding the Royal Victoria hospital, an area along the Newtownards Road referred to as ‘Freedom Corner’ in East Belfast, and in predominantly Nationalist West Belfast we chose the area in the Gaeltacht Quarter where the Glenalina and Whiterock Roads intersect. The dataset allows for analysis on the temporal and spatial dimensions of murals in Belfast, creating understandings of changes in the way that the new messaging and imagery is thought through and painted for the public, offering a useful lens into local understanding of self and other. In concentrating on when and where graffiti is painted local political and social understandings can be deepened by understanding the way that murals change, or remain the same, across time. While the dataset is relatively small, building it has enabled us to tailor it to our project and research questions and set the spatial and temporal boundaries exactly as required. It allowed us unique insights into Belfast’s muralscape since the Good Friday Agreement. Given the novelty of the dataset, we invite other researchers to use it for further research or expand it further. While the geographical focus of this particular dataset is on Belfast, it also serves as a model that can be replicated for similar analysis in other geographical areas. Note: we consulted the following online and open access data sources to build our data set: the Extramural Activity interactive mural map, the Peter Moloney Collection (itself partly embedded within the Extramural Activity map), the Claremont College Collection, and Google Street View. Please use original attribution for any images used.
DOI: 10.17632/hvfh9yvncf.1
title: DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

description: Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in Python/C++ that has been designed to minimize the effort required to build deep learning based representation of potential energy and force field and to perform molecular dynamics. Potential applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems. DeePMD-kit is interfaced with TensorFlow, one of the most popular deep learning frameworks, making the training process highly automatic and efficient. On the other end, DeePMD-kit is interfaced with high-performance classical molecular dynamics and quantum (path-integral) molecular dynamics packages, i.e., LAMMPS and the i-PI, respectively. Thus, upon training, the potential energy and force field models can be used to perform efficient molecular simulations for different purposes. As an example of the many potential applications of the package, we use DeePMD-kit to learn the interatomic potential energy and forces of a water model using data obtained from density functional theory. We demonstrate that the resulted molecular dynamics model reproduces accurately the structural information contained in the original model.
DOI: 10.17632/fn3cxdbnm8.1
title: Data for: Model of DC tunneling conductivity via hydrogen-like impurities in heavily doped compensated semiconductors

description: File "Tunneling.m" provides Mathematica code for reproduction of Table 2 of the article. See "Tunneling.pdf" for the results of the code execution.
DOI: 10.17632/y3fbhpmz83.1
title: Excel Binomial Interest Rate Calibration Model

description: The Excel program generates a binomial interest rate tree based on the Black-Derman-Toy Calibration Model. The user inputs up and down parameters, the probability of an increase in one period, and spot yield curve.
DOI: 10.17632/txn9pj4nn4.1
title: Fiji Sigatoka MCDA-GIS Data

description: The research objective of this paper was to present a set of methods that use a combination of GIS and MCDA to evaluate land suitability for a selection of target crops for agroforestry spatial planning. The first objective is to show how commonly available edaphic and environmental cultivation criteria for agroforestry crops (through websites such as https://agroforestry.org/) can be used within a GIS to identify the most suitable areas for target crops. Because suitable land areas for target crops overlap, there is the issue of deciding which locations are best suited to which crops. The second objective is to present ways of dealing with the problem of deciding where a suite of target crops should be planted. We first look at a method that deals with this problem using an equitable distribution approach—one that distributes the crops to locations based on the proportion of suitable land available to each crop. We then examine a method that uses expert knowledge and MCDA to quantify the relative benefits of each crop and determines the spatial distribution of crops most suitable for different agroforestry strategic goals. In this repository you will find the ArcGIS Pro v 2.5 project with accompanying GIS and and models for our case study. In addition you will find the Excel tables used for AHP calculations. Land Suitability model: The default cultivation parameters are for Tropical almond. See the manuscript for other crop parameters. Weighted Maximum model: The default weights are for the Economic benefit. See the manuscript for AHP weightings of other benefits. See README.txt file for more details
DOI: 10.17632/y4phg9crjt.1
title: Data for: Delineation of groundwater potential areas at Wadi El-Arish, Sinai, Egypt, using geospatial and geophysical techniques

description: The outline of the study area
DOI: 10.17632/mv8hndcd95.2
title: The ECOCAPTURE ethograms: apathy ethogram and disinhibition ethogram

description: This dataset provides two ethograms: the ECOCAPTURE apathy ethogram and the ECOCAPTURE disinhibition ethogram. 

The ECOCAPTURE apathy ethogram includes 13 behaviors and 31 modifiers divided in two behavioral categories: motor patterns, activity states. 
The ECOCAPTURE disinhibition ethogram includes 16 behaviors divided in three disinhibition categories: compulsivity, impulsivity, social disinhibition. 

The ECOCAPTURE protocol [1,2] developed at ICM [3], was designed to assess neuropsychiatric symptoms, such as apathy [4] and disinhibition [5], in natural settings and under a controlled scenario. 
The ECOCAPTURE scenario mimics a naturalistic situation (i.e., waiting comfortably in a waiting room). 
The experiments took place on the ICM’s core facility (PRISME) [6] dedicated to the functional exploration of human behavior.
The PRISME platform was equipped with a six-ceiling camera system (not hidden) covering the entire waiting room. 
During the experiment, individuals’ behavior was video-recorded. The subjects were informed at the time of initial consent that their behavior would be tracked and recorded by video cameras located in the room. 


[1] Institut National de la Santé Et de la Recherche Médicale, France. Quantitative Evaluation of Apathy Close to Real Life Situation by Means of a Multimodal Sensor System Integrated in Healthy Subjects and Patients With Frontotemporal Dementia. Pilot Phase. clinicaltrials.gov; 2017. https://clinicaltrials.gov/ct2/show/NCT02496312 
[2] Institut National de la Santé Et de la Recherche Médicale, France. Assessment of Apathy in a Real-Life Situation, With a Video and Sensors-Based System in Healthy Subject and Patient With Cerebral Disease. clinicaltrials.gov; 2019. https://clinicaltrials.gov/ct2/show/NCT03272230 
[3] Paris Brain Institute (ICM). Institut du Cerveau. https://institutducerveau-icm.org/en/ 
[4] Batrancourt B, Lecouturier K, Ferrand-Verdejo J, et al. Exploration Deficits Under Ecological Conditions as a Marker of Apathy in Frontotemporal Dementia. Front Neurol. 2019;10:941. doi:10.3389/fneur.2019.00941
[5] Godefroy V, Tanguy D, Bouzigues A, et al. Frontotemporal dementia subtypes based on behavioral inhibition deficits. Alzheimers Dement Diagn Assess Dis Monit. 2021;13(1):e12178. doi:10.1002/dad2.12178
[6] PRISME : human behavior exploration core facility. Institut du Cerveau. https://institutducerveau-icm.org/fr/prisme-human-behavior-exploration-core-facility/