Find research datasets worth reusing

opencc-by-4.0Jan 2024View details →

Water surface occurrence and recurrence from the article "Amazon's 2023 Drought: Sentinel-1 Reveals Extreme Rio Negro River Contraction"

This data package contains the 10 m spatial resolution occurrence and recurrence water surface masks from the article "Amazon's 2023 Drought: Sentinel-1 Reveals Extreme Rio Negro River Contraction" . These maps have been produced with Sentinel-1 images (10 m) and a Deep Learning method for image segmentation called U-net, methods and data are fully described in the article. Water surface occurrence is computed for the period 2022-2023 and indicates the percentage of time that a pixel is classified as water (100%: always water, 0%: never water, and values between 0 and 100 indicate seasonality). Water surface recurrence is computed for the period 2022-2023 and indicates the number of times that a pixel was classified as a water surface, i.e., 35 indicates that the pixel was classified 35 times as a water surface during the 2022-2023 period. The total size of the dataset is 158 Mo and is distributed in two Geotiffs, one for the water surface occurence and one for the water surface. When using this dataset, please cite the original article <a href="https://doi.org/10.3390/rs16061056">https://doi.org/10.3390/rs16061056</a>

opencc-by-4.0Jan 2021View details →

Dataset: A Fly in the Ointment: An Empirical Study on the Characteristics of Ethereum Smart Contracts Code Weaknesses and Vulnerabilities

Dataset: A Fly in the Ointment: An Empirical Study on the Characteristics of Ethereum Smart Contracts Code Weaknesses and Vulnerabilities Majd Soud, Grischa Liebel, Mohammad Hamdaqa majd18@ru.is, grischal@ru.is, mhamdaqa@polymtl.ca. This Dataset includes the following:  1. "labeling.xml" files that represents the data for Categories of vulnerabilities in Smart Contracts for four data sources (i.e., Common Vulnerability and Exposure (CVE), Smart Contract Weakness Classification Registry (SWC), Stack Overflow, and GitHub) XML files structure: The XML files can be opened used any editor or any code editor (e.g. Visual Studio Code). 1. Each file has a root that is <Card_Table></Card_Table> which contains all the cards we labeled.  2. Each card is represented by the <Card></Card> and contains the following:             - The tag marked by <Tag> represents the keyword that was used to search and collect the card from StackOverflow.              - The URL marked by <URL> of the URL link which contains all the information of the labeled vulnerability.               - The other tages marked by <OtherTags> that shows all the tags used in the post on Stack Overflow.              - The expert labeling for the categories of vulnerabilities in each card is represented by  <CategoryExpertLabel>             - In more details, some records has the <SecondExpertCategoryLabel> that represents the second expert labeling for the categories of vulnerabilities.             - The <CategoryAgreement> used to calculate the inter-rater agreement between the two labelers.

opencc-by-4.0Mar 2021View details →

Values, distributions and approximations of the empirical liquidity cost function for various futures contracts.

The figures presents the values, distributions and approximations of the empirical liquidity cost function for various futures contracts. The raw data was obtained from the LOB snapshots for the cash-settled futures contracts on the RTS index (RI), on Brent oil (BR) and FX-rate of US dollar versus Russian ruble (Si). The data corresponds to the period from 05 May 2020 to 26 Feb 2021. The tables summarize the results.

Dataset for review on innovative contracts for the promotion of biodiversity and ecosystem services in agricultural management: contract design and governance characteristics

Dataset for H2020 project Contracts2.0 (GA No 818190), WP2, Task 2.1, Deliverable 2.1. This dataset contains the information needed to reproduce the results in: Bredemeier, Birte; Herrmann, Sylvia; Sattler, Claudia; Prager, Katrin; van Bussel, Lenny, Rex, Julia (submitted): Can the greater integration of biodiversity and ecosystem services into agricultural management be achieved through innovative contract design? Submitted to Ecosystem Services. The Contracts2.0 project aims to develop novel contract-based approaches to incentivise farmers for the increased provision of environmental public goods alongside private goods. Based on a literature review and integration of expert knowledge, we identified a comprehensive set of approaches to innovative contracts deviating from mainstream AECM contracts, and provide an overview of the variety of contracts currently being tested and experimented with. This includes different contract types like innovative Payments for Ecosystem Services (PES) approaches, value chain approaches and land tenure contracts, as well as their hybrids. We analysed 62 cases providing insights into characteristics of contract design and contract governance and the wider policy framework. The present dataset contains information on the criteria and specifications used to describe the cases studied, as well as the evaluation of each case. This information has been compiled to the best of our knowledge based on the sources available. For further information on the project Contracts2.0, please visit our website www.project-contracts20.eu.

opencc-by-4.0Dec 2022View details →

JuVer Contract Corpus

This corpus consists of 2110 PDF Files and 2110 XML files with the text extracted from the PDF files. All PDF files are contracts in German publically available on the internet. Most of these contracts are from the city governments of Hamburg and Bremen and were collected from the websites <a href="http://suche.transparenz.hamburg.de/dataset?q=vertrag&esq_title=&check_all_">http://suche.transparenz.hamburg.de/dataset?q=vertrag&esq_title=&check_all_</a> and  https://<a href="https://www.transparenz.bremen.de">www.transparenz.bremen.de</a>. In the XML files the texts are segmented into sentences. Each sentence also has some additional information on the freuency of use in the corpus. The root of each XML file is the element document, that has a referece to the original PDF in an attribute. A document is divided into pages. Pages then consists of the elements heading and sentence. Each sentence has two identifiers, sid for the sentece and cid for the cluster it belongs to. Sentenecs with the same sentence identifier are identical. Sentences with the same cluster identifier are very similar but not necessarily identical.  Sentences were clustered with single link clustering based on trigram (character) overlap. The corpus consists of 106,539 (non-unique) sentences and 3,635,371 tokens, including interpunction.

opencc-by-4.0Jan 2023View details →

Blockchain and Smart Contracts Topics on Reddit

This dataset includes posts related to Ethereum, Stellar, Algorand, Hyperledger, and smart contracts subreddits. The dataset includes URL, title, author, number of comments, and technology (Ethereum, Stellar, etc.). This dataset is used to spot relevant smart contracts topics Reddit's community discusses. Please consider that this dataset will be extended with more information and smart contracts platform-related subreddits.

opencc-by-4.0Dec 2019View details →

Mutation testing of smart contracts at scale

Replication package for the paper <a href="https://arxiv.org/abs/1909.12563">Mutation testing of smart contracts at scale</a>. It is crucial that smart contracts are tested thoroughly due to their immutable nature. Even small bugs in smart contracts can lead to huge monetary losses. However, testing is not enough; it is also im- portant to ensure the quality and completeness of the tests. There are already several approaches that tackle this challenge with mutation test- ing, but their effectiveness is questionable since they only considered small contract samples. Hence, we evaluate the quality of smart contract mutation testing at scale. We choose the most promising of the existing (smart contract specific) mutation operators, analyse their effectiveness in terms of killability and highlight severe vulnerabilities that can be in- jected with the mutations. Moreover, we improve the existing mutation methods by introducing a novel killing condition that is able to detect a deviation in the gas consumption, i.e., in the monetary value that is required to perform transactions.

opencc-by-4.0Dec 2019View details →

Influence of Paleolithic Range Contraction, Admixture and Long-Distance Dispersal on Genetic Gradients of Modern Humans in Asia

Each folder is identified according to the scenario, and contains another folder with the input files (files *.txt, *.par, *.sam, *.asc) to simulate it, the corresponding simulated genetic data (files *.arp) and the derived PC maps (files *.png). A file with the locations of the samples is also included (coord.txt). * Pure Paleolithic expansion *  The folder “Paleo” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a pure Paleolithic expansion, ignoring the range contraction induced by the LGM and LDD events. * Pure Paleolithic expansion considering the range contraction induced by the LGM *  The folder “Paleo_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a pure Paleolithic expansion suffering the range contraction induced by the LGM.  * Pure Paleolithic expansion considering long-distance dispersal (LDD) events *  The folder “Paleo_LDD” contains the input files (INFILES), the genetic data  and the corresponding PC maps simulated under the scenario of a pure Paleolithic expansion considering LDD events.  * Paleolithic expansion followed by two Neolithic expansions (IR=0) from Middle East and East Asia considering the range contraction induced by the LGM *  The folder “Paleo2NeoIR0_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by two Neolithic expansions (IR=0) from Middle East and later from East Asia suffering the range contraction induced by the LGM.  * Paleolithic expansion followed by two Neolithic expansions (IR=0) from Middle East and East Asia considering LDD events *  The folder “Paleo2NeoIR0_LDD” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by two Neolithic expansions from Middle East and later from East Asia considering LDD events.  * Paleolithic expansion followed by a single Neolithic expansion (IR=0) from Middle East considering the range contraction induced by the LGM *  The folder “Paleo_MiddleEastNeoIR0_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansions (IR=0) from Middle East suffering the range contraction induced by the LGM.  * Paleolithic expansion followed by a single Neolithic expansion (IR=0) from East Asia considering the range contraction induced by the LGM *  The folder “Paleo_EastAsiaNeoIR0_REC” contains the input files (INFILES) and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansion (IR=0) from East Asia suffering the range contraction induced by the LGM.  * Paleolithic expansion followed by a single Neolithic expansion (IR=0) from Middle East considering LDD events *  The folder “Paleo_MiddleEastNeoIR0_REC” contains the input files  (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansions (IR=0) from Middle East considering LDD events.  * Paleolithic expansion followed by a single Neolithic expansion (IR=0) from East Asia considering LDD events *  The folder “Paleo_EastAsiaNeoIR0_REC” contains the input files (INFILES) the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansion (IR=0) from East Asia considering LDD events.  * Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from Middle East considering the range contraction induced by the LGM *  The folder “Paleo_MiddleEastNeoIR004_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from East Asia suffering the range contraction induced by the LGM.  * Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from East Asia considering the range contraction induced by the LGM *  The folder “Paleo_EastAsiaNeoIR0_REC” contains the input files (INFILES), the genetic data  and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansions (IR=0.04) from East Asia suffering the range contraction induced by the LGM.  * Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from Middle East considering LDD events *  The folder “Paleo_MiddleEastNeoIR004_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from East Asia considering LDD events.  * Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from East Asia considering LDD events *  The folder “Paleo_EastAsiaNeoIR0_REC” contains the input files  (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansions (IR=0.04) from East Asia considering LDD events.

openother-openMay 2021View details →

renardbebe/Smart-Contract-Benchmark-Suites: Smart-Contract-Benchmark-Suites v0.4.0

A unified smart contract standard data set. Contains: dataset and used tools in paper "Empirical Evaluation of Smart Contract Testing: What Is the Best Choice? "

opencc-by-4.0Mar 2024View details →

Dataset for Gas-centered Mutation Testing of Ethereum Smart Contracts

This dataset contains additional material for the paper entitled "Gas-centered Mutation Testing of Ethereum Smart Contracts", published by Journal of Software: Evolution and Process. This material includes: <ul> <li>Mutation tool, with the implementation of our gas-centered mutation operators.</li> <li>Mutation operators - Example, with the code excerpts used to illustrate the gas perturbation caused by the mutation operators.</li> <li>Smart contract - Accelerator_0b58e2.dir, with the mutants generated in a smart contract and their execution results.</li> <li>Smart contracts_features.xlsx, with the complete list of smart contracts and their characteristics.</li> </ul>

Fig. 7 in Immunocytochemical Analysis of α-Tubulin Distribution Before and After Rapid Axopodial Contraction in the Centrohelid Raphidocystis contractilis

Fig. 7. (A, B) The distribution of α-tubulin in the cell after rapid axopodial contraction. (A) Low-magnification images of the cell after the induction of rapid axopodial contraction. A projection image of the whole cell constructed from 87 optical sections taken at a 0.5 µm interval (left) and the corresponding light micrograph (right). (B) High-magnification images of the same cell shown in (A). A projection image of the equatorial plane of the cell body constructed from 5 optical sections taken at a 0.5 µm interval (left), and the corresponding light micrograph (right). Note that the positive signals in the distal parts of the axopodia have a branched appearance (arrowheads). Scale bars: 20 μm (A), 10 μm (B).

Fig. 4 in Immunocytochemical Analysis of α-Tubulin Distribution Before and After Rapid Axopodial Contraction in the Centrohelid Raphidocystis contractilis

Fig. 4. (A–D) Evaluation of the maintenance of the original lengths of axopodia in R. contractilis using different combinations of fixative and buffer. Cells were fixed with (A) 4% paraformaldehyde in phosphate buffer, (B) 4% paraformaldehyde in PHEM, (C) 0.2% glutaraldehyde in phosphate buffer, or (D) 0.2% glutaraldehyde in PHEM. Note that only fixation with 0.2% glutaraldehyde in PHEM maintained the axopodial length. Scale bar: 20 µm.

Fig. 1 in Immunocytochemical Analysis of α-Tubulin Distribution Before and After Rapid Axopodial Contraction in the Centrohelid Raphidocystis contractilis

Fig. 1. (A, B) Rapid axopodial contraction induced by mechanical stimulation in R. contractilis. Images (A) before and (B) after rapid axopodial contraction. Arrowheads indicate kinetocysts. Note the synchronized retraction of all axopodia and the apparent increases in the widths of contracted axopodia relative to the features observed before the onset of axopodial contraction (an arrow). Scale bar: 20 µm (A, B).

Fig. 6 in Immunocytochemical Analysis of α-Tubulin Distribution Before and After Rapid Axopodial Contraction in the Centrohelid Raphidocystis contractilis

Fig. 6. Confocal analysis of α-tubulin-immunolabeled extended axopodia. Fine reconstructed projection image from 161 optical sections taken at a 0.05 µm (top) and the corresponding light micrograph (bottom). Note the regions of relatively low fluorescence (arrowheads) did not correspond to the location of kinetocysts (arrows). Scale bar: 10 μm.

Fig. 5 in Immunocytochemical Analysis of α-Tubulin Distribution Before and After Rapid Axopodial Contraction in the Centrohelid Raphidocystis contractilis

Fig. 5. (A, B) The distribution of α-tubulin in the cell before rapid axopodial contraction. (A) Low-magnification images of a cell without the induction of rapid axopodial contraction. A projection image of the whole cell was constructed from 192 optical sections obtained at 0.5 µm intervals (left); the corresponding light micrograph is also shown (right). (B) High-magnification images of the same cell shown in (A). A projection image of the equatorial plane of the cell body constructed from 5 optical sections taken at 0.5 µm intervals, and the corresponding light micrograph. The asterisk indicates a centroplast. Note that positive signals were detected along the fully extended axopodia. Scale bars: 20 μm (A), 10 μm (B).

Fig. 3 in Immunocytochemical Analysis of α-Tubulin Distribution Before and After Rapid Axopodial Contraction in the Centrohelid Raphidocystis contractilis

Fig. 3. Schematic illustration of the experimental setup. The fixative is injected into the cell suspension via a micro flow-through chamber with a syringe pump. Next, the cells are fixed by injecting the fixative at a rate below the threshold required for inducing rapid contraction. The cells are then observed under a microscope.

Fig. 2 in Immunocytochemical Analysis of α-Tubulin Distribution Before and After Rapid Axopodial Contraction in the Centrohelid Raphidocystis contractilis

Fig. 2. (A, B) Fine structures associated with axopodial microtubules. (A) Centroplast in the center of the cell. (B) Cross-section of an axopodium in the peripheral region of the cell. Note that bundles of microtubules radiate from the centroplast (arrowheads) and that the axopodium comprises six microtubules. Scale bars: 500 nm (A), 100 nm (B).

opencc-by-4.0Nov 2024View details →

Surface EMG recordings of the biceps brachii muscle during voluntary isometric contractions - pilot study on fatigue

This publication contains the data recorded during a study on muscle fatigue and its evaluation using surface electromyography (EMG). There were a total of 16 participants. Each directory, with an alphanumeric value contains data from a single participant (.mat and .json files). The README.pdf file  in the root directory provides details on the experimental set-up and protocol, and data in each file.  The EMG data are provided in matlab files and in addition to those, there are recordings of the <a href="https://doi.org/10.1016/j.jelekin.2019.05.012">perceived fatigue of the participants using a modified Borg CR-10 scale</a> in the json file, in which further participant and experimental information are provided. For each participant information on gender, age (in aggregate form) and height (in aggregate form) are provided.