cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24038925.v1
title: <b>S</b><b>性</b><b> </b><b> </b><b>益生菌</b><b> 特性评估 </b><i><b>样芽孢</b></i><b>粪便中</b><b>Kele</b><b>猪</b>

description: 文章中结果的原始数据，包括 16s rRNA 序列、菌株全基因序列、基因组 COG 注释、基因组 KEGG 注释、毒力基因注释、抗性基因注释和 GC-MS 测定原始结果。
DOI: 10.5281/zenodo.8301603
title: Universal Qudit Gate Synthesis for Transmons. Open data set

description: Data supporting the original figures 2, 5, 7, 8, 9, 10, 11 and 12 of the related publication.
DOI: 10.5281/zenodo.8301604
title: Universal Qudit Gate Synthesis for Transmons. Open data set

description: Data supporting the original figures 2, 5, 7, 8, 9, 10, 11 and 12 of the related publication.
DOI: 10.6084/m9.figshare.23613804
title: Artificial General Intelligence (AGI)

description: <b>Description</b>The experimental <i>AI Dialog</i> software application is able to build a mental model from a plain English dialogue using speech or textual input. Subsequently, comprehension and logical capability may be tested using plain English queries.<i>AI Dialog</i> is used to experimentally test the validity and utility of a novel software application design, as a path to <i>Artificial General Intelligence</i>, sometimes referred to as <i>Strong Artificial Intelligence</i> or <i>Conversational Artificial Intelligence</i>.The theory behind <i>AI Dialog</i> is fully described in the book: <i>Belch, Francis R. (2023) Artificial General Intelligence – A New Approach</i>, available from: Amazon.com (from September 2023).A short demonstration of the <i>AI Dialog</i> software application is available from <i>YouTube</i>®<i>,</i> and entitled:<i>Artificial General Intelligence – A New Approach – AI Dialog Demonstration.</i>There are also two <i>YouTube</i>® lectures each of about 1 hour duration describing the radical new approach to <i>Artificial General Intelligence</i> used to implement the <i>AI Dialog</i> software application. These are:<i>Artificial General Intelligence – A New Approach – Part I Sentence Semantics</i>.<i>Artificial General Intelligence – A New Approach – Part II Dialogues and Mental Models</i>.This is a free download of the executable of the <i>AI Dialog Software Application Version 4.1 Alpha</i> release. This version supersedes <i>Version 3.2</i> to allow speech as well as textual user input.The <i>AI Dialog</i> software is protected by international copyright, but is made available to use for non-commercial personal study purposes.The application will run on Windows 10® PC, Laptop and Tablet systems, and requires about 1 M byte of memory. The download file is zipped and needs to be unzipped. After this, the content of the folder <i>AI Dialog 4.1 Alpha Release</i> is:• Application Files (Folder)• Documentation (Folder)• NLP2016Autumn (Manifest)• Setup (Application)In the Documentation folder are two PDF files:• Copy Of Tuition Lessons (PDF)• Specification (PDF).The first is a hard copy of the tuition lessons. The second is a specification of a subset of English for use with the <i>AI Dialog</i> system. However, there is no need to consult either of these initially, as <i>AI Dialog</i> incorporates a quick start tuition module.To install <i>AI Dialog</i>, double click the Setup file. This starts <i>AI Dialog</i> immediately after installation, but places an application icon on the Windows 10® Start list for restarting later. After <i>AI Dialog</i> starts, just follow the speech or pop-up message instructions, which lead to quick start interactive tuition modules, fully describing how to use the application.
DOI: 10.5281/zenodo.8158768
title: Polígonos sitios arqueológicos Valle de Camarones, cursos bajo y medio

description: Polígono de los sitios descritos en el catastro de los cursos bajo y medio del valle de Camarones.
DOI: 10.6084/m9.figshare.24058476
title: ENGLISH LANGUAGE SYLLABUS IN ODD SEMESTER 2023/2024: A REVISION(TEACHING THEOLOGY DEPARTMENT)

description: Teaching English for General Purposes (EGP) in theology teaches students to utilize English for academic discourse, research, and communication. Here is a quick summary of this approach:<br>Language Proficiency: Theology EGP improves students' reading, writing, speaking, and listening abilities in English. This skill is necessary for reading and interpreting religious materials, engaging in conversations, and doing international academic research.Academic Vocabulary: Theology has its language and notions. EGP courses emphasize theology-related academic terminology to help students understand and explain theological concepts.Critical thinking and analysis: Teaching EGP in theology promotes these abilities. Students learn to assess religious arguments, interact with other viewpoints, and write well-reasoned English arguments.Writing and Research Skills: Theology EGP courses emphasize academic writing. Teaching students how to compose theological essays and research papers, reference sources, and undertake independent English research. Theology students need good oral communication for seminars, research presentations, and debates. EGP helps students express themselves effectively and convincingly in English. Theology studies are varied and multicultural. Thus, EGP courses generally involve cultural sensitivity and intercultural dialogue. Students are prepared to communicate with classmates and lecturers from other cultures appropriately. EGP courses may expose students to significant English theological literature and help them comprehend its context and historical importance, enhancing their linguistic and religious understanding. EGP in theology frequently takes an interdisciplinary approach, enabling students to apply their language abilities to ethics, history, comparative religion, and more.Digital Skills: EGP courses teach students to use internet research, theological databases, and virtual academic conferences and conversations in the digital eraSYLLABUS DESIGN AUTHORITY: Thobias Sarbunan, M.Pd<br>
DOI: 10.6084/m9.figshare.24058476.v1
title: ENGLISH LANGUAGE SYLLABUS IN ODD SEMESTER 2023/2024: A REVISION(TEACHING THEOLOGY DEPARTMENT)

description: Teaching English for General Purposes (EGP) in theology teaches students to utilize English for academic discourse, research, and communication. Here is a quick summary of this approach:<br>Language Proficiency: Theology EGP improves students' reading, writing, speaking, and listening abilities in English. This skill is necessary for reading and interpreting religious materials, engaging in conversations, and doing international academic research.Academic Vocabulary: Theology has its language and notions. EGP courses emphasize theology-related academic terminology to help students understand and explain theological concepts.Critical thinking and analysis: Teaching EGP in theology promotes these abilities. Students learn to assess religious arguments, interact with other viewpoints, and write well-reasoned English arguments.Writing and Research Skills: Theology EGP courses emphasize academic writing. Teaching students how to compose theological essays and research papers, reference sources, and undertake independent English research. Theology students need good oral communication for seminars, research presentations, and debates. EGP helps students express themselves effectively and convincingly in English. Theology studies are varied and multicultural. Thus, EGP courses generally involve cultural sensitivity and intercultural dialogue. Students are prepared to communicate with classmates and lecturers from other cultures appropriately. EGP courses may expose students to significant English theological literature and help them comprehend its context and historical importance, enhancing their linguistic and religious understanding. EGP in theology frequently takes an interdisciplinary approach, enabling students to apply their language abilities to ethics, history, comparative religion, and more.Digital Skills: EGP courses teach students to use internet research, theological databases, and virtual academic conferences and conversations in the digital eraSYLLABUS DESIGN AUTHORITY: Thobias Sarbunan, M.Pd<br>
DOI: 10.6084/m9.figshare.24058428
title: Immobilization system error

description: This is a table of fixation errors for various retention methods in radiotherapy for dogs.
DOI: 10.6084/m9.figshare.24058428.v1
title: Immobilization system error

description: This is a table of fixation errors for various retention methods in radiotherapy for dogs.
DOI: 10.5255/ukda-sn-856646
title: Municipal Borough and Urban Sanitary Authority Financial Accounts, 1872-1910

description: The data contain town financial accounts reported in the "Local Taxation Returns" report to Parliament, for the years 1872-1910. The accounts disaggregate sources of revenue, types of spending, and loans outstanding annually. The dataset covers more than 1,000 towns that were categorized as "urban sanitary authorities", identifying spending on important sanitation public goods such as sewers and water supply. In addition, it includes separate accounts for the councils of County Boroughs and Municipal Boroughs, including spending on other urban infrastructure, and revenues from municipal trading accounts from tramways, gas, and electricity supply.
DOI: 10.6084/m9.figshare.22548400.v5
title: A scATAC-seq atlas of chromatin accessibility in axolotl brain regions

description: Axolotl (<i>Ambystoma mexicanum</i>) is an excellent model for investigating regeneration, the interaction between regenerative and developmental processes, comparative genomics, and evolution. The brain, which serves as the material basis of consciousness, learning, memory, and behavior, is the most complex and advanced organ in axolotl. The modulation of transcription factors is a crucial aspect in determining the function of diverse regions within the brain. There is, however, no comprehensive understanding of the gene regulatory network of axolotl brain regions. Here, we utilized single-cell ATAC sequencing to generate the chromatin accessibility landscapes of 81,199 cells from the olfactory bulb, telencephalon, diencephalon and mesencephalon, hypothalamus and pituitary, and the rhombencephalon. Based on these data, we identified key transcription factors specific to distinct cell types and compared cell type functions across brain regions. Our results provide a foundation for comprehensive analysis of gene regulatory programs, which are valuable for future studies of axolotl brain development, regeneration, and evolution, as well as on the mechanisms underlying cell-type diversity in vertebrate brains.
DOI: 10.6084/m9.figshare.24058497
title: Thermal ramp, García et al. Database

description: Database from the manuscript "Thermal threshold and interspecific competition contribute to explain intertidal hermit crab assemblages". We estimated the avoidance threshold of the two hermit crab species to increasing water temperatures to help explain their intertidal distribution. We also compared the avoidance threshold of Cli. albidigitus to rising temperatures when presented alone and in the presence of chemical cues of its competitor to assess a potential competitive niche exclusion.
DOI: 10.6084/m9.figshare.24058497.v1
title: Thermal ramp, García et al. Database

description: Database from the manuscript "Thermal threshold and interspecific competition contribute to explain intertidal hermit crab assemblages". We estimated the avoidance threshold of the two hermit crab species to increasing water temperatures to help explain their intertidal distribution. We also compared the avoidance threshold of Cli. albidigitus to rising temperatures when presented alone and in the presence of chemical cues of its competitor to assess a potential competitive niche exclusion.
DOI: 10.6084/m9.figshare.24026337
title: README.rtf

description: DataThis is lots of data for the experiments I did...Experimental data from viscous fingering experiments
DOI: 10.6084/m9.figshare.23910249
title: <b>Coastal Tsunami Prediction in Tohoku Region, Japan, Based on S-net Observations Using Artificial Neural Network</b>

description: In this folder, we provided synthetic earthquake data for model training, including:Parameters for Computing Seafloor deformation (sourcefile.zip)Synthetic offshore bottom pressure gauge data (OBPG.zip)Synthetic tide gauge observations (tide_gauge.zip)We selected 800 scenarios for model training out of 1000 hypothetical tsunamis, and the remaining 200 scenarios for model testing. The training dataset and testing dataset are both randomly selected and shuffled.Please note that because the artificial intelligence network is trained using Python language, Python sequences start numbering from 0. Therefore, these 1,000 scenarios are named from run_000000 to run_000999, including both training and testing files. The folder named run_000009 represents the No. 10 hypothetical tsunami scenario.<br>
DOI: 10.6084/m9.figshare.23910249.v2
title: <b>Coastal Tsunami Prediction in Tohoku Region, Japan, Based on S-net Observations Using Artificial Neural Network</b>

description: In this folder, we provided synthetic earthquake data for model training, including:Parameters for Computing Seafloor deformation (sourcefile.zip)Synthetic offshore bottom pressure gauge data (OBPG.zip)Synthetic tide gauge observations (tide_gauge.zip)We selected 800 scenarios for model training out of 1000 hypothetical tsunamis, and the remaining 200 scenarios for model testing.Please note that because the artificial intelligence network is trained using Python language, Python sequences start numbering from 0. Therefore, these 1,000 scenarios are named from run_000000 to run_000999, including both training and testing files. The folder named run_000009 represents the No. 10 hypothetical tsunami scenario.<br>
DOI: 10.5519/qd.d5rqlynq
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (33 records)
DOI: 10.5281/zenodo.8285125
title: WIA-SZZ: Work Item Aware SZZ - Cloned Repository Files (4/7)

description: For replication purposes, these 7 Zenodo records contain a copy of the cloned repositories from Rosa et. al, ICSE 2021, Evaluating SZZ implementations through a developer-informed oracle, downloaded as of to Dec. 2022. These repositories were used for the evaluation and analysis of our paper WIA-SZZ: Work Item Aware SZZ. A script to download and unzip all files in these Zenodo records is provided as well. 1. https://zenodo.org/record/8285106 (doi: 10.5281/zenodo.8285106)<br> 2. https://zenodo.org/record/8285119 (doi: 10.5281/zenodo.8285119)<br> 3. https://zenodo.org/record/8285121 (doi: 10.5281/zenodo.8285121)<br> 4. https://zenodo.org/record/8285125 (doi: 10.5281/zenodo.8285125)<br> 5. https://zenodo.org/record/8285127 (doi: 10.5281/zenodo.8285127)<br> 6. https://zenodo.org/record/8285138 (doi: 10.5281/zenodo.8285138)<br> 7. https://zenodo.org/record/8285140 (doi: 10.5281/zenodo.8285140)
DOI: 10.5281/zenodo.8285124
title: WIA-SZZ: Work Item Aware SZZ - Cloned Repository Files (4/7)

description: For replication purposes, these 7 Zenodo records contain a copy of the cloned repositories from Rosa et. al, ICSE 2021, Evaluating SZZ implementations through a developer-informed oracle, downloaded as of to Dec. 2022. These repositories were used for the evaluation and analysis of our paper WIA-SZZ: Work Item Aware SZZ. A script to download and unzip all files in these Zenodo records is provided as well. 1. https://zenodo.org/record/8285106 (doi: 10.5281/zenodo.8285106)<br> 2. https://zenodo.org/record/8285119 (doi: 10.5281/zenodo.8285119)<br> 3. https://zenodo.org/record/8285121 (doi: 10.5281/zenodo.8285121)<br> 4. https://zenodo.org/record/8285125 (doi: 10.5281/zenodo.8285125)<br> 5. https://zenodo.org/record/8285127 (doi: 10.5281/zenodo.8285127)<br> 6. https://zenodo.org/record/8285138 (doi: 10.5281/zenodo.8285138)<br> 7. https://zenodo.org/record/8285140 (doi: 10.5281/zenodo.8285140)
DOI: 10.6084/m9.figshare.24057030
title: TRAP_dataset_UTF_8.csv

description: This dataset was collected based on an air pollution control program with the potential use of exploring the joint health effects of air pollution and physical activity. The dataset mainly consists of demographic information and physical activity patterns. We selected two working days and one rest day of the study population to collect activity patterns for 24 consecutive hours per day. Meanwhile, this dataset covers as many occupational groups as possible in order to reveal the behavioral activity patterns of different groups. The TRAP database displays diverse physical activity patterns among residents in northern China, especially in the “BTH (Beijing-Tianjin-Hebei) 2+26” areas.
DOI: 10.6084/m9.figshare.24057030.v1
title: TRAP_dataset_UTF_8.csv

description: This dataset was collected based on an air pollution control program with the potential use of exploring the joint health effects of air pollution and physical activity. The dataset mainly consists of demographic information and physical activity patterns. We selected two working days and one rest day of the study population to collect activity patterns for 24 consecutive hours per day. Meanwhile, this dataset covers as many occupational groups as possible in order to reveal the behavioral activity patterns of different groups. The TRAP database displays diverse physical activity patterns among residents in northern China, especially in the “BTH (Beijing-Tianjin-Hebei) 2+26” areas.
DOI: 10.5281/zenodo.8285138
title: WIA-SZZ: Work Item Aware SZZ - Cloned Repository Files (6/7)

description: For replication purposes, these 7 Zenodo records contain a copy of the cloned repositories from Rosa et. al, ICSE 2021, Evaluating SZZ implementations through a developer-informed oracle, downloaded as of to Dec. 2022. These repositories were used for the evaluation and analysis of our paper WIA-SZZ: Work Item Aware SZZ. A script to download and unzip all files in these Zenodo records is provided as well. 1. https://zenodo.org/record/8285106 (doi: 10.5281/zenodo.8285106)<br> 2. https://zenodo.org/record/8285119 (doi: 10.5281/zenodo.8285119)<br> 3. https://zenodo.org/record/8285121 (doi: 10.5281/zenodo.8285121)<br> 4. https://zenodo.org/record/8285125 (doi: 10.5281/zenodo.8285125)<br> 5. https://zenodo.org/record/8285127 (doi: 10.5281/zenodo.8285127)<br> 6. https://zenodo.org/record/8285138 (doi: 10.5281/zenodo.8285138)<br> 7. https://zenodo.org/record/8285140 (doi: 10.5281/zenodo.8285140)
DOI: 10.5281/zenodo.8285137
title: WIA-SZZ: Work Item Aware SZZ - Cloned Repository Files (6/7)

description: For replication purposes, these 7 Zenodo records contain a copy of the cloned repositories from Rosa et. al, ICSE 2021, Evaluating SZZ implementations through a developer-informed oracle, downloaded as of to Dec. 2022. These repositories were used for the evaluation and analysis of our paper WIA-SZZ: Work Item Aware SZZ. A script to download and unzip all files in these Zenodo records is provided as well. 1. https://zenodo.org/record/8285106 (doi: 10.5281/zenodo.8285106)<br> 2. https://zenodo.org/record/8285119 (doi: 10.5281/zenodo.8285119)<br> 3. https://zenodo.org/record/8285121 (doi: 10.5281/zenodo.8285121)<br> 4. https://zenodo.org/record/8285125 (doi: 10.5281/zenodo.8285125)<br> 5. https://zenodo.org/record/8285127 (doi: 10.5281/zenodo.8285127)<br> 6. https://zenodo.org/record/8285138 (doi: 10.5281/zenodo.8285138)<br> 7. https://zenodo.org/record/8285140 (doi: 10.5281/zenodo.8285140)
DOI: 10.25345/c5cj87w8w
title: MassIVE MSV000092790 - Acute to prolonged lif cycle proteomic profiling of heat shock SGs
title: Time-resolved proteomic profiling of SGs from cultured human U2OS cells over a prolonged heat-shock (HS) and a successive recovery period, sampling at the 6 time points of HS exposure (10, 20, 30, 60, 120, 180 min), as well as 2 time points of recovery (5, 10 min). From the sampled cells, we prepared SG samples using a differential centrifugation plus endogenous G3BP1 immunoprecipitation protocol. Peptides were subsequently TMT-labeled and analyzed by quantitative LC-MS/MS. In G3BP1 dataset, rep1-rep3, HS-10, 20, 30, 60, 120, 180, re5, re10, SG-ls, G3BP1-IP samples were labeled with TMT-126, 127N, 127C, 128N, 128C,129N, 129C, 130N, 130C, 131 label Reagents, respectively; G3BP1_HS0 was a dataset created to integrate a non-heat shock control (HS-0) into the G3BP1 dataset, contains HS0, HS10, and HS60, and the results was integrated into the G3BP1 dataset using the ComBat processing, HS-0_rep1, HS-0_rep2, HS-0_rep3, HS-10_rep1, HS-10_rep2, HS-10_rep3, HS-60_rep1, HS-60_rep2, HS-60_rep3 samples were labeled with TMT-126, 127N, 127C, 128N, 128C,129N, 129C, 130N, 130C label Reagents, respectively. In CAPRIN1 dataset, rep1-rep3, HS-0, 10, 20, 30, 60, 120, 180, re5, re10 samples were labeled with TMT-126, 127N, 127C, 128N, 128C,129N, 129C, 130N, 130C label Reagents, respectively.
DOI: 10.5281/zenodo.8301716
title: Brazilian Secondary School Exam (ENEM) Questions Dataset

description: <strong>Dataset description</strong> Dataset extracted from the tests available on the INEP website. - https://www.gov.br/inep/pt-br/areas-de-atuacao/avaliacao-e-exames-educacionais/enem/provas-e-gabaritos The available data were obtained from tests in PDF and scripts were used to read and process the files to extract the texts related to the questions and alternatives. The extraction was made for enem tests from the years 2010 to 2022 <strong>Description of the dataframe.</strong> Columns: - description (str): containing the text relative to the question - alternatives (list[str]): list of string containing the alternatives to the question - year (int): year of the application of the question - subject (str): the area of subject [Linguagens, códigos e suas tecnologias; Ciências humanas e suas tecnologias; Ciências da natureza e suas tecnologias; Matemática e suas tecnologias] - ground_truth (str): correct alternative of the question <strong>Code used</strong> All the code used to process the data can be found at - https://github.com/wineone/tcc-matheus-lisboa
DOI: 10.5281/zenodo.8301715
title: Brazilian Secondary School Exam (ENEM) Questions Dataset

description: <strong>Dataset description</strong> Dataset extracted from the tests available on the INEP website. - https://www.gov.br/inep/pt-br/areas-de-atuacao/avaliacao-e-exames-educacionais/enem/provas-e-gabaritos The available data were obtained from tests in PDF and scripts were used to read and process the files to extract the texts related to the questions and alternatives. The extraction was made for enem tests from the years 2010 to 2022 <strong>Description of the dataframe.</strong> Columns: - description (str): containing the text relative to the question - alternatives (list[str]): list of string containing the alternatives to the question - year (int): year of the application of the question - subject (str): the area of subject [Linguagens, códigos e suas tecnologias; Ciências humanas e suas tecnologias; Ciências da natureza e suas tecnologias; Matemática e suas tecnologias] - ground_truth (str): correct alternative of the question <strong>Code used</strong> All the code used to process the data can be found at - https://github.com/wineone/tcc-matheus-lisboa
DOI: 10.5063/f1zc81bv
title: GBS genomic data from the wall lizard, Teira dugesii, from Madeira

description: These data originate from genotyping-by-sequencing (GBS) of 94 wall lizards from 15 sites across Madeira. The data have been used to detect genomic SNPs that are correlated with environmental variables across the island.Individuals are labeled in the VCF as say "10.04", indicating individual 4 from site 10. The site locations are described in the Location data.
DOI: 10.5281/zenodo.8302087
title: Payne&Kaltenegger 2023 - Phanerozoic O2

description: Dataset for publication "Oxygen Bounty for Earth-like exoplanets: Spectra of Earth through the Phanerozoic" (Payne & Kaltenegger, 2023). Formatted txt of model cases
DOI: 10.5281/zenodo.8302086
title: Payne&Kaltenegger 2023 - Phanerozoic O2

description: Dataset for publication "Oxygen Bounty for Earth-like exoplanets: Spectra of Earth through the Phanerozoic" (Payne & Kaltenegger, 2023). Formatted txt of model cases