cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3565631
title: Haloferax volcanii theoretical proteome exported from HaloLex

description: The theoretical proteome is derived from the annotated Haloferax volcanii DS2 genome (Hartmann et al, 2010). This proteome represents a Gold Standard Protein based annotation (Pfeiffer and Oesterhelt, 2015). This proteome was exported from HaloLex (Pfeiffer et al, 2008) Various proteome studies are based on versions of this theoretical proteome. Different versions, which are cited in proteome papers, are made available in this series of Zenodo uploads.
description: {"references": ["Hartmann et al, 2010, The complete genome sequence of Haloferax volcanii DS2, a model archaeon, PLoS One (2010) 5: e9605 (doi: 10.1371/journal.pone.0009605).", "Pfeiffer and Oesterhelt, 2015, A manual curation strategy to improve genome annotation: application to a set of haloarchael genomes, Life (Basel) (2015) 5:1427-1444 (doi: 10.3390/life5021427)", "Pfeiffer et al, 2008, Genome information management and integrated data analysis with HaloLex, Arch Microbiol (2008) 190: 281-299 (doi: 10.1007/s00203-008-0389-z)."]}
DOI: 10.15129/575a9712-d9db-4635-8e85-550460d5f879
title: Data for: "Control of laser light by a plasma immersed in a tunable strong magnetic field"

description: The data are about the input files used for numerical simulation with the code Osiris 2.0 (https://picksc.idre.ucla.edu/software/software-production-codes/osiris/) to produce figures 1-4 in the paper, which is to be published in the Optics Express. The input files are in the plain text format, which can be opened with various text editors
DOI: 10.5281/zenodo.3565492
title: WHISPER SET 1: a dataset for multi-channel, multi-device speech separation and speech enhancement

description: This dataset is <code>WHISPER SET 1,</code> a dataset for speech enhancement and source separation recorded with a Wireless Acoustic Sensor Network (WASN) called WHISPER Kiselev2018. The dataset contains samples for up to 4 concurrent speakers and speech in noise. The dataset was recorded in a room with low reverberation (T_60 = 0.2 s) and using 16 microphones. In general, each track contains first a calibration phase where each of the speakers sequentially is active alone for 15 seconds. Followed by 15 seconds of all the speakers together (plus noise in some cases). === Each sample is a 16-channel wav file in which the order of the channel follows the following logic: 0 - module 5 mic 1 1 - module 5 mic 2 2 - module 5 mic 3 3 - module 5 mic 4 4 - module 6 mic 1 5 - module 6 mic 2 6 - module 6 mic 3 7 - module 6 mic 4 8 - module 7 mic 1 9 - module 7 mic 2 10 - module 7 mic 3 11 - module 7 mic 4 12 - module 8 mic 1 13 - module 8 mic 2 14 - module 8 mic 3 15 - module 8 mic 4 Refer to the floor plan for a visual illustration of the microphone arrangement. The files are divided into two subfolders, one for the samples of speech enhancement and one for the samples of speech separation. In the folder of speech separation, the files are divided into subfolders defining the number of speakers in the mixtures (2, 3, or 4) In the folder of speech enhancement, the files are divided into subfolders following the SNR of the mixture (0, -5, -10 dB) Samples are ordered in folders. Each sample folder contains a 15 seconds 16-channels <code>mixture.wav</code> file, plus the 15 seconds 16-channels <code>calibX.wav</code> files one for each speaker alone or noise alone in the mixture. That is a sample with a mixture with 4 speakers will have 4 calibration files (calib1.wav, calib2.wav, calib3.wav, calib4.wav) and a mixture of a speaker plus noise will have 2 calibration files one for speech (calib1.wav) and one for noise (calib2.wav). == A Jupyter notebook is included to show an example of how to use the data of this dataset for speech separation and speech enhancement using beamforming. The notebook is dependent on this beamforming library and this tool to evaluate the quality of the separation. == Refer to the README.md in the dataset for more information. For any question please contact enea.ceolini@gmail.com
DOI: 10.15468/d9rzsh
title: Fungi of Rostovsky Biosphere Reserve

description: Data on 120 species and intraspecific taxa of macromycetes of the Rostov state nature reserve and adjacent territories are presented in the form of an annotated list. In the trophic structure of humus leading saprotrophs, a large proportion of coprotrophs. The presence of xylotrophs and parasites of woody plants in the studied mycobiota is due to both the presence of artificial plantations and natural tree and shrub vegetation. Of the macromycete species identified in the reserve, 10 are listed In the red book of the Rostov region, including 2 species (Amanita vittadinii and Leucopaxillus lepistoides) - in the Red book of the Russian Federation. A number of species have been identified (Polyporus rhizophilus, Gastrosporium simplex, Geastrum campestre, etc.) included in several Red Data Books of the steppe regions of Russia. A large number of rare and indicative species of fungi found in the “Rostov” state nature reserve characterizes this territory as an important site for the conservation of the steppe mycobiota of Eurasia. В виде аннотированного списка приведены накопленные на сегодняшний день данные о 120 видах и внутривидовых таксонах макромицетов Государственного природного заповедника «Ростовский» и прилегающих территорий. В трофической структуре лидируют гумусовые сапротрофы, велика доля копротрофов. Присутствие в изучаемой микобиоте ксилотрофов и паразитов древесных растений обусловлено как наличием искусственных насаждений, так и естественной древесно-кустарниковой растительности. Среди выявленных в заповеднике видов макромицетов 10 внесены в Красную книгу Ростовской области, в том числе 2 вида (Amanita vittadinii и Leucopaxillus lepistoides) – в Красную книгу Российской Федерации. Определен ряд видов (Polyporus rhizophilus, Gastrosporium simplex, Geastrum campestre и др.), включенных в Красные книги степных регионов европейской части страны. Большое число редких и индикаторных видов грибов, обнаруженных в Ростовском заповеднике, подтверждает высокий статус этой территории как важнейшего участка в сохранении степной микобиоты Евразии.
DOI: 10.14457/stou.the.2018.1
title: ปัจจัยที่มีความสัมพันธ์กับการมียาเหลือใช้ของผู้ป่วยนอกโรคเบาหวาน โรงพยาบาลสมเด็จพระยุพราชเดชอุดม
DOI: 10.5281/zenodo.3565793
title: weecology/portalPredictions 2019-12-06

description: Using various models to forecast abundances at Portal
DOI: 10.5281/zenodo.3565794
title: weecology/forecasts 2019-12-06

description: Archived forecasts for future analysis
DOI: 10.14457/stou.the.2017.26
title: การแสวงหาสารสนเทศเพื่อการทำโครงงานของนักศึกษาระดับปริญญาตรี มหาวิทยาลัยสงขลานครินทร์ วิทยาเขตสุราษฎร์ธานี
DOI: 10.14457/stou.the.2017.27
title: การจัดกิจกรรมห้องสมุดโรงเรียนต้นแบบโครงการส่งเสริมนิสัยรักการอ่าน ระดับประถมศึกษา สังกัดสำนักงานเขตพื้นที่การศึกษาประถมศึกษากำแพงเพชร เขต 1
DOI: 10.14457/stou.the.2017.28
title: กระบวนการสร้างสันติวัฒนธรรมในครอบครัวไทยผ่านการเล่านิทานชาดก: กรณีศึกษา ชุมชนตำบลต้นเปา อำเภอสันกำแพง จังหวัดเชียงใหม่
DOI: 10.14457/stou.the.2017.29
title: การดำเนินงานตามมาตรฐานการดูแลนักเรียนประจำที่ส่งผลต่อความพึงพอใจของบุคลากรในโรงเรียนศึกษาสงเคราะห์ภาคตะวันออกเฉียงเหนือ
DOI: 10.14457/stou.the.2017.30
title: ปัจจัยคัดสรรด้านการบริหารที่ส่งผลต่อการจัดการศึกษาเพื่อการมีงานทำของนักเรียนในโรงเรียนเฉพาะความพิการสำหรับนักเรียนที่มีความบกพร่อง ทางสติปัญญา สังกัดสำนักบริหารงานการศึกษาพิเศษ
DOI: 10.14457/stou.the.2018.2
title: การใช้สารสนเทศเพื่อการศึกษาต่อในระดับอุดมศึกษาของนักเรียนชั้นมัธยมศึกษาปีที่ 6 ในโรงเรียนเขตภาคเหนือตอนล่าง
DOI: 10.14457/stou.the.2018.3
title: ผลการใช้หนังสืออิเล็กทรอนิกส์ เรื่อง ภูมิปัญญาท้องถิ่นจังหวัดสมุทรสาครที่มีต่อความสามารถในการอ่านอย่างมีวิจารณญาณและเจตคติต่อท้องถิ่นของนักเรียนชั้นมัธยมศึกษาปีที่ 6 โรงเรียนกระทุ่มแบน "วิเศษสมุทคุณ" จังหวัดสมุทรสาคร
DOI: 10.14457/stou.the.2018.4
title: ปัจจัยที่มีความสัมพันธ์กับการปฏิบัติงานอาสาสมัครสาธารณสุขประจำหมู่บ้านในงานคุ้มครองผู้บริโภคด้านสาธารณสุขของอำเภอพระพรหม จังหวัดนครศรีธรรมราช
DOI: 10.21227/51gn-m114
title: Heidelberg Spiking Datasets

description: The Heidelberg Spiking Datasets comprise two spike-based classification datasets: The Spiking Heidelberg Digits (SHD) dataset and the Spiking Speech Command (SSC) dataset. The latter is derived from Pete Warden's Speech Commands dataset (https://arxiv.org/abs/1804.03209), whereas the former is based on a spoken digit dataset recorded in-house and included in this repository. Both datasets were generated by applying a detailed inner ear model to audio recordings. We distribute the input spikes and target labels in HDF5 format. SHD as well as SSC are released under the Creative Commons Attribution 4.0 International License.
DOI: 10.21227/n8zv-cc72
title: Heidelberg Spiking Datasets

description: The Heidelberg Spiking Datasets comprise two spike-based classification datasets: The Spiking Heidelberg Digits (SHD) dataset and the Spiking Speech Command (SSC) dataset. The latter is derived from Pete Warden's Speech Commands dataset (https://arxiv.org/abs/1804.03209), whereas the former is based on a spoken digit dataset recorded in-house and included in this repository. Both datasets were generated by applying a detailed inner ear model to audio recordings. We distribute the input spikes and target labels in HDF5 format. SHD as well as SSC are released under the Creative Commons Attribution 4.0 International License.
DOI: 10.5519/qd.80lhkcel
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5519/qd.dgvcjoau
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (71 records)
DOI: 10.17632/wxzkschct9.1
title: Phylogenetic analysis of Spodoptera frugiperda based on the DNA sequencing of mtCOI gene of the isolates from Sri Lanka (MN732549 – MN732556)
DOI: 10.21943/auas.10265054
title: Active ingredients and mechanisms of change in motivational interviewing for smoking cessation in patients with coronary artery disease. A mixed methods study

description: Excel of 109 coded transcripts of Motivational Interviewing Sessions.<br>Coding instrument:Motivational Interviewing Sequential Code for Process Exchanges (MI-SCOPE)* Therapist behavior codes* Client behavior codes<br>Study population:* Twenty-four patients (RESPONSE-2 trial, see reference)* Four therapists<br>Data and coding:109 audio-recorded MI-sessions. Coded data are stored in 24 excel-files. Each file consists of 3 to 7 sessions. Extended data description: see under data files Data description FigShare-Art5
DOI: 10.3886/e116078
title: Replication data for: Can Rational Expectations Sticky-Price Models Explain Inflation Dynamics?

description: The canonical inflation specification in sticky-price rational expectations models (the new-Keynesian Phillips curve) is often criticized for failing to account for the dependence of inflation on its own lags. In response, many studies employ a "hybrid" specification in which inflation depends on its lagged and expected future values, together with a driving variable such as the output gap. We consider some simple tests of the hybrid model that are derived from its closed form. We find that the hybrid model describes inflation dynamics poorly, and find little empirical evidence for the type of rational, forward-looking behavior that the model implies.
DOI: 10.5281/zenodo.3565801
title: IO Islamic 262. Ta'rîkh-i-Alfî, General History

description: IO Islamic 262. Ta'rîkh-i-Alfî, General History
DOI: 10.5281/zenodo.3565802
title: IO Islamic 262. Ta'rîkh-i-Alfî, General History

description: IO Islamic 262. Ta'rîkh-i-Alfî, General History
DOI: 10.14457/stou.the.2016.166
title: การพัฒนาโปรแกรมการส่งเสริมพัฒนาการของทารกแรกเกิดถึง 6 เดือน ของมารดาวัยรุ่น
DOI: 10.17632/8hp5t2fjzg.1
title: The CD24+ Cell Subset Promotes Invasion and Metastasis in Human Osteosarcoma

description: NanoAcquity UPLC(Waters Corp., MA,USA) combined with LTQ Orbitrap XL(Thermo Fisher Scientific Inc., MA, USA) was used to study CD24+ and CD24– subsets of cells isolated from the MNNG/HOS cells using a flow cytometry cell sorter. Collected data were searched in the BioWorksBrowser (version Rev. 3.3.1 SP1, Thermo Fisher Scientific Inc.) with the SEQUEST search engines and analyzed using an APEX Quantitative Proteomics Tool (Version1.0.0, Pathogen Functional Genomics Resource Center；J. Craig Venter Institute)and other bioinformatics software. Through the Database for Annotation, Visualization, and Integrated Discovery (DAVID) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database platforms, differentially expressed proteins of the CD24+ and CD24- cell subsets were analyzed for KEGG pathways.
DOI: 10.21227/5tcd-0j88
title: Heidelberg Spiking Datasets

description: The Heidelberg Spiking Datasets comprise two spike-based classification datasets: The Spiking Heidelberg Digits (SHD) dataset and the Spiking Speech Command (SSC) dataset. The latter is derived from Pete Warden's Speech Commands dataset (https://arxiv.org/abs/1804.03209), whereas the former is based on a spoken digit dataset recorded in-house and included in this repository. Both datasets were generated by applying a detailed inner ear model to audio recordings. We distribute the input spikes and target labels in HDF5 format. SHD as well as SSC are released under the Creative Commons Attribution 4.0 International License.
DOI: 10.17632/yxs45cg6rb.1
title: Taxogenomics

description: Referencias
DOI: 10.5281/zenodo.3565803
title: IO Islamic 3291. Ta'rîkh-i-Alfî, General History

description: IO Islamic 3291. Ta'rîkh-i-Alfî, General History
DOI: 10.5281/zenodo.3565804
title: IO Islamic 3291. Ta'rîkh-i-Alfî, General History

description: IO Islamic 3291. Ta'rîkh-i-Alfî, General History
DOI: 10.7910/dvn/ftecd4/l9llwm
title: Harbin_2018-08-09_12-16-09_6175000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/pefjhg
title: Harbin_2018-08-09_12-16-09_9520000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/wvmd7u
title: Harbin_2018-08-10_11-40-01_6175000.dat

description: :unav
DOI: 10.17632/gjpgg96zxx.1
title: The CD24+ Cell Subset Promotes Invasion and Metastasis in Human Osteosarcoma

description: NanoAcquity UPLC(Waters Corp., MA,USA) combined with LTQ Orbitrap XL(Thermo Fisher Scientific Inc., MA, USA) was used to study CD24+ and CD24– subsets of cells isolated from the MNNG/HOS cells using a flow cytometry cell sorter. Collected data were searched in the BioWorksBrowser (version Rev. 3.3.1 SP1, Thermo Fisher Scientific Inc.) with the SEQUEST search engines and analyzed using an APEX Quantitative Proteomics Tool (Version1.0.0, Pathogen Functional Genomics Resource Center；J. Craig Venter Institute)and other bioinformatics software. Through the Database for Annotation, Visualization, and Integrated Discovery (DAVID) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database platforms, differentially expressed proteins of the CD24+ and CD24- cell subsets were analyzed for KEGG pathways.
DOI: 10.7910/dvn/ftecd4/2f9si6
title: Harbin_2018-08-12_10-21-45_6600000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/aldwku
title: Harbin_2018-08-12_10-21-45_9520000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/cf2dee
title: Harbin_2018-08-09_12-16-09_6600000.dat

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DOI: 10.7910/dvn/ftecd4/ioifzq
title: Harbin_2018-08-11_11-09-57_6600000.dat

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DOI: 10.7910/dvn/ftecd4/ip7ola
title: Harbin_2018-08-10_11-40-01_9750000.dat

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DOI: 10.7910/dvn/ftecd4/jbnhw3
title: Harbin_2018-08-11_11-09-57_9520000.dat

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DOI: 10.7910/dvn/ftecd4/jn9lit
title: Harbin_2018-08-10_11-40-01_9520000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/u0all4
title: Harbin_2018-08-10_11-40-01_6600000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/ynstlf
title: Harbin_2018-08-09_12-16-09_6080000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/2hpv6m
title: Harbin_2018-08-10_11-40-01_6080000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/3q8ryy
title: Harbin_2018-08-09_12-16-09_6055000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/6nmpat
title: Harbin_2018-08-12_10-21-45_9750000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/8e19aa
title: Harbin_2018-08-11_11-09-57_6055000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/a7pwnm
title: Harbin_2018-08-11_11-09-57_6014998.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/imxpv7
title: Harbin_2018-08-09_12-16-09_9750000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/ma57ov
title: Harbin_2018-08-11_11-09-57_6175000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/ms7kiu
title: Harbin_2018-08-10_11-40-01_6055000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/yn6lwm
title: Harbin_2018-08-12_10-21-45_6014998.dat

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DOI: 10.5281/zenodo.3565429
title: Post and comments in the r/NEET subreddit

description: submissions.csv: it contains the id of all the Reddit submissions crawled for this study. In order to comply to Reddit Privacy policy, we release only the ids of the submissions together with the metadata created by us (e.g., the assigned topic extracted with LDA). In order to retrieve the full submission, you need to use the Reddit API as described in https://www.reddit.com/dev/api/. If the submission is a post you need to prepend the string "t3_", while if it is a comment you need to prepend "t1_". For instance, if you want to retrieve a post with id "dm6zumf"m you need to call the endpoint in this way: https://www.reddit.com/api/info.json?id=t1_dm6zumf mentions.csv: it contains the mention of attributes extracted by our pattern matching approach. In particular, the field are the following:<br> - labels: it identifies the type of mentions. It can be "AGE","HEALTH", "CONTEXT". "EDUCATION_DROPPED", "EDUCATION", "GENDER".<br> - instance: it identifies the object mentioned (in case of HEALTH label it refers to the health issue).<br> - submission_id: it is the id of the submission the mention it refers to.<br>
DOI: 10.5281/zenodo.3565430
title: Post and comments in the r/NEET subreddit

description: submissions.csv: it contains the id of all the Reddit submissions crawled for this study. In order to comply to Reddit Privacy policy, we release only the ids of the submissions together with the metadata created by us (e.g., the assigned topic extracted with LDA). In order to retrieve the full submission, you need to use the Reddit API as described in https://www.reddit.com/dev/api/. If the submission is a post you need to prepend the string "t3_", while if it is a comment you need to prepend "t1_". For instance, if you want to retrieve a post with id "dm6zumf"m you need to call the endpoint in this way: https://www.reddit.com/api/info.json?id=t1_dm6zumf mentions.csv: it contains the mention of attributes extracted by our pattern matching approach. In particular, the field are the following:<br> - labels: it identifies the type of mentions. It can be "AGE","HEALTH", "CONTEXT". "EDUCATION_DROPPED", "EDUCATION", "GENDER".<br> - instance: it identifies the object mentioned (in case of HEALTH label it refers to the health issue).<br> - submission_id: it is the id of the submission the mention it refers to.<br>
DOI: 10.7910/dvn/ftecd4/1corqz
title: Harbin_2018-08-12_10-21-45_6080000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/6iy8g1
title: Harbin_2018-08-12_10-21-45_6175000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/9jtrhr
title: Harbin_2018-08-10_11-40-01_6014998.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/bdlmqx
title: Harbin_2018-08-11_11-09-57_9750000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/tdnwmn
title: Harbin_2018-08-12_10-21-45_6055000.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/yp2jfi
title: Harbin_2018-08-09_12-16-09_6014998.dat

description: :unav
DOI: 10.7910/dvn/ftecd4/zf3ioi
title: Harbin_2018-08-11_11-09-57_6080000.dat

description: :unav
DOI: 10.21227/gz8g-9d65
title: Heidelberg Spiking Datasets

description: The Heidelberg Spiking Datasets comprise two spike-based classification datasets: The Spiking Heidelberg Digits (SHD) dataset and the Spiking Speech Command (SSC) dataset. The latter is derived from Pete Warden's Speech Commands dataset (https://arxiv.org/abs/1804.03209), whereas the former is based on a spoken digit dataset recorded in-house and included in this repository. Both datasets were generated by applying a detailed inner ear model to audio recordings. We distribute the input spikes and target labels in HDF5 format. SHD as well as SSC are released under the Creative Commons Attribution 4.0 International License.
DOI: 10.21227/brfq-ke91
title: Heidelberg Spiking Datasets

description: The Heidelberg Spiking Datasets comprise two spike-based classification datasets: The Spiking Heidelberg Digits (SHD) dataset and the Spiking Speech Command (SSC) dataset. The latter is derived from Pete Warden's Speech Commands dataset (https://arxiv.org/abs/1804.03209), whereas the former is based on a spoken digit dataset recorded in-house and included in this repository. Both datasets were generated by applying a detailed inner ear model to audio recordings. We distribute the input spikes and target labels in HDF5 format. SHD as well as SSC are released under the Creative Commons Attribution 4.0 International License.
DOI: 10.3886/e116079
title: Replication data for: An Alternative Test of Racial Prejudice in Motor Vehicle Searches: Theory and Evidence

description: We propose a simple model of trooper behavior to design empirical tests for whether troopers of different races are monolithic in their search behavior, and whether they exhibit relative racial prejudice in motor vehicle searches. Our test of relative racial prejudice provides a partial solution to the well-known infra-marginality and omitted-variables problems associated with outcome tests. When applied to a unique dataset from Florida, our tests soundly reject the hypothesis that troopers of different races are monolithic in their search behavior, but the tests fail to reject the hypothesis that troopers of different races do not exhibit relative racial prejudice.
DOI: 10.7910/dvn/3vqxxm/0reuaz
title: Walder&Strijbis_PartycuesDirectDemocracy_Registration_Experiment.pdf

description: :unav
DOI: 10.17632/wsdgt4cf8y.1
title: VismoHisto