cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25739/cdx9-wr97
title: GOMAP Cowpea IT97K-499-35 JGI annotation v1.1

description: This dataset generated by GOMAP is a high-coverage and reproducible functional annotation set based on Gene Ontology (GO) term assignments that covers all protein coding gene models in the JGI Vigna unguiculata v1.1 annotation (variety IT97K-499-35, related publication: http://doi.org/10.1101/518969) with a median of 11 annotations per gene model. It was created in April of 2019.
DOI: 10.7910/dvn/spoksm/33q1wz
title: density_3-5.tab

description: :unav
DOI: 10.7910/dvn/spoksm/caueni
title: flow_7-5.tab

description: :unav
DOI: 10.7910/dvn/spoksm/cp89xf
title: flow_9.tab

description: :unav
DOI: 10.7910/dvn/spoksm/gdcgo0
title: vsl_9-3.tab

description: :unav
DOI: 10.7910/dvn/spoksm/hondux
title: ramp_queue_length_9.tab

description: :unav
DOI: 10.7910/dvn/spoksm/ttqjdt
title: flow_3-6.tab

description: :unav
DOI: 10.7910/dvn/spoksm/ulpzrc
title: density_1-5.tab

description: :unav
DOI: 10.7910/dvn/spoksm/visoo0
title: density_4-1.tab

description: :unav
DOI: 10.7910/dvn/spoksm/6rsiai
title: flow_4-9.tab

description: :unav
DOI: 10.7910/dvn/spoksm/6xhkqm
title: flow_2-3.tab

description: :unav
DOI: 10.7910/dvn/spoksm/hown9f
title: density_1-8.tab

description: :unav
DOI: 10.7910/dvn/spoksm/opike9
title: density_9-13.tab

description: :unav
DOI: 10.7910/dvn/spoksm/qdppdw
title: vsl_5-7.tab

description: :unav
DOI: 10.7910/dvn/spoksm/rbmruj
title: flow_0-5.tab

description: :unav
DOI: 10.7910/dvn/spoksm/te04ni
title: vsl_0-6.tab

description: :unav
DOI: 10.7910/dvn/spoksm/vftbgt
title: flow_3-8.tab

description: :unav
DOI: 10.7910/dvn/spoksm/whb2cl
title: density_3-6.tab

description: :unav
DOI: 10.7910/dvn/spoksm/1e4w2y
title: vsl_8-2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/9wxljl
title: flow_3-5.tab

description: :unav
DOI: 10.7910/dvn/spoksm/cjuzjr
title: flow_1-9.tab

description: :unav
DOI: 10.7910/dvn/spoksm/e9sgbz
title: density_7-2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/fsmtcg
title: density_8-9.tab

description: :unav
DOI: 10.7910/dvn/spoksm/l7m5ft
title: density_0-2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/ludhck
title: flow_8-10.tab

description: :unav
DOI: 10.7910/dvn/spoksm/oykfav
title: ramp_queue_length_2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/uchexj
title: flow_9-9.tab

description: :unav
DOI: 10.7910/dvn/spoksm/01fxsl
title: flow_5-1.tab

description: :unav
DOI: 10.7910/dvn/spoksm/dgyisb
title: flow_2-7.tab

description: :unav
DOI: 10.7910/dvn/spoksm/dpxkiu
title: density_8-3.tab

description: :unav
DOI: 10.7910/dvn/spoksm/naht4g
title: density_1-6.tab

description: :unav
DOI: 10.7910/dvn/spoksm/nqeg05
title: density_7-8.tab

description: :unav
DOI: 10.7910/dvn/spoksm/ojfogw
title: ramp_metering_rate_0-1.tab

description: :unav
DOI: 10.7910/dvn/spoksm/po6pvo
title: density_1-2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/qjtr5m
title: flow_7-1.tab

description: :unav
DOI: 10.7910/dvn/spoksm/z1i3de
title: density_6.tab

description: :unav
DOI: 10.7910/dvn/spoksm/3ojbgs
title: density_3-13.tab

description: :unav
DOI: 10.7910/dvn/spoksm/4evzp3
title: ramp_queue_length_1.tab

description: :unav
DOI: 10.7910/dvn/spoksm/idx5hd
title: vsl_9.tab

description: :unav
DOI: 10.7910/dvn/spoksm/murqgr
title: density_2-3.tab

description: :unav
DOI: 10.7910/dvn/spoksm/prhqza
title: density_6-10.tab

description: :unav
DOI: 10.7910/dvn/spoksm/rarvds
title: vsl_5-4.tab

description: :unav
DOI: 10.7910/dvn/spoksm/rsimkv
title: density_4-4.tab

description: :unav
DOI: 10.7910/dvn/spoksm/tfxisg
title: vsl_4-5.tab

description: :unav
DOI: 10.7910/dvn/spoksm/xlk3ld
title: flow_5-10.tab

description: :unav
DOI: 10.21227/b0fp-rm90
title: Channel Impulse Responses from Mar. 2019 Long Range Experiment (Mediterranean Sea)

description: The Underwater Acoustic & Navigation Lab in University of Haifa conducted a shallow water long-range underwater acoustic communication experiment across the shores of Northern Israel in March 2019. The experiment was designed to verified the adaptive modulation scheme for long-range underwater acoustic communicaiton proposed by the authors. To make the work reproducible, the authors freely share the estimated channel impulse responses from the sea experiment.
DOI: 10.21227/nzgr-ds72
title: Channel Impulse Responses from Mar. 2019 Long Range Experiment (Mediterranean Sea)

description: The Underwater Acoustic & Navigation Lab in University of Haifa conducted a shallow water long-range underwater acoustic communication experiment across the shores of Northern Israel in March 2019. The experiment was designed to verified the adaptive modulation scheme for long-range underwater acoustic communicaiton proposed by the authors. To make the work reproducible, the authors freely share the estimated channel impulse responses from the sea experiment.
DOI: 10.7910/dvn/spoksm/ctblok
title: flow_7-7.tab

description: :unav
DOI: 10.7910/dvn/spoksm/glul97
title: vsl_7-6.tab

description: :unav
DOI: 10.7910/dvn/spoksm/gyqmkt
title: density_0-3.tab

description: :unav
DOI: 10.7910/dvn/spoksm/kvi3c4
title: density_3-11.tab

description: :unav
DOI: 10.7910/dvn/spoksm/ofdcps
title: ramp_queue_length_7-1.tab

description: :unav
DOI: 10.7910/dvn/spoksm/xpwzym
title: density_7-7.tab

description: :unav
DOI: 10.7910/dvn/spoksm/yj7l9c
title: density_5-5.tab

description: :unav
DOI: 10.7910/dvn/spoksm/z7kjko
title: flow_3-1.tab

description: :unav
DOI: 10.7910/dvn/spoksm/zqencj
title: flow_0-12.tab

description: :unav
DOI: 10.34681/nped-kz53
title: National Youth in Transition Database (NYTD)-Services File, FY2011-2018

description: The John H. Chafee Foster Care Independence Program (CFCIP) was initiated in an effort to improve outcomes for youth in foster care who are likely to reach their 18th birthday without having found a permanent home. The program provides funding to states to develop and administer programs designed to help ease the transition from foster care to independence. The law that created CFCIP also required states to develop 1) a system for tracking the services provided through CFCIP, and 2) a method for collecting outcome measures so that the effectiveness of the program can be assessed. These two components together form the National Youth in Transition Database (NYTD). The files contain data from all 50 states, as well as from the District of Columbia and Puerto Rico. The Services component (this dataset) contains cross-sectional information on the services provided by states under CFCIP and the youth who receive those services. Data are submitted by the states every 6 months on a continuing basis. This dataset contains the cumulative data from the beginning of the study through 2018. The https://www.ndacan.cornell.edu/datasets/datasets-list-nytd. Outcomes component contains the results of surveys conducted with youth to examine certain well-being, financial, and educational outcomes as they get older. Data from a survey on outcomes for a cohort of youth is provided every other year beginning with federal fiscal year 2011 (Oct 1, 2010 through Sep 30, 2011). There are three phases of outcome data for a given cohort -- a baseline survey during the year of the youth’s 17 birthday, and two follow-ups: one at age 19, one at age 21. New cohorts will be established every three years (2014, 2017, 2020…) after the initial one in FY2011.
DOI: 10.7910/dvn/spoksm/hcxcft
title: density_0-8.tab

description: :unav
DOI: 10.7910/dvn/spoksm/imzgdm
title: flow_2-13.tab

description: :unav
DOI: 10.7910/dvn/spoksm/jhfkov
title: flow_9-12.tab

description: :unav
DOI: 10.7910/dvn/spoksm/nwcazw
title: vsl_2-3.tab

description: :unav
DOI: 10.7910/dvn/spoksm/rxi9zk
title: vsl_8-3.tab

description: :unav
DOI: 10.7910/dvn/spoksm/w1h3q2
title: density_6-7.tab

description: :unav
DOI: 10.7910/dvn/spoksm/xper2p
title: flow_2-1.tab

description: :unav
DOI: 10.7910/dvn/spoksm/yi5vwh
title: density_6-9.tab

description: :unav
DOI: 10.7910/dvn/spoksm/ecdkvs
title: ramp_queue_length_5.tab

description: :unav
DOI: 10.7910/dvn/spoksm/f28rno
title: vsl_3-2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/kbfjzh
title: density_8-12.tab

description: :unav
DOI: 10.7910/dvn/spoksm/ko1ayx
title: vsl_2-6.tab

description: :unav
DOI: 10.7910/dvn/spoksm/lo6u9f
title: flow_0-9.tab

description: :unav
DOI: 10.7910/dvn/spoksm/rqq7h1
title: density_8-7.tab

description: :unav
DOI: 10.7910/dvn/spoksm/sxt3jd
title: flow_8-11.tab

description: :unav
DOI: 10.17632/6sbfghhkm7.1
title: Rexaxys Project run1

description: this is for first fun data for Rexaxys Project
DOI: 10.17632/xmyrr4y8v8.1
title: KEY FACTORS OF SUSTAINABLE PRODUCT DESIGN: BRAND VALUE AND USER EXPERIENCE

description: In this study, Delphi method and DNAP method were used to explore the key factors for users in their purchasing of notebook computers, and then the key elements of sustainable product design were discussed according to the causal relationship between the key factors.
DOI: 10.17909/t9-6qez-fw41
title: GW170817 ACS Mar 2019
DOI: 10.7910/dvn/spoksm/ej7ww7
title: flow_1.tab

description: :unav
DOI: 10.7910/dvn/spoksm/eohqir
title: density_1-11.tab

description: :unav
DOI: 10.7910/dvn/spoksm/l7nc6p
title: density_4-3.tab

description: :unav
DOI: 10.7910/dvn/spoksm/nbnhdi
title: vsl_0-2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/urgaim
title: flow_4-8.tab

description: :unav
DOI: 10.7910/dvn/spoksm/vbyl3e
title: flow_5-2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/wkf05k
title: density_9-5.tab

description: :unav
DOI: 10.7910/dvn/spoksm/xo7tyz
title: density_8-11.tab

description: :unav
DOI: 10.7910/dvn/spoksm/ytgoqy
title: vsl_5-1.tab

description: :unav
DOI: 10.5281/zenodo.3362810
title: A Review on Emerging Organic-containing Microporous Material Membranes for Carbon Capture and Separation

description: <strong>Published article:</strong> Prasetya, N., Himma, N. F., Doddy Sutrisna, P., Wenten, I. G. & Ladewig, B. P. <em>Chem. Eng. J.</em> 123575 (2019). https://doi.org/10.1016/j.cej.2019.123575 <strong>Abstract</strong> Membrane technology has gained great attention as one of the promising strategies for carbon capture and separation. Intended for such application, membrane fabrication from various materials has been attempted. While gas separation membranes based on dense polymeric materials have been long developed, there is a growing interest to use porous materials as the membrane material. This review then focuses on emerging porous materials to be used for the fabrication of membranes that are designed for CO<sub>2</sub>separation. Criteria for selecting microporous material are first discussed, including physical and chemical properties, and parameters in membrane fabrication. Membranes based on emerging porous materials,such as metal-organic frameworks, porous organic frameworks, and microporous polymers,are then reviewed. Finally, special attention is given to recent advances, challenges, and perspectives in the development of such membranes for carbon capture and separation.
DOI: 10.7910/dvn/spoksm/3qpbwa
title: density_6-2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/4gzlly
title: vsl_5-3.tab

description: :unav
DOI: 10.7910/dvn/spoksm/7pmwga
title: vsl_9-6.tab

description: :unav
DOI: 10.7910/dvn/spoksm/agrqbs
title: ramp_metering_rate_2.tab

description: :unav
DOI: 10.7910/dvn/spoksm/lizl5p
title: flow_6-12.tab

description: :unav
DOI: 10.7910/dvn/spoksm/u5xpkr
title: density_7-12.tab

description: :unav
DOI: 10.25739/chab-0e35
title: GOMAP Peanut IPGI 1.0

description: This dataset generated by GOMAP is a high-coverage and reproducible functional annotation set based on Gene Ontology (GO) term assignments that covers all gene models in the International Peanut Genome Initiative Arachis hypogaea genome annotation 1.0 (cultivar Tifrunner, related publication: https://doi.org/10.1038/s41588-019-0405-z ) with a median of 10 annotations per gene model. It was created in April of 2019.
DOI: 10.5061/dryad.fv453k7/1
title: Dryad Item 10.5061/DRYAD.FV453K7/1

description: (:tba)
DOI: 10.5281/zenodo.3362809
title: A Review on Emerging Organic-containing Microporous Material Membranes for Carbon Capture and Separation

description: <strong>Published article:</strong> Prasetya, N., Himma, N. F., Doddy Sutrisna, P., Wenten, I. G. & Ladewig, B. P. <em>Chem. Eng. J.</em> 123575 (2019). https://doi.org/10.1016/j.cej.2019.123575 <strong>Abstract</strong> Membrane technology has gained great attention as one of the promising strategies for carbon capture and separation. Intended for such application, membrane fabrication from various materials has been attempted. While gas separation membranes based on dense polymeric materials have been long developed, there is a growing interest to use porous materials as the membrane material. This review then focuses on emerging porous materials to be used for the fabrication of membranes that are designed for CO<sub>2</sub>separation. Criteria for selecting microporous material are first discussed, including physical and chemical properties, and parameters in membrane fabrication. Membranes based on emerging porous materials,such as metal-organic frameworks, porous organic frameworks, and microporous polymers,are then reviewed. Finally, special attention is given to recent advances, challenges, and perspectives in the development of such membranes for carbon capture and separation.
DOI: 10.5281/zenodo.3362849
title: Training Data for "Metatranscriptomics analysis using microbiome RNASeq data"

description: Microbiomes play a critical role in host health, disease, and the environment.. Functional microbiome analysis which estimates the functional groups expressed by microbial community enables researchers to look beyond taxonomic composition and correlation with the condition under study. Using microbial community RNA-Seq data and subsequent metatranscriptomics workflows to elucidate the functional complement of the microbiome is gaining interest in the field.<br> This tutorial from Galaxy training network will introduce researchers to the basic concepts of metatranscriptomics data analysis. It takes in paired-end datasets of raw shotgun sequences (in FastQ format) as an input and: preprocess extract and analyze the community structure (taxonomic information) extract and analyze the community functions (functional information) combine taxonomic and functional information to offer insights into taxonomic contribution to a function or functions expressed by a particular taxonomy. The dataset used in the tutorial comes from a time-serie analysis of a microbial community inside a bioreactor (Kunath et al, ISME, 2018). Only the data for one time point (1st) and a biological replicate (A) is analyzed here, after having been trimmed out the original file for the purpose of saving time and resources.
DOI: 10.6073/pasta/7eb9d9c55e18a726a0b29db5d0f58915
title: Respiration in soils collected from the REU synoptic sample grid in the Andrews Experimental Forest, 1994-1995

description: The 1993 (SP005) sampling grid was expanded to 183 sites providing a more comprehensive sampling grid. Because of potential edge effects problems, all sample locations were moved at least 20 meters from the closest road or clearing. Changes from the original location are given in entity 2. CO2 is measured over a period of 41 weeks in soils collected from all of the REU synoptic sample sites in the summer of 1994. Soils were weighted at the same time that respiration was assayed and moisture content was maintained at the same level throughout the series. The time period represented by this data is 15 September 1994 to 12 July 1995. In the initial stages, CO2 concentrations were assayed every week, after 15 weeks, the incubation period was extended to 2 weeks. After the incubation vessels were assayed, the headspace was flushed with lab air and the moisture was adjusted with sterile deionized water. Results show that there was a very high correlation between respiration rates during the 1st and 3rd weeks (r = 0.96) suggesting that the two week incubation period we us as an indicator of initial concentrations of labile carbon is valid. There was also a high correlation between rates observed within the first week and rates observed after 41 weeks (r = 0.85) suggesting that the initial rates provide a good relative guide to rates observed after 10 months. In addition, respiration rates after 41 weeks were 80% of those observed during the first week.
DOI: 10.25739/1ywe-ew96
title: GOMAP Common Bean DOE-JGI and USDA-NIFA v2.0

description: This dataset generated by GOMAP is a high-coverage and reproducible functional annotation set based on Gene Ontology (GO) term assignments that covers all protein coding gene models in the DOE-JGI and USDA-NIFA Phaseolus vulgaris annotation 2.0 (http://phytozome.jgi.doe.gov) with a median of 11 annotations per gene model. It was created in April of 2019.
DOI: 10.5066/f7pc3196
title: Data release for the Understanding recurrent land use processes and long-term transitions in the dynamic south-central United States, c. 1800 to 2006

description: The dataset was generated for the South Central Plains EPA level III ecoregion which extends through eastern Texas, northwestern Louisiana, southwest Arkansas, and a small portion of southeastern Oklahoma covering approximately 15.2 ha. Contained in the data set are land change causes that occurred between 2001 to 2006 such as forest harvest, surficial mining, and cropland expansion. Only those pixels (30-meter resolution) that have changed during the time period have their cause classified, otherwise no change is indicated between 2001 and 2006. In general, the process to create the data combined an automated and manual interpretation approach of spatial data to correctly identify land change causes. In the approach, available spatial data were analyzed using an algorithm-based process of aggregation, validation, and attribution (AVA). Data that could not be validated as to their land change cause in the algorithm, were manually interpreted using historical imagery provided by Google Earth, Landsat satellite data, or high-resolution orthoimagery from National Agricultural Imagery Program (NAIP).
DOI: 10.7910/dvn/tud094/dm4lwa
title: Database_SchoolZones.rar

description: :unav
DOI: 10.25739/2sqc-j140
title: GOMAP Barrel Clover R108_HM340 v1.0

description: This dataset generated by GOMAP is a high-coverage and reproducible functional annotation set based on Gene Ontology (GO) term assignments that covers all protein coding gene models in the R108: v1.0 Medicago truncatula genome annotation (genotype R108_HM340, publication: https://10.1186/s12864-017-3971-4) with a median of 9 annotations per gene model. It was created in April of 2019.
DOI: 10.5281/zenodo.3362276
title: Antarctic continent MAR 6-hourly data

description: Modèle Atmosphérique Régionale (MAR), was utilized Wille et al. (2019; Nature Geoscience). Each file contains snowfall, run off, surface temperature, sublimation, and melt at six-hour timesteps. A description of MAR from Wille et al. (2019) follows as... "Modèle Atmosphérique Régionale (MAR), a regional climate model (RCM) run at a 35 x 35 km2 horizontal resolution over the whole Antarctic continent with a 120 second time step and outputs every six hours. The MAR RCM includes the multi-layer snow model Crocus, which calculates meltwater at the surface when it reaches the melting point in combination with a surplus of energy (a deficit results in refreezing). The presence of meltwater alters the snow characteristics, for example the type and size of snow-grains and the albedo. Percolation through the snowpack is determined through a tipping bucket method based on snow density. We use 30 snow or ice layers of variable thickness from the surface to a 20 m depth. This version of MAR has been extensively tested over the Antarctic ice sheet25 and recently utilized by the Ice Sheet Mass Balance Inter-comparison Exercise (IMBIE) team." Agosta, C. et al. Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes. The Cryosphere 13, 281–296 (2019).
DOI: 10.5281/zenodo.3362277
title: Antarctic continent MAR 6-hourly data

description: Modèle Atmosphérique Régionale (MAR), was utilized Wille et al. (2019; Nature Geoscience). Each file contains snowfall, run off, surface temperature, sublimation, and melt at six-hour timesteps. A description of MAR from Wille et al. (2019) follows as... "Modèle Atmosphérique Régionale (MAR), a regional climate model (RCM) run at a 35 x 35 km2 horizontal resolution over the whole Antarctic continent with a 120 second time step and outputs every six hours. The MAR RCM includes the multi-layer snow model Crocus, which calculates meltwater at the surface when it reaches the melting point in combination with a surplus of energy (a deficit results in refreezing). The presence of meltwater alters the snow characteristics, for example the type and size of snow-grains and the albedo. Percolation through the snowpack is determined through a tipping bucket method based on snow density. We use 30 snow or ice layers of variable thickness from the surface to a 20 m depth. This version of MAR has been extensively tested over the Antarctic ice sheet25 and recently utilized by the Ice Sheet Mass Balance Inter-comparison Exercise (IMBIE) team." Agosta, C. et al. Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes. The Cryosphere 13, 281–296 (2019).
DOI: 10.5061/dryad.677b1c7/1
title: Dryad Item 10.5061/DRYAD.677B1C7/1

description: (:tba)
DOI: 10.5061/dryad.677b1c7/2
title: Dryad Item 10.5061/DRYAD.677B1C7/2

description: (:tba)
DOI: 10.6073/pasta/06d2105761dab76fb480a01b2424338c
title: Plum Island LTER phytoplankton identification using HPLC and Chem Taxonomy along transects in the Plum Island Sound estuary, Massachusetts.

description: Water column samples are collected along an estuarine salinity gradient as part of our monitoring surveys of the Parker River estuary each spring and late summer (typically high vs low freshwater input). Samples are filtered, and stored frozen for later pigment analyses by HPLC. Pigment data are then analyzed by CHEMTAX, calibrated to a matrix of pigment ratios based on taxonomy and enumeration of selected subsamples by microspcopy. Data are presented in terms of chlorophyll a concentrations partitionaed among the major phytoplankton groups as determined by CHEMTAX. For 2003-2006, sampling stations along the Plum Island Sound-Parker River were at fixed geographic locations at specific "Bends" in the river. In 2008, we began sampling the water column in salinity space rather than at specific geographic locations along the river. This sampling approach was adopted in order to follow particular water masses in this macrotidal estuary. In practical terms, it means that sampling locations, or stations, are not static. Therefore, we have mapped the 11 sampling locations (latitude and longitude are logged at each station) from each transect along the mainstem of the estuary, so each station may be placed along the river (to the nearest 0.5km) as well as in salinity space. We have also used the km marker to assign the sampling locations from each survey to one of four bounding boxes : the Sound (Plum Island Sound; EST-PR-SoundBND) which encompasses approximatly the first 9.5 km or the transect, with Okm at the mouth of the sound; the Lower Parker River (EST-PR-LowerParkerBND) , ~9.5 - 14.5 km; the Middle Parker River (EST-PRMiddleParkerBND), ~14.5 - 18.75 km, and the Upper Parker River (EST-PR-UpperParker BND)., ~18.75 to 24.25 km (the Parker R. Dam).
DOI: 10.7910/dvn/wjw1ha/b010nv
title: CueData-1.tab

description: :unav
DOI: 10.7910/dvn/wjw1ha/dtvthi
title: MoveVehdata.tab

description: :unav
DOI: 10.7910/dvn/wjw1ha/hvefsn
title: MoveVehdata-1.tab

description: :unav
DOI: 10.7910/dvn/wjw1ha/iantah
title: CueData.tab

description: :unav
DOI: 10.7910/dvn/wjw1ha/kmv8ue
title: logData-1.tab

description: :unav
DOI: 10.7910/dvn/wjw1ha/qkva9y
title: RLR_S1_02.db

description: :unav