cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18710/3otfvo
title: Replication data for: Biochemical changes after cold acclimation in Nordic red clover (Trifolium pratense L.) accessions with contrasting levels of freezing tolerance

description: The data deposited here correspond to the content of analyzed metabolites (carbohydrates, amino acids and phenolic compounds) in red clover crowns before and after cold acclimation treatment. Carbohydrates and amino acids content was determined through high performance liquid chromatography (HPLC), while phenolic compounds content was determined through liquid chromatography and high-resolution mass spectrometry (HMRS).
description: Empower II software (Waters)
DOI: 10.18710/96nrix/qcvfph
title: C80H162mw6.out
DOI: 10.18710/96nrix/yoqznl
title: 00README.txt
DOI: 10.18710/96nrix/yqzlht
title: valinomycine_mw6.out
DOI: 10.18710/9x52wa/asj1og
title: 20220629_HOP_REDTEC_gal.txt
DOI: 10.18710/9x52wa/nicm8s
title: 20220624_HOP_REDTEC_gal.txt
DOI: 10.18710/9x52wa/sxyorp
title: 20220412_HOP_REDTEC_gal.txt
DOI: 10.18710/apgawl/zlcggw
title: Fold_axes_Devonian_Blomstrandhalvoya.txt

description: Fold axis measurements in Devonian sedimentary rocks in Blomstrandhalvøya.
DOI: 10.18710/bbu6jd/ah14ut
title: model_final.pth
DOI: 10.18710/ces0l8/i7qztt
title: wiki.dan.clean.gz

description: Danish, Wikipedia corpus
DOI: 10.18710/dcd62u/4mdgql
title: Figure4_DYM_Averagedpressuretrend.mat

description: Data set used in Figure 4.
DOI: 10.18710/emjbeo/0gnfni
title: 20220130_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/6ec5za
title: 20220311_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/86bpiz
title: 20220110_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/blpdii
title: 20220211_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/cvcw8z
title: 20220109_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/d0z8r1
title: 20220104_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/fxyejk
title: 20220215_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/h3zp7t
title: 20220327_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/ht5nsi
title: 20220201_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/kilfpt
title: 20220308_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/otelgz
title: 20220122_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/plnm6u
title: 20220126_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/q05x2r
title: 20220202_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/q0hfzs
title: 20220120_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/s5ni9x
title: 20220123_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/vmt4co
title: 20220221_HOP_REDOBS_gps.txt
DOI: 10.18710/fd1zhz/ryvqdq
title: 00_Readme.txt

description: A Readme file for an explanation of the included data published within this dataset, and for an interpretation of the variables in the data file 01_GFL_field_trial_data.xlsx or 02_GFL_field_trial_data.txt
DOI: 10.18710/gti2br/lwzhca
title: questionnaire_english.pdf

description: Questionnaire including consent statement
DOI: 10.18710/gxkvur/wj0adi
title: deflectometry_column_2.zip
DOI: 10.18710/iwdvao/fgxvcm
title: TGO_Ramfjordmoen_ionosonde_data_2016-05_PNG.zip
DOI: 10.18710/keb2mm/c8cafl
title: Day_0_2022-09-01.zip
DOI: 10.18710/lloedm/pnk81l
title: 3_Macro_Analysis_Fig.R
DOI: 10.18710/lmdmsc/cpdou5
title: data_6.bag
DOI: 10.18710/lmdmsc/fyvdeq
title: data_6.bag
DOI: 10.18710/lmdmsc/llxqyp
title: data_7.bag
DOI: 10.18710/lmdmsc/wbzbht
title: data_5.bag
DOI: 10.18710/naqhxl/pyluce
title: References.txt

description: Tabular separated text file
DOI: 10.18710/oat6o9
title: Replication Data for:Contrasting risk patterns from humans and a large carnivore influence the habitat selection of shared prey

description: &lt;p&gt;Abstract of the article&lt;p/&gt;
&lt;p&gt;Spatiotemporal patterns of hunting and predation risk are mediated by the physical landscape, with hunting risk often associated with habitat features contrasting those linked to risk from large carnivores. Contrasting risk patterns from hunters and large carnivores can also vary in time, which may allow prey species to adjust anti-predator strategies not only in risky places but also during risky times. We examined whether moose (Alces alces) in south-central Scandinavia adjusted diel habitat selection during and after the hunting season in response to contrasting human hunting and wolf (Canis lupus) predation risks. &lt;p/&gt;&lt;p&gt; We found evidence for a diel and seasonal shift in habitat selection of moose, consistent with a behavioural adaptation to no hunting risk at night and after the hunting season. We found only partial evidence that moose responded to the seasonal and spatial variation in wolf predation risk. Moose selected habitats of both high and low wolf predation risk during and after the hunting season. Hunting risk was therefore the main driver of moose responses during the hunting season while decreasing in importance during times and in areas when hunting did not occur. However, since we did not find evidence for a diel or seasonal shift in habitat selection consistent with an increase in the importance of wolf predation risk during the night and after the hunting season, our study is in line with the notion that moose in Scandinavia are currently naïve to wolves. &lt;p/&gt;&lt;p&gt;Our study shows the importance of including the effects of humans in studies of predator-prey dynamics in anthropogenic landscapes. An increased understanding of the risk effects arising from humans and large carnivores and the responses of prey might be important for managing ungulate populations, since behaviours aimed at reducing exposure to risk may also affect crucial demographic traits like growth and reproduction. This is especially important considering the return of large carnivores to anthropogenic landscapes.&lt;p/&gt;
description: R
DOI: 10.18710/skqutl/eyrzaa
title: 20221223_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/osv0i2
title: 20221111_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/w9skii
title: 20221005_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/xrldof
title: 20221026_BJN_REDTEC_gal.txt
DOI: 10.18710/tfswlc/guvjsq
title: large_corr_plt_eps80_charged.pdf
DOI: 10.18710/tfswlc/rtlsr7
title: small_mrchemjobs.zip
DOI: 10.18710/bbu6jd
title: Supplementary data for "Object detection neural network improves Fourier ptychography reconstruction"

description: This dataset holds the trained deep learning models for our paper "Object detection neural network improves Fourier ptychography reconstruction". The results produced in the paper can be replicated through the use of these models in conjunction with the inference scripts provided in our GitHub repository: &lt;a href="https://github.com/IAmSuyogJadhav/NN-Illumination-Estimation-FPM"&gt;External Link&lt;/a&gt;.
description: &lt;br /&gt;&lt;b&gt;Abstract&lt;/b&gt;
&lt;br /&gt;
High resolution microscopy is heavily dependent on superb optical elements and superresolution microscopy even more so. Correcting unavoidable optical aberrations during post-processing is an elegant method to reduce the optical system’s complexity. A prime method that promises superresolution, aberration correction, and quantitative phase imaging is Fourier ptychography. This microscopy technique combines many images of the sample, recorded at differing illumination angles akin to computed tomography and uses error minimisation between the recorded images with those generated by a forward model. The more precise knowledge of those illumination angles is available for the image formation forward model, the better the result. Therefore, illumination estimation from the raw data is an important step and supports correct phase recovery and aberration correction. Here, we derive how illumination estimation can be cast as an object detection problem that permits the use of a fast convolutional neural network (CNN) for this task. We find that faster-RCNN delivers highly robust results and outperforms classical approaches by far with an up to 3-fold reduction in estimation errors. Intriguingly, we find that conventionally beneficial smoothing and filtering of raw data is counterproductive in this type of application. We present a detailed analysis of the network’s performance and provide all our developed software openly.
description: Detectron2, 0.2
description: PyTorch, 1.10.0
DOI: 10.18710/emjbeo/h8zjbp
title: 20220111_HOP_REDOBS_gal.txt
DOI: 10.18710/skqutl/mubgst
title: 20221016_BJN_REDTEC_gps.txt
DOI: 10.18710/9x52wa/ict7vh
title: 20220421_HOP_REDTEC_glo.txt
DOI: 10.18710/9x52wa/kd9q33
title: 20220501_HOP_REDTEC_glo.txt
DOI: 10.18710/9x52wa/ryjfqm
title: 20220504_HOP_REDTEC_gal.txt
DOI: 10.18710/9x52wa/tdtzsw
title: 20220608_HOP_REDTEC_gps.txt
DOI: 10.18710/9x52wa/ywli0y
title: 20220414_HOP_REDTEC_gal.txt
DOI: 10.18710/emjbeo/0d9j0l
title: 20220314_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/0drstm
title: 20220124_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/24ggaz
title: 20220103_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/2cpqbj
title: 20220323_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/9zj4bl
title: 20220131_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/aefe5s
title: 20220119_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/anqtdh
title: 20220112_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/atkqac
title: 20220318_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/kvr0s0
title: 20220118_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/l4evfe
title: 20220403_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/nwhjnj
title: 20220208_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/o8cgok
title: 20220403_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/pnb3bq
title: 20220315_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/qb302z
title: 20220525_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/tmsul9
title: 20220223_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/u3pdhg
title: 20220307_HOP_REDOBS_gal.txt
DOI: 10.18710/gxkvur/7hrcbe
title: deflectometry_log.txt
DOI: 10.18710/mwvqfd/b9xndj
title: 20220320_BJN_REDOBS_gal.txt
DOI: 10.18710/mwvqfd/ddlf6w
title: 20220114_BJN_REDOBS_glo.txt
DOI: 10.18710/skqutl/6xk9pg
title: 20221005_BJN_REDTEC_gal.txt
DOI: 10.18710/skqutl/czumvt
title: 20221014_BJN_REDTEC_glo.txt
DOI: 10.18710/skqutl/emzq6w
title: 20221202_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/hnmnla
title: 20221118_BJN_REDTEC_gal.txt
DOI: 10.18710/skqutl/qzmdj1
title: 20221107_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/vh5lrd
title: 20221216_BJN_REDTEC_gal.txt
DOI: 10.18710/skqutl/yqzcl4
title: 20221228_BJN_REDTEC_gal.txt
DOI: 10.18710/skqutl/zocjl1
title: 20221124_BJN_REDTEC_gps.txt
DOI: 10.18710/2lxwnw
title: Replication Data for "Different protein sources in concentrate feed to dairy cows affects cheese making properties and yield"

description: Norwegian Red dairy cows (n = 48) in early/mid lactation were divided in three groups and fed a ration consisting of grass silage and concentrate, where the concentrates were barley based but with different additional protein sources. These were: completely barley-based with no additional protein source (BAR), additional protein from soybean meal (SMB) or additional protein from yeast (Cyberlindnera jadinii) (YEA). The SBM and YEA concentrates had a higher protein content than the barley concentrate. Four batches of cheese were made from pooled milk from each of the three groups of dairy cows and individual milk samples were collected five times during the experiment and were analysed.
DOI: 10.18710/5np4dg/w7vmnm
title: 01_Nie.etal.2022.ImpactFemale.JSJ.rplc.dta

description: The data set supports an analysis of impact of female leadership in a collegial court. The data set (saved in Stata *.dta(tab)) contains all observations (Norwegian supreme court cases 2008-2019 decided in five-justice panels) and variables relevant for a complete replication of the study.
DOI: 10.18710/5np4dg/yqrho7
title: 02_Nie.etal.2022.ImpactFemale.JSJ.rplc.txt

description: The data set supports an analysis of impact of female leadership in a collegial court. The data set (saved in Notepad/Windows10 *.txt) contains all observations (Norwegian supreme court cases 2008-2019 decided in five-justice panels) and variables relevant for a complete replication of the study.
DOI: 10.18710/5wnwrl/xtferr
title: Mul_etal_2022_data.csv
DOI: 10.18710/96nrix/yejmfh
title: readAlkanes.py
DOI: 10.18710/9x52wa/gvypqz
title: 20220917_HOP_REDTEC_gal.txt
DOI: 10.18710/9x52wa/htwntd
title: 20220426_HOP_REDTEC_gps.txt
DOI: 10.18710/9x52wa/jfvfmm
title: 20220524_HOP_REDTEC_gal.txt
DOI: 10.18710/9x52wa/jutwff
title: 20220416_HOP_REDTEC_glo.txt
DOI: 10.18710/9x52wa/lgslxp
title: 20220510_HOP_REDTEC_glo.txt
DOI: 10.18710/9x52wa/ofog2d
title: 20220411_HOP_REDTEC_gal.txt
DOI: 10.18710/9x52wa/porjlu
title: 20220522_HOP_REDTEC_glo.txt
DOI: 10.18710/9x52wa/qd2e6p
title: 20220526_HOP_REDTEC_glo.txt
DOI: 10.18710/9x52wa/u5buot
title: 20220519_HOP_REDTEC_gps.txt
DOI: 10.18710/atcqzw
title: Biber et al.'s (2016) set of 150 BNC items for the analysis of dispersion measures: Dataset for "Evaluation of text-level measures of lexical dispersion"

description: This dataset contains frequencies for a set of 150 word forms in the BNC. The set of items was compiled by Biber et al. (2016) for the purpose of analyzing the behavior of dispersion measures in different distributional settings. It was therefore assembled to cover a broad range of frequency and dispersion levels. For each form, the dataset lists (i) the number occurrences in each of the 4049 text files in the BNC, including zero counts; and (ii) the length of each text file, i.e. the number of word tokens it contains.
description: rcqp (R package), 0.5
DOI: 10.18710/gntwog/zd1qj7
title: raw_data.zip
DOI: 10.18710/htcxrn/eybkfc
title: 19_medaka29_C_5_40x.png

description: Ovaries histology image for fish 29
DOI: 10.18710/htcxrn/qwh5ay
title: 17_medaka26_B_5_40x.png

description: Ovaries histology image for fish 26
DOI: 10.18710/ktyyqy
title: TGO Ramfjordmoen Ionosonde Data July 2022

description: &lt;p&gt;About this dataset: This dataset contains ionosonde data in SAO format and ionograms in PNG format, and covers data from July 01-31, 2022.&lt;/p&gt;&lt;p&gt;About the Tromsø Ionosonde (1993-present): Since 1980, the ionosonde was situated at 69° 35' N, 19° 13' E at Ramfjordmoen near Tromsø, Norway and operated by the Auroral Observatory of the University of Tromsø and later on, in collaboration with QinetiQ. The Lowell ionosonde replaced the Auroral Observatory unit in 1992; see the related publication for details.&lt;/p&gt;
description: TGO Ionosonde Data
DOI: 10.18710/lemwj0/ifklgg
title: Exp00b_eventdata_merged.txt

description: Raw eye tracking data from the unimanual response setup
DOI: 10.18710/lfyoxw/dnwgju
title: TGO_Ramfjordmoen_ionosonde_data_2022-08.PNG.zip
DOI: 10.18710/mpl6fl/rjrokx
title: 03_Figure-3.png
DOI: 10.18710/mwvqfd/1ehkmp
title: 20220222_BJN_REDOBS_gps.txt
DOI: 10.18710/sbr9gj
title: Replication data for "Stress constraints from shear-wave analysis in shallow sediments at an actively seeping pockmark on the W-Svalbard Margin"

description: The attached dataset has ocean bottom seismic (OBS) data, 3D seismic data and matlab scripts used in the analysis of OBS data.
OBS data was acquired using an array of 22 ocean bottom seismometers (OBS) during a research expedition (CAGE-2019-1) around Lunde pockmark, Vestnesa Ridge, W-Svalbard Margin. This data acquisition aims to improve our understanding of actively hydrocarbon gas seeping system in Vestnesa Ridge, west-Svalbard Margin.
3D seismic data was acquired in 2013 around Lunde pockmark, Vestnesa Ridge, W-Svalbard Margin using high-resolution 3D P-Cable seismic data acquisition system. Details of 3D seismic data processing and interpretation are already published in the research article "Role of tectonic stress in seepage evolution along the gas hydrate‐charged Vestnesa Ridge, Fram Strait" (Doi:10.1002/2014GL062474).
description: Petrel
description: Matlab
DOI: 10.18710/skqutl/40xikd
title: 20221224_BJN_REDTEC_glo.txt
DOI: 10.18710/skqutl/cqtz3h
title: 20221023_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/v55m0e
title: 20221127_BJN_REDTEC_glo.txt
DOI: 10.18710/skqutl/xm1u3b
title: 20221126_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/zhvmdp
title: 20221116_BJN_REDTEC_gps.txt
DOI: 10.18710/ur1qaa/rio3bk
title: ProDrop_SWU.xlsx

description: Excel file for ProDrop_SWU.txt
DOI: 10.18710/vzhswt/v9vdrh
title: L.Saccharina_qNMR_calculations.txt

description: This data set presents quantification data from qNMR for Fucus vesiculosus.
DOI: 10.18710/xoyehp/tvrvdq
title: 01_V3_ReadMe_Sajnovics_Demonstratio.txt
DOI: 10.18710/7u6tzp/sc502z
title: 00Readme.txt

description: Readme file for the dataset.
DOI: 10.18710/9x52wa/50bswm
title: 20220406_HOP_REDTEC_gps.txt
DOI: 10.18710/9x52wa/cxwkot
title: 20220428_HOP_REDTEC_gps.txt
DOI: 10.18710/9x52wa/pxr2m7
title: 20220530_HOP_REDTEC_glo.txt
DOI: 10.18710/9x52wa/vma7l1
title: 20220521_HOP_REDTEC_gal.txt
DOI: 10.18710/9x52wa/y5j6rk
title: 20220602_HOP_REDTEC_gps.txt
DOI: 10.18710/gx1vyi
title: Background Data for: "University students’ feedback regarding effective measures to prevent bullying"

description: This study explored university students’ perceptions of the usefulness of some antibullying measures in ensuring a bullying-free learning environment. The results in this paper are part of a larger comparative study that investigated the prevalence of bullying in Norway and Ghana, albeit limiting this paper to students’ recommendations of preventive measures. Students from Norway (n = 438) and Ghana (n = 751) were recruited. The comparative study highlights the sociocultural tendencies underlying some recommendations to provide holistic knowledge. The analyses revealed significant differences in students' recommendations from both countries. Generally, the responses suggest the need for the impartial application of disciplinary measures to students and lecturers; independent contact persons for reporting; students’ and authorities’ collaboration for bullying prevention; antibullying employment contracts; counselling services; and awareness creation. With unique national cultures and changing societal trends, we suggest that national policies that aim at cultural consciousness regarding bullying would be ideal for its prevention.
DOI: 10.18710/ixw3va/mlyhkn
title: HH17-1289-GC-TUNU_30kV_XRF.txt

description: X-ray fluorescence (XRF) data for the sedimentary core HH17-1289-GC-TUNU (.txt) (2/2)
DOI: 10.18710/sk0r1n/qvnjkn
title: DataFile_KnowingDoingFeeling_Longitudinal_sample.csv

description: Longitudinal sample. Unicode UTF-8 encoded plain text files with semicolon-separated values (.csv).
DOI: 10.18710/skqutl/cygyr0
title: 20221228_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/lzjjl1
title: 20221030_BJN_REDTEC_glo.txt
DOI: 10.18710/skqutl/owfnij
title: 20221212_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/uyh15j
title: 20221216_BJN_REDTEC_gps.txt
DOI: 10.18710/skqutl/vczzcj
title: 20221225_BJN_REDTEC_gal.txt
DOI: 10.18710/xosamd/dc45gb
title: herb_v1_experiment3_final_push-table.csv

description: Data for the third experiment
DOI: 10.18710/ykzbmr
title: Replication Data for: Ditransitive constructions in Russian and Ukrainian

description: Publication abstract: This paper presents new experimental data on the acquisition of structures involving ditransitive verbs in two East Slavic languages: Russian and Ukrainian. The results of an elicited production task with adults and 3-6-year-old children show that the ordering of the two object arguments (DPdat and DPacc) is conditioned by the givenness of one of them. Similarly to adults, children place given recipients before themes, preferring the DPdat-DPacc word order in recipient-given contexts. However, unlike adults, they prefer this order in theme-given contexts as well. We propose that these findings might be indicative of a preference for the underlying syntactic structure in child grammars and/or for the use of prosodic means to express the same meaning, rather than a lack of knowledge of the pragmatic principle Given-before-New at this developmental stage.
description: The full dataset consists of (1) experimental stimuli (ppt), (2) coded data in an excel file, (3) the R file with the statistical analysis (txt), and (4) a method description.
DOI: 10.18710/0no42l/fc6aom
title: 01_Gruvefjellet_Summer_Images Raw_Part 2.zip
DOI: 10.18710/2jsp2x/hqqoz7
title: 8_Jesus_fra_Nasaret_II.pdf
DOI: 10.18710/2jsp2x/pnutha
title: 4_Fra_Abraham_til_Josef.pdf
DOI: 10.18710/96nrix/bcsfyd
title: C160H322mw5.out
DOI: 10.18710/emjbeo/iezgwx
title: 20220421_HOP_REDOBS_gal.txt
DOI: 10.18710/gxkvur/okjy4i
title: p_125_3.mat
DOI: 10.18710/gxkvur/sitahf
title: deflectometry_half_2.zip
DOI: 10.18710/htcxrn/0hrjxt
title: 36_medaka88_A_2_40x.png

description: Ovaries histology image for fish 88
DOI: 10.18710/htcxrn/7tirik
title: 06_medaka1_B_3_40x.png

description: Ovaries histology image for fish 1
DOI: 10.18710/ixw3va/squ5rc
title: HH17-1290-GC-TUNU_30kV_XRF.txt

description: X-ray fluorescence (XRF) data for the sedimentary core HH17-1290-GC-TUNU (.txt) (2/2)
DOI: 10.18710/lemwj0/cixcez
title: 00_README.txt
DOI: 10.18710/lmdmsc/hpj98t
title: data_7.bag
DOI: 10.18710/lmdmsc/jn53p0
title: data_0.bag
DOI: 10.18710/mwvqfd/bap36q
title: 20220219_BJN_REDOBS_gal.txt
DOI: 10.18710/q5s1iw/3y7yo9
title: school_f_lex_div.py

description: Python schript written by Christian Wehmeier.
DOI: 10.18710/sk0r1n/oafybz
title: DataFile_KnowingDoingFeeling_CrossSectional_sample.csv

description: Cross-sectional sample. Unicode UTF-8 encoded plain text files with semicolon-separated values (.csv).
DOI: 10.18710/sk0r1n/wwdawb
title: Assignment-based measures for assessing IL skills.pdf

description: This file describes the two assignment-based measures that were used to measure students' information literacy skills: 1) source evaluation measure; 2) source use measure. These measures were designed to assess students' skills in practice, using authentic assignments, when evaluating and using information sources.
DOI: 10.18710/skqutl/br3zks
title: 20221010_BJN_REDTEC_gal.txt
DOI: 10.18710/xosamd/8fkpcx
title: herb_v1_small_worlds_parameterization-table.csv

description: Data used to parameterize the small world model
DOI: 10.18710/xosamd/j1ejnc
title: herb_v1_validation-table.csv

description: Data used for the validation table in the paper.
DOI: 10.18710/z2xusw/6lckrp
title: parts-11600-p00000.dat

description: Binary data containing the position and velocity of the all the plasma particles assigned to the first process (total values is the sum of all processes on all nodes), used to create velocity distributions.
DOI: 10.18710/zm973l/3uitvh
title: koordtrans.jl

description: Coordinate transforms for ECEF, geodetic coordinates, the coordinate system used for the magnetic field and for transforms in general.
DOI: 10.18710/zm973l/4ogn5l
title: loaddata.jl

description: For loading IRI data or ISR data
DOI: 10.18710/zm973l/rc9qap
title: 00_readme.txt
DOI: 10.18710/7u6tzp/tio5bb
title: Dataset documentation.pdf

description: Documentation of the dataset in PDF/A format, based on the Datasheets for Datasets framework.
DOI: 10.18710/9x52wa/jl40mc
title: 20220502_HOP_REDTEC_glo.txt
DOI: 10.18710/emjbeo/z8avbj
title: 20220325_HOP_REDOBS_glo.txt
DOI: 10.18710/htcxrn/bkilfo
title: 05_medaka_quantile_2022.txt

description: Top genes processed using quantile normalization
DOI: 10.18710/htcxrn/uehyzs
title: 34_medaka78_B_4_40x.png

description: Ovaries histology image for fish 78
DOI: 10.18710/j0qx3e/zqtkxs
title: EHT_SOLIS_z0.25_488nmEx_525nmEm_1.35NA_100x_8Hz_3x1.tif
DOI: 10.18710/2ujhhu/jojy9h
title: phoneme_scrabble_tiles.pdf

description: Overview of phoneme scrabble tiles (for each symbol: points/value, number of tiles in game)
DOI: 10.18710/2ujhhu/kcgvfe
title: transcription_test.pdf

description: Test used to measure "transcription ability"
DOI: 10.18710/2ujhhu/nxbvcd
title: transcription_test_design.pdf

description: Design of test part 1: coverage of sub-variables (vowels, consonants, final devoicing, standard accuracy)
DOI: 10.18710/96nrix/ggzjer
title: C240H482.inp
DOI: 10.18710/96nrix/ztjqzt
title: parallel_mw_plots.ipynb
DOI: 10.18710/bbu6jd/8yxlp8
title: cfg.pkl
DOI: 10.18710/bbu6jd/bygtjy
title: cfg.pkl
DOI: 10.18710/ces0l8/rmxxuo
title: wiki.tha.clean.gz

description: Thai, Wikipedia corpus
DOI: 10.18710/dvybty/o1p8gl
title: Larvae_SampleInfo.csv

description: Zooplankton sample collection information
DOI: 10.18710/gxkvur/dlgawx
title: BOS_log.txt
DOI: 10.18710/gxkvur/ksqtec
title: p_125_1.mat
DOI: 10.18710/gxkvur/oetp4l
title: p_125_2.mat
DOI: 10.18710/gxkvur/uaud10
title: deflectometry_full_2.zip