cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18710/dyezdl
title: Video recordings of spawning behavior of Arctic charr; date: 2016-09-20; spawning ground: 3; time: afternoon; camera no: 4

description: &lt;p&gt;This dataset contains video recordings of spawning behavior of Arctic charr (&lt;em&gt;Salvelinus alpinus&lt;/em&gt;) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 4 at spawning ground 3 in the afternoon of 20 September 2016.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "Documentation of the Spawning behavior of Arctic charr video collection", DataverseNO, https://doi.org/10.18710/VIQB0B&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;This dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "The Spawning behavior of Arctic charr video collection". DataverseNO. https://doi.org/10.18710/HTM6-F146.&lt;/b&gt;&lt;/p&gt;
description: afternoon
DOI: 10.18710/mwegac
title: Video recordings of spawning behavior of Arctic charr; date: 2016-09-21; spawning ground: 3; time: morning; camera no: 6

description: &lt;p&gt;This dataset contains video recordings of spawning behavior of Arctic charr (&lt;em&gt;Salvelinus alpinus&lt;/em&gt;) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 6 at spawning ground 3 in the morning of 21 September 2016.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "Documentation of the Spawning behavior of Arctic charr video collection", DataverseNO, https://doi.org/10.18710/VIQB0B&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;This dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "The Spawning behavior of Arctic charr video collection". DataverseNO. https://doi.org/10.18710/HTM6-F146.&lt;/b&gt;&lt;/p&gt;
description: morning
DOI: 10.18710/qnervt/3jok27
title: realisation.1
DOI: 10.18710/qnervt/8vbgrd
title: .master
DOI: 10.18710/qnervt/b3yrjw
title: realisation
DOI: 10.18710/qnervt/dkdrmb
title: realisation
DOI: 10.18710/qnervt/eox0g0
title: .master
DOI: 10.18710/qnervt/fbrylv
title: .master
DOI: 10.18710/qnervt/ga1hh6
title: .master
DOI: 10.18710/qnervt/hqteyf
title: realisation
DOI: 10.18710/qnervt/jhjsoc
title: .master
DOI: 10.18710/qnervt/rmjpbn
title: .master
DOI: 10.18710/qnervt/urllvz
title: .master
DOI: 10.18710/qnervt/wvjasb
title: .master
DOI: 10.18710/qnervt/x3y5sk
title: .master
DOI: 10.18710/qnervt/xnium8
title: .master
DOI: 10.18710/dw4boy/aj0ozt
title: 2016-09-17_spawning_ground_3_morning_cam_1_file_09.MP4
DOI: 10.18710/dxa0f3/fgetus
title: LOPC_2019-05-07_041627.dat
DOI: 10.18710/dxa0f3/yzenif
title: T8_Biovolume_ai0p4_downProfiles.txt
DOI: 10.18710/qnervt/09stfb
title: .master
DOI: 10.18710/qnervt/10kuzl
title: realisation
DOI: 10.18710/qnervt/4ilrkt
title: .master
DOI: 10.18710/qnervt/4ucecr
title: realisation
DOI: 10.18710/qnervt/88ce9q
title: .master
DOI: 10.18710/qnervt/8liila
title: wallpoly
DOI: 10.18710/qnervt/8ng1wd
title: realisation
DOI: 10.18710/qnervt/dcbmoh
title: realisation
DOI: 10.18710/qnervt/ei7ajb
title: .master
DOI: 10.18710/qnervt/griklb
title: .master
DOI: 10.18710/qnervt/jqo5p9
title: .master
DOI: 10.18710/qnervt/ozjata
title: realisation
DOI: 10.18710/qnervt/pfo7ss
title: realisation
DOI: 10.18710/qnervt/pmiwwr
title: realisation
DOI: 10.18710/qnervt/vxpfkr
title: .master
DOI: 10.18710/qnervt/wmpyvj
title: realisation
DOI: 10.18710/qnervt/xbkhuu
title: .master
DOI: 10.18710/qnervt/z3xli1
title: .master
DOI: 10.18710/qnervt/zxiyeb
title: .master
DOI: 10.18710/tm18uz/rjkovi
title: IMG_0023.JPG
DOI: 10.18710/zlw59w/fyr8bo
title: 2_plotting_violin_plot_priorsens.R

description: plotting results from prior sensitivity analysis.
DOI: 10.15468/dl.c7jbry
title: Occurrence Download

description: A dataset containing 117474 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "OccurrenceStatus is Present",
 "PublishingOrg is c8d737e0-2ff8-42e8-b8fc-6b805d26fc5f",
 "TaxonKey is Basidiomycota"
 ]
}

 The dataset includes 117474 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054559-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18710/4yn9sz/n4pvdm
title: patient_dataset.tar0004
DOI: 10.18710/5gek1j/jctgkn
title: 2016-09-21_spawning_ground_3_evening_cam_3_file_08.MP4
DOI: 10.18710/aajyow/swchos
title: Rat_LSEC_cell_associated_processed_6plexTMT.txt

description: Cell associated proteome from LSECs in vitro at 2h and 24h with different treatments Dex and IL-1β
DOI: 10.18710/ce8rqh/6mfgv1
title: Figure_7.jpg

description: High-resolution version of Figure 7 in manuscript.
DOI: 10.18710/dxa0f3/o6b4ez
title: LOPC_2019-04-29_143536.dat
DOI: 10.18710/hdpb8d/qwibgo
title: 2016-09-21_spawning_ground_3_evening_cam_8_file_01.MP4
DOI: 10.18710/ksubim/ycbmlr
title: 2016-09-24_spawning_ground_3_evening_cam_8_file_02.MP4
DOI: 10.18710/qnervt/adjnbs
title: .master
DOI: 10.18710/qnervt/aokh56
title: realisation.1
DOI: 10.18710/qnervt/bwrrvs
title: realisation.1
DOI: 10.18710/qnervt/cjuzwf
title: .master
DOI: 10.18710/qnervt/kr3m7b
title: .master
DOI: 10.18710/qnervt/lwxvgw
title: .master
DOI: 10.18710/qnervt/or7uhu
title: realisation.1
DOI: 10.18710/qnervt/osepb3
title: ert3
DOI: 10.18710/qnervt/pelbwo
title: realisation
DOI: 10.18710/qnervt/pj8ibz
title: .master
DOI: 10.18710/qnervt/przcwp
title: .master
DOI: 10.18710/qnervt/qa5qop
title: .master
DOI: 10.18710/qnervt/rqyclg
title: realisation.1
DOI: 10.18710/qnervt/rxvk5z
title: realisation
DOI: 10.18710/qnervt/wnl9rs
title: realisation.1
DOI: 10.18710/ufuyic/06oyfg
title: Bedding_surfaces_Minkinfjellet_Fm.txt

description: Bedding surfaces in the Minkinfjellet Formation just east of Pyramiden.
DOI: 10.18710/ufuyic/u8pvus
title: 00_ReadMe.txt

description: ReadMe file.
DOI: 10.18710/xakt0m/rtd2dm
title: 2016-09-17_spawning_ground_3_morning_cam_3_file_03.MP4
DOI: 10.18710/4yn9sz
title: UiT_TILs - Replication Data for "A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images"

description: This dataset can be used to replicate the findings in "A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images". 
The motivation for this paper is that increased levels of tumor infiltrating lymphocytes (TILs) indicate favorable outcomes in many types of cancer. Our aim is to leverage computational pathology to automatically quantify TILs in standard diagnostic whole-tissue hematoxylin and eosin stained section slides (H&E slides). Our approach is to transfer an open source machine learning method for segmentation and classification of nuclei in H&E slides trained on public data to TIL quantification without manual labeling of our data. 
Our results show that improved data augmentation improves immune cell detection in H&E WSIs. Moreover, the resulting TIL quantification correlates to patient prognosis and compares favorably to the current state-of-the-art method for immune cell detection in non-small lung cancer (current standard CD8 cells in DAB stained TMAs HR 0.34 95% CI 0.17-0.68 vs TILs in HE WSIs: HoVer-Net PanNuke Model HR 0.30 95% CI 0.15-0.60). Moreover, we implemented a cloud based system to train, deploy, and visually inspect machine learning based annotation for H&E slides. Our pragmatic approach bridges the gap between machine learning research, translational clinical research and clinical implementation. However, validation in prospective studies is needed to assert that the method works in a clinical setting.
The dataset is comprised of three parts: 1) Twenty image patches with and without overlays used by pathologists to manually evaluate the output of the deep learning models, 2) The models trained and subsequently used for inference in the paper, 3) the patient dataset with corresponding image patches used to clinically validate the output of the deep learning models. The tissue samples were collected from patients diagnosed between 1993 and 2003. Supplementing information was collected retrospectively in the time period 2006-2017. The images were produced in 2017.
DOI: 10.18710/qnervt/6nkmdv
title: realisation
DOI: 10.18710/qnervt/jaqwf9
title: .master
DOI: 10.18710/qnervt/k1wrqw
title: .master
DOI: 10.18710/qnervt/khtmth
title: .master
DOI: 10.18710/qnervt/kuy3nf
title: libfacies
DOI: 10.18710/qnervt/lfzpo9
title: .master
DOI: 10.18710/qnervt/o6mudp
title: realisation
DOI: 10.18710/qnervt/ptjjoa
title: .master
DOI: 10.18710/qnervt/tgac0o
title: .master
DOI: 10.18710/qnervt/tot9ib
title: .master
DOI: 10.18710/qnervt/wcbr48
title: .master
DOI: 10.18710/rx1amj/68hw92
title: 2016-09-21_spawning_ground_3_evening_cam_6_file_03.MP4
DOI: 10.18710/0c1sp5/8lfagh
title: 2016-09-23_spawning_ground_3_morning_cam_1_file_12.MP4
DOI: 10.18710/0c1sp5/maq9bb
title: 2016-09-23_spawning_ground_3_morning_cam_1_file_10.MP4
DOI: 10.18710/0c4pbp/m5rtps
title: 2016-09-23_spawning_ground_3_morning_cam_3_file_12.MP4
DOI: 10.18710/2a5rof/cqz6cu
title: 2016-09-22_spawning_ground_3_evening_cam_3_file_12.MP4
DOI: 10.18710/5gek1j/11vvsf
title: 2016-09-21_spawning_ground_3_evening_cam_3_file_10.MP4
DOI: 10.18710/6lhval/q9kjjr
title: 2016-09-24_spawning_ground_3_morning_cam_3_file_11.MP4
DOI: 10.18710/agiym1/r3xcr1
title: 2016-09-22_spawning_ground_3_evening_cam_4_file_01.MP4
DOI: 10.18710/bgyfc1/0f1jif
title: 2016-09-15_spawning_ground_3_morning_cam_1_file_05.MP4
DOI: 10.18710/ct2hsl/0mdq4f
title: 2016-09-22_spawning_ground_3_evening_cam_2_file_18.MP4
DOI: 10.18710/ct2hsl/5asrcd
title: 2016-09-22_spawning_ground_3_evening_cam_2_file_07.MP4
DOI: 10.18710/ct2hsl/rk9g6s
title: 2016-09-22_spawning_ground_3_evening_cam_2_file_04.MP4
DOI: 10.18710/dgyqef/lkclha
title: 2016-09-22_spawning_ground_3_afternoon_cam_6_file_04.MP4
DOI: 10.18710/dgyqef/vfpyjt
title: 2016-09-22_spawning_ground_3_afternoon_cam_6_file_07.MP4
DOI: 10.18710/hkahgr/jp07q1
title: 2016-09-22_spawning_ground_3_afternoon_cam_9_file_03.mp4
DOI: 10.18710/i55xec/0kqxkg
title: 2016-09-25_spawning_ground_3_evening_cam_6_file_04.MP4
DOI: 10.18710/k6asvb/4d0rvn
title: 2016-09-22_spawning_ground_3_evening_cam_1_file_05.MP4
DOI: 10.18710/lpmpx5/hij3qg
title: 2016-09-23_spawning_ground_3_morning_cam_2_file_11.MP4
DOI: 10.18710/lsqvpq/gh23t2
title: 2016-09-17_spawning_ground_3_morning_cam_4_file_12.MP4
DOI: 10.18710/mifrwn/cbhwpv
title: 0_Readme_Plosives_Andreassen-2021.txt

description: This file contains the necessary information to reproduce the study.
DOI: 10.18710/mxeqcr/qjs0h6
title: 2016-09-21_spawning_ground_3_evening_cam_4_file_01.MP4
DOI: 10.18710/nunhdf/bjosz0
title: StudyPopulation_characteristics_CKD.txt

description: Characteristics of study population by CKD stage
DOI: 10.18710/ozpnko/fwzayf
title: 2016-09-22_spawning_ground_3_morning_cam_1_file_09.MP4
DOI: 10.18710/qnervt/axodn9
title: .master
DOI: 10.18710/qnervt/bhfn8r
title: realisation.1
DOI: 10.18710/qnervt/bmimat
title: realisation.1
DOI: 10.18710/qnervt/fnwseg
title: .master
DOI: 10.18710/qnervt/g1brma
title: realisation.1
DOI: 10.18710/qnervt/hklb4e
title: realisation.1
DOI: 10.18710/qnervt/kry214
title: .master
DOI: 10.18710/qnervt/menn2s
title: realisation.1
DOI: 10.18710/qnervt/pfy3u2
title: .master
DOI: 10.18710/qnervt/uuxmun
title: .master
DOI: 10.18710/qnervt/vrkuao
title: libtimedepth
DOI: 10.18710/qnervt/wta4ki
title: realisation
DOI: 10.18710/qnervt/ytbogd
title: .master
DOI: 10.18710/qnervt/ywlv4x
title: realisation.1
DOI: 10.18710/rx1amj/1wepod
title: 2016-09-21_spawning_ground_3_evening_cam_6_file_04.MP4
DOI: 10.18710/0c1sp5
title: Video recordings of spawning behavior of Arctic charr; date: 2016-09-23; spawning ground: 3; time: morning; camera no: 1

description: &lt;p&gt;This dataset contains video recordings of spawning behavior of Arctic charr (&lt;em&gt;Salvelinus alpinus&lt;/em&gt;) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 1 at spawning ground 3 in the morning of 23 September 2016.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "Documentation of the Spawning behavior of Arctic charr video collection", DataverseNO, https://doi.org/10.18710/VIQB0B&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;This dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "The Spawning behavior of Arctic charr video collection". DataverseNO. https://doi.org/10.18710/HTM6-F146.&lt;/b&gt;&lt;/p&gt;
description: morning
DOI: 10.18710/0c1sp5/b5fzmj
title: 2016-09-23_spawning_ground_3_morning_cam_1_file_06.MP4
DOI: 10.18710/5gek1j
title: Video recordings of spawning behavior of Arctic charr; date: 2016-09-21; spawning ground: 3; time: evening; camera no: 3

description: &lt;p&gt;This dataset contains video recordings of spawning behavior of Arctic charr (&lt;em&gt;Salvelinus alpinus&lt;/em&gt;) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 3 at spawning ground 3 in the evening of 21 September 2016.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "Documentation of the Spawning behavior of Arctic charr video collection", DataverseNO, https://doi.org/10.18710/VIQB0B&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;This dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "The Spawning behavior of Arctic charr video collection". DataverseNO. https://doi.org/10.18710/HTM6-F146.&lt;/b&gt;&lt;/p&gt;
description: evening
DOI: 10.18710/hdpb8d
title: Video recordings of spawning behavior of Arctic charr; date: 2016-09-21; spawning ground: 3; time: evening; camera no: 8

description: &lt;p&gt;This dataset contains video recordings of spawning behavior of Arctic charr (&lt;em&gt;Salvelinus alpinus&lt;/em&gt;) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 8 at spawning ground 3 in the evening of 21 September 2016.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "Documentation of the Spawning behavior of Arctic charr video collection", DataverseNO, https://doi.org/10.18710/VIQB0B&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;This dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "The Spawning behavior of Arctic charr video collection". DataverseNO. https://doi.org/10.18710/HTM6-F146.&lt;/b&gt;&lt;/p&gt;
description: evening
DOI: 10.18710/0c4pbp/dk2igv
title: 2016-09-23_spawning_ground_3_morning_cam_3_file_07.MP4
DOI: 10.18710/0c4pbp/t1wtu3
title: 2016-09-23_spawning_ground_3_morning_cam_3_file_16.MP4
DOI: 10.18710/3kuwbf
title: TGO Ramfjordmoen Ionosonde Data April 2021

description: &lt;p&gt;About this dataset: This dataset contains ionosonde data in SAO format and ionograms in PNG format, and covers data from April 01-30, 2021.&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: 10.18710/3kuwbf/ro1vvd
title: TGO_Ramfjordmoen_ionosonde_data_2021-04.PNG.zip
DOI: 10.18710/7jwazx/1s94oz
title: x_valid.npy

description: Validation set x
DOI: 10.18710/840z6y/k1yems
title: 2016-09-23_spawning_ground_3_morning_cam_8_file_07.MP4
DOI: 10.18710/840z6y/pgspml
title: 2016-09-23_spawning_ground_3_morning_cam_8_file_04.MP4
DOI: 10.18710/agiym1
title: Video recordings of spawning behavior of Arctic charr; date: 2016-09-22; spawning ground: 3; time: evening; camera no: 4

description: &lt;p&gt;This dataset contains video recordings of spawning behavior of Arctic charr (&lt;em&gt;Salvelinus alpinus&lt;/em&gt;) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 4 at spawning ground 3 in the evening of 22 September 2016.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "Documentation of the Spawning behavior of Arctic charr video collection", DataverseNO, https://doi.org/10.18710/VIQB0B&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;This dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "The Spawning behavior of Arctic charr video collection". DataverseNO. https://doi.org/10.18710/HTM6-F146.&lt;/b&gt;&lt;/p&gt;
description: evening
DOI: 10.18710/c02ir6/bpnadw
title: 2016-09-23_spawning_ground_3_evening_cam_2_file_09.MP4
DOI: 10.18710/c02ir6/ldskvw
title: 2016-09-23_spawning_ground_3_evening_cam_2_file_07.MP4
DOI: 10.18710/c5veic/2dkla6
title: 2016-09-17_spawning_ground_3_morning_cam_2_file_17.MP4
DOI: 10.18710/c5veic/ksqlbi
title: 2016-09-17_spawning_ground_3_morning_cam_2_file_18.MP4
DOI: 10.18710/ce8rqh/gd4pl3
title: Supplement_S1.jpg

description: High-resolution version of Supplement S1 in manuscript.
DOI: 10.18710/ce8rqh/lyq0c0
title: Figure_3c.jpg

description: High-resolution version of Figure 3c in manuscript.
DOI: 10.18710/dw4boy/3ythay
title: 2016-09-17_spawning_ground_3_morning_cam_1_file_01.MP4
DOI: 10.18710/dw4boy/arhpzq
title: 2016-09-17_spawning_ground_3_morning_cam_1_file_03.MP4
DOI: 10.18710/dw4boy/bwrxgo
title: 2016-09-17_spawning_ground_3_morning_cam_1_file_10.MP4
DOI: 10.18710/dw4boy/gwhzf5
title: 2016-09-17_spawning_ground_3_morning_cam_1_file_04.MP4
DOI: 10.18710/dxa0f3/9cejae
title: LOPC_2019-05-11_073441.dat
DOI: 10.18710/dxa0f3/fmo4c5
title: T10_Biovolume_ai0p4_downProfiles.txt
DOI: 10.18710/dxa0f3/mgq42p
title: T17_Abundance_ai0p4_downProfiles.txt
DOI: 10.18710/dxa0f3/penbep
title: T1_Abundance_ai0p4_downProfiles.txt
DOI: 10.18710/dxa0f3/xr6ewr
title: LOPC_2019-05-08_001838.dat
DOI: 10.18710/fcaa49/ojoodt
title: 2016-09-18_spawning_ground_3_evening_cam_3_file_04.MP4
DOI: 10.18710/gi7oku/txtkar
title: 2016-09-22_spawning_ground_3_evening_cam_8_file_05.MP4
DOI: 10.18710/kwqmyd/xph4a4
title: 2016-09-25_spawning_ground_3_morning_cam_3_file_09.MP4
DOI: 10.18710/lpmpx5
title: Video recordings of spawning behavior of Arctic charr; date: 2016-09-23; spawning ground: 3; time: morning; camera no: 2

description: &lt;p&gt;This dataset contains video recordings of spawning behavior of Arctic charr (&lt;em&gt;Salvelinus alpinus&lt;/em&gt;) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 2 at spawning ground 3 in the morning of 23 September 2016.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;A description of the data structure and format is gathered in the documentation dataset: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "Documentation of the Spawning behavior of Arctic charr video collection", DataverseNO, https://doi.org/10.18710/VIQB0B&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;This dataset is part of a larger collection: Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "The Spawning behavior of Arctic charr video collection". DataverseNO. https://doi.org/10.18710/HTM6-F146.&lt;/b&gt;&lt;/p&gt;
description: morning
DOI: 10.18710/ma1f2z/9edcqu
title: 2016-09-23_spawning_ground_3_evening_cam_1_file_07.MP4
DOI: 10.18710/ma1f2z/eirggb
title: 2016-09-23_spawning_ground_3_evening_cam_1_file_06.MP4
DOI: 10.18710/ma1f2z/znnsz6
title: 2016-09-23_spawning_ground_3_evening_cam_1_file_03.MP4
DOI: 10.18710/n9dh9w/v4f3gj
title: 2016-09-23_spawning_ground_3_afternoon_cam_3_file_03.MP4
DOI: 10.18710/nunhdf
title: Replication data for: Cystatin C proteoforms in chronic kidney disease

description: Supplementary dataset to 'Cystatin C proteoforms in chronic kidney disease'

This is a cross-sectional study on cystatin C proteoforms in patients with chronic kidney disease. The study was done at the University of Bergen and Haukeland University Hospital, Bergen, Norway. 
In total, 157 patients with various degrees of chronic kidney disease were included, and proteoforms of cystatin C were measured with MALDI-TOF. This dataset contains supplementary information.
description: &lt;p&gt; 
&lt;p&gt; ABSTRACT: 
&lt;p&gt; Cystatin C, a cysteine protease inhibitor, is used as a biomarker of renal function. It offers several advantages compared to creatinine, and formulas for the estimation of the glomerular filtration rate based on cystatin C have been developed. Recently, several proteoforms of cystatin C have been discovered, including an intact protein with a hydroxylated proline at the N-terminus, and N-terminal truncated forms. There is little knowledge about the biological significance of these proteoforms. 
&lt;p&gt; Methods: Cross-sectional study of patients with different stages of chronic renal disease (pre-dialysis n=53; hemodialysis n=51, renal transplant n=53). Measurement of cystatin C proteoforms by MALDI-TOF MS, assessment of medicine prescription using the first two levels of the Anatomical Therapeutic chemical system from patients’ records.
&lt;p&gt;Results: Patients receiving hemodialysis had the highest cystatin C concentrations, followed by pre-dialysis patients and patients with a renal transplant. In all groups, the most common proteoforms were native cystatin C and CysC 3Pro-OH while the truncated forms made up 28%. The distribution of the different proteoforms was largely independent of renal function and total cystatin C. However, the use of corticosteroids (ATC-L02) and immunosuppressants (ATC-H04) considerably impacted the distribution of proteoforms. 
&lt;p&gt;Conclusion: The different proteoforms of cystatin C increased proportionally with total cystatin C in patients with chronic kidney disease. Prescription of corticosteroids and immunosuppressants had a significant effect on the distribution of proteoforms. The biological significance of these proteoforms remains to be determined.
description: R studio
DOI: 10.18710/oyih83/vqjllx
title: 3DigitsTrainingset.zip

description: Images for the training set
DOI: 10.18710/pxc6vf/uwtoep
title: 2016-09-24_spawning_ground_3_evening_cam_9_file_03.mp4
DOI: 10.18710/qnervt/sncmmy
title: .master
DOI: 10.18710/qrdet2/gd8cc0
title: radaro3.py

description: Functions for plotting and handling radar and imaging. This code does currently not represent the final state since those files currently are unavailable.