cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24439286
title: Additional file 1 of Approaching autozygosity in a small pedigree of Gochu Asturcelta pigs

description: Additional file 1: Table S1. Pedigree used and raw individual estimates of homozygosity. Description of the pedigree of the Gochu Asturcelta pigs used and raw estimates of homozygosity parameters computed at the individual level. Table S2: BP-adjusted homozygosity estimates. Description of the BP-adjusted homozygosity values and the corresponding increase in homozygosity parameters computed at the individual level. Table S3: Regression of homozygosity against equivalent discrete generations. Regression of four homozygosity estimates and their corresponding individual increase in homozygosity (Δt) and paired increase in homozygosity (Δp) against equivalent discrete generations (t). Table S4: Jackknifed homozygosity values and their corresponding individual increases in homozygosity (Δt) and paired increases in homozygosity (Δp) values. Description of the jackknifed homozygosity values and the corresponding increase in homozygosity parameters computed at the individual level.
DOI: 10.6084/m9.figshare.23849424.v1
title: Additional file 3 of Interleukin-5 levels in relation to malaria severity: a systematic review

description: Additional file 3: Table S3. Quality of the included studies. PRISMA abstract checklist. PRISMA 2020 checklist.
DOI: 10.6084/m9.figshare.23902819.v1
title: Additional file 1 of Global effects of identity and aging on the human sperm methylome

description: Additional file 1. Supplementary Tables.
DOI: 10.57967/hf/1372
title: mri-sym2
DOI: 10.17632/pm2b3b7yz2.1
title: Data and statistical analysis to evaluate the effectiveness of LOs in teaching statistics to nursing

description: This dataset records the assessment of the effectiveness of learning objects in statistical education within nursing degree programs. It includes observations from 54 students with the following variables: - diagnostico_institucional: Assessment by the educational institution. - pre_test: Knowledge assessment prior to the educational intervention. - post_test: Knowledge assessment following the educational intervention. - edad: Age of the students. - campus: Campus of the institution where education is conducted. - sede: University site grouping several campuses together. - sexo: Gender of the student. - promedio_acumulado: Student's academic average up to the point of intervention. - rda_01 to rda_05: Score obtained in the corresponding evaluation of the learning objects. - rda_average: Average object learning outcome scores. - cat_1: Results of the primary evaluation number 1. - asistencia: Attendance record of the students at educational sessions. - RAA5_pre, RAA6_pre, RAA7_pre: Assessment results for each learning outcome before the intervention. - RAA5_post, RAA6_post, RAA7_post: Assessment results for each learning outcome after the intervention. The dataset includes a Quarto file, which performs various statistical analyses in R and returns a report in MS Word format. This data is crucial for future research in statistical teaching methodologies and is of particular interest to those in the field of nursing education. The tabular format is conducive to analysis with statistical software such as R.
DOI: 10.6084/m9.figshare.24209195.v1
title: Additional file 2 of Antifungal screening of selenium nanoparticles biosynthesized by microcystin-producing Desmonostoc alborizicum

description: Supplementary Material 2
DOI: 10.17632/nbnpcdgbdg.1
title: Features of the provision of inpatient medical care to patients with Alzheimer's disease during the SARS-COVID-19 pandemic

description: Background With Alzheimer's disease, the patient is not only unable to help himself, but he cannot even ask for such help. This is especially dangerous for a patient during the SARS-COVID-19 pandemic. Since the deadly complications of SARS-COVID-19 are observed in the age group in which Alzheimer's disease manifests itself. Method We observed 26 women aged 71-84 with Alzheimer's disease. All patients received treatment according to Alzheimer's disease treatment standards. Both amyloid-beta and tau were found in their cerebrospinal fluid. They also showed neurodegeneration in the areas classic for Alzheimer's disease on MRI of the brain. During a pandemic, sickness departments must wear masks and change them every 4 hours to prevent SARS-COVID-19 disease. In patients with Alzheimer's disease, the fulfillment of these requirements on their own is impracticable, since they have memory disorders for current events, changes in mood (apathy). Therefore, constant monitoring of medical personnel for compliance with these requirements is required. These patients in all inpatient care periods were given masks with a built-in 4-hour timer and a sensor that responded to opening contacts when the mask was removed. The end of 4 hours of wearing the mask and the removal of the mask as indicated by sound and light alarms installed in the mask. Result This greatly facilitated the monitoring of compliance with quarantine SARS-COVID-19 measures in patients with Alzheimer's disease. Also, the timely change of the mask was the prevention of hypoxia that develops as a result of wetting the mask with prolonged wearing. Conclusion Prevention of hypoxia with the prolonged wearing of a wet mask alleviates the symptoms of Alzheimer's disease, allows the patient to convey their thoughts and feelings, and significantly improves the quality of life of patients.
DOI: 10.17632/4hcmcwzxfh.1
title: Use Acetazolamide in the Complex Therapy of Alzheimer’s Disease

description: Background Impaired glymphatic clearance is one of the causes of Alzheimer’s disease. Acetazolamide is a drug that affects the normalization of glymphatic clearance. Methods We followed four women aged 65-70 years with a diagnosis of Alzheimer’s disease in 2019-2021. They were treated in the unit according to Alzheimer’s disease treatment standards. During periodic examination by an ophthalmologist, they were diagnosed with first-stage glaucoma (initial) - a blind spot interfering with normal peripheral vision and a deepening of the optic disc in the central zone were identified. For a glaucoma treatment, they were prescribed Acetazolamide 125 mg once a day in the morning for 7 days with weekly monitoring of intraocular pressure. They also received Asparkam, 1 tablet, 3 times a day during Acetazolamide administration to prevent a deficiency of potassium ions in the body. On days 12-14 after normalization intraocular pressure, Acetazolamide administration was discontinued. To monitor the dynamics of cognitive impairment, patients on the unit underwent Trail Making Test Parts A & B paper-pencil versions every month. Results Before glaucoma treatment, the patients' Trail Making Test Parts A speeds were 84, 87, 90, and 92 seconds. The speed of Part B was 270, 300, 293, and 305 seconds. After two weeks of glaucoma treatment, patients again completed the Trail Making Test Parts A & B paper-pencil versions. The patients' speeds for Part A were 60, 68, 63, and 70 seconds. The speeds in Part B were 180, 190, 217, and 194 seconds. Conclusion Administration of Acetazolamide has a positive effect on patients with cognitive deficits and can be successfully used as part of the complex therapy of Alzheimer’s disease. Volume18, IssueS9 Supplement: Dementia Care Practice (Descriptive) December 2022 e059982 Related Information Recommended Subjective cognitive decline and rates of incident Alzheimer's disease and non–Alzheimer's disease dementia Rosalinde E.R. Slot, Sietske A.M. Sikkes, Johannes Berkhof, Henry Brodaty, Rachel Buckley, Enrica Cavedo, Efthimios Dardiotis, Francoise Guillo-Benarous, Harald Hampel, Nicole A. Kochan, Simone Lista, Tobias Luck, Paul Maruff, José Luis Molinuevo, Johannes Kornhuber, Barry Reisberg, Steffi G. Riedel-Heller, Shannon L. Risacher, Susanne Roehr, Perminder S. Sachdev, Nikolaos Scarmeas, Philip Scheltens, Melanie B. Shulman, Andrew J. Saykin, Sander C.J. Verfaillie, Pieter Jelle Visser, Stephanie J.B. Vos, Michael Wagner, Steffen Wolfsgruber, Frank Jessen, the Alzheimer's Disease Neuroimaging Initiative, the DESCRIPA working group, the INSIGHT-preAD study group, SCD-I working group, Wiesje M. van der Flier Alzheimer's & Dementia
DOI: 10.6084/m9.figshare.24159508
title: Additional file 3 of Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

description: Additional file 3: Supplemental Table 5: Summary of the biological and systematic effects, including the variance explained by each effect, with cells coloured by effect size. Supplemental Table 6: Detailed parameters and results of F-tests for biological and systematic effects, along with animal and residual variance estimates.
DOI: 10.6084/m9.figshare.24159502
title: Additional file 1 of Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

description: Additional file 1: Supplemental Table 1. Information for each sample including: SampleID, AnimalID, Flock, Year of Birth (YOB), Sample Date, Diet, Age, Time Off Feed, Feeding, Group, Cohort, Batch, Shelf, Library and Well. Supplemental Table 2. Summary of Supplemental Table 1 based on Flock, Sampling Year and Cohort. Supplemental Table 3. Summary of Supplemental Table 1 based on Animal and Group.
DOI: 10.6084/m9.figshare.24159505
title: Additional file 2 of Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

description: Additional file 2. Supplemental Table 4. Sequencing statistics for all samples split by Group.
DOI: 10.6084/m9.figshare.24159508.v1
title: Additional file 3 of Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

description: Additional file 3: Supplemental Table 5: Summary of the biological and systematic effects, including the variance explained by each effect, with cells coloured by effect size. Supplemental Table 6: Detailed parameters and results of F-tests for biological and systematic effects, along with animal and residual variance estimates.
DOI: 10.6084/m9.figshare.24159517.v1
title: Additional file 6 of Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

description: Additional file 6. Supplemental Table 9. The genomic relationship matrix for the New Zealand samples.
DOI: 10.6084/m9.figshare.24159517
title: Additional file 6 of Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

description: Additional file 6. Supplemental Table 9. The genomic relationship matrix for the New Zealand samples.
DOI: 10.6084/m9.figshare.24159511.v1
title: Additional file 4 of Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

description: Additional file 4: Supplemental Table 7: Heritability and repeatability estimates and standard errors for the reference-based approach. Supplemental Table 8: Heritability and repeatability estimates and standard errors for genera from the reference-free taxonomic assignments.
DOI: 10.17632/rv69rxbv64.1
title: Stress Tests and Model Monoculture

description: This replication package provides the code to replicate Figures 2 and 3 in our paper "Stress Tests and Model Monoculture", using MATLAB R2022a.
DOI: 10.17632/t5pjm79jg6.1
title: Financial Data

description: Financial data of Chinese companies from 2006 to 2021
DOI: 10.17632/n5z9d9h8gk.1
title: jrfapp_datasets

description: CHBR_tele_waveforms.zip: The teleseismic waveforms recorded at the CHBR station in SE of the Iranian plateau from 2016 to 2019. This station belongs to the National Center of Broadband Seismic Network of Iran (http://www.iiees.ac.ir/en/iranian-national-broadband-seismic-network/) installed by the International Institute of Earthquake Engineering and seismology. HYB_P.zip: The teleseismic waveforms at the HYB station in India. This station belongs to the GEOSCOPE network installed by Institut de physique du globe de Paris (IPGP), Observatoire des Sciences de la Terre de Strasbourg (EOST), partners (doi:10.18715/GEOSCOPE.G). CAD_P.zip: The teleseismic waveforms at the CAD station in Tibet. This station belongs to the China National Seismic Network operated by the Institute of Geophysics China Earthquake Administration (IGPCEA), China (10.7914/SN/CB).
DOI: 10.25678/0009d5
title: Data for: Ecological disturbance reduces genomic diversity across an Alpine whitefish adaptive radiation

description: Genomic diversity is associated with the adaptive potential of a population and thereby impacts the extinction risk of a species during environmental change. However, empirical data on genomic diversity of populations before environmental perturbations are rare and hence our understanding on the impact of perturbation on diversity are often limited. We here assess genomic diversity utilising whole-genome resequencing data from all four species of the Lake Constance Alpine whitefish radiation. Our data covers a period of strong but transient anthropogenic environmental change and permits to track changes in genomic diversity in all species over time. Genomic diversity became strongly reduced during the period of anthropogenic disturbance and has not recovered yet. The decrease in genomic diversity varies between 18-30%, depending on the species. Interspecific allele frequency differences of SNPs located in potentially ecologically relevant genes were homogenized over time. This suggests that in addition to the reduction of genome wide genetic variation, differentiation that evolved in the process of adaptation to alternative ecologies between species might have been lost during ecological disturbance. The erosion of substantial amounts of genomic variation within just a few generations in combination with the loss of potentially adaptive genomic differentiation, both of which had evolved over thousands of years, demonstrates the sensitivity of biodiversity in evolutionary young adaptive radiations towards environmental disturbance. Natural history collections, such as the one used for this study, are instrumental for the assessment of genomic consequences of anthropogenic environmental change. Historical samples enable us to document biodiversity loss against the shifting baseline syndrome and advance our understanding of the needs for efficient biodiversity conservation on a global scale.
DOI: 10.17632/27nbpmv8rd.1
title: Sorghum germplasm GBS dataset 2

description: Illumina dataset for 96 sorghum germplasm GBS dataset (76 - 96).
DOI: 10.22008/fk2/qkvxc9/gupvez
title: SICEv2.3.2_Svalbard_1000m_2017_04_01.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_01.nc, date: 2017-04-01
DOI: 10.22008/fk2/qkvxc9/0buzgw
title: SICEv2.3.2_Svalbard_1000m_2017_04_02.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_02.nc, date: 2017-04-02
DOI: 10.22008/fk2/qkvxc9/9xu0uy
title: SICEv2.3.2_Svalbard_1000m_2017_04_03.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_03.nc, date: 2017-04-03
DOI: 10.22008/fk2/qkvxc9/kovzrv
title: SICEv2.3.2_Svalbard_1000m_2017_04_04.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_04.nc, date: 2017-04-04
DOI: 10.22008/fk2/qkvxc9/gmg5s0
title: SICEv2.3.2_Svalbard_1000m_2017_04_05.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_05.nc, date: 2017-04-05
DOI: 10.22008/fk2/qkvxc9/ykwjfp
title: SICEv2.3.2_Svalbard_1000m_2017_04_06.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_06.nc, date: 2017-04-06
DOI: 10.22008/fk2/qkvxc9/cxlnvh
title: SICEv2.3.2_Svalbard_1000m_2017_04_07.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_07.nc, date: 2017-04-07
DOI: 10.22008/fk2/qkvxc9/7f8ksf
title: SICEv2.3.2_Svalbard_1000m_2017_04_08.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_08.nc, date: 2017-04-08
DOI: 10.22008/fk2/qkvxc9/tstqae
title: SICEv2.3.2_Svalbard_1000m_2017_04_09.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_09.nc, date: 2017-04-09
DOI: 10.22008/fk2/qkvxc9/hvvfri
title: SICEv2.3.2_Svalbard_1000m_2017_04_10.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_10.nc, date: 2017-04-10
DOI: 10.22008/fk2/qkvxc9/cwkoea
title: SICEv2.3.2_Svalbard_1000m_2017_04_11.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_11.nc, date: 2017-04-11
DOI: 10.22008/fk2/qkvxc9/u2pigk
title: SICEv2.3.2_Svalbard_1000m_2017_04_12.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_12.nc, date: 2017-04-12
DOI: 10.22008/fk2/qkvxc9/2kdqsk
title: SICEv2.3.2_Svalbard_1000m_2017_04_13.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_13.nc, date: 2017-04-13
DOI: 10.22008/fk2/qkvxc9/w9ijqz
title: SICEv2.3.2_Svalbard_1000m_2017_04_14.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_14.nc, date: 2017-04-14
DOI: 10.22008/fk2/qkvxc9/czl1g0
title: SICEv2.3.2_Svalbard_1000m_2017_04_15.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_15.nc, date: 2017-04-15
DOI: 10.22008/fk2/qkvxc9/6py7h5
title: SICEv2.3.2_Svalbard_1000m_2017_04_16.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_16.nc, date: 2017-04-16
DOI: 10.22008/fk2/qkvxc9/trozpw
title: SICEv2.3.2_Svalbard_1000m_2017_04_17.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_17.nc, date: 2017-04-17
DOI: 10.22008/fk2/qkvxc9/stxhjl
title: SICEv2.3.2_Svalbard_1000m_2017_04_18.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_18.nc, date: 2017-04-18
DOI: 10.22008/fk2/qkvxc9/fph6qe
title: SICEv2.3.2_Svalbard_1000m_2017_04_19.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_19.nc, date: 2017-04-19
DOI: 10.22008/fk2/qkvxc9/lldidh
title: SICEv2.3.2_Svalbard_1000m_2017_04_21.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_21.nc, date: 2017-04-21
DOI: 10.22008/fk2/qkvxc9/wus4w5
title: SICEv2.3.2_Svalbard_1000m_2017_04_20.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_20.nc, date: 2017-04-20
DOI: 10.22008/fk2/qkvxc9/kw78o6
title: SICEv2.3.2_Svalbard_1000m_2017_04_22.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_22.nc, date: 2017-04-22
DOI: 10.22008/fk2/qkvxc9/ofbrs4
title: SICEv2.3.2_Svalbard_1000m_2017_04_23.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_23.nc, date: 2017-04-23
DOI: 10.22008/fk2/qkvxc9/pcboqu
title: SICEv2.3.2_Svalbard_1000m_2017_04_24.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_24.nc, date: 2017-04-24
DOI: 10.22008/fk2/qkvxc9/isfjgx
title: SICEv2.3.2_Svalbard_1000m_2017_04_25.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_25.nc, date: 2017-04-25
DOI: 10.22008/fk2/qkvxc9/k97qch
title: SICEv2.3.2_Svalbard_1000m_2017_04_26.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_26.nc, date: 2017-04-26
DOI: 10.22008/fk2/qkvxc9/t08vuq
title: SICEv2.3.2_Svalbard_1000m_2017_04_27.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_27.nc, date: 2017-04-27
DOI: 10.22008/fk2/qkvxc9/zmfeoz
title: SICEv2.3.2_Svalbard_1000m_2017_04_28.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_28.nc, date: 2017-04-28
DOI: 10.22008/fk2/qkvxc9/eiiiq3
title: SICEv2.3.2_Svalbard_1000m_2017_04_29.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_29.nc, date: 2017-04-29
DOI: 10.22008/fk2/qkvxc9/vhbsqz
title: SICEv2.3.2_Svalbard_1000m_2017_04_30.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_04_30.nc, date: 2017-04-30
DOI: 10.22008/fk2/qkvxc9/3fmpyz
title: SICEv2.3.2_Svalbard_1000m_2017_05_01.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_01.nc, date: 2017-05-01
DOI: 10.22008/fk2/qkvxc9/ciaavh
title: SICEv2.3.2_Svalbard_1000m_2017_05_02.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_02.nc, date: 2017-05-02
DOI: 10.22008/fk2/qkvxc9/uzzesr
title: SICEv2.3.2_Svalbard_1000m_2017_05_03.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_03.nc, date: 2017-05-03
DOI: 10.22008/fk2/qkvxc9/nexmy7
title: SICEv2.3.2_Svalbard_1000m_2017_05_04.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_04.nc, date: 2017-05-04
DOI: 10.22008/fk2/qkvxc9/tdgybc
title: SICEv2.3.2_Svalbard_1000m_2017_05_05.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_05.nc, date: 2017-05-05
DOI: 10.22008/fk2/qkvxc9/olatpo
title: SICEv2.3.2_Svalbard_1000m_2017_05_06.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_06.nc, date: 2017-05-06
DOI: 10.22008/fk2/qkvxc9/chyifh
title: SICEv2.3.2_Svalbard_1000m_2017_05_07.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_07.nc, date: 2017-05-07
DOI: 10.22008/fk2/kule1q/w2be27
title: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_01.nc

description: SICEv2.3.2 output: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_01.nc, date: 2017-04-01
DOI: 10.22008/fk2/qkvxc9/fkhlvm
title: SICEv2.3.2_Svalbard_1000m_2017_05_08.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_08.nc, date: 2017-05-08
DOI: 10.22008/fk2/kule1q/xhncml
title: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_02.nc

description: SICEv2.3.2 output: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_02.nc, date: 2017-04-02
DOI: 10.22008/fk2/qkvxc9/hbzd3o
title: SICEv2.3.2_Svalbard_1000m_2017_05_10.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_10.nc, date: 2017-05-10
DOI: 10.22008/fk2/qkvxc9/zegc9g
title: SICEv2.3.2_Svalbard_1000m_2017_05_09.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_09.nc, date: 2017-05-09
DOI: 10.22008/fk2/kule1q/2rm1xc
title: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_03.nc

description: SICEv2.3.2 output: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_03.nc, date: 2017-04-03
DOI: 10.22008/fk2/qkvxc9/j93kea
title: SICEv2.3.2_Svalbard_1000m_2017_05_11.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_11.nc, date: 2017-05-11
DOI: 10.22008/fk2/kule1q/2bfoq2
title: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_05.nc

description: SICEv2.3.2 output: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_05.nc, date: 2017-04-05
DOI: 10.22008/fk2/kule1q/vjrm61
title: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_04.nc

description: SICEv2.3.2 output: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_04.nc, date: 2017-04-04
DOI: 10.22008/fk2/qkvxc9/z0mqae
title: SICEv2.3.2_Svalbard_1000m_2017_05_12.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_12.nc, date: 2017-05-12
DOI: 10.22008/fk2/kule1q/ttplzb
title: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_06.nc

description: SICEv2.3.2 output: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_06.nc, date: 2017-04-06
DOI: 10.22008/fk2/qkvxc9/jqv0gf
title: SICEv2.3.2_Svalbard_1000m_2017_05_13.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_13.nc, date: 2017-05-13
DOI: 10.22008/fk2/kule1q/q7m3qo
title: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_07.nc

description: SICEv2.3.2 output: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_07.nc, date: 2017-04-07
DOI: 10.22008/fk2/qkvxc9/k4n10x
title: SICEv2.3.2_Svalbard_1000m_2017_05_14.nc

description: SICEv2.3.2 output: SICEv2.3.2_Svalbard_1000m_2017_05_14.nc, date: 2017-05-14
DOI: 10.22008/fk2/kule1q/4hnsom
title: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_08.nc

description: SICEv2.3.2 output: SICEv2.3.2_SouthernArcticCanada_1000m_2017_04_08.nc, date: 2017-04-08