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Figure 9 in French research on fisheries in the Northwest Atlantic, from its origins to the present
Figure 9. – Recording of a thermal profile using an expendable bathythermograph probe temperature recorder aboard the R/V Cryos in 1985 (Photo A. Forest).
Figure 6. – The R in French research on fisheries in the Northwest Atlantic, from its origins to the present
Figure 6. – The R/V Président Théodore Tissier of the Office Scien-Scien- tifique et Technique des Pêches Maritimes carried out surveys in the North West Atlantic mainly during the 1950s (source: www.lepetit-manchot.fr).
Figure 7 in French research on fisheries in the Northwest Atlantic, from its origins to the present
Figure 7. – The Saint-Pierre and Miquelon research center and the R/V Cryos in the 1970s (Photo A. Forest).
Figure 4 in French research on fisheries in the Northwest Atlantic, from its origins to the present
Figure 4. – Map of areas claimed by Canada and France as their Economic Exclusive Zones and the Court of Arbitration decision (from Parsons, 1993).
Figure 1 in Results of the research expedition Biaçores 1971. Fishes and list of stations
Figure 1. – Location of the stations of the Biaçores 1971 cruise (stars). Some stars signal several stations (see Appendix I for details).
Figure 3. Chromatogram from the sample fairs MAC 02 and ARA 0 in Detection of enteropathogens and research of pesticide residues in Lactuca sativa from traditional and agroecological fairs
Figure 3. Chromatogram from the sample fairs MAC 02 and ARA 0, with the peaks of Diphenoconazole compared with the pattern.
Рис. 1. 1 — Eriogyna koreanis (Brechlin, 2009) (Saturniidae), ♂, Казакевичево, из коΛΛекции ЗооΛогического иссΛеΑоватеΛьского музея АΛексанΑра Кёнига (Германия). Фото В. В. ЗоΛотухина; 2 — Nola confusalis; 3 — Negritothripa hampsoni; 4 — Autographa urupina; 5 — Athetis lapidea; 6–7 — Euplexia koreaeplexia; 8 — Nonagria puengeleri; 9 — Lacanobia oleracea; 10 —Actebia squalida Fig. 1. 1 — Eriogyna koreanis (Brechlin, 2009) (Saturniidae), ♂, Kazakevichevo (Kassakewitschevo), collection of the Zoological Research Museum Alexander Koenig (Germany). Photo by V. V. Zolotuhin; 2 — Nola confusalis; 3 — Negritothripa hampsoni; 4 — Autographa urupina; 5 — Athetis lapidea; 6–7 — Euplexia koreaeplexia; 8 — Nonagria puengeleri; 9 — Lacanobia oleracea; 10 —Actebia squalida in Additions To The Macromoth Fauna (Insecta, Lepidoptera, Macroheterocera) Of Bolshekhekhtsyrsky Nature Reserve (Khabarovsky Krai)
Рис. 1. 1 — Eriogyna koreanis (Brechlin, 2009) (Saturniidae), ♂, Казакевичево, из коΛΛекции ЗооΛогического иссΛеΑоватеΛьского музея АΛексанΑра Кёнига (Германия). Фото В. В. ЗоΛотухина; 2 — Nola confusalis; 3 — Negritothripa hampsoni; 4 — Autographa urupina; 5 — Athetis lapidea; 6–7 — Euplexia koreaeplexia; 8 — Nonagria puengeleri; 9 — Lacanobia oleracea; 10 —Actebia squalida Fig. 1. 1 — Eriogyna koreanis (Brechlin, 2009) (Saturniidae), ♂, Kazakevichevo (Kassakewitschevo), collection of the Zoological Research Museum Alexander Koenig (Germany). Photo by V. V. Zolotuhin; 2 — Nola confusalis; 3 — Negritothripa hampsoni; 4 — Autographa urupina; 5 — Athetis lapidea; 6–7 — Euplexia koreaeplexia; 8 — Nonagria puengeleri; 9 — Lacanobia oleracea; 10 —Actebia squalida
Dataset for acceleration measurements at the research bridge openLAB in Bautzen, Germany - Change of dynamic behavior in the concrete hardening process
<p>This data set was collected during the construction phase of the openLAB in Bautzen, Germany during the period from 22.01.2024 - 30.04.2024. It includes acceleration measurements and temperature measurements that record the dynamic behavior of the bridge over a period of 49 days (from 22.01.2024 to 11.03.2024; the remaining data cannot be uploaded due to the Zenodo upload restriction, but can be released on request). The detailed documentation of the data set can be found in the file "Bartels, Dunkel, Marx_2024_Documentation.pdf". The documentation describes the structure, the applied monitoring system and the collected data in detail.</p>
BOLD5000 Additional ROIs and RDMs for neural network research
<p>Artificial neural networks (ANNs) are sensitive to perturbations and adversarial attacks. One hypothesized solution to adversarial robustness is to align manifolds in the embedded space of neural networks with biologically grounded manifolds. Recent state-of-the-art works that emphasize learning robust neural representations, rather than optimizing for a specific target task like classification, support the idea that researchers should investigate this hypothesis. While works have shown that fine-tuning ANNs to coincide with biological vision does increase robustness to both perturbations and adversarial attacks, these works have relied on proprietary datasets- the lack of publicly available biological benchmarks make it difficult to evaluate the efficacy of these claims. Here, we deliver a curated dataset consisting of biological representations of images taken from two commonly used computer vision datasets, ImageNet and COCO, that can be easily integrated into model training and evaluation. Specifically, we take a large functional magnetic resonance imaging (fMRI) dataset (BOLD5000), preprocess it into representational dissimilarity matrices (RDMs), and establish an infrastructure that anyone can use to train models with biologically grounded representations. Using this infrastructure, we investigate the representations of several popular neural networks and find that as networks have been optimized for tasks, their correspondence with biological fidelity has decreased. Additionally, we use a previously unexplored graph-based technique, Fiedler partitioning, to showcase the viability of the biological data, and the potential to extend these analyses by extending RDMs into Laplacian matrices. Overall, our findings demonstrate the potential of utilizing our new biological benchmark to effectively enhance the robustness of models.</p>
Карта-схема района исследований. 1А, 1Б, 1В – станции раЗреЗа 1; 2А, 2Б, 2В – станции раЗреЗа 2; 3А, 3Б, 3В – станции раЗреЗа 3. A schematic map of the research area. 1A, 1Б, 1В – stations of line 1; 2A, 2Б, 2В – stations of line 2; 3A, 3Б, 3В – stations of line 3. in Pelagic larvae of bivalve mollusks in meroplankton in the coastal waters of Aniva Bay (southern Sakhalin, Sea of Okhotsk)
Карта-схема района исследований. 1А, 1Б, 1В – станции раЗреЗа 1; 2А, 2Б, 2В – станции раЗреЗа 2; 3А, 3Б, 3В – станции раЗреЗа 3. A schematic map of the research area. 1A, 1Б, 1В – stations of line 1; 2A, 2Б, 2В – stations of line 2; 3A, 3Б, 3В – stations of line 3.
Data from the paper "The landscape of biomedical research"
<p>Data from the paper "<a href="https://www.cell.com/patterns/fulltext/S2666-3899(24)00076-X">The landscape of biomedical research</a>".</p> <p>The paper used the PubMed 2020 baseline (download date: 26.01.2021, not available anymore) supplemented with additional files from the 2021 baseline (download date: 27.04.2022, not available anymore), both originally obtained from <a href="https://www.nlm.nih.gov/databases/download/pubmed_medline.html">https://www.nlm.nih.gov/databases/download/pubmed_medline.html</a>, courtesy of the U.S. National Library of Medicine. This data can be found in v2 of this repository (<a href="../records/7849020">https://zenodo.org/records/7849020</a>).</p> <p>In the latest version of this repository we provide the PubMed 2024 baseline (download date: 06.02.2024) including all papers until the end of 2023, which is <strong>not</strong> the main data we analyzed in the paper but an updated version including newer articles. The paper contains two supplementary figures (S9 and S10) with the updated embedding.</p> <p>The latest version provided here includes the following files:</p> <p>pubmed_landscape_data_2024_v2.zip, which includes:</p> <p>- from the PubMed database: article title, journal, PMID, and publication year.</p> <p>- produced by us: t-SNE embedding X and Y coordinates, label, color, whether the paper is retracted or not (combining PubMed and Retraction Watch information), affiliation country ( from the first affiliation of the first author), and inferred gender (of both first and last author).</p> <p>(Note: pubmed_landscape_data_2024_v2.zip is identical to pubmed_landscape_data_2024.zip from v3 of this repository, but includes inferred genders additionally.)</p> <p> </p> <p>pubmed_landscape_abstracts_2024.zip, which includes:</p> <p>- from the PubMed database: PMID, and paper abstracts.</p> <p> </p> <p>PubMedBERT_embeddings_float16_2024.npy, which includes:</p> <p>- produced by us: PubMedBERT embeddings of the paper abstracts (numpy.ndarray of shape 23,389,083x768).</p>
Research data related to the article "Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low-lying Coastal Groundwater Systems"
<p><strong>Research Data related to the article "Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low-lying Coastal Groundwater Systems" by Seibert et al. (2024) published in <em>Earth's Future</em></strong></p> <p>Dear reader,</p> <p>reasearch data are provided for the research article "Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low-lying Coastal Groundwater Systems" by Seibert et al. (2024) published in <em>Earth's Future</em>. The authors hope that the research data allows for a better understanding of the modeling workflow. Questions regarding the modeling approach etc. can be directed to the authors, see contact details below.</p> <p>The research data covers the following files:</p> <ul> <li>iMOD-Python (Visser and Bootsma, 2019) scripts to create the iMOD-WQ (Verkaik et al., 2021) input files for the n=566 model variants. Subfolders for each model variant and corresponding files are stored in the subfolder 'model_variants'. An overview regarding the set-up of the model variants is presented in the .xlsx spreadsheet 'model_variants_overview.xlsx' in the folder 'model_variants'.</li> <li>Base data files, used as input files to iMOD-WQ (Verkaik et al., 2021), stored in the subfolder 'imod_input'. However, in most cases no consent for re-distribution of these data sets exists, and they cannot be made freely available through this publication. Please, consider the corresponding meta-data files and/or get in touch with one of the authors for further information.</li> <li>Post-processed model output data, which was further used for model evaluation, stored in the subfolder 'model_output'.</li> <li>Figure files and the corresponding .py scripts, stored in the subfolder 'figures'.</li> </ul> <p>Meta-data files are provided with data files in the different subfolders for clarification.</p> <p>iMOD-WQ (Verkaik et al., 2021) input and .run-files were executed on the University Oldenburg High-Performance Cluster 'Rosa', funded by DFG through its Major Research Instrumentation Program, INST 184/225-1 FUGG, and the Ministry of Science and Culture (MWK) of the Lower Saxony State.</p> <p>Further information on the iMOD suite can be found here: https://deltares.github.io/iMOD-Documentation/</p> <p>The DFG is thanked for SALTSA project funding (DFG project number MA 3274/9-1) within the Priority Programme ‘Regional Sea Level Change and Society (SeaLevel)’. Research related to this article further benefited from funding of the projects WAKOS (BMBF; support code 01LR2003E) and the DFG research unit FOR 5094: The dynamic deep subsurface of high-energy beaches (DynaDeep).</p> <p>Literature:</p> <p>Verkaik, J., Hughes, J. D., van Walsum, P. E. V., Oude Essink, G. H. P., Lin, H. X., & Bierkens, M. F. P. (2021). Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument. Environmental Modelling & Software, 143, p.105092.</p> <p>Visser, M., & Bootsma, H. (2019). iMOD-Python: Work with iMOD MODFLOW models in Python. Retrieved from https://imod.xyz/</p> <p>Seibert, S. L., Greskowiak, J., Oude Essink, G. H. P., & Massmann, G. (2024). Understanding climate change and anthropogenic impacts on the salinization of low‐lying coastal groundwater systems. Earth's Future, 12, e2024EF004737. https://doi.org/10.1029/2024EF004737<br><br><strong>Contact one of the authors if you have further questions</strong>: Stephan L. Seibert (stephan.seibert@uol.de), Janek Greskowiak (janek.greskowiak@uol.de), Gualbert H.P. Oude Essink (Gualbert.OudeEssink@deltares.nl) or Gudrun Massmann (gudrun.massmann@uol.de)</p>
Fig. 2 in Bats of Sicily: historical evidence, current knowledge, research biases and trends
Fig. 2 - Documents in the primary and secondary datasets and the cumulative number of documents issued between 1810 and 2022. / Documenti nei dataset primario e secondario e numero cumulativo di documenti prodotti tra il 1810 e il 2022.
Fig. 5 in Bats of Sicily: historical evidence, current knowledge, research biases and trends
Fig. 5 - Distribution of the primary dataset, secondary dataset, and total documents according to research areas and used methods. / Distribuzione del dataset primario, del dataset secondario e del totale dei documenti in base alle aree di ricerca e ai metodi utilizzati.
Fig. 1 in Bats of Sicily: historical evidence, current knowledge, research biases and trends
Fig. 1 - Flow diagram showing the selection steps of eligible documents obtained from primary and secondary datasets. / Diagramma di flusso che mostra le fasi di selezione dei documenti eligibili ottenuti dai dataset primario e secondario.
Fig. 4 in Bats of Sicily: historical evidence, current knowledge, research biases and trends
Fig. 4 - (A) Bar plot showing the distribution of studies across different habitats (caves, forest, urban area, riparian areas). (B) Species conservation status across Sicilian bat families classified according to the IUCN categories: Least Concern (LC), Vulnerable (VU), Near Threatened (NT), and Data Deficient (DD). / (A) Grafico a barre che mostra la distribuzione degli studi nei diversi habitat (grotte, foreste, aree urbane, aree ripariali). (B) Stato di conservazione delle specie delle famiglie di pipistrelli siciliani classificate secondo le categorie IUCN: Minima preoccupazione (LC), Vulnerabile (VU), Quasi minacciata (NT) e Carenza di dati (DD).
Fig. 3 in Bats of Sicily: historical evidence, current knowledge, research biases and trends
Fig. 3 - Variation of Bat Research Efficiency scores (BRE) in the nine Sicilian provinces. The colour gradient (darker to lighter) indicates a higher to lower BRE. / Variazione dei punteggi di efficienza della ricerca sui pipistrelli (BRE) nelle nove province siciliane. Il gradiente di colore (da più scuro a più chiaro) indica un BRE da più alto a più basso.
Рис. 2. ПяΑеницы (Geometridae) Ботчинского заповеΑника: A — Ourapteryx maculicaudaria, самка; B — Charissa remmi, самка; C — Charissa creperaria, самка; D — Macaria wauaria, самец. ШкаΛа поΑ бабочками — 10 мм. Figs 2. Geometrid moths (Geometridae) of the Botchinsky Reserve: A — Ourapteryx maculicaudaria, female; B — Charissa remmi, female; C — Charissa creperaria, female; D — Macaria wauaria, male. The scale under the moths — 10 mm in Fauna of the geometrid moths (Lepidoptera, Geometridae) of the eastern Sikhote-Alin in the area of the Botchinsky State Nature Reserve I: History of research and subfamilies Archiearinae, Ennominae, Desmobathrinae, and Geometrinae
Рис. 2. ПяΑеницы (Geometridae) Ботчинского заповеΑника: A — Ourapteryx maculicaudaria, самка; B — Charissa remmi, самка; C — Charissa creperaria, самка; D — Macaria wauaria, самец. ШкаΛа поΑ бабочками — 10 мм. Figs 2. Geometrid moths (Geometridae) of the Botchinsky Reserve: A — Ourapteryx maculicaudaria, female; B — Charissa remmi, female; C — Charissa creperaria, female; D — Macaria wauaria, male. The scale under the moths — 10 mm
Рис. 1. Пункты сбора материаΛов в районе Ботчинского заповеΑника. Пункты сбора обозначены красными кружками, наибоΛее крупный из которых соответствует основному месту сбора — корΑону «ТепΛый КΛюч». Номера пунктов сбора соответствуют номерам в тексте при их описании. БΛизко распоΛоженные пункты сборов показаны оΑним симвоΛом Fig. 1. Points of collection of materials in the area of the Botchinsky Nature Reserve. Collection points are marked with red circles, the largest of which corresponds to the main collection point — the cordon "Teply Klyuch". The collection point numbers correspond to the numbers in the text when they are described. Closely located collection points are shown with one symbol in Fauna of the geometrid moths (Lepidoptera, Geometridae) of the eastern Sikhote-Alin in the area of the Botchinsky State Nature Reserve I: History of research and subfamilies Archiearinae, Ennominae, Desmobathrinae, and Geometrinae
Рис. 1. Пункты сбора материаΛов в районе Ботчинского заповеΑника. Пункты сбора обозначены красными кружками, наибоΛее крупный из которых соответствует основному месту сбора — корΑону «ТепΛый КΛюч». Номера пунктов сбора соответствуют номерам в тексте при их описании. БΛизко распоΛоженные пункты сборов показаны оΑним симвоΛом Fig. 1. Points of collection of materials in the area of the Botchinsky Nature Reserve. Collection points are marked with red circles, the largest of which corresponds to the main collection point — the cordon "Teply Klyuch". The collection point numbers correspond to the numbers in the text when they are described. Closely located collection points are shown with one symbol
Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019) in Variability of the gene cyt b in the Korean field mouse Apodemus peninsulae Thomas, 1906 - a reservoir host of AMRV in the Khasansky District of Primorsky Krai
Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019)
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.