cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/f7h70drh
title: Benthic infaunal communities of Baltimore and Norfolk canyons

description: Submarine canyons are morphologically complex systems, acting as major conduits of organic matter along continental shelves, promoting gradients in food resources, habitat heterogeneity, and areas of sediment resuspension and deposition. Often environmental conditions within canyons can be highly distinct, particularly in different parts of the canyon and in contrast to adjacent slopes. Here we examine how biogeochemical drivers shape the differences between canyon and slope infaunal communities in Baltimore and Norfolk Canyons in the U.S. Mid-Atlantic Region. Specific comparisons included macrofaunal communities in Norfolk canyons and adjacent slope, hard substrate associated macrofaunal communities in Norfolk Canyon, macrofaunal communities associated with chemosynthetic habitats (e.g., microbial mats and mussel beds) near Baltimore and Norfolk Canyon, and meiofaunal communities in Baltimore Canyon and the adjacent slope. Replicate sediment cores were collected in each habitat and assessed for infaunal abundance, diversity, and community composition in relation to sediment biogeochemical parameters, including grain size, organic content, stable isotopes, and chlorophyll a. Canyon macrofaunal and meiofaunal communities exhibited differences in abundance, diversity, and community assemblages within the canyon in contrast to the slope, in relation to enrichment patterns of organic matter within the canyon. Chemosynthetic communities differed between habitat types, with microbial mat habitats exhibiting high density but low diversity communities. Macrofaunal communities associated with hard substrates had higher diversity than canyon axis communities and significantly contribute to the overall canyon biodiversity. This study provides a complete benthic infaunal appraisal of two canyon systems in the western Atlantic, highlighting the importance of canyons and their associated environments to host unique ecosystems, enhancing our understanding of the drivers of communities in submarine canyons, and providing regional baseline information for nearby canyon and chemosynthetic systems.
DOI: 10.5066/p9td78fw
title: Data release for tracking rates of post-fire conifer regeneration distinct from deciduous vegetation recovery across the western U.S.

description: Post-fire shifts in vegetation composition will have broad ecological impacts. However, information characterizing post-fire recovery patterns and their drivers are lacking over large spatial extents. In this analysis we used Landsat imagery collected when snow cover (SCS) was present, in combination with growing season (GS) imagery, to distinguish evergreen vegetation from deciduous vegetation. We sought to (1) characterize patterns in the rate of post-fire, dual season Normalized Difference Vegetation Index (NDVI) across the region, (2) relate remotely sensed patterns to field-measured patterns of re-vegetation, and (3) identify seasonally-specific drivers of post-fire rates of NDVI recovery. Rates of post-fire NDVI recovery were calculated for both the GS and SCS for more than 12,500 burned points across the western United States. Points were partitioned into faster and slower rates of NDVI recovery using thresholds derived from field plot data (n=230) and their associated rates of NDVI recovery. We found plots with conifer saplings had significantly higher SCS NDVI recovery rates relative to plots without conifer saplings, while plots with &amp;#8805;50% grass/forbs/shrubs cover had significantly higher GS NDVI recovery rates relative to plots with &lt;50%. GS rates of NDVI recovery were best predicted by burn severity and anomalies in post-fire maximum temperature. SCS NDVI recovery rates were best explained by aridity and growing degree days. This study is the most extensive effort, to date, to track post-fire forest recovery across the western U.S. Isolating patterns and drivers of evergreen recovery from deciduous recovery will enable improved characterization of forest ecological condition across large spatial scales.
DOI: 10.5066/p9m4joov
title: Hepatic Transcriptome of Japanese quail (Coturnix japonica) Exposed to 17B.-Trenbolone

description: The files in this data release are RNA seq datafiles from a study that examined the effects of the synthetic anabolic steroid 17B. hydroxyestra 4,9,11 trien-3-one, trenbolone (17B.T - CAS 10161-33-8), a common contaminant of wastes from confined animal feeding operations (CAFOs). Japanese quail (Coturnix japonica) were exposed in the egg and through feed to multiple doses of 17&beta;T and liver transcriptomes were examined to identify genes and pathways directly affected by this androgenic compound. RNA was extracted from liver of adults and embryos and analyzed (1x50 bp) on an Illumina HiSeq 2000. NCBI Biosample accessions and the raw counts that were input into the differential expression analysis are provided in this dataset. The raw sequence data are available at the NCBI Sequence Read Archive under Bioproject numbers PRJNA313918 and PRJNA313931.
DOI: 10.5066/p9r1s1bd
title: Capture-mark-recapture data for Oregon spotted frogs (Rana pretiosa) along the Deschutes River, Oregon, 2016-2019

description: This dataset contains information from capture-mark-recapture sampling of Oregon spotted frogs (Rana pretiosa) conducted 2016-2019 by USGS as part of a study relating R. pretiosa survival and abundance to wetland inundation in the upper Deschutes River. Data consist of site, survey, habitat, and species detection covariates, as well as 10 years of hydrological and drought metrics used to establish relationships between river flow and area of inundation at survey sites. Remotely sensed and model predicted area wet estimates for the sites are also given.
DOI: 10.5066/p9putqyk
title: Data release for Surficial Geology of the Northern San Luis Valley, Saguache, Fremont, Custer, Alamosa, Rio Grande, Conejos, and Costilla Counties, Colorado

description: The San Luis Valley and associated underlying basin of south-central Colorado and north-central New Mexico is the largest structural and hydrologic basin of the Rio Grande Rift and fluvial system. The surrounding San Juan and Sangre de Cristo Mountains reveal evidence of widespread volcanism and transtensional tectonism beginning in the Oligocene and continuing to the present, as seen in fault displacement of Pleistocene to Holocene deposits along the eastern basin-bounding Sangre de Cristo fault system and fault zones along the western margin of the basin. The San Luis basin can generally be subdivided into northern and southern basins at the structural and physiographic high terrain of the San Luis Hills in the center of the basin, proximal to the Colorado-New Mexico stateline. The northern San Luis Valley can be subdivided into two subbasins at approximately the latitude of the Great Sand Dunes and San Luis Lakes, where the endorheic northern subbasin surface and subsurface flow currently accumulate in a series of playa lakes. To the south of this playa region, the Rio Grande has captured basin hydrology into a through-going fluvial system cutting through the San Luis Hills, carving the Rio Grande gorge, and ultimately flowing into the Gulf of Mexico. This surficial geologic map of the northern San Luis Valley, paired with the Alamosa, CO 1:100,000-scale geologic map (U.S. Geological Survey Scientific Investigations Map 3342) provides new and compiled geologic mapping that characterizes basin deposits and locates the traces of active faults, with the goal to provide geospatial data for future investigations related to western North American neotectonics, Pleistocene paleoclimate, and related geomorphic processes. In addition, present natural and anthropogenic water bodies have been located and updated for hydrologic modeling and water-usage investigations.
DOI: 10.7295/w9cil54592
title: CIL:54592, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54593
title: CIL:54593, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54594
title: CIL:54594, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54595
title: CIL:54595, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54596
title: CIL:54596, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54597
title: CIL:54597, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54598
title: CIL:54598, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54599
title: CIL:54599, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54600
title: CIL:54600, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54601
title: CIL:54601, Mus musculus, Fetal Liver Macrophage
DOI: 10.7295/w9cil54602
title: CIL:54602, Mus musculus, Bone Marrow Derived Macrophage
DOI: 10.7295/w9cil54603
title: CIL:54603, Mus musculus, RAW264.7
DOI: 10.7295/w9cil54604
title: CIL:54604, Mus musculus, RAW264.7
DOI: 10.5281/zenodo.5068366
title: SCLC brain metastasis

description: Brain metastasis is a major cause of morbidity and mortality in cancer patients. Here we investigated mechanisms allowing small-cell lung cancer (SCLC) cells to grow in the brain. We show that SCLC cells undergo a cell state transition towards neuronal differentiation during tumor progression and metastasis, and that this neuronal mimicry is critical for SCLC growth in the brain.
DOI: 10.5281/zenodo.5068365
title: SCLC brain metastasis

description: Brain metastasis is a major cause of morbidity and mortality in cancer patients. Here we investigated mechanisms allowing small-cell lung cancer (SCLC) cells to grow in the brain. We show that SCLC cells undergo a cell state transition towards neuronal differentiation during tumor progression and metastasis, and that this neuronal mimicry is critical for SCLC growth in the brain.
DOI: 10.15151/esrf-es-450256620
title: Interactions of synaptic vesicles in dense pools studied by SAXS

description: We will study the structure and interactions of synaptic vesicles (SV) in a model system of a dense SV pool, mimicking the environment of a synapse, including changes following a calcium signal. For this purpose, we will use the combination of the stopped-flow technique for rapid mixing and highly brilliant ESRF undulator radiation. This will extend previous SAXS of dilute SV suspensions (modelled by a form-factor only) to a more physiological assembly under controlled physicochemical conditions (modelled by a form- and structure-factor [6]). The proposal addresses the fundamental physicochemical principles governing the interaction of SVs in the presence of cytosolic proteins in the synapse, in particular synapsin and alpha-synuclein, as well as the changes associated with calcium.
DOI: 10.15151/esrf-es-472484909
title: Determining symmetry and structure of FeCr2S4

description: In condensed matter physics there is growing interest in correlated phenomena that arise via competing instabilities, such as those provided by systems like FeCr2S4 with its strong spin-orbital (SO) interaction that compete with Jahn-Teller (JT) distortions. In FeCr2S4 these strongly correlated phenomena are manifested as, e.g., a metal-to-insulator transition, colossal magnetoresistance and half-metallic ground state. Despite significant investigation for the last 50 years the exact space-group or even the crystal symmetry, of the low temperature phase is yet to be established. The aim of this proposal is to establish the space-group of the system below 9 K. This will be done with high-resolution X-ray scattering at ID22 to have the best chance possible to observe the subtle structural changes that is expected, before Rietveld refinements are used to determine the symmetry. Time permitting, we will also collect data of the structure across the transitions at 165 K and 60 K.
DOI: 10.15151/esrf-es-449124708
title: Investigation by 3D nano-holotomography of the self-healability of an Aluminium alloy produced by additive manufacturing

description: Al parts might be subjected to overloads leading to voids, cracks and the replacement of the part. A promising solution is to use self-healing material. A self-healing Al alloy was produced by SLM based on Al-Si and Mg powder. The microstructure is composed of a Si network and Mg2Si precipitates in a α-Al matrix. During an overload, void nucleation occurs due to fracture of the Si network and of precipitates. The idea is to use a heat treatment to trigger the diffusion of the healing agents to the cavities. The healing potential of fractured Mg2Si was already proven but the SLM microstructure is different and its influence on the healing efficiency and kinetics needs to be investigated. Nanoholotomography allows observing the same area before and after healing in order to track the damage and to assess the healing potential of the material. As the SLM microstructure will not be noticeable, FIB-SEM will be used to evidence the influence of the microstructure on the healing efficiency.
DOI: 10.6084/m9.figshare.14885238.v1
title: Cointegrate plasmid pSL131_IncA/C_IncX3 with different structures

description: Cointegrate plasmid pSL131_IncA/C_IncX3 with different structures
DOI: 10.5517/ccdc.csd.cc103kwk
title: CCDC 926958: Experimental Crystal Structure Determination

description: Related Article: Chen-Wei Liu, Jian-Hong Liao|2016|CSD Communication|||
description: Related Article: Arvind K. Gupta, Pilli V. V. N. Kishore, Jhih-Yu Cyue, Jian-Hong Liao, Welni Duminy, Werner E. van Zyl, C. W. Liu|2021|Inorg.Chem.|60|8973|doi:10.1021/acs.inorgchem.1c00871
DOI: 10.5517/ccdc.csd.cc24tfkz
title: CCDC 1990651: Experimental Crystal Structure Determination

description: Related Article: Zohar A. Arnon, Topaz Kreiser, Boris Yakimov, Noam Brown, Ruth Aizen, Shira Shaham-Niv, Pandeeswar Makam, Muhammad Nawaz Qaisrani, Emiliano Poli, Antonella Ruggiero, Inna Slutsky, Ali Hassanali, Evgeny Shirshin, Davide Levy, Ehud Gazit|2021|iScience|24|102695|doi:10.1016/j.isci.2021.102695
DOI: 10.25345/c5g543
title: MassIVE MSV000087750 - Protein kinase signalling at the Leishmania kinetochore captured by XL-BioID
title: Elucidating protein kinase driven signaling pathways is an important but challenging problem in cell biology. Phosphoproteomics has been used to identify many phosphorylation sites, however the spatial context of these sites within the cell is mostly unknown making it difficult to reconstruct signalling pathways. To address this problem an in vivo proximity capturing workflow was developed consisting of proximity biotinylation followed by protein cross-linking (XL-BioID). This was applied to protein kinases of the Leishmania kinetochore leading to the discovery of a novel essential kinetochore protein, KKT26. XL-BioID enabled the quantification of proximal phosphosites at the kinetochore through the cell cycle, allowing the phosphorylation state of the kinetochore to be followed during assembly. A specific inhibitor of kinetochore protein kinases KKT10/KKT19 was used to show that XL-BioID provides a spatially focussed view of protein kinase inhibition, identifying 16 inhibitor responsive proximal phosphosites, including 3 on KKT2, demonstrating the potential of this approach for discovery of in vivo kinase signalling pathways.
DOI: 10.25345/c5bc1s
title: MassIVE MSV000087751 - GNPS Ginseng Nodule Bacteria Secondary Metabolites
title: Extracted secondary metabolites from nodule/tumor-like growth-inhabiting bacteria of ginseng plant.
DOI: 10.5517/ccdc.csd.cc26vc5m
title: CCDC 2051120: Experimental Crystal Structure Determination

description: Related Article: Shuai-Kang Yu, Zhi-Ruo Zhang, Zhou-Hong Ren, Hang-Ling Zhai, Qin-Yu Zhu, Jie Dai|2021|Inorg.Chem.|60|9132|doi:10.1021/acs.inorgchem.1c01106
DOI: 10.5517/ccdc.csd.cc24hwq8
title: CCDC 1981480: Experimental Crystal Structure Determination

description: Related Article: Xiaoqin Cui, Fu-Qiang Zhang, Xin Li, Juan-Juan Hou, Huan Li, Xian-Ming Zhang|2021|Inorg.Chem.|60|9174|doi:10.1021/acs.inorgchem.1c01189
DOI: 10.5517/ccdc.csd.cc2716gz
title: CCDC 2056740: Experimental Crystal Structure Determination

description: Related Article: Xiaoqin Cui, Fu-Qiang Zhang, Xin Li, Juan-Juan Hou, Huan Li, Xian-Ming Zhang|2021|Inorg.Chem.|60|9174|doi:10.1021/acs.inorgchem.1c01189
DOI: 10.5517/ccdc.csd.cc2716h0
title: CCDC 2056741: Experimental Crystal Structure Determination

description: Related Article: Xiaoqin Cui, Fu-Qiang Zhang, Xin Li, Juan-Juan Hou, Huan Li, Xian-Ming Zhang|2021|Inorg.Chem.|60|9174|doi:10.1021/acs.inorgchem.1c01189
DOI: 10.5517/ccdc.csd.cc2716j1
title: CCDC 2056742: Experimental Crystal Structure Determination

description: Related Article: Xiaoqin Cui, Fu-Qiang Zhang, Xin Li, Juan-Juan Hou, Huan Li, Xian-Ming Zhang|2021|Inorg.Chem.|60|9174|doi:10.1021/acs.inorgchem.1c01189
DOI: 10.5517/ccdc.csd.cc27b81x
title: CCDC 2065438: Experimental Crystal Structure Determination

description: Related Article: Stefan Henfling, Anastasia Kultaeva, Andreas Pöppl, Jennifer Klose, Berthold Kersting, Kostiantyn V. Domasevitch, Harald Krautscheid|2021|Inorg.Chem.|60|9008|doi:10.1021/acs.inorgchem.1c00914
DOI: 10.5517/ccdc.csd.cc27b82y
title: CCDC 2065439: Experimental Crystal Structure Determination

description: Related Article: Stefan Henfling, Anastasia Kultaeva, Andreas Pöppl, Jennifer Klose, Berthold Kersting, Kostiantyn V. Domasevitch, Harald Krautscheid|2021|Inorg.Chem.|60|9008|doi:10.1021/acs.inorgchem.1c00914
DOI: 10.5517/ccdc.csd.cc27b83z
title: CCDC 2065440: Experimental Crystal Structure Determination

description: Related Article: Stefan Henfling, Anastasia Kultaeva, Andreas Pöppl, Jennifer Klose, Berthold Kersting, Kostiantyn V. Domasevitch, Harald Krautscheid|2021|Inorg.Chem.|60|9008|doi:10.1021/acs.inorgchem.1c00914
DOI: 10.5517/ccdc.csd.cc27b840
title: CCDC 2065441: Experimental Crystal Structure Determination

description: Related Article: Stefan Henfling, Anastasia Kultaeva, Andreas Pöppl, Jennifer Klose, Berthold Kersting, Kostiantyn V. Domasevitch, Harald Krautscheid|2021|Inorg.Chem.|60|9008|doi:10.1021/acs.inorgchem.1c00914
DOI: 10.5517/ccdc.csd.cc27b851
title: CCDC 2065442: Experimental Crystal Structure Determination

description: Related Article: Stefan Henfling, Anastasia Kultaeva, Andreas Pöppl, Jennifer Klose, Berthold Kersting, Kostiantyn V. Domasevitch, Harald Krautscheid|2021|Inorg.Chem.|60|9008|doi:10.1021/acs.inorgchem.1c00914
DOI: 10.5517/ccdc.csd.cc27b0k5
title: CCDC 2065206: Experimental Crystal Structure Determination

description: Related Article: Yuteng Cao, Honglei Xia, Kangcai Wang, Qinghua Zhang, Wenquan Zhang|2021|Inorg.Chem.|60|8409|doi:10.1021/acs.inorgchem.1c00627
DOI: 10.5517/ccdc.csd.cc24hytf
title: CCDC 1981545: Experimental Crystal Structure Determination

description: Related Article: Soumitra Dinda, Srijita Naskar, Subhadip Roy, Kausikisankar Pramanik, Sanjib Ganguly|2021|Polyhedron|205|115318|doi:10.1016/j.poly.2021.115318
DOI: 10.5517/ccdc.csd.cc24hyqb
title: CCDC 1981542: Experimental Crystal Structure Determination

description: Related Article: Soumitra Dinda, Srijita Naskar, Subhadip Roy, Kausikisankar Pramanik, Sanjib Ganguly|2021|Polyhedron|205|115318|doi:10.1016/j.poly.2021.115318
DOI: 10.5517/ccdc.csd.cc27jcy3
title: CCDC 2071325: Experimental Crystal Structure Determination

description: Related Article: Angeera Chandra, Basudeb Dutta, Kunal Pal, Kuladip Jana, Chittranjan Sinha|2021|J.Mol.Struct.|1243|130923|doi:10.1016/j.molstruc.2021.130923
DOI: 10.5517/ccdc.csd.cc2778qh
title: CCDC 2062576: Experimental Crystal Structure Determination

description: Related Article: Lizhong He, Xinhai He, Junbo Wang, Chong Fu, Junhao Liang|2021|Inorg.Chem.|60|8404|doi:10.1021/acs.inorgchem.1c00303
DOI: 10.5517/ccdc.csd.cc27lyxq
title: CCDC 2073804: Experimental Crystal Structure Determination

description: Related Article: Xiao-Yang Chen, Haoyuan Chen, Luka Đorđević, Qing-Hui Guo, Huang Wu, Yu Wang, Long Zhang, Yang Jiao, Kang Cai, Hongliang Chen, Charlotte L. Stern, Samuel I. Stupp, Randall Q. Snurr, Dengke Shen, J. Fraser Stoddart|2021|J.Am.Chem.Soc.|143|9129|doi:10.1021/jacs.1c03277
DOI: 10.5517/ccdc.csd.cc27lyyr
title: CCDC 2073805: Experimental Crystal Structure Determination

description: Related Article: Xiao-Yang Chen, Haoyuan Chen, Luka Đorđević, Qing-Hui Guo, Huang Wu, Yu Wang, Long Zhang, Yang Jiao, Kang Cai, Hongliang Chen, Charlotte L. Stern, Samuel I. Stupp, Randall Q. Snurr, Dengke Shen, J. Fraser Stoddart|2021|J.Am.Chem.Soc.|143|9129|doi:10.1021/jacs.1c03277
DOI: 10.5517/ccdc.csd.cc27lyzs
title: CCDC 2073806: Experimental Crystal Structure Determination

description: Related Article: Xiao-Yang Chen, Haoyuan Chen, Luka Đorđević, Qing-Hui Guo, Huang Wu, Yu Wang, Long Zhang, Yang Jiao, Kang Cai, Hongliang Chen, Charlotte L. Stern, Samuel I. Stupp, Randall Q. Snurr, Dengke Shen, J. Fraser Stoddart|2021|J.Am.Chem.Soc.|143|9129|doi:10.1021/jacs.1c03277
DOI: 10.5517/ccdc.csd.cc27fxxj
title: CCDC 2068968: Experimental Crystal Structure Determination

description: Related Article: Arvind K. Gupta, Pilli V. V. N. Kishore, Jhih-Yu Cyue, Jian-Hong Liao, Welni Duminy, Werner E. van Zyl, C. W. Liu|2021|Inorg.Chem.|60|8973|doi:10.1021/acs.inorgchem.1c00871
DOI: 10.5517/ccdc.csd.cc27nt3v
title: CCDC 2075577: Experimental Crystal Structure Determination

description: Related Article: Rammohan R. Yadav Bheemanaboina, Juan Wang, Yuan-Yuan Hu, Jiang-Ping Meng, Zhi Guan, Cheng-He Zhou|2021|Bioorg.Med.Chem.Lett.|47|128198|doi:10.1016/j.bmcl.2021.128198
DOI: 10.5517/ccdc.csd.cc1m6lt7
title: CCDC 1495899: Experimental Crystal Structure Determination

description: Related Article: Chen-Wei Liu, Jian-Hong Liao|2016|CSD Communication|||
description: Related Article: Arvind K. Gupta, Pilli V. V. N. Kishore, Jhih-Yu Cyue, Jian-Hong Liao, Welni Duminy, Werner E. van Zyl, C. W. Liu|2021|Inorg.Chem.|60|8973|doi:10.1021/acs.inorgchem.1c00871
DOI: 10.6084/m9.figshare.14906499
title: Dataset of DeepOPF-V: Modified IEEE 300-bus system with real-time load data

description: This dataset was generated for the case study in modified IEEE 300-bus system using real-time load data in [1].<br>[1] W. Huang, X. Pan, M. Chen, and S. H. Low, "DeepOPF-V: Solving AC-OPF Problems Efficiently," arXiv preprint arXiv:2103.11793, 2021.<br>
DOI: 10.5517/ccdc.csd.cc27v0qv
title: CCDC 2080587: Experimental Crystal Structure Determination

description: Related Article: Xiaoqin Cui, Fu-Qiang Zhang, Xin Li, Juan-Juan Hou, Huan Li, Xian-Ming Zhang|2021|Inorg.Chem.|60|9174|doi:10.1021/acs.inorgchem.1c01189
DOI: 10.5517/ccdc.csd.cc26vc6n
title: CCDC 2051121: Experimental Crystal Structure Determination

description: Related Article: Shuai-Kang Yu, Zhi-Ruo Zhang, Zhou-Hong Ren, Hang-Ling Zhai, Qin-Yu Zhu, Jie Dai|2021|Inorg.Chem.|60|9132|doi:10.1021/acs.inorgchem.1c01106
DOI: 10.5281/zenodo.5059356
title: Dataset from: "Voluntary Control of Task Selection Does Not Eliminate the Impact of Selection History on Attention"

description: Dataset for Henare, D. T., Kadel, H., & Schubö, A. (2020). Voluntary Control of Task Selection Does Not Eliminate the Impact of Selection History on Attention. <em>Journal of Cognitive Neuroscience</em>, <em>32</em>(11), 2159-2177. https://doi.org/10.1162/jocn_a_01609
description: This work was supported by the Deutsche Forschungsgemeinschaft (German Research Foundation) – SFB/TRR 135, project number 222641018, TP B3.
description: {"references": ["Henare, D. T., Kadel, H., & Schub\u00f6, A. (2020). Voluntary Control of Task Selection Does Not Eliminate the Impact of Selection History on Attention.\u00a0Journal of Cognitive Neuroscience,\u00a032(11), 2159-2177. https://doi.org/10.1162/jocn_a_01609"]}