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Fig. 1 in Callicultureinducingfromredclover(Trifolium Pratense L.) Wild Accessions And Results Of Dna Extraction
Fig. 1. Results of flow cytometry: a) 2n ploidy control, b) the typical result for leaves, c) the typical result for stems, d) the typical result for roots.
FIGURE 2 in DigApp and TaphonomApp: Two new open-access palaeontological and archaeological mobile apps
FIGURE 2. DiggApp Offline modified for excavations at Batallones-10 palaeontological site. A "New Specimen" screen, with "Completeness", "Consolidation", "Preservation" and "Articulation" fields added. B, "Taxonomical Identification" dropdown menu modified to include Batallones-10 faunal list.
FIGURE 3. A in DigApp and TaphonomApp: Two new open-access palaeontological and archaeological mobile apps
FIGURE 3. A, TaphonomApp "Taphonomical Analysis" screen. B, TaphonomApp "New Specimen" scrollable screen.
Analysing the intra and interregional components of spatial accessibility gravity model to capture the level of equity in the distribution of hospital services: does they influence patient mobility?
<p>aggregated_data_age55+.csv and distance_matrix_age55+.csv have been included in the second version of the dataset as the reference population is limited to resident with 55 years old or more.</p>
Fig. 1 in Data storage and data re-use in taxonomy-the need for improved storage and accessibility of heterogeneous data
Fig. 1 (a) Sp_ci_s d_scriptions p_r d_cad_ in s_l_ct_d major groups of organisms (bas_d on data _xtract_d from th_ Int_rnational Plant Nam_s Ind_x (https://www.ipni.org/) for plants, MycoBank (http://www. mycobank.org/) for fungi, Ind_x of Organism Nam_s (http://www. organismnam_s.com/) for ins_cts, and compil_d from various databas_s for v_rt_brat_s: Eschm_y_r Catalog for fish_s (https://www.calacad_my. org/sci_ntists/proj_cts/_schm_y_rs-catalog-of-fish_s), th_ Amphibian Sp_ci_s of th_ World for amphibians (http://r_s_arch.amnh.org/vz/ h_rp_tology/amphibia/), R_ptil_ Databas_ for r_ptil_s (http://www. r_ptil_-databas_.org/), Howard and Moor_ Databas_ (https://www. howardandmoor_.org/) for birds, and ASM Mammal Div_rsity Databas_ (https://mammaldiv_rsity.org/) for mammals, all acc_ss_d in April 2019. Not_ that data for fungi and v_rt_brat_s r_f_r to curr_ntly acc_pt_d sp_ci_s nam_s only wh_r_as ins_ct data also includ_ synonyms and subsp_ci_s, and contain data gaps for s_v_ral d_cad_s in th_ nin_t__nth c_ntury; for all taxa, th_ low valu_s obtain_d for th_ last
Fig. 3. Sealing and walling off the access point between the 2 in Territorial status-quo between the big-headed ant (Hymenoptera: Formicidae) and the Formosan subterranean termite (Isoptera: Rhinotermitidae)
Fig. 3. Sealing and walling off the access point between the 2 species where both termites and ants are depositing sand particles to create a physical sepa- ration with little to no casualties. A) in the tube between the arenas, B) at the entrance of the arena.
◂Fig. 6 Gynoecial development, fruit and seedling of C. crenata %yellow frames), C. cf. grandicalyx %blue frames) and C. sinensis %pink frames; A–F light microscopy, G–K stereo microscopy of endocarp, mesocarp removed; L–O field images; TS in horizontal orientation). A, B TS of anthetic flower %note two to three abortive ovules and strongly stained, peripheral tissue). C, D TS of anthetic flower %note two to three abortive ovules and lignifying portions of prospective mesocarp). E Young fruit %note developing endocarp and flashily pink portions of the mesocarp). F TS of postanthetic flower %note three abortive ovules and lignifying portions of prospective mesocarp). G TS of endocarp, with three developed embryos removed %note scanty endosperm). H Endocarp. J TS of endocarp. K Endocarp. L Immature fruits. M Mature fruits. N Seedlings %note short hypocotyl and long petioles of cotyledons). O Seedlings %note long hypocotyl and short petioles of cotyledons; image taken from cultivated plant, accession number 2012–0005, in the Botanical Garden Munich) %LS, longisection; TS, transverse section; ao, abortive ovule; cot, cotyledon; db, dorsal bundle; c, calyx; ec, endocarp; ens, endosperm; ex, exocarp; fr, fruit; h, hypocotyl; int, integument; lb, lateral bundle; mc, mesocarp; o, ovule; pet, petiolus; sty, style; ut, peripheral tissue; vs, ventral slit) in Observations on flower and fruit anatomy in dioecious species of Cordia (Cordiaceae, Boraginales) with evolutionary interpretations
◂Fig. 6 Gynoecial development, fruit and seedling of C. crenata %yellow frames), C. cf. grandicalyx %blue frames) and C. sinensis %pink frames; A–F light microscopy, G–K stereo microscopy of endocarp, mesocarp removed; L–O field images; TS in horizontal orientation). A, B TS of anthetic flower %note two to three abortive ovules and strongly stained, peripheral tissue). C, D TS of anthetic flower %note two to three abortive ovules and lignifying portions of prospective mesocarp). E Young fruit %note developing endocarp and flashily pink portions of the mesocarp). F TS of postanthetic flower %note three abortive ovules and lignifying portions of prospective mesocarp). G TS of endocarp, with three developed embryos removed %note scanty endosperm). H Endocarp. J TS of endocarp. K Endocarp. L Immature fruits. M Mature fruits. N Seedlings %note short hypocotyl and long petioles of cotyledons). O Seedlings %note long hypocotyl and short petioles of cotyledons; image taken from cultivated plant, accession number 2012–0005, in the Botanical Garden Munich) %LS, longisection; TS, transverse section; ao, abortive ovule; cot, cotyledon; db, dorsal bundle; c, calyx; ec, endocarp; ens, endosperm; ex, exocarp; fr, fruit; h, hypocotyl; int, integument; lb, lateral bundle; mc, mesocarp; o, ovule; pet, petiolus; sty, style; ut, peripheral tissue; vs, ventral slit)
◂Fig. 6 A molecular phylogeny of 56 systematically representative Peridiniaceae, including 42 accessions assignable to P. cinctum from various geographic regions. Maximum likelihood tree (– ln = 21,884.93), as inferred from a rRNA nucleotide alignment (1137 parsimony-informative sites) and with strain number information. Numbers on branches are ML bootstrap (above) and Bayesian support values (below) for the clusters (asterisks indicate maximal support values, values under 50 and 0.90, respectively, are not shown). Clades are indicated (CZE Czech Republic, E East, GER Germany, HET Heterocapsaceae, N North, PPE Protoperidiniaceae, POL Poland, rbn ribotype n, S South, SWE Sweden, UKR Ukraine, W West) in Bumps on the back: An unusual morphology in phylogenetically distinct Peridinium aff. cinctum (= Peridinium tuberosum; Peridiniales, Dinophyceae)
◂Fig. 6 A molecular phylogeny of 56 systematically representative Peridiniaceae, including 42 accessions assignable to P. cinctum from various geographic regions. Maximum likelihood tree (– ln = 21,884.93), as inferred from a rRNA nucleotide alignment (1137 parsimony-informative sites) and with strain number information. Numbers on branches are ML bootstrap (above) and Bayesian support values (below) for the clusters (asterisks indicate maximal support values, values under 50 and 0.90, respectively, are not shown). Clades are indicated (CZE Czech Republic, E East, GER Germany, HET Heterocapsaceae, N North, PPE Protoperidiniaceae, POL Poland, rbn ribotype n, S South, SWE Sweden, UKR Ukraine, W West)
◂Fig. 4 A molecular tree of 51 systematically representative Peridiniaceae, including all 28 accessions assignable to P. volzii. Maximum Likelihood tree (–ln = 22,017.62), as inferred from a rRNA nucleotide alignment (1,129 parsimony-informative sites) and with strain number information. Numbers on branches are ML bootstrap (above) and Bayesian support values (below) for the clusters (asterisks indicate maximal support values, values under 50 and 0.90, respectively, are not shown). Clades are indicated (abbreviations: HET, Heterocapsaceae; PPE, Protoperidiniaceae) in Morphological and molecular variability of Peridinium volzii Lemmerm. (Peridiniaceae, Dinophyceae) and its relevance for infraspecific taxonomy
◂Fig. 4 A molecular tree of 51 systematically representative Peridiniaceae, including all 28 accessions assignable to P. volzii. Maximum Likelihood tree (–ln = 22,017.62), as inferred from a rRNA nucleotide alignment (1,129 parsimony-informative sites) and with strain number information. Numbers on branches are ML bootstrap (above) and Bayesian support values (below) for the clusters (asterisks indicate maximal support values, values under 50 and 0.90, respectively, are not shown). Clades are indicated (abbreviations: HET, Heterocapsaceae; PPE, Protoperidiniaceae)
Survey on data access conditions for sensitive data - Raw Data and Documentation
<p>This Upload concerns the survey entitled “Survey on data access conditions for sensitive data” which was performed by The Dutch Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) and DANS, the Dutch national centre of expertise and repository for research data. The survey was launched in April 2024 and open until July 1st 2024. </p> <p>The goal of the survey was to gather additional information about access conditions and restrictions used by researchers using the DANS and ODISSEI services. The results of the survey can guide us to identify common conditions that should be included in a standardisation effort. Moreover, the results will improve the available guidance that DANS and ODISSEI can provide for their local research community. A comprehensive analysis of the survey and resulting recommendations will be published separately at a later point in time. </p> <p>This upload contains:</p> <ul> <li>a PDF with documentation of the survey, specifically the description and question text.</li> <li>an ODS spreadsheet with the raw data from the survey which was filled in by 46 participants. Please note that the survey was anonymous, no personal data of the respondents was collected. </li> </ul> <p>The survey was executed using EUSurvey (v1.5.3.1). EU Survey is open source and built by DG DIGIT and funded under the ISA, ISA2 and Digital Europe Programme (DIGITAL). EUSurvey is published under the EUPL licence and the source code is available from GitHub: https://github.com/EUSurvey.</p>
Millikelvin confocal microscope with free-space access and high-frequency electrical control
<p>Raw data and analysis scripts repository of the scientific paper "Millikelvin confocal microscope with free-space access and high-frequency<br>electrical control".</p>
Books per Publisher: Data from the Directory of Open Access Books (DOAB)
<p>Quantitative information on publishers and published books from the Directory of Open Access Books (DOAB).</p>
Open Access Tutorial
<p>Das Video ist in einem Werkstattprojekt (Forschendes Lernen) zum Thema Open Access mit Studierenden der FH Potsdam am Fachbereich Informationswissenschaften entstanden.</p> <p>Die Aufgabenstellung war es, ein Video-Tutorial zu Open Access zu produzieren, welches die Entwicklung, ebenso wie Vor- und Nachteile von Open Access erläutert und aufgrund der Ausführungen zur Open Access Publikation motiviert. </p> <p>Das Video gibt einen Überblick über die Geschichte des wissenschaftlichen Publizierens und die Ursprünge der Open Access-Bewegung. Daran anknüpfend werden verschiedene Strategien vorgestellt: der goldene und der grüne Weg. Die Vor- und Nachteile von Open Access werden insbesondere in Hinblick auf Article Processing Charges diskutiert.</p> <p>Umgesetzt wurde das Video mit Simpleshow: https://www.mysimpleshow.com/de/ </p> <p>Urheber des Videos: Studierende Fachhochschule Potsdam, Fachbereich 5 Informationswissenschaften<br> (https://www.fh-potsdam.de/studieren/fachbereiche/informationswissenschaften/)</p> <p>Werkstattleitung: Prof. Dr. jur. Ellen Euler,LL.M. zusammen mit Tutorin: Dorothea Strecker</p>
Numbers of Articles, Books and Dissertation theses indexed in BASE and percentages of items published Open Access, under Creative Commons Licenses and under Open Licenses (2013-2017)
<p>A look at the data provided by the Open Access search engine BASE (http://base-search.net) shows that the Open Science compliance among dissertation theses stagnates. BASE knows three categories of accessibility: Open Access, Unknown, Non-Open Access. In the following tables and graphs, figures reported as "Open Access" have been categorised by BASE as Open Access. The tables and graphics show data from BASE (as of 06.03.2018) as follows:</p> <p>a) Indexed theses, books and journal articles</p> <p>b) Indexed theses, books and journal articles published by Open Access</p> <p>c) indexed theses, books and journal articles under Creative Commons licenses.</p> <p>d) indexed theses, books and journal articles, which are published under open licenses in the sense of the Open License, i. e. reflect terms of use of the Open Source.</p> <p> </p> <p>Although doctoral theses already had a high share of open access by 2013 (43%), by 2017 it had risen by only 5% (2017:48%). At the same time, the proportion of books published in open access rose by 14% (from 20% to 34%) and articles by 17% from 44% (2013) to 61% (2017). The same effect can be seen in the proportion of CC-licensed items: Their share rose by 4% (from 9% to 13%) for doctoral theses, by 9% for books (from 4% to 13%) and 8% for articles (from 10% to 18%) between 2013 and 2017. However, the share of openly licensed items is most pronounced: it did not increase for doctoral theses, but remained at 2% between 2013 and 2017; in the same period it increased by 5% (from 1% to 6%) for books, and by 5% (from 5% to 10%) for articles.</p>
Résultats du sondage institutionnel sur l'Open Access à l'Université de Lausanne
<p>Ces données contiennent les réponses anonymisées des 796 chercheur-e-s de l'institution qui ont complété le sondage institutionnel sur l'Open Access 2017.</p>
Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 11. Online accessible repository of digital data on cultural heritage with X3D models (STARC Web Repository, 2017, © Copyright 2017, STARC, Cyprus Institute. Used with permission)
<p>Prototyping can also include the development of toolkits for automatic content generation simulator, but in the case of an architectural environment, the components are too complex to be automatically generated. Furniture elements or the learning artifacts (i.e. content created by learners) can be converted to be viewed in X3D compatible browsers or included in online galleries (Figure 11). After functional and 3D content prototyping, certain components of the virtual campus can be easily modified and adapted as needed.</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 3. Intelligence of different living creature (accessed 01.11.2017). 3.1. A painting elephant (http://www.wittyfacts.com/suda-the-painting-elephant/); 3.2. A common octopus (https://en.wikipedia.org/wiki/Octopus). 3.3. An African grey parrot (https://en.wikipedia.org/wiki/Grey_parrot)
<p>Many observations proved that octopus species have an impressive spatial learning capacity, advanced navigational abilities, and advanced predatory techniques. The dexterity is important for using and manipulating tools. Zullo, Sumbre, Agnisola, Flash, & Hochner, (2009) studied the successful dexterity of octopuses. They have highly sensitive suction cups and prehensile arms, squid, and cuttlefish. This allows them to hold and manipulate objects. The motor skills of octopuses (Figure 3.2) do not seem to depend upon mapping their body. Some species of parrots are able to mimic very well the human speech. There were performed many studies with parrots that shown that some individuals are able to associate words with their meanings. Another observed ability is to form simple sentences. It has been shown that some grey parrots perform at the cognitive level of a 3-year-old child in some tasks. Pepperberg (2006) proved that some parrots can count up to 6. Figure 3.3 presents a frequently studied species of parrots, called African grey parrot.</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-igure 2. Intelligence of different living creature (accessed 01.11.2017). 2.1. A crow solving a complex task (https://www.disclose.tv/spooky-genius-crow-had-to-be-removed-from-scientific-experiment- 314886). 2.2. A group of dolphins with a social behaviour (http://www.sciencemag.org/news/2012/04/teamwork-builds-big-brains); 2.3. An orangutan that use a spear to fish (https://primatology.net/2008/04/29/orangutan-photographed-using-tool-as-spear-to-fish)
<p>Some species of birds have been shown capable of using different tools. Many studies consider the crows as very intelligent. Smirnova, Lazareva, and Zorina (2000) suggested that crows have some kind of numerical ability. Figure 2.1 presents a crow that uses a tool, a small stone in order to catch a worm from a glass of water.The dolphins in many studies are considered intelligent at the individual level. An advanced ability of dolphins is the self-awareness. Marten and Psarakos (1995) presented an interesting study based on self-view television to distinguish between self-examination and social behavior in the Bottlenose dolphin. The most well-known abilities of dolphins are to teach, learn and cooperate. Dolphins have a complex communication and social behaviour. Figure 2.2 presents the image of a common group of dolphins. Some studies prove that primates are one of the most intelligent in the class of animals (Reader, Hager, & Laland, 2011). Orangutans are one of the most intelligent primates. The ability of orangutans to use different types of tools in order to perform tasks is well-known. Figure 2.3 presents an orangutan that uses a spear to catch fish. The orangutans can be considered intelligent at individual level.</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 1. Intelligence of different simple living creature (accessed 01.11.2017). 1.1. A carnivorous plants catching an insect (https://phys.org/news/2016-05-colombia-peace-reveal-jungle-species.html); 1.2. A colony of ants solving a very complex task (https://mappingignorance.org/2016/05/27/rafting-ants); 1.3. The collective behaviour of a school of fish (https://simple.wikipedia.org/wiki/Shoaling_and_schooling)
<p>The biological intelligence of different life forms, ranging from very simple (such as plants) to very complex (such as humans) is the subject of many studies and a large amount of research. Frequent studies related to different kind of biological intelligence include: the intelligence of horses (Krueger, & Heinze, 2008; Krueger, Farmer, & Heinze, 2014; Schuetz, Farmer, & Krueger, 2016), intelligence of pigs (Broom, Sena, & Moynihan, 2009), intelligence of dogs (Coren, 1995), intelligence of primates (Reader, Hager, & Laland, 2011) and so one. Figures 1, 2, and 3 present some biological life forms that are frequently considered intelligent. Trewavas (2002; 2005) considered that plants intelligence should be based on principles such as their ability to adjust their morphology, and phenotype accordingly to ensure self- preservation and reproduction. Figure 1.1 presents an intelligent plant (carnivorous) that uses a strategy for catching very fast flying insects. In order to eat the insect, it makes a movement. Figure 1.1 presents the catching of an insect by a carnivorous plant. The intelligence of colonies of ants, termites and other insects that live in large colonies is considered at the colony level (Brady, Fisher, Schultz, & Ward, 2014; Johnson, Borowiec, Chiu, Lee, Atallah, & Ward, 2013). Figure 1.2 presents the coherent intelligent surviving behaviour of a colony of a species of ants. The ants make a structural reorganization in order to move on the surface of the water. Figure 1.3 presents a very large school of fish with an intelligent coherent collective feeding and self-protecting behaviour. Each individual fish has a very simple behavior. Based on this it cannot be considered intelligent. The intelligence in large schools of fish emerges at the collective level (Shaw, 1978; Parrish, Viscedo, & Grunbaum, 2002).</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 4. Intelligent robots (accessed 01.11.2017). 4.1. Erica, a humanoid robot (https://www.tech-review.com/erica-is-the-latest-japanese-robot-with-human-appearance.html). 4.2. Atlas, a bipedal humanoid robot developed by Boston Dynamics (https://en.wikipedia.org/wiki/Atlas_(robot))
<p>One of the most highly quoted and interesting definitions of machine intelligence was presented by Alan Turing (1950). Turing considered a computing system intelligent if a human assessor could not decide the nature of the system (being human or artificial) based on questions asked from a room hidden from a human assessor. Until recently there were performed different discussions and comments on the Turing test. Hernández-Orallo (2000) presents an interesting study related to the Turing Test. Dowe and Hajek, (1998) propose a computational extension of the Turing Test. The design and development of intelligent systems are historically very recent. But, even if the advance of hardware and software is very fast, it will take a longer time until the artificial computing systems will attain a similar intelligence with the humans. Based on this fact, we consider that is not appropriate to formulate the problem of the direct comparison at a general level of human intelligence with the machine intelligence. Different definitions were proposed for the intelligence of the agents (Russell, & Norvig, 2003; Iantovics, & Zamfirescu, 2013). Many authors (Russell, & Norvig, 2003; Iantovics, 2005) argue that the intelligence of the agents cannot be defined universally. The impossibility to give a universal definition to the human intelligence is based mostly on the enormous complexity of the human brain and complexity of the human thinking and decision making. Similarly, we may consider the impossibility of universal definition of intelligence of the agents based on the very large variety (by type and complexity) of intelligent agents. The machine intelligence frequently is defined based on different abilities such as (Iantovics, 2005; Sharkey, 2006): autonomous learning, self-adaptation, and evolution. These principles of considering the intelligence are inspired by biological life forms able to learn autonomously during their life cycle, to adapt to the environment and to evolve during more generations. We would like to outline that not all the designed agents are intelligent. There is not a required property of an agent to be intelligent.</p>
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.