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Рис. 1. А — рыжеухий бюΛьбюΛь на боярышнике, с. Δазо, Приморский край, 5.11.2019. Фото В. П. Шохрина; B — рыжеухий бюΛьбюΛь пьет сок кΛена приречного, с. Каймановка, Уссурийский гороΑской округ, Приморский край, 03.04.2022. Фото À. А. БеΛяева; C — рыжеухий бюΛьбюΛь кормится ягоΑами Αевичьего винограΑа пятиΛисточкового, г. ВΛаΑивосток, 02.01.2020. Фото А. П. ХоΑакова; D — рыжеухий бюΛьбюΛь, кΛ. ФореΛевый, окрестности с. ФиΛипповка, Хасанский район, Приморский край, 01.03.2018. Фото Ю. А. Àармана; E — рыжеухий бюΛьбюΛь кормится ягоΑами бархата амурского, г. ВΛа- Αивосток, 06.11.2019. Фото А. В. ВяΛкова; F — рыжеухий бюΛьбюΛь, с. Каймановка, Уссурийский гороΑской округ, Приморский край, 04.05.2022. Фото М. В. МасΛова Fig. 1. A — brown-eared bulbul on a hawthorn tree, Lazo village, Primorsky Region, 5.11.2019. Photo by V. P. Shokhrin; B — brown-eared bulbul drinks the juice of an Amur maple, Kaymanovka Village, Ussuriysky Urban District, Primorsky Region, 03.04.2022. Photo by D. A. Belyaev; C — brown-eared bulbul feeds on the berries of the Virginia creeper, Vladivostok, 02.01.2020. Photo by A. P. Khodakov; D — brown-eared bulbul. Forelevy spring, vicinity of Filippovka Village, Khasansky District, Primorsky Region, 01.03.2018. Photo by Yu. A. Darman; E — brown-eared bulbul feeds on the berries of an Amur cork tree, Vladivostok, 06.11.2019. Photo by A. V. Vyalkov; F — brown-eared bulbul. Kaymanovka Village, Ussuriysky Urban District, Primorsky Region, 04.05.2022. Photo by M. V. Maslov in An increase in the number of records of the brown-eared bulbul Microscelis amaurotis in the Russian Far East in recent years
Рис. 1. А — рыжеухий бюΛьбюΛь на боярышнике, с. Δазо, Приморский край, 5.11.2019. Фото В. П. Шохрина; B — рыжеухий бюΛьбюΛь пьет сок кΛена приречного, с. Каймановка, Уссурийский гороΑской округ, Приморский край, 03.04.2022. Фото À. А. БеΛяева; C — рыжеухий бюΛьбюΛь кормится ягоΑами Αевичьего винограΑа пятиΛисточкового, г. ВΛаΑивосток, 02.01.2020. Фото А. П. ХоΑакова; D — рыжеухий бюΛьбюΛь, кΛ. ФореΛевый, окрестности с. ФиΛипповка, Хасанский район, Приморский край, 01.03.2018. Фото Ю. А. Àармана; E — рыжеухий бюΛьбюΛь кормится ягоΑами бархата амурского, г. ВΛа- Αивосток, 06.11.2019. Фото А. В. ВяΛкова; F — рыжеухий бюΛьбюΛь, с. Каймановка, Уссурийский гороΑской округ, Приморский край, 04.05.2022. Фото М. В. МасΛова Fig. 1. A — brown-eared bulbul on a hawthorn tree, Lazo village, Primorsky Region, 5.11.2019. Photo by V. P. Shokhrin; B — brown-eared bulbul drinks the juice of an Amur maple, Kaymanovka Village, Ussuriysky Urban District, Primorsky Region, 03.04.2022. Photo by D. A. Belyaev; C — brown-eared bulbul feeds on the berries of the Virginia creeper, Vladivostok, 02.01.2020. Photo by A. P. Khodakov; D — brown-eared bulbul. Forelevy spring, vicinity of Filippovka Village, Khasansky District, Primorsky Region, 01.03.2018. Photo by Yu. A. Darman; E — brown-eared bulbul feeds on the berries of an Amur cork tree, Vladivostok, 06.11.2019. Photo by A. V. Vyalkov; F — brown-eared bulbul. Kaymanovka Village, Ussuriysky Urban District, Primorsky Region, 04.05.2022. Photo by M. V. Maslov
Fig. 2 in Recent documentation of the tropical bed bug (Hemiptera: Cimicidae) in Florida since the common bed bug resurgence
Fig. 2. Auto-Montage photograph of a dissected pronotum from Cimex lectularius (A) and Cimex hemipterus (B).
Fig. 1 in Recent documentation of the tropical bed bug (Hemiptera: Cimicidae) in Florida since the common bed bug resurgence
Fig. 1. Auto-Montage photograph of an adult Cimex hemipterus male collected from Brevard County on the right and an adult Cimex lectularius male on the lef. Arrows are pointing to the lateral pronotum margin on both species.
Fig. 1 in Recent advances in our knowledge of Australian anisakid nematodes
Fig. 1. Countries where human cases of anisakidosis have been reported (Gorokhov et al., 1999; Smith, 1999; Lopez-Serrano et al., 2000; Chai et al., 2005; Kapral et al., 2009; Shamsi and Butcher, 2011).
Fig. 2 in Recent advances in our knowledge of Australian anisakid nematodes
Fig. 2. Number of published articles on anisakid nematodes (key word: Anisakidae) until 2013; based on the search on Web of Science and CABI (Gorokhov et al., 1999; Smith, 1999; Lopez-Serrano et al., 2000; Chai et al., 2005; Kapral et al., 2009; Shamsi and Butcher, 2011).
Fig. 1 in Three new records of recent benthic Foraminifera from Korea
Fig. 1. Map of three sampling stations in the southwestern part of Jeju Island (East China Sea). This map is made with Natural Earth free vector and raster map data and QGIS software v.2.18.18.
Plate 1. 1 in Three new records of recent benthic Foraminifera from Korea
Plate 1. 1. (a-d) Ammobaculites formosensis Nakamura, 1937; 1a. SEM image, side view; 1b. Digital camera image, side view; 1c. Frontal view; 1d. Apertural side view. 2. (a-d) Cylindroclavulina bradyi (Cushman, 1911); 2a-b. Side view; 2c-d. Apertural side view. 3. (a-d) Saracenaria hannoverana (Franke, 1936); 3a. Side view; 3b. Ventral view; 3c. Dorsal view; 3d. Apertural side view.
Telescopus finkeldeyi Haacke, 2013 DAMARA TIGER SNAKE Telescopus finkeldeyi Haacke 2013:281. Holotype: TM 53542 (collector J.A. van Rooyen). Type locality: "Rössing Uranium mine area, Swako- mund [sic] district (2214Db) Namibia." Global conservation status (IUCN): Not Evaluated. Global distribution: The species is known from Angola and Namibia. Ocurrences in Angola (Map 364): The species occurs in southwestern Angola. Namibe: "5 km north Namibé" [-15.20000, 12.15000] (Haacke 2013:285). Taxonomic and distributional notes: Some earlier records of T. semiannulatus polystictus in Namibia actually refer to this recently described species. MAP 364. Distribution of Telescopus finkeldeyi in Angola. in Diversity and Distribution of the Amphibians and Terrestrial Reptiles of Angola Atlas of Historical and Bibliographic Records (1840-2017)
Telescopus finkeldeyi Haacke, 2013 DAMARA TIGER SNAKE Telescopus finkeldeyi Haacke 2013:281. Holotype: TM 53542 (collector J.A. van Rooyen). Type locality: "Rössing Uranium mine area, Swako- mund [sic] district (2214Db) Namibia." Global conservation status (IUCN): Not Evaluated. Global distribution: The species is known from Angola and Namibia. Ocurrences in Angola (Map 364): The species occurs in southwestern Angola. Namibe: "5 km north Namibé" [-15.20000, 12.15000] (Haacke 2013:285). Taxonomic and distributional notes: Some earlier records of T. semiannulatus polystictus in Namibia actually refer to this recently described species. MAP 364. Distribution of Telescopus finkeldeyi in Angola.
with Hemidactylus brookii angulatus Hallowell, 1852. The species was recently recorded from Quiçama National Park in Luanda Province (M. Marques, L. Ceríaco, A. Bauer and D. Blackburn pers. obs. 2015, 2016). MAP 130. Distribution of Hemidactylus bayonii in Angola. in Diversity and Distribution of the Amphibians and Terrestrial Reptiles of Angola Atlas of Historical and Bibliographic Records (1840-2017)
with Hemidactylus brookii angulatus Hallowell, 1852. The species was recently recorded from Quiçama National Park in Luanda Province (M. Marques, L. Ceríaco, A. Bauer and D. Blackburn pers. obs. 2015, 2016). MAP 130. Distribution of Hemidactylus bayonii in Angola.
which has priority over all other available names (Lanza and Broadley 2014). More recently, Broadley et al. (2018) split Gonionotophis into four genera, with brussauxi being the only Angolan species remaining in the genus. MAP 291. Distribution of Gonionotophis brussauxi in Angola. in Diversity and Distribution of the Amphibians and Terrestrial Reptiles of Angola Atlas of Historical and Bibliographic Records (1840-2017)
which has priority over all other available names (Lanza and Broadley 2014). More recently, Broadley et al. (2018) split Gonionotophis into four genera, with brussauxi being the only Angolan species remaining in the genus. MAP 291. Distribution of Gonionotophis brussauxi in Angola.
Data of the publication: Recent Advances in Rare Earth Doped Inorganic Crystalline Materials for Quantum Information Processing
<p>Data corresponding to the figures of the publication "Recent Advances in Rare Earth Doped Inorganic Crystalline Materials for Quantum Information Processing" by N. Kunkel and Ph. Goldner (https://doi.org/10.1088/1361-648X/aa529a). A text file describes data in each compressed folder, please refer to the caption in the publication for more details. </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>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 5. What machine intelligence is (accessed 01.11.2017) http://www.ibmbigdatahub.com/blog/measuring-artificial-intelligence-quotient)
<p>There are many developed cooperative systems composed of very simple agents that at the system’s level are considered intelligent. Yang, Galis, Guo, and Liu (2003) presented an intelligent cooperative mobile multiagent system composed of simple reactive agents. The mobile agents are specialized in a computer network administration. They are endowed with knowledge retained as a set of rules which describe network administration tasks. The multiagent system could be considered intelligent based on the fact that it simulates the behavior of a human network administrator. In some cooperative systems, the member agents can organize themselves into cooperative coalitions/groups. Each coalition being able to solve cooperatively problems. Iantovics and Zamfirescu (2013) presented such an adaptive cooperative multiagent system, able to reorganize autonomously the coalitions in order to solve more intelligently problems. The biological and artificial intelligence are by a completely different type (Figure 5). Recently, the biological intelligence is the source of inspiration for the development of many intelligent artificial systems and different problem-solving algorithms.</p>
SNP call data for: The current epidemic of the barley pathogen Ramularia collo-cygni derives from a recent population expansion and shows global admixture
<p>Ramularia Leaf Spot is becoming an ever increasing problem in main barley growing regions since the 1980s, causing up to 70% yield loss in extreme cases. Yet, the causal agent <em>Ramularia collo-cygni</em>, remains poorly studied. The diversity of the pathogen in the field thus far remains unknown. Furthermore, it is unknown to which extend the pathogen has a sexual reproductive cycle. To date, the teleomorph of <em>R. collo-cygni</em> has not been observed.</p> <p>To study the genetic diversity of <em>R. collo-cygni </em>and to get more insights into its biology, we sequenced the genomes of 19 <em>R. collo-cygn</em>i isolates from multiple geographic locations and diverse hosts. Here we share the SNP call data as well as the reference genome.</p> <p>The reference genome files and assembly can be found on ENI: GCA_900074925.1</p> <p>https://www.ebi.ac.uk/ena/data/view/GCA_900074925.1</p> <p>The raw sequence data is also available through ENI: ERX2296228</p> <p>https://www.ebi.ac.uk/ena/data/view/ERX2296228</p>
Figure 3. The effective population size through recent time for 3 in Comparative analyses of past population dynamics between two subterranean zokor species and the response to climate changes
Figure 3. The effective population size through recent time for 3 clades of Gansu zokor (Eospalax cansus).
Fig. 2 in Broad tapeworms (Diphyllobothriidae), parasites of wildlife and humans: Recent progress and future challenges
Fig. 2. Microphotographs of permanent slides of diphyllobothriid tapeworms. A – Dibothriocephalus alasensis from Canis familiaris, Hooper Bay, Alaska, March 18, 1958; fixed after relaxation by R. Rausch (MSBP 17029). B – Dibothriocephalus latus from Homo sapiens, Chile, 19 November 2012; contracted clinical sample fixed with 'cold' fixative by T. Weitzel. C – Dibothriocephalus dalliae from C. familiaris, Alaska, 5 November 1970; fixed after relaxation by R. Rausch (MSBP 26232). D – Diphyllobothrium lanceolatum from Erignathus barbatus, Greenland, 7 October 1987; collected by P. Baagoe (SNM). E – Dibothriocephalus cf. nihonkaiensis from Homo sapiens, Newtok, Alaska, 26 March 1967; fixed after relaxation by R. Rausch (MSBP 26244). F – Diphyllobothrium stemmacephalum from Lagenorhynchus acutus, Wellfleet Bay, Cape Cod, Massachusetts, 1998; collected by J.N. Caira. G – Diphyllobothrium mobile from Ommatophoca rossii, Antarctica, 11 August 1901, Deutsche Südpolar- Expedition; collected by E. Dagobert von Drygalski (ZNB 5188). H – Dibothriocephalus ursi from Ursus arctos middendorfi, Karluk Lake, Kodiak Island, 9 October 1952; fixed after relaxation by R. Rausch; paratype (MSBP 3269). I – Schistocephalus sp. from C. familiaris, Newtok, Alaska, 4 April 1958; fixed after relaxation by R. Rausch (MSBP 17939). Acronyms of museum collections: MSBP – Museum of Southwestern Biology, Division of Parasitology, University of New Mexico, Albuquerque, New Mexico, U.S.A.; SNM – Swedish Museum of Natural History, Stockholm, Sweden; ZNB – Zoologische Museum Berlin, Berlin, Germany.
Figure 2 in Recently resighted population of Blue-breasted Quail (Synoicus chinensis) in and around East Kolkata Wetland is under threat due to development activities
Figure 2. (A) A male Blue-breasted Quails (BBQ) photographed at Baruipur (Photo: Amitava Majumder); (B) A female BBQ (Photo: Amitava Majumder); (C) A flock of BBQ (Photo: Anindya Naskar); (D) Same habitat wherein BBQ sighted in 2019 showing deteriorated condition and movement of heavy vehicles during filling up of wet grasslands (Photo: Anindya Naskar).
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.