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1,641 results for “similarity”
LCCSS: A Similarity Metric for Identifying Similar Test Code
<p>Apresentação do artigo "LCCSS: A Similarity Metric for Identifying Similar Test Code" para o SBCARS 2020.</p>
SemEval-2020 Task 3: Graded Word Similarity in Context
<p>For this tasks we ask participants to build systems that try to predict the effect that context has in human perception of similarity of words.</p> <p>We have seen very interesting work that uses local context to predict <strong>discrete</strong> changes in meaning: the different senses of a polysemous word. However context also has more subtle, <strong>continuous</strong> (<strong>graded</strong>) effects on meaning, even for words not necessarily considered polysemous.</p> <p>In order to be able to look at these effects we are building several datasets where we ask annotators to score how similar a pair of words are after they have read a short paragraph (which contains the two words). Each pair is scored within two of these paragraphs, allowing us to look at changes in similarity ratings due to context.</p> <p>CodaLab was used to run this task, you can see the dedicated website and the results of the participants at: https://competitions.codalab.org/competitions/20905</p>
Scale-dependent drivers of the phylogenetic structure and similarity of tree communities in northwestern Amazonia
<p><span><span><span><span><span><span><span><span><span><span><span><span>1. The extent to which historical dispersal, environmental features and geographic barriers shape the phylogenetic structure and turnover of tree communities in northwestern Amazonia at multiple spatial scales remains poorly understood. </span></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><span>2. We used 85 floristically standardized 0.1-ha plots (DBH ³ 2.5 cm) distributed in three subregions of northwestern (NW) Amazonia across three main habitat types (floodplain, swamp, terra firme forests), to hypothesize that: i) historical dispersal overcome geographical barriers, which meant low local phylogenetic relatedness and low phylogenetic turnover. ii) Geographical barriers triggered dispersal limitation, causing high local and subregional phylogenetic clustering and high regional phylogenetic turnover. iii) Edaphic properties and flooding were negatively associated to stem size and determined the tree phylogenetic structure and turnover at local and regional scales in Amazon forests.</span></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><span>3. We found that the extent to which environmental or evolutionary features shaped the phylogenetic structure and phylogenetic similarity of tree communities in NW Amazonia was scale dependent. Specifically, we show that the relative importance of environmental factors increases as spatial scale and species pool decreases. Further, we find that these results are generally robust for both adult and juvenile trees. </span></span></span></span></span></span></span></span></span></span></span></span></p> <p><i>Synthesis</i><span><span><span><span><span><span><span><span><span><span><span><span>: Our analysis at the regional (NW Amazon) scale lends support to the idea of Amazonian forests as a large metacommunity</span></span></span></span></span></span></span></span></span></span></span></span><span><span><span><span><span><span><span><span><span><span><span><span> primarily structured by historical dispersal at large spatial scales with an increasing importance of environmental factors at finer spatial scales. The convergence of ancestral lineages across </span></span></span></span></span></span></span></span></span></span></span></span><span><span><span><span><span><span><span><span><span><span><span><span>habitat types </span></span></span></span></span></span></span></span></span></span></span></span><span><span><span><span><span><span><span><span><span><span><span><span>may have been due to the relatively recent formation of geographical barriers that promoted local isolation and allopatric speciation.</span></span></span></span></span></span></span></span></span></span></span></span></p>
FIGURE 4 in A new Eumerus hoverfly (Diptera: Syrphidae) from Namibia and South Africa with notes on similar species
FIGURE 4. Eumerus lyneborgi sp. nov., male, holotype, overall appearance. A: dorsal view; B: lateral view. Scale bar = 1 mm.
FIGURE 6 in A new Eumerus hoverfly (Diptera: Syrphidae) from Namibia and South Africa with notes on similar species
FIGURE 6. Eumerus lyneborgi sp. nov., female, paratype (Namibia), overall appearance. A: dorsal view; B: lateral view. Scale bar = 2 mm.
FIGURE 1 in A new Eumerus hoverfly (Diptera: Syrphidae) from Namibia and South Africa with notes on similar species
FIGURE 1. Habitat of Eumerus lyneborgi sp. nov. at The National Botanic Garden of Namibia, Windhoek. A: unmodified highland savannah landscape (Photo: José Manuel Miquel); B: Kaoko Kobas, Cyphostemma uter (Vitaceae), where E. lyneborgi sp. nov. adults were spotted flying (Photo: Eduardo Galante).
FIGURE 11 in A new Eumerus hoverfly (Diptera: Syrphidae) from Namibia and South Africa with notes on similar species
FIGURE 11. Eumerus vestitus, females, paralectotypes, metatibiae. A: specimen with typical E. vestitus morphology; B: outlier specimen (non-conspecific?). Scale bar = 0.25 mm.
FIGURE 10 in A new Eumerus hoverfly (Diptera: Syrphidae) from Namibia and South Africa with notes on similar species
FIGURE 10. Eumerus vestitus, females, paralectotypes, frons (A, B), antennae and eyes (C, D). A, C: specimen with typical E. vestitus morphology; B, D: outlier specimen (non-conspecific?). Scale bar = 0.5 mm.
Bits x la Marató: Looking for similar patients: the AI Doctor House conquers severe COVID-19!
<p>Clinical case reports for the task Looking for similar patients: the AI Doctor House conquers severe COVID-19! at the event Bits x la Marató: https://www.fib.upc.edu/en/la-marato</p> <p> </p> <p>There is a pressing need by healthcare professionals to access information relevant to clinical practice in a more effective way. Over 80% of clinically relevant data is essentially unstructured, mainly images like MRI and clinical texts.</p> <p>One of the challenges faced by doctors is finding patients and clinical cases that show particular similarities to a given case (similar symptoms, diagnosis, treatments, or other characteristics) amongst the rapidly growing amount of clinical records and medical publications and the complexity of the data. Detection of similarities among patients or groups of patients is key for evidence-based clinical practice, the selection of patients for clinical trials, prioritizing patients for vaccination and for understanding the variability in clinical outcomes.</p> <p>From a COVID-19 point of view, AI tools should distinguish between patients with and with no risk of a severe outcome, so that clinicians could intervene promptly. <strong>Specifically, this task aims to promote the development of systems able to detect similarities among a collection of clinical case texts.</strong></p> <p> </p> <p><strong>Technology point of view:</strong></p> <p>The objective is to be able to compute and measure similarity between patients represented by their clinical case, that is, the text describing their medical condition, previous morbidities, medical tests and treatments performed, diagnosis or outcome. This very complex scenario can in principle be approached by a diversity of methodologies ranging from text similarity techniques used to detect plagiarism, clinical concept detection, or even more advanced semantic textual similarity strategies dealing with the meaning of natural language through AI.</p> <p> </p> <p><strong>Healthcare point of view:</strong></p> <p>Access to medically relevant information hidden in clinical texts is one of the principal challenges for healthcare professionals in the AI digital age. Questions such as which are the symptoms of patients with a worse outcome, given similar comorbidities, medications or procedures are very difficult to answer without systematically processing clinical texts. Even simpler, epidemiological questions like how many days have passed before COVID-19 symptoms started or if patients had travelled to certain geographical areas can only be answered efficiently by means of computational tools. Similarities between patients can aid prognosis, diagnosis and decision making, saving vital time to healthcare practitioners.</p> <p> </p> <p>If you need some help, <a href="https://medium.com/@adriensieg/text-similarities-da019229c894">here</a> is a helpful resource that will help you get started.</p> <p> </p> <p><a href="https://www.youtube.com/playlist?list=PL5uSCzf1azhBeVCHyswazImBNpIW8gYTD">YouTube playlist with our session at BITSXLAMARATÓ</a></p>
FIGURE 11 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 11.—Maximum likelihood tree depicting evolutionary relationships within Leucostethus and Colostethinae inferred from mitochondrial and nuclear genes. Bayesian posterior probabilities> 95 and bootstrap support> 70% are indicated by an asterisk (*). The inset map indicates the type locality of Leucostethus bilsa sp. nov. (yellow dot), and localities of Leucostethus sp., Epipedobates boulengeri and E. sp. (aff. darwinwallacei). Colored species next to the clades are species occurring in the Isla Gorgona and the Pacific lowlands of Ecuador.
FIGURE 10 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 10.—Sonogram of the advertisement call of adult male Leucostethus bilsa sp. nov. recorded on 5 January 2004 (tape MR2004-1-12); specimen not collected but photographed in life (see Fig. 4B). Three consecutive notes selected from near the center of a call consisting of 84 notes.
FIGURE 9 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 9.—Ventral view of hyoid plate and mandible (A) and scapular girdle (B) of the skeleton of Leucostethus bilsa sp. nov. (CJ 7775, female). Scale = 3 mm. Photos by Steven Guevara.
FIGURE 7 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 7.—Testes (indicated by arrows) and eggs of Leucostethus bilsa sp. nov., showing differences in pigmentation: (A) both testes unpigmented white (INABIO 3632); (B) one testis unpigmented white, and one testis brown (QCAZ 14700); (C) eggs (CJ 7765). Photos (A, B) by Verónica Armas-Ortiz and HMOA and (C) by Diego Acosta-López and Andrea Terán-Valdez.
FIGURE 6 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 6.—Dorsal (upper row) and ventral (lower row) aspects of preserved paratype specimens of Leucostethus bilsa sp. nov. (A) INABIO 3632, adult male; (B) INABIO 3786, adult male; (C) INABIO 3649, juvenile female; (D) INABIO 3785, sub-adult female). Note dark spotting on the chin of adult males (INABIO 3632 and 3786), in contrast to pale unmarked ventral surfaces of females (INABIO 3649 and 3785), and dark spotting extending ventro-laterally on adult male INABIO 3632. Photos by HMOA.
FIGURE 3 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 3.—Live adults of Leucostethus bilsa sp. nov. depicting variation in coloration: (A) CJ 8423, female, SVL = 25.8 mm); (B) CJ 7765, female, SVL = 25.0 mm). Photos by Diego Acosta-López.
FIGURE 4 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 4.—Live adults of Leucostethus bilsa sp. nov. showing variation: (A) QCAZ 14699, gravid adult female, SVL = 27.4 mm; (B) Not collected, adult male; (C) INABIO 3786, adult male, SVL = 23.0 mm; (D) INABIO 3785, subadult female, SVL = 22.0 mm; (E) ventral view of male (call recording MR2004-1-12) showing gular-chest marks; (F) male (CJ 7213, SVL = 22.8 mm) carrying tadpoles. Photos by GOV (A), MR (B, E), HMO (C, D), SH (F).
FIGURE 1 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 1.—(A) Map showing the collection sites of Leucostethus bilsa sp. nov.; (B) habitat of Leucostethus bilsa sp. nov. at Duchas stream. Reserva Biológica Bilsa, Provincia Esmeraldas, Ecuador. Map by Gustavo Pazmiño-Otamendi; photo by SH.
FIGURE 5 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 5.—Flash coloration, hands, and feet in Leucostethus bilsa sp. nov. (A–E) live adult female CJ 7765; (F–G) live adult male holotype CJ 8311. Note the mustard-yellow paracloacal marks on the dorsal thighs (A), and the mustard-yellow flash marks on axillae, groin, and hind limbs (B, C). Photos by Diego Acosta-López.
FIGURE 8 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 8.—High-resolution computed tomography reconstructions of the skeleton of the male holotype (CJ 8311) of Leucostethus bilsa sp. nov. (A) dorsal view; (B) lateral, dorsal and ventral view of skull; (C) coccyx, ischia and pubes in lateral view; (D) ventral view of pectoral girdle; (E) ventral view of manus; (F) ventral view of pes. Scale = 5 mm.
FIGURE 2 in A new species of Leucostethus (Anura: Dendrobatidae) from the Cordillera Mache-Chindul in northwestern Ecuador, with comments on similar Colostethus and Hyloxalus
FIGURE 2.—Live adult holotype (CJ 8311) of Leucostethus bilsa sp. nov., SVL = 24.3 mm. There is a skin lesion on the anterodorsal left thigh. Photos by Diego Acosta-López.
ScienceDex guides
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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.