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1,066 results for “bayesian”
Raw data for "A Composite Bayesian Optimisation Framework for Material and Structural Design under Uncertainty"
<p>This dataset contains the raw data for the paper "A Composite Bayesian Optimisation Framework for Material and Structural Design under Uncertainty" (submitted) by R. P. Cardoso Coelho, A. F. Carvalho Alves, T. M. Nogueira Pires and F. M. Andrade Pires (INEGI and Faculty of Engineering of the University of Porto, Portugal).</p> <p> </p> <p>The data has been generated with the development branch of piglot - an open-source optimisation toolbox (https://github.com/CM2S/piglot). The numerical simulations have been conducted with both an in-house finite element solver (Links) and with the open-source SCA implementation CRATE (https://github.com/bessagroup/CRATE).</p>
Fig. 1 in A Bayesian analysis of the parasitic ecology in Jenynsia multidentata (Pisces: Anablepidae)
Fig. 1. Map of the sample sites, Salado Relief Channel (S.R.C.) in Samborombon Bay and the Sauce Chico River in Bahia Blanca estuary (B.B.), Argentina.
Fig. 2. Mean and the 95 in A Bayesian analysis of the parasitic ecology in Jenynsia multidentata (Pisces: Anablepidae)
Fig. 2. Mean and the 95% credibility range of Weight (W.) in grams (gr), total and standard length (TL and SL) in centimeters of Jenynsia multidentata Jenyns, 1842 in Salado River Channel (S.R.C.) and Low Sauce River of Bahia Blanca (B.B.), Argentina.
Bayesian inference of the dense matter equation of state built upon extended Skyrme interactions [Data Set]
<pre> </pre> <p>We provide the posterior distributions of the input parameters of the five main runs considered in the article "Bayesian inference of the dense matter equation of state built upon extended Skyrme interactions" (accepted to Phys. Rev. C, arXiv: 2403.19325).</p> <p>Each row in each file corresponds to one equation of state. It contains 13 input parameters of the extend Skyrme interaction that define the effective interaction and that can be used in order to construct equations of state. The input parameters (columns, from left to right) and their dimensions are: </p> <p>C_0 (MeV*fm^3); D_0 (MeV*fm^3); C_3 (MeV*fm^{3+3*sigma}); D_3 (MeV*fm^{3+3*sigma}); C_eff (MeV*fm^5); D_eff (MeV*fm^5); t_4 (MeV*fm^{5+3*beta}); t_5 (MeV*fm^{5+3*gamma}); x_4; x_5; sigma; beta; gamma.</p> <p>See the article for more details.</p>
FIG. 3. — Bayesian consensus tree inferred from concatenated chloroplast rps4 in Pterygoneurum sampaianum (Guim.) Guim.: range extension to Africa, first mentions in France, confirmation of specific status and improved morphological circumscription
FIG. 3. — Bayesian consensus tree inferred from concatenated chloroplast rps4-trnS and trnM-trnV sequence data of the analysed dataset of Pottiaceae subfam. Pottioideae, partitioned between DNA sequence and indel data. Posterior probability from BI is displayed above the branches; bootstrap support (656 replications) from ML analysis is displayed below the branches.
Fig. 1. Bayesian 50 in A phylogenetic survey of the ascomycete genus Arthrorhaphis (Arthrorhaphidaceae, Lecanoromycetes) including new species in Arthrorhaphis citrinella sensu lato
Fig. 1. Bayesian 50% majority-rule consensus tree from analysis of MSA-1, showing the placement of Arthrorhaphis as sister to Ostropales, Ostropomycetidae. Branches supported by BPP ≥ 0.95 and ML BS ≥ 70% are indicated by bold black lines; branches supported only by BPP ≥ 0.95 are indicated by bold grey lines. Numbers in brackets represent clades discussed in the text.
Fig. 2. Bayesian 50 in A phylogenetic survey of the ascomycete genus Arthrorhaphis (Arthrorhaphidaceae, Lecanoromycetes) including new species in Arthrorhaphis citrinella sensu lato
Fig. 2. Bayesian 50% majority-rule consensus tree from analysis of MSA-2, showing the basal position of the exclusively parasitic species in Arthrorhaphis. The evolution of lichenised thalli containing pulvinic acid derivatives in the A. alpina- and the A. citrinella s.l. clades is indicated by an asterisk. Branches supported by BPP ≥ 0.95 and ML BS ≥ 70% are indicated by bold black lines; branches supported only by BPP ≥ 0.95 are indicated by bold grey lines. Numbers in brackets represent clades discussed in the text. Graphical representation of species delimitations in bGMYC, bPtP and bP&P: Colours represent delimited species for each species delimitation analysis independently, but have been selected to highlight delimitations congruent across analyses. White represents missing data. The colouring scheme applies only to the current figure.
Data and software associated with the paper "Bayesian Inference of Joint Coalescence Times of Sampled Sequences"
<p>1. Data files and run logs produced for the paper "Bayesian Inference of Joint Coalescence Times of Sampled Sequences".</p> <p>2. Software script versions used in the above.</p>
Figure 6. Bayesian 90 in A survey of spiders (Arachnida: Araneae) of Prince of Wales Island, Alaska; combining morphological and DNA barcode identification techniques
Figure 6. Bayesian 90% majority rule consensus phylogram for the species Tachygyna ursina (Bishop and Crosby) and outgroup using a three partitioned model (GTR+I+G for each codon position) of a 669 bp region of the COI gene. Survey specimens are highlighted. Posterior probabilities are recorded above branches. Branch lengths from the Bayesian analysis followed by the branch lengths from the Neighbor Joining analysis, where applicable, are recorded below branches.
Figure 4. Bayesian 70 in A survey of spiders (Arachnida: Araneae) of Prince of Wales Island, Alaska; combining morphological and DNA barcode identification techniques
Figure 4. Bayesian 70% majority rule consensus phylogram for the species Parazygiella dispar (Kulczynski) and outgroup using a three partitioned model (GTR+I+G for each codon position) of a 669 bp region of the COI gene. Survey specimens are highlighted. Posterior probabilities are recorded above branches. Branch lengths from the Bayesian analysis followed by the branch lengths from the Neighbor Joining analysis, where applicable, are recorded below branches.
Figure 3. Bayesian 90 in A survey of spiders (Arachnida: Araneae) of Prince of Wales Island, Alaska; combining morphological and DNA barcode identification techniques
Figure 3. Bayesian 90% majority rule consensus phylogram for the species Hyptiotes gertschi Chamberlin and Ivie and outgroup using a three partitioned model (GTR+I+G for each codon position) of a 669 bp region of the COI gene. Survey specimens are highlighted. Posterior probabilities are recorded above branches. Branch lengths from the Bayesian analysis followed by the branch lengths from the Neighbor Joining analysis, where applicable, are recorded below branches. Specimen names include the BOLD sequence record (ex SPIAL163-10) followed by the GenBank sequence record (HQ580637) followed by the BOLD specimen number (ALASKA-02-F08) and then by the species and gene (Hyptiotes_gertschi_COI_5P)
Figure 6. A Bayesian consensus tree derived from 4,001 in A Heron (Aves: Ardeidae) from the Early Miocene St Bathans Fauna of Southern New Zealand
Figure 6. A Bayesian consensus tree derived from 4,001 trees sampled: Run 1 (mean = –546.302, s.d. = 0.099, Effective Sample Size = 3208.424); Run 2 (–546.223, 0.113, 2388.97). Support values are shown above the corresponding node.
Fig 1 in Evolutionary relationships of Macaca fascicularis fascicularis (Raffles 1821) (Primates: Cercopithecidae) from Singapore revealed by Bayesian analysis of mitochondrial DNA sequences
Fig 1. Map of Southeast Asia showing the approximate location of the new (Singapore and Bali) and GenBank sequences included in the study. Numbers correspond to the following locations (haplotype IDs in parentheses): ★, Singapore (Sing1–3); 1, Vietnam (Viet1 & 2); 2, Cambodia (Camb1 & 2); 3, Thailand (Thai1); 4, Thailand (Thai2); 5, Malaysia (Selangor1 & 2); 6, Malaysia (Johor); 7, south Sumatra, Indonesia (Sumatra1 & 2, Java1); 8, Java (Java1); 9, Kalimantan, Borneo (Borneo3); 10, Sarawak, Borneo (Borneo1); 11, Sepilok, Borneo (Borneo2); 12, Bali, Indonesia (Bali1 & 2); 13, Sibuyan, Philippines (Phil1); 14, Bangkok, Thailand (Thai3 & 4); 15, Malaysia (W. Malay); 16, Malaysia (E. Malay2); 17 Malaysia (E. Malay1);18, north Sumatra (Sumatra3–6, 9); 19, west Borneo, Indonesia (Borneo9); 20, west Borneo, Indonesia (Borneo4–7); 21, central Borneo, Indonesia (Borneo4 & 6); 22, Bangka, south Sumatra (Sumatra 7 & 8); 23, Java, Indonesia (Java2 & 3); 24, northeast Borneo, Indonesia (Borneo8); 25, Mindanao, Philippines (Phil2); 26, Timor (Timor). Several Borneo haplotypes appear in multiple locations.
Fig 4. Median-joining haplotype network for M in Evolutionary relationships of Macaca fascicularis fascicularis (Raffles 1821) (Primates: Cercopithecidae) from Singapore revealed by Bayesian analysis of mitochondrial DNA sequences
Fig 4. Median-joining haplotype network for M. fascicularis. The size of the circular nodes representing haplotypes is proportional to the number of sequences comprising the haplotype. Shading of circular nodes corresponds to general geographic groupings including Sundaic islands (white), mainland Indochina (gray), Malay Peninsula and northern Sumatra (dark gray), and Singapore (black). Haplotype identifications are presented in Table 1.
Fig 3 in Evolutionary relationships of Macaca fascicularis fascicularis (Raffles 1821) (Primates: Cercopithecidae) from Singapore revealed by Bayesian analysis of mitochondrial DNA sequences
Fig 3. Phylogenetic tree topology from Bayesian inference of 12S/tRNA-val/16S mtDNA sequences using a Birth-Death speciation tree prior, and HYK+G+I nucleotide substitution model in BEAST v2.1.3. Lettered identifications for clades are presented below the branches at major nodes. Posterior probabilities are displayed above the branches at nodes. Numbers in parentheses appearing with haplotype identifications are presented in Table 1, and correspond to numbered locations presented on the Figure 1 map. The Singapore haplotypes form two phylogenetic subgroupings, one from the Bukit Timah Nature Reserve (Sing1) and the other from the Central Catchment Nature Reserve (Sing2 & Sing3).
Fig 2 in Evolutionary relationships of Macaca fascicularis fascicularis (Raffles 1821) (Primates: Cercopithecidae) from Singapore revealed by Bayesian analysis of mitochondrial DNA sequences
Fig 2. Map of central Singapore showing the sampling locations in the Bukit Timah (BTNR) and Central Catchment (CCNR) Nature Reserves. Map created using ArcGIS® (ESRI® 2015).
Fig. 6. Bayesian inference tree for 5,179 in A new species of Tritetrabdella (Hirudinida: Hirudiniformes: Haemadipsidae) from northern Indochina
Fig. 6. Bayesian inference tree for 5,179 bp alignment positions of nuclear 18S rRNA and 28S rRNA and mitochondrial cytochrome c oxidase subunit I markers. Numbers on nodes indicate bootstrap values for maximum likelihood and Bayesian posterior probabilities.
Figure 2. Bayesian posterior probability 50 in Population genetic structure and demographic history of the Chinese endemic Mongoloniscus sinensis (Dollfus, 1901) (Isopoda: Oniscidea)
Figure 2. Bayesian posterior probability 50% majority-rule consensus tree of the M. sinensis haplotypes. Out-group was Ligia occidentalis; the map showed mitochondrial haplotype clades of Porcellio gigliotose and Trachelipus semiproiectus. The numbers above joints are the bootstrap support values of MP value, ML value, and the posterior probabilities of the BI tree, respectively (MP/ML/BI).
Figure 2. Bayesian phylogram for cytochrome c oxidase subunit I sequences. Upper Sacramento River basin haplotypes are distributed among clades A–D in Extensive diversification of pebblesnails (Lithoglyphidae: Fluminicola) in the upper Sacramento River basin, northwestern USA
Figure 2. Bayesian phylogram for cytochrome c oxidase subunit I sequences. Upper Sacramento River basin haplotypes are distributed among clades A–D. Posterior probability values ≥ 90% are shown. Upper Sacramento River basin lineages newly discovered in this study are highlighted by the larger font. Specimen codes are from Table 1.
Figure 42. Bayesian 50 in A species complex within the isopod genus Haploniscus (Crustacea: Malacostraca: Peracarida) from the Southern Ocean deep sea: a morphological and molecular approach
Figure 42. Bayesian 50% majority rule consensus tree of the 16S rDNA data set. Model choice based on AIC: TVM model with gamma distributed rates (alpha = 0.3755) and no invariant positions (see text for more details). Values above the branches are posterior proabilities of the 16S rDNA data set, values below of the 18S rDNA data set (if applicable).
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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)
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DANDI Archive for NWB datasets
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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.
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