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295 results for “approximation”
FIGURE 6. Macrorhynchia whiteleggei. Colony approximately 15 in New species, new records and redescriptions of Thecate hydroids (Cnidaria: Hydrozoa: Leptothecata) from Southern Australia
FIGURE 6. Macrorhynchia whiteleggei. Colony approximately 15 cm high, in situ photograph, Popes Eye reef, southern Port Phillip, depth 12 m, September 2008.
PLATE 64. Douglassia spp. Map & Lineup. Fig. 1. Approximate known localities. Fig. 2. Holotype, 7.0 x 3.0 in Taxonomic review of tropical western Atlantic shallow water Drilliidae (Mollusca: Gastropoda: Conoidea) including descriptions of 100 new species
PLATE 64. Douglassia spp. Map & Lineup. Fig. 1. Approximate known localities. Fig. 2. Holotype, 7.0 x 3.0 mm, D. bealiana (Schwengel & McGinty, 1942) (ANSP 178702). Fig. 3. Paratype, 13.2 x 5.7 mm, D. enae (Bartsch, 1934) (USNM 429205a). Fig. 4. Holotype, 12.1 x 5.1 mm, D. antillensis, new species (USNM 1291338). Fig. 5. Holotype, 10.3 x 4.4 mm, D. moratensis, new species (USNM 1291340). Fig. 6. Holotype, 10.0 x 4.6 mm, D. curasub (USNM 1231397). Fig. 7. Holotype, 7.9 x 3.5 mm, D. minervaensis (MZSP 122065).
PLATE 57. Decoradrillia spp. map & lineup. Fig. 1. Approximate known localities. Fig. 2. Holotype, 16.1 x 6.2 in Taxonomic review of tropical western Atlantic shallow water Drilliidae (Mollusca: Gastropoda: Conoidea) including descriptions of 100 new species
PLATE 57. Decoradrillia spp. map & lineup. Fig. 1. Approximate known localities. Fig. 2. Holotype, 16.1 x 6.2 mm, D. harlequina, new species (USNM 1291335). Fig. 3. Holotype, 22.0 x 8.5 mm, D. colorea, new species (MZSP 30975). Fig. 4. Possible syntype, 26.2 x 9.7 mm, D. pulchella (Reeve, 1845) (NHMUK 1984156). Image courtesy Harry Taylor, NHMUK Photographic Unit. Fig. 5. Holotype, 18.3 x 6.9 mm, D. festiva, new species (MZSP 122062). Fig. 6. Holotype, 12.0 x 4.3 mm, D. interstincta, new species (USNM 1291337).
PLATE 16. Bellaspira spp. map and lineup. Fig. 1. Approximate known localities. Fig. 2. Holotype, 10.3 x 4.3 in Taxonomic review of tropical western Atlantic shallow water Drilliidae (Mollusca: Gastropoda: Conoidea) including descriptions of 100 new species
PLATE 16. Bellaspira spp. map and lineup. Fig. 1. Approximate known localities. Fig. 2. Holotype, 10.3 x 4.3 mm, B. stahlschmidti, new species (MZSP 122054). Fig. 3. Holotype, 7.4 x 3.5 mm, B. amplicostata, new species (UF 449328). Fig. 4. Holotype, 6.8 x 3.3 mm, B. tricolor, new species (MNHN IM-2012-28007). Fig. 5. Holotype, 6.5 x 2.4 mm, B. hannyae (Jong & Coomans, 1988) (ZMA 3.87.098), photo courtesy of Marien Faber. Fig. 6. Holotype, 5.4 x 2.2 mm, B. minutissima, new species (ANSP 368731). Fig. 7. Paratype, 13.1 x 5.2 mm, B. margaritensis McLean & Poorman, 1970, (USNM 679564). Fig. 8. Holotype, 14.5 x 5.5 mm, B. barbadensis, new species (USNM 900086). Fig. 9. Holotype, 12.8 x 4.9 mm, B. rosea, new species (MZSP 122053). Fig. 10. Non-type, 11.5 x 4.3 mm, B. pentagonalis (Dall, 1889) off Daytona, Volusia Co., E Florida (USNM 900079). Fig. 11. Holotype, 10.3 x 4.6 mm, B. aurantiaca, new species (UF 355560).
FIGURES 13–18. Sulawesi Onthophagus species, dorsal forebody. 13, O. bisscrutator, holotype male from Toraut. 14, O. scrutator, male from Moramo. 15, O. bongkudai, holotype male from Moajat 16, paratype female. 17, O. sangirensis, male from Toraut.18, O. sangirensis, female from Tangkoko. Scale lines approximately 1 in Sulawesi Onthophagus: seven new species in select groups (Coleoptera: Scarabaeidae: Scarabaeinae)
FIGURES 13–18. Sulawesi Onthophagus species, dorsal forebody. 13, O. bisscrutator, holotype male from Toraut. 14, O. scrutator, male from Moramo. 15, O. bongkudai, holotype male from Moajat 16, paratype female. 17, O. sangirensis, male from Toraut.18, O. sangirensis, female from Tangkoko. Scale lines approximately 1 mm.
FIGURES 25–30. Sulawesi Onthophagus species, dorsal forebody. 25, O. sopu, holotype male from Sopu. 26, O. sopu, paratype male from Sopu. 27, O. manguliensis, male from Mangoli. 28, O. annulopunctatus, paratype male from Mogogonipa. 29, O. hollowayi, holotype male from Dumoga. 30, O. seseba, holotype male from Batui. Scale lines approximately 1 in Sulawesi Onthophagus: seven new species in select groups (Coleoptera: Scarabaeidae: Scarabaeinae)
FIGURES 25–30. Sulawesi Onthophagus species, dorsal forebody. 25, O. sopu, holotype male from Sopu. 26, O. sopu, paratype male from Sopu. 27, O. manguliensis, male from Mangoli. 28, O. annulopunctatus, paratype male from Mogogonipa. 29, O. hollowayi, holotype male from Dumoga. 30, O. seseba, holotype male from Batui. Scale lines approximately 1 mm.
"Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images" - Code
<p>A new method for automatic optic disc localization and segmentation is presented. The localization procedure combines vascular and brightness information to provide the best estimate of the optic disc center which is the starting point for the segmentation algorithm. A detection rate of 99.58% and 100% was achieved for the Messidor and ONHSD databases, respectively. A simple circular approximation to the optic disc boundary is proposed based on the maximum average contrast between the inner and outer ring of a circle centered on the estimated location. An average overlap coefficient of 0.890 and 0.865 was achieved for the same datasets, outperforming other state of the art methods. The results obtained confirm the advantages of using a simple circular model under non ideal conditions as opposed to more complex deformable models.</p>
Data from: Inferring state-dependent diversification rates using approximate Bayesian computation (ABC)
<p><span>State-dependent speciation and extinction (SSE) models provide a framework for quantifying whether species traits have an impact on evolutionary rates and how this shapes the variation in species richness among clades in a phylogeny. However, SSE models are becoming increasingly complex, limiting the application of likelihood-based inference methods. Approximate Bayesian computation (ABC), a likelihood-free approach, is a potentially powerful alternative for estimating parameters. One of the key challenges in using ABC is the selection of efficient summary statistics, which can greatly affect the accuracy and precision of the parameter estimates. In state-dependent diversification models, summary statistics need to capture the complex relationships between rates of diversification and species traits. Here, we develop an ABC framework to estimate state-dependent speciation, extinction and transition rates in the BiSSE (binary state dependent speciation and extinction) model. Using different sets of candidate summary statistics, we then compare the inference ability of ABC with that of using likelihood-based maximum likelihood (ML) and Markov chain Monte Carlo (MCMC) methods. Our results show the ABC algorithm can accurately estimate state-dependent diversification rates for most of the model parameter sets we explored. The inference error of the parameters associated with the species-poor state is larger with ABC than in the likelihood estimations only when the speciation rate is highly asymmetric between the two states (</span><em><span>λ</span></em><sub><span>1</span></sub><span> / <em>λ</em><sub>0 </sub></span><span>= 5). Furthermore, we find that the combination of normalized lineage-through-time (nLTT) statistics and phylogenetic signal in binary traits (Fitz and Purvis’s <em>D</em>) constitute efficient summary statistics for the ABC method. By providing insights into the selection of suitable summary statistics, our work aims to contribute to the use of the ABC approach in the development of complex state-dependent diversification models, for which a likelihood is not available.</span></p>
Data from: Inferring state-dependent diversification rates using approximate Bayesian computation (ABC)
<p>State-dependent speciation and extinction (SSE) models provide a framework for quantifying whether species traits have an impact on evolutionary rates and how this shapes the variation in species richness among clades in a phylogeny. However, SSE models are becoming increasingly complex, limiting the application of likelihood-based inference methods. Approximate Bayesian computation (ABC), a likelihood-free approach, is a potentially powerful alternative for estimating parameters. One of the key challenges in using ABC is the selection of efficient summary statistics, which can greatly affect the accuracy and precision of the parameter estimates. In state-dependent diversification models, summary statistics need to capture the complex relationships between rates of diversification and species traits. Here, we develop an ABC framework to estimate state-dependent speciation, extinction and transition rates in the BiSSE (binary state dependent speciation and extinction) model. Using different sets of candidate summary statistics, we then compare the inference ability of ABC with that of using likelihood-based maximum likelihood (ML) and Markov chain Monte Carlo (MCMC) methods. Our results show the ABC algorithm can accurately estimate state-dependent diversification rates for most of the model parameter sets we explored. The inference error of the parameters associated with the species-poor state is larger with ABC than in the likelihood estimations only when the speciation rate is highly asymmetric between the two states (<em>λ</em><sub>1</sub> / <em>λ</em><sub>0 </sub>= 5). Furthermore, we find that the combination of normalized lineage-through-time (nLTT) statistics and phylogenetic signal in binary traits (Fitz and Purvis’s <em>D</em>) constitute efficient summary statistics for the ABC method. By providing insights into the selection of suitable summary statistics, our work aims to contribute to the use of the ABC approach in the development of complex state-dependent diversification models, for which a likelihood is not available.</p>
Gaussian Approximation Potential for BNH
<p>Gaussian Approximation Potential generated over DFT and AIMD data</p>
Coupled cluster cavity Born-Oppenheimer approximation for electronic strong coupling
<p>File to recreate the findings in: Coupled cluster cavity Born-Oppenheimer approximation for electronic strong coupling</p>
Data for An Approximate Skolem Funcion Counter (AAAI-24 paper)
<div> <p>The artifact consists of the necessary data to reproduce the results reported in the AAAI-24 Paper titled "An Approximate Skolem Funcion Counter." <br><br>In particular, the artifact consists of the benchmarks, the log files generated on our computing cluster.</p> <p> </p> </div>
Analytical expression of apparent resistivity for the capacitive resistivity method beyond the quasi-static approximation
<p>We have attached the program files that generates Figures 5 and 6, comparing the previous published potencials (QS), with the newer one named Beyond Quasi Static approximation (BQS).</p>
Dataset for Operational considerations for approximating molecular assembly by Fourier transform mass spectrometry
<p>Dataset to accompany paper in Frontiers in Astronomy and Space Sciences entitled, "Operational considerations for approximating molecular assembly by Fourier transform mass spectrometry." doi: 10.3389/fspas.2024.1485483</p>
A Preliminary Investigation on the Usage of Quantum Approximate Optimization Algorithms for Test Case Selection - Online Appendix
<p>QAOA-TCS - Quantum Regression Test Case Selection <br>This repository contains all the necessary resources to reproduce the results of the QAOA-TCS method. </p> <p>Dataset Files <br>The "datasets" folder contains: <br>- "sir_programs" </p> <p>SIR Programs <br>The "datasets/sir_programs" folder contains, for each SIR program considered by this project, all the files needed to gather statement coverage, execution costs, and past fault coverage information. </p> <p>For example, in the "flex" program folder: <br>- The file "fault-matrix.txt" contains rows representing flex's test cases. Each row has columns representing different versions of the program. Each cell (i,j) contains a binary value (0 or 1) indicating whether the i-th test case detects a fault in the j-th version. This configuration is called the fault matrix and provides historical fault coverage information. <br>- The folder "json_flex" contains a folder for each test case, with files like "flexi.gcov.json" to recover statement coverage and execution costs. These files detail which basic blocks were executed and how many times, enabling the calculation of total statement coverage and execution costs for each test case. </p> <p>Source Code Files </p> <p>DIVGA.m <br>The "MATLAB/DIVGA.m" file contains the pipeline for the DIVGA algorithm. For simplicity, the statement coverage, execution costs, and fault coverage data already gathered by "Notebook.ipynb" are written into text files, which DIVGA.m reads to bypass the actual datasets. </p> <p>DIVGA.m must be reconfigured for each target program. Update parameters like M, N, and gamultiobj routine settings. Ensure H_size in line 104 is less than max{N, M} + 1. Update the denominator in line 53 based on the total number of code lines in the target program. Adjust the result reporting target files as well. </p> <p>Notebook.ipynb <br>This file includes pipelines for dataset analysis, algorithm execution, and empirical comparisons. </p> <p>It has two main sections: </p> <p>1. QAOA-TCS vs SelectQA and Classical Algorithms <br> - Pipelines analyze SIR programs and compare QAOA-TCS, SelectQA, and classical algorithms. Manual configuration is needed when changing the target program, including updating file paths for Pareto fronts and configuring frontiers to build the reference. <br> - Statistical analysis requires populating the variables "algorithm_nondom_sirprogram" with the number of non-dominated solutions found during each of the 10 runs. </p> <p>Results Files <br>The "results" folder contains the outcomes of QAOA-TCS, DIV-GA, Additional Greedy, and SelectQA after experiment execution. These files enable empirical evaluations and comparisons between the methods. </p>
Data Set For GGA24 a non-decomposable approximation for a non-additive kinetic potential
<p>Funding: National Science Center of Poland under grants no. 2023/07/X/ST4/01357 MINIATURA7.</p>
Automatic exhaustive calculations of large material space by Korringa-Kohn-Rostoker coherent approximation method --- Applied to equiatomic quaternary high entropy alloys
<p>Calculated data of equiatomic quaternary solid solution phase (high-entropy alloys) on local magnetic moment, total magnetization, magnetic phase transition temperature and residual resistivity.</p> <p>The data was added on October 28.</p>
Distribution. Sub-Saharan Africa; virtually eradicated from W Africa, and greatly reduced in C and NE Africa. The largest populations exist in Botswana, Tanzania, and Zimbabwe, which account for approximately half of the estimated number of African Wild Dogs remaining in the wild. Other populations occur in Central African Republic, Ethiopia, Kenya, Mozambique, Namibia, South Africa, Sudan, and Zambia. Potential small populations (less than 100 individuals) may exist in Cameroon, Chad, Senegal, and Somalia. in Canidae
Distribution. Sub-Saharan Africa; virtually eradicated from W Africa, and greatly reduced in C and NE Africa. The largest populations exist in Botswana, Tanzania, and Zimbabwe, which account for approximately half of the estimated number of African Wild Dogs remaining in the wild. Other populations occur in Central African Republic, Ethiopia, Kenya, Mozambique, Namibia, South Africa, Sudan, and Zambia. Potential small populations (less than 100 individuals) may exist in Cameroon, Chad, Senegal, and Somalia.
Data for "Exploring Cesium-Tellurium phase space via high-throughput calculations beyond the generalized-gradient approximation"
<p>The AiiDA archives of the high-throughput calculations presented in the paper "Exploring Cesium-Tellurium Phase Space via High-Throughput Density-Functional Theory Calculations".</p> <ul> <li>"calc_mp_Cs-Te.aiida" contains the calculations of the structures originating from the Materials Project database.</li> <li>"calc_oqmd_Cs-Te.aiida" contains the calculations of the structures originating from the open quantum materials database.</li> <li>"calc_mp_Cs-Te_manipulated.aiida" contains the calculations of the structures derived from chemically similar structures originating from the Materials Project database.</li> <li>"calc_oqmd_Cs-Te_manipulated.aiida" contains the calculations of the structures derived from chemically similar structures originating from the open quantum materials database.</li> <li>"calc_Cs5Te3_experimental.aiida" contains the calculations of the additional experimental structure added to the dataset.</li> </ul>
Optimizing Within-Distance Queries by Approximating Shapes with Maximal Bounded Boxes - Datasets
<p>Csv and sql files for the underlying data.<br> Figure 9: Calculating the distance between various number and type of shapes, i.e. from polygons, rotated and axis aligned rectangles, to points, polygons, rotated and axis aligned rectangles.<br> Table 1: Calculating distance between shapes of various complexity, i.e. points, lines, quadrilaterals, hexagons, dodecagons, icosagons, pentacontagons.<br> Table 2: Comparing the ordering of the shapes when distance operation is calculated, (a) from polygons to rectangles, (b) from rectangles to polygons.<br> Table 5 & 6: Within-distance and distance queries between (a) actual polygons, (b) their bounded rectangles, (c) actual polygons and points, (d) their bounded rectangles and points.</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.