86 research outputs found

    FIG. 4 in DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka

    No full text
    FIG. 4. Portrait of M. phillipsi sp. nov. NMSL 2021.03.02.NHPublished as part of Kusuminda, Tharaka, Mannakkara, Amani, Ukuwela, B., Kanishka D., Kruskop, V., Sergei, Amarasinghe & J., Chamara, 2022, DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka, pp. 1-17 in Acta Chiropterologica 24 (1) on page 8, DOI: 10.3161/15081109ACC2022.24.1.001, http://zenodo.org/record/773478

    FIG. 7 in DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka

    No full text
    FIG. 7. Ventral aspect of cranium of Miniopterus species in India and Sri Lanka. A — M. magnater (MHNG 1981.071); B — M. fuliginosus (ZMMU S-164504); C — M. pusillus (V/M/ERS/570); D — M. phillipsi sp. nov. (NMSL 2021.03.01.NH, holotype)Published as part of Kusuminda, Tharaka, Mannakkara, Amani, Ukuwela, B., Kanishka D., Kruskop, V., Sergei, Amarasinghe & J., Chamara, 2022, DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka, pp. 1-17 in Acta Chiropterologica 24 (1) on page 12, DOI: 10.3161/15081109ACC2022.24.1.001, http://zenodo.org/record/773478

    The conformer specific rotational spectrum of 3-phenylpropionitrile utilizing strong field coherence breaking

    No full text
    Made available in DSpace on 2017-07-27T20:15:31Z (GMT). No. of bitstreams: 2 2657.pdf: 14635 bytes, checksum: 04ecba3044c15cfcc4ec776df4b0e60b (MD5) license.txt: 4814 bytes, checksum: a3dad671d2baf2db10a2bec0f2e0c408 (MD5) Previous issue date: 6Made available in DSpace on 2018-01-29T23:03:07Z (GMT). No. of bitstreams: 3 license.txt: 4814 bytes, checksum: a3dad671d2baf2db10a2bec0f2e0c408 (MD5) 2657.pdf: 14635 bytes, checksum: 04ecba3044c15cfcc4ec776df4b0e60b (MD5) 975119.pptx: 11474285 bytes, checksum: 5641db499235101bd5555d0d37a757f3 (MD5) Previous issue date: 6The 8-18 GHz conformer specific rotational spectrum of gauche- and anti-3-phenylpropionitrile (C6H5-CH2-CH2-CN) conformers has been recorded using the strong field coherence breaking (SFCB) technique [1] with a modified line picking scheme for multiple selective excitations (MSE). As the recombination product of benzyl and cyanomethyl resonance-stabilized radicals, 3-phenylpropionitrile is a likely component of the complex organics in Titan’s atmosphere, motivating its structural characterization. Details of the modified line picking scheme, hyperfine constants and relative population ratios of the two conformers will be presented. _x000d_ _x000d_ [1] A.O Hernandez-Castillo, Chamara Abeysekera, Brian M. Hays, Timothy S. Zwier, “Broadband Multi-Resonant Strong Field Coherence Breaking as a Tool for Single Isomer Microwave Spectroscopy.” J. Chem. Phys. 145, 114203 (2016)._x000d

    FIG. 8 in DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka

    No full text
    FIG. 8. Tragus of Miniopterus species in India and Sri Lanka. A — M. magnater (ZMMU S-172585); B — M. fuliginosus (ZMMU S-164505); C — M. phillipsi sp. nov. (NMSL 2021.03.01.NH, holotype); D — M. pusillus (ZMMU S-172595)Published as part of Kusuminda, Tharaka, Mannakkara, Amani, Ukuwela, B., Kanishka D., Kruskop, V., Sergei, Amarasinghe & J., Chamara, 2022, DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka, pp. 1-17 in Acta Chiropterologica 24 (1) on page 14, DOI: 10.3161/15081109ACC2022.24.1.001, http://zenodo.org/record/773478

    FIG. 5 in DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka

    No full text
    FIG. 5. Dorsal aspect of cranium of Miniopterus species in India and Sri Lanka. A — M. magnater (MHNG 1981.071); B — M. fuliginosus (ZMMU S-164504); C — M. pusillus (V/M/ERS/570); D — M. phillipsi sp. nov. (NMSL 2021.03.01.NH, holotype)Published as part of Kusuminda, Tharaka, Mannakkara, Amani, Ukuwela, B., Kanishka D., Kruskop, V., Sergei, Amarasinghe & J., Chamara, 2022, DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka, pp. 1-17 in Acta Chiropterologica 24 (1) on page 11, DOI: 10.3161/15081109ACC2022.24.1.001, http://zenodo.org/record/773478

    FIG. 6 in DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka

    No full text
    FIG. 6. Lateral aspect of cranium and mandible of Miniopterus species in India and Sri Lanka. A — M. magnater (MHNG 1981.071); B — M. fuliginosus (ZMMU S-164504); C — M. pusillus (V/M/ERS/570); D — M. phillipsi sp. nov. (NMSL 2021.03.01.NH, holotype)Published as part of Kusuminda, Tharaka, Mannakkara, Amani, Ukuwela, B., Kanishka D., Kruskop, V., Sergei, Amarasinghe & J., Chamara, 2022, DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka, pp. 1-17 in Acta Chiropterologica 24 (1) on page 12, DOI: 10.3161/15081109ACC2022.24.1.001, http://zenodo.org/record/773478

    FIG. 1 in DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka

    No full text
    FIG. 1. Bayesian majority-rule consensus tree of the COI gene of Asian Miniopterus species. Dark circles depict nodes with Bayesian posterior probability ≥ 0.95 and maximum likelihood bootstrap support ≥ 70. The outgroup Chaerephon plicatus is not shown. Scale bar indicates the number of substitutions per sitePublished as part of Kusuminda, Tharaka, Mannakkara, Amani, Ukuwela, B., Kanishka D., Kruskop, V., Sergei, Amarasinghe & J., Chamara, 2022, DNA Barcoding and Morphological Analyses Reveal a Cryptic Species of Miniopterus from India and Sri Lanka, pp. 1-17 in Acta Chiropterologica 24 (1) on page 5, DOI: 10.3161/15081109ACC2022.24.1.001, http://zenodo.org/record/773478

    DNA barcoding and morphological analyses reveal a cryptic species of Miniopterus from India and Sri Lanka

    No full text
    Kusuminda, Tharaka, Mannakkara, Amani, Ukuwela, Kanishka D. B., Kruskop, Sergei V., Amarasinghe, Chamara J., Saikia, Uttam, Venugopal, Parvathy, Karunarathna, Mathisha, Gamage, Rajika, Ruedi, Manuel, Csorba, Gábor, Yapa, Wipula B., Patterson, Bruce D. (2022): DNA barcoding and morphological analyses reveal a cryptic species of Miniopterus from India and Sri Lanka. Acta Chiropterologica 24 (1): 1-17, DOI: 10.3161/15081109ACC2022.24.1.001, URL: http://dx.doi.org/10.3161/15081109acc2022.24.1.00

    FIG. 8 in DNA barcoding and morphological analyses reveal a cryptic species of Miniopterus from India and Sri Lanka

    No full text
    FIG. 8. Tragus of Miniopterus species in India and Sri Lanka. A — M. magnater (ZMMU S-172585); B — M. fuliginosus (ZMMU S-164505); C — M. phillipsi sp. nov. (NMSL 2021.03.01.NH, holotype); D — M. pusillus (ZMMU S-172595)Published as part of Kusuminda, Tharaka, Mannakkara, Amani, Ukuwela, Kanishka D. B., Kruskop, Sergei V., Amarasinghe, Chamara J., Saikia, Uttam, Venugopal, Parvathy, Karunarathna, Mathisha, Gamage, Rajika, Ruedi, Manuel, Csorba, Gábor, Yapa, Wipula B. & Patterson, Bruce D., 2022, DNA barcoding and morphological analyses reveal a cryptic species of Miniopterus from India and Sri Lanka, pp. 1-17 in Acta Chiropterologica 24 (1) on page 14, DOI: 10.3161/15081109ACC2022.24.1.001, http://zenodo.org/record/773478

    Self-supervised Learning for Single View Depth and Surface Normal Estimation

    No full text
    In this work we present a self-supervised learning framework to simultaneously train two Convolutional Neural Networks (CNNs) to predict depth and surface normals from a single image. In contrast to most existing frameworks which represent outdoor scenes as fronto-parallel planes at piecewise smooth depth, we propose to predict depth with surface orientation while assuming that natural scenes have piece-wise smooth normals. We show that a simple depth-normal consistency as a soft-constraint on the predictions is sufficient and effective for training both these networks simultaneously. The trained normal network provides state-of-the-art predictions while the depth network, relying on much realistic smooth normal assumption, outperforms the traditional self-supervised depth prediction network by a large margin on the KITTI benchmark.Huangying Zhan, Chamara Saroj Weerasekera, Ravi Garg, Ian Rei
    corecore