241,465 research outputs found

    Analysis on Current Situations of Endangered P. intermedius S. Y. Chen

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    We carried out a general survey of current situations of P. intermedius S. Y. Chen. Results show that P. intermedius S. Y. Chen is distributed in Dongkeng Township, Jingnan Township and Yanxi Township. It covers an area of 262.51 hm2. The distribution areas are narrow and limited. What’s worse, it suffers from serious destruction and has been withered in large areas. Besides, according to current introduction test, it is difficult to survive in other places. In accordance with Exploring the Criteria for Endangered Categories of Bamboo Species from China put forward by Ma Naixun et al from the Research Institute of Subtropical Forestry of Chinese Academy of Forestry (RISFCAF), we propose incorporating P. intermedius S. Y. Chen into vulnerable species for protection

    Taiwanomyrme impressus Chen 1957

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    <i>Taiwanomyrme impressus</i> (Chen, 1957) <p>(Figs 2B, D, F, 3C–D, 7)</p> <p> <i>Smicromyrme impressa</i> (!) Chen 1957: 178 (key), 186, ♂ [holotype, ♂, "Kuling [Guling, Jiangxi], 18.ix.1934, O. Piel" (Heude Museum, Shanghai)].</p> <p> <i>Taiwanomyrme impressa</i> (!): Lelej 1996: 6, ♂; 2005: 76.</p> <p> <b>Diagnosis.</b> MALE. Clypeus preapically with short transversely concave area. Both carinae on scape well developed, distance between carinae more than 0.5 × scape width; flagellomere 1 slightly longer than flagellomere 2. Metasomal tergum 2 posteriorly and tergum 3 with band of dense yellow setae. Felt line on tergum 2 about 3 × as long as that on sternum 2. Volsellar cuspis apex with short sparse setae; penial valve apically hook-like. Head and metasoma black; mesosoma ferruginous-red, except sterna and inferior part of mesopleuron black; legs black. Body length 10.0– 15.3 mm. FEMALE unknown.</p> <p> <b>Material examined.</b> CHINA: Fujian, Wuyishan, 7.IX.1989, Wang Jiashe, 1♂, No. 964046 [ZJUH]; Wuyishan, 1.X.1989, Wang Jiashe, 1♂, No. 964294 [ZJUH]; Jiangxi, Guling, VIII.1936, 3 ♂, O. Piel, Nos. 34023241, 34023244, 34023245 [SEMS]; Sichuan, Emeishan, 8.VIII.1980, He Junhua, 1♂, No. 802912 [ZJUH].</p> <p> <b>Distribution.</b> China (Jiangxi and newly recorded from Fujian and Sichuan).</p> <p> <b>Remarks.</b> It is quite possible that the above three males collected at the type locality by O. Piel are paratypes of <i>Smicromyrme impressus</i> Chen.</p>Published as part of <i>Tu, Bin-Bin, Lelej, Arkady S. & Chen, Xue-Xin, 2015, Review of the genus Taiw ano my rme Tsuneki, 1993 (Hymenoptera, Mutillidae, Mutillinae), with description of two new species from China, pp. 588-600 in Zootaxa 4020 (3)</i> on page 591, DOI: 10.11646/zootaxa.4020.3.10, <a href="http://zenodo.org/record/245481">http://zenodo.org/record/245481</a&gt

    Sebastes notius Chen 1971

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    Sebastes notius Chen, 1971. Guadalupe Rockfish or Southern Rockfish. To 21.9 cm (8.6 in) SL (Chen 1971). This species has been collected at two sites: Isla Guadalupe (Chen 1971), central Baja California and in the vicinity of Banco del Tio Sam (Uncle Sam Bank) (25°35’N), southern Baja California (Rocha-Olivares 1998). Benthic; depth: 165–250 m (541–820 ft) (Chen 1971).Published as part of Love, Milton S., Bizzarro, Joseph J., Cornthwaite, Maria, Frable, Benjamin W. & Maslenikov, Katherine P., 2021, Checklist of marine and estuarine fishes from the Alaska-Yukon Border, Beaufort Sea, to Cabo San Lucas, Mexico, pp. 1-285 in Zootaxa 5053 (1) on page 110, DOI: 10.11646/zootaxa.5053.1.1, http://zenodo.org/record/557800

    Blind joint maximum likelihood channel estimation and data detection for SIMO systems

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    A blind adaptive scheme is proposed for joint maximum likelihood (ML) channel estimation and data detection of single-input multiple-output (SIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative optimisation loop. An efficient global optimisation algorithm called the repeated weighted boosting search is employed at the upper level to optimally identify the unknown SIMO channel model, and the Viterbi algorithm is used at the lower level to produce the maximum likelihood sequence estimation of the unknown data sequence. A simulation example is used to demonstrate the effectiveness of this joint ML optimisation scheme for blind adaptive SIMO systems
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