About 114 "species" of Macrothrichidae, Eurycercidae, and Chydoridae (Cladocera, Anomopoda), belonging to 39 genera, have been reported from China, with 14 species in 6 genera in Macrothrichidae, 2 species in one genus in Eurycercidae, and 98 species in 31 genera in Chydoridae. In total, 203 species in 62 genera, 13 families and 4 orders have so far been reported from the country. Of these, 187 are tentatively considered as valid, while 16 are incertae sedis. In reality, many records hide taxonomic problems that remain to be settled. Up to 10 percent of this fauna might be endemic at the species level, but we expect this number to increase pending new, comprehensive studies. No endemic genera fall to be recorded. Most of the several hundreds of taxonomic or biogeeographic papers from which this information was extracted suffer from poor or outdated taxonomy, such that up to half of all species are up for re-evaluation. Detailed morphological examination, but also provoked male production, especially in chydorids, are ways to improve identifications and should be stimulated. On the other hand, the inventory is certainly still incomplete with several tropical-subtropical taxa still to be expected in China. The extreme south and islands are among promising sites that remain to be explored, as well as extreme habitats all over the country. Molecular studies in China started around the beginning or the present decade, and should be multiplied.
We revisit the study of a wrist-mounted camera system (referred to as HandCam) for recognizing activities of hands. HandCam has two unique properties as compared to egocentric systems [10,5] (referred to as HeadCam):(1) it avoids the need to detect hands; (2) it more consistently observes the activities of hands. By taking advantage of these properties, we propose a deep-learning-based method to recognize hand states (free v.s. active hands, hand gestures, object categories), and discover object categories. Moreover, we propose a novel two-streams deep network to further take advantage of both HandCam and HeadCam. We have collected a new synchronized Hand-Cam and HeadCam dataset with 20 videos captured in three scenes for hand states recognition. Experiments show that our HandCam system consistently outperforms a deeplearning-based HeadCam method (with estimated manipulation regions) and a dense-trajectory-based [35] Head-Cam method in all tasks. We also show that HandCam videos captured by different users can be easily aligned to improve free v.s. active recognition accuracy (3.3% improvement) in across-scenes use case. Moreover, we observe that finetuning Convolutional Neural Network [14] consistently improves accuracy. Finally, our novel twostreams deep network combining HandCam and HeadCam features achieves the best performance in four out of five tasks. With more data, we believe a joint HandCam and HeadCam system can robustly log hand states in daily life.
Approximately 199 cladoceran species, 5 marine and 194 freshwater and continental saltwater species, live in China. Of these, 89 species are discussed in this paper. They belong to the 4 cladoceran orders, 10 families and 23 genera. There are 2 species in Leptodoridae; 6 species in 4 genera and 3 families in order Onychopoda; 18 species in 7 genera and 2 families in order Ctenopoda; and 63 species in 11 genera and 4 families in non-Radopoda Anomopoda. Five species might be endemic of China and three of Asia. Many records are suspect at the species level, and numerous taxonomic problems remain to be settled.
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