3 resultados para PALMA AFRICANA

em Indian Institute of Science - Bangalore - Índia


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Elephants use vocalizations for both long and short distance communication. Whereas the acoustic repertoire of the African elephant (Loxodonta africana) has been extensively studied in its savannah habitat, very little is known about the structure and social context of the vocalizations of the Asian elephant (Elephas maximus), which is mostly found in forests. In this study, the vocal repertoire of wild Asian elephants in southern India was examined. The calls could be classified into four mutually exclusive categories, namely, trumpets, chirps, roars, and rumbles, based on quantitative analyses of their spectral and temporal features. One of the call types, the rumble, exhibited high structural diversity, particularly in the direction and extent of frequency modulation of calls. Juveniles produced three of the four call types, including trumpets, roars, and rumbles, in the context of play and distress. Adults produced trumpets and roars in the context of disturbance, aggression, and play. Chirps were typically produced in situations of confusion and alarm. Rumbles were used for contact calling within and among herds, by matriarchs to assemble the herd, in close-range social interactions, and during disturbance and aggression. Spectral and temporal features of the four call types were similar between Asian and African elephants.

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We consider the problem of developing privacy-preserving machine learning algorithms in a dis-tributed multiparty setting. Here different parties own different parts of a data set, and the goal is to learn a classifier from the entire data set with-out any party revealing any information about the individual data points it owns. Pathak et al [7]recently proposed a solution to this problem in which each party learns a local classifier from its own data, and a third party then aggregates these classifiers in a privacy-preserving manner using a cryptographic scheme. The generaliza-tion performance of their algorithm is sensitive to the number of parties and the relative frac-tions of data owned by the different parties. In this paper, we describe a new differentially pri-vate algorithm for the multiparty setting that uses a stochastic gradient descent based procedure to directly optimize the overall multiparty ob-jective rather than combining classifiers learned from optimizing local objectives. The algorithm achieves a slightly weaker form of differential privacy than that of [7], but provides improved generalization guarantees that do not depend on the number of parties or the relative sizes of the individual data sets. Experimental results corrob-orate our theoretical findings.

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The Asian elephant Elephas maximus and the African elephant Loxodonta africana that diverged 5-7 million years ago exhibit differences in their physiology, behaviour and morphology. A comparative genomics approach would be useful and necessary for evolutionary and functional genetic studies of elephants. We performed sequencing of E. maximus and map to L. africana at similar to 15X coverage. Through comparative sequence analyses, we have identified Asian elephant specific homozygous, non-synonymous single nucleotide variants (SNVs) that map to 1514 protein coding genes, many of which are involved in olfaction. We also present the first report of a high-coverage transcriptome sequence in E. maximus from peripheral blood lymphocytes. We have identified 103 novel protein coding transcripts and 66-long non-coding (lnc)RNAs. We also report the presence of 181 protein domains unique to elephants when compared to other Afrotheria species. Each of these findings can be further investigated to gain a better understanding of functional differences unique to elephant species, as well as those unique to elephantids in comparison with other mammals. This work therefore provides a valuable resource to explore the immense research potential of comparative analyses of transcriptome and genome sequences in the Asian elephant.