Discerning the origins of the Negritos, First Sundaland People : deep divergence and archaic admixture

Human presence in Southeast Asia dates back to at least40,000 years ago, when the current islands for meda continental shelf called Sundaland. In the Philippine Islands, Peninsular Malaysia, and Andaman Islands, there exist indigenous groups collectively called Negritos whose ancestry can be traced to the “First Sundaland People.” To understand the relationship between these Negrito groupsand theirdemographic histories, wegeneratedgenome-wide single nucleotide polymorphism datain the Philippine Negritos and compared them with existing data from other populations. Phylogenetic tree analyses show that Negritos are basal to other East and Southeast Asians, and that they diverged from West Eurasians at least 38,000 years ago. We also found relatively high traces of Denisovan admixture in the Philippine Negritos, but not in the Malaysian and Andamanese groups, suggesting independent introgression and/or parallel losses involving Denisovan introgressed regions. Shared genetic loci between all three Negrito groups could be related to skin pigmentation, height, facial morphology and malarial resistance. These results show the unique status of Negrito groups as descended from the First Sundaland People

Instance selection of linear complexity for big data

Over recent decades, database sizes have grown considerably. Larger sizes present new challenges, because machine learning algorithms are not prepared to process such large volumes of information. Instance selection methods can alleviate this problem when the size of the data set is medium to large. However, even these methods face similar problems with very large-to-massive data sets. In this paper, two new algorithms with linear complexity for instance selection purposes are presented. Both algorithms use locality-sensitive hashing to find similarities between instances. While the complexity of conventional methods (usually quadratic, O(n2), or log-linear, O(nlogn)) means that they are unable to process large-sized data sets, the new proposal shows competitive results in terms of accuracy. Even more remarkably, it shortens execution time, as the proposal manages to reduce complexity and make it linear with respect to the data set size. The new proposal has been compared with some of the best known instance selection methods for testing and has also been evaluated on large data sets (up to a million instances).Supported by the Research Projects TIN 2011-24046 and TIN 2015-67534-P from the Spanish Ministry of Economy and Competitiveness

Adoption and impacts of ecologically-based rodent management in the Mekong Delta region

Since 1995, the Australian Center for International Agricultural Research has funded eight ecologically-based rodent management (EBRM) projects to address rodent problems in three countries in Mekong Delta Region, namely: Vietnam, Lao PDR, and Cambodia. This paper aims to analyze the adoption and impacts of EBRM among rice farmers in Cambodia, Lao PDR, and Vietnam; the facilitating and constraining factors in its adoption, and lessons learned that could guide EBRM implementation in the future. The study utilized more of a qualitative approach anchored on an impact pathway framework. Data were gathered through focused group discussions among farmers from 19 villages, key informant interviews among key cooperators from collaborating agencies, and review of project documents and scientific papers published from the projects in the three countries. The ACIAR rodent control projects have brought about widespread adoption and significant impacts- economic, environmental, and socio-cultural- of EBRM in Vietnam but were limited in Lao PDR and Cambodia. The interplay of political, socio-cultural, historical, and economic factors is critical in the adoption of EBRM, and therefore, must be considered in promoting EBRM. © 2015, University of the Philippines Los Banos. All rights reserved