Institution
Al Akhawayn University
Education•Ifrane, Morocco•
About: Al Akhawayn University is a education organization based out in Ifrane, Morocco. It is known for research contribution in the topics: Renewable energy & Smart grid. The organization has 410 authors who have published 689 publications receiving 12893 citations. The organization is also known as: AUI.
Papers published on a yearly basis
Papers
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Broad Institute1, Harvard University2, University of Tübingen3, Max Planck Society4, University of Mainz5, University of Washington6, University of California, Berkeley7, Massachusetts Institute of Technology8, Stockholm University9, University of Adelaide10, The Heritage Foundation11, National Museum of Natural History12, University of Edinburgh13, Sultan Qaboos University14, University of Costa Rica15, University of Antioquia16, Rambam Health Care Campus17, University of Pécs18, Al Akhawayn University19, Catholic University of the Sacred Heart20, University of Oxford21, Belgorod State University22, University of Toronto23, University of Buenos Aires24, University of Bern25, Russian Academy of Sciences26, Paul Sabatier University27, North-Eastern Federal University28, University of Chicago29, University of Arizona30, Stony Brook University31, University of Bergen32, Illumina33, Sofia Medical University34, Bashkir State University35, University of Cambridge36, Vilnius University37, Estonian Biocentre38, University of Strasbourg39, Amgen40, University College London41, Gladstone Institutes42, University of Tartu43, University of Oulu44, Muhimbili University of Health and Allied Sciences45, University of Palermo46, University of Chile47, University of Tarapacá48, Academy of Sciences of Uzbekistan49, Armenian National Academy of Sciences50, University of North Texas51, University of Santiago de Compostela52, University of Kharkiv53, Higher University of San Andrés54, Novosibirsk State University55, Leidos56, Lebanese American University57, University of Split58, University of Pennsylvania59, Banaras Hindu University60, Centre for Cellular and Molecular Biology61, Estonian Academy of Sciences62, Pompeu Fabra University63, Howard Hughes Medical Institute64
TL;DR: It is shown that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, who contributed ancestry to all Europeans but not to Near Easterners; ancient north Eurasians related to Upper Palaeolithic Siberians; and early European farmers, who were mainly of Near Eastern origin but also harboured west Europeanhunter-gatherer related ancestry.
Abstract: We sequenced the genomes of a ∼7,000-year-old farmer from Germany and eight ∼8,000-year-old hunter-gatherers from Luxembourg and Sweden. We analysed these and other ancient genomes with 2,345 contemporary humans to show that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, who contributed ancestry to all Europeans but not to Near Easterners; ancient north Eurasians related to Upper Palaeolithic Siberians, who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunter-gatherer related ancestry. We model these populations' deep relationships and show that early European farmers had ∼44% ancestry from a 'basal Eurasian' population that split before the diversification of other non-African lineages.
1,077 citations
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Bradley University1, University of Tartu2, National Institutes of Health3, University of California4, Pontifical Catholic University of Chile5, University of Louisville6, University of Latvia7, Pennsylvania State University8, Slovak Academy of Sciences9, University of San Carlos10, University of Malta11, Ghent University12, Clemson University13, Laval University14, University of Buenos Aires15, Osaka University16, Illinois State University17, National Autonomous University of Mexico18, University of Brasília19, University of Western Australia20, University of Lima21, Boğaziçi University22, University of Kassel23, York University24, University of Queensland25, Åbo Akademi University26, Al Akhawayn University27, University of Hawaii at Manoa28, University of Catania29, University of Otago30, University of Dhaka31, Chemnitz University of Technology32, Knox College33, Comenius University in Bratislava34, University of Rijeka35, University of Malaya36, Vilnius University37, American University of Beirut38, Kwangju Health College39, University of Salzburg40, Utrecht University41, National Computerization Agency42, City University of Hong Kong43, University of Idaho44, University of Zimbabwe45, University of Lisbon46, University of Central Lancashire47, Loyola Marymount University48, University of KwaZulu-Natal49, University of Granada50, University of Botswana51, Babeș-Bolyai University52, University of Cyprus53, University of Belgrade54, KPMG55, University of Montpellier56, University of Zurich57, University of Alabama58, Baylor University59, Queen's University Belfast60, University of Ljubljana61, University of Haifa62, University of La Serena63, Florida Atlantic University64, University of California, Davis65, University of Dar es Salaam66, Ramapo College67, Cyprus College68, Middle East Technical University69, Nicolaus Copernicus University in Toruń70, University of the South Pacific71, Vrije Universiteit Brussel72, University at Albany, SUNY73, University of the Aegean74, University of Lethbridge75, University of Vienna76, University of Hong Kong77, Yuan Ze University78, Charles University in Prague79, Chonnam National University80, Indian Institutes of Technology81
TL;DR: The Big Five Inventory (BFI) is a self-report measure designed to assess the high-order personality traits of Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness as discussed by the authors.
Abstract: The Big Five Inventory (BFI) is a self-report measure designed to assess the high-order personality traits of Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness. As part of the International Sexuality Description Project, the BFI was translated from English into 28 languages and administered to 17,837 individuals from 56 nations. The resulting cross-cultural data set was used to address three main questions: Does the factor structure of the English BFI fully replicate across cultures? How valid are the BFI trait profiles of individual nations? And how are personality traits distributed throughout the world? The five-dimensional structure was robust across major regions of the world. Trait levels were related in predictable ways to self-esteem, sociosexuality, and national personality profiles. People from the geographic regions of South America and East Asia were significantly different in openness from those inhabiting other world regions. The discussion focuses on limitations of t...
876 citations
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TL;DR: The findings suggest that hypertension observed in this region would be in a large part related to diabetes.
532 citations
Harvard University1, Broad Institute2, University of Tübingen3, Max Planck Society4, University of Mainz5, University of Washington6, University of California, Berkeley7, Massachusetts Institute of Technology8, Stockholm University9, University of Adelaide10, The Heritage Foundation11, National Museum of Natural History12, University of Edinburgh13, Sultan Qaboos University14, University of Costa Rica15, University of Antioquia16, Rambam Health Care Campus17, University of Pécs18, Al Akhawayn University19, Catholic University of the Sacred Heart20, University of Oxford21, Belgorod State University22, University of Toronto23, University of Buenos Aires24, University of Bern25, Russian Academy of Sciences26, Paul Sabatier University27, North-Eastern Federal University28, University of Chicago29, University of Arizona30, Stony Brook University31, University of Bergen32, Illumina33, Sofia Medical University34, Bashkir State University35, University of Cambridge36, Vilnius University37, Estonian Biocentre38, University of Strasbourg39, Amgen40, University College London41, Gladstone Institutes42, University of Tartu43, University of Oulu44, Muhimbili University of Health and Allied Sciences45, University of Palermo46, University of Chile47, University of Tarapacá48, Academy of Sciences of Uzbekistan49, Armenian National Academy of Sciences50, University of North Texas51, University of Santiago de Compostela52, University of Kharkiv53, Higher University of San Andrés54, Novosibirsk State University55, Leidos56, Lebanese American University57, University of Split58, University of Pennsylvania59, Banaras Hindu University60, Centre for Cellular and Molecular Biology61, Estonian Academy of Sciences62, Pompeu Fabra University63, Howard Hughes Medical Institute64
TL;DR: The authors showed that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, ancient north Eurasians related to Upper Palaeolithic Siberians, who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunters-gatherer related ancestry.
Abstract: We sequenced the genomes of a ∼7,000-year-old farmer from Germany and eight ∼8,000-year-old hunter-gatherers from Luxembourg and Sweden. We analysed these and other ancient genomes with 2,345 contemporary humans to show that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, who contributed ancestry to all Europeans but not to Near Easterners; ancient north Eurasians related to Upper Palaeolithic Siberians, who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunter-gatherer related ancestry. We model these populations' deep relationships and show that early European farmers had ∼44% ancestry from a 'basal Eurasian' population that split before the diversification of other non-African lineages.
442 citations
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TL;DR: The validity-guided VGC algorithm uses cluster-validity information to guide a fuzzy (re)clustering process toward better solutions, and VGC's performance approaches that of the (supervised) k-nearest-neighbors algorithm.
Abstract: When clustering algorithms are applied to image segmentation, the goal is to solve a classification problem. However, these algorithms do not directly optimize classification duality. As a result, they are susceptible to two problems: 1) the criterion they optimize may not be a good estimator of "true" classification quality, and 2) they often admit many (suboptimal) solutions. This paper introduces an algorithm that uses cluster validity to mitigate problems 1 and 2. The validity-guided (re)clustering (VGC) algorithm uses cluster-validity information to guide a fuzzy (re)clustering process toward better solutions. It starts with a partition generated by a soft or fuzzy clustering algorithm. Then it iteratively alters the partition by applying (novel) split-and-merge operations to the clusters. Partition modifications that result in improved partition validity are retained. VGC is tested on both synthetic and real-world data. For magnetic resonance image (MRI) segmentation, evaluations by radiologists show that VGC outperforms the (unsupervised) fuzzy c-means algorithm, and VGC's performance approaches that of the (supervised) k-nearest-neighbors algorithm.
436 citations
Authors
Showing all 418 results
Name | H-index | Papers | Citations |
---|---|---|---|
Satoshi Kawata | 87 | 632 | 31450 |
Zouheir Sekkat | 34 | 133 | 4536 |
El-Houssaine Aghezzaf | 29 | 199 | 2924 |
Antonio Rodríguez Andrés | 26 | 91 | 2151 |
Philip C. Abbott | 24 | 96 | 2339 |
Allal Barroug | 22 | 34 | 1764 |
Hidekazu Ishitobi | 21 | 51 | 1131 |
Ahmed Legrouri | 20 | 46 | 1147 |
Mohammed Boulmalf | 18 | 83 | 1034 |
James C. Peyton Jones | 18 | 69 | 945 |
Faridahwati Mohd Shamsudin | 17 | 90 | 968 |
Muhammad Ikram | 17 | 45 | 878 |
Mazin A. M. Al Janabi | 15 | 54 | 587 |
A. Bensaid | 15 | 26 | 2088 |
Dounya Barrit | 14 | 23 | 1232 |