Institution
Martin Luther University of Halle-Wittenberg
Education•Halle, Germany•
About: Martin Luther University of Halle-Wittenberg is a education organization based out in Halle, Germany. It is known for research contribution in the topics: Population & Liquid crystal. The organization has 20232 authors who have published 38773 publications receiving 965004 citations. The organization is also known as: MLU & University of Wittenberg.
Papers published on a yearly basis
Papers
More filters
••
University of Oldenburg1, University of Vienna2, Zoological Society of London3, University College London4, International Union for Conservation of Nature and Natural Resources5, Lincoln University (New Zealand)6, Leibniz Association7, Free University of Berlin8, University of Auckland9, Charles University in Prague10, Stellenbosch University11, Academy of Sciences of the Czech Republic12, National and Kapodistrian University of Athens13, University of Fribourg14, University of Sassari15, University of Porto16, Sapienza University of Rome17, Durham University18, University of Konstanz19, University of Concepción20, Charles Darwin Foundation21, CABI22, University of Göttingen23, Helmholtz Centre for Environmental Research - UFZ24, Martin Luther University of Halle-Wittenberg25, United States Forest Service26, Bielefeld University27, Botanical Society of Britain and Ireland28, Environment Agency29, National Museum of Natural History30, Institut national de la recherche agronomique31, University of Silesia in Katowice32
TL;DR: In this paper, the authors used a database of 45,813 first records of 16,926 established alien species and showed that the annual rate of first records worldwide has increased during the last 200 years, with 37% of all first records reported most recently (1970-2014).
Abstract: Although research on human-mediated exchanges of species has substantially intensified during the last centuries, we know surprisingly little about temporal dynamics of alien species accumulations across regions and taxa. Using a novel database of 45,813 first records of 16,926 established alien species, we show that the annual rate of first records worldwide has increased during the last 200 years, with 37% of all first records reported most recently (1970-2014). Inter-continental and inter-taxonomic variation can be largely attributed to the diaspora of European settlers in the nineteenth century and to the acceleration in trade in the twentieth century. For all taxonomic groups, the increase in numbers of alien species does not show any sign of saturation and most taxa even show increases in the rate of first records over time. This highlights that past efforts to mitigate invasions have not been effective enough to keep up with increasing globalization.
1,301 citations
••
08 Aug 2019TL;DR: A comprehensive overview and analysis of the most recent research in machine learning principles, algorithms, descriptors, and databases in materials science, and proposes solutions and future research paths for various challenges in computational materials science.
Abstract: One of the most exciting tools that have entered the material science toolbox in recent years is machine learning. This collection of statistical methods has already proved to be capable of considerably speeding up both fundamental and applied research. At present, we are witnessing an explosion of works that develop and apply machine learning to solid-state systems. We provide a comprehensive overview and analysis of the most recent research in this topic. As a starting point, we introduce machine learning principles, algorithms, descriptors, and databases in materials science. We continue with the description of different machine learning approaches for the discovery of stable materials and the prediction of their crystal structure. Then we discuss research in numerous quantitative structure–property relationships and various approaches for the replacement of first-principle methods by machine learning. We review how active learning and surrogate-based optimization can be applied to improve the rational design process and related examples of applications. Two major questions are always the interpretability of and the physical understanding gained from machine learning models. We consider therefore the different facets of interpretability and their importance in materials science. Finally, we propose solutions and future research paths for various challenges in computational materials science.
1,301 citations
••
Martin Luther University of Halle-Wittenberg1, Katholieke Universiteit Leuven2, Eppendorf (Germany)3, The Catholic University of America4, Uppsala University5, Karolinska Institutet6, Leiden University Medical Center7, Hebron University8, Radboud University Nijmegen9, Seconda Università degli Studi di Napoli10, University of São Paulo11, University of Oxford12, Medical University of Vienna13, Autonomous University of Barcelona14, Sheba Medical Center15, Ain Shams University16, Clínica Alemana17, Mount Vernon Hospital18, Bank of Cyprus19, Odense University Hospital20, University of Crete21, Marmara University22, University of Valencia23
TL;DR: This ESMO guideline is recommended to be used as the basis for treatment and management decisions, delivering a clear proposal for diagnostic and treatment measures in each stage of rectal and colon cancer and the individual clinical situations.
1,299 citations
•
27 Aug 1998TL;DR: A new algorithm to clustering in large multimedia databases called DENCLUE (DENsity-based CLUstEring) is introduced, which has a firm mathematical basis, has good clustering properties in data sets with large amounts of noise, allows a compact mathematical description of arbitrarily shaped clusters in high-dimensional data sets and is significantly faster than existing algorithms.
Abstract: Several clustering algorithms can be applied to clustering in large multimedia databases. The effectiveness and efficiency of the existing algorithms, however, is somewhat limited, since clustering in multimedia databases requires clustering high-dimensional feature vectors and since multimedia databases often contain large amounts of noise. In this paper, we therefore introduce a new algorithm to clustering in large multimedia databases called DENCLUE (DENsity-based CLUstEring). The basic idea of our new approach is to model the overall point density analytically as the sum of influence functions of the data points. Clusters can then be identified by determining density-attractors and clusters of arbitrary shape can be easily described by a simple equation based on the overall density function. The advantages of our new approach are (1) it has a firm mathematical basis, (2) it has good clustering properties in data sets with large amounts of noise, (3) it allows a compact mathematical description of arbitrarily shaped clusters in high-dimensional data sets and (4) it is significantly faster than existing algorithms. To demonstrate the effectiveness and efficiency of DENCLUE, we perform a series of experiments on a number of different data sets from CAD and molecular biology. A comparison with DBSCAN shows the superiority of our new approach.
1,298 citations
••
TL;DR: The cachectic state was predictive of 18-month mortality independent of age, NYHA class, left-ventricular ejection fraction, and peak oxygen consumption, and a subset of patients at extremely high risk of death was identified.
1,279 citations
Authors
Showing all 20466 results
Name | H-index | Papers | Citations |
---|---|---|---|
Niels Birbaumer | 142 | 835 | 77853 |
Michael Schmitt | 134 | 2007 | 114667 |
Niels E. Skakkebæk | 127 | 596 | 59925 |
Stefan D. Anker | 117 | 415 | 104945 |
Pedro W. Crous | 115 | 809 | 51925 |
Eric Verdin | 115 | 370 | 47971 |
Bernd Nilius | 112 | 496 | 44812 |
Josep Tabernero | 111 | 803 | 68982 |
Hans-Dieter Volk | 107 | 784 | 46622 |
Dan Rujescu | 106 | 552 | 60406 |
John I. Nurnberger | 105 | 522 | 51402 |
Ulrich Gösele | 102 | 603 | 46223 |
Wolfgang J. Parak | 102 | 469 | 43307 |
Martin F. Bachmann | 100 | 415 | 34124 |
Munir Pirmohamed | 97 | 675 | 39822 |