Institution
Stellenbosch University
Education•Stellenbosch, Western Cape, South Africa•
About: Stellenbosch University is a education organization based out in Stellenbosch, Western Cape, South Africa. It is known for research contribution in the topics: Population & Context (language use). The organization has 19165 authors who have published 42248 publications receiving 1063444 citations. The organization is also known as: Maties & University of Stellenbosch.
Papers published on a yearly basis
Papers
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Theo Vos1, Amanuel Alemu Abajobir, Kalkidan Hassen Abate2, Cristiana Abbafati3 +775 more•Institutions (305)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.
10,401 citations
TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.
9,324 citations
TL;DR: In this article, the authors show how to improve the performance of NumPy arrays through vectorizing calculations, avoiding copying data in memory, and minimizing operation counts, which is a technique similar to the one described in this paper.
Abstract: In the Python world, NumPy arrays are the standard representation for numerical data and enable efficient implementation of numerical computations in a high-level language. As this effort shows, NumPy performance can be improved through three techniques: vectorizing calculations, avoiding copying data in memory, and minimizing operation counts.
9,149 citations
University of California, Berkeley1, Stellenbosch University2, University of Jyväskylä3, University of Cambridge4, Google5, University of Toronto6, University of Birmingham7, Temple University8, Amazon.com9, University of British Columbia10, University of Georgia11, University of Oxford12, Los Alamos National Laboratory13, University of California, Irvine14
TL;DR: In this paper, the authors review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data, and their evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
Abstract: Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis. NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
7,624 citations
Australian National University1, Stockholm Resilience Centre2, University of Copenhagen3, McGill University4, Stellenbosch University5, University of Wisconsin-Madison6, Wageningen University and Research Centre7, Stockholm University8, Royal Swedish Academy of Sciences9, Potsdam Institute for Climate Impact Research10, Commonwealth Scientific and Industrial Research Organisation11, International Livestock Research Institute12, University College London13, Stockholm Environment Institute14, The Energy and Resources Institute15, University of California, San Diego16, Royal Institute of Technology17
TL;DR: An updated and extended analysis of the planetary boundary (PB) framework and identifies levels of anthropogenic perturbations below which the risk of destabilization of the Earth system (ES) is likely to remain low—a “safe operating space” for global societal development.
Abstract: The planetary boundaries framework defines a safe operating space for humanity based on the intrinsic biophysical processes that regulate the stability of the Earth system. Here, we revise and update the planetary boundary framework, with a focus on the underpinning biophysical science, based on targeted input from expert research communities and on more general scientific advances over the past 5 years. Several of the boundaries now have a two-tier approach, reflecting the importance of cross-scale interactions and the regional-level heterogeneity of the processes that underpin the boundaries. Two core boundaries—climate change and biosphere integrity—have been identified, each of which has the potential on its own to drive the Earth system into a new state should they be substantially and persistently transgressed.
7,169 citations
Authors
Showing all 19473 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Peter J. Schwartz | 147 | 647 | 107695 |
| Dan J. Stein | 142 | 1727 | 132718 |
| Carl Folke | 133 | 360 | 125990 |
| Siamon Gordon | 131 | 420 | 77948 |
| Daniel J. Klionsky | 131 | 565 | 90977 |
| Richard D. Moore | 119 | 774 | 51857 |
| David M. Richardson | 119 | 575 | 59759 |
| David Zurakowski | 117 | 1168 | 55806 |
| Pedro W. Crous | 115 | 809 | 51925 |
| Ary A. Hoffmann | 113 | 907 | 55354 |
| Mike Clarke | 113 | 1037 | 164328 |
| Douglas B. Kell | 111 | 634 | 50335 |
| Petr Pyšek | 110 | 523 | 54926 |
| Robert U. Newton | 109 | 753 | 42527 |
| Kip S. Thorne | 105 | 360 | 63475 |