1,140 research outputs found
Turbulent Pumping of Magnetic Flux Reduces Solar Cycle Memory and thus Impacts Predictability of the Sun's Activity
Prediction of the Sun's magnetic activity is important because of its effect
on space environment and climate. However, recent efforts to predict the
amplitude of the solar cycle have resulted in diverging forecasts with no
consensus. Yeates et al. (2008) have shown that the dynamical memory of the
solar dynamo mechanism governs predictability and this memory is different for
advection- and diffusion-dominated solar convection zones. By utilizing
stochastically forced, kinematic dynamo simulations, we demonstrate that the
inclusion of downward turbulent pumping of magnetic flux reduces the memory of
both advection- and diffusion-dominated solar dynamos to only one cycle;
stronger pumping degrades this memory further. Thus, our results reconcile the
diverging dynamo-model-based forecasts for the amplitude of solar cycle 24. We
conclude that reliable predictions for the maximum of solar activity can be
made only at the preceding minimum--allowing about 5 years of advance planning
for space weather. For more accurate predictions, sequential data assimilation
would be necessary in forecasting models to account for the Sun's short memory.Comment: 4 figures, 1 tabl
The African Open Science Platform: The Future of Science and Science for the Future
This document presents a draft strategy and makes the scientific case for the African Open Science Platform (AOSP). It is based on an expert group meeting held in Pretoria on 27-28 March 2018. Its purpose is to act as a framework for detailed, work on the creation of the Platform and as a basis for discussion at a stakeholder meeting to be held on 3-4 September 2018, which will lead to a definitive strategy for implementation from 2019. Expert group members at the March meeting were drawn from the following organisations: African Academy of Sciences (AAS), Academy of Science of South Africa (ASSAf), Committee on Data for Science and Technology (CODATA), International Council for Science (ICSU), National Research and Education Networks (NRENS), Research Data Alliance (RDA), South African Department of Science & Technology (DST) and National Research Foundation (NRF), Square Kilometre Array (SKA), UNESCO.
The African Open Science Platform The Future of Science and Science for the Future 4 The African Open Science Platform. The Platform’s mission is to put African scientists at the cutting edge of contemporary, data-intensive science as a fundamental resource for a modern society. Its building blocks are:
• a federated hardware, communications and software infrastructure, including policies and enabling practices, to support Open Science in the digital era;
• a network of excellence in Open Science that supports scientists & other societal actors in accumulating and using modern data resources to maximise scientific, social and economic benefit.
These objectives will be realised through seven related strands of activity:
Strand 0: Register & portal for African & related international data collections & services.
Strand 1: A federated network of computational facilities and services.
Strand 2: Software tools & advice on policies & practices of research data management.
Strand 3: A Data Science Institute at the cutting edge of data analytics and AI.
Strand 4: Priority application programmes: e.g. cities, disease, biosphere, agriculture.
Strand 5: A Network for Education & Skills in data & information.
Strand 6: A Network for Open Science Access and Dialogue.
The document also outlines the proposed governance, membership and management structure of the Platform, the approach to initial funding and the milestones in building up to the launch. The case for Open Science is based on the profound implications for society and for science, of the digital revolution and of the storm of data that it has unleashed and of the pervasive and novel means of communication that it has enabled. No state should fail to recognise this potential or to adapt their national intellectual infrastructure in exploiting benefits and minimising risks. Open Science is a vital enabler in maintaining the rigour and reliability of science; in creatively integrating diverse data resources to address complex modern challenges; in open innovation and in engaging with other societal actors as knowledge partners in tackling shared problems. It is fundamental to realisation of the Sustainable Development Goals. National science systems worldwide are struggling to adapt to this new paradigm. The alternatives are to do so or risk stagnating in a scientific backwater, isolated from creative streams of social, cultural and economic opportunity. Africa should adapt and capitalise on the opportunities, but in its own way, and as a leader not a follower, with broader, more societally-engaged priorities. It should seize the challenge with boldness and resolution
The African Open Science Platform: The Future of Science and Science for the Future
This document presents a draft strategy and makes the scientific case for the African Open Science Platform (AOSP). It is based on an expert group meeting held in Pretoria on 27-28 March 2018. Its purpose is to act as a framework for detailed, work on the creation of the Platform and as a basis for discussion at a stakeholder meeting to be held on 3-4 September 2018, which will lead to a definitive strategy for implementation from 2019. Expert group members at the March meeting were drawn from the following organisations: African Academy of Sciences (AAS), Academy of Science of South Africa (ASSAf), Committee on Data for Science and Technology (CODATA), International Council for Science (ICSU), National Research and Education Networks (NRENS), Research Data Alliance (RDA), South African Department of Science & Technology (DST) and National Research Foundation (NRF), Square Kilometre Array (SKA), UNESCO.
The African Open Science Platform The Future of Science and Science for the Future 4 The African Open Science Platform. The Platform’s mission is to put African scientists at the cutting edge of contemporary, data-intensive science as a fundamental resource for a modern society. Its building blocks are:
• a federated hardware, communications and software infrastructure, including policies and enabling practices, to support Open Science in the digital era;
• a network of excellence in Open Science that supports scientists & other societal actors in accumulating and using modern data resources to maximise scientific, social and economic benefit.
These objectives will be realised through seven related strands of activity:
Strand 0: Register & portal for African & related international data collections & services.
Strand 1: A federated network of computational facilities and services.
Strand 2: Software tools & advice on policies & practices of research data management.
Strand 3: A Data Science Institute at the cutting edge of data analytics and AI.
Strand 4: Priority application programmes: e.g. cities, disease, biosphere, agriculture.
Strand 5: A Network for Education & Skills in data & information.
Strand 6: A Network for Open Science Access and Dialogue.
The document also outlines the proposed governance, membership and management structure of the Platform, the approach to initial funding and the milestones in building up to the launch. The case for Open Science is based on the profound implications for society and for science, of the digital revolution and of the storm of data that it has unleashed and of the pervasive and novel means of communication that it has enabled. No state should fail to recognise this potential or to adapt their national intellectual infrastructure in exploiting benefits and minimising risks. Open Science is a vital enabler in maintaining the rigour and reliability of science; in creatively integrating diverse data resources to address complex modern challenges; in open innovation and in engaging with other societal actors as knowledge partners in tackling shared problems. It is fundamental to realisation of the Sustainable Development Goals. National science systems worldwide are struggling to adapt to this new paradigm. The alternatives are to do so or risk stagnating in a scientific backwater, isolated from creative streams of social, cultural and economic opportunity. Africa should adapt and capitalise on the opportunities, but in its own way, and as a leader not a follower, with broader, more societally-engaged priorities. It should seize the challenge with boldness and resolution
Is Adding the E Enough?: Investigating the Impact of K-12 Engineering Standards on the Implementation of STEM Integration.
The problems that we face in our ever-changing, increasingly global society are multidisciplinary, and many require the integration of multiple science, technology, engineering, and mathematics (STEM) concepts to solve them. National calls for improvement of STEM education in the United States are driving changes in policy, particularly in academic standards. Research on STEM integration in K-12 classrooms has not kept pace with the sweeping policy changes in STEM education. This study addresses the need for research to explore the translation of broad, national-level policy statements regarding STEM education and integration to state-level policies and implementation in K-12 classrooms. An interpretive multicase study design was employed to conduct an in-depth investigation of secondary STEM teachers\u27 implementation of STEM integration in their classrooms during a yearlong professional development program. The interpretive approach was used because it provides holistic descriptions and explanations for the particular phenomenon, in this case STEM integration. The results of this study demonstrate the possibilities of policies that use state standards documents as a mechanism to integrate engineering into science standards. Our cases suggest that STEM integration can be implemented most successfully when mathematics and science teachers work together both in a single classroom (co-teaching) and in multiple classrooms (content teaching—common theme)
The African Open Science Platform: The Future of Science and Science for the Future
This document presents a draft strategy and makes the scientific case for the African Open Science Platform (AOSP). It is based on an expert group meeting held in Pretoria on 27-28 March 2018. Its purpose is to act as a framework for detailed, work on the creation of the Platform and as a basis for discussion at a stakeholder meeting to be held on 3-4 September 2018, which will lead to a definitive strategy for implementation from 2019. Expert group members at the March meeting were drawn from the following organisations: African Academy of Sciences (AAS), Academy of Science of South Africa (ASSAf), Committee on Data for Science and Technology (CODATA), International Council for Science (ICSU), National Research and Education Networks (NRENS), Research Data Alliance (RDA), South African Department of Science & Technology (DST) and National Research Foundation (NRF), Square Kilometre Array (SKA), UNESCO.
The African Open Science Platform The Future of Science and Science for the Future 4 The African Open Science Platform. The Platform’s mission is to put African scientists at the cutting edge of contemporary, data-intensive science as a fundamental resource for a modern society. Its building blocks are:
• a federated hardware, communications and software infrastructure, including policies and enabling practices, to support Open Science in the digital era;
• a network of excellence in Open Science that supports scientists & other societal actors in accumulating and using modern data resources to maximise scientific, social and economic benefit.
These objectives will be realised through seven related strands of activity:
Strand 0: Register & portal for African & related international data collections & services.
Strand 1: A federated network of computational facilities and services.
Strand 2: Software tools & advice on policies & practices of research data management.
Strand 3: A Data Science Institute at the cutting edge of data analytics and AI.
Strand 4: Priority application programmes: e.g. cities, disease, biosphere, agriculture.
Strand 5: A Network for Education & Skills in data & information.
Strand 6: A Network for Open Science Access and Dialogue.
The document also outlines the proposed governance, membership and management structure of the Platform, the approach to initial funding and the milestones in building up to the launch. The case for Open Science is based on the profound implications for society and for science, of the digital revolution and of the storm of data that it has unleashed and of the pervasive and novel means of communication that it has enabled. No state should fail to recognise this potential or to adapt their national intellectual infrastructure in exploiting benefits and minimising risks. Open Science is a vital enabler in maintaining the rigour and reliability of science; in creatively integrating diverse data resources to address complex modern challenges; in open innovation and in engaging with other societal actors as knowledge partners in tackling shared problems. It is fundamental to realisation of the Sustainable Development Goals. National science systems worldwide are struggling to adapt to this new paradigm. The alternatives are to do so or risk stagnating in a scientific backwater, isolated from creative streams of social, cultural and economic opportunity. Africa should adapt and capitalise on the opportunities, but in its own way, and as a leader not a follower, with broader, more societally-engaged priorities. It should seize the challenge with boldness and resolution
Mathematical methods and models for radiation carcinogenesis studies
Research on radiation carcinogenesis requires a twofold approach. Studies of primary molecular lesions and subsequent cytogenetic changes are essential, but they cannot at present provide numerical estimates of the risk of small doses of ionizing radiations. Such estimates require extrapolations from dose, time, and age dependences of tumor rates observed in animal studies and epidemiological investigations, and they necessitate the use of statistical methods that correct for competing risks. A brief survey is given of the historical roots of such methods, of the basic concepts and quantities which are required, and of the maximum likelihood estimates which can be derived for right censored and double censored data. Non-parametric and parametric models for the analysis of tumor rates and their time and dose dependences are explained
Exact Bayesian curve fitting and signal segmentation.
We consider regression models where the underlying functional relationship between the response and the explanatory variable is modeled as independent linear regressions on disjoint segments. We present an algorithm for perfect simulation from the posterior distribution of such a model, even allowing for an unknown number of segments and an unknown model order for the linear regressions within each segment. The algorithm is simple, can scale well to large data sets, and avoids the problem of diagnosing convergence that is present with Monte Carlo Markov Chain (MCMC) approaches to this problem. We demonstrate our algorithm on standard denoising problems, on a piecewise constant AR model, and on a speech segmentation problem
Validation of Tool Mark Comparisons Obtained Using a Quantitative, Comparative, Statistical Algorithm
Developing a conceptual framework for an evaluation system for the NIAID HIV/AIDS clinical trials networks
Globally, health research organizations are called upon to re-examine their policies and practices to more efficiently and effectively address current scientific and social needs, as well as increasing public demands for accountability
Is Adding the E Enough? Investigating the Impact of K-12 Engineering Standards on the Implementation of STEM Integration
- …