Parameter-robust discretization and preconditioning of Biot's consolidation model

Biot's consolidation model in poroelasticity has a number of applications in science, medicine, and engineering. The model depends on various parameters, and in practical applications these parameters ranges over several orders of magnitude. A current challenge is to design discretization techniques and solution algorithms that are well behaved with respect to these variations. The purpose of this paper is to study finite element discretizations of this model and construct block diagonal preconditioners for the discrete Biot systems. The approach taken here is to consider the stability of the problem in non-standard or weighted Hilbert spaces and employ the operator preconditioning approach. We derive preconditioners that are robust with respect to both the variations of the parameters and the mesh refinement. The parameters of interest are small time-step sizes, large bulk and shear moduli, and small hydraulic conductivity.Comment: 24 page

Weakly imposed symmetry and robust preconditioners for Biot's consolidation model

We discuss the construction of robust preconditioners for finite element approximations of Biot's consolidation model in poroelasticity. More precisely, we study finite element methods based on generalizations of the Hellinger-Reissner principle of linear elasticity, where the stress tensor is one of the unknowns. The Biot model has a number of applications in science, medicine, and engineering. A challenge in many of these applications is that the model parameters range over several orders of magnitude. Therefore, discretization procedures which are well behaved with respect to such variations are needed. The focus of the present paper will be on the construction of preconditioners, such that the preconditioned discrete systems are well-conditioned with respect to variations of the model parameters as well as refinements of the discretization. As a byproduct, we also obtain preconditioners for linear elasticity that are robust in the incompressible limit.Comment: 21 page

Persuasive Technology for Learning and Teaching – The EuroPLOT Project

The concept of persuasive design has demonstrated its benefits by changing human behavior in certain situations, but in the area of education and learning, this approach has rarely been used. To change this and to study the feasibility of persuasive technology in teaching and learning, the EuroPLOT project (PLOT = Persuasive Learning Objects and Technologies) has been funded 2010-2013 by the Education, Audiovisual and Culture Executive Agency (EACEA) in the Life-long Learning (LLL) programme. In this program two tools have been developed (PLOTMaker and PLOTLearner) which allow to create learning objects with inherently persuasive concepts embedded. These tools and the learning objects have been evaluated in four case studies: language learning (Ancient Hebrew), museum learning (Kaj Munk Museum, Denmark), chemical handling, and academic Business Computing. These case studies cover a wide range of different learning styles and learning groups, and the results obtained through the evaluation of these case studies show the wide range of success of persuasive learning. They also indicate the limitations and areas where improvements are required

Demonstration of PLOTs from the EuroPLOT project

The EuroPLOT project (2010-2013) has been funded to explore the concept of persuasive design for learning and teaching. It has developed Persuasive Learn-ing Objects and Technologies (PLOTs), manifested in two tools and a set of learning objects that have been tested and evaluated in four different case studies. These PLOTs will be shown in this demonstration, and the participants can try them out and experience for themselves the impact of persuasive technology that is embedded in these PLOTs. This will be one authoring tool (PLOTMaker) and one delivery tool (PLOTLearner). Furthermore, there will be learning objects shown which have been developed for those four different case studies. All of these PLOTs have already been tested and evaluated during case studies with real learners

Beyond BAO: improving cosmological constraints from BOSS with measurement of the void-galaxy cross-correlation

We present a measurement of the anisotropic void-galaxy cross-correlation function in the CMASS galaxy sample of the BOSS DR12 data release. We perform a joint fit to the data for redshift space distortions (RSD) due to galaxy peculiar velocities and anisotropies due to the Alcock-Paczynski (AP) effect, for the first time using a velocity field reconstruction technique to remove the complicating effects of RSD in the void centre positions themselves. Fits to the void-galaxy function give a 1% measurement of the AP parameter combination $D_A(z)H(z)/c = 0.4367\pm 0.0045$ at redshift $z=0.57$, where $D_A$ is the angular diameter distance and $H$ the Hubble parameter, exceeding the precision obtainable from baryon acoustic oscillations (BAO) by a factor of ~3.5 and free of systematic errors. From voids alone we also obtain a 10% measure of the growth rate, $f\sigma_8(z=0.57)=0.501\pm0.051$. The parameter degeneracies are orthogonal to those obtained from galaxy clustering. Combining void information with that from BAO and galaxy RSD in the same CMASS sample, we measure $D_A(0.57)/r_s=9.383\pm 0.077$ (at 0.8% precision), $H(0.57)r_s=(14.05\pm 0.14)\;10^3$ kms$^{-1}$Mpc$^{-1}$ (1%) and $f\sigma_8=0.453\pm0.022$ (4.9%), consistent with cosmic microwave background (CMB) measurements from Planck. These represent a factor \sim2 improvement in precision over previous results through the inclusion of void information. Fitting a flat cosmological constant $\Lambda$CDM model to these results in combination with Planck CMB data, we find up to an 11% reduction in uncertainties on $H_0$ and $\Omega_m$ compared to use of the corresponding BOSS consensus values. Constraints on extended models with non-flat geometry and a dark energy of state that differs from $w=-1$ show an even greater improvement.Comment: 22 pages, 15 figures. Accepted for publication in Phys.Rev.D. v2 corrects small error in likelihood analysis; minor changes to figures and text, cosmological results unchanged. Reconstruction and void-finding code available at https://github.com/seshnadathur/Revolver, likelihood analysis code available at https://github.com/seshnadathur/void-galaxy-cosmo-fitte

Spatial variations of the fine-structure constant in symmetron models

We investigate the variation of the fine-structure constant, {\alpha}, in symmetron models using N-body simulations in which the full spatial distribution of {\alpha} at different redshifts has been calculated. In particular, we obtain simulated sky maps for this variation, and determine its power spectrum. We find that in high-density regions of space (such as deep inside dark matter halos) the value of {\alpha} approaches the value measured on Earth. In the low-density outskirts of halos the scalar field value can approach the symmetry breaking value and leads to significantly different values of {\alpha}. If the scalar-photon coupling strength {\beta}{\gamma} is of order unity we find that the variation of {\alpha} inside dark matter halos can be of the same magnitude as the recent claims by Webb et al. of a dipole variation. Importantly, our results also show that with low-redshift symmetry breaking these models exhibit some dependence of {\alpha} on lookback time (as opposed to a pure spatial dipole) which could in principle be detected by sufficiently accurate spectroscopic measurements, such as those of ALMA and the ELT-HIRES.Comment: 11 pages, 9 figure

Persuasive Technology for Learning in Business Context

"Persuasive Design is a relatively new concept which employs general principles of persuasion that can be implemented in persuasive technology. This concept has been introduced by BJ Fogg in 1998, who since then has further extended it to use computers for changing attitudes and behaviour. Such principles can be applied very well in learning and teaching: in traditional human-led learning, teachers always have employed persuasion as one of the elements of teaching. Persuasive technology moves these principles into the digital domain, by focusing on technology that inherently stimulates learners to learn more quickly and effectively. This is very relevant for the area of Business Management in several aspects: Consumer Behavior, Communications, Human Resource, Marketing & Advertising, Organisational Behavior & Leadership. The persuasive principles identified by BJ Fogg are: reduction, tunnelling, tailoring, suggestion, self-monitoring, surveillance, conditioning, simulation, social signals. Also relevant is the concept of KAIROS, which means the just-in-time, at the right place provision of information/stimulus. In the EuroPLOT project (2010-2013) we have developed persuasive learning objects and tools (PLOTs) in which we have applied persuasive designs and principles. In this context, we have developed a pedagogical framework for active engagement, based on persuasive design in which the principles of persuasive learning have been formalised in a 6-step guide for persuasive learning. These principles have been embedded in two tools – PLOTmaker and PLOTLearner – which have been developed for creating persuasive learning objects. The tools provide specific capability for implementing persuasive principles at the very beginning of the design of learning objects. The feasibility of employing persuasive learning concepts with these tools has been investigated in four different case studies with groups of teachers and learners from realms with distinctly different teaching and learning practices: Business Computing, language learning, museum learning, and chemical substance handling. These case studies have involved the following learner target groups: school children, university students, tertiary students, vocational learners and adult learners. With regards to the learning context, they address archive-based learning, industrial training, and academic teaching. Alltogether, these case studies include participants from Sweden, Africa (Madagascar), Denmark, Czech Republic, and UK. One of the outcomes of this investigation was that one cannot apply a common set of persuasive designs that would be valid for general use in all situations: on the contrary, the persuasive principles are very specific to learning contexts and therefore must be specifically tailored for each situation. Two of these case studies have a direct relevance to education in the realm of Business Management: Business Computing and language learning (for International Business). In this paper we will present the first results from the evaluation of persuasive technology driven learning in these two relevant areas.

Medical Data Architecture Platform and Recommended Requirements for a Medical Data System for Exploration Missions

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically- relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm of medical data management on the International Space Station. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products derived from the third MDA prototype development will directly inform exploration medical system requirements for Level of Care IV in Gateway missions. In fiscal year 2019, the MDA project developed Test Bed 3, the third iteration in a series of prototypes, that featured integrations with cognition tool data, ultrasound image analytics and core Flight Software (cFS). Maintaining a layered architecture design, the framework implemented a plug-in, modular approach in the integration of these external data sources. An early version of MDA Test Bed 3 software was deployed and operated in a simulated analog environment that was part of the Next Space Technologies for Exploration Partnerships (NextSTEP) Gateway tests of multiple habitat prototypes. In addition, the MDA team participated in the Gateway Test and Verification Demonstration, where the MDA cFS applications was integrated with Gateway-in-a-Box software to send and receive medically relevant data over a simulated vehicle network. This software demonstration was given to ExMC and Gateway Program stakeholders at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Also, the integrated prototypes served as a vehicle to provide Level 5 requirements for the Crew Health and Performance Habitat Data System for Gateway Missions (Medical Level of Care IV). In the upcoming fiscal year, the MDA project will continue to provide systems engineering and vertical prototypes to refine requirements for medical Level of Care IV and inform requirements for Level of Care V