Classification of linear differential operators with an invariant subspace of monomials

A complete classification of linear differential operators possessing finite-dimensional invariant subspace with a basis of monomials is presented.Comment: 10 p

Data-driven damage initiation criteria for carbon fiber reinforced polymer composites

Computational progressive failure analysis (PFA) is vital for the design, verification, and validation of carbon fiber reinforced polymer (CFRP) composites. However, the computational cost of PFA is usually high due to the complexity of the model. The damage initiation criterion is one of the essential components of a PFA code to determine the transition of a material’s state from pristine or microscopically damaged to macroscopically damaged. In this thesis, data-driven models are developed to determine the matrix damage initiation based on the Mohr-Coulomb model and Hashin model. For 2D plane stress states, the computational cost for determining damage initiation can be dramatically reduced by implementing a Binary Search (BS) algorithm and predictive machine learning models. We have demonstrated the usage of BS and the training and evaluation of machine learning models as alternative methods to determine macroscale matrix damage initiation. With the data-driven methods, over 99% of the computational time has been saved, while the predictive accuracy stays 99.9% from the traditional approach. For a 3D stress state, 87% of the computational time is saved with the predictive accuracy of 94.7%

Coastal aquifers: Scientific advances in the face of global environmental challenges

This article has been published in final form at http://dx.doi.org/10.1016/j.jhydrol.2017.04.046 © 2017 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 24 month embargo from date of publication (25 May 2017) in accordance with the publisher’s copyright polic

ASK Magazine

Welcome to the Academy of Program and Project Leadership (APPL) and ASK Magazine. APPL helps NASA managers and project teams accomplish today's missions and meet tomorrow's challenges by providing performance enhancement services and tools, supporting career development programs, sponsoring knowledge sharing events and publications, and creating opportunities for project management collaboration with universities, professional associations, industry partners and other government agencies. ASK Magazine grew out of APPL's Knowledge Sharing Initiative. The stories that appear in ASK are written by the 'best of the best' project managers, primarily from NASA, but also from other government agencies and industry. These stories contain genuine nuggets of knowledge and wisdom that are transferable across projects. Who better than a project manager to help another project manager address a critical issue on a project? Big projects, smaLl projects-they're ali here in ASK. Stories in this issue include: Earthly Considerations on Mars, Getting Politically Active, Stumping for the Project, Grins & Giggles: The Launch Pad to High Performance, Transfer Wisdom Workshops: Coming to a NASA Center Near You, Project Management: The Television Show, Lessons Learned Again and Again and Again, Implementation Reviews, ASK Talks with Dr. Michael Hecht, and What Is This Fourth Dimension?

Defining and evaluating stability in early years assessment

Stability is an important underlying assumption in any form of assessment-supported decision-making. Since early years development is frequently described as unstable, the concept plays a central role in the discussion surrounding early years assessment. This paper describes stability as a set of assumptions about the way individual scores change over time. Here, an analytical framework developed by Tisak and Meredith (1990), which can be used to evaluate these assumptions, is extended and applied to evaluate the stability of mathematics scores of 1402 children between kindergarten and third grade. Multilevel models are used to evaluate the assumption that each child has a unique individual growth rate, as well as the assumption that the ranking of children’s test scores is consistent over time. The results show that for a large proportion of the children, assuming unique individual growth rates leads to similar predictions as assuming that children develop at an equal pace. While individual differences in growth rate may provide relevant information, these differences only become apparent after several test administrations. As such, decisions should not be based on perceived stagnated or accelerated growth over a short period

Whole-body arginine dimethylation is associated with all-cause mortality in adult renal transplant recipients

Arginine residues in proteins can be singly or doubly methylated post-translationally. Proteolysis of arginine-methylated proteins provides monomethyl arginine, asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA). ADMA and SDMA are considered cardiovascular risk factors, with the underlying mechanisms being not yet fully understood. SDMA lacks appreciable metabolism and is almost completely eliminated by the kidney, whereas ADMA is extensively metabolized to dimethylamine (DMA), with a minor ADMA fraction of about 10% being excreted unchanged in the urine. Urinary DMA and ADMA are useful measures of whole-body asymmetric arginine-dimethylation, while urinary SDMA serves as a whole-body measure of symmetric arginine-dimethylation. In renal transplant recipients (RTR), we previously found that higher plasma ADMA concentrations and lower urinary ADMA and SDMA concentrations were associated with a higher risk of all-cause mortality. Yet, in this RTR collective, no data were available for urinary DMA. For the present study, we additionally measured the excretion rate of DMA in 24-h collected urine samples of the RTR and of healthy kidney donors in the cohort, with the aim to quantitate whole-body asymmetric (ADMA, DMA) and symmetric (SDMA) arginine-dimethylation. We found that lower DMA excretion rates were associated with higher all-cause mortality, yet not with cardiovascular mortality. In the healthy donors, kidney donation was associated with considerable decreases in ADMA (by - 39%, P < 0.0001) and SDMA (by - 21%, P < 0.0001) excretion rates, yet there was no significant change in DMA (by - 9%, P = 0.226) excretion rate. Our results suggest that protein-arginine dimethylation is altered in RTR compared to healthy kidney donors and that it is pronouncedly shifted from symmetric to asymmetric arginine-dimethylation, with whole-body protein-arginine dimethylation being almost unaffected

Quantum chaos in 2D gravity

We present a quantitative and fully non-perturbative description of the ergodic phase of quantum chaos in the setting of two-dimensional gravity. To this end we describe the doubly non-perturbative completion of semiclassical 2D gravity in terms of its associated universe field theory. The guiding principle of our analysis is a flavor-matrix theory (fMT) description of the ergodic phase of holographic gravity, which exhibits $\mathrm{U}(n|n)$ causal symmetry breaking and restoration. JT gravity and its 2D-gravity cousins alone do not realize an action principle with causal symmetry, however we demonstrate that their {\it universe field theory}, the Kodaira-Spencer (KS) theory of gravity, does. After directly deriving the fMT from brane-antibrane correlators in KS theory, we show that causal symmetry breaking and restoration can be understood geometrically in terms of different (topological) D-brane vacua. We interpret our results in terms of an open-closed string duality between holomorphic Chern-Simons theory and its closed-string equivalent, the KS theory of gravity. Emphasis will be put on relating these geometric principles to the characteristic spectral correlations of the quantum ergodic phase.Comment: 49 pages, 2 appendices, 9 figures; v3: rewrote introduction, simplified Fig.

Leaf Species-Dependent Fungicide Effects on the Function and Abundance of Associated Microbial Communities

Microbially-mediated leaf litter decomposition is a critical ecosystem function in running waters within forested areas, which can be affected by fungicides. However, fungicide effects on leaf litter decomposition have been investigated almost exclusively with black alder leaves, a leaf species with traits favourable to consumers (i.e., low recalcitrance and high nutrient content). At the same time, little is known about fungicide effects on microbial colonisation and decomposition of other leaf species with less favourable traits. In this 21 day lasting study, we explore the effects of increasing fungicide sum concentrations (0-3000 mu g/L) on microbial colonisation and decomposition of three leaf species (black alder, Norway maple and European beech) differing in terms of recalcitrance and nutrient content. Leaf litter decomposition rate, leaf-associated fungal biomass and bacterial density were quantified to observe potential effects at the functional level. Beech, as the species with the least favourable leaf traits, showed a substantially lower decomposition rate (50%) in absence of fungicides than alder and maple. In the presence of high fungicide concentrations (300-3000 mu g/L), beech showed a concentration-related decrease not only in microbial leaf litter decomposition but also fungal biomass. This suggests that favourable traits of leaf litter (as for alder and maple) enable leaf-associated microorganisms to acquire leaf-bound energy more easily to withstand potential effects induced by fungicide exposure. Our results indicate the need to deepen our understanding on how leaf species' traits interact with the impact of chemical stressors on the leaf decomposition activity of microbial communities

Common Data Fusion Framework : An open-source Common Data Fusion Framework for space robotics

Multisensor data fusion plays a vital role in providing autonomous systems with environmental information crucial for reliable functioning. In this article, we summarize the modular structure of the newly developed and released Common Data Fusion Framework and explain how it is used. Sensor data are registered and fused within the Common Data Fusion Framework to produce comprehensive 3D environment representations and pose estimations. The proposed software components to model this process in a reusable manner are presented through a complete overview of the framework, then the provided data fusion algorithms are listed, and through the case of 3D reconstruction from 2D images, the Common Data Fusion Framework approach is exemplified. The Common Data Fusion Framework has been deployed and tested in various scenarios that include robots performing operations of planetary rover exploration and tracking of orbiting satellites