Sensitivity analysis modelling for microscale multiphysics robust engineering design

Sensitivity Analysis (SA) plays an important role in the development of any practical engineering model. It can help to reveal the sources and mechanisms of variability that provide the key to understanding system uncertainty. SA can also be used to calibrate simulation models for closer agreement with experimental results. Robust Engineering Design (RED) seeks to exploit such knowledge in the search for design solutions that are optimal in terms of performance in the face of variability. Microscale and multiphysics problems present challenges to modelling due to their complexity, which puts increased demands on computational methods. For example, in developing a model of a piezoelectric actuator, the process of calibration is prolonged by the number of parameters that are difficult to verify with the physical device. In the approach presented in this paper, normalised sensitivity coefficients are determined directly and accurately using the governing finite element model formulation, offering an efficient means of identifying parameters that affect the output of the model, leading to increased accuracy and knowledge of system performance in the face of variability

Modeling Agglomeration of Dust Particles in Plasma

The charge on an aggregate immersed in a plasma environment distributes itself over the aggregate's surface; this can be approximated theoretically by assuming a multipole distribution. The dipole-dipole (or higher order) charge interactions between fractal aggregates lead to rotations of the grains as they interact. Other properties of the dust grains also influence the agglomeration process, such as the monomer shape (spherical or ellipsoidal) or the presence of magnetic material. Finally, the plasma and grain properties also determine the morphology of the resultant aggregates. Porous and fluffy aggregates are more strongly coupled to the gas, leading to reduced collisional velocities, and greater collisional cross sections. These factors in turn can determine the growth rate of the aggregates and evolution of the dust cloud. This paper gives an overview of the numerical and experimental methods used to study dust agglomeration at CASPER and highlights some recent results

Definition and composition of motor primitives using latent force models and hidden Markov models

In this work a different probabilistic motor primitive parameterization is proposed using latent force models (LFMs). The sequential composition of different motor primitives is also addressed using hidden Markov models (HMMs) which allows to capture the redundancy over dynamics by using a limited set of hidden primitives. The capability of the proposed model to learn and identify motor primitive occurrences over unseen movement realizations is validated using synthetic and motion capture data

Reef fish carbonate production assessments highlight regional variation in sedimentary significance (article)

This is the final published version.Available from GSA via the DOI in this record.The dataset associated with this article is located in ORE at: https://doi.org/10.24378/exe.485Recent studies show that all marine bony fish produce mud-sized (<63 µm) carbonate at rates relevant to carbonate sediment budgets, thus adding to the debate about the often enigmatic origins of fine-grained marine carbonates. However, existing production data are geographically and taxonomically limited, and because different fish families are now known to produce different carbonate polymorphs—an issue relevant to predicting their preservation potential—these limitations represent an important knowledge gap. Here we present new data from sites in the Western Pacific Ocean, based on an analysis of 45 fish species. Our data show that previously reported production outputs (in terms of rates and family-specific mineralogies) are applicable across different biogeographic regions. On this basis, we model carbonate production for nine coral reef systems around Australia, with production rates averaging 2.1–9.6 g m–2 yr–1, and up to 105 g m–2 yr–1 at discrete sites with high fish biomass. With projected production rates on lower-latitude reefs up to two-fold higher, these outputs indicate that carbonate production rates by fish can be comparable with other fine-grained carbonate-producing taxa such as codiacean algae. However, carbonates produced by Australian reef fish assemblages are dominated by a highly unstable amorphous polymorph; a marked contrast to Caribbean assemblages in which Mg calcite dominates. These findings highlight important regional differences in the sedimentary relevance and preservation potential of fish carbonates as a function of historical biogeographic processes that have shaped the world’s marine fish faunas.Salter, Perry, and Wilson were funded through Natural Environment Research Council (NERC) grants NE/K003143/1 and NE/G010617/1. Harborne was funded through NERC fellowship NE/F015704/1 and Australian Research Council (ARC) fellowship DE120102459

Fish as major carbonate mud producers and missing components of the tropical carbonate factory

This a post-print, author-produced version of an article accepted for publication in Proceedings of the National Academy of Sciences of the United States of America. Copyright © 2011 National Academy of Sciences. The definitive version is available at http://www.pnas.org/content/108/10/3865.fullCarbonate mud is a major constituent of recent marine carbonate sediments and of ancient limestones, which contain unique records of changes in ocean chemistry and climate shifts in the geological past. However, the origin of carbonate mud is controversial and often problematic to resolve. Here we show that tropical marine fish produce and excrete various forms of precipitated (nonskeletal) calcium carbonate from their guts (“low” and “high” Mg-calcite and aragonite), but that very fine-grained (mostly < 2 μm) high Mg-calcite crystallites (i.e., MgCO3) are their dominant excretory product. Crystallites from fish are morphologically diverse and species-specific, but all are unique relative to previously known biogenic and abiotic sources of carbonate within open marine systems. Using site specific fish biomass and carbonate excretion rate data we estimate that fish produce ∼6.1 × 106 kg CaCO3/year across the Bahamian archipelago, all as mud-grade (the < 63 μm fraction) carbonate and thus as a potential sediment constituent. Estimated contributions from fish to total carbonate mud production average ∼14% overall, and exceed 70% in specific habitats. Critically, we also document the widespread presence of these distinctive fish-derived carbonates in the finest sediment fractions from all habitat types in the Bahamas, demonstrating that these carbonates have direct relevance to contemporary carbonate sediment budgets. Fish thus represent a hitherto unrecognized but significant source of fine-grained carbonate sediment, the discovery of which has direct application to the conceptual ideas of how marine carbonate factories function both today and in the past

Substitutions in the redox-sensing PAS domain of the NifL regulatory protein define an inter-subunit pathway for redox signal transmission

The Per-ARNT-Sim (PAS) domain is a conserved a/ß fold present within a plethora of signalling proteins from all kingdoms of life. PAS domains are often dimeric and act as versatile sensory and interaction modules to propagate environmental signals to effector domains. The NifL regulatory protein from Azotobacter vinelandii senses the oxygen status of the cell via an FAD cofactor accommodated within the first of two amino-terminal tandem PAS domains, termed PAS1 and PAS2. The redox signal perceived at PAS1 is relayed to PAS2 resulting in conformational reorganization of NifL and consequent inhibition of NifA activity. We have identified mutations in the cofactor-binding cavity of PAS1 that prevent 'release' of the inhibitory signal upon oxidation of FAD. Substitutions of conserved ß-sheet residues on the distal surface of the FAD-binding cavity trap PAS1 in the inhibitory signalling state, irrespective of the redox state of the FAD group. In contrast, substitutions within the flanking A'a-helix that comprises part of the dimerization interface of PAS1 prevent transmission of the inhibitory signal. Taken together, these results suggest an inter-subunit pathway for redox signal transmission from PAS1 that propagates from core to the surface in a conformation-dependent manner requiring a flexible dimer interface

Revisiting protein aggregation as pathogenic in sporadic Parkinson and Alzheimer diseases.

The gold standard for a definitive diagnosis of Parkinson disease (PD) is the pathologic finding of aggregated α-synuclein into Lewy bodies and for Alzheimer disease (AD) aggregated amyloid into plaques and hyperphosphorylated tau into tangles. Implicit in this clinicopathologic-based nosology is the assumption that pathologic protein aggregation at autopsy reflects pathogenesis at disease onset. While these aggregates may in exceptional cases be on a causal pathway in humans (e.g., aggregated α-synuclein in SNCA gene multiplication or aggregated β-amyloid in APP mutations), their near universality at postmortem in sporadic PD and AD suggests they may alternatively represent common outcomes from upstream mechanisms or compensatory responses to cellular stress in order to delay cell death. These 3 conceptual frameworks of protein aggregation (pathogenic, epiphenomenon, protective) are difficult to resolve because of the inability to probe brain tissue in real time. Whereas animal models, in which neither PD nor AD occur in natural states, consistently support a pathogenic role of protein aggregation, indirect evidence from human studies does not. We hypothesize that (1) current biomarkers of protein aggregates may be relevant to common pathology but not to subgroup pathogenesis and (2) disease-modifying treatments targeting oligomers or fibrils might be futile or deleterious because these proteins are epiphenomena or protective in the human brain under molecular stress. Future precision medicine efforts for molecular targeting of neurodegenerative diseases may require analyses not anchored on current clinicopathologic criteria but instead on biological signals generated from large deeply phenotyped aging populations or from smaller but well-defined genetic-molecular cohorts

Performance of GFN1-xTB for periodic optimization of metal organic frameworks

Tight-binding approaches bridge the gap between force field methods and Density Functional Theory (DFT). Density Functional Tight Binding (DFTB) has been employed for a wide range of systems including proteins, clays and 2D and 3D materials. DFTB is 2–3 orders of magnitude faster than DFT, allowing calculations containing up to ca. 5000 atoms. The efficiency of DFTB comes via pre-computed integrals, which are parameterized for each pair of atoms, and the requirement for this parameterization has previously prevented widespread use of DFTB for Metal–Organic Frameworks. The GFN-xTB (Geometries, Frequencies, and Non-covalent interactions Tight Binding) method provides parameters for elements up to Z ≤ 86. We have therefore employed GFN-xTB to periodic optimizations of the Computation Ready Experimental (CoRE) database of MOF structures. We find that 75% of all cell parameters remain within 5% of the reference (experimental) value and that bonds containing metal atoms are typically well conserved with a mean average deviation of 0.187 Å. Therefore GFN-xTB provides the ability to calculate MOF structures more accurately than force fields, and ca. 2 orders of magnitude faster than DFT. We therefore propose that GFN-xTB is a suitable method for screening of hypothetical MOFs (Z ≤ 86), with the advantage of accurate binding energies for adsorption applications