Now showing items 1-20 of 3492

• #### Evolution and scaling of the peak flame surface density in spherical turbulent premixed flames subjected to decaying isotropic turbulence

(Proceedings of the Combustion Institute, Elsevier BV, 2020-07-25) [Article]
The peak flame surface density within the turbulent flame brush is central to turbulent premixed combustion models in the flamelet regime. This work investigates the evolution of the peak surface density in spherically expanding turbulent premixed flames with the help of direct numerical simulations at various values of the Reynolds and Karlovitz number. The flames propagate in decaying isotropic turbulence inside a closed vessel. The effects of turbulent transport, transport due to mean velocity gradient, and flame stretch on the peak surface density are identified and characterized with an analysis based on the transport equation for the flame surface density function. The three mechanisms are governed by distinct flow time scales; turbulent transport by the eddy turnover time, mean transport by a time scale related to the pressure rise in the closed chamber, and flame stretch by the Kolmogorov time scale. Appropriate scaling of the terms is proposed and shown to collapse the data despite variations in the dimensionless groups. Overall, the transport terms lead to a reduction in the peak value of the surface density, while flame stretch has the opposite effect. In the present configuration, a small imbalance between the two leads to an exponential decay of the peak surface density in time. The dimensionless decay rate is found to be consistent with the evolution of the wrinkling scale as defined in the Bray-Moss-Libby model.
• #### Dynamic Traffic Reconstruction using Probe Vehicles

(arXiv, 2020-07-20) [Preprint]
This article deals with the observation problem in traffic flow theory. The model used is the semilinear viscous Burgers equation. Instead of using the traditional fixed sensors to estimate the state of the traffic at given points, the measurements here are obtained from Probe Vehicles (PVs). We propose then a moving dynamic boundary observer whose boundaries are defined by the trajectories of the PVs. The main result of this article is the exponential convergence of the observation error, and, in some cases, its finite-time convergence. Finally, numerical simulations show that it is possible to observe the traffic in the congested, free-flow, and mixed regimes provided that the number of PVs is large enough.
• #### Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation

(arXiv, 2020-07-11) [Preprint]
The ability to perform effective planning is crucial for building an instruction-following agent. When navigating through a new environment, an agent is challenged with (1) connecting the natural language instructions with its progressively growing knowledge of the world; and (2) performing long-range planning and decision making in the form of effective exploration and error correction. Current methods are still limited on both fronts despite extensive efforts. In this paper, we introduce the Evolving Graphical Planner (EGP), a model that performs global planning for navigation based on raw sensory input. The model dynamically constructs a graphical representation, generalizes the action space to allow for more flexible decision making, and performs efficient planning on a proxy graph representation. We evaluate our model on a challenging Vision-and-Language Navigation (VLN) task with photorealistic images and achieve superior performance compared to previous navigation architectures. For instance, we achieve a 53% success rate on the test split of the Room-to-Room navigation task through pure imitation learning, outperforming previous navigation architectures by up to 5%.
• #### A unified first order hyperbolic model for nonlinear dynamic rupture processes in diffuse fracture zones

(arXiv, 2020-07-02) [Preprint]
Earthquake fault zones are more complex, both geometrically and rheologically, than an idealised infinitely thin plane embedded in linear elastic material. To incorporate nonlinear material behaviour, natural complexities and multi-physics coupling within and outside of fault zones, here we present a first order hyperbolic and thermodynamically compatible mathematical model for a continuum in a gravitational field which provides a unified description of nonlinear elasto-plasticity, material damage and of viscous Newtonian flows with phase transition between solid and liquid phases. The fault geometry and secondary cracks are described via a scalar function $\xi \in [0,1]$ that indicates the local level of material damage. The model also permits the representation of arbitrarily complex geometries via a diffuse interface approach based on the solid volume fraction function $\alpha \in [0,1]$. Neither of the two scalar fields $\xi$ and $\alpha$ needs to be mesh-aligned, allowing thus faults and cracks with complex topology and the use of adaptive Cartesian meshes (AMR). The model shares common features with phase-field approaches, but substantially extends them. We show a wide range of numerical applications that are relevant for dynamic earthquake rupture in fault zones, including the co-seismic generation of secondary off-fault shear cracks, tensile rock fracture in the Brazilian disc test, as well as a natural convection problem in molten rock-like material.
• #### Multi-Level Nanoimprint Lithography for Large-Area Thin Film Transistor Backplane Manufacturing

(Journal of Photopolymer Science and Technology, Technical Association of Photopolymers, Japan, 2020-06-30) [Article]
Thin film transistors (TFTs) are the basis for current AMOLED display arrays. For next- generation displays, higher resolution and cost-effective manufacturing of panels is adamant. The current benchmark patterning method in the display industry is photolithography. Here, we propose the use of a hybrid approach of nanoimprint lithography and conventional FPD processing for the realization of high-resolution display backplanes. We demonstrate the realization of sub-micron amorphous oxide semiconductor TFTs with multi-level nanoimprint lithography in order to decrease the number of patterning steps in display manufacturing. Top-gate self-aligned a-IGZO TFTs are realized with performance comparable to benchmark photolithography-based TFTs.
• #### The Influence of Pore Structure and Acidity on the Hydrodesulfurization of Dibenzothiophene over NiMo-Supported Catalysts

(ACS Omega, American Chemical Society (ACS), 2020-06-18) [Article]
A series of mesoporous materials of SBA-16 were in situ incorporated into ZSM-5 crystallites via a two-step self-assemble method, and hydrodesulfurization (HDS) catalysts were prepared on the corresponding ZSM-5/SBA-16 (ZS) composites. The characterization results indicated that ZSM-5 nanoseeds were fabricated into the silica framework of the ZS composites, and the three-dimensional Im3m cubic structure of SBA-16 was retained simultaneously. In addition, the ZS series materials possessed open pores and large surfaces, which would facilitate the diffusion of reactants in the mesoporous channels. Moreover, the introduction of ZSM-5 seeds into composites could enhance the acidities of supports. As a result, the NiMo/ZS series catalysts exhibited high activities for DBT HDS processes. The NiMo/ZS-160 catalyst exhibited the highest catalytic efficiency (96.5%), which was apparently attributed to the synergistic contributions of the physicochemical properties of ZS supports and the dispersion states of active metals. Correspondingly, DBT HDS reactions over the NiMo/ZS series catalysts mainly proceeded via a hydrogenation desulfurization route that benefitted from the enhanced acidities especially the total Brønsted acid.
• #### Boosting the efficiency of water oxidation via surface states on hematite photoanodes by incorporating Bi3+ ions

(Sustainable Energy & Fuels, Royal Society of Chemistry (RSC), 2020-06-17) [Article]
<p>The incorporation of Bi$^{3+}$ ions into the hematite crystal structure induces the creation of oxygen vacancies and boosts the photoelectrochemical water oxidation kinetics.</p>
• #### Human XPG nuclease structure, assembly, and activities with insights for neurodegeneration and cancer from pathogenic mutations

(Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, 2020-06-11) [Article]
Xeroderma pigmentosum group G (XPG) protein is both a functional partner in multiple DNA damage responses (DDR) and a pathway coordinator and structure-specific endonuclease in nucleotide excision repair (NER). Different mutations in the XPG gene ERCC5 lead to either of two distinct human diseases: Cancer-prone xeroderma pigmentosum (XP-G) or the fatal neurodevelopmental disorder Cockayne syndrome (XP-G/CS). To address the enigmatic structural mechanism for these differing disease phenotypes and for XPG’s role in multiple DDRs, here we determined the crystal structure of human XPG catalytic domain (XPGcat), revealing XPG-specific features for its activities and regulation. Furthermore, XPG DNA binding elements conserved with FEN1 superfamily members enable insights on DNA interactions. Notably, all but one of the known pathogenic point mutations map to XPGcat, and both XP-G and XP-G/CS mutations destabilize XPG and reduce its cellular protein levels. Mapping the distinct mutation classes provides structure-based predictions for disease phenotypes: Residues mutated in XP-G are positioned to reduce local stability and NER activity, whereas residues mutated in XP-G/CS have implied long-range structural defects that would likely disrupt stability of the whole protein, and thus interfere with its functional interactions. Combined data from crystallography, biochemistry, small angle X-ray scattering, and electron microscopy unveil an XPG homodimer that binds, unstacks, and sculpts duplex DNA at internal unpaired regions (bubbles) into strongly bent structures, and suggest how XPG complexes may bind both NER bubble junctions and replication forks. Collective results support XPG scaffolding and DNA sculpting functions in multiple DDR processes to maintain genome stability.
• #### Objective identification of local spatial structure for material characterization

(Statistical Analysis and Data Mining: The ASA Data Science Journal, Wiley, 2020-06-08) [Article]
Objective tools for characterizing materials at the atomic level are often difficult to develop because of the size or structure of the data. Atom probe tomography (APT) is a measurement tool that maps the location and type of atoms in materials in three-dimensions (3D), producing data sets with potentially billions of observations. In this work, we present a set of spatial statistics methods developed to test the null hypotheses of no global spatial association; no local spatial association; and no local spatial cross-correlation and apply these for the first time to APT data. The empirical and modeled covariogram and Moran's I can be used to study the global structure of a spatially referenced atomic element. The local indicator of spatial association (LISA) identifies volumes where high levels of values (hot spots) or low levels of values (cold spots) of elemental clustering exist. The local indicator of spatial cross-correlation (LISC) reports where simultaneously high levels or low levels of two atomic elements occur. For each test statistic at each location, an associated p -value is produced that can be used to weigh the evidence in favor of spatial clustering. The size of APT data sets presents some challenges, so the effect of weight functions and neighborhood selection on the computation and significance of the test statistics are discussed, and the issue of multiple statistical testing is also considered. These methods are illustrated using an APT data set with atomic percentages reported in voxels binned to 1 nm3.
• #### A Goniopora stokesi community at Tatsugasako, Otsuki, 2020-01-23Kochi, Japan: a new northernmost specimen-based record

(Plankton and Benthos Research, The Plankton Society of Japan/The Japanese Association of Benthology, 2020-05-29) [Article]
The zooxanthellate scleractinian species Goniopora stokesi is widely distributed across the Indo-Pacific Ocean, and in Japan the northernmost records of this species are from Tatsukushi, Kochi on Shikoku, although these records are not associated with specimens deposited in museums. The species is unique among Goniopora in that it lives on soft bottom sediment, forming free-living colonies, and produces asexual daughter colonies, or ‘polyp balls,’ via budding from parent colonies. Here we report on a large G. stokesi community from Otsuki, Kochi, Japan, representing the northernmost specimen-based record of the species. Specimen-based records are important as verifiable baseline data in light of global warming and climate change, which is expected to drastically effect the marine flora and fauna of Kochi and surrounding areas.
• #### Proteomic responses to ocean acidification in the brain of juvenile coral reef fish

(Cold Spring Harbor Laboratory, 2020-05-28) [Preprint]
AbstractElevated CO2 levels predicted to occur by the end of the century can affect the physiology and behaviour of marine fishes. For one important survival mechanism, the response to chemical alarm cues from conspecifics, substantial among-individual variation in the extent of behavioural impairment when exposed to elevated CO2 has been observed in previous studies. Whole brain transcriptomic data has further emphasized the importance of parental phenotypic variation in the response of juvenile fish to elevated CO2. In this study, we investigate the genome-wide proteomic responses of this variation in the brain of 5-week old spiny damselfish, Acanthochromis polyacanthus. We compared the expression of proteins in the brains of juvenile A. polyacanthus from two different parental behavioural phenotypes (sensitive and tolerant) that had been experimentally exposed to short-term, long-term and inter-generational elevated CO2. Our results show differential expression of key proteins related to stress response and epigenetic markers with elevated CO2 exposure. Proteins related to neurological development were also differentially expressed particularly in the long-term developmental treatment, which might be critical for juvenile development. By contrast, exposure to elevated CO2 in the parental generation resulted in only three differentially expressed proteins in the offspring, revealing potential for inter-generational acclimation. Lastly, we found a distinct proteomic pattern in juveniles due to the behavioural sensitivity of parents to elevated CO2, even though the behaviour of the juvenile fish was impaired regardless of parental phenotype. Our data shows that developing juveniles are affected in their brain protein expression by elevated CO2, but the effect varies with the length of exposure as well as due to variation of parental phenotypes in the population.
• #### Assessing variable activity for Bayesian regression trees

(arXiv, 2020-05-27) [Preprint]
Bayesian Additive Regression Trees (BART) are non-parametric models that can capture complex exogenous variable effects. In any regression problem, it is often of interest to learn which variables are most active. Variable activity in BART is usually measured by counting the number of times a tree splits for each variable. Such one-way counts have the advantage of fast computations. Despite their convenience, one-way counts have several issues. They are statistically unjustified, cannot distinguish between main effects and interaction effects, and become inflated when measuring interaction effects. An alternative method well-established in the literature is Sobol' indices, a variance-based global sensitivity analysis technique. However, these indices often require Monte Carlo integration, which can be computationally expensive. This paper provides analytic expressions for Sobol' indices for BART predictors. These expressions are easy to interpret and are computationally feasible. Furthermore, we will show a fascinating connection between main-effects Sobol' indices and one-way counts. We also introduce a novel ranking method, and use this to demonstrate that the proposed indices preserve the Sobol'-based rank order of variable importance. Finally, we compare these methods using analytic test functions and the En-ROADS climate impacts simulator.
• #### Water and Metal–Organic Frameworks: From Interaction toward Utilization

(Chemical Reviews, American Chemical Society (ACS), 2020-05-16) [Article]
The steep stepwise uptake of water vapor and easy release at low relative pressures and moderate temperatures together with high working capacities make metal−organic frameworks (MOFs) attractive, promising materials for energy efficient applications in adsorption devices for humidity control (evaporation and condensation processes) and heat reallocation (heating and cooling) by utilizing water as benign sorptive and low-grade renewable or waste heat. Emerging MOF-based process applications covered are desiccation, heat pumps/chillers, water harvesting, air conditioning, and desalination. Governing parameters of the intrinsic sorption properties and stability under humid conditions and cyclic operation are identified. Transport of mass and heat in MOF structures, at least as important, is still an underexposed topic. Essential engineering elements of operation and implementation are presented. An update on stability of MOFs in water vapor and liquid systems is provided, and a suite of 18 MOFs are identified for selective use in heat pumps and chillers, while several can be used for air conditioning, water harvesting, and desalination. Most applications with MOFs are still in an exploratory state. An outlook is given for further R&D to realize these applications, providing essential kinetic parameters, performing smart engineering in the design of systems, and conceptual process designs to benchmark them against existing technologies. A concerted effort bridging chemistry, materials science, and engineering is required.
• #### Landscape of the non-coding transcriptome response of two Arabidopsis ecotypes to phosphate starvation

(Plant Physiology, American Society of Plant Biologists (ASPB), 2020-05-13) [Article]
Root architecture varies widely between species, and even between ecotypes of the same species, despite the strong conservation of the coding portion of their genomes. By contrast, non-coding RNAs evolve rapidly between ecotypes and may control their differential responses to the environment, since several long non-coding RNAs (lncRNAs) are known to quantitatively regulate gene expression. Roots from Columbia (Col) and Landsberg erecta (Ler) ecotypes respond differently to phosphate starvation. Here, we compared transcriptomes (mRNAs, lncRNAs, and small RNAs) of root tips from these two ecotypes during early phosphate starvation. We identified thousands of lncRNAs that were largely conserved at the DNA level in these ecotypes. In contrast to coding genes, many lncRNAs were specifically transcribed in one ecotype and/or differentially expressed between ecotypes independent of phosphate availability. We further characterized these ecotype-related lncRNAs and studied their link with siRNAs. Our analysis identified 675 lncRNAs differentially expressed between the two ecotypes, including antisense RNAs targeting key regulators of root-growth responses. Mis-regulation of several intergenic lncRNAs showed that at least two ecotype-related lncRNAs regulate primary root growth in Col. RNA-seq analysis following the deregulation of the lncRNA NPC48 revealed a potential link with root growth and transport functions. This exploration of the non-coding transcriptome identified ecotype-specific lncRNAs-mediated regulation in root apexes. The non-coding genome may harbor further mechanisms involved in ecotype adaptation of roots to different soil environments.
• #### High-purity orbital angular momentum states from a visible metasurface laser

(Nature Photonics, Springer Science and Business Media LLC, 2020-04-27) [Article]
Orbital angular momentum (OAM) from lasers holds promise for compact, at-source solutions for applications ranging from imaging to communications. However, conjugate symmetry between circular spin and opposite helicity OAM states (±ℓ) from conventional spin–orbit approaches has meant that complete control of light’s angular momentum from lasers has remained elusive. Here, we report a metasurface-enhanced laser that overcomes this limitation. We demonstrate new high-purity OAM states with quantum numbers reaching ℓ= 100 and non-symmetric vector vortex beams that lase simultaneously on independent OAM states as much as Δℓ= 90 apart, an extreme violation of previous symmetric spin–orbit lasing devices. Our laser conveniently outputs in the visible, producing new OAM states of light as well as all previously reported OAM modes from lasers, offering a compact and power-scalable source that harnesses intracavity structured matter for the creation of arbitrary chiral states of structured light.
• #### Stabilisation of dianion dimers trapped inside cyanostar macrocycles

(Physical Chemistry Chemical Physics, Royal Society of Chemistry (RSC), 2020-04-21) [Article]
<p>Interanionic H-bonds (IAHBs) are unfavourable interactions in the gas phase becoming favoured when anions are in solution. Dianion dimers are also susceptible to be trapped inside the cavities of cyanostar...</p>
• #### SportsXR -- Immersive Analytics in Sports

(arXiv, 2020-04-17) [Preprint]
We present our initial investigation of key challenges and potentials of immersive analytics (IA) in sports, which we call SportsXR. Sports are usually highly dynamic and collaborative by nature, which makes real-time decision making ubiquitous. However, there is limited support for athletes and coaches to make informed and clear-sighted decisions in real-time. SportsXR aims to support situational awareness for better and more agile decision making in sports. In this paper, we identify key challenges in SportsXR, including data collection, in-game decision making, situated sport-specific visualization design, and collaborating with domain experts. We then present potential user scenarios in training, coaching, and fan experiences. This position paper aims to inform and inspire future SportsXR research.
• #### Forecasting Multi-Dimensional Processes over Graphs

(arXiv, 2020-04-17) [Preprint]
The forecasting of multi-variate time processes through graph-based techniques has recently been addressed under the graph signal processing framework. However, problems in the representation and the processing arise when each time series carries a vector of quantities rather than a scalar one. To tackle this issue, we devise a new framework and propose new methodologies based on the graph vector autoregressive model. More explicitly, we leverage product graphs to model the high-dimensional graph data and develop multi-dimensional graph-based vector autoregressive models to forecast future trends with a number of parameters that is independent of the number of time series and a linear computational complexity. Numerical results demonstrating the prediction of moving point clouds corroborate our findings.
• #### Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis

(Genetics in Medicine, Springer Science and Business Media LLC, 2020-04-15) [Article]
The increasing use of electronic health records (EHRs) and biobanks offers unique opportunities to study Mendelian diseases. We described a novel approach to summarize clinical manifestations from patient EHRs into phenotypic evidence for cystic fibrosis (CF) with potential to alert unrecognized patients of the disease.
• #### Event Based, Near Eye Gaze Tracking Beyond 10,000Hz

(arXiv, 2020-04-07) [Preprint]
Fast and accurate eye tracking is crucial for many applications. Current camera-based eye tracking systems, however, are fundamentally limited by their bandwidth, forcing a tradeoff between image resolution and framerate, i.e. between latency and update rate. Here, we propose a hybrid frame-event-based near-eye gaze tracking system offering update rates beyond 10,000 Hz with an accuracy that matches that of high-end desktop-mounted commercial eye trackers when evaluated in the same conditions. Our system builds on emerging event cameras that simultaneously acquire regularly sampled frames and adaptively sampled events. We develop an online 2D pupil fitting method that updates a parametric model every one or few events. Moreover, we propose a polynomial regressor for estimating the gaze vector from the parametric pupil model in real time. Using the first hybrid frame-event gaze dataset, which will be made public, we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view ranging from 45 degrees to 98 degrees.