A Framework for Modeling Subgrid Effects for Two-Phase Flows in Porous Media

In this paper, we study upscaling for two-phase flows in strongly heterogeneous porous media. Upscaling a hyperbolic convection equation is known to be very difficult due to the presence of nonlocal memory effects. Even for a linear hyperbolic equation with a shear velocity field, the upscaled equation involves a nonlocal history dependent diffusion term, which is not amenable to computation. By performing a systematic multiscale analysis, we derive coupled equations for the average and the fluctuations for the two-phase flow. The homogenized equations for the coupled system are obtained by projecting the fluctuations onto a suitable subspace. This projection corresponds exactly to averaging along streamlines of the flow. Convergence of the multiscale analysis is verified numerically. Moreover, we show how to apply this multiscale analysis to upscale two-phase flows in practical applications

antGLasso: An Efficient Tensor Graphical Lasso Algorithm

The class of bigraphical lasso algorithms (and, more broadly, 'tensor'-graphical lasso algorithms) has been used to estimate dependency structures within matrix and tensor data. However, all current methods to do so take prohibitively long on modestly sized datasets. We present a novel tensor-graphical lasso algorithm that analytically estimates the dependency structure, unlike its iterative predecessors. This provides a speedup of multiple orders of magnitude, allowing this class of algorithms to be used on large, real-world datasets.Comment: 9 pages (21 including supplementary material), 8 figures, submitted to the GLFrontiers workshop at NeurIPS 202

Upscaling for Two-Phase Flows in Porous Media

The understanding and modeling of flow through porous media is an important issue in several branches of engineering. In petroleum engineering, for instance, one wishes to model the "enhanced oil recovery" process, whereby water or steam is injected into an oil saturated porous media in an attempt to displace the oil so that it can be collected. In groundwater contaminant studies the transport of dissolved material, such as toxic metals or radioactive waste, and how it affects drinking water supplies, is of interest. Numerical simulation of these flow are generally difficult. The principal reason for this is the presence of many different length scales in the physical problem, and resolving all these is computationally expensive. To circumvent these difficulties a class of methods known as upscaling methods has been developed where one attempts to solve only for large scale features of interest and model the effect of the small scale features. In this thesis, we review some of the previous efforts in upscaling and introduce a new scheme that attempts to overcome some of the existing shortcomings of these methods. In our analysis, we consider the flow problem in two distinct stages: the first is the determination of the velocity field which gives rise to an elliptic partial differential equation (PDE) and the second is a transport problem which gives rise to a hyperbolic PDE. For the elliptic part, we make use of existing upscaling methods for elliptic equations. In particular, we use the multi-scale finite element method of Hou et al. to solve for the velocity field on a coarse grid, and yet still be able to obtain fine scale information through a special means of interpolation. The analysis of the hyperbolic part forms the main contribution of this thesis. We first analyze the problem by restricting ourselves to the case where the small scales have a periodic structure. With this assumption, we are able to derive a coupled set of equations for the large scale average and the small scale fluctuations about this average. This is done by means of a special averaging, which is done along the fine scale streamlines. This coupled set of equations provides better starting point for both the modeling of the largescale small-scale interactions and the numerical implementation of any scheme. We derive an upscaling scheme from this by tracking only a sub-set of the fluctuations, which are used to approximate the scale interactions. Once this model has been derived, we discuss and present a means to extend it to the case where the fluctuations are more general than periodic. In the sections that follow we provide the details of the numerical implementation, which is a very significant part of any practical method. Finally, we present numerical results using the new scheme and compare this with both resolved computations and some existing upscaling schemes.</p

TMB-Hunt: a web server to screen sequence sets for transmembrane β-barrel proteins

TMB-Hunt is a program that uses a modified k-nearest neighbour (k-NN) algorithm to classify protein sequences as transmembrane β-barrel (TMB) or non-TMB on the basis of whole sequence amino acid composition. By including differentially weighted amino acids, evolutionary information and by calibrating the scoring, a discrimination accuracy of 92.5% was achieved, as tested using a rigorous cross-validation procedure. The TMB-Hunt web server, available at , allows screening of up to 10 000 sequences in a single query and provides results and key statistics in a simple colour coded format

TMB-Hunt: An amino acid composition based method to screen proteomes for beta-barrel transmembrane proteins

BACKGROUND: Beta-barrel transmembrane (bbtm) proteins are a functionally important and diverse group of proteins expressed in the outer membranes of bacteria (both gram negative and acid fast gram positive), mitochondria and chloroplasts. Despite recent publications describing reasonable levels of accuracy for discriminating between bbtm proteins and other proteins, screening of entire genomes remains troublesome as these molecules only constitute a small fraction of the sequences screened. Therefore, novel methods are still required capable of detecting new families of bbtm protein in diverse genomes. RESULTS: We present TMB-Hunt, a program that uses a k-Nearest Neighbour (k-NN) algorithm to discriminate between bbtm and non-bbtm proteins on the basis of their amino acid composition. By including differentially weighted amino acids, evolutionary information and by calibrating the scoring, an accuracy of 92.5% was achieved, with 91% sensitivity and 93.8% positive predictive value (PPV), using a rigorous cross-validation procedure. A major advantage of this approach is that because it does not rely on beta-strand detection, it does not require resolved structures and thus larger, more representative, training sets could be used. It is therefore believed that this approach will be invaluable in complementing other, physicochemical and homology based methods. This was demonstrated by the correct reassignment of a number of proteins which other predictors failed to classify. We have used the algorithm to screen several genomes and have discussed our findings. CONCLUSION: TMB-Hunt achieves a prediction accuracy level better than other approaches published to date. Results were significantly enhanced by use of evolutionary information and a system for calibrating k-NN scoring. Because the program uses a distinct approach to that of other discriminators and thus suffers different liabilities, we believe it will make a significant contribution to the development of a consensus approach for bbtm protein detection

Pushing the boundaries: integration of multi-source digital elevation model data for seamless geological mapping of the UK's coastal zone

Recent advances in marine acoustic survey and land-based topographic monitoring technologies have resulted in increasingly cost-effective data acquisition in coastal areas. The DEFRA-funded National Network of Regional Coastal Monitoring Programmes of England are, for example, utilising swath bathymetry and airborne light detection and ranging (LiDAR) technology more routinely to survey the coastal zone around the coastline of England. The demand for data processing, visualisation and interpretation techniques to keep pace with such advances in data acquisition is clear. This study discusses collection and processing techniques for such data on the south coast of Dorset, England, which have enabled the production of a seamless, high spatial resolution digital elevation model across the coastal zone. Case studies demonstrate how this elevation model can be viewed and analysed using state-of-the-art digital techniques to allow geological mapping to be extended from onshore to offshore in unprecedented detail, effectively eliminating what is known as the ‘White Ribbon’ for coastal geological mapping. The potential for rolling out such techniques for wider surveying programmes across many environmental disciplines is significant, which could contribute towards improving the multi-disciplinary scientific evidence base in the complex coastal zone

Interpreting monitoring data for shoreline and geohazard mapping

The demand for marine-related spatial information has become increasingly apparent in recent years at a European and national scale, due to the increased pressures on the sea-floor environments and marine resources of UK territorial waters. The advent of economically viable swath bathymetry data acquisition in the coastal zone and effective collaborative partnerships between the Channel Coastal Observatory, Maritime and Coastguard Agency, UK Hydrographic Office, British Geological Survey and academic institutions, have opened up new opportunities to produce a robust scientific evidence base to inform integrated coastal zone management objectives and contribute to wider scientific initiatives. Interpretation of high-quality bathymetric data, acoustic backscatter and ground-truthing data allows zones of exposed bedrock, rock outcrops and pinnacles to be identified, along with areas of mobility or stability of surficial sediments. Temporal and spatial analyses of coastal and marine monitoring datasets also contribute to improved understanding of interactions between natural coastal process and coastal-defence and beach-management operations. Furthermore, developments in three-dimensional mapping techniques and visualisation technologies have enabled seamless high-resolution coastal geology maps to be re-interpreted and extended offshore, providing a more complete picture of the baseline geology, physical properties, structure and geohazards in the coastal and nearshore zone. The full paper details the methodology developed to produce a range of indicative marine mapping layers, and presents examples from eastern and southern England where marine-related spatial data has contributed to the multi-disciplinary scientific evidence base to inform development of UK marine policy and planning, coastal management and coastal zone geological mappin

Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation.

Metazoan development involves the successive activation and silencing of specific gene expression programs and is driven by tissue-specific transcription factors programming the chromatin landscape. To understand how this process executes an entire developmental pathway, we generated global gene expression, chromatin accessibility, histone modification, and transcription factor binding data from purified embryonic stem cell-derived cells representing six sequential stages of hematopoietic specification and differentiation. Our data reveal the nature of regulatory elements driving differential gene expression and inform how transcription factor binding impacts on promoter activity. We present a dynamic core regulatory network model for hematopoietic specification and demonstrate its utility for the design of reprogramming experiments. Functional studies motivated by our genome-wide data uncovered a stage-specific role for TEAD/YAP factors in mammalian hematopoietic specification. Our study presents a powerful resource for studying hematopoiesis and demonstrates how such data advance our understanding of mammalian development.This work was funded by a Longer Larger (LoLa) consortium grant from the Biotechnology and Biological Sciences Research Council, UK, to the senior authors and the corresponding author, computing infrastructure grants from the Wellcome Trust and National Institute for Health Research to B.G., grants from Cancer Research UK to G.L. and V.K., and funding from the Bloodwise charity to C.B.This is the final version of the article. It first appeared from Cell Press via http://dx.doi.org/10.1016/j.devcel.2016.01.02