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At least 1,171 records · Page 65

An Entropy-Based Test and Development Framework for Uncertainty Modeling in Level-Set Visualizations

We present a simple comparative framework for testing and developing uncertainty modeling in uncertain marching cubes implementations. The selection of a model to represent the probability distribution of uncertain values directly influences the memory use, run time, and accuracy of an uncertainty visualization algorithm. We use an entropy calculation directly on ensemble data to establish an expected result and then compare the entropy from various probability models, including uniform, Gaussian, histogram, and quantile models. Our results verify that models matching the distribution of the ensemble indeed match the entropy. We further show that fewer bins in nonparametric histogram models are more effective whereas large numbers of bins in quantile models approach data accuracy.

Sisneros, Robert↗

Identification of synthetic consortia from a set of plant-beneficial bacteria

The use of microbial inoculants in agriculture as biofertilisers and/or biopesticides is an appealing alternative to replace or reduce the practice of agrochemicals. Plant microbiota studies are revealing the different bacterial groups which are populating plant microbiomes re-energising the plant probiotic bacteria (PPB) translational research sector. Some single-microbial strain bioinoculants have proven valid in agriculture (e.g., based on Trichoderma, mycorrhiza or rhizobia); however, it is now recommended to consider multistrain consortia since plant-beneficial effects are often a result of community-level interactions in plant microbiomes. A limiting step is the selection of a fitting combination of microbial strains in order to accomplish the best beneficial effect upon plant inoculation. In this study, we have used a subset of 23 previously identified and characterised rice-beneficial bacterial colonisers to design and test a series of associated experiments aimed to identify potential PPB consortia which are able to co-colonise and induce plant growth promotion. Bacterial strains were co-inoculated in vitro and in planta using several different methods and their co-colonisation and co-persistence monitored. Results include the identification of two 5-strain and one 2-strain consortia which displayed plant growth-promoting features. Future practical applications of microbiome research must include experiments aimed at identifying consortia of bacteria which can be most effective as crop amendments.

59 BASIC BIOLOGICAL SCIENCES↗

An improved representation of the relationship between photosynthesis and stomatal conductance leads to more stable estimation of conductance parameters and improves the goodness-of-fit across diverse data sets

Stomata play a central role in surface-atmosphere exchange by controlling the flux of water and CO 2 between the leaf and the atmosphere. Representation of stomatal conductance (g sw ) is therefore an essential component of models that seek to simulate water and CO 2 exchange in plants and ecosystems. For given environmental conditions at the leaf surface (CO 2 concentration and vapor pressure deficit or relative humidity), models typically assume a linear relationship between g sw and photosynthetic CO 2 assimilation (A). However, measurement of leaf-level g sw response curves to changes in A are rare, particularly in the tropics, resulting in only limited data to evaluate this key assumption. Here, we measured the response of g sw and A to irradiance in six tropical species at different leaf phenological stages. We showed that the relationship between g sw and A was not linear, challenging the key assumption upon which optimality theory is based-that the marginal cost of water gain is constant. Our data showed that increasing A resulted in a small increase in g sw at low irradiance, but a much larger increase at high irradiance. We reformulated the popular Unified Stomatal Optimization (USO) model to account for this phenomenon and to enable consistent estimation of the key conductance parameters g 0 and g 1 . Our modification of the USO model improved the goodness-of-fit and reduced bias, enabling robust estimation of conductance parameters at any irradiance. In addition, our modification revealed previously undetectable relationships between the stomatal slope parameter g 1 and other leaf traits. We also observed nonlinear behavior between A and g sw in independent datasets that included data collected from attached and detached leaves, and from plants grown at elevated CO 2 concentration. We propose that this empirical modification of the USO model can improve the measurement of g sw parameters and the estimation of plant and ecosystem-scale water and CO 2 fluxes.

54 ENVIRONMENTAL SCIENCES↗

UNDERSTANDING THE SEMI-PROBABILISTIC APPROACHES IN STRUCTURAL RELIABILITY USED TO SET DESIGN RELIABILITY TARGETS FOR GRAPHITE COMPONENTS USING ASME BPVC METHODS

Graphite is a quasi-brittle material, resulting in random variability in tensile strength distributions. To account for the random variability in strength, HHA-3000 of the ASME BPVC provides two semi-probabilistic methods for qualifying nuclear graphite components in the design stage, the simplified and full assessments. The full and simplified assessments apply statistical methods to engineering-based design problems. This is often referred to as reliability-based design. Reliability-based design (RBD) is a method to develop reliable designs by accounting for uncertainties and result in small chances of failure when also considering safety factors. RBDs provide reliability targets using semi-probabilistic approaches. RBD is implemented in ASME BPVC HHA-3000 for nuclear graphite components, but is not specific to that application. There has been much confusion around the methods implemented in ASME BPVC HHA-3000 for qualifying nuclear graphite components. To address the confusion, this paper takes a hierarchical approach. First, the general RBD framework is presented. Then, the semi-probabilistic methods and the underlying assumptions implemented in the assessments are presented. The semi-probabilistic methods are separated from the engineering modifications that have been made to the assessments. After building the framework and underlying assumptions, the specific methods in the full and simplified assessments are explained in three steps: inputs, methods, outputs. The methods are applied to an H-451 reflector block. Tensile strength properties for other graphite grades are provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Transcriptomic data sets for Novosphingobium aromaticivorans DSM12444 and a ΔSARO_RS14285 mutant grown in the presence of glucose and either protocatechuic, vanillic, syringic, or 4-coumaric acid

The SARO_RS14285 gene, encoding a transcription factor, was deleted in Novosphingobium aromaticivorans DSM12444. The transcriptomes of the parent and ΔSARO_RS14285 strains were determined when grown in medium containing glucose with or without protocatechuic, vanillic, syringic, or 4-coumaric acid. We present the raw RNA sequencing data obtained from these cultures.

Novosphingobium aromaticivorans↗

Transcriptomic Data Sets for Zymomonas mobilis 2032 during Fermentation of Ammonia Fiber Expansion (AFEX)-Pretreated Corn Stover and Switchgrass Hydrolysates

The transcriptomes of Zymomonas mobilis 2032 were captured during the fermentation of ammonia fiber expansion (AFEX)-pretreated corn stover and switchgrass hydrolysates containing different concentrations of glucose and xylose. RNA samples were collected when Z. mobilis was fermenting glucose or xylose. Here, we present transcriptome sequencing (RNA-Seq) data obtained during separate phases of glucose or xylose consumption.

59 BASIC BIOLOGICAL SCIENCES↗

COnTORT: COmprehensive Transcriptomic ORganizational Tool for Simultaneously Retrieving and Organizing Numerous Gene Expression Data Sets from the NCBI Gene Expression Omnibus Database

We introduce COnTORT ( CO mprehensive T ranscriptomic OR ganizational T ool), a publicly available program that retrieves all available gene expression data and associated metadata for an organism from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. The data are compiled into text files that can be used for downstream bioinformatic applications.

Myers, Kevin S.↗

Transcriptomic data sets for Novosphingobium aromaticivorans grown with the β-5-linked aromatic dimer dehydrodiconiferyl alcohol and the related G-aromatic monomers vanillin and ferulic acid

ABSTRACT The transcriptomes of a 2-pyrone-4,6-dicarboxylic acid-producing strain of Novosphingobium aromaticivorans DSM12444 were determined when grown in minimal medium containing glucose alone or glucose plus vanillin, ferulic acid, or the β-5-linked aromatic dimer dehydrodiconiferyl alcohol as carbon sources. Here, we present the RNA-sequencing data we obtained.

Metz, Fletcher↗

Transcriptomic data sets examining several stress responses in Zymomonas mobilis strains

We used RNA-seq to compare gene expression from Zymomonas mobilis ZM4 grown under various conditions: aerobic ± paraquat, anaerobic ± hydrogen peroxide, or an iron chelator. We analyzed two mutant strains lacking predicted transcription factors (ZMO_0442 and ZMO_1411) grown under aerobic or anaerobic conditions. We report the RNA-seq data from these experiments.

Bacterial Stress Response↗

Fast Solution of Fully Implicit Runge--Kutta and Discontinuous Galerkin in Time for Numerical PDEs, Part I: the Linear Setting

Fully implicit Runge--Kutta (IRK) methods have many desirable properties as time integration schemes in terms of accuracy and stability, but high-order IRK methods are not commonly used in practice with numerical PDEs due to the difficulty of solving the stage equations. This paper introduces a theoretical and algorithmic preconditioning framework for solving the systems of equations that arise from IRK methods applied to linear numerical PDEs (without algebraic constraints). Additionally, this framework also naturally applies to discontinuous Galerkin discretizations in time. Under quite general assumptions on the spatial discretization that yield stable time integration, the preconditioned operator is proven to have condition number bounded by a small, order-one constant, independent of the spatial mesh and time-step size, and with only weak dependence on number of stages/polynomial order; for example, the preconditioned operator for 10th-order Gauss IRK has condition number less than two, independent of the spatial discretization and time step. The new method can be used with arbitrary existing preconditioners for backward Euler-type time-stepping schemes and is amenable to the use of three-term recursion Krylov methods when the underlying spatial discretization is symmetric. The new method is demonstrated to be effective on various high-order finite-difference and finite element discretizations of linear parabolic and hyperbolic problems, demonstrating fast, scalable solution of up to 10th-order accuracy. The new method consistently outperforms existing block preconditioning approaches, and in several cases, the new method can achieve 4th-order accuracy using Gauss integration with roughly half the number of preconditioner applications and wallclock time as required using standard diagonally IRK methods.

97 MATHEMATICS AND COMPUTING↗