Learning-based stochastic object models for use in optimizing imaging systems

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Anastasio, Mark A.; Yu, Lifeng; Li, Hua

2017-03-01

It is widely known that the optimization of imaging systems based on objective, or task-based, measures of image quality via computer-simulation requires use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in anatomy within a specified ensemble of patients remains a challenging task. Because they are established by use of image data corresponding a single patient, previously reported numerical anatomical models lack of the ability to accurately model inter- patient variations in anatomy. In certain applications, however, databases of high-quality volumetric images are available that can facilitate this task. In this work, a novel and tractable methodology for learning a SOM from a set of volumetric training images is developed. The proposed method is based upon geometric attribute distribution (GAD) models, which characterize the inter-structural centroid variations and the intra-structural shape variations of each individual anatomical structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations learned from training data. By use of the GAD models, random organ shapes and positions can be generated and integrated to form an anatomical phantom. The randomness in organ shape and position will reflect the variability of anatomy present in the training data. To demonstrate the methodology, a SOM corresponding to the pelvis of an adult male was computed and a corresponding ensemble of phantoms was created. Additionally, computer-simulated X-ray projection images corresponding to the phantoms were computed, from which tomographic images were reconstructed.

Phase diagram for the Winfree model of coupled nonlinear oscillators.

PubMed

Ariaratnam, J T; Strogatz, S H

2001-05-07

In 1967 Winfree proposed a mean-field model for the spontaneous synchronization of chorusing crickets, flashing fireflies, circadian pacemaker cells, or other large populations of biological oscillators. Here we give the first bifurcation analysis of the model, for a tractable special case. The system displays rich collective dynamics as a function of the coupling strength and the spread of natural frequencies. Besides incoherence, frequency locking, and oscillator death, there exist hybrid solutions that combine two or more of these states. We present the phase diagram and derive several of the stability boundaries analytically.

Phase Diagram for the Winfree Model of Coupled Nonlinear Oscillators

NASA Astrophysics Data System (ADS)

Ariaratnam, Joel T.; Strogatz, Steven H.

2001-05-01

In 1967 Winfree proposed a mean-field model for the spontaneous synchronization of chorusing crickets, flashing fireflies, circadian pacemaker cells, or other large populations of biological oscillators. Here we give the first bifurcation analysis of the model, for a tractable special case. The system displays rich collective dynamics as a function of the coupling strength and the spread of natural frequencies. Besides incoherence, frequency locking, and oscillator death, there exist hybrid solutions that combine two or more of these states. We present the phase diagram and derive several of the stability boundaries analytically.

Practical Application of Model-based Programming and State-based Architecture to Space Missions

NASA Technical Reports Server (NTRS)

Horvath, Gregory; Ingham, Michel; Chung, Seung; Martin, Oliver; Williams, Brian

2006-01-01

A viewgraph presentation to develop models from systems engineers that accomplish mission objectives and manage the health of the system is shown. The topics include: 1) Overview; 2) Motivation; 3) Objective/Vision; 4) Approach; 5) Background: The Mission Data System; 6) Background: State-based Control Architecture System; 7) Background: State Analysis; 8) Overview of State Analysis; 9) Background: MDS Software Frameworks; 10) Background: Model-based Programming; 10) Background: Titan Model-based Executive; 11) Model-based Execution Architecture; 12) Compatibility Analysis of MDS and Titan Architectures; 13) Integrating Model-based Programming and Execution into the Architecture; 14) State Analysis and Modeling; 15) IMU Subsystem State Effects Diagram; 16) Titan Subsystem Model: IMU Health; 17) Integrating Model-based Programming and Execution into the Software IMU; 18) Testing Program; 19) Computationally Tractable State Estimation & Fault Diagnosis; 20) Diagnostic Algorithm Performance; 21) Integration and Test Issues; 22) Demonstrated Benefits; and 23) Next Steps

Systems, methods and apparatus for modeling, specifying and deploying policies in autonomous and autonomic systems using agent-oriented software engineering

NASA Technical Reports Server (NTRS)

Sterritt, Roy (Inventor); Hinchey, Michael G. (Inventor); Penn, Joaquin (Inventor)

2011-01-01

Systems, methods and apparatus are provided through which in some embodiments, an agent-oriented specification modeled with MaCMAS, is analyzed, flaws in the agent-oriented specification modeled with MaCMAS are corrected, and an implementation is derived from the corrected agent-oriented specification. Described herein are systems, method and apparatus that produce fully (mathematically) tractable development of agent-oriented specification(s) modeled with methodology fragment for analyzing complex multiagent systems (MaCMAS) and policies for autonomic systems from requirements through to code generation. The systems, method and apparatus described herein are illustrated through an example showing how user formulated policies can be translated into a formal mode which can then be converted to code. The requirements-based programming systems, method and apparatus described herein may provide faster, higher quality development and maintenance of autonomic systems based on user formulation of policies.

Chapter 4. New model systems for the study of developmental evolution in plants.

PubMed

Kramer, Elena M

2009-01-01

The number of genetically tractable plant model systems is rapidly increasing, thanks to the decreasing cost of sequencing and the wide amenability of plants to stable transformation and other functional approaches. In this chapter, I discuss emerging model systems from throughout the land plant phylogeny and consider how their unique attributes are contributing to our understanding of development, evolution, and ecology. These new models are being developed using two distinct strategies: in some cases, they are selected because of their close relationship to the established models, while in others, they are chosen with the explicit intention of exploring distantly related plant lineages. Such complementary approaches are yielding exciting new results that shed light on both micro- and macroevolutionary processes in the context of developmental evolution.

Broad AOX expression in a genetically tractable mouse model does not disturb normal physiology

PubMed Central

Szibor, Marten; Dhandapani, Praveen K.; Dufour, Eric; Holmström, Kira M.; Zhuang, Yuan; Salwig, Isabelle; Wittig, Ilka; Heidler, Juliana; Gizatullina, Zemfira; Fuchs, Helmut; Gailus-Durner, Valérie; de Angelis, Martin Hrabě; Nandania, Jatin; Velagapudi, Vidya; Wietelmann, Astrid; Rustin, Pierre; Gellerich, Frank N.; Braun, Thomas

2017-01-01

ABSTRACT Plants and many lower organisms, but not mammals, express alternative oxidases (AOXs) that branch the mitochondrial respiratory chain, transferring electrons directly from ubiquinol to oxygen without proton pumping. Thus, they maintain electron flow under conditions when the classical respiratory chain is impaired, limiting excess production of oxygen radicals and supporting redox and metabolic homeostasis. AOX from Ciona intestinalis has been used to study and mitigate mitochondrial impairments in mammalian cell lines, Drosophila disease models and, most recently, in the mouse, where multiple lentivector-AOX transgenes conferred substantial expression in specific tissues. Here, we describe a genetically tractable mouse model in which Ciona AOX has been targeted to the Rosa26 locus for ubiquitous expression. The AOXRosa26 mouse exhibited only subtle phenotypic effects on respiratory complex formation, oxygen consumption or the global metabolome, and showed an essentially normal physiology. AOX conferred robust resistance to inhibitors of the respiratory chain in organello; moreover, animals exposed to a systemically applied LD50 dose of cyanide did not succumb. The AOXRosa26 mouse is a useful tool to investigate respiratory control mechanisms and to decipher mitochondrial disease aetiology in vivo. PMID:28067626

Automated Environment Generation for Software Model Checking

NASA Technical Reports Server (NTRS)

Tkachuk, Oksana; Dwyer, Matthew B.; Pasareanu, Corina S.

2003-01-01

A key problem in model checking open systems is environment modeling (i.e., representing the behavior of the execution context of the system under analysis). Software systems are fundamentally open since their behavior is dependent on patterns of invocation of system components and values defined outside the system but referenced within the system. Whether reasoning about the behavior of whole programs or about program components, an abstract model of the environment can be essential in enabling sufficiently precise yet tractable verification. In this paper, we describe an approach to generating environments of Java program fragments. This approach integrates formally specified assumptions about environment behavior with sound abstractions of environment implementations to form a model of the environment. The approach is implemented in the Bandera Environment Generator (BEG) which we describe along with our experience using BEG to reason about properties of several non-trivial concurrent Java programs.

Model-Based Optimal Experimental Design for Complex Physical Systems

DTIC Science & Technology

2015-12-03

for public release. magnitude reduction in estimator error required to make solving the exact optimal design problem tractable. Instead of using a naive...for designing a sequence of experiments uses suboptimal approaches: batch design that has no feedback, or greedy ( myopic ) design that optimally...approved for public release. Equation 1 is difficult to solve directly, but can be expressed in an equivalent form using the principle of dynamic programming

Analysis of SI models with multiple interacting populations using subpopulations.

PubMed

Thomas, Evelyn K; Gurski, Katharine F; Hoffman, Kathleen A

2015-02-01

Computing endemic equilibria and basic reproductive numbers for systems of differential equations describing epidemiological systems with multiple connections between subpopulations is often algebraically intractable. We present an alternative method which deconstructs the larger system into smaller subsystems and captures the interactions between the smaller systems as external forces using an approximate model. We bound the basic reproductive numbers of the full system in terms of the basic reproductive numbers of the smaller systems and use the alternate model to provide approximations for the endemic equilibrium. In addition to creating algebraically tractable reproductive numbers and endemic equilibria, we can demonstrate the influence of the interactions between subpopulations on the basic reproductive number of the full system. The focus of this paper is to provide analytical tools to help guide public health decisions with limited intervention resources.

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Simulating social-ecological systems: the Island Digital Ecosystem Avatars (IDEA) consortium.

PubMed

Davies, Neil; Field, Dawn; Gavaghan, David; Holbrook, Sally J; Planes, Serge; Troyer, Matthias; Bonsall, Michael; Claudet, Joachim; Roderick, George; Schmitt, Russell J; Zettler, Linda Amaral; Berteaux, Véronique; Bossin, Hervé C; Cabasse, Charlotte; Collin, Antoine; Deck, John; Dell, Tony; Dunne, Jennifer; Gates, Ruth; Harfoot, Mike; Hench, James L; Hopuare, Marania; Kirch, Patrick; Kotoulas, Georgios; Kosenkov, Alex; Kusenko, Alex; Leichter, James J; Lenihan, Hunter; Magoulas, Antonios; Martinez, Neo; Meyer, Chris; Stoll, Benoit; Swalla, Billie; Tartakovsky, Daniel M; Murphy, Hinano Teavai; Turyshev, Slava; Valdvinos, Fernanda; Williams, Rich; Wood, Spencer

2016-01-01

Systems biology promises to revolutionize medicine, yet human wellbeing is also inherently linked to healthy societies and environments (sustainability). The IDEA Consortium is a systems ecology open science initiative to conduct the basic scientific research needed to build use-oriented simulations (avatars) of entire social-ecological systems. Islands are the most scientifically tractable places for these studies and we begin with one of the best known: Moorea, French Polynesia. The Moorea IDEA will be a sustainability simulator modeling links and feedbacks between climate, environment, biodiversity, and human activities across a coupled marine-terrestrial landscape. As a model system, the resulting knowledge and tools will improve our ability to predict human and natural change on Moorea and elsewhere at scales relevant to management/conservation actions.

A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

PubMed Central

Blackiston, Douglas; Shomrat, Tal; Nicolas, Cindy L.; Granata, Christopher; Levin, Michael

2010-01-01

A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science. PMID:21179424

Novel Gbeta Mimic Kelch Proteins (Gpb1 and Gpb2 Connect G-Protein Signaling to Ras via Yeast Neurofibromin Homologs Ira1 and Ira2: A Model for Human NF1

DTIC Science & Technology

2008-03-01

tractable fungal model system, Cryptococcus neoformans, and identified two kelch repeat homologs that are involved in mating (Kem1 and Kem2). To...find kelch-repeat proteins involved in G protein signaling, Cryptococcus homologues of Gpb1/2, which interacts with and negatively regulates the G...protein alpha subunit, Gpa2, in S. cerevisiae, were searched by BLAST (tblastn) in Cryptococcus genome database of serotype A (Duke University Medical

Engineering coherence among excited states in synthetic heterodimer systems.

PubMed

Hayes, Dugan; Griffin, Graham B; Engel, Gregory S

2013-06-21

The design principles that support persistent electronic coherence in biological light-harvesting systems are obscured by the complexity of such systems. Some electronic coherences in these systems survive for hundreds of femtoseconds at physiological temperatures, suggesting that coherent dynamics may play a role in photosynthetic energy transfer. Coherent effects may increase energy transfer efficiency relative to strictly incoherent transfer mechanisms. Simple, tractable, manipulable model systems are required in order to probe the fundamental physics underlying these persistent electronic coherences, but to date, these quantum effects have not been observed in small molecules. We have engineered a series of rigid synthetic heterodimers that can serve as such a model system and observed quantum beating signals in their two-dimensional electronic spectra consistent with the presence of persistent electronic coherences.

Robust Fixed-Structure Controller Synthesis

NASA Technical Reports Server (NTRS)

Corrado, Joseph R.; Haddad, Wassim M.; Gupta, Kajal (Technical Monitor)

2000-01-01

The ability to develop an integrated control system design methodology for robust high performance controllers satisfying multiple design criteria and real world hardware constraints constitutes a challenging task. The increasingly stringent performance specifications required for controlling such systems necessitates a trade-off between controller complexity and robustness. The principle challenge of the minimal complexity robust control design is to arrive at a tractable control design formulation in spite of the extreme complexity of such systems. Hence, design of minimal complexitY robust controllers for systems in the face of modeling errors has been a major preoccupation of system and control theorists and practitioners for the past several decades.

On dependency properties of the ISIs generated by a two-compartmental neuronal model.

PubMed

Benedetto, Elisa; Sacerdote, Laura

2013-02-01

One-dimensional leaky integrate and fire neuronal models describe interspike intervals (ISIs) of a neuron as a renewal process and disregarding the neuron geometry. Many multi-compartment models account for the geometrical features of the neuron but are too complex for their mathematical tractability. Leaky integrate and fire two-compartment models seem a good compromise between mathematical tractability and an improved realism. They indeed allow to relax the renewal hypothesis, typical of one-dimensional models, without introducing too strong mathematical difficulties. Here, we pursue the analysis of the two-compartment model studied by Lansky and Rodriguez (Phys D 132:267-286, 1999), aiming of introducing some specific mathematical results used together with simulation techniques. With the aid of these methods, we investigate dependency properties of ISIs for different values of the model parameters. We show that an increase of the input increases the strength of the dependence between successive ISIs.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

PubMed

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2012-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

PubMed Central

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. PMID:24688682

A two-fluid model for avalanche and debris flows.

PubMed

Pitman, E Bruce; Le, Long

2005-07-15

Geophysical mass flows--debris flows, avalanches, landslides--can contain O(10(6)-10(10)) m(3) or more of material, often a mixture of soil and rocks with a significant quantity of interstitial fluid. These flows can be tens of meters in depth and hundreds of meters in length. The range of scales and the rheology of this mixture presents significant modelling and computational challenges. This paper describes a depth-averaged 'thin layer' model of geophysical mass flows containing a mixture of solid material and fluid. The model is derived from a 'two-phase' or 'two-fluid' system of equations commonly used in engineering research. Phenomenological modelling and depth averaging combine to yield a tractable set of equations, a hyperbolic system that describes the motion of the two constituent phases. If the fluid inertia is small, a reduced model system that is easier to solve may be derived.

Self-calibrating models for dynamic monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin

1994-01-01

The present goal in qualitative reasoning is to develop methods for automatically building qualitative and semiquantitative models of dynamic systems and to use them for monitoring and fault diagnosis. The qualitative approach to modeling provides a guarantee of coverage while our semiquantitative methods support convergence toward a numerical model as observations are accumulated. We have developed and applied methods for automatic creation of qualitative models, developed two methods for obtaining tractable results on problems that were previously intractable for qualitative simulation, and developed more powerful methods for learning semiquantitative models from observations and deriving semiquantitative predictions from them. With these advances, qualitative reasoning comes significantly closer to realizing its aims as a practical engineering method.

Automated adaptive inference of phenomenological dynamical models.

PubMed

Daniels, Bryan C; Nemenman, Ilya

2015-08-21

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.

Automated adaptive inference of phenomenological dynamical models

PubMed Central

Daniels, Bryan C.; Nemenman, Ilya

2015-01-01

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508

Epithelial Patterning, Morphogenesis, and Evolution: Drosophila Eggshell as a Model.

PubMed

Osterfield, Miriam; Berg, Celeste A; Shvartsman, Stanislav Y

2017-05-22

Understanding the mechanisms driving tissue and organ formation requires knowledge across scales. How do signaling pathways specify distinct tissue types? How does the patterning system control morphogenesis? How do these processes evolve? The Drosophila egg chamber, where EGF and BMP signaling intersect to specify unique cell types that construct epithelial tubes for specialized eggshell structures, has provided a tractable system to ask these questions. Work there has elucidated connections between scales of development, including across evolutionary scales, and fostered the development of quantitative modeling tools. These tools and general principles can be applied to the understanding of other developmental processes across organisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Canadian Association of Neurosciences Review: learning at a snail's pace.

PubMed

Parvez, Kashif; Rosenegger, David; Martens, Kara; Orr, Michael; Lukowiak, Ken

2006-11-01

While learning and memory are related, they are distinct processes each with different forms of expression and underlying molecular mechanisms. An invertebrate model system, Lymnaea stagnalis, is used to study memory formation of a non-declarative memory. We have done so because: (1) We have discovered the neural circuit that mediates an interesting and tractable behaviour; (2) This behaviour can be operantly conditioned and intermediate-term and long-term memory can be demonstrated; and (3) It is possible to demonstrate that a single neuron in the model system is a necessary site of memory formation. This article reviews how Lymnaea has been used in the study of behavioural and molecular mechanisms underlying consolidation, reconsolidation, extinction and forgetting.

Learning planar Ising models

DOE PAGES

Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael; ...

2016-12-01

Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the bestmore » planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.« less

Learning planar Ising models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael

Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the bestmore » planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.« less

An overview of C. elegans biology.

PubMed

Strange, Kevin

2006-01-01

The establishment of Caenorhabditis elegans as a "model organism" began with the efforts of Sydney Brenner in the early 1960s. Brenner's focus was to find a suitable animal model in which the tools of genetic analysis could be used to define molecular mechanisms of development and nervous system function. C. elegans provides numerous experimental advantages for such studies. These advantages include a short life cycle, production of large numbers of offspring, easy and inexpensive laboratory culture, forward and reverse genetic tractability, and a relatively simple anatomy. This chapter will provide a brief overview of C. elegans biology.

Landau-Zener extension of the Tavis-Cummings model: Structure of the solution

DOE PAGES

Sun, Chen; Sinitsyn, Nikolai A.

2016-09-07

We explore the recently discovered solution of the driven Tavis-Cummings model (DTCM). It describes interaction of an arbitrary number of two-level systems with a bosonic mode that has linearly time-dependent frequency. We derive compact and tractable expressions for transition probabilities in terms of the well-known special functions. In this form, our formulas are suitable for fast numerical calculations and analytical approximations. As an application, we obtain the semiclassical limit of the exact solution and compare it to prior approximations. Furthermore, we also reveal connection between DTCM and q-deformed binomial statistics.

Spatial organization of bacterial chromosomes

PubMed Central

Wang, Xindan; Rudner, David Z.

2014-01-01

Bacterial chromosomes are organized in stereotypical patterns that are faithfully and robustly regenerated in daughter cells. Two distinct spatial patterns were described almost a decade ago in our most tractable model organisms. In recent years, analysis of chromosome organization in a larger and more diverse set of bacteria and a deeper characterization of chromosome dynamics in the original model systems have provided a broader and more complete picture of both chromosome organization and the activities that generate the observed spatial patterns. Here, we summarize these different patterns highlighting similarities and differences and discuss the protein factors that help establish and maintain them. PMID:25460798

Numerical Test of the Additivity Principle in Anomalous Transport

NASA Astrophysics Data System (ADS)

Tamaki, Shuji

2017-10-01

The additivity principle (AP) is one of the remarkable predictions that systematically generates all information on current fluctuations once the value of average current in the linear response regime is input. However, conditions to justify the AP are still ambiguous. We hence consider three tractable models, and discuss possible conditions. The models include the harmonic chain (HC), momentum exchange (ME) model, and momentum flip (MF) model, which respectively show ballistic, anomalous, and diffusive transport. We compare the heat current cumulants predicted by the AP with exact numerical data obtained for these models. The HC does not show the AP, whereas the MF model satisfies it, as expected, since the AP was originally proposed for diffusive systems. Surprisingly, the ME model also shows the AP. The ME model is known to show the anomalous transport similar to that shown in nonlinear systems such as the Fermi-Pasta-Ulam model. Our finding indicates that general nonlinear systems may satisfy the AP. Possible conditions for satisfying the AP are discussed.

OCSEGen: Open Components and Systems Environment Generator

NASA Technical Reports Server (NTRS)

Tkachuk, Oksana

2014-01-01

To analyze a large system, one often needs to break it into smaller components.To analyze a component or unit under analysis, one needs to model its context of execution, called environment, which represents the components with which the unit interacts. Environment generation is a challenging problem, because the environment needs to be general enough to uncover unit errors, yet precise enough to make the analysis tractable. In this paper, we present a tool for automated environment generation for open components and systems. The tool, called OCSEGen, is implemented on top of the Soot framework. We present the tool's current support and discuss its possible future extensions.

A Formal Approach to Requirements-Based Programming

NASA Technical Reports Server (NTRS)

Hinchey, Michael G.; Rash, James L.; Rouff, Christopher A.

2005-01-01

No significant general-purpose method is currently available to mechanically transform system requirements into a provably equivalent model. The widespread use of such a method represents a necessary step toward high-dependability system engineering for numerous application domains. Current tools and methods that start with a formal model of a system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The "gap" unfilled by such tools and methods is that the formal models cannot be proven to be equivalent to the requirements. We offer a method for mechanically transforming requirements into a provably equivalent formal model that can be used as the basis for code generation and other transformations. This method is unique in offering full mathematical tractability while using notations and techniques that are well known and well trusted. Finally, we describe further application areas we are investigating for use of the approach.

Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Webster, Katherine E.; Bremigan, Mary T.; Wagner, Tyler; Stow, Craig A.

2010-01-01

Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

On modeling animal movements using Brownian motion with measurement error.

PubMed

Pozdnyakov, Vladimir; Meyer, Thomas; Wang, Yu-Bo; Yan, Jun

2014-02-01

Modeling animal movements with Brownian motion (or more generally by a Gaussian process) has a long tradition in ecological studies. The recent Brownian bridge movement model (BBMM), which incorporates measurement errors, has been quickly adopted by ecologists because of its simplicity and tractability. We discuss some nontrivial properties of the discrete-time stochastic process that results from observing a Brownian motion with added normal noise at discrete times. In particular, we demonstrate that the observed sequence of random variables is not Markov. Consequently the expected occupation time between two successively observed locations does not depend on just those two observations; the whole path must be taken into account. Nonetheless, the exact likelihood function of the observed time series remains tractable; it requires only sparse matrix computations. The likelihood-based estimation procedure is described in detail and compared to the BBMM estimation.

New tools for the analysis of glial cell biology in Drosophila.

PubMed

Awasaki, Takeshi; Lee, Tzumin

2011-09-01

Because of its genetic, molecular, and behavioral tractability, Drosophila has emerged as a powerful model system for studying molecular and cellular mechanisms underlying the development and function of nervous systems. The Drosophila nervous system has fewer neurons and exhibits a lower glia:neuron ratio than is seen in vertebrate nervous systems. Despite the simplicity of the Drosophila nervous system, glial organization in flies is as sophisticated as it is in vertebrates. Furthermore, fly glial cells play vital roles in neural development and behavior. In addition, powerful genetic tools are continuously being created to explore cell function in vivo. In taking advantage of these features, the fly nervous system serves as an excellent model system to study general aspects of glial cell development and function in vivo. In this article, we review and discuss advanced genetic tools that are potentially useful for understanding glial cell biology in Drosophila. Copyright © 2011 Wiley-Liss, Inc.

Fold or hold: experimental evolution in vitro

PubMed Central

Collins, S; Rambaut, A; Bridgett, S J

2013-01-01

We introduce a system for experimental evolution consisting of populations of short oligonucleotides (Oli populations) evolving in a modified quantitative polymerase chain reaction (qPCR). It is tractable at the genetic, genomic, phenotypic and fitness levels. The Oli system uses DNA hairpins designed to form structures that self-prime under defined conditions. Selection acts on the phenotype of self-priming, after which differences in fitness are amplified and quantified using qPCR. We outline the methodological and bioinformatics tools for the Oli system here and demonstrate that it can be used as a conventional experimental evolution model system by test-driving it in an experiment investigating adaptive evolution under different rates of environmental change. PMID:24003997

Reducing model uncertainty effects in flexible manipulators through the addition of passive damping

NASA Technical Reports Server (NTRS)

Alberts, T. E.

1987-01-01

An important issue in the control of practical systems is the effect of model uncertainty on closed loop performance. This is of particular concern when flexible structures are to be controlled, due to the fact that states associated with higher frequency vibration modes are truncated in order to make the control problem tractable. Digital simulations of a single-link manipulator system are employed to demonstrate that passive damping added to the flexible member reduces adverse effects associated with model uncertainty. A controller was designed based on a model including only one flexible mode. This controller was applied to larger order systems to evaluate the effects of modal truncation. Simulations using a Linear Quadratic Regulator (LQR) design assuming full state feedback illustrate the effect of control spillover. Simulations of a system using output feedback illustrate the destabilizing effect of observation spillover. The simulations reveal that the system with passive damping is less susceptible to these effects than the untreated case.

Stochastic hybrid systems for studying biochemical processes.

PubMed

Singh, Abhyudai; Hespanha, João P

2010-11-13

Many protein and mRNA species occur at low molecular counts within cells, and hence are subject to large stochastic fluctuations in copy numbers over time. Development of computationally tractable frameworks for modelling stochastic fluctuations in population counts is essential to understand how noise at the cellular level affects biological function and phenotype. We show that stochastic hybrid systems (SHSs) provide a convenient framework for modelling the time evolution of population counts of different chemical species involved in a set of biochemical reactions. We illustrate recently developed techniques that allow fast computations of the statistical moments of the population count, without having to run computationally expensive Monte Carlo simulations of the biochemical reactions. Finally, we review different examples from the literature that illustrate the benefits of using SHSs for modelling biochemical processes.

Algorithms and Complexity Results for Genome Mapping Problems.

PubMed

Rajaraman, Ashok; Zanetti, Joao Paulo Pereira; Manuch, Jan; Chauve, Cedric

2017-01-01

Genome mapping algorithms aim at computing an ordering of a set of genomic markers based on local ordering information such as adjacencies and intervals of markers. In most genome mapping models, markers are assumed to occur uniquely in the resulting map. We introduce algorithmic questions that consider repeats, i.e., markers that can have several occurrences in the resulting map. We show that, provided with an upper bound on the copy number of repeated markers and with intervals that span full repeat copies, called repeat spanning intervals, the problem of deciding if a set of adjacencies and repeat spanning intervals admits a genome representation is tractable if the target genome can contain linear and/or circular chromosomal fragments. We also show that extracting a maximum cardinality or weight subset of repeat spanning intervals given a set of adjacencies that admits a genome realization is NP-hard but fixed-parameter tractable in the maximum copy number and the number of adjacent repeats, and tractable if intervals contain a single repeated marker.

Identification of Modules in Protein-Protein Interaction Networks

NASA Astrophysics Data System (ADS)

Erten, Sinan; Koyutürk, Mehmet

In biological systems, most processes are carried out through orchestration of multiple interacting molecules. These interactions are often abstracted using network models. A key feature of cellular networks is their modularity, which contributes significantly to the robustness, as well as adaptability of biological systems. Therefore, modularization of cellular networks is likely to be useful in obtaining insights into the working principles of cellular systems, as well as building tractable models of cellular organization and dynamics. A common, high-throughput source of data on molecular interactions is in the form of physical interactions between proteins, which are organized into protein-protein interaction (PPI) networks. This chapter provides an overview on identification and analysis of functional modules in PPI networks, which has been an active area of research in the last decade.

Framework for cascade size calculations on random networks

NASA Astrophysics Data System (ADS)

Burkholz, Rebekka; Schweitzer, Frank

2018-04-01

We present a framework to calculate the cascade size evolution for a large class of cascade models on random network ensembles in the limit of infinite network size. Our method is exact and applies to network ensembles with almost arbitrary degree distribution, degree-degree correlations, and, in case of threshold models, for arbitrary threshold distribution. With our approach, we shift the perspective from the known branching process approximations to the iterative update of suitable probability distributions. Such distributions are key to capture cascade dynamics that involve possibly continuous quantities and that depend on the cascade history, e.g., if load is accumulated over time. As a proof of concept, we provide two examples: (a) Constant load models that cover many of the analytically tractable casacade models, and, as a highlight, (b) a fiber bundle model that was not tractable by branching process approximations before. Our derivations cover the whole cascade dynamics, not only their steady state. This allows us to include interventions in time or further model complexity in the analysis.

Space-Bounded Church-Turing Thesis and Computational Tractability of Closed Systems.

PubMed

Braverman, Mark; Schneider, Jonathan; Rojas, Cristóbal

2015-08-28

We report a new limitation on the ability of physical systems to perform computation-one that is based on generalizing the notion of memory, or storage space, available to the system to perform the computation. Roughly, we define memory as the maximal amount of information that the evolving system can carry from one instant to the next. We show that memory is a limiting factor in computation even in lieu of any time limitations on the evolving system-such as when considering its equilibrium regime. We call this limitation the space-bounded Church-Turing thesis (SBCT). The SBCT is supported by a simulation assertion (SA), which states that predicting the long-term behavior of bounded-memory systems is computationally tractable. In particular, one corollary of SA is an explicit bound on the computational hardness of the long-term behavior of a discrete-time finite-dimensional dynamical system that is affected by noise. We prove such a bound explicitly.

Sharp Truncation of an Electric Field: An Idealized Model that Warrants Caution

NASA Astrophysics Data System (ADS)

Tu, Hong; Zhu, Jiongming

2016-03-01

In physics, idealized models are often used to simplify complex situations. The motivation of the idealization is to make the real complex system tractable by adopting certain simplifications. In this treatment some unnecessary, negligible aspects are stripped away (so-called Aristotelian idealization), or some deliberate distortions are involved (so-called Galilean idealization). The most important principle in using an idealized model is to make sure that all the neglected aspects do not affect our analysis or result. Point charges, rigid bodies, simple pendulums, frictionless planes, and isolated systems are all frequently used idealized models. However, when they are applied to certain uncommon models, extra precautions should be taken. The possibilities and necessities of adopting the idealizations have to be considered carefully. Sometimes some factors neglected or ignored in the idealization could completely change the result, even make the treatment unphysical and conclusions unscientific.

Effects of Network Structure, Competition and Memory Time on Social Spreading Phenomena

NASA Astrophysics Data System (ADS)

Gleeson, James P.; O'Sullivan, Kevin P.; Baños, Raquel A.; Moreno, Yamir

2016-04-01

Online social media has greatly affected the way in which we communicate with each other. However, little is known about what fundamental mechanisms drive dynamical information flow in online social systems. Here, we introduce a generative model for online sharing behavior that is analytically tractable and that can reproduce several characteristics of empirical micro-blogging data on hashtag usage, such as (time-dependent) heavy-tailed distributions of meme popularity. The presented framework constitutes a null model for social spreading phenomena that, in contrast to purely empirical studies or simulation-based models, clearly distinguishes the roles of two distinct factors affecting meme popularity: the memory time of users and the connectivity structure of the social network.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

Space-Bounded Church-Turing Thesis and Computational Tractability of Closed Systems

NASA Astrophysics Data System (ADS)

Braverman, Mark; Schneider, Jonathan; Rojas, Cristóbal

2015-08-01

We report a new limitation on the ability of physical systems to perform computation—one that is based on generalizing the notion of memory, or storage space, available to the system to perform the computation. Roughly, we define memory as the maximal amount of information that the evolving system can carry from one instant to the next. We show that memory is a limiting factor in computation even in lieu of any time limitations on the evolving system—such as when considering its equilibrium regime. We call this limitation the space-bounded Church-Turing thesis (SBCT). The SBCT is supported by a simulation assertion (SA), which states that predicting the long-term behavior of bounded-memory systems is computationally tractable. In particular, one corollary of SA is an explicit bound on the computational hardness of the long-term behavior of a discrete-time finite-dimensional dynamical system that is affected by noise. We prove such a bound explicitly.

A meteorologically driven maize stress indicator model

NASA Technical Reports Server (NTRS)

Taylor, T. W.; Ravet, F. W. (Principal Investigator)

1981-01-01

A maize soil moisture and temperature stress model is described which was developed to serve as a meteorological data filter to alert commodity analysts to potential stress conditions in the major maize-producing areas of the world. The model also identifies optimum climatic conditions and planting/harvest problems associated with poor tractability.

Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics.

PubMed

Ocone, Andrea; Millar, Andrew J; Sanguinetti, Guido

2013-04-01

Computational modelling of the dynamics of gene regulatory networks is a central task of systems biology. For networks of small/medium scale, the dominant paradigm is represented by systems of coupled non-linear ordinary differential equations (ODEs). ODEs afford great mechanistic detail and flexibility, but calibrating these models to data is often an extremely difficult statistical problem. Here, we develop a general statistical inference framework for stochastic transcription-translation networks. We use a coarse-grained approach, which represents the system as a network of stochastic (binary) promoter and (continuous) protein variables. We derive an exact inference algorithm and an efficient variational approximation that allows scalable inference and learning of the model parameters. We demonstrate the power of the approach on two biological case studies, showing that the method allows a high degree of flexibility and is capable of testable novel biological predictions. http://homepages.inf.ed.ac.uk/gsanguin/software.html. Supplementary data are available at Bioinformatics online.

Analytically tractable climate-carbon cycle feedbacks under 21st century anthropogenic forcing

NASA Astrophysics Data System (ADS)

Lade, Steven J.; Donges, Jonathan F.; Fetzer, Ingo; Anderies, John M.; Beer, Christian; Cornell, Sarah E.; Gasser, Thomas; Norberg, Jon; Richardson, Katherine; Rockström, Johan; Steffen, Will

2018-05-01

Changes to climate-carbon cycle feedbacks may significantly affect the Earth system's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth system models. Here, we construct a stylised global climate-carbon cycle model, test its output against comprehensive Earth system models, and investigate the strengths of its climate-carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon cycle feedbacks and the operation of the carbon cycle. Specific results include that different feedback formalisms measure fundamentally the same climate-carbon cycle processes; temperature dependence of the solubility pump, biological pump, and CO2 solubility all contribute approximately equally to the ocean climate-carbon feedback; and concentration-carbon feedbacks may be more sensitive to future climate change than climate-carbon feedbacks. Simple models such as that developed here also provide workbenches for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the planetary boundaries, that are currently too uncertain to be included in comprehensive Earth system models.

On use of image quality metrics for perceptual blur modeling: image/video compression case

NASA Astrophysics Data System (ADS)

Cha, Jae H.; Olson, Jeffrey T.; Preece, Bradley L.; Espinola, Richard L.; Abbott, A. Lynn

2018-02-01

Linear system theory is employed to make target acquisition performance predictions for electro-optical/infrared imaging systems where the modulation transfer function (MTF) may be imposed from a nonlinear degradation process. Previous research relying on image quality metrics (IQM) methods, which heuristically estimate perceived MTF has supported that an average perceived MTF can be used to model some types of degradation such as image compression. Here, we discuss the validity of the IQM approach by mathematically analyzing the associated heuristics from the perspective of reliability, robustness, and tractability. Experiments with standard images compressed by x.264 encoding suggest that the compression degradation can be estimated by a perceived MTF within boundaries defined by well-behaved curves with marginal error. Our results confirm that the IQM linearizer methodology provides a credible tool for sensor performance modeling.

Enhanced networked server management with random remote backups

NASA Astrophysics Data System (ADS)

Kim, Song-Kyoo

2003-08-01

In this paper, the model is focused on available server management in network environments. The (remote) backup servers are hooked up by VPN (Virtual Private Network) and replace broken main severs immediately. A virtual private network (VPN) is a way to use a public network infrastructure and hooks up long-distance servers within a single network infrastructure. The servers can be represent as "machines" and then the system deals with main unreliable and random auxiliary spare (remote backup) machines. When the system performs a mandatory routine maintenance, auxiliary machines are being used for backups during idle periods. Unlike other existing models, the availability of auxiliary machines is changed for each activation in this enhanced model. Analytically tractable results are obtained by using several mathematical techniques and the results are demonstrated in the framework of optimized networked server allocation problems.

Dynamics of West Nile virus evolution in mosquito vectors.

PubMed

Grubaugh, Nathan D; Ebel, Gregory D

2016-12-01

West Nile virus remains the most common cause of arboviral encephalitis in North America. Since it was introduced, it has undergone adaptive genetic change as it spread throughout the continent. The WNV transmission cycle is relatively tractable in the laboratory. Thus the virus serves as a convenient model system for studying the population biology of mosquito-borne flaviviruses as they undergo transmission to and from mosquitoes and vertebrates. This review summarizes the current knowledge regarding the population dynamics of this virus within mosquito vectors. Copyright © 2016 Elsevier B.V. All rights reserved.

Retooling CFD for hypersonic aircraft

NASA Technical Reports Server (NTRS)

Dwoyer, Douglas L.; Kutler, Paul; Povinelli, Louis A.

1987-01-01

The CFD facility requirements of hypersonic aircraft configuration design development are different from those thus far employed for reentry vehicle design, because (1) the airframe and the propulsion system must be fully integrated to achieve the desired performance; (2) the vehicle must be reusable, with minimum refurbishment requirements between flights; and (3) vehicle performance must be optimized for a wide range of Mach numbers. An evaluation is presently made of flow resolution within shock waves, transition and turbulence phenomenon tractability, chemical reaction modeling, and hypersonic boundary layer transition, with state-of-the-art CFD.

Learning-based stochastic object models for characterizing anatomical variations

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

2018-03-01

It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

Detecting temperature fluctuations at equilibrium.

PubMed

Dixit, Purushottam D

2015-05-21

The Gibbs and the Boltzmann definition of temperature agree only in the macroscopic limit. The ambiguity in identifying the equilibrium temperature of a finite-sized 'small' system exchanging energy with a bath is usually understood as a limitation of conventional statistical mechanics. We interpret this ambiguity as resulting from a stochastically fluctuating temperature coupled with the phase space variables giving rise to a broad temperature distribution. With this ansatz, we develop the equilibrium statistics and dynamics of small systems. Numerical evidence using an analytically tractable model shows that the effects of temperature fluctuations can be detected in the equilibrium and dynamical properties of the phase space of the small system. Our theory generalizes statistical mechanics to small systems relevant in biophysics and nanotechnology.

Modeling Terminal Velocity

ERIC Educational Resources Information Center

Brand, Neal; Quintanilla, John A.

2013-01-01

Using a simultaneously falling softball as a stopwatch, the terminal velocity of a whiffle ball can be obtained to surprisingly high accuracy with only common household equipment. This classroom activity engages students in an apparently daunting task that nevertheless is tractable, using a simple model and mathematical techniques at their…

Prediction of dynamical systems by symbolic regression

NASA Astrophysics Data System (ADS)

Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K.; Noack, Bernd R.

2016-07-01

We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast.

Modelling ecological systems in a changing world

PubMed Central

Evans, Matthew R.

2012-01-01

The world is changing at an unprecedented rate. In such a situation, we need to understand the nature of the change and to make predictions about the way in which it might affect systems of interest; often we may also wish to understand what might be done to mitigate the predicted effects. In ecology, we usually make such predictions (or forecasts) by making use of mathematical models that describe the system and projecting them into the future, under changed conditions. Approaches emphasizing the desirability of simple models with analytical tractability and those that use assumed causal relationships derived statistically from data currently dominate ecological modelling. Although such models are excellent at describing the way in which a system has behaved, they are poor at predicting its future state, especially in novel conditions. In order to address questions about the impact of environmental change, and to understand what, if any, action might be taken to ameliorate it, ecologists need to develop the ability to project models into novel, future conditions. This will require the development of models based on understanding the processes that result in a system behaving the way it does, rather than relying on a description of the system, as a whole, remaining valid indefinitely. PMID:22144381

A Tractable Disequilbrium Framework for Integrating Computational Thermodynamics and Geodynamics

NASA Astrophysics Data System (ADS)

Spiegelman, M. W.; Tweed, L. E. L.; Evans, O.; Kelemen, P. B.; Wilson, C. R.

2017-12-01

The consistent integration of computational thermodynamics and geodynamics is essential for exploring and understanding a wide range of processes from high-PT magma dynamics in the convecting mantle to low-PT reactive alteration of the brittle crust. Nevertheless, considerable challenges remain for coupling thermodynamics and fluid-solid mechanics within computationally tractable and insightful models. Here we report on a new effort, part of the ENKI project, that provides a roadmap for developing flexible geodynamic models of varying complexity that are thermodynamically consistent with established thermodynamic models. The basic theory is derived from the disequilibrium thermodynamics of De Groot and Mazur (1984), similar to Rudge et. al (2011, GJI), but extends that theory to include more general rheologies, multiple solid (and liquid) phases and explicit chemical reactions to describe interphase exchange. Specifying stoichiometric reactions clearly defines the compositions of reactants and products and allows the affinity of each reaction (A = -Δ/Gr) to be used as a scalar measure of disequilibrium. This approach only requires thermodynamic models to return chemical potentials of all components and phases (as well as thermodynamic quantities for each phase e.g. densities, heat capacity, entropies), but is not constrained to be in thermodynamic equilibrium. Allowing meta-stable phases mitigates some of the computational issues involved with the introduction and exhaustion of phases. Nevertheless, for closed systems, these problems are guaranteed to evolve to the same equilibria predicted by equilibrium thermodynamics. Here we illustrate the behavior of this theory for a range of simple problems (constructed with our open-source model builder TerraFERMA) that model poro-viscous behavior in the well understood Fo-Fa binary phase loop. Other contributions in this session will explore a range of models with more petrologically interesting phase diagrams as well as other rheologies.

Kinetic Modeling of Next-Generation High-Energy, High-Intensity Laser-Ion Accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albright, Brian James; Yin, Lin; Stark, David James

One of the long-standing problems in the community is the question of how we can model “next-generation” laser-ion acceleration in a computationally tractable way. A new particle tracking capability in the LANL VPIC kinetic plasma modeling code has enabled us to solve this long-standing problem

Quantum lattice model solver HΦ

NASA Astrophysics Data System (ADS)

Kawamura, Mitsuaki; Yoshimi, Kazuyoshi; Misawa, Takahiro; Yamaji, Youhei; Todo, Synge; Kawashima, Naoki

2017-08-01

HΦ [aitch-phi ] is a program package based on the Lanczos-type eigenvalue solution applicable to a broad range of quantum lattice models, i.e., arbitrary quantum lattice models with two-body interactions, including the Heisenberg model, the Kitaev model, the Hubbard model and the Kondo-lattice model. While it works well on PCs and PC-clusters, HΦ also runs efficiently on massively parallel computers, which considerably extends the tractable range of the system size. In addition, unlike most existing packages, HΦ supports finite-temperature calculations through the method of thermal pure quantum (TPQ) states. In this paper, we explain theoretical background and user-interface of HΦ. We also show the benchmark results of HΦ on supercomputers such as the K computer at RIKEN Advanced Institute for Computational Science (AICS) and SGI ICE XA (Sekirei) at the Institute for the Solid State Physics (ISSP).

The Drosophila melanogaster host model

PubMed Central

Igboin, Christina O.; Griffen, Ann L.; Leys, Eugene J.

2012-01-01

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen–host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial–host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis–host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed. PMID:22368770

The Drosophila melanogaster host model.

PubMed

Igboin, Christina O; Griffen, Ann L; Leys, Eugene J

2012-01-01

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen-host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial-host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis-host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed.

The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks.

PubMed

Morozova, Tatiana V; Goldman, David; Mackay, Trudy F C; Anholt, Robert R H

2012-02-20

Alcoholism is a significant public health problem. A picture of the genetic architecture underlying alcohol-related phenotypes is emerging from genome-wide association studies and work on genetically tractable model organisms.

Surface Transportation Weather Decision Support Requirements - Executive Summary, Version 1.0

DOT National Transportation Integrated Search

1999-12-16

WEATHER: IT AFFECTS THE VISIBILITY, TRACTABILITY, MANEUVERABILITY, VEHICLE STABILITY, EXHAUST EMISSIONS AND STRUCTURAL INTEGRITY OF THE SURFACE TRANSPORTATION SYSTEM. THEREBY WEATHER AFFECTS THE SAFETY, MOBILITY, PRODUCTIVITY AND ENVIRONMENTAL IMPACT...

A Unified Framework for Monetary Theory and Policy Analysis.

ERIC Educational Resources Information Center

Lagos, Ricardo; Wright, Randall

2005-01-01

Search-theoretic models of monetary exchange are based on explicit descriptions of the frictions that make money essential. However, tractable versions of these models typically make strong assumptions that render them ill suited for monetary policy analysis. We propose a new framework, based on explicit micro foundations, within which macro…

Answering Schrödinger's question: A free-energy formulation

NASA Astrophysics Data System (ADS)

Ramstead, Maxwell James Désormeau; Badcock, Paul Benjamin; Friston, Karl John

2018-03-01

The free-energy principle (FEP) is a formal model of neuronal processes that is widely recognised in neuroscience as a unifying theory of the brain and biobehaviour. More recently, however, it has been extended beyond the brain to explain the dynamics of living systems, and their unique capacity to avoid decay. The aim of this review is to synthesise these advances with a meta-theoretical ontology of biological systems called variational neuroethology, which integrates the FEP with Tinbergen's four research questions to explain biological systems across spatial and temporal scales. We exemplify this framework by applying it to Homo sapiens, before translating variational neuroethology into a systematic research heuristic that supplies the biological, cognitive, and social sciences with a computationally tractable guide to discovery.

Design and Functionality of the Graphical Interactive Narrative (Gin) System Version 0.2

DTIC Science & Technology

2012-08-01

System. The purpose of the Gin system is to increase the interactivity and sense of agency for human subjects in virtual environments (VEs) used for...tractability of scenario development while providing the user with an increased sense of agency by allowing them to control their own navigation

Evidence for transgenerational metabolic programming in Drosophila

PubMed Central

Buescher, Jessica L.; Musselman, Laura P.; Wilson, Christina A.; Lang, Tieming; Keleher, Madeline; Baranski, Thomas J.; Duncan, Jennifer G.

2013-01-01

SUMMARY Worldwide epidemiologic studies have repeatedly demonstrated an association between prenatal nutritional environment, birth weight and susceptibility to adult diseases including obesity, cardiovascular disease and type 2 diabetes. Despite advances in mammalian model systems, the molecular mechanisms underlying this phenomenon are unclear, but might involve programming mechanisms such as epigenetics. Here we describe a new system for evaluating metabolic programming mechanisms using a simple, genetically tractable Drosophila model. We examined the effect of maternal caloric excess on offspring and found that a high-sugar maternal diet alters body composition of larval offspring for at least two generations, augments an obese-like phenotype under suboptimal (high-calorie) feeding conditions in adult offspring, and modifies expression of metabolic genes. Our data indicate that nutritional programming mechanisms could be highly conserved and support the use of Drosophila as a model for evaluating the underlying genetic and epigenetic contributions to this phenomenon. PMID:23649823

A meteorologically driven grain sorghum stress indicator model

NASA Technical Reports Server (NTRS)

Taylor, T. W.; Ravet, F. W. (Principal Investigator)

1981-01-01

A grain sorghum soil moisture and temperature stress model is described. It was developed to serve as a meteorological data filter to alert commodity analysts to potential stress conditions and crop phenology in selected grain sorghum production areas. The model also identifies optimum conditions on a daily basis and planting/harvest problems associated with poor tractability.

The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks

PubMed Central

2012-01-01

Alcoholism is a significant public health problem. A picture of the genetic architecture underlying alcohol-related phenotypes is emerging from genome-wide association studies and work on genetically tractable model organisms. PMID:22348705

Linear static structural and vibration analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Baddourah, M. A.; Storaasli, O. O.; Bostic, S. W.

1993-01-01

Parallel computers offer the oppurtunity to significantly reduce the computation time necessary to analyze large-scale aerospace structures. This paper presents algorithms developed for and implemented on massively-parallel computers hereafter referred to as Scalable High-Performance Computers (SHPC), for the most computationally intensive tasks involved in structural analysis, namely, generation and assembly of system matrices, solution of systems of equations and calculation of the eigenvalues and eigenvectors. Results on SHPC are presented for large-scale structural problems (i.e. models for High-Speed Civil Transport). The goal of this research is to develop a new, efficient technique which extends structural analysis to SHPC and makes large-scale structural analyses tractable.

Robust, Decoupled, Flight Control Design with Rate Saturating Actuators

NASA Technical Reports Server (NTRS)

Snell, S. A.; Hess, R. A.

1997-01-01

Techniques for the design of control systems for manually controlled, high-performance aircraft must provide the following: (1) multi-input, multi-output (MIMO) solutions, (2) acceptable handling qualities including no tendencies for pilot-induced oscillations, (3) a tractable approach for compensator design, (4) performance and stability robustness in the presence of significant plant uncertainty, and (5) performance and stability robustness in the presence actuator saturation (particularly rate saturation). A design technique built upon Quantitative Feedback Theory is offered as a candidate methodology which can provide flight control systems meeting these requirements, and do so over a considerable part of the flight envelope. An example utilizing a simplified model of a supermaneuverable fighter aircraft demonstrates the proposed design methodology.

Integrative approaches for modeling regulation and function of the respiratory system.

PubMed

Ben-Tal, Alona; Tawhai, Merryn H

2013-01-01

Mathematical models have been central to understanding the interaction between neural control and breathing. Models of the entire respiratory system-which comprises the lungs and the neural circuitry that controls their ventilation-have been derived using simplifying assumptions to compartmentalize each component of the system and to define the interactions between components. These full system models often rely-through necessity-on empirically derived relationships or parameters, in addition to physiological values. In parallel with the development of whole respiratory system models are mathematical models that focus on furthering a detailed understanding of the neural control network, or of the several functions that contribute to gas exchange within the lung. These models are biophysically based, and rely on physiological parameters. They include single-unit models for a breathing lung or neural circuit, through to spatially distributed models of ventilation and perfusion, or multicircuit models for neural control. The challenge is to bring together these more recent advances in models of neural control with models of lung function, into a full simulation for the respiratory system that builds upon the more detailed models but remains computationally tractable. This requires first understanding the mathematical models that have been developed for the respiratory system at different levels, and which could be used to study how physiological levels of O2 and CO2 in the blood are maintained. Copyright © 2013 Wiley Periodicals, Inc.

Incorporating operational flexibility into electric generation planning Impacts and methods for system design and policy analysis

NASA Astrophysics Data System (ADS)

Palmintier, Bryan S.

This dissertation demonstrates how flexibility in hourly electricity operations can impact long-term planning and analysis for future power systems, particularly those with substantial variable renewables (e.g., wind) or strict carbon policies. Operational flexibility describes a power system's ability to respond to predictable and unexpected changes in generation or demand. Planning and policy models have traditionally not directly captured the technical operating constraints that determine operational flexibility. However, as demonstrated in this dissertation, this capability becomes increasingly important with the greater flexibility required by significant renewables (>= 20%) and the decreased flexibility inherent in some low-carbon generation technologies. Incorporating flexibility can significantly change optimal generation and energy mixes, lower system costs, improve policy impact estimates, and enable system designs capable of meeting strict regulatory targets. Methodologically, this work presents a new clustered formulation that tractably combines a range of normally distinct power system models, from hourly unit-commitment operations to long-term generation planning. This formulation groups similar generators into clusters to reduce problem size, while still retaining the individual unit constraints required to accurately capture operating reserves and other flexibility drivers. In comparisons against traditional unit commitment formulations, errors were generally less than 1% while run times decreased by several orders of magnitude (e.g., 5000x). Extensive numerical simulations, using a realistic Texas-based power system show that ignoring flexibility can underestimate carbon emissions by 50% or result in significant load and wind shedding to meet environmental regulations. Contributions of this dissertation include: 1. Demonstrating that operational flexibility can have an important impact on power system planning, and describing when and how these impacts occur; 2. Demonstrating that a failure to account for operational flexibility can result in undesirable outcomes for both utility planners and policy analysts; and 3. Extending the state of the art for electric power system models by introducing a tractable method for incorporating unit commitment based operational flexibility at full 876o hourly resolution directly into planning optimization. Together these results encourage and offer a new flexibility-aware approach for capacity planning and accompanying policy design that can enable cleaner, less expensive electric power systems for the future. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

Mouse Models of Breast Cancer: Platforms for Discovering Precision Imaging Diagnostics and Future Cancer Medicine.

PubMed

Manning, H Charles; Buck, Jason R; Cook, Rebecca S

2016-02-01

Representing an enormous health care and socioeconomic challenge, breast cancer is the second most common cancer in the world and the second most common cause of cancer-related death. Although many of the challenges associated with preventing, treating, and ultimately curing breast cancer are addressable in the laboratory, successful translation of groundbreaking research to clinical populations remains an important barrier. Particularly when compared with research on other types of solid tumors, breast cancer research is hampered by a lack of tractable in vivo model systems that accurately recapitulate the relevant clinical features of the disease. A primary objective of this article was to provide a generalizable overview of the types of in vivo model systems, with an emphasis primarily on murine models, that are widely deployed in preclinical breast cancer research. Major opportunities to advance precision cancer medicine facilitated by molecular imaging of preclinical breast cancer models are discussed. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Effects of Disturbance on Populations of Marine Mammals

DTIC Science & Technology

2014-09-30

relation between foraging success of mothers and pup production (reproductive rate). Second, we we used mark-recapture models to quantify the...responses to disturbance are not necessarily surrogate measures of population-level responses is widely understood. However, without tractable

First-Principles Propagation of Geoelectric Fields from Ionosphere to Ground using LANLGeoRad

NASA Astrophysics Data System (ADS)

Jeffery, C. A.; Woodroffe, J. R.; Henderson, M. G.

2017-12-01

A notable deficiency in the current SW forecasting chain is the propagation of geoelectric fields from ionosphere to ground using Biot-Savart integrals, which ignore the localized complexity of lithospheric electrical conductivity and the relatively high conductivity of ocean water compared to the lithosphere. Three-dimensional models of Earth conductivity with mesoscale spatial resolution are being developed, but a new approach is needed to incorporate this information into the SW forecast chain. We present initial results from a first-principles geoelectric propagation model call LANLGeoRad, which solves Maxwell's equations on an unstructured geodesic grid. Challenges associated with the disparate response times of millisecond electromagnetic propagation and 10-second geomagnetic fluctuations are highlighted, and a novel rescaling of the ionosphere/ground system is presented that renders this geoelectric system computationally tractable.

Applying dynamic priority scheduling scheme to static systems of pinwheel task model in power-aware scheduling.

PubMed

Seol, Ye-In; Kim, Young-Kuk

2014-01-01

Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10-80% over the existing algorithms.

Applying Dynamic Priority Scheduling Scheme to Static Systems of Pinwheel Task Model in Power-Aware Scheduling

PubMed Central

2014-01-01

Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10–80% over the existing algorithms. PMID:25121126

Stochastic Modeling and Generation of Partially Polarized or Partially Coherent Electromagnetic Waves

NASA Technical Reports Server (NTRS)

Davis, Brynmor; Kim, Edward; Piepmeier, Jeffrey; Hildebrand, Peter H. (Technical Monitor)

2001-01-01

Many new Earth remote-sensing instruments are embracing both the advantages and added complexity that result from interferometric or fully polarimetric operation. To increase instrument understanding and functionality a model of the signals these instruments measure is presented. A stochastic model is used as it recognizes the non-deterministic nature of any real-world measurements while also providing a tractable mathematical framework. A stationary, Gaussian-distributed model structure is proposed. Temporal and spectral correlation measures provide a statistical description of the physical properties of coherence and polarization-state. From this relationship the model is mathematically defined. The model is shown to be unique for any set of physical parameters. A method of realizing the model (necessary for applications such as synthetic calibration-signal generation) is given and computer simulation results are presented. The signals are constructed using the output of a multi-input multi-output linear filter system, driven with white noise.

Natural genetic variation of root system architecture from Arabidopsis to Brachypodium: towards adaptive value.

PubMed

Pacheco-Villalobos, David; Hardtke, Christian S

2012-06-05

Root system architecture is a trait that displays considerable plasticity because of its sensitivity to environmental stimuli. Nevertheless, to a significant degree it is genetically constrained as suggested by surveys of its natural genetic variation. A few regulators of root system architecture have been isolated as quantitative trait loci through the natural variation approach in the dicotyledon model, Arabidopsis. This provides proof of principle that allelic variation for root system architecture traits exists, is genetically tractable, and might be exploited for crop breeding. Beyond Arabidopsis, Brachypodium could serve as both a credible and experimentally accessible model for root system architecture variation in monocotyledons, as suggested by first glimpses of the different root morphologies of Brachypodium accessions. Whether a direct knowledge transfer gained from molecular model system studies will work in practice remains unclear however, because of a lack of comprehensive understanding of root system physiology in the native context. For instance, apart from a few notable exceptions, the adaptive value of genetic variation in root system modulators is unknown. Future studies should thus aim at comprehensive characterization of the role of genetic players in root system architecture variation by taking into account the native environmental conditions, in particular soil characteristics.

Autonomous Guidance of Agile Small-scale Rotorcraft

NASA Technical Reports Server (NTRS)

Mettler, Bernard; Feron, Eric

2004-01-01

This report describes a guidance system for agile vehicles based on a hybrid closed-loop model of the vehicle dynamics. The hybrid model represents the vehicle dynamics through a combination of linear-time-invariant control modes and pre-programmed, finite-duration maneuvers. This particular hybrid structure can be realized through a control system that combines trim controllers and a maneuvering control logic. The former enable precise trajectory tracking, and the latter enables trajectories at the edge of the vehicle capabilities. The closed-loop model is much simpler than the full vehicle equations of motion, yet it can capture a broad range of dynamic behaviors. It also supports a consistent link between the physical layer and the decision-making layer. The trajectory generation was formulated as an optimization problem using mixed-integer-linear-programming. The optimization is solved in a receding horizon fashion. Several techniques to improve the computational tractability were investigate. Simulation experiments using NASA Ames 'R-50 model show that this approach fully exploits the vehicle's agility.

Patho-biotechnology: using bad bugs to do good things.

PubMed

Sleator, Roy D; Hill, Colin

2006-04-01

Pathogenic bacteria have evolved sophisticated strategies to overcome host defences, to interact with the immune system and to interfere with essential host systems. We coin the term 'patho-biotechnology' to describe the exploitation of these valuable traits in biotechnology, medicine and food. This approach shows promise for the development of novel vaccine and drug delivery systems, as well as for the design of more technologically robust and effective probiotic cultures with improved biotechnological and clinical applications. The genetic tractability of Listeria monocytogenes, the availability of the complete genome sequence of this intracellular pathogen, its ability to cope with stress, and its ability to traverse the gastrointestinal tract and induce a strong cellular immune response make L. monocytogenes an ideal model organism for demonstrating the patho-biotechnology concept.

Cluster decomposition of full configuration interaction wave functions: A tool for chemical interpretation of systems with strong correlation

NASA Astrophysics Data System (ADS)

Lehtola, Susi; Tubman, Norm M.; Whaley, K. Birgitta; Head-Gordon, Martin

2017-10-01

Approximate full configuration interaction (FCI) calculations have recently become tractable for systems of unforeseen size, thanks to stochastic and adaptive approximations to the exponentially scaling FCI problem. The result of an FCI calculation is a weighted set of electronic configurations, which can also be expressed in terms of excitations from a reference configuration. The excitation amplitudes contain information on the complexity of the electronic wave function, but this information is contaminated by contributions from disconnected excitations, i.e., those excitations that are just products of independent lower-level excitations. The unwanted contributions can be removed via a cluster decomposition procedure, making it possible to examine the importance of connected excitations in complicated multireference molecules which are outside the reach of conventional algorithms. We present an implementation of the cluster decomposition analysis and apply it to both true FCI wave functions, as well as wave functions generated from the adaptive sampling CI algorithm. The cluster decomposition is useful for interpreting calculations in chemical studies, as a diagnostic for the convergence of various excitation manifolds, as well as as a guidepost for polynomially scaling electronic structure models. Applications are presented for (i) the double dissociation of water, (ii) the carbon dimer, (iii) the π space of polyacenes, and (iv) the chromium dimer. While the cluster amplitudes exhibit rapid decay with an increasing rank for the first three systems, even connected octuple excitations still appear important in Cr2, suggesting that spin-restricted single-reference coupled-cluster approaches may not be tractable for some problems in transition metal chemistry.

Complex Dynamics of Droplet Traffic in a Bifurcating Microfluidic Channel: Periodicity, Multistability, and Selection Rules

NASA Astrophysics Data System (ADS)

Sessoms, D. A.; Amon, A.; Courbin, L.; Panizza, P.

2010-10-01

The binary path selection of droplets reaching a T junction is regulated by time-delayed feedback and nonlinear couplings. Such mechanisms result in complex dynamics of droplet partitioning: numerous discrete bifurcations between periodic regimes are observed. We introduce a model based on an approximation that makes this problem tractable. This allows us to derive analytical formulae that predict the occurrence of the bifurcations between consecutive regimes, establish selection rules for the period of a regime, and describe the evolutions of the period and complexity of droplet pattern in a cycle with the key parameters of the system. We discuss the validity and limitations of our model which describes semiquantitatively both numerical simulations and microfluidic experiments.

Impulsive response of an automatic transmission system with multiple clearances: Formulation, simulation and experiment

NASA Astrophysics Data System (ADS)

Crowther, Ashley R.; Singh, Rajendra; Zhang, Nong; Chapman, Chris

2007-10-01

Impulsive responses in geared systems with multiple clearances are studied when the mean torque excitation and system load change abruptly, with application to a vehicle driveline with an automatic transmission. First, torsional lumped-mass models of the planetary and differential gear sets are formulated using matrix elements. The model is then reduced to address tractable nonlinear problems while successfully retaining the main modes of interest. Second, numerical simulations for the nonlinear model are performed for transient conditions and a typical driving situation that induces an impulsive behaviour simulated. However, initial conditions and excitation and load profiles have to be carefully defined before the model can be numerically solved. It is shown that the impacts within the planetary or differential gears may occur under combinations of engine, braking and vehicle load transients. Our analysis shows that the shaping of the engine transient by the torque converter before reaching the clearance locations is more critical. Third, a free vibration experiment is developed for an analogous driveline with multiple clearances and three experiments that excite different response regimes have been carried out. Good correlations validate the proposed methodology.

A Tractable Numerical Model for Exploring Nonadiabatic Quantum Dynamics

ERIC Educational Resources Information Center

Camrud, Evan; Turner, Daniel B.

2017-01-01

Numerous computational and spectroscopic studies have demonstrated the decisive role played by nonadiabatic coupling in photochemical reactions. Nonadiabatic coupling drives photochemistry when potential energy surfaces are nearly degenerate at avoided crossings or truly degenerate at unavoided crossings. The dynamics induced by nonadiabatic…

Harnessing the hygroscopic and biofluorescent behaviors of genetically tractable microbial cells to design biohybrid wearables.

PubMed

Wang, Wen; Yao, Lining; Cheng, Chin-Yi; Zhang, Teng; Atsumi, Hiroshi; Wang, Luda; Wang, Guanyun; Anilionyte, Oksana; Steiner, Helene; Ou, Jifei; Zhou, Kang; Wawrousek, Chris; Petrecca, Katherine; Belcher, Angela M; Karnik, Rohit; Zhao, Xuanhe; Wang, Daniel I C; Ishii, Hiroshi

2017-05-01

Cells' biomechanical responses to external stimuli have been intensively studied but rarely implemented into devices that interact with the human body. We demonstrate that the hygroscopic and biofluorescent behaviors of living cells can be engineered to design biohybrid wearables, which give multifunctional responsiveness to human sweat. By depositing genetically tractable microbes on a humidity-inert material to form a heterogeneous multilayered structure, we obtained biohybrid films that can reversibly change shape and biofluorescence intensity within a few seconds in response to environmental humidity gradients. Experimental characterization and mechanical modeling of the film were performed to guide the design of a wearable running suit and a fluorescent shoe prototype with bio-flaps that dynamically modulates ventilation in synergy with the body's need for cooling.

The Sphagnome Project: enabling ecological and evolutionary insights through a genus-level sequencing project

DOE PAGES

Weston, David J.; Turetsky, Merritt R.; Johnson, Matthew G.; ...

2017-10-27

Considerable progress has been made in ecological and evolutionary genetics with studies demonstrating how genes underlying plant and microbial traits can influence adaptation and even ‘extend’ to influence community structure and ecosystem level processes. The progress in this area is limited to model systems with deep genetic and genomic resources that often have negligible ecological impact or interest. Therefore, important linkages between genetic adaptations and their consequences at organismal and ecological scales are often lacking. We introduce the Sphagnome Project, which incorporates genomics into a long-running history of Sphagnum research that has documented unparalleled contributions to peatland ecology, carbon sequestration,more » biogeochemistry, microbiome research, niche construction, and ecosystem engineering. The Sphagnome Project encompasses a genus-level sequencing effort that represents a new type of model system driven not only by genetic tractability, but by ecologically relevant questions and hypotheses.« less

The Sphagnome Project: enabling ecological and evolutionary insights through a genus-level sequencing project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weston, David J.; Turetsky, Merritt R.; Johnson, Matthew G.

Considerable progress has been made in ecological and evolutionary genetics with studies demonstrating how genes underlying plant and microbial traits can influence adaptation and even ‘extend’ to influence community structure and ecosystem level processes. The progress in this area is limited to model systems with deep genetic and genomic resources that often have negligible ecological impact or interest. Therefore, important linkages between genetic adaptations and their consequences at organismal and ecological scales are often lacking. We introduce the Sphagnome Project, which incorporates genomics into a long-running history of Sphagnum research that has documented unparalleled contributions to peatland ecology, carbon sequestration,more » biogeochemistry, microbiome research, niche construction, and ecosystem engineering. The Sphagnome Project encompasses a genus-level sequencing effort that represents a new type of model system driven not only by genetic tractability, but by ecologically relevant questions and hypotheses.« less

The Sphagnome Project: enabling ecological and evolutionary insights through a genus-level sequencing project.

PubMed

Weston, David J; Turetsky, Merritt R; Johnson, Matthew G; Granath, Gustaf; Lindo, Zoë; Belyea, Lisa R; Rice, Steven K; Hanson, David T; Engelhardt, Katharina A M; Schmutz, Jeremy; Dorrepaal, Ellen; Euskirchen, Eugénie S; Stenøien, Hans K; Szövényi, Péter; Jackson, Michelle; Piatkowski, Bryan T; Muchero, Wellington; Norby, Richard J; Kostka, Joel E; Glass, Jennifer B; Rydin, Håkan; Limpens, Juul; Tuittila, Eeva-Stiina; Ullrich, Kristian K; Carrell, Alyssa; Benscoter, Brian W; Chen, Jin-Gui; Oke, Tobi A; Nilsson, Mats B; Ranjan, Priya; Jacobson, Daniel; Lilleskov, Erik A; Clymo, R S; Shaw, A Jonathan

2018-01-01

Considerable progress has been made in ecological and evolutionary genetics with studies demonstrating how genes underlying plant and microbial traits can influence adaptation and even 'extend' to influence community structure and ecosystem level processes. Progress in this area is limited to model systems with deep genetic and genomic resources that often have negligible ecological impact or interest. Thus, important linkages between genetic adaptations and their consequences at organismal and ecological scales are often lacking. Here we introduce the Sphagnome Project, which incorporates genomics into a long-running history of Sphagnum research that has documented unparalleled contributions to peatland ecology, carbon sequestration, biogeochemistry, microbiome research, niche construction, and ecosystem engineering. The Sphagnome Project encompasses a genus-level sequencing effort that represents a new type of model system driven not only by genetic tractability, but by ecologically relevant questions and hypotheses. © 2017 UT-Battelle New Phytologist © 2017 New Phytologist Trust.

Foundations of the Bandera Abstraction Tools

NASA Technical Reports Server (NTRS)

Hatcliff, John; Dwyer, Matthew B.; Pasareanu, Corina S.; Robby

2003-01-01

Current research is demonstrating that model-checking and other forms of automated finite-state verification can be effective for checking properties of software systems. Due to the exponential costs associated with model-checking, multiple forms of abstraction are often necessary to obtain system models that are tractable for automated checking. The Bandera Tool Set provides multiple forms of automated support for compiling concurrent Java software systems to models that can be supplied to several different model-checking tools. In this paper, we describe the foundations of Bandera's data abstraction mechanism which is used to reduce the cardinality (and the program's state-space) of data domains in software to be model-checked. From a technical standpoint, the form of data abstraction used in Bandera is simple, and it is based on classical presentations of abstract interpretation. We describe the mechanisms that Bandera provides for declaring abstractions, for attaching abstractions to programs, and for generating abstracted programs and properties. The contributions of this work are the design and implementation of various forms of tool support required for effective application of data abstraction to software components written in a programming language like Java which has a rich set of linguistic features.

Building Systems from Scratch: an Exploratory Study of Students Learning About Climate Change

NASA Astrophysics Data System (ADS)

Puttick, Gillian; Tucker-Raymond, Eli

2018-01-01

Science and computational practices such as modeling and abstraction are critical to understanding the complex systems that are integral to climate science. Given the demonstrated affordances of game design in supporting such practices, we implemented a free 4-day intensive workshop for middle school girls that focused on using the visual programming environment, Scratch, to design games to teach others about climate change. The experience was carefully constructed so that girls of widely differing levels of experience were able to engage in a cycle of game design. This qualitative study aimed to explore the representational choices the girls made as they took up aspects of climate change systems and modeled them in their games. Evidence points to the ways in which designing games about climate science fostered emergent systems thinking and engagement in modeling practices as learners chose what to represent in their games, grappled with the realism of their respective representations, and modeled interactions among systems components. Given the girls' levels of programming skill, parts of systems were more tractable to create than others. The educational purpose of the games was important to the girls' overall design experience, since it influenced their choice of topic, and challenged their emergent understanding of climate change as a systems problem.

Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems

NASA Astrophysics Data System (ADS)

Koch, Patrick Nathan

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.

Overcoming the sign problem at finite temperature: Quantum tensor network for the orbital eg model on an infinite square lattice

NASA Astrophysics Data System (ADS)

Czarnik, Piotr; Dziarmaga, Jacek; Oleś, Andrzej M.

2017-07-01

The variational tensor network renormalization approach to two-dimensional (2D) quantum systems at finite temperature is applied to a model suffering the notorious quantum Monte Carlo sign problem—the orbital eg model with spatially highly anisotropic orbital interactions. Coarse graining of the tensor network along the inverse temperature β yields a numerically tractable 2D tensor network representing the Gibbs state. Its bond dimension D —limiting the amount of entanglement—is a natural refinement parameter. Increasing D we obtain a converged order parameter and its linear susceptibility close to the critical point. They confirm the existence of finite order parameter below the critical temperature Tc, provide a numerically exact estimate of Tc, and give the critical exponents within 1 % of the 2D Ising universality class.

Sleep and Development in Genetically Tractable Model Organisms

PubMed Central

Kayser, Matthew S.; Biron, David

2016-01-01

Sleep is widely recognized as essential, but without a clear singular function. Inadequate sleep impairs cognition, metabolism, immune function, and many other processes. Work in genetic model systems has greatly expanded our understanding of basic sleep neurobiology as well as introduced new concepts for why we sleep. Among these is an idea with its roots in human work nearly 50 years old: sleep in early life is crucial for normal brain maturation. Nearly all known species that sleep do so more while immature, and this increased sleep coincides with a period of exuberant synaptogenesis and massive neural circuit remodeling. Adequate sleep also appears critical for normal neurodevelopmental progression. This article describes recent findings regarding molecular and circuit mechanisms of sleep, with a focus on development and the insights garnered from models amenable to detailed genetic analyses. PMID:27183564

A Probabilistic Model of Illegal Drug Trafficking Operations in the Eastern Pacific and Caribbean Sea

DTIC Science & Technology

2013-09-01

partner agencies and nations, detects, tracks, and interdicts illegal drug-trafficking in this region. In this thesis, we develop a probability model based...trafficking in this region. In this thesis, we develop a probability model based on intelligence inputs to generate a spatial temporal heat map specifying the...complement and vet such complicated simulation by developing more analytically tractable models. We develop probability models to generate a heat map

Feasibility of controlling speed-dependent low-frequency brake vibration amplification by modulating actuation pressure

NASA Astrophysics Data System (ADS)

Sen, Osman Taha; Dreyer, Jason T.; Singh, Rajendra

2014-12-01

In this article, a feasibility study of controlling the low frequency torque response of a disc brake system with modulated actuation pressure (in the open loop mode) is conducted. First, a quasi-linear model of the torsional system is introduced, and analytical solutions are proposed to incorporate the modulation effect. Tractable expressions for three different modulation schemes are obtained, and conditions that would lead to a reduction in the oscillatory amplitudes are identified. Second, these conditions are evaluated with a numerical model of the torsional system with clearance nonlinearity, and analytical solutions are verified in terms of the trends observed. Finally, a laboratory experiment with a solenoid valve is built to modulate actuation pressure with a constant duty cycle, and time-frequency domain data are acquired. Measurements are utilized to assess analytical observations, and all methods show that the speed-dependent brake torque amplitudes can be altered with an appropriate modulation of actuation pressure.

Random blebbing motion: A simple model linking cell structural properties to migration characteristics.

PubMed

Woolley, Thomas E; Gaffney, Eamonn A; Goriely, Alain

2017-07-01

If the plasma membrane of a cell is able to delaminate locally from its actin cortex, a cellular bleb can be produced. Blebs are pressure-driven protrusions, which are noteworthy for their ability to produce cellular motion. Starting from a general continuum mechanics description, we restrict ourselves to considering cell and bleb shapes that maintain approximately spherical forms. From this assumption, we obtain a tractable algebraic system for bleb formation. By including cell-substrate adhesions, we can model blebbing cell motility. Further, by considering mechanically isolated blebbing events, which are randomly distributed over the cell, we can derive equations linking the macroscopic migration characteristics to the microscopic structural parameters of the cell. This multiscale modeling framework is then used to provide parameter estimates, which are in agreement with current experimental data. In summary, the construction of the mathematical model provides testable relationships between the bleb size and cell motility.

Evolution of the archaeal and mammalian information processing systems: towards an archaeal model for human disease.

PubMed

Lyu, Zhe; Whitman, William B

2017-01-01

Current evolutionary models suggest that Eukaryotes originated from within Archaea instead of being a sister lineage. To test this model of ancient evolution, we review recent studies and compare the three major information processing subsystems of replication, transcription and translation in the Archaea and Eukaryotes. Our hypothesis is that if the Eukaryotes arose within the archaeal radiation, their information processing systems will appear to be one of kind and not wholly original. Within the Eukaryotes, the mammalian or human systems are emphasized because of their importance in understanding health. Biochemical as well as genetic studies provide strong evidence for the functional similarity of archaeal homologs to the mammalian information processing system and their dissimilarity to the bacterial systems. In many independent instances, a simple archaeal system is functionally equivalent to more elaborate eukaryotic homologs, suggesting that evolution of complexity is likely an central feature of the eukaryotic information processing system. Because fewer components are often involved, biochemical characterizations of the archaeal systems are often easier to interpret. Similarly, the archaeal cell provides a genetically and metabolically simpler background, enabling convenient studies on the complex information processing system. Therefore, Archaea could serve as a parsimonious and tractable host for studying human diseases that arise in the information processing systems.

Neurophysiology of Drosophila Models of Parkinson's Disease

PubMed Central

West, Ryan J. H.; Furmston, Rebecca; Williams, Charles A. C.; Elliott, Christopher J. H.

2015-01-01

We provide an insight into the role Drosophila has played in elucidating neurophysiological perturbations associated with Parkinson's disease- (PD-) related genes. Synaptic signalling deficits are observed in motor, central, and sensory systems. Given the neurological impact of disease causing mutations within these same genes in humans the phenotypes observed in fly are of significant interest. As such we observe four unique opportunities provided by fly nervous system models of Parkinson's disease. Firstly, Drosophila models are instrumental in exploring the mechanisms of neurodegeneration, with several PD-related mutations eliciting related phenotypes including sensitivity to energy supply and vesicular deformities. These are leading to the identification of plausible cellular mechanisms, which may be specific to (dopaminergic) neurons and synapses rather than general cellular phenotypes. Secondly, models show noncell autonomous signalling within the nervous system, offering the opportunity to develop our understanding of the way pathogenic signalling propagates, resembling Braak's scheme of spreading pathology in PD. Thirdly, the models link physiological deficits to changes in synaptic structure. While the structure-function relationship is complex, the genetic tractability of Drosophila offers the chance to separate fundamental changes from downstream consequences. Finally, the strong neuronal phenotypes permit relevant first in vivo drug testing. PMID:25960916

Genome Engineering of the 2,3-Butanediol Biosynthetic Pathway for Tight Regulation in Cyanobacteria.

PubMed

Nozzi, Nicole E; Atsumi, Shota

2015-11-20

Cyanobacteria have gained popularity among the metabolic engineering community as a tractable photosynthetic host for renewable chemical production. However, though a number of successfully engineered production systems have been reported, long-term genetic stability remains an issue for cyanobacterial systems. The genetic engineering toolbox for cyanobacteria is largely lacking inducible systems for expression control. The characterization of tight regulation systems for use in cyanobacteria may help to alleviate this problem. In this work we explore the function of the IPTG inducible promoter P(L)lacO1 in the model cyanobacterium Synechococcus elongatus PCC 7942 as well as the effect of gene order within an operon on pathway expression. According to our experiments, P(L)lacO1 functions well as an inducible promoter in S. elongatus. Additionally, we found that gene order within an operon can strongly influence control of expression of each gene.

Developing the anemone Aiptasia as a tractable model for cnidarian-dinoflagellate symbiosis: the transcriptome of aposymbiotic A. pallida.

PubMed

Lehnert, Erik M; Burriesci, Matthew S; Pringle, John R

2012-06-22

Coral reefs are hotspots of oceanic biodiversity, forming the foundation of ecosystems that are important both ecologically and for their direct practical impacts on humans. Corals are declining globally due to a number of stressors, including rising sea-surface temperatures and pollution; such stresses can lead to a breakdown of the essential symbiotic relationship between the coral host and its endosymbiotic dinoflagellates, a process known as coral bleaching. Although the environmental stresses causing this breakdown are largely known, the cellular mechanisms of symbiosis establishment, maintenance, and breakdown are still largely obscure. Investigating the symbiosis using an experimentally tractable model organism, such as the small sea anemone Aiptasia, should improve our understanding of exactly how the environmental stressors affect coral survival and growth. We assembled the transcriptome of a clonal population of adult, aposymbiotic (dinoflagellate-free) Aiptasia pallida from ~208 million reads, yielding 58,018 contigs. We demonstrated that many of these contigs represent full-length or near-full-length transcripts that encode proteins similar to those from a diverse array of pathways in other organisms, including various metabolic enzymes, cytoskeletal proteins, and neuropeptide precursors. The contigs were annotated by sequence similarity, assigned GO terms, and scanned for conserved protein domains. We analyzed the frequency and types of single-nucleotide variants and estimated the size of the Aiptasia genome to be ~421 Mb. The contigs and annotations are available through NCBI (Transcription Shotgun Assembly database, accession numbers JV077153-JV134524) and at http://pringlelab.stanford.edu/projects.html. The availability of an extensive transcriptome assembly for A. pallida will facilitate analyses of gene-expression changes, identification of proteins of interest, and other studies in this important emerging model system.

Residence-time framework for modeling multicomponent reactive transport in stream hyporheic zones

NASA Astrophysics Data System (ADS)

Painter, S. L.; Coon, E. T.; Brooks, S. C.

2017-12-01

Process-based models for transport and transformation of nutrients and contaminants in streams require tractable representations of solute exchange between the stream channel and biogeochemically active hyporheic zones. Residence-time based formulations provide an alternative to detailed three-dimensional simulations and have had good success in representing hyporheic exchange of non-reacting solutes. We extend the residence-time formulation for hyporheic transport to accommodate general multicomponent reactive transport. To that end, the integro-differential form of previous residence time models is replaced by an equivalent formulation based on a one-dimensional advection dispersion equation along the channel coupled at each channel location to a one-dimensional transport model in Lagrangian travel-time form. With the channel discretized for numerical solution, the associated Lagrangian model becomes a subgrid model representing an ensemble of streamlines that are diverted into the hyporheic zone before returning to the channel. In contrast to the previous integro-differential forms of the residence-time based models, the hyporheic flowpaths have semi-explicit spatial representation (parameterized by travel time), thus allowing coupling to general biogeochemical models. The approach has been implemented as a stream-corridor subgrid model in the open-source integrated surface/subsurface modeling software ATS. We use bedform-driven flow coupled to a biogeochemical model with explicit microbial biomass dynamics as an example to show that the subgrid representation is able to represent redox zonation in sediments and resulting effects on metal biogeochemical dynamics in a tractable manner that can be scaled to reach scales.

Robust optimization modelling with applications to industry and environmental problems

NASA Astrophysics Data System (ADS)

Chaerani, Diah; Dewanto, Stanley P.; Lesmana, Eman

2017-10-01

Robust Optimization (RO) modeling is one of the existing methodology for handling data uncertainty in optimization problem. The main challenge in this RO methodology is how and when we can reformulate the robust counterpart of uncertain problems as a computationally tractable optimization problem or at least approximate the robust counterpart by a tractable problem. Due to its definition the robust counterpart highly depends on how we choose the uncertainty set. As a consequence we can meet this challenge only if this set is chosen in a suitable way. The development on RO grows fast, since 2004, a new approach of RO called Adjustable Robust Optimization (ARO) is introduced to handle uncertain problems when the decision variables must be decided as a ”wait and see” decision variables. Different than the classic Robust Optimization (RO) that models decision variables as ”here and now”. In ARO, the uncertain problems can be considered as a multistage decision problem, thus decision variables involved are now become the wait and see decision variables. In this paper we present the applications of both RO and ARO. We present briefly all results to strengthen the importance of RO and ARO in many real life problems.

Comparing two Bayes methods based on the free energy functions in Bernoulli mixtures.

PubMed

Yamazaki, Keisuke; Kaji, Daisuke

2013-08-01

Hierarchical learning models are ubiquitously employed in information science and data engineering. The structure makes the posterior distribution complicated in the Bayes method. Then, the prediction including construction of the posterior is not tractable though advantages of the method are empirically well known. The variational Bayes method is widely used as an approximation method for application; it has the tractable posterior on the basis of the variational free energy function. The asymptotic behavior has been studied in many hierarchical models and a phase transition is observed. The exact form of the asymptotic variational Bayes energy is derived in Bernoulli mixture models and the phase diagram shows that there are three types of parameter learning. However, the approximation accuracy or interpretation of the transition point has not been clarified yet. The present paper precisely analyzes the Bayes free energy function of the Bernoulli mixtures. Comparing free energy functions in these two Bayes methods, we can determine the approximation accuracy and elucidate behavior of the parameter learning. Our results claim that the Bayes free energy has the same learning types while the transition points are different. Copyright © 2013 Elsevier Ltd. All rights reserved.

Genetics on the Fly: A Primer on the Drosophila Model System

PubMed Central

Hales, Karen G.; Korey, Christopher A.; Larracuente, Amanda M.; Roberts, David M.

2015-01-01

Fruit flies of the genus Drosophila have been an attractive and effective genetic model organism since Thomas Hunt Morgan and colleagues made seminal discoveries with them a century ago. Work with Drosophila has enabled dramatic advances in cell and developmental biology, neurobiology and behavior, molecular biology, evolutionary and population genetics, and other fields. With more tissue types and observable behaviors than in other short-generation model organisms, and with vast genome data available for many species within the genus, the fly’s tractable complexity will continue to enable exciting opportunities to explore mechanisms of complex developmental programs, behaviors, and broader evolutionary questions. This primer describes the organism’s natural history, the features of sequenced genomes within the genus, the wide range of available genetic tools and online resources, the types of biological questions Drosophila can help address, and historical milestones. PMID:26564900

Organoid Models of Human and Mouse Ductal Pancreatic Cancer

PubMed Central

Boj, Sylvia F.; Hwang, Chang-Il; Baker, Lindsey A.; Chio, Iok In Christine; Engle, Dannielle D.; Corbo, Vincenzo; Jager, Myrthe; Ponz-Sarvise, Mariano; Tiriac, Hervé; Spector, Mona S.; Gracanin, Ana; Oni, Tobiloba; Yu, Kenneth H.; van Boxtel, Ruben; Huch, Meritxell; Rivera, Keith D.; Wilson, John P.; Feigin, Michael E.; Öhlund, Daniel; Handly-Santana, Abram; Ardito-Abraham, Christine M.; Ludwig, Michael; Elyada, Ela; Alagesan, Brinda; Biffi, Giulia; Yordanov, Georgi N.; Delcuze, Bethany; Creighton, Brianna; Wright, Kevin; Park, Youngkyu; Morsink, Folkert H.M.; Molenaar, I. Quintus; Borel Rinkes, Inne H.; Cuppen, Edwin; Hao, Yuan; Jin, Ying; Nijman, Isaac J.; Iacobuzio-Donahue, Christine; Leach, Steven D.; Pappin, Darryl J.; Hammell, Molly; Klimstra, David S.; Basturk, Olca; Hruban, Ralph H.; Offerhaus, George Johan; Vries, Robert G.J.; Clevers, Hans; Tuveson, David A.

2015-01-01

SUMMARY Pancreatic cancer is one of the most lethal malignancies due to its late diagnosis and limited response to treatment. Tractable methods to identify and interrogate pathways involved in pancreatic tumorigenesis are urgently needed. We established organoid models from normal and neoplastic murine and human pancreas tissues. Pancreatic organoids can be rapidly generated from resected tumors and biopsies, survive cryopreservation and exhibit ductal- and disease stage-specific characteristics. Orthotopically transplanted neoplastic organoids recapitulate the full spectrum of tumor development by forming early-grade neoplasms that progress to locally invasive and metastatic carcinomas. Due to their ability to be genetically manipulated, organoids are a platform to probe genetic cooperation. Comprehensive transcriptional and proteomic analyses of murine pancreatic organoids revealed genes and pathways altered during disease progression. The confirmation of many of these protein changes in human tissues demonstrates that organoids are a facile model system to discover characteristics of this deadly malignancy. PMID:25557080

Sleep and Development in Genetically Tractable Model Organisms.

PubMed

Kayser, Matthew S; Biron, David

2016-05-01

Sleep is widely recognized as essential, but without a clear singular function. Inadequate sleep impairs cognition, metabolism, immune function, and many other processes. Work in genetic model systems has greatly expanded our understanding of basic sleep neurobiology as well as introduced new concepts for why we sleep. Among these is an idea with its roots in human work nearly 50 years old: sleep in early life is crucial for normal brain maturation. Nearly all known species that sleep do so more while immature, and this increased sleep coincides with a period of exuberant synaptogenesis and massive neural circuit remodeling. Adequate sleep also appears critical for normal neurodevelopmental progression. This article describes recent findings regarding molecular and circuit mechanisms of sleep, with a focus on development and the insights garnered from models amenable to detailed genetic analyses. Copyright © 2016 by the Genetics Society of America.

Mechanics and morphogenesis of fission yeast cells.

PubMed

Davì, Valeria; Minc, Nicolas

2015-12-01

The integration of biochemical and biomechanical elements is at the heart of morphogenesis. While animal cells are relatively soft objects which shape and mechanics is mostly regulated by cytoskeletal networks, walled cells including those of plants, fungi and bacteria are encased in a rigid cell wall which resist high internal turgor pressure. How these particular mechanical properties may influence basic cellular processes, such as growth, shape and division remains poorly understood. Recent work using the model fungal cell fission yeast, Schizosaccharomyces pombe, highlights important contribution of cell mechanics to various morphogenesis processes. We envision this genetically tractable system to serve as a novel standard for the mechanobiology of walled cell. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evolutionary traps as keys to understanding behavioral maladaptation

USGS Publications Warehouse

Robertson, Bruce A.; Chalfoun, Anna

2016-01-01

Evolutionary traps are severe cases of behavioral maladaptation that occur when, due to human activity, the cues animals use to guide their behavior become uncoupled from their fitness consequences. The result is that animals can prefer the most dangerous resources or behaviors, even when better options are available. Traps are increasingly common and represent a significant wildlife conservation problem. Understanding of the more proximate sensory-cognitive mechanisms underpinning traps remains poor, which highlights the need for interdisciplinary and collaborative approaches to investigating traps. Key to advancing basic trap theory and its conservation applications will be the development of appropriate and tractable model systems to investigate the mechanisms that cause traps within species, and how mechanisms vary across species.

Insect Immunity to Entomopathogenic Fungi.

PubMed

Lu, H-L; St Leger, R J

2016-01-01

The study of infection and immunity in insects has achieved considerable prominence with the appreciation that their host defense mechanisms share many fundamental characteristics with the innate immune system of vertebrates. Studies on the highly tractable model organism Drosophila in particular have led to a detailed understanding of conserved innate immunity networks, such as Toll. However, most of these studies have used opportunistic human pathogens and may not have revealed specialized immune strategies that have arisen through evolutionary arms races with natural insect pathogens. Fungi are the commonest natural insect pathogens, and in this review, we focus on studies using Metarhizium and Beauveria spp. that have addressed immune system function and pathogen virulence via behavioral avoidance, the use of physical barriers, and the activation of local and systemic immune responses. In particular, we highlight studies on the evolutionary genetics of insect immunity and discuss insect-pathogen coevolution. Copyright © 2016 Elsevier Inc. All rights reserved.

Tractable Analysis for Large Social Networks

ERIC Educational Resources Information Center

Zhang, Bin

2012-01-01

Social scientists usually are more interested in consumers' dichotomous choice, such as purchase a product or not, adopt a technology or not, etc. However, up to date, there is nearly no model can help us solve the problem of multi-network effects comparison with a dichotomous dependent variable. Furthermore, the study of multi-network…

Functional Imaging and Optogenetics in Drosophila

PubMed Central

Simpson, Julie H.; Looger, Loren L.

2018-01-01

Understanding how activity patterns in specific neural circuits coordinate an animal’s behavior remains a key area of neuroscience research. Genetic tools and a brain of tractable complexity make Drosophila a premier model organism for these studies. Here, we review the wealth of reagents available to map and manipulate neuronal activity with light. PMID:29618589

Integrating Model-Based Verification into Software Design Education

ERIC Educational Resources Information Center

Yilmaz, Levent; Wang, Shuo

2005-01-01

Proper design analysis is indispensable to assure quality and reduce emergent costs due to faulty software. Teaching proper design verification skills early during pedagogical development is crucial, as such analysis is the only tractable way of resolving software problems early when they are easy to fix. The premise of the presented strategy is…

Reuse, Recycle, Reweigh: Combating Influenza through Efficient Sequential Bayesian Computation for Massive Data.

PubMed

Tom, Jennifer A; Sinsheimer, Janet S; Suchard, Marc A

Massive datasets in the gigabyte and terabyte range combined with the availability of increasingly sophisticated statistical tools yield analyses at the boundary of what is computationally feasible. Compromising in the face of this computational burden by partitioning the dataset into more tractable sizes results in stratified analyses, removed from the context that justified the initial data collection. In a Bayesian framework, these stratified analyses generate intermediate realizations, often compared using point estimates that fail to account for the variability within and correlation between the distributions these realizations approximate. However, although the initial concession to stratify generally precludes the more sensible analysis using a single joint hierarchical model, we can circumvent this outcome and capitalize on the intermediate realizations by extending the dynamic iterative reweighting MCMC algorithm. In doing so, we reuse the available realizations by reweighting them with importance weights, recycling them into a now tractable joint hierarchical model. We apply this technique to intermediate realizations generated from stratified analyses of 687 influenza A genomes spanning 13 years allowing us to revisit hypotheses regarding the evolutionary history of influenza within a hierarchical statistical framework.

Reuse, Recycle, Reweigh: Combating Influenza through Efficient Sequential Bayesian Computation for Massive Data

PubMed Central

Tom, Jennifer A.; Sinsheimer, Janet S.; Suchard, Marc A.

2015-01-01

Massive datasets in the gigabyte and terabyte range combined with the availability of increasingly sophisticated statistical tools yield analyses at the boundary of what is computationally feasible. Compromising in the face of this computational burden by partitioning the dataset into more tractable sizes results in stratified analyses, removed from the context that justified the initial data collection. In a Bayesian framework, these stratified analyses generate intermediate realizations, often compared using point estimates that fail to account for the variability within and correlation between the distributions these realizations approximate. However, although the initial concession to stratify generally precludes the more sensible analysis using a single joint hierarchical model, we can circumvent this outcome and capitalize on the intermediate realizations by extending the dynamic iterative reweighting MCMC algorithm. In doing so, we reuse the available realizations by reweighting them with importance weights, recycling them into a now tractable joint hierarchical model. We apply this technique to intermediate realizations generated from stratified analyses of 687 influenza A genomes spanning 13 years allowing us to revisit hypotheses regarding the evolutionary history of influenza within a hierarchical statistical framework. PMID:26681992

Reply to comment by Jonathan J. Rhodes on "Modeling of the interactions between forest vegetation, disturbances, and sediment yields"

Treesearch

Charles H. Luce; David G. Tarboton; Erkan Istanbulluoglu; Robert T. Pack

2005-01-01

Rhodes [2005] brings up some excellent points in his comments on the work of Istanbulluoglu et al. [2004]. We appreciate the opportunity to respond because it is likely that other readers will also wonder how they can apply the relatively simple analysis to important policy questions. Models necessarily reduce the complexity of the problem to make it tractable and...

Use of mouse models to study the mechanisms and consequences of RBC clearance

PubMed Central

Hod, E. A.; Arinsburg, S. A.; Francis, R. O.; Hendrickson, J. E.; Zimring, J. C.; Spitalnik, S. L.

2013-01-01

Mice provide tractable animal models for studying the pathophysiology of various human disorders. This review discusses the use of mouse models for understanding red-blood-cell (RBC) clearance. These models provide important insights into the pathophysiology of various clinically relevant entities, such as autoimmune haemolytic anaemia, haemolytic transfusion reactions, other complications of RBC transfusions and immunomodulation by Rh immune globulin therapy. Mouse models of both antibody- and non-antibody-mediated RBC clearance are reviewed. Approaches for exploring unanswered questions in transfusion medicine using these models are also discussed. PMID:20345515

Formal Requirements-Based Programming for Complex Systems

NASA Technical Reports Server (NTRS)

Rash, James L.; Hinchey, Michael G.; Rouff, Christopher A.; Gracanin, Denis

2005-01-01

Computer science as a field has not yet produced a general method to mechanically transform complex computer system requirements into a provably equivalent implementation. Such a method would be one major step towards dealing with complexity in computing, yet it remains the elusive holy grail of system development. Currently available tools and methods that start with a formal model of a system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The gap that such tools and methods leave unfilled is that the formal models cannot be proven to be equivalent to the system requirements as originated by the customer For the classes of complex systems whose behavior can be described as a finite (but significant) set of scenarios, we offer a method for mechanically transforming requirements (expressed in restricted natural language, or appropriate graphical notations) into a provably equivalent formal model that can be used as the basis for code generation and other transformations. While other techniques are available, this method is unique in offering full mathematical tractability while using notations and techniques that are well known and well trusted. We illustrate the application of the method to an example procedure from the Hubble Robotic Servicing Mission currently under study and preliminary formulation at NASA Goddard Space Flight Center.

Stochastic Multi-Timescale Power System Operations With Variable Wind Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Hongyu; Krad, Ibrahim; Florita, Anthony

This paper describes a novel set of stochastic unit commitment and economic dispatch models that consider stochastic loads and variable generation at multiple operational timescales. The stochastic model includes four distinct stages: stochastic day-ahead security-constrained unit commitment (SCUC), stochastic real-time SCUC, stochastic real-time security-constrained economic dispatch (SCED), and deterministic automatic generation control (AGC). These sub-models are integrated together such that they are continually updated with decisions passed from one to another. The progressive hedging algorithm (PHA) is applied to solve the stochastic models to maintain the computational tractability of the proposed models. Comparative case studies with deterministic approaches are conductedmore » in low wind and high wind penetration scenarios to highlight the advantages of the proposed methodology, one with perfect forecasts and the other with current state-of-the-art but imperfect deterministic forecasts. The effectiveness of the proposed method is evaluated with sensitivity tests using both economic and reliability metrics to provide a broader view of its impact.« less

Animal and Human Tissue Models of Vertical Listeria monocytogenes Transmission and Implications for Other Pregnancy-Associated Infections.

PubMed

Lowe, David E; Robbins, Jennifer R; Bakardjiev, Anna I

2018-06-01

Intrauterine infections lead to serious complications for mother and fetus, including preterm birth, maternal and fetal death, and neurological sequelae in the surviving offspring. Improving maternal and child heath is a global priority. Yet, the development of strategies to prevent and treat pregnancy-related diseases has lagged behind progress made in other medical fields. One of the challenges is finding tractable model systems that replicate the human maternal-fetal interface. Animal models offer the ability to study pathogenesis and host defenses in vivo However, the anatomy of the maternal-fetal interface is highly divergent across species. While many tools are available to study host responses in the pregnant mouse model, other animals have placentas that are more similar to that of humans. Here we describe new developments in animal and human tissue models to investigate the pathogenesis of listeriosis at the maternal-fetal interface. We highlight gaps in existing knowledge and make recommendations on how they can be filled. Copyright © 2018 American Society for Microbiology.

Landau-Zener extension of the Tavis-Cummings model: structure of the solution

NASA Astrophysics Data System (ADS)

Sun, Chen; Sinitsyn, Nikolai

We explore the recently discovered solution of the driven Tavis-Cummings model (DTCM). It describes interaction of arbitrary number of two-level systems with a bosonic mode that has linearly time-dependent frequency. We derive compact and tractable expressions for transition probabilities in terms of the well known special functions. In the new form, our formulas are suitable for fast numerical calculations and analytical approximations. As an application, we obtain the semiclassical limit of the exact solution and compare it to prior approximations. We also reveal connection between DTCM and q-deformed binomial statistics. Under the auspices of the National Nuclear Security Administration of the U.S. Department of Energy at Los Alamos National Laboratory under Contract No. DE-AC52-06NA25396. Authors also thank the support from the LDRD program at LANL.

Glimmers of a Quantum KAM Theorem: Insights from Quantum Quenches in One-Dimensional Bose Gases

DOE PAGES

Brandino, G. P.; Caux, J. -S.; Konik, R. M.

2015-12-16

Real-time dynamics in a quantum many-body system are inherently complicated and hence difficult to predict. There are, however, a special set of systems where these dynamics are theoretically tractable: integrable models. Such models possess non-trivial conserved quantities beyond energy and momentum. These quantities are believed to control dynamics and thermalization in low dimensional atomic gases as well as in quantum spin chains. But what happens when the special symmetries leading to the existence of the extra conserved quantities are broken? Is there any memory of the quantities if the breaking is weak? Here, in the presence of weak integrability breaking,more » we show that it is possible to construct residual quasi-conserved quantities, so providing a quantum analog to the KAM theorem and its attendant Nekhoreshev estimates. We demonstrate this construction explicitly in the context of quantum quenches in one-dimensional Bose gases and argue that these quasi-conserved quantities can be probed experimentally.« less

Photophysical behavior of polyatomic molecules

NASA Astrophysics Data System (ADS)

Ware, W. R.

1980-10-01

Part one of this report deals with attempts over the past several years to devise a more sophisticated theory of diffusion controlled reactions than that presented by Collins and Kimball. In particular, the investigators were interested in a more realistic formulation of the problem of high concentration quenching where quenches in the vicinity of the molecular to be quenched must be considered. It was desired however, to obtain a formalism which was tractable mathematically and which contained parameters which would be related to experiment. Part two deals with the photophysics of systems exhibiting molecular association both in the ground and excited states has been studied. The emphasis has been on kinetic models, the measurement of rate constants associated with these models, and the determination of activation parameters and equilibrium thermodynamic parameters associated with the exciplex formation and disappearance. Studies of solvent effects and steric effects on the behavior of exciplex systems have been carried out. The case of rapid equilibrium where the monomer and exciplex decay with the same rate constant has also been examined.

Reference hypernetted chain theory for ferrofluid bilayer: Distribution functions compared with Monte Carlo

NASA Astrophysics Data System (ADS)

Polyakov, Evgeny A.; Vorontsov-Velyaminov, Pavel N.

2014-08-01

Properties of ferrofluid bilayer (modeled as a system of two planar layers separated by a distance h and each layer carrying a soft sphere dipolar liquid) are calculated in the framework of inhomogeneous Ornstein-Zernike equations with reference hypernetted chain closure (RHNC). The bridge functions are taken from a soft sphere (1/r12) reference system in the pressure-consistent closure approximation. In order to make the RHNC problem tractable, the angular dependence of the correlation functions is expanded into special orthogonal polynomials according to Lado. The resulting equations are solved using the Newton-GRMES algorithm as implemented in the public-domain solver NITSOL. Orientational densities and pair distribution functions of dipoles are compared with Monte Carlo simulation results. A numerical algorithm for the Fourier-Hankel transform of any positive integer order on a uniform grid is presented.

Reliable transformation system for Microbotryum lychnidis-dioicae informed by genome and transcriptome project.

PubMed

Toh, Su San; Treves, David S; Barati, Michelle T; Perlin, Michael H

2016-10-01

Microbotryum lychnidis-dioicae is a member of a species complex infecting host plants in the Caryophyllaceae. It is used as a model system in many areas of research, but attempts to make this organism tractable for reverse genetic approaches have not been fruitful. Here, we exploited the recently obtained genome sequence and transcriptome analysis to inform our design of constructs for use in Agrobacterium-mediated transformation techniques currently available for other fungi. Reproducible transformation was demonstrated at the genomic, transcriptional and functional levels. Moreover, these initial proof-of-principle experiments provide evidence that supports the findings from initial global transcriptome analysis regarding expression from the respective promoters under different growth conditions of the fungus. The technique thus provides for the first time the ability to stably introduce transgenes and over-express target M. lychnidis-dioicae genes.

Immunity to helminths: resistance, regulation, and susceptibility to gastrointestinal nematodes.

PubMed

Grencis, Richard K

2015-01-01

Helminth parasites are a highly successful group of pathogens that challenge the immune system in a manner distinct from rapidly replicating infectious agents. Of this group, roundworms (nematodes) that dwell in the intestines of humans and other animals are prevalent worldwide. Currently, more than one billion people are infected by at least one species, often for extended periods of time. Thus, host-protective immunity is rarely complete. The reasons for this are complex, but laboratory investigation of tractable model systems in which protective immunity is effective has provided a mechanistic understanding of resistance that is characterized almost universally by a type 2/T helper 2 response. Greater understanding of the mechanisms of susceptibility has also provided the basis for defining host immunoregulation and parasite-evasion strategies, helping place in context the changing patterns of immunological disease observed worldwide.

Quasi-steady-state analysis of coupled flashing ratchets.

PubMed

Levien, Ethan; Bressloff, Paul C

2015-10-01

We perform a quasi-steady-state (QSS) reduction of a flashing ratchet to obtain a Brownian particle in an effective potential. The resulting system is analytically tractable and yet preserves essential dynamical features of the full model. We first use the QSS reduction to derive an explicit expression for the velocity of a simple two-state flashing ratchet. In particular, we determine the relationship between perturbations from detailed balance, which are encoded in the transitions rates of the flashing ratchet, and a tilted-periodic potential. We then perform a QSS analysis of a pair of elastically coupled flashing ratchets, which reduces to a Brownian particle moving in a two-dimensional vector field. We suggest that the fixed points of this vector field accurately approximate the metastable spatial locations of the coupled ratchets, which are, in general, impossible to identify from the full system.

Understanding the complexities of Salmonella-host crosstalk as revealed by in vivo model organisms.

PubMed

Verma, Smriti; Srikanth, Chittur V

2015-07-01

Foodborne infections caused by non-typhoidal Salmonellae, such as Salmonella enterica serovar Typhimurium (ST), pose a major challenge in the developed and developing world. With constant rise of drug-resistant strains, understanding the epidemiology, microbiology, pathogenesis and host-pathogen interactions biology is a mandatory requirement to enable health systems to be ready to combat these illnesses. Patient data from hospitals, at least from some parts of the world, have aided in epidemiological understanding of ST-mediated disease. Most of the other aspects connected to Salmonella-host crosstalk have come from model systems that offer convenience, genetic tractability and low maintenance costs that make them extremely valuable tools. Complex model systems such as the bovine model have helped in understanding key virulence factors needed for infection. Simple systems such as fruit flies and Caenorhabditis elegans have aided in identification of novel virulence factors, host pathways and mechanistic details of interactions. Some of the path-breaking concepts of the field have come from mice model of ST colitis, which allows genetic manipulations as well as high degree of similarity to human counterpart. Together, they are invaluable for correlating in vitro findings of ST-induced disease progression in vivo. The current review is a compilation of various advances of ST-host interactions at cellular and molecular levels that has come from investigations involving model organisms. © 2015 International Union of Biochemistry and Molecular Biology.

Automatic Item Generation via Frame Semantics: Natural Language Generation of Math Word Problems.

ERIC Educational Resources Information Center

Deane, Paul; Sheehan, Kathleen

This paper is an exploration of the conceptual issues that have arisen in the course of building a natural language generation (NLG) system for automatic test item generation. While natural language processing techniques are applicable to general verbal items, mathematics word problems are particularly tractable targets for natural language…

Tractable flux-driven temperature, density, and rotation profile evolution with the quasilinear gyrokinetic transport model QuaLiKiz

NASA Astrophysics Data System (ADS)

Citrin, J.; Bourdelle, C.; Casson, F. J.; Angioni, C.; Bonanomi, N.; Camenen, Y.; Garbet, X.; Garzotti, L.; Görler, T.; Gürcan, O.; Koechl, F.; Imbeaux, F.; Linder, O.; van de Plassche, K.; Strand, P.; Szepesi, G.; Contributors, JET

2017-12-01

Quasilinear turbulent transport models are a successful tool for prediction of core tokamak plasma profiles in many regimes. Their success hinges on the reproduction of local nonlinear gyrokinetic fluxes. We focus on significant progress in the quasilinear gyrokinetic transport model QuaLiKiz (Bourdelle et al 2016 Plasma Phys. Control. Fusion 58 014036), which employs an approximated solution of the mode structures to significantly speed up computation time compared to full linear gyrokinetic solvers. Optimisation of the dispersion relation solution algorithm within integrated modelling applications leads to flux calculations × {10}6-7 faster than local nonlinear simulations. This allows tractable simulation of flux-driven dynamic profile evolution including all transport channels: ion and electron heat, main particles, impurities, and momentum. Furthermore, QuaLiKiz now includes the impact of rotation and temperature anisotropy induced poloidal asymmetry on heavy impurity transport, important for W-transport applications. Application within the JETTO integrated modelling code results in 1 s of JET plasma simulation within 10 h using 10 CPUs. Simultaneous predictions of core density, temperature, and toroidal rotation profiles for both JET hybrid and baseline experiments are presented, covering both ion and electron turbulence scales. The simulations are successfully compared to measured profiles, with agreement mostly in the 5%-25% range according to standard figures of merit. QuaLiKiz is now open source and available at www.qualikiz.com.

Eigenvalue Tests and Distributions for Small Sample Order Determination for Complex Wishart Matrices

DTIC Science & Technology

1994-08-13

theoretic order determination criteria for ARMA(p, q) models can be expressed in the form of equation 4.2. The word ARIMA should not be a distractor...subjectivity is not necessarily bad. It enables us to build tractable models and efficiently achieve reasonable results. The charge of "subjectivity" lodged...signal processing studies because it simplifies the mathematics involved and it is not a bad model for a wide range of situations. Wooding [293] is

Learning and Information Approaches for Inference in Dynamic Data-Driven Geophysical Applications

NASA Astrophysics Data System (ADS)

Ravela, S.

2015-12-01

Many Geophysical inference problems are characterized by non-linear processes, high-dimensional models and complex uncertainties. A dynamic coupling between models, estimation, and sampling is typically sought to efficiently characterize and reduce uncertainty. This process is however fraught with several difficulties. Among them, the key difficulties are the ability to deal with model errors, efficacy of uncertainty quantification and data assimilation. In this presentation, we present three key ideas from learning and intelligent systems theory and apply them to two geophysical applications. The first idea is the use of Ensemble Learning to compensate for model error, the second is to develop tractable Information Theoretic Learning to deal with non-Gaussianity in inference, and the third is a Manifold Resampling technique for effective uncertainty quantification. We apply these methods, first to the development of a cooperative autonomous observing system using sUAS for studying coherent structures. We apply this to Second, we apply this to the problem of quantifying risk from hurricanes and storm surges in a changing climate. Results indicate that learning approaches can enable new effectiveness in cases where standard approaches to model reduction, uncertainty quantification and data assimilation fail.

Assessing the system value of optimal load shifting

DOE PAGES

Merrick, James; Ye, Yinyu; Entriken, Bob

2017-04-30

We analyze a competitive electricity market, where consumers exhibit optimal load shifting behavior to maximize utility and producers/suppliers maximize their profit under supply capacity constraints. The associated computationally tractable formulation can be used to inform market design or policy analysis in the context of increasing availability of the smart grid technologies that enable optimal load shifting. Through analytic and numeric assessment of the model, we assess the equilibrium value of optimal electricity load shifting, including how the value changes as more electricity consumers adopt associated technologies. For our illustrative numerical case, derived from the Current Trends scenario of the ERCOTmore » Long Term System Assessment, the average energy arbitrage value per ERCOT customer of optimal load shifting technologies is estimated to be $3 for the 2031 scenario year. We assess the sensitivity of this result to the flexibility of load, along with its relationship to the deployment of renewables. Finally, the model presented can also be a starting point for designing system operation infrastructure that communicates with the devices that schedule loads in response to price signals.« less

Assessing the system value of optimal load shifting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merrick, James; Ye, Yinyu; Entriken, Bob

We analyze a competitive electricity market, where consumers exhibit optimal load shifting behavior to maximize utility and producers/suppliers maximize their profit under supply capacity constraints. The associated computationally tractable formulation can be used to inform market design or policy analysis in the context of increasing availability of the smart grid technologies that enable optimal load shifting. Through analytic and numeric assessment of the model, we assess the equilibrium value of optimal electricity load shifting, including how the value changes as more electricity consumers adopt associated technologies. For our illustrative numerical case, derived from the Current Trends scenario of the ERCOTmore » Long Term System Assessment, the average energy arbitrage value per ERCOT customer of optimal load shifting technologies is estimated to be $3 for the 2031 scenario year. We assess the sensitivity of this result to the flexibility of load, along with its relationship to the deployment of renewables. Finally, the model presented can also be a starting point for designing system operation infrastructure that communicates with the devices that schedule loads in response to price signals.« less

Multimodal sensorimotor system in unicellular zoospores of a fungus.

PubMed

Swafford, Andrew J M; Oakley, Todd H

2018-01-19

Complex sensory systems often underlie critical behaviors, including avoiding predators and locating prey, mates and shelter. Multisensory systems that control motor behavior even appear in unicellular eukaryotes, such as Chlamydomonas , which are important laboratory models for sensory biology. However, we know of no unicellular opisthokonts that control motor behavior using a multimodal sensory system. Therefore, existing single-celled models for multimodal sensorimotor integration are very distantly related to animals. Here, we describe a multisensory system that controls the motor function of unicellular fungal zoospores. We found that zoospores of Allomyces arbusculus exhibit both phototaxis and chemotaxis. Furthermore, we report that closely related Allomyces species respond to either the chemical or the light stimuli presented in this study, not both, and likely do not share this multisensory system. This diversity of sensory systems within Allomyces provides a rare example of a comparative framework that can be used to examine the evolution of sensory systems following the gain/loss of available sensory modalities. The tractability of Allomyces and related fungi as laboratory organisms will facilitate detailed mechanistic investigations into the genetic underpinnings of novel photosensory systems, and how multisensory systems may have functioned in early opisthokonts before multicellularity allowed for the evolution of specialized cell types. © 2018. Published by The Company of Biologists Ltd.

Elucidation of Prion Protein Conformational Changes Associated with Infectivity by Fluorescence Spectroscopy

DTIC Science & Technology

2006-06-01

This work was supported by grants to MAM from the US Army Research (DAMD17- 03-1-0342) and the NIH COBRE program (P20 RR020185-01). Authors...and more tractable model for PrPSc. This is further supported by an intriguing discovery made by Caughey and coworkers in their search to

Drosophila as a genetic and cellular model for studies on axonal growth

PubMed Central

Sánchez-Soriano, Natalia; Tear, Guy; Whitington, Paul; Prokop, Andreas

2007-01-01

One of the most fascinating processes during nervous system development is the establishment of stereotypic neuronal networks. An essential step in this process is the outgrowth and precise navigation (pathfinding) of axons and dendrites towards their synaptic partner cells. This phenomenon was first described more than a century ago and, over the past decades, increasing insights have been gained into the cellular and molecular mechanisms regulating neuronal growth and navigation. Progress in this area has been greatly assisted by the use of simple and genetically tractable invertebrate model systems, such as the fruit fly Drosophila melanogaster. This review is dedicated to Drosophila as a genetic and cellular model to study axonal growth and demonstrates how it can and has been used for this research. We describe the various cellular systems of Drosophila used for such studies, insights into axonal growth cones and their cytoskeletal dynamics, and summarise identified molecular signalling pathways required for growth cone navigation, with particular focus on pathfinding decisions in the ventral nerve cord of Drosophila embryos. These Drosophila-specific aspects are viewed in the general context of our current knowledge about neuronal growth. PMID:17475018

Structural stability of nonlinear population dynamics.

PubMed

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Structural stability of nonlinear population dynamics

NASA Astrophysics Data System (ADS)

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Suppression of Soot Formation and Shapes of Laminar Jet Diffusion Flames

NASA Technical Reports Server (NTRS)

Xu, F.; Dai, Z.; Faeth, G. M.

2001-01-01

Laminar nonpremixed (diffusion) flames are of interest because they provide model flame systems that are far more tractable for analysis and experiments than practical turbulent flames. In addition, many properties of laminar diffusion flames are directly relevant to turbulent diffusion flames using laminar flamelet concepts. Finally, laminar diffusion flame shapes have been of interest since the classical study of Burke and Schumann because they involve a simple nonintrusive measurement that is convenient for evaluating flame shape predictions. Motivated by these observations, the shapes of round hydrocarbon-fueled laminar jet diffusion flames were considered, emphasizing conditions where effects of buoyancy are small because most practical flames are not buoyant. Earlier studies of shapes of hydrocarbon-fueled nonbuoyant laminar jet diffusion flames considered combustion in still air and have shown that flames at the laminar smoke point are roughly twice as long as corresponding soot-free (blue) flames and have developed simple ways to estimate their shapes. Corresponding studies of hydrocarbon-fueled weakly-buoyant laminar jet diffusion flames in coflowing air have also been reported. These studies were limited to soot-containing flames at laminar smoke point conditions and also developed simple ways to estimate their shapes but the behavior of corresponding soot-free flames has not been addressed. This is unfortunate because ways of selecting flame flow properties to reduce soot concentrations are of great interest; in addition, soot-free flames are fundamentally important because they are much more computationally tractable than corresponding soot-containing flames. Thus, the objectives of the present investigation were to observe the shapes of weakly-buoyant laminar jet diffusion flames at both soot-free and smoke point conditions and to use the results to evaluate simplified flame shape models. The present discussion is brief.

Solving the quantum many-body problem with artificial neural networks

NASA Astrophysics Data System (ADS)

Carleo, Giuseppe; Troyer, Matthias

2017-02-01

The challenge posed by the many-body problem in quantum physics originates from the difficulty of describing the nontrivial correlations encoded in the exponential complexity of the many-body wave function. Here we demonstrate that systematic machine learning of the wave function can reduce this complexity to a tractable computational form for some notable cases of physical interest. We introduce a variational representation of quantum states based on artificial neural networks with a variable number of hidden neurons. A reinforcement-learning scheme we demonstrate is capable of both finding the ground state and describing the unitary time evolution of complex interacting quantum systems. Our approach achieves high accuracy in describing prototypical interacting spins models in one and two dimensions.

An Empirical Polarizable Force Field Based on the Classical Drude Oscillator Model: Development History and Recent Applications

PubMed Central

2016-01-01

Molecular mechanics force fields that explicitly account for induced polarization represent the next generation of physical models for molecular dynamics simulations. Several methods exist for modeling induced polarization, and here we review the classical Drude oscillator model, in which electronic degrees of freedom are modeled by charged particles attached to the nuclei of their core atoms by harmonic springs. We describe the latest developments in Drude force field parametrization and application, primarily in the last 15 years. Emphasis is placed on the Drude-2013 polarizable force field for proteins, DNA, lipids, and carbohydrates. We discuss its parametrization protocol, development history, and recent simulations of biologically interesting systems, highlighting specific studies in which induced polarization plays a critical role in reproducing experimental observables and understanding physical behavior. As the Drude oscillator model is computationally tractable and available in a wide range of simulation packages, it is anticipated that use of these more complex physical models will lead to new and important discoveries of the physical forces driving a range of chemical and biological phenomena. PMID:26815602

Adaptive control using neural networks and approximate models.

PubMed

Narendra, K S; Mukhopadhyay, S

1997-01-01

The NARMA model is an exact representation of the input-output behavior of finite-dimensional nonlinear discrete-time dynamical systems in a neighborhood of the equilibrium state. However, it is not convenient for purposes of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate methods are used for realizing the neural controllers to overcome computational complexity. In this paper, we introduce two classes of models which are approximations to the NARMA model, and which are linear in the control input. The latter fact substantially simplifies both the theoretical analysis as well as the practical implementation of the controller. Extensive simulation studies have shown that the neural controllers designed using the proposed approximate models perform very well, and in many cases even better than an approximate controller designed using the exact NARMA model. In view of their mathematical tractability as well as their success in simulation studies, a case is made in this paper that such approximate input-output models warrant a detailed study in their own right.

Writing Pal: Feasibility of an Intelligent Writing Strategy Tutor in the High School Classroom

ERIC Educational Resources Information Center

Roscoe, Rod D.; McNamara, Danielle S.

2013-01-01

The Writing Pal (W-Pal) is a novel intelligent tutoring system (ITS) that offers writing strategy instruction, game-based practice, essay writing practice, and formative feedback to developing writers. Compared to more tractable and constrained learning domains for ITS, writing is an ill-defined domain because the features of effective writing are…

Peromyscus as a model system for human hepatitis C: An opportunity to advance our understanding of a complex host parasite system.

PubMed

Vandegrift, Kurt J; Critchlow, Justin T; Kapoor, Amit; Friedman, David A; Hudson, Peter J

2017-01-01

Worldwide, there are 185 million people infected with hepatitis C virus and approximately 350,000 people die each year from hepatitis C associated liver diseases. Human hepatitis C research has been hampered by the lack of an appropriate in vivo model system. Most of the in vivo research has been conducted on chimpanzees, which is complicated by ethical concerns, small sample sizes, high costs, and genetic heterogeneity. The house mouse system has led to greater understanding of a wide variety of human pathogens, but it is unreasonable to expect Mus musculus to be a good model system for every human pathogen. Alternative animal models can be developed in these cases. Ferrets (influenza), cotton rats (human respiratory virus), and woodchucks (hepatitis B) are all alternative models that have led to a greater understanding of human pathogens. Rodent models are tractable, genetically amenable and inbred and outbred strains can provide homogeneity in results. Recently, a rodent homolog of hepatitis C was discovered and isolated from the liver of a Peromyscus maniculatus. This represents the first small mammal (mouse) model system for human hepatitis C and it offers great potential to contribute to our understanding and ultimately aid in our efforts to combat this serious public health concern. Peromyscus are available commercially and can be used to inform questions about the origin, transmission, persistence, pathology, and rational treatment of hepatitis C. Here, we provide a disease ecologist's overview of this new virus and some suggestions for useful future experiments. Copyright © 2016. Published by Elsevier Ltd.

Human Chronotypes from a Theoretical Perspective

PubMed Central

Kramer, Achim; Herzel, Hanspeter

2013-01-01

The endogenous circadian timing system has evolved to synchronize an organism to periodically recurring environmental conditions. Those external time cues are called Zeitgebers. When entrained by a Zeitgeber, the intrinsic oscillator adopts a fixed phase relation to the Zeitgeber. Here, we systematically study how the phase of entrainment depends on clock and Zeitgeber properties. We combine numerical simulations of amplitude-phase models with predictions from analytically tractable models. In this way we derive relations between the phase of entrainment to the mismatch between the endogenous and Zeitgeber period, the Zeitgeber strength, and the range of entrainment. A core result is the “180° rule” asserting that the phase varies over a range of about 180° within the entrainment range. The 180° rule implies that clocks with a narrow entrainment range (“strong oscillators”) exhibit quite flexible entrainment phases. We argue that this high sensitivity of the entrainment phase contributes to the wide range of human chronotypes. PMID:23544070

SAHM:VisTrails (Software for Assisted Habitat Modeling for VisTrails): training course

USGS Publications Warehouse

Holcombe, Tracy

2014-01-01

VisTrails is an open-source management and scientific workflow system designed to integrate the best of both scientific workflow and scientific visualization systems. Developers can extend the functionality of the VisTrails system by creating custom modules for bundled VisTrails packages. The Invasive Species Science Branch of the U.S. Geological Survey (USGS) Fort Collins Science Center (FORT) and the U.S. Department of the Interior’s North Central Climate Science Center have teamed up to develop and implement such a module—the Software for Assisted Habitat Modeling (SAHM). SAHM expedites habitat modeling and helps maintain a record of the various input data, the steps before and after processing, and the modeling options incorporated in the construction of an ecological response model. There are four main advantages to using the SAHM:VisTrails combined package for species distribution modeling: (1) formalization and tractable recording of the entire modeling process; (2) easier collaboration through a common modeling framework; (3) a user-friendly graphical interface to manage file input, model runs, and output; and (4) extensibility to incorporate future and additional modeling routines and tools. In order to meet increased interest in the SAHM:VisTrails package, the FORT offers a training course twice a year. The course includes a combination of lecture, hands-on work, and discussion. Please join us and other ecological modelers to learn the capabilities of the SAHM:VisTrails package.

Strategies for Global Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Paul; Morris, Robert; Khatib, Lina; Ramakrishnan, Sailesh

2004-01-01

A temporal reasoning problem can often be naturally characterized as a collection of constraints with associated local preferences for times that make up the admissible values for those constraints. Globally preferred solutions to such problems emerge as a result of well-defined operations that compose and order temporal assignments. The overall objective of this work is a characterization of different notions of global preference, and to identify tractable sub-classes of temporal reasoning problems incorporating these notions. This paper extends previous results by refining the class of useful notions of global temporal preference that are associated with problems that admit of tractable solution techniques. This paper also answers the hitherto open question of whether problems that seek solutions that are globally preferred from a Utilitarian criterion for global preference can be found tractably.

Intra-organizational Computation and Complexity

DTIC Science & Technology

2003-01-01

models. New methodologies, centered on understanding algorithmic complexity, are being developed that may enable us to better handle network data ...tractability of data analysis, and enable more precise theorization. A variety of measures of algorithmic complexity, e.g., Kolmogorov-Chaitin, and a...variety of proxies exist (which are often turned to for pragmatic reasons) ( Lempel and Ziv ,1976). For the most part, social and organizational

Anti-Lemons: School Reputation and Educational Quality. NBER Working Paper No. 15112

ERIC Educational Resources Information Center

MacLeod, W. Bentley; Urquiola, Miguel

2009-01-01

Friedman (1962) argued that a free market in which schools compete based upon their reputation would lead to an efficient supply of educational services. This paper explores this issue by building a tractable model in which rational individuals go to school and accumulate skill valued in a perfectly competitive labor market. To this it adds one…

Distributed Decision Making in a Dynamic Network Environment

DTIC Science & Technology

1990-01-01

protocols, particularly when traffic arrival statistics are varying or unknown, and loads are high. Both nonpreemptive and preemptive repeat disciplines are...The simulation model allows general value functions, continuous time operation, and preemptive or nonpreemptive service. For reasons of tractability... nonpreemptive LIFO, (4) nonpreemptive LIFO with discarding, (5) nonpreemptive HOL, (6) nonpreemp- tive HOL with discarding, (7) preemptive repeat HOL, (8

A Report on Simulation-Driven Reliability and Failure Analysis of Large-Scale Storage Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wan, Lipeng; Wang, Feiyi; Oral, H. Sarp

High-performance computing (HPC) storage systems provide data availability and reliability using various hardware and software fault tolerance techniques. Usually, reliability and availability are calculated at the subsystem or component level using limited metrics such as, mean time to failure (MTTF) or mean time to data loss (MTTDL). This often means settling on simple and disconnected failure models (such as exponential failure rate) to achieve tractable and close-formed solutions. However, such models have been shown to be insufficient in assessing end-to-end storage system reliability and availability. We propose a generic simulation framework aimed at analyzing the reliability and availability of storagemore » systems at scale, and investigating what-if scenarios. The framework is designed for an end-to-end storage system, accommodating the various components and subsystems, their interconnections, failure patterns and propagation, and performs dependency analysis to capture a wide-range of failure cases. We evaluate the framework against a large-scale storage system that is in production and analyze its failure projections toward and beyond the end of lifecycle. We also examine the potential operational impact by studying how different types of components affect the overall system reliability and availability, and present the preliminary results« less

larvalign: Aligning Gene Expression Patterns from the Larval Brain of Drosophila melanogaster.

PubMed

Muenzing, Sascha E A; Strauch, Martin; Truman, James W; Bühler, Katja; Thum, Andreas S; Merhof, Dorit

2018-01-01

The larval brain of the fruit fly Drosophila melanogaster is a small, tractable model system for neuroscience. Genes for fluorescent marker proteins can be expressed in defined, spatially restricted neuron populations. Here, we introduce the methods for 1) generating a standard template of the larval central nervous system (CNS), 2) spatial mapping of expression patterns from different larvae into a reference space defined by the standard template. We provide a manually annotated gold standard that serves for evaluation of the registration framework involved in template generation and mapping. A method for registration quality assessment enables the automatic detection of registration errors, and a semi-automatic registration method allows one to correct registrations, which is a prerequisite for a high-quality, curated database of expression patterns. All computational methods are available within the larvalign software package: https://github.com/larvalign/larvalign/releases/tag/v1.0.

Competition between anisotropic viscous fingers

NASA Astrophysics Data System (ADS)

Pecelerowicz, M.; Budek, A.; Szymczak, P.

2014-09-01

We consider viscous fingers created by injection of low viscosity fluid into the network of capillaries initially filled with a more viscous fluid (motor oil). Due to the anisotropy of the system and its geometry, such a setup promotes the formation of long-and-thin fingers which then grow and compete for the available flow, interacting through the pressure field. The interaction between the fingers is analyzed using the branched growth formalism of Halsey and Leibig (Phys. Rev. A 46, 7723, 1992) using a number of simple, analytically tractable models. It is shown that as soon as the fingers are allowed to capture the flow from one another, the fixed point appears in the phase space, corresponding to the asymptotic state in which the growth of one of the fingers in hindered by the other. The properties of phase space flows in such systems are shown to be remarkably insensitive to the details of the dynamics.

A mathematical model for simulating noise suppression of lined ejectors

NASA Technical Reports Server (NTRS)

Watson, Willie R.

1994-01-01

A mathematical model containing the essential features embodied in the noise suppression of lined ejectors is presented. Although some simplification of the physics is necessary to render the model mathematically tractable, the current model is the most versatile and technologically advanced at the current time. A system of linearized equations and the boundary conditions governing the sound field are derived starting from the equations of fluid dynamics. A nonreflecting boundary condition is developed. In view of the complex nature of the equations, a parametric study requires the use of numerical techniques and modern computers. A finite element algorithm that solves the differential equations coupled with the boundary condition is then introduced. The numerical method results in a matrix equation with several hundred thousand degrees of freedom that is solved efficiently on a supercomputer. The model is validated by comparing results either with exact solutions or with approximate solutions from other works. In each case, excellent correlations are obtained. The usefulness of the model as an optimization tool and the importance of variable impedance liners as a mechanism for achieving broadband suppression within a lined ejector are demonstrated.

Vacation model for Markov machine repair problem with two heterogeneous unreliable servers and threshold recovery

NASA Astrophysics Data System (ADS)

Jain, Madhu; Meena, Rakesh Kumar

2018-03-01

Markov model of multi-component machining system comprising two unreliable heterogeneous servers and mixed type of standby support has been studied. The repair job of broken down machines is done on the basis of bi-level threshold policy for the activation of the servers. The server returns back to render repair job when the pre-specified workload of failed machines is build up. The first (second) repairman turns on only when the work load of N1 (N2) failed machines is accumulated in the system. The both servers may go for vacation in case when all the machines are in good condition and there are no pending repair jobs for the repairmen. Runge-Kutta method is implemented to solve the set of governing equations used to formulate the Markov model. Various system metrics including the mean queue length, machine availability, throughput, etc., are derived to determine the performance of the machining system. To provide the computational tractability of the present investigation, a numerical illustration is provided. A cost function is also constructed to determine the optimal repair rate of the server by minimizing the expected cost incurred on the system. The hybrid soft computing method is considered to develop the adaptive neuro-fuzzy inference system (ANFIS). The validation of the numerical results obtained by Runge-Kutta approach is also facilitated by computational results generated by ANFIS.

Computing the non-Markovian coarse-grained interactions derived from the Mori-Zwanzig formalism in molecular systems: Application to polymer melts

NASA Astrophysics Data System (ADS)

Li, Zhen; Lee, Hee Sun; Darve, Eric; Karniadakis, George Em

2017-01-01

Memory effects are often introduced during coarse-graining of a complex dynamical system. In particular, a generalized Langevin equation (GLE) for the coarse-grained (CG) system arises in the context of Mori-Zwanzig formalism. Upon a pairwise decomposition, GLE can be reformulated into its pairwise version, i.e., non-Markovian dissipative particle dynamics (DPD). GLE models the dynamics of a single coarse particle, while DPD considers the dynamics of many interacting CG particles, with both CG systems governed by non-Markovian interactions. We compare two different methods for the practical implementation of the non-Markovian interactions in GLE and DPD systems. More specifically, a direct evaluation of the non-Markovian (NM) terms is performed in LE-NM and DPD-NM models, which requires the storage of historical information that significantly increases computational complexity. Alternatively, we use a few auxiliary variables in LE-AUX and DPD-AUX models to replace the non-Markovian dynamics with a Markovian dynamics in a higher dimensional space, leading to a much reduced memory footprint and computational cost. In our numerical benchmarks, the GLE and non-Markovian DPD models are constructed from molecular dynamics (MD) simulations of star-polymer melts. Results show that a Markovian dynamics with auxiliary variables successfully generates equivalent non-Markovian dynamics consistent with the reference MD system, while maintaining a tractable computational cost. Also, transient subdiffusion of the star-polymers observed in the MD system can be reproduced by the coarse-grained models. The non-interacting particle models, LE-NM/AUX, are computationally much cheaper than the interacting particle models, DPD-NM/AUX. However, the pairwise models with momentum conservation are more appropriate for correctly reproducing the long-time hydrodynamics characterised by an algebraic decay in the velocity autocorrelation function.

Analytical modeling of the structureborne noise path on a small twin-engine aircraft

NASA Technical Reports Server (NTRS)

Cole, J. E., III; Stokes, A. Westagard; Garrelick, J. M.; Martini, K. F.

1988-01-01

The structureborne noise path of a six passenger twin-engine aircraft is analyzed. Models of the wing and fuselage structures as well as the interior acoustic space of the cabin are developed and used to evaluate sensitivity to structural and acoustic parameters. Different modeling approaches are used to examine aspects of the structureborne path. These approaches are guided by a number of considerations including the geometry of the structures, the frequency range of interest, and the tractability of the computations. Results of these approaches are compared with experimental data.

Real-time million-synapse simulation of rat barrel cortex.

PubMed

Sharp, Thomas; Petersen, Rasmus; Furber, Steve

2014-01-01

Simulations of neural circuits are bounded in scale and speed by available computing resources, and particularly by the differences in parallelism and communication patterns between the brain and high-performance computers. SpiNNaker is a computer architecture designed to address this problem by emulating the structure and function of neural tissue, using very many low-power processors and an interprocessor communication mechanism inspired by axonal arbors. Here we demonstrate that thousand-processor SpiNNaker prototypes can simulate models of the rodent barrel system comprising 50,000 neurons and 50 million synapses. We use the PyNN library to specify models, and the intrinsic features of Python to control experimental procedures and analysis. The models reproduce known thalamocortical response transformations, exhibit known, balanced dynamics of excitation and inhibition, and show a spatiotemporal spread of activity though the superficial cortical layers. These demonstrations are a significant step toward tractable simulations of entire cortical areas on the million-processor SpiNNaker machines in development.

Regulation of zebrafish sleep and arousal states: current and prospective approaches

PubMed Central

Chiu, Cindy N.; Prober, David A.

2013-01-01

Every day, we shift among various states of sleep and arousal to meet the many demands of our bodies and environment. A central puzzle in neurobiology is how the brain controls these behavioral states, which are essential to an animal's well-being and survival. Mammalian models have predominated sleep and arousal research, although in the past decade, invertebrate models have made significant contributions to our understanding of the genetic underpinnings of behavioral states. More recently, the zebrafish has emerged as a promising model system for sleep and arousal research. Here we review experimental evidence that the zebrafish, a diurnal vertebrate, exhibits fundamental behavioral and neurochemical characteristics of mammalian sleep and arousal. We also propose how specific advantages of the zebrafish can be harnessed to advance the field. These include tractable genetics to identify and manipulate molecular and cellular regulators of behavioral states, optical transparency to facilitate in vivo observation of neural structure and function, and amenability to high-throughput drug screens to discover novel therapies for neurological disorders. PMID:23576957

Development of closed-loop neural interface technology in a rat model: combining motor cortex operant conditioning with visual cortex microstimulation.

PubMed

Marzullo, Timothy Charles; Lehmkuhle, Mark J; Gage, Gregory J; Kipke, Daryl R

2010-04-01

Closed-loop neural interface technology that combines neural ensemble decoding with simultaneous electrical microstimulation feedback is hypothesized to improve deep brain stimulation techniques, neuromotor prosthetic applications, and epilepsy treatment. Here we describe our iterative results in a rat model of a sensory and motor neurophysiological feedback control system. Three rats were chronically implanted with microelectrode arrays in both the motor and visual cortices. The rats were subsequently trained over a period of weeks to modulate their motor cortex ensemble unit activity upon delivery of intra-cortical microstimulation (ICMS) of the visual cortex in order to receive a food reward. Rats were given continuous feedback via visual cortex ICMS during the response periods that was representative of the motor cortex ensemble dynamics. Analysis revealed that the feedback provided the animals with indicators of the behavioral trials. At the hardware level, this preparation provides a tractable test model for improving the technology of closed-loop neural devices.

The zebrafish eye—a paradigm for investigating human ocular genetics

PubMed Central

Richardson, R; Tracey-White, D; Webster, A; Moosajee, M

2017-01-01

Although human epidemiological and genetic studies are essential to elucidate the aetiology of normal and aberrant ocular development, animal models have provided us with an understanding of the pathogenesis of multiple developmental ocular malformations. Zebrafish eye development displays in depth molecular complexity and stringent spatiotemporal regulation that incorporates developmental contributions of the surface ectoderm, neuroectoderm and head mesenchyme, similar to that seen in humans. For this reason, and due to its genetic tractability, external fertilisation, and early optical clarity, the zebrafish has become an invaluable vertebrate system to investigate human ocular development and disease. Recently, zebrafish have been at the leading edge of preclinical therapy development, with their amenability to genetic manipulation facilitating the generation of robust ocular disease models required for large-scale genetic and drug screening programmes. This review presents an overview of human and zebrafish ocular development, genetic methodologies employed for zebrafish mutagenesis, relevant models of ocular disease, and finally therapeutic approaches, which may have translational leads in the future. PMID:27612182

Real-time million-synapse simulation of rat barrel cortex

PubMed Central

Sharp, Thomas; Petersen, Rasmus; Furber, Steve

2014-01-01

Simulations of neural circuits are bounded in scale and speed by available computing resources, and particularly by the differences in parallelism and communication patterns between the brain and high-performance computers. SpiNNaker is a computer architecture designed to address this problem by emulating the structure and function of neural tissue, using very many low-power processors and an interprocessor communication mechanism inspired by axonal arbors. Here we demonstrate that thousand-processor SpiNNaker prototypes can simulate models of the rodent barrel system comprising 50,000 neurons and 50 million synapses. We use the PyNN library to specify models, and the intrinsic features of Python to control experimental procedures and analysis. The models reproduce known thalamocortical response transformations, exhibit known, balanced dynamics of excitation and inhibition, and show a spatiotemporal spread of activity though the superficial cortical layers. These demonstrations are a significant step toward tractable simulations of entire cortical areas on the million-processor SpiNNaker machines in development. PMID:24910593

Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover

DOE PAGES

Stegen, James C.; Fredrickson, James K.; Wilkins, Michael J.; ...

2016-04-07

Environmental transition zones are associated with geochemical gradients that overcome energy limitations to microbial metabolism, resulting in biogeochemical hot spots and moments. Riverine systems where groundwater mixes with surface water (the hyporheic zone) are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. To investigate the coupling among groundwater-surface water mixing, microbial communities, and biogeochemistry we applied ecological theory, aqueous biogeochemistry, DNA sequencing, and ultra-high resolution organic carbon profiling to field samples collected across times and locations representing amore » broad range of mixing conditions. Mixing of groundwater and surface water resulted in a shift from transport-driven stochastic dynamics to a deterministic microbial structure associated with elevated biogeochemical rates. While the dynamics of the hyporheic make predictive modeling a challenge, we provide new knowledge that can improve the tractability of such models.« less

Delta-Complete Analysis for Bounded Reachability of Hybrid Systems

DTIC Science & Technology

2014-07-16

framework makes bounded reachability of hybrid systems a much more mathematically tractable problem and show that our practical implementation can handle...step i in the hybrid trajectory to an appropriate discrete mode in H , and make sure that the flow, jump, inv, init conditions are satisfied...trajectories start with some initial state satisfying initq(x0) for some q. In each step, it follows flowq(xi,xti, t) and makes a continuous flow from xi to x t

Tractable Quantification of Metastability for Robust Bipedal Locomotion

DTIC Science & Technology

2015-06-01

environmental conditions, including rough terrain. The intuitive and meaningful robustness quanti cation adopted in this thesis begins by stochastic...the system as a Markov chain. Then, failure rates can be easily quanti ed by calculating the expected number of steps before failure. Once robustness is...sensor noise . . . . . . . . . . . . . . . . . . . 54 5.8 Performance evaluation on the dense mesh . . . . . . . . . . . . . . . . . 56 5.9 Stability of

Laminar Soot Processes Experiment Shedding Light on Flame Radiation

NASA Technical Reports Server (NTRS)

Urban, David L.

1998-01-01

The Laminar Soot Processes (LSP) experiment investigated soot processes in nonturbulent, round gas jet diffusion flames in still air. The soot processes within these flames are relevant to practical combustion in aircraft propulsion systems, diesel engines, and furnaces. However, for the LSP experiment, the flames were slowed and spread out to allow measurements that are not tractable for practical, Earth-bound flames.

Multifractal Value at Risk model

NASA Astrophysics Data System (ADS)

Lee, Hojin; Song, Jae Wook; Chang, Woojin

2016-06-01

In this paper new Value at Risk (VaR) model is proposed and investigated. We consider the multifractal property of financial time series and develop a multifractal Value at Risk (MFVaR). MFVaR introduced in this paper is analytically tractable and not based on simulation. Empirical study showed that MFVaR can provide the more stable and accurate forecasting performance in volatile financial markets where large loss can be incurred. This implies that our multifractal VaR works well for the risk measurement of extreme credit events.

Bridging scales in the evolution of infectious disease life histories: theory.

PubMed

Day, Troy; Alizon, Samuel; Mideo, Nicole

2011-12-01

A significant goal of recent theoretical research on pathogen evolution has been to develop theory that bridges within- and between-host dynamics. The main approach used to date is one that nests within-host models of pathogen replication in models for the between-host spread of infectious diseases. Although this provides an elegant approach, it nevertheless suffers from some practical difficulties. In particular, the information required to satisfactorily model the mechanistic details of the within-host dynamics is not often available. Here, we present a theoretical approach that circumvents these difficulties by quantifying the relevant within-host factors in an empirically tractable way. The approach is closely related to quantitative genetic models for function-valued traits, and it also allows for the prediction of general characteristics of disease life history, including the timing of virulence, transmission, and host recovery. In a companion paper, we illustrate the approach by applying it to data from a model system of malaria. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Dynamic Redox Regulation of IL-4 Signaling.

PubMed

Dwivedi, Gaurav; Gran, Margaret A; Bagchi, Pritha; Kemp, Melissa L

2015-11-01

Quantifying the magnitude and dynamics of protein oxidation during cell signaling is technically challenging. Computational modeling provides tractable, quantitative methods to test hypotheses of redox mechanisms that may be simultaneously operative during signal transduction. The interleukin-4 (IL-4) pathway, which has previously been reported to induce reactive oxygen species and oxidation of PTP1B, may be controlled by several other putative mechanisms of redox regulation; widespread proteomic thiol oxidation observed via 2D redox differential gel electrophoresis upon IL-4 treatment suggests more than one redox-sensitive protein implicated in this pathway. Through computational modeling and a model selection strategy that relied on characteristic STAT6 phosphorylation dynamics of IL-4 signaling, we identified reversible protein tyrosine phosphatase (PTP) oxidation as the primary redox regulatory mechanism in the pathway. A systems-level model of IL-4 signaling was developed that integrates synchronous pan-PTP oxidation with ROS-independent mechanisms. The model quantitatively predicts the dynamics of IL-4 signaling over a broad range of new redox conditions, offers novel hypotheses about regulation of JAK/STAT signaling, and provides a framework for interrogating putative mechanisms involving receptor-initiated oxidation.

Dynamic Redox Regulation of IL-4 Signaling

PubMed Central

Dwivedi, Gaurav; Gran, Margaret A.; Bagchi, Pritha; Kemp, Melissa L.

2015-01-01

Quantifying the magnitude and dynamics of protein oxidation during cell signaling is technically challenging. Computational modeling provides tractable, quantitative methods to test hypotheses of redox mechanisms that may be simultaneously operative during signal transduction. The interleukin-4 (IL-4) pathway, which has previously been reported to induce reactive oxygen species and oxidation of PTP1B, may be controlled by several other putative mechanisms of redox regulation; widespread proteomic thiol oxidation observed via 2D redox differential gel electrophoresis upon IL-4 treatment suggests more than one redox-sensitive protein implicated in this pathway. Through computational modeling and a model selection strategy that relied on characteristic STAT6 phosphorylation dynamics of IL-4 signaling, we identified reversible protein tyrosine phosphatase (PTP) oxidation as the primary redox regulatory mechanism in the pathway. A systems-level model of IL-4 signaling was developed that integrates synchronous pan-PTP oxidation with ROS-independent mechanisms. The model quantitatively predicts the dynamics of IL-4 signaling over a broad range of new redox conditions, offers novel hypotheses about regulation of JAK/STAT signaling, and provides a framework for interrogating putative mechanisms involving receptor-initiated oxidation. PMID:26562652

A High Performance Computing Study of a Scalable FISST-Based Approach to Multi-Target, Multi-Sensor Tracking

NASA Astrophysics Data System (ADS)

Hussein, I.; Wilkins, M.; Roscoe, C.; Faber, W.; Chakravorty, S.; Schumacher, P.

2016-09-01

Finite Set Statistics (FISST) is a rigorous Bayesian multi-hypothesis management tool for the joint detection, classification and tracking of multi-sensor, multi-object systems. Implicit within the approach are solutions to the data association and target label-tracking problems. The full FISST filtering equations, however, are intractable. While FISST-based methods such as the PHD and CPHD filters are tractable, they require heavy moment approximations to the full FISST equations that result in a significant loss of information contained in the collected data. In this paper, we review Smart Sampling Markov Chain Monte Carlo (SSMCMC) that enables FISST to be tractable while avoiding moment approximations. We study the effect of tuning key SSMCMC parameters on tracking quality and computation time. The study is performed on a representative space object catalog with varying numbers of RSOs. The solution is implemented in the Scala computing language at the Maui High Performance Computing Center (MHPCC) facility.

The Quality of the Embedding Potential Is Decisive for Minimal Quantum Region Size in Embedding Calculations: The Case of the Green Fluorescent Protein.

PubMed

Nåbo, Lina J; Olsen, Jógvan Magnus Haugaard; Martínez, Todd J; Kongsted, Jacob

2017-12-12

The calculation of spectral properties for photoactive proteins is challenging because of the large cost of electronic structure calculations on large systems. Mixed quantum mechanical (QM) and molecular mechanical (MM) methods are typically employed to make such calculations computationally tractable. This study addresses the connection between the minimal QM region size and the method used to model the MM region in the calculation of absorption properties-here exemplified for calculations on the green fluorescent protein. We find that polarizable embedding is necessary for a qualitatively correct description of the MM region, and that this enables the use of much smaller QM regions compared to fixed charge electrostatic embedding. Furthermore, absorption intensities converge very slowly with system size and inclusion of effective external field effects in the MM region through polarizabilities is therefore very important. Thus, this embedding scheme enables accurate prediction of intensities for systems that are too large to be treated fully quantum mechanically.

The antiviral innate immune response in fish: evolution and conservation of the IFN system.

PubMed

Langevin, Christelle; Aleksejeva, Elina; Passoni, Gabriella; Palha, Nuno; Levraud, Jean-Pierre; Boudinot, Pierre

2013-12-13

Innate immunity constitutes the first line of the host defense after pathogen invasion. Viruses trigger the expression of interferons (IFNs). These master antiviral cytokines induce in turn a large number of interferon-stimulated genes, which possess diverse effector and regulatory functions. The IFN system is conserved in all tetrapods as well as in fishes, but not in tunicates or in the lancelet, suggesting that it originated in early vertebrates. Viral diseases are an important concern of fish aquaculture, which is why fish viruses and antiviral responses have been studied mostly in species of commercial value, such as salmonids. More recently, there has been an interest in the use of more tractable model fish species, notably the zebrafish. Progress in genomics now makes it possible to get a relatively complete image of the genes involved in innate antiviral responses in fish. In this review, by comparing the IFN system between teleosts and mammals, we will focus on its evolution in vertebrates. © 2013 Elsevier Ltd. All rights reserved.

Using absolute gravimeter data to determine vertical gravity gradients

USGS Publications Warehouse

Robertson, D.S.

2001-01-01

The position versus time data from a free-fall absolute gravimeter can be used to estimate the vertical gravity gradient in addition to the gravity value itself. Hipkin has reported success in estimating the vertical gradient value using a data set of unusually good quality. This paper explores techniques that may be applicable to a broader class of data that may be contaminated with "system response" errors of larger magnitude than were evident in the data used by Hipkin. This system response function is usually modelled as a sum of exponentially decaying sinusoidal components. The technique employed here involves combining the x0, v0 and g parameters from all the drops made during a site occupation into a single least-squares solution, and including the value of the vertical gradient and the coefficients of system response function in the same solution. The resulting non-linear equations must be solved iteratively and convergence presents some difficulties. Sparse matrix techniques are used to make the least-squares problem computationally tractable.

Active Ambiguity Reduction: An Experiment Design Approach to Tractable Qualitative Reasoning.

DTIC Science & Technology

1987-04-20

Approach to Tractable Qualitative Reasoning Shankar A. Rajamoney t [ For Gerald F. DeJong Artificial Intelligence Research Group Coordinated Science...Representations of Knowledge in a Mechanics Problem- Solver." Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge. MIA...International Joint Conference on Artificial Intelligence. Tokyo. Japan. 1979. [de Kleer84] J. de Kleer and J. S. Brown. "A Qualitative Physics Based on

Self-consistent chaos in a mean-field Hamiltonian model of fluids and plasmas

NASA Astrophysics Data System (ADS)

del-Castillo-Negrete, D.; Firpo, Marie-Christine

2002-11-01

We present a mean-field Hamiltonian model that describes the collective dynamics of marginally stable fluids and plasmas. In plasmas, the model describes the self-consistent evolution of electron holes and clumps in phase space. In fluids, the model describes the dynamics of vortices with negative and positive circulation in shear flows. The mean-field nature of the system makes it a tractable model to study the dynamics of large degrees-of-freedom, coupled Hamiltonian systems. Here we focus in the role of self-consistent chaos in the formation and destruction of phase space coherent structures. Numerical simulations in the finite N and in the Narrow kinetic limit (where N is the number of particles) show the existence of coherent, rotating dipole states. We approximate the dipole as two macroparticles, and show that the N = 2 limit has a family of rotating integrable solutions described by a one degree-of-freedom nontwist Hamiltonian. The coherence of the dipole is explained in terms of a parametric resonance between the rotation frequency of the macroparticles and the oscillation frequency of the self-consistent mean field. For a class of initial conditions, the mean field exhibits a self-consistent, elliptic-hyperbolic bifurcation that leads to the destruction of the dipole and violent mixing of the phase space.

Electrons on a spherical surface: Physical properties and hollow spherical clusters

NASA Astrophysics Data System (ADS)

Cricchio, Dario; Fiordilino, Emilio; Persico, Franco

2012-07-01

We discuss the physical properties of a noninteracting electron gas constrained to a spherical surface. In particular we consider its chemical potentials, its ionization potential, and its electric static polarizability. All these properties are discussed analytically as functions of the number N of electrons. The trends obtained with increasing N are compared with those of the corresponding properties experimentally measured or theoretically evaluated for quasispherical hollow atomic and molecular clusters. Most of the properties investigated display similar trends, characterized by a prominence of shell effects. This leads to the definition of a scale-invariant distribution of magic numbers which follows a power law with critical exponent -0.5. We conclude that our completely mechanistic and analytically tractable model can be useful for the analysis of self-assembling complex systems.

Complex Causal Process Diagrams for Analyzing the Health Impacts of Policy Interventions

PubMed Central

Joffe, Michael; Mindell, Jennifer

2006-01-01

Causal diagrams are rigorous tools for controlling confounding. They also can be used to describe complex causal systems, which is done routinely in communicable disease epidemiology. The use of change diagrams has advantages over static diagrams, because change diagrams are more tractable, relate better to interventions, and have clearer interpretations. Causal diagrams are a useful basis for modeling. They make assumptions explicit, provide a framework for analysis, generate testable predictions, explore the effects of interventions, and identify data gaps. Causal diagrams can be used to integrate different types of information and to facilitate communication both among public health experts and between public health experts and experts in other fields. Causal diagrams allow the use of instrumental variables, which can help control confounding and reverse causation. PMID:16449586

Quantum simulations with noisy quantum computers

NASA Astrophysics Data System (ADS)

Gambetta, Jay

Quantum computing is a new computational paradigm that is expected to lie beyond the standard model of computation. This implies a quantum computer can solve problems that can't be solved by a conventional computer with tractable overhead. To fully harness this power we need a universal fault-tolerant quantum computer. However the overhead in building such a machine is high and a full solution appears to be many years away. Nevertheless, we believe that we can build machines in the near term that cannot be emulated by a conventional computer. It is then interesting to ask what these can be used for. In this talk we will present our advances in simulating complex quantum systems with noisy quantum computers. We will show experimental implementations of this on some small quantum computers.

Physiological controls of large‐scale patterning in planarian regeneration: a molecular and computational perspective on growth and form

PubMed Central

Durant, Fallon; Lobo, Daniel; Hammelman, Jennifer

2016-01-01

Abstract Planaria are complex metazoans that repair damage to their bodies and cease remodeling when a correct anatomy has been achieved. This model system offers a unique opportunity to understand how large‐scale anatomical homeostasis emerges from the activities of individual cells. Much progress has been made on the molecular genetics of stem cell activity in planaria. However, recent data also indicate that the global pattern is regulated by physiological circuits composed of ionic and neurotransmitter signaling. Here, we overview the multi‐scale problem of understanding pattern regulation in planaria, with specific focus on bioelectric signaling via ion channels and gap junctions (electrical synapses), and computational efforts to extract explanatory models from functional and molecular data on regeneration. We present a perspective that interprets results in this fascinating field using concepts from dynamical systems theory and computational neuroscience. Serving as a tractable nexus between genetic, physiological, and computational approaches to pattern regulation, planarian pattern homeostasis harbors many deep insights for regenerative medicine, evolutionary biology, and engineering. PMID:27499881

Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Fallah-Ghalhary, G.-A.; Habibi Nokhandan, M.; Mousavi Baygi, M.

2009-04-01

Long-term rainfall prediction is very important to countries thriving on agro-based economy. In general, climate and rainfall are highly non-linear phenomena in nature giving rise to what is known as "butterfly effect". The parameters that are required to predict the rainfall are enormous even for a short period. Soft computing is an innovative approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments, and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability, and better rapport with reality. In this paper, 33 years of rainfall data analyzed in khorasan state, the northeastern part of Iran situated at latitude-longitude pairs (31°-38°N, 74°- 80°E). this research attempted to train Fuzzy Inference System (FIS) based prediction models with 33 years of rainfall data. For performance evaluation, the model predicted outputs were compared with the actual rainfall data. Simulation results reveal that soft computing techniques are promising and efficient. The test results using by FIS model showed that the RMSE was obtained 52 millimeter.

Double-well dynamics of noise-driven control activation in human intermittent control: the case of stick balancing.

PubMed

Zgonnikov, Arkady; Lubashevsky, Ihor

2015-11-01

When facing a task of balancing a dynamic system near an unstable equilibrium, humans often adopt intermittent control strategy: Instead of continuously controlling the system, they repeatedly switch the control on and off. Paradigmatic example of such a task is stick balancing. Despite the simplicity of the task itself, the complexity of human intermittent control dynamics in stick balancing still puzzles researchers in motor control. Here we attempt to model one of the key mechanisms of human intermittent control, control activation, using as an example the task of overdamped stick balancing. In doing so, we focus on the concept of noise-driven activation, a more general alternative to the conventional threshold-driven activation. We describe control activation as a random walk in an energy potential, which changes in response to the state of the controlled system. By way of numerical simulations, we show that the developed model captures the core properties of human control activation observed previously in the experiments on overdamped stick balancing. Our results demonstrate that the double-well potential model provides tractable mathematical description of human control activation at least in the considered task and suggest that the adopted approach can potentially aid in understanding human intermittent control in more complex processes.

Black holes in quasi-topological gravity and conformal couplings

NASA Astrophysics Data System (ADS)

Chernicoff, Mariano; Fierro, Octavio; Giribet, Gaston; Oliva, Julio

2017-02-01

Lovelock theory of gravity provides a tractable model to investigate the effects of higher-curvature terms in the context of AdS/CFT. Yielding second order, ghost-free field equations, this theory represents a minimal setup in which higher-order gravitational couplings in asymptotically Anti-de Sitter (AdS) spaces, including black holes, can be solved analytically. This however has an obvious limitation as in dimensions lower than seven, the contribution from cubic or higher curvature terms is merely topological. Therefore, in order to go beyond quadratic order and study higher terms in AdS5 analytically, one is compelled to look for other toy models. One such model is the so-called quasi-topological gravity, which, despite being a higher-derivative theory, provides a tractable setup with R 3 and R 4 terms. In this paper, we investigate AdS5 black holes in quasi-topological gravity. We consider the theory conformally coupled to matter and in presence of Abelian gauge fields. We show that charged black holes in AdS5 which, in addition, exhibit a backreaction of the matter fields on the geometry can be found explicitly in this theory. These solutions generalize the black hole solution of quasi-topological gravity and exist in a region of the parameter spaces consistent with the constraints coming from causality and other consistency conditions. They have finite conserved charges and exhibit non-trivial thermodynamical properties.

Synergistic effects in threshold models on networks.

PubMed

Juul, Jonas S; Porter, Mason A

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can-depending on a parameter-either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

Synergistic effects in threshold models on networks

NASA Astrophysics Data System (ADS)

Juul, Jonas S.; Porter, Mason A.

2018-01-01

Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

Genomic Sequence and Experimental Tractability of a New Decapod Shrimp Model, Neocaridina denticulata

PubMed Central

Kenny, Nathan J.; Sin, Yung Wa; Shen, Xin; Zhe, Qu; Wang, Wei; Chan, Ting Fung; Tobe, Stephen S.; Shimeld, Sebastian M.; Chu, Ka Hou; Hui, Jerome H. L.

2014-01-01

The speciose Crustacea is the largest subphylum of arthropods on the planet after the Insecta. To date, however, the only publically available sequenced crustacean genome is that of the water flea, Daphnia pulex, a member of the Branchiopoda. While Daphnia is a well-established ecotoxicological model, previous study showed that one-third of genes contained in its genome are lineage-specific and could not be identified in any other metazoan genomes. To better understand the genomic evolution of crustaceans and arthropods, we have sequenced the genome of a novel shrimp model, Neocaridina denticulata, and tested its experimental malleability. A library of 170-bp nominal fragment size was constructed from DNA of a starved single adult and sequenced using the Illumina HiSeq2000 platform. Core eukaryotic genes, the mitochondrial genome, developmental patterning genes (such as Hox) and microRNA processing pathway genes are all present in this animal, suggesting it has not undergone massive genomic loss. Comparison with the published genome of Daphnia pulex has allowed us to reveal 3750 genes that are indeed specific to the lineage containing malacostracans and branchiopods, rather than Daphnia-specific (E-value: 10−6). We also show the experimental tractability of N. denticulata, which, together with the genomic resources presented here, make it an ideal model for a wide range of further aquacultural, developmental, ecotoxicological, food safety, genetic, hormonal, physiological and reproductive research, allowing better understanding of the evolution of crustaceans and other arthropods. PMID:24619275

Explanation and the Theory of Expert Problem Solving

DTIC Science & Technology

1990-02-01

specified output, Our work has aimed to identify the individual generic tasks, to analyze them properly, and to clarify their relationships to more...coverage of hypotheses must be tractable. that there cannot be many incompatibility relationships or cancellation effects between individual hypotheses. and...no necessary relationship between this justificatory argument and the actual reasoning that produced the solution. In Wick’s system the explanation

Thermodynamic laws in isolated systems.

PubMed

Hilbert, Stefan; Hänggi, Peter; Dunkel, Jörn

2014-12-01

The recent experimental realization of exotic matter states in isolated quantum systems and the ensuing controversy about the existence of negative absolute temperatures demand a careful analysis of the conceptual foundations underlying microcanonical thermostatistics. Here we provide a detailed comparison of the most commonly considered microcanonical entropy definitions, focusing specifically on whether they satisfy or violate the zeroth, first, and second laws of thermodynamics. Our analysis shows that, for a broad class of systems that includes all standard classical Hamiltonian systems, only the Gibbs volume entropy fulfills all three laws simultaneously. To avoid ambiguities, the discussion is restricted to exact results and analytically tractable examples.

Simulations of the erythrocyte cytoskeleton at large deformation. II. Micropipette aspiration.

PubMed Central

Discher, D E; Boal, D H; Boey, S K

1998-01-01

Coarse-grained molecular models of the erythrocyte membrane's spectrin cytoskeleton are presented in Monte Carlo simulations of whole cells in micropipette aspiration. The nonlinear chain elasticity and sterics revealed in more microscopic cytoskeleton models (developed in a companion paper; Boey et al., 1998. Biophys. J. 75:1573-1583) are faithfully represented here by two- and three-body effective potentials. The number of degrees of freedom of the system are thereby reduced to a range that is computationally tractable. Three effective models for the triangulated cytoskeleton are developed: two models in which the cytoskeleton is stress-free and does or does not have internal attractive interactions, and a third model in which the cytoskeleton is prestressed in situ. These are employed in direct, finite-temperature simulations of erythrocyte deformation in a micropipette. All three models show reasonable agreement with aspiration measurements made on flaccid human erythrocytes, but the prestressed model alone yields optimal agreement with fluorescence imaging experiments. Ensemble-averaging of nonaxisymmetrical, deformed structures exhibiting anisotropic strain are thus shown to provide an answer to the basic question of how a triangulated mesh such as that of the red cell cytoskeleton deforms in experiment. PMID:9726959

Simulations of the erythrocyte cytoskeleton at large deformation. II. Micropipette aspiration.

PubMed

Discher, D E; Boal, D H; Boey, S K

1998-09-01

Coarse-grained molecular models of the erythrocyte membrane's spectrin cytoskeleton are presented in Monte Carlo simulations of whole cells in micropipette aspiration. The nonlinear chain elasticity and sterics revealed in more microscopic cytoskeleton models (developed in a companion paper; Boey et al., 1998. Biophys. J. 75:1573-1583) are faithfully represented here by two- and three-body effective potentials. The number of degrees of freedom of the system are thereby reduced to a range that is computationally tractable. Three effective models for the triangulated cytoskeleton are developed: two models in which the cytoskeleton is stress-free and does or does not have internal attractive interactions, and a third model in which the cytoskeleton is prestressed in situ. These are employed in direct, finite-temperature simulations of erythrocyte deformation in a micropipette. All three models show reasonable agreement with aspiration measurements made on flaccid human erythrocytes, but the prestressed model alone yields optimal agreement with fluorescence imaging experiments. Ensemble-averaging of nonaxisymmetrical, deformed structures exhibiting anisotropic strain are thus shown to provide an answer to the basic question of how a triangulated mesh such as that of the red cell cytoskeleton deforms in experiment.

Robust planning of dynamic wireless charging infrastructure for battery electric buses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Zhaocai; Song, Ziqi

Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses formore » a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.« less

Robust planning of dynamic wireless charging infrastructure for battery electric buses

DOE PAGES

Liu, Zhaocai; Song, Ziqi

2017-10-01

Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses formore » a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.« less

Well-posedness, linear perturbations, and mass conservation for the axisymmetric Einstein equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dain, Sergio; Ortiz, Omar E.; Facultad de Matematica, Astronomia y Fisica, FaMAF, Universidad Nacional de Cordoba, Instituto de Fisica Enrique Gaviola, IFEG, CONICET, Ciudad Universitaria

2010-02-15

For axially symmetric solutions of Einstein equations there exists a gauge which has the remarkable property that the total mass can be written as a conserved, positive definite, integral on the spacelike slices. The mass integral provides a nonlinear control of the variables along the whole evolution. In this gauge, Einstein equations reduce to a coupled hyperbolic-elliptic system which is formally singular at the axis. As a first step in analyzing this system of equations we study linear perturbations on a flat background. We prove that the linear equations reduce to a very simple system of equations which provide, thoughmore » the mass formula, useful insight into the structure of the full system. However, the singular behavior of the coefficients at the axis makes the study of this linear system difficult from the analytical point of view. In order to understand the behavior of the solutions, we study the numerical evolution of them. We provide strong numerical evidence that the system is well-posed and that its solutions have the expected behavior. Finally, this linear system allows us to formulate a model problem which is physically interesting in itself, since it is connected with the linear stability of black hole solutions in axial symmetry. This model can contribute significantly to solve the nonlinear problem and at the same time it appears to be tractable.« less

Programming strategy for efficient modeling of dynamics in a population of heterogeneous cells.

PubMed

Hald, Bjørn Olav; Garkier Hendriksen, Morten; Sørensen, Preben Graae

2013-05-15

Heterogeneity is a ubiquitous property of biological systems. Even in a genetically identical population of a single cell type, cell-to-cell differences are observed. Although the functional behavior of a given population is generally robust, the consequences of heterogeneity are fairly unpredictable. In heterogeneous populations, synchronization of events becomes a cardinal problem-particularly for phase coherence in oscillating systems. The present article presents a novel strategy for construction of large-scale simulation programs of heterogeneous biological entities. The strategy is designed to be tractable, to handle heterogeneity and to handle computational cost issues simultaneously, primarily by writing a generator of the 'model to be simulated'. We apply the strategy to model glycolytic oscillations among thousands of yeast cells coupled through the extracellular medium. The usefulness is illustrated through (i) benchmarking, showing an almost linear relationship between model size and run time, and (ii) analysis of the resulting simulations, showing that contrary to the experimental situation, synchronous oscillations are surprisingly hard to achieve, underpinning the need for tools to study heterogeneity. Thus, we present an efficient strategy to model the biological heterogeneity, neglected by ordinary mean-field models. This tool is well posed to facilitate the elucidation of the physiologically vital problem of synchronization. The complete python code is available as Supplementary Information. bjornhald@gmail.com or pgs@kiku.dk Supplementary data are available at Bioinformatics online.

High-Content Microfluidic Screening Platform Used To Identify σ2R/Tmem97 Binding Ligands that Reduce Age-Dependent Neurodegeneration in C. elegans SC_APP Model.

PubMed

Mondal, Sudip; Hegarty, Evan; Sahn, James J; Scott, Luisa L; Gökçe, Sertan Kutal; Martin, Chris; Ghorashian, Navid; Satarasinghe, Praveen Navoda; Iyer, Sangeetha; Sae-Lee, Wisath; Hodges, Timothy R; Pierce, Jonathan T; Martin, Stephen F; Ben-Yakar, Adela

2018-05-16

The nematode Caenorhabditis elegans, with tractable genetics and a well-defined nervous system, provides a unique whole-animal model system to identify novel drug targets and therapies for neurodegenerative diseases. Large-scale drug or target screens in models that recapitulate the subtle age- and cell-specific aspects of neurodegenerative diseases are limited by a technological requirement for high-throughput analysis of neuronal morphology. Recently, we developed a single-copy model of amyloid precursor protein (SC_APP) induced neurodegeneration that exhibits progressive degeneration of select cholinergic neurons. Our previous work with this model suggests that small molecule ligands of the sigma 2 receptor (σ2R), which was recently cloned and identified as transmembrane protein 97 (TMEM97), are neuroprotective. To determine structure-activity relationships for unexplored chemical space in our σ2R/Tmem97 ligand collection, we developed an in vivo high-content screening (HCS) assay to identify potential drug leads. The HCS assay uses our recently developed large-scale microfluidic immobilization chip and automated imaging platform. We discovered norbenzomorphans that reduced neurodegeneration in our C. elegans model, including two compounds that demonstrated significant neuroprotective activity at multiple doses. These findings provide further evidence that σ2R/Tmem97-binding norbenzomorphans may represent a new drug class for treating neurodegenerative diseases.

Macroscopic modeling and simulations of supercoiled DNA with bound proteins

NASA Astrophysics Data System (ADS)

Huang, Jing; Schlick, Tamar

2002-11-01

General methods are presented for modeling and simulating DNA molecules with bound proteins on the macromolecular level. These new approaches are motivated by the need for accurate and affordable methods to simulate slow processes (on the millisecond time scale) in DNA/protein systems, such as the large-scale motions involved in the Hin-mediated inversion process. Our approaches, based on the wormlike chain model of long DNA molecules, introduce inhomogeneous potentials for DNA/protein complexes based on available atomic-level structures. Electrostatically, treat those DNA/protein complexes as sets of effective charges, optimized by our discrete surface charge optimization package, in which the charges are distributed on an excluded-volume surface that represents the macromolecular complex. We also introduce directional bending potentials as well as non-identical bead hydrodynamics algorithm to further mimic the inhomogeneous effects caused by protein binding. These models thus account for basic elements of protein binding effects on DNA local structure but remain computational tractable. To validate these models and methods, we reproduce various properties measured by both Monte Carlo methods and experiments. We then apply the developed models to study the Hin-mediated inversion system in long DNA. By simulating supercoiled, circular DNA with or without bound proteins, we observe significant effects of protein binding on global conformations and long-time dynamics of the DNA on the kilo basepair length.

Sensitivity based coupling strengths in complex engineering systems

NASA Technical Reports Server (NTRS)

Bloebaum, C. L.; Sobieszczanski-Sobieski, J.

1993-01-01

The iterative design scheme necessary for complex engineering systems is generally time consuming and difficult to implement. Although a decomposition approach results in a more tractable problem, the inherent couplings make establishing the interdependencies of the various subsystems difficult. Another difficulty lies in identifying the most efficient order of execution for the subsystem analyses. The paper describes an approach for determining the dependencies that could be suspended during the system analysis with minimal accuracy losses, thereby reducing the system complexity. A new multidisciplinary testbed is presented, involving the interaction of structures, aerodynamics, and performance disciplines. Results are presented to demonstrate the effectiveness of the system reduction scheme.

Tractable Algorithms for Proximity Search on Large Graphs

DTIC Science & Technology

2010-07-01

development in information retrieval, 2005. 5.1 164 A. K. Chandra, P. Raghavan, W. L. Ruzzo, and R. Smolensky. The electrical resistance of a graph captures...2007] show how to use hitting times for designing provably manipulation resistant reputation systems. Harmonic func- tions have been used for...commute times with electrical net- works (Doyle and Snell [1984]). Consider an undirected graph. Now think of each edge as a resistor with conductance

Automated Monitoring and Analysis of Social Behavior in Drosophila

PubMed Central

Dankert, Heiko; Wang, Liming; Hoopfer, Eric D.; Anderson, David J.; Perona, Pietro

2009-01-01

We introduce a method based on machine vision for automatically measuring aggression and courtship in Drosophila melanogaster. The genetic and neural circuit bases of these innate social behaviors are poorly understood. High-throughput behavioral screening in this genetically tractable model organism is a potentially powerful approach, but it is currently very laborious. Our system monitors interacting pairs of flies, and computes their location, orientation and wing posture. These features are used for detecting behaviors exhibited during aggression and courtship. Among these, wing threat, lunging and tussling are specific to aggression; circling, wing extension (courtship “song”) and copulation are specific to courtship; locomotion and chasing are common to both. Ethograms may be constructed automatically from these measurements, saving considerable time and effort. This technology should enable large-scale screens for genes and neural circuits controlling courtship and aggression. PMID:19270697

Neurocomputing strategies in decomposition based structural design

NASA Technical Reports Server (NTRS)

Szewczyk, Z.; Hajela, P.

1993-01-01

The present paper explores the applicability of neurocomputing strategies in decomposition based structural optimization problems. It is shown that the modeling capability of a backpropagation neural network can be used to detect weak couplings in a system, and to effectively decompose it into smaller, more tractable, subsystems. When such partitioning of a design space is possible, parallel optimization can be performed in each subsystem, with a penalty term added to its objective function to account for constraint violations in all other subsystems. Dependencies among subsystems are represented in terms of global design variables, and a neural network is used to map the relations between these variables and all subsystem constraints. A vector quantization technique, referred to as a z-Network, can effectively be used for this purpose. The approach is illustrated with applications to minimum weight sizing of truss structures with multiple design constraints.

Flow/Soot-Formation Interactions in Nonbuoyant Laminar Diffusion Flames

NASA Technical Reports Server (NTRS)

Dai, Z.; Lin, K.-C.; Sunderland, P. B.; Xu, F.; Faeth, G. M.

2002-01-01

This is the final report of a research program considering interactions between flow and soot properties within laminar diffusion flames. Laminar diffusion flames were considered because they provide model flame systems that are far more tractable for theoretical and experimental studies than more practical turbulent diffusion flames. In particular, understanding the transport and chemical reaction processes of laminar flames is a necessary precursor to understanding these processes in practical turbulent flames and many aspects of laminar diffusion flames have direct relevance to turbulent diffusion flames through application of the widely recognized laminar flamelet concept of turbulent diffusion flames. The investigation was divided into three phases, considering the shapes of nonbuoyant round laminar jet diffusion flames in still air, the shapes of nonbuoyant round laminar jet diffusion flames in coflowing air, and the hydrodynamic suppression of soot formation in laminar diffusion flames.

Delineating parameter unidentifiabilities in complex models

NASA Astrophysics Data System (ADS)

Raman, Dhruva V.; Anderson, James; Papachristodoulou, Antonis

2017-03-01

Scientists use mathematical modeling as a tool for understanding and predicting the properties of complex physical systems. In highly parametrized models there often exist relationships between parameters over which model predictions are identical, or nearly identical. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, as well as the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast time-scale subsystems, as well as the regimes in parameter space over which such approximations are valid. We base our algorithm on a quantification of regional parametric sensitivity that we call `multiscale sloppiness'. Traditionally, the link between parametric sensitivity and the conditioning of the parameter estimation problem is made locally, through the Fisher information matrix. This is valid in the regime of infinitesimal measurement uncertainty. We demonstrate the duality between multiscale sloppiness and the geometry of confidence regions surrounding parameter estimates made where measurement uncertainty is non-negligible. Further theoretical relationships are provided linking multiscale sloppiness to the likelihood-ratio test. From this, we show that a local sensitivity analysis (as typically done) is insufficient for determining the reliability of parameter estimation, even with simple (non)linear systems. Our algorithm can provide a tractable alternative. We finally apply our methods to a large-scale, benchmark systems biology model of necrosis factor (NF)-κ B , uncovering unidentifiabilities.

Multi-sensory integration in a small brain

NASA Astrophysics Data System (ADS)

Gepner, Ruben; Wolk, Jason; Gershow, Marc

Understanding how fluctuating multi-sensory stimuli are integrated and transformed in neural circuits has proved a difficult task. To address this question, we study the sensori-motor transformations happening in the brain of the Drosophila larva, a tractable model system with about 10,000 neurons. Using genetic tools that allow us to manipulate the activity of individual brain cells through their transparent body, we observe the stochastic decisions made by freely-behaving animals as their visual and olfactory environments fluctuate independently. We then use simple linear-nonlinear models to correlate outputs with relevant features in the inputs, and adaptive filtering processes to track changes in these relevant parameters used by the larva's brain to make decisions. We show how these techniques allow us to probe how statistics of stimuli from different sensory modalities combine to affect behavior, and can potentially guide our understanding of how neural circuits are anatomically and functionally integrated. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street.

PubMed

Panaggio, Mark J; Ottino-Löffler, Bertand J; Hu, Peiguang; Abrams, Daniel M

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this "green-wave" scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street

NASA Astrophysics Data System (ADS)

Panaggio, Mark J.; Ottino-Löffler, Bertand J.; Hu, Peiguang; Abrams, Daniel M.

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this “green-wave” scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

A Genetically Engineered Mouse Model of Neuroblastoma Driven by Mutated ALK and MYCN

DTIC Science & Technology

2015-09-01

Through publications in scientific journals (see Journal publications). What do you plan to do during the next reporting period to accomplish the goals...We plan to elucidate the mechanism of action of the synergy between ALK and CDK inhibitors, validate CDK7 inhibition as a tractable therapeutic...delays and actions or plans to resolve them Nothing to Report Changes that had a significant impact on expenditures Nothing to Report Significant

A Bayesian modification to the Jelinski-Moranda software reliability growth model

NASA Technical Reports Server (NTRS)

Littlewood, B.; Sofer, A.

1983-01-01

The Jelinski-Moranda (JM) model for software reliability was examined. It is suggested that a major reason for the poor results given by this model is the poor performance of the maximum likelihood method (ML) of parameter estimation. A reparameterization and Bayesian analysis, involving a slight modelling change, are proposed. It is shown that this new Bayesian-Jelinski-Moranda model (BJM) is mathematically quite tractable, and several metrics of interest to practitioners are obtained. The BJM and JM models are compared by using several sets of real software failure data collected and in all cases the BJM model gives superior reliability predictions. A change in the assumption which underlay both models to present the debugging process more accurately is discussed.

Spike solutions in Gierer#x2013;Meinhardt model with a time dependent anomaly exponent

NASA Astrophysics Data System (ADS)

Nec, Yana

2018-01-01

Experimental evidence of complex dispersion regimes in natural systems, where the growth of the mean square displacement in time cannot be characterised by a single power, has been accruing for the past two decades. In such processes the exponent γ(t) in ⟨r2⟩ ∼ tγ(t) at times might be approximated by a piecewise constant function, or it can be a continuous function. Variable order differential equations are an emerging mathematical tool with a strong potential to model these systems. However, variable order differential equations are not tractable by the classic differential equations theory. This contribution illustrates how a classic method can be adapted to gain insight into a system of this type. Herein a variable order Gierer-Meinhardt model is posed, a generic reaction- diffusion system of a chemical origin. With a fixed order this system possesses a solution in the form of a constellation of arbitrarily situated localised pulses, when the components' diffusivity ratio is asymptotically small. The pattern was shown to exist subject to multiple step-like transitions between normal diffusion and sub-diffusion, as well as between distinct sub-diffusive regimes. The analytical approximation obtained permits qualitative analysis of the impact thereof. Numerical solution for typical cross-over scenarios revealed such features as earlier equilibration and non-monotonic excursions before attainment of equilibrium. The method is general and allows for an approximate numerical solution with any reasonably behaved γ(t).

Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reed, Sasha C.; Yang, Xiaojuan; Thornton, Peter E.

2015-06-25

Myriad field, laboratory, and modeling studies show that nutrient availability plays a fundamental role in regulating CO 2 exchange between the Earth's biosphere and atmosphere, and in determining how carbon pools and fluxes respond to climatic change. Accordingly, global models that incorporate coupled climate-carbon cycle feedbacks made a significant advance with the introduction of a prognostic nitrogen cycle. Here we propose that incorporating phosphorus cycling represents an important next step in coupled climate-carbon cycling model development, particularly for lowland tropical forests where phosphorus availability is often presumed to limit primary production. We highlight challenges to including phosphorus in modeling effortsmore » and provide suggestions for how to move forward.« less

Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor

USGS Publications Warehouse

Reed, Sasha C.; Yang, Xiaojuan; Thornton, Peter E.

2015-01-01

Myriad field, laboratory, and modeling studies show that nutrient availability plays a fundamental role in regulating CO2 exchange between the Earth's biosphere and atmosphere, and in determining how carbon pools and fluxes respond to climatic change. Accordingly, global models that incorporate coupled climate–carbon cycle feedbacks made a significant advance with the introduction of a prognostic nitrogen cycle. Here we propose that incorporating phosphorus cycling represents an important next step in coupled climate–carbon cycling model development, particularly for lowland tropical forests where phosphorus availability is often presumed to limit primary production. We highlight challenges to including phosphorus in modeling efforts and provide suggestions for how to move forward.

Spectral simplicity of apparent complexity. II. Exact complexities and complexity spectra

NASA Astrophysics Data System (ADS)

Riechers, Paul M.; Crutchfield, James P.

2018-03-01

The meromorphic functional calculus developed in Part I overcomes the nondiagonalizability of linear operators that arises often in the temporal evolution of complex systems and is generic to the metadynamics of predicting their behavior. Using the resulting spectral decomposition, we derive closed-form expressions for correlation functions, finite-length Shannon entropy-rate approximates, asymptotic entropy rate, excess entropy, transient information, transient and asymptotic state uncertainties, and synchronization information of stochastic processes generated by finite-state hidden Markov models. This introduces analytical tractability to investigating information processing in discrete-event stochastic processes, symbolic dynamics, and chaotic dynamical systems. Comparisons reveal mathematical similarities between complexity measures originally thought to capture distinct informational and computational properties. We also introduce a new kind of spectral analysis via coronal spectrograms and the frequency-dependent spectra of past-future mutual information. We analyze a number of examples to illustrate the methods, emphasizing processes with multivariate dependencies beyond pairwise correlation. This includes spectral decomposition calculations for one representative example in full detail.

Immune response and immunopathology during toxoplasmosis1

PubMed Central

Dupont, Christopher D.; Christian, David A.; Hunter, Christopher A.

2012-01-01

Toxoplasma gondii is a protozoan parasite of medical and veterinary significance that is able to infect any warm-blooded vertebrate host. In addition to its importance to public health, several inherent features of the biology of T. gondii have made it an important model organism to study host-pathogen interactions. One factor is the genetic tractability of the parasite, which allows studies on the microbial factors that affect virulence and allows the development of tools that facilitate immune studies. Additionally, mice are natural hosts for T. gondii, and the availability of numerous reagents to study the murine immune system makes this an ideal experimental system to understand the functions of cytokines and effector mechanisms involved in immunity to intracellular microorganisms. In this article, we will review current knowledge of the innate and adaptive immune responses required for resistance to toxoplasmosis, the events that lead to the development of immunopathology, and the natural regulatory mechanisms that limit excessive inflammation during this infection. PMID:22955326

Midbrain-like Organoids from Human Pluripotent Stem Cells Contain Functional Dopaminergic and Neuromelanin-Producing Neurons.

PubMed

Jo, Junghyun; Xiao, Yixin; Sun, Alfred Xuyang; Cukuroglu, Engin; Tran, Hoang-Dai; Göke, Jonathan; Tan, Zi Ying; Saw, Tzuen Yih; Tan, Cheng-Peow; Lokman, Hidayat; Lee, Younghwan; Kim, Donghoon; Ko, Han Seok; Kim, Seong-Oh; Park, Jae Hyeon; Cho, Nam-Joon; Hyde, Thomas M; Kleinman, Joel E; Shin, Joo Heon; Weinberger, Daniel R; Tan, Eng King; Je, Hyunsoo Shawn; Ng, Huck-Hui

2016-08-04

Recent advances in 3D culture systems have led to the generation of brain organoids that resemble different human brain regions; however, a 3D organoid model of the midbrain containing functional midbrain dopaminergic (mDA) neurons has not been reported. We developed a method to differentiate human pluripotent stem cells into a large multicellular organoid-like structure that contains distinct layers of neuronal cells expressing characteristic markers of human midbrain. Importantly, we detected electrically active and functionally mature mDA neurons and dopamine production in our 3D midbrain-like organoids (MLOs). In contrast to human mDA neurons generated using 2D methods or MLOs generated from mouse embryonic stem cells, our human MLOs produced neuromelanin-like granules that were structurally similar to those isolated from human substantia nigra tissues. Thus our MLOs bearing features of the human midbrain may provide a tractable in vitro system to study the human midbrain and its related diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

A Comparison of Solver Performance for Complex Gastric Electrophysiology Models

PubMed Central

Sathar, Shameer; Cheng, Leo K.; Trew, Mark L.

2016-01-01

Computational techniques for solving systems of equations arising in gastric electrophysiology have not been studied for efficient solution process. We present a computationally challenging problem of simulating gastric electrophysiology in anatomically realistic stomach geometries with multiple intracellular and extracellular domains. The multiscale nature of the problem and mesh resolution required to capture geometric and functional features necessitates efficient solution methods if the problem is to be tractable. In this study, we investigated and compared several parallel preconditioners for the linear systems arising from tetrahedral discretisation of electrically isotropic and anisotropic problems, with and without stimuli. The results showed that the isotropic problem was computationally less challenging than the anisotropic problem and that the application of extracellular stimuli increased workload considerably. Preconditioning based on block Jacobi and algebraic multigrid solvers were found to have the best overall solution times and least iteration counts, respectively. The algebraic multigrid preconditioner would be expected to perform better on large problems. PMID:26736543

Linking the development and functioning of a carnivorous pitcher plant's microbial digestive community.

PubMed

Armitage, David W

2017-11-01

Ecosystem development theory predicts that successional turnover in community composition can influence ecosystem functioning. However, tests of this theory in natural systems are made difficult by a lack of replicable and tractable model systems. Using the microbial digestive associates of a carnivorous pitcher plant, I tested hypotheses linking host age-driven microbial community development to host functioning. Monitoring the yearlong development of independent microbial digestive communities in two pitcher plant populations revealed a number of trends in community succession matching theoretical predictions. These included mid-successional peaks in bacterial diversity and metabolic substrate use, predictable and parallel successional trajectories among microbial communities, and convergence giving way to divergence in community composition and carbon substrate use. Bacterial composition, biomass, and diversity positively influenced the rate of prey decomposition, which was in turn positively associated with a host leaf's nitrogen uptake efficiency. Overall digestive performance was greatest during late summer. These results highlight links between community succession and ecosystem functioning and extend succession theory to host-associated microbial communities.

An opioid-like system regulating feeding behavior in C. elegans

PubMed Central

Cheong, Mi Cheong; Artyukhin, Alexander B; You, Young-Jai; Avery, Leon

2015-01-01

Neuropeptides are essential for the regulation of appetite. Here we show that neuropeptides could regulate feeding in mutants that lack neurotransmission from the motor neurons that stimulate feeding muscles. We identified nlp-24 by an RNAi screen of 115 neuropeptide genes, testing whether they affected growth. NLP-24 peptides have a conserved YGGXX sequence, similar to mammalian opioid neuropeptides. In addition, morphine and naloxone respectively stimulated and inhibited feeding in starved worms, but not in worms lacking NPR-17, which encodes a protein with sequence similarity to opioid receptors. Opioid agonists activated heterologously expressed NPR-17, as did at least one NLP-24 peptide. Worms lacking the ASI neurons, which express npr-17, did not response to naloxone. Thus, we suggest that Caenorhabditis elegans has an endogenous opioid system that acts through NPR-17, and that opioids regulate feeding via ASI neurons. Together, these results suggest C. elegans may be the first genetically tractable invertebrate opioid model. DOI: http://dx.doi.org/10.7554/eLife.06683.001 PMID:25898004

Neisseria gonorrhoeae co-infection exacerbates vaginal HIV shedding without affecting systemic viral loads in human CD34+ engrafted mice.

PubMed

Xu, Stacey X; Leontyev, Danila; Kaul, Rupert; Gray-Owen, Scott D

2018-01-01

HIV synergy with sexually transmitted co-infections is well-documented in the clinic. Co-infection with Neisseria gonorrhoeae in particular, increases genital HIV shedding and mucosal transmission. However, no animal model of co-infection currently exists to directly explore this relationship or to bridge the gap in understanding between clinical and in vitro studies of this interaction. This study aims to test the feasibility of using a humanized mouse model to overcome this barrier. Combining recent in vivo modelling advancements in both HIV and gonococcal research, we developed a co-infection model by engrafting immunodeficient NSG mice with human CD34+ hematopoietic stem cells to generate humanized mice that permit both systemic HIV infection and genital N. gonorrhoeae infection. Systemic plasma and vaginal lavage titres of HIV were measured in order to assess the impact of gonococcal challenge on viral plasma titres and genital shedding. Engrafted mice showed human CD45+ leukocyte repopulation in blood and mucosal tissues. Systemic HIV challenge resulted in 104-105 copies/mL of viral RNA in blood by week 4 post-infection, as well as vaginal shedding of virus. Subsequent gonococcal challenge resulted in unchanged plasma HIV levels but higher viral shedding in the genital tract, which reflects published clinical observations. Thus, human CD34+ stem cell-transplanted NSG mice represent an experimentally tractable animal model in which to study HIV shedding during gonococcal co-infection, allowing dissection of molecular and immunological interactions between these pathogens, and providing a platform to assess future therapeutics aimed at reducing HIV transmission.

Ex vivo generation of a functional and regenerative wound epithelium from axolotl (Ambystoma mexicanum) skin.

PubMed

Ferris, Donald R; Satoh, Akira; Mandefro, Berhan; Cummings, Gillian M; Gardiner, David M; Rugg, Elizabeth L

2010-10-01

Urodele amphibians (salamanders) are unique among adult vertebrates in their ability to regenerate structurally complete and fully functional limbs. Regeneration is a stepwise process that requires interactions between keratinocytes, nerves and fibroblasts. The formation of a wound epithelium covering the amputation site is an early and necessary event in the process but the molecular mechanisms that underlie the role of the wound epithelium in regeneration remain unclear. We have developed an ex vivo model that recapitulates many features of in vivo wound healing. The model comprises a circular explant of axolotl (Ambystoma mexicanum) limb skin with a central circular, full thickness wound. Re-epithelialization of the wound area is rapid (typically <11 h) and is dependent on metalloproteinase activity. The ex vivo wound epithelium is viable, responds to neuronal signals and is able to participate in ectopic blastema formation and limb regeneration. This ex vivo model provides a reproducible and tractable system in which to study the cellular and molecular events that underlie wound healing and regeneration. © 2010 The Authors. Journal compilation © 2010 Japanese Society of Developmental Biologists.

Microscopic Description of Thermodynamics of Lipid Membrane at Liquid-Gel Phase Transition

NASA Astrophysics Data System (ADS)

Kheyfets, B.; Galimzyanov, T.; Mukhin, S.

2018-05-01

A microscopic model of the lipid membrane is constructed that provides analytically tractable description of the physical mechanism of the first order liquid-gel phase transition. We demonstrate that liquid-gel phase transition is cooperative effect of the three major interactions: inter-lipid van der Waals attraction, steric repulsion and hydrophobic tension. The model explicitly shows that temperature-dependent inter-lipid steric repulsion switches the system from liquid to gel phase when the temperature decreases. The switching manifests itself in the increase of lateral compressibility of the lipids as the temperature decreases, making phase with smaller area more preferable below the transition temperature. The model gives qualitatively correct picture of abrupt change at transition temperature of the area per lipid, membrane thickness and volume per hydrocarbon group in the lipid chains. The calculated dependence of phase transition temperature on lipid chain length is in quantitative agreement with experimental data. Steric repulsion between the lipid molecules is shown to be the only driver of the phase transition, as van der Waals attraction and hydrophobic tension are weakly temperature dependent.

The processive kinetics of gene conversion in bacteria

PubMed Central

Paulsson, Johan; El Karoui, Meriem; Lindell, Monica

2017-01-01

Summary Gene conversion, non‐reciprocal transfer from one homologous sequence to another, is a major force in evolutionary dynamics, promoting co‐evolution in gene families and maintaining similarities between repeated genes. However, the properties of the transfer – where it initiates, how far it proceeds and how the resulting conversion tracts are affected by mismatch repair – are not well understood. Here, we use the duplicate tuf genes in Salmonella as a quantitatively tractable model system for gene conversion. We selected for conversion in multiple different positions of tuf, and examined the resulting distributions of conversion tracts in mismatch repair‐deficient and mismatch repair‐proficient strains. A simple stochastic model accounting for the essential steps of conversion showed excellent agreement with the data for all selection points using the same value of the conversion processivity, which is the only kinetic parameter of the model. The analysis suggests that gene conversion effectively initiates uniformly at any position within a tuf gene, and proceeds with an effectively uniform conversion processivity in either direction limited by the bounds of the gene. PMID:28256783

Quantum simulation of transverse Ising models with Rydberg atoms

NASA Astrophysics Data System (ADS)

Schauss, Peter

2018-04-01

Quantum Ising models are canonical models for the study of quantum phase transitions (Sachdev 1999 Quantum Phase Transitions (Cambridge: Cambridge University Press)) and are the underlying concept for many analogue quantum computing and quantum annealing ideas (Tanaka et al Quantum Spin Glasses, Annealing and Computation (Cambridge: Cambridge University Press)). Here we focus on the implementation of finite-range interacting Ising spin models, which are barely tractable numerically. Recent experiments with cold atoms have reached the interaction-dominated regime in quantum Ising magnets via optical coupling of trapped neutral atoms to Rydberg states. This approach allows for the tunability of all relevant terms in an Ising spin Hamiltonian with 1/{r}6 interactions in transverse and longitudinal fields. This review summarizes the recent progress of these implementations in Rydberg lattices with site-resolved detection. Strong correlations in quantum Ising models have been observed in several experiments, starting from a single excitation in the superatom regime up to the point of crystallization. The rapid progress in this field makes spin systems based on Rydberg atoms a promising platform for quantum simulation because of the unmatched flexibility and strength of interactions combined with high control and good isolation from the environment.

Laser-SPS systems analysis and environmental impact assessment

NASA Technical Reports Server (NTRS)

Beverly, R. E., III

1980-01-01

The systems feasibility and environmental impact of replacing the microwave transmitters on the Satellite Power System with laser transmitters are examined. The lasers suggested are two molecular-gas electric-discharge lasers (EDL's), namely the CO and CO2 lasers. Calculations are made on system efficiency, atmospheric transmission efficiency, and laser beam spreading. It is found that the present satellite concept using lasers is far too inefficient and massive to be economically viable. However, the safety issues associated with laser power transmission appear tractable, and no effects could be identified which present a real danger of serious injury to the environment, although certain phenomena deserve closer scrutiny.

Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions.

PubMed

Ryan, Nicole A; Johnson, Jeremiah X; Keoleian, Gregory A

2016-09-06

Due to the complexity of power systems, tracking emissions attributable to a specific electrical load is a daunting challenge but essential for many environmental impact studies. Currently, no consensus exists on appropriate methods for quantifying emissions from particular electricity loads. This paper reviews a wide range of the existing methods, detailing their functionality, tractability, and appropriate use. We identified and reviewed 32 methods and models and classified them into two distinct categories: empirical data and relationship models and power system optimization models. To illustrate the impact of method selection, we calculate the CO2 combustion emissions factors associated with electric-vehicle charging using 10 methods at nine charging station locations around the United States. Across the methods, we found an up to 68% difference from the mean CO2 emissions factor for a given charging site among both marginal and average emissions factors and up to a 63% difference from the average across average emissions factors. Our results underscore the importance of method selection and the need for a consensus on approaches appropriate for particular loads and research questions being addressed in order to achieve results that are more consistent across studies and allow for soundly supported policy decisions. The paper addresses this issue by offering a set of recommendations for determining an appropriate model type on the basis of the load characteristics and study objectives.

In defense of compilation: A response to Davis' form and content in model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard

1990-01-01

In a recent paper entitled 'Form and Content in Model Based Reasoning', Randy Davis argues that model based reasoning research aimed at compiling task specific rules from underlying device models is mislabeled, misguided, and diversionary. Some of Davis' claims are examined and his basic conclusions are challenged about the value of compilation research to the model based reasoning community. In particular, Davis' claim is refuted that model based reasoning is exempt from the efficiency benefits provided by knowledge compilation techniques. In addition, several misconceptions are clarified about the role of representational form in compilation. It is concluded that techniques have the potential to make a substantial contribution to solving tractability problems in model based reasoning.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty.

PubMed

Mdluli, Thembi; Buzzard, Gregery T; Rundell, Ann E

2015-09-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm's scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty

PubMed Central

Mdluli, Thembi; Buzzard, Gregery T.; Rundell, Ann E.

2015-01-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm’s scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements. PMID:26379275

Universal distribution of component frequencies in biological and technological systems

PubMed Central

Pang, Tin Yau; Maslov, Sergei

2013-01-01

Bacterial genomes and large-scale computer software projects both consist of a large number of components (genes or software packages) connected via a network of mutual dependencies. Components can be easily added or removed from individual systems, and their use frequencies vary over many orders of magnitude. We study this frequency distribution in genomes of ∼500 bacterial species and in over 2 million Linux computers and find that in both cases it is described by the same scale-free power-law distribution with an additional peak near the tail of the distribution corresponding to nearly universal components. We argue that the existence of a power law distribution of frequencies of components is a general property of any modular system with a multilayered dependency network. We demonstrate that the frequency of a component is positively correlated with its dependency degree given by the total number of upstream components whose operation directly or indirectly depends on the selected component. The observed frequency/dependency degree distributions are reproduced in a simple mathematically tractable model introduced and analyzed in this study. PMID:23530195

Ergodic properties of spiking neuronal networks with delayed interactions

NASA Astrophysics Data System (ADS)

Palmigiano, Agostina; Wolf, Fred

The dynamical stability of neuronal networks, and the possibility of chaotic dynamics in the brain pose profound questions to the mechanisms underlying perception. Here we advance on the tractability of large neuronal networks of exactly solvable neuronal models with delayed pulse-coupled interactions. Pulse coupled delayed systems with an infinite dimensional phase space can be studied in equivalent systems of fixed and finite degrees of freedom by introducing a delayer variable for each neuron. A Jacobian of the equivalent system can be analytically obtained, and numerically evaluated. We find that depending on the action potential onset rapidness and the level of heterogeneities, the asynchronous irregular regime characteristic of balanced state networks loses stability with increasing delays to either a slow synchronous irregular or a fast synchronous irregular state. In networks of neurons with slow action potential onset, the transition to collective oscillations leads to an increase of the exponential rate of divergence of nearby trajectories and of the entropy production rate of the chaotic dynamics. The attractor dimension, instead of increasing linearly with increasing delay as reported in many other studies, decreases until eventually the network reaches full synchrony

Sinking bubbles in stout beers

NASA Astrophysics Data System (ADS)

Lee, W. T.; Kaar, S.; O'Brien, S. B. G.

2018-04-01

A surprising phenomenon witnessed by many is the sinking bubbles seen in a settling pint of stout beer. Bubbles are less dense than the surrounding fluid so how does this happen? Previous work has shown that the explanation lies in a circulation of fluid promoted by the tilted sides of the glass. However, this work has relied heavily on computational fluid dynamics (CFD) simulations. Here, we show that the phenomenon of sinking bubbles can be predicted using a simple analytic model. To make the model analytically tractable, we work in the limit of small bubbles and consider a simplified geometry. The model confirms both the existence of sinking bubbles and the previously proposed mechanism.

Empirical analysis and modeling of manual turnpike tollbooths in China

NASA Astrophysics Data System (ADS)

Zhang, Hao

2017-03-01

To deal with low-level of service satisfaction at tollbooths of many turnpikes in China, we conduct an empirical study and use a queueing model to investigate performance measures. In this paper, we collect archived data from six tollbooths of a turnpike in China. Empirical analysis on vehicle's time-dependent arrival process and collector's time-dependent service time is conducted. It shows that the vehicle arrival process follows a non-homogeneous Poisson process while the collector service time follows a log-normal distribution. Further, we model the process of collecting tolls at tollbooths with MAP / PH / 1 / FCFS queue for mathematical tractability and present some numerical examples.

Aging Studies in Drosophila melanogaster

PubMed Central

Sun, Yaning; Yolitz, Jason; Wang, Cecilia; Spangler, Edward; Zhan, Ming; Zou, Sige

2015-01-01

Summary Drosophila is a genetically tractable system ideal for investigating the mechanisms of aging and developing interventions for promoting healthy aging. Here we describe methods commonly used in Drosophila aging research. These include basic approaches for preparation of diets and measurements of lifespan, food intake and reproductive output. We also describe some commonly used assays to measure changes in physiological and behavioral functions of Drosophila in aging, such as stress resistance and locomotor activity. PMID:23929099

Feeding behavior of Aplysia: a model system for comparing cellular mechanisms of classical and operant conditioning.

PubMed

Baxter, Douglas A; Byrne, John H

2006-01-01

Feeding behavior of Aplysia provides an excellent model system for analyzing and comparing mechanisms underlying appetitive classical conditioning and reward operant conditioning. Behavioral protocols have been developed for both forms of associative learning, both of which increase the occurrence of biting following training. Because the neural circuitry that mediates the behavior is well characterized and amenable to detailed cellular analyses, substantial progress has been made toward a comparative analysis of the cellular mechanisms underlying these two forms of associative learning. Both forms of associative learning use the same reinforcement pathway (the esophageal nerve, En) and the same reinforcement transmitter (dopamine, DA). In addition, at least one cellular locus of plasticity (cell B51) is modified by both forms of associative learning. However, the two forms of associative learning have opposite effects on B51. Classical conditioning decreases the excitability of B51, whereas operant conditioning increases the excitability of B51. Thus, the approach of using two forms of associative learning to modify a single behavior, which is mediated by an analytically tractable neural circuit, is revealing similarities and differences in the mechanisms that underlie classical and operant conditioning.

Task-based data-acquisition optimization for sparse image reconstruction systems

NASA Astrophysics Data System (ADS)

Chen, Yujia; Lou, Yang; Kupinski, Matthew A.; Anastasio, Mark A.

2017-03-01

Conventional wisdom dictates that imaging hardware should be optimized by use of an ideal observer (IO) that exploits full statistical knowledge of the class of objects to be imaged, without consideration of the reconstruction method to be employed. However, accurate and tractable models of the complete object statistics are often difficult to determine in practice. Moreover, in imaging systems that employ compressive sensing concepts, imaging hardware and (sparse) image reconstruction are innately coupled technologies. We have previously proposed a sparsity-driven ideal observer (SDIO) that can be employed to optimize hardware by use of a stochastic object model that describes object sparsity. The SDIO and sparse reconstruction method can therefore be "matched" in the sense that they both utilize the same statistical information regarding the class of objects to be imaged. To efficiently compute SDIO performance, the posterior distribution is estimated by use of computational tools developed recently for variational Bayesian inference. Subsequently, the SDIO test statistic can be computed semi-analytically. The advantages of employing the SDIO instead of a Hotelling observer are systematically demonstrated in case studies in which magnetic resonance imaging (MRI) data acquisition schemes are optimized for signal detection tasks.

Macrophages and cellular immunity in Drosophila melanogaster.

PubMed

Gold, Katrina S; Brückner, Katja

2015-12-01

The invertebrate Drosophila melanogaster has been a powerful model for understanding blood cell development and immunity. Drosophila is a holometabolous insect, which transitions through a series of life stages from embryo, larva and pupa to adulthood. In spite of this, remarkable parallels exist between Drosophila and vertebrate macrophages, both in terms of development and function. More than 90% of Drosophila blood cells (hemocytes) are macrophages (plasmatocytes), making this highly tractable genetic system attractive for studying a variety of questions in macrophage biology. In vertebrates, recent findings revealed that macrophages have two independent origins: self-renewing macrophages, which reside and proliferate in local microenvironments in a variety of tissues, and macrophages of the monocyte lineage, which derive from hematopoietic stem or progenitor cells. Like vertebrates, Drosophila possesses two macrophage lineages with a conserved dual ontogeny. These parallels allow us to take advantage of the Drosophila model when investigating macrophage lineage specification, maintenance and amplification, and the induction of macrophages and their progenitors by local microenvironments and systemic cues. Beyond macrophage development, Drosophila further serves as a paradigm for understanding the mechanisms underlying macrophage function and cellular immunity in infection, tissue homeostasis and cancer, throughout development and adult life. Copyright © 2016. Published by Elsevier Ltd.

Macrophages and cellular immunity in Drosophila melanogaster

PubMed Central

Gold, Katrina S.; Brückner, Katja

2016-01-01

The invertebrate Drosophila melanogaster has been a powerful model for understanding blood cell development and immunity. Drosophila is a holometabolous insect, which transitions through a series of life stages from embryo, larva and pupa to adulthood. In spite of this, remarkable parallels exist between Drosophila and vertebrate macrophages, both in terms of development and function. More than 90% of Drosophila blood cells (hemocytes) are macrophages (plasmatocytes), making this highly tractable genetic system attractive for studying a variety of questions in macrophage biology. In vertebrates, recent findings revealed that macrophages have two independent origins: self-renewing macrophages, which reside and proliferate in local microenvironments in a variety of tissues, and macrophages of the monocyte lineage, which derive from hematopoietic stem or progenitor cells. Like vertebrates, Drosophila possesses two macrophage lineages with a conserved dual ontogeny. These parallels allow us to take advantage of the Drosophila model when investigating macrophage lineage specification, maintenance and amplification, and the induction of macrophages and their progenitors by local microenvironments and systemic cues. Beyond macrophage development, Drosophila further serves as a paradigm for understanding the mechanisms underlying macrophage function and cellular immunity in infection, tissue homeostasis and cancer, throughout development and adult life. PMID:27117654

Using Genetic Buffering Relationships Identified in Fission Yeast to Elucidate the Molecular Pathology of Tuberous Sclerosis

DTIC Science & Technology

2015-07-01

AWARD NUMBER: W81XWH-14-1-0169 TITLE: Using Genetic Buffering Relationships Identified in Fission Yeast to Elucidate the Molecular Pathology of...DATES COVERED 1 July 2014 - 30 June 2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Using Genetic Buffering Relationships Identified in Fission Yeast ...SUPPLEMENTARY NOTES 14. ABSTRACT Using the genetically tractable fission yeast as a model, we sought to exploit recent advances in gene interaction

Using Machine Learning in Adversarial Environments.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warren Leon Davis

Intrusion/anomaly detection systems are among the first lines of cyber defense. Commonly, they either use signatures or machine learning (ML) to identify threats, but fail to account for sophisticated attackers trying to circumvent them. We propose to embed machine learning within a game theoretic framework that performs adversarial modeling, develops methods for optimizing operational response based on ML, and integrates the resulting optimization codebase into the existing ML infrastructure developed by the Hybrid LDRD. Our approach addresses three key shortcomings of ML in adversarial settings: 1) resulting classifiers are typically deterministic and, therefore, easy to reverse engineer; 2) ML approachesmore » only address the prediction problem, but do not prescribe how one should operationalize predictions, nor account for operational costs and constraints; and 3) ML approaches do not model attackers’ response and can be circumvented by sophisticated adversaries. The principal novelty of our approach is to construct an optimization framework that blends ML, operational considerations, and a model predicting attackers reaction, with the goal of computing optimal moving target defense. One important challenge is to construct a realistic model of an adversary that is tractable, yet realistic. We aim to advance the science of attacker modeling by considering game-theoretic methods, and by engaging experimental subjects with red teaming experience in trying to actively circumvent an intrusion detection system, and learning a predictive model of such circumvention activities. In addition, we will generate metrics to test that a particular model of an adversary is consistent with available data.« less

Efforts to make and apply humanized yeast

PubMed Central

Laurent, Jon M.; Young, Jonathan H.; Kachroo, Aashiq H.

2016-01-01

Despite a billion years of divergent evolution, the baker’s yeast Saccharomyces cerevisiae has long proven to be an invaluable model organism for studying human biology. Given its tractability and ease of genetic manipulation, along with extensive genetic conservation with humans, it is perhaps no surprise that researchers have been able to expand its utility by expressing human proteins in yeast, or by humanizing specific yeast amino acids, proteins or even entire pathways. These methods are increasingly being scaled in throughput, further enabling the detailed investigation of human biology and disease-specific variations of human genes in a simplified model organism. PMID:26462863

Theory of multicolor lattice gas - A cellular automaton Poisson solver

NASA Technical Reports Server (NTRS)

Chen, H.; Matthaeus, W. H.; Klein, L. W.

1990-01-01

The present class of models for cellular automata involving a quiescent hydrodynamic lattice gas with multiple-valued passive labels termed 'colors', the lattice collisions change individual particle colors while preserving net color. The rigorous proofs of the multicolor lattice gases' essential features are rendered more tractable by an equivalent subparticle representation in which the color is represented by underlying two-state 'spins'. Schemes for the introduction of Dirichlet and Neumann boundary conditions are described, and two illustrative numerical test cases are used to verify the theory. The lattice gas model is equivalent to a Poisson equation solution.

Analysis of the compressibility of a finite symmetrical nucleus in terms of a simple, analytically tractable model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maheswari, V.S.U.; Ramamurthy, V.S.; Satpathy, L.

1992-12-01

The liquid-drop model type expansion of the finite nuclear compressibility coefficients {ital K}{sub {ital A}} is studied in an energy density formalism, using a leptodermous expansion of the energies. It is found that the effective curvature compressibility coefficient {ital K}{sub {ital c}} is always negative for Skyrme type forces. It is also shown that the unexpectedly large value of about {minus}800 MeV of the surface compressibility coefficient {ital K}{sub {ital s}} found by Sharma {ital et} {ital al}. is an artifact of their analysis procedure.

Parametric Study of a YAV-8B Harrier in Ground Effect Using Time-Dependent Navier-Stokes Computations

NASA Technical Reports Server (NTRS)

Shishir, Pandya; Chaderjian, Neal; Ahmad, Jsaim; Kwak, Dochan (Technical Monitor)

2001-01-01

Flow simulations using the time-dependent Navier-Stokes equations remain a challenge for several reasons. Principal among them are the difficulty to accurately model complex flows, and the time needed to perform the computations. A parametric study of such complex problems is not considered practical due to the large cost associated with computing many time-dependent solutions. The computation time for each solution must be reduced in order to make a parametric study possible. With successful reduction of computation time, the issue of accuracy, and appropriateness of turbulence models will become more tractable.

Novel polyglutamine model uncouples proteotoxicity from aging.

PubMed

Christie, Nakeirah T M; Lee, Amy L; Fay, Hannah G; Gray, Amelia A; Kikis, Elise A

2014-01-01

Polyglutamine expansions in certain proteins are the genetic determinants for nine distinct progressive neurodegenerative disorders and resultant age-related dementia. In these cases, neurodegeneration is due to the aggregation propensity and resultant toxic properties of the polyglutamine-containing proteins. We are interested in elucidating the underlying mechanisms of toxicity of the protein ataxin-3, in which a polyglutamine expansion is the genetic determinant for Machado-Joseph Disease (MJD), also referred to as spinocerebellar ataxia 3 (SCA3). To this end, we have developed a novel model for ataxin-3 protein aggregation, by expressing a disease-related polyglutamine-containing fragment of ataxin-3 in the genetically tractable body wall muscle cells of the model system C. elegans. Here, we demonstrate that this ataxin-3 fragment aggregates in a polyQ length-dependent manner in C. elegans muscle cells and that this aggregation is associated with cellular dysfunction. However, surprisingly, this aggregation and resultant toxicity was not influenced by aging. This is in contrast to polyglutamine peptides alone whose aggregation/toxicity is highly dependent on age. Thus, the data presented here not only describe a new polyglutamine model, but also suggest that protein context likely influences the cellular interactions of the polyglutamine-containing protein and thereby modulates its toxic properties.

Dipole saturated absorption modeling in gas phase: Dealing with a Gaussian beam

NASA Astrophysics Data System (ADS)

Dupré, Patrick

2018-01-01

With the advent of new accurate and sensitive spectrometers, cf. combining optical cavities (for absorption enhancement), the requirement for reliable molecular transition modeling is becoming more pressing. Unfortunately, there is no trivial approach which can provide a definitive formalism allowing us to solve the coupled systems of equations associated with nonlinear absorption. Here, we propose a general approach to deal with any spectral shape of the electromagnetic field interacting with a molecular species under saturation conditions. The development is specifically applied to Gaussian-shaped beams. To make the analytical expressions tractable, approximations are proposed. Finally, two or three numerical integrations are required for describing the Lamb-dip profile. The implemented model allows us to describe the saturated absorption under low pressure conditions where the broadening by the transit-time may dominate the collision rates. The model is applied to two specific overtone transitions of the molecular acetylene. The simulated line shapes are discussed versus the collision and the transit-time rates. The specific collisional and collision-free regimes are illustrated, while the Rabi frequency controls the intermediate regime. We illustrate how to recover the input parameters by fitting the simulated profiles.

Seven challenges for metapopulation models of epidemics, including households models.

PubMed

Ball, Frank; Britton, Tom; House, Thomas; Isham, Valerie; Mollison, Denis; Pellis, Lorenzo; Scalia Tomba, Gianpaolo

2015-03-01

This paper considers metapopulation models in the general sense, i.e. where the population is partitioned into sub-populations (groups, patches,...), irrespective of the biological interpretation they have, e.g. spatially segregated large sub-populations, small households or hosts themselves modelled as populations of pathogens. This framework has traditionally provided an attractive approach to incorporating more realistic contact structure into epidemic models, since it often preserves analytic tractability (in stochastic as well as deterministic models) but also captures the most salient structural inhomogeneity in contact patterns in many applied contexts. Despite the progress that has been made in both the theory and application of such metapopulation models, we present here several major challenges that remain for future work, focusing on models that, in contrast to agent-based ones, are amenable to mathematical analysis. The challenges range from clarifying the usefulness of systems of weakly-coupled large sub-populations in modelling the spread of specific diseases to developing a theory for endemic models with household structure. They include also developing inferential methods for data on the emerging phase of epidemics, extending metapopulation models to more complex forms of human social structure, developing metapopulation models to reflect spatial population structure, developing computationally efficient methods for calculating key epidemiological model quantities, and integrating within- and between-host dynamics in models. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

The filamentous fungus Sordaria macrospora as a genetic model to study fruiting body development.

PubMed

Teichert, Ines; Nowrousian, Minou; Pöggeler, Stefanie; Kück, Ulrich

2014-01-01

Filamentous fungi are excellent experimental systems due to their short life cycles as well as easy and safe manipulation in the laboratory. They form three-dimensional structures with numerous different cell types and have a long tradition as genetic model organisms used to unravel basic mechanisms underlying eukaryotic cell differentiation. The filamentous ascomycete Sordaria macrospora is a model system for sexual fruiting body (perithecia) formation. S. macrospora is homothallic, i.e., self-fertile, easily genetically tractable, and well suited for large-scale genomics, transcriptomics, and proteomics studies. Specific features of its life cycle and the availability of a developmental mutant library make it an excellent system for studying cellular differentiation at the molecular level. In this review, we focus on recent developments in identifying gene and protein regulatory networks governing perithecia formation. A number of tools have been developed to genetically analyze developmental mutants and dissect transcriptional profiles at different developmental stages. Protein interaction studies allowed us to identify a highly conserved eukaryotic multisubunit protein complex, the striatin-interacting phosphatase and kinase complex and its role in sexual development. We have further identified a number of proteins involved in chromatin remodeling and transcriptional regulation of fruiting body development. Furthermore, we review the involvement of metabolic processes from both primary and secondary metabolism, and the role of nutrient recycling by autophagy in perithecia formation. Our research has uncovered numerous players regulating multicellular development in S. macrospora. Future research will focus on mechanistically understanding how these players are orchestrated in this fungal model system. Copyright © 2014 Elsevier Inc. All rights reserved.

High-resolution mapping of bifurcations in nonlinear biochemical circuits

NASA Astrophysics Data System (ADS)

Genot, A. J.; Baccouche, A.; Sieskind, R.; Aubert-Kato, N.; Bredeche, N.; Bartolo, J. F.; Taly, V.; Fujii, T.; Rondelez, Y.

2016-08-01

Analog molecular circuits can exploit the nonlinear nature of biochemical reaction networks to compute low-precision outputs with fewer resources than digital circuits. This analog computation is similar to that employed by gene-regulation networks. Although digital systems have a tractable link between structure and function, the nonlinear and continuous nature of analog circuits yields an intricate functional landscape, which makes their design counter-intuitive, their characterization laborious and their analysis delicate. Here, using droplet-based microfluidics, we map with high resolution and dimensionality the bifurcation diagrams of two synthetic, out-of-equilibrium and nonlinear programs: a bistable DNA switch and a predator-prey DNA oscillator. The diagrams delineate where function is optimal, dynamics bifurcates and models fail. Inverse problem solving on these large-scale data sets indicates interference from enzymatic coupling. Additionally, data mining exposes the presence of rare, stochastically bursting oscillators near deterministic bifurcations.

Effects of Synthetic Diets Enriched in Specific Nutrients on Drosophila Development, Body Fat, and Lifespan.

PubMed

Reis, Tânia

2016-01-01

Gene-diet interactions play a crucial but poorly understood role in susceptibility to obesity. Accordingly, the development of genetically tractable model systems to study the influence of diets in obesity-prone genetic backgrounds is a focus of current research. Here I present a modified synthetic Drosophila diet optimized for timely larval development, a stage dedicated to energy storage. Specifically increasing the levels of individual macronutrients-carbohydrate, lipid, or protein-resulted in markedly different organismal effects. A high-carbohydrate diet adversely affected the timing of development, size, early lifespan and body fat. Strikingly, quadrupling the amount of dietary lipids had none of these effects. Diets rich in protein appeared to be the most beneficial, as larvae developed faster, with no change in size, into long-lived adults. I believe this synthetic diet will significantly facilitate the study of gene-diet interactions in organismal energy balance.

Different parameters support generalization and discrimination learning in Drosophila at the flight simulator.

PubMed

Brembs, Björn; Hempel de Ibarra, Natalie

2006-01-01

We have used a genetically tractable model system, the fruit fly Drosophila melanogaster to study the interdependence between sensory processing and associative processing on learning performance. We investigated the influence of variations in the physical and predictive properties of color stimuli in several different operant-conditioning procedures on the subsequent learning performance. These procedures included context and stimulus generalization as well as color, compound, and conditional discrimination (colors and patterns). A surprisingly complex dependence of the learning performance on the colors' physical and predictive properties emerged, which was clarified by taking into account the fly-subjective perception of the color stimuli. Based on estimates of the stimuli's color and brightness values, we propose that the different tasks are supported by different parameters of the color stimuli; generalization occurs only if the chromaticity is sufficiently similar, whereas discrimination learning relies on brightness differences.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siranosian, Antranik Antonio; Schembri, Philip Edward; Miller, Nathan Andrew

The Benchmark Extensible Tractable Testbed Engineering Resource (BETTER) is proposed as a family of modular test bodies that are intended to support engineering capability development by helping to identify weaknesses and needs. Weapon systems, subassemblies, and components are often complex and difficult to test and analyze, resulting in low confidence and high uncertainties in experimental and simulated results. The complexities make it difficult to distinguish between inherent uncertainties and errors due to insufficient capabilities. BETTER test bodies will first use simplified geometries and materials such that testing, data collection, modeling and simulation can be accomplished with high confidence and lowmore » uncertainty. Modifications and combinations of simple and well-characterized BETTER test bodies can then be used to increase complexity in order to reproduce relevant mechanics and identify weaknesses. BETTER can provide both immediate and long-term improvements in testing and simulation capabilities. This document presents the motivation, concept, benefits and examples for BETTER.« less

Identification of novel anelloviruses with broad diversity in UK rodents

PubMed Central

Nishiyama, Shoko; Dutia, Bernadette M.; Stewart, James P.; Meredith, Anna L.; Shaw, Darren J.; Simmonds, Peter

2014-01-01

Anelloviruses are a family of small circular ssDNA viruses with a vast genetic diversity. Human infections with the prototype anellovirus, torque teno virus (TTV), are ubiquitous and related viruses have been described in a number of other mammalian hosts. Despite over 15 years of investigation, there is still little known about the pathogenesis and possible disease associations of anellovirus infections, arising in part due to the lack of a robust cell culture system for viral replication or tractable small-animal model. We report the identification of diverse anelloviruses in several species of wild rodents. The viruses are highly prevalent in wood mice (Apodemus sylvaticus) and field voles (Microtus agrestis), detectable at a low frequency in bank voles (Myodes glareolus), but absent from house mice (Mus musculus). The viruses identified have a genomic organization consistent with other anelloviruses, but form two clear phylogenetic groups that are as distinct from each other as from defined genera. PMID:24744300

Knockout of Foxp2 disrupts vocal development in mice.

PubMed

Castellucci, Gregg A; McGinley, Matthew J; McCormick, David A

2016-03-16

The FOXP2 gene is important for the development of proper speech motor control in humans. However, the role of the gene in general vocal behavior in other mammals, including mice, is unclear. Here, we track the vocal development of Foxp2 heterozygous knockout (Foxp2+/-) mice and their wildtype (WT) littermates from juvenile to adult ages, and observe severe abnormalities in the courtship song of Foxp2+/- mice. In comparison to their WT littermates, Foxp2+/- mice vocalized less, produced shorter syllable sequences, and possessed an abnormal syllable inventory. In addition, Foxp2+/- song also exhibited irregular rhythmic structure, and its development did not follow the consistent trajectories observed in WT vocalizations. These results demonstrate that the Foxp2 gene is critical for normal vocal behavior in juvenile and adult mice, and that Foxp2 mutant mice may provide a tractable model system for the study of the gene's role in general vocal motor control.

Antimicrobial autophagy: a conserved innate immune response in Drosophila.

PubMed

Moy, Ryan H; Cherry, Sara

2013-01-01

Autophagy is a highly conserved degradative pathway that has rapidly emerged as a critical component of immunity and host defense. Studies have implicated autophagy genes in restricting the replication of a diverse array of pathogens, including bacteria, viruses and protozoans. However, in most cases, the in vivo role of antimicrobial autophagy against pathogens has been undefined. Drosophila provides a genetically tractable model system that can be easily adapted to study autophagy in innate immunity, and recent studies in flies have demonstrated that autophagy is an essential antimicrobial response against bacteria and viruses in vivo. These findings reveal striking conservation of antimicrobial autophagy between flies and mammals, and in particular, the role of pathogen-associated pattern recognition in triggering this response. This review discusses our current understanding of antimicrobial autophagy in Drosophila and its potential relevance to human immunity. Copyright © 2013 S. Karger AG, Basel.

Incorporating Uncertainty into Spacecraft Mission and Trajectory Design

NASA Astrophysics Data System (ADS)

Juliana D., Feldhacker

The complex nature of many astrodynamic systems often leads to high computational costs or degraded accuracy in the analysis and design of spacecraft missions, and the incorporation of uncertainty into the trajectory optimization process often becomes intractable. This research applies mathematical modeling techniques to reduce computational cost and improve tractability for design, optimization, uncertainty quantication (UQ) and sensitivity analysis (SA) in astrodynamic systems and develops a method for trajectory optimization under uncertainty (OUU). This thesis demonstrates the use of surrogate regression models and polynomial chaos expansions for the purpose of design and UQ in the complex three-body system. Results are presented for the application of the models to the design of mid-eld rendezvous maneuvers for spacecraft in three-body orbits. The models are shown to provide high accuracy with no a priori knowledge on the sample size required for convergence. Additionally, a method is developed for the direct incorporation of system uncertainties into the design process for the purpose of OUU and robust design; these methods are also applied to the rendezvous problem. It is shown that the models can be used for constrained optimization with orders of magnitude fewer samples than is required for a Monte Carlo approach to the same problem. Finally, this research considers an application for which regression models are not well-suited, namely UQ for the kinetic de ection of potentially hazardous asteroids under the assumptions of real asteroid shape models and uncertainties in the impact trajectory and the surface material properties of the asteroid, which produce a non-smooth system response. An alternate set of models is presented that enables analytic computation of the uncertainties in the imparted momentum from impact. Use of these models for a survey of asteroids allows conclusions to be drawn on the eects of an asteroid's shape on the ability to successfully divert the asteroid via kinetic impactor.

Compositional and enumerative designs for medical language representation.

PubMed Central

Rassinoux, A. M.; Miller, R. A.; Baud, R. H.; Scherrer, J. R.

1997-01-01

Medical language is in essence highly compositional, allowing complex information to be expressed from more elementary pieces. Embedding the expressive power of medical language into formal systems of representation is recognized in the medical informatics community as a key step towards sharing such information among medical record, decision support, and information retrieval systems. Accordingly, such representation requires managing both the expressiveness of the formalism and its computational tractability, while coping with the level of detail expected by clinical applications. These desiderata can be supported by enumerative as well as compositional approaches, as argued in this paper. These principles have been applied in recasting a frame-based system for general medical findings developed during the 1980s. The new system captures the precise meaning of a subset of over 1500 medical terms for general internal medicine identified from the Quick Medical Reference (QMR) lexicon. In order to evaluate the adequacy of this formal structure in reflecting the deep meaning of the QMR findings, a validation process was implemented. It consists of automatically rebuilding the semantic representation of the QMR findings by analyzing them through the RECIT natural language analyzer, whose semantic components have been adjusted to this frame-based model for the understanding task. PMID:9357700

Compositional and enumerative designs for medical language representation.

PubMed

Rassinoux, A M; Miller, R A; Baud, R H; Scherrer, J R

1997-01-01

Medical language is in essence highly compositional, allowing complex information to be expressed from more elementary pieces. Embedding the expressive power of medical language into formal systems of representation is recognized in the medical informatics community as a key step towards sharing such information among medical record, decision support, and information retrieval systems. Accordingly, such representation requires managing both the expressiveness of the formalism and its computational tractability, while coping with the level of detail expected by clinical applications. These desiderata can be supported by enumerative as well as compositional approaches, as argued in this paper. These principles have been applied in recasting a frame-based system for general medical findings developed during the 1980s. The new system captures the precise meaning of a subset of over 1500 medical terms for general internal medicine identified from the Quick Medical Reference (QMR) lexicon. In order to evaluate the adequacy of this formal structure in reflecting the deep meaning of the QMR findings, a validation process was implemented. It consists of automatically rebuilding the semantic representation of the QMR findings by analyzing them through the RECIT natural language analyzer, whose semantic components have been adjusted to this frame-based model for the understanding task.

Model annotation for synthetic biology: automating model to nucleotide sequence conversion

PubMed Central

Misirli, Goksel; Hallinan, Jennifer S.; Yu, Tommy; Lawson, James R.; Wimalaratne, Sarala M.; Cooling, Michael T.; Wipat, Anil

2011-01-01

Motivation: The need for the automated computational design of genetic circuits is becoming increasingly apparent with the advent of ever more complex and ambitious synthetic biology projects. Currently, most circuits are designed through the assembly of models of individual parts such as promoters, ribosome binding sites and coding sequences. These low level models are combined to produce a dynamic model of a larger device that exhibits a desired behaviour. The larger model then acts as a blueprint for physical implementation at the DNA level. However, the conversion of models of complex genetic circuits into DNA sequences is a non-trivial undertaking due to the complexity of mapping the model parts to their physical manifestation. Automating this process is further hampered by the lack of computationally tractable information in most models. Results: We describe a method for automatically generating DNA sequences from dynamic models implemented in CellML and Systems Biology Markup Language (SBML). We also identify the metadata needed to annotate models to facilitate automated conversion, and propose and demonstrate a method for the markup of these models using RDF. Our algorithm has been implemented in a software tool called MoSeC. Availability: The software is available from the authors' web site http://research.ncl.ac.uk/synthetic_biology/downloads.html. Contact: anil.wipat@ncl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21296753

On a production system using default reasoning for pattern classification

NASA Technical Reports Server (NTRS)

Barry, Matthew R.; Lowe, Carlyle M.

1990-01-01

This paper addresses an unconventional application of a production system to a problem involving belief specialization. The production system reduces a large quantity of low-level descriptions into just a few higher-level descriptions that encompass the problem space in a more tractable fashion. This classification process utilizes a set of descriptions generated by combining the component hierarchy of a physical system with the semantics of the terminology employed in its operation. The paper describes an application of this process in a program, constructed in C and CLIPS, that classifies signatures of electromechanical system configurations. The program compares two independent classifications, describing the actual and expected system configurations, in order to generate a set of contradictions between the two.

Covalent Ligand Discovery against Druggable Hotspots Targeted by Anti-cancer Natural Products.

PubMed

Grossman, Elizabeth A; Ward, Carl C; Spradlin, Jessica N; Bateman, Leslie A; Huffman, Tucker R; Miyamoto, David K; Kleinman, Jordan I; Nomura, Daniel K

2017-11-16

Many natural products that show therapeutic activities are often difficult to synthesize or isolate and have unknown targets, hindering their development as drugs. Identifying druggable hotspots targeted by covalently acting anti-cancer natural products can enable pharmacological interrogation of these sites with more synthetically tractable compounds. Here, we used chemoproteomic platforms to discover that the anti-cancer natural product withaferin A targets C377 on the regulatory subunit PPP2R1A of the tumor-suppressor protein phosphatase 2A (PP2A) complex leading to activation of PP2A activity, inactivation of AKT, and impaired breast cancer cell proliferation. We developed a more synthetically tractable cysteine-reactive covalent ligand, JNS 1-40, that selectively targets C377 of PPP2R1A to impair breast cancer signaling, proliferation, and in vivo tumor growth. Our study highlights the utility of using chemoproteomics to map druggable hotspots targeted by complex natural products and subsequently interrogating these sites with more synthetically tractable covalent ligands for cancer therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parameterized Complexity Results for General Factors in Bipartite Graphs with an Application to Constraint Programming

NASA Astrophysics Data System (ADS)

Gutin, Gregory; Kim, Eun Jung; Soleimanfallah, Arezou; Szeider, Stefan; Yeo, Anders

The NP-hard general factor problem asks, given a graph and for each vertex a list of integers, whether the graph has a spanning subgraph where each vertex has a degree that belongs to its assigned list. The problem remains NP-hard even if the given graph is bipartite with partition U ⊎ V, and each vertex in U is assigned the list {1}; this subproblem appears in the context of constraint programming as the consistency problem for the extended global cardinality constraint. We show that this subproblem is fixed-parameter tractable when parameterized by the size of the second partite set V. More generally, we show that the general factor problem for bipartite graphs, parameterized by |V |, is fixed-parameter tractable as long as all vertices in U are assigned lists of length 1, but becomes W[1]-hard if vertices in U are assigned lists of length at most 2. We establish fixed-parameter tractability by reducing the problem instance to a bounded number of acyclic instances, each of which can be solved in polynomial time by dynamic programming.

Modelling Creativity: Identifying Key Components through a Corpus-Based Approach.

PubMed

Jordanous, Anna; Keller, Bill

2016-01-01

Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research.

Linearly Adjustable International Portfolios

NASA Astrophysics Data System (ADS)

Fonseca, R. J.; Kuhn, D.; Rustem, B.

2010-09-01

We present an approach to multi-stage international portfolio optimization based on the imposition of a linear structure on the recourse decisions. Multiperiod decision problems are traditionally formulated as stochastic programs. Scenario tree based solutions however can become intractable as the number of stages increases. By restricting the space of decision policies to linear rules, we obtain a conservative tractable approximation to the original problem. Local asset prices and foreign exchange rates are modelled separately, which allows for a direct measure of their impact on the final portfolio value.

How Suspicion Grows: Effects of Population Size on Cooperation

DTIC Science & Technology

2014-09-01

suspicious tit-for-tat TFT tit-for-tat TF2T tit-for-two-tats xiii THIS PAGE INTENTIONALLY LEFT BLANK xiv Executive Summary People in a group typically...theoretic model mathematically tractable, we restrict each individual to four strategies: tit-for-two-tats (TF2T), tit-for-tat ( TFT ), suspicious-tit...stranger, TF2T will begin by cooperation twice, TFT by cooperating once, and STFT by defecting once. After the initial moves, in each encounter, the

Toward a Greater Understanding of the Reduction of Drift Coefficients in the Presence of Turbulence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engelbrecht, N. E.; Strauss, R. D.; Burger, R. A.

2017-06-01

Drift effects play a significant role in the transport of charged particles in the heliosphere. A turbulent magnetic field is also known to reduce the effects of particle drifts. The exact nature of this reduction, however, is not clear. This study aims to provide some insight into this reduction and proposes a relatively simple, tractable means of modeling it that provides results in reasonable agreement with numerical simulations of the drift coefficient in a turbulent magnetic field.

Chemical potential driven phase transition of black holes in anti-de Sitter space

NASA Astrophysics Data System (ADS)

Galante, Mario; Giribet, Gaston; Goya, Andrés; Oliva, Julio

2015-11-01

Einstein-Maxwell theory conformally coupled to a scalar field in D dimensions may exhibit a phase transition at low temperature whose end point is an asymptotically anti-de Sitter black hole with a scalar field profile that is regular everywhere outside and on the horizon. This provides a tractable model to study the phase transition of hairy black holes in anti-de Sitter space in which the backreaction on the geometry can be solved analytically.

Tractable Goal Selection with Oversubscribed Resources

NASA Technical Reports Server (NTRS)

Rabideau, Gregg; Chien, Steve; McLaren, David

2009-01-01

We describe an efficient, online goal selection algorithm and its use for selecting goals at runtime. Our focus is on the re-planning that must be performed in a timely manner on the embedded system where computational resources are limited. In particular, our algorithm generates near optimal solutions to problems with fully specified goal requests that oversubscribe available resources but have no temporal flexibility. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. This enables shorter response cycles and greater autonomy for the system under control.

Zebrafish hair cell mechanics and physiology through the lens of noise-induced hair cell death

NASA Astrophysics Data System (ADS)

Coffin, Allison B.; Xu, Jie; Uribe, Phillip M.

2018-05-01

Hair cells are exquisitely sensitive to auditory stimuli, but also to damage from a variety of sources including noise trauma and ototoxic drugs. Mammals cannot regenerate cochlear hair cells, while non-mammalian vertebrates exhibit robust regenerative capacity. Our research group uses the lateral line system of larval zebrafish to explore the mechanisms underlying hair cell damage, identify protective therapies, and determine molecular drivers of innate regeneration. The lateral line system contains externally located sensory organs called neuromasts, each composed of ˜8-20 hair cells. Lateral line hair cells are homologous to vertebrate inner ear hair cells and share similar susceptibility to ototoxic damage. In the last decade, the lateral line has emerged as a powerful model system for understanding hair cell death mechanisms and for identifying novel protective compounds. Here we demonstrate that the lateral line is a tractable model for noise-induced hair cell death. We have developed a novel noise damage system capable of inducing over 50% loss of lateral line hair cells, with hair cell death occurring in a dose- and time-dependent manner. Cell death is greatest 72 hours post-exposure. However, early signs of hair cell damage, including changes in membrane integrity and reduced mechanotransduction, are apparent within hours of noise exposure. These features, early signs of damage followed by delayed hair cell death, are consistent with mammalian data, suggesting that noise acts similarly on zebrafish and mammalian hair cells. In our future work we will use our new model system to investigate noise damage events in real time, and to develop protective therapies for future translational research.

Probabilistic short-term forecasting of eruption rate at Kīlauea Volcano using a physics-based model

NASA Astrophysics Data System (ADS)

Anderson, K. R.

2016-12-01

Deterministic models of volcanic eruptions yield predictions of future activity conditioned on uncertainty in the current state of the system. Physics-based eruption models are well-suited for deterministic forecasting as they can relate magma physics with a wide range of observations. Yet, physics-based eruption forecasting is strongly limited by an inadequate understanding of volcanic systems, and the need for eruption models to be computationally tractable. At Kīlauea Volcano, Hawaii, episodic depressurization-pressurization cycles of the magma system generate correlated, quasi-exponential variations in ground deformation and surface height of the active summit lava lake. Deflations are associated with reductions in eruption rate, or even brief eruptive pauses, and thus partly control lava flow advance rates and associated hazard. Because of the relatively well-understood nature of Kīlauea's shallow magma plumbing system, and because more than 600 of these events have been recorded to date, they offer a unique opportunity to refine a physics-based effusive eruption forecasting approach and apply it to lava eruption rates over short (hours to days) time periods. A simple physical model of the volcano ascribes observed data to temporary reductions in magma supply to an elastic reservoir filled with compressible magma. This model can be used to predict the evolution of an ongoing event, but because the mechanism that triggers events is unknown, event durations are modeled stochastically from previous observations. A Bayesian approach incorporates diverse data sets and prior information to simultaneously estimate uncertain model parameters and future states of the system. Forecasts take the form of probability distributions for eruption rate or cumulative erupted volume at some future time. Results demonstrate the significant uncertainties that still remain even for short-term eruption forecasting at a well-monitored volcano - but also the value of a physics-based, mixed deterministic-probabilistic eruption forecasting approach in reducing and quantifying these uncertainties.

The Use of Scale-Dependent Precision to Increase Forecast Accuracy in Earth System Modelling

NASA Astrophysics Data System (ADS)

Thornes, Tobias; Duben, Peter; Palmer, Tim

2016-04-01

At the current pace of development, it may be decades before the 'exa-scale' computers needed to resolve individual convective clouds in weather and climate models become available to forecasters, and such machines will incur very high power demands. But the resolution could be improved today by switching to more efficient, 'inexact' hardware with which variables can be represented in 'reduced precision'. Currently, all numbers in our models are represented as double-precision floating points - each requiring 64 bits of memory - to minimise rounding errors, regardless of spatial scale. Yet observational and modelling constraints mean that values of atmospheric variables are inevitably known less precisely on smaller scales, suggesting that this may be a waste of computer resources. More accurate forecasts might therefore be obtained by taking a scale-selective approach whereby the precision of variables is gradually decreased at smaller spatial scales to optimise the overall efficiency of the model. To study the effect of reducing precision to different levels on multiple spatial scales, we here introduce a new model atmosphere developed by extending the Lorenz '96 idealised system to encompass three tiers of variables - which represent large-, medium- and small-scale features - for the first time. In this chaotic but computationally tractable system, the 'true' state can be defined by explicitly resolving all three tiers. The abilities of low resolution (single-tier) double-precision models and similar-cost high resolution (two-tier) models in mixed-precision to produce accurate forecasts of this 'truth' are compared. The high resolution models outperform the low resolution ones even when small-scale variables are resolved in half-precision (16 bits). This suggests that using scale-dependent levels of precision in more complicated real-world Earth System models could allow forecasts to be made at higher resolution and with improved accuracy. If adopted, this new paradigm would represent a revolution in numerical modelling that could be of great benefit to the world.

To the theory of particle lifting by terrestrial and Martian dust devils

NASA Astrophysics Data System (ADS)

Kurgansky, M. V.

2018-01-01

The combined Rankine vortex model is applied to describe the radial profile of azimuthal velocity in atmospheric dust devils, and a simplified model version is proposed of the turbulent surface boundary layer beneath the Rankine vortex periphery that corresponds to the potential vortex. Based on the results by Burggraf et al. (1971), it is accepted that the radial velocity near the ground in the potential vortex greatly exceeds the azimuthal velocity, which makes tractable the problem of the surface shear stress determination, including the case of the turbulent surface boundary layer. The constructed model explains exceeding the threshold shear velocity for aeolian transport in typical dust-devil vortices both on Earth and on Mars.

Analytical performance study of solar blind non-line-of-sight ultraviolet short-range communication links.

PubMed

Xu, Zhengyuan; Ding, Haipeng; Sadler, Brian M; Chen, Gang

2008-08-15

Motivated by recent advances in solid-state incoherent ultraviolet sources and solar blind detectors, we study communication link performance over a range of less than 1 km with a bit error rate (BER) below 10(-3) in solar blind non-line-of-sight situation. The widely adopted yet complex single scattering channel model is significantly simplified by means of a closed-form expression for tractable analysis. Path loss is given as a function of transceiver geometry as well as atmospheric scattering and attenuation and is compared with experimental data for model validation. The BER performance of a shot-noise-limited receiver under this channel model is demonstrated.

Detection of Subtle Context-Dependent Model Inaccuracies in High-Dimensional Robot Domains.

PubMed

Mendoza, Juan Pablo; Simmons, Reid; Veloso, Manuela

2016-12-01

Autonomous robots often rely on models of their sensing and actions for intelligent decision making. However, when operating in unconstrained environments, the complexity of the world makes it infeasible to create models that are accurate in every situation. This article addresses the problem of using potentially large and high-dimensional sets of robot execution data to detect situations in which a robot model is inaccurate-that is, detecting context-dependent model inaccuracies in a high-dimensional context space. To find inaccuracies tractably, the robot conducts an informed search through low-dimensional projections of execution data to find parametric Regions of Inaccurate Modeling (RIMs). Empirical evidence from two robot domains shows that this approach significantly enhances the detection power of existing RIM-detection algorithms in high-dimensional spaces.

Transforming Undergraduate Education Through the use of Analytical Reasoning (TUETAR)

NASA Astrophysics Data System (ADS)

Bishop, M. P.; Houser, C.; Lemmons, K.

2015-12-01

Traditional learning limits the potential for self-discovery, and the use of data and knowledge to understand Earth system relationships, processes, feedback mechanisms and system coupling. It is extremely difficult for undergraduate students to analyze, synthesize, and integrate quantitative information related to complex systems, as many concepts may not be mathematically tractable or yet to be formalized. Conceptual models have long served as a means for Earth scientists to organize their understanding of Earth's dynamics, and have served as a basis for human analytical reasoning and landscape interpretation. Consequently, we evaluated the use of conceptual modeling, knowledge representation and analytical reasoning to provide undergraduate students with an opportunity to develop and test geocomputational conceptual models based upon their understanding of Earth science concepts. This study describes the use of geospatial technologies and fuzzy cognitive maps to predict desertification across the South-Texas Sandsheet in an upper-level geomorphology course. Students developed conceptual models based on their understanding of aeolian processes from lectures, and then compared and evaluated their modeling results against an expert conceptual model and spatial predictions, and the observed distribution of dune activity in 2010. Students perceived that the analytical reasoning approach was significantly better for understanding desertification compared to traditional lecture, and promoted reflective learning, working with data, teamwork, student interaction, innovation, and creative thinking. Student evaluations support the notion that the adoption of knowledge representation and analytical reasoning in the classroom has the potential to transform undergraduate education by enabling students to formalize and test their conceptual understanding of Earth science. A model for developing and utilizing this geospatial technology approach in Earth science is presented.

Monitoring with Trackers Based on Semi-Quantitative Models

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin

1997-01-01

In three years of NASA-sponsored research preceding this project, we successfully developed a technology for: (1) building qualitative and semi-quantitative models from libraries of model-fragments, (2) simulating these models to predict future behaviors with the guarantee that all possible behaviors are covered, (3) assimilating observations into behaviors, shrinking uncertainty so that incorrect models are eventually refuted and correct models make stronger predictions for the future. In our object-oriented framework, a tracker is an object which embodies the hypothesis that the available observation stream is consistent with a particular behavior of a particular model. The tracker maintains its own status (consistent, superceded, or refuted), and answers questions about its explanation for past observations and its predictions for the future. In the MIMIC approach to monitoring of continuous systems, a number of trackers are active in parallel, representing alternate hypotheses about the behavior of a system. This approach is motivated by the need to avoid 'system accidents' [Perrow, 1985] due to operator fixation on a single hypothesis, as for example at Three Mile Island. As we began to address these issues, we focused on three major research directions that we planned to pursue over a three-year project: (1) tractable qualitative simulation, (2) semiquantitative inference, and (3) tracking set management. Unfortunately, funding limitations made it impossible to continue past year one. Nonetheless, we made major progress in the first two of these areas. Progress in the third area as slower because the graduate student working on that aspect of the project decided to leave school and take a job in industry. I enclosed a set of abstract of selected papers on the work describe below. Several papers that draw on the research supported during this period appeared in print after the grant period ended.

Stochastic dynamics of cholera epidemics

NASA Astrophysics Data System (ADS)

Azaele, Sandro; Maritan, Amos; Bertuzzo, Enrico; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2010-05-01

We describe the predictions of an analytically tractable stochastic model for cholera epidemics following a single initial outbreak. The exact model relies on a set of assumptions that may restrict the generality of the approach and yet provides a realm of powerful tools and results. Without resorting to the depletion of susceptible individuals, as usually assumed in deterministic susceptible-infected-recovered models, we show that a simple stochastic equation for the number of ill individuals provides a mechanism for the decay of the epidemics occurring on the typical time scale of seasonality. The model is shown to provide a reasonably accurate description of the empirical data of the 2000/2001 cholera epidemic which took place in the Kwa Zulu-Natal Province, South Africa, with possibly notable epidemiological implications.

Birth/birth-death processes and their computable transition probabilities with biological applications.

PubMed

Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W; Minin, Vladimir N; Suchard, Marc A

2018-03-01

Birth-death processes track the size of a univariate population, but many biological systems involve interaction between populations, necessitating models for two or more populations simultaneously. A lack of efficient methods for evaluating finite-time transition probabilities of bivariate processes, however, has restricted statistical inference in these models. Researchers rely on computationally expensive methods such as matrix exponentiation or Monte Carlo approximation, restricting likelihood-based inference to small systems, or indirect methods such as approximate Bayesian computation. In this paper, we introduce the birth/birth-death process, a tractable bivariate extension of the birth-death process, where rates are allowed to be nonlinear. We develop an efficient algorithm to calculate its transition probabilities using a continued fraction representation of their Laplace transforms. Next, we identify several exemplary models arising in molecular epidemiology, macro-parasite evolution, and infectious disease modeling that fall within this class, and demonstrate advantages of our proposed method over existing approaches to inference in these models. Notably, the ubiquitous stochastic susceptible-infectious-removed (SIR) model falls within this class, and we emphasize that computable transition probabilities newly enable direct inference of parameters in the SIR model. We also propose a very fast method for approximating the transition probabilities under the SIR model via a novel branching process simplification, and compare it to the continued fraction representation method with application to the 17th century plague in Eyam. Although the two methods produce similar maximum a posteriori estimates, the branching process approximation fails to capture the correlation structure in the joint posterior distribution.

Proceedings of Joint RL/AFOSR Workshop on Intelligent Information Systems Held at Griffiss AFB, New York on October 22-23, 1991

DTIC Science & Technology

1992-04-01

AND SCHEDULING" TIM FINN, UNIVERSITY OF MARYLAND, BALTIMORE COUNTY E. " EXTRACTING RULES FROM SOFTWARE FOR KNOWLEDGE-BASES" NOAH S. PRYWES, UNIVERSITY...Databases for Planning and Scheduling" Tim Finin, Unisys Corporation 8:30 - 9:00 " Extracting Rules from Software for Knowledge Baseso Noah Prywes, U. of...Space Requirements are Tractable E.G.: FEM, Multiplication Routines, Sorting Programs Lebmwmy fo Al Roseew d. The Ohio Male Unlversity A-2 Type 2

Selection theory of free dendritic growth in a potential flow.

PubMed

von Kurnatowski, Martin; Grillenbeck, Thomas; Kassner, Klaus

2013-04-01

The Kruskal-Segur approach to selection theory in diffusion-limited or Laplacian growth is extended via combination with the Zauderer decomposition scheme. This way nonlinear bulk equations become tractable. To demonstrate the method, we apply it to two-dimensional crystal growth in a potential flow. We omit the simplifying approximations used in a preliminary calculation for the same system [Fischaleck, Kassner, Europhys. Lett. 81, 54004 (2008)], thus exhibiting the capability of the method to extend mathematical rigor to more complex problems than hitherto accessible.

Individual negative symptoms and domains - Relevance for assessment, pathomechanisms and treatment.

PubMed

Kaiser, Stefan; Lyne, John; Agartz, Ingrid; Clarke, Mary; Mørch-Johnsen, Lynn; Faerden, Ann

2017-08-01

The negative symptoms of schizophrenia can be divided into two domains. Avolition/apathy includes the individual symptoms of avolition, asociality and anhedonia. Diminished expression includes blunted affect and alogia. Until now, causes and treatment of negative symptoms have remained a major challenge, which is partially related to the focus on negative symptoms as a broad entity. Here, we propose that negative symptoms may become more tractable when the different domains and individual symptoms are taken into account. There is now increasing evidence that the relationship with clinical variables - in particular outcome - differs between the domains of avolition/apathy and diminished expression. Regarding models of negative symptom formation, those relevant to avolition/apathy are now converging on processes underlying goal-directed behavior and dysfunctions of the reward system. In contrast, models of the diminished expression domains are only beginning to emerge. The aim of this article is to review the specific clinical, behavioral and neural correlates of individual symptoms and domains as a better understanding of these areas may facilitate specific treatment approaches. Copyright © 2016 Elsevier B.V. All rights reserved.

Kidney organogenesis in the zebrafish: insights into vertebrate nephrogenesis and regeneration

PubMed Central

Gerlach, Gary F.; Wingert, Rebecca A.

2012-01-01

Vertebrates form a progressive series of up to three kidney organs during development—the pronephros, mesonephros, and metanephros. Each kidney derives from the intermediate mesoderm and is comprised of conserved excretory units called nephrons. The zebrafish is a powerful model for vertebrate developmental genetics, and recent studies have illustrated that zebrafish and mammals share numerous similarities in nephron composition and physiology. The zebrafish embryo forms an architecturally simple pronephros that has two nephrons, and these eventually become a scaffold onto which a mesonephros of several hundred nephrons is constructed during larval stages. In adult zebrafish, the mesonephros exhibits ongoing nephrogenesis, generating new nephrons from a local pool of renal progenitors during periods of growth or following kidney injury. The characteristics of the zebrafish pronephros and mesonephros make them genetically tractable kidney systems in which to study the functions of renal genes and address outstanding questions about the mechanisms of nephrogenesis. Here, we provide an overview of the formation and composition of these zebrafish kidney organs, and discuss how various zebrafish mutants, gene knockdowns, and transgenic models have created frameworks in which to further delineate nephrogenesis pathways. PMID:24014448

Chemistry and the worm: Caenorhabditis elegans as a platform for integrating chemical and biological research.

PubMed

Hulme, S Elizabeth; Whitesides, George M

2011-05-16

This Review discusses the potential usefulness of the worm Caenorhabditis elegans as a model organism for chemists interested in studying living systems. C. elegans, a 1 mm long roundworm, is a popular model organism in almost all areas of modern biology. The worm has several features that make it attractive for biology: it is small (<1000 cells), transparent, and genetically tractable. Despite its simplicity, the worm exhibits complex phenotypes associated with multicellularity: the worm has differentiated cells and organs, it ages and has a well-defined lifespan, and it is capable of learning and remembering. This Review argues that the balance between simplicity and complexity in the worm will make it a useful tool in determining the relationship between molecular-scale phenomena and organism-level phenomena, such as aging, behavior, cognition, and disease. Following an introduction to worm biology, the Review provides examples of current research with C. elegans that is chemically relevant. It also describes tools-biological, chemical, and physical-that are available to researchers studying the worm. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Generalized activity equations for spiking neural network dynamics.

PubMed

Buice, Michael A; Chow, Carson C

2013-01-01

Much progress has been made in uncovering the computational capabilities of spiking neural networks. However, spiking neurons will always be more expensive to simulate compared to rate neurons because of the inherent disparity in time scales-the spike duration time is much shorter than the inter-spike time, which is much shorter than any learning time scale. In numerical analysis, this is a classic stiff problem. Spiking neurons are also much more difficult to study analytically. One possible approach to making spiking networks more tractable is to augment mean field activity models with some information about spiking correlations. For example, such a generalized activity model could carry information about spiking rates and correlations between spikes self-consistently. Here, we will show how this can be accomplished by constructing a complete formal probabilistic description of the network and then expanding around a small parameter such as the inverse of the number of neurons in the network. The mean field theory of the system gives a rate-like description. The first order terms in the perturbation expansion keep track of covariances.

QR images: optimized image embedding in QR codes.

PubMed

Garateguy, Gonzalo J; Arce, Gonzalo R; Lau, Daniel L; Villarreal, Ofelia P

2014-07-01

This paper introduces the concept of QR images, an automatic method to embed QR codes into color images with bounded probability of detection error. These embeddings are compatible with standard decoding applications and can be applied to any color image with full area coverage. The QR information bits are encoded into the luminance values of the image, taking advantage of the immunity of QR readers against local luminance disturbances. To mitigate the visual distortion of the QR image, the algorithm utilizes halftoning masks for the selection of modified pixels and nonlinear programming techniques to locally optimize luminance levels. A tractable model for the probability of error is developed and models of the human visual system are considered in the quality metric used to optimize the luminance levels of the QR image. To minimize the processing time, the optimization techniques proposed to consider the mechanics of a common binarization method and are designed to be amenable for parallel implementations. Experimental results show the graceful degradation of the decoding rate and the perceptual quality as a function the embedding parameters. A visual comparison between the proposed and existing methods is presented.

Paternal epigenetic programming: evolving metabolic disease risk.

PubMed

Hur, Suzy S J; Cropley, Jennifer E; Suter, Catherine M

2017-04-01

Parental health or exposures can affect the lifetime health outcomes of offspring, independently of inherited genotypes. Such 'epigenetic' effects occur over a broad range of environmental stressors, including defects in parental metabolism. Although maternal metabolic effects are well documented, it has only recently been established that that there is also an independent paternal contribution to long-term metabolic health. Both paternal undernutrition and overnutrition can induce metabolic phenotypes in immediate offspring, and in some cases, the induced phenotype can affect multiple generations, implying inheritance of an acquired trait. The male lineage transmission of metabolic disease risk in these cases implicates a heritable factor carried by sperm. Sperm-based transmission provides a tractable system to interrogate heritable epigenetic factors influencing metabolism, and as detailed here, animal models of paternal programming have already provided some significant insights. Here, we review the evidence for paternal programming of metabolism in humans and animal models, and the available evidence on potential underlying mechanisms. Programming by paternal metabolism can be observed in multiple species across animal phyla, suggesting that this phenomenon may have a unique evolutionary significance. © 2017 Society for Endocrinology.

Evolving nonapeptide mechanisms of gregariousness and social diversity in birds.

PubMed

Goodson, James L; Kelly, Aubrey M; Kingsbury, Marcy A

2012-03-01

Of the major vertebrate taxa, Class Aves is the most extensively studied in relation to the evolution of social systems and behavior, largely because birds exhibit an incomparable balance of tractability, diversity, and cognitive complexity. In addition, like humans, most bird species are socially monogamous, exhibit biparental care, and conduct most of their social interactions through auditory and visual modalities. These qualities make birds attractive as research subjects, and also make them valuable for comparative studies of neuroendocrine mechanisms. This value has become increasingly apparent as more and more evidence shows that social behavior circuits of the basal forebrain and midbrain are deeply conserved (from an evolutionary perspective), and particularly similar in birds and mammals. Among the strongest similarities are the basic structures and functions of avian and mammalian nonapeptide systems, which include mesotocin (MT) and arginine vasotocin (VT) systems in birds, and the homologous oxytocin (OT) and vasopressin (VP) systems, respectively, in mammals. We here summarize these basic properties, and then describe a research program that has leveraged the social diversity of estrildid finches to gain insights into the nonapeptide mechanisms of grouping, a behavioral dimension that is not experimentally tractable in most other taxa. These studies have used five monogamous, biparental finch species that exhibit group sizes ranging from territorial male-female pairs to large flocks containing hundreds or thousands of birds. The results provide novel insights into the history of nonapeptide functions in amniote vertebrates, and yield remarkable clarity on the nonapeptide biology of dinosaurs and ancient mammals. This article is part of a Special Issue entitled Oxytocin, Vasopressin, and Social Behavior. Copyright © 2012 Elsevier Inc. All rights reserved.

Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Issen, Kathleen

2017-06-05

This project employed a continuum approach to formulate an elastic constitutive model for Castlegate sandstone. The resulting constitutive framework for high porosity sandstone is thermodynamically sound, (i.e., does not violate the 1st and 2nd law of thermodynamics), represents known material constitutive response, and is able to be calibrated using available mechanical response data. To authenticate the accuracy of this model, a series of validation criteria were employed, using an existing mechanical response data set for Castlegate sandstone. The resulting constitutive framework is applicable to high porosity sandstones in general, and is tractable for scientists and researchers endeavoring to solve problemsmore » of practical interest.« less

Evolution of host innate defence: insights from C. elegans and primitive invertebrates

PubMed Central

Irazoqui, Javier E.; Urbach, Jonathan M.; Ausubel, Frederick M.

2010-01-01

Preface The genetically tractable model organism Caenorhabditis elegans was first used to model bacterial virulence in vivo a decade ago. Since then, great strides have been made in the identification of host response pathways that are involved in the defence against infection. Strikingly, C. elegans seems to detect and respond to infection without the involvement of its Toll-like receptor homologue, in contrast to the well-established role for these proteins in innate immunity in mammals. What, therefore, do we know about host defence mechanisms in C. elegans, and what can they tell us about innate immunity in higher organisms? PMID:20029447

Compressive Sensing via Nonlocal Smoothed Rank Function

PubMed Central

Fan, Ya-Ru; Liu, Jun; Zhao, Xi-Le

2016-01-01

Compressive sensing (CS) theory asserts that we can reconstruct signals and images with only a small number of samples or measurements. Recent works exploiting the nonlocal similarity have led to better results in various CS studies. To better exploit the nonlocal similarity, in this paper, we propose a non-convex smoothed rank function based model for CS image reconstruction. We also propose an efficient alternating minimization method to solve the proposed model, which reduces a difficult and coupled problem to two tractable subproblems. Experimental results have shown that the proposed method performs better than several existing state-of-the-art CS methods for image reconstruction. PMID:27583683

Defect Genome of Cubic Perovskites for Fuel Cell Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balachandran, Janakiraman; Lin, Lianshan; Anchell, Jonathan S.

Heterogeneities such as point defects, inherent to material systems, can profoundly influence material functionalities critical for numerous energy applications. This influence in principle can be identified and quantified through development of large defect data sets which we call the defect genome, employing high-throughput ab initio calculations. However, high-throughput screening of material models with point defects dramatically increases the computational complexity and chemical search space, creating major impediments toward developing a defect genome. In this paper, we overcome these impediments by employing computationally tractable ab initio models driven by highly scalable workflows, to study formation and interaction of various point defectsmore » (e.g., O vacancies, H interstitials, and Y substitutional dopant), in over 80 cubic perovskites, for potential proton-conducting ceramic fuel cell (PCFC) applications. The resulting defect data sets identify several promising perovskite compounds that can exhibit high proton conductivity. Furthermore, the data sets also enable us to identify and explain, insightful and novel correlations among defect energies, material identities, and defect-induced local structural distortions. Finally, such defect data sets and resultant correlations are necessary to build statistical machine learning models, which are required to accelerate discovery of new materials.« less

Defect Genome of Cubic Perovskites for Fuel Cell Applications

DOE PAGES

Balachandran, Janakiraman; Lin, Lianshan; Anchell, Jonathan S.; ...

2017-10-10

Heterogeneities such as point defects, inherent to material systems, can profoundly influence material functionalities critical for numerous energy applications. This influence in principle can be identified and quantified through development of large defect data sets which we call the defect genome, employing high-throughput ab initio calculations. However, high-throughput screening of material models with point defects dramatically increases the computational complexity and chemical search space, creating major impediments toward developing a defect genome. In this paper, we overcome these impediments by employing computationally tractable ab initio models driven by highly scalable workflows, to study formation and interaction of various point defectsmore » (e.g., O vacancies, H interstitials, and Y substitutional dopant), in over 80 cubic perovskites, for potential proton-conducting ceramic fuel cell (PCFC) applications. The resulting defect data sets identify several promising perovskite compounds that can exhibit high proton conductivity. Furthermore, the data sets also enable us to identify and explain, insightful and novel correlations among defect energies, material identities, and defect-induced local structural distortions. Finally, such defect data sets and resultant correlations are necessary to build statistical machine learning models, which are required to accelerate discovery of new materials.« less

Theory and experimental validation of SPLASH (Single Panel Lamp and Shroud Helper).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, Marvin Elwood; Porter, Jason M.

2005-06-01

The radiant heat test facility develops test sets providing well-characterized thermal environments, often representing fires. Many of the components and procedures have become standardized to such an extent that the development of a specialized design tool was appropriate. SPLASH (Single Panel Lamp and Shroud Helper) is that tool. SPLASH is implemented as a user-friendly program that allows a designer to describe a test setup in terms of parameters such as lamp number, power, position, and separation distance. Thermal radiation is the dominant mechanism of heat transfer and the SPLASH model solves a radiation enclosure problem to estimate temperature distributions inmore » a shroud providing the boundary condition of interest. Irradiance distribution on a specified viewing plane is also estimated. This document provides the theoretical development for the underlying model. A series of tests were conducted to characterize SPLASH's ability to analyze lamp and shroud systems. The comparison suggests that SPLASH succeeds as a design tool. Simplifications made to keep the model tractable are demonstrated to result in estimates that are only approximately as uncertain as many of the properties and characteristics of the operating environment.« less

Rapid Genetic Analysis of Epithelial-Mesenchymal Signaling During Hair Regeneration

PubMed Central

Zhen, Hanson H.; Oro, Anthony E.

2013-01-01

Hair follicle morphogenesis, a complex process requiring interaction between epithelia-derived keratinocytes and the underlying mesenchyme, is an attractive model system to study organ development and tissue-specific signaling. Although hair follicle development is genetically tractable, fast and reproducible analysis of factors essential for this process remains a challenge. Here we describe a procedure to generate targeted overexpression or shRNA-mediated knockdown of factors using lentivirus in a tissue-specific manner. Using a modified version of a hair regeneration model 5, 6, 11, we can achieve robust gain- or loss-of-function analysis in primary mouse keratinocytes or dermal cells to facilitate study of epithelial-mesenchymal signaling pathways that lead to hair follicle morphogenesis. We describe how to isolate fresh primary mouse keratinocytes and dermal cells, which contain dermal papilla cells and their precursors, deliver lentivirus containing either shRNA or cDNA to one of the cell populations, and combine the cells to generate fully formed hair follicles on the backs of nude mice. This approach allows analysis of tissue-specific factors required to generate hair follicles within three weeks and provides a fast and convenient companion to existing genetic models. PMID:23486463

A novel mode of induction of the humoral innate immune response in Drosophila larvae

PubMed Central

Kenmoku, Hiroyuki

2017-01-01

ABSTRACT Drosophila adults have been utilized as a genetically tractable model organism to decipher the molecular mechanisms of humoral innate immune responses. In an effort to promote the utility of Drosophila larvae as an additional model system, in this study, we describe a novel aspect of an induction mechanism for innate immunity in these larvae. By using a fine tungsten needle created for manipulating semi-conductor devices, larvae were subjected to septic injury. However, although Toll pathway mutants were susceptible to infection with Gram-positive bacteria as had been shown for Drosophila adults, microbe clearance was not affected in the mutants. In addition, Drosophila larvae were found to be sensitive to mechanical stimuli with respect to the activation of a sterile humoral response. In particular, pinching with forceps to a degree that might cause minor damage to larval tissues could induce the expression of the antifungal peptide gene Drosomycin; notably, this induction was partially independent of the Toll and immune deficiency pathways. We therefore propose that Drosophila larvae might serve as a useful model to analyze the infectious and non-infectious inflammation that underlies various inflammatory diseases such as ischemia, atherosclerosis and cancer. PMID:28250052

A novel mode of induction of the humoral innate immune response in Drosophila larvae.

PubMed

Kenmoku, Hiroyuki; Hori, Aki; Kuraishi, Takayuki; Kurata, Shoichiro

2017-03-01

Drosophila adults have been utilized as a genetically tractable model organism to decipher the molecular mechanisms of humoral innate immune responses. In an effort to promote the utility of Drosophila larvae as an additional model system, in this study, we describe a novel aspect of an induction mechanism for innate immunity in these larvae. By using a fine tungsten needle created for manipulating semi-conductor devices, larvae were subjected to septic injury. However, although Toll pathway mutants were susceptible to infection with Gram-positive bacteria as had been shown for Drosophila adults, microbe clearance was not affected in the mutants. In addition, Drosophila larvae were found to be sensitive to mechanical stimuli with respect to the activation of a sterile humoral response. In particular, pinching with forceps to a degree that might cause minor damage to larval tissues could induce the expression of the antifungal peptide gene Drosomycin ; notably, this induction was partially independent of the Toll and immune deficiency pathways. We therefore propose that Drosophila larvae might serve as a useful model to analyze the infectious and non-infectious inflammation that underlies various inflammatory diseases such as ischemia, atherosclerosis and cancer. © 2017. Published by The Company of Biologists Ltd.

Transient probabilities for queues with applications to hospital waiting list management.

PubMed

Joy, Mark; Jones, Simon

2005-08-01

In this paper we study queuing systems within the NHS. Recently imposed government performance targets lead NHS executives to investigate and instigate alternative management strategies, thereby imposing structural changes on the queues. Under such circumstances, it is most unlikely that such systems are in equilibrium. It is crucial, in our opinion, to recognise this state of affairs in order to make a balanced assessment of the role of queue management in the modern NHS. From a mathematical perspective it should be emphasised that measures of the state of a queue based upon the assumption of statistical equilibrium (a pervasive methodology in the study of queues) are simply wrong in the above scenario. To base strategic decisions around such ideas is therefore highly questionable and it is one of the purposes of this paper to offer alternatives: we present some (recent) research whose results generate performance measures and measures of risk, for example, of waiting-times growing unacceptably large; we emphasise that these results concern the transient behaviour of the queueing model-there is no asssumption of statistical equilibrium. We also demonstrate that our results are computationally tractable.

Spontaneous emergence of autocatalytic information-coding polymers

DOE PAGES

Tkachenko, Alexei V.; Maslov, Sergei

2015-07-28

Self-replicating systems based on information-coding polymers are of crucial importance in biology. They also recently emerged as a paradigm in material design on nano- and micro-scales. We present a general theoretical and numerical analysis of the problem of spontaneous emergence of autocatalysis for heteropolymers capable of template-assisted ligation driven by cyclic changes in the environment. Our central result is the existence of the first order transition between the regime dominated by free monomers and that with a self-sustaining population of sufficiently long chains. We provide a simple, mathematically tractable model supported by numerical simulations, which predicts the distribution of chainmore » lengths and the onset of autocatalysis in terms of the overall monomer concentration and two fundamental rate constants. Another key result of our study is the emergence of the kinetically limited optimal overlap length between a template and each of its two substrates. The template-assisted ligation allows for heritable transmission of the information encoded in chain sequences thus opening up the possibility of long-term memory and evolvability in such systems.« less

Spontaneous emergence of autocatalytic information-coding polymers

NASA Astrophysics Data System (ADS)

Tkachenko, Alexei V.; Maslov, Sergei

2015-07-01

Self-replicating systems based on information-coding polymers are of crucial importance in biology. They also recently emerged as a paradigm in material design on nano- and micro-scales. We present a general theoretical and numerical analysis of the problem of spontaneous emergence of autocatalysis for heteropolymers capable of template-assisted ligation driven by cyclic changes in the environment. Our central result is the existence of the first order transition between the regime dominated by free monomers and that with a self-sustaining population of sufficiently long chains. We provide a simple, mathematically tractable model supported by numerical simulations, which predicts the distribution of chain lengths and the onset of autocatalysis in terms of the overall monomer concentration and two fundamental rate constants. Another key result of our study is the emergence of the kinetically limited optimal overlap length between a template and each of its two substrates. The template-assisted ligation allows for heritable transmission of the information encoded in chain sequences thus opening up the possibility of long-term memory and evolvability in such systems.

GLUT3 gene expression is critical for embryonic growth, brain development and survival.

PubMed

Carayannopoulos, Mary O; Xiong, Fuxia; Jensen, Penny; Rios-Galdamez, Yesenia; Huang, Haigen; Lin, Shuo; Devaskar, Sherin U

2014-04-01

Glucose is the primary energy source for eukaryotic cells and the predominant substrate for the brain. GLUT3 is essential for trans-placental glucose transport and highly expressed in the mammalian brain. To further elucidate the role of GLUT3 in embryonic development, we utilized the vertebrate whole animal model system of Danio rerio as a tractable system for defining the cellular and molecular mechanisms altered by impaired glucose transport and metabolism related to perturbed expression of GLUT3. The comparable orthologue of human GLUT3 was identified and the expression of this gene abrogated during early embryonic development. In a dose-dependent manner embryonic brain development was disrupted resulting in a phenotype of aberrant brain organogenesis, associated with embryonic growth restriction and increased cellular apoptosis. Rescue of the morphant phenotype was achieved by providing exogenous GLUT3 mRNA. We conclude that GLUT3 is critically important for brain organogenesis and embryonic growth. Disruption of GLUT3 is responsible for the phenotypic spectrum of embryonic growth restriction to demise and neural apoptosis with microcephaly. Copyright © 2014 Elsevier Inc. All rights reserved.

Synergy among Microbiota and Their Hosts: Leveraging the Hawaiian Archipelago and Local Collaborative Networks To Address Pressing Questions in Microbiome Research

PubMed Central

Frank, Kiana L.; Alegado, Rosanna A.; Amend, Anthony S.; Arif, Mohammad; Bennett, Gordon M.; Jani, Andrea J.; Medeiros, Matthew C. I.; Mileyko, Yuriy; Nguyen, Nhu H.; Nigro, Olivia D.; Prisic, Sladjana; Shin, Sangwoo; Takagi, Daisuke; Wilson, Samuel T.; Yew, Joanne Y.

2018-01-01

ABSTRACT Despite increasing acknowledgment that microorganisms underpin the healthy functioning of basically all multicellular life, few cross-disciplinary teams address the diversity and function of microbiota across organisms and ecosystems. Our newly formed consortium of junior faculty spanning fields such as ecology and geoscience to mathematics and molecular biology from the University of Hawai‘i at Mānoa aims to fill this gap. We are united in our mutual interest in advancing a new paradigm for biology that incorporates our modern understanding of the importance of microorganisms. As our first concerted research effort, we will assess the diversity and function of microbes across an entire watershed on the island of Oahu, Hawai‘i. Due to its high ecological diversity across tractable areas of land and sea, Hawai‘i provides a model system for the study of complex microbial communities and the processes they mediate. Owing to our diverse expertise, we will leverage this study system to advance the field of biology. PMID:29556540

GLUT3 Gene Expression is Critical for Embryonic Growth, Brain Development and Survival

PubMed Central

Carayannopoulos, Mary O.; Xiong, Fuxia; Jensen, Penny; Rios-Galdamez, Yesenia; Huang, Haigen; Lin, Shuo; Devaskar, Sherin U.

2015-01-01

Glucose is the primary energy source for eukaryotic cells and the predominant substrate for the brain. GLUT3 is essential for trans-placental glucose transport and highly expressed in the mammalian brain. To further elucidate the role of GLUT3 in embryonic development, we utilized the vertebrate whole animal model system of Danio rerio as a tractable system for defining the cellular and molecular mechanisms altered by impaired glucose transport and metabolism related to perturbed expression of GLUT3. The comparable orthologue of human GLUT3 was identified and the expression of this gene abrogated during early embryonic development. In a dose-dependent manner embryonic brain development was disrupted resulting in a phenotype of aberrant brain organogenesis, associated with embryonic growth restriction and increased cellular apoptosis. Rescue of the morphant phenotype was achieved by providing exogenous GLUT3 mRNA. We conclude that GLUT3 is critically important for brain organogenesis and embryonic growth. Disruption of GLUT3 is responsible for the phenotypic spectrum of embryonic growth restriction to demise and neural apoptosis with microcephaly. PMID:24529979

Coordinated Scheduling for Interdependent Electric Power and Natural Gas Infrastructures

DOE PAGES

Zlotnik, Anatoly; Roald, Line; Backhaus, Scott; ...

2016-03-24

The extensive installation of gas-fired power plants in many parts of the world has led electric systems to depend heavily on reliable gas supplies. The use of gas-fired generators for peak load and reserve provision causes high intraday variability in withdrawals from high-pressure gas transmission systems. Such variability can lead to gas price fluctuations and supply disruptions that affect electric generator dispatch, electricity prices, and threaten the security of power systems and gas pipelines. These infrastructures function on vastly different spatio-temporal scales, which prevents current practices for separate operations and market clearing from being coordinated. Here in this article, wemore » apply new techniques for control of dynamic gas flows on pipeline networks to examine day-ahead scheduling of electric generator dispatch and gas compressor operation for different levels of integration, spanning from separate forecasting, and simulation to combined optimal control. We formulate multiple coordination scenarios and develop tractable physically accurate computational implementations. These scenarios are compared using an integrated model of test networks for power and gas systems with 24 nodes and 24 pipes, respectively, which are coupled through gas-fired generators. The analysis quantifies the economic efficiency and security benefits of gas-electric coordination and dynamic gas system operation.« less

Luciferase-tagged wild-type and tropism-deficient mouse cytomegaloviruses reveal early dynamics of host colonization following peripheral challenge.

PubMed

Farrell, Helen; Oliveira, Martha; Macdonald, Kate; Yunis, Joseph; Mach, Michael; Bruce, Kimberley; Stevenson, Philip; Cardin, Rhonda; Davis-Poynter, Nicholas

2016-12-01

Cytomegaloviruses (CMVs) establish persistent, systemic infections and cause disease by maternal-foetal transfer, suggesting that their dissemination is a key target for antiviral intervention. Late clinical presentation has meant that human CMV (HCMV) dissemination is not well understood. Murine CMV (MCMV) provides a tractable model. Whole mouse imaging of virus-expressed luciferase has proved a useful way to track systemic infections. MCMV, in which the abundant lytic gene M78 was luciferase-tagged via a self-cleaving peptide (M78-LUC), allowed serial, unbiased imaging of systemic and peripheral infection without significant virus attenuation. Ex vivo luciferase imaging showed greater sensitivity than plaque assay, and revealed both well-known infection sites (the lungs, lymph nodes, salivary glands, liver, spleen and pancreas) and less explored sites (the bone marrow and upper respiratory tract). We applied luciferase imaging to tracking MCMV lacking M33, a chemokine receptor conserved in HCMV and a proposed anti-viral drug target. M33-deficient M78-LUC colonized normally in peripheral sites and local draining lymph nodes but spread poorly to the salivary gland, suggesting a defect in vascular transport consistent with properties of a chemokine receptor.

Development of Proteogenomic Approaches to Analyze the Role of Virus-Microbe Interactions in Shaping Natural Microbial Communities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banfield, Jillian; Breitbart, Mya; VerBerkmoes, Nathan

CRISPRs (clustered regularly interspaced short palindromic repeats) are adaptive immune systems in Bacteria and Archaea. Transcripts of the spacers that separate the repeats confer immunity through sequence identity with a targeted region (proto-spacer) in phage/viral, plasmid, or other foreign DNA. Short sequences immediately flanking the proto-spacer (proto-spacer adjacent motifs—PAMs) are important in both procuring spacers from and providing immunity to targeted sequences. New spacers are incorporated unidirectionally at the leader end of the CRISPR loci, thus recording a timeline of recent viral exposure. In the early phase of our research, we documented extremely rapid diversification of the CRISPR loci inmore » natural populations [Tyson and Banfield, 2008] matched by high levels of sequence variation in natural viral populations [Andersson and Banfield, 2008]. Since then, in a genetically tractable model laboratory system, we have 1) tracked phage mutation and CRISPR diversification, and in a natural model system, we have 2) examined population history via over time, 3) investigated the timescale over which spacers become ineffective and the process by which ineffective spacers are removed, and 4) analyzed viral diversity. In addition to research activities, our group has organized five international CRISPR meetings, the fifth to be held at University of California, Berkeley in June 2012. Most importantly, the project provided the majority of funding support for Christine Sun (Ph.D. 2012).« less

Linking micro- and macro-evolution at the cell type level: a view from the lophotrochozoan Platynereis dumerilii.

PubMed

Simakov, Oleg; Larsson, Tomas A; Arendt, Detlev

2013-09-01

Ever since the origin of the first metazoans over 600 million years ago, cell type diversification has been driven by micro-evolutionary processes at population level, leading to macro-evolution changes above species level. In this review, we introduce the marine annelid Platynereis dumerilii, a member of the lophotrochozoan clade (a key yet most understudied superphylum of bilaterians), as a suitable model system for the simultaneous study, at cellular resolution, of macro-evolutionary processes across phyla and of micro-evolutionary processes across highly polymorphic populations collected worldwide. Recent advances in molecular and experimental techniques, easy maintenance and breeding, and the fast, synchronous and stereotypical development have facilitated the establishment of Platynereis as one of the leading model species in the eco-evo-devo field. Most importantly, Platynereis allows the combination of expression profiling, morphological and physiological characterization at the single cell level. Here, we discuss recent advances in the collection of -omics data for the lab strain and for natural populations collected world-wide that can be integrated with population-specific cellular analyses to result in a cellular atlas integrating genetic, phenotypic and ecological variation. This makes Platynereis a tractable system to begin understanding the interplay between macro- and micro-evolutionary processes and cell type diversity.

Normalized Shape and Location of Perturbed Craniofacial Structures in the Xenopus Tadpole Reveal an Innate Ability to Achieve Correct Morphology

PubMed Central

Vandenberg, Laura N.; Adams, Dany S.; Levin, Michael

2012-01-01

Background Embryonic development can often adjust its morphogenetic processes to counteract external perturbation. The existence of self-monitoring responses during pattern formation is of considerable importance to the biomedicine of birth defects, but has not been quantitatively addressed. To understand the computational capabilities of biological tissues in a molecularly-tractable model system, we induced craniofacial defects in Xenopus embryos, then tracked tadpoles with craniofacial deformities and used geometric morphometric techniques to characterize changes in the shape and position of the craniofacial structures. Results Canonical variate analysis revealed that the shapes and relative positions of perturbed jaws and branchial arches were corrected during the first few months of tadpole development. Analysis of the relative movements of the anterior-most structures indicates that misplaced structures move along the anterior-posterior and left-right axes in ways that are significantly different from their normal movements. Conclusions Our data suggest a model in which craniofacial structures utilize a measuring mechanism to assess and adjust their location relative to other local organs. Understanding the correction mechanisms at work in this system could lead to the better understanding of the adaptive decision-making capabilities of living tissues and suggest new approaches to correct birth defects in humans. PMID:22411736

The costs of uncoordinated infrastructure management in multi-reservoir river basins

NASA Astrophysics Data System (ADS)

Jeuland, Marc; Baker, Justin; Bartlett, Ryan; Lacombe, Guillaume

2014-10-01

Though there are surprisingly few estimates of the economic benefits of coordinated infrastructure development and operations in international river basins, there is a widespread belief that improved cooperation is beneficial for managing water scarcity and variability. Hydro-economic optimization models are commonly-used for identifying efficient allocation of water across time and space, but such models typically assume full coordination. In the real world, investment and operational decisions for specific projects are often made without full consideration of potential downstream impacts. This paper describes a tractable methodology for evaluating the economic benefits of infrastructure coordination. We demonstrate its application over a range of water availability scenarios in a catchment of the Mekong located in Lao PDR, the Nam Ngum River Basin. Results from this basin suggest that coordination improves system net benefits from irrigation and hydropower by approximately 3-12% (or US12-53 million/yr) assuming moderate levels of flood control, and that the magnitude of coordination benefits generally increases with the level of water availability and with inflow variability. Similar analyses would be useful for developing a systematic understanding of the factors that increase the costs of non-cooperation in river basin systems worldwide, and would likely help to improve targeting of efforts to stimulate complicated negotiations over water resources.

A Computational Model Predicting Disruption of Blood Vessel Development

PubMed Central

Kleinstreuer, Nicole; Dix, David; Rountree, Michael; Baker, Nancy; Sipes, Nisha; Reif, David; Spencer, Richard; Knudsen, Thomas

2013-01-01

Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a variety of biological pathways linked to endothelial cell (EC) behavior, extracellular matrix (ECM) remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA's ToxCast high-throughput screening (HTS) dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a morphogenetic series of events and for the first time demonstrate the applicability of these models for predictive toxicology. PMID:23592958

Emulation of recharge and evapotranspiration processes in shallow groundwater systems

NASA Astrophysics Data System (ADS)

Doble, Rebecca C.; Pickett, Trevor; Crosbie, Russell S.; Morgan, Leanne K.; Turnadge, Chris; Davies, Phil J.

2017-12-01

In shallow groundwater systems, recharge and evapotranspiration are highly sensitive to changes in the depth to water table. To effectively model these fluxes, complex functions that include soil and vegetation properties are often required. Model emulation (surrogate modelling or meta-modelling) can provide a means of incorporating detailed conceptualisation of recharge and evapotranspiration processes, while maintaining the numerical tractability and computational performance required for regional scale groundwater models and uncertainty analysis. A method for emulating recharge and evapotranspiration processes in groundwater flow models was developed, and applied to the South East region of South Australia and western Victoria, which is characterised by shallow groundwater, wetlands and coastal lakes. The soil-vegetation-atmosphere transfer (SVAT) model WAVES was used to generate relationships between net recharge (diffuse recharge minus evapotranspiration from groundwater) and depth to water table for different combinations of climate, soil and land cover types. These relationships, which mimicked previously described soil, vegetation and groundwater behaviour, were combined into a net recharge lookup table. The segmented evapotranspiration package in MODFLOW was adapted to select values of net recharge from the lookup table depending on groundwater depth, and the climate, soil and land use characteristics of each cell. The model was found to be numerically robust in steady state testing, had no major increase in run time, and would be more efficient than tightly-coupled modelling approaches. It made reasonable predictions of net recharge and groundwater head compared with remotely sensed estimates of net recharge and a standard MODFLOW comparison model. In particular, the method was better able to predict net recharge and groundwater head in areas with steep hydraulic gradients.

Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach

PubMed Central

Henriques, David; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R.

2015-01-01

Motivation: Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters. Results: In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cells. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: julio@iim.csic.es or saezrodriguez@ebi.ac.uk PMID:26002881

Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach.

PubMed

Henriques, David; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R

2015-09-15

Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters. In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cells. Supplementary data are available at Bioinformatics online. julio@iim.csic.es or saezrodriguez@ebi.ac.uk. © The Author 2015. Published by Oxford University Press.

Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

PubMed

Guikema, Seth

2012-07-01

Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

Amblypygids: Model Organisms for the Study of Arthropod Navigation Mechanisms in Complex Environments?

PubMed Central

Wiegmann, Daniel D.; Hebets, Eileen A.; Gronenberg, Wulfila; Graving, Jacob M.; Bingman, Verner P.

2016-01-01

Navigation is an ideal behavioral model for the study of sensory system integration and the neural substrates associated with complex behavior. For this broader purpose, however, it may be profitable to develop new model systems that are both tractable and sufficiently complex to ensure that information derived from a single sensory modality and path integration are inadequate to locate a goal. Here, we discuss some recent discoveries related to navigation by amblypygids, nocturnal arachnids that inhabit the tropics and sub-tropics. Nocturnal displacement experiments under the cover of a tropical rainforest reveal that these animals possess navigational abilities that are reminiscent, albeit on a smaller spatial scale, of true-navigating vertebrates. Specialized legs, called antenniform legs, which possess hundreds of olfactory and tactile sensory hairs, and vision appear to be involved. These animals also have enormous mushroom bodies, higher-order brain regions that, in insects, integrate contextual cues and may be involved in spatial memory. In amblypygids, the complexity of a nocturnal rainforest may impose navigational challenges that favor the integration of information derived from multimodal cues. Moreover, the movement of these animals is easily studied in the laboratory and putative neural integration sites of sensory information can be manipulated. Thus, amblypygids could serve as model organisms for the discovery of neural substrates associated with a unique and potentially sophisticated navigational capability. The diversity of habitats in which amblypygids are found also offers an opportunity for comparative studies of sensory integration and ecological selection pressures on navigation mechanisms. PMID:27014008

Modeling walker synchronization on the Millennium Bridge.

PubMed

Eckhardt, Bruno; Ott, Edward; Strogatz, Steven H; Abrams, Daniel M; McRobie, Allan

2007-02-01

On its opening day the London Millennium footbridge experienced unexpected large amplitude wobbling subsequent to the migration of pedestrians onto the bridge. Modeling the stepping of the pedestrians on the bridge as phase oscillators, we obtain a model for the combined dynamics of people and the bridge that is analytically tractable. It provides predictions for the phase dynamics of individual walkers and for the critical number of people for the onset of oscillations. Numerical simulations and analytical estimates reproduce the linear relation between pedestrian force and bridge velocity as observed in experiments. They allow prediction of the amplitude of bridge motion, the rate of relaxation to the synchronized state and the magnitude of the fluctuations due to a finite number of people.

X-ray Raman scattering from molecules and solids in the framework of the Mahan-Nozières-De Dominicis model

NASA Astrophysics Data System (ADS)

Privalov, Timofei; Gel'mukhanov, Faris; Ågren, Hans

2001-10-01

We have developed a formulation of resonant x-ray Raman scattering of molecules and solids based on the Mahan-Nozières-De Dominicis model. A key step in the formulation is given by a reduction of the Keldysh-Dyson equations for the Green's function to a set of linear algebraic equations. This gave way for a tractable scheme that can be used to analyze the resonant x-ray scattering in the whole time domain. The formalism is used to investigate the role of core-hole relaxation, interference, band filling, detuning, and size of the scattering target. Numerical applications are performed with a one-dimensional tight-binding model.

Flavor instabilities in the neutrino line model

NASA Astrophysics Data System (ADS)

Duan, Huaiyu; Shalgar, Shashank

2015-07-01

A dense neutrino medium can experience collective flavor oscillations through nonlinear neutrino-neutrino refraction. To make this multi-dimensional flavor transport problem more tractable, all existing studies have assumed certain symmetries (e.g., the spatial homogeneity and directional isotropy in the early universe) to reduce the dimensionality of the problem. In this work we show that, if both the directional and spatial symmetries are not enforced in the neutrino line model, collective oscillations can develop in the physical regimes where the symmetry-preserving oscillation modes are stable. Our results suggest that collective neutrino oscillations in real astrophysical environments (such as core-collapse supernovae and black-hole accretion discs) can be qualitatively different from the predictions based on existing models in which spatial and directional symmetries are artificially imposed.

Structural modeling of Ge6.25As32.5Se61.25 using a combination of reverse Monte Carlo and Ab initio molecular dynamics.

PubMed

Opletal, George; Drumm, Daniel W; Wang, Rong P; Russo, Salvy P

2014-07-03

Ternary glass structures are notoriously difficult to model accurately, and yet prevalent in several modern endeavors. Here, a novel combination of Reverse Monte Carlo (RMC) modeling and ab initio molecular dynamics (MD) is presented, rendering these complicated structures computationally tractable. A case study (Ge6.25As32.5Se61.25 glass) illustrates the effects of ab initio MD quench rates and equilibration temperatures, and the combined approach's efficacy over standard RMC or random insertion methods. Submelting point MD quenches achieve the most stable, realistic models, agreeing with both experimental and fully ab initio results. The simple approach of RMC followed by ab initio geometry optimization provides similar quality to the RMC-MD combination, for far fewer resources.

A Model for Simulating the Response of Aluminum Honeycomb Structure to Transverse Loading

NASA Technical Reports Server (NTRS)

Ratcliffe, James G.; Czabaj, Michael W.; Jackson, Wade C.

2012-01-01

A 1-dimensional material model was developed for simulating the transverse (thickness-direction) loading and unloading response of aluminum honeycomb structure. The model was implemented as a user-defined material subroutine (UMAT) in the commercial finite element analysis code, ABAQUS(Registered TradeMark)/Standard. The UMAT has been applied to analyses for simulating quasi-static indentation tests on aluminum honeycomb-based sandwich plates. Comparison of analysis results with data from these experiments shows overall good agreement. Specifically, analyses of quasi-static indentation tests yielded accurate global specimen responses. Predicted residual indentation was also in reasonable agreement with measured values. Overall, this simple model does not involve a significant computational burden, which makes it more tractable to simulate other damage mechanisms in the same analysis.

A Murine Model for Escherichia coli Urinary Tract Infection.

PubMed

Hannan, Thomas J; Hunstad, David A

2016-01-01

Urinary tract infections (UTI) are among the most common bacterial infections of humans. The mouse provides an excellent and tractable model system for cystitis and pyelonephritis caused by Escherichia coli and other uropathogens. Using a well-established model of experimental cystitis in which the bladders of female mice are infected via transurethral catheterization, the molecular details of the pathogenesis of bacterial cystitis have been substantially illuminated in the last decade. Uropathogenic E. coli attach to bladder epithelium (both in human and mouse) via adhesive type 1 pili, establish a replicative niche within epithelial cell cytoplasm, and form intracellular bacterial communities that are protected from antibiotic effects and immune clearance. The use of different inbred and mutant mouse strains offers the opportunity to study outcomes of infection, including resolution, formation of quiescent intracellular bacterial reservoirs, chronic bacterial cystitis, and recurrent infections. Urine, bladder, and kidney tissues can be analyzed by bacterial culture, histology, immunohistochemistry, immunofluorescent and confocal microscopy, electron microscopy, and flow cytometry, while a broad array of soluble markers (e.g., cytokines) can also be profiled in serum, urine, and tissue homogenates by ELISA, Western blotting, multiplex bead array, and other approaches. This model promises to afford continued opportunity for discovery of pathogenic mechanisms and evaluation of therapeutic and preventive strategies for acute, chronic, and recurrent UTI.

Balancing selfishness and norm conformity can explain human behavior in large-scale prisoner's dilemma games and can poise human groups near criticality

NASA Astrophysics Data System (ADS)

Realpe-Gómez, John; Andrighetto, Giulia; Nardin, Luis Gustavo; Montoya, Javier Antonio

2018-04-01

Cooperation is central to the success of human societies as it is crucial for overcoming some of the most pressing social challenges of our time; still, how human cooperation is achieved and may persist is a main puzzle in the social and biological sciences. Recently, scholars have recognized the importance of social norms as solutions to major local and large-scale collective action problems, from the management of water resources to the reduction of smoking in public places to the change in fertility practices. Yet a well-founded model of the effect of social norms on human cooperation is still lacking. Using statistical-physics techniques and integrating findings from cognitive and behavioral sciences, we present an analytically tractable model in which individuals base their decisions to cooperate both on the economic rewards they obtain and on the degree to which their action complies with social norms. Results from this parsimonious model are in agreement with observations in recent large-scale experiments with humans. We also find the phase diagram of the model and show that the experimental human group is poised near a critical point, a regime where recent work suggests living systems respond to changing external conditions in an efficient and coordinated manner.

Novel symmetries in N=2 supersymmetric quantum mechanical models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malik, R.P., E-mail: malik@bhu.ac.in; DST-CIMS, Faculty of Science, BHU-Varanasi-221 005; Khare, Avinash, E-mail: khare@iiserpune.ac.in

We demonstrate the existence of a novel set of discrete symmetries in the context of the N=2 supersymmetric (SUSY) quantum mechanical model with a potential function f(x) that is a generalization of the potential of the 1D SUSY harmonic oscillator. We perform the same exercise for the motion of a charged particle in the X–Y plane under the influence of a magnetic field in the Z-direction. We derive the underlying algebra of the existing continuous symmetry transformations (and corresponding conserved charges) and establish its relevance to the algebraic structures of the de Rham cohomological operators of differential geometry. We showmore » that the discrete symmetry transformations of our present general theories correspond to the Hodge duality operation. Ultimately, we conjecture that any arbitrary N=2 SUSY quantum mechanical system can be shown to be a tractable model for the Hodge theory. -- Highlights: •Discrete symmetries of two completely different kinds of N=2 supersymmetric quantum mechanical models have been discussed. •The discrete symmetries provide physical realizations of Hodge duality. •The continuous symmetries provide the physical realizations of de Rham cohomological operators. •Our work sheds a new light on the meaning of the above abstract operators.« less

Conditional random matrix ensembles and the stability of dynamical systems

NASA Astrophysics Data System (ADS)

Kirk, Paul; Rolando, Delphine M. Y.; MacLean, Adam L.; Stumpf, Michael P. H.

2015-08-01

Random matrix theory (RMT) has found applications throughout physics and applied mathematics, in subject areas as diverse as communications networks, population dynamics, neuroscience, and models of the banking system. Many of these analyses exploit elegant analytical results, particularly the circular law and its extensions. In order to apply these results, assumptions must be made about the distribution of matrix elements. Here we demonstrate that the choice of matrix distribution is crucial. In particular, adopting an unrealistic matrix distribution for the sake of analytical tractability is liable to lead to misleading conclusions. We focus on the application of RMT to the long-standing, and at times fractious, ‘diversity-stability debate’, which is concerned with establishing whether large complex systems are likely to be stable. Early work (and subsequent elaborations) brought RMT to bear on the debate by modelling the entries of a system’s Jacobian matrix as independent and identically distributed (i.i.d.) random variables. These analyses were successful in yielding general results that were not tied to any specific system, but relied upon a restrictive i.i.d. assumption. Other studies took an opposing approach, seeking to elucidate general principles of stability through the analysis of specific systems. Here we develop a statistical framework that reconciles these two contrasting approaches. We use a range of illustrative dynamical systems examples to demonstrate that: (i) stability probability cannot be summarily deduced from any single property of the system (e.g. its diversity); and (ii) our assessment of stability depends on adequately capturing the details of the systems analysed. Failing to condition on the structure of dynamical systems will skew our analysis and can, even for very small systems, result in an unnecessarily pessimistic diagnosis of their stability.

Modelling Creativity: Identifying Key Components through a Corpus-Based Approach

PubMed Central

2016-01-01

Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research. PMID:27706185

Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor.

PubMed

Reed, Sasha C; Yang, Xiaojuan; Thornton, Peter E

2015-10-01

324 I. 324 II. 325 III. 326 IV. 327 328 References 328 SUMMARY: Myriad field, laboratory, and modeling studies show that nutrient availability plays a fundamental role in regulating CO2 exchange between the Earth's biosphere and atmosphere, and in determining how carbon pools and fluxes respond to climatic change. Accordingly, global models that incorporate coupled climate-carbon cycle feedbacks made a significant advance with the introduction of a prognostic nitrogen cycle. Here we propose that incorporating phosphorus cycling represents an important next step in coupled climate-carbon cycling model development, particularly for lowland tropical forests where phosphorus availability is often presumed to limit primary production. We highlight challenges to including phosphorus in modeling efforts and provide suggestions for how to move forward. No claim to original US government works New Phytologist © 2015 New Phytologist Trust.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradler, Kamil; Hayden, Patrick; Touchette, Dave

Coding theorems in quantum Shannon theory express the ultimate rates at which a sender can transmit information over a noisy quantum channel. More often than not, the known formulas expressing these transmission rates are intractable, requiring an optimization over an infinite number of uses of the channel. Researchers have rarely found quantum channels with a tractable classical or quantum capacity, but when such a finding occurs, it demonstrates a complete understanding of that channel's capabilities for transmitting classical or quantum information. Here we show that the three-dimensional capacity region for entanglement-assisted transmission of classical and quantum information is tractable formore » the Hadamard class of channels. Examples of Hadamard channels include generalized dephasing channels, cloning channels, and the Unruh channel. The generalized dephasing channels and the cloning channels are natural processes that occur in quantum systems through the loss of quantum coherence or stimulated emission, respectively. The Unruh channel is a noisy process that occurs in relativistic quantum information theory as a result of the Unruh effect and bears a strong relationship to the cloning channels. We give exact formulas for the entanglement-assisted classical and quantum communication capacity regions of these channels. The coding strategy for each of these examples is superior to a naieve time-sharing strategy, and we introduce a measure to determine this improvement.« less

Binary recursive partitioning: background, methods, and application to psychology.

PubMed

Merkle, Edgar C; Shaffer, Victoria A

2011-02-01

Binary recursive partitioning (BRP) is a computationally intensive statistical method that can be used in situations where linear models are often used. Instead of imposing many assumptions to arrive at a tractable statistical model, BRP simply seeks to accurately predict a response variable based on values of predictor variables. The method outputs a decision tree depicting the predictor variables that were related to the response variable, along with the nature of the variables' relationships. No significance tests are involved, and the tree's 'goodness' is judged based on its predictive accuracy. In this paper, we describe BRP methods in a detailed manner and illustrate their use in psychological research. We also provide R code for carrying out the methods.

Q&A: How do gene regulatory networks control environmental responses in plants?

PubMed

Sun, Ying; Dinneny, José R

2018-04-11

A gene regulatory network (GRN) describes the hierarchical relationship between transcription factors, associated proteins, and their target genes. Studying GRNs allows us to understand how a plant's genotype and environment are integrated to regulate downstream physiological responses. Current efforts in plants have focused on defining the GRNs that regulate functions such as development and stress response and have been performed primarily in genetically tractable model plant species such as Arabidopsis thaliana. Future studies will likely focus on how GRNs function in non-model plants and change over evolutionary time to allow for adaptation to extreme environments. This broader understanding will inform efforts to engineer GRNs to create tailored crop traits.

Planetary Dynamos

NASA Astrophysics Data System (ADS)

Gaur, Vinod K.

The article begins with a reference to the first rational approaches to explaining the earth's magnetic field notably Elsasser's application of magneto-hydrodynamics, followed by brief outlines of the characteristics of planetary magnetic fields and of the potentially insightful homopolar dynamo in illuminating the basic issues: theoretical requirements of asymmetry and finite conductivity in sustaining the dynamo process. It concludes with sections on Dynamo modeling and, in particular, the Geo-dynamo, but not before some of the evocative physical processes mediated by the Lorentz force and the behaviour of a flux tube embedded in a perfectly conducting fluid, using Alfvén theorem, are explained, as well as the traditional intermediate approaches to investigating dynamo processes using the more tractable Kinematic models.

Macrophage–Microbe Interactions: Lessons from the Zebrafish Model

PubMed Central

Yoshida, Nagisa; Frickel, Eva-Maria; Mostowy, Serge

2017-01-01

Macrophages provide front line defense against infections. The study of macrophage–microbe interplay is thus crucial for understanding pathogenesis and infection control. Zebrafish (Danio rerio) larvae provide a unique platform to study macrophage–microbe interactions in vivo, from the level of the single cell to the whole organism. Studies using zebrafish allow non-invasive, real-time visualization of macrophage recruitment and phagocytosis. Furthermore, the chemical and genetic tractability of zebrafish has been central to decipher the complex role of macrophages during infection. Here, we discuss the latest developments using zebrafish models of bacterial and fungal infection. We also review novel aspects of macrophage biology revealed by zebrafish, which can potentiate development of new therapeutic strategies for humans. PMID:29250076

Functional roles and metabolic niches in the honey bee gut microbiota.

PubMed

Bonilla-Rosso, Germán; Engel, Philipp

2018-06-01

Gut microbiota studies on diverse animals facilitate our understanding of the general principles governing microbiota-host interactions. The honey bee adds a relevant study system due to the simplicity and experimental tractability of its gut microbiota, but also because bees are important pollinators that suffer from population declines worldwide. The use of gnotobiotic bees combined with genetic tools, 'omics' analysis, and experimental microbiology has recently provided important insights about the impact of the microbiota on bee health and the general functioning of gut ecosystems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Landscape Encodings Enhance Optimization

PubMed Central

Klemm, Konstantin; Mehta, Anita; Stadler, Peter F.

2012-01-01

Hard combinatorial optimization problems deal with the search for the minimum cost solutions (ground states) of discrete systems under strong constraints. A transformation of state variables may enhance computational tractability. It has been argued that these state encodings are to be chosen invertible to retain the original size of the state space. Here we show how redundant non-invertible encodings enhance optimization by enriching the density of low-energy states. In addition, smooth landscapes may be established on encoded state spaces to guide local search dynamics towards the ground state. PMID:22496860

Distributed sensor networks: a cellular nonlinear network perspective.

PubMed

Haenggi, Martin

2003-12-01

Large-scale networks of integrated wireless sensors become increasingly tractable. Advances in hardware technology and engineering design have led to dramatic reductions in size, power consumption, and cost for digital circuitry, and wireless communications. Networking, self-organization, and distributed operation are crucial ingredients to harness the sensing, computing, and computational capabilities of the nodes into a complete system. This article shows that those networks can be considered as cellular nonlinear networks (CNNs), and that their analysis and design may greatly benefit from the rich theoretical results available for CNNs.

Frontiers in Fluid Mechanics: A Collection of Research Papers Written in Commemoration of the 65th Birthday of Stanley Corrsin.

DTIC Science & Technology

1985-04-30

analogous fashion. If the flow variable lFtis taken at x and F 6(xi,t) > d , - 1, . n, n > 1 is required, various subsets of the flow domain atare obtained...discussed: non-premixed and premixed combustion. The chemistry of combustion in the gas phase involves complex systems of reaction steps with numerous...components. In order to keep the problem tractable, only a greatly simplified and global description of chemistry will be employed. In both cases V

Micropublications: a semantic model for claims, evidence, arguments and annotations in biomedical communications

PubMed Central

2014-01-01

Background Scientific publications are documentary representations of defeasible arguments, supported by data and repeatable methods. They are the essential mediating artifacts in the ecosystem of scientific communications. The institutional “goal” of science is publishing results. The linear document publication format, dating from 1665, has survived transition to the Web. Intractable publication volumes; the difficulty of verifying evidence; and observed problems in evidence and citation chains suggest a need for a web-friendly and machine-tractable model of scientific publications. This model should support: digital summarization, evidence examination, challenge, verification and remix, and incremental adoption. Such a model must be capable of expressing a broad spectrum of representational complexity, ranging from minimal to maximal forms. Results The micropublications semantic model of scientific argument and evidence provides these features. Micropublications support natural language statements; data; methods and materials specifications; discussion and commentary; challenge and disagreement; as well as allowing many kinds of statement formalization. The minimal form of a micropublication is a statement with its attribution. The maximal form is a statement with its complete supporting argument, consisting of all relevant evidence, interpretations, discussion and challenges brought forward in support of or opposition to it. Micropublications may be formalized and serialized in multiple ways, including in RDF. They may be added to publications as stand-off metadata. An OWL 2 vocabulary for micropublications is available at http://purl.org/mp. A discussion of this vocabulary along with RDF examples from the case studies, appears as OWL Vocabulary and RDF Examples in Additional file 1. Conclusion Micropublications, because they model evidence and allow qualified, nuanced assertions, can play essential roles in the scientific communications ecosystem in places where simpler, formalized and purely statement-based models, such as the nanopublications model, will not be sufficient. At the same time they will add significant value to, and are intentionally compatible with, statement-based formalizations. We suggest that micropublications, generated by useful software tools supporting such activities as writing, editing, reviewing, and discussion, will be of great value in improving the quality and tractability of biomedical communications. PMID:26261718

Artificial activation of toxin-antitoxin systems as an antibacterial strategy.

PubMed

Williams, Julia J; Hergenrother, Paul J

2012-06-01

Toxin-antitoxin (TA) systems are unique modules that effect plasmid stabilization via post-segregational killing of the bacterial host. The genes encoding TA systems also exist on bacterial chromosomes, and it has been speculated that these are involved in a variety of cellular processes. Interest in TA systems has increased dramatically over the past 5 years as the ubiquitous nature of TA genes on bacterial genomes has been revealed. The exploitation of TA systems as an antibacterial strategy via artificial activation of the toxin has been proposed and has considerable potential; however, efforts in this area remain in the early stages and several major questions remain. This review investigates the tractability of targeting TA systems to kill bacteria, including fundamental requirements for success, recent advances, and challenges associated with artificial toxin activation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Generalizing Backtrack-Free Search: A Framework for Search-Free Constraint Satisfaction

NASA Technical Reports Server (NTRS)

Jonsson, Ari K.; Frank, Jeremy

2000-01-01

Tractable classes of constraint satisfaction problems are of great importance in artificial intelligence. Identifying and taking advantage of such classes can significantly speed up constraint problem solving. In addition, tractable classes are utilized in applications where strict worst-case performance guarantees are required, such as constraint-based plan execution. In this work, we present a formal framework for search-free (backtrack-free) constraint satisfaction. The framework is based on general procedures, rather than specific propagation techniques, and thus generalizes existing techniques in this area. We also relate search-free problem solving to the notion of decision sets and use the result to provide a constructive criterion that is sufficient to guarantee search-free problem solving.

The tracking performance of distributed recoverable flight control systems subject to high intensity radiated fields

NASA Astrophysics Data System (ADS)

Wang, Rui

It is known that high intensity radiated fields (HIRF) can produce upsets in digital electronics, and thereby degrade the performance of digital flight control systems. Such upsets, either from natural or man-made sources, can change data values on digital buses and memory and affect CPU instruction execution. HIRF environments are also known to trigger common-mode faults, affecting nearly-simultaneously multiple fault containment regions, and hence reducing the benefits of n-modular redundancy and other fault-tolerant computing techniques. Thus, it is important to develop models which describe the integration of the embedded digital system, where the control law is implemented, as well as the dynamics of the closed-loop system. In this dissertation, theoretical tools are presented to analyze the relationship between the design choices for a class of distributed recoverable computing platforms and the tracking performance degradation of a digital flight control system implemented on such a platform while operating in a HIRF environment. Specifically, a tractable hybrid performance model is developed for a digital flight control system implemented on a computing platform inspired largely by the NASA family of fault-tolerant, reconfigurable computer architectures known as SPIDER (scalable processor-independent design for enhanced reliability). The focus will be on the SPIDER implementation, which uses the computer communication system known as ROBUS-2 (reliable optical bus). A physical HIRF experiment was conducted at the NASA Langley Research Center in order to validate the theoretical tracking performance degradation predictions for a distributed Boeing 747 flight control system subject to a HIRF environment. An extrapolation of these results for scenarios that could not be physically tested is also presented.

Many-body theory of effective mass in degenerate semiconductors

NASA Astrophysics Data System (ADS)

Tripathi, G. S.; Shadangi, S. K.

2018-03-01

We derive the many-body theory of the effective mass in the effective mass representation (EMR). In the EMR, we need to solve the equation of motion of an electron in the presence of electron-electron interactions, where the wavefunction is expanded over a complete set of Luttinger-Kohn wavefunctions. We use the Luttinger-Ward thermodynamic potential and the Green’s function perturbation to derive an expression for the band effective mass by taking into account the electron-electron interactions. Both quasi-particle and the correlation contributions are considered. We show that had we considered only the quasi-particle contribution, we would have missed important cancellations. Thus the correlated motion of electrons has important effects in the renormalization of the effective mass. Considering the exchange self-energy in the band model, we derive a tractable expression for the band effective mass. We apply the theory to n-type degenerate semiconductors, PbTe and SnTe, and analyze the impact of the theory on the anisotropic effective mass of the conduction bands in these systems.

Plant Comparative and Functional Genomics

DOE PAGES

Yang, Xiaohan; Leebens-Mack, Jim; Chen, Feng; ...

2015-01-01

Plants form the foundation for our global ecosystem and are essential for environmental and human health. An increasing number of available plant genomes and tractable experimental systems, comparative and functional plant genomics research is greatly expanding our knowledge of the molecular basis of economically and nutritionally important traits in crop plants. Inferences drawn from comparative genomics are motivating experimental investigations of gene function and gene interactions. In this special issue aims to highlight recent advances made in comparative and functional genomics research in plants. Nine original research articles in this special issue cover five important topics: (1) transcription factor genemore » families relevant to abiotic stress tolerance; (2) plant secondary metabolism; (3) transcriptomebased markers for quantitative trait locus; (4) epigenetic modifications in plant-microbe interactions; and (5) computational prediction of protein-protein interactions. Finally, we studied the plant species in these articles which include model species as well as nonmodel plant species of economic importance (e.g., food crops and medicinal plants).« less

Plant Comparative and Functional Genomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaohan; Leebens-Mack, Jim; Chen, Feng

Plants form the foundation for our global ecosystem and are essential for environmental and human health. An increasing number of available plant genomes and tractable experimental systems, comparative and functional plant genomics research is greatly expanding our knowledge of the molecular basis of economically and nutritionally important traits in crop plants. Inferences drawn from comparative genomics are motivating experimental investigations of gene function and gene interactions. In this special issue aims to highlight recent advances made in comparative and functional genomics research in plants. Nine original research articles in this special issue cover five important topics: (1) transcription factor genemore » families relevant to abiotic stress tolerance; (2) plant secondary metabolism; (3) transcriptomebased markers for quantitative trait locus; (4) epigenetic modifications in plant-microbe interactions; and (5) computational prediction of protein-protein interactions. Finally, we studied the plant species in these articles which include model species as well as nonmodel plant species of economic importance (e.g., food crops and medicinal plants).« less

How input fluctuations reshape the dynamics of a biological switching system

NASA Astrophysics Data System (ADS)

Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

2012-12-01

An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

Knockout of Foxp2 disrupts vocal development in mice

PubMed Central

Castellucci, Gregg A.; McGinley, Matthew J.; McCormick, David A.

2016-01-01

The FOXP2 gene is important for the development of proper speech motor control in humans. However, the role of the gene in general vocal behavior in other mammals, including mice, is unclear. Here, we track the vocal development of Foxp2 heterozygous knockout (Foxp2+/−) mice and their wildtype (WT) littermates from juvenile to adult ages, and observe severe abnormalities in the courtship song of Foxp2+/− mice. In comparison to their WT littermates, Foxp2+/− mice vocalized less, produced shorter syllable sequences, and possessed an abnormal syllable inventory. In addition, Foxp2+/− song also exhibited irregular rhythmic structure, and its development did not follow the consistent trajectories observed in WT vocalizations. These results demonstrate that the Foxp2 gene is critical for normal vocal behavior in juvenile and adult mice, and that Foxp2 mutant mice may provide a tractable model system for the study of the gene’s role in general vocal motor control. PMID:26980647

Interspecific Germline Transmission of Cultured Primordial Germ Cells

PubMed Central

van de Lavoir, Marie-Cecile; Collarini, Ellen J.; Leighton, Philip A.; Fesler, Jeffrey; Lu, Daniel R.; Harriman, William D.; Thiyagasundaram, T. S.; Etches, Robert J.

2012-01-01

In birds, the primordial germ cell (PGC) lineage separates from the soma within 24 h following fertilization. Here we show that the endogenous population of about 200 PGCs from a single chicken embryo can be expanded one million fold in culture. When cultured PGCs are injected into a xenogeneic embryo at an equivalent stage of development, they colonize the testis. At sexual maturity, these donor PGCs undergo spermatogenesis in the xenogeneic host and become functional sperm. Insemination of semen from the xenogeneic host into females from the donor species produces normal offspring from the donor species. In our model system, the donor species is chicken (Gallus domesticus) and the recipient species is guinea fowl (Numida meleagris), a member of a different avian family, suggesting that the mechanisms controlling proliferation of the germline are highly conserved within birds. From a pragmatic perspective, these data are the basis of a novel strategy to produce endangered species of birds using domesticated hosts that are both tractable and fecund. PMID:22629301

A simple method for imaging axonal transport in aging neurons using the adult Drosophila wing.

PubMed

Vagnoni, Alessio; Bullock, Simon L

2016-09-01

There is growing interest in the link between axonal cargo transport and age-associated neuronal dysfunction. The study of axonal transport in neurons of adult animals requires intravital or ex vivo imaging approaches, which are laborious and expensive in vertebrate models. We describe simple, noninvasive procedures for imaging cargo motility within axons using sensory neurons of the translucent Drosophila wing. A key aspect is a method for mounting the intact fly that allows detailed imaging of transport in wing neurons. Coupled with existing genetic tools in Drosophila, this is a tractable system for studying axonal transport over the life span of an animal and thus for characterization of the relationship between cargo dynamics, neuronal aging and disease. Preparation of a sample for imaging takes ∼5 min, with transport typically filmed for 2-3 min per wing. We also document procedures for the quantification of transport parameters from the acquired images and describe how the protocol can be adapted to study other cell biological processes in aging neurons.

Jump state estimation with multiple sensors with packet dropping and delaying channels

NASA Astrophysics Data System (ADS)

Dolz, Daniel; Peñarrocha, Ignacio; Sanchis, Roberto

2016-03-01

This work addresses the design of a state observer for systems whose outputs are measured through a communication network. The measurements from each sensor node are assumed to arrive randomly, scarcely and with a time-varying delay. The proposed model of the plant and the network measurement scenarios cover the cases of multiple sensors, out-of-sequence measurements, buffered measurements on a single packet and multirate sensor measurements. A jump observer is proposed that selects a different gain depending on the number of periods elapsed between successfully received measurements and on the available data. A finite set of gains is pre-calculated offline with a tractable optimisation problem, where the complexity of the observer implementation is a design parameter. The computational cost of the observer implementation is much lower than in the Kalman filter, whilst the performance is similar. Several examples illustrate the observer design for different measurement scenarios and observer complexity and show the achievable performance.

Spatial analysis of extension fracture systems: A process modeling approach

USGS Publications Warehouse

Ferguson, C.C.

1985-01-01

Little consensus exists on how best to analyze natural fracture spacings and their sequences. Field measurements and analyses published in geotechnical literature imply fracture processes radically different from those assumed by theoretical structural geologists. The approach adopted in this paper recognizes that disruption of rock layers by layer-parallel extension results in two spacing distributions, one representing layer-fragment lengths and another separation distances between fragments. These two distributions and their sequences reflect mechanics and history of fracture and separation. Such distributions and sequences, represented by a 2 ?? n matrix of lengthsL, can be analyzed using a method that is history sensitive and which yields also a scalar estimate of bulk extension, e (L). The method is illustrated by a series of Monte Carlo experiments representing a variety of fracture-and-separation processes, each with distinct implications for extension history. Resulting distributions of e (L)are process-specific, suggesting that the inverse problem of deducing fracture-and-separation history from final structure may be tractable. ?? 1985 Plenum Publishing Corporation.

Multifractal vector fields and stochastic Clifford algebra.

PubMed

Schertzer, Daniel; Tchiguirinskaia, Ioulia

2015-12-01

In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge up the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schertzer, Daniel, E-mail: Daniel.Schertzer@enpc.fr; Tchiguirinskaia, Ioulia, E-mail: Ioulia.Tchiguirinskaia@enpc.fr

In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge upmore » the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.« less

Pluripotent stem cell-derived natural killer cells for cancer therapy

PubMed Central

Knorr, David A.; Kaufman, Dan S.

2010-01-01

Human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) provide an accessible, genetically tractable and homogenous starting cell populations to efficiently study human blood cell development. These cell populations provide platforms to develop new cell-based therapies to treat both malignant and non-malignant hematological diseases. Our group has previously demonstrated the ability of hESC-derived hematopoietic precursors to produce functional natural killer (NK) cells as well as an explanation of the underlying mechanism responsible for inefficient development of T and B cells from hESCs. hESCs and iPSCs, which can be reliably engineered in vitro, provide an important new model system to study human lymphocyte development and produce enhanced cell-based therapies with potential to serve as a “universal” source of anti-tumor lymphocytes for novel clinical therapies. This review will focus on the application of hESC-derived NK cells with currently used and novel therapeutics for clinical trials, current barriers to translation, and future applications through genetic engineering approaches. PMID:20801411

Systems aspects of COBE science data compression

NASA Technical Reports Server (NTRS)

Freedman, I.; Boggess, E.; Seiler, E.

1993-01-01

A general approach to compression of diverse data from large scientific projects has been developed and this paper addresses the appropriate system and scientific constraints together with the algorithm development and test strategy. This framework has been implemented for the COsmic Background Explorer spacecraft (COBE) by retrofitting the existing VAS-based data management system with high-performance compression software permitting random access to the data. Algorithms which incorporate scientific knowledge and consume relatively few system resources are preferred over ad hoc methods. COBE exceeded its planned storage by a large and growing factor and the retrieval of data significantly affects the processing, delaying the availability of data for scientific usage and software test. Embedded compression software is planned to make the project tractable by reducing the data storage volume to an acceptable level during normal processing.

A mass action model of a Fibroblast Growth Factor signaling pathway and its simplification.

PubMed

Gaffney, E A; Heath, J K; Kwiatkowska, M Z

2008-11-01

We consider a kinetic law of mass action model for Fibroblast Growth Factor (FGF) signaling, focusing on the induction of the RAS-MAP kinase pathway via GRB2 binding. Our biologically simple model suffers a combinatorial explosion in the number of differential equations required to simulate the system. In addition to numerically solving the full model, we show that it can be accurately simplified. This requires combining matched asymptotics, the quasi-steady state hypothesis, and the fact subsets of the equations decouple asymptotically. Both the full and simplified models reproduce the qualitative dynamics observed experimentally and in previous stochastic models. The simplified model also elucidates both the qualitative features of GRB2 binding and the complex relationship between SHP2 levels, the rate SHP2 induces dephosphorylation and levels of bound GRB2. In addition to providing insight into the important and redundant features of FGF signaling, such work further highlights the usefulness of numerous simplification techniques in the study of mass action models of signal transduction, as also illustrated recently by Borisov and co-workers (Borisov et al. in Biophys. J. 89, 951-966, 2005, Biosystems 83, 152-166, 2006; Kiyatkin et al. in J. Biol. Chem. 281, 19925-19938, 2006). These developments will facilitate the construction of tractable models of FGF signaling, incorporating further biological realism, such as spatial effects or realistic binding stoichiometries, despite a more severe combinatorial explosion associated with the latter.

The physical hydrogeology of ore deposits

USGS Publications Warehouse

Ingebritsen, Steven E.; Appold, M.S.

2012-01-01

Hydrothermal ore deposits represent a convergence of fluid flow, thermal energy, and solute flux that is hydrogeologically unusual. From the hydrogeologic perspective, hydrothermal ore deposition represents a complex coupled-flow problem—sufficiently complex that physically rigorous description of the coupled thermal (T), hydraulic (H), mechanical (M), and chemical (C) processes (THMC modeling) continues to challenge our computational ability. Though research into these coupled behaviors has found only a limited subset to be quantitatively tractable, it has yielded valuable insights into the workings of hydrothermal systems in a wide range of geologic environments including sedimentary, metamorphic, and magmatic. Examples of these insights include the quantification of likely driving mechanisms, rates and paths of fluid flow, ore-mineral precipitation mechanisms, longevity of hydrothermal systems, mechanisms by which hydrothermal fluids acquire their temperature and composition, and the controlling influence of permeability and other rock properties on hydrothermal fluid behavior. In this communication we review some of the fundamental theory needed to characterize the physical hydrogeology of hydrothermal systems and discuss how this theory has been applied in studies of Mississippi Valley-type, tabular uranium, porphyry, epithermal, and mid-ocean ridge ore-forming systems. A key limitation in the computational state-of-the-art is the inability to describe fluid flow and transport fully in the many ore systems that show evidence of repeated shear or tensional failure with associated dynamic variations in permeability. However, we discuss global-scale compilations that suggest some numerical constraints on both mean and dynamically enhanced crustal permeability. Principles of physical hydrogeology can be powerful tools for investigating hydrothermal ore formation and are becoming increasingly accessible with ongoing advances in modeling software.

Similar specificities of symbiont uptake by adults and larvae in an anemone model system for coral biology

PubMed Central

Hambleton, Elizabeth A.; Guse, Annika; Pringle, John R.

2014-01-01

Reef-building corals depend for much of their energy on photosynthesis by symbiotic dinoflagellate algae (genus Symbiodinium) that live within their gastrodermal cells. However, the cellular mechanisms underpinning this ecologically critical symbiosis, including those governing the specificity of symbiont uptake by the host, remain poorly understood, in part because of the difficulties of working with corals in the laboratory. Here, we used the small symbiotic sea anemone Aiptasia as an experimentally tractable model system to analyze the specificity and timing of symbiosis onset in larval and adult animals under controlled laboratory conditions. Using four clonal, axenic Symbiodinium strains, we found no difference in uptake specificity between larvae (even when very young) and adults. Although both compatible and incompatible algal strains were found within the larval guts, only the former appeared to be internalized by gastrodermal cells, and they (but not incompatible algae) proliferated rapidly within the larvae in the absence of detectable exchange with other larvae. Older larvae showed reduced ingestion of both compatible and incompatible algae, and the addition of food failed to promote the uptake of an incompatible algal strain. Thus, Aiptasia adults and larvae appear to have similar mechanisms for discriminating between compatible and incompatible dinoflagellate types prior to phagocytosis by host gastrodermal cells. Whether a particular algal strain is compatible or incompatible appears to be stable during years of axenic culture in the absence of a host. These studies provide a foundation for future analyses of the mechanisms of symbiont-uptake specificity in this emerging model system. PMID:24526722

Climate Model Ensemble Methodology: Rationale and Challenges

NASA Astrophysics Data System (ADS)

Vezer, M. A.; Myrvold, W.

2012-12-01

A tractable model of the Earth's atmosphere, or, indeed, any large, complex system, is inevitably unrealistic in a variety of ways. This will have an effect on the model's output. Nonetheless, we want to be able to rely on certain features of the model's output in studies aiming to detect, attribute, and project climate change. For this, we need assurance that these features reflect the target system, and are not artifacts of the unrealistic assumptions that go into the model. One technique for overcoming these limitations is to study ensembles of models which employ different simplifying assumptions and different methods of modelling. One then either takes as reliable certain outputs on which models in the ensemble agree, or takes the average of these outputs as the best estimate. Since the Intergovernmental Panel on Climate Change's Fourth Assessment Report (IPCC AR4) modellers have aimed to improve ensemble analysis by developing techniques to account for dependencies among models, and to ascribe unequal weights to models according to their performance. The goal of this paper is to present as clearly and cogently as possible the rationale for climate model ensemble methodology, the motivation of modellers to account for model dependencies, and their efforts to ascribe unequal weights to models. The method of our analysis is as follows. We will consider a simpler, well-understood case of taking the mean of a number of measurements of some quantity. Contrary to what is sometimes said, it is not a requirement of this practice that the errors of the component measurements be independent; one must, however, compensate for any lack of independence. We will also extend the usual accounts to include cases of unknown systematic error. We draw parallels between this simpler illustration and the more complex example of climate model ensembles, detailing how ensembles can provide more useful information than any of their constituent models. This account emphasizes the epistemic importance of considering degrees of model dependence, and the practice of ascribing unequal weights to models of unequal skill.

A Tractable Estimate for the Dissipation Range Onset Wavenumber Throughout the Heliosphere

NASA Astrophysics Data System (ADS)

Engelbrecht, N. Eugene; Strauss, R. Du Toit

2018-04-01

The modulation of low-energy electrons in the heliosphere is extremely sensitive to the behavior of the dissipation range slab turbulence. The present study derives approximate expressions for the wavenumber at which the dissipation range on the slab turbulence power spectrum commences, by assuming that this onset occurs when dispersive waves propagating parallel to the background magnetic field gyroresonate with thermal plasma particles. This assumption yields results in reasonable agreement with existing spacecraft observations. These expressions are functions of the solar wind proton and electron temperatures, which are here modeled throughout the region where the solar wind is supersonic using a two-component turbulence transport model. The results so acquired are compared with extrapolations of existing models for the dissipation range onset wavenumber, and conclusions are drawn therefrom.

Flavor instabilities in the neutrino line model

DOE PAGES

Duan, Huaiyu; Shalgar, Shashank

2015-05-27

A dense neutrino medium can experience collective flavor oscillations through nonlinear neutrino-neutrino refraction. To make this multi-dimensional flavor transport problem more tractable, all existing studies have assumed certain symmetries (e.g., the spatial homogeneity and directional isotropy in the early universe) to reduce the dimensionality of the problem. In this article we show that, if both the directional and spatial symmetries are not enforced in the neutrino line model, collective oscillations can develop in the physical regimes where the symmetry-preserving oscillation modes are stable. Our results suggest that collective neutrino oscillations in real astrophysical environments (such as core-collapse supernovae and black-holemore » accretion discs) can be qualitatively different from the predictions based on existing models in which spatial and directional symmetries are artificially imposed.« less

SELECTIVE ADVANTAGE OF RECOMBINATION IN EVOLVING PROTEIN POPULATIONS: A LATTICE MODEL STUDY

PubMed Central

WILLIAMS, PAUL D.; POLLOCK, DAVID D.

2010-01-01

Recent research has attempted to clarify the contributions of several mutational processes, such as substitutions or homologous recombination. Simplistic, tractable protein models, which determine the compact native structure phenotype from the sequence genotype, are well-suited to such studies. In this paper, we use a lattice-protein model to examine the effects of point mutation and homologous recombination on evolving populations of proteins. We find that while the majority of mutation and recombination events are neutral or deleterious, recombination is far more likely to be beneficial. This results in a faster increase in fitness during evolution, although the final fitness level is not significantly changed. This transient advantage provides an evolutionary advantage to subpopulations that undergo recombination, allowing fixation of recombination to occur in the population. PMID:25473139

Selective Advantage of Recombination in Evolving Protein Populations:. a Lattice Model Study

NASA Astrophysics Data System (ADS)

Williams, Paul D.; Pollock, David D.; Goldstein, Richard A.

Recent research has attempted to clarify the contributions of several mutational processes, such as substitutions or homologous recombination. Simplistic, tractable protein models, which determine the compact native structure phenotype from the sequence genotype, are well-suited to such studies. In this paper, we use a lattice-protein model to examine the effects of point mutation and homologous recombination on evolving populations of proteins. We find that while the majority of mutation and recombination events are neutral or deleterious, recombination is far more likely to be beneficial. This results in a faster increase in fitness during evolution, although the final fitness level is not significantly changed. This transient advantage provides an evolutionary advantage to subpopulations that undergo recombination, allowing fixation of recombination to occur in the population.

Fast generation of sparse random kernel graphs

DOE PAGES

Hagberg, Aric; Lemons, Nathan; Du, Wen -Bo

2015-09-10

The development of kernel-based inhomogeneous random graphs has provided models that are flexible enough to capture many observed characteristics of real networks, and that are also mathematically tractable. We specify a class of inhomogeneous random graph models, called random kernel graphs, that produces sparse graphs with tunable graph properties, and we develop an efficient generation algorithm to sample random instances from this model. As real-world networks are usually large, it is essential that the run-time of generation algorithms scales better than quadratically in the number of vertices n. We show that for many practical kernels our algorithm runs in timemore » at most ο(n(logn)²). As an example, we show how to generate samples of power-law degree distribution graphs with tunable assortativity.« less

Diagnosing Topological Edge States via Entanglement Monogamy.

PubMed

Meichanetzidis, K; Eisert, J; Cirio, M; Lahtinen, V; Pachos, J K

2016-04-01

Topological phases of matter possess intricate correlation patterns typically probed by entanglement entropies or entanglement spectra. In this Letter, we propose an alternative approach to assessing topologically induced edge states in free and interacting fermionic systems. We do so by focussing on the fermionic covariance matrix. This matrix is often tractable either analytically or numerically, and it precisely captures the relevant correlations of the system. By invoking the concept of monogamy of entanglement, we show that highly entangled states supported across a system bipartition are largely disentangled from the rest of the system, thus, usually appearing as gapless edge states. We then define an entanglement qualifier that identifies the presence of topological edge states based purely on correlations present in the ground states. We demonstrate the versatility of this qualifier by applying it to various free and interacting fermionic topological systems.

Diagnosing Topological Edge States via Entanglement Monogamy

NASA Astrophysics Data System (ADS)

Meichanetzidis, K.; Eisert, J.; Cirio, M.; Lahtinen, V.; Pachos, J. K.

2016-04-01

Topological phases of matter possess intricate correlation patterns typically probed by entanglement entropies or entanglement spectra. In this Letter, we propose an alternative approach to assessing topologically induced edge states in free and interacting fermionic systems. We do so by focussing on the fermionic covariance matrix. This matrix is often tractable either analytically or numerically, and it precisely captures the relevant correlations of the system. By invoking the concept of monogamy of entanglement, we show that highly entangled states supported across a system bipartition are largely disentangled from the rest of the system, thus, usually appearing as gapless edge states. We then define an entanglement qualifier that identifies the presence of topological edge states based purely on correlations present in the ground states. We demonstrate the versatility of this qualifier by applying it to various free and interacting fermionic topological systems.

Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization.

PubMed

Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

2016-03-15

Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. The annotation ontology for rule-based models can be found at http://purl.org/rbm/rbmo The krdf tool and associated executable examples are available at http://purl.org/rbm/rbmo/krdf anil.wipat@newcastle.ac.uk or vdanos@inf.ed.ac.uk. © The Author 2015. Published by Oxford University Press.

Force and Stress along Simulated Dissociation Pathways of Cucurbituril-Guest Systems.

PubMed

Velez-Vega, Camilo; Gilson, Michael K

2012-03-13

The field of host-guest chemistry provides computationally tractable yet informative model systems for biomolecular recognition. We applied molecular dynamics simulations to study the forces and mechanical stresses associated with forced dissociation of aqueous cucurbituril-guest complexes with high binding affinities. First, the unbinding transitions were modeled with constant velocity pulling (steered dynamics) and a soft spring constant, to model atomic force microscopy (AFM) experiments. The computed length-force profiles yield rupture forces in good agreement with available measurements. We also used steered dynamics with high spring constants to generate paths characterized by a tight control over the specified pulling distance; these paths were then equilibrated via umbrella sampling simulations and used to compute time-averaged mechanical stresses along the dissociation pathways. The stress calculations proved to be informative regarding the key interactions determining the length-force profiles and rupture forces. In particular, the unbinding transition of one complex is found to be a stepwise process, which is initially dominated by electrostatic interactions between the guest's ammoniums and the host's carbonyl groups, and subsequently limited by the extraction of the guest's bulky bicyclooctane moiety; the latter step requires some bond stretching at the cucurbituril's extraction portal. Conversely, the dissociation of a second complex with a more slender guest is mainly driven by successive electrostatic interactions between the different guest's ammoniums and the host's carbonyl groups. The calculations also provide information on the origins of thermodynamic irreversibilities in these forced dissociation processes.

Comprehensive solutions to the Bloch equations and dynamical models for open two-level systems

NASA Astrophysics Data System (ADS)

Skinner, Thomas E.

2018-01-01

The Bloch equation and its variants constitute the fundamental dynamical model for arbitrary two-level systems. Many important processes, including those in more complicated systems, can be modeled and understood through the two-level approximation. It is therefore of widespread relevance, especially as it relates to understanding dissipative processes in current cutting-edge applications of quantum mechanics. Although the Bloch equation has been the subject of considerable analysis in the 70 years since its inception, there is still, perhaps surprisingly, significant work that can be done. This paper extends the scope of previous analyses. It provides a framework for more fully understanding the dynamics of dissipative two-level systems. A solution is derived that is compact, tractable, and completely general, in contrast to previous results. Any solution of the Bloch equation depends on three roots of a cubic polynomial that are crucial to the time dependence of the system. The roots are typically only sketched out qualitatively, with no indication of their dependence on the physical parameters of the problem. Degenerate roots, which modify the solutions, have been ignored altogether. Here the roots are obtained explicitly in terms of a single real-valued root that is expressed as a simple function of the system parameters. For the conventional Bloch equation, a simple graphical representation of this root is presented that makes evident the explicit time dependence of the system for each point in the parameter space. Several intuitive, visual models of system dynamics are developed. A Euclidean coordinate system is identified in which any generalized Bloch equation is separable, i.e., the sum of commuting rotation and relaxation operators. The time evolution in this frame is simply a rotation followed by relaxation at modified rates that play a role similar to the standard longitudinal and transverse rates. These rates are functions of the applied field, which provides information towards control of the dissipative process. The Bloch equation also describes a system of three coupled harmonic oscillators, providing additional perspective on dissipative systems.

Testing the mutual information expansion of entropy with multivariate Gaussian distributions.

PubMed

Goethe, Martin; Fita, Ignacio; Rubi, J Miguel

2017-12-14

The mutual information expansion (MIE) represents an approximation of the configurational entropy in terms of low-dimensional integrals. It is frequently employed to compute entropies from simulation data of large systems, such as macromolecules, for which brute-force evaluation of the full configurational integral is intractable. Here, we test the validity of MIE for systems consisting of more than m = 100 degrees of freedom (dofs). The dofs are distributed according to multivariate Gaussian distributions which were generated from protein structures using a variant of the anisotropic network model. For the Gaussian distributions, we have semi-analytical access to the configurational entropy as well as to all contributions of MIE. This allows us to accurately assess the validity of MIE for different situations. We find that MIE diverges for systems containing long-range correlations which means that the error of consecutive MIE approximations grows with the truncation order n for all tractable n ≪ m. This fact implies severe limitations on the applicability of MIE, which are discussed in the article. For systems with correlations that decay exponentially with distance, MIE represents an asymptotic expansion of entropy, where the first successive MIE approximations approach the exact entropy, while MIE also diverges for larger orders. In this case, MIE serves as a useful entropy expansion when truncated up to a specific truncation order which depends on the correlation length of the system.

A Hybrid Vortex Sheet / Point Vortex Model for Unsteady Separated Flows

NASA Astrophysics Data System (ADS)

Darakananda, Darwin; Eldredge, Jeff D.; Colonius, Tim; Williams, David R.

2015-11-01

The control of separated flow over an airfoil is essential for obtaining lift enhancement, drag reduction, and the overall ability to perform high agility maneuvers. In order to develop reliable flight control systems capable of realizing agile maneuvers, we need a low-order aerodynamics model that can accurately predict the force response of an airfoil to arbitrary disturbances and/or actuation. In the present work, we integrate vortex sheets and variable strength point vortices into a method that is able to capture the formation of coherent vortex structures while remaining computationally tractable for control purposes. The role of the vortex sheet is limited to tracking the dynamics of the shear layer immediately behind the airfoil. When parts of the sheet develop into large scale structures, those sections are replaced by variable strength point vortices. We prevent the vortex sheets from growing indefinitely by truncating the tips of the sheets and transfering their circulation into nearby point vortices whenever the length of sheet exceeds a threshold. We demonstrate the model on a variety of canonical problems, including pitch-up and impulse translation of an airfoil at various angles of attack. Support by the U.S. Air Force Office of Scientific Research (FA9550-14-1-0328) with program manager Dr. Douglas Smith is gratefully acknowledged.

Naive Probability: Model-Based Estimates of Unique Events.

PubMed

Khemlani, Sangeet S; Lotstein, Max; Johnson-Laird, Philip N

2015-08-01

We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non-numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P(A), P(B), P(A and B), disjunctions: P(A), P(B), P(A or B or both), and conditional probabilities P(A), P(B), P(B|A). They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning. © 2014 Cognitive Science Society, Inc.

A Single-Amino-Acid Change in Murine Norovirus NS1/2 Is Sufficient for Colonic Tropism and Persistence

PubMed Central

Nice, Timothy J.; Strong, David W.; McCune, Broc T.; Pohl, Calvin S.

2013-01-01

Human norovirus (HuNoV) is the major cause of acute nonbacterial gastroenteritis worldwide but has no clear animal reservoir. HuNoV can persist after the resolution of symptoms, and this persistence may be essential for viral maintenance within the population. Many strains of the related murine norovirus (MNV) also persist, providing a tractable animal model for studying norovirus (NoV) persistence. We have used recombinant cDNA clones of representative persistent (CR6) and nonpersistent (CW3) strains to identify a domain within the nonstructural gene NS1/2 that is necessary and sufficient for persistence. Furthermore, we found that a single change of aspartic acid to glutamic acid in CW3 NS1/2 was sufficient for persistence. This same conservative change also caused increased growth of CW3 in the proximal colon, which we found to be a major tissue reservoir of MNV persistence, suggesting that NS1/2 determines viral tropism that is necessary for persistence. These findings represent the first identified function for NoV NS1/2 during infection and establish a novel model system for the study of enteric viral persistence. PMID:23077309

Using genetic data to estimate diffusion rates in heterogeneous landscapes.

PubMed

Roques, L; Walker, E; Franck, P; Soubeyrand, S; Klein, E K

2016-08-01

Having a precise knowledge of the dispersal ability of a population in a heterogeneous environment is of critical importance in agroecology and conservation biology as it can provide management tools to limit the effects of pests or to increase the survival of endangered species. In this paper, we propose a mechanistic-statistical method to estimate space-dependent diffusion parameters of spatially-explicit models based on stochastic differential equations, using genetic data. Dividing the total population into subpopulations corresponding to different habitat patches with known allele frequencies, the expected proportions of individuals from each subpopulation at each position is computed by solving a system of reaction-diffusion equations. Modelling the capture and genotyping of the individuals with a statistical approach, we derive a numerically tractable formula for the likelihood function associated with the diffusion parameters. In a simulated environment made of three types of regions, each associated with a different diffusion coefficient, we successfully estimate the diffusion parameters with a maximum-likelihood approach. Although higher genetic differentiation among subpopulations leads to more accurate estimations, once a certain level of differentiation has been reached, the finite size of the genotyped population becomes the limiting factor for accurate estimation.

Extraction and representation of nested catchment areas from digital elevation models in lake-dominated topography

NASA Astrophysics Data System (ADS)

Mackay, D. Scott; Band, Lawrence E.

1998-04-01

This paper presents a new method for extracting flow directions, contributing (upslope) areas, and nested catchments from digital elevation models in lake-dominated areas. Existing tools for acquiring descriptive variables of the topography, such as surface flow directions and contributing areas, were developed for moderate to steep topography. These tools are typically difficult to apply in gentle topography owing to limitations in explicitly handling lakes and other flat areas. This paper addresses the problem of accurately representing general topographic features by first identifying distinguishing features, such as lakes, in gentle topography areas and then using these features to guide the search for topographic flow directions and catchment marking. Lakes are explicitly represented in the topology of a watershed for use in water routing. Nonlake flat features help guide the search for topographic flow directions in areas of low signal to noise. This combined feature-based and grid-based search for topographic features yields improved contributing areas and watershed boundaries where there are lakes and other flat areas. Lakes are easily classified from remotely sensed imagery, which makes automated representation of lakes as subsystems within a watershed system tractable with widely available data sets.

Issues concerning the updating of finite-element models from experimental data

NASA Technical Reports Server (NTRS)

Dunn, Shane A.

1994-01-01

Some issues concerning the updating of dynamic finite-element models by incorporation of experimental data are examined here. It is demonstrated how the number of unknowns can be greatly reduced if the physical nature of the model is maintained. The issue of uniqueness is also examined and it is shown that a number of previous workers have been mistaken in their attempts to define both sufficient and necessary measurement requirements for the updating problem to be solved uniquely. The relative merits of modal and frequency response function (frf) data are discussed and it is shown that for measurements at fewer degrees of freedom than are present in the model, frf data will be unlikely to converge easily to a solution. It is then examined how such problems may become more tractable by using new experimental techniques which would allow measurements at all degrees of freedom present in the mathematical model.

Random medium model for cusping of plane waves.

PubMed

Li, Jia; Korotkova, Olga

2017-09-01

We introduce a model for a three-dimensional (3D) Schell-type stationary medium whose degree of potential's correlation satisfies the Fractional Multi-Gaussian (FMG) function. Compared with the scattered profile produced by the Gaussian Schell-model (GSM) medium, the Fractional Multi-Gaussian Schell-model (FMGSM) medium gives rise to a sharp concave intensity apex in the scattered field. This implies that the FMGSM medium also accounts for a larger than Gaussian's power in the bucket (PIB) in the forward scattering direction, hence being a better candidate than the GSM medium for generating highly-focused (cusp-like) scattered profiles in the far zone. Compared to other mathematical models for the medium's correlation function which can produce similar cusped scattered profiles the FMG function offers unprecedented tractability being the weighted superposition of Gaussian functions. Our results provide useful applications to energy counter problems and particle manipulation by weakly scattered fields.

Mathematical modeling of spinning elastic bodies for modal analysis.

NASA Technical Reports Server (NTRS)

Likins, P. W.; Barbera, F. J.; Baddeley, V.

1973-01-01

The problem of modal analysis of an elastic appendage on a rotating base is examined to establish the relative advantages of various mathematical models of elastic structures and to extract general inferences concerning the magnitude and character of the influence of spin on the natural frequencies and mode shapes of rotating structures. In realization of the first objective, it is concluded that except for a small class of very special cases the elastic continuum model is devoid of useful results, while for constant nominal spin rate the distributed-mass finite-element model is quite generally tractable, since in the latter case the governing equations are always linear, constant-coefficient, ordinary differential equations. Although with both of these alternatives the details of the formulation generally obscure the essence of the problem and permit very little engineering insight to be gained without extensive computation, this difficulty is not encountered when dealing with simple concentrated mass models.

Synchronization scenarios in the Winfree model of coupled oscillators

NASA Astrophysics Data System (ADS)

Gallego, Rafael; Montbrió, Ernest; Pazó, Diego

2017-10-01

Fifty years ago Arthur Winfree proposed a deeply influential mean-field model for the collective synchronization of large populations of phase oscillators. Here we provide a detailed analysis of the model for some special, analytically tractable cases. Adopting the thermodynamic limit, we derive an ordinary differential equation that exactly describes the temporal evolution of the macroscopic variables in the Ott-Antonsen invariant manifold. The low-dimensional model is then thoroughly investigated for a variety of pulse types and sinusoidal phase response curves (PRCs). Two structurally different synchronization scenarios are found, which are linked via the mutation of a Bogdanov-Takens point. From our results, we infer a general rule of thumb relating pulse shape and PRC offset with each scenario. Finally, we compare the exact synchronization threshold with the prediction of the averaging approximation given by the Kuramoto-Sakaguchi model. At the leading order, the discrepancy appears to behave as an odd function of the PRC offset.

A Catchment-Based Approach to Modeling Land Surface Processes in a GCM. Part 2; Parameter Estimation and Model Demonstration

NASA Technical Reports Server (NTRS)

Ducharne, Agnes; Koster, Randal D.; Suarez, Max J.; Stieglitz, Marc; Kumar, Praveen

2000-01-01

The viability of a new catchment-based land surface model (LSM) developed for use with general circulation models is demonstrated. First, simple empirical functions -- tractable enough for operational use in the LSM -- are established that faithfully capture the control of topography on the subgrid variability of soil moisture and the surface water budget, as predicted by theory. Next, the full LSM is evaluated offline. Using forcing and validation datasets developed for PILPS Phase 2c, the minimally calibrated model is shown to reproduce observed evaporation and runoff fluxes successfully in the Red-Arkansas River Basin. A complementary idealized study that employs the range of topographic variability seen over North America demonstrates that the simulated surface water budget does vary strongly with topography, which can, by itself, induce variations in annual evaporation as high as 20%.

Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities

PubMed Central

Bardhan, Jaydeep P.

2014-01-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics. PMID:25505358

Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities.

PubMed

Bardhan, Jaydeep P

2013-12-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.

Gradient models in molecular biophysics: progress, challenges, opportunities

NASA Astrophysics Data System (ADS)

Bardhan, Jaydeep P.

2013-12-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g., molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding nonlocal dielectric response. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain, and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost 40 years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The review concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.

4D volcano gravimetry

USGS Publications Warehouse

Battaglia, Maurizio; Gottsmann, J.; Carbone, D.; Fernandez, J.

2008-01-01

Time-dependent gravimetric measurements can detect subsurface processes long before magma flow leads to earthquakes or other eruption precursors. The ability of gravity measurements to detect subsurface mass flow is greatly enhanced if gravity measurements are analyzed and modeled with ground-deformation data. Obtaining the maximum information from microgravity studies requires careful evaluation of the layout of network benchmarks, the gravity environmental signal, and the coupling between gravity changes and crustal deformation. When changes in the system under study are fast (hours to weeks), as in hydrothermal systems and restless volcanoes, continuous gravity observations at selected sites can help to capture many details of the dynamics of the intrusive sources. Despite the instrumental effects, mainly caused by atmospheric temperature, results from monitoring at Mt. Etna volcano show that continuous measurements are a powerful tool for monitoring and studying volcanoes.Several analytical and numerical mathematical models can beused to fit gravity and deformation data. Analytical models offer a closed-form description of the volcanic source. In principle, this allows one to readily infer the relative importance of the source parameters. In active volcanic sites such as Long Valley caldera (California, U.S.A.) and Campi Flegrei (Italy), careful use of analytical models and high-quality data sets has produced good results. However, the simplifications that make analytical models tractable might result in misleading volcanological inter-pretations, particularly when the real crust surrounding the source is far from the homogeneous/ isotropic assumption. Using numerical models allows consideration of more realistic descriptions of the sources and of the crust where they are located (e.g., vertical and lateral mechanical discontinuities, complex source geometries, and topography). Applications at Teide volcano (Tenerife) and Campi Flegrei demonstrate the importance of this more realistic description in gravity calculations. ?? 2008 Society of Exploration Geophysicists. All rights reserved.

Phase transitions and dynamics of bulk and interfacial water.

PubMed

Franzese, G; Hernando-Martínez, A; Kumar, P; Mazza, M G; Stokely, K; Strekalova, E G; de los Santos, F; Stanley, H E

2010-07-21

New experiments on water at the surface of proteins at very low temperature display intriguing dynamic behaviors. The extreme conditions of these experiments make it difficult to explore the wide range of thermodynamic state points needed to offer a suitable interpretation. Detailed simulations suffer from the same problem, where equilibration times at low temperature become extremely long. We show how Monte Carlo simulations and mean field calculations using a tractable model of water help interpret the experimental results. Here we summarize the results for bulk water and investigate the thermodynamic and dynamic properties of supercooled water at an interface.

Cystic Fibrosis Transmembrane Conductance Regulator (ABCC7) Structure

PubMed Central

Hunt, John F.; Wang, Chi; Ford, Robert C.

2013-01-01

Structural studies of the cystic fibrosis transmembrane conductance regulator (CFTR) are reviewed. Like many membrane proteins, full-length CFTR has proven to be difficult to express and purify, hence much of the structural data available is for the more tractable, independently expressed soluble domains. Therefore, this chapter covers structural data for individual CFTR domains in addition to the sparser data available for the full-length protein. To set the context for these studies, we will start by reviewing structural information on model proteins from the ATP-binding cassette (ABC) transporter superfamily, to which CFTR belongs. PMID:23378596

Extended Islands of Tractability for Parsimony Haplotyping

NASA Astrophysics Data System (ADS)

Fleischer, Rudolf; Guo, Jiong; Niedermeier, Rolf; Uhlmann, Johannes; Wang, Yihui; Weller, Mathias; Wu, Xi

Parsimony haplotyping is the problem of finding a smallest size set of haplotypes that can explain a given set of genotypes. The problem is NP-hard, and many heuristic and approximation algorithms as well as polynomial-time solvable special cases have been discovered. We propose improved fixed-parameter tractability results with respect to the parameter "size of the target haplotype set" k by presenting an O *(k 4k )-time algorithm. This also applies to the practically important constrained case, where we can only use haplotypes from a given set. Furthermore, we show that the problem becomes polynomial-time solvable if the given set of genotypes is complete, i.e., contains all possible genotypes that can be explained by the set of haplotypes.

Design and Elaboration of a Tractable Tricyclic Scaffold To Synthesize Druglike Inhibitors of Dipeptidyl Peptidase-4 (DPP-4), Antagonists of the C-C Chemokine Receptor Type 5 (CCR5), and Highly Potent and Selective Phosphoinositol-3 Kinase δ (PI3Kδ) Inhibitors.

PubMed

Schwehm, Carolin; Kellam, Barrie; Garces, Aimie E; Hill, Stephen J; Kindon, Nicholas D; Bradshaw, Tracey D; Li, Jin; Macdonald, Simon J F; Rowedder, James E; Stoddart, Leigh A; Stocks, Michael J

2017-02-23

A novel molecular scaffold has been synthesized, and its incorporation into new analogues of biologically active molecules across multiple target classes will be discussed. In these studies, we have shown use of the tricyclic scaffold to synthesize potent inhibitors of the serine peptidase DPP-4, antagonists of the CCR5 receptor, and highly potent and selective PI3K δ isoform inhibitors. We also describe the predicted physicochemical properties of the resulting inhibitors and conclude that the tractable molecular scaffold could have potential application in future drug discovery programs.

Choosing Meteorological Input for the Global Modeling Initiative Assessment of High Speed Aircraft

NASA Technical Reports Server (NTRS)

Douglas, A. R.; Prather, M. P.; Hall, T. M.; Strahan, S. E.; Rasch, P. J.; Sparling, L. C.; Coy, L.; Rodriquez, J. M.

1998-01-01

The Global Modeling Initiative (GMI) science team is developing a three dimensional chemistry and transport model (CTM) to be used in assessment of the atmospheric effects of aviation. Requirements are that this model be documented, be validated against observations, use a realistic atmospheric circulation, and contain numerical transport and photochemical modules representing atmospheric processes. The model must also retain computational efficiency to be tractable to use for multiple scenarios and sensitivity studies. To meet these requirements, a facility model concept was developed in which the different components of the CTM are evaluated separately. The first use of the GMI model will be to evaluate the impact of the exhaust of supersonic aircraft on the stratosphere. The assessment calculations will depend strongly on the wind and temperature fields used by the CTM. Three meteorological data sets for the stratosphere are available to GMI: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System Data Assimilation System (GEOS DAS), and the Goddard Institute for Space Studies general circulation model (GISS). Objective criteria were established by the GMI team to identify the data set which provides the best representation of the stratosphere. Simulations of gases with simple chemical control were chosen to test various aspects of model transport. The three meteorological data sets were evaluated and graded based on their ability to simulate these aspects of stratospheric measurements. This paper describes the criteria used in grading the meteorological fields. The meteorological data set which has the highest score and therefore was selected for GMI is CCM2. This type of objective model evaluation establishes a physical basis for interpretation of differences between models and observations. Further, the method provides a quantitative basis for defining model errors, for discriminating between different models, and for ready re-evaluation of improved models. These in turn will lead to a higher level of confidence in assessment calculations.

Climate change and species interactions: ways forward.

PubMed

Angert, Amy L; LaDeau, Shannon L; Ostfeld, Richard S

2013-09-01

With ongoing and rapid climate change, ecologists are being challenged to predict how individual species will change in abundance and distribution, how biotic communities will change in structure and function, and the consequences of these climate-induced changes for ecosystem functioning. It is now well documented that indirect effects of climate change on species abundances and distributions, via climatic effects on interspecific interactions, can outweigh and even reverse the direct effects of climate. However, a clear framework for incorporating species interactions into projections of biological change remains elusive. To move forward, we suggest three priorities for the research community: (1) utilize tractable study systems as case studies to illustrate possible outcomes, test processes highlighted by theory, and feed back into modeling efforts; (2) develop a robust analytical framework that allows for better cross-scale linkages; and (3) determine over what time scales and for which systems prediction of biological responses to climate change is a useful and feasible goal. We end with a list of research questions that can guide future research to help understand, and hopefully mitigate, the negative effects of climate change on biota and the ecosystem services they provide. © 2013 New York Academy of Sciences.

P-V-T Properties of Polyimides and Model Imide Compounds

NASA Technical Reports Server (NTRS)

Orwoll, Robert A.

1997-01-01

Aromatic polyimides are used as matrix resins in advanced composites, as high strength films, and as high-temperature adhesives, owing in part to their unusual thermal and chemical stability. The polyimides' desirable qualities of very high softening temperatures and negligibly small solubilities in and low permeabilities by most solvents have limited the kinds of fundamental studies that can be performed on these systems. Consequently, relationships between the molecular structure of polyimides and their bulk properties are not as well understood as might be expected given their widespread applications. In particular, the intermolecular forces in polyimides that play a critical role determining their densities, solubilities, viscosities, moduli, glass transitions, etc. are less well characterized for polyimides than for other widely used polymeric materials. The purpose of the present study is to obtain experimental data for establishing parameters that characterize the intermolecular forces in polyimides. We report here our studies on tractable low molecular-weight imides that contain the same structural features that are present in polyimide materials. We have measured equation-of-state properties and dipole moments for a variety of such systems in the liquid state. Both pure compounds and binary mixtures have been studied.

Modeling and Analysis of Remote, Off-grid Microgrids

NASA Astrophysics Data System (ADS)

Madathil, Sreenath Chalil

Over the past century the electric power industry has evolved to support the delivery of power over long distances with highly interconnected transmission systems. Despite this evolution, some remote communities are not connected to these systems. These communities rely on small, disconnected distribution systems, i.e., microgrids, to deliver power. Power distribution in most of these remote communities often depend on a type of microgrid called "off-grid microgrids". However, as microgrids often are not held to the same reliability standards as transmission grids, remote communities can be at risk to experience extended blackouts. Recent trends have also shown an increased use of renewable energy resources in power systems for remote communities. The increased penetration of renewable resources in power generation will require complex decision making when designing a resilient power system. This is mainly due to the stochastic nature of renewable resources that can lead to loss of load or line overload during their operations. In the first part of this thesis, we develop an optimization model and accompanying solution algorithm for capacity planning and operating microgrids that include N-1 security and other practical modeling features (e.g., AC power flow physics, component efficiencies and thermal limits). We demonstrate the effectiveness of our model and solution approach on two test systems: a modified version of the IEEE 13 node test feeder and a model of a distribution system in a remote Alaskan community. Once a tractable algorithm was identified to solve the above problem, we develop a mathematical model that includes topology design of microgrids. The topology design includes building new lines, making redundant lines, and analyzing N-1 contingencies on generators and lines. We develop a rolling horizon algorithm to efficiently analyze the model and demonstrate the strength of our algorithm in the same network. Finally, we develop a stochastic model that considers generation uncertainties along with N-1 security on generation assets. We develop a chance-constrained model to analyze the efficacy of the problem under consideration and present a case study on an adapted IEEE-13 node network. A successful implementation of this research could help remote communities around the world to enhance their quality of life by providing them with cost-effective, reliable electricity.

Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

2012-01-01

Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Neoplasia and Neoplasm Associated Lesions in Laboratory Colonies of Zebrafish Emphasizing Key Influences of Diet and Aquaculture System Design

PubMed Central

Spitsbergen, Jan M.; Buhler, Donald R.; Peterson, Tracy S.

2014-01-01

During the past decade the zebrafish has emerged as a leading model for mechanistic cancer research due to its sophisticated genetic and genomic resources, its tractability for tissue targeting of transgene expression, its efficiency for forward genetic approaches to cancer model development, and its cost-effectiveness for enhancer and suppressor screens once a cancer model is established. However, in contrast to other laboratory animal species widely used as cancer models, much basic cancer biology information is lacking in zebrafish. As yet data are not published regarding dietary influences on neoplasm incidences in zebrafish. Little information is available regarding spontaneous tumor incidences or histologic types in wild-type (wt) lines of zebrafish. So far a comprehensive database documenting the full spectrum of neoplasia in various organ systems and tissues in not available for zebrafish as it is for other intensely studied laboratory animal species. This manuscript confirms that as in other species diet and husbandry can profoundly influence tumor incidences and histologic spectra in zebrafish. We show that in many laboratory colonies wt lines of zebrafish exhibit elevated neoplasm incidences and neoplasm associated lesions such as heptocyte megalocytosis. We present experimental evidence showing that certain diet and water management regimens can result in high incidences of neoplasia and neoplasm associated lesions. We document the wide array of benign and malignant neoplasms affecting nearly every organ, tissue and cell type in zebrafish, in some cases as a spontaneous aging change, and in other cases due to carcinogen treatment or genetic manipulation. PMID:23382343

A general temporal data model and the structured population event history register

PubMed Central

Clark, Samuel J.

2010-01-01

At this time there are 37 demographic surveillance system sites active in sub-Saharan Africa, Asia and Central America, and this number is growing continuously. These sites and other longitudinal population and health research projects generate large quantities of complex temporal data in order to describe, explain and investigate the event histories of individuals and the populations they constitute. This article presents possible solutions to some of the key data management challenges associated with those data. The fundamental components of a temporal system are identified and both they and their relationships to each other are given simple, standardized definitions. Further, a metadata framework is proposed to endow this abstract generalization with specific meaning and to bind the definitions of the data to the data themselves. The result is a temporal data model that is generalized, conceptually tractable, and inherently contains a full description of the primary data it organizes. Individual databases utilizing this temporal data model can be customized to suit the needs of their operators without modifying the underlying design of the database or sacrificing the potential to transparently share compatible subsets of their data with other similar databases. A practical working relational database design based on this general temporal data model is presented and demonstrated. This work has arisen out of experience with demographic surveillance in the developing world, and although the challenges and their solutions are more general, the discussion is organized around applications in demographic surveillance. An appendix contains detailed examples and working prototype databases that implement the examples discussed in the text. PMID:20396614

Symbiosis induces widespread changes in the proteome of the model cnidarian Aiptasia.

PubMed

Oakley, Clinton A; Ameismeier, Michael F; Peng, Lifeng; Weis, Virginia M; Grossman, Arthur R; Davy, Simon K

2016-07-01

Coral reef ecosystems are metabolically founded on the mutualism between corals and photosynthetic dinoflagellates of the genus Symbiodinium. The glass anemone Aiptasia sp. has become a tractable model for this symbiosis, and recent advances in genetic information have enabled the use of mass spectrometry-based proteomics in this model. We utilized label-free liquid chromatography electrospray-ionization tandem mass spectrometry to analyze the effects of symbiosis on the proteomes of symbiotic and aposymbiotic Aiptasia. We identified and obtained relative quantification of more than 3,300 proteins in 1,578 protein clusters, with 81 protein clusters showing significantly different expression between symbiotic states. Symbiotic anemones showed significantly higher expression of proteins involved in lipid storage and transport, nitrogen transport and cycling, intracellular trafficking, endocytosis and inorganic carbon transport. These changes reflect shifts in host metabolism and nutrient reserves due to increased nutritional exchange with the symbionts, as well as mechanisms for supplying inorganic nutrients to the algae. Aposymbiotic anemones exhibited increased expression of multiple systems responsible for mediating reactive oxygen stress, suggesting that the host derives direct or indirect protection from oxidative stress while in symbiosis. Aposymbiotic anemones also increased their expression of an array of proteases and chitinases, indicating a metabolic shift from autotrophy to heterotrophy. These results provide a comprehensive Aiptasia proteome with more direct relative quantification of protein abundance than transcriptomic methods. The extension of "omics" techniques to this model system will allow more powerful studies of coral physiology, ecosystem function, and the effects of biotic and abiotic stress on the coral-dinoflagellate mutualism. © 2015 John Wiley & Sons Ltd.

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation

PubMed Central

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes “winner-take-all” processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans’ value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light. PMID:29077746

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation.

PubMed

Colas, Jaron T

2017-01-01

In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.

The molecular basis of bacterial-insect symbiosis.

PubMed

Douglas, Angela E

2014-11-25

Insects provide experimentally tractable and cost-effective model systems to investigate the molecular basis of animal-bacterial interactions. Recent research is revealing the central role of the insect innate immune system, especially anti-microbial peptides and reactive oxygen species, in regulating the abundance and composition of the microbiota in various insects, including Drosophila and the mosquitoes Aedes and Anopheles. Interactions between the immune system and microbiota are, however, bidirectional with evidence that members of the resident microbiota can promote immune function, conferring resistance to pathogens and parasites by both activation of immune effectors and production of toxins. Antagonistic and mutualistic interactions among bacteria have also been implicated as determinants of the microbiota composition, including exclusion of pathogens, but the molecular mechanisms are largely unknown. Some bacteria are crucial for insect nutrition, through provisioning of specific nutrients (e.g., B vitamins, essential amino acids) and modulation of the insect nutritional sensing and signaling pathways (e.g., insulin signaling) that regulate nutrient allocation, especially to lipid and other energy reserves. A key challenge for future research is to identify the molecular interaction between specific bacterial effectors and animal receptors, as well as to determine how these interactions translate into microbiota-dependent signaling, metabolism, and immune function in the host. Copyright © 2014. Published by Elsevier Ltd.

From forager tracks to prey distributions: an application to tuna vessel monitoring systems (VMS).

PubMed

Walker, Emily; Rivoirard, Jacques; Gaspar, Philippe; Bez, Nicolas

2015-04-01

In the open ocean, movements of migratory fish populations are typically surveyed using tagging methods that are subject to low sample sizes for archive tags, except for a few notable examples, and poor temporal resolution for conventional tags. Alternatively, one can infer patterns of movement of migratory fish by tracking movements of their predators, i.e., fishing vessels, whose navigational systems (e.g., GPS) provide accurate and frequent VMS (vessel monitoring system) records of movement in pursuit of prey. In this paper, we develop a state-space model that infers the foraging activities of fishing vessels from their tracks. Second, we link foraging activities to probabilities of tuna presence. Finally, using multivariate geostatistical interpolation (cokriging) we map the probability of tuna presence together with their estimation variances and produce a time series of indices of abundance. While the segmentation of the trajectories is validated by observers' data, the present VMS-index is compared to catch rate and proved to be useful for management perspectives. The approach reported in this manuscript extends beyond the case study considered. It can be applied to any foragers that engage in an attempt of capture when they see prey and for whom this attempt is linked to a tractable change in behavior.

A premeiotic function for boule in the planarian Schmidtea mediterranea.

PubMed

Iyer, Harini; Issigonis, Melanie; Sharma, Prashant P; Extavour, Cassandra G; Newmark, Phillip A

2016-06-21

Mutations in Deleted in Azoospermia (DAZ), a Y chromosome gene, are an important cause of human male infertility. DAZ is found exclusively in primates, limiting functional studies of this gene to its homologs: boule, required for meiotic progression of germ cells in invertebrate model systems, and Daz-like (Dazl), required for early germ cell maintenance in vertebrates. Dazl is believed to have acquired its premeiotic role in a vertebrate ancestor following the duplication and functional divergence of the single-copy gene boule. However, multiple homologs of boule have been identified in some invertebrates, raising the possibility that some of these genes may play other roles, including a premeiotic function. Here we identify two boule paralogs in the freshwater planarian Schmidtea mediterranea Smed-boule1 is necessary for meiotic progression of male germ cells, similar to the known function of boule in invertebrates. By contrast, Smed-boule2 is required for the maintenance of early male germ cells, similar to vertebrate Dazl To examine if Boule2 may be functionally similar to vertebrate Dazl, we identify and functionally characterize planarian homologs of human DAZL/DAZ-interacting partners and DAZ family mRNA targets. Finally, our phylogenetic analyses indicate that premeiotic functions of planarian boule2 and vertebrate Dazl evolved independently. Our study uncovers a premeiotic role for an invertebrate boule homolog and offers a tractable invertebrate model system for studying the premeiotic functions of the DAZ protein family.

Homogeneous alignment of liquid crystalline dendrimers confined in a slit-pore. A simulation study.

PubMed

Workineh, Zerihun G; Vanakaras, Alexandros G

2016-03-23

In this work we present results from isobaric-isothermal (NPT) Monte Carlo simulation studies of model liquid crystalline dendrimer (LCDr) systems confined in a slit-pore made of two parallel flat walls. The dendrimers are modelled as a collection of spherical and ellipsoidal particles corresponding to the junction points of the dendritic core and to the mesogenic units respectively. Assuming planar uniform (unidirectional) soft anchoring of the mesogenic units on the substrates we investigate the conformational and alignment properties of the LCDr system at different thermodynamic state points. Tractable coarse grained force fields have been used from our previous work. At low pressures the interior of the pore is almost empty, since almost all LCDrs are anchored to the substrates forming two-dimensional smectic-like structures with the mesogens aligned along the aligning direction of the substrates. As the pressure grows the LCDrs occupy the whole pore. However, even at low temperatures, the smectic organization does not transmit in the interior of the pore and is preserved for distances of 2-3 mesogenic diameters from the walls. For this reason, the global orientational order decreases with increasing pressure (density). In the vicinity (2-3 mesogenic diameters) of the pore walls, mesogenic units preserve the smectic structure whose layers are separated by layers of spherical beads. In this region individual LCDrs possess a rod like shape.

A Unitary Anesthetic Binding Site at High Resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vedula, L. Sangeetha; Brannigan, Grace; Economou, Nicoleta J.

2009-10-21

Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABA{sub A} receptor, but such receptor-channel complexes remain challenging to study at atomic resolution. Until structural biology methods advance to the point of being able to deal with systems such as the GABA{sub A} receptor, it will be necessary to use more tractable surrogates to probe the molecular details of anesthetic recognition. We have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clinically relevant protein targets; here we show thatmore » apoferritin also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABA{sub A} receptors, validating this model system for injectable anesthetics. High resolution x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Molecular dynamics simulations indicate that the ligands undergo considerable fluctuations about their equilibrium positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiologic targets like ion channels.« less

A Unitary Anesthetic Binding Site at High Resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

L Vedula; G Brannigan; N Economou

2011-12-31

Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABA{sub A} receptor, but such receptor-channel complexes remain challenging to study at atomic resolution. Until structural biology methods advance to the point of being able to deal with systems such as the GABA{sub A} receptor, it will be necessary to use more tractable surrogates to probe the molecular details of anesthetic recognition. We have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clinically relevant protein targets; here we show thatmore » apoferritin also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABA{sub A} receptors, validating this model system for injectable anesthetics. High resolution x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Molecular dynamics simulations indicate that the ligands undergo considerable fluctuations about their equilibrium positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiologic targets like ion channels.« less

A Unitary Anesthetic-Binding Site at High Resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vedula, L.; Brannigan, G; Economou, N

2009-01-01

Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABAA receptor, but such receptor-channel complexes remain challenging to study at atomic resolution. Until structural biology methods advance to the point of being able to deal with systems such as the GABA{sub A} receptor, it will be necessary to use more tractable surrogates to probe the molecular details of anesthetic recognition. We have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clinically relevant protein targets; here we show that apoferritinmore » also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABA{sub A} receptors, validating this model system for injectable anesthetics. High resolution x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Molecular dynamics simulations indicate that the ligands undergo considerable fluctuations about their equilibrium positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiologic targets like ion channels.« less

Homogeneous alignment of liquid crystalline dendrimers confined in a slit-pore. A simulation study

NASA Astrophysics Data System (ADS)

Workineh, Zerihun G.; Vanakaras, Alexandros G.

2016-03-01

In this work we present results from isobaric-isothermal (NPT) Monte Carlo simulation studies of model liquid crystalline dendrimer (LCDr) systems confined in a slit-pore made of two parallel flat walls. The dendrimers are modelled as a collection of spherical and ellipsoidal particles corresponding to the junction points of the dendritic core and to the mesogenic units respectively. Assuming planar uniform (unidirectional) soft anchoring of the mesogenic units on the substrates we investigate the conformational and alignment properties of the LCDr system at different thermodynamic state points. Tractable coarse grained force fields have been used from our previous work. At low pressures the interior of the pore is almost empty, since almost all LCDrs are anchored to the substrates forming two-dimensional smectic-like structures with the mesogens aligned along the aligning direction of the substrates. As the pressure grows the LCDrs occupy the whole pore. However, even at low temperatures, the smectic organization does not transmit in the interior of the pore and is preserved for distances of 2-3 mesogenic diameters from the walls. For this reason, the global orientational order decreases with increasing pressure (density). In the vicinity (2-3 mesogenic diameters) of the pore walls, mesogenic units preserve the smectic structure whose layers are separated by layers of spherical beads. In this region individual LCDrs possess a rod like shape.

Solution landscapes in nematic microfluidics

NASA Astrophysics Data System (ADS)

Crespo, M.; Majumdar, A.; Ramos, A. M.; Griffiths, I. M.

2017-08-01

We study the static equilibria of a simplified Leslie-Ericksen model for a unidirectional uniaxial nematic flow in a prototype microfluidic channel, as a function of the pressure gradient G and inverse anchoring strength, B. We numerically find multiple static equilibria for admissible pairs (G , B) and classify them according to their winding numbers and stability. The case G = 0 is analytically tractable and we numerically study how the solution landscape is transformed as G increases. We study the one-dimensional dynamical model, the sensitivity of the dynamic solutions to initial conditions and the rate of change of G and B. We provide a physically interesting example of how the time delay between the applications of G and B can determine the selection of the final steady state.

Nonequilibrium description of de novo biogenesis and transport through Golgi-like cisternae

NASA Astrophysics Data System (ADS)

Sachdeva, Himani; Barma, Mustansir; Rao, Madan

2016-12-01

A central issue in cell biology is the physico-chemical basis of organelle biogenesis in intracellular trafficking pathways, its most impressive manifestation being the biogenesis of Golgi cisternae. At a basic level, such morphologically and chemically distinct compartments should arise from an interplay between the molecular transport and chemical maturation. Here, we formulate analytically tractable, minimalist models, that incorporate this interplay between transport and chemical progression in physical space, and explore the conditions for de novo biogenesis of distinct cisternae. We propose new quantitative measures that can discriminate between the various models of transport in a qualitative manner-this includes measures of the dynamics in steady state and the dynamical response to perturbations of the kind amenable to live-cell imaging.

Buyer-vendor coordination for fixed lifetime product with quantity discount under finite production rate

NASA Astrophysics Data System (ADS)

Zhang, Qinghong; Luo, Jianwen; Duan, Yongrui

2016-03-01

Buyer-vendor coordination has been widely addressed; however, the fixed lifetime of the product is seldom considered. In this paper, we study the coordination of an integrated production-inventory system with quantity discount for a fixed lifetime product under finite production rate and deterministic demand. We first derive the buyer's ordering policy and the vendor's production batch size in decentralised and centralised systems. We then compare the two systems and show the non-coordination of the ordering policies and the production batch sizes. To improve the supply chain efficiency, we propose quantity discount contract and prove that the contract can coordinate the buyer-vendor supply chain. Finally, we present analytically tractable solutions and give a numerical example to illustrate the benefits of the proposed quantity discount strategy.

Modeling congenital disease and inborn errors of development in Drosophila melanogaster

PubMed Central

Moulton, Matthew J.; Letsou, Anthea

2016-01-01

ABSTRACT Fly models that faithfully recapitulate various aspects of human disease and human health-related biology are being used for research into disease diagnosis and prevention. Established and new genetic strategies in Drosophila have yielded numerous substantial successes in modeling congenital disorders or inborn errors of human development, as well as neurodegenerative disease and cancer. Moreover, although our ability to generate sequence datasets continues to outpace our ability to analyze these datasets, the development of high-throughput analysis platforms in Drosophila has provided access through the bottleneck in the identification of disease gene candidates. In this Review, we describe both the traditional and newer methods that are facilitating the incorporation of Drosophila into the human disease discovery process, with a focus on the models that have enhanced our understanding of human developmental disorders and congenital disease. Enviable features of the Drosophila experimental system, which make it particularly useful in facilitating the much anticipated move from genotype to phenotype (understanding and predicting phenotypes directly from the primary DNA sequence), include its genetic tractability, the low cost for high-throughput discovery, and a genome and underlying biology that are highly evolutionarily conserved. In embracing the fly in the human disease-gene discovery process, we can expect to speed up and reduce the cost of this process, allowing experimental scales that are not feasible and/or would be too costly in higher eukaryotes. PMID:26935104

Wetting of Functionalized Polyethylene Film Having Ionizable Organic Acids and Bases at the Polymer-Water Interface: Relations between Functional Group Polarity, Extent of Ionization, and Contact Angle with Water.

DTIC Science & Technology

1988-03-01

functional grouos in the interface contribute independently to the interfacial free energy is inaccurate, but leads to a tractable and physically reasonable...nonpolar, non -ionizable groups. As a limiting case, we consider a system *. containing only one type of polar and one type of nonpolar group (eq 9) with A...groups (protonition or deprotonation): these equations apply to both non - ionizable groups and to PE-CO 2H and PE-NR 2H + . Assuming that Figure 3

The evolution of dorsal-ventral patterning mechanisms in insects.

PubMed

Lynch, Jeremy A; Roth, Siegfried

2011-01-15

The gene regulatory network (GRN) underpinning dorsal-ventral (DV) patterning of the Drosophila embryo is among the most thoroughly understood GRNs, making it an ideal system for comparative studies seeking to understand the evolution of development. With the emergence of widely applicable techniques for testing gene function, species with sequenced genomes, and multiple tractable species with diverse developmental modes, a phylogenetically broad and molecularly deep understanding of the evolution of DV axis formation in insects is feasible. Here, we review recent progress made in this field, compare our emerging molecular understanding to classical embryological experiments, and suggest future directions of inquiry.

Consentaneous Agent-Based and Stochastic Model of the Financial Markets

PubMed Central

Gontis, Vygintas; Kononovicius, Aleksejus

2014-01-01

We are looking for the agent-based treatment of the financial markets considering necessity to build bridges between microscopic, agent based, and macroscopic, phenomenological modeling. The acknowledgment that agent-based modeling framework, which may provide qualitative and quantitative understanding of the financial markets, is very ambiguous emphasizes the exceptional value of well defined analytically tractable agent systems. Herding as one of the behavior peculiarities considered in the behavioral finance is the main property of the agent interactions we deal with in this contribution. Looking for the consentaneous agent-based and macroscopic approach we combine two origins of the noise: exogenous one, related to the information flow, and endogenous one, arising form the complex stochastic dynamics of agents. As a result we propose a three state agent-based herding model of the financial markets. From this agent-based model we derive a set of stochastic differential equations, which describes underlying macroscopic dynamics of agent population and log price in the financial markets. The obtained solution is then subjected to the exogenous noise, which shapes instantaneous return fluctuations. We test both Gaussian and q-Gaussian noise as a source of the short term fluctuations. The resulting model of the return in the financial markets with the same set of parameters reproduces empirical probability and spectral densities of absolute return observed in New York, Warsaw and NASDAQ OMX Vilnius Stock Exchanges. Our result confirms the prevalent idea in behavioral finance that herding interactions may be dominant over agent rationality and contribute towards bubble formation. PMID:25029364

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

PubMed

Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

2011-01-01

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

Childhood pneumonia and crowding, bed-sharing and nutrition: a case-control study from The Gambia.

PubMed

Howie, S R C; Schellenberg, J; Chimah, O; Ideh, R C; Ebruke, B E; Oluwalana, C; Mackenzie, G; Jallow, M; Njie, M; Donkor, S; Dionisio, K L; Goldberg, G; Fornace, K; Bottomley, C; Hill, P C; Grant, C C; Corrah, T; Prentice, A M; Ezzati, M; Greenwood, B M; Smith, P G; Adegbola, R A; Mulholland, K

2016-10-01

Greater Banjul and Upper River Regions, The Gambia. To investigate tractable social, environmental and nutritional risk factors for childhood pneumonia. A case-control study examining the association of crowding, household air pollution (HAP) and nutritional factors with pneumonia was undertaken in children aged 2-59 months: 458 children with severe pneumonia, defined according to the modified WHO criteria, were compared with 322 children with non-severe pneumonia, and these groups were compared to 801 neighbourhood controls. Controls were matched by age, sex, area and season. Strong evidence was found of an association between bed-sharing with someone with a cough and severe pneumonia (adjusted OR [aOR] 5.1, 95%CI 3.2-8.2, P < 0.001) and non-severe pneumonia (aOR 7.3, 95%CI 4.1-13.1, P < 0.001), with 18% of severe cases estimated to be attributable to this risk factor. Malnutrition and pneumonia had clear evidence of association, which was strongest between severe malnutrition and severe pneumonia (aOR 8.7, 95%CI 4.2-17.8, P < 0.001). No association was found between pneumonia and individual carbon monoxide exposure as a measure of HAP. Bed-sharing with someone with a cough is an important risk factor for severe pneumonia, and potentially tractable to intervention, while malnutrition remains an important tractable determinant.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beck, Ashley; Hunt, Kristopher; Bernstein, Hans C.

Interest in microbial communities for bioprocessing has surged in recent years based on the potential to optimize multiple tasks simultaneously and to enhance process productivity and stability. The presence and magnitude of these desirable system properties often result from interactions between functionally distinct community members. The importance of interactions, while appreciated by some disciplines for decades, has gained interest recently due to the development of ‘omics techniques, polymicrobial culturing approaches, and computational methods which has made the systems-level analysis of interacting components more tractable. This review defines and categorizes natural and engineered system components, interactions, and emergent properties, as wellmore » as presents three ecological theories relevant to microbial communities. Case studies are interpreted to illustrate components, interactions, emergent properties and agreement with theoretical concepts. A general foundation is laid to facilitate interpretation of current systems and to aid in future design of microbial systems for the next generation of bioprocesses.« less

Optimal control of epidemic information dissemination over networks.

PubMed

Chen, Pin-Yu; Cheng, Shin-Ming; Chen, Kwang-Cheng

2014-12-01

Information dissemination control is of crucial importance to facilitate reliable and efficient data delivery, especially in networks consisting of time-varying links or heterogeneous links. Since the abstraction of information dissemination much resembles the spread of epidemics, epidemic models are utilized to characterize the collective dynamics of information dissemination over networks. From a systematic point of view, we aim to explore the optimal control policy for information dissemination given that the control capability is a function of its distribution time, which is a more realistic model in many applications. The main contributions of this paper are to provide an analytically tractable model for information dissemination over networks, to solve the optimal control signal distribution time for minimizing the accumulated network cost via dynamic programming, and to establish a parametric plug-in model for information dissemination control. In particular, we evaluate its performance in mobile and generalized social networks as typical examples.

Getting more from accuracy and response time data: methods for fitting the linear ballistic accumulator.

PubMed

Donkin, Chris; Averell, Lee; Brown, Scott; Heathcote, Andrew

2009-11-01

Cognitive models of the decision process provide greater insight into response time and accuracy than do standard ANOVA techniques. However, such models can be mathematically and computationally difficult to apply. We provide instructions and computer code for three methods for estimating the parameters of the linear ballistic accumulator (LBA), a new and computationally tractable model of decisions between two or more choices. These methods-a Microsoft Excel worksheet, scripts for the statistical program R, and code for implementation of the LBA into the Bayesian sampling software WinBUGS-vary in their flexibility and user accessibility. We also provide scripts in R that produce a graphical summary of the data and model predictions. In a simulation study, we explored the effect of sample size on parameter recovery for each method. The materials discussed in this article may be downloaded as a supplement from http://brm.psychonomic-journals.org/content/supplemental.

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

NASA Astrophysics Data System (ADS)

Mach, J. C.; Budrow, C. J.; Pagan, D. C.; Ruff, J. P. C.; Park, J.-S.; Okasinski, J.; Beaudoin, A. J.; Miller, M. P.

2017-05-01

Integrated computational materials engineering (ICME) provides a pathway to advance performance in structures through the use of physically-based models to better understand how manufacturing processes influence product performance. As one particular challenge, consider that residual stresses induced in fabrication are pervasive and directly impact the life of structures. For ICME to be an effective strategy, it is essential that predictive capability be developed in conjunction with critical experiments. In the present work, simulation results from a multi-physics model for gas metal arc welding are evaluated through x-ray diffraction using synchrotron radiation. A test component was designed with intent to develop significant gradients in residual stress, be representative of real-world engineering application, yet remain tractable for finely spaced strain measurements with positioning equipment available at synchrotron facilities. The experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.

Impact of Adsorption on Gas Transport in Nanopores.

PubMed

Wu, Tianhao; Zhang, Dongxiao

2016-03-29

Given the complex nature of the interaction between gas and solid atoms, the development of nanoscale science and technology has engendered a need for further understanding of gas transport behavior through nanopores and more tractable models for large-scale simulations. In the present paper, we utilize molecular dynamic simulations to demonstrate the behavior of gas flow under the influence of adsorption in nano-channels consisting of illite and graphene, respectively. The results indicate that velocity oscillation exists along the cross-section of the nano-channel, and the total mass flow could be either enhanced or reduced depending on variations in adsorption under different conditions. The mechanisms can be explained by the extra average perturbation stress arising from density oscillation via the novel perturbation model for micro-scale simulation, and approximated via the novel dual-region model for macro-scale simulation, which leads to a more accurate permeability correction model for industrial applications than is currently available.

Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii

DOE PAGES

Milano, Elizabeth R.; Payne, Courtney E.; Wolfrum, Edward J.; ...

2018-02-03

Biofuels derived from lignocellulosic plant material are an important component of current renewable energy strategies. Improvement efforts in biofuel feedstock crops have been primarily focused on increasing biomass yield with less consideration for tissue quality or composition. Four primary components found in the plant cell wall contribute to the overall quality of plant tissue and conversion characteristics, cellulose and hemicellulose polysaccharides are the primary targets for fuel conversion, while lignin and ash provide structure and defense. We explore the genetic architecture of tissue characteristics using a quantitative trait loci (QTL) mapping approach in Panicum hallii, a model lignocellulosic grass system.more » Diversity in the mapping population was generated by crossing xeric and mesic varietals, comparative to northern upland and southern lowland ecotypes in switchgrass. We use near-infrared spectroscopy with a primary analytical method to create a P. hallii specific calibration model to quickly quantify cell wall components. Ash, lignin, glucan, and xylan comprise 68% of total dry biomass in P. hallii: comparable to other feedstocks. We identified 14 QTL and one epistatic interaction across these four cell wall traits and found almost half of the QTL to localize to a single linkage group. Panicum hallii serves as the genomic model for its close relative and emerging biofuel crop, switchgrass (P. virgatum). We used high throughput phenotyping to map genomic regions that impact natural variation in leaf tissue composition. Understanding the genetic architecture of tissue traits in a tractable model grass system will lead to a better understanding of cell wall structure as well as provide genomic resources for bioenergy crop breeding programs.« less

Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii

DOE Office of Scientific and Technical Information (OSTI.GOV)

Milano, Elizabeth R.; Payne, Courtney E.; Wolfrum, Edward J.

Biofuels derived from lignocellulosic plant material are an important component of current renewable energy strategies. Improvement efforts in biofuel feedstock crops have been primarily focused on increasing biomass yield with less consideration for tissue quality or composition. Four primary components found in the plant cell wall contribute to the overall quality of plant tissue and conversion characteristics, cellulose and hemicellulose polysaccharides are the primary targets for fuel conversion, while lignin and ash provide structure and defense. We explore the genetic architecture of tissue characteristics using a quantitative trait loci (QTL) mapping approach in Panicum hallii, a model lignocellulosic grass system.more » Diversity in the mapping population was generated by crossing xeric and mesic varietals, comparative to northern upland and southern lowland ecotypes in switchgrass. We use near-infrared spectroscopy with a primary analytical method to create a P. hallii specific calibration model to quickly quantify cell wall components. Ash, lignin, glucan, and xylan comprise 68% of total dry biomass in P. hallii: comparable to other feedstocks. We identified 14 QTL and one epistatic interaction across these four cell wall traits and found almost half of the QTL to localize to a single linkage group. Panicum hallii serves as the genomic model for its close relative and emerging biofuel crop, switchgrass (P. virgatum). We used high throughput phenotyping to map genomic regions that impact natural variation in leaf tissue composition. Understanding the genetic architecture of tissue traits in a tractable model grass system will lead to a better understanding of cell wall structure as well as provide genomic resources for bioenergy crop breeding programs.« less

A Neural Network Architecture For Rapid Model Indexing In Computer Vision Systems

NASA Astrophysics Data System (ADS)

Pawlicki, Ted

1988-03-01

Models of objects stored in memory have been shown to be useful for guiding the processing of computer vision systems. A major consideration in such systems, however, is how stored models are initially accessed and indexed by the system. As the number of stored models increases, the time required to search memory for the correct model becomes high. Parallel distributed, connectionist, neural networks' have been shown to have appealing content addressable memory properties. This paper discusses an architecture for efficient storage and reference of model memories stored as stable patterns of activity in a parallel, distributed, connectionist, neural network. The emergent properties of content addressability and resistance to noise are exploited to perform indexing of the appropriate object centered model from image centered primitives. The system consists of three network modules each of which represent information relative to a different frame of reference. The model memory network is a large state space vector where fields in the vector correspond to ordered component objects and relative, object based spatial relationships between the component objects. The component assertion network represents evidence about the existence of object primitives in the input image. It establishes local frames of reference for object primitives relative to the image based frame of reference. The spatial relationship constraint network is an intermediate representation which enables the association between the object based and the image based frames of reference. This intermediate level represents information about possible object orderings and establishes relative spatial relationships from the image based information in the component assertion network below. It is also constrained by the lawful object orderings in the model memory network above. The system design is consistent with current psychological theories of recognition by component. It also seems to support Marr's notions of hierarchical indexing. (i.e. the specificity, adjunct, and parent indices) It supports the notion that multiple canonical views of an object may have to be stored in memory to enable its efficient identification. The use of variable fields in the state space vectors appears to keep the number of required nodes in the network down to a tractable number while imposing a semantic value on different areas of the state space. This semantic imposition supports an interface between the analogical aspects of neural networks and the propositional paradigms of symbolic processing.

The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization.

PubMed

Noor, Elad; Flamholz, Avi; Bar-Even, Arren; Davidi, Dan; Milo, Ron; Liebermeister, Wolfram

2016-11-01

Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell's capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering. It depends on enzyme parameters (such as kcat and KM constants), but also on metabolite concentrations. Moreover, similar amounts of different enzymes might incur different costs for the cell, depending on enzyme-specific properties such as protein size and half-life. Here, we developed enzyme cost minimization (ECM), a scalable method for computing enzyme amounts that support a given metabolic flux at a minimal protein cost. The complex interplay of enzyme and metabolite concentrations, e.g. through thermodynamic driving forces and enzyme saturation, would make it hard to solve this optimization problem directly. By treating enzyme cost as a function of metabolite levels, we formulated ECM as a numerically tractable, convex optimization problem. Its tiered approach allows for building models at different levels of detail, depending on the amount of available data. Validating our method with measured metabolite and protein levels in E. coli central metabolism, we found typical prediction fold errors of 4.1 and 2.6, respectively, for the two kinds of data. This result from the cost-optimized metabolic state is significantly better than randomly sampled metabolite profiles, supporting the hypothesis that enzyme cost is important for the fitness of E. coli. ECM can be used to predict enzyme levels and protein cost in natural and engineered pathways, and could be a valuable computational tool to assist metabolic engineering projects. Furthermore, it establishes a direct connection between protein cost and thermodynamics, and provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or oversimplified.

An evolutionary reduction principle for mutation rates at multiple Loci.

PubMed

Altenberg, Lee

2011-06-01

A model of mutation rate evolution for multiple loci under arbitrary selection is analyzed. Results are obtained using techniques from Karlin (Evolutionary Biology, vol. 14, pp. 61-204, 1982) that overcome the weak selection constraints needed for tractability in prior studies of multilocus event models.A multivariate form of the reduction principle is found: reduction results at individual loci combine topologically to produce a surface of mutation rate alterations that are neutral for a new modifier allele. New mutation rates survive if and only if they fall below this surface-a generalization of the hyperplane found by Zhivotovsky et al. (Proc. Natl. Acad. Sci. USA 91, 1079-1083, 1994) for a multilocus recombination modifier. Increases in mutation rates at some loci may evolve if compensated for by decreases at other loci. The strength of selection on the modifier scales in proportion to the number of germline cell divisions, and increases with the number of loci affected. Loci that do not make a difference to marginal fitnesses at equilibrium are not subject to the reduction principle, and under fine tuning of mutation rates would be expected to have higher mutation rates than loci in mutation-selection balance.Other results include the nonexistence of 'viability analogous, Hardy-Weinberg' modifier polymorphisms under multiplicative mutation, and the sufficiency of average transmission rates to encapsulate the effect of modifier polymorphisms on the transmission of loci under selection. A conjecture is offered regarding situations, like recombination in the presence of mutation, that exhibit departures from the reduction principle. Constraints for tractability are: tight linkage of all loci, initial fixation at the modifier locus, and mutation distributions comprising transition probabilities of reversible Markov chains.

The Pathophysiology of Repetitive Concussive Traumatic Brain Injury in Experimental Models; New Developments and Open Questions

PubMed Central

Brody, David L; Benetatos, Joseph; Bennett, Rachel E; Klemenhagen, Kristen C; Donald, Christine L Mac

2015-01-01

In recent years, there has been an increasing interest in the pathophysiology of repetitive concussive traumatic brain injury (rcTBI) in large part due to the association with dramatic cases of progressive neurological deterioration in professional athletes, military personnel, and others. However, our understanding of the pathophysiology of rcTBI is less advanced than for more severe brain injuries. Most prominently, the mechanisms underlying traumatic axonal injury, microglial activation, amyloid-beta accumulation, and progressive tau pathology are not yet known. In addition, the role of injury to dendritic spine cytoskeletal structures, vascular reactivity impairments, and microthrombi are intriguing and subjects of ongoing inquiry. Methods for quantitative analysis of axonal injury, dendritic injury, and synaptic loss need to be refined for the field to move forward in a rigorous fashion. We and others are attempting to develop translational approaches to assess these specific pathophysiological events in both animals and humans to facilitate clinically relevant pharmacodynamic assessments of candidate therapeutics. In this article, we review and discuss several of the recent experimental results from our lab and others. We include new initial data describing the difficulty in modeling progressive tau pathology in experimental rcTBI, and results demonstrating that sertraline can alleviate social interaction deficits and depressive-like behaviors following experimental rcTBI plus foot shock stress. Furthermore, we propose a discrete set of open, experimentally tractable questions that may serve as a framework for future investigations. In addition, we also raise several important questions that are less experimentally tractable at this time, in hopes that they may stimulate future methodological developments to address them. PMID:25684677

A rapid response air quality analysis system for use in projects having stringent quality assurance requirements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, A.W.

1990-04-01

This paper describes an approach to solve air quality problems which frequently occur during iterations of the baseline change process. From a schedule standpoint, it is desirable to perform this evaluation in as short a time as possible while budgetary pressures limit the size of the staff available to do the work. Without a method in place to deal with baseline change proposal requests the environment analysts may not be able to produce the analysis results in the time frame expected. Using a concept called the Rapid Response Air Quality Analysis System (RAAS), the problems of timing and cost becomemore » tractable. The system could be adapted to assess other atmospheric pathway impacts, e.g., acoustics or visibility. The air quality analysis system used to perform the EA analysis (EA) for the Salt Repository Project (part of the Civilian Radioactive Waste Management Program), and later to evaluate the consequences of proposed baseline changes, consists of three components: Emission source data files; Emission rates contained in spreadsheets; Impact assessment model codes. The spreadsheets contain user-written codes (macros) that calculate emission rates from (1) emission source data (e.g., numbers and locations of sources, detailed operating schedules, and source specifications including horsepower, load factor, and duty cycle); (2) emission factors such as those published by the U.S. Environmental Protection Agency, and (3) control efficiencies.« less

MAVS-dependent host species range and pathogenicity of human hepatitis A virus.

PubMed

Hirai-Yuki, Asuka; Hensley, Lucinda; McGivern, David R; González-López, Olga; Das, Anshuman; Feng, Hui; Sun, Lu; Wilson, Justin E; Hu, Fengyu; Feng, Zongdi; Lovell, William; Misumi, Ichiro; Ting, Jenny P-Y; Montgomery, Stephanie; Cullen, John; Whitmire, Jason K; Lemon, Stanley M

2016-09-30

Hepatotropic viruses are important causes of human disease, but the intrahepatic immune response to hepatitis viruses is poorly understood because of a lack of tractable small- animal models. We describe a murine model of hepatitis A virus (HAV) infection that recapitulates critical features of type A hepatitis in humans. We demonstrate that the capacity of HAV to evade MAVS-mediated type I interferon responses defines its host species range. HAV-induced liver injury was associated with interferon-independent intrinsic hepatocellular apoptosis and hepatic inflammation that unexpectedly resulted from MAVS and IRF3/7 signaling. This murine model thus reveals a previously undefined link between innate immune responses to virus infection and acute liver injury, providing a new paradigm for viral pathogenesis in the liver. Copyright © 2016, American Association for the Advancement of Science.

Construction of high quality Gateway™ entry libraries and their application to yeast two-hybrid for the monocot model plant Brachypodium distachyon.

PubMed

Cao, Shuanghe; Siriwardana, Chamindika L; Kumimoto, Roderick W; Holt, Ben F

2011-05-19

Monocots, especially the temperate grasses, represent some of the most agriculturally important crops for both current food needs and future biofuel development. Because most of the agriculturally important grass species are difficult to study (e.g., they often have large, repetitive genomes and can be difficult to grow in laboratory settings), developing genetically tractable model systems is essential. Brachypodium distachyon (hereafter Brachypodium) is an emerging model system for the temperate grasses. To fully realize the potential of this model system, publicly accessible discovery tools are essential. High quality cDNA libraries that can be readily adapted for multiple downstream purposes are a needed resource. Additionally, yeast two-hybrid (Y2H) libraries are an important discovery tool for protein-protein interactions and are not currently available for Brachypodium. We describe the creation of two high quality, publicly available Gateway™ cDNA entry libraries and their derived Y2H libraries for Brachypodium. The first entry library represents cloned cDNA populations from both short day (SD, 8/16-h light/dark) and long day (LD, 20/4-h light/dark) grown plants, while the second library was generated from hormone treated tissues. Both libraries have extensive genome coverage (~5 × 107 primary clones each) and average clone lengths of ~1.5 Kb. These entry libraries were then used to create two recombination-derived Y2H libraries. Initial proof-of-concept screens demonstrated that a protein with known interaction partners could readily re-isolate those partners, as well as novel interactors. Accessible community resources are a hallmark of successful biological model systems. Brachypodium has the potential to be a broadly useful model system for the grasses, but still requires many of these resources. The Gateway™ compatible entry libraries created here will facilitate studies for multiple user-defined purposes and the derived Y2H libraries can be immediately applied to large scale screening and discovery of novel protein-protein interactions. All libraries are freely available for distribution to the research community.

Science and Sentiment: Grinnell's Fact-Based Philosophy of Biodiversity Conservation.

PubMed

Shavit, Ayelet; Griesemer, James R

2018-06-01

At the beginning of the twentieth century, the biologist Joseph Grinnell made a distinction between science and sentiment for producing fact-based generalizations on how to conserve biodiversity. We are inspired by Grinnellian science, which successfully produced a century-long impact on studying and conserving biodiversity that runs orthogonal to some familiar philosophical distinctions such as fact versus value, emotion versus reason and basic versus applied science. According to Grinnell, unlike sentiment-based generalizations, a fact-based generalization traces its diverse commitments and thus becomes tractable for its audience. We argue that foregrounding tractability better explains Grinnell's practice in the context of his time as well as in the context of current discourse among scientists over the political "biases" of biodiversity research and its problem of "reproducibility."

Identification of Small RNA-Protein Partners in Plant Symbiotic Bacteria.

PubMed

Robledo, Marta; Matia-González, Ana M; García-Tomsig, Natalia I; Jiménez-Zurdo, José I

2018-01-01

The identification of the protein partners of bacterial small noncoding RNAs (sRNAs) is essential to understand the mechanistic principles and functions of riboregulation in prokaryotic cells. Here, we describe an optimized affinity chromatography protocol that enables purification of in vivo formed sRNA-protein complexes in Sinorhizobium meliloti, a genetically tractable nitrogen-fixing plant symbiotic bacterium. The procedure requires the tagging of the desired sRNA with the MS2 aptamer, which is affinity-captured by the MS2-MBP protein conjugated to an amylose resin. As proof of principle, we show recovery of the RNA chaperone Hfq associated to the strictly Hfq-dependent AbcR2 trans-sRNA. This method can be applied for the investigation of sRNA-protein interactions on a broad range of genetically tractable α-proteobacteria.

The ALK receptor in sympathetic neuron development and neuroblastoma.

PubMed

Janoueix-Lerosey, Isabelle; Lopez-Delisle, Lucille; Delattre, Olivier; Rohrer, Hermann

2018-05-01

The ALK gene encodes a tyrosine kinase receptor characterized by an expression pattern mainly restricted to the developing central and peripheral nervous systems. In 2008, the discovery of ALK activating mutations in neuroblastoma, a tumor of the sympathetic nervous system, represented a breakthrough in the understanding of the pathogenesis of this pediatric cancer and established mutated ALK as a tractable therapeutic target for precision medicine. Subsequent studies addressed the identity of ALK ligands, as well as its physiological function in the sympathoadrenal lineage, its role in neuroblastoma development and the signaling pathways triggered by mutated ALK. This review focuses on these different aspects of the ALK biology and summarizes the various therapeutic strategies relying on ALK inhibition in neuroblastoma, either as monotherapies or combinatory treatments.

Microbiota-induced changes in drosophila melanogaster host gene expression and gut morphology.

PubMed

Broderick, Nichole A; Buchon, Nicolas; Lemaitre, Bruno

2014-05-27

To elucidate mechanisms underlying the complex relationships between a host and its microbiota, we used the genetically tractable model Drosophila melanogaster. Consistent with previous studies, the microbiota was simple in composition and diversity. However, analysis of single flies revealed high interfly variability that correlated with differences in feeding. To understand the effects of this simple and variable consortium, we compared the transcriptome of guts from conventionally reared flies to that for their axenically reared counterparts. Our analysis of two wild-type fly lines identified 121 up- and 31 downregulated genes. The majority of these genes were associated with immune responses, tissue homeostasis, gut physiology, and metabolism. By comparing the transcriptomes of young and old flies, we identified temporally responsive genes and showed that the overall impact of microbiota was greater in older flies. In addition, comparison of wild-type gene expression with that of an immune-deficient line revealed that 53% of upregulated genes exerted their effects through the immune deficiency (Imd) pathway. The genes included not only classic immune response genes but also those involved in signaling, gene expression, and metabolism, unveiling new and unexpected connections between immunity and other systems. Given these findings, we further characterized the effects of gut-associated microbes on gut morphology and epithelial architecture. The results showed that the microbiota affected gut morphology through their impacts on epithelial renewal rate, cellular spacing, and the composition of different cell types in the epithelium. Thus, while bacteria in the gut are highly variable, the influence of the microbiota at large has far-reaching effects on host physiology. The guts of animals are in constant association with microbes, and these interactions are understood to have important roles in animal development and physiology. Yet we know little about the mechanisms underlying the establishment and function of these associations. Here, we used the fruit fly to understand how the microbiota affects host function. Importantly, we found that the microbiota has far-reaching effects on host physiology, ranging from immunity to gut structure. Our results validate the notion that important insights on complex host-microbe relationships can be obtained from the use of a well-established and genetically tractable invertebrate model. Copyright © 2014 Broderick et al.

A Scalable Computational Framework for Establishing Long-Term Behavior of Stochastic Reaction Networks

PubMed Central

Khammash, Mustafa

2014-01-01

Reaction networks are systems in which the populations of a finite number of species evolve through predefined interactions. Such networks are found as modeling tools in many biological disciplines such as biochemistry, ecology, epidemiology, immunology, systems biology and synthetic biology. It is now well-established that, for small population sizes, stochastic models for biochemical reaction networks are necessary to capture randomness in the interactions. The tools for analyzing such models, however, still lag far behind their deterministic counterparts. In this paper, we bridge this gap by developing a constructive framework for examining the long-term behavior and stability properties of the reaction dynamics in a stochastic setting. In particular, we address the problems of determining ergodicity of the reaction dynamics, which is analogous to having a globally attracting fixed point for deterministic dynamics. We also examine when the statistical moments of the underlying process remain bounded with time and when they converge to their steady state values. The framework we develop relies on a blend of ideas from probability theory, linear algebra and optimization theory. We demonstrate that the stability properties of a wide class of biological networks can be assessed from our sufficient theoretical conditions that can be recast as efficient and scalable linear programs, well-known for their tractability. It is notably shown that the computational complexity is often linear in the number of species. We illustrate the validity, the efficiency and the wide applicability of our results on several reaction networks arising in biochemistry, systems biology, epidemiology and ecology. The biological implications of the results as well as an example of a non-ergodic biological network are also discussed. PMID:24968191

A Tractable Experimental Model for Study of Human and Animal Scabies

PubMed Central

Mounsey, Kate; Ho, Mei-Fong; Kelly, Andrew; Willis, Charlene; Pasay, Cielo; Kemp, David J.; McCarthy, James S.; Fischer, Katja

2010-01-01

Background Scabies is a parasitic skin infestation caused by the burrowing mite Sarcoptes scabiei. It is common worldwide and spreads rapidly under crowded conditions, such as those found in socially disadvantaged communities of Indigenous populations and in developing countries. Pruritic scabies lesions facilitate opportunistic bacterial infections, particularly Group A streptococci. Streptococcal infections cause significant sequelae and the increased community streptococcal burden has led to extreme levels of acute rheumatic fever and rheumatic heart disease in Australia's Indigenous communities. In addition, emerging resistance to currently available therapeutics emphasizes the need to identify potential targets for novel chemotherapeutic and/or immunological intervention. Scabies research has been severely limited by the availability of parasites, and scabies remains a truly neglected infectious disease. We report development of a tractable model for scabies in the pig, Sus domestica. Methodology/Principal Findings Over five years and involving ten independent cohorts, we have developed a protocol for continuous passage of Sarcoptes scabiei var. suis. To increase intensity and duration of infestation without generating animal welfare issues we have optimised an immunosuppression regimen utilising daily oral treatment with 0.2mg/kg dexamethasone. Only mild, controlled side effects are observed, and mange infection can be maintained indefinitely providing large mite numbers (>6000 mites/g skin) for molecular-based research on scabies. In pilot experiments we explore whether any adaptation of the mite population is reflected in genetic changes. Phylogenetic analysis was performed comparing sets of genetic data obtained from pig mites collected from naturally infected pigs with data from pig mites collected from the most recent cohort. Conclusions/Significance A reliable pig/scabies animal model will facilitate in vivo studies on host immune responses to scabies including the relations to the associated bacterial pathogenesis and more detailed studies of molecular evolution and host adaption. It is a most needed tool for the further investigation of this important and widespread parasitic disease. PMID:20668508

Parameterizing by the Number of Numbers

NASA Astrophysics Data System (ADS)

Fellows, Michael R.; Gaspers, Serge; Rosamond, Frances A.

The usefulness of parameterized algorithmics has often depended on what Niedermeier has called "the art of problem parameterization". In this paper we introduce and explore a novel but general form of parameterization: the number of numbers. Several classic numerical problems, such as Subset Sum, Partition, 3-Partition, Numerical 3-Dimensional Matching, and Numerical Matching with Target Sums, have multisets of integers as input. We initiate the study of parameterizing these problems by the number of distinct integers in the input. We rely on an FPT result for Integer Linear Programming Feasibility to show that all the above-mentioned problems are fixed-parameter tractable when parameterized in this way. In various applied settings, problem inputs often consist in part of multisets of integers or multisets of weighted objects (such as edges in a graph, or jobs to be scheduled). Such number-of-numbers parameterized problems often reduce to subproblems about transition systems of various kinds, parameterized by the size of the system description. We consider several core problems of this kind relevant to number-of-numbers parameterization. Our main hardness result considers the problem: given a non-deterministic Mealy machine M (a finite state automaton outputting a letter on each transition), an input word x, and a census requirement c for the output word specifying how many times each letter of the output alphabet should be written, decide whether there exists a computation of M reading x that outputs a word y that meets the requirement c. We show that this problem is hard for W[1]. If the question is whether there exists an input word x such that a computation of M on x outputs a word that meets c, the problem becomes fixed-parameter tractable.

Full-Duplex Bidirectional Secure Communications Under Perfect and Distributionally Ambiguous Eavesdropper's CSI

NASA Astrophysics Data System (ADS)

Li, Qiang; Zhang, Ying; Lin, Jingran; Wu, Sissi Xiaoxiao

2017-09-01

Consider a full-duplex (FD) bidirectional secure communication system, where two communication nodes, named Alice and Bob, simultaneously transmit and receive confidential information from each other, and an eavesdropper, named Eve, overhears the transmissions. Our goal is to maximize the sum secrecy rate (SSR) of the bidirectional transmissions by optimizing the transmit covariance matrices at Alice and Bob. To tackle this SSR maximization (SSRM) problem, we develop an alternating difference-of-concave (ADC) programming approach to alternately optimize the transmit covariance matrices at Alice and Bob. We show that the ADC iteration has a semi-closed-form beamforming solution, and is guaranteed to converge to a stationary solution of the SSRM problem. Besides the SSRM design, this paper also deals with a robust SSRM transmit design under a moment-based random channel state information (CSI) model, where only some roughly estimated first and second-order statistics of Eve's CSI are available, but the exact distribution or other high-order statistics is not known. This moment-based error model is new and different from the widely used bounded-sphere error model and the Gaussian random error model. Under the consider CSI error model, the robust SSRM is formulated as an outage probability-constrained SSRM problem. By leveraging the Lagrangian duality theory and DC programming, a tractable safe solution to the robust SSRM problem is derived. The effectiveness and the robustness of the proposed designs are demonstrated through simulations.

Identifying research priorities for public health research to address health inequalities: use of Delphi-like survey methods.

PubMed

Turner, S; Ollerhead, E; Cook, A

2017-10-09

In the funding of health research and public health research it is vital that research questions posed are important and that funded research meets a research need or a gap in evidence. Many methods are used in the identification of research priorities, however, these can be resource intensive, costly and logistically challenging. Identifying such research priorities can be particularly challenging for complex public health problems as there is a need to consult a number of experts across disciplines and with a range of expertise. This study investigated the use of Delphi-like survey methods in identifying important research priorities relating to health inequalities and framing tractable research questions for topic areas identified. The study was conducted in two phases, both using Delphi-like survey methods. Firstly, public health professionals with an interest in health inequalities were asked to identify research priorities. Secondly academic researchers were asked to frame tractable research questions relating to the priorities identified. These research priorities identified using Delphi-like survey methods were subsequently compared to those identified using different methods. A total of 52 public health professionals and 21 academics across the United Kingdom agreed to take part. The response rates were high, from public health professionals across three survey rounds (69%, 50% and 40%) and from academics across one round (52%), indicating that participants were receptive to the method and motivated to respond. The themes identified as encompassing the most important research priorities were mental health, healthy environment and health behaviours. Within these themes, the topic areas that emerged most strongly included community interventions for prevention of mental health problems and the food and alcohol environment. Some responses received from academic researchers were (as requested) in the form of tractable research questions, whereas others contributed further potential topic areas instead. Delphi-like survey methods are practical and productive as a means of obtaining opinions from a wide number of relevant experts identifying potential priority topic areas for research; however, this method is less appropriate for framing tractable research questions.

A generative spike train model with time-structured higher order correlations.

PubMed

Trousdale, James; Hu, Yu; Shea-Brown, Eric; Josić, Krešimir

2013-01-01

Emerging technologies are revealing the spiking activity in ever larger neural ensembles. Frequently, this spiking is far from independent, with correlations in the spike times of different cells. Understanding how such correlations impact the dynamics and function of neural ensembles remains an important open problem. Here we describe a new, generative model for correlated spike trains that can exhibit many of the features observed in data. Extending prior work in mathematical finance, this generalized thinning and shift (GTaS) model creates marginally Poisson spike trains with diverse temporal correlation structures. We give several examples which highlight the model's flexibility and utility. For instance, we use it to examine how a neural network responds to highly structured patterns of inputs. We then show that the GTaS model is analytically tractable, and derive cumulant densities of all orders in terms of model parameters. The GTaS framework can therefore be an important tool in the experimental and theoretical exploration of neural dynamics.

A knowledge base architecture for distributed knowledge agents

NASA Technical Reports Server (NTRS)

Riedesel, Joel; Walls, Bryan

1990-01-01

A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

New solutions with accelerated expansion in string theory

DOE PAGES

Dodelson, Matthew; Dong, Xi; Silverstein, Eva; ...

2014-12-05

We present concrete solutions with accelerated expansion in string theory, requiring a small, tractable list of stress energy sources. We explain how this construction (and others in progress) evades previous no go theorems for simple accelerating solutions. Our solutions respect an approximate scaling symmetry and realize discrete sequences of values for the equation of state, including one with an accumulation point at w = –1 and another accumulating near w = –1/3 from below. In another class of models, a density of defects generates scaling solutions with accelerated expansion. Here, we briefly discuss potential applications to dark energy phenomenology, andmore » to holography for cosmology.« less

Alligator, Alligator mississippiensis, habitat suitability index model

USGS Publications Warehouse

Waddle, J. Hardin

2017-01-01

The 2012 Coastal Master Plan utilized Habitat Suitability Indices (HSIs) to evaluate potential project effects on wildlife species. Even though HSIs quantify habitat condition, which may not directly correlate to species abundance, they remain a practical and tractable way to assess changes in habitat quality from various restoration actions. As part of the legislatively mandated five year update to the 2012 plan, the wildlife habitat suitability indices were updated and revised using literature and existing field data where available. The outcome of these efforts resulted in improved, or in some cases entirely new suitability indices. This report describes the development of the habitat suitability indices for the American alligator, Alligator mississippiensis.

Markovian Search Games in Heterogeneous Spaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Griffin, Christopher H

2009-01-01

We consider how to search for a mobile evader in a large heterogeneous region when sensors are used for detection. Sensors are modeled using probability of detection. Due to environmental effects, this probability will not be constant over the entire region. We map this problem to a graph search problem and, even though deterministic graph search is NP-complete, we derive a tractable, optimal, probabilistic search strategy. We do this by defining the problem as a differential game played on a Markov chain. We prove that this strategy is optimal in the sense of Nash. Simulations of an example problem illustratemore » our approach and verify our claims.« less

RT-Syn: A real-time software system generator

NASA Technical Reports Server (NTRS)

Setliff, Dorothy E.

1992-01-01

This paper presents research into providing highly reusable and maintainable components by using automatic software synthesis techniques. This proposal uses domain knowledge combined with automatic software synthesis techniques to engineer large-scale mission-critical real-time software. The hypothesis centers on a software synthesis architecture that specifically incorporates application-specific (in this case real-time) knowledge. This architecture synthesizes complex system software to meet a behavioral specification and external interaction design constraints. Some examples of these external constraints are communication protocols, precisions, timing, and space limitations. The incorporation of application-specific knowledge facilitates the generation of mathematical software metrics which are used to narrow the design space, thereby making software synthesis tractable. Success has the potential to dramatically reduce mission-critical system life-cycle costs not only by reducing development time, but more importantly facilitating maintenance, modifications, and extensions of complex mission-critical software systems, which are currently dominating life cycle costs.

Mainstreaming Caenorhabditis elegans in experimental evolution.

PubMed

Gray, Jeremy C; Cutter, Asher D

2014-03-07

Experimental evolution provides a powerful manipulative tool for probing evolutionary process and mechanism. As this approach to hypothesis testing has taken purchase in biology, so too has the number of experimental systems that use it, each with its own unique strengths and weaknesses. The depth of biological knowledge about Caenorhabditis nematodes, combined with their laboratory tractability, positions them well for exploiting experimental evolution in animal systems to understand deep questions in evolution and ecology, as well as in molecular genetics and systems biology. To date, Caenorhabditis elegans and related species have proved themselves in experimental evolution studies of the process of mutation, host-pathogen coevolution, mating system evolution and life-history theory. Yet these organisms are not broadly recognized for their utility for evolution experiments and remain underexploited. Here, we outline this experimental evolution work undertaken so far in Caenorhabditis, detail simple methodological tricks that can be exploited and identify research areas that are ripe for future discovery.

A solid criterion based on strict LMI without invoking equality constraint for stabilization of continuous singular systems.

PubMed

Zhang, Xuefeng; Chen, YangQuan

2017-11-01

The paper considers the stabilization issue of linear continuous singular systems by dealing with strict linear matrix inequalities (LMIs) without invoking equality constraint and proposes a complete and effective solved LMIs formulation. The criterion is necessary and sufficient condition and can be directly solved the feasible solutions with LMI toolbox and is much more tractable and reliable in numerical simulation than existing results, which involve positive semi-definite LMIs with equality constraints. The most important property of the criterion proposed in the paper is that it can overcome the drawbacks of the invalidity caused by the singularity of Ω=PE T +SQ for stabilization of singular systems. Two counterexamples are presented to avoid the disadvantages of the existing condition of stabilization of continuous singular systems. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

An evolving effective stress approach to anisotropic distortional hardening

DOE PAGES

Lester, B. T.; Scherzinger, W. M.

2018-03-11

A new yield surface with an evolving effective stress definition is proposed for consistently and efficiently describing anisotropic distortional hardening. Specifically, a new internal state variable is introduced to capture the thermodynamic evolution between different effective stress definitions. The corresponding yield surface and evolution equations of the internal variables are derived from thermodynamic considerations enabling satisfaction of the second law. A closest point projection return mapping algorithm for the proposed model is formulated and implemented for use in finite element analyses. Finally, select constitutive and larger scale boundary value problems are solved to explore the capabilities of the model andmore » examine the impact of distortional hardening on constitutive and structural responses. Importantly, these simulations demonstrate the tractability of the proposed formulation in investigating large-scale problems of interest.« less

An evolving effective stress approach to anisotropic distortional hardening

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lester, B. T.; Scherzinger, W. M.

A new yield surface with an evolving effective stress definition is proposed for consistently and efficiently describing anisotropic distortional hardening. Specifically, a new internal state variable is introduced to capture the thermodynamic evolution between different effective stress definitions. The corresponding yield surface and evolution equations of the internal variables are derived from thermodynamic considerations enabling satisfaction of the second law. A closest point projection return mapping algorithm for the proposed model is formulated and implemented for use in finite element analyses. Finally, select constitutive and larger scale boundary value problems are solved to explore the capabilities of the model andmore » examine the impact of distortional hardening on constitutive and structural responses. Importantly, these simulations demonstrate the tractability of the proposed formulation in investigating large-scale problems of interest.« less

Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models

NASA Astrophysics Data System (ADS)

Allen, J. I.; Somerfield, P. J.; Gilbert, F. J.

2007-01-01

Marine ecosystem models are becoming increasingly complex and sophisticated, and are being used to estimate the effects of future changes in the earth system with a view to informing important policy decisions. Despite their potential importance, far too little attention has been, and is generally, paid to model errors and the extent to which model outputs actually relate to real-world processes. With the increasing complexity of the models themselves comes an increasing complexity among model results. If we are to develop useful modelling tools for the marine environment we need to be able to understand and quantify the uncertainties inherent in the simulations. Analysing errors within highly multivariate model outputs, and relating them to even more complex and multivariate observational data, are not trivial tasks. Here we describe the application of a series of techniques, including a 2-stage self-organising map (SOM), non-parametric multivariate analysis, and error statistics, to a complex spatio-temporal model run for the period 1988-1989 in the Southern North Sea, coinciding with the North Sea Project which collected a wealth of observational data. We use model output, large spatio-temporally resolved data sets and a combination of methodologies (SOM, MDS, uncertainty metrics) to simplify the problem and to provide tractable information on model performance. The use of a SOM as a clustering tool allows us to simplify the dimensions of the problem while the use of MDS on independent data grouped according to the SOM classification allows us to validate the SOM. The combination of classification and uncertainty metrics allows us to pinpoint the variables and associated processes which require attention in each region. We recommend the use of this combination of techniques for simplifying complex comparisons of model outputs with real data, and analysis of error distributions.

Sizing a rainwater harvesting cistern by minimizing costs

NASA Astrophysics Data System (ADS)

Pelak, Norman; Porporato, Amilcare

2016-10-01

Rainwater harvesting (RWH) has the potential to reduce water-related costs by providing an alternate source of water, in addition to relieving pressure on public water sources and reducing stormwater runoff. Existing methods for determining the optimal size of the cistern component of a RWH system have various drawbacks, such as specificity to a particular region, dependence on numerical optimization, and/or failure to consider the costs of the system. In this paper a formulation is developed for the optimal cistern volume which incorporates the fixed and distributed costs of a RWH system while also taking into account the random nature of the depth and timing of rainfall, with a focus on RWH to supply domestic, nonpotable uses. With rainfall inputs modeled as a marked Poisson process, and by comparing the costs associated with building a cistern with the costs of externally supplied water, an expression for the optimal cistern volume is found which minimizes the water-related costs. The volume is a function of the roof area, water use rate, climate parameters, and costs of the cistern and of the external water source. This analytically tractable expression makes clear the dependence of the optimal volume on the input parameters. An analysis of the rainfall partitioning also characterizes the efficiency of a particular RWH system configuration and its potential for runoff reduction. The results are compared to the RWH system at the Duke Smart Home in Durham, NC, USA to show how the method could be used in practice.

Phototrophic Biofilm Assembly in Microbial-Mat-Derived Unicyanobacterial Consortia: Model Systems for the Study of Autotroph-Heterotroph Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cole, Jessica K.; Hutchison, Janine R.; Renslow, Ryan S.

2014-04-07

Though microbial autotroph-heterotroph interactions influence biogeochemical cycles on a global scale, the diversity and complexity of natural systems and their intractability to in situ environmental manipulation makes elucidation of the principles governing these interactions challenging. Examination of primary succession during phototrophic biofilm assembly provides a robust means by which to elucidate the dynamics of such interactions and determine their influence upon recruitment and maintenance of phylogenetic and functional diversity in microbial communities. We isolated and characterized two unicyanobacterial consortia from the Hot Lake phototrophic mat, quantifying the structural and community composition of their assembling biofilms. The same heterotrophs were retainedmore » in both consortia and included members of Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes, taxa frequently reported as consorts of microbial photoautotrophs. Cyanobacteria led biofilm assembly, eventually giving way to a late heterotrophic bloom. The consortial biofilms exhibited similar patterns of assembly, with the relative abundances of members of Bacteroidetes and Alphaproteobacteria increasing and members of Gammaproteobacteria decreasing as colonization progressed. Despite similar trends in assembly at higher taxa, the consortia exhibited substantial differences in community structure at the species level. These similar patterns of assembly with divergent community structures suggest that, while similar niches are created by the metabolism of the cyanobacteria, the resultant webs of autotroph-heterotroph and heterotroph-heterotroph interactions driving metabolic exchange are specific to each primary producer. Altogether, our data support these Hot Lake unicyanobacterial consortia as generalizable model systems whose simplicity and tractability permit the deciphering of community assembly principles relevant to natural microbial communities.« less

Phototrophic biofilm assembly in microbial-mat-derived unicyanobacterial consortia: model systems for the study of autotroph-heterotroph interactions

PubMed Central

Cole, Jessica K.; Hutchison, Janine R.; Renslow, Ryan S.; Kim, Young-Mo; Chrisler, William B.; Engelmann, Heather E.; Dohnalkova, Alice C.; Hu, Dehong; Metz, Thomas O.; Fredrickson, Jim K.; Lindemann, Stephen R.

2014-01-01

Microbial autotroph-heterotroph interactions influence biogeochemical cycles on a global scale, but the diversity and complexity of natural systems and their intractability to in situ manipulation make it challenging to elucidate the principles governing these interactions. The study of assembling phototrophic biofilm communities provides a robust means to identify such interactions and evaluate their contributions to the recruitment and maintenance of phylogenetic and functional diversity over time. To examine primary succession in phototrophic communities, we isolated two unicyanobacterial consortia from the microbial mat in Hot Lake, Washington, characterizing the membership and metabolic function of each consortium. We then analyzed the spatial structures and quantified the community compositions of their assembling biofilms. The consortia retained the same suite of heterotrophic species, identified as abundant members of the mat and assigned to Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes. Autotroph growth rates dominated early in assembly, yielding to increasing heterotroph growth rates late in succession. The two consortia exhibited similar assembly patterns, with increasing relative abundances of members from Bacteroidetes and Alphaproteobacteria concurrent with decreasing relative abundances of those from Gammaproteobacteria. Despite these similarities at higher taxonomic levels, the relative abundances of individual heterotrophic species were substantially different in the developing consortial biofilms. This suggests that, although similar niches are created by the cyanobacterial metabolisms, the resulting webs of autotroph-heterotroph and heterotroph-heterotroph interactions are specific to each primary producer. The relative simplicity and tractability of the Hot Lake unicyanobacterial consortia make them useful model systems for deciphering interspecies interactions and assembly principles relevant to natural microbial communities. PMID:24778628

Creutzfeldt-Jakob disease and mad cows: lessons learnt from yeast cells.

PubMed

Hofmann, J; Wolf, H; Grassmann, A; Arndt, V; Graham, J; Vorberg, I

2012-01-24

Transmissible spongiform encephalopathies are fatal neurodegenerative diseases that affect mammals including humans. The proteinaceous nature of the infectious agent, the prion, and its propagation, challenge established dogmas in biology. It is now widely accepted that prion diseases are caused by unconventional agents principally composed of a misfolded host-encoded protein, PrP. Surprisingly, major break-throughs in prion research came from studies on functionally unrelated proteins in yeast and filamentous fungi. Aggregates composed of these proteins act as epigenetic elements of inheritance that can propagate their alternative states by a conformational switch into an ordered ß-sheet rich polymer just like mammalian prions. Since their discovery prions of lower eukaryotes have provided invaluable insights into all aspects of prion biogenesis. Importantly, yeast prions provide proof-of-principle that distinct protein conformers can be infectious and can serve as genetic elements that have the capacity to encipher strain specific information. As a powerful and tractable model system, yeast prions will continue to increase our understanding of prion-host cell interaction and potential mechanisms of protein-based epigenetic inheritance.

Caenorhabditis elegans star formation and negative chemotaxis induced by infection with corynebacteria.

PubMed

Antunes, Camila Azevedo; Clark, Laura; Wanuske, Marie-Therès; Hacker, Elena; Ott, Lisa; Simpson-Louredo, Liliane; de Luna, Maria das Gracas; Hirata, Raphael; Mattos-Guaraldi, Ana Luíza; Hodgkin, Jonathan; Burkovski, Andreas

2016-01-01

Caenorhabditis elegans is one of the major model systems in biology based on advantageous properties such as short life span, transparency, genetic tractability and ease of culture using an Escherichia coli diet. In its natural habitat, compost and rotting plant material, this nematode lives on bacteria. However, C. elegans is a predator of bacteria, but can also be infected by nematopathogenic coryneform bacteria such Microbacterium and Leucobacter species, which display intriguing and diverse modes of pathogenicity. Depending on the nematode pathogen, aggregates of worms, termed worm-stars, can be formed, or severe rectal swelling, so-called Dar formation, can be induced. Using the human and animal pathogens Corynebacterium diphtheriae and Corynebacterium ulcerans as well as the non-pathogenic species Corynebacterium glutamicum, we show that these coryneform bacteria can also induce star formation slowly in worms, as well as a severe tail-swelling phenotype. While C. glutamicum had a significant, but minor influence on survival of C. elegans, nematodes were killed after infection with C. diphtheriae and C. ulcerans. The two pathogenic species were avoided by the nematodes and induced aversive learning in C. elegans.

Fidelity Witnesses for Fermionic Quantum Simulations

NASA Astrophysics Data System (ADS)

Gluza, M.; Kliesch, M.; Eisert, J.; Aolita, L.

2018-05-01

The experimental interest and developments in quantum spin-1 /2 chains has increased uninterruptedly over the past decade. In many instances, the target quantum simulation belongs to the broader class of noninteracting fermionic models, constituting an important benchmark. In spite of this class being analytically efficiently tractable, no direct certification tool has yet been reported for it. In fact, in experiments, certification has almost exclusively relied on notions of quantum state tomography scaling very unfavorably with the system size. Here, we develop experimentally friendly fidelity witnesses for all pure fermionic Gaussian target states. Their expectation value yields a tight lower bound to the fidelity and can be measured efficiently. We derive witnesses in full generality in the Majorana-fermion representation and apply them to experimentally relevant spin-1 /2 chains. Among others, we show how to efficiently certify strongly out-of-equilibrium dynamics in critical Ising chains. At the heart of the measurement scheme is a variant of importance sampling specially tailored to overlaps between covariance matrices. The method is shown to be robust against finite experimental-state infidelities.

PPDB - A tool for investigation of plants physiology based on gene ontology.

PubMed

Sharma, Ajay Shiv; Gupta, Hari Om; Prasad, Rajendra

2014-09-02

Representing the way forward, from functional genomics and its ontology to functional understanding and physiological model, in a computationally tractable fashion is one of the ongoing challenges faced by computational biology. To tackle the standpoint, we herein feature the applications of contemporary database management to the development of PPDB, a searching and browsing tool for the Plants Physiology Database that is based upon the mining of a large amount of gene ontology data currently available. The working principles and search options associated with the PPDB are publicly available and freely accessible on-line ( http://www.iitr.ernet.in/ajayshiv/ ) through a user friendly environment generated by means of Drupal-6.24. By knowing that genes are expressed in temporally and spatially characteristic patterns and that their functionally distinct products often reside in specific cellular compartments and may be part of one or more multi-component complexes, this sort of work is intended to be relevant for investigating the functional relationships of gene products at a system level and, thus, helps us approach to the full physiology.

PPDB: A Tool for Investigation of Plants Physiology Based on Gene Ontology.

PubMed

Sharma, Ajay Shiv; Gupta, Hari Om; Prasad, Rajendra

2015-09-01

Representing the way forward, from functional genomics and its ontology to functional understanding and physiological model, in a computationally tractable fashion is one of the ongoing challenges faced by computational biology. To tackle the standpoint, we herein feature the applications of contemporary database management to the development of PPDB, a searching and browsing tool for the Plants Physiology Database that is based upon the mining of a large amount of gene ontology data currently available. The working principles and search options associated with the PPDB are publicly available and freely accessible online ( http://www.iitr.ac.in/ajayshiv/ ) through a user-friendly environment generated by means of Drupal-6.24. By knowing that genes are expressed in temporally and spatially characteristic patterns and that their functionally distinct products often reside in specific cellular compartments and may be part of one or more multicomponent complexes, this sort of work is intended to be relevant for investigating the functional relationships of gene products at a system level and, thus, helps us approach to the full physiology.

Prandiology of Drosophila and the CAFE assay

PubMed Central

Ja, William W.; Carvalho, Gil B.; Mak, Elizabeth M.; de la Rosa, Noelle N.; Fang, Annie Y.; Liong, Jonathan C.; Brummel, Ted; Benzer, Seymour

2007-01-01

Studies of feeding behavior in genetically tractable invertebrate model systems have been limited by the lack of proper methodology. We introduce the Capillary Feeder (CAFE), a method allowing precise, real-time measurement of ingestion by individual or grouped fruit flies on the scale of minutes to days. Using this technique, we conducted the first quantitative analysis of prandial behavior in Drosophila melanogaster. Our results allow the dissection of feeding into discrete bouts of ingestion, defining two separate parameters, meal volume and frequency, that can be uncoupled and thus are likely to be independently regulated. In addition, our long-term measurements show that flies can ingest as much as 1.7× their body mass over 24 h. Besides the study of appetite, the CAFE can be used to monitor oral drug delivery. As an illustration, we used the CAFE to test the effects of dietary supplementation with two compounds, paraquat and ethanol, on food ingestion and preference. Paraquat, a prooxidant widely used in stress tests, had a strong anorexigenic effect. In contrast, in a feeding preference assay, ethanol-laced food, but not ethanol by itself, acted as an attractant. PMID:17494737

Transcriptional regulation of Drosophila gonad formation.

PubMed

Tripathy, Ratna; Kunwar, Prabhat S; Sano, Hiroko; Renault, Andrew D

2014-08-15

The formation of the Drosophila embryonic gonad, involving the fusion of clusters of somatic gonadal precursor cells (SGPs) and their ensheathment of germ cells, provides a simple and genetically tractable model for the interplay between cells during organ formation. In a screen for mutants affecting gonad formation we identified a SGP cell autonomous role for Midline (Mid) and Longitudinals lacking (Lola). These transcriptional factors are required for multiple aspects of SGP behaviour including SGP cluster fusion, germ cell ensheathment and gonad compaction. The lola locus encodes more than 25 differentially spliced isoforms and we have identified an isoform specific requirement for lola in the gonad which is distinct from that in nervous system development. Mid and Lola work in parallel in gonad formation and surprisingly Mid overexpression in a lola background leads to additional SGPs at the expense of fat body cells. Our findings support the idea that although the transcription factors required by SGPs can ostensibly be assigned to those being required for either SGP specification or behaviour, they can also interact to impinge on both processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Identification of neoblast- and regeneration-specific miRNAs in the planarian Schmidtea mediterranea

PubMed Central

Sasidharan, Vidyanand; Lu, Yi-Chien; Bansal, Dhiru; Dasari, Pranavi; Poduval, Deepak; Seshasayee, Aswin; Resch, Alissa M.; Graveley, Brenton R.; Palakodeti, Dasaradhi

2013-01-01

In recent years, the planarian Schmidtea mediterranea has emerged as a tractable model system to study stem cell biology and regeneration. MicroRNAs are small RNA species that control gene expression by modulating translational repression and mRNA stability and have been implicated in the regulation of various cellular processes. Though recent studies have identified several miRNAs in S. mediterranea, their expression in neoblast subpopulations and during regeneration has not been examined. Here, we identify several miRNAs whose expression is enriched in different neoblast subpopulations and in regenerating tissue at different time points in S. mediterranea. Some of these miRNAs were enriched within 3 h post-amputation and may, therefore, play a role in wound healing and/or neoblast migration. Our results also revealed miRNAs, such as sme-miR-2d-3p and the sme-miR-124 family, whose expression is enriched in the cephalic ganglia, are also expressed in the brain primordium during CNS regeneration. These results provide new insight into the potential biological functions of miRNAs in neoblasts and regeneration in planarians. PMID:23974438

IL17 factors are early regulators in the gut epithelium during inflammatory response to Vibrio in the sea urchin larva

PubMed Central

Buckley, Katherine M; Ho, Eric Chun Hei; Hibino, Taku; Schrankel, Catherine S; Schuh, Nicholas W; Wang, Guizhi; Rast, Jonathan P

2017-01-01

IL17 cytokines are central mediators of mammalian immunity. In vertebrates, these factors derive from diverse cellular sources. Sea urchins share a molecular heritage with chordates that includes the IL17 system. Here, we characterize the role of epithelial expression of IL17 in the larval gut-associated immune response. The purple sea urchin genome encodes 10 IL17 subfamilies (35 genes) and 2 IL17 receptors. Most of these subfamilies are conserved throughout echinoderms. Two IL17 subfamilies are sequentially strongly upregulated and attenuated in the gut epithelium in response to bacterial disturbance. IL17R1 signal perturbation results in reduced expression of several response genes including an IL17 subtype, indicating a potential feedback. A third IL17 subfamily is activated in adult immune cells indicating that expression in immune cells and epithelia is divided among families. The larva provides a tractable model to investigate the regulation and consequences of gut epithelial IL17 expression across the organism. DOI: http://dx.doi.org/10.7554/eLife.23481.001 PMID:28447937

Central pattern generators for social vocalization: Androgen-dependent neurophysiological mechanisms

PubMed Central

Bass, Andrew H.; Remage-Healey, Luke

2008-01-01

Historically, most studies of vertebrate central pattern generators (CPGs) have focused on mechanisms for locomotion and respiration. Here, we highlight new results for ectothermic vertebrates, namely teleost fish and amphibians, showing how androgenic steroids can influence the temporal patterning of CPGs for social vocalization. Investigations of vocalizing teleosts show how androgens can rapidly (within minutes) modulate the neurophysiological output of the vocal CPG (fictive vocalizations that mimic the temporal properties of natural vocalizations) inclusive of their divergent actions between species, as well as intraspecific differences between male reproductive morphs. Studies of anuran amphibians (frogs) demonstrate that long-term steroid treatments (wks) can masculinize the fictive vocalizations of females, inclusive of its sensitivity to rapid modulation by serotonin. Given the conserved organization of vocal control systems across vertebrate groups, the vocal CPGs of fish and amphibians provide tractable models for identifying androgen-dependent events that are fundamental to the mechanisms of vocal motor patterning. These basic mechanisms can also inform our understanding of the more complex CPGs for vocalization, and social behaviors in general, that have evolved among birds and mammals. PMID:18262186

Flame Shapes of Luminous NonBuoyant Laminar Coflowing Jet Diffusion Flames

NASA Technical Reports Server (NTRS)

Lin, K.-C.; Faeth, G. M.

1999-01-01

Laminar diffusion flames are of interest as model flame systems that are more tractable for analysis and experiments than practical turbulent diffusion flames. Certainly understanding laminar flames must precede understanding more complex turbulent flames while man'y laminar diffusion flame properties are directly relevant to turbulent diffusion flames using laminar flamelet concepts. Laminar diffusion flame shapes have been of interest since the classical study of Burke and Schumann because they involve a simple nonintrusive measurement that is convenient for evaluating flame structure predictions. Motivated by these observations, the shapes of laminar flames were considered during the present investigation. The present study was limited to nonbuoyant flames because most practical flames are not buoyant. Effects of buoyancy were minimized by observing flames having large flow velocities at small pressures. Present methods were based on the study of the shapes of nonbu,3yant round laminar jet diffusion flames of Lin et al. where it was found that a simple analysis due to Spalding yielded good predictions of the flame shapes reported by Urban et al. and Sunderland et al.

Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes II: Size Effects on Ionic Distributions and Diffusion-Reaction Rates

PubMed Central

Lu, Benzhuo; Zhou, Y.C.

2011-01-01

The effects of finite particle size on electrostatics, density profiles, and diffusion have been a long existing topic in the study of ionic solution. The previous size-modified Poisson-Boltzmann and Poisson-Nernst-Planck models are revisited in this article. In contrast to many previous works that can only treat particle species with a single uniform size or two sizes, we generalize the Borukhov model to obtain a size-modified Poisson-Nernst-Planck (SMPNP) model that is able to treat nonuniform particle sizes. The numerical tractability of the model is demonstrated as well. The main contributions of this study are as follows. 1), We show that an (arbitrarily) size-modified PB model is indeed implied by the SMPNP equations under certain boundary/interface conditions, and can be reproduced through numerical solutions of the SMPNP. 2), The size effects in the SMPNP effectively reduce the densities of highly concentrated counterions around the biomolecule. 3), The SMPNP is applied to the diffusion-reaction process for the first time, to our knowledge. In the case of low substrate density near the enzyme reactive site, it is observed that the rate coefficients predicted by SMPNP model are considerably larger than those by the PNP model, suggesting both ions and substrates are subject to finite size effects. 4), An accurate finite element method and a convergent Gummel iteration are developed for the numerical solution of the completely coupled nonlinear system of SMPNP equations. PMID:21575582

Multiscale climate emulator of multimodal wave spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, Ana; Hegermiller, Christie A.; Antolinez, Jose A. A.; Camus, Paula; Vitousek, Sean; Ruggiero, Peter; Barnard, Patrick L.; Erikson, Li H.; Tomás, Antonio; Mendez, Fernando J.

2017-02-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this complex problem tractable using computationally expensive numerical models. So far, the skill of statistical-downscaling model-based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Multiscale Climate Emulator of Multimodal Wave Spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, A.; Hegermiller, C.; Alvarez Antolinez, J. A.; Camus, P.; Vitousek, S.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Tomas, A.; Mendez, F. J.

2016-12-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this problem complex yet tractable using computationally-expensive numerical models. So far, the skill of statistical-downscaling models based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical-downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the Southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships

NASA Astrophysics Data System (ADS)

Haghighi, Erfan; Kirchner, James W.

2017-07-01

Despite many efforts to develop evapotranspiration (ET) models with improved parametrizations of resistance terms for water vapor transfer into the atmosphere, estimates of ET and its partitioning remain prone to bias. Much of this bias could arise from inadequate representations of physical interactions near nonuniform surfaces from which localized heat and water vapor fluxes emanate. This study aims to provide a mechanistic bridge from land-surface characteristics to vertical transport predictions, and proposes a new physically based ET model that builds on a recently developed bluff-rough bare soil evaporation model incorporating coupled soil moisture-atmospheric controls. The newly developed ET model explicitly accounts for (1) near-surface turbulent interactions affecting soil drying and (2) soil-moisture-dependent stomatal responses to atmospheric evaporative demand that influence leaf (and canopy) transpiration. Model estimates of ET and its partitioning were in good agreement with available field-scale data, and highlight hidden processes not accounted for by commonly used ET schemes. One such process, nonlinear vegetation-induced turbulence (as a function of vegetation stature and cover fraction) significantly influences ET-soil moisture relationships. Our results are particularly important for water resources and land use planning of semiarid sparsely vegetated ecosystems where soil surface interactions are known to play a critical role in land-climate interactions. This study potentially facilitates a mathematically tractable description of the strength (i.e., the slope) of the ET-soil moisture relationship, which is a core component of models that seek to predict land-atmosphere coupling and its feedback to the climate system in a changing climate.

Failure of Local Thermal Equilibrium in Quantum Friction

NASA Astrophysics Data System (ADS)

Intravaia, F.; Behunin, R. O.; Henkel, C.; Busch, K.; Dalvit, D. A. R.

2016-09-01

Recent progress in manipulating atomic and condensed matter systems has instigated a surge of interest in nonequilibrium physics, including many-body dynamics of trapped ultracold atoms and ions, near-field radiative heat transfer, and quantum friction. Under most circumstances the complexity of such nonequilibrium systems requires a number of approximations to make theoretical descriptions tractable. In particular, it is often assumed that spatially separated components of a system thermalize with their immediate surroundings, although the global state of the system is out of equilibrium. This powerful assumption reduces the complexity of nonequilibrium systems to the local application of well-founded equilibrium concepts. While this technique appears to be consistent for the description of some phenomena, we show that it fails for quantum friction by underestimating by approximately 80% the magnitude of the drag force. Our results show that the correlations among the components of driven, but steady-state, quantum systems invalidate the assumption of local thermal equilibrium, calling for a critical reexamination of this approach for describing the physics of nonequilibrium systems.

Dynamic remapping of parallel computations with varying resource demands

NASA Technical Reports Server (NTRS)

Nicol, D. M.; Saltz, J. H.

1986-01-01

A large class of computational problems is characterized by frequent synchronization, and computational requirements which change as a function of time. When such a problem must be solved on a message passing multiprocessor machine, the combination of these characteristics lead to system performance which decreases in time. Performance can be improved with periodic redistribution of computational load; however, redistribution can exact a sometimes large delay cost. We study the issue of deciding when to invoke a global load remapping mechanism. Such a decision policy must effectively weigh the costs of remapping against the performance benefits. We treat this problem by constructing two analytic models which exhibit stochastically decreasing performance. One model is quite tractable; we are able to describe the optimal remapping algorithm, and the optimal decision policy governing when to invoke that algorithm. However, computational complexity prohibits the use of the optimal remapping decision policy. We then study the performance of a general remapping policy on both analytic models. This policy attempts to minimize a statistic W(n) which measures the system degradation (including the cost of remapping) per computation step over a period of n steps. We show that as a function of time, the expected value of W(n) has at most one minimum, and that when this minimum exists it defines the optimal fixed-interval remapping policy. Our decision policy appeals to this result by remapping when it estimates that W(n) is minimized. Our performance data suggests that this policy effectively finds the natural frequency of remapping. We also use the analytic models to express the relationship between performance and remapping cost, number of processors, and the computation's stochastic activity.

Impact of Calibrated Land Surface Model Parameters on the Accuracy and Uncertainty of Land-Atmosphere Coupling in WRF Simulations

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Modelling solid solutions with cluster expansion, special quasirandom structures, and thermodynamic approaches

NASA Astrophysics Data System (ADS)

Saltas, V.; Horlait, D.; Sgourou, E. N.; Vallianatos, F.; Chroneos, A.

2017-12-01

Modelling solid solutions is fundamental in understanding the properties of numerous materials which are important for a range of applications in various fields including nanoelectronics and energy materials such as fuel cells, nuclear materials, and batteries, as the systematic understanding throughout the composition range of solid solutions for a range of conditions can be challenging from an experimental viewpoint. The main motivation of this review is to contribute to the discussion in the community of the applicability of methods that constitute the investigation of solid solutions computationally tractable. This is important as computational modelling is required to calculate numerous defect properties and to act synergistically with experiment to understand these materials. This review will examine in detail two examples: silicon germanium alloys and MAX phase solid solutions. Silicon germanium alloys are technologically important in nanoelectronic devices and are also relevant considering the recent advances in ternary and quaternary groups IV and III-V semiconductor alloys. MAX phase solid solutions display a palette of ceramic and metallic properties and it is anticipated that via their tuning they can have applications ranging from nuclear to aerospace industries as well as being precursors for particular MXenes. In the final part, a brief summary assesses the limitations and possibilities of the methodologies discussed, whereas there is discussion on the future directions and examples of solid solution systems that should prove fruitful to consider.

Learning Quantitative Sequence-Function Relationships from Massively Parallel Experiments

NASA Astrophysics Data System (ADS)

Atwal, Gurinder S.; Kinney, Justin B.

2016-03-01

A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships—functions that map the sequence of DNA, RNA, or protein to a biochemically relevant activity. Most sequence-function relationships in biology are quantitative, but only recently have experimental techniques for effectively measuring these relationships been developed. The advent of such "massively parallel" experiments presents an exciting opportunity for the concepts and methods of statistical physics to inform the study of biological systems. After reviewing these recent experimental advances, we focus on the problem of how to infer parametric models of sequence-function relationships from the data produced by these experiments. Specifically, we retrace and extend recent theoretical work showing that inference based on mutual information, not the standard likelihood-based approach, is often necessary for accurately learning the parameters of these models. Closely connected with this result is the emergence of "diffeomorphic modes"—directions in parameter space that are far less constrained by data than likelihood-based inference would suggest. Analogous to Goldstone modes in physics, diffeomorphic modes arise from an arbitrarily broken symmetry of the inference problem. An analytically tractable model of a massively parallel experiment is then described, providing an explicit demonstration of these fundamental aspects of statistical inference. This paper concludes with an outlook on the theoretical and computational challenges currently facing studies of quantitative sequence-function relationships.

Heterogeneous network epidemics: real-time growth, variance and extinction of infection.

PubMed

Ball, Frank; House, Thomas

2017-09-01

Recent years have seen a large amount of interest in epidemics on networks as a way of representing the complex structure of contacts capable of spreading infections through the modern human population. The configuration model is a popular choice in theoretical studies since it combines the ability to specify the distribution of the number of contacts (degree) with analytical tractability. Here we consider the early real-time behaviour of the Markovian SIR epidemic model on a configuration model network using a multitype branching process. We find closed-form analytic expressions for the mean and variance of the number of infectious individuals as a function of time and the degree of the initially infected individual(s), and write down a system of differential equations for the probability of extinction by time t that are numerically fast compared to Monte Carlo simulation. We show that these quantities are all sensitive to the degree distribution-in particular we confirm that the mean prevalence of infection depends on the first two moments of the degree distribution and the variance in prevalence depends on the first three moments of the degree distribution. In contrast to most existing analytic approaches, the accuracy of these results does not depend on having a large number of infectious individuals, meaning that in the large population limit they would be asymptotically exact even for one initial infectious individual.

Towards systems metabolic engineering in Pichia pastoris.

PubMed

Schwarzhans, Jan-Philipp; Luttermann, Tobias; Geier, Martina; Kalinowski, Jörn; Friehs, Karl

2017-11-01

The methylotrophic yeast Pichia pastoris is firmly established as a host for the production of recombinant proteins, frequently outperforming other heterologous hosts. Already, a sizeable amount of systems biology knowledge has been acquired for this non-conventional yeast. By applying various omics-technologies, productivity features have been thoroughly analyzed and optimized via genetic engineering. However, challenging clonal variability, limited vector repertoire and insufficient genome annotation have hampered further developments. Yet, in the last few years a reinvigorated effort to establish P. pastoris as a host for both protein and metabolite production is visible. A variety of compounds from terpenoids to polyketides have been synthesized, often exceeding the productivity of other microbial systems. The clonal variability was systematically investigated and strategies formulated to circumvent untargeted events, thereby streamlining the screening procedure. Promoters with novel regulatory properties were discovered or engineered from existing ones. The genetic tractability was increased via the transfer of popular manipulation and assembly techniques, as well as the creation of new ones. A second generation of sequencing projects culminated in the creation of the second best functionally annotated yeast genome. In combination with landmark physiological insights and increased output of omics-data, a good basis for the creation of refined genome-scale metabolic models was created. The first application of model-based metabolic engineering in P. pastoris showcased the potential of this approach. Recent efforts to establish yeast peroxisomes for compartmentalized metabolite synthesis appear to fit ideally with the well-studied high capacity peroxisomal machinery of P. pastoris. Here, these recent developments are collected and reviewed with the aim of supporting the establishment of systems metabolic engineering in P. pastoris. Copyright © 2017. Published by Elsevier Inc.

Nonlinear Model Predictive Control for Cooperative Control and Estimation

NASA Astrophysics Data System (ADS)

Ru, Pengkai

Recent advances in computational power have made it possible to do expensive online computations for control systems. It is becoming more realistic to perform computationally intensive optimization schemes online on systems that are not intrinsically stable and/or have very small time constants. Being one of the most important optimization based control approaches, model predictive control (MPC) has attracted a lot of interest from the research community due to its natural ability to incorporate constraints into its control formulation. Linear MPC has been well researched and its stability can be guaranteed in the majority of its application scenarios. However, one issue that still remains with linear MPC is that it completely ignores the system's inherent nonlinearities thus giving a sub-optimal solution. On the other hand, if achievable, nonlinear MPC, would naturally yield a globally optimal solution and take into account all the innate nonlinear characteristics. While an exact solution to a nonlinear MPC problem remains extremely computationally intensive, if not impossible, one might wonder if there is a middle ground between the two. We tried to strike a balance in this dissertation by employing a state representation technique, namely, the state dependent coefficient (SDC) representation. This new technique would render an improved performance in terms of optimality compared to linear MPC while still keeping the problem tractable. In fact, the computational power required is bounded only by a constant factor of the completely linearized MPC. The purpose of this research is to provide a theoretical framework for the design of a specific kind of nonlinear MPC controller and its extension into a general cooperative scheme. The controller is designed and implemented on quadcopter systems.

4D atlas of the mouse embryo for precise morphological staging.

PubMed

Wong, Michael D; van Eede, Matthijs C; Spring, Shoshana; Jevtic, Stefan; Boughner, Julia C; Lerch, Jason P; Henkelman, R Mark

2015-10-15

After more than a century of research, the mouse remains the gold-standard model system, for it recapitulates human development and disease and is quickly and highly tractable to genetic manipulations. Fundamental to the power and success of using a mouse model is the ability to stage embryonic mouse development accurately. Past staging systems were limited by the technologies of the day, such that only surface features, visible with a light microscope, could be recognized and used to define stages. With the advent of high-throughput 3D imaging tools that capture embryo morphology in microscopic detail, we now present the first 4D atlas staging system for mouse embryonic development using optical projection tomography and image registration methods. By tracking 3D trajectories of every anatomical point in the mouse embryo from E11.5 to E14.0, we established the first 4D atlas compiled from ex vivo 3D mouse embryo reference images. The resulting 4D atlas comprises 51 interpolated 3D images in this gestational range, resulting in a temporal resolution of 72 min. From this 4D atlas, any mouse embryo image can be subsequently compared and staged at the global, voxel and/or structural level. Assigning an embryonic stage to each point in anatomy allows for unprecedented quantitative analysis of developmental asynchrony among different anatomical structures in the same mouse embryo. This comprehensive developmental data set offers developmental biologists a new, powerful staging system that can identify and compare differences in developmental timing in wild-type embryos and shows promise for localizing deviations in mutant development. © 2015. Published by The Company of Biologists Ltd.

Normalizing the environment recapitulates adult human immune traits in laboratory mice.

PubMed

Beura, Lalit K; Hamilton, Sara E; Bi, Kevin; Schenkel, Jason M; Odumade, Oludare A; Casey, Kerry A; Thompson, Emily A; Fraser, Kathryn A; Rosato, Pamela C; Filali-Mouhim, Ali; Sekaly, Rafick P; Jenkins, Marc K; Vezys, Vaiva; Haining, W Nicholas; Jameson, Stephen C; Masopust, David

2016-04-28

Our current understanding of immunology was largely defined in laboratory mice, partly because they are inbred and genetically homogeneous, can be genetically manipulated, allow kinetic tissue analyses to be carried out from the onset of disease, and permit the use of tractable disease models. Comparably reductionist experiments are neither technically nor ethically possible in humans. However, there is growing concern that laboratory mice do not reflect relevant aspects of the human immune system, which may account for failures to translate disease treatments from bench to bedside. Laboratory mice live in abnormally hygienic specific pathogen free (SPF) barrier facilities. Here we show that standard laboratory mouse husbandry has profound effects on the immune system and that environmental changes produce mice with immune systems closer to those of adult humans. Laboratory mice--like newborn, but not adult, humans--lack effector-differentiated and mucosally distributed memory T cells. These cell populations were present in free-living barn populations of feral mice and pet store mice with diverse microbial experience, and were induced in laboratory mice after co-housing with pet store mice, suggesting that the environment is involved in the induction of these cells. Altering the living conditions of mice profoundly affected the cellular composition of the innate and adaptive immune systems, resulted in global changes in blood cell gene expression to patterns that more closely reflected the immune signatures of adult humans rather than neonates, altered resistance to infection, and influenced T-cell differentiation in response to a de novo viral infection. These data highlight the effects of environment on the basal immune state and response to infection and suggest that restoring physiological microbial exposure in laboratory mice could provide a relevant tool for modelling immunological events in free-living organisms, including humans.

Baldovin-Stella stochastic volatility process and Wiener process mixtures

NASA Astrophysics Data System (ADS)

Peirano, P. P.; Challet, D.

2012-08-01

Starting from inhomogeneous time scaling and linear decorrelation between successive price returns, Baldovin and Stella recently proposed a powerful and consistent way to build a model describing the time evolution of a financial index. We first make it fully explicit by using Student distributions instead of power law-truncated Lévy distributions and show that the analytic tractability of the model extends to the larger class of symmetric generalized hyperbolic distributions and provide a full computation of their multivariate characteristic functions; more generally, we show that the stochastic processes arising in this framework are representable as mixtures of Wiener processes. The basic Baldovin and Stella model, while mimicking well volatility relaxation phenomena such as the Omori law, fails to reproduce other stylized facts such as the leverage effect or some time reversal asymmetries. We discuss how to modify the dynamics of this process in order to reproduce real data more accurately.

Approximate Bayesian computation for spatial SEIR(S) epidemic models.

PubMed

Brown, Grant D; Porter, Aaron T; Oleson, Jacob J; Hinman, Jessica A

2018-02-01

Approximate Bayesia n Computation (ABC) provides an attractive approach to estimation in complex Bayesian inferential problems for which evaluation of the kernel of the posterior distribution is impossible or computationally expensive. These highly parallelizable techniques have been successfully applied to many fields, particularly in cases where more traditional approaches such as Markov chain Monte Carlo (MCMC) are impractical. In this work, we demonstrate the application of approximate Bayesian inference to spatially heterogeneous Susceptible-Exposed-Infectious-Removed (SEIR) stochastic epidemic models. These models have a tractable posterior distribution, however MCMC techniques nevertheless become computationally infeasible for moderately sized problems. We discuss the practical implementation of these techniques via the open source ABSEIR package for R. The performance of ABC relative to traditional MCMC methods in a small problem is explored under simulation, as well as in the spatially heterogeneous context of the 2014 epidemic of Chikungunya in the Americas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatiotemporal Bayesian analysis of Lyme disease in New York state, 1990-2000.

PubMed

Chen, Haiyan; Stratton, Howard H; Caraco, Thomas B; White, Dennis J

2006-07-01

Mapping ordinarily increases our understanding of nontrivial spatial and temporal heterogeneities in disease rates. However, the large number of parameters required by the corresponding statistical models often complicates detailed analysis. This study investigates the feasibility of a fully Bayesian hierarchical regression approach to the problem and identifies how it outperforms two more popular methods: crude rate estimates (CRE) and empirical Bayes standardization (EBS). In particular, we apply a fully Bayesian approach to the spatiotemporal analysis of Lyme disease incidence in New York state for the period 1990-2000. These results are compared with those obtained by CRE and EBS in Chen et al. (2005). We show that the fully Bayesian regression model not only gives more reliable estimates of disease rates than the other two approaches but also allows for tractable models that can accommodate more numerous sources of variation and unknown parameters.

Halogenase engineering and its utility in medicinal chemistry.

PubMed

Fraley, Amy E; Sherman, David H

2018-06-15

Halogenation is commonly used in medicinal chemistry to improve the potency of pharmaceutical leads. While synthetic methods for halogenation present selectivity and reactivity challenges, halogenases have evolved over time to perform selective reactions under benign conditions. The optimization of halogenation biocatalysts has utilized enzyme evolution and structure-based engineering alongside biotransformation in a variety of systems to generate stable site-selective variants. The recent improvements in halogenase-catalyzed reactions has demonstrated the utility of these biocatalysts for industrial purposes, and their ability to achieve a broad substrate scope implies a synthetic tractability with increasing relevance in medicinal chemistry. Copyright © 2018 Elsevier Ltd. All rights reserved.

A study of tumour growth based on stoichiometric principles: a continuous model and its discrete analogue.

PubMed

Saleem, M; Agrawal, Tanuja; Anees, Afzal

2014-01-01

In this paper, we consider a continuous mathematically tractable model and its discrete analogue for the tumour growth. The model formulation is based on stoichiometric principles considering tumour-immune cell interactions in potassium (K (+))-limited environment. Our both continuous and discrete models illustrate 'cancer immunoediting' as a dynamic process having all three phases namely elimination, equilibrium and escape. The stoichiometric principles introduced into the model allow us to study its dynamics with the variation in the total potassium in the surrounding of the tumour region. It is found that an increase in the total potassium may help the patient fight the disease for a longer period of time. This result seems to be in line with the protective role of the potassium against the risk of pancreatic cancer as has been reported by Bravi et al. [Dietary intake of selected micronutrients and risk of pancreatic cancer: An Italian case-control study, Ann. Oncol. 22 (2011), pp. 202-206].