The tractable cognition thesis.

PubMed

Van Rooij, Iris

2008-09-01

The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the Tractable Cognition thesis: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories of cognition. To utilize this constraint, a precise and workable definition of "computational tractability" is needed. Following computer science tradition, many cognitive scientists and psychologists define computational tractability as polynomial-time computability, leading to the P-Cognition thesis. This article explains how and why the P-Cognition thesis may be overly restrictive, risking the exclusion of veridical computational-level theories from scientific investigation. An argument is made to replace the P-Cognition thesis by the FPT-Cognition thesis as an alternative formalization of the Tractable Cognition thesis (here, FPT stands for fixed-parameter tractable). Possible objections to the Tractable Cognition thesis, and its proposed formalization, are discussed, and existing misconceptions are clarified. 2008 Cognitive Science Society, Inc.

Light Diffraction by Large Amplitude Ultrasonic Waves in Liquids

NASA Technical Reports Server (NTRS)

Adler, Laszlo; Cantrell, John H.; Yost, William T.

2016-01-01

Light diffraction from ultrasound, which can be used to investigate nonlinear acoustic phenomena in liquids, is reported for wave amplitudes larger than that typically reported in the literature. Large amplitude waves result in waveform distortion due to the nonlinearity of the medium that generates harmonics and produces asymmetries in the light diffraction pattern. For standing waves with amplitudes above a threshold value, subharmonics are generated in addition to the harmonics and produce additional diffraction orders of the incident light. With increasing drive amplitude above the threshold a cascade of period-doubling subharmonics are generated, terminating in a region characterized by a random, incoherent (chaotic) diffraction pattern. To explain the experimental results a toy model is introduced, which is derived from traveling wave solutions of the nonlinear wave equation corresponding to the fundamental and second harmonic standing waves. The toy model reduces the nonlinear partial differential equation to a mathematically more tractable nonlinear ordinary differential equation. The model predicts the experimentally observed cascade of period-doubling subharmonics terminating in chaos that occurs with increasing drive amplitudes above the threshold value. The calculated threshold amplitude is consistent with the value estimated from the experimental data.

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

A BAC-based physical map of the Hessian fly (Mayetiola destructor) genome anchored to polytene chromosomes

USDA-ARS?s Scientific Manuscript database

The Hessian fly (Mayetiola destructor) is an important insect pest of wheat and an experimental organism for studies of plant-insect interactions. It has tractable genetics, polytene chromosomes, a relatively small genome (158 Mb), and shares a gene-for-gene relationship with wheat. To improve its...

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.

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.

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.

Rebuilding the Injured Lung

PubMed Central

2015-01-01

The 57th annual Thomas L. Petty Aspen Lung Conference, entitled “Rebuilding the Injured Lung,” was held from June 4 to 7, 2014 at the Gant Conference Center in Aspen, Colorado. Investigators from a wide range of disciplines and perspectives convened to discuss the biology of lung injury, how the lung repairs itself, how and why repair fails, and how the repair process can be enhanced. Among the challenges identified in the course of the conference was how to develop more predictive experimental models that capture the multidimensional complexity of lung injury and repair in a tractable manner. From such approaches that successfully fuse the biological and physical sciences, the group envisioned that new therapies for acute and chronic lung injury would emerge. The discussion of experimental therapeutics ranged from pharmaceuticals and cells that interdict fibrosis and enhance repair to a de novo lung derived from stem cells repopulating a decellularized matrix. PMID:25830839

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.

Ontogenetic and Experience-Dependent Changes in Defensive Behavior in Captive-Bred Hawaiian Bobtail Squid, Euprymna scolopes

PubMed Central

Seehafer, Kia; Brophy, Samantha; Tom, Sara R.; Crook, Robyn J.

2018-01-01

Cephalopod molluscs are known for their extensive behavioral repertoire and their impressive learning abilities. Their primary defensive behaviors, such as camouflage, have received detailed study, but knowledge is limited to intensive study of relatively few species. A considerable challenge facing cephalopod research is the need to establish new models that can be captive bred, are tractable for range of different experimental procedures, and that will address broad questions in biological research. The Hawaiian Bobtail Squid (Euprymna scolopes) is a small, tropical cephalopod that has a long history of research in the field of microbial symbiosis, but offers great promise as a novel behavioral and neurobiological model. It can be bred in the laboratory through multiple generations, one of the few species of cephalopod that can meet this requirement (which is incorporated in regulations such as EU directive 2010/63/EU). Additionally, laboratory culture makes E. scolopes an ideal model for studying ontogeny- and experience-dependent behaviors. In this study, we show that captive bred juvenile and adult E. scolopes produce robust, repeatable defensive behaviors when placed in an exposed environment and presented with a visual threat. Further, adult and juvenile squid employ different innate defensive behaviors when presented with a size-matched model predator. When a 10-min training procedure was repeated over three consecutive days, defensive behaviors habituated in juvenile squid for at least 5 days after training, but memory did not appear to persist for 14 days. In contrast, adult squid did not show any evidence of long-term habituation memory. Thus we conclude that this species produces a range of quantifiable, modifiable behaviors even in a laboratory environment where ecologically-relevant, complex behavioral sequences may not reliably occur. We suggest that the lack of long-term memory in adult squid may be related to their less escalated initial response to the mimic, and thus indicates less motivation to retain memory and not necessary inability to form memory. This is the first demonstration of age-related differences in defensive behaviors in Euprymna, and the first record of habituation in this experimentally tractable genus of squid. PMID:29651249

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

DOE PAGES

Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; ...

2016-12-20

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. In this paper, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting inmore » the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Finally, coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology.« less

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

PubMed Central

Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

2016-01-01

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

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

Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. In this paper, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting inmore » the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Finally, coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology.« less

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 motor unit-based model of muscle fatigue

PubMed Central

2017-01-01

Muscle fatigue is a temporary decline in the force and power capacity of skeletal muscle resulting from muscle activity. Because control of muscle is realized at the level of the motor unit (MU), it seems important to consider the physiological properties of motor units when attempting to understand and predict muscle fatigue. Therefore, we developed a phenomenological model of motor unit fatigue as a tractable means to predict muscle fatigue for a variety of tasks and to illustrate the individual contractile responses of MUs whose collective action determines the trajectory of changes in muscle force capacity during prolonged activity. An existing MU population model was used to simulate MU firing rates and isometric muscle forces and, to that model, we added fatigue-related changes in MU force, contraction time, and firing rate associated with sustained voluntary contractions. The model accurately estimated endurance times for sustained isometric contractions across a wide range of target levels. In addition, simulations were run for situations that have little experimental precedent to demonstrate the potential utility of the model to predict motor unit fatigue for more complicated, real-world applications. Moreover, the model provided insight into the complex orchestration of MU force contributions during fatigue, that would be unattainable with current experimental approaches. PMID:28574981

Classical topological paramagnetism

NASA Astrophysics Data System (ADS)

Bondesan, R.; Ringel, Z.

2017-05-01

Topological phases of matter are one of the hallmarks of quantum condensed matter physics. One of their striking features is a bulk-boundary correspondence wherein the topological nature of the bulk manifests itself on boundaries via exotic massless phases. In classical wave phenomena, analogous effects may arise; however, these cannot be viewed as equilibrium phases of matter. Here, we identify a set of rules under which robust equilibrium classical topological phenomena exist. We write simple and analytically tractable classical lattice models of spins and rotors in two and three dimensions which, at suitable parameter ranges, are paramagnetic in the bulk but nonetheless exhibit some unusual long-range or critical order on their boundaries. We point out the role of simplicial cohomology as a means of classifying, writing, and analyzing such models. This opens an experimental route for studying strongly interacting topological phases of spins.

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

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.

The Tractable Cognition Thesis

ERIC Educational Resources Information Center

van Rooij, Iris

2008-01-01

The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the "Tractable Cognition thesis": Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories…

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.

Design of orbital debris shields for oblique hypervelocity impact

NASA Technical Reports Server (NTRS)

Fahrenthold, Eric P.

1994-01-01

A new impact debris propagation code was written to link CTH simulations of space debris shield perforation to the Lagrangian finite element code DYNA3D, for space structure wall impact simulations. This software (DC3D) simulates debris cloud evolution using a nonlinear elastic-plastic deformable particle dynamics model, and renders computationally tractable the supercomputer simulation of oblique impacts on Whipple shield protected structures. Comparison of three dimensional, oblique impact simulations with experimental data shows good agreement over a range of velocities of interest in the design of orbital debris shielding. Source code developed during this research is provided on the enclosed floppy disk. An abstract based on the work described was submitted to the 1994 Hypervelocity Impact Symposium.

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.

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.

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.

The development and validation of a numerical integration method for non-linear viscoelastic modeling

PubMed Central

Ramo, Nicole L.; Puttlitz, Christian M.

2018-01-01

Compelling evidence that many biological soft tissues display both strain- and time-dependent behavior has led to the development of fully non-linear viscoelastic modeling techniques to represent the tissue’s mechanical response under dynamic conditions. Since the current stress state of a viscoelastic material is dependent on all previous loading events, numerical analyses are complicated by the requirement of computing and storing the stress at each step throughout the load history. This requirement quickly becomes computationally expensive, and in some cases intractable, for finite element models. Therefore, we have developed a strain-dependent numerical integration approach for capturing non-linear viscoelasticity that enables calculation of the current stress from a strain-dependent history state variable stored from the preceding time step only, which improves both fitting efficiency and computational tractability. This methodology was validated based on its ability to recover non-linear viscoelastic coefficients from simulated stress-relaxation (six strain levels) and dynamic cyclic (three frequencies) experimental stress-strain data. The model successfully fit each data set with average errors in recovered coefficients of 0.3% for stress-relaxation fits and 0.1% for cyclic. The results support the use of the presented methodology to develop linear or non-linear viscoelastic models from stress-relaxation or cyclic experimental data of biological soft tissues. PMID:29293558

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

DOE PAGES

Mach, J. C.; Budrow, C. J.; Pagan, D. C.; ...

2017-03-15

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 paper, 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 developmore » 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. Finally, the experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.« less

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

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

Mach, J. C.; Budrow, C. J.; Pagan, D. C.

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 paper, 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 developmore » 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. Finally, the experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.« less

Whole-mount in situ hybridization in the rotifer Brachionus plicatilis representing a basal branch of lophotrochozoans.

PubMed

Boell, Louis A; Bucher, Gregor

2008-08-01

In order to broaden the comparative scope of evolutionary developmental biology and to refine our picture of animal macroevolution, it is necessary to establish new model organisms, especially from previously underrepresented groups, like the Lophotrochozoa. We have established the culture and protocols for molecular developmental biology in the rotifer species Brachionus plicatilis Müller (Rotifera, Monogononta). Rotifers are nonsegmented animals with enigmatic basal position within the lophotrochozoans and marked by several evolutionary novelties like the wheel organ (corona), the median eye, and the nonpaired posterior foot. The expression of Bp-Pax-6 is shown using whole-mount in situ hybridization. The inexpensive easy culture and experimental tractability of Brachionus as well as the range of interesting questions to which it holds the key make it a promising addition to the "zoo" of evo-devo model organisms.

Light-induced depigmentation in planarians models the pathophysiology of acute porphyrias.

PubMed

Stubenhaus, Bradford M; Dustin, John P; Neverett, Emily R; Beaudry, Megan S; Nadeau, Leanna E; Burk-McCoy, Ethan; He, Xinwen; Pearson, Bret J; Pellettieri, Jason

2016-05-31

Porphyrias are disorders of heme metabolism frequently characterized by extreme photosensitivity. This symptom results from accumulation of porphyrins, tetrapyrrole intermediates in heme biosynthesis that generate reactive oxygen species when exposed to light, in the skin of affected individuals. Here we report that in addition to producing an ommochrome body pigment, the planarian flatworm Schmidtea mediterranea generates porphyrins in its subepithelial pigment cells under physiological conditions, and that this leads to pigment cell loss when animals are exposed to intense visible light. Remarkably, porphyrin biosynthesis and light-induced depigmentation are enhanced by starvation, recapitulating a common feature of some porphyrias - decreased nutrient intake precipitates an acute manifestation of the disease. Our results establish planarians as an experimentally tractable animal model for research into the pathophysiology of acute porphyrias, and potentially for the identification of novel pharmacological interventions capable of alleviating porphyrin-mediated photosensitivity or decoupling dieting and fasting from disease pathogenesis.

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.

Brachypodium as a model for the grasses: today and the future

USDA-ARS?s Scientific Manuscript database

Over the past several years, Brachypodium distachyon (Brachypodium) has emerged as a tractable model system to study biological questions relevant to the grasses. To place its relevance in the larger context of plant biology, we outline here the expanding adoption of Brachypodium as a model grass an...

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

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.

Human embryonic stem cell lines model experimental human cytomegalovirus latency.

PubMed

Penkert, Rhiannon R; Kalejta, Robert F

2013-05-28

Herpesviruses are highly successful pathogens that persist for the lifetime of their hosts primarily because of their ability to establish and maintain latent infections from which the virus is capable of productively reactivating. Human cytomegalovirus (HCMV), a betaherpesvirus, establishes latency in CD34(+) hematopoietic progenitor cells during natural infections in the body. Experimental infection of CD34(+) cells ex vivo has demonstrated that expression of the viral gene products that drive productive infection is silenced by an intrinsic immune defense mediated by Daxx and histone deacetylases through heterochromatinization of the viral genome during the establishment of latency. Additional mechanistic details about the establishment, let alone maintenance and reactivation, of HCMV latency remain scarce. This is partly due to the technical challenges of CD34(+) cell culture, most notably, the difficulty in preventing spontaneous differentiation that drives reactivation and renders them permissive for productive infection. Here we demonstrate that HCMV can establish, maintain, and reactivate in vitro from experimental latency in cultures of human embryonic stem cells (ESCs), for which spurious differentiation can be prevented or controlled. Furthermore, we show that known molecular aspects of HCMV latency are faithfully recapitulated in these cells. In total, we present ESCs as a novel, tractable model for studies of HCMV latency.

Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes

PubMed Central

Edmunds, Richard C.; Su, Baofeng; Balhoff, James P.; Eames, B. Frank; Dahdul, Wasila M.; Lapp, Hilmar; Lundberg, John G.; Vision, Todd J.; Dunham, Rex A.; Mabee, Paula M.; Westerfield, Monte

2016-01-01

Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

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

A combinatorial model for dentate gyrus sparse coding

DOE PAGES

Severa, William; Parekh, Ojas; James, Conrad D.; ...

2016-12-29

The dentate gyrus forms a critical link between the entorhinal cortex and CA3 by providing a sparse version of the signal. Concurrent with this increase in sparsity, a widely accepted theory suggests the dentate gyrus performs pattern separation—similar inputs yield decorrelated outputs. Although an active region of study and theory, few logically rigorous arguments detail the dentate gyrus’s (DG) coding. We suggest a theoretically tractable, combinatorial model for this action. The model provides formal methods for a highly redundant, arbitrarily sparse, and decorrelated output signal.To explore the value of this model framework, we assess how suitable it is for twomore » notable aspects of DG coding: how it can handle the highly structured grid cell representation in the input entorhinal cortex region and the presence of adult neurogenesis, which has been proposed to produce a heterogeneous code in the DG. We find tailoring the model to grid cell input yields expansion parameters consistent with the literature. In addition, the heterogeneous coding reflects activity gradation observed experimentally. Lastly, we connect this approach with more conventional binary threshold neural circuit models via a formal embedding.« less

Epilepsy research methods update: Understanding the causes of epileptic seizures and identifying new treatments using non-mammalian model organisms.

PubMed

Cunliffe, Vincent T; Baines, Richard A; Giachello, Carlo N G; Lin, Wei-Hsiang; Morgan, Alan; Reuber, Markus; Russell, Claire; Walker, Matthew C; Williams, Robin S B

2015-01-01

This narrative review is intended to introduce clinicians treating epilepsy and researchers familiar with mammalian models of epilepsy to experimentally tractable, non-mammalian research models used in epilepsy research, ranging from unicellular eukaryotes to more complex multicellular organisms. The review focuses on four model organisms: the social amoeba Dictyostelium discoideum, the roundworm Caenorhabditis elegans, the fruit fly Drosophila melanogaster and the zebrafish Danio rerio. We consider recent discoveries made with each model organism and discuss the importance of these advances for the understanding and treatment of epilepsy in humans. The relative ease with which mutations in genes of interest can be produced and studied quickly and cheaply in these organisms, together with their anatomical and physiological simplicity in comparison to mammalian species, are major advantages when researchers are trying to unravel complex disease mechanisms. The short generation times of most of these model organisms also mean that they lend themselves particularly conveniently to the investigation of drug effects or epileptogenic processes across the lifecourse. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

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…

The Genome of the Western Clawed Frog Xenopus tropicalis

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

Hellsten, Uffe; Harland, Richard M.; Gilchrist, Michael J.

2009-10-01

The western clawed frog Xenopus tropicalis is an important model for vertebrate development that combines experimental advantages of the African clawed frog Xenopus laevis with more tractable genetics. Here we present a draft genome sequence assembly of X. tropicalis. This genome encodes over 20,000 protein-coding genes, including orthologs of at least 1,700 human disease genes. Over a million expressed sequence tags validated the annotation. More than one-third of the genome consists of transposable elements, with unusually prevalent DNA transposons. Like other tetrapods, the genome contains gene deserts enriched for conserved non-coding elements. The genome exhibits remarkable shared synteny with humanmore » and chicken over major parts of large chromosomes, broken by lineage-specific chromosome fusions and fissions, mainly in the mammalian lineage.« less

Tunable interactions between paramagnetic colloidal particles driven in a modulated ratchet potential.

PubMed

Straube, Arthur V; Tierno, Pietro

2014-06-14

We study experimentally and theoretically the interactions between paramagnetic particles dispersed in water and driven above the surface of a stripe patterned magnetic garnet film. An external rotating magnetic field modulates the stray field of the garnet film and generates a translating potential landscape which induces directed particle motion. By varying the ellipticity of the rotating field, we tune the inter-particle interactions from net repulsive to net attractive. For attractive interactions, we show that pairs of particles can approach each other and form stable doublets which afterwards travel along the modulated landscape at a constant mean speed. We measure the strength of the attractive force between the moving particles and propose an analytically tractable model that explains the observations and is in quantitative agreement with experiment.

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.

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.

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

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

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

Unfolding of Proteins: Thermal and Mechanical Unfolding

NASA Technical Reports Server (NTRS)

Hur, Joe S.; Darve, Eric

2004-01-01

We have employed a Hamiltonian model based on a self-consistent Gaussian appoximation to examine the unfolding process of proteins in external - both mechanical and thermal - force elds. The motivation was to investigate the unfolding pathways of proteins by including only the essence of the important interactions of the native-state topology. Furthermore, if such a model can indeed correctly predict the physics of protein unfolding, it can complement more computationally expensive simulations and theoretical work. The self-consistent Gaussian approximation by Micheletti et al. has been incorporated in our model to make the model mathematically tractable by signi cantly reducing the computational cost. All thermodynamic properties and pair contact probabilities are calculated by simply evaluating the values of a series of Incomplete Gamma functions in an iterative manner. We have compared our results to previous molecular dynamics simulation and experimental data for the mechanical unfolding of the giant muscle protein Titin (1TIT). Our model, especially in light of its simplicity and excellent agreement with experiment and simulation, demonstrates the basic physical elements necessary to capture the mechanism of protein unfolding in an external force field.

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.

Copper toxicology, oxidative stress and inflammation using zebrafish as experimental model.

PubMed

Pereira, Talita Carneiro Brandão; Campos, Maria Martha; Bogo, Maurício Reis

2016-07-01

Copper is an essential micronutrient and a key catalytic cofactor in a wide range of enzymes. As a trace element, copper levels are tightly regulated and both its deficit and excess are deleterious to the organism. Under inflammatory conditions, serum copper levels are increased and trigger oxidative stress responses that activate inflammatory responses. Interestingly, copper dyshomeostasis, oxidative stress and inflammation are commonly present in several chronic diseases. Copper exposure can be easily modeled in zebrafish; a consolidated model in toxicology with increasing interest in immunity-related research. As a result of developmental, economical and genetic advantages, this freshwater teleost is uniquely suitable for chemical and genetic large-scale screenings, representing a powerful experimental tool for a whole-organism approach, mechanistic studies, disease modeling and beyond. Copper toxicological and more recently pro-inflammatory effects have been investigated in both larval and adult zebrafish with breakthrough findings. Here, we provide an overview of copper metabolism in health and disease and its effects on oxidative stress and inflammation responses in zebrafish models. Copper-induced inflammation is highlighted owing to its potential to easily mimic pro-oxidative and pro-inflammatory features that combined with zebrafish genetic tractability could help further in the understanding of copper metabolism, inflammatory responses and related diseases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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…

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

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.

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.

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

Analytically tractable model for community ecology with many species

NASA Astrophysics Data System (ADS)

Dickens, Benjamin; Fisher, Charles K.; Mehta, Pankaj

2016-08-01

A fundamental problem in community ecology is understanding how ecological processes such as selection, drift, and immigration give rise to observed patterns in species composition and diversity. Here, we analyze a recently introduced, analytically tractable, presence-absence (PA) model for community assembly, and we use it to ask how ecological traits such as the strength of competition, the amount of diversity, and demographic and environmental stochasticity affect species composition in a community. In the PA model, species are treated as stochastic binary variables that can either be present or absent in a community: species can immigrate into the community from a regional species pool and can go extinct due to competition and stochasticity. Building upon previous work, we show that, despite its simplicity, the PA model reproduces the qualitative features of more complicated models of community assembly. In agreement with recent studies of large, competitive Lotka-Volterra systems, the PA model exhibits distinct ecological behaviors organized around a special ("critical") point corresponding to Hubbell's neutral theory of biodiversity. These results suggest that the concepts of ecological "phases" and phase diagrams can provide a powerful framework for thinking about community ecology, and that the PA model captures the essential ecological dynamics of community assembly.

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.

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

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

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

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

ERIC Educational Resources Information Center

Tu, Hong; Zhu, Jiongming

2016-01-01

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…

Modeling and control of flexible space platforms with articulated payloads

NASA Technical Reports Server (NTRS)

Graves, Philip C.; Joshi, Suresh M.

1989-01-01

The first steps in developing a methodology for spacecraft control-structure interaction (CSI) optimization are identification and classification of anticipated missions, and the development of tractable mathematical models in each mission class. A mathematical model of a generic large flexible space platform (LFSP) with multiple independently pointed rigid payloads is considered. The objective is not to develop a general purpose numerical simulation, but rather to develop an analytically tractable mathematical model of such composite systems. The equations of motion for a single payload case are derived, and are linearized about zero steady-state. The resulting model is then extended to include multiple rigid payloads, yielding the desired analytical form. The mathematical models developed clearly show the internal inertial/elastic couplings, and are therefore suitable for analytical and numerical studies. A simple decentralized control law is proposed for fine pointing the payloads and LFSP attitude control, and simulation results are presented for an example problem. The decentralized controller is shown to be adequate for the example problem chosen, but does not, in general, guarantee stability. A centralized dissipative controller is then proposed, requiring a symmetric form of the composite system equations. Such a controller guarantees robust closed loop stability despite unmodeled elastic dynamics and parameter uncertainties.

Whole-mount in situ hybridization in the Rotifer Brachionus plicatilis representing a basal branch of lophotrochozoans

PubMed Central

Boell, Louis A.

2008-01-01

In order to broaden the comparative scope of evolutionary developmental biology and to refine our picture of animal macroevolution, it is necessary to establish new model organisms, especially from previously underrepresented groups, like the Lophotrochozoa. We have established the culture and protocols for molecular developmental biology in the rotifer species Brachionus plicatilis Müller (Rotifera, Monogononta). Rotifers are nonsegmented animals with enigmatic basal position within the lophotrochozoans and marked by several evolutionary novelties like the wheel organ (corona), the median eye, and the nonpaired posterior foot. The expression of Bp-Pax-6 is shown using whole-mount in situ hybridization. The inexpensive easy culture and experimental tractability of Brachionus as well as the range of interesting questions to which it holds the key make it a promising addition to the “zoo” of evo-devo model organisms. Electronic supplementary material The online version of this article (doi:10.1007/s00427-008-0234-z) contains supplementary material, which is available to authorized users. PMID:18594859

Wrinkle-free design of thin membrane structures using stress-based topology optimization

NASA Astrophysics Data System (ADS)

Luo, Yangjun; Xing, Jian; Niu, Yanzhuang; Li, Ming; Kang, Zhan

2017-05-01

Thin membrane structures would experience wrinkling due to local buckling deformation when compressive stresses are induced in some regions. Using the stress criterion for membranes in wrinkled and taut states, this paper proposed a new stress-based topology optimization methodology to seek the optimal wrinkle-free design of macro-scale thin membrane structures under stretching. Based on the continuum model and linearly elastic assumption in the taut state, the optimization problem is defined as to maximize the structural stiffness under membrane area and principal stress constraints. In order to make the problem computationally tractable, the stress constraints are reformulated into equivalent ones and relaxed by a cosine-type relaxation scheme. The reformulated optimization problem is solved by a standard gradient-based algorithm with the adjoint-variable sensitivity analysis. Several examples with post-bulking simulations and experimental tests are given to demonstrate the effectiveness of the proposed optimization model for eliminating stress-related wrinkles in the novel design of thin membrane structures.

From functional architecture to functional connectomics.

PubMed

Reid, R Clay

2012-07-26

"Receptive Fields, Binocular Interaction and Functional Architecture in the Cat's Visual Cortex" by Hubel and Wiesel (1962) reported several important discoveries: orientation columns, the distinct structures of simple and complex receptive fields, and binocular integration. But perhaps the paper's greatest influence came from the concept of functional architecture (the complex relationship between in vivo physiology and the spatial arrangement of neurons) and several models of functionally specific connectivity. They thus identified two distinct concepts, topographic specificity and functional specificity, which together with cell-type specificity constitute the major determinants of nonrandom cortical connectivity. Orientation columns are iconic examples of topographic specificity, whereby axons within a column connect with cells of a single orientation preference. Hubel and Wiesel also saw the need for functional specificity at a finer scale in their model of thalamic inputs to simple cells, verified in the 1990s. The difficult but potentially more important question of functional specificity between cortical neurons is only now becoming tractable with new experimental techniques. Copyright © 2012 Elsevier Inc. All rights reserved.

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

Scalable tuning of building models to hourly data

DOE PAGES

Garrett, Aaron; New, Joshua Ryan

2015-03-31

Energy models of existing buildings are unreliable unless calibrated so they correlate well with actual energy usage. Manual tuning requires a skilled professional, is prohibitively expensive for small projects, imperfect, non-repeatable, non-transferable, and not scalable to the dozens of sensor channels that smart meters, smart appliances, and cheap/ubiquitous sensors are beginning to make available today. A scalable, automated methodology is needed to quickly and intelligently calibrate building energy models to all available data, increase the usefulness of those models, and facilitate speed-and-scale penetration of simulation-based capabilities into the marketplace for actualized energy savings. The "Autotune'' project is a novel, model-agnosticmore » methodology which leverages supercomputing, large simulation ensembles, and big data mining with multiple machine learning algorithms to allow automatic calibration of simulations that match measured experimental data in a way that is deployable on commodity hardware. This paper shares several methodologies employed to reduce the combinatorial complexity to a computationally tractable search problem for hundreds of input parameters. Furthermore, accuracy metrics are provided which quantify model error to measured data for either monthly or hourly electrical usage from a highly-instrumented, emulated-occupancy research home.« less

Calibration of aero-structural reduced order models using full-field experimental measurements

NASA Astrophysics Data System (ADS)

Perez, R.; Bartram, G.; Beberniss, T.; Wiebe, R.; Spottswood, S. M.

2017-03-01

The structural response of hypersonic aircraft panels is a multi-disciplinary problem, where the nonlinear structural dynamics, aerodynamics, and heat transfer models are coupled. A clear understanding of the impact of high-speed flow effects on the structural response, and the potential influence of the structure on the local environment, is needed in order to prevent the design of overly-conservative structures, a common problem in past hypersonic programs. The current work investigates these challenges from a structures perspective. To this end, the first part of this investigation looks at the modeling of the response of a rectangular panel to an external heating source (thermo-structural coupling) where the temperature effect on the structure is obtained from forward looking infrared (FLIR) measurements and the displacement via 3D-digital image correlation (DIC). The second part of the study uses data from a previous series of wind-tunnel experiments, performed to investigate the response of a compliant panel to the effects of high-speed flow, to train a pressure surrogate model. In this case, the panel aero-loading is obtained from fast-response pressure sensitive paint (PSP) measurements, both directly and from the pressure surrogate model. The result of this investigation is the use of full-field experimental measurements to update the structural model and train a computational efficient model of the loading environment. The use of reduced order models, informed by these full-field physical measurements, is a significant step toward the development of accurate simulation models of complex structures that are computationally tractable.

Biological system interactions.

PubMed Central

Adomian, G; Adomian, G E; Bellman, R E

1984-01-01

Mathematical modeling of cellular population growth, interconnected subsystems of the body, blood flow, and numerous other complex biological systems problems involves nonlinearities and generally randomness as well. Such problems have been dealt with by mathematical methods often changing the actual model to make it tractable. The method presented in this paper (and referenced works) allows much more physically realistic solutions. PMID:6585837

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.

Hierarchical Model for the Analysis of Scattering Data of Complex Materials

DOE PAGES

Oyedele, Akinola; Mcnutt, Nicholas W.; Rios, Orlando; ...

2016-05-16

Interpreting the results of scattering data for complex materials with a hierarchical structure in which at least one phase is amorphous presents a significant challenge. Often the interpretation relies on the use of large-scale molecular dynamics (MD) simulations, in which a structure is hypothesized and from which a radial distribution function (RDF) can be extracted and directly compared against an experimental RDF. This computationally intensive approach presents a bottleneck in the efficient characterization of the atomic structure of new materials. Here, we propose and demonstrate an approach for a hierarchical decomposition of the RDF in which MD simulations are replacedmore » by a combination of tractable models and theory at the atomic scale and the mesoscale, which when combined yield the RDF. We apply the procedure to a carbon composite, in which graphitic nanocrystallites are distributed in an amorphous domain. We compare the model with the RDF from both MD simulation and neutron scattering data. Ultimately, this procedure is applicable for understanding the fundamental processing-structure-property relationships in complex magnetic materials.« less

An analytically tractable model for community ecology with many species

NASA Astrophysics Data System (ADS)

Dickens, Benjamin; Fisher, Charles; Mehta, Pankaj; Pankaj Mehta Biophysics Theory Group Team

A fundamental problem in community ecology is to understand how ecological processes such as selection, drift, and immigration yield observed patterns in species composition and diversity. Here, we present an analytically tractable, presence-absence (PA) model for community assembly and use it to ask how ecological traits such as the strength of competition, diversity in competition, and stochasticity affect species composition in a community. In our PA model, we treat species as stochastic binary variables that can either be present or absent in a community: species can immigrate into the community from a regional species pool and can go extinct due to competition and stochasticity. Despite its simplicity, the PA model reproduces the qualitative features of more complicated models of community assembly. In agreement with recent work on large, competitive Lotka-Volterra systems, the PA model exhibits distinct ecological behaviors organized around a special (``critical'') point corresponding to Hubbell's neutral theory of biodiversity. Our results suggest that the concepts of ``phases'' and phase diagrams can provide a powerful framework for thinking about community ecology and that the PA model captures the essential ecological dynamics of community assembly. Pm was supported by a Simons Investigator in the Mathematical Modeling of Living Systems and a Sloan Research Fellowship.

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…

Verifying and Validating Simulation Models

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

Hemez, Francois M.

2015-02-23

This presentation is a high-level discussion of the Verification and Validation (V&V) of computational models. Definitions of V&V are given to emphasize that “validation” is never performed in a vacuum; it accounts, instead, for the current state-of-knowledge in the discipline considered. In particular comparisons between physical measurements and numerical predictions should account for their respective sources of uncertainty. The differences between error (bias), aleatoric uncertainty (randomness) and epistemic uncertainty (ignorance, lack-of- knowledge) are briefly discussed. Four types of uncertainty in physics and engineering are discussed: 1) experimental variability, 2) variability and randomness, 3) numerical uncertainty and 4) model-form uncertainty. Statisticalmore » sampling methods are available to propagate, and analyze, variability and randomness. Numerical uncertainty originates from the truncation error introduced by the discretization of partial differential equations in time and space. Model-form uncertainty is introduced by assumptions often formulated to render a complex problem more tractable and amenable to modeling and simulation. The discussion concludes with high-level guidance to assess the “credibility” of numerical simulations, which stems from the level of rigor with which these various sources of uncertainty are assessed and quantified.« less

Bayesian calibration for electrochemical thermal model of lithium-ion cells

NASA Astrophysics Data System (ADS)

Tagade, Piyush; Hariharan, Krishnan S.; Basu, Suman; Verma, Mohan Kumar Singh; Kolake, Subramanya Mayya; Song, Taewon; Oh, Dukjin; Yeo, Taejung; Doo, Seokgwang

2016-07-01

Pseudo-two dimensional electrochemical thermal (P2D-ECT) model contains many parameters that are difficult to evaluate experimentally. Estimation of these model parameters is challenging due to computational cost and the transient model. Due to lack of complete physical understanding, this issue gets aggravated at extreme conditions like low temperature (LT) operations. This paper presents a Bayesian calibration framework for estimation of the P2D-ECT model parameters. The framework uses a matrix variate Gaussian process representation to obtain a computationally tractable formulation for calibration of the transient model. Performance of the framework is investigated for calibration of the P2D-ECT model across a range of temperatures (333 Ksbnd 263 K) and operating protocols. In the absence of complete physical understanding, the framework also quantifies structural uncertainty in the calibrated model. This information is used by the framework to test validity of the new physical phenomena before incorporation in the model. This capability is demonstrated by introducing temperature dependence on Bruggeman's coefficient and lithium plating formation at LT. With the incorporation of new physics, the calibrated P2D-ECT model accurately predicts the cell voltage with high confidence. The accurate predictions are used to obtain new insights into the low temperature lithium ion cell behavior.

Rendering the Intractable More Tractable: Tools from Caenorhabditis elegans Ripe for Import into Parasitic Nematodes

PubMed Central

Ward, Jordan D.

2015-01-01

Recent and rapid advances in genetic and molecular tools have brought spectacular tractability to Caenorhabditis elegans, a model that was initially prized because of its simple design and ease of imaging. C. elegans has long been a powerful model in biomedical research, and tools such as RNAi and the CRISPR/Cas9 system allow facile knockdown of genes and genome editing, respectively. These developments have created an additional opportunity to tackle one of the most debilitating burdens on global health and food security: parasitic nematodes. I review how development of nonparasitic nematodes as genetic models informs efforts to import tools into parasitic nematodes. Current tools in three commonly studied parasites (Strongyloides spp., Brugia malayi, and Ascaris suum) are described, as are tools from C. elegans that are ripe for adaptation and the benefits and barriers to doing so. These tools will enable dissection of a huge array of questions that have been all but completely impenetrable to date, allowing investigation into host–parasite and parasite–vector interactions, and the genetic basis of parasitism. PMID:26644478

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.

Functional identification of spike-processing neural circuits.

PubMed

Lazar, Aurel A; Slutskiy, Yevgeniy B

2014-02-01

We introduce a novel approach for a complete functional identification of biophysical spike-processing neural circuits. The circuits considered accept multidimensional spike trains as their input and comprise a multitude of temporal receptive fields and conductance-based models of action potential generation. Each temporal receptive field describes the spatiotemporal contribution of all synapses between any two neurons and incorporates the (passive) processing carried out by the dendritic tree. The aggregate dendritic current produced by a multitude of temporal receptive fields is encoded into a sequence of action potentials by a spike generator modeled as a nonlinear dynamical system. Our approach builds on the observation that during any experiment, an entire neural circuit, including its receptive fields and biophysical spike generators, is projected onto the space of stimuli used to identify the circuit. Employing the reproducing kernel Hilbert space (RKHS) of trigonometric polynomials to describe input stimuli, we quantitatively describe the relationship between underlying circuit parameters and their projections. We also derive experimental conditions under which these projections converge to the true parameters. In doing so, we achieve the mathematical tractability needed to characterize the biophysical spike generator and identify the multitude of receptive fields. The algorithms obviate the need to repeat experiments in order to compute the neurons' rate of response, rendering our methodology of interest to both experimental and theoretical neuroscientists.

Determining the mechanical constitutive properties of metals as a function of strain rate and temperature: A combined experimental and modeling approach

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

I. M. Robertson; A. Beaudoin; J. Lambros

2004-01-05

OAK-135 Development and validation of constitutive models for polycrystalline materials subjected to high strain rate loading over a range of temperatures are needed to predict the response of engineering materials to in-service type conditions (foreign object damage, high-strain rate forging, high-speed sheet forming, deformation behavior during forming, response to extreme conditions, etc.). To account accurately for the complex effects that can occur during extreme and variable loading conditions, requires significant and detailed computational and modeling efforts. These efforts must be closely coupled with precise and targeted experimental measurements that not only verify the predictions of the models, but also providemore » input about the fundamental processes responsible for the macroscopic response. Achieving this coupling between modeling and experimentation is the guiding principle of this program. Specifically, this program seeks to bridge the length scale between discrete dislocation interactions with grain boundaries and continuum models for polycrystalline plasticity. Achieving this goal requires incorporating these complex dislocation-interface interactions into the well-defined behavior of single crystals. Despite the widespread study of metal plasticity, this aspect is not well understood for simple loading conditions, let alone extreme ones. Our experimental approach includes determining the high-strain rate response as a function of strain and temperature with post-mortem characterization of the microstructure, quasi-static testing of pre-deformed material, and direct observation of the dislocation behavior during reloading by using the in situ transmission electron microscope deformation technique. These experiments will provide the basis for development and validation of physically-based constitutive models, which will include dislocation-grain boundary interactions for polycrystalline systems. One aspect of the program will involve the dire ct observation of specific mechanisms of micro-plasticity, as these will indicate the boundary value problem that should be addressed. This focus on the pre-yield region in the quasi-static effort (the elasto-plastic transition) is also a tractable one from an experimental and modeling viewpoint. In addition, our approach will minimize the need to fit model parameters to experimental data to obtain convergence. These are critical steps to reach the primary objective of simulating and modeling material performance under extreme loading conditions. In this annual report, we describe the progress made in the first year of this program.« less

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

The speed-accuracy tradeoff: history, physiology, methodology, and behavior

PubMed Central

Heitz, Richard P.

2014-01-01

There are few behavioral effects as ubiquitous as the speed-accuracy tradeoff (SAT). From insects to rodents to primates, the tendency for decision speed to covary with decision accuracy seems an inescapable property of choice behavior. Recently, the SAT has received renewed interest, as neuroscience approaches begin to uncover its neural underpinnings and computational models are compelled to incorporate it as a necessary benchmark. The present work provides a comprehensive overview of SAT. First, I trace its history as a tractable behavioral phenomenon and the role it has played in shaping mathematical descriptions of the decision process. Second, I present a “users guide” of SAT methodology, including a critical review of common experimental manipulations and analysis techniques and a treatment of the typical behavioral patterns that emerge when SAT is manipulated directly. Finally, I review applications of this methodology in several domains. PMID:24966810

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

Membrane-spanning α-helical barrels as tractable protein-design targets.

PubMed

Niitsu, Ai; Heal, Jack W; Fauland, Kerstin; Thomson, Andrew R; Woolfson, Derek N

2017-08-05

The rational ( de novo ) design of membrane-spanning proteins lags behind that for water-soluble globular proteins. This is due to gaps in our knowledge of membrane-protein structure, and experimental difficulties in studying such proteins compared to water-soluble counterparts. One limiting factor is the small number of experimentally determined three-dimensional structures for transmembrane proteins. By contrast, many tens of thousands of globular protein structures provide a rich source of 'scaffolds' for protein design, and the means to garner sequence-to-structure relationships to guide the design process. The α-helical coiled coil is a protein-structure element found in both globular and membrane proteins, where it cements a variety of helix-helix interactions and helical bundles. Our deep understanding of coiled coils has enabled a large number of successful de novo designs. For one class, the α-helical barrels-that is, symmetric bundles of five or more helices with central accessible channels-there are both water-soluble and membrane-spanning examples. Recent computational designs of water-soluble α-helical barrels with five to seven helices have advanced the design field considerably. Here we identify and classify analogous and more complicated membrane-spanning α-helical barrels from the Protein Data Bank. These provide tantalizing but tractable targets for protein engineering and de novo protein design.This article is part of the themed issue 'Membrane pores: from structure and assembly, to medicine and technology'. © 2017 The Author(s).

The Awesome Power of Yeast Evolutionary Genetics: New Genome Sequences and Strain Resources for the Saccharomyces sensu stricto Genus

PubMed Central

Scannell, Devin R.; Zill, Oliver A.; Rokas, Antonis; Payen, Celia; Dunham, Maitreya J.; Eisen, Michael B.; Rine, Jasper; Johnston, Mark; Hittinger, Chris Todd

2011-01-01

High-quality, well-annotated genome sequences and standardized laboratory strains fuel experimental and evolutionary research. We present improved genome sequences of three species of Saccharomyces sensu stricto yeasts: S. bayanus var. uvarum (CBS 7001), S. kudriavzevii (IFO 1802T and ZP 591), and S. mikatae (IFO 1815T), and describe their comparison to the genomes of S. cerevisiae and S. paradoxus. The new sequences, derived by assembling millions of short DNA sequence reads together with previously published Sanger shotgun reads, have vastly greater long-range continuity and far fewer gaps than the previously available genome sequences. New gene predictions defined a set of 5261 protein-coding orthologs across the five most commonly studied Saccharomyces yeasts, enabling a re-examination of the tempo and mode of yeast gene evolution and improved inferences of species-specific gains and losses. To facilitate experimental investigations, we generated genetically marked, stable haploid strains for all three of these Saccharomyces species. These nearly complete genome sequences and the collection of genetically marked strains provide a valuable toolset for comparative studies of gene function, metabolism, and evolution, and render Saccharomyces sensu stricto the most experimentally tractable model genus. These resources are freely available and accessible through www.SaccharomycesSensuStricto.org. PMID:22384314

Experimental design for dynamics identification of cellular processes.

PubMed

Dinh, Vu; Rundell, Ann E; Buzzard, Gregery T

2014-03-01

We address the problem of using nonlinear models to design experiments to characterize the dynamics of cellular processes by using the approach of the Maximally Informative Next Experiment (MINE), which was introduced in W. Dong et al. (PLoS ONE 3(8):e3105, 2008) and independently in M.M. Donahue et al. (IET Syst. Biol. 4:249-262, 2010). In this approach, existing data is used to define a probability distribution on the parameters; the next measurement point is the one that yields the largest model output variance with this distribution. Building upon this approach, we introduce the Expected Dynamics Estimator (EDE), which is the expected value using this distribution of the output as a function of time. We prove the consistency of this estimator (uniform convergence to true dynamics) even when the chosen experiments cluster in a finite set of points. We extend this proof of consistency to various practical assumptions on noisy data and moderate levels of model mismatch. Through the derivation and proof, we develop a relaxed version of MINE that is more computationally tractable and robust than the original formulation. The results are illustrated with numerical examples on two nonlinear ordinary differential equation models of biomolecular and cellular processes.

Different Parameters Support Generalization and Discrimination Learning in "Drosophila" at the Flight Simulator

ERIC Educational Resources Information Center

Brembs, Bjorn; de Ibarra, Natalie Hempel

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…

Electrical Wave Propagation in a Minimally Realistic Fiber Architecture Model of the Left Ventricle

NASA Astrophysics Data System (ADS)

Song, Xianfeng; Setayeshgar, Sima

2006-03-01

Experimental results indicate a nested, layered geometry for the fiber surfaces of the left ventricle, where fiber directions are approximately aligned in each surface and gradually rotate through the thickness of the ventricle. Numerical and analytical results have highlighted the importance of this rotating anisotropy and its possible destabilizing role on the dynamics of scroll waves in excitable media with application to the heart. Based on the work of Peskin[1] and Peskin and McQueen[2], we present a minimally realistic model of the left ventricle that adequately captures the geometry and anisotropic properties of the heart as a conducting medium while being easily parallelizable, and computationally more tractable than fully realistic anatomical models. Complementary to fully realistic and anatomically-based computational approaches, studies using such a minimal model with the addition of successively realistic features, such as excitation-contraction coupling, should provide unique insight into the basic mechanisms of formation and obliteration of electrical wave instabilities. We describe our construction, implementation and validation of this model. [1] C. S. Peskin, Communications on Pure and Applied Mathematics 42, 79 (1989). [2] C. S. Peskin and D. M. McQueen, in Case Studies in Mathematical Modeling: Ecology, Physiology, and Cell Biology, 309(1996)

Biostatistical analysis of quantitative immunofluorescence microscopy images.

PubMed

Giles, C; Albrecht, M A; Lam, V; Takechi, R; Mamo, J C

2016-12-01

Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

A mixture theory model of fluid and solute transport in the microvasculature of normal and malignant tissues. II: Factor sensitivity analysis, calibration, and validation.

PubMed

Schuff, M M; Gore, J P; Nauman, E A

2013-12-01

The treatment of cancerous tumors is dependent upon the delivery of therapeutics through the blood by means of the microcirculation. Differences in the vasculature of normal and malignant tissues have been recognized, but it is not fully understood how these differences affect transport and the applicability of existing mathematical models has been questioned at the microscale due to the complex rheology of blood and fluid exchange with the tissue. In addition to determining an appropriate set of governing equations it is necessary to specify appropriate model parameters based on physiological data. To this end, a two stage sensitivity analysis is described which makes it possible to determine the set of parameters most important to the model's calibration. In the first stage, the fluid flow equations are examined and a sensitivity analysis is used to evaluate the importance of 11 different model parameters. Of these, only four substantially influence the intravascular axial flow providing a tractable set that could be calibrated using red blood cell velocity data from the literature. The second stage also utilizes a sensitivity analysis to evaluate the importance of 14 model parameters on extravascular flux. Of these, six exhibit high sensitivity and are integrated into the model calibration using a response surface methodology and experimental intra- and extravascular accumulation data from the literature (Dreher et al. in J Natl Cancer Inst 98(5):335-344, 2006). The model exhibits good agreement with the experimental results for both the mean extravascular concentration and the penetration depth as a function of time for inert dextran over a wide range of molecular weights.

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.

PubMed

Fernandez-de-Cossio-Diaz, Jorge; Leon, Kalet; Mulet, Roberto

2017-11-01

In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures

PubMed Central

Leon, Kalet; Mulet, Roberto

2017-01-01

In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced. PMID:29131817

Evaluation of invertebrate infection models for pathogenic corynebacteria.

PubMed

Ott, Lisa; McKenzie, Ashleigh; Baltazar, Maria Teresa; Britting, Sabine; Bischof, Andrea; Burkovski, Andreas; Hoskisson, Paul A

2012-08-01

For several pathogenic bacteria, model systems for host-pathogen interactions were developed, which provide the possibility of quick and cost-effective high throughput screening of mutant bacteria for genes involved in pathogenesis. A number of different model systems, including amoeba, nematodes, insects, and fish, have been introduced, and it was observed that different bacteria respond in different ways to putative surrogate hosts, and distinct model systems might be more or less suitable for a certain pathogen. The aim of this study was to develop a suitable invertebrate model for the human and animal pathogens Corynebacterium diphtheriae, Corynebacterium pseudotuberculosis, and Corynebacterium ulcerans. The results obtained in this study indicate that Acanthamoeba polyphaga is not optimal as surrogate host, while both Caenorhabtitis elegans and Galleria larvae seem to offer tractable models for rapid assessment of virulence between strains. Caenorhabtitis elegans gives more differentiated results and might be the best model system for pathogenic corynebacteria, given the tractability of bacteria and the range of mutant nematodes available to investigate the host response in combination with bacterial virulence. Nevertheless, Galleria will also be useful in respect to innate immune responses to pathogens because insects offer a more complex cell-based innate immune system compared with the simple innate immune system of C. elegans. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

The genome of Aiptasia, a sea anemone model for coral symbiosis

PubMed Central

Baumgarten, Sebastian; Simakov, Oleg; Esherick, Lisl Y.; Liew, Yi Jin; Lehnert, Erik M.; Michell, Craig T.; Li, Yong; Hambleton, Elizabeth A.; Guse, Annika; Oates, Matt E.; Gough, Julian; Weis, Virginia M.; Aranda, Manuel; Pringle, John R.; Voolstra, Christian R.

2015-01-01

The most diverse marine ecosystems, coral reefs, depend upon a functional symbiosis between a cnidarian animal host (the coral) and intracellular photosynthetic dinoflagellate algae. The molecular and cellular mechanisms underlying this endosymbiosis are not well understood, in part because of the difficulties of experimental work with corals. The small sea anemone Aiptasia provides a tractable laboratory model for investigating these mechanisms. Here we report on the assembly and analysis of the Aiptasia genome, which will provide a foundation for future studies and has revealed several features that may be key to understanding the evolution and function of the endosymbiosis. These features include genomic rearrangements and taxonomically restricted genes that may be functionally related to the symbiosis, aspects of host dependence on alga-derived nutrients, a novel and expanded cnidarian-specific family of putative pattern-recognition receptors that might be involved in the animal–algal interactions, and extensive lineage-specific horizontal gene transfer. Extensive integration of genes of prokaryotic origin, including genes for antimicrobial peptides, presumably reflects an intimate association of the animal–algal pair also with its prokaryotic microbiome. PMID:26324906

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.

From Engrams to Pathologies of the Brain

PubMed Central

Denny, Christine A.; Lebois, Evan; Ramirez, Steve

2017-01-01

Memories are the experiential threads that tie our past to the present. The biological realization of a memory is termed an engram—the enduring biochemical and physiological processes that enable learning and retrieval. The past decade has witnessed an explosion of engram research that suggests we are closing in on boundary conditions for what qualifies as the physical manifestation of memory. In this review, we provide a brief history of engram research, followed by an overview of the many rodent models available to probe memory with intersectional strategies that have yielded unprecedented spatial and temporal resolution over defined sets of cells. We then discuss the limitations and controversies surrounding engram research and subsequently attempt to reconcile many of these views both with data and by proposing a conceptual shift in the strategies utilized to study memory. We finally bridge this literature with human memory research and disorders of the brain and end by providing an experimental blueprint for future engram studies in mammals. Collectively, we believe that we are in an era of neuroscience where engram research has transitioned from ephemeral and philosophical concepts to provisional, tractable, experimental frameworks for studying the cellular, circuit and behavioral manifestations of memory. PMID:28439228

From Engrams to Pathologies of the Brain.

PubMed

Denny, Christine A; Lebois, Evan; Ramirez, Steve

2017-01-01

Memories are the experiential threads that tie our past to the present. The biological realization of a memory is termed an engram-the enduring biochemical and physiological processes that enable learning and retrieval. The past decade has witnessed an explosion of engram research that suggests we are closing in on boundary conditions for what qualifies as the physical manifestation of memory. In this review, we provide a brief history of engram research, followed by an overview of the many rodent models available to probe memory with intersectional strategies that have yielded unprecedented spatial and temporal resolution over defined sets of cells. We then discuss the limitations and controversies surrounding engram research and subsequently attempt to reconcile many of these views both with data and by proposing a conceptual shift in the strategies utilized to study memory. We finally bridge this literature with human memory research and disorders of the brain and end by providing an experimental blueprint for future engram studies in mammals. Collectively, we believe that we are in an era of neuroscience where engram research has transitioned from ephemeral and philosophical concepts to provisional, tractable, experimental frameworks for studying the cellular, circuit and behavioral manifestations of memory.

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.

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

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.

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

Functional genetics for all: engineered nucleases, CRISPR and the gene editing revolution.

PubMed

Gilles, Anna F; Averof, Michalis

2014-01-01

Developmental biology, as all experimental science, is empowered by technological advances. The availability of genetic tools in some species - designated as model organisms - has driven their use as major platforms for understanding development, physiology and behavior. Extending these tools to a wider range of species determines whether (and how) we can experimentally approach developmental diversity and evolution. During the last two decades, comparative developmental biology (evo-devo) was marked by the introduction of gene knockdown and deep sequencing technologies that are applicable to a wide range of species. These approaches allowed us to test the developmental role of specific genes in diverse species, to study biological processes that are not accessible in established models and, in some cases, to conduct genome-wide screens that overcome the limitations of the candidate gene approach. The recent discovery of CRISPR/Cas as a means of precise alterations into the genome promises to revolutionize developmental genetics. In this review we describe the development of gene editing tools, from zinc-finger nucleases to TALENs and CRISPR, and examine their application in gene targeting, their limitations and the opportunities they present for evo-devo. We outline their use in gene knock-out and knock-in approaches, and in manipulating gene functions by directing molecular effectors to specific sites in the genome. The ease-of-use and efficiency of CRISPR in diverse species provide an opportunity to close the technology gap that exists between established model organisms and emerging genetically-tractable species.

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

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.

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

Computational Nonlinear Morphology with Emphasis on Semitic Languages. Studies in Natural Language Processing.

ERIC Educational Resources Information Center

Kiraz, George Anton

This book presents a tractable computational model that can cope with complex morphological operations, especially in Semitic languages, and less complex morphological systems present in Western languages. It outlines a new generalized regular rewrite rule system that uses multiple finite-state automata to cater to root-and-pattern morphology,…

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

Hyper-Spectral Image Analysis With Partially Latent Regression and Spatial Markov Dependencies

NASA Astrophysics Data System (ADS)

Deleforge, Antoine; Forbes, Florence; Ba, Sileye; Horaud, Radu

2015-09-01

Hyper-spectral data can be analyzed to recover physical properties at large planetary scales. This involves resolving inverse problems which can be addressed within machine learning, with the advantage that, once a relationship between physical parameters and spectra has been established in a data-driven fashion, the learned relationship can be used to estimate physical parameters for new hyper-spectral observations. Within this framework, we propose a spatially-constrained and partially-latent regression method which maps high-dimensional inputs (hyper-spectral images) onto low-dimensional responses (physical parameters such as the local chemical composition of the soil). The proposed regression model comprises two key features. Firstly, it combines a Gaussian mixture of locally-linear mappings (GLLiM) with a partially-latent response model. While the former makes high-dimensional regression tractable, the latter enables to deal with physical parameters that cannot be observed or, more generally, with data contaminated by experimental artifacts that cannot be explained with noise models. Secondly, spatial constraints are introduced in the model through a Markov random field (MRF) prior which provides a spatial structure to the Gaussian-mixture hidden variables. Experiments conducted on a database composed of remotely sensed observations collected from the Mars planet by the Mars Express orbiter demonstrate the effectiveness of the proposed model.

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

Community assembly of the worm gut microbiome

NASA Astrophysics Data System (ADS)

Gore, Jeff

It has become increasingly clear that human health is strongly influenced by the bacteria that live within the gut, known collectively as the gut microbiome. This complex community varies tremendously between individuals, but understanding the sources that lead to this heterogeneity is challenging. To address this challenge, we are using a bottom-up approach to develop a predictive understanding of how the microbiome assembles and functions within a simple and experimentally tractable gut, the gut of the worm C. elegans. We have found that stochastic community assembly in the C. elegansintestine is sufficient to produce strong inter-worm heterogeneity in community composition. When worms are fed with two neutrally-competing fluorescently labeled bacterial strains, we observe stochastically-driven bimodality in community composition, where approximately half of the worms are dominated by each bacterial strain. A simple model incorporating stochastic colonization suggests that heterogeneity between worms is driven by the low rate at which bacteria successfully establish new intestinal colonies. We can increase this rate experimentally by feeding worms at high bacterial density; in these conditions the bimodality disappears. We have also characterized all pairwise interspecies competitions among a set of eleven bacterial species, illuminating the rules governing interspecies community assembly. These results demonstrate the potential importance of stochastic processes in bacterial community formation and suggest a role for C. elegans as a model system for ecology of host-associated communities.

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

Empirical analysis of RNA robustness and evolution using high-throughput sequencing of ribozyme reactions.

PubMed

Hayden, Eric J

2016-08-15

RNA molecules provide a realistic but tractable model of a genotype to phenotype relationship. This relationship has been extensively investigated computationally using secondary structure prediction algorithms. Enzymatic RNA molecules, or ribozymes, offer access to genotypic and phenotypic information in the laboratory. Advancements in high-throughput sequencing technologies have enabled the analysis of sequences in the lab that now rivals what can be accomplished computationally. This has motivated a resurgence of in vitro selection experiments and opened new doors for the analysis of the distribution of RNA functions in genotype space. A body of computational experiments has investigated the persistence of specific RNA structures despite changes in the primary sequence, and how this mutational robustness can promote adaptations. This article summarizes recent approaches that were designed to investigate the role of mutational robustness during the evolution of RNA molecules in the laboratory, and presents theoretical motivations, experimental methods and approaches to data analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

The left-right asymmetry of liver lobation is generated by Pitx2c-mediated asymmetries in the hepatic diverticulum.

PubMed

Womble, Mandy; Amin, Nirav M; Nascone-Yoder, Nanette

2018-07-15

Internal organs exhibit left-right asymmetric sizes, shapes and anatomical positions, but how these different lateralities develop is poorly understood. Here we use the experimentally tractable Xenopus model to uncover the morphogenetic events that drive the left-right asymmetrical lobation of the liver. On the right side of the early hepatic diverticulum, endoderm cells become columnar and apically constricted, forming an expanded epithelial surface and, ultimately, an enlarged right liver lobe. In contrast, the cells on the left side become rounder, and rearrange into a compact, stratified architecture that produces a smaller left lobe. Side-specific gain- and loss-of-function studies reveal that asymmetric expression of the left-right determinant Pitx2c elicits distinct epithelial morphogenesis events in the left side of the diverticulum. Surprisingly, the cellular events induced by Pitx2c during liver development are opposite those induced in other digestive organs, suggesting divergent cellular mechanisms underlie the formation of different lateralities. Copyright © 2018 Elsevier Inc. All rights reserved.

A General Tool for Engineering the NAD/NADP Cofactor Preference of Oxidoreductases.

PubMed

Cahn, Jackson K B; Werlang, Caroline A; Baumschlager, Armin; Brinkmann-Chen, Sabine; Mayo, Stephen L; Arnold, Frances H

2017-02-17

The ability to control enzymatic nicotinamide cofactor utilization is critical for engineering efficient metabolic pathways. However, the complex interactions that determine cofactor-binding preference render this engineering particularly challenging. Physics-based models have been insufficiently accurate and blind directed evolution methods too inefficient to be widely adopted. Building on a comprehensive survey of previous studies and our own prior engineering successes, we present a structure-guided, semirational strategy for reversing enzymatic nicotinamide cofactor specificity. This heuristic-based approach leverages the diversity and sensitivity of catalytically productive cofactor binding geometries to limit the problem to an experimentally tractable scale. We demonstrate the efficacy of this strategy by inverting the cofactor specificity of four structurally diverse NADP-dependent enzymes: glyoxylate reductase, cinnamyl alcohol dehydrogenase, xylose reductase, and iron-containing alcohol dehydrogenase. The analytical components of this approach have been fully automated and are available in the form of an easy-to-use web tool: Cofactor Specificity Reversal-Structural Analysis and Library Design (CSR-SALAD).

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

Phenotype and Age Differences in Blood Gas Characteristics, Electrolytes, Hemoglobin, Plasma Glucose and Cortisol in Female Squirrel Monkeys

NASA Technical Reports Server (NTRS)

Brizzee, K. R.; Ordy, J. M.; Dunlap, W. P.; Kendrick, R.; Wengenack, T. M.

1988-01-01

Due to its small size, lower cost, tractable nature, successful breeding in captivity and its status near the middle of the primate phylogenetic scale, the squirrel monkey has become an attractive primate model for basic and biomedical research. Although the squirrel monkey now is being used more extensively in many laboratories with diverse interests, only fragmentary reports have been published regarding basic physiological characteristics, or baseline blood reference values of different phenotypes, particularly blood gases, hematology and serum chemical constituents. It is becoming recognized increasingly that these baseline blood reference values are important not only in the care and maintenance of the squirrel monkey, but are critical for assessing normal physiological status, as well as the effects of various experimental treatments. The purpose of this study was to compare differences in blood gases, electrolytes, hematology, blood glucose and cortisol among young and old Bolivian (Roman type) and Colombian (Gothic type) phenotypes of the squirrel monkey.

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

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.

A dispersion relationship governing incompressible wall turbulence

NASA Technical Reports Server (NTRS)

Tsuge, S.

1978-01-01

The method of separation of variables is shown to make turbulent correlation equations of Karman-Howarth type tractable for shear turbulence as well under the condition of neglected triple correlation. The separated dependent variable obeys an Orr-Sommerfeld equation. A new analytical method is developed using a scaling law different from the classical one due to Heisenberg and Lin and more appropriate for wall turbulent profiles. A dispersion relationship between the wave number and the separation constant which has the dimension of a frequency is derived in support of experimental observations of wave or coherent structure of wall turbulence.

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.

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

2007-03-01

Saccharomyces cerevisiae and model fungus Cryptococcus neoformans as models to understand how the GAP activity of the yeast neurofibromin homologs, Ira1...another genetically 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

A cerebellar learning model of vestibulo-ocular reflex adaptation in wild-type and mutant mice.

PubMed

Clopath, Claudia; Badura, Aleksandra; De Zeeuw, Chris I; Brunel, Nicolas

2014-05-21

Mechanisms of cerebellar motor learning are still poorly understood. The standard Marr-Albus-Ito theory posits that learning involves plasticity at the parallel fiber to Purkinje cell synapses under control of the climbing fiber input, which provides an error signal as in classical supervised learning paradigms. However, a growing body of evidence challenges this theory, in that additional sites of plasticity appear to contribute to motor adaptation. Here, we consider phase-reversal training of the vestibulo-ocular reflex (VOR), a simple form of motor learning for which a large body of experimental data is available in wild-type and mutant mice, in which the excitability of granule cells or inhibition of Purkinje cells was affected in a cell-specific fashion. We present novel electrophysiological recordings of Purkinje cell activity measured in naive wild-type mice subjected to this VOR adaptation task. We then introduce a minimal model that consists of learning at the parallel fibers to Purkinje cells with the help of the climbing fibers. Although the minimal model reproduces the behavior of the wild-type animals and is analytically tractable, it fails at reproducing the behavior of mutant mice and the electrophysiology data. Therefore, we build a detailed model involving plasticity at the parallel fibers to Purkinje cells' synapse guided by climbing fibers, feedforward inhibition of Purkinje cells, and plasticity at the mossy fiber to vestibular nuclei neuron synapse. The detailed model reproduces both the behavioral and electrophysiological data of both the wild-type and mutant mice and allows for experimentally testable predictions. Copyright © 2014 the authors 0270-6474/14/347203-13$15.00/0.

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.

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

From drug to protein: using yeast genetics for high-throughput target discovery.

PubMed

Armour, Christopher D; Lum, Pek Yee

2005-02-01

The budding yeast Saccharomyces cerevisiae has long been an effective eukaryotic model system for understanding basic cellular processes. The genetic tractability and ease of manipulation in the laboratory make yeast well suited for large-scale chemical and genetic screens. Several recent studies describing the use of yeast genetics for high-throughput drug target identification are discussed in this review.

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

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.

CNTNAP2 is a direct FoxP2 target in vitro and in vivo in zebra finches: complex regulation by age and activity.

PubMed

Adam, I; Mendoza, E; Kobalz, U; Wohlgemuth, S; Scharff, C

2017-07-01

Mutations of FOXP2 are associated with altered brain structure, including the striatal part of the basal ganglia, and cause a severe speech and language disorder. Songbirds serve as a tractable neurobiological model for speech and language research. Experimental downregulation of FoxP2 in zebra finch Area X, a nucleus of the striatal song control circuitry, affects synaptic transmission and spine densities. It also renders song learning and production inaccurate and imprecise, similar to the speech impairment of patients carrying FOXP2 mutations. Here we show that experimental downregulation of FoxP2 in Area X using lentiviral vectors leads to reduced expression of CNTNAP2, a FOXP2 target gene in humans. In addition, natural downregulation of FoxP2 by age or by singing also downregulated CNTNAP2 expression. Furthermore, we report that FoxP2 binds to and activates the avian CNTNAP2 promoter in vitro. Taken together these data establish CNTNAP2 as a direct FoxP2 target gene in songbirds, likely affecting synaptic function relevant for song learning and song maintenance. © 2017 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.

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.

Phase Helps Find Geometrically Optimal Gaits

NASA Astrophysics Data System (ADS)

Revzen, Shai; Hatton, Ross

Geometric motion planning describes motions of animals and machines governed by g ˙ = gA (q) q ˙ - a connection A (.) relating shape q and shape velocity q ˙ to body frame velocity g-1 g ˙ ∈ se (3) . Measuring the entire connection over a multidimensional q is often unfeasible with current experimental methods. We show how using a phase estimator can make tractable measuring the local structure of the connection surrounding a periodic motion q (φ) driven by a phase φ ∈S1 . This approach reduces the complexity of the estimation problem by a factor of dimq . The results suggest that phase estimation can be combined with geometric optimization into an iterative gait optimization algorithm usable on experimental systems, or alternatively, to allow the geometric optimality of an observed gait to be detected. ARO W911NF-14-1-0573, NSF 1462555.

Solving and Learning Soft Temporal Constraints: Experimental Setting and Results

NASA Technical Reports Server (NTRS)

Rossi, F.; Sperduti, A.; Venable, K. B.; Khatib, L.; Morris, P.; Morris, R.; Clancy, Daniel (Technical Monitor)

2002-01-01

Soft temporal constraints problems allow to describe in a natural way scenarios where events happen over time and preferences are associated to event distances and durations. However, sometimes such local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. Machine learning techniques can be useful in this respect. In this paper we describe two solvers (one more general and the other one more efficient) for tractable subclasses of soft temporal problems, and we show some experimental results. The random generator used to build the problems on which tests are performed is also described. We also compare the two solvers highlighting the tradeoff between performance and representational power. Finally, we present a learning module and we show its behavior on randomly-generated examples.

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.

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.

Homeostasis and catabolism of choline and glycine betaine: lessons from Pseudomonas aeruginosa.

PubMed

Wargo, Matthew J

2013-04-01

Most sequenced bacteria possess mechanisms to import choline and glycine betaine (GB) into the cytoplasm. The primary role of choline in bacteria appears to be as the precursor to GB, and GB is thought to primarily act as a potent osmoprotectant. Choline and GB may play accessory roles in shaping microbial communities, based on their limited availability and ability to enhance survival under stress conditions. Choline and GB enrichment near eukaryotes suggests a role in the chemical relationships between these two kingdoms, and some of these interactions have been experimentally demonstrated. While many bacteria can convert choline to GB for osmoprotection, a variety of soil- and water-dwelling bacteria have catabolic pathways for the multistep conversion of choline, via GB, to glycine and can thereby use choline and GB as sole sources of carbon and nitrogen. In these choline catabolizers, the GB intermediate represents a metabolic decision point to determine whether GB is catabolized or stored as an osmo- and stress protectant. This minireview focuses on this decision point in Pseudomonas aeruginosa, which aerobically catabolizes choline and can use GB as an osmoprotectant and a nutrient source. P. aeruginosa is an experimentally tractable and ecologically relevant model to study the regulatory pathways controlling choline and GB homeostasis in choline-catabolizing bacteria. The study of P. aeruginosa associations with eukaryotes and other bacteria also makes this a powerful model to study the impact of choline and GB, and their associated regulatory and catabolic pathways, on host-microbe and microbe-microbe relationships.

Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications.

PubMed

Shang, Fanhua; Cheng, James; Liu, Yuanyuan; Luo, Zhi-Quan; Lin, Zhouchen

2017-09-04

The heavy-tailed distributions of corrupted outliers and singular values of all channels in low-level vision have proven effective priors for many applications such as background modeling, photometric stereo and image alignment. And they can be well modeled by a hyper-Laplacian. However, the use of such distributions generally leads to challenging non-convex, non-smooth and non-Lipschitz problems, and makes existing algorithms very slow for large-scale applications. Together with the analytic solutions to Lp-norm minimization with two specific values of p, i.e., p=1/2 and p=2/3, we propose two novel bilinear factor matrix norm minimization models for robust principal component analysis. We first define the double nuclear norm and Frobenius/nuclear hybrid norm penalties, and then prove that they are in essence the Schatten-1/2 and 2/3 quasi-norms, respectively, which lead to much more tractable and scalable Lipschitz optimization problems. Our experimental analysis shows that both our methods yield more accurate solutions than original Schatten quasi-norm minimization, even when the number of observations is very limited. Finally, we apply our penalties to various low-level vision problems, e.g. moving object detection, image alignment and inpainting, and show that our methods usually outperform the state-of-the-art methods.

Computational prediction and experimental verification of HVA1-like abscisic acid responsive promoters in rice (Oryza sativa).

PubMed

Ross, Christian; Shen, Qingxi J

2006-09-01

Abscisic acid (ABA) is one of the central plant hormones, responsible for controlling both maturation and germination in seeds, as well as mediating adaptive responses to desiccation, injury, and pathogen infection in vegetative tissues. Thorough analyses of two barley genes, HVA1 and HVA22, indicate that their response to ABA relies on the interaction of two cis-acting elements in their promoters, an ABA response element (ABRE) and a coupling element (CE). Together, they form an ABA response promoter complex (ABRC). Comparison of promoters of barley HVA1 and it rice orthologue indicates that the structures and sequences of their ABRCs are highly similar. Prediction of ABA responsive genes in the rice genome is then tractable to a bioinformatics approach based on the structures of the well-defined barley ABRCs. Here we describe a model developed based on the consensus, inter-element spacing and orientations of experimentally determined ABREs and CEs. Our search of the rice promoter database for promoters that fit the model has generated a partial list of genes in rice that have a high likelihood of being involved in the ABA signaling network. The ABA inducibility of some of the rice genes identified was validated with quantitative reverse transcription PCR (QPCR). By limiting our input data to known enhancer modules and experimentally derived rules, we have generated a high confidence subset of ABA-regulated genes. The results suggest that the pathways by which cereals respond to biotic and abiotic stresses overlap significantly, and that regulation is not confined to the level transcription. The large fraction of putative regulatory genes carrying HVA1-like enhancer modules in their promoters suggests the ABA signal enters at multiple points into a complex regulatory network that remains largely unmapped.

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.

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

RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data.

PubMed

Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

2016-06-15

Protein-RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein-RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset. We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein-RNA structure-based models on an unprecedented scale. Software and models are freely available at http://rck.csail.mit.edu/ bab@mit.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

A novel model to predict gas-phase hydroxyl radical oxidation kinetics of polychlorinated compounds.

PubMed

Luo, Shuang; Wei, Zongsu; Spinney, Richard; Yang, Zhihui; Chai, Liyuan; Xiao, Ruiyang

2017-04-01

In this study, a novel model based on aromatic meta-substituent grouping was presented to predict the second-order rate constants (k) for OH oxidation of PCBs in gas-phase. Since the oxidation kinetics are dependent on the chlorination degree and position, we hypothesized that it may be more accurate for k value prediction if we group PCB congeners based on substitution positions (i.e., ortho (o), meta (m), and para (p)). To test this hypothesis, we examined the correlation of polarizability (α), a quantum chemical based descriptor for k values, with an empirical Hammett constant (σ + ) on each substitution position. Our result shows that α is highly linearly correlated to ∑σ o,m,p + based on aromatic meta-substituents leading to the grouping based predictive model. With the new model, the calculated k values exhibited an excellent agreement with experimental measurements, and greater predictive power than the quantum chemical based quantitative structure activity relationship (QSAR) model. Further, the relationship of α and ∑σ o,m,p + for PCDDs congeners, together with highest occupied molecular orbital (HOMO) distribution, were used to validate the aromatic meta-substituent grouping method. This newly developed model features a combination of good predictability of quantum chemical based QSAR model and simplicity of Hammett relationship, showing a great potential for fast and computational tractable prediction of k values for gas-phase OH oxidation of polychlorinated compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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.

Niche metabolism in parasitic protozoa

PubMed Central

Ginger, Michael L

2005-01-01

Complete or partial genome sequences have recently become available for several medically and evolutionarily important parasitic protozoa. Through the application of bioinformatics complete metabolic repertoires for these parasites can be predicted. For experimentally intractable parasites insight provided by metabolic maps generated in silico has been startling. At its more extreme end, such bioinformatics reckoning facilitated the discovery in some parasites of mitochondria remodelled beyond previous recognition, and the identification of a non-photosynthetic chloroplast relic in malarial parasites. However, for experimentally tractable parasites, mapping of the general metabolic terrain is only a first step in understanding how the parasite modulates its streamlined, yet still often puzzlingly complex, metabolism in order to complete life cycles within host, vector, or environment. This review provides a comparative overview and discussion of metabolic strategies used by several different parasitic protozoa in order to subvert and survive host defences, and illustrates how genomic data contribute to the elucidation of parasite metabolism. PMID:16553311

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.

Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP.

PubMed

Shim, Yoonsik; Philippides, Andrew; Staras, Kevin; Husbands, Phil

2016-10-01

We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven by input timing dependent plasticity (ITDP). The ITDP gating mechanism is based on recent experimental findings. An abstract, analytically tractable model of the ITDP driven ensemble architecture is derived from a logical model based on the probabilities of neural firing events. A detailed analysis of this model provides insights that allow it to be extended into a full, biologically plausible, computational implementation of the architecture which is demonstrated on a visual classification task. The extended model makes use of a style of spiking network, first introduced as a model of cortical microcircuits, that is capable of Bayesian inference, effectively performing expectation maximization. The unsupervised ensemble learning mechanism, based around such spiking expectation maximization (SEM) networks whose combined outputs are mediated by ITDP, is shown to perform the visual classification task well and to generalize to unseen data. The combined ensemble performance is significantly better than that of the individual classifiers, validating the ensemble architecture and learning mechanisms. The properties of the full model are analysed in the light of extensive experiments with the classification task, including an investigation into the influence of different input feature selection schemes and a comparison with a hierarchical STDP based ensemble architecture.

Estimating true evolutionary distances under the DCJ model.

PubMed

Lin, Yu; Moret, Bernard M E

2008-07-01

Modern techniques can yield the ordering and strandedness of genes on each chromosome of a genome; such data already exists for hundreds of organisms. The evolutionary mechanisms through which the set of the genes of an organism is altered and reordered are of great interest to systematists, evolutionary biologists, comparative genomicists and biomedical researchers. Perhaps the most basic concept in this area is that of evolutionary distance between two genomes: under a given model of genomic evolution, how many events most likely took place to account for the difference between the two genomes? We present a method to estimate the true evolutionary distance between two genomes under the 'double-cut-and-join' (DCJ) model of genome rearrangement, a model under which a single multichromosomal operation accounts for all genomic rearrangement events: inversion, transposition, translocation, block interchange and chromosomal fusion and fission. Our method relies on a simple structural characterization of a genome pair and is both analytically and computationally tractable. We provide analytical results to describe the asymptotic behavior of genomes under the DCJ model, as well as experimental results on a wide variety of genome structures to exemplify the very high accuracy (and low variance) of our estimator. Our results provide a tool for accurate phylogenetic reconstruction from multichromosomal gene rearrangement data as well as a theoretical basis for refinements of the DCJ model to account for biological constraints. All of our software is available in source form under GPL at http://lcbb.epfl.ch.

Maximum Entropy Principle for Transportation

NASA Astrophysics Data System (ADS)

Bilich, F.; DaSilva, R.

2008-11-01

In this work we deal with modeling of the transportation phenomenon for use in the transportation planning process and policy-impact studies. The model developed is based on the dependence concept, i.e., the notion that the probability of a trip starting at origin i is dependent on the probability of a trip ending at destination j given that the factors (such as travel time, cost, etc.) which affect travel between origin i and destination j assume some specific values. The derivation of the solution of the model employs the maximum entropy principle combining a priori multinomial distribution with a trip utility concept. This model is utilized to forecast trip distributions under a variety of policy changes and scenarios. The dependence coefficients are obtained from a regression equation where the functional form is derived based on conditional probability and perception of factors from experimental psychology. The dependence coefficients encode all the information that was previously encoded in the form of constraints. In addition, the dependence coefficients encode information that cannot be expressed in the form of constraints for practical reasons, namely, computational tractability. The equivalence between the standard formulation (i.e., objective function with constraints) and the dependence formulation (i.e., without constraints) is demonstrated. The parameters of the dependence-based trip-distribution model are estimated, and the model is also validated using commercial air travel data in the U.S. In addition, policy impact analyses (such as allowance of supersonic flights inside the U.S. and user surcharge at noise-impacted airports) on air travel are performed.

Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP

PubMed Central

Staras, Kevin

2016-01-01

We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven by input timing dependent plasticity (ITDP). The ITDP gating mechanism is based on recent experimental findings. An abstract, analytically tractable model of the ITDP driven ensemble architecture is derived from a logical model based on the probabilities of neural firing events. A detailed analysis of this model provides insights that allow it to be extended into a full, biologically plausible, computational implementation of the architecture which is demonstrated on a visual classification task. The extended model makes use of a style of spiking network, first introduced as a model of cortical microcircuits, that is capable of Bayesian inference, effectively performing expectation maximization. The unsupervised ensemble learning mechanism, based around such spiking expectation maximization (SEM) networks whose combined outputs are mediated by ITDP, is shown to perform the visual classification task well and to generalize to unseen data. The combined ensemble performance is significantly better than that of the individual classifiers, validating the ensemble architecture and learning mechanisms. The properties of the full model are analysed in the light of extensive experiments with the classification task, including an investigation into the influence of different input feature selection schemes and a comparison with a hierarchical STDP based ensemble architecture. PMID:27760125

Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data.

PubMed

Liu, Yuanyuan; Shang, Fanhua; Jiao, Licheng; Cheng, James; Cheng, Hong

2015-11-01

In recent years, low-rank tensor completion (LRTC) problems have received a significant amount of attention in computer vision, data mining, and signal processing. The existing trace norm minimization algorithms for iteratively solving LRTC problems involve multiple singular value decompositions of very large matrices at each iteration. Therefore, they suffer from high computational cost. In this paper, we propose a novel trace norm regularized CANDECOMP/PARAFAC decomposition (TNCP) method for simultaneous tensor decomposition and completion. We first formulate a factor matrix rank minimization model by deducing the relation between the rank of each factor matrix and the mode- n rank of a tensor. Then, we introduce a tractable relaxation of our rank function, and then achieve a convex combination problem of much smaller-scale matrix trace norm minimization. Finally, we develop an efficient algorithm based on alternating direction method of multipliers to solve our problem. The promising experimental results on synthetic and real-world data validate the effectiveness of our TNCP method. Moreover, TNCP is significantly faster than the state-of-the-art methods and scales to larger problems.

Glycan Engagement Dictates Hydrocephalus Induction by Serotype 1 Reovirus

PubMed Central

Stencel-Baerenwald, Jennifer; Reiss, Kerstin; Blaum, Bärbel S.; Colvin, Daniel; Li, Xiao-Nan; Abel, Ty; Boyd, Kelli; Stehle, Thilo

2015-01-01

ABSTRACT Receptors expressed on the host cell surface adhere viruses to target cells and serve as determinants of viral tropism. Several viruses bind cell surface glycans to facilitate entry, but the contribution of specific glycan moieties to viral disease is incompletely understood. Reovirus provides a tractable experimental model for studies of viral neuropathogenesis. In newborn mice, serotype 1 (T1) reovirus causes hydrocephalus, whereas serotype 3 (T3) reovirus causes encephalitis. T1 and T3 reoviruses engage distinct glycans, suggesting that glycan-binding capacity contributes to these differences in pathogenesis. Using structure-guided mutagenesis, we engineered a mutant T1 reovirus incapable of binding the T1 reovirus-specific glycan receptor, GM2. The mutant virus induced substantially less hydrocephalus than wild-type virus, an effect phenocopied by wild-type virus infection of GM2-deficient mice. In comparison to wild-type virus, yields of mutant virus were diminished in cultured ependymal cells, the cell type that lines the brain ventricles. These findings suggest that GM2 engagement targets reovirus to ependymal cells in mice and illuminate the function of glycan engagement in reovirus serotype-dependent disease. PMID:25736887

Adipogenesis and epicardial adipose tissue: A novel fate of the epicardium induced by mesenchymal transformation and PPARγ activation

PubMed Central

Yamaguchi, Yukiko; Cavallero, Susana; Patterson, Michaela; Shen, Hua; Xu, Jian; Kumar, S. Ram; Sucov, Henry M.

2015-01-01

The hearts of many mammalian species are surrounded by an extensive layer of fat called epicardial adipose tissue (EAT). The lineage origins and determinative mechanisms of EAT development are unclear, in part because mice and other experimentally tractable model organisms are thought to not have this tissue. In this study, we show that mouse hearts have EAT, localized to a specific region in the atrial–ventricular groove. Lineage analysis indicates that this adipose tissue originates from the epicardium, a multipotent epithelium that until now is only established to normally generate cardiac fibroblasts and coronary smooth muscle cells. We show that adoption of the adipocyte fate in vivo requires activation of the peroxisome proliferator activated receptor gamma (PPARγ) pathway, and that this fate can be ectopically induced in mouse ventricular epicardium, either in embryonic or adult stages, by expression and activation of PPARγ at times of epicardium–mesenchymal transformation. Human embryonic ventricular epicardial cells natively express PPARγ, which explains the abundant presence of fat seen in human hearts at birth and throughout life. PMID:25646471

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.

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.

Caenorhabditis elegans as an experimental tool for the study of complex neurological diseases: Parkinson's disease, Alzheimer's disease and autism spectrum disorder.

PubMed

Calahorro, Fernando; Ruiz-Rubio, Manuel

2011-12-01

The nematode Caenorhabditis elegans has a very well-defined and genetically tractable nervous system which offers an effective model to explore basic mechanistic pathways that might be underpin complex human neurological diseases. Here, the role C. elegans is playing in understanding two neurodegenerative conditions, Parkinson's and Alzheimer's disease (AD), and a complex neurological condition, autism, is used as an exemplar of the utility of this model system. C. elegans is an imperfect model of Parkinson's disease because it lacks orthologues of the human disease-related genes PARK1 and LRRK2 which are linked to the autosomal dominant form of this disease. Despite this fact, the nematode is a good model because it allows transgenic expression of these human genes and the study of the impact on dopaminergic neurons in several genetic backgrounds and environmental conditions. For AD, C. elegans has orthologues of the amyloid precursor protein and both human presenilins, PS1 and PS2. In addition, many of the neurotoxic properties linked with Aβ amyloid and tau peptides can be studied in the nematode. Autism spectrum disorder is a complex neurodevelopmental disorder characterised by impairments in human social interaction, difficulties in communication, and restrictive and repetitive behaviours. Establishing C. elegans as a model for this complex behavioural disorder is difficult; however, abnormalities in neuronal synaptic communication are implicated in the aetiology of the disorder. Numerous studies have associated autism with mutations in several genes involved in excitatory and inhibitory synapses in the mammalian brain, including neuroligin, neurexin and shank, for which there are C. elegans orthologues. Thus, several molecular pathways and behavioural phenotypes in C. elegans have been related to autism. In general, the nematode offers a series of advantages that combined with knowledge from other animal models and human research, provides a powerful complementary experimental approach for understanding the molecular mechanisms and underlying aetiology of complex neurological diseases.

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

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.

Tracking Temporal Hazard in the Human Electroencephalogram Using a Forward Encoding Model

PubMed Central

2018-01-01

Abstract Human observers automatically extract temporal contingencies from the environment and predict the onset of future events. Temporal predictions are modeled by the hazard function, which describes the instantaneous probability for an event to occur given it has not occurred yet. Here, we tackle the question of whether and how the human brain tracks continuous temporal hazard on a moment-to-moment basis, and how flexibly it adjusts to strictly implicit variations in the hazard function. We applied an encoding-model approach to human electroencephalographic data recorded during a pitch-discrimination task, in which we implicitly manipulated temporal predictability of the target tones by varying the interval between cue and target tone (i.e. the foreperiod). Critically, temporal predictability either was driven solely by the passage of time (resulting in a monotonic hazard function) or was modulated to increase at intermediate foreperiods (resulting in a modulated hazard function with a peak at the intermediate foreperiod). Forward-encoding models trained to predict the recorded EEG signal from different temporal hazard functions were able to distinguish between experimental conditions, showing that implicit variations of temporal hazard bear tractable signatures in the human electroencephalogram. Notably, this tracking signal was reconstructed best from the supplementary motor area, underlining this area’s link to cognitive processing of time. Our results underline the relevance of temporal hazard to cognitive processing and show that the predictive accuracy of the encoding-model approach can be utilized to track abstract time-resolved stimuli. PMID:29740594

Coarse-grained modeling of RNA 3D structure.

PubMed

Dawson, Wayne K; Maciejczyk, Maciej; Jankowska, Elzbieta J; Bujnicki, Janusz M

2016-07-01

Functional RNA molecules depend on three-dimensional (3D) structures to carry out their tasks within the cell. Understanding how these molecules interact to carry out their biological roles requires a detailed knowledge of RNA 3D structure and dynamics as well as thermodynamics, which strongly governs the folding of RNA and RNA-RNA interactions as well as a host of other interactions within the cellular environment. Experimental determination of these properties is difficult, and various computational methods have been developed to model the folding of RNA 3D structures and their interactions with other molecules. However, computational methods also have their limitations, especially when the biological effects demand computation of the dynamics beyond a few hundred nanoseconds. For the researcher confronted with such challenges, a more amenable approach is to resort to coarse-grained modeling to reduce the number of data points and computational demand to a more tractable size, while sacrificing as little critical information as possible. This review presents an introduction to the topic of coarse-grained modeling of RNA 3D structures and dynamics, covering both high- and low-resolution strategies. We discuss how physics-based approaches compare with knowledge based methods that rely on databases of information. In the course of this review, we discuss important aspects in the reasoning process behind building different models and the goals and pitfalls that can result. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Pathway Design, Engineering, and Optimization.

PubMed

Garcia-Ruiz, Eva; HamediRad, Mohammad; Zhao, Huimin

The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.

Membrane ion transport in non-excitable tissues.

PubMed Central

Nehrke, Keith

2014-01-01

The facilitated movement of ions across cell membranes can be characterized as occurring through active (ATP-dependent), secondary active (coupled), or passive transport processes. Each of these processes is mediated by a diverse group of membrane proteins. Over the past fifteen years, studies of membrane transport in C. elegans have benefited from the fact that worms are anatomically simple, easily and economically cultured, and genetically tractable. These experimental advantages have been instrumental in defining how membrane transport processes contribute to whole organism physiology. The focus of this review is to survey the recent advances in our understanding of membrane transport that have arisen from integrative physiological approaches in the nematode C. elegans. PMID:25536490

Cell-autonomous correction of ring chromosomes in human induced pluripotent stem cells

NASA Astrophysics Data System (ADS)

Bershteyn, Marina; Hayashi, Yohei; Desachy, Guillaume; Hsiao, Edward C.; Sami, Salma; Tsang, Kathryn M.; Weiss, Lauren A.; Kriegstein, Arnold R.; Yamanaka, Shinya; Wynshaw-Boris, Anthony

2014-03-01

Ring chromosomes are structural aberrations commonly associated with birth defects, mental disabilities and growth retardation. Rings form after fusion of the long and short arms of a chromosome, and are sometimes associated with large terminal deletions. Owing to the severity of these large aberrations that can affect multiple contiguous genes, no possible therapeutic strategies for ring chromosome disorders have been proposed. During cell division, ring chromosomes can exhibit unstable behaviour leading to continuous production of aneuploid progeny with low viability and high cellular death rate. The overall consequences of this chromosomal instability have been largely unexplored in experimental model systems. Here we generated human induced pluripotent stem cells (iPSCs) from patient fibroblasts containing ring chromosomes with large deletions and found that reprogrammed cells lost the abnormal chromosome and duplicated the wild-type homologue through the compensatory uniparental disomy (UPD) mechanism. The karyotypically normal iPSCs with isodisomy for the corrected chromosome outgrew co-existing aneuploid populations, enabling rapid and efficient isolation of patient-derived iPSCs devoid of the original chromosomal aberration. Our results suggest a fundamentally different function for cellular reprogramming as a means of `chromosome therapy' to reverse combined loss-of-function across many genes in cells with large-scale aberrations involving ring structures. In addition, our work provides an experimentally tractable human cellular system for studying mechanisms of chromosomal number control, which is of critical relevance to human development and disease.

The Insect Pathogens.

PubMed

Lovett, Brian; St Leger, Raymond J

2017-03-01

Fungi are the most common disease-causing agents of insects; aside from playing a crucial role in natural ecosystems, insect-killing fungi are being used as alternatives to chemical insecticides and as resources for biotechnology and pharmaceuticals. Some common experimentally tractable genera, such as Metarhizium spp., exemplify genetic diversity and dispersal because they contain numerous intraspecific variants with distinct environmental and insect host ranges. The availability of tools for molecular genetics and multiple sequenced genomes has made these fungi ideal experimental models for answering basic questions on the genetic and genomic processes behind adaptive phenotypes. For example, comparative genomics of entomopathogenic fungi has shown they exhibit diverse reproductive modes that often determine rates and patterns of genome evolution and are linked as cause or effect with pathogenic strategies. Fungal-insect pathogens represent lifestyle adaptations that evolved numerous times, and there are significant differences in host range and pathogenic strategies between the major groups. However, typically, spores landing on the cuticle produce appressoria and infection pegs that breach the cuticle using mechanical pressure and cuticle-degrading enzymes. Once inside the insect body cavity, fungal pathogens face a potent and comprehensively studied immune defense by which the host attempts to eliminate or reduce an infection. The Fungal Kingdom stands alone in the range, extent, and complexity of their manipulation of arthropod behavior. In part, this is because most only sporulate on cadavers, so they must ensure the dying host positions itself to allow efficient transmission.

Homeostasis and Catabolism of Choline and Glycine Betaine: Lessons from Pseudomonas aeruginosa

PubMed Central

2013-01-01

Most sequenced bacteria possess mechanisms to import choline and glycine betaine (GB) into the cytoplasm. The primary role of choline in bacteria appears to be as the precursor to GB, and GB is thought to primarily act as a potent osmoprotectant. Choline and GB may play accessory roles in shaping microbial communities, based on their limited availability and ability to enhance survival under stress conditions. Choline and GB enrichment near eukaryotes suggests a role in the chemical relationships between these two kingdoms, and some of these interactions have been experimentally demonstrated. While many bacteria can convert choline to GB for osmoprotection, a variety of soil- and water-dwelling bacteria have catabolic pathways for the multistep conversion of choline, via GB, to glycine and can thereby use choline and GB as sole sources of carbon and nitrogen. In these choline catabolizers, the GB intermediate represents a metabolic decision point to determine whether GB is catabolized or stored as an osmo- and stress protectant. This minireview focuses on this decision point in Pseudomonas aeruginosa, which aerobically catabolizes choline and can use GB as an osmoprotectant and a nutrient source. P. aeruginosa is an experimentally tractable and ecologically relevant model to study the regulatory pathways controlling choline and GB homeostasis in choline-catabolizing bacteria. The study of P. aeruginosa associations with eukaryotes and other bacteria also makes this a powerful model to study the impact of choline and GB, and their associated regulatory and catabolic pathways, on host-microbe and microbe-microbe relationships. PMID:23354714

Motoneuron membrane potentials follow a time inhomogeneous jump diffusion process.

PubMed

Jahn, Patrick; Berg, Rune W; Hounsgaard, Jørn; Ditlevsen, Susanne

2011-11-01

Stochastic leaky integrate-and-fire models are popular due to their simplicity and statistical tractability. They have been widely applied to gain understanding of the underlying mechanisms for spike timing in neurons, and have served as building blocks for more elaborate models. Especially the Ornstein-Uhlenbeck process is popular to describe the stochastic fluctuations in the membrane potential of a neuron, but also other models like the square-root model or models with a non-linear drift are sometimes applied. Data that can be described by such models have to be stationary and thus, the simple models can only be applied over short time windows. However, experimental data show varying time constants, state dependent noise, a graded firing threshold and time-inhomogeneous input. In the present study we build a jump diffusion model that incorporates these features, and introduce a firing mechanism with a state dependent intensity. In addition, we suggest statistical methods to estimate all unknown quantities and apply these to analyze turtle motoneuron membrane potentials. Finally, simulated and real data are compared and discussed. We find that a square-root diffusion describes the data much better than an Ornstein-Uhlenbeck process with constant diffusion coefficient. Further, the membrane time constant decreases with increasing depolarization, as expected from the increase in synaptic conductance. The network activity, which the neuron is exposed to, can be reasonably estimated to be a threshold version of the nerve output from the network. Moreover, the spiking characteristics are well described by a Poisson spike train with an intensity depending exponentially on the membrane potential.

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.

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.

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.

Hook, Line and Infection: A Guide to Culturing Parasites, Establishing Infections and Assessing Immune Responses in the Three-Spined Stickleback.

PubMed

Stewart, Alexander; Jackson, Joseph; Barber, Iain; Eizaguirre, Christophe; Paterson, Rachel; van West, Pieter; Williams, Chris; Cable, Joanne

2017-01-01

The three-spined stickleback (Gasterosteus aculeatus) is a model organism with an extremely well-characterized ecology, evolutionary history, behavioural repertoire and parasitology that is coupled with published genomic data. These small temperate zone fish therefore provide an ideal experimental system to study common diseases of coldwater fish, including those of aquacultural importance. However, detailed information on the culture of stickleback parasites, the establishment and maintenance of infections and the quantification of host responses is scattered between primary and grey literature resources, some of which is not readily accessible. Our aim is to lay out a framework of techniques based on our experience to inform new and established laboratories about culture techniques and recent advances in the field. Here, essential knowledge on the biology, capture and laboratory maintenance of sticklebacks, and their commonly studied parasites is drawn together, highlighting recent advances in our understanding of the associated immune responses. In compiling this guide on the maintenance of sticklebacks and a range of common, taxonomically diverse parasites in the laboratory, we aim to engage a broader interdisciplinary community to consider this highly tractable model when addressing pressing questions in evolution, infection and aquaculture. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Electronic structures of C u 2 O , C u 4 O 3 , and CuO: A joint experimental and theoretical study

DOE PAGES

Wang, Y.; Lany, S.; Ghanbaja, J.; ...

2016-12-14

We present a joint experimental and theoretical study for the electronic structures of copper oxides including Cu 2O, CuO, and the metastable mixed-valence oxide Cu 4O 3. The optical band gap is determined by experimental optical absorption coefficient, and the electronic structure in valence and conduction bands is probed by photoemission and electron energy loss spectroscopies, respectively. Furthermore, we compare our experimental results with many-body GW calculations utilizing an additional on-site potential for d-orbital energies that facilitates tractable and predictive computations. The side-by-side comparison between the three oxides, including a band insulator (Cu2O) and two Mott/charge-transfer insulators (CuO, Cu 4Omore » 3) leads to a consistent picture for the optical and band-structure properties of the Cu oxides, strongly supporting indirect band gaps of about 1.2 and 0.8 eV in CuO and Cu 4O 3, respectively. This comparison also points towards surface oxidation and reduction effects that can complicate the interpretation of the photoemission spectra.« less

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.

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.

An algorithm to predict the connectome of neural microcircuits

PubMed Central

Reimann, Michael W.; King, James G.; Muller, Eilif B.; Ramaswamy, Srikanth; Markram, Henry

2015-01-01

Experimentally mapping synaptic connections, in terms of the numbers and locations of their synapses and estimating connection probabilities, is still not a tractable task, even for small volumes of tissue. In fact, the six layers of the neocortex contain thousands of unique types of synaptic connections between the many different types of neurons, of which only a handful have been characterized experimentally. Here we present a theoretical framework and a data-driven algorithmic strategy to digitally reconstruct the complete synaptic connectivity between the different types of neurons in a small well-defined volume of tissue—the micro-scale connectome of a neural microcircuit. By enforcing a set of established principles of synaptic connectivity, and leveraging interdependencies between fundamental properties of neural microcircuits to constrain the reconstructed connectivity, the algorithm yields three parameters per connection type that predict the anatomy of all types of biologically viable synaptic connections. The predictions reproduce a spectrum of experimental data on synaptic connectivity not used by the algorithm. We conclude that an algorithmic approach to the connectome can serve as a tool to accelerate experimental mapping, indicating the minimal dataset required to make useful predictions, identifying the datasets required to improve their accuracy, testing the feasibility of experimental measurements, and making it possible to test hypotheses of synaptic connectivity. PMID:26500529

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

Maximum entropy principal for transportation

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

Bilich, F.; Da Silva, R.

In this work we deal with modeling of the transportation phenomenon for use in the transportation planning process and policy-impact studies. The model developed is based on the dependence concept, i.e., the notion that the probability of a trip starting at origin i is dependent on the probability of a trip ending at destination j given that the factors (such as travel time, cost, etc.) which affect travel between origin i and destination j assume some specific values. The derivation of the solution of the model employs the maximum entropy principle combining a priori multinomial distribution with a trip utilitymore » concept. This model is utilized to forecast trip distributions under a variety of policy changes and scenarios. The dependence coefficients are obtained from a regression equation where the functional form is derived based on conditional probability and perception of factors from experimental psychology. The dependence coefficients encode all the information that was previously encoded in the form of constraints. In addition, the dependence coefficients encode information that cannot be expressed in the form of constraints for practical reasons, namely, computational tractability. The equivalence between the standard formulation (i.e., objective function with constraints) and the dependence formulation (i.e., without constraints) is demonstrated. The parameters of the dependence-based trip-distribution model are estimated, and the model is also validated using commercial air travel data in the U.S. In addition, policy impact analyses (such as allowance of supersonic flights inside the U.S. and user surcharge at noise-impacted airports) on air travel are performed.« less

Compressive mechanical characterization of non-human primate spinal cord white matter.

PubMed

Jannesar, Shervin; Allen, Mark; Mills, Sarah; Gibbons, Anne; Bresnahan, Jacqueline C; Salegio, Ernesto A; Sparrey, Carolyn J

2018-05-02

The goal of developing computational models of spinal cord injury (SCI) is to better understand the human injury condition. However, finite element models of human SCI have used rodent spinal cord tissue properties due to a lack of experimental data. Central nervous system tissues in non human primates (NHP) closely resemble that of humans and therefore, it is expected that material constitutive models obtained from NHPs will increase the fidelity and the accuracy of human SCI models. Human SCI most often results from compressive loading and spinal cord white matter properties affect FE predicted patterns of injury; therefore, the objectives of this study were to characterize the unconfined compressive response of NHP spinal cord white matter and present an experimentally derived, finite element tractable constitutive model for the tissue. Cervical spinal cords were harvested from nine male adult NHPs (Macaca mulatta). White matter biopsy samples (3 mm in diameter) were taken from both lateral columns of the spinal cord and were divided into four strain rate groups for unconfined dynamic compression and stress relaxation (post-mortem <1-hour). The NHP spinal cord white matter compressive response was sensitive to strain rate and showed substantial stress relaxation confirming the viscoelastic behavior of the material. An Ogden 1st order model best captured the non-linear behavior of NHP white matter in a quasi-linear viscoelastic material model with 4-term Prony series. This study is the first to characterize NHP spinal cord white matter at high (>10/sec) strain rates typical of traumatic injury. The finite element derived material constitutive model of this study will increase the fidelity of SCI computational models and provide important insights for transferring pre-clinical findings to clinical treatments. Spinal cord injury (SCI) finite element (FE) models provide an important tool to bridge the gap between animal studies and human injury, assess injury prevention technologies (e.g. helmets, seatbelts), and provide insight into the mechanisms of injury. Although, FE model outcomes depend on the assumed material constitutive model, there is limited experimental data for fresh spinal cords and all was obtained from rodent, porcine or bovine tissues. Central nervous system tissues in non human primates (NHP) more closely resemble humans. This study characterizes fresh NHP spinal cord material properties at high strains rates and large deformations typical of SCI for the first time. A constitutive model was defined that can be readily implemented in finite strain FE analysis of SCI. Copyright © 2018. Published by Elsevier Ltd.

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

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.

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.

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

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.

Side-wall gas 'creep' and 'thermal stress convection' in microgravity experiments on film growth by vapor transport

NASA Technical Reports Server (NTRS)

Rosner, Daniel E.

1989-01-01

While 'no-slip' boundary conditions and the Navier-Stokes equations of continuum fluid mechanics have served the vapor transport community well until now, it is pointed out that transport conditions within highly nonisothermal ampoules are such that the nonisothermal side walls 'drive' the dominant convective flow, and the familiar Stokes-Fourier-Fick laws governing the molecular fluxes of momentum, energy, and (species) mass in the 'continuum' field equations will often prove to be inadequate, even at Knudsen numbers as small as 0.001. The implications of these interesting gas kinetic phenomena under microgravity conditions, and even under 'earth-bound' experimental conditions, are outlined here, along with a tractable approach to their systematic treatment.

Quantum Computing: Solving Complex Problems

ScienceCinema

DiVincenzo, David

2018-05-22

One of the motivating ideas of quantum computation was that there could be a new kind of machine that would solve hard problems in quantum mechanics. There has been significant progress towards the experimental realization of these machines (which I will review), but there are still many questions about how such a machine could solve computational problems of interest in quantum physics. New categorizations of the complexity of computational problems have now been invented to describe quantum simulation. The bad news is that some of these problems are believed to be intractable even on a quantum computer, falling into a quantum analog of the NP class. The good news is that there are many other new classifications of tractability that may apply to several situations of physical interest.

Bacterial Communities of Diverse Drosophila Species: Ecological Context of a Host–Microbe Model System

PubMed Central

Bhatnagar, Srijak; Eisen, Jonathan A.; Kopp, Artyom

2011-01-01

Drosophila melanogaster is emerging as an important model of non-pathogenic host–microbe interactions. The genetic and experimental tractability of Drosophila has led to significant gains in our understanding of animal–microbial symbiosis. However, the full implications of these results cannot be appreciated without the knowledge of the microbial communities associated with natural Drosophila populations. In particular, it is not clear whether laboratory cultures can serve as an accurate model of host–microbe interactions that occur in the wild, or those that have occurred over evolutionary time. To fill this gap, we characterized natural bacterial communities associated with 14 species of Drosophila and related genera collected from distant geographic locations. To represent the ecological diversity of Drosophilids, examined species included fruit-, flower-, mushroom-, and cactus-feeders. In parallel, wild host populations were compared to laboratory strains, and controlled experiments were performed to assess the importance of host species and diet in shaping bacterial microbiome composition. We find that Drosophilid flies have taxonomically restricted bacterial communities, with 85% of the natural bacterial microbiome composed of only four bacterial families. The dominant bacterial taxa are widespread and found in many different host species despite the taxonomic, ecological, and geographic diversity of their hosts. Both natural surveys and laboratory experiments indicate that host diet plays a major role in shaping the Drosophila bacterial microbiome. Despite this, the internal bacterial microbiome represents only a highly reduced subset of the external bacterial communities, suggesting that the host exercises some level of control over the bacteria that inhabit its digestive tract. Finally, we show that laboratory strains provide only a limited model of natural host–microbe interactions. Bacterial taxa used in experimental studies are rare or absent in wild Drosophila populations, while the most abundant associates of natural Drosophila populations are rare in the lab. PMID:21966276

Non-Markovian quantum processes: Complete framework and efficient characterization

NASA Astrophysics Data System (ADS)

Pollock, Felix A.; Rodríguez-Rosario, César; Frauenheim, Thomas; Paternostro, Mauro; Modi, Kavan

2018-01-01

Currently, there is no systematic way to describe a quantum process with memory solely in terms of experimentally accessible quantities. However, recent technological advances mean we have control over systems at scales where memory effects are non-negligible. The lack of such an operational description has hindered advances in understanding physical, chemical, and biological processes, where often unjustified theoretical assumptions are made to render a dynamical description tractable. This has led to theories plagued with unphysical results and no consensus on what a quantum Markov (memoryless) process is. Here, we develop a universal framework to characterize arbitrary non-Markovian quantum processes. We show how a multitime non-Markovian process can be reconstructed experimentally, and that it has a natural representation as a many-body quantum state, where temporal correlations are mapped to spatial ones. Moreover, this state is expected to have an efficient matrix-product-operator form in many cases. Our framework constitutes a systematic tool for the effective description of memory-bearing open-system evolutions.

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.

A Multiscale Progressive Failure Modeling Methodology for Composites that Includes Fiber Strength Stochastics

NASA Technical Reports Server (NTRS)

Ricks, Trenton M.; Lacy, Thomas E., Jr.; Bednarcyk, Brett A.; Arnold, Steven M.; Hutchins, John W.

2014-01-01

A multiscale modeling methodology was developed for continuous fiber composites that incorporates a statistical distribution of fiber strengths into coupled multiscale micromechanics/finite element (FE) analyses. A modified two-parameter Weibull cumulative distribution function, which accounts for the effect of fiber length on the probability of failure, was used to characterize the statistical distribution of fiber strengths. A parametric study using the NASA Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) was performed to assess the effect of variable fiber strengths on local composite failure within a repeating unit cell (RUC) and subsequent global failure. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a unidirectional SCS-6/TIMETAL 21S metal matrix composite tensile dogbone specimen at 650 degC. Multiscale progressive failure analyses were performed to quantify the effect of spatially varying fiber strengths on the RUC-averaged and global stress-strain responses and failure. The ultimate composite strengths and distribution of failure locations (predominately within the gage section) reasonably matched the experimentally observed failure behavior. The predicted composite failure behavior suggests that use of macroscale models that exploit global geometric symmetries are inappropriate for cases where the actual distribution of local fiber strengths displays no such symmetries. This issue has not received much attention in the literature. Moreover, the model discretization at a specific length scale can have a profound effect on the computational costs associated with multiscale simulations.models that yield accurate yet tractable results.

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.

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.

Natural selection promotes antigenic evolvability.

PubMed

Graves, Christopher J; Ros, Vera I D; Stevenson, Brian; Sniegowski, Paul D; Brisson, Dustin

2013-01-01

The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios) and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish chronic infections.

Natural Selection Promotes Antigenic Evolvability

PubMed Central

Graves, Christopher J.; Ros, Vera I. D.; Stevenson, Brian; Sniegowski, Paul D.; Brisson, Dustin

2013-01-01

The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed ‘cassettes’ that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios) and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish chronic infections. PMID:24244173

Quantifying the brush structure and assembly of mixed brush nanoparticles in solution

NASA Astrophysics Data System (ADS)

Koski, Jason; Frischknecht, Amalie

The arrangement of nanoparticles in a polymer melt or solution is critical to the resulting material properties. A common strategy to control the distribution of nanoparticles is to graft polymer chains onto the surface of the nanoparticles. An emerging strategy to further control the arrangement of nanoparticles is to graft polymer chains of different types and/or different lengths onto the surface of the nanoparticle, though this considerably increases the parameter space needed to describe the system. Theoretical models that are capable of predicting the assembly of nanoparticles in a melt or solution are thus desirable to guide experiments. In this talk, I will describe a recently developed non-equilibrium method that is appealing in its ability to tractably account for fluctuations and that can directly relate to experiments. To showcase the utility of this method, I apply it to mixed brush grafted nanoparticles in solution where fluctuations are prominent. Specifically, I investigate the role of experimentally relevant parameters on the structure of the brush and the corresponding effects on the assembly of the nanoparticles in solution. These results can be directly linked to experiments to help narrow the relevant parameter space for optimizing these materials.

E-RNAi: a web application for the multi-species design of RNAi reagents—2010 update

PubMed Central

Horn, Thomas; Boutros, Michael

2010-01-01

The design of RNA interference (RNAi) reagents is an essential step for performing loss-of-function studies in many experimental systems. The availability of sequenced and annotated genomes greatly facilitates RNAi experiments in an increasing number of organisms that were previously not genetically tractable. The E-RNAi web-service, accessible at http://www.e-rnai.org/, provides a computational resource for the optimized design and evaluation of RNAi reagents. The 2010 update of E-RNAi now covers 12 genomes, including Drosophila, Caenorhabditis elegans, human, emerging model organisms such as Schmidtea mediterranea and Acyrthosiphon pisum, as well as the medically relevant vectors Anopheles gambiae and Aedes aegypti. The web service calculates RNAi reagents based on the input of target sequences, sequence identifiers or by visual selection of target regions through a genome browser interface. It identifies optimized RNAi target-sites by ranking sequences according to their predicted specificity, efficiency and complexity. E-RNAi also facilitates the design of secondary RNAi reagents for validation experiments, evaluation of pooled siRNA reagents and batch design. Results are presented online, as a downloadable HTML report and as tab-delimited files. PMID:20444868

Efficient CRISPR/Cas9-assisted gene targeting enables rapid and precise genetic manipulation of mammalian neural stem cells

PubMed Central

Bressan, Raul Bardini; Dewari, Pooran Singh; Kalantzaki, Maria; Gangoso, Ester; Matjusaitis, Mantas; Garcia-Diaz, Claudia; Blin, Carla; Grant, Vivien; Bulstrode, Harry; Gogolok, Sabine; Skarnes, William C.

2017-01-01

Mammalian neural stem cell (NSC) lines provide a tractable model for discovery across stem cell and developmental biology, regenerative medicine and neuroscience. They can be derived from foetal or adult germinal tissues and continuously propagated in vitro as adherent monolayers. NSCs are clonally expandable, genetically stable, and easily transfectable – experimental attributes compatible with targeted genetic manipulations. However, gene targeting, which is crucial for functional studies of embryonic stem cells, has not been exploited to date in NSC lines. Here, we deploy CRISPR/Cas9 technology to demonstrate a variety of sophisticated genetic modifications via gene targeting in both mouse and human NSC lines, including: (1) efficient targeted transgene insertion at safe harbour loci (Rosa26 and AAVS1); (2) biallelic knockout of neurodevelopmental transcription factor genes; (3) simple knock-in of epitope tags and fluorescent reporters (e.g. Sox2-V5 and Sox2-mCherry); and (4) engineering of glioma mutations (TP53 deletion; H3F3A point mutations). These resources and optimised methods enable facile and scalable genome editing in mammalian NSCs, providing significant new opportunities for functional genetic analysis. PMID:28096221

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.

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.

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.

Cutoff size need not strongly influence molecular dynamics results for solvated polypeptides.

PubMed

Beck, David A C; Armen, Roger S; Daggett, Valerie

2005-01-18

The correct treatment of van der Waals and electrostatic nonbonded interactions in molecular force fields is essential for performing realistic molecular dynamics (MD) simulations of solvated polypeptides. The most computationally tractable treatment of nonbonded interactions in MD utilizes a spherical distance cutoff (typically, 8-12 A) to reduce the number of pairwise interactions. In this work, we assess three spherical atom-based cutoff approaches for use with all-atom explicit solvent MD: abrupt truncation, a CHARMM-style electrostatic shift truncation, and our own force-shifted truncation. The chosen system for this study is an end-capped 17-residue alanine-based alpha-helical peptide, selected because of its use in previous computational and experimental studies. We compare the time-averaged helical content calculated from these MD trajectories with experiment. We also examine the effect of varying the cutoff treatment and distance on energy conservation. We find that the abrupt truncation approach is pathological in its inability to conserve energy. The CHARMM-style shift truncation performs quite well but suffers from energetic instability. On the other hand, the force-shifted spherical cutoff method conserves energy, correctly predicts the experimental helical content, and shows convergence in simulation statistics as the cutoff is increased. This work demonstrates that by using proper and rigorous techniques, it is possible to correctly model polypeptide dynamics in solution with a spherical cutoff. The inherent computational advantage of spherical cutoffs over Ewald summation (and related) techniques is essential in accessing longer MD time scales.

Marking individual ants for behavioral sampling in a laboratory colony.

PubMed

Holbrook, C Tate

2009-07-01

Ant societies are tractable and malleable, two features that make them ideal models for probing the organization of complex biological systems. The ability to identify specific individuals while they function as part of a colony permits an integrative analysis of social complexity, including self-organizational processes (i.e., how individual-level properties and social interactions give rise to emergent, colony-level attributes such as division of labor and collective decision making). Effects of genotype, nutrition, and physiology on individual behavior and the organization of work also can be investigated in this manner, through correlative and manipulative approaches. Moreover, aspects of colony demography (e.g., colony size, and age and size distributions of workers) can be altered experimentally to examine colony development and regulatory mechanisms underlying colony homeostasis and resiliency. This protocol describes how to sample the behavior of ants living in a colony under laboratory conditions. Specifically, it outlines how to identify and observe individuals within a colony, an approach that can be used to quantify individual- and colony-level patterns of behavior. When a lower-resolution measure of overall group behavior is desired, individual identities might not be required. Given the diversity of ants and their study, this protocol provides a very general methodology; the details can be modified according to the body size, colony size, and ecology of the focal species, as well as to specific research aims. These basic techniques can also be extended to more advanced experimental designs such as manipulation of colony demography and hormone treatment.

Thin Shell evolution of NIF capsule with asymmetric drive and the resulting neutron diagnostics

NASA Astrophysics Data System (ADS)

Buchoff, Michael; Hammer, Jim

2015-11-01

One of the major impediments to achieving ignition via ICF is the non-spherical implosion arising from small asymmetries in the drive forcing the collapse of the capsule. Likewise, an experimental diagnostic for quantifying the characteristics of the implosion asymmetry is the final state neutrons, whose number and velocity distributions are not experimentally consistent with the expectation of a spherical implosion. In principle, connecting these initial and final state asymmetries could be solved via hydrodynamic simulations, but due to the multiple scales traversed throughout this process, these calculations are difficult and expensive, leaving much of the potential drive asymmetry profiles unexplored. In this work, we solve the resulting analytic equations from the thin-shell model proposed by Ott et. al. to evolve the capsule over a range of different drive asymmetries from its initial state (when the shell aspect ratio is much greater than 1) to a radius of roughly 250 microns, consisting of a layer of dense CH, a cold layer of dense DT, and a warm core of sparsely distributed DT. At this stage, more tractable hydrodynamical simulations are performed in the ARES code suite, determining the distribution of neutron from thermonuclear yield. These and future results allow for a multitude of tests of asymmetric sources to compare with and potentially guide experiment. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

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.

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.

A Unified Model for Left-Right Asymmetry? Comparison and Synthesis of Molecular Models of Embryonic Laterality

PubMed Central

Vandenberg, Laura N.; Levin, Michael

2013-01-01

Understanding how and when the left-right (LR) axis is first established is a fundamental question in developmental biology. A popular model is that the LR axis is established relatively late in embryogenesis, due to the movement of motile cilia and the resultant directed fluid flow during late gastrulation/early neurulation. Yet, a large body of evidence suggests that biophysical, molecular, and bioelectrical asymmetries exist much earlier in development, some as early as the first cell cleavage after fertilization. Alternative models of LR asymmetry have been proposed that accommodate these data, postulating that asymmetry is established due to a chiral cytoskeleton and/or the asymmetric segregation of chromatids. There are some similarities, and many differences, in how these various models postulate the origin and timing of symmetry breaking and amplification, and these events’ linkage to the well-conserved subsequent asymmetric transcriptional cascades. This review examines experimental data that lend strong support to an early origin of LR asymmetry, yet are also consistent with later roles for cilia in the amplification of LR pathways. In this way, we propose that the various models of asymmetry can be unified: early events are needed to initiate LR asymmetry, and later events could be utilized by some species to maintain LR-biases. We also present an alternative hypothesis, which proposes that individual embryos stochastically choose one of several possible pathways with which to establish their LR axis. These two hypotheses are both tractable in appropriate model species; testing them to resolve open questions in the field of LR patterning will reveal interesting new biology of wide relevance to developmental, cell, and evolutionary biology. PMID:23583583

A unified model for left-right asymmetry? Comparison and synthesis of molecular models of embryonic laterality.

PubMed

Vandenberg, Laura N; Levin, Michael

2013-07-01

Understanding how and when the left-right (LR) axis is first established is a fundamental question in developmental biology. A popular model is that the LR axis is established relatively late in embryogenesis, due to the movement of motile cilia and the resultant directed fluid flow during late gastrulation/early neurulation. Yet, a large body of evidence suggests that biophysical, molecular, and bioelectrical asymmetries exist much earlier in development, some as early as the first cell cleavage after fertilization. Alternative models of LR asymmetry have been proposed that accommodate these data, postulating that asymmetry is established due to a chiral cytoskeleton and/or the asymmetric segregation of chromatids. There are some similarities, and many differences, in how these various models postulate the origin and timing of symmetry breaking and amplification, and these events' linkage to the well-conserved subsequent asymmetric transcriptional cascades. This review examines experimental data that lend strong support to an early origin of LR asymmetry, yet are also consistent with later roles for cilia in the amplification of LR pathways. In this way, we propose that the various models of asymmetry can be unified: early events are needed to initiate LR asymmetry, and later events could be utilized by some species to maintain LR-biases. We also present an alternative hypothesis, which proposes that individual embryos stochastically choose one of several possible pathways with which to establish their LR axis. These two hypotheses are both tractable in appropriate model species; testing them to resolve open questions in the field of LR patterning will reveal interesting new biology of wide relevance to developmental, cell, and evolutionary biology. Copyright © 2013 Elsevier Inc. All rights reserved.

Inversion of left-right asymmetry alters performance of Xenopus tadpoles in nonlateralized cognitive tasks.

PubMed

Blackiston, Douglas J; Levin, Michael

2013-08-01

Left-right behavioural biases are well documented across the animal kingdom, and handedness has long been associated with cognitive performance. However, the relationship between body laterality and cognitive ability is poorly understood. The embryonic pathways dictating normal left-right patterning have been molecularly dissected in model vertebrates, and numerous genetic and pharmacological treatments now facilitate experimental randomization or reversal of the left-right axis in these animals. Several recent studies showed a link between brain asymmetry and strongly lateralized behaviours such as eye use preference. However, links between laterality of the body and performance on cognitive tasks utilizing nonlateralized cues remain unknown. Xenopus tadpoles are an established model for the study of early left-right patterning, and protocols were recently developed to quantitatively evaluate learning and memory in these animals. Using an automated testing and training platform, we tested wild-type, left-right-randomized and left-right-reversed tadpoles for their ability to learn colour cues in an automated assay. Our results indicate that animals with either randomization or reversal of somatic left-right patterning learned more slowly than wild-type siblings, although all groups were able to reach the same performance optimum given enough training sessions. These results are the first analysis of the link between body laterality and learning of nonlateralized cues, and they position the Xenopus tadpole as an attractive and tractable model for future studies of the links between asymmetry of the body, lateralization of the brain and behaviour.

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).

Image interpolation and denoising for division of focal plane sensors using Gaussian processes.

PubMed

Gilboa, Elad; Cunningham, John P; Nehorai, Arye; Gruev, Viktor

2014-06-16

Image interpolation and denoising are important techniques in image processing. These methods are inherent to digital image acquisition as most digital cameras are composed of a 2D grid of heterogeneous imaging sensors. Current polarization imaging employ four different pixelated polarization filters, commonly referred to as division of focal plane polarization sensors. The sensors capture only partial information of the true scene, leading to a loss of spatial resolution as well as inaccuracy of the captured polarization information. Interpolation is a standard technique to recover the missing information and increase the accuracy of the captured polarization information. Here we focus specifically on Gaussian process regression as a way to perform a statistical image interpolation, where estimates of sensor noise are used to improve the accuracy of the estimated pixel information. We further exploit the inherent grid structure of this data to create a fast exact algorithm that operates in ����(N(3/2)) (vs. the naive ���� (N³)), thus making the Gaussian process method computationally tractable for image data. This modeling advance and the enabling computational advance combine to produce significant improvements over previously published interpolation methods for polarimeters, which is most pronounced in cases of low signal-to-noise ratio (SNR). We provide the comprehensive mathematical model as well as experimental results of the GP interpolation performance for division of focal plane polarimeter.

The Soil Foam Drainage Equation - an alternative model for unsaturated flow in porous media

NASA Astrophysics Data System (ADS)

Assouline, Shmuel; Lehmann, Peter; Hoogland, Frouke; Or, Dani

2017-04-01

The analogy between the geometry and dynamics of wet foam drainage and gravity drainage of unsaturated porous media expands modeling capabilities for capillary flows and supplements the standard Richards equation representation. The governing equation for draining foam (or a soil variant termed the soil foam drainage equation - SFDE) obviates the need for macroscopic unsaturated hydraulic conductivity function by an explicit account of diminishing flow pathway sizes as the medium gradually drains. Potential advantages of the proposed drainage foam formalism include direct description of transient flow without requiring constitutive functions; evolution of capillary cross sections that provides consistent description of self-regulating internal fluxes (e.g., towards field capacity); and a more intuitive geometrical picture of capillary flow across textural boundaries. We will present new and simple analytical expressions for drainage rates and volumes from unsaturated porous media subjected to different boundary conditions that are in good agreement with the numerical solution of the SFDE and experimental results. The foam drainage methodology expands the range of tools available for describing and quantifying unsaturated flows and provides geometrically tractable links between evolution of liquid configuration and flow dynamics in unsaturated porous media. The resulting geometrical representation of capillary drainage could improve understanding of colloid and pathogen transport. The explicit geometrical interpretation of flow pathways underlying the hydraulic functions used by the Richards equation offers new insights that benefit both approaches.

Laminar Diffusion Flame Studies (Ground- and Space-Based Studies)

NASA Technical Reports Server (NTRS)

Dai, Z.; El-Leathy, A. M.; Lin, K.-C.; Sunderland, P. B.; Xu, F.; Faeth, G. M.; Urban, D. L. (Technical Monitor); Yuan, Z.-G. (Technical Monitor)

2000-01-01

Laminar diffusion flames are of interest because they provide model flame systems that are far more tractable for analysis and experiments than more practical turbulent diffusion flames. Certainly, understanding flame processes within laminar diffusion flames must precede understanding these processes in more complex turbulent diffusion flames. In addition, many properties of laminar diffusion flames are directly relevant to turbulent diffusion flames using laminar flamelet concepts. Laminar jet diffusion flame shapes (luminous flame boundaries) have been of particular interest since the classical study of Burke and Schumann because they are a simple nonintrusive measurement that is convenient for evaluating flame structure predictions. Thus, consideration of laminar flame shapes is undertaken in the following, emphasizing conditions where effects of gravity are small, due to the importance of such conditions to practical applications. Another class of interesting properties of laminar diffusion flames are their laminar soot and smoke point properties (i.e., the flame length, fuel flow rate, characteristic residence time, etc., at the onset of soot appearance in the flame (the soot point) and the onset of soot emissions from the flame (the smoke point)). These are useful observable soot properties of nonpremixed flames because they provide a convenient means to rate several aspects of flame sooting properties: the relative propensity of various fuels to produce soot in flames; the relative effects of fuel structure, fuel dilution, flame temperature and ambient pressure on the soot appearance and emission properties of flames; the relative levels of continuum radiation from soot in flames; and effects of the intrusion of gravity (or buoyant motion) on emissions of soot from flames. An important motivation to define conditions for soot emissions is that observations of laminar jet diffusion flames in critical environments, e.g., space shuttle and space station facilities, cannot involve soot emitting flames in order to ensure that test chamber windows used for experimental observations are not blocked by soot deposits, thereby compromising unusually valuable experimental results. Another important motivation to define conditions where soot is present in diffusion flames is that flame chemistry, transport and radiation properties are vastly simplified when soot is absent, making such flames far more tractable for detailed numerical simulations than corresponding soot-containing flames. Motivated by these observations, the objectives of this phase of the investigation were as follows: (1) Observe flame-sheet shapes (the location of the reaction zone near phi=1) of nonluminous (soot free) laminar jet diffusion flames in both still and coflowing air and use these results to develop simplified models of flame-sheet shapes for these conditions; (2) Observe luminous flame boundaries of luminous (soot-containing) laminar jet diffusion flames in both still and coflowing air and use these results to develop simplified models of luminous flame boundaries for these conditions. In order to fix ideas here, maximum luminous flame boundaries at the laminar smoke point conditions were sought, i.e., luminous flame boundaries at the laminar smoke point; (3) Observe effects of coflow on laminar soot- and smoke-point conditions because coflow has been proposed as a means to control soot emissions and minimize the presence of soot in diffusion flames.

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

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.

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.

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

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.

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.

Susceptibility and antibody response of the laboratory model zebra finch (Taeniopygia guttata) to West Nile Virus

USGS Publications Warehouse

Hofmeister, Erik K.; Lund, Melissa; Shearn-Bochsler, Valerie I.; Balakrishnan, Christopher N.

2017-01-01

Since the introduction of West Nile virus (WNV) into North America in 1999 a number of passerine bird species have been found to play a role in the amplification of the virus. Arbovirus surveillance, observational studies and experimental studies have implicated passerine birds (songbirds, e.g., crows, American robins, house sparrows, and house finches) as significant reservoirs of WNV in North America, yet we lack a tractable passerine animal model for controlled studies of the virus. The zebra finch (Taeniopygia guttata) serves as a model system across a diversity of fields, and here we develop the zebra finch a songbird model for WNV. Like many natural hosts of WNV, we found that zebra finches developed sufficient viremia to serve as a competent host, yet in general resisted mortality from infection. In the Australian zebra finch (AZF) T. g. castanotis, we detected WNV in the majority of sampled tissues by 4 days post injection (dpi). However, WNV was not detected in tissues of sacrificed birds at 14 dpi, shortly after the development of detectable anti-WNV antibodies in the majority of birds indicating successful viral clearance. We compared susceptibility between the two zebra finch subspecies AZF and Timor zebra finch (TZF) T. g. guttata. Compared to AZF, WNV RNA was detected in a larger proportion of challenged TZF and molecular detection of virus in the serum of TZF was significantly higher than in AZF. Given the observed moderate host competence and disease susceptibility, we suggest that zebra finches are appropriate as models for the study of WNV and although underutilized in this respect, may be ideal models for the study of the many diseases carried and transmitted by songbirds.

A PDX/organoid biobank of advanced prostate cancers captures genomic and phenotypic heterogeneity for disease modeling and therapeutic screening.

PubMed

Beshiri, Michael L; Tice, Caitlin M; Tran, Crystal; Nguyen, Holly M; Sowalsky, Adam G; Agarwal, Supreet; Jansson, Keith H; Yang, Qi; McGowen, Kerry A; Yin, Juan Juan; Alilin, Aian Neil; Karzai, Fatima H; Dahut, William; Corey, Eva; Kelly, Kathleen

2018-05-10

Prostate cancer translational research has been hampered by the lack of comprehensive and tractable models   that represent the genomic landscape of clinical disease. Metastatic castrate-resistant prostate cancer (mCRPC) patient-derived xenografts (PDXs) recapitulate the genetic and phenotypic diversity of the disease. We sought to establish a representative, preclinical platform of PDX-derived organoids that is experimentally facile for high throughput and mechanistic analysis. Using 20 models from the LuCaP mCRPC PDX cohort, including adenocarcinoma and neuroendocrine lineages, we systematically tested > 20 modifications to prostate organoid conditions. Organoids were evaluated for genomic and phenotypic stability and continued reliance on the AR signaling pathway. The utility of the platform as a genotype-dependent model of drug sensitivity was tested with olaparib and carboplatin. All PDX models proliferated as organoids in culture. Greater than fifty percent could be continuously cultured long-term in modified conditions; however, none of the PDXs could be established long-term as organoids under previously-reported conditions. Additionally, the modified conditions improved the establishment of patient biopsies over current methods. The genomic heterogeneity of the PDXs, was conserved in organoids. Lineage markers and transcriptomes were maintained between PDXs and organoids. Dependence on AR signaling, was preserved in adenocarcinoma organoids, replicating a dominant characteristic of CRPC. Finally, we observed maximum cytotoxicity to the PARP inhibitor olaparib in BRCA2 -/- organoids, similar to responses observed in patients. The LuCaP PDX/organoid models provide an expansive, genetically-characterized platform to investigate mechanisms of pathogenesis as well as therapeutic responses and their molecular correlates in mCRPC. Copyright ©2018, American Association for Cancer Research.

Fragment-based drug design.

PubMed

Feyfant, Eric; Cross, Jason B; Paris, Kevin; Tsao, Désirée H H

2011-01-01

Fragment-based drug design (FBDD), which is comprised of both fragment screening and the use of fragment hits to design leads, began more than 15 years ago and has been steadily gaining in popularity and utility. Its origin lies on the fact that the coverage of chemical space and the binding efficiency of hits are directly related to the size of the compounds screened. Nevertheless, FBDD still faces challenges, among them developing fragment screening libraries that ensure optimal coverage of chemical space, physical properties and chemical tractability. Fragment screening also requires sensitive assays, often biophysical in nature, to detect weak binders. In this chapter we will introduce the technologies used to address these challenges and outline the experimental advantages that make FBDD one of the most popular new hit-to-lead process.

Design and Implementation of Secure and Reliable Communication using Optical Wireless Communication

NASA Astrophysics Data System (ADS)

Saadi, Muhammad; Bajpai, Ambar; Zhao, Yan; Sangwongngam, Paramin; Wuttisittikulkij, Lunchakorn

2014-11-01

Wireless networking intensify the tractability in the home and office environment to connect the internet without wires but at the cost of risks associated with stealing the data or threat of loading malicious code with the intention of harming the network. In this paper, we proposed a novel method of establishing a secure and reliable communication link using optical wireless communication (OWC). For security, spatial diversity based transmission using two optical transmitters is used and the reliability in the link is achieved by a newly proposed method for the construction of structured parity check matrix for binary Low Density Parity Check (LDPC) codes. Experimental results show that a successful secure and reliable link between the transmitter and the receiver can be achieved by using the proposed novel technique.

A Scalable Nonuniform Pointer Analysis for Embedded Program

NASA Technical Reports Server (NTRS)

Venet, Arnaud

2004-01-01

In this paper we present a scalable pointer analysis for embedded applications that is able to distinguish between instances of recursively defined data structures and elements of arrays. The main contribution consists of an efficient yet precise algorithm that can handle multithreaded programs. We first perform an inexpensive flow-sensitive analysis of each function in the program that generates semantic equations describing the effect of the function on the memory graph. These equations bear numerical constraints that describe nonuniform points-to relationships. We then iteratively solve these equations in order to obtain an abstract storage graph that describes the shape of data structures at every point of the program for all possible thread interleavings. We bring experimental evidence that this approach is tractable and precise for real-size embedded applications.

The native microbiome of the nematode Caenorhabditis elegans: gateway to a new host-microbiome model.

PubMed

Dirksen, Philipp; Marsh, Sarah Arnaud; Braker, Ines; Heitland, Nele; Wagner, Sophia; Nakad, Rania; Mader, Sebastian; Petersen, Carola; Kowallik, Vienna; Rosenstiel, Philip; Félix, Marie-Anne; Schulenburg, Hinrich

2016-05-09

Host-microbe associations underlie many key processes of host development, immunity, and life history. Yet, none of the current research on the central model species Caenorhabditis elegans considers the worm's natural microbiome. Instead, almost all laboratories exclusively use the canonical strain N2 and derived mutants, maintained through routine bleach sterilization in monoxenic cultures with an E. coli strain as food. Here, we characterize for the first time the native microbiome of C. elegans and assess its influence on nematode life history characteristics. Nematodes sampled directly from their native habitats carry a species-rich bacterial community, dominated by Proteobacteria such as Enterobacteriaceae and members of the genera Pseudomonas, Stenotrophomonas, Ochrobactrum, and Sphingomonas. The C. elegans microbiome is distinct from that of the worm's natural environment and the congeneric species C. remanei. Exposure to a derived experimental microbiome revealed that bacterial composition is influenced by host developmental stage and genotype. These experiments also showed that the microbes enhance host fitness under standard and also stressful conditions (e.g., high temperature and either low or high osmolarity). Taking advantage of the nematode's transparency, we further demonstrate that several Proteobacteria are able to enter the C. elegans gut and that an Ochrobactrum isolate even seems to be able to persist in the intestines under stressful conditions. Moreover, three Pseudomonas isolates produce an anti-fungal effect in vitro which we show can contribute to the worm's defense against fungal pathogens in vivo. This first systematic analysis of the nematode's native microbiome reveals a species-rich bacterial community to be associated with C. elegans, which is likely of central importance for our understanding of the worm's biology. The information acquired and the microbial isolates now available for experimental work establishes C. elegans as a tractable model for the in-depth dissection of host-microbiome interactions.

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.

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

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.

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.

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.

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.

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.

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.

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.

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

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

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.

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.

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

A New Distance Metric for Unsupervised Learning of Categorical Data.

PubMed

Jia, Hong; Cheung, Yiu-Ming; Liu, Jiming

2016-05-01

Distance metric is the basis of many learning algorithms, and its effectiveness usually has a significant influence on the learning results. In general, measuring distance for numerical data is a tractable task, but it could be a nontrivial problem for categorical data sets. This paper, therefore, presents a new distance metric for categorical data based on the characteristics of categorical values. In particular, the distance between two values from one attribute measured by this metric is determined by both the frequency probabilities of these two values and the values of other attributes that have high interdependence with the calculated one. Dynamic attribute weight is further designed to adjust the contribution of each attribute-distance to the distance between the whole data objects. Promising experimental results on different real data sets have shown the effectiveness of the proposed distance metric.

Primary Characterization of Small RNAs in Symbiotic Nitrogen-Fixing Bacteria.

PubMed

Robledo, Marta; García-Tomsig, Natalia I; Jiménez-Zurdo, José I

2018-01-01

High-throughput transcriptome profiling (RNAseq) has uncovered large and heterogeneous populations of small noncoding RNA species (sRNAs) with potential regulatory roles in bacteria. A large fraction of sRNAs are differentially regulated and rely on protein-assisted antisense interactions to trans-encoded target mRNAs to fine-tune posttranscriptional reprogramming of gene expression in response to external cues. However, annotation and function of sRNAs are still largely overlooked in nonmodel bacteria with complex lifestyles. Here, we describe experimental protocols successfully applied for the accurate annotation, expression profiling and target mRNA identification of trans-acting sRNAs in the nitrogen-fixing α-rhizobium Sinorhizobium meliloti. The protocols presented here can be similarly applied for the characterization of trans-sRNAs in genetically tractable α-proteobacteria of agronomical or clinical relevance interacting with eukaryotic hosts.

Cryptic binding sites on proteins: definition, detection, and druggability.

PubMed

Vajda, Sandor; Beglov, Dmitri; Wakefield, Amanda E; Egbert, Megan; Whitty, Adrian

2018-05-22

Many proteins in their unbound structures lack surface pockets appropriately sized for drug binding. Hence, a variety of experimental and computational tools have been developed for the identification of cryptic sites that are not evident in the unbound protein but form upon ligand binding, and can provide tractable drug target sites. The goal of this review is to discuss the definition, detection, and druggability of such sites, and their potential value for drug discovery. Novel methods based on molecular dynamics simulations are particularly promising and yield a large number of transient pockets, but it has been shown that only a minority of such sites are generally capable of binding ligands with substantial affinity. Based on recent studies, current methodology can be improved by combining molecular dynamics with fragment docking and machine learning approaches. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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

Nematode-bacterium symbioses--cooperation and conflict revealed in the "omics" age.

PubMed

Murfin, Kristen E; Dillman, Adler R; Foster, Jeremy M; Bulgheresi, Silvia; Slatko, Barton E; Sternberg, Paul W; Goodrich-Blair, Heidi

2012-08-01

Nematodes are ubiquitous organisms that have a significant global impact on ecosystems, economies, agriculture, and human health. The applied importance of nematodes and the experimental tractability of many species have promoted their use as models in various research areas, including developmental biology, evolutionary biology, ecology, and animal-bacterium interactions. Nematodes are particularly well suited for the investigation of host associations with bacteria because all nematodes have interacted with bacteria during their evolutionary history and engage in a variety of association types. Interactions between nematodes and bacteria can be positive (mutualistic) or negative (pathogenic/parasitic) and may be transient or stably maintained (symbiotic). Furthermore, since many mechanistic aspects of nematode-bacterium interactions are conserved, their study can provide broader insights into other types of associations, including those relevant to human diseases. Recently, genome-scale studies have been applied to diverse nematode-bacterial interactions and have helped reveal mechanisms of communication and exchange between the associated partners. In addition to providing specific information about the system under investigation, these studies also have helped inform our understanding of genome evolution, mutualism, and innate immunity. In this review we discuss the importance and diversity of nematodes, "omics"' studies in nematode-bacterial systems, and the wider implications of the findings.

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.

Nonparametric density estimation and optimal bandwidth selection for protein unfolding and unbinding data

NASA Astrophysics Data System (ADS)

Bura, E.; Zhmurov, A.; Barsegov, V.

2009-01-01

Dynamic force spectroscopy and steered molecular simulations have become powerful tools for analyzing the mechanical properties of proteins, and the strength of protein-protein complexes and aggregates. Probability density functions of the unfolding forces and unfolding times for proteins, and rupture forces and bond lifetimes for protein-protein complexes allow quantification of the forced unfolding and unbinding transitions, and mapping the biomolecular free energy landscape. The inference of the unknown probability distribution functions from the experimental and simulated forced unfolding and unbinding data, as well as the assessment of analytically tractable models of the protein unfolding and unbinding requires the use of a bandwidth. The choice of this quantity is typically subjective as it draws heavily on the investigator's intuition and past experience. We describe several approaches for selecting the "optimal bandwidth" for nonparametric density estimators, such as the traditionally used histogram and the more advanced kernel density estimators. The performance of these methods is tested on unimodal and multimodal skewed, long-tailed distributed data, as typically observed in force spectroscopy experiments and in molecular pulling simulations. The results of these studies can serve as a guideline for selecting the optimal bandwidth to resolve the underlying distributions from the forced unfolding and unbinding data for proteins.

Constraint-based Temporal Reasoning with Preferences

NASA Technical Reports Server (NTRS)

Khatib, Lina; Morris, Paul; Morris, Robert; Rossi, Francesca; Sperduti, Alessandro; Venable, K. Brent

2005-01-01

Often we need to work in scenarios where events happen over time and preferences are associated to event distances and durations. Soft temporal constraints allow one to describe in a natural way problems arising in such scenarios. In general, solving soft temporal problems require exponential time in the worst case, but there are interesting subclasses of problems which are polynomially solvable. In this paper we identify one of such subclasses giving tractability results. Moreover, we describe two solvers for this class of soft temporal problems, and we show some experimental results. The random generator used to build the problems on which tests are performed is also described. We also compare the two solvers highlighting the tradeoff between performance and robustness. Sometimes, however, temporal local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. To model everything in a uniform way via local preferences only, and also to take advantage of the existing constraint solvers which exploit only local preferences, we show that machine learning techniques can be useful in this respect. In particular, we present a learning module based on a gradient descent technique which induces local temporal preferences from global ones. We also show the behavior of the learning module on randomly-generated examples.

Topics in electron capture by fast ions

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

Hsin, S.H.

1987-01-01

The post-collision interaction (PCI) model was applied, together with the eikonal approximation, to study the (n = 2,3) capture cross sections in p + H(ls) collisions. The results indeed improve the previous eikonal calculations for l = 0 cases, and agree quite well with present experimental data. Calculations using the strong-potential Born (SPB) approximation, with the Sil and McGuire technique, for capture into the np, nd levels are also presented. While these cross sections are smaller than cross sections for capture into the ns levels at high velocities, nevertheless the Thomas peak is clearly evident in both the absolute valuemore » m = 2, absolute value m = 1 and m = 0 magnetic substates in p + H(ls) collisions. Also calculated were corrections to the SPB using the Distorted-Wave Born formalism of Taulbjerg and Briggs. In the sense of a plane-wave Born expansion, all terms of the third Born approximation and all single switching fourth Born terms are included, but a peaking approximation is needed to reduce the calculation to tractable form. Effects of the higher terms are most visible in the valley between the Thomas peak and the forward peak. The Thomas peak is visible in the correction term, even though it includes no second Born contributions.« less

Structural insights into binding of small molecule inhibitors to Enhancer of Zeste Homolog 2

NASA Astrophysics Data System (ADS)

Kalinić, Marko; Zloh, Mire; Erić, Slavica

2014-11-01

Enhancer of Zeste Homolog 2 (EZH2) is a SET domain protein lysine methyltransferase (PKMT) which has recently emerged as a chemically tractable and therapeutically promising epigenetic target, evidenced by the discovery and characterization of potent and highly selective EZH2 inhibitors. However, no experimental structures of the inhibitors co-crystallized to EZH2 have been resolved, and the structural basis for their activity and selectivity remains unknown. Considering the need to minimize cross-reactivity between prospective PKMT inhibitors, much can be learned from understanding the molecular basis for selective inhibition of EZH2. Thus, to elucidate the binding of small-molecule inhibitors to EZH2, we have developed a model of its fully-formed cofactor binding site and used it to carry out molecular dynamics simulations of protein-ligand complexes, followed by molecular mechanics/generalized born surface area calculations. The obtained results are in good agreement with biochemical inhibition data and reflect the structure-activity relationships of known ligands. Our findings suggest that the variable and flexible post-SET domain plays an important role in inhibitor binding, allowing possibly distinct binding modes of inhibitors with only small variations in their structure. Insights from this study present a good basis for design of novel and optimization of existing compounds targeting the cofactor binding site of EZH2.

Nematode-Bacterium Symbioses - Cooperation and Conflict Revealed in the 'Omics' Age

PubMed Central

Murfin, Kristen E.; Dillman, Adler R.; Foster, Jeremy M.; Bulgheresi, Silvia; Slatko, Barton E.; Sternberg, Paul W.; Goodrich-Blair, Heidi

2012-01-01

Nematodes are ubiquitous organisms that have a significant global impact on ecosystems, economies, agriculture, and human health. The applied importance of nematodes and the experimental tractability of many species have promoted their use as models in various research areas, including developmental biology, evolutionary biology, ecology, and animal-bacterium interactions. Nematodes are particularly well suited for investigating host associations with bacteria because all nematodes have interacted with bacteria during their evolutionary history and engage in a diversity of association types. Interactions between nematodes and bacteria can be positive (mutualistic) or negative (pathogenic/parasitic) and may be transient or stably maintained (symbiotic). Furthermore, since many mechanistic aspects of nematode-bacterium interactions are conserved their study can provide broader insights into other types of associations, including those relevant to human diseases. Recently, genome-scale studies have been applied to diverse nematode-bacterial interactions, and have helped reveal mechanisms of communication and exchange between the associated partners. In addition to providing specific information about the system under investigation, these studies also have helped inform our understanding of genome evolution, mutualism, and innate immunity. In this review we will discuss the importance and diversity of nematodes, 'omics' studies in nematode-bacterial systems, and the wider implications of the findings. PMID:22983035

A study of hadronic decays of the chi(c) states produced in psi-prime radiative transitions at the Beijing Experimental Spectrometer

NASA Astrophysics Data System (ADS)

Varner, Gary Sim

1999-11-01

Utilizing the world's largest sample of resonant y' decays, as measured by the Beijing Experimental Spectrometer (BES) during 1993-1995, a comprehensive study of the hadronic decay modes of the χc (3P1 Charmonium) states has been undertaken. Compared with the data set for the Mark I detector, whose published measurements of many of these hadronic decays have been definitive for almost 20 years, roughly an order of magnitude larger statistics has been obtained. Taking advantage of these larger statistics, many new hadronic decay modes have been discovered, while others have been refined. An array of first observations, improvements, confirmations or limits are reported with respect to current world values. These higher precision and newly discovered decay modes are an excellent testing ground for recent theoretical interest in the contribution of higher Fock states and the color octet mechanism in heavy quarkonium annihilation and subsequent light hadronization. Because these calculations are largely tractable only in two body decays, these are the focus of this dissertation. A comparison of current theoretical calculations and experimental results is presented, indicating the success of these phenomenological advances. Measurements for which there are as yet no suitable theoretical prediction are indicated.

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

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.

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

The blastema and epimorphic regeneration in mammals.

PubMed

Seifert, Ashley W; Muneoka, Ken

2018-01-15

Studying regeneration in animals where and when it occurs is inherently interesting and a challenging research topic within developmental biology. Historically, vertebrate regeneration has been investigated in animals that display enhanced regenerative abilities and we have learned much from studying organ regeneration in amphibians and fish. From an applied perspective, while regeneration biologists will undoubtedly continue to study poikilothermic animals (i.e., amphibians and fish), studies focused on homeotherms (i.e., mammals and birds) are also necessary to advance regeneration biology. Emerging mammalian models of epimorphic regeneration are poised to help link regenerative biology and regenerative medicine. The regenerating rodent digit tip, which parallels human fingertip regeneration, and the regeneration of large circular defects through the ear pinna in spiny mice and rabbits, provide tractable, experimental systems where complex tissue structures are regrown through blastema formation and morphogenesis. Using these models as examples, we detail similarities and differences between the mammalian blastema and its classical counterpart to arrive at a broad working definition of a vertebrate regeneration blastema. This comparison leads us to conclude that regenerative failure is not related to the availability of regeneration-competent progenitor cells, but is most likely a function of the cellular response to the microenvironment that forms following traumatic injury. Recent studies demonstrating that targeted modification of this microenvironment can restrict or enhance regenerative capabilities in mammals helps provide a roadmap for eventually pushing the limits of human regeneration. Copyright © 2017 Elsevier Inc. All rights reserved.

Genetic modification of the diarrhoeal pathogen Cryptosporidium parvum.

PubMed

Vinayak, Sumiti; Pawlowic, Mattie C; Sateriale, Adam; Brooks, Carrie F; Studstill, Caleb J; Bar-Peled, Yael; Cipriano, Michael J; Striepen, Boris

2015-07-23

Recent studies into the global causes of severe diarrhoea in young children have identified the protozoan parasite Cryptosporidium as the second most important diarrhoeal pathogen after rotavirus. Diarrhoeal disease is estimated to be responsible for 10.5% of overall child mortality. Cryptosporidium is also an opportunistic pathogen in the contexts of human immunodeficiency virus (HIV)-caused AIDS and organ transplantation. There is no vaccine and only a single approved drug that provides no benefit for those in gravest danger: malnourished children and immunocompromised patients. Cryptosporidiosis drug and vaccine development is limited by the poor tractability of the parasite, which includes a lack of systems for continuous culture, facile animal models, and molecular genetic tools. Here we describe an experimental framework to genetically modify this important human pathogen. We established and optimized transfection of C. parvum sporozoites in tissue culture. To isolate stable transgenics we developed a mouse model that delivers sporozoites directly into the intestine, a Cryptosporidium clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 system, and in vivo selection for aminoglycoside resistance. We derived reporter parasites suitable for in vitro and in vivo drug screening, and we evaluated the basis of drug susceptibility by gene knockout. We anticipate that the ability to genetically engineer this parasite will be transformative for Cryptosporidium research. Genetic reporters will provide quantitative correlates for disease, cure and protection, and the role of parasite genes in these processes is now open to rigorous investigation.

Complex computation in the retina

NASA Astrophysics Data System (ADS)

Deshmukh, Nikhil Rajiv

Elucidating the general principles of computation in neural circuits is a difficult problem requiring both a tractable model circuit as well as sophisticated measurement tools. This thesis advances our understanding of complex computation in the salamander retina and its underlying circuitry and furthers the development of advanced tools to enable detailed study of neural circuits. The retina provides an ideal model system for neural circuits in general because it is capable of producing complex representations of the visual scene, and both its inputs and outputs are accessible to the experimenter. Chapter 2 describes the biophysical mechanisms that give rise to the omitted stimulus response in retinal ganglion cells described in Schwartz et al., (2007) and Schwartz and Berry, (2008). The extra response to omitted flashes is generated at the input to bipolar cells, and is separable from the characteristic latency shift of the OSR apparent in ganglion cells, which must occur downstream in the circuit. Chapter 3 characterizes the nonlinearities at the first synapse of the ON pathway in response to high contrast flashes and develops a phenomenological model that captures the effect of synaptic activation and intracellular signaling dynamics on flash responses. This work is the first attempt to model the dynamics of the poorly characterized mGluR6 transduction cascade unique to ON bipolar cells, and explains the second lobe of the biphasic flash response. Complementary to the study of neural circuits, recent advances in wafer-scale photolithography have made possible new devices to measure the electrical and mechanical properties of neurons. Chapter 4 reports a novel piezoelectric sensor that facilitates the simultaneous measurement of electrical and mechanical signals in neural tissue. This technology could reveal the relationship between the electrical activity of neurons and their local mechanical environment, which is critical to the study of mechanoreceptors, neural development, and traumatic brain injury. Chapter 5 describes advances in the development, fabrication, and testing of a prototype silicon micropipette for patch clamp physiology. Nanoscale photolithography addresses some of the limitations of traditional glass patch electrodes, such as the rapid dialysis of the cell with internal solution, and provides a platform for integration of microfluidics and electronics into the device, which can enable novel experimental methodology.

Explaining evolution via constrained persistent perfect phylogeny

PubMed Central

2014-01-01

Background The perfect phylogeny is an often used model in phylogenetics since it provides an efficient basic procedure for representing the evolution of genomic binary characters in several frameworks, such as for example in haplotype inference. The model, which is conceptually the simplest, is based on the infinite sites assumption, that is no character can mutate more than once in the whole tree. A main open problem regarding the model is finding generalizations that retain the computational tractability of the original model but are more flexible in modeling biological data when the infinite site assumption is violated because of e.g. back mutations. A special case of back mutations that has been considered in the study of the evolution of protein domains (where a domain is acquired and then lost) is persistency, that is the fact that a character is allowed to return back to the ancestral state. In this model characters can be gained and lost at most once. In this paper we consider the computational problem of explaining binary data by the Persistent Perfect Phylogeny model (referred as PPP) and for this purpose we investigate the problem of reconstructing an evolution where some constraints are imposed on the paths of the tree. Results We define a natural generalization of the PPP problem obtained by requiring that for some pairs (character, species), neither the species nor any of its ancestors can have the character. In other words, some characters cannot be persistent for some species. This new problem is called Constrained PPP (CPPP). Based on a graph formulation of the CPPP problem, we are able to provide a polynomial time solution for the CPPP problem for matrices whose conflict graph has no edges. Using this result, we develop a parameterized algorithm for solving the CPPP problem where the parameter is the number of characters. Conclusions A preliminary experimental analysis shows that the constrained persistent perfect phylogeny model allows to explain efficiently data that do not conform with the classical perfect phylogeny model. PMID:25572381

Quasi-laminar stability and sensitivity analyses for turbulent flows: Prediction of low-frequency unsteadiness and passive control

NASA Astrophysics Data System (ADS)

Mettot, Clément; Sipp, Denis; Bézard, Hervé

2014-04-01

This article presents a quasi-laminar stability approach to identify in high-Reynolds number flows the dominant low-frequencies and to design passive control means to shift these frequencies. The approach is based on a global linear stability analysis of mean-flows, which correspond to the time-average of the unsteady flows. Contrary to the previous work by Meliga et al. ["Sensitivity of 2-D turbulent flow past a D-shaped cylinder using global stability," Phys. Fluids 24, 061701 (2012)], we use the linearized Navier-Stokes equations based solely on the molecular viscosity (leaving aside any turbulence model and any eddy viscosity) to extract the least stable direct and adjoint global modes of the flow. Then, we compute the frequency sensitivity maps of these modes, so as to predict before hand where a small control cylinder optimally shifts the frequency of the flow. In the case of the D-shaped cylinder studied by Parezanović and Cadot [J. Fluid Mech. 693, 115 (2012)], we show that the present approach well captures the frequency of the flow and recovers accurately the frequency control maps obtained experimentally. The results are close to those already obtained by Meliga et al., who used a more complex approach in which turbulence models played a central role. The present approach is simpler and may be applied to a broader range of flows since it is tractable as soon as mean-flows — which can be obtained either numerically from simulations (Direct Numerical Simulation (DNS), Large Eddy Simulation (LES), unsteady Reynolds-Averaged-Navier-Stokes (RANS), steady RANS) or from experimental measurements (Particle Image Velocimetry - PIV) — are available. We also discuss how the influence of the control cylinder on the mean-flow may be more accurately predicted by determining an eddy-viscosity from numerical simulations or experimental measurements. From a technical point of view, we finally show how an existing compressible numerical simulation code may be used in a black-box manner to extract the global modes and sensitivity maps.

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.

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.

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.

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.

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%.

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.

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.

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.

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.

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.

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.

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.

Practical Bayesian tomography

NASA Astrophysics Data System (ADS)

Granade, Christopher; Combes, Joshua; Cory, D. G.

2016-03-01

In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of-the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we address all three problems. First, we use modern statistical methods, as pioneered by Huszár and Houlsby (2012 Phys. Rev. A 85 052120) and by Ferrie (2014 New J. Phys. 16 093035), to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first priors on quantum states and channels that allow for including useful experimental insight. Finally, we develop a method that allows tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.

Invertebrate biomechanics.

PubMed

Patek, S N; Summers, A P

2017-05-22

Invertebrate biomechanics focuses on mechanical analyses of non-vertebrate animals, which at root is no different in aim and technique from vertebrate biomechanics, or for that matter the biomechanics of plants and fungi. But invertebrates are special - they are fabulously diverse in form, habitat, and ecology and manage this without the use of hard, internal skeletons. They are also numerous and, in many cases, tractable in an experimental and field setting. In this Primer, we will probe three axes of invertebrate diversity: worms (Phylum Annelida), spiders (Class Arachnida) and insects (Class Insecta); three habitats: subterranean, terrestrial and airborne; and three integrations with other fields: ecology, engineering and evolution. Our goal is to capture the field of invertebrate biomechanics, which has blossomed from having a primary focus on discoveries at the interface of physics and biology to being inextricably linked with integrative challenges that span biology, physics, mathematics and engineering. Copyright © 2017 Elsevier Ltd. All rights reserved.

Proteins of Unknown Biochemical Function: A Persistent Problem and a Roadmap to Help Overcome It.

PubMed

Niehaus, Thomas D; Thamm, Antje M K; de Crécy-Lagard, Valérie; Hanson, Andrew D

2015-11-01

The number of sequenced genomes is rapidly increasing, but functional annotation of the genes in these genomes lags far behind. Even in Arabidopsis (Arabidopsis thaliana), only approximately 40% of enzyme- and transporter-encoding genes have credible functional annotations, and this number is even lower in nonmodel plants. Functional characterization of unknown genes is a challenge, but various databases (e.g. for protein localization and coexpression) can be mined to provide clues. If homologous microbial genes exist-and about one-half the genes encoding unknown enzymes and transporters in Arabidopsis have microbial homologs-cross-kingdom comparative genomics can powerfully complement plant-based data. Multiple lines of evidence can strengthen predictions and warrant experimental characterization. In some cases, relatively quick tests in genetically tractable microbes can determine whether a prediction merits biochemical validation, which is costly and demands specialized skills. © 2015 American Society of Plant Biologists. All Rights Reserved.

Oxytocin mediated behavior in invertebrates: An evolutionary perspective.

PubMed

Lockard, Meghan A; Ebert, Margaret S; Bargmann, Cornelia I

2017-02-01

The molecular and functional conservation of oxytocin-related neuropeptides in behavior is striking. In animals separated by at least 600 million years of evolution, from roundworms to humans, oxytocin homologs play critical roles in the modulation of reproductive behavior and other biological functions. Here, we review the roles of oxytocin in invertebrate behavior from an evolutionary perspective. We begin by tracing the evolution of oxytocin through the invertebrate animal lineages, and then describe common themes in invertebrate behaviors that are mediated by oxytocin-related peptides, including reproductive behavior, learning and memory, food arousal, and predator/prey relationships. Finally, we discuss interesting future directions that have recently become experimentally tractable. Studying oxytocin in invertebrates offers precise insights into the activity of neuropeptides on well-defined neural circuits; the principles that emerge may also be represented in the more complex vertebrate brain. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 128-142, 2017. © 2016 Wiley Periodicals, Inc.

Efficient estimation of the maximum metabolic productivity of batch systems

DOE PAGES

St. John, Peter C.; Crowley, Michael F.; Bomble, Yannick J.

2017-01-31

Production of chemicals from engineered organisms in a batch culture involves an inherent trade-off between productivity, yield, and titer. Existing strategies for strain design typically focus on designing mutations that achieve the highest yield possible while maintaining growth viability. While these methods are computationally tractable, an optimum productivity could be achieved by a dynamic strategy in which the intracellular division of resources is permitted to change with time. New methods for the design and implementation of dynamic microbial processes, both computational and experimental, have therefore been explored to maximize productivity. However, solving for the optimal metabolic behavior under the assumptionmore » that all fluxes in the cell are free to vary is a challenging numerical task. Here, previous studies have therefore typically focused on simpler strategies that are more feasible to implement in practice, such as the time-dependent control of a single flux or control variable.« less

Establishing Causality: Opportunities of Synthetic Communities for Plant Microbiome Research.

PubMed

Vorholt, Julia A; Vogel, Christine; Carlström, Charlotte I; Müller, Daniel B

2017-08-09

Plant microbiome research highlights the importance of indigenous microbial communities for host phenotypes such as growth and health. It aims to discover the molecular basis by which host-microbe and microbe-microbe interactions shape and maintain microbial communities and to understand the role of individual microorganisms, as well as their collective ecosystem function. Here, we discuss reductionist approaches to disentangle the inherent complexity of interactions in situ. Experimentally tractable, synthetic communities enable testing of hypotheses by targeted manipulation in gnotobiotic systems. Modifications of microbial, host, and environmental parameters allow for the quantitative assessment of host and microbe characteristics with dynamic and spatial resolution. We summarize first insights from this emerging field and discuss current challenges and limitations. Using multifaceted approaches to detect interactions and functions will provide new insights into the fundamental biology of plant-microbe interactions and help to harness the power of the microbiome. Copyright © 2017 Elsevier Inc. All rights reserved.

Image restoration for three-dimensional fluorescence microscopy using an orthonormal basis for efficient representation of depth-variant point-spread functions

PubMed Central

Patwary, Nurmohammed; Preza, Chrysanthe

2015-01-01

A depth-variant (DV) image restoration algorithm for wide field fluorescence microscopy, using an orthonormal basis decomposition of DV point-spread functions (PSFs), is investigated in this study. The efficient PSF representation is based on a previously developed principal component analysis (PCA), which is computationally intensive. We present an approach developed to reduce the number of DV PSFs required for the PCA computation, thereby making the PCA-based approach computationally tractable for thick samples. Restoration results from both synthetic and experimental images show consistency and that the proposed algorithm addresses efficiently depth-induced aberration using a small number of principal components. Comparison of the PCA-based algorithm with a previously-developed strata-based DV restoration algorithm demonstrates that the proposed method improves performance by 50% in terms of accuracy and simultaneously reduces the processing time by 64% using comparable computational resources. PMID:26504634

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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

Oceans of opportunity: exploring vertebrate hematopoiesis in zebrafish.

PubMed

Carroll, Kelli J; North, Trista E

2014-08-01

Exploitation of the zebrafish model in hematology research has surged in recent years, becoming one of the most useful and tractable systems for understanding regulation of hematopoietic development, homeostasis, and malignancy. Despite the evolutionary distance between zebrafish and humans, remarkable genetic and phenotypic conservation in the hematopoietic system has enabled significant advancements in our understanding of blood stem and progenitor cell biology. The strengths of zebrafish in hematology research lie in the ability to perform real-time in vivo observations of hematopoietic stem, progenitor, and effector cell emergence, expansion, and function, as well as the ease with which novel genetic and chemical modifiers of specific hematopoietic processes or cell types can be identified and characterized. Further, myriad transgenic lines have been developed including fluorescent reporter systems to aid in the visualization and quantification of specified cell types of interest and cell-lineage relationships, as well as effector lines that can be used to implement a wide range of experimental manipulations. As our understanding of the complex nature of blood stem and progenitor cell biology during development, in response to infection or injury, or in the setting of hematologic malignancy continues to deepen, zebrafish will remain essential for exploring the spatiotemporal organization and integration of these fundamental processes, as well as the identification of efficacious small molecule modifiers of hematopoietic activity. In this review, we discuss the biology of the zebrafish hematopoietic system, including similarities and differences from mammals, and highlight important tools currently utilized in zebrafish embryos and adults to enhance our understanding of vertebrate hematology, with emphasis on findings that have impacted our understanding of the onset or treatment of human hematologic disorders and disease. Copyright © 2014 ISEH - International Society for Experimental Hematology. Published by Elsevier Inc. All rights reserved.

Inelastic cross sections for low-energy electrons in liquid water: exchange and correlation effects.

PubMed

Emfietzoglou, Dimitris; Kyriakou, Ioanna; Garcia-Molina, Rafael; Abril, Isabel; Nikjoo, Hooshang

2013-11-01

Low-energy electrons play a prominent role in radiation therapy and biology as they are the largest contributor to the absorbed dose. However, no tractable theory exists to describe the interaction of low-energy electrons with condensed media. This article presents a new approach to include exchange and correlation (XC) effects in inelastic electron scattering at low energies (below ∼10 keV) in the context of the dielectric theory. Specifically, an optical-data model of the dielectric response function of liquid water is developed that goes beyond the random phase approximation (RPA) by accounting for XC effects using the concept of the many-body local-field correction (LFC). It is shown that the experimental energy-loss-function of liquid water can be reproduced by including into the RPA dispersion relations XC effects (up to second order) calculated in the time-dependent local-density approximation with the addition of phonon-induced broadening in N. D. Mermin's relaxation-time approximation. Additional XC effects related to the incident and/or struck electrons are included by means of the vertex correction calculated by a modified Hubbard formula for the exchange-only LFC. Within the first Born approximation, the present XC corrections cause a significantly larger reduction (∼10-50%) to the inelastic cross section compared to the commonly used Mott and Ochkur approximations, while also yielding much better agreement with the recent experimental data for amorphous ice. The current work offers a manageable, yet rigorous, approach for including non-Born effects in the calculation of inelastic cross sections for low-energy electrons in liquid water, which due to its generality, can be easily extended to other condensed media.

Ptychographic overlap constraint errors and the limits of their numerical recovery using conjugate gradient descent methods.

PubMed

Tripathi, Ashish; McNulty, Ian; Shpyrko, Oleg G

2014-01-27

Ptychographic coherent x-ray diffractive imaging is a form of scanning microscopy that does not require optics to image a sample. A series of scanned coherent diffraction patterns recorded from multiple overlapping illuminated regions on the sample are inverted numerically to retrieve its image. The technique recovers the phase lost by detecting the diffraction patterns by using experimentally known constraints, in this case the measured diffraction intensities and the assumed scan positions on the sample. The spatial resolution of the recovered image of the sample is limited by the angular extent over which the diffraction patterns are recorded and how well these constraints are known. Here, we explore how reconstruction quality degrades with uncertainties in the scan positions. We show experimentally that large errors in the assumed scan positions on the sample can be numerically determined and corrected using conjugate gradient descent methods. We also explore in simulations the limits, based on the signal to noise of the diffraction patterns and amount of overlap between adjacent scan positions, of just how large these errors can be and still be rendered tractable by this method.

Space shuttle booster multi-engine base flow analysis

NASA Technical Reports Server (NTRS)

Tang, H. H.; Gardiner, C. R.; Anderson, W. A.; Navickas, J.

1972-01-01

A comprehensive review of currently available techniques pertinent to several prominent aspects of the base thermal problem of the space shuttle booster is given along with a brief review of experimental results. A tractable engineering analysis, capable of predicting the power-on base pressure, base heating, and other base thermal environmental conditions, such as base gas temperature, is presented and used for an analysis of various space shuttle booster configurations. The analysis consists of a rational combination of theoretical treatments of the prominent flow interaction phenomena in the base region. These theories consider jet mixing, plume flow, axisymmetric flow effects, base injection, recirculating flow dynamics, and various modes of heat transfer. Such effects as initial boundary layer expansion at the nozzle lip, reattachment, recompression, choked vent flow, and nonisoenergetic mixing processes are included in the analysis. A unified method was developed and programmed to numerically obtain compatible solutions for the various flow field components in both flight and ground test conditions. Preliminary prediction for a 12-engine space shuttle booster base thermal environment was obtained for a typical trajectory history. Theoretical predictions were also obtained for some clustered-engine experimental conditions. Results indicate good agreement between the data and theoretical predicitons.

Photofragmentation of Gas-Phase Lanthanide Cyclopentadienyl Complexes: Experimental and Time-Dependent Excited-State Molecular Dynamics

PubMed Central

2015-01-01

Unimolecular gas-phase laser-photodissociation reaction mechanisms of open-shell lanthanide cyclopentadienyl complexes, Ln(Cp)3 and Ln(TMCp)3, are analyzed from experimental and computational perspectives. The most probable pathways for the photoreactions are inferred from photoionization time-of-flight mass spectrometry (PI-TOF-MS), which provides the sequence of reaction intermediates and the distribution of final products. Time-dependent excited-state molecular dynamics (TDESMD) calculations provide insight into the electronic mechanisms for the individual steps of the laser-driven photoreactions for Ln(Cp)3. Computational analysis correctly predicts several key reaction products as well as the observed branching between two reaction pathways: (1) ligand ejection and (2) ligand cracking. Simulations support our previous assertion that both reaction pathways are initiated via a ligand-to-metal charge-transfer (LMCT) process. For the more complex chemistry of the tetramethylcyclopentadienyl complexes Ln(TMCp)3, TMESMD is less tractable, but computational geometry optimization reveals the structures of intermediates deduced from PI-TOF-MS, including several classic “tuck-in” structures and products of Cp ring expansion. The results have important implications for metal–organic catalysis and laser-assisted metal–organic chemical vapor deposition (LCVD) of insulators with high dielectric constants. PMID:24910492

Pushing the boundaries of resistance: insights from Brachypodium-rust interactions

PubMed Central

Figueroa, Melania; Castell-Miller, Claudia V.; Li, Feng; Hulbert, Scot H.; Bradeen, James M.

2015-01-01

The implications of global population growth urge transformation of current food and bioenergy production systems to sustainability. Members of the family Poaceae are of particular importance both in food security and for their applications as biofuel substrates. For centuries, rust fungi have threatened the production of valuable crops such as wheat, barley, oat, and other small grains; similarly, biofuel crops can also be susceptible to these pathogens. Emerging rust pathogenic races with increased virulence and recurrent rust epidemics around the world point out the vulnerability of monocultures. Basic research in plant immunity, especially in model plants, can make contributions to understanding plant resistance mechanisms and improve disease management strategies. The development of the grass Brachypodium distachyon as a genetically tractable model for monocots, especially temperate cereals and grasses, offers the possibility to overcome the experimental challenges presented by the genetic and genomic complexities of economically valuable crop plants. The numerous resources and tools available in Brachypodium have opened new doors to investigate the underlying molecular and genetic bases of plant–microbe interactions in grasses and evidence demonstrating the applicability and advantages of working with B. distachyon is increasing. Importantly, several interactions between B. distachyon and devastating plant pathogens, such rust fungi, have been examined in the context of non-host resistance. Here, we discuss the use of B. distachyon in these various pathosystems. Exploiting B. distachyon to understand the mechanisms underpinning disease resistance to non-adapted rust fungi may provide effective and durable approaches to fend off these pathogens. The close phylogenetic relationship among Brachypodium spp. and grasses with industrial and agronomic value support harnessing this model plant to improve cropping systems and encourage its use in translational research. PMID:26284085

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.

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

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

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.

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.

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.

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

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

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.

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.

The geometric signature: Quantifying landslide-terrain types from digital elevation models

USGS Publications Warehouse

Pike, R.J.

1988-01-01

Topography of various types and scales can be fingerprinted by computer analysis of altitude matrices (digital elevation models, or DEMs). The critical analytic tool is the geometric signature, a set of measures that describes topographic form well enough to distinguish among geomorphically disparate landscapes. Different surficial processes create topography with diagnostic forms that are recognizable in the field. The geometric signature abstracts those forms from contour maps or their DEMs and expresses them numerically. This multivariate characterization enables once-in-tractable problems to be addressed. The measures that constitute a geometric signature express different but complementary attributes of topographic form. Most parameters used here are statistical estimates of central tendency and dispersion for five major categories of terrain geometry; altitude, altitude variance spectrum, slope between slope reversals, and slope and its curvature at fixed slope lengths. As an experimental application of geometric signatures, two mapped terrain types associated with different processes of shallow landsliding in Marin County, California, were distinguished consistently by a 17-variable description of topography from 21??21 DEMs (30-m grid spacing). The small matrix is a statistical window that can be used to scan large DEMs by computer, thus potentially automating the mapping of contrasting terrain types. The two types in Marin County host either (1) slow slides: earth flows and slump-earth flows, or (2) rapid flows: debris avalanches and debris flows. The signature approach should adapt to terrain taxonomy and mapping in other areas, where conditions differ from those in Central California. ?? 1988 International Association for Mathematical Geology.

Different modes of retrovirus restriction by human APOBEC3A and APOBEC3G in vivo.

PubMed

Stavrou, Spyridon; Crawford, Daniel; Blouch, Kristin; Browne, Edward P; Kohli, Rahul M; Ross, Susan R

2014-05-01

The apolipoprotein B editing complex 3 (A3) cytidine deaminases are among the most highly evolutionarily selected retroviral restriction factors, both in terms of gene copy number and sequence diversity. Primate genomes encode seven A3 genes, and while A3F and 3G are widely recognized as important in the restriction of HIV, the role of the other genes, particularly A3A, is not as clear. Indeed, since human cells can express multiple A3 genes, and because of the lack of an experimentally tractable model, it is difficult to dissect the individual contribution of each gene to virus restriction in vivo. To overcome this problem, we generated human A3A and A3G transgenic mice on a mouse A3 knockout background. Using these mice, we demonstrate that both A3A and A3G restrict infection by murine retroviruses but by different mechanisms: A3G was packaged into virions and caused extensive deamination of the retrovirus genomes while A3A was not packaged and instead restricted infection when expressed in target cells. Additionally, we show that a murine leukemia virus engineered to express HIV Vif overcame the A3G-mediated restriction, thereby creating a novel model for studying the interaction between these proteins. We have thus developed an in vivo system for understanding how human A3 proteins use different modes of restriction, as well as a means for testing therapies that disrupt HIV Vif-A3G interactions.

Natural reservoirs for homologs of hepatitis C virus

PubMed Central

Pfaender, Stephanie; Brown, Richard JP; Pietschmann, Thomas; Steinmann, Eike

2014-01-01

Hepatitis C virus is considered a major public health problem, infecting 2%–3% of the human population. Hepatitis C virus infection causes acute and chronic liver disease, including chronic hepatitis, cirrhosis and hepatocellular carcinoma. In fact, hepatitis C virus infection is the most frequent indication for liver transplantation and a vaccine is not available. Hepatitis C virus displays a narrow host species tropism, naturally infecting only humans, although chimpanzees are also susceptible to experimental infection. To date, there is no evidence for an animal reservoir of viruses closely related to hepatitis C virus which may have crossed the species barrier to cause disease in humans and resulted in the current pandemic. In fact, due to this restricted host range, a robust immunocompetent small animal model is still lacking, hampering mechanistic analysis of virus pathogenesis, immune control and prophylactic vaccine development. Recently, several studies discovered new viruses related to hepatitis C virus, belonging to the hepaci- and pegivirus genera, in small wild mammals (rodents and bats) and domesticated animals which live in close contact with humans (dogs and horses). Genetic and biological characterization of these newly discovered hepatitis C virus-like viruses infecting different mammals will contribute to our understanding of the origins of hepatitis C virus in humans and enhance our ability to study pathogenesis and immune responses using tractable animal models. In this review article, we start with an introduction on the genetic diversity of hepatitis C virus and then focus on the newly discovered viruses closely related to hepatitis C virus. Finally, we discuss possible theories about the origin of this important viral human pathogen. PMID:26038514

Defining the Transcriptional Landscape during Cytomegalovirus Latency with Single-Cell RNA Sequencing

PubMed Central

2018-01-01

ABSTRACT Primary infection with human cytomegalovirus (HCMV) results in a lifelong infection due to its ability to establish latent infection, with one characterized viral reservoir being hematopoietic cells. Although reactivation from latency causes serious disease in immunocompromised individuals, our molecular understanding of latency is limited. Here, we delineate viral gene expression during natural HCMV persistent infection by analyzing the massive transcriptome RNA sequencing (RNA-seq) atlas generated by the Genotype-Tissue Expression (GTEx) project. This systematic analysis reveals that HCMV persistence in vivo is prevalent in diverse tissues. Notably, we find only viral transcripts that resemble gene expression during various stages of lytic infection with no evidence of any highly restricted latency-associated viral gene expression program. To further define the transcriptional landscape during HCMV latent infection, we also used single-cell RNA-seq and a tractable experimental latency model. In contrast to some current views on latency, we also find no evidence for any highly restricted latency-associated viral gene expression program. Instead, we reveal that latency-associated gene expression largely mirrors a late lytic viral program, albeit at much lower levels of expression. Overall, our work has the potential to revolutionize our understanding of HCMV persistence and suggests that latency is governed mainly by quantitative changes, with a limited number of qualitative changes, in viral gene expression. PMID:29535194

Gait control in a soft robot by sensing interactions with the environment using self-deformation.

PubMed

Umedachi, Takuya; Kano, Takeshi; Ishiguro, Akio; Trimmer, Barry A

2016-12-01

All animals use mechanosensors to help them move in complex and changing environments. With few exceptions, these sensors are embedded in soft tissues that deform in normal use such that sensory feedback results from the interaction of an animal with its environment. Useful information about the environment is expected to be embedded in the mechanical responses of the tissues during movements. To explore how such sensory information can be used to control movements, we have developed a soft-bodied crawling robot inspired by a highly tractable animal model, the tobacco hornworm Manduca sexta . This robot uses deformations of its body to detect changes in friction force on a substrate. This information is used to provide local sensory feedback for coupled oscillators that control the robot's locomotion. The validity of the control strategy is demonstrated with both simulation and a highly deformable three-dimensionally printed soft robot. The results show that very simple oscillators are able to generate propagating waves and crawling/inching locomotion through the interplay of deformation in different body parts in a fully decentralized manner. Additionally, we confirmed numerically and experimentally that the gait pattern can switch depending on the surface contact points. These results are expected to help in the design of adaptable, robust locomotion control systems for soft robots and also suggest testable hypotheses about how soft animals use sensory feedback.

Gait control in a soft robot by sensing interactions with the environment using self-deformation

PubMed Central

Ishiguro, Akio; Trimmer, Barry A.

2016-01-01

All animals use mechanosensors to help them move in complex and changing environments. With few exceptions, these sensors are embedded in soft tissues that deform in normal use such that sensory feedback results from the interaction of an animal with its environment. Useful information about the environment is expected to be embedded in the mechanical responses of the tissues during movements. To explore how such sensory information can be used to control movements, we have developed a soft-bodied crawling robot inspired by a highly tractable animal model, the tobacco hornworm Manduca sexta. This robot uses deformations of its body to detect changes in friction force on a substrate. This information is used to provide local sensory feedback for coupled oscillators that control the robot's locomotion. The validity of the control strategy is demonstrated with both simulation and a highly deformable three-dimensionally printed soft robot. The results show that very simple oscillators are able to generate propagating waves and crawling/inching locomotion through the interplay of deformation in different body parts in a fully decentralized manner. Additionally, we confirmed numerically and experimentally that the gait pattern can switch depending on the surface contact points. These results are expected to help in the design of adaptable, robust locomotion control systems for soft robots and also suggest testable hypotheses about how soft animals use sensory feedback. PMID:28083114

Targeted Knockdown of Bone Morphogenetic Protein Signaling within Neural Progenitors Protects the Brain and Improves Motor Function following Postnatal Hypoxia-Ischemia

PubMed Central

Dettman, Robert W.; Birch, Derin; Fernando, Augusta; Kessler, John A.; Dizon, Maria L.V.

2018-01-01

Hypoxic-ischemic injury (HI) to the neonatal human brain results in myelin loss that, in some children, can manifest as cerebral palsy. Previously, we had found that neuronal overexpression of the bone morphogenic protein (BMP) inhibitor noggin during development increased oligodendroglia and improved motor function in an experimental model of HI utilizing unilateral common carotid artery ligation followed by hypoxia. As BMPs are known to negatively regulate oligodendroglial fate specification of neural stem cells and alter differentiation of committed oligodendroglia, BMP signaling is likely an important mechanism leading to myelin loss. Here, we showed that BMP signaling is upregulated within oligodendroglia of the neonatal brain. We tested the hypothesis that inhibition of BMP signaling specifically within neural progenitor cells (NPCs) is sufficient to protect oligodendroglia. We conditionally deleted the BMP receptor 2 subtype (BMPR2) in NG2-expressing cells after HI. We found that BMPR2 deletion globally protects the brain as assessed by MRI and protects motor function as assessed by digital gait analysis, and that conditional deletion of BMPR2 maintains oligodendrocyte marker expression by immunofluorescence and Western blot and prevents loss of oligodendroglia. Finally, BMPR2 deletion after HI results in an increase in noncompacted myelin. Thus, our data indicate that inhibition of BMP signaling specifically in NPCs may be a tractable strategy to protect the newborn brain from HI. PMID:29324456

Evolutionary and biotechnology implications of plastid genome variation in the inverted-repeat-lacking clade of legumes.

PubMed

Sabir, Jamal; Schwarz, Erika; Ellison, Nicholas; Zhang, Jin; Baeshen, Nabih A; Mutwakil, Muhammed; Jansen, Robert; Ruhlman, Tracey

2014-08-01

Land plant plastid genomes (plastomes) provide a tractable model for evolutionary study in that they are relatively compact and gene dense. Among the groups that display an appropriate level of variation for structural features, the inverted-repeat-lacking clade (IRLC) of papilionoid legumes presents the potential to advance general understanding of the mechanisms of genomic evolution. Here, are presented six complete plastome sequences from economically important species of the IRLC, a lineage previously represented by only five completed plastomes. A number of characters are compared across the IRLC including gene retention and divergence, synteny, repeat structure and functional gene transfer to the nucleus. The loss of clpP intron 2 was identified in one newly sequenced member of IRLC, Glycyrrhiza glabra. Using deeply sequenced nuclear transcriptomes from two species helped clarify the nature of the functional transfer of accD to the nucleus in Trifolium, which likely occurred in the lineage leading to subgenus Trifolium. Legumes are second only to cereal crops in agricultural importance based on area harvested and total production. Genetic improvement via plastid transformation of IRLC crop species is an appealing proposition. Comparative analyses of intergenic spacer regions emphasize the need for complete genome sequences for developing transformation vectors for plastid genetic engineering of legume crops. © 2014 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Yeast Communities of Diverse Drosophila Species: Comparison of Two Symbiont Groups in the Same Hosts

PubMed Central

Eisen, Jonathan A.; Kopp, Artyom

2012-01-01

The combination of ecological diversity with genetic and experimental tractability makes Drosophila a powerful model for the study of animal-associated microbial communities. Despite the known importance of yeasts in Drosophila physiology, behavior, and fitness, most recent work has focused on Drosophila-bacterial interactions. In order to get a more complete understanding of the Drosophila microbiome, we characterized the yeast communities associated with different Drosophila species collected around the world. We focused on the phylum Ascomycota because it constitutes the vast majority of the Drosophila-associated yeasts. Our sampling strategy allowed us to compare the distribution and structure of the yeast and bacterial communities in the same host populations. We show that yeast communities are dominated by a small number of abundant taxa, that the same yeast lineages are associated with different host species and populations, and that host diet has a greater effect than host species on yeast community composition. These patterns closely parallel those observed in Drosophila bacterial communities. However, we do not detect a significant correlation between the yeast and bacterial communities of the same host populations. Comparative analysis of different symbiont groups provides a more comprehensive picture of host-microbe interactions. Future work on the role of symbiont communities in animal physiology, ecological adaptation, and evolution would benefit from a similarly holistic approach. PMID:22885750

“Glowing Head” Mice: A Genetic Tool Enabling Reliable Preclinical Image-Based Evaluation of Cancers in Immunocompetent Allografts

PubMed Central

Day, Chi-Ping; Carter, John; Ohler, Zoe Weaver; Bonomi, Carrie; El Meskini, Rajaa; Martin, Philip; Graff-Cherry, Cari; Feigenbaum, Lionel; Tüting, Thomas; Van Dyke, Terry; Hollingshead, Melinda; Merlino, Glenn

2014-01-01

Preclinical therapeutic assessment currently relies on the growth response of established human cell lines xenografted into immunocompromised mice, a strategy that is generally not predictive of clinical outcomes. Immunocompetent genetically engineered mouse (GEM)-derived tumor allograft models offer highly tractable preclinical alternatives and facilitate analysis of clinically promising immunomodulatory agents. Imageable reporters are essential for accurately tracking tumor growth and response, particularly for metastases. Unfortunately, reporters such as luciferase and GFP are foreign antigens in immunocompetent mice, potentially hindering tumor growth and confounding therapeutic responses. Here we assessed the value of reporter-tolerized GEMs as allograft recipients by targeting minimal expression of a luciferase-GFP fusion reporter to the anterior pituitary gland (dubbed the “Glowing Head” or GH mouse). The luciferase-GFP reporter expressed in tumor cells induced adverse immune responses in wildtype mouse, but not in GH mouse, as transplantation hosts. The antigenicity of optical reporters resulted in a decrease in both the growth and metastatic potential of the labeled tumor in wildtype mice as compared to the GH mice. Moreover, reporter expression can also alter the tumor response to chemotherapy or targeted therapy in a context-dependent manner. Thus the GH mice and experimental approaches vetted herein provide concept validation and a strategy for effective, reproducible preclinical evaluation of growth and response kinetics for traceable tumors. PMID:25369133

Designed protein reveals structural determinants of extreme kinetic stability

PubMed Central

Broom, Aron; Ma, S. Martha; Xia, Ke; Rafalia, Hitesh; Trainor, Kyle; Colón, Wilfredo; Gosavi, Shachi; Meiering, Elizabeth M.

2015-01-01

The design of stable, functional proteins is difficult. Improved design requires a deeper knowledge of the molecular basis for design outcomes and properties. We previously used a bioinformatics and energy function method to design a symmetric superfold protein composed of repeating structural elements with multivalent carbohydrate-binding function, called ThreeFoil. This and similar methods have produced a notably high yield of stable proteins. Using a battery of experimental and computational analyses we show that despite its small size and lack of disulfide bonds, ThreeFoil has remarkably high kinetic stability and its folding is specifically chaperoned by carbohydrate binding. It is also extremely stable against thermal and chemical denaturation and proteolytic degradation. We demonstrate that the kinetic stability can be predicted and modeled using absolute contact order (ACO) and long-range order (LRO), as well as coarse-grained simulations; the stability arises from a topology that includes many long-range contacts which create a large and highly cooperative energy barrier for unfolding and folding. Extensive data from proteomic screens and other experiments reveal that a high ACO/LRO is a general feature of proteins with strong resistances to denaturation and degradation. These results provide tractable approaches for predicting resistance and designing proteins with sufficient topological complexity and long-range interactions to accommodate destabilizing functional features as well as withstand chemical and proteolytic challenge. PMID:26554002

A Screenable In Vivo Assay for Mitochondrial Modulators Using Transgenic Bioluminescent Caenorhabditis elegans.

PubMed

Lagido, Cristina; McLaggan, Debbie; Glover, L Anne

2015-10-16

The multicellular model organism Caenorhabditis elegans is a small nematode of approximately 1 mm in size in adulthood that is genetically and experimentally tractable. It is economical and easy to culture and dispense in liquid medium which makes it well suited for medium-throughput screening. We have previously validated the use of transgenic luciferase expressing C. elegans strains to provide rapid in vivo assessment of the nematode's ATP levels.(1-3) Here we present the required materials and procedure to carry out bioassays with the bioluminescent C. elegans strains PE254 or PE255 (or any of their derivative strains). The protocol allows for in vivo detection of sublethal effects of drugs that may identify mitochondrial toxicity, as well as for in vivo detection of potential beneficial drug effects. Representative results are provided for the chemicals paraquat, rotenone, oxaloacetate and for four firefly luciferase inhibitory compounds. The methodology can be scaled up to provide a platform for screening drug libraries for compounds capable of modulating mitochondrial function. Pre-clinical evaluation of drug toxicity is often carried out on immortalized cancerous human cell lines which derive ATP mostly from glycolysis and are often tolerant of mitochondrial toxicants.(4,5) In contrast, C. elegans depends on oxidative phosphorylation to sustain development into adulthood, drawing a parallel with humans and providing a unique opportunity for compound evaluation in the physiological context of a whole live multicellular organism.

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...

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

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.

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

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.

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

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.

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.

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].

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

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.

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.

Long-Term Adult Feline Liver Organoid Cultures for Disease Modeling of Hepatic Steatosis.

PubMed

Kruitwagen, Hedwig S; Oosterhoff, Loes A; Vernooij, Ingrid G W H; Schrall, Ingrid M; van Wolferen, Monique E; Bannink, Farah; Roesch, Camille; van Uden, Lisa; Molenaar, Martijn R; Helms, J Bernd; Grinwis, Guy C M; Verstegen, Monique M A; van der Laan, Luc J W; Huch, Meritxell; Geijsen, Niels; Vries, Robert G; Clevers, Hans; Rothuizen, Jan; Schotanus, Baukje A; Penning, Louis C; Spee, Bart

2017-04-11

Hepatic steatosis is a highly prevalent liver disease, yet research is hampered by the lack of tractable cellular and animal models. Steatosis also occurs in cats, where it can cause severe hepatic failure. Previous studies demonstrate the potential of liver organoids for modeling genetic diseases. To examine the possibility of using organoids to model steatosis, we established a long-term feline liver organoid culture with adult liver stem cell characteristics and differentiation potential toward hepatocyte-like cells. Next, organoids from mouse, human, dog, and cat liver were provided with fatty acids. Lipid accumulation was observed in all organoids and interestingly, feline liver organoids accumulated more lipid droplets than human organoids. Finally, we demonstrate effects of interference with β-oxidation on lipid accumulation in feline liver organoids. In conclusion, feline liver organoids can be successfully cultured and display a predisposition for lipid accumulation, making them an interesting model in hepatic steatosis research. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

A study of tumour growth based on stoichiometric principles: a continuous model and its discrete analogue

PubMed Central

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]. PMID:24963981

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.

Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

PubMed

Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V

2016-01-01

Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

Signatures of criticality arise from random subsampling in simple population models.

PubMed

Nonnenmacher, Marcel; Behrens, Christian; Berens, Philipp; Bethge, Matthias; Macke, Jakob H

2017-10-01

The rise of large-scale recordings of neuronal activity has fueled the hope to gain new insights into the collective activity of neural ensembles. How can one link the statistics of neural population activity to underlying principles and theories? One attempt to interpret such data builds upon analogies to the behaviour of collective systems in statistical physics. Divergence of the specific heat-a measure of population statistics derived from thermodynamics-has been used to suggest that neural populations are optimized to operate at a "critical point". However, these findings have been challenged by theoretical studies which have shown that common inputs can lead to diverging specific heat. Here, we connect "signatures of criticality", and in particular the divergence of specific heat, back to statistics of neural population activity commonly studied in neural coding: firing rates and pairwise correlations. We show that the specific heat diverges whenever the average correlation strength does not depend on population size. This is necessarily true when data with correlations is randomly subsampled during the analysis process, irrespective of the detailed structure or origin of correlations. We also show how the characteristic shape of specific heat capacity curves depends on firing rates and correlations, using both analytically tractable models and numerical simulations of a canonical feed-forward population model. To analyze these simulations, we develop efficient methods for characterizing large-scale neural population activity with maximum entropy models. We find that, consistent with experimental findings, increases in firing rates and correlation directly lead to more pronounced signatures. Thus, previous reports of thermodynamical criticality in neural populations based on the analysis of specific heat can be explained by average firing rates and correlations, and are not indicative of an optimized coding strategy. We conclude that a reliable interpretation of statistical tests for theories of neural coding is possible only in reference to relevant ground-truth models.

Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems

NASA Technical Reports Server (NTRS)

Koch, Patrick N.

1997-01-01

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: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.

A few scenarios still do not fit all

NASA Astrophysics Data System (ADS)

Schweizer, Vanessa

2018-05-01

For integrated climate change research, the Scenario Matrix Architecture provides a tractable menu of possible emissions trajectories, socio-economic futures and policy environments. However, the future of decision support may lie in searchable databases.

Applying the multivariate time-rescaling theorem to neural population models

PubMed Central

Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon

2011-01-01

Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436

Co-evolution for Problem Simplification

NASA Technical Reports Server (NTRS)

Haith, Gary L.; Lohn, Jason D.; Cplombano, Silvano P.; Stassinopoulos, Dimitris

1999-01-01

This paper explores a co-evolutionary approach applicable to difficult problems with limited failure/success performance feedback. Like familiar "predator-prey" frameworks this algorithm evolves two populations of individuals - the solutions (predators) and the problems (prey). The approach extends previous work by rewarding only the problems that match their difficulty to the level of solut,ion competence. In complex problem domains with limited feedback, this "tractability constraint" helps provide an adaptive fitness gradient that, effectively differentiates the candidate solutions. The algorithm generates selective pressure toward the evolution of increasingly competent solutions by rewarding solution generality and uniqueness and problem tractability and difficulty. Relative (inverse-fitness) and absolute (static objective function) approaches to evaluating problem difficulty are explored and discussed. On a simple control task, this co-evolutionary algorithm was found to have significant advantages over a genetic algorithm with either a static fitness function or a fitness function that changes on a hand-tuned schedule.

Tractable Pareto Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Robert; Morris, Paul; Khatib, Lina; Venable, Brent

2003-01-01

This paper focuses on temporal constraint problems where the objective is to optimize a set of local preferences for when events occur. In previous work, a subclass of these problems has been formalized as a generalization of Temporal CSPs, and a tractable strategy for optimization has been proposed, where global optimality is defined as maximizing the minimum of the component preference values. This criterion for optimality, which we call 'Weakest Link Optimization' (WLO), is known to have limited practical usefulness because solutions are compared only on the basis of their worst value; thus, there is no requirement to improve the other values. To address this limitation, we introduce a new algorithm that re-applies WLO iteratively in a way that leads to improvement of all the values. We show the value of this strategy by proving that, with suitable preference functions, the resulting solutions are Pareto Optimal.

Tractable Experiment Design via Mathematical Surrogates

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

Williams, Brian J.

This presentation summarizes the development and implementation of quantitative design criteria motivated by targeted inference objectives for identifying new, potentially expensive computational or physical experiments. The first application is concerned with estimating features of quantities of interest arising from complex computational models, such as quantiles or failure probabilities. A sequential strategy is proposed for iterative refinement of the importance distributions used to efficiently sample the uncertain inputs to the computational model. In the second application, effective use of mathematical surrogates is investigated to help alleviate the analytical and numerical intractability often associated with Bayesian experiment design. This approach allows formore » the incorporation of prior information into the design process without the need for gross simplification of the design criterion. Illustrative examples of both design problems will be presented as an argument for the relevance of these research problems.« less

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.

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.

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.

Optimal structure and parameter learning of Ising models

DOE PAGES

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant; ...

2018-03-16

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

Optimal structure and parameter learning of Ising models

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

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

Recurrent dynamics in an epidemic model due to stimulated bifurcation crossovers

NASA Astrophysics Data System (ADS)

Juanico, Drandreb Earl

2015-05-01

Epidemics are known to persist in the form of recurrence cycles. Despite intervention efforts through vaccination and targeted social distancing, peaks of activity for infectious diseases like influenza reappear over time. Analysis of a stochastic model is here undertaken to explore a proposed cycle-generating mechanism - the bifurcation crossover. Time series from simulations of the model exhibit oscillations similar to the temporal signature of influenza activity. Power-spectral density indicates a resonant frequency, which corresponds to the annual seasonality of influenza in temperate zones. The study finds that intervention actions influence the extinguishability of epidemic activity. Asymptotic solution to a backward Kolmogorov equation corresponds to a mean extinction time that is a function of both intervention efficacy and population size. Intervention efficacy must be greater than a certain threshold to increase the chances of extinguishing the epidemic. Agreement of the model with several phenomenological features of epidemic cycles lends to it a tractability that may serve as early warning of imminent outbreaks.

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.

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.

Markov-modulated Markov chains and the covarion process of molecular evolution.

PubMed

Galtier, N; Jean-Marie, A

2004-01-01

The covarion (or site specific rate variation, SSRV) process of biological sequence evolution is a process by which the evolutionary rate of a nucleotide/amino acid/codon position can change in time. In this paper, we introduce time-continuous, space-discrete, Markov-modulated Markov chains as a model for representing SSRV processes, generalizing existing theory to any model of rate change. We propose a fast algorithm for diagonalizing the generator matrix of relevant Markov-modulated Markov processes. This algorithm makes phylogeny likelihood calculation tractable even for a large number of rate classes and a large number of states, so that SSRV models become applicable to amino acid or codon sequence datasets. Using this algorithm, we investigate the accuracy of the discrete approximation to the Gamma distribution of evolutionary rates, widely used in molecular phylogeny. We show that a relatively large number of classes is required to achieve accurate approximation of the exact likelihood when the number of analyzed sequences exceeds 20, both under the SSRV and among site rate variation (ASRV) models.

Recurrent dynamics in an epidemic model due to stimulated bifurcation crossovers

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

Juanico, Drandreb Earl; National Institute of Physics, University of the Philippines, Diliman, Quezon City, Philippines 1101

Epidemics are known to persist in the form of recurrence cycles. Despite intervention efforts through vaccination and targeted social distancing, peaks of activity for infectious diseases like influenza reappear over time. Analysis of a stochastic model is here undertaken to explore a proposed cycle-generating mechanism – the bifurcation crossover. Time series from simulations of the model exhibit oscillations similar to the temporal signature of influenza activity. Power-spectral density indicates a resonant frequency, which corresponds to the annual seasonality of influenza in temperate zones. The study finds that intervention actions influence the extinguishability of epidemic activity. Asymptotic solution to a backwardmore » Kolmogorov equation corresponds to a mean extinction time that is a function of both intervention efficacy and population size. Intervention efficacy must be greater than a certain threshold to increase the chances of extinguishing the epidemic. Agreement of the model with several phenomenological features of epidemic cycles lends to it a tractability that may serve as early warning of imminent outbreaks.« less

Exploring the zebra finch Taeniopygia guttata as a novel animal model for the speech-language deficit of fragile X syndrome.

PubMed

Winograd, Claudia; Ceman, Stephanie

2012-01-01

Fragile X syndrome (FXS) is the most common cause of inherited intellectual disability and presents with markedly atypical speech-language, likely due to impaired vocal learning. Although current models have been useful for studies of some aspects of FXS, zebra finch is the only tractable lab model for vocal learning. The neural circuits for vocal learning in the zebra finch have clear relationships to the pathways in the human brain that may be affected in FXS. Further, finch vocal learning may be quantified using software designed specifically for this purpose. Knockdown of the zebra finch FMR1 gene may ultimately enable novel tests of therapies that are modality-specific, using drugs or even social strategies, to ameliorate deficits in vocal development and function. In this chapter, we describe the utility of the zebra finch model and present a hypothesis for the role of FMRP in the developing neural circuitry for vocalization.

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.

Approximate strip exchanging.

PubMed

Roy, Swapnoneel; Thakur, Ashok Kumar

2008-01-01

Genome rearrangements have been modelled by a variety of primitives such as reversals, transpositions, block moves and block interchanges. We consider such a genome rearrangement primitive Strip Exchanges. Given a permutation, the challenge is to sort it by using minimum number of strip exchanges. A strip exchanging move interchanges the positions of two chosen strips so that they merge with other strips. The strip exchange problem is to sort a permutation using minimum number of strip exchanges. We present here the first non-trivial 2-approximation algorithm to this problem. We also observe that sorting by strip-exchanges is fixed-parameter-tractable. Lastly we discuss the application of strip exchanges in a different area Optical Character Recognition (OCR) with an example.

Chemical vapor deposition fluid flow simulation modelling tool

NASA Technical Reports Server (NTRS)

Bullister, Edward T.

1992-01-01

Accurate numerical simulation of chemical vapor deposition (CVD) processes requires a general purpose computational fluid dynamics package combined with specialized capabilities for high temperature chemistry. In this report, we describe the implementation of these specialized capabilities in the spectral element code NEKTON. The thermal expansion of the gases involved is shown to be accurately approximated by the low Mach number perturbation expansion of the incompressible Navier-Stokes equations. The radiative heat transfer between multiple interacting radiating surfaces is shown to be tractable using the method of Gebhart. The disparate rates of reaction and diffusion in CVD processes are calculated via a point-implicit time integration scheme. We demonstrate the use above capabilities on prototypical CVD applications.

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.

Bounded-Degree Approximations of Stochastic Networks

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

Quinn, Christopher J.; Pinar, Ali; Kiyavash, Negar

2017-06-01

We propose algorithms to approximate directed information graphs. Directed information graphs are probabilistic graphical models that depict causal dependencies between stochastic processes in a network. The proposed algorithms identify optimal and near-optimal approximations in terms of Kullback-Leibler divergence. The user-chosen sparsity trades off the quality of the approximation against visual conciseness and computational tractability. One class of approximations contains graphs with speci ed in-degrees. Another class additionally requires that the graph is connected. For both classes, we propose algorithms to identify the optimal approximations and also near-optimal approximations, using a novel relaxation of submodularity. We also propose algorithms to identifymore » the r-best approximations among these classes, enabling robust decision making.« less

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.

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.

Tackling the achilles' heel of genetic testing.

PubMed

Watkins, Hugh

2015-01-14

Assigning pathogenicity to rare genetic variants is at its hardest with the enormous titin gene, but comprehensive genomic analysis makes the task more tractable (Roberts et al., this issue). Copyright © 2015, American Association for the Advancement of Science.

Non-self recognition, transcriptional reprogramming, and secondary metabolite accumulation during plant/pathogen interactions

PubMed Central

Hahlbrock, Klaus; Bednarek, Pawel; Ciolkowski, Ingo; Hamberger, Björn; Heise, Andreas; Liedgens, Hiltrud; Logemann, Elke; Nürnberger, Thorsten; Schmelzer, Elmon; Somssich, Imre E.; Tan, Jianwen

2003-01-01

Disease resistance of plants involves two distinct forms of chemical communication with the pathogen: recognition and defense. Both are essential components of a highly complex, multifaceted defense response, which begins with non-self recognition through the perception of pathogen-derived signal molecules and results in the production, inter alia, of antibiotically active compounds (phytoalexins) and cell wall-reinforcing material around the infection site. To elucidate the molecular details and the genomic basis of the underlying chains of events, we used two different experimental systems: suspension-cultured cells of Petroselinum crispum (parsley) and wild-type as well as mutant plants of Arabidopsis thaliana. Particular emphasis was placed on the structural and functional identification of signal and defense molecules, and on the mechanisms of signal perception, intracellular signal transduction and transcriptional reprogramming, including the structural and functional characterization of the responsible cis-acting gene promoter elements and transacting regulatory proteins. Comparing P. crispum and A. thaliana allows us to distinguish species-specific defense mechanisms from more universal responses, and furthermore provides general insights into the nature of the interactions. Despite the complexity of the pathogen defense response, it is experimentally tractable, and knowledge gained so far has opened up a new realm of gene technology-assisted strategies for resistance breeding of crop plants. PMID:12704242

Evaluating physiological responses of plants to salinity stress

PubMed Central

Negrão, S.; Schmöckel, S. M.; Tester, M.

2017-01-01

Background Because soil salinity is a major abiotic constraint affecting crop yield, much research has been conducted to develop plants with improved salinity tolerance. Salinity stress impacts many aspects of a plant’s physiology, making it difficult to study in toto. Instead, it is more tractable to dissect the plant’s response into traits that are hypothesized to be involved in the overall tolerance of the plant to salinity. Scope and conclusions We discuss how to quantify the impact of salinity on different traits, such as relative growth rate, water relations, transpiration, transpiration use efficiency, ionic relations, photosynthesis, senescence, yield and yield components. We also suggest some guidelines to assist with the selection of appropriate experimental systems, imposition of salinity stress, and obtaining and analysing relevant physiological data using appropriate indices. We illustrate how these indices can be used to identify relationships amongst the proposed traits to identify which traits are the most important contributors to salinity tolerance. Salinity tolerance is complex and involves many genes, but progress has been made in studying the mechanisms underlying a plant’s response to salinity. Nevertheless, several previous studies on salinity tolerance could have benefited from improved experimental design. We hope that this paper will provide pertinent information to researchers on performing proficient assays and interpreting results from salinity tolerance experiments. PMID:27707746

A Global Covariance Descriptor for Nuclear Atypia Scoring in Breast Histopathology Images.

PubMed

Khan, Adnan Mujahid; Sirinukunwattana, Korsuk; Rajpoot, Nasir

2015-09-01

Nuclear atypia scoring is a diagnostic measure commonly used to assess tumor grade of various cancers, including breast cancer. It provides a quantitative measure of deviation in visual appearance of cell nuclei from those in normal epithelial cells. In this paper, we present a novel image-level descriptor for nuclear atypia scoring in breast cancer histopathology images. The method is based on the region covariance descriptor that has recently become a popular method in various computer vision applications. The descriptor in its original form is not suitable for classification of histopathology images as cancerous histopathology images tend to possess diversely heterogeneous regions in a single field of view. Our proposed image-level descriptor, which we term as the geodesic mean of region covariance descriptors, possesses all the attractive properties of covariance descriptors lending itself to tractable geodesic-distance-based k-nearest neighbor classification using efficient kernels. The experimental results suggest that the proposed image descriptor yields high classification accuracy compared to a variety of widely used image-level descriptors.

Phonons in random alloys: The itinerant coherent-potential approximation

NASA Astrophysics Data System (ADS)

Ghosh, Subhradip; Leath, P. L.; Cohen, Morrel H.

2002-12-01

We present the itinerant coherent-potential approximation (ICPA), an analytic, translationally invariant, and tractable form of augmented-space-based multiple-scattering theory18 in a single-site approximation for harmonic phonons in realistic random binary alloys with mass and force-constant disorder. We provide expressions for quantities needed for comparison with experimental structure factors such as partial and average spectral functions and derive the sum rules associated with them. Numerical results are presented for Ni55Pd45 and Ni50Pt50 alloys which serve as test cases, the former for weak force-constant disorder and the latter for strong. We present results on dispersion curves and disorder-induced widths. Direct comparisons with the single-site coherent potential approximation (CPA) and experiment are made which provide insight into the physics of force-constant changes in random alloys. The CPA accounts well for the weak force-constant disorder case but fails for strong force-constant disorder where the ICPA succeeds.

An approximate method for calculating three-dimensional inviscid hypersonic flow fields

NASA Technical Reports Server (NTRS)

Riley, Christopher J.; Dejarnette, Fred R.

1990-01-01

An approximate solution technique was developed for 3-D inviscid, hypersonic flows. The method employs Maslen's explicit pressure equation in addition to the assumption of approximate stream surfaces in the shock layer. This approximation represents a simplification to Maslen's asymmetric method. The present method presents a tractable procedure for computing the inviscid flow over 3-D surfaces at angle of attack. The solution procedure involves iteratively changing the shock shape in the subsonic-transonic region until the correct body shape is obtained. Beyond this region, the shock surface is determined using a marching procedure. Results are presented for a spherically blunted cone, paraboloid, and elliptic cone at angle of attack. The calculated surface pressures are compared with experimental data and finite difference solutions of the Euler equations. Shock shapes and profiles of pressure are also examined. Comparisons indicate the method adequately predicts shock layer properties on blunt bodies in hypersonic flow. The speed of the calculations makes the procedure attractive for engineering design applications.

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.

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.

Valuing options in shot noise market

NASA Astrophysics Data System (ADS)

Laskin, Nick

2018-07-01

A new exactly solvable option pricing model has been introduced and elaborated. It is assumed that a stock price follows a Geometric shot noise process. An arbitrage-free integro-differential option pricing equation has been obtained and solved. The new Greeks have been analytically calculated. It has been shown that in diffusion approximation the developed option pricing model incorporates the well-known Black-Scholes equation and its solution. The stochastic dynamic origin of the Black-Scholes volatility has been uncovered. To model the observed market stock price patterns consisting of high frequency small magnitude and low frequency large magnitude jumps, the superposition of two Geometric shot noises has been implemented. A new generalized option pricing equation has been obtained and its exact solution was found. Merton's jump-diffusion formula for option price was recovered in diffusion approximation. Despite the non-Gaussian nature of probability distributions involved, the new option pricing model has the same degree of analytical tractability as the Black-Scholes model and the Merton jump-diffusion model. This attractive feature allows one to derive exact formulas to value options and option related instruments in the market with jump-like price patterns.

Local rules simulation of the kinetics of virus capsid self-assembly.

PubMed

Schwartz, R; Shor, P W; Prevelige, P E; Berger, B

1998-12-01

A computer model is described for studying the kinetics of the self-assembly of icosahedral viral capsids. Solution of this problem is crucial to an understanding of the viral life cycle, which currently cannot be adequately addressed through laboratory techniques. The abstract simulation model employed to address this is based on the local rules theory of. Proc. Natl. Acad. Sci. USA. 91:7732-7736). It is shown that the principle of local rules, generalized with a model of kinetics and other extensions, can be used to simulate complicated problems in self-assembly. This approach allows for a computationally tractable molecular dynamics-like simulation of coat protein interactions while retaining many relevant features of capsid self-assembly. Three simple simulation experiments are presented to illustrate the use of this model. These show the dependence of growth and malformation rates on the energetics of binding interactions, the tolerance of errors in binding positions, and the concentration of subunits in the examples. These experiments demonstrate a tradeoff within the model between growth rate and fidelity of assembly for the three parameters. A detailed discussion of the computational model is also provided.

Perspectives of Light-Front Quantized Field Theory: Some New Results

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

Srivastava, Prem P.

1999-08-13

A review of some basic topics in the light-front (LF) quantization of relativistic field theory is made. It is argued that the LF quantization is equally appropriate as the conventional one and that they lead, assuming the microcausality principle, to the same physical content. This is confirmed in the studies on the LF of the spontaneous symmetry breaking (SSB), of the degenerate vacua in Schwinger model (SM) and Chiral SM (CSM), of the chiral boson theory, and of the QCD in covariant gauges among others. The discussion on the LF is more economical and more transparent than that found inmore » the conventional equal-time quantized theory. The removal of the constraints on the LF phase space by following the Dirac method, in fact, results in a substantially reduced number of independent dynamical variables. Consequently, the descriptions of the physical Hilbert space and the vacuum structure, for example, become more tractable. In the context of the Dyson-Wick perturbation theory the relevant propagators in the front form theory are causal. The Wick rotation can then be performed to employ the Euclidean space integrals in momentum space. The lack of manifest covariance becomes tractable, and still more so if we employ, as discussed in the text, the Fourier transform of the fermionic field based on a special construction of the LF spinor. The fact that the hyperplanes x{sup {+-}} = 0 constitute characteristic surfaces of the hyperbolic partial differential equation is found irrelevant in the quantized theory; it seems sufficient to quantize the theory on one of the characteristic hyperplanes.« less

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.

Multicomponent Gas Diffusion and an Appropriate Momentum Boundary Condition

NASA Technical Reports Server (NTRS)

Noever, David A.

1994-01-01

Multicomponent gas diffusion is reviewed with particular emphasis on gas flows near solid boundaries-the so-called Kramers-Kistemaker effect. The aim is to derive an appropriate momentum boundary condition which governs many gaseous species diffusing together. The many species' generalization of the traditional single gas condition, either as slip or stick (no-slip), is not obvious, particularly for technologically important cases of lower gas pressures and very dissimilar molecular weight gases. No convincing theoretical case exists for why two gases should interact with solid boundaries equally but in opposite flow directions, such that the total gas flow exactly vanishes. ln this way, the multicomponent no-slip boundary requires careful treatment The approaches discussed here generally adopt a microscopic model for gas-solid contact. The method has the advantage that the mathematics remain tractable and hence experimentally testable. Two new proposals are put forward, the first building in some molecular collision physics, the second drawing on a detailed view of surface diffusion which does not unphysically extrapolate bulk gas properties to govern the adsorbed molecules. The outcome is a better accounting of previously anomalous experiments. Models predict novel slip conditions appearing even for the case of equal molecular weight components. These approaches become particularly significant in view of a conceptual contradiction found to arise in previous derivations of the appropriate boundary conditions. The analogous case of three gases, one of which is uniformly distributed and hence non-diffusing, presents a further refinement which gives unexpected flow reversals near solid boundaries. This case is investigated alone and for aggregating gas species near their condensation point. In addition to predicting new physics, this investigation carries practical implications for controlling vapor diffusion in the growth of crystals used in medical diagnosis (e.g. mercuric iodide) and semiconductors.

Hybrid finite-volume/transported PDF method for the simulation of turbulent reactive flows

NASA Astrophysics Data System (ADS)

Raman, Venkatramanan

A novel computational scheme is formulated for simulating turbulent reactive flows in complex geometries with detailed chemical kinetics. A Probability Density Function (PDF) based method that handles the scalar transport equation is coupled with an existing Finite Volume (FV) Reynolds-Averaged Navier-Stokes (RANS) flow solver. The PDF formulation leads to closed chemical source terms and facilitates the use of detailed chemical mechanisms without approximations. The particle-based PDF scheme is modified to handle complex geometries and grid structures. Grid-independent particle evolution schemes that scale linearly with the problem size are implemented in the Monte-Carlo PDF solver. A novel algorithm, in situ adaptive tabulation (ISAT) is employed to ensure tractability of complex chemistry involving a multitude of species. Several non-reacting test cases are performed to ascertain the efficiency and accuracy of the method. Simulation results from a turbulent jet-diffusion flame case are compared against experimental data. The effect of micromixing model, turbulence model and reaction scheme on flame predictions are discussed extensively. Finally, the method is used to analyze the Dow Chlorination Reactor. Detailed kinetics involving 37 species and 158 reactions as well as a reduced form with 16 species and 21 reactions are used. The effect of inlet configuration on reactor behavior and product distribution is analyzed. Plant-scale reactors exhibit quenching phenomena that cannot be reproduced by conventional simulation methods. The FV-PDF method predicts quenching accurately and provides insight into the dynamics of the reactor near extinction. The accuracy of the fractional time-stepping technique in discussed in the context of apparent multiple-steady states observed in a non-premixed feed configuration of the chlorination reactor.

A Bayesian Framework to Account for Complex Non-Genetic Factors in Gene Expression Levels Greatly Increases Power in eQTL Studies

PubMed Central

Durbin, Richard; Winn, John

2010-01-01

Gene expression measurements are influenced by a wide range of factors, such as the state of the cell, experimental conditions and variants in the sequence of regulatory regions. To understand the effect of a variable of interest, such as the genotype of a locus, it is important to account for variation that is due to confounding causes. Here, we present VBQTL, a probabilistic approach for mapping expression quantitative trait loci (eQTLs) that jointly models contributions from genotype as well as known and hidden confounding factors. VBQTL is implemented within an efficient and flexible inference framework, making it fast and tractable on large-scale problems. We compare the performance of VBQTL with alternative methods for dealing with confounding variability on eQTL mapping datasets from simulations, yeast, mouse, and human. Employing Bayesian complexity control and joint modelling is shown to result in more precise estimates of the contribution of different confounding factors resulting in additional associations to measured transcript levels compared to alternative approaches. We present a threefold larger collection of cis eQTLs than previously found in a whole-genome eQTL scan of an outbred human population. Altogether, 27% of the tested probes show a significant genetic association in cis, and we validate that the additional eQTLs are likely to be real by replicating them in different sets of individuals. Our method is the next step in the analysis of high-dimensional phenotype data, and its application has revealed insights into genetic regulation of gene expression by demonstrating more abundant cis-acting eQTLs in human than previously shown. Our software is freely available online at http://www.sanger.ac.uk/resources/software/peer/. PMID:20463871

The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization

PubMed Central

Noor, Elad; Flamholz, Avi; Bar-Even, Arren; Davidi, Dan; Milo, Ron; Liebermeister, Wolfram

2016-01-01

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. PMID:27812109

The BioC-BioGRID corpus: full text articles annotated for curation of protein–protein and genetic interactions

PubMed Central

Kim, Sun; Chatr-aryamontri, Andrew; Chang, Christie S.; Oughtred, Rose; Rust, Jennifer; Wilbur, W. John; Comeau, Donald C.; Dolinski, Kara; Tyers, Mike

2017-01-01

A great deal of information on the molecular genetics and biochemistry of model organisms has been reported in the scientific literature. However, this data is typically described in free text form and is not readily amenable to computational analyses. To this end, the BioGRID database systematically curates the biomedical literature for genetic and protein interaction data. This data is provided in a standardized computationally tractable format and includes structured annotation of experimental evidence. BioGRID curation necessarily involves substantial human effort by expert curators who must read each publication to extract the relevant information. Computational text-mining methods offer the potential to augment and accelerate manual curation. To facilitate the development of practical text-mining strategies, a new challenge was organized in BioCreative V for the BioC task, the collaborative Biocurator Assistant Task. This was a non-competitive, cooperative task in which the participants worked together to build BioC-compatible modules into an integrated pipeline to assist BioGRID curators. As an integral part of this task, a test collection of full text articles was developed that contained both biological entity annotations (gene/protein and organism/species) and molecular interaction annotations (protein–protein and genetic interactions (PPIs and GIs)). This collection, which we call the BioC-BioGRID corpus, was annotated by four BioGRID curators over three rounds of annotation and contains 120 full text articles curated in a dataset representing two major model organisms, namely budding yeast and human. The BioC-BioGRID corpus contains annotations for 6409 mentions of genes and their Entrez Gene IDs, 186 mentions of organism names and their NCBI Taxonomy IDs, 1867 mentions of PPIs and 701 annotations of PPI experimental evidence statements, 856 mentions of GIs and 399 annotations of GI evidence statements. The purpose, characteristics and possible future uses of the BioC-BioGRID corpus are detailed in this report. Database URL: http://bioc.sourceforge.net/BioC-BioGRID.html PMID:28077563

Analytical Modelling of the Spread of Disease in Confined and Crowded Spaces

NASA Astrophysics Data System (ADS)

Goscé, Lara; Barton, David A. W.; Johansson, Anders

2014-05-01

Since 1927 and until recently, most models describing the spread of disease have been of compartmental type, based on the assumption that populations are homogeneous and well-mixed. Recent models have utilised agent-based models and complex networks to explicitly study heterogeneous interaction patterns, but this leads to an increasing computational complexity. Compartmental models are appealing because of their simplicity, but their parameters, especially the transmission rate, are complex and depend on a number of factors, which makes it hard to predict how a change of a single environmental, demographic, or epidemiological factor will affect the population. Therefore, in this contribution we propose a middle ground, utilising crowd-behaviour research to improve compartmental models in crowded situations. We show how both the rate of infection as well as the walking speed depend on the local crowd density around an infected individual. The combined effect is that the rate of infection at a population scale has an analytically tractable non-linear dependency on crowd density. We model the spread of a hypothetical disease in a corridor and compare our new model with a typical compartmental model, which highlights the regime in which current models may not produce credible results.

Effects of flight activity and age on oxidative damage in the honey bee, Apis mellifera.

PubMed

Margotta, Joseph W; Roberts, Stephen P; Elekonich, Michelle M

2018-05-03

Frequent and highly aerobic behaviors likely contribute to naturally occurring stress, accelerate senescence, and limit lifespan. To understand how the physiological and cellular mechanisms that determine the onset and duration of senescence are shaped by behavioral development and behavioral duration, we exploited the tractability of the honey bee ( Apis mellifera ) model system. First, we determined if a cause-effect relationship exists between honey bee flight and oxidative stress by comparing oxidative damage accrued from intense flight bouts to damage accrued from D-galactose ingestion, which induces oxidative stress and limit lifespan in other insects. Second, we experimentally manipulated the duration of honey bee flight across a range of ages to determine their effects on reactive oxygen species (ROS) accumulation and associated enzymatic antioxidant protective mechanisms. In bees fed D-galactose, lipid peroxidation (MDA) was higher than in bees fed sucrose and age-matched bees with high and low flight experience collected from a colony. Bees with high amounts of flight experience exhibited elevated 8-OHdG, a marker of oxidative DNA damage, relative to bees with less flight experience. Bees with high amounts of flight experience also showed increased levels of pro-oxidants (superoxide and H 2 O 2 ) and decreased or unchanged levels of antioxidants (SOD and catalase). These data implicate an imbalance of pro- to antioxidants in flight-associated oxidative stress and reveal how behavior can damage a cell and consequently limit lifespan. © 2018. Published by The Company of Biologists Ltd.

Multi-tissue DNA methylation age predictor in mouse.

PubMed

Stubbs, Thomas M; Bonder, Marc Jan; Stark, Anne-Katrien; Krueger, Felix; von Meyenn, Ferdinand; Stegle, Oliver; Reik, Wolf

2017-04-11

DNA methylation changes at a discrete set of sites in the human genome are predictive of chronological and biological age. However, it is not known whether these changes are causative or a consequence of an underlying ageing process. It has also not been shown whether this epigenetic clock is unique to humans or conserved in the more experimentally tractable mouse. We have generated a comprehensive set of genome-scale base-resolution methylation maps from multiple mouse tissues spanning a wide range of ages. Many CpG sites show significant tissue-independent correlations with age which allowed us to develop a multi-tissue predictor of age in the mouse. Our model, which estimates age based on DNA methylation at 329 unique CpG sites, has a median absolute error of 3.33 weeks and has similar properties to the recently described human epigenetic clock. Using publicly available datasets, we find that the mouse clock is accurate enough to measure effects on biological age, including in the context of interventions. While females and males show no significant differences in predicted DNA methylation age, ovariectomy results in significant age acceleration in females. Furthermore, we identify significant differences in age-acceleration dependent on the lipid content of the diet. Here we identify and characterise an epigenetic predictor of age in mice, the mouse epigenetic clock. This clock will be instrumental for understanding the biology of ageing and will allow modulation of its ticking rate and resetting the clock in vivo to study the impact on biological age.

Reinforcement learning and episodic memory in humans and animals: an integrative framework

PubMed Central

Gershman, Samuel J.; Daw, Nathaniel D.

2018-01-01

We review the psychology and neuroscience of reinforcement learning (RL), which has witnessed significant progress in the last two decades, enabled by the comprehensive experimental study of simple learning and decision-making tasks. However, the simplicity of these tasks misses important aspects of reinforcement learning in the real world: (i) State spaces are high-dimensional, continuous, and partially observable; this implies that (ii) data are relatively sparse: indeed precisely the same situation may never be encountered twice; and also that (iii) rewards depend on long-term consequences of actions in ways that violate the classical assumptions that make RL tractable. A seemingly distinct challenge is that, cognitively, these theories have largely connected with procedural and semantic memory: how knowledge about action values or world models extracted gradually from many experiences can drive choice. This misses many aspects of memory related to traces of individual events, such as episodic memory. We suggest that these two gaps are related. In particular, the computational challenges can be dealt with, in part, by endowing RL systems with episodic memory, allowing them to (i) efficiently approximate value functions over complex state spaces, (ii) learn with very little data, and (iii) bridge long-term dependencies between actions and rewards. We review the computational theory underlying this proposal and the empirical evidence to support it. Our proposal suggests that the ubiquitous and diverse roles of memory in RL may function as part of an integrated learning system. PMID:27618944

CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models

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

Haraldsdóttir, Hulda S.; Cousins, Ben; Thiele, Ines

In constraint-based metabolic modelling, physical and biochemical constraints define a polyhedral convex set of feasible flux vectors. Uniform sampling of this set provides an unbiased characterization of the metabolic capabilities of a biochemical network. However, reliable uniform sampling of genome-scale biochemical networks is challenging due to their high dimensionality and inherent anisotropy. Here, we present an implementation of a new sampling algorithm, coordinate hit-and-run with rounding (CHRR). This algorithm is based on the provably efficient hit-and-run random walk and crucially uses a preprocessing step to round the anisotropic flux set. CHRR provably converges to a uniform stationary sampling distribution. Wemore » apply it to metabolic networks of increasing dimensionality. We show that it converges several times faster than a popular artificial centering hit-and-run algorithm, enabling reliable and tractable sampling of genome-scale biochemical networks.« less

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.

Magnetic pumping of particles in the outer Jovian magnetosphere

NASA Technical Reports Server (NTRS)

Borovsky, J. E.

1980-01-01

The mechanism of magnetic pumping consists of two processes, the adiabatic motion of charged particles in a time varying magnetic field and their pitch-angle diffusion. The result is a systematic increase in the energy of charged particles trapped in mirror (and particularly, magnetospheric) magnetic fields. A numerical model of the mechanism is constructed, compared with analytic theory where possible, and, through elementary exercises, is used to predict the consequences of the process for cases that are not tractable by analytical means. For energy dependent pitch angle diffusion rates, characteristic 'two temperature' distributions are produced. Application of the model to the outer Jovian magnetosphere shows that beyond 20 Jupiter radii in the outer magnetosphere, particles may be magnetically pumped to energies of the order of 1 - 2 MeV. Two temperature distribution functions with "break points" at 1 - 4 KeV for electrons and 8 - 35 KeV for ions are predicted.

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

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

Transformations based on continuous piecewise-affine velocity fields

DOE PAGES

Freifeld, Oren; Hauberg, Soren; Batmanghelich, Kayhan; ...

2017-01-11

Here, we propose novel finite-dimensional spaces of well-behaved Rn → Rn transformations. The latter are obtained by (fast and highly-accurate) integration of continuous piecewise-affine velocity fields. The proposed method is simple yet highly expressive, effortlessly handles optional constraints (e.g., volume preservation and/or boundary conditions), and supports convenient modeling choices such as smoothing priors and coarse-to-fine analysis. Importantly, the proposed approach, partly due to its rapid likelihood evaluations and partly due to its other properties, facilitates tractable inference over rich transformation spaces, including using Markov-Chain Monte-Carlo methods. Its applications include, but are not limited to: monotonic regression (more generally, optimization overmore » monotonic functions); modeling cumulative distribution functions or histograms; time-warping; image warping; image registration; real-time diffeomorphic image editing; data augmentation for image classifiers. Our GPU-based code is publicly available.« 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

Transformations Based on Continuous Piecewise-Affine Velocity Fields

PubMed Central

Freifeld, Oren; Hauberg, Søren; Batmanghelich, Kayhan; Fisher, Jonn W.

2018-01-01

We propose novel finite-dimensional spaces of well-behaved ℝn → ℝn transformations. The latter are obtained by (fast and highly-accurate) integration of continuous piecewise-affine velocity fields. The proposed method is simple yet highly expressive, effortlessly handles optional constraints (e.g., volume preservation and/or boundary conditions), and supports convenient modeling choices such as smoothing priors and coarse-to-fine analysis. Importantly, the proposed approach, partly due to its rapid likelihood evaluations and partly due to its other properties, facilitates tractable inference over rich transformation spaces, including using Markov-Chain Monte-Carlo methods. Its applications include, but are not limited to: monotonic regression (more generally, optimization over monotonic functions); modeling cumulative distribution functions or histograms; time-warping; image warping; image registration; real-time diffeomorphic image editing; data augmentation for image classifiers. Our GPU-based code is publicly available. PMID:28092517

A Drosophila model for alcohol reward

PubMed Central

Kaun, K.R.; Azanchi, R.; Maung, Z.; Hirsh, J.; Heberlein, U.

2014-01-01

The rewarding properties of drugs contribute to the development of abuse and addiction. Here we present a new assay to investigate the motivational properties of ethanol in the genetically tractable model, Drosophila melanogaster. Flies learn to associate cues with ethanol intoxication and, although transiently aversive, the experience leads to a long-lasting attraction for the ethanol-paired cue, implying that intoxication is rewarding. Temporally blocking transmission in dopaminergic neurons revealed that flies require activation of these neurons to express, but not develop, conditioned preference for ethanol-associated cues. Moreover, flies acquire, consolidate, and retrieve these rewarding memories using distinct sets of neurons of the mushroom body. Finally, mutations in scabrous, encoding a fibrinogen-related peptide that regulates Notch signaling, disrupt the formation of memories for ethanol reward. Our results thus establish that Drosophila can be useful in understanding the molecular, genetic and neural mechanisms underling the rewarding properties of ethanol. PMID:21499254

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.

CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models

DOE PAGES

Haraldsdóttir, Hulda S.; Cousins, Ben; Thiele, Ines; ...

2017-01-31

In constraint-based metabolic modelling, physical and biochemical constraints define a polyhedral convex set of feasible flux vectors. Uniform sampling of this set provides an unbiased characterization of the metabolic capabilities of a biochemical network. However, reliable uniform sampling of genome-scale biochemical networks is challenging due to their high dimensionality and inherent anisotropy. Here, we present an implementation of a new sampling algorithm, coordinate hit-and-run with rounding (CHRR). This algorithm is based on the provably efficient hit-and-run random walk and crucially uses a preprocessing step to round the anisotropic flux set. CHRR provably converges to a uniform stationary sampling distribution. Wemore » apply it to metabolic networks of increasing dimensionality. We show that it converges several times faster than a popular artificial centering hit-and-run algorithm, enabling reliable and tractable sampling of genome-scale biochemical networks.« less

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.

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.

Markovian Interpretations of Dual Retrieval Processes

PubMed Central

Gomes, C. F. A.; Nakamura, K.; Reyna, V. F.

2013-01-01

A half-century ago, at the dawn of the all-or-none learning era, Estes showed that finite Markov chains supply a tractable, comprehensive framework for discrete-change data of the sort that he envisioned for shifts in conditioning states in stimulus sampling theory. Shortly thereafter, such data rapidly accumulated in many spheres of human learning and animal conditioning, and Estes’ work stimulated vigorous development of Markov models to handle them. A key outcome was that the data of the workhorse paradigms of episodic memory, recognition and recall, proved to be one- and two-stage Markovian, respectively, to close approximations. Subsequently, Markov modeling of recognition and recall all but disappeared from the literature, but it is now reemerging in the wake of dual-process conceptions of episodic memory. In recall, in particular, Markov models are being used to measure two retrieval operations (direct access and reconstruction) and a slave familiarity operation. In the present paper, we develop this family of models and present the requisite machinery for fit evaluation and significance testing. Results are reviewed from selected experiments in which the recall models were used to understand dual memory processes. PMID:24948840

Active Subspaces for Wind Plant Surrogate Modeling

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

King, Ryan N; Quick, Julian; Dykes, Katherine L

Understanding the uncertainty in wind plant performance is crucial to their cost-effective design and operation. However, conventional approaches to uncertainty quantification (UQ), such as Monte Carlo techniques or surrogate modeling, are often computationally intractable for utility-scale wind plants because of poor congergence rates or the curse of dimensionality. In this paper we demonstrate that wind plant power uncertainty can be well represented with a low-dimensional active subspace, thereby achieving a significant reduction in the dimension of the surrogate modeling problem. We apply the active sub-spaces technique to UQ of plant power output with respect to uncertainty in turbine axial inductionmore » factors, and find a single active subspace direction dominates the sensitivity in power output. When this single active subspace direction is used to construct a quadratic surrogate model, the number of model unknowns can be reduced by up to 3 orders of magnitude without compromising performance on unseen test data. We conclude that the dimension reduction achieved with active subspaces makes surrogate-based UQ approaches tractable for utility-scale wind plants.« less

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

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.

Analysis of Neuronal Spike Trains, Deconstructed

PubMed Central

Aljadeff, Johnatan; Lansdell, Benjamin J.; Fairhall, Adrienne L.; Kleinfeld, David

2016-01-01

As information flows through the brain, neuronal firing progresses from encoding the world as sensed by the animal to driving the motor output of subsequent behavior. One of the more tractable goals of quantitative neuroscience is to develop predictive models that relate the sensory or motor streams with neuronal firing. Here we review and contrast analytical tools used to accomplish this task. We focus on classes of models in which the external variable is compared with one or more feature vectors to extract a low-dimensional representation, the history of spiking and other variables are potentially incorporated, and these factors are nonlinearly transformed to predict the occurrences of spikes. We illustrate these techniques in application to datasets of different degrees of complexity. In particular, we address the fitting of models in the presence of strong correlations in the external variable, as occurs in natural sensory stimuli and in movement. Spectral correlation between predicted and measured spike trains is introduced to contrast the relative success of different methods. PMID:27477016

Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation.

PubMed

Bisconti, Cristian; Corallo, Angelo; Fortunato, Laura; Gentile, Antonio A; Massafra, Andrea; Pellè, Piergiuseppe

2015-01-01

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages.

Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation

PubMed Central

Bisconti, Cristian; Corallo, Angelo; Fortunato, Laura; Gentile, Antonio A.; Massafra, Andrea; Pellè, Piergiuseppe

2015-01-01

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages. PMID:26617539

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

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

CMB and matter power spectra with non-linear dark-sector interactions

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

Marttens, R.F. vom; Casarini, L.; Zimdahl, W.

2017-01-01

An interaction between dark matter and dark energy, proportional to the product of their energy densities, results in a scaling behavior of the ratio of these densities with respect to the scale factor of the Robertson-Walker metric. This gives rise to a class of cosmological models which deviate from the standard model in an analytically tractable way. In particular, it becomes possible to quantify the role of potential dark-energy perturbations. We investigate the impact of this interaction on the structure formation process. Using the (modified) CAMB code we obtain the CMB spectrum as well as the linear matter power spectrum.more » It is shown that the strong degeneracy in the parameter space present in the background analysis is considerably reduced by considering Planck data. Our analysis is compatible with the ΛCDM model at the 2σ confidence level with a slightly preferred direction of the energy flow from dark matter to dark energy.« less

Elevated temperature alters carbon cycling in a model microbial community

NASA Astrophysics Data System (ADS)

Mosier, A.; Li, Z.; Thomas, B. C.; Hettich, R. L.; Pan, C.; Banfield, J. F.

2013-12-01

Earth's climate is regulated by biogeochemical carbon exchanges between the land, oceans and atmosphere that are chiefly driven by microorganisms. Microbial communities are therefore indispensible to the study of carbon cycling and its impacts on the global climate system. In spite of the critical role of microbial communities in carbon cycling processes, microbial activity is currently minimally represented or altogether absent from most Earth System Models. Method development and hypothesis-driven experimentation on tractable model ecosystems of reduced complexity, as presented here, are essential for building molecularly resolved, benchmarked carbon-climate models. Here, we use chemoautotropic acid mine drainage biofilms as a model community to determine how elevated temperature, a key parameter of global climate change, regulates the flow of carbon through microbial-based ecosystems. This study represents the first community proteomics analysis using tandem mass tags (TMT), which enable accurate, precise, and reproducible quantification of proteins. We compare protein expression levels of biofilms growing over a narrow temperature range expected to occur with predicted climate changes. We show that elevated temperature leads to up-regulation of proteins involved in amino acid metabolism and protein modification, and down-regulation of proteins involved in growth and reproduction. Closely related bacterial genotypes differ in their response to temperature: Elevated temperature represses carbon fixation by two Leptospirillum genotypes, whereas carbon fixation is significantly up-regulated at higher temperature by a third closely related genotypic group. Leptospirillum group III bacteria are more susceptible to viral stress at elevated temperature, which may lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, this proteogenomics approach revealed the effects of climate change on carbon cycling pathways and other microbial activities. When scaled to more complex ecosystems and integrated into Earth System Models, this approach could significantly improve predictions of global carbon-climate feedbacks. Experiments such as these are a critical first step designed at understanding climate change impacts in order to better predict ecosystem adaptations, assess the viability of mitigation strategies, and inform relevant policy decisions.

Martian ages

NASA Technical Reports Server (NTRS)

Neukum, G.; Hiller, K.

1981-01-01

Four discussions are conducted: (1) the methodology of relative age determination by impact crater statistics, (2) a comparison of proposed Martian impact chronologies for the determination of absolute ages from crater frequencies, (3) a report on work dating Martian volcanoes and erosional features by impact crater statistics, and (4) an attempt to understand the main features of Martian history through a synthesis of crater frequency data. Two cratering chronology models are presented and used for inference of absolute ages from crater frequency data, and it is shown that the interpretation of all data available and tractable by the methodology presented leads to a global Martian geological history that is characterized by two epochs of activity. It is concluded that Mars is an ancient planet with respect to its surface features.

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.

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.

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.

User Manual for SAHM package for VisTrails

USGS Publications Warehouse

Talbert, C.B.; Talbert, M.K.

2012-01-01

The Software for Assisted Habitat I\\•1odeling (SAHM) has been created to both expedite habitat modeling and help maintain a record of the various input data, pre-and post-processing steps and modeling options incorporated in the construction of a species distribution model. The four main advantages to using the combined VisTrail: SAHM package for species distribution modeling are: 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 4. extensibility to incorporate future and additional modeling routines and tools. This user manual provides detailed information on each module within the SAHM package, their input, output, common connections, optional arguments, and default settings. This information can also be accessed for individual modules by right clicking on the documentation button for any module in VisTrail or by right clicking on any input or output for a module and selecting view documentation. This user manual is intended to accompany the user guide which provides detailed instructions on how to install the SAHM package within VisTrails and then presents information on the use of the package.

Quantifying, Visualizing, and Monitoring Lead Optimization.

PubMed

Maynard, Andrew T; Roberts, Christopher D

2016-05-12

Although lead optimization (LO) is by definition a process, process-centric analysis and visualization of this important phase of pharmaceutical R&D has been lacking. Here we describe a simple statistical framework to quantify and visualize the progression of LO projects so that the vital signs of LO convergence can be monitored. We refer to the resulting visualizations generated by our methodology as the "LO telemetry" of a project. These visualizations can be automated to provide objective, holistic, and instantaneous analysis and communication of LO progression. This enhances the ability of project teams to more effectively drive LO process, while enabling management to better coordinate and prioritize LO projects. We present the telemetry of five LO projects comprising different biological targets and different project outcomes, including clinical compound selection, termination due to preclinical safety/tox, and termination due to lack of tractability. We demonstrate that LO progression is accurately captured by the telemetry. We also present metrics to quantify LO efficiency and tractability.

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.

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.

Exploiting Bounded Signal Flow for Graph Orientation Based on Cause-Effect Pairs

NASA Astrophysics Data System (ADS)

Dorn, Britta; Hüffner, Falk; Krüger, Dominikus; Niedermeier, Rolf; Uhlmann, Johannes

We consider the following problem: Given an undirected network and a set of sender-receiver pairs, direct all edges such that the maximum number of "signal flows" defined by the pairs can be routed respecting edge directions. This problem has applications in communication networks and in understanding protein interaction based cell regulation mechanisms. Since this problem is NP-hard, research so far concentrated on polynomial-time approximation algorithms and tractable special cases. We take the viewpoint of parameterized algorithmics and examine several parameters related to the maximum signal flow over vertices or edges. We provide several fixed-parameter tractability results, and in one case a sharp complexity dichotomy between a linear-time solvable case and a slightly more general NP-hard case. We examine the value of these parameters for several real-world network instances. For many relevant cases, the NP-hard problem can be solved to optimality. In this way, parameterized analysis yields both deeper insight into the computational complexity and practical solving strategies.

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.

Analysis of tractable distortion metrics for EEG compression applications.

PubMed

Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cárdenas-Barrera, Julián; Cruz-Roldán, Fernando

2012-07-01

Coding distortion in lossy electroencephalographic (EEG) signal compression methods is evaluated through tractable objective criteria. The percentage root-mean-square difference, which is a global and relative indicator of the quality held by reconstructed waveforms, is the most widely used criterion. However, this parameter does not ensure compliance with clinical standard guidelines that specify limits to allowable noise in EEG recordings. As a result, expert clinicians may have difficulties interpreting the resulting distortion of the EEG for a given value of this parameter. Conversely, the root-mean-square error is an alternative criterion that quantifies distortion in understandable units. In this paper, we demonstrate that the root-mean-square error is better suited to control and to assess the distortion introduced by compression methods. The experiments conducted in this paper show that the use of the root-mean-square error as target parameter in EEG compression allows both clinicians and scientists to infer whether coding error is clinically acceptable or not at no cost for the compression ratio.

Predicting debris-flow initiation and run-out with a depth-averaged two-phase model and adaptive numerical methods

NASA Astrophysics Data System (ADS)

George, D. L.; Iverson, R. M.

2012-12-01

Numerically simulating debris-flow motion presents many challenges due to the complicated physics of flowing granular-fluid mixtures, the diversity of spatial scales (ranging from a characteristic particle size to the extent of the debris flow deposit), and the unpredictability of the flow domain prior to a simulation. Accurately predicting debris-flows requires models that are complex enough to represent the dominant effects of granular-fluid interaction, while remaining mathematically and computationally tractable. We have developed a two-phase depth-averaged mathematical model for debris-flow initiation and subsequent motion. Additionally, we have developed software that numerically solves the model equations efficiently on large domains. A unique feature of the mathematical model is that it includes the feedback between pore-fluid pressure and the evolution of the solid grain volume fraction, a process that regulates flow resistance. This feature endows the model with the ability to represent the transition from a stationary mass to a dynamic flow. With traditional approaches, slope stability analysis and flow simulation are treated separately, and the latter models are often initialized with force balances that are unrealistically far from equilibrium. Additionally, our new model relies on relatively few dimensionless parameters that are functions of well-known material properties constrained by physical data (eg. hydraulic permeability, pore-fluid viscosity, debris compressibility, Coulomb friction coefficient, etc.). We have developed numerical methods and software for accurately solving the model equations. By employing adaptive mesh refinement (AMR), the software can efficiently resolve an evolving debris flow as it advances through irregular topography, without needing terrain-fit computational meshes. The AMR algorithms utilize multiple levels of grid resolutions, so that computationally inexpensive coarse grids can be used where the flow is absent, and much higher resolution grids evolve with the flow. The reduction in computational cost, due to AMR, makes very large-scale problems tractable on personal computers. Model accuracy can be tested by comparison of numerical predictions and empirical data. These comparisons utilize controlled experiments conducted at the USGS debris-flow flume, which provide detailed data about flow mobilization and dynamics. Additionally, we have simulated historical large-scale debris flows, such as the (≈50 million m^3) debris flow that originated on Mt. Meager, British Columbia in 2010. This flow took a very complex route through highly variable topography and provides a valuable benchmark for testing. Maps of the debris flow deposit and data from seismic stations provide evidence regarding flow initiation, transit times and deposition. Our simulations reproduce many of the complex patterns of the event, such as run-out geometry and extent, and the large-scale nature of the flow and the complex topographical features demonstrate the utility of AMR in flow simulations.

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.

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

De novo establishment of wild-type song culture in the zebra finch

PubMed Central

Feher, Olga; Wang, Haibin; Saar, Sigal; Mitra, Partha P.; Tchernichovski, Ofer

2009-01-01

What sort of culture would evolve in an island colony of naive founders? This question cannot be studied experimentally in humans. We performed the analogous experiment using socially learned birdsong. Culture is typically viewed as consisting of traits inherited epigenetically, via social learning. However, cultural diversity has species-typical constraints1, presumably of genetic origin. A celebrated, if contentious, example is whether a universal grammar constrains syntactic diversity in human languages2. Oscine songbirds exhibit song learning and provide biologically tractable models of culture: members of a species show individual variation in song3 and geographically separated groups have local song dialects 4,5. Different species exhibit distinct song cultures6,7, suggestive of genetic constraints8,9. Absent such constraints, innovations and copying errors should cause unbounded variation over multiple generations or geographical distance, contrary to observations9. We asked if wild-type song culture might emerge over multiple generations in an isolated colony founded by isolates, and if so, how this might happen and what type of social environment is required10. Zebra finch isolates, unexposed to singing males during development, produce song with characteristics that differ from the wild-type song found in laboratory11 or natural colonies. In tutoring lineages starting from isolate founders, we quantified alterations in song across tutoring generations in two social environments: tutor-pupil pairs in sound-isolated chambers and an isolated semi-natural colony. In both settings, juveniles imitated the isolate tutors, but changed certain characteristics of the songs. These alterations accumulated over learning generations. Consequently, songs evolved toward the wild-type in 3–4 generations. Thus, species-typical song culture can appear de novo. Our study has parallels with language change and evolution12,13. In analogy to models in quantitative genetics14,15, we model song culture as a multi-generational phenotype, partly encoded genetically in an isolate founding population, influenced by environmental variables, and taking multiple generations to emerge. PMID:19412161

The circadian clock in skin: implications for adult stem cells, tissue regeneration, cancer, aging, and immunity

PubMed Central

Plikus, Maksim V.; Van Spyk, Elyse Noelani; Pham, Kim; Geyfman, Mikhail; Kumar, Vivek; Takahashi, Joseph S.; Andersen, Bogi

2015-01-01

Historically work on peripheral circadian clocks has been focused on organs and tissues that have prominent metabolic functions, such as liver, fat and muscle. In recent years, skin is emerging as a model for studying circadian clock regulation of cell proliferation, stem cell functions, tissue regeneration, aging and carcinogenesis. Morphologically skin is complex, containing multiple cell types and structures, and there is evidence for a functional circadian clock in most, if not all, of its cell types. Despite the complexity, skin stem cell populations are well defined, experimentally tractable and exhibit prominent daily cell proliferation cycles. Hair follicle stem cells also participate in recurrent, long-lasting cycles of regeneration -- the hair growth cycles. Among other advantages of skin is a broad repertoire of available genetic tools enabling the creation of cell-type specific circadian mutants. Also, due to the accessibility of the skin, in vivo imaging techniques can be readily applied to study the circadian clock and its outputs in real time, even at the single-cell level. Skin provides the first line of defense against many environmental and stress factors that exhibit dramatic diurnal variations such as solar UV radiation and temperature. Studies have already linked the circadian clock to the control of UVB-induced DNA damage and skin cancers. Due to the important role that skin plays in the defense against microorganisms, it represents a promising model system to further explore the role of the clock in the regulation of the body's immune functions. To that end, recent studies have already linked the circadian clock to psoriasis, one of the most common immune-mediated skin disorders. The skin also provides opportunities to interrogate clock regulation of tissue metabolism in the context of stem cells and regeneration. Furthermore, many animal species feature prominent seasonal hair molt cycles, offering an attractive model for investigating the role of clock in seasonal organismal behaviors. PMID:25589491

Algal Biofuels | Bioenergy | NREL

Science.gov Websites

growth conditions in a laboratory setting, particularly when strains are maintained under constant other products during phototrophic growth. NREL bioethylene research received a 2015 R&D 100 Award and winter crops, growth on either salt water or fresh water, and genetic tractability. For more

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.

The tangled bank of amino acids

PubMed Central

Pollock, David D.

2016-01-01

Abstract The use of amino acid substitution matrices to model protein evolution has yielded important insights into both the evolutionary process and the properties of specific protein families. In order to make these models tractable, standard substitution matrices represent the average results of the evolutionary process rather than the underlying molecular biophysics and population genetics, treating proteins as a set of independently evolving sites rather than as an integrated biomolecular entity. With advances in computing and the increasing availability of sequence data, we now have an opportunity to move beyond current substitution matrices to more interpretable mechanistic models with greater fidelity to the evolutionary process of mutation and selection and the holistic nature of the selective constraints. As part of this endeavour, we consider how epistatic interactions induce spatial and temporal rate heterogeneity, and demonstrate how these generally ignored factors can reconcile standard substitution rate matrices and the underlying biology, allowing us to better understand the meaning of these substitution rates. Using computational simulations of protein evolution, we can demonstrate the importance of both spatial and temporal heterogeneity in modelling protein evolution. PMID:27028523

A framework for studying emotions across species.

PubMed

Anderson, David J; Adolphs, Ralph

2014-03-27

Since the 19th century, there has been disagreement over the fundamental question of whether "emotions" are cause or consequence of their associated behaviors. This question of causation is most directly addressable in genetically tractable model organisms, including invertebrates such as Drosophila. Yet there is ongoing debate about whether such species even have "emotions," as emotions are typically defined with reference to human behavior and neuroanatomy. Here, we argue that emotional behaviors are a class of behaviors that express internal emotion states. These emotion states exhibit certain general functional and adaptive properties that apply across any specific human emotions like fear or anger, as well as across phylogeny. These general properties, which can be thought of as "emotion primitives," can be modeled and studied in evolutionarily distant model organisms, allowing functional dissection of their mechanistic bases and tests of their causal relationships to behavior. More generally, our approach not only aims at better integration of such studies in model organisms with studies of emotion in humans, but also suggests a revision of how emotion should be operationalized within psychology and psychiatry. Copyright © 2014 Elsevier Inc. All rights reserved.

A Framework for Studying Emotions Across Phylogeny

PubMed Central

Anderson, David J.; Adolphs, Ralph

2014-01-01

Since the 19th century, there has been disagreement over the fundamental question of whether “emotions” are cause or consequence of their associated behaviors. This question of causation is most directly addressable in genetically tractable model organisms, including invertebrates such as Drosophila. Yet there is ongoing debate about whether such species even have “emotions,” since emotions are typically defined with reference to human behavior and neuroanatomy. Here we argue that emotional behaviors are a class of behaviors that express internal emotion states. These emotion states exhibit certain general functional and adaptive properties that apply across any specific human emotions like fear or anger, as well as across phylogeny. These general properties, which can be thought of as “emotion primitives”, can be modeled and studied in evolutionarily distant model organisms, allowing functional dissection of their mechanistic bases, and tests of their causal relationships to behavior. More generally, our approach aims not only at better integration of such studies in model organisms with studies of emotion in humans, but also suggests a revision of how emotion should be operationalized within psychology and psychiatry. PMID:24679535

Using Satellite Tracking to Optimize Protection of Long-Lived Marine Species: Olive Ridley Sea Turtle Conservation in Central Africa

PubMed Central

Maxwell, Sara M.; Breed, Greg A.; Nickel, Barry A.; Makanga-Bahouna, Junior; Pemo-Makaya, Edgard; Parnell, Richard J.; Formia, Angela; Ngouessono, Solange; Godley, Brendan J.; Costa, Daniel P.; Witt, Matthew J.; Coyne, Michael S.

2011-01-01

Tractable conservation measures for long-lived species require the intersection between protection of biologically relevant life history stages and a socioeconomically feasible setting. To protect breeding adults, we require knowledge of animal movements, how movement relates to political boundaries, and our confidence in spatial analyses of movement. We used satellite tracking and a switching state-space model to determine the internesting movements of olive ridley sea turtles (Lepidochelys olivacea) (n = 18) in Central Africa during two breeding seasons (2007-08, 2008-09). These movements were analyzed in relation to current park boundaries and a proposed transboundary park between Gabon and the Republic of Congo, both created to reduce unintentional bycatch of sea turtles in marine fisheries. We additionally determined confidence intervals surrounding home range calculations. Turtles remained largely within a 30 km radius from the original nesting site before departing for distant foraging grounds. Only 44.6 percent of high-density areas were found within the current park but the proposed transboundary park would incorporate 97.6 percent of high-density areas. Though tagged individuals originated in Gabon, turtles were found in Congolese waters during greater than half of the internesting period (53.7 percent), highlighting the need for international cooperation and offering scientific support for a proposed transboundary park. This is the first comprehensive study on the internesting movements of solitary nesting olive ridley sea turtles, and it suggests the opportunity for tractable conservation measures for female nesting olive ridleys at this and other solitary nesting sites around the world. We draw from our results a framework for cost-effective protection of long-lived species using satellite telemetry as a primary tool. PMID:21589942

Localization of canine brachycephaly using an across breed mapping approach.

PubMed

Bannasch, Danika; Young, Amy; Myers, Jeffrey; Truvé, Katarina; Dickinson, Peter; Gregg, Jeffrey; Davis, Ryan; Bongcam-Rudloff, Eric; Webster, Matthew T; Lindblad-Toh, Kerstin; Pedersen, Niels

2010-03-10

The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10-30) and control (20-60) samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.

Organic-matter loading determines regime shifts and alternative states in an aquatic ecosystem

PubMed Central

Sirota, Jennie; Baiser, Benjamin; Gotelli, Nicholas J.; Ellison, Aaron M.

2013-01-01

Slow changes in underlying state variables can lead to “tipping points,” rapid transitions between alternative states (“regime shifts”) in a wide range of complex systems. Tipping points and regime shifts routinely are documented retrospectively in long time series of observational data. Experimental induction of tipping points and regime shifts is rare, but could lead to new methods for detecting impending tipping points and forestalling regime shifts. By using controlled additions of detrital organic matter (dried, ground arthropod prey), we experimentally induced a shift from aerobic to anaerobic states in a miniature aquatic ecosystem: the self-contained pools that form in leaves of the carnivorous northern pitcher plant, Sarracenia purpurea. In unfed controls, the concentration of dissolved oxygen ([O2]) in all replicates exhibited regular diurnal cycles associated with daytime photosynthesis and nocturnal plant respiration. In low prey-addition treatments, the regular diurnal cycles of [O2] were disrupted, but a regime shift was not detected. In high prey-addition treatments, the variance of the [O2] time series increased until the system tipped from an aerobic to an anaerobic state. In these treatments, replicate [O2] time series predictably crossed a tipping point at ∼45 h as [O2] was decoupled from diurnal cycles of photosynthesis and respiration. Increasing organic-matter loading led to predictable changes in [O2] dynamics, with high loading consistently driving the system past a well-defined tipping point. The Sarracenia microecosystem functions as a tractable experimental system in which to explore the forecasting and management of tipping points and alternative regimes. PMID:23613583

Organic-matter loading determines regime shifts and alternative states in an aquatic ecosystem.

PubMed

Sirota, Jennie; Baiser, Benjamin; Gotelli, Nicholas J; Ellison, Aaron M

2013-05-07

Slow changes in underlying state variables can lead to "tipping points," rapid transitions between alternative states ("regime shifts") in a wide range of complex systems. Tipping points and regime shifts routinely are documented retrospectively in long time series of observational data. Experimental induction of tipping points and regime shifts is rare, but could lead to new methods for detecting impending tipping points and forestalling regime shifts. By using controlled additions of detrital organic matter (dried, ground arthropod prey), we experimentally induced a shift from aerobic to anaerobic states in a miniature aquatic ecosystem: the self-contained pools that form in leaves of the carnivorous northern pitcher plant, Sarracenia purpurea. In unfed controls, the concentration of dissolved oxygen ([O2]) in all replicates exhibited regular diurnal cycles associated with daytime photosynthesis and nocturnal plant respiration. In low prey-addition treatments, the regular diurnal cycles of [O2] were disrupted, but a regime shift was not detected. In high prey-addition treatments, the variance of the [O2] time series increased until the system tipped from an aerobic to an anaerobic state. In these treatments, replicate [O2] time series predictably crossed a tipping point at ~45 h as [O2] was decoupled from diurnal cycles of photosynthesis and respiration. Increasing organic-matter loading led to predictable changes in [O2] dynamics, with high loading consistently driving the system past a well-defined tipping point. The Sarracenia microecosystem functions as a tractable experimental system in which to explore the forecasting and management of tipping points and alternative regimes.

Device-independent point estimation from finite data and its application to device-independent property estimation

NASA Astrophysics Data System (ADS)

Lin, Pei-Sheng; Rosset, Denis; Zhang, Yanbao; Bancal, Jean-Daniel; Liang, Yeong-Cherng

2018-03-01

The device-independent approach to physics is one where conclusions are drawn directly from the observed correlations between measurement outcomes. In quantum information, this approach allows one to make strong statements about the properties of the underlying systems or devices solely via the observation of Bell-inequality-violating correlations. However, since one can only perform a finite number of experimental trials, statistical fluctuations necessarily accompany any estimation of these correlations. Consequently, an important gap remains between the many theoretical tools developed for the asymptotic scenario and the experimentally obtained raw data. In particular, a physical and concurrently practical way to estimate the underlying quantum distribution has so far remained elusive. Here, we show that the natural analogs of the maximum-likelihood estimation technique and the least-square-error estimation technique in the device-independent context result in point estimates of the true distribution that are physical, unique, computationally tractable, and consistent. They thus serve as sound algorithmic tools allowing one to bridge the aforementioned gap. As an application, we demonstrate how such estimates of the underlying quantum distribution can be used to provide, in certain cases, trustworthy estimates of the amount of entanglement present in the measured system. In stark contrast to existing approaches to device-independent parameter estimations, our estimation does not require the prior knowledge of any Bell inequality tailored for the specific property and the specific distribution of interest.

Gaussian process regression of chirplet decomposed ultrasonic B-scans of a simulated design case

NASA Astrophysics Data System (ADS)

Wertz, John; Homa, Laura; Welter, John; Sparkman, Daniel; Aldrin, John

2018-04-01

The US Air Force seeks to implement damage tolerant lifecycle management of composite structures. Nondestructive characterization of damage is a key input to this framework. One approach to characterization is model-based inversion of the ultrasonic response from damage features; however, the computational expense of modeling the ultrasonic waves within composites is a major hurdle to implementation. A surrogate forward model with sufficient accuracy and greater computational efficiency is therefore critical to enabling model-based inversion and damage characterization. In this work, a surrogate model is developed on the simulated ultrasonic response from delamination-like structures placed at different locations within a representative composite layup. The resulting B-scans are decomposed via the chirplet transform, and a Gaussian process model is trained on the chirplet parameters. The quality of the surrogate is tested by comparing the B-scan for a delamination configuration not represented within the training data set. The estimated B-scan has a maximum error of ˜15% for an estimated reduction in computational runtime of ˜95% for 200 function calls. This considerable reduction in computational expense makes full 3D characterization of impact damage tractable.

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.

Hypothesis testing of a change point during cognitive decline among Alzheimer's disease patients.

PubMed

Ji, Ming; Xiong, Chengjie; Grundman, Michael

2003-10-01

In this paper, we present a statistical hypothesis test for detecting a change point over the course of cognitive decline among Alzheimer's disease patients. The model under the null hypothesis assumes a constant rate of cognitive decline over time and the model under the alternative hypothesis is a general bilinear model with an unknown change point. When the change point is unknown, however, the null distribution of the test statistics is not analytically tractable and has to be simulated by parametric bootstrap. When the alternative hypothesis that a change point exists is accepted, we propose an estimate of its location based on the Akaike's Information Criterion. We applied our method to a data set from the Neuropsychological Database Initiative by implementing our hypothesis testing method to analyze Mini Mental Status Exam scores based on a random-slope and random-intercept model with a bilinear fixed effect. Our result shows that despite large amount of missing data, accelerated decline did occur for MMSE among AD patients. Our finding supports the clinical belief of the existence of a change point during cognitive decline among AD patients and suggests the use of change point models for the longitudinal modeling of cognitive decline in AD research.

Contextual Fear Conditioning in Zebrafish

ERIC Educational Resources Information Center

Kenney, Justin W.; Scott, Ian C.; Josselyn, Sheena A.; Frankland, Paul W.

2017-01-01

Zebrafish are a genetically tractable vertebrate that hold considerable promise for elucidating the molecular basis of behavior. Although numerous recent advances have been made in the ability to precisely manipulate the zebrafish genome, much less is known about many aspects of learning and memory in adult fish. Here, we describe the development…