Analytical instrumentation infrastructure for combinatorial and high-throughput development of formulated discrete and gradient polymeric sensor materials arrays

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Hassib, Lamyaa

2005-06-01

Multicomponent polymer-based formulations of optical sensor materials are difficult and time consuming to optimize using conventional approaches. To address these challenges, our long-term goal is to determine relationships between sensor formulation and sensor response parameters using new scientific methodologies. As the first step, we have designed and implemented an automated analytical instrumentation infrastructure for combinatorial and high-throughput development of polymeric sensor materials for optical sensors. Our approach is based on the fabrication and performance screening of discrete and gradient sensor arrays. Simultaneous formation of multiple sensor coatings into discrete 4×6, 6×8, and 8×12 element arrays (3-15μL volume per element) and their screening provides not only a well-recognized acceleration in the screening rate, but also considerably reduces or even eliminates sources of variability, which are randomly affecting sensors response during a conventional one-at-a-time sensor coating evaluation. The application of gradient sensor arrays provides additional capabilities for rapid finding of the optimal formulation parameters.

One-Dimensional Czedli-Type Islands

ERIC Educational Resources Information Center

Horvath, Eszter K.; Mader, Attila; Tepavcevic, Andreja

2011-01-01

The notion of an island has surfaced in recent algebra and coding theory research. Discrete versions provide interesting combinatorial problems. This paper presents the one-dimensional case with finitely many heights, a topic convenient for student research.

Beyond Aztec Castles: Toric Cascades in the dP 3 Quiver

NASA Astrophysics Data System (ADS)

Lai, Tri; Musiker, Gregg

2017-12-01

Given one of an infinite class of supersymmetric quiver gauge theories, string theorists can associate a corresponding toric variety (which is a Calabi-Yau 3-fold) as well as an associated combinatorial model known as a brane tiling. In combinatorial language, a brane tiling is a bipartite graph on a torus and its perfect matchings are of interest to both combinatorialists and physicists alike. A cluster algebra may also be associated to such quivers and in this paper we study the generators of this algebra, known as cluster variables, for the quiver associated to the cone over the del Pezzo surface d P 3. In particular, mutation sequences involving mutations exclusively at vertices with two in-coming arrows and two out-going arrows are referred to as toric cascades in the string theory literature. Such toric cascades give rise to interesting discrete integrable systems on the level of cluster variable dynamics. We provide an explicit algebraic formula for all cluster variables that are reachable by toric cascades as well as a combinatorial interpretation involving perfect matchings of subgraphs of the d P 3 brane tiling for these formulas in most cases.

Partial differential equations constrained combinatorial optimization on an adiabatic quantum computer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh

Partial differential equation-constrained combinatorial optimization (PDECCO) problems are a mixture of continuous and discrete optimization problems. PDECCO problems have discrete controls, but since the partial differential equations (PDE) are continuous, the optimization space is continuous as well. Such problems have several applications, such as gas/water network optimization, traffic optimization, micro-chip cooling optimization, etc. Currently, no efficient classical algorithm which guarantees a global minimum for PDECCO problems exists. A new mapping has been developed that transforms PDECCO problem, which only have linear PDEs as constraints, into quadratic unconstrained binary optimization (QUBO) problems that can be solved using an adiabatic quantum optimizer (AQO). The mapping is efficient, it scales polynomially with the size of the PDECCO problem, requires only one PDE solve to form the QUBO problem, and if the QUBO problem is solved correctly and efficiently on an AQO, guarantees a global optimal solution for the original PDECCO problem.

A discrete scattering series representation for lattice embedded models of chain cyclization

NASA Astrophysics Data System (ADS)

Fraser, Simon J.; Winnik, Mitchell A.

1980-01-01

In this paper we develop a lattice based model of chain cyclization in the presence of a set of occupied sites V in the lattice. We show that within the approximation of a Markovian chain propagator the effect of V on the partition function for the system can be written as a time-ordered exponential series in which V behaves like a scattering potential and chainlength is the timelike parameter. The discrete and finite nature of this model allows us to obtain rigorous upper and lower bounds to the series limit. We adapt these formulas to calculation of the partition functions and cyclization probabilities of terminally and globally cyclizing chains. Two classes of cyclization are considered: in the first model the target set H may be visited repeatedly (the Markovian model); in the second case vertices in H may be visited at most once(the non-Markovian or taboo model). This formulation depends on two fundamental combinatorial structures, namely the inclusion-exclusion principle and the set of subsets of a set. We have tried to interpret these abstract structures with physical analogies throughout the paper.

Effect of the Implicit Combinatorial Model on Combinatorial Reasoning in Secondary School Pupils.

ERIC Educational Resources Information Center

Batanero, Carmen; And Others

1997-01-01

Elementary combinatorial problems may be classified into three different combinatorial models: (1) selection; (2) partition; and (3) distribution. The main goal of this research was to determine the effect of the implicit combinatorial model on pupils' combinatorial reasoning before and after instruction. Gives an analysis of variance of the…

A combinatorial morphospace for angiosperm pollen

NASA Astrophysics Data System (ADS)

Mander, Luke

2016-04-01

The morphology of angiosperm (flowering plant) pollen is extraordinarily diverse. This diversity results from variations in the morphology of discrete anatomical components. These components include the overall shape of a pollen grain, the stratification of the exine, the number and form of any apertures, the type of dispersal unit, and the nature of any surface ornamentation. Different angiosperm pollen morphotypes reflect different combinations of these discrete components. In this talk, I ask the following question: given the anatomical components of angiosperm pollen that are known to exist in the plant kingdom, how many unique biologically plausible combinations of these components are there? I explore this question from the perspective of enumerative combinatorics using an algorithm I have written in the Python programming language. This algorithm (1) calculates the number of combinations of these components; (2) enumerates those combinations; and (3) graphically displays those combinations. The result is a combinatorial morphospace that reflects an underlying notion that the process of morphogenesis in angiosperm pollen can be thought of as an n choose k counting problem. I compare the morphology of extant and fossil angiosperm pollen grains to this morphospace, and suggest that from a combinatorial point of view angiosperm pollen is not as diverse as it could be, which may be a result of developmental constraints.

Gesellschaft fuer angewandte Mathematik und Mechanik, Annual Scientific Meeting, Technische Universitaet Berlin, Berlin, West Germany, April 8-11, 1980, Reports. Parts 1 & 2

NASA Astrophysics Data System (ADS)

1981-04-01

The main topics discussed were related to nonparametric statistics, plane and antiplane states in finite elasticity, free-boundary-variational inequalities, the numerical solution of free boundary-value problems, discrete and combinatorial optimization, mathematical modelling in fluid mechanics, a survey and comparison regarding thermodynamic theories, invariant and almost invariant subspaces in linear systems with applications to disturbance isolation, nonlinear acoustics, and methods of function theory in the case of partial differential equations, giving particular attention to elliptic problems in the plane.

Applications of algebraic topology to compatible spatial discretizations.

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

Bochev, Pavel Blagoveston; Hyman, James M.

We provide a common framework for compatible discretizations using algebraic topology to guide our analysis. The main concept is the natural inner product on cochains, which induces a combinatorial Hodge theory. The framework comprises of mutually consistent operations of differentiation and integration, has a discrete Stokes theorem, and preserves the invariants of the DeRham cohomology groups. The latter allows for an elementary calculation of the kernel of the discrete Laplacian. Our framework provides an abstraction that includes examples of compatible finite element, finite volume and finite difference methods. We describe how these methods result from the choice of a reconstructionmore » operator and when they are equivalent.« less

A stochastic discrete optimization model for designing container terminal facilities

NASA Astrophysics Data System (ADS)

Zukhruf, Febri; Frazila, Russ Bona; Burhani, Jzolanda Tsavalista

2017-11-01

As uncertainty essentially affect the total transportation cost, it remains important in the container terminal that incorporates several modes and transshipments process. This paper then presents a stochastic discrete optimization model for designing the container terminal, which involves the decision of facilities improvement action. The container terminal operation model is constructed by accounting the variation of demand and facilities performance. In addition, for illustrating the conflicting issue that practically raises in the terminal operation, the model also takes into account the possible increment delay of facilities due to the increasing number of equipment, especially the container truck. Those variations expectantly reflect the uncertainty issue in the container terminal operation. A Monte Carlo simulation is invoked to propagate the variations by following the observed distribution. The problem is constructed within the framework of the combinatorial optimization problem for investigating the optimal decision of facilities improvement. A new variant of glow-worm swarm optimization (GSO) is thus proposed for solving the optimization, which is rarely explored in the transportation field. The model applicability is tested by considering the actual characteristics of the container terminal.

Combinatorial invariants and covariants as tools for conical intersections.

PubMed

Ryb, Itai; Baer, Roi

2004-12-01

The combinatorial invariant and covariant are introduced as practical tools for analysis of conical intersections in molecules. The combinatorial invariant is a quantity depending on adiabatic electronic states taken at discrete nuclear configuration points. It is invariant to the phase choice (gauge) of these states. In the limit that the points trace a loop in nuclear configuration space, the value of the invariant approaches the corresponding Berry phase factor. The Berry phase indicates the presence of an odd or even number of conical intersections on surfaces bounded by these loops. Based on the combinatorial invariant, we develop a computationally simple and efficient method for locating conical intersections. The method is robust due to its use of gauge invariant nature. It does not rely on the landscape of intersecting potential energy surfaces nor does it require the computation of nonadiabatic couplings. We generalize the concept to open paths and combinatorial covariants for higher dimensions obtaining a technique for the construction of the gauge-covariant adiabatic-diabatic transformation matrix. This too does not make use of nonadiabatic couplings. The importance of using gauge-covariant expressions is underlined throughout. These techniques can be readily implemented by standard quantum chemistry codes. (c) 2004 American Institute of Physics.

A Design Method for Topologically Insulating Metamaterials

NASA Astrophysics Data System (ADS)

Matlack, Kathryn; Serra-Garcia, Marc; Palermo, Antonio; Huber, Sebastian; Daraio, Chiara

Topological insulators are a unique class of electronic materials that exhibit protected edge states that are insulating in the bulk, and immune to back-scattering and defects. Discrete models, such as mass-spring systems, provide a means to translate these properties, based on the quantum hall spin effect, to the mechanical domain. This talk will present how to engineer a 2D mechanical metamaterial that supports topologically-protected and defect-immune edge states, directly from the mass-spring model of a topological insulator. The design method uses combinatorial searches plus gradient-based optimizations to determine the configuration of the metamaterials building blocks that leads to the global behavior specified by the target mass-spring model. We use metamaterials with weakly coupled unit cells to isolate the dynamics within our frequency range of interest and to enable a systematic design process. This approach can generally be applied to implement behaviors of a discrete model directly in mechanical, acoustic, or photonic metamaterials within the weak-coupling regime. This work was partially supported by the ETH Postdoctoral Fellowship, and by the Swiss National Science Foundation.

Combinatorial chemistry on solid support in the search for central nervous system agents.

PubMed

Zajdel, Paweł; Pawłowski, Maciej; Martinez, Jean; Subra, Gilles

2009-08-01

The advent of combinatorial chemistry was one of the most important developments, that has significantly contributed to the drug discovery process. Within just a few years, its initial concept aimed at production of libraries containing huge number of compounds (thousands to millions), so called screening libraries, has shifted towards preparation of small and medium-sized rationally designed libraries. When applicable, the use of solid supports for the generation of libraries has been a real breakthrough in enhancing productivity. With a limited amount of resin and simple manual workups, the split/mix procedure may generate thousands of bead-tethered compounds. Beads can be chemically or physically encoded to facilitate the identification of a hit after the biological assay. Compartmentalization of solid supports using small reactors like teabags, kans or pellicular discrete supports like Lanterns resulted in powerful sort and combine technologies, relying on codes 'written' on the reactor, and thus reducing the need for automation and improving the number of compounds synthesized. These methods of solid-phase combinatorial chemistry have been recently supported by introduction of solid-supported reagents and scavenger resins. The first part of this review discusses the general premises of combinatorial chemistry and some methods used in the design of primary and focused combinatorial libraries. The aim of the second part is to present combinatorial chemistry methodologies aimed at discovering bioactive compounds acting on diverse GPCR involved in central nervous system disorders.

Cuisenaire Rods Go to College.

ERIC Educational Resources Information Center

Chinn, Phyllis; And Others

1992-01-01

Presents examples of questions and answers arising from a hands-on and exploratory approach to discrete mathematics using cuisenaire rods. Combinatorial questions about trains formed of cuisenaire rods provide the setting for discovering numerical patterns by experimentation and organizing the results using induction and successive differences.…

Solar Proton Transport Within an ICRU Sphere Surrounded by a Complex Shield: Ray-trace Geometry

NASA Technical Reports Server (NTRS)

Slaba, Tony C.; Wilson, John W.; Badavi, Francis F.; Reddell, Brandon D.; Bahadori, Amir A.

2015-01-01

A computationally efficient 3DHZETRN code with enhanced neutron and light ion (Z is less than or equal to 2) propagation was recently developed for complex, inhomogeneous shield geometry described by combinatorial objects. Comparisons were made between 3DHZETRN results and Monte Carlo (MC) simulations at locations within the combinatorial geometry, and it was shown that 3DHZETRN agrees with the MC codes to the extent they agree with each other. In the present report, the 3DHZETRN code is extended to enable analysis in ray-trace geometry. This latest extension enables the code to be used within current engineering design practices utilizing fully detailed vehicle and habitat geometries. Through convergence testing, it is shown that fidelity in an actual shield geometry can be maintained in the discrete ray-trace description by systematically increasing the number of discrete rays used. It is also shown that this fidelity is carried into transport procedures and resulting exposure quantities without sacrificing computational efficiency.

Solar proton exposure of an ICRU sphere within a complex structure part II: Ray-trace geometry.

PubMed

Slaba, Tony C; Wilson, John W; Badavi, Francis F; Reddell, Brandon D; Bahadori, Amir A

2016-06-01

A computationally efficient 3DHZETRN code with enhanced neutron and light ion (Z ≤ 2) propagation was recently developed for complex, inhomogeneous shield geometry described by combinatorial objects. Comparisons were made between 3DHZETRN results and Monte Carlo (MC) simulations at locations within the combinatorial geometry, and it was shown that 3DHZETRN agrees with the MC codes to the extent they agree with each other. In the present report, the 3DHZETRN code is extended to enable analysis in ray-trace geometry. This latest extension enables the code to be used within current engineering design practices utilizing fully detailed vehicle and habitat geometries. Through convergence testing, it is shown that fidelity in an actual shield geometry can be maintained in the discrete ray-trace description by systematically increasing the number of discrete rays used. It is also shown that this fidelity is carried into transport procedures and resulting exposure quantities without sacrificing computational efficiency. Published by Elsevier Ltd.

Discrete exterior calculus discretization of incompressible Navier-Stokes equations over surface simplicial meshes

NASA Astrophysics Data System (ADS)

Mohamed, Mamdouh S.; Hirani, Anil N.; Samtaney, Ravi

2016-05-01

A conservative discretization of incompressible Navier-Stokes equations is developed based on discrete exterior calculus (DEC). A distinguishing feature of our method is the use of an algebraic discretization of the interior product operator and a combinatorial discretization of the wedge product. The governing equations are first rewritten using the exterior calculus notation, replacing vector calculus differential operators by the exterior derivative, Hodge star and wedge product operators. The discretization is then carried out by substituting with the corresponding discrete operators based on the DEC framework. Numerical experiments for flows over surfaces reveal a second order accuracy for the developed scheme when using structured-triangular meshes, and first order accuracy for otherwise unstructured meshes. By construction, the method is conservative in that both mass and vorticity are conserved up to machine precision. The relative error in kinetic energy for inviscid flow test cases converges in a second order fashion with both the mesh size and the time step.

Combinatorial Multiobjective Optimization Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Crossley, William A.; Martin. Eric T.

2002-01-01

The research proposed in this document investigated multiobjective optimization approaches based upon the Genetic Algorithm (GA). Several versions of the GA have been adopted for multiobjective design, but, prior to this research, there had not been significant comparisons of the most popular strategies. The research effort first generalized the two-branch tournament genetic algorithm in to an N-branch genetic algorithm, then the N-branch GA was compared with a version of the popular Multi-Objective Genetic Algorithm (MOGA). Because the genetic algorithm is well suited to combinatorial (mixed discrete / continuous) optimization problems, the GA can be used in the conceptual phase of design to combine selection (discrete variable) and sizing (continuous variable) tasks. Using a multiobjective formulation for the design of a 50-passenger aircraft to meet the competing objectives of minimizing takeoff gross weight and minimizing trip time, the GA generated a range of tradeoff designs that illustrate which aircraft features change from a low-weight, slow trip-time aircraft design to a heavy-weight, short trip-time aircraft design. Given the objective formulation and analysis methods used, the results of this study identify where turboprop-powered aircraft and turbofan-powered aircraft become more desirable for the 50 seat passenger application. This aircraft design application also begins to suggest how a combinatorial multiobjective optimization technique could be used to assist in the design of morphing aircraft.

Counting It Twice.

ERIC Educational Resources Information Center

Schattschneider, Doris

1991-01-01

Provided are examples from many domains of mathematics that illustrate the Fubini Principle in its discrete version: the value of a summation over a rectangular array is independent of the order of summation. Included are: counting using partitions as in proof by pictures, combinatorial arguments, indirect counting as in the inclusion-exclusion…

Genetic Networks and Anticipation of Gene Expression Patterns

NASA Astrophysics Data System (ADS)

Gebert, J.; Lätsch, M.; Pickl, S. W.; Radde, N.; Weber, G.-W.; Wünschiers, R.

2004-08-01

An interesting problem for computational biology is the analysis of time-series expression data. Here, the application of modern methods from dynamical systems, optimization theory, numerical algorithms and the utilization of implicit discrete information lead to a deeper understanding. In [1], we suggested to represent the behavior of time-series gene expression patterns by a system of ordinary differential equations, which we analytically and algorithmically investigated under the parametrical aspect of stability or instability. Our algorithm strongly exploited combinatorial information. In this paper, we deepen, extend and exemplify this study from the viewpoint of underlying mathematical modelling. This modelling consists in evaluating DNA-microarray measurements as the basis of anticipatory prediction, in the choice of a smooth model given by differential equations, in an approach of the right-hand side with parametric matrices, and in a discrete approximation which is a least squares optimization problem. We give a mathematical and biological discussion, and pay attention to the special case of a linear system, where the matrices do not depend on the state of expressions. Here, we present first numerical examples.

Optimal Iterative Task Scheduling for Parallel Simulations.

DTIC Science & Technology

1991-03-01

State University, Pullman, Washington. November 1976. 19. Grimaldi , Ralph P . Discrete and Combinatorial Mathematics. Addison-Wesley. June 1989. 20...2 4.8.1 Problem Description .. .. .. .. ... .. ... .... 4-25 4.8.2 Reasons for Level-Strate- p Failure. .. .. .. .. ... 4-26...f- I CA A* overview................................ C-1 C .2 Sample A* r......................... .... C-I C-3 Evaluation P

Brain Embodiment of Syntax and Grammar: Discrete Combinatorial Mechanisms Spelt Out in Neuronal Circuits

ERIC Educational Resources Information Center

Pulvermuller, Friedemann

2010-01-01

Neuroscience has greatly improved our understanding of the brain basis of abstract lexical and semantic processes. The neuronal devices underlying words and concepts are distributed neuronal assemblies reaching into sensory and motor systems of the cortex and, at the cognitive level, information binding in such widely dispersed circuits is…

Combinatorial structures to modeling simple games and applications

NASA Astrophysics Data System (ADS)

Molinero, Xavier

2017-09-01

We connect three different topics: combinatorial structures, game theory and chemistry. In particular, we establish the bases to represent some simple games, defined as influence games, and molecules, defined from atoms, by using combinatorial structures. First, we characterize simple games as influence games using influence graphs. It let us to modeling simple games as combinatorial structures (from the viewpoint of structures or graphs). Second, we formally define molecules as combinations of atoms. It let us to modeling molecules as combinatorial structures (from the viewpoint of combinations). It is open to generate such combinatorial structures using some specific techniques as genetic algorithms, (meta-)heuristics algorithms and parallel programming, among others.

An instructive model of entropy

NASA Astrophysics Data System (ADS)

Zimmerman, Seth

2010-09-01

This article first notes the misinterpretation of a common thought experiment, and the misleading comment that 'systems tend to flow from less probable to more probable macrostates'. It analyses the experiment, generalizes it and introduces a new tool of investigation, the simplectic structure. A time-symmetric model is built upon this structure, yielding several non-intuitive results. The approach is combinatorial rather than statistical, and assumes that entropy is equivalent to 'missing information'. The intention of this article is not only to present interesting results, but also, by deliberately starting with a simple example and developing it through proof and computer simulation, to clarify the often confusing subject of entropy. The article should be particularly stimulating to students and instructors of discrete mathematics or undergraduate physics.

An Analysis of Statements of the Multiplication Principle in Combinatorics, Discrete, and Finite Mathematics Textbooks

ERIC Educational Resources Information Center

Lockwood, Elise; Reed, Zackery; Caughman, John S.

2017-01-01

The multiplication principle serves as a cornerstone in enumerative combinatorics. The principle underpins many basic counting formulas and provides students with a critical element of combinatorial justification. Given its importance, the way in which it is presented in textbooks is surprisingly varied. In this paper, we analyze a number of…

RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

ERIC Educational Resources Information Center

Ellington, Roni; Wachira, James; Nkwanta, Asamoah

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses…

Development of combinatorial chemistry methods for coatings: high-throughput adhesion evaluation and scale-up of combinatorial leads.

PubMed

Potyrailo, Radislav A; Chisholm, Bret J; Morris, William G; Cawse, James N; Flanagan, William P; Hassib, Lamyaa; Molaison, Chris A; Ezbiansky, Karin; Medford, George; Reitz, Hariklia

2003-01-01

Coupling of combinatorial chemistry methods with high-throughput (HT) performance testing and measurements of resulting properties has provided a powerful set of tools for the 10-fold accelerated discovery of new high-performance coating materials for automotive applications. Our approach replaces labor-intensive steps with automated systems for evaluation of adhesion of 8 x 6 arrays of coating elements that are discretely deposited on a single 9 x 12 cm plastic substrate. Performance of coatings is evaluated with respect to their resistance to adhesion loss, because this parameter is one of the primary considerations in end-use automotive applications. Our HT adhesion evaluation provides previously unavailable capabilities of high speed and reproducibility of testing by using a robotic automation, an expanded range of types of tested coatings by using the coating tagging strategy, and an improved quantitation by using high signal-to-noise automatic imaging. Upon testing, the coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Using our HT methodology, we have developed several coatings leads. These HT screening results for the best coating compositions have been validated on the traditional scales of coating formulation and adhesion loss testing. These validation results have confirmed the superb performance of combinatorially developed coatings over conventional coatings on the traditional scale.

Iconicity and the Emergence of Combinatorial Structure in Language.

PubMed

Verhoef, Tessa; Kirby, Simon; de Boer, Bart

2016-11-01

In language, recombination of a discrete set of meaningless building blocks forms an unlimited set of possible utterances. How such combinatorial structure emerged in the evolution of human language is increasingly being studied. It has been shown that it can emerge when languages culturally evolve and adapt to human cognitive biases. How the emergence of combinatorial structure interacts with the existence of holistic iconic form-meaning mappings in a language is still unknown. The experiment presented in this paper studies the role of iconicity and human cognitive learning biases in the emergence of combinatorial structure in artificial whistled languages. Participants learned and reproduced whistled words for novel objects with the use of a slide whistle. Their reproductions were used as input for the next participant, to create transmission chains and simulate cultural transmission. Two conditions were studied: one in which the persistence of iconic form-meaning mappings was possible and one in which this was experimentally made impossible. In both conditions, cultural transmission caused the whistled languages to become more learnable and more structured, but this process was slightly delayed in the first condition. Our findings help to gain insight into when and how words may lose their iconic origins when they become part of an organized linguistic system. Copyright © 2015 Cognitive Science Society, Inc.

A combinatorial approach to angiosperm pollen morphology.

PubMed

Mander, Luke

2016-11-30

Angiosperms (flowering plants) are strikingly diverse. This is clearly expressed in the morphology of their pollen grains, which are characterized by enormous variety in their shape and patterning. In this paper, I approach angiosperm pollen morphology from the perspective of enumerative combinatorics. This involves generating angiosperm pollen morphotypes by algorithmically combining character states and enumerating the results of these combinations. I use this approach to generate 3 643 200 pollen morphotypes, which I visualize using a parallel-coordinates plot. This represents a raw morphospace. To compare real-world and theoretical morphologies, I map the pollen of 1008 species of Neotropical angiosperms growing on Barro Colorado Island (BCI), Panama, onto this raw morphospace. This highlights that, in addition to their well-documented taxonomic diversity, Neotropical rainforests also represent an enormous reservoir of morphological diversity. Angiosperm pollen morphospace at BCI has been filled mostly by pollen morphotypes that are unique to single plant species. Repetition of pollen morphotypes among higher taxa at BCI reflects both constraint and convergence. This combinatorial approach to morphology addresses the complexity that results from large numbers of discrete character combinations and could be employed in any situation where organismal form can be captured by discrete morphological characters. © 2016 The Author(s).

A combinatorial approach to angiosperm pollen morphology

PubMed Central

2016-01-01

Angiosperms (flowering plants) are strikingly diverse. This is clearly expressed in the morphology of their pollen grains, which are characterized by enormous variety in their shape and patterning. In this paper, I approach angiosperm pollen morphology from the perspective of enumerative combinatorics. This involves generating angiosperm pollen morphotypes by algorithmically combining character states and enumerating the results of these combinations. I use this approach to generate 3 643 200 pollen morphotypes, which I visualize using a parallel-coordinates plot. This represents a raw morphospace. To compare real-world and theoretical morphologies, I map the pollen of 1008 species of Neotropical angiosperms growing on Barro Colorado Island (BCI), Panama, onto this raw morphospace. This highlights that, in addition to their well-documented taxonomic diversity, Neotropical rainforests also represent an enormous reservoir of morphological diversity. Angiosperm pollen morphospace at BCI has been filled mostly by pollen morphotypes that are unique to single plant species. Repetition of pollen morphotypes among higher taxa at BCI reflects both constraint and convergence. This combinatorial approach to morphology addresses the complexity that results from large numbers of discrete character combinations and could be employed in any situation where organismal form can be captured by discrete morphological characters. PMID:27881756

Spectral monodromy of non-self-adjoint operators

NASA Astrophysics Data System (ADS)

Phan, Quang Sang

2014-01-01

In the present paper, we build a combinatorial invariant, called the "spectral monodromy" from the spectrum of a single (non-self-adjoint) h-pseudodifferential operator with two degrees of freedom in the semi-classical limit. Our inspiration comes from the quantum monodromy defined for the joint spectrum of an integrable system of n commuting self-adjoint h-pseudodifferential operators, given by S. Vu Ngoc ["Quantum monodromy in integrable systems," Commun. Math. Phys. 203(2), 465-479 (1999)]. The first simple case that we treat in this work is a normal operator. In this case, the discrete spectrum can be identified with the joint spectrum of an integrable quantum system. The second more complex case we propose is a small perturbation of a self-adjoint operator with a classical integrability property. We show that the discrete spectrum (in a small band around the real axis) also has a combinatorial monodromy. The main difficulty in this case is that we do not know the description of the spectrum everywhere, but only in a Cantor type set. In addition, we also show that the corresponding monodromy can be identified with the classical monodromy, defined by J. Duistermaat ["On global action-angle coordinates," Commun. Pure Appl. Math. 33(6), 687-706 (1980)].

Ant algorithms for discrete optimization.

PubMed

Dorigo, M; Di Caro, G; Gambardella, L M

1999-01-01

This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined. In the second part of the article a number of applications of ACO algorithms to combinatorial optimization and routing in communications networks are described. We conclude with a discussion of related work and of some of the most important aspects of the ACO metaheuristic.

Analysis of Streamline Separation at Infinity Using Time-Discrete Markov Chains.

PubMed

Reich, W; Scheuermann, G

2012-12-01

Existing methods for analyzing separation of streamlines are often restricted to a finite time or a local area. In our paper we introduce a new method that complements them by allowing an infinite-time-evaluation of steady planar vector fields. Our algorithm unifies combinatorial and probabilistic methods and introduces the concept of separation in time-discrete Markov-Chains. We compute particle distributions instead of the streamlines of single particles. We encode the flow into a map and then into a transition matrix for each time direction. Finally, we compare the results of our grid-independent algorithm to the popular Finite-Time-Lyapunov-Exponents and discuss the discrepancies.

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate

NASA Astrophysics Data System (ADS)

Eldawud, Reem; Reitzig, Manuela; Opitz, Jörg; Rojansakul, Yon; Jiang, Wenjuan; Nangia, Shikha; Zoica Dinu, Cerasela

2016-02-01

Nanodiamonds (NDs) are an emerging class of engineered nanomaterials that hold great promise for the next generation of bionanotechnological products to be used for drug and gene delivery, or for bio-imaging and biosensing. Previous studies have shown that upon their cellular uptake, NDs exhibit high biocompatibility in various in vitro and in vivo set-ups. Herein we hypothesized that the increased NDs biocompatibility is a result of minimum membrane perturbations and their reduced ability to induce disruption or damage during cellular translocation. Using multi-scale combinatorial approaches that simulate ND-membrane interactions, we correlated NDs real-time cellular uptake and kinetics with the ND-induced membrane fluctuations to derive energy requirements for the uptake to occur. Our discrete and real-time analyses showed that the majority of NDs internalization occurs within 2 h of cellular exposure, however, with no effects on cellular viability, proliferation or cellular behavior. Furthermore, our simulation analyses using coarse-grained models identified key changes in the energy profile, membrane deformation and recovery time, all functions of the average ND or ND-based agglomerate size. Understanding the mechanisms responsible for ND-cell membrane interactions could possibly advance their implementation in various biomedical applications.

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate

PubMed Central

Eldawud, Reem; Reitzig, Manuela; Opitz, Jörg; Rojansakul, Yon; Jiang, Wenjuan; Nangia, Shikha; Dinu, Cerasela Zoica

2016-01-01

Nanodiamonds (NDs) are an emerging class of engineered nanomaterials that hold great promise for the next generation of bionanotechnological products to be used for drug and gene delivery, or for bio-imaging and biosensing. Previous studies have shown that upon their cellular uptake, NDs exhibit high biocompatibility in various in vitro and in vivo set-ups. Herein we hypothesized that the increased NDs biocompatibility is a result of minimum membrane perturbations and their reduced ability to induce disruption or damage during cellular translocation. Using multi-scale combinatorial approaches that simulate ND-membrane interactions, we correlated NDs real-time cellular uptake and kinetics with the ND-induced membrane fluctuations to derive energy requirements for the uptake to occur. Our discrete and real-time analyses showed that the majority of NDs internalization occurs within 2 h of cellular exposure, however, with no effects on cellular viability, proliferation or cellular behavior. Furthermore, our simulation analyses using coarse-grained models identified key changes in the energy profile, membrane deformation and recovery time, all functions of the average ND or ND-based agglomerate size. Understanding the mechanisms responsible for ND-cell membrane interactions could possibly advance their implementation in various biomedical applications. PMID:26820775

Asessing for Structural Understanding in Childrens' Combinatorial Problem Solving.

ERIC Educational Resources Information Center

English, Lyn

1999-01-01

Assesses children's structural understanding of combinatorial problems when presented in a variety of task situations. Provides an explanatory model of students' combinatorial understandings that informs teaching and assessment. Addresses several components of children's structural understanding of elementary combinatorial problems. (Contains 50…

Combinatorial materials synthesis and high-throughput screening: an integrated materials chip approach to mapping phase diagrams and discovery and optimization of functional materials.

PubMed

Xiang, X D

Combinatorial materials synthesis methods and high-throughput evaluation techniques have been developed to accelerate the process of materials discovery and optimization and phase-diagram mapping. Analogous to integrated circuit chips, integrated materials chips containing thousands of discrete different compositions or continuous phase diagrams, often in the form of high-quality epitaxial thin films, can be fabricated and screened for interesting properties. Microspot x-ray method, various optical measurement techniques, and a novel evanescent microwave microscope have been used to characterize the structural, optical, magnetic, and electrical properties of samples on the materials chips. These techniques are routinely used to discover/optimize and map phase diagrams of ferroelectric, dielectric, optical, magnetic, and superconducting materials.

Why is combinatorial communication rare in the natural world, and why is language an exception to this trend?

PubMed

Scott-Phillips, Thomas C; Blythe, Richard A

2013-11-06

In a combinatorial communication system, some signals consist of the combinations of other signals. Such systems are more efficient than equivalent, non-combinatorial systems, yet despite this they are rare in nature. Why? Previous explanations have focused on the adaptive limits of combinatorial communication, or on its purported cognitive difficulties, but neither of these explains the full distribution of combinatorial communication in the natural world. Here, we present a nonlinear dynamical model of the emergence of combinatorial communication that, unlike previous models, considers how initially non-communicative behaviour evolves to take on a communicative function. We derive three basic principles about the emergence of combinatorial communication. We hence show that the interdependence of signals and responses places significant constraints on the historical pathways by which combinatorial signals might emerge, to the extent that anything other than the most simple form of combinatorial communication is extremely unlikely. We also argue that these constraints can be bypassed if individuals have the socio-cognitive capacity to engage in ostensive communication. Humans, but probably no other species, have this ability. This may explain why language, which is massively combinatorial, is such an extreme exception to nature's general trend for non-combinatorial communication.

Multiclass Data Segmentation using Diffuse Interface Methods on Graphs

DTIC Science & Technology

2014-01-01

37] that performs interac- tive image segmentation using the solution to a combinatorial Dirichlet problem. Elmoataz et al . have developed general...izations of the graph Laplacian [25] for image denoising and manifold smoothing. Couprie et al . in [18] define a conve- niently parameterized graph...continuous setting carry over to the discrete graph representation. For general data segmentation, Bresson et al . in [8], present rigorous convergence

Further Results on Constructions of Generalized Bent Boolean Functions

DTIC Science & Technology

2016-03-01

China; 2Naval Postgraduate School, Applied Mathematics Department, Monterey, CA 93943, USA; 3Science and Technology on Communication Security...in 1976 as an interesting combinatorial object with the important property of having op- timal nonlinearity [1]. Since bent functions have many...77–94 10 Zhao Y, Li H L. On bent functions with some symmet- ric properties. Discret Appl Math, 2006, 154: 2537– 2543

A Classification of Designated Logic Systems

DTIC Science & Technology

1988-02-01

Introduction to Logic. New York: Macmillan Publishing, 1972. Grimaldi , Ralph P . Discrete and Combinatorial Mathematics. Reading: Addison-Wesley...sound basis for understanding non-classical logic systems. I would like to thank the Air Force Institute of Technology for funding this research. vi p ...6 p ILLUSTRATIONS Figure Page 1. Two Classifications of Designated Logic Systems 13 2. Two Partitions of Two-valued Logic Systems 14 3. Two

Some unsolved problems in discrete mathematics and mathematical cybernetics

NASA Astrophysics Data System (ADS)

Korshunov, Aleksei D.

2009-10-01

There are many unsolved problems in discrete mathematics and mathematical cybernetics. Writing a comprehensive survey of such problems involves great difficulties. First, such problems are rather numerous and varied. Second, they greatly differ from each other in degree of completeness of their solution. Therefore, even a comprehensive survey should not attempt to cover the whole variety of such problems; only the most important and significant problems should be reviewed. An impersonal choice of problems to include is quite hard. This paper includes 13 unsolved problems related to combinatorial mathematics and computational complexity theory. The problems selected give an indication of the author's studies for 50 years; for this reason, the choice of the problems reviewed here is, to some extent, subjective. At the same time, these problems are very difficult and quite important for discrete mathematics and mathematical cybernetics. Bibliography: 74 items.

Development of hydrogel TentaGel shell-core beads for ultrahigh throughput solution-phase screening of encoded OBOC combinatorial small molecule libraries.

PubMed

Baek, Hyoung Gee; Liu, Ruiwu; Lam, Kit S

2009-01-01

The one-bead one-compound (OBOC) combinatorial library method enables the rapid generation and screening of millions of discrete chemical compounds on beads. Most of the OBOC screening methods require the library compounds to remain tethered to the bead during screening process. Methods have also been developed to release library compounds from immobilized beads for in situ solution phase or "lawn" assays. However, this latter approach, while extremely powerful, is severely limited by the lack of suitable solid supports for such assays. Here, we report on the development of a novel hydrogel TentaGel shell-core (HTSC) bead in which hydrogel is grafted onto the polystyrene-based TentaGel (TG) bead as an outer shell (5-80 mum thick) via free radical surface-initiated polymerization. This novel shell-core bilayer resin enables the preparation of encoded OBOC combinatorial small molecule libraries, such that the library compounds reside on the highly hydrophilic outer layer and the coding tags reside in the polystyrene-based TG core. Using fluorescein as a model small molecule compound, we have demonstrated that fluorescein molecules that have been linked covalently to the hydrogel shell via a disulfide bond could readily diffuse out of the hydrogel layer into the bead surrounding after reduction with dithiothreitol. In contrast, under identical condition, the released fluorescein molecules remained bound to unmodified TG bead. We have prepared an encoded OBOC small molecule library on the novel shell-core beads and demonstrated that the beads can be readily decoded.

Past tense in the brain's time: neurophysiological evidence for dual-route processing of past-tense verbs.

PubMed

Bakker, Iske; Macgregor, Lucy J; Pulvermüller, Friedemann; Shtyrov, Yury

2013-05-01

A controversial issue in neuro- and psycholinguistics is whether regular past-tense forms of verbs are stored lexically or generated productively by the application of abstract combinatorial schemas, for example affixation rules. The success or failure of models in accounting for this particular issue can be used to draw more general conclusions about cognition and the degree to which abstract, symbolic representations and rules are psychologically and neurobiologically real. This debate can potentially be resolved using a neurophysiological paradigm, in which alternative predictions of the brain response patterns for lexical and syntactic processing are put to the test. We used magnetoencephalography (MEG) to record neural responses to spoken monomorphemic words ('hide'), pseudowords ('smide'), regular past-tense forms ('cried') and ungrammatical (overregularised) past-tense forms ('flied') in a passive listening oddball paradigm, in which lexically and syntactically modulated stimuli are known to elicit distinct patterns of the mismatch negativity (MMN) brain response. We observed an enhanced ('lexical') MMN to monomorphemic words relative to pseudowords, but a reversed ('syntactic') MMN to ungrammatically inflected past tenses relative to grammatical forms. This dissociation between responses to monomorphemic and bimorphemic stimuli indicates that regular past tenses are processed more similarly to syntactic sequences than to lexically stored monomorphemic words, suggesting that regular past tenses are generated productively by the application of a combinatorial scheme to their separately represented stems and affixes. We suggest discrete combinatorial neuronal assemblies, which bind classes of sequentially occurring lexical elements into morphologically complex units, as the neurobiological basis of regular past tense inflection. Copyright © 2013 Elsevier Inc. All rights reserved.

Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints

NASA Astrophysics Data System (ADS)

Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.

2018-01-01

Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds.

PubMed

Uher, Vojtěch; Gajdoš, Petr; Radecký, Michal; Snášel, Václav

2016-01-01

The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds

PubMed Central

Radecký, Michal; Snášel, Václav

2016-01-01

The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds. PMID:27974884

Multiclass Data Segmentation Using Diffuse Interface Methods on Graphs

DTIC Science & Technology

2014-01-01

interac- tive image segmentation using the solution to a combinatorial Dirichlet problem. Elmoataz et al . have developed general- izations of the graph...Laplacian [25] for image denoising and manifold smoothing. Couprie et al . in [18] define a conve- niently parameterized graph-based energy function that...over to the discrete graph representation. For general data segmentation, Bresson et al . in [8], present rigorous convergence results for two algorithms

Designing a multiroute synthesis scheme in combinatorial chemistry.

PubMed

Akavia, Adi; Senderowitz, Hanoch; Lerner, Alon; Shamir, Ron

2004-01-01

Solid-phase mix-and-split combinatorial synthesis is often used to produce large arrays of compounds to be tested during the various stages of the drug development process. This method can be represented by a synthesis graph in which nodes correspond to grow operations and arcs to beads transferred among the different reaction vessels. In this work, we address the problem of designing such a graph which maximizes the number of produced target compounds (namely, compounds out of an input library of desired molecules), given constraints on the number of beads used for library synthesis and on the number of reaction vessels available for concurrent grow steps. We present a heuristic based on a discrete search for solving this problem, test our solution on several data sets, explore its behavior, and show that it achieves good performance.

Nonparametric Combinatorial Sequence Models

NASA Astrophysics Data System (ADS)

Wauthier, Fabian L.; Jordan, Michael I.; Jojic, Nebojsa

This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This paper presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three sequence datasets which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution induced by the prior. By integrating out the posterior our method compares favorably to leading binding predictors.

In silico modeling of axonal reconnection within a discrete fiber tract after spinal cord injury.

PubMed

Woolfe, Franco; Waxman, Stephen G; Hains, Bryan C

2007-02-01

Following spinal cord injury (SCI), descending axons that carry motor commands from the brain to the spinal cord are injured or transected, producing chronic motor dysfunction and paralysis. Reconnection of these axons is a major prerequisite for restoration of function after SCI. Thus far, only modest gains in motor function have been achieved experimentally or in the clinic after SCI, identifying the practical limitations of current treatment approaches. In this paper, we use an ordinary differential equation (ODE) to simulate the relative and synergistic contributions of several experimentally-established biological factors related to inhibition or promotion of axonal repair and restoration of function after SCI. The factors were mathematically modeled by the ODE. The results of our simulation show that in a model system, many factors influenced the achievability of axonal reconnection. Certain factors more strongly affected axonal reconnection in isolation, and some factors interacted in a synergistic fashion to produce further improvements in axonal reconnection. Our data suggest that mathematical modeling may be useful in evaluating the complex interactions of discrete therapeutic factors not possible in experimental preparations, and highlight the benefit of a combinatorial therapeutic approach focused on promoting axonal sprouting, attraction of cut ends, and removal of growth inhibition for achieving axonal reconnection. Predictions of this simulation may be of utility in guiding future experiments aimed at restoring function after SCI.

cDREM: inferring dynamic combinatorial gene regulation.

PubMed

Wise, Aaron; Bar-Joseph, Ziv

2015-04-01

Genes are often combinatorially regulated by multiple transcription factors (TFs). Such combinatorial regulation plays an important role in development and facilitates the ability of cells to respond to different stresses. While a number of approaches have utilized sequence and ChIP-based datasets to study combinational regulation, these have often ignored the combinational logic and the dynamics associated with such regulation. Here we present cDREM, a new method for reconstructing dynamic models of combinatorial regulation. cDREM integrates time series gene expression data with (static) protein interaction data. The method is based on a hidden Markov model and utilizes the sparse group Lasso to identify small subsets of combinatorially active TFs, their time of activation, and the logical function they implement. We tested cDREM on yeast and human data sets. Using yeast we show that the predicted combinatorial sets agree with other high throughput genomic datasets and improve upon prior methods developed to infer combinatorial regulation. Applying cDREM to study human response to flu, we were able to identify several combinatorial TF sets, some of which were known to regulate immune response while others represent novel combinations of important TFs.

Maintaining Consistency of Spatial Information in the Hippocampal Network: A Combinatorial Geometry Model.

PubMed

Dabaghian, Y

2016-06-01

Place cells in the rat hippocampus play a key role in creating the animal's internal representation of the world. During active navigation, these cells spike only in discrete locations, together encoding a map of the environment. Electrophysiological recordings have shown that the animal can revisit this map mentally during both sleep and awake states, reactivating the place cells that fired during its exploration in the same sequence in which they were originally activated. Although consistency of place cell activity during active navigation is arguably enforced by sensory and proprioceptive inputs, it remains unclear how a consistent representation of space can be maintained during spontaneous replay. We propose a model that can account for this phenomenon and suggest that a spatially consistent replay requires a number of constraints on the hippocampal network that affect its synaptic architecture and the statistics of synaptic connection strengths.

Bifurcation-based approach reveals synergism and optimal combinatorial perturbation.

PubMed

Liu, Yanwei; Li, Shanshan; Liu, Zengrong; Wang, Ruiqi

2016-06-01

Cells accomplish the process of fate decisions and form terminal lineages through a series of binary choices in which cells switch stable states from one branch to another as the interacting strengths of regulatory factors continuously vary. Various combinatorial effects may occur because almost all regulatory processes are managed in a combinatorial fashion. Combinatorial regulation is crucial for cell fate decisions because it may effectively integrate many different signaling pathways to meet the higher regulation demand during cell development. However, whether the contribution of combinatorial regulation to the state transition is better than that of a single one and if so, what the optimal combination strategy is, seem to be significant issue from the point of view of both biology and mathematics. Using the approaches of combinatorial perturbations and bifurcation analysis, we provide a general framework for the quantitative analysis of synergism in molecular networks. Different from the known methods, the bifurcation-based approach depends only on stable state responses to stimuli because the state transition induced by combinatorial perturbations occurs between stable states. More importantly, an optimal combinatorial perturbation strategy can be determined by investigating the relationship between the bifurcation curve of a synergistic perturbation pair and the level set of a specific objective function. The approach is applied to two models, i.e., a theoretical multistable decision model and a biologically realistic CREB model, to show its validity, although the approach holds for a general class of biological systems.

Oscillatory Critical Amplitudes in Hierarchical Models and the Harris Function of Branching Processes

NASA Astrophysics Data System (ADS)

Costin, Ovidiu; Giacomin, Giambattista

2013-02-01

Oscillatory critical amplitudes have been repeatedly observed in hierarchical models and, in the cases that have been taken into consideration, these oscillations are so small to be hardly detectable. Hierarchical models are tightly related to iteration of maps and, in fact, very similar phenomena have been repeatedly reported in many fields of mathematics, like combinatorial evaluations and discrete branching processes. It is precisely in the context of branching processes with bounded off-spring that T. Harris, in 1948, first set forth the possibility that the logarithm of the moment generating function of the rescaled population size, in the super-critical regime, does not grow near infinity as a power, but it has an oscillatory prefactor (the Harris function). These oscillations have been observed numerically only much later and, while the origin is clearly tied to the discrete character of the iteration, the amplitude size is not so well understood. The purpose of this note is to reconsider the issue for hierarchical models and in what is arguably the most elementary setting—the pinning model—that actually just boils down to iteration of polynomial maps (and, notably, quadratic maps). In this note we show that the oscillatory critical amplitude for pinning models and the Harris function coincide. Moreover we make explicit the link between these oscillatory functions and the geometry of the Julia set of the map, making thus rigorous and quantitative some ideas set forth in Derrida et al. (Commun. Math. Phys. 94:115-132, 1984).

Applications of Derandomization Theory in Coding

NASA Astrophysics Data System (ADS)

Cheraghchi, Mahdi

2011-07-01

Randomized techniques play a fundamental role in theoretical computer science and discrete mathematics, in particular for the design of efficient algorithms and construction of combinatorial objects. The basic goal in derandomization theory is to eliminate or reduce the need for randomness in such randomized constructions. In this thesis, we explore some applications of the fundamental notions in derandomization theory to problems outside the core of theoretical computer science, and in particular, certain problems related to coding theory. First, we consider the wiretap channel problem which involves a communication system in which an intruder can eavesdrop a limited portion of the transmissions, and construct efficient and information-theoretically optimal communication protocols for this model. Then we consider the combinatorial group testing problem. In this classical problem, one aims to determine a set of defective items within a large population by asking a number of queries, where each query reveals whether a defective item is present within a specified group of items. We use randomness condensers to explicitly construct optimal, or nearly optimal, group testing schemes for a setting where the query outcomes can be highly unreliable, as well as the threshold model where a query returns positive if the number of defectives pass a certain threshold. Finally, we design ensembles of error-correcting codes that achieve the information-theoretic capacity of a large class of communication channels, and then use the obtained ensembles for construction of explicit capacity achieving codes. [This is a shortened version of the actual abstract in the thesis.

Neural Meta-Memes Framework for Combinatorial Optimization

NASA Astrophysics Data System (ADS)

Song, Li Qin; Lim, Meng Hiot; Ong, Yew Soon

In this paper, we present a Neural Meta-Memes Framework (NMMF) for combinatorial optimization. NMMF is a framework which models basic optimization algorithms as memes and manages them dynamically when solving combinatorial problems. NMMF encompasses neural networks which serve as the overall planner/coordinator to balance the workload between memes. We show the efficacy of the proposed NMMF through empirical study on a class of combinatorial problem, the quadratic assignment problem (QAP).

Concept of combinatorial de novo design of drug-like molecules by particle swarm optimization.

PubMed

Hartenfeller, Markus; Proschak, Ewgenij; Schüller, Andreas; Schneider, Gisbert

2008-07-01

We present a fast stochastic optimization algorithm for fragment-based molecular de novo design (COLIBREE, Combinatorial Library Breeding). The search strategy is based on a discrete version of particle swarm optimization. Molecules are represented by a scaffold, which remains constant during optimization, and variable linkers and side chains. Different linkers represent virtual chemical reactions. Side-chain building blocks were obtained from pseudo-retrosynthetic dissection of large compound databases. Here, ligand-based design was performed using chemically advanced template search (CATS) topological pharmacophore similarity to reference ligands as fitness function. A weighting scheme was included for particle swarm optimization-based molecular design, which permits the use of many reference ligands and allows for positive and negative design to be performed simultaneously. In a case study, the approach was applied to the de novo design of potential peroxisome proliferator-activated receptor subtype-selective agonists. The results demonstrate the ability of the technique to cope with large combinatorial chemistry spaces and its applicability to focused library design. The technique was able to perform exploitation of a known scheme and at the same time explorative search for novel ligands within the framework of a given molecular core structure. It thereby represents a practical solution for compound screening in the early hit and lead finding phase of a drug discovery project.

Creative thought as blind-variation and selective-retention: Combinatorial models of exceptional creativity

NASA Astrophysics Data System (ADS)

Simonton, Dean Keith

2010-06-01

Campbell (1960) proposed that creative thought should be conceived as a blind-variation and selective-retention process (BVSR). This article reviews the developments that have taken place in the half century that has elapsed since his proposal, with special focus on the use of combinatorial models as formal representations of the general theory. After defining the key concepts of blind variants, creative thought, and disciplinary context, the combinatorial models are specified in terms of individual domain samples, variable field size, ideational combination, and disciplinary communication. Empirical implications are then derived with respect to individual, domain, and field systems. These abstract combinatorial models are next provided substantive reinforcement with respect to findings concerning the cognitive processes, personality traits, developmental factors, and social contexts that contribute to creativity. The review concludes with some suggestions regarding future efforts to explicate creativity according to BVSR theory.

Computation of the area in the discrete plane: Green's theorem revisited

NASA Astrophysics Data System (ADS)

Chalifour, Alain; Nouboud, Fathallah; Voisin, Yvon

2017-11-01

The detection of the contour of a binary object is a common problem; however, the area of a region, and its moments, can be a significant parameter. In several metrology applications, the area of planar objects must be measured. The area is obtained by counting the pixels inside the contour or using a discrete version of Green's formula. Unfortunately, we obtain the area enclosed by the polygonal line passing through the centers of the pixels along the contour. We present a modified version of Green's theorem in the discrete plane, which allows for the computation of the exact area of a two-dimensional region in the class of polyominoes. Penalties are introduced and associated with each successive pair of Freeman displacements along the contour in an eight-connectivity system. The proposed equation is shown to be true and properties of the equation related to the topology of the regions are presented. The proposed approach is adapted for faster computation than the combinatorial approach proposed in the literature.

Combinatorial Problems of Applied Discrete Mathematics.

DTIC Science & Technology

1979-12-01

204 .I (30) 3. Steiner, Combinatorische Aufgabe, Z. Reine Angew. Math. 45 (1853) 18 1—182. (31) IC. Takeuchi, A table of difference sets generating...Assoc. Fr. Ay. Sd . 1 (1900) 122— 123; 2 (1901) 170—203. • (33) R.M. Wilson, Cyclotomy and difference fam ilies in elementary Abelian groups , 3. Number...the differe nt cliques containing either A or B. Let us first introduce the following notations. If A is a vertex in G, then 1(A) denotes the set of

Combinatorial-topological framework for the analysis of global dynamics.

PubMed

Bush, Justin; Gameiro, Marcio; Harker, Shaun; Kokubu, Hiroshi; Mischaikow, Konstantin; Obayashi, Ippei; Pilarczyk, Paweł

2012-12-01

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications.

Combinatorial-topological framework for the analysis of global dynamics

NASA Astrophysics Data System (ADS)

Bush, Justin; Gameiro, Marcio; Harker, Shaun; Kokubu, Hiroshi; Mischaikow, Konstantin; Obayashi, Ippei; Pilarczyk, Paweł

2012-12-01

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications.

Precursors to language: Social cognition and pragmatic inference in primates.

PubMed

Seyfarth, Robert M; Cheney, Dorothy L

2017-02-01

Despite their differences, human language and the vocal communication of nonhuman primates share many features. Both constitute forms of coordinated activity, rely on many shared neural mechanisms, and involve discrete, combinatorial cognition that includes rich pragmatic inference. These common features suggest that during evolution the ancestors of all modern primates faced similar social problems and responded with similar systems of communication and cognition. When language later evolved from this common foundation, many of its distinctive features were already present.

A new multi-objective optimization model for preventive maintenance and replacement scheduling of multi-component systems

NASA Astrophysics Data System (ADS)

Moghaddam, Kamran S.; Usher, John S.

2011-07-01

In this article, a new multi-objective optimization model is developed to determine the optimal preventive maintenance and replacement schedules in a repairable and maintainable multi-component system. In this model, the planning horizon is divided into discrete and equally-sized periods in which three possible actions must be planned for each component, namely maintenance, replacement, or do nothing. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability simultaneously over the planning horizon. Because of the complexity, combinatorial and highly nonlinear structure of the mathematical model, two metaheuristic solution methods, generational genetic algorithm, and a simulated annealing are applied to tackle the problem. The Pareto optimal solutions that provide good tradeoffs between the total cost and the overall reliability of the system can be obtained by the solution approach. Such a modeling approach should be useful for maintenance planners and engineers tasked with the problem of developing recommended maintenance plans for complex systems of components.

Combinatorial Methods for Exploring Complex Materials

NASA Astrophysics Data System (ADS)

Amis, Eric J.

2004-03-01

Combinatorial and high-throughput methods have changed the paradigm of pharmaceutical synthesis and have begun to have a similar impact on materials science research. Already there are examples of combinatorial methods used for inorganic materials, catalysts, and polymer synthesis. For many investigations the primary goal has been discovery of new material compositions that optimize properties such as phosphorescence or catalytic activity. In the midst of the excitement generated to "make things", another opportunity arises for materials science to "understand things" by using the efficiency of combinatorial methods. We have shown that combinatorial methods hold potential for rapid and systematic generation of experimental data over the multi-parameter space typical of investigations in polymer physics. We have applied the combinatorial approach to studies of polymer thin films, biomaterials, polymer blends, filled polymers, and semicrystalline polymers. By combining library fabrication, high-throughput measurements, informatics, and modeling we can demonstrate validation of the methodology, new observations, and developments toward predictive models. This talk will present some of our latest work with applications to coating stability, multi-component formulations, and nanostructure assembly.

Application of computer assisted combinatorial chemistry in antivirial, antimalarial and anticancer agents design

NASA Astrophysics Data System (ADS)

Burello, E.; Bologa, C.; Frecer, V.; Miertus, S.

Combinatorial chemistry and technologies have been developed to a stage where synthetic schemes are available for generation of a large variety of organic molecules. The innovative concept of combinatorial design assumes that screening of a large and diverse library of compounds will increase the probability of finding an active analogue among the compounds tested. Since the rate at which libraries are screened for activity currently constitutes a limitation to the use of combinatorial technologies, it is important to be selective about the number of compounds to be synthesized. Early experience with combinatorial chemistry indicated that chemical diversity alone did not result in a significant increase in the number of generated lead compounds. Emphasis has therefore been increasingly put on the use of computer assisted combinatorial chemical techniques. Computational methods are valuable in the design of virtual libraries of molecular models. Selection strategies based on computed physicochemical properties of the models or of a target compound are introduced to reduce the time and costs of library synthesis and screening. In addition, computational structure-based library focusing methods can be used to perform in silico screening of the activity of compounds against a target receptor by docking the ligands into the receptor model. Three case studies are discussed dealing with the design of targeted combinatorial libraries of inhibitors of HIV-1 protease, P. falciparum plasmepsin and human urokinase as potential antivirial, antimalarial and anticancer drugs. These illustrate library focusing strategies.

The transmission process: A combinatorial stochastic process for the evolution of transmission trees over networks.

PubMed

Sainudiin, Raazesh; Welch, David

2016-12-07

We derive a combinatorial stochastic process for the evolution of the transmission tree over the infected vertices of a host contact network in a susceptible-infected (SI) model of an epidemic. Models of transmission trees are crucial to understanding the evolution of pathogen populations. We provide an explicit description of the transmission process on the product state space of (rooted planar ranked labelled) binary transmission trees and labelled host contact networks with SI-tags as a discrete-state continuous-time Markov chain. We give the exact probability of any transmission tree when the host contact network is a complete, star or path network - three illustrative examples. We then develop a biparametric Beta-splitting model that directly generates transmission trees with exact probabilities as a function of the model parameters, but without explicitly modelling the underlying contact network, and show that for specific values of the parameters we can recover the exact probabilities for our three example networks through the Markov chain construction that explicitly models the underlying contact network. We use the maximum likelihood estimator (MLE) to consistently infer the two parameters driving the transmission process based on observations of the transmission trees and use the exact MLE to characterize equivalence classes over the space of contact networks with a single initial infection. An exploratory simulation study of the MLEs from transmission trees sampled from three other deterministic and four random families of classical contact networks is conducted to shed light on the relation between the MLEs of these families with some implications for statistical inference along with pointers to further extensions of our models. The insights developed here are also applicable to the simplest models of "meme" evolution in online social media networks through transmission events that can be distilled from observable actions such as "likes", "mentions", "retweets" and "+1s" along with any concomitant comments. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations

NASA Astrophysics Data System (ADS)

Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.

2017-09-01

This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

Building polyhedra by self-assembly: theory and experiment.

PubMed

Kaplan, Ryan; Klobušický, Joseph; Pandey, Shivendra; Gracias, David H; Menon, Govind

2014-01-01

We investigate the utility of a mathematical framework based on discrete geometry to model biological and synthetic self-assembly. Our primary biological example is the self-assembly of icosahedral viruses; our synthetic example is surface-tension-driven self-folding polyhedra. In both instances, the process of self-assembly is modeled by decomposing the polyhedron into a set of partially formed intermediate states. The set of all intermediates is called the configuration space, pathways of assembly are modeled as paths in the configuration space, and the kinetics and yield of assembly are modeled by rate equations, Markov chains, or cost functions on the configuration space. We review an interesting interplay between biological function and mathematical structure in viruses in light of this framework. We discuss in particular: (i) tiling theory as a coarse-grained description of all-atom models; (ii) the building game-a growth model for the formation of polyhedra; and (iii) the application of these models to the self-assembly of the bacteriophage MS2. We then use a similar framework to model self-folding polyhedra. We use a discrete folding algorithm to compute a configuration space that idealizes surface-tension-driven self-folding and analyze pathways of assembly and dominant intermediates. These computations are then compared with experimental observations of a self-folding dodecahedron with side 300 μm. In both models, despite a combinatorial explosion in the size of the configuration space, a few pathways and intermediates dominate self-assembly. For self-folding polyhedra, the dominant intermediates have fewer degrees of freedom than comparable intermediates, and are thus more rigid. The concentration of assembly pathways on a few intermediates with distinguished geometric properties is biologically and physically important, and suggests deeper mathematical structure.

Combinatorial Nano-Bio Interfaces.

PubMed

Cai, Pingqiang; Zhang, Xiaoqian; Wang, Ming; Wu, Yun-Long; Chen, Xiaodong

2018-06-08

Nano-bio interfaces are emerging from the convergence of engineered nanomaterials and biological entities. Despite rapid growth, clinical translation of biomedical nanomaterials is heavily compromised by the lack of comprehensive understanding of biophysicochemical interactions at nano-bio interfaces. In the past decade, a few investigations have adopted a combinatorial approach toward decoding nano-bio interfaces. Combinatorial nano-bio interfaces comprise the design of nanocombinatorial libraries and high-throughput bioevaluation. In this Perspective, we address challenges in combinatorial nano-bio interfaces and call for multiparametric nanocombinatorics (composition, morphology, mechanics, surface chemistry), multiscale bioevaluation (biomolecules, organelles, cells, tissues/organs), and the recruitment of computational modeling and artificial intelligence. Leveraging combinatorial nano-bio interfaces will shed light on precision nanomedicine and its potential applications.

Combinatorial Color Space Models for Skin Detection in Sub-continental Human Images

NASA Astrophysics Data System (ADS)

Khaled, Shah Mostafa; Saiful Islam, Md.; Rabbani, Md. Golam; Tabassum, Mirza Rehenuma; Gias, Alim Ul; Kamal, Md. Mostafa; Muctadir, Hossain Muhammad; Shakir, Asif Khan; Imran, Asif; Islam, Saiful

Among different color models HSV, HLS, YIQ, YCbCr, YUV, etc. have been most popular for skin detection. Most of the research done in the field of skin detection has been trained and tested on human images of African, Mongolian and Anglo-Saxon ethnic origins, skin colors of Indian sub-continentals have not been focused separately. Combinatorial algorithms, without affecting asymptotic complexity can be developed using the skin detection concepts of these color models for boosting detection performance. In this paper a comparative study of different combinatorial skin detection algorithms have been made. For training and testing 200 images (skin and non skin) containing pictures of sub-continental male and females have been used to measure the performance of the combinatorial approaches, and considerable development in success rate with True Positive of 99.5% and True Negative of 93.3% have been observed.

Exact combinatorial approach to finite coagulating systems

NASA Astrophysics Data System (ADS)

Fronczak, Agata; Chmiel, Anna; Fronczak, Piotr

2018-02-01

This paper outlines an exact combinatorial approach to finite coagulating systems. In this approach, cluster sizes and time are discrete and the binary aggregation alone governs the time evolution of the systems. By considering the growth histories of all possible clusters, an exact expression is derived for the probability of a coagulating system with an arbitrary kernel being found in a given cluster configuration when monodisperse initial conditions are applied. Then this probability is used to calculate the time-dependent distribution for the number of clusters of a given size, the average number of such clusters, and that average's standard deviation. The correctness of our general expressions is proved based on the (analytical and numerical) results obtained for systems with the constant kernel. In addition, the results obtained are compared with the results arising from the solutions to the mean-field Smoluchowski coagulation equation, indicating its weak points. The paper closes with a brief discussion on the extensibility to other systems of the approach presented herein, emphasizing the issue of arbitrary initial conditions.

Multitriangulations, pseudotriangulations and some problems of realization of polytopes

NASA Astrophysics Data System (ADS)

Pilaud, Vincent

2010-09-01

This thesis explores two specific topics of discrete geometry, the multitriangulations and the polytopal realizations of products, whose connection is the problem of finding polytopal realizations of a given combinatorial structure. A k-triangulation is a maximal set of chords of the convex n-gon such that no k+1 of them mutually cross. We propose a combinatorial and geometric study of multitriangulations based on their stars, which play the same role as triangles of triangulations. This study leads to interpret multitriangulations by duality as pseudoline arrangements with contact points covering a given support. We exploit finally these results to discuss some open problems on multitriangulations, in particular the question of the polytopal realization of their flip graphs. We study secondly the polytopality of Cartesian products. We investigate the existence of polytopal realizations of cartesian products of graphs, and we study the minimal dimension that can have a polytope whose k-skeleton is that of a product of simplices.

Graph cuts for curvature based image denoising.

PubMed

Bae, Egil; Shi, Juan; Tai, Xue-Cheng

2011-05-01

Minimization of total variation (TV) is a well-known method for image denoising. Recently, the relationship between TV minimization problems and binary MRF models has been much explored. This has resulted in some very efficient combinatorial optimization algorithms for the TV minimization problem in the discrete setting via graph cuts. To overcome limitations, such as staircasing effects, of the relatively simple TV model, variational models based upon higher order derivatives have been proposed. The Euler's elastica model is one such higher order model of central importance, which minimizes the curvature of all level lines in the image. Traditional numerical methods for minimizing the energy in such higher order models are complicated and computationally complex. In this paper, we will present an efficient minimization algorithm based upon graph cuts for minimizing the energy in the Euler's elastica model, by simplifying the problem to that of solving a sequence of easy graph representable problems. This sequence has connections to the gradient flow of the energy function, and converges to a minimum point. The numerical experiments show that our new approach is more effective in maintaining smooth visual results while preserving sharp features better than TV models.

State-Transition Structures in Physics and in Computation

NASA Astrophysics Data System (ADS)

Petri, C. A.

1982-12-01

In order to establish close connections between physical and computational processes, it is assumed that the concepts of “state” and of “transition” are acceptable both to physicists and to computer scientists, at least in an informal way. The aim of this paper is to propose formal definitions of state and transition elements on the basis of very low level physical concepts in such a way that (1) all physically possible computations can be described as embedded in physical processes; (2) the computational aspects of physical processes can be described on a well-defined level of abstraction; (3) the gulf between the continuous models of physics and the discrete models of computer science can be bridged by simple mathematical constructs which may be given a physical interpretation; (4) a combinatorial, nonstatistical definition of “information” can be given on low levels of abstraction which may serve as a basis to derive higher-level concepts of information, e.g., by a statistical or probabilistic approach. Conceivable practical consequences are discussed.

Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models.

PubMed

Luo, Li; Luo, Le; Zhang, Xinli; He, Xiaoli

2017-07-10

Accurate forecasting of hospital outpatient visits is beneficial for the reasonable planning and allocation of healthcare resource to meet the medical demands. In terms of the multiple attributes of daily outpatient visits, such as randomness, cyclicity and trend, time series methods, ARIMA, can be a good choice for outpatient visits forecasting. On the other hand, the hospital outpatient visits are also affected by the doctors' scheduling and the effects are not pure random. Thinking about the impure specialty, this paper presents a new forecasting model that takes cyclicity and the day of the week effect into consideration. We formulate a seasonal ARIMA (SARIMA) model on a daily time series and then a single exponential smoothing (SES) model on the day of the week time series, and finally establish a combinatorial model by modifying them. The models are applied to 1 year of daily visits data of urban outpatients in two internal medicine departments of a large hospital in Chengdu, for forecasting the daily outpatient visits about 1 week ahead. The proposed model is applied to forecast the cross-sectional data for 7 consecutive days of daily outpatient visits over an 8-weeks period based on 43 weeks of observation data during 1 year. The results show that the two single traditional models and the combinatorial model are simplicity of implementation and low computational intensiveness, whilst being appropriate for short-term forecast horizons. Furthermore, the combinatorial model can capture the comprehensive features of the time series data better. Combinatorial model can achieve better prediction performance than the single model, with lower residuals variance and small mean of residual errors which needs to be optimized deeply on the next research step.

Optimal weighted combinatorial forecasting model of QT dispersion of ECGs in Chinese adults.

PubMed

Wen, Zhang; Miao, Ge; Xinlei, Liu; Minyi, Cen

2016-07-01

This study aims to provide a scientific basis for unifying the reference value standard of QT dispersion of ECGs in Chinese adults. Three predictive models including regression model, principal component model, and artificial neural network model are combined to establish the optimal weighted combination model. The optimal weighted combination model and single model are verified and compared. Optimal weighted combinatorial model can reduce predicting risk of single model and improve the predicting precision. The reference value of geographical distribution of Chinese adults' QT dispersion was precisely made by using kriging methods. When geographical factors of a particular area are obtained, the reference value of QT dispersion of Chinese adults in this area can be estimated by using optimal weighted combinatorial model and reference value of the QT dispersion of Chinese adults anywhere in China can be obtained by using geographical distribution figure as well.

A Combinatorial Approach to Detecting Gene-Gene and Gene-Environment Interactions in Family Studies

PubMed Central

Lou, Xiang-Yang; Chen, Guo-Bo; Yan, Lei; Ma, Jennie Z.; Mangold, Jamie E.; Zhu, Jun; Elston, Robert C.; Li, Ming D.

2008-01-01

Widespread multifactor interactions present a significant challenge in determining risk factors of complex diseases. Several combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have emerged as a promising tool for better detecting gene-gene (G × G) and gene-environment (G × E) interactions. We recently developed a general combinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, which can entertain both qualitative and quantitative phenotypes and allows for both discrete and continuous covariates to detect G × G and G × E interactions in a sample of unrelated individuals. In this article, we report the development of an algorithm that can be used to study G × G and G × E interactions for family-based designs, called pedigree-based GMDR (PGMDR). Compared to the available method, our proposed method has several major improvements, including allowing for covariate adjustments and being applicable to arbitrary phenotypes, arbitrary pedigree structures, and arbitrary patterns of missing marker genotypes. Our Monte Carlo simulations provide evidence that the PGMDR method is superior in performance to identify epistatic loci compared to the MDR-pedigree disequilibrium test (PDT). Finally, we applied our proposed approach to a genetic data set on tobacco dependence and found a significant interaction between two taste receptor genes (i.e., TAS2R16 and TAS2R38) in affecting nicotine dependence. PMID:18834969

Integrating Multiple Data Sources for Combinatorial Marker Discovery: A Study in Tumorigenesis.

PubMed

Bandyopadhyay, Sanghamitra; Mallik, Saurav

2018-01-01

Identification of combinatorial markers from multiple data sources is a challenging task in bioinformatics. Here, we propose a novel computational framework for identifying significant combinatorial markers ( s) using both gene expression and methylation data. The gene expression and methylation data are integrated into a single continuous data as well as a (post-discretized) boolean data based on their intrinsic (i.e., inverse) relationship. A novel combined score of methylation and expression data (viz., ) is introduced which is computed on the integrated continuous data for identifying initial non-redundant set of genes. Thereafter, (maximal) frequent closed homogeneous genesets are identified using a well-known biclustering algorithm applied on the integrated boolean data of the determined non-redundant set of genes. A novel sample-based weighted support ( ) is then proposed that is consecutively calculated on the integrated boolean data of the determined non-redundant set of genes in order to identify the non-redundant significant genesets. The top few resulting genesets are identified as potential s. Since our proposed method generates a smaller number of significant non-redundant genesets than those by other popular methods, the method is much faster than the others. Application of the proposed technique on an expression and a methylation data for Uterine tumor or Prostate Carcinoma produces a set of significant combination of markers. We expect that such a combination of markers will produce lower false positives than individual markers.

Morphological Constraints on Cerebellar Granule Cell Combinatorial Diversity.

PubMed

Gilmer, Jesse I; Person, Abigail L

2017-12-13

Combinatorial expansion by the cerebellar granule cell layer (GCL) is fundamental to theories of cerebellar contributions to motor control and learning. Granule cells (GrCs) sample approximately four mossy fiber inputs and are thought to form a combinatorial code useful for pattern separation and learning. We constructed a spatially realistic model of the cerebellar GCL and examined how GCL architecture contributes to GrC combinatorial diversity. We found that GrC combinatorial diversity saturates quickly as mossy fiber input diversity increases, and that this saturation is in part a consequence of short dendrites, which limit access to diverse inputs and favor dense sampling of local inputs. This local sampling also produced GrCs that were combinatorially redundant, even when input diversity was extremely high. In addition, we found that mossy fiber clustering, which is a common anatomical pattern, also led to increased redundancy of GrC input combinations. We related this redundancy to hypothesized roles of temporal expansion of GrC information encoding in service of learned timing, and we show that GCL architecture produces GrC populations that support both temporal and combinatorial expansion. Finally, we used novel anatomical measurements from mice of either sex to inform modeling of sparse and filopodia-bearing mossy fibers, finding that these circuit features uniquely contribute to enhancing GrC diversification and redundancy. Our results complement information theoretic studies of granule layer structure and provide insight into the contributions of granule layer anatomical features to afferent mixing. SIGNIFICANCE STATEMENT Cerebellar granule cells are among the simplest neurons, with tiny somata and, on average, just four dendrites. These characteristics, along with their dense organization, inspired influential theoretical work on the granule cell layer as a combinatorial expander, where each granule cell represents a unique combination of inputs. Despite the centrality of these theories to cerebellar physiology, the degree of expansion supported by anatomically realistic patterns of inputs is unknown. Using modeling and anatomy, we show that realistic input patterns constrain combinatorial diversity by producing redundant combinations, which nevertheless could support temporal diversification of like combinations, suitable for learned timing. Our study suggests a neural substrate for producing high levels of both combinatorial and temporal diversity in the granule cell layer. Copyright © 2017 the authors 0270-6474/17/3712153-14$15.00/0.

PROBABILISTIC CROSS-IDENTIFICATION IN CROWDED FIELDS AS AN ASSIGNMENT PROBLEM

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

Budavári, Tamás; Basu, Amitabh, E-mail: budavari@jhu.edu, E-mail: basu.amitabh@jhu.edu

2016-10-01

One of the outstanding challenges of cross-identification is multiplicity: detections in crowded regions of the sky are often linked to more than one candidate associations of similar likelihoods. We map the resulting maximum likelihood partitioning to the fundamental assignment problem of discrete mathematics and efficiently solve the two-way catalog-level matching in the realm of combinatorial optimization using the so-called Hungarian algorithm. We introduce the method, demonstrate its performance in a mock universe where the true associations are known, and discuss the applicability of the new procedure to large surveys.

Landscape Encodings Enhance Optimization

PubMed Central

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

2012-01-01

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

Probabilistic Cross-identification in Crowded Fields as an Assignment Problem

NASA Astrophysics Data System (ADS)

Budavári, Tamás; Basu, Amitabh

2016-10-01

One of the outstanding challenges of cross-identification is multiplicity: detections in crowded regions of the sky are often linked to more than one candidate associations of similar likelihoods. We map the resulting maximum likelihood partitioning to the fundamental assignment problem of discrete mathematics and efficiently solve the two-way catalog-level matching in the realm of combinatorial optimization using the so-called Hungarian algorithm. We introduce the method, demonstrate its performance in a mock universe where the true associations are known, and discuss the applicability of the new procedure to large surveys.

Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching

NASA Astrophysics Data System (ADS)

Shen, Kaiming; Yu, Wei

2018-05-01

This two-part paper develops novel methodologies for using fractional programming (FP) techniques to design and optimize communication systems. Part I of this paper proposes a new quadratic transform for FP and treats its application for continuous optimization problems. In this Part II of the paper, we study discrete problems, such as those involving user scheduling, which are considerably more difficult to solve. Unlike the continuous problems, discrete or mixed discrete-continuous problems normally cannot be recast as convex problems. In contrast to the common heuristic of relaxing the discrete variables, this work reformulates the original problem in an FP form amenable to distributed combinatorial optimization. The paper illustrates this methodology by tackling the important and challenging problem of uplink coordinated multi-cell user scheduling in wireless cellular systems. Uplink scheduling is more challenging than downlink scheduling, because uplink user scheduling decisions significantly affect the interference pattern in nearby cells. Further, the discrete scheduling variable needs to be optimized jointly with continuous variables such as transmit power levels and beamformers. The main idea of the proposed FP approach is to decouple the interaction among the interfering links, thereby permitting a distributed and joint optimization of the discrete and continuous variables with provable convergence. The paper shows that the well-known weighted minimum mean-square-error (WMMSE) algorithm can also be derived from a particular use of FP; but our proposed FP-based method significantly outperforms WMMSE when discrete user scheduling variables are involved, both in term of run-time efficiency and optimizing results.

Implementing finite state machines in a computer-based teaching system

NASA Astrophysics Data System (ADS)

Hacker, Charles H.; Sitte, Renate

1999-09-01

Finite State Machines (FSM) are models for functions commonly implemented in digital circuits such as timers, remote controls, and vending machines. Teaching FSM is core in the curriculum of many university digital electronic or discrete mathematics subjects. Students often have difficulties grasping the theoretical concepts in the design and analysis of FSM. This has prompted the author to develop an MS-WindowsTM compatible software, WinState, that provides a tutorial style teaching aid for understanding the mechanisms of FSM. The animated computer screen is ideal for visually conveying the required design and analysis procedures. WinState complements other software for combinatorial logic previously developed by the author, and enhances the existing teaching package by adding sequential logic circuits. WinState enables the construction of a students own FSM, which can be simulated, to test the design for functionality and possible errors.

Novel Design Strategy for Checkpoint Kinase 2 Inhibitors Using Pharmacophore Modeling, Combinatorial Fusion, and Virtual Screening

PubMed Central

Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the BesttrainBesttest and FasttrainFasttest prediction results. The potential inhibitors were selected from NCI database by screening according to BesttrainBesttest + FasttrainFasttest prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study. PMID:24864236

Thermal analysis of combinatorial solid geometry models using SINDA

NASA Technical Reports Server (NTRS)

Gerencser, Diane; Radke, George; Introne, Rob; Klosterman, John; Miklosovic, Dave

1993-01-01

Algorithms have been developed using Monte Carlo techniques to determine the thermal network parameters necessary to perform a finite difference analysis on Combinatorial Solid Geometry (CSG) models. Orbital and laser fluxes as well as internal heat generation are modeled to facilitate satellite modeling. The results of the thermal calculations are used to model the infrared (IR) images of targets and assess target vulnerability. Sample analyses and validation are presented which demonstrate code products.

Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment.

PubMed

Minovski, Nikola; Perdih, Andrej; Solmajer, Tom

2012-05-01

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.

Composite solvers for linear saddle point problems arising from the incompressible Stokes equations with highly heterogeneous viscosity structure

NASA Astrophysics Data System (ADS)

Sanan, P.; Schnepp, S. M.; May, D.; Schenk, O.

2014-12-01

Geophysical applications require efficient forward models for non-linear Stokes flow on high resolution spatio-temporal domains. The bottleneck in applying the forward model is solving the linearized, discretized Stokes problem which takes the form of a large, indefinite (saddle point) linear system. Due to the heterogeniety of the effective viscosity in the elliptic operator, devising effective preconditioners for saddle point problems has proven challenging and highly problem-dependent. Nevertheless, at least three approaches show promise for preconditioning these difficult systems in an algorithmically scalable way using multigrid and/or domain decomposition techniques. The first is to work with a hierarchy of coarser or smaller saddle point problems. The second is to use the Schur complement method to decouple and sequentially solve for the pressure and velocity. The third is to use the Schur decomposition to devise preconditioners for the full operator. These involve sub-solves resembling inexact versions of the sequential solve. The choice of approach and sub-methods depends crucially on the motivating physics, the discretization, and available computational resources. Here we examine the performance trade-offs for preconditioning strategies applied to idealized models of mantle convection and lithospheric dynamics, characterized by large viscosity gradients. Due to the arbitrary topological structure of the viscosity field in geodynamical simulations, we utilize low order, inf-sup stable mixed finite element spatial discretizations which are suitable when sharp viscosity variations occur in element interiors. Particular attention is paid to possibilities within the decoupled and approximate Schur complement factorization-based monolithic approaches to leverage recently-developed flexible, communication-avoiding, and communication-hiding Krylov subspace methods in combination with `heavy' smoothers, which require solutions of large per-node sub-problems, well-suited to solution on hybrid computational clusters. To manage the combinatorial explosion of solver options (which include hybridizations of all the approaches mentioned above), we leverage the modularity of the PETSc library.

Microprocessor-based integration of microfluidic control for the implementation of automated sensor monitoring and multithreaded optimization algorithms.

PubMed

Ezra, Elishai; Maor, Idan; Bavli, Danny; Shalom, Itai; Levy, Gahl; Prill, Sebastian; Jaeger, Magnus S; Nahmias, Yaakov

2015-08-01

Microfluidic applications range from combinatorial synthesis to high throughput screening, with platforms integrating analog perfusion components, digitally controlled micro-valves and a range of sensors that demand a variety of communication protocols. Currently, discrete control units are used to regulate and monitor each component, resulting in scattered control interfaces that limit data integration and synchronization. Here, we present a microprocessor-based control unit, utilizing the MS Gadgeteer open framework that integrates all aspects of microfluidics through a high-current electronic circuit that supports and synchronizes digital and analog signals for perfusion components, pressure elements, and arbitrary sensor communication protocols using a plug-and-play interface. The control unit supports an integrated touch screen and TCP/IP interface that provides local and remote control of flow and data acquisition. To establish the ability of our control unit to integrate and synchronize complex microfluidic circuits we developed an equi-pressure combinatorial mixer. We demonstrate the generation of complex perfusion sequences, allowing the automated sampling, washing, and calibrating of an electrochemical lactate sensor continuously monitoring hepatocyte viability following exposure to the pesticide rotenone. Importantly, integration of an optical sensor allowed us to implement automated optimization protocols that require different computational challenges including: prioritized data structures in a genetic algorithm, distributed computational efforts in multiple-hill climbing searches and real-time realization of probabilistic models in simulated annealing. Our system offers a comprehensive solution for establishing optimization protocols and perfusion sequences in complex microfluidic circuits.

On the information content of discrete phylogenetic characters.

PubMed

Bordewich, Magnus; Deutschmann, Ina Maria; Fischer, Mareike; Kasbohm, Elisa; Semple, Charles; Steel, Mike

2017-12-16

Phylogenetic inference aims to reconstruct the evolutionary relationships of different species based on genetic (or other) data. Discrete characters are a particular type of data, which contain information on how the species should be grouped together. However, it has long been known that some characters contain more information than others. For instance, a character that assigns the same state to each species groups all of them together and so provides no insight into the relationships of the species considered. At the other extreme, a character that assigns a different state to each species also conveys no phylogenetic signal. In this manuscript, we study a natural combinatorial measure of the information content of an individual character and analyse properties of characters that provide the maximum phylogenetic information, particularly, the number of states such a character uses and how the different states have to be distributed among the species or taxa of the phylogenetic tree.

Quadratic constrained mixed discrete optimization with an adiabatic quantum optimizer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh; Jacobson, N. Tobias; Moussa, Jonathan E.; Frankel, Steven H.; Kais, Sabre

2014-07-01

We extend the family of problems that may be implemented on an adiabatic quantum optimizer (AQO). When a quadratic optimization problem has at least one set of discrete controls and the constraints are linear, we call this a quadratic constrained mixed discrete optimization (QCMDO) problem. QCMDO problems are NP-hard, and no efficient classical algorithm for their solution is known. Included in the class of QCMDO problems are combinatorial optimization problems constrained by a linear partial differential equation (PDE) or system of linear PDEs. An essential complication commonly encountered in solving this type of problem is that the linear constraint may introduce many intermediate continuous variables into the optimization while the computational cost grows exponentially with problem size. We resolve this difficulty by developing a constructive mapping from QCMDO to quadratic unconstrained binary optimization (QUBO) such that the size of the QUBO problem depends only on the number of discrete control variables. With a suitable embedding, taking into account the physical constraints of the realizable coupling graph, the resulting QUBO problem can be implemented on an existing AQO. The mapping itself is efficient, scaling cubically with the number of continuous variables in the general case and linearly in the PDE case if an efficient preconditioner is available.

Combinatorial explosion in model gene networks

NASA Astrophysics Data System (ADS)

Edwards, R.; Glass, L.

2000-09-01

The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such networks are extremely rich and they offer novel ways to think about how mutations can alter dynamics.

Combinatorial explosion in model gene networks.

PubMed

Edwards, R.; Glass, L.

2000-09-01

The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such networks are extremely rich and they offer novel ways to think about how mutations can alter dynamics. (c) 2000 American Institute of Physics.

Discovery of Antibiotics-derived Polymers for Gene Delivery using Combinatorial Synthesis and Cheminformatics Modeling

PubMed Central

Potta, Thrimoorthy; Zhen, Zhuo; Grandhi, Taraka Sai Pavan; Christensen, Matthew D.; Ramos, James; Breneman, Curt M.; Rege, Kaushal

2014-01-01

We describe the combinatorial synthesis and cheminformatics modeling of aminoglycoside antibiotics-derived polymers for transgene delivery and expression. Fifty-six polymers were synthesized by polymerizing aminoglycosides with diglycidyl ether cross-linkers. Parallel screening resulted in identification of several lead polymers that resulted in high transgene expression levels in cells. The role of polymer physicochemical properties in determining efficacy of transgene expression was investigated using Quantitative Structure-Activity Relationship (QSAR) cheminformatics models based on Support Vector Regression (SVR) and ‘building block’ polymer structures. The QSAR model exhibited high predictive ability, and investigation of descriptors in the model, using molecular visualization and correlation plots, indicated that physicochemical attributes related to both, aminoglycosides and diglycidyl ethers facilitated transgene expression. This work synergistically combines combinatorial synthesis and parallel screening with cheminformatics-based QSAR models for discovery and physicochemical elucidation of effective antibiotics-derived polymers for transgene delivery in medicine and biotechnology. PMID:24331709

Identification of combinatorial drug regimens for treatment of Huntington's disease using Drosophila

NASA Astrophysics Data System (ADS)

Agrawal, Namita; Pallos, Judit; Slepko, Natalia; Apostol, Barbara L.; Bodai, Laszlo; Chang, Ling-Wen; Chiang, Ann-Shyn; Michels Thompson, Leslie; Marsh, J. Lawrence

2005-03-01

We explore the hypothesis that pathology of Huntington's disease involves multiple cellular mechanisms whose contributions to disease are incrementally additive or synergistic. We provide evidence that the photoreceptor neuron degeneration seen in flies expressing mutant human huntingtin correlates with widespread degenerative events in the Drosophila CNS. We use a Drosophila Huntington's disease model to establish dose regimens and protocols to assess the effectiveness of drug combinations used at low threshold concentrations. These proof of principle studies identify at least two potential combinatorial treatment options and illustrate a rapid and cost-effective paradigm for testing and optimizing combinatorial drug therapies while reducing side effects for patients with neurodegenerative disease. The potential for using prescreening in Drosophila to inform combinatorial therapies that are most likely to be effective for testing in mammals is discussed. combinatorial treatments | neurodegeneration

An Onto-Semiotic Analysis of Combinatorial Problems and the Solving Processes by University Students

ERIC Educational Resources Information Center

Godino, Juan D.; Batanero, Carmen; Roa, Rafael

2005-01-01

In this paper we describe an ontological and semiotic model for mathematical knowledge, using elementary combinatorics as an example. We then apply this model to analyze the solving process of some combinatorial problems by students with high mathematical training, and show its utility in providing a semiotic explanation for the difficulty of…

Novel design strategy for checkpoint kinase 2 inhibitors using pharmacophore modeling, combinatorial fusion, and virtual screening.

PubMed

Lin, Chun-Yuan; Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.

Computer Description of Black Hawk Helicopter

DTIC Science & Technology

1979-06-01

Model Combinatorial Geometry Models Black Hawk Helicopter Helicopter GIFT Computer Code Geometric Description of Targets 20. ABSTRACT...description was made using the technique of combinatorial geometry (COM-GEOM) and will be used as input to the GIFT computer code which generates Tliic...rnHp The data used bv the COVART comtmter code was eenerated bv the Geometric Information for Targets ( GIFT )Z computer code. This report documents

A Model of Students' Combinatorial Thinking

ERIC Educational Resources Information Center

Lockwood, Elise

2013-01-01

Combinatorial topics have become increasingly prevalent in K-12 and undergraduate curricula, yet research on combinatorics education indicates that students face difficulties when solving counting problems. The research community has not yet addressed students' ways of thinking at a level that facilitates deeper understanding of how students…

Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior

PubMed Central

Kochemazov, Stepan; Semenov, Alexander

2014-01-01

In this paper, we propose an approach for modeling and analysis of a number of phenomena of collective behavior. By collectives we mean multi-agent systems that transition from one state to another at discrete moments of time. The behavior of a member of a collective (agent) is called conforming if the opinion of this agent at current time moment conforms to the opinion of some other agents at the previous time moment. We presume that at each moment of time every agent makes a decision by choosing from the set (where 1-decision corresponds to action and 0-decision corresponds to inaction). In our approach we model collective behavior with synchronous Boolean networks. We presume that in a network there can be agents that act at every moment of time. Such agents are called instigators. Also there can be agents that never act. Such agents are called loyalists. Agents that are neither instigators nor loyalists are called simple agents. We study two combinatorial problems. The first problem is to find a disposition of instigators that in several time moments transforms a network from a state where the majority of simple agents are inactive to a state with the majority of active agents. The second problem is to find a disposition of loyalists that returns the network to a state with the majority of inactive agents. Similar problems are studied for networks in which simple agents demonstrate the contrary to conforming behavior that we call anticonforming. We obtained several theoretical results regarding the behavior of collectives of agents with conforming or anticonforming behavior. In computational experiments we solved the described problems for randomly generated networks with several hundred vertices. We reduced corresponding combinatorial problems to the Boolean satisfiability problem (SAT) and used modern SAT solvers to solve the instances obtained. PMID:25526612

Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors

PubMed Central

Zhou, Nannan; Xu, Yuan; Liu, Xian; Wang, Yulan; Peng, Jianlong; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang

2015-01-01

The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds. In this study, a combinatorial three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed based on previously reported FGFR1 inhibitors with diverse structural skeletons. This model was evaluated for its prediction performance on a diverse test set containing 232 FGFR inhibitors, and it yielded a SD value of 0.75 pIC50 units from measured inhibition affinities and a Pearson’s correlation coefficient R2 of 0.53. This result suggests that the combinatorial 3D-QSAR model could be used to search for new FGFR1 hit structures and predict their potential activity. To further evaluate the performance of the model, a decoy set validation was used to measure the efficiency of the model by calculating EF (enrichment factor). Based on the combinatorial pharmacophore model, a virtual screening against SPECS database was performed. Nineteen novel active compounds were successfully identified, which provide new chemical starting points for further structural optimization of FGFR1 inhibitors. PMID:26110383

RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

PubMed Central

Ellington, Roni; Wachira, James

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems. PMID:20810968

RNA secondary structure prediction by using discrete mathematics: an interdisciplinary research experience for undergraduate students.

PubMed

Ellington, Roni; Wachira, James; Nkwanta, Asamoah

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems.

Combinatorial Histone Acetylation Patterns Are Generated by Motif-Specific Reactions.

PubMed

Blasi, Thomas; Feller, Christian; Feigelman, Justin; Hasenauer, Jan; Imhof, Axel; Theis, Fabian J; Becker, Peter B; Marr, Carsten

2016-01-27

Post-translational modifications (PTMs) are pivotal to cellular information processing, but how combinatorial PTM patterns ("motifs") are set remains elusive. We develop a computational framework, which we provide as open source code, to investigate the design principles generating the combinatorial acetylation patterns on histone H4 in Drosophila melanogaster. We find that models assuming purely unspecific or lysine site-specific acetylation rates were insufficient to explain the experimentally determined motif abundances. Rather, these abundances were best described by an ensemble of models with acetylation rates that were specific to motifs. The model ensemble converged upon four acetylation pathways; we validated three of these using independent data from a systematic enzyme depletion study. Our findings suggest that histone acetylation patterns originate through specific pathways involving motif-specific acetylation activity. Copyright © 2016 Elsevier Inc. All rights reserved.

Exact model reduction of combinatorial reaction networks

PubMed Central

Conzelmann, Holger; Fey, Dirk; Gilles, Ernst D

2008-01-01

Background Receptors and scaffold proteins usually possess a high number of distinct binding domains inducing the formation of large multiprotein signaling complexes. Due to combinatorial reasons the number of distinguishable species grows exponentially with the number of binding domains and can easily reach several millions. Even by including only a limited number of components and binding domains the resulting models are very large and hardly manageable. A novel model reduction technique allows the significant reduction and modularization of these models. Results We introduce methods that extend and complete the already introduced approach. For instance, we provide techniques to handle the formation of multi-scaffold complexes as well as receptor dimerization. Furthermore, we discuss a new modeling approach that allows the direct generation of exactly reduced model structures. The developed methods are used to reduce a model of EGF and insulin receptor crosstalk comprising 5,182 ordinary differential equations (ODEs) to a model with 87 ODEs. Conclusion The methods, presented in this contribution, significantly enhance the available methods to exactly reduce models of combinatorial reaction networks. PMID:18755034

Applications of Combinatorial Programming to Data Analysis: The Traveling Salesman and Related Problems

ERIC Educational Resources Information Center

Hubert, Lawrence J.; Baker, Frank B.

1978-01-01

The "Traveling Salesman" and similar combinatorial programming tasks encountered in operations research are discussed as possible data analysis models in psychology, for example, in developmental scaling, Guttman scaling, profile smoothing, and data array clustering. A short overview of various computational approaches from this area of…

A phase transition in energy-filtered RNA secondary structures.

PubMed

Han, Hillary S W; Reidys, Christian M

2012-10-01

In this article we study the effect of energy parameters on minimum free energy (mfe) RNA secondary structures. Employing a simplified combinatorial energy model that is only dependent on the diagram representation and is not sequence-specific, we prove the following dichotomy result. Mfe structures derived via the Turner energy parameters contain only finitely many complex irreducible substructures, and just minor parameter changes produce a class of mfe structures that contain a large number of small irreducibles. We localize the exact point at which the distribution of irreducibles experiences this phase transition from a discrete limit to a central limit distribution and, subsequently, put our result into the context of quantifying the effect of sparsification of the folding of these respective mfe structures. We show that the sparsification of realistic mfe structures leads to a constant time and space reduction, and that the sparsification of the folding of structures with modified parameters leads to a linear time and space reduction. We, furthermore, identify the limit distribution at the phase transition as a Rayleigh distribution.

Generalised Spin Dynamics and Induced Bounds of Automorphic [A]nX, [AX]n NMR Systems via Dual Tensorial Sets: An Invariant Cardinality Role for CFP

NASA Astrophysics Data System (ADS)

Temme, Francis P.

For uniform spins and their indistinguishable point sets of tensorial bases defining automorphic group-based Liouvillian NMR spin dynamics, the role of recursively-derived coefficients of fractional parentage (CFP) bijections and Schur duality-defined CFP(0)(n) ≡ ¦GI¦(n) group invariant cardinality is central both to understanding the impact of time-reversal invariance(TRI) spin physics, and to analysis as density-matrix formalisms over democratic recoupled (DR) dual tensorial sets, {T{ṽ}k(11.1)(SU2 × ln)}. Over abstract spin space, these tensorial sets are (ṽ) invariant-theoretic forms which lie beyond the Liouvillian graph recoupling and Racah-forms envisaged by Sanctuary [1]. This is a direct consequence of the dominance of the ln group. It leads to new views on the value of projective group actions as mappings over specialised Liouvillian carrier spaces, and on the need for the replacement of Racah-Wigner (R-W) orthogonality for distinct point sets, by criteria based on explicit properties of invariants [J. Phys.: Math. & Theor. A 41, 015210 (2008)] for multiple invariant systems. Ũ × P group actions over disjoint (L) carrier subspaces, leading to exclusively combinatorial views of the nature of quantal completeness for indistinguishable point-based tensorial sets. Such generalised invariant-theoretic approaches lie beyond the range of Lévi-Civitá generator views, or of Lévy-Leblond and Lévy-Nahas [9] with its additional cyclic-commutators defining mono-invariant DR forms. Comparison of the latter with generalised multiple-invariant techniques provides an answer to the question of precisely why [A]n≥4(X) and [AX]n≥4 NMR system spin dynamics are not ameniable to conventional R-W analysis of recoupled discrete-point tensorial systems. Our work augments earlier Hilbert space views, both of Louck and Biedenharn [21] on boson pattern projective mapping, and of Corio [19]. The roles of recent ln group action and (λ ⊢ n)-Schur combinatorial concepts, as well as of polyhedral-combinatorial modelling over invariance algebras, contribute significantly to our understanding of invariant-based techniques of Liouville dual tensorial sets for automorphic NMR spin physics.1

Emergent latent symbol systems in recurrent neural networks

NASA Astrophysics Data System (ADS)

Monner, Derek; Reggia, James A.

2012-12-01

Fodor and Pylyshyn [(1988). Connectionism and cognitive architecture: A critical analysis. Cognition, 28(1-2), 3-71] famously argued that neural networks cannot behave systematically short of implementing a combinatorial symbol system. A recent response from Frank et al. [(2009). Connectionist semantic systematicity. Cognition, 110(3), 358-379] claimed to have trained a neural network to behave systematically without implementing a symbol system and without any in-built predisposition towards combinatorial representations. We believe systems like theirs may in fact implement a symbol system on a deeper and more interesting level: one where the symbols are latent - not visible at the level of network structure. In order to illustrate this possibility, we demonstrate our own recurrent neural network that learns to understand sentence-level language in terms of a scene. We demonstrate our model's learned understanding by testing it on novel sentences and scenes. By paring down our model into an architecturally minimal version, we demonstrate how it supports combinatorial computation over distributed representations by using the associative memory operations of Vector Symbolic Architectures. Knowledge of the model's memory scheme gives us tools to explain its errors and construct superior future models. We show how the model designs and manipulates a latent symbol system in which the combinatorial symbols are patterns of activation distributed across the layers of a neural network, instantiating a hybrid of classical symbolic and connectionist representations that combines advantages of both.

Signal dimensionality and the emergence of combinatorial structure.

PubMed

Little, Hannah; Eryılmaz, Kerem; de Boer, Bart

2017-11-01

In language, a small number of meaningless building blocks can be combined into an unlimited set of meaningful utterances. This is known as combinatorial structure. One hypothesis for the initial emergence of combinatorial structure in language is that recombining elements of signals solves the problem of overcrowding in a signal space. Another hypothesis is that iconicity may impede the emergence of combinatorial structure. However, how these two hypotheses relate to each other is not often discussed. In this paper, we explore how signal space dimensionality relates to both overcrowding in the signal space and iconicity. We use an artificial signalling experiment to test whether a signal space and a meaning space having similar topologies will generate an iconic system and whether, when the topologies differ, the emergence of combinatorially structured signals is facilitated. In our experiments, signals are created from participants' hand movements, which are measured using an infrared sensor. We found that participants take advantage of iconic signal-meaning mappings where possible. Further, we use trajectory predictability, measures of variance, and Hidden Markov Models to measure the use of structure within the signals produced and found that when topologies do not match, then there is more evidence of combinatorial structure. The results from these experiments are interpreted in the context of the differences between the emergence of combinatorial structure in different linguistic modalities (speech and sign). Copyright © 2017 Elsevier B.V. All rights reserved.

Tanglegrams: A Reduction Tool for Mathematical Phylogenetics.

PubMed

Matsen, Frederick A; Billey, Sara C; Kas, Arnold; Konvalinka, Matjaz

2018-01-01

Many discrete mathematics problems in phylogenetics are defined in terms of the relative labeling of pairs of leaf-labeled trees. These relative labelings are naturally formalized as tanglegrams, which have previously been an object of study in coevolutionary analysis. Although there has been considerable work on planar drawings of tanglegrams, they have not been fully explored as combinatorial objects until recently. In this paper, we describe how many discrete mathematical questions on trees "factor" through a problem on tanglegrams, and how understanding that factoring can simplify analysis. Depending on the problem, it may be useful to consider a unordered version of tanglegrams, and/or their unrooted counterparts. For all of these definitions, we show how the isomorphism types of tanglegrams can be understood in terms of double cosets of the symmetric group, and we investigate their automorphisms. Understanding tanglegrams better will isolate the distinct problems on leaf-labeled pairs of trees and reveal natural symmetries of spaces associated with such problems.

Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method

PubMed Central

Besalú, Emili

2016-01-01

The Superposing Significant Interaction Rules (SSIR) method is described. It is a general combinatorial and symbolic procedure able to rank compounds belonging to combinatorial analogue series. The procedure generates structure-activity relationship (SAR) models and also serves as an inverse SAR tool. The method is fast and can deal with large databases. SSIR operates from statistical significances calculated from the available library of compounds and according to the previously attached molecular labels of interest or non-interest. The required symbolic codification allows dealing with almost any combinatorial data set, even in a confidential manner, if desired. The application example categorizes molecules as binding or non-binding, and consensus ranking SAR models are generated from training and two distinct cross-validation methods: leave-one-out and balanced leave-two-out (BL2O), the latter being suited for the treatment of binary properties. PMID:27240346

Graph Theory

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

Sanfilippo, Antonio P.

2005-12-27

Graph theory is a branch of discrete combinatorial mathematics that studies the properties of graphs. The theory was pioneered by the Swiss mathematician Leonhard Euler in the 18th century, commenced its formal development during the second half of the 19th century, and has witnessed substantial growth during the last seventy years, with applications in areas as diverse as engineering, computer science, physics, sociology, chemistry and biology. Graph theory has also had a strong impact in computational linguistics by providing the foundations for the theory of features structures that has emerged as one of the most widely used frameworks for themore » representation of grammar formalisms.« less

An application of different dioids in public key cryptography

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

Durcheva, Mariana I., E-mail: mdurcheva66@gmail.com

2014-11-18

Dioids provide a natural framework for analyzing a broad class of discrete event dynamical systems such as the design and analysis of bus and railway timetables, scheduling of high-throughput industrial processes, solution of combinatorial optimization problems, the analysis and improvement of flow systems in communication networks. They have appeared in several branches of mathematics such as functional analysis, optimization, stochastic systems and dynamic programming, tropical geometry, fuzzy logic. In this paper we show how to involve dioids in public key cryptography. The main goal is to create key – exchange protocols based on dioids. Additionally the digital signature scheme ismore » presented.« less

Novel Modeling of Combinatorial miRNA Targeting Identifies SNP with Potential Role in Bone Density

PubMed Central

Coronnello, Claudia; Hartmaier, Ryan; Arora, Arshi; Huleihel, Luai; Pandit, Kusum V.; Bais, Abha S.; Butterworth, Michael; Kaminski, Naftali; Stormo, Gary D.; Oesterreich, Steffi; Benos, Panayiotis V.

2012-01-01

MicroRNAs (miRNAs) are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting), a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD) in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential tool for miRNA-related studies. PMID:23284279

Using Combinatorial Approach to Improve Students' Learning of the Distributive Law and Multiplicative Identities

ERIC Educational Resources Information Center

Tsai, Yu-Ling; Chang, Ching-Kuch

2009-01-01

This article reports an alternative approach, called the combinatorial model, to learning multiplicative identities, and investigates the effects of implementing results for this alternative approach. Based on realistic mathematics education theory, the new instructional materials or modules of the new approach were developed by the authors. From…

A combinatorial approach to protein docking with flexible side chains.

PubMed

Althaus, Ernst; Kohlbacher, Oliver; Lenhof, Hans-Peter; Müller, Peter

2002-01-01

Rigid-body docking approaches are not sufficient to predict the structure of a protein complex from the unbound (native) structures of the two proteins. Accounting for side chain flexibility is an important step towards fully flexible protein docking. This work describes an approach that allows conformational flexibility for the side chains while keeping the protein backbone rigid. Starting from candidates created by a rigid-docking algorithm, we demangle the side chains of the docking site, thus creating reasonable approximations of the true complex structure. These structures are ranked with respect to the binding free energy. We present two new techniques for side chain demangling. Both approaches are based on a discrete representation of the side chain conformational space by the use of a rotamer library. This leads to a combinatorial optimization problem. For the solution of this problem, we propose a fast heuristic approach and an exact, albeit slower, method that uses branch-and-cut techniques. As a test set, we use the unbound structures of three proteases and the corresponding protein inhibitors. For each of the examples, the highest-ranking conformation produced was a good approximation of the true complex structure.

Synthesizing optimal waste blends

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

Narayan, V.; Diwekar, W.M.; Hoza, M.

Vitrification of tank wastes to form glass is a technique that will be used for the disposal of high-level waste at Hanford. Process and storage economics show that minimizing the total number of glass logs produced is the key to keeping cost as low as possible. The amount of glass produced can be reduced by blending of the wastes. The optimal way to combine the tanks to minimize the vole of glass can be determined from a discrete blend calculation. However, this problem results in a combinatorial explosion as the number of tanks increases. Moreover, the property constraints make thismore » problem highly nonconvex where many algorithms get trapped in local minima. In this paper the authors examine the use of different combinatorial optimization approaches to solve this problem. A two-stage approach using a combination of simulated annealing and nonlinear programming (NLP) is developed. The results of different methods such as the heuristics approach based on human knowledge and judgment, the mixed integer nonlinear programming (MINLP) approach with GAMS, and branch and bound with lower bound derived from the structure of the given blending problem are compared with this coupled simulated annealing and NLP approach.« less

Coarse-grained molecular dynamics simulations of depletion-induced interactions for soft matter systems

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

Shendruk, Tyler N., E-mail: tyler.shendruk@physics.ox.ac.uk; Bertrand, Martin; Harden, James L.

2014-12-28

Given the ubiquity of depletion effects in biological and other soft matter systems, it is desirable to have coarse-grained Molecular Dynamics (MD) simulation approaches appropriate for the study of complex systems. This paper examines the use of two common truncated Lennard-Jones (Weeks-Chandler-Andersen (WCA)) potentials to describe a pair of colloidal particles in a thermal bath of depletants. The shifted-WCA model is the steeper of the two repulsive potentials considered, while the combinatorial-WCA model is the softer. It is found that the depletion-induced well depth for the combinatorial-WCA model is significantly deeper than the shifted-WCA model because the resulting overlap ofmore » the colloids yields extra accessible volume for depletants. For both shifted- and combinatorial-WCA simulations, the second virial coefficients and pair potentials between colloids are demonstrated to be well approximated by the Morphometric Thermodynamics (MT) model. This agreement suggests that the presence of depletants can be accurately modelled in MD simulations by implicitly including them through simple, analytical MT forms for depletion-induced interactions. Although both WCA potentials are found to be effective generic coarse-grained simulation approaches for studying depletion effects in complicated soft matter systems, combinatorial-WCA is the more efficient approach as depletion effects are enhanced at lower depletant densities. The findings indicate that for soft matter systems that are better modelled by potentials with some compressibility, predictions from hard-sphere systems could greatly underestimate the magnitude of depletion effects at a given depletant density.« less

Research on parallel combinatory spread spectrum communication system with double information matching

NASA Astrophysics Data System (ADS)

Xue, Wei; Wang, Qi; Wang, Tianyu

2018-04-01

This paper presents an improved parallel combinatory spread spectrum (PC/SS) communication system with the method of double information matching (DIM). Compared with conventional PC/SS system, the new model inherits the advantage of high transmission speed, large information capacity and high security. Besides, the problem traditional system will face is the high bit error rate (BER) and since its data-sequence mapping algorithm. Hence the new model presented shows lower BER and higher efficiency by its optimization of mapping algorithm.

Sparse signals recovered by non-convex penalty in quasi-linear systems.

PubMed

Cui, Angang; Li, Haiyang; Wen, Meng; Peng, Jigen

2018-01-01

The goal of compressed sensing is to reconstruct a sparse signal under a few linear measurements far less than the dimension of the ambient space of the signal. However, many real-life applications in physics and biomedical sciences carry some strongly nonlinear structures, and the linear model is no longer suitable. Compared with the compressed sensing under the linear circumstance, this nonlinear compressed sensing is much more difficult, in fact also NP-hard, combinatorial problem, because of the discrete and discontinuous nature of the [Formula: see text]-norm and the nonlinearity. In order to get a convenience for sparse signal recovery, we set the nonlinear models have a smooth quasi-linear nature in this paper, and study a non-convex fraction function [Formula: see text] in this quasi-linear compressed sensing. We propose an iterative fraction thresholding algorithm to solve the regularization problem [Formula: see text] for all [Formula: see text]. With the change of parameter [Formula: see text], our algorithm could get a promising result, which is one of the advantages for our algorithm compared with some state-of-art algorithms. Numerical experiments show that our method performs much better than some state-of-the-art methods.

Homology groups for particles on one-connected graphs

NASA Astrophysics Data System (ADS)

MaciÄ Żek, Tomasz; Sawicki, Adam

2017-06-01

We present a mathematical framework for describing the topology of configuration spaces for particles on one-connected graphs. In particular, we compute the homology groups over integers for different classes of one-connected graphs. Our approach is based on some fundamental combinatorial properties of the configuration spaces, Mayer-Vietoris sequences for different parts of configuration spaces, and some limited use of discrete Morse theory. As one of the results, we derive the closed-form formulae for ranks of the homology groups for indistinguishable particles on tree graphs. We also give a detailed discussion of the second homology group of the configuration space of both distinguishable and indistinguishable particles. Our motivation is the search for new kinds of quantum statistics.

A programmable microfluidic static droplet array for droplet generation, transportation, fusion, storage, and retrieval.

PubMed

Jin, Si Hyung; Jeong, Heon-Ho; Lee, Byungjin; Lee, Sung Sik; Lee, Chang-Soo

2015-01-01

We present a programmable microfluidic static droplet array (SDA) device that can perform user-defined multistep combinatorial protocols. It combines the passive storage of aqueous droplets without any external control with integrated microvalves for discrete sample dispensing and dispersion-free unit operation. The addressable picoliter-volume reaction is systematically achieved by consecutively merging programmable sequences of reagent droplets. The SDA device is remarkably reusable and able to perform identical enzyme kinetic experiments at least 30 times via automated cross-contamination-free removal of droplets from individual hydrodynamic traps. Taking all these features together, this programmable and reusable universal SDA device will be a general microfluidic platform that can be reprogrammed for multiple applications.

Learning to Predict Combinatorial Structures

NASA Astrophysics Data System (ADS)

Vembu, Shankar

2009-12-01

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. For several combinatorial structures, including cycles, partially ordered sets, permutations and other graph classes, these assumptions do not hold. In this thesis, we address the problem of designing learning algorithms for predicting combinatorial structures by introducing two new assumptions: (i) The first assumption is that a particular counting problem can be solved efficiently. The consequence is a generalisation of the classical ridge regression for structured prediction. (ii) The second assumption is that a particular sampling problem can be solved efficiently. The consequence is a new technique for designing and analysing probabilistic structured prediction models. These results can be applied to solve several complex learning problems including but not limited to multi-label classification, multi-category hierarchical classification, and label ranking.

On the suitability of different representations of solid catalysts for combinatorial library design by genetic algorithms.

PubMed

Gobin, Oliver C; Schüth, Ferdi

2008-01-01

Genetic algorithms are widely used to solve and optimize combinatorial problems and are more often applied for library design in combinatorial chemistry. Because of their flexibility, however, their implementation can be challenging. In this study, the influence of the representation of solid catalysts on the performance of genetic algorithms was systematically investigated on the basis of a new, constrained, multiobjective, combinatorial test problem with properties common to problems in combinatorial materials science. Constraints were satisfied by penalty functions, repair algorithms, or special representations. The tests were performed using three state-of-the-art evolutionary multiobjective algorithms by performing 100 optimization runs for each algorithm and test case. Experimental data obtained during the optimization of a noble metal-free solid catalyst system active in the selective catalytic reduction of nitric oxide with propene was used to build up a predictive model to validate the results of the theoretical test problem. A significant influence of the representation on the optimization performance was observed. Binary encodings were found to be the preferred encoding in most of the cases, and depending on the experimental test unit, repair algorithms or penalty functions performed best.

Core and region-enriched networks of behaviorally regulated genes and the singing genome

PubMed Central

Whitney, Osceola; Pfenning, Andreas R.; Howard, Jason T.; Blatti, Charles A; Liu, Fang; Ward, James M.; Wang, Rui; Audet, Jean-Nicolas; Kellis, Manolis; Mukherjee, Sayan; Sinha, Saurabh; Hartemink, Alexander J.; West, Anne E.; Jarvis, Erich D.

2015-01-01

Songbirds represent an important model organism for elucidating molecular mechanisms that link genes with complex behaviors, in part because they have discrete vocal learning circuits that have parallels with those that mediate human speech. We found that ~10% of the genes in the avian genome were regulated by singing, and we found a striking regional diversity of both basal and singing-induced programs in the four key song nuclei of the zebra finch, a vocal learning songbird. The region-enriched patterns were a result of distinct combinations of region-enriched transcription factors (TFs), their binding motifs, and presinging acetylation of histone 3 at lysine 27 (H3K27ac) enhancer activity in the regulatory regions of the associated genes. RNA interference manipulations validated the role of the calcium-response transcription factor (CaRF) in regulating genes preferentially expressed in specific song nuclei in response to singing. Thus, differential combinatorial binding of a small group of activity-regulated TFs and predefined epigenetic enhancer activity influences the anatomical diversity of behaviorally regulated gene networks. PMID:25504732

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4

NASA Astrophysics Data System (ADS)

Evensen, Erik; Joseph-McCarthy, Diane; Weiss, Gregory A.; Schreiber, Stuart L.; Karplus, Martin

2007-07-01

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.

A combinatorial perspective of the protein inference problem.

PubMed

Yang, Chao; He, Zengyou; Yu, Weichuan

2013-01-01

In a shotgun proteomics experiment, proteins are the most biologically meaningful output. The success of proteomics studies depends on the ability to accurately and efficiently identify proteins. Many methods have been proposed to facilitate the identification of proteins from peptide identification results. However, the relationship between protein identification and peptide identification has not been thoroughly explained before. In this paper, we devote ourselves to a combinatorial perspective of the protein inference problem. We employ combinatorial mathematics to calculate the conditional protein probabilities (protein probability means the probability that a protein is correctly identified) under three assumptions, which lead to a lower bound, an upper bound, and an empirical estimation of protein probabilities, respectively. The combinatorial perspective enables us to obtain an analytical expression for protein inference. Our method achieves comparable results with ProteinProphet in a more efficient manner in experiments on two data sets of standard protein mixtures and two data sets of real samples. Based on our model, we study the impact of unique peptides and degenerate peptides (degenerate peptides are peptides shared by at least two proteins) on protein probabilities. Meanwhile, we also study the relationship between our model and ProteinProphet. We name our program ProteinInfer. Its Java source code, our supplementary document and experimental results are available at: >http://bioinformatics.ust.hk/proteininfer.

Seven Modeling Perspectives on Teaching and Learning: Some Interrelations and Cognitive Effects

ERIC Educational Resources Information Center

Easley, J. A., Jr.

1977-01-01

The categories of models associated with the seven perspectives are designated as combinatorial models, sampling models, cybernetic models, game models, critical thinking models, ordinary language analysis models, and dynamic structural models. (DAG)

Energy Landscapes for the Self-Assembly of Supramolecular Polyhedra

NASA Astrophysics Data System (ADS)

Russell, Emily R.; Menon, Govind

2016-06-01

We develop a mathematical model for the energy landscape of polyhedral supramolecular cages recently synthesized by self-assembly (Sun et al. in Science 328:1144-1147, 2010). Our model includes two essential features of the experiment: (1) geometry of the organic ligands and metallic ions; and (2) combinatorics. The molecular geometry is used to introduce an energy that favors square-planar vertices (modeling {Pd}^{2+} ions) and bent edges with one of two preferred opening angles (modeling boomerang-shaped ligands of two types). The combinatorics of the model involve two-colorings of edges of polyhedra with four-valent vertices. The set of such two-colorings, quotiented by the octahedral symmetry group, has a natural graph structure and is called the combinatorial configuration space. The energy landscape of our model is the energy of each state in the combinatorial configuration space. The challenge in the computation of the energy landscape is a combinatorial explosion in the number of two-colorings of edges. We describe sampling methods based on the symmetries of the configurations and connectivity of the configuration graph. When the two preferred opening angles encompass the geometrically ideal angle, the energy landscape exhibits a very low-energy minimum for the most symmetric configuration at equal mixing of the two angles, even when the average opening angle does not match the ideal angle.

On Singularities and Black Holes in Combination-Driven Models of Technological Innovation Networks

PubMed Central

Solé, Ricard; Amor, Daniel R.; Valverde, Sergi

2016-01-01

It has been suggested that innovations occur mainly by combination: the more inventions accumulate, the higher the probability that new inventions are obtained from previous designs. Additionally, it has been conjectured that the combinatorial nature of innovations naturally leads to a singularity: at some finite time, the number of innovations should diverge. Although these ideas are certainly appealing, no general models have been yet developed to test the conditions under which combinatorial technology should become explosive. Here we present a generalised model of technological evolution that takes into account two major properties: the number of previous technologies needed to create a novel one and how rapidly technology ages. Two different models of combinatorial growth are considered, involving different forms of ageing. When long-range memory is used and thus old inventions are available for novel innovations, singularities can emerge under some conditions with two phases separated by a critical boundary. If the ageing has a characteristic time scale, it is shown that no singularities will be observed. Instead, a “black hole” of old innovations appears and expands in time, making the rate of invention creation slow down into a linear regime. PMID:26821277

On Singularities and Black Holes in Combination-Driven Models of Technological Innovation Networks.

PubMed

Solé, Ricard; Amor, Daniel R; Valverde, Sergi

2016-01-01

It has been suggested that innovations occur mainly by combination: the more inventions accumulate, the higher the probability that new inventions are obtained from previous designs. Additionally, it has been conjectured that the combinatorial nature of innovations naturally leads to a singularity: at some finite time, the number of innovations should diverge. Although these ideas are certainly appealing, no general models have been yet developed to test the conditions under which combinatorial technology should become explosive. Here we present a generalised model of technological evolution that takes into account two major properties: the number of previous technologies needed to create a novel one and how rapidly technology ages. Two different models of combinatorial growth are considered, involving different forms of ageing. When long-range memory is used and thus old inventions are available for novel innovations, singularities can emerge under some conditions with two phases separated by a critical boundary. If the ageing has a characteristic time scale, it is shown that no singularities will be observed. Instead, a "black hole" of old innovations appears and expands in time, making the rate of invention creation slow down into a linear regime.

Galaxy Redshifts from Discrete Optimization of Correlation Functions

NASA Astrophysics Data System (ADS)

Lee, Benjamin C. G.; Budavári, Tamás; Basu, Amitabh; Rahman, Mubdi

2016-12-01

We propose a new method of constraining the redshifts of individual extragalactic sources based on celestial coordinates and their ensemble statistics. Techniques from integer linear programming (ILP) are utilized to optimize simultaneously for the angular two-point cross- and autocorrelation functions. Our novel formalism introduced here not only transforms the otherwise hopelessly expensive, brute-force combinatorial search into a linear system with integer constraints but also is readily implementable in off-the-shelf solvers. We adopt Gurobi, a commercial optimization solver, and use Python to build the cost function dynamically. The preliminary results on simulated data show potential for future applications to sky surveys by complementing and enhancing photometric redshift estimators. Our approach is the first application of ILP to astronomical analysis.

Measurement problem in Program Universe. Revision

NASA Astrophysics Data System (ADS)

Noyes, H. P.; Gefwert, C.; Manthey, M. J.

1985-07-01

The measurement problem of contemporary physics is in our view an artifact of its philosophical and mathematical underpinnings. We describe a new philosophical view of theory formation, rooted in Wittgenstein, and Bishop's and Martin-Loef's constructivity, which obviates such discussions. We present an unfinished, but very encouraging, theory which is compatible with this philosophical framework. The theory is based on the concepts of counting and combinatorics in the framework provided by the combinatorial hierarchy, a unique hierarchy of bit strings which interact by an operation called discrimination. Measurement criteria incorporate c, h-bar and m/sub p/ or (not and) G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact.

'Extremotaxis': computing with a bacterial-inspired algorithm.

PubMed

Nicolau, Dan V; Burrage, Kevin; Nicolau, Dan V; Maini, Philip K

2008-01-01

We present a general-purpose optimization algorithm inspired by "run-and-tumble", the biased random walk chemotactic swimming strategy used by the bacterium Escherichia coli to locate regions of high nutrient concentration The method uses particles (corresponding to bacteria) that swim through the variable space (corresponding to the attractant concentration profile). By constantly performing temporal comparisons, the particles drift towards the minimum or maximum of the function of interest. We illustrate the use of our method with four examples. We also present a discrete version of the algorithm. The new algorithm is expected to be useful in combinatorial optimization problems involving many variables, where the functional landscape is apparently stochastic and has local minima, but preserves some derivative structure at intermediate scales.

The disadvantage of combinatorial communication.

PubMed Central

Lachmann, Michael; Bergstrom, Carl T.

2004-01-01

Combinatorial communication allows rapid and efficient transfer of detailed information, yet combinatorial communication is used by few, if any, non-human species. To complement recent studies illustrating the advantages of combinatorial communication, we highlight a critical disadvantage. We use the concept of information value to show that deception poses a greater and qualitatively different threat to combinatorial signalling than to non-combinatorial systems. This additional potential for deception may represent a strategic barrier that has prevented widespread evolution of combinatorial communication. Our approach has the additional benefit of drawing clear distinctions among several types of deception that can occur in communication systems. PMID:15556886

The disadvantage of combinatorial communication.

PubMed

Lachmann, Michael; Bergstrom, Carl T

2004-11-22

Combinatorial communication allows rapid and efficient transfer of detailed information, yet combinatorial communication is used by few, if any, non-human species. To complement recent studies illustrating the advantages of combinatorial communication, we highlight a critical disadvantage. We use the concept of information value to show that deception poses a greater and qualitatively different threat to combinatorial signalling than to non-combinatorial systems. This additional potential for deception may represent a strategic barrier that has prevented widespread evolution of combinatorial communication. Our approach has the additional benefit of drawing clear distinctions among several types of deception that can occur in communication systems.

Novel In Vivo Model for Combinatorial Fluorescence Labeling in Mouse Prostate

PubMed Central

Fang, Xiaolan; Gyabaah, Kenneth; Nickkholgh, Bita; Cline, J. Mark; Balaji, K.C.

2015-01-01

BACKGROUND The epithelial layer of prostate glands contains several types of cells, including luminal and basal cells. Yet there is paucity of animal models to study the cellular origin of normal or neoplastic development in the prostate to facilitate the treatment of heterogenous prostate diseases by targeting individual cell lineages. METHODS We developed a mouse model that expresses different types of fluorescent proteins (XFPs) specifically in prostatic cells. Using an in vivo stochastic fluorescent protein combinatorial strategy, XFP signals were expressed specifically in prostate of Protein Kinase D1 (PKD1) knock-out, K-RasG12D knock-in, and Phosphatase and tensin homolog (PTEN) and PKD1 double knock-out mice under the control of PB-Cre promoter. RESULTS In vivo XFP signals were observed in prostate of PKD1 knock-out, K-RasG12D knock-in, and PTEN PKD1 double knock-out mice, which developed normal, hyperplastic, and neoplastic prostate, respectively. The patchy expression pattern of XFPs in neoplasia tissue indicated the clonal origin of cancer cells in the prostate. CONCLUSIONS The transgenic mouse models demonstrate combinatorial fluorescent protein expression in normal and cancerous prostatic tissues. This novel prostate-specific fluorescent labeled mouse model, which we named Prorainbow, could be useful in studying benign and malignant pathology of prostate. PMID:25753731

Novel In Vivo model for combinatorial fluorescence labeling in mouse prostate.

PubMed

Fang, Xiaolan; Gyabaah, Kenneth; Nickkholgh, Bita; Cline, J Mark; Balaji, K C

2015-06-15

The epithelial layer of prostate glands contains several types of cells, including luminal and basal cells. Yet there is paucity of animal models to study the cellular origin of normal or neoplastic development in the prostate to facilitate the treatment of heterogenous prostate diseases by targeting individual cell lineages. We developed a mouse model that expresses different types of fluorescent proteins (XFPs) specifically in prostatic cells. Using an in vivo stochastic fluorescent protein combinatorial strategy, XFP signals were expressed specifically in prostate of Protein Kinase D1 (PKD1) knock-out, K-Ras(G) (12) (D) knock-in, and Phosphatase and tensin homolog (PTEN) and PKD1 double knock-out mice under the control of PB-Cre promoter. In vivo XFP signals were observed in prostate of PKD1 knock-out, K-Ras(G) (12) (D) knock-in, and PTEN PKD1 double knock-out mice, which developed normal, hyperplastic, and neoplastic prostate, respectively. The patchy expression pattern of XFPs in neoplasia tissue indicated the clonal origin of cancer cells in the prostate. The transgenic mouse models demonstrate combinatorial fluorescent protein expression in normal and cancerous prostatic tissues. This novel prostate-specific fluorescent labeled mouse model, which we named Prorainbow, could be useful in studying benign and malignant pathology of prostate. © 2015 Wiley Periodicals, Inc.

A dynamical systems model for combinatorial cancer therapy enhances oncolytic adenovirus efficacy by MEK-inhibition.

PubMed

Bagheri, Neda; Shiina, Marisa; Lauffenburger, Douglas A; Korn, W Michael

2011-02-01

Oncolytic adenoviruses, such as ONYX-015, have been tested in clinical trials for currently untreatable tumors, but have yet to demonstrate adequate therapeutic efficacy. The extent to which viruses infect targeted cells determines the efficacy of this approach but many tumors down-regulate the Coxsackievirus and Adenovirus Receptor (CAR), rendering them less susceptible to infection. Disrupting MAPK pathway signaling by pharmacological inhibition of MEK up-regulates CAR expression, offering possible enhanced adenovirus infection. MEK inhibition, however, interferes with adenovirus replication due to resulting G1-phase cell cycle arrest. Therefore, enhanced efficacy will depend on treatment protocols that productively balance these competing effects. Predictive understanding of how to attain and enhance therapeutic efficacy of combinatorial treatment is difficult since the effects of MEK inhibitors, in conjunction with adenovirus/cell interactions, are complex nonlinear dynamic processes. We investigated combinatorial treatment strategies using a mathematical model that predicts the impact of MEK inhibition on tumor cell proliferation, ONYX-015 infection, and oncolysis. Specifically, we fit a nonlinear differential equation system to dedicated experimental data and analyzed the resulting simulations for favorable treatment strategies. Simulations predicted enhanced combinatorial therapy when both treatments were applied simultaneously; we successfully validated these predictions in an ensuing explicit test study. Further analysis revealed that a CAR-independent mechanism may be responsible for amplified virus production and cell death. We conclude that integrated computational and experimental analysis of combinatorial therapy provides a useful means to identify treatment/infection protocols that yield clinically significant oncolysis. Enhanced oncolytic therapy has the potential to dramatically improve non-surgical cancer treatment, especially in locally advanced or metastatic cases where treatment options remain limited.

Structure-based design of combinatorial mutagenesis libraries

PubMed Central

Verma, Deeptak; Grigoryan, Gevorg; Bailey-Kellogg, Chris

2015-01-01

The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high-throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general-purpose method, called “Structure-based Optimization of Combinatorial Mutagenesis” (SOCoM), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library-averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β-lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure-based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large-scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure-based assessments, such as the energy gap between alternative conformational or bound states. PMID:25611189

Structure-based design of combinatorial mutagenesis libraries.

PubMed

Verma, Deeptak; Grigoryan, Gevorg; Bailey-Kellogg, Chris

2015-05-01

The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high-throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general-purpose method, called "Structure-based Optimization of Combinatorial Mutagenesis" (SOCoM), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library-averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β-lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure-based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large-scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure-based assessments, such as the energy gap between alternative conformational or bound states. © 2015 The Protein Society.

A new discrete dynamic model of ABA-induced stomatal closure predicts key feedback loops

PubMed Central

Acharya, Biswa R.; Jeon, Byeong Wook; Zañudo, Jorge G. T.; Zhu, Mengmeng; Osman, Karim; Assmann, Sarah M.

2017-01-01

Stomata, microscopic pores in leaf surfaces through which water loss and carbon dioxide uptake occur, are closed in response to drought by the phytohormone abscisic acid (ABA). This process is vital for drought tolerance and has been the topic of extensive experimental investigation in the last decades. Although a core signaling chain has been elucidated consisting of ABA binding to receptors, which alleviates negative regulation by protein phosphatases 2C (PP2Cs) of the protein kinase OPEN STOMATA 1 (OST1) and ultimately results in activation of anion channels, osmotic water loss, and stomatal closure, over 70 additional components have been identified, yet their relationships with each other and the core components are poorly elucidated. We integrated and processed hundreds of disparate observations regarding ABA signal transduction responses underlying stomatal closure into a network of 84 nodes and 156 edges and, as a result, established those relationships, including identification of a 36-node, strongly connected (feedback-rich) component as well as its in- and out-components. The network’s domination by a feedback-rich component may reflect a general feature of rapid signaling events. We developed a discrete dynamic model of this network and elucidated the effects of ABA plus knockout or constitutive activity of 79 nodes on both the outcome of the system (closure) and the status of all internal nodes. The model, with more than 1024 system states, is far from fully determined by the available data, yet model results agree with existing experiments in 82 cases and disagree in only 17 cases, a validation rate of 75%. Our results reveal nodes that could be engineered to impact stomatal closure in a controlled fashion and also provide over 140 novel predictions for which experimental data are currently lacking. Noting the paucity of wet-bench data regarding combinatorial effects of ABA and internal node activation, we experimentally confirmed several predictions of the model with regard to reactive oxygen species, cytosolic Ca2+ (Ca2+c), and heterotrimeric G-protein signaling. We analyzed dynamics-determining positive and negative feedback loops, thereby elucidating the attractor (dynamic behavior) repertoire of the system and the groups of nodes that determine each attractor. Based on this analysis, we predict the likely presence of a previously unrecognized feedback mechanism dependent on Ca2+c. This mechanism would provide model agreement with 10 additional experimental observations, for a validation rate of 85%. Our research underscores the importance of feedback regulation in generating robust and adaptable biological responses. The high validation rate of our model illustrates the advantages of discrete dynamic modeling for complex, nonlinear systems common in biology. PMID:28937978

Computational Modeling of Proteins based on Cellular Automata: A Method of HP Folding Approximation.

PubMed

Madain, Alia; Abu Dalhoum, Abdel Latif; Sleit, Azzam

2018-06-01

The design of a protein folding approximation algorithm is not straightforward even when a simplified model is used. The folding problem is a combinatorial problem, where approximation and heuristic algorithms are usually used to find near optimal folds of proteins primary structures. Approximation algorithms provide guarantees on the distance to the optimal solution. The folding approximation approach proposed here depends on two-dimensional cellular automata to fold proteins presented in a well-studied simplified model called the hydrophobic-hydrophilic model. Cellular automata are discrete computational models that rely on local rules to produce some overall global behavior. One-third and one-fourth approximation algorithms choose a subset of the hydrophobic amino acids to form H-H contacts. Those algorithms start with finding a point to fold the protein sequence into two sides where one side ignores H's at even positions and the other side ignores H's at odd positions. In addition, blocks or groups of amino acids fold the same way according to a predefined normal form. We intend to improve approximation algorithms by considering all hydrophobic amino acids and folding based on the local neighborhood instead of using normal forms. The CA does not assume a fixed folding point. The proposed approach guarantees one half approximation minus the H-H endpoints. This lower bound guaranteed applies to short sequences only. This is proved as the core and the folds of the protein will have two identical sides for all short sequences.

Hybrid Self-Adaptive Evolution Strategies Guided by Neighborhood Structures for Combinatorial Optimization Problems.

PubMed

Coelho, V N; Coelho, I M; Souza, M J F; Oliveira, T A; Cota, L P; Haddad, M N; Mladenovic, N; Silva, R C P; Guimarães, F G

2016-01-01

This article presents an Evolution Strategy (ES)--based algorithm, designed to self-adapt its mutation operators, guiding the search into the solution space using a Self-Adaptive Reduced Variable Neighborhood Search procedure. In view of the specific local search operators for each individual, the proposed population-based approach also fits into the context of the Memetic Algorithms. The proposed variant uses the Greedy Randomized Adaptive Search Procedure with different greedy parameters for generating its initial population, providing an interesting exploration-exploitation balance. To validate the proposal, this framework is applied to solve three different [Formula: see text]-Hard combinatorial optimization problems: an Open-Pit-Mining Operational Planning Problem with dynamic allocation of trucks, an Unrelated Parallel Machine Scheduling Problem with Setup Times, and the calibration of a hybrid fuzzy model for Short-Term Load Forecasting. Computational results point out the convergence of the proposed model and highlight its ability in combining the application of move operations from distinct neighborhood structures along the optimization. The results gathered and reported in this article represent a collective evidence of the performance of the method in challenging combinatorial optimization problems from different application domains. The proposed evolution strategy demonstrates an ability of adapting the strength of the mutation disturbance during the generations of its evolution process. The effectiveness of the proposal motivates the application of this novel evolutionary framework for solving other combinatorial optimization problems.

A review on data mining and continuous optimization applications in computational biology and medicine.

PubMed

Weber, Gerhard-Wilhelm; Ozöğür-Akyüz, Süreyya; Kropat, Erik

2009-06-01

An emerging research area in computational biology and biotechnology is devoted to mathematical modeling and prediction of gene-expression patterns; it nowadays requests mathematics to deeply understand its foundations. This article surveys data mining and machine learning methods for an analysis of complex systems in computational biology. It mathematically deepens recent advances in modeling and prediction by rigorously introducing the environment and aspects of errors and uncertainty into the genetic context within the framework of matrix and interval arithmetics. Given the data from DNA microarray experiments and environmental measurements, we extract nonlinear ordinary differential equations which contain parameters that are to be determined. This is done by a generalized Chebychev approximation and generalized semi-infinite optimization. Then, time-discretized dynamical systems are studied. By a combinatorial algorithm which constructs and follows polyhedra sequences, the region of parametric stability is detected. In addition, we analyze the topological landscape of gene-environment networks in terms of structural stability. As a second strategy, we will review recent model selection and kernel learning methods for binary classification which can be used to classify microarray data for cancerous cells or for discrimination of other kind of diseases. This review is practically motivated and theoretically elaborated; it is devoted to a contribution to better health care, progress in medicine, a better education, and more healthy living conditions.

Quantum Efficiency and Bandgap Analysis for Combinatorial Photovoltaics: Sorting Activity of Cu–O Compounds in All-Oxide Device Libraries

PubMed Central

2014-01-01

All-oxide-based photovoltaics (PVs) encompass the potential for extremely low cost solar cells, provided they can obtain an order of magnitude improvement in their power conversion efficiencies. To achieve this goal, we perform a combinatorial materials study of metal oxide based light absorbers, charge transporters, junctions between them, and PV devices. Here we report the development of a combinatorial internal quantum efficiency (IQE) method. IQE measures the efficiency associated with the charge separation and collection processes, and thus is a proxy for PV activity of materials once placed into devices, discarding optical properties that cause uncontrolled light harvesting. The IQE is supported by high-throughput techniques for bandgap fitting, composition analysis, and thickness mapping, which are also crucial parameters for the combinatorial investigation cycle of photovoltaics. As a model system we use a library of 169 solar cells with a varying thickness of sprayed titanium dioxide (TiO2) as the window layer, and covarying thickness and composition of binary compounds of copper oxides (Cu–O) as the light absorber, fabricated by Pulsed Laser Deposition (PLD). The analysis on the combinatorial devices shows the correlation between compositions and bandgap, and their effect on PV activity within several device configurations. The analysis suggests that the presence of Cu4O3 plays a significant role in the PV activity of binary Cu–O compounds. PMID:24410367

Set-Based Discrete Particle Swarm Optimization Based on Decomposition for Permutation-Based Multiobjective Combinatorial Optimization Problems.

PubMed

Yu, Xue; Chen, Wei-Neng; Gu, Tianlong; Zhang, Huaxiang; Yuan, Huaqiang; Kwong, Sam; Zhang, Jun

2018-07-01

This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.

Adapting an Ant Colony Metaphor for Multi-Robot Chemical Plume Tracing

PubMed Central

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments. PMID:22666056

Adapting an ant colony metaphor for multi-robot chemical plume tracing.

PubMed

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments.

Synthesis of Chemiluminescent Esters: A Combinatorial Synthesis Experiment for Organic Chemistry Students

ERIC Educational Resources Information Center

Duarte, Robert; Nielson, Janne T.; Dragojlovic, Veljko

2004-01-01

A group of techniques aimed at synthesizing a large number of structurally diverse compounds is called combinatorial synthesis. Synthesis of chemiluminescence esters using parallel combinatorial synthesis and mix-and-split combinatorial synthesis is experimented.

Evolution of speech-specific cognitive adaptations.

PubMed

de Boer, Bart

2015-01-01

This paper argues that an evolutionary perspective is natural when investigating cognitive adaptations related to language. This is because there appears to be correspondence between traits that linguists consider interesting and traits that have undergone selective pressure related to language. The paper briefly reviews theoretical results that shed light on what kind of adaptations we can expect to have evolved and then reviews concrete work related to the evolution of adaptations for combinatorial speech. It turns out that there is as yet no strong direct evidence for cognitive traits that have undergone selection related to speech, but there is indirect evidence that indicates selection. However, the traits that may have undergone selection are expected to be continuously variable ones, rather than the discrete ones that linguists have focused on traditionally.

FOURTH SEMINAR TO THE MEMORY OF D.N. KLYSHKO: Algebraic solution of the synthesis problem for coded sequences

NASA Astrophysics Data System (ADS)

Leukhin, Anatolii N.

2005-08-01

The algebraic solution of a 'complex' problem of synthesis of phase-coded (PC) sequences with the zero level of side lobes of the cyclic autocorrelation function (ACF) is proposed. It is shown that the solution of the synthesis problem is connected with the existence of difference sets for a given code dimension. The problem of estimating the number of possible code combinations for a given code dimension is solved. It is pointed out that the problem of synthesis of PC sequences is related to the fundamental problems of discrete mathematics and, first of all, to a number of combinatorial problems, which can be solved, as the number factorisation problem, by algebraic methods by using the theory of Galois fields and groups.

Transversal homoclinic orbits in a transiently chaotic neural network.

PubMed

Chen, Shyan-Shiou; Shih, Chih-Wen

2002-09-01

We study the existence of snap-back repellers, hence the existence of transversal homoclinic orbits in a discrete-time neural network. Chaotic behaviors for the network system in the sense of Li and Yorke or Marotto can then be concluded. The result is established by analyzing the structures of the system and allocating suitable parameters in constructing the fixed points and their pre-images for the system. The investigation provides a theoretical confirmation on the scenario of transient chaos for the system. All the parameter conditions for the theory can be examined numerically. The numerical ranges for the parameters which yield chaotic dynamics and convergent dynamics provide significant information in the annealing process in solving combinatorial optimization problems using this transiently chaotic neural network. (c) 2002 American Institute of Physics.

Multiple-variable neighbourhood search for the single-machine total weighted tardiness problem

NASA Astrophysics Data System (ADS)

Chung, Tsui-Ping; Fu, Qunjie; Liao, Ching-Jong; Liu, Yi-Ting

2017-07-01

The single-machine total weighted tardiness (SMTWT) problem is a typical discrete combinatorial optimization problem in the scheduling literature. This problem has been proved to be NP hard and thus provides a challenging area for metaheuristics, especially the variable neighbourhood search algorithm. In this article, a multiple variable neighbourhood search (m-VNS) algorithm with multiple neighbourhood structures is proposed to solve the problem. Special mechanisms named matching and strengthening operations are employed in the algorithm, which has an auto-revising local search procedure to explore the solution space beyond local optimality. Two aspects, searching direction and searching depth, are considered, and neighbourhood structures are systematically exchanged. Experimental results show that the proposed m-VNS algorithm outperforms all the compared algorithms in solving the SMTWT problem.

Combinatorial QSAR Modeling of Rat Acute Toxicity by Oral Exposure

EPA Science Inventory

Quantitative Structure-Activity Relationship (QSAR) toxicity models have become popular tools for identifying potential toxic compounds and prioritizing candidates for animal toxicity tests. However, few QSAR studies have successfully modeled large, diverse mammalian toxicity end...

A new approach to the rationale discovery of polymeric biomaterials

PubMed Central

Kohn, Joachim; Welsh, William J.; Knight, Doyle

2007-01-01

This paper attempts to illustrate both the need for new approaches to biomaterials discovery as well as the significant promise inherent in the use of combinatorial and computational design strategies. The key observation of this Leading Opinion Paper is that the biomaterials community has been slow to embrace advanced biomaterials discovery tools such as combinatorial methods, high throughput experimentation, and computational modeling in spite of the significant promise shown by these discovery tools in materials science, medicinal chemistry and the pharmaceutical industry. It seems that the complexity of living cells and their interactions with biomaterials has been a conceptual as well as a practical barrier to the use of advanced discovery tools in biomaterials science. However, with the continued increase in computer power, the goal of predicting the biological response of cells in contact with biomaterials surfaces is within reach. Once combinatorial synthesis, high throughput experimentation, and computational modeling are integrated into the biomaterials discovery process, a significant acceleration is possible in the pace of development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems. PMID:17644176

Taylor O(h³) Discretization of ZNN Models for Dynamic Equality-Constrained Quadratic Programming With Application to Manipulators.

PubMed

Liao, Bolin; Zhang, Yunong; Jin, Long

2016-02-01

In this paper, a new Taylor-type numerical differentiation formula is first presented to discretize the continuous-time Zhang neural network (ZNN), and obtain higher computational accuracy. Based on the Taylor-type formula, two Taylor-type discrete-time ZNN models (termed Taylor-type discrete-time ZNNK and Taylor-type discrete-time ZNNU models) are then proposed and discussed to perform online dynamic equality-constrained quadratic programming. For comparison, Euler-type discrete-time ZNN models (called Euler-type discrete-time ZNNK and Euler-type discrete-time ZNNU models) and Newton iteration, with interesting links being found, are also presented. It is proved herein that the steady-state residual errors of the proposed Taylor-type discrete-time ZNN models, Euler-type discrete-time ZNN models, and Newton iteration have the patterns of O(h(3)), O(h(2)), and O(h), respectively, with h denoting the sampling gap. Numerical experiments, including the application examples, are carried out, of which the results further substantiate the theoretical findings and the efficacy of Taylor-type discrete-time ZNN models. Finally, the comparisons with Taylor-type discrete-time derivative model and other Lagrange-type discrete-time ZNN models for dynamic equality-constrained quadratic programming substantiate the superiority of the proposed Taylor-type discrete-time ZNN models once again.

Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication

ERIC Educational Resources Information Center

Wolf, Michael Maclean

2009-01-01

Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work on optimizing matrix-vector multiplication using combinatorial techniques. Our research has focused on two different problems in combinatorial scientific…

Combinatorial investigation of rare-earth free permanent magnets

NASA Astrophysics Data System (ADS)

Fackler, Sean Wu

The combinatorial high throughput method allows one to rapidly study a large number of samples with systematically changing parameters. We apply this method to study Fe-Co-V alloys as alternatives to rare-earth permanent magnets. Rare-earth permanent magnets derive their unmatched magnetic properties from the hybridization of Fe and Co with the f-orbitals of rare-earth elements, which have strong spin-orbit coupling. It is predicted that Fe and Co may also have strong hybridization with 4d and 5d refractory transition metals with strong spin-orbit coupling. Refractory transition metals like V also have the desirable property of high temperature stability, which is important for permanent magnet applications in traction motors. In this work, we focus on the role of crystal structure, composition, and secondary phases in the origin of competitive permanent magnetic properties of a particular Fe-Co-V alloy. Fe38Co52V10, compositions are known as Vicalloys. Fe-CoV composition spreads were sputtered onto three-inch silicon wafers and patterned into discrete sample pads forming a combinatorial library. We employed highthroughput screening methods using synchrotron X-rays, wavelength dispersive spectroscopy, and magneto-optical Kerr effect (MOKE) to rapidly screen crystal structure, composition, and magnetic properties, respectively. We found that in-plane magnetic coercive fields of our Vicalloy thin films agree with known bulk values (300 G), but found a remarkable eight times increase of the out-of-plane coercive fields (˜2,500 G). To explain this, we measured the switching fields between in-plane and out-of-plane thin film directions which revealed that the Kondorsky model of 180° domain wall reversal was responsible for Vicalloy's enhanced out-of-plane coercive field and possibly its permanent magnetic properties. The Kondorsky model suggests that domain-wall pinning is the origin of Vicalloy's permanent magnetic properties, in contrast to strain, shape, or crystalline anisotropy mechanisms suggested in the literature. We also studied the thickness dependence of an Fe70Co30- V thin film library to consider the unique effects of our thin film libraries which are not found in bulk samples. We present results of data mining of synchrotron X-ray diffraction data using non-negative matrix factorization (NMF). NMF can automatically identify pure crystal phases that make up an unknown phase mixture. We found a strong correlation between magnetic properties and crystal phase quantity using this valuable visualization. In addition to the combinatorial study, this dissertation includes a study of strain controlled properties of magnetic thin films for future applications in random access memories. We investigated the local coupling between dense magnetic stripe domains in transcritical Permalloy (tPy) thin films and ferroelectric domains of BaTiO3 single crystals in a tPy/BaTiO3 heterostructure. Two distinct changes in the magnetic stripe domains of tPy were observed from the magnetic force microscopy images after cooling the heterostructure from above the ferroelectric Curie temperature of BaTiO3 (120°C) to room temperature. First, an abrupt break in the magnetic stripe domain direction was found at the ferroelectric a-c-domain boundaries due to an induced change in in-plane magnetic anisotropy. Second, the magnetic stripe domain period increased when coupled to a ferroelectric a-domain due to a change in out-of-plane magnetic anisotropy. Micromagnetic simulations reveal that local magnetic anisotropy energy from inverse magnetostriction is conserved between in-plane and out-of-plane components.

Functional autonomy of distant-acting human enhancers

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

Visel, Axel; Akiyama, Jennifer A.; Shoukry, Malak

2009-02-19

Many human genes are associated with dispersed arrays of transcriptional enhancers that regulate their expression in time and space. Studies in invertebrate model systems have suggested that these elements function as discrete and independent regulatory units, but the in vivo combinatorial properties of vertebrate enhancers remain poorly understood. To explore the modularity and regulatory autonomy of human developmental enhancers, we experimentally concatenated up to four enhancers from different genes and used a transgenic mouse assay to compare the in vivo activity of these compound elements with that of the single modules. In all of the six different combinations of elementsmore » tested, the reporter gene activity patterns were additive without signs of interference between the individual modules, indicating that regulatory specificity was maintained despite the presence of closely-positioned heterologous enhancers. Even in cases where two elements drove expression in close anatomical proximity, such as within neighboring subregions of the developing limb bud, the compound patterns did not show signs of cross-inhibition between individual elements or novel expression sites. These data indicate that human developmental enhancers are highly modular and functionally autonomous and suggest that genomic enhancer shuffling may have contributed to the evolution of complex gene expression patterns in vertebrates« less

Combinatorial optimization in foundry practice

NASA Astrophysics Data System (ADS)

Antamoshkin, A. N.; Masich, I. S.

2016-04-01

The multicriteria mathematical model of foundry production capacity planning is suggested in the paper. The model is produced in terms of pseudo-Boolean optimization theory. Different search optimization methods were used to solve the obtained problem.

Modeling Lignin Polymerization. I. Simulation Model of Dehydrogenation Polymers1[OA

PubMed Central

van Parijs, Frederik R.D.; Morreel, Kris; Ralph, John; Boerjan, Wout; Merks, Roeland M.H.

2010-01-01

Lignin is a heteropolymer that is thought to form in the cell wall by combinatorial radical coupling of monolignols. Here, we present a simulation model of in vitro lignin polymerization, based on the combinatorial coupling theory, which allows us to predict the reaction conditions controlling the primary structure of lignin polymers. Our model predicts two controlling factors for the β-O-4 content of syringyl-guaiacyl lignins: the supply rate of monolignols and the relative amount of supplied sinapyl alcohol monomers. We have analyzed the in silico degradability of the resulting lignin polymers by cutting the resulting lignin polymers at β-O-4 bonds. These are cleaved in analytical methods used to study lignin composition, namely thioacidolysis and derivatization followed by reductive cleavage, under pulping conditions, and in some lignocellulosic biomass pretreatments. PMID:20472753

XML Encoding of Features Describing Rule-Based Modeling of Reaction Networks with Multi-Component Molecular Complexes

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2011-01-01

Multi-state molecules and multi-component complexes are commonly involved in cellular signaling. Accounting for molecules that have multiple potential states, such as a protein that may be phosphorylated on multiple residues, and molecules that combine to form heterogeneous complexes located among multiple compartments, generates an effect of combinatorial complexity. Models involving relatively few signaling molecules can include thousands of distinct chemical species. Several software tools (StochSim, BioNetGen) are already available to deal with combinatorial complexity. Such tools need information standards if models are to be shared, jointly evaluated and developed. Here we discuss XML conventions that can be adopted for modeling biochemical reaction networks described by user-specified reaction rules. These could form a basis for possible future extensions of the Systems Biology Markup Language (SBML). PMID:21464833

High-throughput combinatorial chemical bath deposition: The case of doping Cu (In, Ga) Se film with antimony

NASA Astrophysics Data System (ADS)

Yan, Zongkai; Zhang, Xiaokun; Li, Guang; Cui, Yuxing; Jiang, Zhaolian; Liu, Wen; Peng, Zhi; Xiang, Yong

2018-01-01

The conventional methods for designing and preparing thin film based on wet process remain a challenge due to disadvantages such as time-consuming and ineffective, which hinders the development of novel materials. Herein, we present a high-throughput combinatorial technique for continuous thin film preparation relied on chemical bath deposition (CBD). The method is ideally used to prepare high-throughput combinatorial material library with low decomposition temperatures and high water- or oxygen-sensitivity at relatively high-temperature. To check this system, a Cu(In, Ga)Se (CIGS) thin films library doped with 0-19.04 at.% of antimony (Sb) was taken as an example to evaluate the regulation of varying Sb doping concentration on the grain growth, structure, morphology and electrical properties of CIGS thin film systemically. Combined with the Energy Dispersive Spectrometer (EDS), X-ray Photoelectron Spectroscopy (XPS), automated X-ray Diffraction (XRD) for rapid screening and Localized Electrochemical Impedance Spectroscopy (LEIS), it was confirmed that this combinatorial high-throughput system could be used to identify the composition with the optimal grain orientation growth, microstructure and electrical properties systematically, through accurately monitoring the doping content and material composition. According to the characterization results, a Sb2Se3 quasi-liquid phase promoted CIGS film-growth model has been put forward. In addition to CIGS thin film reported here, the combinatorial CBD also could be applied to the high-throughput screening of other sulfide thin film material systems.

Fast Combinatorial Algorithm for the Solution of Linearly Constrained Least Squares Problems

DOEpatents

Van Benthem, Mark H.; Keenan, Michael R.

2008-11-11

A fast combinatorial algorithm can significantly reduce the computational burden when solving general equality and inequality constrained least squares problems with large numbers of observation vectors. The combinatorial algorithm provides a mathematically rigorous solution and operates at great speed by reorganizing the calculations to take advantage of the combinatorial nature of the problems to be solved. The combinatorial algorithm exploits the structure that exists in large-scale problems in order to minimize the number of arithmetic operations required to obtain a solution.

Combinatorial Algorithms to Enable Computational Science and Engineering: Work from the CSCAPES Institute

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

Boman, Erik G.; Catalyurek, Umit V.; Chevalier, Cedric

2015-01-16

This final progress report summarizes the work accomplished at the Combinatorial Scientific Computing and Petascale Simulations Institute. We developed Zoltan, a parallel mesh partitioning library that made use of accurate hypergraph models to provide load balancing in mesh-based computations. We developed several graph coloring algorithms for computing Jacobian and Hessian matrices and organized them into a software package called ColPack. We developed parallel algorithms for graph coloring and graph matching problems, and also designed multi-scale graph algorithms. Three PhD students graduated, six more are continuing their PhD studies, and four postdoctoral scholars were advised. Six of these students and Fellowsmore » have joined DOE Labs (Sandia, Berkeley), as staff scientists or as postdoctoral scientists. We also organized the SIAM Workshop on Combinatorial Scientific Computing (CSC) in 2007, 2009, and 2011 to continue to foster the CSC community.« less

Combinatorial influence of environmental parameters on transcription factor activity.

PubMed

Knijnenburg, T A; Wessels, L F A; Reinders, M J T

2008-07-01

Cells receive a wide variety of environmental signals, which are often processed combinatorially to generate specific genetic responses. Changes in transcript levels, as observed across different environmental conditions, can, to a large extent, be attributed to changes in the activity of transcription factors (TFs). However, in unraveling these transcription regulation networks, the actual environmental signals are often not incorporated into the model, simply because they have not been measured. The unquantified heterogeneity of the environmental parameters across microarray experiments frustrates regulatory network inference. We propose an inference algorithm that models the influence of environmental parameters on gene expression. The approach is based on a yeast microarray compendium of chemostat steady-state experiments. Chemostat cultivation enables the accurate control and measurement of many of the key cultivation parameters, such as nutrient concentrations, growth rate and temperature. The observed transcript levels are explained by inferring the activity of TFs in response to combinations of cultivation parameters. The interplay between activated enhancers and repressors that bind a gene promoter determine the possible up- or downregulation of the gene. The model is translated into a linear integer optimization problem. The resulting regulatory network identifies the combinatorial effects of environmental parameters on TF activity and gene expression. The Matlab code is available from the authors upon request. Supplementary data are available at Bioinformatics online.

MARCC (Matrix-Assisted Reader Chromatin Capture): an antibody-free method to enrich and analyze combinatorial nucleosome modifications

PubMed Central

Su, Zhangli

2016-01-01

Combinatorial patterns of histone modifications are key indicators of different chromatin states. Most of the current approaches rely on the usage of antibodies to analyze combinatorial histone modifications. Here we detail an antibody-free method named MARCC (Matrix-Assisted Reader Chromatin Capture) to enrich combinatorial histone modifications. The combinatorial patterns are enriched on native nucleosomes extracted from cultured mammalian cells and prepared by micrococcal nuclease digestion. Such enrichment is achieved by recombinant chromatin-interacting protein modules, or so-called reader domains, which can bind in a combinatorial modification-dependent manner. The enriched chromatin can be quantified by western blotting or mass spectrometry for the co-existence of histone modifications, while the associated DNA content can be analyzed by qPCR or next-generation sequencing. Altogether, MARCC provides a reproducible, efficient and customizable solution to enrich and analyze combinatorial histone modifications. PMID:26131849

A New Approach for Proving or Generating Combinatorial Identities

ERIC Educational Resources Information Center

Gonzalez, Luis

2010-01-01

A new method for proving, in an immediate way, many combinatorial identities is presented. The method is based on a simple recursive combinatorial formula involving n + 1 arbitrary real parameters. Moreover, this formula enables one not only to prove, but also generate many different combinatorial identities (not being required to know them "a…

Combinatorial techniques to efficiently investigate and optimize organic thin film processing and properties.

PubMed

Wieberger, Florian; Kolb, Tristan; Neuber, Christian; Ober, Christopher K; Schmidt, Hans-Werner

2013-04-08

In this article we present several developed and improved combinatorial techniques to optimize processing conditions and material properties of organic thin films. The combinatorial approach allows investigations of multi-variable dependencies and is the perfect tool to investigate organic thin films regarding their high performance purposes. In this context we develop and establish the reliable preparation of gradients of material composition, temperature, exposure, and immersion time. Furthermore we demonstrate the smart application of combinations of composition and processing gradients to create combinatorial libraries. First a binary combinatorial library is created by applying two gradients perpendicular to each other. A third gradient is carried out in very small areas and arranged matrix-like over the entire binary combinatorial library resulting in a ternary combinatorial library. Ternary combinatorial libraries allow identifying precise trends for the optimization of multi-variable dependent processes which is demonstrated on the lithographic patterning process. Here we verify conclusively the strong interaction and thus the interdependency of variables in the preparation and properties of complex organic thin film systems. The established gradient preparation techniques are not limited to lithographic patterning. It is possible to utilize and transfer the reported combinatorial techniques to other multi-variable dependent processes and to investigate and optimize thin film layers and devices for optical, electro-optical, and electronic applications.

A New Combinatorial Optimization Approach for Integrated Feature Selection Using Different Datasets: A Prostate Cancer Transcriptomic Study

PubMed Central

Puthiyedth, Nisha; Riveros, Carlos; Berretta, Regina; Moscato, Pablo

2015-01-01

Background The joint study of multiple datasets has become a common technique for increasing statistical power in detecting biomarkers obtained from smaller studies. The approach generally followed is based on the fact that as the total number of samples increases, we expect to have greater power to detect associations of interest. This methodology has been applied to genome-wide association and transcriptomic studies due to the availability of datasets in the public domain. While this approach is well established in biostatistics, the introduction of new combinatorial optimization models to address this issue has not been explored in depth. In this study, we introduce a new model for the integration of multiple datasets and we show its application in transcriptomics. Methods We propose a new combinatorial optimization problem that addresses the core issue of biomarker detection in integrated datasets. Optimal solutions for this model deliver a feature selection from a panel of prospective biomarkers. The model we propose is a generalised version of the (α,β)-k-Feature Set problem. We illustrate the performance of this new methodology via a challenging meta-analysis task involving six prostate cancer microarray datasets. The results are then compared to the popular RankProd meta-analysis tool and to what can be obtained by analysing the individual datasets by statistical and combinatorial methods alone. Results Application of the integrated method resulted in a more informative signature than the rank-based meta-analysis or individual dataset results, and overcomes problems arising from real world datasets. The set of genes identified is highly significant in the context of prostate cancer. The method used does not rely on homogenisation or transformation of values to a common scale, and at the same time is able to capture markers associated with subgroups of the disease. PMID:26106884

Dynamic combinatorial libraries: new opportunities in systems chemistry.

PubMed

Hunt, Rosemary A R; Otto, Sijbren

2011-01-21

Combinatorial chemistry is a tool for selecting molecules with special properties. Dynamic combinatorial chemistry started off aiming to be just that. However, unlike ordinary combinatorial chemistry, the interconnectedness of dynamic libraries gives them an extra dimension. An understanding of these molecular networks at systems level is essential for their use as a selection tool and creates exciting new opportunities in systems chemistry. In this feature article we discuss selected examples and considerations related to the advanced exploitation of dynamic combinatorial libraries for their originally conceived purpose of identifying strong binding interactions. Also reviewed are examples illustrating a trend towards increasing complexity in terms of network behaviour and reversible chemistry. Finally, new applications of dynamic combinatorial chemistry in self-assembly, transport and self-replication are discussed.

Experimental analysis of chaotic neural network models for combinatorial optimization under a unifying framework.

PubMed

Kwok, T; Smith, K A

2000-09-01

The aim of this paper is to study both the theoretical and experimental properties of chaotic neural network (CNN) models for solving combinatorial optimization problems. Previously we have proposed a unifying framework which encompasses the three main model types, namely, Chen and Aihara's chaotic simulated annealing (CSA) with decaying self-coupling, Wang and Smith's CSA with decaying timestep, and the Hopfield network with chaotic noise. Each of these models can be represented as a special case under the framework for certain conditions. This paper combines the framework with experimental results to provide new insights into the effect of the chaotic neurodynamics of each model. By solving the N-queen problem of various sizes with computer simulations, the CNN models are compared in different parameter spaces, with optimization performance measured in terms of feasibility, efficiency, robustness and scalability. Furthermore, characteristic chaotic neurodynamics crucial to effective optimization are identified, together with a guide to choosing the corresponding model parameters.

Quantitative Structure--Activity Relationship Modeling of Rat Acute Toxicity by Oral Exposure

EPA Science Inventory

Background: Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. Objective: In this study, a combinatorial QSAR approach has been employed for the creation of robust and predictive models of acute toxi...

Second quantization in bit-string physics

NASA Technical Reports Server (NTRS)

Noyes, H. Pierre

1993-01-01

Using a new fundamental theory based on bit-strings, a finite and discrete version of the solutions of the free one particle Dirac equation as segmented trajectories with steps of length h/mc along the forward and backward light cones executed at velocity +/- c are derived. Interpreting the statistical fluctuations which cause the bends in these segmented trajectories as emission and absorption of radiation, these solutions are analogous to a fermion propagator in a second quantized theory. This allows us to interpret the mass parameter in the step length as the physical mass of the free particle. The radiation in interaction with it has the usual harmonic oscillator structure of a second quantized theory. How these free particle masses can be generated gravitationally using the combinatorial hierarchy sequence (3,10,137,2(sup 127) + 136), and some of the predictive consequences are sketched.

CRAVE: a database, middleware and visualization system for phenotype ontologies.

PubMed

Gkoutos, Georgios V; Green, Eain C J; Greenaway, Simon; Blake, Andrew; Mallon, Ann-Marie; Hancock, John M

2005-04-01

A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies. CRAVE is a web-accessible JAVA application that accesses an underlying MySQL database of ontologies via a JAVA persistent middleware layer (Chameleon). This maps the database tables into discrete JAVA classes and creates memory resident, interlinked objects corresponding to the ontology data. These JAVA objects are accessed via calls through the middleware's application programming interface. CRAVE allows simultaneous display and linking of multiple ontologies and searching using Boolean and advanced searches.

When do combinatorial mechanisms apply in the production of inflected words?

PubMed

Cholin, Joana; Rapp, Brenda; Miozzo, Michele

2010-01-01

A central question for theories of inflected word processing is to determine under what circumstances compositional procedures apply. Some accounts (e.g., the dual-mechanism model; Clahsen, 1999 ) propose that compositional processes only apply to verbs that take productive affixes. For all other verbs, inflected forms are assumed to be stored in the lexicon in a nondecomposed manner. This account makes clear predictions about the consequences of disruption to the lexical access mechanisms involved in the spoken production of inflected forms. Briefly, it predicts that nonproductive forms (which require lexical access) should be more affected than productive forms (which, depending on the language task, may not). We tested these predictions through the detailed analysis of the spoken production of a German-speaking individual with an acquired lexical impairment resulting from a stroke. Analyses of response accuracy, error types, and frequency effects revealed that combinatorial processes are not restricted to verbs that take productive inflections. On this basis, we propose an alternative account, the stem-based assembly model (SAM), which posits that combinatorial processes may be available to all stems and not only to those that combine with productive affixes.

SRC family kinases as novel therapeutic targets to treat breast cancer brain metastases.

PubMed

Zhang, Siyuan; Huang, Wen-Chien; Zhang, Lin; Zhang, Chenyu; Lowery, Frank J; Ding, Zhaoxi; Guo, Hua; Wang, Hai; Huang, Suyun; Sahin, Aysegul A; Aldape, Kenneth D; Steeg, Patricia S; Yu, Dihua

2013-09-15

Despite better control of early-stage disease and improved overall survival of patients with breast cancer, the incidence of life-threatening brain metastases continues to increase in some of these patients. Unfortunately, other than palliative treatments there is no effective therapy for this condition. In this study, we reveal a critical role for Src activation in promoting brain metastasis in a preclinical model of breast cancer and we show how Src-targeting combinatorial regimens can treat HER2(+) brain metastases in this model. We found that Src was hyperactivated in brain-seeking breast cancer cells derived from human cell lines or from patients' brain metastases. Mechanistically, Src activation promoted tumor cell extravasation into the brain parenchyma via permeabilization of the blood-brain barrier. When combined with the EGFR/HER2 dual-targeting drug lapatinib, an Src-targeting combinatorial regimen prevented outgrowth of disseminated breast cancer cells through the induction of cell-cycle arrest. More importantly, this combinatorial regimen inhibited the outgrowth of established experimental brain metastases, prolonging the survival of metastases-bearing mice. Our results provide a rationale for clinical evaluation of Src-targeting regimens to treat patients with breast cancer suffering from brain metastasis. ©2013 AACR.

When do combinatorial mechanisms apply in the production of inflected words?

PubMed Central

Cholin, Joana; Rapp, Brenda; Miozzo, Michele

2010-01-01

A central question for theories of inflected word processing is to determine under what circumstances compositional procedures apply. Some accounts (e.g., the Dual Mechanism Model; Clahsen, 1999) propose that compositional processes only apply to verbs that take productive affixes. For all other verbs, inflected forms are assumed to be stored in the lexicon in a non-decomposed manner. This account makes clear predictions about the consequences of disruption to the lexical access mechanisms involved in the spoken production of inflected forms. Briefly, it predicts that non-productive forms (which require lexical access) should be more affected than productive forms (which, depending on the language task, may not). We tested these predictions through the detailed analysis of the spoken production of a German-speaking individual with an acquired lexical impairment resulting from a stroke. Analyses of response accuracy, error types, and frequency effects revealed that combinatorial processes are not restricted to verbs that take productive inflections. On this basis, we propose an alternative account, the Stem-based Assembly Model (SAM) that posits that combinatorial processes may be available to all stems, and not only those that combine with productive affixes. PMID:21104479

Applications of high throughput (combinatorial) methodologies to electronic, magnetic, optical, and energy-related materials

NASA Astrophysics Data System (ADS)

Green, Martin L.; Takeuchi, Ichiro; Hattrick-Simpers, Jason R.

2013-06-01

High throughput (combinatorial) materials science methodology is a relatively new research paradigm that offers the promise of rapid and efficient materials screening, optimization, and discovery. The paradigm started in the pharmaceutical industry but was rapidly adopted to accelerate materials research in a wide variety of areas. High throughput experiments are characterized by synthesis of a "library" sample that contains the materials variation of interest (typically composition), and rapid and localized measurement schemes that result in massive data sets. Because the data are collected at the same time on the same "library" sample, they can be highly uniform with respect to fixed processing parameters. This article critically reviews the literature pertaining to applications of combinatorial materials science for electronic, magnetic, optical, and energy-related materials. It is expected that high throughput methodologies will facilitate commercialization of novel materials for these critically important applications. Despite the overwhelming evidence presented in this paper that high throughput studies can effectively inform commercial practice, in our perception, it remains an underutilized research and development tool. Part of this perception may be due to the inaccessibility of proprietary industrial research and development practices, but clearly the initial cost and availability of high throughput laboratory equipment plays a role. Combinatorial materials science has traditionally been focused on materials discovery, screening, and optimization to combat the extremely high cost and long development times for new materials and their introduction into commerce. Going forward, combinatorial materials science will also be driven by other needs such as materials substitution and experimental verification of materials properties predicted by modeling and simulation, which have recently received much attention with the advent of the Materials Genome Initiative. Thus, the challenge for combinatorial methodology will be the effective coupling of synthesis, characterization and theory, and the ability to rapidly manage large amounts of data in a variety of formats.

Scaffold architecture and pharmacophoric properties of natural products and trade drugs: application in the design of natural product-based combinatorial libraries.

PubMed

Lee, M L; Schneider, G

2001-01-01

Natural products were analyzed to determine whether they contain appealing novel scaffold architectures for potential use in combinatorial chemistry. Ring systems were extracted and clustered on the basis of structural similarity. Several such potential scaffolds for combinatorial chemistry were identified that are not present in current trade drugs. For one of these scaffolds a virtual combinatorial library was generated. Pharmacophoric properties of natural products, trade drugs, and the virtual combinatorial library were assessed using a self-organizing map. Obviously, current trade drugs and natural products have several topological pharmacophore patterns in common. These features can be systematically explored with selected combinatorial libraries based on a combination of natural product-derived and synthetic molecular building blocks.

Discrete ellipsoidal statistical BGK model and Burnett equations

NASA Astrophysics Data System (ADS)

Zhang, Yu-Dong; Xu, Ai-Guo; Zhang, Guang-Cai; Chen, Zhi-Hua; Wang, Pei

2018-06-01

A new discrete Boltzmann model, the discrete ellipsoidal statistical Bhatnagar-Gross-Krook (ESBGK) model, is proposed to simulate nonequilibrium compressible flows. Compared with the original discrete BGK model, the discrete ES-BGK has a flexible Prandtl number. For the discrete ES-BGK model in the Burnett level, two kinds of discrete velocity model are introduced and the relations between nonequilibrium quantities and the viscous stress and heat flux in the Burnett level are established. The model is verified via four benchmark tests. In addition, a new idea is introduced to recover the actual distribution function through the macroscopic quantities and their space derivatives. The recovery scheme works not only for discrete Boltzmann simulation but also for hydrodynamic ones, for example, those based on the Navier-Stokes or the Burnett equations.

Use of combinatorial chemistry to speed drug discovery.

PubMed

Rádl, S

1998-10-01

IBC's International Conference on Integrating Combinatorial Chemistry into the Discovery Pipeline was held September 14-15, 1998. The program started with a pre-conference workshop on High-Throughput Compound Characterization and Purification. The agenda of the main conference was divided into sessions of Synthesis, Automation and Unique Chemistries; Integrating Combinatorial Chemistry, Medicinal Chemistry and Screening; Combinatorial Chemistry Applications for Drug Discovery; and Information and Data Management. This meeting was an excellent opportunity to see how big pharma, biotech and service companies are addressing the current bottlenecks in combinatorial chemistry to speed drug discovery. (c) 1998 Prous Science. All rights reserved.

Coupled Phases and Combinatorial Selection in Fluctuating Hydrothermal Pools: A Scenario to Guide Experimental Approaches to the Origin of Cellular Life

PubMed Central

Damer, Bruce; Deamer, David

2015-01-01

Hydrothermal fields on the prebiotic Earth are candidate environments for biogenesis. We propose a model in which molecular systems driven by cycles of hydration and dehydration in such sites undergo chemical evolution in dehydrated films on mineral surfaces followed by encapsulation and combinatorial selection in a hydrated bulk phase. The dehydrated phase can consist of concentrated eutectic mixtures or multilamellar liquid crystalline matrices. Both conditions organize and concentrate potential monomers and thereby promote polymerization reactions that are driven by reduced water activity in the dehydrated phase. In the case of multilamellar lipid matrices, polymers that have been synthesized are captured in lipid vesicles upon rehydration to produce a variety of molecular systems. Each vesicle represents a protocell, an “experiment” in a natural version of combinatorial chemistry. Two kinds of selective processes can then occur. The first is a physical process in which relatively stable molecular systems will be preferentially selected. The second is a chemical process in which rare combinations of encapsulated polymers form systems capable of capturing energy and nutrients to undergo growth by catalyzed polymerization. Given continued cycling over extended time spans, such combinatorial processes will give rise to molecular systems having the fundamental properties of life. PMID:25780958

Diversity-oriented combinatorial biosynthesis of benzenediol lactone scaffolds by subunit shuffling of fungal polyketide synthases.

PubMed

Xu, Yuquan; Zhou, Tong; Zhang, Shuwei; Espinosa-Artiles, Patricia; Wang, Luoyi; Zhang, Wei; Lin, Min; Gunatilaka, A A Leslie; Zhan, Jixun; Molnár, István

2014-08-26

Combinatorial biosynthesis aspires to exploit the promiscuity of microbial anabolic pathways to engineer the synthesis of new chemical entities. Fungal benzenediol lactone (BDL) polyketides are important pharmacophores with wide-ranging bioactivities, including heat shock response and immune system modulatory effects. Their biosynthesis on a pair of sequentially acting iterative polyketide synthases (iPKSs) offers a test case for the modularization of secondary metabolic pathways into "build-couple-pair" combinatorial synthetic schemes. Expression of random pairs of iPKS subunits from four BDL model systems in a yeast heterologous host created a diverse library of BDL congeners, including a polyketide with an unnatural skeleton and heat shock response-inducing activity. Pairwise heterocombinations of the iPKS subunits also helped to illuminate the innate, idiosyncratic programming of these enzymes. Even in combinatorial contexts, these biosynthetic programs remained largely unchanged, so that the iPKSs built their cognate biosynthons, coupled these building blocks into chimeric polyketide intermediates, and catalyzed intramolecular pairing to release macrocycles or α-pyrones. However, some heterocombinations also provoked stuttering, i.e., the relaxation of iPKSs chain length control to assemble larger homologous products. The success of such a plug and play approach to biosynthesize novel chemical diversity bodes well for bioprospecting unnatural polyketides for drug discovery.

Magnetic microspheres and tissue model studies for therapeutic applications

NASA Technical Reports Server (NTRS)

Ramachandran, Narayanan; Mazuruk, Konstantin

2004-01-01

The use of magnetic fluids and magnetic particles in combinatorial hyperthermia therapy for cancer treatment is reviewed. The investigation approach adopted for producing thermoregulating particles and tissue model studies for studying particle retention and heating characteristics is discussed.

Development of the Architectural Simulation Model for Future Launch Systems and its Application to an Existing Launch Fleet

NASA Technical Reports Server (NTRS)

Rabadi, Ghaith

2005-01-01

A significant portion of lifecycle costs for launch vehicles are generated during the operations phase. Research indicates that operations costs can account for a large percentage of the total life-cycle costs of reusable space transportation systems. These costs are largely determined by decisions made early during conceptual design. Therefore, operational considerations are an important part of vehicle design and concept analysis process that needs to be modeled and studied early in the design phase. However, this is a difficult and challenging task due to uncertainties of operations definitions, the dynamic and combinatorial nature of the processes, and lack of analytical models and the scarcity of historical data during the conceptual design phase. Ultimately, NASA would like to know the best mix of launch vehicle concepts that would meet the missions launch dates at the minimum cost. To answer this question, we first need to develop a model to estimate the total cost, including the operational cost, to accomplish this set of missions. In this project, we have developed and implemented a discrete-event simulation model using ARENA (a simulation modeling environment) to determine this cost assessment. Discrete-event simulation is widely used in modeling complex systems, including transportation systems, due to its flexibility, and ability to capture the dynamics of the system. The simulation model accepts manifest inputs including the set of missions that need to be accomplished over a period of time, the clients (e.g., NASA or DoD) who wish to transport the payload to space, the payload weights, and their destinations (e.g., International Space Station, LEO, or GEO). A user of the simulation model can define an architecture of reusable or expendable launch vehicles to achieve these missions. Launch vehicles may belong to different families where each family may have it own set of resources, processing times, and cost factors. The goal is to capture the required resource levels of the major launch elements and their required facilities. The model s output can show whether or not a certain architecture of vehicles can meet the launch dates, and if not, how much the delay cost would be. It will also produce aggregate figures of missions cost based on element procurement cost, processing cost, cargo integration cost, delay cost, and mission support cost. One of the most useful features of this model is that it is stochastic where it accepts statistical distributions to represent the processing times mimicking the stochastic nature of real systems.

A Discrete Fruit Fly Optimization Algorithm for the Traveling Salesman Problem.

PubMed

Jiang, Zi-Bin; Yang, Qiong

2016-01-01

The fruit fly optimization algorithm (FOA) is a newly developed bio-inspired algorithm. The continuous variant version of FOA has been proven to be a powerful evolutionary approach to determining the optima of a numerical function on a continuous definition domain. In this study, a discrete FOA (DFOA) is developed and applied to the traveling salesman problem (TSP), a common combinatorial problem. In the DFOA, the TSP tour is represented by an ordering of city indices, and the bio-inspired meta-heuristic search processes are executed with two elaborately designed main procedures: the smelling and tasting processes. In the smelling process, an effective crossover operator is used by the fruit fly group to search for the neighbors of the best-known swarm location. During the tasting process, an edge intersection elimination (EXE) operator is designed to improve the neighbors of the non-optimum food location in order to enhance the exploration performance of the DFOA. In addition, benchmark instances from the TSPLIB are classified in order to test the searching ability of the proposed algorithm. Furthermore, the effectiveness of the proposed DFOA is compared to that of other meta-heuristic algorithms. The results indicate that the proposed DFOA can be effectively used to solve TSPs, especially large-scale problems.

A Discrete Fruit Fly Optimization Algorithm for the Traveling Salesman Problem

PubMed Central

Jiang, Zi-bin; Yang, Qiong

2016-01-01

The fruit fly optimization algorithm (FOA) is a newly developed bio-inspired algorithm. The continuous variant version of FOA has been proven to be a powerful evolutionary approach to determining the optima of a numerical function on a continuous definition domain. In this study, a discrete FOA (DFOA) is developed and applied to the traveling salesman problem (TSP), a common combinatorial problem. In the DFOA, the TSP tour is represented by an ordering of city indices, and the bio-inspired meta-heuristic search processes are executed with two elaborately designed main procedures: the smelling and tasting processes. In the smelling process, an effective crossover operator is used by the fruit fly group to search for the neighbors of the best-known swarm location. During the tasting process, an edge intersection elimination (EXE) operator is designed to improve the neighbors of the non-optimum food location in order to enhance the exploration performance of the DFOA. In addition, benchmark instances from the TSPLIB are classified in order to test the searching ability of the proposed algorithm. Furthermore, the effectiveness of the proposed DFOA is compared to that of other meta-heuristic algorithms. The results indicate that the proposed DFOA can be effectively used to solve TSPs, especially large-scale problems. PMID:27812175

Elastic properties of fcc Fe-Mn-X (X = Cr, Co, Ni, Cu) alloys studied by the combinatorial thin film approach and ab initio calculations.

PubMed

Reeh, S; Kasprzak, M; Klusmann, C D; Stalf, F; Music, D; Ekholm, M; Abrikosov, I A; Schneider, J M

2013-06-19

The elastic properties of fcc Fe-Mn-X (X = Cr, Co, Ni, Cu) alloys with additions of up to 8 at.% X were studied by combinatorial thin film growth and characterization and by ab initio calculations using the disordered local moments (DLM) approach. The lattice parameter and Young's modulus values change only marginally with X. The calculations and experiments are in good agreement. We demonstrate that the elastic properties of transition metal alloyed Fe-Mn can be predicted by the DLM model.

A combinatorial model of malware diffusion via bluetooth connections.

PubMed

Merler, Stefano; Jurman, Giuseppe

2013-01-01

We outline here the mathematical expression of a diffusion model for cellphones malware transmitted through Bluetooth channels. In particular, we provide the deterministic formula underlying the proposed infection model, in its equivalent recursive (simple but computationally heavy) and closed form (more complex but efficiently computable) expression.

A binomial modeling approach for upscaling colloid transport under unfavorable conditions: Emergent prediction of extended tailing

NASA Astrophysics Data System (ADS)

Hilpert, Markus; Rasmuson, Anna; Johnson, William P.

2017-07-01

Colloid transport in saturated porous media is significantly influenced by colloidal interactions with grain surfaces. Near-surface fluid domain colloids experience relatively low fluid drag and relatively strong colloidal forces that slow their downgradient translation relative to colloids in bulk fluid. Near-surface fluid domain colloids may reenter into the bulk fluid via diffusion (nanoparticles) or expulsion at rear flow stagnation zones, they may immobilize (attach) via primary minimum interactions, or they may move along a grain-to-grain contact to the near-surface fluid domain of an adjacent grain. We introduce a simple model that accounts for all possible permutations of mass transfer within a dual pore and grain network. The primary phenomena thereby represented in the model are mass transfer of colloids between the bulk and near-surface fluid domains and immobilization. Colloid movement is described by a Markov chain, i.e., a sequence of trials in a 1-D network of unit cells, which contain a pore and a grain. Using combinatorial analysis, which utilizes the binomial coefficient, we derive the residence time distribution, i.e., an inventory of the discrete colloid travel times through the network and of their probabilities to occur. To parameterize the network model, we performed mechanistic pore-scale simulations in a single unit cell that determined the likelihoods and timescales associated with the above colloid mass transfer processes. We found that intergrain transport of colloids in the near-surface fluid domain can cause extended tailing, which has traditionally been attributed to hydrodynamic dispersion emanating from flow tortuosity of solute trajectories.

MIFT: GIFT Combinatorial Geometry Input to VCS Code

DTIC Science & Technology

1977-03-01

r-w w-^ H ^ß0318is CQ BRL °RCUMr REPORT NO. 1967 —-S: ... MIFT: GIFT COMBINATORIAL GEOMETRY INPUT TO VCS CODE Albert E...TITLE (and Subtitle) MIFT: GIFT Combinatorial Geometry Input to VCS Code S. TYPE OF REPORT & PERIOD COVERED FINAL 6. PERFORMING ORG. REPORT NUMBER...Vehicle Code System (VCS) called MORSE was modified to accept the GIFT combinatorial geometry package. GIFT , as opposed to the geometry package

Combinatorial influence of environmental parameters on transcription factor activity

PubMed Central

Knijnenburg, T.A.; Wessels, L.F.A.; Reinders, M.J.T.

2008-01-01

Motivation: Cells receive a wide variety of environmental signals, which are often processed combinatorially to generate specific genetic responses. Changes in transcript levels, as observed across different environmental conditions, can, to a large extent, be attributed to changes in the activity of transcription factors (TFs). However, in unraveling these transcription regulation networks, the actual environmental signals are often not incorporated into the model, simply because they have not been measured. The unquantified heterogeneity of the environmental parameters across microarray experiments frustrates regulatory network inference. Results: We propose an inference algorithm that models the influence of environmental parameters on gene expression. The approach is based on a yeast microarray compendium of chemostat steady-state experiments. Chemostat cultivation enables the accurate control and measurement of many of the key cultivation parameters, such as nutrient concentrations, growth rate and temperature. The observed transcript levels are explained by inferring the activity of TFs in response to combinations of cultivation parameters. The interplay between activated enhancers and repressors that bind a gene promoter determine the possible up- or downregulation of the gene. The model is translated into a linear integer optimization problem. The resulting regulatory network identifies the combinatorial effects of environmental parameters on TF activity and gene expression. Availability: The Matlab code is available from the authors upon request. Contact: t.a.knijnenburg@tudelft.nl Supplementary information: Supplementary data are available at Bioinformatics online. PMID:18586711

Observables of QCD diffraction

NASA Astrophysics Data System (ADS)

Mieskolainen, Mikael; Orava, Risto

2017-03-01

A new combinatorial vector space measurement model is introduced for soft QCD diffraction. The model independent mathematical construction resolves experimental complications; the theoretical framework of the approach includes the Good-Walker view of diffraction, Regge phenomenology together with AGK cutting rules and random fluctuations.

Polymeric nanofiber coating with tunable combinatorial antibiotic delivery prevents biofilm-associated infection in vivo

PubMed Central

Ashbaugh, Alyssa G.; Jiang, Xuesong; Zheng, Jesse; Tsai, Andrew S.; Kim, Woo-Shin; Thompson, John M.; Miller, Robert J.; Shahbazian, Jonathan H.; Wang, Yu; Dillen, Carly A.; Ordonez, Alvaro A.; Chang, Yong S.; Jain, Sanjay K.; Jones, Lynne C.; Sterling, Robert S.; Mao, Hai-Quan; Miller, Lloyd S.

2016-01-01

Bacterial biofilm formation is a major complication of implantable medical devices that results in therapeutically challenging chronic infections, especially in cases involving antibiotic-resistant bacteria. As an approach to prevent these infections, an electrospun composite coating comprised of poly(lactic-coglycolic acid) (PLGA) nanofibers embedded in a poly(ε-caprolactone) (PCL) film was developed to locally codeliver combinatorial antibiotics from the implant surface. The release of each antibiotic could be adjusted by loading each drug into the different polymers or by varying PLGA:PCL polymer ratios. In a mouse model of biofilm-associated orthopedic-implant infection, three different combinations of antibiotic-loaded coatings were highly effective in preventing infection of the bone/joint tissue and implant biofilm formation and were biocompatible with enhanced osseointegration. This nanofiber composite-coating technology could be used to tailor the delivery of combinatorial antimicrobial agents from various metallic implantable devices or prostheses to effectively decrease biofilm-associated infections in patients. PMID:27791154

On the consistency between nearest-neighbor peridynamic discretizations and discretized classical elasticity models

DOE PAGES

Seleson, Pablo; Du, Qiang; Parks, Michael L.

2016-08-16

The peridynamic theory of solid mechanics is a nonlocal reformulation of the classical continuum mechanics theory. At the continuum level, it has been demonstrated that classical (local) elasticity is a special case of peridynamics. Such a connection between these theories has not been extensively explored at the discrete level. This paper investigates the consistency between nearest-neighbor discretizations of linear elastic peridynamic models and finite difference discretizations of the Navier–Cauchy equation of classical elasticity. While nearest-neighbor discretizations in peridynamics have been numerically observed to present grid-dependent crack paths or spurious microcracks, this paper focuses on a different, analytical aspect of suchmore » discretizations. We demonstrate that, even in the absence of cracks, such discretizations may be problematic unless a proper selection of weights is used. Specifically, we demonstrate that using the standard meshfree approach in peridynamics, nearest-neighbor discretizations do not reduce, in general, to discretizations of corresponding classical models. We study nodal-based quadratures for the discretization of peridynamic models, and we derive quadrature weights that result in consistency between nearest-neighbor discretizations of peridynamic models and discretized classical models. The quadrature weights that lead to such consistency are, however, model-/discretization-dependent. We motivate the choice of those quadrature weights through a quadratic approximation of displacement fields. The stability of nearest-neighbor peridynamic schemes is demonstrated through a Fourier mode analysis. Finally, an approach based on a normalization of peridynamic constitutive constants at the discrete level is explored. This approach results in the desired consistency for one-dimensional models, but does not work in higher dimensions. The results of the work presented in this paper suggest that even though nearest-neighbor discretizations should be avoided in peridynamic simulations involving cracks, such discretizations are viable, for example for verification or validation purposes, in problems characterized by smooth deformations. Furthermore, we demonstrate that better quadrature rules in peridynamics can be obtained based on the functional form of solutions.« less

A Combinatorial Model of Malware Diffusion via Bluetooth Connections

PubMed Central

Merler, Stefano; Jurman, Giuseppe

2013-01-01

We outline here the mathematical expression of a diffusion model for cellphones malware transmitted through Bluetooth channels. In particular, we provide the deterministic formula underlying the proposed infection model, in its equivalent recursive (simple but computationally heavy) and closed form (more complex but efficiently computable) expression. PMID:23555677

Small-kernel, constrained least-squares restoration of sampled image data

NASA Technical Reports Server (NTRS)

Hazra, Rajeeb; Park, Stephen K.

1992-01-01

Following the work of Park (1989), who extended a derivation of the Wiener filter based on the incomplete discrete/discrete model to a more comprehensive end-to-end continuous/discrete/continuous model, it is shown that a derivation of the constrained least-squares (CLS) filter based on the discrete/discrete model can also be extended to this more comprehensive continuous/discrete/continuous model. This results in an improved CLS restoration filter, which can be efficiently implemented as a small-kernel convolution in the spatial domain.

Structural Validation of Nursing Terminologies

PubMed Central

Hardiker, Nicholas R.; Rector, Alan L.

2001-01-01

Objective: The purpose of the study is twofold: 1) to explore the applicability of combinatorial terminologies as the basis for building enumerated classifications, and 2) to investigate the usefulness of formal terminological systems for performing such classification and for assisting in the refinement of both combinatorial terminologies and enumerated classifications. Design: A formal model of the beta version of the International Classification for Nursing Practice (ICNP) was constructed in the compositional terminological language GRAIL (GALEN Representation and Integration Language). Terms drawn from the North American Nursing Diagnosis Association Taxonomy I (NANDA taxonomy) were mapped into the model and classified automatically using GALEN technology. Measurements: The resulting generated hierarchy was compared with the NANDA taxonomy to assess coverage and accuracy of classification. Results: In terms of coverage, in this study ICNP was able to capture 77 percent of NANDA terms using concepts drawn from five of its eight axes. Three axes—Body Site, Topology, and Frequency—were not needed. In terms of accuracy, where hierarchic relationships existed in the generated hierarchy or the NANDA taxonomy, or both, 6 were identical, 19 existed in the generated hierarchy alone (2 of these were considered suitable for incorporation into the NANDA taxonomy and 17 were considered inaccurate), and 23 appeared in the NANDA taxonomy alone (8 of these were considered suitable for incorporation into ICNP, 9 were considered inaccurate, and 6 reflected different, equally valid perspectives). Sixty terms appeared at the top level, with no indenting, in both the generated hierarchy and the NANDA taxonomy. Conclusions: With appropriate refinement, combinatorial terminologies such as ICNP have the potential to provide a useful foundation for representing enumerated classifications such as NANDA. Technologies such as GALEN make possible the process of building automatically enumerated classifications while providing a useful means of validating and refining both combinatorial terminologies and enumerated classifications. PMID:11320066

FOREWORD: Focus on Combinatorial Materials Science Focus on Combinatorial Materials Science

NASA Astrophysics Data System (ADS)

Chikyo, Toyohiro

2011-10-01

About 15 years have passed since the introduction of modern combinatorial synthesis and high-throughput techniques for the development of novel inorganic materials; however, similar methods existed before. The most famous was reported in 1970 by Hanak who prepared composition-spread films of metal alloys by sputtering mixed-material targets. Although this method was innovative, it was rarely used because of the large amount of data to be processed. This problem is solved in the modern combinatorial material research, which is strongly related to computer data analysis and robotics. This field is still at the developing stage and may be enriched by new methods. Nevertheless, given the progress in measurement equipment and procedures, we believe the combinatorial approach will become a major and standard tool of materials screening and development. The first article of this journal, published in 2000, was titled 'Combinatorial solid state materials science and technology', and this focus issue aims to reintroduce this topic to the Science and Technology of Advanced Materials audience. It covers recent progress in combinatorial materials research describing new results in catalysis, phosphors, polymers and metal alloys for shape memory materials. Sophisticated high-throughput characterization schemes and innovative synthesis tools are also presented, such as spray deposition using nanoparticles or ion plating. On a technical note, data handling systems are introduced to familiarize researchers with the combinatorial methodology. We hope that through this focus issue a wide audience of materials scientists can learn about recent and future trends in combinatorial materials science and high-throughput experimentation.

Combinatorial anticancer effects of curcumin and 5-fluorouracil loaded thiolated chitosan nanoparticles towards colon cancer treatment.

PubMed

Anitha, A; Deepa, N; Chennazhi, K P; Lakshmanan, Vinoth-Kumar; Jayakumar, R

2014-09-01

Evaluation of the combinatorial anticancer effects of curcumin/5-fluorouracil loaded thiolated chitosan nanoparticles (CRC-TCS-NPs/5-FU-TCS-NPs) on colon cancer cells and the analysis of pharmacokinetics and biodistribution of CRC-TCS-NPs/5-FU-TCS-NPs in a mouse model. CRC-TCS-NPs/5-FU-TCS-NPs were developed by ionic cross-linking. The in vitro combinatorial anticancer effect of the nanomedicine was proven by different assays. Further the pharmacokinetics and biodistribution analyses were performed in Swiss Albino mouse using HPLC. The 5-FU-TCS-NPs (size: 150±40nm, zeta potential: +48.2±5mV) and CRC-TCS-NPs (size: 150±20nm, zeta potential: +35.7±3mV) were proven to be compatible with blood. The in vitro drug release studies at pH4.5 and 7.4 showed a sustained release profile over a period of 4 days, where both the systems exhibited a higher release in acidic pH. The in vitro combinatorial anticancer effects in colon cancer (HT29) cells using MTT, live/dead, mitochondrial membrane potential and cell cycle analysis measurements confirmed the enhanced anticancer effects (2.5 to 3 fold). The pharmacokinetic studies confirmed the improved plasma concentrations of 5-FU and CRC up to 72h, unlike bare CRC and 5-FU. To conclude, the combination of 5-FU-TCS-NPs and CRC-TCS-NPs showed enhanced anticancer effects on colon cancer cells in vitro and improved the bioavailability of the drugs in vivo. The enhanced anticancer effects of combinatorial nanomedicine are advantageous in terms of reduction in the dosage of 5-FU, thereby improving the chemotherapeutic efficacy and patient compliance of colorectal cancer cases. Copyright © 2014 Elsevier B.V. All rights reserved.

A priori discretization error metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan A.; Craig, James R.; Shafii, Mahyar

2016-12-01

Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a subbasin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under candidate discretization schemes validate the strong correlation between the proposed discretization error metrics and hydrologic simulation responses. Discretization decision-making results show that the common and convenient approach of making uniform discretization decisions across the watershed performs worse than the proposed non-uniform discretization approach in terms of preserving spatial heterogeneity under the same computational cost.

Evaluation of the Optimum Composition of Low-Temperature Fuel Cell Electrocatalysts for Methanol Oxidation by Combinatorial Screening.

PubMed

Antolini, Ermete

2017-02-13

Combinatorial chemistry and high-throughput screening represent an innovative and rapid tool to prepare and evaluate a large number of new materials, saving time and expense for research and development. Considering that the activity and selectivity of catalysts depend on complex kinetic phenomena, making their development largely empirical in practice, they are prime candidates for combinatorial discovery and optimization. This review presents an overview of recent results of combinatorial screening of low-temperature fuel cell electrocatalysts for methanol oxidation. Optimum catalyst compositions obtained by combinatorial screening were compared with those of bulk catalysts, and the effect of the library geometry on the screening of catalyst composition is highlighted.

Combinatorial computational chemistry approach for materials design: applications in deNOx catalysis, Fischer-Tropsch synthesis, lanthanoid complex, and lithium ion secondary battery.

PubMed

Koyama, Michihisa; Tsuboi, Hideyuki; Endou, Akira; Takaba, Hiromitsu; Kubo, Momoji; Del Carpio, Carlos A; Miyamoto, Akira

2007-02-01

Computational chemistry can provide fundamental knowledge regarding various aspects of materials. While its impact in scientific research is greatly increasing, its contributions to industrially important issues are far from satisfactory. In order to realize industrial innovation by computational chemistry, a new concept "combinatorial computational chemistry" has been proposed by introducing the concept of combinatorial chemistry to computational chemistry. This combinatorial computational chemistry approach enables theoretical high-throughput screening for materials design. In this manuscript, we review the successful applications of combinatorial computational chemistry to deNO(x) catalysts, Fischer-Tropsch catalysts, lanthanoid complex catalysts, and cathodes of the lithium ion secondary battery.

Replicator equations, maximal cliques, and graph isomorphism.

PubMed

Pelillo, M

1999-11-15

We present a new energy-minimization framework for the graph isomorphism problem that is based on an equivalent maximum clique formulation. The approach is centered around a fundamental result proved by Motzkin and Straus in the mid-1960s, and recently expanded in various ways, which allows us to formulate the maximum clique problem in terms of a standard quadratic program. The attractive feature of this formulation is that a clear one-to-one correspondence exists between the solutions of the quadratic program and those in the original, combinatorial problem. To solve the program we use the so-called replicator equations--a class of straightforward continuous- and discrete-time dynamical systems developed in various branches of theoretical biology. We show how, despite their inherent inability to escape from local solutions, they nevertheless provide experimental results that are competitive with those obtained using more elaborate mean-field annealing heuristics.

Gain-Sparsity and Symmetry-Forced Rigidity in the Plane.

PubMed

Jordán, Tibor; Kaszanitzky, Viktória E; Tanigawa, Shin-Ichi

We consider planar bar-and-joint frameworks with discrete point group symmetry in which the joint positions are as generic as possible subject to the symmetry constraint. We provide combinatorial characterizations for symmetry-forced rigidity of such structures with rotation symmetry or dihedral symmetry of order 2 k with odd k , unifying and extending previous work on this subject. We also explore the matroidal background of our results and show that the matroids induced by the row independence of the orbit matrices of the symmetric frameworks are isomorphic to gain sparsity matroids defined on the quotient graph of the framework, whose edges are labeled by elements of the corresponding symmetry group. The proofs are based on new Henneberg type inductive constructions of the gain graphs that correspond to the bases of the matroids in question, which can also be seen as symmetry preserving graph operations in the original graph.

An Analytical Framework for Runtime of a Class of Continuous Evolutionary Algorithms.

PubMed

Zhang, Yushan; Hu, Guiwu

2015-01-01

Although there have been many studies on the runtime of evolutionary algorithms in discrete optimization, relatively few theoretical results have been proposed on continuous optimization, such as evolutionary programming (EP). This paper proposes an analysis of the runtime of two EP algorithms based on Gaussian and Cauchy mutations, using an absorbing Markov chain. Given a constant variation, we calculate the runtime upper bound of special Gaussian mutation EP and Cauchy mutation EP. Our analysis reveals that the upper bounds are impacted by individual number, problem dimension number n, searching range, and the Lebesgue measure of the optimal neighborhood. Furthermore, we provide conditions whereby the average runtime of the considered EP can be no more than a polynomial of n. The condition is that the Lebesgue measure of the optimal neighborhood is larger than a combinatorial calculation of an exponential and the given polynomial of n.

Gradient Material Strategies for Hydrogel Optimization in Tissue Engineering Applications

PubMed Central

2018-01-01

Although a number of combinatorial/high-throughput approaches have been developed for biomaterial hydrogel optimization, a gradient sample approach is particularly well suited to identify hydrogel property thresholds that alter cellular behavior in response to interacting with the hydrogel due to reduced variation in material preparation and the ability to screen biological response over a range instead of discrete samples each containing only one condition. This review highlights recent work on cell–hydrogel interactions using a gradient material sample approach. Fabrication strategies for composition, material and mechanical property, and bioactive signaling gradient hydrogels that can be used to examine cell–hydrogel interactions will be discussed. The effects of gradients in hydrogel samples on cellular adhesion, migration, proliferation, and differentiation will then be examined, providing an assessment of the current state of the field and the potential of wider use of the gradient sample approach to accelerate our understanding of matrices on cellular behavior. PMID:29485612

On the way to language: event segmentation in homesign and gesture*

PubMed Central

ÖZYÜREK, ASLI; FURMAN, REYHAN; GOLDIN-MEADOW, SUSAN

2014-01-01

Languages typically express semantic components of motion events such as manner (roll) and path (down) in separate lexical items. We explore how these combinatorial possibilities of language arise by focusing on (i) gestures produced by deaf children who lack access to input from a conventional language (homesign); (ii) gestures produced by hearing adults and children while speaking; and (iii) gestures used by hearing adults without speech when asked to do so in elicited descriptions of motion events with simultaneous manner and path. Homesigners tended to conflate manner and path in one gesture, but also used a mixed form, adding a manner and/or path gesture to the conflated form sequentially. Hearing speakers, with or without speech, used the conflated form, gestured manner, or path, but rarely used the mixed form. Mixed form may serve as an intermediate structure on the way to the discrete and sequenced forms found in natural languages. PMID:24650738

Geometry Helps to Compare Persistence Diagrams

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

Kerber, Michael; Morozov, Dmitriy; Nigmetov, Arnur

2015-11-16

Exploiting geometric structure to improve the asymptotic complexity of discrete assignment problems is a well-studied subject. In contrast, the practical advantages of using geometry for such problems have not been explored. We implement geometric variants of the Hopcroft--Karp algorithm for bottleneck matching (based on previous work by Efrat el al.), and of the auction algorithm by Bertsekas for Wasserstein distance computation. Both implementations use k-d trees to replace a linear scan with a geometric proximity query. Our interest in this problem stems from the desire to compute distances between persistence diagrams, a problem that comes up frequently in topological datamore » analysis. We show that our geometric matching algorithms lead to a substantial performance gain, both in running time and in memory consumption, over their purely combinatorial counterparts. Moreover, our implementation significantly outperforms the only other implementation available for comparing persistence diagrams.« less

Exome sequence analysis suggests genetic burden contributes to phenotypic variability and complex neuropathy

PubMed Central

Gonzaga-Jauregui, Claudia; Harel, Tamar; Gambin, Tomasz; Kousi, Maria; Griffin, Laurie B.; Francescatto, Ludmila; Ozes, Burcak; Karaca, Ender; Jhangiani, Shalini; Bainbridge, Matthew N.; Lawson, Kim S.; Pehlivan, Davut; Okamoto, Yuji; Withers, Marjorie; Mancias, Pedro; Slavotinek, Anne; Reitnauer, Pamela J; Goksungur, Meryem T.; Shy, Michael; Crawford, Thomas O.; Koenig, Michel; Willer, Jason; Flores, Brittany N.; Pediaditrakis, Igor; Us, Onder; Wiszniewski, Wojciech; Parman, Yesim; Antonellis, Anthony; Muzny, Donna M.; Katsanis, Nicholas; Battaloglu, Esra; Boerwinkle, Eric; Gibbs, Richard A.; Lupski, James R.

2015-01-01

Charcot-Marie-Tooth (CMT) disease is a clinically and genetically heterogeneous distal symmetric polyneuropathy. Whole-exome sequencing (WES) of 40 individuals from 37 unrelated families with CMT-like peripheral neuropathy refractory to molecular diagnosis identified apparent causal mutations in ~45% (17/37) of families. Three candidate disease genes are proposed, supported by a combination of genetic and in vivo studies. Aggregate analysis of mutation data revealed a significantly increased number of rare variants across 58 neuropathy associated genes in subjects versus controls; confirmed in a second ethnically discrete neuropathy cohort, suggesting mutation burden potentially contributes to phenotypic variability. Neuropathy genes shown to have highly penetrant Mendelizing variants (HMPVs) and implicated by burden in families were shown to interact genetically in a zebrafish assay exacerbating the phenotype established by the suppression of single genes. Our findings suggest that the combinatorial effect of rare variants contributes to disease burden and variable expressivity. PMID:26257172

Theory of Stochastic Laplacian Growth

NASA Astrophysics Data System (ADS)

Alekseev, Oleg; Mineev-Weinstein, Mark

2017-07-01

We generalize the diffusion-limited aggregation by issuing many randomly-walking particles, which stick to a cluster at the discrete time unit providing its growth. Using simple combinatorial arguments we determine probabilities of different growth scenarios and prove that the most probable evolution is governed by the deterministic Laplacian growth equation. A potential-theoretical analysis of the growth probabilities reveals connections with the tau-function of the integrable dispersionless limit of the two-dimensional Toda hierarchy, normal matrix ensembles, and the two-dimensional Dyson gas confined in a non-uniform magnetic field. We introduce the time-dependent Hamiltonian, which generates transitions between different classes of equivalence of closed curves, and prove the Hamiltonian structure of the interface dynamics. Finally, we propose a relation between probabilities of growth scenarios and the semi-classical limit of certain correlation functions of "light" exponential operators in the Liouville conformal field theory on a pseudosphere.

Discrete event simulation model for external yard choice of import container terminal in a port buffer area

NASA Astrophysics Data System (ADS)

Rusgiyarto, Ferry; Sjafruddin, Ade; Frazila, Russ Bona; Suprayogi

2017-06-01

Increasing container traffic and land acquisition problem for terminal expansion leads to usage of external yard in a port buffer area. This condition influenced the terminal performance because a road which connects the terminal and the external yard was also used by non-container traffic. Location choice problem considered to solve this condition, but the previous research has not taken account a stochastic condition of container arrival rate and service time yet. Bi-level programming framework was used to find optimum location configuration. In the lower-level, there was a problem to construct the equation, which correlated the terminal operation and the road due to different time cycle equilibrium. Container moves from the quay to a terminal gate in a daily unit of time, meanwhile, it moves from the terminal gate to the external yard through the road in a minute unit of time. If the equation formulated in hourly unit equilibrium, it cannot catch up the container movement characteristics in the terminal. Meanwhile, if the equation formulated in daily unit equilibrium, it cannot catch up the road traffic movement characteristics in the road. This problem can be addressed using simulation model. Discrete Event Simulation Model was used to simulate import container flow processes in the container terminal and external yard. Optimum location configuration in the upper-level was the combinatorial problem, which was solved by Full Enumeration approach. The objective function of the external yard location model was to minimize user transport cost (or time) and to maximize operator benefit. Numerical experiment was run for the scenario assumption of two container handling ways, three external yards, and thirty-day simulation periods. Jakarta International Container Terminal (JICT) container characteristics data was referred for the simulation. Based on five runs which were 5, 10, 15, 20, and 30 repetitions, operation one of three available external yards (external yard - 3) was the optimum result. Apparently, the model confirmed the hypothesis that there was an optimum configuration of the external yard. Nevertheless, the model needs detail elaboration related to the objective function and the optimization constraint. It requires detail validation, in term of service time value, distribution pattern, and arrival rate in each unit server modeled in the next step of the research. The model gave unique and relatively consistent value of each run. It was indicated that the method has a chance to solve the research problem.

On the discretization and control of an SEIR epidemic model with a periodic impulsive vaccination

NASA Astrophysics Data System (ADS)

Alonso-Quesada, S.; De la Sen, M.; Ibeas, A.

2017-01-01

This paper deals with the discretization and control of an SEIR epidemic model. Such a model describes the transmission of an infectious disease among a time-varying host population. The model assumes mortality from causes related to the disease. Our study proposes a discretization method including a free-design parameter to be adjusted for guaranteeing the positivity of the resulting discrete-time model. Such a method provides a discrete-time model close to the continuous-time one without the need for the sampling period to be as small as other commonly used discretization methods require. This fact makes possible the design of impulsive vaccination control strategies with less burden of measurements and related computations if one uses the proposed instead of other discretization methods. The proposed discretization method and the impulsive vaccination strategy designed on the resulting discretized model are the main novelties of the paper. The paper includes (i) the analysis of the positivity of the obtained discrete-time SEIR model, (ii) the study of stability of the disease-free equilibrium point of a normalized version of such a discrete-time model and (iii) the existence and the attractivity of a globally asymptotically stable disease-free periodic solution under a periodic impulsive vaccination. Concretely, the exposed and infectious subpopulations asymptotically converge to zero as time tends to infinity while the normalized subpopulations of susceptible and recovered by immunization individuals oscillate in the context of such a solution. Finally, a numerical example illustrates the theoretic results.

Chemoinformatic Analysis of Combinatorial Libraries, Drugs, Natural Products and Molecular Libraries Small Molecule Repository

PubMed Central

Singh, Narender; Guha, Rajarshi; Giulianotti, Marc; Pinilla, Clemencia; Houghten, Richard; Medina-Franco, Jose L.

2009-01-01

A multiple criteria approach is presented, that is used to perform a comparative analysis of four recently developed combinatorial libraries to drugs, Molecular Libraries Small Molecule Repository (MLSMR) and natural products. The compound databases were assessed in terms of physicochemical properties, scaffolds and fingerprints. The approach enables the analysis of property space coverage, degree of overlap between collections, scaffold and structural diversity and overall structural novelty. The degree of overlap between combinatorial libraries and drugs was assessed using the R-NN curve methodology, which measures the density of chemical space around a query molecule embedded in the chemical space of a target collection. The combinatorial libraries studied in this work exhibit scaffolds that were not observed in the drug, MLSMR and natural products collections. The fingerprint-based comparisons indicate that these combinatorial libraries are structurally different to current drugs. The R-NN curve methodology revealed that a proportion of molecules in the combinatorial libraries are located within the property space of the drugs. However, the R-NN analysis also showed that there are a significant number of molecules in several combinatorial libraries that are located in sparse regions of the drug space. PMID:19301827

A priori discretization quality metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan; Craig, James; Shafii, Mahyar; Basu, Nandita

2016-04-01

In distributed hydrologic modelling, a watershed is treated as a set of small homogeneous units that address the spatial heterogeneity of the watershed being simulated. The ability of models to reproduce observed spatial patterns firstly depends on the spatial discretization, which is the process of defining homogeneous units in the form of grid cells, subwatersheds, or hydrologic response units etc. It is common for hydrologic modelling studies to simply adopt a nominal or default discretization strategy without formally assessing alternative discretization levels. This approach lacks formal justifications and is thus problematic. More formalized discretization strategies are either a priori or a posteriori with respect to building and running a hydrologic simulation model. A posteriori approaches tend to be ad-hoc and compare model calibration and/or validation performance under various watershed discretizations. The construction and calibration of multiple versions of a distributed model can become a seriously limiting computational burden. Current a priori approaches are more formalized and compare overall heterogeneity statistics of dominant variables between candidate discretization schemes and input data or reference zones. While a priori approaches are efficient and do not require running a hydrologic model, they do not fully investigate the internal spatial pattern changes of variables of interest. Furthermore, the existing a priori approaches focus on landscape and soil data and do not assess impacts of discretization on stream channel definition even though its significance has been noted by numerous studies. The primary goals of this study are to (1) introduce new a priori discretization quality metrics considering the spatial pattern changes of model input data; (2) introduce a two-step discretization decision-making approach to compress extreme errors and meet user-specified discretization expectations through non-uniform discretization threshold modification. The metrics for the first time provides quantification of the routing relevant information loss due to discretization according to the relationship between in-channel routing length and flow velocity. Moreover, it identifies and counts the spatial pattern changes of dominant hydrological variables by overlaying candidate discretization schemes upon input data and accumulating variable changes in area-weighted way. The metrics are straightforward and applicable to any semi-distributed or fully distributed hydrological model with grid scales are greater than input data resolutions. The discretization metrics and decision-making approach are applied to the Grand River watershed located in southwestern Ontario, Canada where discretization decisions are required for a semi-distributed modelling application. Results show that discretization induced information loss monotonically increases as discretization gets rougher. With regards to routing information loss in subbasin discretization, multiple interesting points rather than just the watershed outlet should be considered. Moreover, subbasin and HRU discretization decisions should not be considered independently since subbasin input significantly influences the complexity of HRU discretization result. Finally, results show that the common and convenient approach of making uniform discretization decisions across the watershed domain performs worse compared to a metric informed non-uniform discretization approach as the later since is able to conserve more watershed heterogeneity under the same model complexity (number of computational units).

Extended Maptree: a Representation of Fine-Grained Topology and Spatial Hierarchy of Bim

NASA Astrophysics Data System (ADS)

Wu, Y.; Shang, J.; Hu, X.; Zhou, Z.

2017-09-01

Spatial queries play significant roles in exchanging Building Information Modeling (BIM) data and integrating BIM with indoor spatial information. However, topological operators implemented for BIM spatial queries are limited to qualitative relations (e.g. touching, intersecting). To overcome this limitation, we propose an extended maptree model to represent the fine-grained topology and spatial hierarchy of indoor spaces. The model is based on a maptree which consists of combinatorial maps and an adjacency tree. Topological relations (e.g., adjacency, incidence, and covering) derived from BIM are represented explicitly and formally by extended maptrees, which can facilitate the spatial queries of BIM. To construct an extended maptree, we first use a solid model represented by vertical extrusion and boundary representation to generate the isolated 3-cells of combinatorial maps. Then, the spatial relationships defined in IFC are used to sew them together. Furthermore, the incremental edges of extended maptrees are labeled as removed 2-cells. Based on this, we can merge adjacent 3-cells according to the spatial hierarchy of IFC.

Smooth Constrained Heuristic Optimization of a Combinatorial Chemical Space

DTIC Science & Technology

2015-05-01

ARL-TR-7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...

Preparation of cherry-picked combinatorial libraries by string synthesis.

PubMed

Furka, Arpád; Dibó, Gábor; Gombosuren, Naran

2005-03-01

String synthesis [1-3] is an efficient and cheap manual method for preparation of combinatorial libraries by using macroscopic solid support units. Sorting the units between two synthetic steps is an important operation of the procedure. The software developed to guide sorting can be used only when complete combinatorial libraries are prepared. Since very often only selected components of the full libraries are needed, new software was constructed that guides sorting in preparation of non-complete combinatorial libraries. Application of the software is described in details.

What Diagrams Argue in Late Imperial Chinese Combinatorial Texts.

PubMed

Bréard, Andrea

2015-01-01

Attitudes towards diagrammatic reasoning and visualization in mathematics were seldom spelled out in texts from pre-modern China, although illustrations figure prominently in mathematical literature since the eleventh century. Taking the sums of finite series and their combinatorial interpretation as a case study, this article investigates the epistemological function of illustrations from the eleventh to the nineteenth century that encode either the mathematical objects themselves or represent their related algorithms. It particularly focuses on the two illustrations given in Wang Lai's (1768-1813) Mathematical Principles of Sequential Combinations, arguing that they reflect a specific mode of nineteenth-century mathematical argumentative practice and served as a heuristic model for later authors.

Unitals and ovals of symmetric block designs in LDPC and space-time coding

NASA Astrophysics Data System (ADS)

Andriamanalimanana, Bruno R.

2004-08-01

An approach to the design of LDPC (low density parity check) error-correction and space-time modulation codes involves starting with known mathematical and combinatorial structures, and deriving code properties from structure properties. This paper reports on an investigation of unital and oval configurations within generic symmetric combinatorial designs, not just classical projective planes, as the underlying structure for classes of space-time LDPC outer codes. Of particular interest are the encoding and iterative (sum-product) decoding gains that these codes may provide. Various small-length cases have been numerically implemented in Java and Matlab for a number of channel models.

Rule-based modeling and simulations of the inner kinetochore structure.

PubMed

Tschernyschkow, Sergej; Herda, Sabine; Gruenert, Gerd; Döring, Volker; Görlich, Dennis; Hofmeister, Antje; Hoischen, Christian; Dittrich, Peter; Diekmann, Stephan; Ibrahim, Bashar

2013-09-01

Combinatorial complexity is a central problem when modeling biochemical reaction networks, since the association of a few components can give rise to a large variation of protein complexes. Available classical modeling approaches are often insufficient for the analysis of very large and complex networks in detail. Recently, we developed a new rule-based modeling approach that facilitates the analysis of spatial and combinatorially complex problems. Here, we explore for the first time how this approach can be applied to a specific biological system, the human kinetochore, which is a multi-protein complex involving over 100 proteins. Applying our freely available SRSim software to a large data set on kinetochore proteins in human cells, we construct a spatial rule-based simulation model of the human inner kinetochore. The model generates an estimation of the probability distribution of the inner kinetochore 3D architecture and we show how to analyze this distribution using information theory. In our model, the formation of a bridge between CenpA and an H3 containing nucleosome only occurs efficiently for higher protein concentration realized during S-phase but may be not in G1. Above a certain nucleosome distance the protein bridge barely formed pointing towards the importance of chromatin structure for kinetochore complex formation. We define a metric for the distance between structures that allow us to identify structural clusters. Using this modeling technique, we explore different hypothetical chromatin layouts. Applying a rule-based network analysis to the spatial kinetochore complex geometry allowed us to integrate experimental data on kinetochore proteins, suggesting a 3D model of the human inner kinetochore architecture that is governed by a combinatorial algebraic reaction network. This reaction network can serve as bridge between multiple scales of modeling. Our approach can be applied to other systems beyond kinetochores. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Validation of an Instrument and Testing Protocol for Measuring the Combinatorial Analysis Schema.

ERIC Educational Resources Information Center

Staver, John R.; Harty, Harold

1979-01-01

Designs a testing situation to examine the presence of combinatorial analysis, to establish construct validity in the use of an instrument, Combinatorial Analysis Behavior Observation Scheme (CABOS), and to investigate the presence of the schema in young adolescents. (Author/GA)

BPS counting for knots and combinatorics on words

NASA Astrophysics Data System (ADS)

Kucharski, Piotr; Sułkowski, Piotr

2016-11-01

We discuss relations between quantum BPS invariants defined in terms of a product decomposition of certain series, and difference equations (quantum A-polynomials) that annihilate such series. We construct combinatorial models whose structure is encoded in the form of such difference equations, and whose generating functions (Hilbert-Poincaré series) are solutions to those equations and reproduce generating series that encode BPS invariants. Furthermore, BPS invariants in question are expressed in terms of Lyndon words in an appropriate language, thereby relating counting of BPS states to the branch of mathematics referred to as combinatorics on words. We illustrate these results in the framework of colored extremal knot polynomials: among others we determine dual quantum extremal A-polynomials for various knots, present associated combinatorial models, find corresponding BPS invariants (extremal Labastida-Mariño-Ooguri-Vafa invariants) and discuss their integrality.

Putative Digenic Inheritance of Heterozygous RP1L1 and C2orf71 Null Mutations in Syndromic Retinal Dystrophy

PubMed Central

Liu, Yangfan P.; Bosch, Daniëlle G.M.; Siemiatkowska, Anna M.; Rendtorff, Nanna Dahl; Boonstra, F. Nienke; Möller, Claes; Tranebjærg, Lisbeth; Katsanis, Nicholas; Cremers, Frans P.M.

2018-01-01

Background Retinitis pigmentosa (RP) is the most common cause of inherited retinal degeneration and can occur in non-syndromic and syndromic forms. Syndromic RP is accompanied by other symptoms such as intellectual disability, hearing loss, or congenital abnormalities. Both forms are known to exhibit complex genetic interactions that can modulate the penetrance and expressivity of the phenotype. Materials and methods In an individual with atypical RP, hearing loss, ataxia and cerebellar atrophy whole exome sequencing was performed. The candidate pathogenic variants were tested by developing an in vivo zebrafish model and assaying for retinal and cerebellar integrity. Results Exome sequencing revealed a complex heterozygous protein-truncating mutation in RP1L1, p.[(Lys111Glnfs*27; Q2373*)], and a heterozygous nonsense mutation in C2orf71, p.(Ser512*). Mutations in both genes have previously been implicated in autosomal recessive non-syndromic RP, raising the possibility of a digenic model in this family. Functional testing in a zebrafish model for two key phenotypes of the affected person showed that the combinatorial suppression of rp1l1 and c2orf71l induced discrete pathology in terms of reduction of eye size with concomitant loss of rhodopsin in the photoreceptors, and disorganization of the cerebellum. Conclusions We propose that the combination of heterozygous loss-of-function mutations in these genes drives syndromic retinal dystrophy, likely through the genetic interaction of at least two loci. Haploinsufficiency at each of these loci is insufficient to induce overt pathology. PMID:27029556

Rule-based spatial modeling with diffusing, geometrically constrained molecules.

PubMed

Gruenert, Gerd; Ibrahim, Bashar; Lenser, Thorsten; Lohel, Maiko; Hinze, Thomas; Dittrich, Peter

2010-06-07

We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly.

Rule-based spatial modeling with diffusing, geometrically constrained molecules

PubMed Central

2010-01-01

Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Results Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. Conclusions We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly. PMID:20529264

Principles of Discrete Time Mechanics

NASA Astrophysics Data System (ADS)

Jaroszkiewicz, George

2014-04-01

1. Introduction; 2. The physics of discreteness; 3. The road to calculus; 4. Temporal discretization; 5. Discrete time dynamics architecture; 6. Some models; 7. Classical cellular automata; 8. The action sum; 9. Worked examples; 10. Lee's approach to discrete time mechanics; 11. Elliptic billiards; 12. The construction of system functions; 13. The classical discrete time oscillator; 14. Type 2 temporal discretization; 15. Intermission; 16. Discrete time quantum mechanics; 17. The quantized discrete time oscillator; 18. Path integrals; 19. Quantum encoding; 20. Discrete time classical field equations; 21. The discrete time Schrodinger equation; 22. The discrete time Klein-Gordon equation; 23. The discrete time Dirac equation; 24. Discrete time Maxwell's equations; 25. The discrete time Skyrme model; 26. Discrete time quantum field theory; 27. Interacting discrete time scalar fields; 28. Space, time and gravitation; 29. Causality and observation; 30. Concluding remarks; Appendix A. Coherent states; Appendix B. The time-dependent oscillator; Appendix C. Quaternions; Appendix D. Quantum registers; References; Index.

Setting up virgin stress conditions in discrete element models.

PubMed

Rojek, J; Karlis, G F; Malinowski, L J; Beer, G

2013-03-01

In the present work, a methodology for setting up virgin stress conditions in discrete element models is proposed. The developed algorithm is applicable to discrete or coupled discrete/continuum modeling of underground excavation employing the discrete element method (DEM). Since the DEM works with contact forces rather than stresses there is a need for the conversion of pre-excavation stresses to contact forces for the DEM model. Different possibilities of setting up virgin stress conditions in the DEM model are reviewed and critically assessed. Finally, a new method to obtain a discrete element model with contact forces equivalent to given macroscopic virgin stresses is proposed. The test examples presented show that good results may be obtained regardless of the shape of the DEM domain.

Setting up virgin stress conditions in discrete element models

PubMed Central

Rojek, J.; Karlis, G.F.; Malinowski, L.J.; Beer, G.

2013-01-01

In the present work, a methodology for setting up virgin stress conditions in discrete element models is proposed. The developed algorithm is applicable to discrete or coupled discrete/continuum modeling of underground excavation employing the discrete element method (DEM). Since the DEM works with contact forces rather than stresses there is a need for the conversion of pre-excavation stresses to contact forces for the DEM model. Different possibilities of setting up virgin stress conditions in the DEM model are reviewed and critically assessed. Finally, a new method to obtain a discrete element model with contact forces equivalent to given macroscopic virgin stresses is proposed. The test examples presented show that good results may be obtained regardless of the shape of the DEM domain. PMID:27087731

Combinatorial enzyme technology for the conversion of agricultural fibers to functional properties

USDA-ARS?s Scientific Manuscript database

The concept of combinatorial chemistry has received little attention in agriculture and food research, although its applications in this area were described more than fifteen years ago (1, 2). More recently, interest in the use of combinatorial chemistry in agrochemical discovery has been revitalize...

An Investigation into Post-Secondary Students' Understanding of Combinatorial Questions

ERIC Educational Resources Information Center

Bulone, Vincent William

2017-01-01

The purpose of this dissertation was to study aspects of how post-secondary students understand combinatorial problems. Within this dissertation, I considered understanding through two different lenses: i) student connections to previous problems; and ii) common combinatorial distinctions such as ordered versus unordered and repetitive versus…

Mixed-up trees: the structure of phylogenetic mixtures.

PubMed

Matsen, Frederick A; Mossel, Elchanan; Steel, Mike

2008-05-01

In this paper, we apply new geometric and combinatorial methods to the study of phylogenetic mixtures. The focus of the geometric approach is to describe the geometry of phylogenetic mixture distributions for the two state random cluster model, which is a generalization of the two state symmetric (CFN) model. In particular, we show that the set of mixture distributions forms a convex polytope and we calculate its dimension; corollaries include a simple criterion for when a mixture of branch lengths on the star tree can mimic the site pattern frequency vector of a resolved quartet tree. Furthermore, by computing volumes of polytopes we can clarify how "common" non-identifiable mixtures are under the CFN model. We also present a new combinatorial result which extends any identifiability result for a specific pair of trees of size six to arbitrary pairs of trees. Next we present a positive result showing identifiability of rates-across-sites models. Finally, we answer a question raised in a previous paper concerning "mixed branch repulsion" on trees larger than quartet trees under the CFN model.

Biogeography-based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task-time management

NASA Astrophysics Data System (ADS)

Zadeh, S. M.; Powers, D. M. W.; Sammut, K.; Yazdani, A. M.

2016-12-01

Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle's mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the Biogeography-Based Optimization (BBO) algorithm toward satisfying objectives of both higher-lower level motion planners and guarantees maximization of the mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios including the particular cost constraints in time-varying operating fields. To show the reliability of the proposed model, performance of each motion planner assessed separately and then statistical analysis is undertaken to evaluate the total performance of the entire model. The simulation results indicate the stability of the contributed model and its feasible application for real experiments.

The "p"-Median Model as a Tool for Clustering Psychological Data

ERIC Educational Resources Information Center

Kohn, Hans-Friedrich; Steinley, Douglas; Brusco, Michael J.

2010-01-01

The "p"-median clustering model represents a combinatorial approach to partition data sets into disjoint, nonhierarchical groups. Object classes are constructed around "exemplars", that is, manifest objects in the data set, with the remaining instances assigned to their closest cluster centers. Effective, state-of-the-art implementations of…

SCRIB and PUF60 Are Primary Drivers of the Multisystemic Phenotypes of the 8q24.3 Copy-Number Variant

PubMed Central

Dauber, Andrew; Golzio, Christelle; Guenot, Cécile; Jodelka, Francine M.; Kibaek, Maria; Kjaergaard, Susanne; Leheup, Bruno; Martinet, Danielle; Nowaczyk, Malgorzata J.M.; Rosenfeld, Jill A.; Zeesman, Susan; Zunich, Janice; Beckmann, Jacques S.; Hirschhorn, Joel N.; Hastings, Michelle L.; Jacquemont, Sebastien; Katsanis, Nicholas

2013-01-01

Copy-number variants (CNVs) represent a significant interpretative challenge, given that each CNV typically affects the dosage of multiple genes. Here we report on five individuals with coloboma, microcephaly, developmental delay, short stature, and craniofacial, cardiac, and renal defects who harbor overlapping microdeletions on 8q24.3. Fine mapping localized a commonly deleted 78 kb region that contains three genes: SCRIB, NRBP2, and PUF60. In vivo dissection of the CNV showed discrete contributions of the planar cell polarity effector SCRIB and the splicing factor PUF60 to the syndromic phenotype, and the combinatorial suppression of both genes exacerbated some, but not all, phenotypic components. Consistent with these findings, we identified an individual with microcephaly, short stature, intellectual disability, and heart defects with a de novo c.505C>T variant leading to a p.His169Tyr change in PUF60. Functional testing of this allele in vivo and in vitro showed that the mutation perturbs the relative dosage of two PUF60 isoforms and, subsequently, the splicing efficiency of downstream PUF60 targets. These data inform the functions of two genes not associated previously with human genetic disease and demonstrate how CNVs can exhibit complex genetic architecture, with the phenotype being the amalgam of both discrete dosage dysfunction of single transcripts and also of binary genetic interactions. PMID:24140112

cGRNB: a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets.

PubMed

Xu, Huayong; Yu, Hui; Tu, Kang; Shi, Qianqian; Wei, Chaochun; Li, Yuan-Yuan; Li, Yi-Xue

2013-01-01

We are witnessing rapid progress in the development of methodologies for building the combinatorial gene regulatory networks involving both TFs (Transcription Factors) and miRNAs (microRNAs). There are a few tools available to do these jobs but most of them are not easy to use and not accessible online. A web server is especially needed in order to allow users to upload experimental expression datasets and build combinatorial regulatory networks corresponding to their particular contexts. In this work, we compiled putative TF-gene, miRNA-gene and TF-miRNA regulatory relationships from forward-engineering pipelines and curated them as built-in data libraries. We streamlined the R codes of our two separate forward-and-reverse engineering algorithms for combinatorial gene regulatory network construction and formalized them as two major functional modules. As a result, we released the cGRNB (combinatorial Gene Regulatory Networks Builder): a web server for constructing combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. The cGRNB enables two major network-building modules, one for MPGE (miRNA-perturbed gene expression) datasets and the other for parallel miRNA/mRNA expression datasets. A miRNA-centered two-layer combinatorial regulatory cascade is the output of the first module and a comprehensive genome-wide network involving all three types of combinatorial regulations (TF-gene, TF-miRNA, and miRNA-gene) are the output of the second module. In this article we propose cGRNB, a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. Since parallel miRNA/mRNA expression datasets are rapidly accumulated by the advance of next-generation sequencing techniques, cGRNB will be very useful tool for researchers to build combinatorial gene regulatory networks based on expression datasets. The cGRNB web-server is free and available online at http://www.scbit.org/cgrnb.

Combinatorial effects on clumped isotopes and their significance in biogeochemistry

NASA Astrophysics Data System (ADS)

Yeung, Laurence Y.

2016-01-01

The arrangement of isotopes within a collection of molecules records their physical and chemical histories. Clumped-isotope analysis interrogates these arrangements, i.e., how often rare isotopes are bound together, which in many cases can be explained by equilibrium and/or kinetic isotope fractionation. However, purely combinatorial effects, rooted in the statistics of pairing atoms in a closed system, are also relevant, and not well understood. Here, I show that combinatorial isotope effects are most important when two identical atoms are neighbors on the same molecule (e.g., O2, N2, and D-D clumping in CH4). When the two halves of an atom pair are either assembled with different isotopic preferences or drawn from different reservoirs, combinatorial effects cause depletions in clumped-isotope abundance that are most likely between zero and -1‰, although they could potentially be -10‰ or larger for D-D pairs. These depletions are of similar magnitude, but of opposite sign, to low-temperature equilibrium clumped-isotope effects for many small molecules. Enzymatic isotope-pairing reactions, which can have site-specific isotopic fractionation factors and atom reservoirs, should express this class of combinatorial isotope effect, although it is not limited to biological reactions. Chemical-kinetic isotope effects, which are related to a bond-forming transition state, arise independently and express second-order combinatorial effects related to the abundance of the rare isotope. Heteronuclear moeties (e.g., Csbnd O and Csbnd H), are insensitive to direct combinatorial influences, but secondary combinatorial influences are evident. In general, both combinatorial and chemical-kinetic factors are important for calculating and interpreting clumped-isotope signatures of kinetically controlled reactions. I apply this analytical framework to isotope-pairing reactions relevant to geochemical oxygen, carbon, and nitrogen cycling that may be influenced by combinatorial clumped-isotope effects. These isotopic signatures, manifest as either directly bound isotope ;clumps; or as features of a molecule's isotopic anatomy, are linked to molecular mechanisms and may eventually provide additional information about biogeochemical cycling on environmentally relevant spatial scales.

Integrated microfluidic devices for combinatorial cell-based assays.

PubMed

Yu, Zeta Tak For; Kamei, Ken-ichiro; Takahashi, Hiroko; Shu, Chengyi Jenny; Wang, Xiaopu; He, George Wenfu; Silverman, Robert; Radu, Caius G; Witte, Owen N; Lee, Ki-Bum; Tseng, Hsian-Rong

2009-06-01

The development of miniaturized cell culture platforms for performing parallel cultures and combinatorial assays is important in cell biology from the single-cell level to the system level. In this paper we developed an integrated microfluidic cell-culture platform, Cell-microChip (Cell-microChip), for parallel analyses of the effects of microenvironmental cues (i.e., culture scaffolds) on different mammalian cells and their cellular responses to external stimuli. As a model study, we demonstrated the ability of culturing and assaying several mammalian cells, such as NIH 3T3 fibroblast, B16 melanoma and HeLa cell lines, in a parallel way. For functional assays, first we tested drug-induced apoptotic responses from different cell lines. As a second functional assay, we performed "on-chip" transfection of a reporter gene encoding an enhanced green fluorescent protein (EGFP) followed by live-cell imaging of transcriptional activation of cyclooxygenase 2 (Cox-2) expression. Collectively, our Cell-microChip approach demonstrated the capability to carry out parallel operations and the potential to further integrate advanced functions and applications in the broader space of combinatorial chemistry and biology.

Integrated microfluidic devices for combinatorial cell-based assays

PubMed Central

Yu, Zeta Tak For; Kamei, Ken-ichiro; Takahashi, Hiroko; Shu, Chengyi Jenny; Wang, Xiaopu; He, George Wenfu; Silverman, Robert

2010-01-01

The development of miniaturized cell culture platforms for performing parallel cultures and combinatorial assays is important in cell biology from the single-cell level to the system level. In this paper we developed an integrated microfluidic cell-culture platform, Cell-microChip (Cell-μChip), for parallel analyses of the effects of microenvir-onmental cues (i.e., culture scaffolds) on different mammalian cells and their cellular responses to external stimuli. As a model study, we demonstrated the ability of culturing and assaying several mammalian cells, such as NIH 3T3 fibro-blast, B16 melanoma and HeLa cell lines, in a parallel way. For functional assays, first we tested drug-induced apoptotic responses from different cell lines. As a second functional assay, we performed "on-chip" transfection of a reporter gene encoding an enhanced green fluorescent protein (EGFP) followed by live-cell imaging of transcriptional activation of cyclooxygenase 2 (Cox-2) expression. Collectively, our Cell-μChip approach demonstrated the capability to carry out parallel operations and the potential to further integrate advanced functions and applications in the broader space of combinatorial chemistry and biology. PMID:19130244

Sequence-independent construction of ordered combinatorial libraries with predefined crossover points.

PubMed

Jézéquel, Laetitia; Loeper, Jacqueline; Pompon, Denis

2008-11-01

Combinatorial libraries coding for mosaic enzymes with predefined crossover points constitute useful tools to address and model structure-function relationships and for functional optimization of enzymes based on multivariate statistics. The presented method, called sequence-independent generation of a chimera-ordered library (SIGNAL), allows easy shuffling of any predefined amino acid segment between two or more proteins. This method is particularly well adapted to the exchange of protein structural modules. The procedure could also be well suited to generate ordered combinatorial libraries independent of sequence similarities in a robotized manner. Sequence segments to be recombined are first extracted by PCR from a single-stranded template coding for an enzyme of interest using a biotin-avidin-based method. This technique allows the reduction of parental template contamination in the final library. Specific PCR primers allow amplification of two complementary mosaic DNA fragments, overlapping in the region to be exchanged. Fragments are finally reassembled using a fusion PCR. The process is illustrated via the construction of a set of mosaic CYP2B enzymes using this highly modular approach.

The construction of combinatorial manifolds with prescribed sets of links of vertices

NASA Astrophysics Data System (ADS)

Gaifullin, A. A.

2008-10-01

To every oriented closed combinatorial manifold we assign the set (with repetitions) of isomorphism classes of links of its vertices. The resulting transformation \\mathcal{L} is the main object of study in this paper. We pose an inversion problem for \\mathcal{L} and show that this problem is closely related to Steenrod's problem on the realization of cycles and to the Rokhlin-Schwartz-Thom construction of combinatorial Pontryagin classes. We obtain a necessary condition for a set of isomorphism classes of combinatorial spheres to belong to the image of \\mathcal{L}. (Sets satisfying this condition are said to be balanced.) We give an explicit construction showing that every balanced set of isomorphism classes of combinatorial spheres falls into the image of \\mathcal{L} after passing to a multiple set and adding several pairs of the form (Z,-Z), where -Z is the sphere Z with the orientation reversed. Given any singular simplicial cycle \\xi of a space X, this construction enables us to find explicitly a combinatorial manifold M and a map \\varphi\\colon M\\to X such that \\varphi_* \\lbrack M \\rbrack =r[\\xi] for some positive integer r. The construction is based on resolving singularities of \\xi. We give applications of the main construction to cobordisms of manifolds with singularities and cobordisms of simple cells. In particular, we prove that every rational additive invariant of cobordisms of manifolds with singularities admits a local formula. Another application is the construction of explicit (though inefficient) local combinatorial formulae for polynomials in the rational Pontryagin classes of combinatorial manifolds.

The Effects of Time Advance Mechanism on Simple Agent Behaviors in Combat Simulations

DTIC Science & Technology

2011-12-01

modeling packages that illustrate the differences between discrete-time simulation (DTS) and discrete-event simulation ( DES ) methodologies. Many combat... DES ) models , often referred to as “next-event” (Law and Kelton 2000) or discrete time simulation (DTS), commonly referred to as “time-step.” DTS...discrete-time simulation (DTS) and discrete-event simulation ( DES ) methodologies. Many combat models use DTS as their simulation time advance mechanism

Training and Transfer in Combinatorial Problem Solving: The Development of Formal Reasoning During Early Adolescence

ERIC Educational Resources Information Center

Barratt, Barnaby B.

1975-01-01

This study investigated the emergence of combinatorial competence in early adolescence and the effectiveness of a programmed discovery training procedure. Significant increases in combinatorial skill with age were shown; it was found that the expression of this skill was significantly facilitated if problems involved concrete material of low…

Invention as a combinatorial process: evidence from US patents

PubMed Central

Youn, Hyejin; Strumsky, Deborah; Bettencourt, Luis M. A.; Lobo, José

2015-01-01

Invention has been commonly conceptualized as a search over a space of combinatorial possibilities. Despite the existence of a rich literature, spanning a variety of disciplines, elaborating on the recombinant nature of invention, we lack a formal and quantitative characterization of the combinatorial process underpinning inventive activity. Here, we use US patent records dating from 1790 to 2010 to formally characterize invention as a combinatorial process. To do this, we treat patented inventions as carriers of technologies and avail ourselves of the elaborate system of technology codes used by the United States Patent and Trademark Office to classify the technologies responsible for an invention's novelty. We find that the combinatorial inventive process exhibits an invariant rate of ‘exploitation’ (refinements of existing combinations of technologies) and ‘exploration’ (the development of new technological combinations). This combinatorial dynamic contrasts sharply with the creation of new technological capabilities—the building blocks to be combined—that has significantly slowed down. We also find that, notwithstanding the very reduced rate at which new technologies are introduced, the generation of novel technological combinations engenders a practically infinite space of technological configurations. PMID:25904530

Combinatorial application of two aldehyde oxidoreductases on isobutanol production in the presence of furfural.

PubMed

Seo, Hyung-Min; Jeon, Jong-Min; Lee, Ju Hee; Song, Hun-Suk; Joo, Han-Byul; Park, Sung-Hee; Choi, Kwon-Young; Kim, Yong Hyun; Park, Kyungmoon; Ahn, Jungoh; Lee, Hongweon; Yang, Yung-Hun

2016-01-01

Furfural is a toxic by-product formulated from pretreatment processes of lignocellulosic biomass. In order to utilize the lignocellulosic biomass on isobutanol production, inhibitory effect of the furfural on isobutanol production was investigated and combinatorial application of two oxidoreductases, FucO and YqhD, was suggested as an alternative strategy. Furfural decreased cell growth and isobutanol production when only YqhD or FucO was employed as an isobutyraldehyde oxidoreductase. However, combinatorial overexpression of FucO and YqhD could overcome the inhibitory effect of furfural giving higher isobutanol production by 110% compared with overexpression of YqhD. The combinatorial oxidoreductases increased furfural detoxification rate 2.1-fold and also accelerated glucose consumption 1.4-fold. When it compares to another known system increasing furfural tolerance, membrane-bound transhydrogenase (pntAB), the combinatorial aldehyde oxidoreductases were better on cell growth and production. Thus, to control oxidoreductases is important to produce isobutanol using furfural-containing biomass and the combinatorial overexpression of FucO and YqhD can be an alternative strategy.

Tumor-targeting peptides from combinatorial libraries*

PubMed Central

Liu, Ruiwu; Li, Xiaocen; Xiao, Wenwu; Lam, Kit S.

2018-01-01

Cancer is one of the major and leading causes of death worldwide. Two of the greatest challenges infighting cancer are early detection and effective treatments with no or minimum side effects. Widespread use of targeted therapies and molecular imaging in clinics requires high affinity, tumor-specific agents as effective targeting vehicles to deliver therapeutics and imaging probes to the primary or metastatic tumor sites. Combinatorial libraries such as phage-display and one-bead one-compound (OBOC) peptide libraries are powerful approaches in discovering tumor-targeting peptides. This review gives an overview of different combinatorial library technologies that have been used for the discovery of tumor-targeting peptides. Examples of tumor-targeting peptides identified from each combinatorial library method will be discussed. Published tumor-targeting peptide ligands and their applications will also be summarized by the combinatorial library methods and their corresponding binding receptors. PMID:27210583

Dynamic combinatorial libraries: from exploring molecular recognition to systems chemistry.

PubMed

Li, Jianwei; Nowak, Piotr; Otto, Sijbren

2013-06-26

Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines.

A discrete epidemic model for bovine Babesiosis disease and tick populations

NASA Astrophysics Data System (ADS)

Aranda, Diego F.; Trejos, Deccy Y.; Valverde, Jose C.

2017-06-01

In this paper, we provide and study a discrete model for the transmission of Babesiosis disease in bovine and tick populations. This model supposes a discretization of the continuous-time model developed by us previously. The results, here obtained by discrete methods as opposed to continuous ones, show that similar conclusions can be obtained for the discrete model subject to the assumption of some parametric constraints which were not necessary in the continuous case. We prove that these parametric constraints are not artificial and, in fact, they can be deduced from the biological significance of the model. Finally, some numerical simulations are given to validate the model and verify our theoretical study.

ALC: automated reduction of rule-based models

PubMed Central

Koschorreck, Markus; Gilles, Ernst Dieter

2008-01-01

Background Combinatorial complexity is a challenging problem for the modeling of cellular signal transduction since the association of a few proteins can give rise to an enormous amount of feasible protein complexes. The layer-based approach is an approximative, but accurate method for the mathematical modeling of signaling systems with inherent combinatorial complexity. The number of variables in the simulation equations is highly reduced and the resulting dynamic models show a pronounced modularity. Layer-based modeling allows for the modeling of systems not accessible previously. Results ALC (Automated Layer Construction) is a computer program that highly simplifies the building of reduced modular models, according to the layer-based approach. The model is defined using a simple but powerful rule-based syntax that supports the concepts of modularity and macrostates. ALC performs consistency checks on the model definition and provides the model output in different formats (C MEX, MATLAB, Mathematica and SBML) as ready-to-run simulation files. ALC also provides additional documentation files that simplify the publication or presentation of the models. The tool can be used offline or via a form on the ALC website. Conclusion ALC allows for a simple rule-based generation of layer-based reduced models. The model files are given in different formats as ready-to-run simulation files. PMID:18973705

Synergistic Effect of Combinatorial Treatment with Curcumin and Mitomycin C on the Induction of Apoptosis of Breast Cancer Cells: A cDNA Microarray Analysis

PubMed Central

Zhou, Qian-Mei; Chen, Qi-Long; Du, Jia; Wang, Xiu-Feng; Lu, Yi-Yu; Zhang, Hui; Su, Shi-Bing

2014-01-01

In order to explore the synergistic mechanisms of combinatorial treatment using curcumin and mitomycin C (MMC) for breast cancer, MCF-7 breast cancer xenografts were conducted to observe the synergistic effect of combinatorial treatment using curcumin and MMC at various dosages. The synergistic mechanisms of combinatorial treatment using curcumin and MMC on the inhibition of tumor growth were explored by differential gene expression profile, gene ontology (GO), ingenuity pathway analysis (IPA) and Signal–Net network analysis. The expression levels of selected genes identified by cDNA microarray expression profiling were validated by quantitative RT-PCR (qRT-PCR) and Western blot analysis. Effect of combinatorial treatment on the inhibition of cell growth was observed by MTT assay. Apoptosis was detected by flow cytometric analysis and Hoechst 33258 staining. The combinatorial treatment of 100 mg/kg curcumin and 1.5 mg/kg MMC revealed synergistic inhibition on tumor growth. Among 1501 differentially expressed genes, the expression of 25 genes exhibited an obvious change and a significant difference in 27 signal pathways was observed (p < 0.05). In addition, Mapk1 (ERK) and Mapk14 (MAPK p38) had more cross-interactions with other genes and revealed an increase in expression by 8.14- and 11.84-fold, respectively during the combinatorial treatment by curcumin and MMC when compared with the control. Moreover, curcumin can synergistically improve tumoricidal effect of MMC in another human breast cancer MDA-MB-231 cells. Apoptosis was significantly induced by the combinatorial treatment (p < 0.05) and significantly inhibited by ERK inhibitor (PD98059) in MCF-7 cells (p < 0.05). The synergistic effect of combinatorial treatment by curcumin and MMC on the induction of apoptosis in breast cancer cells may be via the ERK pathway. PMID:25226537

Bulk combinatorial synthesis and high throughput characterization for rapid assessment of magnetic materials: Application of laser engineered net shaping (LENS)

DOE PAGES

Geng, J.; Nlebedim, I. C.; Besser, M. F.; ...

2016-04-15

A bulk combinatorial approach for synthesizing alloy libraries using laser engineered net shaping (LENS; i.e., 3D printing) was utilized to rapidly assess material systems for magnetic applications. The LENS system feeds powders in different ratios into a melt pool created by a laser to synthesize samples with bulk (millimeters) dimensions. By analyzing these libraries with autosampler differential scanning calorimeter/thermal gravimetric analysis and vibrating sample magnetometry, we are able to rapidly characterize the thermodynamic and magnetic properties of the libraries. Furthermore, the Fe-Co binary alloy was used as a model system and the results were compared with data in the literature.

Synergism and Combinatorial Coding for Binary Odor Mixture Perception in Drosophila

PubMed Central

Chakraborty, Tuhin Subhra; Siddiqi, Obaid

2016-01-01

Most odors in the natural environment are mixtures of several compounds. Olfactory receptors housed in the olfactory sensory neurons detect these odors and transmit the information to the brain, leading to decision-making. But whether the olfactory system detects the ingredients of a mixture separately or treats mixtures as different entities is not well understood. Using Drosophila melanogaster as a model system, we have demonstrated that fruit flies perceive binary odor mixtures in a manner that is heavily dependent on both the proportion and the degree of dilution of the components, suggesting a combinatorial coding at the peripheral level. This coding strategy appears to be receptor specific and is independent of interneuronal interactions. PMID:27588303

Molecular mechanisms of floral organ specification by MADS domain proteins.

PubMed

Yan, Wenhao; Chen, Dijun; Kaufmann, Kerstin

2016-02-01

Flower development is a model system to understand organ specification in plants. The identities of different types of floral organs are specified by homeotic MADS transcription factors that interact in a combinatorial fashion. Systematic identification of DNA-binding sites and target genes of these key regulators show that they have shared and unique sets of target genes. DNA binding by MADS proteins is not based on 'simple' recognition of a specific DNA sequence, but depends on DNA structure and combinatorial interactions. Homeotic MADS proteins regulate gene expression via alternative mechanisms, one of which may be to modulate chromatin structure and accessibility in their target gene promoters. Copyright © 2015 Elsevier Ltd. All rights reserved.

Solubility limits in quaternary SnTe-based alloys [Metastability and solubility limits in quaternary SnTe-based alloys guided by combinatorial sputtering

DOE PAGES

Siol, Sebastian; Holder, Aaron; Ortiz, Brenden R.; ...

2017-05-09

Here, the controlled decomposition of metastable alloys is an attractive route to form nanostructured thermoelectric materials with reduced thermal conductivity. The ternary SnTe–MnTe and SnTe–SnSe heterostructural alloys have been demonstrated as promising materials for thermoelectric applications. In this work, the quaternary Sn 1–yMnyTe 1–xSe x phase space serves as a relevant model system to explore how a combination of computational and combinatorial-growth methods can be used to study equilibrium and non-equilibrium solubility limits. Results from first principle calculations indicate low equilibrium solubility for x,y < 0.05 that are in good agreement with results obtained from bulk equilibrium synthesis experiments andmore » predict significantly higher spinodal limits. An experimental screening using sputtered combinatorial thin film sample libraries showed a remarkable increase in non-equilibrium solubility for x,y > 0.2. These theoretical and experimental results were used to guide the bulk synthesis of metastable alloys. The ability to reproduce the non-equilibrium solubility levels in bulk materials indicates that such theoretical calculations and combinatorial growth can inform bulk synthetic routes. Further, the large difference between equilibrium and non-equilibrium solubility limits in Sn 1–yMn yTe 1–xSe x indicates these metastable alloys are attractive in terms of nano-precipitate formation for potential thermoelectric applications.« less

Spread the word: MMN brain response reveals whole-form access of discontinuous particle verbs.

PubMed

Hanna, Jeff; Cappelle, Bert; Pulvermüller, Friedemann

2017-12-01

The status of particle verbs such as rise (…) up as either lexically stored or combinatorially assembled is an issue which so far has not been settled decisively. In this study, we use the mismatch negativity (MMN) brain response to observe neurophysiological responses to discontinuous particle verbs. The MMN can be used to distinguish between whole-form storage and combinatorial processes, as it is enhanced to stored words compared to unknown pseudowords, whereas combinatorially legal strings elicit a reduced MMN relative to ungrammatical ones. Earlier work had found larger MMNs to congruent than to incongruent verb-particle combinations when particle and verb appeared as adjacent elements, thus suggesting whole-form storage at least in this case. However, it is still possible that particle verbs discontinuously spread out across a sentence would elicit the combinatorial, grammar-violation response pattern instead. Here, we tested the brain signatures of discontinuous verb-particle combinations, orthogonally varying congruence and semantic transparency. The results show for the first time brain indices of whole-form storage for discontinuous constituents, thus arguing in favour of access to whole-form-stored lexical elements in the processing of particle verbs, irrespective of their semantic opacity. Results are discussed in the context of linguistic debates about the status of particle verbs as words, lexical elements or syntactically generated combinations. The explanation of the pattern of results within a neurobiological language model is highlighted. Copyright © 2017 Elsevier Inc. All rights reserved.

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

Data Mining and Machine Learning Tools for Combinatorial Material Science of All-Oxide Photovoltaic Cells.

PubMed

Yosipof, Abraham; Nahum, Oren E; Anderson, Assaf Y; Barad, Hannah-Noa; Zaban, Arie; Senderowitz, Hanoch

2015-06-01

Growth in energy demands, coupled with the need for clean energy, are likely to make solar cells an important part of future energy resources. In particular, cells entirely made of metal oxides (MOs) have the potential to provide clean and affordable energy if their power conversion efficiencies are improved. Such improvements require the development of new MOs which could benefit from combining combinatorial material sciences for producing solar cells libraries with data mining tools to direct synthesis efforts. In this work we developed a data mining workflow and applied it to the analysis of two recently reported solar cell libraries based on Titanium and Copper oxides. Our results demonstrate that QSAR models with good prediction statistics for multiple solar cells properties could be developed and that these models highlight important factors affecting these properties in accord with experimental findings. The resulting models are therefore suitable for designing better solar cells. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multimode resource-constrained multiple project scheduling problem under fuzzy random environment and its application to a large scale hydropower construction project.

PubMed

Xu, Jiuping; Feng, Cuiying

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method.

Multimode Resource-Constrained Multiple Project Scheduling Problem under Fuzzy Random Environment and Its Application to a Large Scale Hydropower Construction Project

PubMed Central

Xu, Jiuping

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method. PMID:24550708

Automated combinatorial method for fast and robust prediction of lattice thermal conductivity

NASA Astrophysics Data System (ADS)

Plata, Jose J.; Nath, Pinku; Usanmaz, Demet; Toher, Cormac; Fornari, Marco; Buongiorno Nardelli, Marco; Curtarolo, Stefano

The lack of computationally inexpensive and accurate ab-initio based methodologies to predict lattice thermal conductivity, κl, without computing the anharmonic force constants or performing time-consuming ab-initio molecular dynamics, is one of the obstacles preventing the accelerated discovery of new high or low thermal conductivity materials. The Slack equation is the best alternative to other more expensive methodologies but is highly dependent on two variables: the acoustic Debye temperature, θa, and the Grüneisen parameter, γ. Furthermore, different definitions can be used for these two quantities depending on the model or approximation. Here, we present a combinatorial approach based on the quasi-harmonic approximation to elucidate which definitions of both variables produce the best predictions of κl. A set of 42 compounds was used to test accuracy and robustness of all possible combinations. This approach is ideal for obtaining more accurate values than fast screening models based on the Debye model, while being significantly less expensive than methodologies that solve the Boltzmann transport equation.

Combinatorial theory of Macdonald polynomials I: proof of Haglund's formula.

PubMed

Haglund, J; Haiman, M; Loehr, N

2005-02-22

Haglund recently proposed a combinatorial interpretation of the modified Macdonald polynomials H(mu). We give a combinatorial proof of this conjecture, which establishes the existence and integrality of H(mu). As corollaries, we obtain the cocharge formula of Lascoux and Schutzenberger for Hall-Littlewood polynomials, a formula of Sahi and Knop for Jack's symmetric functions, a generalization of this result to the integral Macdonald polynomials J(mu), a formula for H(mu) in terms of Lascoux-Leclerc-Thibon polynomials, and combinatorial expressions for the Kostka-Macdonald coefficients K(lambda,mu) when mu is a two-column shape.

Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore

PubMed Central

Ibrahim, Bashar; Henze, Richard; Gruenert, Gerd; Egbert, Matthew; Huwald, Jan; Dittrich, Peter

2013-01-01

A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models. PMID:24709796

The Spectrum of Mathematical Models.

ERIC Educational Resources Information Center

Karplus, Walter J.

1983-01-01

Mathematical modeling problems encountered in many disciplines are discussed in terms of the modeling process and applications of models. The models are classified according to three types of abstraction: continuous-space-continuous-time, discrete-space-continuous-time, and discrete-space-discrete-time. Limitations in different kinds of modeling…

Inhibition of Hepatitis C Virus Replication by Intracellular Delivery of Multiple siRNAs by Nanosomes

PubMed Central

Chandra, Partha K; Kundu, Anup K; Hazari, Sidhartha; Chandra, Sruti; Bao, Lili; Ooms, Tara; Morris, Gilbert F; Wu, Tong; Mandal, Tarun K; Dash, Srikanta

2012-01-01

Sustained antiviral responses of chronic hepatitis C virus (HCV) infection have improved recently by the use of direct-acting antiviral agents along with interferon (IFN)-α and ribavirin. However, the emergence of drug-resistant variants is expected to be a major problem. We describe here a novel combinatorial small interfering RNA (siRNA) nanosome-based antiviral approach to clear HCV infection. Multiple siRNAs targeted to the highly conserved 5′-untranslated region (UTR) of the HCV genome were synthesized and encapsulated into lipid nanoparticles called nanosomes. We show that siRNA can be repeatedly delivered to 100% of cells in culture using nanosomes without toxicity. Six siRNAs dramatically reduced HCV replication in both the replicon and infectious cell culture model. Repeated treatments with two siRNAs were better than a single siRNA treatment in minimizing the development of an escape mutant, resulting in rapid inhibition of viral replication. Systemic administration of combinatorial siRNA-nanosomes is well tolerated in BALB/c mice without liver injury or histological toxicity. As a proof-of-principle, we showed that systemic injections of siRNA nanosomes significantly reduced HCV replication in a liver tumor-xenotransplant mouse model of HCV. Our results indicate that systemic delivery of combinatorial siRNA nanosomes can be used to minimize the development of escape mutants and inhibition of HCV infection. PMID:22617108

Multiobjective optimization of combinatorial libraries.

PubMed

Agrafiotis, D K

2002-01-01

Combinatorial chemistry and high-throughput screening have caused a fundamental shift in the way chemists contemplate experiments. Designing a combinatorial library is a controversial art that involves a heterogeneous mix of chemistry, mathematics, economics, experience, and intuition. Although there seems to be little agreement as to what constitutes an ideal library, one thing is certain: only one property or measure seldom defines the quality of the design. In most real-world applications, a good experiment requires the simultaneous optimization of several, often conflicting, design objectives, some of which may be vague and uncertain. In this paper, we discuss a class of algorithms for subset selection rooted in the principles of multiobjective optimization. Our approach is to employ an objective function that encodes all of the desired selection criteria, and then use a simulated annealing or evolutionary approach to identify the optimal (or a nearly optimal) subset from among the vast number of possibilities. Many design criteria can be accommodated, including diversity, similarity to known actives, predicted activity and/or selectivity determined by quantitative structure-activity relationship (QSAR) models or receptor binding models, enforcement of certain property distributions, reagent cost and availability, and many others. The method is robust, convergent, and extensible, offers the user full control over the relative significance of the various objectives in the final design, and permits the simultaneous selection of compounds from multiple libraries in full- or sparse-array format.

On the relationship of steady states of continuous and discrete models arising from biology.

PubMed

Veliz-Cuba, Alan; Arthur, Joseph; Hochstetler, Laura; Klomps, Victoria; Korpi, Erikka

2012-12-01

For many biological systems that have been modeled using continuous and discrete models, it has been shown that such models have similar dynamical properties. In this paper, we prove that this happens in more general cases. We show that under some conditions there is a bijection between the steady states of continuous and discrete models arising from biological systems. Our results also provide a novel method to analyze certain classes of nonlinear models using discrete mathematics.

Robust inference in discrete hazard models for randomized clinical trials.

PubMed

Nguyen, Vinh Q; Gillen, Daniel L

2012-10-01

Time-to-event data in which failures are only assessed at discrete time points are common in many clinical trials. Examples include oncology studies where events are observed through periodic screenings such as radiographic scans. When the survival endpoint is acknowledged to be discrete, common methods for the analysis of observed failure times include the discrete hazard models (e.g., the discrete-time proportional hazards and the continuation ratio model) and the proportional odds model. In this manuscript, we consider estimation of a marginal treatment effect in discrete hazard models where the constant treatment effect assumption is violated. We demonstrate that the estimator resulting from these discrete hazard models is consistent for a parameter that depends on the underlying censoring distribution. An estimator that removes the dependence on the censoring mechanism is proposed and its asymptotic distribution is derived. Basing inference on the proposed estimator allows for statistical inference that is scientifically meaningful and reproducible. Simulation is used to assess the performance of the presented methodology in finite samples.

Optimizing Perioperative Decision Making: Improved Information for Clinical Workflow Planning

PubMed Central

Doebbeling, Bradley N.; Burton, Matthew M.; Wiebke, Eric A.; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

2012-01-01

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40–70% of hospital revenues and 30–40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction. PMID:23304284

Parallelization of combinatorial search when solving knapsack optimization problem on computing systems based on multicore processors

NASA Astrophysics Data System (ADS)

Rahman, P. A.

2018-05-01

This scientific paper deals with the model of the knapsack optimization problem and method of its solving based on directed combinatorial search in the boolean space. The offered by the author specialized mathematical model of decomposition of the search-zone to the separate search-spheres and the algorithm of distribution of the search-spheres to the different cores of the multi-core processor are also discussed. The paper also provides an example of decomposition of the search-zone to the several search-spheres and distribution of the search-spheres to the different cores of the quad-core processor. Finally, an offered by the author formula for estimation of the theoretical maximum of the computational acceleration, which can be achieved due to the parallelization of the search-zone to the search-spheres on the unlimited number of the processor cores, is also given.

Pancreatic cancer combination therapy using a BH3 mimetic and a synthetic tetracycline

PubMed Central

Quinn, Bridget A.; Dash, Rupesh; Sarkar, Siddik; Azab, Belal; Bhoopathi, Praveen; Das, Swadesh K.; Emdad, Luni; Wei, Jun; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B.

2015-01-01

Improved treatments for pancreatic cancer remain a clinical imperative. Sabutoclax, a small molecule BH3 mimetic, inhibits the function of anti-apoptotic Bcl-2 proteins. Minocycline, a synthetic tetracycline, displays antitumor activity. Here we offer evidence of the combinatorial antitumor potency of these agents in several preclinical models of pancreatic cancer. Sabutoclax induced growth arrest and apoptosis in pancreatic cancer cells and synergized with Minocycline to yield a robust mitochondria-mediated caspase-dependent cytotoxicity. This combinatorial property relied upon loss of phosphorylated Stat3 insofar as reintroduction of activated Stat3 rescued cells from toxicity. Tumor growth was inhibited potently in both immune-deficient and immune-competent models with evidence of extended survival. Overall, our results showed that that the combination of Sabutoclax and Minocycline was highly cytotoxic to pancreatic cancer cells and safely efficacious in vivo. PMID:26032425

Optimizing perioperative decision making: improved information for clinical workflow planning.

PubMed

Doebbeling, Bradley N; Burton, Matthew M; Wiebke, Eric A; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

2012-01-01

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40-70% of hospital revenues and 30-40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction.

Phage display for the discovery of hydroxyapatite-associated peptides.

PubMed

Jin, Hyo-Eon; Chung, Woo-Jae; Lee, Seung-Wuk

2013-01-01

In nature, proteins play a critical role in the biomineralization process. Understanding how different peptide or protein sequences selectively interact with the target crystal is of great importance. Identifying such protein structures is one of the critical steps in verifying the molecular mechanisms of biomineralization. One of the promising ways to obtain such information for a particular crystal surface is to screen combinatorial peptide libraries in a high-throughput manner. Among the many combinatorial library screening procedures, phage display is a powerful method to isolate such proteins and peptides. In this chapter, we will describe our established methods to perform phage display with inorganic crystal surfaces. Specifically, we will use hydroxyapatite as a model system for discovery of apatite-associated proteins in bone or tooth biomineralization studies. This model approach can be generalized to other desired crystal surfaces using the same experimental design principles with a little modification of the procedures. © 2013 Elsevier Inc. All rights reserved.

To Think without Thinking: The Implications of Combinatory Play and the Creative Process for Neuroaesthetics

ERIC Educational Resources Information Center

Stevens, Victoria

2014-01-01

The author considers combinatory play as an intersection between creativity, play, and neuroaesthetics. She discusses combinatory play as vital to the creative process in art and science, particularly with regard to the incubation of new ideas. She reviews findings from current neurobiological research and outlines the way that the brain activates…

Noise Propagation and Uncertainty Quantification in Hybrid Multiphysics Models: Initiation and Reaction Propagation in Energetic Materials

DTIC Science & Technology

2016-05-23

general model for heterogeneous granular media under compaction and (ii) the lack of a reliable multiscale discrete -to-continuum framework for...dynamics. These include a continuum- discrete model of heat dissipation/diffusion and a continuum- discrete model of compaction of a granular material with...the lack of a general model for het- erogeneous granular media under compac- tion and (ii) the lack of a reliable multi- scale discrete -to-continuum

Investigation into discretization methods of the six-parameter Iwan model

NASA Astrophysics Data System (ADS)

Li, Yikun; Hao, Zhiming; Feng, Jiaquan; Zhang, Dingguo

2017-02-01

Iwan model is widely applied for the purpose of describing nonlinear mechanisms of jointed structures. In this paper, parameter identification procedures of the six-parameter Iwan model based on joint experiments with different preload techniques are performed. Four kinds of discretization methods deduced from stiffness equation of the six-parameter Iwan model are provided, which can be used to discretize the integral-form Iwan model into a sum of finite Jenkins elements. In finite element simulation, the influences of discretization methods and numbers of Jenkins elements on computing accuracy are discussed. Simulation results indicate that a higher accuracy can be obtained with larger numbers of Jenkins elements. It is also shown that compared with other three kinds of discretization methods, the geometric series discretization based on stiffness provides the highest computing accuracy.

How does a three-dimensional continuum muscle model affect the kinematics and muscle strains of a finite element neck model compared to a discrete muscle model in rear-end, frontal, and lateral impacts.

PubMed

Hedenstierna, Sofia; Halldin, Peter

2008-04-15

A finite element (FE) model of the human neck with incorporated continuum or discrete muscles was used to simulate experimental impacts in rear, frontal, and lateral directions. The aim of this study was to determine how a continuum muscle model influences the impact behavior of a FE human neck model compared with a discrete muscle model. Most FE neck models used for impact analysis today include a spring element musculature and are limited to discrete geometries and nodal output results. A solid-element muscle model was thought to improve the behavior of the model by adding properties such as tissue inertia and compressive stiffness and by improving the geometry. It would also predict the strain distribution within the continuum elements. A passive continuum muscle model with nonlinear viscoelastic materials was incorporated into the KTH neck model together with active spring muscles and used in impact simulations. The resulting head and vertebral kinematics was compared with the results from a discrete muscle model as well as volunteer corridors. The muscle strain prediction was compared between the 2 muscle models. The head and vertebral kinematics were within the volunteer corridors for both models when activated. The continuum model behaved more stiffly than the discrete model and needed less active force to fit the experimental results. The largest difference was seen in the rear impact. The strain predicted by the continuum model was lower than for the discrete model. The continuum muscle model stiffened the response of the KTH neck model compared with a discrete model, and the strain prediction in the muscles was improved.

Reducing Neuronal Networks to Discrete Dynamics

PubMed Central

Terman, David; Ahn, Sungwoo; Wang, Xueying; Just, Winfried

2008-01-01

We consider a general class of purely inhibitory and excitatory-inhibitory neuronal networks, with a general class of network architectures, and characterize the complex firing patterns that emerge. Our strategy for studying these networks is to first reduce them to a discrete model. In the discrete model, each neuron is represented as a finite number of states and there are rules for how a neuron transitions from one state to another. In this paper, we rigorously demonstrate that the continuous neuronal model can be reduced to the discrete model if the intrinsic and synaptic properties of the cells are chosen appropriately. In a companion paper [1], we analyze the discrete model. PMID:18443649

Combinatorial genetic perturbation to refine metabolic circuits for producing biofuels and biochemicals.

PubMed

Kim, Hyo Jin; Turner, Timothy Lee; Jin, Yong-Su

2013-11-01

Recent advances in metabolic engineering have enabled microbial factories to compete with conventional processes for producing fuels and chemicals. Both rational and combinatorial approaches coupled with synthetic and systematic tools play central roles in metabolic engineering to create and improve a selected microbial phenotype. Compared to knowledge-based rational approaches, combinatorial approaches exploiting biological diversity and high-throughput screening have been demonstrated as more effective tools for improving various phenotypes of interest. In particular, identification of unprecedented targets to rewire metabolic circuits for maximizing yield and productivity of a target chemical has been made possible. This review highlights general principles and the features of the combinatorial approaches using various libraries to implement desired phenotypes for strain improvement. In addition, recent applications that harnessed the combinatorial approaches to produce biofuels and biochemicals will be discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

Tumor-targeting peptides from combinatorial libraries.

PubMed

Liu, Ruiwu; Li, Xiaocen; Xiao, Wenwu; Lam, Kit S

2017-02-01

Cancer is one of the major and leading causes of death worldwide. Two of the greatest challenges in fighting cancer are early detection and effective treatments with no or minimum side effects. Widespread use of targeted therapies and molecular imaging in clinics requires high affinity, tumor-specific agents as effective targeting vehicles to deliver therapeutics and imaging probes to the primary or metastatic tumor sites. Combinatorial libraries such as phage-display and one-bead one-compound (OBOC) peptide libraries are powerful approaches in discovering tumor-targeting peptides. This review gives an overview of different combinatorial library technologies that have been used for the discovery of tumor-targeting peptides. Examples of tumor-targeting peptides identified from each combinatorial library method will be discussed. Published tumor-targeting peptide ligands and their applications will also be summarized by the combinatorial library methods and their corresponding binding receptors. Copyright © 2017. Published by Elsevier B.V.

Discrete Latent Markov Models for Normally Distributed Response Data

ERIC Educational Resources Information Center

Schmittmann, Verena D.; Dolan, Conor V.; van der Maas, Han L. J.; Neale, Michael C.

2005-01-01

Van de Pol and Langeheine (1990) presented a general framework for Markov modeling of repeatedly measured discrete data. We discuss analogical single indicator models for normally distributed responses. In contrast to discrete models, which have been studied extensively, analogical continuous response models have hardly been considered. These…

Suffix Ordering and Morphological Processing

ERIC Educational Resources Information Center

Plag, Ingo; Baayen, Harald

2009-01-01

There is a long-standing debate about the principles constraining the combinatorial properties of suffixes. Hay 2002 and Hay & Plag 2004 proposed a model in which suffixes can be ordered along a hierarchy of processing complexity. We show that this model generalizes to a larger set of suffixes, and we provide independent evidence supporting the…

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

DOE PAGES

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting; ...

2018-03-28

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

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

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

USMC Inventory Control Using Optimization Modeling and Discrete Event Simulation

DTIC Science & Technology

2016-09-01

release. Distribution is unlimited. USMC INVENTORY CONTROL USING OPTIMIZATION MODELING AND DISCRETE EVENT SIMULATION by Timothy A. Curling...USING OPTIMIZATION MODELING AND DISCRETE EVENT SIMULATION 5. FUNDING NUMBERS 6. AUTHOR(S) Timothy A. Curling 7. PERFORMING ORGANIZATION NAME(S...optimization and discrete -event simulation. This construct can potentially provide an effective means in improving order management decisions. However

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

PubMed Central

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928–0.988,  = 0.894–0.954, RMSE = 0.002–0.412, s = 0.001–0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery. PMID:28059133

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme.

PubMed

Leong, Max K; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-06

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r 2  = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pK i values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r 2  = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q 2  = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

NASA Astrophysics Data System (ADS)

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics.

Comparison of vertical discretization techniques in finite-difference models of ground-water flow; example from a hypothetical New England setting

USGS Publications Warehouse

Harte, Philip T.

1994-01-01

Proper discretization of a ground-water-flow field is necessary for the accurate simulation of ground-water flow by models. Although discretiza- tion guidelines are available to ensure numerical stability, current guidelines arc flexible enough (particularly in vertical discretization) to allow for some ambiguity of model results. Testing of two common types of vertical-discretization schemes (horizontal and nonhorizontal-model-layer approach) were done to simulate sloping hydrogeologic units characteristic of New England. Differences of results of model simulations using these two approaches are small. Numerical errors associated with use of nonhorizontal model layers are small (4 percent). even though this discretization technique does not adhere to the strict formulation of the finite-difference method. It was concluded that vertical discretization by means of the nonhorizontal layer approach has advantages in representing the hydrogeologic units tested and in simplicity of model-data input. In addition, vertical distortion of model cells by this approach may improve the representation of shallow flow processes.

The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities

ERIC Educational Resources Information Center

Bauer, Daniel J.; Curran, Patrick J.

2004-01-01

Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…

Nonlinear Maps for Design of Discrete Time Models of Neuronal Network Dynamics

DTIC Science & Technology

2016-02-29

Performance/Technic~ 02-01-2016- 02-29-2016 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER Nonlinear Maps for Design of Discrete -Time Models of Neuronal...neuronal model in the form of difference equations that generates neuronal states in discrete moments of time. In this approach, time step can be made...propose to use modern DSP ideas to develop new efficient approaches to the design of such discrete -time models for studies of large-scale neuronal

Nonlinear Maps for Design of Discrete-Time Models of Neuronal Network Dynamics

DTIC Science & Technology

2016-03-31

2016 Performance/Technic~ 03-01-2016- 03-31-2016 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER Nonlinear Maps for Design of Discrete -Time Models of...simulations is to design a neuronal model in the form of difference equations that generates neuronal states in discrete moments of time. In this...responsive tiring patterns. We propose to use modern DSP ideas to develop new efficient approaches to the design of such discrete -time models for

A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem

PubMed Central

Zamli, Kamal Z.; Din, Fakhrud; Bures, Miroslav

2018-01-01

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1). In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). Within the QLSCA, we eliminate the switching probability. Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically identify the best operation during runtime. Additionally, we integrate two new operations (Lévy flight motion and crossover) into the QLSCA to facilitate jumping out of local minima/maxima and enhance the solution diversity. To assess its performance, we adopt the QLSCA for the combinatorial test suite minimization problem. Experimental results reveal that the QLSCA is statistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level. However, concerning the comparison with discrete particle swarm optimization (DPSO), there is no significant difference in performance at the 95% confidence level. On a positive note, the QLSCA statistically outperforms the DPSO in certain configurations at the 90% confidence level. PMID:29771918

A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem.

PubMed

Zamli, Kamal Z; Din, Fakhrud; Ahmed, Bestoun S; Bures, Miroslav

2018-01-01

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1). In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). Within the QLSCA, we eliminate the switching probability. Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically identify the best operation during runtime. Additionally, we integrate two new operations (Lévy flight motion and crossover) into the QLSCA to facilitate jumping out of local minima/maxima and enhance the solution diversity. To assess its performance, we adopt the QLSCA for the combinatorial test suite minimization problem. Experimental results reveal that the QLSCA is statistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level. However, concerning the comparison with discrete particle swarm optimization (DPSO), there is no significant difference in performance at the 95% confidence level. On a positive note, the QLSCA statistically outperforms the DPSO in certain configurations at the 90% confidence level.

Generalized probabilistic theories and conic extensions of polytopes

NASA Astrophysics Data System (ADS)

Fiorini, Samuel; Massar, Serge; Patra, Manas K.; Tiwary, Hans Raj

2015-01-01

Generalized probabilistic theories (GPT) provide a general framework that includes classical and quantum theories. It is described by a cone C and its dual C*. We show that whether some one-way communication complexity problems can be solved within a GPT is equivalent to the recently introduced cone factorization of the corresponding communication matrix M. We also prove an analogue of Holevo's theorem: when the cone C is contained in {{{R}}n}, the classical capacity of the channel realized by sending GPT states and measuring them is bounded by log n. Polytopes and optimising functions over polytopes arise in many areas of discrete mathematics. A conic extension of a polytope is the intersection of a cone C with an affine subspace whose projection onto the original space yields the desired polytope. Extensions of polytopes can sometimes be much simpler geometric objects than the polytope itself. The existence of a conic extension of a polytope is equivalent to that of a cone factorization of the slack matrix of the polytope, on the same cone. We show that all 0/1 polytopes whose vertices can be recognized by a polynomial size circuit, which includes as a special case the travelling salesman polytope and many other polytopes from combinatorial optimization, have small conic extension complexity when the cone is the completely positive cone. Using recent exponential lower bounds on the linear extension complexity of polytopes, this provides an exponential gap between the communication complexity of GPT based on the completely positive cone and classical communication complexity, and a conjectured exponential gap with quantum communication complexity. Our work thus relates the communication complexity of generalizations of quantum theory to questions of mainstream interest in the area of combinatorial optimization.

Joint modeling of longitudinal data and discrete-time survival outcome.

PubMed

Qiu, Feiyou; Stein, Catherine M; Elston, Robert C

2016-08-01

A predictive joint shared parameter model is proposed for discrete time-to-event and longitudinal data. A discrete survival model with frailty and a generalized linear mixed model for the longitudinal data are joined to predict the probability of events. This joint model focuses on predicting discrete time-to-event outcome, taking advantage of repeated measurements. We show that the probability of an event in a time window can be more precisely predicted by incorporating the longitudinal measurements. The model was investigated by comparison with a two-step model and a discrete-time survival model. Results from both a study on the occurrence of tuberculosis and simulated data show that the joint model is superior to the other models in discrimination ability, especially as the latent variables related to both survival times and the longitudinal measurements depart from 0. © The Author(s) 2013.

Simultaneous modelling of multi-purpose/multi-stop activity patterns and quantities consumed

NASA Astrophysics Data System (ADS)

Roy, John R.; Smith, Nariida C.; Xu, Blake

Whereas for commuting travel there is a one-to-one correspondence between commuters and jobs, and for commodity flows a one-to-one correspondence between the size of orders and the shipping cost of the commodities, the situation is much more complex for retail/service travel. A typical shopper may make a single trip or multi-stop tour to buy/consume a quite diverse set of commodities/services at different locations in quite variable quantities. At the same time, the general pattern of the tour is clearly dependent on the activities and goods available at potential stops. These interdependencies have been alluded to in the literature, especially by spatial economists. However, until some preliminary work by the first author, there has been no attempt to formally include these interdependencies in a general model. This paper presents a framework for achieving this goal by developing an evolutionary set of models starting from the simplest forms available. From the above, it is clear that such interdependency models will inevitably have high dimensionality and combinatorial complexity. This rules out a simultaneous treatment of all the events using an individual choice approach. If an individual choice approach is to be applied in a tractable manner, the set of interdependent events needs to be segmented into several subsets, with simultaneity recognised within each subset, but a mere sequential progression occurring between subsets. In this paper, full event interdependencies are retained at the expense of modelling market segments of consumers rather than a sample of representative individuals. We couple the travel and consumption events in the only feasible way, by modelling the tours as discrete entities, in conjunction with the amount of each commodity consumed per stop on each such tour in terms of the continuous quantities of microeconomics. This is performed both under a budget/income constraint from microeconomics and a time budget constraint from time geography. The model considers both physical trips and tele-orders.

Theory of epigenetic coding.

PubMed

Elder, D

1984-06-07

The logic of genetic control of development may be based on a binary epigenetic code. This paper revises the author's previous scheme dealing with the numerology of annelid metamerism in these terms. Certain features of the code had been deduced to be combinatorial, others not. This paradoxical contrast is resolved here by the interpretation that these features relate to different operations of the code; the combinatiorial to coding identity of units, the non-combinatorial to coding production of units. Consideration of a second paradox in the theory of epigenetic coding leads to a new solution which further provides a basis for epimorphic regeneration, and may in particular throw light on the "regeneration-duplication" phenomenon. A possible test of the model is also put forward.

It looks easy! Heuristics for combinatorial optimization problems.

PubMed

Chronicle, Edward P; MacGregor, James N; Ormerod, Thomas C; Burr, Alistair

2006-04-01

Human performance on instances of computationally intractable optimization problems, such as the travelling salesperson problem (TSP), can be excellent. We have proposed a boundary-following heuristic to account for this finding. We report three experiments with TSPs where the capacity to employ this heuristic was varied. In Experiment 1, participants free to use the heuristic produced solutions significantly closer to optimal than did those prevented from doing so. Experiments 2 and 3 together replicated this finding in larger problems and demonstrated that a potential confound had no effect. In all three experiments, performance was closely matched by a boundary-following model. The results implicate global rather than purely local processes. Humans may have access to simple, perceptually based, heuristics that are suited to some combinatorial optimization tasks.

An Introduction to Simulated Annealing

ERIC Educational Resources Information Center

Albright, Brian

2007-01-01

An attempt to model the physical process of annealing lead to the development of a type of combinatorial optimization algorithm that takes on the problem of getting trapped in a local minimum. The author presents a Microsoft Excel spreadsheet that illustrates how this works.

Combinatorial chemistry has matured in the last three decades: dedicated to Professor Árpád Furka on the occasion of his 80th birthday.

PubMed

Dibó, Gábor

2012-02-01

Combinatorial chemistry was introduced in the 1980s. It provided the possibility to produce new compounds in practically unlimited number. New strategies and technologies have also been developed that made it possible to screen very large number of compounds and to identify useful components in mixtures containing millions of different substances. This dramatically changed the drug discovery process and the way of thinking of synthetic chemists. In addition, combinatorial strategies became useful in areas such as pharmaceutical research, agrochemistry, catalyst design, and materials research. Prof. Árpád Furka is one of the pioneers of combinatorial chemistry.

Construction of a virtual combinatorial library using SMILES strings to discover potential structure-diverse PPAR modulators.

PubMed

Liao, Chenzhong; Liu, Bing; Shi, Leming; Zhou, Jiaju; Lu, Xian-Ping

2005-07-01

Based on the structural characters of PPAR modulators, a virtual combinatorial library containing 1226,625 compounds was constructed using SMILES strings. Selected ADME filters were employed to compel compounds having poor drug-like properties from this library. This library was converted to sdf and mol2 files by CONCORD 4.0, and was then docked to PPARgamma by DOCK 4.0 to identify new chemical entities that may be potential drug leads against type 2 diabetes and other metabolic diseases. The method to construct virtual combinatorial library using SMILES strings was further visualized by Visual Basic.net that can facilitate the needs of generating other type virtual combinatorial libraries.

Numerical treatment of a geometrically nonlinear planar Cosserat shell model

NASA Astrophysics Data System (ADS)

Sander, Oliver; Neff, Patrizio; Bîrsan, Mircea

2016-05-01

We present a new way to discretize a geometrically nonlinear elastic planar Cosserat shell. The kinematical model is similar to the general six-parameter resultant shell model with drilling rotations. The discretization uses geodesic finite elements (GFEs), which leads to an objective discrete model which naturally allows arbitrarily large rotations. GFEs of any approximation order can be constructed. The resulting algebraic problem is a minimization problem posed on a nonlinear finite-dimensional Riemannian manifold. We solve this problem using a Riemannian trust-region method, which is a generalization of Newton's method that converges globally without intermediate loading steps. We present the continuous model and the discretization, discuss the properties of the discrete model, and show several numerical examples, including wrinkling of thin elastic sheets in shear.

Combinatorial control of messenger RNAs by Pumilio, Nanos and Brain Tumor Proteins

PubMed Central

Arvola, René M.

2017-01-01

ABSTRACT Eukaryotes possess a vast array of RNA-binding proteins (RBPs) that affect mRNAs in diverse ways to control protein expression. Combinatorial regulation of mRNAs by RBPs is emerging as the rule. No example illustrates this as vividly as the partnership of 3 Drosophila RBPs, Pumilio, Nanos and Brain Tumor, which have overlapping functions in development, stem cell maintenance and differentiation, fertility and neurologic processes. Here we synthesize 30 y of research with new insights into their molecular functions and mechanisms of action. First, we provide an overview of the key properties of each RBP. Next, we present a detailed analysis of their collaborative regulatory mechanism using a classic example of the developmental morphogen, hunchback, which is spatially and temporally regulated by the trio during embryogenesis. New biochemical, structural and functional analyses provide insights into RNA recognition, cooperativity, and regulatory mechanisms. We integrate these data into a model of combinatorial RNA binding and regulation of translation and mRNA decay. We then use this information, transcriptome wide analyses and bioinformatics predictions to assess the global impact of Pumilio, Nanos and Brain Tumor on gene regulation. Together, the results support pervasive, dynamic post-transcriptional control. PMID:28318367

Combinatorial control of messenger RNAs by Pumilio, Nanos and Brain Tumor Proteins.

PubMed

Arvola, René M; Weidmann, Chase A; Tanaka Hall, Traci M; Goldstrohm, Aaron C

2017-11-02

Eukaryotes possess a vast array of RNA-binding proteins (RBPs) that affect mRNAs in diverse ways to control protein expression. Combinatorial regulation of mRNAs by RBPs is emerging as the rule. No example illustrates this as vividly as the partnership of 3 Drosophila RBPs, Pumilio, Nanos and Brain Tumor, which have overlapping functions in development, stem cell maintenance and differentiation, fertility and neurologic processes. Here we synthesize 30 y of research with new insights into their molecular functions and mechanisms of action. First, we provide an overview of the key properties of each RBP. Next, we present a detailed analysis of their collaborative regulatory mechanism using a classic example of the developmental morphogen, hunchback, which is spatially and temporally regulated by the trio during embryogenesis. New biochemical, structural and functional analyses provide insights into RNA recognition, cooperativity, and regulatory mechanisms. We integrate these data into a model of combinatorial RNA binding and regulation of translation and mRNA decay. We then use this information, transcriptome wide analyses and bioinformatics predictions to assess the global impact of Pumilio, Nanos and Brain Tumor on gene regulation. Together, the results support pervasive, dynamic post-transcriptional control.

Discretization-dependent model for weakly connected excitable media

NASA Astrophysics Data System (ADS)

Arroyo, Pedro André; Alonso, Sergio; Weber dos Santos, Rodrigo

2018-03-01

Pattern formation has been widely observed in extended chemical and biological processes. Although the biochemical systems are highly heterogeneous, homogenized continuum approaches formed by partial differential equations have been employed frequently. Such approaches are usually justified by the difference of scales between the heterogeneities and the characteristic spatial size of the patterns. Under different conditions, for example, under weak coupling, discrete models are more adequate. However, discrete models may be less manageable, for instance, in terms of numerical implementation and mesh generation, than the associated continuum models. Here we study a model to approach discreteness which permits the computer implementation on general unstructured meshes. The model is cast as a partial differential equation but with a parameter that depends not only on heterogeneities sizes, as in the case of quasicontinuum models, but also on the discretization mesh. Therefore, we refer to it as a discretization-dependent model. We validate the approach in a generic excitable media that simulates three different phenomena: the propagation of action membrane potential in cardiac tissue, in myelinated axons of neurons, and concentration waves in chemical microemulsions.

Systematic Identification of Combinatorial Drivers and Targets in Cancer Cell Lines

PubMed Central

Tabchy, Adel; Eltonsy, Nevine; Housman, David E.; Mills, Gordon B.

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance. PMID:23577104

Systematic identification of combinatorial drivers and targets in cancer cell lines.

PubMed

Tabchy, Adel; Eltonsy, Nevine; Housman, David E; Mills, Gordon B

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.

An evaluation of methods for estimating the number of local optima in combinatorial optimization problems.

PubMed

Hernando, Leticia; Mendiburu, Alexander; Lozano, Jose A

2013-01-01

The solution of many combinatorial optimization problems is carried out by metaheuristics, which generally make use of local search algorithms. These algorithms use some kind of neighborhood structure over the search space. The performance of the algorithms strongly depends on the properties that the neighborhood imposes on the search space. One of these properties is the number of local optima. Given an instance of a combinatorial optimization problem and a neighborhood, the estimation of the number of local optima can help not only to measure the complexity of the instance, but also to choose the most convenient neighborhood to solve it. In this paper we review and evaluate several methods to estimate the number of local optima in combinatorial optimization problems. The methods reviewed not only come from the combinatorial optimization literature, but also from the statistical literature. A thorough evaluation in synthetic as well as real problems is given. We conclude by providing recommendations of methods for several scenarios.

Combinatorial materials approach to accelerate materials discovery for transportation (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tong, Wei

2017-04-01

Combinatorial material research offers fast and efficient solutions to identify promising and advanced materials. It has revolutionized the pharmaceutical industry and now is being applied to accelerate the discovery of other new compounds, e.g. superconductors, luminescent materials, catalysts etc. Differing from the traditional trial-and-error process, this approach allows for the synthesis of a large number of compositionally diverse compounds by varying the combinations of the components and adjusting the ratios. It largely reduces the cost of single-sample synthesis/characterization, along with the turnaround time in the material discovery process, therefore, could dramatically change the existing paradigm for discovering and commercializing new materials. This talk outlines the use of combinatorial materials approach in the material discovery in transportation sector. It covers the general introduction to the combinatorial material concept, state of art for its application in energy-related research. At the end, LBNL capabilities in combinatorial materials synthesis and high throughput characterization that are applicable for material discovery research will be highlighted.

SMITHERS: An object-oriented modular mapping methodology for MCNP-based neutronic–thermal hydraulic multiphysics

DOE PAGES

Richard, Joshua; Galloway, Jack; Fensin, Michael; ...

2015-04-04

A novel object-oriented modular mapping methodology for externally coupled neutronics–thermal hydraulics multiphysics simulations was developed. The Simulator using MCNP with Integrated Thermal-Hydraulics for Exploratory Reactor Studies (SMITHERS) code performs on-the-fly mapping of material-wise power distribution tallies implemented by MCNP-based neutron transport/depletion solvers for use in estimating coolant temperature and density distributions with a separate thermal-hydraulic solver. The key development of SMITHERS is that it reconstructs the hierarchical geometry structure of the material-wise power generation tallies from the depletion solver automatically, with only a modicum of additional information required from the user. In addition, it performs the basis mapping from themore » combinatorial geometry of the depletion solver to the required geometry of the thermal-hydraulic solver in a generalizable manner, such that it can transparently accommodate varying levels of thermal-hydraulic solver geometric fidelity, from the nodal geometry of multi-channel analysis solvers to the pin-cell level of discretization for sub-channel analysis solvers.« less

Molecular dynamics simulation on HP1 protein binding by histone H3 tail methylation and phosphorylation

NASA Astrophysics Data System (ADS)

Jiang, Yan-Ke; Zou, Jian-Wei; Wu, Yu-Qian; Zhang, Na; Yu, Qing-Sen; Jiang, Yong-Jun

Trimethylation of histone H3 lysine 9 is important for recruiting heterochromatin protein 1 (HP1) to discrete regions of the genome, thereby regulating gene expression, chromatin packaging, and heterochromatin formation. Phosphorylation of histone H3 has been linked with mitotic chromatin condensation. During mitosis in vivo, H3 lysine 9 methylation and serine 10 phosphorylation can occur concomitantly on the same histone tail, whereas the influence of phosphorylation to trimethylation H3 tail recruiting HP1 remains controversial. In this work, molecular dynamics simulation of HP1 complexed with both trimethylated and phosphorylated H3 tail were performed and compared with the results from the previous methylated H3-HP1 trajectory. It is clear from the 10-ns dynamics simulation that two adjacent posttranslational modifications directly increase the flexibility of the H3 tail and weaken HP1 binding to chromatin. A combinatorial readout of two adjacent posttranslational modifications-a stable methylation and a dynamic phosphorylation mark-establish a regulatory mechanism of protein-protein interactions.

Broad Integration of Expression Maps and Co-Expression Networks Compassing Novel Gene Functions in the Brain

PubMed Central

Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo

2014-01-01

Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas. PMID:25382412

Locality for quantum systems on graphs depends on the number field

NASA Astrophysics Data System (ADS)

Hall, H. Tracy; Severini, Simone

2013-07-01

Adapting a definition of Aaronson and Ambainis (2005 Theory Comput. 1 47-79), we call a quantum dynamics on a digraph saturated Z-local if the nonzero transition amplitudes specifying the unitary evolution are in exact correspondence with the directed edges (including loops) of the digraph. This idea appears recurrently in a variety of contexts including angular momentum, quantum chaos, and combinatorial matrix theory. Complete characterization of the digraph properties that allow such a process to exist is a long-standing open question that can also be formulated in terms of minimum rank problems. We prove that saturated Z-local dynamics involving complex amplitudes occur on a proper superset of the digraphs that allow restriction to the real numbers or, even further, the rationals. Consequently, among these fields, complex numbers guarantee the largest possible choice of topologies supporting a discrete quantum evolution. A similar construction separates complex numbers from the skew field of quaternions. The result proposes a concrete ground for distinguishing between complex and quaternionic quantum mechanics.

A characterization of horizontal visibility graphs and combinatorics on words

NASA Astrophysics Data System (ADS)

Gutin, Gregory; Mansour, Toufik; Severini, Simone

2011-06-01

A Horizontal Visibility Graph (HVG) is defined in association with an ordered set of non-negative reals. HVGs realize a methodology in the analysis of time series, their degree distribution being a good discriminator between randomness and chaos Luque et al. [B. Luque, L. Lacasa, F. Ballesteros, J. Luque, Horizontal visibility graphs: exact results for random time series, Phys. Rev. E 80 (2009), 046103]. We prove that a graph is an HVG if and only if it is outerplanar and has a Hamilton path. Therefore, an HVG is a noncrossing graph, as defined in algebraic combinatorics Flajolet and Noy [P. Flajolet, M. Noy, Analytic combinatorics of noncrossing configurations, Discrete Math., 204 (1999) 203-229]. Our characterization of HVGs implies a linear time recognition algorithm. Treating ordered sets as words, we characterize subfamilies of HVGs highlighting various connections with combinatorial statistics and introducing the notion of a visible pair. With this technique, we determine asymptotically the average number of edges of HVGs.

ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

PubMed Central

2011-01-01

Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics. PMID:21774817

Systemic combinatorial peptide selection yields a non-canonical iron-mimicry mechanism for targeting tumors in a mouse model of human glioblastoma

PubMed Central

Staquicini, Fernanda I.; Ozawa, Michael G.; Moya, Catherine A.; Driessen, Wouter H.P.; Barbu, E. Magda; Nishimori, Hiroyuki; Soghomonyan, Suren; Flores, Leo G.; Liang, Xiaowen; Paolillo, Vincenzo; Alauddin, Mian M.; Basilion, James P.; Furnari, Frank B.; Bogler, Oliver; Lang, Frederick F.; Aldape, Kenneth D.; Fuller, Gregory N.; Höök, Magnus; Gelovani, Juri G.; Sidman, Richard L.; Cavenee, Webster K.; Pasqualini, Renata; Arap, Wadih

2010-01-01

The management of CNS tumors is limited by the blood-brain barrier (BBB), a vascular interface that restricts the passage of most molecules from the blood into the brain. Here we show that phage particles targeted with certain ligand motifs selected in vivo from a combinatorial peptide library can cross the BBB under normal and pathological conditions. Specifically, we demonstrated that phage clones displaying an iron-mimic peptide were able to target a protein complex of transferrin and transferrin receptor (TfR) through a non-canonical allosteric binding mechanism and that this functional protein complex mediated transport of the corresponding viral particles into the normal mouse brain. We also showed that, in an orthotopic mouse model of human glioblastoma, a combination of TfR overexpression plus extended vascular permeability and ligand retention resulted in remarkable brain tumor targeting of chimeric adeno-associated virus/phage particles displaying the iron-mimic peptide and carrying a gene of interest. As a proof of concept, we delivered the HSV thymidine kinase gene for molecular-genetic imaging and targeted therapy of intracranial xenografted tumors. Finally, we established that these experimental findings might be clinically relevant by determining through human tissue microarrays that many primary astrocytic tumors strongly express TfR. Together, our combinatorial selection system and results may provide a translational avenue for the targeted detection and treatment of brain tumors. PMID:21183793

Combinatorial Therapy with Acetylation and Methylation Modifiers Attenuates Lung Vascular Hyperpermeability in Endotoxemia-Induced Mouse Inflammatory Lung Injury

PubMed Central

Thangavel, Jayakumar; Malik, Asrar B.; Elias, Harold K.; Rajasingh, Sheeja; Simpson, Andrew D.; Sundivakkam, Premanand K.; Vogel, Stephen M.; Xuan, Yu-Ting; Dawn, Buddhadeb; Rajasingh, Johnson

2015-01-01

Impairment of tissue fluid homeostasis and migration of inflammatory cells across the vascular endothelial barrier are crucial factors in the pathogenesis of acute lung injury (ALI). The goal for treatment of ALI is to target pathways that lead to profound dysregulation of the lung endothelial barrier. Although studies have shown that chemical epigenetic modifiers can limit lung inflammation in experimental ALI models, studies to date have not examined efficacy of a combination of DNA methyl transferase inhibitor 5-Aza 2-deoxycytidine and histone deacetylase inhibitor trichostatin A (herein referred to as Aza+TSA) after endotoxemia-induced mouse lung injury. We tested the hypothesis that treatment with Aza+TSA after lipopolysaccharide induction of ALI through epigenetic modification of lung endothelial cells prevents inflammatory lung injury. Combinatorial treatment with Aza+TSA mitigated the increased endothelial permeability response after lipopolysaccharide challenge. In addition, we observed reduced lung inflammation and lung injury. Aza+TSA also significantly reduced mortality in the ALI model. The protection was ascribed to inhibition of the eNOS-Cav1-MLC2 signaling pathway and enhanced acetylation of histone markers on the vascular endothelial-cadherin promoter. In summary, these data show for the first time the efficacy of combinatorial Aza+TSA therapy in preventing ALI in lipopolysaccharide-induced endotoxemia and raise the possibility of an essential role of DNA methyl transferase and histone deacetylase in the mechanism of ALI. PMID:24929240

Discovery of the leinamycin family of natural products by mining actinobacterial genomes

PubMed Central

Xu, Zhengren; Guo, Zhikai; Hindra; Ma, Ming; Zhou, Hao; Gansemans, Yannick; Zhu, Xiangcheng; Huang, Yong; Zhao, Li-Xing; Jiang, Yi; Cheng, Jinhua; Van Nieuwerburgh, Filip; Suh, Joo-Won; Duan, Yanwen

2017-01-01

Nature’s ability to generate diverse natural products from simple building blocks has inspired combinatorial biosynthesis. The knowledge-based approach to combinatorial biosynthesis has allowed the production of designer analogs by rational metabolic pathway engineering. While successful, structural alterations are limited, with designer analogs often produced in compromised titers. The discovery-based approach to combinatorial biosynthesis complements the knowledge-based approach by exploring the vast combinatorial biosynthesis repertoire found in Nature. Here we showcase the discovery-based approach to combinatorial biosynthesis by targeting the domain of unknown function and cysteine lyase domain (DUF–SH) didomain, specific for sulfur incorporation from the leinamycin (LNM) biosynthetic machinery, to discover the LNM family of natural products. By mining bacterial genomes from public databases and the actinomycetes strain collection at The Scripps Research Institute, we discovered 49 potential producers that could be grouped into 18 distinct clades based on phylogenetic analysis of the DUF–SH didomains. Further analysis of the representative genomes from each of the clades identified 28 lnm-type gene clusters. Structural diversities encoded by the LNM-type biosynthetic machineries were predicted based on bioinformatics and confirmed by in vitro characterization of selected adenylation proteins and isolation and structural elucidation of the guangnanmycins and weishanmycins. These findings demonstrate the power of the discovery-based approach to combinatorial biosynthesis for natural product discovery and structural diversity and highlight Nature’s rich biosynthetic repertoire. Comparative analysis of the LNM-type biosynthetic machineries provides outstanding opportunities to dissect Nature’s biosynthetic strategies and apply these findings to combinatorial biosynthesis for natural product discovery and structural diversity. PMID:29229819

Discovery of the leinamycin family of natural products by mining actinobacterial genomes.

PubMed

Pan, Guohui; Xu, Zhengren; Guo, Zhikai; Hindra; Ma, Ming; Yang, Dong; Zhou, Hao; Gansemans, Yannick; Zhu, Xiangcheng; Huang, Yong; Zhao, Li-Xing; Jiang, Yi; Cheng, Jinhua; Van Nieuwerburgh, Filip; Suh, Joo-Won; Duan, Yanwen; Shen, Ben

2017-12-26

Nature's ability to generate diverse natural products from simple building blocks has inspired combinatorial biosynthesis. The knowledge-based approach to combinatorial biosynthesis has allowed the production of designer analogs by rational metabolic pathway engineering. While successful, structural alterations are limited, with designer analogs often produced in compromised titers. The discovery-based approach to combinatorial biosynthesis complements the knowledge-based approach by exploring the vast combinatorial biosynthesis repertoire found in Nature. Here we showcase the discovery-based approach to combinatorial biosynthesis by targeting the domain of unknown function and cysteine lyase domain (DUF-SH) didomain, specific for sulfur incorporation from the leinamycin (LNM) biosynthetic machinery, to discover the LNM family of natural products. By mining bacterial genomes from public databases and the actinomycetes strain collection at The Scripps Research Institute, we discovered 49 potential producers that could be grouped into 18 distinct clades based on phylogenetic analysis of the DUF-SH didomains. Further analysis of the representative genomes from each of the clades identified 28 lnm -type gene clusters. Structural diversities encoded by the LNM-type biosynthetic machineries were predicted based on bioinformatics and confirmed by in vitro characterization of selected adenylation proteins and isolation and structural elucidation of the guangnanmycins and weishanmycins. These findings demonstrate the power of the discovery-based approach to combinatorial biosynthesis for natural product discovery and structural diversity and highlight Nature's rich biosynthetic repertoire. Comparative analysis of the LNM-type biosynthetic machineries provides outstanding opportunities to dissect Nature's biosynthetic strategies and apply these findings to combinatorial biosynthesis for natural product discovery and structural diversity.

Integrable discrete PT symmetric model.

PubMed

Ablowitz, Mark J; Musslimani, Ziad H

2014-09-01

An exactly solvable discrete PT invariant nonlinear Schrödinger-like model is introduced. It is an integrable Hamiltonian system that exhibits a nontrivial nonlinear PT symmetry. A discrete one-soliton solution is constructed using a left-right Riemann-Hilbert formulation. It is shown that this pure soliton exhibits unique features such as power oscillations and singularity formation. The proposed model can be viewed as a discretization of a recently obtained integrable nonlocal nonlinear Schrödinger equation.

Modeling Anti-Air Warfare With Discrete Event Simulation and Analyzing Naval Convoy Operations

DTIC Science & Technology

2016-06-01

WARFARE WITH DISCRETE EVENT SIMULATION AND ANALYZING NAVAL CONVOY OPERATIONS by Ali E. Opcin June 2016 Thesis Advisor: Arnold H. Buss Co...REPORT DATE June 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MODELING ANTI-AIR WARFARE WITH DISCRETE EVENT...In this study, a discrete event simulation (DES) was built by modeling ships, and their sensors and weapons, to simulate convoy operations under

Achieving Remission in Gulf War Illness: A Simulation-Based Approach to Treatment Design.

PubMed

Craddock, Travis J A; Del Rosario, Ryan R; Rice, Mark; Zysman, Joel P; Fletcher, Mary Ann; Klimas, Nancy G; Broderick, Gordon

2015-01-01

Gulf War Illness (GWI) is a chronic multi-symptom disorder affecting up to one-third of the 700,000 returning veterans of the 1991 Persian Gulf War and for which there is no known cure. GWI symptoms span several of the body's principal regulatory systems and include debilitating fatigue, severe musculoskeletal pain, cognitive and neurological problems. Using computational models, our group reported previously that GWI might be perpetuated at least in part by natural homeostatic regulation of the neuroendocrine-immune network. In this work, we attempt to harness these regulatory dynamics to identify treatment courses that might produce lasting remission. Towards this we apply a combinatorial optimization scheme to the Monte Carlo simulation of a discrete ternary logic model that represents combined hypothalamic-pituitary-adrenal (HPA), gonadal (HPG), and immune system regulation in males. In this work we found that no single intervention target allowed a robust return to normal homeostatic control. All combined interventions leading to a predicted remission involved an initial inhibition of Th1 inflammatory cytokines (Th1Cyt) followed by a subsequent inhibition of glucocorticoid receptor function (GR). These first two intervention events alone ended in stable and lasting return to the normal regulatory control in 40% of the simulated cases. Applying a second cycle of this combined treatment improved this predicted remission rate to 2 out of 3 simulated subjects (63%). These results suggest that in a complex illness such as GWI, a multi-tiered intervention strategy that formally accounts for regulatory dynamics may be required to reset neuroendocrine-immune homeostasis and support extended remission.

A Simulation of Alternatives for Wholesale Inventory Replenishment

DTIC Science & Technology

2016-03-01

algorithmic details. The last method is a mixed-integer, linear optimization model. Comparative Inventory Simulation, a discrete event simulation model, is...simulation; event graphs; reorder point; fill-rate; backorder; discrete event simulation; wholesale inventory optimization model 15. NUMBER OF PAGES...model. Comparative Inventory Simulation, a discrete event simulation model, is designed to find fill rates achieved for each National Item

Combinatorial pretreatment and fermentation optimization enabled a record yield on lignin bioconversion.

PubMed

Liu, Zhi-Hua; Xie, Shangxian; Lin, Furong; Jin, Mingjie; Yuan, Joshua S

2018-01-01

Lignin valorization has recently been considered to be an essential process for sustainable and cost-effective biorefineries. Lignin represents a potential new feedstock for value-added products. Oleaginous bacteria such as Rhodococcus opacus can produce intracellular lipids from biodegradation of aromatic substrates. These lipids can be used for biofuel production, which can potentially replace petroleum-derived chemicals. However, the low reactivity of lignin produced from pretreatment and the underdeveloped fermentation technology hindered lignin bioconversion to lipids. In this study, combinatorial pretreatment with an optimized fermentation strategy was evaluated to improve lignin valorization into lipids using R. opacus PD630. As opposed to single pretreatment, combinatorial pretreatment produced a 12.8-75.6% higher lipid concentration in fermentation using lignin as the carbon source. Gas chromatography-mass spectrometry analysis showed that combinatorial pretreatment released more aromatic monomers, which could be more readily utilized by lignin-degrading strains. Three detoxification strategies were used to remove potential inhibitors produced from pretreatment. After heating detoxification of the lignin stream, the lipid concentration further increased by 2.9-9.7%. Different fermentation strategies were evaluated in scale-up lipid fermentation using a 2.0-l fermenter. With laccase treatment of the lignin stream produced from combinatorial pretreatment, the highest cell dry weight and lipid concentration were 10.1 and 1.83 g/l, respectively, in fed-batch fermentation, with a total soluble substrate concentration of 40 g/l. The improvement of the lipid fermentation performance may have resulted from lignin depolymerization by the combinatorial pretreatment and laccase treatment, reduced inhibition effects by fed-batch fermentation, adequate oxygen supply, and an accurate pH control in the fermenter. Overall, these results demonstrate that combinatorial pretreatment, together with fermentation optimization, favorably improves lipid production using lignin as the carbon source. Combinatorial pretreatment integrated with fed-batch fermentation was an effective strategy to improve the bioconversion of lignin into lipids, thus facilitating lignin valorization in biorefineries.

A discrete control model of PLANT

NASA Technical Reports Server (NTRS)

Mitchell, C. M.

1985-01-01

A model of the PLANT system using the discrete control modeling techniques developed by Miller is described. Discrete control models attempt to represent in a mathematical form how a human operator might decompose a complex system into simpler parts and how the control actions and system configuration are coordinated so that acceptable overall system performance is achieved. Basic questions include knowledge representation, information flow, and decision making in complex systems. The structure of the model is a general hierarchical/heterarchical scheme which structurally accounts for coordination and dynamic focus of attention. Mathematically, the discrete control model is defined in terms of a network of finite state systems. Specifically, the discrete control model accounts for how specific control actions are selected from information about the controlled system, the environment, and the context of the situation. The objective is to provide a plausible and empirically testable accounting and, if possible, explanation of control behavior.

Single agent and synergistic combinatorial efficacy of first-in-class small molecule imipridone ONC201 in hematological malignancies.

PubMed

Prabhu, Varun V; Talekar, Mala K; Lulla, Amriti R; Kline, C Leah B; Zhou, Lanlan; Hall, Junior; Van den Heuvel, A Pieter J; Dicker, David T; Babar, Jawad; Grupp, Stephan A; Garnett, Mathew J; McDermott, Ultan; Benes, Cyril H; Pu, Jeffrey J; Claxton, David F; Khan, Nadia; Oster, Wolfgang; Allen, Joshua E; El-Deiry, Wafik S

2018-01-01

ONC201, founding member of the imipridone class of small molecules, is currently being evaluated in advancer cancer clinical trials. We explored single agent and combinatorial efficacy of ONC201 in preclinical models of hematological malignancies. ONC201 demonstrated (GI50 1-8 µM) dose- and time-dependent efficacy in acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myelogenous leukemia (CML), chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL), mantle cell lymphoma (MCL), Burkitt's lymphoma, anaplastic large cell lymphoma (ALCL), cutaneous T-cell lymphoma (CTCL), Hodgkin's lymphoma (nodular sclerosis) and multiple myeloma (MM) cell lines including cells resistant to standard of care (dexamethasone in MM) and primary samples. ONC201 induced caspase-dependent apoptosis that involved activation of the integrated stress response (ATF4/CHOP) pathway, inhibition of Akt phosphorylation, Foxo3a activation, downregulation of cyclin D1, IAP and Bcl-2 family members. ONC201 synergistically reduced cell viability in combination with cytarabine and 5-azacytidine in AML cells. ONC201 combined with cytarabine in a Burkitt's lymphoma xenograft model induced tumor growth inhibition that was superior to either agent alone. ONC201 synergistically combined with bortezomib in MM, MCL and ALCL cells and with ixazomib or dexamethasone in MM cells. ONC201 combined with bortezomib in a Burkitt's lymphoma xenograft model reduced tumor cell density and improved CHOP induction compared to either agent alone. These results serve as a rationale for ONC201 single-agent trials in relapsed/refractory acute leukemia, non-Hodgkin's lymphoma, MM and combination trial with dexamethasone in MM, provide pharmacodynamic biomarkers and identify further synergistic combinatorial regimens that can be explored in the clinic.

Modelling road accident blackspots data with the discrete generalized Pareto distribution.

PubMed

Prieto, Faustino; Gómez-Déniz, Emilio; Sarabia, José María

2014-10-01

This study shows how road traffic networks events, in particular road accidents on blackspots, can be modelled with simple probabilistic distributions. We considered the number of crashes and the number of fatalities on Spanish blackspots in the period 2003-2007, from Spanish General Directorate of Traffic (DGT). We modelled those datasets, respectively, with the discrete generalized Pareto distribution (a discrete parametric model with three parameters) and with the discrete Lomax distribution (a discrete parametric model with two parameters, and particular case of the previous model). For that, we analyzed the basic properties of both parametric models: cumulative distribution, survival, probability mass, quantile and hazard functions, genesis and rth-order moments; applied two estimation methods of their parameters: the μ and (μ+1) frequency method and the maximum likelihood method; used two goodness-of-fit tests: Chi-square test and discrete Kolmogorov-Smirnov test based on bootstrap resampling; and compared them with the classical negative binomial distribution in terms of absolute probabilities and in models including covariates. We found that those probabilistic models can be useful to describe the road accident blackspots datasets analyzed. Copyright © 2014 Elsevier Ltd. All rights reserved.

A discrete-space urban model with environmental amenities

Treesearch

Liaila Tajibaeva; Robert G. Haight; Stephen Polasky

2008-01-01

This paper analyzes the effects of providing environmental amenities associated with open space in a discrete-space urban model and characterizes optimal provision of open space across a metropolitan area. The discrete-space model assumes distinct neighborhoods in which developable land is homogeneous within a neighborhood but heterogeneous across neighborhoods. Open...

Wheat mill stream properties for discrete element method modeling

USDA-ARS?s Scientific Manuscript database

A discrete phase approach based on individual wheat kernel characteristics is needed to overcome the limitations of previous statistical models and accurately predict the milling behavior of wheat. As a first step to develop a discrete element method (DEM) model for the wheat milling process, this s...

Variable selection in discrete survival models including heterogeneity.

PubMed

Groll, Andreas; Tutz, Gerhard

2017-04-01

Several variable selection procedures are available for continuous time-to-event data. However, if time is measured in a discrete way and therefore many ties occur models for continuous time are inadequate. We propose penalized likelihood methods that perform efficient variable selection in discrete survival modeling with explicit modeling of the heterogeneity in the population. The method is based on a combination of ridge and lasso type penalties that are tailored to the case of discrete survival. The performance is studied in simulation studies and an application to the birth of the first child.

An Indexed Combinatorial Library: The Synthesis and Testing of Insect Repellents

NASA Astrophysics Data System (ADS)

Miles, William H.; Gelato, Kathy A.; Pompizzi, Kristen M.; Scarbinsky, Aislinn M.; Albrecht, Brian K.; Reynolds, Elaine R.

2001-04-01

An indexed combinatorial library of amides was prepared by the reaction of amines and acid chlorides. A simple test for insect repellency using fruit flies (Drosophila melanogaster) allowed the determination of the most repellent sublibraries. The student-generated data were collected and analyzed to determine the most active amide(s) in the library. This experiment illustrates the fundamentals of combinatorial chemistry, a field that has undergone explosive growth in the last decade.

Discretization and control of an SEIR epidemic model under equilibrium Wiener noise disturbances

NASA Astrophysics Data System (ADS)

Alonso, Santiago; De la Sen, Manuel; Nistal, Raul; Ibeas, Asier

2017-11-01

A discretized SEIR epidemic model, subject to Wiener noise disturbances of the equilibrium points, is studied. The discrete-time model is got from a general discretization technique applied to its continuous-time counterpart so that its behaviour be close to its continuous-time counterpart irrespective of the size of the discretization period. The positivity and stability of a normalized version of such a discrete-time model are emphasized. The paper also proposes the design of a periodic impulsive vaccination which is periodically injected to the susceptible subpopulation in order to eradicate the propagation of the disease or, at least, to reduce its unsuitable infective effects within the potentially susceptible subpopulation. The existence and asymptotic stability of a disease-free periodic solution are proved. In particular, both the exposed and infectious subpopulations converge asymptotically to zero as time tends to infinity while the normalized subpopulations of susceptible and recovered by immunization oscillate.

Exploiting Lipid Permutation Symmetry to Compute Membrane Remodeling Free Energies.

PubMed

Bubnis, Greg; Risselada, Herre Jelger; Grubmüller, Helmut

2016-10-28

A complete physical description of membrane remodeling processes, such as fusion or fission, requires knowledge of the underlying free energy landscapes, particularly in barrier regions involving collective shape changes, topological transitions, and high curvature, where Canham-Helfrich (CH) continuum descriptions may fail. To calculate these free energies using atomistic simulations, one must address not only the sampling problem due to high free energy barriers, but also an orthogonal sampling problem of combinatorial complexity stemming from the permutation symmetry of identical lipids. Here, we solve the combinatorial problem with a permutation reduction scheme to map a structural ensemble into a compact, nondegenerate subregion of configuration space, thereby permitting straightforward free energy calculations via umbrella sampling. We applied this approach, using a coarse-grained lipid model, to test the CH description of bending and found sharp increases in the bending modulus for curvature radii below 10 nm. These deviations suggest that an anharmonic bending term may be required for CH models to give quantitative energetics of highly curved states.

A method for aircraft concept exploration using multicriteria interactive genetic algorithms

NASA Astrophysics Data System (ADS)

Buonanno, Michael Alexander

2005-08-01

The problem of aircraft concept selection has become increasingly difficult in recent years due to changes in the primary evaluation criteria of concepts. In the past, performance was often the primary discriminator, whereas modern programs have placed increased emphasis on factors such as environmental impact, economics, supportability, aesthetics, and other metrics. The revolutionary nature of the vehicles required to simultaneously meet these conflicting requirements has prompted a shift from design using historical data regression techniques for metric prediction to the use of sophisticated physics-based analysis tools that are capable of analyzing designs outside of the historical database. The use of optimization methods with these physics-based tools, however, has proven difficult because of the tendency of optimizers to exploit assumptions present in the models and drive the design towards a solution which, while promising to the computer, may be infeasible due to factors not considered by the computer codes. In addition to this difficulty, the number of discrete options available at this stage may be unmanageable due to the combinatorial nature of the concept selection problem, leading the analyst to select a sub-optimum baseline vehicle. Some extremely important concept decisions, such as the type of control surface arrangement to use, are frequently made without sufficient understanding of their impact on the important system metrics due to a lack of historical guidance, computational resources, or analysis tools. This thesis discusses the difficulties associated with revolutionary system design, and introduces several new techniques designed to remedy them. First, an interactive design method has been developed that allows the designer to provide feedback to a numerical optimization algorithm during runtime, thereby preventing the optimizer from exploiting weaknesses in the analytical model. This method can be used to account for subjective criteria, or as a crude measure of un-modeled quantitative criteria. Other contributions of the work include a modified Structured Genetic Algorithm that enables the efficient search of large combinatorial design hierarchies and an improved multi-objective optimization procedure that can effectively optimize several objectives simultaneously. A new conceptual design method has been created by drawing upon each of these new capabilities and aspects of more traditional design methods. The ability of this new technique to assist in the design of revolutionary vehicles has been demonstrated using a problem of contemporary interest: the concept exploration of a supersonic business jet. This problem was found to be a good demonstration case because of its novelty and unique requirements, and the results of this proof of concept exercise indicate that the new method is effective at providing additional insight into the relationship between a vehicle's requirements and its favorable attributes.

The role of seniority-zero states in nuclear level densities

DOE PAGES

Åberg, S.; Carlsson, B. G.; Døssing, Th.; ...

2015-06-01

At low excitation energies seniority-zero states dominate the level density of K=0 bands in deformed even–even nuclei, while they play no role at higher excitation energies. We describe the level densities in a Fermi-gas model as well as in a combinatorial level-density model and compare to detailed experimental data for some rare-earth nuclei.

Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria

PubMed Central

Farasat, Iman; Kushwaha, Manish; Collens, Jason; Easterbrook, Michael; Guido, Matthew; Salis, Howard M

2014-01-01

Developing predictive models of multi-protein genetic systems to understand and optimize their behavior remains a combinatorial challenge, particularly when measurement throughput is limited. We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi-protein expression space across a > 10,000-fold range with tailored search parameters and well-predicted translation rates. We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram-positive and gram-negative bacterial hosts. We then combined the search algorithm with system-level kinetic modeling, requiring the construction and characterization of 73 variants to build a sequence-expression-activity map (SEAMAP) for a biosynthesis pathway. Using model predictions, we designed and characterized 47 additional pathway variants to navigate its activity space, find optimal expression regions with desired activity response curves, and relieve rate-limiting steps in metabolism. Creating sequence-expression-activity maps accelerates the optimization of many protein systems and allows previous measurements to quantitatively inform future designs. PMID:24952589

Pulled Motzkin paths

NASA Astrophysics Data System (ADS)

Janse van Rensburg, E. J.

2010-08-01

In this paper the models of pulled Dyck paths in Janse van Rensburg (2010 J. Phys. A: Math. Theor. 43 215001) are generalized to pulled Motzkin path models. The generating functions of pulled Motzkin paths are determined in terms of series over trinomial coefficients and the elastic response of a Motzkin path pulled at its endpoint (see Orlandini and Whittington (2004 J. Phys. A: Math. Gen. 37 5305-14)) is shown to be R(f) = 0 for forces pushing the endpoint toward the adsorbing line and R(f) = f(1 + 2cosh f))/(2sinh f) → f as f → ∞, for forces pulling the path away from the X-axis. In addition, the elastic response of a Motzkin path pulled at its midpoint is shown to be R(f) = 0 for forces pushing the midpoint toward the adsorbing line and R(f) = f(1 + 2cosh (f/2))/sinh (f/2) → 2f as f → ∞, for forces pulling the path away from the X-axis. Formal combinatorial identities arising from pulled Motzkin path models are also presented. These identities are the generalization of combinatorial identities obtained in directed paths models to their natural trinomial counterparts.

The mathematics of a successful deconvolution: a quantitative assessment of mixture-based combinatorial libraries screened against two formylpeptide receptors.

PubMed

Santos, Radleigh G; Appel, Jon R; Giulianotti, Marc A; Edwards, Bruce S; Sklar, Larry A; Houghten, Richard A; Pinilla, Clemencia

2013-05-30

In the past 20 years, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds for drug discovery and basic research. Mixture-based libraries and positional scanning deconvolution combine two approaches for the rapid identification of specific scaffolds and active ligands. Here we present a quantitative assessment of the screening of 32 positional scanning libraries in the identification of highly specific and selective ligands for two formylpeptide receptors. We also compare and contrast two mixture-based library approaches using a mathematical model to facilitate the selection of active scaffolds and libraries to be pursued for further evaluation. The flexibility demonstrated in the differently formatted mixture-based libraries allows for their screening in a wide range of assays.

Compensatory neurofuzzy model for discrete data classification in biomedical

NASA Astrophysics Data System (ADS)

Ceylan, Rahime

2015-03-01

Biomedical data is separated to two main sections: signals and discrete data. So, studies in this area are about biomedical signal classification or biomedical discrete data classification. There are artificial intelligence models which are relevant to classification of ECG, EMG or EEG signals. In same way, in literature, many models exist for classification of discrete data taken as value of samples which can be results of blood analysis or biopsy in medical process. Each algorithm could not achieve high accuracy rate on classification of signal and discrete data. In this study, compensatory neurofuzzy network model is presented for classification of discrete data in biomedical pattern recognition area. The compensatory neurofuzzy network has a hybrid and binary classifier. In this system, the parameters of fuzzy systems are updated by backpropagation algorithm. The realized classifier model is conducted to two benchmark datasets (Wisconsin Breast Cancer dataset and Pima Indian Diabetes dataset). Experimental studies show that compensatory neurofuzzy network model achieved 96.11% accuracy rate in classification of breast cancer dataset and 69.08% accuracy rate was obtained in experiments made on diabetes dataset with only 10 iterations.

Partition-based discrete-time quantum walks

NASA Astrophysics Data System (ADS)

Konno, Norio; Portugal, Renato; Sato, Iwao; Segawa, Etsuo

2018-04-01

We introduce a family of discrete-time quantum walks, called two-partition model, based on two equivalence-class partitions of the computational basis, which establish the notion of local dynamics. This family encompasses most versions of unitary discrete-time quantum walks driven by two local operators studied in literature, such as the coined model, Szegedy's model, and the 2-tessellable staggered model. We also analyze the connection of those models with the two-step coined model, which is driven by the square of the evolution operator of the standard discrete-time coined walk. We prove formally that the two-step coined model, an extension of Szegedy model for multigraphs, and the two-tessellable staggered model are unitarily equivalent. Then, selecting one specific model among those families is a matter of taste not generality.

Combinatorial fabrication and screening of organic light-emitting device arrays

NASA Astrophysics Data System (ADS)

Shinar, Joseph; Shinar, Ruth; Zhou, Zhaoqun

2007-11-01

The combinatorial fabrication and screening of 2-dimensional (2-d) small molecular UV-violet organic light-emitting device (OLED) arrays, 1-d blue-to-red arrays, 1-d intense white OLED libraries, 1-d arrays to study Förster energy transfer in guest-host OLEDs, and 2-d arrays to study exciplex emission from OLEDs is described. The results demonstrate the power of combinatorial approaches for screening OLED materials and configurations, and for studying their basic properties.

Combinatorial Dyson-Schwinger equations and inductive data types

NASA Astrophysics Data System (ADS)

Kock, Joachim

2016-06-01

The goal of this contribution is to explain the analogy between combinatorial Dyson-Schwinger equations and inductive data types to a readership of mathematical physicists. The connection relies on an interpretation of combinatorial Dyson-Schwinger equations as fixpoint equations for polynomial functors (established elsewhere by the author, and summarised here), combined with the now-classical fact that polynomial functors provide semantics for inductive types. The paper is expository, and comprises also a brief introduction to type theory.

Combinatorial stresses kill pathogenic Candida species

PubMed Central

Kaloriti, Despoina; Tillmann, Anna; Cook, Emily; Jacobsen, Mette; You, Tao; Lenardon, Megan; Ames, Lauren; Barahona, Mauricio; Chandrasekaran, Komelapriya; Coghill, George; Goodman, Daniel; Gow, Neil A. R.; Grebogi, Celso; Ho, Hsueh-Lui; Ingram, Piers; McDonagh, Andrew; De Moura, Alessandro P. S.; Pang, Wei; Puttnam, Melanie; Radmaneshfar, Elahe; Romano, Maria Carmen; Silk, Daniel; Stark, Jaroslav; Stumpf, Michael; Thiel, Marco; Thorne, Thomas; Usher, Jane; Yin, Zhikang; Haynes, Ken; Brown, Alistair J. P.

2012-01-01

Pathogenic microbes exist in dynamic niches and have evolved robust adaptive responses to promote survival in their hosts. The major fungal pathogens of humans, Candida albicans and Candida glabrata, are exposed to a range of environmental stresses in their hosts including osmotic, oxidative and nitrosative stresses. Significant efforts have been devoted to the characterization of the adaptive responses to each of these stresses. In the wild, cells are frequently exposed simultaneously to combinations of these stresses and yet the effects of such combinatorial stresses have not been explored. We have developed a common experimental platform to facilitate the comparison of combinatorial stress responses in C. glabrata and C. albicans. This platform is based on the growth of cells in buffered rich medium at 30°C, and was used to define relatively low, medium and high doses of osmotic (NaCl), oxidative (H 2O2) and nitrosative stresses (e.g., dipropylenetriamine (DPTA)-NONOate). The effects of combinatorial stresses were compared with the corresponding individual stresses under these growth conditions. We show for the first time that certain combinations of combinatorial stress are especially potent in terms of their ability to kill C. albicans and C. glabrata and/or inhibit their growth. This was the case for combinations of osmotic plus oxidative stress and for oxidative plus nitrosative stress. We predict that combinatorial stresses may be highly signif cant in host defences against these pathogenic yeasts. PMID:22463109

Steam explosion and its combinatorial pretreatment refining technology of plant biomass to bio-based products.

PubMed

Chen, Hong-Zhang; Liu, Zhi-Hua

2015-06-01

Pretreatment is a key unit operation affecting the refinery efficiency of plant biomass. However, the poor efficiency of pretreatment and the lack of basic theory are the main challenges to the industrial implementation of the plant biomass refinery. The purpose of this work is to review steam explosion and its combinatorial pretreatment as a means of overcoming the intrinsic characteristics of plant biomass, including recalcitrance, heterogeneity, multi-composition, and diversity. The main advantages of the selective use of steam explosion and other combinatorial pretreatments across the diversity of raw materials are introduced. Combinatorial pretreatment integrated with other unit operations is proposed as a means to exploit the high-efficiency production of bio-based products from plant biomass. Finally, several pilot- and demonstration-scale operations of the plant biomass refinery are described. Based on the principle of selective function and structure fractionation, and multi-level and directional composition conversion, an integrated process with the combinatorial pretreatments of steam explosion and other pretreatments as the core should be feasible and conform to the plant biomass refinery concept. Combinatorial pretreatments of steam explosion and other pretreatments should be further exploited based on the type and intrinsic characteristics of the plant biomass used, the bio-based products to be made, and the complementarity of the processes. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluation of the Navys Sea/Shore Flow Policy

DTIC Science & Technology

2016-06-01

Std. Z39.18 i Abstract CNA developed an independent Discrete -Event Simulation model to evaluate and assess the effect of...a more steady manning level, but the variability remains, even if the system is optimized. In building a Discrete -Event Simulation model, we...steady-state model. In FY 2014, CNA developed a Discrete -Event Simulation model to evaluate the impact of sea/shore flow policy (the DES-SSF model

Peridynamics with LAMMPS : a user guide.

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

Lehoucq, Richard B.; Silling, Stewart Andrew; Plimpton, Steven James

2008-01-01

Peridynamics is a nonlocal formulation of continuum mechanics. The discrete peridynamic model has the same computational structure as a molecular dynamic model. This document details the implementation of a discrete peridynamic model within the LAMMPS molecular dynamic code. This document provides a brief overview of the peridynamic model of a continuum, then discusses how the peridynamic model is discretized, and overviews the LAMMPS implementation. A nontrivial example problem is also included.

Defeaturing CAD models using a geometry-based size field and facet-based reduction operators.

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

Quadros, William Roshan; Owen, Steven James

2010-04-01

We propose a method to automatically defeature a CAD model by detecting irrelevant features using a geometry-based size field and a method to remove the irrelevant features via facet-based operations on a discrete representation. A discrete B-Rep model is first created by obtaining a faceted representation of the CAD entities. The candidate facet entities are then marked for reduction by using a geometry-based size field. This is accomplished by estimating local mesh sizes based on geometric criteria. If the field value at a facet entity goes below a user specified threshold value then it is identified as an irrelevant featuremore » and is marked for reduction. The reduction of marked facet entities is primarily performed using an edge collapse operator. Care is taken to retain a valid geometry and topology of the discrete model throughout the procedure. The original model is not altered as the defeaturing is performed on a separate discrete model. Associativity between the entities of the discrete model and that of original CAD model is maintained in order to decode the attributes and boundary conditions applied on the original CAD entities onto the mesh via the entities of the discrete model. Example models are presented to illustrate the effectiveness of the proposed approach.« less

On discrete control of nonlinear systems with applications to robotics

NASA Technical Reports Server (NTRS)

Eslami, Mansour

1989-01-01

Much progress has been reported in the areas of modeling and control of nonlinear dynamic systems in a continuous-time framework. From implementation point of view, however, it is essential to study these nonlinear systems directly in a discrete setting that is amenable for interfacing with digital computers. But to develop discrete models and discrete controllers for a nonlinear system such as robot is a nontrivial task. Robot is also inherently a variable-inertia dynamic system involving additional complications. Not only the computer-oriented models of these systems must satisfy the usual requirements for such models, but these must also be compatible with the inherent capabilities of computers and must preserve the fundamental physical characteristics of continuous-time systems such as the conservation of energy and/or momentum. Preliminary issues regarding discrete systems in general and discrete models of a typical industrial robot that is developed with full consideration of the principle of conservation of energy are presented. Some research on the pertinent tactile information processing is reviewed. Finally, system control methods and how to integrate these issues in order to complete the task of discrete control of a robot manipulator are also reviewed.

Exact static solutions for discrete phi4 models free of the Peierls-Nabarro barrier: discretized first-integral approach.

PubMed

Dmitriev, S V; Kevrekidis, P G; Yoshikawa, N; Frantzeskakis, D J

2006-10-01

We propose a generalization of the discrete Klein-Gordon models free of the Peierls-Nabarro barrier derived in Spreight [Nonlinearity 12, 1373 (1999)] and Barashenkov [Phys. Rev. E 72, 035602(R) (2005)], such that they support not only kinks but a one-parameter set of exact static solutions. These solutions can be obtained iteratively from a two-point nonlinear map whose role is played by the discretized first integral of the static Klein-Gordon field, as suggested by Dmitriev [J. Phys. A 38, 7617 (2005)]. We then discuss some discrete phi4 models free of the Peierls-Nabarro barrier and identify for them the full space of available static solutions, including those derived recently by Cooper [Phys. Rev. E 72, 036605 (2005)] but not limited to them. These findings are also relevant to standing wave solutions of discrete nonlinear Schrödinger models. We also study stability of the obtained solutions. As an interesting aside, we derive the list of solutions to the continuum phi4 equation that fill the entire two-dimensional space of parameters obtained as the continuum limit of the corresponding space of the discrete models.

Evidence for morphological composition in compound words using MEG.

PubMed

Brooks, Teon L; Cid de Garcia, Daniela

2015-01-01

Psycholinguistic and electrophysiological studies of lexical processing show convergent evidence for morpheme-based lexical access for morphologically complex words that involves early decomposition into their constituent morphemes followed by some combinatorial operation. Considering that both semantically transparent (e.g., sailboat) and semantically opaque (e.g., bootleg) compounds undergo morphological decomposition during the earlier stages of lexical processing, subsequent combinatorial operations should account for the difference in the contribution of the constituent morphemes to the meaning of these different word types. In this study we use magnetoencephalography (MEG) to pinpoint the neural bases of this combinatorial stage in English compound word recognition. MEG data were acquired while participants performed a word naming task in which three word types, transparent compounds (e.g., roadside), opaque compounds (e.g., butterfly), and morphologically simple words (e.g., brothel) were contrasted in a partial-repetition priming paradigm where the word of interest was primed by one of its constituent morphemes. Analysis of onset latency revealed shorter latencies to name compound words than simplex words when primed, further supporting a stage of morphological decomposition in lexical access. An analysis of the associated MEG activity uncovered a region of interest implicated in morphological composition, the Left Anterior Temporal Lobe (LATL). Only transparent compounds showed increased activity in this area from 250 to 470 ms. Previous studies using sentences and phrases have highlighted the role of LATL in performing computations for basic combinatorial operations. Results are in tune with decomposition models for morpheme accessibility early in processing and suggest that semantics play a role in combining the meanings of morphemes when their composition is transparent to the overall word meaning.

A general gridding, discretization, and coarsening methodology for modeling flow in porous formations with discrete geological features

NASA Astrophysics Data System (ADS)

Karimi-Fard, M.; Durlofsky, L. J.

2016-10-01

A comprehensive framework for modeling flow in porous media containing thin, discrete features, which could be high-permeability fractures or low-permeability deformation bands, is presented. The key steps of the methodology are mesh generation, fine-grid discretization, upscaling, and coarse-grid discretization. Our specialized gridding technique combines a set of intersecting triangulated surfaces by constructing approximate intersections using existing edges. This procedure creates a conforming mesh of all surfaces, which defines the internal boundaries for the volumetric mesh. The flow equations are discretized on this conforming fine mesh using an optimized two-point flux finite-volume approximation. The resulting discrete model is represented by a list of control-volumes with associated positions and pore-volumes, and a list of cell-to-cell connections with associated transmissibilities. Coarse models are then constructed by the aggregation of fine-grid cells, and the transmissibilities between adjacent coarse cells are obtained using flow-based upscaling procedures. Through appropriate computation of fracture-matrix transmissibilities, a dual-continuum representation is obtained on the coarse scale in regions with connected fracture networks. The fine and coarse discrete models generated within the framework are compatible with any connectivity-based simulator. The applicability of the methodology is illustrated for several two- and three-dimensional examples. In particular, we consider gas production from naturally fractured low-permeability formations, and transport through complex fracture networks. In all cases, highly accurate solutions are obtained with significant model reduction.

Overland flow connectivity on planar patchy hillslopes - modified percolation theory approaches and combinatorial model of urns

NASA Astrophysics Data System (ADS)

Nezlobin, David; Pariente, Sarah; Lavee, Hanoch; Sachs, Eyal

2017-04-01

Source-sink systems are very common in hydrology; in particular, some land cover types often generate runoff (e.g. embedded rocks, bare soil) , while other obstruct it (e.g. vegetation, cracked soil). Surface runoff coefficients of patchy slopes/plots covered by runoff generating and obstructing covers (e.g., bare soil and vegetation) depend critically on the percentage cover (i.e. sources/sinks abundance) and decrease strongly with observation scale. The classic mathematical percolation theory provides a powerful apparatus for describing the runoff connectivity on patchy hillslopes, but it ignores strong effect of the overland flow directionality. To overcome this and other difficulties, modified percolation theory approaches can be considered, such as straight percolation (for the planar slopes), quasi-straight percolation and models with limited obstruction. These approaches may explain both the observed critical dependence of runoff coefficients on percentage cover and their scale decrease in systems with strong flow directionality (e.g. planar slopes). The contributing area increases sharply when the runoff generating percentage cover approaches the straight percolation threshold. This explains the strong increase of the surface runoff and erosion for relatively low values (normally less than 35%) of the obstructing cover (e.g., vegetation). Combinatorial models of urns with restricted occupancy can be applied for the analytic evaluation of meaningful straight percolation quantities, such as NOGA's (Non-Obstructed Generating Area) expected value and straight percolation probability. It is shown that the nature of the cover-related runoff scale decrease is combinatorial - the probability for the generated runoff to avoid obstruction in unit area decreases with scale for the non-trivial percentage cover values. The magnitude of the scale effect is found to be a skewed non-monotonous function of the percentage cover. It is shown that the cover-related scale effect becomes less prominent if the obstructing capacity decreases, as generally occurs during heavy rainfalls. The plot width have a moderate positive statistical effect on runoff and erosion coefficients, since wider patchy plots have, on average, a greater normalized contributing area and a higher probability to have runoff of a certain length. The effect of plot width depends by itself on the percentage cover, plot length, and compared width scales. The contributing area uncertainty brought about by cover spatial arrangement is examined, including its dependence on the percentage cover and scale. In general, modified percolation theory approaches and combinatorial models of urns with restricted occupancy may link between critical dependence of runoff on percentage cover, cover-related scale effect, and statistical uncertainty of the observed quantities.

Applying Multivariate Discrete Distributions to Genetically Informative Count Data.

PubMed

Kirkpatrick, Robert M; Neale, Michael C

2016-03-01

We present a novel method of conducting biometric analysis of twin data when the phenotypes are integer-valued counts, which often show an L-shaped distribution. Monte Carlo simulation is used to compare five likelihood-based approaches to modeling: our multivariate discrete method, when its distributional assumptions are correct, when they are incorrect, and three other methods in common use. With data simulated from a skewed discrete distribution, recovery of twin correlations and proportions of additive genetic and common environment variance was generally poor for the Normal, Lognormal and Ordinal models, but good for the two discrete models. Sex-separate applications to substance-use data from twins in the Minnesota Twin Family Study showed superior performance of two discrete models. The new methods are implemented using R and OpenMx and are freely available.

Evaluation of the Current Status of the Combinatorial Approach for the Study of Phase Diagrams

PubMed Central

Wong-Ng, W.

2012-01-01

This paper provides an evaluation of the effectiveness of using the high throughput combinatorial approach for preparing phase diagrams of thin film and bulk materials. Our evaluation is based primarily on examples of combinatorial phase diagrams that have been reported in the literature as well as based on our own laboratory experiments. Various factors that affect the construction of these phase diagrams are examined. Instrumentation and analytical approaches needed to improve data acquisition and data analysis are summarized. PMID:26900530

Research on thermal protection mechanism of forward-facing cavity and opposing jet combinatorial thermal protection system

NASA Astrophysics Data System (ADS)

Lu, Hai-Bo; Liu, Wei-Qiang

2014-04-01

Validated by the correlated experiments, a nose-tip with forward-facing cavity/opposing jet/the combinatorial configuration of forward-facing cavity and opposing jet thermal protection system (TPS) are investigated numerically. The physical mechanism of these TPS is discussed, and the cooling efficiency of them is compared. The combinatorial system is more suitable to be the TPS for the high speed vehicles which need fly under various flow conditions with long-range and long time.

Combinatorial approach to the representation of the Schur-Weyl duality in one-dimensional spin systems

NASA Astrophysics Data System (ADS)

Jakubczyk, Dorota; Jakubczyk, Paweł

2018-02-01

We propose combinatorial approach to the representation of Schur-Weyl duality in physical systems on the example of one-dimensional spin chains. Exploiting the Robinson-Schensted-Knuth algorithm, we perform decomposition of the dual group representations into irreducible representations in a fully combinatorial way. As representation space, we choose the Hilbert space of the spin chains, but this approach can be easily generalized to an arbitrary physical system where the Schur-Weyl duality works.

Massively multiplex single-cell Hi-C

PubMed Central

Ramani, Vijay; Deng, Xinxian; Qiu, Ruolan; Gunderson, Kevin L; Steemers, Frank J; Disteche, Christine M; Noble, William S; Duan, Zhijun; Shendure, Jay

2016-01-01

We present single-cell combinatorial indexed Hi-C (sciHi-C), which applies the concept of combinatorial cellular indexing to chromosome conformation capture. In this proof-of-concept, we generate and sequence six sciHi-C libraries comprising a total of 10,696 single cells. We use sciHi-C data to separate cells by karytoypic and cell-cycle state differences and identify cell-to-cell heterogeneity in mammalian chromosomal conformation. Our results demonstrate that combinatorial indexing is a generalizable strategy for single-cell genomics. PMID:28135255

Thermal modelling using discrete vasculature for thermal therapy: a review

PubMed Central

Kok, H.P.; Gellermann, J.; van den Berg, C.A.T.; Stauffer, P.R.; Hand, J.W.; Crezee, J.

2013-01-01

Reliable temperature information during clinical hyperthermia and thermal ablation is essential for adequate treatment control, but conventional temperature measurements do not provide 3D temperature information. Treatment planning is a very useful tool to improve treatment quality and substantial progress has been made over the last decade. Thermal modelling is a very important and challenging aspect of hyperthermia treatment planning. Various thermal models have been developed for this purpose, with varying complexity. Since blood perfusion is such an important factor in thermal redistribution of energy in in vivo tissue, thermal simulations are most accurately performed by modelling discrete vasculature. This review describes the progress in thermal modelling with discrete vasculature for the purpose of hyperthermia treatment planning and thermal ablation. There has been significant progress in thermal modelling with discrete vasculature. Recent developments have made real-time simulations possible, which can provide feedback during treatment for improved therapy. Future clinical application of thermal modelling with discrete vasculature in hyperthermia treatment planning is expected to further improve treatment quality. PMID:23738700

Combinatorial Interdependence in Lottery

ERIC Educational Resources Information Center

Helman, Danny

2005-01-01

This paper examines a real life question of gamble facing lottery players. Combinatorial dependence plays a central role in shaping the game probabilistic structure, but might not carry the merited weight in punters' considerations.

Ensemble-type numerical uncertainty information from single model integrations

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

Rauser, Florian, E-mail: florian.rauser@mpimet.mpg.de; Marotzke, Jochem; Korn, Peter

2015-07-01

We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of themore » influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.« less

Performance on perceptual word identification is mediated by discrete states.

PubMed

Swagman, April R; Province, Jordan M; Rouder, Jeffrey N

2015-02-01

We contrast predictions from discrete-state models of all-or-none information loss with signal-detection models of graded strength for the identification of briefly flashed English words. Previous assessments have focused on whether ROC curves are straight or not, which is a test of a discrete-state model where detection leads to the highest confidence response with certainty. We along with many others argue this certainty assumption is too constraining, and, consequently, the straight-line ROC test is too stringent. Instead, we assess a core property of discrete-state models, conditional independence, where the pattern of responses depends only on which state is entered. The conditional independence property implies that confidence ratings are a mixture of detect and guess state responses, and that stimulus strength factors, the duration of the flashed word in this report, affect only the probability of entering a state and not responses conditional on a state. To assess this mixture property, 50 participants saw words presented briefly on a computer screen at three variable flash durations followed by either a two-alternative confidence ratings task or a yes-no confidence ratings task. Comparable discrete-state and signal-detection models were fit to the data for each participant and task. The discrete-state models outperformed the signal detection models for 90 % of participants in the two-alternative task and for 68 % of participants in the yes-no task. We conclude discrete-state models are viable for predicting performance across stimulus conditions in a perceptual word identification task.

Identifiability of tree-child phylogenetic networks under a probabilistic recombination-mutation model of evolution.

PubMed

Francis, Andrew; Moulton, Vincent

2018-06-07

Phylogenetic networks are an extension of phylogenetic trees which are used to represent evolutionary histories in which reticulation events (such as recombination and hybridization) have occurred. A central question for such networks is that of identifiability, which essentially asks under what circumstances can we reliably identify the phylogenetic network that gave rise to the observed data? Recently, identifiability results have appeared for networks relative to a model of sequence evolution that generalizes the standard Markov models used for phylogenetic trees. However, these results are quite limited in terms of the complexity of the networks that are considered. In this paper, by introducing an alternative probabilistic model for evolution along a network that is based on some ground-breaking work by Thatte for pedigrees, we are able to obtain an identifiability result for a much larger class of phylogenetic networks (essentially the class of so-called tree-child networks). To prove our main theorem, we derive some new results for identifying tree-child networks combinatorially, and then adapt some techniques developed by Thatte for pedigrees to show that our combinatorial results imply identifiability in the probabilistic setting. We hope that the introduction of our new model for networks could lead to new approaches to reliably construct phylogenetic networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

RINGMesh: A programming library for developing mesh-based geomodeling applications

NASA Astrophysics Data System (ADS)

Pellerin, Jeanne; Botella, Arnaud; Bonneau, François; Mazuyer, Antoine; Chauvin, Benjamin; Lévy, Bruno; Caumon, Guillaume

2017-07-01

RINGMesh is a C++ open-source programming library for manipulating discretized geological models. It is designed to ease the development of applications and workflows that use discretized 3D models. It is neither a geomodeler, nor a meshing software. RINGMesh implements functionalities to read discretized surface-based or volumetric structural models and to check their validity. The models can be then exported in various file formats. RINGMesh provides data structures to represent geological structural models, either defined by their discretized boundary surfaces, and/or by discretized volumes. A programming interface allows to develop of new geomodeling methods, and to plug in external software. The goal of RINGMesh is to help researchers to focus on the implementation of their specific method rather than on tedious tasks common to many applications. The documented code is open-source and distributed under the modified BSD license. It is available at https://www.ring-team.org/index.php/software/ringmesh.

Additivity vs Synergism: Investigation of the Additive Interaction of Cinnamon Bark Oil and Meropenem in Combinatory Therapy.

PubMed

Yang, Shun-Kai; Yusoff, Khatijah; Mai, Chun-Wai; Lim, Wei-Meng; Yap, Wai-Sum; Lim, Swee-Hua Erin; Lai, Kok-Song

2017-11-04

Combinatory therapies have been commonly applied in the clinical setting to tackle multi-drug resistant bacterial infections and these have frequently proven to be effective. Specifically, combinatory therapies resulting in synergistic interactions between antibiotics and adjuvant have been the main focus due to their effectiveness, sidelining the effects of additivity, which also lowers the minimal effective dosage of either antimicrobial agent. Thus, this study was undertaken to look at the effects of additivity between essential oils and antibiotic, via the use of cinnamon bark essential oil (CBO) and meropenem as a model for additivity. Comparisons between synergistic and additive interaction of CBO were performed in terms of the ability of CBO to disrupt bacterial membrane, via zeta potential measurement, outer membrane permeability assay and scanning electron microscopy. It has been found that the additivity interaction between CBO and meropenem showed similar membrane disruption ability when compared to those synergistic combinations which was previously reported. Hence, results based on our studies strongly suggest that additive interaction acts on a par with synergistic interaction. Therefore, further investigation in additive interaction between antibiotics and adjuvant should be performed for a more in depth understanding of the mechanism and the impacts of such interaction.

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

Siol, Sebastian; Holder, Aaron; Ortiz, Brenden R.

Here, the controlled decomposition of metastable alloys is an attractive route to form nanostructured thermoelectric materials with reduced thermal conductivity. The ternary SnTe–MnTe and SnTe–SnSe heterostructural alloys have been demonstrated as promising materials for thermoelectric applications. In this work, the quaternary Sn 1–yMnyTe 1–xSe x phase space serves as a relevant model system to explore how a combination of computational and combinatorial-growth methods can be used to study equilibrium and non-equilibrium solubility limits. Results from first principle calculations indicate low equilibrium solubility for x,y < 0.05 that are in good agreement with results obtained from bulk equilibrium synthesis experiments andmore » predict significantly higher spinodal limits. An experimental screening using sputtered combinatorial thin film sample libraries showed a remarkable increase in non-equilibrium solubility for x,y > 0.2. These theoretical and experimental results were used to guide the bulk synthesis of metastable alloys. The ability to reproduce the non-equilibrium solubility levels in bulk materials indicates that such theoretical calculations and combinatorial growth can inform bulk synthetic routes. Further, the large difference between equilibrium and non-equilibrium solubility limits in Sn 1–yMn yTe 1–xSe x indicates these metastable alloys are attractive in terms of nano-precipitate formation for potential thermoelectric applications.« less

Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing

DTIC Science & Technology

2012-12-14

Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing Matei Zaharia Tathagata Das Haoyuan Li Timothy Hunter Scott Shenker Ion...SUBTITLE Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...time. However, current programming models for distributed stream processing are relatively low-level often leaving the user to worry about consistency of

Discrete stochastic analogs of Erlang epidemic models.

PubMed

Getz, Wayne M; Dougherty, Eric R

2018-12-01

Erlang differential equation models of epidemic processes provide more realistic disease-class transition dynamics from susceptible (S) to exposed (E) to infectious (I) and removed (R) categories than the ubiquitous SEIR model. The latter is itself is at one end of the spectrum of Erlang SE[Formula: see text]I[Formula: see text]R models with [Formula: see text] concatenated E compartments and [Formula: see text] concatenated I compartments. Discrete-time models, however, are computationally much simpler to simulate and fit to epidemic outbreak data than continuous-time differential equations, and are also much more readily extended to include demographic and other types of stochasticity. Here we formulate discrete-time deterministic analogs of the Erlang models, and their stochastic extension, based on a time-to-go distributional principle. Depending on which distributions are used (e.g. discretized Erlang, Gamma, Beta, or Uniform distributions), we demonstrate that our formulation represents both a discretization of Erlang epidemic models and generalizations thereof. We consider the challenges of fitting SE[Formula: see text]I[Formula: see text]R models and our discrete-time analog to data (the recent outbreak of Ebola in Liberia). We demonstrate that the latter performs much better than the former; although confining fits to strict SEIR formulations reduces the numerical challenges, but sacrifices best-fit likelihood scores by at least 7%.

A discrete geometric approach for simulating the dynamics of thin viscous threads

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

Audoly, B., E-mail: audoly@lmm.jussieu.fr; Clauvelin, N.; Brun, P.-T.

We present a numerical model for the dynamics of thin viscous threads based on a discrete, Lagrangian formulation of the smooth equations. The model makes use of a condensed set of coordinates, called the centerline/spin representation: the kinematic constraints linking the centerline's tangent to the orientation of the material frame is used to eliminate two out of three degrees of freedom associated with rotations. Based on a description of twist inspired from discrete differential geometry and from variational principles, we build a full-fledged discrete viscous thread model, which includes in particular a discrete representation of the internal viscous stress. Consistencymore » of the discrete model with the classical, smooth equations for thin threads is established formally. Our numerical method is validated against reference solutions for steady coiling. The method makes it possible to simulate the unsteady behavior of thin viscous threads in a robust and efficient way, including the combined effects of inertia, stretching, bending, twisting, large rotations and surface tension.« less

Performance evaluation of coherent Ising machines against classical neural networks

NASA Astrophysics Data System (ADS)

Haribara, Yoshitaka; Ishikawa, Hitoshi; Utsunomiya, Shoko; Aihara, Kazuyuki; Yamamoto, Yoshihisa

2017-12-01

The coherent Ising machine is expected to find a near-optimal solution in various combinatorial optimization problems, which has been experimentally confirmed with optical parametric oscillators and a field programmable gate array circuit. The similar mathematical models were proposed three decades ago by Hopfield et al in the context of classical neural networks. In this article, we compare the computational performance of both models.

Structural alignment of protein descriptors - a combinatorial model.

PubMed

Antczak, Maciej; Kasprzak, Marta; Lukasiak, Piotr; Blazewicz, Jacek

2016-09-17

Structural alignment of proteins is one of the most challenging problems in molecular biology. The tertiary structure of a protein strictly correlates with its function and computationally predicted structures are nowadays a main premise for understanding the latter. However, computationally derived 3D models often exhibit deviations from the native structure. A way to confirm a model is a comparison with other structures. The structural alignment of a pair of proteins can be defined with the use of a concept of protein descriptors. The protein descriptors are local substructures of protein molecules, which allow us to divide the original problem into a set of subproblems and, consequently, to propose a more efficient algorithmic solution. In the literature, one can find many applications of the descriptors concept that prove its usefulness for insight into protein 3D structures, but the proposed approaches are presented rather from the biological perspective than from the computational or algorithmic point of view. Efficient algorithms for identification and structural comparison of descriptors can become crucial components of methods for structural quality assessment as well as tertiary structure prediction. In this paper, we propose a new combinatorial model and new polynomial-time algorithms for the structural alignment of descriptors. The model is based on the maximum-size assignment problem, which we define here and prove that it can be solved in polynomial time. We demonstrate suitability of this approach by comparison with an exact backtracking algorithm. Besides a simplification coming from the combinatorial modeling, both on the conceptual and complexity level, we gain with this approach high quality of obtained results, in terms of 3D alignment accuracy and processing efficiency. All the proposed algorithms were developed and integrated in a computationally efficient tool descs-standalone, which allows the user to identify and structurally compare descriptors of biological molecules, such as proteins and RNAs. Both PDB (Protein Data Bank) and mmCIF (macromolecular Crystallographic Information File) formats are supported. The proposed tool is available as an open source project stored on GitHub ( https://github.com/mantczak/descs-standalone ).

A Systematic Study of Simple Combinatorial Configurations.

ERIC Educational Resources Information Center

Dubois, Jean-Guy

1984-01-01

A classification of the simple combinatorial configurations which correspond to various cases of distribution and ordering of objects into boxes is given (in French). Concrete descriptions, structured relations, translations, and formalizations are discussed. (MNS)

Combinatorial Mathematics: Research into Practice

ERIC Educational Resources Information Center

Sriraman, Bharath; English, Lyn D.

2004-01-01

Implications and suggestions for using combinatorial mathematics in the classroom through a survey and synthesis of numerous research studies are presented. The implications revolve around five major themes that emerge from analysis of these studies.

Associative Algorithms for Computational Creativity

ERIC Educational Resources Information Center

Varshney, Lav R.; Wang, Jun; Varshney, Kush R.

2016-01-01

Computational creativity, the generation of new, unimagined ideas or artifacts by a machine that are deemed creative by people, can be applied in the culinary domain to create novel and flavorful dishes. In fact, we have done so successfully using a combinatorial algorithm for recipe generation combined with statistical models for recipe ranking…

Selective oxidation of lignin model compounds – a combinatorial application of the laccase-mediator system

USDA-ARS?s Scientific Manuscript database

Identifying suitable reaction conditions remains an important task in the development of practical enzyme catalysts. Laccases play an important role in the biological break down of lignin and have great potential in the deconstruction of lignocellulosic feedstocks. We examined 16 laccases, both comm...

Generalized Success-Breeds-Success Principle Leading to Time-Dependent Informetric Distributions.

ERIC Educational Resources Information Center

Egghe, Leo; Rousseau, Ronald

1995-01-01

Reformulates the success-breeds-success (SBS) principle in informetrics in order to generate a general theory of source-item relationships. Topics include a time-dependent probability, a new model for the expected probability that is compared with the SBS principle with exact combinatorial calculations, classical frequency distributions, and…

On Praising Convergent Thinking: Creativity as Blind Variation and Selective Retention

ERIC Educational Resources Information Center

Simonton, Dean Keith

2015-01-01

Arthur Cropley (2006) emphasized the critical place that convergent thinking has in creativity. Although he briefly refers to the blind variation and selective retention (BVSR) theory of creativity, his discussion could not reflect the most recent theoretical and empirical developments in BVSR, especially the resulting combinatorial models.…

Enabling techniques in the search for new antibiotics: Combinatorial biosynthesis of sugar-containing antibiotics.

PubMed

Park, Je Won; Nam, Sang-Jip; Yoon, Yeo Joon

2017-06-15

Nature has a talent for inventing a vast number of natural products, including hybrids generated by blending different scaffolds, resulting in a myriad of bioactive chemical entities. Herein, we review the highlights and recent trends (2010-2016) in the combinatorial biosynthesis of sugar-containing antibiotics where nature's structural diversification capabilities are exploited to enable the creation of new anti-infective and anti-proliferative drugs. In this review, we describe the modern combinatorial biosynthetic approaches for polyketide synthase-derived complex and aromatic polyketides, non-ribosomal peptide synthetase-directed lipo-/glycopeptides, aminoglycosides, nucleoside antibiotics, and alkaloids, along with their therapeutic potential. Finally, we present the feasible nexus between combinatorial biosynthesis, systems biology, and synthetic biology as a toolbox to provide new antibiotics that will be indispensable in the post-antibiotic era. Copyright © 2016 Elsevier Inc. All rights reserved.

Combinatorial vector fields and the valley structure of fitness landscapes.

PubMed

Stadler, Bärbel M R; Stadler, Peter F

2010-12-01

Adaptive (downhill) walks are a computationally convenient way of analyzing the geometric structure of fitness landscapes. Their inherently stochastic nature has limited their mathematical analysis, however. Here we develop a framework that interprets adaptive walks as deterministic trajectories in combinatorial vector fields and in return associate these combinatorial vector fields with weights that measure their steepness across the landscape. We show that the combinatorial vector fields and their weights have a product structure that is governed by the neutrality of the landscape. This product structure makes practical computations feasible. The framework presented here also provides an alternative, and mathematically more convenient, way of defining notions of valleys, saddle points, and barriers in landscape. As an application, we propose a refined approximation for transition rates between macrostates that are associated with the valleys of the landscape.

Measuring and Specifying Combinatorial Coverage of Test Input Configurations

PubMed Central

Kuhn, D. Richard; Kacker, Raghu N.; Lei, Yu

2015-01-01

A key issue in testing is how many tests are needed for a required level of coverage or fault detection. Estimates are often based on error rates in initial testing, or on code coverage. For example, tests may be run until a desired level of statement or branch coverage is achieved. Combinatorial methods present an opportunity for a different approach to estimating required test set size, using characteristics of the test set. This paper describes methods for estimating the coverage of, and ability to detect, t-way interaction faults of a test set based on a covering array. We also develop a connection between (static) combinatorial coverage and (dynamic) code coverage, such that if a specific condition is satisfied, 100% branch coverage is assured. Using these results, we propose practical recommendations for using combinatorial coverage in specifying test requirements. PMID:28133442

Video modeling to train staff to implement discrete-trial instruction.

PubMed

Catania, Cynthia N; Almeida, Daniel; Liu-Constant, Brian; DiGennaro Reed, Florence D

2009-01-01

Three new direct-service staff participated in a program that used a video model to train target skills needed to conduct a discrete-trial session. Percentage accuracy in completing a discrete-trial teaching session was evaluated using a multiple baseline design across participants. During baseline, performances ranged from a mean of 12% to 63% accuracy. During video modeling, there was an immediate increase in accuracy to a mean of 98%, 85%, and 94% for each participant. Performance during maintenance and generalization probes remained at high levels. Results suggest that video modeling can be an effective technique to train staff to conduct discrete-trial sessions.

Combinatorial chemical bath deposition of CdS contacts for chalcogenide photovoltaics

DOE PAGES

Mokurala, Krishnaiah; Baranowski, Lauryn L.; de Souza Lucas, Francisco W.; ...

2016-08-01

Contact layers play an important role in thin film solar cells, but new material development and optimization of its thickness is usually a long and tedious process. A high-throughput experimental approach has been used to accelerate the rate of research in photovoltaic (PV) light absorbers and transparent conductive electrodes, however the combinatorial research on contact layers is less common. Here, we report on the chemical bath deposition (CBD) of CdS thin films by combinatorial dip coating technique and apply these contact layers to Cu(In,Ga)Se 2 (CIGSe) and Cu 2ZnSnSe 4 (CZTSe) light absorbers in PV devices. Combinatorial thickness steps ofmore » CdS thin films were achieved by removal of the substrate from the chemical bath, at regular intervals of time, and in equal distance increments. The trends in the photoconversion efficiency and in the spectral response of the PV devices as a function of thickness of CdS contacts were explained with the help of optical and morphological characterization of the CdS thin films. The maximum PV efficiency achieved for the combinatorial dip-coating CBD was similar to that for the PV devices processed using conventional CBD. Finally, the results of this study lead to the conclusion that combinatorial dip-coating can be used to accelerate the optimization of PV device performance of CdS and other candidate contact layers for a wide range of emerging absorbers.« less

Polynomial functors and combinatorial Dyson-Schwinger equations

NASA Astrophysics Data System (ADS)

Kock, Joachim

2017-04-01

We present a general abstract framework for combinatorial Dyson-Schwinger equations, in which combinatorial identities are lifted to explicit bijections of sets, and more generally equivalences of groupoids. Key features of combinatorial Dyson-Schwinger equations are revealed to follow from general categorical constructions and universal properties. Rather than beginning with an equation inside a given Hopf algebra and referring to given Hochschild 1-cocycles, our starting point is an abstract fixpoint equation in groupoids, shown canonically to generate all the algebraic structures. Precisely, for any finitary polynomial endofunctor P defined over groupoids, the system of combinatorial Dyson-Schwinger equations X = 1 + P(X) has a universal solution, namely the groupoid of P-trees. The isoclasses of P-trees generate naturally a Connes-Kreimer-like bialgebra, in which the abstract Dyson-Schwinger equation can be internalised in terms of canonical B+-operators. The solution to this equation is a series (the Green function), which always enjoys a Faà di Bruno formula, and hence generates a sub-bialgebra isomorphic to the Faà di Bruno bialgebra. Varying P yields different bialgebras, and cartesian natural transformations between various P yield bialgebra homomorphisms and sub-bialgebras, corresponding for example to truncation of Dyson-Schwinger equations. Finally, all constructions can be pushed inside the classical Connes-Kreimer Hopf algebra of trees by the operation of taking core of P-trees. A byproduct of the theory is an interpretation of combinatorial Green functions as inductive data types in the sense of Martin-Löf type theory (expounded elsewhere).

Discrete time rescaling theorem: determining goodness of fit for discrete time statistical models of neural spiking.

PubMed

Haslinger, Robert; Pipa, Gordon; Brown, Emery

2010-10-01

One approach for understanding the encoding of information by spike trains is to fit statistical models and then test their goodness of fit. The time-rescaling theorem provides a goodness-of-fit test consistent with the point process nature of spike trains. The interspike intervals (ISIs) are rescaled (as a function of the model's spike probability) to be independent and exponentially distributed if the model is accurate. A Kolmogorov-Smirnov (KS) test between the rescaled ISIs and the exponential distribution is then used to check goodness of fit. This rescaling relies on assumptions of continuously defined time and instantaneous events. However, spikes have finite width, and statistical models of spike trains almost always discretize time into bins. Here we demonstrate that finite temporal resolution of discrete time models prevents their rescaled ISIs from being exponentially distributed. Poor goodness of fit may be erroneously indicated even if the model is exactly correct. We present two adaptations of the time-rescaling theorem to discrete time models. In the first we propose that instead of assuming the rescaled times to be exponential, the reference distribution be estimated through direct simulation by the fitted model. In the second, we prove a discrete time version of the time-rescaling theorem that analytically corrects for the effects of finite resolution. This allows us to define a rescaled time that is exponentially distributed, even at arbitrary temporal discretizations. We demonstrate the efficacy of both techniques by fitting generalized linear models to both simulated spike trains and spike trains recorded experimentally in monkey V1 cortex. Both techniques give nearly identical results, reducing the false-positive rate of the KS test and greatly increasing the reliability of model evaluation based on the time-rescaling theorem.

Simulation of Hydraulic and Natural Fracture Interaction Using a Coupled DFN-DEM Model

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

Zhou, J.; Huang, H.; Deo, M.

2016-03-01

The presence of natural fractures will usually result in a complex fracture network due to the interactions between hydraulic and natural fracture. The reactivation of natural fractures can generally provide additional flow paths from formation to wellbore which play a crucial role in improving the hydrocarbon recovery in these ultra-low permeability reservoir. Thus, accurate description of the geometry of discrete fractures and bedding is highly desired for accurate flow and production predictions. Compared to conventional continuum models that implicitly represent the discrete feature, Discrete Fracture Network (DFN) models could realistically model the connectivity of discontinuities at both reservoir scale andmore » well scale. In this work, a new hybrid numerical model that couples Discrete Fracture Network (DFN) and Dual-Lattice Discrete Element Method (DL-DEM) is proposed to investigate the interaction between hydraulic fracture and natural fractures. Based on the proposed model, the effects of natural fracture orientation, density and injection properties on hydraulic-natural fractures interaction are investigated.« less

Simulation of Hydraulic and Natural Fracture Interaction Using a Coupled DFN-DEM Model

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

J. Zhou; H. Huang; M. Deo

The presence of natural fractures will usually result in a complex fracture network due to the interactions between hydraulic and natural fracture. The reactivation of natural fractures can generally provide additional flow paths from formation to wellbore which play a crucial role in improving the hydrocarbon recovery in these ultra-low permeability reservoir. Thus, accurate description of the geometry of discrete fractures and bedding is highly desired for accurate flow and production predictions. Compared to conventional continuum models that implicitly represent the discrete feature, Discrete Fracture Network (DFN) models could realistically model the connectivity of discontinuities at both reservoir scale andmore » well scale. In this work, a new hybrid numerical model that couples Discrete Fracture Network (DFN) and Dual-Lattice Discrete Element Method (DL-DEM) is proposed to investigate the interaction between hydraulic fracture and natural fractures. Based on the proposed model, the effects of natural fracture orientation, density and injection properties on hydraulic-natural fractures interaction are investigated.« less

Parameter redundancy in discrete state-space and integrated models.

PubMed

Cole, Diana J; McCrea, Rachel S

2016-09-01

Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multilayer shallow water models with locally variable number of layers and semi-implicit time discretization

NASA Astrophysics Data System (ADS)

Bonaventura, Luca; Fernández-Nieto, Enrique D.; Garres-Díaz, José; Narbona-Reina, Gladys

2018-07-01

We propose an extension of the discretization approaches for multilayer shallow water models, aimed at making them more flexible and efficient for realistic applications to coastal flows. A novel discretization approach is proposed, in which the number of vertical layers and their distribution are allowed to change in different regions of the computational domain. Furthermore, semi-implicit schemes are employed for the time discretization, leading to a significant efficiency improvement for subcritical regimes. We show that, in the typical regimes in which the application of multilayer shallow water models is justified, the resulting discretization does not introduce any major spurious feature and allows again to reduce substantially the computational cost in areas with complex bathymetry. As an example of the potential of the proposed technique, an application to a sediment transport problem is presented, showing a remarkable improvement with respect to standard discretization approaches.

A Bayesian hierarchical model for discrete choice data in health care.

PubMed

Antonio, Anna Liza M; Weiss, Robert E; Saigal, Christopher S; Dahan, Ely; Crespi, Catherine M

2017-01-01

In discrete choice experiments, patients are presented with sets of health states described by various attributes and asked to make choices from among them. Discrete choice experiments allow health care researchers to study the preferences of individual patients by eliciting trade-offs between different aspects of health-related quality of life. However, many discrete choice experiments yield data with incomplete ranking information and sparsity due to the limited number of choice sets presented to each patient, making it challenging to estimate patient preferences. Moreover, methods to identify outliers in discrete choice data are lacking. We develop a Bayesian hierarchical random effects rank-ordered multinomial logit model for discrete choice data. Missing ranks are accounted for by marginalizing over all possible permutations of unranked alternatives to estimate individual patient preferences, which are modeled as a function of patient covariates. We provide a Bayesian version of relative attribute importance, and adapt the use of the conditional predictive ordinate to identify outlying choice sets and outlying individuals with unusual preferences compared to the population. The model is applied to data from a study using a discrete choice experiment to estimate individual patient preferences for health states related to prostate cancer treatment.

CAMELOT: Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox

NASA Astrophysics Data System (ADS)

Di Carlo, Marilena; Romero Martin, Juan Manuel; Vasile, Massimiliano

2018-03-01

Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox (CAMELOT) is a toolbox for the fast preliminary design and optimisation of low-thrust trajectories. It solves highly complex combinatorial problems to plan multi-target missions characterised by long spirals including different perturbations. To do so, CAMELOT implements a novel multi-fidelity approach combining analytical surrogate modelling and accurate computational estimations of the mission cost. Decisions are then made using two optimisation engines included in the toolbox, a single-objective global optimiser, and a combinatorial optimisation algorithm. CAMELOT has been applied to a variety of case studies: from the design of interplanetary trajectories to the optimal de-orbiting of space debris and from the deployment of constellations to on-orbit servicing. In this paper, the main elements of CAMELOT are described and two examples, solved using the toolbox, are presented.

The Mathematics of a Successful Deconvolution: A Quantitative Assessment of Mixture-Based Combinatorial Libraries Screened Against Two Formylpeptide Receptors

PubMed Central

Santos, Radleigh G.; Appel, Jon R.; Giulianotti, Marc A.; Edwards, Bruce S.; Sklar, Larry A.; Houghten, Richard A.; Pinilla, Clemencia

2014-01-01

In the past 20 years, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds for drug discovery and basic research. Mixture-based libraries and positional scanning deconvolution combine two approaches for the rapid identification of specific scaffolds and active ligands. Here we present a quantitative assessment of the screening of 32 positional scanning libraries in the identification of highly specific and selective ligands for two formylpeptide receptors. We also compare and contrast two mixture-based library approaches using a mathematical model to facilitate the selection of active scaffolds and libraries to be pursued for further evaluation. The flexibility demonstrated in the differently formatted mixture-based libraries allows for their screening in a wide range of assays. PMID:23722730

Differential regulation of transcription through distinct Suppressor of Hairless DNA binding site architectures during Notch signaling in proneural clusters.

PubMed

Cave, John W; Xia, Li; Caudy, Michael

2011-01-01

In Drosophila melanogaster, achaete (ac) and m8 are model basic helix-loop-helix activator (bHLH A) and repressor genes, respectively, that have the opposite cell expression pattern in proneural clusters during Notch signaling. Previous studies have shown that activation of m8 transcription in specific cells within proneural clusters by Notch signaling is programmed by a "combinatorial" and "architectural" DNA transcription code containing binding sites for the Su(H) and proneural bHLH A proteins. Here we show the novel result that the ac promoter contains a similar combinatorial code of Su(H) and bHLH A binding sites but contains a different Su(H) site architectural code that does not mediate activation during Notch signaling, thus programming a cell expression pattern opposite that of m8 in proneural clusters.

Evaluation of the Navys Sea/Shore Flow Policy

DTIC Science & Technology

2016-06-01

CNA developed an independent Discrete -Event Simulation model to evaluate and assess the effect of alternative sea/shore flow policies. In this study...remains, even if the system is optimized. In building a Discrete -Event Simulation model, we discovered key factors that should be included in the... Discrete -Event Simulation model to evaluate the impact of sea/shore flow policy (the DES-SSF model) and compared the results with the SSFM for one

Direct Profiling the Post-Translational Modification Codes of a Single Protein Immobilized on a Surface Using Cu-free Click Chemistry.

PubMed

Kim, Kyung Lock; Park, Kyeng Min; Murray, James; Kim, Kimoon; Ryu, Sung Ho

2018-05-23

Combinatorial post-translational modifications (PTMs), which can serve as dynamic "molecular barcodes", have been proposed to regulate distinct protein functions. However, studies of combinatorial PTMs on single protein molecules have been hindered by a lack of suitable analytical methods. Here, we describe erasable single-molecule blotting (eSiMBlot) for combinatorial PTM profiling. This assay is performed in a highly multiplexed manner and leverages the benefits of covalent protein immobilization, cyclic probing with different antibodies, and single molecule fluorescence imaging. Especially, facile and efficient covalent immobilization on a surface using Cu-free click chemistry permits multiple rounds (>10) of antibody erasing/reprobing without loss of antigenicity. Moreover, cumulative detection of coregistered multiple data sets for immobilized single-epitope molecules, such as HA peptide, can be used to increase the antibody detection rate. Finally, eSiMBlot enables direct visualization and quantitative profiling of combinatorial PTM codes at the single-molecule level, as we demonstrate by revealing the novel phospho-codes of ligand-induced epidermal growth factor receptor. Thus, eSiMBlot provides an unprecedentedly simple, rapid, and versatile platform for analyzing the vast number of combinatorial PTMs in biological pathways.

Direct Profiling the Post-Translational Modification Codes of a Single Protein Immobilized on a Surface Using Cu-free Click Chemistry

PubMed Central

2018-01-01

Combinatorial post-translational modifications (PTMs), which can serve as dynamic “molecular barcodes”, have been proposed to regulate distinct protein functions. However, studies of combinatorial PTMs on single protein molecules have been hindered by a lack of suitable analytical methods. Here, we describe erasable single-molecule blotting (eSiMBlot) for combinatorial PTM profiling. This assay is performed in a highly multiplexed manner and leverages the benefits of covalent protein immobilization, cyclic probing with different antibodies, and single molecule fluorescence imaging. Especially, facile and efficient covalent immobilization on a surface using Cu-free click chemistry permits multiple rounds (>10) of antibody erasing/reprobing without loss of antigenicity. Moreover, cumulative detection of coregistered multiple data sets for immobilized single-epitope molecules, such as HA peptide, can be used to increase the antibody detection rate. Finally, eSiMBlot enables direct visualization and quantitative profiling of combinatorial PTM codes at the single-molecule level, as we demonstrate by revealing the novel phospho-codes of ligand-induced epidermal growth factor receptor. Thus, eSiMBlot provides an unprecedentedly simple, rapid, and versatile platform for analyzing the vast number of combinatorial PTMs in biological pathways.

Lexicographic goal programming and assessment tools for a combinatorial production problem.

DOT National Transportation Integrated Search

2008-01-01

NP-complete combinatorial problems often necessitate the use of near-optimal solution techniques including : heuristics and metaheuristics. The addition of multiple optimization criteria can further complicate : comparison of these solution technique...

Leveraging Modeling Approaches: Reaction Networks and Rules

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatio-temporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks – the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks. PMID:22161349

Leveraging modeling approaches: reaction networks and rules.

PubMed

Blinov, Michael L; Moraru, Ion I

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high-resolution and/or high-throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks - the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.

Current Density and Continuity in Discretized Models

ERIC Educational Resources Information Center

Boykin, Timothy B.; Luisier, Mathieu; Klimeck, Gerhard

2010-01-01

Discrete approaches have long been used in numerical modelling of physical systems in both research and teaching. Discrete versions of the Schrodinger equation employing either one or several basis functions per mesh point are often used by senior undergraduates and beginning graduate students in computational physics projects. In studying…

Discrete Time Rescaling Theorem: Determining Goodness of Fit for Discrete Time Statistical Models of Neural Spiking

PubMed Central

Haslinger, Robert; Pipa, Gordon; Brown, Emery

2010-01-01

One approach for understanding the encoding of information by spike trains is to fit statistical models and then test their goodness of fit. The time rescaling theorem provides a goodness of fit test consistent with the point process nature of spike trains. The interspike intervals (ISIs) are rescaled (as a function of the model’s spike probability) to be independent and exponentially distributed if the model is accurate. A Kolmogorov Smirnov (KS) test between the rescaled ISIs and the exponential distribution is then used to check goodness of fit. This rescaling relies upon assumptions of continuously defined time and instantaneous events. However spikes have finite width and statistical models of spike trains almost always discretize time into bins. Here we demonstrate that finite temporal resolution of discrete time models prevents their rescaled ISIs from being exponentially distributed. Poor goodness of fit may be erroneously indicated even if the model is exactly correct. We present two adaptations of the time rescaling theorem to discrete time models. In the first we propose that instead of assuming the rescaled times to be exponential, the reference distribution be estimated through direct simulation by the fitted model. In the second, we prove a discrete time version of the time rescaling theorem which analytically corrects for the effects of finite resolution. This allows us to define a rescaled time which is exponentially distributed, even at arbitrary temporal discretizations. We demonstrate the efficacy of both techniques by fitting Generalized Linear Models (GLMs) to both simulated spike trains and spike trains recorded experimentally in monkey V1 cortex. Both techniques give nearly identical results, reducing the false positive rate of the KS test and greatly increasing the reliability of model evaluation based upon the time rescaling theorem. PMID:20608868

Enhancement of the Logistics Battle Command Model: Architecture Upgrades and Attrition Module Development

DTIC Science & Technology

2017-01-05

module. 15. SUBJECT TERMS Logistics, attrition, discrete event simulation, Simkit, LBC 16. SECURITY CLASSIFICATION OF: Unclassified 17. LIMITATION...stochastics, and discrete event model programmed in Java building largely on the Simkit library. The primary purpose of the LBC model is to support...equations makes them incompatible with the discrete event construct of LBC. Bullard further advances this methodology by developing a stochastic

Quantum Walks on the Line with Phase Parameters

NASA Astrophysics Data System (ADS)

Villagra, Marcos; Nakanishi, Masaki; Yamashita, Shigeru; Nakashima, Yasuhiko

In this paper, a study on discrete-time coined quantum walks on the line is presented. Clear mathematical foundations are still lacking for this quantum walk model. As a step toward this objective, the following question is being addressed: Given a graph, what is the probability that a quantum walk arrives at a given vertex after some number of steps? This is a very natural question, and for random walks it can be answered by several different combinatorial arguments. For quantum walks this is a highly non-trivial task. Furthermore, this was only achieved before for one specific coin operator (Hadamard operator) for walks on the line. Even considering only walks on lines, generalizing these computations to a general SU(2) coin operator is a complex task. The main contribution is a closed-form formula for the amplitudes of the state of the walk (which includes the question above) for a general symmetric SU(2) operator for walks on the line. To this end, a coin operator with parameters that alters the phase of the state of the walk is defined. Then, closed-form solutions are computed by means of Fourier analysis and asymptotic approximation methods. We also present some basic properties of the walk which can be deducted using weak convergence theorems for quantum walks. In particular, the support of the induced probability distribution of the walk is calculated. Then, it is shown how changing the parameters in the coin operator affects the resulting probability distribution.

Stochastic Kuramoto oscillators with discrete phase states.

PubMed

Jörg, David J

2017-09-01

We present a generalization of the Kuramoto phase oscillator model in which phases advance in discrete phase increments through Poisson processes, rendering both intrinsic oscillations and coupling inherently stochastic. We study the effects of phase discretization on the synchronization and precision properties of the coupled system both analytically and numerically. Remarkably, many key observables such as the steady-state synchrony and the quality of oscillations show distinct extrema while converging to the classical Kuramoto model in the limit of a continuous phase. The phase-discretized model provides a general framework for coupled oscillations in a Markov chain setting.

Stochastic Kuramoto oscillators with discrete phase states

NASA Astrophysics Data System (ADS)

Jörg, David J.

2017-09-01

We present a generalization of the Kuramoto phase oscillator model in which phases advance in discrete phase increments through Poisson processes, rendering both intrinsic oscillations and coupling inherently stochastic. We study the effects of phase discretization on the synchronization and precision properties of the coupled system both analytically and numerically. Remarkably, many key observables such as the steady-state synchrony and the quality of oscillations show distinct extrema while converging to the classical Kuramoto model in the limit of a continuous phase. The phase-discretized model provides a general framework for coupled oscillations in a Markov chain setting.

Boundaries, kinetic properties, and final domain structure of plane discrete uniform Poisson-Voronoi tessellations with von Neumann neighborhoods.

PubMed

Korobov, A

2009-03-01

Discrete random tessellations appear not infrequently in describing nucleation and growth transformations. Generally, several non-Euclidean metrics are possible in this case. Previously [A. Korobov, Phys. Rev. B 76, 085430 (2007)] continual analogs of such tessellations have been studied. Here one of the simplest discrete varieties of the Kolmogorov-Johnson-Mehl-Avrami model, namely, the model with von Neumann neighborhoods, has been examined per se, i.e., without continualization. The tessellation is uniform in the sense that domain boundaries consist of tiles. Similarities and distinctions between discrete and continual models are discussed.

"Anticlumping" and Other Combinatorial Effects on Clumped Isotopes: Implications for Tracing Biogeochemical Cycling

NASA Astrophysics Data System (ADS)

Yeung, L.

2015-12-01

I present a mode of isotopic ordering that has purely combinatorial origins. It can be important when identical rare isotopes are paired by coincidence (e.g., they are neighbors on the same molecule), or when extrinsic factors govern the isotopic composition of the two atoms that share a chemical bond. By itself, combinatorial isotope pairing yields products with isotopes either randomly distributed or with a deficit relative to a random distribution of isotopes. These systematics arise because of an unconventional coupling between the formation of singly- and multiply-substituted isotopic moieties. In a random distribution, rare isotopes are symmetrically distributed: Single isotopic substitutions (e.g., H‒D and D‒H in H2) occur with equal probability, and double isotopic substitutions (e.g., D2) occur according to random chance. The absence of symmetry in a bond-making complex can yield unequal numbers of singly-substituted molecules (e.g., more H‒D than D‒H in H2), which is recorded in the product molecule as a deficit in doubly-substituted moieties and an "anticlumped" isotope distribution (i.e., Δn < 0). Enzymatic isotope pairing reactions, which can have site-specific isotopic fractionation factors and atom reservoirs, should express this class of combinatorial isotope effect. Chemical-kinetic isotope effects, which are related to the bond-forming transition state, arise independently and express second-order combinatorial effects. In general, both combinatorial and chemical factors are important for calculating and interpreting clumped-isotope signatures of individual reactions. In many reactions relevant to geochemical oxygen, carbon, and nitrogen cycling, combinatorial isotope pairing likely plays a strong role in the clumped isotope distribution of the products. These isotopic signatures, manifest as either directly bound isotope clumps or as features of a molecule's isotopic anatomy, could be exploited as tracers of biogeochemistry that can relate molecular mechanisms to signals observable at environmentally relevant spatial scales.

Inferring the Why in Images

DTIC Science & Technology

2014-01-01

model. We combinatorially replaced tokens with words from our vocabulary to score the relationships be- tween concepts. The second-order queries (not...is the action, y3 is an object, and y4 is the scene. Language Potentials: We captialize on state-of-the-art natural language models to score the rela...model estimated on billions of web-pages [4, 10] to form each L(·). Scoring Function: Given the image x, we score a possible labeling configuration y of

Balancing focused combinatorial libraries based on multiple GPCR ligands

NASA Astrophysics Data System (ADS)

Soltanshahi, Farhad; Mansley, Tamsin E.; Choi, Sun; Clark, Robert D.

2006-08-01

G-Protein coupled receptors (GPCRs) are important targets for drug discovery, and combinatorial chemistry is an important tool for pharmaceutical development. The absence of detailed structural information, however, limits the kinds of combinatorial design techniques that can be applied to GPCR targets. This is particularly problematic given the current emphasis on focused combinatorial libraries. By linking an incremental construction method (OptDesign) to the very fast shape-matching capability of ChemSpace, we have created an efficient method for designing targeted sublibraries that are topomerically similar to known actives. Multi-objective scoring allows consideration of multiple queries (actives) simultaneously. This can lead to a distribution of products skewed towards one particular query structure, however, particularly when the ligands of interest are quite dissimilar to one another. A novel pivoting technique is described which makes it possible to generate promising designs even under those circumstances. The approach is illustrated by application to some serotonergic agonists and chemokine antagonists.

Optimized Reaction Conditions for Amide Bond Formation in DNA-Encoded Combinatorial Libraries.

PubMed

Li, Yizhou; Gabriele, Elena; Samain, Florent; Favalli, Nicholas; Sladojevich, Filippo; Scheuermann, Jörg; Neri, Dario

2016-08-08

DNA-encoded combinatorial libraries are increasingly being used as tools for the discovery of small organic binding molecules to proteins of biological or pharmaceutical interest. In the majority of cases, synthetic procedures for the formation of DNA-encoded combinatorial libraries incorporate at least one step of amide bond formation between amino-modified DNA and a carboxylic acid. We investigated reaction conditions and established a methodology by using 1-ethyl-3-(3-(dimethylamino)propyl)carbodiimide, 1-hydroxy-7-azabenzotriazole and N,N'-diisopropylethylamine (EDC/HOAt/DIPEA) in combination, which provided conversions greater than 75% for 423/543 (78%) of the carboxylic acids tested. These reaction conditions were efficient with a variety of primary and secondary amines, as well as with various types of amino-modified oligonucleotides. The reaction conditions, which also worked efficiently over a broad range of DNA concentrations and reaction scales, should facilitate the synthesis of novel DNA-encoded combinatorial libraries.

Combinatorial games with a pass: a dynamical systems approach.

PubMed

Morrison, Rebecca E; Friedman, Eric J; Landsberg, Adam S

2011-12-01

By treating combinatorial games as dynamical systems, we are able to address a longstanding open question in combinatorial game theory, namely, how the introduction of a "pass" move into a game affects its behavior. We consider two well known combinatorial games, 3-pile Nim and 3-row Chomp. In the case of Nim, we observe that the introduction of the pass dramatically alters the game's underlying structure, rendering it considerably more complex, while for Chomp, the pass move is found to have relatively minimal impact. We show how these results can be understood by recasting these games as dynamical systems describable by dynamical recursion relations. From these recursion relations, we are able to identify underlying structural connections between these "games with passes" and a recently introduced class of "generic (perturbed) games." This connection, together with a (non-rigorous) numerical stability analysis, allows one to understand and predict the effect of a pass on a game.

Mixture-based combinatorial libraries from small individual peptide libraries: a case study on α1-antitrypsin deficiency.

PubMed

Chang, Yi-Pin; Chu, Yen-Ho

2014-05-16

The design, synthesis and screening of diversity-oriented peptide libraries using a "libraries from libraries" strategy for the development of inhibitors of α1-antitrypsin deficiency are described. The major buttress of the biochemical approach presented here is the use of well-established solid-phase split-and-mix method for the generation of mixture-based libraries. The combinatorial technique iterative deconvolution was employed for library screening. While molecular diversity is the general consideration of combinatorial libraries, exquisite design through systematic screening of small individual libraries is a prerequisite for effective library screening and can avoid potential problems in some cases. This review will also illustrate how large peptide libraries were designed, as well as how a conformation-sensitive assay was developed based on the mechanism of the conformational disease. Finally, the combinatorially selected peptide inhibitor capable of blocking abnormal protein aggregation will be characterized by biophysical, cellular and computational methods.

Mind the Gap: A Semicontinuum Model for Discrete Electrical Propagation in Cardiac Tissue.

PubMed

Costa, Caroline Mendonca; Silva, Pedro Andre Arroyo; dos Santos, Rodrigo Weber

2016-04-01

Electrical propagation in cardiac tissue is a discrete or discontinuous phenomenon that reflects the complexity of the anatomical structures and their organization in the heart, such as myocytes, gap junctions, microvessels, and extracellular matrix, just to name a few. Discrete models or microscopic and discontinuous models are, so far, the best options to accurately study how structural properties of cardiac tissue influence electrical propagation. These models are, however, inappropriate in the context of large scale simulations, which have been traditionally performed by the use of continuum and macroscopic models, such as the monodomain and the bidomain models. However, continuum models may fail to reproduce many important physiological and physiopathological aspects of cardiac electrophysiology, for instance, those related to slow conduction. In this study, we develop a new mathematical model that combines characteristics of both continuum and discrete models. The new model was evaluated in scenarios of low gap-junctional coupling, where slow conduction is observed, and was able to reproduce conduction block, increase of the maximum upstroke velocity and of the repolarization dispersion. None of these features can be captured by continuum models. In addition, the model overcomes a great disadvantage of discrete models, as it allows variation of the spatial resolution within a certain range.

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.

Family of columns isospectral to gravity-loaded columns with tip force: A discrete approach

NASA Astrophysics Data System (ADS)

Ramachandran, Nirmal; Ganguli, Ranjan

2018-06-01

A discrete model is introduced to analyze transverse vibration of straight, clamped-free (CF) columns of variable cross-sectional geometry under the influence of gravity and a constant axial force at the tip. The discrete model is used to determine critical combinations of loading parameters - a gravity parameter and a tip force parameter - that cause onset of dynamic instability in the CF column. A methodology, based on matrix-factorization, is described to transform the discrete model into a family of models corresponding to weightless and unloaded clamped-free (WUCF) columns, each with a transverse vibration spectrum isospectral to the original model. Characteristics of models in this isospectral family are dependent on three transformation parameters. A procedure is discussed to convert the isospectral discrete model description into geometric description of realistic columns i.e. from the discrete model, we construct isospectral WUCF columns with rectangular cross-sections varying in width and depth. As part of numerical studies to demonstrate efficacy of techniques presented, frequency parameters of a uniform column and three types of tapered CF columns under different combinations of loading parameters are obtained from the discrete model. Critical combinations of these parameters for a typical tapered column are derived. These results match with published results. Example CF columns, under arbitrarily-chosen combinations of loading parameters are considered and for each combination, isospectral WUCF columns are constructed. Role of transformation parameters in determining characteristics of isospectral columns is discussed and optimum values are deduced. Natural frequencies of these WUCF columns computed using Finite Element Method (FEM) match well with those of the given gravity-loaded CF column with tip force, hence confirming isospectrality.

Integrable Semi-discrete Kundu-Eckhaus Equation: Darboux Transformation, Breather, Rogue Wave and Continuous Limit Theory

NASA Astrophysics Data System (ADS)

Zhao, Hai-qiong; Yuan, Jinyun; Zhu, Zuo-nong

2018-02-01

To get more insight into the relation between discrete model and continuous counterpart, a new integrable semi-discrete Kundu-Eckhaus equation is derived from the reduction in an extended Ablowitz-Ladik hierarchy. The integrability of the semi-discrete model is confirmed by showing the existence of Lax pair and infinite number of conservation laws. The dynamic characteristics of the breather and rational solutions have been analyzed in detail for our semi-discrete Kundu-Eckhaus equation to reveal some new interesting phenomena which was not found in continuous one. It is shown that the theory of the discrete system including Lax pair, Darboux transformation and explicit solutions systematically yields their continuous counterparts in the continuous limit.

Aspects of job scheduling

NASA Technical Reports Server (NTRS)

Phillips, K.

1976-01-01

A mathematical model for job scheduling in a specified context is presented. The model uses both linear programming and combinatorial methods. While designed with a view toward optimization of scheduling of facility and plant operations at the Deep Space Communications Complex, the context is sufficiently general to be widely applicable. The general scheduling problem including options for scheduling objectives is discussed and fundamental parameters identified. Mathematical algorithms for partitioning problems germane to scheduling are presented.

Analyzing neuronal networks using discrete-time dynamics

NASA Astrophysics Data System (ADS)

Ahn, Sungwoo; Smith, Brian H.; Borisyuk, Alla; Terman, David

2010-05-01

We develop mathematical techniques for analyzing detailed Hodgkin-Huxley like models for excitatory-inhibitory neuronal networks. Our strategy for studying a given network is to first reduce it to a discrete-time dynamical system. The discrete model is considerably easier to analyze, both mathematically and computationally, and parameters in the discrete model correspond directly to parameters in the original system of differential equations. While these networks arise in many important applications, a primary focus of this paper is to better understand mechanisms that underlie temporally dynamic responses in early processing of olfactory sensory information. The models presented here exhibit several properties that have been described for olfactory codes in an insect’s Antennal Lobe. These include transient patterns of synchronization and decorrelation of sensory inputs. By reducing the model to a discrete system, we are able to systematically study how properties of the dynamics, including the complex structure of the transients and attractors, depend on factors related to connectivity and the intrinsic and synaptic properties of cells within the network.

A Stochastic Dynamic Programming Model With Fuzzy Storage States Applied to Reservoir Operation Optimization

NASA Astrophysics Data System (ADS)

Mousavi, Seyed Jamshid; Mahdizadeh, Kourosh; Afshar, Abbas

2004-08-01

Application of stochastic dynamic programming (SDP) models to reservoir optimization calls for state variables discretization. As an important variable discretization of reservoir storage volume has a pronounced effect on the computational efforts. The error caused by storage volume discretization is examined by considering it as a fuzzy state variable. In this approach, the point-to-point transitions between storage volumes at the beginning and end of each period are replaced by transitions between storage intervals. This is achieved by using fuzzy arithmetic operations with fuzzy numbers. In this approach, instead of aggregating single-valued crisp numbers, the membership functions of fuzzy numbers are combined. Running a simulated model with optimal release policies derived from fuzzy and non-fuzzy SDP models shows that a fuzzy SDP with a coarse discretization scheme performs as well as a classical SDP having much finer discretized space. It is believed that this advantage in the fuzzy SDP model is due to the smooth transitions between storage intervals which benefit from soft boundaries.

Application of network methods for understanding evolutionary dynamics in discrete habitats.

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory

PubMed Central

Pratte, Michael S.; Park, Young Eun; Rademaker, Rosanne L.; Tong, Frank

2016-01-01

If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced “oblique effect”, with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit. PMID:28004957

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory.

PubMed

Pratte, Michael S; Park, Young Eun; Rademaker, Rosanne L; Tong, Frank

2017-01-01

If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced "oblique effect," with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Transport of calcium ions through a bulk membrane by use of a dynamic combinatorial library.

PubMed

Saggiomo, Vittorio; Lüning, Ulrich

2009-07-07

In a bulk membrane transport experiment, a dynamic combinatorial library (DCL) has been used to transport calcium ions; the calcium ions amplify the formation of a macrocyclic carrier which results in transport.

Counting Pizza Pieces and Other Combinatorial Problems.

ERIC Educational Resources Information Center

Maier, Eugene

1988-01-01

The general combinatorial problem of counting the number of regions into which the interior of a circle is divided by a family of lines is considered. A general formula is developed and its use is illustrated in two situations. (PK)

On the existence of binary simplex codes. [using combinatorial construction

NASA Technical Reports Server (NTRS)

Taylor, H.

1977-01-01

Using a simple combinatorial construction, the existence of a binary simplex code with m codewords for all m is greater than or equal to 1 is proved. The problem of the shortest possible length is left open.

Application of combinatorial biocatalysis for a unique ring expansion of dihydroxymethylzearalenone

USDA-ARS?s Scientific Manuscript database

Combinatorial biocatalysis was applied to generate a diverse set of dihydroxymethylzearalenone derivatives with modified ring structure. In one chemoenzymatic reaction sequence, dihydroxymethylzearalenone was first subjected to a unique enzyme-catalyzed oxidative ring opening reaction that creates ...

Fostering Recursive Thinking in Combinatorics through the Use of Manipulatives and Computing Technology.

ERIC Educational Resources Information Center

Abramovich, Sergei; Pieper, Anne

1996-01-01

Describes the use of manipulatives for solving simple combinatorial problems which can lead to the discovery of recurrence relations for permutations and combinations. Numerical evidence and visual imagery generated by a computer spreadsheet through modeling these relations can enable students to experience the ease and power of combinatorial…

Thinking about Evolution: Combinatorial Play as a Strategy for Exercising Scientific Creativity

ERIC Educational Resources Information Center

Wingate, Richard J. T.

2011-01-01

An enduring focus in education on how scientists formulate experiments and "do science" in the laboratory has excluded a vital element of scientific practice: the creative and imaginative thinking that generates models and testable hypotheses. In this case study, final-year biomedical sciences university students were invited to create and justify…

Combined small-molecule inhibition accelerates the derivation of functional, early-born, cortical neurons from human pluripotent stem cells

PubMed Central

Qi, Yuchen; Zhang, Xin-Jun; Renier, Nicolas; Wu, Zhuhao; Atkin, Talia; Sun, Ziyi; Ozair, M. Zeeshan; Tchieu, Jason; Zimmer, Bastian; Fattahi, Faranak; Ganat, Yosif; Azevedo, Ricardo; Zeltner, Nadja; Brivanlou, Ali H.; Karayiorgou, Maria; Gogos, Joseph; Tomishima, Mark; Tessier-Lavigne, Marc; Shi, Song-Hai; Studer, Lorenz

2017-01-01

Considerable progress has been made in converting human pluripotent stem cells (hPSCs) into functional neurons. However, the protracted timing of human neuron specification and functional maturation remains a key challenge that hampers the routine application of hPSC-derived lineages in disease modeling and regenerative medicine. Using a combinatorial small-molecule screen, we previously identified conditions for the rapid differentiation of hPSCs into peripheral sensory neurons. Here we generalize the approach to central nervous system (CNS) fates by developing a small-molecule approach for accelerated induction of early-born cortical neurons. Combinatorial application of 6 pathway inhibitors induces post-mitotic cortical neurons with functional electrophysiological properties by day 16 of differentiation, in the absence of glial cell co-culture. The resulting neurons, transplanted at 8 days of differentiation into the postnatal mouse cortex, are functional and establish long-distance projections, as shown using iDISCO whole brain imaging. Accelerated differentiation into cortical neuron fates should facilitate hPSC-based strategies for disease modeling and cell therapy in CNS disorders. PMID:28112759

An improved switching converter model using discrete and average techniques

NASA Technical Reports Server (NTRS)

Shortt, D. J.; Lee, F. C.

1982-01-01

The nonlinear modeling and analysis of dc-dc converters has been done by averaging and discrete-sampling techniques. The averaging technique is simple, but inaccurate as the modulation frequencies approach the theoretical limit of one-half the switching frequency. The discrete technique is accurate even at high frequencies, but is very complex and cumbersome. An improved model is developed by combining the aforementioned techniques. This new model is easy to implement in circuit and state variable forms and is accurate to the theoretical limit.

Modeling discrete and rhythmic movements through motor primitives: a review.

PubMed

Degallier, Sarah; Ijspeert, Auke

2010-10-01

Rhythmic and discrete movements are frequently considered separately in motor control, probably because different techniques are commonly used to study and model them. Yet the increasing interest in finding a comprehensive model for movement generation requires bridging the different perspectives arising from the study of those two types of movements. In this article, we consider discrete and rhythmic movements within the framework of motor primitives, i.e., of modular generation of movements. In this way we hope to gain an insight into the functional relationships between discrete and rhythmic movements and thus into a suitable representation for both of them. Within this framework we can define four possible categories of modeling for discrete and rhythmic movements depending on the required command signals and on the spinal processes involved in the generation of the movements. These categories are first discussed in terms of biological concepts such as force fields and central pattern generators and then illustrated by several mathematical models based on dynamical system theory. A discussion on the plausibility of theses models concludes the work.

Discrete-time model reduction in limited frequency ranges

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Juang, Jer-Nan; Longman, Richard W.

1991-01-01

A mathematical formulation for model reduction of discrete time systems such that the reduced order model represents the system in a particular frequency range is discussed. The algorithm transforms the full order system into balanced coordinates using frequency weighted discrete controllability and observability grammians. In this form a criterion is derived to guide truncation of states based on their contribution to the frequency range of interest. Minimization of the criterion is accomplished without need for numerical optimization. Balancing requires the computation of discrete frequency weighted grammians. Close form solutions for the computation of frequency weighted grammians are developed. Numerical examples are discussed to demonstrate the algorithm.

Discrete factor approximations in simultaneous equation models: estimating the impact of a dummy endogenous variable on a continuous outcome.

PubMed

Mroz, T A

1999-10-01

This paper contains a Monte Carlo evaluation of estimators used to control for endogeneity of dummy explanatory variables in continuous outcome regression models. When the true model has bivariate normal disturbances, estimators using discrete factor approximations compare favorably to efficient estimators in terms of precision and bias; these approximation estimators dominate all the other estimators examined when the disturbances are non-normal. The experiments also indicate that one should liberally add points of support to the discrete factor distribution. The paper concludes with an application of the discrete factor approximation to the estimation of the impact of marriage on wages.

Fractional discrete-time consensus models for single- and double-summator dynamics

NASA Astrophysics Data System (ADS)

Wyrwas, Małgorzata; Mozyrska, Dorota; Girejko, Ewa

2018-04-01

The leader-following consensus problem of fractional-order multi-agent discrete-time systems is considered. In the systems, interactions between opinions are defined like in Krause and Cucker-Smale models but the memory is included by taking the fractional-order discrete-time operator on the left-hand side of the nonlinear systems. In this paper, we investigate fractional-order models of opinions for the single- and double-summator dynamics of discrete-time by analytical methods as well as by computer simulations. The necessary and sufficient conditions for the leader-following consensus are formulated by proposing a consensus control law for tracking the virtual leader.

An advanced environment for hybrid modeling of biological systems based on modelica.

PubMed

Pross, Sabrina; Bachmann, Bernhard

2011-01-20

Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. Hybrid Petri Nets, consisting of time-discrete Petri Net elements as well as continuous ones, have proven to be ideal for this task. Therefore, a new Petri Net library was implemented based on the object-oriented modeling language Modelica which allows the modeling of discrete, stochastic and continuous Petri Net elements by differential, algebraic and discrete equations. An appropriate Modelica-tool performs the hybrid simulation with discrete events and the solution of continuous differential equations. A special sub-library contains so-called wrappers for specific reactions to simplify the modeling process. The Modelica-models can be connected to Simulink-models for parameter optimization, sensitivity analysis and stochastic simulation in Matlab. The present paper illustrates the implementation of the Petri Net component models, their usage within the modeling process and the coupling between the Modelica-tool Dymola and Matlab/Simulink. The application is demonstrated by modeling the metabolism of Chinese Hamster Ovary Cells.

Criticism of EFSA's scientific opinion on combinatorial effects of 'stacked' GM plants.

PubMed

Bøhn, Thomas

2018-01-01

Recent genetically modified plants tend to include both insect resistance and herbicide tolerance traits. Some of these 'stacked' GM plants have multiple Cry-toxins expressed as well as tolerance to several herbicides. This means that non-target organisms in the environment (biodiversity) will be co-exposed to multiple stressors simultaneously. A similar co-exposure may happen to consumers through chemical residues in the food chain. EFSA, the responsible unit for minimizing risk of harm in European food chains, has expressed its scientific interest in combinatorial effects. However, when new data showed how two Cry-toxins acted in combination (added toxicity), and that the same Cry-toxins showed combinatorial effects when co-exposed with Roundup (Bøhn et al., 2016), EFSA dismissed these new peer-reviewed results. In effect, EFSA claimed that combinatorial effects are not relevant for itself. EFSA was justifying this by referring to a policy question, and by making invalid assumptions, which could have been checked directly with the lead-author. With such approach, EFSA may miss the opportunity to improve its environmental and health risk assessment of toxins and pesticides in the food chain. Failure to follow its own published requests for combinatorial effects research, may also risk jeopardizing EFSA's scientific and public reputation. Copyright © 2017. Published by Elsevier Ltd.

Border and surface tracing--theoretical foundations.

PubMed

Brimkov, Valentin E; Klette, Reinhard

2008-04-01

In this paper we define and study digital manifolds of arbitrary dimension, and provide (in particular)a general theoretical basis for curve or surface tracing in picture analysis. The studies involve properties such as one-dimensionality of digital curves and (n-1)-dimensionality of digital hypersurfaces that makes them discrete analogs of corresponding notions in continuous topology. The presented approach is fully based on the concept of adjacency relation and complements the concept of dimension as common in combinatorial topology. This work appears to be the first one on digital manifolds based ona graph-theoretical definition of dimension. In particular, in the n-dimensional digital space, a digital curve is a one-dimensional object and a digital hypersurface is an (n-1)-dimensional object, as it is in the case of curves and hypersurfaces in the Euclidean space. Relying on the obtained properties of digital hypersurfaces, we propose a uniform approach for studying good pairs defined by separations and obtain a classification of good pairs in arbitrary dimension. We also discuss possible applications of the presented definitions and results.

Approximate labeling via graph cuts based on linear programming.

PubMed

Komodakis, Nikos; Tziritas, Georgios

2007-08-01

A new framework is presented for both understanding and developing graph-cut-based combinatorial algorithms suitable for the approximate optimization of a very wide class of Markov Random Fields (MRFs) that are frequently encountered in computer vision. The proposed framework utilizes tools from the duality theory of linear programming in order to provide an alternative and more general view of state-of-the-art techniques like the \\alpha-expansion algorithm, which is included merely as a special case. Moreover, contrary to \\alpha-expansion, the derived algorithms generate solutions with guaranteed optimality properties for a much wider class of problems, for example, even for MRFs with nonmetric potentials. In addition, they are capable of providing per-instance suboptimality bounds in all occasions, including discrete MRFs with an arbitrary potential function. These bounds prove to be very tight in practice (that is, very close to 1), which means that the resulting solutions are almost optimal. Our algorithms' effectiveness is demonstrated by presenting experimental results on a variety of low-level vision tasks, such as stereo matching, image restoration, image completion, and optical flow estimation, as well as on synthetic problems.

Impact of the rail-pad multi-discrete model upon the prediction of the rail response

NASA Astrophysics Data System (ADS)

Mazilu, T.; Leu, M.

2017-08-01

Wheel/rail vibration has many technical effects such as wear of the rolling surfaces, rolling noise, settlement of the ballast and subgrade etc. This vibration is depending on the rail pad characteristic and subsequently, it is important to have an accurate overview on the relation between the rail pad characteristic and the level of the wheel/rail vibration. To this end, much theoretical and experimental research has been developed in the past, and for the theoretical approach the track model, in general, and, particularly, the rail pad model is of crucial importance. Usually, the rail pad model is discrete model one, neglecting the length of the rail pad. This fact is questionable because the sleepers span is only 4 times the rail pad length. Using the rail pad discrete model, the rail response is overestimated when the frequency of the excitation equals the pinned-pinned resonance frequency. In this paper, a multi-discrete model for the rail pad, consisting in many Kelvin-Voigt parallel systems, is inserted into an analytical model of the track. The track model is reduced to a rail taken as infinite Timoshenko beam, discretely supported via rail pad, sleeper and ballast. The influence of the number of Kelvin-Voigt systems of the rail pad model on the rail response is analysed.

Improving Our Ability to Evaluate Underlying Mechanisms of Behavioral Onset and Other Event Occurrence Outcomes: A Discrete-Time Survival Mediation Model

PubMed Central

Fairchild, Amanda J.; Abara, Winston E.; Gottschall, Amanda C.; Tein, Jenn-Yun; Prinz, Ronald J.

2015-01-01

The purpose of this article is to introduce and describe a statistical model that researchers can use to evaluate underlying mechanisms of behavioral onset and other event occurrence outcomes. Specifically, the article develops a framework for estimating mediation effects with outcomes measured in discrete-time epochs by integrating the statistical mediation model with discrete-time survival analysis. The methodology has the potential to help strengthen health research by targeting prevention and intervention work more effectively as well as by improving our understanding of discretized periods of risk. The model is applied to an existing longitudinal data set to demonstrate its use, and programming code is provided to facilitate its implementation. PMID:24296470

A novel method for multifactorial bio-chemical experiments design based on combinational design theory.

PubMed

Wang, Xun; Sun, Beibei; Liu, Boyang; Fu, Yaping; Zheng, Pan

2017-01-01

Experimental design focuses on describing or explaining the multifactorial interactions that are hypothesized to reflect the variation. The design introduces conditions that may directly affect the variation, where particular conditions are purposely selected for observation. Combinatorial design theory deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of balance and/or symmetry. In this work, borrowing the concept of "balance" in combinatorial design theory, a novel method for multifactorial bio-chemical experiments design is proposed, where balanced templates in combinational design are used to select the conditions for observation. Balanced experimental data that covers all the influencing factors of experiments can be obtianed for further processing, such as training set for machine learning models. Finally, a software based on the proposed method is developed for designing experiments with covering influencing factors a certain number of times.

Lossless compression of VLSI layout image data.

PubMed

Dai, Vito; Zakhor, Avideh

2006-09-01

We present a novel lossless compression algorithm called Context Copy Combinatorial Code (C4), which integrates the advantages of two very disparate compression techniques: context-based modeling and Lempel-Ziv (LZ) style copying. While the algorithm can be applied to many lossless compression applications, such as document image compression, our primary target application has been lossless compression of integrated circuit layout image data. These images contain a heterogeneous mix of data: dense repetitive data better suited to LZ-style coding, and less dense structured data, better suited to context-based encoding. As part of C4, we have developed a novel binary entropy coding technique called combinatorial coding which is simultaneously as efficient as arithmetic coding, and as fast as Huffman coding. Compression results show C4 outperforms JBIG, ZIP, BZIP2, and two-dimensional LZ, and achieves lossless compression ratios greater than 22 for binary layout image data, and greater than 14 for gray-pixel image data.

A combinatorial framework to quantify peak/pit asymmetries in complex dynamics.

PubMed

Hasson, Uri; Iacovacci, Jacopo; Davis, Ben; Flanagan, Ryan; Tagliazucchi, Enzo; Laufs, Helmut; Lacasa, Lucas

2018-02-23

We explore a combinatorial framework which efficiently quantifies the asymmetries between minima and maxima in local fluctuations of time series. We first showcase its performance by applying it to a battery of synthetic cases. We find rigorous results on some canonical dynamical models (stochastic processes with and without correlations, chaotic processes) complemented by extensive numerical simulations for a range of processes which indicate that the methodology correctly distinguishes different complex dynamics and outperforms state of the art metrics in several cases. Subsequently, we apply this methodology to real-world problems emerging across several disciplines including cases in neurobiology, finance and climate science. We conclude that differences between the statistics of local maxima and local minima in time series are highly informative of the complex underlying dynamics and a graph-theoretic extraction procedure allows to use these features for statistical learning purposes.

Scaffold diversification enhances effectiveness of a superlibrary of hyperthermophilic proteins.

PubMed

Hussain, Mahmud; Gera, Nimish; Hill, Andrew B; Rao, Balaji M

2013-01-18

The use of binding proteins from non-immunoglobulin scaffolds has become increasingly common in biotechnology and medicine. Typically, binders are isolated from a combinatorial library generated by mutating a single scaffold protein. In contrast, here we generated a "superlibrary" or "library-of-libraries" of 4 × 10(8) protein variants by mutagenesis of seven different hyperthermophilic proteins; six of the seven proteins have not been used as scaffolds prior to this study. Binding proteins for five different model targets were successfully isolated from this library. Binders obtained were derived from five out of the seven scaffolds. Strikingly, binders from this modestly sized superlibrary have affinities comparable or higher than those obtained from a library with 1000-fold higher sequence diversity but derived from a single stable scaffold. Thus scaffold diversification, i.e., randomization of multiple different scaffolds, is a powerful alternate strategy for combinatorial library construction.

Accurate multiple sequence-structure alignment of RNA sequences using combinatorial optimization.

PubMed

Bauer, Markus; Klau, Gunnar W; Reinert, Knut

2007-07-27

The discovery of functional non-coding RNA sequences has led to an increasing interest in algorithms related to RNA analysis. Traditional sequence alignment algorithms, however, fail at computing reliable alignments of low-homology RNA sequences. The spatial conformation of RNA sequences largely determines their function, and therefore RNA alignment algorithms have to take structural information into account. We present a graph-based representation for sequence-structure alignments, which we model as an integer linear program (ILP). We sketch how we compute an optimal or near-optimal solution to the ILP using methods from combinatorial optimization, and present results on a recently published benchmark set for RNA alignments. The implementation of our algorithm yields better alignments in terms of two published scores than the other programs that we tested: This is especially the case with an increasing number of input sequences. Our program LARA is freely available for academic purposes from http://www.planet-lisa.net.

Combinatorial Methodology for Screening Selectivity in Polymeric Pervaporation Membranes.

PubMed

Godbole, Rutvik V; Ma, Lan; Doerfert, Michael D; Williams, Porsche; Hedden, Ronald C

2015-11-09

Combinatorial methodology is described for rapid screening of selectivity in polymeric pervaporation membrane materials for alcohol-water separations. The screening technique is demonstrated for ethanol-water separation using a model polyacrylate system. The materials studied are cross-linked random copolymers of a hydrophobic comonomer (n-butyl acrylate, B) and a hydrophilic comonomer (2-hydroxyethyl acrylate, H). A matrix of materials is prepared that has orthogonal variations in two key variables, H:B ratio and cross-linker concentration. For mixtures of ethanol and water, equilibrium selectivities and distribution coefficients are obtained by combining swelling measurements with high-throughput HPLC analysis. Based on the screening results, two copolymers are selected for further study as pervaporation membranes to quantify permeability selectivity and the flux of ethanol. The screening methodology described has good potential to accelerate the search for new membrane materials, as it is adaptable to a broad range of polymer chemistries.

Encoding Schemes For A Digital Optical Multiplier Using The Modified Signed-Digit Number Representation

NASA Astrophysics Data System (ADS)

Lasher, Mark E.; Henderson, Thomas B.; Drake, Barry L.; Bocker, Richard P.

1986-09-01

The modified signed-digit (MSD) number representation offers full parallel, carry-free addition. A MSD adder has been described by the authors. This paper describes how the adder can be used in a tree structure to implement an optical multiply algorithm. Three different optical schemes, involving position, polarization, and intensity encoding, are proposed for realizing the trinary logic system. When configured in the generic multiplier architecture, these schemes yield the combinatorial logic necessary to carry out the multiplication algorithm. The optical systems are essentially three dimensional arrangements composed of modular units. Of course, this modularity is important for design considerations, while the parallelism and noninterfering communication channels of optical systems are important from the standpoint of reduced complexity. The authors have also designed electronic hardware to demonstrate and model the combinatorial logic required to carry out the algorithm. The electronic and proposed optical systems will be compared in terms of complexity and speed.

Graphene Microcapsule Arrays for Combinatorial Electron Microscopy and Spectroscopy in Liquids

DOE PAGES

Yulaev, Alexander; Guo, Hongxuan; Strelcov, Evgheni; ...

2017-04-27

Atomic-scale thickness, molecular impermeability, low atomic number, and mechanical strength make graphene an ideal electron-transparent membrane for material characterization in liquids and gases with scanning electron microscopy and spectroscopy. Here in this paper, we present a novel sample platform made of an array of thousands of identical isolated graphene-capped microchannels with high aspect ratio. A combination of a global wide field of view with high resolution local imaging of the array allows for high throughput in situ studies as well as for combinatorial screening of solutions, liquid interfaces, and immersed samples. We demonstrate the capabilities of this platform by studyingmore » a pure water sample in comparison with alkali halide solutions, a model electrochemical plating process, and beam-induced crystal growth in liquid electrolyte. Spectroscopic characterization of liquid interfaces and immersed objects with Auger and X-ray fluorescence analysis through the graphene membrane are also demonstrated.« less

Automated phase mapping with AgileFD and its application to light absorber discovery in the V–Mn–Nb oxide system

DOE PAGES

Suram, Santosh K.; Xue, Yexiang; Bai, Junwen; ...

2016-11-21

Rapid construction of phase diagrams is a central tenet of combinatorial materials science with accelerated materials discovery efforts often hampered by challenges in interpreting combinatorial X-ray diffraction data sets, which we address by developing AgileFD, an artificial intelligence algorithm that enables rapid phase mapping from a combinatorial library of X-ray diffraction patterns. AgileFD models alloying-based peak shifting through a novel expansion of convolutional nonnegative matrix factorization, which not only improves the identification of constituent phases but also maps their concentration and lattice parameter as a function of composition. By incorporating Gibbs’ phase rule into the algorithm, physically meaningful phase mapsmore » are obtained with unsupervised operation, and more refined solutions are attained by injecting expert knowledge of the system. The algorithm is demonstrated through investigation of the V–Mn–Nb oxide system where decomposition of eight oxide phases, including two with substantial alloying, provides the first phase map for this pseudoternary system. This phase map enables interpretation of high-throughput band gap data, leading to the discovery of new solar light absorbers and the alloying-based tuning of the direct-allowed band gap energy of MnV 2O 6. Lastly, the open-source family of AgileFD algorithms can be implemented into a broad range of high throughput workflows to accelerate materials discovery.« less

Automated phase mapping with AgileFD and its application to light absorber discovery in the V–Mn–Nb oxide system

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

Suram, Santosh K.; Xue, Yexiang; Bai, Junwen

Rapid construction of phase diagrams is a central tenet of combinatorial materials science with accelerated materials discovery efforts often hampered by challenges in interpreting combinatorial X-ray diffraction data sets, which we address by developing AgileFD, an artificial intelligence algorithm that enables rapid phase mapping from a combinatorial library of X-ray diffraction patterns. AgileFD models alloying-based peak shifting through a novel expansion of convolutional nonnegative matrix factorization, which not only improves the identification of constituent phases but also maps their concentration and lattice parameter as a function of composition. By incorporating Gibbs’ phase rule into the algorithm, physically meaningful phase mapsmore » are obtained with unsupervised operation, and more refined solutions are attained by injecting expert knowledge of the system. The algorithm is demonstrated through investigation of the V–Mn–Nb oxide system where decomposition of eight oxide phases, including two with substantial alloying, provides the first phase map for this pseudoternary system. This phase map enables interpretation of high-throughput band gap data, leading to the discovery of new solar light absorbers and the alloying-based tuning of the direct-allowed band gap energy of MnV 2O 6. Lastly, the open-source family of AgileFD algorithms can be implemented into a broad range of high throughput workflows to accelerate materials discovery.« less

HnRNP L and L-like cooperate in multiple-exon regulation of CD45 alternative splicing

PubMed Central

Preußner, Marco; Schreiner, Silke; Hung, Lee-Hsueh; Porstner, Martina; Jäck, Hans-Martin; Benes, Vladimir; Rätsch, Gunnar; Bindereif, Albrecht

2012-01-01

CD45 encodes a trans-membrane protein-tyrosine phosphatase expressed in diverse cells of the immune system. By combinatorial use of three variable exons 4–6, isoforms are generated that differ in their extracellular domain, thereby modulating phosphatase activity and immune response. Alternative splicing of these CD45 exons involves two heterogeneous ribonucleoproteins, hnRNP L and its cell-type specific paralog hnRNP L-like (LL). To address the complex combinatorial splicing of exons 4–6, we investigated hnRNP L/LL protein expression in human B-cells in relation to CD45 splicing patterns, applying RNA-Seq. In addition, mutational and RNA-binding analyses were carried out in HeLa cells. We conclude that hnRNP LL functions as the major CD45 splicing repressor, with two CA elements in exon 6 as its primary target. In exon 4, one element is targeted by both hnRNP L and LL. In contrast, exon 5 was never repressed on its own and only co-regulated with exons 4 and 6. Stable L/LL interaction requires CD45 RNA, specifically exons 4 and 6. We propose a novel model of combinatorial alternative splicing: HnRNP L and LL cooperate on the CD45 pre-mRNA, bridging exons 4 and 6 and looping out exon 5, thereby achieving full repression of the three variable exons. PMID:22402488

Chimeric Rhinoviruses Displaying MPER Epitopes Elicit Anti-HIV Neutralizing Responses

PubMed Central

Yi, Guohua; Lapelosa, Mauro; Bradley, Rachel; Mariano, Thomas M.; Dietz, Denise Elsasser; Hughes, Scott; Wrin, Terri; Petropoulos, Chris; Gallicchio, Emilio; Levy, Ronald M.; Arnold, Eddy; Arnold, Gail Ferstandig

2013-01-01

Background The development of an effective AIDS vaccine has been a formidable task, but remains a critical necessity. The well conserved membrane-proximal external region (MPER) of the HIV-1 gp41 glycoprotein is one of the crucial targets for AIDS vaccine development, as it has the necessary attribute of being able to elicit antibodies capable of neutralizing diverse isolates of HIV. Methodology/Principle Findings Guided by X-ray crystallography, molecular modeling, combinatorial chemistry, and powerful selection techniques, we designed and produced six combinatorial libraries of chimeric human rhinoviruses (HRV) displaying the MPER epitopes corresponding to mAbs 2F5, 4E10, and/or Z13e1, connected to an immunogenic surface loop of HRV via linkers of varying lengths and sequences. Not all libraries led to viable chimeric viruses with the desired sequences, but the combinatorial approach allowed us to examine large numbers of MPER-displaying chimeras. Among the chimeras were five that elicited antibodies capable of significantly neutralizing HIV-1 pseudoviruses from at least three subtypes, in one case leading to neutralization of 10 pseudoviruses from all six subtypes tested. Conclusions Optimization of these chimeras or closely related chimeras could conceivably lead to useful components of an effective AIDS vaccine. While the MPER of HIV may not be immunodominant in natural infection by HIV-1, its presence in a vaccine cocktail could provide critical breadth of protection. PMID:24039745

Neural fate decisions mediated by combinatorial regulation of Hes1 and miR-9.

PubMed

Li, Shanshan; Liu, Yanwei; Liu, Zengrong; Wang, Ruiqi

2016-01-01

In the nervous system, Hes1 shows an oscillatory manner in neural progenitors but a persistent one in neurons. Many models involving Hes1 have been provided for the study of neural differentiation but few of them take the role of microRNA into account. It is known that a microRNA, miR-9, plays crucial roles in modulating Hes1 oscillations. However, the roles of miR-9 in controlling Hes1 oscillations and inducing transition between different cell fates still need to be further explored. Here we provide a mathematical model to show the interaction between miR-9 and Hes1, with the aim of understanding how the Hes1 oscillations are produced, how they are controlled, and further, how they are terminated. Based on the experimental findings, the model demonstrates the essential roles of Hes1 and miR-9 in regulating the dynamics of the system. In particular, the model suggests that the balance between miR-9 and Hes1 plays important roles in the choice between progenitor maintenance and neural differentiation. In addition, the synergistic (or antagonistic) effects of several important regulations are investigated so as to elucidate the effects of combinatorial regulation in neural decision-making. Our model provides a qualitative mechanism for understanding the process in neural fate decisions regulated by Hes1 and miR-9.

Novel fragment-based QSAR modeling and combinatorial design of pyrazole-derived CRK3 inhibitors as potent antileishmanials.

PubMed

Goyal, Sukriti; Dhanjal, Jaspreet K; Tyagi, Chetna; Goyal, Manisha; Grover, Abhinav

2014-07-01

The CRK3 cyclin-dependent kinase of Leishmania plays an important role in regulating the cell-cycle progression at the G2/M phase checkpoint transition, proliferation, and viability inside the host macrophage. In this study, a novel fragment-based QSAR model has been developed using 22 pyrazole-derived compounds exhibiting inhibitory activity against Leishmanial CRK3. Unlike other QSAR methods, this fragment-based method gives flexibility to study the relationship between molecular fragments of interest and their contribution for the variation in the biological response by evaluating cross-term fragment descriptors. Based on the fragment-based QSAR model, a combinatorial library was generated, and top two compounds were reported after predicting their activity. The QSAR model showed satisfactory statistical parameters for the data set (r(2) = 0.8752, q(2) = 0.6690, F-ratio = 30.37, and pred_r(2) = 0.8632) with four descriptors describing the nature of substituent groups and the environment of the substitution site. Evaluation of the model implied that electron-rich substitution at R1 position improves the inhibitory activity, while decline in inhibitory activity was observed in presence of nitrogen at R2 position. The analysis carried out in this study provides a substantial basis for consideration of the designed pyrazole-based leads as potent antileishmanial drugs. © 2014 John Wiley & Sons A/S.

Fuzzy logic of Aristotelian forms

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

Perlovsky, L.I.

1996-12-31

Model-based approaches to pattern recognition and machine vision have been proposed to overcome the exorbitant training requirements of earlier computational paradigms. However, uncertainties in data were found to lead to a combinatorial explosion of the computational complexity. This issue is related here to the roles of a priori knowledge vs. adaptive learning. What is the a-priori knowledge representation that supports learning? I introduce Modeling Field Theory (MFT), a model-based neural network whose adaptive learning is based on a priori models. These models combine deterministic, fuzzy, and statistical aspects to account for a priori knowledge, its fuzzy nature, and data uncertainties.more » In the process of learning, a priori fuzzy concepts converge to crisp or probabilistic concepts. The MFT is a convergent dynamical system of only linear computational complexity. Fuzzy logic turns out to be essential for reducing the combinatorial complexity to linear one. I will discuss the relationship of the new computational paradigm to two theories due to Aristotle: theory of Forms and logic. While theory of Forms argued that the mind cannot be based on ready-made a priori concepts, Aristotelian logic operated with just such concepts. I discuss an interpretation of MFT suggesting that its fuzzy logic, combining a-priority and adaptivity, implements Aristotelian theory of Forms (theory of mind). Thus, 2300 years after Aristotle, a logic is developed suitable for his theory of mind.« less

Discrete-Slots Models of Visual Working-Memory Response Times

PubMed Central

Donkin, Christopher; Nosofsky, Robert M.; Gold, Jason M.; Shiffrin, Richard M.

2014-01-01

Much recent research has aimed to establish whether visual working memory (WM) is better characterized by a limited number of discrete all-or-none slots or by a continuous sharing of memory resources. To date, however, researchers have not considered the response-time (RT) predictions of discrete-slots versus shared-resources models. To complement the past research in this field, we formalize a family of mixed-state, discrete-slots models for explaining choice and RTs in tasks of visual WM change detection. In the tasks under investigation, a small set of visual items is presented, followed by a test item in 1 of the studied positions for which a change judgment must be made. According to the models, if the studied item in that position is retained in 1 of the discrete slots, then a memory-based evidence-accumulation process determines the choice and the RT; if the studied item in that position is missing, then a guessing-based accumulation process operates. Observed RT distributions are therefore theorized to arise as probabilistic mixtures of the memory-based and guessing distributions. We formalize an analogous set of continuous shared-resources models. The model classes are tested on individual subjects with both qualitative contrasts and quantitative fits to RT-distribution data. The discrete-slots models provide much better qualitative and quantitative accounts of the RT and choice data than do the shared-resources models, although there is some evidence for “slots plus resources” when memory set size is very small. PMID:24015956

Estimation of rates-across-sites distributions in phylogenetic substitution models.

PubMed

Susko, Edward; Field, Chris; Blouin, Christian; Roger, Andrew J

2003-10-01

Previous work has shown that it is often essential to account for the variation in rates at different sites in phylogenetic models in order to avoid phylogenetic artifacts such as long branch attraction. In most current models, the gamma distribution is used for the rates-across-sites distributions and is implemented as an equal-probability discrete gamma. In this article, we introduce discrete distribution estimates with large numbers of equally spaced rate categories allowing us to investigate the appropriateness of the gamma model. With large numbers of rate categories, these discrete estimates are flexible enough to approximate the shape of almost any distribution. Likelihood ratio statistical tests and a nonparametric bootstrap confidence-bound estimation procedure based on the discrete estimates are presented that can be used to test the fit of a parametric family. We applied the methodology to several different protein data sets, and found that although the gamma model often provides a good parametric model for this type of data, rate estimates from an equal-probability discrete gamma model with a small number of categories will tend to underestimate the largest rates. In cases when the gamma model assumption is in doubt, rate estimates coming from the discrete rate distribution estimate with a large number of rate categories provide a robust alternative to gamma estimates. An alternative implementation of the gamma distribution is proposed that, for equal numbers of rate categories, is computationally more efficient during optimization than the standard gamma implementation and can provide more accurate estimates of site rates.

Reproducing the nonlinear dynamic behavior of a structured beam with a generalized continuum model

NASA Astrophysics Data System (ADS)

Vila, J.; Fernández-Sáez, J.; Zaera, R.

2018-04-01

In this paper we study the coupled axial-transverse nonlinear vibrations of a kind of one dimensional structured solids by application of the so called Inertia Gradient Nonlinear continuum model. To show the accuracy of this axiomatic model, previously proposed by the authors, its predictions are compared with numeric results from a previously defined finite discrete chain of lumped masses and springs, for several number of particles. A continualization of the discrete model equations based on Taylor series allowed us to set equivalent values of the mechanical properties in both discrete and axiomatic continuum models. Contrary to the classical continuum model, the inertia gradient nonlinear continuum model used herein is able to capture scale effects, which arise for modes in which the wavelength is comparable to the characteristic distance of the structured solid. The main conclusion of the work is that the proposed generalized continuum model captures the scale effects in both linear and nonlinear regimes, reproducing the behavior of the 1D nonlinear discrete model adequately.

Modelling heat transfer during flow through a random packed bed of spheres

NASA Astrophysics Data System (ADS)

Burström, Per E. C.; Frishfelds, Vilnis; Ljung, Anna-Lena; Lundström, T. Staffan; Marjavaara, B. Daniel

2018-04-01

Heat transfer in a random packed bed of monosized iron ore pellets is modelled with both a discrete three-dimensional system of spheres and a continuous Computational Fluid Dynamics (CFD) model. Results show a good agreement between the two models for average values over a cross section of the bed for an even temperature profiles at the inlet. The advantage with the discrete model is that it captures local effects such as decreased heat transfer in sections with low speed. The disadvantage is that it is computationally heavy for larger systems of pellets. If averaged values are sufficient, the CFD model is an attractive alternative that is easy to couple to the physics up- and downstream the packed bed. The good agreement between the discrete and continuous model furthermore indicates that the discrete model may be used also on non-Stokian flow in the transitional region between laminar and turbulent flow, as turbulent effects show little influence of the overall heat transfer rates in the continuous model.

Affixation in semantic space: Modeling morpheme meanings with compositional distributional semantics.

PubMed

Marelli, Marco; Baroni, Marco

2015-07-01

The present work proposes a computational model of morpheme combination at the meaning level. The model moves from the tenets of distributional semantics, and assumes that word meanings can be effectively represented by vectors recording their co-occurrence with other words in a large text corpus. Given this assumption, affixes are modeled as functions (matrices) mapping stems onto derived forms. Derived-form meanings can be thought of as the result of a combinatorial procedure that transforms the stem vector on the basis of the affix matrix (e.g., the meaning of nameless is obtained by multiplying the vector of name with the matrix of -less). We show that this architecture accounts for the remarkable human capacity of generating new words that denote novel meanings, correctly predicting semantic intuitions about novel derived forms. Moreover, the proposed compositional approach, once paired with a whole-word route, provides a new interpretative framework for semantic transparency, which is here partially explained in terms of ease of the combinatorial procedure and strength of the transformation brought about by the affix. Model-based predictions are in line with the modulation of semantic transparency on explicit intuitions about existing words, response times in lexical decision, and morphological priming. In conclusion, we introduce a computational model to account for morpheme combination at the meaning level. The model is data-driven, theoretically sound, and empirically supported, and it makes predictions that open new research avenues in the domain of semantic processing. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Running Clubs--A Combinatorial Investigation.

ERIC Educational Resources Information Center

Nissen, Phillip; Taylor, John

1991-01-01

Presented is a combinatorial problem based on the Hash House Harriers rule which states that the route of the run should not have previously been traversed by the club. Discovered is how many weeks the club can meet before the rule has to be broken. (KR)

Quantum Resonance Approach to Combinatorial Optimization

NASA Technical Reports Server (NTRS)

Zak, Michail

1997-01-01

It is shown that quantum resonance can be used for combinatorial optimization. The advantage of the approach is in independence of the computing time upon the dimensionality of the problem. As an example, the solution to a constraint satisfaction problem of exponential complexity is demonstrated.

An Embedded 3D Fracture Modeling Approach for Simulating Fracture-Dominated Fluid Flow and Heat Transfer in Geothermal Reservoirs

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

Johnston, Henry; Wang, Cong; Winterfeld, Philip

An efficient modeling approach is described for incorporating arbitrary 3D, discrete fractures, such as hydraulic fractures or faults, into modeling fracture-dominated fluid flow and heat transfer in fractured geothermal reservoirs. This technique allows 3D discrete fractures to be discretized independently from surrounding rock volume and inserted explicitly into a primary fracture/matrix grid, generated without including 3D discrete fractures in prior. An effective computational algorithm is developed to discretize these 3D discrete fractures and construct local connections between 3D fractures and fracture/matrix grid blocks of representing the surrounding rock volume. The constructed gridding information on 3D fractures is then added tomore » the primary grid. This embedded fracture modeling approach can be directly implemented into a developed geothermal reservoir simulator via the integral finite difference (IFD) method or with TOUGH2 technology This embedded fracture modeling approach is very promising and computationally efficient to handle realistic 3D discrete fractures with complicated geometries, connections, and spatial distributions. Compared with other fracture modeling approaches, it avoids cumbersome 3D unstructured, local refining procedures, and increases computational efficiency by simplifying Jacobian matrix size and sparsity, while keeps sufficient accuracy. Several numeral simulations are present to demonstrate the utility and robustness of the proposed technique. Our numerical experiments show that this approach captures all the key patterns about fluid flow and heat transfer dominated by fractures in these cases. Thus, this approach is readily available to simulation of fractured geothermal reservoirs with both artificial and natural fractures.« less

Ecological monitoring in a discrete-time prey-predator model.

PubMed

Gámez, M; López, I; Rodríguez, C; Varga, Z; Garay, J

2017-09-21

The paper is aimed at the methodological development of ecological monitoring in discrete-time dynamic models. In earlier papers, in the framework of continuous-time models, we have shown how a systems-theoretical methodology can be applied to the monitoring of the state process of a system of interacting populations, also estimating certain abiotic environmental changes such as pollution, climatic or seasonal changes. In practice, however, there may be good reasons to use discrete-time models. (For instance, there may be discrete cycles in the development of the populations, or observations can be made only at discrete time steps.) Therefore the present paper is devoted to the development of the monitoring methodology in the framework of discrete-time models of population ecology. By monitoring we mean that, observing only certain component(s) of the system, we reconstruct the whole state process. This may be necessary, e.g., when in a complex ecosystem the observation of the densities of certain species is impossible, or too expensive. For the first presentation of the offered methodology, we have chosen a discrete-time version of the classical Lotka-Volterra prey-predator model. This is a minimal but not trivial system where the methodology can still be presented. We also show how this methodology can be applied to estimate the effect of an abiotic environmental change, using a component of the population system as an environmental indicator. Although this approach is illustrated in a simplest possible case, it can be easily extended to larger ecosystems with several interacting populations and different types of abiotic environmental effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

A discrete event simulation tool to support and predict hospital and clinic staffing.

PubMed

DeRienzo, Christopher M; Shaw, Ryan J; Meanor, Phillip; Lada, Emily; Ferranti, Jeffrey; Tanaka, David

2017-06-01

We demonstrate how to develop a simulation tool to help healthcare managers and administrators predict and plan for staffing needs in a hospital neonatal intensive care unit using administrative data. We developed a discrete event simulation model of nursing staff needed in a neonatal intensive care unit and then validated the model against historical data. The process flow was translated into a discrete event simulation model. Results demonstrated that the model can be used to give a respectable estimate of annual admissions, transfers, and deaths based upon two different staffing levels. The discrete event simulation tool model can provide healthcare managers and administrators with (1) a valid method of modeling patient mix, patient acuity, staffing needs, and costs in the present state and (2) a forecast of how changes in a unit's staffing, referral patterns, or patient mix would affect a unit in a future state.

Relating coupled map lattices to integro-difference equations: dispersal-driven instabilities in coupled map lattices.

PubMed

White, Steven M; White, K A Jane

2005-08-21

Recently there has been a great deal of interest within the ecological community about the interactions of local populations that are coupled only by dispersal. Models have been developed to consider such scenarios but the theory needed to validate model outcomes has been somewhat lacking. In this paper, we present theory which can be used to understand these types of interaction when population exhibit discrete time dynamics. In particular, we consider a spatial extension to discrete-time models, known as coupled map lattices (CMLs) which are discrete in space. We introduce a general form of the CML and link this to integro-difference equations via a special redistribution kernel. General conditions are then derived for dispersal-driven instabilities. We then apply this theory to two discrete-time models; a predator-prey model and a host-pathogen model.

A general population-genetic model for the production by population structure of spurious genotype-phenotype associations in discrete, admixed or spatially distributed populations.

PubMed

Rosenberg, Noah A; Nordborg, Magnus

2006-07-01

In linkage disequilibrium mapping of genetic variants causally associated with phenotypes, spurious associations can potentially be generated by any of a variety of types of population structure. However, mathematical theory of the production of spurious associations has largely been restricted to population structure models that involve the sampling of individuals from a collection of discrete subpopulations. Here, we introduce a general model of spurious association in structured populations, appropriate whether the population structure involves discrete groups, admixture among such groups, or continuous variation across space. Under the assumptions of the model, we find that a single common principle--applicable to both the discrete and admixed settings as well as to spatial populations--gives a necessary and sufficient condition for the occurrence of spurious associations. Using a mathematical connection between the discrete and admixed cases, we show that in admixed populations, spurious associations are less severe than in corresponding mixtures of discrete subpopulations, especially when the variance of admixture across individuals is small. This observation, together with the results of simulations that examine the relative influences of various model parameters, has important implications for the design and analysis of genetic association studies in structured populations.

Comprehensive human transcription factor binding site map for combinatory binding motifs discovery.

PubMed

Müller-Molina, Arnoldo J; Schöler, Hans R; Araúzo-Bravo, Marcos J

2012-01-01

To know the map between transcription factors (TFs) and their binding sites is essential to reverse engineer the regulation process. Only about 10%-20% of the transcription factor binding motifs (TFBMs) have been reported. This lack of data hinders understanding gene regulation. To address this drawback, we propose a computational method that exploits never used TF properties to discover the missing TFBMs and their sites in all human gene promoters. The method starts by predicting a dictionary of regulatory "DNA words." From this dictionary, it distills 4098 novel predictions. To disclose the crosstalk between motifs, an additional algorithm extracts TF combinatorial binding patterns creating a collection of TF regulatory syntactic rules. Using these rules, we narrowed down a list of 504 novel motifs that appear frequently in syntax patterns. We tested the predictions against 509 known motifs confirming that our system can reliably predict ab initio motifs with an accuracy of 81%-far higher than previous approaches. We found that on average, 90% of the discovered combinatorial binding patterns target at least 10 genes, suggesting that to control in an independent manner smaller gene sets, supplementary regulatory mechanisms are required. Additionally, we discovered that the new TFBMs and their combinatorial patterns convey biological meaning, targeting TFs and genes related to developmental functions. Thus, among all the possible available targets in the genome, the TFs tend to regulate other TFs and genes involved in developmental functions. We provide a comprehensive resource for regulation analysis that includes a dictionary of "DNA words," newly predicted motifs and their corresponding combinatorial patterns. Combinatorial patterns are a useful filter to discover TFBMs that play a major role in orchestrating other factors and thus, are likely to lock/unlock cellular functional clusters.

Comprehensive Human Transcription Factor Binding Site Map for Combinatory Binding Motifs Discovery

PubMed Central

Müller-Molina, Arnoldo J.; Schöler, Hans R.; Araúzo-Bravo, Marcos J.

2012-01-01

To know the map between transcription factors (TFs) and their binding sites is essential to reverse engineer the regulation process. Only about 10%–20% of the transcription factor binding motifs (TFBMs) have been reported. This lack of data hinders understanding gene regulation. To address this drawback, we propose a computational method that exploits never used TF properties to discover the missing TFBMs and their sites in all human gene promoters. The method starts by predicting a dictionary of regulatory “DNA words.” From this dictionary, it distills 4098 novel predictions. To disclose the crosstalk between motifs, an additional algorithm extracts TF combinatorial binding patterns creating a collection of TF regulatory syntactic rules. Using these rules, we narrowed down a list of 504 novel motifs that appear frequently in syntax patterns. We tested the predictions against 509 known motifs confirming that our system can reliably predict ab initio motifs with an accuracy of 81%—far higher than previous approaches. We found that on average, 90% of the discovered combinatorial binding patterns target at least 10 genes, suggesting that to control in an independent manner smaller gene sets, supplementary regulatory mechanisms are required. Additionally, we discovered that the new TFBMs and their combinatorial patterns convey biological meaning, targeting TFs and genes related to developmental functions. Thus, among all the possible available targets in the genome, the TFs tend to regulate other TFs and genes involved in developmental functions. We provide a comprehensive resource for regulation analysis that includes a dictionary of “DNA words,” newly predicted motifs and their corresponding combinatorial patterns. Combinatorial patterns are a useful filter to discover TFBMs that play a major role in orchestrating other factors and thus, are likely to lock/unlock cellular functional clusters. PMID:23209563

Energy Criterion for the Spectral Stability of Discrete Breathers.

PubMed

Kevrekidis, Panayotis G; Cuevas-Maraver, Jesús; Pelinovsky, Dmitry E

2016-08-26

Discrete breathers are ubiquitous structures in nonlinear anharmonic models ranging from the prototypical example of the Fermi-Pasta-Ulam model to Klein-Gordon nonlinear lattices, among many others. We propose a general criterion for the emergence of instabilities of discrete breathers analogous to the well-established Vakhitov-Kolokolov criterion for solitary waves. The criterion involves the change of monotonicity of the discrete breather's energy as a function of the breather frequency. Our analysis suggests and numerical results corroborate that breathers with increasing (decreasing) energy-frequency dependence are generically unstable in soft (hard) nonlinear potentials.

The quest for solvable multistate Landau-Zener models

DOE PAGES

Sinitsyn, Nikolai A.; Chernyak, Vladimir Y.

2017-05-24

Recently, integrability conditions (ICs) in mutistate Landau-Zener (MLZ) theory were proposed. They describe common properties of all known solved systems with linearly time-dependent Hamiltonians. Here we show that ICs enable efficient computer assisted search for new solvable MLZ models that span complexity range from several interacting states to mesoscopic systems with many-body dynamics and combinatorially large phase space. This diversity suggests that nontrivial solvable MLZ models are numerous. Additionally, we refine the formulation of ICs and extend the class of solvable systems to models with points of multiple diabatic level crossing.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Formal Operations and Ego Identity in Adolescence.

ERIC Educational Resources Information Center

Wagner, Janis A.

1987-01-01

Investigated the relationship between the development of formal operations and the formation of ego identity in adolescence. Obtained significant positive correlations between combinatorial ability and degree of identity, suggesting that high identity may facilitate the application of combinatorial operations. Found some gender differences in task…

Manipulating Combinatorial Structures.

ERIC Educational Resources Information Center

Labelle, Gilbert

This set of transparencies shows how the manipulation of combinatorial structures in the context of modern combinatorics can easily lead to interesting teaching and learning activities at every level of education from elementary school to university. The transparencies describe: (1) the importance and relations of combinatorics to science and…

Gian-Carlos Rota and Combinatorial Math.

ERIC Educational Resources Information Center

Kolata, Gina Bari

1979-01-01

Presents the first of a series of occasional articles about mathematics as seen through the eyes of its prominent scholars. In an interview with Gian-Carlos Rota of the Massachusetts Institute of Technology he discusses how combinatorial mathematics began as a field and its future. (HM)