Boolean networks with veto functions
NASA Astrophysics Data System (ADS)
Ebadi, Haleh; Klemm, Konstantin
2014-08-01
Boolean networks are discrete dynamical systems for modeling regulation and signaling in living cells. We investigate a particular class of Boolean functions with inhibiting inputs exerting a veto (forced zero) on the output. We give analytical expressions for the sensitivity of these functions and provide evidence for their role in natural systems. In an intracellular signal transduction network [Helikar et al., Proc. Natl. Acad. Sci. USA 105, 1913 (2008), 10.1073/pnas.0705088105], the functions with veto are over-represented by a factor exceeding the over-representation of threshold functions and canalyzing functions in the same system. In Boolean networks for control of the yeast cell cycle [Li et al., Proc. Natl. Acad. Sci. USA 101, 4781 (2004), 10.1073/pnas.0305937101; Davidich et al., PLoS ONE 3, e1672 (2008), 10.1371/journal.pone.0001672], no or minimal changes to the wiring diagrams are necessary to formulate their dynamics in terms of the veto functions introduced here.
State feedback control design for Boolean networks.
Liu, Rongjie; Qian, Chunjiang; Liu, Shuqian; Jin, Yu-Fang
2016-08-26
Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the mathematical condition on controllability to real boolean operations in a network. Further, no realtime control strategy has been proposed to drive a Boolean network. In this study, we applied semi-tensor product to represent boolean functions in a network and explored controllability of a boolean network based on the transition matrix and time transition diagram. We determined the necessary and sufficient condition for a controllable Boolean network and mapped this requirement in transition matrix to real boolean functions and structure property of a network. An efficient tool is offered to assess controllability of an arbitrary Boolean network and to determine all reachable and non-reachable states. We found six simplest forms of controllable 2-node Boolean networks and explored the consistency of transition matrices while extending these six forms to controllable networks with more nodes. Importantly, we proposed the first state feedback control strategy to drive the network based on the status of all nodes in the network. Finally, we applied our reachability condition to the major switch of P53 pathway to predict the progression of the pathway and validate the prediction with published experimental results. This control strategy allowed us to apply realtime control to drive Boolean networks, which could not be achieved by the current control strategy for Boolean networks. Our results enabled a more comprehensive understanding of the evolution of Boolean networks and might be extended to output feedback control design.
Fisher information at the edge of chaos in random Boolean networks.
Wang, X Rosalind; Lizier, Joseph T; Prokopenko, Mikhail
2011-01-01
We study the order-chaos phase transition in random Boolean networks (RBNs), which have been used as models of gene regulatory networks. In particular we seek to characterize the phase diagram in information-theoretic terms, focusing on the effect of the control parameters (activity level and connectivity). Fisher information, which measures how much system dynamics can reveal about the control parameters, offers a natural interpretation of the phase diagram in RBNs. We report that this measure is maximized near the order-chaos phase transitions in RBNs, since this is the region where the system is most sensitive to its parameters. Furthermore, we use this study of RBNs to clarify the relationship between Shannon and Fisher information measures.
BEAT: A Web-Based Boolean Expression Fault-Based Test Case Generation Tool
ERIC Educational Resources Information Center
Chen, T. Y.; Grant, D. D.; Lau, M. F.; Ng, S. P.; Vasa, V. R.
2006-01-01
BEAT is a Web-based system that generates fault-based test cases from Boolean expressions. It is based on the integration of our several fault-based test case selection strategies. The generated test cases are considered to be fault-based, because they are aiming at the detection of particular faults. For example, when the Boolean expression is in…
Symbolic Boolean Manipulation with Ordered Binary Decision Diagrams
1992-07-01
memories , where careful attention has been given to programming the memory management routines [Brace et al 19901. To extract maximum performance, it...OBDDs) represent Boolean functions as directed acyclic graphs. They form a canonical representation, making testing of functional properties such as...indicated 3 X X2 X3 f 000 0 0 01 0X22 0 10 0 0 11 1 d 1 0 0 0 X3 X 3X 1 01 1 1 10 0 - i"o11 10o 1 1 Figure 1: Truth Table and Decison Tree Repremmtatios
Mining TCGA Data Using Boolean Implications
Sinha, Subarna; Tsang, Emily K.; Zeng, Haoyang; Meister, Michela; Dill, David L.
2014-01-01
Boolean implications (if-then rules) provide a conceptually simple, uniform and highly scalable way to find associations between pairs of random variables. In this paper, we propose to use Boolean implications to find relationships between variables of different data types (mutation, copy number alteration, DNA methylation and gene expression) from the glioblastoma (GBM) and ovarian serous cystadenoma (OV) data sets from The Cancer Genome Atlas (TCGA). We find hundreds of thousands of Boolean implications from these data sets. A direct comparison of the relationships found by Boolean implications and those found by commonly used methods for mining associations show that existing methods would miss relationships found by Boolean implications. Furthermore, many relationships exposed by Boolean implications reflect important aspects of cancer biology. Examples of our findings include cis relationships between copy number alteration, DNA methylation and expression of genes, a new hierarchy of mutations and recurrent copy number alterations, loss-of-heterozygosity of well-known tumor suppressors, and the hypermethylation phenotype associated with IDH1 mutations in GBM. The Boolean implication results used in the paper can be accessed at http://crookneck.stanford.edu/microarray/TCGANetworks/. PMID:25054200
Cryptographic Boolean Functions with Biased Inputs
2015-07-31
theory of random graphs developed by Erdős and Rényi [2]. The graph properties in a random graph expressed as such Boolean functions are used by...distributed Bernoulli variates with the parameter p. Since our scope is within the area of cryptography , we initiate an analysis of cryptographic...Boolean functions with biased inputs, which we refer to as µp-Boolean functions, is a common generalization of Boolean functions which stems from the
Monotone Boolean approximation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hulme, B.L.
1982-12-01
This report presents a theory of approximation of arbitrary Boolean functions by simpler, monotone functions. Monotone increasing functions can be expressed without the use of complements. Nonconstant monotone increasing functions are important in their own right since they model a special class of systems known as coherent systems. It is shown here that when Boolean expressions for noncoherent systems become too large to treat exactly, then monotone approximations are easily defined. The algorithms proposed here not only provide simpler formulas but also produce best possible upper and lower monotone bounds for any Boolean function. This theory has practical application formore » the analysis of noncoherent fault trees and event tree sequences.« less
NASA Technical Reports Server (NTRS)
Tucker, Jerry H.; Tapia, Moiez A.; Bennett, A. Wayne
1988-01-01
The concept of Boolean integration is developed, and different Boolean integral operators are introduced. Given the changes in a desired function in terms of the changes in its arguments, the ways of 'integrating' (i.e. realizing) such a function, if it exists, are presented. The necessary and sufficient conditions for integrating, in different senses, the expression specifying the changes are obtained. Boolean calculus has applications in the design of logic circuits and in fault analysis.
On the Run-Time Optimization of the Boolean Logic of a Program.
ERIC Educational Resources Information Center
Cadolino, C.; Guazzo, M.
1982-01-01
Considers problem of optimal scheduling of Boolean expression (each Boolean variable represents binary outcome of program module) on single-processor system. Optimization discussed consists of finding operand arrangement that minimizes average execution costs representing consumption of resources (elapsed time, main memory, number of…
Jimena: efficient computing and system state identification for genetic regulatory networks.
Karl, Stefan; Dandekar, Thomas
2013-10-11
Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed. (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones). Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior.
Barra, Adriano; Genovese, Giuseppe; Sollich, Peter; Tantari, Daniele
2018-02-01
Restricted Boltzmann machines are described by the Gibbs measure of a bipartite spin glass, which in turn can be seen as a generalized Hopfield network. This equivalence allows us to characterize the state of these systems in terms of their retrieval capabilities, both at low and high load, of pure states. We study the paramagnetic-spin glass and the spin glass-retrieval phase transitions, as the pattern (i.e., weight) distribution and spin (i.e., unit) priors vary smoothly from Gaussian real variables to Boolean discrete variables. Our analysis shows that the presence of a retrieval phase is robust and not peculiar to the standard Hopfield model with Boolean patterns. The retrieval region becomes larger when the pattern entries and retrieval units get more peaked and, conversely, when the hidden units acquire a broader prior and therefore have a stronger response to high fields. Moreover, at low load retrieval always exists below some critical temperature, for every pattern distribution ranging from the Boolean to the Gaussian case.
Mcclenny, Levi D; Imani, Mahdi; Braga-Neto, Ulisses M
2017-11-25
Gene regulatory networks govern the function of key cellular processes, such as control of the cell cycle, response to stress, DNA repair mechanisms, and more. Boolean networks have been used successfully in modeling gene regulatory networks. In the Boolean network model, the transcriptional state of each gene is represented by 0 (inactive) or 1 (active), and the relationship among genes is represented by logical gates updated at discrete time points. However, the Boolean gene states are never observed directly, but only indirectly and incompletely through noisy measurements based on expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays. The Partially-Observed Boolean Dynamical System (POBDS) signal model is distinct from other deterministic and stochastic Boolean network models in removing the requirement of a directly observable Boolean state vector and allowing uncertainty in the measurement process, addressing the scenario encountered in practice in transcriptomic analysis. BoolFilter is an R package that implements the POBDS model and associated algorithms for state and parameter estimation. It allows the user to estimate the Boolean states, network topology, and measurement parameters from time series of transcriptomic data using exact and approximated (particle) filters, as well as simulate the transcriptomic data for a given Boolean network model. Some of its infrastructure, such as the network interface, is the same as in the previously published R package for Boolean Networks BoolNet, which enhances compatibility and user accessibility to the new package. We introduce the R package BoolFilter for Partially-Observed Boolean Dynamical Systems (POBDS). The BoolFilter package provides a useful toolbox for the bioinformatics community, with state-of-the-art algorithms for simulation of time series transcriptomic data as well as the inverse process of system identification from data obtained with various expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays.
"Antelope": a hybrid-logic model checker for branching-time Boolean GRN analysis
2011-01-01
Background In Thomas' formalism for modeling gene regulatory networks (GRNs), branching time, where a state can have more than one possible future, plays a prominent role. By representing a certain degree of unpredictability, branching time can model several important phenomena, such as (a) asynchrony, (b) incompletely specified behavior, and (c) interaction with the environment. Introducing more than one possible future for a state, however, creates a difficulty for ordinary simulators, because infinitely many paths may appear, limiting ordinary simulators to statistical conclusions. Model checkers for branching time, by contrast, are able to prove properties in the presence of infinitely many paths. Results We have developed Antelope ("Analysis of Networks through TEmporal-LOgic sPEcifications", http://turing.iimas.unam.mx:8080/AntelopeWEB/), a model checker for analyzing and constructing Boolean GRNs. Currently, software systems for Boolean GRNs use branching time almost exclusively for asynchrony. Antelope, by contrast, also uses branching time for incompletely specified behavior and environment interaction. We show the usefulness of modeling these two phenomena in the development of a Boolean GRN of the Arabidopsis thaliana root stem cell niche. There are two obstacles to a direct approach when applying model checking to Boolean GRN analysis. First, ordinary model checkers normally only verify whether or not a given set of model states has a given property. In comparison, a model checker for Boolean GRNs is preferable if it reports the set of states having a desired property. Second, for efficiency, the expressiveness of many model checkers is limited, resulting in the inability to express some interesting properties of Boolean GRNs. Antelope tries to overcome these two drawbacks: Apart from reporting the set of all states having a given property, our model checker can express, at the expense of efficiency, some properties that ordinary model checkers (e.g., NuSMV) cannot. This additional expressiveness is achieved by employing a logic extending the standard Computation-Tree Logic (CTL) with hybrid-logic operators. Conclusions We illustrate the advantages of Antelope when (a) modeling incomplete networks and environment interaction, (b) exhibiting the set of all states having a given property, and (c) representing Boolean GRN properties with hybrid CTL. PMID:22192526
Stability of Boolean multilevel networks.
Cozzo, Emanuele; Arenas, Alex; Moreno, Yamir
2012-09-01
The study of the interplay between the structure and dynamics of complex multilevel systems is a pressing challenge nowadays. In this paper, we use a semiannealed approximation to study the stability properties of random Boolean networks in multiplex (multilayered) graphs. Our main finding is that the multilevel structure provides a mechanism for the stabilization of the dynamics of the whole system even when individual layers work on the chaotic regime, therefore identifying new ways of feedback between the structure and the dynamics of these systems. Our results point out the need for a conceptual transition from the physics of single-layered networks to the physics of multiplex networks. Finally, the fact that the coupling modifies the phase diagram and the critical conditions of the isolated layers suggests that interdependency can be used as a control mechanism.
Inferring Toxicological Responses of HepG2 Cells from ...
Understanding the dynamic perturbation of cell states by chemicals can aid in for predicting their adverse effects. High-content imaging (HCI) was used to measure the state of HepG2 cells over three time points (1, 24, and 72 h) in response to 976 ToxCast chemicals for 10 different concentrations (0.39-200µM). Cell state was characterized by p53 activation (p53), c-Jun activation (SK), phospho-Histone H2A.x (OS), phospho-Histone H3 (MA), alpha tubulin (Mt), mitochondrial membrane potential (MMP), mitochondrial mass (MM), cell cycle arrest (CCA), nuclear size (NS) and cell number (CN). Dynamic cell state perturbations due to each chemical concentration were utilized to infer coarse-grained dependencies between cellular functions as Boolean networks (BNs). BNs were inferred from data in two steps. First, the data for each state variable were discretized into changed/active (> 1 standard deviation), and unchanged/inactive values. Second, the discretized data were used to learn Boolean relationships between variables. In our case, a BN is a wiring diagram between nodes that represent 10 previously described observable phenotypes. Functional relationships between nodes were represented as Boolean functions. We found that inferred BN show that HepG2 cell response is chemical and concentration specific. We observed presence of both point and cycle BN attractors. In addition, there are instances where Boolean functions were not found. We believe that this may be either
Understanding genetic regulatory networks
NASA Astrophysics Data System (ADS)
Kauffman, Stuart
2003-04-01
Random Boolean networks (RBM) were introduced about 35 years ago as first crude models of genetic regulatory networks. RBNs are comprised of N on-off genes, connected by a randomly assigned regulatory wiring diagram where each gene has K inputs, and each gene is controlled by a randomly assigned Boolean function. This procedure samples at random from the ensemble of all possible NK Boolean networks. The central ideas are to study the typical, or generic properties of this ensemble, and see 1) whether characteristic differences appear as K and biases in Boolean functions are introducted, and 2) whether a subclass of this ensemble has properties matching real cells. Such networks behave in an ordered or a chaotic regime, with a phase transition, "the edge of chaos" between the two regimes. Networks with continuous variables exhibit the same two regimes. Substantial evidence suggests that real cells are in the ordered regime. A key concept is that of an attractor. This is a reentrant trajectory of states of the network, called a state cycle. The central biological interpretation is that cell types are attractors. A number of properties differentiate the ordered and chaotic regimes. These include the size and number of attractors, the existence in the ordered regime of a percolating "sea" of genes frozen in the on or off state, with a remainder of isolated twinkling islands of genes, a power law distribution of avalanches of gene activity changes following perturbation to a single gene in the ordered regime versus a similar power law distribution plus a spike of enormous avalanches of gene changes in the chaotic regime, and the existence of branching pathway of "differentiation" between attractors induced by perturbations in the ordered regime. Noise is serious issue, since noise disrupts attractors. But numerical evidence suggests that attractors can be made very stable to noise, and meanwhile, metaplasias may be a biological manifestation of noise. As we learn more about the wiring diagram and constraints on rules controlling real genes, we can build refined ensembles reflecting these properties, study the generic properties of the refined ensembles, and hope to gain insight into the dynamics of real cells.
Veliz-Cuba, Alan; Aguilar, Boris; Hinkelmann, Franziska; Laubenbacher, Reinhard
2014-06-26
A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for large Boolean networks with high average connectivity remains an open problem.
2014-01-01
Background A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. Results This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. Conclusions The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for large Boolean networks with high average connectivity remains an open problem. PMID:24965213
Identification of control targets in Boolean molecular network models via computational algebra.
Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard
2016-09-23
Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.
Describing the What and Why of Students' Difficulties in Boolean Logic
ERIC Educational Resources Information Center
Herman, Geoffrey L.; Loui, Michael C.; Kaczmarczyk, Lisa; Zilles, Craig
2012-01-01
The ability to reason with formal logic is a foundational skill for computer scientists and computer engineers that scaffolds the abilities to design, debug, and optimize. By interviewing students about their understanding of propositional logic and their ability to translate from English specifications to Boolean expressions, we characterized…
The phase topology of a special case of Goryachev integrability in rigid body dynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ryabov, P. E., E-mail: orelryabov@mail.ru
2014-07-31
The phase topology of a special case of Goryachev integrability in the problem of motion of a rigid body in a fluid is investigated using the method of Boolean functions, which was developed by Kharlamov for algebraically separated systems. The bifurcation diagram of the moment map is found and the Fomenko invariant, which classifies the systems up to rough Liouville equivalence, is specified. Bibliography: 15 titles. (paper)
Hiraishi, Kunihiko
2014-01-01
One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs. PMID:24587766
A method of transition conflict resolving in hierarchical control
NASA Astrophysics Data System (ADS)
Łabiak, Grzegorz
2016-09-01
The paper concerns the problem of automatic solving of transition conflicts in hierarchical concurrent state machines (also known as UML state machine). Preparing by the designer a formal specification of a behaviour free from conflicts can be very complex. In this paper, it is proposed a method for solving conflicts through transition predicates modification. Partially specified predicates in the nondeterministic diagram are transformed into a symbolic Boolean space, whose points of the space code all possible valuations of transition predicates. Next, all valuations under partial specifications are logically multiplied by a function which represents all possible orthogonal predicate valuations. The result of this operation contains all possible collections of predicates, which under given partial specification make that the original diagram is conflict free and deterministic.
Inferring Boolean network states from partial information
2013-01-01
Networks of molecular interactions regulate key processes in living cells. Therefore, understanding their functionality is a high priority in advancing biological knowledge. Boolean networks are often used to describe cellular networks mathematically and are fitted to experimental datasets. The fitting often results in ambiguities since the interpretation of the measurements is not straightforward and since the data contain noise. In order to facilitate a more reliable mapping between datasets and Boolean networks, we develop an algorithm that infers network trajectories from a dataset distorted by noise. We analyze our algorithm theoretically and demonstrate its accuracy using simulation and microarray expression data. PMID:24006954
Phase transition of Boolean networks with partially nested canalizing functions
NASA Astrophysics Data System (ADS)
Jansen, Kayse; Matache, Mihaela Teodora
2013-07-01
We generate the critical condition for the phase transition of a Boolean network governed by partially nested canalizing functions for which a fraction of the inputs are canalizing, while the remaining non-canalizing inputs obey a complementary threshold Boolean function. Past studies have considered the stability of fully or partially nested canalizing functions paired with random choices of the complementary function. In some of those studies conflicting results were found with regard to the presence of chaotic behavior. Moreover, those studies focus mostly on ergodic networks in which initial states are assumed equally likely. We relax that assumption and find the critical condition for the sensitivity of the network under a non-ergodic scenario. We use the proposed mathematical model to determine parameter values for which phase transitions from order to chaos occur. We generate Derrida plots to show that the mathematical model matches the actual network dynamics. The phase transition diagrams indicate that both order and chaos can occur, and that certain parameters induce a larger range of values leading to order versus chaos. The edge-of-chaos curves are identified analytically and numerically. It is shown that the depth of canalization does not cause major dynamical changes once certain thresholds are reached; these thresholds are fairly small in comparison to the connectivity of the nodes.
Nadkarni, P M
1997-08-01
Concept Locator (CL) is a client-server application that accesses a Sybase relational database server containing a subset of the UMLS Metathesaurus for the purpose of retrieval of concepts corresponding to one or more query expressions supplied to it. CL's query grammar permits complex Boolean expressions, wildcard patterns, and parenthesized (nested) subexpressions. CL translates the query expressions supplied to it into one or more SQL statements that actually perform the retrieval. The generated SQL is optimized by the client to take advantage of the strengths of the server's query optimizer, and sidesteps its weaknesses, so that execution is reasonably efficient.
Towards Symbolic Model Checking for Multi-Agent Systems via OBDDs
NASA Technical Reports Server (NTRS)
Raimondi, Franco; Lomunscio, Alessio
2004-01-01
We present an algorithm for model checking temporal-epistemic properties of multi-agent systems, expressed in the formalism of interpreted systems. We first introduce a technique for the translation of interpreted systems into boolean formulae, and then present a model-checking algorithm based on this translation. The algorithm is based on OBDD's, as they offer a compact and efficient representation for boolean formulae.
On complexity of trellis structure of linear block codes
NASA Technical Reports Server (NTRS)
Lin, Shu
1990-01-01
The trellis structure of linear block codes (LBCs) is discussed. The state and branch complexities of a trellis diagram (TD) for a LBC is investigated. The TD with the minimum number of states is said to be minimal. The branch complexity of a minimal TD for a LBC is expressed in terms of the dimensions of specific subcodes of the given code. Then upper and lower bounds are derived on the number of states of a minimal TD for a LBC, and it is shown that a cyclic (or shortened cyclic) code is the worst in terms of the state complexity among the LBCs of the same length and dimension. Furthermore, it is shown that the structural complexity of a minimal TD for a LBC depends on the order of its bit positions. This fact suggests that an appropriate permutation of the bit positions of a code may result in an equivalent code with a much simpler minimal TD. Boolean polynomial representation of codewords of a LBC is also considered. This representation helps in study of the trellis structure of the code. Boolean polynomial representation of a code is applied to construct its minimal TD. Particularly, the construction of minimal trellises for Reed-Muller codes and the extended and permuted binary primitive BCH codes which contain Reed-Muller as subcodes is emphasized. Finally, the structural complexity of minimal trellises for the extended and permuted, and double-error-correcting BCH codes is analyzed and presented. It is shown that these codes have relatively simple trellis structure and hence can be decoded with the Viterbi decoding algorithm.
Modeling stochasticity and robustness in gene regulatory networks.
Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis
2009-06-15
Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.
Predictive computation of genomic logic processing functions in embryonic development
Peter, Isabelle S.; Faure, Emmanuel; Davidson, Eric H.
2012-01-01
Gene regulatory networks (GRNs) control the dynamic spatial patterns of regulatory gene expression in development. Thus, in principle, GRN models may provide system-level, causal explanations of developmental process. To test this assertion, we have transformed a relatively well-established GRN model into a predictive, dynamic Boolean computational model. This Boolean model computes spatial and temporal gene expression according to the regulatory logic and gene interactions specified in a GRN model for embryonic development in the sea urchin. Additional information input into the model included the progressive embryonic geometry and gene expression kinetics. The resulting model predicted gene expression patterns for a large number of individual regulatory genes each hour up to gastrulation (30 h) in four different spatial domains of the embryo. Direct comparison with experimental observations showed that the model predictively computed these patterns with remarkable spatial and temporal accuracy. In addition, we used this model to carry out in silico perturbations of regulatory functions and of embryonic spatial organization. The model computationally reproduced the altered developmental functions observed experimentally. Two major conclusions are that the starting GRN model contains sufficiently complete regulatory information to permit explanation of a complex developmental process of gene expression solely in terms of genomic regulatory code, and that the Boolean model provides a tool with which to test in silico regulatory circuitry and developmental perturbations. PMID:22927416
Inference of combinatorial Boolean rules of synergistic gene sets from cancer microarray datasets.
Park, Inho; Lee, Kwang H; Lee, Doheon
2010-06-15
Gene set analysis has become an important tool for the functional interpretation of high-throughput gene expression datasets. Moreover, pattern analyses based on inferred gene set activities of individual samples have shown the ability to identify more robust disease signatures than individual gene-based pattern analyses. Although a number of approaches have been proposed for gene set-based pattern analysis, the combinatorial influence of deregulated gene sets on disease phenotype classification has not been studied sufficiently. We propose a new approach for inferring combinatorial Boolean rules of gene sets for a better understanding of cancer transcriptome and cancer classification. To reduce the search space of the possible Boolean rules, we identify small groups of gene sets that synergistically contribute to the classification of samples into their corresponding phenotypic groups (such as normal and cancer). We then measure the significance of the candidate Boolean rules derived from each group of gene sets; the level of significance is based on the class entropy of the samples selected in accordance with the rules. By applying the present approach to publicly available prostate cancer datasets, we identified 72 significant Boolean rules. Finally, we discuss several identified Boolean rules, such as the rule of glutathione metabolism (down) and prostaglandin synthesis regulation (down), which are consistent with known prostate cancer biology. Scripts written in Python and R are available at http://biosoft.kaist.ac.kr/~ihpark/. The refined gene sets and the full list of the identified Boolean rules are provided in the Supplementary Material. Supplementary data are available at Bioinformatics online.
Harris, Daniel R.; Henderson, Darren W.; Kavuluru, Ramakanth; Stromberg, Arnold J.; Johnson, Todd R.
2015-01-01
We present a custom, Boolean query generator utilizing common-table expressions (CTEs) that is capable of scaling with big datasets. The generator maps user-defined Boolean queries, such as those interactively created in clinical-research and general-purpose healthcare tools, into SQL. We demonstrate the effectiveness of this generator by integrating our work into the Informatics for Integrating Biology and the Bedside (i2b2) query tool and show that it is capable of scaling. Our custom generator replaces and outperforms the default query generator found within the Clinical Research Chart (CRC) cell of i2b2. In our experiments, sixteen different types of i2b2 queries were identified by varying four constraints: date, frequency, exclusion criteria, and whether selected concepts occurred in the same encounter. We generated non-trivial, random Boolean queries based on these 16 types; the corresponding SQL queries produced by both generators were compared by execution times. The CTE-based solution significantly outperformed the default query generator and provided a much more consistent response time across all query types (M=2.03, SD=6.64 vs. M=75.82, SD=238.88 seconds). Without costly hardware upgrades, we provide a scalable solution based on CTEs with very promising empirical results centered on performance gains. The evaluation methodology used for this provides a means of profiling clinical data warehouse performance. PMID:25192572
Integrating Multiple Data Sources for Combinatorial Marker Discovery: A Study in Tumorigenesis.
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.
Phase transitions in restricted Boltzmann machines with generic priors
NASA Astrophysics Data System (ADS)
Barra, Adriano; Genovese, Giuseppe; Sollich, Peter; Tantari, Daniele
2017-10-01
We study generalized restricted Boltzmann machines with generic priors for units and weights, interpolating between Boolean and Gaussian variables. We present a complete analysis of the replica symmetric phase diagram of these systems, which can be regarded as generalized Hopfield models. We underline the role of the retrieval phase for both inference and learning processes and we show that retrieval is robust for a large class of weight and unit priors, beyond the standard Hopfield scenario. Furthermore, we show how the paramagnetic phase boundary is directly related to the optimal size of the training set necessary for good generalization in a teacher-student scenario of unsupervised learning.
Optimization of digital designs
NASA Technical Reports Server (NTRS)
Miles, Lowell H. (Inventor); Whitaker, Sterling R. (Inventor)
2009-01-01
An application specific integrated circuit is optimized by translating a first representation of its digital design to a second representation. The second representation includes multiple syntactic expressions that admit a representation of a higher-order function of base Boolean values. The syntactic expressions are manipulated to form a third representation of the digital design.
Toward using games to teach fundamental computer science concepts
NASA Astrophysics Data System (ADS)
Edgington, Jeffrey Michael
Video and computer games have become an important area of study in the field of education. Games have been designed to teach mathematics, physics, raise social awareness, teach history and geography, and train soldiers in the military. Recent work has created computer games for teaching computer programming and understanding basic algorithms. We present an investigation where computer games are used to teach two fundamental computer science concepts: boolean expressions and recursion. The games are intended to teach the concepts and not how to implement them in a programming language. For this investigation, two computer games were created. One is designed to teach basic boolean expressions and operators and the other to teach fundamental concepts of recursion. We describe the design and implementation of both games. We evaluate the effectiveness of these games using before and after surveys. The surveys were designed to ascertain basic understanding, attitudes and beliefs regarding the concepts. The boolean game was evaluated with local high school students and students in a college level introductory computer science course. The recursion game was evaluated with students in a college level introductory computer science course. We present the analysis of the collected survey information for both games. This analysis shows a significant positive change in student attitude towards recursion and modest gains in student learning outcomes for both topics.
Discrete interference modeling via boolean algebra.
Beckhoff, Gerhard
2011-01-01
Two types of boolean functions are considered, the locus function of n variables, and the interval function of ν = n - 1 variables. A 1-1 mapping is given that takes elements (cells) of the interval function to antidual pairs of elements in the locus function, and vice versa. A set of ν binary codewords representing the intervals are defined and used to generate the codewords of all genomic regions. Next a diallelic three-point system is reviewed in the light of boolean functions, which leads to redefining complete interference by a logic function. Together with the upper bound of noninterference already defined by a boolean function, it confines the region of interference. Extensions of these two functions to any finite number of ν are straightforward, but have been also made in terms of variables taken from the inclusion-exclusion principle (expressing "at least" and "exactly equal to" a decimal integer). Two coefficients of coincidence for systems with more than three loci are defined and discussed, one using the average of several individual coefficients and the other taking as coefficient a real number between zero and one. Finally, by way of a malfunction of the mod-2 addition, it is shown that a four-point system may produce two different functions, one of which exhibiting loss of a class of odd recombinants.
Diagnostic reasoning techniques for selective monitoring
NASA Technical Reports Server (NTRS)
Homem-De-mello, L. S.; Doyle, R. J.
1991-01-01
An architecture for using diagnostic reasoning techniques in selective monitoring is presented. Given the sensor readings and a model of the physical system, a number of assertions are generated and expressed as Boolean equations. The resulting system of Boolean equations is solved symbolically. Using a priori probabilities of component failure and Bayes' rule, revised probabilities of failure can be computed. These will indicate what components have failed or are the most likely to have failed. This approach is suitable for systems that are well understood and for which the correctness of the assertions can be guaranteed. Also, the system must be such that changes are slow enough to allow the computation.
NASA Astrophysics Data System (ADS)
Thakar, Juilee; Albert, Réka
The following sections are included: * Introduction * Boolean Network Concepts and History * Extensions of the Classical Boolean Framework * Boolean Inference Methods and Examples in Biology * Dynamic Boolean Models: Examples in Plant Biology, Developmental Biology and Immunology * Conclusions * References
Identification of Boolean Network Models From Time Series Data Incorporating Prior Knowledge.
Leifeld, Thomas; Zhang, Zhihua; Zhang, Ping
2018-01-01
Motivation: Mathematical models take an important place in science and engineering. A model can help scientists to explain dynamic behavior of a system and to understand the functionality of system components. Since length of a time series and number of replicates is limited by the cost of experiments, Boolean networks as a structurally simple and parameter-free logical model for gene regulatory networks have attracted interests of many scientists. In order to fit into the biological contexts and to lower the data requirements, biological prior knowledge is taken into consideration during the inference procedure. In the literature, the existing identification approaches can only deal with a subset of possible types of prior knowledge. Results: We propose a new approach to identify Boolean networks from time series data incorporating prior knowledge, such as partial network structure, canalizing property, positive and negative unateness. Using vector form of Boolean variables and applying a generalized matrix multiplication called the semi-tensor product (STP), each Boolean function can be equivalently converted into a matrix expression. Based on this, the identification problem is reformulated as an integer linear programming problem to reveal the system matrix of Boolean model in a computationally efficient way, whose dynamics are consistent with the important dynamics captured in the data. By using prior knowledge the number of candidate functions can be reduced during the inference. Hence, identification incorporating prior knowledge is especially suitable for the case of small size time series data and data without sufficient stimuli. The proposed approach is illustrated with the help of a biological model of the network of oxidative stress response. Conclusions: The combination of efficient reformulation of the identification problem with the possibility to incorporate various types of prior knowledge enables the application of computational model inference to systems with limited amount of time series data. The general applicability of this methodological approach makes it suitable for a variety of biological systems and of general interest for biological and medical research.
Saturation: An efficient iteration strategy for symbolic state-space generation
NASA Technical Reports Server (NTRS)
Ciardo, Gianfranco; Luettgen, Gerald; Siminiceanu, Radu; Bushnell, Dennis M. (Technical Monitor)
2001-01-01
This paper presents a novel algorithm for generating state spaces of asynchronous systems using Multi-valued Decision Diagrams. In contrast to related work, the next-state function of a system is not encoded as a single Boolean function, but as cross-products of integer functions. This permits the application of various iteration strategies to build a system's state space. In particular, this paper introduces a new elegant strategy, called saturation, and implements it in the tool SMART. On top of usually performing several orders of magnitude faster than existing BDD-based state-space generators, the algorithm's required peak memory is often close to the nal memory needed for storing the overall state spaces.
ERIC Educational Resources Information Center
Lowe, M. Sara; Maxson, Bronwen K.; Stone, Sean M.; Miller, Willie; Snajdr, Eric; Hanna, Kathleen
2018-01-01
Boolean logic can be a difficult concept for first-year, introductory students to grasp. This paper compares the results of Boolean and natural language searching across several databases with searches created from student research questions. Performance differences between databases varied. Overall, natural search language is at least as good as…
A sparse matrix algorithm on the Boolean vector machine
NASA Technical Reports Server (NTRS)
Wagner, Robert A.; Patrick, Merrell L.
1988-01-01
VLSI technology is being used to implement a prototype Boolean Vector Machine (BVM), which is a large network of very small processors with equally small memories that operate in SIMD mode; these use bit-serial arithmetic, and communicate via cube-connected cycles network. The BVM's bit-serial arithmetic and the small memories of individual processors are noted to compromise the system's effectiveness in large numerical problem applications. Attention is presently given to the implementation of a basic matrix-vector iteration algorithm for space matrices of the BVM, in order to generate over 1 billion useful floating-point operations/sec for this iteration algorithm. The algorithm is expressed in a novel language designated 'BVM'.
Computational complexity of Boolean functions
NASA Astrophysics Data System (ADS)
Korshunov, Aleksei D.
2012-02-01
Boolean functions are among the fundamental objects of discrete mathematics, especially in those of its subdisciplines which fall under mathematical logic and mathematical cybernetics. The language of Boolean functions is convenient for describing the operation of many discrete systems such as contact networks, Boolean circuits, branching programs, and some others. An important parameter of discrete systems of this kind is their complexity. This characteristic has been actively investigated starting from Shannon's works. There is a large body of scientific literature presenting many fundamental results. The purpose of this survey is to give an account of the main results over the last sixty years related to the complexity of computation (realization) of Boolean functions by contact networks, Boolean circuits, and Boolean circuits without branching. Bibliography: 165 titles.
Boolean dynamics of genetic regulatory networks inferred from microarray time series data
Martin, Shawn; Zhang, Zhaoduo; Martino, Anthony; ...
2007-01-31
Methods available for the inference of genetic regulatory networks strive to produce a single network, usually by optimizing some quantity to fit the experimental observations. In this paper we investigate the possibility that multiple networks can be inferred, all resulting in similar dynamics. This idea is motivated by theoretical work which suggests that biological networks are robust and adaptable to change, and that the overall behavior of a genetic regulatory network might be captured in terms of dynamical basins of attraction. We have developed and implemented a method for inferring genetic regulatory networks for time series microarray data. Our methodmore » first clusters and discretizes the gene expression data using k-means and support vector regression. We then enumerate Boolean activation–inhibition networks to match the discretized data. In conclusion, the dynamics of the Boolean networks are examined. We have tested our method on two immunology microarray datasets: an IL-2-stimulated T cell response dataset and a LPS-stimulated macrophage response dataset. In both cases, we discovered that many networks matched the data, and that most of these networks had similar dynamics.« less
Synchronization Analysis of Master-Slave Probabilistic Boolean Networks.
Lu, Jianquan; Zhong, Jie; Li, Lulu; Ho, Daniel W C; Cao, Jinde
2015-08-28
In this paper, we analyze the synchronization problem of master-slave probabilistic Boolean networks (PBNs). The master Boolean network (BN) is a deterministic BN, while the slave BN is determined by a series of possible logical functions with certain probability at each discrete time point. In this paper, we firstly define the synchronization of master-slave PBNs with probability one, and then we investigate synchronization with probability one. By resorting to new approach called semi-tensor product (STP), the master-slave PBNs are expressed in equivalent algebraic forms. Based on the algebraic form, some necessary and sufficient criteria are derived to guarantee synchronization with probability one. Further, we study the synchronization of master-slave PBNs in probability. Synchronization in probability implies that for any initial states, the master BN can be synchronized by the slave BN with certain probability, while synchronization with probability one implies that master BN can be synchronized by the slave BN with probability one. Based on the equivalent algebraic form, some efficient conditions are derived to guarantee synchronization in probability. Finally, several numerical examples are presented to show the effectiveness of the main results.
Synchronization Analysis of Master-Slave Probabilistic Boolean Networks
Lu, Jianquan; Zhong, Jie; Li, Lulu; Ho, Daniel W. C.; Cao, Jinde
2015-01-01
In this paper, we analyze the synchronization problem of master-slave probabilistic Boolean networks (PBNs). The master Boolean network (BN) is a deterministic BN, while the slave BN is determined by a series of possible logical functions with certain probability at each discrete time point. In this paper, we firstly define the synchronization of master-slave PBNs with probability one, and then we investigate synchronization with probability one. By resorting to new approach called semi-tensor product (STP), the master-slave PBNs are expressed in equivalent algebraic forms. Based on the algebraic form, some necessary and sufficient criteria are derived to guarantee synchronization with probability one. Further, we study the synchronization of master-slave PBNs in probability. Synchronization in probability implies that for any initial states, the master BN can be synchronized by the slave BN with certain probability, while synchronization with probability one implies that master BN can be synchronized by the slave BN with probability one. Based on the equivalent algebraic form, some efficient conditions are derived to guarantee synchronization in probability. Finally, several numerical examples are presented to show the effectiveness of the main results. PMID:26315380
Evolutionary Algorithms for Boolean Functions in Diverse Domains of Cryptography.
Picek, Stjepan; Carlet, Claude; Guilley, Sylvain; Miller, Julian F; Jakobovic, Domagoj
2016-01-01
The role of Boolean functions is prominent in several areas including cryptography, sequences, and coding theory. Therefore, various methods for the construction of Boolean functions with desired properties are of direct interest. New motivations on the role of Boolean functions in cryptography with attendant new properties have emerged over the years. There are still many combinations of design criteria left unexplored and in this matter evolutionary computation can play a distinct role. This article concentrates on two scenarios for the use of Boolean functions in cryptography. The first uses Boolean functions as the source of the nonlinearity in filter and combiner generators. Although relatively well explored using evolutionary algorithms, it still presents an interesting goal in terms of the practical sizes of Boolean functions. The second scenario appeared rather recently where the objective is to find Boolean functions that have various orders of the correlation immunity and minimal Hamming weight. In both these scenarios we see that evolutionary algorithms are able to find high-quality solutions where genetic programming performs the best.
A Simple Blueprint for Automatic Boolean Query Processing.
ERIC Educational Resources Information Center
Salton, G.
1988-01-01
Describes a new Boolean retrieval environment in which an extended soft Boolean logic is used to automatically construct queries from original natural language formulations provided by users. Experimental results that compare the retrieval effectiveness of this method to conventional Boolean and vector processing are discussed. (27 references)…
Lähdesmäki, Harri; Hautaniemi, Sampsa; Shmulevich, Ilya; Yli-Harja, Olli
2006-01-01
A significant amount of attention has recently been focused on modeling of gene regulatory networks. Two frequently used large-scale modeling frameworks are Bayesian networks (BNs) and Boolean networks, the latter one being a special case of its recent stochastic extension, probabilistic Boolean networks (PBNs). PBN is a promising model class that generalizes the standard rule-based interactions of Boolean networks into the stochastic setting. Dynamic Bayesian networks (DBNs) is a general and versatile model class that is able to represent complex temporal stochastic processes and has also been proposed as a model for gene regulatory systems. In this paper, we concentrate on these two model classes and demonstrate that PBNs and a certain subclass of DBNs can represent the same joint probability distribution over their common variables. The major benefit of introducing the relationships between the models is that it opens up the possibility of applying the standard tools of DBNs to PBNs and vice versa. Hence, the standard learning tools of DBNs can be applied in the context of PBNs, and the inference methods give a natural way of handling the missing values in PBNs which are often present in gene expression measurements. Conversely, the tools for controlling the stationary behavior of the networks, tools for projecting networks onto sub-networks, and efficient learning schemes can be used for DBNs. In other words, the introduced relationships between the models extend the collection of analysis tools for both model classes. PMID:17415411
Optimal stabilization of Boolean networks through collective influence
NASA Astrophysics Data System (ADS)
Wang, Jiannan; Pei, Sen; Wei, Wei; Feng, Xiangnan; Zheng, Zhiming
2018-03-01
Boolean networks have attracted much attention due to their wide applications in describing dynamics of biological systems. During past decades, much effort has been invested in unveiling how network structure and update rules affect the stability of Boolean networks. In this paper, we aim to identify and control a minimal set of influential nodes that is capable of stabilizing an unstable Boolean network. For locally treelike Boolean networks with biased truth tables, we propose a greedy algorithm to identify influential nodes in Boolean networks by minimizing the largest eigenvalue of a modified nonbacktracking matrix. We test the performance of the proposed collective influence algorithm on four different networks. Results show that the collective influence algorithm can stabilize each network with a smaller set of nodes compared with other heuristic algorithms. Our work provides a new insight into the mechanism that determines the stability of Boolean networks, which may find applications in identifying virulence genes that lead to serious diseases.
NASA Astrophysics Data System (ADS)
Ebadi, H.; Saeedian, M.; Ausloos, M.; Jafari, G. R.
2016-11-01
The Boolean network is one successful model to investigate discrete complex systems such as the gene interacting phenomenon. The dynamics of a Boolean network, controlled with Boolean functions, is usually considered to be a Markovian (memory-less) process. However, both self-organizing features of biological phenomena and their intelligent nature should raise some doubt about ignoring the history of their time evolution. Here, we extend the Boolean network Markovian approach: we involve the effect of memory on the dynamics. This can be explored by modifying Boolean functions into non-Markovian functions, for example, by investigating the usual non-Markovian threshold function —one of the most applied Boolean functions. By applying the non-Markovian threshold function on the dynamical process of the yeast cell cycle network, we discover a power-law-like memory with a more robust dynamics than the Markovian dynamics.
On the Computation of Comprehensive Boolean Gröbner Bases
NASA Astrophysics Data System (ADS)
Inoue, Shutaro
We show that a comprehensive Boolean Gröbner basis of an ideal I in a Boolean polynomial ring B (bar A,bar X) with main variables bar X and parameters bar A can be obtained by simply computing a usual Boolean Gröbner basis of I regarding both bar X and bar A as variables with a certain block term order such that bar X ≫ bar A. The result together with a fact that a finite Boolean ring is isomorphic to a direct product of the Galois field mathbb{GF}_2 enables us to compute a comprehensive Boolean Gröbner basis by only computing corresponding Gröbner bases in a polynomial ring over mathbb{GF}_2. Our implementation in a computer algebra system Risa/Asir shows that our method is extremely efficient comparing with existing computation algorithms of comprehensive Boolean Gröbner bases.
Guide to Human Factors Information Sources.
1984-11-01
intermediary, a computer search is sometimes unnecessary. A lucid way of presenting a search objective is either by Boolean (and/or) expressions or by Venn...1965). Human factors evaluation in system development. New York: John Wiley & Sons. 56. Murray, E. J. (1965). Sleep, dreams , and arousal. New York
On the robustness of complex heterogeneous gene expression networks.
Gómez-Gardeñes, Jesús; Moreno, Yamir; Floría, Luis M
2005-04-01
We analyze a continuous gene expression model on the underlying topology of a complex heterogeneous network. Numerical simulations aimed at studying the chaotic and periodic dynamics of the model are performed. The results clearly indicate that there is a region in which the dynamical and structural complexity of the system avoid chaotic attractors. However, contrary to what has been reported for Random Boolean Networks, the chaotic phase cannot be completely suppressed, which has important bearings on network robustness and gene expression modeling.
Synchronization of coupled large-scale Boolean networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Fangfei, E-mail: li-fangfei@163.com
2014-03-15
This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.
State feedback controller design for the synchronization of Boolean networks with time delays
NASA Astrophysics Data System (ADS)
Li, Fangfei; Li, Jianning; Shen, Lijuan
2018-01-01
State feedback control design to make the response Boolean network synchronize with the drive Boolean network is far from being solved in the literature. Motivated by this, this paper studies the feedback control design for the complete synchronization of two coupled Boolean networks with time delays. A necessary condition for the existence of a state feedback controller is derived first. Then the feedback control design procedure for the complete synchronization of two coupled Boolean networks is provided based on the necessary condition. Finally, an example is given to illustrate the proposed design procedure.
The mathematics of a quantum Hamiltonian computing half adder Boolean logic gate.
Dridi, G; Julien, R; Hliwa, M; Joachim, C
2015-08-28
The mathematics behind the quantum Hamiltonian computing (QHC) approach of designing Boolean logic gates with a quantum system are given. Using the quantum eigenvalue repulsion effect, the QHC AND, NAND, OR, NOR, XOR, and NXOR Hamiltonian Boolean matrices are constructed. This is applied to the construction of a QHC half adder Hamiltonian matrix requiring only six quantum states to fullfil a half Boolean logical truth table. The QHC design rules open a nano-architectronic way of constructing Boolean logic gates inside a single molecule or atom by atom at the surface of a passivated semi-conductor.
Development of Boolean calculus and its application
NASA Technical Reports Server (NTRS)
Tapia, M. A.
1979-01-01
Formal procedures for synthesis of asynchronous sequential system using commercially available edge-sensitive flip-flops are developed. Boolean differential is defined. The exact number of compatible integrals of a Boolean differential were calculated.
NASA Technical Reports Server (NTRS)
Szallasi, Zoltan; Liang, Shoudan
2000-01-01
In this paper we show how Boolean genetic networks could be used to address complex problems in cancer biology. First, we describe a general strategy to generate Boolean genetic networks that incorporate all relevant biochemical and physiological parameters and cover all of their regulatory interactions in a deterministic manner. Second, we introduce 'realistic Boolean genetic networks' that produce time series measurements very similar to those detected in actual biological systems. Third, we outline a series of essential questions related to cancer biology and cancer therapy that could be addressed by the use of 'realistic Boolean genetic network' modeling.
Automatic query formulations in information retrieval.
Salton, G; Buckley, C; Fox, E A
1983-07-01
Modern information retrieval systems are designed to supply relevant information in response to requests received from the user population. In most retrieval environments the search requests consist of keywords, or index terms, interrelated by appropriate Boolean operators. Since it is difficult for untrained users to generate effective Boolean search requests, trained search intermediaries are normally used to translate original statements of user need into useful Boolean search formulations. Methods are introduced in this study which reduce the role of the search intermediaries by making it possible to generate Boolean search formulations completely automatically from natural language statements provided by the system patrons. Frequency considerations are used automatically to generate appropriate term combinations as well as Boolean connectives relating the terms. Methods are covered to produce automatic query formulations both in a standard Boolean logic system, as well as in an extended Boolean system in which the strict interpretation of the connectives is relaxed. Experimental results are supplied to evaluate the effectiveness of the automatic query formulation process, and methods are described for applying the automatic query formulation process in practice.
An Attractor-Based Complexity Measurement for Boolean Recurrent Neural Networks
Cabessa, Jérémie; Villa, Alessandro E. P.
2014-01-01
We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equivalence between Boolean recurrent neural networks and some specific class of -automata, and then translating the most refined classification of -automata to the Boolean neural network context. As a result, a hierarchical classification of Boolean neural networks based on their attractive dynamics is obtained, thus providing a novel refined attractor-based complexity measurement for Boolean recurrent neural networks. These results provide new theoretical insights to the computational and dynamical capabilities of neural networks according to their attractive potentialities. An application of our findings is illustrated by the analysis of the dynamics of a simplified model of the basal ganglia-thalamocortical network simulated by a Boolean recurrent neural network. This example shows the significance of measuring network complexity, and how our results bear new founding elements for the understanding of the complexity of real brain circuits. PMID:24727866
Proposed method to construct Boolean functions with maximum possible annihilator immunity
NASA Astrophysics Data System (ADS)
Goyal, Rajni; Panigrahi, Anupama; Bansal, Rohit
2017-07-01
Nonlinearity and Algebraic(annihilator) immunity are two core properties of a Boolean function because optimum values of Annihilator Immunity and nonlinearity are required to resist fast algebraic attack and differential cryptanalysis respectively. For a secure cypher system, Boolean function(S-Boxes) should resist maximum number of attacks. It is possible if a Boolean function has optimal trade-off among its properties. Before constructing Boolean functions, we fixed the criteria of our constructions based on its properties. In present work, our construction is based on annihilator immunity and nonlinearity. While keeping above facts in mind,, we have developed a multi-objective evolutionary approach based on NSGA-II and got the optimum value of annihilator immunity with good bound of nonlinearity. We have constructed balanced Boolean functions having the best trade-off among balancedness, Annihilator immunity and nonlinearity for 5, 6 and 7 variables by the proposed method.
ERIC Educational Resources Information Center
Hildreth, Charles R.
1983-01-01
This editorial addresses the issue of whether or not to provide free-text, keyword/boolean search capabilities in the information retrieval mechanisms of online public access catalogs and discusses online catalogs developed prior to 1980--keyword searching, phrase searching, and precoordination and postcoordination. (EJS)
Minimum energy control and optimal-satisfactory control of Boolean control network
NASA Astrophysics Data System (ADS)
Li, Fangfei; Lu, Xiwen
2013-12-01
In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.
Identifying a Probabilistic Boolean Threshold Network From Samples.
Melkman, Avraham A; Cheng, Xiaoqing; Ching, Wai-Ki; Akutsu, Tatsuya
2018-04-01
This paper studies the problem of exactly identifying the structure of a probabilistic Boolean network (PBN) from a given set of samples, where PBNs are probabilistic extensions of Boolean networks. Cheng et al. studied the problem while focusing on PBNs consisting of pairs of AND/OR functions. This paper considers PBNs consisting of Boolean threshold functions while focusing on those threshold functions that have unit coefficients. The treatment of Boolean threshold functions, and triplets and -tuplets of such functions, necessitates a deepening of the theoretical analyses. It is shown that wide classes of PBNs with such threshold functions can be exactly identified from samples under reasonable constraints, which include: 1) PBNs in which any number of threshold functions can be assigned provided that all have the same number of input variables and 2) PBNs consisting of pairs of threshold functions with different numbers of input variables. It is also shown that the problem of deciding the equivalence of two Boolean threshold functions is solvable in pseudopolynomial time but remains co-NP complete.
Adaptiveness in monotone pseudo-Boolean optimization and stochastic neural computation.
Grossi, Giuliano
2009-08-01
Hopfield neural network (HNN) is a nonlinear computational model successfully applied in finding near-optimal solutions of several difficult combinatorial problems. In many cases, the network energy function is obtained through a learning procedure so that its minima are states falling into a proper subspace (feasible region) of the search space. However, because of the network nonlinearity, a number of undesirable local energy minima emerge from the learning procedure, significantly effecting the network performance. In the neural model analyzed here, we combine both a penalty and a stochastic process in order to enhance the performance of a binary HNN. The penalty strategy allows us to gradually lead the search towards states representing feasible solutions, so avoiding oscillatory behaviors or asymptotically instable convergence. Presence of stochastic dynamics potentially prevents the network to fall into shallow local minima of the energy function, i.e., quite far from global optimum. Hence, for a given fixed network topology, the desired final distribution on the states can be reached by carefully modulating such process. The model uses pseudo-Boolean functions both to express problem constraints and cost function; a combination of these two functions is then interpreted as energy of the neural network. A wide variety of NP-hard problems fall in the class of problems that can be solved by the model at hand, particularly those having a monotonic quadratic pseudo-Boolean function as constraint function. That is, functions easily derived by closed algebraic expressions representing the constraint structure and easy (polynomial time) to maximize. We show the asymptotic convergence properties of this model characterizing its state space distribution at thermal equilibrium in terms of Markov chain and give evidence of its ability to find high quality solutions on benchmarks and randomly generated instances of two specific problems taken from the computational graph theory.
Griffin: A Tool for Symbolic Inference of Synchronous Boolean Molecular Networks.
Muñoz, Stalin; Carrillo, Miguel; Azpeitia, Eugenio; Rosenblueth, David A
2018-01-01
Boolean networks are important models of biochemical systems, located at the high end of the abstraction spectrum. A number of Boolean gene networks have been inferred following essentially the same method. Such a method first considers experimental data for a typically underdetermined "regulation" graph. Next, Boolean networks are inferred by using biological constraints to narrow the search space, such as a desired set of (fixed-point or cyclic) attractors. We describe Griffin , a computer tool enhancing this method. Griffin incorporates a number of well-established algorithms, such as Dubrova and Teslenko's algorithm for finding attractors in synchronous Boolean networks. In addition, a formal definition of regulation allows Griffin to employ "symbolic" techniques, able to represent both large sets of network states and Boolean constraints. We observe that when the set of attractors is required to be an exact set, prohibiting additional attractors, a naive Boolean coding of this constraint may be unfeasible. Such cases may be intractable even with symbolic methods, as the number of Boolean constraints may be astronomically large. To overcome this problem, we employ an Artificial Intelligence technique known as "clause learning" considerably increasing Griffin 's scalability. Without clause learning only toy examples prohibiting additional attractors are solvable: only one out of seven queries reported here is answered. With clause learning, by contrast, all seven queries are answered. We illustrate Griffin with three case studies drawn from the Arabidopsis thaliana literature. Griffin is available at: http://turing.iimas.unam.mx/griffin.
Boolean integral calculus for digital systems
NASA Technical Reports Server (NTRS)
Tucker, J. H.; Tapia, M. A.; Bennett, A. W.
1985-01-01
The concept of Boolean integration is introduced and developed. When the changes in a desired function are specified in terms of changes in its arguments, then ways of 'integrating' (i.e., realizing) the function, if it exists, are presented. Boolean integral calculus has applications in design of logic circuits.
A Comparison of Two Methods for Boolean Query Relevancy Feedback.
ERIC Educational Resources Information Center
Salton, G.; And Others
1984-01-01
Evaluates and compares two recently proposed automatic methods for relevance feedback of Boolean queries (Dillon method, which uses probabilistic approach as basis, and disjunctive normal form method). Conclusions are drawn concerning the use of effective feedback methods in a Boolean query environment. Nineteen references are included. (EJS)
Altered Micro-RNA Degradation Promotes Tumor Heterogeneity: A Result from Boolean Network Modeling.
Wu, Yunyi; Krueger, Gerhard R F; Wang, Guanyu
2016-02-01
Cancer heterogeneity may reflect differential dynamical outcomes of the regulatory network encompassing biomolecules at both transcriptional and post-transcriptional levels. In other words, differential gene-expression profiles may correspond to different stable steady states of a mathematical model for simulation of biomolecular networks. To test this hypothesis, we simplified a regulatory network that is important for soft-tissue sarcoma metastasis and heterogeneity, comprising of transcription factors, micro-RNAs, and signaling components of the NOTCH pathway. We then used a Boolean network model to simulate the dynamics of this network, and particularly investigated the consequences of differential miRNA degradation modes. We found that efficient miRNA degradation is crucial for sustaining a homogenous and healthy phenotype, while defective miRNA degradation may lead to multiple stable steady states and ultimately to carcinogenesis and heterogeneity. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.
Boolean Classes and Qualitative Inquiry. WCER Working Paper No. 2006-3
ERIC Educational Resources Information Center
Nathan, Mitchell J.; Jackson, Kristi
2006-01-01
The prominent role of Boolean classes in qualitative data analysis software is viewed by some as an encroachment of logical positivism on qualitative research methodology. The authors articulate an embodiment perspective, in which Boolean classes are viewed as conceptual metaphors for apprehending and manipulating data, concepts, and categories in…
Algebraic model checking for Boolean gene regulatory networks.
Tran, Quoc-Nam
2011-01-01
We present a computational method in which modular and Groebner bases (GB) computation in Boolean rings are used for solving problems in Boolean gene regulatory networks (BN). In contrast to other known algebraic approaches, the degree of intermediate polynomials during the calculation of Groebner bases using our method will never grow resulting in a significant improvement in running time and memory space consumption. We also show how calculation in temporal logic for model checking can be done by means of our direct and efficient Groebner basis computation in Boolean rings. We present our experimental results in finding attractors and control strategies of Boolean networks to illustrate our theoretical arguments. The results are promising. Our algebraic approach is more efficient than the state-of-the-art model checker NuSMV on BNs. More importantly, our approach finds all solutions for the BN problems.
E-Referencer: Transforming Boolean OPACs to Web Search Engines.
ERIC Educational Resources Information Center
Khoo, Christopher S. G.; Poo, Danny C. C.; Toh, Teck-Kang; Hong, Glenn
E-Referencer is an expert intermediary system for searching library online public access catalogs (OPACs) on the World Wide Web. It is implemented as a proxy server that mediates the interaction between the user and Boolean OPACs. It transforms a Boolean OPAC into a retrieval system with many of the search capabilities of Web search engines.…
Cut set-based risk and reliability analysis for arbitrarily interconnected networks
Wyss, Gregory D.
2000-01-01
Method for computing all-terminal reliability for arbitrarily interconnected networks such as the United States public switched telephone network. The method includes an efficient search algorithm to generate minimal cut sets for nonhierarchical networks directly from the network connectivity diagram. Efficiency of the search algorithm stems in part from its basis on only link failures. The method also includes a novel quantification scheme that likewise reduces computational effort associated with assessing network reliability based on traditional risk importance measures. Vast reductions in computational effort are realized since combinatorial expansion and subsequent Boolean reduction steps are eliminated through analysis of network segmentations using a technique of assuming node failures to occur on only one side of a break in the network, and repeating the technique for all minimal cut sets generated with the search algorithm. The method functions equally well for planar and non-planar networks.
Expected Number of Fixed Points in Boolean Networks with Arbitrary Topology.
Mori, Fumito; Mochizuki, Atsushi
2017-07-14
Boolean network models describe genetic, neural, and social dynamics in complex networks, where the dynamics depend generally on network topology. Fixed points in a genetic regulatory network are typically considered to correspond to cell types in an organism. We prove that the expected number of fixed points in a Boolean network, with Boolean functions drawn from probability distributions that are not required to be uniform or identical, is one, and is independent of network topology if only a feedback arc set satisfies a stochastic neutrality condition. We also demonstrate that the expected number is increased by the predominance of positive feedback in a cycle.
SETS. Set Equation Transformation System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Worrell, R.B.
1992-01-13
SETS is used for symbolic manipulation of Boolean equations, particularly the reduction of equations by the application of Boolean identities. It is a flexible and efficient tool for performing probabilistic risk analysis (PRA), vital area analysis, and common cause analysis. The equation manipulation capabilities of SETS can also be used to analyze noncoherent fault trees and determine prime implicants of Boolean functions, to verify circuit design implementation, to determine minimum cost fire protection requirements for nuclear reactor plants, to obtain solutions to combinatorial optimization problems with Boolean constraints, and to determine the susceptibility of a facility to unauthorized access throughmore » nullification of sensors in its protection system.« less
On spectral techniques in analysis of Boolean networks
NASA Astrophysics Data System (ADS)
Kesseli, Juha; Rämö, Pauli; Yli-Harja, Olli
2005-06-01
In this work we present results that can be used for analysis of Boolean networks. The results utilize Fourier spectra of the functions in the network. An accurate formula is given for Derrida plots of networks of finite size N based on a result on Boolean functions presented in another context. Derrida plots are widely used to examine the stability issues of Boolean networks. For the limit N→∞, we give a computationally simple form that can be used as a good approximation for rather small networks as well. A formula for Derrida plots of random Boolean networks (RBNs) presented earlier in the literature is given an alternative derivation. It is shown that the information contained in the Derrida plot is equal to the average Fourier spectrum of the functions in the network. In the case of random networks the mean Derrida plot can be obtained from the mean spectrum of the functions. The method is applied to real data by using the Boolean functions found in genetic regulatory networks of eukaryotic cells in an earlier study. Conventionally, Derrida plots and stability analysis have been computed with statistical sampling resulting in poorer accuracy.
Automatic Screening for Perturbations in Boolean Networks.
Schwab, Julian D; Kestler, Hans A
2018-01-01
A common approach to address biological questions in systems biology is to simulate regulatory mechanisms using dynamic models. Among others, Boolean networks can be used to model the dynamics of regulatory processes in biology. Boolean network models allow simulating the qualitative behavior of the modeled processes. A central objective in the simulation of Boolean networks is the computation of their long-term behavior-so-called attractors. These attractors are of special interest as they can often be linked to biologically relevant behaviors. Changing internal and external conditions can influence the long-term behavior of the Boolean network model. Perturbation of a Boolean network by stripping a component of the system or simulating a surplus of another element can lead to different attractors. Apparently, the number of possible perturbations and combinations of perturbations increases exponentially with the size of the network. Manually screening a set of possible components for combinations that have a desired effect on the long-term behavior can be very time consuming if not impossible. We developed a method to automatically screen for perturbations that lead to a user-specified change in the network's functioning. This method is implemented in the visual simulation framework ViSiBool utilizing satisfiability (SAT) solvers for fast exhaustive attractor search.
Boolean Minimization and Algebraic Factorization Procedures for Fully Testable Sequential Machines
1989-09-01
Boolean Minimization and Algebraic Factorization Procedures for Fully Testable Sequential Machines Srinivas Devadas and Kurt Keutzer F ( Abstract In this...Projects Agency under contract number N00014-87-K-0825. Author Information Devadas : Department of Electrical Engineering and Computer Science, Room 36...MA 02139; (617) 253-0292. 0 * Boolean Minimization and Algebraic Factorization Procedures for Fully Testable Sequential Machines Siivas Devadas
Stabilization of perturbed Boolean network attractors through compensatory interactions
2014-01-01
Background Understanding and ameliorating the effects of network damage are of significant interest, due in part to the variety of applications in which network damage is relevant. For example, the effects of genetic mutations can cascade through within-cell signaling and regulatory networks and alter the behavior of cells, possibly leading to a wide variety of diseases. The typical approach to mitigating network perturbations is to consider the compensatory activation or deactivation of system components. Here, we propose a complementary approach wherein interactions are instead modified to alter key regulatory functions and prevent the network damage from triggering a deregulatory cascade. Results We implement this approach in a Boolean dynamic framework, which has been shown to effectively model the behavior of biological regulatory and signaling networks. We show that the method can stabilize any single state (e.g., fixed point attractors or time-averaged representations of multi-state attractors) to be an attractor of the repaired network. We show that the approach is minimalistic in that few modifications are required to provide stability to a chosen attractor and specific in that interventions do not have undesired effects on the attractor. We apply the approach to random Boolean networks, and further show that the method can in some cases successfully repair synchronous limit cycles. We also apply the methodology to case studies from drought-induced signaling in plants and T-LGL leukemia and find that it is successful in both stabilizing desired behavior and in eliminating undesired outcomes. Code is made freely available through the software package BooleanNet. Conclusions The methodology introduced in this report offers a complementary way to manipulating node expression levels. A comprehensive approach to evaluating network manipulation should take an "all of the above" perspective; we anticipate that theoretical studies of interaction modification, coupled with empirical advances, will ultimately provide researchers with greater flexibility in influencing system behavior. PMID:24885780
On the inherent competition between valid and spurious inductive inferences in Boolean data
NASA Astrophysics Data System (ADS)
Andrecut, M.
Inductive inference is the process of extracting general rules from specific observations. This problem also arises in the analysis of biological networks, such as genetic regulatory networks, where the interactions are complex and the observations are incomplete. A typical task in these problems is to extract general interaction rules as combinations of Boolean covariates, that explain a measured response variable. The inductive inference process can be considered as an incompletely specified Boolean function synthesis problem. This incompleteness of the problem will also generate spurious inferences, which are a serious threat to valid inductive inference rules. Using random Boolean data as a null model, here we attempt to measure the competition between valid and spurious inductive inference rules from a given data set. We formulate two greedy search algorithms, which synthesize a given Boolean response variable in a sparse disjunct normal form, and respectively a sparse generalized algebraic normal form of the variables from the observation data, and we evaluate numerically their performance.
Autonomous Modeling, Statistical Complexity and Semi-annealed Treatment of Boolean Networks
NASA Astrophysics Data System (ADS)
Gong, Xinwei
This dissertation presents three studies on Boolean networks. Boolean networks are a class of mathematical systems consisting of interacting elements with binary state variables. Each element is a node with a Boolean logic gate, and the presence of interactions between any two nodes is represented by directed links. Boolean networks that implement the logic structures of real systems are studied as coarse-grained models of the real systems. Large random Boolean networks are studied with mean field approximations and used to provide a baseline of possible behaviors of large real systems. This dissertation presents one study of the former type, concerning the stable oscillation of a yeast cell-cycle oscillator, and two studies of the latter type, respectively concerning the statistical complexity of large random Boolean networks and an extension of traditional mean field techniques that accounts for the presence of short loops. In the cell-cycle oscillator study, a novel autonomous update scheme is introduced to study the stability of oscillations in small networks. A motif that corrects pulse-growing perturbations and a motif that grows pulses are identified. A combination of the two motifs is capable of sustaining stable oscillations. Examining a Boolean model of the yeast cell-cycle oscillator using an autonomous update scheme yields evidence that it is endowed with such a combination. Random Boolean networks are classified as ordered, critical or disordered based on their response to small perturbations. In the second study, random Boolean networks are taken as prototypical cases for the evaluation of two measures of complexity based on a criterion for optimal statistical prediction. One measure, defined for homogeneous systems, does not distinguish between the static spatial inhomogeneity in the ordered phase and the dynamical inhomogeneity in the disordered phase. A modification in which complexities of individual nodes are calculated yields vanishing complexity values for networks in the ordered and critical phases and for highly disordered networks, peaking somewhere in the disordered phase. Individual nodes with high complexity have, on average, a larger influence on the system dynamics. Lastly, a semi-annealed approximation that preserves the correlation between states at neighboring nodes is introduced to study a social game-inspired network model in which all links are bidirectional and all nodes have a self-input. The technique developed here is shown to yield accurate predictions of distribution of players' states, and accounts for some nontrivial collective behavior of game theoretic interest.
Floral Morphogenesis: Stochastic Explorations of a Gene Network Epigenetic Landscape
Aldana, Maximino; Benítez, Mariana; Cortes-Poza, Yuriria; Espinosa-Soto, Carlos; Hartasánchez, Diego A.; Lotto, R. Beau; Malkin, David; Escalera Santos, Gerardo J.; Padilla-Longoria, Pablo
2008-01-01
In contrast to the classical view of development as a preprogrammed and deterministic process, recent studies have demonstrated that stochastic perturbations of highly non-linear systems may underlie the emergence and stability of biological patterns. Herein, we address the question of whether noise contributes to the generation of the stereotypical temporal pattern in gene expression during flower development. We modeled the regulatory network of organ identity genes in the Arabidopsis thaliana flower as a stochastic system. This network has previously been shown to converge to ten fixed-point attractors, each with gene expression arrays that characterize inflorescence cells and primordial cells of sepals, petals, stamens, and carpels. The network used is binary, and the logical rules that govern its dynamics are grounded in experimental evidence. We introduced different levels of uncertainty in the updating rules of the network. Interestingly, for a level of noise of around 0.5–10%, the system exhibited a sequence of transitions among attractors that mimics the sequence of gene activation configurations observed in real flowers. We also implemented the gene regulatory network as a continuous system using the Glass model of differential equations, that can be considered as a first approximation of kinetic-reaction equations, but which are not necessarily equivalent to the Boolean model. Interestingly, the Glass dynamics recover a temporal sequence of attractors, that is qualitatively similar, although not identical, to that obtained using the Boolean model. Thus, time ordering in the emergence of cell-fate patterns is not an artifact of synchronous updating in the Boolean model. Therefore, our model provides a novel explanation for the emergence and robustness of the ubiquitous temporal pattern of floral organ specification. It also constitutes a new approach to understanding morphogenesis, providing predictions on the population dynamics of cells with different genetic configurations during development. PMID:18978941
An Improvement to a Multi-Client Searchable Encryption Scheme for Boolean Queries.
Jiang, Han; Li, Xue; Xu, Qiuliang
2016-12-01
The migration of e-health systems to the cloud computing brings huge benefits, as same as some security risks. Searchable Encryption(SE) is a cryptography encryption scheme that can protect the confidentiality of data and utilize the encrypted data at the same time. The SE scheme proposed by Cash et al. in Crypto2013 and its follow-up work in CCS2013 are most practical SE Scheme that support Boolean queries at present. In their scheme, the data user has to generate the search tokens by the counter number one by one and interact with server repeatedly, until he meets the correct one, or goes through plenty of tokens to illustrate that there is no search result. In this paper, we make an improvement to their scheme. We allow server to send back some information and help the user to generate exact search token in the search phase. In our scheme, there are only two round interaction between server and user, and the search token has [Formula: see text] elements, where n is the keywords number in query expression, and [Formula: see text] is the minimum documents number that contains one of keyword in query expression, and the computation cost of server is [Formula: see text] modular exponentiation operation.
Computing preimages of Boolean networks.
Klotz, Johannes; Bossert, Martin; Schober, Steffen
2013-01-01
In this paper we present an algorithm based on the sum-product algorithm that finds elements in the preimage of a feed-forward Boolean networks given an output of the network. Our probabilistic method runs in linear time with respect to the number of nodes in the network. We evaluate our algorithm for randomly constructed Boolean networks and a regulatory network of Escherichia coli and found that it gives a valid solution in most cases.
Ahnert, S E; Fink, T M A
2016-07-01
Network motifs have been studied extensively over the past decade, and certain motifs, such as the feed-forward loop, play an important role in regulatory networks. Recent studies have used Boolean network motifs to explore the link between form and function in gene regulatory networks and have found that the structure of a motif does not strongly determine its function, if this is defined in terms of the gene expression patterns the motif can produce. Here, we offer a different, higher-level definition of the 'function' of a motif, in terms of two fundamental properties of its dynamical state space as a Boolean network. One is the basin entropy, which is a complexity measure of the dynamics of Boolean networks. The other is the diversity of cyclic attractor lengths that a given motif can produce. Using these two measures, we examine all 104 topologically distinct three-node motifs and show that the structural properties of a motif, such as the presence of feedback loops and feed-forward loops, predict fundamental characteristics of its dynamical state space, which in turn determine aspects of its functional versatility. We also show that these higher-level properties have a direct bearing on real regulatory networks, as both basin entropy and cycle length diversity show a close correspondence with the prevalence, in neural and genetic regulatory networks, of the 13 connected motifs without self-interactions that have been studied extensively in the literature. © 2016 The Authors.
Bánfai, Balázs; Porció, Roland; Kovács, Tibor
2014-01-01
SNOMED CT is a vital component in the future of semantic interoperability in healthcare as it provides the meaning to EHRs via its semantically rich, controlled terminology. Communicating the concepts of this terminology to both humans and machines is crucial therefore formal guidelines for diagram and expression representations have been developed by the curators of SNOMED CT. This paper presents a novel, model-based approach to implementing these guidelines that allows simultaneous editing of a concept via both diagram and expression editors. The implemented extensible software component can be embedded both both desktop and web applications.
Dragović, Ivana; Turajlić, Nina; Pilčević, Dejan; Petrović, Bratislav; Radojević, Dragan
2015-01-01
Fuzzy inference systems (FIS) enable automated assessment and reasoning in a logically consistent manner akin to the way in which humans reason. However, since no conventional fuzzy set theory is in the Boolean frame, it is proposed that Boolean consistent fuzzy logic should be used in the evaluation of rules. The main distinction of this approach is that it requires the execution of a set of structural transformations before the actual values can be introduced, which can, in certain cases, lead to different results. While a Boolean consistent FIS could be used for establishing the diagnostic criteria for any given disease, in this paper it is applied for determining the likelihood of peritonitis, as the leading complication of peritoneal dialysis (PD). Given that patients could be located far away from healthcare institutions (as peritoneal dialysis is a form of home dialysis) the proposed Boolean consistent FIS would enable patients to easily estimate the likelihood of them having peritonitis (where a high likelihood would suggest that prompt treatment is indicated), when medical experts are not close at hand. PMID:27069500
Exploiting Surroundedness for Saliency Detection: A Boolean Map Approach.
Zhang, Jianming; Sclaroff, Stan
2016-05-01
We demonstrate the usefulness of surroundedness for eye fixation prediction by proposing a Boolean Map based Saliency model (BMS). In our formulation, an image is characterized by a set of binary images, which are generated by randomly thresholding the image's feature maps in a whitened feature space. Based on a Gestalt principle of figure-ground segregation, BMS computes a saliency map by discovering surrounded regions via topological analysis of Boolean maps. Furthermore, we draw a connection between BMS and the Minimum Barrier Distance to provide insight into why and how BMS can properly captures the surroundedness cue via Boolean maps. The strength of BMS is verified by its simplicity, efficiency and superior performance compared with 10 state-of-the-art methods on seven eye tracking benchmark datasets.
Network dynamics and systems biology
NASA Astrophysics Data System (ADS)
Norrell, Johannes A.
The physics of complex systems has grown considerably as a field in recent decades, largely due to improved computational technology and increased availability of systems level data. One area in which physics is of growing relevance is molecular biology. A new field, systems biology, investigates features of biological systems as a whole, a strategy of particular importance for understanding emergent properties that result from a complex network of interactions. Due to the complicated nature of the systems under study, the physics of complex systems has a significant role to play in elucidating the collective behavior. In this dissertation, we explore three problems in the physics of complex systems, motivated in part by systems biology. The first of these concerns the applicability of Boolean models as an approximation of continuous systems. Studies of gene regulatory networks have employed both continuous and Boolean models to analyze the system dynamics, and the two have been found produce similar results in the cases analyzed. We ask whether or not Boolean models can generically reproduce the qualitative attractor dynamics of networks of continuously valued elements. Using a combination of analytical techniques and numerical simulations, we find that continuous networks exhibit two effects---an asymmetry between on and off states, and a decaying memory of events in each element's inputs---that are absent from synchronously updated Boolean models. We show that in simple loops these effects produce exactly the attractors that one would predict with an analysis of the stability of Boolean attractors, but in slightly more complicated topologies, they can destabilize solutions that are stable in the Boolean approximation, and can stabilize new attractors. Second, we investigate ensembles of large, random networks. Of particular interest is the transition between ordered and disordered dynamics, which is well characterized in Boolean systems. Networks at the transition point, called critical, exhibit many of the features of regulatory networks, and recent studies suggest that some specific regulatory networks are indeed near-critical. We ask whether certain statistical measures of the ensemble behavior of large continuous networks are reproduced by Boolean models. We find that, in spite of the lack of correspondence between attractors observed in smaller systems, the statistical characterization given by the continuous and Boolean models show close agreement, and the transition between order and disorder known in Boolean systems can occur in continuous systems as well. One effect that is not present in Boolean systems, the failure of information to propagate down chains of elements of arbitrary length, is present in a class of continuous networks. In these systems, a modified Boolean theory that takes into account the collective effect of propagation failure on chains throughout the network gives a good description of the observed behavior. We find that propagation failure pushes the system toward greater order, resulting in a partial or complete suppression of the disordered phase. Finally, we explore a dynamical process of direct biological relevance: asymmetric cell division in A. thaliana. The long term goal is to develop a model for the process that accurately accounts for both wild type and mutant behavior. To contribute to this endeavor, we use confocal microscopy to image roots in a SHORT-ROOT inducible mutant. We compute correlation functions between the locations of asymmetrically divided cells, and we construct stochastic models based on a few simple assumptions that accurately predict the non-zero correlations. Our result shows that intracellular processes alone cannot be responsible for the observed divisions, and that an intercell signaling mechanism could account for the measured correlations.
Theory and calculus of cubical complexes
NASA Technical Reports Server (NTRS)
Perlman, M.
1973-01-01
Combination switching networks with multiple outputs may be represented by Boolean functions. Report has been prepared which describes derivation and use of extraction algorithm that may be adapted to simplification of such simultaneous Boolean functions.
ERIC Educational Resources Information Center
Bossé, Michael J.; Adu-Gyamfi, Kwaku; Chandler, Kayla; Lynch-Davis, Kathleen
2016-01-01
Dynamic mathematical environments allow users to reify mathematical concepts through multiple representations, transform mathematical relations and organically explore mathematical properties, investigate integrated mathematics, and develop conceptual understanding. Herein, we integrate Boolean algebra, the functionalities of a dynamic…
... Boolean useRights, FileShare share, Int32 bufferSize, FileOptions options, SECURITY_ATTRIBUTES secAttrs, String msgPath, Boolean bFromProxy) at System.IO.FileStream..ctor(String path, FileMode mode, FileAccess ...
Complete all-optical processing polarization-based binary logic gates and optical processors.
Zaghloul, Y A; Zaghloul, A R M
2006-10-16
We present a complete all-optical-processing polarization-based binary-logic system, by which any logic gate or processor can be implemented. Following the new polarization-based logic presented in [Opt. Express 14, 7253 (2006)], we develop a new parallel processing technique that allows for the creation of all-optical-processing gates that produce a unique output either logic 1 or 0 only once in a truth table, and those that do not. This representation allows for the implementation of simple unforced OR, AND, XOR, XNOR, inverter, and more importantly NAND and NOR gates that can be used independently to represent any Boolean expression or function. In addition, the concept of a generalized gate is presented which opens the door for reconfigurable optical processors and programmable optical logic gates. Furthermore, the new design is completely compatible with the old one presented in [Opt. Express 14, 7253 (2006)], and with current semiconductor based devices. The gates can be cascaded, where the information is always on the laser beam. The polarization of the beam, and not its intensity, carries the information. The new methodology allows for the creation of multiple-input-multiple-output processors that implement, by itself, any Boolean function, such as specialized or non-specialized microprocessors. Three all-optical architectures are presented: orthoparallel optical logic architecture for all known and unknown binary gates, singlebranch architecture for only XOR and XNOR gates, and the railroad (RR) architecture for polarization optical processors (POP). All the control inputs are applied simultaneously leading to a single time lag which leads to a very-fast and glitch-immune POP. A simple and easy-to-follow step-by-step algorithm is provided for the POP, and design reduction methodologies are briefly discussed. The algorithm lends itself systematically to software programming and computer-assisted design. As examples, designs of all binary gates, multiple-input gates, and sequential and non-sequential Boolean expressions are presented and discussed. The operation of each design is simply understood by a bullet train traveling at the speed of light on a railroad system preconditioned by the crossover states predetermined by the control inputs. The presented designs allow for optical processing of the information eliminating the need to convert it, back and forth, to an electronic signal for processing purposes. All gates with a truth table, including for example Fredkin, Toffoli, testable reversible logic, and threshold logic gates, can be designed and implemented using the railroad architecture. That includes any future gates not known today. Those designs and the quantum gates are not discussed in this paper.
Fast Formal Analysis of Requirements via "Topoi Diagrams"
NASA Technical Reports Server (NTRS)
Menzies, Tim; Powell, John; Houle, Michael E.; Kelly, John C. (Technical Monitor)
2001-01-01
Early testing of requirements can decrease the cost of removing errors in software projects. However, unless done carefully, that testing process can significantly add to the cost of requirements analysis. We show here that requirements expressed as topoi diagrams can be built and tested cheaply using our SP2 algorithm, the formal temporal properties of a large class of topoi can be proven very quickly, in time nearly linear in the number of nodes and edges in the diagram. There are two limitations to our approach. Firstly, topoi diagrams cannot express certain complex concepts such as iteration and sub-routine calls. Hence, our approach is more useful for requirements engineering than for traditional model checking domains. Secondly, out approach is better for exploring the temporal occurrence of properties than the temporal ordering of properties. Within these restrictions, we can express a useful range of concepts currently seen in requirements engineering, and a wide range of interesting temporal properties.
Do health technology assessments comply with QUOROM diagram guidance? An empirical study.
Hind, Daniel; Booth, Andrew
2007-11-20
The Quality of Reporting of Meta-analyses (QUOROM) statement provides guidance for improving the quality of reporting of systematic reviews and meta-analyses. To make the process of study selection transparent it recommends "a flow diagram providing information about the number of RCTs identified, included, and excluded and the reasons for excluding them". We undertook an empirical study to identify the extent of compliance in the UK Health Technology Assessment (HTA) programme. We searched Medline to retrieve all systematic reviews of therapeutic interventions in the HTA monograph series published from 2001 to 2005. Two researchers recorded whether each study contained a meta-analysis of controlled trials, whether a QUOROM flow diagram was presented and, if so, whether it expressed the relationship between the number of citations and the number of studies. We used Cohen's kappa to test inter-rater reliability. 87 systematic reviews were retrieved. There was good and excellent inter-rater reliability for, respectively, whether a review contained a meta-analysis and whether each diagram contained a citation-to-study relationship. 49% of systematic reviews used a study selection flow diagram. When only systematic reviews containing a meta-analysis were analysed, compliance was only 32%. Only 20 studies (23% of all systematic reviews; 43% of those having a study selection diagram) had a diagram which expressed the relationship between citations and studies. Compliance with the recommendations of the QUOROM statement is not universal in systematic reviews or meta-analyses. Flow diagrams make the conduct of study selection transparent only if the relationship between citations and studies is clearly expressed. Reviewers should understand what they are counting: citations, papers, studies and trials are fundamentally different concepts which should not be confused in a diagram.
Sanchez, Robersy; Grau, Ricardo
2005-09-01
A Boolean structure of the genetic code where Boolean deductions have biological and physicochemical meanings was discussed in a previous paper. Now, from these Boolean deductions we propose to define the value of amino acid information in order to consider the genetic information system as a communication system and to introduce the semantic content of information ignored by the conventional information theory. In this proposal, the value of amino acid information is proportional to the molecular weight of amino acids with a proportional constant of about 1.96 x 10(25) bits per kg. In addition to this, for the experimental estimations of the minimum energy dissipation in genetic logic operations, we present two postulates: (1) the energy Ei (i=1,2,...,20) of amino acids in the messages conveyed by proteins is proportional to the value of information, and (2) amino acids are distributed according to their energy Ei so the amino acid population in proteins follows a Boltzmann distribution. Specifically, in the genetic message carried by the DNA from the genomes of living organisms, we found that the minimum energy dissipation in genetic logic operations was close to kTLn(2) joules per bit.
Lavrova, Anastasia I; Postnikov, Eugene B; Zyubin, Andrey Yu; Babak, Svetlana V
2017-04-01
We consider two approaches to modelling the cell metabolism of 6-mercaptopurine, one of the important chemotherapy drugs used for treating acute lymphocytic leukaemia: kinetic ordinary differential equations, and Boolean networks supplied with one controlling node, which takes continual values. We analyse their interplay with respect to taking into account ATP concentration as a key parameter of switching between different pathways. It is shown that the Boolean networks, which allow avoiding the complexity of general kinetic modelling, preserve the possibility of reproducing the principal switching mechanism.
Improving the quantum cost of reversible Boolean functions using reorder algorithm
NASA Astrophysics Data System (ADS)
Ahmed, Taghreed; Younes, Ahmed; Elsayed, Ashraf
2018-05-01
This paper introduces a novel algorithm to synthesize a low-cost reversible circuits for any Boolean function with n inputs represented as a Positive Polarity Reed-Muller expansion. The proposed algorithm applies a predefined rules to reorder the terms in the function to minimize the multi-calculation of common parts of the Boolean function to decrease the quantum cost of the reversible circuit. The paper achieves a decrease in the quantum cost and/or the circuit length, on average, when compared with relevant work in the literature.
Volumetric T-spline Construction Using Boolean Operations
2013-07-01
SUBTITLE Volumetric T-spline Construction Using Boolean Operations 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d...Acknowledgements The work of L. Liu and Y. Zhang was supported by ONR-YIP award N00014- 10-1-0698 and an ONR Grant N00014-08-1-0653. T. J.R. Hughes was sup- 16...T-spline Construction Using Boolean Operations 17 ported by ONR Grant N00014-08-1-0992, NSF GOALI CMI-0700807/0700204, NSF CMMI-1101007 and a SINTEF
PSPVDC: An Adaptation of the PSP that Incorporates Verified Design by Contract
2013-05-01
characteristics mentioned above, including the following: • Java Modeling Language (JML) implements DbC in Java . VDbC can then be carried out using tools like...Extended Static Checking (ESC/ Java ) [Cok 2005] or TACO [Galeotti 2010]. • Perfect Developer [Crocker 2003] is a specification and modeling language...These are written in the language employed in the environment (e.g., as Java Boolean expressions, if JML is used) which we call the carrier lan
Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures
NASA Technical Reports Server (NTRS)
Liang, Shoudan; Fuhrman, Stefanie; Somogyi, Roland
1998-01-01
Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.
Dynamic Network-Based Epistasis Analysis: Boolean Examples
Azpeitia, Eugenio; Benítez, Mariana; Padilla-Longoria, Pablo; Espinosa-Soto, Carlos; Alvarez-Buylla, Elena R.
2011-01-01
In this article we focus on how the hierarchical and single-path assumptions of epistasis analysis can bias the inference of gene regulatory networks. Here we emphasize the critical importance of dynamic analyses, and specifically illustrate the use of Boolean network models. Epistasis in a broad sense refers to gene interactions, however, as originally proposed by Bateson, epistasis is defined as the blocking of a particular allelic effect due to the effect of another allele at a different locus (herein, classical epistasis). Classical epistasis analysis has proven powerful and useful, allowing researchers to infer and assign directionality to gene interactions. As larger data sets are becoming available, the analysis of classical epistasis is being complemented with computer science tools and system biology approaches. We show that when the hierarchical and single-path assumptions are not met in classical epistasis analysis, the access to relevant information and the correct inference of gene interaction topologies is hindered, and it becomes necessary to consider the temporal dynamics of gene interactions. The use of dynamical networks can overcome these limitations. We particularly focus on the use of Boolean networks that, like classical epistasis analysis, relies on logical formalisms, and hence can complement classical epistasis analysis and relax its assumptions. We develop a couple of theoretical examples and analyze them from a dynamic Boolean network model perspective. Boolean networks could help to guide additional experiments and discern among alternative regulatory schemes that would be impossible or difficult to infer without the elimination of these assumption from the classical epistasis analysis. We also use examples from the literature to show how a Boolean network-based approach has resolved ambiguities and guided epistasis analysis. Our article complements previous accounts, not only by focusing on the implications of the hierarchical and single-path assumption, but also by demonstrating the importance of considering temporal dynamics, and specifically introducing the usefulness of Boolean network models and also reviewing some key properties of network approaches. PMID:22645556
Analytical expressions for stability regions in the Ince-Strutt diagram of Mathieu equation
NASA Astrophysics Data System (ADS)
Butikov, Eugene I.
2018-04-01
Simple analytical expressions are suggested for transition curves that separate, in the Ince-Strutt diagram, different types of solutions to the famous Mathieu equation. The derivations of these expressions in this paper rely on physically meaningful periodic solutions describing various regular motions of a familiar nonlinear mechanical system—a rigid planar pendulum with a vertically oscillating pivot. The paper is accompanied by a relevant simulation program.
Acoustic logic gates and Boolean operation based on self-collimating acoustic beams
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Ting; Xu, Jian-yi; Cheng, Ying, E-mail: chengying@nju.edu.cn
2015-03-16
The reveal of self-collimation effect in two-dimensional (2D) photonic or acoustic crystals has opened up possibilities for signal manipulation. In this paper, we have proposed acoustic logic gates based on the linear interference of self-collimated beams in 2D sonic crystals (SCs) with line-defects. The line defects on the diagonal of the 2D square SCs are actually functioning as a 3 dB splitter. By adjusting the phase difference between two input signals, the basic Boolean logic functions such as XOR, OR, AND, and NOT are achieved both theoretically and experimentally. Due to the non-diffracting property of self-collimation beams, more complex Boolean logicmore » and algorithms such as NAND, NOR, and XNOR can be realized by cascading the basic logic gates. The achievement of acoustic logic gates and Boolean operation provides a promising approach for acoustic signal computing and manipulations.« less
Wang, Yuhao; Li, Xin; Xu, Kai; Ren, Fengbo; Yu, Hao
2017-04-01
Compressive sensing is widely used in biomedical applications, and the sampling matrix plays a critical role on both quality and power consumption of signal acquisition. It projects a high-dimensional vector of data into a low-dimensional subspace by matrix-vector multiplication. An optimal sampling matrix can ensure accurate data reconstruction and/or high compression ratio. Most existing optimization methods can only produce real-valued embedding matrices that result in large energy consumption during data acquisition. In this paper, we propose an efficient method that finds an optimal Boolean sampling matrix in order to reduce the energy consumption. Compared to random Boolean embedding, our data-driven Boolean sampling matrix can improve the image recovery quality by 9 dB. Moreover, in terms of sampling hardware complexity, it reduces the energy consumption by 4.6× and the silicon area by 1.9× over the data-driven real-valued embedding.
Sun, Mengyang; Cheng, Xianrui; Socolar, Joshua E S
2013-06-01
A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.
Li, X Y; Yang, G W; Zheng, D S; Guo, W S; Hung, W N N
2015-04-28
Genetic regulatory networks are the key to understanding biochemical systems. One condition of the genetic regulatory network under different living environments can be modeled as a synchronous Boolean network. The attractors of these Boolean networks will help biologists to identify determinant and stable factors. Existing methods identify attractors based on a random initial state or the entire state simultaneously. They cannot identify the fixed length attractors directly. The complexity of including time increases exponentially with respect to the attractor number and length of attractors. This study used the bounded model checking to quickly locate fixed length attractors. Based on the SAT solver, we propose a new algorithm for efficiently computing the fixed length attractors, which is more suitable for large Boolean networks and numerous attractors' networks. After comparison using the tool BooleNet, empirical experiments involving biochemical systems demonstrated the feasibility and efficiency of our approach.
BoolNet--an R package for generation, reconstruction and analysis of Boolean networks.
Müssel, Christoph; Hopfensitz, Martin; Kestler, Hans A
2010-05-15
As the study of information processing in living cells moves from individual pathways to complex regulatory networks, mathematical models and simulation become indispensable tools for analyzing the complex behavior of such networks and can provide deep insights into the functioning of cells. The dynamics of gene expression, for example, can be modeled with Boolean networks (BNs). These are mathematical models of low complexity, but have the advantage of being able to capture essential properties of gene-regulatory networks. However, current implementations of BNs only focus on different sub-aspects of this model and do not allow for a seamless integration into existing preprocessing pipelines. BoolNet efficiently integrates methods for synchronous, asynchronous and probabilistic BNs. This includes reconstructing networks from time series, generating random networks, robustness analysis via perturbation, Markov chain simulations, and identification and visualization of attractors. The package BoolNet is freely available from the R project at http://cran.r-project.org/ or http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/boolnet/ under Artistic License 2.0. hans.kestler@uni-ulm.de Supplementary data are available at Bioinformatics online.
Spin wave Feynman diagram vertex computation package
NASA Astrophysics Data System (ADS)
Price, Alexander; Javernick, Philip; Datta, Trinanjan
Spin wave theory is a well-established theoretical technique that can correctly predict the physical behavior of ordered magnetic states. However, computing the effects of an interacting spin wave theory incorporating magnons involve a laborious by hand derivation of Feynman diagram vertices. The process is tedious and time consuming. Hence, to improve productivity and have another means to check the analytical calculations, we have devised a Feynman Diagram Vertex Computation package. In this talk, we will describe our research group's effort to implement a Mathematica based symbolic Feynman diagram vertex computation package that computes spin wave vertices. Utilizing the non-commutative algebra package NCAlgebra as an add-on to Mathematica, symbolic expressions for the Feynman diagram vertices of a Heisenberg quantum antiferromagnet are obtained. Our existing code reproduces the well-known expressions of a nearest neighbor square lattice Heisenberg model. We also discuss the case of a triangular lattice Heisenberg model where non collinear terms contribute to the vertex interactions.
A transition calculus for Boolean functions. [logic circuit analysis
NASA Technical Reports Server (NTRS)
Tucker, J. H.; Bennett, A. W.
1974-01-01
A transition calculus is presented for analyzing the effect of input changes on the output of logic circuits. The method is closely related to the Boolean difference, but it is more powerful. Both differentiation and integration are considered.
Risk assessment techniques with applicability in marine engineering
NASA Astrophysics Data System (ADS)
Rudenko, E.; Panaitescu, F. V.; Panaitescu, M.
2015-11-01
Nowadays risk management is a carefully planned process. The task of risk management is organically woven into the general problem of increasing the efficiency of business. Passive attitude to risk and awareness of its existence are replaced by active management techniques. Risk assessment is one of the most important stages of risk management, since for risk management it is necessary first to analyze and evaluate risk. There are many definitions of this notion but in general case risk assessment refers to the systematic process of identifying the factors and types of risk and their quantitative assessment, i.e. risk analysis methodology combines mutually complementary quantitative and qualitative approaches. Purpose of the work: In this paper we will consider as risk assessment technique Fault Tree analysis (FTA). The objectives are: understand purpose of FTA, understand and apply rules of Boolean algebra, analyse a simple system using FTA, FTA advantages and disadvantages. Research and methodology: The main purpose is to help identify potential causes of system failures before the failures actually occur. We can evaluate the probability of the Top event.The steps of this analize are: the system's examination from Top to Down, the use of symbols to represent events, the use of mathematical tools for critical areas, the use of Fault tree logic diagrams to identify the cause of the Top event. Results: In the finally of study it will be obtained: critical areas, Fault tree logical diagrams and the probability of the Top event. These results can be used for the risk assessment analyses.
Penguin-like diagrams from the standard model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ping, Chia Swee
2015-04-24
The Standard Model is highly successful in describing the interactions of leptons and quarks. There are, however, rare processes that involve higher order effects in electroweak interactions. One specific class of processes is the penguin-like diagram. Such class of diagrams involves the neutral change of quark flavours accompanied by the emission of a gluon (gluon penguin), a photon (photon penguin), a gluon and a photon (gluon-photon penguin), a Z-boson (Z penguin), or a Higgs-boson (Higgs penguin). Such diagrams do not arise at the tree level in the Standard Model. They are, however, induced by one-loop effects. In this paper, wemore » present an exact calculation of the penguin diagram vertices in the ‘tHooft-Feynman gauge. Renormalization of the vertex is effected by a prescription by Chia and Chong which gives an expression for the counter term identical to that obtained by employing Ward-Takahashi identity. The on-shell vertex functions for the penguin diagram vertices are obtained. The various penguin diagram vertex functions are related to one another via Ward-Takahashi identity. From these, a set of relations is obtained connecting the vertex form factors of various penguin diagrams. Explicit expressions for the gluon-photon penguin vertex form factors are obtained, and their contributions to the flavor changing processes estimated.« less
Characterizing short-term stability for Boolean networks over any distribution of transfer functions
Seshadhri, C.; Smith, Andrew M.; Vorobeychik, Yevgeniy; ...
2016-07-05
Here we present a characterization of short-term stability of random Boolean networks under arbitrary distributions of transfer functions. Given any distribution of transfer functions for a random Boolean network, we present a formula that decides whether short-term chaos (damage spreading) will happen. We provide a formal proof for this formula, and empirically show that its predictions are accurate. Previous work only works for special cases of balanced families. Finally, it has been observed that these characterizations fail for unbalanced families, yet such families are widespread in real biological networks.
A Note on a Sampling Theorem for Functions over GF(q)n Domain
NASA Astrophysics Data System (ADS)
Ukita, Yoshifumi; Saito, Tomohiko; Matsushima, Toshiyasu; Hirasawa, Shigeichi
In digital signal processing, the sampling theorem states that any real valued function ƒ can be reconstructed from a sequence of values of ƒ that are discretely sampled with a frequency at least twice as high as the maximum frequency of the spectrum of ƒ. This theorem can also be applied to functions over finite domain. Then, the range of frequencies of ƒ can be expressed in more detail by using a bounded set instead of the maximum frequency. A function whose range of frequencies is confined to a bounded set is referred to as bandlimited function. And a sampling theorem for bandlimited functions over Boolean domain has been obtained. Here, it is important to obtain a sampling theorem for bandlimited functions not only over Boolean domain (GF(q)n domain) but also over GF(q)n domain, where q is a prime power and GF(q) is Galois field of order q. For example, in experimental designs, although the model can be expressed as a linear combination of the Fourier basis functions and the levels of each factor can be represented by GF(q)n, the number of levels often take a value greater than two. However, the sampling theorem for bandlimited functions over GF(q)n domain has not been obtained. On the other hand, the sampling points are closely related to the codewords of a linear code. However, the relation between the parity check matrix of a linear code and any distinct error vectors has not been obtained, although it is necessary for understanding the meaning of the sampling theorem for bandlimited functions. In this paper, we generalize the sampling theorem for bandlimited functions over Boolean domain to a sampling theorem for bandlimited functions over GF(q)n domain. We also present a theorem for the relation between the parity check matrix of a linear code and any distinct error vectors. Lastly, we clarify the relation between the sampling theorem for functions over GF(q)n domain and linear codes.
Cryptographic Properties of Monotone Boolean Functions
2016-01-01
Algebraic attacks on stream ciphers with linear feedback, in: Advances in Cryptology (Eurocrypt 2003), Lecture Notes in Comput. Sci. 2656, Springer, Berlin...spectrum, algebraic immu- nity MSC 2010: 06E30, 94C10, 94A60, 11T71, 05E99 || Communicated by: Carlo Blundo 1 Introduction Let F 2 be the prime eld of...7]. For the reader’s convenience, we recall some basic notions below. Any f ∈ Bn can be expressed in algebraic normal form (ANF) as f(x 1 , x 2
Spinning AdS loop diagrams: two point functions
NASA Astrophysics Data System (ADS)
Giombi, Simone; Sleight, Charlotte; Taronna, Massimo
2018-06-01
We develop a systematic approach to evaluating AdS loop amplitudes with spinning legs based on the spectral (or "split") representation of bulk-to-bulk propagators, which re-expresses loop diagrams in terms of spectral integrals and higher-point tree diagrams. In this work we focus on 2pt one-loop Witten diagrams involving totally symmetric fields of arbitrary mass and integer spin. As an application of this framework, we study the contribution to the anomalous dimension of higher-spin currents generated by bubble diagrams in higher-spin gauge theories on AdS.
Quantum algorithms on Walsh transform and Hamming distance for Boolean functions
NASA Astrophysics Data System (ADS)
Xie, Zhengwei; Qiu, Daowen; Cai, Guangya
2018-06-01
Walsh spectrum or Walsh transform is an alternative description of Boolean functions. In this paper, we explore quantum algorithms to approximate the absolute value of Walsh transform W_f at a single point z0 (i.e., |W_f(z0)|) for n-variable Boolean functions with probability at least 8/π 2 using the number of O(1/|W_f(z_{0)|ɛ }) queries, promised that the accuracy is ɛ , while the best known classical algorithm requires O(2n) queries. The Hamming distance between Boolean functions is used to study the linearity testing and other important problems. We take advantage of Walsh transform to calculate the Hamming distance between two n-variable Boolean functions f and g using O(1) queries in some cases. Then, we exploit another quantum algorithm which converts computing Hamming distance between two Boolean functions to quantum amplitude estimation (i.e., approximate counting). If Ham(f,g)=t≠0, we can approximately compute Ham( f, g) with probability at least 2/3 by combining our algorithm and {Approx-Count(f,ɛ ) algorithm} using the expected number of Θ( √{N/(\\lfloor ɛ t\\rfloor +1)}+√{t(N-t)}/\\lfloor ɛ t\\rfloor +1) queries, promised that the accuracy is ɛ . Moreover, our algorithm is optimal, while the exact query complexity for the above problem is Θ(N) and the query complexity with the accuracy ɛ is O(1/ɛ 2N/(t+1)) in classical algorithm, where N=2n. Finally, we present three exact quantum query algorithms for two promise problems on Hamming distance using O(1) queries, while any classical deterministic algorithm solving the problem uses Ω(2n) queries.
Development of Boolean calculus and its applications. [digital systems design
NASA Technical Reports Server (NTRS)
Tapia, M. A.
1980-01-01
The development of Boolean calculus for its application to developing digital system design methodologies that would reduce system complexity, size, cost, speed, power requirements, etc., is discussed. Synthesis procedures for logic circuits are examined particularly asynchronous circuits using clock triggered flip flops.
Advanced Feedback Methods in Information Retrieval.
ERIC Educational Resources Information Center
Salton, G.; And Others
1985-01-01
In this study, automatic feedback techniques are applied to Boolean query statements in online information retrieval to generate improved query statements based on information contained in previously retrieved documents. Feedback operations are carried out using conventional Boolean logic and extended logic. Experimental output is included to…
Compact universal logic gates realized using quantization of current in nanodevices.
Zhang, Wancheng; Wu, Nan-Jian; Yang, Fuhua
2007-12-12
This paper proposes novel universal logic gates using the current quantization characteristics of nanodevices. In nanodevices like the electron waveguide (EW) and single-electron (SE) turnstile, the channel current is a staircase quantized function of its control voltage. We use this unique characteristic to compactly realize Boolean functions. First we present the concept of the periodic-threshold threshold logic gate (PTTG), and we build a compact PTTG using EW and SE turnstiles. We show that an arbitrary three-input Boolean function can be realized with a single PTTG, and an arbitrary four-input Boolean function can be realized by using two PTTGs. We then use one PTTG to build a universal programmable two-input logic gate which can be used to realize all two-input Boolean functions. We also build a programmable three-input logic gate by using one PTTG. Compared with linear threshold logic gates, with the PTTG one can build digital circuits more compactly. The proposed PTTGs are promising for future smart nanoscale digital system use.
Phase transition in NK-Kauffman networks and its correction for Boolean irreducibility
NASA Astrophysics Data System (ADS)
Zertuche, Federico
2014-05-01
In a series of articles published in 1986, Derrida and his colleagues studied two mean field treatments (the quenched and the annealed) for NK-Kauffman networks. Their main results lead to a phase transition curve Kc 2 pc(1-pc)=1 (0
Controllability and observability of Boolean networks arising from biology
NASA Astrophysics Data System (ADS)
Li, Rui; Yang, Meng; Chu, Tianguang
2015-02-01
Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.
Solving a discrete model of the lac operon using Z3
NASA Astrophysics Data System (ADS)
Gutierrez, Natalia A.
2014-05-01
A discrete model for the Lcac Operon is solved using the SMT-solver Z3. Traditionally the Lac Operon is formulated in a continuous math model. This model is a system of ordinary differential equations. Here, it was considerated as a discrete model, based on a Boolean red. The biological problem of Lac Operon is enunciated as a problem of Boolean satisfiability, and it is solved using an STM-solver named Z3. Z3 is a powerful solver that allows understanding the basic dynamic of the Lac Operon in an easier and more efficient way. The multi-stability of the Lac Operon can be easily computed with Z3. The code that solves the Boolean red can be written in Python language or SMT-Lib language. Both languages were used in local version of the program as online version of Z3. For future investigations it is proposed to solve the Boolean red of Lac Operon using others SMT-solvers as cvc4, alt-ergo, mathsat and yices.
Perturbation propagation in random and evolved Boolean networks
NASA Astrophysics Data System (ADS)
Fretter, Christoph; Szejka, Agnes; Drossel, Barbara
2009-03-01
In this paper, we investigate the propagation of perturbations in Boolean networks by evaluating the Derrida plot and its modifications. We show that even small random Boolean networks agree well with the predictions of the annealed approximation, but nonrandom networks show a very different behaviour. We focus on networks that were evolved for high dynamical robustness. The most important conclusion is that the simple distinction between frozen, critical and chaotic networks is no longer useful, since such evolved networks can display the properties of all three types of networks. Furthermore, we evaluate a simplified empirical network and show how its specific state space properties are reflected in the modified Derrida plots.
Multilayer neural networks with extensively many hidden units.
Rosen-Zvi, M; Engel, A; Kanter, I
2001-08-13
The information processing abilities of a multilayer neural network with a number of hidden units scaling as the input dimension are studied using statistical mechanics methods. The mapping from the input layer to the hidden units is performed by general symmetric Boolean functions, whereas the hidden layer is connected to the output by either discrete or continuous couplings. Introducing an overlap in the space of Boolean functions as order parameter, the storage capacity is found to scale with the logarithm of the number of implementable Boolean functions. The generalization behavior is smooth for continuous couplings and shows a discontinuous transition to perfect generalization for discrete ones.
The objective of this work is to elucidate biological networks underlying cellular tipping points using time-course data. We discretized the high-content imaging (HCI) data and inferred Boolean networks (BNs) that could accurately predict dynamic cellular trajectories. We found t...
Boolean linear differential operators on elementary cellular automata
NASA Astrophysics Data System (ADS)
Martín Del Rey, Ángel
2014-12-01
In this paper, the notion of boolean linear differential operator (BLDO) on elementary cellular automata (ECA) is introduced and some of their more important properties are studied. Special attention is paid to those differential operators whose coefficients are the ECA with rule numbers 90 and 150.
Web-based metabolic network visualization with a zooming user interface
2011-01-01
Background Displaying complex metabolic-map diagrams, for Web browsers, and allowing users to interact with them for querying and overlaying expression data over them is challenging. Description We present a Web-based metabolic-map diagram, which can be interactively explored by the user, called the Cellular Overview. The main characteristic of this application is the zooming user interface enabling the user to focus on appropriate granularities of the network at will. Various searching commands are available to visually highlight sets of reactions, pathways, enzymes, metabolites, and so on. Expression data from single or multiple experiments can be overlaid on the diagram, which we call the Omics Viewer capability. The application provides Web services to highlight the diagram and to invoke the Omics Viewer. This application is entirely written in JavaScript for the client browsers and connect to a Pathway Tools Web server to retrieve data and diagrams. It uses the OpenLayers library to display tiled diagrams. Conclusions This new online tool is capable of displaying large and complex metabolic-map diagrams in a very interactive manner. This application is available as part of the Pathway Tools software that powers multiple metabolic databases including Biocyc.org: The Cellular Overview is accessible under the Tools menu. PMID:21595965
Bosonic Loop Diagrams as Perturbative Solutions of the Classical Field Equations in ϕ4-Theory
NASA Astrophysics Data System (ADS)
Finster, Felix; Tolksdorf, Jürgen
2012-05-01
Solutions of the classical ϕ4-theory in Minkowski space-time are analyzed in a perturbation expansion in the nonlinearity. Using the language of Feynman diagrams, the solution of the Cauchy problem is expressed in terms of tree diagrams which involve the retarded Green's function and have one outgoing leg. In order to obtain general tree diagrams, we set up a "classical measurement process" in which a virtual observer of a scattering experiment modifies the field and detects suitable energy differences. By adding a classical stochastic background field, we even obtain all loop diagrams. The expansions are compared with the standard Feynman diagrams of the corresponding quantum field theory.
Evolution of canalizing Boolean networks
NASA Astrophysics Data System (ADS)
Szejka, A.; Drossel, B.
2007-04-01
Boolean networks with canalizing functions are used to model gene regulatory networks. In order to learn how such networks may behave under evolutionary forces, we simulate the evolution of a single Boolean network by means of an adaptive walk, which allows us to explore the fitness landscape. Mutations change the connections and the functions of the nodes. Our fitness criterion is the robustness of the dynamical attractors against small perturbations. We find that with this fitness criterion the global maximum is always reached and that there is a huge neutral space of 100% fitness. Furthermore, in spite of having such a high degree of robustness, the evolved networks still share many features with “chaotic” networks.
Phased-mission system analysis using Boolean algebraic methods
NASA Technical Reports Server (NTRS)
Somani, Arun K.; Trivedi, Kishor S.
1993-01-01
Most reliability analysis techniques and tools assume that a system is used for a mission consisting of a single phase. However, multiple phases are natural in many missions. The failure rates of components, system configuration, and success criteria may vary from phase to phase. In addition, the duration of a phase may be deterministic or random. Recently, several researchers have addressed the problem of reliability analysis of such systems using a variety of methods. A new technique for phased-mission system reliability analysis based on Boolean algebraic methods is described. Our technique is computationally efficient and is applicable to a large class of systems for which the failure criterion in each phase can be expressed as a fault tree (or an equivalent representation). Our technique avoids state space explosion that commonly plague Markov chain-based analysis. A phase algebra to account for the effects of variable configurations and success criteria from phase to phase was developed. Our technique yields exact (as opposed to approximate) results. The use of our technique was demonstrated by means of an example and present numerical results to show the effects of mission phases on the system reliability.
Circulant Matrices and Affine Equivalence of Monomial Rotation Symmetric Boolean Functions
2015-01-01
definitions , including monomial rotation symmetric (MRS) Boolean functions and affine equivalence, and a known result for such quadratic functions...degree of the MRS is, we have a similar result as [40, Theorem 1.1] for n = 4p (p prime), or squarefree integers n, which along with our Theorem 5.2
User Practices in Keyword and Boolean Searching on an Online Public Access Catalog.
ERIC Educational Resources Information Center
Ensor, Pat
1992-01-01
Discussion of keyword and Boolean searching techniques in online public access catalogs (OPACs) focuses on a study conducted at Indiana State University that examined users' attitudes toward searching on NOTIS (Northwestern Online Total Integrated System). Relevant literature is reviewed, and implications for library instruction are suggested. (17…
Using Vector and Extended Boolean Matching in an Expert System for Selecting Foster Homes.
ERIC Educational Resources Information Center
Fox, Edward A.; Winett, Sheila G.
1990-01-01
Describes FOCES (Foster Care Expert System), a prototype expert system for choosing foster care placements for children which integrates information retrieval techniques with artificial intelligence. The use of prototypes and queries in Prolog routines, extended Boolean matching, and vector correlation are explained, as well as evaluation by…
A Construction of Boolean Functions with Good Cryptographic Properties
2014-01-01
be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT...2008, LNCS 5350, Springer–Verlag, 2008, pp. 425–440. [10] C. Carlet and K. Feng, “An Infinite Class of Balanced Vectorial Boolean Functions with Optimum
Using computer algebra and SMT solvers in algebraic biology
NASA Astrophysics Data System (ADS)
Pineda Osorio, Mateo
2014-05-01
Biologic processes are represented as Boolean networks, in a discrete time. The dynamics within these networks are approached with the help of SMT Solvers and the use of computer algebra. Software such as Maple and Z3 was used in this case. The number of stationary states for each network was calculated. The network studied here corresponds to the immune system under the effects of drastic mood changes. Mood is considered as a Boolean variable that affects the entire dynamics of the immune system, changing the Boolean satisfiability and the number of stationary states of the immune network. Results obtained show Z3's great potential as a SMT Solver. Some of these results were verified in Maple, even though it showed not to be as suitable for the problem approach. The solving code was constructed using Z3-Python and Z3-SMT-LiB. Results obtained are important in biology systems and are expected to help in the design of immune therapies. As a future line of research, more complex Boolean network representations of the immune system as well as the whole psychological apparatus are suggested.
Therapeutic target discovery using Boolean network attractors: improvements of kali
Guziolowski, Carito
2018-01-01
In a previous article, an algorithm for identifying therapeutic targets in Boolean networks modelling pathological mechanisms was introduced. In the present article, the improvements made on this algorithm, named kali, are described. These improvements are (i) the possibility to work on asynchronous Boolean networks, (ii) a finer assessment of therapeutic targets and (iii) the possibility to use multivalued logic. kali assumes that the attractors of a dynamical system, such as a Boolean network, are associated with the phenotypes of the modelled biological system. Given a logic-based model of pathological mechanisms, kali searches for therapeutic targets able to reduce the reachability of the attractors associated with pathological phenotypes, thus reducing their likeliness. kali is illustrated on an example network and used on a biological case study. The case study is a published logic-based model of bladder tumorigenesis from which kali returns consistent results. However, like any computational tool, kali can predict but cannot replace human expertise: it is a supporting tool for coping with the complexity of biological systems in the field of drug discovery. PMID:29515890
3D Boolean operations in virtual surgical planning.
Charton, Jerome; Laurentjoye, Mathieu; Kim, Youngjun
2017-10-01
Boolean operations in computer-aided design or computer graphics are a set of operations (e.g. intersection, union, subtraction) between two objects (e.g. a patient model and an implant model) that are important in performing accurate and reproducible virtual surgical planning. This requires accurate and robust techniques that can handle various types of data, such as a surface extracted from volumetric data, synthetic models, and 3D scan data. This article compares the performance of the proposed method (Boolean operations by a robust, exact, and simple method between two colliding shells (BORES)) and an existing method based on the Visualization Toolkit (VTK). In all tests presented in this article, BORES could handle complex configurations as well as report impossible configurations of the input. In contrast, the VTK implementations were unstable, do not deal with singular edges and coplanar collisions, and have created several defects. The proposed method of Boolean operations, BORES, is efficient and appropriate for virtual surgical planning. Moreover, it is simple and easy to implement. In future work, we will extend the proposed method to handle non-colliding components.
Generalization and capacity of extensively large two-layered perceptrons.
Rosen-Zvi, Michal; Engel, Andreas; Kanter, Ido
2002-09-01
The generalization ability and storage capacity of a treelike two-layered neural network with a number of hidden units scaling as the input dimension is examined. The mapping from the input to the hidden layer is via Boolean functions; the mapping from the hidden layer to the output is done by a perceptron. The analysis is within the replica framework where an order parameter characterizing the overlap between two networks in the combined space of Boolean functions and hidden-to-output couplings is introduced. The maximal capacity of such networks is found to scale linearly with the logarithm of the number of Boolean functions per hidden unit. The generalization process exhibits a first-order phase transition from poor to perfect learning for the case of discrete hidden-to-output couplings. The critical number of examples per input dimension, alpha(c), at which the transition occurs, again scales linearly with the logarithm of the number of Boolean functions. In the case of continuous hidden-to-output couplings, the generalization error decreases according to the same power law as for the perceptron, with the prefactor being different.
NASA Technical Reports Server (NTRS)
Demerdash, N. A. O.; Nehl, T. W.
1979-01-01
The development, fabrication and evaluation of a prototype electromechanical actuator (EMA) is discussed. Application of the EMA as a motor for control surfaces in aerospace flight is examined. A mathematical model of the EMA is developed for design optimization. Nonlinearities which complicate the mathematical model are discussed. The dynamics of the EMA from the underlying physical principles are determined and a discussion of similating the control logic by means of equivalent boolean expressions is presented.
Ostrowski, M; Paulevé, L; Schaub, T; Siegel, A; Guziolowski, C
2016-11-01
Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that end, we identify a necessary condition that must be satisfied by the dynamics of a Boolean network to be consistent with a discretized time series trace. Based on this condition, we use Answer Set Programming to compute an over-approximation of the set of Boolean networks which fit best with experimental data and provide the corresponding encodings. Combined with model-checking approaches, we end up with a global learning algorithm. Our approach is able to learn logic models with a true positive rate higher than 78% in two case studies of mammalian signaling networks; for a larger case study, our method provides optimal answers after 7min of computation. We quantified the gain in our method predictions precision compared to learning approaches based on static data. Finally, as an application, our method proposes erroneous time-points in the time series data with respect to the optimal learned logic models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Anthropomorphic robot for recognition and drawing generalized object images
NASA Astrophysics Data System (ADS)
Ginzburg, Vera M.
1998-10-01
The process of recognition, for instance, understanding the text, written by different fonts, consists in the depriving of the individual attributes of the letters in the particular font. It is shown that such process, in Nature and technique, can be provided by the narrowing the spatial frequency of the object's image by its defocusing. In defocusing images remain only areas, so-called Informative Fragments (IFs), which all together form the generalized (stylized) image of many identical objects. It is shown that the variety of shapes of IFs is restricted and can be presented by `Geometrical alphabet'. The `letters' for this alphabet can be created using two basic `genetic' figures: a stripe and round spot. It is known from physiology that the special cells of visual cortex response to these particular figures. The prototype of such `genetic' alphabet has been made using Boolean algebra (Venn's diagrams). The algorithm for drawing the letter's (`genlet's') shape in this alphabet and generalized images of objects (for example, `sleeping cat'), are given. A scheme of an anthropomorphic robot is shown together with results of model computer experiment of the robot's action--`drawing' the generalized image.
Interpolation of the Extended Boolean Retrieval Model.
ERIC Educational Resources Information Center
Zanger, Daniel Z.
2002-01-01
Presents an interpolation theorem for an extended Boolean information retrieval model. Results show that whenever two or more documents are similarly ranked at any two points for a query containing exactly two terms, then they are similarly ranked at all points in between; and that results can fail for queries with more than two terms. (Author/LRW)
The Concept of the "Imploded Boolean Search": A Case Study with Undergraduate Chemistry Students
ERIC Educational Resources Information Center
Tomaszewski, Robert
2016-01-01
Critical thinking and analytical problem-solving skills in research involves using different search strategies. A proposed concept for an "Imploded Boolean Search" combines three unique identifiable field types to perform a search: keyword(s), numerical value(s), and a chemical structure or reaction. The object of this type of search is…
Energy and criticality in random Boolean networks
NASA Astrophysics Data System (ADS)
Andrecut, M.; Kauffman, S. A.
2008-06-01
The central issue of the research on the Random Boolean Networks (RBNs) model is the characterization of the critical transition between ordered and chaotic phases. Here, we discuss an approach based on the ‘energy’ associated with the unsatisfiability of the Boolean functions in the RBNs model, which provides an upper bound estimation for the energy used in computation. We show that in the ordered phase the RBNs are in a ‘dissipative’ regime, performing mostly ‘downhill’ moves on the ‘energy’ landscape. Also, we show that in the disordered phase the RBNs have to ‘hillclimb’ on the ‘energy’ landscape in order to perform computation. The analytical results, obtained using Derrida's approximation method, are in complete agreement with numerical simulations.
Optical programmable Boolean logic unit.
Chattopadhyay, Tanay
2011-11-10
Logic units are the building blocks of many important computational operations likes arithmetic, multiplexer-demultiplexer, radix conversion, parity checker cum generator, etc. Multifunctional logic operation is very much essential in this respect. Here a programmable Boolean logic unit is proposed that can perform 16 Boolean logical operations from a single optical input according to the programming input without changing the circuit design. This circuit has two outputs. One output is complementary to the other. Hence no loss of data can occur. The circuit is basically designed by a 2×2 polarization independent optical cross bar switch. Performance of the proposed circuit has been achieved by doing numerical simulations. The binary logical states (0,1) are represented by the absence of light (null) and presence of light, respectively.
Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R
2017-01-01
Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.
Research issues of geometry-based visual languages and some solutions
NASA Astrophysics Data System (ADS)
Green, Thorn G.
This dissertation addresses the problem of how to design visual language systems that are based upon Geometric Algebra, and provide a visual coupling of algebraic expressions and geometric depictions. This coupling of algebraic expressions and geometric depictions provides a new means for expressing both mathematical and geometric relationships present in mathematics, physics, and Computer-Aided Geometric Design (CAGD). Another significant feature of such a system is that the result of changing a parameter (by dragging the mouse) can be seen immediately in the depiction(s) of all expressions that use that parameter. This greatly aides the cognition of the relationships between variables. Systems for representing such a coupling of algebra and geometry have characteristics of both visual language systems, and systems for scientific visualization. Instead of using a parsing or dataflow paradigm for the visual language representation, the systems instead represent equations as manipulatible constrained diagrams for their visualization. This requires that the design of such a system have (but is not limited to) a means for parsing equations entered by the user, a scheme for producing a visual representation of these equations; techniques for maintaining the coupling between the expressions entered and the diagrams displayed; algorithms for maintaining the consistency of the diagrams; and, indexing capabilities that are efficient enough to allow diagrams to be created, and manipulated in a short enough period of time. The author proposes solutions for how such a design can be realized.
Borate mineral assemblages in the system Na2OCaOMgOB2O3H2O
Christ, C.L.; Truesdell, A.H.; Erd, Richard C.
1967-01-01
he significant known hydrated borate mineral assemblages (principally of the western United States) in the system Na2OCaOz.sbnd;MgOB2O3H2O are expressible in three ternary composition diagrams. Phase rule interpretation of the diagrams is consistent with observation, if the activity of H2O is generally considered to be determined by the geologic environment. The absence of conflicting tie-lines on a diagram indicates that the several mineral assemblages of the diagram were formed under relatively narrow ranges of temperature and pressure. The known structural as well as empirical formulas for the minerals are listed, and the more recent (since 1960) crystal structure findings are discussed briefly. Schematic Gibbs free energy-composition diagrams based on known solubility-temperature relations in the systems Na2B4O7-H2O and Na2B4O7-NaCl-H2O, are highly useful in the interpretation and prediction of the stability relations in these systems; in particular these diagrams indicate clearly that tincalconite, although geologically important, is everywhere a metastable phase. Crystal-chemical considerations indicate that the same thermodynamic and kinetic behavior observed in the Na2B4O7-H2O system will hold in the Ca2B6O11-H2O system. This conclusion is confirmed by the petrologic evidence. The chemical relations among the mineral assemblages of a ternary diagram are expressed by a schematic "activity-activity" diagram. These activity-activity diagrams permit the tracing-out of the paragenetic sequences as a function of changing cation and H2O activities. ?? 1967.
Poisson equation for the three-loop ladder diagram in string theory at genus one
NASA Astrophysics Data System (ADS)
Basu, Anirban
2016-11-01
The three-loop ladder diagram is a graph with six links and four cubic vertices that contributes to the D12ℛ4 amplitude at genus one in type II string theory. The vertices represent the insertion points of vertex operators on the toroidal worldsheet and the links represent scalar Green functions connecting them. By using the properties of the Green function and manipulating the various expressions, we obtain a modular invariant Poisson equation satisfied by this diagram, with source terms involving one-, two- and three-loop diagrams. Unlike the source terms in the Poisson equations for diagrams at lower orders in the momentum expansion or the Mercedes diagram, a particular source term involves a five-point function containing a holomorphic and a antiholomorphic worldsheet derivative acting on different Green functions. We also obtain simple equalities between topologically distinct diagrams, and consider some elementary examples.
Designing Networks that are Capable of Self-Healing and Adapting
2017-04-01
from statistical mechanics, combinatorics, boolean networks, and numerical simulations, and inspired by design principles from biological networks, we... principles for self-healing networks, and applications, and construct an all-possible-paths model for network adaptation. 2015-11-16 UNIT CONVERSION...combinatorics, boolean networks, and numerical simulations, and inspired by design principles from biological networks, we will undertake the fol
NASA Astrophysics Data System (ADS)
Zhu, Zheng; Andresen, Juan Carlos; Janzen, Katharina; Katzgraber, Helmut G.
2013-03-01
We study the equilibrium and nonequilibrium properties of Boolean decision problems with competing interactions on scale-free graphs in a magnetic field. Previous studies at zero field have shown a remarkable equilibrium stability of Boolean variables (Ising spins) with competing interactions (spin glasses) on scale-free networks. When the exponent that describes the power-law decay of the connectivity of the network is strictly larger than 3, the system undergoes a spin-glass transition. However, when the exponent is equal to or less than 3, the glass phase is stable for all temperatures. First we perform finite-temperature Monte Carlo simulations in a field to test the robustness of the spin-glass phase and show, in agreement with analytical calculations, that the system exhibits a de Almeida-Thouless line. Furthermore, we study avalanches in the system at zero temperature to see if the system displays self-organized criticality. This would suggest that damage (avalanches) can spread across the whole system with nonzero probability, i.e., that Boolean decision problems on scale-free networks with competing interactions are fragile when not in thermal equilibrium.
Models as Feedback: Developing Representational Competence in Chemistry
ERIC Educational Resources Information Center
Padalkar, Shamin; Hegarty, Mary
2015-01-01
Spatial information in science is often expressed through representations such as diagrams and models. Learning the strengths and limitations of these representations and how to relate them are important aspects of developing scientific understanding, referred to as "representational competence." Diagram translation is particularly…
Implementing neural nets with programmable logic
NASA Technical Reports Server (NTRS)
Vidal, Jacques J.
1988-01-01
Networks of Boolean programmable logic modules are presented as one purely digital class of artificial neural nets. The approach contrasts with the continuous analog framework usually suggested. Programmable logic networks are capable of handling many neural-net applications. They avoid some of the limitations of threshold logic networks and present distinct opportunities. The network nodes are called dynamically programmable logic modules. They can be implemented with digitally controlled demultiplexers. Each node performs a Boolean function of its inputs which can be dynamically assigned. The overall network is therefore a combinational circuit and its outputs are Boolean global functions of the network's input variables. The approach offers definite advantages for VLSI implementation, namely, a regular architecture with limited connectivity, simplicity of the control machinery, natural modularity, and the support of a mature technology.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rivera-Durón, R. R., E-mail: roberto.rivera@ipicyt.edu.mx; Campos-Cantón, E., E-mail: eric.campos@ipicyt.edu.mx; Campos-Cantón, I.
We present the design of an autonomous time-delay Boolean network realized with readily available electronic components. Through simulations and experiments that account for the detailed nonlinear response of each circuit element, we demonstrate that a network with five Boolean nodes displays complex behavior. Furthermore, we show that the dynamics of two identical networks display near-instantaneous synchronization to a periodic state when forced by a common periodic Boolean signal. A theoretical analysis of the network reveals the conditions under which complex behavior is expected in an individual network and the occurrence of synchronization in the forced networks. This research will enablemore » future experiments on autonomous time-delay networks using readily available electronic components with dynamics on a slow enough time-scale so that inexpensive data collection systems can faithfully record the dynamics.« less
Stabilizing Motifs in Autonomous Boolean Networks and the Yeast Cell Cycle Oscillator
NASA Astrophysics Data System (ADS)
Sevim, Volkan; Gong, Xinwei; Socolar, Joshua
2009-03-01
Synchronously updated Boolean networks are widely used to model gene regulation. Some properties of these model networks are known to be artifacts of the clocking in the update scheme. Autonomous updating is a less artificial scheme that allows one to introduce small timing perturbations and study stability of the attractors. We argue that the stabilization of a limit cycle in an autonomous Boolean network requires a combination of motifs such as feed-forward loops and auto-repressive links that can correct small fluctuations in the timing of switching events. A recently published model of the transcriptional cell-cycle oscillator in yeast contains the motifs necessary for stability under autonomous updating [1]. [1] D. A. Orlando, et al. Nature (London), 4530 (7197):0 944--947, 2008.
Feedback Controller Design for the Synchronization of Boolean Control Networks.
Liu, Yang; Sun, Liangjie; Lu, Jianquan; Liang, Jinling
2016-09-01
This brief investigates the partial and complete synchronization of two Boolean control networks (BCNs). Necessary and sufficient conditions for partial and complete synchronization are established by the algebraic representations of logical dynamics. An algorithm is obtained to construct the feedback controller that guarantees the synchronization of master and slave BCNs. Two biological examples are provided to illustrate the effectiveness of the obtained results.
Computer Aided Instruction for a Course in Boolean Algebra and Logic Design. Final Report (Revised).
ERIC Educational Resources Information Center
Roy, Rob
The use of computers to prepare deficient college and graduate students for courses that build upon previously acquired information would solve the growing problem of professors who must spend up to one third of their class time in review of material. But examination of students who were taught Boolean Algebra and Logic Design by means of Computer…
NASA Astrophysics Data System (ADS)
Cheng, Maurice M. W.; Gilbert, John K.
2015-01-01
This study investigated students' interpretation of diagrams representing the human circulatory system. We conducted an interview study with three students aged 14-15 (Year 10) who were studying biology in a Hong Kong school. During the interviews, students were asked to interpret diagrams and relationships between diagrams that represented aspects of the circulatory system. All diagrams used in the interviews had been used by their teacher when teaching the topic. Students' interpretations were expressed by their verbal response and their drawing. Dual coding theory was used to interpret students' responses. There was evidence that one student relied on verbal recall as a strategy in interpreting diagrams. It was found that students might have relied unduly on similarities in spatial features, rather than on deeper meanings represented by conventions, of diagrams when they associated diagrams that represented different aspects of the circulatory system. A pattern of students' understanding of structure-behaviour-function relationship of the biological system was observed. This study suggests the importance of a consistent diagrammatic and verbal representation in communicating scientific ideas. Implications for teaching practice that facilitates learning with diagrams and address students' undue focus on spatial features of diagrams are discussed.
Zhang, Fan; Liu, Runsheng; Zheng, Jie
2016-12-23
Linking computational models of signaling pathways to predicted cellular responses such as gene expression regulation is a major challenge in computational systems biology. In this work, we present Sig2GRN, a Cytoscape plugin that is able to simulate time-course gene expression data given the user-defined external stimuli to the signaling pathways. A generalized logical model is used in modeling the upstream signaling pathways. Then a Boolean model and a thermodynamics-based model are employed to predict the downstream changes in gene expression based on the simulated dynamics of transcription factors in signaling pathways. Our empirical case studies show that the simulation of Sig2GRN can predict changes in gene expression patterns induced by DNA damage signals and drug treatments. As a software tool for modeling cellular dynamics, Sig2GRN can facilitate studies in systems biology by hypotheses generation and wet-lab experimental design. http://histone.scse.ntu.edu.sg/Sig2GRN/.
Proposal for nanoscale cascaded plasmonic majority gates for non-Boolean computation.
Dutta, Sourav; Zografos, Odysseas; Gurunarayanan, Surya; Radu, Iuliana; Soree, Bart; Catthoor, Francky; Naeemi, Azad
2017-12-19
Surface-plasmon-polariton waves propagating at the interface between a metal and a dielectric, hold the key to future high-bandwidth, dense on-chip integrated logic circuits overcoming the diffraction limitation of photonics. While recent advances in plasmonic logic have witnessed the demonstration of basic and universal logic gates, these CMOS oriented digital logic gates cannot fully utilize the expressive power of this novel technology. Here, we aim at unraveling the true potential of plasmonics by exploiting an enhanced native functionality - the majority voter. Contrary to the state-of-the-art plasmonic logic devices, we use the phase of the wave instead of the intensity as the state or computational variable. We propose and demonstrate, via numerical simulations, a comprehensive scheme for building a nanoscale cascadable plasmonic majority logic gate along with a novel referencing scheme that can directly translate the information encoded in the amplitude and phase of the wave into electric field intensity at the output. Our MIM-based 3-input majority gate displays a highly improved overall area of only 0.636 μm 2 for a single-stage compared with previous works on plasmonic logic. The proposed device demonstrates non-Boolean computational capability and can find direct utility in highly parallel real-time signal processing applications like pattern recognition.
Microstructural Characterization of HSLA-100 GMA-Weldments
1987-09-01
Intermeiate Oxygen Regime ----------- 66 D.) Schematic CCT Diagram - --------------- 66 9 ACKNOWLEDGEMENTS I wish to express my appreciation to my thesis...have been observed in this research [review Figures 31 (a), (b) and 35 (a)]. Figure 38 (d) shows a schematic CCT diagram reported by Glover (Ref. 5) and...Regime B.) High Ox. gen Regime C. )Interme late Oxygen Regime D.1 Schematic CCT Diagram 66 LIST OF REFERENCES 1. Anderson, T.L., Hyatt J A West, J.C
Deriving Laws from Ordering Relations
NASA Technical Reports Server (NTRS)
Knuth, Kevin H.
2003-01-01
It took much effort in the early days of non-Euclidean geometry to break away from the mindset that all spaces are flat and that two distinct parallel lines do not cross. Up to that point, all that was known was Euclidean geometry, and it was difficult to imagine anything else. We have suffered a similar handicap brought on by the enormous relevance of Boolean algebra to the problems of our age-logic and set theory. Previously, I demonstrated that the algebra of questions is not Boolean, but rather is described by the free distributive algebra. To get to this stage took much effort, as many obstacles-most self-placed-had to be overcome. As Boolean algebras were all I had ever known, it was almost impossible for me to imagine working with an algebra where elements do not have complements. With this realization, it became very clear that the sum and product rules of probability theory at the most basic level had absolutely nothing to do with the Boolean algebra of logical statements. Instead, a measure of degree of inclusion can be invented for many different partially ordered sets, and the sum and product rules fall out of the associativity and distributivity of the algebra. To reinforce this very important idea, this paper will go over how these constructions are made, while focusing on the underlying assumptions. I will derive the sum and product rules for a distributive lattice in general and demonstrate how this leads to probability theory on the Boolean lattice and is related to the calculus of quantum mechanical amplitudes on the partially ordered set of experimental setups. I will also discuss the rules that can be derived from modular lattices and their relevance to the cross-ratio of projective geometry.
Detection of LiveLock in BPMN Using Process Expression
NASA Astrophysics Data System (ADS)
Tantitharanukul, Nasi; Jumpamule, Watcharee
Although the Business Process Modeling Notation (BPMN) is a popular tool for modeling business process in conceptual level, the result diagram may contain structural problem. One of the structural problems is livelock. In this problem, one token proceeds to end event, while other token is still in process with no progression. In this paper, we introduce an expression liked method to detect livelock in the BPMN diagram. Our approach utilizes the power of the declarative ability of expression to determine all of the possible process chains, and indicate whether there are livelock or not. As a result, we have shown that our method can detect livelock, if any.
The computational core and fixed point organization in Boolean networks
NASA Astrophysics Data System (ADS)
Correale, L.; Leone, M.; Pagnani, A.; Weigt, M.; Zecchina, R.
2006-03-01
In this paper, we analyse large random Boolean networks in terms of a constraint satisfaction problem. We first develop an algorithmic scheme which allows us to prune simple logical cascades and underdetermined variables, returning thereby the computational core of the network. Second, we apply the cavity method to analyse the number and organization of fixed points. We find in particular a phase transition between an easy and a complex regulatory phase, the latter being characterized by the existence of an exponential number of macroscopically separated fixed point clusters. The different techniques developed are reinterpreted as algorithms for the analysis of single Boolean networks, and they are applied in the analysis of and in silico experiments on the gene regulatory networks of baker's yeast (Saccharomyces cerevisiae) and the segment-polarity genes of the fruitfly Drosophila melanogaster.
Observability of Boolean multiplex control networks
NASA Astrophysics Data System (ADS)
Wu, Yuhu; Xu, Jingxue; Sun, Xi-Ming; Wang, Wei
2017-04-01
Boolean multiplex (multilevel) networks (BMNs) are currently receiving considerable attention as theoretical arguments for modeling of biological systems and system level analysis. Studying control-related problems in BMNs may not only provide new views into the intrinsic control in complex biological systems, but also enable us to develop a method for manipulating biological systems using exogenous inputs. In this article, the observability of the Boolean multiplex control networks (BMCNs) are studied. First, the dynamical model and structure of BMCNs with control inputs and outputs are constructed. By using of Semi-Tensor Product (STP) approach, the logical dynamics of BMCNs is converted into an equivalent algebraic representation. Then, the observability of the BMCNs with two different kinds of control inputs is investigated by giving necessary and sufficient conditions. Finally, examples are given to illustrate the efficiency of the obtained theoretical results.
Boolean network representation of contagion dynamics during a financial crisis
NASA Astrophysics Data System (ADS)
Caetano, Marco Antonio Leonel; Yoneyama, Takashi
2015-01-01
This work presents a network model for representation of the evolution of certain patterns of economic behavior. More specifically, after representing the agents as points in a space in which each dimension associated to a relevant economic variable, their relative "motions" that can be either stationary or discordant, are coded into a boolean network. Patterns with stationary averages indicate the maintenance of status quo, whereas discordant patterns represent aggregation of new agent into the cluster or departure from the former policies. The changing patterns can be embedded into a network representation, particularly using the concept of autocatalytic boolean networks. As a case study, the economic tendencies of the BRIC countries + Argentina were studied. Although Argentina is not included in the cluster formed by BRIC countries, it tends to follow the BRIC members because of strong commercial ties.
NASA Astrophysics Data System (ADS)
Uezu, Tatsuya; Kiyokawa, Shuji
2016-06-01
We investigate the supervised batch learning of Boolean functions expressed by a two-layer perceptron with a tree-like structure. We adopt continuous weights (spherical model) and the Gibbs algorithm. We study the Parity and And machines and two types of noise, input and output noise, together with the noiseless case. We assume that only the teacher suffers from noise. By using the replica method, we derive the saddle point equations for order parameters under the replica symmetric (RS) ansatz. We study the critical value αC of the loading rate α above which the learning phase exists for cases with and without noise. We find that αC is nonzero for the Parity machine, while it is zero for the And machine. We derive the exponents barβ of order parameters expressed as (α - α C)bar{β} when α is near to αC. Furthermore, in the Parity machine, when noise exists, we find a spin glass solution, in which the overlap between the teacher and student vectors is zero but that between student vectors is nonzero. We perform Markov chain Monte Carlo simulations by simulated annealing and also by exchange Monte Carlo simulations in both machines. In the Parity machine, we study the de Almeida-Thouless stability, and by comparing theoretical and numerical results, we find that there exist parameter regions where the RS solution is unstable, and that the spin glass solution is metastable or unstable. We also study asymptotic learning behavior for large α and derive the exponents hat{β } of order parameters expressed as α - hat{β } when α is large in both machines. By simulated annealing simulations, we confirm these results and conclude that learning takes place for the input noise case with any noise amplitude and for the output noise case when the probability that the teacher's output is reversed is less than one-half.
NASA Astrophysics Data System (ADS)
Zhu, Zheng; Andresen, Juan Carlos; Moore, M. A.; Katzgraber, Helmut G.
2014-02-01
We study the equilibrium and nonequilibrium properties of Boolean decision problems with competing interactions on scale-free networks in an external bias (magnetic field). Previous studies at zero field have shown a remarkable equilibrium stability of Boolean variables (Ising spins) with competing interactions (spin glasses) on scale-free networks. When the exponent that describes the power-law decay of the connectivity of the network is strictly larger than 3, the system undergoes a spin-glass transition. However, when the exponent is equal to or less than 3, the glass phase is stable for all temperatures. First, we perform finite-temperature Monte Carlo simulations in a field to test the robustness of the spin-glass phase and show that the system has a spin-glass phase in a field, i.e., exhibits a de Almeida-Thouless line. Furthermore, we study avalanche distributions when the system is driven by a field at zero temperature to test if the system displays self-organized criticality. Numerical results suggest that avalanches (damage) can spread across the whole system with nonzero probability when the decay exponent of the interaction degree is less than or equal to 2, i.e., that Boolean decision problems on scale-free networks with competing interactions can be fragile when not in thermal equilibrium.
Particle–hole ring diagrams for fermions in two dimensions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kaiser, N., E-mail: nkaiser@ph.tum.de
2014-11-15
The set of particle–hole ring diagrams for a many-fermion system in two dimensions is studied. The complex-valued polarization function is derived in detail and shown to be expressible in terms of square-root functions. For a contact-interaction the perturbative contributions to the energy per particle Ē(k{sub f}) are calculated in a closed analytical form from third up to twelfth order. The resummation of the particle–hole ring diagrams to all orders is studied and a pronounced dependence on the dimensionless coupling parameter α is found. There is a substantial difference between the complete ring-sum with all exchange-type diagrams included and the standardmore » resummation of the leading n-ring diagrams only. The spin factor S{sub n}(g) associated to the nth order ring diagrams is derived for arbitrary spin-degeneracy g.« less
Exact Algorithms for Output Encoding, State Assignment and Four-Level Boolean Minimization
1989-10-01
APPROVED FOR PUBLIC DISTRIBUTION • DTIC MASSACHUSETTS INTITUTE OF TECHNOLOGY M VLSI PUBLICATIONSJAN 17 1990 VLSI Memo No. 89-569 JN. 9October 1989...nunijize large funclions exacly within reasonable amocunt. of CPt targeting twro-level logic imnplemientations involve finding ap- time. However, thle ,, m ...0(NV!) m ~iimizations . n5 10 The inptut encoding problemt can be exactly solved using mrultiple-valued Boolean nimuization. We present an exact (a) (b
Huang, Wei Tao; Luo, Hong Qun; Li, Nian Bing
2014-05-06
The most serious, and yet unsolved, problem of constructing molecular computing devices consists in connecting all of these molecular events into a usable device. This report demonstrates the use of Boolean logic tree for analyzing the chemical event network based on graphene, organic dye, thrombin aptamer, and Fenton reaction, organizing and connecting these basic chemical events. And this chemical event network can be utilized to implement fluorescent combinatorial logic (including basic logic gates and complex integrated logic circuits) and fuzzy logic computing. On the basis of the Boolean logic tree analysis and logic computing, these basic chemical events can be considered as programmable "words" and chemical interactions as "syntax" logic rules to construct molecular search engine for performing intelligent molecular search query. Our approach is helpful in developing the advanced logic program based on molecules for application in biosensing, nanotechnology, and drug delivery.
A single-layer platform for Boolean logic and arithmetic through DNA excision in mammalian cells
Weinberg, Benjamin H.; Hang Pham, N. T.; Caraballo, Leidy D.; Lozanoski, Thomas; Engel, Adrien; Bhatia, Swapnil; Wong, Wilson W.
2017-01-01
Genetic circuits engineered for mammalian cells often require extensive fine-tuning to perform their intended functions. To overcome this problem, we present a generalizable biocomputing platform that can engineer genetic circuits which function in human cells with minimal optimization. We used our Boolean Logic and Arithmetic through DNA Excision (BLADE) platform to build more than 100 multi-input-multi-output circuits. We devised a quantitative metric to evaluate the performance of the circuits in human embryonic kidney and Jurkat T cells. Of 113 circuits analysed, 109 functioned (96.5%) with the correct specified behavior without any optimization. We used our platform to build a three-input, two-output Full Adder and six-input, one-output Boolean Logic Look Up Table. We also used BLADE to design circuits with temporal small molecule-mediated inducible control and circuits that incorporate CRISPR/Cas9 to regulate endogenous mammalian genes. PMID:28346402
An Automated Design Framework for Multicellular Recombinase Logic.
Guiziou, Sarah; Ulliana, Federico; Moreau, Violaine; Leclere, Michel; Bonnet, Jerome
2018-05-18
Tools to systematically reprogram cellular behavior are crucial to address pressing challenges in manufacturing, environment, or healthcare. Recombinases can very efficiently encode Boolean and history-dependent logic in many species, yet current designs are performed on a case-by-case basis, limiting their scalability and requiring time-consuming optimization. Here we present an automated workflow for designing recombinase logic devices executing Boolean functions. Our theoretical framework uses a reduced library of computational devices distributed into different cellular subpopulations, which are then composed in various manners to implement all desired logic functions at the multicellular level. Our design platform called CALIN (Composable Asynchronous Logic using Integrase Networks) is broadly accessible via a web server, taking truth tables as inputs and providing corresponding DNA designs and sequences as outputs (available at http://synbio.cbs.cnrs.fr/calin ). We anticipate that this automated design workflow will streamline the implementation of Boolean functions in many organisms and for various applications.
Tracking perturbations in Boolean networks with spectral methods
NASA Astrophysics Data System (ADS)
Kesseli, Juha; Rämö, Pauli; Yli-Harja, Olli
2005-08-01
In this paper we present a method for predicting the spread of perturbations in Boolean networks. The method is applicable to networks that have no regular topology. The prediction of perturbations can be performed easily by using a presented result which enables the efficient computation of the required iterative formulas. This result is based on abstract Fourier transform of the functions in the network. In this paper the method is applied to show the spread of perturbations in networks containing a distribution of functions found from biological data. The advances in the study of the spread of perturbations can directly be applied to enable ways of quantifying chaos in Boolean networks. Derrida plots over an arbitrary number of time steps can be computed and thus distributions of functions compared with each other with respect to the amount of order they create in random networks.
ERIC Educational Resources Information Center
Strickland, Amanda M.; Kraft, Adam; Bhattacharyya, Gautam
2010-01-01
As part of our investigations into the development of representational competence, we report results from a study in which we elicited sixteen graduate students' expressed mental models of commonly-used terms for describing organic reactions--functional group, nucleophile/electrophile, acid/base--and for diagrams of transformations and their…
Emergence of diversity in homogeneous coupled Boolean networks
NASA Astrophysics Data System (ADS)
Kang, Chris; Aguilar, Boris; Shmulevich, Ilya
2018-05-01
The origin of multicellularity in metazoa is one of the fundamental questions of evolutionary biology. We have modeled the generic behaviors of gene regulatory networks in isogenic cells as stochastic nonlinear dynamical systems—coupled Boolean networks with perturbation. Model simulations under a variety of dynamical regimes suggest that the central characteristic of multicellularity, permanent spatial differentiation (diversification), indeed can arise. Additionally, we observe that diversification is more likely to occur near the critical regime of Lyapunov stability.
Shamshirband, Shahaboddin; Banjanovic-Mehmedovic, Lejla; Bosankic, Ivan; Kasapovic, Suad; Abdul Wahab, Ainuddin Wahid Bin
2016-01-01
Intelligent Transportation Systems rely on understanding, predicting and affecting the interactions between vehicles. The goal of this paper is to choose a small subset from the larger set so that the resulting regression model is simple, yet have good predictive ability for Vehicle agent speed relative to Vehicle intruder. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data resulting from these measurements. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of agent speed relative to intruder. This process includes several ways to discover a subset of the total set of recorded parameters, showing good predictive capability. The ANFIS network was used to perform a variable search. Then, it was used to determine how 9 parameters (Intruder Front sensors active (boolean), Intruder Rear sensors active (boolean), Agent Front sensors active (boolean), Agent Rear sensors active (boolean), RSSI signal intensity/strength (integer), Elapsed time (in seconds), Distance between Agent and Intruder (m), Angle of Agent relative to Intruder (angle between vehicles °), Altitude difference between Agent and Intruder (m)) influence prediction of agent speed relative to intruder. The results indicated that distance between Vehicle agent and Vehicle intruder (m) and angle of Vehicle agent relative to Vehicle Intruder (angle between vehicles °) is the most influential parameters to Vehicle agent speed relative to Vehicle intruder.
Marmarelis, Vasilis Z.; Zanos, Theodoros P.; Berger, Theodore W.
2010-01-01
This paper presents a new modeling approach for neural systems with point-process (spike) inputs and outputs that utilizes Boolean operators (i.e. modulo 2 multiplication and addition that correspond to the logical AND and OR operations respectively, as well as the AND_NOT logical operation representing inhibitory effects). The form of the employed mathematical models is akin to a “Boolean-Volterra” model that contains the product terms of all relevant input lags in a hierarchical order, where terms of order higher than first represent nonlinear interactions among the various lagged values of each input point-process or among lagged values of various inputs (if multiple inputs exist) as they reflect on the output. The coefficients of this Boolean-Volterra model are also binary variables that indicate the presence or absence of the respective term in each specific model/system. Simulations are used to explore the properties of such models and the feasibility of their accurate estimation from short data-records in the presence of noise (i.e. spurious spikes). The results demonstrate the feasibility of obtaining reliable estimates of such models, with excitatory and inhibitory terms, in the presence of considerable noise (spurious spikes) in the outputs and/or the inputs in a computationally efficient manner. A pilot application of this approach to an actual neural system is presented in the companion paper (Part II). PMID:19517238
The Design and Implementation of a Translator for Arithmetic and Boolean Expressions.
1980-01-01
fault toleranc- P-or imTarop-r token.- or incorrect tok- n or(I-r. F C icD - MUS" hc-IV CnP 2J n,-)2ri 9 Iot t rq 3C003 G~T. 3OD 0L 3COC~ 5G F. 30005 ... 30005 .GE. ph 50015 60. C 30006 .LE. DP 50016 61. C RELPNT-INTEGER, POINTER TO ENTRIES IN RELOPS ARRAYY 62. C TEMP -INTEGER, USED FOR DETERMINING IF...30002, 50012, 30003, 50013, 30004, 50014, 30005 , 50015, 71. 1 30006, 50016/, SUB/50006/, THEN/142408/ 72. C 73. C ******** EXECUTABLE CODE******** 74
A Module Language for Typing by Contracts
NASA Technical Reports Server (NTRS)
Glouche, Yann; Talpin, Jean-Pierre; LeGuernic, Paul; Gautier, Thierry
2009-01-01
Assume-guarantee reasoning is a popular and expressive paradigm for modular and compositional specification of programs. It is becoming a fundamental concept in some computer-aided design tools for embedded system design. In this paper, we elaborate foundations for contract-based embedded system design by proposing a general-purpose module language based on a Boolean algebra allowing to define contracts. In this framework, contracts are used to negotiate the correctness of assumptions made on the definition of a component at the point where it is used and provides guarantees to its environment. We illustrate this presentation with the specification of a simplified 4-stroke engine model.
Spinning geodesic Witten diagrams
Dyer, Ethan; Freedman, Daniel Z.; Sully, James
2017-11-10
We present an expression for the four-point conformal blocks of symmetric traceless operators of arbitrary spin as an integral over a pair of geodesics in Anti-de Sitter space, generalizing the geodesic Witten diagram formalism of Hijano et al. to arbitrary spin. As an intermediate step in the derivation, we identify a convenient basis of bulk threepoint interaction vertices which give rise to all possible boundary three point structures. Lastly, we highlight a direct connection between the representation of the conformal block as geodesic Witten diagram and the shadow operator formalism.
Visualization of Concurrent Program Executions
NASA Technical Reports Server (NTRS)
Artho, Cyrille; Havelund, Klaus; Honiden, Shinichi
2007-01-01
Various program analysis techniques are efficient at discovering failures and properties. However, it is often difficult to evaluate results, such as program traces. This calls for abstraction and visualization tools. We propose an approach based on UML sequence diagrams, addressing shortcomings of such diagrams for concurrency. The resulting visualization is expressive and provides all the necessary information at a glance.
Kaneko, Yuko; Kondo, Harumi; Takeuchi, Tsutomu
2013-08-01
To investigate the performance of the new remission criteria for rheumatoid arthritis (RA) in daily clinical practice and the effect of possible misclassification of remission when 44 joints are assessed. Disease activity and remission rate were calculated according to the Disease Activity Score (DAS28), Simplified Disease Activity Index (SDAI), Clinical Disease Activity Index (CDAI), and a Boolean-based definition for 1402 patients with RA in Keio University Hospital. Characteristics of patients in remission were investigated, and the number of misclassified patients was determined--those classified as being in remission based on 28-joint count but as nonremission based on a 44-joint count for each definition criterion. Of all patients analyzed, 46.6%, 45.9%, 41.0%, and 31.5% were classified as in remission in the DAS28, SDAI, CDAI, and Boolean definitions, respectively. Patients classified into remission based only on the DAS28 showed relatively low erythrocyte sedimentation rates but greater swollen joint counts than those classified into remission based on the other definitions. In patients classified into remission based only on the Boolean criteria, the mean physician global assessment was greater than the mean patient global assessment. Although 119 patients had ≤ 1 involved joint in the 28-joint count but > 1 in the 44-joint count, only 34 of these 119 (2.4% of all subjects) were found to have been misclassified into remission. In practice, about half of patients with RA can achieve clinical remission within the DAS28, SDAI, and CDAI; and one-third according to the Boolean-based definition. Patients classified in remission based on a 28-joint count may have pain and swelling in the feet, but misclassification of remission was relatively rare and was seen in only 2.4% of patients under a Boolean definition. The 28-joint count can be sufficient for assessing clinical remission based on the new remission criteria.
Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering
NASA Technical Reports Server (NTRS)
Dhaeseleer, Patrik; Liang, Shoudan; Somogyi, Roland
2000-01-01
Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.
A stochastic and dynamical view of pluripotency in mouse embryonic stem cells
Lee, Esther J.
2018-01-01
Pluripotent embryonic stem cells are of paramount importance for biomedical sciences because of their innate ability for self-renewal and differentiation into all major cell lines. The fateful decision to exit or remain in the pluripotent state is regulated by complex genetic regulatory networks. The rapid growth of single-cell sequencing data has greatly stimulated applications of statistical and machine learning methods for inferring topologies of pluripotency regulating genetic networks. The inferred network topologies, however, often only encode Boolean information while remaining silent about the roles of dynamics and molecular stochasticity inherent in gene expression. Herein we develop a framework for systematically extending Boolean-level network topologies into higher resolution models of networks which explicitly account for the promoter architectures and gene state switching dynamics. We show the framework to be useful for disentangling the various contributions that gene switching, external signaling, and network topology make to the global heterogeneity and dynamics of transcription factor populations. We find the pluripotent state of the network to be a steady state which is robust to global variations of gene switching rates which we argue are a good proxy for epigenetic states of individual promoters. The temporal dynamics of exiting the pluripotent state, on the other hand, is significantly influenced by the rates of genetic switching which makes cells more responsive to changes in extracellular signals. PMID:29451874
Random Boolean networks for autoassociative memory: Optimization and sequential learning
NASA Astrophysics Data System (ADS)
Sherrington, D.; Wong, K. Y. M.
Conventional neural networks are based on synaptic storage of information, even when the neural states are discrete and bounded. In general, the set of potential local operations is much greater. Here we discuss some aspects of the properties of networks of binary neurons with more general Boolean functions controlling the local dynamics. Two specific aspects are emphasised; (i) optimization in the presence of noise and (ii) a simple model for short-term memory exhibiting primacy and recency in the recall of sequentially taught patterns.
Security analysis of boolean algebra based on Zhang-Wang digital signature scheme
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zheng, Jinbin, E-mail: jbzheng518@163.com
2014-10-06
In 2005, Zhang and Wang proposed an improvement signature scheme without using one-way hash function and message redundancy. In this paper, we show that this scheme exits potential safety concerns through the analysis of boolean algebra, such as bitwise exclusive-or, and point out that mapping is not one to one between assembly instructions and machine code actually by means of the analysis of the result of the assembly program segment, and which possibly causes safety problems unknown to the software.
Realization of a quantum Hamiltonian Boolean logic gate on the Si(001):H surface.
Kolmer, Marek; Zuzak, Rafal; Dridi, Ghassen; Godlewski, Szymon; Joachim, Christian; Szymonski, Marek
2015-08-07
The design and construction of the first prototypical QHC (Quantum Hamiltonian Computing) atomic scale Boolean logic gate is reported using scanning tunnelling microscope (STM) tip-induced atom manipulation on an Si(001):H surface. The NOR/OR gate truth table was confirmed by dI/dU STS (Scanning Tunnelling Spectroscopy) tracking how the surface states of the QHC quantum circuit on the Si(001):H surface are shifted according to the input logical status.
Boolean gates on actin filaments
NASA Astrophysics Data System (ADS)
Siccardi, Stefano; Tuszynski, Jack A.; Adamatzky, Andrew
2016-01-01
Actin is a globular protein which forms long polar filaments in the eukaryotic cytoskeleton. Actin networks play a key role in cell mechanics and cell motility. They have also been implicated in information transmission and processing, memory and learning in neuronal cells. The actin filaments have been shown to support propagation of voltage pulses. Here we apply a coupled nonlinear transmission line model of actin filaments to study interactions between voltage pulses. To represent digital information we assign a logical TRUTH value to the presence of a voltage pulse in a given location of the actin filament, and FALSE to the pulse's absence, so that information flows along the filament with pulse transmission. When two pulses, representing Boolean values of input variables, interact, then they can facilitate or inhibit further propagation of each other. We explore this phenomenon to construct Boolean logical gates and a one-bit half-adder with interacting voltage pulses. We discuss implications of these findings on cellular process and technological applications.
PyBoolNet: a python package for the generation, analysis and visualization of boolean networks.
Klarner, Hannes; Streck, Adam; Siebert, Heike
2017-03-01
The goal of this project is to provide a simple interface to working with Boolean networks. Emphasis is put on easy access to a large number of common tasks including the generation and manipulation of networks, attractor and basin computation, model checking and trap space computation, execution of established graph algorithms as well as graph drawing and layouts. P y B ool N et is a Python package for working with Boolean networks that supports simple access to model checking via N u SMV, standard graph algorithms via N etwork X and visualization via dot . In addition, state of the art attractor computation exploiting P otassco ASP is implemented. The package is function-based and uses only native Python and N etwork X data types. https://github.com/hklarner/PyBoolNet. hannes.klarner@fu-berlin.de. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
Discrete dynamic modeling of cellular signaling networks.
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.
Origins of Chaos in Autonomous Boolean Networks
NASA Astrophysics Data System (ADS)
Socolar, Joshua; Cavalcante, Hugo; Gauthier, Daniel; Zhang, Rui
2010-03-01
Networks with nodes consisting of ideal Boolean logic gates are known to display either steady states, periodic behavior, or an ultraviolet catastrophe where the number of logic-transition events circulating in the network per unit time grows as a power-law. In an experiment, non-ideal behavior of the logic gates prevents the ultraviolet catastrophe and may lead to deterministic chaos. We identify certain non-ideal features of real logic gates that enable chaos in experimental networks. We find that short-pulse rejection and the asymmetry between the logic states tends to engender periodic behavior. On the other hand, a memory effect termed ``degradation'' can generate chaos. Our results strongly suggest that deterministic chaos can be expected in a large class of experimental Boolean-like networks. Such devices may find application in a variety of technologies requiring fast complex waveforms or flat power spectra. The non-ideal effects identified here also have implications for the statistics of attractors in large complex networks.
Experimental Clocking of Nanomagnets with Strain for Ultralow Power Boolean Logic.
D'Souza, Noel; Salehi Fashami, Mohammad; Bandyopadhyay, Supriyo; Atulasimha, Jayasimha
2016-02-10
Nanomagnetic implementations of Boolean logic have attracted attention because of their nonvolatility and the potential for unprecedented overall energy-efficiency. Unfortunately, the large dissipative losses that occur when nanomagnets are switched with a magnetic field or spin-transfer-torque severely compromise the energy-efficiency. Recently, there have been experimental reports of utilizing the Spin Hall effect for switching magnets, and theoretical proposals for strain induced switching of single-domain magnetostrictive nanomagnets, that might reduce the dissipative losses significantly. Here, we experimentally demonstrate, for the first time that strain-induced switching of single-domain magnetostrictive nanomagnets of lateral dimensions ∼200 nm fabricated on a piezoelectric substrate can implement a nanomagnetic Boolean NOT gate and steer bit information unidirectionally in dipole-coupled nanomagnet chains. On the basis of the experimental results with bulk PMN-PT substrates, we estimate that the energy dissipation for logic operations in a reasonably scaled system using thin films will be a mere ∼1 aJ/bit.
Runtime Verification of C Programs
NASA Technical Reports Server (NTRS)
Havelund, Klaus
2008-01-01
We present in this paper a framework, RMOR, for monitoring the execution of C programs against state machines, expressed in a textual (nongraphical) format in files separate from the program. The state machine language has been inspired by a graphical state machine language RCAT recently developed at the Jet Propulsion Laboratory, as an alternative to using Linear Temporal Logic (LTL) for requirements capture. Transitions between states are labeled with abstract event names and Boolean expressions over such. The abstract events are connected to code fragments using an aspect-oriented pointcut language similar to ASPECTJ's or ASPECTC's pointcut language. The system is implemented in the C analysis and transformation package CIL, and is programmed in OCAML, the implementation language of CIL. The work is closely related to the notion of stateful aspects within aspect-oriented programming, where pointcut languages are extended with temporal assertions over the execution trace.
Noise-induced multistability in the regulation of cancer by genes and pseudogenes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Petrosyan, K. G., E-mail: pkaren@phys.sinica.edu.tw; Hu, Chin-Kun, E-mail: huck@phys.sinica.edu.tw; National Center for Theoretical Sciences, National Tsing Hua University, Hsinchu 30013, Taiwan
2016-07-28
We extend a previously introduced model of stochastic gene regulation of cancer to a nonlinear case having both gene and pseudogene messenger RNAs (mRNAs) self-regulated. The model consists of stochastic Boolean genetic elements and possesses noise-induced multistability (multimodality). We obtain analytical expressions for probabilities for the case of constant but finite number of microRNA molecules which act as a noise source for the competing gene and pseudogene mRNAs. The probability distribution functions display both the global bistability regime as well as even-odd number oscillations for a certain range of model parameters. Statistical characteristics of the mRNA’s level fluctuations are evaluated.more » The obtained results of the extended model advance our understanding of the process of stochastic gene and pseudogene expressions that is crucial in regulation of cancer.« less
Spot the difference: Causal contrasts in scientific diagrams.
Scholl, Raphael
2016-12-01
An important function of scientific diagrams is to identify causal relationships. This commonly relies on contrasts that highlight the effects of specific difference-makers. However, causal contrast diagrams are not an obvious and easy to recognize category because they appear in many guises. In this paper, four case studies are presented to examine how causal contrast diagrams appear in a wide range of scientific reports, from experimental to observational and even purely theoretical studies. It is shown that causal contrasts can be expressed in starkly different formats, including photographs of complexly visualized macromolecules as well as line graphs, bar graphs, or plots of state spaces. Despite surface differences, however, there is a measure of conceptual unity among such diagrams. In empirical studies they often serve not only to infer and communicate specific causal claims, but also as evidence for them. The key data of some studies is given nowhere except in the diagrams. Many diagrams show multiple causal contrasts in order to demonstrate both that an effect exists and that the effect is specific - that is, to narrowly circumscribe the phenomenon to be explained. In a large range of scientific reports, causal contrast diagrams reflect the core epistemic claims of the researchers. Copyright © 2016. Published by Elsevier Ltd.
Expressions Module for the Satellite Orbit Analysis Program
NASA Technical Reports Server (NTRS)
Edmonds, Karina
2008-01-01
The Expressions Module is a software module that has been incorporated into the Satellite Orbit Analysis Program (SOAP). The module includes an expressions- parser submodule built on top of an analytical system, enabling the user to define logical and numerical variables and constants. The variables can capture output from SOAP orbital-prediction and geometric-engine computations. The module can combine variables and constants with built-in logical operators (such as Boolean AND, OR, and NOT), relational operators (such as >, <, or =), and mathematical operators (such as addition, subtraction, multiplication, division, modulus, exponentiation, differentiation, and integration). Parentheses can be used to specify precedence of operations. The module contains a library of mathematical functions and operations, including logarithms, trigonometric functions, Bessel functions, minimum/ maximum operations, and floating- point-to-integer conversions. The module supports combinations of time, distance, and angular units and has a dimensional- analysis component that checks for correct usage of units. A parser based on the Flex language and the Bison program looks for and indicates errors in syntax. SOAP expressions can be built using other expressions as arguments, thus enabling the user to build analytical trees. A graphical user interface facilitates use.
A Clb/Cdk1-mediated regulation of Fkh2 synchronizes CLB expression in the budding yeast cell cycle.
Linke, Christian; Chasapi, Anastasia; González-Novo, Alberto; Al Sawad, Istabrak; Tognetti, Silvia; Klipp, Edda; Loog, Mart; Krobitsch, Sylvia; Posas, Francesc; Xenarios, Ioannis; Barberis, Matteo
2017-01-01
Precise timing of cell division is achieved by coupling waves of cyclin-dependent kinase (Cdk) activity with a transcriptional oscillator throughout cell cycle progression. Although details of transcription of cyclin genes are known, it is unclear which is the transcriptional cascade that modulates their expression in a timely fashion. Here, we demonstrate that a Clb/Cdk1-mediated regulation of the Fkh2 transcription factor synchronizes the temporal mitotic CLB expression in budding yeast. A simplified kinetic model of the cyclin/Cdk network predicts a linear cascade where a Clb/Cdk1-mediated regulation of an activator molecule drives CLB3 and CLB2 expression. Experimental validation highlights Fkh2 as modulator of CLB3 transcript levels, besides its role in regulating CLB2 expression. A Boolean model based on the minimal number of interactions needed to capture the information flow of the Clb/Cdk1 network supports the role of an activator molecule in the sequential activation, and oscillatory behavior, of mitotic Clb cyclins. This work illustrates how transcription and phosphorylation networks can be coupled by a Clb/Cdk1-mediated regulation that synchronizes them.
Conceptual and logical level of database modeling
NASA Astrophysics Data System (ADS)
Hunka, Frantisek; Matula, Jiri
2016-06-01
Conceptual and logical levels form the top most levels of database modeling. Usually, ORM (Object Role Modeling) and ER diagrams are utilized to capture the corresponding schema. The final aim of business process modeling is to store its results in the form of database solution. For this reason, value oriented business process modeling which utilizes ER diagram to express the modeling entities and relationships between them are used. However, ER diagrams form the logical level of database schema. To extend possibilities of different business process modeling methodologies, the conceptual level of database modeling is needed. The paper deals with the REA value modeling approach to business process modeling using ER-diagrams, and derives conceptual model utilizing ORM modeling approach. Conceptual model extends possibilities for value modeling to other business modeling approaches.
Iddings, J.P.
1903-01-01
The value of graphical methods for expressing relative quantities has been well established in all kinds of statistical exposition and discussion. Their use in conveying definite conceptions of relative quantities of chemical and mineral components of rocks is becoming more and more frequent, and the value of the results in some cases can not be overestimated. This is especially true when a series or group of rocks is being considered. The intricate variations in the amounts of numerous mineral components, or of chemical components, baffle most attempts to comprehend their interrelationships by simple contemplation or by study of the numbers in which they may be expressed. Many facts and relations are overlooked which arc readily observed when diagrams are used to represent numerical figures. Moreover, visual memory is sufficiently developed in most persons to enable them to carry in mind simple geometrical forms, where it does not permit them to recollect manifold assemblages of oft-repeated numbers. Mental impressions of simple diagrams are, therefore, more definite and lasting and enable the student to store up a much greater amount of quantitative data than he could otherwise acquire.
Generating probabilistic Boolean networks from a prescribed transition probability matrix.
Ching, W-K; Chen, X; Tsing, N-K
2009-11-01
Probabilistic Boolean networks (PBNs) have received much attention in modeling genetic regulatory networks. A PBN can be regarded as a Markov chain process and is characterised by a transition probability matrix. In this study, the authors propose efficient algorithms for constructing a PBN when its transition probability matrix is given. The complexities of the algorithms are also analysed. This is an interesting inverse problem in network inference using steady-state data. The problem is important as most microarray data sets are assumed to be obtained from sampling the steady-state.
NASA Astrophysics Data System (ADS)
Willemse, Tim A. C.
We introduce the concept of consistent correlations for parameterised Boolean equation systems (PBESs), motivated largely by the laborious proofs of correctness required for most manipulations in this setting. Consistent correlations focus on relating the equations that occur in PBESs, rather than their solutions. For a fragment of PBESs, consistent correlations are shown to coincide with a recently introduced form of bisimulation. Finally, we show that bisimilarity on processes induces consistent correlations on PBESs encoding model checking problems. We apply our theory to two example manipulations from the literature.
A Parallel Approach in Computing Correlation Immunity up to Six Variables
2015-03-10
their nonlinearity is divisible by 4. Let CI(n, k) (respectively, BCI (n, k)) be the number of exact order k correlation im- mune, (respectively...further balanced) n-variable Boolean functions. The notations CI(n, k, d), BCI (n, k, d) restricts the previous count to degree d Boolean functions...Theorem 3. The following are true: (i) BCI (n, n, 0) = 0, CI(n, n, 0) = 2, CI(n, k, 1) = BCI (n, k, 1) = 2 ( n k+1 ) , 0 ≤ k ≤ n− 1. (ii) BCI (n, n− 2) = 2
On Weak and Strong 2k- bent Boolean Functions
2016-01-01
U.S.A. Email: pstanica@nps.edu Abstract—In this paper we introduce a sequence of discrete Fourier transforms and define new versions of bent...denotes the complex conjugate of z. An important tool in our analysis is the discrete Fourier transform , known in Boolean functions literature, as Walsh...Hadamard, or Walsh–Hadamard transform , which is the func- tion Wf : Fn2 → C, defined by Wf (u) = 2− n 2 ∑ x∈Vn (−1)f(x)⊕u·x. Any f ∈ Bn can be
Qubits and quantum Hamiltonian computing performances for operating a digital Boolean 1/2-adder
NASA Astrophysics Data System (ADS)
Dridi, Ghassen; Faizy Namarvar, Omid; Joachim, Christian
2018-04-01
Quantum Boolean (1 + 1) digits 1/2-adders are designed with 3 qubits for the quantum computing (Qubits) and 4 quantum states for the quantum Hamiltonian computing (QHC) approaches. Detailed analytical solutions are provided to analyse the time operation of those different 1/2-adder gates. QHC is more robust to noise than Qubits and requires about the same amount of energy for running its 1/2-adder logical operations. QHC is faster in time than Qubits but its logical output measurement takes longer.
Mathematical modeling of gene expression: a guide for the perplexed biologist
Ay, Ahmet; Arnosti, David N.
2011-01-01
The detailed analysis of transcriptional networks holds a key for understanding central biological processes, and interest in this field has exploded due to new large-scale data acquisition techniques. Mathematical modeling can provide essential insights, but the diversity of modeling approaches can be a daunting prospect to investigators new to this area. For those interested in beginning a transcriptional mathematical modeling project we provide here an overview of major types of models and their applications to transcriptional networks. In this discussion of recent literature on thermodynamic, Boolean and differential equation models we focus on considerations critical for choosing and validating a modeling approach that will be useful for quantitative understanding of biological systems. PMID:21417596
Measuring Questions: Relevance and its Relation to Entropy
NASA Technical Reports Server (NTRS)
Knuth, Kevin H.
2004-01-01
The Boolean lattice of logical statements induces the free distributive lattice of questions. Inclusion on this lattice is based on whether one question answers another. Generalizing the zeta function of the question lattice leads to a valuation called relevance or bearing, which is a measure of the degree to which one question answers another. Richard Cox conjectured that this degree can be expressed as a generalized entropy. With the assistance of yet another important result from Janos Acz6l, I show that this is indeed the case; and that the resulting inquiry calculus is a natural generalization of information theory. This approach provides a new perspective of the Principle of Maximum Entropy.
Evaluating Feynman integrals by the hypergeometry
NASA Astrophysics Data System (ADS)
Feng, Tai-Fu; Chang, Chao-Hsi; Chen, Jian-Bin; Gu, Zhi-Hua; Zhang, Hai-Bin
2018-02-01
The hypergeometric function method naturally provides the analytic expressions of scalar integrals from concerned Feynman diagrams in some connected regions of independent kinematic variables, also presents the systems of homogeneous linear partial differential equations satisfied by the corresponding scalar integrals. Taking examples of the one-loop B0 and massless C0 functions, as well as the scalar integrals of two-loop vacuum and sunset diagrams, we verify our expressions coinciding with the well-known results of literatures. Based on the multiple hypergeometric functions of independent kinematic variables, the systems of homogeneous linear partial differential equations satisfied by the mentioned scalar integrals are established. Using the calculus of variations, one recognizes the system of linear partial differential equations as stationary conditions of a functional under some given restrictions, which is the cornerstone to perform the continuation of the scalar integrals to whole kinematic domains numerically with the finite element methods. In principle this method can be used to evaluate the scalar integrals of any Feynman diagrams.
Exploratory analysis regarding the domain definitions for computer based analytical models
NASA Astrophysics Data System (ADS)
Raicu, A.; Oanta, E.; Barhalescu, M.
2017-08-01
Our previous computer based studies dedicated to structural problems using analytical methods defined the composite cross section of a beam as a result of Boolean operations with so-called ‘simple’ shapes. Using generalisations, in the class of the ‘simple’ shapes were included areas bounded by curves approximated using spline functions and areas approximated as polygons. However, particular definitions lead to particular solutions. In order to ascend above the actual limitations, we conceived a general definition of the cross sections that are considered now calculus domains consisting of several subdomains. The according set of input data use complex parameterizations. This new vision allows us to naturally assign a general number of attributes to the subdomains. In this way there may be modelled new phenomena that use map-wise information, such as the metal alloys equilibrium diagrams. The hierarchy of the input data text files that use the comma-separated-value format and their structure are also presented and discussed in the paper. This new approach allows us to reuse the concepts and part of the data processing software instruments already developed. The according software to be subsequently developed will be modularised and generalised in order to be used in the upcoming projects that require rapid development of computer based models.
Synchronous versus asynchronous modeling of gene regulatory networks.
Garg, Abhishek; Di Cara, Alessandro; Xenarios, Ioannis; Mendoza, Luis; De Micheli, Giovanni
2008-09-01
In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.
Zhou, Jindan; Rudd, Kenneth E.
2013-01-01
EcoGene (http://ecogene.org) is a database and website devoted to continuously improving the structural and functional annotation of Escherichia coli K-12, one of the most well understood model organisms, represented by the MG1655(Seq) genome sequence and annotations. Major improvements to EcoGene in the past decade include (i) graphic presentations of genome map features; (ii) ability to design Boolean queries and Venn diagrams from EcoArray, EcoTopics or user-provided GeneSets; (iii) the genome-wide clone and deletion primer design tool, PrimerPairs; (iv) sequence searches using a customized EcoBLAST; (v) a Cross Reference table of synonymous gene and protein identifiers; (vi) proteome-wide indexing with GO terms; (vii) EcoTools access to >2000 complete bacterial genomes in EcoGene-RefSeq; (viii) establishment of a MySql relational database; and (ix) use of web content management systems. The biomedical literature is surveyed daily to provide citation and gene function updates. As of September 2012, the review of 37 397 abstracts and articles led to creation of 98 425 PubMed-Gene links and 5415 PubMed-Topic links. Annotation updates to Genbank U00096 are transmitted from EcoGene to NCBI. Experimental verifications include confirmation of a CTG start codon, pseudogene restoration and quality assurance of the Keio strain collection. PMID:23197660
Zhou, Jindan; Rudd, Kenneth E
2013-01-01
EcoGene (http://ecogene.org) is a database and website devoted to continuously improving the structural and functional annotation of Escherichia coli K-12, one of the most well understood model organisms, represented by the MG1655(Seq) genome sequence and annotations. Major improvements to EcoGene in the past decade include (i) graphic presentations of genome map features; (ii) ability to design Boolean queries and Venn diagrams from EcoArray, EcoTopics or user-provided GeneSets; (iii) the genome-wide clone and deletion primer design tool, PrimerPairs; (iv) sequence searches using a customized EcoBLAST; (v) a Cross Reference table of synonymous gene and protein identifiers; (vi) proteome-wide indexing with GO terms; (vii) EcoTools access to >2000 complete bacterial genomes in EcoGene-RefSeq; (viii) establishment of a MySql relational database; and (ix) use of web content management systems. The biomedical literature is surveyed daily to provide citation and gene function updates. As of September 2012, the review of 37 397 abstracts and articles led to creation of 98 425 PubMed-Gene links and 5415 PubMed-Topic links. Annotation updates to Genbank U00096 are transmitted from EcoGene to NCBI. Experimental verifications include confirmation of a CTG start codon, pseudogene restoration and quality assurance of the Keio strain collection.
Stochastic, real-space, imaginary-time evaluation of third-order Feynman-Goldstone diagrams
NASA Astrophysics Data System (ADS)
Willow, Soohaeng Yoo; Hirata, So
2014-01-01
A new, alternative set of interpretation rules of Feynman-Goldstone diagrams for many-body perturbation theory is proposed, which translates diagrams into algebraic expressions suitable for direct Monte Carlo integrations. A vertex of a diagram is associated with a Coulomb interaction (rather than a two-electron integral) and an edge with the trace of a Green's function in real space and imaginary time. With these, 12 diagrams of third-order many-body perturbation (MP3) theory are converted into 20-dimensional integrals, which are then evaluated by a Monte Carlo method. It uses redundant walkers for convergence acceleration and a weight function for importance sampling in conjunction with the Metropolis algorithm. The resulting Monte Carlo MP3 method has low-rank polynomial size dependence of the operation cost, a negligible memory cost, and a naturally parallel computational kernel, while reproducing the correct correlation energies of small molecules within a few mEh after 106 Monte Carlo steps.
Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach.
Steggles, L Jason; Banks, Richard; Shaw, Oliver; Wipat, Anil
2007-02-01
New developments in post-genomic technology now provide researchers with the data necessary to study regulatory processes in a holistic fashion at multiple levels of biological organization. One of the major challenges for the biologist is to integrate and interpret these vast data resources to gain a greater understanding of the structure and function of the molecular processes that mediate adaptive and cell cycle driven changes in gene expression. In order to achieve this biologists require new tools and techniques to allow pathway related data to be modelled and analysed as network structures, providing valuable insights which can then be validated and investigated in the laboratory. We propose a new technique for constructing and analysing qualitative models of genetic regulatory networks based on the Petri net formalism. We take as our starting point the Boolean network approach of treating genes as binary switches and develop a new Petri net model which uses logic minimization to automate the construction of compact qualitative models. Our approach addresses the shortcomings of Boolean networks by providing access to the wide range of existing Petri net analysis techniques and by using non-determinism to cope with incomplete and inconsistent data. The ideas we present are illustrated by a case study in which the genetic regulatory network controlling sporulation in the bacterium Bacillus subtilis is modelled and analysed. The Petri net model construction tool and the data files for the B. subtilis sporulation case study are available at http://bioinf.ncl.ac.uk/gnapn.
Hall-plot of the phase diagram for Ba(Fe1-xCox)2As2
NASA Astrophysics Data System (ADS)
Iida, Kazumasa; Grinenko, Vadim; Kurth, Fritz; Ichinose, Ataru; Tsukada, Ichiro; Ahrens, Eike; Pukenas, Aurimas; Chekhonin, Paul; Skrotzki, Werner; Teresiak, Angelika; Hühne, Ruben; Aswartham, Saicharan; Wurmehl, Sabine; Mönch, Ingolf; Erbe, Manuela; Hänisch, Jens; Holzapfel, Bernhard; Drechsler, Stefan-Ludwig; Efremov, Dmitri V.
2016-06-01
The Hall effect is a powerful tool for investigating carrier type and density. For single-band materials, the Hall coefficient is traditionally expressed simply by , where e is the charge of the carrier, and n is the concentration. However, it is well known that in the critical region near a quantum phase transition, as it was demonstrated for cuprates and heavy fermions, the Hall coefficient exhibits strong temperature and doping dependencies, which can not be described by such a simple expression, and the interpretation of the Hall coefficient for Fe-based superconductors is also problematic. Here, we investigate thin films of Ba(Fe1-xCox)2As2 with compressive and tensile in-plane strain in a wide range of Co doping. Such in-plane strain changes the band structure of the compounds, resulting in various shifts of the whole phase diagram as a function of Co doping. We show that the resultant phase diagrams for different strain states can be mapped onto a single phase diagram with the Hall number. This universal plot is attributed to the critical fluctuations in multiband systems near the antiferromagnetic transition, which may suggest a direct link between magnetic and superconducting properties in the BaFe2As2 system.
Logic circuits from zero forcing.
Burgarth, Daniel; Giovannetti, Vittorio; Hogben, Leslie; Severini, Simone; Young, Michael
We design logic circuits based on the notion of zero forcing on graphs; each gate of the circuits is a gadget in which zero forcing is performed. We show that such circuits can evaluate every monotone Boolean function. By using two vertices to encode each logical bit, we obtain universal computation. We also highlight a phenomenon of "back forcing" as a property of each function. Such a phenomenon occurs in a circuit when the input of gates which have been already used at a given time step is further modified by a computation actually performed at a later stage. Finally, we show that zero forcing can be also used to implement reversible computation. The model introduced here provides a potentially new tool in the analysis of Boolean functions, with particular attention to monotonicity. Moreover, in the light of applications of zero forcing in quantum mechanics, the link with Boolean functions may suggest a new directions in quantum control theory and in the study of engineered quantum spin systems. It is an open technical problem to verify whether there is a link between zero forcing and computation with contact circuits.
Introduction to focus issue: quantitative approaches to genetic networks.
Albert, Réka; Collins, James J; Glass, Leon
2013-06-01
All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.
Discrete Logic Modelling Optimization to Contextualize Prior Knowledge Networks Using PRUNET
Androsova, Ganna; del Sol, Antonio
2015-01-01
High-throughput technologies have led to the generation of an increasing amount of data in different areas of biology. Datasets capturing the cell’s response to its intra- and extra-cellular microenvironment allows such data to be incorporated as signed and directed graphs or influence networks. These prior knowledge networks (PKNs) represent our current knowledge of the causality of cellular signal transduction. New signalling data is often examined and interpreted in conjunction with PKNs. However, different biological contexts, such as cell type or disease states, may have distinct variants of signalling pathways, resulting in the misinterpretation of new data. The identification of inconsistencies between measured data and signalling topologies, as well as the training of PKNs using context specific datasets (PKN contextualization), are necessary conditions to construct reliable, predictive models, which are current challenges in the systems biology of cell signalling. Here we present PRUNET, a user-friendly software tool designed to address the contextualization of a PKNs to specific experimental conditions. As the input, the algorithm takes a PKN and the expression profile of two given stable steady states or cellular phenotypes. The PKN is iteratively pruned using an evolutionary algorithm to perform an optimization process. This optimization rests in a match between predicted attractors in a discrete logic model (Boolean) and a Booleanized representation of the phenotypes, within a population of alternative subnetworks that evolves iteratively. We validated the algorithm applying PRUNET to four biological examples and using the resulting contextualized networks to predict missing expression values and to simulate well-characterized perturbations. PRUNET constitutes a tool for the automatic curation of a PKN to make it suitable for describing biological processes under particular experimental conditions. The general applicability of the implemented algorithm makes PRUNET suitable for a variety of biological processes, for instance cellular reprogramming or transitions between healthy and disease states. PMID:26058016
Structures and Boolean Dynamics in Gene Regulatory Networks
NASA Astrophysics Data System (ADS)
Szedlak, Anthony
This dissertation discusses the topological and dynamical properties of GRNs in cancer, and is divided into four main chapters. First, the basic tools of modern complex network theory are introduced. These traditional tools as well as those developed by myself (set efficiency, interset efficiency, and nested communities) are crucial for understanding the intricate topological properties of GRNs, and later chapters recall these concepts. Second, the biology of gene regulation is discussed, and a method for disease-specific GRN reconstruction developed by our collaboration is presented. This complements the traditional exhaustive experimental approach of building GRNs edge-by-edge by quickly inferring the existence of as of yet undiscovered edges using correlations across sets of gene expression data. This method also provides insight into the distribution of common mutations across GRNs. Third, I demonstrate that the structures present in these reconstructed networks are strongly related to the evolutionary histories of their constituent genes. Investigation of how the forces of evolution shaped the topology of GRNs in multicellular organisms by growing outward from a core of ancient, conserved genes can shed light upon the ''reverse evolution'' of normal cells into unicellular-like cancer states. Next, I simulate the dynamics of the GRNs of cancer cells using the Hopfield model, an infinite range spin-glass model designed with the ability to encode Boolean data as attractor states. This attractor-driven approach facilitates the integration of gene expression data into predictive mathematical models. Perturbations representing therapeutic interventions are applied to sets of genes, and the resulting deviations from their attractor states are recorded, suggesting new potential drug targets for experimentation. Finally, I extend the Hopfield model to modular networks, cyclic attractors, and complex attractors, and apply these concepts to simulations of the cell cycle process. Futher development of these and other theoretical and computational tools is necessary to analyze the deluge of experimental data produced by modern and future biological high throughput methods. (Abstract shortened by ProQuest.).
Introduction to Focus Issue: Quantitative Approaches to Genetic Networks
NASA Astrophysics Data System (ADS)
Albert, Réka; Collins, James J.; Glass, Leon
2013-06-01
All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.
On construction of stochastic genetic networks based on gene expression sequences.
Ching, Wai-Ki; Ng, Michael M; Fung, Eric S; Akutsu, Tatsuya
2005-08-01
Reconstruction of genetic regulatory networks from time series data of gene expression patterns is an important research topic in bioinformatics. Probabilistic Boolean Networks (PBNs) have been proposed as an effective model for gene regulatory networks. PBNs are able to cope with uncertainty, corporate rule-based dependencies between genes and discover the sensitivity of genes in their interactions with other genes. However, PBNs are unlikely to use directly in practice because of huge amount of computational cost for obtaining predictors and their corresponding probabilities. In this paper, we propose a multivariate Markov model for approximating PBNs and describing the dynamics of a genetic network for gene expression sequences. The main contribution of the new model is to preserve the strength of PBNs and reduce the complexity of the networks. The number of parameters of our proposed model is O(n2) where n is the number of genes involved. We also develop efficient estimation methods for solving the model parameters. Numerical examples on synthetic data sets and practical yeast data sequences are given to demonstrate the effectiveness of the proposed model.
NASA Astrophysics Data System (ADS)
Gong, Weiwei; Zhou, Xu
2017-06-01
In Computer Science, the Boolean Satisfiability Problem(SAT) is the problem of determining if there exists an interpretation that satisfies a given Boolean formula. SAT is one of the first problems that was proven to be NP-complete, which is also fundamental to artificial intelligence, algorithm and hardware design. This paper reviews the main algorithms of the SAT solver in recent years, including serial SAT algorithms, parallel SAT algorithms, SAT algorithms based on GPU, and SAT algorithms based on FPGA. The development of SAT is analyzed comprehensively in this paper. Finally, several possible directions for the development of the SAT problem are proposed.
NASA Technical Reports Server (NTRS)
Strahler, Alan H.; Jupp, David L. B.
1990-01-01
Geometric-optical discrete-element mathematical models for forest canopies have been developed using the Boolean logic and models of Serra. The geometric-optical approach is considered to be particularly well suited to describing the bidirectional reflectance of forest woodland canopies, where the concentration of leaf material within crowns and the resulting between-tree gaps make plane-parallel, radiative-transfer models inappropriate. The approach leads to invertible formulations, in which the spatial and directional variance provides the means for remote estimation of tree crown size, shape, and total cover from remotedly sensed imagery.
A Parallel Approach in Computing Correlation Immunity up to Six Variables
2015-07-24
nonlinearity is divisible by 4. Let CI(n, k) (respectively, BCI (n, k)) be the number of exact order k corre- lation immune, (respectively, further...balanced) n-variable Boolean functions. The notations CI(n, k, d), BCI (n, k, d) restricts the previous count to degree d Boolean functions. Theorem 3...The following are true: (i) BCI (n, n, 0) = 0, CI(n, n, 0) = 2, CI(n, k, 1) = BCI (n, k, 1) = 2 ( n k+1 ) , 0 ≤ k ≤ n− 1. (ii) BCI (n, n− 2) = 2 ( n n−1
High speed all optical logic gates based on quantum dot semiconductor optical amplifiers.
Ma, Shaozhen; Chen, Zhe; Sun, Hongzhi; Dutta, Niloy K
2010-03-29
A scheme to realize all-optical Boolean logic functions AND, XOR and NOT using semiconductor optical amplifiers with quantum-dot active layers is studied. nonlinear dynamics including carrier heating and spectral hole-burning are taken into account together with the rate equations scheme. Results show with QD excited state and wetting layer serving as dual-reservoir of carriers, as well as the ultra fast carrier relaxation of the QD device, this scheme is suitable for high speed Boolean logic operations. Logic operation can be carried out up to speed of 250 Gb/s.
Pathway collages: personalized multi-pathway diagrams.
Paley, Suzanne; O'Maille, Paul E; Weaver, Daniel; Karp, Peter D
2016-12-13
Metabolic pathway diagrams are a classical way of visualizing a linked cascade of biochemical reactions. However, to understand some biochemical situations, viewing a single pathway is insufficient, whereas viewing the entire metabolic network results in information overload. How do we enable scientists to rapidly construct personalized multi-pathway diagrams that depict a desired collection of interacting pathways that emphasize particular pathway interactions? We define software for constructing personalized multi-pathway diagrams called pathway-collages using a combination of manual and automatic layouts. The user specifies a set of pathways of interest for the collage from a Pathway/Genome Database. Layouts for the individual pathways are generated by the Pathway Tools software, and are sent to a Javascript Pathway Collage application implemented using Cytoscape.js. That application allows the user to re-position pathways; define connections between pathways; change visual style parameters; and paint metabolomics, gene expression, and reaction flux data onto the collage to obtain a desired multi-pathway diagram. We demonstrate the use of pathway collages in two application areas: a metabolomics study of pathogen drug response, and an Escherichia coli metabolic model. Pathway collages enable facile construction of personalized multi-pathway diagrams.
How little data is enough? Phase-diagram analysis of sparsity-regularized X-ray computed tomography
Jørgensen, J. S.; Sidky, E. Y.
2015-01-01
We introduce phase-diagram analysis, a standard tool in compressed sensing (CS), to the X-ray computed tomography (CT) community as a systematic method for determining how few projections suffice for accurate sparsity-regularized reconstruction. In CS, a phase diagram is a convenient way to study and express certain theoretical relations between sparsity and sufficient sampling. We adapt phase-diagram analysis for empirical use in X-ray CT for which the same theoretical results do not hold. We demonstrate in three case studies the potential of phase-diagram analysis for providing quantitative answers to questions of undersampling. First, we demonstrate that there are cases where X-ray CT empirically performs comparably with a near-optimal CS strategy, namely taking measurements with Gaussian sensing matrices. Second, we show that, in contrast to what might have been anticipated, taking randomized CT measurements does not lead to improved performance compared with standard structured sampling patterns. Finally, we show preliminary results of how well phase-diagram analysis can predict the sufficient number of projections for accurately reconstructing a large-scale image of a given sparsity by means of total-variation regularization. PMID:25939620
How little data is enough? Phase-diagram analysis of sparsity-regularized X-ray computed tomography.
Jørgensen, J S; Sidky, E Y
2015-06-13
We introduce phase-diagram analysis, a standard tool in compressed sensing (CS), to the X-ray computed tomography (CT) community as a systematic method for determining how few projections suffice for accurate sparsity-regularized reconstruction. In CS, a phase diagram is a convenient way to study and express certain theoretical relations between sparsity and sufficient sampling. We adapt phase-diagram analysis for empirical use in X-ray CT for which the same theoretical results do not hold. We demonstrate in three case studies the potential of phase-diagram analysis for providing quantitative answers to questions of undersampling. First, we demonstrate that there are cases where X-ray CT empirically performs comparably with a near-optimal CS strategy, namely taking measurements with Gaussian sensing matrices. Second, we show that, in contrast to what might have been anticipated, taking randomized CT measurements does not lead to improved performance compared with standard structured sampling patterns. Finally, we show preliminary results of how well phase-diagram analysis can predict the sufficient number of projections for accurately reconstructing a large-scale image of a given sparsity by means of total-variation regularization.
Controlling false-negative errors in microarray differential expression analysis: a PRIM approach.
Cole, Steve W; Galic, Zoran; Zack, Jerome A
2003-09-22
Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed 'false negative' error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements. Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays. Freestanding JAVA application at http://microarray.crump.ucla.edu/focus
Barnabe, Cheryl; Thanh, Nguyen Xuan; Ohinmaa, Arto; Homik, Joanne; Barr, Susan G; Martin, Liam; Maksymowych, Walter P
2014-08-01
Sustained remission in rheumatoid arthritis (RA) results in healthcare utilization cost savings. We evaluated the variation in estimates of savings when different definitions of remission [2011 American College of Rheumatology/European League Against Rheumatism Boolean Definition, Simplified Disease Activity Index (SDAI) ≤ 3.3, Clinical Disease Activity Index (CDAI) ≤ 2.8, and Disease Activity Score-28 (DAS28) ≤ 2.6] are applied. The annual mean healthcare service utilization costs were estimated from provincial physician billing claims, outpatient visits, and hospitalizations, with linkage to clinical data from the Alberta Biologics Pharmacosurveillance Program (ABioPharm). Cost savings in patients who had a 1-year continuous period of remission were compared to those who did not, using 4 definitions of remission. In 1086 patients, sustained remission rates were 16.1% for DAS28, 8.8% for Boolean, 5.5% for CDAI, and 4.2% for SDAI. The estimated mean annual healthcare cost savings per patient achieving remission (relative to not) were SDAI $1928 (95% CI 592, 3264), DAS28 $1676 (95% CI 987, 2365), and Boolean $1259 (95% CI 417, 2100). The annual savings by CDAI remission per patient were not significant at $423 (95% CI -1757, 2602). For patients in DAS28, Boolean, and SDAI remission, savings were seen both in costs directly related to RA and its comorbidities, and in costs for non-RA-related conditions. The magnitude of the healthcare cost savings varies according to the remission definition used in classifying patient disease status. The highest point estimate for cost savings was observed in patients attaining SDAI remission and the least with the CDAI; confidence intervals for these estimates do overlap. Future pharmacoeconomic analyses should employ all response definitions in assessing the influence of treatment.
Modeling and controlling the two-phase dynamics of the p53 network: a Boolean network approach
NASA Astrophysics Data System (ADS)
Lin, Guo-Qiang; Ao, Bin; Chen, Jia-Wei; Wang, Wen-Xu; Di, Zeng-Ru
2014-12-01
Although much empirical evidence has demonstrated that p53 plays a key role in tumor suppression, the dynamics and function of the regulatory network centered on p53 have not yet been fully understood. Here, we develop a Boolean network model to reproduce the two-phase dynamics of the p53 network in response to DNA damage. In particular, we map the fates of cells into two types of Boolean attractors, and we find that the apoptosis attractor does not exist for minor DNA damage, reflecting that the cell is reparable. As the amount of DNA damage increases, the basin of the repair attractor shrinks, accompanied by the rising of the apoptosis attractor and the expansion of its basin, indicating that the cell becomes more irreparable with more DNA damage. For severe DNA damage, the repair attractor vanishes, and the apoptosis attractor dominates the state space, accounting for the exclusive fate of death. Based on the Boolean network model, we explore the significance of links, in terms of the sensitivity of the two-phase dynamics, to perturbing the weights of links and removing them. We find that the links are either critical or ordinary, rather than redundant. This implies that the p53 network is irreducible, but tolerant of small mutations at some ordinary links, and this can be interpreted with evolutionary theory. We further devised practical control schemes for steering the system into the apoptosis attractor in the presence of DNA damage by pinning the state of a single node or perturbing the weight of a single link. Our approach offers insights into understanding and controlling the p53 network, which is of paramount importance for medical treatment and genetic engineering.
Wittmann, Dominik M; Krumsiek, Jan; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Klamt, Steffen; Theis, Fabian J
2009-01-01
Background The understanding of regulatory and signaling networks has long been a core objective in Systems Biology. Knowledge about these networks is mainly of qualitative nature, which allows the construction of Boolean models, where the state of a component is either 'off' or 'on'. While often able to capture the essential behavior of a network, these models can never reproduce detailed time courses of concentration levels. Nowadays however, experiments yield more and more quantitative data. An obvious question therefore is how qualitative models can be used to explain and predict the outcome of these experiments. Results In this contribution we present a canonical way of transforming Boolean into continuous models, where the use of multivariate polynomial interpolation allows transformation of logic operations into a system of ordinary differential equations (ODE). The method is standardized and can readily be applied to large networks. Other, more limited approaches to this task are briefly reviewed and compared. Moreover, we discuss and generalize existing theoretical results on the relation between Boolean and continuous models. As a test case a logical model is transformed into an extensive continuous ODE model describing the activation of T-cells. We discuss how parameters for this model can be determined such that quantitative experimental results are explained and predicted, including time-courses for multiple ligand concentrations and binding affinities of different ligands. This shows that from the continuous model we may obtain biological insights not evident from the discrete one. Conclusion The presented approach will facilitate the interaction between modeling and experiments. Moreover, it provides a straightforward way to apply quantitative analysis methods to qualitatively described systems. PMID:19785753
Hirabayashi, Yasuhiko; Ishii, Tomonori
2013-01-01
To seek the cutoff value of the 28-joint disease activity score using erythrocyte sedimentation rate (DAS28-ESR) that is necessary to achieve remission under the new Boolean-based criteria, we analyzed the data for 285 patients with rheumatoid arthritis registered between May 2008 and November 2009 by the Michinoku Tocilizumab Study Group and observed for 1 year after receiving tocilizumab (TCZ) in real clinical practice. Remission rates under the DAS28-ESR criteria and the Boolean criteria were assessed every 6 months after the first TCZ dose. The DAS28-ESR cutoff value necessary to achieve remission under the new criteria was analyzed by receiver operating characteristic (ROC) analysis. Data were analyzed using last observation carried forward. After 12 months of TCZ use, remission was achieved in 164 patients (57.5 %) by DAS28-ESR and 71 patients (24.9 %) under the new criteria for clinical trials. CRP levels scarcely affected remission rates, and the difference between remission rates defined by DAS28-ESR and by the new criteria was mainly due to patient global assessment (PGA). Improvement of PGA was inversely related to disease duration. ROC analysis revealed that the DAS28-ESR cutoff value necessary to predict remission under the new criteria for clinical trials was 1.54, with a sensitivity of 88.7 %, specificity of 85.5 %, positive predictive value of 67.0 %, and negative predictive value of 95.8 %. A DAS28-ESR cutoff value of 1.54 may be reasonable to predict achievement of remission under the new Boolean-based criteria for clinical trials in patients receiving TCZ.
Exact Maximum-Entropy Estimation with Feynman Diagrams
NASA Astrophysics Data System (ADS)
Netser Zernik, Amitai; Schlank, Tomer M.; Tessler, Ran J.
2018-02-01
A longstanding open problem in statistics is finding an explicit expression for the probability measure which maximizes entropy with respect to given constraints. In this paper a solution to this problem is found, using perturbative Feynman calculus. The explicit expression is given as a sum over weighted trees.
Stage line diagram: an age-conditional reference diagram for tracking development.
van Buuren, Stef; Ooms, Jeroen C L
2009-05-15
This paper presents a method for calculating stage line diagrams, a novel type of reference diagram useful for tracking developmental processes over time. Potential fields of applications include: dentistry (tooth eruption), oncology (tumor grading, cancer staging), virology (HIV infection and disease staging), psychology (stages of cognitive development), human development (pubertal stages) and chronic diseases (stages of dementia). Transition probabilities between successive stages are modeled as smoothly varying functions of age. Age-conditional references are calculated from the modeled probabilities by the mid-P value. It is possible to eliminate the influence of age by calculating standard deviation scores (SDS). The method is applied to the empirical data to produce reference charts on secondary sexual maturation. The mean of the empirical SDS in the reference population is close to zero, whereas the variance depends on age. The stage line diagram provides quick insight into both status (in SDS) and tempo (in SDS/year) of development of an individual child. Other measures (e.g. height SDS, body mass index SDS) from the same child can be added to the chart. Diagrams for sexual maturation are available as a web application at http://vps.stefvanbuuren.nl/puberty. The stage line diagram expresses status and tempo of discrete changes on a continuous scale. Wider application of these measures scores opens up new analytic possibilities. (c) 2009 John Wiley & Sons, Ltd.
Walko, Gernot; Viswanathan, Priyalakshmi; Tihy, Matthieu; Nijjher, Jagdeesh; Dunn, Sara-Jane; Lamond, Angus I
2017-01-01
Epidermal homeostasis depends on a balance between stem cell renewal and terminal differentiation. The transition between the two cell states, termed commitment, is poorly understood. Here, we characterise commitment by integrating transcriptomic and proteomic data from disaggregated primary human keratinocytes held in suspension to induce differentiation. Cell detachment induces several protein phosphatases, five of which - DUSP6, PPTC7, PTPN1, PTPN13 and PPP3CA – promote differentiation by negatively regulating ERK MAPK and positively regulating AP1 transcription factors. Conversely, DUSP10 expression antagonises commitment. The phosphatases form a dynamic network of transient positive and negative interactions that change over time, with DUSP6 predominating at commitment. Boolean network modelling identifies a mandatory switch between two stable states (stem and differentiated) via an unstable (committed) state. Phosphatase expression is also spatially regulated in vivo and in vitro. We conclude that an auto-regulatory phosphatase network maintains epidermal homeostasis by controlling the onset and duration of commitment. PMID:29043977
Influenza-like illness surveillance on Twitter through automated learning of naïve language.
Gesualdo, Francesco; Stilo, Giovanni; Agricola, Eleonora; Gonfiantini, Michaela V; Pandolfi, Elisabetta; Velardi, Paola; Tozzi, Alberto E
2013-01-01
Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillance. When speaking of an illness, Twitter users often report a combination of symptoms, rather than a suspected or final diagnosis, using naïve, everyday language. We developed a minimally trained algorithm that exploits the abundance of health-related web pages to identify all jargon expressions related to a specific technical term. We then translated an influenza case definition into a Boolean query, each symptom being described by a technical term and all related jargon expressions, as identified by the algorithm. Subsequently, we monitored all tweets that reported a combination of symptoms satisfying the case definition query. In order to geolocalize messages, we defined 3 localization strategies based on codes associated with each tweet. We found a high correlation coefficient between the trend of our influenza-positive tweets and ILI trends identified by US traditional surveillance systems.
Influenza-Like Illness Surveillance on Twitter through Automated Learning of Naïve Language
Gesualdo, Francesco; Stilo, Giovanni; Agricola, Eleonora; Gonfiantini, Michaela V.; Pandolfi, Elisabetta; Velardi, Paola; Tozzi, Alberto E.
2013-01-01
Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillance. When speaking of an illness, Twitter users often report a combination of symptoms, rather than a suspected or final diagnosis, using naïve, everyday language. We developed a minimally trained algorithm that exploits the abundance of health-related web pages to identify all jargon expressions related to a specific technical term. We then translated an influenza case definition into a Boolean query, each symptom being described by a technical term and all related jargon expressions, as identified by the algorithm. Subsequently, we monitored all tweets that reported a combination of symptoms satisfying the case definition query. In order to geolocalize messages, we defined 3 localization strategies based on codes associated with each tweet. We found a high correlation coefficient between the trend of our influenza-positive tweets and ILI trends identified by US traditional surveillance systems. PMID:24324799
Jafari, Mohieddin; Ansari-Pour, Naser; Azimzadeh, Sadegh; Mirzaie, Mehdi
It is nearly half a century past the age of the introduction of the Central Dogma (CD) of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology.
Jafari, Mohieddin; Ansari-Pour, Naser; Azimzadeh, Sadegh; Mirzaie, Mehdi
2017-01-01
It is nearly half a century past the age of the introduction of the Central Dogma (CD) of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology. PMID:29267315
DOE Office of Scientific and Technical Information (OSTI.GOV)
Miyadera, Takayuki; Imai, Hideki; Graduate School of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551
This paper discusses the no-cloning theorem in a logicoalgebraic approach. In this approach, an orthoalgebra is considered as a general structure for propositions in a physical theory. We proved that an orthoalgebra admits cloning operation if and only if it is a Boolean algebra. That is, only classical theory admits the cloning of states. If unsharp propositions are to be included in the theory, then a notion of effect algebra is considered. We proved that an atomic Archimedean effect algebra admitting cloning operation is a Boolean algebra. This paper also presents a partial result, indicating a relation between the cloningmore » on effect algebras and hidden variables.« less
1982-11-05
routines required by the Back End. 3.3 Detailed Functional Requirements 3.3.1 Front End 3.3.1.1 DRIVER The DRIVER is the primary user interface to the...Main 2. Exam ple" !.i ,, , ,vari able • id -: go for B Boolean Ai ’ A" ’ I type d 1 I , for Boolean I (from Standard) i I - - for A function i fuction ...TN in. If a TN cannot be allocated to the primary area of storage it needs(such as a register) it is allocated to the spill area reserved in the local
A comparison of Boolean-based retrieval to the WAIS system for retrieval of aeronautical information
NASA Technical Reports Server (NTRS)
Marchionini, Gary; Barlow, Diane
1994-01-01
An evaluation of an information retrieval system using a Boolean-based retrieval engine and inverted file architecture and WAIS, which uses a vector-based engine, was conducted. Four research questions in aeronautical engineering were used to retrieve sets of citations from the NASA Aerospace Database which was mounted on a WAIS server and available through Dialog File 108 which served as the Boolean-based system (BBS). High recall and high precision searches were done in the BBS and terse and verbose queries were used in the WAIS condition. Precision values for the WAIS searches were consistently above the precision values for high recall BBS searches and consistently below the precision values for high precision BBS searches. Terse WAIS queries gave somewhat better precision performance than verbose WAIS queries. In every case, a small number of relevant documents retrieved by one system were not retrieved by the other, indicating the incomplete nature of the results from either retrieval system. Relevant documents in the WAIS searches were found to be randomly distributed in the retrieved sets rather than distributed by ranks. Advantages and limitations of both types of systems are discussed.
Feedback topology and XOR-dynamics in Boolean networks with varying input structure
NASA Astrophysics Data System (ADS)
Ciandrini, L.; Maffi, C.; Motta, A.; Bassetti, B.; Cosentino Lagomarsino, M.
2009-08-01
We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter γ . We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying γ , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.
Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks
NASA Astrophysics Data System (ADS)
Villegas, Pablo; Ruiz-Franco, José; Hidalgo, Jorge; Muñoz, Miguel A.
2016-10-01
Gene regulatory networks can be successfully modeled as Boolean networks. A much discussed hypothesis says that such model networks reproduce empirical findings the best if they are tuned to operate at criticality, i.e. at the borderline between their ordered and disordered phases. Critical networks have been argued to lead to a number of functional advantages such as maximal dynamical range, maximal sensitivity to environmental changes, as well as to an excellent tradeoff between stability and flexibility. Here, we study the effect of noise within the context of Boolean networks trained to learn complex tasks under supervision. We verify that quasi-critical networks are the ones learning in the fastest possible way -even for asynchronous updating rules- and that the larger the task complexity the smaller the distance to criticality. On the other hand, when additional sources of intrinsic noise in the network states and/or in its wiring pattern are introduced, the optimally performing networks become clearly subcritical. These results suggest that in order to compensate for inherent stochasticity, regulatory and other type of biological networks might become subcritical rather than being critical, all the most if the task to be performed has limited complexity.
On the number of different dynamics in Boolean networks with deterministic update schedules.
Aracena, J; Demongeot, J; Fanchon, E; Montalva, M
2013-04-01
Deterministic Boolean networks are a type of discrete dynamical systems widely used in the modeling of genetic networks. The dynamics of such systems is characterized by the local activation functions and the update schedule, i.e., the order in which the nodes are updated. In this paper, we address the problem of knowing the different dynamics of a Boolean network when the update schedule is changed. We begin by proving that the problem of the existence of a pair of update schedules with different dynamics is NP-complete. However, we show that certain structural properties of the interaction diagraph are sufficient for guaranteeing distinct dynamics of a network. In [1] the authors define equivalence classes which have the property that all the update schedules of a given class yield the same dynamics. In order to determine the dynamics associated to a network, we develop an algorithm to efficiently enumerate the above equivalence classes by selecting a representative update schedule for each class with a minimum number of blocks. Finally, we run this algorithm on the well known Arabidopsis thaliana network to determine the full spectrum of its different dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.
Feedback topology and XOR-dynamics in Boolean networks with varying input structure.
Ciandrini, L; Maffi, C; Motta, A; Bassetti, B; Cosentino Lagomarsino, M
2009-08-01
We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter gamma. We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying gamma , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.
Boolean logic analysis for flow regime recognition of gas-liquid horizontal flow
NASA Astrophysics Data System (ADS)
Ramskill, Nicholas P.; Wang, Mi
2011-10-01
In order to develop a flowmeter for the accurate measurement of multiphase flows, it is of the utmost importance to correctly identify the flow regime present to enable the selection of the optimal method for metering. In this study, the horizontal flow of air and water in a pipeline was studied under a multitude of conditions using electrical resistance tomography but the flow regimes that are presented in this paper have been limited to plug and bubble air-water flows. This study proposes a novel method for recognition of the prevalent flow regime using only a fraction of the data, thus rendering the analysis more efficient. By considering the average conductivity of five zones along the central axis of the tomogram, key features can be identified, thus enabling the recognition of the prevalent flow regime. Boolean logic and frequency spectrum analysis has been applied for flow regime recognition. Visualization of the flow using the reconstructed images provides a qualitative comparison between different flow regimes. Application of the Boolean logic scheme enables a quantitative comparison of the flow patterns, thus reducing the subjectivity in the identification of the prevalent flow regime.
Interference and Polarized Light.
ERIC Educational Resources Information Center
Charas, Seymour
1988-01-01
Discusses a demonstration of interference phenomena using three sheets of polaroid material, a light source, and a light meter. Describes instructional procedures with mathematical expressions and a diagram. (YP)
NASA Astrophysics Data System (ADS)
Homem-de-Mello, Luiz S.
1992-04-01
While in NASA's earlier space missions such as Voyager the number of sensors was in the hundreds, future platforms such as the Space Station Freedom will have tens of thousands sensors. For these planned missions it will be impossible to use the comprehensive monitoring strategy that was used in the past in which human operators monitored all sensors all the time. A selective monitoring strategy must be substituted for the current comprehensive strategy. This selective monitoring strategy uses computer tools to preprocess the incoming data and direct the operators' attention to the most critical parts of the physical system at any given time. There are several techniques that can be used to preprocess the incoming information. This paper presents an approach to using diagnostic reasoning techniques to preprocess the sensor data and detect which parts of the physical system require more attention because components have failed or are most likely to have failed. Given the sensor readings and a model of the physical system, a number of assertions are generated and expressed as Boolean equations. The resulting system of Boolean equations is solved symbolically. Using a priori probabilities of component failure and Bayes' rule, revised probabilities of failure can be computed. These will indicate what components have failed or are the most likely to have failed. This approach is suitable for systems that are well understood and for which the correctness of the assertions can be guaranteed. Also, the system must be such that assertions can be made from instantaneous measurements. And the system must be such that changes are slow enough to allow the computation.
NASA Astrophysics Data System (ADS)
Stefanucci, G.; Pavlyukh, Y.; Uimonen, A.-M.; van Leeuwen, R.
2014-09-01
We present a diagrammatic approach to construct self-energy approximations within many-body perturbation theory with positive spectral properties. The method cures the problem of negative spectral functions which arises from a straightforward inclusion of vertex diagrams beyond the GW approximation. Our approach consists of a two-step procedure: We first express the approximate many-body self-energy as a product of half-diagrams and then identify the minimal number of half-diagrams to add in order to form a perfect square. The resulting self-energy is an unconventional sum of self-energy diagrams in which the internal lines of half a diagram are time-ordered Green's functions, whereas those of the other half are anti-time-ordered Green's functions, and the lines joining the two halves are either lesser or greater Green's functions. The theory is developed using noninteracting Green's functions and subsequently extended to self-consistent Green's functions. Issues related to the conserving properties of diagrammatic approximations with positive spectral functions are also addressed. As a major application of the formalism we derive the minimal set of additional diagrams to make positive the spectral function of the GW approximation with lowest-order vertex corrections and screened interactions. The method is then applied to vertex corrections in the three-dimensional homogeneous electron gas by using a combination of analytical frequency integrations and numerical Monte Carlo momentum integrations to evaluate the diagrams.
Atomic density functional and diagram of structures in the phase field crystal model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ankudinov, V. E., E-mail: vladimir@ankudinov.org; Galenko, P. K.; Kropotin, N. V.
2016-02-15
The phase field crystal model provides a continual description of the atomic density over the diffusion time of reactions. We consider a homogeneous structure (liquid) and a perfect periodic crystal, which are constructed from the one-mode approximation of the phase field crystal model. A diagram of 2D structures is constructed from the analytic solutions of the model using atomic density functionals. The diagram predicts equilibrium atomic configurations for transitions from the metastable state and includes the domains of existence of homogeneous, triangular, and striped structures corresponding to a liquid, a body-centered cubic crystal, and a longitudinal cross section of cylindricalmore » tubes. The method developed here is employed for constructing the diagram for the homogeneous liquid phase and the body-centered iron lattice. The expression for the free energy is derived analytically from density functional theory. The specific features of approximating the phase field crystal model are compared with the approximations and conclusions of the weak crystallization and 2D melting theories.« less
A Clinical Decision Support System for Breast Cancer Patients
NASA Astrophysics Data System (ADS)
Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.
This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.
An autocatalytic network model for stock markets
NASA Astrophysics Data System (ADS)
Caetano, Marco Antonio Leonel; Yoneyama, Takashi
2015-02-01
The stock prices of companies with businesses that are closely related within a specific sector of economy might exhibit movement patterns and correlations in their dynamics. The idea in this work is to use the concept of autocatalytic network to model such correlations and patterns in the trends exhibited by the expected returns. The trends are expressed in terms of positive or negative returns within each fixed time interval. The time series derived from these trends is then used to represent the movement patterns by a probabilistic boolean network with transitions modeled as an autocatalytic network. The proposed method might be of value in short term forecasting and identification of dependencies. The method is illustrated with a case study based on four stocks of companies in the field of natural resource and technology.
Boolean function applied to Mimosa pudica movements.
De Luccia, Thiago Paes de Barros; Friedman, Pedro
2011-09-01
Seismonastic or thigmonastic movements of Mimosa pudica L. is mostly because of the fast loss of water from swollen motor cells, resulting in temporary collapse of cells and quick curvature in the parts where these cells are located. Because of this, the plant has been much studied since the 18th century, leading us to think about the classical binomial stimulus-response (action-reaction) when compared to animals. Mechanic and electrical stimuli were used to investigate the analogy of mimosa branch with an artificial neuron model and to observe the action potential propagation through the mimosa branch. Boolean function applied to the mimosa branch in analogy with an artificial neuron model is one of the peculiarities of our hypothesis.
Nonvolatile “AND,” “OR,” and “NOT” Boolean logic gates based on phase-change memory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Y.; Zhong, Y. P.; Deng, Y. F.
2013-12-21
Electronic devices or circuits that can implement both logic and memory functions are regarded as the building blocks for future massive parallel computing beyond von Neumann architecture. Here we proposed phase-change memory (PCM)-based nonvolatile logic gates capable of AND, OR, and NOT Boolean logic operations verified in SPICE simulations and circuit experiments. The logic operations are parallel computing and results can be stored directly in the states of the logic gates, facilitating the combination of computing and memory in the same circuit. These results are encouraging for ultralow-power and high-speed nonvolatile logic circuit design based on novel memory devices.
Reservoir computing with a single time-delay autonomous Boolean node
NASA Astrophysics Data System (ADS)
Haynes, Nicholas D.; Soriano, Miguel C.; Rosin, David P.; Fischer, Ingo; Gauthier, Daniel J.
2015-02-01
We demonstrate reservoir computing with a physical system using a single autonomous Boolean logic element with time-delay feedback. The system generates a chaotic transient with a window of consistency lasting between 30 and 300 ns, which we show is sufficient for reservoir computing. We then characterize the dependence of computational performance on system parameters to find the best operating point of the reservoir. When the best parameters are chosen, the reservoir is able to classify short input patterns with performance that decreases over time. In particular, we show that four distinct input patterns can be classified for 70 ns, even though the inputs are only provided to the reservoir for 7.5 ns.
Questions Revisited: A Close Examination of Calculus of Inference and Inquiry
NASA Technical Reports Server (NTRS)
Knuth, Kevin H.; Koga, Dennis (Technical Monitor)
2003-01-01
In this paper I examine more closely the way in which probability theory, the calculus of inference, is derived from the Boolean lattice structure of logical assertions ordered by implication. I demonstrate how the duality between the logical conjunction and disjunction in Boolean algebra is lost when deriving the probability calculus. In addition, I look more closely at the other lattice identities to verify that they are satisfied by the probability calculus. Last, I look towards developing the calculus of inquiry demonstrating that there is a sum and product rule for the relevance measure as well as a Bayes theorem. Current difficulties in deriving the complete inquiry calculus will also be discussed.
Optical reversible programmable Boolean logic unit.
Chattopadhyay, Tanay
2012-07-20
Computing with reversibility is the only way to avoid dissipation of energy associated with bit erase. So, a reversible microprocessor is required for future computing. In this paper, a design of a simple all-optical reversible programmable processor is proposed using a polarizing beam splitter, liquid crystal-phase spatial light modulators, a half-wave plate, and plane mirrors. This circuit can perform 16 logical operations according to three programming inputs. Also, inputs can be easily recovered from the outputs. It is named the "reversible programmable Boolean logic unit (RPBLU)." The logic unit is the basic building block of many complex computational operations. Hence the design is important in sense. Two orthogonally polarized lights are defined here as two logical states, respectively.
Extending Clause Learning of SAT Solvers with Boolean Gröbner Bases
NASA Astrophysics Data System (ADS)
Zengler, Christoph; Küchlin, Wolfgang
We extend clause learning as performed by most modern SAT Solvers by integrating the computation of Boolean Gröbner bases into the conflict learning process. Instead of learning only one clause per conflict, we compute and learn additional binary clauses from a Gröbner basis of the current conflict. We used the Gröbner basis engine of the logic package Redlog contained in the computer algebra system Reduce to extend the SAT solver MiniSAT with Gröbner basis learning. Our approach shows a significant reduction of conflicts and a reduction of restarts and computation time on many hard problems from the SAT 2009 competition.
Adaptation and survivors in a random Boolean network.
Nakamura, Ikuo
2002-04-01
We introduce the competitive agent with imitation strategy in a random Boolean network, in which the agent plays a competitive game that rewards those in minority. After a long time interval, the worst performer changes its strategy to the one of the best and the process is repeated. The network, initially in a chaotic state, evolves to an intermittent state and finally reaches a frozen state. Time series of survived species (whose strategies are imitated by other agents) in the system depend on the connectivity of each agent. In a system with various connectivity groups, the low connectivity groups win the minority game over the high connectivity groups. We also compared the result with mutation strategy system.
Huang, Hung-Chung; Jupiter, Daniel; VanBuren, Vincent
2010-01-01
Background Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers. Methodology/Principal Findings In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs) of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness) were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic), and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as ‘brain group’ and ‘non-brain group’; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes. Conclusions/Significance The methodology employed here may be used to facilitate disease-specific biomarker discovery. PMID:20140228
A method for developing design diagrams for ceramic and glass materials using fatigue data
NASA Technical Reports Server (NTRS)
Heslin, T. M.; Magida, M. B.; Forrest, K. A.
1986-01-01
The service lifetime of glass and ceramic materials can be expressed as a plot of time-to-failure versus applied stress whose plot is parametric in percent probability of failure. This type of plot is called a design diagram. Confidence interval estimates for such plots depend on the type of test that is used to generate the data, on assumptions made concerning the statistical distribution of the test results, and on the type of analysis used. This report outlines the development of design diagrams for glass and ceramic materials in engineering terms using static or dynamic fatigue tests, assuming either no particular statistical distribution of test results or a Weibull distribution and using either median value or homologous ratio analysis of the test results.
Development of a computer-aided design software for dental splint in orthognathic surgery
NASA Astrophysics Data System (ADS)
Chen, Xiaojun; Li, Xing; Xu, Lu; Sun, Yi; Politis, Constantinus; Egger, Jan
2016-12-01
In the orthognathic surgery, dental splints are important and necessary to help the surgeon reposition the maxilla or mandible. However, the traditional methods of manual design of dental splints are difficult and time-consuming. The research on computer-aided design software for dental splints is rarely reported. Our purpose is to develop a novel special software named EasySplint to design the dental splints conveniently and efficiently. The design can be divided into two steps, which are the generation of initial splint base and the Boolean operation between it and the maxilla-mandibular model. The initial splint base is formed by ruled surfaces reconstructed using the manually picked points. Then, a method to accomplish Boolean operation based on the distance filed of two meshes is proposed. The interference elimination can be conducted on the basis of marching cubes algorithm and Boolean operation. The accuracy of the dental splint can be guaranteed since the original mesh is utilized to form the result surface. Using EasySplint, the dental splints can be designed in about 10 minutes and saved as a stereo lithography (STL) file for 3D printing in clinical applications. Three phantom experiments were conducted and the efficiency of our method was demonstrated.
Development of a computer-aided design software for dental splint in orthognathic surgery
Chen, Xiaojun; Li, Xing; Xu, Lu; Sun, Yi; Politis, Constantinus; Egger, Jan
2016-01-01
In the orthognathic surgery, dental splints are important and necessary to help the surgeon reposition the maxilla or mandible. However, the traditional methods of manual design of dental splints are difficult and time-consuming. The research on computer-aided design software for dental splints is rarely reported. Our purpose is to develop a novel special software named EasySplint to design the dental splints conveniently and efficiently. The design can be divided into two steps, which are the generation of initial splint base and the Boolean operation between it and the maxilla-mandibular model. The initial splint base is formed by ruled surfaces reconstructed using the manually picked points. Then, a method to accomplish Boolean operation based on the distance filed of two meshes is proposed. The interference elimination can be conducted on the basis of marching cubes algorithm and Boolean operation. The accuracy of the dental splint can be guaranteed since the original mesh is utilized to form the result surface. Using EasySplint, the dental splints can be designed in about 10 minutes and saved as a stereo lithography (STL) file for 3D printing in clinical applications. Three phantom experiments were conducted and the efficiency of our method was demonstrated. PMID:27966601
Development of a computer-aided design software for dental splint in orthognathic surgery.
Chen, Xiaojun; Li, Xing; Xu, Lu; Sun, Yi; Politis, Constantinus; Egger, Jan
2016-12-14
In the orthognathic surgery, dental splints are important and necessary to help the surgeon reposition the maxilla or mandible. However, the traditional methods of manual design of dental splints are difficult and time-consuming. The research on computer-aided design software for dental splints is rarely reported. Our purpose is to develop a novel special software named EasySplint to design the dental splints conveniently and efficiently. The design can be divided into two steps, which are the generation of initial splint base and the Boolean operation between it and the maxilla-mandibular model. The initial splint base is formed by ruled surfaces reconstructed using the manually picked points. Then, a method to accomplish Boolean operation based on the distance filed of two meshes is proposed. The interference elimination can be conducted on the basis of marching cubes algorithm and Boolean operation. The accuracy of the dental splint can be guaranteed since the original mesh is utilized to form the result surface. Using EasySplint, the dental splints can be designed in about 10 minutes and saved as a stereo lithography (STL) file for 3D printing in clinical applications. Three phantom experiments were conducted and the efficiency of our method was demonstrated.
Bounds on the number of hidden neurons in three-layer binary neural networks.
Zhang, Zhaozhi; Ma, Xiaomin; Yang, Yixian
2003-09-01
This paper investigates an important problem concerning the complexity of three-layer binary neural networks (BNNs) with one hidden layer. The neuron in the studied BNNs employs a hard limiter activation function with only integer weights and an integer threshold. The studies are focused on implementations of arbitrary Boolean functions which map from [0, 1]n into [0, 1]. A deterministic algorithm called set covering algorithm (SCA) is proposed for the construction of a three-layer BNN to implement an arbitrary Boolean function. The SCA is based on a unit sphere covering (USC) of the Hamming space (HS) which is chosen in advance. It is proved that for the implementation of an arbitrary Boolean function of n-variables (n > or = 3) by using SCA, [3L/2] hidden neurons are necessary and sufficient, where L is the number of unit spheres contained in the chosen USC of the n-dimensional HS. It is shown that by using SCA, the number of hidden neurons required is much less than that by using a two-parallel hyperplane method. In order to indicate the potential ability of three-layer BNNs, a lower bound on the required number of hidden neurons which is derived by using the method of estimating the Vapnik-Chervonenkis (VC) dimension is also given.
Loop expansion around the Bethe approximation through the M-layer construction
NASA Astrophysics Data System (ADS)
Altieri, Ada; Chiara Angelini, Maria; Lucibello, Carlo; Parisi, Giorgio; Ricci-Tersenghi, Federico; Rizzo, Tommaso
2017-11-01
For every physical model defined on a generic graph or factor graph, the Bethe M-layer construction allows building a different model for which the Bethe approximation is exact in the large M limit, and coincides with the original model for M=1 . The 1/M perturbative series is then expressed by a diagrammatic loop expansion in terms of so-called fat diagrams. Our motivation is to study some important second-order phase transitions that do exist on the Bethe lattice, but are either qualitatively different or absent in the corresponding fully connected case. In this case, the standard approach based on a perturbative expansion around the naive mean field theory (essentially a fully connected model) fails. On physical grounds, we expect that when the construction is applied to a lattice in finite dimension there is a small region of the external parameters, close to the Bethe critical point, where strong deviations from mean-field behavior will be observed. In this region, the 1/M expansion for the corrections diverges, and can be the starting point for determining the correct non-mean-field critical exponents using renormalization group arguments. In the end, we will show that the critical series for the generic observable can be expressed as a sum of Feynman diagrams with the same numerical prefactors of field theories. However, the contribution of a given diagram is not evaluated by associating Gaussian propagators to its lines, as in field theories: one has to consider the graph as a portion of the original lattice, replacing the internal lines with appropriate one-dimensional chains, and attaching to the internal points the appropriate number of infinite-size Bethe trees to restore the correct local connectivity of the original model. The actual contribution of each (fat) diagram is the so-called line-connected observable, which also includes contributions from sub-diagrams with appropriate prefactors. In order to compute the corrections near to the critical point, Feynman diagrams (with their symmetry factors) can be read directly from the appropriate field-theoretical literature; the computation of momentum integrals is also quite similar; the extra work consists of computing the line-connected observable of the associated fat diagram in the limit of all lines becoming infinitely long.
The value of less connected agents in Boolean networks
NASA Astrophysics Data System (ADS)
Epstein, Daniel; Bazzan, Ana L. C.
2013-11-01
In multiagent systems, agents often face binary decisions where one seeks to take either the minority or the majority side. Examples are minority and congestion games in general, i.e., situations that require coordination among the agents in order to depict efficient decisions. In minority games such as the El Farol Bar Problem, previous works have shown that agents may reach appropriate levels of coordination, mostly by looking at the history of past decisions. Not many works consider any kind of structure of the social network, i.e., how agents are connected. Moreover, when structure is indeed considered, it assumes some kind of random network with a given, fixed connectivity degree. The present paper departs from the conventional approach in some ways. First, it considers more realistic network topologies, based on preferential attachments. This is especially useful in social networks. Second, the formalism of random Boolean networks is used to help agents to make decisions given their attachments (for example acquaintances). This is coupled with a reinforcement learning mechanism that allows agents to select strategies that are locally and globally efficient. Third, we use agent-based modeling and simulation, a microscopic approach, which allows us to draw conclusions about individuals and/or classes of individuals. Finally, for the sake of illustration we use two different scenarios, namely the El Farol Bar Problem and a binary route choice scenario. With this approach we target systems that adapt dynamically to changes in the environment, including other adaptive decision-makers. Our results using preferential attachments and random Boolean networks are threefold. First we show that an efficient equilibrium can be achieved, provided agents do experimentation. Second, microscopic analysis show that influential agents tend to consider few inputs in their Boolean functions. Third, we have also conducted measurements related to network clustering and centrality that help to see how agents are organized.
Disparity between ultrasound and clinical findings in psoriatic arthritis.
Husic, Rusmir; Gretler, Judith; Felber, Anja; Graninger, Winfried B; Duftner, Christina; Hermann, Josef; Dejaco, Christian
2014-08-01
To investigate the association between psoriatic arthritis (PsA)-specific clinical composite scores and ultrasound-verified pathology as well as comparison of clinical and ultrasound definitions of remission. We performed a prospective study on 70 consecutive PsA patients. Clinical assessments included components of Disease Activity Index for Psoriatic Arthritis (DAPSA) and the Composite Psoriatic Disease Activity Index (CPDAI). Minimal disease activity (MDA) and the following remission criteria were applied: CPDAI joint, entheses and dactylitis domains (CPDAI-JED)=0, DAPSA≤3.3, Boolean's remission definition and physician-judged remission (rem-phys). B-mode and power Doppler (PD-) ultrasound findings were semiquantitatively scored at 68 joints (evaluating synovia, peritendinous tissue, tendons and bony changes) and 14 entheses. Ultrasound remission and minimal ultrasound disease activity (MUDA) were defined as PD-score=0 and PD-score ≤1, respectively, at joints, peritendinous tissue, tendons and entheses. DAPSA but not CPDAI correlated with B-mode and PD-synovitis. Ultrasound signs of enthesitis, dactylitis, tenosynovitis and perisynovitis were not linked with clinical composites. Clinical remission or MDA was observed in 15.7% to 47.1% of PsA patients. Ultrasound remission and MUDA were present in 4.3% and 20.0% of patients, respectively. Joint and tendon-related PD-scores were higher in patients with active versus inactive disease according to CPDAI-JED, DAPSA, Boolean's and rem-phys, whereas no difference was observed regarding enthesitis and perisynovitis. DAPSA≤3.3 (OR 3.9, p=0.049) and Boolean's definition (OR 4.6, p=0.03) were more useful to predict MUDA than other remission criteria. PsA-specific composite scores partially reflect ultrasound findings. DAPSA and Boolean's remission definitions better identify MUDA patients than other clinical criteria. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
A Simple Optical Waveguide Experiment.
ERIC Educational Resources Information Center
Phelps, J.; Sambles, J. R.
1989-01-01
Describes a thin film rectangular dielectric waveguide and its laboratory use. Discusses the theory of uniaxial thin film waveguides with mathematical expressions and the laboratory procedures for a classroom experiment with diagrams. (Author/YP)
ERIC Educational Resources Information Center
Carpenter, D. Rae, Jr.; And Others
1988-01-01
Discusses a demonstration of vertical collision of two balls. Shows the theoretical height ratio using mathematical expression and diagrams. Compares it with researchers' experimental results. Expands the two-ball collision to multi-ball system. (YP)
Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.
Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence
2012-08-29
Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential equations on probability distributions. We developed a C++ software, MaBoSS, that is able to simulate such a system by applying Kinetic Monte-Carlo (or Gillespie algorithm) on the Boolean state space. This software, parallelized and optimized, computes the temporal evolution of probability distributions and estimates stationary distributions. Applications of the Boolean Kinetic Monte-Carlo are demonstrated for three qualitative models: a toy model, a published model of p53/Mdm2 interaction and a published model of the mammalian cell cycle. Our approach allows to describe kinetic phenomena which were difficult to handle in the original models. In particular, transient effects are represented by time dependent probability distributions, interpretable in terms of cell populations.
Construction and analysis of gene-gene dynamics influence networks based on a Boolean model.
Mazaya, Maulida; Trinh, Hung-Cuong; Kwon, Yung-Keun
2017-12-21
Identification of novel gene-gene relations is a crucial issue to understand system-level biological phenomena. To this end, many methods based on a correlation analysis of gene expressions or structural analysis of molecular interaction networks have been proposed. They have a limitation in identifying more complicated gene-gene dynamical relations, though. To overcome this limitation, we proposed a measure to quantify a gene-gene dynamical influence (GDI) using a Boolean network model and constructed a GDI network to indicate existence of a dynamical influence for every ordered pair of genes. It represents how much a state trajectory of a target gene is changed by a knockout mutation subject to a source gene in a gene-gene molecular interaction (GMI) network. Through a topological comparison between GDI and GMI networks, we observed that the former network is denser than the latter network, which implies that there exist many gene pairs of dynamically influencing but molecularly non-interacting relations. In addition, a larger number of hub genes were generated in the GDI network. On the other hand, there was a correlation between these networks such that the degree value of a node was positively correlated to each other. We further investigated the relationships of the GDI value with structural properties and found that there are negative and positive correlations with the length of a shortest path and the number of paths, respectively. In addition, a GDI network could predict a set of genes whose steady-state expression is affected in E. coli gene-knockout experiments. More interestingly, we found that the drug-targets with side-effects have a larger number of outgoing links than the other genes in the GDI network, which implies that they are more likely to influence the dynamics of other genes. Finally, we found biological evidences showing that the gene pairs which are not molecularly interacting but dynamically influential can be considered for novel gene-gene relationships. Taken together, construction and analysis of the GDI network can be a useful approach to identify novel gene-gene relationships in terms of the dynamical influence.
Boolean function applied to Mimosa pudica movements
Friedman, Pedro
2011-01-01
Seismonastic or thigmonastic movements of Mimosa pudica L. is mostly because of the fast loss of water from swollen motor cells, resulting in temporary collapse of cells and quick curvature in the parts where these cells are located. Because of this, the plant has been much studied since the 18th century, leading us to think about the classical binomial stimulus-response (action-reaction) when compared to animals. Mechanic and electrical stimuli were used to investigate the analogy of mimosa branch with an artificial neuron model and to observe the action potential propagation through the mimosa branch. Boolean function applied to the mimosa branch in analogy with an artificial neuron model is one of the peculiarities of our hypothesis. PMID:21847029
Investigating Cell Criticality
NASA Astrophysics Data System (ADS)
Serra, R.; Villani, M.; Damiani, C.; Graudenzi, A.; Ingrami, P.; Colacci, A.
Random Boolean networks provide a way to give a precise meaning to the notion that living beings are in a critical state. Some phenomena which are observed in real biological systems (distribution of "avalanches" in gene knock-out experiments) can be modeled using random Boolean networks, and the results can be analytically proven to depend upon the Derrida parameter, which also determines whether the network is critical. By comparing observed and simulated data one can then draw inferences about the criticality of biological cells, although with some care because of the limited number of experimental observations. The relationship between the criticality of a single network and that of a set of interacting networks, which simulate a tissue or a bacterial colony, is also analyzed by computer simulations.
Programming Cell Adhesion for On-Chip Sequential Boolean Logic Functions.
Qu, Xiangmeng; Wang, Shaopeng; Ge, Zhilei; Wang, Jianbang; Yao, Guangbao; Li, Jiang; Zuo, Xiaolei; Shi, Jiye; Song, Shiping; Wang, Lihua; Li, Li; Pei, Hao; Fan, Chunhai
2017-08-02
Programmable remodelling of cell surfaces enables high-precision regulation of cell behavior. In this work, we developed in vitro constructed DNA-based chemical reaction networks (CRNs) to program on-chip cell adhesion. We found that the RGD-functionalized DNA CRNs are entirely noninvasive when interfaced with the fluidic mosaic membrane of living cells. DNA toehold with different lengths could tunably alter the release kinetics of cells, which shows rapid release in minutes with the use of a 6-base toehold. We further demonstrated the realization of Boolean logic functions by using DNA strand displacement reactions, which include multi-input and sequential cell logic gates (AND, OR, XOR, and AND-OR). This study provides a highly generic tool for self-organization of biological systems.
Reliable computation from contextual correlations
NASA Astrophysics Data System (ADS)
Oestereich, André L.; Galvão, Ernesto F.
2017-12-01
An operational approach to the study of computation based on correlations considers black boxes with one-bit inputs and outputs, controlled by a limited classical computer capable only of performing sums modulo-two. In this setting, it was shown that noncontextual correlations do not provide any extra computational power, while contextual correlations were found to be necessary for the deterministic evaluation of nonlinear Boolean functions. Here we investigate the requirements for reliable computation in this setting; that is, the evaluation of any Boolean function with success probability bounded away from 1 /2 . We show that bipartite CHSH quantum correlations suffice for reliable computation. We also prove that an arbitrarily small violation of a multipartite Greenberger-Horne-Zeilinger noncontextuality inequality also suffices for reliable computation.
The pseudo-Boolean optimization approach to form the N-version software structure
NASA Astrophysics Data System (ADS)
Kovalev, I. V.; Kovalev, D. I.; Zelenkov, P. V.; Voroshilova, A. A.
2015-10-01
The problem of developing an optimal structure of N-version software system presents a kind of very complex optimization problem. This causes the use of deterministic optimization methods inappropriate for solving the stated problem. In this view, exploiting heuristic strategies looks more rational. In the field of pseudo-Boolean optimization theory, the so called method of varied probabilities (MVP) has been developed to solve problems with a large dimensionality. Some additional modifications of MVP have been made to solve the problem of N-version systems design. Those algorithms take into account the discovered specific features of the objective function. The practical experiments have shown the advantage of using these algorithm modifications because of reducing a search space.
A procedure concept for local reflex control of grasping
NASA Technical Reports Server (NTRS)
Fiorini, Paolo; Chang, Jeffrey
1989-01-01
An architecture is proposed for the control of robotic devices, and in particular of anthropomorphic hands, characterized by a hierarchical structure in which every level of the architecture contains data and control function with varying degree of abstraction. Bottom levels of the hierarchy interface directly with sensors and actuators, and process raw data and motor commands. Higher levels perform more symbolic types of tasks, such as application of boolean rules and general planning operations. Layers implementation has to be consistent with the type of operation and its requirements for real time control. It is proposed to implement the rule level with a Boolean Artificial Neural Network characterized by a response time sufficient for producing reflex corrective action at the actuator level.
On the effective field theory for quasi-single field inflation
NASA Astrophysics Data System (ADS)
Tong, Xi; Wang, Yi; Zhou, Siyi
2017-11-01
We study the effective field theory (EFT) description of the virtual particle effects in quasi-single field inflation, which unifies the previous results on large mass and large mixing cases. By using a horizon crossing approximation and matching with known limits, approximate expressions for the power spectrum and the spectral index are obtained. The error of the approximate solution is within 10% in dominate parts of the parameter space, which corresponds to less-than-0.1% error in the ns-r diagram. The quasi-single field corrections on the ns-r diagram are plotted for a few inflation models. Especially, the quasi-single field correction drives m2phi2 inflation to the best fit region on the ns-r diagram, with an amount of equilateral non-Gaussianity which can be tested in future experiments.
Measurement uncertainty of liquid chromatographic analyses visualized by Ishikawa diagrams.
Meyer, Veronika R
2003-09-01
Ishikawa, or cause-and-effect diagrams, help to visualize the parameters that influence a chromatographic analysis. Therefore, they facilitate the set up of the uncertainty budget of the analysis, which can then be expressed in mathematical form. If the uncertainty is calculated as the Gaussian sum of all uncertainty parameters, it is necessary to quantitate them all, a task that is usually not practical. The other possible approach is to use the intermediate precision as a base for the uncertainty calculation. In this case, it is at least necessary to consider the uncertainty of the purity of the reference material in addition to the precision data. The Ishikawa diagram is then very simple, and so is the uncertainty calculation. This advantage is given by the loss of information about the parameters that influence the measurement uncertainty.
iGC-an integrated analysis package of gene expression and copy number alteration.
Lai, Yi-Pin; Wang, Liang-Bo; Wang, Wei-An; Lai, Liang-Chuan; Tsai, Mong-Hsun; Lu, Tzu-Pin; Chuang, Eric Y
2017-01-14
With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual. We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance. The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .
The state diagram for cell adhesion under flow: leukocyte rolling and firm adhesion.
Chang, K C; Tees, D F; Hammer, D A
2000-10-10
Leukocyte adhesion under flow in the microvasculature is mediated by binding between cell surface receptors and complementary ligands expressed on the surface of the endothelium. Leukocytes adhere to endothelium in a two-step mechanism: rolling (primarily mediated by selectins) followed by firm adhesion (primarily mediated by integrins). Using a computational method called "Adhesive Dynamics," we have simulated the adhesion of a cell to a surface in flow, and elucidated the relationship between receptor-ligand functional properties and the dynamics of adhesion. We express this relationship in a state diagram, a one-to-one map between the biophysical properties of adhesion molecules and various adhesive behaviors. Behaviors that are observed in simulations include firm adhesion, transient adhesion (rolling), and no adhesion. We varied the dissociative properties, association rate, bond elasticity, and shear rate and found that the unstressed dissociation rate, k(r)(o), and the bond interaction length, gamma, are the most important molecular properties controlling the dynamics of adhesion. Experimental k(r)(o) and gamma values from the literature for molecules that are known to mediate rolling adhesion fall within the rolling region of the state diagram. We explain why L-selectin-mediated rolling, which has faster k(r)(o) than other selectins, is accompanied by a smaller value for gamma. We also show how changes in association rate, shear rate, and bond elasticity alter the dynamics of adhesion. The state diagram (which must be mapped for each receptor-ligand system) presents a concise and comprehensive means of understanding the relationship between bond functional properties and the dynamics of adhesion mediated by receptor-ligand bonds.
CRAVE: a database, middleware and visualization system for phenotype ontologies.
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.
A model for cancer tissue heterogeneity.
Mohanty, Anwoy Kumar; Datta, Aniruddha; Venkatraj, Vijayanagaram
2014-03-01
An important problem in the study of cancer is the understanding of the heterogeneous nature of the cell population. The clonal evolution of the tumor cells results in the tumors being composed of multiple subpopulations. Each subpopulation reacts differently to any given therapy. This calls for the development of novel (regulatory network) models, which can accommodate heterogeneity in cancerous tissues. In this paper, we present a new approach to model heterogeneity in cancer. We model heterogeneity as an ensemble of deterministic Boolean networks based on prior pathway knowledge. We develop the model considering the use of qPCR data. By observing gene expressions when the tissue is subjected to various stimuli, the compositional breakup of the tissue under study can be determined. We demonstrate the viability of this approach by using our model on synthetic data, and real-world data collected from fibroblasts.
Repair-level analysis for Space Station Freedom
NASA Technical Reports Server (NTRS)
Chadwick, M.; Yaniec, J.
1992-01-01
To assign repair or discard-at-failure designations for orbital replacement units (ORUs) used on Space Station Freedom Electric Power System (SSFEPS), new algorithms and methods were required. Unique parameters, such as upmass costs, extravehicular activity costs and intravehicular activity (IVA) costs specific to Space Station Freedom's maintenance concept were incorporated into the Repair-Level Analysis (RLA). Additional outputs were also required of the SSFEPS RLA that were not required of previous RLAs. These outputs included recommendations for the number of launches that an ORU should be capable of attaining and an economic basis for condemnation rate. These unique parameters were not addressable using existing RLA models: therefore, a new approach was developed. In addition, it was found that preemptive analysis could be performed using spreadsheet-based Boolean expressions to represent the logical condition of the items under analysis.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anderko, A.; Sanders, S.J.; Young, R.D.
1997-01-01
A method was developed for construction of stability diagrams for metals in the presence of realistically modeled aqueous solutions. The method was based on a comprehensive thermodynamic model that combines the Helgeson-Kirkham-Flowers (HKF) equation of state for standard-state properties with a solution nonideality model based on the activity coefficient expressions developed by Bromley and Pitzer. Composition-dependent nonideality effects were incorporated into the calculation of predominance areas for dissolved and solid species. Using the combined thermodynamic model, stability diagrams can be computed for systems involving concentrated solutions (i.e., with molalities up to 30 mol/kg) at temperatures up to 573 K andmore » pressures up to 100 MPa. Since the diagrams are based on a realistic thermodynamic model for the aqueous phase, they are referred to as real-solution stability diagrams. In addition to customary potential (E) and pH variables, concentrations of various active species (e.g., complexing agents) can be used as independent variables, making it possible to analyze effects of various compounds that promote or inhibit corrosion. Usefulness of the methodology was demonstrated by generating real-solution stability diagrams for five representative systems (i.e., sulfur-water [S-H{sub 2}O], copper-ammonia-water [Cu-NH{sub 3}-H{sub 2}O], titanium-chlorine-calcium-water [Ti-Cl-Ca-H{sub 2}O], iron-sulfur-water [Fe-S-H{sub 2}O], and zinc-water [Zn-H{sub 2}O]).« less
Information processing in dendrites I. Input pattern generalisation.
Gurney, K N
2001-10-01
In this paper and its companion, we address the question as to whether there are any general principles underlying information processing in the dendritic trees of biological neurons. In order to address this question, we make two assumptions. First, the key architectural feature of dendrites responsible for many of their information processing abilities is the existence of independent sub-units performing local non-linear processing. Second, any general functional principles operate at a level of abstraction in which neurons are modelled by Boolean functions. To accommodate these assumptions, we therefore define a Boolean model neuron-the multi-cube unit (MCU)-which instantiates the notion of the discrete functional sub-unit. We then use this model unit to explore two aspects of neural functionality: generalisation (in this paper) and processing complexity (in its companion). Generalisation is dealt with from a geometric viewpoint and is quantified using a new metric-the set of order parameters. These parameters are computed for threshold logic units (TLUs), a class of random Boolean functions, and MCUs. Our interpretation of the order parameters is consistent with our knowledge of generalisation in TLUs and with the lack of generalisation in randomly chosen functions. Crucially, the order parameters for MCUs imply that these functions possess a range of generalisation behaviour. We argue that this supports the general thesis that dendrites facilitate input pattern generalisation despite any local non-linear processing within functionally isolated sub-units.
Attractor-Based Obstructions to Growth in Homogeneous Cyclic Boolean Automata.
Khan, Bilal; Cantor, Yuri; Dombrowski, Kirk
2015-11-01
We consider a synchronous Boolean organism consisting of N cells arranged in a circle, where each cell initially takes on an independently chosen Boolean value. During the lifetime of the organism, each cell updates its own value by responding to the presence (or absence) of diversity amongst its two neighbours' values. We show that if all cells eventually take a value of 0 (irrespective of their initial values) then the organism necessarily has a cell count that is a power of 2. In addition, the converse is also proved: if the number of cells in the organism is a proper power of 2, then no matter what the initial values of the cells are, eventually all cells take on a value of 0 and then cease to change further. We argue that such an absence of structure in the dynamical properties of the organism implies a lack of adaptiveness, and so is evolutionarily disadvantageous. It follows that as the organism doubles in size (say from m to 2m) it will necessarily encounter an intermediate size that is a proper power of 2, and suffers from low adaptiveness. Finally we show, through computational experiments, that one way an organism can grow to more than twice its size and still avoid passing through intermediate sizes that lack structural dynamics, is for the organism to depart from assumptions of homogeneity at the cellular level.
Evolution of a designless nanoparticle network into reconfigurable Boolean logic
NASA Astrophysics Data System (ADS)
Bose, S. K.; Lawrence, C. P.; Liu, Z.; Makarenko, K. S.; van Damme, R. M. J.; Broersma, H. J.; van der Wiel, W. G.
2015-12-01
Natural computers exploit the emergent properties and massive parallelism of interconnected networks of locally active components. Evolution has resulted in systems that compute quickly and that use energy efficiently, utilizing whatever physical properties are exploitable. Man-made computers, on the other hand, are based on circuits of functional units that follow given design rules. Hence, potentially exploitable physical processes, such as capacitive crosstalk, to solve a problem are left out. Until now, designless nanoscale networks of inanimate matter that exhibit robust computational functionality had not been realized. Here we artificially evolve the electrical properties of a disordered nanomaterials system (by optimizing the values of control voltages using a genetic algorithm) to perform computational tasks reconfigurably. We exploit the rich behaviour that emerges from interconnected metal nanoparticles, which act as strongly nonlinear single-electron transistors, and find that this nanoscale architecture can be configured in situ into any Boolean logic gate. This universal, reconfigurable gate would require about ten transistors in a conventional circuit. Our system meets the criteria for the physical realization of (cellular) neural networks: universality (arbitrary Boolean functions), compactness, robustness and evolvability, which implies scalability to perform more advanced tasks. Our evolutionary approach works around device-to-device variations and the accompanying uncertainties in performance. Moreover, it bears a great potential for more energy-efficient computation, and for solving problems that are very hard to tackle in conventional architectures.
Attractor-Based Obstructions to Growth in Homogeneous Cyclic Boolean Automata
Khan, Bilal; Cantor, Yuri; Dombrowski, Kirk
2016-01-01
We consider a synchronous Boolean organism consisting of N cells arranged in a circle, where each cell initially takes on an independently chosen Boolean value. During the lifetime of the organism, each cell updates its own value by responding to the presence (or absence) of diversity amongst its two neighbours’ values. We show that if all cells eventually take a value of 0 (irrespective of their initial values) then the organism necessarily has a cell count that is a power of 2. In addition, the converse is also proved: if the number of cells in the organism is a proper power of 2, then no matter what the initial values of the cells are, eventually all cells take on a value of 0 and then cease to change further. We argue that such an absence of structure in the dynamical properties of the organism implies a lack of adaptiveness, and so is evolutionarily disadvantageous. It follows that as the organism doubles in size (say from m to 2m) it will necessarily encounter an intermediate size that is a proper power of 2, and suffers from low adaptiveness. Finally we show, through computational experiments, that one way an organism can grow to more than twice its size and still avoid passing through intermediate sizes that lack structural dynamics, is for the organism to depart from assumptions of homogeneity at the cellular level. PMID:27660398
String & Sticky Tape Experiments: Two-Dimensional Collisions Using Pendulums.
ERIC Educational Resources Information Center
Edge, R. D.
1989-01-01
Introduces a method for two-dimensional kinematics measurements by hanging marbles with long strings. Describes experimental procedures for conservation of momentum and obtaining the coefficient of restitution. Provides diagrams and mathematical expressions for the activities. (YP)
A Simple Method to Determine the Refractive Index of Glass.
ERIC Educational Resources Information Center
Mak, Se-yuen
1988-01-01
Describes an experiment for determining the refractive index. Discusses the experiment procedure and mathematical expression for calculating the index. Provides two geometrical diagrams and a graph for determining the index with a typical data. (YP)
Density-functional theory for fluid-solid and solid-solid phase transitions.
Bharadwaj, Atul S; Singh, Yashwant
2017-03-01
We develop a theory to describe solid-solid phase transitions. The density functional formalism of classical statistical mechanics is used to find an exact expression for the difference in the grand thermodynamic potentials of the two coexisting phases. The expression involves both the symmetry conserving and the symmetry broken parts of the direct pair correlation function. The theory is used to calculate phase diagram of systems of soft spheres interacting via inverse power potentials u(r)=ε(σ/r)^{n}, where parameter n measures softness of the potential. We find that for 1/n<0.154 systems freeze into the face centered cubic (fcc) structure while for 1/n≥0.154 the body-centred-cubic (bcc) structure is preferred. The bcc structure transforms into the fcc structure upon increasing the density. The calculated phase diagram is in good agreement with the one found from molecular simulations.
Gene network analysis: from heart development to cardiac therapy.
Ferrazzi, Fulvia; Bellazzi, Riccardo; Engel, Felix B
2015-03-01
Networks offer a flexible framework to represent and analyse the complex interactions between components of cellular systems. In particular gene networks inferred from expression data can support the identification of novel hypotheses on regulatory processes. In this review we focus on the use of gene network analysis in the study of heart development. Understanding heart development will promote the elucidation of the aetiology of congenital heart disease and thus possibly improve diagnostics. Moreover, it will help to establish cardiac therapies. For example, understanding cardiac differentiation during development will help to guide stem cell differentiation required for cardiac tissue engineering or to enhance endogenous repair mechanisms. We introduce different methodological frameworks to infer networks from expression data such as Boolean and Bayesian networks. Then we present currently available temporal expression data in heart development and discuss the use of network-based approaches in published studies. Collectively, our literature-based analysis indicates that gene network analysis constitutes a promising opportunity to infer therapy-relevant regulatory processes in heart development. However, the use of network-based approaches has so far been limited by the small amount of samples in available datasets. Thus, we propose to acquire high-resolution temporal expression data to improve the mathematical descriptions of regulatory processes obtained with gene network inference methodologies. Especially probabilistic methods that accommodate the intrinsic variability of biological systems have the potential to contribute to a deeper understanding of heart development.
On-shell structures of MHV amplitudes beyond the planar limit
Arkani-Hamed, Nima; Bourjaily, Jacob L.; Cachazo, Freddy; ...
2015-06-25
We initiate an exploration of on-shell functions in N=4 SYM beyond the planar limit by providing compact, combinatorial expressions for all leading singularities of MHV amplitudes and showing that they can always be expressed as a positive sum of differently ordered Parke-Taylor tree amplitudes. This is understood in terms of an extended notion of positivity in G(2, n), the Grassmannian of 2-planes in n dimensions: a single on-shell diagram can be associated with many different “positive” regions, of which the familiar G +(2, n) associated with planar diagrams is just one example. The decomposition into Parke-Taylor factors is simply amore » “triangulation” of these extended positive regions. The U(1) decoupling and Kleiss-Kuijf (KK) relations satisfied by the Parke-Taylor amplitudes also follow naturally from this geometric picture. Finally, these results suggest that non-planar MHV amplitudes in N=4 SYM at all loop orders can be expressed as a sum of polylogarithms weighted by color factors and (unordered) Parke-Taylor amplitudes.« less
Loke, Desmond; Skelton, Jonathan M; Chong, Tow-Chong; Elliott, Stephen R
2016-12-21
One of the requirements for achieving faster CMOS electronics is to mitigate the unacceptably large chip areas required to steer heat away from or, more recently, toward the critical nodes of state-of-the-art devices. Thermal-guiding (TG) structures can efficiently direct heat by "meta-materials" engineering; however, some key aspects of the behavior of these systems are not fully understood. Here, we demonstrate control of the thermal-diffusion properties of TG structures by using nanometer-scale, CMOS-integrable, graphene-on-silica stacked materials through finite-element-methods simulations. It has been shown that it is possible to implement novel, controllable, thermally based Boolean-logic and spike-timing-dependent plasticity operations for advanced (neuromorphic) computing applications using such thermal-guide architectures.
Modeling gene regulatory networks: A network simplification algorithm
NASA Astrophysics Data System (ADS)
Ferreira, Luiz Henrique O.; de Castro, Maria Clicia S.; da Silva, Fabricio A. B.
2016-12-01
Boolean networks have been used for some time to model Gene Regulatory Networks (GRNs), which describe cell functions. Those models can help biologists to make predictions, prognosis and even specialized treatment when some disturb on the GRN lead to a sick condition. However, the amount of information related to a GRN can be huge, making the task of inferring its boolean network representation quite a challenge. The method shown here takes into account information about the interactome to build a network, where each node represents a protein, and uses the entropy of each node as a key to reduce the size of the network, allowing the further inferring process to focus only on the main protein hubs, the ones with most potential to interfere in overall network behavior.
NASA Astrophysics Data System (ADS)
Ghaemi, Mehrdad; Javadi, Nabi
2017-11-01
The phase diagrams of the three-layer Ising model on the honeycomb lattice with a diluted surface have been constructed using the probabilistic cellular automata based on Glauber algorithm. The effects of the exchange interactions on the phase diagrams have been investigated. A general mathematical expression for the critical temperature is obtained in terms of relative coupling r = J1/J and Δs = (Js/J) - 1, where J and Js represent the nearest neighbor coupling within inner- and surface-layers, respectively, and each magnetic site in the surface-layer is coupled with the nearest neighbor site in the inner-layer via the exchange coupling J1. In the case of antiferromagnetic coupling between surface-layer and inner-layer, system reveals many interesting phenomena, such as the possibility of existence of compensation line before the critical temperature.
Designing Class Methods from Dataflow Diagrams
NASA Astrophysics Data System (ADS)
Shoval, Peretz; Kabeli-Shani, Judith
A method for designing the class methods of an information system is described. The method is part of FOOM - Functional and Object-Oriented Methodology. In the analysis phase of FOOM, two models defining the users' requirements are created: a conceptual data model - an initial class diagram; and a functional model - hierarchical OO-DFDs (object-oriented dataflow diagrams). Based on these models, a well-defined process of methods design is applied. First, the OO-DFDs are converted into transactions, i.e., system processes that supports user task. The components and the process logic of each transaction are described in detail, using pseudocode. Then, each transaction is decomposed, according to well-defined rules, into class methods of various types: basic methods, application-specific methods and main transaction (control) methods. Each method is attached to a proper class; messages between methods express the process logic of each transaction. The methods are defined using pseudocode or message charts.
Development of a mathematical model of the human cardiovascular system: An educational perspective
NASA Astrophysics Data System (ADS)
Johnson, Bruce Allen
A mathematical model of the human cardiovascular system will be a useful educational tool in biological sciences and bioengineering classrooms. The goal of this project is to develop a mathematical model of the human cardiovascular system that responds appropriately to variations of significant physical variables. Model development is based on standard fluid statics and dynamics principles, pressure-volume characteristics of the cardiac cycle, and compliant behavior of blood vessels. Cardiac cycle phases provide the physical and logical model structure, and Boolean algebra links model sections. The model is implemented using VisSim, a highly intuitive and easily learned block diagram modeling software package. Comparisons of model predictions of key variables to published values suggest that the model reasonably approximates expected behavior of those variables. The model responds plausibly to variations of independent variables. Projected usefulness of the model as an educational tool is threefold: independent variables which determine heart function may be easily varied to observe cause and effect; the model is used in an interactive setting; and the relationship of governing equations to model behavior is readily viewable and intuitive. Future use of this model in classrooms may give a more reasonable indication of its value as an educational tool.* *This dissertation includes a CD that is multimedia (contains text and other applications that are not available in a printed format). The CD requires the following applications: CorelPhotoHouse, CorelWordPerfect, VisSinViewer (included on CD), Internet access.
GENPLOT: A formula-based Pascal program for data manipulation and plotting
NASA Astrophysics Data System (ADS)
Kramer, Matthew J.
Geochemical processes involving alteration, differentiation, fractionation, or migration of elements may be elucidated by a number of discrimination or variation diagrams (e.g., AFM, Harker, Pearce, and many others). The construction of these diagrams involves arithmetic combination of selective elements (involving major, minor, or trace elements). GENPLOT utilizes a formula-based algorithm (an expression parser) which enables the program to manipulate multiparameter databases and plot XY, ternary, tetrahedron, and REE type plots without needing to change either the source code or rearranging databases. Formulae may be any quadratic expression whose variables are the column headings of the data matrix. A full-screen editor with limited equations and arithmetic functions (spreadsheet) has been incorporated into the program to aid data entry and editing. Data are stored as ASCII files to facilitate interchange of data between other programs and computers. GENPLOT was developed in Turbo Pascal for the IBM and compatible computers but also is available in Apple Pascal for the Apple Ile and Ill. Because the source code is too extensive to list here (about 5200 lines of Pascal code), the expression parsing routine, which is central to GENPLOT's flexibility is incorporated into a smaller demonstration program named SOLVE. The following paper includes a discussion on how the expression parser works and a detailed description of GENPLOT's capabilities.
Conceptual search in electronic patient record.
Baud, R H; Lovis, C; Ruch, P; Rassinoux, A M
2001-01-01
Search by content in a large corpus of free texts in the medical domain is, today, only partially solved. The so-called GREP approach (Get Regular Expression and Print), based on highly efficient string matching techniques, is subject to inherent limitations, especially its inability to recognize domain specific knowledge. Such methods oblige the user to formulate his or her query in a logical Boolean style; if this constraint is not fulfilled, the results are poor. The authors present an enhancement to string matching search by the addition of a light conceptual model behind the word lexicon. The new system accepts any sentence as a query and radically improves the quality of results. Efficiency regarding execution time is obtained at the expense of implementing advanced indexing algorithms in a pre-processing phase. The method is described and commented and a brief account of the results illustrates this paper.
Electrical Circuits in the Mathematics/Computer Science Classroom.
ERIC Educational Resources Information Center
McMillan, Robert D.
1988-01-01
Shows how, with little or no electrical background, students can apply Boolean algebra concepts to design and build integrated electrical circuits in the classroom that will reinforce important ideas in mathematics. (PK)
Topological Aspects of Information Retrieval.
ERIC Educational Resources Information Center
Egghe, Leo; Rousseau, Ronald
1998-01-01
Discusses topological aspects of theoretical information retrieval, including retrieval topology; similarity topology; pseudo-metric topology; document spaces as topological spaces; Boolean information retrieval as a subsystem of any topological system; and proofs of theorems. (LRW)
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.
Defining of the BDX930 Assembly Language
NASA Technical Reports Server (NTRS)
Boyer, R. S.; Moore, J. S.
1983-01-01
A definition of the BDX930 assembly language is presented. Various definition problems and suggested solutions are included. A class of defined recognizers based on boolean valued nowrecursive functions is employed in preprocessing.
Application of a Discrete Nonlinear Spectral Model to Ideal Cases of Wind Wave Generation.
1982-04-01
WRITE (6965)) bBD ODRM4T (IHII C SKI ’> 3 LINS i AND WRITE PLOT TITLE (IDOCHAR S PER LINE t 10 LINES AXI4CH-,(NClkR*9) /10 dRJTE (660) (TJL..EfI),I-I...A*CaGE.D.)JPP-J>P I F ( 8 D Do)) jpp-j P?+2 MiFPPeE)’i)&O TO 44 73 40JT-NPr(NIN,JPP) ;o TD (72, 14,7b,7BhNOUT 44 IF(A*3)q46q4b47 46 JPP-2 ;0 TO 73...EXTEZNAL FJNrI3N LAND IJS 13 THE BOOLEAN I.EoLDGICAL$ AND 01’ Td C FULLWORD INTEGCRS. C EXTEtNAL FJN:TION LOR, I,JS 1)7 THE BOOLEAN OR OF TWO FULLWORD
Analog Approach to Constraint Satisfaction Enabled by Spin Orbit Torque Magnetic Tunnel Junctions.
Wijesinghe, Parami; Liyanagedera, Chamika; Roy, Kaushik
2018-05-02
Boolean satisfiability (k-SAT) is an NP-complete (k ≥ 3) problem that constitute one of the hardest classes of constraint satisfaction problems. In this work, we provide a proof of concept hardware based analog k-SAT solver, that is built using Magnetic Tunnel Junctions (MTJs). The inherent physics of MTJs, enhanced by device level modifications, is harnessed here to emulate the intricate dynamics of an analog satisfiability (SAT) solver. In the presence of thermal noise, the MTJ based system can successfully solve Boolean satisfiability problems. Most importantly, our results exhibit that, the proposed MTJ based hardware SAT solver is capable of finding a solution to a significant fraction (at least 85%) of hard 3-SAT problems, within a time that has a polynomial relationship with the number of variables(<50).
Kerkhofs, Johan; Geris, Liesbet
2015-01-01
Boolean models have been instrumental in predicting general features of gene networks and more recently also as explorative tools in specific biological applications. In this study we introduce a basic quantitative and a limited time resolution to a discrete (Boolean) framework. Quantitative resolution is improved through the employ of normalized variables in unison with an additive approach. Increased time resolution stems from the introduction of two distinct priority classes. Through the implementation of a previously published chondrocyte network and T helper cell network, we show that this addition of quantitative and time resolution broadens the scope of biological behaviour that can be captured by the models. Specifically, the quantitative resolution readily allows models to discern qualitative differences in dosage response to growth factors. The limited time resolution, in turn, can influence the reachability of attractors, delineating the likely long term system behaviour. Importantly, the information required for implementation of these features, such as the nature of an interaction, is typically obtainable from the literature. Nonetheless, a trade-off is always present between additional computational cost of this approach and the likelihood of extending the model’s scope. Indeed, in some cases the inclusion of these features does not yield additional insight. This framework, incorporating increased and readily available time and semi-quantitative resolution, can help in substantiating the litmus test of dynamics for gene networks, firstly by excluding unlikely dynamics and secondly by refining falsifiable predictions on qualitative behaviour. PMID:26067297
Wang, Guan-Ying; Zhang, Sa-Li; Wang, Xiu-Ru; Feng, Min; Li, Chun; An, Yuan; Li, Xiao-Feng; Wang, Li-Zhi; Wang, Cai-Hong; Wang, Yong-Fu; Yang, Rong; Yan, Hui-Ming; Wang, Guo-Chun; Lu, Xin; Liu, Xia; Zhu, Ping; Chen, Li-Na; Jin, Hong-Tao; Liu, Jin-Ting; Guo, Hui-Fang; Chen, Hai-Ying; Xie, Jian-Li; Wei, Ping; Wang, Jun-Xiang; Liu, Xiang-Yuan; Sun, Lin; Cui, Liu-Fu; Shu, Rong; Liu, Bai-Lu; Yu, Ping; Zhang, Zhuo-Li; Li, Guang-Tao; Li, Zhen-Bin; Yang, Jing; Li, Jun-Fang; Jia, Bin; Zhang, Feng-Xiao; Tao, Jie-Mei; Lin, Jin-Ying; Wei, Mei-Qiu; Liu, Xiao-Min; Ke, Dan; Hu, Shao-Xian; Ye, Cong; Han, Shu-Ling; Yang, Xiu-Yan; Li, Hao; Huang, Ci-Bo; Gao, Ming; Lai, Bei; Cheng, Yong-Jing; Li, Xing-Fu; Song, Li-Jun; Yu, Xiao-Xia; Wang, Ai-Xue; Wu, Li-Jun; Wang, Yan-Hua; He, Lan; Sun, Wen-Wen; Gong, Lu; Wang, Xiao-Yuan; Wang, Yi; Zhao, Yi; Li, Xiao-Xia; Wang, Yan; Zhang, Yan; Su, Yin; Zhang, Chun-Fang; Mu, Rong; Li, Zhan-Guo
2015-02-01
The aim of this study is to investigate the remission rate of rheumatoid arthritis (RA) in China and identify its potential determinants. A multi-center cross-sectional study was conducted from July 2009 to January 2012. Data were collected by face-to-face interviews of the rheumatology outpatients in 28 tertiary hospitals in China. The remission rates were calculated in 486 RA patients according to different definitions of remission: the Disease Activity Score in 28 joints (DAS28), the Simplified Disease Activity Index (SDAI), the Clinical Disease Activity Index (CDAI), and the American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) Boolean definition. Potential determinants of RA remission were assessed by univariate and multivariate analyses. The remission rates of RA from this multi-center cohort were 8.6% (DAS28), 8.4% (SDAI), 8.2% (CDAI), and 6.8% (Boolean), respectively. Favorable factors associated with remission were: low Health Assessment Questionnaire (HAQ) score, absence of rheumatoid factor (RF) and anti-cyclic citrullinated peptide (anti-CCP), and treatment of methotrexate (MTX) and hydroxychloroquine (HCQ). Younger age was also predictive for the DAS28 and the Boolean remission. Multivariate analyses revealed a low HAQ score, the absence of anti-CCP, and the treatment with HCQ as independent determinants of remission. The clinical remission rate of RA patients was low in China. A low HAQ score, the absence of anti-CCP, and HCQ were significant independent determinants for RA remission.
Fusama, Mie; Miura, Yasushi; Yukioka, Kumiko; Kuroiwa, Takanori; Yukioka, Chikako; Inoue, Miyako; Nakanishi, Tae; Murata, Norikazu; Takai, Noriko; Higashi, Kayoko; Kuritani, Taro; Maeda, Keiji; Sano, Hajime; Yukioka, Masao; Nakahara, Hideko
2015-09-01
To evaluate whether the psychological state is related to the Boolean-based definition of patient global assessment (PGA) remission in patients with rheumatoid arthritis (RA). Patients with RA who met the criteria of swollen joint count (SJC) ≤ 1, tender joint count (TJC) ≤ 1 and C-reactive protein (CRP) ≤ 1 were divided into two groups, PGA remission group (PGA ≤ 1 cm) and non-remission group (PGA > 1 cm). Anxiety was evaluated utilizing the Hospital Anxiety and Depression Scale-Anxiety (HADS-A), while depression was evaluated with HADS-Depression (HADS-D) and the Center for Epidemiologic Studies Depression Scale (CES-D). Comparison analyses were done between the PGA remission and non-remission groups in HADS-A, HADS-D and CES-D. Seventy-eight patients met the criteria for SJC ≤ 1, TJC ≤ 1 and CRP ≤ 1. There were no significant differences between the PGA remission group (n = 45) and the non-remission group (n = 33) in age, sex, disease duration and Steinbrocker's class and stage. HADS-A, HADS-D and CES-D scores were significantly lower in the PGA remission group. Patients with RA who did not meet the PGA remission criteria despite good disease condition were in a poorer psychological state than those who satisfied the Boolean-based definition of clinical remission. Psychological support might be effective for improvement of PGA, resulting in the attainment of true remission.
Analytic representations of mK , FK, mη, and Fη in two loop S U (3 ) chiral perturbation theory
NASA Astrophysics Data System (ADS)
Ananthanarayan, B.; Bijnens, Johan; Friot, Samuel; Ghosh, Shayan
2018-06-01
In this work, we consider expressions for the masses and decay constants of the pseudoscalar mesons in S U (3 ) chiral perturbation theory. These involve sunset diagrams and their derivatives evaluated at p2=mP2 (P =π , K , η ). Recalling that there are three mass scales in this theory, mπ, mK and mη, there are instances when the finite part of the sunset diagrams do not admit an expression in terms of elementary functions, and have therefore been evaluated numerically in the past. In a recent publication, an expansion in the external momentum was performed to obtain approximate analytic expressions for mπ and Fπ, the pion mass and decay constant. We provide fully analytic exact expressions for mK and mη, the kaon and eta masses, and FK and Fη, the kaon and eta decay constants. These expressions, calculated using Mellin-Barnes methods, are in the form of double series in terms of two mass ratios. A numerical analysis of the results to evaluate the relative size of contributions coming from loops, chiral logarithms as well as phenomenological low-energy constants is presented. We also present a set of approximate analytic expressions for mK, FK, mη and Fη that facilitate comparisons with lattice results. Finally, we show how exact analytic expressions for mπ and Fπ may be obtained, the latter having been used in conjunction with the results for FK to produce a recently published analytic representation of FK/Fπ.
On Connected Diagrams and Cumulants of Erdős-Rényi Matrix Models
NASA Astrophysics Data System (ADS)
Khorunzhiy, O.
2008-08-01
Regarding the adjacency matrices of n-vertex graphs and related graph Laplacian we introduce two families of discrete matrix models constructed both with the help of the Erdős-Rényi ensemble of random graphs. Corresponding matrix sums represent the characteristic functions of the average number of walks and closed walks over the random graph. These sums can be considered as discrete analogues of the matrix integrals of random matrix theory. We study the diagram structure of the cumulant expansions of logarithms of these matrix sums and analyze the limiting expressions as n → ∞ in the cases of constant and vanishing edge probabilities.
Assessment of Steel Reinforcement Corrosion State by Parameters of Potentiodynamic Diagrams
NASA Astrophysics Data System (ADS)
Krajči, Ľudovít; Jerga, Ján
2015-12-01
The environment of the steel reinforcement has a significant impact on the durability and service life of a concrete structure. It is not only the presence of aggressive substances from the environment, but also the own composition of concrete mixture. The use of new types of cements, additives and admixtures must be preceded by verification, if they themselves shall not initiate the corrosion. There is a need for closer physical expression of the parameters of the potentiodynamic diagrams allowing reliable assessment of the influence of the surrounding environment on electrochemical behaviour of reinforcement. The analysis of zero retardation limits of potentiodynamic curves is presented.
Assessing the Math Performance of Young ESL Students.
ERIC Educational Resources Information Center
Lee, Fong Yun; Silverman, Fredrick L.; Montoya, Patricia
2002-01-01
Describes proven assessment strategies, which, used separately or in combination, can help young ESL students express their understanding of math concepts while building their English-language skills: Manipulative objects, diagrams, and physical movement. Also describes other assessment techniques including self-assessment, interviewing, and…
Automated Library System Specifications.
1986-06-01
University), LIS (Georqetown Universitv Medical Center) 20 DiSTRI3UT!ON.. AVAILABILITY OF ABSTRACT 21 ABSTRACT SECURITY CLASSIFICATION :UNCLASSIFIED...Interface) acquisitions, patron access catalo. (Boolean search), authority Afiles, zana ~ezient reports. Serials control expected in 1985. INDIVIDUALIZATIOI
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peng, Bo; Kowalski, Karol
In this paper we derive basic properties of the Green’s function matrix elements stemming from the exponential coupled cluster (CC) parametrization of the ground-state wave function. We demon- strate that all intermediates used to express retarded (or equivalently, ionized) part of the Green’s function in the ω-representation can be expressed through connected diagrams only. Similar proper- ties are also shared by the first order ω-derivatives of the retarded part of the CC Green’s function. This property can be extended to any order ω-derivatives of the Green’s function. Through the Dyson equation of CC Green’s function, the derivatives of corresponding CCmore » self-energy can be evaluated analytically. In analogy to the CC Green’s function, the corresponding CC self-energy is expressed in terms of connected diagrams only. Moreover, the ionized part of the CC Green’s func- tion satisfies the non-homogeneous linear system of ordinary differential equations, whose solution may be represented in the exponential form. Our analysis can be easily generalized to the advanced part of the CC Green’s function.« less
The SU(r)2 string functions as q-diagrams
NASA Astrophysics Data System (ADS)
Genish, Arel; Gepner, Doron
2016-06-01
A generalized Roger Ramanujan (GRR) type expression for the characters of A-type parafermions has been a long standing puzzle dating back to conjectures made regarding some of the characters in the 90s. Not long ago we have put forward such GRR type identities describing any of the level two ADE-type generalized parafermions characters at any rank. These characters are the string functions of simply laced Lie algebras at level two, as such, they are also of mathematical interest. In our last joint paper we presented the complete derivation for the D-type generalized parafermions characters identities. Here we generalize our previous discussion and prove the GRR type expressions for the characters of A-type generalized parafermions. To prove the A-type GRR conjecture we study further the q-diagrams, introduced in our last joint paper, and examine the diagrammatic interpretations of known identities among them Slater identities for the characters of the first minimal model, which is the Ising model, and the Bailey lemma.
Data Quality Screening Service
NASA Technical Reports Server (NTRS)
Strub, Richard; Lynnes, Christopher; Hearty, Thomas; Won, Young-In; Fox, Peter; Zednik, Stephan
2013-01-01
A report describes the Data Quality Screening Service (DQSS), which is designed to help automate the filtering of remote sensing data on behalf of science users. Whereas this process often involves much research through quality documents followed by laborious coding, the DQSS is a Web Service that provides data users with data pre-filtered to their particular criteria, while at the same time guiding the user with filtering recommendations of the cognizant data experts. The DQSS design is based on a formal semantic Web ontology that describes data fields and the quality fields for applying quality control within a data product. The accompanying code base handles several remote sensing datasets and quality control schemes for data products stored in Hierarchical Data Format (HDF), a common format for NASA remote sensing data. Together, the ontology and code support a variety of quality control schemes through the implementation of the Boolean expression with simple, reusable conditional expressions as operands. Additional datasets are added to the DQSS simply by registering instances in the ontology if they follow a quality scheme that is already modeled in the ontology. New quality schemes are added by extending the ontology and adding code for each new scheme.
Ramírez, Carlos; Mendoza, Luis
2018-04-01
Blood cell formation has been recognized as a suitable system to study celular differentiation mainly because of its experimental accessibility, and because it shows characteristics such as hierarchical and gradual bifurcated patterns of commitment, which are present in several developmental processes. Although hematopoiesis has been extensively studied and there is a wealth of molecular and cellular data about it, it is not clear how the underlying molecular regulatory networks define or restrict cellular differentiation processes. Here, we infer the molecular regulatory network that controls the differentiation of a blood cell subpopulation derived from the granulocyte-monocyte precursor (GMP), comprising monocytes, neutrophils, eosinophils, basophils and mast cells. We integrate published qualitative experimental data into a model to describe temporal expression patterns observed in GMP-derived cells. The model is implemented as a Boolean network, and its dynamical behavior is studied. Steady states of the network can be clearly identified with the expression profiles of monocytes, mast cells, neutrophils, basophils, and eosinophils, under wild-type and mutant backgrounds. All scripts are publicly available at https://github.com/caramirezal/RegulatoryNetworkGMPModel. lmendoza@biomedicas.unam.mx. Supplementary data are available at Bioinformatics online.
Jenkins, Dafyd J; Stekel, Dov J
2010-02-01
Gene regulation is one important mechanism in producing observed phenotypes and heterogeneity. Consequently, the study of gene regulatory network (GRN) architecture, function and evolution now forms a major part of modern biology. However, it is impossible to experimentally observe the evolution of GRNs on the timescales on which living species evolve. In silico evolution provides an approach to studying the long-term evolution of GRNs, but many models have either considered network architecture from non-adaptive evolution, or evolution to non-biological objectives. Here, we address a number of important modelling and biological questions about the evolution of GRNs to the realistic goal of biomass production. Can different commonly used simulation paradigms, in particular deterministic and stochastic Boolean networks, with and without basal gene expression, be used to compare adaptive with non-adaptive evolution of GRNs? Are these paradigms together with this goal sufficient to generate a range of solutions? Will the interaction between a biological goal and evolutionary dynamics produce trade-offs between growth and mutational robustness? We show that stochastic basal gene expression forces shrinkage of genomes due to energetic constraints and is a prerequisite for some solutions. In systems that are able to evolve rates of basal expression, two optima, one with and one without basal expression, are observed. Simulation paradigms without basal expression generate bloated networks with non-functional elements. Further, a range of functional solutions was observed under identical conditions only in stochastic networks. Moreover, there are trade-offs between efficiency and yield, indicating an inherent intertwining of fitness and evolutionary dynamics.
Modeling the formation of iron sulfide scales using thermodynamic simulation software
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anderko, A.; Shuler, P.J.
1998-12-31
A program has been developed for generating stability diagrams that concisely represent the thermodynamic state of multicomponent, multiphase aqueous systems in wide ranges of temperature and component concentrations. The diagrams are based on a thermodynamic model that combines the Helgeson-Kirkham-Flowers equation of state for standard-state properties with a solutions nonideality model based on the activity coefficient expressions developed by Bromley and Pitzer. The diagrams offer a flexible choice of independent variables, which include component concentrations in addition to the potential and pH. The stability diagrams are used to predict the conditions that favor the formation of stable and metastable ironmore » sulfide species, which are commonly deposited under oil field-related conditions. First, the diagrams have been applied to establish a sequence of transformations that iron sulfides undergo as they age. The predicted transformation sequences take into account environmental variables (e.g., hydrogen sulfide concentration, oxygen availability, etc.). The predictions are in agreement with experimental data on iron sulfide formation at the iron/solution interface and in bulk solution. The understanding of iron sulfide transformation sequences makes it possible to simulate experimental studies of H{sub 2}S/CO{sub 2} corrosion in the presence or absence of oxygen. A comparison with laboratory corrosion rate data under gas pipeline conditions indicates that the magnitude of corrosion rates can be correlated with the predicted stability of metastable iron sulfide phases.« less
The Reactome Pathway Knowledgebase
Jupe, Steven; Matthews, Lisa; Sidiropoulos, Konstantinos; Gillespie, Marc; Garapati, Phani; Haw, Robin; Jassal, Bijay; Korninger, Florian; May, Bruce; Milacic, Marija; Roca, Corina Duenas; Rothfels, Karen; Sevilla, Cristoffer; Shamovsky, Veronica; Shorser, Solomon; Varusai, Thawfeek; Viteri, Guilherme; Weiser, Joel
2018-01-01
Abstract The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism, and other cellular processes as an ordered network of molecular transformations—an extended version of a classic metabolic map, in a single consistent data model. Reactome functions both as an archive of biological processes and as a tool for discovering unexpected functional relationships in data such as gene expression profiles or somatic mutation catalogues from tumor cells. To support the continued brisk growth in the size and complexity of Reactome, we have implemented a graph database, improved performance of data analysis tools, and designed new data structures and strategies to boost diagram viewer performance. To make our website more accessible to human users, we have improved pathway display and navigation by implementing interactive Enhanced High Level Diagrams (EHLDs) with an associated icon library, and subpathway highlighting and zooming, in a simplified and reorganized web site with adaptive design. To encourage re-use of our content, we have enabled export of pathway diagrams as ‘PowerPoint’ files. PMID:29145629
Phase Diagram in a Random Mixture of Two Antiferromagnets with Competing Spin Anisotropies. I
NASA Astrophysics Data System (ADS)
Someya, Yoshiko
1981-12-01
The phase diagram of a random mixture of two antiferromagnets with competing spin anisotropies (A1-xBx) has been analyzed by extending the theory of Matsubara and Inawashiro, and Oguchi and Ishikawa. In the model assumed, the anisotropy energies are expressed by the anisotropic exchange interactions. According to this formulation, it has been shown that the concentration dependence of TN becomes a function of \\includegraphics{dummy.eps}, where P, Q=A, B; SP is a magnitude of P-spin, and JPQη is a η component of exchange integral between P- and Q-spin). Further, the phase boundary between an AF phase and an OAF (oblique antiferromagnetic) phase at T{=}0 K has been shown to be determined by α({\\equiv}SB/SA), if \\includegraphics{dummy.eps} are given. The obtained phase diagrams for Fe1-xCoxCl2, K2Mn1-xFexF4 and Fe1-xCoxCl2\\cdot2H2O are compared with the experimental ones.
Nonvolatile reconfigurable sequential logic in a HfO2 resistive random access memory array.
Zhou, Ya-Xiong; Li, Yi; Su, Yu-Ting; Wang, Zhuo-Rui; Shih, Ling-Yi; Chang, Ting-Chang; Chang, Kuan-Chang; Long, Shi-Bing; Sze, Simon M; Miao, Xiang-Shui
2017-05-25
Resistive random access memory (RRAM) based reconfigurable logic provides a temporal programmable dimension to realize Boolean logic functions and is regarded as a promising route to build non-von Neumann computing architecture. In this work, a reconfigurable operation method is proposed to perform nonvolatile sequential logic in a HfO 2 -based RRAM array. Eight kinds of Boolean logic functions can be implemented within the same hardware fabrics. During the logic computing processes, the RRAM devices in an array are flexibly configured in a bipolar or complementary structure. The validity was demonstrated by experimentally implemented NAND and XOR logic functions and a theoretically designed 1-bit full adder. With the trade-off between temporal and spatial computing complexity, our method makes better use of limited computing resources, thus provides an attractive scheme for the construction of logic-in-memory systems.
Synthesizing Biomolecule-based Boolean Logic Gates
Miyamoto, Takafumi; Razavi, Shiva; DeRose, Robert; Inoue, Takanari
2012-01-01
One fascinating recent avenue of study in the field of synthetic biology is the creation of biomolecule-based computers. The main components of a computing device consist of an arithmetic logic unit, the control unit, memory, and the input and output devices. Boolean logic gates are at the core of the operational machinery of these parts, hence to make biocomputers a reality, biomolecular logic gates become a necessity. Indeed, with the advent of more sophisticated biological tools, both nucleic acid- and protein-based logic systems have been generated. These devices function in the context of either test tubes or living cells and yield highly specific outputs given a set of inputs. In this review, we discuss various types of biomolecular logic gates that have been synthesized, with particular emphasis on recent developments that promise increased complexity of logic gate circuitry, improved computational speed, and potential clinical applications. PMID:23526588
Interconnect-free parallel logic circuits in a single mechanical resonator
Mahboob, I.; Flurin, E.; Nishiguchi, K.; Fujiwara, A.; Yamaguchi, H.
2011-01-01
In conventional computers, wiring between transistors is required to enable the execution of Boolean logic functions. This has resulted in processors in which billions of transistors are physically interconnected, which limits integration densities, gives rise to huge power consumption and restricts processing speeds. A method to eliminate wiring amongst transistors by condensing Boolean logic into a single active element is thus highly desirable. Here, we demonstrate a novel logic architecture using only a single electromechanical parametric resonator into which multiple channels of binary information are encoded as mechanical oscillations at different frequencies. The parametric resonator can mix these channels, resulting in new mechanical oscillation states that enable the construction of AND, OR and XOR logic gates as well as multibit logic circuits. Moreover, the mechanical logic gates and circuits can be executed simultaneously, giving rise to the prospect of a parallel logic processor in just a single mechanical resonator. PMID:21326230
Interconnect-free parallel logic circuits in a single mechanical resonator.
Mahboob, I; Flurin, E; Nishiguchi, K; Fujiwara, A; Yamaguchi, H
2011-02-15
In conventional computers, wiring between transistors is required to enable the execution of Boolean logic functions. This has resulted in processors in which billions of transistors are physically interconnected, which limits integration densities, gives rise to huge power consumption and restricts processing speeds. A method to eliminate wiring amongst transistors by condensing Boolean logic into a single active element is thus highly desirable. Here, we demonstrate a novel logic architecture using only a single electromechanical parametric resonator into which multiple channels of binary information are encoded as mechanical oscillations at different frequencies. The parametric resonator can mix these channels, resulting in new mechanical oscillation states that enable the construction of AND, OR and XOR logic gates as well as multibit logic circuits. Moreover, the mechanical logic gates and circuits can be executed simultaneously, giving rise to the prospect of a parallel logic processor in just a single mechanical resonator.
NASA Technical Reports Server (NTRS)
Strahler, Alan H.; Li, Xiao-Wen; Jupp, David L. B.
1991-01-01
The bidirectional radiance or reflectance of a forest or woodland can be modeled using principles of geometric optics and Boolean models for random sets in a three dimensional space. This model may be defined at two levels, the scene includes four components; sunlight and shadowed canopy, and sunlit and shadowed background. The reflectance of the scene is modeled as the sum of the reflectances of the individual components as weighted by their areal proportions in the field of view. At the leaf level, the canopy envelope is an assemblage of leaves, and thus the reflectance is a function of the areal proportions of sunlit and shadowed leaf, and sunlit and shadowed background. Because the proportions of scene components are dependent upon the directions of irradiance and exitance, the model accounts for the hotspot that is well known in leaf and tree canopies.
Synthesizing biomolecule-based Boolean logic gates.
Miyamoto, Takafumi; Razavi, Shiva; DeRose, Robert; Inoue, Takanari
2013-02-15
One fascinating recent avenue of study in the field of synthetic biology is the creation of biomolecule-based computers. The main components of a computing device consist of an arithmetic logic unit, the control unit, memory, and the input and output devices. Boolean logic gates are at the core of the operational machinery of these parts, and hence to make biocomputers a reality, biomolecular logic gates become a necessity. Indeed, with the advent of more sophisticated biological tools, both nucleic acid- and protein-based logic systems have been generated. These devices function in the context of either test tubes or living cells and yield highly specific outputs given a set of inputs. In this review, we discuss various types of biomolecular logic gates that have been synthesized, with particular emphasis on recent developments that promise increased complexity of logic gate circuitry, improved computational speed, and potential clinical applications.
Simultaneous G-Quadruplex DNA Logic.
Bader, Antoine; Cockroft, Scott L
2018-04-03
A fundamental principle of digital computer operation is Boolean logic, where inputs and outputs are described by binary integer voltages. Similarly, inputs and outputs may be processed on the molecular level as exemplified by synthetic circuits that exploit the programmability of DNA base-pairing. Unlike modern computers, which execute large numbers of logic gates in parallel, most implementations of molecular logic have been limited to single computing tasks, or sensing applications. This work reports three G-quadruplex-based logic gates that operate simultaneously in a single reaction vessel. The gates respond to unique Boolean DNA inputs by undergoing topological conversion from duplex to G-quadruplex states that were resolved using a thioflavin T dye and gel electrophoresis. The modular, addressable, and label-free approach could be incorporated into DNA-based sensors, or used for resolving and debugging parallel processes in DNA computing applications. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Satisfiability of logic programming based on radial basis function neural networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged
2014-07-10
In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We appliedmore » the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems.« less
Some Applications Of Semigroups And Computer Algebra In Discrete Structures
NASA Astrophysics Data System (ADS)
Bijev, G.
2009-11-01
An algebraic approach to the pseudoinverse generalization problem in Boolean vector spaces is used. A map (p) is defined, which is similar to an orthogonal projection in linear vector spaces. Some other important maps with properties similar to those of the generalized inverses (pseudoinverses) of linear transformations and matrices corresponding to them are also defined and investigated. Let Ax = b be an equation with matrix A and vectors x and b Boolean. Stochastic experiments for solving the equation, which involves the maps defined and use computer algebra methods, have been made. As a result, the Hamming distance between vectors Ax = p(b) and b is equal or close to the least possible. We also share our experience in using computer algebra systems for teaching discrete mathematics and linear algebra and research. Some examples for computations with binary relations using Maple are given.
Lattice Theory, Measures and Probability
NASA Astrophysics Data System (ADS)
Knuth, Kevin H.
2007-11-01
In this tutorial, I will discuss the concepts behind generalizing ordering to measuring and apply these ideas to the derivation of probability theory. The fundamental concept is that anything that can be ordered can be measured. Since we are in the business of making statements about the world around us, we focus on ordering logical statements according to implication. This results in a Boolean lattice, which is related to the fact that the corresponding logical operations form a Boolean algebra. The concept of logical implication can be generalized to degrees of implication by generalizing the zeta function of the lattice. The rules of probability theory arise naturally as a set of constraint equations. Through this construction we are able to neatly connect the concepts of order, structure, algebra, and calculus. The meaning of probability is inherited from the meaning of the ordering relation, implication, rather than being imposed in an ad hoc manner at the start.
A solution to the surface intersection problem. [Boolean functions in geometric modeling
NASA Technical Reports Server (NTRS)
Timer, H. G.
1977-01-01
An application-independent geometric model within a data base framework should support the use of Boolean operators which allow the user to construct a complex model by appropriately combining a series of simple models. The use of these operators leads to the concept of implicitly and explicitly defined surfaces. With an explicitly defined model, the surface area may be computed by simply summing the surface areas of the bounding surfaces. For an implicitly defined model, the surface area computation must deal with active and inactive regions. Because the surface intersection problem involves four unknowns and its solution is a space curve, the parametric coordinates of each surface must be determined as a function of the arc length. Various subproblems involved in the general intersection problem are discussed, and the mathematical basis for their solution is presented along with a program written in FORTRAN IV for implementation on the IBM 370 TSO system.
Polynomial algebra of discrete models in systems biology.
Veliz-Cuba, Alan; Jarrah, Abdul Salam; Laubenbacher, Reinhard
2010-07-01
An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network models to logical models and Petri nets. They are used to model a variety of biochemical networks, such as metabolic networks, gene regulatory networks and signal transduction networks. There is increasing evidence that such models can capture key dynamic features of biological networks and can be used successfully for hypothesis generation. This article provides a unified framework that can aid the mathematical analysis of Boolean network models, logical models and Petri nets. They can be represented as polynomial dynamical systems, which allows the use of a variety of mathematical tools from computer algebra for their analysis. Algorithms are presented for the translation into polynomial dynamical systems. Examples are given of how polynomial algebra can be used for the model analysis. alanavc@vt.edu Supplementary data are available at Bioinformatics online.
Graphene-based non-Boolean logic circuits
NASA Astrophysics Data System (ADS)
Liu, Guanxiong; Ahsan, Sonia; Khitun, Alexander G.; Lake, Roger K.; Balandin, Alexander A.
2013-10-01
Graphene revealed a number of unique properties beneficial for electronics. However, graphene does not have an energy band-gap, which presents a serious hurdle for its applications in digital logic gates. The efforts to induce a band-gap in graphene via quantum confinement or surface functionalization have not resulted in a breakthrough. Here we show that the negative differential resistance experimentally observed in graphene field-effect transistors of "conventional" design allows for construction of viable non-Boolean computational architectures with the gapless graphene. The negative differential resistance—observed under certain biasing schemes—is an intrinsic property of graphene, resulting from its symmetric band structure. Our atomistic modeling shows that the negative differential resistance appears not only in the drift-diffusion regime but also in the ballistic regime at the nanometer-scale—although the physics changes. The obtained results present a conceptual change in graphene research and indicate an alternative route for graphene's applications in information processing.
Insights into Fourier Synthesis and Analysis: Part 2--A Simplified Mathematics.
ERIC Educational Resources Information Center
Moore, Guy S. M.
1988-01-01
Introduced is an analysis of a waveform into its Fourier components. Topics included are simplified analysis of a square waveform, a triangular waveform, half-wave rectified alternating current (AC), and impulses. Provides the mathematical expression and simplified analysis diagram of each waveform. (YP)
Factors associated with sustained remission in patients with rheumatoid arthritis.
Martire, María Victoria; Marino Claverie, Lucila; Duarte, Vanesa; Secco, Anastasia; Mammani, Marta
2015-01-01
To find out the factors that are associated with sustained remission measured by DAS28 and boolean ACR EULAR 2011 criteria at the time of diagnosis of rheumatoid arthritis. Medical records of patients with rheumatoid arthritis in sustained remission according to DAS28 were reviewed. They were compared with patients who did not achieved values of DAS28<2.6 in any visit during the first 3 years after diagnosis. We also evaluated if patients achieved the boolean ACR/EULAR criteria. Variables analyzed: sex, age, smoking, comorbidities, rheumatoid factor, anti-CCP, ESR, CRP, erosions, HAQ, DAS28, extra-articular manifestations, time to initiation of treatment, involvement of large joints, number of tender joints, number of swollen joints, pharmacological treatment. Forty five patients that achieved sustained remission were compared with 44 controls. The variables present at diagnosis that significantly were associated with remission by DAS28 were: lower values of DAS28, HAQ, ESR, NTJ, NSJ, negative CRP, absence of erosions, male sex and absence of involvement of large joints. Only 24.71% achieved the boolean criteria. The variables associated with sustained remission by these criteria were: lower values of DAS28, HAQ, ESR, number of tender joints and number of swollen joints, negative CRP and absence of erosions. The factors associated with sustained remission were the lower baseline disease activity, the low degree of functional disability and lower joint involvement. We consider it important to recognize these factors to optimize treatment. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.
Boolean Operations with Prism Algebraic Patches
Bajaj, Chandrajit; Paoluzzi, Alberto; Portuesi, Simone; Lei, Na; Zhao, Wenqi
2009-01-01
In this paper we discuss a symbolic-numeric algorithm for Boolean operations, closed in the algebra of curved polyhedra whose boundary is triangulated with algebraic patches (A-patches). This approach uses a linear polyhedron as a first approximation of both the arguments and the result. On each triangle of a boundary representation of such linear approximation, a piecewise cubic algebraic interpolant is built, using a C1-continuous prism algebraic patch (prism A-patch) that interpolates the three triangle vertices, with given normal vectors. The boundary representation only stores the vertices of the initial triangulation and their external vertex normals. In order to represent also flat and/or sharp local features, the corresponding normal-per-face and/or normal-per-edge may be also given, respectively. The topology is described by storing, for each curved triangle, the two triples of pointers to incident vertices and to adjacent triangles. For each triangle, a scaffolding prism is built, produced by its extreme vertices and normals, which provides a containment volume for the curved interpolating A-patch. When looking for the result of a regularized Boolean operation, the 0-set of a tri-variate polynomial within each such prism is generated, and intersected with the analogous 0-sets of the other curved polyhedron, when two prisms have non-empty intersection. The intersection curves of the boundaries are traced and used to decompose each boundary into the 3 standard classes of subpatches, denoted in, out and on. While tracing the intersection curves, the locally refined triangulation of intersecting patches is produced, and added to the boundary representation. PMID:21516262
Computing smallest intervention strategies for multiple metabolic networks in a boolean model.
Lu, Wei; Tamura, Takeyuki; Song, Jiangning; Akutsu, Tatsuya
2015-02-01
This article considers the problem whereby, given two metabolic networks N1 and N2, a set of source compounds, and a set of target compounds, we must find the minimum set of reactions whose removal (knockout) ensures that the target compounds are not producible in N1 but are producible in N2. Similar studies exist for the problem of finding the minimum knockout with the smallest side effect for a single network. However, if technologies of external perturbations are advanced in the near future, it may be important to develop methods of computing the minimum knockout for multiple networks (MKMN). Flux balance analysis (FBA) is efficient if a well-polished model is available. However, that is not always the case. Therefore, in this article, we study MKMN in Boolean models and an elementary mode (EM)-based model. Integer linear programming (ILP)-based methods are developed for these models, since MKMN is NP-complete for both the Boolean model and the EM-based model. Computer experiments are conducted with metabolic networks of clostridium perfringens SM101 and bifidobacterium longum DJO10A, respectively known as bad bacteria and good bacteria for the human intestine. The results show that larger networks are more likely to have MKMN solutions. However, solving for these larger networks takes a very long time, and often the computation cannot be completed. This is reasonable, because small networks do not have many alternative pathways, making it difficult to satisfy the MKMN condition, whereas in large networks the number of candidate solutions explodes. Our developed software minFvskO is available online.
An analytic approach to sunset diagrams in chiral perturbation theory: Theory and practice
NASA Astrophysics Data System (ADS)
Ananthanarayan, B.; Bijnens, Johan; Ghosh, Shayan; Hebbar, Aditya
2016-12-01
We demonstrate the use of several code implementations of the Mellin-Barnes method available in the public domain to derive analytic expressions for the sunset diagrams that arise in the two-loop contribution to the pion mass and decay constant in three-flavoured chiral perturbation theory. We also provide results for all possible two mass configurations of the sunset integral, and derive a new one-dimensional integral representation for the one mass sunset integral with arbitrary external momentum. Thoroughly annotated Mathematica notebooks are provided as ancillary files in the Electronic Supplementary Material to this paper, which may serve as pedagogical supplements to the methods described in this paper.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kashani-Poor, A.
2004-11-03
We demonstrate that for a broad class of local Calabi-Yau geometries built around a string of IP{sup 1}s--those whose toric diagrams are given by triangulations of a strip--we can derive simple rules, based on the topological vertex, for obtaining expressions for the topological string partition function in which the sums over Young tableaux have been performed. By allowing non-trivial tableaux on the external legs of the corresponding web diagrams, these strips can be used as building blocks for more general geometries. As applications of our result, we study the behavior of topological string amplitudes under flops, as well as checkmore » Nekrasov's conjecture in its most general form.« less
NASA Astrophysics Data System (ADS)
Ohata, Koji; Naruse, Hajime; Yokokawa, Miwa; Viparelli, Enrica
2017-11-01
Understanding of the formative conditions of fluvial bedforms is significant for both river management and geological studies. Diagrams showing bedform stability conditions have been widely used for the analyses of sedimentary structures. However, the use of discriminants to determine the boundaries of different bedforms regimes has not yet been explored. In this study, we use discriminant functions to describe formative conditions for a range of fluvial bedforms in a 3-D dimensionless parametric space. We do this by means of discriminant analysis using the Mahalanobis distance. We analyzed 3,793 available laboratory and field data and used these to produce new bedform phase diagrams. These diagrams employ three dimensionless parameters representing properties of flow hydraulics and sediment particles as their axes. The discriminant functions for bedform regimes proposed herein are quadratic functions of three dimensionless parameters and are expressed as curved surfaces in 3-D space. These empirical functions can be used to estimate paleoflow velocities from sedimentary structures. As an example of the reconstruction of hydraulic conditions, we calculated the paleoflow velocity of the 2011 Tohoku-Oki tsunami backwash flow from the sedimentary structures of the tsunami deposit. In so doing, we successfully reconstructed reasonable values of the paleoflow velocities.
A Note about Information Science Research.
ERIC Educational Resources Information Center
Salton, Gerard
1985-01-01
Discusses the relationship between information science research and practice and briefly describes current research on 10 topics in information retrieval literature: vector processing retrieval strategy, probabilistic retrieval models, inverted file procedures, relevance feedback, Boolean query formulations, front-end procedures, citation…
Bibliographic Instruction in the 21st Century.
ERIC Educational Resources Information Center
Poirier, Gayle
2000-01-01
Discusses bibliographic instruction in libraries. Topics include a history of bibliographic instruction; the Internet and electronic searching; librarians' use of technology; defining information needs; locating and accessing information, including classification systems and Boolean searching; evaluating information; using and communication…
Video-Based Affect Detection in Noninteractive Learning Environments
ERIC Educational Resources Information Center
Chen, Yuxuan; Bosch, Nigel; D'Mello, Sidney
2015-01-01
The current paper explores possible solutions to the problem of detecting affective states from facial expressions during text/diagram comprehension, a context devoid of interactive events that can be used to infer affect. These data present an interesting challenge for face-based affect detection because likely locations of affective facial…
ERIC Educational Resources Information Center
Hogarth, Burne
This student artist's handbook uses drawings and diagrams to demonstrate the basic structure, proportions, and expressive nature of the human form from an artist's point of view. Emphasis is placed upon the relationship of mass to movement. Drawings of the figure in action reveal the rhythmic relationship of muscles and their effect upon surface…
Need Assessment: Winnowing Expressed Concerns for Critical Needs. A Training Manual.
ERIC Educational Resources Information Center
Eastmond, Jefferson N.
A procedure is given for determining various concerns for the identification of priority needs or important problems. Chapters deal with procedures for harvesting educational concerns, illustrations of the systematic harvesting of concerns, concerns classification and analysis, and conducting the need assessment. A diagram of the procedure for…
Automatic Synthesis of UML Designs from Requirements in an Iterative Process
NASA Technical Reports Server (NTRS)
Schumann, Johann; Whittle, Jon; Clancy, Daniel (Technical Monitor)
2001-01-01
The Unified Modeling Language (UML) is gaining wide popularity for the design of object-oriented systems. UML combines various object-oriented graphical design notations under one common framework. A major factor for the broad acceptance of UML is that it can be conveniently used in a highly iterative, Use Case (or scenario-based) process (although the process is not a part of UML). Here, the (pre-) requirements for the software are specified rather informally as Use Cases and a set of scenarios. A scenario can be seen as an individual trace of a software artifact. Besides first sketches of a class diagram to illustrate the static system breakdown, scenarios are a favorite way of communication with the customer, because scenarios describe concrete interactions between entities and are thus easy to understand. Scenarios with a high level of detail are often expressed as sequence diagrams. Later in the design and implementation stage (elaboration and implementation phases), a design of the system's behavior is often developed as a set of statecharts. From there (and the full-fledged class diagram), actual code development is started. Current commercial UML tools support this phase by providing code generators for class diagrams and statecharts. In practice, it can be observed that the transition from requirements to design to code is a highly iterative process. In this talk, a set of algorithms is presented which perform reasonable synthesis and transformations between different UML notations (sequence diagrams, Object Constraint Language (OCL) constraints, statecharts). More specifically, we will discuss the following transformations: Statechart synthesis, introduction of hierarchy, consistency of modifications, and "design-debugging".
Algebraic diagrammatic construction formalism with three-body interactions
NASA Astrophysics Data System (ADS)
Raimondi, Francesco; Barbieri, Carlo
2018-05-01
Background: Self-consistent Green's function theory has recently been extended to the basic formalism needed to account for three-body interactions [Carbone, Cipollone, Barbieri, Rios, and Polls, Phys. Rev. C 88, 054326 (2013), 10.1103/PhysRevC.88.054326]. The contribution of three-nucleon forces has so far been included in ab initio calculations on nuclear matter and finite nuclei only as averaged two-nucleon forces. Purpose: We derive the working equations for all possible two- and three-nucleon terms that enter the expansion of the self-energy up to the third order, thus including the interaction-irreducible (i.e., not averaged) diagrams with three-nucleon forces that have been previously neglected. Methods: We employ the algebraic diagrammatic construction up to the third order as an organization scheme for generating a nonperturbative self-energy, in which ring (particle-hole) and ladder (particle-particle) diagrams are resummed to all orders. Results: We derive expressions of the static and dynamic self-energy up to the third order, by taking into account the set of diagrams required when either the skeleton or nonskeleton expansions of the single-particle propagator are assumed. A hierarchy of importance among different diagrams is revealed, and a particular emphasis is given to a third-order diagram [see Fig. 2(c)] that is expected to play a significant role among those featuring an interaction-irreducible three-nucleon force. Conclusion: A consistent formalism to resum at infinite order correlations induced by three-nucleon forces in the self-consistent Green's function theory is now available and ready to be implemented in the many-body solvers.
Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles
With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate t...
A Boolean Network Model of Nuclear Receptor Mediated Cell Cycle Progression
Nuclear receptors (NRs) are ligand-activated transcription factors that regulate a broad range of cellular processes. Hormones, lipids and xenobiotics have been shown to activate NRs with a range of consequences on development, metabolism, oxidative stress, apoptosis, and prolif...
A Boolean Network Model of Nuclear Receptor Mediated Cell Cycle Progression (S)
Nuclear receptors (NRs) are ligand-activated transcription factors that regulate a broad range of cellular processes. Hormones, lipids and xenobiotics have been shown to activate NRs with a range of consequences on development, metabolism, oxidative stress, apoptosis, and prolif...
Automatic Query Formulations in Information Retrieval.
ERIC Educational Resources Information Center
Salton, G.; And Others
1983-01-01
Introduces methods designed to reduce role of search intermediaries by generating Boolean search formulations automatically using term frequency considerations from natural language statements provided by system patrons. Experimental results are supplied and methods are described for applying automatic query formulation process in practice.…
Digital Equipment Corporation's CRDOM Software and Database Publications.
ERIC Educational Resources Information Center
Adams, Michael Q.
1986-01-01
Acquaints information professionals with Digital Equipment Corporation's compact optical disk read-only-memory (CDROM) search and retrieval software and growing library of CDROM database publications (COMPENDEX, Chemical Abstracts Services). Highlights include MicroBASIS, boolean operators, range operators, word and phrase searching, proximity…
ERIC Educational Resources Information Center
Dalton, LeRoy C., Ed.; Snyder, Henry D., Ed.
The ten chapters in this booklet cover topics not ordinarily discussed in the classroom: Fibonacci sequences, projective geometry, groups, infinity and transfinite numbers, Pascal's Triangle, topology, experiments with natural numbers, non-Euclidean geometries, Boolean algebras, and the imaginary and the infinite in geometry. Each chapter is…
Leak location using the pattern of the frequency response diagram in pipelines: a numerical study
NASA Astrophysics Data System (ADS)
Lee, Pedro J.; Vítkovský, John P.; Lambert, Martin F.; Simpson, Angus R.; Liggett, James A.
2005-06-01
This paper presents a method of leak detection in a single pipe where the behaviour of the system frequency response diagram (FRD) is used as an indicator of the pipe integrity. The presence of a leak in a pipe imposes a pattern on the resonance peaks of the FRD that can be used as a clear indication of leakage. Analytical expressions describing the pattern of the resonance peaks are derived. Illustrations of how this pattern can be used to individually locate and size multiple leaks within the system are presented. Practical issues with the technique, such as the procedure for frequency response extraction, the impact of measurement position, noise- and frequency-dependent friction are also discussed.
Energy level diagrams for black hole orbits
NASA Astrophysics Data System (ADS)
Levin, Janna
2009-12-01
A spinning black hole with a much smaller black hole companion forms a fundamental gravitational system, like a colossal classical analog to an atom. In an appealing if imperfect analogy with atomic physics, this gravitational atom can be understood through a discrete spectrum of periodic orbits. Exploiting a correspondence between the set of periodic orbits and the set of rational numbers, we are able to construct periodic tables of orbits and energy level diagrams of the accessible states around black holes. We also present a closed-form expression for the rational q, thereby quantifying zoom-whirl behavior in terms of spin, energy and angular momentum. The black hole atom is not just a theoretical construct, but corresponds to extant astrophysical systems detectable by future gravitational wave observatories.
Chebouba, Lokmane; Miannay, Bertrand; Boughaci, Dalila; Guziolowski, Carito
2018-03-08
During the last years, several approaches were applied on biomedical data to detect disease specific proteins and genes in order to better target drugs. It was shown that statistical and machine learning based methods use mainly clinical data and improve later their results by adding omics data. This work proposes a new method to discriminate the response of Acute Myeloid Leukemia (AML) patients to treatment. The proposed approach uses proteomics data and prior regulatory knowledge in the form of networks to predict cancer treatment outcomes by finding out the different Boolean networks specific to each type of response to drugs. To show its effectiveness we evaluate our method on a dataset from the DREAM 9 challenge. The results are encouraging and demonstrate the benefit of our approach to distinguish patient groups with different response to treatment. In particular each treatment response group is characterized by a predictive model in the form of a signaling Boolean network. This model describes regulatory mechanisms which are specific to each response group. The proteins in this model were selected from the complete dataset by imposing optimization constraints that maximize the difference in the logical response of the Boolean network associated to each group of patients given the omic dataset. This mechanistic and predictive model also allow us to classify new patients data into the two different patient response groups. We propose a new method to detect the most relevant proteins for understanding different patient responses upon treatments in order to better target drugs using a Prior Knowledge Network and proteomics data. The results are interesting and show the effectiveness of our method.
ASP-G: an ASP-based method for finding attractors in genetic regulatory networks
Mushthofa, Mushthofa; Torres, Gustavo; Van de Peer, Yves; Marchal, Kathleen; De Cock, Martine
2014-01-01
Motivation: Boolean network models are suitable to simulate GRNs in the absence of detailed kinetic information. However, reducing the biological reality implies making assumptions on how genes interact (interaction rules) and how their state is updated during the simulation (update scheme). The exact choice of the assumptions largely determines the outcome of the simulations. In most cases, however, the biologically correct assumptions are unknown. An ideal simulation thus implies testing different rules and schemes to determine those that best capture an observed biological phenomenon. This is not trivial because most current methods to simulate Boolean network models of GRNs and to compute their attractors impose specific assumptions that cannot be easily altered, as they are built into the system. Results: To allow for a more flexible simulation framework, we developed ASP-G. We show the correctness of ASP-G in simulating Boolean network models and obtaining attractors under different assumptions by successfully recapitulating the detection of attractors of previously published studies. We also provide an example of how performing simulation of network models under different settings help determine the assumptions under which a certain conclusion holds. The main added value of ASP-G is in its modularity and declarativity, making it more flexible and less error-prone than traditional approaches. The declarative nature of ASP-G comes at the expense of being slower than the more dedicated systems but still achieves a good efficiency with respect to computational time. Availability and implementation: The source code of ASP-G is available at http://bioinformatics.intec.ugent.be/kmarchal/Supplementary_Information_Musthofa_2014/asp-g.zip. Contact: Kathleen.Marchal@UGent.be or Martine.DeCock@UGent.be Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25028722
Intelligent Machines in the 21st Century: Automating the Processes of Inference and Inquiry
NASA Technical Reports Server (NTRS)
Knuth, Kevin H.
2003-01-01
The last century saw the application of Boolean algebra toward the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines. in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. However, modern intelligent machines work by inferring knowledge using only their pre-programmed prior knowledge and the data provided. They lack the ability to ask questions, or request data that would aid their inferences. Recent advances in understanding the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we identified the algebra of questions as the free distributive algebra, which now allows us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper we describe this logic of inference and inquiry using the mathematics of partially ordered sets and the scaffolding of lattice theory, discuss the far-reaching implications of the methodology, and demonstrate its application with current examples in machine learning. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them to not only make inferences from data, but also decide which question to ask, experiment to perform, or measurement to take given what they have learned and what they are designed to understand.
Computing Smallest Intervention Strategies for Multiple Metabolic Networks in a Boolean Model
Lu, Wei; Song, Jiangning; Akutsu, Tatsuya
2015-01-01
Abstract This article considers the problem whereby, given two metabolic networks N1 and N2, a set of source compounds, and a set of target compounds, we must find the minimum set of reactions whose removal (knockout) ensures that the target compounds are not producible in N1 but are producible in N2. Similar studies exist for the problem of finding the minimum knockout with the smallest side effect for a single network. However, if technologies of external perturbations are advanced in the near future, it may be important to develop methods of computing the minimum knockout for multiple networks (MKMN). Flux balance analysis (FBA) is efficient if a well-polished model is available. However, that is not always the case. Therefore, in this article, we study MKMN in Boolean models and an elementary mode (EM)-based model. Integer linear programming (ILP)-based methods are developed for these models, since MKMN is NP-complete for both the Boolean model and the EM-based model. Computer experiments are conducted with metabolic networks of clostridium perfringens SM101 and bifidobacterium longum DJO10A, respectively known as bad bacteria and good bacteria for the human intestine. The results show that larger networks are more likely to have MKMN solutions. However, solving for these larger networks takes a very long time, and often the computation cannot be completed. This is reasonable, because small networks do not have many alternative pathways, making it difficult to satisfy the MKMN condition, whereas in large networks the number of candidate solutions explodes. Our developed software minFvskO is available online. PMID:25684199
Model-Checking with Edge-Valued Decision Diagrams
NASA Technical Reports Server (NTRS)
Roux, Pierre; Siminiceanu, Radu I.
2010-01-01
We describe an algebra of Edge-Valued Decision Diagrams (EVMDDs) to encode arithmetic functions and its implementation in a model checking library along with state-of-the-art algorithms for building the transition relation and the state space of discrete state systems. We provide efficient algorithms for manipulating EVMDDs and give upper bounds of the theoretical time complexity of these algorithms for all basic arithmetic and relational operators. We also demonstrate that the time complexity of the generic recursive algorithm for applying a binary operator on EVMDDs is no worse than that of Multi-Terminal Decision Diagrams. We have implemented a new symbolic model checker with the intention to represent in one formalism the best techniques available at the moment across a spectrum of existing tools: EVMDDs for encoding arithmetic expressions, identity-reduced MDDs for representing the transition relation, and the saturation algorithm for reachability analysis. We compare our new symbolic model checking EVMDD library with the widely used CUDD package and show that, in many cases, our tool is several orders of magnitude faster than CUDD.
Wei, Hua; Hu, Bo; Tang, Suming; Zhao, Guojie; Guan, Yifu
2016-01-01
Small molecule metabolites and their allosterically regulated repressors play an important role in many gene expression and metabolic disorder processes. These natural sensors, though valuable as good logic switches, have rarely been employed without transcription machinery in cells. Here, two pairs of repressors, which function in opposite ways, were cloned, purified and used to control DNA replication in rolling circle amplification (RCA) in vitro. By using metabolites and repressors as inputs, RCA signals as outputs, four basic logic modules were constructed successfully. To achieve various logic computations based on these basic modules, we designed series and parallel strategies of circular templates, which can further assemble these repressor modules in an RCA platform to realize twelve two-input Boolean logic gates and a three-input logic gate. The RCA-output and RCA-assembled platform was proved to be easy and flexible for complex logic processes and might have application potential in molecular computing and synthetic biology. PMID:27869177
Towards data integration automation for the French rare disease registry.
Maaroufi, Meriem; Choquet, Rémy; Landais, Paul; Jaulent, Marie-Christine
2015-01-01
Building a medical registry upon an existing infrastructure and rooted practices is not an easy task. It is the case for the BNDMR project, the French rare disease registry, that aims to collect administrative and medical data of rare disease patients seen in different hospitals. To avoid duplicating data entry for health professionals, the project plans to deploy connectors with the existing systems to automatically retrieve data. Given the data heterogeneity and the large number of source systems, the automation of connectors creation is required. In this context, we propose a methodology that optimizes the use of existing alignment approaches in the data integration processes. The generated mappings are formalized in exploitable mapping expressions. Following this methodology, a process has been experimented on specific data types of a source system: Boolean and predefined lists. As a result, effectiveness of the used alignment approach has been enhanced and more good mappings have been detected. Nonetheless, further improvements could be done to deal with the semantic issue and process other data types.
A biochemical logic gate using an enzyme and its inhibitor. Part II: The logic gate.
Sivan, Sarit; Tuchman, Samuel; Lotan, Noah
2003-06-01
Enzyme-Based Logic Gates (ENLOGs) are key components in bio-molecular systems for information processing. This report and the previous one in this series address the characterization of two bio-molecular switching elements, namely the alpha-chymotrypsin (alphaCT) derivative p-phenylazobenzoyl-alpha-chymotrypsin (PABalphaCT) and its inhibitor (proflavine), as well as their assembly into a logic gate. The experimental output of the proposed system is expressed in terms of enzymic activity and this was translated into logic output (i.e. "1" or "0") relative to a predetermined threshold value. We have found that an univalent link exists between the dominant isomers of PABalphaCT (cis or trans), the dominant form of either acridine (proflavine) or acridan and the logic output of the system. Thus, of all possible combinations, only the trans-PABalphaCT and the acridan lead to an enzymic activity that can be defined as logic output "1". The system operates under the rules of Boolean algebra and performs as an "AND" logic gate.
Logic regression and its extensions.
Schwender, Holger; Ruczinski, Ingo
2010-01-01
Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.
Towards data integration automation for the French rare disease registry
Maaroufi, Meriem; Choquet, Rémy; Landais, Paul; Jaulent, Marie-Christine
2015-01-01
Building a medical registry upon an existing infrastructure and rooted practices is not an easy task. It is the case for the BNDMR project, the French rare disease registry, that aims to collect administrative and medical data of rare disease patients seen in different hospitals. To avoid duplicating data entry for health professionals, the project plans to deploy connectors with the existing systems to automatically retrieve data. Given the data heterogeneity and the large number of source systems, the automation of connectors creation is required. In this context, we propose a methodology that optimizes the use of existing alignment approaches in the data integration processes. The generated mappings are formalized in exploitable mapping expressions. Following this methodology, a process has been experimented on specific data types of a source system: Boolean and predefined lists. As a result, effectiveness of the used alignment approach has been enhanced and more good mappings have been detected. Nonetheless, further improvements could be done to deal with the semantic issue and process other data types. PMID:26958224
Symmetry preserving truncations of the gap and Bethe-Salpeter equations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Binosi, Daniele; Chang, Lei; Papavassiliou, Joannis
2016-05-01
Ward-Green-Takahashi (WGT) identities play a crucial role in hadron physics, e.g. imposing stringent relationships between the kernels of the one-and two-body problems, which must be preserved in any veracious treatment of mesons as bound states. In this connection, one may view the dressed gluon-quark vertex, Gamma(alpha)(mu), as fundamental. We use a novel representation of Gamma(alpha)(mu), in terms of the gluon-quark scattering matrix, to develop a method capable of elucidating the unique quark-antiquark Bethe-Salpeter kernel, K, that is symmetry consistent with a given quark gap equation. A strength of the scheme is its ability to expose and capitalize on graphic symmetriesmore » within the kernels. This is displayed in an analysis that reveals the origin of H-diagrams in K, which are two-particle-irreducible contributions, generated as two-loop diagrams involving the three-gluon vertex, that cannot be absorbed as a dressing of Gamma(alpha)(mu) in a Bethe-Salpeter kernel nor expressed as a member of the class of crossed-box diagrams. Thus, there are no general circumstances under which the WGT identities essential for a valid description of mesons can be preserved by a Bethe-Salpeter kernel obtained simply by dressing both gluon-quark vertices in a ladderlike truncation; and, moreover, adding any number of similarly dressed crossed-box diagrams cannot improve the situation.« less
Jani, Saurin D; Argraves, Gary L; Barth, Jeremy L; Argraves, W Scott
2010-04-01
An important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases. Here we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH) hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc.) or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.). Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina. GeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment) to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies, intermolecular interactions, overlays of genes onto KEGG pathway diagrams and heatmaps of expression intensity values. GeneMesh is freely available online at http://proteogenomics.musc.edu/genemesh/.
Make Mine a Metasearcher, Please!
ERIC Educational Resources Information Center
Repman, Judi; Carlson, Randal D.
2000-01-01
Describes metasearch tools and explains their value in helping library media centers improve students' Web searches. Discusses Boolean queries and the emphasis on speed at the expense of comprehensiveness; and compares four metasearch tools, including the number of search engines consulted, user control, and databases included. (LRW)
Boolean Approaches in Digital Diagnosis
1989-12-04
Automation Conference, pages 64-70, 1983. 16. Barry W. Johnson. Design and A nalysis of Fault-Tolerant Digital Systems. Addison- Wesley Publishing...Mitchell. On a new algebra of logic. In C.S. Peirce, edhitor, Studies in Logic. Little, Brown. Boston. 1883. 2:3. Roger S. Pressman . Softwrare Engineering
Presentation of Repeated Phrases in a Computer-Assisted Abstracting Tool Kit.
ERIC Educational Resources Information Center
Craven, Timothy C.
2001-01-01
Discusses automatic indexing methods and describes the development of a prototype computerized abstractor's assistant. Highlights include the text network management system, TEXNET; phrase selection that follows indexing; phrase display, including Boolean capabilities; results of preliminary testing; and availability of TEXNET software. (LRW)
Stochastic Pseudo-Boolean Optimization
2011-07-31
Right-Hand Side,” 2009 IN- FORMS Annual Meeting, San Diego, CA, October 11-14, 2009. 113 References [1] A.-Ghouila-Houri. Caracterisation des matrices...Optimization, 10:7–21, 2005. [30] P. Camion. Caracterisation des matrices unimodulaires. Cahiers Centre Etudes Rech., 5(4), 1963. [31] P. Camion
Order or chaos in Boolean gene networks depends on the mean fraction of canalizing functions
NASA Astrophysics Data System (ADS)
Karlsson, Fredrik; Hörnquist, Michael
2007-10-01
We explore the connection between order/chaos in Boolean networks and the naturally occurring fraction of canalizing functions in such systems. This fraction turns out to give a very clear indication of whether the system possesses ordered or chaotic dynamics, as measured by Derrida plots, and also the degree of order when we compare different networks with the same number of vertices and edges. By studying also a wide distribution of indegrees in a network, we show that the mean probability of canalizing functions is a more reliable indicator of the type of dynamics for a finite network than the classical result on stability relating the bias to the mean indegree. Finally, we compare by direct simulations two biologically derived networks with networks of similar sizes but with power-law and Poisson distributions of indegrees, respectively. The biologically motivated networks are not more ordered than the latter, and in one case the biological network is even chaotic while the others are not.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beiu, V.; Makaruk, H.E.
1997-09-01
The starting points of this paper are two size-optimal solutions: (1) one for implementing arbitrary Boolean functions; and (2) another one for implementing certain subclasses of Boolean functions. Because VLSI implementations do not cope well with highly interconnected nets -- the area of a chip grows with the cube of the fan-in -- this paper will analyze the influence of limited fan-in on the size optimality for the two solutions mentioned. First, the authors will extend a result from Horne and Hush valid for fan-in {Delta} = 2 to arbitrary fan-in. Second, they will prove that size-optimal solutions are obtainedmore » for small constant fan-ins for both constructions, while relative minimum size solutions can be obtained for fan-ins strictly lower that linear. These results are in agreement with similar ones proving that for small constant fan-ins ({Delta} = 6...9) there exist VLSI-optimal (i.e., minimizing AT{sup 2}) solutions, while there are similar small constants relating to the capacity of processing information.« less
Realisation of all 16 Boolean logic functions in a single magnetoresistance memory cell.
Gao, Shuang; Yang, Guang; Cui, Bin; Wang, Shouguo; Zeng, Fei; Song, Cheng; Pan, Feng
2016-07-07
Stateful logic circuits based on next-generation nonvolatile memories, such as magnetoresistance random access memory (MRAM), promise to break the long-standing von Neumann bottleneck in state-of-the-art data processing devices. For the successful commercialisation of stateful logic circuits, a critical step is realizing the best use of a single memory cell to perform logic functions. In this work, we propose a method for implementing all 16 Boolean logic functions in a single MRAM cell, namely a magnetoresistance (MR) unit. Based on our experimental results, we conclude that this method is applicable to any MR unit with a double-hump-like hysteresis loop, especially pseudo-spin-valve magnetic tunnel junctions with a high MR ratio. Moreover, after simply reversing the correspondence between voltage signals and output logic values, this method could also be applicable to any MR unit with a double-pit-like hysteresis loop. These results may provide a helpful solution for the final commercialisation of MRAM-based stateful logic circuits in the near future.
Two classes of ODE models with switch-like behavior.
Just, Winfried; Korb, Mason; Elbert, Ben; Young, Todd
2013-12-01
In cases where the same real-world system can be modeled both by an ODE system ⅅ and a Boolean system , it is of interest to identify conditions under which the two systems will be consistent, that is, will make qualitatively equivalent predictions. In this note we introduce two broad classes of relatively simple models that provide a convenient framework for studying such questions. In contrast to the widely known class of Glass networks, the right-hand sides of our ODEs are Lipschitz-continuous. We prove that if has certain structures, consistency between ⅅ and is implied by sufficient separation of time scales in one class of our models. Namely, if the trajectories of are "one-stepping" then we prove a strong form of consistency and if has a certain monotonicity property then there is a weaker consistency between ⅅ and . These results appear to point to more general structure properties that favor consistency between ODE and Boolean models.
NASA Astrophysics Data System (ADS)
Szejka, Agnes; Drossel, Barbara
2010-02-01
We study the evolution of Boolean networks as model systems for gene regulation. Inspired by biological networks, we select simultaneously for robust attractors and for the ability to respond to external inputs by changing the attractor. Mutations change the connections between the nodes and the update functions. In order to investigate the influence of the type of update functions, we perform our simulations with canalizing as well as with threshold functions. We compare the properties of the fitness landscapes that result for different versions of the selection criterion and the update functions. We find that for all studied cases the fitness landscape has a plateau with maximum fitness resulting in the fact that structurally very different networks are able to fulfill the same task and are connected by neutral paths in network (“genotype”) space. We find furthermore a connection between the attractor length and the mutational robustness, and an extremely long memory of the initial evolutionary stage.
Comparison of Seven Methods for Boolean Factor Analysis and Their Evaluation by Information Gain.
Frolov, Alexander A; Húsek, Dušan; Polyakov, Pavel Yu
2016-03-01
An usual task in large data set analysis is searching for an appropriate data representation in a space of fewer dimensions. One of the most efficient methods to solve this task is factor analysis. In this paper, we compare seven methods for Boolean factor analysis (BFA) in solving the so-called bars problem (BP), which is a BFA benchmark. The performance of the methods is evaluated by means of information gain. Study of the results obtained in solving BP of different levels of complexity has allowed us to reveal strengths and weaknesses of these methods. It is shown that the Likelihood maximization Attractor Neural Network with Increasing Activity (LANNIA) is the most efficient BFA method in solving BP in many cases. Efficacy of the LANNIA method is also shown, when applied to the real data from the Kyoto Encyclopedia of Genes and Genomes database, which contains full genome sequencing for 1368 organisms, and to text data set R52 (from Reuters 21578) typically used for label categorization.
Stability and structural properties of gene regulation networks with coregulation rules.
Warrell, Jonathan; Mhlanga, Musa
2017-05-07
Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated expression of modules (and module groups) of functionally related genes across the genome. Coregulation can also arise through the physical association of multi-gene complexes through chromosomal looping, which are then transcribed together. We present a general formalism for modeling coregulation rules in the framework of Random Boolean Networks (RBN), and develop specific models for transcription factor networks with modular structure (including module groups, and multi-input modules (MIM) with autoregulation) and multi-gene complexes (including hierarchical differentiation between multi-gene complex members). We develop a mean-field approach to analyse the dynamical stability of large networks incorporating coregulation, and show that autoregulated MIM and hierarchical gene-complex models can achieve greater stability than networks without coregulation whose rules have matching activation frequency. We provide further analysis of the stability of small networks of both kinds through simulations. We also characterize several general properties of the transients and attractors in the hierarchical coregulation model, and show using simulations that the steady-state distribution factorizes hierarchically as a Bayesian network in a Markov Jump Process analogue of the RBN model. Copyright © 2017. Published by Elsevier Ltd.
Read, Mark; Andrews, Paul S; Timmis, Jon; Kumar, Vipin
2014-10-06
We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML's ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML's lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML's activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology.
Read, Mark; Andrews, Paul S.; Timmis, Jon; Kumar, Vipin
2014-01-01
We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML's ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML's lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML's activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology. PMID:25142524
Modeling Nuclear Receptor-Mediated Activity and Hepatotoxicity with Boolean Networks
Predicting the human health risk of chronic exposure to environmental contaminants remains an open problem. Chronic exposure to a wide array of chemicals – e.g., conazoles, perfluourinated chemicals and phthalates – has been associated with a range of hepatic lesions in rodents t...
Probabilistic Relational Structures and Their Applications
ERIC Educational Resources Information Center
Domotor, Zoltan
The principal objects of the investigation reported were, first, to study qualitative probability relations on Boolean algebras, and secondly, to describe applications in the theories of probability logic, information, automata, and probabilistic measurement. The main contribution of this work is stated in 10 definitions and 20 theorems. The basic…
Massive Query Resolution for Rapid Selective Dissemination of Information.
ERIC Educational Resources Information Center
Cohen, Jonathan D.
1999-01-01
Outlines an efficient approach to performing query resolution which, when matched with a keyword scanner, offers rapid selecting and routing for massive Boolean queries, and which is suitable for implementation on a desktop computer. Demonstrates the system's operation with large examples in a practical setting. (AEF)
Computer Solution of the Two-Dimensional Tether Ball: Problem to Illustrate Newton's Second Law.
ERIC Educational Resources Information Center
Zimmerman, W. Bruce
Force diagrams involving angular velocity, linear velocity, centripetal force, work, and kinetic energy are given with related equations of motion expressed in polar coordinates. The computer is used to solve differential equations, thus reducing the mathematical requirements of the students. An experiment is conducted using an air table to check…
Visualization of Dietary Patterns and Their Associations With Age-Related Macular Degeneration.
Chiu, Chung-Jung; Chang, Min-Lee; Li, Tricia; Gensler, Gary; Taylor, Allen
2017-03-01
We aimed to visualize the relationship of predominant dietary patterns and their associations with AMD. A total of 8103 eyes from 4088 participants in the baseline Age-Related Eye Disease Study (AREDS) were classified into three groups: control (n = 2739), early AMD (n = 4599), and advanced AMD (n = 765). Using principle component analysis, two major dietary patterns and eight minor dietary patterns were characterized. Applying logistic regression in our analysis, we related dietary patterns to the prevalence of AMD. Qualitative comparative analysis by operating Boolean algebra and drawing Venn diagrams was used to visualize our findings. In general, the eight minor patterns were subsets or extensions of either one of the two major dietary patterns (Oriental and Western patterns) and consisted of fewer characteristic foods than the two major dietary patterns. Unlike the two major patterns, which were more strongly associated with both early and advanced AMD, none of the eight minors were associated with early AMD and only four minor patterns, including the Steak pattern (odds ratio comparing the highest to lowest quintile of the pattern score = 1.73 [95% confidence interval: 1.24 to 2.41; Ptrend = 0.02]), the Breakfast pattern (0.60 [0.44 to 0.82]; Ptrend = 0.004]), the Caribbean pattern (0.64 [0.47 to 0.89; Ptrend = 0.009]), and the Peanut pattern (0.64 [0.46 to 0.89; Ptrend = 0.03]), were significantly associated with advanced AMD. Our data also suggested several potential beneficial (peanuts, pizza, coffee, and tea) and harmful (salad dressing) foods for AMD. Our data indicate that a diet of various healthy foods may be optimal for reducing AMD risk. The effects of some specific foods in the context of overall diet warrant further study.
Breast cancer research output, 1945-2008: a bibliometric and density-equalizing analysis.
Glynn, Ronan W; Scutaru, Cristian; Kerin, Michael J; Sweeney, Karl J
2010-01-01
Breast cancer is the most common form of cancer among women, with an estimated 194,280 new cases diagnosed in the United States in 2009 alone. The primary aim of this work was to provide an in-depth evaluation of research yield in breast cancer from 1945 to 2008, using large-scale data analysis, the employment of bibliometric indicators of production and quality, and density-equalizing mapping. Data were retrieved from the Web of Science (WOS) Science Citation Expanded database; this was searched using the Boolean operator, 'OR', with different terms related to breast cancer, including "breast cancer", "mammary ductal carcinoma" and "breast tumour". Data were then extracted from each file, transferred to Excel charts and visualised as diagrams. Mapping was performed as described by Groneberg-Kloft et al. in 2008. A total of 180,126 breast cancer-associated items were produced over the study period; these had been cited 4,136,224 times. The United States returned the greatest level of output (n = 77,101), followed by the UK (n = 18,357) and Germany (n = 12,529). International cooperation peaked in 2008, with 3,127 entries produced as a result; relationships between the United States and other countries formed the basis for the 10 most common forms of bilateral cooperation. Publications from nations with high levels of international cooperation were associated with greater average citation rates. A total of 4,096 journals published at least one item on breast cancer, although the top 50 most prolific titles together accounted for over 43% (77,517/180,126) of the total output. Breast cancer-associated research output continues to increase annually. In an era when bibliometric indicators are increasingly being employed in performance assessment, these findings should provide useful information for those tasked with improving that performance.
Dataflow Computation for the J-Machine
1990-06-01
MOVE 8. 1 CALL ClrTVCTO1 ;((:LkBEL (:LITERAL (:SYIBOL : BBD -IF-4)))) ZIDIF.4: ROVE [1,133, 3.3 ROV 13. A2 ((:TERIXATM)) SUSPEND ;((:LAEL (:LITBUAL...deftostant syn 0) (detconstant int-tag ’int) (detconatant Int 1) (detconstant id-tag ’ td ) (defconstant td 9) (Aotconstaut boolean-tag lbool
Exploiting the Maximum Entropy Principle to Increase Retrieval Effectiveness.
ERIC Educational Resources Information Center
Cooper, William S.
1983-01-01
Presents information retrieval design approach in which queries of computer-based system consist of sets of terms, either unweighted or weighted with subjective term precision estimates, and retrieval outputs ranked by probability of usefulness estimated by "maximum entropy principle." Boolean and weighted request systems are discussed.…
"Back-Stage" Dissent: Student Twitter Use Addressing Instructor Ideology
ERIC Educational Resources Information Center
Linvill, Darren L.; Boatwright, Brandon C.; Grant, Will J.
2018-01-01
In this content analysis, we explored how students address instructor ideology in the university classroom through the social media platform Twitter. We employed Boolean search operators through Salesforce Marketing Cloud Radian6 software to gather tweets and identified English language tweets by how students referenced their instructor's…
Topology of Document Retrieval Systems.
ERIC Educational Resources Information Center
Everett, Daniel M.; Cater, Steven C.
1992-01-01
Explains the use of a topological structure to examine the closeness between documents in retrieval systems and analyzes the topological structure of a vector-space model, a fuzzy-set model, an extended Boolean model, a probabilistic model, and a TIRS (Topological Information Retrieval System) model. Proofs for the results are appended. (17…
ERIC Educational Resources Information Center
Kolata, Gina
1985-01-01
To determine how hard it is for computers to solve problems, researchers have classified groups of problems (polynomial hierarchy) according to how much time they seem to require for their solutions. A difficult and complex proof is offered which shows that a combinatorial approach (using Boolean circuits) may resolve the problem. (JN)
The Impact of Text Browsing on Text Retrieval Performance.
ERIC Educational Resources Information Center
Bodner, Richard C.; Chignell, Mark H.; Charoenkitkarn, Nipon; Golovchinsky, Gene; Kopak, Richard W.
2001-01-01
Compares empirical results from three experiments using Text Retrieval Conference (TREC) data and search topics that involved three different user interfaces. Results show that marking Boolean queries on text, which encourages browsing, and hypertext interfaces to text retrieval systems can benefit recall and can also benefit novice users.…
LISA's Move from SilverPlatter to Bowker--Looking at the Interface.
ERIC Educational Resources Information Center
Stein, Jonathan
1994-01-01
Compares LISA (Library and Information Science Abstracts) on SilverPlatter's CD-ROM with its replacement version, Bowker-Saur's LISA Plus. Features reviewed include entry to the databases; use of Boolean search facilities; indexes and browsing; displaying and printing records; subsidiary functions; on-screen help; and interfaces. (Contains eight…
Library Dream Machines: Helping Students Master Super Online Catalogs.
ERIC Educational Resources Information Center
Webb, T. D.
1992-01-01
Describes how automation has transformed the library and how super-catalogs have affected the process of doing research. Explains how faculty and librarians can work together to help students to use the available databases effectively, by teaching them Boolean logic, standard record formats, filing rules, etc. (DMM)
Fundamentals of Digital Logic.
ERIC Educational Resources Information Center
Noell, Monica L.
This course is designed to prepare electronics personnel for further training in digital techniques, presenting need to know information that is basic to any maintenance course on digital equipment. It consists of seven study units: (1) binary arithmetic; (2) boolean algebra; (3) logic gates; (4) logic flip-flops; (5) nonlogic circuits; (6)…
ERIC Educational Resources Information Center
Miller-Whitehead, Marie
Keyword and text string searches of online library catalogs often provide different results according to library and database used and depending upon how books and journals are indexed. For this reason, online databases such as ERIC often provide tutorials and recommendations for searching their site, such as how to use Boolean search strategies.…
A Hypermedia Computer-Aided Parasitology Tutoring System.
ERIC Educational Resources Information Center
Theodoropoulos, Georgios; Loumos, Vassili
A hypermedia tutoring system for teaching parasitology to college students was developed using an object oriented software development tool, Knowledge Pro. The program was designed to meet four objectives: knowledge incorporation, tutoring, indexing of key words for Boolean search, and random generation of quiz questions with instant scoring. The…
Community Information Centers and the Computer.
ERIC Educational Resources Information Center
Carroll, John M.; Tague, Jean M.
Two computer data bases have been developed by the Computer Science Department at the University of Western Ontario for "Information London," the local community information center. One system, called LONDON, permits Boolean searches of a file of 5,000 records describing human service agencies in the London area. The second system,…
Cryptographic Properties of the Hidden Weighted Bit Function
2013-12-23
valid OMB control number. 1. REPORT DATE 23 DEC 2013 2. REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4. TITLE AND SUBTITLE...K. Feng, An Infinite Class of Balanced Vectorial Boolean Functions with Optimum Algebraic Immunity and Good Nonlinearity, in: IWCC 2009, In: LNCS
Assessing Institutional Ineffectiveness: A Strategy for Improvement.
ERIC Educational Resources Information Center
Cameron, Kim S.
1984-01-01
Based on the theory that institutional change and improvement are motivated more by knowledge of problems than by knowledge of successes, a fault tree analysis technique using Boolean logic for assessing institutional ineffectiveness by determining weaknesses in the system is presented. Advantages and disadvantages of focusing on weakness rather…
Subject Retrieval from Full-Text Databases in the Humanities
ERIC Educational Resources Information Center
East, John W.
2007-01-01
This paper examines the problems involved in subject retrieval from full-text databases of secondary materials in the humanities. Ten such databases were studied and their search functionality evaluated, focusing on factors such as Boolean operators, document surrogates, limiting by subject area, proximity operators, phrase searching, wildcards,…
Kolmogorov proof of the Clauser, Horne, Shimony and Holt inequalities
NASA Astrophysics Data System (ADS)
Revzen, M.
Boolean logic is used to prove the CHSH inequalities. The proof elucidates the connection between Einstein elements of reality and quantum non-locality. The violation of the CHSH inequality by quantum theory is discussed and the two-stage view of quantum measurement relevance to incompatible observables is outlined.
State-transition diagrams for biologists.
Bersini, Hugues; Klatzmann, David; Six, Adrien; Thomas-Vaslin, Véronique
2012-01-01
It is clearly in the tradition of biologists to conceptualize the dynamical evolution of biological systems in terms of state-transitions of biological objects. This paper is mainly concerned with (but obviously not limited too) the immunological branch of biology and shows how the adoption of UML (Unified Modeling Language) state-transition diagrams can ease the modeling, the understanding, the coding, the manipulation or the documentation of population-based immune software model generally defined as a set of ordinary differential equations (ODE), describing the evolution in time of populations of various biological objects. Moreover, that same UML adoption naturally entails a far from negligible representational economy since one graphical item of the diagram might have to be repeated in various places of the mathematical model. First, the main graphical elements of the UML state-transition diagram and how they can be mapped onto a corresponding ODE mathematical model are presented. Then, two already published immune models of thymocyte behavior and time evolution in the thymus, the first one originally conceived as an ODE population-based model whereas the second one as an agent-based one, are refactored and expressed in a state-transition form so as to make them much easier to understand and their respective code easier to access, to modify and run. As an illustrative proof, for any immunologist, it should be possible to understand faithfully enough what the two software models are supposed to reproduce and how they execute with no need to plunge into the Java or Fortran lines.
State-Transition Diagrams for Biologists
Bersini, Hugues; Klatzmann, David; Six, Adrien; Thomas-Vaslin, Véronique
2012-01-01
It is clearly in the tradition of biologists to conceptualize the dynamical evolution of biological systems in terms of state-transitions of biological objects. This paper is mainly concerned with (but obviously not limited too) the immunological branch of biology and shows how the adoption of UML (Unified Modeling Language) state-transition diagrams can ease the modeling, the understanding, the coding, the manipulation or the documentation of population-based immune software model generally defined as a set of ordinary differential equations (ODE), describing the evolution in time of populations of various biological objects. Moreover, that same UML adoption naturally entails a far from negligible representational economy since one graphical item of the diagram might have to be repeated in various places of the mathematical model. First, the main graphical elements of the UML state-transition diagram and how they can be mapped onto a corresponding ODE mathematical model are presented. Then, two already published immune models of thymocyte behavior and time evolution in the thymus, the first one originally conceived as an ODE population-based model whereas the second one as an agent-based one, are refactored and expressed in a state-transition form so as to make them much easier to understand and their respective code easier to access, to modify and run. As an illustrative proof, for any immunologist, it should be possible to understand faithfully enough what the two software models are supposed to reproduce and how they execute with no need to plunge into the Java or Fortran lines. PMID:22844438
Example of a Bayes network of relations among visual features
NASA Astrophysics Data System (ADS)
Agosta, John M.
1991-10-01
Bayes probability networks, also termed `influence diagrams,' promise to be a versatile, rigorous, and expressive uncertainty reasoning tool. This paper presents an example of how a Bayes network can express constraints among visual hypotheses. An example is presented of a model composed of cylindric primitives, inferred from a line drawing of a plumbing fixture. Conflict between interpretations of candidate cylinders is expressed by two parameters, one for the presence and one for the absence of visual evidence of their intersection. It is shown how `partial exclusion' relations are so generated and how they determine the degree of competition among the set of hypotheses. Solving this network obtains the assemblies of cylinders most likely to form an object.
Bilsland, Alan E.; Stevenson, Katrina; Liu, Yu; Hoare, Stacey; Cairney, Claire J.; Roffey, Jon; Keith, W. Nicol
2014-01-01
Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability. PMID:24550717
Narsai, Reena; Devenish, James; Castleden, Ian; Narsai, Kabir; Xu, Lin; Shou, Huixia; Whelan, James
2013-01-01
Omics research in Oryza sativa (rice) relies on the use of multiple databases to obtain different types of information to define gene function. We present Rice DB, an Oryza information portal that is a functional genomics database, linking gene loci to comprehensive annotations, expression data and the subcellular location of encoded proteins. Rice DB has been designed to integrate the direct comparison of rice with Arabidopsis (Arabidopsis thaliana), based on orthology or ‘expressology’, thus using and combining available information from two pre-eminent plant models. To establish Rice DB, gene identifiers (more than 40 types) and annotations from a variety of sources were compiled, functional information based on large-scale and individual studies was manually collated, hundreds of microarrays were analysed to generate expression annotations, and the occurrences of potential functional regulatory motifs in promoter regions were calculated. A range of computational subcellular localization predictions were also run for all putative proteins encoded in the rice genome, and experimentally confirmed protein localizations have been collated, curated and linked to functional studies in rice. A single search box allows anything from gene identifiers (for rice and/or Arabidopsis), motif sequences, subcellular location, to keyword searches to be entered, with the capability of Boolean searches (such as AND/OR). To demonstrate the utility of Rice DB, several examples are presented including a rice mitochondrial proteome, which draws on a variety of sources for subcellular location data within Rice DB. Comparisons of subcellular location, functional annotations, as well as transcript expression in parallel with Arabidopsis reveals examples of conservation between rice and Arabidopsis, using Rice DB (http://ricedb.plantenergy.uwa.edu.au). PMID:24147765
Narsai, Reena; Devenish, James; Castleden, Ian; Narsai, Kabir; Xu, Lin; Shou, Huixia; Whelan, James
2013-12-01
Omics research in Oryza sativa (rice) relies on the use of multiple databases to obtain different types of information to define gene function. We present Rice DB, an Oryza information portal that is a functional genomics database, linking gene loci to comprehensive annotations, expression data and the subcellular location of encoded proteins. Rice DB has been designed to integrate the direct comparison of rice with Arabidopsis (Arabidopsis thaliana), based on orthology or 'expressology', thus using and combining available information from two pre-eminent plant models. To establish Rice DB, gene identifiers (more than 40 types) and annotations from a variety of sources were compiled, functional information based on large-scale and individual studies was manually collated, hundreds of microarrays were analysed to generate expression annotations, and the occurrences of potential functional regulatory motifs in promoter regions were calculated. A range of computational subcellular localization predictions were also run for all putative proteins encoded in the rice genome, and experimentally confirmed protein localizations have been collated, curated and linked to functional studies in rice. A single search box allows anything from gene identifiers (for rice and/or Arabidopsis), motif sequences, subcellular location, to keyword searches to be entered, with the capability of Boolean searches (such as AND/OR). To demonstrate the utility of Rice DB, several examples are presented including a rice mitochondrial proteome, which draws on a variety of sources for subcellular location data within Rice DB. Comparisons of subcellular location, functional annotations, as well as transcript expression in parallel with Arabidopsis reveals examples of conservation between rice and Arabidopsis, using Rice DB (http://ricedb.plantenergy.uwa.edu.au). © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.
Erdoğdu, Utku; Tan, Mehmet; Alhajj, Reda; Polat, Faruk; Rokne, Jon; Demetrick, Douglas
2013-01-01
The availability of enough samples for effective analysis and knowledge discovery has been a challenge in the research community, especially in the area of gene expression data analysis. Thus, the approaches being developed for data analysis have mostly suffered from the lack of enough data to train and test the constructed models. We argue that the process of sample generation could be successfully automated by employing some sophisticated machine learning techniques. An automated sample generation framework could successfully complement the actual sample generation from real cases. This argument is validated in this paper by describing a framework that integrates multiple models (perspectives) for sample generation. We illustrate its applicability for producing new gene expression data samples, a highly demanding area that has not received attention. The three perspectives employed in the process are based on models that are not closely related. The independence eliminates the bias of having the produced approach covering only certain characteristics of the domain and leading to samples skewed towards one direction. The first model is based on the Probabilistic Boolean Network (PBN) representation of the gene regulatory network underlying the given gene expression data. The second model integrates Hierarchical Markov Model (HIMM) and the third model employs a genetic algorithm in the process. Each model learns as much as possible characteristics of the domain being analysed and tries to incorporate the learned characteristics in generating new samples. In other words, the models base their analysis on domain knowledge implicitly present in the data itself. The developed framework has been extensively tested by checking how the new samples complement the original samples. The produced results are very promising in showing the effectiveness, usefulness and applicability of the proposed multi-model framework.
Manickam, Cordelia; Nwanze, Chiadika; Ram, Daniel R; Shah, Spandan V; Smith, Scott; Jones, Rhianna; Hueber, Brady; Kroll, Kyle; Varner, Valerie; Goepfert, Paul; Jost, Stephanie; Reeves, R Keith
2018-05-03
Recently, a seemingly novel innate immune cell subset bearing features of natural killer and B cells was identified in mice. So-called NKB cells appear as first responders to infections, but whether this cell population is truly novel or is in fact a subpopulation of B cells and exists in higher primates remains unclear. The objective of this study was to identify NKB cells in primates and study the impact of HIV/SIV infections. NKB cells were quantified in both naïve and lentivirus infected rhesus macaques and humans by excluding lineage markers (CD3, CD127), and positive Boolean gating for CD20, NKG2A/C and/or NKp46. Additional phenotypic measures were conducted by RNA-probe and traditional flow cytometry. Circulating cytotoxic NKB cells were found at similar frequencies in humans and rhesus macaques (range, 0.01-0.2% of total lymphocytes). NKB cells were notably enriched in spleen (median, 0.4% of lymphocytes), but were otherwise systemically distributed in tonsil, lymph nodes, colon, and jejunum. Expression of immunoglobulins was highly variable, but heavily favoured IgM and IgA rather than IgG. Interestingly, NKB cell frequencies expanded in PBMC and colon during SIV infection, as did IgG expression, but were generally unaltered in HIV-infected humans. These results suggest a cell type expressing both natural killer and B-cell features exists in rhesus macaques and humans and are perturbed by HIV/SIV infection. The full functional niche remains unknown, but the unique phenotype and systemic distribution could make NKB cells unique targets for immunotherapeutics or vaccine strategies.
Osman, S M; Grosdidier, B; Ali, I; Abdellah, A Ben
2013-06-01
Quite recently, we reported a semianalytical equation of state (EOS) for the Ga-Pb alloy [Phys. Rev. B 78, 024205 (2008)], which was based on the first-order perturbation theory of fluid mixtures, within the simplified random phase approximation, in conjunction with the Grosdidier et al. model pair potentials for Ga-Ga and Pb-Pb with a suitable nonadditive pair potential between Ga-Pb unlike pairs. In the present work, we employ the present EOS to calculate the Ga-Pb phase diagram along the immiscibility gap region. The accuracy of the EOS is tested by consulting the empirical binodal curve. A statistical-mechanical-based theory for the surface tension is employed to obtain an analytical expression for the alloy surface tension. We calculated the surface tension along the bimodal curve and at extreme conditions of temperatures and pressures. The surface tension exhibits reasonably well the prewetting transition of Pb atoms at the surface of the Ga-rich liquid alloy and could qualitatively explain the prewetting phenomena occurring in the Ga-rich side of the phase diagram. The predicted prewetting line and wetting temperature qualitatively agree with the empirical measurements.
Modeling transcriptional networks regulating secondary growth and wood formation in forest trees
Lijun Liu; Vladimir Filkov; Andrew Groover
2013-01-01
The complex interactions among the genes that underlie a biological process can be modeled and presented as a transcriptional network, in which genes (nodes) and their interactions (edges) are shown in a graphical form similar to a wiring diagram. A large number of genes have been identified that are expressed during the radial woody growth of tree stems (secondary...
A Model of Object-Identities and Values
1990-02-23
integrity constraints in its construct, which provides the natural integration of the logical database model and the object-oriented database model. 20...portions are integrated by a simple commutative diagram of modeling functions. The formalism includes the expression of integrity constraints in its ...38 .5.2.2 The (Concept Model and Its Semantics .. .. .. .. ... .... ... .. 40 5.2.3 Two K%.inds of Predicates
Zhang, Jingshan; Maslov, Sergei; Shakhnovich, Eugene I
2008-01-01
Crowded intracellular environments present a challenge for proteins to form functional specific complexes while reducing non-functional interactions with promiscuous non-functional partners. Here we show how the need to minimize the waste of resources to non-functional interactions limits the proteome diversity and the average concentration of co-expressed and co-localized proteins. Using the results of high-throughput Yeast 2-Hybrid experiments, we estimate the characteristic strength of non-functional protein–protein interactions. By combining these data with the strengths of specific interactions, we assess the fraction of time proteins spend tied up in non-functional interactions as a function of their overall concentration. This allows us to sketch the phase diagram for baker's yeast cells using the experimentally measured concentrations and subcellular localization of their proteins. The positions of yeast compartments on the phase diagram are consistent with our hypothesis that the yeast proteome has evolved to operate closely to the upper limit of its size, whereas keeping individual protein concentrations sufficiently low to reduce non-functional interactions. These findings have implication for conceptual understanding of intracellular compartmentalization, multicellularity and differentiation. PMID:18682700
Exploratory study on the effect of discount pricing strategies for new product introduction
NASA Astrophysics Data System (ADS)
Mat Zaib, Nurul Afiqah; Bazin, Nor Erne Nazira; Mustaffa, Noorfa Haszlinna
2013-04-01
Rapid introduction of new product into the market has resulted in growing competition between retailers. Nowadays, retailers compete with one another in order to increase revenue and to maintain their position in the marketplace. This situation has forced the retailers to enhance their strategic management as well as creating competitive advantages. Generally, this situation can be observed in highly demanded product such as fashion goods and high technology electronic devices (smart phone, notebook). The consequence from the intense competition and new product introduction is difficulties in retailers pricing management. Retailers are now facing with complexity in making decisions on suitable pricing strategies and discount level for new product in association with the product life cycle. Thus, this research aims to investigate the suitable discount pricing strategies that can be integrated in every phase of product life cycle. This paper presents relationships between the discount pricing and the stages in the product life cycle in the form of conceptual diagram and mathematical expression. A system dynamic approach is used for developing the conceptual diagram and formulating the mathematical expression for the discount pricing strategies to visualize the relationship between discount pricing and product life cycle.
An algebra-based method for inferring gene regulatory networks.
Vera-Licona, Paola; Jarrah, Abdul; Garcia-Puente, Luis David; McGee, John; Laubenbacher, Reinhard
2014-03-26
The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the dynamic patterns present in the network. Boolean polynomial dynamical systems provide a powerful modeling framework for the reverse engineering of gene regulatory networks, that enables a rich mathematical structure on the model search space. A C++ implementation of the method, distributed under LPGL license, is available, together with the source code, at http://www.paola-vera-licona.net/Software/EARevEng/REACT.html.
Introducing Online Bibliographic Service to its Users: The Online Presentation
ERIC Educational Resources Information Center
Crane, Nancy B.; Pilachowski, David M.
1978-01-01
A description of techniques for introducing online services to new user groups includes discussion of terms and their definitions, evolution of online searching, advantages and disadvantages of online searching, production of the data bases, search strategies, Boolean logic, costs and charges, "do's and don'ts," and a user search questionnaire. (J…
A Study of Search Intermediary Working Notes: Implications for IR System Design.
ERIC Educational Resources Information Center
Spink, Amanda; Goodrum, Abby
1996-01-01
Reports findings from an exploratory study investigating working notes created during encoding and external storage (EES) processes by human search intermediaries (librarians at the University of North Texas) using a Boolean information retrieval (IR) system. Implications for the design of IR interfaces and further research is discussed.…
Recognition vs Reverse Engineering in Boolean Concepts Learning
ERIC Educational Resources Information Center
Shafat, Gabriel; Levin, Ilya
2012-01-01
This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…
Target-Based Maintenance of Privacy Preserving Association Rules
ERIC Educational Resources Information Center
Ahluwalia, Madhu V.
2011-01-01
In the context of association rule mining, the state-of-the-art in privacy preserving data mining provides solutions for categorical and Boolean association rules but not for quantitative association rules. This research fills this gap by describing a method based on discrete wavelet transform (DWT) to protect input data privacy while preserving…
Information Resources Usage in Project Management Digital Learning System
ERIC Educational Resources Information Center
Davidovitch, Nitza; Belichenko, Margarita; Kravchenko, Yurii
2017-01-01
The article combines a theoretical approach to structuring knowledge that is based on the integrated use of fuzzy semantic network theory predicates, Boolean functions, theory of complexity of network structures and some practical aspects to be considered in the distance learning at the university. The paper proposes a methodological approach that…
Algebraic grid adaptation method using non-uniform rational B-spline surface modeling
NASA Technical Reports Server (NTRS)
Yang, Jiann-Cherng; Soni, B. K.
1992-01-01
An algebraic adaptive grid system based on equidistribution law and utilized by the Non-Uniform Rational B-Spline (NURBS) surface for redistribution is presented. A weight function, utilizing a properly weighted boolean sum of various flow field characteristics is developed. Computational examples are presented to demonstrate the success of this technique.
A Characterization of Banach Spaces Containing l1
Rosenthal, Haskell P.
1974-01-01
It is proved that a Banach space contains a subspace isomorphic to l1 if (and only if) it has a bounded sequence with no weak-Cauchy subsequence. The proof yields that a sequence of subsets of a given set has a subsequence that is either convergent or Boolean independent. PMID:16592162
Deriving Laws from Ordering Relations
NASA Technical Reports Server (NTRS)
Knuth, Kevin H.
2004-01-01
The effect of Richard T. Cox's contribution to probability theory was to generalize Boolean implication among logical statements to degrees of implication, which are manipulated using rules derived from consistency with Boolean algebra. These rules are known as the sum rule, the product rule and Bayes Theorem, and the measure resulting from this generalization is probability. In this paper, I will describe how Cox s technique can be further generalized to include other algebras and hence other problems in science and mathematics. The result is a methodology that can be used to generalize an algebra to a calculus by relying on consistency with order theory to derive the laws of the calculus. My goals are to clear up the mysteries as to why the same basic structure found in probability theory appears in other contexts, to better understand the foundations of probability theory, and to extend these ideas to other areas by developing new mathematics and new physics. The relevance of this methodology will be demonstrated using examples from probability theory, number theory, geometry, information theory, and quantum mechanics.
Networks and games for precision medicine.
Biane, Célia; Delaplace, Franck; Klaudel, Hanna
2016-12-01
Recent advances in omics technologies provide the leverage for the emergence of precision medicine that aims at personalizing therapy to patient. In this undertaking, computational methods play a central role for assisting physicians in their clinical decision-making by combining data analysis and systems biology modelling. Complex diseases such as cancer or diabetes arise from the intricate interplay of various biological molecules. Therefore, assessing drug efficiency requires to study the effects of elementary perturbations caused by diseases on relevant biological networks. In this paper, we propose a computational framework called Network-Action Game applied to best drug selection problem combining Game Theory and discrete models of dynamics (Boolean networks). Decision-making is modelled using Game Theory that defines the process of drug selection among alternative possibilities, while Boolean networks are used to model the effects of the interplay between disease and drugs actions on the patient's molecular system. The actions/strategies of disease and drugs are focused on arc alterations of the interactome. The efficiency of this framework has been evaluated for drug prediction on a model of breast cancer signalling. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
The logical primitives of thought: Empirical foundations for compositional cognitive models.
Piantadosi, Steven T; Tenenbaum, Joshua B; Goodman, Noah D
2016-07-01
The notion of a compositional language of thought (LOT) has been central in computational accounts of cognition from earliest attempts (Boole, 1854; Fodor, 1975) to the present day (Feldman, 2000; Penn, Holyoak, & Povinelli, 2008; Fodor, 2008; Kemp, 2012; Goodman, Tenenbaum, & Gerstenberg, 2015). Recent modeling work shows how statistical inferences over compositionally structured hypothesis spaces might explain learning and development across a variety of domains. However, the primitive components of such representations are typically assumed a priori by modelers and theoreticians rather than determined empirically. We show how different sets of LOT primitives, embedded in a psychologically realistic approximate Bayesian inference framework, systematically predict distinct learning curves in rule-based concept learning experiments. We use this feature of LOT models to design a set of large-scale concept learning experiments that can determine the most likely primitives for psychological concepts involving Boolean connectives and quantification. Subjects' inferences are most consistent with a rich (nonminimal) set of Boolean operations, including first-order, but not second-order, quantification. Our results more generally show how specific LOT theories can be distinguished empirically. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Deeper and sparser nets are optimal
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beiu, V.; Makaruk, H.E.
1998-03-01
The starting points of this paper are two size-optimal solutions: (1) one for implementing arbitrary Boolean functions (Home and Hush, 1994); and (2) another one for implementing certain sub-classes of Boolean functions (Red`kin, 1970). Because VLSI implementations do not cope well with highly interconnected nets--the area of a chip grows with the cube of the fan-in (Hammerstrom, 1988)--this paper will analyze the influence of limited fan-in on the size optimality for the two solutions mentioned. First, the authors will extend a result from Home and Hush (1994) valid for fan-in {Delta} = 2 to arbitrary fan-in. Second, they will provemore » that size-optimal solutions are obtained for small constant fan-in for both constructions, while relative minimum size solutions can be obtained for fan-ins strictly lower that linear. These results are in agreement with similar ones proving that for small constant fan-ins ({Delta} = 6...9) there exist VLSI-optimal (i.e., minimizing AT{sup 2}) solutions (Beiu, 1997a), while there are similar small constants relating to the capacity of processing information (Miller 1956).« less
Deeper sparsely nets are size-optimal
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beiu, V.; Makaruk, H.E.
1997-12-01
The starting points of this paper are two size-optimal solutions: (i) one for implementing arbitrary Boolean functions (Horne, 1994); and (ii) another one for implementing certain sub-classes of Boolean functions (Red`kin, 1970). Because VLSI implementations do not cope well with highly interconnected nets--the area of a chip grows with the cube of the fan-in (Hammerstrom, 1988)--this paper will analyze the influence of limited fan-in on the size optimality for the two solutions mentioned. First, the authors will extend a result from Horne and Hush (1994) valid for fan-in {Delta} = 2 to arbitrary fan-in. Second, they will prove that size-optimalmore » solutions are obtained for small constant fan-in for both constructions, while relative minimum size solutions can be obtained for fan-ins strictly lower than linear. These results are in agreement with similar ones proving that for small constant fan-ins ({Delta} = 6...9) there exist VLSI-optimal (i.e. minimizing AT{sup 2}) solutions (Beiu, 1997a), while there are similar small constants relating to the capacity of processing information (Miller 1956).« less
Stability Depends on Positive Autoregulation in Boolean Gene Regulatory Networks
Pinho, Ricardo; Garcia, Victor; Irimia, Manuel; Feldman, Marcus W.
2014-01-01
Network motifs have been identified as building blocks of regulatory networks, including gene regulatory networks (GRNs). The most basic motif, autoregulation, has been associated with bistability (when positive) and with homeostasis and robustness to noise (when negative), but its general importance in network behavior is poorly understood. Moreover, how specific autoregulatory motifs are selected during evolution and how this relates to robustness is largely unknown. Here, we used a class of GRN models, Boolean networks, to investigate the relationship between autoregulation and network stability and robustness under various conditions. We ran evolutionary simulation experiments for different models of selection, including mutation and recombination. Each generation simulated the development of a population of organisms modeled by GRNs. We found that stability and robustness positively correlate with autoregulation; in all investigated scenarios, stable networks had mostly positive autoregulation. Assuming biological networks correspond to stable networks, these results suggest that biological networks should often be dominated by positive autoregulatory loops. This seems to be the case for most studied eukaryotic transcription factor networks, including those in yeast, flies and mammals. PMID:25375153
Utilization of Large Scale Surface Models for Detailed Visibility Analyses
NASA Astrophysics Data System (ADS)
Caha, J.; Kačmařík, M.
2017-11-01
This article demonstrates utilization of large scale surface models with small spatial resolution and high accuracy, acquired from Unmanned Aerial Vehicle scanning, for visibility analyses. The importance of large scale data for visibility analyses on the local scale, where the detail of the surface model is the most defining factor, is described. The focus is not only the classic Boolean visibility, that is usually determined within GIS, but also on so called extended viewsheds that aims to provide more information about visibility. The case study with examples of visibility analyses was performed on river Opava, near the Ostrava city (Czech Republic). The multiple Boolean viewshed analysis and global horizon viewshed were calculated to determine most prominent features and visibility barriers of the surface. Besides that, the extended viewshed showing angle difference above the local horizon, which describes angular height of the target area above the barrier, is shown. The case study proved that large scale models are appropriate data source for visibility analyses on local level. The discussion summarizes possible future applications and further development directions of visibility analyses.
Laomettachit, Teeraphan; Chen, Katherine C; Baumann, William T; Tyson, John J
2016-01-01
To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a "standard component" modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with "standard components" can capture in quantitative detail many essential properties of cell cycle control in budding yeast.
Laomettachit, Teeraphan; Chen, Katherine C.; Baumann, William T.
2016-01-01
To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a “standard component” modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with “standard components” can capture in quantitative detail many essential properties of cell cycle control in budding yeast. PMID:27187804
Programmable bioelectronics in a stimuli-encoded 3D graphene interface
NASA Astrophysics Data System (ADS)
Parlak, Onur; Beyazit, Selim; Tse-Sum-Bui, Bernadette; Haupt, Karsten; Turner, Anthony P. F.; Tiwari, Ashutosh
2016-05-01
The ability to program and mimic the dynamic microenvironment of living organisms is a crucial step towards the engineering of advanced bioelectronics. Here, we report for the first time a design for programmable bioelectronics, with `built-in' switchable and tunable bio-catalytic performance that responds simultaneously to appropriate stimuli. The designed bio-electrodes comprise light and temperature responsive compartments, which allow the building of Boolean logic gates (i.e. ``OR'' and ``AND'') based on enzymatic communications to deliver logic operations.The ability to program and mimic the dynamic microenvironment of living organisms is a crucial step towards the engineering of advanced bioelectronics. Here, we report for the first time a design for programmable bioelectronics, with `built-in' switchable and tunable bio-catalytic performance that responds simultaneously to appropriate stimuli. The designed bio-electrodes comprise light and temperature responsive compartments, which allow the building of Boolean logic gates (i.e. ``OR'' and ``AND'') based on enzymatic communications to deliver logic operations. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr02355j
Counting and classifying attractors in high dimensional dynamical systems.
Bagley, R J; Glass, L
1996-12-07
Randomly connected Boolean networks have been used as mathematical models of neural, genetic, and immune systems. A key quantity of such networks is the number of basins of attraction in the state space. The number of basins of attraction changes as a function of the size of the network, its connectivity and its transition rules. In discrete networks, a simple count of the number of attractors does not reveal the combinatorial structure of the attractors. These points are illustrated in a reexamination of dynamics in a class of random Boolean networks considered previously by Kauffman. We also consider comparisons between dynamics in discrete networks and continuous analogues. A continuous analogue of a discrete network may have a different number of attractors for many different reasons. Some attractors in discrete networks may be associated with unstable dynamics, and several different attractors in a discrete network may be associated with a single attractor in the continuous case. Special problems in determining attractors in continuous systems arise when there is aperiodic dynamics associated with quasiperiodicity of deterministic chaos.
Similar environments but diverse fates: Responses of budding yeast to nutrient deprivation
Honigberg, Saul M.
2016-01-01
Diploid budding yeast (Saccharomyces cerevisiae) can adopt one of several alternative differentiation fates in response to nutrient limitation, and each of these fates provides distinct biological functions. When different strain backgrounds are taken into account, these various fates occur in response to similar environmental cues, are regulated by the same signal transduction pathways, and share many of the same master regulators. I propose that the relationships between fate choice, environmental cues and signaling pathways are not Boolean, but involve graded levels of signals, pathway activation and master-regulator activity. In the absence of large differences between environmental cues, small differences in the concentration of cues may be reinforced by cell-to-cell signals. These signals are particularly essential for fate determination within communities, such as colonies and biofilms, where fate choice varies dramatically from one region of the community to another. The lack of Boolean relationships between cues, signaling pathways, master regulators and cell fates may allow yeast communities to respond appropriately to the wide range of environments they encounter in nature. PMID:27917388
Two classes of ODE models with switch-like behavior
Just, Winfried; Korb, Mason; Elbert, Ben; Young, Todd
2013-01-01
In cases where the same real-world system can be modeled both by an ODE system ⅅ and a Boolean system 𝔹, it is of interest to identify conditions under which the two systems will be consistent, that is, will make qualitatively equivalent predictions. In this note we introduce two broad classes of relatively simple models that provide a convenient framework for studying such questions. In contrast to the widely known class of Glass networks, the right-hand sides of our ODEs are Lipschitz-continuous. We prove that if 𝔹 has certain structures, consistency between ⅅ and 𝔹 is implied by sufficient separation of time scales in one class of our models. Namely, if the trajectories of 𝔹 are “one-stepping” then we prove a strong form of consistency and if 𝔹 has a certain monotonicity property then there is a weaker consistency between ⅅ and 𝔹. These results appear to point to more general structure properties that favor consistency between ODE and Boolean models. PMID:24244061
Mood and anxiety disorders as early manifestations of medical illness: a systematic review.
Cosci, Fiammetta; Fava, Giovanni A; Sonino, Nicoletta
2015-01-01
Affective disturbances involving alterations of mood, anxiety and irritability may be early symptoms of medical illnesses. The aim of this paper was to provide a systematic review of the literature with qualitative data synthesis. MEDLINE, PsycINFO, EMBASE, Cochrane, and ISI Web of Science were systematically searched from inception to February 2014. Search terms were 'prodrome/early symptom', combined using the Boolean 'AND' operator with 'anxiety/depression/mania/hypomania/irritability/irritable mood/hostility', combined with the Boolean 'AND' operator with 'medical illness/medical disorder'. PRISMA guidelines were followed. A total of 21 studies met the inclusion criteria and were analyzed. Depression was found to be the most common affective prodrome of medical disorders and was consistently reported in Cushing's syndrome, hypothyroidism, hyperparathyroidism, pancreatic and lung cancer, myocardial infarction, Wilson's disease, and AIDS. Mania, anxiety and irritability were less frequent. Physicians may not pursue medical workup of cases that appear to be psychiatric in nature. They should be alerted that disturbances in mood, anxiety and irritability may antedate the appearance of a medical disorder.
Two Methods for Efficient Solution of the Hitting-Set Problem
NASA Technical Reports Server (NTRS)
Vatan, Farrokh; Fijany, Amir
2005-01-01
A paper addresses much of the same subject matter as that of Fast Algorithms for Model-Based Diagnosis (NPO-30582), which appears elsewhere in this issue of NASA Tech Briefs. However, in the paper, the emphasis is more on the hitting-set problem (also known as the transversal problem), which is well known among experts in combinatorics. The authors primary interest in the hitting-set problem lies in its connection to the diagnosis problem: it is a theorem of model-based diagnosis that in the set-theory representation of the components of a system, the minimal diagnoses of a system are the minimal hitting sets of the system. In the paper, the hitting-set problem (and, hence, the diagnosis problem) is translated from a combinatorial to a computational problem by mapping it onto the Boolean satisfiability and integer- programming problems. The paper goes on to describe developments nearly identical to those summarized in the cited companion NASA Tech Briefs article, including the utilization of Boolean-satisfiability and integer- programming techniques to reduce the computation time and/or memory needed to solve the hitting-set problem.
General method to find the attractors of discrete dynamic models of biological systems.
Gan, Xiao; Albert, Réka
2018-04-01
Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.
General method to find the attractors of discrete dynamic models of biological systems
NASA Astrophysics Data System (ADS)
Gan, Xiao; Albert, Réka
2018-04-01
Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.
Huang, Liqiang
2015-05-01
Basic visual features (e.g., color, orientation) are assumed to be processed in the same general way across different visual tasks. Here, a significant deviation from this assumption was predicted on the basis of the analysis of stimulus spatial structure, as characterized by the Boolean-map notion. If a task requires memorizing the orientations of a set of bars, then the map consisting of those bars can be readily used to hold the overall structure in memory and will thus be especially useful. If the task requires visual search for a target, then the map, which contains only an overall structure, will be of little use. Supporting these predictions, the present study demonstrated that in comparison to stimulus colors, bar orientations were processed more efficiently in change-detection tasks but less efficiently in visual search tasks (Cohen's d = 4.24). In addition to offering support for the role of the Boolean map in conscious access, the present work also throws doubts on the generality of processing visual features. © The Author(s) 2015.
Layered Systems Engineering Engines
NASA Technical Reports Server (NTRS)
Breidenthal, Julian C.; Overman, Marvin J.
2009-01-01
A notation is described for depicting the relationships between multiple, contemporaneous systems engineering efforts undertaken within a multi-layer system-of-systems hierarchy. We combined the concepts of remoteness of activity from the end customer, depiction of activity on a timeline, and data flow to create a new kind of diagram which we call a "Layered Vee Diagram." This notation is an advance over previous notations because it is able to be simultaneously precise about activity, level of granularity, product exchanges, and timing; these advances provide systems engineering managers a significantly improved ability to express and understand the relationships between many systems engineering efforts. Using the new notation, we obtain a key insight into the relationship between project duration and the strategy selected for chaining the systems engineering effort between layers, as well as insights into the costs, opportunities, and risks associated with alternate chaining strategies.
Narang, Sahil; Best, Andrew; Curtis, Sean; Manocha, Dinesh
2015-01-01
Pedestrian crowds often have been modeled as many-particle system including microscopic multi-agent simulators. One of the key challenges is to unearth governing principles that can model pedestrian movement, and use them to reproduce paths and behaviors that are frequently observed in human crowds. To that effect, we present a novel crowd simulation algorithm that generates pedestrian trajectories that exhibit the speed-density relationships expressed by the Fundamental Diagram. Our approach is based on biomechanical principles and psychological factors. The overall formulation results in better utilization of free space by the pedestrians and can be easily combined with well-known multi-agent simulation techniques with little computational overhead. We are able to generate human-like dense crowd behaviors in large indoor and outdoor environments and validate the results with captured real-world crowd trajectories. PMID:25875932
Intelligent machines in the twenty-first century: foundations of inference and inquiry.
Knuth, Kevin H
2003-12-15
The last century saw the application of Boolean algebra to the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines, in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. Recent advances in our understanding of the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we recently identified the algebra of questions as the free distributive algebra, which will now allow us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper, we examine the foundations of inference and inquiry. We begin with a history of inferential reasoning, highlighting key concepts that have led to the automation of inference in modern machine-learning systems. We then discuss the foundations of inference in more detail using a modern viewpoint that relies on the mathematics of partially ordered sets and the scaffolding of lattice theory. This new viewpoint allows us to develop the logic of inquiry and introduce a measure describing the relevance of a proposed question to an unresolved issue. Last, we will demonstrate the automation of inference, and discuss how this new logic of inquiry will enable intelligent machines to ask questions. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them not only to make inferences from data, but also to decide which question to ask, which experiment to perform, or which measurement to take given what they have learned and what they are designed to understand.
Sampson, Margaret; Barrowman, Nicholas J; Moher, David; Clifford, Tammy J; Platt, Robert W; Morrison, Andra; Klassen, Terry P; Zhang, Li
2006-02-24
Most electronic search efforts directed at identifying primary studies for inclusion in systematic reviews rely on the optimal Boolean search features of search interfaces such as DIALOG and Ovid. Our objective is to test the ability of an Ultraseek search engine to rank MEDLINE records of the included studies of Cochrane reviews within the top half of all the records retrieved by the Boolean MEDLINE search used by the reviewers. Collections were created using the MEDLINE bibliographic records of included and excluded studies listed in the review and all records retrieved by the MEDLINE search. Records were converted to individual HTML files. Collections of records were indexed and searched through a statistical search engine, Ultraseek, using review-specific search terms. Our data sources, systematic reviews published in the Cochrane library, were included if they reported using at least one phase of the Cochrane Highly Sensitive Search Strategy (HSSS), provided citations for both included and excluded studies and conducted a meta-analysis using a binary outcome measure. Reviews were selected if they yielded between 1000-6000 records when the MEDLINE search strategy was replicated. Nine Cochrane reviews were included. Included studies within the Cochrane reviews were found within the first 500 retrieved studies more often than would be expected by chance. Across all reviews, recall of included studies into the top 500 was 0.70. There was no statistically significant difference in ranking when comparing included studies with just the subset of excluded studies listed as excluded in the published review. The relevance ranking provided by the search engine was better than expected by chance and shows promise for the preliminary evaluation of large results from Boolean searches. A statistical search engine does not appear to be able to make fine discriminations concerning the relevance of bibliographic records that have been pre-screened by systematic reviewers.
Recurrent-neural-network-based Boolean factor analysis and its application to word clustering.
Frolov, Alexander A; Husek, Dusan; Polyakov, Pavel Yu
2009-07-01
The objective of this paper is to introduce a neural-network-based algorithm for word clustering as an extension of the neural-network-based Boolean factor analysis algorithm (Frolov , 2007). It is shown that this extended algorithm supports even the more complex model of signals that are supposed to be related to textual documents. It is hypothesized that every topic in textual data is characterized by a set of words which coherently appear in documents dedicated to a given topic. The appearance of each word in a document is coded by the activity of a particular neuron. In accordance with the Hebbian learning rule implemented in the network, sets of coherently appearing words (treated as factors) create tightly connected groups of neurons, hence, revealing them as attractors of the network dynamics. The found factors are eliminated from the network memory by the Hebbian unlearning rule facilitating the search of other factors. Topics related to the found sets of words can be identified based on the words' semantics. To make the method complete, a special technique based on a Bayesian procedure has been developed for the following purposes: first, to provide a complete description of factors in terms of component probability, and second, to enhance the accuracy of classification of signals to determine whether it contains the factor. Since it is assumed that every word may possibly contribute to several topics, the proposed method might be related to the method of fuzzy clustering. In this paper, we show that the results of Boolean factor analysis and fuzzy clustering are not contradictory, but complementary. To demonstrate the capabilities of this attempt, the method is applied to two types of textual data on neural networks in two different languages. The obtained topics and corresponding words are at a good level of agreement despite the fact that identical topics in Russian and English conferences contain different sets of keywords.
Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior
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
Intelligent machines in the twenty-first century: foundations of inference and inquiry
NASA Technical Reports Server (NTRS)
Knuth, Kevin H.
2003-01-01
The last century saw the application of Boolean algebra to the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines, in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. Recent advances in our understanding of the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we recently identified the algebra of questions as the free distributive algebra, which will now allow us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper, we examine the foundations of inference and inquiry. We begin with a history of inferential reasoning, highlighting key concepts that have led to the automation of inference in modern machine-learning systems. We then discuss the foundations of inference in more detail using a modern viewpoint that relies on the mathematics of partially ordered sets and the scaffolding of lattice theory. This new viewpoint allows us to develop the logic of inquiry and introduce a measure describing the relevance of a proposed question to an unresolved issue. Last, we will demonstrate the automation of inference, and discuss how this new logic of inquiry will enable intelligent machines to ask questions. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them not only to make inferences from data, but also to decide which question to ask, which experiment to perform, or which measurement to take given what they have learned and what they are designed to understand.
Shen, Jiayun; Shang, Qing; Wong, Chun-Kwok; Li, Edmund K; Wang, Shang; Li, Rui-Jie; Lee, Ka-Lai; Leung, Ying-Ying; Ying, King-Yee; Yim, Cheuk-Wan; Kun, Emily W; Leung, Moon-Ho; Li, Martin; Li, Tena K; Zhu, Tracy Y; Yu, Shui-Lian; Kuan, Woon-Pang; Yu, Cheuk-Man; Tam, Lai-Shan
2015-08-01
To study the association between the baseline IL-33 and soluble ST2 (sST2) levels with disease remission and progression of carotid atherosclerosis in early rheumatoid arthritis (ERA) patients. A total of 98 ERA patients were enrolled. Disease activity and the presence of carotid plaque were evaluated at baseline and 12 months later. Plasma IL-33 and sST2 levels were determined using enzyme-linked immunosorbent assay kits. Baseline IL-33 and sST2 levels were associated with inflammatory markers and cardiovascular (CV) risk factors. Overall, 44(45%), 18(18%), and 21(21%) patients achieved remission based on 28-joint disease activity score (DAS28), Boolean, and simplified disease activity score (SDAI) criteria at 12 months, respectively. Patients with detectable IL-33 at baseline were less likely to achieve DAS28 (P = 0.010) and SDAI remission (P = 0.021), while a lower baseline sST2 level was able to predict DAS28, Boolean, and SDAI remission (P = 0.005, 0.001, and <0.001, respectively). Using multivariate analysis, a lower baseline sST2 level independently predict Boolean (OR = 0.789; P = 0.005) and SDAI remission (0.812; P = 0.008). Regarding carotid atherosclerosis, 9/98(9.2%) patients had plaque progression at 12 months. Baseline IL-33 was detectable in 8/9(89%) and 42/83(51%) of patients with and without plaque progression respectively (P = 0.029). Baseline detectable IL-33 was an independent predictor for plaque progression after adjusting for traditional CV risk factors (P = 0.017). Lower baseline sST2 levels independently predict disease remission and baseline detectable IL-33 independently predicts carotid plaque progression in ERA patients. This study suggests that inflammation induced by the IL-33/ST2 axis may play a significant role in the development of cardiovascular disease in RA. Copyright © 2015 Elsevier Inc. All rights reserved.
[Identification of meridian-acupoint diagrams and meridian diagrams].
Shen, Wei-hong
2008-08-01
In acu-moxibustion literature, there are two kinds of diagrams, meridian-acupoint diagrams and meridian diagrams. Because they are very similar in outline, and people now have seldom seen the typical ancient meridian diagrams, meridian-acupoint diagrams have been being incorrectly considered to be the meridian diagrams for a long time. It results in confusion in acu-moxibustion academia. The present paper stresses its importance in academic research and introduces some methods for identifying them correctly. The key points for identification of meridian-acupoint diagrams and meridian diagrams are: the legend of diagrams and the drawing style of the ancient charts. In addition, the author makes a detailed explanation about some acu-moxibustion charts which are easily confused. In order to distinguish meridian-acupoint diagrams and meridian diagrams correctly, he or she shoulnd understand the diagrams' intrinsic information as much as possible and make a comprehensive analysis about them.
Alternative thermodynamic cycle for the Stirling machine
NASA Astrophysics Data System (ADS)
Romanelli, Alejandro
2017-12-01
We develop an alternative thermodynamic cycle for the Stirling machine, where the polytropic process plays a central role. Analytical expressions for pressure and temperatures of the working gas are obtained as a function of the volume and the parameter that characterizes the polytropic process. This approach achieves closer agreement with the experimental pressure-volume diagram and can be adapted to any type of Stirling engine.
Reliability analysis of the solar array based on Fault Tree Analysis
NASA Astrophysics Data System (ADS)
Jianing, Wu; Shaoze, Yan
2011-07-01
The solar array is an important device used in the spacecraft, which influences the quality of in-orbit operation of the spacecraft and even the launches. This paper analyzes the reliability of the mechanical system and certifies the most vital subsystem of the solar array. The fault tree analysis (FTA) model is established according to the operating process of the mechanical system based on DFH-3 satellite; the logical expression of the top event is obtained by Boolean algebra and the reliability of the solar array is calculated. The conclusion shows that the hinges are the most vital links between the solar arrays. By analyzing the structure importance(SI) of the hinge's FTA model, some fatal causes, including faults of the seal, insufficient torque of the locking spring, temperature in space, and friction force, can be identified. Damage is the initial stage of the fault, so limiting damage is significant to prevent faults. Furthermore, recommendations for improving reliability associated with damage limitation are discussed, which can be used for the redesigning of the solar array and the reliability growth planning.
Sánchez, Benjamín J; Pérez-Correa, José R; Agosin, Eduardo
2014-09-01
Dynamic flux balance analysis (dFBA) has been widely employed in metabolic engineering to predict the effect of genetic modifications and environmental conditions in the cell׳s metabolism during dynamic cultures. However, the importance of the model parameters used in these methodologies has not been properly addressed. Here, we present a novel and simple procedure to identify dFBA parameters that are relevant for model calibration. The procedure uses metaheuristic optimization and pre/post-regression diagnostics, fixing iteratively the model parameters that do not have a significant role. We evaluated this protocol in a Saccharomyces cerevisiae dFBA framework calibrated for aerobic fed-batch and anaerobic batch cultivations. The model structures achieved have only significant, sensitive and uncorrelated parameters and are able to calibrate different experimental data. We show that consumption, suboptimal growth and production rates are more useful for calibrating dynamic S. cerevisiae metabolic models than Boolean gene expression rules, biomass requirements and ATP maintenance. Copyright © 2014 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.
A network model for biofilm development in Escherichia coli K-12.
Shalá, Andrew A; Restrepo, Silvia; González Barrios, Andrés F
2011-09-22
In nature, bacteria often exist as biofilms. Biofilms are communities of microorganisms attached to a surface. It is clear that biofilm-grown cells harbor properties remarkably distinct from planktonic cells. Biofilms frequently complicate treatments of infections by protecting bacteria from the immune system, decreasing antibiotic efficacy and dispersing planktonic cells to distant body sites. In this work, we employed enhanced Boolean algebra to model biofilm formation. The network obtained describes biofilm formation successfully, assuming - in accordance with the literature - that when the negative regulators (RscCD and EnvZ/OmpR) are off, the positive regulator (FlhDC) is on. The network was modeled under three different conditions through time with satisfactory outcomes. Each cluster was constructed using the K-means/medians Clustering Support algorithm on the basis of published Affymetrix microarray gene expression data from biofilm-forming bacteria and the planktonic state over four time points for Escherichia coli K-12. The different phenotypes obtained demonstrate that the network model of biofilm formation can simulate the formation or repression of biofilm efficiently in E. coli K-12.
Compile-Time Schedulability Analysis of Communicating Concurrent Programs
2006-06-28
synchronize via the read and write operations on the FIFO channels. These operations have been implemented with the help of semaphores , which...3 1.1.2 Synchronous Dataflow . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.1.3 Boolean Dataflow...described by concurrent programs . . . . . . . . . 4 1.3 A synchronous dataflow model, its topology matrix, and repetition vector . 10 1.4 Select and
Cells adapt to their environment via homeostatic processes that are regulated by complex molecular networks. Our objective was to learn key elements of these networks in HepG2 cells using ToxCast High-content imaging (HCI) measurements taken over three time points (1, 24, and 72h...
A Model of Knowledge Based Information Retrieval with Hierarchical Concept Graph.
ERIC Educational Resources Information Center
Kim, Young Whan; Kim, Jin H.
1990-01-01
Proposes a model of knowledge-based information retrieval (KBIR) that is based on a hierarchical concept graph (HCG) which shows relationships between index terms and constitutes a hierarchical thesaurus as a knowledge base. Conceptual distance between a query and an object is discussed and the use of Boolean operators is described. (25…
ERIC Educational Resources Information Center
Ceulemans, Eva; Van Mechelen, Iven; Leenen, Iwin
2007-01-01
Hierarchical classes models are quasi-order retaining Boolean decomposition models for N-way N-mode binary data. To fit these models to data, rationally started alternating least squares (or, equivalently, alternating least absolute deviations) algorithms have been proposed. Extensive simulation studies showed that these algorithms succeed quite…
Bringing Federal Documents to the Forefront for Library Users: Selective Cataloging Using an OPAC.
ERIC Educational Resources Information Center
Oliva, Victor T.
2000-01-01
Reviews the value of federal depository document titles and discuses reasons why many are worth cataloging. Several approaches to cataloging these titles to make them more readily accessible are profiled. The Adelphi University Library (New York) has devised a system, using Boolean logic and an online public access catalog to choose which titles…
ERIC Educational Resources Information Center
Cooper, Barry; Glaesser, Judith
2016-01-01
We discuss a recent development in the set theoretic analysis of data sets characterized by limited diversity. Ragin, in developing his Qualitative Comparative Analysis (QCA), developed a standard analysis that produces parsimonious, intermediate, and complex Boolean solutions of truth tables. Schneider and Wagemann argue this standard analysis…
Crisp Sets and Boolean Algebra: A Research Strategy for Student Affairs
ERIC Educational Resources Information Center
Banning, James; Eversole, Barbara; Most, David; Kuk, Linda
2008-01-01
A review of student affairs journals clearly points out that most, if not all, research strategies within the field fall within traditional approaches based on quantitative methods and, more recently, qualitative methods. The purpose of this article is not to discourage use of these time honored research strategies, but to suggest the inclusion of…
ERIC Educational Resources Information Center
Liu, Xiaokai
2018-01-01
Writing as one of essential skills in English learning is attached more and more importance. English writing involves not only the application of lexicon and grammar, but also the construction of the text and the expression of the thought. For Chinese EFL learners, the common problem in English writing is that they tend to apply the Chinese…
Thurman, E.M.; Ferrer, I.; Barcelo, D.
2001-01-01
An evaluation of over 75 pesticides by high-performance liquid chromatography/mass spectrometry (HPLC/MS) clearly shows that different classes of pesticides are more sensitive using either atmospheric pressure chemical ionization (APCI) or electrospray ionization (ESI). For example, neutral and basic pesticides (phenylureas, triazines) are more sensitive using APCI (especially positive ion). While cationic and anionic herbicides (bipyridylium ions, sulfonic acids) are more sensitive using ESI (especially negative ion). These data are expressed graphically in a figure called an ionization-continuum diagram, which shows that protonation in the gas phase (proton affinity) and polarity in solution, expressed as proton addition or subtraction (pKa), is useful in selecting APCI or ESI. Furthermore, sodium adduct formation commonly occurs using positive ion ESI but not using positive ion APCI, which reflects the different mechanisms of ionization and strengthens the usefulness of the ionization-continuum diagram. The data also show that the concept of "wrong-way around" ESI (the sensitivity of acidic pesticides in an acidic mobile phase) is a useful modification of simple pKa theory for mobile-phase selection. Finally, this finding is used to enhance the chromatographic separation of oxanilic and sulfonic acid herbicides while maintaining good sensitivity in LC/MS using ESI negative.
Universal Off-Equilibrium Scaling of Critical Cumulants in the QCD Phase Diagram
Mukherjee, Swagato; Venugopalan, Raju; Yin, Yi
2016-11-23
Exploiting the universality between the QCD critical point and the three-dimensional Ising model, closed form expressions derived for nonequilibrium critical cumulants on the crossover side of the critical point reveal that they can differ in both magnitude and sign from equilibrium expectations. Here, we demonstrate here that key elements of the Kibble-Zurek framework of nonequilibrium phase transitions can be employed to describe the dynamics of these critical cumulants. Lastly, our results suggest that observables sensitive to critical dynamics in heavy-ion collisions should be expressible as universal scaling functions, thereby providing powerful model-independent guidance in searches for the QCD critical point.
Genetic Approaches to Reveal the Connectivity of Adult-Born Neurons
Arenkiel, Benjamin R.
2011-01-01
Much has been learned about the environmental and molecular factors that influence the division, migration, and programmed cell death of adult-born neurons in the mammalian brain. However, detailed knowledge of the mechanisms that govern the formation and maintenance of functional circuit connectivity via adult neurogenesis remains elusive. Recent advances in genetic technologies now afford the ability to precisely target discrete brain tissues, neuronal subtypes, and even single neurons for vital reporter expression and controlled activity manipulations. Here, I review current viral tracing methods, heterologous receptor expression systems, and optogenetic technologies that hold promise toward elucidating the wiring diagrams and circuit properties of adult-born neurons. PMID:21519388
NASA Technical Reports Server (NTRS)
Windley, P. J.
1991-01-01
In this paper we explore the specification and verification of VLSI designs. The paper focuses on abstract specification and verification of functionality using mathematical logic as opposed to low-level boolean equivalence verification such as that done using BDD's and Model Checking. Specification and verification, sometimes called formal methods, is one tool for increasing computer dependability in the face of an exponentially increasing testing effort.
2010-12-01
with high correlation immunity and then evaluate these functions for other desirable cryptographic features. C. METHOD The only known primary methods...out if not used) # ---------------------------------- # PRIMARY = < primary file 1> < primary file 2> #SECONDARY = <secondary file 1...finding the fuction value for a //set u and for each value of v. end end
Sequential, progressive, equal-power, reflective beam-splitter arrays
NASA Astrophysics Data System (ADS)
Manhart, Paul K.
2017-11-01
The equations to calculate equal-power reflectivity of a sequential series of beam splitters is presented. Non-sequential optical design examples are offered for uniform illumination using diode lasers. Objects created using Boolean operators and Swept Surfaces can create objects capable of reflecting light into predefined elevation and azimuth angles. Analysis of the illumination patterns for the array are also presented.
ERIC Educational Resources Information Center
Oldroyd, Betty K.; Schroder, J. J.
1982-01-01
Reviews the advantages and disadvantages of different types of term combination using the positional logic capability of online information retrieval systems and describes a study in which searches for material on "microwave integrated circuits" were conducted in order to find the most economical way of generating the most relevant…
Developing and Testing an Online Tool for Teaching GIS Concepts Applied to Spatial Decision-Making
ERIC Educational Resources Information Center
Carver, Steve; Evans, Andy; Kingston, Richard
2004-01-01
The development and testing of a Web-based GIS e-learning resource is described. This focuses on the application of GIS for siting a nuclear waste disposal facility and the associated principles of spatial decision-making using Boolean and weighted overlay methods. Initial student experiences in using the system are analysed as part of a research…
ERIC Educational Resources Information Center
Kalechofsky, Robert
This research paper proposes several mathematical models which help clarify Piaget's theory of cognition on the concrete and formal operational stages. Some modified lattice models were used for the concrete stage and a combined Boolean Algebra and group theory model was used for the formal stage. The researcher used experiments cited in the…
Recent development and biomedical applications of probabilistic Boolean networks
2013-01-01
Probabilistic Boolean network (PBN) modelling is a semi-quantitative approach widely used for the study of the topology and dynamic aspects of biological systems. The combined use of rule-based representation and probability makes PBN appealing for large-scale modelling of biological networks where degrees of uncertainty need to be considered. A considerable expansion of our knowledge in the field of theoretical research on PBN can be observed over the past few years, with a focus on network inference, network intervention and control. With respect to areas of applications, PBN is mainly used for the study of gene regulatory networks though with an increasing emergence in signal transduction, metabolic, and also physiological networks. At the same time, a number of computational tools, facilitating the modelling and analysis of PBNs, are continuously developed. A concise yet comprehensive review of the state-of-the-art on PBN modelling is offered in this article, including a comparative discussion on PBN versus similar models with respect to concepts and biomedical applications. Due to their many advantages, we consider PBN to stand as a suitable modelling framework for the description and analysis of complex biological systems, ranging from molecular to physiological levels. PMID:23815817
Construction of a fuzzy and Boolean logic gates based on DNA.
Zadegan, Reza M; Jepsen, Mette D E; Hildebrandt, Lasse L; Birkedal, Victoria; Kjems, Jørgen
2015-04-17
Logic gates are devices that can perform logical operations by transforming a set of inputs into a predictable single detectable output. The hybridization properties, structure, and function of nucleic acids can be used to make DNA-based logic gates. These devices are important modules in molecular computing and biosensing. The ideal logic gate system should provide a wide selection of logical operations, and be integrable in multiple copies into more complex structures. Here we show the successful construction of a small DNA-based logic gate complex that produces fluorescent outputs corresponding to the operation of the six Boolean logic gates AND, NAND, OR, NOR, XOR, and XNOR. The logic gate complex is shown to work also when implemented in a three-dimensional DNA origami box structure, where it controlled the position of the lid in a closed or open position. Implementation of multiple microRNA sensitive DNA locks on one DNA origami box structure enabled fuzzy logical operation that allows biosensing of complex molecular signals. Integrating logic gates with DNA origami systems opens a vast avenue to applications in the fields of nanomedicine for diagnostics and therapeutics. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
An alternative data filling approach for prediction of missing data in soft sets (ADFIS).
Sadiq Khan, Muhammad; Al-Garadi, Mohammed Ali; Wahab, Ainuddin Wahid Abdul; Herawan, Tutut
2016-01-01
Soft set theory is a mathematical approach that provides solution for dealing with uncertain data. As a standard soft set, it can be represented as a Boolean-valued information system, and hence it has been used in hundreds of useful applications. Meanwhile, these applications become worthless if the Boolean information system contains missing data due to error, security or mishandling. Few researches exist that focused on handling partially incomplete soft set and none of them has high accuracy rate in prediction performance of handling missing data. It is shown that the data filling approach for incomplete soft set (DFIS) has the best performance among all previous approaches. However, in reviewing DFIS, accuracy is still its main problem. In this paper, we propose an alternative data filling approach for prediction of missing data in soft sets, namely ADFIS. The novelty of ADFIS is that, unlike the previous approach that used probability, we focus more on reliability of association among parameters in soft set. Experimental results on small, 04 UCI benchmark data and causality workbench lung cancer (LUCAP2) data shows that ADFIS performs better accuracy as compared to DFIS.
3D GIS spatial operation based on extended Euler operators
NASA Astrophysics Data System (ADS)
Xu, Hongbo; Lu, Guonian; Sheng, Yehua; Zhou, Liangchen; Guo, Fei; Shang, Zuoyan; Wang, Jing
2008-10-01
The implementation of 3 dimensions spatial operations, based on certain data structure, has a lack of universality and is not able to treat with non-manifold cases, at present. ISO/DIS 19107 standard just presents the definition of Boolean operators and set operators for topological relationship query, and OGC GeoXACML gives formal definitions for several set functions without implementation detail. Aiming at these problems, based mathematical foundation on cell complex theory, supported by non-manifold data structure and using relevant research in the field of non-manifold geometry modeling for reference, firstly, this paper according to non-manifold Euler-Poincaré formula constructs 6 extended Euler operators and inverse operators to carry out creating, updating and deleting 3D spatial elements, as well as several pairs of supplementary Euler operators to convenient for implementing advanced functions. Secondly, we change topological element operation sequence of Boolean operation and set operation as well as set functions defined in GeoXACML into combination of extended Euler operators, which separates the upper functions and lower data structure. Lastly, we develop underground 3D GIS prototype system, in which practicability and credibility of extended Euler operators faced to 3D GIS presented by this paper are validated.
NASA Astrophysics Data System (ADS)
Ye, Weiming; Li, Pengfei; Huang, Xuhui; Xia, Qinzhi; Mi, Yuanyuan; Chen, Runsheng; Hu, Gang
2010-10-01
Exploring the principle and relationship of gene transcriptional regulations (TR) has been becoming a generally researched issue. So far, two major mathematical methods, ordinary differential equation (ODE) method and Boolean map (BM) method have been widely used for these purposes. It is commonly believed that simplified BMs are reasonable approximations of more realistic ODEs, and both methods may reveal qualitatively the same essential features though the dynamical details of both systems may show some differences. In this Letter we exhaustively enumerated all the 3-gene networks and many autonomous randomly constructed TR networks with more genes by using both the ODE and BM methods. In comparison we found that both methods provide practically identical results in most of cases of steady solutions. However, to our great surprise, most of network structures showing periodic cycles with the BM method possess only stationary states in ODE descriptions. These observations strongly suggest that many periodic oscillations and other complicated oscillatory states revealed by the BM rule may be related to the computational errors of variable and time discretizations and rarely have correspondence in realistic biology transcriptional regulatory circuits.
Current-induced modulation of backward spin-waves in metallic microstructures
NASA Astrophysics Data System (ADS)
Sato, Nana; Lee, Seo-Won; Lee, Kyung-Jin; Sekiguchi, Koji
2017-03-01
We performed a propagating spin-wave spectroscopy for backward spin-waves in ferromagnetic metallic microstructures in the presence of electric-current. Even with the smaller current injection of 5× {{10}10} A m-2 into ferromagnetic microwires, the backward spin-waves exhibit a gigantic 200 MHz frequency shift and a 15% amplitude change, showing 60 times larger modulation compared to previous reports. Systematic experiments by measuring dependences on a film thickness of mirowire, on the wave-vector of spin-wave, and on the magnitude of bias field, we revealed that for the backward spin-waves a distribution of internal magnetic field generated by electric-current efficiently modulates the frequency and amplitude of spin-waves. The gigantic frequency and amplitude changes were reproduced by a micromagnetics simulation, predicting that the current-injection of 5× {{10}11} A m-2 allows 3 GHz frequency shift. The effective coupling between electric-current and backward spin-waves has a potential to build up a logic control method which encodes signals into the phase and amplitude of spin-waves. The metallic magnonics cooperating with electronics could suggest highly integrated magnonic circuits both in Boolean and non-Boolean principles.
Crack stability and branching at interfaces
NASA Astrophysics Data System (ADS)
Thomson, Robb
1995-11-01
The various events that occur at a crack on an interface are explored, and described in terms of a simple graphical construction called the crack stability diagram. For simple Griffith cleavage in a homogeneous material, the stability diagram is a sector of a circle in the space of stress intensity factors, KI/KII. The Griffith circle is limited in both positive and negative KII directions by nonblunting dislocation emission on the cleavage plane. For a branching plane inclined at an angle to the original cleavage plane, both cleavage and emission (which blunts the crack) can be described as a balance between an elastic driving force and a lattice resistance for the event. We use an analytic expression obtained by Cotterell and Rice for cleavage, and show that it is an excellent approximation, but show that the lattice resistance includes a cornering resistance, in addition to the standard surface energy in the final cleavage criterion. Our discussion of the lattaice resistance is derived from simulations in two-dimensional hexagonal lattices with UBER force laws with a variety of shapes. Both branching cleavage and blunting emission can be described in terms of a stability diagram in the space of the remote stress intensity factors, and the competition between events on the initial cleavage plane and those on the branching plane can be described by overlays of the two appropriate stability diagrams. The popular criterion that kII=0 on the branching plane is explored for lattices and found to fail significantly, because the lattice stabilizes cleavage by the anisotropy of the surface energy. Also, in the lattice, dislocation emission must must always be considered as an alternative competing event to branching.
Comprehending 3D Diagrams: Sketching to Support Spatial Reasoning.
Gagnier, Kristin M; Atit, Kinnari; Ormand, Carol J; Shipley, Thomas F
2017-10-01
Science, technology, engineering, and mathematics (STEM) disciplines commonly illustrate 3D relationships in diagrams, yet these are often challenging for students. Failing to understand diagrams can hinder success in STEM because scientific practice requires understanding and creating diagrammatic representations. We explore a new approach to improving student understanding of diagrams that convey 3D relations that is based on students generating their own predictive diagrams. Participants' comprehension of 3D spatial diagrams was measured in a pre- and post-design where students selected the correct 2D slice through 3D geologic block diagrams. Generating sketches that predicated the internal structure of a model led to greater improvement in diagram understanding than visualizing the interior of the model without sketching, or sketching the model without attempting to predict unseen spatial relations. In addition, we found a positive correlation between sketched diagram accuracy and improvement on the diagram comprehension measure. Results suggest that generating a predictive diagram facilitates students' abilities to make inferences about spatial relationships in diagrams. Implications for use of sketching in supporting STEM learning are discussed. Copyright © 2016 Cognitive Science Society, Inc.
Ad Hoc Information Extraction for Clinical Data Warehouses.
Dietrich, Georg; Krebs, Jonathan; Fette, Georg; Ertl, Maximilian; Kaspar, Mathias; Störk, Stefan; Puppe, Frank
2018-05-01
Clinical Data Warehouses (CDW) reuse Electronic health records (EHR) to make their data retrievable for research purposes or patient recruitment for clinical trials. However, much information are hidden in unstructured data like discharge letters. They can be preprocessed and converted to structured data via information extraction (IE), which is unfortunately a laborious task and therefore usually not available for most of the text data in CDW. The goal of our work is to provide an ad hoc IE service that allows users to query text data ad hoc in a manner similar to querying structured data in a CDW. While search engines just return text snippets, our systems also returns frequencies (e.g. how many patients exist with "heart failure" including textual synonyms or how many patients have an LVEF < 45) based on the content of discharge letters or textual reports for special investigations like heart echo. Three subtasks are addressed: (1) To recognize and to exclude negations and their scopes, (2) to extract concepts, i.e. Boolean values and (3) to extract numerical values. We implemented an extended version of the NegEx-algorithm for German texts that detects negations and determines their scope. Furthermore, our document oriented CDW PaDaWaN was extended with query functions, e.g. context sensitive queries and regex queries, and an extraction mode for computing the frequencies for Boolean and numerical values. Evaluations in chest X-ray reports and in discharge letters showed high F1-scores for the three subtasks: Detection of negated concepts in chest X-ray reports with an F1-score of 0.99 and in discharge letters with 0.97; of Boolean values in chest X-ray reports about 0.99, and of numerical values in chest X-ray reports and discharge letters also around 0.99 with the exception of the concept age. The advantages of an ad hoc IE over a standard IE are the low development effort (just entering the concept with its variants), the promptness of the results and the adaptability by the user to his or her particular question. Disadvantage are usually lower accuracy and confidence.This ad hoc information extraction approach is novel and exceeds existing systems: Roogle [1] extracts predefined concepts from texts at preprocessing and makes them retrievable at runtime. Dr. Warehouse [2] applies negation detection and indexes the produced subtexts which include affirmed findings. Our approach combines negation detection and the extraction of concepts. But the extraction does not take place during preprocessing, but at runtime. That provides an ad hoc, dynamic, interactive and adjustable information extraction of random concepts and even their values on the fly at runtime. We developed an ad hoc information extraction query feature for Boolean and numerical values within a CDW with high recall and precision based on a pipeline that detects and removes negations and their scope in clinical texts. Schattauer GmbH.
Bochevarov, Arteum D; Sherrill, C David
2004-08-22
We present a general computer algorithm to contract an arbitrary number of second-quantized expressions and simplify the obtained analytical result. The functions that perform these operations are a part of the program Nostromo which facilitates the handling and analysis of the complicated mathematical formulas which are often encountered in modern quantum-chemical models. In contrast to existing codes of this kind, Nostromo is based solely on the Goldstone-diagrammatic representation of algebraic expressions in Fock space and has capabilities to work with operators as well as scalars. Each Goldstone diagram is internally represented by a line of text which is easy to interpret and transform. The calculation of matrix elements does not exploit Wick's theorem in a direct way, but uses diagrammatic techniques to produce only nonzero terms. The identification of equivalent expressions and their subsequent factorization in the final result is performed easily by analyzing the topological structure of the diagrammatic expressions. (c) 2004 American Institute of Physics
Fundamentals of Electrical Propulsion Plant Design,
1982-04-06
through connection of resonant filters or through use of multiphase conversion power circuits. Figure 9.25. Block Diagram of a Frequency Converter Control...first harmonic, active power Pa’ consumed by the converter at the point of application of this emf, is determined from expression P. = 3EM i cos i...armature shunting contactor K3 KDD diesel starting contactor K.U KZ protection contactor K3 KMM maximum power contactor KM KO compensating winding KO
Expression of Superparamagnetic Particles on FORC Diagrams
NASA Astrophysics Data System (ADS)
Hirt, A. M.; Kumari, M.; Crippa, F.; Petri-Fink, A.
2015-12-01
Identification of superparamagnetic (SP) particles in natural materials provides information on processes that lead to the new formation or dissolution of iron oxides. SP particles express themselves on first-order reversal curve (FORC) diagrams as a distribution centered near the origin of the diagram. Pike et al. (2001, GJI, 145, 721) demonstrated that thermal relaxation produces an upward shift in the FORC distribution, and attributed this to a pause encountered at each reversal field. In this study we examine the relationship between this upward shift and particles size on two sets of synthetic iron oxide nanoparticles. One set of coated magnetite particles have well-constrained particles size with 9, 16 and 20 nm as their diameter. A second set from the FeraSpin™ Series, consisting of FeraSpinXS, M and XL, were evaluated. Rock magnetic experiments indicate that the first set of samples is exclusively magnetite, whereas the FeraSpin samples contain predominantly magnetite with some degree of oxidation. Samples from both sets show that the upward shift of the FORC distribution at the origin increases with decreasing particle size. The amount of shift in the FeraSpin series is less when compared to the samples from the first set. This is attributed to the effect of interaction that counteracts the effect of thermal relaxation behavior of the SP particles. The FeraSpin series also shows a broader FORC distribution on the vertical axis that appears to be related to non-saturation of the hysteresis curve at maximum applied field. This non-saturation behavior can be due to spins of very fine particles or oxidation to hematite. AC susceptibility at low temperature indicates that particle interaction may affect the effective magnetic particle size. Our results suggest that the FORC distribution in pure SP particle systems provides information on the particle size distribution or oxidation, which can be further evaluated with low temperature techniques.
Diagram, a Learning Environment for Initiation to Object-Oriented Modeling with UML Class Diagrams
ERIC Educational Resources Information Center
Py, Dominique; Auxepaules, Ludovic; Alonso, Mathilde
2013-01-01
This paper presents Diagram, a learning environment for object-oriented modelling (OOM) with UML class diagrams. Diagram an open environment, in which the teacher can add new exercises without constraints on the vocabulary or the size of the diagram. The interface includes methodological help, encourages self-correcting and self-monitoring, and…
NASA Astrophysics Data System (ADS)
Jian, Yu-Cin; Wu, Chao-Jung
2015-02-01
We investigated strategies used by readers when reading a science article with a diagram and assessed whether semantic and spatial representations were constructed while reading the diagram. Seventy-one undergraduate participants read a scientific article while tracking their eye movements and then completed a reading comprehension test. Our results showed that the text-diagram referencing strategy was commonly used. However, some readers adopted other reading strategies, such as reading the diagram or text first. We found all readers who had referred to the diagram spent roughly the same amount of time reading and performed equally well. However, some participants who ignored the diagram performed more poorly on questions that tested understanding of basic facts. This result indicates that dual coding theory may be a possible theory to explain the phenomenon. Eye movement patterns indicated that at least some readers had extracted semantic information of the scientific terms when first looking at the diagram. Readers who read the scientific terms on the diagram first tended to spend less time looking at the same terms in the text, which they read after. Besides, presented clear diagrams can help readers process both semantic and spatial information, thereby facilitating an overall understanding of the article. In addition, although text-first and diagram-first readers spent similar total reading time on the text and diagram parts of the article, respectively, text-first readers had significantly less number of saccades of text and diagram than diagram-first readers. This result might be explained as text-directed reading.
Quantifying Performance Bias in Label Fusion
2012-08-21
detect ), may provide the end-user with the means to appropriately adjust the performance and optimal thresholds for performance by fusing legacy systems...boolean combination of classification systems in ROC space: An application to anomaly detection with HMMs. Pattern Recognition, 43(8), 2732-2752. 10...Shamsuddin, S. (2009). An overview of neural networks use in anomaly intrusion detection systems. Paper presented at the Research and Development (SCOReD
2017-09-01
information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and...maintaining the data needed, and completing and reviewing the collection of information . Send comments regarding this burden estimate or any other aspect...of this collection of information , including suggestions for reducing this burden to Washington headquarters Services, Directorate for Information
Further Results on Constructions of Generalized Bent Boolean Functions
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
INM Integrated Noise Model Version 2. Programmer’s Guide
1979-09-01
cost, turnaround time, and system-dependent limitations. 3.2 CONVERSION PROBLEMS Item Item Item No. Desciption Category 1 BLOCK DATA Initialization IBM ...Restricted 2 Boolean Operations Differences Call Statement Parameters Extensions 4 Data Initialization IBM Restricted 5 ENTRY Differences 6 EQUIVALENCE...Machine Dependent 7 Format: A CDC Extension 8 Hollerith Strings IBM Restricted 9 Hollerith Variables IBM Restricted 10 Identifier Names CDC Extension
ERIC Educational Resources Information Center
Tang, Michael; David, Hyerle; Byrne, Roxanne; Tran, John
2012-01-01
This paper is a mathematical (Boolean) analysis a set of cognitive maps called Thinking Maps[R], based on Albert Upton's semantic principles developed in his seminal works, Design for Thinking (1961) and Creative Analysis (1961). Albert Upton can be seen as a brilliant thinker who was before his time or after his time depending on the future of…