Distributing the computation in combinatorial optimization experiments over the cloud

Directory of Open Access Journals (Sweden)

Mario Brcic

2017-12-01

Full Text Available Combinatorial optimization is an area of great importance since many of the real-world problems have discrete parameters which are part of the objective function to be optimized. Development of combinatorial optimization algorithms is guided by the empirical study of the candidate ideas and their performance over a wide range of settings or scenarios to infer general conclusions. Number of scenarios can be overwhelming, especially when modeling uncertainty in some of the problem’s parameters. Since the process is also iterative and many ideas and hypotheses may be tested, execution time of each experiment has an important role in the efficiency and successfulness. Structure of such experiments allows for significant execution time improvement by distributing the computation. We focus on the cloud computing as a cost-efficient solution in these circumstances. In this paper we present a system for validating and comparing stochastic combinatorial optimization algorithms. The system also deals with selection of the optimal settings for computational nodes and number of nodes in terms of performance-cost tradeoff. We present applications of the system on a new class of project scheduling problem. We show that we can optimize the selection over cloud service providers as one of the settings and, according to the model, it resulted in a substantial cost-savings while meeting the deadline.

Phase Transitions in Combinatorial Optimization Problems Basics, Algorithms and Statistical Mechanics

CERN Document Server

Hartmann, Alexander K

2005-01-01

A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with the concepts and methods of theoretical physics. The authors cover rapid developments and analytical methods that are both extremely complex and spread by word-of-mouth, providing all the necessary

Combinatorial Clustering Algorithm of Quantum-Behaved Particle Swarm Optimization and Cloud Model

Directory of Open Access Journals (Sweden)

Mi-Yuan Shan

2013-01-01

Full Text Available We propose a combinatorial clustering algorithm of cloud model and quantum-behaved particle swarm optimization (COCQPSO to solve the stochastic problem. The algorithm employs a novel probability model as well as a permutation-based local search method. We are setting the parameters of COCQPSO based on the design of experiment. In the comprehensive computational study, we scrutinize the performance of COCQPSO on a set of widely used benchmark instances. By benchmarking combinatorial clustering algorithm with state-of-the-art algorithms, we can show that its performance compares very favorably. The fuzzy combinatorial optimization algorithm of cloud model and quantum-behaved particle swarm optimization (FCOCQPSO in vague sets (IVSs is more expressive than the other fuzzy sets. Finally, numerical examples show the clustering effectiveness of COCQPSO and FCOCQPSO clustering algorithms which are extremely remarkable.

Combinatorial thin film materials science: From alloy discovery and optimization to alloy design

Energy Technology Data Exchange (ETDEWEB)

Gebhardt, Thomas, E-mail: gebhardt@mch.rwth-aachen.de; Music, Denis; Takahashi, Tetsuya; Schneider, Jochen M.

2012-06-30

This paper provides an overview of modern alloy development, from discovery and optimization towards alloy design, based on combinatorial thin film materials science. The combinatorial approach, combining combinatorial materials synthesis of thin film composition-spreads with high-throughput property characterization has proven to be a powerful tool to delineate composition-structure-property relationships, and hence to efficiently identify composition windows with enhanced properties. Furthermore, and most importantly for alloy design, theoretical models and hypotheses can be critically appraised. Examples for alloy discovery, optimization, and alloy design of functional as well as structural materials are presented. Using Fe-Mn based alloys as an example, we show that the combination of modern electronic-structure calculations with the highly efficient combinatorial thin film composition-spread method constitutes an effective tool for knowledge-based alloy design.

Combinatorial thin film materials science: From alloy discovery and optimization to alloy design

International Nuclear Information System (INIS)

Gebhardt, Thomas; Music, Denis; Takahashi, Tetsuya; Schneider, Jochen M.

2012-01-01

This paper provides an overview of modern alloy development, from discovery and optimization towards alloy design, based on combinatorial thin film materials science. The combinatorial approach, combining combinatorial materials synthesis of thin film composition-spreads with high-throughput property characterization has proven to be a powerful tool to delineate composition–structure–property relationships, and hence to efficiently identify composition windows with enhanced properties. Furthermore, and most importantly for alloy design, theoretical models and hypotheses can be critically appraised. Examples for alloy discovery, optimization, and alloy design of functional as well as structural materials are presented. Using Fe-Mn based alloys as an example, we show that the combination of modern electronic-structure calculations with the highly efficient combinatorial thin film composition-spread method constitutes an effective tool for knowledge-based alloy design.

Binary Cockroach Swarm Optimization for Combinatorial Optimization Problem

Directory of Open Access Journals (Sweden)

Ibidun Christiana Obagbuwa

2016-09-01

Full Text Available The Cockroach Swarm Optimization (CSO algorithm is inspired by cockroach social behavior. It is a simple and efficient meta-heuristic algorithm and has been applied to solve global optimization problems successfully. The original CSO algorithm and its variants operate mainly in continuous search space and cannot solve binary-coded optimization problems directly. Many optimization problems have their decision variables in binary. Binary Cockroach Swarm Optimization (BCSO is proposed in this paper to tackle such problems and was evaluated on the popular Traveling Salesman Problem (TSP, which is considered to be an NP-hard Combinatorial Optimization Problem (COP. A transfer function was employed to map a continuous search space CSO to binary search space. The performance of the proposed algorithm was tested firstly on benchmark functions through simulation studies and compared with the performance of existing binary particle swarm optimization and continuous space versions of CSO. The proposed BCSO was adapted to TSP and applied to a set of benchmark instances of symmetric TSP from the TSP library. The results of the proposed Binary Cockroach Swarm Optimization (BCSO algorithm on TSP were compared to other meta-heuristic algorithms.

From combinatorial optimization to real algebraic geometry and back

Directory of Open Access Journals (Sweden)

Janez Povh

2014-12-01

Full Text Available In this paper, we explain the relations between combinatorial optimization and real algebraic geometry with a special focus to the quadratic assignment problem. We demonstrate how to write a quadratic optimization problem over discrete feasible set as a linear optimization problem over the cone of completely positive matrices. The latter formulation enables a hierarchy of approximations which rely on results from polynomial optimization, a sub-eld of real algebraic geometry.

Machine learning meliorates computing and robustness in discrete combinatorial optimization problems.

Directory of Open Access Journals (Sweden)

Fushing Hsieh

2016-11-01

Full Text Available Discrete combinatorial optimization problems in real world are typically defined via an ensemble of potentially high dimensional measurements pertaining to all subjects of a system under study. We point out that such a data ensemble in fact embeds with system's information content that is not directly used in defining the combinatorial optimization problems. Can machine learning algorithms extract such information content and make combinatorial optimizing tasks more efficient? Would such algorithmic computations bring new perspectives into this classic topic of Applied Mathematics and Theoretical Computer Science? We show that answers to both questions are positive. One key reason is due to permutation invariance. That is, the data ensemble of subjects' measurement vectors is permutation invariant when it is represented through a subject-vs-measurement matrix. An unsupervised machine learning algorithm, called Data Mechanics (DM, is applied to find optimal permutations on row and column axes such that the permuted matrix reveals coupled deterministic and stochastic structures as the system's information content. The deterministic structures are shown to facilitate geometry-based divide-and-conquer scheme that helps optimizing task, while stochastic structures are used to generate an ensemble of mimicries retaining the deterministic structures, and then reveal the robustness pertaining to the original version of optimal solution. Two simulated systems, Assignment problem and Traveling Salesman problem, are considered. Beyond demonstrating computational advantages and intrinsic robustness in the two systems, we propose brand new robust optimal solutions. We believe such robust versions of optimal solutions are potentially more realistic and practical in real world settings.

Phase Transitions in Combinatorial Optimization Problems: Basics, Algorithms and Statistical Mechanics

Science.gov (United States)

Hartmann, Alexander K.; Weigt, Martin

2005-10-01

A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with the concepts and methods of theoretical physics. The authors cover rapid developments and analytical methods that are both extremely complex and spread by word-of-mouth, providing all the necessary basics in required detail. Throughout, the algorithms are shown with examples and calculations, while the proofs are given in a way suitable for graduate students, post-docs, and researchers. Ideal for newcomers to this young, multidisciplinary field.

Advances in bio-inspired computing for combinatorial optimization problems

CERN Document Server

Pintea, Camelia-Mihaela

2013-01-01

Advances in Bio-inspired Combinatorial Optimization Problems' illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems.Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization problems, for example: the Generalized Traveling Salesman Problem and the Railway Traveling Salesman Problem, are solved and their results are discussed.Some of the main concepts and models described in this book are: inner rule to guide ant search - a recent model in ant optimization, heterogeneous sensitive a

View Discovery in OLAP Databases through Statistical Combinatorial Optimization

Energy Technology Data Exchange (ETDEWEB)

Joslyn, Cliff A.; Burke, Edward J.; Critchlow, Terence J.

2009-05-01

The capability of OLAP database software systems to handle data complexity comes at a high price for analysts, presenting them a combinatorially vast space of views of a relational database. We respond to the need to deploy technologies sufficient to allow users to guide themselves to areas of local structure by casting the space of ``views'' of an OLAP database as a combinatorial object of all projections and subsets, and ``view discovery'' as an search process over that lattice. We equip the view lattice with statistical information theoretical measures sufficient to support a combinatorial optimization process. We outline ``hop-chaining'' as a particular view discovery algorithm over this object, wherein users are guided across a permutation of the dimensions by searching for successive two-dimensional views, pushing seen dimensions into an increasingly large background filter in a ``spiraling'' search process. We illustrate this work in the context of data cubes recording summary statistics for radiation portal monitors at US ports.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

Science.gov (United States)

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

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

Science.gov (United States)

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

2018-01-01

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

First steps in combinatorial optimization on graphons: matchings

Czech Academy of Sciences Publication Activity Database

Doležal, Martin; Hladký, J.; Hu, P.; Piguet, Diana

2017-01-01

Roč. 61, August (2017), s. 359-365 ISSN 1571-0653 R&D Projects: GA ČR GA16-07378S; GA ČR GJ16-07822Y EU Projects: European Commission(XE) 628974 - PAECIDM Institutional support: RVO:67985840 ; RVO:67985807 Keywords : graphon * graph limits * matching * combinatorial optimization Subject RIV: BA - General Mathematics ; BA - General Mathematics (UIVT-O) OBOR OECD: Pure mathematics ; Pure mathematics (UIVT-O) http://www.sciencedirect.com/science/article/pii/S1571065317301452

First steps in combinatorial optimization on graphons: matchings

Czech Academy of Sciences Publication Activity Database

Doležal, Martin; Hladký, J.; Hu, P.; Piguet, Diana

2017-01-01

Roč. 61, August (2017), s. 359-365 ISSN 1571-0653 R&D Projects: GA ČR GA16-07378S; GA ČR GJ16-07822Y EU Projects: European Commission(XE) 628974 - PAECIDM Institutional support: RVO:67985840 ; RVO:67985807 Keywords : graphon * graph limits * matching * combinatorial optimization Subject RIV: BA - General Mathematics; BA - General Mathematics (UIVT-O) OBOR OECD: Pure mathematics; Pure mathematics (UIVT-O) http://www.sciencedirect.com/science/article/pii/S1571065317301452

Particle Swarm Optimization applied to combinatorial problem aiming the fuel recharge problem solution in a nuclear reactor

International Nuclear Information System (INIS)

Meneses, Anderson Alvarenga de Moura; Schirru, Roberto

2005-01-01

This work focuses on the usage the Artificial Intelligence technique Particle Swarm Optimization (PSO) to optimize the fuel recharge at a nuclear reactor. This is a combinatorial problem, in which the search of the best feasible solution is done by minimizing a specific objective function. However, in this first moment it is possible to compare the fuel recharge problem with the Traveling Salesman Problem (TSP), since both of them are combinatorial, with one advantage: the evaluation of the TSP objective function is much more simple. Thus, the proposed methods have been applied to two TSPs: Oliver 30 and Rykel 48. In 1995, KENNEDY and EBERHART presented the PSO technique to optimize non-linear continued functions. Recently some PSO models for discrete search spaces have been developed for combinatorial optimization. Although all of them having different formulation from the ones presented here. In this paper, we use the PSO theory associated with to the Random Keys (RK)model, used in some optimizations with Genetic Algorithms. The Particle Swarm Optimization with Random Keys (PSORK) results from this association, which combines PSO and RK. The adaptations and changings in the PSO aim to allow the usage of the PSO at the nuclear fuel recharge. This work shows the PSORK being applied to the proposed combinatorial problem and the obtained results. (author)

Editorial: Cologne/Twente workshop on graphs and combinatorial optimization CTW 2007

NARCIS (Netherlands)

Faigle, U.; Hurink, Johann L.

2010-01-01

The 6th Cologne-Twente Workshop on Graphs and Combinatorial Optimization (CTW 2007) was held at the University of Twente, The Netherlands, 29-31 May, 2007. The CTW started as a series of biennial meetings at the Universities of Cologne in Germany and Twente in the Netherlands. Ever increasing

View discovery in OLAP databases through statistical combinatorial optimization

Energy Technology Data Exchange (ETDEWEB)

Hengartner, Nick W [Los Alamos National Laboratory; Burke, John [PNNL; Critchlow, Terence [PNNL; Joslyn, Cliff [PNNL; Hogan, Emilie [PNNL

2009-01-01

OnLine Analytical Processing (OLAP) is a relational database technology providing users with rapid access to summary, aggregated views of a single large database, and is widely recognized for knowledge representation and discovery in high-dimensional relational databases. OLAP technologies provide intuitive and graphical access to the massively complex set of possible summary views available in large relational (SQL) structured data repositories. The capability of OLAP database software systems to handle data complexity comes at a high price for analysts, presenting them a combinatorially vast space of views of a relational database. We respond to the need to deploy technologies sufficient to allow users to guide themselves to areas of local structure by casting the space of 'views' of an OLAP database as a combinatorial object of all projections and subsets, and 'view discovery' as an search process over that lattice. We equip the view lattice with statistical information theoretical measures sufficient to support a combinatorial optimization process. We outline 'hop-chaining' as a particular view discovery algorithm over this object, wherein users are guided across a permutation of the dimensions by searching for successive two-dimensional views, pushing seen dimensions into an increasingly large background filter in a 'spiraling' search process. We illustrate this work in the context of data cubes recording summary statistics for radiation portal monitors at US ports.

Development of Combinatorial Methods for Alloy Design and Optimization

International Nuclear Information System (INIS)

Pharr, George M.; George, Easo P.; Santella, Michael L

2005-01-01

The primary goal of this research was to develop a comprehensive methodology for designing and optimizing metallic alloys by combinatorial principles. Because conventional techniques for alloy preparation are unavoidably restrictive in the range of alloy composition that can be examined, combinatorial methods promise to significantly reduce the time, energy, and expense needed for alloy design. Combinatorial methods can be developed not only to optimize existing alloys, but to explore and develop new ones as well. The scientific approach involved fabricating an alloy specimen with a continuous distribution of binary and ternary alloy compositions across its surface--an ''alloy library''--and then using spatially resolved probing techniques to characterize its structure, composition, and relevant properties. The three specific objectives of the project were: (1) to devise means by which simple test specimens with a library of alloy compositions spanning the range interest can be produced; (2) to assess how well the properties of the combinatorial specimen reproduce those of the conventionally processed alloys; and (3) to devise screening tools which can be used to rapidly assess the important properties of the alloys. As proof of principle, the methodology was applied to the Fe-Ni-Cr ternary alloy system that constitutes many commercially important materials such as stainless steels and the H-series and C-series heat and corrosion resistant casting alloys. Three different techniques were developed for making alloy libraries: (1) vapor deposition of discrete thin films on an appropriate substrate and then alloying them together by solid-state diffusion; (2) co-deposition of the alloying elements from three separate magnetron sputtering sources onto an inert substrate; and (3) localized melting of thin films with a focused electron-beam welding system. Each of the techniques was found to have its own advantages and disadvantages. A new and very powerful technique for

Statistical physics of hard combinatorial optimization: Vertex cover problem

Science.gov (United States)

Zhao, Jin-Hua; Zhou, Hai-Jun

2014-07-01

Typical-case computation complexity is a research topic at the boundary of computer science, applied mathematics, and statistical physics. In the last twenty years, the replica-symmetry-breaking mean field theory of spin glasses and the associated message-passing algorithms have greatly deepened our understanding of typical-case computation complexity. In this paper, we use the vertex cover problem, a basic nondeterministic-polynomial (NP)-complete combinatorial optimization problem of wide application, as an example to introduce the statistical physical methods and algorithms. We do not go into the technical details but emphasize mainly the intuitive physical meanings of the message-passing equations. A nonfamiliar reader shall be able to understand to a large extent the physics behind the mean field approaches and to adjust the mean field methods in solving other optimization problems.

A combinatorial approach to the design of vaccines.

Science.gov (United States)

Martínez, Luis; Milanič, Martin; Legarreta, Leire; Medvedev, Paul; Malaina, Iker; de la Fuente, Ildefonso M

2015-05-01

We present two new problems of combinatorial optimization and discuss their applications to the computational design of vaccines. In the shortest λ-superstring problem, given a family S1,...,S(k) of strings over a finite alphabet, a set Τ of "target" strings over that alphabet, and an integer λ, the task is to find a string of minimum length containing, for each i, at least λ target strings as substrings of S(i). In the shortest λ-cover superstring problem, given a collection X1,...,X(n) of finite sets of strings over a finite alphabet and an integer λ, the task is to find a string of minimum length containing, for each i, at least λ elements of X(i) as substrings. The two problems are polynomially equivalent, and the shortest λ-cover superstring problem is a common generalization of two well known combinatorial optimization problems, the shortest common superstring problem and the set cover problem. We present two approaches to obtain exact or approximate solutions to the shortest λ-superstring and λ-cover superstring problems: one based on integer programming, and a hill-climbing algorithm. An application is given to the computational design of vaccines and the algorithms are applied to experimental data taken from patients infected by H5N1 and HIV-1.

Crossover versus Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems

Directory of Open Access Journals (Sweden)

E. Osaba

2014-01-01

Full Text Available Since their first formulation, genetic algorithms (GAs have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot of research works annually. Although throughout history there have been many studies analyzing various concepts of GAs, in the literature there are few studies that analyze objectively the influence of using blind crossover operators for combinatorial optimization problems. For this reason, in this paper a deep study on the influence of using them is conducted. The study is based on a comparison of nine techniques applied to four well-known combinatorial optimization problems. Six of the techniques are GAs with different configurations, and the remaining three are evolutionary algorithms that focus exclusively on the mutation process. Finally, to perform a reliable comparison of these results, a statistical study of them is made, performing the normal distribution z-test.

Crossover versus Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems

Science.gov (United States)

Osaba, E.; Carballedo, R.; Diaz, F.; Onieva, E.; de la Iglesia, I.; Perallos, A.

2014-01-01

Since their first formulation, genetic algorithms (GAs) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot of research works annually. Although throughout history there have been many studies analyzing various concepts of GAs, in the literature there are few studies that analyze objectively the influence of using blind crossover operators for combinatorial optimization problems. For this reason, in this paper a deep study on the influence of using them is conducted. The study is based on a comparison of nine techniques applied to four well-known combinatorial optimization problems. Six of the techniques are GAs with different configurations, and the remaining three are evolutionary algorithms that focus exclusively on the mutation process. Finally, to perform a reliable comparison of these results, a statistical study of them is made, performing the normal distribution z-test. PMID:25165731

Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining

KAUST Repository

Hussain, Shahid

2016-01-01

This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.

Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining

KAUST Repository

Hussain, Shahid

2016-07-10

This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.

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

Science.gov (United States)

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

2008-07-01

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

Combinatorial Libraries of Bis-Heterocyclic Compounds with Skeletal Diversity

OpenAIRE

Soural, Miroslav; Bouillon, Isabelle; Krchňák, Viktor

2008-01-01

Combinatorial solid-phase synthesis of bis-heterocyclic compounds, characterized by the presence of two heterocyclic cores connected by a spacer of variable length/structure, provided structurally heterogeneous libraries with skeletal diversity. Both heterocyclic rings were assembled on resin in a combinatorial fashion.

Analysis and design of algorithms for combinatorial problems

CERN Document Server

Ausiello, G

1985-01-01

Combinatorial problems have been from the very beginning part of the history of mathematics. By the Sixties, the main classes of combinatorial problems had been defined. During that decade, a great number of research contributions in graph theory had been produced, which laid the foundations for most of the research in graph optimization in the following years. During the Seventies, a large number of special purpose models were developed. The impressive growth of this field since has been strongly determined by the demand of applications and influenced by the technological increases in computing power and the availability of data and software. The availability of such basic tools has led to the feasibility of the exact or well approximate solution of large scale realistic combinatorial optimization problems and has created a number of new combinatorial problems.

Combinatorial Libraries of Bis-Heterocyclic Compounds with Skeletal Diversity

Science.gov (United States)

Soural, Miroslav; Bouillon, Isabelle; Krchňák, Viktor

2009-01-01

Combinatorial solid-phase synthesis of bis-heterocyclic compounds, characterized by the presence of two heterocyclic cores connected by a spacer of variable length/structure, provided structurally heterogeneous libraries with skeletal diversity. Both heterocyclic rings were assembled on resin in a combinatorial fashion. PMID:18811208

Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort.

Science.gov (United States)

Jeschek, Markus; Gerngross, Daniel; Panke, Sven

2016-03-31

Rational flux design in metabolic engineering approaches remains difficult since important pathway information is frequently not available. Therefore empirical methods are applied that randomly change absolute and relative pathway enzyme levels and subsequently screen for variants with improved performance. However, screening is often limited on the analytical side, generating a strong incentive to construct small but smart libraries. Here we introduce RedLibs (Reduced Libraries), an algorithm that allows for the rational design of smart combinatorial libraries for pathway optimization thereby minimizing the use of experimental resources. We demonstrate the utility of RedLibs for the design of ribosome-binding site libraries by in silico and in vivo screening with fluorescent proteins and perform a simple two-step optimization of the product selectivity in the branched multistep pathway for violacein biosynthesis, indicating a general applicability for the algorithm and the proposed heuristics. We expect that RedLibs will substantially simplify the refactoring of synthetic metabolic pathways.

Particle Swarm Optimization applied to combinatorial problem aiming the fuel recharge problem solution in a nuclear reactor; Particle swarm optimization aplicado ao problema combinatorio com vistas a solucao do problema de recarga em um reator nuclear

Energy Technology Data Exchange (ETDEWEB)

Meneses, Anderson Alvarenga de Moura; Schirru, Roberto [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear]. E-mail: ameneses@con.ufrj.br; schirru@lmp.ufrj.br

2005-07-01

This work focuses on the usage the Artificial Intelligence technique Particle Swarm Optimization (PSO) to optimize the fuel recharge at a nuclear reactor. This is a combinatorial problem, in which the search of the best feasible solution is done by minimizing a specific objective function. However, in this first moment it is possible to compare the fuel recharge problem with the Traveling Salesman Problem (TSP), since both of them are combinatorial, with one advantage: the evaluation of the TSP objective function is much more simple. Thus, the proposed methods have been applied to two TSPs: Oliver 30 and Rykel 48. In 1995, KENNEDY and EBERHART presented the PSO technique to optimize non-linear continued functions. Recently some PSO models for discrete search spaces have been developed for combinatorial optimization. Although all of them having different formulation from the ones presented here. In this paper, we use the PSO theory associated with to the Random Keys (RK)model, used in some optimizations with Genetic Algorithms. The Particle Swarm Optimization with Random Keys (PSORK) results from this association, which combines PSO and RK. The adaptations and changings in the PSO aim to allow the usage of the PSO at the nuclear fuel recharge. This work shows the PSORK being applied to the proposed combinatorial problem and the obtained results. (author)

Integer programming and combinatorial optimization : 15th international conference, IPCO 2011, New York NY, USA, June 15-17, 2011 : proceedings

NARCIS (Netherlands)

Günlük, O.; Woeginger, G.J.

2011-01-01

This volume contains the 33 papers presented at IPCO 2011, the 15th Conference on Integer Programming and Combinatorial Optimization, held during June 15–17, 2011 at the IBM T.J. Watson Research Center in New York, USA. IPCO conferences are sponsored by the Mathematical Optimization Society. The

The Combinatorial Trace Method in Action

Science.gov (United States)

Krebs, Mike; Martinez, Natalie C.

2013-01-01

On any finite graph, the number of closed walks of length k is equal to the sum of the kth powers of the eigenvalues of any adjacency matrix. This simple observation is the basis for the combinatorial trace method, wherein we attempt to count (or bound) the number of closed walks of a given length so as to obtain information about the graph's…

A new evolutionary algorithm with LVQ learning for the optimization of combinatory problems as a reload of nuclear reactors

International Nuclear Information System (INIS)

Machado, Marcelo Dornellas

1999-04-01

Genetic algorithms are biologically motivated adaptive systems which have been used, with good results, for function optimization. In this work, a new learning mode, to be used by the Population-Based Incremental Learning (PBIL) algorithm, who combines mechanisms of standard genetic algorithm with simple competitive learning, has the aim to build a new evolutionary algorithm to be used in optimization of numerical problems and combinatorial problems. This new learning mode uses a variable learning rate during the optimization process, constituting a process know as proportional reward. The development of this new algorithm aims its application in the optimization of reload problem of PWR nuclear reactors. This problem can be interpreted as search of a load pattern to be used in the nucleus of the reactor in order to increase the useful life of the nuclear fuel. For the test, two classes of problems are used: numerical problems and combinatorial problem, the major interest relies on the last class. The results achieved with the tests indicate the applicability of the new learning mode, showing its potential as a developing tool in the solution of reload problem. (author)

An improved superconducting neural circuit and its application for a neural network solving a combinatorial optimization problem

International Nuclear Information System (INIS)

Onomi, T; Nakajima, K

2014-01-01

We have proposed a superconducting Hopfield-type neural network for solving the N-Queens problem which is one of combinatorial optimization problems. The sigmoid-shape function of a neuron output is represented by the output of coupled SQUIDs gate consisting of a single-junction and a double-junction SQUIDs. One of the important factors for an improvement of the network performance is an improvement of a threshold characteristic of a neuron circuit. In this paper, we report an improved design of coupled SQUID gates for a superconducting neural network. A step-like function with a steep threshold at a rising edge is desirable for a neuron circuit to solve a combinatorial optimization problem. A neuron circuit is composed of two coupled SQUIDs gates with a cascade connection in order to obtain such characteristics. The designed neuron circuit is fabricated by a 2.5 kA/cm 2 Nb/AlOx/Nb process. The operation of a fabricated neuron circuit is experimentally demonstrated. Moreover, we discuss about the performance of the neural network using the improved neuron circuits and delayed negative self-connections.

Ranked solutions to a class of combinatorial optimizations - with applications in mass spectrometry based peptide sequencing

Science.gov (United States)

Doerr, Timothy; Alves, Gelio; Yu, Yi-Kuo

2006-03-01

Typical combinatorial optimizations are NP-hard; however, for a particular class of cost functions the corresponding combinatorial optimizations can be solved in polynomial time. This suggests a way to efficiently find approximate solutions - - find a transformation that makes the cost function as similar as possible to that of the solvable class. After keeping many high-ranking solutions using the approximate cost function, one may then re-assess these solutions with the full cost function to find the best approximate solution. Under this approach, it is important to be able to assess the quality of the solutions obtained, e.g., by finding the true ranking of kth best approximate solution when all possible solutions are considered exhaustively. To tackle this statistical issue, we provide a systematic method starting with a scaling function generated from the fininte number of high- ranking solutions followed by a convergent iterative mapping. This method, useful in a variant of the directed paths in random media problem proposed here, can also provide a statistical significance assessment for one of the most important proteomic tasks - - peptide sequencing using tandem mass spectrometry data.

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin : Fragment-Based Drug Design Facilitated by Dynamic Combinatorial Chemistry

NARCIS (Netherlands)

Mondal, Milon; Radeva, Nedyalka; Fanlo-Virgos, Hugo; Otto, Sijbren; Klebe, Gerhard; Hirsch, Anna K. H.

2016-01-01

Fragment-based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit-identification strategy for

Efficient high-precision matrix algebra on parallel architectures for nonlinear combinatorial optimization

KAUST Repository

Gunnels, John; Lee, Jon; Margulies, Susan

2010-01-01

We provide a first demonstration of the idea that matrix-based algorithms for nonlinear combinatorial optimization problems can be efficiently implemented. Such algorithms were mainly conceived by theoretical computer scientists for proving efficiency. We are able to demonstrate the practicality of our approach by developing an implementation on a massively parallel architecture, and exploiting scalable and efficient parallel implementations of algorithms for ultra high-precision linear algebra. Additionally, we have delineated and implemented the necessary algorithmic and coding changes required in order to address problems several orders of magnitude larger, dealing with the limits of scalability from memory footprint, computational efficiency, reliability, and interconnect perspectives. © Springer and Mathematical Programming Society 2010.

Efficient high-precision matrix algebra on parallel architectures for nonlinear combinatorial optimization

KAUST Repository

Gunnels, John

2010-06-01

We provide a first demonstration of the idea that matrix-based algorithms for nonlinear combinatorial optimization problems can be efficiently implemented. Such algorithms were mainly conceived by theoretical computer scientists for proving efficiency. We are able to demonstrate the practicality of our approach by developing an implementation on a massively parallel architecture, and exploiting scalable and efficient parallel implementations of algorithms for ultra high-precision linear algebra. Additionally, we have delineated and implemented the necessary algorithmic and coding changes required in order to address problems several orders of magnitude larger, dealing with the limits of scalability from memory footprint, computational efficiency, reliability, and interconnect perspectives. © Springer and Mathematical Programming Society 2010.

Combinatorial chemistry

DEFF Research Database (Denmark)

Nielsen, John

1994-01-01

An overview of combinatorial chemistry is presented. Combinatorial chemistry, sometimes referred to as `irrational drug design,' involves the generation of molecular diversity. The resulting chemical library is then screened for biologically active compounds.......An overview of combinatorial chemistry is presented. Combinatorial chemistry, sometimes referred to as `irrational drug design,' involves the generation of molecular diversity. The resulting chemical library is then screened for biologically active compounds....

Maximum length scale in density based topology optimization

DEFF Research Database (Denmark)

Lazarov, Boyan Stefanov; Wang, Fengwen

2017-01-01

The focus of this work is on two new techniques for imposing maximum length scale in topology optimization. Restrictions on the maximum length scale provide designers with full control over the optimized structure and open possibilities to tailor the optimized design for broader range...... of manufacturing processes by fulfilling the associated technological constraints. One of the proposed methods is based on combination of several filters and builds on top of the classical density filtering which can be viewed as a low pass filter applied to the design parametrization. The main idea...

Accessing Specific Peptide Recognition by Combinatorial Chemistry

DEFF Research Database (Denmark)

Li, Ming

Molecular recognition is at the basis of all processes for life, and plays a central role in many biological processes, such as protein folding, the structural organization of cells and organelles, signal transduction, and the immune response. Hence, my PhD project is entitled “Accessing Specific...... Peptide Recognition by Combinatorial Chemistry”. Molecular recognition is a specific interaction between two or more molecules through noncovalent bonding, such as hydrogen bonding, metal coordination, van der Waals forces, π−π, hydrophobic, or electrostatic interactions. The association involves kinetic....... Combinatorial chemistry was invented in 1980s based on observation of functional aspects of the adaptive immune system. It was employed for drug development and optimization in conjunction with high-throughput synthesis and screening. (chapter 2) Combinatorial chemistry is able to rapidly produce many thousands...

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

Science.gov (United States)

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

2017-08-07

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

Integer linear models with a polynomial number of variables and constraints for some classical combinatorial optimization problems

Directory of Open Access Journals (Sweden)

Nelson Maculan

2003-01-01

Full Text Available We present integer linear models with a polynomial number of variables and constraints for combinatorial optimization problems in graphs: optimum elementary cycles, optimum elementary paths and optimum tree problems.Apresentamos modelos lineares inteiros com um número polinomial de variáveis e restrições para problemas de otimização combinatória em grafos: ciclos elementares ótimos, caminhos elementares ótimos e problemas em árvores ótimas.

Particle swarm optimization with random keys applied to the nuclear reactor reload problem

Energy Technology Data Exchange (ETDEWEB)

Meneses, Anderson Alvarenga de Moura [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE). Programa de Engenharia Nuclear; Fundacao Educacional de Macae (FUNEMAC), RJ (Brazil). Faculdade Professor Miguel Angelo da Silva Santos; Machado, Marcelo Dornellas; Medeiros, Jose Antonio Carlos Canedo; Schirru, Roberto [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE). Programa de Engenharia Nuclear]. E-mails: ameneses@con.ufrj.br; marcelo@lmp.ufrj.br; canedo@lmp.ufrj.br; schirru@lmp.ufrj.br

2007-07-01

In 1995, Kennedy and Eberhart presented the Particle Swarm Optimization (PSO), an Artificial Intelligence metaheuristic technique to optimize non-linear continuous functions. The concept of Swarm Intelligence is based on the socials aspects of intelligence, it means, the ability of individuals to learn with their own experience in a group as well as to take advantage of the performance of other individuals. Some PSO models for discrete search spaces have been developed for combinatorial optimization, although none of them presented satisfactory results to optimize a combinatorial problem as the nuclear reactor fuel reloading problem (NRFRP). In this sense, we developed the Particle Swarm Optimization with Random Keys (PSORK) in previous research to solve Combinatorial Problems. Experiences demonstrated that PSORK performed comparable to or better than other techniques. Thus, PSORK metaheuristic is being applied in optimization studies of the NRFRP for Angra 1 Nuclear Power Plant. Results will be compared with Genetic Algorithms and the manual method provided by a specialist. In this experience, the problem is being modeled for an eight-core symmetry and three-dimensional geometry, aiming at the minimization of the Nuclear Enthalpy Power Peaking Factor as well as the maximization of the cycle length. (author)

Particle swarm optimization with random keys applied to the nuclear reactor reload problem

International Nuclear Information System (INIS)

Meneses, Anderson Alvarenga de Moura; Fundacao Educacional de Macae; Machado, Marcelo Dornellas; Medeiros, Jose Antonio Carlos Canedo; Schirru, Roberto

2007-01-01

In 1995, Kennedy and Eberhart presented the Particle Swarm Optimization (PSO), an Artificial Intelligence metaheuristic technique to optimize non-linear continuous functions. The concept of Swarm Intelligence is based on the socials aspects of intelligence, it means, the ability of individuals to learn with their own experience in a group as well as to take advantage of the performance of other individuals. Some PSO models for discrete search spaces have been developed for combinatorial optimization, although none of them presented satisfactory results to optimize a combinatorial problem as the nuclear reactor fuel reloading problem (NRFRP). In this sense, we developed the Particle Swarm Optimization with Random Keys (PSORK) in previous research to solve Combinatorial Problems. Experiences demonstrated that PSORK performed comparable to or better than other techniques. Thus, PSORK metaheuristic is being applied in optimization studies of the NRFRP for Angra 1 Nuclear Power Plant. Results will be compared with Genetic Algorithms and the manual method provided by a specialist. In this experience, the problem is being modeled for an eight-core symmetry and three-dimensional geometry, aiming at the minimization of the Nuclear Enthalpy Power Peaking Factor as well as the maximization of the cycle length. (author)

Combinatorial Algorithms for Portfolio Optimization Problems - Case of Risk Moderate Investor

Science.gov (United States)

Juarna, A.

2017-03-01

Portfolio optimization problem is a problem of finding optimal combination of n stocks from N ≥ n available stocks that gives maximal aggregate return and minimal aggregate risk. In this paper given N = 43 from the IDX (Indonesia Stock Exchange) group of the 45 most-traded stocks, known as the LQ45, with p = 24 data of monthly returns for each stock, spanned over interval 2013-2014. This problem actually is a combinatorial one where its algorithm is constructed based on two considerations: risk moderate type of investor and maximum allowed correlation coefficient between every two eligible stocks. The main outputs resulted from implementation of the algorithms is a multiple curve of three portfolio’s attributes, e.g. the size, the ratio of return to risk, and the percentage of negative correlation coefficient for every two chosen stocks, as function of maximum allowed correlation coefficient between each two stocks. The output curve shows that the portfolio contains three stocks with ratio of return to risk at 14.57 if the maximum allowed correlation coefficient between every two eligible stocks is negative and contains 19 stocks with maximum allowed correlation coefficient 0.17 to get maximum ratio of return to risk at 25.48.

Lexicographic goal programming and assessment tools for a combinatorial production problem.

Science.gov (United States)

2008-01-01

NP-complete combinatorial problems often necessitate the use of near-optimal solution techniques including : heuristics and metaheuristics. The addition of multiple optimization criteria can further complicate : comparison of these solution technique...

MiYA, an efficient machine-learning workflow in conjunction with the YeastFab assembly strategy for combinatorial optimization of heterologous metabolic pathways in Saccharomyces cerevisiae.

Science.gov (United States)

Zhou, Yikang; Li, Gang; Dong, Junkai; Xing, Xin-Hui; Dai, Junbiao; Zhang, Chong

2018-05-01

Facing boosting ability to construct combinatorial metabolic pathways, how to search the metabolic sweet spot has become the rate-limiting step. We here reported an efficient Machine-learning workflow in conjunction with YeastFab Assembly strategy (MiYA) for combinatorial optimizing the large biosynthetic genotypic space of heterologous metabolic pathways in Saccharomyces cerevisiae. Using β-carotene biosynthetic pathway as example, we first demonstrated that MiYA has the power to search only a small fraction (2-5%) of combinatorial space to precisely tune the expression level of each gene with a machine-learning algorithm of an artificial neural network (ANN) ensemble to avoid over-fitting problem when dealing with a small number of training samples. We then applied MiYA to improve the biosynthesis of violacein. Feed with initial data from a colorimetric plate-based, pre-screened pool of 24 strains producing violacein, MiYA successfully predicted, and verified experimentally, the existence of a strain that showed a 2.42-fold titer improvement in violacein production among 3125 possible designs. Furthermore, MiYA was able to largely avoid the branch pathway of violacein biosynthesis that makes deoxyviolacein, and produces very pure violacein. Together, MiYA combines the advantages of standardized building blocks and machine learning to accelerate the Design-Build-Test-Learn (DBTL) cycle for combinatorial optimization of metabolic pathways, which could significantly accelerate the development of microbial cell factories. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Adaptive treatment-length optimization in spatiobiologically integrated radiotherapy

Science.gov (United States)

Ajdari, Ali; Ghate, Archis; Kim, Minsun

2018-04-01

Recent theoretical research on spatiobiologically integrated radiotherapy has focused on optimization models that adapt fluence-maps to the evolution of tumor state, for example, cell densities, as observed in quantitative functional images acquired over the treatment course. We propose an optimization model that adapts the length of the treatment course as well as the fluence-maps to such imaged tumor state. Specifically, after observing the tumor cell densities at the beginning of a session, the treatment planner solves a group of convex optimization problems to determine an optimal number of remaining treatment sessions, and a corresponding optimal fluence-map for each of these sessions. The objective is to minimize the total number of tumor cells remaining (TNTCR) at the end of this proposed treatment course, subject to upper limits on the biologically effective dose delivered to the organs-at-risk. This fluence-map is administered in future sessions until the next image is available, and then the number of sessions and the fluence-map are re-optimized based on the latest cell density information. We demonstrate via computer simulations on five head-and-neck test cases that such adaptive treatment-length and fluence-map planning reduces the TNTCR and increases the biological effect on the tumor while employing shorter treatment courses, as compared to only adapting fluence-maps and using a pre-determined treatment course length based on one-size-fits-all guidelines.

A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems

Directory of Open Access Journals (Sweden)

Angel A. Juan

2015-12-01

Full Text Available Many combinatorial optimization problems (COPs encountered in real-world logistics, transportation, production, healthcare, financial, telecommunication, and computing applications are NP-hard in nature. These real-life COPs are frequently characterized by their large-scale sizes and the need for obtaining high-quality solutions in short computing times, thus requiring the use of metaheuristic algorithms. Metaheuristics benefit from different random-search and parallelization paradigms, but they frequently assume that the problem inputs, the underlying objective function, and the set of optimization constraints are deterministic. However, uncertainty is all around us, which often makes deterministic models oversimplified versions of real-life systems. After completing an extensive review of related work, this paper describes a general methodology that allows for extending metaheuristics through simulation to solve stochastic COPs. ‘Simheuristics’ allow modelers for dealing with real-life uncertainty in a natural way by integrating simulation (in any of its variants into a metaheuristic-driven framework. These optimization-driven algorithms rely on the fact that efficient metaheuristics already exist for the deterministic version of the corresponding COP. Simheuristics also facilitate the introduction of risk and/or reliability analysis criteria during the assessment of alternative high-quality solutions to stochastic COPs. Several examples of applications in different fields illustrate the potential of the proposed methodology.

Optimization of fracture length in gas/condensate reservoirs

Energy Technology Data Exchange (ETDEWEB)

Mohan, J.; Sharma, M.M.; Pope, G.A. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Texas Univ., Austin, TX (United States)

2006-07-01

A common practice that improves the productivity of gas-condensate reservoirs is hydraulic fracturing. Two important variables that determine the effectiveness of hydraulic fractures are fracture length and fracture conductivity. Although there are no simple guidelines for the optimization of fracture length and the factors that affect it, it is preferable to have an optimum fracture length for a given proppant volume in order to maximize productivity. An optimization study was presented in which fracture length was estimated at wells where productivity was maximized. An analytical expression that takes into account non-Darcy flow and condensate banking was derived. This paper also reviewed the hydraulic fracturing process and discussed previous simulation studies that investigated the effects of well spacing and fracture length on well productivity in low permeability gas reservoirs. The compositional simulation study and results and discussion were also presented. The analytical expression for optimum fracture length, analytical expression with condensate dropout, and equations for the optimum fracture length with non-Darcy flow in the fracture were included in an appendix. The Computer Modeling Group's GEM simulator, an equation-of-state compositional simulator, was used in this study. It was concluded that for cases with non-Darcy flow, the optimum fracture lengths are lower than those obtained with Darcy flow. 18 refs., 5 tabs., 22 figs., 1 appendix.

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

Science.gov (United States)

Batanero, Carmen; And Others

1997-01-01

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

Exploiting Quantum Resonance to Solve Combinatorial Problems

Science.gov (United States)

Zak, Michail; Fijany, Amir

2006-01-01

Quantum resonance would be exploited in a proposed quantum-computing approach to the solution of combinatorial optimization problems. In quantum computing in general, one takes advantage of the fact that an algorithm cannot be decoupled from the physical effects available to implement it. Prior approaches to quantum computing have involved exploitation of only a subset of known quantum physical effects, notably including parallelism and entanglement, but not including resonance. In the proposed approach, one would utilize the combinatorial properties of tensor-product decomposability of unitary evolution of many-particle quantum systems for physically simulating solutions to NP-complete problems (a class of problems that are intractable with respect to classical methods of computation). In this approach, reinforcement and selection of a desired solution would be executed by means of quantum resonance. Classes of NP-complete problems that are important in practice and could be solved by the proposed approach include planning, scheduling, search, and optimal design.

Solution of combinatorial optimization problems by an accelerated hopfield neural network. Kobai kasokugata poppu firudo nyuraru netto ni yoru kumiawase saitekika mondai no kaiho

Energy Technology Data Exchange (ETDEWEB)

Ohori, T.; Yamamoto, H.; Setsu, Nenso; Watanabe, K. (Hokkaido Inst. of Technology, Hokkaido (Japan))

1994-04-20

The accelerated approximate solution of combinatorial optimization problems by symmetry integrating hopfield neural network (NN) has been applied to many combinatorial problems such as the traveling salesman problem, the network planning problem, etc. However, the hopfield NN converges to local minimum solutions very slowly. In this paper, a general inclination model composed by introducing an accelerated parameter to the hopfield model is proposed, and it has been shown that the acceleration parameter can make the model converge to the local minima more quickly. Moreover, simulation experiments for random quadratic combinatorial problems with two and twenty-five variables were carried out. The results show that the acceleration of convergence makes the attraction region of the local minimum change and the accuracy of solution worse. If an initial point is selected around the center of unit hyper cube, solutions with high accuracy not affected by the acceleration parameter can be obtained. 9 refs., 8 figs., 3 tabs.

Combinatorial Strategies for Synthesis and Characterization of Alloy Microstructures over Large Compositional Ranges.

Science.gov (United States)

Li, Yanglin; Jensen, Katharine E; Liu, Yanhui; Liu, Jingbei; Gong, Pan; Scanley, B Ellen; Broadbridge, Christine C; Schroers, Jan

2016-10-10

The exploration of new alloys with desirable properties has been a long-standing challenge in materials science because of the complex relationship between composition and microstructure. In this Research Article, we demonstrate a combinatorial strategy for the exploration of composition dependence of microstructure. This strategy is comprised of alloy library synthesis followed by high-throughput microstructure characterization. As an example, we synthesized a ternary Au-Cu-Si composition library containing over 1000 individual alloys using combinatorial sputtering. We subsequently melted and resolidified the entire library at controlled cooling rates. We used scanning optical microscopy and X-ray diffraction mapping to explore trends in phase formation and microstructural length scale with composition across the library. The integration of combinatorial synthesis with parallelizable analysis methods provides a efficient method for examining vast compositional ranges. The availability of microstructures from this vast composition space not only facilitates design of new alloys by controlling effects of composition on phase selection, phase sequence, length scale, and overall morphology, but also will be instrumental in understanding the complex process of microstructure formation in alloys.

Characterizing the combinatorial beam angle selection problem

Science.gov (United States)

Bangert, Mark; Ziegenhein, Peter; Oelfke, Uwe

2012-10-01

The beam angle selection (BAS) problem in intensity-modulated radiation therapy is often interpreted as a combinatorial optimization problem, i.e. finding the best combination of η beams in a discrete set of candidate beams. It is well established that the combinatorial BAS problem may be solved efficiently with metaheuristics such as simulated annealing or genetic algorithms. However, the underlying parameters of the optimization process, such as the inclusion of non-coplanar candidate beams, the angular resolution in the space of candidate beams, and the number of evaluated beam ensembles as well as the relative performance of different metaheuristics have not yet been systematically investigated. We study these open questions in a meta-analysis of four strategies for combinatorial optimization in order to provide a reference for future research related to the BAS problem in intensity-modulated radiation therapy treatment planning. We introduce a high-performance inverse planning engine for BAS. It performs a full fluence optimization for ≈3600 treatment plans per hour while handling up to 50 GB of dose influence data (≈1400 candidate beams). For three head and neck patients, we compare the relative performance of a genetic, a cross-entropy, a simulated annealing and a naive iterative algorithm. The selection of ensembles with 5, 7, 9 and 11 beams considering either only coplanar or all feasible candidate beams is studied for an angular resolution of 5°, 10°, 15° and 20° in the space of candidate beams. The impact of different convergence criteria is investigated in comparison to a fixed termination after the evaluation of 10 000 beam ensembles. In total, our simulations comprise a full fluence optimization for about 3000 000 treatment plans. All four combinatorial BAS strategies yield significant improvements of the objective function value and of the corresponding dose distributions compared to standard beam configurations with equi

Characterizing the combinatorial beam angle selection problem

International Nuclear Information System (INIS)

Bangert, Mark; Ziegenhein, Peter; Oelfke, Uwe

2012-01-01

The beam angle selection (BAS) problem in intensity-modulated radiation therapy is often interpreted as a combinatorial optimization problem, i.e. finding the best combination of η beams in a discrete set of candidate beams. It is well established that the combinatorial BAS problem may be solved efficiently with metaheuristics such as simulated annealing or genetic algorithms. However, the underlying parameters of the optimization process, such as the inclusion of non-coplanar candidate beams, the angular resolution in the space of candidate beams, and the number of evaluated beam ensembles as well as the relative performance of different metaheuristics have not yet been systematically investigated. We study these open questions in a meta-analysis of four strategies for combinatorial optimization in order to provide a reference for future research related to the BAS problem in intensity-modulated radiation therapy treatment planning. We introduce a high-performance inverse planning engine for BAS. It performs a full fluence optimization for ≈3600 treatment plans per hour while handling up to 50 GB of dose influence data (≈1400 candidate beams). For three head and neck patients, we compare the relative performance of a genetic, a cross-entropy, a simulated annealing and a naive iterative algorithm. The selection of ensembles with 5, 7, 9 and 11 beams considering either only coplanar or all feasible candidate beams is studied for an angular resolution of 5°, 10°, 15° and 20° in the space of candidate beams. The impact of different convergence criteria is investigated in comparison to a fixed termination after the evaluation of 10 000 beam ensembles. In total, our simulations comprise a full fluence optimization for about 3000 000 treatment plans. All four combinatorial BAS strategies yield significant improvements of the objective function value and of the corresponding dose distributions compared to standard beam configurations with equi

Probabilistic methods in combinatorial analysis

CERN Document Server

Sachkov, Vladimir N

2014-01-01

This 1997 work explores the role of probabilistic methods for solving combinatorial problems. These methods not only provide the means of efficiently using such notions as characteristic and generating functions, the moment method and so on but also let us use the powerful technique of limit theorems. The basic objects under investigation are nonnegative matrices, partitions and mappings of finite sets, with special emphasis on permutations and graphs, and equivalence classes specified on sequences of finite length consisting of elements of partially ordered sets; these specify the probabilist

Design and spectroscopic reflectometry characterization of pulsed laser deposition combinatorial libraries

International Nuclear Information System (INIS)

Schenck, Peter K.; Bassim, Nabil D.; Otani, Makoto; Oguchi, Hiroyuki; Green, Martin L.

2007-01-01

The goal of the design of pulsed laser deposition (PLD) combinatorial library films is to optimize the compositional coverage of the films while maintaining a uniform thickness. The deposition pattern of excimer laser PLD films can be modeled with a bimodal cos n distribution. Deposited films were characterized using a spectroscopic reflectometer (250-1000 nm) to map the thickness of both single composition calibration films and combinatorial library films. These distribution functions were used to simulate the composition and thickness of multiple target combinatorial library films. The simulations were correlated with electron-probe microanalysis wavelength-dispersive spectroscopy (EPMA-WDS) composition maps. The composition and thickness of the library films can be fine-tuned by adjusting the laser spot size, fluence, background gas pressure, target geometry and other processing parameters which affect the deposition pattern. Results from compositionally graded combinatorial library films of the ternary system Al 2 O 3 -HfO 2 -Y 2 O 3 are discussed

LDRD final report : robust analysis of large-scale combinatorial applications.

Energy Technology Data Exchange (ETDEWEB)

Carr, Robert D.; Morrison, Todd (University of Colorado, Denver, CO); Hart, William Eugene; Benavides, Nicolas L. (Santa Clara University, Santa Clara, CA); Greenberg, Harvey J. (University of Colorado, Denver, CO); Watson, Jean-Paul; Phillips, Cynthia Ann

2007-09-01

Discrete models of large, complex systems like national infrastructures and complex logistics frameworks naturally incorporate many modeling uncertainties. Consequently, there is a clear need for optimization techniques that can robustly account for risks associated with modeling uncertainties. This report summarizes the progress of the Late-Start LDRD 'Robust Analysis of Largescale Combinatorial Applications'. This project developed new heuristics for solving robust optimization models, and developed new robust optimization models for describing uncertainty scenarios.

Combinatorial commutative algebra

CERN Document Server

Miller, Ezra

2005-01-01

Offers an introduction to combinatorial commutative algebra, focusing on combinatorial techniques for multigraded polynomial rings, semigroup algebras, and determined rings. The chapters in this work cover topics ranging from homological invariants of monomial ideals and their polyhedral resolutions, to tools for studying algebraic varieties.

Dynamic combinatorial chemistry

NARCIS (Netherlands)

Otto, Sijbren; Furlan, Ricardo L.E.; Sanders, Jeremy K.M.

2002-01-01

A combinatorial library that responds to its target by increasing the concentration of strong binders at the expense of weak binders sounds ideal. Dynamic combinatorial chemistry has the potential to achieve exactly this. In this review, we will highlight the unique features that distinguish dynamic

Relationships among hamstring muscle optimal length and hamstring flexibility and strength

OpenAIRE

Xianglin Wan; Feng Qu; William E. Garrett; Hui Liu; Bing Yu

2017-01-01

Background: Hamstring muscle strain injury (hamstring injury) due to excessive muscle strain is one of the most common injuries in sports. The relationships among hamstring muscle optimal lengths and hamstring flexibility and strength were unknown, which limited our understanding of risk factors for hamstring injury. This study was aimed at examining the relationships among hamstring muscle optimal length and flexibility and strength. Methods: Hamstring flexibility and isokinetic strength ...

Relativity in Combinatorial Gravitational Fields

Directory of Open Access Journals (Sweden)

Mao Linfan

2010-04-01

Full Text Available A combinatorial spacetime $(mathscr{C}_G| uboverline{t}$ is a smoothly combinatorial manifold $mathscr{C}$ underlying a graph $G$ evolving on a time vector $overline{t}$. As we known, Einstein's general relativity is suitable for use only in one spacetime. What is its disguise in a combinatorial spacetime? Applying combinatorial Riemannian geometry enables us to present a combinatorial spacetime model for the Universe and suggest a generalized Einstein gravitational equation in such model. Forfinding its solutions, a generalized relativity principle, called projective principle is proposed, i.e., a physics law ina combinatorial spacetime is invariant under a projection on its a subspace and then a spherically symmetric multi-solutions ofgeneralized Einstein gravitational equations in vacuum or charged body are found. We also consider the geometrical structure in such solutions with physical formations, and conclude that an ultimate theory for the Universe maybe established if all such spacetimes in ${f R}^3$. Otherwise, our theory is only an approximate theory and endless forever.

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

Science.gov (United States)

Antolini, Ermete

2017-02-13

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

Combinatorial Nano-Bio Interfaces.

Science.gov (United States)

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

2018-06-08

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

Two is better than one; toward a rational design of combinatorial therapy.

Science.gov (United States)

Chen, Sheng-Hong; Lahav, Galit

2016-12-01

Drug combination is an appealing strategy for combating the heterogeneity of tumors and evolution of drug resistance. However, the rationale underlying combinatorial therapy is often not well established due to lack of understandings of the specific pathways responding to the drugs, and their temporal dynamics following each treatment. Here we present several emerging trends in harnessing properties of biological systems for the optimal design of drug combinations, including the type of drugs, specific concentration, sequence of addition and the temporal schedule of treatments. We highlight recent studies showing different approaches for efficient design of drug combinations including single-cell signaling dynamics, adaption and pathway crosstalk. Finally, we discuss novel and feasible approaches that can facilitate the optimal design of combinatorial therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Combinatorial process optimization for negative photo-imageable spin-on dielectrics and investigation of post-apply bake and post-exposure bake interactions

Science.gov (United States)

Kim, Jihoon; Zhang, Ruzhi M.; Wolfer, Elizabeth; Patel, Bharatkumar K.; Toukhy, Medhat; Bogusz, Zachary; Nagahara, Tatsuro

2012-03-01

Patternable dielectric materials were developed and introduced to reduce semiconductor manufacturing complexity and cost of ownership (CoO). However, the bestowed dual functionalities of photo-imageable spin-on dielectrics (PSOD) put great challenges on the material design and development. In this work, we investigated the combinatorial process optimization for the negative-tone PSOD lithography by employing the Temperature Gradient Plate (TGP) technique which significantly reduced the numbers of wafers processed and minimized the developmental time. We demonstrated that this TGP combinatorial is very efficient at evaluating the effects and interactions of several independent variables such as post-apply bake (PAB) and post-exposure bake (PEB). Unlike most of the conventional photoresists, PAB turned out to have a great effect on the PSOD pattern profiles. Based on our extensive investigation, we observed great correlation between PAB and PEB processes. In this paper, we will discuss the variation of pattern profiles as a matrix of PAB and PEB and propose two possible cross-linking mechanisms for the PSOD materials to explain the unusual experimental results.

Non-unique factorizations algebraic, combinatorial and analytic theory

CERN Document Server

Geroldinger, Alfred

2006-01-01

From its origins in algebraic number theory, the theory of non-unique factorizations has emerged as an independent branch of algebra and number theory. Focused efforts over the past few decades have wrought a great number and variety of results. However, these remain dispersed throughout the vast literature. For the first time, Non-Unique Factorizations: Algebraic, Combinatorial, and Analytic Theory offers a look at the present state of the theory in a single, unified resource.Taking a broad look at the algebraic, combinatorial, and analytic fundamentals, this book derives factorization results and applies them in concrete arithmetical situations using appropriate transfer principles. It begins with a basic introduction that can be understood with knowledge of standard basic algebra. The authors then move to the algebraic theory of monoids, arithmetic theory of monoids, the structure of sets of lengths, additive group theory, arithmetical invariants, and the arithmetic of Krull monoids. They also provide a s...

Combinatorial therapy discovery using mixed integer linear programming.

Science.gov (United States)

Pang, Kaifang; Wan, Ying-Wooi; Choi, William T; Donehower, Lawrence A; Sun, Jingchun; Pant, Dhruv; Liu, Zhandong

2014-05-15

Combinatorial therapies play increasingly important roles in combating complex diseases. Owing to the huge cost associated with experimental methods in identifying optimal drug combinations, computational approaches can provide a guide to limit the search space and reduce cost. However, few computational approaches have been developed for this purpose, and thus there is a great need of new algorithms for drug combination prediction. Here we proposed to formulate the optimal combinatorial therapy problem into two complementary mathematical algorithms, Balanced Target Set Cover (BTSC) and Minimum Off-Target Set Cover (MOTSC). Given a disease gene set, BTSC seeks a balanced solution that maximizes the coverage on the disease genes and minimizes the off-target hits at the same time. MOTSC seeks a full coverage on the disease gene set while minimizing the off-target set. Through simulation, both BTSC and MOTSC demonstrated a much faster running time over exhaustive search with the same accuracy. When applied to real disease gene sets, our algorithms not only identified known drug combinations, but also predicted novel drug combinations that are worth further testing. In addition, we developed a web-based tool to allow users to iteratively search for optimal drug combinations given a user-defined gene set. Our tool is freely available for noncommercial use at http://www.drug.liuzlab.org/. zhandong.liu@bcm.edu Supplementary data are available at Bioinformatics online.

On an extension of a combinatorial identity

Indian Academy of Sciences (India)

to an infinite family of 4-way combinatorial identities. In some particular cases we get even 5-way combinatorial identities which give us four new combinatorial versions of. Göllnitz–Gordon identities. Keywords. n-Color partitions; lattice paths; Frobenius partitions; Göllnitz–Gordon identities; combinatorial interpretations. 1.

Nonparametric combinatorial sequence models.

Science.gov (United States)

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

2011-11-01

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

Automatic generation of combinatorial test data

CERN Document Server

Zhang, Jian; Ma, Feifei

2014-01-01

This book reviews the state-of-the-art in combinatorial testing, with particular emphasis on the automatic generation of test data. It describes the most commonly used approaches in this area - including algebraic construction, greedy methods, evolutionary computation, constraint solving and optimization - and explains major algorithms with examples. In addition, the book lists a number of test generation tools, as well as benchmarks and applications. Addressing a multidisciplinary topic, it will be of particular interest to researchers and professionals in the areas of software testing, combi

Optimization design of strong and tough nacreous nanocomposites through tuning characteristic lengths

Science.gov (United States)

Ni, Yong; Song, Zhaoqiang; Jiang, Hongyuan; Yu, Shu-Hong; He, Linghui

2015-08-01

How nacreous nanocomposites with optimal combinations of stiffness, strength and toughness depend on constituent property and microstructure parameters is studied using a nonlinear shear-lag model. We show that the interfacial elasto-plasticity and the overlapping length between bricks dependent on the brick size and brick staggering mode significantly affect the nonuniformity of the shear stress, the stress-transfer efficiency and thus the failure path. There are two characteristic lengths at which the strength and toughness are optimized respectively. Simultaneous optimization of the strength and toughness is achieved by matching these lengths as close as possible in the nacreous nanocomposite with regularly staggered brick-and-mortar (BM) structure where simultaneous uniform failures of the brick and interface occur. In the randomly staggered BM structure, as the overlapping length is distributed, the nacreous nanocomposite turns the simultaneous uniform failure into progressive interface or brick failure with moderate decrease of the strength and toughness. Specifically there is a parametric range at which the strength and toughness are insensitive to the brick staggering randomness. The obtained results propose a parametric selection guideline based on the length matching for rational design of nacreous nanocomposites. Such guideline explains why nacre is strong and tough while most artificial nacreous nanocomposites aere not.

Iterative optimization of xylose catabolism in Saccharomyces cerevisiae using combinatorial expression tuning.

Science.gov (United States)

Latimer, Luke N; Dueber, John E

2017-06-01

A common challenge in metabolic engineering is rapidly identifying rate-controlling enzymes in heterologous pathways for subsequent production improvement. We demonstrate a workflow to address this challenge and apply it to improving xylose utilization in Saccharomyces cerevisiae. For eight reactions required for conversion of xylose to ethanol, we screened enzymes for functional expression in S. cerevisiae, followed by a combinatorial expression analysis to achieve pathway flux balancing and identification of limiting enzymatic activities. In the next round of strain engineering, we increased the copy number of these limiting enzymes and again tested the eight-enzyme combinatorial expression library in this new background. This workflow yielded a strain that has a ∼70% increase in biomass yield and ∼240% increase in xylose utilization. Finally, we chromosomally integrated the expression library. This library enriched for strains with multiple integrations of the pathway, which likely were the result of tandem integrations mediated by promoter homology. Biotechnol. Bioeng. 2017;114: 1301-1309. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Combinatorial optimization in foundry practice

Science.gov (United States)

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.

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

Science.gov (United States)

Xiang, X D

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

Relationships among hamstring muscle optimal length and hamstring flexibility and strength

Directory of Open Access Journals (Sweden)

Xianglin Wan

2017-09-01

Conclusion: Hamstring flexibility may affect hamstring muscle maximum strain in movements. With similar hamstring flexibility, hamstring muscle maximal strain in a given movement may be different between genders. Hamstring muscle lengths in standing should not be used as an approximation of their optimal lengths in calculation of hamstring muscle strain in musculoskeletal system modeling.

Development of automatic combinatorial system for synthesis of nanoparticles using microreactors

Energy Technology Data Exchange (ETDEWEB)

Watanabe, Kosuke; Maeda, Hideaki [Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, 6-1 Kasuga-koen, Kasuga, Fukuoka, 816-8580 (Japan); Orimoto, Yuuichi; Yamashita, Kenichi; Uehara, Masato; Nakamura, Hiroyuki [Measurement Solution Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 807-1, Shuku, Tosu, Saga, 841-0052 (Japan); Furuya, Takeshi, E-mail: maeda-h@aist.go.jp [Nanosystem Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, 305-8565 (Japan)

2011-10-29

In this study, automatic system for combinatorial synthesis of nanoparticles (NPs) was developed and optimization of reaction parameter for NPs synthesis was performed. Microreactor was employed for kinetic control constantly. Programmable equipments were employed for additional speed up and used a microreactor. Six reaction condition parameters were systematically combined to produce CdSe synthesis condition sets. Reaction conditions of 3404 experimental sets were synthesized and characterized in 1 month. As a result of some multivariate analyses using the numerous and complicated data, we found as follows: 1) neural network is an effective method to analyze data from combinatorial synthesis, 2) weighting evaluation method was effective to find the condition for balanced NP properties.

Combinatorial effects of arginine and fluoride on oral bacteria.

Science.gov (United States)

Zheng, X; Cheng, X; Wang, L; Qiu, W; Wang, S; Zhou, Y; Li, M; Li, Y; Cheng, L; Li, J; Zhou, X; Xu, X

2015-02-01

Dental caries is closely associated with the microbial disequilibrium between acidogenic/aciduric pathogens and alkali-generating commensal residents within the dental plaque. Fluoride is a widely used anticaries agent, which promotes tooth hard-tissue remineralization and suppresses bacterial activities. Recent clinical trials have shown that oral hygiene products containing both fluoride and arginine possess a greater anticaries effect compared with those containing fluoride alone, indicating synergy between fluoride and arginine in caries management. Here, we hypothesize that arginine may augment the ecological benefit of fluoride by enriching alkali-generating bacteria in the plaque biofilm and thus synergizes with fluoride in controlling dental caries. Specifically, we assessed the combinatory effects of NaF/arginine on planktonic and biofilm cultures of Streptococcus mutans, Streptococcus sanguinis, and Porphyromonas gingivalis with checkerboard microdilution assays. The optimal NaF/arginine combinations were selected, and their combinatory effects on microbial composition were further examined in single-, dual-, and 3-species biofilm using bacterial species-specific fluorescence in situ hybridization and quantitative polymerase chain reaction. We found that arginine synergized with fluoride in suppressing acidogenic S. mutans in both planktonic and biofilm cultures. In addition, the NaF/arginine combination synergistically reduced S. mutans but enriched S. sanguinis within the multispecies biofilms. More importantly, the optimal combination of NaF/arginine maintained a "streptococcal pressure" against the potential growth of oral anaerobe P. gingivalis within the alkalized biofilm. Taken together, we conclude that the combinatory application of fluoride and arginine has a potential synergistic effect in maintaining a healthy oral microbial equilibrium and thus represents a promising ecological approach to caries management. © International & American

Combinatorial Hybrid Systems

DEFF Research Database (Denmark)

Larsen, Jesper Abildgaard; Wisniewski, Rafal; Grunnet, Jacob Deleuran

2008-01-01

indicates for a given face the future simplex. In the suggested definition we allow nondeterminacy in form of splitting and merging of solution trajectories. The combinatorial vector field gives rise to combinatorial counterparts of most concepts from dynamical systems, such as duals to vector fields, flow......, flow lines, fixed points and Lyapunov functions. Finally it will be shown how this theory extends to switched dynamical systems and an algorithmic overview of how to do supervisory control will be shown towards the end....

cDREM: inferring dynamic combinatorial gene regulation.

Science.gov (United States)

Wise, Aaron; Bar-Joseph, Ziv

2015-04-01

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

Cryptographic Combinatorial Securities Exchanges

Science.gov (United States)

Thorpe, Christopher; Parkes, David C.

We present a useful new mechanism that facilitates the atomic exchange of many large baskets of securities in a combinatorial exchange. Cryptography prevents information about the securities in the baskets from being exploited, enhancing trust. Our exchange offers institutions who wish to trade large positions a new alternative to existing methods of block trading: they can reduce transaction costs by taking advantage of other institutions’ available liquidity, while third party liquidity providers guarantee execution—preserving their desired portfolio composition at all times. In our exchange, institutions submit encrypted orders which are crossed, leaving a “remainder”. The exchange proves facts about the portfolio risk of this remainder to third party liquidity providers without revealing the securities in the remainder, the knowledge of which could also be exploited. The third parties learn either (depending on the setting) the portfolio risk parameters of the remainder itself, or how their own portfolio risk would change if they were to incorporate the remainder into a portfolio they submit. In one setting, these third parties submit bids on the commission, and the winner supplies necessary liquidity for the entire exchange to clear. This guaranteed clearing, coupled with external price discovery from the primary markets for the securities, sidesteps difficult combinatorial optimization problems. This latter method of proving how taking on the remainder would change risk parameters of one’s own portfolio, without revealing the remainder’s contents or its own risk parameters, is a useful protocol of independent interest.

Combinatorial designs constructions and analysis

CERN Document Server

Stinson, Douglas R

2004-01-01

Created to teach students many of the most important techniques used for constructing combinatorial designs, this is an ideal textbook for advanced undergraduate and graduate courses in combinatorial design theory. The text features clear explanations of basic designs, such as Steiner and Kirkman triple systems, mutual orthogonal Latin squares, finite projective and affine planes, and Steiner quadruple systems. In these settings, the student will master various construction techniques, both classic and modern, and will be well-prepared to construct a vast array of combinatorial designs. Design theory offers a progressive approach to the subject, with carefully ordered results. It begins with simple constructions that gradually increase in complexity. Each design has a construction that contains new ideas or that reinforces and builds upon similar ideas previously introduced. A new text/reference covering all apsects of modern combinatorial design theory. Graduates and professionals in computer science, applie...

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment‐Based Drug Design Facilitated by Dynamic Combinatorial Chemistry

Science.gov (United States)

Mondal, Milon; Radeva, Nedyalka; Fanlo‐Virgós, Hugo; Otto, Sijbren; Klebe, Gerhard

2016-01-01

Abstract Fragment‐based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit‐identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X‐ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis‐acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240‐fold improvement in potency compared to the parent hits. Subsequent X‐ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit‐identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit‐to‐lead optimization. PMID:27400756

Optimization of inhibitory decision rules relative to length and coverage

KAUST Repository

Alsolami, Fawaz; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2012-01-01

The paper is devoted to the study of algorithms for optimization of inhibitory rules relative to the length and coverage. In contrast with usual rules that have on the right-hand side a relation "attribute ≠ value", inhibitory rules have a relation

Combinatorial structures to modeling simple games and applications

Science.gov (United States)

Molinero, Xavier

2017-09-01

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

Dynamic combinatorial libraries : new opportunities in systems chemistry

NARCIS (Netherlands)

Hunt, Rosemary A. R.; Otto, Sijbren; Hunt, Rosemary A.R.

2011-01-01

Combinatorial chemistry is a tool for selecting molecules with special properties. Dynamic combinatorial chemistry started off aiming to be just that. However, unlike ordinary combinatorial chemistry, the interconnectedness of dynamic libraries gives them an extra dimension. An understanding of

Optimization of the Critical Diameter and Average Path Length of Social Networks

Directory of Open Access Journals (Sweden)

Haifeng Du

2017-01-01

Full Text Available Optimizing average path length (APL by adding shortcut edges has been widely discussed in connection with social networks, but the relationship between network diameter and APL is generally ignored in the dynamic optimization of APL. In this paper, we analyze this relationship and transform the problem of optimizing APL into the problem of decreasing diameter to 2. We propose a mathematic model based on a memetic algorithm. Experimental results show that our algorithm can efficiently solve this problem as well as optimize APL.

Boltzmann Oracle for Combinatorial Systems

OpenAIRE

Pivoteau , Carine; Salvy , Bruno; Soria , Michèle

2008-01-01

International audience; Boltzmann random generation applies to well-defined systems of recursive combinatorial equations. It relies on oracles giving values of the enumeration generating series inside their disk of convergence. We show that the combinatorial systems translate into numerical iteration schemes that provide such oracles. In particular, we give a fast oracle based on Newton iteration.

Combinatorial Interpretation of General Eulerian Numbers

OpenAIRE

Tingyao Xiong; Jonathan I. Hall; Hung-Ping Tsao

2014-01-01

Since 1950s, mathematicians have successfully interpreted the traditional Eulerian numbers and $q-$Eulerian numbers combinatorially. In this paper, the authors give a combinatorial interpretation to the general Eulerian numbers defined on general arithmetic progressions { a, a+d, a+2d,...}.

Systematization of Accurate Discrete Optimization Methods

Directory of Open Access Journals (Sweden)

V. A. Ovchinnikov

2015-01-01

Full Text Available The object of study of this paper is to define accurate methods for solving combinatorial optimization problems of structural synthesis. The aim of the work is to systemize the exact methods of discrete optimization and define their applicability to solve practical problems.The article presents the analysis, generalization and systematization of classical methods and algorithms described in the educational and scientific literature.As a result of research a systematic presentation of combinatorial methods for discrete optimization described in various sources is given, their capabilities are described and properties of the tasks to be solved using the appropriate methods are specified.

The Optimization of the Data Packet Length in Adaptive Radio Networks

Directory of Open Access Journals (Sweden)

Anatolii P. Voiter

2017-10-01

Full Text Available Background. Development of methods and means of the adaptive management of the radio networks bandwidth with competitive access to the radio channel. Objective. The aim of the paper is to determine the packet length effect on the effective radio networks transmission rate with taking into account the parameters, formats, and procedures of the physical and link levels at using the MAC protocol with a rigid strategy of competitive access to the radio channel. Methods. The goal is achieved by creating and analyzing the mathematical model of the effective transmission rate in radio networks. The model is described by the equation for the effective transmission rate, which is the function of both the probability of the conflict-free transmission of the MAC protocol and the coefficient of the data packet size deviation from the optimal for LLC protocol. Results. It is proved that there is the optimal deviation of the data packet length for each MAC protocol traffic intensity value, which provides the most effective transfer rate. This makes the possibility for adaptive management of the radio bandwidth by applying a pre-calculated deviation of the data packet size in dependence on the traffic intensity. Conclusions. The proposed mathematical model is the tool for calculation of both the radio bandwidth network capacity and the optimal deviation of the data packet length at adaptive management of competitive access to a radio channel with a rigid strategy at conditions of the significant fluctuation in traffic intensity.

Combinatorial synthesis of natural products

DEFF Research Database (Denmark)

Nielsen, John

2002-01-01

Combinatorial syntheses allow production of compound libraries in an expeditious and organized manner immediately applicable for high-throughput screening. Natural products possess a pedigree to justify quality and appreciation in drug discovery and development. Currently, we are seeing a rapid...... increase in application of natural products in combinatorial chemistry and vice versa. The therapeutic areas of infectious disease and oncology still dominate but many new areas are emerging. Several complex natural products have now been synthesised by solid-phase methods and have created the foundation...... for preparation of combinatorial libraries. In other examples, natural products or intermediates have served as building blocks or scaffolds in the synthesis of complex natural products, bioactive analogues or designed hybrid molecules. Finally, structural motifs from the biologically active parent molecule have...

Tumor-targeting peptides from combinatorial libraries*

Science.gov (United States)

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

2018-01-01

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

Ant colony optimization and constraint programming

CERN Document Server

Solnon, Christine

2013-01-01

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts. The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment-Based Drug Design Facilitated by Dynamic Combinatorial Chemistry.

Science.gov (United States)

Mondal, Milon; Radeva, Nedyalka; Fanlo-Virgós, Hugo; Otto, Sijbren; Klebe, Gerhard; Hirsch, Anna K H

2016-08-01

Fragment-based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit-identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X-ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis-acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240-fold improvement in potency compared to the parent hits. Subsequent X-ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit-identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit-to-lead optimization. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Combinatorial programming of human neuronal progenitors using magnetically-guided stoichiometric mRNA delivery.

Science.gov (United States)

Azimi, Sayyed M; Sheridan, Steven D; Ghannad-Rezaie, Mostafa; Eimon, Peter M; Yanik, Mehmet Fatih

2018-05-01

Identification of optimal transcription-factor expression patterns to direct cellular differentiation along a desired pathway presents significant challenges. We demonstrate massively combinatorial screening of temporally-varying mRNA transcription factors to direct differentiation of neural progenitor cells using a dynamically-reconfigurable magnetically-guided spotting technology for localizing mRNA, enabling experiments on millimetre size spots. In addition, we present a time-interleaved delivery method that dramatically reduces fluctuations in the delivered transcription-factor copy-numbers per cell. We screened combinatorial and temporal delivery of a pool of midbrain-specific transcription factors to augment the generation of dopaminergic neurons. We show that the combinatorial delivery of LMX1A, FOXA2 and PITX3 is highly effective in generating dopaminergic neurons from midbrain progenitors. We show that LMX1A significantly increases TH -expression levels when delivered to neural progenitor cells either during proliferation or after induction of neural differentiation, while FOXA2 and PITX3 increase expression only when delivered prior to induction, demonstrating temporal dependence of factor addition. © 2018, Azimi et al.

Number systems and combinatorial problems

OpenAIRE

Yordzhev, Krasimir

2014-01-01

The present work has been designed for students in secondary school and their teachers in mathematics. We will show how with the help of our knowledge of number systems we can solve problems from other fields of mathematics for example in combinatorial analysis and most of all when proving some combinatorial identities. To demonstrate discussed in this article method we have chosen several suitable mathematical tasks.

Introduction to combinatorial geometry

International Nuclear Information System (INIS)

Gabriel, T.A.; Emmett, M.B.

1985-01-01

The combinatorial geometry package as used in many three-dimensional multimedia Monte Carlo radiation transport codes, such as HETC, MORSE, and EGS, is becoming the preferred way to describe simple and complicated systems. Just about any system can be modeled using the package with relatively few input statements. This can be contrasted against the older style geometry packages in which the required input statements could be large even for relatively simple systems. However, with advancements come some difficulties. The users of combinatorial geometry must be able to visualize more, and, in some instances, all of the system at a time. Errors can be introduced into the modeling which, though slight, and at times hard to detect, can have devastating effects on the calculated results. As with all modeling packages, the best way to learn the combinatorial geometry is to use it, first on a simple system then on more complicated systems. The basic technique for the description of the geometry consists of defining the location and shape of the various zones in terms of the intersections and unions of geometric bodies. The geometric bodies which are generally included in most combinatorial geometry packages are: (1) box, (2) right parallelepiped, (3) sphere, (4) right circular cylinder, (5) right elliptic cylinder, (6) ellipsoid, (7) truncated right cone, (8) right angle wedge, and (9) arbitrary polyhedron. The data necessary to describe each of these bodies are given. As can be easily noted, there are some subsets included for simplicity

Estimation of tissue stiffness, reflex activity, optimal muscle length and slack length in stroke patients using an electromyography driven antagonistic wrist model.

Science.gov (United States)

de Gooijer-van de Groep, Karin L; de Vlugt, Erwin; van der Krogt, Hanneke J; Helgadóttir, Áróra; Arendzen, J Hans; Meskers, Carel G M; de Groot, Jurriaan H

2016-06-01

About half of all chronic stroke patients experience loss of arm function coinciding with increased stiffness, reduced range of motion and a flexed wrist due to a change in neural and/or structural tissue properties. Quantitative assessment of these changes is of clinical importance, yet not trivial. The goal of this study was to quantify the neural and structural properties contributing to wrist joint stiffness and to compare these properties between healthy subjects and stroke patients. Stroke patients (n=32) and healthy volunteers (n=14) were measured using ramp-and-hold rotations applied to the wrist joint by a haptic manipulator. Neural (reflexive torque) and structural (connective tissue stiffness and slack lengths and (contractile) optimal muscle lengths) parameters were estimated using an electromyography driven antagonistic wrist model. Kruskal-Wallis analysis with multiple comparisons was used to compare results between healthy subjects, stroke patients with modified Ashworth score of zero and stroke patients with modified Ashworth score of one or more. Stroke patients with modified Ashworth score of one or more differed from healthy controls (Pslack length of connective tissue of the flexor muscles. Non-invasive quantitative analysis, including estimation of optimal muscle lengths, enables to identify neural and non-neural changes in chronic stroke patients. Monitoring these changes in time is important to understand the recovery process and to optimize treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Introduction to combinatorial designs

CERN Document Server

Wallis, WD

2007-01-01

Combinatorial theory is one of the fastest growing areas of modern mathematics. Focusing on a major part of this subject, Introduction to Combinatorial Designs, Second Edition provides a solid foundation in the classical areas of design theory as well as in more contemporary designs based on applications in a variety of fields. After an overview of basic concepts, the text introduces balanced designs and finite geometries. The author then delves into balanced incomplete block designs, covering difference methods, residual and derived designs, and resolvability. Following a chapter on the e

Use of combinatorial chemistry to speed drug discovery.

Science.gov (United States)

Rádl, S

1998-10-01

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

Optimization by GRASP greedy randomized adaptive search procedures

CERN Document Server

Resende, Mauricio G C

2016-01-01

This is the first book to cover GRASP (Greedy Randomized Adaptive Search Procedures), a metaheuristic that has enjoyed wide success in practice with a broad range of applications to real-world combinatorial optimization problems. The state-of-the-art coverage and carefully crafted pedagogical style lends this book highly accessible as an introductory text not only to GRASP, but also to combinatorial optimization, greedy algorithms, local search, and path-relinking, as well as to heuristics and metaheuristics, in general. The focus is on algorithmic and computational aspects of applied optimization with GRASP with emphasis given to the end-user, providing sufficient information on the broad spectrum of advances in applied optimization with GRASP. For the more advanced reader, chapters on hybridization with path-relinking and parallel and continuous GRASP present these topics in a clear and concise fashion. Additionally, the book offers a very complete annotated bibliography of GRASP and combinatorial optimizat...

Synthesis of new water-soluble metal-binding polymers: Combinatorial chemistry approach. 1998 annual progress report

International Nuclear Information System (INIS)

Kurth, M.J.; Miller, R.B.; Sawan, S.; Smith, B.F.

1998-01-01

'(1) Develop rapid discovery and optimization approaches to new water-soluble chelating polymers for use in Polymer Filtration (PF) systems, and (2) evaluate the concept of using water and organic soluble polymers as new solid supports for combinatorial synthesis. Polymer Filtration (PF), which uses water-soluble metal-binding polymers to sequester metal ions in dilute solution with ultrafiltration (UF) to separate the polymers, is a new technology to selectively remove or recover hazardous and valuable metal ions. Future directions in PF must include rapid development, testing, and characterization of new metal-binding polymers. Thus, the authors are building upon and adapting the combinatorial chemistry approach developed for rapid molecule generation for the drug industry to the rapid development of new chelating polymers. The authors have focused on four areas including the development of: (1) synthetic procedures, (2) small ultrafiltration equipment compatible with organic- and aqueous-based combinatorial synthesis, (3) rapid assay techniques, and (4) polymer characterization techniques.'

Asessing for Structural Understanding in Childrens' Combinatorial Problem Solving.

Science.gov (United States)

English, Lyn

1999-01-01

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

Dynamic combinatorial chemistry with diselenides and disulfides in water

DEFF Research Database (Denmark)

Rasmussen, Brian; Sørensen, Anne; Gotfredsen, Henrik

2014-01-01

Diselenide exchange is introduced as a reversible reaction in dynamic combinatorial chemistry in water. At neutral pH, diselenides are found to mix with disulfides and form dynamic combinatorial libraries of diselenides, disulfides, and selenenylsulfides. This journal is......Diselenide exchange is introduced as a reversible reaction in dynamic combinatorial chemistry in water. At neutral pH, diselenides are found to mix with disulfides and form dynamic combinatorial libraries of diselenides, disulfides, and selenenylsulfides. This journal is...

Tap-length optimization of adaptive filters used in stereophonic acoustic echo cancellation

DEFF Research Database (Denmark)

Kar, Asutosh; Swamy, M.N.S.

2017-01-01

An adaptive filter with a large number of weights or taps is necessary for stereophonic acoustic echo cancellation (SAEC), depending on the room impulse response and acoustic path where the cancellation is performed. However, a large tap-length results in slow convergence and increases...... the complexity of the tapped delay line structure for FIR adaptive filters. To overcome this problem, there is a need for an optimum tap-length-estimation algorithm that provides better convergence for the adaptive filters used in SAEC. This paper presents a solution to the problem of balancing convergence...... and steady-state performance of long length adaptive filters used for SAEC by proposing a new tap-length-optimization algorithm. The optimum tap length and step size of the adaptive filter are derived considering an impulse response with an exponentially-decaying envelope, which models a wide range...

Nonlinear Multidimensional Assignment Problems Efficient Conic Optimization Methods and Applications

Science.gov (United States)

2015-06-24

WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Arizona State University School of Mathematical & Statistical Sciences 901 S...SUPPLEMENTARY NOTES 14. ABSTRACT The major goals of this project were completed: the exact solution of previously unsolved challenging combinatorial optimization... combinatorial optimization problem, the Directional Sensor Problem, was solved in two ways. First, heuristically in an engineering fashion and second, exactly

Fourier analysis in combinatorial number theory

International Nuclear Information System (INIS)

Shkredov, Il'ya D

2010-01-01

In this survey applications of harmonic analysis to combinatorial number theory are considered. Discussion topics include classical problems of additive combinatorics, colouring problems, higher-order Fourier analysis, theorems about sets of large trigonometric sums, results on estimates for trigonometric sums over subgroups, and the connection between combinatorial and analytic number theory. Bibliography: 162 titles.

Fourier analysis in combinatorial number theory

Energy Technology Data Exchange (ETDEWEB)

Shkredov, Il' ya D [M. V. Lomonosov Moscow State University, Moscow (Russian Federation)

2010-09-16

In this survey applications of harmonic analysis to combinatorial number theory are considered. Discussion topics include classical problems of additive combinatorics, colouring problems, higher-order Fourier analysis, theorems about sets of large trigonometric sums, results on estimates for trigonometric sums over subgroups, and the connection between combinatorial and analytic number theory. Bibliography: 162 titles.

Optimization of inhibitory decision rules relative to length and coverage

KAUST Repository

Alsolami, Fawaz

2012-01-01

The paper is devoted to the study of algorithms for optimization of inhibitory rules relative to the length and coverage. In contrast with usual rules that have on the right-hand side a relation "attribute ≠ value", inhibitory rules have a relation "attribute = value" on the right-hand side. The considered algorithms are based on extensions of dynamic programming. © 2012 Springer-Verlag.

Solid-Phase Synthesis of Small Molecule Libraries using Double Combinatorial Chemistry

DEFF Research Database (Denmark)

Nielsen, John; Jensen, Flemming R.

1997-01-01

The first synthesis of a combinatorial library using double combinatorial chemistry is presented. Coupling of unprotected Fmoc-tyrosine to the solid support was followed by Mitsunobu O-alkylation. Introduction of a diacid linker yields a system in which the double combinatorial step can be demons......The first synthesis of a combinatorial library using double combinatorial chemistry is presented. Coupling of unprotected Fmoc-tyrosine to the solid support was followed by Mitsunobu O-alkylation. Introduction of a diacid linker yields a system in which the double combinatorial step can...

Optimization of path length stretching in Monte Carlo calculations for non-leakage problems

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J.E. [Delft Univ. of Technology (Netherlands)

2005-07-01

Path length stretching (or exponential biasing) is a well known variance reduction technique in Monte Carlo calculations. It can especially be useful in shielding problems where particles have to penetrate a lot of material before being tallied. Several authors sought for optimization of the path length stretching parameter for detection of the leakage of neutrons from a slab. Here the adjoint function behaves as a single exponential function and can well be used to determine the stretching parameter. In this paper optimization is sought for a detector embedded in the system, which changes the adjoint function in the detector drastically. From literature it is known that the combination of path length stretching and angular biasing can result in appreciable variance reduction. However, angular biasing is not generally available in general purpose Monte Carlo codes and therefore we want to restrict ourselves to the application of pure path length stretching and finding optimum parameters for that. Nonetheless, the starting point for our research is the zero-variance scheme. In order to study the solution in detail the simplified monoenergetic two-direction model is adopted, which allows analytical solutions and can still be used in a Monte Carlo simulation. Knowing the zero-variance solution analytically, it is shown how optimum path length stretching parameters can be derived from it. It results in path length shrinking in the detector. Results for the variance in the detector response are shown in comparison with other patterns for the stretching parameter. The effect of anisotropic scattering on the path length stretching parameter is taken into account. (author)

Local formulae for combinatorial Pontryagin classes

International Nuclear Information System (INIS)

Gaifullin, Alexander A

2004-01-01

Let p(|K|) be the characteristic class of a combinatorial manifold K given by a polynomial p in the rational Pontryagin classes of K. We prove that for any polynomial p there is a function taking each combinatorial manifold K to a cycle z p (K) in its rational simplicial chains such that: 1) the Poincare dual of z p (K) represents the cohomology class p(|K|); 2) the coefficient of each simplex Δ in the cycle z p (K) is determined solely by the combinatorial type of linkΔ. We explicitly describe all such functions for the first Pontryagin class. We obtain estimates for the denominators of the coefficients of the simplices in the cycles z p (K)

Modeling length of stay as an optimized two-dass prediction problem

NARCIS (Netherlands)

Verduijn, M.; Peek, N.; Voorbraak, F.; de Jonge, E.; de Mol, B. A. J. M.

2007-01-01

Objectives. To develop a predictive model for the outcome length of stay at the Intensive Care Unit (ICU LOS), including the choice of an optimal dichotomization threshold for this outcome. Reduction of prediction problems of this type of outcome to a two-doss problem is a common strategy to

Heterogenous phase as a mean in combinatorial chemistry

International Nuclear Information System (INIS)

Abdel-Hamid, S.G.

2007-01-01

Combinatorial chemistry is a rapid and inexpensive technique for the synthesis of hundreds of thousands of organic compounds of potential medicinal activity. In the past few decades a large number of combinatorial libraries have been constructed, and significantly supplement the chemical diversity of the traditional collections of the potentially active medicinal compounds. Solid phase synthesis was used to enrich the combinatorial chemistry libraries, through the use of solid supports (resins) and their modified forms. Most of the new libraries of compounds appeared recently, were synthesized by the use of solid-phase. Solid-phase combinatorial chemistry (SPCC) is now considered as an outstanding branch in pharmaceutical chemistry research and used extensively as a tool for drug discovery within the context of high-throughput chemical synthesis. The best pure libraries synthesized by the use of solid phase combinatorial chemistry (SPCC) may well be those of intermediate complexity that are free of artifact-causing nuisance compounds. (author)

Two combinatorial optimization problems for SNP discovery using base-specific cleavage and mass spectrometry.

Science.gov (United States)

Chen, Xin; Wu, Qiong; Sun, Ruimin; Zhang, Louxin

2012-01-01

The discovery of single-nucleotide polymorphisms (SNPs) has important implications in a variety of genetic studies on human diseases and biological functions. One valuable approach proposed for SNP discovery is based on base-specific cleavage and mass spectrometry. However, it is still very challenging to achieve the full potential of this SNP discovery approach. In this study, we formulate two new combinatorial optimization problems. While both problems are aimed at reconstructing the sample sequence that would attain the minimum number of SNPs, they search over different candidate sequence spaces. The first problem, denoted as SNP - MSP, limits its search to sequences whose in silico predicted mass spectra have all their signals contained in the measured mass spectra. In contrast, the second problem, denoted as SNP - MSQ, limits its search to sequences whose in silico predicted mass spectra instead contain all the signals of the measured mass spectra. We present an exact dynamic programming algorithm for solving the SNP - MSP problem and also show that the SNP - MSQ problem is NP-hard by a reduction from a restricted variation of the 3-partition problem. We believe that an efficient solution to either problem above could offer a seamless integration of information in four complementary base-specific cleavage reactions, thereby improving the capability of the underlying biotechnology for sensitive and accurate SNP discovery.

MIFT: GIFT Combinatorial Geometry Input to VCS Code

Science.gov (United States)

1977-03-01

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

Combinatorial stresses kill pathogenic Candida species

Science.gov (United States)

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

2012-01-01

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

Toward Chemical Implementation of Encoded Combinatorial Libraries

DEFF Research Database (Denmark)

Nielsen, John; Janda, Kim D.

1994-01-01

The recent application of "combinatorial libraries" to supplement existing drug screening processes might simplify and accelerate the search for new lead compounds or drugs. Recently, a scheme for encoded combinatorial chemistry was put forward to surmount a number of the limitations possessed...

A New Approach for Proving or Generating Combinatorial Identities

Science.gov (United States)

Gonzalez, Luis

2010-01-01

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

Combinatorial methods with computer applications

CERN Document Server

Gross, Jonathan L

2007-01-01

Combinatorial Methods with Computer Applications provides in-depth coverage of recurrences, generating functions, partitions, and permutations, along with some of the most interesting graph and network topics, design constructions, and finite geometries. Requiring only a foundation in discrete mathematics, it can serve as the textbook in a combinatorial methods course or in a combined graph theory and combinatorics course.After an introduction to combinatorics, the book explores six systematic approaches within a comprehensive framework: sequences, solving recurrences, evaluating summation exp

The priming of basic combinatory responses in MEG.

Science.gov (United States)

Blanco-Elorrieta, Esti; Ferreira, Victor S; Del Prato, Paul; Pylkkänen, Liina

2018-01-01

Priming has been a powerful tool for the study of human memory and especially the memory representations relevant for language. However, although it is well established that lexical access can be primed, we do not know exactly what types of computations can be primed above the word level. This work took a neurobiological approach and assessed the ways in which the complex representation of a minimal combinatory phrase, such as red boat, can be primed, as evidenced by the spatiotemporal profiles of magnetoencephalography (MEG) signals. Specifically, we built upon recent progress on the neural signatures of phrasal composition and tested whether the brain activities implicated for the basic combination of two words could be primed. In two experiments, MEG was recorded during a picture naming task where the prime trials were designed to replicate previously reported combinatory effects and the target trials to test whether those combinatory effects could be primed. The manipulation of the primes was successful in eliciting larger activity for adjective-noun combinations than single nouns in left anterior temporal and ventromedial prefrontal cortices, replicating prior MEG studies on parallel contrasts. Priming of similarly timed activity was observed during target trials in anterior temporal cortex, but only when the prime and target shared an adjective. No priming in temporal cortex was observed for single word repetition and two control tasks showed that the priming effect was not elicited if the prime pictures were simply viewed but not named. In sum, this work provides evidence that very basic combinatory operations can be primed, with the necessity for some lexical overlap between prime and target suggesting combinatory conceptual, as opposed to syntactic processing. Both our combinatory and priming effects were early, onsetting between 100 and 150ms after picture onset and thus are likely to reflect the very earliest planning stages of a combinatory message

In vivo myograph measurement of muscle contraction at optimal length

Directory of Open Access Journals (Sweden)

Ahmed Aminul

2007-01-01

Full Text Available Abstract Background Current devices for measuring muscle contraction in vivo have limited accuracy in establishing and re-establishing the optimum muscle length. They are variable in the reproducibility to determine the muscle contraction at this length, and often do not maintain precise conditions during the examination. Consequently, for clinical testing only semi-quantitative methods have been used. Methods We present a newly developed myograph, an accurate measuring device for muscle contraction, consisting of three elements. Firstly, an element for adjusting the axle of the device and the physiological axis of muscle contraction; secondly, an element to accurately position and reposition the extremity of the muscle; and thirdly, an element for the progressive pre-stretching and isometric locking of the target muscle. Thus it is possible to examine individual in vivo muscles in every pre-stretched, specified position, to maintain constant muscle-length conditions, and to accurately re-establish the conditions of the measurement process at later sessions. Results In a sequence of experiments the force of contraction of the muscle at differing stretching lengths were recorded and the forces determined. The optimum muscle length for maximal force of contraction was established. In a following sequence of experiments with smaller graduations around this optimal stretching length an increasingly accurate optimum muscle length for maximal force of contraction was determined. This optimum length was also accurately re-established at later sessions. Conclusion We have introduced a new technical solution for valid, reproducible in vivo force measurements on every possible point of the stretching curve. Thus it should be possible to study the muscle contraction in vivo to the same level of accuracy as is achieved in tests with in vitro organ preparations.

Submodular functions and optimization

CERN Document Server

Fujishige, Satoru

2005-01-01

It has widely been recognized that submodular functions play essential roles in efficiently solvable combinatorial optimization problems. Since the publication of the 1st edition of this book fifteen years ago, submodular functions have been showing further increasing importance in optimization, combinatorics, discrete mathematics, algorithmic computer science, and algorithmic economics, and there have been made remarkable developments of theory and algorithms in submodular functions. The 2nd edition of the book supplements the 1st edition with a lot of remarks and with new two chapters: "Submodular Function Minimization" and "Discrete Convex Analysis." The present 2nd edition is still a unique book on submodular functions, which is essential to students and researchers interested in combinatorial optimization, discrete mathematics, and discrete algorithms in the fields of mathematics, operations research, computer science, and economics. Key features: - Self-contained exposition of the theory of submodular ...

The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem

Directory of Open Access Journals (Sweden)

Denis Pinha

2016-11-01

Full Text Available This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.

Information-theoretic lengths of Jacobi polynomials

Energy Technology Data Exchange (ETDEWEB)

Guerrero, A; Dehesa, J S [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, Granada (Spain); Sanchez-Moreno, P, E-mail: agmartinez@ugr.e, E-mail: pablos@ugr.e, E-mail: dehesa@ugr.e [Instituto ' Carlos I' de Fisica Teorica y Computacional, Universidad de Granada, Granada (Spain)

2010-07-30

The information-theoretic lengths of the Jacobi polynomials P{sup ({alpha}, {beta})}{sub n}(x), which are information-theoretic measures (Renyi, Shannon and Fisher) of their associated Rakhmanov probability density, are investigated. They quantify the spreading of the polynomials along the orthogonality interval [- 1, 1] in a complementary but different way as the root-mean-square or standard deviation because, contrary to this measure, they do not refer to any specific point of the interval. The explicit expressions of the Fisher length are given. The Renyi lengths are found by the use of the combinatorial multivariable Bell polynomials in terms of the polynomial degree n and the parameters ({alpha}, {beta}). The Shannon length, which cannot be exactly calculated because of its logarithmic functional form, is bounded from below by using sharp upper bounds to general densities on [- 1, +1] given in terms of various expectation values; moreover, its asymptotics is also pointed out. Finally, several computational issues relative to these three quantities are carefully analyzed.

Combinatorial effect of mutagenesis and medium component optimization on Bacillus amyloliquefaciens antifungal activity and efficacy in eradicating Botrytis cinerea.

Science.gov (United States)

Masmoudi, Fatma; Ben Khedher, Saoussen; Kamoun, Amel; Zouari, Nabil; Tounsi, Slim; Trigui, Mohamed

2017-04-01

This work is directed towards Bacillus amyloliquefaciens strain BLB371 metabolite production for biocontrol of fungal phytopathogens. In order to maximise antifungal metabolite production by this strain, two approaches were combined: random mutagenesis and medium component optimization. After three rounds of mutagenesis, a hyper active mutant, named M3-7, was obtained. It produces 7 fold more antifungal metabolites (1800AU/mL) than the wild strain in MC medium. A hybrid design was applied to optimise a new medium to enhance antifungal metabolite production by M3-7. The new optimized medium (35g/L of peptone, 32.5g/L of sucrose, 10.5g/L of yeast extract, 2.4g/L of KH 2 PO 4 , 1.3g/L of MgSO 4 and 23mg/L of MnSO 4 ) achieved 1.62 fold enhancement in antifungal compound production (3000AU/mL) by this mutant, compared to that achieved in MC medium. Therefore, combinatory effect of these two approaches (mutagenesis and medium component optimization) allowed 12 fold improvement in antifungal activity (from 250UA/mL to 3000UA/mL). This improvement was confirmed against several phytopathogenic fungi with an increase of MIC and MFC over than 50%. More interestingly, a total eradication of gray mold was obtained on tomato fruits infected by Botrytis cinerea and treated by M3-7, compared to those treated by BLB371. From the practical point of view, combining random mutagenesis and medium optimization could be considered as an excellent tool for obtaining promising biological products useful against phytopathogenic fungi. Copyright © 2017 Elsevier GmbH. All rights reserved.

Topology optimization of a flexible multibody system with variable-length bodies described by ALE–ANCF

DEFF Research Database (Denmark)

Sun, Jialiang; Tian, Qiang; Hu, Haiyan

2018-01-01

Recent years have witnessed the application of topology optimization to flexible multibody systems (FMBS) so as to enhance their dynamic performances. In this study, an explicit topology optimization approach is proposed for an FMBS with variable-length bodies via the moving morphable components...... (MMC). Using the arbitrary Lagrangian–Eulerian (ALE) formulation, the thin plate elements of the absolute nodal coordinate formulation (ANCF) are used to describe the platelike bodies with variable length. For the thin plate element of ALE–ANCF, the elastic force and additional inertial force, as well...

Morphological Constraints on Cerebellar Granule Cell Combinatorial Diversity.

Science.gov (United States)

Gilmer, Jesse I; Person, Abigail L

2017-12-13

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

Maximization of Tsallis entropy in the combinatorial formulation

International Nuclear Information System (INIS)

Suyari, Hiroki

2010-01-01

This paper presents the mathematical reformulation for maximization of Tsallis entropy S q in the combinatorial sense. More concretely, we generalize the original derivation of Maxwell-Boltzmann distribution law to Tsallis statistics by means of the corresponding generalized multinomial coefficient. Our results reveal that maximization of S 2-q under the usual expectation or S q under q-average using the escort expectation are naturally derived from the combinatorial formulations for Tsallis statistics with respective combinatorial dualities, that is, one for additive duality and the other for multiplicative duality.

Jack superpolynomials: physical and combinatorial definitions

International Nuclear Information System (INIS)

Desrosiers, P.; Mathieu, P.; Lapointe, L.

2004-01-01

Jack superpolynomials are eigenfunctions of the supersymmetric extension of the quantum trigonometric Calogero-Moser-Sutherland Hamiltonian. They are orthogonal with respect to the scalar product, dubbed physical, that is naturally induced by this quantum-mechanical problem. But Jack superpolynomials can also be defined more combinatorially, starting from the multiplicative bases of symmetric superpolynomials, enforcing orthogonality with respect to a one-parameter deformation of the combinatorial scalar product. Both constructions turn out to be equivalent. (author)

Torus actions, combinatorial topology, and homological algebra

International Nuclear Information System (INIS)

Bukhshtaber, V M; Panov, T E

2000-01-01

This paper is a survey of new results and open problems connected with fundamental combinatorial concepts, including polytopes, simplicial complexes, cubical complexes, and arrangements of subspaces. Attention is concentrated on simplicial and cubical subdivisions of manifolds, and especially on spheres. Important constructions are described that enable one to study these combinatorial objects by using commutative and homological algebra. The proposed approach to combinatorial problems is based on the theory of moment-angle complexes recently developed by the authors. The crucial construction assigns to each simplicial complex K with m vertices a T m -space Z K with special bigraded cellular decomposition. In the framework of this theory, well-known non-singular toric varieties arise as orbit spaces of maximally free actions of subtori on moment-angle complexes corresponding to simplicial spheres. It is shown that diverse invariants of simplicial complexes and related combinatorial-geometric objects can be expressed in terms of bigraded cohomology rings of the corresponding moment-angle complexes. Finally, it is shown that the new relationships between combinatorics, geometry, and topology lead to solutions of some well-known topological problems

Stochastic optimization: beyond mathematical programming

CERN Multimedia

CERN. Geneva

2015-01-01

Stochastic optimization, among which bio-inspired algorithms, is gaining momentum in areas where more classical optimization algorithms fail to deliver satisfactory results, or simply cannot be directly applied. This presentation will introduce baseline stochastic optimization algorithms, and illustrate their efficiency in different domains, from continuous non-convex problems to combinatorial optimization problem, to problems for which a non-parametric formulation can help exploring unforeseen possible solution spaces.

Combinatorial Alanine Substitution Enables Rapid Optimization of Cytochrome P450BM3 for Selective Hydroxylation of Large Substrates

KAUST Repository

Lewis, Jared C.; Mantovani, Simone M.; Fu, Yu; Snow, Christopher D.; Komor, Russell S.; Wong , Chi-Huey; Arnold, Frances H.

2010-01-01

Made for each other: Combinatorial alanine substitution of active site residues in a thermostable cytochrome P450BM3 variant was used to generate an enzyme that is active with large substrates. Selective hydroxylation of methoxymethylated

Combinatorial matrix theory

CERN Document Server

Mitjana, Margarida

2018-01-01

This book contains the notes of the lectures delivered at an Advanced Course on Combinatorial Matrix Theory held at Centre de Recerca Matemàtica (CRM) in Barcelona. These notes correspond to five series of lectures. The first series is dedicated to the study of several matrix classes defined combinatorially, and was delivered by Richard A. Brualdi. The second one, given by Pauline van den Driessche, is concerned with the study of spectral properties of matrices with a given sign pattern. Dragan Stevanović delivered the third one, devoted to describing the spectral radius of a graph as a tool to provide bounds of parameters related with properties of a graph. The fourth lecture was delivered by Stephen Kirkland and is dedicated to the applications of the Group Inverse of the Laplacian matrix. The last one, given by Ángeles Carmona, focuses on boundary value problems on finite networks with special in-depth on the M-matrix inverse problem.

Combinatorial identities for tenth order mock theta functions

Indian Academy of Sciences (India)

44

which lead us to one 4-way and one 3-way combinatorial identity. ... mock theta functions, partition identities and different combinatorial parameters, see for ... 3. Example 1.1. There are twelve (n + 1)–color partitions of 2: 21, 21 + 01, 11 + 11, ...

On the combinatorial foundations of Regge-calculus

International Nuclear Information System (INIS)

Budach, L.

1989-01-01

Lipschitz-Killing curvatures of piecewise flat spaces are combinatorial analogues of Lipschitz-Killing curvatures of Riemannian manifolds. In the following paper rigorous combinatorial representations and proofs of all basic results for Lipschitz-Killing curvatures not using analytic arguments are given. The principal tools for an elementary representation of Regge calculus can be developed by means of basic properties of dihedral angles. (author)

Combinatorial Speculations and the Combinatorial Conjecture for Mathematics

OpenAIRE

Mao, Linfan

2006-01-01

Combinatorics is a powerful tool for dealing with relations among objectives mushroomed in the past century. However, an more important work for mathematician is to apply combinatorics to other mathematics and other sciences not merely to find combinatorial behavior for objectives. Recently, such research works appeared on journals for mathematics and theoretical physics on cosmos. The main purpose of this paper is to survey these thinking and ideas for mathematics and cosmological physics, s...

Manipulating Combinatorial Structures.

Science.gov (United States)

Labelle, Gilbert

This set of transparencies shows how the manipulation of combinatorial structures in the context of modern combinatorics can easily lead to interesting teaching and learning activities at every level of education from elementary school to university. The transparencies describe: (1) the importance and relations of combinatorics to science and…

Cubical version of combinatorial differential forms

DEFF Research Database (Denmark)

Kock, Anders

2010-01-01

The theory of combinatorial differential forms is usually presented in simplicial terms. We present here a cubical version; it depends on the possibility of forming affine combinations of mutual neighbour points in a manifold, in the context of synthetic differential geometry.......The theory of combinatorial differential forms is usually presented in simplicial terms. We present here a cubical version; it depends on the possibility of forming affine combinations of mutual neighbour points in a manifold, in the context of synthetic differential geometry....

Some experience of shielding calculations by combinatorial method

International Nuclear Information System (INIS)

Korobejnikov, V.V.; Oussanov, V.I.

1996-01-01

Some aspects of the compound systems shielding calculations by a combinatorial approach are discussed. The effectiveness of such an approach is based on the fundamental characteristic of a compound system: if some element of the system have in itself mathematical or physical properties favorable for calculation, these properties may be used in a combinatorial approach and are lost when the system is being calculated in the whole by a direct approach. The combinatorial technique applied is well known. A compound system are being splitting for two or more auxiliary subsystems (so that calculation each of them is a more simple problem than calculation of the original problem (or at last is a soluble problem if original one is not). Calculation of every subsystem are carried out by suitable method and code, the coupling being made through boundary conditions or boundary source. The special consideration in the paper is given to a fast reactor shielding combinatorial analysis and to the testing of the results received. (author)

Solid-Phase Synthesis of Small Molecule Libraries using Double Combinatorial Chemistry

DEFF Research Database (Denmark)

Nielsen, John; Jensen, Flemming R.

1997-01-01

The first synthesis of a combinatorial library using double combinatorial chemistry is presented. Coupling of unprotected Fmoc-tyrosine to the solid support was followed by Mitsunobu O-alkylation. Introduction of a diacid linker yields a system in which the double combinatorial step can be demons...

Causal gene identification using combinatorial V-structure search.

Science.gov (United States)

Cai, Ruichu; Zhang, Zhenjie; Hao, Zhifeng

2013-07-01

With the advances of biomedical techniques in the last decade, the costs of human genomic sequencing and genomic activity monitoring are coming down rapidly. To support the huge genome-based business in the near future, researchers are eager to find killer applications based on human genome information. Causal gene identification is one of the most promising applications, which may help the potential patients to estimate the risk of certain genetic diseases and locate the target gene for further genetic therapy. Unfortunately, existing pattern recognition techniques, such as Bayesian networks, cannot be directly applied to find the accurate causal relationship between genes and diseases. This is mainly due to the insufficient number of samples and the extremely high dimensionality of the gene space. In this paper, we present the first practical solution to causal gene identification, utilizing a new combinatorial formulation over V-Structures commonly used in conventional Bayesian networks, by exploring the combinations of significant V-Structures. We prove the NP-hardness of the combinatorial search problem under a general settings on the significance measure on the V-Structures, and present a greedy algorithm to find sub-optimal results. Extensive experiments show that our proposal is both scalable and effective, particularly with interesting findings on the causal genes over real human genome data. Copyright © 2013 Elsevier Ltd. All rights reserved.

Payment for multiple forest benefits alters the effect of tree disease on optimal forest rotation length.

Science.gov (United States)

Macpherson, Morag F; Kleczkowski, Adam; Healey, John R; Hanley, Nick

2017-04-01

Forests deliver multiple benefits both to their owners and to wider society. However, a wave of forest pests and pathogens is threatening this worldwide. In this paper we examine the effect of disease on the optimal rotation length of a single-aged, single rotation forest when a payment for non-timber benefits, which is offered to private forest owners to partly internalise the social values of forest management, is included. Using a generalisable bioeconomic framework we show how this payment counteracts the negative economic effect of disease by increasing the optimal rotation length, and under some restrictive conditions, even makes it optimal to never harvest the forest. The analysis shows a range of complex interactions between factors including the rate of spread of infection and the impact of disease on the value of harvested timber and non-timber benefits. A key result is that the effect of disease on the optimal rotation length is dependent on whether the disease affects the timber benefit only compared to when it affects both timber and non-timber benefits. Our framework can be extended to incorporate multiple ecosystem services delivered by forests and details of how disease can affect their production, thus facilitating a wide range of applications.

The World of Combinatorial Fuzzy Problems and the Efficiency of Fuzzy Approximation Algorithms

OpenAIRE

Yamakami, Tomoyuki

2015-01-01

We re-examine a practical aspect of combinatorial fuzzy problems of various types, including search, counting, optimization, and decision problems. We are focused only on those fuzzy problems that take series of fuzzy input objects and produce fuzzy values. To solve such problems efficiently, we design fast fuzzy algorithms, which are modeled by polynomial-time deterministic fuzzy Turing machines equipped with read-only auxiliary tapes and write-only output tapes and also modeled by polynomia...

Quantum particle swarm approaches applied to combinatorial problems

Energy Technology Data Exchange (ETDEWEB)

Nicolau, Andressa dos S.; Schirru, Roberto; Lima, Alan M.M. de, E-mail: andressa@lmp.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Programa de Engenharia Nuclear

2017-07-01

Quantum Particle Swarm Optimization (QPSO) is a global convergence algorithm that combines the classical PSO philosophy and quantum mechanics to improve performance of PSO. Different from PSO it only has the 'measurement' of the position equation for all particles. The process of 'measurement' in quantum mechanics, obey classic laws while the particle itself follows the quantum rules. QPSO works like PSO in search ability but has fewer parameters control. In order to improve the QPSO performance, some strategies have been proposed in the literature. Weighted QPSO (WQPSO) is a version of QPSO, where weight parameter is insert in the calculation of the balance between the global and local searching of the algorithm. It has been shown to perform well in finding the optimal solutions for many optimization problems. In this article random confinement was introduced in WQPSO. The WQPSO with random confinement was tested in two combinatorial problems. First, we execute the model on Travelling Salesman Problem (TSP) to find the parameters' values resulting in good solutions in general. Finally, the model was tested on Nuclear Reactor Reload Problem, and the performance was compared with QPSO standard. (author)

Quantum particle swarm approaches applied to combinatorial problems

International Nuclear Information System (INIS)

Nicolau, Andressa dos S.; Schirru, Roberto; Lima, Alan M.M. de

2017-01-01

Quantum Particle Swarm Optimization (QPSO) is a global convergence algorithm that combines the classical PSO philosophy and quantum mechanics to improve performance of PSO. Different from PSO it only has the 'measurement' of the position equation for all particles. The process of 'measurement' in quantum mechanics, obey classic laws while the particle itself follows the quantum rules. QPSO works like PSO in search ability but has fewer parameters control. In order to improve the QPSO performance, some strategies have been proposed in the literature. Weighted QPSO (WQPSO) is a version of QPSO, where weight parameter is insert in the calculation of the balance between the global and local searching of the algorithm. It has been shown to perform well in finding the optimal solutions for many optimization problems. In this article random confinement was introduced in WQPSO. The WQPSO with random confinement was tested in two combinatorial problems. First, we execute the model on Travelling Salesman Problem (TSP) to find the parameters' values resulting in good solutions in general. Finally, the model was tested on Nuclear Reactor Reload Problem, and the performance was compared with QPSO standard. (author)

Immune-Stimulating Combinatorial Therapy for Prostate Cancer

Science.gov (United States)

2016-10-01

Overlap: None 20 90061946 (Drake) Title: Epigenetic Drugs and Immuno Therapy for Prostate Cancer (EDIT-PC) Effort: 1.2 calendar months (10% effort...AWARD NUMBER: W81XWH-15-1-0667 TITLE: Immune-Stimulating Combinatorial Therapy for Prostate Cancer PRINCIPAL INVESTIGATOR: Robert Ivkov...Stimulating Combinatorial Therapy for Prostate Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-15-1-0667 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S

Optimal recombination in genetic algorithms for combinatorial optimization problems: Part I

Directory of Open Access Journals (Sweden)

Eremeev Anton V.

2014-01-01

Full Text Available This paper surveys results on complexity of the optimal recombination problem (ORP, which consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. We consider efficient reductions of the ORPs, allowing to establish polynomial solvability or NP-hardness of the ORPs, as well as direct proofs of hardness results. Part I presents the basic principles of optimal recombination with a survey of results on Boolean Linear Programming Problems. Part II (to appear in a subsequent issue is devoted to the ORPs for problems which are naturally formulated in terms of search for an optimal permutation.

On the Cut-off Point for Combinatorial Group Testing

DEFF Research Database (Denmark)

Fischer, Paul; Klasner, N.; Wegener, I.

1999-01-01

is answered by 1 if Q contains at least one essential object and by 0 otherwise. In the statistical setting the objects are essential, independently of each other, with a given probability p combinatorial setting the number k ... group testing is equal to p* = 12(3 - 5), i.e., the strategy of testing each object individually minimizes the average number of queries iff p >= p* or n = 1. In the combinatorial setting the worst case number of queries is of interest. It has been conjectured that the cut-off point of combinatorial...

Infinitary Combinatory Reduction Systems

DEFF Research Database (Denmark)

Ketema, Jeroen; Simonsen, Jakob Grue

2011-01-01

We define infinitary Combinatory Reduction Systems (iCRSs), thus providing the first notion of infinitary higher-order rewriting. The systems defined are sufficiently general that ordinary infinitary term rewriting and infinitary ¿-calculus are special cases. Furthermore,we generalise a number...

Combinatorial Quantum Field Theory and Gluing Formula for Determinants

NARCIS (Netherlands)

Reshetikhin, N.; Vertman, B.

2015-01-01

We define the combinatorial Dirichlet-to-Neumann operator and establish a gluing formula for determinants of discrete Laplacians using a combinatorial Gaussian quantum field theory. In case of a diagonal inner product on cochains we provide an explicit local expression for the discrete

Electricity price forecast using Combinatorial Neural Network trained by a new stochastic search method

International Nuclear Information System (INIS)

Abedinia, O.; Amjady, N.; Shafie-khah, M.; Catalão, J.P.S.

2015-01-01

Highlights: • Presenting a Combinatorial Neural Network. • Suggesting a new stochastic search method. • Adapting the suggested method as a training mechanism. • Proposing a new forecast strategy. • Testing the proposed strategy on real-world electricity markets. - Abstract: Electricity price forecast is key information for successful operation of electricity market participants. However, the time series of electricity price has nonlinear, non-stationary and volatile behaviour and so its forecast method should have high learning capability to extract the complex input/output mapping function of electricity price. In this paper, a Combinatorial Neural Network (CNN) based forecasting engine is proposed to predict the future values of price data. The CNN-based forecasting engine is equipped with a new training mechanism for optimizing the weights of the CNN. This training mechanism is based on an efficient stochastic search method, which is a modified version of chemical reaction optimization algorithm, giving high learning ability to the CNN. The proposed price forecast strategy is tested on the real-world electricity markets of Pennsylvania–New Jersey–Maryland (PJM) and mainland Spain and its obtained results are extensively compared with the results obtained from several other forecast methods. These comparisons illustrate effectiveness of the proposed strategy.

Distributed optimization using ant colony optimization in a concrete delivery supply chain

NARCIS (Netherlands)

Faria, J.M.; Silva, C.A.; Costa Sousa, da J.M.; Surico, M.; Kaymak, U.

2006-01-01

The timely production and distribution of rapidly perishable goods such as ready-mixed concrete is a complex combinatorial optimization problem in the context of supply chain management. The problem involves several tightly interrelated scheduling and routing problems that have to be solved

Combinatorial Cis-regulation in Saccharomyces Species

Directory of Open Access Journals (Sweden)

Aaron T. Spivak

2016-03-01

Full Text Available Transcriptional control of gene expression requires interactions between the cis-regulatory elements (CREs controlling gene promoters. We developed a sensitive computational method to identify CRE combinations with conserved spacing that does not require genome alignments. When applied to seven sensu stricto and sensu lato Saccharomyces species, 80% of the predicted interactions displayed some evidence of combinatorial transcriptional behavior in several existing datasets including: (1 chromatin immunoprecipitation data for colocalization of transcription factors, (2 gene expression data for coexpression of predicted regulatory targets, and (3 gene ontology databases for common pathway membership of predicted regulatory targets. We tested several predicted CRE interactions with chromatin immunoprecipitation experiments in a wild-type strain and strains in which a predicted cofactor was deleted. Our experiments confirmed that transcription factor (TF occupancy at the promoters of the CRE combination target genes depends on the predicted cofactor while occupancy of other promoters is independent of the predicted cofactor. Our method has the additional advantage of identifying regulatory differences between species. By analyzing the S. cerevisiae and S. bayanus genomes, we identified differences in combinatorial cis-regulation between the species and showed that the predicted changes in gene regulation explain several of the species-specific differences seen in gene expression datasets. In some instances, the same CRE combinations appear to regulate genes involved in distinct biological processes in the two different species. The results of this research demonstrate that (1 combinatorial cis-regulation can be inferred by multi-genome analysis and (2 combinatorial cis-regulation can explain differences in gene expression between species.

Conferences on Combinatorial and Additive Number Theory

CERN Document Server

2014-01-01

This proceedings volume is based on papers presented at the Workshops on Combinatorial and Additive Number Theory (CANT), which were held at the Graduate Center of the City University of New York in 2011 and 2012. The goal of the workshops is to survey recent progress in combinatorial number theory and related parts of mathematics. The workshop attracts researchers and students who discuss the state-of-the-art, open problems, and future challenges in number theory.

Effects of word width and word length on optimal character size for reading of horizontally scrolling Japanese words

Directory of Open Access Journals (Sweden)

Wataru eTeramoto

2016-02-01

Full Text Available The present study investigated whether word width and length affect the optimal character size for reading of horizontally scrolling Japanese words, using reading speed as a measure. In Experiment 1, three Japanese words, each consisting of 4 Hiragana characters, sequentially scrolled on a display screen from right to left. Participants, all Japanese native speakers, were instructed to read the words aloud as accurately as possible, irrespective of their order within the sequence. To quantitatively measure their reading performance, we used rapid serial visual presentation paradigm, where the scrolling rate was increased until the participants began to make mistakes. Thus, the highest scrolling rate at which the participants’ performance exceeded 88.9% correct rate was calculated for each character size (0.3, 0.6, 1.0, and 3.0° and scroll window size (5 or 10 character spaces. Results showed that the reading performance was highest in the range of 0.6° to 1.0°, irrespective of the scroll window size. Experiment 2 investigated whether the optimal character size observed in Experiment 1 was applicable for any word width and word length (i.e., the number of characters in a word. Results showed that reading speeds were slower for longer than shorter words and the word width of 3.6° was optimal among the word lengths tested (3, 4, and 6 character words. Considering that character size varied depending on word width and word length in the present study, this means that the optimal character size can be changed by word width and word length.

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

Science.gov (United States)

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

2008-11-11

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

Simultaneous Disulfide and Boronic Acid Ester Exchange in Dynamic Combinatorial Libraries

Directory of Open Access Journals (Sweden)

Sanna L. Diemer

2015-09-01

Full Text Available Dynamic combinatorial chemistry has emerged as a promising tool for the discovery of complex receptors in supramolecular chemistry. At the heart of dynamic combinatorial chemistry are the reversible reactions that enable the exchange of building blocks between library members in dynamic combinatorial libraries (DCLs ensuring thermodynamic control over the system. If more than one reversible reaction operates in a single dynamic combinatorial library, the complexity of the system increases dramatically, and so does its possible applications. One can imagine two reversible reactions that operate simultaneously or two reversible reactions that operate independently. Both these scenarios have advantages and disadvantages. In this contribution, we show how disulfide exchange and boronic ester transesterification can function simultaneous in dynamic combinatorial libraries under appropriate conditions. We describe the detailed studies necessary to establish suitable reaction conditions and highlight the analytical techniques appropriate to study this type of system.

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

Science.gov (United States)

Li, Jianwei; Nowak, Piotr; Otto, Sijbren

2013-06-26

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

Combinatorial Micro-Macro Dynamical Systems

OpenAIRE

Diaz, Rafael; Villamarin, Sergio

2015-01-01

The second law of thermodynamics states that the entropy of an isolated system is almost always increasing. We propose combinatorial formalizations of the second law and explore their conditions of possibilities.

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

Directory of Open Access Journals (Sweden)

Nannan Zhou

2015-06-01

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

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

Science.gov (United States)

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

2018-01-01

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

Sequential optimization of approximate inhibitory rules relative to the length, coverage and number of misclassifications

KAUST Repository

Alsolami, Fawaz; Chikalov, Igor; Moshkov, Mikhail

2013-01-01

This paper is devoted to the study of algorithms for sequential optimization of approximate inhibitory rules relative to the length, coverage and number of misclassifications. Theses algorithms are based on extensions of dynamic programming approach

On Definitions and Existence of Combinatorial Entropy of 2d Fields

DEFF Research Database (Denmark)

Forchhammer, Søren Otto; Shtarkov, Yuri; Justesen, Jørn

1998-01-01

Different definitions of combinatorial entropy is presented and conditions for their existence examined.......Different definitions of combinatorial entropy is presented and conditions for their existence examined....

Effects of Word Width and Word Length on Optimal Character Size for Reading of Horizontally Scrolling Japanese Words.

Science.gov (United States)

Teramoto, Wataru; Nakazaki, Takuyuki; Sekiyama, Kaoru; Mori, Shuji

2016-01-01

The present study investigated, whether word width and length affect the optimal character size for reading of horizontally scrolling Japanese words, using reading speed as a measure. In Experiment 1, three Japanese words, each consisting of four Hiragana characters, sequentially scrolled on a display screen from right to left. Participants, all Japanese native speakers, were instructed to read the words aloud as accurately as possible, irrespective of their order within the sequence. To quantitatively measure their reading performance, we used rapid serial visual presentation paradigm, where the scrolling rate was increased until the participants began to make mistakes. Thus, the highest scrolling rate at which the participants' performance exceeded 88.9% correct rate was calculated for each character size (0.3°, 0.6°, 1.0°, and 3.0°) and scroll window size (5 or 10 character spaces). Results showed that the reading performance was highest in the range of 0.6° to 1.0°, irrespective of the scroll window size. Experiment 2 investigated whether the optimal character size observed in Experiment 1 was applicable for any word width and word length (i.e., the number of characters in a word). Results showed that reading speeds were slower for longer than shorter words and the word width of 3.6° was optimal among the word lengths tested (three, four, and six character words). Considering that character size varied depending on word width and word length in the present study, this means that the optimal character size can be changed by word width and word length in scrolling Japanese words.

Ant Colony Optimization and the Minimum Cut Problem

DEFF Research Database (Denmark)

Kötzing, Timo; Lehre, Per Kristian; Neumann, Frank

2010-01-01

Ant Colony Optimization (ACO) is a powerful metaheuristic for solving combinatorial optimization problems. With this paper we contribute to the theoretical understanding of this kind of algorithm by investigating the classical minimum cut problem. An ACO algorithm similar to the one that was prov...

Enabling high performance computational science through combinatorial algorithms

International Nuclear Information System (INIS)

Boman, Erik G; Bozdag, Doruk; Catalyurek, Umit V; Devine, Karen D; Gebremedhin, Assefaw H; Hovland, Paul D; Pothen, Alex; Strout, Michelle Mills

2007-01-01

The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation

Enabling high performance computational science through combinatorial algorithms

Energy Technology Data Exchange (ETDEWEB)

Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Bozdag, Doruk [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Catalyurek, Umit V [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Devine, Karen D [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw H [Computer Science and Center for Computational Science, Old Dominion University (United States); Hovland, Paul D [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science and Center for Computational Science, Old Dominion University (United States); Strout, Michelle Mills [Computer Science, Colorado State University (United States)

2007-07-15

The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation.

Combinatorial Mathematics: Research into Practice

Science.gov (United States)

Sriraman, Bharath; English, Lyn D.

2004-01-01

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

Recent advances in combinatorial biosynthesis for drug discovery

Directory of Open Access Journals (Sweden)

Sun H

2015-02-01

Full Text Available Huihua Sun,1,* Zihe Liu,1,* Huimin Zhao,1,2 Ee Lui Ang1 1Metabolic Engineering Research Laboratory, Institute of Chemical and Engineering Sciences, Agency for Science, Technology and Research, Singapore; 2Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA *These authors contributed equally to this work Abstract: Because of extraordinary structural diversity and broad biological activities, natural products have played a significant role in drug discovery. These therapeutically important secondary metabolites are assembled and modified by dedicated biosynthetic pathways in their host living organisms. Traditionally, chemists have attempted to synthesize natural product analogs that are important sources of new drugs. However, the extraordinary structural complexity of natural products sometimes makes it challenging for traditional chemical synthesis, which usually involves multiple steps, harsh conditions, toxic organic solvents, and byproduct wastes. In contrast, combinatorial biosynthesis exploits substrate promiscuity and employs engineered enzymes and pathways to produce novel “unnatural” natural products, substantially expanding the structural diversity of natural products with potential pharmaceutical value. Thus, combinatorial biosynthesis provides an environmentally friendly way to produce natural product analogs. Efficient expression of the combinatorial biosynthetic pathway in genetically tractable heterologous hosts can increase the titer of the compound, eventually resulting in less expensive drugs. In this review, we will discuss three major strategies for combinatorial biosynthesis: 1 precursor-directed biosynthesis; 2 enzyme-level modification, which includes swapping of the entire domains, modules and subunits, site-specific mutagenesis, and directed evolution; 3 pathway-level recombination. Recent examples of combinatorial biosynthesis employing these

Secretory Overexpression of Bacillus thermocatenulatus Lipase in Saccharomyces cerevisiae Using Combinatorial Library Strategy.

Science.gov (United States)

Kajiwara, Shota; Yamada, Ryosuke; Ogino, Hiroyasu

2018-04-10

Simple and cost-effective lipase expression host microorganisms are highly desirable. A combinatorial library strategy is used to improve the secretory expression of lipase from Bacillus thermocatenulatus (BTL2) in the culture supernatant of Saccharomyces cerevisiae. A plasmid library including expression cassettes composed of sequences encoding one of each 15 promoters, 15 secretion signals, and 15 terminators derived from yeast species, S. cerevisiae, Pichia pastoris, and Hansenula polymorpha, is constructed. The S. cerevisiae transformant YPH499/D4, comprising H. polymorpha GAP promoter, S. cerevisiae SAG1 secretion signal, and P. pastoris AOX1 terminator, is selected by high-throughput screening. This transformant expresses BTL2 extra-cellularly with a 130-fold higher than the control strain, comprising S. cerevisiae PGK1 promoter, S. cerevisiae α-factor secretion signal, and S. cerevisiae PGK1 terminator, after cultivation for 72 h. This combinatorial library strategy holds promising potential for application in the optimization of the secretory expression of proteins in yeast. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combinatorial designs a tribute to Haim Hanani

CERN Document Server

Hartman, A

1989-01-01

Haim Hanani pioneered the techniques for constructing designs and the theory of pairwise balanced designs, leading directly to Wilson''s Existence Theorem. He also led the way in the study of resolvable designs, covering and packing problems, latin squares, 3-designs and other combinatorial configurations.The Hanani volume is a collection of research and survey papers at the forefront of research in combinatorial design theory, including Professor Hanani''s own latest work on Balanced Incomplete Block Designs. Other areas covered include Steiner systems, finite geometries, quasigroups, and t-designs.

A quark interpretation of the combinatorial hierarchy

International Nuclear Information System (INIS)

Enqvist, Kari.

1979-01-01

We propose a physical interpretation of the second level of the combinatorial hierarchy in terms of three quarks, three antiquarks and the vacuum. This interpretation allows us to introduce a new quantum number, which measures electromagnetic mass splitting of the quarks. We extend our argument by analogue to baryons, and find some SU(3) and some new mass formulas for baryons. The generalization of our approach to other hierarchy levels is discussed. We present also an empirical mass formula for baryons, which seems to be loosely connected with the combinatorial hierarchy. (author)

Thickness optimization of fiber reinforced laminated composites using the discrete material optimization method

DEFF Research Database (Denmark)

Sørensen, Søren Nørgaard; Lund, Erik

2012-01-01

This work concerns a novel large-scale multi-material topology optimization method for simultaneous determination of the optimum variable integer thickness and fiber orientation throughout laminate structures with fixed outer geometries while adhering to certain manufacturing constraints....... The conceptual combinatorial/integer problem is relaxed to a continuous problem and solved on basis of the so-called Discrete Material Optimization method, explicitly including the manufacturing constraints as linear constraints....

Efficiency Intra-Cluster Device-to-Device Relay Selection for Multicast Services Based on Combinatorial Auction

Directory of Open Access Journals (Sweden)

Yong Zhang

2015-12-01

Full Text Available In Long Term Evolution-Advanced (LTE-A networks, Device-to-device (D2D communications can be utilized to enhance the performance of multicast services by leveraging D2D relays to serve nodes with worse channel conditions within a cluster. For traditional D2D relay schemes, D2D links with poor channel condition may be the bottleneck of system sum data rate. In this paper, to optimize the throughput of D2D communications, we introduce an iterative combinatorial auction algorithm for efficient D2D relay selection. In combinatorial auctions, the User Equipments (UEs that fails to correctly receive multicast data from eNodeB (eNB are viewed as bidders that compete for D2D relays, while the eNB is treated as the auctioneer. We also give properties of convergency and low-complexity and present numerical simulations to verify the efficiency of the proposed algorithm.

Automated Implanter Endstation for Combinatorial Materials Science with Ion Beams

International Nuclear Information System (INIS)

Grosshans, I.; Karl, H.; Stritzker, B.

2003-01-01

The discovery, understanding and optimization of new complex functional materials requires combinatorial synthesis techniques and fast screening instrumentation for the measurement of the samples. In this contribution the synthesis of buried II-VI compound semiconductor nanocrystals by ion-implantation in SiO2 on silicon will be presented. For that we constructed a computer controlled implanter target end station, in which a 4-inch wafer can be implanted with a lateral pattern of distinct dose, composition or energy combinations. The chemical reaction of the constituents is initiated either during the implantation process or ex-situ by a rapid thermal process, where a reactive atmosphere can be applied. The resulting optical photoluminescence properties of the individual fields of the pattern can then be screened in rapid succession in an optical cryostat into which the whole wafer is mounted and cooled down. In this way, complex interdependences of the physical parameters can be studied on a single wafer and the technically relevant properties optimized

Optimization strategies in complex systems

NARCIS (Netherlands)

Bussolari, L.; Contucci, P.; Giardinà, C.; Giberti, C.; Unguendoli, F.; Vernia, C.

2003-01-01

We consider a class of combinatorial optimization problems that emerge in a variety of domains among which: condensed matter physics, theory of financial risks, error correcting codes in information transmissions, molecular and protein conformation, image restoration. We show the performances of two

Combinatorial Dyson-Schwinger equations and inductive data types

Science.gov (United States)

Kock, Joachim

2016-06-01

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

A Simple Combinatorial Codon Mutagenesis Method for Targeted Protein Engineering.

Science.gov (United States)

Belsare, Ketaki D; Andorfer, Mary C; Cardenas, Frida S; Chael, Julia R; Park, Hyun June; Lewis, Jared C

2017-03-17

Directed evolution is a powerful tool for optimizing enzymes, and mutagenesis methods that improve enzyme library quality can significantly expedite the evolution process. Here, we report a simple method for targeted combinatorial codon mutagenesis (CCM). To demonstrate the utility of this method for protein engineering, CCM libraries were constructed for cytochrome P450 BM3 , pfu prolyl oligopeptidase, and the flavin-dependent halogenase RebH; 10-26 sites were targeted for codon mutagenesis in each of these enzymes, and libraries with a tunable average of 1-7 codon mutations per gene were generated. Each of these libraries provided improved enzymes for their respective transformations, which highlights the generality, simplicity, and tunability of CCM for targeted protein engineering.

Solving the neutron diffusion equation on combinatorial geometry computational cells for reactor physics calculations

International Nuclear Information System (INIS)

Azmy, Y. Y.

2004-01-01

An approach is developed for solving the neutron diffusion equation on combinatorial geometry computational cells, that is computational cells composed by combinatorial operations involving simple-shaped component cells. The only constraint on the component cells from which the combinatorial cells are assembled is that they possess a legitimate discretization of the underlying diffusion equation. We use the Finite Difference (FD) approximation of the x, y-geometry diffusion equation in this work. Performing the same combinatorial operations involved in composing the combinatorial cell on these discrete-variable equations yields equations that employ new discrete variables defined only on the combinatorial cell's volume and faces. The only approximation involved in this process, beyond the truncation error committed in discretizing the diffusion equation over each component cell, is a consistent-order Legendre series expansion. Preliminary results for simple configurations establish the accuracy of the solution to the combinatorial geometry solution compared to straight FD as the system dimensions decrease. Furthermore numerical results validate the consistent Legendre-series expansion order by illustrating the second order accuracy of the combinatorial geometry solution, the same as standard FD. Nevertheless the magnitude of the error for the new approach is larger than FD's since it incorporates the additional truncated series approximation. (authors)

Effect of calibration data series length on performance and optimal parameters of hydrological model

Directory of Open Access Journals (Sweden)

Chuan-zhe Li

2010-12-01

Full Text Available In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments (data are non-continuous and fragmental in some catchments, we used non-continuous calibration periods for more independent streamflow data for SIMHYD (simple hydrology model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization (PSO method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.

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

Science.gov (United States)

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

2017-07-10

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

The Combinatorial Rigidity Conjecture is False for Cubic Polynomials

DEFF Research Database (Denmark)

Henriksen, Christian

2003-01-01

We show that there exist two cubic polynomials with connected Julia sets which are combinatorially equivalent but not topologically conjugate on their Julia sets. This disproves a conjecture by McMullen from 1995.......We show that there exist two cubic polynomials with connected Julia sets which are combinatorially equivalent but not topologically conjugate on their Julia sets. This disproves a conjecture by McMullen from 1995....

A low complexity method for the optimization of network path length in spatially embedded networks

International Nuclear Information System (INIS)

Chen, Guang; Yang, Xu-Hua; Xu, Xin-Li; Ming, Yong; Chen, Sheng-Yong; Wang, Wan-Liang

2014-01-01

The average path length of a network is an important index reflecting the network transmission efficiency. In this paper, we propose a new method of decreasing the average path length by adding edges. A new indicator is presented, incorporating traffic flow demand, to assess the decrease in the average path length when a new edge is added during the optimization process. With the help of the indicator, edges are selected and added into the network one by one. The new method has a relatively small time computational complexity in comparison with some traditional methods. In numerical simulations, the new method is applied to some synthetic spatially embedded networks. The result shows that the method can perform competitively in decreasing the average path length. Then, as an example of an application of this new method, it is applied to the road network of Hangzhou, China. (paper)

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

International Nuclear Information System (INIS)

Gaifullin, A A

2008-01-01

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

Dendrimer-based dynamic combinatorial libraries

NARCIS (Netherlands)

Chang, T.; Meijer, E.W.

2005-01-01

The aim of this project is to create water-sol. dynamic combinatorial libraries based upon dendrimer-guest complexes. The guest mols. are designed to bind to dendrimers using multiple secondary interactions, such as electrostatics and hydrogen bonding. We have been able to incorporate various guest

Computational Complexity of Combinatorial Surfaces

NARCIS (Netherlands)

Vegter, Gert; Yap, Chee K.

1990-01-01

We investigate the computational problems associated with combinatorial surfaces. Specifically, we present an algorithm (based on the Brahana-Dehn-Heegaard approach) for transforming the polygonal schema of a closed triangulated surface into its canonical form in O(n log n) time, where n is the

Combinatorial auctions for electronic business

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

(6) Information feedback: An auction protocol may be a direct mechanism or an .... transparency of allocation decisions arise in resolving these ties. .... bidding, however more recently, combinatorial bids are allowed [50] making ...... Also, truth revelation and other game theoretic considerations are not taken into account.

Combinatorial Proofs and Algebraic Proofs

Indian Academy of Sciences (India)

Permanent link: https://www.ias.ac.in/article/fulltext/reso/018/07/0630-0645. Keywords. Combinatorial proof; algebraic proof; binomial identity; recurrence relation; composition; Fibonacci number; Fibonacci identity; Pascal triangle. Author Affiliations. Shailesh A Shirali1. Sahyadri School Tiwai Hill, Rajgurunagar Pune 410 ...

Combinatorial Screening for Transgenic Yeasts with High Cellulase Activities in Combination with a Tunable Expression System.

Directory of Open Access Journals (Sweden)

Yoichiro Ito

Full Text Available Combinatorial screening used together with a broad library of gene expression cassettes is expected to produce a powerful tool for the optimization of the simultaneous expression of multiple enzymes. Recently, we proposed a highly tunable protein expression system that utilized multiple genome-integrated target genes to fine-tune enzyme expression in yeast cells. This tunable system included a library of expression cassettes each composed of three gene-expression control elements that in different combinations produced a wide range of protein expression levels. In this study, four gene expression cassettes with graded protein expression levels were applied to the expression of three cellulases: cellobiohydrolase 1, cellobiohydrolase 2, and endoglucanase 2. After combinatorial screening for transgenic yeasts simultaneously secreting these three cellulases, we obtained strains with higher cellulase expressions than a strain harboring three cellulase-expression constructs within one high-performance gene expression cassette. These results show that our method will be of broad use throughout the field of metabolic engineering.

Combinatorial Screening for Transgenic Yeasts with High Cellulase Activities in Combination with a Tunable Expression System

Science.gov (United States)

Ito, Yoichiro; Yamanishi, Mamoru; Ikeuchi, Akinori; Imamura, Chie; Matsuyama, Takashi

2015-01-01

Combinatorial screening used together with a broad library of gene expression cassettes is expected to produce a powerful tool for the optimization of the simultaneous expression of multiple enzymes. Recently, we proposed a highly tunable protein expression system that utilized multiple genome-integrated target genes to fine-tune enzyme expression in yeast cells. This tunable system included a library of expression cassettes each composed of three gene-expression control elements that in different combinations produced a wide range of protein expression levels. In this study, four gene expression cassettes with graded protein expression levels were applied to the expression of three cellulases: cellobiohydrolase 1, cellobiohydrolase 2, and endoglucanase 2. After combinatorial screening for transgenic yeasts simultaneously secreting these three cellulases, we obtained strains with higher cellulase expressions than a strain harboring three cellulase-expression constructs within one high-performance gene expression cassette. These results show that our method will be of broad use throughout the field of metabolic engineering. PMID:26692026

An Optimization Framework for Combining the Petroleum Replenishment Problem with the Optimal Bidding in Combinatorial Auctions

Directory of Open Access Journals (Sweden)

Chefi Triki

2016-08-01

Full Text Available We address in this paper a periodic petroleum station replenishment problem (PPSRP that aims to plan the delivery of petroleum products to a set of geographically dispatched stations. It is assumed that each station is characterized by its weekly demand and by its frequency of service. The main objective of the delivery process is to minimize the total travelled distance by the vailable trucks over an extended planning horizon. The problem configuration is described through a set of trucks with several compartments each and a set of stations with demands and prefixed delivery frequencies. Given such input data, the minimization of the total distance is subject to assignment and routing constraints that express the capacity limitations of each truck's compartment in terms of the frequency and the pathways' restrictions. In this paper, we develop and solve the full space mathematical formulation for the PPSRP with application to the Omani context. Our ultimate aim is to include such a model into an integrated framework having the objective of advising petroleum distribution companies on how to prepare bids in case of participation in combinatorial auctions of the transportation procurement.

Paths and partitions: Combinatorial descriptions of the parafermionic states

Science.gov (United States)

Mathieu, Pierre

2009-09-01

The Zk parafermionic conformal field theories, despite the relative complexity of their modes algebra, offer the simplest context for the study of the bases of states and their different combinatorial representations. Three bases are known. The classic one is given by strings of the fundamental parafermionic operators whose sequences of modes are in correspondence with restricted partitions with parts at distance k -1 differing at least by 2. Another basis is expressed in terms of the ordered modes of the k -1 different parafermionic fields, which are in correspondence with the so-called multiple partitions. Both types of partitions have a natural (Bressoud) path representation. Finally, a third basis, formulated in terms of different paths, is inherited from the solution of the restricted solid-on-solid model of Andrews-Baxter-Forrester. The aim of this work is to review, in a unified and pedagogical exposition, these four different combinatorial representations of the states of the Zk parafermionic models. The first part of this article presents the different paths and partitions and their bijective relations; it is purely combinatorial, self-contained, and elementary; it can be read independently of the conformal-field-theory applications. The second part links this combinatorial analysis with the bases of states of the Zk parafermionic theories. With the prototypical example of the parafermionic models worked out in detail, this analysis contributes to fix some foundations for the combinatorial study of more complicated theories. Indeed, as we briefly indicate in ending, generalized versions of both the Bressoud and the Andrews-Baxter-Forrester paths emerge naturally in the description of the minimal models.

Combinatorial algebra syntax and semantics

CERN Document Server

Sapir, Mark V

2014-01-01

Combinatorial Algebra: Syntax and Semantics provides a comprehensive account of many areas of combinatorial algebra. It contains self-contained proofs of  more than 20 fundamental results, both classical and modern. This includes Golod–Shafarevich and Olshanskii's solutions of Burnside problems, Shirshov's solution of Kurosh's problem for PI rings, Belov's solution of Specht's problem for varieties of rings, Grigorchuk's solution of Milnor's problem, Bass–Guivarc'h theorem about the growth of nilpotent groups, Kleiman's solution of Hanna Neumann's problem for varieties of groups, Adian's solution of von Neumann-Day's problem, Trahtman's solution of the road coloring problem of Adler, Goodwyn and Weiss. The book emphasize several ``universal" tools, such as trees, subshifts, uniformly recurrent words, diagrams and automata.   With over 350 exercises at various levels of difficulty and with hints for the more difficult problems, this book can be used as a textbook, and aims to reach a wide and diversified...

The variance of length of stay and the optimal DRG outlier payments.

Science.gov (United States)

Felder, Stefan

2009-09-01

Prospective payment schemes in health care often include supply-side insurance for cost outliers. In hospital reimbursement, prospective payments for patient discharges, based on their classification into diagnosis related group (DRGs), are complemented by outlier payments for long stay patients. The outlier scheme fixes the length of stay (LOS) threshold, constraining the profit risk of the hospitals. In most DRG systems, this threshold increases with the standard deviation of the LOS distribution. The present paper addresses the adequacy of this DRG outlier threshold rule for risk-averse hospitals with preferences depending on the expected value and the variance of profits. It first shows that the optimal threshold solves the hospital's tradeoff between higher profit risk and lower premium loading payments. It then demonstrates for normally distributed truncated LOS that the optimal outlier threshold indeed decreases with an increase in the standard deviation.

Combinatorial methods for advanced materials research and development

Energy Technology Data Exchange (ETDEWEB)

Cremer, R.; Dondorf, S.; Hauck, M.; Horbach, D.; Kaiser, M.; Krysta, S.; Kyrylov, O.; Muenstermann, E.; Philipps, M.; Reichert, K.; Strauch, G. [Rheinisch-Westfaelische Technische Hochschule Aachen (Germany). Lehrstuhl fuer Theoretische Huettenkunde

2001-10-01

The applicability of combinatorial methods in developing advanced materials is illustrated presenting four examples for the deposition and characterization of one- and two-dimensionally laterally graded coatings, which were deposited by means of (reactive) magnetron sputtering and plasma-enhanced chemical vapor deposition. To emphasize the advantages of combinatorial approaches, metastable hard coatings like (Ti,Al)N and (Ti,Al,Hf)N respectively, as well as Ge-Sb-Te based films for rewritable optical data storage were investigated with respect to the relations between structure, composition, and the desired materials properties. (orig.)

Markov's theorem and algorithmically non-recognizable combinatorial manifolds

International Nuclear Information System (INIS)

Shtan'ko, M A

2004-01-01

We prove the theorem of Markov on the existence of an algorithmically non-recognizable combinatorial n-dimensional manifold for every n≥4. We construct for the first time a concrete manifold which is algorithmically non-recognizable. A strengthened form of Markov's theorem is proved using the combinatorial methods of regular neighbourhoods and handle theory. The proofs coincide for all n≥4. We use Borisov's group with insoluble word problem. It has two generators and twelve relations. The use of this group forms the base for proving the strengthened form of Markov's theorem

Construction of Short-length High-rates Ldpc Codes Using Difference Families

OpenAIRE

Deny Hamdani; Ery Safrianti

2007-01-01

Low-density parity-check (LDPC) code is linear-block error-correcting code defined by sparse parity-check matrix. It isdecoded using the massage-passing algorithm, and in many cases, capable of outperforming turbo code. This paperpresents a class of low-density parity-check (LDPC) codes showing good performance with low encoding complexity.The code is constructed using difference families from combinatorial design. The resulting code, which is designed tohave short code length and high code r...

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

Science.gov (United States)

Bulone, Vincent William

2017-01-01

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

The island model for parallel implementation of evolutionary algorithm of Population-Based Incremental Learning (PBIL) optimization

International Nuclear Information System (INIS)

Lima, Alan M.M. de; Schirru, Roberto

2000-01-01

Genetic algorithms are biologically motivated adaptive systems which have been used, with good results, for function optimization. The purpose of this work is to introduce a new parallelization method to be applied to the Population-Based Incremental Learning (PBIL) algorithm. PBIL combines standard genetic algorithm mechanisms with simple competitive learning and has ben successfully used in combinatorial optimization problems. The development of this algorithm aims its application to the reload optimization of PWR nuclear reactors. Tests have been performed with combinatorial optimization problems similar to the reload problem. Results are compared to the serial PBIL ones, showing the new method's superiority and its viability as a tool for the nuclear core reload problem solution. (author)

A note on the depth function of combinatorial optimization problems

NARCIS (Netherlands)

Woeginger, G.J.

2001-01-01

In a recent paper [Discrete Appl. Math. 43 (1993) 115–129], Kern formulates two conjectures on the relationship between the computational complexity of computing the depth function of a discrete optimization problem and the computational complexity of solving this optimization problem to optimality.

Enumeration of Combinatorial Classes of Single Variable Complex Polynomial Vector Fields

DEFF Research Database (Denmark)

Dias, Kealey

A vector field in the space of degree d monic, centered single variable complex polynomial vector fields has a combinatorial structure which can be fully described by a combinatorial data set consisting of an equivalence relation and a marked subset on the integers mod 2d-2, satisfying certain...

Sequential optimization of approximate inhibitory rules relative to the length, coverage and number of misclassifications

KAUST Repository

Alsolami, Fawaz

2013-01-01

This paper is devoted to the study of algorithms for sequential optimization of approximate inhibitory rules relative to the length, coverage and number of misclassifications. Theses algorithms are based on extensions of dynamic programming approach. The results of experiments for decision tables from UCI Machine Learning Repository are discussed. © 2013 Springer-Verlag.

Theory of site-specific interactions of the combinatorial transcription factors with DNA

International Nuclear Information System (INIS)

Murugan, R

2010-01-01

We derive a functional relationship between the mean first passage time associated with the concurrent binding of multiple transcription factors (TFs) at their respective combinatorial cis-regulatory module sites (CRMs) and the number n of TFs involved in the regulation of the initiation of transcription of a gene of interest. Our results suggest that the overall search time τ s that is required by the n TFs to locate their CRMs which are all located on the same DNA chain scales with n as τ s ∼n α where α ∼ (2/5). When the jump size k that is associated with the dynamics of all the n TFs along DNA is higher than that of the critical jump size k c that scales with the size of DNA N as k c ∼ N 2/3 , we observe a similar power law scaling relationship and also the exponent α. When k c , α shows a strong dependence on both n and k. Apparently there is a critical number of combinatorial TFs n c ∼ 20 that is required to efficiently regulate the initiation of transcription of a given gene below which (2/5) 1. These results seem to be independent of the initial distances between the TFs and their corresponding CRMs and also suggest that the maximum number of TFs involved in a given combinatorial regulation of the initiation of transcription of a gene of interest seems to be restricted by the degree of condensation of the genomic DNA. The optimum number m opt of roadblock protein molecules per genome at which the search time associated with these n TFs to locate their binding sites is a minimum seems to scale as m opt ∼Ln α/2 where L is the sliding length of TFs whose maximum value seems to be such that L ≤ 10 4 bps for the E. coli bacterial genome.

Combinatorial vector fields and the valley structure of fitness landscapes.

Science.gov (United States)

Stadler, Bärbel M R; Stadler, Peter F

2010-12-01

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

Logging to Facilitate Combinatorial System Testing

NARCIS (Netherlands)

Kruse, P.M.; Prasetya, I.S.W.B.; Hage, J; Elyasov, Alexander

2014-01-01

Testing a web application is typically very complicated. Imposing simple coverage criteria such as function or line coverage is often not sufficient to uncover bugs due to incorrect components integration. Combinatorial testing can enforce a stronger criterion, while still allowing the

Combinatorial computational chemistry approach to the design of metal catalysts for deNOx

International Nuclear Information System (INIS)

Endou, Akira; Jung, Changho; Kusagaya, Tomonori; Kubo, Momoji; Selvam, Parasuraman; Miyamoto, Akira

2004-01-01

Combinatorial chemistry is an efficient technique for the synthesis and screening of a large number of compounds. Recently, we introduced the combinatorial approach to computational chemistry for catalyst design and proposed a new method called ''combinatorial computational chemistry''. In the present study, we have applied this combinatorial computational chemistry approach to the design of precious metal catalysts for deNO x . As the first step of the screening of the metal catalysts, we studied Rh, Pd, Ag, Ir, Pt, and Au clusters regarding the adsorption properties towards NO molecule. It was demonstrated that the energetically most stable adsorption state of NO on Ir model cluster, which was irrespective of both the shape and number of atoms including the model clusters

Balancing focused combinatorial libraries based on multiple GPCR ligands

Science.gov (United States)

Soltanshahi, Farhad; Mansley, Tamsin E.; Choi, Sun; Clark, Robert D.

2006-08-01

G-Protein coupled receptors (GPCRs) are important targets for drug discovery, and combinatorial chemistry is an important tool for pharmaceutical development. The absence of detailed structural information, however, limits the kinds of combinatorial design techniques that can be applied to GPCR targets. This is particularly problematic given the current emphasis on focused combinatorial libraries. By linking an incremental construction method (OptDesign) to the very fast shape-matching capability of ChemSpace, we have created an efficient method for designing targeted sublibraries that are topomerically similar to known actives. Multi-objective scoring allows consideration of multiple queries (actives) simultaneously. This can lead to a distribution of products skewed towards one particular query structure, however, particularly when the ligands of interest are quite dissimilar to one another. A novel pivoting technique is described which makes it possible to generate promising designs even under those circumstances. The approach is illustrated by application to some serotonergic agonists and chemokine antagonists.

Optimal choice of word length when comparing two Markov sequences using a χ 2-statistic.

Science.gov (United States)

Bai, Xin; Tang, Kujin; Ren, Jie; Waterman, Michael; Sun, Fengzhu

2017-10-03

Alignment-free sequence comparison using counts of word patterns (grams, k-tuples) has become an active research topic due to the large amount of sequence data from the new sequencing technologies. Genome sequences are frequently modelled by Markov chains and the likelihood ratio test or the corresponding approximate χ 2 -statistic has been suggested to compare two sequences. However, it is not known how to best choose the word length k in such studies. We develop an optimal strategy to choose k by maximizing the statistical power of detecting differences between two sequences. Let the orders of the Markov chains for the two sequences be r 1 and r 2 , respectively. We show through both simulations and theoretical studies that the optimal k= max(r 1 ,r 2 )+1 for both long sequences and next generation sequencing (NGS) read data. The orders of the Markov chains may be unknown and several methods have been developed to estimate the orders of Markov chains based on both long sequences and NGS reads. We study the power loss of the statistics when the estimated orders are used. It is shown that the power loss is minimal for some of the estimators of the orders of Markov chains. Our studies provide guidelines on choosing the optimal word length for the comparison of Markov sequences.

The combinatorial derivation

Directory of Open Access Journals (Sweden)

Igor V. Protasov

2013-09-01

$\\Delta(A=\\{g\\in G:|gA\\cap A|=\\infty\\}$. The mapping $\\Delta:\\mathcal{P}_G\\rightarrow\\mathcal{P}_G$, $A\\mapsto\\Delta(A$, is called a combinatorial derivation and can be considered as an analogue of the topological derivation $d:\\mathcal{P}_X\\rightarrow\\mathcal{P}_X$, $A\\mapsto A^d$, where $X$ is a topological space and $A^d$ is the set of all limit points of $A$. Content: elementary properties, thin and almost thin subsets, partitions, inverse construction and $\\Delta$-trajectories,  $\\Delta$ and $d$.

Dynamic Combinatorial Chemistry

DEFF Research Database (Denmark)

Lisbjerg, Micke

This thesis is divided into seven chapters, which can all be read individually. The first chapter, however, contains a general introduction to the chemistry used in the remaining six chapters, and it is therefore recommended to read chapter one before reading the other chapters. Chapter 1...... is a general introductory chapter for the whole thesis. The history and concepts of dynamic combinatorial chemistry are described, as are some of the new and intriguing results recently obtained. Finally, the properties of a broad range of hexameric macrocycles are described in detail. Chapter 2 gives...

CCLab--a multi-objective genetic algorithm based combinatorial library design software and an application for histone deacetylase inhibitor design.

Science.gov (United States)

Fang, Guanghua; Xue, Mengzhu; Su, Mingbo; Hu, Dingyu; Li, Yanlian; Xiong, Bing; Ma, Lanping; Meng, Tao; Chen, Yuelei; Li, Jingya; Li, Jia; Shen, Jingkang

2012-07-15

The introduction of the multi-objective optimization has dramatically changed the virtual combinatorial library design, which can consider many objectives simultaneously, such as synthesis cost and drug-likeness, thus may increase positive rates of biological active compounds. Here we described a software called CCLab (Combinatorial Chemistry Laboratory) for combinatorial library design based on the multi-objective genetic algorithm. Tests of the convergence ability and the ratio to re-take the building blocks in the reference library were conducted to assess the software in silico, and then it was applied to a real case of designing a 5×6 HDAC inhibitor library. Sixteen compounds in the resulted library were synthesized, and the histone deactetylase (HDAC) enzymatic assays proved that 14 compounds showed inhibitory ratios more than 50% against tested 3 HDAC enzymes at concentration of 20 μg/mL, with IC(50) values of 3 compounds comparable to SAHA. These results demonstrated that the CCLab software could enhance the hit rates of the designed library and would be beneficial for medicinal chemists to design focused library in drug development (the software can be downloaded at: http://202.127.30.184:8080/drugdesign.html). Copyright © 2012 Elsevier Ltd. All rights reserved.

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

Directory of Open Access Journals (Sweden)

Adel Tabchy

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

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

Science.gov (United States)

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

2013-01-01

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

Combinatorial Alanine Substitution Enables Rapid Optimization of Cytochrome P450BM3 for Selective Hydroxylation of Large Substrates

KAUST Repository

Lewis, Jared C.

2010-11-24

Made for each other: Combinatorial alanine substitution of active site residues in a thermostable cytochrome P450BM3 variant was used to generate an enzyme that is active with large substrates. Selective hydroxylation of methoxymethylated monosaccharides, alkaloids, and steroids was thus made possible (see Scheme). This approach could be useful for improving the activity of enzymes that show only limited activity with larger substrates. © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Some results from the combinatorial approach to quantum logic

International Nuclear Information System (INIS)

Greechie, R.J.

1976-01-01

The combinatorial approach to quantum logic focuses on certain interconnections between graphs, combinatorial designs, and convex sets as applied to a quantum logic. This article is concerned only with orthomodular lattices and associated structures. A class of complete atomic irreducible semimodular orthomodular lattices is derived which may not be represented as linear subspaces of a vector space over a division ring. Each of these lattices is a proposition system of dimension three. These proposition systems form orthocomplemented non-Desarguesian projective geometries. (B.R.H.)

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

Science.gov (United States)

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

DNA-Encoded Dynamic Combinatorial Chemical Libraries.

Science.gov (United States)

Reddavide, Francesco V; Lin, Weilin; Lehnert, Sarah; Zhang, Yixin

2015-06-26

Dynamic combinatorial chemistry (DCC) explores the thermodynamic equilibrium of reversible reactions. Its application in the discovery of protein binders is largely limited by difficulties in the analysis of complex reaction mixtures. DNA-encoded chemical library (DECL) technology allows the selection of binders from a mixture of up to billions of different compounds; however, experimental results often show low a signal-to-noise ratio and poor correlation between enrichment factor and binding affinity. Herein we describe the design and application of DNA-encoded dynamic combinatorial chemical libraries (EDCCLs). Our experiments have shown that the EDCCL approach can be used not only to convert monovalent binders into high-affinity bivalent binders, but also to cause remarkably enhanced enrichment of potent bivalent binders by driving their in situ synthesis. We also demonstrate the application of EDCCLs in DNA-templated chemical reactions. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combinatorial synthesis of ceramic materials

Science.gov (United States)

Lauf, Robert J.; Walls, Claudia A.; Boatner, Lynn A.

2006-11-14

A combinatorial library includes a gelcast substrate defining a plurality of cavities in at least one surface thereof; and a plurality of gelcast test materials in the cavities, at least two of the test materials differing from the substrate in at least one compositional characteristic, the two test materials differing from each other in at least one compositional characteristic.

WORKSHOP ON NEW DEVELOPMENTS IN CHEMICAL SEPARATIONS FROM COMBINATORIAL CHEMISTRY AND RELATED SYNTHETIC STRATEGIES

Energy Technology Data Exchange (ETDEWEB)

Weber, Stephen G. [University of Pittsburgh, Pittsburgh, Pennsylvania

1998-08-22

The power of combinatorial chemistry and related high throughput synthetic strategies is currently being pursued as a fruitful way to develop molecules and materials with new properties. The strategy is motivated, for example in the pharmaceutical industry, by the difficulty of designing molecules to bind to specific sites on target biomolecules. By synthesizing a variety of similar structures, and then finding the one that has the most potent activity, new so-called lead structures will be found rapidly. Existing lead structures can be optimized. This relatively new approach has many implications for separation science. The most obvious is the call for more separations power: higher resolution, lower concentrations, higher speed. This pressure butresses the traditional directions of research into the development of more useful separations. The advent of chip-based, electroosmotically pumped systems1 will certainly accelerate progress in this traditional direction. The progress in combinatorial chemistry and related synthetic strategies gives rise to two other, broadly significant possibilities for large changes in separation science. One possibility results from the unique requirements of the synthesis of a huge number of products simultaneously. Can syntheses and separations be designed to work together to create strategies that lead to mixtures containing only desired products but without side products? The other possibility results from the need for molecular selectivity in separations. Can combinatorial syntheses and related strategies be used in the development of better separations media? A workshop in two parts was held. In one half-day session, pedagogical presentations educated across the barriers of discipline and scale. In the second half-day session, the participants broke into small groups to flesh out new ideas. A panel summarized the breakout discussions.

Optimization method to branch-and-bound large SBO state spaces under dynamic probabilistic risk assessment via use of LENDIT scales and S2R2 sets

International Nuclear Information System (INIS)

Nielsen, Joseph; Tokuhiro, Akira; Khatry, Jivan; Hiromoto, Robert

2014-01-01

Traditional probabilistic risk assessment (PRA) methods have been developed to evaluate risk associated with complex systems; however, PRA methods lack the capability to evaluate complex dynamic systems. In these systems, time and energy scales associated with transient events may vary as a function of transition times and energies to arrive at a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. Unfortunately DPRA methods introduce issues associated with combinatorial explosion of states. In order to address this combinatorial complexity, a branch-and-bound optimization technique is applied to the DPRA formalism to control the combinatorial state explosion. In addition, a new characteristic scaling metric (LENDIT – length, energy, number, distribution, information and time) is proposed as linear constraints that are used to guide the branch-and-bound algorithm to limit the number of possible states to be analyzed. The LENDIT characterization is divided into four groups or sets – 'state, system, resource and response' (S2R2) – describing reactor operations (normal and off-normal). In this paper we introduce the branch-and-bound DPRA approach and the application of LENDIT scales and S2R2 sets to a station blackout (SBO) transient. (author)

Laguerre-type derivatives: Dobinski relations and combinatorial identities

International Nuclear Information System (INIS)

Penson, K. A.; Blasiak, P.; Horzela, A.; Duchamp, G. H. E.; Solomon, A. I.

2009-01-01

We consider properties of the operators D(r,M)=a r (a † a) M (which we call generalized Laguerre-type derivatives), with r=1,2,..., M=0,1,..., where a and a † are boson annihilation and creation operators, respectively, satisfying [a,a † ]=1. We obtain explicit formulas for the normally ordered form of arbitrary Taylor-expandable functions of D(r,M) with the help of an operator relation that generalizes the Dobinski formula. Coherent state expectation values of certain operator functions of D(r,M) turn out to be generating functions of combinatorial numbers. In many cases the corresponding combinatorial structures can be explicitly identified.

Aircraft technology portfolio optimization using ant colony optimization

Science.gov (United States)

Villeneuve, Frederic J.; Mavris, Dimitri N.

2012-11-01

Technology portfolio selection is a combinatorial optimization problem often faced with a large number of combinations and technology incompatibilities. The main research question addressed in this article is to determine if Ant Colony Optimization (ACO) is better suited than Genetic Algorithms (GAs) and Simulated Annealing (SA) for technology portfolio optimization when incompatibility constraints between technologies are present. Convergence rate, capability to find optima, and efficiency in handling of incompatibilities are the three criteria of comparison. The application problem consists of finding the best technology portfolio from 29 aircraft technologies. The results show that ACO and GAs converge faster and find optima more easily than SA, and that ACO can optimize portfolios with technology incompatibilities without using penalty functions. This latter finding paves the way for more use of ACO when the number of constraints increases, such as in the technology and concept selection for complex engineering systems.

Landscape encodings enhance optimization.

Directory of Open Access Journals (Sweden)

Konstantin Klemm

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

Landscape Encodings Enhance Optimization

Science.gov (United States)

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

2012-01-01

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

Combinatorial reasoning an introduction to the art of counting

CERN Document Server

DeTemple, Duane

2014-01-01

Written by well-known scholars in the field, this book introduces combinatorics alongside modern techniques, showcases the interdisciplinary aspects of the topic, and illustrates how to problem solve with a multitude of exercises throughout. The authors' approach is very reader-friendly and avoids the ""scholarly tone"" found in many books on this topic. Combinatorial Reasoning: An Introduction to the Art of Counting: Focuses on enumeration and combinatorial thinking as a way to develop a variety of effective approaches to solving counting problemsIncludes brief summaries of basic concepts f

Virtual screening of combinatorial library of novel benzenesulfonamides on mycobacterial carbonic anhydrase II

Directory of Open Access Journals (Sweden)

Dikant F.

2016-12-01

Full Text Available Combinatorial library of novel benzenesulfonamides was docked (Schrodinger Glide into mycobacterial carbonic anhydrase (mtCA II and human (hCA II isoforms with an aim to find drug candidates with selective activity on mtCA II. The predicted selectivity was calculated based on optimized MM-GBSA free energies for ligand enzyme interactions. Selectivity, LogP (o/w and interaction energy were used to calculate the selection index which determined the subset of best scoring molecules selected for further evaluation. Structure-activity relationship was found for fragment subsets, showing us the possible way regarding how to influence lipophilicity without affecting ligand-enzyme binding properties.

Capacity Allocation and Revenue Sharing in Airline Alliances: A Combinatorial Auction-Based Modeling

Directory of Open Access Journals (Sweden)

Ying-jing Gu

2017-01-01

Full Text Available This paper attempts to establish a framework to help airline alliances effectively allocate their seat capacity with the purpose of maximizing alliances’ revenue. By assuming the airline alliance as the auctioneer and seat capacity in an itinerary as lots, the combinatorial auction model is constructed to optimize the allocation of the seat, and the revenue sharing method is established to share revenue between partners by Vickrey-Clarke-Groves (VCG mechanism. The result of the numerical study shows that the seat capacity allocation is effective even without information exchanging completely and the twofold revenue shares method shows more excitation for the airlines.

Best Hiding Capacity Scheme for Variable Length Messages Using Particle Swarm Optimization

Science.gov (United States)

Bajaj, Ruchika; Bedi, Punam; Pal, S. K.

Steganography is an art of hiding information in such a way that prevents the detection of hidden messages. Besides security of data, the quantity of data that can be hidden in a single cover medium, is also very important. We present a secure data hiding scheme with high embedding capacity for messages of variable length based on Particle Swarm Optimization. This technique gives the best pixel positions in the cover image, which can be used to hide the secret data. In the proposed scheme, k bits of the secret message are substituted into k least significant bits of the image pixel, where k varies from 1 to 4 depending on the message length. The proposed scheme is tested and results compared with simple LSB substitution, uniform 4-bit LSB hiding (with PSO) for the test images Nature, Baboon, Lena and Kitty. The experimental study confirms that the proposed method achieves high data hiding capacity and maintains imperceptibility and minimizes the distortion between the cover image and the obtained stego image.

Combinatorial interpretations of particular evaluations of complete and elementary symmetric functions

OpenAIRE

Mongelli, Pietro

2011-01-01

The Jacobi-Stirling numbers and the Legendre-Stirling numbers of the first and second kind were first introduced in [6], [7]. In this paper we note that Jacobi-Stirling numbers and Legendre-Stirling numbers are specializations of elementary and complete symmetric functions. We then study combinatorial interpretations of this specialization and obtain new combinatorial interpretations of the Jacobi-Stirling and Legendre-Stirling numbers.

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

Science.gov (United States)

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

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

Gian-Carlos Rota and Combinatorial Math.

Science.gov (United States)

Kolata, Gina Bari

1979-01-01

Presents the first of a series of occasional articles about mathematics as seen through the eyes of its prominent scholars. In an interview with Gian-Carlos Rota of the Massachusetts Institute of Technology he discusses how combinatorial mathematics began as a field and its future. (HM)

A Model of Students' Combinatorial Thinking

Science.gov (United States)

Lockwood, Elise

2013-01-01

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

Capability of focused Ar ion beam sputtering for combinatorial synthesis of metal films

International Nuclear Information System (INIS)

Nagata, T.; Haemori, M.; Chikyow, T.

2009-01-01

The authors examined the use of focused Ar ion beam sputtering (FAIS) for combinatorial synthesis. A Langmuir probe revealed that the electron temperature and density for FAIS of metal film deposition was lower than that of other major combinatorial thin film growth techniques such as pulsed laser deposition. Combining FAIS with the combinatorial method allowed the compositional fraction of the Pt-Ru binary alloy to be systematically controlled. Pt-Ru alloy metal film grew epitaxially on ZnO substrates, and crystal structures changed from the Pt phase (cubic structure) to the Ru phase (hexagonal structure) in the Pt-Ru alloy phase diagram. The alloy film has a smooth surface, with the Ru phase, in particular, showing a clear step-and-terrace structure. The combination of FAIS and the combinatorial method has major potential for the fabrication of high quality composition-spread metal film.

Capability of focused Ar ion beam sputtering for combinatorial synthesis of metal films

Energy Technology Data Exchange (ETDEWEB)

Nagata, T.; Haemori, M.; Chikyow, T. [Advanced Electric Materials Center, National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044 (Japan)

2009-05-15

The authors examined the use of focused Ar ion beam sputtering (FAIS) for combinatorial synthesis. A Langmuir probe revealed that the electron temperature and density for FAIS of metal film deposition was lower than that of other major combinatorial thin film growth techniques such as pulsed laser deposition. Combining FAIS with the combinatorial method allowed the compositional fraction of the Pt-Ru binary alloy to be systematically controlled. Pt-Ru alloy metal film grew epitaxially on ZnO substrates, and crystal structures changed from the Pt phase (cubic structure) to the Ru phase (hexagonal structure) in the Pt-Ru alloy phase diagram. The alloy film has a smooth surface, with the Ru phase, in particular, showing a clear step-and-terrace structure. The combination of FAIS and the combinatorial method has major potential for the fabrication of high quality composition-spread metal film.

A Robust and Versatile Method of Combinatorial Chemical Synthesis of Gene Libraries via Hierarchical Assembly of Partially Randomized Modules

Science.gov (United States)

Popova, Blagovesta; Schubert, Steffen; Bulla, Ingo; Buchwald, Daniela; Kramer, Wilfried

2015-01-01

A major challenge in gene library generation is to guarantee a large functional size and diversity that significantly increases the chances of selecting different functional protein variants. The use of trinucleotides mixtures for controlled randomization results in superior library diversity and offers the ability to specify the type and distribution of the amino acids at each position. Here we describe the generation of a high diversity gene library using tHisF of the hyperthermophile Thermotoga maritima as a scaffold. Combining various rational criteria with contingency, we targeted 26 selected codons of the thisF gene sequence for randomization at a controlled level. We have developed a novel method of creating full-length gene libraries by combinatorial assembly of smaller sub-libraries. Full-length libraries of high diversity can easily be assembled on demand from smaller and much less diverse sub-libraries, which circumvent the notoriously troublesome long-term archivation and repeated proliferation of high diversity ensembles of phages or plasmids. We developed a generally applicable software tool for sequence analysis of mutated gene sequences that provides efficient assistance for analysis of library diversity. Finally, practical utility of the library was demonstrated in principle by assessment of the conformational stability of library members and isolating protein variants with HisF activity from it. Our approach integrates a number of features of nucleic acids synthetic chemistry, biochemistry and molecular genetics to a coherent, flexible and robust method of combinatorial gene synthesis. PMID:26355961

Algorithms in combinatorial design theory

CERN Document Server

Colbourn, CJ

1985-01-01

The scope of the volume includes all algorithmic and computational aspects of research on combinatorial designs. Algorithmic aspects include generation, isomorphism and analysis techniques - both heuristic methods used in practice, and the computational complexity of these operations. The scope within design theory includes all aspects of block designs, Latin squares and their variants, pairwise balanced designs and projective planes and related geometries.

Synthesizing optimal waste blends

International Nuclear Information System (INIS)

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

1996-01-01

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

Summation on the basis of combinatorial representation of equal powers

Directory of Open Access Journals (Sweden)

Alexander I. Nikonov

2016-03-01

Full Text Available In the paper the conclusion of combinatorial expressions for the sums of members of several sequences is considered. Conclusion is made on the basis of combinatorial representation of the sum of the weighted equal powers. The weighted members of a geometrical progression, the simple arithmetic-geometrical and combined progressions are subject to summation. One of principal places in the given conclusion occupies representation of members of each of the specified progressions in the form of matrix elements. The row of this matrix is formed with use of a gang of equal powers with the set weight factor. Besides, in work formulas of combinatorial identities with participation of free components of the sums of equal powers, and also separate power-member of sequence of equal powers or a geometrical progression are presented. All presented formulas have the general basis-components of the sums of equal powers.

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

Science.gov (United States)

Staver, John R.; Harty, Harold

1979-01-01

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

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

Science.gov (United States)

Su, Zhangli

2016-01-01

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

On the complexity of determining tolerances for ->e--optimal solutions to min-max combinatorial optimization problems

NARCIS (Netherlands)

Ghosh, D.; Sierksma, G.

2000-01-01

Sensitivity analysis of e-optimal solutions is the problem of calculating the range within which a problem parameter may lie so that the given solution re-mains e-optimal. In this paper we study the sensitivity analysis problem for e-optimal solutions tocombinatorial optimization problems with

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

Science.gov (United States)

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

2016-01-01

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

Frontiers in Optimization : Theory and Applications

CERN Document Server

Maulik, Ujjwal; Li, Xiang; FOTA 2016; Operations Research and Optimization

2018-01-01

This book discusses recent developments in the vast domain of optimization. Featuring papers presented at the 1st International Conference on Frontiers in Optimization: Theory and Applications (FOTA 2016), held at the Heritage Institute of Technology, Kolkata, on 24–26 December 2016, it opens new avenues of research in all topics related to optimization, such as linear and nonlinear optimization; combinatorial-, stochastic-, dynamic-, fuzzy-, and uncertain optimization; optimal control theory; as well as multi-objective, evolutionary and convex optimization and their applications in intelligent information and technology, systems science, knowledge management, information and communication, supply chain and inventory control, scheduling, networks, transportation and logistics and finance. The book is a valuable resource for researchers, scientists and engineers from both academia and industry.

INdAM conference "CoMeTA 2013 - Combinatorial Methods in Topology and Algebra"

CERN Document Server

Delucchi, Emanuele; Moci, Luca

2015-01-01

Combinatorics plays a prominent role in contemporary mathematics, due to the vibrant development it has experienced in the last two decades and its many interactions with other subjects. This book arises from the INdAM conference "CoMeTA 2013 - Combinatorial Methods in Topology and Algebra,'' which was held in Cortona in September 2013. The event brought together emerging and leading researchers at the crossroads of Combinatorics, Topology and Algebra, with a particular focus on new trends in subjects such as: hyperplane arrangements; discrete geometry and combinatorial topology; polytope theory and triangulations of manifolds; combinatorial algebraic geometry and commutative algebra; algebraic combinatorics; and combinatorial representation theory. The book is divided into two parts. The first expands on the topics discussed at the conference by providing additional background and explanations, while the second presents original contributions on new trends in the topics addressed by the conference.

Combinatorial algebraic geometry selected papers from the 2016 apprenticeship program

CERN Document Server

Sturmfels, Bernd

2017-01-01

This volume consolidates selected articles from the 2016 Apprenticeship Program at the Fields Institute, part of the larger program on Combinatorial Algebraic Geometry that ran from July through December of 2016. Written primarily by junior mathematicians, the articles cover a range of topics in combinatorial algebraic geometry including curves, surfaces, Grassmannians, convexity, abelian varieties, and moduli spaces. This book bridges the gap between graduate courses and cutting-edge research by connecting historical sources, computation, explicit examples, and new results.

Optimization of the alkyl side chain length of fluorine-18-labeled 7α-alkyl-fluoroestradiol

International Nuclear Information System (INIS)

Okamoto, Mayumi; Shibayama, Hiromitsu; Naka, Kyosuke; Kitagawa, Yuya; Ishiwata, Kiichi; Shimizu, Isao; Toyohara, Jun

2016-01-01

Introduction: Several lines of evidence suggest that 7α-substituted estradiol derivatives bind to the estrogen receptor (ER). In line with this hypothesis, we designed and synthesized 18 F-labeled 7α-fluoroalkylestradiol (Cn-7α-[ 18 F]FES) derivatives as molecular probes for visualizing ERs. Previously, we successfully synthesized 7α-(3-[ 18 F]fluoropropyl)estradiol (C3-7α-[ 18 F]FES) and showed promising results for quantification of ER density in vivo, although extensive metabolism was observed in rodents. Therefore, optimization of the alkyl side chain length is needed to obtain suitable radioligands based on Cn-7α-substituted estradiol pharmacophores. Methods: We synthesized fluoromethyl (23; C1-7α-[ 18 F]FES) to fluorohexyl (26; C6-7α-[ 18 F]FES) derivatives, except fluoropropyl (C3-7α-[ 18 F]FES) and fluoropentyl derivatives (C5-7α-[ 18 F]FES), which have been previously synthesized. In vitro binding to the α-subtype (ERα) isoform of ERs and in vivo biodistribution studies in mature female mice were carried out. Results: The in vitro IC 50 value of Cn-7α-FES tended to gradually decrease depending on the alkyl side chain length. C1-7α-[ 18 F]FES (23) showed the highest uptake in ER-rich tissues such as the uterus. Uterus uptake also gradually decreased depending on the alkyl side chain length. As a result, in vivo uterus uptake reflected the in vitro ERα affinity of each compound. Bone uptake, which indicates de-fluorination, was marked in 7α-(2-[ 18 F]fluoroethyl)estradiol (C2-7α-[ 18 F]FES) (24) and 7α-(4-[ 18 F]fluorobutyl)estradiol (C4-7α-[ 18 F]FES) (25) derivatives. However, C1-7α-[ 18 F]FES (23) and C6-7α-[ 18 F]FES (26) showed limited uptake in bone. As a result, in vivo bone uptake (de-fluorination) showed a bell-shaped pattern, depending on the alkyl side chain length. C1-7α-[ 18 F]FES (23) showed the same levels of uptake in uterus and bone compared with those of 16α-[ 18 F]fluoro-17β-estradiol. Conclusions: The optimal alkyl

PIPERIDINE OLIGOMERS AND COMBINATORIAL LIBRARIES THEREOF

DEFF Research Database (Denmark)

1999-01-01

The present invention relates to piperidine oligomers, methods for the preparation of piperidine oligomers and compound libraries thereof, and the use of piperidine oligomers as drug substances. The present invention also relates to the use of combinatorial libraries of piperidine oligomers...... in libraries (arrays) of compounds especially suitable for screening purposes....

Three Syntactic Theories for Combinatory Graph Reduction

DEFF Research Database (Denmark)

Danvy, Olivier; Zerny, Ian

2011-01-01

in a third syntactic theory. The structure of the store-based abstract machine corresponding to this third syntactic theory oincides with that of Turner's original reduction machine. The three syntactic theories presented here The three syntactic heories presented here therefore have the following......We present a purely syntactic theory of graph reduction for the canonical combinators S, K, and I, where graph vertices are represented with evaluation contexts and let expressions. We express this syntactic theory as a reduction semantics, which we refocus into the first storeless abstract machine...... for combinatory graph reduction, which we refunctionalize into the first storeless natural semantics for combinatory graph reduction.We then factor out the introduction of let expressions to denote as many graph vertices as possible upfront instead of on demand, resulting in a second syntactic theory, this one...

Three Syntactic Theories for Combinatory Graph Reduction

DEFF Research Database (Denmark)

Danvy, Olivier; Zerny, Ian

2013-01-01

, as a store-based reduction semantics of combinatory term graphs. We then refocus this store-based reduction semantics into a store-based abstract machine. The architecture of this store-based abstract machine coincides with that of Turner's original reduction machine. The three syntactic theories presented......We present a purely syntactic theory of graph reduction for the canonical combinators S, K, and I, where graph vertices are represented with evaluation contexts and let expressions. We express this rst syntactic theory as a storeless reduction semantics of combinatory terms. We then factor out...... the introduction of let expressions to denote as many graph vertices as possible upfront instead of on demand . The factored terms can be interpreted as term graphs in the sense of Barendregt et al. We express this second syntactic theory, which we prove equivalent to the rst, as a storeless reduction semantics...

Quantum fields and processes a combinatorial approach

CERN Document Server

Gough, John

2018-01-01

Wick ordering of creation and annihilation operators is of fundamental importance for computing averages and correlations in quantum field theory and, by extension, in the Hudson-Parthasarathy theory of quantum stochastic processes, quantum mechanics, stochastic processes, and probability. This book develops the unified combinatorial framework behind these examples, starting with the simplest mathematically, and working up to the Fock space setting for quantum fields. Emphasizing ideas from combinatorics such as the role of lattice of partitions for multiple stochastic integrals by Wallstrom-Rota and combinatorial species by Joyal, it presents insights coming from quantum probability. It also introduces a 'field calculus' which acts as a succinct alternative to standard Feynman diagrams and formulates quantum field theory (cumulant moments, Dyson-Schwinger equation, tree expansions, 1-particle irreducibility) in this language. Featuring many worked examples, the book is aimed at mathematical physicists, quant...

Quantum fields and processes a combinatorial approach

CERN Document Server

Gough, John

2018-01-01

Wick ordering of creation and annihilation operators is of fundamental importance for computing averages and correlations in quantum field theory and, by extension, in the Hudson–Parthasarathy theory of quantum stochastic processes, quantum mechanics, stochastic processes, and probability. This book develops the unified combinatorial framework behind these examples, starting with the simplest mathematically, and working up to the Fock space setting for quantum fields. Emphasizing ideas from combinatorics such as the role of lattice of partitions for multiple stochastic integrals by Wallstrom–Rota and combinatorial species by Joyal, it presents insights coming from quantum probability. It also introduces a 'field calculus' which acts as a succinct alternative to standard Feynman diagrams and formulates quantum field theory (cumulant moments, Dyson–Schwinger equation, tree expansions, 1-particle irreducibility) in this language. Featuring many worked examples, the book is aimed at mathematical physicists,...

Recent developments of discrete material optimization of laminated composite structures

DEFF Research Database (Denmark)

Lund, Erik; Sørensen, Rene

2015-01-01

This work will give a quick summary of recent developments of the Discrete Material Optimization approach for structural optimization of laminated composite structures. This approach can be seen as a multi-material topology optimization approach for selecting the best ply material and number...... of plies in a laminated composite structure. The conceptual combinatorial design problem is relaxed to a continuous problem such that well-established gradient based optimization techniques can be applied, and the optimization problem is solved on basis of interpolation schemes with penalization...

A Convergent Solid-Phase Synthesis of Actinomycin Analogues - Towards Implementation of Double-Combinatorial Chemistry

DEFF Research Database (Denmark)

Tong, Glenn; Nielsen, John

1996-01-01

The actinomycin antibiotics bind to nucleic acids via both intercalation and hydrogen bonding. We found this 'double-action attack' mechanism very attractive in our search for a novel class of nucleic acid binders. A highly convergent, solid-phase synthetic strategy has been developed for a class...... with the requirements for combinatorial synthesis and furthermore, the final segment condensation allows, for the first time, double-combinatorial chemistry to be performed where two combinatorial libraries can be reacted with each other. Copyright (C) 1996 Elsevier Science Ltd....

A fast combinatorial enhancement technique for earthquake damage identification based on remote sensing image

Science.gov (United States)

Dou, Aixia; Wang, Xiaoqing; Ding, Xiang; Du, Zecheng

2010-11-01

On the basis of the study on the enhancement methods of remote sensing images obtained after several earthquakes, the paper designed a new and optimized image enhancement model which was implemented by combining different single methods. The patterns of elementary model units and combined types of model were defined. Based on the enhancement model database, the algorithm of combinatorial model was brought out via C++ programming. The combined model was tested by processing the aerial remote sensing images obtained after 1976 Tangshan earthquake. It was proved that the definition and implementation of combined enhancement model can efficiently improve the ability and flexibility of image enhancement algorithm.

Log-balanced combinatorial sequences

Directory of Open Access Journals (Sweden)

Tomislav Došlic

2005-01-01

Full Text Available We consider log-convex sequences that satisfy an additional constraint imposed on their rate of growth. We call such sequences log-balanced. It is shown that all such sequences satisfy a pair of double inequalities. Sufficient conditions for log-balancedness are given for the case when the sequence satisfies a two- (or more- term linear recurrence. It is shown that many combinatorially interesting sequences belong to this class, and, as a consequence, that the above-mentioned double inequalities are valid for all of them.

AFRICAN BUFFALO OPTIMIZATION ico-pdf

Directory of Open Access Journals (Sweden)

Julius Beneoluchi Odili

2016-02-01

Full Text Available This is an introductory paper to the newly-designed African Buffalo Optimization (ABO algorithm for solving combinatorial and other optimization problems. The algorithm is inspired by the behavior of African buffalos, a species of wild cows known for their extensive migrant lifestyle. This paper presents an overview of major metaheuristic algorithms with the aim of providing a basis for the development of the African Buffalo Optimization algorithm which is a nature-inspired, population-based metaheuristic algorithm. Experimental results obtained from applying the novel ABO to solve a number of benchmark global optimization test functions as well as some symmetric and asymmetric Traveling Salesman’s Problems when compared to the results obtained from using other popular optimization methods show that the African Buffalo Optimization is a worthy addition to the growing number of swarm intelligence optimization techniques.

Multiobjective optimal placement of switches and protective devices in electric power distribution systems using ant colony optimization

Energy Technology Data Exchange (ETDEWEB)

Tippachon, Wiwat; Rerkpreedapong, Dulpichet [Department of Electrical Engineering, Kasetsart University, 50 Phaholyothin Rd., Ladyao, Jatujak, Bangkok 10900 (Thailand)

2009-07-15

This paper presents a multiobjective optimization methodology to optimally place switches and protective devices in electric power distribution networks. Identifying the type and location of them is a combinatorial optimization problem described by a nonlinear and nondifferential function. The multiobjective ant colony optimization (MACO) has been applied to this problem to minimize the total cost while simultaneously minimize two distribution network reliability indices including system average interruption frequency index (SAIFI) and system interruption duration index (SAIDI). Actual distribution feeders are used in the tests, and test results have shown that the algorithm can determine the set of optimal nondominated solutions. It allows the utility to obtain the optimal type and location of devices to achieve the best system reliability with the lowest cost. (author)

Novel Combinatorial Chemistry-Derived Inhibitors of Oncogenic Phosphatases

National Research Council Canada - National Science Library

Lazo, John

1999-01-01

Our overall goal of this US Army Breast Cancer Grant entitled "Novel Combinatorial Chemistry-Derived Inhibitors of Oncogenic Phosphatases" is to identity and develop novel therapeutic agents for human breast cancer...

Combinatorial Solid-Phase Synthesis of Balanol Analogues

DEFF Research Database (Denmark)

Nielsen, John; Lyngsø, Lars Ole

1996-01-01

The natural product balanol has served as a template for the design and synthesis of a combinatorial library using solid-phase chemistry. Using a retrosynthetic analysis, the structural analogues have been assembled from three relatively accessible building blocks. The solid-phase chemistry inclu...

Infinitary Combinatory Reduction Systems: Normalising Reduction Strategies

NARCIS (Netherlands)

Ketema, J.; Simonsen, Jakob Grue

2010-01-01

We study normalising reduction strategies for infinitary Combinatory Reduction Systems (iCRSs). We prove that all fair, outermost-fair, and needed-fair strategies are normalising for orthogonal, fully-extended iCRSs. These facts properly generalise a number of results on normalising strategies in

Mitigation of Control Channel Jamming via Combinatorial Key Distribution

Science.gov (United States)

Falahati, Abolfazl; Azarafrooz, Mahdi

The problem of countering control channel jamming against internal adversaries in wireless ad hoc networks is addressed. Using combinatorial key distribution, a new method to secure the control channel access is introduced. This method, utilizes the established keys in the key establishment phase to hide the location of control channels without the need for a secure BS. This is in obtained by combination of a collision free one-way function and a combinatorial key establishment method. The proposed scheme can be considered as a special case of the ALOHA random access schemes which uses the common established keys as its seeds to generate the pattern of transmission.

Functional completeness of the mixed λ-calculus and combinatory logic

DEFF Research Database (Denmark)

Nielson, Hanne Riis; Nielson, Flemming

1990-01-01

Functional completeness of the combinatory logic means that every lambda-expression may be translated into an equivalent combinator expression and this is the theoretical basis for the implementation of functional languages on combinator-based abstract machines. To obtain efficient implementations...... it is important to distinguish between early and late binding times, i.e. to distinguish between compile-time and run-time computations. The authors therefore introduce a two-level version of the lambda-calculus where this distinction is made in an explicit way. Turning to the combinatory logic they generate...

A combinatorial perspective of the protein inference problem.

Science.gov (United States)

Yang, Chao; He, Zengyou; Yu, Weichuan

2013-01-01

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

Effects of Suboptimal Bidding in Combinatorial Auctions

Science.gov (United States)

Schneider, Stefan; Shabalin, Pasha; Bichler, Martin

Though the VCG auction assumes a central place in the mechanism design literature, there are a number of reasons for favoring iterative combinatorial auction designs. Several promising ascending auction formats have been developed throughout the past few years based on primal-dual and subgradient algorithms and linear programming theory. Prices are interpreted as a feasible dual solution and the provisional allocation is interpreted as a feasible primal solution. iBundle( 3) (Parkes and Ungar 2000), dVSV (de Vries et al. 2007) and the Ascending Proxy auction (Ausubel and Milgrom 2002) result in VCG payoffs when the coalitional value function satisfies the buyer submodularity condition and bidders bid straightforward, which is an expost Nash equilibrium in that case. iBEA and CreditDebit auctions (Mishra and Parkes 2007) do not even require the buyer submodularity condition and achieve the same properties for general valuations. In many situations, however, one cannot assume bidders to bid straightforward and it is not clear from the theory how these non-linear personalized price auctions (NLPPAs) perform in this case. Robustness of auctions with respect to different bidding behavior is therefore a critical issue for any application. We have conducted a large number of computational experiments to analyze the performance of NLPPA designs with respect to different bidding strategies and different valuation models. We compare the results of NLPPAs to those of the VCG auction and those of iterative combinatorial auctions with approximate linear prices, such as ALPS (Bichler et al. 2009) and the Combinatorial Clock auction (Porter et al. 2003).

Design of combinatorial libraries for the exploration of virtual hits from fragment space searches with LoFT.

Science.gov (United States)

Lessel, Uta; Wellenzohn, Bernd; Fischer, J Robert; Rarey, Matthias

2012-02-27

A case study is presented illustrating the design of a focused CDK2 library. The scaffold of the library was detected by a feature trees search in a fragment space based on reactions from combinatorial chemistry. For the design the software LoFT (Library optimizer using Feature Trees) was used. The special feature called FTMatch was applied to restrict the parts of the queries where the reagents are permitted to match. This way a 3D scoring function could be simulated. Results were compared with alternative designs by GOLD docking and ROCS 3D alignments.

Control of p-type and n-type thermoelectric properties of bismuth telluride thin films by combinatorial sputter coating technology

International Nuclear Information System (INIS)

Goto, Masahiro; Sasaki, Michiko; Xu, Yibin; Zhan, Tianzhuo; Isoda, Yukihiro; Shinohara, Yoshikazu

2017-01-01

Highlights: • p- and n-type bismuth telluride thin films have been synthesized using a combinatorial sputter coating system (COSCOS) while changing only one of the experimental conditions, the RF power. • The dimensionless figure of merit (ZT) was optimized by the technique. • The fabrication of a Π-structured TE device was demonstrated. - Abstract: p- and n-type bismuth telluride thin films have been synthesized by using a combinatorial sputter coating system (COSCOS). The crystal structure and crystal preferred orientation of the thin films were changed by controlling the coating condition of the radio frequency (RF) power during the sputter coating. As a result, the p- and n-type films and their dimensionless figure of merit (ZT) were optimized by the technique. The properties of the thin films such as the crystal structure, crystal preferred orientation, material composition and surface morphology were analyzed by X-ray diffraction, energy-dispersive X-ray spectroscopy and atomic force microscopy. Also, the thermoelectric properties of the Seebeck coefficient, electrical conductivity and thermal conductivity were measured. ZT for n- and p-type bismuth telluride thin films was found to be 0.27 and 0.40 at RF powers of 90 and 120 W, respectively. The proposed technology can be used to fabricate thermoelectric p–n modules of bismuth telluride without any doping process.

Control of p-type and n-type thermoelectric properties of bismuth telluride thin films by combinatorial sputter coating technology

Energy Technology Data Exchange (ETDEWEB)

Goto, Masahiro, E-mail: goto.masahiro@nims.go.jp [Thermoelectric Materials Group, Center for Green Research on Energy and Environmental Materials, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan); Thermal Management and Thermoelectric Materials Group, Center for Materials Research by Information Integration (CMI2), National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan); Sasaki, Michiko [Thermal Management and Thermoelectric Materials Group, Center for Materials Research by Information Integration (CMI2), National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan); Xu, Yibin [Thermal Management and Thermoelectric Materials Group, Center for Materials Research by Information Integration (CMI2), National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan); Materials Database Group, Center for Materials Research by Information Integration (CMI2), National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan); Zhan, Tianzhuo [Thermal Management and Thermoelectric Materials Group, Center for Materials Research by Information Integration (CMI2), National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan); Isoda, Yukihiro [Thermoelectric Materials Group, Center for Green Research on Energy and Environmental Materials, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan); Shinohara, Yoshikazu [Thermoelectric Materials Group, Center for Green Research on Energy and Environmental Materials, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan); Thermal Management and Thermoelectric Materials Group, Center for Materials Research by Information Integration (CMI2), National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan)

2017-06-15

Highlights: • p- and n-type bismuth telluride thin films have been synthesized using a combinatorial sputter coating system (COSCOS) while changing only one of the experimental conditions, the RF power. • The dimensionless figure of merit (ZT) was optimized by the technique. • The fabrication of a Π-structured TE device was demonstrated. - Abstract: p- and n-type bismuth telluride thin films have been synthesized by using a combinatorial sputter coating system (COSCOS). The crystal structure and crystal preferred orientation of the thin films were changed by controlling the coating condition of the radio frequency (RF) power during the sputter coating. As a result, the p- and n-type films and their dimensionless figure of merit (ZT) were optimized by the technique. The properties of the thin films such as the crystal structure, crystal preferred orientation, material composition and surface morphology were analyzed by X-ray diffraction, energy-dispersive X-ray spectroscopy and atomic force microscopy. Also, the thermoelectric properties of the Seebeck coefficient, electrical conductivity and thermal conductivity were measured. ZT for n- and p-type bismuth telluride thin films was found to be 0.27 and 0.40 at RF powers of 90 and 120 W, respectively. The proposed technology can be used to fabricate thermoelectric p–n modules of bismuth telluride without any doping process.

Combinatorial biosynthesis of medicinal plant secondary metabolites

NARCIS (Netherlands)

Julsing, Mattijs K.; Koulman, Albert; Woerdenbag, Herman J.; Quax, Wim J.; Kayser, Oliver

2006-01-01

Combinatorial biosynthesis is a new tool in the generation of novel natural products and for the production of rare and expensive natural products. The basic concept is combining metabolic pathways in different organisms on a genetic level. As a consequence heterologous organisms provide precursors

Combinatorial aspects of covering arrays

Directory of Open Access Journals (Sweden)

Charles J. Colbourn

2004-11-01

Full Text Available Covering arrays generalize orthogonal arrays by requiring that t -tuples be covered, but not requiring that the appearance of t -tuples be balanced.Their uses in screening experiments has found application in software testing, hardware testing, and a variety of fields in which interactions among factors are to be identified. Here a combinatorial view of covering arrays is adopted, encompassing basic bounds, direct constructions, recursive constructions, algorithmic methods, and applications.

KENO-IV/CG, the combinatorial geometry version of the KENO Monte Carlo criticality safety program

International Nuclear Information System (INIS)

West, J.T.; Petrie, L.M.; Fraley, S.K.

1979-09-01

KENO-IV/CG was developed to merge the simple geometry input description utilized by combinatorial geometry with the repeating lattice feature of the original KENO geometry package. The result is a criticality code with the ability to model a complex system of repeating rectangular lattices inside a complicated three-dimensional geometry system. Furthermore, combinatorial geometry was modified to differentiate between combinatorial zones describing a particular KENO BOX to be repeated in a KENO array and those combinatorial zones describing geometry external to an array. This allows the user to maintain a simple coordinate system without any geometric conflict due to spatial overlap. Several difficult criticality design problems have been solved with the new geometry package in KENO-IV/CG, thus illustrating the power of the code to model difficult geometries with a minimum of effort

BWR fuel cycle optimization using neural networks

International Nuclear Information System (INIS)

Ortiz-Servin, Juan Jose; Castillo, Jose Alejandro; Pelta, David Alejandro

2011-01-01

Highlights: → OCONN a new system to optimize all nuclear fuel management steps in a coupled way. → OCON is based on an artificial recurrent neural network to find the best combination of partial solutions to each fuel management step. → OCONN works with a fuel lattices' stock, a fuel reloads' stock and a control rod patterns' stock, previously obtained with different heuristic techniques. → Results show OCONN is able to find good combinations according the global objective function. - Abstract: In nuclear fuel management activities for BWRs, four combinatorial optimization problems are solved: fuel lattice design, axial fuel bundle design, fuel reload design and control rod patterns design. Traditionally, these problems have been solved in separated ways due to their complexity and the required computational resources. In the specialized literature there are some attempts to solve fuel reloads and control rod patterns design or fuel lattice and axial fuel bundle design in a coupled way. In this paper, the system OCONN to solve all of these problems in a coupled way is shown. This system is based on an artificial recurrent neural network to find the best combination of partial solutions to each problem, in order to maximize a global objective function. The new system works with a fuel lattices' stock, a fuel reloads' stock and a control rod patterns' stock, previously obtained with different heuristic techniques. The system was tested to design an equilibrium cycle with a cycle length of 18 months. Results show that the new system is able to find good combinations. Cycle length is reached and safety parameters are fulfilled.

Optical tools for high-throughput screening of abrasion resistance of combinatorial libraries of organic coatings

Science.gov (United States)

Potyrailo, Radislav A.; Chisholm, Bret J.; Olson, Daniel R.; Brennan, Michael J.; Molaison, Chris A.

2002-02-01

Design, validation, and implementation of an optical spectroscopic system for high-throughput analysis of combinatorially developed protective organic coatings are reported. Our approach replaces labor-intensive coating evaluation steps with an automated system that rapidly analyzes 8x6 arrays of coating elements that are deposited on a plastic substrate. Each coating element of the library is 10 mm in diameter and 2 to 5 micrometers thick. Performance of coatings is evaluated with respect to their resistance to wear abrasion because this parameter is one of the primary considerations in end-use applications. Upon testing, the organic coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Coatings are abraded using industry-accepted abrasion test methods at single-or multiple-abrasion conditions, followed by high- throughput analysis of abrasion-induced light scatter. The developed automated system is optimized for the analysis of diffusively scattered light that corresponds to 0 to 30% haze. System precision of 0.1 to 2.5% relative standard deviation provides capability for the reliable ranking of coatings performance. While the system was implemented for high-throughput screening of combinatorially developed organic protective coatings for automotive applications, it can be applied to a variety of other applications where materials ranking can be achieved using optical spectroscopic tools.

Ant Colony Optimization ACO For The Traveling Salesman Problem TSP Using Partitioning

Directory of Open Access Journals (Sweden)

Alok Bajpai

2015-08-01

Full Text Available Abstract An ant colony optimization is a technique which was introduced in 1990s and which can be applied to a variety of discrete combinatorial optimization problem and to continuous optimization. The ACO algorithm is simulated with the foraging behavior of the real ants to find the incremental solution constructions and to realize a pheromone laying-and-following mechanism. This pheromone is the indirect communication among the ants. In this paper we introduces the partitioning technique based on the divide and conquer strategy for the traveling salesman problem which is one of the most important combinatorial problem in which the original problem is partitioned into the group of sub problems. And then we apply the ant colony algorithm using candidate list strategy for each smaller sub problems. After that by applying the local optimization and combining the sub problems to find the good solution for the original problem by improving the exploration efficiency of the ants. At the end of this paper we have also be presented the comparison of result with the normal ant colony system for finding the optimal solution to the traveling salesman problem.

A Hybrid Method for Modeling and Solving Supply Chain Optimization Problems with Soft and Logical Constraints

Directory of Open Access Journals (Sweden)

Paweł Sitek

2016-01-01

Full Text Available This paper presents a hybrid method for modeling and solving supply chain optimization problems with soft, hard, and logical constraints. Ability to implement soft and logical constraints is a very important functionality for supply chain optimization models. Such constraints are particularly useful for modeling problems resulting from commercial agreements, contracts, competition, technology, safety, and environmental conditions. Two programming and solving environments, mathematical programming (MP and constraint logic programming (CLP, were combined in the hybrid method. This integration, hybridization, and the adequate multidimensional transformation of the problem (as a presolving method helped to substantially reduce the search space of combinatorial models for supply chain optimization problems. The operation research MP and declarative CLP, where constraints are modeled in different ways and different solving procedures are implemented, were linked together to use the strengths of both. This approach is particularly important for the decision and combinatorial optimization models with the objective function and constraints, there are many decision variables, and these are summed (common in manufacturing, supply chain management, project management, and logistic problems. The ECLiPSe system with Eplex library was proposed to implement a hybrid method. Additionally, the proposed hybrid transformed model is compared with the MILP-Mixed Integer Linear Programming model on the same data instances. For illustrative models, its use allowed finding optimal solutions eight to one hundred times faster and reducing the size of the combinatorial problem to a significant extent.

Optimal recombination in genetic algorithms for combinatorial optimization problems: Part II

Directory of Open Access Journals (Sweden)

Eremeev Anton V.

2014-01-01

Full Text Available This paper surveys results on complexity of the optimal recombination problem (ORP, which consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. In Part II, we consider the computational complexity of ORPs arising in genetic algorithms for problems on permutations: the Travelling Salesman Problem, the Shortest Hamilton Path Problem and the Makespan Minimization on Single Machine and some other related problems. The analysis indicates that the corresponding ORPs are NP-hard, but solvable by faster algorithms, compared to the problems they are derived from.

An Adaptive Genetic Algorithm with Dynamic Population Size for Optimizing Join Queries

OpenAIRE

Vellev, Stoyan

2008-01-01

The problem of finding the optimal join ordering executing a query to a relational database management system is a combinatorial optimization problem, which makes deterministic exhaustive solution search unacceptable for queries with a great number of joined relations. In this work an adaptive genetic algorithm with dynamic population size is proposed for optimizing large join queries. The performance of the algorithm is compared with that of several classical non-determinis...

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

Science.gov (United States)

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

2009-08-01

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

Characterizing the Incentive Compatible and Pareto Optimal Efficiency Space for Two Players, k Items, Public Budget and Quasilinear Utilities

Directory of Open Access Journals (Sweden)

Anat Lerner

2014-04-01

Full Text Available We characterize the efficiency space of deterministic, dominant-strategy incentive compatible, individually rational and Pareto-optimal combinatorial auctions in a model with two players and k nonidentical items. We examine a model with multidimensional types, private values and quasilinear preferences for the players with one relaxation: one of the players is subject to a publicly known budget constraint. We show that if it is publicly known that the valuation for the largest bundle is less than the budget for at least one of the players, then Vickrey-Clarke-Groves (VCG uniquely fulfills the basic properties of being deterministic, dominant-strategy incentive compatible, individually rational and Pareto optimal. Our characterization of the efficient space for deterministic budget constrained combinatorial auctions is similar in spirit to that of Maskin 2000 for Bayesian single-item constrained efficiency auctions and comparable with Ausubel and Milgrom 2002 for non-constrained combinatorial auctions.

Fast sequential Monte Carlo methods for counting and optimization

CERN Document Server

Rubinstein, Reuven Y; Vaisman, Radislav

2013-01-01

A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the

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

Science.gov (United States)

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

2012-01-01

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

Criticism of EFSA's scientific opinion on combinatorial effects of 'stacked' GM plants.

Science.gov (United States)

Bøhn, Thomas

2018-01-01

Recent genetically modified plants tend to include both insect resistance and herbicide tolerance traits. Some of these 'stacked' GM plants have multiple Cry-toxins expressed as well as tolerance to several herbicides. This means that non-target organisms in the environment (biodiversity) will be co-exposed to multiple stressors simultaneously. A similar co-exposure may happen to consumers through chemical residues in the food chain. EFSA, the responsible unit for minimizing risk of harm in European food chains, has expressed its scientific interest in combinatorial effects. However, when new data showed how two Cry-toxins acted in combination (added toxicity), and that the same Cry-toxins showed combinatorial effects when co-exposed with Roundup (Bøhn et al., 2016), EFSA dismissed these new peer-reviewed results. In effect, EFSA claimed that combinatorial effects are not relevant for itself. EFSA was justifying this by referring to a policy question, and by making invalid assumptions, which could have been checked directly with the lead-author. With such approach, EFSA may miss the opportunity to improve its environmental and health risk assessment of toxins and pesticides in the food chain. Failure to follow its own published requests for combinatorial effects research, may also risk jeopardizing EFSA's scientific and public reputation. Copyright © 2017. Published by Elsevier Ltd.

Implementation of a combinatorial cleavage and deprotection scheme

DEFF Research Database (Denmark)

Nielsen, John; Rasmussen, Palle H.

1996-01-01

Phthalhydrazide libraries are synthesized in solution from substituted hydrazines and phthalimides in several different library formats including single compounds, indexed sub-libraries and a full library. When carried out during solid-phase synthesis, this combinatorial cleavage and deprotection...

Optimization of ordered plasmid assembly by gap repair in Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Eckert-Boulet, Nadine Valerie; Pedersen, Mette Louise; Krogh, Berit Olsen

2012-01-01

Combinatorial genetic libraries are powerful tools for diversifying and optimizing biomolecules. The process of library assembly is a major limiting factor for library complexity and quality. Gap repair by homologous recombination in Saccharomyces cerevisiae can facilitate in vivo assembly of DNA...

Dynamic combinatorial chemistry at the phospholipid bilayer interface

NARCIS (Netherlands)

Mansfeld, Friederike M.; Au-Yeung, Ho Yu; Sanders, Jeremy K.M.; Otto, Sijbren

2010-01-01

Background: Molecular recognition at the environment provided by the phospholipid bilayer interface plays an important role in biology and is subject of intense investigation. Dynamic combinatorial chemistry is a powerful approach for exploring molecular recognition, but has thus far not been

Programme for test generation for combinatorial and sequential systems

International Nuclear Information System (INIS)

Tran Huy Hoan

1973-01-01

This research thesis reports the computer-assisted search for tests aimed at failure detection in combinatorial and sequential logic circuits. As he wants to deal with complex circuits with many modules such as those met in large scale integrated circuits (LSI), the author used propagation paths. He reports the development of a method which is valid for combinatorial systems and for several sequential circuits comprising elementary logic modules and JK and RS flip-flops. This method is developed on an IBM 360/91 computer in PL/1 language. The used memory space is limited and adjustable with respect to circuit dimension. Computing time is short when compared to that needed by other programmes. The solution is practical and efficient for failure test and localisation

Combinatorial nuclear level density by a Monte Carlo method

International Nuclear Information System (INIS)

Cerf, N.

1994-01-01

We present a new combinatorial method for the calculation of the nuclear level density. It is based on a Monte Carlo technique, in order to avoid a direct counting procedure which is generally impracticable for high-A nuclei. The Monte Carlo simulation, making use of the Metropolis sampling scheme, allows a computationally fast estimate of the level density for many fermion systems in large shell model spaces. We emphasize the advantages of this Monte Carlo approach, particularly concerning the prediction of the spin and parity distributions of the excited states,and compare our results with those derived from a traditional combinatorial or a statistical method. Such a Monte Carlo technique seems very promising to determine accurate level densities in a large energy range for nuclear reaction calculations

The Yoccoz Combinatorial Analytic Invariant

DEFF Research Database (Denmark)

Petersen, Carsten Lunde; Roesch, Pascale

2008-01-01

In this paper we develop a combinatorial analytic encoding of the Mandelbrot set M. The encoding is implicit in Yoccoz' proof of local connectivity of M at any Yoccoz parameter, i.e. any at most finitely renormalizable parameter for which all periodic orbits are repelling. Using this encoding we ...... to reprove that the dyadic veins of M are arcs and that more generally any two Yoccoz parameters are joined by a unique ruled (in the sense of Douady-Hubbard) arc in M....

An experimental analysis of design choices of multi-objective ant colony optimization algorithms

OpenAIRE

Lopez-Ibanez, Manuel; Stutzle, Thomas

2012-01-01

There have been several proposals on how to apply the ant colony optimization (ACO) metaheuristic to multi-objective combinatorial optimization problems (MOCOPs). This paper proposes a new formulation of these multi-objective ant colony optimization (MOACO) algorithms. This formulation is based on adding specific algorithm components for tackling multiple objectives to the basic ACO metaheuristic. Examples of these components are how to represent multiple objectives using pheromone and heuris...

Comprehensive human transcription factor binding site map for combinatory binding motifs discovery.

Directory of Open Access Journals (Sweden)

Arnoldo J Müller-Molina

Full Text Available To know the map between transcription factors (TFs and their binding sites is essential to reverse engineer the regulation process. Only about 10%-20% of the transcription factor binding motifs (TFBMs have been reported. This lack of data hinders understanding gene regulation. To address this drawback, we propose a computational method that exploits never used TF properties to discover the missing TFBMs and their sites in all human gene promoters. The method starts by predicting a dictionary of regulatory "DNA words." From this dictionary, it distills 4098 novel predictions. To disclose the crosstalk between motifs, an additional algorithm extracts TF combinatorial binding patterns creating a collection of TF regulatory syntactic rules. Using these rules, we narrowed down a list of 504 novel motifs that appear frequently in syntax patterns. We tested the predictions against 509 known motifs confirming that our system can reliably predict ab initio motifs with an accuracy of 81%-far higher than previous approaches. We found that on average, 90% of the discovered combinatorial binding patterns target at least 10 genes, suggesting that to control in an independent manner smaller gene sets, supplementary regulatory mechanisms are required. Additionally, we discovered that the new TFBMs and their combinatorial patterns convey biological meaning, targeting TFs and genes related to developmental functions. Thus, among all the possible available targets in the genome, the TFs tend to regulate other TFs and genes involved in developmental functions. We provide a comprehensive resource for regulation analysis that includes a dictionary of "DNA words," newly predicted motifs and their corresponding combinatorial patterns. Combinatorial patterns are a useful filter to discover TFBMs that play a major role in orchestrating other factors and thus, are likely to lock/unlock cellular functional clusters.

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

Science.gov (United States)

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

2017-04-01

effect becomes less prominent if the obstructing capacity decreases, as generally occurs during heavy rainfalls. The plot width have a moderate positive statistical effect on runoff and erosion coefficients, since wider patchy plots have, on average, a greater normalized contributing area and a higher probability to have runoff of a certain length. The effect of plot width depends by itself on the percentage cover, plot length, and compared width scales. The contributing area uncertainty brought about by cover spatial arrangement is examined, including its dependence on the percentage cover and scale. In general, modified percolation theory approaches and combinatorial models of urns with restricted occupancy may link between critical dependence of runoff on percentage cover, cover-related scale effect, and statistical uncertainty of the observed quantities.

Isocyanide based multi component reactions in combinatorial chemistry.

NARCIS (Netherlands)

Dömling, A.

1998-01-01

Although usually regarded as a recent development, the combinatorial approach to the synthesis of libraries of new drug candidates was first described as early as 1961 using the isocyanide-based one-pot multicomponent Ugi reaction. Isocyanide-based multi component reactions (MCR's) markedly differ

Combinatorial Aspects of the Generalized Euler's Totient

Directory of Open Access Journals (Sweden)

Nittiya Pabhapote

2010-01-01

Full Text Available A generalized Euler's totient is defined as a Dirichlet convolution of a power function and a product of the Souriau-Hsu-Möbius function with a completely multiplicative function. Two combinatorial aspects of the generalized Euler's totient, namely, its connections to other totients and its relations with counting formulae, are investigated.

ON 3-WAY COMBINATORIAL IDENTITIES A. K. AGARWAL MEGHA ...

Indian Academy of Sciences (India)

36

∗Corresponding author: Department of Basic and Applied Sciences, University College of Engineering,. Punjabi ... In this paper we provide combinatorial meanings to two generalized basic ... 2010 Mathematics Subject Classification. 05A15 ...

Exact model reduction of combinatorial reaction networks

Directory of Open Access Journals (Sweden)

Fey Dirk

2008-08-01

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

Neon soft x-ray emission studies from the UNU-ICTP plasma focus operated with longer than optimal anode length

International Nuclear Information System (INIS)

Mohammadi, M A; Verma, R; Sobhanian, S; Wong, C S; Lee, S; Springham, S V; Tan, T L; Lee, P; Rawat, R S

2007-01-01

The UNU-ICTP plasma focus with a significantly longer than conventional anode can still be a reasonably good neon soft x-ray (SXR) source. The highest average neon SXR yield of 3.3 J was achieved at 3 mbar. The time difference between the two first peaks of the voltage probe signal at the radial collapse phase was found to be inversely related to the SXR yield, i.e. the smaller the time difference, the higher the yield and vice versa. The estimation of average current sheath speeds using the shadowgraphic method coupled with laser and focus peak timing signals showed that the average axial rundown speed is similar to the one obtained for the optimal anode length but the average radial compression speed is decreased significantly. The range of pressure for a good neon SXR yield, however, has become much narrower, making efficient plasma focus operation a very sensitive function of the filling gas pressure for longer than the optimal anode length

Combinatorial structures and processing in neural blackboard architectures

NARCIS (Netherlands)

van der Velde, Frank; van der Velde, Frank; de Kamps, Marc; Besold, Tarek R.; d'Avila Garcez, Artur; Marcus, Gary F.; Miikkulainen, Risto

2015-01-01

We discuss and illustrate Neural Blackboard Architectures (NBAs) as the basis for variable binding and combinatorial processing the brain. We focus on the NBA for sentence structure. NBAs are based on the notion that conceptual representations are in situ, hence cannot be copied or transported.

3rd World Congress on Global Optimization in Engineering & Science

CERN Document Server

Ruan, Ning; Xing, Wenxun; WCGO-III; Advances in Global Optimization

2015-01-01

This proceedings volume addresses advances in global optimization—a multidisciplinary research field that deals with the analysis, characterization, and computation of global minima and/or maxima of nonlinear, non-convex, and nonsmooth functions in continuous or discrete forms. The volume contains selected papers from the third biannual World Congress on Global Optimization in Engineering & Science (WCGO), held in the Yellow Mountains, Anhui, China on July 8-12, 2013. The papers fall into eight topical sections: mathematical programming; combinatorial optimization; duality theory; topology optimization; variational inequalities and complementarity problems; numerical optimization; stochastic models and simulation; and complex simulation and supply chain analysis.

Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network

Science.gov (United States)

Kuhn, D. Richard; Kacker, Raghu; Lei, Yu

2010-01-01

This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.

Advanced Aqueous Phase Catalyst Development using Combinatorial Methods, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — Combinatorial methods are proposed to develop advanced Aqueous Oxidation Catalysts (AOCs) with the capability to mineralize organic contaminants present in effluents...

Device for preparing combinatorial libraries in powder metallurgy.

Science.gov (United States)

Yang, Shoufeng; Evans, Julian R G

2004-01-01

This paper describes a powder-metering, -mixing, and -dispensing mechanism that can be used as a method for producing large numbers of samples for metallurgical evaluation or electrical or mechanical testing from multicomponent metal and cermet powder systems. It is designed to make use of the same commercial powders that are used in powder metallurgy and, therefore, to produce samples that are faithful to the microstructure of finished products. The particle assemblies produced by the device could be consolidated by die pressing, isostatic pressing, laser sintering, or direct melting. The powder metering valve provides both on/off and flow rate control of dry powders in open capillaries using acoustic vibration. The valve is simple and involves no relative movement, avoiding seizure with fine powders. An orchestra of such valves can be arranged on a building platform to prepare multicomponent combinatorial libraries. As with many combinatorial devices, identification and evaluation of sources of mixing error as a function of sample size is mandatory. Such an analysis is presented.

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

Science.gov (United States)

Chen, Hong-Zhang; Liu, Zhi-Hua

2015-06-01

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

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

Science.gov (United States)

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

2003-01-01

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

3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences

CERN Document Server

Dinh, Tao; Nguyen, Ngoc

2015-01-01

This proceedings set contains 85 selected full papers presented at the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2015, held on May 11–13, 2015 at Lorraine University, France. The present part I of the 2 volume set includes articles devoted to Combinatorial optimization and applications, DC programming and DCA: thirty years of Developments, Dynamic Optimization, Modelling and Optimization in financial engineering, Multiobjective programming, Numerical Optimization, Spline Approximation and Optimization, as well as Variational Principles and Applications

A combinatorial enumeration problem of RNA secondary structures

African Journals Online (AJOL)

use

2011-12-21

Dec 21, 2011 ... interesting combinatorial questions (Chen et al., 2005;. Liu, 2006; Schmitt and Waterman 1994; Stein and. Waterman 1978). The research on the enumeration of. RNA secondary structures becomes one of the hot topics in Computational Molecular Biology. An RNA molecule is described by its sequences of.

Optimal covariate designs theory and applications

CERN Document Server

Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar

2015-01-01

This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...

Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z. [Institute of Applied Physics and Computational Mathematics, Beijing, 100094 (China)

2013-07-01

Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)

Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

International Nuclear Information System (INIS)

Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.

2013-01-01

Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)

Graphical-based construction of combinatorial geometries for radiation transport and shielding applications

International Nuclear Information System (INIS)

Burns, T.J.

1992-01-01

A graphical-based code system is being developed at ORNL to manipulate combinatorial geometries for radiation transport and shielding applications. The current version (basically a combinatorial geometry debugger) consists of two parts: a FORTRAN-based ''view'' generator and a Microsoft Windows application for displaying the geometry. Options and features of both modules are discussed. Examples illustrating the various options available are presented. The potential for utilizing the images produced using the debugger as a visualization tool for the output of the radiation transport codes is discussed as is the future direction of the development

Information content versus word length in random typing

International Nuclear Information System (INIS)

Ferrer-i-Cancho, Ramon; Moscoso del Prado Martín, Fermín

2011-01-01

Recently, it has been claimed that a linear relationship between a measure of information content and word length is expected from word length optimization and it has been shown that this linearity is supported by a strong correlation between information content and word length in many languages (Piantadosi et al 2011 Proc. Nat. Acad. Sci. 108 3825). Here, we study in detail some connections between this measure and standard information theory. The relationship between the measure and word length is studied for the popular random typing process where a text is constructed by pressing keys at random from a keyboard containing letters and a space behaving as a word delimiter. Although this random process does not optimize word lengths according to information content, it exhibits a linear relationship between information content and word length. The exact slope and intercept are presented for three major variants of the random typing process. A strong correlation between information content and word length can simply arise from the units making a word (e.g., letters) and not necessarily from the interplay between a word and its context as proposed by Piantadosi and co-workers. In itself, the linear relation does not entail the results of any optimization process. (letter)

Solutions manual to accompany Combinatorial reasoning an introduction to the art of counting

CERN Document Server

DeTemple, Duane

2014-01-01

This is a solutions manual to accompany Combinatorial Reasoning: An Introduction to the Art of CountingWritten by well-known scholars in the field, Combinatorial Reasoning: An Introduction to the Art of Counting introduces combinatorics alongside modern techniques, showcases the interdisciplinary aspects of the topic, and illustrates how to problem solve with a multitude of exercises throughout. The authors'' approach is very reader-friendly and avoids the ""scholarly tone"" found in many books on this topic.  

Olefin Metathesis in Peptidomimetics, Dynamic Combinatorial Chemistry, and Molecular Imprinting

National Research Council Canada - National Science Library

Low, Tammy K

2006-01-01

.... Our research goals consisted of employing olefin metathesis in the synthesis of peptidomimetics, and studying the feasibility of this method in dynamic combinatorial chemistry and molecular imprinting of nerve agents...

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha

2013-11-25

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Hypercontractivity in group Von Neumann algebras

CERN Document Server

Junge, Marius; Parcet, Javier

2017-01-01

In this paper, the authors provide a combinatorial/numerical method to establish new hypercontractivity estimates in group von Neumann algebras. They illustrate their method with free groups, triangular groups and finite cyclic groups, for which they obtain optimal time hypercontractive L_2 \\to L_q inequalities with respect to the Markov process given by the word length and with q an even integer. Interpolation and differentiation also yield general L_p \\to L_q hypercontrativity for 1 < p \\le q < \\infty via logarithmic Sobolev inequalities. The authors' method admits further applications to other discrete groups without small loops as far as the numerical part-which varies from one group to another-is implemented and tested on a computer. The authors also develop another combinatorial method which does not rely on computational estimates and provides (non-optimal) L_p \\to L_q hypercontractive inequalities for a larger class of groups/lengths, including any finitely generated group equipped with a condit...

CUNY Graduate Center Workshops on Combinatorial and Additive Number Theory

CERN Document Server

2017-01-01

Based on talks from the 2015 and 2016 Combinatorial and Additive Number Theory (CANT) workshops at the City University of New York, these proceedings offer 19 peer-reviewed and edited papers on current topics in number theory. Held every year since 2003, the workshop series surveys state-of-the-art open problems in combinatorial and additive number theory and related parts of mathematics. Sumsets, partitions, convex polytopes and discrete geometry, Ramsey theory, primality testing, and cryptography are among the topics featured in this volume. Each contribution is dedicated to a specific topic that reflects the latest results by experts in the field. Researchers and graduate students interested in the current progress in number theory will find this selection of articles relevant and compelling. .

Sentence processing in an artificial language: Learning and using combinatorial constraints.

Science.gov (United States)

Amato, Michael S; MacDonald, Maryellen C

2010-07-01

A study combining artificial grammar and sentence comprehension methods investigated the learning and online use of probabilistic, nonadjacent combinatorial constraints. Participants learned a small artificial language describing cartoon monsters acting on objects. Self-paced reading of sentences in the artificial language revealed comprehenders' sensitivity to nonadjacent combinatorial constraints, without explicit awareness of the probabilities embedded in the language. These results show that even newly-learned constraints have an identifiable effect on online sentence processing. The rapidity of learning in this paradigm relative to others has implications for theories of implicit learning and its role in language acquisition. 2010 Elsevier B.V. All rights reserved.

Combinatorial Testing for VDM

DEFF Research Database (Denmark)

Larsen, Peter Gorm; Lausdahl, Kenneth; Battle, Nick

2010-01-01

by forgotten preconditions as well as broken invariants and post-conditions. Trace definitions are defined as regular expressions describing possible sequences of operation calls, and are conceptually similar to UML sequence diagrams. In this paper we present a tool enabling test automation based on VDM traces......Abstract—Combinatorial testing in VDM involves the automatic generation and execution of a large collection of test cases derived from templates provided in the form of trace definitions added to a VDM specification. The main value of this is the rapid detection of run-time errors caused......, and explain how it is possible to reduce large collections of test cases in different ways. Its use is illustrated with a small case study....

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

Science.gov (United States)

Lee, M L; Schneider, G

2001-01-01

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

A combinatorial approximation algorithm for CDMA downlink rate allocation

NARCIS (Netherlands)

Boucherie, Richardus J.; Bumb, A.F.; Endrayanto, A.I.; Woeginger, Gerhard; Raghavan, S.; Anandalingam, G.

2006-01-01

This paper presents a combinatorial algorithm for downlink rate allocation in Code Division Multiple Access (CDMA) mobile networks. By discretizing the coverage area into small segments, the transmit power requirements are characterized via a matrix representation that separates user and system

A combinatorial approximation algorithm for CDMA downlink rate allocation

NARCIS (Netherlands)

Boucherie, Richardus J.; Bumb, A.F.; Endrayanto, A.I.; Woeginger, Gerhard

2004-01-01

This paper presents a combinatorial algorithm for downlink rate allocation in Code Division Multiple Access (CDMA) mobile networks. By discretizing the coverage area into small segments, the transmit power requirements are characterized via a matrix representation that separates user and system

Development of tight-binding, chemical-reaction-dynamics simulator for combinatorial computational chemistry

International Nuclear Information System (INIS)

Kubo, Momoji; Ando, Minako; Sakahara, Satoshi; Jung, Changho; Seki, Kotaro; Kusagaya, Tomonori; Endou, Akira; Takami, Seiichi; Imamura, Akira; Miyamoto, Akira

2004-01-01

Recently, we have proposed a new concept called 'combinatorial computational chemistry' to realize a theoretical, high-throughput screening of catalysts and materials. We have already applied our combinatorial, computational-chemistry approach, mainly based on static first-principles calculations, to various catalysts and materials systems and its applicability to the catalysts and materials design was strongly confirmed. In order to realize more effective and efficient combinatorial, computational-chemistry screening, a high-speed, chemical-reaction-dynamics simulator based on quantum-chemical, molecular-dynamics method is essential. However, to the best of our knowledge, there is no chemical-reaction-dynamics simulator, which has an enough high-speed ability to perform a high-throughput screening. In the present study, we have succeeded in the development of a chemical-reaction-dynamics simulator based on our original, tight-binding, quantum-chemical, molecular-dynamics method, which is more than 5000 times faster than the regular first-principles, molecular-dynamics method. Moreover, its applicability and effectiveness to the atomistic clarification of the methanol-synthesis dynamics at reaction temperature were demonstrated

Combinatorial Approaches for the Identification of Brain Drug Delivery Targets

Science.gov (United States)

Stutz, Charles C.; Zhang, Xiaobin; Shusta, Eric V.

2018-01-01

The blood-brain barrier (BBB) represents a large obstacle for the treatment of central nervous system diseases. Targeting endogenous nutrient transporters that transcytose the BBB is one promising approach to selectively and noninvasively deliver a drug payload to the brain. The main limitations of the currently employed transcytosing receptors are their ubiquitous expression in the peripheral vasculature and the inherent low levels of transcytosis mediated by such systems. In this review, approaches designed to increase the repertoire of transcytosing receptors which can be targeted for the purpose of drug delivery are discussed. In particular, combinatorial protein libraries can be screened on BBB cells in vitro or in vivo to isolate targeting peptides or antibodies that can trigger transcytosis. Once these targeting reagents are discovered, the cognate BBB transcytosis system can be identified using techniques such as expression cloning or immunoprecipitation coupled with mass spectrometry. Continued technological advances in BBB genomics and proteomics, membrane protein manipulation, and in vitro BBB technology promise to further advance the capability to identify and optimize peptides and antibodies capable of mediating drug transport across the BBB. PMID:23789958

Combinatorial processing libraries for bulk BiFeO3-PbTiO3 piezoelectric ceramics

International Nuclear Information System (INIS)

Hu, W.; Tan, X.; Rajan, K.

2010-01-01

A high throughput approach for generating combinatorial libraries with varying processing conditions for bulk ceramics has been developed. This approach utilized the linear temperature gradient in a tube furnace to screen a whole temperature range for optimized preparation. With this approach, the processing of 0.98[0.6BiFeO 3 -0.4PbTiO 3 ]-0.02Pb(Mg 1/3 Nb 2/3 )O 3 ceramic powders and pellets for high-temperature piezoelectric applications was demonstrated to identify the best synthesis conditions for phase purity. The dielectric property measurement on the as-processed solid solution ceramics confirmed the high Curie temperature and the improved loss tangent with the Pb(Mg 1/3 Nb 2/3 )O 3 doping. (orig.)

An Improved Real-Coded Population-Based Extremal Optimization Method for Continuous Unconstrained Optimization Problems

Directory of Open Access Journals (Sweden)

Guo-Qiang Zeng

2014-01-01

Full Text Available As a novel evolutionary optimization method, extremal optimization (EO has been successfully applied to a variety of combinatorial optimization problems. However, the applications of EO in continuous optimization problems are relatively rare. This paper proposes an improved real-coded population-based EO method (IRPEO for continuous unconstrained optimization problems. The key operations of IRPEO include generation of real-coded random initial population, evaluation of individual and population fitness, selection of bad elements according to power-law probability distribution, generation of new population based on uniform random mutation, and updating the population by accepting the new population unconditionally. The experimental results on 10 benchmark test functions with the dimension N=30 have shown that IRPEO is competitive or even better than the recently reported various genetic algorithm (GA versions with different mutation operations in terms of simplicity, effectiveness, and efficiency. Furthermore, the superiority of IRPEO to other evolutionary algorithms such as original population-based EO, particle swarm optimization (PSO, and the hybrid PSO-EO is also demonstrated by the experimental results on some benchmark functions.

Some Combinatorial Interpretations and Applications of Fuss-Catalan Numbers

OpenAIRE

Lin, Chin-Hung

2011-01-01

Fuss-Catalan number is a family of generalized Catalan numbers. We begin by two definitions of Fuss-Catalan numbers and some basic properties. And we give some combinatorial interpretations different from original Catalan numbers. Finally we generalize the Jonah's theorem as its applications.

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

Science.gov (United States)

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

2005-07-01

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

TARCMO: Theory and Algorithms for Robust, Combinatorial, Multicriteria Optimization

Science.gov (United States)

2016-11-28

methods is presented in the book chapter [CG16d]. 4.4 Robust Timetable Information Problems. Timetable information is the process of determining a...Princeton and Oxford, 2009. [BTN98] A. Ben-Tal and A. Nemirovski. Robust convex optimization. Math - ematics of Operations Research, 23(4):769–805...Goerigk. A note on upper bounds to the robust knapsack problem with discrete scenarios. Annals of Operations Research, 223(1):461–469, 2014. [GS16] M

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

Science.gov (United States)

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

2017-06-15

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

Theory of Randomized Search Heuristics in Combinatorial Optimization

DEFF Research Database (Denmark)

The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS), the Metr......The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS...... analysis of randomized algorithms to RSHs. Mostly, the expected runtime of RSHs on selected problems is analzyed. Thereby, we understand why and when RSHs are efficient optimizers and, conversely, when they cannot be efficient. The tutorial will give an overview on the analysis of RSHs for solving...

An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man

KAUST Repository

Ravasi, Timothy; Suzuki, Harukazu; Cannistraci, Carlo; Katayama, Shintaro; Bajic, Vladimir B.; Tan, Kai; Akalin, Altuna; Schmeier, Sebastian; Kanamori-Katayama, Mutsumi; Bertin, Nicolas; Carninci, Piero; Daub, Carsten O.; Forrest, Alistair R.R.; Gough, Julian; Grimmond, Sean; Han, Jung-Hoon; Hashimoto, Takehiro; Hide, Winston; Hofmann, Oliver; Kamburov, Atanas; Kaur, Mandeep; Kawaji, Hideya; Kubosaki, Atsutaka; Lassmann, Timo; van Nimwegen, Erik; MacPherson, Cameron Ross; Ogawa, Chihiro; Radovanovic, Aleksandar; Schwartz, Ariel; Teasdale, Rohan D.; Tegné r, Jesper; Lenhard, Boris; Teichmann, Sarah A.; Arakawa, Takahiro; Ninomiya, Noriko; Murakami, Kayoko; Tagami, Michihira; Fukuda, Shiro; Imamura, Kengo; Kai, Chikatoshi; Ishihara, Ryoko; Kitazume, Yayoi; Kawai, Jun; Hume, David A.; Ideker, Trey; Hayashizaki, Yoshihide

2010-01-01

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man

KAUST Repository

Ravasi, Timothy

2010-03-01

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

Skeletal Diversity in Combinatorial Fashion: A New Format for the Castagnoli-Cushman Reaction.

Science.gov (United States)

Lepikhina, Anastasia; Dar'in, Dmitry; Bakulina, Olga; Chupakhin, Evgeny; Krasavin, Mikhail

2017-11-13

A new format for the Castagnoli-Cushman reaction of structurally diverse dicarboxylic acids, amines, and aldehydes in the presence of acetic anhydride as dehydrating agent is described. The reaction is distinctly amenable to parallel format: the combinatorial array of 180 reactions delivered 157 products of >85% purity without chromatographic purification (of this number, 143 compounds had >94% purity). The new method offers a convenient preparation of the skeletally and peripherally diverse, lead- and druglike γ- and δ-lactam carboxylic acids with high diastereoselectivity in combinatorial fashion.

Optimal Control Surface Layout for an Aeroservoelastic Wingbox

Science.gov (United States)

Stanford, Bret K.

2017-01-01

This paper demonstrates a technique for locating the optimal control surface layout of an aeroservoelastic Common Research Model wingbox, in the context of maneuver load alleviation and active utter suppression. The combinatorial actuator layout design is solved using ideas borrowed from topology optimization, where the effectiveness of a given control surface is tied to a layout design variable, which varies from zero (the actuator is removed) to one (the actuator is retained). These layout design variables are optimized concurrently with a large number of structural wingbox sizing variables and control surface actuation variables, in order to minimize the sum of structural weight and actuator weight. Results are presented that demonstrate interdependencies between structural sizing patterns and optimal control surface layouts, for both static and dynamic aeroelastic physics.

Combinatorial development of antibacterial Zr-Cu-Al-Ag thin film metallic glasses.

Science.gov (United States)

Liu, Yanhui; Padmanabhan, Jagannath; Cheung, Bettina; Liu, Jingbei; Chen, Zheng; Scanley, B Ellen; Wesolowski, Donna; Pressley, Mariyah; Broadbridge, Christine C; Altman, Sidney; Schwarz, Udo D; Kyriakides, Themis R; Schroers, Jan

2016-05-27

Metallic alloys are normally composed of multiple constituent elements in order to achieve integration of a plurality of properties required in technological applications. However, conventional alloy development paradigm, by sequential trial-and-error approach, requires completely unrelated strategies to optimize compositions out of a vast phase space, making alloy development time consuming and labor intensive. Here, we challenge the conventional paradigm by proposing a combinatorial strategy that enables parallel screening of a multitude of alloys. Utilizing a typical metallic glass forming alloy system Zr-Cu-Al-Ag as an example, we demonstrate how glass formation and antibacterial activity, two unrelated properties, can be simultaneously characterized and the optimal composition can be efficiently identified. We found that in the Zr-Cu-Al-Ag alloy system fully glassy phase can be obtained in a wide compositional range by co-sputtering, and antibacterial activity is strongly dependent on alloy compositions. Our results indicate that antibacterial activity is sensitive to Cu and Ag while essentially remains unchanged within a wide range of Zr and Al. The proposed strategy not only facilitates development of high-performing alloys, but also provides a tool to unveil the composition dependence of properties in a highly parallel fashion, which helps the development of new materials by design.

Combinatorial algorithms enabling computational science: tales from the front

International Nuclear Information System (INIS)

Bhowmick, Sanjukta; Boman, Erik G; Devine, Karen; Gebremedhin, Assefaw; Hendrickson, Bruce; Hovland, Paul; Munson, Todd; Pothen, Alex

2006-01-01

Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations. The importance of discrete algorithms continues to grow with the demands of new applications and advanced architectures. This paper surveys some recent developments in this rapidly changing and highly interdisciplinary field

Combinatorial algorithms enabling computational science: tales from the front

Energy Technology Data Exchange (ETDEWEB)

Bhowmick, Sanjukta [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Devine, Karen [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw [Computer Science Department, Old Dominion University (United States); Hendrickson, Bruce [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Hovland, Paul [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Munson, Todd [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science Department, Old Dominion University (United States)

2006-09-15

Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations. The importance of discrete algorithms continues to grow with the demands of new applications and advanced architectures. This paper surveys some recent developments in this rapidly changing and highly interdisciplinary field.

Dynamic combinatorial libraries based on hydrogen-bonde molecular boxes

NARCIS (Netherlands)

Kerckhoffs, J.M.C.A.; Mateos timoneda, Miguel; Reinhoudt, David; Crego Calama, Mercedes

2007-01-01

This article describes two different types of dynamic combinatorial libraries of host and guest molecules. The first part of this article describes the encapsulation of alizarin trimer 2 a3 by dynamic mixtures of up to twenty different self-assembled molecular receptors together with the

Optimization of cellulose nanocrystal length and surface charge density through phosphoric acid hydrolysis

Science.gov (United States)

Vanderfleet, Oriana M.; Osorio, Daniel A.; Cranston, Emily D.

2017-12-01

Cellulose nanocrystals (CNCs) are emerging nanomaterials with a large range of potential applications. CNCs are typically produced through acid hydrolysis with sulfuric acid; however, phosphoric acid has the advantage of generating CNCs with higher thermal stability. This paper presents a design of experiments approach to optimize the hydrolysis of CNCs from cotton with phosphoric acid. Hydrolysis time, temperature and acid concentration were varied across nine experiments and a linear least-squares regression analysis was applied to understand the effects of these parameters on CNC properties. In all but one case, rod-shaped nanoparticles with a high degree of crystallinity and thermal stability were produced. A statistical model was generated to predict CNC length, and trends in phosphate content and zeta potential were elucidated. The CNC length could be tuned over a relatively large range (238-475 nm) and the polydispersity could be narrowed most effectively by increasing the hydrolysis temperature and acid concentration. The CNC phosphate content was most affected by hydrolysis temperature and time; however, the charge density and colloidal stability were considered low compared with sulfuric acid hydrolysed CNCs. This study provides insight into weak acid hydrolysis and proposes `design rules' for CNCs with improved size uniformity and charge density. This article is part of a discussion meeting issue `New horizons for cellulose nanotechnology'.

On-bead combinatorial synthesis and imaging of chemical exchange saturation transfer magnetic resonance imaging agents to identify factors that influence water exchange.

Science.gov (United States)

Napolitano, Roberta; Soesbe, Todd C; De León-Rodríguez, Luis M; Sherry, A Dean; Udugamasooriya, D Gomika

2011-08-24

The sensitivity of magnetic resonance imaging (MRI) contrast agents is highly dependent on the rate of water exchange between the inner sphere of a paramagnetic ion and bulk water. Normally, identifying a paramagnetic complex that has optimal water exchange kinetics is done by synthesizing and testing one compound at a time. We report here a rapid, economical on-bead combinatorial synthesis of a library of imaging agents. Eighty different 1,4,7,10-tetraazacyclododecan-1,4,7,10-tetraacetic acid (DOTA)-tetraamide peptoid derivatives were prepared on beads using a variety of charged, uncharged but polar, hydrophobic, and variably sized primary amines. A single chemical exchange saturation transfer image of the on-bead library easily distinguished those compounds having the most favorable water exchange kinetics. This combinatorial approach will allow rapid screening of libraries of imaging agents to identify the chemical characteristics of a ligand that yield the most sensitive imaging agents. This technique could be automated and readily adapted to other types of MRI or magnetic resonance/positron emission tomography agents as well.

Quantum resonance for simulating combinatorial problems

International Nuclear Information System (INIS)

Zak, Michail; Fijany, Amir

2005-01-01

Quantum computing by simulations is based upon similarity between mathematical formalism of a quantum phenomenon and phenomena to be analyzed. In this Letter, the mathematical formalism of quantum resonance combined with tensor product decomposability of unitary evolutions is mapped onto a class of NP-complete combinatorial problems. It has been demonstrated that nature has polynomial resources for solving NP-complete problems and that will help to develop a new strategy for artificial intelligence, as well as to re-evaluate the role of natural selection in biological evolution

Design and Optimization of 22 nm Gate Length High-k/Metal gate NMOS Transistor

International Nuclear Information System (INIS)

Afifah Maheran A H; Menon P S; Shaari, S; Elgomati, H A; Salehuddin, F; Ahmad, I

2013-01-01

In this paper, we invented the optimization experiment design of a 22 nm gate length NMOS device which uses a combination of high-k material and metal as the gate which was numerically developed using an industrial-based simulator. The high-k material is Titanium dioxide (TiO 2 ), while the metal gate is Tungsten Silicide (WSi x ). The design is optimized using the L9 Taguchi method to get the optimum parameter design. There are four process parameters and two noise parameters which were varied for analyzing the effect on the threshold voltage (V th ). The objective of this experiment is to minimize the variance of V th where Taguchi's nominal-the-best signal-to-noise ratio (S/N Ratio) was used. The best settings of the process parameters were determined using Analysis of Mean (ANOM) and analysis of variance (ANOVA) to reduce the variability of V th . The results show that the V th values have least variance and the mean value can be adjusted to 0.306V ±0.027 for the NMOS device which is in line with projections by the ITRS specifications.

A combinatorial approach to diffeomorphism invariant quantum gauge theories

International Nuclear Information System (INIS)

Zapata, J.A.

1997-01-01

Quantum gauge theory in the connection representation uses functions of holonomies as configuration observables. Physical observables (gauge and diffeomorphism invariant) are represented in the Hilbert space of physical states; physical states are gauge and diffeomorphism invariant distributions on the space of functions of the holonomies of the edges of a certain family of graphs. Then a family of graphs embedded in the space manifold (satisfying certain properties) induces a representation of the algebra of physical observables. We construct a quantum model from the set of piecewise linear graphs on a piecewise linear manifold, and another manifestly combinatorial model from graphs defined on a sequence of increasingly refined simplicial complexes. Even though the two models are different at the kinematical level, they provide unitarily equivalent representations of the algebra of physical observables in separable Hilbert spaces of physical states (their s-knot basis is countable). Hence, the combinatorial framework is compatible with the usual interpretation of quantum field theory. copyright 1997 American Institute of Physics

A discrete optimization method for nuclear fuel management

International Nuclear Information System (INIS)

Argaud, J.P.

1993-01-01

Nuclear fuel management can be seen as a large discrete optimization problem under constraints, and optimization methods on such problems are numerically costly. After an introduction of the main aspects of nuclear fuel management, this paper presents a new way to treat the combinatorial problem by using information included in the gradient of optimized cost function. A new search process idea is to choose, by direct observation of the gradient, the more interesting changes in fuel loading patterns. An example is then developed to illustrate an operating mode of the method. Finally, connections with classical simulated annealing and genetic algorithms are described as an attempt to improve search processes. 16 refs., 2 figs

Gas-Foamed Scaffold Gradients for Combinatorial Screening in 3D

Directory of Open Access Journals (Sweden)

Joachim Kohn

2012-03-01

Full Text Available Current methods for screening cell-material interactions typically utilize a two-dimensional (2D culture format where cells are cultured on flat surfaces. However, there is a need for combinatorial and high-throughput screening methods to systematically screen cell-biomaterial interactions in three-dimensional (3D tissue scaffolds for tissue engineering. Previously, we developed a two-syringe pump approach for making 3D scaffold gradients for use in combinatorial screening of salt-leached scaffolds. Herein, we demonstrate that the two-syringe pump approach can also be used to create scaffold gradients using a gas-foaming approach. Macroporous foams prepared by a gas-foaming technique are commonly used for fabrication of tissue engineering scaffolds due to their high interconnectivity and good mechanical properties. Gas-foamed scaffold gradient libraries were fabricated from two biodegradable tyrosine-derived polycarbonates: poly(desaminotyrosyl-tyrosine ethyl ester carbonate (pDTEc and poly(desaminotyrosyl-tyrosine octyl ester carbonate (pDTOc. The composition of the libraries was assessed with Fourier transform infrared spectroscopy (FTIR and showed that pDTEc/pDTOc gas-foamed scaffold gradients could be repeatably fabricated. Scanning electron microscopy showed that scaffold morphology was similar between the pDTEc-rich ends and the pDTOc-rich ends of the gradient. These results introduce a method for fabricating gas-foamed polymer scaffold gradients that can be used for combinatorial screening of cell-material interactions in 3D.

Swarm intelligence of artificial bees applied to In-Core Fuel Management Optimization

Energy Technology Data Exchange (ETDEWEB)

Santos de Oliveira, Iona Maghali, E-mail: ioliveira@con.ufrj.br [Nuclear Engineering Program, Federal University of Rio de Janeiro, P.O. Box 68509, Zip Code 21945-970, Rio de Janeiro, RJ (Brazil); Schirru, Roberto, E-mail: schirru@lmp.ufrj.br [Nuclear Engineering Program, Federal University of Rio de Janeiro, P.O. Box 68509, Zip Code 21945-970, Rio de Janeiro, RJ (Brazil)

2011-05-15

Research highlights: > We present Artificial Bee Colony with Random Keys (ABCRK) for In-Core Fuel Management Optimization. > Its performance is examined through the optimization of a Brazilian '2-loop' PWR. > Feasibility of using ABCRK is shown against some well known population-based algorithms. > Additional advantage includes the utilization of fewer control parameters. - Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new member of swarm intelligence. ABC tries to simulate the intelligent behavior of real honey bees in food foraging and can be used for solving continuous optimization and multi-dimensional numeric problems. This paper introduces the Artificial Bee Colony with Random Keys (ABCRK), a modified ABC algorithm for solving combinatorial problems such as the In-Core Fuel Management Optimization (ICFMO). The ICFMO is a hard combinatorial optimization problem in Nuclear Engineering which during many years has been solved by expert knowledge. It aims at getting the best arrangement of fuel in the nuclear reactor core that leads to a maximization of the operating time. As a consequence, the operation cost decreases and money is saved. In this study, ABCRK is used for optimizing the ICFMO problem of a Brazilian '2-loop' Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) and the results obtained with the proposed algorithm are compared with those obtained by Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The results show that the performance of the ABCRK algorithm is better than or similar to that of other population-based algorithms, with the advantage of employing fewer control parameters.

Swarm intelligence of artificial bees applied to In-Core Fuel Management Optimization

International Nuclear Information System (INIS)

Santos de Oliveira, Iona Maghali; Schirru, Roberto

2011-01-01

Research highlights: → We present Artificial Bee Colony with Random Keys (ABCRK) for In-Core Fuel Management Optimization. → Its performance is examined through the optimization of a Brazilian '2-loop' PWR. → Feasibility of using ABCRK is shown against some well known population-based algorithms. → Additional advantage includes the utilization of fewer control parameters. - Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new member of swarm intelligence. ABC tries to simulate the intelligent behavior of real honey bees in food foraging and can be used for solving continuous optimization and multi-dimensional numeric problems. This paper introduces the Artificial Bee Colony with Random Keys (ABCRK), a modified ABC algorithm for solving combinatorial problems such as the In-Core Fuel Management Optimization (ICFMO). The ICFMO is a hard combinatorial optimization problem in Nuclear Engineering which during many years has been solved by expert knowledge. It aims at getting the best arrangement of fuel in the nuclear reactor core that leads to a maximization of the operating time. As a consequence, the operation cost decreases and money is saved. In this study, ABCRK is used for optimizing the ICFMO problem of a Brazilian '2-loop' Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) and the results obtained with the proposed algorithm are compared with those obtained by Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The results show that the performance of the ABCRK algorithm is better than or similar to that of other population-based algorithms, with the advantage of employing fewer control parameters.

Combinatorial nuclear level-density model

International Nuclear Information System (INIS)

Uhrenholt, H.; Åberg, S.; Dobrowolski, A.; Døssing, Th.; Ichikawa, T.; Möller, P.

2013-01-01

A microscopic nuclear level-density model is presented. The model is a completely combinatorial (micro-canonical) model based on the folded-Yukawa single-particle potential and includes explicit treatment of pairing, rotational and vibrational states. The microscopic character of all states enables extraction of level-distribution functions with respect to pairing gaps, parity and angular momentum. The results of the model are compared to available experimental data: level spacings at neutron separation energy, data on total level-density functions from the Oslo method, cumulative level densities from low-lying discrete states, and data on parity ratios. Spherical and deformed nuclei follow basically different coupling schemes, and we focus on deformed nuclei

Development of a coherent transition radiation-based bunch length monitor with application to the APS RF thermionic gun beam optimization

CERN Document Server

Lumpkin, Alex H; Berg, W J; Borland, M; Happek, U; Lewellen, J W; Sereno, N S

2001-01-01

We report further development of an EPICS-compatible bunch length monitor based on the autocorrelation of coherent transition radiation (CTR). In this case the monitor was used to optimize the beam from the S-band thermionic RF gun on the Advanced Photon Source (APS) linac. Bunch lengths of 400-500 fs (FWHM) were measured in the core of the beam, which corresponded to about 100-A peak current in each micropulse. The dependence of the CTR signal on the square of the beam charge for the beam core was demonstrated. We also report the first use of the beam accelerated to 217 MeV for successful visible wavelength SASE FEL experiments.

Recursive deconvolution of combinatorial chemical libraries.

OpenAIRE

Erb, E; Janda, K D; Brenner, S

1994-01-01

A recursive strategy that solves for the active members of a chemical library is presented. A pentapeptide library with an alphabet of Gly, Leu, Phe, and Tyr (1024 members) was constructed on a solid support by the method of split synthesis. One member of this library (NH2-Tyr-Gly-Gly-Phe-Leu) is a native binder to a beta-endorphin antibody. A variation of the split synthesis approach is used to build the combinatorial library. In four vials, a member of the library's alphabet is coupled to a...

Construction of Short-Length High-Rates LDPC Codes Using Difference Families

Directory of Open Access Journals (Sweden)

Deny Hamdani

2010-10-01

Full Text Available Low-density parity-check (LDPC code is linear-block error-correcting code defined by sparse parity-check matrix. It is decoded using the massage-passing algorithm, and in many cases, capable of outperforming turbo code. This paper presents a class of low-density parity-check (LDPC codes showing good performance with low encoding complexity. The code is constructed using difference families from  combinatorial design. The resulting code, which is designed to have short code length and high code rate, can be encoded with low complexity due to its quasi-cyclic structure, and performs well when it is iteratively decoded with the sum-product algorithm. These properties of LDPC code are quite suitable for applications in future wireless local area network.

Biomechanical optimization of implant diameter and length for immediate loading: a nonlinear finite element analysis.

Science.gov (United States)

Kong, Liang; Gu, Zexu; Li, Tao; Wu, Junjie; Hu, Kaijin; Liu, Yanpu; Zhou, Hongzhi; Liu, Baolin

2009-01-01

A nonlinear finite element method was applied to examine the effects of implant diameter and length on the maximum von Mises stresses in the jaw, and to evaluate the maximum displacement of the implant-abutment complex in immediate-loading models. The implant diameter (D) ranged from 3.0 to 5.0 mm and implant length (L) ranged from 6.0 to 16.0 mm. The results showed that the maximum von Mises stress in cortical bone was decreased by 65.8% under a buccolingual load with an increase in D. In cancellous bone, it was decreased by 71.5% under an axial load with an increase in L. The maximum displacement in the implant-abutment complex decreased by 64.8% under a buccolingual load with an increase in D. The implant was found to be more sensitive to L than to D under axial loads, while D played a more important role in enhancing its stability under buccolingual loads. When D exceeded 4.0 mm and L exceeded 11.0 mm, both minimum stress and displacement were obtained. Therefore, these dimensions were the optimal biomechanical selections for immediate-loading implants in type B/2 bone.

A combinatorial approach towards the design of nanofibrous scaffolds for chondrogenesis

Science.gov (United States)

Ahmed, Maqsood; Ramos, Tiago André Da Silva; Damanik, Febriyani; Quang Le, Bach; Wieringa, Paul; Bennink, Martin; van Blitterswijk, Clemens; de Boer, Jan; Moroni, Lorenzo

2015-10-01

The extracellular matrix (ECM) is a three-dimensional (3D) structure composed of proteinaceous fibres that provide physical and biological cues to direct cell behaviour. Here, we build a library of hybrid collagen-polymer fibrous scaffolds with nanoscale dimensions and screen them for their ability to grow chondrocytes for cartilage repair. Poly(lactic acid) and poly (lactic-co-glycolic acid) at two different monomer ratios (85:15 and 50:50) were incrementally blended with collagen. Physical properties (wettability and stiffness) of the scaffolds were characterized and related to biological performance (proliferation, ECM production, and gene expression) and structure-function relationships were developed. We found that soft scaffolds with an intermediate wettability composed of the highly biodegradable PLGA50:50 and collagen, in two ratios (40:60 and 60:40), were optimal for chondrogenic differentiation of ATDC5 cells as determined by increased ECM production and enhanced cartilage specific gene expression. Long-term cultures indicated a stable phenotype with minimal de-differentiation or hypertrophy. The combinatorial methodology applied herein is a promising approach for the design and development of scaffolds for regenerative medicine.

Combinatorial experiment in Ni-Ti thin films by laser interference structuring

International Nuclear Information System (INIS)

Liu, K.W.; Gachot, C.; Leibenguth, P.; Muecklich, F.

2005-01-01

Combinatorial experiments are achieved on periodically structured Ni-Ti thin film composition spreads by laser interference irradiation using a Nd:YAG laser. Continuous Ni-Ti compositional spreads covering almost the whole binary system are prepared by combining sputter mask, shutter and movement of substrate. The continuous compositional spread is subsequently micro-structured into a sample library consisting of well-defined lines of individual samples by laser interference irradiation. The composition and microstructure effects in continuous spread and sample libraries after laser structuring are explored by scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) and white light interferometry (WLI) microscopy. The sample library consists of individual samples with a distance of about 5 μm and a composition resolution as high as 0.1 at.% in between. Although, there are certain difficulties so far in obtaining the optimized laser fluence for the spread, the laser interference irradiation provides an effective way to prepare thin film libraries with around 200 sample lines within 1 mm

Generation of Length Distribution, Length Diagram, Fibrogram, and Statistical Characteristics by Weight of Cotton Blends

Directory of Open Access Journals (Sweden)

B. Azzouz

2007-01-01

Full Text Available The textile fibre mixture as a multicomponent blend of variable fibres imposes regarding the proper method to predict the characteristics of the final blend. The length diagram and the fibrogram of cotton are generated. Then the length distribution, the length diagram, and the fibrogram of a blend of different categories of cotton are determined. The length distributions by weight of five different categories of cotton (Egyptian, USA (Pima, Brazilian, USA (Upland, and Uzbekistani are measured by AFIS. From these distributions, the length distribution, the length diagram, and the fibrogram by weight of four binary blends are expressed. The length parameters of these cotton blends are calculated and their variations are plotted against the mass fraction x of one component in the blend .These calculated parameters are compared to those of real blends. Finally, the selection of the optimal blends using the linear programming method, based on the hypothesis that the cotton blend parameters vary linearly in function of the components rations, is proved insufficient.

Software for the decision making support on the design of natural gas distribution networks; Software de apoio a decisao para o projeto de rede urbanas de distribuicao de gas natural

Energy Technology Data Exchange (ETDEWEB)

Goldbarg, Marco C.; Goldbarg, Elizabeth F.G. [Universidade Federal do Rio Grande do Norte (UFRN), Natal, RN (Brazil); Campos, Michel F. [PETROBRAS, Rio de Janeiro, RJ (Brazil)

2004-07-01

This work presents a computational system to aid the decision making process of installing new networks to distribute natural gas in an urban area. The system is called POM-DIGAS. The purpose of the software is to optimize the design of natural gas distribution networks. The general optimization problem comprises two combinatorial problems. The first one refers to the definition of the network layout. In this problem the objective is to minimize the total length of the network. The second combinatorial problem considers the pipe size optimization in which one must choose the diameters of the pipes regarding the demand requirements. POM-DIGAS is a composite of models and algorithms developed to tackle the two combinatorial problems. Furthermore, the software has a geographic information mode, a tool to automatically acquire several types of data concerning the project and a mode with distinct flow equations in order to allow the utilization of different methodologies for computing the network flows. The system was applied to a case study developed for the city of Natal, Rio Grande do Norte. This work was supported by RedeGasEnergia, FINEP and PETROBRAS. (author)

New high-throughput material-exploration system based on combinatorial chemistry and electrostatic atomization

International Nuclear Information System (INIS)

Fujimoto, K.; Takahashi, H.; Ito, S.; Inoue, S.; Watanabe, M.

2006-01-01

As a tool to facilitate future material explorations, our group has developed a new combinatorial system for the high-throughput preparation of compounds made up of more than three components. The system works in two steps: the atomization of a liquid by a high electric field followed by deposition to a grounded substrate. The combinatorial system based on this method has plural syringe pumps. The each starting materials are fed through the syringe pumps into a manifold, thoroughly mixed as they pass through the manifold, and atomized from the tip of a stainless steel nozzle onto a grounded substrate

"One-sample concept" micro-combinatory for high throughput TEM of binary films.

Science.gov (United States)

Sáfrán, György

2018-04-01

Phases of thin films may remarkably differ from that of bulk. Unlike to the comprehensive data files of Binary Phase Diagrams [1] available for bulk, complete phase maps for thin binary layers do not exist. This is due to both the diverse metastable, non-equilibrium or instable phases feasible in thin films and the required volume of characterization work with analytical techniques like TEM, SAED and EDS. The aim of the present work was to develop a method that remarkably facilitates the TEM study of the diverse binary phases of thin films, or the creation of phase maps. A micro-combinatorial method was worked out that enables both preparation and study of a gradient two-component film within a single TEM specimen. For a demonstration of the technique thin Mn x Al 1- x binary samples with evolving concentration from x = 0 to x = 1 have been prepared so that the transition from pure Mn to pure Al covers a 1.5 mm long track within the 3 mm diameter TEM grid. The proposed method enables the preparation and study of thin combinatorial samples including all feasible phases as a function of composition or other deposition parameters. Contrary to known "combinatorial chemistry", in which a series of different samples are deposited in one run, and investigated, one at a time, the present micro-combinatorial method produces a single specimen condensing a complete library of a binary system that can be studied, efficiently, within a single TEM session. That provides extremely high throughput for TEM characterization of composition-dependent phases, exploration of new materials, or the construction of phase diagrams of binary films. Copyright © 2018 Elsevier B.V. All rights reserved.

Ranked solutions to a class of combinatorial optimizations—with applications in mass spectrometry based peptide sequencing and a variant of directed paths in random media

Science.gov (United States)

Doerr, Timothy P.; Alves, Gelio; Yu, Yi-Kuo

2005-08-01

Typical combinatorial optimizations are NP-hard; however, for a particular class of cost functions the corresponding combinatorial optimizations can be solved in polynomial time using the transfer matrix technique or, equivalently, the dynamic programming approach. This suggests a way to efficiently find approximate solutions-find a transformation that makes the cost function as similar as possible to that of the solvable class. After keeping many high-ranking solutions using the approximate cost function, one may then re-assess these solutions with the full cost function to find the best approximate solution. Under this approach, it is important to be able to assess the quality of the solutions obtained, e.g., by finding the true ranking of the kth best approximate solution when all possible solutions are considered exhaustively. To tackle this statistical issue, we provide a systematic method starting with a scaling function generated from the finite number of high-ranking solutions followed by a convergent iterative mapping. This method, useful in a variant of the directed paths in random media problem proposed here, can also provide a statistical significance assessment for one of the most important proteomic tasks-peptide sequencing using tandem mass spectrometry data. For directed paths in random media, the scaling function depends on the particular realization of randomness; in the mass spectrometry case, the scaling function is spectrum-specific.

Dynamic Combinatorial Chemistry with Diselenides, Disulfides, Imines and Metal Coordination

DEFF Research Database (Denmark)

Sørensen, Anne

combinatorial chemistry, namely the reversible diselenide exchange reaction. The first part of the thesis describes the development of a thermally induced OAr → SeAr migration reaction. Here, it was proven possible to rearrange a variety of substituted O-aryl selenocarbamates into the corresponding Se...

Confluence of an extension of combinatory logic by Boolean constants

DEFF Research Database (Denmark)

Czajka, Łukasz

2017-01-01

We show confluence of a conditional term rewriting system CL-pc1, which is an extension of Combinatory Logic by Boolean constants. This solves problem 15 from the RTA list of open problems. The proof has been fully formalized in the Coq proof assistant....

Combinatorial chemistry approach to development of molecular plastic solar cells

NARCIS (Netherlands)

Godovsky, Dmitri; Inganäs, Olle; Brabec, Christoph J.; Sariciftci, N. Serdar; Hummelen, Jan C.; Janssen, Rene A.J.; Prato, M.; Maggini, M.; Segura, Jose; Martin, Nazario

1999-01-01

We used a combinatorial chemistry approach to develop the molecular plastic solar cells based on soluble fullerene derivatives or solubilized TCNQ molecules in combination with conjugated polymers. Profiles, formed by the diffusion of low molecular weight component in the spin-cast polymer host were

Measuring the combinatorial expression of solute transporters and metalloproteinases transcripts in colorectal cancer

Directory of Open Access Journals (Sweden)

Cosgrove Leah

2009-08-01

Full Text Available Abstract Background It was hypothesised that colorectal cancer (CRC could be diagnosed in biopsies by measuring the combined expression of a small set of well known genes. Genes were chosen based on their role in either the breakdown of the extracellular matrix or with changes in cellular metabolism both of which are associated with CRC progression Findings Gene expression data derived from quantitative real-time PCR for the solute transporter carriers (SLCs and the invasion-mediating matrix metalloproteinases (MMPs were examined using a Linear Descriminant Analysis (LDA. The combination of MMP-7 and SLC5A8 was found to be the most predictive of CRC. Conclusion A combinatorial analysis technique is an effective method for both furthering our understanding on the molecular basis of some aspects of CRC, as well as for leveraging well defined cancer-related gene sets to identify cancer. In this instance, the combination of MMP-7 and SLC5A8 were optimal for identifying CRC.

Quantum mechanical energy-based screening of combinatorially generated library of tautomers. TauTGen: a tautomer generator program.

Science.gov (United States)

Harańczyk, Maciej; Gutowski, Maciej

2007-01-01

We describe a procedure of finding low-energy tautomers of a molecule. The procedure consists of (i) combinatorial generation of a library of tautomers, (ii) screening based on the results of geometry optimization of initial structures performed at the density functional level of theory, and (iii) final refinement of geometry for the top hits at the second-order Möller-Plesset level of theory followed by single-point energy calculations at the coupled cluster level of theory with single, double, and perturbative triple excitations. The library of initial structures of various tautomers is generated with TauTGen, a tautomer generator program. The procedure proved to be successful for these molecular systems for which common chemical knowledge had not been sufficient to predict the most stable structures.

Using combinatorial problem decomposition for optimizing plutonium inventory management

International Nuclear Information System (INIS)

Niquil, Y.; Gondran, M.; Voskanian, A.; Paris-11 Univ., 91 - Orsay

1997-03-01

Plutonium Inventory Management Optimization can be modeled as a very large 0-1 linear program. To solve it, problem decomposition is necessary, since other classic techniques are not efficient for such a size. The first decomposition consists in favoring constraints that are the most difficult to reach and variables that have the highest influence on the cost: fortunately, both correspond to stock output decisions. The second decomposition consists in mixing continuous linear program solving and integer linear program solving. Besides, the first decisions to be taken are systematically favored, for they are based on data considered to be sure, when data supporting later decisions in known with less accuracy and confidence. (author)

Using combinatorial problem decomposition for optimizing plutonium inventory management

Energy Technology Data Exchange (ETDEWEB)

Niquil, Y.; Gondran, M. [Electricite de France (EDF), 92 - Clamart (France). Direction des Etudes et Recherches; Voskanian, A. [Electricite de France (EDF), 92 - Clamart (France). Direction des Etudes et Recherches]|[Paris-11 Univ., 91 - Orsay (France). Lab. de Recherche en Informatique

1997-03-01

Plutonium Inventory Management Optimization can be modeled as a very large 0-1 linear program. To solve it, problem decomposition is necessary, since other classic techniques are not efficient for such a size. The first decomposition consists in favoring constraints that are the most difficult to reach and variables that have the highest influence on the cost: fortunately, both correspond to stock output decisions. The second decomposition consists in mixing continuous linear program solving and integer linear program solving. Besides, the first decisions to be taken are systematically favored, for they are based on data considered to be sure, when data supporting later decisions in known with less accuracy and confidence. (author) 7 refs.

Determination Of Optimal Stope Strike Length On Steep Orebodies Through Laser Scanning At Lubambe Copper Zambia

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Kalume H

2017-08-01

Full Text Available Lubambe Copper Mine is located in Chililabombwe Zambia and is a joint copper mining venture with three partners that include African Rainbow Minerals 40 Vale 40 and the Government of Zambia 20. The current mining method utilises Longitudinal Room and Pillar Mining LRP on 70m long panels strike length. However these long panels have resulted in unprecedented levels of dilution mainly from the collapse of hanging wall laminated ore shale OS2 leading to reduced recoveries. Observations made underground show high variability in geological and geotechnical conditions of the rock mass with factors such as weathering on joints lamina spaced joints and stress changes induced by mining all contributing to weakening and early collapse of the hanging wall. Therefore a study was undertaken to establish the optimal stope strike length of steep ore bodies at Lubambe. The exercise involved the use of Faro Laser Scanner every four stope rings blasted with time when the scan was performed noted. The spatial coherence of lasers makes them ideal measuring tools in situations where measurements need to be taken in inaccessible areas. Recent advances in laser scanning coupled with the exponential increase in processing power have greatly improved the methods used to estimate stope tonnages extracted from massive inaccessible stopes. The collected data was then used to construct digital three dimensional models of the stope contents. Sections were cut every metre with deformations taken and analysed with respect to time. Deformation rates from the hanging wall was reducing from 0.14thr to 0.07thr between rings 1 to 8. This reduction was as a result of slot blasting that involved drilling and blasting a number of holes at the same time. Between rings 8 to 25 deformation was constant averaging 0.28thr and between rings 26 and 28 a sharp increase in deformation rate was experienced from as low as 0.16thr to 6.33thr. This sharp increase defines the optimal stope length

Anti-termite efficacy of Capparis decidua and its combinatorial ...

African Journals Online (AJOL)

Michael Horsfall

ABSTRACT: Capparis deciduas and its combinatorial mixtures were evaluated to observe the anti-termite efficacy against Indian white termite Odontotermes obesus. These have shown very high termiticidal activity and wood protection in the soil. It is proved by very low LD50 values i.e. 0.0218mg/g and 0.021mg/g obtained ...

A Nonpolynomial Optimal Algorithm for Sequencing Inspectors in a Repeat Inspection System with Rework

Directory of Open Access Journals (Sweden)

Moon Hee Yang

2015-01-01

Full Text Available Assuming that two types of inspection errors are nonidentical and that only the items rejected by an inspector are reworked and sent to the next inspection cycle, we formulate a combinatorial optimization problem for simultaneously determining both the minimum frequency of inspection-rework cycles and the optimal sequence of inspectors selected from a set of available inspectors, in order to meet the constraints of the outgoing quality level. Based on the inherent properties from our mathematical model, we provide a nonpolynomial optimal algorithm with a time complexity of O(2m.

Combinatorial drug screening identifies Ewing sarcoma-specific sensitivities

OpenAIRE

Radic-Sarikas, Branka; Tsafou, Kalliopi P.; Emdal, Kristina B.; Papamarkou, Theodore; Huber, Kilian V.M.; Mutz, Cornelia; Toretsky, Jeffrey A.; Bennett, Keiryn L.; Olsen, Jesper V.; Brunak, Søren; Kovar, Heinrich; Superti-Furga, Giulio

2017-01-01

Improvements in survival for Ewing sarcoma pediatric and adolescent patients have been modest over the past 20 years. Combinations of anticancer agents endure as an option to overcome resistance to single treatments caused by compensatory pathways. Moreover, combinations are thought to lessen any associated adverse side effects through reduced dosing, which is particularly important in childhood tumors. Using a parallel phenotypic combinatorial screening approach of cells derived from three p...

The optimal design of 15 nm gate-length junctionless SOI FinFETs for reducing leakage current

International Nuclear Information System (INIS)

Liu, Xi; Wu, Meile; Jin, Xiaoshi; Chuai, Rongyan; Lee, Jung-Hee; Lee, Jong-Ho

2013-01-01

Junctionless (JL) transistors need to be heavily doped to have large drain current in the ON-state, which engenders the effect of band-to-band tunneling (BTBT) in the OFF-state simultaneously. It causes an obvious increase of the leakage current in the OFF-state. This paper presents an effective method of reducing the leakage current by changing the geometrical shape and dimension of the oxide layer under the edge of the gate. The optimal design of 15 nm gate-length JL silicon-on-insulator FinFETs with the triple-gate structure is performed for reducing the effect of BTBT through simulation and analysis by this means. (paper)

Multi-line split DNA synthesis: a novel combinatorial method to make high quality peptide libraries

Directory of Open Access Journals (Sweden)

Ueno Shingo

2004-09-01

Full Text Available Abstract Background We developed a method to make a various high quality random peptide libraries for evolutionary protein engineering based on a combinatorial DNA synthesis. Results A split synthesis in codon units was performed with mixtures of bases optimally designed by using a Genetic Algorithm program. It required only standard DNA synthetic reagents and standard DNA synthesizers in three lines. This multi-line split DNA synthesis (MLSDS is simply realized by adding a mix-and-split process to normal DNA synthesis protocol. Superiority of MLSDS method over other methods was shown. We demonstrated the synthesis of oligonucleotide libraries with 1016 diversity, and the construction of a library with random sequence coding 120 amino acids containing few stop codons. Conclusions Owing to the flexibility of the MLSDS method, it will be able to design various "rational" libraries by using bioinformatics databases.

ON range searching in the group model and combinatorial discrepancy

DEFF Research Database (Denmark)

Larsen, Kasper Green

2014-01-01

In this paper we establish an intimate connection between dynamic range searching in the group model and combinatorial discrepancy. Our result states that, for a broad class of range searching data structures (including all known upper bounds), it must hold that $t_u t_q=\\Omega(\\mbox{disc}^2......)$, where $t_u$ is the worst case update time, $t_q$ is the worst case query time, and disc is the combinatorial discrepancy of the range searching problem in question. This relation immediately implies a whole range of exceptionally high and near-tight lower bounds for all of the basic range searching...... problems. We list a few of them in the following: (1) For $d$-dimensional halfspace range searching, we get a lower bound of $t_u t_q=\\Omega(n^{1-1/d})$. This comes within an lg lg $n$ factor of the best known upper bound. (2) For orthogonal range searching, we get a lower bound of $t_u t...

ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

KAUST Repository

Kuwahara, Hiroyuki; Umarov, Ramzan; Almasri, Islam; Gao, Xin

2017-01-01

To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

KAUST Repository

Kuwahara, Hiroyuki

2017-03-01

To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

Solidified self-nanoemulsifying formulation for oral delivery of combinatorial therapeutic regimen

DEFF Research Database (Denmark)

Jain, Amit K; Thanki, Kaushik; Jain, Sanyog

2014-01-01

PURPOSE: The present work reports rationalized development and characterization of solidified self-nanoemulsifying drug delivery system for oral delivery of combinatorial (tamoxifen and quercetin) therapeutic regimen. METHODS: Suitable oil for the preparation of liquid SNEDDS was selected based...

Combinatorial assembly of small molecules into bivalent antagonists of TrkC or TrkA receptors.

Directory of Open Access Journals (Sweden)

Fouad Brahimi

Full Text Available A library of peptidomimetics was assembled combinatorially into dimers on a triazine-based core. The pharmacophore corresponds to β-turns of the neurotrophin polypeptides neurotrophin-3 (NT-3, nerve growth factor (NGF, or brain-derived neurotrophic factor (BDNF. These are the natural ligands for TrkC, TrkA, and TrkB receptors, respectively. The linker length and the side-chain orientation of each monomer within the bivalent mimics were systematically altered, and the impact of these changes on the function of each ligand was evaluated. While the monovalent peptidomimetics had no detectable binding or bioactivity, four bivalent peptidomimetics (2c, 2d, 2e, 3f are selective TrkC ligands with antagonistic activity, and two bivalent peptidomimetics (1a, 1b are TrkC and TrkA ligands with antagonistic activity. All these bivalent compounds block ligand-dependent receptor activation and cell survival, without affecting neuritogenic differentiation. This work adds to our understanding of how the neurotrophins function through Trk receptors, and demonstrates that peptidomimetics can be designed to selectively disturb specific biological signals, and may be used as pharmacological probes or as therapeutic leads. The concept of altering side-chain, linker length, and sequence orientation of a subunit within a pharmacophore provides an easy modular approach to generate larger libraries with diversified bioactivity.

Validity of plant fiber length measurement : a review of fiber length measurement based on kenaf as a model

Science.gov (United States)

James S. Han; Theodore. Mianowski; Yi-yu. Lin

1999-01-01

The efficacy of fiber length measurement techniques such as digitizing, the Kajaani procedure, and NIH Image are compared in order to determine the optimal tool. Kenaf bast fibers, aspen, and red pine fibers were collected from different anatomical parts, and the fiber lengths were compared using various analytical tools. A statistical analysis on the validity of the...

Automated Lead Optimization of MMP-12 Inhibitors Using a Genetic Algorithm.

Science.gov (United States)

Pickett, Stephen D; Green, Darren V S; Hunt, David L; Pardoe, David A; Hughes, Ian

2011-01-13

Traditional lead optimization projects involve long synthesis and testing cycles, favoring extensive structure-activity relationship (SAR) analysis and molecular design steps, in an attempt to limit the number of cycles that a project must run to optimize a development candidate. Microfluidic-based chemistry and biology platforms, with cycle times of minutes rather than weeks, lend themselves to unattended autonomous operation. The bottleneck in the lead optimization process is therefore shifted from synthesis or test to SAR analysis and design. As such, the way is open to an algorithm-directed process, without the need for detailed user data analysis. Here, we present results of two synthesis and screening experiments, undertaken using traditional methodology, to validate a genetic algorithm optimization process for future application to a microfluidic system. The algorithm has several novel features that are important for the intended application. For example, it is robust to missing data and can suggest compounds for retest to ensure reliability of optimization. The algorithm is first validated on a retrospective analysis of an in-house library embedded in a larger virtual array of presumed inactive compounds. In a second, prospective experiment with MMP-12 as the target protein, 140 compounds are submitted for synthesis over 10 cycles of optimization. Comparison is made to the results from the full combinatorial library that was synthesized manually and tested independently. The results show that compounds selected by the algorithm are heavily biased toward the more active regions of the library, while the algorithm is robust to both missing data (compounds where synthesis failed) and inactive compounds. This publication places the full combinatorial library and biological data into the public domain with the intention of advancing research into algorithm-directed lead optimization methods.

Introducing Dynamic Combinatorial Chemistry: Probing the Substrate Selectivity of Acetylcholinesterase

Science.gov (United States)

Angelin, Marcus; Larsson, Rikard; Vongvilai, Pornrapee; Ramstrom, Olof

2010-01-01

In this laboratory experiment, college students are introduced to dynamic combinatorial chemistry (DCC) and apply it to determine the substrate selectivity of acetylcholinesterase (AChE). Initially, the students construct a chemical library of dynamically interchanging thioesters and thiols. Then, AChE is added and allowed to select and hydrolyze…

Optimal placement of excitations and sensors for verification of large dynamical systems

Science.gov (United States)

Salama, M.; Rose, T.; Garba, J.

1987-01-01

The computationally difficult problem of the optimal placement of excitations and sensors to maximize the observed measurements is studied within the framework of combinatorial optimization, and is solved numerically using a variation of the simulated annealing heuristic algorithm. Results of numerical experiments including a square plate and a 960 degrees-of-freedom Control of Flexible Structure (COFS) truss structure, are presented. Though the algorithm produces suboptimal solutions, its generality and simplicity allow the treatment of complex dynamical systems which would otherwise be difficult to handle.

Length scale and manufacturability in density-based topology optimization

DEFF Research Database (Denmark)

Lazarov, Boyan Stefanov; Wang, Fengwen; Sigmund, Ole

2016-01-01

Since its original introduction in structural design, density-based topology optimization has been applied to a number of other fields such as microelectromechanical systems, photonics, acoustics and fluid mechanics. The methodology has been well accepted in industrial design processes where it can...... provide competitive designs in terms of cost, materials and functionality under a wide set of constraints. However, the optimized topologies are often considered as conceptual due to loosely defined topologies and the need of postprocessing. Subsequent amendments can affect the optimized design...

Decision and Inhibitory Rule Optimization for Decision Tables with Many-valued Decisions

KAUST Repository

Alsolami, Fawaz

2016-04-25

‘If-then’ rule sets are one of the most expressive and human-readable knowledge representations. This thesis deals with optimization and analysis of decision and inhibitory rules for decision tables with many-valued decisions. The most important areas of applications are knowledge extraction and representation. The benefit of considering inhibitory rules is connected with the fact that in some situations they can describe more knowledge than the decision ones. Decision tables with many-valued decisions arise in combinatorial optimization, computational geometry, fault diagnosis, and especially under the processing of data sets. In this thesis, various examples of real-life problems are considered which help to understand the motivation of the investigation. We extend relatively simple results obtained earlier for decision rules over decision tables with many-valued decisions to the case of inhibitory rules. The behavior of Shannon functions (which characterize complexity of rule systems) is studied for finite and infinite information systems, for global and local approaches, and for decision and inhibitory rules. The extensions of dynamic programming for the study of decision rules over decision tables with single-valued decisions are generalized to the case of decision tables with many-valued decisions. These results are also extended to the case of inhibitory rules. As a result, we have algorithms (i) for multi-stage optimization of rules relative to such criteria as length or coverage, (ii) for counting the number of optimal rules, (iii) for construction of Pareto optimal points for bi-criteria optimization problems, (iv) for construction of graphs describing relationships between two cost functions, and (v) for construction of graphs describing relationships between cost and accuracy of rules. The applications of created tools include comparison (based on information about Pareto optimal points) of greedy heuristics for bi-criteria optimization of rules

A set of rules for constructing an admissible set of D optimal exact ...

African Journals Online (AJOL)

In the search for a D-optimal exact design using the combinatorial iterative technique introduced by Onukogu and Iwundu, 2008, all the support points that make up the experimental region are grouped into H concentric balls according to their distances from the centre. Any selection of N support points from the balls defines ...

Loading pattern optimization using ant colony algorithm

International Nuclear Information System (INIS)

Hoareau, Fabrice

2008-01-01

Electricite de France (EDF) operates 58 nuclear power plants (NPP), of the Pressurized Water Reactor type. The loading pattern optimization of these NPP is currently done by EDF expert engineers. Within this framework, EDF R and D has developed automatic optimization tools that assist the experts. LOOP is an industrial tool, developed by EDF R and D and based on a simulated annealing algorithm. In order to improve the results of such automatic tools, new optimization methods have to be tested. Ant Colony Optimization (ACO) algorithms are recent methods that have given very good results on combinatorial optimization problems. In order to evaluate the performance of such methods on loading pattern optimization, direct comparisons between LOOP and a mock-up based on the Max-Min Ant System algorithm (a particular variant of ACO algorithms) were made on realistic test-cases. It is shown that the results obtained by the ACO mock-up are very similar to those of LOOP. Future research will consist in improving these encouraging results by using parallelization and by hybridizing the ACO algorithm with local search procedures. (author)

AngelStow: A Commercial Optimization-Based Decision Support Tool for Stowage Planning

DEFF Research Database (Denmark)

Delgado-Ortegon, Alberto; Jensen, Rune Møller; Guilbert, Nicolas

save port fees, optimize use of vessel capacity, and reduce bunker consumption. Stowage Coordinators (SCs) produce these plans manually with the help of graphical tools, but high-quality SPs are hard to generate with the limited support they provide. In this abstract, we introduce AngelStow which...... is a commercial optimization-based decision support tool for stowing container vessels developed in collaboration between Ange Optimization and The IT University of Copenhagen. The tool assists SCs in the process of generating SPs interactively, focusing on satisfying and optimizing constraints and objectives...... that are tedious to deal with for humans, while letting the SCs use their expertise to deal with hard combinatorial objectives and corner cases....

Deciphering Cis-Regulatory Element Mediated Combinatorial Regulation in Rice under Blast Infected Condition.

Directory of Open Access Journals (Sweden)

Arindam Deb

Full Text Available Combinations of cis-regulatory elements (CREs present at the promoters facilitate the binding of several transcription factors (TFs, thereby altering the consequent gene expressions. Due to the eminent complexity of the regulatory mechanism, the combinatorics of CRE-mediated transcriptional regulation has been elusive. In this work, we have developed a new methodology that quantifies the co-occurrence tendencies of CREs present in a set of promoter sequences; these co-occurrence scores are filtered in three consecutive steps to test their statistical significance; and the significantly co-occurring CRE pairs are presented as networks. These networks of co-occurring CREs are further transformed to derive higher order of regulatory combinatorics. We have further applied this methodology on the differentially up-regulated gene-sets of rice tissues under fungal (Magnaporthe infected conditions to demonstrate how it helps to understand the CRE-mediated combinatorial gene regulation. Our analysis includes a wide spectrum of biologically important results. The CRE pairs having a strong tendency to co-occur often exhibit very similar joint distribution patterns at the promoters of rice. We couple the network approach with experimental results of plant gene regulation and defense mechanisms and find evidences of auto and cross regulation among TF families, cross-talk among multiple hormone signaling pathways, similarities and dissimilarities in regulatory combinatorics between different tissues, etc. Our analyses have pointed a highly distributed nature of the combinatorial gene regulation facilitating an efficient alteration in response to fungal attack. All together, our proposed methodology could be an important approach in understanding the combinatorial gene regulation. It can be further applied to unravel the tissue and/or condition specific combinatorial gene regulation in other eukaryotic systems with the availability of annotated genomic

Optimal shaping and positioning of energy-efficient buildings

Directory of Open Access Journals (Sweden)

Barović Dušan D.

2017-01-01

Full Text Available Due to the number of variables and the complexity of objective functions, optimal design of an energy-efficient building is hard combinatorial problem of multi-objective optimisation. Therefore, it is necessary to describe structure and its position in surroundings precisely but by as few variables as possible. This paper presents methodology for finding adequate methodology for defining geometry and orientation of a given building, as well as its elements of importance for energy-efficiency analysis.

Dynamic combinatorial chemistry to identify binders of ThiT, an S-component of the energy-coupling factor transporter for thiamine

NARCIS (Netherlands)

Monjas, Leticia; Swier, Lotteke J Y M; Setyawati, Inda; Slotboom, Dirk Jan; Hirsch, Anna Katharina Herta

2017-01-01

We applied dynamic combinatorial chemistry (DCC) to identify ligands of ThiT, the S-component of the energy-coupling factor (ECF) transporter for thiamine in Lactococcus lactis. We used a pre-equilibrated dynamic combinatorial library (DCL) and saturation-transfer difference (STD) NMR spectroscopy

Visibility-based optimal path and motion planning

CERN Document Server

Wang, Paul Keng-Chieh

2015-01-01

This monograph deals with various visibility-based path and motion planning problems motivated by real-world applications such as exploration and mapping planetary surfaces, environmental surveillance using stationary or mobile robots, and imaging of global air/pollutant circulation. The formulation and solution of these problems call for concepts and methods from many areas of applied mathematics including computational geometry, set-covering, non-smooth optimization, combinatorial optimization and optimal control. Emphasis is placed on the formulation of new problems and methods of approach to these problems. Since geometry and visualization play important roles in the understanding of these problems, intuitive interpretations of the basic concepts are presented before detailed mathematical development. The development of a particular topic begins with simple cases illustrated by specific examples, and then progresses forward to more complex cases. The intended readers of this monograph are primarily studen...

Method and apparatus for combinatorial chemistry

Science.gov (United States)

Foote, Robert S [Oak Ridge, TN

2012-06-05

A method and apparatus are provided for performing light-directed reactions in spatially addressable channels within a plurality of channels. One aspect of the invention employs photoactivatable reagents in solutions disposed into spatially addressable flow streams to control the parallel synthesis of molecules immobilized within the channels. The reagents may be photoactivated within a subset of channels at the site of immobilized substrate molecules or at a light-addressable site upstream from the substrate molecules. The method and apparatus of the invention find particularly utility in the synthesis of biopolymer arrays, e.g., oligonucleotides, peptides and carbohydrates, and in the combinatorial synthesis of small molecule arrays for drug discovery.

Geometric Generalisation of Surrogate Model-Based Optimisation to Combinatorial and Program Spaces

Directory of Open Access Journals (Sweden)

Yong-Hyuk Kim

2014-01-01

Full Text Available Surrogate models (SMs can profitably be employed, often in conjunction with evolutionary algorithms, in optimisation in which it is expensive to test candidate solutions. The spatial intuition behind SMs makes them naturally suited to continuous problems, and the only combinatorial problems that have been previously addressed are those with solutions that can be encoded as integer vectors. We show how radial basis functions can provide a generalised SM for combinatorial problems which have a geometric solution representation, through the conversion of that representation to a different metric space. This approach allows an SM to be cast in a natural way for the problem at hand, without ad hoc adaptation to a specific representation. We test this adaptation process on problems involving binary strings, permutations, and tree-based genetic programs.

Discovery of Cationic Polymers for Non-viral Gene Delivery using Combinatorial Approaches

Science.gov (United States)

Barua, Sutapa; Ramos, James; Potta, Thrimoorthy; Taylor, David; Huang, Huang-Chiao; Montanez, Gabriela; Rege, Kaushal

2015-01-01

Gene therapy is an attractive treatment option for diseases of genetic origin, including several cancers and cardiovascular diseases. While viruses are effective vectors for delivering exogenous genes to cells, concerns related to insertional mutagenesis, immunogenicity, lack of tropism, decay and high production costs necessitate the discovery of non-viral methods. Significant efforts have been focused on cationic polymers as non-viral alternatives for gene delivery. Recent studies have employed combinatorial syntheses and parallel screening methods for enhancing the efficacy of gene delivery, biocompatibility of the delivery vehicle, and overcoming cellular level barriers as they relate to polymer-mediated transgene uptake, transport, transcription, and expression. This review summarizes and discusses recent advances in combinatorial syntheses and parallel screening of cationic polymer libraries for the discovery of efficient and safe gene delivery systems. PMID:21843141

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

Science.gov (United States)

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

Multi-objective optimization in computer networks using metaheuristics

CERN Document Server

Donoso, Yezid

2007-01-01

Metaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design and to provide for these kinds of applications as well as for those resources necessary for functionality. Multi-Objective Optimization in Computer Networks Using Metaheuristics provides a solution to the multi-objective problem in routing computer networks. It analyzes layer 3 (IP), layer 2 (MPLS), and layer 1 (GMPLS and wireless functions). In particular, it assesses basic optimization concepts, as well as several techniques and algorithms for the search of minimals; examines the basic multi-objective optimization concepts and the way to solve them through traditional techniques and through several metaheuristics; and demonstrates how to analytically model the compu...

Efficient Discovery of Nonlinear Dependencies in a Combinatorial Catalyst Data Set

Czech Academy of Sciences Publication Activity Database

Cawse, J.N.; Baerns, M.; Holeňa, Martin

2004-01-01

Roč. 44, č. 3 (2004), s. 143-146 ISSN 0095-2338 Source of funding: V - iné verejné zdroje Keywords : combinatorial catalysis * genetic algorithms * nonlinear dependency * data analysis * high-order interactions Subject RIV: IN - Informatics, Computer Science Impact factor: 2.810, year: 2004

A combinatorial framework to quantify peak/pit asymmetries in complex dynamics

NARCIS (Netherlands)

Hasson, Uri; Iacovacci, Jacopo; Davis, Ben; Flanagan, Ryan; Tagliazucchi, E.; Laufs, Helmut; Lacasa, Lucas

2018-01-01

We explore a combinatorial framework which efficiently quantifies the asymmetries between minima and maxima in local fluctuations of time series. We first showcase its performance by applying it to a battery of synthetic cases. We find rigorous results on some canonical dynamical models (stochastic

Sentence Processing in an Artificial Language: Learning and Using Combinatorial Constraints

Science.gov (United States)

Amato, Michael S.; MacDonald, Maryellen C.

2010-01-01

A study combining artificial grammar and sentence comprehension methods investigated the learning and online use of probabilistic, nonadjacent combinatorial constraints. Participants learned a small artificial language describing cartoon monsters acting on objects. Self-paced reading of sentences in the artificial language revealed comprehenders'…

Workshop on Strategic Behavior and Phase Transitions in Random and Complex Combinatorial Structures : Extended Abstracts

CERN Document Server

Kirousis, Lefteris; Ortiz-Gracia, Luis; Serna, Maria

2017-01-01

This book is divided into two parts, the first of which seeks to connect the phase transitions of various disciplines, including game theory, and to explore the synergies between statistical physics and combinatorics. Phase Transitions has been an active multidisciplinary field of research, bringing together physicists, computer scientists and mathematicians. The main research theme explores how atomic agents that act locally and microscopically lead to discontinuous macroscopic changes. Adopting this perspective has proven to be especially useful in studying the evolution of random and usually complex or large combinatorial objects (like networks or logic formulas) with respect to discontinuous changes in global parameters like connectivity, satisfiability etc. There is, of course, an obvious strategic element in the formation of a transition: the atomic agents “selfishly” seek to optimize a local parameter. However, up to now this game-theoretic aspect of abrupt, locally triggered changes had not been e...

Obfuscation Framework Based on Functionally Equivalent Combinatorial Logic Families

Science.gov (United States)

2008-03-01

of Defense, or the United States Government . AFIT/GCS/ENG/08-12 Obfuscation Framework Based on Functionally Equivalent Combinatorial Logic Families...time, United States policy strongly encourages the sale and transfer of some military equipment to foreign governments and makes it easier for...Proceedings of the International Conference on Availability, Reliability and Security, 2007. 14. McDonald, J. Todd and Alec Yasinsac. “Of unicorns and random

Statistical mechanical analysis of linear programming relaxation for combinatorial optimization problems

Science.gov (United States)

Takabe, Satoshi; Hukushima, Koji

2016-05-01

Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α -uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α =2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c =e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c =1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α ≥3 , minimum vertex covers on α -uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c =e /(α -1 ) where the replica symmetry is broken.

Statistical mechanical analysis of linear programming relaxation for combinatorial optimization problems.

Science.gov (United States)

Takabe, Satoshi; Hukushima, Koji

2016-05-01

Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α-uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α=2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c=e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c=1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α≥3, minimum vertex covers on α-uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c=e/(α-1) where the replica symmetry is broken.

Optimal patent policies: A survey

DEFF Research Database (Denmark)

Poulsen, Odile

2002-01-01

This paper surveys some of the patent literature, in particular, it focuses on optimal patent policies. We compare two situations. The first where the government only has a single policy tool to design the optimal patent policy, namely the optimal patent length. In the second situation......, the government uses two policy tools, the optimal breadth and length. We show that theoretical models give very different answers to what is the optimal patent policy. In particular, we show that the optimal patent policy depends among othet things on the price elasticity of demand, the intersectoral elasticity...... of research outputs as well as the degree of compettition in the R&D sector. The actual law on intellectual property, which advocates a unique patent length of 20 years is in general not supported by theoretical models....

Length and coverage of inhibitory decision rules

KAUST Repository

Alsolami, Fawaz

2012-01-01

Authors present algorithms for optimization of inhibitory rules relative to the length and coverage. Inhibitory rules have a relation "attribute ≠ value" on the right-hand side. The considered algorithms are based on extensions of dynamic programming. Paper contains also comparison of length and coverage of inhibitory rules constructed by a greedy algorithm and by the dynamic programming algorithm. © 2012 Springer-Verlag.

Optimal design of a diesel-PV-wind system with batteries and hydro pumped storage in a Colombian community

NARCIS (Netherlands)

Alvarez, Semaria Ruiz; Ruiz, Alejandro Márquez; Oviedo, Jairo Espinosa

2017-01-01

This paper proposes to use a combinatorial optimization technique, the branch and cut algorithm, to design an hybrid isolated microgrid in the Colombian community of Unguia. In addition, this paper presents a comparison between the designs obtained with the branch and cut algorithm, the software

Optimization image of magnetic resonance imaging (MRI) T2 fast spin echo (FSE) with variation echo train length (ETL) on the rupture tendon achilles case

International Nuclear Information System (INIS)

Muzamil, Akhmad; Firmansyah, Achmad Haries

2017-01-01

The research was done the optimization image of Magnetic Resonance Imaging (MRI) T2 Fast Spin Echo (FSE) with variation Echo Train Length (ETL) on the Rupture Tendon Achilles case. This study aims to find the variations Echo Train Length (ETL) from the results of ankle’s MRI image and find out how the value of Echo Train Length (ETL) works on the MRI ankle to produce optimal image. In this research, the used ETL variations were 12 and 20 with the interval 2 on weighting T2 FSE sagittal. The study obtained the influence of Echo Train Length (ETL) on the quality of ankle MRI image sagittal using T2 FSE weighting and analyzed in 25 images of five patients. The data analysis has done quantitatively with the Region of Interest (ROI) directly on computer MRI image planes which conducted statistical tests Signal to Noise Ratio (SNR) and Contras to Noise Ratio (CNR). The Signal to Noise Ratio (SNR) was the highest finding on fat tissue, while the Contras to Noise Ratio (CNR) on the Tendon-Fat tissue with ETL 12 found in two patients. The statistics test showed the significant SNR value of the 0.007 (p<0.05) of Tendon tissue, 0.364 (p>0.05) of the Fat, 0.912 (p>0.05) of the Fibula, and 0.436 (p>0.05) of the Heel Bone. For the contrast to noise ratio (CNR) of the Tendon-FAT tissue was about 0.041 (p>0.05). The results of the study showed that ETL variation with T2 FSE sagittal weighting had difference at Tendon tissue and Tendon-Fat tissue for MRI imaging quality. SNR and CNR were an important aspect on imaging optimization process to give the diagnose information. (paper)

Similarity searching and scaffold hopping in synthetically accessible combinatorial chemistry spaces.

Science.gov (United States)

Boehm, Markus; Wu, Tong-Ying; Claussen, Holger; Lemmen, Christian

2008-04-24

Large collections of combinatorial libraries are an integral element in today's pharmaceutical industry. It is of great interest to perform similarity searches against all virtual compounds that are synthetically accessible by any such library. Here we describe the successful application of a new software tool CoLibri on 358 combinatorial libraries based on validated reaction protocols to create a single chemistry space containing over 10 (12) possible products. Similarity searching with FTrees-FS allows the systematic exploration of this space without the need to enumerate all product structures. The search result is a set of virtual hits which are synthetically accessible by one or more of the existing reaction protocols. Grouping these virtual hits by their synthetic protocols allows the rapid design and synthesis of multiple follow-up libraries. Such library ideas support hit-to-lead design efforts for tasks like follow-up from high-throughput screening hits or scaffold hopping from one hit to another attractive series.

Affinity-based screening of combinatorial libraries using automated, serial-column chromatography

Energy Technology Data Exchange (ETDEWEB)

Evans, D.M.; Williams, K.P.; McGuinness, B. [PerSeptive Biosystems, Framingham, MA (United States)] [and others

1996-04-01

The authors have developed an automated serial chromatographic technique for screening a library of compounds based upon their relative affinity for a target molecule. A {open_quotes}target{close_quotes} column containing the immobilized target molecule is set in tandem with a reversed-phase column. A combinatorial peptide library is injected onto the target column. The target-bound peptides are eluted from the first column and transferred automatically to the reversed-phase column. The target-specific peptide peaks from the reversed-phase column are identified and sequenced. Using a monoclonal antibody (3E-7) against {beta}-endorphin as a target, we selected a single peptide with sequence YGGFL from approximately 5800 peptides present in a combinatorial library. We demonstrated the applicability of the technology towards selection of peptides with predetermined affinity for bacterial lipopolysaccharide (LPS, endotoxin). We expect that this technology will have broad applications for high throughput screening of chemical libraries or natural product extracts. 21 refs., 4 figs.

A Combinatorial Proof of a Result on Generalized Lucas Polynomials

Directory of Open Access Journals (Sweden)

Laugier Alexandre

2016-09-01

Full Text Available We give a combinatorial proof of an elementary property of generalized Lucas polynomials, inspired by [1]. These polynomials in s and t are defined by the recurrence relation 〈n〉 = s〈n-1〉+t〈n-2〉 for n ≥ 2. The initial values are 〈0〉 = 2; 〈1〉= s, respectively.

Combinatorial interpretation of Haldane-Wu fractional exclusion statistics.

Science.gov (United States)

Aringazin, A K; Mazhitov, M I

2002-08-01

Assuming that the maximal allowed number of identical particles in a state is an integer parameter, q, we derive the statistical weight and analyze the associated equation that defines the statistical distribution. The derived distribution covers Fermi-Dirac and Bose-Einstein ones in the particular cases q=1 and q--> infinity (n(i)/q-->1), respectively. We show that the derived statistical weight provides a natural combinatorial interpretation of Haldane-Wu fractional exclusion statistics, and present exact solutions of the distribution equation.

Combinatorial Models for Assembly and Decomposition of Products

OpenAIRE

A. N. Bojko

2015-01-01

The paper discusses the most popular combinatorial models that are used for the synthesis of design solutions at the stage of the assembly process flow preparation. It shows that while assembling the product the relations of parts can be represented as a structure of preferences, which is formed on the basis of objective design restrictions put in at the stage of the product design. This structure is a binary preference relation pre-order. Its symmetrical part is equivalence and describes the...

Spatial planning via extremal optimization enhanced by cell-based local search

International Nuclear Information System (INIS)

Sidiropoulos, Epaminondas

2014-01-01

A new treatment is presented for land use planning problems by means of extremal optimization in conjunction to cell-based neighborhood local search. Extremal optimization, inspired by self-organized critical models of evolution has been applied mainly to the solution of classical combinatorial optimization problems. Cell-based local search has been employed by the author elsewhere in problems of spatial resource allocation in combination with genetic algorithms and simulated annealing. In this paper it complements extremal optimization in order to enhance its capacity for a spatial optimization problem. The hybrid method thus formed is compared to methods of the literature on a specific characteristic problem. It yields better results both in terms of objective function values and in terms of compactness. The latter is an important quantity for spatial planning. The present treatment yields significant compactness values as emergent results

Quick screening for new flux pinning materials in YBCO films with the combinatorial-PLD method

International Nuclear Information System (INIS)

Yoshimura, T.; Ichino, Y.; Yoshida, Y.; Takai, Y.; Kita, R.; Suzuki, K.; Takeuchi, T.

2011-01-01

An effective way to improve the superconducting properties in REBa 2 Cu 3 O y (REBCO) films under a magnetic field is to dope artificial pinning centers (APC). The pinning performance depends on the content of the APC materials. Usually, the optimal APC content is explored by preparing films one at a time from the REBCO target using different APC material content, which is an extremely time-consuming process. The combinatorial-PLD (C-PLD) method allowed us to prepare films that continuously changed in composition across a single substrate. In this study, we used the C-PLD method to prepare BaSnO 3 (BSO)-doped YBCO films. The films were deposited on SrTiO 3 substrate using a fourth-harmonic Nd:YAG laser. From the results of the J c -B curves at 77 K and B//c, the film that contained 3.2 vol.% of BSO exhibited the best pinning performance in this study. We showed that the C-PLD method was efficient for quick screening of the optimal APC content with only one deposition. We also used the C-PLD method to explore new APC materials, and proved that it can quickly evaluate the new APC materials Ba 3 Cu 3 In 4 O 12 and BaTbO 3 .

Mixture-based combinatorial libraries from small individual peptide libraries: a case study on α1-antitrypsin deficiency.

Science.gov (United States)

Chang, Yi-Pin; Chu, Yen-Ho

2014-05-16

The design, synthesis and screening of diversity-oriented peptide libraries using a "libraries from libraries" strategy for the development of inhibitors of α1-antitrypsin deficiency are described. The major buttress of the biochemical approach presented here is the use of well-established solid-phase split-and-mix method for the generation of mixture-based libraries. The combinatorial technique iterative deconvolution was employed for library screening. While molecular diversity is the general consideration of combinatorial libraries, exquisite design through systematic screening of small individual libraries is a prerequisite for effective library screening and can avoid potential problems in some cases. This review will also illustrate how large peptide libraries were designed, as well as how a conformation-sensitive assay was developed based on the mechanism of the conformational disease. Finally, the combinatorially selected peptide inhibitor capable of blocking abnormal protein aggregation will be characterized by biophysical, cellular and computational methods.

Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model

Science.gov (United States)

Deng, Guang-Feng; Lin, Woo-Tsong

This work presents Ant Colony Optimization (ACO), which was initially developed to be a meta-heuristic for combinatorial optimization, for solving the cardinality constraints Markowitz mean-variance portfolio model (nonlinear mixed quadratic programming problem). To our knowledge, an efficient algorithmic solution for this problem has not been proposed until now. Using heuristic algorithms in this case is imperative. Numerical solutions are obtained for five analyses of weekly price data for the following indices for the period March, 1992 to September, 1997: Hang Seng 31 in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA and Nikkei 225 in Japan. The test results indicate that the ACO is much more robust and effective than Particle swarm optimization (PSO), especially for low-risk investment portfolios.

Optimizing x-ray mirror thermal performance using variable length cooling for second generation FELs

Science.gov (United States)

Hardin, Corey L.; Srinivasan, Venkat N.; Amores, Lope; Kelez, Nicholas M.; Morton, Daniel S.; Stefan, Peter M.; Nicolas, Josep; Zhang, Lin; Cocco, Daniele

2016-09-01

The success of the LCLS led to an interest across a number of disciplines in the scientific community including physics, chemistry, biology, and material science. Fueled by this success, SLAC National Accelerator Laboratory is developing a new high repetition rate free electron laser, LCLS-II, a superconducting linear accelerator capable of a repetition rate up to 1 MHz. Undulators will be optimized for 200 to 1300 eV soft X-rays, and for 1000 to 5000 eV hard X-rays. To absorb spontaneous radiation, higher harmonic energies and deflect the x-ray beam to various end stations, the transport and diagnostics system includes grazing incidence plane mirrors on both the soft and Hard X-ray beamline. To deliver the FEL beam with minimal power loss and wavefront distortion, we need mirrors of height errors below 1nm rms in operational conditions. We need to mitigate the thermal load effects due to the high repetition rate. The absorbed thermal profile is highly dependent on the beam divergence, and this is a function of the photon energy. To address this complexity, we developed a mirror cradle with variable length cooling and first order curve correction. Mirror figure error is minimized using variable length water-cooling through a gallium-indium eutectic bath. Curve correction is achieved with an off-axis bender that will be described in details. We present the design features, mechanical analysis and results from optical and mechanical tests of a prototype assembly, with particular regards to the figure sensitivity to bender corrections.

Simulated annealing method for electronic circuits design: adaptation and comparison with other optimization methods

International Nuclear Information System (INIS)

Berthiau, G.

1995-10-01

The circuit design problem consists in determining acceptable parameter values (resistors, capacitors, transistors geometries ...) which allow the circuit to meet various user given operational criteria (DC consumption, AC bandwidth, transient times ...). This task is equivalent to a multidimensional and/or multi objective optimization problem: n-variables functions have to be minimized in an hyper-rectangular domain ; equality constraints can be eventually specified. A similar problem consists in fitting component models. In this way, the optimization variables are the model parameters and one aims at minimizing a cost function built on the error between the model response and the data measured on the component. The chosen optimization method for this kind of problem is the simulated annealing method. This method, provided by the combinatorial optimization domain, has been adapted and compared with other global optimization methods for the continuous variables problems. An efficient strategy of variables discretization and a set of complementary stopping criteria have been proposed. The different parameters of the method have been adjusted with analytical functions of which minima are known, classically used in the literature. Our simulated annealing algorithm has been coupled with an open electrical simulator SPICE-PAC of which the modular structure allows the chaining of simulations required by the circuit optimization process. We proposed, for high-dimensional problems, a partitioning technique which ensures proportionality between CPU-time and variables number. To compare our method with others, we have adapted three other methods coming from combinatorial optimization domain - the threshold method, a genetic algorithm and the Tabu search method - The tests have been performed on the same set of test functions and the results allow a first comparison between these methods applied to continuous optimization variables. Finally, our simulated annealing program

Extended fuel cycle length

International Nuclear Information System (INIS)

Bruyere, M.; Vallee, A.; Collette, C.

1986-09-01

Extended fuel cycle length and burnup are currently offered by Framatome and Fragema in order to satisfy the needs of the utilities in terms of fuel cycle cost and of overall systems cost optimization. We intend to point out the consequences of an increased fuel cycle length and burnup on reactor safety, in order to determine whether the bounding safety analyses presented in the Safety Analysis Report are applicable and to evaluate the effect on plant licensing. This paper presents the results of this examination. The first part indicates the consequences of increased fuel cycle length and burnup on the nuclear data used in the bounding accident analyses. In the second part of this paper, the required safety reanalyses are presented and the impact on the safety margins of different fuel management strategies is examined. In addition, systems modifications which can be required are indicated

Optimization and quantization in gradient symbol systems: a framework for integrating the continuous and the discrete in cognition.

Science.gov (United States)

Smolensky, Paul; Goldrick, Matthew; Mathis, Donald

2014-08-01

Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The framework we introduce here, Gradient Symbol Processing, characterizes the emergence of grammatical macrostructure from the Parallel Distributed Processing microstructure (McClelland, Rumelhart, & The PDP Research Group, 1986) of language processing. The mental representations that emerge, Distributed Symbol Systems, have both combinatorial and gradient structure. They are processed through Subsymbolic Optimization-Quantization, in which an optimization process favoring representations that satisfy well-formedness constraints operates in parallel with a distributed quantization process favoring discrete symbolic structures. We apply a particular instantiation of this framework, λ-Diffusion Theory, to phonological production. Simulations of the resulting model suggest that Gradient Symbol Processing offers a way to unify accounts of grammatical competence with both discrete and continuous patterns in language performance. Copyright © 2013 Cognitive Science Society, Inc.

Hierarchical Bayesian mixture modelling for antigen-specific T-cell subtyping in combinatorially encoded flow cytometry studies

DEFF Research Database (Denmark)

Lin, Lin; Chan, Cliburn; Hadrup, Sine R

2013-01-01

subtype identification in this novel, general model framework, and provide a detailed example using simulated data. We then describe application to a data set from an experimental study of antigen-specific T-cell subtyping using combinatorially encoded assays in human blood samples. Summary comments...... profiling in many biological areas, traditional flow cytometry measures relative levels of abundance of marker proteins using fluorescently labeled tags that identify specific markers by a single-color. One specific and important recent development in this area is the use of combinatorial marker assays...

Complexity and Tractability Islands for Combinatorial Auctions on Discrete Intervals with Gaps

NARCIS (Netherlands)

Döcker, J.; Dorn, B.; Endriss, U.; Krüger, D.; Kaminka, G.A.; Fox, M.; Bouquet, P.; Hüllermeyer, E.; Dignum, V.; Dignum, F.; van Harmelen, F.

2016-01-01

Combinatorial auctions are mechanisms for allocating bundles of goods to agents who each have preferences over these goods. Finding an economically efficient allocation, the so-called winner determination problem, is computationally intractable in the general case, which is why it is important to

Optimization of fuel reloads for a BWR using the ant colony system

International Nuclear Information System (INIS)

Esquivel E, J.; Ortiz S, J. J.

2009-10-01

In this work some results obtained during the development of optimization systems are presented, which are employees for the fuel reload design in a BWR. The systems use the ant colony optimization technique. As first instance, a system is developed that was adapted at travel salesman problem applied for the 32 state capitals of Mexican Republic. The purpose of this implementation is that a similarity exists with the design of fuel reload, since the two problems are of combinatorial optimization with decision variables that have similarity between both. The system was coupled to simulator SIMULATE-3, obtaining good results when being applied to an operation cycle in equilibrium for reactors of nuclear power plant of Laguna Verde. (Author)

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

Science.gov (United States)

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

2011-02-01

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

COGEDIF - automatic TORT and DORT input generation from MORSE combinatorial geometry models

International Nuclear Information System (INIS)

Castelli, R.A.; Barnett, D.A.

1992-01-01

COGEDIF is an interactive utility which was developed to automate the preparation of two and three dimensional geometrical inputs for the ORNL-TORT and DORT discrete ordinates programs from complex three dimensional models described using the MORSE combinatorial geometry input description. The program creates either continuous or disjoint mesh input based upon the intersections of user defined meshing planes and the MORSE body definitions. The composition overlay of the combinatorial geometry is used to create the composition mapping of the discretized geometry based upon the composition found at the centroid of each of the mesh cells. This program simplifies the process of using discrete orthogonal mesh cells to represent non-orthogonal geometries in large models which require mesh sizes of the order of a million cells or more. The program was specifically written to take advantage of the new TORT disjoint mesh option which was developed at ORNL

Caffeine and length dependence of staircase potentiation in skeletal muscle.

Science.gov (United States)

Rassier, D E; Tubman, L A; MacIntosh, B R

1998-01-01

Skeletal muscle sensitivity to Ca2+ is greater at long lengths, and this results in an optimal length for twitch contractions that is longer than optimal length for tetanic contractions. Caffeine abolishes this length dependence of Ca2+ sensitivity. Muscle length (ML) also affects the degree of staircase potentiation. Since staircase potentiation is apparently caused by an increased Ca2+ sensitivity of the myofilaments, we tested the hypothesis that caffeine depresses the length dependence of staircase potentiation. In situ isometric twitch contractions of rat gastrocnemius muscle before and after 10 s of 10-Hz stimulation were analyzed at seven different lengths to evaluate the length dependence of staircase potentiation. In the absence of caffeine, length dependence of Ca2+ sensitivity was observed, and the degree of potentiation after 10-Hz stimulation showed a linear decrease with increased length (DT = 1.47 - 0.05 ML, r2 = 0.95, where DT is developed tension). Length dependence of Ca2+ sensitivity was decreased by caffeine when caffeine was administered in amounts estimated to result in 0.5 and 0.75 mM concentrations. Furthermore, the negative slope of the relationship between staircase potentiation and muscle length was diminished at the lower caffeine dose, and the slope was not different from zero after the higher dose (DT = 1.53 - 0.009 ML, r2 = 0.43). Our study shows that length dependence of Ca2+ sensitivity in intact skeletal muscle is diminished by caffeine. Caffeine also suppressed the length dependence of staircase potentiation, suggesting that the mechanism of this length dependence may be closely related to the mechanism for length dependence of Ca2+ sensitivity.

Totally optimal decision rules

KAUST Repository

Amin, Talha

2017-11-22

Optimality of decision rules (patterns) can be measured in many ways. One of these is referred to as length. Length signifies the number of terms in a decision rule and is optimally minimized. Another, coverage represents the width of a rule’s applicability and generality. As such, it is desirable to maximize coverage. A totally optimal decision rule is a decision rule that has the minimum possible length and the maximum possible coverage. This paper presents a method for determining the presence of totally optimal decision rules for “complete” decision tables (representations of total functions in which different variables can have domains of differing values). Depending on the cardinalities of the domains, we can either guarantee for each tuple of values of the function that totally optimal rules exist for each row of the table (as in the case of total Boolean functions where the cardinalities are equal to 2) or, for each row, we can find a tuple of values of the function for which totally optimal rules do not exist for this row.

Totally optimal decision rules

KAUST Repository

Amin, Talha M.; Moshkov, Mikhail

2017-01-01

Optimality of decision rules (patterns) can be measured in many ways. One of these is referred to as length. Length signifies the number of terms in a decision rule and is optimally minimized. Another, coverage represents the width of a rule’s applicability and generality. As such, it is desirable to maximize coverage. A totally optimal decision rule is a decision rule that has the minimum possible length and the maximum possible coverage. This paper presents a method for determining the presence of totally optimal decision rules for “complete” decision tables (representations of total functions in which different variables can have domains of differing values). Depending on the cardinalities of the domains, we can either guarantee for each tuple of values of the function that totally optimal rules exist for each row of the table (as in the case of total Boolean functions where the cardinalities are equal to 2) or, for each row, we can find a tuple of values of the function for which totally optimal rules do not exist for this row.

Combinatorial discovery of new methanol-tolerant non-noble metal cathode electrocatalysts for direct methanol fuel cells.

Science.gov (United States)

Yu, Jong-Sung; Kim, Min-Sik; Kim, Jung Ho

2010-12-14

Combinatorial synthesis and screening were used to identify methanol-tolerant non-platinum cathode electrocatalysts for use in direct methanol fuel cells (DMFCs). Oxygen reduction consumes protons at the surface of DMFC cathode catalysts. In combinatorial screening, this pH change allows one to differentiate active catalysts using fluorescent acid-base indicators. Combinatorial libraries of carbon-supported catalyst compositions containing Ru, Mo, W, Sn, and Se were screened. Ternary and quaternary compositions containing Ru, Sn, Mo, Se were more active than the "standard" Alonso-Vante catalyst, Ru(3)Mo(0.08)Se(2), when tested in liquid-feed DMFCs. Physical characterization of the most active catalysts by powder X-ray diffraction, gas adsorption, and X-ray photoelectron spectroscopy revealed that the predominant crystalline phase was hexagonal close-packed (hcp) ruthenium, and showed a surface mostly covered with oxide. The best new catalyst, Ru(7.0)Sn(1.0)Se(1.0), was significantly more active than Ru(3)Se(2)Mo(0.08), even though the latter contained smaller particles.

Template-based combinatorial enumeration of virtual compound libraries for lipids.

Science.gov (United States)

Sud, Manish; Fahy, Eoin; Subramaniam, Shankar

2012-09-25

A variety of software packages are available for the combinatorial enumeration of virtual libraries for small molecules, starting from specifications of core scaffolds with attachments points and lists of R-groups as SMILES or SD files. Although SD files include atomic coordinates for core scaffolds and R-groups, it is not possible to control 2-dimensional (2D) layout of the enumerated structures generated for virtual compound libraries because different packages generate different 2D representations for the same structure. We have developed a software package called LipidMapsTools for the template-based combinatorial enumeration of virtual compound libraries for lipids. Virtual libraries are enumerated for the specified lipid abbreviations using matching lists of pre-defined templates and chain abbreviations, instead of core scaffolds and lists of R-groups provided by the user. 2D structures of the enumerated lipids are drawn in a specific and consistent fashion adhering to the framework for representing lipid structures proposed by the LIPID MAPS consortium. LipidMapsTools is lightweight, relatively fast and contains no external dependencies. It is an open source package and freely available under the terms of the modified BSD license.

Combinatorial One-Pot Synthesis of Poly-N-acetyllactosamine Oligosaccharides with Leloir-Glycosyltransferases

Czech Academy of Sciences Publication Activity Database

Rech, C.; Rosencrantz, R. R.; Křenek, Karel; Pelantová, Helena; Bojarová, Pavla; Roemer, Ch. E.; Hanisch, F.-G.; Křen, Vladimír; Elling, L.

2011-01-01

Roč. 353, č. 13 (2011), s. 2492-2500 ISSN 1615-4150 R&D Projects: GA MŠk OC09045 Institutional research plan: CEZ:AV0Z50200510 Keywords : combinatorial chemistry * biocatalysis * carbohydrates Subject RIV: CC - Organic Chemistry Impact factor: 6.048, year: 2011

A model-based combinatorial optimisation approach for energy-efficient processing of microalgae

NARCIS (Netherlands)

Slegers, P.M.; Koetzier, B.J.; Fasaei, F.; Wijffels, R.H.; Straten, van G.; Boxtel, van A.J.B.

2014-01-01

The analyses of algae biorefinery performance are commonly based on fixed performance data for each processing step. In this work, we demonstrate a model-based combinatorial approach to derive the design-specific upstream energy consumption and biodiesel yield in the production of biodiesel from

Global optimization of discrete truss topology design problems using a parallel cut-and-branch method

DEFF Research Database (Denmark)

Rasmussen, Marie-Louise Højlund; Stolpe, Mathias

2008-01-01

the physics, and the cuts (Combinatorial Benders’ and projected Chvátal–Gomory) come from an understanding of the particular mathematical structure of the reformulation. The impact of a stronger representation is investigated on several truss topology optimization problems in two and three dimensions.......The subject of this article is solving discrete truss topology optimization problems with local stress and displacement constraints to global optimum. We consider a formulation based on the Simultaneous ANalysis and Design (SAND) approach. This intrinsically non-convex problem is reformulated...

Novel Power Flow Problem Solutions Method’s Based on Genetic Algorithm Optimization for Banks Capacitor Compensation Using an Fuzzy Logic Rule Bases for Critical Nodal Detections

Directory of Open Access Journals (Sweden)

Nasri Abdelfatah

2011-01-01

Full Text Available The Reactive power flow’s is one of the most electrical distribution systems problem wich have great of interset of the electrical network researchers, it’s  cause’s active power transmission reduction, power losses decreasing, and  the drop voltage’s increase. In this research we described the efficiency of the FLC-GAO approach to solve the optimal power flow (OPF combinatorial problem. The proposed approach employ tow algorithms, Fuzzy logic controller (FLC algorithm for critical nodal detection and gentic algorithm  optimization (GAO algorithm for optimal seizing capacitor.GAO method is more efficient in combinatory problem solutions. The proposed approach has been examined and tested on the standard IEEE 57-bus the resulats show the power loss minimization denhancement, voltage profile, and stability improvement. The proposed approach results have been compared to those that reported in the literature recently. The results are promising and show the effectiveness and robustness of the proposed approach.

Optimization of stochastic discrete systems and control on complex networks computational networks

CERN Document Server

Lozovanu, Dmitrii

2014-01-01

This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors' new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book's final chapter is devoted to finite horizon stochastic con...

Combinatorial synthesis of oxazol-thiazole bis-heterocyclic compounds.

Science.gov (United States)

Murru, Siva; Nefzi, Adel

2014-01-13

A combinatorial library of novel oxazol-thiazole bis-heterocycles was synthesized in good to excellent overall yields with high purity using a solution and solid-phase parallel synthesis approach. Oxazole amino acids, prepared from serine methyl ester and amino acids via coupling and cyclodehydration, were treated with Fmoc-NCS and α-haloketones for the parallel synthesis of diverse bis-heterocycles. Fmoc-isothiocyanate is used as a traceless reagent for thiazole formation. Oxazole diversity can be achieved by using variety of amino acids, whereas thiazole diversity is produced with various haloketones.

Proceedings of the 8th Nordic Combinatorial Conference

DEFF Research Database (Denmark)

Geil, Olav; Andersen, Lars Døvling

The Nordic Combinatorial Conferences were initiated in 1981 by mathematicians from Stavanger. Held approximately every three years since then, the conferences have been able to sustain the interest from combinatorialists all over the Nordic countries. In 2004 the 8th conference is held in Aalborg......, Denmark. We are pleased that so many people have chosen to attend, and that lectures were offered from more participants than we had originally reserved time for. We asked two mathematicians to give special lectures and are happy that both accepted immediately. Andries Brouwer from the Technical...

Optimal Length of Follow-up for the Detection of Unsuccessful Pediatric Pyeloplasty: A Single-Center Experience

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Utsav K. Bansal

2017-06-01

Full Text Available ObjectivesTo assess the optimal length of follow-up for patients undergoing both open and minimally invasive pyeloplasties to ensure prompt detection of a recurrent obstruction. There are no standard guidelines on ideal follow-up and imaging post-pediatric pyeloplasty currently.MethodsA retrospective chart review identified 264 patients (<18 years old who underwent pyeloplasty for ureteropelvic junction obstruction between April 2002 and December 2014. Ultrasound was obtained every 3–4 months for the first year following pyeloplasty and thereafter at discretion of treating physician. Patient characteristics including symptoms and imaging were reviewed.ResultsOf the 264 patients, 72% were male with mean age of 51 months and follow-up of 26.8 months. Approximately 73% followed up to 3 years. Fourteen patients (5.3% had a recurrent obstruction. Among the failures, 85% were diagnosed and underwent successful redo pyeloplasty within 3 years. Six infants had a recurrence (43% of all unsuccessful surgeries and were diagnosed within 3 years of the initial surgery. Patients undergoing a minimally invasive procedure were less likely to be followed for more than 3 years compared to an open procedure (p < 0.001. Patients with severe hydronephrosis preoperatively were followed longer (p = 0.031. Age at surgery and type of surgical approach (p < 0.01 were significant predictors of length of follow-up in a negative binomial regression.ConclusionBased on the results, a minimum of 3 years of follow-up is necessary to detect the majority of recurrent obstructions. Those patients who have higher than average lengths of follow-up tend to be younger and/or underwent an open surgical approach.

Estimating meme fitness in adaptive memetic algorithms for combinatorial problems.

Science.gov (United States)

Smith, J E

2012-01-01

Among the most promising and active research areas in heuristic optimisation is the field of adaptive memetic algorithms (AMAs). These gain much of their reported robustness by adapting the probability with which each of a set of local improvement operators is applied, according to an estimate of their current value to the search process. This paper addresses the issue of how the current value should be estimated. Assuming the estimate occurs over several applications of a meme, we consider whether the extreme or mean improvements should be used, and whether this aggregation should be global, or local to some part of the solution space. To investigate these issues, we use the well-established COMA framework that coevolves the specification of a population of memes (representing different local search algorithms) alongside a population of candidate solutions to the problem at hand. Two very different memetic algorithms are considered: the first using adaptive operator pursuit to adjust the probabilities of applying a fixed set of memes, and a second which applies genetic operators to dynamically adapt and create memes and their functional definitions. For the latter, especially on combinatorial problems, credit assignment mechanisms based on historical records, or on notions of landscape locality, will have limited application, and it is necessary to estimate the value of a meme via some form of sampling. The results on a set of binary encoded combinatorial problems show that both methods are very effective, and that for some problems it is necessary to use thousands of variables in order to tease apart the differences between different reward schemes. However, for both memetic algorithms, a significant pattern emerges that reward based on mean improvement is better than that based on extreme improvement. This contradicts recent findings from adapting the parameters of operators involved in global evolutionary search. The results also show that local reward schemes

Asymmetric proteome equalization of the skeletal muscle proteome using a combinatorial hexapeptide library.

Directory of Open Access Journals (Sweden)

Jenny Rivers

Full Text Available Immobilized combinatorial peptide libraries have been advocated as a strategy for equalization of the dynamic range of a typical proteome. The technology has been applied predominantly to blood plasma and other biological fluids such as urine, but has not been used extensively to address the issue of dynamic range in tissue samples. Here, we have applied the combinatorial library approach to the equalization of a tissue where there is also a dramatic asymmetry in the range of abundances of proteins; namely, the soluble fraction of skeletal muscle. We have applied QconCAT and label-free methodology to the quantification of the proteins that bind to the beads as the loading is progressively increased. Although some equalization is achieved, and the most abundant proteins no longer dominate the proteome analysis, at high protein loadings a new asymmetry of protein expression is reached, consistent with the formation of complex assembles of heat shock proteins, cytoskeletal elements and other proteins on the beads. Loading at different ionic strength values leads to capture of different subpopulations of proteins, but does not completely eliminate the bias in protein accumulation. These assemblies may impair the broader utility of combinatorial library approaches to the equalization of tissue proteomes. However, the asymmetry in equalization is manifest at either low and high ionic strength values but manipulation of the solvent conditions may extend the capacity of the method.

A binary plasmid system for shuffling combinatorial antibody libraries.

OpenAIRE

Collet, T A; Roben, P; O'Kennedy, R; Barbas, C F; Burton, D R; Lerner, R A

1992-01-01

We have used a binary system of replicon-compatible plasmids to test the potential for promiscuous recombination of heavy and light chains within sets of human Fab fragments isolated from combinatorial antibody libraries. Antibody molecules showed a surprising amount of promiscuity in that a particular heavy chain could recombine with multiple light chains with retention of binding to a protein antigen. The degree to which a given heavy chain productively paired with any light chain to bind a...

The length of the male urethra

Directory of Open Access Journals (Sweden)

Tobias. S. Kohler

2008-08-01

Full Text Available PURPOSE: Catheter-based medical devices are an important component of the urologic armamentarium. To our knowledge, there is no population-based data regarding normal male urethral length. We evaluated the length of the urethra in men with normal genitourinary anatomy undergoing either Foley catheter removal or standard cystoscopy. MATERIALS AND METHODS: Male urethral length was obtained in 109 men. After study permission was obtained, the subject's penis was placed on a gentle stretch and the catheter was marked at the tip of the penis. The catheter was then removed and the distance from the mark to the beginning of the re-inflated balloon was measured. Alternatively, urethral length was measured at the time of cystoscopy, on removal of the cystoscope. Data on age, weight, and height was obtained in patients when possible. RESULTS: The mean urethral length was 22.3 cm with a standard deviation of 2.4 cm. Urethral length varied between 15 cm and 29 cm. No statistically significant correlation was found between urethral length and height, weight, body mass index (BMI, or age. CONCLUSIONS: Literature documenting the length of the normal male adult urethra is scarce. Our data adds to basic anatomic information of the male urethra and may be used to optimize genitourinary device design.

Middle-down hybrid chromatography/tandem mass spectrometry workflow for characterization of combinatorial post-translational modifications in histones.

Science.gov (United States)

Sidoli, Simone; Schwämmle, Veit; Ruminowicz, Chrystian; Hansen, Thomas A; Wu, Xudong; Helin, Kristian; Jensen, Ole N

2014-10-01

We present an integrated middle-down proteomics platform for sensitive mapping and quantification of coexisting PTMs in large polypeptides (5-7 kDa). We combined an RP trap column with subsequent weak cation exchange-hydrophilic interaction LC interfaced directly to high mass accuracy ESI MS/MS using electron transfer dissociation. This enabled automated and efficient separation and sequencing of hypermodified histone N-terminal tails for unambiguous localization of combinatorial PTMs. We present Histone Coder and IsoScale software to extract, filter, and analyze MS/MS data, including quantification of cofragmenting isobaric polypeptide species. We characterized histone tails derived from murine embryonic stem cells knockout in suppressor of zeste12 (Suz12(-/-) ) and quantified 256 combinatorial histone marks in histones H3, H4, and H2A. Furthermore, a total of 713 different combinatorial histone marks were identified in purified histone H3. We measured a seven-fold reduction of H3K27me2/me3 (where me2 and me3 are dimethylation and trimethylation, respectively) in Suz12(-) (/) (-) cells and detected significant changes of the relative abundance of 16 other single PTMs of histone H3 and other combinatorial marks. We conclude that the inactivation of Suz12 is associated with changes in the abundance of not only H3K27 methylation but also multiple other PTMs in histone H3 tails. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The PBIL algorithm applied to a nuclear reactor design optimization

Energy Technology Data Exchange (ETDEWEB)

Machado, Marcelo D.; Medeiros, Jose A.C.C.; Lima, Alan M.M. de; Schirru, Roberto [Instituto Alberto Luiz Coimbra de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ-RJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear. Lab. de Monitoracao de Processos]. E-mails: marcelo@lmp.ufrj.br; canedo@lmp.ufrj.br; alan@lmp.ufrj.br; schirru@lmp.ufrj.br

2007-07-01

The Population-Based Incremental Learning (PBIL) algorithm is a method that combines the mechanism of genetic algorithm with the simple competitive learning, creating an important tool to be used in the optimization of numeric functions and combinatory problems. PBIL works with a set of solutions to the problems, called population, whose objective is create a probability vector, containing real values in each position, that when used in a decoding procedure gives subjects that present the best solutions for the function to be optimized. In this work a new form of learning for algorithm PBIL is developed, having aimed at to reduce the necessary time for the optimization process. This new algorithm will be used in the nuclear reactor design optimization. The optimization problem consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the average peak-factor in a 3-enrichment zone reactor, considering some restrictions. In this optimization is used the computational code HAMMER, and the results compared with other methods of optimization by artificial intelligence. (author)

The PBIL algorithm applied to a nuclear reactor design optimization

International Nuclear Information System (INIS)

Machado, Marcelo D.; Medeiros, Jose A.C.C.; Lima, Alan M.M. de; Schirru, Roberto

2007-01-01

The Population-Based Incremental Learning (PBIL) algorithm is a method that combines the mechanism of genetic algorithm with the simple competitive learning, creating an important tool to be used in the optimization of numeric functions and combinatory problems. PBIL works with a set of solutions to the problems, called population, whose objective is create a probability vector, containing real values in each position, that when used in a decoding procedure gives subjects that present the best solutions for the function to be optimized. In this work a new form of learning for algorithm PBIL is developed, having aimed at to reduce the necessary time for the optimization process. This new algorithm will be used in the nuclear reactor design optimization. The optimization problem consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the average peak-factor in a 3-enrichment zone reactor, considering some restrictions. In this optimization is used the computational code HAMMER, and the results compared with other methods of optimization by artificial intelligence. (author)

Combinatorial identities for Stirling numbers the unpublished notes of H. W. Gould

CERN Document Server

Quaintance, Jocelyn

2016-01-01

This book is a unique work which provides an in-depth exploration into the mathematical expertise, philosophy, and knowledge of H W Gould. It is written in a style that is accessible to the reader with basic mathematical knowledge, and yet contains material that will be of interest to the specialist in enumerative combinatorics. This book begins with exposition on the combinatorial and algebraic techniques that Professor Gould uses for proving binomial identities. These techniques are then applied to develop formulas which relate Stirling numbers of the second kind to Stirling numbers of the first kind. Professor Gould's techniques also provide connections between both types of Stirling numbers and Bernoulli numbers. Professor Gould believes his research success comes from his intuition on how to discover combinatorial identities.This book will appeal to a wide audience and may be used either as lecture notes for a beginning graduate level combinatorics class, or as a research supplement for the specialist in...

Approximability of optimization problems through adiabatic quantum computation

CERN Document Server

Cruz-Santos, William

2014-01-01

The adiabatic quantum computation (AQC) is based on the adiabatic theorem to approximate solutions of the Schrödinger equation. The design of an AQC algorithm involves the construction of a Hamiltonian that describes the behavior of the quantum system. This Hamiltonian is expressed as a linear interpolation of an initial Hamiltonian whose ground state is easy to compute, and a final Hamiltonian whose ground state corresponds to the solution of a given combinatorial optimization problem. The adiabatic theorem asserts that if the time evolution of a quantum system described by a Hamiltonian is l

Sensitivity analysis and design optimization through automatic differentiation

International Nuclear Information System (INIS)

Hovland, Paul D; Norris, Boyana; Strout, Michelle Mills; Bhowmick, Sanjukta; Utke, Jean

2005-01-01

Automatic differentiation is a technique for transforming a program or subprogram that computes a function, including arbitrarily complex simulation codes, into one that computes the derivatives of that function. We describe the implementation and application of automatic differentiation tools. We highlight recent advances in the combinatorial algorithms and compiler technology that underlie successful implementation of automatic differentiation tools. We discuss applications of automatic differentiation in design optimization and sensitivity analysis. We also describe ongoing research in the design of language-independent source transformation infrastructures for automatic differentiation algorithms

Optimization of Kα bursts for photon energies between 1.7 and 7 keV produced by femtosecond-laser-produced plasmas of different scale length

International Nuclear Information System (INIS)

Ziener, Ch.; Uschmann, I.; Stobrawa, G.; Reich, Ch.; Gibbon, P.; Feurer, T.; Morak, A.; Duesterer, S.; Schwoerer, H.; Foerster, E.; Sauerbrey, R.

2002-01-01

The conversion efficiency of a 90 fs high-power laser pulse focused onto a solid target into x-ray Kα line emission was measured. By using three different elements as target material (Si, Ti, and Co), interesting candidates for fast x-ray diffraction applications were selected. The Kα output was measured with toroidally bent crystal monochromators combined with a GaAsP Schottky diode. Optimization was performed for different laser intensities as well as for different density scale lengths of a preformed plasma. These different scale lengths were realized by prepulses of different intensities and delay times with respect to the main pulse. Whereas the Kα yield varied by a factor of 1.8 for different laser intensities, the variation of the density scale length could provide a gain factor up to 4.6 for the Kα output

Performance analysis of demodulation with diversity -- A combinatorial approach I: Symmetric function theoretical methods

OpenAIRE

Jean-Louis Dornstetter; Daniel Krob; Jean-Yves Thibon; Ekaterina A. Vassilieva

2002-01-01

This paper is devoted to the presentation of a combinatorial approach, based on the theory of symmetric functions, for analyzing the performance of a family of demodulation methods used in mobile telecommunications.

Optimization of personalized therapies for anticancer treatment.

Science.gov (United States)

Vazquez, Alexei

2013-04-12

As today, there are hundreds of targeted therapies for the treatment of cancer, many of which have companion biomarkers that are in use to inform treatment decisions. If we would consider this whole arsenal of targeted therapies as a treatment option for every patient, very soon we will reach a scenario where each patient is positive for several markers suggesting their treatment with several targeted therapies. Given the documented side effects of anticancer drugs, it is clear that such a strategy is unfeasible. Here, we propose a strategy that optimizes the design of combinatorial therapies to achieve the best response rates with the minimal toxicity. In this methodology markers are assigned to drugs such that we achieve a high overall response rate while using personalized combinations of minimal size. We tested this methodology in an in silico cancer patient cohort, constructed from in vitro data for 714 cell lines and 138 drugs reported by the Sanger Institute. Our analysis indicates that, even in the context of personalized medicine, combinations of three or more drugs are required to achieve high response rates. Furthermore, patient-to-patient variations in pharmacokinetics have a significant impact in the overall response rate. A 10 fold increase in the pharmacokinetics variations resulted in a significant drop the overall response rate. The design of optimal combinatorial therapy for anticancer treatment requires a transition from the one-drug/one-biomarker approach to global strategies that simultaneously assign makers to a catalog of drugs. The methodology reported here provides a framework to achieve this transition.

Exploiting Elementary Landscapes for TSP, Vehicle Routing and Scheduling

Science.gov (United States)

2015-09-03

similar mathematical foundation to enable gradient descent methods for discrete combinatorial optimization problems. We are also generalizing our prior...research has exploited statistical and mathematical properties of elementary landscapes to develop new gradient methods for combinatorial optimization... mathematically methods to more automatically identify elementary landscapes. If a combinatorial optimization problem is a superposition of elemen

Intrinsic information carriers in combinatorial dynamical systems

Science.gov (United States)

Harmer, Russ; Danos, Vincent; Feret, Jérôme; Krivine, Jean; Fontana, Walter

2010-09-01

Many proteins are composed of structural and chemical features—"sites" for short—characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the ambient protein. Independence quickly generates a startling combinatorial complexity that shapes most biological networks, such as mammalian signaling systems, and effectively prevents their study in terms of kinetic equations—unless the complexity is radically trimmed. Yet, if combinatorial complexity is key to the system's behavior, eliminating it will prevent, not facilitate, understanding. A more adequate representation of a combinatorial system is provided by a graph-based framework of rewrite rules where each rule specifies only the information that an interaction mechanism depends on. Unlike reactions, which deal with molecular species, rules deal with patterns, i.e., multisets of molecular species. Although the stochastic dynamics induced by a collection of rules on a mixture of molecules can be simulated, it appears useful to capture the system's average or deterministic behavior by means of differential equations. However, expansion of the rules into kinetic equations at the level of molecular species is not only impractical, but conceptually indefensible. If rules describe bona fide patterns of interaction, molecular species are unlikely to constitute appropriate units of dynamics. Rather, we must seek aggregate variables reflective of the causal structure laid down by the rules. We call these variables "fragments" and the process of identifying them "fragmentation." Ideally, fragments are aspects of the system's microscopic population that the set of rules can actually distinguish on average; in practice, it may only be feasible to identify an approximation to this. Most importantly, fragments are

Intrinsic information carriers in combinatorial dynamical systems.

Science.gov (United States)

Harmer, Russ; Danos, Vincent; Feret, Jérôme; Krivine, Jean; Fontana, Walter

2010-09-01

Many proteins are composed of structural and chemical features--"sites" for short--characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the ambient protein. Independence quickly generates a startling combinatorial complexity that shapes most biological networks, such as mammalian signaling systems, and effectively prevents their study in terms of kinetic equations-unless the complexity is radically trimmed. Yet, if combinatorial complexity is key to the system's behavior, eliminating it will prevent, not facilitate, understanding. A more adequate representation of a combinatorial system is provided by a graph-based framework of rewrite rules where each rule specifies only the information that an interaction mechanism depends on. Unlike reactions, which deal with molecular species, rules deal with patterns, i.e., multisets of molecular species. Although the stochastic dynamics induced by a collection of rules on a mixture of molecules can be simulated, it appears useful to capture the system's average or deterministic behavior by means of differential equations. However, expansion of the rules into kinetic equations at the level of molecular species is not only impractical, but conceptually indefensible. If rules describe bona fide patterns of interaction, molecular species are unlikely to constitute appropriate units of dynamics. Rather, we must seek aggregate variables reflective of the causal structure laid down by the rules. We call these variables "fragments" and the process of identifying them "fragmentation." Ideally, fragments are aspects of the system's microscopic population that the set of rules can actually distinguish on average; in practice, it may only be feasible to identify an approximation to this. Most importantly, fragments are

Synthesis of new water-soluble metal-binding polymers: Combinatorial chemistry approach. 1997 mid-year progress report

International Nuclear Information System (INIS)

Smith, B.F.

1997-01-01

'The first objective of this research is to develop rapid discovery and optimization approaches to new water-soluble chelating polymers. A byproduct of the development approach will be the new, selective, and efficient metal-binding agents. The second objective is to evaluate the concept of using water and organic soluble polymers as new solid supports for combinatorial synthesis. The technology under development, Polymer Filtration (PF), is a technique to selectively remove or recover hazardous and valuable metal ions and radionuclides from various dilute aqueous streams. Not only can this technology be used to remediate contaminated soils and solid surfaces and treat aqueous wastes, it can also be incorporated into facilities as a pollution prevention and waste minimization technology. Polymer Filtration uses water-soluble metal-binding polymers to sequester metal ions in dilute solution. The water-soluble polymers have a sufficiently large molecular size that they can be separated and concentrated using commercial ultrafiltration technology. Water, small organic molecules, and unbound metals pass freely through the ultrafiltration membrane while concentrating the metal-binding polymer. The polymers can then be reused by changing the solution conditions to release the metal ions. The metal-ions are recovered in concentrated form for recycle or disposal using a diafiltration process. The water-soluble polymer can be recycled for further aqueous-stream processing. To advance Polymer Filtration technology to the selectivity levels required for DOE needs. fixture directions in Polymer Filtration must include rapid development, testing, and characterization of new metal-binding polymers. The development of new chelating molecules can be equated to the process of new drugs or new materials discovery. Thus, the authors want to build upon and adapt the combinatorial chemistry approaches developed for rapid molecule generation for the drug industry to the rapid

Concentration and length dependence of DNA looping in transcriptional regulation.

Directory of Open Access Journals (Sweden)

Lin Han

2009-05-01

Full Text Available In many cases, transcriptional regulation involves the binding of transcription factors at sites on the DNA that are not immediately adjacent to the promoter of interest. This action at a distance is often mediated by the formation of DNA loops: Binding at two or more sites on the DNA results in the formation of a loop, which can bring the transcription factor into the immediate neighborhood of the relevant promoter. These processes are important in settings ranging from the historic bacterial examples (bacterial metabolism and the lytic-lysogeny decision in bacteriophage, to the modern concept of gene regulation to regulatory processes central to pattern formation during development of multicellular organisms. Though there have been a variety of insights into the combinatorial aspects of transcriptional control, the mechanism of DNA looping as an agent of combinatorial control in both prokaryotes and eukaryotes remains unclear. We use single-molecule techniques to dissect DNA looping in the lac operon. In particular, we measure the propensity for DNA looping by the Lac repressor as a function of the concentration of repressor protein and as a function of the distance between repressor binding sites. As with earlier single-molecule studies, we find (at least two distinct looped states and demonstrate that the presence of these two states depends both upon the concentration of repressor protein and the distance between the two repressor binding sites. We find that loops form even at interoperator spacings considerably shorter than the DNA persistence length, without the intervention of any other proteins to prebend the DNA. The concentration measurements also permit us to use a simple statistical mechanical model of DNA loop formation to determine the free energy of DNA looping, or equivalently, the for looping.

Combinatorial nanomedicines for colon cancer therapy.

Science.gov (United States)

Anitha, A; Maya, S; Sivaram, Amal J; Mony, U; Jayakumar, R

2016-01-01

Colon cancer is one of the major causes of cancer deaths worldwide. Even after surgical resection and aggressive chemotherapy, 50% of colorectal carcinoma patients develop recurrent disease. Thus, the rationale of developing new therapeutic approaches to improve the current chemotherapeutic regimen would be highly recommended. There are reports on the effectiveness of combination chemotherapy in colon cancer and it has been practiced in clinics for long time. These approaches are associated with toxic side effects. Later, the drug delivery research had shown the potential of nanoencapsulation techniques and active targeting as an effective method to improve the effectiveness of chemotherapy with less toxicity. This current focus article provides a brief analysis of the ongoing research in the colon cancer area using the combinatorial nanomedicines and its outcome. © 2015 Wiley Periodicals, Inc.

A combinatorial proof of Postnikov's identity and a generalized enumeration of labeled trees

OpenAIRE

Seo, Seunghyun

2004-01-01

In this paper, we give a simple combinatorial explanation of a formula of A. Postnikov relating bicolored rooted trees to bicolored binary trees. We also present generalized formulas for the number of labeled k-ary trees, rooted labeled trees, and labeled plane trees.

Parameter Estimation of Permanent Magnet Synchronous Motor Using Orthogonal Projection and Recursive Least Squares Combinatorial Algorithm

Directory of Open Access Journals (Sweden)

Iman Yousefi

2015-01-01

Full Text Available This paper presents parameter estimation of Permanent Magnet Synchronous Motor (PMSM using a combinatorial algorithm. Nonlinear fourth-order space state model of PMSM is selected. This model is rewritten to the linear regression form without linearization. Noise is imposed to the system in order to provide a real condition, and then combinatorial Orthogonal Projection Algorithm and Recursive Least Squares (OPA&RLS method is applied in the linear regression form to the system. Results of this method are compared to the Orthogonal Projection Algorithm (OPA and Recursive Least Squares (RLS methods to validate the feasibility of the proposed method. Simulation results validate the efficacy of the proposed algorithm.

Performance analysis of demodulation with diversity -- A combinatorial approach I: Symmetric function theoretical methods

Directory of Open Access Journals (Sweden)

Jean-Louis Dornstetter

2002-12-01

Full Text Available This paper is devoted to the presentation of a combinatorial approach, based on the theory of symmetric functions, for analyzing the performance of a family of demodulation methods used in mobile telecommunications.

ACOustic: A Nature-Inspired Exploration Indicator for Ant Colony Optimization

Directory of Open Access Journals (Sweden)

Rafid Sagban

2015-01-01

Full Text Available A statistical machine learning indicator, ACOustic, is proposed to evaluate the exploration behavior in the iterations of ant colony optimization algorithms. This idea is inspired by the behavior of some parasites in their mimicry to the queens’ acoustics of their ant hosts. The parasites’ reaction results from their ability to indicate the state of penetration. The proposed indicator solves the problem of robustness that results from the difference of magnitudes in the distance’s matrix, especially when combinatorial optimization problems with rugged fitness landscape are applied. The performance of the proposed indicator is evaluated against the existing indicators in six variants of ant colony optimization algorithms. Instances for travelling salesman problem and quadratic assignment problem are used in the experimental evaluation. The analytical results showed that the proposed indicator is more informative and more robust.

Optimization of the core configuration design using a hybrid artificial intelligence algorithm for research reactors

International Nuclear Information System (INIS)

Hedayat, Afshin; Davilu, Hadi; Barfrosh, Ahmad Abdollahzadeh; Sepanloo, Kamran

2009-01-01

To successfully carry out material irradiation experiments and radioisotope productions, a high thermal neutron flux at irradiation box over a desired life time of a core configuration is needed. On the other hand, reactor safety and operational constraints must be preserved during core configuration selection. Two main objectives and two safety and operational constraints are suggested to optimize reactor core configuration design. Suggested parameters and conditions are considered as two separate fitness functions composed of two main objectives and two penalty functions. This is a constrained and combinatorial type of a multi-objective optimization problem. In this paper, a fast and effective hybrid artificial intelligence algorithm is introduced and developed to reach a Pareto optimal set. The hybrid algorithm is composed of a fast and elitist multi-objective genetic algorithm (GA) and a fast fitness function evaluating system based on the cascade feed forward artificial neural networks (ANNs). A specific GA representation of core configuration and also special GA operators are introduced and used to overcome the combinatorial constraints of this optimization problem. A software package (Core Pattern Calculator 1) is developed to prepare and reform required data for ANNs training and also to revise the optimization results. Some practical test parameters and conditions are suggested to adjust main parameters of the hybrid algorithm. Results show that introduced ANNs can be trained and estimate selected core parameters of a research reactor very quickly. It improves effectively optimization process. Final optimization results show that a uniform and dense diversity of Pareto fronts are gained over a wide range of fitness function values. To take a more careful selection of Pareto optimal solutions, a revision system is introduced and used. The revision of gained Pareto optimal set is performed by using developed software package. Also some secondary operational

Optimization of the core configuration design using a hybrid artificial intelligence algorithm for research reactors

Energy Technology Data Exchange (ETDEWEB)

Hedayat, Afshin, E-mail: ahedayat@aut.ac.i [Department of Nuclear Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, P.O. Box 15875-4413, Tehran (Iran, Islamic Republic of); Reactor Research and Development School, Nuclear Science and Technology Research Institute (NSTRI), End of North Karegar Street, P.O. Box 14395-836, Tehran (Iran, Islamic Republic of); Davilu, Hadi [Department of Nuclear Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, P.O. Box 15875-4413, Tehran (Iran, Islamic Republic of); Barfrosh, Ahmad Abdollahzadeh [Department of Computer Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, P.O. Box 15875-4413, Tehran (Iran, Islamic Republic of); Sepanloo, Kamran [Reactor Research and Development School, Nuclear Science and Technology Research Institute (NSTRI), End of North Karegar Street, P.O. Box 14395-836, Tehran (Iran, Islamic Republic of)

2009-12-15

To successfully carry out material irradiation experiments and radioisotope productions, a high thermal neutron flux at irradiation box over a desired life time of a core configuration is needed. On the other hand, reactor safety and operational constraints must be preserved during core configuration selection. Two main objectives and two safety and operational constraints are suggested to optimize reactor core configuration design. Suggested parameters and conditions are considered as two separate fitness functions composed of two main objectives and two penalty functions. This is a constrained and combinatorial type of a multi-objective optimization problem. In this paper, a fast and effective hybrid artificial intelligence algorithm is introduced and developed to reach a Pareto optimal set. The hybrid algorithm is composed of a fast and elitist multi-objective genetic algorithm (GA) and a fast fitness function evaluating system based on the cascade feed forward artificial neural networks (ANNs). A specific GA representation of core configuration and also special GA operators are introduced and used to overcome the combinatorial constraints of this optimization problem. A software package (Core Pattern Calculator 1) is developed to prepare and reform required data for ANNs training and also to revise the optimization results. Some practical test parameters and conditions are suggested to adjust main parameters of the hybrid algorithm. Results show that introduced ANNs can be trained and estimate selected core parameters of a research reactor very quickly. It improves effectively optimization process. Final optimization results show that a uniform and dense diversity of Pareto fronts are gained over a wide range of fitness function values. To take a more careful selection of Pareto optimal solutions, a revision system is introduced and used. The revision of gained Pareto optimal set is performed by using developed software package. Also some secondary operational

Optimization of an individual re-identification modeling process using biometric features

Energy Technology Data Exchange (ETDEWEB)

Heredia-Langner, Alejandro; Amidan, Brett G.; Matzner, Shari; Jarman, Kristin H.

2014-09-24

We present results from the optimization of a re-identification process using two sets of biometric data obtained from the Civilian American and European Surface Anthropometry Resource Project (CAESAR) database. The datasets contain real measurements of features for 2378 individuals in a standing (43 features) and seated (16 features) position. A genetic algorithm (GA) was used to search a large combinatorial space where different features are available between the probe (seated) and gallery (standing) datasets. Results show that optimized model predictions obtained using less than half of the 43 gallery features and data from roughly 16% of the individuals available produce better re-identification rates than two other approaches that use all the information available.

Application of Tabu Search Algorithm in Job Shop Scheduling

Directory of Open Access Journals (Sweden)

Betrianis Betrianis

2010-10-01

Full Text Available Tabu Search is one of local search methods which is used to solve the combinatorial optimization problem. This method aimed is to make the searching process of the best solution in a complex combinatorial optimization problem(np hard, ex : job shop scheduling problem, became more effective, in a less computational time but with no guarantee to optimum solution.In this paper, tabu search is used to solve the job shop scheduling problem consists of 3 (three cases, which is ordering package of September, October and November with objective of minimizing makespan (Cmax. For each ordering package, there is a combination for initial solution and tabu list length. These result then  compared with 4 (four other methods using basic dispatching rules such as Shortest Processing Time (SPT, Earliest Due Date (EDD, Most Work Remaining (MWKR dan First Come First Served (FCFS. Scheduling used Tabu Search Algorithm is sensitive for variables changes and gives makespan shorter than scheduling used by other four methods.

Correcting underestimation of optimal fracture length by modeling proppant conductivity variations in hydraulically fractured gas/condensate reservoirs

Energy Technology Data Exchange (ETDEWEB)

Akram, A.H.; Samad, A. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Schlumberger, Houston, TX (United States)

2006-07-01

A study was conducted in which a newly developed numerical simulator was used to forecast the productivity of a hydraulically fractured well in a retrograde gas-condensate sandstone reservoir. The effect of condensate dropout was modeled in both the reservoir and the proppant pack. The type of proppant and the stress applied to it are among the factors that determine proppant conductivity in a single-phase flow. Other factors include the high velocity of gas and the presence of liquid in the proppant pack. It was concluded that apparent proppant permeability in a gas condensate reservoir varies along the length of the hydraulic fracture and depends on the distance from the wellbore. It will increase towards the tip of the fracture where liquid ratio and velocity are lower. Apparent proppant permeability also changes with time. Forecasting is most accurate when these conditions are considered in the simulation. There are 2 problems associated with the use of a constant proppant permeability in a gas condensate reservoir. The first relates to the fact that it is impossible to obtain a correct single number that will mimic the drawdown of the real fracture at a particular rate without going through the process of determining the proppant permeability profile in a numerical simulator. The second problem relates to the fact that constant proppant permeability yields an optimal fracture length that is too short. Analytical modeling does not account for these complexities. It was determined that the only way to accurately simulate the behaviour of a hydraulic fracture in a high rate well, is by advanced numerical modeling that considers varying apparent proppant permeability in terms of time and distance along the fracture length. 10 refs., 2 tabs., 16 figs., 1 appendix.

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

Science.gov (United States)

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

2016-12-01

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

A Review On Job Shop Scheduling Using Non-Conventional Optimization Algorithm

OpenAIRE

K.Mallikarjuna; Venkatesh.G

2014-01-01

A great deal of research has been focused on solving job shop scheduling problem (∫J), over the last four decades, resulting in a wide variety of approaches. Recently much effort has been concentrated on hybrid methods to solve ∫J, as a single technique cannot solve this stubborn problem. As a result much effort has recently been concentrated on techniques that lead to combinatorial optimization methods and a meta-strategy which guides the search out of local optima. In this p...

ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization

DEFF Research Database (Denmark)

Pappalardo, F.; Halling-Brown, M. D.; Rapin, Nicolas

2009-01-01

conceptual models of the immune system, models of antigen processing and presentation, system-level models of the immune system, Grid computing, and database technology to facilitate discovery, formulation and optimization of vaccines. ImmunoGrid modules share common conceptual models and ontologies......Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines...

Correspondence optimization in 2D standardized carotid wall thickness map by description length minimization: A tool for increasing reproducibility of 3D ultrasound-based measurements.

Science.gov (United States)

Chen, Yimin; Chiu, Bernard

2016-12-01

The previously described 2D standardized vessel-wall-plus-plaque thickness (VWT) maps constructed from 3D ultrasound vessel wall measurements using an arc-length (AL) scaling approach adjusted the geometric variability of carotid arteries and has allowed for the comparisons of VWT distributions in longitudinal and cross-sectional studies. However, this mapping technique did not optimize point correspondence of the carotid arteries investigated. The potential misalignment may lead to errors in point-wise VWT comparisons. In this paper, we developed and validated an algorithm based on steepest description length (DL) descent to optimize the point correspondence implied by the 2D VWT maps. The previously described AL approach was applied to obtain initial 2D maps for a group of carotid arteries. The 2D maps were reparameterized based on an iterative steepest DL descent approach, which consists of the following two steps. First, landmarks established by resampling the 2D maps were aligned using the Procrustes algorithm. Then, the gradient of the DL with respect to horizontal and vertical reparameterizations of each landmark on the 2D maps was computed, and the 2D maps were subsequently deformed in the direction of the steepest descent of DL. These two steps were repeated until convergence. The quality of the correspondence was evaluated in a phantom study and an in vivo study involving ten carotid arteries enrolled in a 3D ultrasound interscan variability study. The correspondence quality was evaluated in terms of the compactness and generalization ability of the statistical shape model built based on the established point correspondence in both studies. In the in vivo study, the effect of the proposed algorithm on interscan variability of VWT measurements was evaluated by comparing the percentage of landmarks with statistically significant VWT-change before and after point correspondence optimization. The statistical shape model constructed with optimized

A combinatorial method for the vanishing of the Poisson brackets of an integrable Lotka-Volterra system

International Nuclear Information System (INIS)

Itoh, Yoshiaki

2009-01-01

The combinatorial method is useful to obtain conserved quantities for some nonlinear integrable systems, as an alternative to the Lax representation method. Here we extend the combinatorial method and introduce an elementary geometry to show the vanishing of the Poisson brackets of the Hamiltonian structure for a Lotka-Volterra system of competing species. We associate a set of points on a circle with a set of species of the Lotka-Volterra system, where the dominance relations between points are given by the dominance relations between the species. We associate each term of the conserved quantities with a subset of points on the circle, which simplifies to show the vanishing of the Poisson brackets

Quantum computation and swarm intelligence applied in the optimization of identification of accidents in a PWR nuclear power plant

International Nuclear Information System (INIS)

Nicolau, Andressa; Schirru, Roberto; Medeiros, Jose A.C.C.

2009-01-01

This work presents the results of a performance evaluation study of the quantum based algorithms, QEA (Quantum Inspired Evolutionary Algorithm) and QSE (Quantum Swarm Evolutionary), when applied to the transient identification optimization problem of a nuclear power station operating at 100% of full power. For the sake of evaluation of the algorithms 3 benchmark functions were used. When compared to other similar optimization methods QEA showed that it can be an efficient optimization tool, not only for combinatorial problems but also for numerical problems, particularly for complex problems as the identification of transients in a nuclear power station. (author)

Rapid mapping of protein functional epitopes by combinatorial alanine scanning

OpenAIRE

Weiss, GA; Watanabe, CK; Zhong, A; Goddard, A; Sidhu, SS

2000-01-01

A combinatorial alanine-scanning strategy was used to determine simultaneously the functional contributions of 19 side chains buried at the interface between human growth hormone and the extracellular domain of its receptor. A phage-displayed protein library was constructed in which the 19 side chains were preferentially allowed to vary only as the wild type or alanine. The library pool was subjected to binding selections to isolate functional clones, and DNA sequencing was used to determine ...

Combinatorial investigation of Pt-Ru-Sn alloys as an anode electrocatalysts for direct alcohol fuel cells

Energy Technology Data Exchange (ETDEWEB)

Chu, Young Hwan [Department of New Energy.Resource Engineering, College of Science and Engineering, Sangji University, 124, Sangjidae-gil, Wonju-si, Gangwon-Do 220-702 (Korea); Shul, Yong Gun [Department of Chemical and Biomolecular Engineering, Yonsei University, 134, Shinchon-Dong, Seodaemun-Gu, Seoul 120-749 (Korea)

2010-10-15

Low-temperature direct alcohol fuel cells fed with different kinds of alcohol (methanol, ethanol and 2-propanol) have been investigated by employing ternary electrocatalysts (Pt-Ru-Sn) as anode catalysts. Combinatorial chemistry has been applied to screen the 66-PtRuSn-anode arrays at the same time to reduce cost, time, and effort when we select the optimum composition of electrocatalysts for DAFCs (Direct Alcohol Fuel Cells). PtRuSn (80:20:0) showed the lowest onset potential for methanol electro-oxidation, PtRuSn (50:0:50) for ethanol, and PtRuSn (20:70:10) for 2-propanol in CV results respectively, and single cell performance test indicated that Ru is more suitable for direct methanol fuel cell system, Sn for direct ethanol fuel cell system, and 2-propanol could be applied as fuel with low platinum composition anode electrocatalyst. The single cell performance results and electrochemical results (CV) were well matched with the combinatorial electrochemical results. As a result, we could verify the availability of combinatorial chemistry by comparing the results of each extreme electrocatalysts compositions as follows: PtRuSn (80:20:0) for methanol, PtRuSn (50:0:50) for ethanol and PtRuSn (20:70:10) for 2-propanol. (author)

Diagnostic value of newborn foot length to predict gestational age

Directory of Open Access Journals (Sweden)

Mutia Farah Fawziah

2017-08-01

Full Text Available Background  Identification of gestational age, especially within 48 hours of birth, is crucial for newborns, as the earlier preterm status is detected, the earlier the child can receive optimal management. Newborn foot length is an anthropometric measurement which is easy to perform, inexpensive, and potentially efficient for predicting gestational age. Objective  To analyze the diagnostic value of newborn foot length in predicting gestational age. Methods  This diagnostic study was performed between October 2016 and February 2017 in the High Care Unit of Neonates at Dr. Moewardi General Hospital, Surakarta. A total of 152 newborns were consecutively selected and underwent right foot length measurements before 96 hours of age. The correlation between newborn foot length to classify as full term and gestational age was analyzed with Spearman’s correlation test because of non-normal data distribution. The cut-off point of newborn foot length was calculated by receiver operating characteristic (ROC curve and diagnostic values of newborn foot length were analyzed by 2 x 2 table with SPSS 21.0 software. Results There were no significant differences between male and female newborns in terms of gestational age, birth weight, choronological age, and newborn foot length (P>0.05. Newborn foot length and gestational age had a significant correlation (r=0.53; P=0.000. The optimal cut-off newborn foot length to predict full term status was 7.1 cm. Newborn foot length below 7.1 cm had sensitivity 75%, specificity 98%, positive predictive value 94.3%, negative predictive value 90.6%, positive likelihood ratio 40.5, negative likelihood ratio 0.25, and post-test probability 94.29%, to predict preterm status in newborns. Conclusion  Newborn foot length can be used to predict gestational age, especially for the purpose of differentiating between preterm and full term newborns.

Novel modeling of combinatorial miRNA targeting identifies SNP with potential role in bone density.

Directory of Open Access Journals (Sweden)

Claudia Coronnello

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

A stochastic discrete optimization model for designing container terminal facilities

Science.gov (United States)

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

2017-11-01

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