New approximations for minimum-weighted dominating sets and minimum-weighted connected dominating sets on unit disk graphs

Given a node-weighted graph, the minimum-weighted dominating set (MWDS) problem is to find a minimum-weighted vertex subset such that, for any vertex, it is contained in this subset or it has a neighbor contained in this set. And the minimum-weighted connected dominating set (MWCDS) problem is to find a MWDS such that the graph induced by this subset is connected. In this paper, we study these two problems on a unit disk graph. A (4 +ε)-approximation algorithm for an MWDS based on a dynamic programming algorithm for a Min-Weight Chromatic Disk Cover is presented. Meanwhile, we also propose a (1 +ε)-approximation algorithm for the connecting part by showing a polynomial-time approximation scheme for a Node-Weighted Steiner Tree problem when the given terminal set is c-local and thus obtain a (5 +ε)-approximation algorithm for an MWCDS.     

A dual K-Na selective Prussian blue nanotubes sensor

A strategy for dual sensing of Na⁺ and K⁺ ions using Prussian blue nanotubes via selective inter/deintercalation of K⁺ ion and competitive inhibition by Na⁺ ion, is reported. The analytical signal is derived from the cyclic voltammetry cathodic peak position E_pc of Prussian blue nanotubes. Na⁺ and K⁺ levels in a sample solution can be determined conveniently using one Prussian blue nanotubes sensor. In addition, this versatile method can be applied for the analysis of single type of either Na⁺ or K⁺ ions. The dual-ion sensor response towards Na⁺ and K⁺ can be described using a model based on the competitive inhibition effects of Na⁺ on K⁺ inter/deintercalation in Prussian blue nanotubes. Successful application of the Prussian blue nanotubes sensor for Na⁺ and K⁺ determination is demonstrated in artificial saliva.     

Performance evaluation for a transportation system in stochastic case

In a single-commodity multistate flow network, the arc capacity is stochastic and thus the system capacity (i.e. the maximum flow from the source to the sink) is not a fixed number. This paper constructs a multicommodity multistate flow network with weighted capacity allocation to model a transportation system. Each arc with cost attribute has several possible capacities. The capacity weight, the consumed amount of arc capacity by per commodity, varies with the arcs and types of commodity. We define the system capacity as a demand vector d if the system fulfills at most d. The addressed problem in this work is to measure the service quality of a transportation system. We propose a performance index, the probability that the upper bound of the system capacity equals a demand vector d subject to the budget constraint. A simple algorithm based on minimal cuts is presented to generate all (d,B)-MC that are the maximal capacity vectors meeting exactly the demand d under the budget B. The proposed performance index can be subsequently evaluated in terms of such (d,B)-MC.     

Embedding hamiltonian paths in hypercubes with a required vertex in a fixed position

Assume that n is a positive integer with n?2. It is proved that between any two different vertices x and y of Qn there exists a path Pl(x,y) of length l for any l with h(x,y)?l?n²−1 and 2|(l−h(x,y)). We expect such path Pl(x,y) can be further extended by including the vertices not in Pl(x,y) into a hamiltonian path from x to a fixed vertex z or a hamiltonian cycle. In this paper, we prove that for any two vertices x and z from different partite set of n-dimensional hypercube Qn, for any vertex y∈V(Qn)−{x,z}, and for any integer l with h(x,y)?l?n²−1−h(y,z) and 2|(l−h(x,y)), there exists a hamiltonian path R(x,y,z;l) from x to z such that dR(x,y,z;l)(x,y)=l. Moreover, for any two distinct vertices x and y of Qn and for any integer l with h(x,y)?l?²n−1 and 2|(l−h(x,y)), there exists a hamiltonian cycle S(x,y;l) such that dS(x,y;l)(x,y)=l.     

A full-wave solver of the Maxwell's equations in 3D cold plasmas

A new solver for Maxwell's equations in three-dimensional (3D) plasma configurations is presented. The new code LEMan (Low-frequency ElectroMagnetic wave propagation) determines a global solution of the wave equation in a realistic stellarator geometry at low frequencies. The code is aimed at the applications with relatively small computational resources and is very efficient in the Alfvén frequency range. In the present work, the cold plasma model is implemented. Finite elements are applied for the radial discretization and the spectral representation is used for the poloidal and toroidal angles. Special care is taken to avoid the numerical pollution of the spectrum as well as to ensure the energy conservation. The numerical scheme and the convergence properties are discussed. Several benchmarks and results in different geometries are presented.     

Novel carbazole/anthracene hybrids for efficient blue organic light-emitting diodes

Two novel carbazole/anthracene hybrided molecules, namely 2-(anthracen-9-yl)-9-ethyl-9H-carbazole (AnCz) and 2,7-di(anthracen-9-yl)-9-ethyl-9H-carbazole (2AnCz), were designed and synthesized via palladium catalyzed coupling reaction. The anthracene was attached either at the 2-site (AnCz) or at both 2,7-sites (2AnCz) of the central carbazole core to tune the conjugation state and the optoelectronic properties of the resultant molecules. Both of them show good solubility in common organic solvents. They also possess relatively high HOMO levels (−5.39 eV, −5.40 eV) that would facilitate efficient hole injection and be favorable for high power efficiencies when used in organic light-emitting devices (OLEDs). AnCz and 2AnCz were used as non-doped emitter to fabricate OLEDs by vacuum evaporation. Good performance was achieved with maximum luminance efficiency of 2.61 cd A⁻¹ and CIE coordinates of (0.15, 0.12) for AnCz, and 9.52 cd A⁻¹ and (0.22, 0.37) for 2AnCz.     

Heuristic computation of the rovibrational G matrix in optimized molecule-fixed axes. Gmat 2.1

Gmat 2.1 is a program able to compute the rovibrational G matrix in different molecule-fixed axes extending the capabilities of Gmat 1.0. The present version is able to select optimal molecule-fixed axes minimizing the pure rotational kinetic elements, the rovibrational kinetic elements or both simultaneously. To such an end, it uses a hybrid minimization approach. Thus, it combines a global search heuristic based in simulated annealing with a gradient-free local minimization. As the previous version, the program handles the structural results of potential energy hypersurface mappings computed in computer clusters or computational Grid environments. However, since now more general molecule-fixed axes can be defined, a procedure is implemented to ensure the same minimum of the cost function is used in all the molecular structures. In addition, an algorithm for the unambiguous definition of the molecule-fixed axes orientation is used.

Program summary

Program title: Gmat 2.1Catalogue identifier: AECZ_v2_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECZ_v2_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 52 555No. of bytes in distributed program, including test data, etc.: 932 366Distribution format: tar.gzProgramming language: Standard ANSI C++Computer: AllOperating system: Linux, WindowsClassification: 16.2Catalogue identifier of previous version: AECZ_v1_0Journal reference of previous version: Comput. Phys. Comm. 180 (2009) 1183Does the new version supersede the previous version?: YesNature of problem: When building molecular rovibrational Hamiltonians, the kinetic terms depend on the molecule-fixed axes orientation. Thus, an appropriate orientation can significantly simplify the treatment of pure rotation and rovibrational coupling. The kinetic terms are collected in the rovibrational G matrix. Thus, selection of an appropriate molecule-fixed reference frame is equivalent to localize the axes that minimize specific G matrix elements. From this standpoint, three different kinds of molecule-fixed axes are of interest: first, axes minimizing pure rotational elements of the G matrix; second, axes minimizing all the rovibrational G matrix elements; third, axes minimizing simultaneously pure rotational + rovibrational coupling elements.Solution method: In order to carry out the optimal selection of molecule-fixed axes, we add a hybrid method of minimization to the capabilities included in the first version of the program [1]. Thus, we minimize specific elements of the rovibrational G matrix. To such an end, we apply a heuristic global optimization strategy, simulated annealing [2], followed by a Powell's local minimization [3]. We also include a procedure to ensure that the same minimum is used when several molecular configurations are considered. In addition, an unambiguous molecule-fixed axes ordering is implemented.Reasons for new version: The previous version of the program, Gmat 1.0, works in principal axes of inertia. Although this axes system is adequate for pure vibrational Hamiltonians, it is not always optimal for the construction of general rovibrational Hamiltonians. However, implementing the methods presented here, we can obtain molecule-fixed axes minimizing pure rotational or/and rovibrational interactions in the G matrix. In this form, we can derive the simplest analytical form of the rovibrational Hamiltonian.Summary of revisions: Some new methods have been introduced:

1.

A method to build the molecule-fixed axes rotation matrix from the Euler angles.

2.

Methods for rotating nuclear coordinates and their derivatives using the rotation matrix.

3.

A method for applying simulated annealing to the search of the global minimum of a cost function formed by rotational or rovibrational G matrix elements.

4.

A method implementing Powell.

Running time: The sample tests take a few seconds to execute.References:

[1]

M.E. Castro, A. Niño, C. Muñoz-Caro, Comput. Phys. Comm. 180 (2009) 1183.

[2]

S. Kirkpatrick, C.D. Gelatt Jr., M.P. Vecchi, Science 220 (4598) (1983) 671.

[3]

W.H. Press, B.P. Flannery, S.A. Teukolsky, W.T. Vetterling, Numerical Recipes. The Art of Scientific Computing, Cambridge University Press, Cambridge, 2007.

     

Supporting early pruning in top-k query processing on massive data

This paper analyzes the execution behavior of “No Random Accesses” (NRA) and determines the depths to which each sorted file is scanned in growing phase and shrinking phase of NRA respectively. The analysis shows that NRA needs to maintain a large quantity of candidate tuples in growing phase on massive data. Based on the analysis, this paper proposes a novel top-k algorithm Top-K with Early Pruning (TKEP) which performs early pruning in growing phase. General rule and mathematical analysis for early pruning are presented in this paper. The theoretical analysis shows that early pruning can prune most of the candidate tuples. Although TKEP is an approximate method to obtain the top-k result, the probability for correctness is extremely high. Extensive experiments show that TKEP has a significant advantage over NRA.     

On polymorphic types of untyped terms

Let S be a finite set of β normal closed terms and M and N a pair of β normal, η   distinct, closed terms. Then there exist polymorphic types a,b$a,b$ such that every member of S can be typed as a, and M and N have η expansions which can be typed as b; where, in the resulting typings, the members of S can be simultaneously consistently identified, and the η expansions of M and N are βη inconsistent (no model with more than one element of any type). A similar result holds in the presence of surjective pairing.     

Salicylaldehyde based colorimetric and “turn on” fluorescent sensors for fluoride anion sensing employing hydrogen bonding

Two salicylaldehyde based colorimetric and fluorescent chemosensors 1 and 2 were developed. Both receptors 1 and 2 showed unique selectivity for the fluoride anions over other anions in DMSO solution. [TBA] OH and ¹H NMR titration experiments revealed that the F⁻-induced colorimetric and “turn on” fluorescence response were driven by hydrogen bonding interaction between the OH protons and F⁻.     

Learning complex action models with quantifiers and logical implications

Automated planning requires action models described using languages such as the Planning Domain Definition Language (PDDL) as input, but building action models from scratch is a very difficult and time-consuming task, even for experts. This is because it is difficult to formally describe all conditions and changes, reflected in the preconditions and effects of action models. In the past, there have been algorithms that can automatically learn simple action models from plan traces. However, there are many cases in the real world where we need more complicated expressions based on universal and existential quantifiers, as well as logical implications in action models to precisely describe the underlying mechanisms of the actions. Such complex action models cannot be learned using many previous algorithms. In this article, we present a novel algorithm called LAMP (Learning Action Models from Plan traces), to learn action models with quantifiers and logical implications from a set of observed plan traces with only partially observed intermediate state information. The LAMP algorithm generates candidate formulas that are passed to a Markov Logic Network (MLN) for selecting the most likely subsets of candidate formulas. The selected subset of formulas is then transformed into learned action models, which can then be tweaked by domain experts to arrive at the final models. We evaluate our approach in four planning domains to demonstrate that LAMP is effective in learning complex action models. We also analyze the human effort saved by using LAMP in helping to create action models through a user study. Finally, we apply LAMP to a real-world application domain for software requirement engineering to help the engineers acquire software requirements and show that LAMP can indeed help experts a great deal in real-world knowledge-engineering applications.     

An efficient algorithm for constructing a connected dominating set in mobile ad hoc networks

The connected dominating set (CDS) is widely used as a virtual backbone in mobile ad hoc networks. Although many distributed algorithms for constructing the CDS have been proposed, nearly all of them require two or more separated phases, which may cause problems such as long delay in the later phases when the network size is large. This paper proposes a Distributed Single-Phase algorithm for constructing a connected dominating set, DSP-CDS, in ad hoc networks. The DSP-CDS is an asynchronous distributed algorithm and converges quickly in a single phase. Each node uses one-hop neighborhood information and makes a local decision on whether to join the dominating set. Each node bases its decision on a key variable, strength, which guarantees that the dominating set is connected when the algorithm converges. The rules for computing strength can be changed to accommodate different application needs. The DSP-CDS adapts well to dynamic network topologies, upon which the algorithm makes only necessary local updates to maintain the CDS of the network. The performance of the DSP-CDS can be tuned by adjusting two main parameters. Extensive simulations have demonstrated that those parameters can affect the CDS size, the CDS diameter, and number of rounds for the algorithm to converge. Comparisons with other multiple-phase CDS algorithms have shown that the DSP-CDS converges fast and generates a CDS of comparable size.     

On the embedding degree of reductions of an elliptic curve

Given an elliptic curve E over Q we estimate the number of primes p?T for which the number of points on reduction of E modulo p has a large prime factor ? and also a small embedding degree with respect to ?. Such curves are important for a number of cryptographic applications. However our result shows that they are very rare. On the other hand, it also shows that the so-called MOV attack is not likely to affect the reduction of a given elliptic curve over Q modulo a random prime.     

The values of college students in business simulation game: A means-end chain approach

Business simulation games (BSGs) enable students to practice making decisions in a virtual environment, accumulate experience in application of strategies, and train themselves in modes of decision-making. This study examines the value sought by players of BSG. In this study, a means-end chain (MEC) model was adopted as the basis, and ladder method soft laddering was used to conduct in-depth interviews with students who had experience in using BSGs. The chain concept of “attribute-consequence-value” was used to understand students’ value cognition structures. Content analysis was used to analyze the attributes-consequences-values for BSGs players, then converted into a Hierarchical Value Map (HVM). The results showed that students consider teamwork and market diversity as the most important attributes, and the consequences of a cooperative approach and market diversity are emotional exchange and multi-thinking, with the ultimate value brought to users by exchanges between teams and constant thinking being interpersonal relationships and a sense of accomplishment.     

Enhanced chemosensing of ammonia based on the novel molecular semiconductor-doped insulator (MSDI) heterojunctions

A series of new molecular semiconductor-doped insulator (MSDI) heterojunctions as conductimetric transducers to NH₃ sensing were fabricated based on a novel semiconducting molecular material, an amphiphilic tris(phthalocyaninato) rare earth triple-decker complex, Eu₂[Pc(15C5)₄]₂[Pc(OC₁₀H₂₁)₈], quasi-Langmuir-Shäfer (QLS) film, as a top-layer, and vacuum-deposited and cast film of CuPc as well as copper tetra-tert-butyl phthalocyanine (CuTTBPc) QLS film as a sub-layer, named as MSDIs 1, 2 and 3, respectively. MSDIs 1-3 and respective sub-layers prepared from three different methods were characterized by X-ray diffraction, electronic absorption spectra and current-voltage (I-V) measurements. Depending on the sub-layer film-forming method used, α-phase CuPc film structure, β-phase CuPc crystallites and H-type aggregates of CuTTBPc have been obtained, respectively. An increasing sensitivity to NH₃ at varied concentrations in the range of 15-800 ppm, follows the order MSDI 2 < MSDI 3 < MSDI 1, revealing the effect of sub-layer film structures on sensing performance of the MSDIs. In particular, the time-dependent current plot of the MSDI 1, with α-phase CuPc film as a sub-layer, clearly shows an excellent separation of the different ammonia concentration levels and nearly complete reversibility and reproducibility even at room temperature, which is unique among the phthalocyanine-based ammonia sensors thus far reported in the literature. This provides a general method to improve sensor response of organic heterojunctions by controlling and tuning the film structure of sub-layer with appropriate fabrication techniques. On the other hand, the enhanced sensitivity, stability and reproducible response of the MSDI 1 heterostructure in comparison with the respective single-layer films have also been obtained. A judicious combination of materials and molecular architectures has led to enhanced sensing properties of the MSDI 1, in which control at the molecular level can be achieved.     

Geometry-based semantic ID for persistent and interoperable reference in feature-based parametric modeling

In current feature-based parametric design systems, the reusability principle is not fully supported as it was expected. Unpredictability and ambiguity of models often happen during design modification within one system as well as among different systems. This reference deficiency significantly reduces the power of feature-based parametric modeling, where geometry re-evaluation generates unexpected shapes. In this paper, a sufficient condition of B-Rep variance based on geometry continuity in parametric complex Euclidean (P^pC³) space is proposed. Shape and relation parameters are differentiated in P^pC³, thus parametric family can be defined. A semantic id scheme based on continuity of geometry is developed to solve the problem of naming persistency and to improve interoperability of CAD feature modeling. Hierarchical namespaces localize entity creation and identification. All geometric and topological entities are referred uniformly based on surface ids, and topology semantics is retained in id itself.     

A metaheuristic approach to the optimal definition of molecule-fixed axes in rovibrational Hamiltonians

We develop an algorithmic, metaheuristic approach to the definition of molecule-fixed axes orientation in molecules of arbitrary size. The goal is to simplify the treatment of overall rotation and rotation-vibration interaction in rovibrational Hamiltonians. Considering the kinetic elements of the rovibrational Hamiltonian, given by the G matrix, we select the optimal orientation of molecule-fixed axes minimizing specific G matrix elements. To such an end, we develop a global minimization method based in a hybrid Simulated Annealing+Powell's local minimization. The parameters of the method are calibrated using a set of non-rigid molecules: Acetaldehyde, glycolaldehyde, methyl formate and ethyl methyl ether. The results show that the principal axes of inertia do not give the simplest form to the pure rotational contribution. However, minimization of the G matrix rotational element does. Finally, we observe that in the cases considered it is not possible to nullify all the rotation-vibration coupling elements, since the torsional motions are coupled with the overall rotation. However, the treatment yields the optimal solution. The methodology proposed allows also to simplify simultaneously the pure rotational+rotation-vibration coupling elements in rovibrational Hamiltonians.     

A constrained optimization approach for an adaptive generalized subspace tracking algorithm

In this paper, we present an orthonormal version of the generalized signal subspace tracking. It is based on an interpretation of the generalized signal subspace as the solution of a constrained minimization task. This algorithm, referred to as the CGST algorithm, guarantees the C_x-orthonormality of the estimated generalized signal subspace basis at each iteration which C_x denotes the correlation matrix of the sequence x(t). An efficient implementation of the proposed algorithm enhances applicability of it in real time applications.     

Descendants of a recognizable tree language for sets of linear monadic term rewrite rules

For a tree language L and a set S of term rewrite rules over Σ, the descendant of L for S is the set S^∗(L) of trees reachable from a tree in L by rewriting in S. For a recognizable tree language L, we study the set D(L) of descendants of L for all sets of linear monadic term rewrite rules over Σ. We show that D(L) is finite. For each tree automaton A over Σ, we can effectively construct a set {R₁,…,Rk} of linear monadic term rewrite systems over Σ such that and for any 1?i<j?k, .