Transferability of Multipole Charge Density Parameters for Supramolecular Synthons: A New Tool for Quantitative Crystal Engineering

The modularity of the supramolecular synthon is used to obtain transferability of charge density derived multipolar parameters for structural fragments, thus creating an opportunity to derive charge density maps for new compounds. On the basis of high resolution X-ray diffraction data obtained at 100 K for three compounds methoxybenzoic acid, acetanilide, and 4-methyl-benzoic acid, multipole parameters for O-H center dot center dot center dot O carboxylic acid dimer and N-H center dot center dot center dot O amide infinite chain synthon fragments have been derived. The robustness associated with these supramolecular synthons has been used to model charge density derived multipolar parameters for 4-(acetylamino)benzoic acid and 4-methylacetanilide. The study provides pointers to the design and fabrication of a synthon library of high resolution X-ray diffraction data sets. It has been demonstrated that the derived charge density features can be exploited in both intra- and intermolecular space for any organic compound based on transferability of multipole parameters. The supramolecular synthon based fragments approach (SBFA) has been compared with experimental charge density data to check the reliability of use of this methodology for transferring charge density derived multipole parameters.

Armchair or Zigzag? A tool for characterizing graphene edge

Electronic, magnetic, and structural properties of graphene flakes depend sensitively upon the type of edge atoms. We present a simple software tool for determining the type of edge atoms in a honeycomb lattice. The algorithm is based on nearest neighbor counting. Whether an edge atom is of armchair or zigzag type is decided by the unique pattern of its nearest neighbors. Particular attention is paid to the practical aspects of using the tool, as additional features such as extracting out the edges from the lattice could help in analyzing images from transmission microscopy or other experimental probes. Ultimately, the tool in combination with density-functional theory or tight-binding method can also be helpful in correlating the properties of graphene flakes with the different armchair-to-zigzag ratios. Program summary Program title: edgecount Catalogue identifier: AEIA_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEIA_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 66685 No. of bytes in distributed program, including test data, etc.: 485 381 Distribution format: tar.gz Programming language: FORTRAN 90/95 Computer: Most UNIX-based platforms Operating system: Linux, Mac OS Classification: 16.1, 7.8 Nature of problem: Detection and classification of edge atoms in a finite patch of honeycomb lattice. Solution method: Build nearest neighbor (NN) list; assign types to edge atoms on the basis of their NN pattern. Running time: Typically similar to second(s) for all examples. (C) 2010 Elsevier B.V. All rights reserved.

Search Strategies for Multiple UAV Search and Destroy Missions

Multiple UAVs are deployed to carry out a search and destroy mission in a bounded region. The UAVs have limited sensor range and can carry limited resources which reduce with use. The UAVs perform a search task to detect targets. When a target is detected which requires different type and quantities of resources to completely destroy, then a team of UAVs called as a coalition is formed to attack the target. The coalition members have to modify their route to attack the target, in the process, the search task is affected, as search and destroy tasks are coupled. The performance of the mission is a function of the search and the task allocation strategies. Therefore, for a given task allocation strategy, we need to devise search strategies that are efficient. In this paper, we propose three different search strategies namely; random search strategy, lanes based search strategy and grid based search strategy and analyze their performance through Monte-Carlo simulations. The results show that the grid based search strategy performs the best but with high information overhead.

Ultrafast laser spectroscopy-A tool chemists and biologists

Application of ultrafast lasers to chemistry and biology has been an active area of research in the international scene for over a decade for physical and biophysical chemists. Perhaps, ultrafast laser spectroscopy is one of the most versatile tools available today to experimentally study structure and dynamics in the time domain of nanoseconds (10(-9) sec) to femtoseconds (10(-15) sec). In this article we attempt to highlight some of the recent developments in ultrafast laser spectroscopy with particular reference to vibrational spectroscopy, viz. infrared and Raman spectroscopy, in the above time domain.

Frontier Based Multiple Goal Search in Unknown Environments

We present a frontier based algorithm for searching multiple goals in a fully unknown environment, with only information about the regions where the goals are most likely to be located. Our algorithm chooses an ``active goal'' from the ``active goal list'' generated by running a Traveling Salesman Problem (Tsp) routine with the given centroid locations of the goal regions. We use the concept of ``goal switching'' which helps not only in reaching more number of goals in given time, but also prevents unnecessary search around the goals that are not accessible (surrounded by walls). The simulation study shows that our algorithm outperforms Multi-Heuristic LRTA* (MELRTA*) which is a significant representative of multiple goal search approaches in an unknown environment, especially in environments with wall like obstacles.

Layered Tabu Search Algorithm for Large-MIMO Detection and a Lower Bound on ML Performance

In this paper, we are concerned with low-complexity detection in large multiple-input multiple-output (MIMO) systems with tens of transmit/receive antennas. Our new contributions in this paper are two-fold. First, we propose a low-complexity algorithm for large-MIMO detection based on a layered low-complexity local neighborhood search. Second, we obtain a lower bound on the maximum-likelihood (ML) bit error performance using the local neighborhood search. The advantages of the proposed ML lower bound are i) it is easily obtained for MIMO systems with large number of antennas because of the inherent low complexity of the search algorithm, ii) it is tight at moderate-to-high SNRs, and iii) it can be tightened at low SNRs by increasing the number of symbols in the neighborhood definition. Interestingly, the proposed detection algorithm based on the layered local search achieves bit error performances which are quite close to this lower bound for large number of antennas and higher-order QAM. For e. g., in a 32 x 32 V-BLAST MIMO system, the proposed detection algorithm performs close to within 1.7 dB of the proposed ML lower bound at 10(-3) BER for 16-QAM (128 bps/Hz), and close to within 4.5 dB of the bound for 64-QAM (192 bps/Hz).

Multiple UAV Coalitions for a Search and Prosecute Mission

Unmanned aerial vehicles (UAVs) have the potential to carry resources in support of search and prosecute operations. Often to completely prosecute a target, UAVs may have to simultaneously attack the target with various resources with different capacities. However, the UAVs are capable of carrying only limited resources in small quantities, hence, a group of UAVs (coalition) needs to be assigned that satisfies the target resource requirement. The assigned coalition must be such that it minimizes the target prosecution delay and the size of the coalition. The problem of forming coalitions is computationally intensive due to the combinatorial nature of the problem, but for real-time applications computationally cheap solutions are required. In this paper, we propose decentralized sub-optimal (polynomial time) and decentralized optimal coalition formation algorithms that generate coalitions for a single target with low computational complexity. We compare the performance of the proposed algorithms to that of a global optimal solution for which we need to solve a centralized combinatorial optimization problem. This problem is computationally intensive because the solution has to (a) provide a coalition for each target, (b) design a sequence in which targets need to be prosecuted, and (c) take into account reduction of UAV resources with usage. To solve this problem we use the Particle Swarm Optimization (PSO) technique. Through simulations, we study the performance of the proposed algorithms in terms of mission performance, complexity of the algorithms and the time taken to form the coalition. The simulation results show that the solution provided by the proposed algorithms is close to the global optimal solution and requires far less computational resources.

Reduced Order Suboptimal Control Design for a Class of Nonlinear Distributed Parameter Systems Using POD and /spl thetas/-D Techniques

A new computational tool is presented in this paper for suboptimal control design of a class of nonlinear distributed parameter systems. First proper orthogonal decomposition based problem-oriented basis functions are designed, which are then used in a Galerkin projection to come up with a low-order lumped parameter approximation. Next, a suboptimal controller is designed using the emerging /spl thetas/-D technique for lumped parameter systems. This time domain sub-optimal control solution is then mapped back to the distributed domain using the same basis functions, which essentially leads to a closed form solution for the controller in a state feedback form. Numerical results for a real-life nonlinear temperature control problem indicate that the proposed method holds promise as a good suboptimal control design technique for distributed parameter systems.

Automated Multi-Agent Search Using Centroidal Voronoi Configuration

This paper addresses the problem of automated multiagent search in an unknown environment. Autonomous agents equipped with sensors carry out a search operation in a search space, where the uncertainty, or lack of information about the environment, is known a priori as an uncertainty density distribution function. The agents are deployed in the search space to maximize single step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for the proposed sequential deploy and search strategy. It is shown that with the proposed control law the agent trajectories converge in a globally asymptotic manner to the centroidal Voronoi configuration. Simulation experiments are provided to validate the strategy. Note to Practitioners-In this paper, searching an unknown region to gather information about it is modeled as a problem of using search as a means of reducing information uncertainty about the region. Moreover, multiple automated searchers or agents are used to carry out this operation optimally. This problem has many applications in search and surveillance operations using several autonomous UAVs or mobile robots. The concept of agents converging to the centroid of their Voronoi cells, weighted with the uncertainty density, is used to design a search strategy named as sequential deploy and search. Finally, the performance of the strategy is validated using simulations.

Genetic search: Analysis using fitness moments

Genetic Algorithms are efficient and robust search methods that are being employed in a plethora of applications with extremely large search spaces. The directed search mechanism employed in Genetic Algorithms performs a simultaneous and balanced, exploration of new regions in the search space and exploitation of already discovered regions.This paper introduces the notion of fitness moments for analyzing the working of Genetic Algorithms (GAs). We show that the fitness moments in any generation may be predicted from those of the initial population. Since a knowledge of the fitness moments allows us to estimate the fitness distribution of strings, this approach provides for a method of characterizing the dynamics of GAs. In particular the average fitness and fitness variance of the population in any generation may be predicted. We introduce the technique of fitness-based disruption of solutions for improving the performance of GAs. Using fitness moments, we demonstrate the advantages of using fitness-based disruption. We also present experimental results comparing the performance of a standard GA and GAs (CDGA and AGA) that incorporate the principle of fitness-based disruption. The experimental evidence clearly demonstrates the power of fitness based disruption.

Image analysis using multifractals

The efficacy of the multifractal spectrum as a tool for characterizing images has been studied. This spectrum has been computed for digitized images of the nucleus of human cervical cancer cells and it was observed that the entire spectrum is almost fully reproduced for a normal cell while only the right half (q<0) of the spectrum is reproduced for a cancerous cell. Cells in stages in between the two extremes show a shortening of the left half of the spectrum proportional to their condition. The extent of this shortening has been found to be sufficient to permit a classification between three classes of cells at varying distances from a basal cancerous layer-the superficial cells, the intermediate cells and the parabasal cells. This technique may be used for automatic screening of the population while also indicating the stage of malignancy

Unwinding of heterologous DNA by RecA protein during the search for homologous sequences

The search for homologous sequences promoted by RecA protein in vitro involves a presynaptic filament and naked duplex DNA, the multiple contacts of which produce nucleoprotein networks or coaggregates. The single-stranded DNA within the presynaptic filaments, however, is extended to an axial spacing 1.5 times that of B-form DNA. To investigate this paradoxical difference between the spacing of bases in the RecA presynaptic filament versus the target duplex DNA, we explored the effect of heterologous contacts on the conformation of DNA, and vice versa. In the presence of wheat germ topoisomerase I, RecA presynaptic filaments induced a rapid, limited reduction in the linking number of heterologous circular duplex DNA. This limited unwinding of heterologous duplex DNA, termed heterologous unwinding, was detected within 30 seconds and reached a steady state within a few minutes. Presynaptic filaments that were formed in the presence of ATP?S and separated from free RecA protein by gel filtration also generated a ladder of topoisomers upon incubation with relaxed duplex DNA and topoisomerase. The inhibition of heterologous contacts by 60 mImage -NaCl or 5 mImage -ADP resulted in a corresponding decrease in heterologous unwinding. In reciprocal fashion, the stability or number of heterologous contacts with presynaptic filaments was inversely related to the linking number of circular duplex DNA. These observations show that heterologous contacts with the presynaptic filament cause a limited unwinding of the duplex DNA, and conversely that the ability of the DNA to unwind stabilizes transient heterologous contacts.

iPBA: a tool for protein structure comparison using sequence alignment strategies

With the immense growth in the number of available protein structures, fast and accurate structure comparison has been essential. We propose an efficient method for structure comparison, based on a structural alphabet. Protein Blocks (PBs) is a widely used structural alphabet with 16 pentapeptide conformations that can fairly approximate a complete protein chain. Thus a 3D structure can be translated into a 1D sequence of PBs. With a simple Needleman-Wunsch approach and a raw PB substitution matrix, PB-based structural alignments were better than many popular methods. iPBA web server presents an improved alignment approach using (i) specialized PB Substitution Matrices (SM) and (ii) anchor-based alignment methodology. With these developments, the quality of similar to 88% of alignments was improved. iPBA alignments were also better than DALI, MUSTANG and GANGSTA(+) in > 80% of the cases. The webserver is designed to for both pairwise comparisons and database searches. Outputs are given as sequence alignment and superposed 3D structures displayed using PyMol and Jmol. A local alignment option for detecting subs-structural similarity is also embedded. As a fast and efficient `sequence-based' structure comparison tool, we believe that it will be quite useful to the scientific community. iPBA can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/ipba/.

Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

Search for sub-mm, mm and radio continuum emission from extremely red objects

We present the results of sub-mm, mm (850 mum, 450 mum and 1250 mum) and radio (1.4 and 4.8 GHz) continuum observations of a sample of 27 K-selected Extremely Red Objects, or EROs, (14 of which form a complete sample with K < 20 and I - K > 5) aimed at detecting dusty starbursts, deriving the fraction of UltraLuminous Infrared Galaxies (ULIGs) in ERO samples, and constraining their redshifts using the radio-FIR correlation. One ERO was tentatively detected at 1250 mum and two were detected at 1.4 GHz, one of which has a less secure identification as an ERO counterpart. Limits on their redshifts and their star forming properties are derived and discussed. We stacked the observations of the undetected objects at 850 mum, 1250 mum and 4.8 GHz in order to search for possible statistical emission from the ERO population as a whole, but no significant detections were derived either for the whole sample or as a function of the average NIR colours. These results strongly suggest that the dominant population of EROs with K < 20 is not comprised of ULIGs like HR 10, but is probably made of radio-quiet ellipticals and weaker starburst galaxies with L < 10(12) L . and SFR < few hundred M. yr(-1).