Photochemical oxidation of thio ketones: steric and electronic aspects

Oxidation of diaryl, aryl alkyl, and dialkyl thioketones by singlet oxygen generated via self-sensitization and other independent methods yielded the corresponding ketone and sulfine in varying amounts. A zwitterionic/ diradical intermediate arising out of the primary interaction of singlet oxygen with the thiocarbonyl chromophore is believed to be the common intermediate for the ketone and sulfine. While closure of the zwitterion/diradical to give 1,2,3-dioxathietane would lead to the ketone, competing oxygen elimination is believed to lead to the sulfine. This partitioning is governed by steric and electronic factors operating on the zwitterionic/diradical intermediate.

Synergistic Execution of Stream Programs on Multicores with Accelerators

The StreamIt programming model has been proposed to exploit parallelism in streaming applications oil general purpose multicore architectures. The StreamIt graphs describe task, data and pipeline parallelism which can be exploited on accelerators such as Graphics Processing Units (GPUs) or CellBE which support abundant parallelism in hardware. In this paper, we describe a novel method to orchestrate the execution of if StreamIt program oil a multicore platform equipped with an accelerator. The proposed approach identifies, using profiling, the relative benefits of executing a task oil the superscalar CPU cores and the accelerator. We formulate the problem of partitioning the work between the CPU cores and the GPU, taking into account the latencies for data transfers and the required buffer layout transformations associated with the partitioning, as all integrated Integer Linear Program (ILP) which can then be solved by an ILP solver. We also propose an efficient heuristic algorithm for the work-partitioning between the CPU and the GPU, which provides solutions which are within 9.05% of the optimal solution on an average across the benchmark Suite. The partitioned tasks are then software pipelined to execute oil the multiple CPU cores and the Streaming Multiprocessors (SMs) of the GPU. The software pipelining algorithm orchestrates the execution between CPU cores and the GPU by emitting the code for the CPU and the GPU, and the code for the required data transfers. Our experiments on a platform with 8 CPU cores and a GeForce 8800 GTS 512 GPU show a geometric mean speedup of 6.94X with it maximum of 51.96X over it single threaded CPU execution across the StreamIt benchmarks. This is a 18.9% improvement over it partitioning strategy that maps only the filters that cannot be executed oil the GPU - the filters with state that is persistent across firings - onto the CPU.

DFL: A Data Flow Language

Many novel computer architectures like array and multiprocessors which achieve high performance through the use of concurrency exploit variations of the von Neumann model of computation. The effective utilization of the machines makes special demands on programmers and their programming languages, such as the structuring of data into vectors or the partitioning of programs into concurrent processes. In comparison, the data flow model of computation demands only that the principle of structured programming be followed. A data flow program, often represented as a data flow graph, is a program that expresses a computation by indicating the data dependencies among operators. A data flow computer is a machine designed to take advantage of concurrency in data flow graphs by executing data independent operations in parallel. In this paper, we discuss the design of a high level language (DFL: Data Flow Language) suitable for data flow computers. Some sample procedures in DFL are presented. The implementation aspects have not been discussed in detail since there are no new problems encountered. The language DFL embodies the concepts of functional programming, but in appearance closely resembles Pascal. The language is a better vehicle than the data flow graph for expressing a parallel algorithm. The compiler has been implemented on a DEC 1090 system in Pascal.

Oxidations of thio ketones by singlet and triplet oxygen

Oxidation of di-tert-butyl thioketone (1) and 2,2,4,4-tetramethylcyclobutylth ioketone (2) by singlet oxygen yields the corresponding sulfine and ketone; in the case of 1 the sulfine is the major product, whereas in 2 it is the ketone. 1,2,3-Dioxathietane has been suggested as the precursor for the ketones, and the zwitterionic/diradid peroxide is believed to be a common primary intermediate for both sulfine and ketone. Steric influence is felt both during primary interaction between singlet oxygen and thioketone and during the partitioning of the peroxide intermediate. Steric interaction is suggested as the reason for variations in the product distribution between 1 and 2. Singlet oxygen is also generated through energy transfer from the triplet state of thioketones. These excited states also directly react with oxygen to yield ketone.

Oxidations of thio ketones by singlet and triplet oxygen

Oxidation of di-tert-butyl thioketone (1) and 2,2,4,4-tetramethylcyclobutylth ioketone (2) by singlet oxygen yields the corresponding sulfine and ketone; in the case of 1 the sulfine is the major product, whereas in 2 it is the ketone. 1,2,3-Dioxathietane has been suggested as the precursor for the ketones, and the zwitterionic/diradid peroxide is believed to be a common primary intermediate for both sulfine and ketone. Steric influence is felt both during primary interaction between singlet oxygen and thioketone and during the partitioning of the peroxide intermediate. Steric interaction is suggested as the reason for variations in the product distribution between 1 and 2. Singlet oxygen is also generated through energy transfer from the triplet state of thioketones. These excited states also directly react with oxygen to yield ketone.

Comparative life-history traits in a fig wasp community: implications for community structure

1. Whether life-history traits can determine community composition and structure is an important question that has been well explored theoretically, but has received scant empirical attention. Life-history traits of a seven-member community of galler and parasitoid fig wasp species (Chalcidoidea), developing within the inflorescences (syconia) of Ficus racemosa (Moraceae) in India, were determined and used to examine community structure and ecology. 2. Gallers were pro-ovigenic (all eggs are mature upon adult emergence) whereas parasitoids were synovigenic (eggs mature progressively during adult lifespan). Initial egg load was correlated with body size for some species, and there was a trade-off between egg number and egg size across all species. Although all species completed their development and left the syconium concurrently, they differed in their adult and pre-adult lifespans. Providing sucrose solutions increased parasitoid lifespan but had no effect on the longevity of some galler species. While feeding regimes and body size affected longevity in most species, an interaction effect between these variables was detected for only one species. 3. Life-history traits of wasp species exhibited a continuum in relation to their arrival sequence at syconia for oviposition during syconium development, and therefore reflected their ecology. The largest number of eggs, smallest egg sizes, and shortest longevities were characteristic of the earliest-arriving galling wasps at the smallest, immature syconia; the converse characterised the later-arriving parasitoids at the larger, already parasitised syconia. Thus life history is an important correlate of community resource partitioning and can be used to understand community structure. 4. This is the first comprehensive study of life-history traits in a fig wasp community. The comparative approach revealed constraints and flexibility in trait evolution.

Optimal resource allocation in conflicts with the Lanchester linear law (2,1) model

This paper presents a detailed analysis of a model for military conflicts where the defending forces have to determine an optimal partitioning of available resources to counter attacks from an adversary in two different fronts in an area fire situation. Lanchester linear law attrition model is used to develop the dynamical equations governing the variation in force strength. Here we address a static resource allocation problem namely, Time-Zero-Allocation (TZA) where the resource allocation is done only at the initial time. Numerical examples are given to support the analytical results.

Clustering in Concept Association Networks

We view association of concepts as a complex network and present a heuristic for clustering concepts by taking into account the underlying network structure of their associations. Clusters generated from our approach are qualitatively better than clusters generated from the conventional spectral clustering mechanism used for graph partitioning.

Two-agent cooperative search using game models with endurance-time constraints

In this article, the problem of two Unmanned Aerial Vehicles (UAVs) cooperatively searching an unknown region is addressed. The search region is discretized into hexagonal cells and each cell is assumed to possess an uncertainty value. The UAVs have to cooperatively search these cells taking limited endurance, sensor and communication range constraints into account. Due to limited endurance, the UAVs need to return to the base station for refuelling and also need to select a base station when multiple base stations are present. This article proposes a route planning algorithm that takes endurance time constraints into account and uses game theoretical strategies to reduce the uncertainty. The route planning algorithm selects only those cells that ensure the agent will return to any one of the available bases. A set of paths are formed using these cells which the game theoretical strategies use to select a path that yields maximum uncertainty reduction. We explore non-cooperative Nash, cooperative and security strategies from game theory to enhance the search effectiveness. Monte-Carlo simulations are carried out which show the superiority of the game theoretical strategies over greedy strategy for different look ahead step length paths. Within the game theoretical strategies, non-cooperative Nash and cooperative strategy perform similarly in an ideal case, but Nash strategy performs better than the cooperative strategy when the perceived information is different. We also propose a heuristic based on partitioning of the search space into sectors to reduce computational overhead without performance degradation.

Parallelization of an unstructured data based cell centre finite volume code, HIFUN-3D

This work describes the parallelization of High Resolution flow solver on unstructured meshes, HIFUN-3D, an unstructured data based finite volume solver for 3-D Euler equations. For mesh partitioning, we use METIS, a software based on multilevel graph partitioning. The unstructured graph used for partitioning is associated with weights both on its vertices and edges. The data residing on every processor is split into four layers. Such a novel procedure of handling data helps in maintaining the effectiveness of the serial code. The communication of data across the processors is achieved by explicit message passing using the standard blocking mode feature of Message Passing Interface (MPI). The parallel code is tested on PACE++128 available in CFD Center

Temporal associations in fig-wasp-ant interactions: diel and phenological patterns

In a complex multitrophic plant-animal interaction system in which there are direct and indirect interactions between species, comprehending the dynamics of these multiple partners is very important for an understanding of how the system is structured. We investigated the plant Ficus racemosa L. (Moraceae) and its community of obligatory mutualistic and parasitic fig wasps (Hymenoptera: Chalcidoidea) that develop within the fig inflorescence or syconium, as well as their interaction with opportunistic ants. We focused on temporal resource partitioning among members of the fig wasp community over the development cycle of the fig syconia during which wasp oviposition and development occur and we studied the activity rhythm of the ants associated with this community. We found that the seven members of the wasp community partitioned their oviposition across fig syconium development phenology and showed interspecific variation in activity across the day-night cycle. The wasps presented a distinct sequence in their arrival at fig syconia for oviposition, with the parasitoid wasps following the galling wasps. Although fig wasps are known to be largely diurnal, we documented night oviposition in several fig wasp species for the first time. Ant activity on the fig syconia was correlated with wasp activity and was dependent on whether the ants were predatory or trophobiont-tending species; only numbers of predatory ants increased during peak arrivals of the wasps.

Algorithms for Colouring Random k-colourable Graphs

The k-colouring problem is to colour a given k-colourable graph with k colours. This problem is known to be NP-hard even for fixed k greater than or equal to 3. The best known polynomial time approximation algorithms require n(delta) (for a positive constant delta depending on k) colours to colour an arbitrary k-colourable n-vertex graph. The situation is entirely different if we look at the average performance of an algorithm rather than its worst-case performance. It is well known that a k-colourable graph drawn from certain classes of distributions can be ii-coloured almost surely in polynomial time. In this paper, we present further results in this direction. We consider k-colourable graphs drawn from the random model in which each allowed edge is chosen independently with probability p(n) after initially partitioning the vertex set into ii colour classes. We present polynomial time algorithms of two different types. The first type of algorithm always runs in polynomial time and succeeds almost surely. Algorithms of this type have been proposed before, but our algorithms have provably exponentially small failure probabilities. The second type of algorithm always succeeds and has polynomial running time on average. Such algorithms are more useful and more difficult to obtain than the first type of algorithms. Our algorithms work as long as p(n) greater than or equal to n(-1+is an element of) where is an element of is a constant greater than 1/4.

Synthesis of FeCu Nanopowder by Levitational Gas Condensation Process

Condensation from the vapor state is an important technique for the preparation of nanopowders. Levitational gas condensation is one such technique that has a unique ability of attaining steady state. Here, we present the results of applying this technique to an iron-copper alloy (96Fe-4Cu). A qualitative model of the process is proposed to understand the process and the characteristics of resultant powder. A phase diagram of the alloy system in the liquid-vapor region was calculated to help understand the course of condensation, especially partitioning and coring during processing. The phase diagram could not explain coring in view of the simultaneous occurrence of solidification and the fast homogenization through diffusion in the nanoparticles; however, it could predict the very low levels of copper observed in the levitated drop. The enrichment of copper observed near the surface of the powder was considered to be a manifestation of the lower surface energy of copper compared with that of iron. Heat transfer calculations indicated that most condensed particles can undergo solidification even when they are still in the proximity of the levitated drop. It helped us to predict the temperature and the cooling rate of the powder particles as they move away from the levitated drop. The particles formed by the process seem to be single domain, single crystals that are magnetic in nature. They, thus, can agglomerate by forming a chain-like structure, which manifests as a three-dimensional network enclosing a large unoccupied space, as noticed in scanning electron microscopy and transmission electron microscopy studies. This also explains the observed low packing density of the nanopowders.

A comparison between conceptual clustering and conventional clustering

Clustering is a process of partitioning a given set of patterns into meaningful groups. The clustering process can be viewed as consisting of the following three phases: (i) feature selection phase, (ii) classification phase, and (iii) description generation phase. Conventional clustering algorithms implicitly use knowledge about the clustering environment to a large extent in the feature selection phase. This reduces the need for the environmental knowledge in the remaining two phases, permitting the usage of simple numerical measure of similarity in the classification phase. Conceptual clustering algorithms proposed by Michalski and Stepp [IEEE Trans. PAMI, PAMI-5, 396–410 (1983)] and Stepp and Michalski [Artif. Intell., pp. 43–69 (1986)] make use of the knowledge about the clustering environment in the form of a set of predefined concepts to compute the conceptual cohesiveness during the classification phase. Michalski and Stepp [IEEE Trans. PAMI, PAMI-5, 396–410 (1983)] have argued that the results obtained with the conceptual clustering algorithms are superior to conventional methods of numerical classification. However, this claim was not supported by the experimental results obtained by Dale [IEEE Trans. PAMI, PAMI-7, 241–244 (1985)]. In this paper a theoretical framework, based on an intuitively appealing set of axioms, is developed to characterize the equivalence between the conceptual clustering and conventional clustering. In other words, it is shown that any classification obtained using conceptual clustering can also be obtained using conventional clustering and vice versa.

A near-optimal initial seed value selection in K-means means algorithm using a genetic algorithm

The K-means algorithm for clustering is very much dependent on the initial seed values. We use a genetic algorithm to find a near-optimal partitioning of the given data set by selecting proper initial seed values in the K-means algorithm. Results obtained are very encouraging and in most of the cases, on data sets having well separated clusters, the proposed scheme reached a global minimum.