Efficient mining of discriminative molecular fragments

Frequent pattern discovery in structured data is receiving an increasing attention in many application areas of sciences. However, the computational complexity and the large amount of data to be explored often make the sequential algorithms unsuitable. In this context high performance distributed computing becomes a very interesting and promising approach. In this paper we present a parallel formulation of the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The application is characterized by a highly irregular tree-structured computation. No estimation is available for task workloads, which show a power-law distribution in a wide range. The proposed approach allows dynamic resource aggregation and provides fault and latency tolerance. These features make the distributed application suitable for multi-domain heterogeneous environments, such as computational Grids. The distributed application has been evaluated on the well known National Cancer Institute’s HIV-screening dataset.

Selective and highly efficient dye scavenging by a pH-responsive molecular hydrogelator

A structurally simple low molecular weight hydrogelator derived from isophthalic acid forms robust pH-responsive hydrogels capable of highly efficient and selective dye adsorption.

Farming systems methodology for efficient resource management at the farm level: a review from an Indian perspective

Farming systems research is a multi-disciplinary holistic approach to solve the problems of small farms. Small and marginal farmers are the core of the Indian rural economy Constituting 0.80 of the total farming community but possessing only 0.36 of the total operational land. The declining trend of per capita land availability poses a serious challenge to the sustainability and profitability of farming. Under such conditions, it is appropriate to integrate land-based enterprises such as dairy, fishery, poultry, duckery, apiary, field and horticultural cropping within the farm, with the objective of generating adequate income and employment for these small and marginal farmers Under a set of farm constraints and varying levels of resource availability and Opportunity. The integration of different farm enterprises can be achieved with the help of a linear programming model. For the current review, integrated farming systems models were developed, by Way Of illustration, for the marginal, small, medium and large farms of eastern India using linear programming. Risk analyses were carried out for different levels of income and enterprise combinations. The fishery enterprise was shown to be less risk-prone whereas the crop enterprise involved greater risk. In general, the degree of risk increased with the increasing level of income. With increase in farm income and risk level, the resource use efficiency increased. Medium and large farms proved to be more profitable than small and marginal farms with higher level of resource use efficiency and return per Indian rupee (Rs) invested. Among the different enterprises of integrated farming systems, a chain of interaction and resource flow was observed. In order to make fanning profitable and improve resource use efficiency at the farm level, the synergy among interacting components of farming systems should be exploited. In the process of technology generation, transfer and other developmental efforts at the farm level (contrary to the discipline and commodity-based approaches which have a tendency to be piecemeal and in isolation), it is desirable to place a whole-farm scenario before the farmers to enhance their farm income, thereby motivating them towards more efficient and sustainable fanning.

Pea-barley intercropping for efficient symbiotic N-2-fixation, soil N acquisition and use of other nutrients in European organic cropping systems

Complementarity in acquisition of nitrogen (N) from soil and N-2-fixation within pea and barley intercrops was studied in organic field experiments across Western Europe (Denmark, United Kingdom, France, Germany and Italy). Spring pea and barley were sown either as sole crops, at the recommended plant density (P100 and B100, respectively) or in replacement (P50B50) or additive (P100B50) intercropping designs, in each of three cropping seasons (2003-2005). Irrespective of site and intercrop design, Land Equivalent Ratios (LER) between 1.4 at flowering and 1.3 at maturity showed that total N recovery was greater in the pea-barley intercrops than in the sole Crops Suggesting a high degree of complementarity over a wide range of growing conditions. Complementarity was partly attributed to greater soil mineral N acquisition by barley, forcing pea to rely more on N-2-fixation. At all sites the proportion of total aboveground pea N that was derived from N-2-fixation was greater when intercropped with barley than when grown as a sole crop. No consistent differences were found between the two intercropping designs. Simultaneously, the accumulation Of Phosphorous (P), potassium (K) and sulphur (S) in Danish and German experiments was 20% higher in the intercrop (P50B50) than in the respective sole crops, possibly influencing general crop yields and thereby competitive ability for other resources. Comparing all sites and seasons, the benefits of organic pea-barley intercropping for N acquisition were highly resilient. It is concluded that pea-barley intercropping is a relevant cropping strategy to adopt when trying to optimize N-2-fixation inputs to the cropping system. (C) 2009 Elsevier B.V. All rights reserved.

The use of life-cycle assessment to evaluate the environmental impacts of growing genetically modified, nitrogen use-efficient canola

Agriculture, particularly intensive crop production, makes a significant contribution to environmental pollution. A variety of canola (Brassica napus) has been genetically modified to enhance nitrogen use efficiency, effectively reducing the amount of fertilizer required for crop production. A partial life-cycle assessment adapted to crop production was used to assess the potential environmental impacts of growing genetically modified, nitrogen use-efficient (GMNUE) canola in North Dakota and Minnesota compared with a conventionally bred control variety. The analysis took into account the entire production system used to produce 1 tonne of canola. This comprised raw material extraction, processing and transportation, as well as all agricultural field operations. All emissions associated with the production of 1 tonne of canola were listed, aggregated and weighted in order to calculate the level of environmental impact. The findings show that there are a range of potential environmental benefits associated with growing GMNUE canola. These include reduced impacts on global warming, freshwater ecotoxicity, eutrophication and acidification. Given the large areas of canola grown in North America and, in particular, Canada, as well as the wide acceptance of genetically modified varieties in this area, there is the potential for GMNUE canola to reduce pollution from agriculture, with the largest reductions predicted to be in greenhouse gases and diffuse water pollution.

The failure of meta-analytic asymptotics for the seemingly efficient estimator of the common risk difference

We consider the case of a multicenter trial in which the center specific sample sizes are potentially small. Under homogeneity, the conventional procedure is to pool information using a weighted estimator where the weights used are inverse estimated center-specific variances. Whereas this procedure is efficient for conventional asymptotics (e. g. center-specific sample sizes become large, number of center fixed), it is commonly believed that the efficiency of this estimator holds true also for meta-analytic asymptotics (e.g. center-specific sample size bounded, potentially small, and number of centers large). In this contribution we demonstrate that this estimator fails to be efficient. In fact, it shows a persistent bias with increasing number of centers showing that it isnot meta-consistent. In addition, we show that the Cochran and Mantel-Haenszel weighted estimators are meta-consistent and, in more generality, provide conditions on the weights such that the associated weighted estimator is meta-consistent.

Determination of the optical properties of plastic films used as cladding materials in novel energy efficient greenhouses

Greenhouse cladding materials are a major component in the design of energy efficient greenhouses. The optical properties of cladding materials determine a major part of the overall performance of a greenhouse both in terms of the energy balance of the greenhouse and on crop behavior. Various film plastic greenhouse-cladding materials were measured under laboratory conditions using a spectroradiometer equipped with an integrating sphere. Films were measured over a range of angles of incidence and the effect of increasing distance between double films was also measured. PAR transmission remained nearly constant for angles of incidence increased up to 30 degrees but fell rapidly thereafter as the angles of incidence increased up to 90 degrees. Increasing distance between double films did not significantly affect PAR transmission in all films examined. These results are discussed in relation to the design criteria for an energy efficient greenhouse.

Efficient and cost-effective experimental determination of kinetic constants and data: the success of a Bayesian systematic approach to drug transport, receptor binding, continuous culture and cell transport kinetics

Details about the parameters of kinetic systems are crucial for progress in both medical and industrial research, including drug development, clinical diagnosis and biotechnology applications. Such details must be collected by a series of kinetic experiments and investigations. The correct design of the experiment is essential to collecting data suitable for analysis, modelling and deriving the correct information. We have developed a systematic and iterative Bayesian method and sets of rules for the design of enzyme kinetic experiments. Our method selects the optimum design to collect data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. The rules select features of the design such as the substrate range and the number of measurements. We show here that this method can be directly applied to the study of other important kinetic systems, including drug transport, receptor binding, microbial culture and cell transport kinetics. It is possible to reduce the errors in the estimated parameters and, most importantly, increase the efficiency and cost-effectiveness by reducing the necessary amount of experiments and data points measured. (C) 2003 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Efficient and accurate experimental design for enzyme kinetics: Bayesian studies reveal a systematic approach

In areas such as drug development, clinical diagnosis and biotechnology research, acquiring details about the kinetic parameters of enzymes is crucial. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. We demonstrate that a Bayesian approach (the use of prior knowledge) can produce major gains quantifiable in terms of information, productivity and accuracy of each experiment. Developing the use of Bayesian Utility functions, we have used a systematic method to identify the optimum experimental designs for a number of kinetic model data sets. This has enabled the identification of trends between kinetic model types, sets of design rules and the key conclusion that such designs should be based on some prior knowledge of K-M and/or the kinetic model. We suggest an optimal and iterative method for selecting features of the design such as the substrate range, number of measurements and choice of intermediate points. The final design collects data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. (C) 2003 Elsevier Science B.V. All rights reserved.

Design and analysis of climate model experiments for the efficient estimation of anthropogenic signals

Presented herein is an experimental design that allows the effects of several radiative forcing factors on climate to be estimated as precisely as possible from a limited suite of atmosphere-only general circulation model (GCM) integrations. The forcings include the combined effect of observed changes in sea surface temperatures, sea ice extent, stratospheric (volcanic) aerosols, and solar output, plus the individual effects of several anthropogenic forcings. A single linear statistical model is used to estimate the forcing effects, each of which is represented by its global mean radiative forcing. The strong colinearity in time between the various anthropogenic forcings provides a technical problem that is overcome through the design of the experiment. This design uses every combination of anthropogenic forcing rather than having a few highly replicated ensembles, which is more commonly used in climate studies. Not only is this design highly efficient for a given number of integrations, but it also allows the estimation of (nonadditive) interactions between pairs of anthropogenic forcings. The simulated land surface air temperature changes since 1871 have been analyzed. The changes in natural and oceanic forcing, which itself contains some forcing from anthropogenic and natural influences, have the most influence. For the global mean, increasing greenhouse gases and the indirect aerosol effect had the largest anthropogenic effects. It was also found that an interaction between these two anthropogenic effects in the atmosphere-only GCM exists. This interaction is similar in magnitude to the individual effects of changing tropospheric and stratospheric ozone concentrations or to the direct (sulfate) aerosol effect. Various diagnostics are used to evaluate the fit of the statistical model. For the global mean, this shows that the land temperature response is proportional to the global mean radiative forcing, reinforcing the use of radiative forcing as a measure of climate change. The diagnostic tests also show that the linear model was suitable for analyses of land surface air temperature at each GCM grid point. Therefore, the linear model provides precise estimates of the space time signals for all forcing factors under consideration. For simulated 50-hPa temperatures, results show that tropospheric ozone increases have contributed to stratospheric cooling over the twentieth century almost as much as changes in well-mixed greenhouse gases.

Alkene-arene meta photocycloadditions with a four-carbon-atom tether: efficient approach toward the polycyclic ring systems of aphidicolin and stemodinone

At the end of its tether! The fusion of a six-membered ring onto the four-carbon-atom tether of substrate 1 provides an efficient approach toward the polycyclic ring systems of the natural products aphidicolin and stemodinone. The reaction represents a unique example of a preference for product formation from an endo exciplex in an intramolecular system (exo:endo 2:3=1.0:1.2).

First efficient and general copper-catalyzed [2,3]-rearrangement of tetrahydropyridinium ylids

The factors affecting the copper-catalyzed rearrangement of ammonium ylids derived from tetrahydropyriclines and diazoesters; have been examined,and the first examples of high-yielding metal-catalyzed [2,3]-sigmatropic rearrangements of a wide range of such ylids are reported. The nature of the alpha-substituent in the diazo component of the reaction has a dramatic effect upon the yields of the reaction, with electron-withdrawing substituents enhancing the yield of the reaction.