Reducing the babel in plant volatile communication: using the forest to see the trees

While plants of a single species emit a diversity of volatile organic compounds (VOCs) to attract or repel interacting organisms, these specific messages may be lost in the midst of the hundreds of VOCs produced by sympatric plants of different species, many of which may have no signal content. Receivers must be able to reduce the babel or noise in these VOCs in order to correctly identify the message. For chemical ecologists faced with vast amounts of data on volatile signatures of plants in different ecological contexts, it is imperative to employ accurate methods of classifying messages, so that suitable bioassays may then be designed to understand message content. We demonstrate the utility of `Random Forests' (RF), a machine-learning algorithm, for the task of classifying volatile signatures and choosing the minimum set of volatiles for accurate discrimination, using datam from sympatric Ficus species as a case study. We demonstrate the advantages of RF over conventional classification methods such as principal component analysis (PCA), as well as data-mining algorithms such as support vector machines (SVM), diagonal linear discriminant analysis (DLDA) and k-nearest neighbour (KNN) analysis. We show why a tree-building method such as RF, which is increasingly being used by the bioinformatics, food technology and medical community, is particularly advantageous for the study of plant communication using volatiles, dealing, as it must, with abundant noise.

Distributed nonlinear optimization algorithms for general network problems

There are a number of large networks which occur in many problems dealing with the flow of power, communication signals, water, gas, transportable goods, etc. Both design and planning of these networks involve optimization problems. The first part of this paper introduces the common characteristics of a nonlinear network (the network may be linear, the objective function may be non linear, or both may be nonlinear). The second part develops a mathematical model trying to put together some important constraints based on the abstraction for a general network. The third part deals with solution procedures; it converts the network to a matrix based system of equations, gives the characteristics of the matrix and suggests two solution procedures, one of them being a new one. The fourth part handles spatially distributed networks and evolves a number of decomposition techniques so that we can solve the problem with the help of a distributed computer system. Algorithms for parallel processors and spatially distributed systems have been described.There are a number of common features that pertain to networks. A network consists of a set of nodes and arcs. In addition at every node, there is a possibility of an input (like power, water, message, goods etc) or an output or none. Normally, the network equations describe the flows amoungst nodes through the arcs. These network equations couple variables associated with nodes. Invariably, variables pertaining to arcs are constants; the result required will be flows through the arcs. To solve the normal base problem, we are given input flows at nodes, output flows at nodes and certain physical constraints on other variables at nodes and we should find out the flows through the network (variables at nodes will be referred to as across variables).The optimization problem involves in selecting inputs at nodes so as to optimise an objective function; the objective may be a cost function based on the inputs to be minimised or a loss function or an efficiency function. The above mathematical model can be solved using Lagrange Multiplier technique since the equalities are strong compared to inequalities. The Lagrange multiplier technique divides the solution procedure into two stages per iteration. Stage one calculates the problem variables % and stage two the multipliers lambda. It is shown that the Jacobian matrix used in stage one (for solving a nonlinear system of necessary conditions) occurs in the stage two also.A second solution procedure has also been imbedded into the first one. This is called total residue approach. It changes the equality constraints so that we can get faster convergence of the iterations.Both solution procedures are found to coverge in 3 to 7 iterations for a sample network.The availability of distributed computer systems — both LAN and WAN — suggest the need for algorithms to solve the optimization problems. Two types of algorithms have been proposed — one based on the physics of the network and the other on the property of the Jacobian matrix. Three algorithms have been deviced, one of them for the local area case. These algorithms are called as regional distributed algorithm, hierarchical regional distributed algorithm (both using the physics properties of the network), and locally distributed algorithm (a multiprocessor based approach with a local area network configuration). The approach used was to define an algorithm that is faster and uses minimum communications. These algorithms are found to converge at the same rate as the non distributed (unitary) case.

Does Uncertainty Affect Investment and Labor Demand?

This paper analyzes the effect of uncertainty on investment and labor demand for Finnish firms during the time period 1987 – 2000. Utilizing a stock return based measure of uncertainty decomposed into systematic and idiosyncratic components, the results reveal that idiosyncratic uncertainty significantly reduces both investment and labor demand. Idiosyncratic uncertainty seems to influence investment in the current period, whereas the depressing effect on labor demand appears with a one-year lag. The results provide support that the depressing effect of idiosyncratic uncertainty on investment is stronger for small firms in comparison to large firms. Some evidence is reported regarding differential effects of uncertainty on labor demand conditional on firm characteristics. Most importantly, the depressing effect of lagged idiosyncratic uncertainty on labor demand tends to be stronger for diversified firms compared with focused firms.

Studies on the phase transitions in thiourea

Thiourea (CS(NH2)2) is one of the few examples of molecular crystals exhibiting ferroelectric properties. The dielectric constant along the ferroelectric axis [100] shows maxima at 169, 177 and 202 K. An inflection point occurs at 170.5 KZ Following Goldsmith and White the phases are named as I (F.E. below 169 K), II (A.F.E. 169 K

Affinity purification and characterization of 2,4-dichlorophenol hydroxylase from Pseudomonas cepacia

2,4-Dichlorophenol hydroxylase, a flavoprotein monooxygenase from Pseudomonas cepacia grown on 2,4-dichlorophenoxyacetic acid (2,4-D) as the sole source of carbon, was purified to homogeneity by a single-step affinity chromatography on 2,4-DCP-Sepharose CL-4B. The enzyme was eluted from the affinity matrix with the substrate 2,4-dichlorophenol. The enzyme has a molecular weight of 275,000 consisting of four identical subunits of molecular weight 69,000 and requires exogenous addition of FAD for its complete catalytic activity. The enzyme required an external electron donor NADPH for hydroxylation of 2,4-dichlorophenol to 3,5-dicholorocatechol. NADPH was preferred over NADH. The enzyme had Km value of 14 μImage for 2,4-dichlorophenol, and 100 μImage for NADPH. The enzyme activity was significantly inhibited by heavy metal ions like Hg2+ and Zn2+ and showed marked inhibition with thiol reagents. Trichlorophenols inhibited the enzyme competitively. The hydroxylase activity decreased as a function of increasing concentrations of Cibacron blue and Procion red dyes. The apoenzyme prepared showed complete loss of FAD when monitored spectrophotometrically and had no enzymatic activity. The inactive apoenzyme was reconstituted with exogenous FAD which completely restored the enzyme activity.

Crystal structure of hexanediamine-glutamic acid complex

Polyamines are some of the most important and ubiquitous small molecules that modulate several functions of plant, animal and bacterial cells. Despite the simplicity of their chemical structure, their specific interactions with other biomolecules cannot be explained solely on the basis of their electrostatic properties. To evolve a structural understanding on the specificity of these interactions it is necessary to determine the structure of complexes of polyamines with other, representative biomolecules. This paper reports the structure of the 1:2 complex of hexanediamine and L-glutamic acid. The complex crystallizes in the monoclonic space group P2(1) with a = 5.171(1) angstrom, b = 22.044(2) angstrom, c = 10.181(2) angstrom and beta = 104.51(1)-degrees. The structure was refined to an R factor of 6.6%. The structures of these complexes not only suggest the importance of hydrogen-bonding interactions of polyamines but also provide some insight into other complementary interactions probably important for the specificity of biomolecular interactions.

Low-Temperature Fluorination Of Some Nonmetals And Nonmetal Compounds With Fluorine

Low temperature fluorination with elemental fluorine of elemental phosphorus, sulphur, silicon, amorphous carbon and phosphorus trichloride, phosphorus pentoxide, triphenylphosphine, hexafluorodisilane, hexachlorodisilane, hexabromodisilane, tetrasulphur tetranitride, sulphur dioxide, thionyl chloride and sulphuryl chloride has been carried out in freon-11 medium. The corresponding fluoro compounds have been isolated in near quantitative yields, purified by low temperature fractional condensation and characterised by IR spectroscopy and elemental analysis.

Photoemission study of the high-Tc superconductor Bi1.8Pb0.4Sr2Ca2.2Cu3O10

Ultraviolet and X-ray photoemission spectroscopic (UPS and XPS) studies to characterize the electronic structure of bismuth cuprate superconductor with nominal composition of Bi1.8Pb0.4Sr2Ca2.2Cu3O10 have been carried out. The data clearly shows the metallic emission at the Fermi level (EF). The shoulder (-1.2 eV) near the EF is attributed to the Cu-O derived states. Cu satellite structures observed both in the UPS and XPS show the strongly correlated nature of the Cu 3d electrons. Core level shifts indicate that 3+ and 4+ are the main oxidation of Bi and Pb, respectively. The Pb core lines show two components indicating their inequivalent sites. Core level O 1s spectrum is deconvoluted to show the presence of structurally non-equivalent oxygen sites.

29Si NMR chemical shifts in silicates

29Si chemical shifts in a wide variety of silicates in crystalline, glassy and gel states have been related to a parameter, P, which takes into account the electronegativity and the structural description of the silicate units as well as the ionic potential of the modifier cation. The relation, δ(ppm)=28.4 [1−exp(−P)]−110.5, besides having predictive value, satisfactorily accounts for all the available chemical-shifts data on silicates and shows the right kind of limiting behaviour, with δ approaching the Q0 value at large P.

Macroscopic model of city traffic using bond graph modelling

Modelling of city traffic involves capturing of all the dynamics that exist in real-time traffic. Probabilistic models and queuing theory have been used for mathematical representation of the traffic system. This paper proposes the concept of modelling the traffic system using bond graphs wherein traffic flow is based on energy conservation. The proposed modelling approach uses switched junctions to model complex traffic networks. This paper presents the modelling, simulation and experimental validation aspects.

Synthetic and physicochemical studies of uranium complexes with semicarbazone and hydrazone

Uranyl complexes of two Schiff bases, semicarbazone and hydrazone containing OON donor atoms have been synthesized and characterized on the basis of NMR, IR and electronic spectral studies, conductance, magnetic susceptibility and thermogravimetric data. The 1H NMR spectrum of the semicarbazone complex shows low field signals due to OH, NH and ---CH=N groups at 10.23, 9.31 and 8.17 ppm, respectively. The aromatic protons appear in the range 7.74–7.40 ppm. On complexation with U(VI) the signals due to OH and NH disappear evidently due to their participation in coordination. The coordination number of the o-vanillin semicarbazone (oVSC) complex is 6 whereas, that of the o-vanillin isonicotinic acid hydrazone (oVINAH) complex is 8, in addition to the two oxygen atoms already bonded to U(VI) in each species. The thermograms show the presence of 3 and 2 water molecules in these complexes, respectively and the IR spectral data also support the above conclusion. Suitable structures have been assigned.

Component wave delineation of ECG by filtering in the Fourier domain

A complete solution to the fundamental problem of delineation of an ECG signal into its component waves by filtering the discrete Fourier transform of the signal is presented. The set of samples in a component wave is transformed into a complex sequence with a distinct frequency band. The filter characteristics are determined from the time signal itself. Multiplication of the transformed signal with a complex sinusoidal function allows the use of a bank of low-pass filters for the delineation of all component waves. Data from about 300 beats have been analysed and the results are highly satisfactory both qualitatively and quantitatively.

Controlled Diffusions with Constraints, II

We consider the ergodic control for a controlled nondegenerate diffusion when m other (m finite) ergodic costs are required to satisfy prescribed bounds. Under a condition on the cost functions that penalizes instability, the existence of an optimal stable Markov control is established by convex analytic arguments.