Direct versus indirect sexual selection: genetic basis of colour, size and recruitment in a wild bird

Indirect and direct models of sexual selection make different predictions regarding the quantitative genetic relationships between sexual ornaments and fitness. Indirect models predict that ornaments should have a high heritability and that strong positive genetic covariance should exist between fitness and the ornament. Direct models, on the other hand, make no such assumptions about the level of genetic variance in fitness and the ornament, and are therefore likely to be more important when environmental sources of variation are large. Here we test these predictions in a wild population of the blue tit (Parus caeruleus), a species in which plumage coloration has been shown to be under sexual selection. Using 3 years of cross-fostering data from over 250 breeding attempts, we partition the covariance between parental coloration and aspects of nestling fitness into a genetic and environmental component. Contrary to indirect models of sexual selection, but in agreement with direct models, we show that variation in coloration is only weakly heritable (h(2) < 0.11), and that two components of offspring fitness-nestling size and fledgling recruitment-are strongly dependent on parental effects, rather than genetic effects. Furthermore, there was no evidence of significant positive genetic covariation between parental colour and offspring traits. Contrary to direct benefit models, however, we find little evidence that variation in colour reliably indicates the level of parental care provided by either males or females. Taken together, these results indicate that the assumptions of indirect models of sexual selection are not supported by the genetic basis of the traits reported on here.

Chemical composition and in vitro fermentation of tannin-rich tree fruits

Dry and mature tree fruits are a potential source of protein for goats in the semi-arid areas of southern Africa, but their chemical composition and feeding value is largely unknown. This study presents the chemical composition and in vitro fermentation of indehiscent whole fruits and separated seed and hull fractions from Acacia nilotica, Acacia erubescens, Acacia sieberiana, Acacia erioloba, Piliostigma thonningii and Dichrostachys cinerea trees. Results indicate that the N contents of whole fruits ranged between 13.5 g/kg DM (A. nilotica) and 27.1 g/kg DM (A. erubescens). Seeds had a higher N content than hulls for all tree species. A. nilotica, D. cinerea and P thonningii fruits had high levels of extractable phenolics (758, 458 and 299 g/kg DM, respectively). Soluble phenolics (SPh) and ytterbium precipitable phenolics (YbPh) levels were negatively correlated to in vitro gas production but positively correlated to in vitro organic matter degradability (iOMD). Partition factors for whole fruits at 48 h ranged between 3.6 mg/ml for A. erioloba and 7.8 mg/ml for A. nilotica. Seeds of A. erioloba, A. erubescens and P thonningii were consistently fermented more efficiently throughout the incubation period compared to their whole fruits or hulls. Estimating in vitro degradability of phenolic-rich substrates through filtration procedures can give erroneous results due to the loss of soluble phenolics, which are not necessarily degradable. The feeding value of fruits from D. cinerea and A. nilotica tree species may be reduced due to the presence of high levels of phenolics. (C) 2007 Elsevier B.V. All rights reserved.

Modelling 2,4-dichlorophenol bioavailability and bioaccumulation by the freshwater fingernail clam Sphaerium corneum using artificial particles and humic acids

The complex and variable composition of natural sediments makes it very difficult to predict the bioavailability and bioaccumulation of sediment-bound contaminants. Several approaches have been proposed to overcome this problem, including an experimental model using artificial particles with or without humic acids as a source of organic matter. For this work, we have applied this experimental model, and also a sample of a natural sediment, to investigate the uptake and bioaccumulation of 2,4-dichlorophenol (2,4-DCP) by Sphaerium corneum. Additionally, the particle-water partition coefficients (K-d) were calculated. The results showed that the bioaccumulation of 2,4-DCP by clams did not depend solely on the levels of chemical dissolved, but also on the amount sorbed onto the particles and the characteristics and the strength of that binding. This study confirms the value of using artificial particles as a suitable experimental model for assessing the fate of sediment-bound contaminants. (c) 2006 Elsevier Ltd. All rights reserved.

Analysis of shade and temperature effects on assimilate partitioning in the everbearing strawberry 'Everest' as the basis for optimised long-season fruit production

Growth patterns and cropping were evaluated over the season for the everbearing strawberry 'Everest' at a range of temperatures (15-27degreesC) in two light environments (ambient and 50% shade). The highest yield was recorded for unshaded plants grown at 23degreesC, but the optimum temperature for vegetative growth was 15degreesC. With increasing temperature fruit number increased, but fruit weight decreased. Fruit weight was also significantly reduced by shade, and although 'Everest' showed a degree of shade tolerance in vegetative growth, yield was consistently reduced by shade. Shade also reduced the number of crowns developed by the plants over the course of the season, emphasising that crown number was ultimately the limiting factor for yield potential. We conclude that, in contrast to Junebearers which partition more assimilates to fruit at temperatures around 15degreesC (Le Miere et al., 1998), optimised cropping in the everbearer 'Everest' is achieved at the significantly higher temperature of 23degreesC. These findings have significance for commercial production, in which protection tends to reduce light levels but increase average temperature throughout the season.

High-affinity small molecule-phospholipid complex formation: Binding of siramesine to phosphatidic acid

Siramesine (SRM) is a sigma-2 receptor agonist which has been recently shown to inhibit growth of cancer cells. Fluorescence spectroscopy experiments revealed two distinct binding sites for this drug in phospholipid membranes. More specifically, acidic phospholipids retain siramesine on the bilayer surface due to a high-affinity interaction, reaching saturation at an apparent 1:1 drug-acidic phospholipid stoichiometry, where after the drug penetrates into the hydrocarbon core of the membrane. This behavior was confirmed using Langmuir films. Of the anionic phospholipids, the highest affinity, comparable to the affinities for the binding of small molecule ligands to proteins, was measured for phosphatidic acid (PA, mole fraction Of X-PA = 0.2 in phosphatidylcholine vesicles), yielding a molecular partition coefficient of 240 +/- 80 x 10(6). An MD simulation on the siramesine:PA interaction was in agreement with the above data. Taking into account the key role of PA as a signaling molecule promoting cell growth our results suggest a new paradigm for the development of anticancer drugs, viz. design of small molecules specifically scavenging phospholipids involved in the signaling cascades controlling cell behavior.

Composite nanoparticles

The method of measuring the partition coefficient of a test molecule comprises incorporating the molecule in a composition of nanoparticles having a porous surface and a first solvent, wherein a second solvent has been absorbed into the porous surface, and said first solvent is immiscible with said second solvent, and then separating the nanoparticles and the first solvent. The amount of the molecule which remains in the first solvent is determined to enable calculation of the partition coefficient. The nanoparticles may have a magnetic core to allow easy separation.

Effect of internal partitioning on indoor air quality of rooms with mixing ventilation - basic study

The internal partitioning, which is frequently introduced in open-space planning due to its flexibility, was tested to study its effects on the room air quality as well as ventilation performance. For the study, physical tests using a small model room and numerical modeling using CFD computation were utilized to evaluate different test conditions employing mixing ventilation from the ceiling. The partition parameters, such as its location, height, and the gap underneath, as well as contaminant source location were tested under isothermal conditions. This paper summarizes the results from the study.

Antioxidant properties of Teaw (Cratoxylum formosum Dyer) extract in soybean oil and emulsions

The antioxidant activity of an extract from Teaw (Cratoxylum formosum Dyer) leaves was studied in soybean oil and soybean oil-in-water emulsions. Samples containing the extract or reference antioxidants including chlorogenic acid, which comprises 60% of the Teaw extract, were stored at 60 degrees C and analyzed periodically for peroxide value (PV) and thiobarbituric acid reactive substances (TBARS) to allow both hydroperoxides and hydroperoxide degradation products to be monitored. Chlorogenic acid and the Teaw extract were more effective than a-tocopherol in inhibiting lipid oxidation in bulk oil but were less effective in an oil-in-water emulsion in accordance with the polar paradox. The PV/TBARS ratio for oil samples containing chlorogenic acid was higher than for alpha-tocopherol and BHT because chlorogenic acid inhibits both hydroperoxide formation by radical scavenging and hydroperoxide decomposition by metal chelation. The importance of the metal-chelating activity in retarding hydroperoxide decomposition was confirmed by studying the decomposition of oil samples containing added ferric ions. The PV/TBARS ratio was higher for citric acid than for (x-tocopherol in the presence of added ferric chloride, but the order was reversed in samples lacking ferric chloride. Samples containing added chlorogenic acid gave the highest PV/TBARS ratios both in the presence and absence of ferric ions. The PV/TBARS ratios for the samples containing antioxidants fell rapidly to lower values in a soybean oil-in-water emulsion than in the soybean oil. This was due to increased hydroperoxide decomposition in the emulsion at the same PV. The Teaw extract contained 12% oil-soluble components, which contributed to a slightly higher oil-water partition coefficient than that of chlorogenic acid. The antioxidant activity of the aqueous phase of the Teaw extract was reduced more than that of chlorogenic acid by partitioning of the oil-soluble components into oil, which showed that the less-polar components contributed to the antioxidant activity of the Teaw extract in aqueous media.

Drug interaction and location in liposomes: correlation with polar surface areas

An important step in liposome characterization is to determine the location of a drug within the liposome. This work thus investigated the interaction of dipalmitoylphosphatidylcholine liposomes with drugs of varied water solubility, polar surface area (PSA) and partition coefficient using high sensitivity differential scanning calorimetry. Lipophilic estradiol (ES) interacted strongest with the acyl chains of the lipid membrane, followed by the somewhat polar 5-fluorouracil (5-FU). Strongly hydrophilic mannitol (MAN) showed no evidence of interaction but water soluble polymers inulin (IN) and an antisense oligonucleotide (OLG), which have very high PSAs, interacted with the lipid head groups. Accordingly, the drugs could be classified as: hydrophilic ones situated in the aqueous core and which may interact with the head groups; those located at the water-bilayer interface with some degree of penetration into the lipid bilayer; those lipophilic drugs constrained within the bilayer. (c) 2004 Elsevier B.V. All rights reserved.

Contextual emergence of mental states from neurodynamics

The emergence of mental states from neural states by partitioning the neural phase space is analyzed in terms of symbolic dynamics. Well-defined mental states provide contexts inducing a criterion of structural stability for the neurodynamics that can be implemented by particular partitions. This leads to distinguished subshifts of finite type that are either cyclic or irreducible. Cyclic shifts correspond to asymptotically stable fixed points or limit tori whereas irreducible shifts are obtained from generating partitions of mixing hyperbolic systems. These stability criteria are applied to the discussion of neural correlates of consiousness, to the definition of macroscopic neural states, and to aspects of the symbol grounding problem. In particular, it is shown that compatible mental descriptions, topologically equivalent to the neurodynamical description, emerge if the partition of the neural phase space is generating. If this is not the case, mental descriptions are incompatible or complementary. Consequences of this result for an integration or unification of cognitive science or psychology, respectively, will be indicated.

Finite- N effects for ideal polymer chains near a flat impenetrable wall

This paper addresses the statistical mechanics of ideal polymer chains next to a hard wall. The principal quantity of interest, from which all monomer densities can be calculated, is the partition function, G N(z) , for a chain of N discrete monomers with one end fixed a distance z from the wall. It is well accepted that in the limit of infinite N , G N(z) satisfies the diffusion equation with the Dirichlet boundary condition, G N(0) = 0 , unless the wall possesses a sufficient attraction, in which case the Robin boundary condition, G N(0) = - x G N ′(0) , applies with a positive coefficient, x . Here we investigate the leading N -1/2 correction, D G N(z) . Prior to the adsorption threshold, D G N(z) is found to involve two distinct parts: a Gaussian correction (for z <~Unknown control sequence '\lesssim' aN 1/2 with a model-dependent amplitude, A , and a proximal-layer correction (for z <~Unknown control sequence '\lesssim' a described by a model-dependent function, B(z).

Baroclinic waves with parameterized effects of moisture interpreted using Rossby wave components

A theoretical framework is developed for the evolution of baroclinic waves with latent heat release parameterized in terms of vertical velocity. Both wave–conditional instability of the second kind (CISK) and large-scale rain approaches are included. The new quasigeostrophic framework covers evolution from general initial conditions on zonal flows with vertical shear, planetary vorticity gradient, a lower boundary, and a tropopause. The formulation is given completely in terms of potential vorticity, enabling the partition of perturbations into Rossby wave components, just as for the dry problem. Both modal and nonmodal development can be understood to a good approximation in terms of propagation and interaction between these components alone. The key change with moisture is that growing normal modes are described in terms of four counterpropagating Rossby wave (CRW) components rather than two. Moist CRWs exist above and below the maximum in latent heating, in addition to the upper- and lower-level CRWs of dry theory. Four classifications of baroclinic development are defined by quantifying the strength of interaction between the four components and identifying the dominant pairs, which range from essentially dry instability to instability in the limit of strong heating far from boundaries, with type-C cyclogenesis and diabatic Rossby waves being intermediate types. General initial conditions must also include passively advected residual PV, as in the dry problem.

Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Optimal piecewise locally linear modeling

Associative memory networks such as Radial Basis Functions, Neurofuzzy and Fuzzy Logic used for modelling nonlinear processes suffer from the curse of dimensionality (COD), in that as the input dimension increases the parameterization, computation cost, training data requirements, etc. increase exponentially. Here a new algorithm is introduced for the construction of a Delaunay input space partitioned optimal piecewise locally linear models to overcome the COD as well as generate locally linear models directly amenable to linear control and estimation algorithms. The training of the model is configured as a new mixture of experts network with a new fast decision rule derived using convex set theory. A very fast simulated reannealing (VFSR) algorithm is utilized to search a global optimal solution of the Delaunay input space partition. A benchmark non-linear time series is used to demonstrate the new approach.

Data based constructive identification - overcoming the curse of dimensionality

The modelling of a nonlinear stochastic dynamical processes from data involves solving the problems of data gathering, preprocessing, model architecture selection, learning or adaptation, parametric evaluation and model validation. For a given model architecture such as associative memory networks, a common problem in non-linear modelling is the problem of "the curse of dimensionality". A series of complementary data based constructive identification schemes, mainly based on but not limited to an operating point dependent fuzzy models, are introduced in this paper with the aim to overcome the curse of dimensionality. These include (i) a mixture of experts algorithm based on a forward constrained regression algorithm; (ii) an inherent parsimonious delaunay input space partition based piecewise local lineal modelling concept; (iii) a neurofuzzy model constructive approach based on forward orthogonal least squares and optimal experimental design and finally (iv) the neurofuzzy model construction algorithm based on basis functions that are Bézier Bernstein polynomial functions and the additive decomposition. Illustrative examples demonstrate their applicability, showing that the final major hurdle in data based modelling has almost been removed.