Pheromone specificity inEriocrania semipurpurella (Stephens) andE. sangii (Wood) (Lepidoptera: Eriocraniidae) based on chirality of semiochemicals

The fifth abdominal segment of femaleEriocrania semipurpurella (Stephens) andE. sangii (Wood) contains a pair of exocrine glands. Hexane extracts of this segment were prepared from both species and analyzed by gas chromatography with simultaneous flame ionization and electroantennographic detection (EAD). For both species, the EAD active peaks were identified as nonan-2-one, (Z)-6-nonen-2-one, and (Z)-6-nonen-2-ol by means of mass spectrometry and comparison of retention indices with those of synthetic standards. Enantiomeric separation of chiral alcohols from the female extracts was achieved by gas chromatographic analysis on a cyclodextrin column. InE. semipurpurella, a mixture of (2S,6Z)-nonen-2-ol and (2R,6Z)-nonen-2-ol (2: I) was found, whereas inE. sangii (2S,6Z)-nonen-2-ol was the predominant enantiomer and only traces of theR enantiomer were indicated by the antennal response. In field tests, a blend of the three compounds was not attractive to conspecific males. A subtractive assay showed that the alcohol in various enantiomeric mixtures was the only attractive compound, whereas addition of (Z)-6-nonen-2-one to the alcohol completely inhibited the attraction of both species. A trapping experiment including a wide range of ratios between theR andS enantiomers showed that baits containing 95–100% of theS enantiomer were attractive to maleE. sangii, whereas males ofE. semipurpurella were attracted to all tested ratios of the enantiomers. However, the response profiles of maleE. semipurpurella differed between populations from southern Sweden, south Finland, and the Kola Peninsula in Russia. In south Sweden males were maximally attracted to a racemic mixture of the alcohols. At the Kola PeninsulaE. semipurpurella was attracted to baits containing 95–100% of theR enantiomer. In south Finland all tested ratios between 0 and 100%R enantiomer trappedE. semipurpurella, but the trap catches appeared to be bimodally distributed with peaks around 15 and 70%R enantiomer. The trapping results suggest the existence of pheromone races or sibling species among the specimens identified asE. semipurpurella.Dedicated to Prof. H. J. Bestmann on the occasion of his 70th birthday.     

Synthesis of amphiphilic (meth)acrylates with oligo(ethylene glycol) and (or) oligo(propylene glycol) blocks by the esterification of (meth)acrylic acid

Thermoresponsive PEG-based (PEG stands polyethylene glycol) polymers are unique for use in medicine because of their low toxicity, good biocompatibility and biodegradability, but usually more hydrophobic and more toxic comonomers are used to adjust lower critical solution temperature (LCST). A convenient way to overcome this problem and to finely tune LCST is to use alkoxy oligo(ethylene glycol)- or alkoxy oligo(propylene glycol) (meth)acrylates as starting comonomers. Here we report on the conditions for the simple and affordable synthesis of methoxy oligo(propylene glycol) (meth)acrylate- and methoxy oligo(propylene glycol)-block-oligo(ethylene glycol) (meth)acrylate-based macromonomers with high yields (80%–98.7%) by the acid-catalyzed esterification of (meth)acrylic acid with alkoxy oligo(alkylene glycols) containing oligo(ethylene glycol) (OEG) and/or oligo(propylene glycol) (OPG) blocks. p-Toluene sulphonic acid (pTSA), alkyl(C₁₂–C₁₄)benzene sulfonic acid (ABSA) and H₂SO₄ were used as catalysts. It has been shown that pTSA and ABSA are practically the same in catalytic activity and are superior to sulfuric acid. The reaction orders with respect to catalyst was found to be close to 1 in all cases. It has been shown that the reaction is actually insensitive to the lengths of OEG and OPG blocks, as well as to the structure of the terminal alkyl group, while the esterification of acrylic acid (AA) proceeds much faster compared to methacrylic acid (MAA) one under the same conditions. The influence of temperature on the equilibrium conversions of alcohols was determined, which were found to be 89%–93% for the esterification of AA and 61%–86% for MAA in the temperature range of 60–120°C. A further increase in conversion was achieved by introducing an azeotropic agent (toluene), its optimal concentration was found to be 10%–15%.     

Monitoring the curing processes of epoxy oligomers with partially substituted polyethoxymetallosiloxanes by IR spectroscopy and thermomechanical analysis

In this work, the curing of «ED-20» epoxy resin with partially siloxy-substituted aluminum, iron, and zirconium siloxanes that we obtained previously was studied. The initial content of a metallosiloxane in the compositions was 5–50 wt% with respect to the resin. In all the cases, thermal curing was used to obtain a series of samples in the form of solid homogeneous materials. The fact of the epoxy ring opening in the resin was confirmed by IR spectroscopy. The catalytic properties of the metal atom in a metallosiloxane were found to affect the curing process. The samples demonstrate rather a high resistance to thermooxidative destruction, and in most cases, their glass transition temperatures are lower than those obtained upon standard curing of «ED-20» resin with triethylenetetramine. Partially siloxy-substituted metalloalkoxysiloxanes can be efficient agents for curing and formation of a hybrid material based on epoxy resins.     

Rollout sampling approximate policy iteration

Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervised learning problem. This paper proposes variants of an improved policy iteration scheme which addresses the core sampling problem in evaluating a policy through simulation as a multi-armed bandit machine. The resulting algorithm offers comparable performance to the previous algorithm achieved, however, with significantly less computational effort. An order of magnitude improvement is demonstrated experimentally in two standard reinforcement learning domains: inverted pendulum and mountain-car.     

On the correspondence from Bayesian log-linear modelling to logistic regression modelling with <Emphasis Type="Italic">g</Emphasis>-priors

Consider a set of categorical variables where at least one of them is binary. The log-linear model that describes the counts in the resulting contingency table implies a specific logistic regression model, with the binary variable as the outcome. Within the Bayesian framework, the g-prior and mixtures of g-priors are commonly assigned to the parameters of a generalized linear model. We prove that assigning a g-prior (or a mixture of g-priors) to the parameters of a certain log-linear model designates a g-prior (or a mixture of g-priors) on the parameters of the corresponding logistic regression. By deriving an asymptotic result, and with numerical illustrations, we demonstrate that when a g-prior is adopted, this correspondence extends to the posterior distribution of the model parameters. Thus, it is valid to translate inferences from fitting a log-linear model to inferences within the logistic regression framework, with regard to the presence of main effects and interaction terms.     

A global piecewise smooth Newton method for fast large-scale model predictive control

In this paper, the strictly convex quadratic program (QP) arising in model predictive control (MPC) for constrained linear systems is reformulated as a system of piecewise affine equations. A regularized piecewise smooth Newton method with exact line search on a convex, differentiable, piecewise-quadratic merit function is proposed for the solution of the reformulated problem. The algorithm has considerable merits when applied to MPC over standard active set or interior point algorithms. Its performance is tested and compared against state-of-the-art QP solvers on a series of benchmark problems. The proposed algorithm is orders of magnitudes faster, especially for large-scale problems and long horizons. For example, for the challenging crude distillation unit model of Pannocchia, Rawlings, and Wright (2007) with 252 states, 32 inputs, and 90 outputs, the average running time of the proposed approach is 1.57 ms.     

Volumetric Curved Planar Reformation for virtual endoscopy

Curved Planar Reformation (CPR) has proved to be a practical and widely used tool for the visualization of curved tubular structures within the human body. It has been useful in medical procedures involving the examination of blood vessels and the spine. However, it is more difficult to use it for large, tubular, structures such as the trachea and the colon because abnormalities may be smaller relative to the size of the structure and may not have such distinct density and shape characteristics. Our new approach improves on this situation by using volume rendering for hollow regions and standard CPR for the surrounding tissue. This effectively combines gray scale contextual information with detailed color information from the area of interest. The approach is successfully used with each of the standard CPR types and the resulting images are promising as an alternative to virtual endoscopy. Because the CPR and the volume rendering are tightly coupled, the projection method used has a significant effect on properties of the volume renderer, such as distortion and isometry. We describe and compare the different CPR projection methods and how they affect the volume rendering process. A version of the algorithm is also presented which makes use of importance driven techniques; this ensures the users attention is always focused on the area of interest and also improves the speed of the algorithm.     

Correlating burst events on streaming stock market data

We address the problem of monitoring and identification of correlated burst patterns in multi-stream time series databases. We follow a two-step methodology: first we identify the burst sections in our data and subsequently we store them for easy retrieval in an efficient in-memory index. The burst detection scheme imposes a variable threshold on the examined data and takes advantage of the skewed distribution that is typically encountered in many applications. The detected bursts are compacted into burst intervals and stored in an interval index. The index facilitates the identification of correlated bursts by performing very efficient overlap operations on the stored burst regions. We present the merits of the proposed indexing scheme through a thorough analysis of its complexity. We also manifest the real-time response of our burst indexing technique, and demonstrate the usefulness of the approach for correlating surprising volume trading events using historical stock data of the NY stock exchange. While the focus of this work is on financial data, the proposed methods and data-structures can find applications for anomaly or novelty detection in telecommunication, network traffic and medical data.