Lower Bounds from State Space Relaxations for Concave Cost Network Flow Problems

In this paper we obtain Lower Bounds (LBs) to concave cost network flow problems. The LBs are derived from state space relaxations of a dynamic programming formulation, which involve the use of non-injective mapping functions guaranteing a reduction on the cardinality of the state space. The general state space relaxation procedure is extended to address problems involving transitions that go across several stages, as is the case of network flow problems. Applications for these LBs include: estimation of the quality of heuristic solutions; local search methods that use information of the LB solution structure to find initial solutions to restart the search (Fontes et al., 2003, Networks, 41, 221–228); and branch-and-bound (BB) methods having as a bounding procedure a modified version of the LB algorithm developed here, (see Fontes et al., 2005a). These LBs are iteratively improved by penalizing, in a Lagrangian fashion, customers not exactly satisfied or by performing state space modifications. Both the penalties and the state space are updated by using the subgradient method. Additional constraints are developed to improve further the LBs by reducing the searchable space. The computational results provided show that very good bounds can be obtained for concave cost network flow problems, particularly for fixed-charge problems.     

Synthesis of new azulene derivatives and study of their effect on lipid peroxidation and lipoxygenase activity

The relationship between free radicals and acute or chronic inflammation has been well established. We have previously reported the significant antioxidant activity of the natural azulene derivatives chamazulene and guaiazulene. Furthermore, some synthetic azulene analogues have been found to possess anti-inflammatory activity. In this investigation we report the synthesis of five 3-alkyl or 3-(hydroxy)alkylazulene-1-carboxylic acids and esters, from tropolone, via the corresponding furanone. The synthesised compounds were tested for their effect on the peroxidation of rat hepatic microsomal membrane lipids, applying the 2-thiobarbituric acid test. Their anti-inflammatory activity was evaluated in vitro by the offered inhibition of soybean lipoxygenase. All the tested molecules were found to inhibit lipid peroxidation by 100% at 1 mM. They were also found to considerably inhibit lipoxygenase activity. The above results are discussed in relation to the structure and physicochemical properties of the examined azulene derivatives.     

Antioxidant activity of novel indole derivatives and protection of the myocardial damage in rabbits

Novel indole derivatives containing a triazole moiety (1a-d, 2a-c) were synthesized as lead compounds with interesting pharmacological profiles. Their antioxidant activity was investigated on in vitro non-enzymatic rat hepatic microsomal lipid peroxidation. All compounds showed significant effect in the above assay. The effect depended mainly on the attachment position of the triazole moiety on the indole nucleus. The most potent antioxidant derivatives la, 1c and 1d were tested for their protective ability against the oxidative damage of the myocardium after ischemia-reperfusion, in male rabbits which were subjected to 30 min regional ischemia followed by reperfusion. The tested antioxidant compounds 1a, 1c and 1d were continuously infused for 30 min starting at 10th min of ischemia and lasted at 10th min of reperfusion. The concentration of malondialdehyde (MDA, a marker of lipid peroxidation) and hemodynamic parameters (blood pressure and heart rate) were measured in the baseline, at 20th min of the sustained ischemia, 1st and 20th min of reperfusion. It was found that the examined compounds la, 1c and 1d reduced significantly the level of MDA in rabbits under ischemia-reperfusion and proved to be promising substances for further evaluation of anti-ischemic properties.     

13C-nmr of carbonyl compounds 1. Stereodynamic behaviour of acyclic and cyclic dienones

The conformational mobility of a series of conjugated dienones is investigated by low-temperature NMR- and IR-spectroscopy and interpreted in terms of substituent effects.     

Amphiphilic gradient copolymers of 2‐methyl‐ and 2‐phenyl‐2‐oxazoline: self‐organization in aqueous media and drug encapsulation

Gradient (or pseudo‐diblock) copolymers were synthesized from 2‐methyl‐2‐oxazoline and 2‐phenyl‐2‐oxazoline monomer mixtures via cationic polymerization. The self‐assembling properties of these biocompatible gradient copolymers in aqueous solutions were investigated, in an effort to use the produced nanostructures as nanocarriers for hydrophobic pharmaceutical molecules. Dynamic and static light scattering as well as AFM measurements showed that the copolymers assemble in different supramolecular nanostructures (spherical micelles, vesicles and aggregates) depending on copolymer composition. Fluorescence spectroscopy studies revealed a microenvironment of unusually high polarity inside the nanostructures. This observation is related partly to the gradient structure of the copolymers. The polymeric nanostructures were stable with time. Their structural properties in different aqueous media—PBS buffer, RPMI solution—simulating conditions used in pharmacological/medicinal studies, have been also investigated and a composition dependent behavior was observed. Finally, the hydrophobic drug indomethacin was successfully encapsulated within the gradient copolymer nanostructures and the properties of the mixed aggregates were studied in respect to the initial copolymer assemblies. The produced aggregates encapsulating indomethacin showed a significant increase of their mass and size compared to original purely polymeric ones. © 2011 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2012     

Artificial Neural Networks in water analysis: Theory and applications

Artificial Neural Networks (ANNs) have seen an explosion of interest over the last two decades and have been successfully applied in all fields of chemistry and particularly in analytical chemistry. Inspired from biological systems and originated from the perceptron, i.e. a program unit that learns concepts, ANNs are capable of gradual learning over time and modelling extremely complex functions. In addition to the traditional multivariate chemometric techniques, ANNs are often applied for prediction, clustering, classification, modelling of a property, process control, procedural optimisation and/or regression of the obtained data. This paper aims at presenting the most common network architectures such as Multi-layer Perceptrons (MLPs), Radial Basis Function (RBF) and Kohonen's self-organisations maps (SOM). Moreover, back-propagation (BP), the most widespread algorithm used today and its modifications, such as quick-propagation (QP) and Delta-bar-Delta, are also discussed. All architectures correlate input variables to output variables through non-linear, weighted, parameterised functions, called neurons. In addition, various training algorithms have been developed in order to minimise the prediction error made by the network. The applications of ANNs in water analysis and water quality assessment are also reviewed. Most of the ANNs works are focused on modelling and parameters prediction. In the case of water quality assessment, extended predictive models are constructed and optimised, while variables correlation and significance is usually estimated in the framework of the predictive or classifier models. On the contrary, ANNs models are not frequently used for clustering/classification purposes, although they seem to be an effective tool. ANNs proved to be a powerful, yet often complementary, tool for water quality assessment, prediction and classification.     

QuEChERS and solid phase extraction methods for the determination of energy crop pesticides in soil,plant and runoff water matrices

QuEChERS and solid phase extraction (SPE) methods were applied for determining four herbicides (metazachlor, oxyfluorfen, quizalofop-p-ethyl, quinmerac) and one insecticide (α(±)-cypermethrin) in runoff water, soil, sunflower and oilseed rape plant matrices. Determination was performed using gas chromatography mass spectrometry (GC-MS), whereas high-pressure liquid chromatography mass spectrometry (HPLC-MS) was used for quinmerac. In all substrates linearity was evaluated using matrix-matched calibration samples at five concentration levels (50–1000 ng L^?1 for water, 5–500 μg kg^?1 for soil and 2.5–500 μg kg^?1 for sunflower or oilseed rape plant). Correlation coefficient was higher than 0.992 for all pesticides in all substrates. Acceptable mean recovery values were obtained for all pesticides in water (65.4–108.8%), soil (70.0–110.0%) and plant (66.1–118.6%), with intra- and inter-day RSD% below 20%. LODs were in the range of 0.250–26.6 ng L^?1 for water, 0.10–1.8 μg kg^?1 for soil and 0.15–2.0 μg kg^?1 for plants. The methods can be efficiently applied for field dissipation studies of the pesticides in energy crop cultivations.     

On the Rational Drug Design for Hypertension through NMR Spectroscopy

Antagonists of the AT1receptor (AT1R) are beneficial molecules that can prevent the peptide hormone angiotensin II from binding and activating the specific receptor causing hypertension in pathological states. This review article summarizes the multifaced applications of solid and liquid state high resolution nuclear magnetic resonance (NMR) spectroscopy in antihypertensive commercial drugs that act as AT1R antagonists. The 3D architecture of these compounds is explored through 2D NOESY spectroscopy and their interactions with micelles and lipid bilayers are described using solid state ¹³CP/MAS, ³¹P and ²H static solid state NMR spectroscopy. Due to their hydrophobic character, AT1R antagonists do not exert their optimum profile on the AT1R. Therefore, various vehicles are explored so as to effectively deliver these molecules to the site of action and to enhance their pharmaceutical efficacy. Cyclodextrins and polymers comprise successful examples of effective drug delivery vehicles, widely used for the delivery of hydrophobic drugs to the active site of the receptor. High resolution NMR spectroscopy provides valuable information on the physical-chemical forces that govern these drug:vehicle interactions, knowledge required to get a deeper understanding on the stability of the formed complexes and therefore the appropriateness and usefulness of the drug delivery system. In addition, it provides valuable information on the rational design towards the synthesis of more stable and efficient drug formulations.     

Shellability and higher Cohen-Macaulay connectivity of generalized cluster complexes

Let Φ be a finite root system of rank n and let m be a nonnegative integer. The generalized cluster complex Δ^m(Φ) was introduced by S. Fomin and N. Reading. It was conjectured by these authors that Δ^m(Φ) is shellable and by V. Reiner that it is (m + 1)-Cohen-Macaulay, in the sense of Baclawski. These statements are proved in this paper. Analogous statements are shown to hold for the positive part Δ₊^m(Φ) of Δ^m(Φ). An explicit homotopy equivalence is given between Δ₊^m(Φ) and the poset of generalized noncrossing partitions, associated to the pair (Φ, m) by D. Armstrong.