Multi-scale coarse-graining of diblock copolymer self-assembly: from monomers to ordered micelles

Starting from a microscopic lattice model, we investigate clustering, micellization and micelle ordering in semi-dilute solutions of AB diblock copolymers in a selective solvent. To bridge the gap in length scales, from monomers to ordered micellar structures, we implement a two-step coarse graining strategy, whereby the AB copolymers are mapped onto ``ultrasoft'' dumbells with monomer-averaged effective interactions between the centres of mass of the blocks. Monte Carlo simulations of this coarse-grained model yield clear-cut evidence for self-assembly into micelles with a mean aggregation number n of roughly 100 beyond a critical concentration. At a slightly higher concentration the micelles spontaneously undergo a disorder-order transition to a cubic phase. We determine the effective potential between these micelles from first principles.Comment: 4 pages, 4 figures, submitted to Phys. Rev. Lett

Variation in contents of crude protein and mineral elements in 32 cowpea (Vigna unguiculata (L.) Walp) accessions in Ghana

Thirty-two cowpea accessions were studied for variation in contents of protein and mineral nutrients (calcium, magnesium, potassium and sodium). Cowpea flour from 40 wholesome dried seeds of each accession was used for the analysis. The wet oxidation method was used to determine the content of mineral nutrients. Nitrogen content was determined by the Kjeldahl procedure. Protein content ranged from 16.35 to 27.27 per cent. Sodium content ranged from 90.53 to 91.30 ppm, and potassium content from 30.33 to 71.30 ppm. Similarly, values for magnesium and calcium ranged from 146.73 to 968.20 ppm and from 43.33 to 171.20 ppm, respectively. Percent crude protein correlated significantly positively with sodium and negatively with calcium. Magnesium was correlated significantly with potassium. Black seeds generally recorded the highest percent crude protein on the average, while cream seeds had the highest magnesium and calcium contents, respectively. Trente-deux accessions de dolique étaient étudiées pour la variation en teneurs de protéines et de nutriments minérales (le calcium). La farine de dolique de quarante graines saines séchés de chaque accession était utilisée pour l'analyse. La détermination de nutriments minérales était par la méthode d'oxydation humide. La teneur d'azote était déterminée par la procédure de Kjeldahl. Teneur de protéine variait entre 16.35 et 27.27 %. La teneur de sodium variait entre 90.53 et 91.30 ppm, la teneur de potassium variait entre 30.33 et 71.30 ppm. De la même façon les valeurs pour le magnésium et le calcium variaient respectivement entre 146.73 et 98.20 ppm et entre 43.33 et 171.20 ppm. Le pourcentage de protéine brute corrélait considérablement positivement avec sodium en négativement avec calcium. Le magnésium était corrélé considérablement avec le potassium. Les graines colorées noires enregistraient en général le plus élevé du pourcentage de protéine brute en moyenne, alors que les graines colorées crèmes avaient les teneurs de magnésium et de calcium les plus élevées respectivement. Ghana Journal of Agricultural Science Vol. 39 (1) 2006: pp. 83-8

Coarse-graining diblock copolymer solutions: a macromolecular version of the Widom-Rowlinson model

We propose a systematic coarse-grained representation of block copolymers, whereby each block is reduced to a single ``soft blob'' and effective intra- as well as intermolecular interactions act between centres of mass of the blocks. The coarse-graining approach is applied to simple athermal lattice models of symmetric AB diblock copolymers, in particular to a Widom-Rowlinson-like model where blocks of the same species behave as ideal polymers (i.e. freely interpenetrate), while blocks of opposite species are mutually avoiding walks. This incompatibility drives microphase separation for copolymer solutions in the semi-dilute regime. An appropriate, consistent inversion procedure is used to extract effective inter- and intramolecular potentials from Monte Carlo results for the pair distribution functions of the block centres of mass in the infinite dilution limit.Comment: To be published in mol.phys(2005

Why Spiking Neural Networks Are Efficient: A Theorem

Current artificial neural networks are very successful in many machine learning applications, but in some cases they still lag behind human abilities. To improve their performance, a natural idea is to simulate features of biological neurons which are not yet implemented in machine learning. One of such features is the fact that in biological neural networks, signals are represented by a train of spikes. Researchers have tried adding this spikiness to machine learning and indeed got very good results, especially when processing time series (and, more generally, spatio-temporal data). In this paper, we provide a theoretical explanation for this empirical success

The Effects of 50k Ultramarathon Running on Quadriceps Torque and Circulating Inflammatory Calprotectin

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Influence of solvent quality on polymer solutions: a Monte Carlo study of bulk and interfacial properties

The effect of solvent quality on dilute and semi-dilute regimes of polymers in solution is studied by means of Monte Carlo simulations. The equation of state, adsorptions near a hard wall, wall-polymer surface tension and effective depletion potentials are all calculated as a function of concentration and solvent quality. We find important differences between polymers in good and theta solvents. In the dilute regime, the physical properties for polymers in a theta solvent closely resemble those of ideal polymers. In the semi-dilute regime, however, significant differences are found.Comment: 10 pages, 13 figure

Beyond prejudice: Are negative evaluations the problem and is getting us to like one another more the solution?

publication-status: Acceptedtypes: ArticleThis is a post print version of an article published in Behavioral and Brain Sciences, 2012, 35 (6), pp 438-439 DOI: http://dx.doi.org/10.1017/S0140525X12001252 Copyright © Cambridge University Press 2012For most of the history of prejudice research, negativity has been treated as its emotional and cognitive signature, a conception that continues to dominate work on the topic. By this definition, prejudice occurs when we dislike or derogate members of other groups. Recent research, however, has highlighted the need for a more nuanced and ‘inclusive’ (Eagly 2004) perspective on the role of intergroup emotions and beliefs in sustaining discrimination. On the one hand, several independent lines of research have shown that unequal intergroup relations are often marked by attitudinal complexity, with positive responses such as affection and admiration mingling with negative responses such as contempt and resentment. Simple antipathy is the exception rather than the rule. On the other hand, there is mounting evidence that nurturing bonds of affection between the advantaged and the disadvantaged sometimes entrenches rather than disrupts wider patterns of discrimination. Notably, prejudice reduction interventions may have ironic effects on the political attitudes of the historically disadvantaged, decreasing their perceptions of injustice and willingness to engage in collective action to transform social inequalities. These developments raise a number of important questions. Has the time come to challenge the assumption that negative evaluations are inevitably the cognitive and affective hallmarks of discrimination? Is the orthodox concept of prejudice in danger of side-tracking, if not obstructing, progress towards social justice in a fuller sense? What are the prospects for reconciling a prejudice reduction model of change, designed to get people to like one another more, with a collective action model of change, designed to ignite struggles to achieve intergroup equality