The logic of ideas in Christopher Hill's English revolution

This article examines the role played by ideas and their thinkers in Christopher Hill's histories of the English Revolution. Hill protested against a reductionist economic determinism with no place for the intrinsic power of ideas, but his account of ideas gave them a progressive logic parallel to, if not always easy to link with, that of economic development, and threatened to divorce them from their muddled and imperfect thinkers. This account of the logic of ideas had a striking impact on the way in which the more mainstream radicals of the English Revolution appeared in Hill's work, with both the Levellers and James Harrington being half assimilated to, and half pushed aside in favor of, the more thoroughgoing economic radicals who expressed, in however ragged a way, the intrinsic potential of their ideas. However, Hill's writings also betray a surprising attraction to religious over secular forms of radicalism.

Aesthetical and narrative uses of the trench in the Hollywood cinema of 1918-1930

Throughout history of painting, the representation of landscape has been considered a laboratory for the human gaze on the world. The First World War and its new approach to the battlefield altered deeply the classical forms of representation, and replaced them with a mechanised and fragmentary vision, which was related with the development of photography and cinema. As Vicente J. Benet has analysed, Hollywod cinema used these deep changes in its filmic versions of the conflict, although it organised them following a narrative logic. In this text we intend to study how the battlefield and, particularly, the trench, are inserted in this logic of the history of landscape painting. We do so through some Hollywood films from the period 1918-1930. Firstly, we approach the trench as a composition value which can structure the image and guide the camera movement. In the second place, we study how it creates a dialog between its inside, melodrama scenery, and the outside, battlefield and danger. In both cases, we conclude that the trench as a form and as a narrative element plays a structuring and integrative role with the storytelling logic.

Complement 4 phenotypes and genotypes in Brazilian patients with classical 21-hydroxylase deficiency

The aim of this work was to analyse C4 genotypes, C4 protein levels, phenotypes and genotypes in patients with the classical form of 21-hydroxylase deficiency. Fifty-four patients from 46 families (36 female, 18 male; mean age 10.8 years) with different clinical manifestations (31 salt-wasting; 23 simple-virilizing) were studied. Taq I Southern blotting was used to perform molecular analysis of the C4/CYP21 gene cluster and the genotypes were defined according to gene organization within RCCX modules. Serum C4 isotypes were assayed by enzyme-linked immunosorbent assay. The results revealed 12 different haplotypes of the C4/CYP21 gene cluster. Total functional activity of the classical pathway (CH50) was reduced in individuals carrying different genotypes because of low C4 concentrations (43% of all patients) to complete or partial C4 allotype deficiency. Thirteen of 54 patients presented recurrent infections affecting the respiratory and/or the urinary tracts, none of them with severe infections. Low C4A or C4B correlated well with RCCX monomodular gene organization, but no association between C4 haplotypes and recurrent infections or autoimmunity was observed. Considering this redundant gene cluster, C4 seems to be a well-protected gene segment along the evolutionary process.

A hybrid approach to learn with imbalanced classes using evolutionary algorithms

There is an increasing interest in the application of Evolutionary Algorithms (EAs) to induce classification rules. This hybrid approach can benefit areas where classical methods for rule induction have not been very successful. One example is the induction of classification rules in imbalanced domains. Imbalanced data occur when one or more classes heavily outnumber other classes. Frequently, classical machine learning (ML) classifiers are not able to learn in the presence of imbalanced data sets, inducing classification models that always predict the most numerous classes. In this work, we propose a novel hybrid approach to deal with this problem. We create several balanced data sets with all minority class cases and a random sample of majority class cases. These balanced data sets are fed to classical ML systems that produce rule sets. The rule sets are combined creating a pool of rules and an EA is used to build a classifier from this pool of rules. This hybrid approach has some advantages over undersampling, since it reduces the amount of discarded information, and some advantages over oversampling, since it avoids overfitting. The proposed approach was experimentally analysed and the experimental results show an improvement in the classification performance measured as the area under the receiver operating characteristics (ROC) curve.

The Stern-Gerlach Phenomenon According to Classical Electrodynamics

We present a description of the Stem-Gerlach type experiments using only the concepts of classical electrodynamics and the Newton`s equations of motion. The quantization of the projections of the spin (or the projections of the magnetic dipole) is not introduced in our calculations. The main characteristic of our approach is a quantitative analysis of the motion of the magnetic atoms at the entrance of the magnetic field region. This study reveals a mechanism which modifies continuously the orientation of the magnetic dipole of the atom in a very short time interval, at the entrance of the magnetic field region. The mechanism is based on the conservation of the total energy associated with a magnetic dipole which moves in a non uniform magnetic field generated by an electromagnet. A detailed quantitative comparison with the (1922) Stem-Gerlach experiment and the didactical (1967) experiment by J.R. Zacharias is presented. We conclude, contrary to the original Stern-Gerlach statement, that the classical explanations are not ruled out by the experimental data.

Classical simulation of deposition of thiophene oligomers on TiO(2)-anatase: Relevance of long-range electrostatic interactions

We performed classical molecular dynamics simulations of the vapor-deposition of alpha-T4 oligomers on the TiO(2)-anatase (101) surface, comparing different sets of charges associated with the atoms of the model. The potential energy surfaces for alpha-T4 and TiO(2) were described by re-parametrizations of the Universal force field with charges given by the charge equilibration (QEq) scheme, or with fixed charges obtained by an ab initio method using the Hirshfeld partition. The two sets of charges lead to completely different results for the interface formation, and for the characteristics of the organic film, with a clearly defined alpha-T4 contact layer in the QEq case, and a more homogeneous molecular distribution when using Hirshfeld charges. The main reason for the discrepancy was found to be the incorrect charge assignment given by QEq to the sulfur and alpha-carbon atoms in thiophenes, and highlight the relevance of long-range interactions in the organization of molecular films. (C) 2009 Elsevier B.V. All rights reserved.

Classical strings in AdS(4) x CP(3) with three angular momenta

In this paper, rotating strings in three directions of AdS(4) x CP(3) geometry are studied; its divergent energy limit, and conserved charges are also determined. An interpretation of these configurations as either giant magnons or spiky strings is discussed.

Ground-state energy of a classical artificial molecule

We study the ground-state energy of a classical artificial molecule formed by two-dimensional clusters (artificial atoms) of N/2 charged particles separated by a distance d. For the small molecules of N = 2 and 4, we obtain analytical expressions for this energy. For the larger ones, we calculate the ground-state energy using molecular dynamics simulation for N up to 128. From our numerical results, we are able to find out a function to approximate the ground-state energy of the molecules covering the range from atoms to molecules for any inter-atom distance d and for particle number from N = 8 to 128 within a difference less than one percent from the MD data.

Classical and hologram QSAR studies on a series of inhibitors of trypanosomatid Glyceraldehyde-3-Phosphate Dehydrogenase

Leishmaniasis and trypanosomiasis are major causes of morbidity and mortality in both tropical and subtropical regions of the world. The current available drugs are limited, ineffective, and require long treatment regimens. Due to the high dependence of trypanosomatids on glycolysis as a source of energy, some glycolytic enzymes have been identified as attractive targets for drug design. In the present work, classical Two-Dimensional Quantitative Structure -Activity Relationships (2D QSAR) and Hologram QSAR (HQSAR) studies were performed on a series of adenosine derivatives as inhibitors of Leishmania mexicana Glyceraldehyde-3-Phosphate Dehydrogenase (LmGAPDH). Significant correlation coefficients (classical QSAR, r(2)=0.83 and q(2) =0.81; HQSAR, r(2)=0.91 and q(2) =0.86) were obtained for the 56 training set compounds, indicating the potential of the models for untested compounds. The models were then externally validated using a test set of 14 structurally related compounds and the predicted values were in good agreement with the experimental results (classical QSAR, r(pred)(2) = 0.94; HQSAR, r(pred)(2) = 0.92).

Fragment-based and classical quantitative structure-activity relationships for a series of hydrazides as antituberculosis agents

Worldwide, tuberculosis (TB) is the leading cause of death among curable infectious diseases. Multidrug-resistant Mycobacterium tuberculosis is an emerging problem of great importance to public health, and there is an urgent need for new anti-TB drugs. In the present work, classical 2D quantitative structure-activity relationships (QSAR) and hologram QSAR (HQSAR) studies were performed on a training set of 91 isoniazid derivatives. Significant statistical models (classical QSAR, q(2) = 0.68 and r(2) = 0.72; HQSAR, q(2) = 0.63 and r(2) = 0.86) were obtained, indicating their consistency for untested compounds. The models were then used to evaluate an external test set containing 24 compounds which were not included in the training set, and the predicted values were in good agreement with the experimental results (HQSAR, r(pred)(2) = 0.87; classical QSAR, r(pred)(2) = 0.75).