Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

Hydrogen annealing effect on DC and low-frequency noise characteristics in CMOS FinFETs

The hydrogen annealing process has been used to improve surface roughness of the Si-fin in CMOS FinFETs for the first time. Hydrogen annealing was performed after Si-fin etch and before gate oxidation. As a result, increased saturation current with a lowered threshold voltage and a decreased low-frequency noise level over the entire range of drain current have been attained. The low-frequency noise characteristics indicate that the oxide trap density is reduced by a factor of 3 due to annealing. These results suggest that hydrogen annealing is very effective for improving device performance and for attaining a high-quality surface of the etched Si-fin.     

The postmodernity of football hooliganism

By using a 'cultural' definition of 'postmodernism' (derived from Jameson and Martin) in which postmodernism is regarded as the transgression of modern boundaries, this article traces the emergence of postmodern aspects to violent male fandom at football games since the 1960s. It is argued that at games, male fans have created imaginary masculine and national boundaries by which they have affirmed their identities but that in fighting they have sought to breach these boundaries in postmodern fashion.     

Area- and time-specific marginal capacity costs of electricity distribution

Marginal costs of electricity vary by time and location. In the past, researchers attributed the variations to factors related to electricity generation and transmission. These authors, however, have not analyzed possible variations in marginal distribution capacity costs (MDCC). The objectives of this paper are:

1. (i) to show that large MDCC variations are due to the dispersion in distribution capital expenditures by time and space,

2. (ii) to propose a method for quantifying the area- and time-specific MDCC in the presence of lumpy investments, and

3. (iii) to compare our MDCC estimates to those commonly used in the electric utility industry.

Our proposed method and its results were adopted by the California Public Utilities Commission (CPUC) in 1992 for Pacific Gas and Electric Company (PG&E), the largest privately owned electric utility in the U.S.     

Aortic valve papillary fibroelastoma. A diagnosis by transthoracic echocardiography

Cardiac papillary fibroelastomas are unusual, frond-like growths typically found on cardiac valves, diagnosed incidentally on autopsy or cardiac surgery, but rarely during life. We report a rare case of an aortic valve papillary fibroelastoma detected by transthoracic echocardiography and confirmed by histologic study.