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     

MANAGING DISTRIBUTED COMPUTING Five Practices for Success

Management of distributed environments requires corporate IS managers to shift from being operators of a central utility to facilitators who can recognize the synergy among loosely related groups of users. Success depends on the development of new ways of visualizing and measuring the service delivery process.     

Simulation of magnetic component models in electric circuitsincluding dynamic thermal effects

It is essential in the simulation of power electronics applications to model magnetic components accurately. In addition to modeling the nonlinear hysteresis behavior, eddy currents and winding losses must be included to provide a realistic model. In practice the losses in magnetic components give rise to significant temperature increases which can lead to major changes in the component behavior. In this paper a model of magnetic components is presented which integrates a nonlinear model of hysteresis, electro-magnetic windings and thermal behavior in a single model for use in circuit simulation of power electronics systems. Measurements and simulations are presented which demonstrate the accuracy of the approach for the electrical, magnetic and thermal domains across a variety of operating conditions, including static thermal conditions and dynamic self heating     

Deposition of thin film silicon using the pulsed PECVD and HWCVD techniques

We report on the use of pulsed plasma-enhanced chemical vapor deposition (P-PECVD) technique and show that “state-of-the-art” amorphous silicon (a-Si:H) materials and solar cells can be produced at a deposition rate of up to 15 Å/s using a modulation frequency in the range 1–100 kHz. The approach has also been developed to deposit materials and devices onto large area, 30 cm×40 cm, substrates with thickness uniformity (<5%), and gas utilization rate (>25%). We have developed a new “hot wire” chemical vapor deposition (HWCVD) method and report that our new filament material, graphite, has so far shown no appreciable degradation even after deposition of 500 μm of amorphous silicon. We report that this technique can produce “state-of-the-art” a-Si:H and that a solar cell of p/i/n configuration exhibited an initial efficiency approaching 9%. The use of microcrystalline silicon (μc-Si) materials to produce low-cost stable solar cells is gaining considerable attention. We show that both of these techniques can produce thin film μc-Si, dependent on process conditions, with 1 1 1 and/or 2 2 0 orientations and with a grain size of approx. 500 A. Inclusion of these types of materials into a solar cell configuration will be discussed.     

What We Mean by Future-Proofing

Perhaps the most powerful claim that advocates of fiber can make,on top of the massive bandwidthfiber makes possible today, is that fiber is future-proof. That is, the fiber that is laid today can be upgraded so that the same strands of glass can carry massively more bandwidth in the future.     

Resource contention in shared-memory multiprocessors: A parameterized performance degradation model

A standard metric conventionally employed to compare the performance of different multiprocessor systems is speedup. Although providing a measure of the improvement in execution speed achievable on a system, this metric does not yield any insight into the factors responsible for limiting the potential improvement in speed. This paper studies the performance degradation in shared-memory multiprocessors as a result of contention for shared-memory resources. A replicate workload framework with a flexible mechanism for workload specification is proposed for measuring performance. Two normalized performance metrics—efficiency and overhead factor—are introduced to quantify the factors limiting performance and facilitate comparison across architectures. Finally, the proposed model is employed to measure and compare the performance of three contemporary shared-memory systems, with special emphasis on the newly released BBN Butterfly-II (TC2000), currently undergoing Beta test.