R.F. diode sputtering in permanent-match mode

A constans-voltage r.f. diode sputtering set incorporating a self-excited oscillator was designed. The variable discharge impedance was stabilized, as seen from the r.f. generator output, by suitable capacitive discharge shunting combined with a rather tight coupling to the generator. A conventional r.f. power oscillator of the Colpitt type was used and, as the loading of the oscillator by the discharge and its associated electrical network was essentially constant, there was no need for an impedance matching network or voltage-and/or power-controlling servosystems to assure stable operation of the equipment.For bias sputtering, the variation in the substrate holder voltage was established by variation of the mutual inductance to the bias circuit which allows the bias voltage to be operated in phase or 180° out of phase with respect to the target voltage. The r.f. generator had a line-modulated power supply; its influence on the accelerating voltages governing sputtering was considered and the ion energy distribution was studied. The operation of the equipment is illustrated by refractive index results obtained in TiO₂ films deposited by in-phase and inverse-phase bias sputtering.     

Entrainment in a disaggregated economic long wave model

This paper investigates how mode-locking and other nonlinear dynamic phenomena arise through the interaction of two capital-producing sectors in a disaggregated economic long wave model. Each sector in isolation produces a self-sustained oscillation with a period and amplitude determined by the characteristics of that sector. However, the sectors interact through their mutual dependence on each other's output for their own production. When this coupling is accounted for, the two sectors tend to synchronize or lock together with a rational proportion between the periods. While keeping the aggregate equilibrium characteristics of the system constant, we study how this locking occurs as a function of the difference in capital lifetimes and as a function of the strength of the coupling between the sectors. Besides mode-locking and quasi-periodic behavior, the observed phenomena include cascades of period-doubling bifurcations, chaos, and intermittency. When the difference in capital lifetimes is very large, the coupled system tends to behave like a one-sector model with a reduced capital content of production.     

Why not one big database? Principles for data ownership

This research concerns incentive principles which drive information sharing and affect database value. Many real world centralization and standardization efforts have failed, typically because departments lacked incentives or needed greater local autonomy. While intangible factors such as “ownership” have been described as the key to providing incentives, these soft issues have largely eluded formal characterization. Using an incomplete contracts approach from economics, we model the costs and benefits of restructuring organizational control, including critical intangible factors, by explicitly considering the role of data “ownership”. There are two principal contributions from the approach taken here. First, it defines mathematically precise terms for analysing the incentive costs and benefits of changing control. Second, this theoretical framework leads to the development of a concrete model and seven normative principles for improved database management. These principles may be instrumental to designers in a variety of applications such as the decision to decentralize or to outsource information technology and they can be useful in determining the value of standards and translators. Applications of the proposed theory are also illustrated through case histories.     

Preface

On behalf of the program committee co-chairs of IFIP 2011 International Conference on Network and Parallel Computing(NPC 2011),we are very happy to organize a special section of five best paper nominees selected from the conference.The committee reviewed our 54 submissions over a 6-week period from mid-April to the end of May     

Extensible Recognition of Algorithmic Patterns in DSP Programs for Automatic Parallelization

We introduce an extensible knowledge based tool for idiom (pattern) recognition in DSP (digital signal processing) programs. Our tool utilizes functionality provided by the Cetus compiler infrastructure for detecting certain computation patterns that frequently occur in DSP code. We focus on recognizing patterns for for-loops and statements in their bodies as these often are the performance critical constructs in DSP applications for which replacement by highly optimized, target-specific parallel algorithms will be most profitable. For better structuring and efficiency of pattern recognition, we classify patterns by different levels of complexity such that patterns in higher levels are defined in terms of lower level patterns. The tool works statically on the intermediate representation. For better extensibility and abstraction, most of the structural part of recognition rules is specified in XML form to separate the tool implementation from the pattern specifications. Information about detected patterns will later be used for optimized code generation by local algorithm replacement e.g. for the low-power high-throughput multicore DSP architecture ePUMA.     

Multiple symbols soft-decision metrics for coded frequency-shift keying signals

This paper derives a novel multiple symbols soft-decision metrics for frequency-shift keying signals which are affected by additive symmetric α -stable (S α S) noise and fading. The approximate metric, which is for the case where channel state information (phases, amplitudes, and noise dispersion parameter) is unknown is obtained based on a generalized-likelihood ratio (GLR) approach. The metric is obtained in closed form and proved to be effective. The performances of the multiple symbols soft-decision metrics are compared numerically for a turbo-coded system. The proposed multiple symbols metric provides substantial improvement over earlier single-symbol metrics.     

The development of the HiPE system: design and experience report

The concurrent functional programming language Erlang has been designed to ease the development of large-scale distributed soft real-time control applications. So far, it has been used quite successfully in industry, both within Ericsson Telecom, where it was designed and developed, and by other companies. This declarative language success-story has taken place despite the fact that Erlang implementations are slow compared with implementations of other functional languages. Wanting to improve the performance aspects of publicly available Erlang implementations, which are based on emulators, we embarked on a project called HiPE (High-Performance Erlang) whose aim has been to develop an efficient just-in-time native code compiler for Erlang (called the HiPE system). Since its start in 1996, the system has gone through various (re-)design phases, partly due to implementation choices that did not turn out to be as promising as they appeared on paper, but mainly due to changes in Ericssons Erlang system upon which the HiPE system is built. In this article, we describe how the HiPE system was developed, what it currently looks like, and its current performance. We critically examine design decisions that we took, and the main lessons learnt from implementing them. Finally, we also report on our experiences from trying to keep up with the concurrent development of Ericssons base Erlang system. As such, this article both documents the HiPE system and can serve as possible guidance to anyone wishing to attempt a similar feat.     

SYNTACTIC SIMPLIFICATION AND SEMANTIC ENRICHMENT—TRIMMING DEPENDENCY GRAPHS FOR EVENT EXTRACTION

In our approach to event extraction, dependency graphs constitute the fundamental data structure for knowledge capture. Two types of trimming operations pave the way to more effective relation extraction. First, we simplify the syntactic representation structures resulting from parsing by pruning informationally irrelevant lexical material from dependency graphs. Second, we enrich informationally relevant lexical material in the simplified dependency graphs with additional semantic meta data at several layers of conceptual granularity. These two aggregation operations on linguistic representation structures are intended to avoid overfitting of machine learning‐based classifiers which we use for event extraction (besides manually curated dictionaries). Given this methodological framework, the corresponding JReX system developed by the Julie Lab Team from Friedrich‐Schiller‐Universität Jena (Germany) scored on 2nd rank among 24 competing teams for Task 1 in the “BioNLP’09 Shared Task on Event Extraction,” with 45.8% recall, 47.5% precision and 46.7% F1‐score on all 3,182 events. In more recent experiments, based on slight modifications of JReX and using the same data sets, we were able to achieve 45.9% recall, 57.7% precision, and 51.1% F1‐score.     

Pre-requisites for large scale coordination

Communication is in this paper seen as the foundation for purposeful human–human activity in dynamic environments. Coordination is a central issue in large systems such as military organisations, enterprises, or rescue organisations, and communication is needed in order to achieve coordination in such systems. This paper suggest a holistic approach to control, where control in a large system is seen as an emergent product of human interaction, focusing on human–human communication from a technical, organisational, temporal, and social perspective.

Human type 10 17β-hydroxysteroid dehydrogenase: molecular modelling and substrate docking

17β-hydroxysteroid dehydrogenases catalyze the oxidoreduction of hydroxy/oxo groups at position C17 of steroid hormones, thereby constituting a prereceptor control mechanism of hormone action. At present, 11 different mammalian 17β-hydroxysteroid dehydrogenases have been identified, catalyzing the cell- and steroid-specific activation and inactivation of estrogens and androgens. The human type 10 17β-hydroxysteroid dehydrogenase (17β-HSD-10) is a multifunctional mitochondrial enzyme that efficiently catalyzes the oxidative inactivation at C17 of androgens and estrogens. However, it also mediates oxidation of 3-hydroxy groups of androgens, thereby reactivating androgen metabolites. Finally, it is involved in β-oxidation of fatty acids by catalyzing the L-hydroxyacyl CoA dehydrogenase reaction of the β-oxidation cycle. These features and expression profiles suggest a critical role of 17β-HSD-10 in neurodegenerative and steroid-dependent cancer forms. Since no three-dimensional structure of 17β-HSD-10 is available, homology modelling was carried out to understand the molecular basis of these substrate specificities. The structure obtained displays the properties of a one-domain, /β fold enzyme of the SDR family. The active site is located within a large, hydrophobic cleft, which forms optimal contacts with the different steroid surfaces. The data provide explanations for the substrate specificities toward the various classes of sex steroid hormones. The model is suitable to explore substrate and inhibitor characteristics that may be used in the development of novel strategies in the treatment of degenerative or malignant diseases.