Robust algorithms for solving stochastic partial differential equations

A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.

Most of the patients presenting myocardial infarction would not be eligible for intensive lipid-lowering based on clinical algorithms or plasma C-reactive protein

Objective: The study we assessed how often patients who are manifesting a myocardial infarction (MI) would not be considered candidates for intensive lipid-lowering therapy based on the current guidelines. Methods: In 355 consecutive patients manifesting ST elevation MI (STEMI), admission plasma C-reactive protein (CRP) was measured and Framingham risk score (FRS), PROCAM risk score, Reynolds risk score, ASSIGN risk score, QRISK, and SCORE algorithms were applied. Cardiac computed tomography and carotid ultrasound were performed to assess the coronary artery calcium score (CAC), carotid intima-media thickness (cIMT) and the presence of carotid plaques. Results: Less than 50% of STEMI patients would be identified as having high risk before the event by any of these algorithms. With the exception of FRS (9%), all other algorithms would assign low risk to about half of the enrolled patients. Plasma CRP was <1.0 mg/L in 70% and >2 mg/L in 14% of the patients. The average cIMT was 0.8 +/- 0.2 mm and only in 24% of patients was >= 1.0 mm. Carotid plaques were found in 74% of patients. CAC > 100 was found in 66% of patients. Adding CAC >100 plus the presence of carotid plaque, a high-risk condition would be identified in 100% of the patients using any of the above mentioned algorithms. Conclusion: More than half of patients manifesting STEMI would not be considered as candidates for intensive preventive therapy by the current clinical algorithms. The addition of anatomical parameters such as CAC and the presence of carotid plaques can substantially reduce the CVD risk underestimation. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Genetic algorithms for continuous optimization problems - a concept of parameter-space size adjustment

The concept of parameter-space size adjustment is pn,posed in order to enable successful application of genetic algorithms to continuous optimization problems. Performance of genetic algorithms with six different combinations of selection and reproduction mechanisms, with and without parameter-space size adjustment, were severely tested on eleven multiminima test functions. An algorithm with the best performance was employed for the determination of the model parameters of the optical constants of Pt, Ni and Cr.

Concurreny based transition refinement for the verification of distributed algorithms

We suggest a new notion of behaviour preserving transition refinement based on partial order semantics. This notion is called transition refinement. We introduced transition refinement for elementary (low-level) Petri Nets earlier. For modelling and verifying complex distributed algorithms, high-level (Algebraic) Petri nets are usually used. In this paper, we define transition refinement for Algebraic Petri Nets. This notion is more powerful than transition refinement for elementary Petri nets because it corresponds to the simultaneous refinement of several transitions in an elementary Petri net. Transition refinement is particularly suitable for refinement steps that increase the degree of distribution of an algorithm, e.g. when synchronous communication is replaced by asynchronous message passing. We study how to prove that a replacement of a transition is a transition refinement.

Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.

Smallest weak and smallest totally weak critical sets in the latin squares of order at most seven

A critical set in a latin square of order n is a set of entries in a latin square which can be embedded in precisely one latin square of order n. Also, if any element of the critical set is deleted, the remaining set can be embedded in more than one latin square of order n. In this paper we find smallest weak and smallest totally weak critical sets for all the latin squares of orders six and seven. Moreover, we computationally prove that there is no (totally) weak critical set in the back circulant latin square of order five and we find a totally weak critical set of size seven in the other main class of latin squares of order five.

On the direct product of two weak uniquely completable partial latin squares

In this note we show by counter-example that the direct product of two weak uniquely completable partial latin squares is not necessarily a uniquely completable partial latin square. This counter-example rejects a conjecture by Gower (see [3]) on the direct product of two uniquely completable partial latin squares.

Human GC-AG alternative intron isoforms with weak donor sites show enhanced consensus at acceptor exon positions

It has been previously observed that the intrinsically weak variant GC donor sites, in order to be recognized by the U2-type spliceosome, possess strong consensus sequences maximized for base pair formation with U1 and U5/U6 snRNAs. However, variability in signal strength is a fundamental mechanism for splice site selection in alternative splicing. Here we report human alternative GC-AG introns (for the first time from any species), and show that while constitutive GC-AG introns do possess strong signals at their donor sites, a large subset of alternative GC-AG introns possess weak consensus sequences at their donor sites. Surprisingly, this subset of alternative isoforms shows strong consensus at acceptor exon positions 1 and 2. The improved consensus at the acceptor exon can facilitate a strong interaction with U5 snRNA, which tethers the two exons for ligation during the second step of splicing. Further, these isoforms nearly always possess alternative acceptor sites and always possess alternative acceptor sites and exhibit particularly weak polypyrimidine tracts characteristic of AG-dependent introns. The acceptor exon nucleotides are part of the consensus required for the U2AF(35)-mediated recognition of AG in such introns. Such improved consensus at acceptor exons is not found in either normal or alternative GT-AG introns having weak donor sites or weak polypyrimidine,tracts. The changes probably reflect mechanisms that allow GC-AG alternative intron isoforms to cope with two conflicting requirements, namely an apparent need for differential splice strength to direct the choice of alternative sites and a need for improved donor signals to compensate for the central mismatch base pair (C-A) in the RNA duplex of U1 snRNA and the pre-mRNA. The other important findings include (i) one in every twenty alternative introns is a GC-AG intron, and (ii) three of every five observed GC-AG introns are alternative isoforms.

Mathematical methods for spatially cohesive reserve design

The problem of designing spatially cohesive nature reserve systems that meet biodiversity objectives is formulated as a nonlinear integer programming problem. The multiobjective function minimises a combination of boundary length, area and failed representation of the biological attributes we are trying to conserve. The task is to reserve a subset of sites that best meet this objective. We use data on the distribution of habitats in the Northern Territory, Australia, to show how simulated annealing and a greedy heuristic algorithm can be used to generate good solutions to such large reserve design problems, and to compare the effectiveness of these methods.