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PubMed2001

Extremal optimization for graph partitioning.

Extremal optimization is a new general-purpose method for approximating solutions to hard optimization problems. We study the method in detail by way of the computationally hard (NP-hard) graph partitioning problem. We discuss the scaling behavior of extremal optimization, focusing on the convergence of the average run as a function of run time and system size. The method has a single free parameter, which we determine numerically and justify using a simple argument. On random graphs, our numerical results demonstrate that extremal optimization maintains consistent accuracy for increasing system sizes, with an approximation error decreasing over run time roughly as a power law t(-0.4). On geometrically structured graphs, the scaling of results from the average run suggests that these are far from optimal with large fluctuations between individual trials. But when only the best runs are considered, results consistent with theoretical arguments are recovered.

Journal Article↗

PubMed2004

Extremal optimization at the phase transition of the three-coloring problem.

We investigate the phase transition in vertex coloring on random graphs, using the extremal optimization heuristic. Three-coloring is among the hardest combinatorial optimization problems and is equivalent to a 3-state anti-ferromagnetic Potts model. Like many other such optimization problems, it has been shown to exhibit a phase transition in its ground state behavior under variation of a system parameter: the graph's mean vertex degree. This phase transition is often associated with the instances of highest complexity. We use extremal optimization to measure the ground state cost and the "backbone," an order parameter related to ground state overlap, averaged over a large number of instances near the transition for random graphs of size n up to 512. For these graphs, benchmarks show that extremal optimization reaches ground states and explores a sufficient number of them to give the correct backbone value after about O (n(3.5)) update steps. Finite size scaling yields a critical mean degree value alpha(c) =4.703 (28). Furthermore, the exploration of the degenerate ground states indicates that the backbone order parameter, measuring the constrainedness of the problem, exhibits a first-order phase transition.

Journal Article↗

PubMed2005

Possible connection between the optimal path and flow in percolation clusters.

We study the behavior of the optimal path between two sites separated by a distance on a d-dimensional lattice of linear size L with weight assigned to each site. We focus on the strong disorder limit, i.e., when the weight of a single site dominates the sum of the weights along each path. We calculate the probability distribution P(l opt/r,L) of the optimal path length l opt, and find for r <<L a power-law decay with l opt, characterized by exponent g opt. We determine the scaling form of P(l opt/r,L) in two- and three-dimensional lattices. To test the conjecture that the optimal paths in strong disorder and flow in percolation clusters belong to the same universality class, we study the tracer path length l tr of tracers inside percolation through their probability distribution P(l tr/r,L). We find that, because the optimal path is not constrained to belong to a percolation cluster, the two problems are different. However, by constraining the optimal paths to remain inside the percolation clusters in analogy to tracers in percolation, the two problems exhibit similar scaling properties.

Journal Article↗

PubMed2006

Development of optimal models of porous media by combining static and dynamic data: the porosity distribution.

This paper is part of a project, the goal of which is the development of the optimal spatial distributions of the porosity and permeability of a large-scale porous medium by using complementary static and dynamic data for the medium. The data include limited measurements of the porosity, which the method honors (preserves) in the optimal model and utilizes its correlation function, together with the first-arrival (FA) times, at a certain number of receivers, of seismic waves that have propagated in the medium and the time dependence of the pressure of a fluid flowing in the medium. The method uses the simulated-annealing (SA) technique in order to develop the optimal model. In the present paper we utilize the porosity and FA times data in order to develop the optimal spatial distribution of the porosity. This is accomplished by combining the SA method with a simulator that solves for the numerical solution of the acoustic-wave equation from which the FA times are estimated, limited porosity, and FA times data. We show that the optimal model not only honors the data, but also provides accurate estimates of the porosities in the rest of the porous medium. The efficiency of the computations is discussed in detail.

Journal Article↗

PubMed2004

The potentials of conditional optimization in phasing and model building of protein crystal structures.

Model building is a pivotal step in protein-structure determination, because with an atomic model available the vast amount of geometrical prior knowledge may be applied to the structure-determination process. Here, conditional optimization, a method that does not require interpretation of the electron-density map, is described. Instead, this method refines loose atoms for which all chemical interpretations are considered simultaneously using an N-particle formalism. This method bears the potential of introducing the geometrical data much earlier in the structure-determination process, i.e. well before an interpretable electron-density map has been obtained. Here, results from two tests are presented: automated model building of three proteins with diffraction data extending to 2.4-3.0 A resolution and ab initio phasing of a small four-helical bundle with diffraction data to 2.0 A resolution. Models built automatically by the widely used programs ARP/wARP and RESOLVE and those from conditional optimization per se, without discrete modelling steps, had comparable phase quality and completeness, except in loop regions, which are poorly modelled by the current force field in conditional optimization. Optimization of multiple random starting models by conditional optimization yielded models revealing the four helices of the four-helical bundle.

Bacterial Outer Membrane Proteins↗

PubMed2001

A rate distortion optimal ECG coding algorithm.

Signal compression is an important problem encountered in many applications. Various techniques have been proposed over the years for addressing the problem. In this paper, we present a time domain algorithm based on the coding of line segments which are used to approximate the signal. These segments are fit in a way that is optimal in the rate distortion sense. Although the approach is applicable to any type of signal, we focus, in this paper, on the compression of electrocardiogram (ECG) signals. ECG signal compression has traditionally been tackled by heuristic approaches. However, it has been demonstrated [1] that exact optimization algorithms outperform these heuristic approaches by a wide margin with respect to reconstruction error. By formulating the compression problem as a graph theory problem, known optimization theory can be applied in order to yield optimal compression. In this paper, we present an algorithm that will guarantee the smallest possible distortion among all methods applying linear interpolation given an upper bound on the available number of bits. Using a varied signal test set, extensive coding experiments are presented. We compare the results from our coding method to traditional time domain ECG compression methods, as well as, to more recently developed frequency domain methods. Evaluation is based both on percentage root-mean-square difference (PRD) performance measure and visual inspection of the reconstructed signals. The results demonstrate that the exact optimization methods have superior performance compared to both traditional ECG compression methods and the frequency domain methods.

Algorithms↗

PubMed2005

Energy-optimal electrical excitation of nerve fibers.

We derive, based on an analytical nerve membrane model and optimal control theory of dynamical systems, an energy-optimal stimulation current waveform for electrical excitation of nerve fibers. Optimal stimulation waveforms for nonleaky and leaky membranes are calculated. The case with a leaky membrane is a realistic case. Finally, we compare the waveforms and energies necessary for excitation of a leaky membrane in the case where the stimulation waveform is a square-wave current pulse, and in the case of energy-optimal stimulation. The optimal stimulation waveform is an exponentially rising waveform and necessitates considerably less energy to excite the nerve than a square-wave pulse (especially true for larger pulse durations). The described theoretical results can lead to drastically increased battery lifetime and/or decreased energy transmission requirements for implanted biomedical systems.

Action Potentials↗

PubMed2006

Source-optimized irregular repeat accumulate codes with inherent unequal error protection capabilities and their application to scalable image transmission.

The common practice for achieving unequal error protection (UEP) in scalable multimedia communication systems is to design rate-compatible punctured channel codes before computing the UEP rate assignments. This paper proposes a new approach to designing powerful irregular repeat accumulate (IRA) codes that are optimized for the multimedia source and to exploiting the inherent irregularity in IRA codes for UEP. Using the end-to-end distortion due to the first error bit in channel decoding as the cost function, which is readily given by the operational distortion-rate function of embedded source codes, we incorporate this cost function into the channel code design process via density evolution and obtain IRA codes that minimize the average cost function instead of the usual probability of error. Because the resulting IRA codes have inherent UEP capabilities due to irregularity, the new IRA code design effectively integrates channel code optimization and UEP rate assignments, resulting in source-optimized channel coding or joint source-channel coding. We simulate our source-optimized IRA codes for transporting SPIHT-coded images over a binary symmetric channel with crossover probability p. When p = 0.03 and the channel code length is long (e.g., with one codeword for the whole 512 x 512 image), we are able to operate at only 9.38% away from the channel capacity with code length 132380 bits, achieving the best published results in terms of average peak signal-to-noise ratio (PSNR). Compared to conventional IRA code design (that minimizes the probability of error) with the same code rate, the performance gain in average PSNR from using our proposed source-optimized IRA code design is 0.8759 dB when p = 0.1 and the code length is 12800 bits. As predicted by Shannon's separation principle, we observe that this performance gain diminishes as the code length increases.

Algorithms↗

PubMed2002

Integrated surface model optimization for freehand three-dimensional echocardiography.

The major obstacle of three-dimensional (3-D) echocardiography is that the ultrasound image quality is too low to reliably detect features locally. Almost all available surface-finding algorithms depend on decent quality boundaries to get satisfactory surface models. We formulate the surface model optimization problem in a Bayesian framework, such that the inference made about a surface model is based on the integration of both the low-level image evidence and the high-level prior shape knowledge through a pixel class prediction mechanism. We model the probability of pixel classes instead of making explicit decisions about them. Therefore, we avoid the unreliable edge detection or image segmentation problem and the pixel correspondence problem. An optimal surface model best explains the observed images such that the posterior probability of the surface model for the observed images is maximized. The pixel feature vector as the image evidence includes several parameters such as the smoothed grayscale value and the minimal second directional derivative. Statistically, we describe the feature vector by the pixel appearance probability model obtained by a nonparametric optimal quantization technique. Qualitatively, we display the imaging plane intersections of the optimized surface models together with those of the ground-truth surfaces reconstructed from manual delineations. Quantitatively, we measure the projection distance error between the optimized and the ground-truth surfaces. In our experiment, we use 20 studies to obtain the probability models offline. The prior shape knowledge is represented by a catalog of 86 left ventricle surface models. In another set of 25 test studies, the average epicardial and endocardial surface projection distance errors are 3.2 +/- 0.85 mm and 2.6 +/- 0.78 mm, respectively.

Algorithms↗

PubMed2002

The optimal stimulation pattern for skeletal muscle is dependent on muscle length.

Stimulation patterns can be optimized by maximizing the force-time integral (FTI) per stimulation pulse of the elicited muscle contraction. Such patterns, providing the desired force output with the minimum number of pulses, may reduce muscle fatigue, which has been shown to correlate to the number of pulses delivered. Applications of electrical stimulation to use muscle as a controllable biological actuator may, therefore, be improved. Although muscle operates over a range of lengths, optimized patterns have been determined only at optimal muscle length. In this study, the patterns with up to four pulses that produced the highest isometric FTI were determined at 10 muscle lengths for 11 rabbit tibialis anterior muscles. The interpulse intervals (IPIs) used ranged from 4 to 54 ms. At high muscle length, the optimal stimulation pattern consisted of an initial short IPI (doublet) followed by longer IPIs, in agreement with previous studies. However, at low length, the third pulse still elicited more than linear summation (triplet); furthermore, the relative enhancement of the FTI per pulse was considerably larger at low length than at high length, suggesting that optimal stimulation patterns are length dependent.

Animals↗

PubMed2004

Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN).

Type-2 fuzzy logic system (FLS) cascaded with neural network, type-2 fuzzy neural network (T2FNN), is presented in this paper to handle uncertainty with dynamical optimal learning. A T2FNN consists of a type-2 fuzzy linguistic process as the antecedent part, and the two-layer interval neural network as the consequent part. A general T2FNN is computational-intensive due to the complexity of type 2 to type 1 reduction. Therefore, the interval T2FNN is adopted in this paper to simplify the computational process. The dynamical optimal training algorithm for the two-layer consequent part of interval T2FNN is first developed. The stable and optimal left and right learning rates for the interval neural network, in the sense of maximum error reduction, can be derived for each iteration in the training process (back propagation). It can also be shown both learning rates cannot be both negative. Further, due to variation of the initial MF parameters, i.e., the spread level of uncertain means or deviations of interval Gaussian MFs, the performance of back propagation training process may be affected. To achieve better total performance, a genetic algorithm (GA) is designed to search optimal spread rate for uncertain means and optimal learning for the antecedent part. Several examples are fully illustrated. Excellent results are obtained for the truck backing-up control and the identification of nonlinear system, which yield more improved performance than those using type-1 FNN.

Algorithms↗

PubMed1993

Studies of contact hypersensitivity induction in mice with optimal sensitizing doses of hapten.

To avoid unsuspected and unwanted consequences of excess hapten during epicutaneous sensitization, optimal sensitizing doses of dinitrofluorobenzene (DNFB) were determined for several ultraviolet B radiation (UVB)-resistant and UVB-susceptible strains of mice. Using these doses of hapten applied epicutaneously or injected intracutaneously into normal or UVB-exposed body wall skin, it was determined that four consecutive daily exposures to UVB prevented contact hypersensitivity induction in all mice when optimal sensitizing doses of DNFB were applied epicutaneously. By contrast, UVB-resistant, but not UVB-susceptible, mice developed contact hypersensitivity when an optimal sensitizing dose of DNFB was injected intracutaneously into UVB-irradiated skin. Moreover, whereas UVB-susceptible mice failed to develop contact hypersensitivity when an optimal sensitizing dose of DNFB was painted on skin exposed to a single dose of UVB, UVB-resistant mice did develop contact hypersensitivity under similar circumstances. Based on these results, it is concluded that 1) conventional doses of epicutaneously applied haptens induce contact hypersensitivity with the aid of antigen-presenting cells derived from both the epidermis and the dermis, 2) the phenomenon of UVB susceptibility is mediated by cells and molecules within the dermis when conventional doses of hapten and UVB radiation are employed, and 3) UVB susceptibility is mediated by cells and molecules within the epidermis when optimal sensitizing doses of hapten and a single exposure to UVB are employed.

Animals↗

PubMed2002

Evolutionary optimality applied to Drosophila experiments: hypothesis of constrained reproductive efficiency.

The general purpose of the paper is to test evolutionary optimality theories with experimental data on reproduction, energy consumption, and longevity in a particular Drosophila genotype. We describe the resource allocation in Drosophila females in terms of the oxygen consumption rates devoted to reproduction and to maintenance. The maximum ratio of the component spent on reproduction to the total rate of oxygen consumption, which can be realized by the female reproductive machinery, is called metabolic reproductive efficiency (MRE). We regard MRE as an evolutionary constraint. We demonstrate that MRE may be evaluated for a particular Drosophila phenotype given the fecundity pattern, the age-related pattern of oxygen consumption rate, and the longevity. We use a homeostatic model of aging to simulate a life history of a representative female fly, which describes the control strain in the long-term experiments with the Wayne State Drosophila genotype. We evaluate the theoretically optimal trade-offs in this genotype. Then we apply the Van Noordwijk-de Jong resource acquisition and allocation model, Kirkwood's disposable soma theory. and the Partridge-Barton optimality approach to test if the experimentally observed trade-offs may be regarded as close to the theoretically optimal ones. We demonstrate that the two approaches by Partridge-Barton and Kirkwood allow a positive answer to the question, whereas the Van Noordwijk-de Jong approach may be used to illustrate the optimality. We discuss the prospects of applying the proposed technique to various Drosophila experiments, in particular those including manipulations affecting fecundity.

Aging↗

PubMed2005

Frequency and effect of optimal anticoagulation before onset of ischaemic stroke in patients with known atrial fibrillation.

BACKGROUND: The aims of the study were (i) to examine which antithrombotic therapy patients with known atrial fibrillation use at the point of time when they suffer an ischaemic stroke, (ii) to evaluate the effects of optimal antithrombotic treatment on outcome and severity of the stroke. METHODS: Patients with known atrial fibrillation before onset of acute ischaemic stroke, and age >60 years were included. Antithrombotic therapy on admission was classified into four groups: no antithrombotic therapy, aspirin, sub-optimal anticoagulation (warfarin and international normalized ratio, INR<2.0) and optimal anticoagulation (warfarin and INR>or=2.0). PRIMARY OUTCOME: modified Rankin Scale (mRS) 5 or 6 at day 7 poststroke. SECONDARY OUTCOMES: (i) death or discharge to a nursing home, (ii) death, (iii) stroke severity on admission assessed by Scandinavian Stroke Scale. RESULTS: A total of 394 patients were included. On admission 109 (28%) patients used no antithrombotic therapy, 169 (43%) aspirin, 52 (13%) warfarin and had an INR<2.0, and 64 (16%) used warfarin and had an INR>or=2.0. The proportion of patients with an mRS 5 or 6 and the corresponding odds ratios were: in the warfarin group with INR<2.0, 16 (31%), OR 3.1 (CI: 1.2-8.0), (P=0.019), in the group with no antithrombotic therapy 29 (27%), 2.5 (1.1-5.9), (P=0.034), and in the aspirin group 41(24%), 2.2 (1.0-5.1) (P=0.054), compared with the warfarin group with INR>or=2.0, where eight (13%) patients had a poor outcome. A significantly higher proportion of patients died or were discharged to a nursing home in the warfarin group with an INR<2.0 (P=0.014), in the aspirin group (P=0.018) and in the no-treatment group (P=0.035), compared with the warfarin group with an INR>or=2.0. No significant differences were found regarding death alone and stroke severity on admission. DISCUSSION: Few patients with known atrial fibrillation who suffer an ischaemic stroke receive optimal antithrombotic therapy prior to the onset of stroke. Optimal anticoagulation does not only reduce the risk of ischaemic stroke, but also appears to reduce death and severe dependency as well as the need for nursing home care, if an ischaemic stroke occurs.

Aged↗

PubMed2004

Optimizing imaging parameters for the separation of multiple labels in a fluorescence image.

A theoretical analysis is presented on how to separate the contributions from individual, simultaneously present fluorophores in a spectrally resolved image. Equations are derived that allow the calculation of the signal-to-noise ratio of the estimates for such contributions, given the spectral information on the individual fluorophores, the excitation wavelengths and intensities, and the number and widths of the spectral detection channels. We then ask how such imaging parameters have to be chosen for optimal fluorophore separation. We optimize the signal-to-noise ratio or optimize a newly defined 'figure of merit', which is a measure of efficiency in the use of emitted photons. The influence of photobleaching on the resolution and on the choice of imaging parameters is discussed, as well as the additional resolution gained by including fluorescence lifetime information. A surprisingly small number of spectral channels are required for an almost optimal resolution, if the borders of these channels are optimally selected. The detailed consideration of photobleaching is found to be essential, whenever there is significant bleaching. Consideration of fluorescence lifetime information (in addition to spectral information) improves results, particularly when lifetimes differ by more than a factor of two.

Bacterial Proteins↗

PubMed1994

Unrealistic optimism: a behavioural sciences classroom demonstration project.

Unrealistic optimism may contribute to risky health practices and to a delay in seeking treatment for medical conditions, as most individuals perceive themselves to be at little risk for various disorders. It is thus an important concept to present to medical students as part of their behavioural sciences training. Social psychological concepts such as unrealistic optimism may appear, on initial presentation to students, to be a misjudgement based on faulty understanding of risk estimates by the general population. This project aimed to teach the principle of unrealistic optimism by having students document their own beliefs about health risks. Students rated their own risk, relative to other classmates, of experiencing a range of 17 health problems. Questionnaires were completed by two classes of medical students (n = 257). Class results showed varying levels of unrealistic optimism for all 17 conditions. Males and females differed significantly on three of the 17 conditions. Student data were obtained rapidly in a large didactic setting and served to illustrate the concept of unrealistic optimism which was subsequently taught in class. Such exercises may be a useful teaching aid to students providing them with feedback on their own cognitive processes and illustrating that they display cognitive distortions similar to those of patients.

Attitude to Health↗

PubMed2005

Optimized Scansystem platelet kit for bacterial detection with enhanced sensitivity: detection within 24 h after spiking.

BACKGROUND AND OBJECTIVES: The prevention and detection of bacterial contamination of platelet concentrates remains a major challenge for transfusion medicine. To be suitable for blood-transfusion services, the contamination detection method must be highly sensitive, easy to perform and preferably of low cost. In this spiking study, we evaluated the new optimized Scansystem Platelet Kit detection method for use on apheresis platelets. STUDY DESIGN AND METHODS: Apheresis platelet concentrates (APCs) were individually spiked with 10 colony-forming units (CFU)/ml of one of 10 different strains of bacteria. The spiked APCs were analysed at specific time-points during incubation by using the optimized Scansystem Platelet Kit. Bacterial enumeration was performed by plating onto blood agar. RESULTS: All the bacterial strains tested were detected by using the optimized Scansystem Platelet Kit when sampled 24 h after spiking. Compared to the Scansystem standard kit, sensitivity was increased to < 50 CFU/ml. The identity of the spiked bacteria was confirmed by Gram staining and DNA fingerprinting. CONCLUSION: The optimized Scansystem Platelet Kit was able to reliably detect, within 70 min, 10 transfusion-relevant bacterial species in APCs when a sample volume was taken 24 h after spiking. This is the first study carried out by using the optimized Scansystem bacterial detection that was found to have an enhanced sensitivity compared to the standard kit.

Bacteria↗

PubMed2005

Optimal reproductive allocation in annuals and an informational constraint on plasticity.

In this computational study, we examined optimal reproductive allocation schedules in annual plants whose season lengths vary in predictability. We discuss relationships among season-length predictability, the form of the optimal allocation schedule, the degree of plasticity reflected in the optimal reaction norm, and the competitive consequences of plasticity and bet-hedging. We used an evolutionary algorithm to search the allocation-schedule space for optima, given different distributions of season length. The resulting schedules maximize geometric-mean fecundity under their selecting distributions. We then examined the relative fitness of these schedules in simulated competition among reaction norms optimized for different degrees of season-length predictability. Gradedness of optimal schedules decreases with increasing season-length predictability, and reaction norms comprising highly graded schedules reflect lesser plasticity than norms comprising schedules that are less graded. In simulations, competitively successful genotypes were those that reflected plasticity appropriate to the season-length predictability. Informational constraints in the form of low season-length predictability select for low plasticity and high bet-hedging in allocation. Because an environmental cue must mediate the relationship between environment and fitness, plasticity in reproductive allocation ought to be understood not as a direct response to the selective environment, but rather to cues that are correlated with relevant environmental parameters.

Adaptation, Physiological↗