Effects of data characteristics on the results of reserve selection algorithms

We tested the effects of four data characteristics on the results of reserve selection algorithms. The data characteristics were nestedness of features (land types in this case), rarity of features, size variation of sites (potential reserves) and size of data sets (numbers of sites and features). We manipulated data sets to produce three levels, with replication, of each of these data characteristics while holding the other three characteristics constant. We then used an optimizing algorithm and three heuristic algorithms to select sites to solve several reservation problems. We measured efficiency as the number or total area of selected sites, indicating the relative cost of a reserve system. Higher nestedness increased the efficiency of all algorithms (reduced the total cost of new reserves). Higher rarity reduced the efficiency of all algorithms (increased the total cost of new reserves). More variation in site size increased the efficiency of all algorithms expressed in terms of total area of selected sites. We measured the suboptimality of heuristic algorithms as the percentage increase of their results over optimal (minimum possible) results. Suboptimality is a measure of the reliability of heuristics as indicative costing analyses. Higher rarity reduced the suboptimality of heuristics (increased their reliability) and there is some evidence that more size variation did the same for the total area of selected sites. We discuss the implications of these results for the use of reserve selection algorithms as indicative and real-world planning tools.

Genetic algorithms for design of liquid retaining structure

In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.

The determinants of default risk in Brazil

We formulated a general unrestricted model of the Brazilian Emerging Markets Bond Index Plus (EMBI+) spreads, a proxy for the country`s default risk. Employing algorithms that perform automated model selection, we found that macroeconomic fundamentals, such as current account deficit ratio to gross domestic product, public deficit ratio to gross domestic product and imports over foreign exchange reserves, can explain a great part of the variation in EMBI+ spreads. There is also robust evidence of systematic contagion from Argentina and Mexico and that the variance of the spread also affects its mean.

Highly integrated and automated high-speed grinding system for printer heads constructed by combination materials

The fabrication of heavy-duty printer heads involves a great deal of grinding work. Previously in the printer manufacturing industry, four grinding procedures were manually conducted in four grinding machines, respectively. The productivity of the whole grinding process was low due to the long loading time. Also, the machine floor space occupation was large because of the four separate grinding machines. The manual operation also caused inconsistent quality. This paper reports the system and process development of a highly integrated and automated high-speed grinding system for printer heads. The developed system, which is believed to be the first of its kind, not only produces printer heads of consistently good quality, but also significantly reduces the cycle time and machine floor space occupation.

Automated determination of rifampicin in plasma samples by in-tube solid-phase microextraction coupled with liquid chromatography

A sensitive and automated method is described for determination of rifampicin in plasma samples for therapeutic drug monitoring by in-tube solid-phase microextraction coupled with liquid chromatography (in-tube SPME/LC). Important factors in the optimization of in-tube SPME are discussed, such as coating type, sample pH, sample draw/eject volume, number of draw/eject cycles, and draw/eject flow rate. Analyte pre-concentrated in the polyethylene glycol phase was directly transferred to the liquid chromatographic column by percolation of the mobile phase, without carryover. The method was linear over the 0.1-100 mu g/mL range, with a linear coefficient value (r(2)) of 0.998. The inter-assay precision presented coefficient of variation <= 1.7%. The effectiveness and practicability of the proposed method are proven by analysis of plasma samples from ageing patients undergoing therapy with rifampicin. (C) 2011 Elsevier B.V. All rights reserved.

Use of the q-Gaussian mutation in evolutionary algorithms

This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.

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.

Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

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.

Agreement for Detecting Glaucoma Progression with the GDx Guided Progression Analysis, Automated Perimetry, and Optic Disc Photography

Purpose: To evaluate the ability of the GDx Variable Corneal Compensation (VCC) Guided Progression Analysis (GPA) software for detecting glaucomatous progression. Design: Observational cohort study. Participants: The study included 453 eyes from 252 individuals followed for an average of 46 +/- 14 months as part of the Diagnostic Innovations in Glaucoma Study. At baseline, 29% of the eyes were classified as glaucomatous, 67% of the eyes were classified as suspects, and 5% of the eyes were classified as healthy. Methods: Images were obtained annually with the GDx VCC and analyzed for progression using the Fast Mode of the GDx GPA software. Progression using conventional methods was determined by the GPA software for standard automated achromatic perimetry (SAP) and by masked assessment of optic disc stereophotographs by expert graders. Main Outcome Measures: Sensitivity, specificity, and likelihood ratios (LRs) for detection of glaucoma progression using the GDx GPA were calculated with SAP and optic disc stereophotographs used as reference standards. Agreement among the different methods was reported using the AC(1) coefficient. Results: Thirty-four of the 431 glaucoma and glaucoma suspect eyes (8%) showed progression by SAP or optic disc stereophotographs. The GDx GPA detected 17 of these eyes for a sensitivity of 50%. Fourteen eyes showed progression only by the GDx GPA with a specificity of 96%. Positive and negative LRs were 12.5 and 0.5, respectively. None of the healthy eyes showed progression by the GDx GPA, with a specificity of 100% in this group. Inter-method agreement (AC1 coefficient and 95% confidence intervals) for non-progressing and progressing eyes was 0.96 (0.94-0.97) and 0.44 (0.28-0.61), respectively. Conclusions: The GDx GPA detected glaucoma progression in a significant number of cases showing progression by conventional methods, with high specificity and high positive LRs. Estimates of the accuracy for detecting progression suggest that the GDx GPA could be used to complement clinical evaluation in the detection of longitudinal change in glaucoma. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references. Ophthalmology 2010; 117: 462-470 (C) 2010 by the American Academy of Ophthalmology.

Relationship between Optical Coherence Tomography, Pattern Electroretinogram and Automated Perimetry in Eyes with Temporal Hemianopia from Chiasmal Compression

PURPOSE. To evaluate the relationship between pattern electroretinogram (PERG) amplitude, macular and retinal nerve fiber layer (RNFL) thickness by optical coherence tomography (OCT), and visual field (VF) loss on standard automated perimetry (SAP) in eyes with temporal hemianopia from chiasmal compression. METHODS. Forty-one eyes from 41 patients with permanent temporal VF defects from chiasmal compression and 41 healthy subjects underwent transient full-field and hemifield (temporal or nasal) stimulation PERG, SAP and time domain-OCT macular and RNFL thickness measurements. Comparisons were made using Student`s t-test. Deviation from normal VF sensitivity for the central 18 of VF was expressed in 1/Lambert units. Correlations between measurements were verified by linear regression analysis. RESULTS. PERG and OCT measurements were significantly lower in eyes with temporal hemianopia than in normal eyes. A significant correlation was found between VF sensitivity loss and fullfield or nasal, but not temporal, hemifield PERG amplitude. Likewise a significant correlation was found between VF sensitivity loss and most OCT parameters. No significant correlation was observed between OCT and PERG parameters, except for nasal hemifield amplitude. A significant correlation was observed between several macular and RNFL thickness parameters. CONCLUSIONS. In patients with chiasmal compression, PERG amplitude and OCT thickness measurements were significant related to VF loss, but not to each other. OCT and PERG quantify neuronal loss differently, but both technologies are useful in understanding structure-function relationship in patients with chiasmal compression. (ClinicalTrials.gov number, NCT00553761.) (Invest Ophthalmol Vis Sci. 2009; 50: 3535-3541) DOI:10.1167/iovs.08-3093

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.