Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Assessment of total uncertainty in cocaine and benzoylecgonine wastewater load measurements

To check the effectiveness of campaigns preventing drug abuse or indicating local effects of efforts against drug trafficking, it is beneficial to know consumed amounts of substances in a high spatial and temporal resolution. The analysis of drugs of abuse in wastewater (WW) has the potential to provide this information. In this study, the reliability of WW drug consumption estimates is assessed and a novel method presented to calculate the total uncertainty in observed WW cocaine (COC) and benzoylecgonine (BE) loads. Specifically, uncertainties resulting from discharge measurements, chemical analysis and the applied sampling scheme were addressed and three approaches presented. These consist of (i) a generic model-based procedure to investigate the influence of the sampling scheme on the uncertainty of observed or expected drug loads, (ii) a comparative analysis of two analytical methods (high performance liquid chromatography-tandem mass spectrometry and gas chromatography-mass spectrometry), including an extended cross-validation by influent profiling over several days, and (iii) monitoring COC and BE concentrations in WW of the largest Swiss sewage treatment plants. In addition, the COC and BE loads observed in the sewage treatment plant of the city of Berne were used to back-calculate the COC consumption. The estimated mean daily consumed amount was 107 ± 21 g of pure COC, corresponding to 321 g of street-grade COC.

A tutorial on data-driven methods for statistically assessing ERP topographies

Dynamic changes in ERP topographies can be conveniently analyzed by means of microstates, the so-called "atoms of thoughts", that represent brief periods of quasi-stable synchronized network activation. Comparing temporal microstate features such as on- and offset or duration between groups and conditions therefore allows a precise assessment of the timing of cognitive processes. So far, this has been achieved by assigning the individual time-varying ERP maps to spatially defined microstate templates obtained from clustering the grand mean data into predetermined numbers of topographies (microstate prototypes). Features obtained from these individual assignments were then statistically compared. This has the problem that the individual noise dilutes the match between individual topographies and templates leading to lower statistical power. We therefore propose a randomization-based procedure that works without assigning grand-mean microstate prototypes to individual data. In addition, we propose a new criterion to select the optimal number of microstate prototypes based on cross-validation across subjects. After a formal introduction, the method is applied to a sample data set of an N400 experiment and to simulated data with varying signal-to-noise ratios, and the results are compared to existing methods. In a first comparison with previously employed statistical procedures, the new method showed an increased robustness to noise, and a higher sensitivity for more subtle effects of microstate timing. We conclude that the proposed method is well-suited for the assessment of timing differences in cognitive processes. The increased statistical power allows identifying more subtle effects, which is particularly important in small and scarce patient populations.

A serial scheme for minimizing the duration of resource-constrained projects within Microsoft Project

Microsoft Project is one of the most-widely used software packages for project management. For the scheduling of resource-constrained projects, the package applies a priority-based procedure using a specific schedule-generation scheme. This procedure performs relatively poorly when compared against other software packages or state-of-the-art methods for resource-constrained project scheduling. In Microsoft Project 2010, it is possible to work with schedules that are infeasible with respect to the precedence or the resource constraints. We propose a novel schedule-generation scheme that makes use of this possibility. Under this scheme, the project tasks are scheduled sequentially while taking into account all temporal and resource constraints that a user can define within Microsoft Project. The scheme can be implemented as a priority-rule based heuristic procedure. Our computational results for two real-world construction projects indicate that this procedure outperforms the built-in procedure of Microsoft Project

Quantitative PCR for the diagnosis of cutaneous leishmaniasis from formalin-fixed and paraffin-embedded skin sections.

The present report describes a real-time PCR-based procedure to reliably determine the quantity of Leishmania amastigotes in relation to the amount of host tissue in histological skin sections from canine and equine cases of cutaneous leishmaniasis. The novel diagnostic Leishmania-PCR has a detection limit of <0.02 amastigotes per μg tissue, which corresponds well to the detection limit of immunohistochemistry and is far beyond that of conventional histology. Our results emphasise the importance of PCR to complement routine histology of cutaneous leishmaniasis cases, particularly in laboratories in which no immunohistochemical assay is available.

Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.

Optimized on-line enantioselective capillary electrophoretic method for kinetic and inhibition studies of drug metabolism mediated by cytochrome P450 enzymes.

Pharmacokinetic and pharmacodynamic properties of a chiral drug can significantly differ between application of the racemate and single enantiomers. During drug development, the characteristics of candidate compounds have to be assessed prior to clinical testing. Since biotransformation significantly influences drug actions in an organism, metabolism studies represent a crucial part of such tests. Hence, an optimized and economical capillary electrophoretic method for on-line studies of the enantioselective drug metabolism mediated by cytochrome P450 enzymes was developed. It comprises a diffusion-based procedure, which enables mixing of the enzyme with virtually any compound inside the nanoliter-scale capillary reactor and without the need of additional optimization of mixing conditions. For CYP3A4, ketamine as probe substrate and highly sulfated γ-cyclodextrin as chiral selector, improved separation conditions for ketamine and norketamine enantiomers compared to a previously published electrophoretically mediated microanalysis method were elucidated. The new approach was thoroughly validated for the CYP3A4-mediated N-demethylation pathway of ketamine and applied to the determination of its kinetic parameters and the inhibition characteristics in presence of ketoconazole and dexmedetomidine. The determined parameters were found to be comparable to literature data obtained with different techniques. The presented method constitutes a miniaturized and cost-effective tool, which should be suitable for the assessment of the stereoselective aspects of kinetic and inhibition studies of cytochrome P450-mediated metabolic steps within early stages of the development of a new drug.

Finite element analysis of aortic root dilation: a new procedure to reproduce pathology based on experimental data

Sinotubular junction dilation is one of the most frequent pathologies associated with aortic root incompetence. Hence, we create a finite element model considering the whole root geometry; then, starting from healthy valve models and referring to measures of pathological valves reported in the literature, we reproduce the pathology of the aortic root by imposing appropriate boundary conditions. After evaluating the virtual pathological process, we are able to correlate dimensions of non-functional valves with dimensions of competent valves. Such a relation could be helpful in recreating a competent aortic root and, in particular, it could provide useful information in advance in aortic valve sparing surgery.

Multimodal Registration Procedure for the Initial Spatial Alignment of a Retinal Video Sequence to a Retinal Composite Image

Accurate placement of lesions is crucial for the effectiveness and safety of a retinal laser photocoagulation treatment. Computer assistance provides the capability for improvements to treatment accuracy and execution time. The idea is to use video frames acquired from a scanning digital ophthalmoscope (SDO) to compensate for retinal motion during laser treatment. This paper presents a method for the multimodal registration of the initial frame from an SDO retinal video sequence to a retinal composite image, which may contain a treatment plan. The retinal registration procedure comprises the following steps: 1) detection of vessel centerline points and identification of the optic disc; 2) prealignment of the video frame and the composite image based on optic disc parameters; and 3) iterative matching of the detected vessel centerline points in expanding matching regions. This registration algorithm was designed for the initialization of a real-time registration procedure that registers the subsequent video frames to the composite image. The algorithm demonstrated its capability to register various pairs of SDO video frames and composite images acquired from patients.

High-throughput procedure for tick surveys of tick-borne encephalitis virus and its application in a national surveillance study in Switzerland

Tick-borne encephalitis (TBE), a viral infection of the central nervous system, is endemic in many Eurasian countries. In Switzerland, TBE risk areas have been characterized by geographic mapping of clinical cases. Since mass vaccination should significantly decrease the number of TBE cases, alternative methods for exposure risk assessment are required. We established a new PCR-based test for the detection of TBE virus (TBEV) in ticks. The protocol involves an automated, high-throughput nucleic acid extraction method (QIAsymphony SP system) and a one-step duplex real-time reverse transcription-PCR (RT-PCR) assay for the detection of European subtype TBEV, including an internal process control. High usability, reproducibility, and equivalent performance for virus concentrations down to 5 x 10(3) viral genome equivalents/microl favor the automated protocol compared to the modified guanidinium thiocyanate-phenol-chloroform extraction procedure. The real-time RT-PCR allows fast, sensitive (limit of detection, 10 RNA copies/microl), and specific (no false-positive test results for other TBEV subtypes, other flaviviruses, or other tick-transmitted pathogens) detection of European subtype TBEV. The new detection method was applied in a national surveillance study, in which 62,343 Ixodes ricinus ticks were screened for the presence of TBE virus. A total of 38 foci of endemicity could be identified, with a mean virus prevalence of 0.46%. The foci do not fully agree with those defined by disease mapping. Therefore, the proposed molecular test procedure constitutes a prerequisite for an appropriate TBE surveillance. Our data are a unique complement of human TBE disease case mapping in Switzerland.

Population-based trend analysis of laparoscopic Nissen and Toupet fundoplications for gastroesophageal reflux disease

The Nissen and Toupet fundoplications are the most commonly used techniques for surgical treatment of gastroesophageal reflux disease. To date, no population-based trend analysis has been reported examining the choice of procedure and short-term outcomes. This study was designed to analyze trends in the use of Nissen versus Toupet fundoplications, and corresponding short-term outcomes during a 10-year period between 1995 and 2004.

Light-emitting diode and laser fluorescence-based devices in detecting occlusal caries

The aim of this study was to assess the performance of two light-emitting diode (LED)- and two laser fluorescence-based devices in detecting occlusal caries in vitro. Ninety-seven permanent molars were assessed twice by two examiners using two LED- (Midwest Caries - MID and VistaProof - VP) and two laser fluorescence-based (DIAGNOdent 2095 - LF and DIAGNOdent pen 2190 - LFpen) devices. After measuring, the teeth were histologically prepared and classified according to lesion extension. At D1 the specificities were 0.76 (LF and LFpen), 0.94 (MID), and 0.70 (VP); the sensitivities were 0.70 (LF), 0.62 (LFpen), 0.31 (MID), and 0.75 (VP). At D(3) threshold the specificities were 0.88 (LF), 0.87 (LFpen), 0.90 (MID), and 0.70 (VP); the sensitivities were 0.63 (LF and LFpen), 0.70 (MID), and 0.96 (VP). Spearman's rank correlations with histology were 0.56 (LF), 0.51 (LFpen), 0.55 (MID), and 0.58 (VP). Inter- and intraexaminer ICC values were high and varied from 0.83 to 0.90. Both LF devices seemed to be useful auxiliary tools to the conventional methods, presenting good reproducibility and better accuracy at D(3) threshold. MID was not able to differentiate sound surfaces from enamel caries and VP still needs improvement on the cut-off limits for its use.