Implementing statistical learning methods through Bayesian networks (Part 2): bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.

Portafolio selection with skewness: a comparison of methods and a generalized two fund separation result

This contribution compares existing and newly developed techniques for geometrically representing mean-variances-kewness portfolio frontiers based on the rather widely adapted methodology of polynomial goal programming (PGP) on the one hand and the more recent approach based on the shortage function on the other hand. Moreover, we explain the working of these different methodologies in detail and provide graphical illustrations. Inspired by these illustrations, we prove a generalization of the well-known two fund separation theorem from traditionalmean-variance portfolio theory.

Predictors of awakening from postanoxic status epilepticus after therapeutic hypothermia.

BACKGROUND: Postanoxic status epilepticus (PSE) is considered a predictor of fatal outcome and therefore not intensively treated; however, some patients have had favorable outcomes. The aim of this study was to identify favorable predictors for awakening beyond vegetative state in PSE. METHODS: We studied six subjects treated with hypothermia improving beyond vegetative state after cerebral anoxia, despite PSE. They were among a cohort of patients treated for anoxic encephalopathy with therapeutic hypothermia in our institution between October 1999 and May 2006 (retrospectively, 3/107 patients) and June 2006 and May 2008 (prospectively, 3/74 patients). PSE was defined by clinical and EEG criteria. Outcome was assessed according to the Glasgow-Pittsburgh Cerebral Performance Categories (CPC). RESULTS: All improving patients had preserved brainstem reflexes, cortical somatosensory evoked potentials, and reactive EEG background during PSE. Half of them had myoclonic PSE, while three had nonconvulsive PSE. In the prospective arm, 3/28 patients with PSE showed this clinical-electrophysiologic profile; all awoke. Treatments consisted of benzodiazepines, various antiepileptic drugs, and propofol. One subject died of pneumonia in a minimally conscious state, one patient returned to baseline (CPC1), three had moderate impairment (CPC2), and one remained dependent (CPC3). Patients with nonconvulsive PSE showed a better prognosis than subjects with myoclonic PSE (p = 0.042). CONCLUSION: Patients with postanoxic status epilepticus and preserved brainstem reactions, somatosensory evoked potentials, and EEG reactivity may have a favorable outcome if their condition is treated as status epilepticus.

Improved detection of microbial ureteral stent colonisation by sonication.

PURPOSE: The diagnosis of microbial ureteral stent colonisation (MUSC) is difficult, since routine diagnostic techniques do not accurately detect microorganisms embedded in biofilms. New methods may improve diagnostic yield and understanding the pathophysiology of MUSC. The aim of the present study was to evaluate the potential of sonication in the detection of MUSC and to identify risk factors for device colonisation. METHODS: Four hundred and eight polyurethane ureteral stents of 300 consecutive patients were prospectively evaluated. Conventional urine culture (CUC) was obtained prior to stent placement and device removal. Sonication was performed to dislodge adherent microorganisms. Data of patient sex and age, indwelling time and indication for stent placement were recorded. RESULTS: Sonicate-fluid culture detected MUSC in 36%. Ureteral stents inserted during urinary tract infection (UTI) were more frequently colonised (59%) compared to those placed in sterile urine (26%; P < 0.001). Female sex (P < 0.001) and continuous stenting (P < 0.005) were significant risk factors for MUSC; a similar trend was observed in patients older than 50 years (P = 0.16). MUSC and indwelling time were positively correlated (P < 0.005). MUSC was accompanied by positive CUC in 36%. Most commonly isolated microorganisms were Coagulase-negative staphylococci (18.3%), Enterococci (17.9%) and Enterobacteriaceae (16.9%). CONCLUSIONS: Sonication is a promising approach in the diagnosis of MUSC. Significant risk factors for MUSC are UTI at the time of stent insertion, female sex, continuous stenting and indwelling time. CUC is a poor predictor of MUSC. The clinical relevance of MUSC needs further evaluation to classify isolated microorganism properly as contaminants or pathogens.

Pancreatic stone protein as a novel marker for neonatal sepsis.

PURPOSE: Early-onset sepsis (EOS) is one of the main causes for the admission of newborns to the neonatal intensive care unit. However, traditional infection markers are poor diagnostic markers of EOS. Pancreatic stone protein (PSP) is a promising sepsis marker in adults. The aim of this study was to investigate whether determining PSP improves the diagnosis of EOS in comparison with other infection markers. METHODS: This was a prospective multicentre study involving 137 infants with a gestational age of >34 weeks who were admitted with suspected EOS. PSP, procalcitonin (PCT), soluble human triggering receptor expressed on myeloid cells-1 (sTREM-1), macrophage migration inhibitory factor (MIF) and C-reactive protein (CRP) were measured at admission. Receiver-operating characteristic (ROC) curve analysis was performed. RESULTS: The level of PSP in infected infants was significantly higher than that in uninfected ones (median 11.3 vs. 7.5 ng/ml, respectively; p = 0.001). The ROC area under the curve was 0.69 [95 % confidence interval (CI) 0.59-0.80; p < 0.001] for PSP, 0.77 (95 % CI 0.66-0.87; p < 0.001) for PCT, 0.66 (95 % CI 0.55-0.77; p = 0.006) for CRP, 0.62 (0.51-0.73; p = 0.055) for sTREM-1 and 0.54 (0.41-0.67; p = 0.54) for MIF. PSP independently of PCT predicted EOS (p < 0.001), and the use of both markers concomitantly significantly increased the ability to diagnose EOS. A bioscore combining PSP (>9 ng/ml) and PCT (>2 ng/ml) was the best predictor of EOS (0.83; 95 % CI 0.74-0.93; p < 0.001) and resulted in a negative predictive value of 100 % and a positive predictive value of 71 %. CONCLUSIONS: In this prospective study, the diagnostic performance of PSP and PCT was superior to that of traditional markers and a combination bioscore improved the diagnosis of sepsis. Our findings suggest that PSP is a valuable biomarker in combination with PCT in EOS.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Evaluation of four whole-plant inoculation methods to analyze the pathogenicity of Erwinia amylovora under quarantine conditions

Four methods were tested to assess the fire-blight disease response on grafted pear plants. The leaves of the plants were inoculated with Erwinia amylovora suspensions by pricking with clamps, cutting with scissors, local infiltration, and painting a bacterial suspension onto the leaves with a paintbrush. The effects of the inoculation methods were studied in dose-time-response experiments carried out in climate chambers under quarantine conditions. A modified Gompertz model was used to analyze the disease-time relatiobbnships and provided information on the rate of infection progression (rg) and time delay to the start of symptoms (t0). The disease-pathogen-dose relationships were analyzed according to a hyperbolic saturation model in which the median effective dose (ED50) of the pathogen and maximum disease level (ymax) were determined. Localized infiltration into the leaf mesophile resulted in the early (short t0) but slow (low rg) development of infection whereas in leaves pricked with clamps disease symptoms developed late (long t0) but rapidly (high rg). Paintbrush inoculation of the plants resulted in an incubation period of medium length, a moderate rate of infection progression, and low ymax values. In leaves inoculated with scissors, fire-blight symptoms developed early (short t0) and rapidly (high rg), and with the lowest ED50 and the highest ymax

Body composition: overview of methods and future directions of research.

A short overview is given on the most important analytical body composition methods. Principles of the methods and advantages and limitations of the methods are discussed also in relation to other fields of research such as energy metabolism. Attention is given to some new developments in body composition research such as chemical multiple-compartment models, computerized tomography or nuclear magnetic resonance imaging (tissue level), and multifrequency bioelectrical impedance. Possible future directions of body composition research in the light of these new developments are discussed.

A comparative analysis of two methods for the calculation of electric-field-induced perturbations to molecular vibration

Two common methods of accounting for electric-field-induced perturbations to molecular vibration are analyzed and compared. The first method is based on a perturbation-theoretic treatment and the second on a finite-field treatment. The relationship between the two, which is not immediately apparent, is made by developing an algebraic formalism for the latter. Some of the higher-order terms in this development are documented here for the first time. As well as considering vibrational dipole polarizabilities and hyperpolarizabilities, we also make mention of the vibrational Stark effec

A comparative analysis by means of quantum molecular similarity measures of density distributions derived from conventional ab initio and density functional methods

A procedure based on quantum molecular similarity measures (QMSM) has been used to compare electron densities obtained from conventional ab initio and density functional methodologies at their respective optimized geometries. This method has been applied to a series of small molecules which have experimentally known properties and molecular bonds of diverse degrees of ionicity and covalency. Results show that in most cases the electron densities obtained from density functional methodologies are of a similar quality than post-Hartree-Fock generalized densities. For molecules where Hartree-Fock methodology yields erroneous results, the density functional methodology is shown to yield usually more accurate densities than those provided by the second order Møller-Plesset perturbation theory

Two complementary molecular energy decomposition schemes: the Mayer and Ziegler-Rauk methods in comparison

In the present paper we discuss and compare two different energy decomposition schemes: Mayer's Hartree-Fock energy decomposition into diatomic and monoatomic contributions [Chem. Phys. Lett. 382, 265 (2003)], and the Ziegler-Rauk dissociation energy decomposition [Inorg. Chem. 18, 1558 (1979)]. The Ziegler-Rauk scheme is based on a separation of a molecule into fragments, while Mayer's scheme can be used in the cases where a fragmentation of the system in clearly separable parts is not possible. In the Mayer scheme, the density of a free atom is deformed to give the one-atom Mulliken density that subsequently interacts to give rise to the diatomic interaction energy. We give a detailed analysis of the diatomic energy contributions in the Mayer scheme and a close look onto the one-atom Mulliken densities. The Mulliken density ρA has a single large maximum around the nuclear position of the atom A, but exhibits slightly negative values in the vicinity of neighboring atoms. The main connecting point between both analysis schemes is the electrostatic energy. Both decomposition schemes utilize the same electrostatic energy expression, but differ in how fragment densities are defined. In the Mayer scheme, the electrostatic component originates from the interaction of the Mulliken densities, while in the Ziegler-Rauk scheme, the undisturbed fragment densities interact. The values of the electrostatic energy resulting from the two schemes differ significantly but typically have the same order of magnitude. Both methods are useful and complementary since Mayer's decomposition focuses on the energy of the finally formed molecule, whereas the Ziegler-Rauk scheme describes the bond formation starting from undeformed fragment densities

Personality traits and virtual reality performance.

BACKGROUND: Surgeons' personalities have been described as different from those of the general population, but this was based on small descriptive studies limited by the choice of evaluation instrument. Furthermore, although the importance of the human factor in team performance has been recognized, the effect of personality traits on technical performance is unknown. This study aimed to compare surgical residents' personality traits with those of the general population and to evaluate whether an association exists between their personality traits and technical performance using a virtual reality (VR) laparoscopy simulator. METHODS: In this study, 95 participants (54 residents with basic, 29 with intermediate laparoscopic experience, and 12 students) underwent personality assessment using the NEO-Five Factor Inventory and performed five VR tasks of the Lap Mentor? basic tasks module. The residents' personality traits were compared with those of the general population, and the association between VR performance and personality traits was investigated. RESULTS: Surgical residents showed personality traits different from those of the general population, demonstrating lower neuroticism, higher extraversion and conscientiousness, and male residents showed greater openness. In the multivariable analysis, adjusted for gender and surgical experience, none of the personality traits was found to be an independent predictor of technical performance. CONCLUSIONS: Surgical residents present distinct personality traits that differ from those of the general population. These traits were not found to be associated with technical performance in a virtual environment. The traits may, however, play an important role in team performance, which in turn is highly relevant for optimal surgical performance.

Plasma leptin levels in men are not related to the development of lipoatrophy during antiretroviral therapy.

OBJECTIVES: To assess the correlations between the hormone leptin and lipoatrophy in HIV-positive, treatment-naive patients on combination antiretroviral therapy (cART). DESIGN: Case-control study nested in a multicentre cohort of HIV-infected adults. Cases were patients that developed lipoatrophy and controls those who did not. PATIENTS AND METHODS: Clinical parameters and plasma leptin determinations were studied in 97 HIV-1-infected, treatment-naive Caucasian men (10 cases and 87 controls) on an unchanged and virologically successful drug regimen with a zidovudine/lamivudine backbone at baseline and after 2 years of cART. The association of plasma leptin levels and the development of lipoatrophy was investigated. RESULTS: Two years of cART was not associated with a change in plasma leptin levels. Plasma leptin levels remained sensible to changes in body mass index. There was no difference in leptin levels between patients who developed lipoatrophy and controls, neither before nor after cART. The only predictor of development of lipoatrophy was a higher age (P = 0.02). CONCLUSIONS: Leptin as measured in plasma is unlikely to play a major role in the genesis of lipoatrophy.

Simulation methods with extended stability for stiff biochemical kinetics

Background: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows. Results: In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be well-behaved, leading to significantly larger step sizes.Conclusions: The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems.