A Monte Carlo method for accelerating the computation of animated radiosity sequences

Realistic rendering animation is known to be an expensive processing task when physically-based global illumination methods are used in order to improve illumination details. This paper presents an acceleration technique to compute animations in radiosity environments. The technique is based on an interpolated approach that exploits temporal coherence in radiosity. A fast global Monte Carlo pre-processing step is introduced to the whole computation of the animated sequence to select important frames. These are fully computed and used as a base for the interpolation of all the sequence. The approach is completely view-independent. Once the illumination is computed, it can be visualized by any animated camera. Results present significant high speed-ups showing that the technique could be an interesting alternative to deterministic methods for computing non-interactive radiosity animations for moderately complex scenarios

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.

Molecular markers allow sibling species identification in red wood ants (Formica rufa group)

Red wood ants (Formica rufa group) constitute a group of species that are considered to be among the most promising bioindicators in forest ecosystems. However, because of their morphological similarity and intraspecific variability, morphological species identification can be difficult. Considerable expertise is necessary to discriminate between the sibling species F. lugubris and F. paralugubris, two species that often live in sympatry in the same Alpine forests. New taxonomic tools providing rapid and reliable species identification are needed. We present a simple and reliable molecular technique based on mtDNA (COI gene) and a restriction enzyme for discriminating between F. lugubris and F. paralugubris. We confirm the validity of this method with a Bayesian analysis based on microsatellites. This new molecular tool represents a clear breakthrough for discriminating between F. lugubris and F. paralugubris and is likely to be helpful in large-scale biomonitoring.

A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis.

Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG.

Bayesian nash equilibrium in ''linear'' cournot models with private information about costs

Calculating explicit closed form solutions of Cournot models where firms have private information about their costs is, in general, very cumbersome. Most authors consider therefore linear demands and constant marginal costs. However, within this framework, the nonnegativity constraint on prices (and quantities) has been ignored or not properly dealt with and the correct calculation of all Bayesian Nash equilibria is more complicated than expected. Moreover, multiple symmetric and interior Bayesianf equilibria may exist for an open set of parameters. The reason for this is that linear demand is not really linear, since there is a kink at zero price: the general ''linear'' inverse demand function is P (Q) = max{a - bQ, 0} rather than P (Q) = a - bQ.

Bayesian Markov chain Monte Carlo inversion of geophysical data for the purpose of estimating the hydraulic properties of the unsaturated zone

Ground-penetrating radar (GPR) has the potential to provide valuable information on hydrological properties of the vadose zone because of their strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR data within a coupled geophysical-hydrological framework may allow for effective estimation of subsurface van-Genuchten-Mualem (VGM) parameters and their corresponding uncertainties. An important and still unresolved issue, however, is how to best integrate GPR data into a stochastic inversion in order to estimate the VGM parameters and their uncertainties, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first introduce a fully Bayesian inversion called Markov-chain-Monte-carlo (MCMC) strategy to perform the stochastic inversion of steady-state GPR data to estimate the VGM parameters and their uncertainties. Within this study, the choice of the prior parameter probability distributions from which potential model configurations are drawn and tested against observed data was also investigated. Analysis of both synthetic and field data collected at the Eggborough (UK) site indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when these data are combined with a realistic, informative prior. A subsequent study explore in detail the dynamic infiltration case, specifically to what extent time-lapse ZOP GPR data, collected during a forced infiltration experiment at the Arrenaes field site (Denmark), can help to quantify VGM parameters and their uncertainties using the MCMC inversion strategy. The findings indicate that the stochastic inversion of time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions. In turn, this significantly improves knowledge of the hydraulic properties, which are required to predict hydraulic behaviour. Finally, another aspect that needed to be addressed involved the comparison of time-lapse GPR data collected under different infiltration conditions (i.e., natural loading and forced infiltration conditions) to estimate the VGM parameters using the MCMC inversion strategy. The results show that for the synthetic example, considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions. When investigating data collected at the Arrenaes field site, further complications arised due to model error and showed the importance of also including a rigorous analysis of the propagation of model error with time and depth when considering time-lapse data. Although the efforts in this thesis were focused on GPR data, the corresponding findings are likely to have general applicability to other types of geophysical data and field environments. Moreover, the obtained results allow to have confidence for future developments in integration of geophysical data with stochastic inversions to improve the characterization of the unsaturated zone but also reveal important issues linked with stochastic inversions, namely model errors, that should definitely be addressed in future research.

Development of a cost-effective method for platelet-rich plasma (PRP) preparation for topical wound healing.

Platelet-rich plasma (PRP) is a volume of plasma fraction of autologous blood having platelet concentrations above baseline whole-blood values due to processing and concentration. PRP is used in various surgical fields to enhance soft-tissue and bone healing by delivering supra-physiological concentrations of autologous platelets at the site of tissue damage. These preparations may provide a good cellular source of various growth factors and cytokines, and modulate tissue response to injury. Common clinically available materials for blood preparations combined with a two-step centrifugation protocol at 280g each, to ensure cellular component integrity, provided platelet preparations which were concentrated 2-3 fold over total blood values. Costs were shown to be lower than those of other methods which require specific equipment and high-cost disposables, while safety and traceability can be increased. PRP can be used for the treatment of wounds of all types including burns and also of split-thickness skin graft donor sites, which are frequently used in burn management. The procedure can be standardized and is easy to adapt in clinical settings with minimal infrastructure, thus enabling large numbers of patients to benefit from a form of cellular therapy.

Spatial relationship between the atmospheric circulation and the precipitation measured in the western Swiss Alps by means of the analogue method

An adaptation technique based on the synoptic atmospheric circulation to forecast local precipitation, namely the analogue method, has been implemented for the western Swiss Alps. During the calibration procedure, relevance maps were established for the geopotential height data. These maps highlight the locations were the synoptic circulation was found of interest for the precipitation forecasting at two rain gauge stations (Binn and Les Marécottes) that are located both in the alpine Rhône catchment, at a distance of about 100 km from each other. These two stations are sensitive to different atmospheric circulations. We have observed that the most relevant data for the analogue method can be found where specific atmospheric circulation patterns appear concomitantly with heavy precipitation events. Those skilled regions are coherent with the atmospheric flows illustrated, for example, by means of the back trajectories of air masses. Indeed, the circulation recurrently diverges from the climatology during days with strong precipitation on the southern part of the alpine Rhône catchment. We have found that for over 152 days with precipitation amount above 50 mm at the Binn station, only 3 did not show a trajectory of a southerly flow, meaning that such a circulation was present for 98% of the events. Time evolution of the relevance maps confirms that the atmospheric circulation variables have significantly better forecasting skills close to the precipitation period, and that it seems pointless for the analogue method to consider circulation information days before a precipitation event as a primary predictor. Even though the occurrence of some critical circulation patterns leading to heavy precipitation events can be detected by precursors at remote locations and 1 week ahead (Grazzini, 2007; Martius et al., 2008), time extrapolation by the analogue method seems to be rather poor. This would suggest, in accordance with previous studies (Obled et al., 2002; Bontron and Obled, 2005), that time extrapolation should be done by the Global Circulation Model, which can process atmospheric variables that can be used by the adaptation method.

Combined laparoscopic-endoscopic method using an omental plug for therapy of gastroduodenal ulcer perforation.

BACKGROUND: Laparoscopic techniques have been proposed as an alternative to open surgery for therapy of peptic ulcer perforation. They provide better postoperative comfort and absence of parietal complications, but leakage occurs in 5% of cases. We describe a new method combining laparoscopy and endoluminal endoscopy, designed to ensure complete closure of the perforation. METHODS: Six patients with anterior ulcer perforations (4 duodenal, 2 gastric) underwent a concomitant laparoscopy and endoluminal endoscopy with closure of the orifice by an omental plug attracted into the digestive tract. RESULTS: All perforations were sealed. The mean operating time was 72 minutes. The mean hospital stay was 5.5 days. There was no morbidity and no mortality. At the 30-day evaluation all ulcers but one (due to Helicobacter pylori persistence) were healed. CONCLUSIONS: This method is safe and effective. Its advantages compared with open surgery or laparoscopic patching as well as its cost-effectiveness should be studied in prospective randomized trials.

Response-to-comments about: "Is it really the method for carbon dioxide determination in human postmortem cardiac gas samples using Headspace-Gas Chromatography-Mass Spectrometry valid?" from T. Saffaj and B. Ihssane

Saffaj et al. recently criticized our method of monitoring carbon dioxide in human postmortem cardiac gas samples using Headspace-Gas Chromatography-Mass Spectrometry. According to the authors, their demonstration, based on the latest SFSTP guidelines (established after 2007 [1,2]) fitted for the validation of drug monitoring bioanalytical methods, has put in evidence potential errors. However, our validation approach was built using SFSTP guidelines established before 2007 [3-6]. We justify the use of these guidelines because of the post-mortem context of the study (and not clinical) and the gaseous state of the sample (and not solid or liquid). Using these guidelines, our validation remains correct.

A systematic and feasible method for computing nuclear contributions to electrical properties of polyatomic molecules

An analytic method to evaluate nuclear contributions to electrical properties of polyatomic molecules is presented. Such contributions control changes induced by an electric field on equilibrium geometry (nuclear relaxation contribution) and vibrational motion (vibrational contribution) of a molecular system. Expressions to compute the nuclear contributions have been derived from a power series expansion of the potential energy. These contributions to the electrical properties are given in terms of energy derivatives with respect to normal coordinates, electric field intensity or both. Only one calculation of such derivatives at the field-free equilibrium geometry is required. To show the useful efficiency of the analytical evaluation of electrical properties (the so-called AEEP method), results for calculations on water and pyridine at the SCF/TZ2P and the MP2/TZ2P levels of theory are reported. The results obtained are compared with previous theoretical calculations and with experimental values

Adaptação para a língua portuguesa e validação do Lunney Scoring Method for Rating Accuracy of Nursing Diagnoses

O Lunney Scoring Method for Rating Accuracy of Nursing Diagnoses (LSM) é uma escala de diferencial semântico que foi desenvolvida por Lunney para estimar a acurácia dos diagnósticos de enfermagem. O objetivo deste estudo foi adaptar o LSM para a língua portuguesa e avaliar as sua propriedades psicométricas. A escala original foi traduzida para o português, revertida para o inglês e as duas versões em inglês foram comparadas para ajustar a versão em português que passou a ser denominada Escala de Acurácia de Diagnóstico de Enfermagem de Lunney - EADE. Quatro enfermeiras foram orientadas sobre a EADE e a aplicaram em 159 diagnósticos formulados para 26 pacientes de três estudos primários com base nos registros de entrevista e exame físico de cada paciente. Os índices Kappa de Cohen mostraram ausência de concordância entre as avaliadoras, o que indica que o instrumento adaptado não tem confiabilidade satisfatória. Em virtude desse resultado, não foi realizada estimativa de validade.

Select-divide-and-conquer method for large-scale configuration interaction

A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,...,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0={T0egy, T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates KS with attributes above T1≤T0. An eigenproblem of dimension d0+d1 for S0+S 1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j≥2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson's eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0, 1, 2,...,R} regulate accuracy; for large-dimensional S, high accuracy requires S 0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24 × 106, involving 1.2 × 1012 nonzero matrix elements, and 8.4×109 Slater determinants