Hybrid Multiscale Finite Volume method for two-phase flow in porous media

We present a novel hybrid (or multiphysics) algorithm, which couples pore-scale and Darcy descriptions of two-phase flow in porous media. The flow at the pore-scale is described by the Navier?Stokes equations, and the Volume of Fluid (VOF) method is used to model the evolution of the fluid?fluid interface. An extension of the Multiscale Finite Volume (MsFV) method is employed to construct the Darcy-scale problem. First, a set of local interpolators for pressure and velocity is constructed by solving the Navier?Stokes equations; then, a coarse mass-conservation problem is constructed by averaging the pore-scale velocity over the cells of a coarse grid, which act as control volumes; finally, a conservative pore-scale velocity field is reconstructed and used to advect the fluid?fluid interface. The method relies on the localization assumptions used to compute the interpolators (which are quite straightforward extensions of the standard MsFV) and on the postulate that the coarse-scale fluxes are proportional to the coarse-pressure differences. By numerical simulations of two-phase problems, we demonstrate that these assumptions provide hybrid solutions that are in good agreement with reference pore-scale solutions and are able to model the transition from stable to unstable flow regimes. Our hybrid method can naturally take advantage of several adaptive strategies and allows considering pore-scale fluxes only in some regions, while Darcy fluxes are used in the rest of the domain. Moreover, since the method relies on the assumption that the relationship between coarse-scale fluxes and pressure differences is local, it can be used as a numerical tool to investigate the limits of validity of Darcy's law and to understand the link between pore-scale quantities and their corresponding Darcy-scale variables.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

Mesurer la stigmatisaion perçue chez les personnes souffrant de troubles psychiques : traduction française, validation et adaptation de la Stigma Scale

L'objectif de l'étude présentée est d'adapter et de valider une version française de la Stigma Scale (King, 2007) auprès d'une population de personnes souffrant de troubles psychiques. Dans une première phase, la stabilité temporelle (fidélité test-retest), la cohérence interne et la validité convergente de l'instrument original à 28 items traduit en français ont été évaluées auprès d'un échantillon de 183 patients. Les résultats d'analyses factorielles confirmatoires ne nous ont pas permis de confirmer la structure originale de l'instrument. Nous avons donc proposé, sur la base des résultats d'une analyse factorielle exploratoire, une version courte de l'échelle de stigmatisation (9 items) qui conserve la structure en trois facteurs du modèle original. Dans une deuxième phase, nous avons examiné les qualités psychométriques et validé cette version abrégée de l'échelle de stigmatisation auprès d'un second échantillon de 234 patients. Les indices d'ajustements de notre analyse factorielle confirmatoire confirme la structure en trois facteurs de la version abrégée de la Stigma Scale. Les résultats suggèrent que la version française abrégée de l'échelle de stigmatisation constitue un instrument utile, fiable et valide dans l'autoévaluation de la stigmatisation perçue par des personnes souffrant de troubles psychiques. - Aim People suffering from mental illness are exposed to stigma. However, only few tools are available to assess stigmatization as perceived from the patient's perspective. The aim of this study is to adapt and validate a French version of the Stigma Scale (King, 2007). This self-report questionnaire has a three-factor structure: discrimination, disclosure and positive aspects of mental illness. Discrimination subscale refers to perceived negative reactions by others. Disclosure subscale refers mainly to managing disclosure to avoid discrimination and finally positive aspects subscale taps into how patients are becoming more accepting, more understanding toward their illness. Method In the first step, internal consistency, convergent validity and test-retest reliability of the French adaptation of the 28-item scale have been assessed on a sample of 183 patients. Results of confirmatory factor analyses (CFA) did not confirm the hypothesized structure. In light of the failed attempts to validate the original version, an alternative 9-item short-form version of the Stigma Scale, maintaining the integrity of the original model, was developed based on results of exploratory factor analyses in the first sample and cross- validated in a new sample of 234 patients. Results Results of CFA did not confirm that the data fitted well to the three-factor model of the 28-item Stigma Scale (χ2/άί=2.02, GFI=0.77, AGFI=0.73, RMSEA=0.07, CFI=0.77 et NNFI=0.75). Cronbach's α are excellent for discrimination (0.84) and disclosure (0.83) subscales but poor for potential positive aspects (0.46). External validity is satisfactory. Overall Stigma Scale total score is negatively correlated with score on Rosenberg's Self-Esteem Scale (r = -0.49), and each sub-scale is significantly correlated with a visual analogue scale that refers to the specific aspect of stigma (0.43 < |r| < 0.60). Intraclass correlation coefficients between 0.68 and 0.89 indicate good test- retest reliability. Results of CFA demonstrate that the items chosen for the short version of the Stigma Scale have the expected fit properties fa2/df=1.02, GFI=0.98, AGFI=0.98, RMSEA=0.01, CFI=1.0 et NNFI=1.0). Considering the small number (3 items) of items in each subscales of the short version of the Stigma Scale, a coefficients for the discrimination (0.57), disclosure (0.80) and potential positive aspects subscales (0.62) are considered as good. Conclusion Our results suggest that the 9-item French short-version of the Stigma Scale is a useful, reliable and valid self-report questionnaire to assess perceived stigmatization in people suffering from mental illness. The time of completion is really short and questions are well understood and accepted by the patients.

Validation of an adapted falls efficacy scale in older rehabilitation patients.

OBJECTIVE: To determine the psychometric properties of an adapted version of the Falls Efficacy Scale (FES) in older rehabilitation patients. DESIGN: Cross-sectional survey. SETTING: Postacute rehabilitation facility in Switzerland. PARTICIPANTS: Seventy elderly persons aged 65 years and older receiving postacute, inpatient rehabilitation. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: FES questions asked about subject's confidence (range, 0 [none]-10 [full]) in performing 12 activities of daily living (ADLs) without falling. Construct validity was assessed using correlation with measures of physical (basic ADLs [BADLs]), cognitive (Mini-Mental State Examination [MMSE]), affective (15-item Geriatric Depression Scale [GDS]), and mobility (Performance Oriented Mobility Assessment [POMA]) performance. Predictive validity was assessed using the length of rehabilitation stay as the outcome. To determine test-retest reliability, FES administration was repeated in a random subsample (n=20) within 72 hours. RESULTS: FES scores ranged from 10 to 120 (mean, 88.7+/-26.5). Internal consistency was optimal (Cronbach alpha=.90), and item-to-total correlations were all significant, ranging from .56 (toilet use) to .82 (reaching into closets). Test-retest reliability was high (intraclass correlation coefficient, .97; 95% confidence interval, .95-.99; P<.001). Subjects reporting a fall in the previous year had lower FES scores than nonfallers (85.0+/-25.2 vs 94.4+/-27.9, P=.054). The FES correlated with POMA (Spearman rho=.40, P<.001), MMSE (rho=.37, P=.001), BADL (rho=.43, P<.001), and GDS (rho=-.53, P<.001) scores. These relationships remained significant in multivariable analysis for BADLs and GDS, confirming FES construct validity. There was a significant inverse relationship between FES score and the length of rehabilitation stay, independent of sociodemographic, functional, cognitive, and fall status. CONCLUSIONS: This adapted FES is reliable and valid in older patients undergoing postacute rehabilitation. The independent association between poor falls efficacy and increased length of stay has not been previously described and needs further investigations.

Use of high-resolution geophysical data to characterize heterogeneous aquifers: influence of data integration method on hydrological predictions

The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. The investigation of exactly how much benefit can be brought by geophysical data in terms of its effect on hydrological predictions, however, has received considerably less attention in the literature. Here, we examine the potential hydrological benefits brought by a recently introduced simulated annealing (SA) conditional stochastic simulation method designed for the assimilation of diverse hydrogeophysical data sets. We consider the specific case of integrating crosshole ground-penetrating radar (GPR) and borehole porosity log data to characterize the porosity distribution in saturated heterogeneous aquifers. In many cases, porosity is linked to hydraulic conductivity and thus to flow and transport behavior. To perform our evaluation, we first generate a number of synthetic porosity fields exhibiting varying degrees of spatial continuity and structural complexity. Next, we simulate the collection of crosshole GPR data between several boreholes in these fields, and the collection of porosity log data at the borehole locations. The inverted GPR data, together with the porosity logs, are then used to reconstruct the porosity field using the SA-based method, along with a number of other more elementary approaches. Assuming that the grid-cell-scale relationship between porosity and hydraulic conductivity is unique and known, the porosity realizations are then used in groundwater flow and contaminant transport simulations to assess the benefits and limitations of the different approaches.

Malaria diagnosis from pooled blood samples: comparative analysis of real-time PCR, nested PCR and immunoassay as a platform for the molecular and serological diagnosis of malaria on a large-scale

Malaria diagnoses has traditionally been made using thick blood smears, but more sensitive and faster techniques are required to process large numbers of samples in clinical and epidemiological studies and in blood donor screening. Here, we evaluated molecular and serological tools to build a screening platform for pooled samples aimed at reducing both the time and the cost of these diagnoses. Positive and negative samples were analysed in individual and pooled experiments using real-time polymerase chain reaction (PCR), nested PCR and an immunochromatographic test. For the individual tests, 46/49 samples were positive by real-time PCR, 46/49 were positive by nested PCR and 32/46 were positive by immunochromatographic test. For the assays performed using pooled samples, 13/15 samples were positive by real-time PCR and nested PCR and 11/15 were positive by immunochromatographic test. These molecular methods demonstrated sensitivity and specificity for both the individual and pooled samples. Due to the advantages of the real-time PCR, such as the fast processing and the closed system, this method should be indicated as the first choice for use in large-scale diagnosis and the nested PCR should be used for species differentiation. However, additional field isolates should be tested to confirm the results achieved using cultured parasites and the serological test should only be adopted as a complementary method for malaria diagnosis.

Identification of potential rockfall source areas at a regional scale using a DEM-based geomorphometric analysis

The availability of high resolution Digital Elevation Models (DEM) at a regional scale enables the analysis of topography with high levels of detail. Hence, a DEM-based geomorphometric approach becomes more accurate for detecting potential rockfall sources. Potential rockfall source areas are identified according to the slope angle distribution deduced from high resolution DEM crossed with other information extracted from geological and topographic maps in GIS format. The slope angle distribution can be decomposed in several Gaussian distributions that can be considered as characteristic of morphological units: rock cliffs, steep slopes, footslopes and plains. A terrain is considered as potential rockfall sources when their slope angles lie over an angle threshold, which is defined where the Gaussian distribution of the morphological unit "Rock cliffs" become dominant over the one of "Steep slopes". In addition to this analysis, the cliff outcrops indicated by the topographic maps were added. They contain however "flat areas", so that only the slope angles values above the mode of the Gaussian distribution of the morphological unit "Steep slopes" were considered. An application of this method is presented over the entire Canton of Vaud (3200 km2), Switzerland. The results were compared with rockfall sources observed on the field and orthophotos analysis in order to validate the method. Finally, the influence of the cell size of the DEM is inspected by applying the methodology over six different DEM resolutions.

Multi-scale label interaction to improve object detection and segmentation

The project aims at advancing the state of the art in the use of context information for classification of image and video data. The use of context in the classification of images has been showed of great importance to improve the performance of actual object recognition systems. In our project we proposed the concept of Multi-scale Feature Labels as a general and compact method to exploit the local and global context. The feature extraction from the discriminative probability or classification confidence label field is of great novelty. Moreover the use of a multi-scale representation of the feature labels lead to a compact and efficient description of the context. The goal of the project has been also to provide a general-purpose method and prove its suitability in different image/video analysis problem. The two-year project generated 5 journal publications (plus 2 under submission), 10 conference publications (plus 2 under submission) and one patent (plus 1 pending). Of these publications, a relevant number make use of the main result of this project to improve the results in detection and/or segmentation of objects.

Diagnosis of muscular dystrophies at the nanometer scale

The diagnosis of muscular dystrophies or the assessment of the functional benefit of gene or cell therapies can be difficult, especially for poorly accessible muscles, and it often lacks a singlefiber resolution. In the present study, we evaluated whether muscle diseases can be diagnosed from small biopsies using atomic force microscopy (AFM). AFM was shown to provide a sensitive and quantitative description of the resistance of normal and dystrophic myofibers within live muscle tissues explanted from Duchenne mdx mice. The rescue of dystrophin expression by gene therapy approaches led to the functional recovery of treated dystrophic muscle fibers, as probed using AFM and by in situ wholemuscle strength measurements. Comparison of muscles treated with viral or non-viral vectors indicated that the efficacy of the gene transfer approaches could be distinguished with a single myofiber resolution. This indicated full correction of the resistance to deformation in nearly all of the muscle fibers treated with an adeno-associated viral vector that mediates exon-skipping on the dystrophin mRNA. Having shown that AFM can provide a quantitative assessment of the expression of muscle proteins and of the muscular function in animal models, we assessed myofiber resistance in the context of human muscular dystrophies and myopathies. Thus, various forms of human Becker syndrome can also be detected using AFM in blind studies of small frozen biopsies from human patients. Interestingly, it also allowed the detection of anomalies in a fraction of the muscle fibers from patients showing a muscle weakness that could not be attributed to a known molecular or genetic defect. Overall, we conclude that AFM may provide a useful method to complement current diagnosis tools of known and unknown muscular diseases, in research and in a clinical context.

Symptoms, comorbidity, and clinical course of depression in immigrants: Putting psychopathology in context.

BACKGROUND: Migration is considered a depression risk factor when associated with psychosocial adversity, but its impact on depression's clinical characteristics has not been specifically studied. We compared 85 migrants to 34 controls, examining depression's severity, symptomatology, comorbidity profile and clinical course. METHOD: A MINI interview modified to assess course characteristics was used to assign DSM-IV axis I diagnoses; medical files were used for Somatoform Disorders. Severity was assessed with the Montgomery-Asberg scale. Wherever possible, we adjusted comparisons for age and gender using logistic and linear regressions. RESULTS: Depression in migrants was characterized by higher comorbidity (mostly somatoform and anxiety disorders), higher severity, and a non-recurrent, chronic course. LIMITATIONS: Our sample comes from a single center, and should be replicated in other health care facilities and other countries. Somatoform disorder diagnoses were solely based on file-content. CONCLUSION: Depression in migrants presented as a complex, chronic clinical picture. Most of our migrant patients experienced significant psychosocial adversity before and after migration: beyond cultural issues, our results suggest that psychosocial adversity impacts on the clinical expression of depression. Our study also suggests that migration associated with psychosocial adversity might play a specific etiological role, resulting in a distinct clinical picture, questioning the DSM-IV unitarian model of depression. The chronic course might indicate a resistance to standard therapeutic regimen and hints at the necessity of developing specific treatment strategies, adapted to the individual patients and their specific context.

Cultural adaptation of the scale Pain Assessment in Advanced Dementia – PAINAD to Brazil

Objective: To translate and culturally adapt to Brazil the scale Pain Assessment in Advanced Dementia(PAINAD).Method: The cultural adaptation process followed the methodology of a theorical reference, in five steps: translation to Brazilian Portuguese, consensual version of translations, back-translation to the original language, revision by a committee of specialists in the field and a equivalency pre-test. The instrument was assessed and applied by 27 health professionals in the last step. Results: The Escala de Avaliação de Dor em Demência Avançada was culturally adapted to Brazil and presented semantic equivalency to the original, besides clarity, applicability and easy comprehension of the instrument items. Conclusion: This process secured the psychometric properties as the reliability and content validity of the referred scale.


Study of adaptation and validation of the Practice environment scale of the nursing work index for the portuguese reality

Objective: Testing the psychometric properties of the Portuguese version of the Practice Environment Scale of the Nursing Work Index. Method: A descriptive, analytical and cross-sectional study, for the cross-cultural adaptation and validation of the psychometric properties of the scale. The study participants were 236 nurses from two hospitals in the regions of Lisbon and Vale do Tejo. Results: The 0.92 Cronbach’s alpha was obtained for overall reliability and support of a five-dimension structure. Conclusion: The excellent quality of adjustment of analysis confirms the validity of the adapted version to hospital care settings, although there was no total coincidence of items in the five dimensions


Multi-scale integration and predictability in resting state brain activity.

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.

Distributional equivalence and subcompositional coherence in the analysis of contingency tables, ratio-scale measurements and compositional data

We consider two fundamental properties in the analysis of two-way tables of positive data: the principle of distributional equivalence, one of the cornerstones of correspondence analysis of contingency tables, and the principle of subcompositional coherence, which forms the basis of compositional data analysis. For an analysis to be subcompositionally coherent, it suffices to analyse the ratios of the data values. The usual approach to dimension reduction in compositional data analysis is to perform principal component analysis on the logarithms of ratios, but this method does not obey the principle of distributional equivalence. We show that by introducing weights for the rows and columns, the method achieves this desirable property. This weighted log-ratio analysis is theoretically equivalent to spectral mapping , a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra. The close relationship between spectral mapping and correspondence analysis is also explained, as well as their connection with association modelling. The weighted log-ratio methodology is applied here to frequency data in linguistics and to chemical compositional data in archaeology.

A new alternative method for testing skin irritation using a human skin model: a pilot study.

Studies assessing skin irritation to chemicals have traditionally used laboratory animals; however, such methods are questionable regarding their relevance for humans. New in vitro methods have been validated, such as the reconstructed human epidermis (RHE) model (Episkin®, Epiderm®). The comparison (accuracy) with in vivo results such as the 4-h human patch test (HPT) is 76% at best (Epiderm®). There is a need to develop an in vitro method that better simulates the anatomo-pathological changes encountered in vivo. To develop an in vitro method to determine skin irritation using human viable skin through histopathology, and compare the results of 4 tested substances to the main in vitro methods and in vivo animal method (Draize test). Human skin removed during surgery was dermatomed and mounted on an in vitro flow-through diffusion cell system. Ten chemicals with known non-irritant (heptylbutyrate, hexylsalicylate, butylmethacrylate, isoproturon, bentazon, DEHP and methylisothiazolinone (MI)) and irritant properties (folpet, 1-bromohexane and methylchloroisothiazolinone (MCI/MI)), a negative control (sodiumchloride) and a positive control (sodiumlaurylsulphate) were applied. The skin was exposed at least for 4h. Histopathology was performed to investigate irritation signs (spongiosis, necrosis, vacuolization). We obtained 100% accuracy with the HPT model; 75% with the RHE models and 50% with the Draize test for 4 tested substances. The coefficients of variation (CV) between our three test batches were <0.1, showing good reproducibility. Furthermore, we reported objectively histopathological irritation signs (irritation scale): strong (folpet), significant (1-bromohexane), slight (MCI/MI at 750/250ppm) and none (isoproturon, bentazon, DEHP and MI). This new in vitro test method presented effective results for the tested chemicals. It should be further validated using a greater number of substances; and tested in different laboratories in order to suitably evaluate reproducibility.