Dissolution-Precipitation in Porous Media: Experiments and Modelling

The evolution of porosity due to dissolution/precipitation processes of minerals and the associated change of transport parameters are of major interest for natural geological environments and engineered underground structures. We designed a reproducible and fast to conduct 2D experiment, which is flexible enough to investigate several process couplings implemented in the numerical code OpenGeosys-GEM (OGS-GEM). We investigated advective-diffusive transport of solutes, effect of liquid phase density on advective transport, and kinetically controlled dissolution/precipitation reactions causing porosity changes. In addition, the system allowed to investigate the influence of microscopic (pore scale) processes on macroscopic (continuum scale) transport. A Plexiglas tank of dimension 10 × 10 cm was filled with a 1 cm thick reactive layer consisting of a bimodal grain size distribution of celestite (SrSO4) crystals, sandwiched between two layers of sand. A barium chloride solution was injected into the tank causing an asymmetric flow field to develop. As the barium chloride reached the celestite region, dissolution of celestite was initiated and barite precipitated. Due to the higher molar volume of barite, its precipitation caused a porosity decrease and thus also a decrease in the permeability of the porous medium. The change of flow in space and time was observed via injection of conservative tracers and analysis of effluents. In addition, an extensive post-mortem analysis of the reacted medium was conducted. We could successfully model the flow (with and without fluid density effects) and the transport of conservative tracers with a (continuum scale) reactive transport model. The prediction of the reactive experiments initially failed. Only the inclusion of information from post-mortem analysis gave a satisfactory match for the case where the flow field changed due to dissolution/precipitation reactions. We concentrated on the refinement of post-mortem analysis and the investigation of the dissolution/precipitation mechanisms at the pore scale. Our analytical techniques combined scanning electron microscopy (SEM) and synchrotron X-ray micro-diffraction/micro-fluorescence performed at the XAS beamline (Swiss Light Source). The newly formed phases include an epitaxial growth of barite micro-crystals on large celestite crystals (epitaxial growth) and a nano-crystalline barite phase (resulting from the dissolution of small celestite crystals) with residues of celestite crystals in the pore interstices. Classical nucleation theory, using well-established and estimated parameters describing barite precipitation, was applied to explain the mineralogical changes occurring in our system. Our pore scale investigation showed limits of the continuum scale reactive transport model. Although kinetic effects were implemented by fixing two distinct rates for the dissolution of large and small celestite crystals, instantaneous precipitation of barite was assumed as soon as oversaturation occurred. Precipitation kinetics, passivation of large celestite crystals and metastability of supersaturated solutions, i.e. the conditions under which nucleation cannot occur despite high supersaturation, were neglected. These results will be used to develop a pore scale model that describes precipitation and dissolution of crystals at the pore scale for various transport and chemical conditions. Pore scale modelling can be used to parameterize constitutive equations to introduce pore-scale corrections into macroscopic (continuum) reactive transport models. Microscopic understanding of the system is fundamental for modelling from the pore to the continuum scale.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

Citizen science reveals unexpected continental-scale evolutionary change in a model organism

Organisms provide some of the most sensitive indicators of climate change and evolutionary responses are becoming apparent in species with short generation times. Large datasets on genetic polymorphism that can provide an historical benchmark against which to test for recent evolutionary responses are very rare, but an exception is found in the brown-lipped banded snail (Cepaea nemoralis). This species is sensitive to its thermal environment and exhibits several polymorphisms of shell colour and banding pattern affecting shell albedo in the majority of populations within its native range in Europe. We tested for evolutionary changes in shell albedo that might have been driven by the warming of the climate in Europe over the last half century by compiling an historical dataset for 6,515 native populations of C. nemoralis and comparing this with new data on nearly 3,000 populations. The new data were sampled mainly in 2009 through the Evolution MegaLab, a citizen science project that engaged thousands of volunteers in 15 countries throughout Europe in the biggest such exercise ever undertaken. A known geographic cline in the frequency of the colour phenotype with the highest albedo (yellow) was shown to have persisted and a difference in colour frequency between woodland and more open habitats was confirmed, but there was no general increase in the frequency of yellow shells. This may have been because snails adapted to a warming climate through behavioural thermoregulation. By contrast, we detected an unexpected decrease in the frequency of Unbanded shells and an increase in the Mid-banded morph. Neither of these evolutionary changes appears to be a direct response to climate change, indicating that the influence of other selective agents, possibly related to changing predation pressure and habitat change with effects on micro-climate.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by process-based modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under http://www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws. We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10 m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25 m resolution.

Dimensional approaches to schizophrenia: A comparison of the Bern Psychopathology scale and the five-factor model of the Positive and Negative Syndrome Scale

The aim was to examine to what extent the dimensions of the BPS map the five factors derived from the PANSS in order to explore the level of agreement of these alternative dimensional approaches in patients with schizophrenia. 149 inpatients with schizophrenia spectrum disorders were recruited. Psychopathological symptoms were assessed with the Bern Psychopathology Scale (BPS) and the Positive and Negative Syndrome Scale (PANSS). Linear regression analyses were conducted to explore the association between the factors and the items of the BPS. The robustness of patterns was evaluated. An understandable overlap of both approaches was found for positive and negative symptoms and excitement. The PANSS positive factor was associated with symptoms of the affect domain in terms of both inhibition and disinhibition, the PANSS negative factor with symptoms of all three domains of the BPS as an inhibition and the PANSS excitement factor with an inhibition of the affect domain and a disinhibition of the language and motor domains. The results show that here is only a partial overlap between the system-specific approach of the BPS and the five-factor PANSS model. A longitudinal assessment of psychopathological symptoms would therefore be of interest.

Single fluoroscopic image based 2D/3D reconstruction of a scaled, patient-specific vertebral model

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes

Background Prognostic models have been developed for patients infected with HIV-1 who start combination antiretroviral therapy (ART) in high-income countries, but not for patients in sub-Saharan Africa. We developed two prognostic models to estimate the probability of death in patients starting ART in sub-Saharan Africa. Methods We analysed data for adult patients who started ART in four scale-up programmes in Côte d'Ivoire, South Africa, and Malawi from 2004 to 2007. Patients lost to follow-up in the first year were excluded. We used Weibull survival models to construct two prognostic models: one with CD4 cell count, clinical stage, bodyweight, age, and sex (CD4 count model); and one that replaced CD4 cell count with total lymphocyte count and severity of anaemia (total lymphocyte and haemoglobin model), because CD4 cell count is not routinely measured in many African ART programmes. Death from all causes in the first year of ART was the primary outcome. Findings 912 (8·2%) of 11 153 patients died in the first year of ART. 822 patients were lost to follow-up and not included in the main analysis; 10 331 patients were analysed. Mortality was strongly associated with high baseline CD4 cell count (≥200 cells per μL vs <25; adjusted hazard ratio 0·21, 95% CI 0·17–0·27), WHO clinical stage (stages III–IV vs I–II; 3·45, 2·43–4·90), bodyweight (≥60 kg vs <45 kg; 0·23, 0·18–0·30), and anaemia status (none vs severe: 0·27, 0·20–0·36). Other independent risk factors for mortality were low total lymphocyte count, advanced age, and male sex. Probability of death at 1 year ranged from 0·9% (95% CI 0·6–1·4) to 52·5% (43·8–61·7) with the CD4 model, and from 0·9% (0·5–1·4) to 59·6% (48·2–71·4) with the total lymphocyte and haemoglobin model. Both models accurately predict early mortality in patients starting ART in sub-Saharan Africa compared with observed data. Interpretation Prognostic models should be used to counsel patients, plan health services, and predict outcomes for patients with HIV-1 infection in sub-Saharan Africa.

Millennial and sub-millennial scale climatic variations recorded in polar ice cores over the last glacial period

Since its discovery in Greenland ice cores, the millennial scale climatic variability of the last glacial period has been increasingly documented at all latitudes with studies focusing mainly on Marine Isotopic Stage 3 (MIS 3; 28–60 thousand of years before present, hereafter ka) and characterized by short Dansgaard-Oeschger (DO) events. Recent and new results obtained on the EPICA and NorthGRIP ice cores now precisely describe the rapid variations of Antarctic and Greenland temperature during MIS 5 (73.5–123 ka), a time period corresponding to relatively high sea level. The results display a succession of abrupt events associated with long Greenland InterStadial phases (GIS) enabling us to highlight a sub-millennial scale climatic variability depicted by (i) short-lived and abrupt warming events preceding some GIS (precursor-type events) and (ii) abrupt warming events at the end of some GIS (rebound-type events). The occurrence of these sub-millennial scale events is suggested to be driven by the insolation at high northern latitudes together with the internal forcing of ice sheets. Thanks to a recent NorthGRIP-EPICA Dronning Maud Land (EDML) common timescale over MIS 5, the bipolar sequence of climatic events can be established at millennial to sub-millennial timescale. This shows that for extraordinary long stadial durations the accompanying Antarctic warming amplitude cannot be described by a simple linear relationship between the two as expected from the bipolar seesaw concept. We also show that when ice sheets are extensive, Antarctica does not necessarily warm during the whole GS as the thermal bipolar seesaw model would predict, questioning the Greenland ice core temperature records as a proxy for AMOC changes throughout the glacial period.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Tracing of 15N in a mountain spruce forest: comparison of experimental data with th TRACE model

Despite numerous studies about nitrogen-cycling in forest ecosystems, many uncertainties remain, especially regarding the longer-term nitrogen accumulation. To contribute to filling this gap, the dynamic process-based model TRACE, with the ability to simulate 15N tracer redistribution in forest ecosystems was used to study N cycling processes in a mountain spruce forest of the northern edge of the Alps in Switzerland (Alptal, SZ). Most modeling analyses of N-cycling and C-N interactions have very limited ability to determine whether the process interactions are captured correctly. Because the interactions in such a system are complex, it is possible to get the whole-system C and N cycling right in a model without really knowing if the way the model combines fine-scale interactions to derive whole-system cycling is correct. With the possibility to simulate 15N tracer redistribution in ecosystem compartments, TRACE features a very powerful tool for the validation of fine-scale processes captured by the model. We first adapted the model to the new site (Alptal, Switzerland; long-term low-dose N-amendment experiment) by including a new algorithm for preferential water flow and by parameterizing of differences in drivers such as climate, N deposition and initial site conditions. After the calibration of key rates such as NPP and SOM turnover, we simulated patterns of 15N redistribution to compare against 15N field observations from a large-scale labeling experiment. The comparison of 15N field data with the modeled redistribution of the tracer in the soil horizons and vegetation compartments shows that the majority of fine-scale processes are captured satisfactorily. Particularly, the model is able to reproduce the fact that the largest part of the N deposition is immobilized in the soil. The discrepancies of 15N recovery in the LF and M soil horizon can be explained by the application method of the tracer and by the retention of the applied tracer by the well developed moss layer, which is not considered in the model. Discrepancies in the dynamics of foliage and litterfall 15N recovery were also observed and are related to the longevity of the needles in our mountain forest. As a next step, we will use the final Alptal version of the model to calculate the effects of climate change (temperature, CO2) and N deposition on ecosystem C sequestration in this regionally representative Norway spruce (Picea abies) stand.

TALDICE-1 age scale of the Talos Dome deep ice core, East Antarctica

A new deep ice core drilling program, TALDICE, has been successfully handled by a European team at Talos Dome, in the Ross Sea sector of East Antarctica, down to 1620 m depth. Using stratigraphic markers and a new inverse method, we produce the first official chronology of the ice core, called TALDICE-1. We show that it notably improves an a priori chronology resulting from a one-dimensional ice flow model. It is in agreement with a posteriori controls of the resulting accumulation rate and thinning function along the core. An absolute uncertainty of only 300 yr is obtained over the course of the last deglaciation. This uncertainty remains lower than 600 yr over Marine Isotope Stage 3, back to 50 kyr BP. The phasing of the TALDICE ice core climate record with respect to the central East Antarctic plateau and Greenland records can thus be determined with a precision allowing for a discussion of the mechanisms at work at sub-millennial time scales.

German Validation of the Conners Adult ADHD Rating Scale-Self-Report: Confirmation of Factor Structure in a Large Sample of Participants With ADHD

Objective: The Conners Adult ADHD Rating Scales (CAARS) assess symptoms specific to adults that are frequently used and have been translated into German. The current study tests the factor structure of the CAARS in a large sample of German adults with ADHD and compares the means of the CAARS subscales with those of healthy German controls. Method: CAARS were completed by 466 participants with ADHD and 851 healthy control participants. Confirmatory factor analysis was used to establish model fit with the American original. Comparisons between participants with ADHD and healthy controls and influences of gender, age, and degree of education were analyzed. Results: Confirmatory factor analysis showed a very good fit with the model for the American original. Differences between ADHD participants and healthy controls on all Conners Adult ADHD Rating Scales-Self-Report (CAARS-S) subscales were substantial and significant. Conclusion: The factor structure of the original American model was successfully replicated in this sample of adult German ADHD participants. (J. of Att. Dis. 2012; XX(X) 1-XX).

The Strauss and Carpenter Prognostic Scale in subjects clinically at high risk of psychosis

Objective:  To investigate the predictive value of the Strauss and Carpenter Prognostic Scale (SCPS) for transition to a first psychotic episode in subjects clinically at high risk (CHR) of psychosis. Method:  Two hundred and forty-four CHR subjects participating in the European Prediction of Psychosis Study were assessed with the SCPS, an instrument that has been shown to predict outcome in patients with schizophrenia reliably. Results:  At 18-month follow-up, 37 participants had made the transition to psychosis. The SCPS total score was predictive of a first psychotic episode (P < 0.0001). SCPS items that remained as independent predictors in the Cox proportional hazard model were as follows: most usual quality of useful work in the past year (P = 0.006), quality of social relations (P = 0.006), presence of thought disorder, delusions or hallucinations in the past year (P = 0.001) and reported severity of subjective distress in past month (P = 0.003). Conclusion:  The SCPS could make a valuable contribution to a more accurate prediction of psychosis in CHR subjects as a second-step tool. SCPS items assessing quality of useful work and social relations, positive symptoms and subjective distress have predictive value for transition. Further research should focus on investigating whether targeted early interventions directed at the predictive domains may improve outcomes.