Use of the FACTS solvation model for protein-ligand docking calculations. Application to EADock.

Protein-ligand docking has made important progress during the last decade and has become a powerful tool for drug development, opening the way to virtual high throughput screening and in silico structure-based ligand design. Despite the flattering picture that has been drawn, recent publications have shown that the docking problem is far from being solved, and that more developments are still needed to achieve high successful prediction rates and accuracy. Introducing an accurate description of the solvation effect upon binding is thought to be essential to achieve this goal. In particular, EADock uses the Generalized Born Molecular Volume 2 (GBMV2) solvent model, which has been shown to reproduce accurately the desolvation energies calculated by solving the Poisson equation. Here, the implementation of the Fast Analytical Continuum Treatment of Solvation (FACTS) as an implicit solvation model in small molecules docking calculations has been assessed using the EADock docking program. Our results strongly support the use of FACTS for docking. The success rates of EADock/FACTS and EADock/GBMV2 are similar, i.e. around 75% for local docking and 65% for blind docking. However, these results come at a much lower computational cost: FACTS is 10 times faster than GBMV2 in calculating the total electrostatic energy, and allows a speed up of EADock by a factor of 4. This study also supports the EADock development strategy relying on the CHARMM package for energy calculations, which enables straightforward implementation and testing of the latest developments in the field of Molecular Modeling.

A physical frequency-dependent compact model for RF integrated inductors

A frequency-dependent compact model for inductors in high ohmic substrates, which is based on an energy point-of-view, is developed. This approach enables the description of the most important coupling phenomena that take place inside the device. Magnetically induced losses are quite accurately calculated and coupling between electric and magnetic fields is given by means of a delay constant. The later coupling phenomenon provides a modified procedure for the computation of the fringing capacitance value, when the self-resonance frequency of the inductor is used as a fitting parameter. The model takes into account the width of every metal strip and the pitch between strips. This enables the description of optimized layout inductors. Data from experiments and electromagnetic simulators are presented to test the accuracy of the model.

Computer-assisted cartography using topographic properties: precision and accuracy of local soil maps in central Mexico

Map units directly related to properties of soil-landscape are generated by local soil classes. Therefore to take into consideration the knowledge of farmers is essential to automate the procedure. The aim of this study was to map local soil classes by computer-assisted cartography (CAC), using several combinations of topographic properties produced by GIS (digital elevation model, aspect, slope, and profile curvature). A decision tree was used to find the number of topographic properties required for digital cartography of the local soil classes. The maps produced were evaluated based on the attributes of map quality defined as precision and accuracy of the CAC-based maps. The evaluation was carried out in Central Mexico using three maps of local soil classes with contrasting landscape and climatic conditions (desert, temperate, and tropical). In the three areas the precision (56 %) of the CAC maps based on elevation as topographical feature was higher than when based on slope, aspect and profile curvature. The accuracy of the maps (boundary locations) was however low (33 %), in other words, further research is required to improve this indicator.

Phase-field model for Hele-Shaw flows with arabitrary contrast II: numerical approach

We present a phase-field model for the dynamics of the interface between two inmiscible fluids with arbitrary viscosity contrast in a rectangular Hele-Shaw cell. With asymptotic matching techniques we check the model to yield the right Hele-Shaw equations in the sharp-interface limit, and compute the corrections to these equations to first order in the interface thickness. We also compute the effect of such corrections on the linear dispersion relation of the planar interface. We discuss in detail the conditions on the interface thickness to control the accuracy and convergence of the phase-field model to the limiting Hele-Shaw dynamics. In particular, the convergence appears to be slower for high viscosity contrasts.

Accuracy of four cardiovascular risk scores in a Swiss population-based cohort

Purpose: To assess the global cardiovascular (CV) risk of an individual, several scores have been developed. However, their accuracy and comparability need to be evaluated in populations others from which they were derived. The aim of this study was to compare the predictive accuracy of 4 CV risk scores using data of a large population-based cohort. Methods: Prospective cohort study including 4980 participants (2698 women, mean age± SD: 52.7±10.8 years) in Lausanne, Switzerland followed for an average of 5.5 years (range 0.2 - 8.5). Two end points were assessed: 1) coronary heart disease (CHD), and 2) CV diseases (CVD). Four risk scores were compared: original and recalibrated Framingham coronary heart disease scores (1998 and 2001); original PROCAM score (2002) and its recalibrated version for Switzerland (IAS-AGLA); Reynolds risk score. Discrimination was assessed using Harrell's C statistics, model fitness using Akaike's information criterion (AIC) and calibration using pseudo Hosmer-Lemeshow test. The sensitivity, specificity and corresponding 95% confidence intervals were assessed for each risk score using the highest risk category ([20+ % at 10 years) as the "positive" test. Results: Recalibrated and original 1998 and original 2001 Framingham scores show better discrimination (>0.720) and model fitness (low AIC) for CHD and CVD. All 4 scores are correctly calibrated (Chi2<20). The recalibrated Framingham 1998 score has the best sensitivities, 37.8% and 40.4%, for CHD and CVD, respectively. All scores present specificities >90%. Framingham 1998, PROCAM and IAS-AGLA scores include the greatest proportion of subjects (>200) in the high risk category whereas recalibrated Framingham 2001 and Reynolds include <=44 subjects. Conclusion: In this cohort, we see variations of accuracy between risk scores, the original Framingham 2001 score demonstrating the best compromise between its accuracy and its limited selection of subjects in the highest risk category. We advocate that national guidelines, based on independently validated data, take into account calibrated CV risk scores for their respective countries.

The statistical accuracy of surveys on business and economic perspectives: a case study

In this paper, we develop a new decision making model and apply it in political Surveys of economic climate collect opinions of managers about the short-term future evolution of their business. Interviews are carried out on a regular basis and responses measure optimistic, neutral or pessimistic views about the economic perspectives. We propose a method to evaluate the sampling error of the average opinion derived from a particular type of survey data. Our variance estimate is useful to interpret historical trends and to decide whether changes in the index from one period to another are due to a structural change or whether ups and downs can be attributed to sampling randomness. An illustration using real data from a survey of business managers opinions is discussed.

Statistical assessment of dataset shift and model portability in multi-angle in-track image acquisitions

In this study we propose an evaluation of the angular effects altering the spectral response of the land-cover over multi-angle remote sensing image acquisitions. The shift in the statistical distribution of the pixels observed in an in-track sequence of WorldView-2 images is analyzed by means of a kernel-based measure of distance between probability distributions. Afterwards, the portability of supervised classifiers across the sequence is investigated by looking at the evolution of the classification accuracy with respect to the changing observation angle. In this context, the efficiency of various physically and statistically based preprocessing methods in obtaining angle-invariant data spaces is compared and possible synergies are discussed.

Factor structure of early smoking experiences and associations with smoking behavior: valence or sensitivity model?

The Early Smoking Experience (ESE) questionnaire is the most widely used questionnaire to assess initial subjective experiences of cigarette smoking. However, its factor structure is not clearly defined and can be perceived from two main standpoints: valence, or positive and negative experiences, and sensitivity to nicotine. This article explores the ESE's factor structure and determines which standpoint was more relevant. It compares two groups of young Swiss men (German- and French-speaking). We examined baseline data on 3,368 tobacco users from a representative sample in the ongoing Cohort Study on Substance Use Risk Factors (C-SURF). ESE, continued tobacco use, weekly smoking and nicotine dependence were assessed. Exploratory structural equation modeling (ESEM) and structural equation modeling (SEM) were performed. ESEM clearly distinguished positive experiences from negative experiences, but negative experiences were divided in experiences related to dizziness and experiences related to irritations. SEM underlined the reinforcing effects of positive experiences, but also of experiences related to dizziness on nicotine dependence and weekly smoking. The best ESE structure for predictive accuracy of experiences on smoking behavior was a compromise between the valence and sensitivity standpoints, which showed clinical relevance.

Prospective sampling based on model ensembles improves the detection of rare species

Identifying the geographic distribution of populations is a basic, yet crucial step in many fundamental and applied ecological projects, as it provides key information on which many subsequent analyses depend. However, this task is often costly and time consuming, especially where rare species are concerned and where most sampling designs generally prove inefficient. At the same time, rare species are those for which distribution data are most needed for their conservation to be effective. To enhance fieldwork sampling, model-based sampling (MBS) uses predictions from species distribution models: when looking for the species in areas of high habitat suitability, chances should be higher to find them. We thoroughly tested the efficiency of MBS by conducting an important survey in the Swiss Alps, assessing the detection rate of three rare and five common plant species. For each species, habitat suitability maps were produced following an ensemble modeling framework combining two spatial resolutions and two modeling techniques. We tested the efficiency of MBS and the accuracy of our models by sampling 240 sites in the field (30 sitesx8 species). Across all species, the MBS approach proved to be effective. In particular, the MBS design strictly led to the discovery of six sites of presence of one rare plant, increasing chances to find this species from 0 to 50%. For common species, MBS doubled the new population discovery rates as compared to random sampling. Habitat suitability maps coming from the combination of four individual modeling methods predicted well the species' distribution and more accurately than the individual models. As a conclusion, using MBS for fieldwork could efficiently help in increasing our knowledge of rare species distribution. More generally, we recommend using habitat suitability models to support conservation plans.

Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease.

The failure of current strategies to provide an explanation for controversial findings on the pattern of pathophysiological changes in Alzheimer's Disease (AD) motivates the necessity to develop new integrative approaches based on multi-modal neuroimaging data that captures various aspects of disease pathology. Previous studies using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (sMRI) report controversial results about time-line, spatial extent and magnitude of glucose hypometabolism and atrophy in AD that depend on clinical and demographic characteristics of the studied populations. Here, we provide and validate at a group level a generative anatomical model of glucose hypo-metabolism and atrophy progression in AD based on FDG-PET and sMRI data of 80 patients and 79 healthy controls to describe expected age and symptom severity related changes in AD relative to a baseline provided by healthy aging. We demonstrate a high level of anatomical accuracy for both modalities yielding strongly age- and symptom-severity- dependant glucose hypometabolism in temporal, parietal and precuneal regions and a more extensive network of atrophy in hippocampal, temporal, parietal, occipital and posterior caudate regions. The model suggests greater and more consistent changes in FDG-PET compared to sMRI at earlier and the inversion of this pattern at more advanced AD stages. Our model describes, integrates and predicts characteristic patterns of AD related pathology, uncontaminated by normal age effects, derived from multi-modal data. It further provides an integrative explanation for findings suggesting a dissociation between early- and late-onset AD. The generative model offers a basis for further development of individualized biomarkers allowing accurate early diagnosis and treatment evaluation.

A multi-temporal approach to model endangered species distribution in Europe: the case of the Eurasian otter in Italy

We analysed the relationship between changes in land cover patterns and the Eurasian otter occurrence over the course of about 20 years (1985-2006) using multi-temporal Species Distribution Models (SDMs). The study area includes five river catchments covering most of the otter's Italian range. Land cover and topographic data were used as proxies of the ecological requirements of the otter within a 300-m buffer around river courses. We used species presence, pseudo-absence data, and environmental predictors to build past (1985) and current (2006) SDMs by applying an ensemble procedure through the BIOMOD modelling package. The performance of each model was evaluated by measuring the area under the curve (AUC) of the receiver-operating characteristic (ROC). Multi-temporal analyses of species distribution and land cover maps were performed by comparing the maps produced for 1985 and 2006. The ensemble procedure provided a good overall modelling accuracy, revealing that elevation and slope affected the otter's distribution in the past; in contrast, land cover predictors, such as cultivations and forests, were more important in the present period. During the transition period, 20.5% of the area became suitable, with 76% of the new otter presence data being located in these newly available areas. The multi-temporal analysis suggested that the quality of otter habitat improved in the last 20 years owing to the expansion of forests and to the reduction of cultivated fields in riparian belts. The evidence presented here stresses the great potential of riverine habitat restoration and environmental management for the future expansion of the otter in Italy

Using tools to help cost estimating and pricing: examination of costing model's and cost breakdown's workability and their capability to cooperative work

Tämä diplomityö käsittelee työkaluja, jotka on suunniteltu kustannusten ennakointiin ja hinnan asetantaan. Aluksi on käyty läpi perinteisen ja toimintoperusteisen kustannuslaskennan perusteita. Näiden menetelmien välisiä eroja on tarkasteltu ja toimintoperusteisen kustannuslaskennan paremmin sopivuus nykypäivän yrityksille on perusteltu. Toisena käsitellään hinnoittelu. Hinnan merkitys, hinnoittelumenetelmät ja päätös lopullisesta hinnasta on käyty läpi. Hinnoittelun jälkeen esitellään kustannusjärjestelmät ja kustannusten arviointi. Nämä asiat todistavat, että tarkat kustannusarviot ovat elintärkeitä yritykselle. Tuotteen kustannusarviointi, hinnan asetanta ja tarjoaminen ovat erittäin merkityksellisiä asioita ottaen huomioon koko projektin elinkaaren ja tulevat tuotot. Nykyään on yleistä käyttää työkaluja kustannusarvioinnissa ja joskus myös hinnoittelussa. Työkalujen luotettavuus on tiedettävä, ennenkuin työkalut otetaan käyttöön. Myös työkalujen käyttäjät täytyy perehdyttää hyvin. Muuten yritys todennäköisesti kohtaa odottamattomia ja epämiellyttäviä yllätyksiä.

Measuring the relative effect of factors affecting species distribution model predictions

1. Species distribution models are increasingly used to address conservation questions, so their predictive capacity requires careful evaluation. Previous studies have shown how individual factors used in model construction can affect prediction. Although some factors probably have negligible effects compared to others, their relative effects are largely unknown. 2. We introduce a general "virtual ecologist" framework to study the relative importance of factors involved in the construction of species distribution models. 3. We illustrate the framework by examining the relative importance of five key factors-a missing covariate, spatial autocorrelation due to a dispersal process in presences/absences, sample size, sampling design and modeling technique-in a real study framework based on plants in a mountain landscape at regional scale, and show that, for the parameter values considered here, most of the variation in prediction accuracy is due to sample size and modeling technique. Contrary to repeatedly reported concerns, spatial autocorrelation has only comparatively small effects. 4. This study shows the importance of using a nested statistical framework to evaluate the relative effects of factors that may affect species distribution models.

Single breath-hold 3D measurement of left atrial volume using compressed sensing cardiovascular magnetic resonance and a non-model-based reconstruction approach.

BACKGROUND: Left atrial (LA) dilatation is associated with a large variety of cardiac diseases. Current cardiovascular magnetic resonance (CMR) strategies to measure LA volumes are based on multi-breath-hold multi-slice acquisitions, which are time-consuming and susceptible to misregistration. AIM: To develop a time-efficient single breath-hold 3D CMR acquisition and reconstruction method to precisely measure LA volumes and function. METHODS: A highly accelerated compressed-sensing multi-slice cine sequence (CS-cineCMR) was combined with a non-model-based 3D reconstruction method to measure LA volumes with high temporal and spatial resolution during a single breath-hold. This approach was validated in LA phantoms of different shapes and applied in 3 patients. In addition, the influence of slice orientations on accuracy was evaluated in the LA phantoms for the new approach in comparison with a conventional model-based biplane area-length reconstruction. As a reference in patients, a self-navigated high-resolution whole-heart 3D dataset (3D-HR-CMR) was acquired during mid-diastole to yield accurate LA volumes. RESULTS: Phantom studies. LA volumes were accurately measured by CS-cineCMR with a mean difference of -4.73 ± 1.75 ml (-8.67 ± 3.54%, r2 = 0.94). For the new method the calculated volumes were not significantly different when different orientations of the CS-cineCMR slices were applied to cover the LA phantoms. Long-axis "aligned" vs "not aligned" with the phantom long-axis yielded similar differences vs the reference volume (-4.87 ± 1.73 ml vs. -4.45 ± 1.97 ml, p = 0.67) and short-axis "perpendicular" vs. "not-perpendicular" with the LA long-axis (-4.72 ± 1.66 ml vs. -4.75 ± 2.13 ml; p = 0.98). The conventional bi-plane area-length method was susceptible for slice orientations (p = 0.0085 for the interaction of "slice orientation" and "reconstruction technique", 2-way ANOVA for repeated measures). To use the 3D-HR-CMR as the reference for LA volumes in patients, it was validated in the LA phantoms (mean difference: -1.37 ± 1.35 ml, -2.38 ± 2.44%, r2 = 0.97). Patient study: The CS-cineCMR LA volumes of the mid-diastolic frame matched closely with the reference LA volume (measured by 3D-HR-CMR) with a difference of -2.66 ± 6.5 ml (3.0% underestimation; true LA volumes: 63 ml, 62 ml, and 395 ml). Finally, a high intra- and inter-observer agreement for maximal and minimal LA volume measurement is also shown. CONCLUSIONS: The proposed method combines a highly accelerated single-breathhold compressed-sensing multi-slice CMR technique with a non-model-based 3D reconstruction to accurately and reproducibly measure LA volumes and function.