Stiffness tomography by atomic force microscopy.

The atomic force microscope is a convenient tool to probe living samples at the nanometric scale. Among its numerous capabilities, the instrument can be operated as a nano-indenter to gather information about the mechanical properties of the sample. In this operating mode, the deformation of the cantilever is displayed as a function of the indentation depth of the tip into the sample. Fitting this curve with different theoretical models permits us to estimate the Young's modulus of the sample at the indentation spot. We describe what to our knowledge is a new technique to process these curves to distinguish structures of different stiffness buried into the bulk of the sample. The working principle of this new imaging technique has been verified by finite element models and successfully applied to living cells.

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Oscillation modes of microtubules.

Microtubules are long, filamentous protein complexes which play a central role in several cellular physiological processes, such as cell division transport and locomotion. Their mechanical properties are extremely important since they determine the biological function. In a recently published experiment [Phys. Rev. Lett. 89 (2002) 248101], microtubule's Young's and shear moduli were simultaneously measured, proving that they are highly anisotropic. Together with the known structure, this finding opens the way to better understand and predict their mechanical behavior under a particular set of conditions. In the present study, we modeled microtubules by using the finite elements method and analyzed their oscillation modes. The analysis revealed that oscillation modes involving a change in the diameter of the microtubules strongly depend on the shear modulus. In these modes, the correlation times of the movements are just slightly shorter than diffusion times of free molecules surrounding the microtubule. It could be therefore speculated that the matching of the two timescales could play a role in facilitating the interactions between microtubules and MT associated proteins, and between microtubules and tubulins themselves.

Multi-parametric evaluation of sit-to-stand and stand-to-sit transitions in elderly people.

The aim of this study was to extract multi-parametric measures characterizing different features of sit-to-stand (Si-St) and stand-to-sit (St-Si) transitions in older persons, using a single inertial sensor attached to the chest. Investigated parameters were transition's duration, range of trunk tilt, smoothness of transition pattern assessed by its fractal dimension, and trunk movement's dynamic described by local wavelet energy. A measurement protocol with a Si-St followed by a St-Si postural transition was performed by two groups of participants: the first group (N=79) included Frail Elderly subjects admitted to a post-acute rehabilitation facility and the second group (N=27) were healthy community-dwelling elderly persons. Subjects were also evaluated with Tinetti's POMA scale. Compared to Healthy Elderly persons, frail group at baseline had significantly longer Si-St (3.85±1.04 vs. 2.60±0.32, p=0.001) and St-Si (4.08±1.21 vs. 2.81±0.36, p=0.001) transition's duration. Frail older persons also had significantly decreased smoothness of Si-St transition pattern (1.36±0.07 vs. 1.21±0.05, p=0.001) and dynamic of trunk movement. Measurements after three weeks of rehabilitation in frail older persons showed that smoothness of transition pattern had the highest improvement effect size (0.4) and discriminative performance. These results demonstrate the potential interest of such parameters to distinguish older subjects with different functional and health conditions.

Temperature-dependent elasticity of microtubules

Central to the biological function of microtubules is their ability to modify their length which occurs by addition and removal of subunits at the ends of the polymer, both in vivo and in vitro. This dynamic behavior is strongly influenced by temperature. Here, we show that the lateral interaction between tubulin subunits forming microtubule is strongly temperature dependent. Microtubules deposited on prefabricated substrates were deformed in an atomic force microscope during imaging, in two different experimental geometries. Microtubules were modeled as anisotropic, with the Young's modulus corresponding to the resistance of protofilaments to stretching and the shear modulus describing the weak interaction between the protofilaments. Measurements involving radial compression of microtubules deposited on flat mica confirm that microtubule elasticity depends on the temperature. Bending measurements performed on microtubules deposited on lithographically fabricated substrates show that this temperature dependence is due to changing shear modulus, implying that the lateral interaction between the protofilaments is strongly determined by the temperature. These measurements are in good agreement with previously reported measurements of the disassembly rate of microtubules, demonstrating that the mechanical and dynamic properties of microtubules are closely related.

Biomechanical characterization and in vitro mechanical injury of elderly human femoral head cartilage: comparison to adult bovine humeral head cartilage.

OBJECTIVES: In vitro mechanical injury of articular cartilage is useful to identify events associated with development of post-traumatic osteoarthritis (OA). To date, many in vitro injury models have used animal cartilage despite the greater clinical relevance of human cartilage. We aimed to characterize a new in vitro injury model using elderly human femoral head cartilage and compare its behavior to that of an existing model with adult bovine humeral head cartilage. DESIGN: Mechanical properties of human and bovine cartilage disks were characterized by elastic modulus and hydraulic permeability in radially confined axial compression, and by Young's modulus, Poisson's ratio, and direction-dependent radial strain in unconfined compression. Biochemical composition was assessed in terms of tissue water, solid, and glycosaminoglycan (GAG) contents. Responses to mechanical injury were assessed by observation of macroscopic superficial tissue cracks and histological measurements of cell viability following single injurious ramp loads at 7 or 70%/s strain rate to 3 or 14 MPa peak stress. RESULTS: Confined compression moduli and Young's moduli were greater in elderly human femoral cartilage vs adult bovine humeral cartilage whereas hydraulic permeability was less. Radial deformations of axially compressed explant disks were more anisotropic (direction-dependent) for the human cartilage. In both cartilage sources, tissue cracking and associated cell death during injurious loading was common for 14 MPa peak stress at both strain rates. CONCLUSION: Despite differences in mechanical properties, acute damage induced by injurious loading was similar in both elderly human femoral cartilage and adult bovine humeral cartilage, supporting the clinical relevance of animal-based cartilage injury models. However, inherent structural differences such as cell density may influence subsequent cell-mediated responses to injurious loading and affect the development of OA.

Frequency-dependent attenuation as a potential indicator of oil saturation

At seismic frequencies, wave-induced fluid flow is a major cause of P-wave attenuation in partially saturated porous rocks. Attenuation is of great importance for the oil industry in the interpretation of seismic field data. Here, the effects on P-wave attenuation resulting from changes in oil saturation are studied for media with coexisting water, oil, and gas. For that, creep experiments are numerically simulated by solving Biot's equations for consolidation of poroelastic media with the finite-element method. The experiments yield time-dependent stress?strain relations that are used to calculate the complex P-wave modulus from which frequency-dependent P-wave attenuation is determined. The models are layered media with periodically alternating triplets of layers. Models consisting of triplets of layers having randomly varying layer thicknesses are also considered. The layers in each triplet are fully saturated with water, oil, and gas. The layer saturated with water has lower porosity and permeability than the layers saturated with oil and gas. These models represent hydrocarbon reservoirs in which water is the wetting fluid preferentially saturating regions of lower porosity. The results from the numerical experiments showed that increasing oil saturation, connected to a decrease in gas saturation, resulted in a significant increase of attenuation at low frequencies (lower than 2 Hz). Furthermore, replacing the oil with water resulted in a distinguishable behavior of the frequency-dependent attenuation. These results imply that, according to the physical mechanism of wave-induced fluid flow, frequency-dependent attenuation in media saturated with water, oil, and gas is a potential indicator of oil saturation.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

The clinical use of quantitative ultrasound (QUS) in the detection and management of osteoporosis

For the detection and management of osteoporosis and osteoporosis-related fractures, quantitative ultrasound (QUS) is emerging as a relatively low-cost and readily accessible alternative to dual-energy X-ray absorptiometry (DXA) measurement of bone mineral density (BMD) in certain circumstances. The following is a brief, but thorough review of the existing literature with respect to the use of QUS in 6 settings: 1) assessing fragility fracture risk; 2) diagnosing osteoporosis; 3) initiating osteoporosis treatment; 4) monitoring osteoporosis treatment; 5) osteoporosis case finding; and 6) quality assurance and control. Many QUS devices exist that are quite different with respect to the parameters they measure and the strength of empirical evidence supporting their use. In general, heel QUS appears to be most tested and most effective. Overall, some, but not all, heel QUS devices are effective assessing fracture risk in some, but not all, populations, the evidence being strongest for Caucasian females over 55 years old. Otherwise, the evidence is fair with respect to certain devices allowing for the accurate diagnosis of likelihood of osteoporosis, and generally fair to poor in terms of QUS use when initiating or monitoring osteoporosis treatment. A reasonable protocol is proposed herein for case-finding purposes, which relies on a combined assessment of clinical risk factors (CR.F) and heel QUS. Finally, several recommendations are made for quality assurance and control.

Comparison of aortic elasticity determined by cardiovascular magnetic resonance imaging in obese versus lean adults.

The vascular properties of large vessels in the obese have not been adequately studied. We used cardiovascular magnetic resonance imaging to quantify the cross-sectional area and elastic properties of the ascending thoracic and abdominal aorta in 21 clinically healthy obese young adult men and 25 men who were age-matched lean controls. Obese subjects had greater maximal cross-sectional area of the ascending thoracic aorta (984 +/- 252 vs 786 +/- 109 mm(2), p <0.01) and of the abdominal aorta (415 +/- 71 vs 374 +/- 51 mm(2), p <0.05). When indexed for height the differences persisted, but when indexed for body surface area, a significant difference between groups was found only for the maximal abdominal aortic cross-sectional area. The obese subjects also had decreased abdominal aortic elasticity, characterized by 24% lower compliance (0.0017 +/- 0.0004 vs 0.0021 +/- 0.0005 mm(2)/kPa/mm, p <0.01), 22% higher stiffness index beta (6.0 +/- 1.5 vs 4.9 +/- 0.7, p <0.005), and 41% greater pressure-strain elastic modulus (72 +/- 25 vs 51 +/- 9, p <0.005). At the ascending thoracic aorta, only the pressure-strain elastic modulus was different between obese and lean subjects (85 +/- 42 vs 65 +/- 26 kPa, respectively; p <0.05), corresponding to a 31% difference-but arterial compliance and stiffness index were not significantly different between groups. In clinically healthy young adult obese men, obesity is associated with increased cross-sectional aortic area and decreased aortic elasticity.

Conditioning of multiple-point statistics facies simulations to tomographic images

Geophysical tomography captures the spatial distribution of the underlying geophysical property at a relatively high resolution, but the tomographic images tend to be blurred representations of reality and generally fail to reproduce sharp interfaces. Such models may cause significant bias when taken as a basis for predictive flow and transport modeling and are unsuitable for uncertainty assessment. We present a methodology in which tomograms are used to condition multiple-point statistics (MPS) simulations. A large set of geologically reasonable facies realizations and their corresponding synthetically calculated cross-hole radar tomograms are used as a training image. The training image is scanned with a direct sampling algorithm for patterns in the conditioning tomogram, while accounting for the spatially varying resolution of the tomograms. In a post-processing step, only those conditional simulations that predicted the radar traveltimes within the expected data error levels are accepted. The methodology is demonstrated on a two-facies example featuring channels and an aquifer analog of alluvial sedimentary structures with five facies. For both cases, MPS simulations exhibit the sharp interfaces and the geological patterns found in the training image. Compared to unconditioned MPS simulations, the uncertainty in transport predictions is markedly decreased for simulations conditioned to tomograms. As an improvement to other approaches relying on classical smoothness-constrained geophysical tomography, the proposed method allows for: (1) reproduction of sharp interfaces, (2) incorporation of realistic geological constraints and (3) generation of multiple realizations that enables uncertainty assessment.

3-D density structure and geological evolution of Stromboli volcano (Aeolian Islands, Italy) inferred from land-based and sea-surface gravity data

We present the first density model of Stromboli volcano (Aeolian Islands, Italy) obtained by simultaneously inverting land-based (543) and sea-surface (327) relative gravity data. Modern positioning technology, a 1 x 1 m digital elevation model, and a 15 x 15 m bathymetric model made it possible to obtain a detailed 3-D density model through an iteratively reweighted smoothness-constrained least-squares inversion that explained the land-based gravity data to 0.09 mGal and the sea-surface data to 5 mGal. Our inverse formulation avoids introducing any assumptions about density magnitudes. At 125 m depth from the land surface, the inferred mean density of the island is 2380 kg m(-3), with corresponding 2.5 and 97.5 percentiles of 2200 and 2530 kg m-3. This density range covers the rock densities of new and previously published samples of Paleostromboli I, Vancori, Neostromboli and San Bartolo lava flows. High-density anomalies in the central and southern part of the island can be related to two main degassing faults crossing the island (N41 and NM) that are interpreted as preferential regions of dyke intrusions. In addition, two low-density anomalies are found in the northeastern part and in the summit area of the island. These anomalies seem to be geographically related with past paroxysmal explosive phreato-magmatic events that have played important roles in the evolution of Stromboli Island by forming the Scari caldera and the Neostromboli crater, respectively. (C) 2014 Elsevier B.V. All rights reserved.