Systematic weakly nonlinear analysis of interfacial instabilities in Hele-Shaw flows

We develop a systematic method to derive all orders of mode couplings in a weakly nonlinear approach to the dynamics of the interface between two immiscible viscous fluids in a Hele-Shaw cell. The method is completely general: it applies to arbitrary geometry and driving. Here we apply it to the channel geometry driven by gravity and pressure. The finite radius of convergence of the mode-coupling expansion is found. Calculation up to third-order couplings is done, which is necessary to account for the time-dependent Saffman-Taylor finger solution and the case of zero viscosity contrast. The explicit results provide relevant analytical information about the role that the viscosity contrast and the surface tension play in the dynamics of the system. We finally check the quantitative validity of different orders of approximation and a resummation scheme against a physically relevant, exact time-dependent solution. The agreement between the low-order approximations and the exact solution is excellent within the radius of convergence, and is even reasonably good beyond this radius.

From lattice-gas models to nonlinear diffusion models: A derivation of macroscopic equations and fluctuations

We derive nonlinear diffusion equations and equations containing corrections due to fluctuations for a coarse-grained concentration field. To deal with diffusion coefficients with an explicit dependence on the concentration values, we generalize the Van Kampen method of expansion of the master equation to field variables. We apply these results to the derivation of equations of phase-separation dynamics and interfacial growth instabilities.

Thermal and back-action noises in dual-sphere gravitational-wave detectors

We study the sensitivity limits of a broadband gravitational-wave detector based on dual resonators such as nested spheres. We determine both the thermal and back-action noises when the resonators displacements are read out with an optomechanical sensor. We analyze the contributions of all mechanical modes, using a new method to deal with the force-displacement transfer functions in the intermediate frequency domain between the two gravitational-wave sensitive modes associated with each resonator. This method gives an accurate estimate of the mechanical response, together with an evaluation of the estimate error. We show that very high sensitivities can be reached on a wide frequency band for realistic parameters in the case of a dual-sphere detector.

Body composition using bio-impedance analysis in pediatric patients with inflammatory bowel disease. Corcordance with dual energy X-ray absorptiometry and comparison with healthy controls

Introduction: Growth is a central process in paediatrics. Weight and height evaluation are therefore routine exams for every child but in some situation, particularly inflammatory bowel disease (IBD), a wider evaluation of nutritional status needs to be performed. Objectives: To assess the accuracy of bio-impedance analysis (BIA) compared to the gold standard dual energy X-ray absorptiometry (DEXA) in estimating percentage body fat (fat mass; FM) and lean body mass (fat free mass; FFM) in children with inflammatory bowel disease (IBD). To compare FM and FFM levels between patients with IBD and healthy controls. Methods: Twenty-nine healthy controls (12 females; mean age: 12.7 ± 1.9 years) and 21 patients (11 females; 14.3 ± 1.3 years) were recruited from August 2011 to October 2012 at our institution. BIA was performed in all children and DEXA in patients only. Concordance between BIA and DEXA was assessed using Lin's concordance correlation and the Bland-Altman method. Between-group comparisons were made using analysis of variance adjusting for age. Results: BIA-derived FM% showed a good concordance with DEXA-derived values, while BIA-derived FFM% tended to be slightly higher than DEXA-derived values (table). No differences were found between patients and controls regarding body mass index (mean ± SD: 19.3 ± 3.3 vs. 20.1 ± 2.8 kg/m2, respectively; age-adjusted P = 0.08) and FM% (boys: 25.3 ± 10.2 vs. 22.6 ± 7.1%, for patients and controls, respectively; P = 0.20; girls: 28.2 ± 5.7 vs. 26.4 ± 7.7%; P = 0.91). Also, no differences were found regarding FFM% in boys (74.9 ± 10.2 vs. 77.4 ± 7.1%; P = 0.22) and girls (71.8 ± 5.6 vs. 73.5 ± 7.7%; P = 0.85). Conclusion: BIA adequately assesses body composition (FM%) in children with IBD and could advantageously replace DEXA, which is more expensive and less available. No differences in body composition were found between children with IBD and healthy controls.

Bioavailability of repeated oral administration of MDL 100,240, a dual inhibitor of angiotensin-converting enzyme and neutral endopeptidase in healthy volunteers.

BACKGROUND: MDL 100,240 (pyrido[2,1-a] [2]benzazepine-4-carboxylic acid,7-[[2-(acetylthio)-1-oxo-3-phenylpropyl]amino]-1,2,3,4,6,7,8, 12b-octahydro-6-oxo, [4S-[4alpha,7alpha(R(*)),12bbeta]]-) is a molecule possessing an inhibiting ability on both angiotensin converting enzyme (ACE) and neutral endopeptidase, the enzyme responsible for atrial natriuretic peptide (ANP) degradation. Such a dual mechanism of action presents a potential clinical interest for the treatment of hypertension and congestive heart failure. OBJECTIVES: To evaluate the bioavailability of MDL 100,240 and its accumulation over repeated oral administration, using ACE inhibition as a surrogate for plasma drug level and determining its profile after oral and i.v. administration. METHODS: First, in an open, one-period, single-dose study, the ACE inhibition profile was characterised following a 12.5 mg MDL 100,240 i.v. infusion. Second, in a three-group, parallel, randomised, double-blind study, each group of four subjects received q.d., over 8 days, 2.5, 10 or 20 mg of MDL 100,240 orally. The ACE inhibition profile was determined on day 1 and day 8. Trough plasma ACE was measured on days 2, 3 and 4. The recovery of ACE activity was monitored up to 72 h after the last dose of MDL 100,240. RESULTS: ACE inhibition profile was similar on day 1 and day 8, and trough inhibition remained unchanged after the 8 days of treatment with 10 mg or 20 mg. Following repeated 2.5-mg ingestion, trough inhibition increased from 33% to 44% after the eighth dose. The oral bioavailability of MDL 100,240 was estimated at 85%, not statistically different from 100%. The accumulation ratio at steady state was estimated at 112%. Expressing the accumulation ratio in terms of half-life, a t(1/2) of 0.31 days or 7. 5 h was estimated. CONCLUSION: MDL 100,240 (oral solution) has a good bioavailability, as estimated by ACE inhibition, and no drug accumulation seems to occur over 8 days with the 10-mg and 20-mg doses, but a slight rise in the trough level is observed with the 2. 5-mg dose.

Geomorphological method in the elaboration of hazard maps for flash-floods in the municipality of Jucuarán (El Salvador)

This work deals with the elaboration of flood hazard maps. These maps reflect the areas prone to floods based on the effects of Hurricane Mitch in the Municipality of Jucuarán of El Salvador. Stream channels located in the coastal range in the SE of El Salvador flow into the Pacific Ocean and generate alluvial fans. Communities often inhabit these fans can be affected by floods. The geomorphology of these stream basins is associated with small areas, steep slopes, well developed regolite and extensive deforestation. These features play a key role in the generation of flash-floods. This zone lacks comprehensive rainfall data and gauging stations. The most detailed topographic maps are on a scale of 1:25 000. Given that the scale was not sufficiently detailed, we used aerial photographs enlarged to the scale of 1:8000. The effects of Hurricane Mitch mapped on these photographs were regarded as the reference event. Flood maps have a dual purpose (1) community emergency plans, (2) regional land use planning carried out by local authorities. The geomorphological method is based on mapping the geomorphological evidence (alluvial fans, preferential stream channels, erosion and sedimentation, man-made terraces). Following the interpretation of the photographs this information was validated on the field and complemented by eyewitness reports such as the height of water and flow typology. In addition, community workshops were organized to obtain information about the evolution and the impact of the phenomena. The superimposition of this information enables us to obtain a comprehensive geomorphological map. Another aim of the study was the calculation of the peak discharge using the Manning and the paleohydraulic methods and estimates based on geomorphologic criterion. The results were compared with those obtained using the rational method. Significant differences in the order of magnitude of the calculated discharges were noted. The rational method underestimated the results owing to short and discontinuous periods of rainfall data with the result that probabilistic equations cannot be applied. The Manning method yields a wide range of results because of its dependence on the roughness coefficient. The paleohydraulic method yielded higher values than the rational and Manning methods. However, it should be pointed out that it is possible that bigger boulders could have been moved had they existed. These discharge values are lower than those obtained by the geomorphological estimates, i.e. much closer to reality. The flood hazard maps were derived from the comprehensive geomorphological map. Three categories of hazard were established (very high, high and moderate) using flood energy, water height and velocity flow deduced from geomorphological and eyewitness reports.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Phase-sensitive dual-inversion recovery for accelerated carotid vessel wall imaging.

OBJECTIVES: Dual-inversion recovery (DIR) is widely used for magnetic resonance vessel wall imaging. However, optimal contrast may be difficult to obtain and is subject to RR variability. Furthermore, DIR imaging is time-inefficient and multislice acquisitions may lead to prolonged scanning times. Therefore, an extension of phase-sensitive (PS) DIR is proposed for carotid vessel wall imaging. METHODS: The statistical distribution of the phase signal after DIR is probed to segment carotid lumens and suppress their residual blood signal. The proposed PS-DIR technique was characterized over a broad range of inversion times. Multislice imaging was then implemented by interleaving the acquisition of 3 slices after DIR. Quantitative evaluation was then performed in healthy adult subjects and compared with conventional DIR imaging. RESULTS: Single-slice PS-DIR provided effective blood-signal suppression over a wide range of inversion times, enhancing wall-lumen contrast and vessel wall conspicuity for carotid arteries. Multislice PS-DIR imaging with effective blood-signal suppression is enabled. CONCLUSIONS: A variant of the PS-DIR method has successfully been implemented and tested for carotid vessel wall imaging. This technique removes timing constraints related to inversion recovery, enhances wall-lumen contrast, and enables a 3-fold increase in volumetric coverage at no extra cost in scanning time.

"Suddenly I get into the zone": Examining discontinuities and nonlinear changes in flow experiences at work

Work-related flow is defined as a sudden and enjoyable merging of action and awareness that represents a peak experience in the daily lives of workers. Employees" perceptions of challenge and skill and their subjective experiences in terms of enjoyment, interest and absorption were measured using the experience sampling method, yielding a total of 6981 observations from a sample of 60 employees. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes. According to the R2, AICc and BIC indexes, the nonlinear dynamical systems model (i.e. cusp catastrophe model) fit the data better than the linear and logistic regression models. Likewise, the cusp catastrophe model appears to be especially powerful for modelling those cases of high levels of flow. Overall, flow represents a nonequilibrium condition that combines continuous and abrupt changes across time. Research and intervention efforts concerned with this process should focus on the variable of challenge, which, according to our study, appears to play a key role in the abrupt changes observed in work-related flow.

Dynamics of flow: a nonlinear perspective

The aims of this study are to consider the experience of flow from a nonlinear dynamics perspective. The processes and temporal nature of intrinsic motivation and flow, would suggest that flow experiences fluctuate over time in a dynamical fashion. Thus it can be argued that the potential for chaos is strong. The sample was composed of 20 employees (both full and part time) recruited from a number of different organizations and work backgrounds. The Experience Sampling Method (ESM) was used for data collection. Once obtained the temporal series, they were subjected to various analyses proper to the com- plexity theory (Visual Recurrence Analysis and Surrogate Data Analysis). Results showed that in 80% of the cases, flow presented a chaotic dynamic, in that, flow experiences delineated a complex dynamic whose patterns of change were not easy to predict. Implications of the study, its limitations and future research are discussed.

Parametric Approach to Blind Deconvolution of Nonlinear Channels

A parametric procedure for the blind inversion of nonlinear channels is proposed, based on a recent method of blind source separation in nonlinear mixtures. Experiments show that the proposed algorithms perform efficiently, even in the presence of hard distortion. The method, based on the minimization of the output mutual information, needs the knowledge of log-derivative of input distribution (the so-called score function). Each algorithm consists of three adaptive blocks: one devoted to adaptive estimation of the score function, and two other blocks estimating the inverses of the linear and nonlinear parts of the channel, (quasi-)optimally adapted using the estimated score functions. This paper is mainly concerned by the nonlinear part, for which we propose two parametric models, the first based on a polynomial model and the second on a neural network, while [14, 15] proposed non-parametric approaches.

A Fast Gradient Approximation for Nonlinear Blind Signal Processing

When dealing with nonlinear blind processing algorithms (deconvolution or post-nonlinear source separation), complex mathematical estimations must be done giving as a result very slow algorithms. This is the case, for example, in speech processing, spike signals deconvolution or microarray data analysis. In this paper, we propose a simple method to reduce computational time for the inversion of Wiener systems or the separation of post-nonlinear mixtures, by using a linear approximation in a minimum mutual information algorithm. Simulation results demonstrate that linear spline interpolation is fast and accurate, obtaining very good results (similar to those obtained without approximation) while computational time is dramatically decreased. On the other hand, cubic spline interpolation also obtains similar good results, but due to its intrinsic complexity, the global algorithm is much more slow and hence not useful for our purpose.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Trabecular Bone Score (TBS)--A Novel Method to Evaluate Bone Microarchitectural Texture in Patients With Primary Hyperparathyroidism.

Context: In the milder form of primary hyperparathyroidism (PHPT), cancellous bone, represented by areal bone mineral density at the lumbar spine by dual-energy x-ray absorptiometry (DXA), is preserved. This finding is in contrast to high-resolution peripheral quantitative computed tomography (HRpQCT) results of abnormal trabecular microstructure and epidemiological evidence for increased overall fracture risk in PHPT. Because DXA does not directly measure trabecular bone and HRpQCT is not widely available, we used trabecular bone score (TBS), a novel gray-level textural analysis applied to spine DXA images, to estimate indirectly trabecular microarchitecture. Objective: The purpose of this study was to assess TBS from spine DXA images in relation to HRpQCT indices and bone stiffness in radius and tibia in PHPT. Design and Setting: This was a cross-sectional study conducted in a referral center. Patients: Participants were 22 postmenopausal women with PHPT. Main Outcome Measures: Outcomes measured were areal bone mineral density by DXA, TBS indices derived from DXA images, HRpQCT standard measures, and bone stiffness assessed by finite element analysis at distal radius and tibia. Results: TBS in PHPT was low at 1.24, representing abnormal trabecular microstructure (normal ≥1.35). TBS was correlated with whole bone stiffness and all HRpQCT indices, except for trabecular thickness and trabecular stiffness at the radius. At the tibia, correlations were observed between TBS and volumetric densities, cortical thickness, trabecular bone volume, and whole bone stiffness. TBS correlated with all indices of trabecular microarchitecture, except trabecular thickness, after adjustment for body weight. Conclusion: TBS, a measurement technology readily available by DXA, shows promise in the clinical assessment of trabecular microstructure in PHPT.

Linear and nonlinear terrain deformation maps from a reduced set of interferometric SAR images

In this paper, an advanced technique for the generation of deformation maps using synthetic aperture radar (SAR) data is presented. The algorithm estimates the linear and nonlinear components of the displacement, the error of the digital elevation model (DEM) used to cancel the topographic terms, and the atmospheric artifacts from a reduced set of low spatial resolution interferograms. The pixel candidates are selected from those presenting a good coherence level in the whole set of interferograms and the resulting nonuniform mesh tessellated with the Delauney triangulation to establish connections among them. The linear component of movement and DEM error are estimated adjusting a linear model to the data only on the connections. Later on, this information, once unwrapped to retrieve the absolute values, is used to calculate the nonlinear component of movement and atmospheric artifacts with alternate filtering techniques in both the temporal and spatial domains. The method presents high flexibility with respect to the required number of images and the baselines length. However, better results are obtained with large datasets of short baseline interferograms. The technique has been tested with European Remote Sensing SAR data from an area of Catalonia (Spain) and validated with on-field precise leveling measurements.