Seismic reflectivity of the sediment-covered seafloor: Effects of velocity gradients and fine-scale layering

Knowledge of the reflectivity of the sediment-covered seabed is of significant importance to marine seismic data acquisition and interpretation as it governs the generation of reverberations in the water layer. In this context pertinent, but largely unresolved, questions concern the importance of the typically very prominent vertical seismic velocity gradients as well as the potential presence and magnitude of anisotropy in soft surficial seabed sediments. To address these issues, we explore the seismic properties of granulometric end-member-type clastic sedimentary seabed models consisting of sand, silt, and clay as well as scale-invariant stochastic layer sequences of these components characterized by realistic vertical gradients of the P- and S-wave velocities. Using effective media theory, we then assess the nature and magnitude of seismic anisotropy associated with these models. Our results indicate that anisotropy is rather benign for P-waves, and that the S-wave velocities in the axial directions differ only slightly. Because of the very high P- to S-wave velocity ratios in the vicinity of the seabed our models nevertheless suggest that S-wave triplications may occur at very small incidence angles. To numerically evaluate the P-wave reflection coefficient of our seabed models, we apply a frequency-slowness technique to the corresponding synthetic seismic wavefields. Comparison with analytical plane-wave reflection coefficients calculated for corresponding isotropic elastic half-space models shows that the differences tend to be most pronounced in the vicinity of the elastic equivalent of the critical angle as well as in the post-critical range. We also find that the presence of intrinsic anisotropy in the clay component of our layered models tends to dramatically reduce the overall magnitude of the P-wave reflection coefficient as well as its variation with incidence angle.

Estimation of the correlation structure of crustal velocity heterogeneity from seismic reflection data

Numerous sources of evidence point to the fact that heterogeneity within the Earth's deep crystalline crust is complex and hence may be best described through stochastic rather than deterministic approaches. As seismic reflection imaging arguably offers the best means of sampling deep crustal rocks in situ, much interest has been expressed in using such data to characterize the stochastic nature of crustal heterogeneity. Previous work on this problem has shown that the spatial statistics of seismic reflection data are indeed related to those of the underlying heterogeneous seismic velocity distribution. As of yet, however, the nature of this relationship has remained elusive due to the fact that most of the work was either strictly empirical or based on incorrect methodological approaches. Here, we introduce a conceptual model, based on the assumption of weak scattering, that allows us to quantitatively link the second-order statistics of a 2-D seismic velocity distribution with those of the corresponding processed and depth-migrated seismic reflection image. We then perform a sensitivity study in order to investigate what information regarding the stochastic model parameters describing crustal velocity heterogeneity might potentially be recovered from the statistics of a seismic reflection image using this model. Finally, we present a Monte Carlo inversion strategy to estimate these parameters and we show examples of its application at two different source frequencies and using two different sets of prior information. Our results indicate that the inverse problem is inherently non-unique and that many different combinations of the vertical and lateral correlation lengths describing the velocity heterogeneity can yield seismic images with the same 2-D autocorrelation structure. The ratio of all of these possible combinations of vertical and lateral correlation lengths, however, remains roughly constant which indicates that, without additional prior information, the aspect ratio is the only parameter describing the stochastic seismic velocity structure that can be reliably recovered.

Sperm velocity in an Alpine whitefish: effects of age, size, condition, fluctuating asymmetry and gonad abnormalities

The relationship between sperm velocity and individual age, size, body condition and fluctuating asymmetry was investigated in Alpine whitefish Coregonus fatioi. The fish analysed belonged to one among several sympatric whitefish populations of Lake Thun, Switzerland, which are characterized by a high prevalence of gonad alterations. Therefore, sperm velocity data were also tested for a link between gonad deformation and sperm swimming speed. Sperm velocity was significantly lower in larger-grown individuals and in individuals of higher body condition. As expected, sperm velocity was higher in males with higher levels of fluctuating asymmetry, but it did not significantly vary with male age. Moreover, variation in sperm velocity was found to be significantly higher in individuals showing some types of gonad alterations but it did not significantly correlate with the presence of other types of alterations. (C) 2007 The Authors Journal compilation (C) 2007 The Fisheries Society of the British Isles.

Bilateral Sequential NAION: A Comparison of Visual Outcomes in Fellow Eyes Using Quantitative Analysis of Goldmann Visual Fields

Purpose: Previous studies of the visual outcome in bilateral non-arteritic anterior ischemic optic neuropathy (NAION) have yielded conflicting results, specifically regarding congruity between fellow eyes. Prior studies have used measures of acuity and computerized perimetry but none has compared Goldmann visual field outcomes between fellow eyes. In order to better define the concordance of visual loss in this condition, we reviewed our cases of bilateral sequential NAION, including measures of visual acuity, pupillary function and both pattern and severity of visual field loss.Methods: We performed a retrospective chart review of 102 patients with a diagnosis of bilateral sequential NAION. Of the 102 patients, 86 were included in the study for analysis of final visual outcome between the affected eyes. Visual function was assessed using visual acuity, Goldmann visual fields, color vision and RAPD. A quantitative total visual field score and score per quadrant was analyzed for each eye using the numerical Goldmann visual field scoring method previously described by Esterman and colleagues. Based upon these scores, we calculated the total deviation and pattern deviation between fellow eyes and between eyes of different patients. Statistical significance was determined using nonparametric tests.Results: A statistically significant correlation was found between fellow eyes for multiple parameters, including logMAR visual acuity (P = 0.0101), global visual field (P = 0.0001), superior visual field (P = 0.0001), and inferior visual field (P = 0.0001). In addition, the mean deviation of both total (P = 0.0000000007) and pattern (P = 0.000000004) deviation analyses was significantly less between fellow eyes ("intra"-eyes) than between eyes of different patients ("inter"-eyes).Conclusions: Visual function between fellow eyes showed a fair to moderate correlation that was statistically significant. The pattern of vision loss was also more similar in fellow eyes than between eyes of different patients. These results may help allow better prediction of visual outcome for the second eye in patients with NAION. These findings may also be useful for evaluating efficacy of therapeutic interventions.

Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

Early parenteral lipids and growth velocity in extremely-low-birth-weight infants.

BACKGROUND & AIMS: Whether early parenteral lipids improve postnatal growth of preterm neonates remains unclear. We aimed to assess the effects of parenteral lipids on growth velocity in extremely-low-birth-weight infants. METHODS: This retrospective cohort study included 121 extremely-low-birth-weight infants. The associations between parenteral lipids (cumulative intakes during the first week and delays in their introduction) and growth velocities (weight, head circumference and length) up to 28 days of life and to 36 weeks of corrected age were analysed using uni- and multivariate linear regression. RESULTS: Univariate analyses showed a significant positive association between the cumulative intakes of parenteral lipids during the first week and i) weight gain up to day 28; ii) weight gain up to 36 weeks of corrected age; iii) head circumference growth up to day 28. There was a negative correlation between the delay in parenteral lipid introduction and weight gain up to day 28. In multivariate analyses, the association between the cumulative intakes of parenteral lipids and weight gain up to 28 days was independent of gestational age at birth, birth weight, sex, smallness for gestational age, and enteral intakes (regression coefficient: 0.19; 95% CI: 0.01-0.38) and, up to 36 weeks, independent of gestational age, birth weight, sex, smallness for gestational age and parenteral glucose and amino acids (0.16; 95% CI: 0.04-0.27). CONCLUSIONS: Parenteral lipids during the first week were positively associated with weight gain in extremely-low-birth-weight infants and could improve early nutritional support of preterm neonates.

Constraints on the permeability structure of alluvial aquifers from the poro-elastic inversion of multi-frequency P-wave velocity logs

We have explored the possibility of obtaining first-order permeability estimates for saturated alluvial sediments based on the poro-elastic interpretation of the P-wave velocity dispersion inferred from sonic logs. Modern sonic logging tools designed for environmental and engineering applications allow one for P-wave velocity measurements at multiple emitter frequencies over a bandwidth covering 5 to 10 octaves. Methodological considerations indicate that, for saturated unconsolidated sediments in the silt to sand range and typical emitter frequencies ranging from approximately 1 to 30 kHz, the observable velocity dispersion should be sufficiently pronounced to allow one for reliable first-order estimations of the permeability structure. The corresponding predictions have been tested on and verified for a borehole penetrating a typical surficial alluvial aquifer. In addition to multifrequency sonic logs, a comprehensive suite of nuclear and electrical logs, an S-wave log, a litholog, and a limited number laboratory measurements of the permeability from retrieved core material were also available. This complementary information was found to be essential for parameterizing the poro-elastic inversion procedure and for assessing the uncertainty and internal consistency of corresponding permeability estimates. Our results indicate that the thus obtained permeability estimates are largely consistent with those expected based on the corresponding granulometric characteristics, as well as with the available evidence form laboratory measurements. These findings are also consistent with evidence from ocean acoustics, which indicate that, over a frequency range of several orders-of-magnitude, the classical theory of poro-elasticity is generally capable of explaining the observed P-wave velocity dispersion in medium- to fine-grained seabed sediments

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

Changes in Aortic Pulse Wave Velocity in Hypertensive Postmenopausal Women: Comparison Between a Calcium Channel Blocker vs Angiotensin Receptor Blocker Regimen.

J Clin Hypertens (Greenwich). 2012;14:773-778. ©2012 Wiley Periodicals, Inc. Postmenopausal women are at greater risk for hypertension-related cardiovascular disease. Antihypertensive therapy may help alleviate arterial stiffness that represents a potential modifiable risk factor of hypertension. This randomized controlled study investigated the difference between an angiotensin receptor blocker and a calcium channel blocker in reducing arterial stiffness. Overall, 125 postmenopausal hypertensive women (age, 61.4±6 years; systolic blood pressure/diastolic blood pressure [SBP/DBP], 158±11/92±9 mm Hg) were randomized to valsartan 320 mg±hydrochlorothiazide (HCTZ) (n=63) or amlodipine 10 mg±HCTZ (n=62). The primary outcome was carotid-to-femoral pulse wave velocity (PWV) changes after 38 weeks of treatment. Both treatments lowered peripheral blood pressure (BP) (-22.9/-10.9 mm Hg for valsartan and -25.2/-11.7 mm Hg for amlodipine, P=not significant) and central BP (-15.7/-7.6 mm Hg for valsartan and -19.2/-10.3 mm Hg for amlodipine, P<.05 for central DBP). Both treatments similarly reduced the carotid-femoral PWV (-1.9 vs -1.7 m/s; P=not significant). Amlodipine was associated with a higher incidence of peripheral edema compared with the valsartan group (77% vs 14%, P<.001). BP lowering in postmenopausal women led to a reduction in arterial stiffness as assessed by PWV measurement. Both regimens reduced PWV to a similar degree after 38 weeks of treatment despite differences in central BP lowering, suggesting that the effect of valsartan on PWV is mediated through nonhemodynamic effects.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Geostatistical inversion of seismic and GPR reflection images: what can we actually resolve?

Estimation of the spatial statistics of subsurface velocity heterogeneity from surface-based geophysical reflection survey data is a problem of significant interest in seismic and ground-penetrating radar (GPR) research. A method to effectively address this problem has been recently presented, but our knowledge regarding the resolution of the estimated parameters is still inadequate. Here we examine this issue using an analytical approach that is based on the realistic assumption that the subsurface velocity structure can be characterized as a band-limited scale-invariant medium. Our work importantly confirms recent numerical findings that the inversion of seismic or GPR reflection data for the geostatistical properties of the probed subsurface region is sensitive to the aspect ratio of the velocity heterogeneity and to the decay of its power spectrum, but not to the individual values of the horizontal and vertical correlation lengths.

Distribution of arm velocity and frequency of arm usage during daily activity: objective outcome evaluation after shoulder surgery.

In clinical settings, functional evaluation of shoulder movement is primarily based on what the patient thinks he/she is able to do rather than what he/she is actually performing. We proposed a new approach for shoulder assessment based on inertial sensors to monitor arm movement in the daily routine. The detection of movement of the humerus relative to the trunk was first validated in a laboratory setting (sensitivity>95%, specificity>97%). Then, 41 control subjects and 21 patients suffering from a rotator cuff tear were evaluated (before and after surgery) using clinical questionnaires and a one-day measurement of arm movement. The quantity of movement was estimated with the movement frequency and its symmetry index (SIFr). The quality of movement was assessed using the Kolmogorov-Smirnov distance (KS) between the cumulative distribution of the arm velocity for controls and the same distribution for each patient. SIFr presented differences between patients and controls at 3 month follow-up (p<0.05) while KS showed differences also after 6 months (p<0.01). SIFr illustrated a change in dominance due to the disorder whereas KS, which appeared independent of the dominance and occupation, showed a change in movement velocity. Both parameters were correlated to clinical scores (R(2) reaching 0.5). This approach provides clinicians with new objective parameters for evaluating the functional ability of the shoulder in daily conditions, which could be useful for outcome assessment after surgery.