2,075 research outputs found
New CPT methods for evaluation of the axial capacity of driven piles
High costs associated with offshore foundation installations have provided strong impetus to the offshore energy sector in the search for more reliable design methods. This paper provides a summary of an Industry sponsored project that led to the development of new CPT-based design methods for the evaluation of the axial capacity of driven piles. Particular attention was given to the need for the new methods to be applicable to large diameter offshore piles given that many existing methods are derived by calibration with capacities measured in static pile load tests on smaller diameter onshore piles. The basic mechanisms supporting the general format of the expressions proposed for shaft friction and end bearing in sands and clays are described. It is shown how the new expressions, which are calibrated against a database of the most reliable load tests reported in the literature, lead to better predictions of capacity compared to other methods and can also satisfactorily predict the capacity of piles driven into deposits comprising interbedded layers of sand, silt and clay. Recommendations for the prediction of pile displacements at working loads using CPT data are also presented.New CPT methods for evaluation of the axial capacity of driven pilespublishedVersio
Statistical properties of absolute log-returns and a stochastic model of stock markets with heterogeneous agents
This paper is intended as an investigation of the statistical properties of
{\it absolute log-returns}, defined as the absolute value of the logarithmic
price change, for the Nikkei 225 index in the 28-year period from January 4,
1975 to December 30, 2002. We divided the time series of the Nikkei 225 index
into two periods, an inflationary period and a deflationary period. We have
previously [18] found that the distribution of absolute log-returns can be
approximated by the power-law distribution in the inflationary period, while
the distribution of absolute log-returns is well described by the exponential
distribution in the deflationary period.\par To further explore these empirical
findings, we have introduced a model of stock markets which was proposed in
[19,20]. In this model, the stock market is composed of two groups of traders:
{\it the fundamentalists}, who believe that the asset price will return to the
fundamental price, and {\it the interacting traders}, who can be noise traders.
We show through numerical simulation of the model that when the number of
interacting traders is greater than the number of fundamentalists, the
power-law distribution of absolute log-returns is generated by the interacting
traders' herd behavior, and, inversely, when the number of fundamentalists is
greater than the number of interacting traders, the exponential distribution of
absolute log-returns is generated.Comment: 12 pages, 5 figure
A 3D Fully Convolutional Neural Network With Top-Down Attention-Guided Refinement for Accurate and Robust Automatic Segmentation of Amygdala and Its Subnuclei
Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorders. However, most existing deep learning based approaches in neuroimaging do not investigate the specific difficulties that exist in segmenting extremely small but important brain regions such as the subnuclei of the amygdala. To tackle this challenging task, we developed a dual-branch dilated residual 3D fully convolutional network with parallel convolutions to extract more global context and alleviate the class imbalance issue by maintaining a small receptive field that is just the size of the regions of interest (ROIs). We also conduct multi-scale feature fusion in both parallel and series to compensate the potential information loss during convolutions, which has been shown to be important for small objects. The serial feature fusion enabled by residual connections is further enhanced by a proposed top-down attention-guided refinement unit, where the high-resolution low-level spatial details are selectively integrated to complement the high-level but coarse semantic information, enriching the final feature representations. As a result, the segmentations resulting from our method are more accurate both volumetrically and morphologically, compared with other deep learning based approaches. To the best of our knowledge, this work is the first deep learning-based approach that targets the subregions of the amygdala. We also demonstrated the feasibility of using a cycle-consistent generative adversarial network (CycleGAN) to harmonize multi-site MRI data, and show that our method generalizes well to challenging traumatic brain injury (TBI) datasets collected from multiple centers. This appears to be a promising strategy for image segmentation for multiple site studies and increased morphological variability from significant brain pathology
Generation of defects and disorder from deeply quenching a liquid to form a solid
We show how deeply quenching a liquid to temperatures where it is linearly
unstable and the crystal is the equilibrium phase often produces crystalline
structures with defects and disorder. As the solid phase advances into the
liquid phase, the modulations in the density distribution created behind the
advancing solidification front do not necessarily have a wavelength that is the
same as the equilibrium crystal lattice spacing. This is because in a deep
enough quench the front propagation is governed by linear processes, but the
crystal lattice spacing is determined by nonlinear terms. The wavelength
mismatch can result in significant disorder behind the front that may or may
not persist in the latter stage dynamics. We support these observations by
presenting results from dynamical density functional theory calculations for
simple one- and two-component two-dimensional systems of soft core particles.Comment: 25 pages, 11 figure
Curvature Based Biomarkers for Diabetic Retinopathy via Exponential Curve Fits in SE(2)
We propose a robust and fully automatic method for the analysis of vessel tortuosity. Our method does not rely on pre-segmentation of vessels, but instead acts directly on retinal image data. The method is based on theory of best-fit exponential curves in the roto-translation group SE(2). We lift 2D images to 3D functions called orientation scores by including an orientation dimension in the domain. In the extended domain of positions and orientations (identified with SE(2)) we study exponential curves, whose spatial projections have constant curvature. By locally fitting such curves to data in orientation scores, via our new iterative stabilizing refinement method, we are able to assign to each location a curvature and confidence value. These values are then used to define global tortuosity measures. The method is validated on synthetic and retinal images. We show that the tortuosity measures can serve as effective biomarkers for diabetes and different stages of diabetic retinopathy
Retinal Artery/Vein Classification via Graph Cut Optimization
In many diseases with a cardiovascular component, the geometry of microvascular blood vessels changes. These changes are specific to arteries and veins, and can be studied in the microvasculature of the retina using retinal photography. To facilitate large-scale studies of artery/vein-specific changes in the retinal vasculature, automated classification of the vessels is required. Here we present a novel method for artery/vein classification based on local and contextual feature analysis of retinal vessels. For each vessel, local information in the form of a transverse intensity profile is extracted. Crossings and bifurcations of vessels provide contextual information. The local and contextual features are integrated into a non-submodular energy function, which is optimized exactly using graph cuts. The method was validated on a ground truth data set of 150 retinal fundus images, achieving an accuracy of 88.0% for all vessels and 94.0% for the six arteries and six veins with highest caliber in the image
Axial vector current in an electromagnetic field and low-energy neutrino-photon interactions
An expression for the axial vector current in a strong, slowly varying
electromagnetic field is obtained. We apply this expression to the construction
of the effective action for low-energy neutrino-photon interactions.Comment: 6 pages, references updated, final version to appear in Phys. Rev.
Single-hole properties in the - and strong-coupling models
We report numerical results for the single-hole properties in the -
model and the strong-coupling approximation to the Hubbard model in two
dimensions. Using the hopping basis with over states we discuss (for an
infinite system) the bandwidth, the leading Fourier coefficients in the
dispersion, the band masses, and the spin-spin correlations near the hole. We
compare our results with those obtained by other methods. The band minimum is
found to be at () for the - model for , and for the strong-coupling model for . The bandwidth
in both models is approximately at large , in rough agreement with
loop-expansion results but in disagreement with other results. The
strong-coupling bandwidth for t/J\agt6 can be obtained from the - model
by treating the three-site terms in first-order perturbation theory. The
dispersion along the magnetic zone face is flat, giving a large
parallel/perpendicular band mass ratio.Comment: 1 RevTeX file with epsf directives to include 8 .eps figures 8 figure
files encoded using uufile
Attitudes to a male contraceptive pill in a group of contraceptive users in the UK
BACKGROUND. Small scale trials of male hormonal contraception have produced encouraging results. Attitudes to and beliefs about a proposed male pill may affect uptake. METHODS. This paper examines attitudes towards a proposed âmale contraceptive pillâ among a self selected sample of 54 men and 134 women, living in a non-metropolitan centre in the East of England, United Kingdom who were already users of contraception. Thirty four respondents were also interviewed and their views on the male pill were qualitatively analysed.
RESULTS. The acceptability of a male pill was high with just under half (49.5%) of respondents indicating that they would use it. Gender, length of relationship, age and educational achievement did not affect the reported acceptability. 42% of respondents expressed concerns that men would forget to take a male pill. Women were significantly more likely to express this concern than men. 26% of respondents expressed health concerns. Willingness to take a male pill was associated with expressing the view that increased protection against pregnancy would be an advantage of such a method. Those unwilling or undecided were more likely to express concerns about the effect of a pill on future fertility.
CONCLUSIONS. A male pill was accepted as a potential aid to increased fertility control by a large proportion of a convenience sample of contraceptive users in the East of England. If a male pill were to be marketed in the UK this study suggests that concerns about effects on future fertility and health risks may need to be addressed
- âŠ