Magnitude and distribution of sea turtle bycatch in the sea scallop (Placopecten magellanicus) dredge fishery in two areas of the northwestern Atlantic Ocean, 2001–2002

In May 2001, the National Marine Fisheries Service (NMFS) opened two areas in the northwestern Atlantic Ocean that had been previously closed to the U.S. sea scallop (Placopecten magellanicus) dredge fishery. Upon reopening these areas, termed the “Hudson Canyon Controlled Access Area” and the “Virginia Beach Controlled Access Area,” NMFS observers found that marine turtles were being caught incidentally in scallop dredges. This study uses the generalized linear model and the generalized additive model fitting techniques to identify environmental factors and gear characteristics that influence bycatch rates, and to predict total bycatch in these two areas during May-December 2001 and 2002 by incorporating environmental factors into the models. Significant factors affecting sea turtle bycatch were season, time-of-day, sea surface temperature, and depth zone. In estimating total bycatch, rates were stratified according to a combination of all these factors except time-of-day which was not available in fishing logbooks. Highest bycatch rates occurred during the summer season, in temperatures greater than 19°C, and in water depths from 49 to 57 m. Total estimated bycatch of sea turtles during May–December in 2001 and 2002 in both areas combined was 169 animals (CV=55.3), of which 164 (97%) animals were caught in the Hudson Canyon area. From these findings, it may be possible to predict hot spots for sea turtle bycatch in future years in the controlled access areas.

The influence of peel angle on the mechanics of peeling flexible adherends with arbitrary load-extension characteristics

The peel test is commonly used to determine the strength of adhesive joints. In its simplest form, a thin flexible strip which has been bonded to a rigid surface is peeled from the substrate at a constant rate and the peeling force which is applied to the debonding surfaces by the tension in the tape is measured. Peeling can be carried out with the peel angle, i.e. the angle made by the peel force with the substrate surface, from any value above about 10° although peeling tests at 90 and 180° are most common. If the tape is sufficiently thin for its bending resistance to be negligibly small then as well as the debonding or decohesion energy associated with the adhesive in and around the point of separation, the relation between the peeling force and the peeling angle is influenced both by the mechanical properties of the tape and any pre-strain locked into the tape during its application to the substrate. The analytic solution for a tape material which can be idealised as elastic perfectly-plastic is well established. Here, we present a more general form of analysis, applicable in principle to any constitutive relation between tape load and tape extension. Non-linearity between load and extension is of increasing significance as the peel angle is decreased: the model presented is consistent with existing equations describing the failure of a lap joint between non-linear materials. The analysis also allows for energy losses within the adhesive layer which themselves may be influenced by both peel rate and peel angle. We have experimentally examined the application of this new analysis to several specific peeling cases including tapes of cellophane, poly-vinyl chloride and PTFE. © 2005 Elsevier Ltd. All rights reserved.

Chemical vapor deposition of nanocrystalline graphene directly on arbitrary high-temperature insulating substrates

Large area uniform nanocrystalline graphene is grown by chemical vapor deposition on arbitrary insulating substrates that can survive ∼1000°C. The as-synthesized graphene is nanocrystalline with a domain size in the order of ∼10 nm. The material possesses a transparency and conductivity similar to standard graphene fabricated by exfoliation or catalysis. A noncatalytic mechanism is proposed to explain the experimental phenomena. The developed technique is scalable and reproducible, compatible with the existing semiconductor technology, and thus can be very useful in nanoelectronic applications such as transparent electronics, nanoelectromechanical systems, as well as molecular electronics. © 2012 IEEE.

Calibration of the spring constant of cantilevers of arbitrary shape using the phase signal in an atomic force microscope.

The measurement of cantilever parameters is an essential part of performing a calibrated measurement with an atomic force microscope (AFM). The thermal motion method is a widely used technique for calibrating the spring constant of an AFM cantilever, which can be applied to non-rectangular cantilevers. Given the trend towards high frequency scanning, calibration of non-rectangular cantilevers is of increasing importance. This paper presents two results relevant to cantilever calibration via the thermal motion method. We demonstrate the possibility of using the AFM's phase signal to acquire the thermal motion. This avoids the challenges associated with connecting the raw photodiode signal to a separate spectrum analyser. We also describe how numerical calculations may be used to calculate the parameters needed in a thermal motion calibration of a non-rectangular cantilever. Only accurate knowledge of the relative size of the in-plane dimensions of the cantilever is needed in this computation. We use this pair of results in the calibration of a variety of rectangular and non-rectangular cantilevers. We observe an average difference between the Sader and thermal motion values of cantilever stiffness of 10%.

Gaussian Approximation Potential: an interatomic potential derived from first principles Quantum Mechanics

Simulation of materials at the atomistic level is an important tool in studying microscopic structure and processes. The atomic interactions necessary for the simulation are correctly described by Quantum Mechanics. However, the computational resources required to solve the quantum mechanical equations limits the use of Quantum Mechanics at most to a few hundreds of atoms and only to a small fraction of the available configurational space. This thesis presents the results of my research on the development of a new interatomic potential generation scheme, which we refer to as Gaussian Approximation Potentials. In our framework, the quantum mechanical potential energy surface is interpolated between a set of predetermined values at different points in atomic configurational space by a non-linear, non-parametric regression method, the Gaussian Process. To perform the fitting, we represent the atomic environments by the bispectrum, which is invariant to permutations of the atoms in the neighbourhood and to global rotations. The result is a general scheme, that allows one to generate interatomic potentials based on arbitrary quantum mechanical data. We built a series of Gaussian Approximation Potentials using data obtained from Density Functional Theory and tested the capabilities of the method. We showed that our models reproduce the quantum mechanical potential energy surface remarkably well for the group IV semiconductors, iron and gallium nitride. Our potentials, while maintaining quantum mechanical accuracy, are several orders of magnitude faster than Quantum Mechanical methods.

Reconstruction of arbitrary biochemical reaction networks: A compressive sensing approach

Reconstruction of biochemical reaction networks (BRN) and genetic regulatory networks (GRN) in particular is a central topic in systems biology which raises crucial theoretical challenges in system identification. Nonlinear Ordinary Differential Equations (ODEs) that involve polynomial and rational functions are typically used to model biochemical reaction networks. Such nonlinear models make the problem of determining the connectivity of biochemical networks from time-series experimental data quite difficult. In this paper, we present a network reconstruction algorithm that can deal with ODE model descriptions containing polynomial and rational functions. Rather than identifying the parameters of linear or nonlinear ODEs characterised by pre-defined equation structures, our methodology allows us to determine the nonlinear ODEs structure together with their associated parameters. To solve the network reconstruction problem, we cast it as a compressive sensing (CS) problem and use sparse Bayesian learning (SBL) algorithms as a computationally efficient and robust way to obtain its solution. © 2012 IEEE.

Learning based automatic face annotation for arbitrary poses and expressions from frontal images only

Statistical approaches for building non-rigid deformable models, such as the Active Appearance Model (AAM), have enjoyed great popularity in recent years, but typically require tedious manual annotation of training images. In this paper, a learning based approach for the automatic annotation of visually deformable objects from a single annotated frontal image is presented and demonstrated on the example of automatically annotating face images that can be used for building AAMs for fitting and tracking. This approach employs the idea of initially learning the correspondences between landmarks in a frontal image and a set of training images with a face in arbitrary poses. Using this learner, virtual images of unseen faces at any arbitrary pose for which the learner was trained can be reconstructed by predicting the new landmark locations and warping the texture from the frontal image. View-based AAMs are then built from the virtual images and used for automatically annotating unseen images, including images of different facial expressions, at any random pose within the maximum range spanned by the virtually reconstructed images. The approach is experimentally validated by automatically annotating face images from three different databases. © 2009 IEEE.

An Arbitrary Lagrangian Eulerian Method for Three-Phase Flows with Triple Junction Points

We present a moving mesh method suitable for solving two-dimensional and axisymmetric three-liquid flows with triple junction points. This method employs a body-fitted unstructured mesh where the interfaces between liquids are lines of the mesh system, and the triple junction points (if exist) are mesh nodes. To enhance the accuracy and the efficiency of the method, the mesh is constantly adapted to the evolution of the interfaces by refining and coarsening the mesh locally; dynamic boundary conditions on interfaces, in particular the triple points, are therefore incorporated naturally and accurately in a Finite- Element formulation. In order to allow pressure discontinuity across interfaces, double-values of pressure are necessary for interface nodes and triple-values of pressure on triple junction points. The resulting non-linear system of mass and momentum conservation is then solved by an Uzawa method, with the zero resultant condition on triple points reinforced at each time step. The method is used to investigate the rising of a liquid drop with an attached bubble in a lighter liquid.

A Numerical Method for Calculating Transmission Coefficients Across Arbitrary Potential Barriers with High Accuracy

We report a new method for calculating transmission coefficients across arbitrary potential barriers based on the Runge-Kutta method. A numerical solution of the Schrodinger equation is calculated using the Runge-Kutta method,and a new model is established to analyze the numerical results to find the transmission coefficient. This technique is applied to various cases, such as parabolic potential barrier and double-barrier structures. Transmission probability with high precision is obtained and discussed. The tunnelling current density through a MOS structure is also explored and the result coincides with the Fowler-Nordheim model,which indicates the applicability of our method.