Cost function adaptation: a stochastic gradient algorithm for data echo cancellation

A family of stochastic gradient algorithms and their behaviour in the data echo cancellation work platform are presented. The cost function adaptation algorithms use an error exponent update strategy based on an absolute error mapping, which is updated at every iteration. The quadratic and nonquadratic cost functions are special cases of the new family. Several possible realisations are introduced using these approaches. The noisy error problem is discussed and the digital recursive filter estimator is proposed. The simulation outcomes confirm the effectiveness of the proposed family of algorithms.

Spectral induced polarization signatures of abiotic FeS precipitation

In recent years, geophysical methods have been shown to be sensitive to microbial-induced mineralization processes. The spectral induced-polarization (SIP) method appears to be very promising for monitoring mineralization and microbial processes. With this work, we study the links of mineralization and SIP signals, in the absence of microbial activity. We recorded the SIP response during abiotic FeS precipitation. We show that the SIP signals are diagnostic of FeS mineralization and can be differentiated from SIP signals from biomineralization processes. More specifically, the imaginary conductivity shows almost linear dependence on the amount of FeS precipitating out of solution, above the threshold value 0.006 gr under our experimental conditions. This research has direct implications for the use of the SIP method as a monitoring and decision-making tool for sustainable remediation of metals in contaminated soils and groundwater.

Segmentation of optic disc in retinal images using an improved gradient vector flow algorithm

Image segmentation plays an important role in the analysis of retinal images as the extraction of the optic disk provides important cues for accurate diagnosis of various retinopathic diseases. In recent years, gradient vector flow (GVF) based algorithms have been used successfully to successfully segment a variety of medical imagery. However, due to the compromise of internal and external energy forces within the resulting partial differential equations, these methods can lead to less accurate segmentation results in certain cases. In this paper, we propose the use of a new mean shift-based GVF segmentation algorithm that drives the internal/external energies towards the correct direction. The proposed method incorporates a mean shift operation within the standard GVF cost function to arrive at a more accurate segmentation. Experimental results on a large dataset of retinal images demonstrate that the presented method optimally detects the border of the optic disc.

Relativistic laser pulse compression in plasmas with a linear axial density gradient

The self-compression of a relativistic Gaussian laser pulse propagating in a non-uniform plasma is investigated. A linear density inhomogeneity (density ramp) is assumed in the axial direction. The nonlinear Schrodinger equation is first solved within a one-dimensional geometry by using the paraxial formalism to demonstrate the occurrence of longitudinal pulse compression and the associated increase in intensity. Both longitudinal and transverse self-compression in plasma is examined for a finite extent Gaussian laser pulse. A pair of appropriate trial functions, for the beam width parameter (in space) and the pulse width parameter (in time) are defined and the corresponding equations of space and time evolution are derived. A numerical investigation shows that inhomogeneity in the plasma can further boost the compression mechanism and localize the pulse intensity, in comparison with a homogeneous plasma. A 100 fs pulse is compressed in an inhomogeneous plasma medium by more than ten times. Our findings indicate the possibility for the generation of particularly intense and short pulses, with relevance to the future development of tabletop high-power ultrashort laser pulse based particle acceleration devices and associated high harmonic generation. An extension of the model is proposed to investigate relativistic laser pulse compression in magnetized plasmas.

The synthesis and characterization of nanophase hydroxyapatite using a novel dispersant-aided precipitation method

The synthesis of nanophase hydroxyapatite (nHA) is of importance in the field of biomaterials and bone tissue engineering. The bioactive and osteoconductive properties of nHA are of much benefit to a wide range of biomedical applications such as producing bone tissue engineered constructs, coating medical implants, or as a carrier for plasmid DNA in gene delivery. This study aimed to develop a novel low-temperature dispersant-aided precipitation reaction to produce nHA particles (