Preventing adolescent depression: An evaluation of the problem solving for life program

This study evaluated the effectiveness of the Problem Solving For Life program as it universal approach to the prevention of adolescent depression. Short-term results indicated that participants with initially elevated depressions scores (high risk) who received the intervention showed a significantly greater decrease in depressive symptoms and increase in life problem-solving scores from pre- to postintervention compared with a high-risk control group. Low-risk participants who received the intervention reported a small but significant decrease in depression scores over the intervention period, whereas the low-risk controls reported an increase in depression scores. The low-risk group reported a significantly greater increase in problem-solving scores over the intervention period compared with low-risk controls. These results were not maintained, however, at 12-month follow-up.

Urea based osmoregulation and endocrine control in elasmobranch fish with special reference to euryhalinity

Since the landmark contributions of Homer Smith and co-workers in the 1930s there has been a considerable advance in our knowledge regarding the osmoregulatory strategy of elasmobranch fish. Smith recognised that urea was retained in the body fluids as part of the 'osmoregulatory ballast' of elasmobranch fish so that body fluid osmolality is raised to a level that is iso- or slightly hyper-osmotic to that of the surrounding medium. From studies at that time he also postulated that many marine dwelling elasmobranchs were not capable of adaptation to dilute environments. However, more recent investigations have demonstrated that, at least in some species, this may not be the case. Gradual acclimation of marine dwelling elasmobranchs to varying environmental salinities under laboratory conditions has demonstrated that these fish do have the capacity to acclimate to changes in salinity through independent regulation of Na+, Cl- and urea levels. This suggests that many of the presumed stenohaline marine elasmobranchs could in fact be described as partially euryhaline. The contributions of Thomas Thorson in the 1970s demonstrated the osmoregulatory strategy of a fully euryhaline elasmobranch, the bull shark, Carcharhinus leucas, and more recent investigations have examined the mechanisms behind this strategy in the euryhaline elasmobranch, Dasyatis sabina. Both partially euryhaline and fully euryhaline species utilise the same physiological processes to control urea, Na+ and Cl- levels within the body fluids. The role of the gills, kidney, liver, rectal gland and drinking process is discussed in relation to the endocrine control of urea, Na+ and Cl- levels as elasmobranchs acclimate to different environmental salinities. (C) 2003 Elsevier Inc. All rights reserved.

An implementation of nonlinear multiuser detection in Rayleigh fading channel

A blind nonlinear interference cancellation receiver for code-division multiple-access- (CDMA-) based communication systems operating over Rayleigh flat-fading channels is proposed. The receiver which assumes knowledge of the signature waveforms of all the users is implemented in an asynchronous CDMA environment. Unlike the conventional MMSE receiver, the proposed blind ICA multiuser detector is shown to be robust without training sequences and with only knowledge of the signature waveforms. It has achieved nearly the same performance of the conventional training-based MMSE receiver. Several comparisons and experiments are performed based on examining BER performance in AWGN and Rayleigh fading in order to verify the validity of the proposed blind ICA multiuser detector.

Enhanced detection-guided NLMS estimation of sparse FIR-modeled signal channels

In various signal-channel-estimation problems, the channel being estimated may be well approximated by a discrete finite impulse response (FIR) model with sparsely separated active or nonzero taps. A common approach to estimating such channels involves a discrete normalized least-mean-square (NLMS) adaptive FIR filter, every tap of which is adapted at each sample interval. Such an approach suffers from slow convergence rates and poor tracking when the required FIR filter is "long." Recently, NLMS-based algorithms have been proposed that employ least-squares-based structural detection techniques to exploit possible sparse channel structure and subsequently provide improved estimation performance. However, these algorithms perform poorly when there is a large dynamic range amongst the active taps. In this paper, we propose two modifications to the previous algorithms, which essentially remove this limitation. The modifications also significantly improve the applicability of the detection technique to structurally time varying channels. Importantly, for sparse channels, the computational cost of the newly proposed detection-guided NLMS estimator is only marginally greater than that of the standard NLMS estimator. Simulations demonstrate the favourable performance of the newly proposed algorithm. © 2006 IEEE.

Performance comparison between uniformly and nonuniformly spaced adaptive antennas with respect to tolerance to pointing errors

The paper presents theoretical and experimental investigations into performances of narrowband uniformly and nonuniformly spaced adaptive linear dipole array antennas that are subjected to pointing errors. The analysis focuses on the array's output Signal to Interference plus Noise Ratio. The presence of mutual coupling between the array elements is taken into account. It is shown that the array's tolerance to pointing errors can be enhanced by controlling the interelement spacing. (c) 2006 Wiley Periodicals, Inc.

Blind multiuser receiver for DS-CDMA wireless system

We consider blind signal detection in an asynchronous code-division multiple-access (CDMA) system employing short spreading sequences in the presence of unknown multipath fading. This approach is capable of countering the presence of multiple-access interference (MAI) in CDMA fading channels. The proposed blind multiuser detector is based on an independent component analysis (ICA) to mitigate both MAI and noise. This algorithm has been utilised in blind source separation (BSS) of unknown sources from their mixtures. It can also be used for estimating the basis vectors of BSS. The aim is to include an ICA algorithm within a wireless receiver in order to reduce the level of interference in wideband systems. This blind multiuser detector requires no training sequence compared with the conventional multiuser detection receiver. The proposed ICA blind multiuser detector is made robust with respect to knowledge of signature waveforms and the timing of the user of interest. Several experiments are performed in order to verify the validity of the proposed ICA algorithm.

Performance analysis using equivariant kernel density estimator in nonlinear mixture

This paper investigates the performance analysis of separation of mutually independent sources in nonlinear models. The nonlinear mapping constituted by an unsupervised linear mixture is followed by an unknown and invertible nonlinear distortion, are found in many signal processing cases. Generally, blind separation of sources from their nonlinear mixtures is rather difficult. We propose using a kernel density estimator incorporated with equivariant gradient analysis to separate the sources with nonlinear distortion. The kernel density estimator parameters of which are iteratively updated to minimize the output independence expressed as a mutual information criterion. The equivariant gradient algorithm has the form of nonlinear decorrelation to perform the convergence analysis. Experiments are proposed to illustrate these results.

Investigating the performance analysis of EASI algorithm and EKENS algorithm in nonlinear model

This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.