Statistically robust evidence of stochastic resonance in human auditory perceptual system

In human perception, exogenous noise is known to yield a masking effect, i.e. an increase of the perceptual threshold relative to a stimulus acting on the same modality. However, somehow counter-intuitively, the opposite mechanism can occasionally occur: a decrease of the perceptual threshold for a non-vanishing, virtuous amount of noise. This mechanism, called stochastic resonance, is deemed to provide important information about the role of noise in the human brain. In this paper, we investigate stochastic resonance in a detection task in the auditory modality. Normal-hearing participants were asked to judge the presence of acoustic stimuli of different intensity and superimposed to different levels of white noise. The matrix-like outcomes of a behavioural experiment were fitted by a two-dimensional, noise-dependent psychometric function. The fit revealed a statistically significant stochastic resonance in 43% of the experimental runs. We conclude that, in the auditory modality, stochastic resonance is a tiny effect that, under conventional circumstances, is largely overrun by standard masking.     

Calculation of three-dimensional thermal-gradient-induced stress birefringence in slab lasers

The thermal-gradient-induced stress birefringence and depolarization losses were reported previously for a Yb:YAG slab in which the plane-strain approximation applied. In this paper we present analyses of these phenomena applying a full three-dimensional treatment of deposited pump power and cooling in a Yb:YAG slab. We treat both straight-through and zigzag propagation and the cases of the slab length along the crystalline [1 1 1] and [1 1 0] axes. We also describe the losses in a slab with undoped Brewster ends and pump edges.     

Artificial neural network modeling of diuron and irgarol-based HPLC data and their levels from the seawaters in Izmir,Turkey

The LC determination of two well-known antifouling booster biocides, diuron and irgarol, was investigated from the seawaters in ?zmir, Turkey. The biocide levels were pre-concentrated through C18 solid-phase extraction cartridges and they were analyzed by the LC-UV method. An artificial neural network (ANN) was used to model the data obtained from LC optimization. Column temperature, percentage of acetonitrile, flow rate, wavelength, pH, and concentration of biocides were used as input parameters. The retention time was selected as output parameter. The best back-propagation algorithm in ANN modeling for diuron and irgarol was found to be the Levenberg–Marquardt algorithm. The limits of detection for diuron and irgarol were calculated as 25.38 and 39.49 ng L^?1, respectively. The inter-day and intra-day precisions were obtained less than 13.5% for each biocide. The recovery rate for diuron was 96.9% and for irgarol it was 84.6%. The maximum diuron and irgarol levels were measured as 1779 ng L^?1 and 908 ng L^?1, respectively. In conclusion, ANN is a robust modeling method to predict the retention time in LC studies. Since diuron and irgarol have been detected in Turkish waters, it is therefore suggested that booster biocides with less impact on the environment should be used in antifouling paint formulas.     

A Low Cost Gram Quantity Preparative Reverse Phase Chromatography System

Abstract

The preparation of a low cost reverse phase preparative liquid chromatography system is described. The described system is capable of providing gram quantity scale-up from analytical reverse phase hplc systems. Load capacity is in the two gram range.     

Dynamics of a FitzHugh-Nagumo system subjected to autocorrelated noise

We analyze the dynamics of the FitzHugh-Nagumo (FHN) model in the presence of colored noise and a periodic signal. Two cases are considered: (i) the dynamics of the membrane potential is affected by the noise, (ii) the slow dynamics of the recovery variable is subject to noise. We investigate the role of the colored noise on the neuron dynamics by the mean response time (MRT) of the neuron. We find meaningful modifications of the resonant activation (RA) and noise enhanced stability (NES) phenomena due to the correlation time of the noise. For strongly correlated noise we observe suppression of NES effect and persistence of RA phenomenon, with an efficiency enhancement of the neuronal response. Finally we show that the self-correlation of the colored noise causes a reduction of the effective noise intensity, which appears as a rescaling of the fluctuations affecting the FHN system.