Sharif Digital Repository

Many studies in the field of sleep have focused on connectivity and coherence. Still, the nonstationary nature of electroencephalography (EEG) makes many of the previous methods unsuitable for automatic sleep detection. Time-frequency representations and high-order spectra are applied to nonstationary signal analysis and nonlinearity investigation, respectively. Therefore, combining wavelet and bispectrum, wavelet-based bi-phase (Wbiph) was proposed and used as a novel feature for sleep-wake classification. The results of the statistical analysis with emphasis on the importance of the gamma rhythm in sleep detection show that the Wbiph is more potent than coherence in the wake-sleep... 

Several researches have been done to identify visual system characteristics. Some of them are based on the processing of the brain signal recordings. Visual evoked potentials (VEPs) are electrical signals which are produced in response to the visual stimuli and recorded by means of electrodes placed on the head. These signals are usually characterized by the amplitude and latency of their peaks. Different types of visual stimuli and visual system characteristics can affect the shape and hence the characteristics of VEPs. In this paper, proper visual stimuli were used and VEPs were recorded in order to classify visual acuity. To achieve this goal, visual evoked potentials were recorded and... 

Resection of the epilepsy foci is the best treatment for more than 15% of epileptic patients or 50% of patients who are refractory to all forms of medical treatment. Accurate mapping of the locations of epileptic neuronal networks can result in the complete resection of epileptic foci. Even though currently electroencephalography is the best technique for mapping the epileptic focus, it cannot define the boundary of epilepsy that accurately. Herein we put forward a new accurate brain mapping technique using superparamagnetic nanoparticles (SPMNs). The main hypothesis in this new approach is the creation of super-paramagnetic aggregates in the epileptic foci due to high electrical and... 

This study develops a photosynthetic microalgae microbial fuel cell (PMMFC) engaged Chlorella vulgaris microalgae to investigate effect of light intensities and illumination regimes on simultaneous production of bioelectricity, biomass and wastewater treatment. The performance of the system under different light intensity (3500, 5000, 7000 and 10,000 lx) and light/dark regimes (24/00, 12/12, 16/8 h) was investigated. The optimum light intensity and light/dark regimes for achieving maximum yield of PMMFC were obtained. The maximum power density of 126 mW m−3, the coulombic efficiency of 78% and COD removal of 5.47% were achieved. The maximum biomass concentration of 4 g l−1 (or biomass yield... 

Recently graph theory and complex networks have been widely used as a mean to model functionality of the brain. Among different neuroimaging techniques available for constructing the brain functional networks, electroencephalography (EEG) with its high temporal resolution is a useful instrument of the analysis of functional interdependencies between different brain regions. Alzheimer's disease (AD) is a neurodegenerative disease, which leads to substantial cognitive decline, and eventually, dementia in aged people. To achieve a deeper insight into the behavior of functional cerebral networks in AD, here we study their synchronizability in 17 newly diagnosed AD patients compared to 17 healthy... 

Effect of cathodic enzymatic decolorization of reactive blue 221 (RB221) on the performance of a dual-chamber microbial fuel cell (MFC) was investigated. Immobilized laccase on the surface of a modified graphite electrode was used in the cathode compartment in order to decolorize the azo dye and enhance the oxygen reduction reaction. First, methylene blue which is an electroactive polymer was electropolymerized on the surface of a graphite bar to prepare the modified electrode. Utilization of the modified electrode with no enzyme in the MFC increased the power density up to 57% due to the reduction of internal resistance from 1000 to 750 Ω. Using the electropolymerized-enzymatic cathode... 

Regression analysis of real-world data has not always been an easy task, especially when input vectors are presented in a very low dimensional space. EEG-based fatigue detection deals with low dimensional problems and plays a major role in reducing the risk of fatal accidents. We propose a kernel projection pursuit regression algorithm which is a two-step nonlinearity encoding algorithm tailored for such low dimensional problems such as fatigue detection. In this way, data nonlinearity can be investigated from two different perspectives: by first transforming the data into a high dimensional intermediate space and then, applying their spline estimations to the output variables allowing for... 

Human mind from system perspective deals with high dimensional complex world as an adaptive Multi-Input Multi-Output complex system. This view is theorized by reductionism theory in philosophy of mind, where the world is represented as logical combination of simpler sub-systems for human so that operate with less energy. On the other hand, Human usually uses linguistic rules to describe and manipulate his expert knowledge about the world; the way that is well modeled by Fuzzy Logic. But how such a symbolic form of knowledge can be encoded and stored in plausible neural circuitry? Based on mentioned postulates, we have proposed an adaptive Neuro-Fuzzy machine in order to model a rule-based... 

Objective(s): Seizure detection during online recording of electrophysiological parameters is very important in epileptic patients. In the present study, online analysis of field potential recordings was used for detecting spontaneous seizures in epileptic animals. Materials and Methods: Epilepsy was induced in rats by pilocarpine injection. During the chronic period of the pilocarpine model, local field potential (LFP) recording was run for at least 24 hr. At the same time, video monitoring of the animals was done to determine the real time of seizure occurrence. Both power and sample entropy of LFP were used for online analysis. Results: Obtained results showed that changes in LFP power... 

Anaerobic digestion processes and the conductive electron transfer approach were used to describe the bioenergy production processes in a microbial fuel cell (MFC), respectively. The present model is a far more completed form of conduction-based modeling which is able to predict performance of an MFC fed with complex substrates and inoculated with multi-population culture. One-dimensional spatial distributions of the different microorganisms, as biocatalysts of processes and intermediates produced in the different steps of the anaerobic digestion processes in the biofilm, as well as the dynamic behavior of the anolyte including syntropic interactions among different groups of microorganisms... 

Denoising is an important preprocessing stage in some Electroencephalography (EEG) applications such as epileptic source localization. In this paper, we propose a new algorithm for denoising the interictal EEG data. The proposed algorithm is based on Generalized Eigenvalue Decomposition of two covariance matrices of the observations. Since one of these matrices is related to the spike durations, we should estimate the occurrence time of the spike peaks and the exact spike durations. To this end, we propose a spike detection algorithm which is based on the available spike detection methods. The comparison of the results of the proposed algorithm with the results of two well-known ICA... 

Exploiting of the nanostructure arrays as a promising candidate for excitation of neural cells has been analyzed. Based on the importance of the coupling effect between electrode and neuron, a multiphyscis modeling approach has been proposed. The model incorporates theoretically both structural effects (size, geometry) and electrophysiological effects. The system of equations for proposed model has been solved numerically using Finite Element Method for Poisson equation and Finite Difference Method for Cable equation. In this regards we have combined the system of equations in COMSOL platform with Matlab interface accordingly. We have analyzed the effect of excitation of neuron with an extra... 

Temporal synchronization of neuronal activity plays an important role in various brain functions such as binding, cognition, information processing, and computation. Patients suffering from disorders such as Alzheimer’s disease or schizophrenia show abnormality in the synchronization patterns. Electroencephalography (EEG) is a cheap, non-invasive, and easy-to-use method with fine temporal resolution. Modern multichannel EEG data are increasingly being used in brain studies. Traditional approaches for identifying synchronous activity in EEG are through univariate techniques such as power spectral density or bivariate techniques such as coherence. In this paper, we review two methods for... 

The objective of present study is to analyze the dynamic modeling of bioelectrochemical processes and improvement of the performance of previous models using quantitative data of bacterial transport parameters. The main deficiency of previous MFC models concerning spatial distribution of biocatalysts is an assumption of initial distribution of attached/suspended bacteria on electrode or in anolyte bulk which is the foundation for biofilm formation. In order to modify this imperfection, the quantification of chemotactic motility to understand the mechanisms of the suspended microorganisms’ distribution in anolyte and/or their attachment to anode surface to extend the biofilm is implemented... 

In addition to its biological importance, DPhPC lipid bilayers are widely used in droplet bilayers, study of integral membrane proteins, drug delivery systems as well as patch-clamp electrophysiology of ion channels, yet their mechanical properties are not fully measured. Herein, we examined the effect of the ether linkage on the mechanical properties of ester- and ether-DPhPC lipid bilayers using all-atom molecular dynamics simulation. The values of area per lipid, thickness, intrinsic lateral pressure profile, order parameter, and elasticity moduli were estimated using various computational frameworks and were compared with available experimental values. Overall, a good agreement was... 

Brain Computer Interface provides a new communication channel for people who have severe brain injuries. Among different types of BCIs, SSVEP-based one has been focused in recent years. In this type of BCI, selection of twinkling frequency of external visual stimulant and the distance between stimulants (in case of more than one stimulant) is so important. In this work, a SSVEP-based BCI with two external stimulants was designed. In order to determine the best twinkling frequency of stimulants and the best distance between them, the classification accuracy for seven different twinkling frequency pairs and five different stimulants distances was calculated. Two methods for feature extraction... 

Increasing the number of car accidents and other cerebral disease cause to progress in using Brain-Compute Interface (BCI) as a common subject for research and treatment. The aim of Brain-Computer Interface system is to establish a new communication system that translates human intentions, reflected by brain signals, into a control signal for an output device such as a computer. To this end, different processes must be done on brain signals and these signals must be classified by suitable methods. There are various methods to classify ECoG signals which are different in features and classifiers. Used features depend on extracted features, feature reduction methods and measures of feature... 

The activity generated in the brain in response to external stimulations which is named the evoked potential (EP) is typically buried in the background EEG. Because of the low signal to noise ratio ofEPs, it is difficult to record single trial evoked potentials. The traditional technique which is based on ensemble averaging destroys the dynamic information of single trials. In this paper, a new method has been proposed based on generalized eigen value decomposition to extract single trial EPs from single channel EEG recordings. The extraction of the N75-P100-N135 complex in simulated and actual visual evoked potentials is mainly taken under consideration. To illustrate the effectiveness of... 

Ethylene glycol is an environmental pollutant, which exists in airport runoff and industrial waste. In this article, biodegradation of ethylene glycol in a two-chamber, batch-mode microbial fuel cell was investigated. Glucose and ethylene glycol at different concentrations were used as carbon and energy sources. Chemical oxygen demand removal in the range of 92-98% indicated that microbial fuel cell can be used for biodegradation of ethylene glycol. Ethylene glycol also improved power generation and the maximum power density was 5.72 mW/m2 (137.32 mW/m3), with respect to the same glucose and ethylene glycol concentrations (500 ppm)  

While energy consumption is increasing worldwide due to population growth, the fossil fuels are unstable and exhaustible resources for establishing sustainable life. Using biodegradable compounds present in the wastewater produced in industrial process as a renewable source is an enchanting approach followed by scientists for maintaining a sustainable energy production to vanquish this problem for ulterior generations. In this research, bioelectricity generation with whey degradation was investigated in a two-chamber microbial fuel cell with humic acid as anodic electron mediator and a cathode compartment including combinational electron acceptor. Escherichia coli was able to use the...