Sharif Digital Repository

In this study, Pseudomonas aeruginosa BBRC-10036 was used for lipase production. The organism secreted the enzyme extracellulary. First of all, effect of initial pH of the culture broth on lipase activity was studied in order to determine the optimum condition for lipase production. After production, this enzyme must be separated from culture and after that the enzyme must be purified for using in analysis and industry. Different methods are used for purification of the enzyme. In this research, first precipitation was used and then this lipase has been purified by Ion exchange Chromatography leading to 2.33- fold purification and 11.47% recovery. In precipitation by acetone, maximum... 

In this study, polyoxometalate (POM) intercalated in the layered double hydroxide (LDH) was synthesized by a selective ion-exchange method. For this purpose, the nanocluster [VW12O40]3- was immobilized on the Mg2+/A13+/Cl–LDH support. The heterogeneous catalyst was characterized by FT-IR, XRD, SEM and analysis of ICP. The LDH-POM was applied as a catalyst in efficient oxidation of sulfides to sulfoxides using UHP as oxidant and CH3OH/ CH¬2¬Cl¬2 ¬as a solvent at room temperature, as well as epoxidation of olefins using TBHP as an oxidants and C¬2H4Cl2 as a solvent in 84°C. This catalyst showed excellent catalytic activities for a substrate/catalyst ratio (200:1). For example, this catalytic... 

Epilepsy is one of the diseases that affects the quality of life of epileptic patients. Epileptic patients lose control during epileptic seizures and are more likely to face problems. Designing and creating a seizure detection system can reduce casualties from epileptic attacks. In this study, we present an automatic method that reduces the artifact from the raw signals, and then classifies the seizure and non-seizure epochs. At all stages, it is assumed that no information is available about the patient and this detection is made only based on the information of other patients. The data from this study were recorded in Temple Hospital and the recording conditions were not controlled, so... 

Time perception is a concept that describes how a person interprets the duration of an event. Depending on the circumstances, people may feel that time passes quickly or slowly. So far, the understanding, comparison, and estimation of the time interval have been described using a simple model, a pacemaker accumulator, that is powerful in explaining behavioral and biological data. Also, the role of the frequency band, Contingent Negative Variation (CNV), and Event-Related Potential (ERP) components have been investigated in the passage of time and the perception of time duration. Still, the stimuli used in these studies were not melodic. Predicting is one of the main behaviors of the brain.... 

Attention is one of the important aspects of brain cognitive activities, which has been widely discussed in psychology and neuroscience and is one of the main fields of research in the education field. The human sense of hearing is very complex, impactful and crucial in many processes such as learning. Human body always does several tasks and uses different senses simultaneously. For example, a student who listens to his/her teacher in the class, at the same time pays attention to the teacher, looks at a text or image, and sometimes writes a note.Using the electroencephalogram (EEG) signal for attention assessment and other cognitive activities is considered because of its facile recording,... 

The brain electrical signal (EEG) has been widely used in clinical and academic research, due to its ease of recording, non-invasiveness and precision. One of the applications can be emotion recognition from the brain's electrical signal. Generally, two types of parameters (Valence and Arousal) are used to determine the type of emotion, which, in turn, indicate "positive or negative" and "level of extroversion or excitement" for a specific emotion. The significance of emotion is determined by the effects of this phenomenon on daily tasks, especially in cases where the person is confronted with activities that require careful attention and concentration.In the emotion recognition problem,... 

Depression is a type of mental disorder that is characterized by the continuous occurrence of bad moods in the affected person. Studies by the World Health Organization (WHO) show that depression is the second disease that threatens human life, and eight hundred thousand people die due to suicide every year. In order to reduce the damage caused by depression, it is necessary to have an accurate method for diagnosing depression and its rapid treatment, in which electroencephalogram (EEG) signals are considered as one of the best methods for diagnosing depression. Until now, various researches have been conducted to diagnose depression using electroencephalogram signals, most of which were... 

Traditional assumptions about assessment and learning have been challenged in higher education. Alternative types of assessment have been introduced to align to the students’ learning aims. Although, the growing body of literature of alternative types of assessment such as peer-assessment and self-assessment shed light on the advantages and benefits of embedding assessment in classroom activities, there is not absolute agreement on the consistency and accuracy of these types of assessment. To this aim, this study attempted to investigate the reliability and validity of self-assessment and peer-assessment of Iranian EFL learners’ written and oral production. The data was obtained from 32... 

The field of emotion recognition is a growing area with multiple interdisciplinary applications, and processing and analyzing electroencephalogram signals (EEG) is one of its standard methods. In most articles, emotional elicitation methods for EEG signal recording involve visual-auditory stimulation; however, the use of virtual reality methods for recording signals with more realistic information is suggested. Therefore, in the present study, the VREED dataset, whose emotional elicitation is virtual reality, has been used to classify positive and negative emotions. The best classification accuracy in the VREED dataset article is 73.77% ± 2.01, achieved by combining features of relative... 

The analysis of cerebral signals, encompassing both invasive and non-invasive electroencephalogram recordings, is extensively utilized in the exploration of neural systems and the examination of neurological disorders. Empirical research has indicated that under certain conditions, such as epileptic episodes, cerebral signals exhibit frequency components exceeding 80 Hz, which are designated as high frequency oscillations. Consequently, high frequency oscillations are recognized as a promising biomarker for epilepsy and the delineation of epileptic foci. The objective of this dissertation is to evaluate the existing methodologies for the detection of high frequency oscillations and to... 

High-frequency oscillations (HFOs) in brain electrical signals are activities within the 80–500 Hz frequency range that are distinct from the baseline and include at least four oscillatory cycles. Research indicates that HFOs could serve as potential biomarkers for neurological disorders. Manual detection of HFOs is time-consuming and prone to human error, making automated HFO detection methods increasingly necessary. These automated methods typically rely on the signal's energy within the HFO frequency band. Tensor decompositions are mathematical models capable of extracting hidden information from multidimensional data. Due to the multidimensional nature of brain electrical signals, tensor... 

Nowadays, Electroencephalogram (EEG) is the most common method for brain activity measurement. Event Related Potentials (ERP) which are recorded through EEG, have many applications. Detecting ERP signals is an important task since their amplitudes are quite small compared to the background EEG. The usual way to address this problem is to repeat the process of EEG recording several times and use the average signal. Though averaging can be helpful, there is a need for more complicated filtering. Blind source separation methods are frequently used for ERP denoising. These methods don’t use prior information for extracting sources and their use is limited to 2D problems only. To address these... 

The use of brain signals in controlling devices and communication with the external environment has been very much considered recently. The Brain-Computer Interface (BCI) systems enable people to easily handle most of their daily physical activity using the brain signal, without any need for movement. One of the most common BCI systems is P300 speller. In this type of BCI systems, the user can spell words without the need for typing with hands. In these systems, the electrical potential of the user's brain signals is distorted by visual, auditory, or tactile stimuli from his/her normal state. An essential principle in these systems is to exploit appropriate feature extraction methods which... 

Among the most costly diseases that affect a person's quality of life throughout his or her life, mental disorders (excluding sleep disorders) affect up to 25 percent of people in any community. One of the most common types of these disorders in Iran is depressive disorder, which according to official statistics, 13% of Iranians have some symptoms of it. Until now, the diagnosis of this disease has been traditionally done in clinics with interviews and questionnaires tests based on behavioral psychology and using symptom assessment. Therefore, there is a relatively low accuracy in the treatment process. Nowadays, with the help of functional brain imaging such as electroencephalogram (EEG)... 

The auditory system with its unique features has been considered by researchers in the past and its various parts from the outside of the body to its internal parts have been studied. The auditory nervous system, as the most important part of the auditory system, is responsible for receiving and processing information from the ear. The auditory system has different anatomical and physiological characteristics. The result of these characteristics is processing power in the field of time and frequency, which has received more attention in this dissertation. This processing power is most evident in the central auditory nervous system. This section includes nerve neurons and synapses from the... 

The processing of brain signals, including the electrocorticogram (ECoG) signal, is widely used in the investigation of neurological diseases. Conventionally, the ECoG signal has frequency components up to the range of 80 Hz. Studies have proven that in some conditions, such as epilepsy, the brain signal includes frequency components higher than 80 Hz, which are called high-frequency oscillations (HFO). Therefore, HFOs are recognized as a biomarker for epilepsy. The aim of this thesis is to review the previous methods of detecting HFOs and to present new methods with greater efficiency in the direction of diagnosis or treatment of epileptic patients. For this purpose, we used the ECoG data... 

The Brain Computer Interface (BCI) translates brain signals into a series of commands, enabling individuals to fulfill many of their basic needs without physical activity. Electroencephalogram (EEG) signals are commonly used as input for BCI systems, because the recording of this signal is non-invasive, inexpensive, and also have an acceptable time resolution. One of the most prevalent methods in BCI systems is the brain-computer interface based on Steady State Visual Evoked Potentials (SSVEP). These systems provide high response speed and Information Transfer Rate (ITR) as well as a good signal-to-noise ratio (SNR). The main purpose of these systems is to detect the frequency of SSVEP in... 

In most of brain studies, the primary objective is to find dipole activities, an underdetermined problem that requires additional constraints. Adequate constraints can be added by using information from other modalities. This research aims to develop a platform that combines various noninvasive modalities to improve localization accuracy. To accomplish this, two novel general approaches to combining modalities are proposed. In the first approach, the result of localizing by different methods and in different modalities are processed and combined in intervals by Dempster Shaffer's combination law. The final amount of bipolar activity is obtained by cumulating the activities obtained at... 

The Oil wells are usually damaged because of the drilling process and production scenarios or fluid injection during EOR processes. These damages would critically affect the rate of production and injectivity of the well in the form of plugging damage. Different methods are used to fix these damages and increase the production flow from the oil wells. One of the most widely used well-stimulation methods to remediate this challenge is well acidizing. Although this method has very high efficiency in improving the ability of wells, if it is not designed and implemented correctly and optimally, it can cause induced damage and even lead to the well shutting. This challenge is especially reported... 

EEG brain signals have gained particular attention among researchers in the field of brain signal processing due to their easy and cheap recording, high temporal resolution, and non-invasiveness. On the other hand, defects such as high vulnerability to various types of noise and artifacts have caused the main challenge before processing them to improve the signal-to-noise ratio and the interpretability of brain connectivity obtained from them. In order to solve these challenges, two important problems of "separation of desired and undesired signal subspace" and "functional and effective connectivity analysis" have been raised, respectively. In solving both problems, EEG signals are usually...