Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different lobes from both hemispheres (left and right). The network nodes of these models were simulated based on the local dynamics of the S-J 2D model, which were generated by adjusting the global coupling between the excitatory and inhibitory populations. The connection strength between the inhibitory and excitatory neurons of the local model was also adjusted to investigate different morphology patterns. Results: The proposed network models were developed and evaluated by simulations. Different abnormal patterns of EEG brain activities such as HFO S ripples on spikes, spikes, continuous spikes, sporadic spikes and ploy2 spikes ranging from 94 to 144 Hz were regenerated. Different morphology patterns of abnormality were generated from novel BNMs and the epileptiform abnormal pattern obtained in actual EEG and other computational models were also compared. Significant: This study is able to assist researchers and clinical doctors in the field of epilepsy to better understand the complex neural mechanisms behind the abnormal oscillatory activities, which may lead to the discovery of new clinical interventions in epilepsy.
Background; Neonatal period is a very vulnerable period of life due to many problems, In spite of advances in perinatal and neonatal care still, the mortality rate of neonate high especially in developing country The World Health Organization estimates that globally four million neonatal deaths per year, Developing countries account for around 99% of the neonatal mortality in the world, In Iraq. Neonatal mortality rate about 19 per 1000 live births which represent 56% of child death below 5 years age in 2012. .
Objectives The aims of the study were to determine the institutional new-born case fatality rate and the cause of admission and death in the neonatal care unit.
Method; Across-section study was carried out of the Neonatal Ca
Various methods are utilized providing complexity for cryptosystem with the aim to increase the security and avoiding hacker attack. Hybrid cryptosystem is one of these cryptosystems which is used two types of cryptosystems and has many applications in data transmitted. This research, proposed a novel method that used power exponent instead of using the prime number directly and also providing complexity of asymmetric cryptosystems. This method has been applied theoretically in two public systems RSA and EL-Gamal. Power RSA and Power EL-Gamal are modified asymmetric cryptosystems, in which the power number is kept by the sender and the receiver. Moreover, we use group theory to prove that these cryptosystems work properly. Our exten
... Show MoreA new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte
... Show MoreLinear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.
In this paper we have been focus for the comparison between three forms for classification data belongs
... Show MoreModern French novel has gained a distinctive status in the history of French literature during the first half of the twentieth century. This is due to many factors including the new literary descriptive objective style adopted by novelists like Alain Robbe – Grillet that has long been regarded as the outstanding writer of the nouveau roman, as well as its major spokesman, a representative writer and a leading theoretician of the new novel that has broken the classical rules of the one hero and evolved, through questioning the relationship of man and the world and reevaluating the limits of contemporary fiction , into creating a new form of narrative.
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... Show MoreDelivering therapeutic agents to the brain remains a major challenge due to the restrictive nature of the blood–brain barrier (BBB). Intranasal administration has emerged as a promising, non-invasive approach that bypasses the BBB and facilitates direct nose-to-brain transport via the olfactory and trigeminal pathways. In this study, we developed a nanostructured lipid carrier (NLC) system for the intranasal delivery of dolutegravir sodium, a potent integrase inhibitor, with the goal of enhancing brain bioavailability for the treatment of neuroHIV and related central nervous system (CNS) complications. The NLCs were optimized for particle size, polydispersity index (PDI), and drug incorporation efficiency. The optimized formulation exhibi
... Show MoreMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
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