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Novel large scale brain network models for EEG epileptic pattern generations
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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.

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Publication Date
Mon May 02 2022
Journal Name
International Journal Of Research In Social Sciences & Humanities An International Open-access Peer Reviewed Referred Journal
Identity Construction and Social Structures in Sia Figiel’s Novel Where We Once Belonged
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This article focuses on identity construction and social structures within the Sāmoan community as represented in Sia Figiel’s novel Where We Once Belonged. I argue that however the post/colonial Sāmoan identity is hybridized, the essence of the individual is still connected to Fa’a Sāmoa-the Sāmoan traditions and ways. However rapid are the colonial vicissitudes, the Sāmoan literature and lifestyle are developed to be a resistance platform. This resistance platform is dedicated not only to expose the colonial impact but also to assist the social and political reconstruction of post/colonial Samoa. To this end, this article studies identity construction, and the challenges that women face within Sāmoan social structures.

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Publication Date
Wed Jun 13 2018
Journal Name
Rasayan Journal Of Chemistry
Novel Thermodynamic Properties of Binary Mixtures of Tetrahydrofurfuryl Alcohol wiyh some Alcohols At 298.15 K
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Publication Date
Mon Jan 01 2018
Journal Name
Rasayan Journal Of Chemistry
NOVEL THERMODYNAMIC PROPERTIES OF BINARY MIXTURES OF TETRAHYDROFURFURYL ALCOHOL WITH SOME ALCOHOLS AT 298.15 K
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Highly-charged EDTA-2Na salt as a novel draw solution in pressure-retarded Osmosis process
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Designing and Synthesising Novel Benzophenone Biscyclic Imides Comprising Drug Moity with Investigating their Antimicrobial Activity
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The present work involved designing and synthesizing of a series of new. compounds which their molecules are composed from two biologically active components namely sulfamethoxazole or β-lactam containing drugs and cyclic imides. The target new compounds were synthesized by two steps in the first one a series of six bis (N-drug phthalamic acid_4-yl) ketone (1-6) were prepared from the reaction of sulfamethoxazole or β-lactam containing drugs with benzophenone 3, 3′, 4, 4′ -tetracarboxylic dianhydride.

In the second step, compounds (1-6) were introduced in dehydration reaction via fusion process producing the target compounds bis (N-drug phthalimidyl-4-yl) ketone (7-12). The antibacterial and antifungal high

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Publication Date
Thu Aug 08 2024
Journal Name
New Materials, Compounds And Applications
MOLECULAR MODELLING AND THEORETICAL DESIGN OF NOVEL NIRMATRELVIR DERIVATIVES AS SARS-COV-2 ENTRY INHIBITORS
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The pandemic SARS-CoV-2 is highly transmittable with its proliferation among nations. This study aims to design and exploring the efficacy of novel nirmatrelvir derivatives as SARS entry inhibitors by adapting a molecular modeling approach combined with theoretical design. The study focuses on the preparation of these derivatives and understanding their effectiveness, with a special focus on their binding affinity to the S protein, which is pivotal for the virus’s access to the host cell. Considering molecular docking aspects in the scope of a study on nirmatrelvir derivatives and S protein, dynamics simulations with 25 nanoseconds of their binding are explored. The study shows that these derivatives might work as effective antivi

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Publication Date
Mon May 01 2017
Journal Name
2017 24th International Conference On Telecommunications (ict)
Load balancing by dynamic BBU-RRH mapping in a self-optimised Cloud Radio Access Network
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Estimation of Heavy Metals Contamination in the Soil of Zaafaraniya City Using the Neural Network
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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Cost of Optimum Design of Trunk Mains Network Using Geographical Information System and Support Programs
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Sewer network is one of the important utilities in modern cities which discharge the sewage from all facilities. The increase of population numbers consequently leads to the increase in water consumption; hence waste water generation. Sewer networks work is very expensive and need to be designed accurately. Thus construction effective sewer network system with minimum cost is very necessary to handle waste water generation.

 In this study trunk mains networks design was applied which connect the pump stations together by underground pipes for too long distances. They usually have large diameters with varying depths which consequently need excavations and gathering from pump stations and transport the sewage

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