The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which can be quantified as a biomarker. The objective of the study reported in this paper is to develop robust EEG-based biomarkers for detecting AD in its early stages. We present a new approach to quantify the slowing of the EEG, one of the most consistent features at different stages of dementia, based on changes in the EEG amplitudes (ΔEEG A ). The new approach has sensitivity and specificity values of 100% and 88.88%, respectively, and outperformed the Lempel-Ziv Complexity (LZC) approach in discriminating between AD and normal subjects.
Various semantic innovations and expansions have been tackled as factors and sources of neos. A variety of internal (linguistic) and external (extra-linguistic) motives and motifs leads to the appearance of new terms causing such changes in the political language. Some statesmen are productive in introducing new terms and creative in manipulating expressions and meanings.
New words are nonces that get metaphorical expansion for quadrilateral motivations resting on extra meaning innovation, new terms at the semantic expansions to be honed as neos. In tracing the phases of the semantic processes of neos and hulks, lexical and semantic changes might be of widening or narrowing of refe
... Show MoreThis paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance
... Show MoreStroke is the second largest cause of death worldwide and one of the most common causes of disability. However, several approaches have been proposed to deal with stroke patient rehabilitation like robotic devices and virtual reality systems, researchers have found that the brain-computer interfaces (BCI) approaches can provide better results. In this study, the electroencephalography (EEG) dataset from post-stroke patients were investigated to identify the effects of the motor imagery (MI)-based BCI therapy by investigating sensorimotor areas using frequency and time-domain features and to select particular methods that help in enhancing the MI-based BCI systems for stroke patients using EEG signal processing. Therefore, to detect
... Show MoreClimate change is a global environmental issue and a common concern for humanity, and it is an inevitable result of civilization development, especially after the industrial revolution All areas of life At the level of the Iraqi situation , Iraq faces several challenges posed by Climate change , Such as high temperature, lack of rain, water scarcity , land salinity , and the increase in the proportion of sand and dust storms and the resulting disasters, which impedes development and hinders efforts to reduce poverty , enhance livelihoods , and reduce conflict to obtain natural resources.
... Show MoreBackground : It has been suggested that pretreatment with a statin agent prior to
myocardial infarction limits myocardial
creatine kinase release, and thus may act to
limit myocardial infarct size in humans.
Objective : To examine the effect of very
early statin initiation for acute myocardial
infarction (AMI), to the extent of
myonecrosis as manifested by peak serum
creatine kinase levels.
Methods : Patients with AMI admitted to AlKindy teaching hospital cardiac care unit
from 1st February 2007 to 28th February
2008, who fulfilled the inclusion criteria
cited in the present study, were randomly
assigned into two study groups. The statin
group patients have received a single oral
dose of 40 mg
Shumblan (SH) is one of the most undesirable aquatic plants widespread in the irrigation channels and water bodies. This work focuses on boosting the biogas potential of shumblan by co-digesting it with other types of wastes without employing any chemical or thermal pretreatments as done in previous studies. A maximum biogas recovery of 378 ml/g VS was reached using shumblan with cow manure as inoculum in a ratio of 1:1. The methane content of the biogas was 55%. Based on volatile solid (VS) and C/N ratios, biogas productions of 518, 434, and 580 ml/g VS were obtained when the shumblan was co-digested with food wastes (SH:F), paper wastes (SH:P), and green wastes (SH:G) respectively. No significant changes of methane contents were observ
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