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.
Non-biodegradability of rubber tires contributes to pollution and fire hazards in the natural environment. In this study, the flexural behavior of the Rubberized Reactive Powder Concrete (RRPC) beams that contained various proportions and sizes of scrap tire rubber was investigated and compared to the flexural behavior of the regular RPC. Fresh properties, hardened properties, load-deflection relation, first crack load, ultimate load, and crack width are studied and analyzed. Mixes were made using micro steel fiber of the straight type, and they had an aspect ratio of 65. Thirteen beams were tested under two loading points (Repeated loading) with small-scale beams (1100 mm, 150 mm, 100 mm) size.
The fine aggregate
... Show Morein this paper, the current work was devoted to the manufacture of TiO2 nanoparticles doped with manganese, synthesis by the sol-gel technique using a dip-conting device, for their hydrophilic properties and photocatalytic activity, and the products were characterized by X-ray diffraction, scanning electron microscopy, and Uv-Visible absorption, and the results XRD showed an phase Anatase , and the results of the SEM Explained the shape of the morphology of the samples after the doping process compared with pure TiO2, and the results of a shift in light absorption from ultraviolet rays to visible light were evident. The results showed that the thin films have a high wettability under visible rays
... Show MoreTiO2 thin films were deposited by reactive d.c magnetron sputtering method on a glass substrate with various ratio of gas flow (Oxygen /Argon) (50/50, 100/50 and 150/50) at substrate temperature 573K. It can be observe that the optical energy gap of TiO2 thin films dependent on the ratio of gas flow (oxygen/argon), it varies between (3.45eV-3.57eV) also it is seen that the optical constants (α, n, K, εr and εi ) has been varied with the change of the ratio of gas flow (Oxygen /Argon).
The gypseous soil may be one of the problems that face the engineers especially when it used as a foundation for hydraulic structures, roads, and other structures. Gypseous soil is strong soil and has good properties when it is dry, but the problem arises when building hydraulic installations or heavy buildings on this soil after wetting the water to the soil by raising the water table level from any source or from rainfall which leads to dissolve the gypsum content. Cement-stabilized soil has been successfully used as a facing or lining for earth channel, highway embankments and drainage ditches to reduce the risk of erosion and collapsibility of soil. This study is deliberate the treatment of gypseous soil by using a mixture
... Show MoreFour simply supported reinforced concrete (RC) beams were test experimentaly and analyzed using the extended finite element method (XFEM). This method is used to treat the discontinuities resulting from the fracture process and crack propagation in that occur in concrete. The Meso-Scale Approach (MSA) used to model concrete as a heterogenous material consists of a three-phasic material (coarse aggregate, mortar, and air voids in the cement paste). The coarse aggregate that was used in the casting of these beams rounded and crashed aggregate shape with maximum size of 20 mm. The compressive strength used in these beams is equal to 17 MPa and 34 MPa, respectively. These RC beams are designed to fail due to flexure when subjected to lo
... Show More(Sb2S3)1-xSnx thin films with different concentrations (0, 0.05 and
0.15) and thicknesses (300,500 and 700nm) have been deposited by
single source vacuum thermal evaporation onto glass substrates at
ambient temperature to study the effect of tin content, thickness and
on its structural morphology, and electrical properties. AFM study
revealed that microstructure parameters such as crystallite size, and
roughness found to depend upon deposition conditions. The DC
conductivity of the vacuum evaporated (Sb2S3)1-x Snx thin films was
measured in the temperature range (293-473)K and was found to
increase on order of magnitude with
Flexure members such as reinforced concrete (RC) simply supported beams subjected to two-point loading were analyzed numerically. The Extended Finite Element Method (XFEM) was employed for the treatment the non-smooth h behaviour such as discontinuities and singularities. This method is a powerful technique used for the analysis of the fracture process and crack propagation in concrete. Concrete is a heterogeneous material that consists of coarse aggregate, cement mortar and air voids distributed in the cement paste. Numerical modeling of concrete comprises a two-scale model, using mesoscale and macroscale numerical models. The effectiveness and validity of the Meso-Scale Approach (MSA) in modeling of the reinforced concrete beams w
... Show MoreWhenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas
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