Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

This study proposes a new method for designing adaptive routing algorithms for three‐dimensional (3D) networks‐on‐chip (NoCs). This method is based on extending the existing 2D turn model adaptive routing to a 3D scenario. A 3D plane‐balanced approach with maximal degree of adaptiveness is achieved by applying a well‐defined set of rules for different strata of the 3D NoC. The proposed method is applicable to any of the turn models. In this study, the authors employ odd–even turn model as a basis for introducing the proposed strategy. Experimental results show that the new 3D odd–even turn model can achieve up to 28.5% improvement in performance over conventional 3D odd–even approach. The improvement is consistent fo

The fouling depositions of crude oil stream were studied theoretically in a shell and tube heat exchanger to investigate the effect of depositions on the heat transfer process. The employed heat exchanger was with steam flowing in the inner tubes and crude oil in the shell at different velocities and bulk temperatures. It is assumed that fouling occurs only on the heated stream side (crude oil). The analysis was carried out for turbulent flow heat transfer conditions with wide range of Reynolds number, bulk temperature and time. Many previously proposed models for fouling resistance were employed to estimate a new model for fouling rate. It is found that the fouling rate and consequently the heat transfer coefficient were affected by Rey

Heat shock protein 70 (HSP70) is a crucial protein with vital biological tasks in cell continuation of life. The variation of HSP70 activation occurs as a consequence of stress that includes temperature states, toxicity, poisoning with heavy metals, and tumor-related conditions. One of the master jobs of the HSP family is the suppression of caspase-mediated apoptosis signals. A high level of the expression of HSP70 is accountable for tumorigenesis and resistance against chemotherapeutic drugs. For this reason, the detection of HSP70 may help to diagnose cancerous diseases. From the other side, targeting this chaperone might help in treatment by maintaining late caspase-dependent events. This study was conducted to detect the presenc

The present research focuses on the study of the effect of mass transfer resistance on the rate of heat transfer in pool boiling. The nucleate pool boiling heat transfer coefficients for binary mixtures (ethanol-n-butanol, acetone-n-butanol, acetone-ethanol, hexane-benzene, hexane-heptane, and methanol-water) were measured at different concentrations of the more volatile components. The systems chosen covered a wide range of mixture behaviors.

The experimental set up for the present investigation includes electric heating element submerged in the test liquid mounted vertically. Thermocouple and a digital indictor measured the temperature of the heater surface. The actual heat transfer rate being obtained by multiplying the voltme

This research was conducted to measure the safety of heat stable enterotoxin a (STa) produced by enterotoxigenic Escherichia coli, through studying its toxic effect on human blood lymphocyte, since it showed a promising effect in reducing the proliferation of colorectal cancer cells. the cytogenetic effects of (STa) by using five different concentrations (100, 200, 400, 800 and 1600μg/ml) in comparison with negative (PBS, Phosphate buffer saline) and positive (MMC, Mitomycin C) at concentration of 5μg/ml, controls on human blood lymphocytes obtained from both (10) normal healthy persons and (20) colorectal cancer patients was measured by employing the following parameters: mitotic index, blast index, chromosomal aberrations and micronucle

The influence of adding metal foam fins on the heat transfer characteristics of an air to water double pipe heat exchanger is numerically investigated. The hot fluid is water which flows in the inner cylinder whereas the cold fluid is air which circulates in the annular gap in parallel flow with water. Ten fins of metal foam (Porosity = 0.93), are added in the gap between the two cylinder, and distributed periodically with the axial distance. Finite volume method is used to solve the governing equations in porous and non-porous regions. The numerical investigations cover three values for Reynolds number (1000 ,1500, 2000), and Darcy number (1 x10^-1, 1 x10^-2, 1x10^-3). The comparison betwee