The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

A simple, fast, selective of a new flow injection analysis method coupled with potentiometric detection was used to determine vitamin B1 in pharmaceutical formulations via the prepared new selective membranes. Two electrodes were constructed for the determination of vitamin B1 based on the ion-pair vitamin B1-phosphotungestic acid (B1-PTA) in a poly (vinyl chloride) supported with a plasticized di-butyl phthalate (DBPH) and di-butyl phosphate (DBP). Applications of these ion selective electrodes for the determination of vitamin B1 in the pharmaceutical preparations for batch and flow injection systems were described. The ion selective membrane exhibited a near-Nernstian slope values 56.88 and 58.53 mV / decade, with the linear dy

This paper presents an enhancement technique for tracking and regulating the blood glucose level for diabetic patients using an intelligent auto-tuning Proportional-Integral-Derivative PID controller. The proposed controller aims to generate the best insulin control action responsible for regulating the blood glucose level precisely, accurately, and quickly. The tuning control algorithm used the Dolphin Echolocation Optimization (DEO) algorithm for obtaining the near-optimal PID controller parameters with a proposed time domain specification performance index. The MATLAB simulation results for three different patients showed that the effectiveness and the robustness of the proposed control algorithm in terms of fast gene

Background: Cystinosis is a rare autosomal recessive lysosomal storage disease with high morbidity and mortality. It is caused by mutations in the CTNS gene that encodes the cystine transporter, cystinosin, which leads to lysosomal cystine accumulation. It is the major cause of inherited Fanconi syndrome, and should be suspected in young children with failure to thrive and signs of renal proximal tubular damage. The diagnosis can be missed in infants, because not all signs of renal Fanconi syndrome are present during the first months of life. Elevated white blood cell cystine content is the cornerstone of the diagnosis. Since chitotriosidase (CHIT1 or chitinase-1) is mainly produced by activated macrophages both in normal and inflammator

The performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to resul

The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ

The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

       Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty

Separation of Trigonelline, the major alkaloid in fenugreek seeds, is difficult because the extract of these seeds usually contains Trigonelline, choline, mucilage, and steroidal saponins, in addition to some other substances. This study amis to isolate the quaternary ammonium alkaloid (Trigonelline) and choline from fenugreek seeds (Trigonella-foenum graecum L.) which have similar physiochemical properties by modifying of the classical method. Seeds were defatted and then extracted with methanol. The presence of alkaloids was detected by using Mayer's and Dragendorff's reagents. In this work, trigonilline was isolated with traces of choline by subsequent processes of purification using analytical and preparative TLC techniques.