Background: Worldwide gastric cancer is the fifth most common cancer with poor prognosis. In early stages, it is hard to distinguish gastric cancer from benign gastric diseases, resulting in delayed diagnosis. There is a need to develop a biomarker for differentiating between gastric cancer and benign gastric diseases. Serum cholinesterase is synthesized in liver and released into plasma, and it has an important role in oncogenesis.

Objectives: To determine the correlation between serum cholinesterase activity and gastric cancer, in comparison to benign gastric diseases.

Subjects and Methods: A case control study carried out at Medical City Direct

The study aims to find out the effectiveness of using the Google classroom educational platform in teaching mathematics curricula from the viewpoint of teachers in the Governorate of Al Dhahirah, Sultanate of Oman. The researcher adopted the descriptive-analytical approach. To collect the needed data, a questionnaire of two dimensions was used. It includes (13) items to measure the effectiveness of using the Google classroom in teaching mathematics curricula from the teacher's point of view and includes (10) items to measure the difficulties of using the Google classroom in teaching mathematics curricula from the teachers' point of view. These tools were applied to (32) male and (31) female as the study sample. They represent mathematics

Fiber Bragg Grating has many advantages where it can be used as a temperature sensor, pressure sensor or even as a refractive index sensor. Designing each of this fiber Bragg grating sensors should include some requirements. Fiber Bragg grating refractive index sensor is a very important application. In order to increase the sensing ability of fiber Bragg gratings, many methods were followed. In our proposed work, the fiber Bragg grating was written in a D-shaped optical fiber by using a phase mask method with KrFexcimer. The resultant fiber Bragg grating has a high reflectivity 99.99% with a Bragg wavelength of 1551.2 nm as a best result obtained from a phase mask with a grating period of 1057 nm. In this work it was found that the rota

When a vehicle is left parked in the sun for an extended period, the gathered heat causes damage to several interiors within the cabin and causes discomfort for people and animals left inside the car. In the present work, the effect of the orientation of a parked white minibus on temperature distribution and cooling load calculation is studied experimentally in an open environment. Two different cases were studied facing south and facing east. For several hours, the temperature inside the car cabin had been monitored and measured at five separate locations. The cooling load calculations are carried out based on the experimental measurements. The results show that the overheating of parked cars always happens as a result

In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i