Corona virus sickness has become a big public health issue in 2019. Because of its contact-transparent characteristics, it is rapidly spreading. The use of a face mask is among the most efficient methods for preventing the transmission of the Covid-19 virus. Wearing the face mask alone can cut the chance of catching the virus by over 70\%. Consequently, World Health Organization (WHO) advised wearing masks in crowded places as precautionary measures. Because of the incorrect use of facial masks, illnesses have spread rapidly in some locations. To solve this challenge, we needed a reliable mask monitoring system. Numerous government entities are attempting to make wearing a face mask mandatory; this process can be facilitated by using face m

This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi

The antiviral activity of leaf extracts from Datura stramonium and tomato plants inoculated with TMV, combined with 20% skimmed milk, was investigated. A TMV isolate was confirmed using bioassay, serological, and molecular approaches and subsequently used to inoculate plants. Tomato plants, both pre- and post-inoculated with TMV, were sprayed with leaf extracts from either TMV-free or infected plants, alone or mixed with 20% skimmed milk. Enzyme-linked immunosorbent assay (ELISA) using tobamovirus-specific antibodies and local lesion tests were conducted to assess antiviral activity based on virus concentration and infectivity in treated plants. The experiment followed a completely randomized design (CRD), and the Least Significant

INTRODUCTION: A range of tools and technologies are at disposal for the purpose of defect detection. These include but are not limited to sensors, Statistical Process Control (SPC) software, Artificial Intelligence (AI) and machine learning (ML) algorithms, X-ray systems, ultrasound systems, and eddy current systems. OBJECTIVES: The determination of the suitable instrument or combination of instruments is contingent upon the precise production procedure and the category of flaw being identified. In certain cases, defects may necessitate real-time monitoring and analysis through the use of sensors and SPC software, whereas more comprehensive analysis may be required for other defects through the utilization of X-ray or ultrasound sy

Two experiments were carried out, the first at the College of Agriculture - University of Baghdad during spring season 2017 Everest cv. class (Elite) was used to study the effect of foliar application of calcium and magnesium and addition of humic acid to the soil on potato growth and yield, The layout of the experiment was factorial within RCBD design using three replicates. Calcium and Magnesium sprayed with concentrations (0, 500, 1000 mg.L-1), while the  humic acid was added to the soil with (0, 0.75 gm.m2),  The second experiment included  storage of tubers produced from the spring season, with to study the effect of field treatments  on improving the storability of the tubers. The results showed that the treatment of calci