The influence of sensing element length of no-core fiber strain sensor has been studied and experimentally demonstrated, four different lengths of 125 μm diameter no-core fiber is fused between two standard single-mode fibers and bi-directionally strained, the highest obtained sensitivity was around 16.37 pm με -1 which was exhibited in the shortest no-core fiber segment, to the best of our knowledge this is the first study of the influence of no-core fiber strain sensors length on sensor sensitivity. The proposed sensor can be used in many opto-mechanical applications such as, structural health monitoring, aerospace vehicles and airplane components monitoring.

Two grades of paving asphalt with penetration of 46 and 65 are studied for determining changes in their physical and chemical properties caused by ageing.
The ageing process has been conducted on two petroleum paving asphalt cement using thin film oven test at 150, 163 and 175 C, and ageing time 5, 10,15, 20, 25 and 30 hours. The effect of ageing time and temperature on penetration, kinematic viscosity, softening point, solubility in trichloroethylene, heat loss and changes in chemical composition are investigated. The results of thin film oven test process indicte that the asphaltenes concentration of all aged asphalt increases with increasing ageing time, while the opposite was observed for polar-aromatic and naphthene-aromatic. The

International trade in services is becoming increasingly important as it is an economic activity that deals with invisible trade, which has become increasingly important in the balance of international trade. The establishment of the WTO is a starting point in international trade relations. It is responsible for all aspects of international trade, , And in view of the continued increase in international trade in services, the need for more internationally recognized rules has become more urgent, especially as it has been increasingly proven that the traditional framework of public services is inadequate to operate some of the most dynamic and innovative sectors of the economy. (GATS) to be the regulatory framework for this sector

Green synthesis of silver nanoparticles (AgNPs) using different plant parts has shown a great potential in medicinal and industrial applications. In this study, AgNPs were in vitro green synthesized using A. graecorum, and its antifungal and antitumoractivities were investigated. Scanning electron microscopy (SEM) image result indicated spherical shape of AgNPs with a size range of 22-36 nm indicated by using Image J program. The functional groups indicated by Fourier-transform infrared spectroscopy (FTIR) represented the groups involved in the reduction of silver ion into nanoparticles. Alhagi graecorum AgNPs inhibited MCF-7 breast cancer cell line growth in increased concentration depend manner, significant differences shown at

The article discusses the spatial analysis of the chemical soil properties that is a key component of the agriculture ecosystem based on satellite images. The main objective of the present study is to measure the chemical soil properties (total dissolved salts (TDS), Electrical conductivity (EC), PH, and) and the ​spatial variability. On 13 November 2020 (wet season), a total of 12 soil samples were collected in the field through random sampling in the Sanam mountain-Al Zubair region south of Basra province, to contain its soil samples components of minerals and precious elements such as silica and sulfur. From experimental results, the soil sample in the sixth position has the highest concentration of TDS values, reached (5798.4

Spelling correction is considered a challenging task for resource-scarce languages. The Arabic language is one of these resource-scarce languages, which suffers from the absence of a large spelling correction dataset, thus datasets injected with artificial errors are used to overcome this problem. In this paper, we trained the Text-to-Text Transfer Transformer (T5) model using artificial errors to correct Arabic soft spelling mistakes. Our T5 model can correct 97.8% of the artificial errors that were injected into the test set. Additionally, our T5 model achieves a character error rate (CER) of 0.77% on a set that contains real soft spelling mistakes. We achieved these results using a 4-layer T5 model trained with a 90% error inject