Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

As they include both nucleophilic and electrophilic moieties on the same skeleton, enaminones are an important subclass of chemical compounds that contain conjugated NC=CC=O fragments. These active sites aid in the production of organic molecules containing linear or cyclic heteroatoms. Enaminones and the chemica1 compounds produced from them are both biologically active against the most dangerous bacteria. As a result, they have been utilized as starting materials for the synthesis of anti-inf1ammatory, antibacteria1, anticonvulsant, anticancer, anti-urease, anti-malaria1, optically luminescent, corrosion inhibition, and antitumor agents. Their synthesis has usually a terrific deal of interest and a plethora of synthetic paths have been na

Isatin is a heterocyclic molecule that belongs to one of the most important classes of organic compounds known as indolines. Isatin, isatin analogs, and their Schiff bases have recently attracted a lot of attention in medicinal chemistry. Isatin, itself, shows various biological activities such as antiviral, anticancer, antimicrobial, anti-inflammatory, analgesic, antioxidant, and anticonvulsant. Bis- Schiff bases containing isatin moiety have been known to possess a wide spectrum of pharmacological activities. This review offers up-to-date information on the most active isatin bis-Schiff bases, which would include anticancer, antimicrobial, antiviral, anticonvulsant, anti-inflammatory, and analgesic activities. These observations c

Isatin is a heterocyclic molecule that belongs to one of the most important classes of organic compounds known as indolines. Isatin, isatin analogs, and their Schiff bases have recently attracted a lot of attention in medicinal chemistry. Isatin, itself, shows various biological activities such as antiviral, anticancer, antimicrobial, anti-inflammatory, analgesic, antioxidant, and anticonvulsant. Bis- Schiff bases containing isatin moiety have been known to possess a wide spectrum of pharmacological activities. This review offers up-to-date information on the most active isatin bis-Schiff bases, which would include anticancer, antimicrobial, antiviral, anticonvulsant, anti-inflammatory, and analgesic activities. These observations c

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip