D-mannose sugar was used to prepare [benzoic acid 6-formyl-2,2-dimethyl-tetrahydrofuro[3,4-d][1,3]dioxol-4-yl ester] (compound A). The condensation reaction of folic acid with (compound A) resulted in the formation of new ligand [L]. These compounds were characterized by elemental analysis CHN, atomic absorption A.A, (FT-I.R.), (U.V.-Vis), TLC, E.S. mass (for electrospray), molar conductance, and melting point. The new tetradentate ligand [L], reacted with two moles of some selected metal ions and two moles of (2-aminophenol), (metal : ligand : 2-aminophenol) at reflux in water medium to give a series of new complexes of the general formula K2[M2(L)(HA)2] where M= Co(II), Ni(II), Cu(II) and Cd(II). These complexes were characterized by elem

Double hydrothermal method was used to prepare nano gamma alumina   using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, CTAB (cetyltrimethylammonium bromide) as surfactant, and variable acids: weak acids like; citric, and acitic acids, and strong acids like; hydrochloric and nitric acids as a bridge between aluminum salts and surfactant. Different crystallization times  12, 24, 48, and 72 hrs were applied. All the batches were prepared at pH equals to 9. XRD diffraction technique was used to investigate the crystalline nano gamma alumina pure from surfactant. N₂ adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the average p

Plumbago (Plumbaginaceae) is a genus of 10-20 species of flowering plants used in traditional Indian medicine, native to warm temperature to tropical regions of the world. The roots of Plumbago europaea, the Iraqi species of Plumbago, have been used for the treatment of cancer, rheumatoid arthritis, and dysmenorrhea. The main active constituents from dried powdered leaves and roots of Plumbago europaea were extracted by Soxhlet apparatus using ethyl acetate, the main active constituent was characterized by spectroscopic analysis (IR, ¹H NMR, and ¹³C NMR)   as plumbagin. Quantitative and qualitative study of plumbagin in the roots and leaves extracts was carried out by HP

A novel metal-organic framework (MOF) sorbent based on tannic acid/copper (TA/Cu) was synthesized and characterized for the application of the anticancer drug imatinib (IMA) from biological samples. The TA/Cu MOF was prepared via a facile coordination reaction and thoroughly characterized by SEM, XRD, and FTIR techniques. Critical parameters influencing the extraction efficiency of imatinib mesylate (IMAM), including pH, ionic strength, desorption solvent, and adsorption-desorption time were optimized. With acetonitrile as the desorption solvent, the method demonstrated a broad linear range of 0.55-300 μg L-1 under ideal conditions. Limits of detection and quantification were found to be 0.16 μg L-1 and 0.55 μg L-1, respectively.

A novel metal-organic framework (MOF) sorbent based on tannic acid/copper (TA/Cu) was synthesized and characterized for the application of the anticancer drug imatinib (IMA) from biological samples. The TA/Cu MOF was prepared via a facile coordination reaction and thoroughly characterized by SEM, XRD, and FTIR techniques. Critical parameters influencing the extraction efficiency of imatinib mesylate (IMAM), including pH, ionic strength, desorption solvent, and adsorption-desorption time were optimized. With acetonitrile as the desorption solvent, the method demonstrated a broad linear range of 0.55-300 μg L-1 under ideal conditions. Limits of detection and quantification were found to be 0.16 μg L-1 and 0.55 μg L-1, respectively.

A novel metal-organic framework (MOF) sorbent based on tannic acid/copper (TA/Cu) was synthesized and characterized for the application of the anticancer drug imatinib (IMA) from biological samples. The TA/Cu MOF was prepared via a facile coordination reaction and thoroughly characterized by SEM, XRD, and FTIR techniques. Critical parameters influencing the extraction efficiency of imatinib mesylate (IMAM), including pH, ionic strength, desorption solvent, and adsorption-desorption time were optimized. With acetonitrile as the desorption solvent, the method demonstrated a broad linear range of 0.55-300 μg L-1 under ideal conditions. Limits of detection and quantification were found to be 0.16 μg L-1 and 0.55 μg L-1, respectively.

Infection with cryptosporidiosis endangers the lives of many people with immunodeficiency, especially HIV patients. Nitazoxanide is one of the main therapeutic drugs used to treat cryptosporidiosis. However, it is poorly soluble in water, which restricts its usefulness and efficacy in immunocompromised patients. Surfactants have an amphiphilic character which indicates their ability to improve the water solubility of the hydrophobic drugs. Our research concerns the synthesis of new cationic Gemini surfactants that have the ability to improve the solubility of the drug Nanazoxide. So, we synthesized cationic Gemini surfactants. N1,N1,N3,N3-tetramethyl-N1,N3-bis(2-octadecanamidoethyl)propane-1,3-diaminium bromide (CGSPS18) and 2,2‘-(etha

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet