In the present study, chitosan Schiff base has been prepared from chitosan reaction with p-chloro benzaldehyde. The AuNPs and AgNPs were manufactured by extract of onion peels as a reducing agent. The AuNPs and AgNPs that have been synthesized were characterized through UV-vis spectroscopy, XRD analyses and SEM microscopy. The polymer blends of the chitosan / PEG has been prepared by using the approach of solution casting. Chitosan Schiff base / PEG Au and Ag nanocomposites were synthesized, nanocomposites and polymer blends have been characterized by FTIR which confirm the formation of Schiff base by revealing a new band of absorption at 1693 cm-1 as a result of the (C=N) imine group. FESEM, DSC and TGA confirm the thermal stability

Aim: To evaluate the cytotoxic activity of newly synthesized a series of novel HDAC inhibitors comprising sulfonamide as zinc binding group and Isatin derivatives as cap group joined by mono amide linker as required to act as HDAC inhibitors. Materials and Methods: The utilization of sulfonamide as zinc binding group joined by N-alkylation reaction with ethyl-bromo hexanoate as linker group that joined by amide reaction with Isatin derivatives as cap groups which known to possess antitumor activity in the designed of new histone deacetylase inhibitors and using the docking and MTT assay to evaluate the compounds. Results: Four compounds have been synthesized and characterized successfully by ART-FTIR, NMR and ESI-Ms. the compounds w

Objective: To enhance bonding strength between thermoplastic denture base and acrylic soft liner through ethyl acetate surface treatment. Materials and Methods: Modifications of thermoplastic acrylic denture base surface were investigated with SEM. FTIR was used to detect whether there was a chemical bond between thermoplastic acrylic and the organic solvent. A total of 80 samples were prepared and divided into 20 samples for the surface roughness test and 60 samples for the shear bond strength test. Failure type was assessed visually. Results: Shear bond strength and surface roughness values of un treated samples were lower in comparison to surface treated groups; the greatest post thermocycling bond strength value was recorded for the sam

Using zooplankton as bioindicators, this study evaluates the ecological condition of the Euphrates River in Iraq's Babylon Province. Site 1 (North Hillah, next to the old Babylon ruins), Site 2 (Hillah city center), Site 3 (South Hillah, close to Al-Mahaweel), and Site 4 (near Al-Kifl town) were the four monitoring locations chosen along the river. The highest and lowest averages of the measured physical and chemical factors indicate temperature (25.1°-29.4°), pH (7.2-7.9), electrical conductivity (EC) (940 µS/cm-1241µS/cm), total dissolved solids TDS (591 mg/L-789mg/L), dissolved oxygen (DO) (5.6 mg/ l-7.1 mg/L), biological oxygen demand (BOD5) (2.4mg/L-4.2 mg/L), nitrate (1.3 mg/L–3.2 mg/L), nitrite (0.04 mg/L–0.13 mg/L),

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

Single mode-no core-single mode fiber structure with a section of tuned no-core fiber diameter to sense changes in relative humidity has been experimentally demonstrated. The sensor performance with tuned NCF diameter was investigated to maximize the evanescent fields. Different tuned diameters of of (100, 80, and 60)μm were obtained by chemical etching process based on hydrofluoric acid immersion. The highest wavelength sensitivity was obtained 184.57 pm/RH% in the RH range of 30% –100% when the no-core fiber diameter diameter was 60 μm and the sensor response was in real-time measurements