Nonsteroidal anti-inflammatory drugs (NSAIDs) are drugs that help reduce inflammation, which often helps to relieve pain. In this research new ibuprofen oxothiazolidnone derivatives were synthesized from the reaction of Schiff base derivatives of Ibuprofen with mercapto acetic acid VI a-c, to improve the potency and to decrease the drug's potential side effects, a new series of 4-thiazolidinone derivatives of ibuprofen was synthesized VI a-c . The characterizations of the compounds were identified by using FTIR, 1HNMR technique and by measuring the physical properties.

Fourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.

Catalytic reduction is considered an effective approach for the reduction of toxic organic pollutants from the environment, but finding an active catalyst is still a big challenge. Herein, Ag decorated CeO2 catalyst was synthesized through polyol reduction method and applied for catalytic reduction (conversion) of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). The Ag decorated CeO2 catalyst displayed an outstanding reduction activity with 99% conversion of 4-NP in 5 min with a 0.61 min−1 reaction rate (k). A number of structural characterization techniques were executed to investigate the influence of Ag on CeO2 and its effect on the catalytic conversion of 4-NP. The outstanding catalytic performances of the Ag-CeO2 catalyst can be assigne

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

Background: Adipose derived-mesenchymal stem cells have been used as an alternative to bone marrow cells in this study. Objective: We investigated the in vitro isolation, identification, and differentiation of stem cells into neuron cells, in order to produce neuron cells via cell culture, which would be useful in nerve injury treatment. Method: Mouse adipose mesenchymal stem cells were dissected from the abdominal subcutaneous region. Neural differentiation was induced using β-mercaptoethanol. This study included two different neural stage markers, i.e. nestin and neurofilament light-chain, to detect immature and mature neurons, respectively. Results: The immunocytochemistry results showed that the use of β-mercaptoethanol resulted in

The performance analyses of 15 kWp (kW peak) Grid -Tied solar PV system (that considered first of its type) implemented at the Training and Energy Research Center Subsidiary of Iraqi Ministry of Electricity in Baghdad city has been achieved. The system consists of 72 modules arranged in 6 strings were each string contains 12 modules connected in series to increase the voltage output while these strings connected in parallel to increase the current output. According to the observed duration, the reference daily yields, array daily yields and final daily yields of this system were (5.9, 4.56, 4.4) kWh/kWp/day respectively. The energy yield was 1585 kWh/kWp/year while the annual total solar irradiation received by solar array system was 198

  This study was conducted to determine the effect of different concentrations of   ethanol  extract of propolis against two  fungi Botrytis cinerea, Altrnaria sp.      The most important chemical constituents of propolis diagnosed by the Infra Red Spectroscopy, were the  Flavonoids  specificaly.       Results showed a high antifungal activity of ethanol  extract of propolis, evidently with a high concentration  of extract (5) mg\ml, which completely inhibited the radial growth on both  solid and liquid media (PDA &PD Broth ) of both fungi .         We observed that , ethanol  extract p