Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75.00%, and 30.20%, respectively. Two species of bacteria and one type of fungus were examined at three different use concentrations if possible of MnO2 nanoparticles. Antibiotics like Amoxicillin and Metronidazole were used as a control group to see how the findings stacked up.
Arum maculatum is traditionally used for the control of many diseases and illnesses such as kidney pain, liver injury, hemorrhoids. However, the detailed biomedical knowledge about this species is still lacking. This study reports on the bioactive components and the possible mechanisms underlying the antioxidant, anti-inflammatory and cytotoxic activity of A. maculatum leaf extract. Gas chromatography-mass spectrometry (GC-MS) was used for phytochemical analysis. Assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide ) (MTT) was used to determine the cytotoxicity in the murine cell line L20B upon exposure to different extract concentrations for 24 h. Enzyme-linked immunosorbent assay (ELISA) was used to detect pro-in
... Show MoreMorus alba, member of the Moraceae family, is a perennial tree utilized in folk medicine, preparing the modern drug, and considered the main food for silkworms. However, data on chemical content in the leaves is still limited; the main objective of this study is to detect the presence and determine the concentration of different polyphenolic constituents in the leaves of the Morus alba plant by reverse phase-high performance liquid chromatography (RP-HPLC) and evaluate the cytotoxic effect of ethyl acetate extract of this plant on human breast cancer (AMJ-13) cell line. Phytochemical analysis of the Morus alba leaves ethyl acetate extract led to identifying and quantification of six polyphenolic constituents designated as phenolic a
... Show MoreA study was conducted to evaluate the antibacterial effect of Phyllanthus emblica extract (ethanol:methanol, 1:1) against Pseudomonas aeruginosa, Staphylococcus aureus and Escherichia coli at different concentrations, i.e. 0.625, 1.25, 2.50, 5.0, 10.0 and 20.0 mg/ml. The antibacterial activity was determined by the agar well diffusion method to investigate the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). The alcoholic extract of Phyllanthus emblica had the highest antibacterial activity at 20 mg/ml and 5 mg/ml except for Pseudomonas aeruginosa where the value of inhibition was between 20 and 10 mg/ml. The MIC concentrations were mostly very high and ranged from 5 to 1.25 mg/ml, while the MBC range fro
... Show MoreThe protective effect of ginger extract against cisplatin-induced hepatotoxicity and cardiotoxicity was evaluated in 30 albino white rats(weighing 200-300 gm ) classified into 5groups (6 rats per each group). The rats were treated with 0.5g/kg/day or 1g/kg/day ginger extract orally 5 successive days before and 5 successive days after induction of toxicity with intraperitoneal (IP) injection of (10mg/kg ) cisplatin, resulted in a significant reduction in the levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT) , total serum billirubin(TSB) , lactate dehydrogenase (LDH) and creatine kinase(CK) enzymes in comparison with the cisplatin treated animals; ginger extract
... Show MoreIn recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
... Show MoreAn easy, eclectic, precise high-Performance Liquid Chromatographic (HPLC) procedure was evolved and validated to estimate of Piroxicam and Codeine phosphate. Chromatographic demarcation was accomplished on a C18 column [Use BDS Hypersil C18, 5μ, 150 x 4.6 mm] using a mobile phase of methanol: phosphate buffer (60:40, v/v, pH=2.3), the flow rate was 1.1 mL/min, UV detection was at 214 nm. System Suitability tests (SSTs) are typically performed to assess the suitability and effectiveness of the entire chromatography system. The retention time for Piroxicam was found to be 3.95 minutes and 1.46 minutes for Codeine phosphate. The evolved method has been validated through precision, limit of quantitation, specificity,
... Show MoreMany objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector. Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art a
... Show MoreImage is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran
... Show MoreThe aim of this research is controlling the amount of the robotic hand catching force using the artificial muscle wire as an actuator to achieve the desired response of the robotic hand in order to catch different things without destroying or dropping them; where the process is to be similar to that of human hand catching way. The proper selection of the amount of the catching force is achieved through out simulation using the fuzzy control technique. The mechanism of the arrangement of the muscle wires is proposed to achieve good force selections. The results indicate the feasibility of using this proposed technique which mimics human reasoning where as the weight of the caught peace increases, the force increases also with approximatel
... Show MoreAutism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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