This work was influenced the separation and preconcentration steps were carried out to determination of metformin (MET) in pharmaceutical preparations and human serum samples. Complex formation method and cloud-point extraction (CPE) coupling with UV-Visible spectrophotometry were used to investigated of study target.The results has showed the best optical characteristic for calibration curve and statistical data which were obtained under optimum conditions. The first method is based on the reaction of MET with nickel (II) in alkaline medium an absorption maximum ?)max) at 434nm. ''Beer's low'' is obeyed in the concentration range (10-100µg.ml-1) with molar absorptivity of 3.9x103 L.mol-1.cm-1.The limit of detection and quantitation valu

Emulsion Liquid Membrane (ELM) is an emerging technology that removes contaminants from water and industrial wastewater. This study investigated the stability and extraction efficiency of ELM for the removal of Chlorpyrifos Pesticide (CP) from wastewater. The stability was studied in terms of emulsion breakage. The proposed ELM included n-hexane as a diluent, span-80 as a surfactant, and hydrochloric acid (HCl) as a stripping agent. Parameters such as mixing speed, aqueous feed solution pH, internal-to-organic membrane volume ratio, and external-to-emulsion volume ratio were investigated. A minimum emulsion breakage of 0.66% coupled with a maximum chlorpyrifos extraction and stripping efficiency were achieved at 96.1% and 95.7% at b

Focal adhesion kinase (FAK), ephrin receptor type A4 (EphA4), and adiponectin (ADPN) are important indicators in inflammation, tumor growth, migration, and angiogenesis in some cancers. The predictive impact of their concentrations in acute myeloid leukemia (AML) patients to be identified remains. The research sought to explore the effect of FAK, EphA4, and ADPN as prognostic biomarkers, and their influence on patient survival, and to look for any potential correlation between their levels with hematological parameters in AML patients.

In this study, nanoparticles were synthesized using the pulsed laser ablation technique, employing an Nd:YAG laser with a wavelength of 1064 nm. The ablation process was carried out at room temperature under varying laser energy of 950 mJ. The structural characteristics of the resulting nanoparticles were investigated using X-ray diffraction (XRD) and atomic force microscopy (AFM). The biological impact of the synthesized nanoparticles was assessed by administering two different doses (1 ml/kg and 4 ml/kg) to experimental animal models. The study evaluated changes in thyroid hormone levels, specifically thyroid-stimulating hormone (T_SH), triiodothyronine (T[Formula: see text] and thyroxine (T[Formula: see text]

Cold atmospheric plasma (CAP) is used widely in medical and biological fields because of non-thermal effected. Direct application of plasma is preferred in medical functions, so, direct application of cold plasma has obtained by the floating electrode dielectric barrier discharge (FE-DBD) system. The purpose of this paper to review the effect of (CAP) on the reproductive hormones (testosterone, LH, E2, progesterone, for male rats. The study appeared that no significant effect on E2 and progesterone hormone for all time of exposure, besides this significant difference in LH hormone (P<0.05) at 15 sec, (P<0.0001) at 30, 90 sec and (P<0.001) at 60 sec of exposure to plasma. Added to that significant difference (P<0.01) at 15, 30, 60 sec and no

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class