The cost-effective removal of heavy metal ions represents a significant challenge in environmental science. In this study, we developed a straightforward and efficient reusable adsorbent by amalgamating chitosan and vermiculite (forming the CSVT composite), and comprehensively investigated its selective adsorption mechanism. Different techniques, such as Fourier-transform infrared spectroscopy (FTIR), zeta potential analysis, scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer, Emmett, Teller (BET) analysis were employed for this purpose. The prepared CSVT composite exhibited a larger surface area and higher mesoporosity increasing from 1.9 to 17.24 m2/g compared to pristine chitosan. The adsorption capabilities of the CSVT composite and pristine chitosan for Cu(II) and Cd(II) species were systematically examined. Due to its porous structure and increased surface area, the CSVT composite demonstrated superior adsorption ability when compared to pristine chitosan. The maximum adsorption capacities of Cu(II) and Cd(II), determined by Langmuir adsorption isotherms in batch experiments, were found to be 116.22 and 147.64 mg/g, respectively, under initial pH conditions of 8 and an initial concentration of 250 mg/L. The thermodynamic analysis revealed that the adsorption process for both metal ions is spontaneous, endothermic physisorption, and thermodynamically favorable. These findings collectively affirm the CSVT composite as a highly promising adsorbent for the efficient and selective removal of Cu(II) and Cd(II) from aqueous solutions
Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this
... Show MoreWe propose a system to detect human faces in color images type BMP by using two methods RGB and YCbCr to determine which is the best one to be used, also determine the effect of applying Low pass filter, Contrast and Brightness on the image. In face detection we try to find the forehead from the binary image by scanning of the image that starts in the middle of the image then precedes by finding the continuous white pixel after continuous black pixel and the maximum width of the white pixel by scanning left and right vertically(sampled w) if the new width is half the previous one the scanning stops.
The aim of the current research is to identify the personal distance between members of society, as well as, to identify the feelings of satisfaction and positivity from respecting the permissible personal distance. The study also aims to identify the feelings of annoyance and comfort from approaching and going beyond personal distance and not respecting it. To achieve these goals, the researchers reviewed previous literature, theories, and studies that dealt with personal distance. The researchers reached a number of results; first, personal distance is not a law but rather a cultural guiding principle for social and professional morals. Second, there are four distances (intimate distance, the distance between friends, social distance,
... Show MoreThe reaction of LAs-Cl8 : [ (2,2- (1-(3,4-bis(carboxylicdichloromethoxy)-5-oxo-2,5- dihydrofuran-2-yl)ethane – 1,2-diyl)bis(2,2-dichloroacetic acid)]with sodium azide in ethanol with drops of distilled water has been investigated . The new product L-AZ :(3Z ,5Z,8Z)-2- azido-8-[azido(3Z,5Z)-2-azido-2,6-bis(azidocarbonyl)-8,9-dihydro-2H-1,7-dioxa-3,4,5- triazonine-9-yl]methyl]-9-[(1-azido-1-hydroxy)methyl]-2H-1,7-dioxa-3,4,5-triazonine – 2,6 – dicarbonylazide was isolated and characterized by elemental analysis (C.H.N) , 1H-NMR , Mass spectrum and Fourier transform infrared spectrophotometer (FT-IR) . The reaction of the L-AZ withM+n: [ ( VO(II) , Cr(III) ,Mn(II) , Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) and Hg(II)] has been i
... Show MoreThis study included isolation of some active materials from Curcuma longa such as tannins, saponins and volatile oils with percentage of 59%, 31%, and 9% respectively. Also the study included the determination of minerals in Curcuma longa such as " Na, Ca and K" using Flame photometer. The concentrations of these minerals were (14 ppm),(10 ppm) and )76 ppm) respectively. The anti-bacterial activity study was performed for the active materials isolated from Curcuma longa against two genus of pathogenic bacteria, Escherichia Coli and Staphylococcus aurous by using agar-well diffusion method. It appeared from this study that all of the extraction have inhibitory effect on bacteria was used. The inhibition zone diameter varies with
... Show MoreThe current study focuses on the bacterium Acinetobacter baumannii due to its importance as a nosocomial infections source in addition to its increased resistance against antibiotics. Different clinical and hospital environment samples were collected, and cultured on A. baumannii selective media: Leed Acinetobacter agar and Herellea agar. A. baumannii have been identified by traditional methods, followed by confirmation using molecular identification to detect blaoxa-51 like gene which is considered a diagnostic gene since it is present in genome of all A. baumannii strains. The result was, nineteen bacterial isolates of A.baumannii were obtained, from twenty-seven suspected isolate
... Show MoreThe guava plant, Psidium guajava L., serves as proof of the abundant donations of nature, providing a delicious guava fruit; this plant is rich in groups of medicinal and nutritional benefits. Guava belonging to the Myrtaceae family, many previous studies reported many phytochemical constituents in its leaves that have many pharmacological activities and medicinal properties; this study focuses on the isolation, structural elucidation and calculation concentration of flavonoids, assessment of the cytotoxic activityof hyperin from Psidium guajava leaves newly cultivated in Iraq. The isolation process involved the use of thin-layer chromatography (TLC) and preparative high-performance liquid chromatography (PHPLC) and structural eluci
... Show MoreThin films of tin sulfide (SnS) were prepared by thermal evaporation technique on glass substrates, with thickness in the range of 100, 200 and 300nm and their physical properties were studied with appropriate techniques. The phase of the synthesized thin films was confirmed by X-ray diffraction analysis. Further, the crystallite size was calculated by Scherer formula and found to increase from 58 to 79 nm with increase of thickness. The obtained results were discussed in view of testing the suitability of SnS film as an absorber for the fabrication of low-cost and non toxic solar cell. For thickness, t=300nm, the films showed orthorhombic OR phase with a strong (111) preferred orientation. The films deposited with thickness < 200nm deviate
... Show MoreMortar of ordinary Portland cement was blended with cockles shell
powder at different weight ratios to investigate the effect of powder
admixture on their strength and thermal conductivity. Results showed
that addition of cockles shell powder at 50% of mortar weight
improves hardness and compressive strength notably and reduces the
thermal conductivity of the end product. Results suggest the
possibility to incorporate cockles shell powders as constituents in
cement mortars for construction and plastering applications.
Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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