In this work, the detection of zinc (Zn) ions that cause water pollution is studied using the CSNPs- Linker-alkaloids compound that was prepared by linking extracted alkaloids from Iraqi Catharanthus roseus plant with Chitosan nanoparticles (CSNPs) using maleic anhydride. This compound is characterized by an X-ray diffractometer (XRD) which shows that it has an orthorhombic structure with crystallite size in the nano dimension. Zeta Potential results show that the CSNPs-Linker-alkaloids carried a positive charge of 54.4 mV, which means it possesses high stability. The Fourier transform infrared spectroscopy (FTIR) shows a new distinct band at 1708.93 cm-1 due to C=O esterification. Scanning electron microscope (SEM) images show that the CSNPs- Linker- alkaloids compound have two shapes in the nano dimension: spherical particles and nanotubes, which may be due to nuclei and growth processes, respectively. The energy gap calculated from the photoluminescence spectrum is equal to 2.5 eV. The Hall effect measurements prove that the synthesized CSNPs- Linker-alkaloids compound is a p-type semiconductor. The cycle voltammetry technique was used to detect the Zn ions in different concentrations in the water by modifying the electrochemical system's glassy carbon electrode (GCE) with a CSNPs-Linker-alkaloids compound. The modified electrode was used to detect Zn ions in the range of (1-8) ppm, which causes water pollution. The best sensor sensitivity R² equals 0.997 for oxidation and 0.993 for reduction. This modified electrode (GCE /CSNPs- Linker-alkaloids) acts as a good biosensor for heavy metals detection in water as well as for biophysics applications.
With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect
... Show MorePseudomonas aeruginosa readily binds to different kind of abiotic surfaces and form biofilm. The ability of the bacterial species to form biofilm onto polyvinyl chloride (PVC) is associated with several economic, health and environmental problems. The effect of kind of water on ability of this bacterium to form biofilm is scanty in literature. In present study, the ability of different environmental isolates of P. aeruginosa to form biofilm onto polystyrene microtiter plate was evaluated. Furthermore, the effect of waters that collected from different sources on biofilm formation of this bacterium onto PVC was studied. Spectrophotometric method was used to check the ability of bacteria to form biofilm and evaluated the role of waters onto a
... Show MoreLoanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing lette
... Show MoreIn this research, Schiff bases derived from the reaction of anthrone with different heterocyclic amines have been described. The resulted Schiff base compounds were reacted with various nucleophiles in order to obtain new heterocyclic derivatives. Chemical structures of all products were confirmed by IR, 1H-, 13C-NMR spectral data and elemental analysis. All synthesized compounds were in vitro tested against a standard strain of pathogenic microorganism including Gram +ve bacteria (Staphylococcus aureus), Gram –ve bacteria (Escherichia coli), and fungi (Candida albicans).
Metal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limit
... Show MoreThe majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe
Abstract. The main technique for removing bacteria from water for various applications is chemical disinfection. However, this method has many disadvantages such as producing disinfectant by-products (DBPs), biofilm formation and either rendering the water unpotable (at high residual disinfection) or leaving a potential for lethal diseases such as Cholera (if the residual disinfection is too low). Recently, a process was developed for continuous removal of bacteria from water using the principle of froth flotation through compressed air only without any chemicals (Hassan, 2015). This work examines the extent to which chemical free froth flotation can purify drinking water. The experiments were carried out using two flotation columns
... Show MoreAbstract. Shock chlorination is a well-known practice in swimming pools and domestic wells. One of the limitations for using this technique in drinking water purification facilities is the difficulty of quickly removing high chlorine concentrations in water distribution systems or production facilities. In order to use this method in the drinking water industry a shock de-chlorination method should be introduced for producing microorganism and biocide free water. De-chlorination using natural stagnant aeration (leaving the water to lose the chlorine naturally) is the safest known method if compared with chemical and charcoaling methods. Unfortunately, stagnant aeration is a slow process. Therefore, developing a process for accelerat
... Show MoreThe aim of this paper is to investigate the effects of Nd:YAG laser shock processing (LSP) on micro-hardness and surface roughness of 86400Cu-Zn alloy. X-ray fluorescence technique was used to analyze the chemical composition of this alloy. LSP treatment was performed with a Q-switched Nd: YAG laser with a wavelength of 1064 nm. The results show that laser shock processing can significantly increase. The micro-hardness and surface roughness of the LSP-treated sample. Vickers diamond indenter was used to measure the micro-hardness of all samples with different laser pulse energy and the different number of laser pulses. It is found that the metal hardness can be significantly increased to more than 80% by increasing the laser energy and t
... Show MoreDigital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou
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