This study assessed the advantage of using earthworms in combination with punch waste and nutrients in remediating drill cuttings contaminated with hydrocarbons. Analyses were performed on day 0, 7, 14, 21, and 28 of the experiment. Two hydrocarbon concentrations were used (20000 mg/kg and 40000 mg/kg) for three groups of earthworms number which were five, ten and twenty earthworms. After 28 days, the total petroleum hydrocarbon (TPH) concentration (20000 mg/kg) was reduced to 13200 mg/kg, 9800 mg/kg, and 6300 mg/kg in treatments with five, ten and twenty earthworms respectively. Also, TPH concentration (40000 mg/kg) was reduced to 22000 mg/kg, 10100 mg/kg, and 4200 mg/kg in treatments with the above number of earthworms respectively. The present study revealed that the trend of degradation was observed to increase significantly with an increase in Earthworms number and with an increase in number of tested days. The results of this study have shown that TPH with certain concentrations can be reduced to acceptable levels by using the selected earthworms named Allolobophora. Also the study results revealed that the present bioremediation can be considered an additional option to deal with the local petroleum contaminated sites.
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User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption user-face is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract
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New ligands, N1, N4-bis (benzo[d]thiazol-2- ylcarbamothioyl) succinamide (L1) and N1, N4- bis (benzylcarbamothioyl)succinamide (L2), derived from succinyl chloride and 2-amino benzothiazole or benzylamine, respectively, have been used to prepare a set of transition metal complexes with the general formula [M2(L)Cl4], where L=L1 or L2, M = Mn(II), Ni(II), Cu(II), Cd(II), Co(II), Zn(II) or Hg(II). The synthesized compounds were characterized using various analytical techniques including TGA, 13C NMR, mass spectroscopy, 1H and Fourier-transform infrared (FTIR) spectroscopy, magnetic measurement, molar conductivity, electronic spectrum, (%M, %C, %H, %N) and atomic absorption flame (AAF) analysis. The results showed that (L1, L2) bin
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In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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In this work, a Photonic Crystal Fiber (PCF) sensor based on the Surface Plasmon Resonance (SPR) technology was proposed. A thin layer of gold (Au) was deposited on a D-shaped Photonic Crystal Fiber (PCF), which was coated with plasmonic chemically stable gold material with a thickness of 40nm. The performance parameters like sensitivity including wavelength sensitivity and amplitude sensitivity and resolution were evaluated by simulation using COMSOL software. The proposed sensor was created by using the finite element approach, it is numerically examined. The results show that the surface of D-shaped Photonic Crystal Fiber coated with Au behaves as a sensor to detect the refractive index (IR) of toxic metal ions. The impacts of the str
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Detecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.
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The escalating generation of industrial waste alongside the growing demand for high-performance, environmentally sustainable drilling fluids presents critical challenges to the oil and gas sector. Conventional drilling fluid additives are predominantly synthesized from virgin materials, contributing to resource depletion and environmental burden. Objectives: This study pioneers a circular economy approach by synthesizing silica nanoparticles (SiO2NPS) and alumina nanoparticles (Al2O3NPs) entirely from locally sourced industrial waste — bentonite clay and aluminum scrap, respectively — and evaluating their performance as functional additives in water-based drilling fluids (WBDFs). Novelty: To the best of our knowledge, this represents th
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