In this study, a packed bed was used to remove pathogenic bacteria from synthetic contaminated water. Two types of packing material substrates, sand and zeolite, were used. These substrates were coated with silver nanoparticles (AgNPs), which were prepared by decomposition of Ag ions from AgNO3 solution. The prepared coated packings were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy and transmission electron microscopy. The packed column consisted of a PVC cylinder of 2 cm diameter and 20 cm in length. The column was packed with silver nanoparticlecoated substrates (sand or zeolite) at a depth of 10 cm. Four types of bacteria were studied: Escherichia coli, Shigella dysenteriae, Pseudomonas aerugi

In this study, titanium dioxide (TiO₂) nanoparticles incorporated with cement were synthesis by a simple casting method as a function concentration of TiO₂ (0.2, 0.4, 0.8, 1, and 2 wt%). The prepared samples were characterized using the technique of Field Emission Scanning Electron Microscope (FESEM) and UV-Visible spectrophotometer, which was used to measure the adsorption spectra. The observed photocatalytic efficiency of TiO₂ nanoparticles (NP) incorporated with cement was investigated by decomposing the dye methyl blue (MB) solution under sunlight irradiation. According to the slope, the value of the k constant at the best sample is 0.8wt%, k=0.8265 min^-1. FESEM image of the TiO₂

The aim of this paper was to investigate the removal efficiencies of Zn⁺² ions from wastewater by adsorption (using tobacco leaves) and forward osmosis (using cellulose triacetate (CTA) membrane). Various experimental parameters were investigated in adsorption experiment such as: effect of pH (3 - 7), contact time (0  - 220) min, solute concentration (10 - 100) mg/l, and adsorbent dose (0.2 - 5)g. Whereas for forward osmosis the operating parameters studied were: draw solution concentration (10 - 150) g/l, pH of feed solution (4 - 7), feed solution concentration (10 - 100) mg/l. The result showed that the removal efficiency by using adsorption was 70% and the removal efficiency by using forward osmosis was 96.2 %. 

“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical

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Arsenic is a prevalent and pervasive environmental contaminant with varied amounts in drinking water. Arsenic exposure causes cancer, cardiovascular, liver, nerve, and ophthalmic diseases. The current study aimed to find the best conditions for eliminating arsenic from simulated wastewater and their effect on biomarkers of hepatic in mice. Adsorption tests including pH, contact duration, Al-kheriat dosage, and arsenic concentrations were evaluated. Seventy-two healthy albino mice (male) were accidentally allocated into nine groups (n = 8), the first group was considered as healthy control, the second group (AL-Kheriat), and other groups received AL-Kheriat and arsenic 25, 50, 75, 100, 125, 150 and 175 mg/kg, respectively. Next 10 days, the

  Computer software is frequently used for medical decision support systems in different areas. Magnetic Resonance Images (MRI) are widely used images for brain classification issue. This paper presents an improved method for brain classification of MRI images. The proposed method contains three phases, which are, feature extraction, dimensionality reduction, and an improved classification technique. In the first phase, the features of MRI images are obtained by discrete wavelet transform (DWT). In the second phase, the features of MRI images have been reduced, using principal component analysis (PCA). In the last (third) stage, an improved classifier is developed. In the proposed classifier, Dragonfly algorithm is used instead

Extraction of copper (Cu) from aqueous solution utilizing Liquid Membrane technology (LM) is more effective than precipitation method that forms sludge and must be disposed of in landfills. In this work, we have formulated a liquid surfactant membrane (LSM) that uses kerosene oil as the main diluent of LSM to remove copper ions from the aqueous waste solution through di- (2-ethylhexyl) phosphoric acid - D2EHPA- as a carrier. This technique displays several advantages including one-stage extraction and stripping process, simple operation, low energy requirement, and. In this study, the LSM process was used to transport Cu (II) ions from the feed phase to the stripping phase, which was prepared, using H₂SO₄. For LSM p