The adsorption of Cr (VI) from aqueous solution by spent tea leaves (STL) was studied at different initial Cr (VI) concentrations, adsorbent dose, pH and contact time under batch isotherm experiments The adsorption experiments were carried out at 30°C and the effects of the four parameters on chromium uptake to establish a mathematical model description percentage removal of Cr (VI). The
analysis results showed that the experimental data were adequately fitted to second order polynomial model with correlation coefficients for this model was (R2 = 0.9891). The optimum operating parameters of initial Cr (VI) concentrations, adsorbent dose, pH and contact time were 50 mg/l, 0.7625 g, 3 and 100 min, respectively. At these conditions, the maximum percentage removal of Cr (VI) was 92.88%. The amounts of Cr (VI) adsorbed onto STL were highly affected by the solution pH value. Equilibrium data was modeled with Langmuir and Freundlich models isotherms. Langmuir model is found very well represent the equilibrium data with correlation factor is close to unity than the Freundlich model. The maximum monolayer adsorption capacity was found to be 47.98 mg/g at optimum conditions. The saturated adsorbent was regenerated by base treatment and found to be reuse efficiently after fourth cycle
at optimum conditions as well as for safe disposal of base that contains high concentration of Cr (VI) is precipitated as barium chromate.
Objective: The antimicrobial efficacy of three disinfection solutions: 5.25% sodium hypochlorite (NaOCl), 2% chlorhexidine (CHX) and Listerine mouthwash were investigated as routine chair-side gutta-percha (GP) disinfection reagents. Design: four groups of gutta percha points were contaminated with E. faecalis bacteria then disinfected by immersion in different solutions (5.25% sodium hypochlorite, 2% chlorhexidine gluconate, Listerine mouth wash and distilled water as control) after 1 and 7 days culturing periods. The antibacterial efficacy of these disinfection solutions was evaluated by using colonies per units (CPU) Methods: Forty GP cones (F3 Dentsply) were sterilized with ethylene oxide gas before immersed contamination within broth m
... Show MoreThis work was conducted to study the extraction of eucalyptus oil from natural plants (Eucalyptus camaldulensis leaves) using water distillation method by Clevenger apparatus. The effects of main operating parameters were studied: time to reach equilibrium, temperature (70 to100°C), solvent to solid ratio (4:1 to 8:1 (v/w)), agitation speed (0 to 900 rpm), and particle size (0.5 to 2.5 cm) of the fresh leaves, to find the best processing conditions for achieving maximum oil yield. The results showed that the agitation speed of 900 rpm, temperature 100° C, with solvent to solid ratio 5:1 (v/w) of particle size 0.5 cm for 160 minute give the highest percentage of oil (46.25 wt.%). The extracted oil was examined by HPLC.
Selective recovery of atropine from Datura innoxia seeds was studied. Applying pertraction in a rotating film contactor (RFC) the alkaloid was successfully recovered from native aqueous extracts obtained from the plant seeds. Decane as a liquid membrane and sulfuric acid as a stripping agent were used. Pertraction from native liquid extracts provided also a good atropine refinement, since the most of co-extracted from the plant species remained in the feed or membrane solution. Solid–liquid extraction of atropine from Datura innoxia seeds was coupled with RF-pertraction in order to purify simultaneously the extract obtained from the plant. Applying the integrated process, proposed in this study, a product containing 92.6% atropine was
... Show MoreThis paper aims to find new analytical closed-forms to the solutions of the nonhomogeneous functional differential equations of the nth order with finite and constants delays and various initial delay conditions in terms of elementary functions using Laplace transform method. As well as, the definition of dynamical systems for ordinary differential equations is used to introduce the definition of dynamical systems for delay differential equations which contain multiple delays with a discussion of their dynamical properties: The exponential stability and strong stability
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.