A major disadvantage of dose reconstruction by means of thermoluminescence (TL) is the fact that during readout of any TL material exposed to ionizing radiation (i.e., during measuring the glow curve), the radiation-induced signal gets lost. Application of the photo-transferred thermoluminescence phenomenon (PTTL) may offer a solution to this problem. In PTTL, the residual signal that is not destroyed by conventional TL readout (because it comes from deeper electron traps) can be readout through simultaneous stimulation by UV light and heating, allowing to obtain information about the absorbed dose in a second run. The present paper describes the application of PTTL for emergency dose assessment. For this, MTS-N thermoluminescent detectors (LiF: Mg, Ti) were exposed using a high-energy Clinac 2300 medical linear accelerator to doses of 100 mGy, 300 mGy, 500 mGy, 700 mGy and 1000 mGy. Irradiation with UV radiation allowed the determination of the optimal heating time of 3 h, while the optimal temperature was identified to be 70 °C. The results obtained demonstrated the usefulness of the PTTL method for emergency dose assessment. The efficiency of the PTTL method was determined as 19%. Finally it was found that the detector background after UV exposure should not be underestimated during routine dose measurements.
The study aimed to investigate the effect of different times as follows 0.5, 1.00, 2.00 and 3.00 hrs, type of solvent (acetone, methanol and ethanol) and temperature (~ 25 and 50)ºc on curcumin percentage yield from turmeric rhizomes. The results showed significant differences (p? 0.05) in all variables. The curcumin content which were determined spectrophotometrically ranged between (0.55-2.90) %. The maximum yield was obtained when temperature, time and solvent were 50ºC, 3 hrs and acetone, respectively.
This work is concerned with designing two types of controllers, a PID and a Fuzzy PID, to be used
for flying and stabilizing a quadcopter. The designed controllers have been tuned, tested, and
compared using two performance indices which are the Integral Square Error (ISE) and the Integral
Absolute Error (IAE), and also some response characteristics like the rise time, overshoot, settling
time, and the steady state error. To try and test the controllers, a quadcopter mathematical model has
been developed. The model concentrated on the rotational dynamics of the quadcopter, i.e. the roll,
pitch, and yaw variables. The work has been simulated with “MATLAB”. To make testing the
simulated model and the controllers m
This study focuses on producing wood-plastic composites using unsaturated polyester resin reinforced with Pistacia vera shell particles and wood industry waste powder. Composites with reinforcement ratios of 0%, 20%, 30%, and 40% were prepared and tested for thermal conductivity, impact strength, hardness, and compressive strength. The results revealed that thermal conductivity increases with reinforcement, while maintaining good thermal insulation, reaching a peak value of 0.633453 W/m·K. Hardness decreased with increased reinforcement, reaching a minimum nominal hardness value of 0.9479. Meanwhile, impact strength and compressive strength improved, with peak values of 14.103 k/m² and 57.3864568 MPa, respectively. The main aim is to manu
... Show MoreDye-sensitized solar cells (DSSC) create imitation photosynthesis by using chemical reactions to produce electricity from sunlight. DSSC has been pursued in numerous studies due to its capability to achieve efficiencies of up to 15% with artificial photosensitizer in diffuse light. However, artificial photosensitizers present a limitation because of the complex processing of metal compound. Therefore, various types of sensitizers were developed and synthesized to surpass the artificial sensitizer performances such as natural sensitizers from bio-based materials including plants, due to simple processing techniques and low environmental impact. Thus, this study examines the potential and properties of natural sensitizers from the was
... Show MoreThis work discusses the beginning of fractional calculus and how the Sumudu and Elzaki transforms are applied to fractional derivatives. This approach combines a double Sumudu-Elzaki transform strategy to discover analytic solutions to space-time fractional partial differential equations in Mittag-Leffler functions subject to initial and boundary conditions. Where this method gets closer and closer to the correct answer, and the technique's efficacy is demonstrated using numerical examples performed with Matlab R2015a.
A series of new 4-(((4-(5-(Aryl)-1,3,4-oxadiazol-2-yl)benzyl)oxy)methyl)-2,6-dimethoxy phenol (6a-i) were synthesized from cyclization of 4-(((4-hydroxy-3,5-dimethoxy benzyl)oxy)methyl)benzohydrazide with substituted carboxylic acid in the presences of phosphorusoxy chloride.The resulting compounds were characterized by IR, 1H-NMR, 13C-NMR, and HRMS data. 2,2-Diphenyl-1-picrylhydrazide (DPPH) and ferric reducing antioxidant power (FRAP) assays were used to screen their antioxidant properties. Compounds 6i and 6h exhibited significant antioxidant ability in both assay. Furthermore, type of substituent and their position of the aryl attached 1,3,4-oxadiazole ring at position five are play an important roles in enhancing or declining the antio
... Show MoreArbuscular mycorrhizal fungi and sulphur foam added either at direct seeding or at transplanting decreased the effects of nematode (Meloidogyne javanica) on eggplant growth, and improved plant health. Experiments were conducted to study the possible interactions between the Mycorrhizal fungi (Glomus mossae and Gigaspora spp.) and sulphur foam to control M. javanica on eggplant at seed or seedling stage. Experiment at seed stage treated with Mycorrhiza or sulphur foam alone or together stimulated the growth and reduced Nematode infestation significantly. Treated plant at seedling stage increased plant growth and reduced the number of galls /gm of root system. The interaction between Mycorrhiza and sulpher foam treatments was not significant
... Show MoreSoftware-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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