Synthesis of a Potential Tumor Imaging Agent by Oxidative Radioiodination of Aspirin and Its Preclinical Study

Radiochemistry - Aspirin, one of nonsteroidal anti-inflammatory analgesic drugs, was labeled with 125I with a labeling yield of 85.5% under the following conditions: pH 9, 100 mg of the substrate,...     

A hybrid chaotic blowfish encryption for high-resolution satellite imagery

Multimedia Tools and Applications - In this article, we have designed a new information confidentiality mechanism based on the combination of Blowfish encryption algorithm along with Henon and Chen...     

A fast branch,bound and remember algorithm for disassembly line balancing problem

In recent years, the interests of disassembly line have increased owing to economic reasons and the increase of environmental awareness. Effective line can provide many advantages in terms of economic aspect and it facilitates competition the companies with others. This study contributes to the relevant literature by a branch, bound and remember algorithm for disassembly line balancing problem with AND/OR precedence. The proposed exact solution method employs the memory-based dominance rule to eliminate the reduplicated sub-problems by storing all the searched sub-problems and to utilise cyclic best-first search strategy to obtain high-quality complete solutions fast. In this paper, minimising the number of stations is taken as the performance measure. The proposed methodology is tested on a set of 260 instances and compared with the mathematical model using CPLEX solver and five well-known metaheuristics. Computational results show that the proposed method is capable of obtaining the optimal solutions for all the tested instances with less than 0.1?seconds on average. Additionally, comparative study demonstrates that the proposed method is the state-of-the-art algorithm and outperforms the CPLEX solver and metaheuristics in terms of both solution quality and search speed aspects.     

Design and analysis of a solar tower power plant integrated with thermal energy storage system for cogeneration

In the current study, a solar tower–based energy system integrated with a thermal energy storage option is offered to supply both the electricity and freshwater through distillation and reverse osmosis technologies. A high‐temperature thermal energy storage subsystem using molten salt is considered for the effective and efficient operation of the integrated system. The molten salt is heated up to 565°C through passing the solar tower. The thermal energy storage tanks are designed to store heat up to 12 hours. The temperature variations in the storage tanks are studied and compared accordingly for evaluation. The effect of operating temperatures on the freshwater production and overall system efficiency is determined. About 24.46 MW electricity is generated in the steam turbine under sunny conditions. Furthermore, the storage subsystem stores heat during sunny hours to utilize later in cloudy hours and night time. The produced power decreases to 20.17 MW in discharging hours due to temperature decrease in the tank. The electricity generated by the system is then used to produce freshwater through the reverse osmosis units and also to supply electricity for the residential use. A total flowrate of 240.02 kg/s freshwater is obtained by distillation and reverse osmosis subsystems.     

Frontiers in combustion techniques and burner designs for emissions control and CO2 capture: A review

The use of fossil fuel is expected to increase significantly by midcentury because of the large rise in the world energy demand despite the effective integration of renewable energies in the energy production sector. This increase, alongside with the development of stricter emission regulations, forced the manufacturers of combustion systems, especially gas turbines, to develop novel combustion techniques for the control of NO_x and CO₂ emissions, the latter being a greenhouse gas responsible for more than 60% to the global warming problem. The present review addresses different burner designs and combustion techniques for clean power production in gas turbines. Combustion and emission characteristics, flame instabilities, and solution techniques are presented, such as lean premixed air‐fuel (LPM) and premixed oxy‐fuel combustion techniques, and the combustor performance is compared for both cases. The fuel flexibility approach is also reviewed, as one of the combustion techniques for controlling emissions and reducing flame instabilities, focusing on the hydrogen‐enrichment and the integrated fuel‐flexible premixed oxy‐combustion approaches. State‐of‐the‐art burner designs for gas turbine combustion applications are reviewed in this study, including stagnation point reverse flow (SPRF) burner, dry low NO_x (DLN) and dry low‐emission (DLE) burners, EnVironmental burners (including EV, AEV, and SEV burners), perforated plate (PP) burner, and micromixer (MM) burner. Special emphasis is made on the MM combustor technology, as one of the most recent advances in gas turbines for stable premixed flame operation with wide turndown and effective control of NO_x emissions. Since the generation of pure oxygen is prerequisite to oxy‐combustion, oxygen‐separation membranes became of immense importance either for air separation for clean oxy‐combustion applications or for conversion/splitting of the effluent CO₂ into useful chemical and energy products. The different carbon‐capture technologies, along with the most recent carbon‐utilization approaches towards CO₂ emissions control, are also reviewed.     

A green approach for modification and functionalization of wool fabric using bio- and nano-technologies

In the present work, we propose a green and sustainable strategy for eco-friendly surface modification of wool structure using biosynthesized kerationlytic proteases, from C4-ITA-EGY, Streptomyces harbinensis S11-ITA-EGY and Streptomyces carpaticus S33-ITA-EGY, followed by subsequent environmentally sound functionalization of the bio-treated substrates using ZnONPs, ZrO₂NPs, ascorbic acid and vanillin, individually, to provide durable antibacterial as well as UV-protection properties. Both surface modification changes and the extent of functionalization of the final products were characterized by SEM, EDX, antibacterial efficacy, UV-blocking ability, loss in weight, nitrogen content and durability to washing analysis. The obtained data reveal that the developed green wool fabrics exhibit outstanding durable antibacterial activity and UV-blocking ability for fabricating multi-functional textile products that can be utilized in a wide range of sustainable protective textiles, irrespective of the used post-finishing formulation ingredients. The results also show that both modification and functionalization processes are governed by the type of enzyme and kind of active material respectively. Moreover, the biosynthesized kerationlytic proteases could be accessibly used to remove protein-based stains like blood and egg.

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Properties and microstructure of copper-alloyed solid solution-strengthened ductile iron

Solid solution-strengthened ductile iron (DI) exhibits outstanding mechanical properties due to the high silicon content. The strengthening by silicon addition is limited since additions above 4.3?wt-% lead to embrittlement. For a further improvement of mechanical properties, other alloying elements need to be considered. In the present work, the effect of various copper additions on the microstructure and the mechanical properties of solid solution-strengthened DI were investigated. The results show that no appreciable strengthening can be achieved by copper addition without the formation of pearlite in the matrix. The pearlite content increases considerably for Cu-additions above 0.23?wt-% and is independent of the cooling rate for the cooling conditions analysed.     

Cryptanalysis of Merkle-Hellman Cipher Using Parallel Genetic Algorithm

Mobile Networks and Applications - In 1976, Whitfield Diffie and Martin Hellman introduced the public key cryptography or asymmetric cryptography standards. Two years later, an asymmetric...     

Improved monarch butterfly optimization for unconstrained global search and neural network training

This work is a seminal attempt to address the drawbacks of the recently proposed monarch butterfly optimization (MBO) algorithm. This algorithm suffers from premature convergence, which makes it less suitable for solving real-world problems. The position updating of MBO is modified to involve previous solutions in addition to the best solution obtained thus far. To prove the efficiency of the Improved MBO (IMBO), a set of 23 well-known test functions is employed. The statistical results show that IMBO benefits from high local optima avoidance and fast convergence speed which helps this algorithm to outperform basic MBO and another recent variant of this algorithm called greedy strategy and self-adaptive crossover operator MBO (GCMBO). The results of the proposed algorithm are compared with nine other approaches in the literature for verification. The comparative analysis shows that IMBO provides very competitive results and tends to outperform current algorithms. To demonstrate the applicability of IMBO at solving challenging practical problems, it is also employed to train neural networks as well. The IMBO-based trainer is tested on 15 popular classification datasets obtained from the University of California at Irvine (UCI) Machine Learning Repository. The results are compared to a variety of techniques in the literature including the original MBO and GCMBO. It is observed that IMBO improves the learning of neural networks significantly, proving the merits of this algorithm for solving challenging problems.