Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies

The growing prevalence of droughts and water scarcity have increased the importance of operating dam and reservoir systems efficiently. Several methods based on algorithms have been developed in recent years in a bid to optimize water release operation policy, in order to overcome or minimize the impact of droughts. However, all of these algorithms suffer from some weaknesses or drawbacks – notably early convergence, a low rate of convergence, or trapping in local optimizations – that limit their effectiveness and efficiency in seeking to determine the global optima for the operation of water systems. Against this background, the present study seeks to introduce and test a Hybrid Algorithm (HA) which integrates the Gravitational Search Algorithm (GSA) with the Particle Swarm Optimization Algorithm (PSOA) with the goal of minimizing irrigation deficiencies in a multi-reservoir system. The proposed algorithm was tested for a specific important multi-reservoir system in Iran: namely the Golestan Dam and Voshmgir Dam system. The results showed that applying the HA could reduce average irrigation deficiencies for the Golestan Dam substantially, to only 2 million cubic meters (MCM), compared to deficiency values for the Genetic Algorithm (GA), PSOA and GSA of 15.1, 6.7 and 5.8 MCM respectively. In addition, the HA performed very efficiently, reducing substantially the computational time needed to achieve the global optimal when compared with the other algorithms tested. Furthermore, the HA showed itself capable of assuring a high volumetric reliability index (VRI) to meet the pattern of water demand downstream from the dams, as well as clearly outperforming the other algorithms on other important indices. In conclusion, the proposed HA seems to offer considerable potential as an optimizer for dam and reservoir operations world-wide.

     

Robust and efficient memory management in Apache AsterixDB

Traditional relational database systems handle data by dividing their memory into sections such as a buffer cache and working memory, assigning a memory budget to each section to efficiently manage a limited amount of overall memory. They also assign memory budgets to memory-intensive operators such as sorts and joins and control the allocation of memory to these operators; each memory-intensive operator attempts to maximize its memory usage to reduce disk I/O cost. Implementing such memory-intensive operators requires a careful design and application of appropriate algorithms that properly utilize memory. Today's Big Data management systems need the ability to handle large amounts of data similarly, as it is unrealistic to assume that truly big data will fit into memory. In this article, we share our memory management experiences in Apache AsterixDB, an open-source Big Data management software platform that scales out horizontally on shared-nothing commodity computing clusters. We describe the implementation of AsterixDB's memory-intensive operators and their designs related to memory management. We also discuss memory management at the global (cluster) level. We conducted an experimental study using several synthetic and real datasets to explore the impact of this work. We believe that future Big Data management system builders can benefit from these experiences.     

Sensitivity Investigation of SW-B80N80 Nanotube to Polychlorinated Biphenyl-153 (PCB-153): DFT Methods

Polychlorinated biphenyls (PCBs) is one of the most persistent organic pollutants that exist in the atmosphere and can be concentrated in lithosphere and hydrosphere. Because of low biodegradability and lipophilicity, PCBs accumulate in fatty tissues and through oxidative stress could lead to cancers and central nervous system disorders. Currently, degradation of these synthetic pollutants is one of the environmental issues. The aim of this study is to provide a sensor for detection of PCB-153 (PCB-153). Nano boron nitride compounds (B_nN_m) are magic materials with high stability that can be used as a sensor for detection of chlorinated aromatic compounds. In this study, sensitivity of B₈₀N₈₀ as a form of single-walled boron nitride nanotubes (SW-B₈₀N₈₀ nanotube (8,8)) to PCB-153 has been investigated. The PCB-153 is closed to the SW-B₈₀N₈₀ nanotube and electron exchanges between them have been evaluated using density functional calculations by B3LYP/6–31G^* method. The calculation of the electronic properties has shown that SW-B₈₀N₈₀ nanotube is very sensitive to the presence of PCB-153 molecules. The HOMO/LUMO and gap energy (E_g) changes were considerable. Gap energy decreased from 4.214 eV to 2.022 eV during the formation of complex PCB-153-SW-B₈₀N₈₀ nanotube that leads to conversion of PCB-153 into the other products. According to thermodynamic parameter calculation through the IR-DFT method, it is expected that SW-B₈₀N₈₀ nanotube will be a suitable candidate in the elimination of PCB-153, as well as a gas sensor.     

A queuing approach for a tri-objective manufacturing problem with defects: a tuned Pareto-based genetic algorithm

In this research, a manufacturing facility with independent workstations to remanufacture nonconforming products is investigated. Each workstation is first modeled as an M/M/m queuing system with m being a decision variable. Then, a tri-objective integer nonlinear programming models is developed to formulate the problem. The first objective tries to minimize the waiting times of products, while the second one tries to maximize the minimum reliability of machines at the workstations. Since minimization of the waiting times results in using a large number of machines with higher idle times, the third objective is considered to minimize the mean idle time of the machines. The aim is to determine optimal number of machines at each workstation. Since the problem belongs to the class of NP-hard problems, the non-dominated sorting genetic algorithm-II (NSGA-II) is utilized to find Pareto fronts. Because there is no benchmark available in the literature to validate the results obtained, the non-dominated ranked genetic algorithm (NRGA) is used as well. In both algorithms, not only the best operators are selected but also all of their important parameters are calibrated using statistical analysis. The performances of the algorithms are statistically compared using the t test. Besides, the multiple attribute decision-making method of TOPSIS is used to determine the better algorithm. The applicability of the proposed model and the solution algorithms is demonstrated via some illustrative examples.     

Role of parietal and principal gastric mucosa cells in the phenomenon of concentration of aluminum and indium

The subcellular behavior of aluminum and indium, used in medical and industrial fields, was studied in the gastric mucosa and the liver after their intragastric administration to rats, using, two of the most sensitive methods of observation and microanalysis, the transmission electron microscopy, and the secondary ion mass spectrometry. The ultrastructural study showed the presence of electron dense deposits, in the lysosomes of parietal and principal gastric mucosa cells but no loaded lysosomes were observed in the different studied hepatic territories. The microanalytical study allowed the identification of the chemical species present in those deposits as aluminum or indium isotopes and the cartography of their distribution. No modification was observed in control rats tissues. In comparison to previous studies describing the mechanism of aluminum concentration in the gastric mucosa and showing that this element was concentrated in the lysosomes of fundic and antral human gastric mucosa, our study provided additional informations about the types of cells involved in the phenomenon of concentration of aluminum and indium, which are the parietal and the principal cells of the gastric mucosa. Our study demonstrated that these cells have the ability to concentrate selectively aluminum and indium in their lysosomes, as a defensive reaction against intoxication by foreign elements.     

Effect of Impeller Spacing on the Flow Field of Yield-Pseudoplastic Fluids Generated by a Coaxial Mixing System Composed of Two Central Impellers and an Anchor

The three-dimensional flow field generated by a coaxial mixer composed of double Scaba impellers and an anchor in the mixing of the xanthan gum solution, a non-Newtonian yield-pseudoplastic fluid was investigated using the computational fluid dynamics (CFD) technique. The mixing time measurements were performed by a non-intrusive flow visualization technique called electrical resistance tomography (ERT). To evaluate the influence of the impeller spacing on the hydrodynamics of the double Scaba-anchor coaxial mixer, the upper impeller submergence was set to 0.140?m while the lower impeller clearance and the spacing between two central impellers were changed within a wide range. The experiments and simulations were conducted for both co-rotating and counter-rotating regimes at different impeller spacing. The analysis of the collected data with respect to the power number, flow number, mixing time, and pumping effectiveness proved that the co-rotating mode had superiority over the counter-rotating regime. Furthermore, the impact of the impeller spacing in the co-rotating mode was assessed with respect to the mixing time, power number, and mixing energy. The results demonstrated that a coaxial mixer with the impeller spacing of almost equal to the central impeller diameter (C₂?=?0.175?m) and the impeller clearance of C₃?=?0.185?m was the most efficient configuration compared to the other cases. Additionally, the influence of the impeller spacing on the flow pattern was assessed in terms of the radial velocity, tangential velocity, axial velocity, shear rate, and apparent viscosity profiles. When the impeller spacing (C₂) was varied, the merging flow and parallel flow patterns were observed.     

Rheological characterization of polypropylene/poly(ethylene-<Emphasis Type="Italic">co</Emphasis>-propylene) in-reactor blends synthesized under different polymerization conditions

In-reactor blends of polypropylene/poly(ethylene-co-propylene) with complex microstructure, synthesized through different polymerization procedures; two-step (one homopolymerization and one copolymerization under high ethylene concentration) and three-step (with an additional copolymerization step under low ethylene concentration), were characterized by rheological measurements. The effects of a change in the polymerization process on the types and amounts of block copolymers in the blends were evaluated using small amplitude oscillation rheometry in the linear viscoelastic region. The Palierne model in its complete form was employed to model the rheological behavior of the blends. For this analysis the reactor products were separated into xylene cold insoluble (XCI) and xylene cold soluble fractions. Besides, another two copolymer fractions at 80 and 100 °C, which are crystallizable copolymer fractions and contain block copolymers rich in polyethylene and polypropylene, respectively, were separated from XCI fraction by xylene using temperature gradient elution fractionation method. Considering all copolymer fractions as dispersed and the remained fraction (mostly polypropylene) as matrix phase, it was shown that the rheological properties of the blends could not be predicted by Palierne model. It was found that only by considering part of block copolymer fractions having long polypropylene sequences along with polypropylene homopolymer as one phase, the rheological properties of the blends could be predicted by Palierne model. By rheological modeling, it was confirmed that the amounts of copolymers with long polypropylene sequences which are miscible with the matrix are higher in the case of three-step blends and also the elasticity of three-step polymerized blends is higher than two-step polymerized blends.     

Catalytic performance of CeAPSO-34 molecular sieve with various cerium content for methanol conversion to olefin

A series of CeAPSO-34s with various cerium contents was synthesized and characterized by multiple techniques such as XRD, SEM, BET, ²⁹Si MAS NMR, NH₃-TPD and CO₂-TPD. NH₃-TPD spectra showed that a number of acid sites, especially those of strong acidity, is reduced with the increasing of Ce incorporation. Incorporation of metal ions gave rise to more silica-islands in the CeAPSO-34 framework. CO₂-TPD showed that basic sites on the surface of modified samples are due to the presence of Ce-containing species incorporation into the framework of CeAPSO-34 molecular sieves. The performance of the catalysts was studied in methanol to olefin reactions at 425 °C under the atmospheric pressure. The results showed that the incorporation of cerium ions had great effects on the structure and acidity of the molecular sieves. All SAPO-34 and MeAPSO-34 molecular sieves were the very active and selective catalyst for light olefins production. Cerium incorporation improved the catalyst lifetime and favored the ethylene and propylene generation. However, an excess Ce content resulted in an inferior catalytic performance and stability. Therefore, there existed optimal cerium content for a specific SAPO-34.     

Novel functionalized monomers based on kojic acid: snythesis,characterization, polymerization and evalution of antimicrobial activity

Two novel acrylate monomers, [5-(benzyloxy)-4-oxo-4H-pyran-2-yl]methyl acrylate and {1-[(5-(benzyloxy)-4-oxo-4H-pyran-2-yl)methyl]-1,2,3-triazol-4-yl}methyl acrylate were synthesized by the reaction of 5-benzyloxy-2-(hydroxymethyl)-4H-pyran-4-one and 5-(benzyloxy)-2-{[4-(hydroxymethyl)-1,2,3-triazol-1-yl]methyl}-4H-pyran-4-one with acryloyl chloride in the presence of triethylamine, respectively. These monomers were polymerized using 2,2^′-azobisisobutyronitrile (AIBN) as the initiator in N,N-dimethylformamide:14-dioxane (10:1) solution. The thermal behavior of the polymers was investigated by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The synthesized compounds were evaluated for their antibacterial and antifungal activites aganist bacteria and fungi using the disk diffusion method. The results indicated that some of these compounds demonstrated moderate to good antibacterial and antifungal activities.     

Structural Performance of RC Beams Poststrengthened with Carbon, Aramid, and Glass FRP Systems

The use of fiber-reinforced polymers (FRPs) to poststrengthen concrete structures started to be investigated in the mid-1970s and today is widely recognized as an attractive technique to be used in civil structures, especially when aggressive environments prevent the use of materials that are susceptible to corrosion, such as steel. Different FRP poststrengthening techniques have been developed and applied in existing structures, aiming to increase their load capacity. Most FRP systems used nowadays consist of carbon fibers embedded in epoxy matrix. Regardless of the advantages and the good results achieved using carbon fiber-reinforced polymers, some new possibilities, such as the use of prestressing and lower cost fiber materials, are being analyzed in an attempt to provide viable alternatives for a more efficient, safe, and rational use of FRP systems. The main purpose of the present work was to make a comparative analysis of the behavior of reinforced concrete beams poststrengthened with carbon, aramid, and glass FRP subjected to static loading tests. Experimental results were evaluated against theoretical ones obtained through an analytical model that considers a trilinear behavior for the load versus displacement curves. The experimental results indicate that all FRP systems applied have appropriate structural performance for use in poststrengthening applications of RC. The choice of the more suitable system would, therefore, be strongly influenced by circumstances regarding cost limitations and level of reinforcement required.