Multi-Objective Surface Water Resource Management Considering Conflict Resolution and Utility Function Optimization

In the present research, a multi-objective model is developed for surface water resource management in the river basin area which is connected to the lake. This model considers different components of sustainable water resource management including economic, social and environmental aspects, and simultaneously tries to resolve conflicts between different stakeholders by means of non-symmetric Nash bargaining, which is linked to the multi-objective optimization method. This study proposes a new methodology to improve Nash Conflict Resolution through finding the optimum degree of the utility function. The proposed model is examined in the Zarrineh River basin in Iran. The results show that the amount of available resources or volume of reservoirs play a significant role in determining the optimal degree of the utility function and efficiency of the proposed method in such a way that the higher amount of resources or the larger reservoirs will result in the higher optimal degree of the utility function. In the proposed multi-objective model, two different amounts of surface water inflow are considered. The first assumed amount is the long-term average flow rate and the second one is equal to 80% of the first mode, which is reduced based on the estimated impacts of climate changes. This multi-objective allocation model could supply 100 and 97.5% of the environmental demand of Lake Urmia in the first and second situations, respectively.     

Synthesis,characterization and thermal dissociation of 2‐butoxyethanol‐blocked diisocyanates and their use in the synthesis of isocyanate‐terminated prepolymers

A series of blocked diisocyanates has been synthesized from toluene diisocyante (TDI), isophorone diisocyanate (IPDI), hexamethylene diisocyanate (HDI), 4,4′‐diphenylmethane diisocyanate (MDI) and 2‐butoxyethanol. The synthesis of blocked diisocyanate adducts was confirmed by Fourier transform infrared, ¹H NMR, electron impact mass spectrometry and nitrogen analysis. Differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA) and carbon dioxide evolution were used to determine the minimum de‐blocking temperatures. De‐blocking temperatures determined by these three techniques were found to be in the order DSC > TGA > CO₂ evolution. The effect of different metal catalysts on thermal de‐blocking reaction of the blocked diisocyanates was studied, using the carbon dioxide evolution method. It was found that iron(III) oxide has the maximum catalytic activity on de‐blocking. The solubility of the blocked diisocyanate adducts was determined in different solvents. The study revealed that at 30 °C blocked IPDI and HDI adducts show better solubility than adducts based on TDI and MDI. Isocyanate‐terminated prepolymers of blocked diisocyanates and hydroxyl‐terminated polybutadiene (HTPB) were prepared. The storage stability and gelation times of the prepolymers were studied. Results showed that all the diisocyanate‐HTPB compositions are stable at 50 °C for more than three months. However, aliphatic diisocyanate‐HTPB compositions require greater gelation time than aromatic diisocyanate‐HTPB compositions at their respective de‐blocking temperatures. Copyright © 2007 Society of Chemical Industry     

PSO-DS: a scheduling engine for scientific workflow managers

Cloud computing, an important source of computing power for the scientific community, requires enhanced tools for an efficient use of resources. Current solutions for workflows execution lack frameworks to deeply analyze applications and consider realistic execution times as well as computation costs. In this study, we propose cloud user–provider affiliation (CUPA) to guide workflow’s owners in identifying the required tools to have his/her application running. Additionally, we develop PSO-DS, a specialized scheduling algorithm based on particle swarm optimization. CUPA encompasses the interaction of cloud resources, workflow manager system and scheduling algorithm. Its featured scheduler PSO-DS is capable of converging strategic tasks distribution among resources to efficiently optimize makespan and monetary cost. We compared PSO-DS performance against four well-known scientific workflow schedulers. In a test bed based on VMware vSphere, schedulers mapped five up-to-date benchmarks representing different scientific areas. PSO-DS proved its efficiency by reducing makespan and monetary cost of tested workflows by 75 and 78%, respectively, when compared with other algorithms. CUPA, with the featured PSO-DS, opens the path to develop a full system in which scientific cloud users can run their computationally expensive experiments.     

Interface evolution in the platelet-like SiC@C and SiC@SiO<Subscript>2</Subscript> monocrystal nanocapsules

Carbon-coated SiC@C nanocapsules (NCs) with a hexagonal platelet-like morphology were fabricated by a simple direct current (DC) arc-discharge plasma method.The SiC@C NCs were monocrystalline,120-150 nm in size,and approximately 50 nm thick.The formation of the as-prepared SiC@C NCs included nucleation of truncated octahedral SiC seeds and subsequent anisotropic growth of the seeds into hexagonal nanoplatelets in a carbon-rich atmosphere.The disordered carbon layers on the SiC@C NCs were converted into SiO2 shells of SiC@SiO2 NCs by heat treatment at 650 ℃ in air,during which the shape and inherent characteristics of the crystalline SiC core were obtained.The interface evolution from carbon to SiO2 shells endowed the SiC@SiO2 NCs with enhanced photocatalytic activity due to the hydrophilic and transparent nature of the SiO2 shell,as well as to the photosensitive SiC nanocrystals.The band gap of the nanostructured SiC core was determined to be 2.70 eV.The SiC@SiO2 NCs degraded approximately 95％ of methylene blue in 160 min under visible light irradiation.     

The immunologic identification of abnormal hemoglobins

Guinea pig antisera against human hemoglobin contain antibodies to multiple antigenic determinants. Hemoglobin variants having single amino acid substitutions affecting these determinants are recognized as antigenically deficient in a radioimmunoassay system. The multivalent antisera may be made more selective by appropriate absorption with hemoglobin variants. Three such antisera containing antibodies specific, respectively, for the beta-chain of Hb A, Hb S, and Hb C are described. They can differentiate among the hemoglobins of individuals who possess these variants alone or in any paired combination. Their discriminating ability is not hindered by the presence of 1,000-fold concentrations of Hb F and may therefore be extended to the early prenatal diagnosis of sickling disorders. The antisera described also detect several other variants of Hb A. The approximate location of the substitution in variants so detected can be determined by a complementation test. This is based on the finding that two antigenically deficient hemoglobins will complement each other in mixture provided their amino acid substitutions involve different determinants.     

Application of Artificial Intelligent Tools to Modeling of Glucosamine Preparation from Exoskeleton of Shrimp

The objective of this study was to forecast and optimize the glucosamine production yield from chitin (obtained from Persian Gulf shrimp) by means of genetic algorithm (GA), particle swarm optimization (PSO), and artificial neural networks (ANNs) as tools of artificial intelligence methods. Three factors (acid concentration, acid solution to chitin ratio, and reaction time) were used as the input parameters of the models investigated. According to the obtained results, the production yield of glucosamine hydrochloride depends linearly on acid concentration, acid solution to solid ratio, and time and also the cross-product of acid concentration and time and the cross-product of solids to acid solution ratio and time. The production yield significantly increased with an increase of acid concentration, acid solution ratio, and reaction time. The production yield is inversely related to the cross-product of acid concentration and time. It means that at high acid concentrations, the longer reaction times give lower production yields. The results revealed that the average percent error (PE) for prediction of production yield by GA, PSO, and ANN are 6.84, 7.11, and 5.49%, respectively. Considering the low PE, it might be concluded that these models have a good predictive power in the studied range of variables and they have the ability of generalization to unknown cases.     

Studies of Novel Heterocyclic Insensitive High Explosive Compounds: Pyridines,Pyrimidines, Pyrazines and Their Bicyclic Analogues

The rationale behind using heterocyclic compounds [1], particularly nitrogen heterocycles, as higher energy insensitive high explosives is discussed, including the potential advantages compared with carbocyclic compounds. The types of functional groups used to impart energy to heterocyclic nuclei, whilst maintaining insensitivity, and methodologies for their introduction, are covered. The latter include nitration (by conventional and clean synthetic methods), amination, and oxidation (on ring heteroatoms and of exocyclic amino groups). Strategies for maximising the energetic content of a given heterocyclic nucleus are also examined. The syntheses of specific examples at QinetiQ are described, based on the following nuclei: pyridine, pyrimidine, pyrazine, quinoxaline, quinazoline, pteridine and purine. Strategies for obtaining the desired amino‐nitro derivatives and their heterocyclic N‐oxides are outlined. Optimisation of the synthetic routes for several candidates is discussed. The physical, explosive and thermal properties of the more successful candidates are described, with suggestions for their potential application in military stores.     

Ile-1781-Leu and Asp-2078-Gly Mutations in ACCase Gene,Endow Cross-resistance to APP,CHD, and PPZ in Phalaris minor from Mexico

Herbicides that inhibit acetyl coenzyme A carboxylase (ACCase) are commonly used in Mexico to control weedy grasses such as little seed canarygrass (Phalaris minor). These herbicides are classified into three major families (ariloxyphenoxypropionates (APP), cyclohexanodiones (CHD), and, recently, phenylpyrazolines (PPZ)). In this work, the resistance to ACCase (APP, CHD, and PPZ) inhibiting herbicides was studied in a biotype of Phalaris minor (P. minor) from Mexico, by carrying out bioassays at the whole-plant level and investigating the mechanism behind this resistance. Dose-response and ACCase in vitro activity assays showed cross-resistance to all ACCase herbicides used. There was no difference in the absorption, translocation, and metabolism of the ¹⁴C-diclofop-methyl between the R and S biotypes. The PCR generated CT domain fragments of ACCase from the R biotype and an S reference were sequenced and compared. The Ile-1781-Leu and Asp-2078-Gly point mutations were identified. These mutations could explain the loss of affinity for ACCase by the ACCase-inhibing herbicides. This is the first report showing that this substitution confers resistance to APP, CHD, and PPZ herbicides in P. minor from Mexico. The mutations have been described previously only in a few cases; however, this is the first study reporting on a pattern of cross-resistance with these mutations in P. minor. The findings could be useful for better management of resistant biotypes carrying similar mutations.     

A comprehensive study on wastewater treatment using photo-impinging streams reactor: Continuous treatment

The degradation of phenol was investigated in a continuous flow impinging streams system. In the first step, statistical experimental designs were used to optimize the process of phenol degradation in a photo-impinging streams reactor. The more important factors affecting phenol degradation (p<0.05) were screened by a two-level Plackett-Burman design. Four of the latter parameters, namely phenol concentration, catalyst loading, pH and slurry flow rate, were selected for final process optimization, applying central composite design (CCD). The predicted data showed that the maximum removal efficiency of phenol (99%) could be obtained under the optimum operating conditions (phenol concentration=50 mg l ^?1, catalyst loading=2.1 g l ^?1, pH 6.2 and slurry flow rate=550ml min^?1). These predicted values were then verified by certain validating experiments. A good correlation was observed between the predicted data and those determined by the experimental study. This may confirm the validity of the statistical optimum strategy. Finally, continuous degradation of phenol was performed, and the results indicated a higher efficiency and an increased performance capability of the present reactor in comparison with the conventional processes.