Multiobjective Calibration of Reservoir Water Quality Modeling Using Multiobjective Particle Swarm Optimization (MOPSO)

Water resource management encounters large variety of multi objective problems that require powerful optimization tools in order to fully characterize the existing tradeoffs between various objectives that can be minimizing difference between forecasted physical, chemical, and biological behaviors of model and measured data. Calibration of complex water quality models for river and reservoir systems may include conflicting objectives addressed by various combinations of interacting calibration parameters. Calibration of the two dimensional CE-QUAL-W2 water quality and hydrodynamic model is an excellent example where the model must be calibrated for both hydrodynamic and water quality behavior. The aim of the present study is to show how multiobjective particle swarm optimization (MOPSO) can be implemented for automatic calibration of water quality and hydrodynamic parameters of a 2-dimensional, hydrodynamic, and water quality models (CEQUAL-W2) to predict physical, chemical, and biological behaviors of a water body, and then focus on a relevant case study. So MOPSO is utilized to generate Pareto optimal solutions for two conflicting calibration objectives. A combined measure of thermal and reservoir water level is considered as the first calibration objective. The second objective is formulated to forecast the best physical, chemical, and biological behavior of the model. Realizing the strong interactions between water quality and hydrodynamic issues of water bodies and their dependencies on the same set of calibration parameters, the proposed multiobjective approach may provide a wide version of all possible calibration solutions for better decision making to select best solution from pareto front.     

Volatile Compounds of Roasted and Steamed Malaysian Tropical Almond Nut (Terminalia catappa L.)

The flavor extract components contributing to the characteristic aroma notes of roasted and steamed tropical almond nuts were investigated by means of gas chromatography-olfactometry and mass spectrometry of solvent extracts. Roasting and steaming data revealed all of the main classes of compounds commonly listed as thermally generated flavors in oily seeds. A total of 72 volatile compounds were identified in the sample from roasted nuts; among these were 27 hydrocarbons, 12 aldehydes, 12 ketones, 8 acids, 4 esters, 3 alcohols, 3 furans, and a pyrazine. The steamed nuts, however, yielded 66 peaks from which 63 volatile compounds were identified (22 hydrocarbons, 9 aldehydes, 9 ketones, 9 esters, 4 acids, 9 alcohols, and a pyrazine). The small number of aldehydes, ketones, pyrazine, and alcohols identified are the ones most likely to contribute to the aroma of the nuts.     

Diluted Air Combustion and NOx Emission in a HiTAC Furnace

CFD modeling of NOx emission via N₂O-intermediate mechanism was developed to predict the NOx formation in an experimental furnace equipped with high temperature air combustion (HiTAC) system. The good agreement between the predicted and measured results illustrates the superiority of using a N₂O-intermediate model in prediction of NOx emission during low peak temperature, which happens in HiTAC systems. Moreover, the CFD and measured results show that the flame volume as well as NOx emission significantly depends on temperature and oxygen concentration. Lower NOx emission was experimentally and numerically obtained at lower input oxygen concentration conditions.     

Two-Variable Refined Plate Theory for Thermoelastic Bending Analysis of Functionally Graded Sandwich Plates

The thermoelastic bending analysis of functionally graded sandwich plates using the two-variable refined plate theory is presented in this paper. Unlike any other theory, the number of unknown functions involved is only four, as against five in case of other shear deformation theories. The theory presented is variationally consistent, has strong similarity with classical plate theory in many aspects, does not require shear correction factor, and gives rise to transverse shear stress variation such that the transverse shear stresses vary parabolically across the thickness satisfying shear stress free surface conditions. The sandwich plate faces are assumed to have isotropic, two-constituent material distribution through the thickness, and the modulus of elasticity, Poisson's ratio of the faces, and thermal expansion coefficients are assumed to vary according to a power law distribution in terms of the volume fractions of the constituents. The core layer is still homogeneous and made of an isotropic ceramic material. Several kinds of sandwich plates are used taking into account the symmetry of the plate and the thickness of each layer. The influences played by the transverse shear deformation, thermal load, plate aspect ratio, and volume fraction distribution are studied. Numerical results for deflections and stresses of functionally graded metal–ceramic plates are investigated. It can be concluded that the proposed theory is accurate and simple in solving the thermoelastic bending behavior of functionally graded plates.     

Modeling of conjugated heat transfer in a thick walled enclosure filled with nanofluid

The objective of this paper is to investigate the conjugated heat transfer in a thick walled cavity filled with copper-water nanofluid. The analysis uses a two-dimensional rectangular enclosure under conjugated convective-conductive heat transfer conditions and considers a range of Rayleigh numbers. The enclosure was subjected to a constant and uniform heat flux at the left thick wall generating a natural convection flow. The thicknesses of the other boundaries are assumed to be zero. The right wall is kept at a low constant temperature while the horizontal walls are assumed to be adiabatic. A moveable divider is located at the bottom wall of the cavity. The governing equations are derived based on the conceptual model in the Cartesian coordinate system. The study has been carried out for the Rayleigh number in the range of 10⁵ ≤ Ra ≤ 10⁸, and for the solid volume fraction at 0 ≤ ? ≤ 0.05. Results are presented in the form of streamlines, isotherms, average Nusselt number and input heat absorption by the nanofluid. The effects of solid volume fraction of nanofluids, the location of the divider and also the value of the ambient convective heat transfer coefficient on the hydrodynamic and thermal characteristics of flow have been analyzed. An increase in the average Nusselt number was found with the solid concentration for the whole range of Rayleigh number. In addition, results show that the position of the divider and the ambient convective heat transfer coefficient have a considerable effect on the heat transfer enhancement.     

A Framework for Ground Water Management Based on Bayesian Network and MCDM Techniques

Groundwater resources are steadily subjected to increasing water demands. The aquifers are considered as the most accessible source of fresh water. In recent years, they have been faced with severe water withdrawal in arid and semi-arid countries like Iran and thus some aquifers was considered as forbidden aquifers that it means the water withdrawal from these aquifers is unauthorized. Given a critical situation, groundwater resources management in the form of tools such as monitoring the level of the aquifers and developing the restoring scenarios is essential. Therefore, for this purpose, a framework has been developed based on prediction of groundwater level using Bayesian Networks (BNs) model. Furthermore, Multi Criteria Decision Making methods (MCDM) techniques proposed and employed for ranking of proposed groundwater management scenarios. This framework was evaluated for restoring the Birjand aquifer in Iran in different hydrological conditions. A probabilistic Dynamic BN was proposed for groundwater level prediction under uncertainties. After analyzing the obtained results, the applicable short term scenarios for groundwater management as well as appropriate economic, social and technical criteria were defined for decision making procedure. Then, using elicitation of decision makers’ opinions on the relative importance and performance of criteria, SAW, TOPSIS and PROMETHEE-II techniques were applied to rank the scenarios and the obtained results were aggregated by Borda method for final ranking of the scenarios. Lastly, the final results demonstrates the capability of the proposed framework for groundwater resources planning and management which can be employed for reducing the risk of aquifer level declining.     

红枣色素的提取及稳定性的研究

本文对红枣色素的提取方法和色素的基本性质进行了研究。通过研究发现，所选用的16种不同的提取溶液当中，红枣色素在以50％（pH3）的乙醇水溶液提取时，效果最好，色素的最大吸收峰在320nm处；日光、温度、和大多数金属离予，对这种色素的稳定性无太大的影响，这种色素的耐糖性和耐光性很好。红枣色素的pH稳定性无论在酸性或在碱性条件下都很稳定。红枣色素稳定性不受人体所需的微量元素Ca^2＋、Na^＋、Fe^2＋、K^＋、Mg^2＋、Mn^2＋、Zn^2＋和Fe^3＋的影响。温度变化（20～100℃）也对色素稳定性几乎无影响。根据研究结果可以初步确定，红枣色素具备了作为天然色素使用的最基本的性能，可开发利用。     

野西瓜苗种子油理化性质和脂肪酸成分分析

本文采用索氏提取法提取野西瓜苗种子油,并测定了野西瓜苗种子油的常见理化性质,同时采用GC-MS法分析了野西瓜苗种子油中脂肪酸成分.结果表明,野西瓜苗种子油的提取率为16%,折光率为1.4741,碘价为126.9gI/100g,酸价为6.73mg（KOH）/g,皂化价为185mg（KOH）/g.GC-MS分析共确定了10种脂肪酸,主要是亚油酸、棕榈酸、油酸、硬脂酸,其中亚油酸含量为63.61%,棕榈酸含量为16.72%,油酸含量为12.30%,硬脂酸含量为2.23%,不饱和脂肪酸总含量为79.11%.     

A robust unified approach to analyzing methylation and gene expression data

Microarray technology has made it possible to investigate expression levels, and more recently methylation signatures, of thousands of genes simultaneously, in a biological sample. Since more and more data from different biological systems or technological platforms are being generated at an incredible rate, there is an increasing need to develop statistical methods that are applicable to multiple data types and platforms. Motivated by such a need, a flexible finite mixture model that is applicable to methylation, gene expression, and potentially data from other biological systems, is proposed. Two major thrusts of this approach are to allow for a variable number of components in the mixture to capture non-biological variation and small biases, and to use a robust procedure for parameter estimation and probe classification. The method was applied to the analysis of methylation signatures of three breast cancer cell lines. It was also tested on three sets of expression microarray data to study its power and type I error rates. Comparison with a number of existing methods in the literature yielded very encouraging results; lower type I error rates and comparable/better power were achieved based on the limited study. Furthermore, the method also leads to more biologically interpretable results for the three breast cancer cell lines.     

Combined cross-linking treatments of bovine serum albumin gel beadlets for controlled-delivery of caffeine

Combined cross-linking agents (CCLA) of microbial transglutaminase (MTgase) and ribose were applied during production of bovine serum albumin gels via incubation and heating treatment, respectively. CCLA produced stronger gels with lower protein solubility in disruptive solvents (1% sodium dodecyl sulphate plus 1% β-mercaptoethanol) as compared to BSA gels (BSA/Control) or gels produced using single cross-linking agents (SCLA) of MTGase or ribose. The gels were then converted into dried beadlets containing caffeine following a freeze-drying process. In-vitro controlled-release of caffeine and swelling ratio studies of the beadlets in artificial saliva or simulated gastric fluid indicated that CCLA beadlets had the slowest release of caffeine and the lowest swelling ratio as compared to other beadlets. Scanning electron microscopy (SEM) data suggested that the improved release and the lower swelling ratio were mainly due to the denser network formed within the CCLA beadlets that had restricted the diffusion of caffeine and hampered the enzymatic breakdown of the matrix. The additional protein cross-linkings formed as a result of MTgase incubation and ribose-induced Maillard reaction could provide a delay action in releasing caffeine that potentially extend the duration of the action of the drug during ingestion.