Development of green extraction process to produce antioxidant-rich extracts from purple coneflower

The present study was conducted to develop subcritical water extraction (SWE) of Echinacea purpurea flowers. The influence of temperature and extraction time on quality of extracts considering total phenols content, total flavonoids content, antioxidant capacity and extraction yield, was determined. Optimized extraction parameters for maximised investigated responses were as follows: 147.56 °C and 8.43 min. The experimental values agreed with the values predicted, thus indicating the adequacy of central composite experimental design for modelling the SWE of bioactive compounds from E. purpurea. Results of the study also highlighted the potential application of E. purpurea subcritical water extracts as a source of valuable bioactive compounds.     

Dynamic probe of ZnTe(110) surface by scanning tunneling microscopy

The reconstructed surface structure of the II–VI semiconductor ZnTe (110), which is a promising material in the research field of semiconductor spintronics, was studied by scanning tunneling microscopy/spectroscopy (STM/STS). First, the surface states formed by reconstruction by the charge transfer of dangling bond electrons from cationic Zn to anionic Te atoms, which are similar to those of IV and III–V semiconductors, were confirmed in real space. Secondly, oscillation in tunneling current between binary states, which is considered to reflect a conformational change in the topmost Zn–Te structure between the reconstructed and bulk-like ideal structures, was directly observed by STM. Third, using the technique of charge injection, a surface atomic structure was successfully fabricated, suggesting the possibility of atomic-scale manipulation of this widely applicable surface of ZnTe.     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

An optimization model for evaluating the economic impact of availability and maintenance notions during the synthesis and design of a power plant

In this paper, we introduce an optimization strategy in order to comprehensively quantify the impact of availability and maintenance notions during the early stages of synthesis and design of a new natural gas combined cycle power plant. A detailed state-space approach is thoroughly discussed, where influence of maintenance funds on each component's repair rate is directly assessed.In this context, analysis of the reliability characteristics of the system is centered at two designer-adopted parameters, which largely influence the obtained results: the number of components which may fail independently at the same time, and the number of simultaneous failure/repair events.Then, optimal solutions are evaluated as the availability-related parameters and the amount of resources assigned for maintenance actions are varied across a wide range of feasible values, which enable obtaining more accurate and detailed estimations of the expected economic performance for the project when compared with traditional economic evaluation approaches.     

CO压缩机优化运行总结

为确保原CO压缩机在净化系统升级改造项目实施后能安全稳定运行,采取了流程优化、工艺条件论证、设备缺陷排查、联锁指标重新确定等一系列措施。改造措施实施后,CO压缩机出口压力稳定在3.23 MPa左右,有效缓解了前后工序压力波动对压缩机稳定运行的影响,各级水冷却器的换热效果也得到了较大的改善。     

红岭矿18线南西翼通风系统技术改造

针对矿山18线南西翼矿体开采过程中存在的通风系统不完善、风量欠缺、污风无法及时排出等问题，运用风压平衡原理、网络优化技术、机站优化技术以及计算机网络模拟技术展开研究，拟定了3种可行的通风方案。经技术经济比较，确定了新掘18线905～855 m回风井（1.5 m），保留该井905 m 水平回风机站，并在855 m 水平新设1台K45 6 №12风机（18.5 kW）方案。数值模拟结果表明：18线南西翼通风系统总风量达到20.5 m3/s，井下风流的可调性和稳定性增强，为矿山的安全生产提供了有力保障。     

A new decomposition based evolutionary algorithm with uniform designs for many-objective optimization

For many-objective optimization problems, how to get a set of solutions with good convergence and diversity is a difficult and challenging work. In this paper, a new decomposition based evolutionary algorithm with uniform designs is proposed to achieve the goal. The proposed algorithm adopts the uniform design method to set the weight vectors which are uniformly distributed over the design space, and the size of the weight vectors neither increases nonlinearly with the number of objectives nor considers a formulaic setting. A crossover operator based on the uniform design method is constructed to enhance the search capacity of the proposed algorithm. Moreover, in order to improve the convergence performance of the algorithm, a sub-population strategy is used to optimize each sub-problem. Comparing with some efficient state-of-the-art algorithms, e.g., NSGAII-CE, MOEA/D and HypE, on six benchmark functions, the proposed algorithm is able to find a set of solutions with better diversity and convergence.     

Silver-plated polyamide fabrics with high electromagnetic shielding effectiveness performance prepared by in situ reduction of polydopamine and chemical silvering

In this article, the silver-plated polyamide fabrics (SPPAFs) with high electroconductibility and shielding effectiveness were fabricated by using in situ reduction of polydopamine and chemical silvering. The effects of SPPAFs dopamine (C₈H₁₁O₂N) and silver nitrate (AgNO₃) concentration on surface resistivity and electromagnetic interference shielding effectiveness were studied. The results showed that the surface resistivity of SPPAFs can reach a minimum value of 0.06 ± 0.014 Ω cm⁻¹, when C₈H₁₁O₂N concentration is 4 g L⁻¹ and the AgNO₃ concentration is 120 g L⁻¹. The shielding effectiveness of SPPAFs in the wide frequency range of 10–3000 MHz increases with the increase in the concentration of AgNO₃, and increases first and stabilizes afterward with increasing C₈H₁₁O₂N concentration. When the concentration of C₈H₁₁O₂N and AgNO₃ is 3 and 120 g L⁻¹, respectively, mean shielding effectiveness values in the low-, medium-, and high-frequency bands are 71.3, 73.8, and 76.1 dB, respectively. Moreover, the mean shielding effectiveness values is 83.79 dB in the frequency range of 1.2–2.3 GHz. The dominant shielding mechanism of SPPAFs is the reflected electromagnetic waves and the absorption shielding effectiveness is less than 2 dB. The average electromagnetic shielding values of SPPAFs are above 67 dB after 16 weeks of storage, when C₈H₁₁O₂N concentration is 4 g L⁻¹ and the AgNO₃ concentration is 80 and 100 g L⁻¹. The prepared SPPAFs show promising applications in military textiles and smart wearable clothing. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48227.     

Global optimization for power dispatch problems based on theory of moments

Non-convex of an optimal power dispatch problem makes it difficult to guarantee the global optimum. This paper presents a convex relaxation approach, called the Moment Semidefinite Programming (MSDP) method, to facilitate the search for deterministic global optimal solutions. The method employs a sequence of moments, which can linearize polynomial functions and construct positive semidefinite moment matrices, to form an SDP convex relaxation for power dispatch problems. In particular, the rank of the moment matrix is used as a sufficient condition to ensure the global optimality. The same condition can also be leveraged to estimate the number of global optimal solution(s). This method is effectively applied to {0,1}-economic dispatch (ED) problems and optimal power flow (OPF) problems. Simulation results showed that the MSDP method is capable of solving {0,1}-ED problems with integer values directly, and is able to identify if more than one global optimal solutions exist. In additional, the method can obtain rank-1 moment matrices for OPF’s counterexamples of existing SDP method, this ensures the global solution and overcomes the problem that existing SDP method cannot meet the rank-1 condition sometimes.     

Kariya (Hildegardia barteri) seed oil extraction: comparative evaluation of solvents,modeling, and optimization techniques

In this work, the effects of solid/solvent ratio (0.10–0.25?g/ml), extraction time (3–8?h), and solvent type (n-hexane, ethyl acetate, and acetone) together with their shared interactions on Kariya seed oil (KSO) yield were investigated. The oil extraction process was modeled via response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) while the optimization of the three input variables essential to the oil extraction process was carried out by genetic algorithm (GA) and RSM methods. The low mean relative percent deviation (MRPD) of 0.94–4.69% and high coefficient of determination (R²) > 0.98 for the models developed demonstrate that they describe the solvent extraction process with high accuracy in this order: ANFIS, ANN, and RSM. The best operating condition (solid/solvent ratio of 0.1?g/ml, extraction time of 8?h, and acetone as solvent of extraction) that gave the highest KSO yield (32.52?wt.%) was obtained using GA-ANFIS and GA-ANN. Solvent extraction efficiency evaluation showed that ethyl acetate, n-hexane, and acetone gave maximum experimental oil yields of 19.20?±?0.28, 25.11?±?0.01, and 32.33?±?0.04?wt.%, respectively. Properties of the KSO varied based on the type of solvent used. The results of this work showed that KSO could function as raw material in both food and chemical industries.