Design-Operation of Multi-Hydropower Reservoirs: HBMO Approach

To illustrate and test the applicability and performance of the innovative honey-bee mating optimization (HBMO) algorithm in highly non-convex hydropower system design and operation, two problems are considered: single reservoir and multi-reservoir. Both hydropower problems are formulated to minimize the total present net cost of the system, while achieving the maximum possible ratio for generated power to installed capacity. The single hydropower reservoir problem is approached by the developed algorithm in 10 different runs. The first feasible solution was generated initially and later improved significantly and solutions converged to a near optimal solution very rapidly. In the application of the proposed algorithm to a five-reservoir hydropower system with 48 periods and a total of 230 decision variables, in early mating flights, the first feasible solution was identified and the results converged to a near optimal solution in later mating flights. In the case of the multi-reservoir problem, an efficient gradient-based nonlinear-programming solver (LINGO 8.0) failed to find a feasible solution and for the single hydropower reservoir design problem it performed much worse than the proposed algorithm.     

Protein Kinase C as a Therapeutic Target in Non-Small Cell Lung Cancer

Driver-directed therapeutics have revolutionized cancer treatment, presenting similar or better efficacy compared to traditional chemotherapy and substantially improving quality of life. Despite significant advances, targeted therapy is greatly limited by resistance acquisition, which emerges in nearly all patients receiving treatment. As a result, identifying the molecular modulators of resistance is of great interest. Recent work has implicated protein kinase C (PKC) isozymes as mediators of drug resistance in non-small cell lung cancer (NSCLC). Importantly, previous findings on PKC have implicated this family of enzymes in both tumor-promotive and tumor-suppressive biology in various tissues. Here, we review the biological role of PKC isozymes in NSCLC through extensive analysis of cell-line-based studies to better understand the rationale for PKC inhibition. PKC isoforms α, ε, η, ι, ζ upregulation has been reported in lung cancer, and overexpression correlates with worse prognosis in NSCLC patients. Most importantly, PKC isozymes have been established as mediators of resistance to tyrosine kinase inhibitors in NSCLC. Unfortunately, however, PKC-directed therapeutics have yielded unsatisfactory results, likely due to a lack of specific evaluation for PKC. To achieve satisfactory results in clinical trials, predictive biomarkers of PKC activity must be established and screened for prior to patient enrollment. Furthermore, tandem inhibition of PKC and molecular drivers may be a potential therapeutic strategy to prevent the emergence of resistance in NSCLC.     

Inventory lot-sizing with supplier selection using hybrid intelligent algorithm

In supply chain management (SCM), multi-product and multi-period models are usually used to select the suppliers. In the real world of SCM, however, there are normally several echelons which need to be integrated into inventory management. This paper presents a hybrid intelligent algorithm, based on the push SCM, which uses a fuzzy neural network and a genetic algorithm to forecast the rate of demand, determine the material planning and select the optimal supplier. We test the proposed algorithm in a case study conducted in Iran.     

POLAROGRAPHIC CHARACTERIZATION OF AROMATIC STRUCTURES IN COAL LIQUID PRODUCTS

Reducible aromatic species in coal liquid products from five major processes (Synthoil, FMC COED, HRI H-Coal, PAMCO SRC, and Catalytic Inc. SRC) together with solvent elution chromatography fractions of a selected asphaltene has been evaluated. The half-wave potentials measurments are found to be consistant with other methods. The total polarographic reduction of measurement per average molecule for Synthoil solvent fractions, as measured by diffusion constant (i_d/C), increases in the following manner: gas oil → resin → asphaltene → carbene → carboid. The same trend was observed when color indices (I) and refractive indices (n₂₅) were individually studied.     

Taguchi统计学分析方法优化Al 7068-TiC纳米复合材料的凝固行为

采用机械合金化和热压工艺制备高强Al 7068?5%TiC(质量分数)纳米复合材料。基于致密化的重要性和晶粒生长的影响,以获得较高抗压强度为目标,采用Taguchi统计法对制备Al 7068?5%TiC块体纳米复合材料的热压条件进行优化。结果表明：在500 MPa和385°C下热压30 min能获得抗压强度为938 MPa、硬度为HV 265的Al 7068?TiC纳米复合材料。此外,方差分析结果表明,外加压力是影响纳米复合材料热压过程最关键的因素。各因素对纳米复合材料热压过程影响贡献率为外加压力(61.3%)、热压温度(29.53%)和热压时间(4.49%)。     

The effect of MWNTs concentration and nanofiber orientation on mechanical properties of PAA nanocomposite nanofibrous web

In this research, nanocomposite nanofibrous webs of poly(acrylic acid) (PAA)/multi‐walled carbon nanotubes (MWNTs) were obtained via electrospinning. The effect of MWNTs concentration on the morphology and mechanical properties of PAA/MWNTs nanofibers was investigated by changing the MWNTs content from 0 to 5 wt%. The results showed that average diameter of nanofibers increased with increasing the MWNTs concentration and presence of MWNTs led to the enhancement of mechanical properties. Also, the results revealed that the strength, modulus, and elongation at break of samples increased 3.22, 2.70, and 4.27 fold, respectively, after adding 3 wt% of MWNTs. In addition, the effect of rotating speed of collector on the orientation of PAA nanofibers and its effect on mechanical properties was investigated. Scanning electron microscopy (SEM) studies demonstrated that the degree of nanofibers orientation increased with the augmentation of drum speed to 25 rps. Moreover, the average nanofibers diameter decreased with the increase of drum speed. Improvement of nanofiber orientation resulted in superior mechanical properties that is, higher strength and modulus of aligned nanofiber layers were obtained in comparison to nonaligned layers (12.6 and 26.6 fold, respectively). POLYM. COMPOS., 37:3149–3159, 2016. © 2015 Society of Plastics Engineers     

Probing effects of alternately‐embedded phenoxy phenyl lateral groups on properties of novel aromatic poly(ether‐urea)s

A new class of alternate aromatic poly(ether‐urea)s having bulky phenoxy phenyl lateral groups was prepared by the reaction of 2,2′‐bis[(p‐phenoxy phenyl)]‐4,4′‐diaminodiphenyl ether (PPAPE) with two diisocyanates, isophorone diisocyanate and 2,4‐tolylene diisocyanate. The limited viscosity values as well as M _n and M _w values of the resulting polymers were determined. The resulting poly(ether‐urea)s could be easily cast into optically‐transparent, flexible, and light color films. The cut‐off wavelength values and the percentage of transmittance at 800 nm were found to be at about 415 nm and 85%, respectively. PPAPE‐derived poly(ether‐urea)s showed a low‐crystallinity and had excellent solubility in polar organic solvents. T_onset, T_g, T_d5%, and T_d10% values of the PPAPE‐derived polymers measured from their DSC and TGA thermograms were up to 270, 280, 315, and 340°C, respectively. Surface morphology of the resulted poly(ether‐urea)s were also evaluated by their scanning electron microscopy images. Excellent organo‐solubility, satisfactory film quality, moderate T_g values, and good thermal stability make this class of poly (ether‐urea)s promising high‐performance polymeric materials. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

B4C reinforced NiTi-based composites: Microstructure and wear performance

In this study, NiTi–x wt.% B₄C (x = 0, 2, and 4) composites were consolidated with spark plasma sintering method, and the effects of boron carbide reinforcement addition on the microstructure and wear behavior of samples were investigated. Identification of the constituent phases of samples by the X-ray diffraction method plus Rietveld analysis revealed that the stability of the martensite phase increased in the composite samples because of mismatch stresses between the NiTi matrix phase and the reinforcing particles, which increases the density of the dislocations and facilitates the diffusion process that subsequently leads to the formation of stable intermetallics. The results of hardness test indicated that the hardness value increased from 3.67 GPa for pure NiTi to 10.99 GPa for NiTi–4 wt.% B₄C. Results of wear test revealed that boron carbide reinforced composite specimens had higher wear resistance, whereas wear rate of NiTi sample was 3.6 × 10⁻³ mm³/N m, and it reached to .21 × 10⁻³ mm³/N m for NiTi–4 wt.% B₄C. Investigation of microstructure by scanning electron microscopy images and EDS analysis revealed that the wear mechanism in NiTi samples was abrasive and the addition of B₄C to NiTi changed the wear mechanisms from abrasive to a combination of oxidation, adhesive, and delamination mechanisms.     

An intelligent hybrid meta-heuristic for solving a case of no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines

This paper addresses the problem of no-wait two-stage flexible flow shop scheduling problem (NWTSFFSSP) considering unrelated parallel machines, sequence-dependent setup times, probable reworks and different ready times to actualize the problem. The performance measure used in this study is minimizing maximum completion time (makespan). Because of the complexity of addressed problem, we propose a novel intelligent hybrid algorithm [called hybrid algorithm (HA)] based on imperialist competitive algorithm (ICA) which are combined with simulated annealing (SA), variable neighborhood search (VNS) and genetic algorithm (GA) for solving the mentioned problem. The hybridization is carried out to overcome some existing drawbacks of each of these three algorithms and also for increasing the capability of ICA. To achieve reliable results, Taguchi approach is used to define robust parameters' values for our proposed algorithm. A simulation model is developed to study the performance of our proposed algorithm against ICA, SA, VNS, GA and ant colony optimization (ACO). The results of the study reveal the relative superiority of HA studied. In addition, potential areas for further researches are highlighted.     

Application of a modified VIKOR method for decision-making problems in lean tool selection

Group decision making with multiple criteria is the most popular method for ranking a set of alternatives. In this regard, all alternatives are compared based on a common criteria set. Meanwhile, decision makers sometimes encounter special situations, for example, having to select from among a set of alternatives without a set of criteria or with a set of criteria that are grouped/related to various alternatives. Thus, it may be impossible to select from among a set of alternatives using typical methods. Hence, in this study, a new, modified VIKOR method is proposed to address the lean tool selection problems in manufacturing systems. In this study, a model was developed to help practitioners improve their ability to solve problems when the possible solutions have their own individual criteria. In fact the modified VIKOR method can be applied to rank alternatives in threefold: alternatives with common criteria, without common criteria, with integrated common, and uncommon criteria. This paper offers numerical examples of the model, using a case study to illustrate an application of the proposed model and properly assess the validity of this new method. The results demonstrate the usefulness and effectiveness of the modified new method. The model covers the lack existing in the current literature to assess effectiveness of applying lean tools.