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Three experiments for to pot ond one field experiment were carried out at Agric. Res. Station, Fac. Agric., Al-Azhar Univ. Nasr City and El-Aklag region, Kaliobia Governorate, Egypt, during 2011/2012, 2012/2013 and 2013/2014 to investigate the influence of mineral nitrogen fertilizer and biological ones i.e. Cerialen and Biogen under foliar spraying with Cysteine on the productivity of three wheat varieties (Sakha-93. Masry-1 and Banisweif). The studied treatments were recommended dose of N (75 kg N/fed., F1), recommended dose of N. fertilizer + Cysteine at the rate of 150 ppm (F2) 50% recommended dose of N fertilizer + Cerialine + Cysteine (F3) and 50% recommended dose of N fertilizer + biogen + Cysteine (F4). Complete randomized design was applied for the pot experiments, whereas split plot design was conducted for the experimental field. The results revealed that the difference between the investigated varieties due to plant height (cm) and flag leaf area (cm2) was substantial. Sakha-93 var. pronounced its superiority due to the both studied growth characters during the pot and field experiment. F2 treatment located the first order and gave the tallest wheat plants, whereas F4 treatment awarded the largest area of flag leaf, during the three experimental seasons. Yield and yield components parameters (No of grains/spike, 1000-grain weight (g), grain yield (g/plant in pots and ardab/fed. in field), straw yield (g/plant and ton/fed. in field) and biological yield (g/plant in pots and ton/fed. in field ) differed significantly between varieties. the maximum value were obtained from Sakha-93 and Masry-1, while the minimum ones associated with Baniswif variety, through the three experimental seasons. With the exception of straw yield either pot experiments or the field one, F2 and F4 treatments resulted in the heighest data for the previous yield and yield components parameters. The effect for the first order interaction (Var. x Fert.) on the studied characters differed with the characters difference (significant or nonsignificant) as shown from the obtained results during the three experimental seasons. [ABSTRACT FROM AUTHOR]

SUMMARY Absorption refrigeration cycles are alternatives to conventional vapor-compression cycles in which the energy required for refrigeration is provided by heat instead of mechanical work. In this paper, a novel refrigeration cycle utilizing the immiscible liquid-phase separation behavior is simulated and analyzed using Aspen simulator. The two conjugate liquids adopted in this work are triethylamine (solute) and water (solvent). This binary system has a low critical solution temperature of 18 °C. The thermophysical properties of the binary mixture are generated using the universal functional activity coefficient (UNIFAC) and the nonrandom two-liquid (NRTL) models. The phase splitting phenomenon at the generator temperature is predicted by both models. However, in comparison with the available experimental data for the same binary mixture, NRTL model gives better predictions for the flow rates and compositions of the material streams. Heat duties of the evaporator, absorber, and generator and the power consumption of the solution pump have been calculated using UNIFAC and NRTL models. The cycle COP that plays a major role in determining the cycle economical viability has been predicted for different operating conditions using the two models. Simulation results show that, for a waste heat reservoir at 60 °C and using NRTL model, the COP is about 2.0. Second law analysis conducted for all cycle components of the cycle shows that about 42% of the total exergy destructed occurs in the generator. Finally, the liquid-phase separation refrigeration cycle is predicted to be a promising cycle in the near future because of hardware and energy savings. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Artificial neural network (ANN) simulation is used to predict the rejection of two salts (NaCl and MgCl2) at typical seawater concentrations in a cross-flow nanofiltration membrane process. Rejections are predicted as a function of feed pressure and permeate flux with the salt concentration as a parameter. ANN predictions of the two salts' rejections are compared with experimental results obtained using three different nanofiltration membranes (NF90, NF270 and N30F) in a cross flow filtration set-up. The experimental program spans a concentration range of 5000 to 25 000 ppm for NaCl solution and of 5000 to 20 000 ppm for MgCl2 solution at pressures covering the range of 2–9 bars. The effects of the training algorithm, neural network architectures and transfer function on the ANN performance, as reflected by the percentage average absolute deviation are discussed. A network with one hidden layer comprising four neurones is found to be adequate for mapping input–output relationships and providing a good interpolative tool. Algorithms based on the conjugate gradient, regularization and quasi-Newton principles were found to outperform those based on the gradient descent and variable momentum gradient descent. The former algorithms gave an average absolute percentage deviation up to 5% whereas deviations up to 20% are obtained from the latter algorithms. For most of the cases considered, the ANN proved to be an adequate interpolation tool, where an excellent prediction was obtained for some concentration levels not represented in the training data set. For very limited cases, the ANN predictive performance was poor. However, the network's performance in these extreme cases didn't improve even with increasing the data points in the training data set. [ABSTRACT FROM AUTHOR]

The degree of compatibility of NR/EPDM blend can be improved by the use of specially selected polymeric compounds. Acrylonitrile and N-(4-chlorophenyl) acrylamide were homopolymerized and then copolymerized. The two homopolymers and the copolymer were incorporated each into the noncompatible blend system (50/50) NR/EPDM as compatibilizers. The effects of these compounds on the compatibility of both rubbers were evaluated by ultrasonic, differential scanning calorimetry (DSC), and rheometric techniques. The results obtained were compared with those of a reference blend. It was found that a fairly good compatibility had been achieved using polyacrylonitrile. [ABSTRACT FROM AUTHOR]

Thangirala Sudha,1 Dhruba J Bharali,1 Murat Yalcin,1,2 Noureldien HE Darwish,1,3 Melis Debreli Coskun,1,4 Kelly A Keating,1 Hung-Yun Lin,5,6 Paul J Davis,1,7 Shaker A Mousa1 1The Pharmaceutical Research Institute, Albany College of Pharmacy and Health Sciences, Rensselaer, NY, USA; 2Department of Physiology, Veterinary Medicine Faculty, Uludag University, Gorukle, Bursa, Turkey; 3Department of Clinical Pathology, Faculty of Medicine, Mansoura University, Mansoura, Egypt; 4Department of Biology, Faculty of Arts and Sciences, Uludag University, Gorukle, Bursa, Turkey; 5PhD Program for Cancer Biology and Drug Discovery, College of Medical Science and Technology, 6Taipei Cancer Center, Taipei Medical University, Taipei, Taiwan; 7Department of Medicine, Albany Medical College, Albany, NY, USA Abstract: The tetraiodothyroacetic acid (tetrac) component of nano-diamino-tetrac (NDAT) is chemically bonded via a linker to a poly(lactic-co-glycolic acid) nanoparticle that can encapsulate anticancer drugs. Tetrac targets the plasma membrane of cancer cells at a receptor on the extracellular domain of integrin αvβ3. In this study, we evaluate the efficiency of NDAT delivery of paclitaxel and doxorubicin to, respectively, pancreatic and breast cancer orthotopic nude mouse xenografts. Intra-tumoral drug concentrations were 5-fold (paclitaxel; P

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