Predicting the yield of pomegranate oil from supercritical extraction using artificial neural networks and an adaptive-network-based fuzzy inference system

Various simulation tools were used to develop an effective intelligent system to predict the effects of temperature and pressure on an oil extraction yield. Pomegranate oil was extracted using a supercritical CO₂ (SC-CO₂) process. Several simulation systems including a back-propagation neural network (BPNN), a radial basis function neural network (RBFNN) and an adaptive-network-based fuzzy inference system (ANFIS) were tested and their results were compared to determine the best predictive model. The performance of these networks was evaluated using the coefficient of determination (R²) and the mean square error (MSE). The best correlation between the predicted and the experimental data was achieved using the BPNN method with an R² of 0.9948.     

Effects of forage provision to dairy calves on growth performance and rumen fermentation: A meta-analysis and meta-regression

A meta-analysis of the potential effect of forage provision on growth performance and rumen fermentation of dairy calves was conducted using published data from the literature (1998–2016). Meta-regression was used to evaluate the effects of different forage levels, forage sources, forage offering methods, physical forms of starter, and grain sources on the heterogeneity of the results. We considered 27 studies that reported the effects of forage provision to dairy calves. Estimated effect sizes of forage were calculated on starter feed intake, average daily gain (ADG), feed efficiency (FE), body weight (BW), and rumen fermentation parameters. Intake of starter feed, ADG, BW, ruminal pH, and rumen molar proportion of acetate increased when supplementing forage but FE decreased. Heterogeneity (the amount of variation among studies) was significant for intake of starter feed, ADG, FE, final BW, and rumen fermentation parameters. Improving overall starter feed intake was greater in calves offered alfalfa hay compared with those offered other types of forages. During the milk feeding and overall periods, improving ADG was greater for calves fed a high level of forage (>10% in dry matter) compared with those fed a low level of forage (≤10% in dry matter) diets. The advantages reported in weight gain at a high level of forage could be due to increased gut fill. Improving overall ADG was lower for calves offered forages with textured starter feed compared with ground starter feed. The meta-regression analysis revealed that changes associated with forage provision affect FE differently for various forage sources and forage offering methods during the milk-feeding period. Forage sources also modulated the effect of feeding forage on ruminal pH during the milk-feeding period. In conclusion, forage has the potential to affect starter feed intake and performance of dairy calves, but its effects depend on source, level, and method of forage feeding and physical form of starter feed independently of grain sources included in the starter feed.     

On the Role of Dilution on Selective Hydrolytic Precipitation from Bimetallic Solutions: Zn–Ni Sulfate Solution

This paper introduces and discusses some potential effects of dilution in aqueous precipitation processes. The response of a sulfate solution comprising of 0.3 mol L^?1 Zn and 0.015 mol L^?1 Ni diluted with NaOH solution has been simulated. Considerable changes in separation pH, separation potential and precipitating minerals, have appeared after dilution. An increase in separation pH from 6.86 to 7.45 due to 100 times dilution has been predicted. It has also been revealed that the selectively precipitable zinc decreases from 89.4 to 85.7 % as a result of dilution. The products of zinc precipitation from undiluted and 100 times diluted solutions should be ZnO and Zn₄(OH)₆SO₄, respectively, according to equilibrium analysis. Despite the acceptable agreement of experimental results, the full agreement has been restricted in some cases by kinetic difficulty of ZnO precipitation and local high pH zone effect that has led to nickel co-precipitation.     

Broadband amplifier and high performance tunable laser with an extinction ratio of higher than 60 dB using bismuth oxide-based erbium-doped fiber

A Bi₂O₃-based erbium-doped fiber (Bi-EDF) ring laser with a 70?nm tunable range is demonstrated with a 49?cm long Bi-EDF in which tuning range can be extended to larger than 100?nm using an optical switch to alter the length of Bi-EDF in the laser cavity. With an extinction ratio of better than 60?dB throughout the entire tuning range, the measured FWHM of laser lines are measured to be 0.09?nm. In addition, the common amplification parameters are measured and studied in detail for various pumping configurations.     

High-speed contouring enhanced with P-H curves

In this paper, Pythagorean hodograph (P-H) curve theory is used for high-speed contouring applications. There are large contouring errors around sharp corners when low-bandwidth servo controllers (such as P-PI control) are used. It is possible to construct a P-H curve in the region of sharp corners in order to decrease the amount of cornering error. The developed algorithm is implemented for various corners with different angles. With respect to sharp tool paths, the total machining time is increased by a small amount, but the cornering error is reduced to the allowable tolerance limit. The results of simulation, such as the total cornering time and the cornering error, are compared with previously published methods. It has been shown that the over-corner P-H approach will substantially decrease the amount of cornering error.     

Electrodeposition of nickel oxide nanoparticles on glassy carbon surfaces: application to the direct electron transfer of tyrosinase

This work describes the performance of a tyrosinase/nickel oxide nanoparticles/glassy carbon (Tyr/NiO NPs/GC) electrode. This electrode was prepared by first applying a NiO NPs electrochemical deposition onto the GC electrode surface and then tyrosinase immobilization was applied to the surface of electrodeposited NiO NPs. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) procedures demonstrated the existence of different NiO NP geometrical structures. These geometrical structures could lead to better immobilization of proteins on their surfaces. The copper containing enzyme tyrosinase successfully achieved electrical contact with the electrode because of the unique structural alignment of tyrosinase enzyme on the nanometer-scale nickel oxide surfaces. This method could be suitable for application to nanofabricated devices facilitating better performance. It was concluded that tyrosinase can be effectively applied to nanometer-scale nickel oxide surfaces.     

Performance Evaluation of ANN and ANFIS Models for Estimating Garlic Crop Evapotranspiration

Estimation of evapotranspiration (ET) is necessary in water resources management, farm irrigation scheduling, and environmental assessment. Hence, in practical hydrology, it is often necessary to reliably and consistently estimate evapotranspiration. In this study, two artificial intelligence (AI) techniques, including artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), were used to compute garlic crop water requirements. Various architectures and input combinations of the models were compared for modeling garlic crop evapotranspiration. A case study in a semiarid region located in Hamedan Province in Iran was conducted with lysimeter measurements and weather daily data, including maximum temperature, minimum temperature, maximum relative humidity, minimum relative humidity, wind speed, and solar radiation during 2008–2009. Both ANN and ANFIS models produced reasonable results. The ANN, with 6-6-1 architecture, presented a superior ability to estimate garlic crop evapotranspiration. The estimates of the ANN and ANFIS models were compared with the garlic crop evapotranspiration (ETc) values measured by lysimeter and those of the crop coefficient approach. Based on these comparisons, it can be concluded that the ANN and ANFIS techniques are suitable for simulation of ETc.