Short communication: Genetic parameters of individual fatty acids in milk of Canadian Holsteins

The objective of the present study was to estimate heritabilities of milk fatty acids (FA) and genetic and phenotypic correlations among milk FA and milk production traits in Canadian Holsteins. One morning milk sample was collected from each of 3,185 dairy cows between February and June 2010 from 52 commercial herds enrolled in Valacta (Ste-Anne-de-Bellevue, Quebec, Canada). Individual FA percentages (g/100 g of total FA) were determined for each sample by gas chromatography. After editing the data, 2,573 cows from 46 herds remained. Genetic parameters were estimated using multitrait animal models fitted under REML. The model included fixed effects of age at calving and stage of lactation each nested within parity and random effects of herd-year-season of calving, animal, and residual. The pedigree of animals with data was traced back 5 generations on both the male and female sides to account for relationships among animals. The estimates of heritability for individual FA ranged from 0.01 to 0.39, with standard errors ranging from 0.01 to 0.06. Generally, monounsaturated FA (MUFA) and saturated FA (SFA) showed higher heritability estimates than polyunsaturated FA (PUFA). Overall, SFA were negatively genetically correlated with MUFA and PUFA, whereas genetic correlations between MUFA and PUFA were positive. The SFA showed positive associations with fat yield and fat percentage, whereas unsaturated FA were negatively associated with fat yield and fat percentage. Bovine milk FA composition could be improved through genetic selection, and selection for MUFA or against SFA could alter the bovine milk fat profile in a desirable direction.     

Numerical and experimental analysis of a horizontal ground-coupled heat pump system

The main objective of this work is to evaluate a heat pump system using the ground as a source of heat. A ground-coupled heat pump (GCHP) system has been installed and tested at the test room, University of Firat, Elazig, Turkey. Results obtained during experimental testing are presented and discussed here. The coefficient of performance (COP_sys) of the GCHP system is determined from the measured data. A numerical model of heat transfer in the ground was developed for determining the temperature distribution in the vicinity of the pipe. The finite difference approximation is used for numerical analysis. It is observed that the numerical results agree with the experimental results.     

Statistical and neural network assessment of the compression index of clay-bearing soils

The compression index is used to estimate the consolidation settlement of clay-bearing soils. As the determination of compression index from oedometer tests is relatively time-consuming, empirical equations based on index properties can be useful. In this study the performance of widely used single and multi-variable empirical equations was evaluated using a database consisting of 135 test data. New empirical equations were developed utilizing least square regression analysis. In addition, an artificial neural network (ANN) with eight input variables was also developed to estimate the compression index. It was concluded that ANN provides the best results.      

Predicting performance of a ground-source heat pump system using fuzzy weighted pre-processing-based ANFIS

The goal of this work is to predict the daily performance (COP) of a ground-source heat pump (GSHP) system with the minimum data set based on an adaptive neuro-fuzzy inference system (ANFIS) with a fuzzy weighted pre-processing (FWP) method. To evaluate the effectiveness of our proposal (FWP–ANFIS), a computer simulation is developed on MATLAB environment. The comparison of the proposed hybridized system's results with the standard ANFIS results is carried out and the results are given in the tables. The efficiency of the proposed method was demonstrated by using the 3-fold cross-validation test. The statistical methods, such as the root-mean squared (RMS), the coefficient of multiple determinations (R²) and the coefficient of variation (cov), are given to compare the predicted and actual values for model validation. The average R² values is 0.9998, the average RMS value is 0.0272 and the average cov value is 0.7733, which can be considered as very promising. The data set for the COP of GSHP system available included 38 data patterns. The simulation results show that the FWP-based ANFIS can be used in an alternative way in these systems. The prediction results of the proposed structure were much better than the standard ANFIS results. Therefore, instead of limited experimental data found in the literature, faster and simpler solutions are obtained using hybridized structures such as FWP-based ANFIS.     

Active learning: an empirical study of common baselines

Most of the empirical evaluations of active learning approaches in the literature have focused on a single classifier and a single performance measure. We present an extensive empirical evaluation of common active learning baselines using two probabilistic classifiers and several performance measures on a number of large datasets. In addition to providing important practical advice, our findings highlight the importance of overlooked choices in active learning experiments in the literature. For example, one of our findings shows that model selection is as important as devising an active learning approach, and choosing one classifier and one performance measure can often lead to unexpected and unwarranted conclusions. Active learning should generally improve the model’s capability to distinguish between instances of different classes, but our findings show that the improvements provided by active learning for one performance measure often came at the expense of another measure. We present several such results, raise questions, guide users and researchers to better alternatives, caution against unforeseen side effects of active learning, and suggest future research directions.     

Investigation of alkaline water electrolysis performance for different cost effective electrodes under magnetic field

Alkaline water electrolysis is the easiest methods for hydrogen production because of their simplicity. Although the simplicity is an advantage; reducing the energy consumption and maintaining the durability and the safety of these systems are the main challenges. In this paper, alkaline water electrolysis system, that uses cost effective electrode materials and magnetic field effects are presented. Cost effective electrodes such as high carbon steel, 304 stainless steel, 316L low carbon steel and graphite material are used for the hydrogen production. After the selection of the best electrode pair, effects of magnetic field to hydrogen production and change of current density are investigated for KOH electrolytes in different concentrations (5 wt%, 10 wt% and 15 wt%). According to the experimental observations the direction of the Lorentz Force affects the hydrogen production and current density. When the Lorentz Force is directed upward, it enhances the hydrogen production for 5 wt% and 15 wt% KOH solution by almost 17%. The increase in current density for 5 wt%, 10 wt% and 15 wt% concentration is 19%, 5%, 13%, respectively. Forced convection in the magnetic field enhances the separation of gas bubbles from electrode surface. Downward directed Lorentz Force decreases hydrogen production and current density values significantly. For 5 wt%, 10 wt% and 15 wt% the hydrogen production decreases by 14%, 8%, 7%, respectively. Similarly, current density for downward directed Lorentz Force decreases by 11%, 7%, 4%, respectively.     

Buffer effects on the mosaic structure of the HR-GaN grown on 6H-SiC substrate by MOCVD

High-resistive GaN (>10⁸ Ω cm) layers have been grown with different buffer structures on 6H-SiC substrate using metalorganic chemical vapor deposition reactor. Different combination of the GaN/AlN super lattice, low temperature AlN, high temperature AlN and Al_xGa_1?xN (x ≈ 0.67) layers were used in the buffer structures. The growth parameters of the buffer layers were optimized for obtaining a high-resistive GaN epilayer. The mosaic structure parameters, such as lateral and vertical coherence lengths, tilt and twist angle (and heterogeneous strain), and dislocation densities (edge and screw dislocations) of the high-resistive GaN epilayers have been investigated using x-ray diffraction measurements. In addition, the residual stress behaviors in the high-resistive GaN epilayers were determined using both x-ray diffraction and Raman measurements. It was found that the buffer structures between the HR-GaN and SiC substrate have been found to have significant effect on the surface morphology and the mosaic structures parameters. On the other hand, both XRD and Raman results confirmed that there is low residual stress in the high-resistive GaN epilayers grown on different buffer structures.     

Investigation of the stability of the radiation sensitivity of TL peaks of quartz extracted from tiles

One of the most important mineral in dosimetric investigation is quartz, which is found abundantly in archaeological and geological materials. Although there are many studies about its thermoluminescence (TL) properties in the literature, it may exhibit different properties for each quartz mineral extracted from the different region of the world. In the present work, the stabilities and dose responses of glow peaks of quartz obtained from the tiles of Kubad Abad Palace in central Turkey were investigated after annealing at 500 and 600 °C for 1 h. The variation of radiation sensitivity of TL peaks of the quartz grains extracted from tiles are found to be more stable after annealing at 600 °C than 500 °C for 1 h. The TL dose responses of glow peaks of annealed and unannealed quartz samples were also studied up to approximately 3 kGy. It was observed that the pre-irradiation heat treatments affect the dose response behaviors of glow peaks.     

Evaluation of the performance of calix[8]arene derivatives as liquid phase extraction material for the removal of azo dyes

This paper presents a study on the removal of azo dyes (Reactive Black 5, Trapaeolin 000, Methyl Orange and Direct Violet 51) with calix[n]arene derivatives from aqueous solution into the organic phase in order to explore the potential use of calixarenes as low-cost efficient extractants for wastewater dye removal. The carboxylic acid derivative of calix[8]arene shows highest affinity towards the azo dyes. The influence of NaCl (present in the solution) on extraction process was also studied. The extent of the dye removal increased with the addition of NaCl. The proposed extraction mechanism involves several kinds of interactions: electrostatic repulsion between carboxylic acid groups of calix[8]arenes and sulfonate groups of azo dyes, hydrogen bonding and formation of an inclusion complex due to three dimensional cavity type calix[n]arene molecules through host-guest interactions.