Prediction accuracies and genetic parameters for test-day traits from genomic and pedigree-based random regression models with or without heat stress interactions

The aim of this study was to compare genetic (co)variance components and prediction accuracies of breeding values from genomic random regression models (gRRM) and pedigree-based random regression models (pRRM), both defined with or without an additional environmental gradient. The used gradient was a temperature-humidity index (THI), considered in statistical models to investigate possible genotype by environment (G×E) interactions. Data included 106,505 test-day records for milk yield (MY) and 106,274 test-day records for somatic cell score (SCS) from 12,331 genotyped Holstein Friesian daughters of 522 genotyped sires. After single nucleotide polymorphism quality control, all genotyped animals had 40,468 single nucleotide polymorphism markers. Test-day traits from recording years 2010 to 2015 were merged with temperature and humidity data from the nearest weather station. In this regard, 58 large-scale farms from the German federal states of Berlin-Brandenburg and Mecklenburg-West Pomerania were allocated to 31 weather stations. For models with a THI gradient, additive genetic variances and heritabilities for MY showed larger fluctuations in dependency of DIM and THI than for SCS. For both traits, heritabilities were smaller from the gRRM compared with estimates from the pRRM. Milk yield showed considerably larger G×E interactions than SCS. In genomic models including a THI gradient, genetic correlations between different DIM × THI combinations ranged from 0.26 to 0.94 for MY. For SCS, the lowest genetic correlation was 0.78, estimated between SCS from the last DIM class and the highest THI class. In addition, for THI × THI combinations, genetic correlations were smaller for MY compared with SCS. A 5-fold cross-validation was used to assess prediction accuracies from 4 different models. The 4 different models were gRRM and pRRM, both modeled with or without G×E interactions. Prediction accuracy was the correlation between breeding values for the prediction data set (i.e., excluding the phenotypic records from this data set) with respective breeding values considering all phenotypic information. Prediction accuracies for sires and for their daughters were largest for the gRRM considering G×E interactions. Such modeling with 2 covariates, DIM and THI, also allowed accurate predictions of genetic values at specific DIM. In comparison with a pRRM, the effect of a gRRM with G×E interactions on gain in prediction accuracies was stronger for daughters than for sires. In conclusion, we found stronger effect of THI alterations on genetic parameter estimates for MY than for SCS. Hence, gRRM considering THI especially contributed to gain in prediction accuracies for MY.     

Microstructure and Optical Bandgap of Cobalt Selenide Nanofilms

Semiconductors - The purpose of this research is to explore the properties of CoSe nanostructured thin films on glass substrates prepared by a chemical solution deposition method. Special attention...     

Oligomeric Composition of Polyols From Fatty Acid Methyl Ester: The Effect of Ring‐Opening Reactants of Epoxide Groups

Commercial availability of fatty acid methyl ester (FAME) from palm oil targeted for biodiesel offers a good feedstock for the production of structurally well‐defined polyols for polyurethane applications. The effect of molecular weight (MW), odd and even carbon numbers, and the linear and branched structure reactants used in the ring‐opening reaction of epoxidized fatty acid methyl ester (E‐FAME) on the properties of polyols was investigated. Conversions of E‐FAME to PolyFAME polyols were confirmed by Fourier transform infrared analysis, oxirane oxygen content, and hydroxyl number. Gel permeation chromatography (GPC) calibrated against polyether polyols as a standard and vapor pressure osmometry were used for MW determination. GPC chromatograms of PolyFAME polyols clearly demonstrated the formation of oligomers during ring‐opening reactions. MW, and odd and even carbon numbers in a structure of linear diols and branched diol used in the syntheses of PolyFAME polyols did not have an effect on crystallinity, glass transition, or melt temperatures measured using Differential scanning calorimetry (DSC). PolyFAME polyols ring‐opened with water, methanol, and 1,2‐propanediol contained secondary hydroxyl groups, whereas PolyFAME polyols ring‐opened with linear diols contained a mixture of primary and secondary hydroxyl groups. It was found that the concentration of primary hydroxyl groups increased significantly by increasing the number of carbons from C2 to C3 in the linear diols. The viscosity of PolyFAME polyols also increased with the MW of linear diols used in the E‐FAME ring‐opening reaction. These findings would be beneficial for formulators in choosing the most cost effective polyols for polyurethane formulations.     

A Numerical and Experimental Investigation into Hot Stamping of Boron Alloyed Heat Treated Steels

Hot stamping of steel sheets using water or nitrogen cooling media was studied on a laboratory scale. Sheets of grade 22MnB5 boron steels in three different thicknesses were investigated and the results of experimental hot stamping tests were considered. Microstructural analysis, linear and surface hardness profiling as well as tensile tests of formed samples were carried out. After hot stamping, mostly fully martensitic microstructures, which yield ultra high strength levels, were produced. It is concluded that die cooling media, i.e., water or nitrogen, have a significant effect on material properties after hot stamping. Using liquid nitrogen as coolant in the punch instead of water increases yield strength by 50 to 65MPa. Moreover, the evolution of the temperature and force during the hot stamping process was simulated by using a coupled thermomechanical FEM program. The results of numerical simulation and experimental results are in good agreement.     

Sensitivity Analysis on Neural Network Algorithm for Primary Superheater Spray Modeling

ABSTRACT

Nonlinear, large inertia with long dead time is always associated with the main steam temperature parameter in coal fired power plant. Successful control of the main steam temperature within ±2°C of its setpoint is the ultimate target for coal-fired power plant operators. Two of the most common main steam temperature circuit are primary superheater spray and secondary superheater spray. Various methods were used to model the primary superheater spray control valve opening, and the neural network remains one of the most popular choices among researchers. It remains inconclusive which neural network algorithm types, setup, number of layers, and training algorithm will give the best result. As such, the paper shows the best setup for the neural network algorithm based on sensitivity analysis methodology for one hidden layer. The inputs selected for the neural network are generator output, main steam flow, total spray flow, and secondary superheater outlet steam temperature, while the output selected is primary spray flow control valve opening.     

Identification and Affinity Determination of Protein-Antibody and Protein-Aptamer Epitopes by Biosensor-Mass Spectrometry Combination

Analytical methods for molecular characterization of diagnostic or therapeutic targets have recently gained high interest. This review summarizes the combination of mass spectrometry and surface plasmon resonance (SPR) biosensor analysis for identification and affinity determination of protein interactions with antibodies and DNA-aptamers. The binding constant (K_D) of a protein–antibody complex is first determined by immobilizing an antibody or DNA-aptamer on an SPR chip. A proteolytic peptide mixture is then applied to the chip, and following removal of unbound material by washing, the epitope(s) peptide(s) are eluted and identified by MALDI-MS. The SPR-MS combination was applied to a wide range of affinity pairs. Distinct epitope peptides were identified for the cardiac biomarker myoglobin (MG) both from monoclonal and polyclonal antibodies, and binding constants determined for equine and human MG provided molecular assessment of cross immunoreactivities. Mass spectrometric epitope identifications were obtained for linear, as well as for assembled (“conformational”) antibody epitopes, e.g., for the polypeptide chemokine Interleukin-8. Immobilization using protein G substantially improved surface fixation and antibody stabilities for epitope identification and affinity determination. Moreover, epitopes were successfully determined for polyclonal antibodies from biological material, such as from patient antisera upon enzyme replacement therapy of lysosomal diseases. The SPR-MS combination was also successfully applied to identify linear and assembled epitopes for DNA–aptamer interaction complexes of the tumor diagnostic protein C-Met. In summary, the SPR-MS combination has been established as a powerful molecular tool for identification of protein interaction epitopes.     

Cervical spondylotic myelopathy: surgical results and factors affecting prognosis

OBJECTIVE: A variety of factors may affect surgical outcome in patients with cervical spondylotic myelopathy. The aim of this study is to determine these factors on the basis of preoperative radiological and clinical data. METHODS: To assess the factors affecting postoperative outcome after surgery for cervical spondylotic myelopathy, the clinical and radiological data of 27 patients with cervical spondylotic myelopathy were reviewed. Functional and neurological statuses were assessed using the Japanese Orthopaedic Association (JOA) scale modified by Benzel. In all patients, the effect of age, symptom duration, cervical curvature, presence or absence of preoperative high signal intensity within the spinal cord as revealed by T2-weighted magnetic resonance imaging, and diameters of the spinal canal and vertebral body on pre- and postoperative neurological statuses were investigated. Plain radiographs were obtained for all patients, magnetic resonance images for 21 patients (77.8%), computed tomographic scans for 13 patients (48.1%), myelograms for 6 patients (22.2%), and computed tomographic myelograms for 4 patients (14.8%). There were five patients with a JOA score of 10, six patients with a JOA score of 11, six patients with a JOA score of 12, four patients with a JOA score of 13, four patients with a JOA score of 14, one patient with a JOA score of 15, and one patient with a JOA score of 16. All patients underwent cervical laminectomies. The mean follow-up period was 54.1 months. The final neurological examinations revealed improvement in the JOA scores of 85.1 % of the patients. RESULTS: Statistical analysis of all patients revealed mean JOA scores of 12.185 +/- 1.618 and 14.370 +/- 2.15 before surgery and at final examination, respectively. The difference between the preoperative JOA score and the final JOA score was determined to be statistically significant (P < 0.0001). Statistical analyses also showed better neurological improvement in patients younger than 60 years and in patients with normal preoperative cervical lordosis. Although patients without preoperative high signal intensity of the spinal cord showed a better improvement rate than did patients with preoperative high signal intensity, the determined difference was statistically insignificant. CONCLUSION: It can be concluded that age and abnormal cervical curvature predict less postoperative neurological improvement. The presence of preoperative high signal intensity within the spinal cord may also reflect less neurological improvement.