Single-step Methods Research Articles

Genetic evaluation for three-way crossbreeding.

BackgroundCommercial pig producers generally use a terminal crossbreeding system with three breeds. Many pig breeding organisations have started to use genomic selection for which genetic evaluation is often done by applying single-step methods for which the pedigree-based additive genetic relationship matrix is replaced by a combined relationship matrix based on both marker genotypes and pedigree. Genomic selection is implemented for purebreds, but it also offers opportunities for incorporating information from crossbreds and selecting for crossbred performance. However, models for genetic evaluation for the three-way crossbreeding system have not been developed.ResultsFour-variate models for three-way terminal crossbreeding are presented in which the first three variables contain the records for the three pure breeds and the fourth variable contains the records for the three-way crossbreds. For purebred animals, the models provide breeding values for both purebred and crossbred performances. Heterogeneity of genetic architecture between breeds and genotype by environment interactions are modelled through genetic correlations between these breeding values. Specification of the additive genetic relationships is essential for these models and can be defined either within populations or across populations. Based on these two types of additive genetic relationships, both pedigree-based, marker-based and combined relationships based on both pedigree and marker information are presented. All these models for three-way crossbreeding can be formulated using Kronecker matrix products and therefore fitted using Henderson’s mixed model equations and standard animal breeding software.ConclusionsModels for genetic evaluation in the three-way crossbreeding system are presented. They provide estimated breeding values for both purebred and crossbred performances, and can use pedigree-based or marker-based relationships, or combined relationships based on both pedigree and marker information. This provides a framework that allows information from three-way crossbred animals to be incorporated into a genetic evaluation system.

Phase methods for measuring the spatial orientation of objects using satellite navigation equipment

This paper discusses phase methods for measuring the spatial orientation of objects using satellite navigation equipment. An analysis of methods for resolving phase ambiguity is presented in the paper. The effectiveness and applicability of the single-step methods are discussed in detail. The authors have shown that applying the exhaustive method requires a constellation of 5 - 6 visible satellites. The measurement of signals, having a base length of 1 m transmitted from 8 satellites, demonstrates that an unambiguous solution is achieved practically in all cases.

Chemical tools for probing histone deacetylase (HDAC) activity.

Histone deacetylases (HDACs) enzymes are responsible for removing epigenetic markers on histone proteins, which results in chromatin inactivation and gene repression. An evaluation of HDAC activity is essential for not only determining the physiological function of HDACs, but also for developing HDAC-targeting drugs. This review focuses on the chemical tools used to detect HDAC activity. We highlight activity-based probes and positron emission tomography probes based on the chemical structure of the inhibitors. We also summarize fluorogenic probes used in single-step methods for HDAC detection. These fluorogenic probes are designed based on the nucleophilicity of the amino group, aggregation via electrostatic interactions, and changes in the DNA binding properties. These fluorogenic systems may enable facile and rapid screening to evaluate HDAC inhibitors, which will contribute to the development of epigenetic drugs.

On the Hospital Volume and Outcome Relationship: Does Specialization Matter More Than Volume?

To evaluate the relationship between hospital volume and outcome by focusing on alternative measures of volume that capture specialization and overall throughput of hospitals. Hospital administrative data from the state of Victoria, Australia; data contain 1,798,474 admitted episodes reported by 135 public and private acute-care hospitals. This study contrasts the volume-outcome relationship using regression models with different measures of volume; two-step and single-step risk-adjustment methods are used. The sample is restricted to ischemic heart disease (IHD) patients (ICD-10 codes: I20-I25) admitted during 2001/02 to 2004/05. Overall hospital throughput and degree of specialization display more substantive implications for the volume-outcome relationship than conventional caseload volume measure. Two-step estimation when corrected for heteroscedasticity produces comparable results to single-step methods. Different measures of volume could lead to vastly different conclusions about the volume-outcome relationship. Hospital specialization and throughput should both be included as measures of volume to capture the notion of size, focus, and possible congestion effects.

Genomic prediction of traits related to canine hip dysplasia.

Increased concern for the welfare of pedigree dogs has led to development of selection programs against inherited diseases. An example is canine hip dysplasia (CHD), which has a moderate heritability and a high prevalence in some large-sized breeds. To date, selection using phenotypes has led to only modest improvement, and alternative strategies such as genomic selection (GS) may prove more effective. The primary aims of this study were to compare the performance of pedigree- and genomic-based breeding against CHD in the UK Labrador retriever population and to evaluate the performance of different GS methods. A sample of 1179 Labrador Retrievers evaluated for CHD according to the UK scoring method (hip score, HS) was genotyped with the Illumina CanineHD BeadChip. Twelve functions of HS and its component traits were analyzed using different statistical methods (GBLUP, Bayes C and Single-Step methods), and results were compared with a pedigree-based approach (BLUP) using cross-validation. Genomic methods resulted in similar or higher accuracies than pedigree-based methods with training sets of 944 individuals for all but the untransformed HS, suggesting that GS is an effective strategy. GBLUP and Bayes C gave similar prediction accuracies for HS and related traits, indicating a polygenic architecture. This conclusion was also supported by the low accuracies obtained in additional GBLUP analyses performed using only the SNPs with highest test statistics, also indicating that marker-assisted selection (MAS) would not be as effective as GS. A Single-Step method that combines genomic and pedigree information also showed higher accuracy than GBLUP and Bayes C for the log-transformed HS, which is currently used for pedigree based evaluations in UK. In conclusion, GS is a promising alternative to pedigree-based selection against CHD, requiring more phenotypes with genomic data to improve further the accuracy of prediction.

Validation of a penetrating captive bolt device with air-channel pithing as a single-step method for euthanasia of cattle in mass depopulation situations

The objective of this study was to evaluate the use of a penetrating captive bolt device with a built-in low pressure air-channel pithing as a single-step method for humane euthanasia of cattle in a mass depopulation scenario. Currently, the only single step methods of euthanasia approved for use in cattle are gunshot or barbiturate overdose both of which are impractical for mass depopulation situations.

Improved methods for the simultaneous inclusion of multiple polynomial zeros

Using a new fixed point relation, the interval methods for the simultaneous inclusion of complex multiple zeros in circular complex arithmetic are constructed. Using the concept of the R-order of convergence of mutually dependent sequences, we present the convergence analysis for the total-step and the single-step methods with Schröder’s and Halley-like corrections under computationally verifiable initial conditions. The suggested algorithms possess a great computational efficiency since the increase of the convergence rate is attained without additional calculations. Two numerical examples are given to demonstrate convergence characteristics of the proposed method.

Genomic evaluation of both purebred and crossbred performances

BackgroundFor a two-breed crossbreeding system, Wei and van der Werf presented a model for genetic evaluation using information from both purebred and crossbred animals. The model provides breeding values for both purebred and crossbred performances. Genomic evaluation incorporates marker genotypes into a genetic evaluation system. Among popular methods are the so-called single-step methods, in which marker genotypes are incorporated into a traditional animal model by using a combined relationship matrix that extends the marker-based relationship matrix to non-genotyped animals. However, a single-step method for genomic evaluation of both purebred and crossbred performances has not been developed yet.ResultsAn extension of the Wei and van der Werf model that incorporates genomic information is presented. The extension consists of four steps: (1) the Wei van der Werf model is reformulated using two partial relationship matrices for the two breeds; (2) marker-based partial relationship matrices are constructed; (3) marker-based partial relationship matrices are adjusted to be compatible to pedigree-based partial relationship matrices and (4) combined partial relationship matrices are constructed using information from both pedigree and marker genotypes. The extension of the Wei van der Werf model can be implemented using software that allows inverse covariance matrices in sparse format as input.ConclusionsA method for genomic evaluation of both purebred and crossbred performances was developed for a two-breed crossbreeding system. The method allows information from crossbred animals to be incorporated in a coherent manner for such crossbreeding systems.

Interior a posteriori error estimates for time discrete approximations of parabolic problems

We derive a posteriori estimates for single-step methods, including Runge---Kutta and Galerkin methods for the time discretization of linear parabolic equations. We focus on the estimation of the error at the nodes and derive a posteriori estimates that show the full classical order (superconvergence order) in the interior of the spatial domain without any compatibility assumptions.

Implicit-Explicit Formulations of a Three-Dimensional Nonhydrostatic Unified Model of the Atmosphere (NUMA)

We derive an implicit-explicit (IMEX) formalism for the three-dimensional (3D) Euler equations that allow a unified representation of various nonhydrostatic flow regimes, including cloud resolving and mesoscale (flow in a 3D Cartesian domain) as well as global regimes (flow in spherical geometries). This general IMEX formalism admits numerous types of methods including single-stage multistep methods (e.g., Adams methods and backward difference formulas) and multistage single-step methods (e.g., additive Runge--Kutta methods). The significance of this result is that it allows a numerical model to reuse the same machinery for all classes of time-integration methods described in this work. We also derive two classes of IMEX methods, one-dimensional and 3D, and show that they achieve their expected theoretical rates of convergence regardless of the geometry (e.g., 3D box or sphere) and introduce a new second-order IMEX Runge--Kutta method that performs better than the other second-order methods considered. We then compare all the IMEX methods in terms of accuracy and efficiency for two types of geophysical fluid dynamics problems: buoyant convection and inertia-gravity waves. These results show that the high-order time-integration methods yield better efficiency particularly when high levels of accuracy are desired.

Chemometrics assisted resolving of net faradaic current contribution from total current in potential step and staircase cyclic voltammetry

Total current in the electroanalytical data is assumed to be consisting of three main constituents: faradaic current, step charging current and induced charging current. Both charging currents can cause an interfering effect on precise determination of faradaic currents, and hence insert direct effects on sensitivity and detection limit of the electroanalytical techniques. Despite the widespread techniques introduced until now, the extraction of the net faradaic current from total current still remains a challenge. In this work, by using multivariate curve resolution-alternating least square (MCR-ALS) as a powerful curve resolution-based chemometrics method, a straightforward method has been introduced for resolving faradaic current from the two types of charging currents (step charging current and induced charging current) in single potential step and staircase cyclic voltammetric methods. By simultaneous analyses of the current data matrices for different electrochemical systems, the three sources of current were successfully identified and their contributions in the total signal were easily calculated. Also, in this manner, the cell time constant can be obtained easily. Contrary to the previously reported methods, the present method does not need any pre-determined mathematical method; particularly there is no need to know the cell time constant.

Effect of excess Nb2O5 on the growth behavior of KSr2Nb5O15 particles by molten salt synthesis

The single-step and two-step molten salt synthesis (MSS) methods have been utilized to synthesize anisometric KSr2Nb5O15 (KSN) particles. To facilitate morphological and dimensional control, the effects of excess Nb2O5 on the growth behavior of the product particles have been investigated, and a defect reaction growth mechanism is proposed. It was found that excess Nb2O5 could promote the growth of product particles in both the single-step and two-step MSS. The aspect ratio of the product particles increased and reached the maximum value (16.85 for the single-step MSS and 52.29 for the two-step MSS), then decreased with increasing amounts of excess Nb2O5. Using single-step MSS, two morphologies (rod-like and columnar) were formed as the excess Nb2O5 content was changed. This was caused by the nucleation of new particles at the particle edges. However, needle-like KSN particles were observed in the two-step MSS, which can be explained by the defect reaction mechanism. The in situ epitaxial growth, as controlled by the defect reaction mechanism, determines the morphology and size of the particles obtained using the two-step MSS.

Compatibility of pedigree-based and marker-based relationship matrices for single-step genetic evaluation

BackgroundSingle-step methods provide a coherent and conceptually simple approach to incorporate genomic information into genetic evaluations. An issue with single-step methods is compatibility between the marker-based relationship matrix for genotyped animals and the pedigree-based relationship matrix. Therefore, it is necessary to adjust the marker-based relationship matrix to the pedigree-based relationship matrix. Moreover, with data from routine evaluations, this adjustment should in principle be based on both observed marker genotypes and observed phenotypes, but until now this has been overlooked. In this paper, I propose a new method to address this issue by 1) adjusting the pedigree-based relationship matrix to be compatible with the marker-based relationship matrix instead of the reverse and 2) extending the single-step genetic evaluation using a joint likelihood of observed phenotypes and observed marker genotypes. The performance of this method is then evaluated using two simulated datasets.ResultsThe method derived here is a single-step method in which the marker-based relationship matrix is constructed assuming all allele frequencies equal to 0.5 and the pedigree-based relationship matrix is constructed using the unusual assumption that animals in the base population are related and inbred with a relationship coefficient γ and an inbreeding coefficient γ / 2. Taken together, this γ parameter and a parameter that scales the marker-based relationship matrix can handle the issue of compatibility between marker-based and pedigree-based relationship matrices. The full log-likelihood function used for parameter inference contains two terms. The first term is the REML-log-likelihood for the phenotypes conditional on the observed marker genotypes, whereas the second term is the log-likelihood for the observed marker genotypes. Analyses of the two simulated datasets with this new method showed that 1) the parameters involved in adjusting marker-based and pedigree-based relationship matrices can depend on both observed phenotypes and observed marker genotypes and 2) a strong association between these two parameters exists. Finally, this method performed at least as well as a method based on adjusting the marker-based relationship matrix.ConclusionsUsing the full log-likelihood and adjusting the pedigree-based relationship matrix to be compatible with the marker-based relationship matrix provides a new and interesting approach to handle the issue of compatibility between the two matrices in single-step genetic evaluation.

Effectiveness of genomic prediction on milk flow traits in dairy cattle

BackgroundMilkability, primarily evaluated by measurements of milking speed and time, has an economic impact in milk production of dairy cattle. Recently the Italian Brown Swiss Breeders Association has included milking speed in genetic evaluations. The main objective of this study was to investigate the possibility of implementing genomic selection for milk flow traits in the Italian Brown Swiss population and thereby evaluate the potential of genomic selection for novel traits in medium-sized populations. Predicted breeding values and reliabilities based on genomic information were compared with those obtained from traditional breeding values.MethodsMilk flow measures for total milking time, ascending time, time of plateau, descending time, average milk flow and maximum milk flow were collected on 37 213 Italian Brown Swiss cows. Breeding values for genotyped sires (n = 1351) were obtained from standard BLUP and genome-enhanced breeding value techniques utilizing two-stage and single-step methods. Reliabilities from a validation dataset were estimated and used to compare accuracies obtained from parental averages with genome-enhanced predictions.ResultsGenome-enhanced breeding values evaluated using two-stage methods had similar reliabilities with values ranging from 0.34 to 0.49 for the different traits. Across two-stage methods, the average increase in reliability from parental average was approximately 0.17 for all traits, with the exception of descending time, for which reliability increased to 0.11. Combining genomic and pedigree information in a single-step produced the largest increases in reliability over parent averages: 0.20, 0.24, 0.21, 0.14, 0.20 and 0.21 for total milking time, ascending time, time of plateau, descending time, average milk flow and maximum milk flow, respectively.ConclusionsUsing genomic models increased the accuracy of prediction compared to traditional BLUP methods. Our results show that, among the methods used to predict genome-enhanced breeding values, the single-step method was the most successful at increasing the reliability for most traits. The single-step method takes advantage of all the data available, including phenotypes from non-genotyped animals, and can easily be incorporated into current breeding evaluations.

Comparison on genomic predictions using three GBLUP methods and two single-step blending methods in the Nordic Holstein population

BackgroundA single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population.MethodsThe data consisted of de-regressed proofs (DRP) for 5 214 genotyped and 9 374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect.ResultsAveraged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods.ConclusionsThe single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix.

Spanning tests in return and stochastic discount factor mean–variance frontiers: A unifying approach

We propose new spanning tests that assess if the initial and additional assets share the economically meaningful cost and mean representing portfolios. We prove their asymptotic equivalence to existing tests under local alternatives. We also show that unlike two-step or iterated procedures, single-step methods such as continuously updated GMM yield numerically identical overidentifying restrictions test, so there is arguably a single spanning test. To prove these results, we extend optimal GMM inference to deal with singularities in the long run second moment matrix of the influence functions. Finally, we test for spanning using size and book-to-market sorted US stock portfolios.

Single-step methods for genomic evaluation in pigs

Genetic evaluation based on information from phenotypes, pedigree and markers can be implemented using a recently developed single-step method. In this paper we compare accuracies of predicted breeding values for daily gain and feed conversion ratio (FCR) in Danish Duroc pigs obtained from different versions of single-step methods, the traditional pedigree-based method and the genomic BLUP (GBLUP) method. In particular, we present a single-step method with an adjustment of the genomic relationship matrix so that it is compatible to the pedigree-based relationship matrix. Comparisons are made for both genotyped and non-genotyped animals and univariate and bivariate models. The results show that the three methods with marker information (two single-step methods and GBLUP) produce more accurate predictions of genotyped animals than the pedigree-based method. In addition, single-step methods provide more accurate predictions for non-genotyped animals. The results also show that the single-step method with adjusted genomic relationship matrix produce more accurate predictions than the original single-step method. Finally, the results for the bivariate analyses show a somewhat improved accuracy and reduced inflation of predictions for FCR for the two single-step methods compared with the univariate analyses. The conclusions are: first, the methods with marker information improve prediction compared with the pedigree-based method; second, a single-step method, contrary to GBLUP, provides improved predictions for all animals compared to the pedigree-based method; and third, a single-step method should be used with an adjustment of the genomic relationship matrix.

Single step approach to make diagnostic impressions of both the arches and face bow transfer: A novel technique

Mounting the maxillary and mandibular dentulous casts for Diagnostic purpose requires many steps (including making maxillary and mandibular impressions, face-bow transfer, and bite registration) or many appointments. A simple new technique of doing all of this together without compromising on the accuracy can save time over the conventional mounting procedure. To compare the accuracy of a new technique of a single-step diagnostic mounting procedure with that of the conventional diagnostic mounting procedure. Ten dentulous patients with the full complement of teeth and without any history of temporomandibular disorder and orthodontic treatment were selected for this study. A detachable metal triple tray to replace the fork part of the face bow fork that further could be attached to face bow was fabricated. Dual-arch impressions and face-bow transfer were made in these subjects using this modified triple tray. These mountings were compared with the ones done with the conventional mounting procedure. Five linear measurements (using stable reference points on the articulator and the cast) were made and the values obtained by both the methods were compared. The Student's 't' test for statistical analysis was used in this study. The measurement values obtained by the single-step method were almost similar to the ones obtained by the conventional method. The various mean measurements for the single step and conventional methods were 37.7 ± 6.8 and 38.5 ± 6.5 mm; 70.0 ± 4.4 and 70.1 ± 4.2 mm; 57.0 ± 4.9 and 57.3 ± 4.2 mm; 71.3 ± 4.5 and 71.0 ± 4.6 mm; and 58.7 ± 2.5 and 58.3 ± 2.3 mm; respectively. The differences between the values obtained by the conventional and single-step methods were not statistically significant. The single-step procedure of diagnostic mounting can be used as an alternative to the conventional method, without compromising the quality of mounting.

A family of high-order multistep methods with vanished phase-lag and its derivatives for the numerical solution of the Schrödinger equation

Many simulation algorithms (chemical reaction systems, differential systems arising from the modelling of transient behaviour in the process industries etc.) contain the numerical solution of systems of differential equations. For the efficient solution of the above mentioned problems, linear multistep methods or Runge–Kutta single-step methods are used. For the simulation of chemical procedures the radial Schrödinger equation is used frequently. In the present paper we will study a class of linear multistep methods. More specifically, the purpose of this paper is to develop an efficient algorithm for the approximate solution of the radial Schrödinger equation and related problems. This algorithm belongs in the category of the multistep methods. In order to produce an efficient multistep method the phase-lag property and its derivatives are used. Hence the main result of this paper is the development of an efficient multistep method for the numerical solution of systems of ordinary differential equations with oscillating or periodical solutions. The reason of their efficiency, as the analysis proved, is that the phase-lag and its derivatives are eliminated. Another reason of the efficiency of the new obtained methods is that they have high algebraic order

Enhanced the superplasticity in Ti–6.5Al–2Zr–1Mo–1V alloy by a two-step deformation method

A two-step deformation method was adopted to investigate the superplasticity of Ti–6.5Al–2Zr–1Mo–1V alloy in this work, in which the specified pre-elongation was obtained by the constant velocity in the first step, and then the specimen was deformed to fracture by the maximum m-value method in the second step. The superplastic tensile tests were performed on a SANS CMT4104 electronic tensile testing machine at all temperatures ranging from 1123 to 1223K and pre-elongations ranging from 100% to 200%, and the maximum elongation-to-failure values between 188% and 1456% were obtained. For comparison, the constant velocity and the maximum m-value methods were also applied separately at 1173K in the study. The experimental results indicate that the superplasticity of Ti–6.5Al–2Zr–1Mo–1V alloy has been improved greatly by the two-step method compared with these single-step deformation methods. The ductility of the alloy was increased significantly at a pre-elongation of 150% and deformation temperature of 1173K, at which the maximum elongation of 1456% was attained in the present work.