Inbreeding in Swiss Braunvieh and its influence on breeding values predicted from a repeatability animal model.

Inbreeding coefficients were computed for 910,444 animals of the Swiss Braunvieh population. Of the animals born in 1984, 71.5% were inbred with 67.9, 3.4, and .2% having inbreeding coefficients between greater than 0 and 5%, greater than 5 to 10%, and greater than 10%, respectively. The average inbreeding coefficient was 1.14% but, for animals with both parents and at least one grandparent known, it was 1.67%. Breeding values for total milk, fat, and protein yields and for fat and protein percentages were predicted using a repeatability animal model including a regression on the inbreeding coefficient. Phenotypic performance was sizeably depressed for milk yield only (-26 kg/% of inbreeding or 2.4% of the phenotypic standard deviation). Adjusting for inbreeding increased the estimated genetic trend slightly. Inbreeding is only partially accounted for when it is ignored in the construction of the inverse of the numerator relationship matrix. This effect was investigated by comparing predicted breeding values from a model including the complete matrix with predicted breeding values from a model including a matrix constructed with inbreeding ignored. Only .8% of all predicted breeding values were affected by more than +/- 5.5 kg. The maximum difference observed was 55.3 kg. The observed average absolute differences between the breeding values of offspring predicted with the two models increased with inbreeding of parents.     

EDT Method for Multiple Labelled Objects Subject to Tied Distances

Machine Intelligence Research - The success of new scientific areas can be assessed by their potential for contributing to new theoretical approaches aligned with real-world applications. The...     

Online identification of appliances from power consumption data collected by smart meters

The efficient use of resources is a matter of great concern in today’s society, especially in the energy sector. Although the main strategy to decrease energy use has long been focused on supply, over the last few years, there has been a shift to the demand side. Under this new line of action, demand-side management networks have emerged and extended from the household level to larger installations, with the appearance of the concepts of Smart Grids and even Smart Cities. The extended use of Smart Meters for measuring residential electricity consumption facilitates the creation of such intelligent environments. In this context, this article proposes a system which extracts value from the collected consumer information to identify the appliances belonging to that smart environment by means of machine learning techniques. Considering the large amount of information that would be handled when millions of homes were sending data, big data technology has been used. An experiment to evaluate the classification method was carried out with seven devices and three different configurations. The results are also reported, achieving promising results, with recognition rates of 75 % after 1 h of training and 100 % after 4 h.     

A new methodology to solve non‐linear equation systems using genetic algorithms. Application to combined cyclegas turbine simulation

This paper shows a methodology to sort out the equations of a non‐linear system in order to solve it by the fixed‐point method. The arrangement of the equations is established by a genetic algorithm that deals with a population of possible resolution processes of the system. The method is specially useful in the following situations: first, when the system is very non‐linear and has many variables (where the Newton–Raphson method does not work properly); second, when the number of equations and variables may be altered because the equation system may change in each simulation and, therefore, more than one only solution process is needed if the fixed‐point process is employed. As an example, the methodology has been applied to solve the equation system that models the behaviour of a heat recovery steam generator of a combined cycle power plant at full load and part load conditions. Copyright © 2005 John Wiley & Sons, Ltd.     

Gate‐Controlled Energy Barrier at a Graphene/Molecular Semiconductor Junction

The formation of an energy‐barrier at a metal/molecular semiconductor junction is a universal phenomenon which limits the performance of many molecular semiconductor‐based electronic devices, from field‐effect transistors to light‐emitting diodes. In general, a specific metal/molecular semiconductor combination of materials leads to a fixed energy‐barrier. However, in this work, a graphene/C₆₀ vertical field‐effect transistor is presented in which control of the interfacial energy‐barrier is demonstrated, such that the junction switches from a highly rectifying diode at negative gate voltages to a highly conductive nonrectifying behavior at positive gate voltages and at room temperature. From the experimental data, an energy‐barrier modulation of up to 660 meV, a transconductance of up to five orders of magnitude, and a gate‐modulated photocurrent are extracted. The ability to tune the graphene/molecular semiconductor energy‐barrier provides a promising route toward novel, high performance molecular devices.     

Integrated Fire Evolution Monitoring System (IFEMS) for monitoring spatial-temporal behaviour of multiple fire phenomena

This study focuses on multiple fire phenomena in Valencia, Spain. The monitoring of fire recurrence was conducted by means of smoke visualization, mapping the burned area and fire detection, and took place for the whole of the fire period from 21 May to 13 July 1994. The temporal and spatial evolution of the fire was addressed on a daily basis, by means of approaches for mapping burned areas, fire detection, and integrated fire evolution monitoring system.     

Unipolar plasma electrolytic oxidation: Waveform optimisation for corrosion resistance of commercially pure titanium

This study deals with the anodisation of titanium grade 2 in 0.5-M sulphuric acid using a pulsed signal in a unipolar regime. The electrical parameters investigated are voltage, frequency and duty cycle. The use of duty cycles with a high percentage of anodic polarisation (90%), combined with high frequencies (1000 Hz) and the higher voltage tested (220 V), favoured the establishment of a plasma regime involving strong dielectric discharges, allowing the growth of thicker oxides but with rough architecture. The corrosion resistance of the formed film has been characterised by potentiodynamic tests in 0.5-M NaBr for localised corrosion resistance and by immersion tests in 10% v/v sulphuric acid solution for a uniform corrosion assessment. Current–time curves, visual observations and electron microscope analysis (scanning electron microscopy, energy-dispersive X-ray spectroscopy) were the tools selected to provide a correlation between technological parameters and oxide growth mechanism. For localised and uniform corrosion, anodisation at 220 V with a high level of anodic polarisation (90%) and frequency (1000 Hz) was verified to be particularly advantageous.     

Analysis of cubic and orthorhombic C<Subscript>3</Subscript>A hydration in presence of gypsum and lime

Field emission scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD) have been used to study the microstructural changes and phase development that take place during the hydration of cubic (pure) and orthorhombic (Na-doped) tricalcium aluminate (C₃A) and gypsum in the absence and presence of lime. The results demonstrate that important differences occur in the hydration of each C₃A polymorph and gypsum when no lime is added; orthorhombic C₃A reacts faster with gypsum than the cubic phase, forming longer ettringite needles; however, the presence of lime slows down the formation of ettringite in the orthorhombic sample. Additional rheometric tests showed the possible effects on the setting time in these cementitious mixes.     

Multiround algorithms for scheduling divisible loads

Divisible load applications occur in many fields of science and engineering and can be easily parallelized in a master-worker fashion, but pose several scheduling challenges. While a number of approaches have been proposed that allocate load to workers in a single round, using multiple rounds improves overlap of computation with communication. Unfortunately, multiround algorithms are difficult to analyze and have thus received only limited attention. In this paper, we answer three open questions in the multiround divisible load scheduling area: 1) how to account for latencies, 2) how to account for heterogeneous platforms, and 3) how many rounds should be used. To answer 1), we derive the first closed-form optimal schedule for a homogeneous platform with both computation and communication latencies, for a given number of rounds. To answer 2) and 3), we present a novel algorithm, UMR. We evaluate UMR in a variety of realistic scenarios.