5,750 research outputs found

    Behaviour of dairy cows on organic and non-organic farms

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    There is an increasing number of organic dairy farms in the UK. The aim of this study is to compare behaviour of dairy cows on organic and non-organic farms. Twenty organic and 20 non-organic farms throughout the UK were visited over two winters (2004/05 and 2005/06). Organic and non-organic farms were paired for housing type, herd size, milk production traits and location. The number of cows feeding was counted every fifteen minutes for 4.5 h after new feed was available post morning milking. Behaviour at the feed-face was recorded for 60 minutes and aggressive interactions between cows were quantified. Farm type had no effect on numbers of cows feeding. There were more interactions between cows feeding at open feed-faces compared to head-bale barriers. At open feed-faces, there were more interactions on organic farms than non-organic. It is possible that organic cows were hungrier than non-organic cows after the arrival of new feed

    No classical limit of quantum decay for broad states

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    Though the classical treatment of spontaneous decay leads to an exponential decay law, it is well known that this is an approximation of the quantum mechanical result which is a non-exponential at very small and large times for narrow states. The non exponential nature at large times is however hard to establish from experiments. A method to recover the time evolution of unstable states from a parametrization of the amplitude fitted to data is presented. We apply the method to a realistic example of a very broad state, the sigma meson and reveal that an exponential decay is not a valid approximation at any time for this state. This example derived from experiment, shows the unique nature of broad resonances

    UAV Model-based Flight Control with Artificial Neural Networks: A Survey

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    Model-Based Control (MBC) techniques have dominated flight controller designs for Unmanned Aerial Vehicles (UAVs). Despite their success, MBC-based designs rely heavily on the accuracy of the mathematical model of the real plant and they suffer from the explosion of complexity problem. These two challenges may be mitigated by Artificial Neural Networks (ANNs) that have been widely studied due to their unique features and advantages in system identification and controller design. Viewed from this perspective, this survey provides a comprehensive literature review on combined MBC-ANN techniques that are suitable for UAV flight control, i.e., low-level control. The objective is to pave the way and establish a foundation for efficient controller designs with performance guarantees. A reference template is used throughout the survey as a common basis for comparative studies to fairly determine capabilities and limitations of existing research. The end-result offers supported information for advantages, disadvantages and applicability of a family of relevant controllers to UAV prototypes

    Mars Sample Return Mission: Mars Ascent Vehicle Propulsion Design

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    The aim of this research is to analyze a potential Mars Sample Return (MSR) mission through the study of an optimized design of the Mars Ascent Vehicle (MAV) propulsion system. The main goal of the MSR mission is to return to Earth samples of rocks and dust collected by a rover operating on the surface of Mars, and conveyed to the MAV into an Orbit Sample (OS) canister. The MAV must accomplish an initial ascent phase from the Mars surface to a circular Low Mars Orbit (LMO) with a radius of 500 Km and 30° inclination, and then with its second stage it must circularize into the target LMO where it releases the OS payload. A combination of the MAV and a second vehicle, the Mars Earth Return Vehicle (MERV) orbiter, is required to fulfill the final return phase from Mars to the Earth. After completing three different phases of rendezvous operations, with a final Hohmann Transfer the MERV is able to bring the OS to Earth with its payload. A spreadsheet model enables the evaluation of two different MAV architecture: a two-stage solid rocket, and a two-stage hybrid rocket. The study is based on the main rocket science equations, including the Tsiolkovsky Rocket Equation that calculates the change in velocity Delta V for the two stages of the MAV and the amount of propellant needed for both stages. From the analysis it can be noted that the two-stage hybrid design has significant advantages, firstly in terms of Gross Lift Off Mass GLOM (270 Kg) when compared to the solid solution (355 Kg). The hybrid rocket also has lower mass by up to 60 Kg since it does not require a thermal igloo. Finally, the mass fractions for both stages are comparable, and the required Delta V for the hybrid stages are less than those needed for the solid, allowing considerable fuel savings. The hybrid solution is ultimately preferred, considering the best performance related to the thermal fuel properties enabling the MAV to safely operated in the harsh Martian environment

    Sensitivity-analysis method for inverse simulation application

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    An important criticism of traditional methods of inverse simulation that are based on the Newton–Raphson algorithm is that they suffer from numerical problems. In this paper these problems are discussed and a new method based on sensitivity-analysis theory is developed and evaluated. The Jacobian matrix may be calculated by solving a sensitivity equation and this has advantages over the approximation methods that are usually applied when the derivatives of output variables with respect to inputs cannot be found analytically. The methodology also overcomes problems of input-output redundancy that arise in the traditional approaches to inverse simulation. The sensitivity- analysis approach makes full use of information within the time interval over which key quantities are compared, such as the difference between calculated values and the given ideal maneuver after each integration step. Applications to nonlinear HS125 aircraft and Lynx helicopter models show that, for this sensitivity-analysis method, more stable and accurate results are obtained than from use of the traditional Newton–Raphson approach

    A framework for community curation of interspecies interactions literature

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    The quantity and complexity of data being generated and published in biology has increased substantially, but few methods exist for capturing knowledge about phenotypes derived from molecular interactions between diverse groups of species, in such a way that is amenable to data-driven biology and research. To improve access to this knowledge, we have constructed a framework for the curation of the scientific literature studying interspecies interactions, using data curated for the Pathogen–Host Interactions database (PHI-base) as a case study. The framework provides a curation tool, phenotype ontology, and controlled vocabularies to curate pathogen–host interaction data, at the level of the host, pathogen, strain, gene, and genotype. The concept of a multispecies genotype, the ‘metagenotype,’ is introduced to facilitate capturing changes in the disease-causing abilities of pathogens, and host resistance or susceptibility, observed by gene alterations. We report on this framework and describe PHI-Canto, a community curation tool for use by publication authors

    Facial recognition during early motherhood: Investigating the persistence of age and affect biases

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    Converging evidence demonstrates increased levels of sensitivity to infant faces in mothers. This may be reflective of a series of psychological and neurobiological changes that occur in the transition to, and during early, parenthood for the purpose of appropriate caregiving; however, this enhanced infant facial recognition is in contrast with the general adult literature regarding facial processing. In the current study, we aimed to replicate a prior study of emotion facial recognition in pregnant women in a sample of mothers with children under a year old, utilizing a paradigm in which adult and infant faces gradually changed from neutral expressions to either happy or sad expressions. Mothers were faster at the recognition of adult faces in comparison to infant faces, and were also faster at happy faces in comparison to sad faces. Results are discussed in context of the current processing literature regarding the perinatal period, and implications for the persistence of the own-age bias and happy face advantage are considered
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