How to motivate laying hens to use the hen run?

In organic agriculture, hens are kept in free range systems. A free range is an enrichment for the hens and brings several advantages for them. Laying hens may show behavioural elements that are not possible in a poultry house. For instance, sunbathing behaviour is only shown in direct sunlight and not in artificial light (Huber, 1987). Hens spend 35.3-47.5% of their time with food searching (Fölsch and Vestergaard, 1981) and, in natural habitats, invertebrate food appears to be an importnat addition to the diet (Savory et al. 1978). Free range systems may also have an influence on animal health and product quality. Lopez-Bote et al. (1998) suggested that some constituents of grass might be of interest for the production of eggs rich in (n-3) fatty acids. In flocks of free range hens, generally only a small proportion of the flock is outside at any one time, and most hens stay near the poultry house. In an account of the uneven distribution of the hens in the free range area, Menzi et al. (1997) found a nutrient and heavy metal overload on the frequently used parts of the run. For a better distribution, they, as well as several label programmes, recommend to structure the outdoor area with trees and installations providing shade and protection for the hens. We attempted to determine management and structural factors that would result in more hens in the run and a more even distribution of the animals in several experiments, with a special emphasis on the idea that the hen run should be easily manageable for the farmer

Optimising the use of hen runs by structures and management

One of the main problems in free range husbandry of laying hens is the uneven use of the hen run. This leads to an overuse of pasture near the hen house. In a series of behavioural experiments we tried to determine management and structuring factors which may result in more hens in the run and a more even distribution of the animals

On acceleration and motion of ions in corona and solar wind

Equations of motion for ions in corona and solar win

Panel III: Implications of the New Telecommunications Legislation

We present a method that employs a tree-based Neural Network (NN) for performing classification. The novel mechanism, apart from incorporating the information provided by unlabeled and labeled instances, re-arranges the nodes of the tree as per the laws of Adaptive Data Structures (ADSs). Particularly, we investigate the Pattern Recognition (PR) capabilities of the Tree-Based Topology-Oriented SOM (TTOSOM) when Conditional Rotations (CONROT) [8] are incorporated into the learning scheme. The learning methodology inherits all the properties of the TTOSOM-based classifier designed in [4]. However, we now augment it with the property that frequently accessed nodes are moved closer to the root of the tree. Our experimental results show that on average, the classification capabilities of our proposed strategy are reasonably comparable to those obtained by some of the state-of-the-art classification schemes that only use labeled instances during the training phase. The experiments also show that improved levels of accuracy can be obtained by imposing trees with a larger number of nodes

Astronomical-topographic levelling using high-precision astrogeodetic vertical deflections and digital terrain model data

At the beginning of the twenty-first century, a technological change took place in geodetic astronomy by the development of Digital Zenith Camera Systems (DZCS). Such instruments provide vertical deflection data at an angular accuracy level of 0".1 and better. Recently, DZCS have been employed for the collection of dense sets of astrogeodetic vertical deflection data in several test areas in Germany with high-resolution digital terrain model (DTM) data (10-50 m resolution) available. These considerable advancements motivate a new analysis of the method of astronomical-topographic levelling, which uses DTM data for the interpolation between the astrogeodetic stations. We present and analyse a least-squares collocation technique that uses DTM data for the accurate interpolation of vertical deflection data. The combination of both data sets allows a precise determination of the gravity field along profiles, even in regions with a rugged topography. The accuracy of the method is studied with particular attention on the density of astrogeodetic stations. The error propagation rule of astronomical levelling is empirically derived. It accounts for the signal omission that increases with the station spacing. In a test area located in the German Alps, the method was successfully applied to the determination of a quasigeoid profile of 23 km length. For a station spacing from a few 100 m to about 2 km, the accuracy of the quasigeoid was found to be about 1-2 mm, which corresponds to a relative accuracy of about 0.05-0.1 ppm. Application examples are given, such as the local and regional validation of gravity field models computed from gravimetric data and the economic gravity field determination in geodetically less covered regions

An episode mimicking a versive seizure in acute bilateral pontine stroke.

Pontine ischemia usually results in focal deficits such as hemiparesis, facial palsy, dysarthria, disorders of eye movements or vertigo. Although rarely described, involuntary abnormal movements and "convulsions" due to pontine lesions can also occur. Here we describe a 67-year-old woman with hypertension who presented with a tonic movement mimicking a versive seizure in the acute phase of bilateral pontine ischemia. Post-stroke movement disorders are well known. They are usually associated with supratentorial lesions and rarely occur in the acute phase, but "seizure-like" episodes can be seen in pontine ischemia. Awareness of this rare phenomenon is useful for the management of acute stroke patients

An end-to-end process model for supervised machine learning classification: from problem to deployment in information systems

Extracting meaningful knowledge from (big) data represents a key success factor in many industries today. Supervised machine learning (SML) has emerged as a popular technique to learn patterns in complex data sets and to identify hidden correlations. When this insight is turned into action, business value is created. However, common data mining processes are generally not tailored to SML. In addition, they fall short of providing an end-to-end view that not only supports building a ”one off” model, but also covers its operational deployment within an information system. In this research-in-progress work we apply a Design Science Research (DSR) approach to develop a SML process model artifact that comprises model initiation, error estimation and deployment. In a first cycle, we evaluate the artifact in an illustrative scenario to demonstrate suitability. The results encourage us to further refine the approach and to prepare evaluations in concrete use cases. Thus, we move towards contributing a general process model that supports the systematic design of machine learning solutions to turn insights into continuous action

I\u27ve Set My Heart On You

https://digitalcommons.library.umaine.edu/mmb-vp/3235/thumbnail.jp

Data Analysis Techniques for Fan Performance in Highly-Distorted Flows from Boundary Layer Ingesting Inlets

The design of a unique distortion-tolerant fan for a high-bypass ratio boundary-layer ingesting propulsion system has been completed and a rig constructed and tested in the NASA Glenn 8x6 wind tunnel. Processing the data from the experiment presented some interesting challenges because of the complexity of the experimental setup and the flow through the test rig. The experiment was run in three phases, each of which employed a unique complement of inlet throat and fan face instrumentation to avoid the blockage that would have resulted from simultaneously installing all of the rakes. The measurement from the individual test points were subsequently combined to compute the overall stage performance. A CFD model of the experiment was used to gain understanding of the flow field and to test some of the techniques proposed for interpolating and extrapolating the measurements into regions where measurements were not made. This capability became extremely useful when it was discovered that there was an unexpected total temperature distortion in the tunnel. The CFD model was modified by inserting a total temperature profile at the upstream boundary that mimicked the measured distortion where measurements were available and that CFD solution was used to investigate methods to infer the complete total temperature field at the fan face