The Effect of Diet and Oral Antibiotic Therapy on Immune Function and Productivity in Young Pigs

Medicated early weaning programs have been shown to be an excellent method to control disease incidence in the young pig. Additional research by Dritz, et al1, showed that early weaning at 7-10 days without medication resulted in significant weight gains over conventional weaning at 14-17 days. We were interested in the effects of low levels of conventional water and feed grade antibiotic tratments on performance and immunological parameters of the young pig in a commercial operation. Previously, we had tested this treatment at a research facility and had shown increased production and a decreased polyclonal immunological response in the reated animals23. The use of such a program would be a benefit to producers who do not have the production facilities that allowing for early weaning (7-10 days) and/or multisite production. A study was conducted to determine the effect of AureomycinTM and Aureo-SulmetTM on production. The study was a 2X2 factorial experiment to determine the effect of weaning treatment and nutrition level on immune response

Studies in Antarctic palaeobotany.

Collections of three fossil'floras have"been made recentlý by the British Antarctic Survey. They include Lower Permian'material f=m the Theron F4untainsp Coats Landt Antarctic I-lainland, Mid - Upper Triassic material from Livingston Island in the South Shetlands and Tertiaxy material from King George-, Island in the South Shetlands, Each collection is described in detail systematically and is discussed with reference to its compositiong, comparison with other floras, age and possible palaeoenvironmen

Outbreak of encephalitic listeriosis in red-legged partridges (Alectoris rufa)

An outbreak of neurological disease was investigated in red-legged partridges between 8 and 28 days of age. Clinical signs included torticollis, head tilt and incoordination and over an initial eight day period approximately 30–40 fatalities occurred per day. No significant gross post mortem findings were detected. Histopathological examination of the brain and bacterial cultures followed by partial sequencing confirmed a diagnosis of encephalitis due to Listeria monocytogenes. Further isolates were obtained from follow-up carcasses, environmental samples and pooled tissue samples of newly imported day-old chicks prior to placement on farm. These isolates had the same antibiotic resistance pattern as the isolate of the initial post mortem submission and belonged to the same fluorescent amplified fragment length polymorphism (fAFLP) subtype. This suggested that the isolates were very closely related or identical and that the pathogen had entered the farm with the imported day-old chicks, resulting in disease manifestation in partridges between 8 and 28 days of age. Reports of outbreaks of encephalitic listeriosis in avian species are rare and this is to the best of our knowledge the first reported outbreak in red-legged partridges

Future opportunities and trends for e-infrastructures and life sciences: Going beyond the grid to enable life science data analysis

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community

A methodology for measuring the sustainability of car transport systems

Measuring the sustainability of car fleets, an important task in developing transport policy, can be accomplished with an appropriate set of indicators. We applied the Process Analysis Method of sustainability assessment to generate an indicator set in a systematic and transparent way, that is consistent with a declared definition of a sustainable transport system. Our method identifies stakeholder groups, the full range of impacts across the environmental, economic and human/social domains of sustainability, and those who generate and receive those impacts. Car users are shown by the analysis to have dual roles, both as individual makers of decisions and as beneficiaries/sufferers of the impacts resulting from communal choice. Thus car users, through their experience of service quality, are a potential force for system change. Our method addresses many of the well-known flaws in measuring transport sustainability. The indicator set created is independent of national characteristics and will be useful to transport policy practitioners and sustainable mobility researchers globally. © 2013 Elsevier Ltd

The distribution of transit durations for Kepler planet candidates and implications for their orbital eccentricities

‘In these times, during the rise in the popularity of institutional repositories, the Society does not forbid authors from depositing their work in such repositories. However, the AAS regards the deposit of scholarly work in such repositories to be a decision of the individual scholar, as long as the individual's actions respect the diligence of the journals and their reviewers.’ Original article can be found at : http://iopscience.iop.org/ Copyright American Astronomical SocietyDoppler planet searches have discovered that giant planets follow orbits with a wide range of orbital eccentricities, revolutionizing theories of planet formation. The discovery of hundreds of exoplanet candidates by NASA's Kepler mission enables astronomers to characterize the eccentricity distribution of small exoplanets. Measuring the eccentricity of individual planets is only practical in favorable cases that are amenable to complementary techniques (e.g., radial velocities, transit timing variations, occultation photometry). Yet even in the absence of individual eccentricities, it is possible to study the distribution of eccentricities based on the distribution of transit durations (relative to the maximum transit duration for a circular orbit). We analyze the transit duration distribution of Kepler planet candidates. We find that for host stars with T > 5100 K we cannot invert this to infer the eccentricity distribution at this time due to uncertainties and possible systematics in the host star densities. With this limitation in mind, we compare the observed transit duration distribution with models to rule out extreme distributions. If we assume a Rayleigh eccentricity distribution for Kepler planet candidates, then we find best fits with a mean eccentricity of 0.1-0.25 for host stars with T ≤ 5100 K. We compare the transit duration distribution for different subsets of Kepler planet candidates and discuss tentative trends with planetary radius and multiplicity. High-precision spectroscopic follow-up observations for a large sample of host stars will be required to confirm which trends are real and which are the results of systematic errors in stellar radii. Finally, we identify planet candidates that must be eccentric or have a significantly underestimated stellar radius.Peer reviewedFinal Accepted Versio

Optimal dynamic portfolio selection with earnings-at-risk

In this paper we investigate a continuous-time portfolio selection problem. Instead of using the classical variance as usual, we use earnings-at-risk (EaR) of terminal wealth as a measure of risk. In the settings of Black-Scholes type financial markets and constantly-rebalanced portfolio (CRP) investment strategies, we obtain closed-form expressions for the best CRP investment strategy and the efficient frontier of the mean-EaR problem, and compare our mean-EaR analysis to the classical mean-variance analysis and to the mean-CaR (capital-at-risk) analysis. We also examine some economic implications arising from using the mean-EaR model. © 2007 Springer Science+Business Media, LLC.postprin

Energy Contents of Some Well-Known Solutions in Teleparallel Gravity

In the context of teleparallel equivalent to General Relativity, we study energy and its relevant quantities for some well-known black hole solutions. For this purpose, we use the Hamiltonian approach which gives reasonable and interesting results. We find that our results of energy exactly coincide with several prescriptions in General Relativity. This supports the claim that different energy-momentum prescriptions can give identical results for a given spacetime. We also evaluate energy-momentum flux of these solutions.Comment: 16 pages, accepted for publication in Astrophys. Space Sc

Object Detection-Based Location and Activity Classification from Egocentric Videos: A Systematic Analysis

Egocentric vision has emerged in the daily practice of application domains such as lifelogging, activity monitoring, robot navigation and the analysis of social interactions. Plenty of research focuses on location detection and activity recognition, with applications in the area of Ambient Assisted Living. The basis of this work is the idea that indoor locations and daily activities can be characterized by the presence of specific objects. Objects can be obtained either from laborious human annotations or automatically, using vision-based detectors. We perform a study regarding the use of object detections as input for location and activity classification and analyze the influence of various detection parameters. We compare our detections against manually provided object labels and show that location classification is affected by detection quality and quantity. Utilization of the temporal structure in object detections mitigates the consequences of noisy ones. Moreover, we determine that the recognition of activities is related to the presence of specific objects and that the lack of explicit associations between certain activities and objects hurts classification performance for these activities. Finally, we discuss the outcomes of each task and our method’s potential for real-world applications