A stochastic movement simulator improves estimates of landscape connectivity

Acknowledgments This publication issued from the project TenLamas funded by the French Ministère de l'Energie, de l'Ecologie, du Développement Durable et de la Mer through the EU FP6 BiodivERsA Eranet; by the Agence Nationale de la Recherche (ANR) through the open call INDHET and 6th extinction MOBIGEN to V. M. Stevens, M. Baguette, and A. Coulon, and young researcher GEMS (ANR-13-JSV7-0010-01) to V. M. Stevens and M. Baguette; and by a VLIR-VLADOC scholarship awarded to J. Aben. L. Lens, J. Aben, D. Strubbe, and E. Matthysen are grateful to the Research Foundation Flanders (FWO) for financial support of fieldwork and genetic analysis (grant G.0308.13). V. M. Stevens and M. Baguette are members of the “Laboratoire d'Excellence” (LABEX) entitled TULIP (ANR-10-LABX-41). J. M. J. Travis and S. C. F. Palmer also acknowledge the support of NERC. A. Coulon and J. Aben contributed equally to the work.Peer reviewedPublisher PD

Cognitive mapping of organic vegetable production in Flanders to support farmers strategy design

Organic farmers inherently have to cope with complex agricultural production system processes. Next to pursuing economic performance, farm management also encompasses optimization of the farm's ecological and social performance. The question arises how to maintain a certain balance between the multiple purposes. For this consideration, farmers as well as researchers need to have a good understanding of the whole farm functioning. Therefore this study aims to model the factors and their inter-relations influencing an organic farmers' decision-making process. These factors and inter-relations were modelled by using the qualitative cognitive mapping technique. Cognitive mapping can be used to develop maps of socio-ecological systems based on people's knowledge of ecosystems. Different stakeholders (farmers and experts) were interviewed in order to represent and visualize their tacit knowledge. Through in-depth interviews, stakeholders were questioned on the critical success factors of organic farm management and how these factors relate to each other. Based on these interviews, individual cognitive maps were constructed which were subsequently merged to build a social cognitive map. The social cognitive map represents the stakeholders' perception of the agricultural production system. It covers a broad range of factors (economic, agro-technical and biophysical factors, next to a few social factors), of which the most central ones are crop choice, crop rotation, marketing and technology and mechanization

Temperature-dependent thermal conductivity in silicon nanostructured materials studied by the Boltzmann transport equation

Nanostructured materials exhibit low thermal conductivity because of the additional scattering due to phonon-boundary interactions. As these interactions are highly sensitive to the mean free path (MFP) of phonons, MFP distributions in nanostructures can be dramatically distorted relative to bulk. Here we calculate the MFP distribution in periodic nanoporous Si for different temperatures, using the recently developed MFP-dependent Boltzmann transport equation. After analyzing the relative contribution of each phonon branch to thermal transport in nanoporous Si, we find that at room temperature optical phonons contribute 17% to heat transport, compared to 5% in bulk Si. Interestingly, we observe a constant thermal conductivity over the range 200 K < T < 300 K. We attribute this behavior to the ballistic transport of acoustic phonons with long intrinsic MFP and the temperature dependence of the heat capacity. Our findings, which are in qualitative agreement with the temperature trend of thermal conductivities measured in nanoporous Si-based systems, shed light on the origin of the reduction of thermal conductivity in nanostructured materials and demonstrate the necessity of multiscale heat transport engineering, in which the bulk material and geometry are optimized concurrently.United States. Dept. of Energy. Office of Science (Solid-State Solar-Thermal Energy Conversion Center Award DE-SC0001299)Deshpande Center for Technological Innovatio

Symbolic Algebra and Renormalization of Gauge Theories

Symbolic algebra relevant to the renormalization of gauge theories can be efficiently performed by machine using modern packages. We devise a scheme for representing and manipulating the objects involved in perturbative calculations of gauge theories. This scheme is readily implemented using the general purpose package, Mathematica. The techniques discussed are used to calculate renormalization group functions for a non-abelian $SU(m)$ gauge theory with massless fermions in a representation R, in the two-loop approximation, and to simplify some expressions arising in electroweak calculations at the two loop level.Comment: 16 pages, LaTex, 2 diagrams drawn with FEYNMAN, uses cite.sty Entire manuscript available as a ps file at http://www.physics.adelaide.edu.au/theory/home.html Also available via anonymous ftp at ftp://adelphi.adelaide.edu.au/pub/theory/ADP-95-41.T193.ps Accepted for publication in Computer Physics Communicatio

Rare presentation of a squamous cell carcinoma originating from gastric compartment 1 in an alpaca = Bijzondere presentatie van een squameus celcarcinoom afkomstig vancompartiment 1 van de maag bij een alpaca

A twenty-year-old, male, intact alpaca with a history of anorexia, progressive weakness and recumbency was euthanized because of a poor prognosis and clinical deterioration. The animal was submitted for necropsy at the pathology department of Dierengezondheidszorg Vlaanderen (DGZ) diagnostic lab. A full necropsy was performed and showed a large firm white mass measuring 18x8x10 cm attached to the dorsal wall of gastric compartment 1 (C1) and expanding to the abdominal aorta. Miliary small white metastatic nodules were present on the pleura and peritoneum (carcinomatosis). Multiple small white metastatic nodules were also present in the parenchyma of the liver. On histological investigation, this neoplasia was characterized as squamous cell carcinoma (SCC)