Abstract-The success of swarm behaviors often depends on the range at which robots can communicate and the speed at which they change their behavior. Challenges arise when the communication range is too small with respect to the dynamics of the robot, preventing interactions from lasting long enough to achieve coherent swarming. To alleviate this dependency, most swarm experiments done in laboratory environments rely on communication hardware that is relatively long range and wheeled robotic platforms that have omnidirectional motion. Instead, we focus on deploying a swarm of small fixed-wing flying robots. Such platforms have limited payload, resulting in the use of short-range communication hardware. Furthermore, they are required to maintain forward motion to avoid stalling and typically adopt low turn rates because of physical or energy constraints. The tradeoff between communication range and flight dynamics is exhaustively studied in simulation in the scope of Reynolds flocking and demonstrated with up to 10 robots in outdoor experiments.

Abstract. In a simple conceptual cloud-aerosol model the mass of secondary organic aerosol (SOA) that may be formed in multiphase reaction in an idealized scenario involving two cloud cycles separated with a cloud-free period is evaluated. The conditions are set to those typical of continental clouds, and each parameter used in the model calculations is selected as a mean of available observational data of individual species for which the multiphase SOA formation route has been established. In the idealized setting gas and aqueous-phase reactions are both considered, but only the latter is expected to yield products of sufficiently low volatility to be retained by aerosol particles after the cloud dissipates. The key variable of the model is the Henry-constant which primarily determines how important multiphase reactions are relative to gas-phase photooxidation processes. The precursor considered in the model is assumed to already have some affinity to water, i.e. it is a compound having oxygen-containing functional group(s). As a principal model output an aerosol yield parameter is calculated for the multiphase SOA formation route as a function of the Henry-constant, and has been found to be significant already above H~103 M atm-1. Among the potential precursors that may be eligible for this mechanism based on their Henry constants, there are a suite of oxygenated compounds such as primary oxidation products of biogenic and anthropogenic hydrocarbons, including, for example, pinonaldehyde. Finally, the analogy of multiphase SOA formation to in-cloud sulfate production is exploited.

This study investigated whether chronic coadministration of alpha-dihydroergocryptine (DHEC) altered the plasma pharmacokinetics of individualized treatments with levodopa in 12 patients with Parkinson's disease. Steady-state pharmacokinetics of plasma levodopa (L-Dopa) under combined treatment were compared with those under treatment with L-Dopa alone. There was no evidence of increased exposure to L-Dopa caused by concomitant treatment with DHEC. In contrast, additional treatment with DHEC reduced the overall exposure to L-Dopa (17.5% reduction in area under the curve; 95% CI: 23%-6%). This effect was small but statistically significant for the area under the plasma concentration-time curve, whereas tmax (time of maximum plasma concentration) and peak-to-trough fluctuation were not affected. Cmax (maximum plasma concentration), on average, was reduced to a similar extent (-14.5%; 95% CI: 38% to -17%), albeit not significantly. The magnitude of the interaction does not suggest changing the current clinical practice of up-titrating DHEC and subsequently adapting L-Dopa to the individual needs of patients.

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most policy evaluation models do not incorporate geography which is in contradiction with the increased interest in agglomeration effects (such as localized knowledge spillovers) in economics. this paper explains the manner how the geography of innovation literature contributes to develop models to be used for assessing regional, macro and interregional impacts of development policy interventions. the case of the paper is the GmR-Hungary model. Policy simulation results demonstrate the power of such a modeling approach. De la Géographie de l'Innovation à l'analyse des politiques de développement : l'approche GMR RÉSUMÉ.-la plupart des modèles d'évaluation des politiques publiques ne tiennent pas compte de la Géographie. ceci est en contradiction avec l'intérêt croissant porté en économie aux effets d'agglomération (comme les formes localisées de diffusion des connaissances, « localized knowledge spillovers »). c'est pourquoi cet article explique la façon dont la Géographie de l'innovation contribue au développement de modèles pouvant être utilisés pour analyser les impacts des politiques de développement, au niveau régional, macroéconomique et interrégional. le cas étudié dans cet article est le modèle GmR appliqué à la Hongrie. les résultats des simulations démontrent la puissance de cette forme de modélisation. the author expresses his thanks to the collaborators on the GmR-Hungary model project: Hans Joachim schalk, atsushi Koike, lori tavasszy, János monigl, Zoltán Újhelyi, Péter Járosi, onno Hoffmeister, Balázs marján and tamás Révész. special appreciation goes for the comments on earlier versions of the model and this paper to Jan oosterhaven, tamás mellár, Gábor Rappai, Roberta capello, János Vincze, Klára major, andrás simon, corinne autant-Bernard, nadine massard, Peter nijkamp, Johannes Bröcker, Zoltan acs, ed Faser, Jun Koo, michael luger, Zoltán schepp, Gábor Balás, attila Béres, tamás tétényi, lászló ember the two anonymous referees and participants in several conferences, workshops and seminars where model results were presented. * a. Varga : department of economics and Regional studies, Faculty of Business and economics, university of Pécs. 1. For a systematic overview of the subject see reamer, ICerman and YoutIe [2003].