Structure of Titan ’ s induced magnetosphere under varying background magnetic fi eld conditions: Survey of Cassini magnetometer data from fl ybys TA – T85

Cassini magnetic field observations between 2004 and 2012 suggest the ambient field conditions near Titan’s orbit to differ significantly from the frequently applied pre-Cassini picture (background magnetic field homogeneous and perpendicular to Titan’s orbital plane, stationary upstream conditions). In this study, we analyze the impact of these varying background field conditions on the structure of Titan’s induced magnetosphere by conducting a systematic survey of Cassini magnetic field observations in the interaction region during flybys TA–T85 (July 2004–July 2012). We introduce a set of criteria that allow to identify deviations in the structure of Titan’s induced magnetosphere—as seen by the Cassini magnetometer (MAG)—from the picture of steady-state field line draping. These disruptions are classified as “weak”, “moderate”, or “strong”. After applying this classification scheme to all available Titan encounters, we survey the data for a possible correlation between the disruptions of the draping pattern and the ambient magnetospheric field conditions, as characterized by Simon et al. [2010a]. Our major findings are: (1) When Cassini is embedded in the northern or southern lobe of Saturn’s magnetodisk within a ` 3 h interval around closest approach, Titan’s induced magnetosphere shows little or no deviations at all from the steady-state draping picture. (2) Even when Titan is embedded in perturbed current sheet fields during an encounter, the notion of draping the average background field around the moon’s ionosphere is still applicable to explain MAG observations from numerous Titan flybys. (3) Only when Titan is exposed to intense north- south oscillations of Saturn’s current sheet at the time of an encounter, the signatures of the moon’s induced magnetosphere may be completely obscured by the ambient field perturbations. (4) So far, T70 is the only flyby that fully meets the idealized pre-Cassini picture of the Titan interaction (steady background field perpendicular to Titan’s orbital plane, steady upstream flow, unperturbed induced magnetosphere).Fil: Simon, Sven. University of Cologne. Institute of Geophysics and Meteorology; AlemaniaFil: van Treeck, Shari C.. University of Cologne. Institute of Geophysics and Meteorology; AlemaniaFil: Wennmacher, Alexandre. University of Cologne. Institute of Geophysics and Meteorology; AlemaniaFil: Saur, Joachim. University of Cologne. Institute of Geophysics and Meteorology; AlemaniaFil: Neubauer, Fritz M.. University of Cologne. Institute of Geophysics and Meteorology; AlemaniaFil: Bertucci, Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio(i); ArgentinaFil: Dougherty, Michele K.. Imperial College Of Science And Technology. Space and Atmospheric Physics Group; Reino Unid

Probing the Superfluid to Mott Insulator Transition at the Single Atom Level

Quantum gases in optical lattices offer an opportunity to experimentally realize and explore condensed matter models in a clean, tunable system. We investigate the Bose-Hubbard model on a microscopic level using single atom-single lattice site imaging; our technique enables space- and time-resolved characterization of the number statistics across the superfluid-Mott insulator quantum phase transition. Site-resolved probing of fluctuations provides us with a sensitive local thermometer, allows us to identify microscopic heterostructures of low entropy Mott domains, and enables us to measure local quantum dynamics, revealing surprisingly fast transition timescales. Our results may serve as a benchmark for theoretical studies of quantum dynamics, and may guide the engineering of low entropy phases in a lattice

Diversification and hybridization in firm knowledge bases in nanotechnologies

The paper investigates the linkages between the characteristics of technologies and the structure of a firms' knowledge base. Nanotechnologies have been defined as converging technologies that operate at the nanoscale, and which require integration to fulfill their economic promises. Based on a worldwide database of nanofirms, the paper analyses the degree of convergence and the convergence mechanisms within firms. It argues that the degree of convergence in a firm's nano-knowledge base is relatively independent from the size of the firm's nano-knowledge base. However, while firms with small nano-knowledge bases tend to exploit convergence in each of their patents/publications, firms with large nano-knowledge bases tend to separate their nano-R&D activities in the different established fields and achieve diversity through the juxtaposition of the output of these independent activities For more informations http://www.nanoeconomics.eu/

Blended Biogeography-based Optimization for Constrained Optimization

Biogeography-based optimization (BBO) is a new evolutionary optimization method that is based on the science of biogeography. We propose two extensions to BBO. First, we propose a blended migration operator. Benchmark results show that blended BBO outperforms standard BBO. Second, we employ blended BBO to solve constrained optimization problems. Constraints are handled by modifying the BBO immigration and emigration procedures. The approach that we use does not require any additional tuning parameters beyond those that are required for unconstrained problems. The constrained blended BBO algorithm is compared with solutions based on a stud genetic algorithm (SGA) and standard particle swarm optimization 2007 (SPSO 07). The numerical results demonstrate that constrained blended BBO outperforms SGA and performs similarly to SPSO 07 for constrained single-objective optimization problems

Analysis of Migration Models of Biogeography-based Optimization Using Markov Theory

Biogeography-based optimization (BBO) is a new evolutionary algorithm inspired by biogeography, which involves the study of the migration of biological species between habitats. Previous work has shown that various migration models of BBO result in significant changes in performance. Sinusoidal migration models have been shown to provide the best performance so far. Motivated by biogeography theory and previous results, in this paper a generalized sinusoidal migration model curve is proposed. A previously derived BBO Markov model is used to analyze the effect of migration models on optimization performance, and new theoretical results which are confirmed with simulation results are obtained. The results show that the generalized sinusoidal migration model is significantly better than other models for simple but representative problems, including a unimodal one-max problem, a multimodal problem, and a deceptive problem. In addition, performance comparison is further investigated through 23 benchmark functions with a wide range of dimensions and diverse complexities, to verify the superiority of the generalized sinusoidal migration model

In vitro identification and in silico utilization of interspecies sequence similarities using GeneChip(® )technology

BACKGROUND: Genomic approaches in large animal models (canine, ovine etc) are challenging due to insufficient genomic information for these species and the lack of availability of corresponding microarray platforms. To address this problem, we speculated that conserved interspecies genetic sequences can be experimentally detected by cross-species hybridization. The Affymetrix platform probe redundancy offers flexibility in selecting individual probes with high sequence similarities between related species for gene expression analysis. RESULTS: Gene expression profiles of 40 canine samples were generated using the human HG-U133A GeneChip (U133A). Due to interspecies genetic differences, only 14 ± 2% of canine transcripts were detected by U133A probe sets whereas profiling of 40 human samples detected 49 ± 6% of human transcripts. However, when these probe sets were deconstructed into individual probes and examined performance of each probe, we found that 47% of human probes were able to find their targets in canine tissues and generate a detectable hybridization signal. Therefore, we restricted gene expression analysis to these probes and observed the 60% increase in the number of identified canine transcripts. These results were validated by comparison of transcripts identified by our restricted analysis of cross-species hybridization with transcripts identified by hybridization of total lung canine mRNA to new Affymetrix Canine GeneChip(®). CONCLUSION: The experimental identification and restriction of gene expression analysis to probes with detectable hybridization signal drastically increases transcript detection of canine-human hybridization suggesting the possibility of broad utilization of cross-hybridizations of related species using GeneChip technology