Topological Non--connectivity Threshold in long-range spin systems

We demonstrate the existence of a topological disconnection threshold, recently found in Ref. \cite{JSP}, for generic $1-d$ anisotropic Heisenberg models interacting with an inter--particle potential $R^{-\alpha}$ when $0<\alpha < 1$ (here $R$ is the distance among spins). We also show that if $\alpha$ is greater than the embedding dimension $d$ then the ratio between the disconnected energy region and the total energy region goes to zero when the number of spins becomes very large. On the other hand, numerical simulations in $d=2,3$ for the long-range case $\alpha < d$ support the conclusion that such a ratio remains finite for large $N$ values. The disconnection threshold can thus be thought as a distinctive property of anisotropic long-range interacting systems.Comment: submitted to PR

MOFs as multifunctional catalysts: One-pot synthesis of menthol from citronellal over a bifunctional MIL-101 catalyst

A bifunctional MOF catalyst containing coordinatively unsaturated Cr3+ sites and palladium nanoparticles (Pd@MIL-101) has been used for the cyclization of citronellal to isopulegol and for the one-pot tandem isomerization/hydrogenation of citronellal to menthol. The MOF was found to be stable under the reaction conditions used, and the results obtained indicate that the performance of this bifunctional solid catalyst is comparable with other state-of-the-art materials for the tandem reaction: Full citronellal conversion was attained over Pd@MIL-101 in 18 h, with 86% selectivity to menthols and a diastereoselectivity of 81% to the desired (-)-menthol, while up to 30 h were necessary for attaining similar values over Ir/H-beta under analogous reaction conditions.Financial support by Ministerio de Educacion y Ciencia e Innovacion (Project MIYCIN, CSD2009-00050; PROGRAMA CONSOLIDER. INGENIO 2009), Generalidad Valenciana (GV PROMETEO/2008/130) and the CSIC (Proyectos Intramurales Especiales 201080I020) is gratefully acknowledged.García Cirujano, F.; Llabrés I Xamena, FX.; Corma Canós, A. (2012). MOFs as multifunctional catalysts: One-pot synthesis of menthol from citronellal over a bifunctional MIL-101 catalyst. Dalton Transactions. 41:4249-4254. https://doi.org/10.1039/c2dt12480gS4249425441Corma, A., García, H., & Llabrés i Xamena, F. X. (2010). Engineering Metal Organic Frameworks for Heterogeneous Catalysis. Chemical Reviews, 110(8), 4606-4655. doi:10.1021/cr9003924Farrusseng, D., Aguado, S., & Pinel, C. (2009). Metal-Organic Frameworks: Opportunities for Catalysis. Angewandte Chemie International Edition, 48(41), 7502-7513. doi:10.1002/anie.200806063Lee, J., Farha, O. K., Roberts, J., Scheidt, K. A., Nguyen, S. T., & Hupp, J. T. (2009). Metal–organic framework materials as catalysts. 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(So) Big Data and the transformation of the city

The exponential increase in the availability of large-scale mobility data has fueled the vision of smart cities that will transform our lives. The truth is that we have just scratched the surface of the research challenges that should be tackled in order to make this vision a reality. Consequently, there is an increasing interest among different research communities (ranging from civil engineering to computer science) and industrial stakeholders in building knowledge discovery pipelines over such data sources. At the same time, this widespread data availability also raises privacy issues that must be considered by both industrial and academic stakeholders. In this paper, we provide a wide perspective on the role that big data have in reshaping cities. The paper covers the main aspects of urban data analytics, focusing on privacy issues, algorithms, applications and services, and georeferenced data from social media. In discussing these aspects, we leverage, as concrete examples and case studies of urban data science tools, the results obtained in the “City of Citizens” thematic area of the Horizon 2020 SoBigData initiative, which includes a virtual research environment with mobility datasets and urban analytics methods developed by several institutions around Europe. We conclude the paper outlining the main research challenges that urban data science has yet to address in order to help make the smart city vision a reality

The Northern ROSAT All-Sky (NORAS) Galaxy Cluster Survey I: X-ray Properties of Clusters Detected as Extended X-ray Sources

In the construction of an X-ray selected sample of galaxy clusters for cosmological studies, we have assembled a sample of 495 X-ray sources found to show extended X-ray emission in the first processing of the ROSAT All-Sky Survey. The sample covers the celestial region with declination $\delta \ge 0\deg$ and galactic latitude $|b_{II}| \ge 20\deg$ and comprises sources with a count rate $\ge 0.06$ counts s$^{-1}$ and a source extent likelihood of 7. In an optical follow-up identification program we find 378 (76%) of these sources to be clusters of galaxies. ...Comment: 61 pages; ApJS in press; fixed bug in table file; also available at (better image quality) http://www.xray.mpe.mpg.de/theorie/NORAS

Italian multicenter study on infection hazards during dental practice: Control of environmental microbial contamination in public dental surgeries

Background. The present study assessed microbial contamination in Italian dental surgeries. Methods. An evaluation of water, air and surface microbial contamination in 102 dental units was carried out in eight Italian cities. Results. The findings showed water microbial contamination in all the dental surgeries; the proportion of water samples with microbial levels above those recommended decreased during working. With regard to Legionella spp., the proportion of positive samples was 33.3%. During work activity, the index of microbial air contamination (IMA) increased. The level of microbial accumulation on examined surfaces did not change over time. Conclusion. These findings confirm that some Italian dental surgeries show high biocontamination, as in other European Countries, which highlights the risk of occupational exposure and the need to apply effective measures to reduce microbial loads

MyWay: Location prediction via mobility profiling

Forecasting the future positions of mobile users is a valuable task allowing us to operate efficiently a myriad of different applications which need this type of information. We propose MyWay, a prediction system which exploits the individual systematic behaviors modeled by mobility profiles to predict human movements. MyWay provides three strategies: the individual strategy uses only the user individual mobility profile, the collective strategy takes advantage of all users individual systematic behaviors, and the hybrid strategy that is a combination of the previous two. A key point is that MyWay only requires the sharing of individual mobility profiles, a concise representation of the user's movements, instead of raw trajectory data revealing the detailed movement of the users. We evaluate the prediction performances of our proposal by a deep experimentation on large real-world data. The results highlight that the synergy between the individual and collective knowledge is the key for a better prediction and allow the system to outperform the state-of-art methods