Acquiring, archiving, analyzing and exchanging seismic data in real time at the Seismological Research Center of the OGS in Italy

The Centro di Ricerche Sismologiche (CRS, Seismological Research Center) of the Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS, Italian National Institute for Oceanography and Experimental Geophysics) in Udine (Italy) after the strong earthquake (magnitude M=6.4) occurred in 1976 in the Italian Friuli-Venezia Giulia region, started to operate the North-east Italy (NI) seismic network: it currently consists of 11 very sensitive broad band and 23 more simple short period seismic stations, all telemetered to and acquired in real time at the OGS-CRS data center in Udine. Real time data exchange agreements in place with other Italian, Slovenian, Austrian and Swiss seismological institutes lead to a total number of 89 seismic stations acquired in real time, which makes the OGS the reference institute for seismic monitoring of Northeastern Italy. Since 2002 OGS-CRS is using the Antelope software suite as the main tool for collecting, analyzing, archiving and exchanging seismic data in the framework of the EU Interreg IIIA project “Trans-national seismological networks in the South-Eastern Alps”. SeisComP is also used as a real time data exchange server tool. At OGS-CRS we then adapted existing programs and created new ones like: a customized web-accessible server to manually relocate earthquakes, a script for automatic moment tensor determination, scripts for web publishing of earthquake parametric data, waveforms, state of health parameters and shaking maps, noise characterization by means of automatic spectra analysis, plus scripts for email/SMS/fax alerting. A new OGS-CRS real time web site has also been recently designed and made operative in the framework of the DPC-INGV S3 Project

Interactions of SARS Coronavirus Nucleocapsid Protein with the host cell proteasome subunit p42

<p>Abstract</p> <p>Background</p> <p>Severe acute respiratory syndrome-associated coronavirus (SARS-CoV) spreads rapidly and has a high case-mortality rate. The nucleocapsid protein (NP) of SARS-CoV may be critical for pathogenicity. This study sought to discover the host proteins that interact with SARS-CoV NP.</p> <p>Results</p> <p>Using surface plasmon resonance biomolecular interaction analysis (SPR/BIA) and matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry, we found that only the proteasome subunit p42 from human fetal lung diploid fibroblast (2BS) cells bound to SARS-CoV NP. This interaction was confirmed by the glutathione S-transferase (GST) fusion protein pulldown technique. The co-localization signal of SARS-CoV NP and proteasome subunit p42 in 2BS cells was detected using indirect immunofluorescence and confocal microscopy. p42 is a subunit of the 26S proteasome; this large, multi-protein complex is a component of the ubiquitin-proteasome pathway, which is involved in a variety of basic cellular processes and inflammatory responses.</p> <p>Conclusion</p> <p>To our knowledge, this is the first report that SARS-CoV NP interacts with the proteasome subunit p42 within host cells. These data enhance our understanding of the molecular mechanisms of SARS-CoV pathogenicity and the means by which SARS-CoV interacts with host cells.</p

Lattice and magnetic dynamics in YVO3 Mott insulator studied by neutron scattering and first-principles calculations

The Mott insulator YVO3 with TN = 118 K is revisited to explore the role of spin, lattice and orbital correlations across the multiple structural and magnetic transitions observed as a function of temperature. Upon cooling, the crystal structure changes from orthorhombic to monoclinic at 200 K, and back to orthorhombic at 77 K, followed by magnetic transitions. From the paramagnetic high temperature phase, C-type ordering is first observed at 118 K, followed by a G-type spin re- orientation transition at 77 K. The dynamics of the transitions were investigated via inelastic neutron scattering and first principles calculations. An overall good agreement between the neutron data and calculated spectra was observed. From the magnon density of states, the magnetic exchange constants were deduced to be Jab = Jc = -5.8 meV in the G-type spin phase, and Jab = -3.8 meV, Jc = 7.6 meV at 80 K and Jab = -3.0 meV, Jc = 6.0 meV at 100 K in the C-type spin phase. Paramagnetic scattering was observed in the spin ordered phases, well below the C-type transition temperature, that continuously increased above the transition. Fluctuations in the temperature dependence of the phonon density of states were observed between 50 and 80 K as well, coinciding with the G-type to C-type transition. These fluctuations are attributed to optical oxygen modes above 40 meV, from first principles calculations. In contrast, little change in the phonon spectra is observed across TN.This work has been supported by the Department of Energy, Grant number DE-FG02-01ER4592. This work was also partly supported by the Materials Research Sci- ence and Engineering Centers, National Science Founda- tion, Grant number DMR-1720595, by providing sample used in this work and by the National Institute of Stan- dards and Technology, US Department of Commerce, in providing computing resources for DFT calculations used in this work.Center for Dynamics and Control of Material

Adaptive optimal output regulation for wheel-legged robot Ollie: A data-driven approach

The dynamics of a robot may vary during operation due to both internal and external factors, such as non-ideal motor characteristics and unmodeled loads, which would lead to control performance deterioration and even instability. In this paper, the adaptive optimal output regulation (AOOR)-based controller is designed for the wheel-legged robot Ollie to deal with the possible model uncertainties and disturbances in a data-driven approach. We test the AOOR-based controller by forcing the robot to stand still, which is a conventional index to judge the balance controller for two-wheel robots. By online training with small data, the resultant AOOR achieves the optimality of the control performance and stabilizes the robot within a small displacement in rich experiments with different working conditions. Finally, the robot further balances a rolling cylindrical bottle on its top with the balance control using the AOOR, but it fails with the initial controller. Experimental results demonstrate that the AOOR-based controller shows the effectiveness and high robustness with model uncertainties and external disturbances

Multiferroic Magnon Spin-Torque Based Reconfigurable Logic-In-Memory

Magnons, bosonic quasiparticles carrying angular momentum, can flow through insulators for information transmission with minimal power dissipation. However, it remains challenging to develop a magnon-based logic due to the lack of efficient electrical manipulation of magnon transport. Here we present a magnon logic-in-memory device in a spin-source/multiferroic/ferromagnet structure, where multiferroic magnon modes can be electrically excited and controlled. In this device, magnon information is encoded to ferromagnetic bits by the magnon-mediated spin torque. We show that the ferroelectric polarization can electrically modulate the magnon spin-torque by controlling the non-collinear antiferromagnetic structure in multiferroic bismuth ferrite thin films with coupled antiferromagnetic and ferroelectric orders. By manipulating the two coupled non-volatile state variables (ferroelectric polarization and magnetization), we further demonstrate reconfigurable logic-in-memory operations in a single device. Our findings highlight the potential of multiferroics for controlling magnon information transport and offer a pathway towards room-temperature voltage-controlled, low-power, scalable magnonics for in-memory computing

MicroRNA profiling of diverse endothelial cell types

<p>Abstract</p> <p>Background</p> <p>MicroRNAs are ~22-nt long regulatory RNAs that serve as critical modulators of post-transcriptional gene regulation. The diversity of miRNAs in endothelial cells (ECs) and the relationship of this diversity to epithelial and hematologic cells is unknown. We investigated the baseline miRNA signature of human ECs cultured from the aorta (HAEC), coronary artery (HCEC), umbilical vein (HUVEC), pulmonary artery (HPAEC), pulmonary microvasculature (HPMVEC), dermal microvasculature (HDMVEC), and brain microvasculature (HBMVEC) to understand the diversity of miRNA expression in ECs.</p> <p>Results</p> <p>We identified 166 expressed miRNAs, of which 3 miRNAs (miR-99b, miR-20b and let-7b) differed significantly between EC types and predicted EC clustering. We confirmed the significance of these miRNAs by RT-PCR analysis and in a second data set by Sylamer analysis. We found wide diversity of miRNAs between endothelial, epithelial and hematologic cells with 99 miRNAs shared across cell types and 31 miRNAs unique to ECs. We show polycistronic miRNA chromosomal clusters have common expression levels within a given cell type.</p> <p>Conclusions</p> <p>EC miRNA expression levels are generally consistent across EC types. Three microRNAs were variable within the dataset indicating potential regulatory changes that could impact on EC phenotypic differences. MiRNA expression in endothelial, epithelial and hematologic cells differentiate these cell types. This data establishes a valuable resource characterizing the diverse miRNA signature of ECs.</p

Coupling Coordination and Spatiotemporal Evolution between Carbon Emissions, Industrial Structure, and Regional Innovation of Counties in Shandong Province

Industrial structure and regional innovation have a significant impact on emissions. This study explores, from the multivariate coupling and spatial perspectives, the degree of coupling coordination between three factors: industrial structure, carbon emissions, and regional innovation of 97 counties in Shandong Province, China from 2000 to 2017. On the basis of global spatial autocorrelation and cold and hot spots, this article analyzes the spatial characteristics and aggregation effects of coupled and coordinated development within each region. The results are as follows. (1) The coupling degree between carbon emissions, industrial structure, and regional innovation in these counties fluctuated upward from 2000 to 2017. Coupling coordination progressed from low coordination to basic coordination. Regional differences in coupling coordination degree are evident, showing a stepped spatial distribution pattern with high levels in the east and low levels in the west. (2) During the study period, the coupling coordination showed a positive correlation in spatial distribution. Moran’s I varies from 0.057 to 0.305 on a global basis. Spatial clustering is characterized by agglomeration of cold spots and hot spots. (3) The coupling coordination exhibited significant spatial differentiation. The hot spots were distributed in the eastern part, while the cold spots were located in the western part. The results of this study suggest that the counties in Shandong Province should promote industrial structure upgrades and enhance regional innovation to reduce carbon emissions