Mineralization behaviour of some new phema-based copolymers with potential uses in tissue engineering

This paper reports the mineralization ability of 2-hydroxyethyl methacrylate (HEMA) and 2-methacryloylamido glutamic acid (MAGA) based copolymers incubated in synthetic fluids. MAGA monomer was obtained by organic synthesis and next p(HEMA-co-MAGA) copolymers with different compositions were prepared by bulk radical polymerization using benzoyle peroxide as initiator and ethyleneglycol dimethacrylate as cross-linking agent. The monomer and polymers were further characterized by FTIR-ATR spectroscopy to confirm their structure. Finally, polymers ability to initiate the formation and growth of HA crystals onto their surface in synthetic fluids was proven. SEM analysis showed the formation of apatite-like crystals (calcospherites), fact confirmed also by EDX analysis

Metallurgical industry in Romania in the context of the economic crisis

The magnitude of the economic crisis and the influence on the developments of industrial branches was different.Although European economies are strongly interconnected both internally and externally, the way in which an economic branch has crossed and is trying to overcome the economic crisis has some peculiarities arising from its specificity on the one hand, and on the other hand, from the policies applied in the field. Based on these considerations,the paper examines how Romanian metallurgical industry passes through the economic crisis as compared with other industries. Also based on quantitative analyses performed and taking into account the specific phenomenon of seasonality are presented models of evolution of this industry with horizon in February 2015

Field Line Resonances in Quiet and Disturbed Time Three-Dimensional Magnetospheres

Numerical solutions for field line resonances (FLR) in the magnetosphere are presented for three-dimensional equilibrium magnetic fields represented by two Euler potentials as B = -j Y -a, where j is the poloidal flux and a is a toroidal angle-like variable. The linearized ideal-MHD equations for FLR harmonics of shear Alfvin waves and slow magnetosonic modes are solved for plasmas with the pressure assumed to be isotropic and constant along a field line. The coupling between the shear Alfvin waves and the slow magnetosonic waves is via the combined effects of geodesic magnetic field curvature and plasma pressure. Numerical solutions of the FLR equations are obtained for a quiet time magnetosphere as well as a disturbed time magnetosphere with a thin current sheet in the near-Earth region. The FLR frequency spectra in the equatorial plane as well as in the auroral latitude are presented. The field line length, magnetic field intensity, plasma beta, geodesic curvature and pressure gradient in the poloidal flux surface are important in determining the FLR frequencies. In general, the computed shear Alfvin FLR frequency based on the full MHD model is larger than that based on the commonly adopted cold plasma model in the beq > 1 region. For the quiet time magnetosphere, the shear Alfvin resonance frequency decreases monotonically with the equatorial field line distance, which reasonably explains the harmonically structured continuous spectrum of the azimuthal magnetic field oscillations as a function of L shell in the L is less than or equal to 9RE region. However, the FLR frequency spectrum for the disturbed time magnetosphere with a near-Earth thin current sheet is substantially different from that for the quiet time magnetosphere for R > 6RE, mainly due to shorter field line length due to magnetic field compression by solar wind, reduced magnetic field intensity in the high-beta current sheet region, azimuthal pressure gradient, and geodesic magnetic field curvature

Low Latency Geo-distributed Data Analytics

Low latency analytics on geographically distributed dat-asets (across datacenters, edge clusters) is an upcoming and increasingly important challenge. The dominant approach of aggregating all the data to a single data-center significantly inflates the timeliness of analytics. At the same time, running queries over geo-distributed inputs using the current intra-DC analytics frameworks also leads to high query response times because these frameworks cannot cope with the relatively low and variable capacity of WAN links. We present Iridium, a system for low latency geo-distri-buted analytics. Iridium achieves low query response times by optimizing placement of both data and tasks of the queries. The joint data and task placement op-timization, however, is intractable. Therefore, Iridium uses an online heuristic to redistribute datasets among the sites prior to queries ’ arrivals, and places the tasks to reduce network bottlenecks during the query’s ex-ecution. Finally, it also contains a knob to budget WAN usage. Evaluation across eight worldwide EC2 re-gions using production queries show that Iridium speeds up queries by 3 × − 19 × and lowers WAN usage by 15% − 64 % compared to existing baselines

LINVIEW: Incremental View Maintenance for Complex Analytical Queries

Many analytics tasks and machine learning problems can be naturally expressed by iterative linear algebra programs. In this paper, we study the incremental view maintenance problem for such complex analytical queries. We develop a framework, called LINVIEW, for capturing deltas of linear algebra programs and understanding their computational cost. Linear algebra operations tend to cause an avalanche effect where even very local changes to the input matrices spread out and infect all of the intermediate results and the final view, causing incremental view maintenance to lose its performance benefit over re-evaluation. We develop techniques based on matrix factorizations to contain such epidemics of change. As a consequence, our techniques make incremental view maintenance of linear algebra practical and usually substantially cheaper than re-evaluation. We show, both analytically and experimentally, the usefulness of these techniques when applied to standard analytics tasks. Our evaluation demonstrates the efficiency of LINVIEW in generating parallel incremental programs that outperform re-evaluation techniques by more than an order of magnitude.Comment: 14 pages, SIGMO

Using Trusted Execution Environments for Secure Stream Processing of Medical Data

Processing sensitive data, such as those produced by body sensors, on third-party untrusted clouds is particularly challenging without compromising the privacy of the users generating it. Typically, these sensors generate large quantities of continuous data in a streaming fashion. Such vast amount of data must be processed efficiently and securely, even under strong adversarial models. The recent introduction in the mass-market of consumer-grade processors with Trusted Execution Environments (TEEs), such as Intel SGX, paves the way to implement solutions that overcome less flexible approaches, such as those atop homomorphic encryption. We present a secure streaming processing system built on top of Intel SGX to showcase the viability of this approach with a system specifically fitted for medical data. We design and fully implement a prototype system that we evaluate with several realistic datasets. Our experimental results show that the proposed system achieves modest overhead compared to vanilla Spark while offering additional protection guarantees under powerful attackers and threat models.Comment: 19th International Conference on Distributed Applications and Interoperable System