433 research outputs found
Expansion of magnetic clouds in the outer heliosphere
A large amount of magnetized plasma is frequently ejected from the Sun as
coronal mass ejections (CMEs). Some of these ejections are detected in the
solar wind as magnetic clouds (MCs) that have flux rope signatures. Magnetic
clouds are structures that typically expand in the inner heliosphere. We derive
the expansion properties of MCs in the outer heliosphere from one to five
astronomical units to compare them with those in the inner heliosphere. We
analyze MCs observed by the Ulysses spacecraft using insitu magnetic field and
plasma measurements. The MC boundaries are defined in the MC frame after
defining the MC axis with a minimum variance method applied only to the flux
rope structure. As in the inner heliosphere, a large fraction of the velocity
profile within MCs is close to a linear function of time. This is indicative
of} a self-similar expansion and a MC size that locally follows a power-law of
the solar distance with an exponent called zeta. We derive the value of zeta
from the insitu velocity data. We analyze separately the non-perturbed MCs
(cases showing a linear velocity profile almost for the full event), and
perturbed MCs (cases showing a strongly distorted velocity profile). We find
that non-perturbed MCs expand with a similar non-dimensional expansion rate
(zeta=1.05+-0.34), i.e. slightly faster than at the solar distance and in the
inner heliosphere (zeta=0.91+-0.23). The subset of perturbed MCs expands, as in
the inner heliosphere, at a significantly lower rate and with a larger
dispersion (zeta=0.28+-0.52) as expected from the temporal evolution found in
numerical simulations. This local measure of the expansion also agrees with the
distribution with distance of MC size,mean magnetic field, and plasma
parameters. The MCs interacting with a strong field region, e.g. another MC,
have the most variable expansion rate (ranging from compression to
over-expansion)
Residual stress measurements on a deep rolled aluminum specimen through X-Ray Diffraction and Hole-Drilling, validated on a calibration bench
Residual stress measurements are notably affected by a high sensitivity to errors in input data. Measurements should then be presented together with an estimation of their accuracy. A common strategy is to carry out more measurements and/or to compare the results of different techniques. However, error contributions due to biases could be dangerously left unseen. In a previous work, the authors presented a calibration bench which can impose a known bending stress distribution on a specimen while simultaneously performing X-Ray Diffraction (XRD) or Hole-Drilling Method (HDM) residual stress measurements. Since the external load can freely be applied and removed, the superposition principle can be exploited to simultaneously identify either the reference bending stress distribution or the actual residual stress distribution, with the same experimental setup. A deep rolling treatment was measured and analyzed on the calibration bench with both XRD and HDM. First, residual stresses on the surface were evaluated with XRD measurements, then electrochemical material removal was performed to investigate stresses at higher depths. After that, HDM measurements were carried out and compared with the results of XRD. Both methods were also used to identify the known bending stresses, providing an additional validation of the residual stress results
Corrección de errores de nivelación de datos aerogeofÃsicos
En el presente trabajo se realiza una mejora a la técnica de correlación lÃnea a lÃnea (line-to-line correlation) para la remoción de errores de nivelación de datos geofÃsicos obtenidos mediante prospección aérea. Esta técnica, bajo la hipótesis de continuidad y fuerte correlación de los registros de perfiles de lÃneas de vuelo adyacentes, logra la nivelación mediante la construcción de un filtro funcional mediante una ventana móvil en una dimensión. Se aplica este filtro lÃnea a lÃnea en forma recursiva logrando disminuir los errores de nivelación y ajustarlos en el sentido de los cuadrados mÃnimos.
Nuestra mejora consiste en la implementación de la técnica mediante la aplicación de filtros n-dimensionales, sobre bases de sucesiones polinomiales ortogonales. El procedimiento utilizado consistió en la generación de datos sintéticos a los cuales se les introdujo errores de nivelación ad-hoc de diferentes caracterÃsticas tÃpicas para simular los encontrados en una aeroprospección real. Luego aplicamos la técnica con este método mejorado como si se tratase de datos reales y comparamos con los datos sintéticos sin error de nivelación. Hemos hallado los rangos en que las bases ortogonales de Legendre y Chebyshev mejoran notablemente la estabilidad y resultados de la técnica, respecto de la implementación usando la base canónica.
Luego se ha aplicado la técnica mejorada a un registro aeromagnético real adquirido sobre el área volcánica del Archipiélago James Ross, en el Mar de Weddell, en el extremo nororiental de la PenÃnsula Antártica, obteniendo un muy buen resultado en la remoción de los errores de nivelación de la prospección. La remoción efectiva de los errores de nivelación resulta de fundamental importancia para lograr obtener, a partir de la inversión de los datos, modelos consistentes y representativos de la realidad geofÃsica que intenta describirse.Eje: GeofÃsica Aplicada y Ambiental.Facultad de Ciencias Astronómicas y GeofÃsica
Assessment of internal diameters of abdominal and femoral blood vessels in 250 living subjects using color Doppler ultrasonography.
Calibration of the operative cosmic ray detector at Marambio Base in the Antarctic Peninsula
During 2019 an Antarctic Space Weather Laboratory was deployed at Marambio base in the Antarctic Peninsula. The
main instrument installed was a cosmic ray detector based on water Cherenkov radiation (WCD). This detector is the
first permanent Antarctic node of the LAGO (Latin American Giant Observatory) Collaboration. Long-term calibrated
observations of the WCD will be presented here. Finally, the global galactic cosmic rays variability observed with the
WCD will be compared with observations of a neutron monitor with similar rigidity cut off than the Marambio site
Internal jugular vein valves: an assessment of prevalence, morphology and competence by color Doppler echography in 240 healthy subjects.
Internal jugular vein valves: an assessment of prevalence, morphology and competence by Color Doppler Echography in 240 healthy subjects
A big data platform for large scale event processing
To date, big data applications have focused on the store-and-process paradigm. In this paper we describe an initiative to deal with big data applications for continuous streams of events. In many emerging applications, the volume of data being streamed is so large that the traditional ‘store-then-process’ paradigm is either not suitable or too inefficient. Moreover, soft-real time requirements might severely limit the engineering solutions. Many scenarios fit this description. In network security for cloud data centres, for instance, very high volumes of IP packets and events from sensors at firewalls, network switches and routers and servers need to be analyzed and should detect attacks in minimal time, in order to limit the effect of the malicious activity over the IT infrastructure. Similarly, in the fraud department of a credit card company, payment requests should be processed online and need to be processed as quickly as possible in order to provide meaningful results in real-time. An ideal system would detect fraud during the authorization process that lasts hundreds of milliseconds and deny the payment authorization, minimizing the damage to the user and the credit card company
StreamCloud: An elastic and scalable data streaming system
Many applications in several domains such as telecommunications, network security, large scale sensor networks, require online processing of continuous data lows. They produce very high loads that requires aggregating the processing capacity of many nodes. Current Stream Processing Engines do not scale with the input load due to single-node bottlenecks. Additionally, they are based on static con?gurations that lead to either under or over-provisioning. In this paper, we present StreamCloud, a scalable and elastic stream processing engine for processing large data stream volumes. StreamCloud uses a novel parallelization technique that splits queries into subqueries that are allocated to independent sets of nodes in a way that minimizes the distribution overhead. Its elastic protocols exhibit low intrusiveness, enabling effective adjustment of resources to the incoming load. Elasticity is combined with dynamic load balancing to minimize the computational resources used. The paper presents the system design, implementation and a thorough evaluation of the scalability and elasticity of the fully implemented system
Assessment of internal diameters of abdominal and femoral blood vessels in 250 living subjects using Color Doppler ultrasonography
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