1,721,054 research outputs found
Solar Wind Magnetic Field Background Spectrum from Fluid to Kinetic Scales
No full textDuring solar activity minima, the solar wind is highly structured in fast and slow wind flows. These two dynamical regimes remarkably differ not only for average magnetic field and plasma values but also for the type of fluctuations they transport. Fast wind is characterized by large amplitude, incompressible fluctuations, mainly Alfvénic, slow wind is generally populated by smaller amplitude and less Alfvénic fluctuations, mainly compressive. Moving from fast to slow wind, along the speed profile of a high velocity stream, we observe the following behavior:a) the power level of magnetic field fluctuations within the inertial range largely decreases, keeping the typical Kolmogorov scaling;b) at proton scales, for about one decade, right beyond the high frequency break generally corresponding to the location of the ion-cyclotron resonance condition, the spectral index becomes flatter and flatter towards a value of -2.7, typically found in literature;c) at higher frequencies, before the electron scales, the spectral index remains around -2.7 and the power level does not change showing to be irrespective of the flow speed. This behavior is typically encountered during quiet solar activity conditions and suggests the existence of a sort of magnetic field background spectrum. Then, an Alfvènic spectrum would be added to this background any time the observer would enter and cross a fluxtube channeling the fast wind into the interplanetary space. Several example, in the limits of the available data, will be reported and the corresponding spectra from different epochs and source regions will be compared
Metis aboard the Solar Orbiter space mission: Doses from galactic cosmic rays and solar energetic particles
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Galactic cosmic-ray flux short-term variations and associated interplanetary structures with LISA Pathfinder
No full textThe European Space Agency LISA Pathfinder (LPF) mission orbited around
the Sun-Earth first Lagrangian point L1 between January 2016 and July
2017. A particle detector aboard LPF allowed for galactic cosmic-ray
(GCR) integral flux measurements above 70 MeV n(-1) between 2016
February 18 and 2017 July 3 during the descending phase of the present
solar cycle N. 24, which is characterized by a positive polarity period.
The statistical uncertainty on hourly-averaged GCR countings was of 1%.
The characteristics of recurrent and non-recurrent GCR flux short-term
variations observed with LPF are reported here. In particular, it is
focused on GCR flux variation profiles and their association with the
passage of large-scale interplanetary structures. Forbush decrease
observations and geomagnetic storm occurrence during LPF are also
briefly discussed
Prediction of geomagnetic events from solar wind data using deep learning
Full text linkThe recent technological maturity attained by deep
learning drew the attention of numerous scientific communities.
Among these, Space Weather is leveraging such tools to support
its activities related to forecasting harmful events. Coronal
mass ejections (CMEs) are one of the most critical phenomena
occurring in the solar system: their propagation may impact the
Earth, altering the equilibrium of the terrestrial surface under
different aspects, requiring their prediction to take counter-
measures accordingly. Classical forecasting methods are built
upon solar remote-sensing observations to forecast the CME
onset, intensity, and arrival time. Although such methods could
provide alerts within 1-4 days in advance, their estimations
are affected by large uncertainties. On the other hand, deep
learning has been offering valid alternatives through recent
studies, devising data-driven models to obtain real-time alerts
while monitoring such events remotely.
The goal of this work is that of developing neural network
architectures able to offer CME predictions leveraging the La-
grangian point L1 measurements, taking advantage of historical
data related to these phenomena past behaviors to predict future
trends.
In this paper, two main phases may be distinguished: first,
the manipulation of the dataset - mostly through augmentation
techniques - to make it more suitable for the proposed prediction
steps. Second, the implementation of different network structures
for multiple classification tasks concerning various aspects of
CMEs, to prove the effectiveness of deep learning algorithms in
reaching the desired goal
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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