792 research outputs found
Generalized h-index for Disclosing Latent Facts in Citation Networks
What is the value of a scientist and its impact upon the scientific thinking?
How can we measure the prestige of a journal or of a conference? The evaluation
of the scientific work of a scientist and the estimation of the quality of a
journal or conference has long attracted significant interest, due to the
benefits from obtaining an unbiased and fair criterion. Although it appears to
be simple, defining a quality metric is not an easy task. To overcome the
disadvantages of the present metrics used for ranking scientists and journals,
J.E. Hirsch proposed a pioneering metric, the now famous h-index. In this
article, we demonstrate several inefficiencies of this index and develop a pair
of generalizations and effective variants of it to deal with scientist ranking
and with publication forum ranking. The new citation indices are able to
disclose trendsetters in scientific research, as well as researchers that
constantly shape their field with their influential work, no matter how old
they are. We exhibit the effectiveness and the benefits of the new indices to
unfold the full potential of the h-index, with extensive experimental results
obtained from DBLP, a widely known on-line digital library.Comment: 19 pages, 17 tables, 27 figure
STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization
Accurate prediction of the transmission of epidemic diseases such as COVID-19
is crucial for implementing effective mitigation measures. In this work, we
develop a tensor method to predict the evolution of epidemic trends for many
regions simultaneously. We construct a 3-way spatio-temporal tensor (location,
attribute, time) of case counts and propose a nonnegative tensor factorization
with latent epidemiological model regularization named STELAR. Unlike standard
tensor factorization methods which cannot predict slabs ahead, STELAR enables
long-term prediction by incorporating latent temporal regularization through a
system of discrete-time difference equations of a widely adopted
epidemiological model. We use latent instead of location/attribute-level
epidemiological dynamics to capture common epidemic profile sub-types and
improve collaborative learning and prediction. We conduct experiments using
both county- and state-level COVID-19 data and show that our model can identify
interesting latent patterns of the epidemic. Finally, we evaluate the
predictive ability of our method and show superior performance compared to the
baselines, achieving up to 21% lower root mean square error and 25% lower mean
absolute error for county-level prediction.Comment: AAAI 202
First results on the performance of the CMS global calorimeter trigger
The CMS Global Calorimeter Trigger (GCT) uses data from the CMS calorimeters to compute a number kinematical quantities which characterize the LHC event. The GTC output is used by the Global Trigger (GT) along with data from the Global Muon Trigger (GMT) to produce the Level-1 Accept (L1A) decision. The design for the current GCT system commenced early in 2006. After a rapid development phase all the different GCT components have been produced and a large fraction of them have been installed at the CMS electronics cavern (USC-55). There the GCT system has been under test since March 2007. This paper reports results from tests which took place at the USC-55. Initial tests aimed to test the integrity of the GCT data and establish that the proper synchronization had been achieved both internally within GCT as well as with the Regional Calorimeter Trigger (RCT) which provides the GCT input data and with GT which receives the GCT results. After synchronization and data integrity had been established, Monte Carlo Events with electrons in the final state were injected at the GCT inputs and were propagated to the GCT outputs. The GCT output was compared with the predictions of the GCT emulator model in the CMS Monte Carlo and were found to be identical
Enhanced optical conductivity and many-body effects in strongly-driven photo-excited semi-metallic graphite
The excitation of quasi-particles near the extrema of the electronic band
structure is a gateway to electronic phase transitions in condensed matter. In
a many-body system, quasi-particle dynamics are strongly influenced by the
electronic single-particle structure and have been extensively studied in the
weak optical excitation regime. Yet, under strong optical excitation, where
light fields coherently drive carriers, the dynamics of many-body interactions
that can lead to new quantum phases remain largely unresolved. Here, we induce
such a highly non-equilibrium many-body state through strong optical excitation
of charge carriers near the van Hove singularity in graphite. We investigate
the system's evolution into a strongly-driven photo-excited state with
attosecond soft X-ray core-level spectroscopy. Surprisingly, we find an
enhancement of the optical conductivity of nearly ten times the quantum
conductivity and pinpoint it to carrier excitations in flat bands. This
interaction regime is robust against carrier-carrier interaction with coherent
optical phonons acting as an attractive force reminiscent of superconductivity.
The strongly-driven non-equilibrium state is markedly different from the
single-particle structure and macroscopic conductivity and is a consequence of
the non-adiabatic many-body state
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The Hypanis fluvial deltaic system in Xanthe Terra: a candidate ExoMars 2018 Rover landing site
The search for life on Mars is a cornerstone of international solar system exploration. In 2018, the European Space agency will launch the ExoMars Rover to further this goal. The key science objectives of the ExoMars Rover are to: 1) search for signs of past and present life on Mars; 2) investigate the water/geochemical environment as a function of depth in the shallow subsurface; and 3) to characterize the surface environment. ExoMars will drill into the sub-surface to look for indicators of past life using a variety of complementary techniques, including assessment of morphology (potential fossil organisms), mineralogy (past environments) and a search for organic molecules and their chirality (biomarkers).
The choice of landing site is vital if the objectives are to be met. The landing site must: (i) be ancient (≥3.6 Ga); (ii) show abundant morphological and mineral evidence for long-term, or frequently reoccurring, aqueous activity; (iii) include numerous sedimentary outcrops that (iv) are distributed over the landing region (the typical Rover traverse range is a few km, but ellipse size is ~ 104 by 19 km). Various ‘engineering constraints’ also apply, including: (i) latitude limited to 5º S to 25º N; (ii) maximum altitude of the landing site 2 km below Mars’s datum; and (iii) few steep slopes within the ellipse
Performance of the CMS Global Calorimeter Trigger
The CMS Global Calorimeter Trigger system performs a wide-variety of calorimeter data processing functions required by the CMS Level-1 trigger. It is responsible for finding and classifying jets and tau-jets, calculating total and missing transverse energy, total transverse energy identified within jets, sorting e/ candidates, and calculating several quantities based on forward calorimetry for minimum-bias triggers. The system is based on high-speed serial optical links and large FPGAs. The system has provided CMS with calorimeter triggers during commissioning and cosmic runs throughout 2008. The performance of the system in validation tests and cosmic runs is presented here
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