176 research outputs found
Post-hoc derivation of SOHO Michelson doppler imager flat fields
<p><b>Context:</b> The SOHO satellite now offers a unique perspective on the Sun as it is the only space-based instrument that can provide large, high-resolution data sets over an entire 11-year solar cycle. This unique property enables detailed studies of long-term variations in the Sun. One significant problem when looking for such changes is determining what component of any variation is due to deterioration of the instrument and what is due to the Sun itself. One of the key parameters that changes over time is the apparent sensitivity of individual pixels in the CCD array. This can change considerably as a result of optics damage, radiation damage, and aging of the sensor itself. In addition to reducing the sensitivity of the telescope over time, this damage significantly changes the uniformity of the flat field of the instrument, a property that is very hard to recalibrate in space. For procedures such as feature tracking and intensity analysis, this can cause significant errors.</p>
<p><b>Aims:</b> We present a method for deriving high-precision flat fields for high-resolution MDI continuum data, using analysis of existing continuum and magnetogram data sets.</p>
<p><b>Methods:</b> A flat field is constructed using a large set (1000-4000 frames) of cospatial magnetogram and continuum data. The magnetogram data is used to identify and mask out magnetically active regions on the continuum data, allowing systematic biases to be avoided. This flat field can then be used to correct individual continuum images from a similar time.</p>
<p><b>Results:</b> This method allows us to reduce the residual flat field error by around a factor 6-30, depending on the area considered, enough to significantly change the results from correlation-tracking analysis. One significant advantage of this method is that it can be done retrospectively using archived data, without requiring any special satellite operations.</p>
Multilingual Word Sense Induction to Improve Web Search Result Clustering
In [12] a novel approach to Web search result clustering based on Word Sense Induction, i.e. the automatic discovery of word senses from raw text was presented; key to the proposed approach is the idea of, first, automatically in- ducing senses for the target query and, second, clustering the search results based on their semantic similarity to the word senses induced. In [1] we proposed an innovative Word Sense Induction method based on multilingual data; key to our approach was the idea that a multilingual context representation, where the context of the words is expanded by considering its translations in different languages, may im- prove the WSI results; the experiments showed a clear per- formance gain. In this paper we give some preliminary ideas to exploit our multilingual Word Sense Induction method to Web search result clustering
The Horizontal Component of Photospheric Plasma Flows During the Emergence of Active Regions on the Sun
The dynamics of horizontal plasma flows during the first hours of the
emergence of active region magnetic flux in the solar photosphere have been
analyzed using SOHO/MDI data. Four active regions emerging near the solar limb
have been considered. It has been found that extended regions of Doppler
velocities with different signs are formed in the first hours of the magnetic
flux emergence in the horizontal velocity field. The flows observed are
directly connected with the emerging magnetic flux; they form at the beginning
of the emergence of active regions and are present for a few hours. The Doppler
velocities of flows observed increase gradually and reach their peak values
4-12 hours after the start of the magnetic flux emergence. The peak values of
the mean (inside the +/-500 m/s isolines) and maximum Doppler velocities are
800-970 m/s and 1410-1700 m/s, respectively. The Doppler velocities observed
substantially exceed the separation velocities of the photospheric magnetic
flux outer boundaries. The asymmetry was detected between velocity structures
of leading and following polarities. Doppler velocity structures located in a
region of leading magnetic polarity are more powerful and exist longer than
those in regions of following polarity. The Doppler velocity asymmetry between
the velocity structures of opposite sign reaches its peak values soon after the
emergence begins and then gradually drops within 7-12 hours. The peak values of
asymmetry for the mean and maximal Doppler velocities reach 240-460 m/s and
710-940 m/s, respectively. An interpretation of the observable flow of
photospheric plasma is given.Comment: 20 pages, 10 figures, 3 tables. The results of article were presented
at the ESPM-13 (12-16 September 2011, Rhodes, Greece, Abstract Book p. 102,
P.4.12,
http://astro.academyofathens.gr/espm13/documents/ESPM13_abstract_programme_book.pdf
Intake of nitrate and nitrite and the risk of gastric cancer: a prospective cohort study.
The association between the intake of nitrate or nitrite and gastric cancer risk was investigated in a prospective cohort study started in 1986 in the Netherlands, of 120,852 men and women aged 55-69 years. At baseline, data on dietary intake, smoking habits and other covariates were collected by means of a self-administered questionnaire. For data analysis, a case-cohort approach was used, in which the person-years at risk were estimated from a randomly selected subcohort (1688 men and 1812 women). After 6.3 years of follow-up, 282 microscopically confirmed incident cases of stomach cancer were detected: 219 men and 63 women. We did not find a higher risk of gastric cancer among people with a higher nitrate intake from food [rate ratio (RR) highest/lowest quintile = 0.80, 95% CI 0.47-1.37, trend-P = 0.18], a higher nitrate intake from drinking water (RR highest/lowest quintile = 0.88, 95% CI 0.59-1.32, trend-P = 0.39) or a higher intake of nitrite (RR highest/lowest quintile = 1.44, 95% CI 0.95-2.18, trend-P = 0.24). Rate ratios for gastric cancer were also computed for each tertile of nitrate intake from foods within tertiles of vitamin C intake and intake of beta-carotene, but no consistent pattern was found. Therefore, our study does not support a positive association between the intake of nitrate or nitrite and gastric cancer risk
Second-Order Belief Hidden Markov Models
Hidden Markov Models (HMMs) are learning methods for pattern recognition. The
probabilistic HMMs have been one of the most used techniques based on the
Bayesian model. First-order probabilistic HMMs were adapted to the theory of
belief functions such that Bayesian probabilities were replaced with mass
functions. In this paper, we present a second-order Hidden Markov Model using
belief functions. Previous works in belief HMMs have been focused on the
first-order HMMs. We extend them to the second-order model
Structural Invariance of Sunspot Umbrae Over the Solar Cycle: 1993-2004
Measurements of maximum magnetic flux, minimum intensity, and size are
presented for 12 967 sunspot umbrae detected on the NASA/NSO
spectromagnetograms between 1993 and 2004 to study umbral structure and
strength during the solar cycle. The umbrae are selected using an automated
thresholding technique. Measured umbral intensities are first corrected for a
confirming observation of umbral limb-darkening. Log-normal fits to the
observed size distribution confirm that the size spectrum shape does not vary
with time. The intensity-magnetic flux relationship is found to be steady over
the solar cycle. The dependence of umbral size on the magnetic flux and minimum
intensity are also independent of cycle phase and give linear and quadratic
relations, respectively. While the large sample size does show a low amplitude
oscillation in the mean minimum intensity and maximum magnetic flux correlated
with the solar cycle, this can be explained in terms of variations in the mean
umbral size. These size variations, however, are small and do not substantiate
a meaningful change in the size spectrum of the umbrae generated by the Sun.
Thus, in contrast to previous reports, the observations suggest the equilibrium
structure, as testified by the invariant size-magnetic field relationship, as
well as the mean size (i.e. strength) of sunspot umbrae do not significantly
depend on solar cycle phase.Comment: 17 pages, 6 figures. Published in Solar Physic
Positive words carry less information than negative words
We show that the frequency of word use is not only determined by the word
length \cite{Zipf1935} and the average information content
\cite{Piantadosi2011}, but also by its emotional content. We have analyzed
three established lexica of affective word usage in English, German, and
Spanish, to verify that these lexica have a neutral, unbiased, emotional
content. Taking into account the frequency of word usage, we find that words
with a positive emotional content are more frequently used. This lends support
to Pollyanna hypothesis \cite{Boucher1969} that there should be a positive bias
in human expression. We also find that negative words contain more information
than positive words, as the informativeness of a word increases uniformly with
its valence decrease. Our findings support earlier conjectures about (i) the
relation between word frequency and information content, and (ii) the impact of
positive emotions on communication and social links.Comment: 16 pages, 3 figures, 3 table
Modeling the Subsurface Structure of Sunspots
While sunspots are easily observed at the solar surface, determining their
subsurface structure is not trivial. There are two main hypotheses for the
subsurface structure of sunspots: the monolithic model and the cluster model.
Local helioseismology is the only means by which we can investigate
subphotospheric structure. However, as current linear inversion techniques do
not yet allow helioseismology to probe the internal structure with sufficient
confidence to distinguish between the monolith and cluster models, the
development of physically realistic sunspot models are a priority for
helioseismologists. This is because they are not only important indicators of
the variety of physical effects that may influence helioseismic inferences in
active regions, but they also enable detailed assessments of the validity of
helioseismic interpretations through numerical forward modeling. In this paper,
we provide a critical review of the existing sunspot models and an overview of
numerical methods employed to model wave propagation through model sunspots. We
then carry out an helioseismic analysis of the sunspot in Active Region 9787
and address the serious inconsistencies uncovered by
\citeauthor{gizonetal2009}~(\citeyear{gizonetal2009,gizonetal2009a}). We find
that this sunspot is most probably associated with a shallow, positive
wave-speed perturbation (unlike the traditional two-layer model) and that
travel-time measurements are consistent with a horizontal outflow in the
surrounding moat.Comment: 73 pages, 19 figures, accepted by Solar Physic
Joint Analysis of Multiple Metagenomic Samples
The availability of metagenomic sequencing data, generated by sequencing DNA pooled from multiple microbes living jointly, has increased sharply in the last few years with developments in sequencing technology. Characterizing the contents of metagenomic samples is a challenging task, which has been extensively attempted by both supervised and unsupervised techniques, each with its own limitations. Common to practically all the methods is the processing of single samples only; when multiple samples are sequenced, each is analyzed separately and the results are combined. In this paper we propose to perform a combined analysis of a set of samples in order to obtain a better characterization of each of the samples, and provide two applications of this principle. First, we use an unsupervised probabilistic mixture model to infer hidden components shared across metagenomic samples. We incorporate the model in a novel framework for studying association of microbial sequence elements with phenotypes, analogous to the genome-wide association studies performed on human genomes: We demonstrate that stratification may result in false discoveries of such associations, and that the components inferred by the model can be used to correct for this stratification. Second, we propose a novel read clustering (also termed “binning”) algorithm which operates on multiple samples simultaneously, leveraging on the assumption that the different samples contain the same microbial species, possibly in different proportions. We show that integrating information across multiple samples yields more precise binning on each of the samples. Moreover, for both applications we demonstrate that given a fixed depth of coverage, the average per-sample performance generally increases with the number of sequenced samples as long as the per-sample coverage is high enough
Insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3) overexpression in pancreatic ductal adenocarcinoma correlates with poor survival
<p>Abstract</p> <p>Background</p> <p>Pancreatic ductal adenocarcinoma is a lethal disease with a 5-year survival rate of 4% and typically presents in an advanced stage. In this setting, prognostic markers identifying the more agrressive tumors could aid in managment decisions. Insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3, also known as IMP3 or KOC) is an oncofetal RNA-binding protein that regulates targets such as insulin-like growth factor-2 (IGF-2) and ACTB (beta-actin).</p> <p>Methods</p> <p>We evaluated the expression of IGF2BP3 by immunohistochemistry using a tissue microarray of 127 pancreatic ductal adenocarcinomas with tumor grade 1, 2 and 3 according to WHO criteria, and the prognostic value of IGF2BP3 expression.</p> <p>Results</p> <p>IGF2BP3 was found to be selectively overexpressed in pancreatic ductal adenocarcinoma tissues but not in benign pancreatic tissues. Nine (38%) patient samples of tumor grade 1 (n = 24) and 27 (44%) of tumor grade 2 (n = 61) showed expression of IGF2BP3. The highest rate of expression was seen in poorly differentiated specimen (grade 3, n = 42) with 26 (62%) positive samples. Overall survival was found to be significantly shorter in patients with IGF2BP3 expressing tumors (P = 0.024; RR 2.3, 95% CI 1.2-4.8).</p> <p>Conclusions</p> <p>Our data suggest that IGF2BP3 overexpression identifies a subset of pancreatic ductal adenocarcinomas with an extremely poor outcome and supports the rationale for developing therapies to target the IGF pathway in this cancer.</p
- …