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&gt

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