Large deviations for stochastic Volterra equations

This paper is devoted to prove a large-deviation principle for solutions to multidimensional stochastic Volterra equations.

Bioinformatics: making large-scale science happen

Bionformatics is a rapidly evolving research field dedicated toanalyzing and managing biological data with computational resources. This paperaims to overview some of the processes and applications currently implementedat CCiT-UB¿s Bioinformatics Unit, focusing mainly on the areas of Genomics,Transcriptomics and Proteomics

The EU-ADR Web Platform: delivering advanced pharmacovigilance tools

PURPOSE: Pharmacovigilance methods have advanced greatly during the last decades, making post-market drug assessment an essential drug evaluation component. These methods mainly rely on the use of spontaneous reporting systems and health information databases to collect expertise from huge amounts of real-world reports. The EU-ADR Web Platform was built to further facilitate accessing, monitoring and exploring these data, enabling an in-depth analysis of adverse drug reactions risks.METHODS: The EU-ADR Web Platform exploits the wealth of data collected within a large-scale European initiative, the EU-ADR project. Millions of electronic health records, provided by national health agencies, are mined for specific drug events, which are correlated with literature, protein and pathway data, resulting in a rich drug-event dataset. Next, advanced distributed computing methods are tailored to coordinate the execution of data-mining and statistical analysis tasks. This permits obtaining a ranked drug-event list, removing spurious entries and highlighting relationships with high risk potential.RESULTS: The EU-ADR Web Platform is an open workspace for the integrated analysis of pharmacovigilance datasets. Using this software, researchers can access a variety of tools provided by distinct partners in a single centralized environment. Besides performing standalone drug-event assessments, they can also control the pipeline for an improved batch analysis of custom datasets. Drug-event pairs can be substantiated and statistically analysed within the platform's innovative working environment.CONCLUSIONS: A pioneering workspace that helps in explaining the biological path of adverse drug reactions was developed within the EU-ADR project consortium. This tool, targeted at the pharmacovigilance community, is available online at https://bioinformatics.ua.pt/euadr/. Copyright © 2012 John Wiley & Sons, Ltd.

Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.

Fluid dynamical prediction of changed v1-flow at energies available at the CERN Large Hadron Collider

Substantial collective flow is observed in collisions between lead nuclei at Large Hadron Collider (LHC) as evidenced by the azimuthal correlations in the transverse momentum distributions of the produced particles. Our calculations indicate that the global v1-flow, which at RHIC peaked at negative rapidities (named third flow component or antiflow), now at LHC is going to turn toward forward rapidities (to the same side and direction as the projectile residue). Potentially this can provide a sensitive barometer to estimate the pressure and transport properties of the quark-gluon plasma. Our calculations also take into account the initial state center-of-mass rapidity fluctuations, and demonstrate that these are crucial for v1 simulations. In order to better study the transverse momentum flow dependence we suggest a new"symmetrized" vS1(pt) function, and we also propose a new method to disentangle global v1 flow from the contribution generated by the random fluctuations in the initial state. This will enhance the possibilities of studying the collective Global v1 flow both at the STAR Beam Energy Scan program and at LHC.

Goal setting and monetary incentives: when large stakes are not enough

The aim of this paper is to test the effectiveness of wage-irrelevant goal setting policies in a laboratory environment. In our design, managers can assign a goal to their workers by setting a certain level of performance on the work task. We establish our theoretical conjectures by developing a model where assigned goals act as reference points to workers’ intrinsic motivation. Consistent with our model, we find that managers set goals which are challenging but attainable for an average-ability worker. Workers respond to these goals by increasing effort, performance and by decreasing on-the-job leisure activities with respect to the no-goal setting baseline. Finally, we study the interaction between goal setting and monetary rewards and find that goal setting is most effective when monetary incentives are strong. These results suggest that goal setting may produce intrinsic motivation and increase workers’ performance beyond what is achieved using solely monetary incentives.

Averting risk in the face of large losses: Bernoulli vs. Tversky and Kahneman

We experimentally question the assertion of Prospect Theory that people display risk attraction in choices involving high-probability losses. Indeed, our experimental participants tend to avoid fair risks for large (up to ? 90), high-probability (80%) losses. Our research hinges on a novel experimental method designed to alleviate the house-money bias that pervades experiments with real (not hypothetical) loses.Our results vindicate Daniel Bernoulli?s view that risk aversion is the dominant attitude,But, contrary to the Bernoulli-inspired canonical expected utility theory, we do find frequent risk attraction for small amounts of money at stake.In any event, we attempt neither to test expected utility versus nonexpected utility theories, nor to contribute to the important literature that estimates value and weighting functions. The question that we ask is more basic, namely: do people display risk aversion when facing large losses, or large gains? And, at the risk of oversimplifying, our answer is yes.

Large gypsum nodules in the Paleogene and Neogene evaporites of Spain: distribution and palaeogeographic significance

Sabkha and deep burial set tings are the most com mon sites where diagenetic anhydrite forms. In a sabkha setting, displacive facies (iso lated nodules, bed ded nodules, enterolithic levels) of early diagenetic or primary anhydrite are generated (Shearman, 1966; Hardie, 1967). These anhydrite facies are commonly foundat the top of shoal ing cycles representing the evolution from subaqueous depositional conditions at the base (carbonates, lutites) to exposure conditions at the top where in ter stitially-grown gypsum/anhydrite de velops ( sabkha cy cles). In a deep burial setting, gypsum transforms to tally to anhydrite with in creas ing temperature and lithostatic pressure (Murray, 1964). Al though this mineral transformation usually preserves the depositional gypsum facies, a significant textural change is in volved in other cases, resulting in replacive anhydrite with a nodular-mosaic or"chicken-wire" fabric (Warren, 2006). In the two settings, how ever, the size of the individual anhydrite nodules is relatively small, rarely reaching some tens of centimetres across. More over, bedding is preserved or little disturbed, al though minor de formation is caused by the displacive sabkha nodules.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Polyunsaturated aldehydes from large phytoplankton of the Atlantic Ocean Surface (42ºN to 33ºS)

Polyunsaturated aldehydes (PUAs) are organic compounds mainly produced by diatoms, after cell wounding. These compounds are increasingly reported as teratogenic for species of grazers and deleterious for phytoplanktonic species, but there is still scarce information regarding concentration ranges and the composition of PUAs in the open ocean. In this study, we analyzed the spatial distribution and the type of aldehydes produced by the large-sized (>10 μm) phytoplankton in the Atlantic Ocean surface. Analyses were conducted on PUAs released after mechanical disruption of the phytoplankton cells, referred to here as potential PUAs (pPUAs). Results show the ubiquitous presence of pPUA in the open ocean, including upwelling areas, as well as oligotrophic gyres. Total pPUA concentrations ranged from zero to 4.18 pmol from cells in 1 L. Identified PUAs were heptadienal, octadienal and decadienal, with heptadienal being the most common (79% of total stations). PUA amount and composition across the Atlantic Ocean was mainly related to the nitrogen:phosphorus ratio, suggesting nutrient-driven mechanisms of PUA production. Extending the range of trophic conditions considered by adding data reported for productive coastal waters, we found a pattern of PUA variation in relation to trophic status.

Large D gravity and low D strings

We show that in the limit of a large number of dimensions a wide class of nonextremal neutral black holes has a universal near-horizon limit. The limiting geometry is the two-dimensional black hole of string theory with a two-dimensional target space. Its conformal symmetry explains the properties of massless scalars found recently in the large-D limit. For black branes with string charges, the near-horizon geometry is that of the three-dimensional black strings of Horne and Horowitz. The analogies between the α′ expansion in string theory and the large-D expansion in gravity suggest a possible effective string description of the large-D limit of black holes. We comment on applications to several subjects, in particular to the problem of critical collapse.

DnaSP v5: A software for comprehensive analysis of DNA polymorphism data

DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.