Directed, Elliptic, and Higher Order Flow Harmonics of Protons, Deuterons, and Tritons in Au+Au Collisions at sqrt[s_{NN}]=2.4 GeV.

Flow coefficients v_{n} of the orders n=1-6 are measured with the High-Acceptance DiElectron Spectrometer (HADES) at GSI for protons, deuterons, and tritons as a function of centrality, transverse momentum, and rapidity in Au+Au collisions at sqrt[s_{NN}]=2.4 GeV. Combining the information from the flow coefficients of all orders allows us to construct for the first time, at collision energies of a few GeV, a multidifferential picture of the angular emission pattern of these particles. It reflects the complicated interplay between the effect of the central fireball pressure on the emission of particles and their subsequent interaction with spectator matter. The high precision information on higher order flow coefficients is a major step forward in constraining the equation of state of dense baryonic matter.

Strong Absorption of Hadrons with Hidden and Open Strangeness in Nuclear Matter.

We present the first observation of K^{-} and ϕ absorption within nuclear matter by means of π^{-}-induced reactions on C and W targets at an incident beam momentum of 1.7 GeV/c studied with HADES at SIS18/GSI. The double ratio (K^{-}/K^{+})_{W}/(K^{-}/K^{+})_{C} is found to be 0.319±0.009(stat)_{-0.012}^{+0.014}(syst) indicating a larger absorption of K^{-} in heavier targets as compared to lighter ones. The measured ϕ/K^{-} ratios in π^{-}+C and π^{-}+W reactions within the HADES acceptance are found to be equal to 0.55±0.04(stat)_{-0.07}^{+0.06}(syst) and to 0.63±0.06(stat)_{-0.11}^{+0.11}(syst), respectively. The similar ratios measured in the two different reactions demonstrate for the first time experimentally that the dynamics of the ϕ meson in nuclear medium is strongly coupled to the K^{-} dynamics. The large difference in the ϕ production off C and W nuclei is discussed in terms of a strong ϕN in-medium coupling. These results are relevant for the description of heavy-ion collisions and the structure of neutron stars.

Subthreshold Ξ

Results on the production of the double strange cascade hyperon Ξ^{-} are reported for collisions of p(3.5 GeV)+Nb, studied with the High Acceptance Di-Electron Spectrometer (HADES) at SIS18 at GSI Helmholtzzentrum for Heavy-Ion Research, Darmstadt. For the first time, subthreshold Ξ^{-} production is observed in proton-nucleus interactions. Assuming a Ξ^{-} phase-space distribution similar to that of Λ hyperons, the production probability amounts to P_{Ξ^{-}}=[2.0±0.4(stat)±0.3(norm)±0.6(syst)]×10^{-4} resulting in a Ξ^{-}/(Λ+Σ^{0}) ratio of P_{Ξ^{-}}/P_{Λ+Σ^{0}}=[1.2±0.3(stat)±0.4(syst)]×10^{-2}. Available model predictions are significantly lower than the measured Ξ^{-} yield.

Feature extraction by statistical contact potentials and wavelet transform for predicting subcellular localizations in gram negative bacterial proteins.

Predicting the localization of a protein has become a useful practice for inferring its function. Most of the reported methods to predict subcellular localizations in Gram-negative bacterial proteins make use of standard protein representations that generally do not take into account the distribution of the amino acids and the structural information of the proteins. Here, we propose a protein representation based on the structural information contained in the pairwise statistical contact potentials. The wavelet transform decodes the information contained in the primary structure of the proteins, allowing the identification of patterns along the proteins, which are used to characterize the subcellular localizations. Then, a support vector machine classifier is trained to categorize them. Cellular compartments like periplasm and extracellular medium are difficult to predict, having a high false negative rate. The wavelet-based method achieves an overall high performance while maintaining a low false negative rate, particularly, on "periplasm" and "extracellular medium". Our results suggest the proposed protein characterization is a useful alternative to representing and predicting protein sequences over the classical and cutting edge protein depictions.

Multiobjective optimization-based design of wearable electrocardiogram monitoring systems.

Nowadays, the use of Wearable User Interfaces has been extensively growing in medical monitoring applications. However, production and manufacture of prototypes without automation tools may lead to non viable results since it is often common to find an optimization problem where several variables are in conflict with each other. Thus, it is necessary to design a strategy for balancing the variables and constraints, systematizing the design in order to reduce the risks that are present when it is exclusively guided by the intuition of the developer. This paper proposes a framework for designing wearable ECG monitoring systems using multi-objective optimization. The main contributions of this work are the model to automate the design process, including a mathematical expression relating the principal variables that make up the criteria of functionality and wearability. We also introduce a novel yardstick for deciding the location of electrodes, based on reducing interference from ECG by maximizing the electrode-skin contact.

Contact potentials via wavelet transform for prediction of subcellular localizations in gram negative bacterial proteins.

Predicting the localization of a protein has become a useful practice for inferring its function. Most of the reported methods to predict subcellular localizations in Gram-negative bacterial proteins have shown a low false positive rate. However, some subcellular compartmens like "periplasm" and "extracellular medium" are difficult to predict and remain high false negative rates. In this paper, a method based on representation from statistical contact potentials and wavelet transform is presented. The wavelet-based method achieves an overall high performance holding low false and negative rates particularly on periplasm and extracellular medium. Results suggest the contact potentials as an useful alternative to characterize protein sequences.

A comparison of multi-label techniques based on problem transformation for protein functional prediction.

A comparative analysis of four multi-label classification methods is performed in order to determine the best topology for the problem of protein function prediction, using support vector machines as base classifiers. Comparisons are done in terms of performance and computational cost of parallelized versions of the algorithms, for determining its applicability in high-throughput scenarios. Results show that the performance of the binary relevance strategy, together with a technique of class balance, remains above several recently proposed techniques for the problem at hand, while employing the smallest computational cost when parallelized. However, stacked classfiers and chain classifications can be conveniently used in pipelines, due to the low number of false positives reported.

An adaptation of Pfam profiles to predict protein sub-cellular localization in Gram positive bacteria.

Predicting the sub-cellular localization of a protein can provide useful information to uncover its molecular functions. In this sense, numerous prediction techniques have been developed, which usually have been focused on global information of the protein or sequence alignments. However, several studies have shown that the functional nature of proteins is ruled by conserved sub-sequence patterns known as domains. In this paper, an alternative methodology (PfamFeat) for gram-positive bacterial sub-cellular localization was developed. PfamFeat is based on information provided by Pfam database, which stores a series of HMM-profiles describing common protein domains. The likelihood of a sequence, to be generated by a given HMM-profile, can be used to characterize sequences in order to use pattern recognition techniques. Success rates obtained with a simple one-nearest neighbor classifier demonstrate that this method is competitive with popular sub-cellular prediction algorithms and it constitutes a promising research trend.

Prediction of protein subcellular localization based on variable-length motifs detection and dissimilarity based classification.

Predict the function of unknown proteins is one of the principal goals in computational biology. The subcellular localization of a protein allows further understanding its structure and molecular function. Numerous prediction techniques have been developed, usually focusing on global information of the protein. But, predictions can be done through the identification of functional sub-sequence patterns known as motifs. For motifs discovery problem, many methods requires a predefined fixed window size in advance and aligned sequences. To confront these problems we proposed a method based on variable length motifs characterization and detection using the continuous wavelet transform (CWT) and a dissimilarity space representation. For analyzing the motifs results generated by our approach, we divide the entire dataset into training (60%) and validation (40%). A Support Vector Machine (SVM) classifier is used as predictor for validation set. The highest Sn = 82.58% and Sp = 92.86%, across 10-fold cross validation, is obtained for endosome proteins. Average results Sn = 74% and Sp = 75.58% are comparable to current state of the art. For data sets whose identity is low (< 40%), the motifs characterization and localization based on CWT shows a good performance and the interpretability of the subsequences in each subcellular localization.

Predictability of protein subcellular locations by pattern recognition techniques.

An analysis of the predictability of subcellular locations is performed by using simple pattern recognition techniques in an attempt to capture the real dimensions of the problem at hand. Results show that there are some particular locations that does not need of high complexity classification models to be predicted with high accuracies, and some partial biological explanations are formulated. All the experiments were carried out over a set of Arabidopsis Thaliana proteins and classes were defined according to the plants GO slim.

Deep subthreshold Xi;{-} production in Ar + KCl reactions at 1.76A GeV.

We report first results on a deep subthreshold production of the doubly strange hyperon Xi;{-} in a heavy-ion reaction. At a beam energy of 1.76A GeV the reaction Ar + KCl was studied with the High Acceptance Di-Electron Spectrometer at SIS18/GSI. A high-statistics and high-purity Lambda sample was collected, allowing for the investigation of the decay channel Xi;{-} --> Lambdapi;{-}. The deduced Xi;{-}/(Lambda + Sigma;{0}) production ratio of (5.6 +/- 1.2_{-1.7};{+1.8}) x 10;{-3} is significantly larger than available model predictions.

Dielectron production in 12C+12C collisions at 2A GeV with the HADES spectrometer.

The invariant-mass spectrum of e+e- pairs produced in 12C+12C collisions at an incident energy of 2 GeV per nucleon has been measured for the first time. The measured pair production probabilities span over 5 orders of magnitude from the pi(0)-Dalitz to the rho/omega invariant-mass region. Dalitz decays of pi(0) and eta account for all the yield up to 0.15 GeV/c(2), but for only about 50% above this mass. A comparison with model calculations shows that the excess pair yield is likely due to baryon-resonance and vector-meson decays. Transport calculations based on vacuum spectral functions fail, however, to describe the entire mass region.

[Neurofibroma of the lower lip]. / Neurofibroma de labio inferior.

Reporting a nervous tumor diagnosed as Neurofibroma, which owing to its localisation, on the lower lip, and its possible origin, from a salivary gland, should be considered an extraordinary rarity. The AA, make a bibliographic review of the commonest sites of the growth, the histological description and consider some possible differential diagnosis with special emphasis to the schwannoma and the Recklinghausen's disease.

Blastomicosis sudamericana en una niña. Forma diseminada a localización ósea predominante / [South American blastomycosis in a girl. Disseminated form and predominant bone localization]

Los autores presentan una observación de Blastomicosis Sudamericana (Paracoccidioidomicosis) en una niña de 10 años de edad. Destacan la escasa incidencia de la afección en la infancia y estiman que es la primera publicación argentina referida a niños. Hacen referencia ala forma clínica, poco común, de localización ósea predominante con que ha evolucionado. Luego de la descripción clínica y de los comentarios acerca del diagnóstico diferencial, mencionan la rápida mejoría lograda con la administración de un derivado sulfamídico de acción lenta.

The authors present a case of Southamerican Blastomycosis in a tenyears old girl. They emphasize the unusual incidence of the disease in children and consider that this is the first argentine publication in Pediatrics. They also refer to the unusal evolution with preferent localization in bones. After the clinical description and the commentaries about the differential diagnosis the authors mention the rapid improvement obtained by giving a sulfamide derivate.