A new method for calculating the convergent point of a moving group

Context. Convergent point (CP) search methods are important tools for studying the kinematic properties of open clusters and young associations whose members share the same spatial motion. Aims. We present a new CP search strategy based on proper motion data. We test the new algorithm on synthetic data and compare it with previous versions of the CP search method. As an illustration and validation of the new method we also present an application to the Hyades open cluster and a comparison with independent results. Methods. The new algorithm rests on the idea of representing the stellar proper motions by great circles over the celestial sphere and visualizing their intersections as the CP of the moving group. The new strategy combines a maximum-likelihood analysis for simultaneously determining the CP and selecting the most likely group members and a minimization procedure that returns a refined CP position and its uncertainties. The method allows one to correct for internal motions within the group and takes into account that the stars in the group lie at different distances. Results. Based on Monte Carlo simulations, we find that the new CP search method in many cases returns a more precise solution than its previous versions. The new method is able to find and eliminate more field stars in the sample and is not biased towards distant stars. The CP solution for the Hyades open cluster is in excellent agreement with previous determinations.

A search for anisotropy in the arrival directions of ultra high energy cosmic rays recorded at the Pierre Auger Observatory

Observations of cosmic rays arrival directions made with the Pierre Auger Observatory have previously provided evidence of anisotropy at the 99% CL using the correlation of ultra high energy cosmic rays (UHECRs) with objects drawn from the Veron-Cetty Veron catalog. In this paper we report on the use of three catalog independent methods to search for anisotropy. The 2pt-L, 2pt+ and 3pt methods, each giving a different measure of self-clustering in arrival directions, were tested on mock cosmic ray data sets to study the impacts of sample size and magnetic smearing on their results, accounting for both angular and energy resolutions. If the sources of UHECRs follow the same large scale structure as ordinary galaxies in the local Universe and if UHECRs are deflected no more than a few degrees, a study of mock maps suggests that these three method can efficiently respond to the resulting anisotropy with a P-value = 1.0% or smaller with data sets as few as 100 events. using data taken from January 1, 2004 to July 31, 2010 we examined the 20, 30, ... , 110 highest energy events with a corresponding minimum energy threshold of about 49.3 EeV. The minimum P-values found were 13.5% using the 2pt-L method, 1.0% using the 2pt+ method and 1.1% using the 3pt method for the highest 100 energy events. In view of the multiple (correlated) scans performed on the data set, these catalog-independent methods do not yield strong evidence of anisotropy in the highest energy cosmic rays.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

A search for point sources of EeV neutrons

A thorough search of the sky exposed at the Pierre Auger Cosmic Ray Observatory reveals no statistically significant excess of events in any small solid angle that would be indicative of a flux of neutral particles from a discrete source. The search covers from -90 degrees to +15 degrees in declination using four different energy ranges above 1 EeV (10(18) eV). The method used in this search is more sensitive to neutrons than to photons. The upper limit on a neutron flux is derived for a dense grid of directions for each of the four energy ranges. These results constrain scenarios for the production of ultrahigh energy cosmic rays in the Galaxy.

Diagnostic methods in sepsis: the need of speed

Objective: Sepsis is a common condition encountered in hospital environments. There is no effective treatment for sepsis, and it remains an important cause of death at intensive care units. This study aimed to discuss some methods that are available in clinics, and tests that have been recently developed for the diagnosis of sepsis. Methods: A systematic review was performed through the analysis of the following descriptors: sepsis, diagnostic methods, biological markers, and cytokines. Results: The deleterious effects of sepsis are caused by an imbalance between the invasiveness of the pathogen and the ability of the host to mount an effective immune response. Consequently, the host's immune surveillance fails to eliminate the pathogen, allowing it to spread. Moreover, there is a pro-inflammatory mediator release, inappropriate activation of the coagulation and complement cascades, leading to dysfunction of multiple organs and systems. The difficulty achieve total recovery of the patient is explainable. There is an increased incidence of sepsis worldwide due to factors such as aging population, larger number of surgeries, and number of microorganisms resistant to existing antibiotics. Conclusion: The search for new diagnostic markers associated with increased risk of sepsis development and molecules that can be correlated to certain steps of sepsis is becoming necessary. This would allow for earlier diagnosis, facilitate patient prognosis characterization, and prediction of possible evolution of each case. All other markers are regrettably constrained to research units.

A new evolutionary clustering search for a no-wait flow shop problem with set-up times

This paper addresses the m-machine no-wait flow shop problem where the set-up time of a job is separated from its processing time. The performance measure considered is the total flowtime. A new hybrid metaheuristic Genetic Algorithm-Cluster Search is proposed to solve the scheduling problem. The performance of the proposed method is evaluated and the results are compared with the best method reported in the literature. Experimental tests show superiority of the new method for the test problems set, regarding the solution quality. (c) 2012 Elsevier Ltd. All rights reserved.

Diagnostic methods in sepsis: the need of speed

OBJECTIVE: Sepsis is a common condition encountered in hospital environments. There is no effective treatment for sepsis, and it remains an important cause of death at intensive care units. This study aimed to discuss some methods that are available in clinics, and tests that have been recently developed for the diagnosis of sepsis. METHODS: A systematic review was performed through the analysis of the following descriptors: sepsis, diagnostic methods, biological markers, and cytokines. RESULTS: The deleterious effects of sepsis are caused by an imbalance between the invasiveness of the pathogen and the ability of the host to mount an effective immune response. Consequently, the host's immune surveillance fails to eliminate the pathogen, allowing it to spread. Moreover, there is a pro-inflammatory mediator release, inappropriate activation of the coagulation and complement cascades, leading to dysfunction of multiple organs and systems. The difficulty achieve total recovery of the patient is explainable. There is an increased incidence of sepsis worldwide due to factors such as aging population, larger number of surgeries, and number of microorganisms resistant to existing antibiotics. CONCLUSION: The search for new diagnostic markers associated with increased risk of sepsis development and molecules that can be correlated to certain steps of sepsis is becoming necessary. This would allow for earlier diagnosis, facilitate patient prognosis characterization, and prediction of possible evolution of each case. All other markers are regrettably constrained to research units.