The abundance of Bullet-groups in LCDM

We estimate the expected distribution of displacements between the two dominant dark matter (DM) peaks (DM-DM displacements) and between DM and gaseous baryon peak (DM-gas displacements) in dark matter halos with masses larger than $10^{13}$ Msun/h. We use as a benchmark the observation of SL2S J08544-0121, which is the lowest mass system ($1.0\times 10^{14}$ Msun/h) observed so far featuring a bi-modal dark matter distribution with a dislocated gas component. We find that $(50 \pm 10)$% of the dark matter halos with circular velocities in the range 300 km/s to 700 km/s (groups) show DM-DM displacements equal or larger than $186 \pm 30$ kpc/h as observed in SL2S J08544-0121. For dark matter halos with circular velocities larger than 700 km/s (clusters) this fraction rises to 70 $\pm$ 10%. Using the same simulation we estimate the DM-gas displacements and find that 0.1 to 1.0% of the groups should present separations equal or larger than $87\pm 14$kpc/h corresponding to our observational benchmark; for clusters this fraction rises to (7 $\pm$ 3)%, consistent with previous studies of dark matter to baryon separations. Considering both constraints on the DM-DM and DM-gas displacements we find that the number density of groups similar to SL2S J08544-0121 is $\sim 6.0\times 10^{-7}$ Mpc$^{-3}$, three times larger than the estimated value for clusters. These results open up the possibility for a new statistical test of LCDM by looking for DM-gas displacements in low mass clusters and groups.Comment: 6 pages, 3 figures, accepted for publication in ApJ Letter

A data relocation approach for terrain surface analysis on multi-GPU systems: a case study on the total viewshed problem

Digital Elevation Models (DEMs) are important datasets for modelling the line of sight, such as radio signals, sound waves and human vision. These are commonly analyzed using rotational sweep algorithms. However, such algorithms require large numbers of memory accesses to 2D arrays which, despite being regular, result in poor data locality in memory. Here, we propose a new methodology called skewed Digital Elevation Model (sDEM), which substantially improves the locality of memory accesses and increases the inherent parallelism involved in the computation of rotational sweep-based algorithms. In particular, sDEM applies a data restructuring technique before accessing the memory and performing the computation. To demonstrate the high efficiency of sDEM, we use the problem of total viewshed computation as a case study considering different implementations for single-core, multi-core, single-GPU and multi-GPU platforms. We conducted two experiments to compare sDEM with (i) the most commonly used geographic information systems (GIS) software and (ii) the state-of-the-art algorithm. In the first experiment, sDEM is on average 8.8x faster than current GIS software despite being able to consider only few points because of their limitations. In the second experiment, sDEM is 827.3x faster than the state-of-the-art algorithm in the best case

Overall evaluation of Skylab imagery for mapping of Latin America

The author has identified the following significant results. Skylab imagery is both desired and needed by the Latin American catographic agencies. The imagery is cost beneficial for the production of new mapping and maintenance of existing maps at national topographic series scales. If this information was available on a near time routine coverage basis, it would provide an excellent additional data base to the Latin American cartographic community, specifically Argentina, Bolivia, Chile, Colombia, Dominican Republic, Guatemala, Paraguay, and Venezuela

Strength, jumping, and change of direction speed asymmetries are not associated with athletic performance in elite academy soccer players

The aims of the present study were twofold: 1) to measure inter-limb asymmetries from a battery of fitness tests in youth soccer players and, 2) determine the association between asymmetry and measures of athletic performance. Sixteen elite youth soccer players (14.7 ± 0.2 years) performed a single leg Abalakov test (ABK), change of direction (COD) test over 10 m (5 + 5) and 20 m (10 + 10), and an iso-inertial power test. Subjects also performed 10 m, 20 m and 30 m sprints and a bilateral countermovement jump (CMJ), which were correlated with all ABK, COD and iso-inertial asymmetry scores. A one-way repeated measures ANOVA showed significant differences between inter-limb asymmetry scores across multiple tests (p 0.05) between the different inter-limb asymmetry scores, and between asymmetry scores and athletic performance. These findings show the test-specific nature of asymmetries in youth soccer players, with the iso-inertial power test being the most sensitive in detecting asymmetry. Moreover, the results obtained suggest that inherent asymmetry in young soccer players did not negatively impact their performance

Computer simulations of nematic drops: Coupling between drop shape and nematic order

We perform Monte Carlo computer simulations of nematic drops in equilibrium with their vapor using a Gay-Berne interaction between the rod-like molecules. To generate the drops, we initially perform NPT simulations close to the nematic-vapor coexistence region, allow the system to equilibrate and subsequently induce a sudden volume expansion, followed with NVT simulations. The resultant drops coexist with their vapor and are generally not spherical but elongated, have the rodlike particles tangentially aligned at the surface and an overall nematic orientation along the main axis of the drop. We find that the drop eccentricity increases with increasing molecular elongation, κ. For small κ the nematic texture in the drop is bipolar with two surface defects, or boojums, maximizing their distance along this same axis. For sufficiently high κ, the shape of the drop becomes singular in the vicinity of the defects, and there is a crossover to an almost homogeneous texture; this reflects a transition from a spheroidal to a spindle-like dro

Neuronal Metabolism and Neuroprotection: Neuroprotective Effect of Fingolimod on Menadione-Induced Mitochondrial Damage

Imbalance in the oxidative status in neurons, along with mitochondrial damage, are common characteristics in some neurodegenerative diseases. The maintenance in energy production is crucial to face and recover from oxidative damage, and the preservation of different sources of energy production is essential to preserve neuronal function. Fingolimod phosphate is a drug with neuroprotective and antioxidant actions, used in the treatment of multiple sclerosis. This work was performed in a model of oxidative damage on neuronal cell cultures exposed to menadione in the presence or absence of fingolimod phosphate. We studied the mitochondrial function, antioxidant enzymes, protein nitrosylation, and several pathways related with glucose metabolism and glycolytic and pentose phosphate in neuronal cells cultures. Our results showed that menadione produces a decrease in mitochondrial function, an imbalance in antioxidant enzymes, and an increase in nitrosylated proteins with a decrease in glycolysis and glucose-6-phosphate dehydrogenase. All these effects were counteracted when fingolimod phosphate was present in the incubation media. These effects were mediated, at least in part, by the interaction of this drug with its specific S1P receptors. These actions would make this drug a potential tool in the treatment of neurodegenerative processes, either to slow progression or alleviate symptoms

Asynchronous processing for latent fingerprint identification on heterogeneous CPU-GPU systems

Latent fingerprint identification is one of the most essential identification procedures in criminal investigations. Addressing this task is challenging as (i) it requires analyzing massive databases in reasonable periods and (ii) it is commonly solved by combining different methods with very complex data-dependencies, which make fully exploiting heterogeneous CPU-GPU systems very complex. Most efforts in this context focus on improving the accuracy of the approaches and neglect reducing the processing time. Indeed, the most accurate approach was designed for one single thread. This work introduces the fastest methodology for latent fingerprint identification maintaining high accuracy called Asynchronous processing for Latent Fingerprint Identification (ALFI). ALFI fully exploits all the resources of CPU-GPU systems using asynchronous processing and fine-coarse parallelism for analyzing massive databases. Our approach reduces idle times in processing and exploits the inherent parallelism of comparing latent fingerprints to fingerprint impressions. We analyzed the performance of ALFI on Linux and Windows operating systems using the well-known NIST/FVC databases. Experimental results reveal that ALFI is in average 22x faster than the state-of-the-art algorithm, reaching a value of 44.7x for the best-studied case

Identification of Latent Topics in Patients Surviving COVID-19 in Mexico

With the outbreak of the SARS-CoV-2 o COVID-19 pandemic, multiple studies of risk factors and their influence on patient deaths have been developed. However, little attention is often paid to analyzing patients in risk groups despite the fact that they have been infected and inpatients can survive. In this article, with the dataset available from the Ministery of the health of Mexico, this paper proposes the use of the latent topic extraction algorithm Latent Dirichlet Allocation (LDA) for the study of COVID-19 survival factors in Mexico. The results let us conclude that in the year before strategies for prevention and control of COVID-19, the latent topics support that patients without comorbidities have a low risk of death, compared with the period of 2021, wherein in spite of having some risk factors patients can survive