Reconciling a significant hierarchical assembly of massive early-type galaxies at z<~1 with mass downsizing

Hierarchical models predict that massive early-type galaxies (mETGs) are the latest systems to be in place into the cosmic scenario (at z<~0.5), conflicting with the observational phenomenon of galaxy mass downsizing, which poses that the most massive galaxies have been in place earlier that their lower-mass counterparts (since z~0.7). We have developed a semi-analytical model to test the feasibility of the major-merger origin hypothesis for mETGs, just accounting for the effects on galaxy evolution of the major mergers strictly reported by observations. The most striking model prediction is that very few present-day mETGs have been really in place since z~1, because ~90% of the mETGs existing at z~1 are going to be involved in a major merger between z~1 and the present. Accounting for this, the model derives an assembly redshift for mETGs in good agreement with hierarchical expectations, reproducing observational mass downsizing trends at the same time.Comment: 2 pages, 1 figure, Proceedings of Symposium 2 of JENAM 2010, "Environment and the Formation of Galaxies: 30 years later", ed. I. Ferreras and A. Pasquali, Astrophysics & Space Science Proceedings, Springe

Computational Analysis of a Spiral Thermoelectric Nanoantenna for Solar Energy Harvesting Applications

Thermo-electrical nanoantennas have been proposed as an alternative option for conversion solar energy harvesting applications. In this work, the response of a spiral broadband antenna has been obtained from numerical and theoretical simulations perspectives. The results show that this device exhibits a responsivity of 20mV/W under 117W/cm2, for a single-frequency radiation. We discuss strategies for enhanced efficiency

Integrating knowledge tracing and item response theory: A tale of two frameworks

Traditionally, the assessment and learning science commu-nities rely on different paradigms to model student performance. The assessment community uses Item Response Theory which allows modeling different student abilities and problem difficulties, while the learning science community uses Knowledge Tracing, which captures skill acquisition. These two paradigms are complementary - IRT cannot be used to model student learning, while Knowledge Tracing assumes all students and problems are the same. Recently, two highly related models based on a principled synthesis of IRT and Knowledge Tracing were introduced. However, these two models were evaluated on different data sets, using different evaluation metrics and with different ways of splitting the data into training and testing sets. In this paper we reconcile the models' results by presenting a unified view of the two models, and by evaluating the models under a common evaluation metric. We find that both models are equivalent and only differ in their training procedure. Our results show that the combined IRT and Knowledge Tracing models offer the best of assessment and learning sciences - high prediction accuracy like the IRT model, and the ability to model student learning like Knowledge Tracing

The scaling of X-ray variability with luminosity in Ultra-luminous X-ray sources

We investigated the relationship between the X-ray variability amplitude and X-ray luminosity for a sample of 14 bright Ultra-luminous X-ray sources (ULXs) with XMM-Newton/EPIC data, and compare it with the well established similar relationship for Active Galactic Nuclei (AGN). We computed the normalised excess variance in the 2-10 keV light curves of these objects and their 2-10 keV band intrinsic luminosity. We also determined model "variability-luminosity" relationships for AGN, under several assumptions regarding their power-spectral shape. We compared these model predictions at low luminosities with the ULX data. The variability amplitude of the ULXs is significantly smaller than that expected from a simple extrapolation of the AGN "variability-luminosity" relationship at low luminosities. We also find evidence for an anti-correlation between the variability amplitude and L(2-10 keV) for ULXs. The shape of this relationship is consistent with the AGN data but only if the ULXs data are shifted by four orders of magnitudes in luminosity. Most (but not all) of the ULXs could be "scaled-down" version of AGN if we assume that: i) their black hole mass and accretion rate are of the order of ~(2.5-30)x 10E+03 Msolar and ~ 1-80 % of the Eddington limit, and ii) their Power Spectral Density has a doubly broken power-law shape. This PDS shape and accretion rate is consistent with Galactic black hole systems operating in their so-called "low-hard" and "very-high" states.Comment: 10 pages, 5 figures, 2 tables, accepted for publication in A&

Quantification of virus syndrome in chili peppers

One of the most important problems to produce chili crops is the presence of diseases caused by pathogen agents, such as viruses, therefore, there is a substantial necessity to better predict the behavior of the diseases of these crops, determining a more precise quantification of the disease’s syndrome that allows the investigators to evaluate better practices, from handling to the experimental level and will permit producers to take opportunistic corrective action thereby, reducing production loses and increasing the quality of the crop. This review discussed methods that have been used for the quantification of disease in plants, specifically for chili peppers crops, thereby, suggesting a better alternative for the quantification of the disease’ syndromes in regards to this crop. The result of these reflections indicates that most methods used for quantification are based on visual assessments, discarding differences of data between distinctive evaluators. These methods generate subjective results.Key words: Quantification, plant diseases, severity, syndrome, viruses

Associations Between Dry Land Strength and Power Measurements with Swimming Performance in Elite Athletes: a Pilot Study

The main aim of the present study was to analyze the relationships between dry land strength and power measurements with swimming performance. Ten male national level swimmers (age: 14.9 ± 0.74 years, body mass: 60.0 ± 6.26 kg, height: 171.9 ± 6.26, 100 m long course front crawl performance: 59.9 ± 1.87 s) volunteered as subjects. Height and Work were estimated for CMJ. Mean power in the propulsive phase was assessed for squat, bench press (concentric phase) and lat pull down back. Mean force production was evaluated through 30 s maximal effort tethered swimming in front crawl using whole body, arms only and legs only. Swimming velocity was calculated from a maximal bout of 50 m front crawl. Height of CMJ did not correlate with any of the studied variables. There were positive and moderate-strong associations between the work during CMJ and mean propulsive power in squat with tethered forces during whole body and legs only swimming. Mean propulsive power of bench press and lat pull down presented positive and moderate-strong relationships with mean force production in whole body and arms only. Swimming performance is related with mean power of lat pull down back. So, lat pull down back is the most related dry land test with swimming performance; bench press with force production in water arms only; and work during CMJ with tethered forces legs only.UBI/FCSH/Santander/2010info:eu-repo/semantics/publishedVersio

Association Between Force-Time Curve Characteristics and Vertical Jump Performance in Trained Athletes

Countermovement jump (CMJ) has been extensively used in training; yet, limited and contradictory kinematic data are available for trained subjects. To our best knowledge, no other studies have evaluated the associations between force-time curve characteristics and CMJ in a large sample of trained athletes using a linear transducer. Thus, the aim of this study was to determine the association between force-time measures and CMJ performance collected with a linear transducer. Thirty-five trained athletes were asked to perform 3 maximal weighted CMJ using a linear transducer attached to a barbell (17 kg). The data indicated that the maximal rate of force development (RFD(max)) was strongly related to CMJ displacement (r = 0.809/0.807, p < 0.001) and also to the percentage of peak force (r = -0.823/-0.809, p < 0.001) at RFD(max). Velocity and displacement at RFD(max) were not correlated to CMJ height. It was therefore concluded that the percentage of PF applied at RFD(max) and RFD(max) were the best predictive variables for CMJ performance in this study.info:eu-repo/semantics/publishedVersio

Understanding vehicular routing behavior with location-based service data

This is the final published version, also available from Springer Nature via the DOI in this record.Properly extracting patterns of individual mobility with high resolution data sources such as the one extracted from smartphone applications offers important opportunities. Potential opportunities not offered by call detailed records (CDRs), which offer resolutions triangulated from antennas, are route choices, travel modes detection and close encounters. Nowadays, there is not a standard and large scale data set collected over long periods that allows us to characterize these. In this work we thoroughly examine the use of data from smartphone applications, also referred to as location-based services (LBS) data, to extract and understand the vehicular route choice behavior. Taking the Dallas-Fort Worth metroplex as an example, we first extract the vehicular trips with simple rules and reconstruct the origin-destination matrix by coupling the extracted vehicular trips of the active LBS users and the United States census data. We then present a method to derive the commonly used routes by individuals from the LBS traces with varying sample rate intervals. We further inspect the relation between the number of routes and the trip characteristics, including the departure time, trip length and travel time. Specifically, we consider the travel time index and buffer index for the LBS users taking different number of routes. Empirical results demonstrate that during the peak hours, travelers tend to reduce the impact of traffic congestion by taking alternative routes. Overall, the proposed data analysis framework is cost-effective to treat sparse data generated from the use of smartphones to inform routing behavior. The potential in practice is to inform demand management strategies, by targeting individual users while generating large scale estimates of congestion mitigation.MIT Energy InitiativeBerkeley Deep Drive consortiu

Color image segmentation using perceptual spaces through applets for determining and preventing diseases in chili peppers

Plant pathogens cause disease in plants. Chili peppers are one of the most important crops in the world. There are currently disease detection techniques classified as: biochemical, microscopy, immunology, nucleic acid hybridization, identification by visual inspection in vitro or in situ but these have the following disadvantages: they require several days, their implementation is costly and highly trained. This paper proposes a method for knowing and preventing the disease in chili peppers plant through a color image processing, using online system developed in Java applets. This system gets results in real time and remotely (Internet). The images are converted to perceptual spaces [hue, saturation and lightness (HSL), hue, saturation, and intensity (HSI) and hue saturation and value (HSV)]. Sequence was applied to the proposed method. HSI color space was the best detected disease. The percentage of disease in the leaf is of 12.42%. HSL and HSV do not expose the exact area of the disease compared to the HSI color space. Finally, images were analyzed and the disease is known by the expert in plant pathology to take preventive or corrective actions.Keywords: Applets, knowing disease, color image segmentation, perceptual spacesAfrican Journal of Biotechnology Vol. 12(7), pp. 679-68

A universal model for mobility and migration patterns

Introduced in its contemporary form by George Kingsley Zipf in 1946, but with roots that go back to the work of Gaspard Monge in the 18th century, the gravity law is the prevailing framework to predict population movement, cargo shipping volume, inter-city phone calls, as well as bilateral trade flows between nations. Despite its widespread use, it relies on adjustable parameters that vary from region to region and suffers from known analytic inconsistencies. Here we introduce a stochastic process capturing local mobility decisions that helps us analytically derive commuting and mobility fluxes that require as input only information on the population distribution. The resulting radiation model predicts mobility patterns in good agreement with mobility and transport patterns observed in a wide range of phenomena, from long-term migration patterns to communication volume between different regions. Given its parameter-free nature, the model can be applied in areas where we lack previous mobility measurements, significantly improving the predictive accuracy of most of phenomena affected by mobility and transport processes.Comment: Main text and supplementary informatio