Classical properties of algebras using a new graph association

We study the relation between algebraic structures and Graph Theory. We have defined five different weighted digraphs associated to a finite dimensional algebra over a field in order to tackle important properties of the associated algebras, mainly the nilpotency and solvability in the case of Leibniz algebras

Monte Carlo simulations of post-common-envelope white dwarf + main sequence binaries: The effects of including recombination energy

Detached WD+MS PCEBs are perhaps the most suitable objects for testing predictions of close-compact binary-star evolution theories, in particular, CE evolution. The population of WD+MS PCEBs has been simulated by several authors in the past and compared with observations. However, most of those predictions did not take the possible contributions to the envelope ejection from additional sources of energy (mostly recombination energy) into account. Here we update existing binary population models of WD+MS PCEBs by assuming that a fraction of the recombination energy available within the envelope contributes to ejecting the envelope. We performed Monte Carlo simulations of 10^7 MS+MS binaries for 9 different models using standard assumptions for the initial primary mass function, binary separations, and initial-mass-ratio distribution and evolved these systems using the publicly available BSE code. Including a fraction of recombination energy leads to a clear prediction of a large number of long orbital period (>~10 days) systems mostly containing high-mass WDs. The fraction of systems with He-core WD primaries increases with the CE efficiency and the existence of very low-mass He WDs is only predicted for high values of the CE efficiency (>~0.5). All models predict on average longer orbital periods for PCEBs containing C/O-core WDs than for PCEBs containing He WDs. This effect increases with increasing values of both efficiencies. Longer periods after the CE phase are also predicted for systems containing more massive secondary stars. The initial-mass-ratio distribution affects the distribution of orbital periods, especially the distribution of secondary star masses. Our simulations, in combination with a large and homogeneous observational sample, can provide constraints on the values of the CE efficiencies, as well as on the initial-mass-ratio distribution for MS+MS binary stars.Comment: 11 pages, 10 figures, accepted for publication in A&

Entropic Barriers, Frustration and Order: Basic Ingredients in Protein Folding

We solve a model that takes into account entropic barriers, frustration, and the organization of a protein-like molecule. For a chain of size $M$, there is an effective folding transition to an ordered structure. Without frustration, this state is reached in a time that scales as $M^{\lambda}$, with $\lambda\simeq 3$. This scaling is limited by the amount of frustration which leads to the dynamical selectivity of proteins: foldable proteins are limited to $\sim 300$ monomers; and they are stable in {\it one} range of temperatures, independent of size and structure. These predictions explain generic properties of {\it in vivo} proteins.Comment: 4 pages, 4 Figures appended as postscript fil

A Risk-Based Model Predictive Control Approach to Adaptive Interventions in Behavioral Health

This brief examines how control engineering and risk management techniques can be applied in the field of behavioral health through their use in the design and implementation of adaptive behavioral interventions. Adaptive interventions are gaining increasing acceptance as a means to improve prevention and treatment of chronic, relapsing disorders, such as abuse of alcohol, tobacco, and other drugs, mental illness, and obesity. A risk-based model predictive control (MPC) algorithm is developed for a hypothetical intervention inspired by Fast Track, a real-life program whose long-term goal is the prevention of conduct disorders in at-risk children. The MPC-based algorithm decides on the appropriate frequency of counselor home visits, mentoring sessions, and the availability of after-school recreation activities by relying on a model that includes identifiable risks, their costs, and the cost/benefit assessment of mitigating actions. MPC is particularly suited for the problem because of its constraint-handling capabilities, and its ability to scale to interventions involving multiple tailoring variables. By systematically accounting for risks and adapting treatment components over time, an MPC approach as described in this brief can increase intervention effectiveness and adherence while reducing waste, resulting in advantages over conventional fixed treatment. A series of simulations are conducted under varying conditions to demonstrate the effectiveness of the algorithm

Monte Carlo simulations of post-common-envelope white dwarf + main sequence binaries: comparison with the SDSS DR7 observed sample

Detached white dwarf + main sequence (WD+MS) systems represent the simplest population of post-common envelope binaries (PCEBs). Since the ensemble properties of this population carries important information about the characteristics of the common-envelope (CE) phase, it deserves close scrutiny. However, most population synthesis studies do not fully take into account the effects of the observational selection biases of the samples used to compare with the theoretical simulations. Here we present the results of a set of detailed Monte Carlo simulations of the population of WD+MS binaries in the Sloan Digital Sky Survey (SDSS) Data Release 7. We used up-to-date stellar evolutionary models, a complete treatment of the Roche lobe overflow episode, and a full implementation of the orbital evolution of the binary systems. Moreover, in our treatment we took into account the selection criteria and all the known observational biases. Our population synthesis study allowed us to make a meaningful comparison with the available observational data. In particular, we examined the CE efficiency, the possible contribution of internal energy, and the initial mass ratio distribution (IMRD) of the binary systems. We found that our simulations correctly reproduce the properties of the observed distribution of WD+MS PCEBs. In particular, we found that once the observational biases are carefully taken into account, the distribution of orbital periods and of masses of the WD and MS stars can be correctly reproduced for several choices of the free parameters and different IMRDs, although models in which a moderate fraction (<=10%) of the internal energy is used to eject the CE and in which a low value of CE efficiency is used (<=0.3) seem to fit better the observational data. We also found that systems with He-core WDs are over-represented in the observed sample, due to selection effects.Comment: 15 pages, 7 figures, accepted for publication in A&

Exploring the spectroscopic diversity of type Ia supernovae with DRACULA: a machine learning approach

The existence of multiple subclasses of type Ia supernovae (SNeIa) has been the subject of great debate in the last decade. One major challenge inevitably met when trying to infer the existence of one or more subclasses is the time consuming, and subjective, process of subclass definition. In this work, we show how machine learning tools facilitate identification of subtypes of SNeIa through the establishment of a hierarchical group structure in the continuous space of spectral diversity formed by these objects. Using Deep Learning, we were capable of performing such identification in a 4 dimensional feature space (+1 for time evolution), while the standard Principal Component Analysis barely achieves similar results using 15 principal components. This is evidence that the progenitor system and the explosion mechanism can be described by a small number of initial physical parameters. As a proof of concept, we show that our results are in close agreement with a previously suggested classification scheme and that our proposed method can grasp the main spectral features behind the definition of such subtypes. This allows the confirmation of the velocity of lines as a first order effect in the determination of SNIa subtypes, followed by 91bg-like events. Given the expected data deluge in the forthcoming years, our proposed approach is essential to allow a quick and statistically coherent identification of SNeIa subtypes (and outliers). All tools used in this work were made publicly available in the Python package Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy (DRACULA) and can be found within COINtoolbox (https://github.com/COINtoolbox/DRACULA).Comment: 16 pages, 12 figures, accepted for publication in MNRA

Redes de transmisión inteligente. Beneficios y riesgos

ResumenActualmente los sistemas eléctricos operan cada vez más cercanos a sus límites de estabilidad, es por ello que se hace necesaria y primordial la transición hacia nuevos sistemas de transmisión que garanticen la eficiente entrega de la energía eléctrica, evitando con ello cortes de energía que generan importantes pérdidas en la economía de cualquier país del mundo. En este documento se realiza un análisis de los elementos necesarios para una sana y eficiente transición de una red de transmisión eléctrica verticalmente, integrada hacia una red de transmisión inteligente. Se presenta un análisis comparativo entre dos de los marcos de referencia más importantes, el de la UE y el de EUA, en el modelo, desarrollo, beneficios y riesgos en la implementación de estos sistemas.AbstractNowadays the Power Systems are working near their stability limits, for this reason it is necessary and essential a transition to new transmission systems that ensure efficient delivery of electrical energy, with the objective to prevent “blackouts” that cause significant losses in the economy of any country in the world. This paper analyzes important elements to consider having a healthy and efficient transition from a power grid vertically integrated into a smart transmission grid. A comparative analysis in the model, development, benefits and risks of the implementation of these systems, between two of the main marc of references of smart grids, the EU and the USA is presented

Fluid--Gravity Correspondence under the presence of viscosity

The present work addresses the analogy between the speed of sound of a viscous, barotropic, and irrotational fluid and the equation of motion for a non--massive field in a curved manifold. It will be shown that the presence of viscosity implies the introduction, into the equation of motion of the gravitational analogue, of a source term which entails the flow of energy from the non--massive field to the curvature of the spacetime manifold. The stress-energy tensor is also computed and it is found not to be constant, which is consistent with such energy interchange