Spatio-temporal modeling of infectious diseases by integrating compartment and point process models

Infectious disease modeling plays an important role in understanding disease spreading dynamics and can be used for prevention and control. The well-known SIR (Susceptible, Infected, and Recovered) compartment model and spatial and spatio-temporal statistical models are common choices for studying problems of this kind. This paper proposes a spatio-temporal modeling framework to characterize infectious disease dynamics by integrating the SIR compartment and log-Gaussian Cox process (LGCP) models. The method’s performance is assessed via simulation using a combination of real and synthetic data for a region in São Paulo, Brazil. We also apply our modeling approach to analyze COVID-19 dynamics in Cali, Colombia. The results show that our modified LGCP model, which takes advantage of information obtained from the previous SIR modeling step, leads to a better forecasting performance than equivalent models that do not do that. Finally, the proposed method also allows the incorporation of age-stratified contact information, which provides valuable decision-making insights

Bound states of scalar particles in the presence of a short range potential

We analyze the behavior of the energy spectrum of the Klein-Gordon equation in the presence of a truncated hyperbolic tangent potential. From our analysis we obtain that, for some values of the potential there is embedding of the bound states into the negative energy continuum, showing that, in opposition to the general belief, relativistic scalar particles in one-dimensional short range potentials can exhibit resonant behavior and not only the Schiff-Snyder effect.Comment: To appear in Modern Physics Letters

Proyecto para la creación de una empresa de confección de camisetas a base de algodón orgánico en la ciudad de Guayaquil

Este documento presenta un análisis de viabilidad y factibilidad de implantar una fábrica que confeccione camisetas en la ciudad de Guayaquil y muestra el plan de negocios para esta empresa. Para esto se realizó un análisis del sector textil e investigación de mercados para identificar estrategias y acciones a seguir. La investigación incluyó a compradores en centros comerciales y competencia en el mercado. En base a la investigación sectorial y a resultados del análisis de la investigación se llegó a la conclusión que el proyecto es totalmente viable; debido a que hay una gran disposición ecologista de la gente y que estarían dispuestos a comprar, y es también factible; porque a través de la aplicación de estrategia de nicho de mercado y diferentes tácticas, la fábrica logrará participación de mercado y sobre todo alta rentabilidad.FEN-ESPO

Voltage control of frequency, effective damping and threshold current in nano-constriction-based spin Hall nano-oscillators

Using micromagnetic simulations, we study the interplay between strongly voltage-controlled magnetic anisotropy (VCMA), $\Delta K = \pm$200 kJ/m$^3$, and gate width, $w=$ 10--400 nm, in voltage-gated W/CoFeB/MgO based nano-constriction spin Hall nano-oscillators. The VCMA modifies the local magnetic properties such that the magnetodynamics transitions between regimes of \emph{i}) confinement, \emph{ii}) tuning, and \emph{iii}) separation, with qualitatively different behavior. We find that the strongest tuning is achieved for gate widths of the same size as the the constriction width, for which the effective damping can be increased an order of magnitude compared to its intrinsic value. As a consequence, voltage control remains efficient over a very large frequency range, and subsequent manufacturing advances could allow SHNOs to be easily integrated into next-generation electronics for further fundamental studies and industrial applications

“proyecto para la implementación de plantación de flores tropicales para la exportación y comercialización interna mediante página web”

El proyecto se trata del establecimiento de una plantación de 8 hectáreas de flores tropicales específicamente Heliconias y Gingers, la misma que estará ubicada en el cantón Santo Domingo de los Colorados perteneciente a la provincia de Santo Domingo de los Tsáchilas, Ecuador. La ciudad es conocida por poseer un clima tropical húmedo, óptimo para este tipo de cultivos. La producción en su totalidad será exportada directamente hacia los países de destino para ingresar con un precio más competitivo ya que no se utilizarán intermediarios. Las flores de segunda se destinarán al mercado interno, las que se comercializarán mediante una página web con arreglos florales elaborados. El proyecto conlleva el establecimiento de la plantación, esto incluye la adquisición del terreno, maquinarias, insumos, recurso humano y capital y la comercialización del producto. Los productos que ofreceremos serán flores exóticas de la familia de las Heliconias y Gingers caracterizados por sus formas atractivas y colores peculiares con una calidad muy alta y producida bajo buenas prácticas agrícolas y aplicando avances tecnológicos reduciendo al máximo los riesgos de contaminación y agilizando los procesos. Nuestro mercado objetivo será Estados Unidos principalmente el estado de La Florida. Cabe recalcar que el proyecto tendrá un impacto social positivo en zona ya que para su operación demanda mano de obra directa e indirecta de hombres y mujeres campesinos de entre 18 y 35 años

Separation of Stellar Populations by an Evolving Bar: Implications for the Bulge of the Milky Way

We present a novel interpretation of the previously puzzling different behaviours of stellar populations of the Milky Way’s bulge. We first show, by means of pure N - body simulations, that initially co-spatial stellar populations with different in-plane random motions separate when a bar forms. The radially cooler populations form a strong bar, and are vertically thin and peanut-shaped, while the hotter populations form a weaker bar and become a vertically thicker box. We demonstrate that it is the radial, not the vertical, velocity dispersion that dominates this evolution. As- suming that early stellar discs heat rapidly as they form, then both the in-plane and vertical random motions correlate with stellar age and chemistry, leading to different density distributions for metal-rich and metal-poor stars. We then use a high resolu- tion simulation, in which all stars form out of gas, to demonstrate that this is what happens. When we apply these results to the Milky Way we show that a very broad range of observed trends for ages, densities, kinematics, and chemistries, that have been presented as evidence for contradictory paths to the formation of the bulge, are in fact consistent with a bulge which formed from a continuum of disc stellar popu- lations which were kinematically separated by the bar. For the first time we are able to account for the bulge’s main trends via a model in which the bulge formed largely in situ. Since the model is generic, we also predict the general appearance of stellar population maps of external edge-on galaxies

Partition Quantitative Assessment (PQA): A quantitative methodology to assess the embedded noise in clustered omics and systems biology data

Identifying groups that share common features among datasets through clustering analysis is a typical problem in many fields of science, particularly in post-omics and systems biology research. In respect of this, quantifying how a measure can cluster or organize intrinsic groups is important since currently there is no statistical evaluation of how ordered is, or how much noise is embedded in the resulting clustered vector. Many of the literature focuses on how well the clustering algorithm orders the data, with several measures regarding external and internal statistical measures; but none measure has been developed to statistically quantify the noise in an arranged vector posterior a clustering algorithm, i.e., how much of the clustering is due to randomness. Here, we present a quantitative methodology, based on autocorrelation, to assess this problem.Comment: 9 pages, 6 figure

A little garbage in, lots of garbage out: Assessing the impact of careless responding in personality survey data

[EN]In self-report surveys, it is common that some individuals do not pay enough attention and effort to give valid responses. Our aim was to investigate the extent to which careless and insufficient effort responding contributes to the biasing of data.We performed analyses of dimensionality, internal structure, and data reliability of four personality scales (extroversion, conscientiousness, stability, and dispositional optimism) in two independent samples. In order to identify careless/insufficient effort (C/IE) respondents, we used a factor mixture model (FMM) designed to detect inconsistencies of response to items with different semantic polarity. The FMM identified between 4.4% and 10% of C/IE cases, depending on the scale and the sample examined. In the complete samples, all the theoretical models obtained an unacceptable fit, forcing the rejection of the starting hypothesis and making additional wording factors necessary. In the clean samples, all the theoretical models fitted satisfactorily, and the wording factors practically disappeared. Trait estimates in the clean samples were between 4.5% and 11.8% more accurate than in the complete samples. These results show that a limited amount of C/IE data can lead to a drastic deterioration in the fit of the theoretical model, produce large amounts of spurious variance, raise serious doubts about the dimensionality and internal structure of the data, and reduce the reliability with which the trait scores of all surveyed are estimated. Identifying and filtering C/IE responses is necessary to ensure the validity of research result

CloudBench: an integrated evaluation of VM placement algorithms in clouds

A complex and important task in the cloud resource management is the efficient allocation of virtual machines (VMs), or containers, in physical machines (PMs). The evaluation of VM placement techniques in real-world clouds can be tedious, complex and time-consuming. This situation has motivated an increasing use of cloud simulators that facilitate this type of evaluations. However, most of the reported VM placement techniques based on simulations have been evaluated taking into account one specific cloud resource (e.g., CPU), whereas values often unrealistic are assumed for other resources (e.g., RAM, awaiting times, application workloads, etc.). This situation generates uncertainty, discouraging their implementations in real-world clouds. This paper introduces CloudBench, a methodology to facilitate the evaluation and deployment of VM placement strategies in private clouds. CloudBench considers the integration of a cloud simulator with a real-world private cloud. Two main tools were developed to support this methodology, a specialized multi-resource cloud simulator (CloudBalanSim), which is in charge of evaluating VM placement techniques, and a distributed resource manager (Balancer), which deploys and tests in a real-world private cloud the best VM placement configurations that satisfied user requirements defined in the simulator. Both tools generate feedback information, from the evaluation scenarios and their obtained results, which is used as a learning asset to carry out intelligent and faster evaluations. The experiments implemented with the CloudBench methodology showed encouraging results as a new strategy to evaluate and deploy VM placement algorithms in the cloud.This work was partially funded by the Spanish Ministry of Economy, Industry and Competitiveness under the Grant TIN2016-79637-P “Towards Unifcation of HPC and Big Data Paradigms” and by the Mexican Council of Science and Technology (CONACYT) through a Ph.D. Grant (No. 212677)