Inferring the particle-wise dynamics of amorphous solids from the local structure at the jamming point

Jamming is a phenomenon shared by a wide variety of systems, such as granular materials, foams, and glasses in their high density regime. This has motivated the development of a theoretical framework capable of explaining many of their static critical properties with a unified approach. However the dynamics occurring in the vicinity of the jamming point has received little attention and the problem of finding a connection with the local structure of the configuration remains unexplored. Here we address this issue by constructing physically well defined structural variables using the information contained in the network of contacts of jammed configurations, and then showing that such variables yield a resilient statistical description of the particle-wise dynamics near this critical point. Our results are based on extensive numerical simulations of systems of spherical particles that allow us to statistically characterize the trajectories of individual particles in terms of their first two moments. We first demonstrate that, besides displaying a broad distribution of mobilities, particles may also have preferential directions of motion. Next, we associate each of these features with a structural variable computed uniquely in terms of the contact vectors at jamming, obtaining considerably high statistical correlations. The robustness of our approach is confirmed by testing two types of dynamical protocols, namely Molecular Dynamics and Monte Carlo, with different types of interaction. We also provide evidence that the dynamical regime we study here is dominated by anharmonic effects and therefore it cannot be described properly in terms of vibrational modes. Finally, we show that correlations decay slowly and in an interaction-independent fashion, suggesting a universal rate of information loss.Comment: Same as published version; better figures placemen

Non-convex image reconstruction via Expectation Propagation

Tomographic image reconstruction can be mapped to a problem of finding solutions to a large system of linear equations which maximize a function that includes \textit{a priori} knowledge regarding features of typical images such as smoothness or sharpness. This maximization can be performed with standard local optimization tools when the function is concave, but it is generally intractable for realistic priors, which are non-concave. We introduce a new method to reconstruct images obtained from Radon projections by using Expectation Propagation, which allows us to reframe the problem from an Bayesian inference perspective. We show, by means of extensive simulations, that, compared to state-of-the-art algorithms for this task, Expectation Propagation paired with very simple but non log-concave priors, is often able to reconstruct images up to a smaller error while using a lower amount of information per pixel. We provide estimates for the critical rate of information per pixel above which recovery is error-free by means of simulations on ensembles of phantom and real images.Comment: 12 pages, 6 figure

Improving randomness characterization through Bayesian model selection

Nowadays random number generation plays an essential role in technology with important applications in areas ranging from cryptography, which lies at the core of current communication protocols, to Monte Carlo methods, and other probabilistic algorithms. In this context, a crucial scientific endeavour is to develop effective methods that allow the characterization of random number generators. However, commonly employed methods either lack formality (e.g. the NIST test suite), or are inapplicable in principle (e.g. the characterization derived from the Algorithmic Theory of Information (ATI)). In this letter we present a novel method based on Bayesian model selection, which is both rigorous and effective, for characterizing randomness in a bit sequence. We derive analytic expressions for a model's likelihood which is then used to compute its posterior probability distribution. Our method proves to be more rigorous than NIST's suite and the Borel-Normality criterion and its implementation is straightforward. We have applied our method to an experimental device based on the process of spontaneous parametric downconversion, implemented in our laboratory, to confirm that it behaves as a genuine quantum random number generator (QRNG). As our approach relies on Bayesian inference, which entails model generalizability, our scheme transcends individual sequence analysis, leading to a characterization of the source of the random sequences itself.Comment: 25 page

Finite size effects in the microscopic critical properties of jammed configurations: a comprehensive study of the effects of different types of disorder

Jamming criticality defines a universality class that includes systems as diverse as glasses, colloids, foams, amorphous solids, constraint satisfaction problems, neural networks, etc. A peculiarly interesting feature of this class is that small interparticle forces ($f$) and gaps ($h$) are distributed according to non-trivial power laws. A recently developed mean-field (MF) theory predicts the characteristic exponents of these distributions in the limit of very high spatial dimension, $d ightarrowinfty$ and, remarkably, their values seemingly agree with numerical estimates in physically relevant dimensions, $d=2$ and $3$. These exponents are further connected through a pair of inequalities derived from stability conditions, and both theoretical predictions and previous numerical investigations suggest that these inequalities are saturated. Systems at the jamming point are thus only marginally stable. Despite the key physical role played by these exponents, their systematic evaluation has remained elusive. Here, we carefully test their value by analyzing the finite-size scaling of the distributions of $f$ and $h$ for various particle-based models for jamming. Both the dimension and the direction of approach to the jamming point are also considered. We show that, in all models, finite-size effects are much more pronounced in the distribution of $h$ than in that of $f$. We thus conclude that gaps are correlated over considerably longer scales than forces. Additionally, remarkable agreement with MF predictions is obtained in all but one model, near-crystalline packings. Our results thus help to better delineate the domain of the jamming universality class. We furthermore uncover a secondary linear regime in the distribution tails of both $f$ and $h$. This surprisingly robust feature is thought to follow from the (near) isostaticity of our configurations

El COVID-19 y el sistema tributario en los Estados Unidos de América del Norte

Since David Ricardo, taxation has been considered the main concern for the evolution of the economy, prices and long-term income. Given this, the article analyzes the state of the North American tax system based on the reforms introduced in the framework of the pandemic caused by COVID-19 in 2020. To do this, the reforms of the Trump and Biden governments are considered, which are presented in the period 2018-20221 to face the collateral damage of the North American and international economy. In this sense, the Trump government’s position of protectionism and economic warfare, the COVID-19 pandemic, the shortage of international markets and the recovery measures introduced in the change of government by President Biden are considered. Finally, the article presents how these reforms not only face the COVID-19 contingency but also mark the economic-political line of Republicans and Democrats in the United States of America.Desde David Ricardo la tributación se ha considerado la principal preocupación para la evolución de la economía, los precios y las rentas a largo plazo. Ante ello, el artículo analiza el estado del sistema tributario norteamericano a partir de las reformas introducidas en el marco de la pandemia ocasionada por el COVID-19 en el año 2020, para lo cual se tienen en cuenta las reformas de los gobiernos Trump y Biden en el periodo 2018-2021 para hacer frente a los daños colaterales de la economía norteamericana e internacional. En ese sentido, se tienen en cuanta la postura de proteccionismo y guerra económica del gobierno Trump, la pandemia del COVID-19, el desabastecimiento de los mercados internacionales y las medidas de recuperación introducidas en el gobierno del presidente Biden. Finalmente, el artículo hace hincapié en que dichas reformas no sólo buscan enfrentar la contingencia del COVID-19 sino que marcan la línea económico-política de republicanos y demócratas en los Estados Unidos de América

Calidad de la leche de vaca en una zona de riego del estado de Puebla

El objetivo fue determinar la calidad de la leche cruda en base a su composición y a la posible contaminación con metales pesados por la ingestión de alfalfa (Medicago sativa) cultivada en suelos que son irrigados con aguas del canal de riego de Valsequillo en el estado de Puebla. Se muestrearon suelo agrícola, alfalfa y 136 vacas de las cuales se tomaron dos muestras de leche directamente de la ubre, siendo una muestra para calidad en cuanto a su composición y la otra para contenido de metales pesados  (Cd,  Pb,  Cr  y  Zn).  Para  el  análisis  estadístico  se  utilizó  un  GLM  mediante  el  paquete estadístico  SAS.  En  este  trabajo  de  encontró  diferencia  p Cr> Zn> Cd, (38; 31.38; 22.78: 2 mg kg-1), seguida de la planta, que tuvo niveles altos. En relación a la leche la concentración promedio obtenida de Pb fue 0.13 mg kg-1. Además de encontrar niveles considerables de Cd, Cr y Zn. En relación la composición de la leche no existió p>0.05 entre el tipo de productores, siendo de manera general una leche con bajo porcentaje en grasa. Por tanto se concluye que la leche producida en la región de estudio presenta baja calidad en cuanto a su contenido y considerable nivel de contaminación con metales pesados lo que representa un riesgo para la salud de sus consumidores

Tissue culture of ornamental cacti

Cacti species are plants that are well adapted to growing in arid and semiarid regions where the main problem is water availability. Cacti have developed a series of adaptations to cope with water scarcity, such as reduced leaf surface via morphological modifications including spines, cereous cuticles, extended root systems and stem tissue modifications to increase water storage, and crassulacean acid metabolism to reduce transpiration and water loss. Furthermore, seeds of these plants very often exhibit dormancy, a phenomenon that helps to prevent germination when the availability of water is reduced. In general, cactus species exhibit a low growth rate that makes their rapid propagation difficult. Cacti are much appreciated as ornamental plants due to their great variety and diversity of forms and their beautiful short-life flowers; however, due to difficulties in propagating them rapidly to meet market demand, they are very often over-collected in their natural habitats, which leads to numerous species being threatened, endangered or becoming extinct. Therefore, plant tissue culture techniques may facilitate their propagation over a shorter time period than conventional techniques used for commercial purposes; or may help to recover populations of endangered or threatened species for their re-introduction in the wild; or may also be of value to the preservation and conservation of the genetic resources of this important family. Herein we present the state-of-the-art of tissue culture techniques used for ornamental cacti and selected suggestions for solving a number of the problems faced by members of the Cactaceae family