Detection of time reversibility in time series by ordinal patterns analysis

Time irreversibility is a common signature of nonlinear processes, and a fundamental property of non-equilibrium systems driven by non-conservative forces. A time series is said to be reversible if its statistical properties are invariant regardless of the direction of time. Here we propose the Time Reversibility from Ordinal Patterns method (TiROP) to assess time-reversibility from an observed finite time series. TiROP captures the information of scalar observations in time forward, as well as its time-reversed counterpart by means of ordinal patterns. The method compares both underlying information contents by quantifying its (dis)-similarity via Jensen-Shannon divergence. The statistic is contrasted with a population of divergences coming from a set of surrogates to unveil the temporal nature and its involved time scales. We tested TiROP in different synthetic and real, linear and non linear time series, juxtaposed with results from the classical Ramsey's time reversibility test. Our results depict a novel, fast-computation, and fully data-driven methodology to assess time-reversibility at different time scales with no further assumptions over data. This approach adds new insights about the current non-linear analysis techniques, and also could shed light on determining new physiological biomarkers of high reliability and computational efficiency.Comment: 8 pages, 5 figures, 1 tabl

Bioagent defeat in shock driven gas flow

The problem of planar shock interaction with gas cylinders whose axis of symmetry is parallel to the plane of the shock has been well studied both experimentally and numerically, and in this case, the flow evolution driven by Richtmyer-Meshkov instability is well characterized (although, as this thesis shows, assumptions commonly made about the experimental conditions need to be carefully checked). However, for a similar oblique interaction, with the plane of the shock and the axis of the density interface being non-parallel, presently only numerical results exist. The problem of oblique shock interaction is quite interesting to study experimentally both because of a variety of relevant applications and because it adds large-scale three-dimensionality to the initial conditions. Additionally, there is a considerable interest in the problem of shock interaction with particulates, droplets, and bioagents suspended in gas. Here we describe an experimental arrangement for the studies of planar and oblique shocks and present some preliminary results

The Innocent Can Still Be Found Guilty

Wrongful convictions target specific groups of people within society in the U.S. The criminal justice and court systems are heavily influenced by the racial biases that surround their integral processes when it comes to convicting citizens of their accused crimes. African American men are heavily targeted when it comes to being convicted of a violent crime that they did not commit, when compared to that of white males. These racial biases can be viewed through careful observation of prior research and shows how these biases have been ingrained within the training police officers undergo. It is also evident that these biases are seemingly present in the minds of victims of violent crimes. As racial stereotypes obscure their sense of judgment when it comes to identifying the perpetrator of the crime from a group of people in a lineup. A lineup is a method of identification that is used in order to help victims identify the offender from a group of people who have been arrested and match a similar description. Statistics on the groups of people that are wrongfully convicted are analyzed, as well as cases that involve the use of different kinds of evidence which have led to wrongful convictions. The systems in place that are meant to fairly convict offenders of their crimes are heavily flawed and outdated as statistics clearly outline the margins of error included within every wrongful conviction that is made. These findings may also suggest which racial group is targeted the most when it comes to being wrongfully convicted as a result of errors created from these flawed systems. Changes in policies such as making it mandatory for investigators to film interrogation, could reduce the rate of wrongful convictions. However, the enforcement of policy changes can be ignored by those in power, in order to reap the underlying benefits that come with a wrongful conviction. Key Words: wrongful convictions, evidence, racial biases, eyewitness, policy, exonerate, racial stereotypes&nbsp

Non-parametric resampling of random walks for spectral network clustering

Parametric resampling schemes have been recently introduced in complex network analysis with the aim of assessing the statistical significance of graph clustering and the robustness of community partitions. We propose here a method to replicate structural features of complex networks based on the non-parametric resampling of the transition matrix associated with an unbiased random walk on the graph. We test this bootstrapping technique on synthetic and real-world modular networks and we show that the ensemble of replicates obtained through resampling can be used to improve the performance of standard spectral algorithms for community detection.Comment: 5 pages, 2 figure

Graph analysis of functional brain networks: practical issues in translational neuroscience

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires a know-how of all the methodological steps of the processing pipeline that manipulates the input brain signals and extract the functional network properties. On the other hand, a knowledge of the neural phenomenon under study is required to perform physiological-relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes