On the Use of Complexity Algorithms: a Cautionary Lesson from Climate Research

Complexity algorithms provide information about datasets which is radically different from classical moment statistics. Instead of focusing on the divergences from central values, they quantify other characteristics such as order, pattern repetitions, or the existence of attractors. However, those analyses must be done with the proper statistical treatment, which is, unfortunately, not always the case. In this contribution, I provide an example of the hazards of applying complexity measures without sufficient care by correcting a previously published analysis that aimed to quantify the complexity of climate. I clarify some misconceptions about the use of Sample Entropy and revise the incorrect assessments and conclusions drawn from the previous misapplication of the methods

Thermodynamics and life Past, Present and Future of the use of energy by living beings

[EN] Life emerged on Earth more than 3.5 Gyr ago and it has been using energy ever since. The purpose of this thesis is to study several aspects of the relationship between energy and life. First, I start with the analysis of the nitrogen requirements of life in the Early Earth, and conclude that life was not able to produce enough biological nitrogen by itself, meaning that other sources of energy were required by the time. In the course of evolution, life developed the ability to use the solar energy that reached the surface of our planet, and its use modified not only the evolution of the living beings but also the evolution of the atmosphere. The changes in the atmosphere were followed by changes in the maximum efficiency in the energy obtainable from solar radiation. On a different aspect, it is believed that Mars was inside the so-called habitable zone once, where liquid water exists and the conditions are suitable for life, but now the environment is dry and harsh. Despite the fact that we have not found life so far in the planet, a biosphere might be living beneath the regolith and chemolithotrophic organisms could be using chemical energy to survive in the current martian environment. I analyse the energetic features of the present day near-surface martian atmosphere using the state-of-the-art knowledge of the thermodynamic variables nowadays, provided by rovers and satellites. As many of those spacecrafts are powered with solar energy, the knowledge of the maximum obtainable work of solar cells in the environment of Mars is extremely important for the future of exploration and colonization of the planet. I provide clues on the maximum efficiency of solar radiation in the planet under different conditions

Approximate Entropy and Sample Entropy: A Comprehensive Tutorial

Approximate Entropy and Sample Entropy are two algorithms for determining the regularity of series of data based on the existence of patterns. Despite their similarities, the theoretical ideas behind those techniques are different but usually ignored. This paper aims to be a complete guideline of the theory and application of the algorithms, intended to explain their characteristics in detail to researchers from different fields. While initially developed for physiological applications, both algorithms have been used in other fields such as medicine, telecommunications, economics or Earth sciences. In this paper, we explain the theoretical aspects involving Information Theory and Chaos Theory, provide simple source codes for their computation, and illustrate the techniques with a step by step example of how to use the algorithms properly. This paper is not intended to be an exhaustive review of all previous applications of the algorithms but rather a comprehensive tutorial where no previous knowledge isrequired to understand the methodology

Human vision is determined based on information theory

Acknowledgements A.D.-B. wants to acknowledge to the Energy research program of Fundación Iberdrola España for the 2015 Fellowship award which partially funded this investigation.Peer reviewedPublisher PD

Effect of scattering angle on Earth reflectance

After March 2020 the range of scattering angle for DSCOVR EPIC and NISTAR has been substantially increased with its upper bound reaching 178°. This provides a unique opportunity to observe bi-directional effects of reflectance near backscattering directions. The dependence of the top-of-atmosphere (TOA) reflectance on scattering angle is shown separately for ocean and land areas, for cloudy and clear pixels, while cloudy pixels are also separated into liquid and ice clouds. A strong increase of TOA reflectance towards backscattering direction is reported for all components (except cloudless areas over ocean). The observed increase of reflectance is confirmed by cloud and vegetation models. The strongest correlation between TOA reflectance and scattering angle was found near IR where contribution from vegetation dominates. Surface Bidirectional Reflectance Factor (BRF) acquired by DSCOVR EPIC and Terra MISR sensors over the Amazon basin is used to demonstrate the bi-directional effects of solar zenith and scattering angles on variation of reflected radiation from rainforest.Published versio

Cloud Height Daytime Variability From DSCOVR/EPIC and GOES-R/ABI Observations

One of the largest uncertainties in climate sensitivity predictions is the influence of clouds. While some aspects of cloud formation and evolution are well understood, others such as the diurnal variability of their heights remains largely unexplored at global scales. Aiming to fill that fundamental gap in cloud knowledge, this paper studies the daytime evolution of cloud top height using the EPIC instrument aboard the DSCOVR satellite, complemented by coincident cloud height retrievals by GOES-R’s ABI instrument. Both datasets indicate that cloud height exhibits a minimum around midday for low clouds with amplitudes between 250 and 600 m depending on the season. The two datasets also agree that high clouds exhibit a contrasting behavior with steady increase of cloud height from morning to evening. We investigate dependences on the type of underlying surface, finding that the amplitude of the diurnal cycles is weaker over ocean than over land for both EPIC and ABI retrievals. We also find a positive correlation between cloud fraction and height over ocean which turns negative over land for low clouds, while for high clouds the correlation is largely positive

Phase angle and the estimation of Earth reflectance

First author draf

Real-time motion detection by lateral inhibition in accumulative computation.

Many researchers have explored the relationship between recurrent neural networks and finite state machines. Finite state machines constitute the best characterized computational model, whereas artificial neural networks have become a very successful tool for modeling and problem solving. In the few last years, the neurally inspired lateral inhibition in accumulative computation (LIAC) method and its application to the motion detection task have been introduced. The article shows how to implement the tasks directly related to LIAC in motion detection by means of a formal model described as finite state machines. This paper introduces two steps towards that direction: (a) A simplification of the general LIAC method is performed by formally transforming it into a finite state machine. (b) A hardware implementation of such a designed LIAC module, as well as an 8×8 LIAC module, has been tested on several video sequences, providing promising performance results

A historical perspective of algorithmic lateral inhibition and accumulative computation in computer vision

Certainly, one of the prominent ideas of Professor José Mira was that it is absolutely mandatory to specify the mechanisms and/or processes underlying each task and inference mentioned in an architecture in order to make operational that architecture. The conjecture of the last fifteen years of joint research has been that any bottom-up organization may be made operational using two biologically inspired methods called ?algorithmic lateral inhibition?, a generalization of lateral inhibition anatomical circuits, and ?accumulative computation?, a working memory related to the temporal evolution of the membrane potential. This paper is dedicated to the computational formulation of both methods. Finally, all of the works of our group related to this methodological approximation are mentioned and summarized, showing that all of them support the validity of this approximation

Neurally inspired mechanisms of the dynamic visual attention map generation task

A model for dynamic visual attention is briefly introduced in this paper. A PSM (problem-solving method) for a generic ?Dynamic Attention Map Generation? task to obtain a Dynamic Attention Map from a dynamic scene is proposed. Our approach enables tracking objects that keep attention in accordance with a set of characteristics defined by the observer. This paper mainly focuses on those subtasks of the model inspired in neuronal mechanisms, such as accumulative computation and lateral interaction. The subtasks which incorporate these biologically plausible capacities are called ?Working Memory Generation? and ?Thresholded Permanency Calculation?