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Entropy magazine11/28/2023 ![]() ![]() The existence of specific finite moments is closely related to the concept of a tail index, and its estimation is one of key problems in statistics. But, when the data are collected by a heavy-tailed distribution, the mathematical bases of the usual statistics is not satisfied. Indeed, the usual statistical approach is based on the Kolmogorov's law of large numbers which requires the existence of the first finite moment, and the Lyapunov's version of the central limit theorem assumes an existence of the finite moment of an order higher than two. Scientists and engineers have always searched for the best statistical distribution useful to predict the behavior of the systems under consideration. However, especially in the beginning of any epidemics we have only partial access to validated data also because the number of infected people is still rather small and follows a dynamic process. Traditionally, epidemiological analyses are based on sigmoidal models, which indeed are useful if the evolution of the epidemics follows well-established patterns. Consequently, it is fundamental to develop a reliable analytical approach that allows such predictive modeling. To implement effective public health measures in a timely manner and allocate scarce resources according to geographic need, it is very important to forecast the diffusion or spread of the infection amongst the population. Consequently, the interest in forecasting the diffusion of such global infectious disease threats is continuously increasing. Moreover, epidemics and pandemics can cause also significant, widespread economic hardship and potentially lead to social unrest. Some recent examples of pandemics are the 2003 SARS (Severe Acute Respiratory Syndrome), the 2014 West Africa Ebola epidemic, and the present COVID-19 caused by the coronavirus SARS-Cov-2. Indeed, epidemics can occur in a community or region by causing illness in excess of normal expectancy pandemics are no more than a large-scale global epidemic which determine a growth in morbidity and mortality over a wide geographic area. This is particularly true in epidemiology. Consequently, in any field of research, scientists, and engineers have always taken attention to find the best statistical distribution to predict the systems behavior. It’s pulp sci-fi done so right.In the natural, social, economic, and physical sciences a large variety of phenomena are characterized by regularities, which can be analytically described by a defined statistical distribution. This gorgeous, 16-issue omnibus publishes just in time for Christmas shopping, and I strongly encourage you to pick this up for yourself or for the comic geek who’s close to your heart. Honestly, I can’t praise Black Science enough. Every panel impresses and captivates with its brilliant hues, fanciful creatures, thought-provoking dialogue and gut-wrenching loss. Matteo Scalera and Dean White illustrate something truly stunning here, and I can’t wait to see what follows. However, what transpires is nowhere near what he expected: Grant, his children and his colleagues are stranded in constantly changing dimensions with no easy answers and no clear villain-just more questions. The easiest way to describe Black Science is “ Lost in Space with anarchist scientists.” Grant McKay, a former member of the Anarchist Order of Scientists and current shitty husband/father, creates a device known as the Pillar to travel through an infinite variety of dimensions with the intention of improving the quality of life within each one. While working at Black Cat Comics in Sugar House, it seemed that every hour I had at least one patron asking this same question or some form of it: “What’s your favorite book out right now?” My answer was always the same: Black Science. Black Science: The Beginners’ Guide to Entropy Image Comics ![]()
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