Inequality, a scourge of the XXI century

Social and economic inequality is a plague of the XXI Century. It is continuously widening, as the wealth of a relatively small group increases and, therefore, the rest of the world shares a shrinking fraction of resources. This situation has been predicted and denounced by economists and econophysicists. The latter ones have widely used models of market dynamics which consider that wealth distribution is the result of wealth exchanges among economic agents. A simple analogy relates the wealth in a society with the kinetic energy of the molecules in a gas, and the trade between agents to the energy exchange between the molecules during collisions. However, while in physical systems, thanks to the equipartition of energy, the gas eventually arrives at an equilibrium state, in many exchange models the economic system never equilibrates. Instead, it moves toward a "condensed" state, where one or a few agents concentrate all the wealth of the society and the rest of agents shares zero or a very small fraction of the total wealth. Here we discuss two ways of avoiding the "condensed" state. On one hand, we consider a regulatory policy that favors the poorest agent in the exchanges, thus increasing the probability that the wealth goes from the richest to the poorest agent. On the other hand, we study a tax system and its effects on wealth distribution. We compare the redistribution processes and conclude that complete control of the inequalities can be attained with simple regulations or interventions

A concentração de riqueza em sistemas de trocas binárias não enviesadas

Buscando explicar a crescente concentração de riqueza no mundo, diversos modelos supõem a existência de um viés favorecendo os mais ricos que provoca tal efeito. Modelos inspirados na física estatística dos gases, onde agentes econômicos são selecionados sequencial e aleatoriamente para efetuarem uma troca binária de riqueza, porém, mostram que dinâmicas não-viesadas, que não privilegiam nem pobres nem ricos, podem elas mesmas produzir um viés, aumentando a desigualdade inde nidamente até chegar a uma situação onde um indivíduo concentra toda a riqueza disponível. Além disso, o sistema está sempre fora de equilíbrio até que a desigualdade perfeita do estado nal seja atingida, com o m do uxo de riqueza. Esses resultados indicam que um mercado imparcial, dentro da hipótese de um mercado e ciente sem arbitragem, pode ser responsável por uma concentração extrema de riqueza. Ainda não existe, porém, uma prova geral de que qualquer dinâmica de trocas binárias não-viesadas leva inevitavelmente ao aumento de desigualdade e a diminuição de mobilidade. Buscando cobrir essa lacuna na teoria da econofísica, será apresentada uma demonstração analítica simples, mas rigorosa, de que qualquer regra não-viesada está condenada a conduzir o sistema à desigualdade perfeita.Seeking to explain the growing concentration of wealth in the world, several models postulate the existence of a bias favoring the richest causing this e ect. Models inspired by the statistical physics of gases, where economic agents are selected sequentially and randomly to e ect a binary exchange of wealth, however, show that non-biased dynamics, which favor neither the poor nor the rich, can themselves produce a bias, increasing inequality inde nitely until reaching a situation where one individual concentrates all the available wealth. In addition, the system is always out of balance until the perfect inequality of the nal state is reached, with the ow of wealth. These results indicate that a balanced market, within the assumption of e cient market and without arbitrage, may be responsible for an extreme concentration of wealth. However, there is still no general proof that any dynamic of biased binary exchanges inevitably leads to an increase in inequality and decreased mobility. Seeking to ll this gap in the theory of econophysics, we show here a simple but rigorous analytical demonstration that any unbiased rule is doomed to lead the system to perfect inequality

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Uso de curvas de remanência e de FORC na análise de interações magnéticas em sistemas nanoestruturados

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A concentração de riqueza em sistemas de trocas binárias não enviesadas

Buscando explicar a crescente concentração de riqueza no mundo, diversos modelos supõem a existência de um viés favorecendo os mais ricos que provoca tal efeito. Modelos inspirados na física estatística dos gases, onde agentes econômicos são selecionados sequencial e aleatoriamente para efetuarem uma troca binária de riqueza, porém, mostram que dinâmicas não-viesadas, que não privilegiam nem pobres nem ricos, podem elas mesmas produzir um viés, aumentando a desigualdade inde nidamente até chegar a uma situação onde um indivíduo concentra toda a riqueza disponível. Além disso, o sistema está sempre fora de equilíbrio até que a desigualdade perfeita do estado nal seja atingida, com o m do uxo de riqueza. Esses resultados indicam que um mercado imparcial, dentro da hipótese de um mercado e ciente sem arbitragem, pode ser responsável por uma concentração extrema de riqueza. Ainda não existe, porém, uma prova geral de que qualquer dinâmica de trocas binárias não-viesadas leva inevitavelmente ao aumento de desigualdade e a diminuição de mobilidade. Buscando cobrir essa lacuna na teoria da econofísica, será apresentada uma demonstração analítica simples, mas rigorosa, de que qualquer regra não-viesada está condenada a conduzir o sistema à desigualdade perfeita.Seeking to explain the growing concentration of wealth in the world, several models postulate the existence of a bias favoring the richest causing this e ect. Models inspired by the statistical physics of gases, where economic agents are selected sequentially and randomly to e ect a binary exchange of wealth, however, show that non-biased dynamics, which favor neither the poor nor the rich, can themselves produce a bias, increasing inequality inde nitely until reaching a situation where one individual concentrates all the available wealth. In addition, the system is always out of balance until the perfect inequality of the nal state is reached, with the ow of wealth. These results indicate that a balanced market, within the assumption of e cient market and without arbitrage, may be responsible for an extreme concentration of wealth. However, there is still no general proof that any dynamic of biased binary exchanges inevitably leads to an increase in inequality and decreased mobility. Seeking to ll this gap in the theory of econophysics, we show here a simple but rigorous analytical demonstration that any unbiased rule is doomed to lead the system to perfect inequality