Food for Thought Integrating population genomics and biophysical models towards evolutionary-based fisheries management

Overfishing and rapid environmental shifts pose severe challenges to the resilience and viability of marine fish populations. To develop and implement measures that enhance species’ adaptive potential to cope with those pressures while, at the same time, ensuring sustainable exploitation rates is part of the central goal of fisheries management. Here, we argue that a combination of biophysical modelling and population genomic assessments offer ideal management tools to define stocks, their physical connectivity and ultimately, their short-term adaptive potential. To date, biophysical modelling has often been confined to fisheries ecology whereas evolutionary hypotheses remain rarely considered. When identified, connectivity patterns are seldom explored to understand the evolution and distribution of adaptive genetic variation, a proxy for species’ evolutionary potential. Here, we describe a framework that expands on the conventional seascape genetics approach by using biophysical modelling and population genomics. The goals are to identify connectivity patterns and selective pressures, as well as putative adaptive variants directly responding to the selective pressures and, ultimately, link both to define testable hypotheses over species response to shifting ecological conditions and overexploitation

Utilização do pH e TRH como estratégia operacional para geração de nitrito.

Projeto/Plano de Ação: 02.07.60.700-03

Comparação da partida de reatores com atividade anammox com diferentes concentrações de inóculo.

Projeto: 02.07.06.007

Progressão de carga em um reator de bancada com atividade anammox.

Projeto/Plano de Ação: 02.07.60700-03

Quantum conductance-temperature phase diagram of granular superconductor KxFe2-ySe2

It is now well established that the microstructure of Fe-based chalcogenide KxFe2−ySe2 consists of, at least, a minor (~15 percent), nano-sized, superconducting KsFe2Se2 phase and a major (~85 percent) insulating antiferromagnetic K2Fe4Se5 matrix. Other intercalated A1−xFe2−ySe2 (A = Li, Na, Ba, Sr, Ca, Yb, Eu, ammonia, amide, pyridine, ethylenediamine etc.) manifest a similar microstructure. On subjecting each of these systems to a varying control parameter (e.g. heat treatment, concentration x,y, or pressure p), one obtains an exotic normal-state and superconducting phase diagram. With the objective of rationalizing the properties of such a diagram, we envisage a system consisting of nanosized superconducting granules which are embedded within an insulating continuum. Then, based on the standard granular superconductor model, an induced variation in size, distribution, separation and Fe-content of the superconducting granules can be expressed in terms of model parameters (e.g. tunneling conductance, g, Coulomb charging energy, Ec, superconducting gap of single granule, Δ, and Josephson energy J = πΔg/2). We show, with illustration from experiments, that this granular scenario explains satisfactorily the evolution of normal-state and superconducting properties (best visualized on a g - E c/∆ T phase diagram) of AxFe2−ySe2 when any of x, y, p, or heat treatment is varied

Finite size analysis of a two-dimensional Ising model within a nonextensive approach

In this work we present a thorough analysis of the phase transitions that occur in a ferromagnetic 2D Ising model, with only nearest-neighbors interactions, in the framework of the Tsallis nonextensive statistics. We performed Monte Carlo simulations on square lattices with linear sizes L ranging from 32 up to 512. The statistical weight of the Metropolis algorithm was changed according to the nonextensive statistics. Discontinuities in the m(T) curve are observed for $q\leq 0.5$. However, we have verified only one peak on the energy histograms at the critical temperatures, indicating the occurrence of continuous phase transitions. For the $0.5<q\leq 1.0$ regime, we have found continuous phase transitions between the ordered and the disordered phases, and determined the critical exponents via finite-size scaling. We verified that the critical exponents $\alpha$, $\beta$ and $\gamma$ depend on the entropic index $q$ in the range $0.5<q\leq 1.0$ in the form $\alpha (q)=(10 q^{2}-33 q+23)/20$, $\beta (q)=(2 q-1)/8$ and $\gamma (q)=(q^{2}-q+7)/4$. On the other hand, the critical exponent $\nu$ does not depend on $q$. This suggests a violation of the scaling relations $2 \beta +\gamma =d \nu$ and $\alpha +2 \beta +\gamma =2$ and a nonuniversality of the critical exponents along the ferro-paramagnetic frontier.Comment: accepted for publication in Phys. Rev.

Análise de Envoltória de Dados para alocação de recursos: uma proposta de algoritmo sequencial.

Este trabalho apresenta um modelo sequencial de atribuição de recursos em modelos DEA, inspirado no modelo de votação de Hondt, considerando-se que o excesso de recursos a ser distribuído tem soma constante. Caso fosse de interesse realocal os recursos já existentes, mantendo-se constante o total dos recursos (soma dos recursos constante) poderia ser usado o modelo DEA com Ganhos de Soma Zero - GSZ-DEA, orientado a inputs. O algoritmo sequencial de alocação de recursos em DEA proposto neste artigo é aplicado à distribuição de vagas docentes aos departamentos de ensino do Centro Tecnológico da UFF. O modelo considera o número de professores de cada departamento, o envolvimento com atividades de ensino e pesquisa e a existência de projetos de expansão aprovados