Novitates rio munis 1. A new endemic scaphopetalum (Malvaceae) from Mount Mitra, Equatorial Guinea

A new species of Scaphopetalum from Monte Mitra is described

An exploration strategy for non-stationary opponents

The success or failure of any learning algorithm is partially due to the exploration strategy it exerts. However, most exploration strategies assume that the environment is stationary and non-strategic. In this work we shed light on how to design exploration strategies in non-stationary and adversarial environments. Our proposed adversarial drift exploration (DE) is able to efficiently explore the state space while keeping track of regions of the environment that have changed. This proposed exploration is general enough to be applied in single agent non-stationary environments as well as in multiagent settings where the opponent changes its strategy in time. We use a two agent strategic interaction setting to test this new type of exploration, where the opponent switches between different behavioral patterns to emulate a non-deterministic, stochastic and adversarial environment. The agent’s objective is to learn a model of the opponent’s strategy to act optimally. Our contribution is twofold. First, we present DE as a strategy for switch detection. Second, we propose a new algorithm called R-max# for learning and planning against non-stationary opponent. To handle such opponents, R-max# reasons and acts in terms of two objectives: (1) to maximize utilities in the short term while learning and (2) eventually explore opponent behavioral changes. We provide theoretical results showing that R-max# is guaranteed to detect the opponent’s switch and learn a new model in terms of finite sample complexity. R-max# makes efficient use of exploration experiences, which results in rapid adaptation and efficient DE, to deal with the non-stationary nature of the opponent. We show experimentally how using DE outperforms the state of the art algorithms that were explicitly designed for modeling opponents (in terms average rewards) in two complimentary domains

Efficiently detecting switches against non-stationary opponents

Interactions in multiagent systems are generally more complicated than single agent ones. Game theory provides solutions on how to act in multiagent scenarios; however, it assumes that all agents will act rationally. Moreover, some works also assume the opponent will use a stationary strategy. These assumptions usually do not hold in real world scenarios where agents have limited capacities and may deviate from a perfect rational response. Our goal is still to act optimally in these cases by learning the appropriate response and without any prior policies on how to act. Thus, we focus on the problem when another agent in the environment uses different stationary strategies over time. This will turn the problem into learning in a non-stationary environment, posing a problem for most learning algorithms. This paper introduces DriftER, an algorithm that (1) learns a model of the opponent, (2) uses that to obtain an optimal policy and then (3) determines when it must re-learn due to an opponent strategy change. We provide theoretical results showing that DriftER guarantees to detect switches with high probability. Also, we provide empirical results showing that our approach outperforms state of the art algorithms, in normal form games such as prisoner’s dilemma and then in a more realistic scenario, the Power TAC simulator

Effect of multi-component school-based program on body mass index, cardiovascular and diabetes risks in a multi-ethnic study

Background: Mexico occupies one of the first places worldwide in childhood obesity. Its Mestizo and Indigenous communities present different levels of westernization which have triggered different epidemiological diseases. We assessed the effects of a multi-component school-based intervention program on obesity, cardiovascular and diabetes risk factors. Methods: A physical activity, health education and parent involvement (PAHEPI) program was developed and applied in six urban (Mestizo ethnic group) and indigenous (Seri and Yaqui ethnic groups) primary schools for 12 weeks. A total of 320 children aged 4–12 years participated in intervention program; 203 under Treatment 1 (PAHEPI program) and 117, only from Mestizo groups, under Treatment 2 (PAHEPI+ school meals). For Body Mass Index (BMI), cardiovascular and diabetes factors, pairwise comparisons of values at baseline and after treatments were done using Wilcoxon signed rank test. Generalized linear models were applied to assess the intervention effect by age, sex and nutritional status in relation to ethnicity and treatment. Results: We observed improvements on BMI in children with overweight-obesity and in triglycerides in the three ethnic groups. The Mestizo ethnic group showed the largest improvements under Treatment 2. While Seris showed improvements only in cardiovascular risk factors, Yaquis also showed improvements in diabetes risk factors, though not in BMI. Conclusions: This study showed that the same intervention may have positive but different effects in different ethnic groups depending on their lifestyle and their emerging epidemiological disease. Including this type of intervention as part of the school curriculum would allow to adapt to ethnic group in order to contribute more efficiently to child welfare

Sandpiles with height restrictions

We study stochastic sandpile models with a height restriction in one and two dimensions. A site can topple if it has a height of two, as in Manna's model, but, in contrast to previously studied sandpiles, here the height (or number of particles per site), cannot exceed two. This yields a considerable simplification over the unrestricted case, in which the number of states per site is unbounded. Two toppling rules are considered: in one, the particles are redistributed independently, while the other involves some cooperativity. We study the fixed-energy system (no input or loss of particles) using cluster approximations and extensive simulations, and find that it exhibits a continuous phase transition to an absorbing state at a critical value zeta_c of the particle density. The critical exponents agree with those of the unrestricted Manna sandpile.Comment: 10 pages, 14 figure

Activated Random Walkers: Facts, Conjectures and Challenges

We study a particle system with hopping (random walk) dynamics on the integer lattice $\mathbb Z^d$. The particles can exist in two states, active or inactive (sleeping); only the former can hop. The dynamics conserves the number of particles; there is no limit on the number of particles at a given site. Isolated active particles fall asleep at rate $\lambda > 0$, and then remain asleep until joined by another particle at the same site. The state in which all particles are inactive is absorbing. Whether activity continues at long times depends on the relation between the particle density $\zeta$ and the sleeping rate $\lambda$. We discuss the general case, and then, for the one-dimensional totally asymmetric case, study the phase transition between an active phase (for sufficiently large particle densities and/or small $\lambda$) and an absorbing one. We also present arguments regarding the asymptotic mean hopping velocity in the active phase, the rate of fixation in the absorbing phase, and survival of the infinite system at criticality. Using mean-field theory and Monte Carlo simulation, we locate the phase boundary. The phase transition appears to be continuous in both the symmetric and asymmetric versions of the process, but the critical behavior is very different. The former case is characterized by simple integer or rational values for critical exponents ($\beta = 1$, for example), and the phase diagram is in accord with the prediction of mean-field theory. We present evidence that the symmetric version belongs to the universality class of conserved stochastic sandpiles, also known as conserved directed percolation. Simulations also reveal an interesting transient phenomenon of damped oscillations in the activity density

IFNL4 ss469415590 polymorphism is associated with unfavourable clinical and immunological status in HIV-infected individuals

AbstractThe IFNL4 ss469415590 polymorphism, in high linkage disequilibrium with the IL28B rs12979860 variant, has been associated with hepatitis C virus clearance. We evaluated whether ss469415590 is associated with clinical and immunovirological parameters in human immunodeficiency virus-infected subjects. We found an independent association of the IFNL4 ss469415590 polymorphism with higher prevalence of AIDS-defining illnesses and lower CD4 T cell numbers. These results suggest the existence of common host defence mechanisms against different viral infections