Evaluation of genotypic and phenotypic methods for differentiation of the members of the Anginosus group streptococci

The terminology and classification of the Anginosus group streptococci has been inconsistent. We tested the utility of 16S rRNA gene and tuf gene sequencing and conventional biochemical tests for the reliable differentiation of the Anginosus group streptococci. Biochemical testing included Rapid ID 32 Strep, API Strep, Fluo-Card Milleri, Wee-tabs, and Lancefield antigen typing. Altogether, 61 Anginosus group isolates from skin and soft tissue infections and four reference strains were included. Our results showed a good agreement between 16S rRNA gene and tuf gene sequencing. Using the full sequence was less discriminatory than using the first part of the 16S rRNA gene. The three species could not be separated with the API 20 Strep test. Streptococcus intermedius could be differentiated from the other two species by β-galactosidase (ONPG) and β-N-acetyl-glucosaminidase reactions. Rapid ID 32 Strep β-glucosidase reaction was useful in separating S. anginosus strains from S. constellatus. In conclusion, both 16S rRNA gene and tuf gene sequencing can be used for the reliable identification of the Anginosus group streptococci. S. intermedius can be readily differentiated from the other two species by phenotypic tests; however, 16S rRNA gene or tuf gene sequencing may be needed for separating some strains of S. constellatus from S. anginosus

Prioritized Sweeping Neural DynaQ with Multiple Predecessors, and Hippocampal Replays

During sleep and awake rest, the hippocampus replays sequences of place cells that have been activated during prior experiences. These have been interpreted as a memory consolidation process, but recent results suggest a possible interpretation in terms of reinforcement learning. The Dyna reinforcement learning algorithms use off-line replays to improve learning. Under limited replay budget, a prioritized sweeping approach, which requires a model of the transitions to the predecessors, can be used to improve performance. We investigate whether such algorithms can explain the experimentally observed replays. We propose a neural network version of prioritized sweeping Q-learning, for which we developed a growing multiple expert algorithm, able to cope with multiple predecessors. The resulting architecture is able to improve the learning of simulated agents confronted to a navigation task. We predict that, in animals, learning the world model should occur during rest periods, and that the corresponding replays should be shuffled.Comment: Living Machines 2018 (Paris, France

Simulating Dynamical Features of Escape Panic

One of the most disastrous forms of collective human behaviour is the kind of crowd stampede induced by panic, often leading to fatalities as people are crushed or trampled. Sometimes this behaviour is triggered in life-threatening situations such as fires in crowded buildings; at other times, stampedes can arise from the rush for seats or seemingly without causes. Tragic examples within recent months include the panics in Harare, Zimbabwe, and at the Roskilde rock concert in Denmark. Although engineers are finding ways to alleviate the scale of such disasters, their frequency seems to be increasing with the number and size of mass events. Yet, systematic studies of panic behaviour, and quantitative theories capable of predicting such crowd dynamics, are rare. Here we show that simulations based on a model of pedestrian behaviour can provide valuable insights into the mechanisms of and preconditions for panic and jamming by incoordination. Our results suggest practical ways of minimising the harmful consequences of such events and the existence of an optimal escape strategy, corresponding to a suitable mixture of individualistic and collective behaviour.Comment: For related information see http://angel.elte.hu/~panic, http://www.helbing.org, http://angel.elte.hu/~fij, and http://angel.elte.hu/~vicse

Likelihood inference for exponential-trawl processes

Integer-valued trawl processes are a class of serially correlated, stationary and infinitely divisible processes that Ole E. Barndorff-Nielsen has been working on in recent years. In this Chapter, we provide the first analysis of likelihood inference for trawl processes by focusing on the so-called exponential-trawl process, which is also a continuous time hidden Markov process with countable state space. The core ideas include prediction decomposition, filtering and smoothing, complete-data analysis and EM algorithm. These can be easily scaled up to adapt to more general trawl processes but with increasing computation efforts.Comment: 29 pages, 6 figures, forthcoming in: "A Fascinating Journey through Probability, Statistics and Applications: In Honour of Ole E. Barndorff-Nielsen's 80th Birthday", Springer, New Yor

Principles of Stakes Fairness in Sport

Fairness in sport is not just about assigning the top prizes to the worthiest competitors. It is also about the way the prize structure itself is organised. For many sporting competitions, although it may be acceptable for winners to receive more than losers, it can seem unfair for winners to take everything and for losers to get nothing. Yet this insight leaves unanswered some difficult questions about what stakes fairness requires and which principles of stakes fairness are appropriate for particular competitions. In this article I specify a range of different principles of stakes fairness (ten in total) that could regulate sporting competitions. I also put forward a theoretical method for pairing up appropriate principles of stakes fairness with given sporting competitions. Specifically, I argue that the underlying rationales for holding sporting competitions can provide useful guides for identifying appropriate principles of stakes fairness. I then seek to clarify and work through some of the implications of this method for a sample of real world controversies over sporting prize structures. I also attempt to refine the method in response to two possible objections from indeterminacy and relativism. Finally, I compare and contrast my conclusions with more general philosophical debates about justice

Coherent motion of stereocilia assures the concerted gating of hair-cell transduction channels

The hair cell's mechanoreceptive organelle, the hair bundle, is highly sensitive because its transduction channels open over a very narrow range of displacements. The synchronous gating of transduction channels also underlies the active hair-bundle motility that amplifies and tunes responsiveness. The extent to which the gating of independent transduction channels is coordinated depends on how tightly individual stereocilia are constrained to move as a unit. Using dual-beam interferometry in the bullfrog's sacculus, we found that thermal movements of stereocilia located as far apart as a bundle's opposite edges display high coherence and negligible phase lag. Because the mechanical degrees of freedom of stereocilia are strongly constrained, a force applied anywhere in the hair bundle deflects the structure as a unit. This feature assures the concerted gating of transduction channels that maximizes the sensitivity of mechanoelectrical transduction and enhances the hair bundle's capacity to amplify its inputs.Comment: 24 pages, including 6 figures, published in 200