Scaling the tail beat frequency and swimming speed in underwater undulatory swimming.

Undulatory swimming is the predominant form of locomotion in aquatic vertebrates. A myriad of animals of different species and sizes oscillate their bodies to propel themselves in aquatic environments with swimming speed scaling as the product of the animal length by the oscillation frequency. Although frequency tuning is the primary means by which a swimmer selects its speed, there is no consensus on the mechanisms involved. In this article, we propose scaling laws for undulatory swimmers that relate oscillation frequency to length by taking into account both the biological characteristics of the muscles and the interaction of the moving swimmer with its environment. Results are supported by an extensive literature review including approximately 1200 individuals of different species, sizes and swimming environments. We highlight a crossover in size around 0.5-1 m. Below this value, the frequency can be tuned between 2-20 Hz due to biological constraints and the interplay between slow and fast muscles. Above this value, the fluid-swimmer interaction must be taken into account and the frequency is inversely proportional to the length of the animal. This approach predicts a maximum swimming speed around 5-10 m.s-1 for large swimmers, consistent with the threshold to prevent bubble cavitation.

Reinforcement learning approach to control an inverted pendulum: A general framework for educational purposes.

Machine learning is often cited as a new paradigm in control theory, but is also often viewed as empirical and less intuitive for students than classical model-based methods. This is particularly the case for reinforcement learning, an approach that does not require any mathematical model to drive a system inside an unknown environment. This lack of intuition can be an obstacle to design experiments and implement this approach. Reversely there is a need to gain experience and intuition from experiments. In this article, we propose a general framework to reproduce successful experiments and simulations based on the inverted pendulum, a classic problem often used as a benchmark to evaluate control strategies. Two algorithms (basic Q-Learning and Deep Q-Networks (DQN)) are introduced, both in experiments and in simulation with a virtual environment, to give a comprehensive understanding of the approach and discuss its implementation on real systems. In experiments, we show that learning over a few hours is enough to control the pendulum with high accuracy. Simulations provide insights about the effect of each physical parameter and tests the feasibility and robustness of the approach.

[Accidents attended in a basic health area of Girona, Spain]. / Accidentes atendidos en un área básica de salud de Girona, España.

BACKGROUND: Accidents have been largely unstudied in the area of Primary Care. They are one of the most frequent motives for consultation in the Emergency Services and the first assistance that accident victims receive is usually in primary care centres. Establishment of the incidence and clinicoepidemiological characteristics of the accidents attended in a Basic Health Area can provide important information about which of these could be susceptible to preventive actions. DESIGN: descriptive study. LOCATION: primary care: SAMPLE: all the patients attended for accidents (389) in the Primary Care Centre between October 1998 and May 1999. VARIABLES: age, sex, place of the accident, type of lesion, location of lesions, agents involved, intentionality, complementary tests, treatment and referral. STATISTICAL ANALYSIS: estimation of means, standard deviation, proportions and 95% confidence intervals. RESULTS: Incidence: 4.1% (CI95%: 3.7-4.5%). Sex: males 59% (CI95%: 54.2-64%) and females 40.9% (CI95%: 36-45.8%). Age: younger than 20 years, 50.4% (CI95%: 45.4-55.4%). Most common activity associated with accidents: leisure 24.4% (CI95%: 20.2-28.7%). PLACE: home 36.2% (C95%: 31.5-41%). Most frequent lesion: contusion 39.6% (CI95%: 34.7-44.4%). Most frequent site of lesion: arms 37.5% (CI95%: 32.7-42.3%). Most common agent involved: tools and machinery 15.9% (CI95%: 12.3-19.6%). Of these, 92.2% (CI95%: 89.3-94.7%) were accidental. Type of visit: 83.3% (CI95%: 79.6-87%) were attended as emergencies; 79.5% (CI95%: 75.4-83.5%) received treatment with dressings and/or medication. Of these, 9.8% (CI95%: 6.8-12.7%) required referral to a hospital, 13.3% (CI95%: 10-16.7%) required complementary tests. CONCLUSIONS: Most accidents occur in young people and educational campaigns to prevent accidents and directed towards this population group are clearly needed.