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1.
Nat Commun ; 14(1): 5569, 2023 09 09.
Article in English | MEDLINE | ID: mdl-37689714

ABSTRACT

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.


Subject(s)
Locomotion , Swimming , Animals , Consensus , Muscles
2.
PLoS One ; 18(2): e0280071, 2023.
Article in English | MEDLINE | ID: mdl-36780874

ABSTRACT

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.


Subject(s)
Algorithms , Reinforcement, Psychology , Humans , Computer Simulation , Machine Learning , Students
3.
Rev Esp Salud Publica ; 76(1): 57-64, 2002.
Article in Spanish | MEDLINE | ID: mdl-11905400

ABSTRACT

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.


Subject(s)
Accidents/statistics & numerical data , Wounds and Injuries/epidemiology , Accident Prevention , Accidents, Home/statistics & numerical data , Accidents, Occupational/statistics & numerical data , Accidents, Traffic/statistics & numerical data , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Child , Child, Preschool , Data Interpretation, Statistical , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Primary Health Care , Sex Factors , Spain , Wounds and Injuries/therapy
4.
Rev. esp. salud pública ; 76(1): 57-64, ene. 2002.
Article in Es | IBECS | ID: ibc-16242

ABSTRACT

Fundamentos: Los accidentes constituyen una patología poco estudiada en el ámbito de la Atención Primaria. Son una de las consultas más frecuentes en los servicios de urgencias y los Centros de Atención Primaria realizan la primera asistencia a la mayoría de los accidentados. Conocer la incidencia y las características clínico-epidemiológicas de los accidentes atendidos en una Área Básica de Salud puede aportar información sobre cuáles pueden ser susceptibles de actividades de prevención. Métodos: Diseño: estudio descriptivo. Emplazamiento: atención primaria. Muestra: todos los pacientes (389) que fueron atendidos por accidente en el Centro de Atención Primaria, entre octubre-98 y mayo-99. Variables: edad, sexo, lugar del accidente, tipo de lesión, localización, agentes implicados, intencionalidad, pruebas complementarias, tratamiento y derivación. Análisis estadísticos: estimación de medias, desviación estándar, estimación de proporciones e intervalos de confianza del 95 per cent. Resultados: Incidencia: 4,1 per cent (IC95 per cent: 3,7-4,5 per cent). Sexo: varones 59 per cent (IC95 per cent:54,2-64 per cent) y mujeres 40,9 per cent (IC95 per cent: 36-45,8 per cent). Edad: menores de 20 años, el 50,4 per cent (IC95 per cent:45,4-55,4 per cent);.Actividad de mayor accidentalidad: ocio 24,4 per cent (IC95 per cent: 20,2-28,7 per cent). Lugar: hogar 36,2 per cent (IC95 per cent: 31,5-41 per cent). Lesión más frecuente: contusiones 39,6 per cent (IC95 per cent:34,7-44,4 per cent).Localización más frecuente: extremidad superior 37,5 per cent (IC95 per cent: 32,7-42,3 per cent); Agente mayoritariamente implicado: herramientas y máquinas: 15,9 per cent (IC95 per cent:12,3-19,6 per cent). El 92,2 per cent (IC95 per cent: 89,3-94,7 per cent) fueron casuales. Tipo de visita: el 83,3 per cent (IC95 per cent: 79,6-87 per cent) fueron atendidos con carácter urgente; el 79,5 per cent (IC95 per cent:75,4-83,5 per cent) recibió tratamiento con cura y/o fármacos. El 9,8 per cent (IC95 per cent:6,8-12,7 per cent) requirió derivación hospitalaria, Un 13,3 per cent (IC95 per cent: 0-16,7 per cent) requirió pruebas complementarias. Conclusiones: El mayor porcentaje de accidentalidad se da en población joven, por lo que se evidencia la necesidad de incorporar intervenciones de educación sanitaria para la prevención de accidentes dirigidas a dicha población (AU)


Subject(s)
Middle Aged , Child , Child, Preschool , Adult , Adolescent , Aged , Aged, 80 and over , Male , Infant , Infant, Newborn , Female , Humans , Spain , Sex Factors , Wounds and Injuries , Primary Health Care , Data Interpretation, Statistical , Accidents, Traffic , Accident Prevention , Accidents, Occupational , Accidents, Home , Accidents , Age Factors
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