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The lungs of infants with respiratory distress syndrome are developmentally deficient in a material called surfactant, which helps prevent the collapse of the terminal air spaces (the future site of alveolar development) throughout the normal cycle of inhalation and exhalation. This deficiency of surfactant is related to inhibition from the ...
It is the most common cause of respiratory distress in term neonates. [2] [3] It consists of a period of tachypnea (rapid breathing, higher than the normal range of 30–60 times per minute). Usually, this condition resolves over 24–72 hours. Treatment is supportive and may include supplemental oxygen and antibiotics.
Whether a behavior is pathological is by definition subject to personal intuition. Pathologies depend on context, training, and experience, and what is pathological to one researcher may very well be standard behavior to another. Pathological examples can show the importance of the assumptions in a theorem.
In machine learning, a neural differential equation is a differential equation whose right-hand side is parametrized by the weights θ of a neural network. [1] In particular, a neural ordinary differential equation (neural ODE) is an ordinary differential equation of the form
An attractor network is a type of recurrent dynamical network, that evolves toward a stable pattern over time.Nodes in the attractor network converge toward a pattern that may either be fixed-point (a single state), cyclic (with regularly recurring states), chaotic (locally but not globally unstable) or random (). [1]
A plot of Lorenz' strange attractor for values ρ=28, σ = 10, β = 8/3. The butterfly effect or sensitive dependence on initial conditions is the property of a dynamical system that, starting from any of various arbitrarily close alternative initial conditions on the attractor, the iterated points will become arbitrarily spread out from each other.
Of course, y is not actually completely constant at x = 0.001 – this is just its main behaviour in the vicinity of this point.It may be that retaining only the leading-order (or approximately leading-order) terms, and regarding all the other smaller terms as negligible, is insufficient (when using the model for future prediction, for example), and so it may be necessary to also retain the ...
A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate. Normal distributions are important in statistics and are often used in the natural and social sciences to represent real-valued random variables whose distributions are not known.