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Coriolis force

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Coriolis force. --- Coriolis force. --- Energy levels (Quantum mechanics). --- Energy levels (Quantum mechanics).

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Do genes explain life? Can advances in evolutionary and molecular biology account for what we look like, how we behave, and why we die? In this powerful intervention into current biological thinking, Brian Goodwin argues that such genetic reductionism has important limits. Drawing on the sciences of complexity, the author shows how an understanding of the self-organizing patterns of networks is necessary for making sense of nature. Genes are important, but only as part of a process constrained by environment, physical laws, and the universal tendencies of complex adaptive systems. In a new preface for this edition, Goodwin reflects on the advances in both genetics and the sciences of complexity since the book's original publication.

Morphology. --- Acanthostega (fossil tetrapod). --- Barlow, Kenneth. --- Beloussov, Boris. --- Beloussov-Zhabotinsky reaction. --- Coriolis force. --- Darwin, Charles. --- Dasycladales (algae). --- Gaia hypothesis. --- Kant, Immanuel. --- Lamarckian inheritance. --- alternate phyllotaxis. --- attractors. --- autopoesis. --- bifurcations. --- causation. --- cellular automata. --- dolphins. --- entropy. --- excitable media. --- flower primordia. --- genocentric biology. --- historical explanations. --- homunculus theory. --- infarcts. --- invariant sets. --- inverse problem. --- limb buds. --- meristems. --- monocotyledons. --- moving boundary problems. --- natural history. --- neurulation. --- organisms. --- parastichies. --- phyllotaxy. --- quantum mechanics. --- sociobiology.

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This book includes an editorial and 12 research papers on micromixers collected from the Special Issue published in Micromachines. The topics of the papers are focused on the design of micromixers, their fabrication, and their analysis. Some of them proposed novel micromixer designs. Most of them deal with passive micromixers, but two papers report studies on electrokinetic micromixers. Fully three-dimensional (3D) micromixers were investigated in some cases. One of the papers applied optimization techniques to the design of a 3D micromixer. A review paper is also included and reports a review of recently developed passive micromixers and a comparative analysis of 10 typical micromixers.

Technology: general issues --- passive micromixers --- comparative analysis --- Navier-Stokes equations --- mixing index --- pressure drop --- mixing cost --- micromachining --- micro EDM milling --- empirical modelling --- micromixer --- design for manufacturing --- computational fluid dynamics --- micromixers --- acoustic micromixers --- active micromixers --- electromagnetic micromixers --- voice-coil mixers --- mixers --- anti-reciprocity --- electrical impedance --- mechanical velocity --- gyrator --- electro-mechanical systems --- micro heat exchanger --- vortex shedding --- thermal mixing --- computational fluid dynamics (CFD) --- thermal engineering --- three-dimensional (3D) printing --- micronozzles --- Y-shaped structure --- mixing efficiency --- histogram and standard deviation --- split-and-recombine --- additive manufacturing --- surface metrology --- asymmetric split-and-recombine (ASAR) --- stereolithography --- surface roughness --- soft tooling --- centrifugal microfluidics --- U-shaped channel --- Coriolis force --- flow visualization --- microfluidics --- T-shaped micromixer --- vortex --- obstacles --- engulfment flow --- particle tracking --- electrokinetic vortices --- T-type microchannel --- zeta potential ratio --- length ratio --- Navier–Stokes equations --- optimization --- RBNN --- TLCCM configuration --- mixing rate --- kinematics --- deformation --- vorticity --- stretching --- folding --- diffusive mixing --- passive mixing --- fluid overlapping --- sequential injection --- segmentation --- concentric flow --- CFD --- n/a

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The classical Melnikov method provides information on the behavior of deterministic planar systems that may exhibit transitions, i.e. escapes from and captures into preferred regions of phase space. This book develops a unified treatment of deterministic and stochastic systems that extends the applicability of the Melnikov method to physically realizable stochastic planar systems with additive, state-dependent, white, colored, or dichotomous noise. The extended Melnikov method yields the novel result that motions with transitions are chaotic regardless of whether the excitation is deterministic or stochastic. It explains the role in the occurrence of transitions of the characteristics of the system and its deterministic or stochastic excitation, and is a powerful modeling and identification tool. The book is designed primarily for readers interested in applications. The level of preparation required corresponds to the equivalent of a first-year graduate course in applied mathematics. No previous exposure to dynamical systems theory or the theory of stochastic processes is required. The theoretical prerequisites and developments are presented in the first part of the book. The second part of the book is devoted to applications, ranging from physics to mechanical engineering, naval architecture, oceanography, nonlinear control, stochastic resonance, and neurophysiology.

Differentiable dynamical systems. --- Chaotic behavior in systems. --- Stochastic systems. --- Systems, Stochastic --- Stochastic processes --- System analysis --- Chaos in systems --- Chaos theory --- Chaotic motion in systems --- Differentiable dynamical systems --- Dynamics --- Nonlinear theories --- System theory --- Differential dynamical systems --- Dynamical systems, Differentiable --- Dynamics, Differentiable --- Differential equations --- Global analysis (Mathematics) --- Topological dynamics --- Affine transformation. --- Amplitude. --- Arbitrarily large. --- Attractor. --- Autocovariance. --- Big O notation. --- Central limit theorem. --- Change of variables. --- Chaos theory. --- Coefficient of variation. --- Compound Probability. --- Computational problem. --- Control theory. --- Convolution. --- Coriolis force. --- Correlation coefficient. --- Covariance function. --- Cross-covariance. --- Cumulative distribution function. --- Cutoff frequency. --- Deformation (mechanics). --- Derivative. --- Deterministic system. --- Diagram (category theory). --- Diffeomorphism. --- Differential equation. --- Dirac delta function. --- Discriminant. --- Dissipation. --- Dissipative system. --- Dynamical system. --- Eigenvalues and eigenvectors. --- Equations of motion. --- Even and odd functions. --- Excitation (magnetic). --- Exponential decay. --- Extreme value theory. --- Flow velocity. --- Fluid dynamics. --- Forcing (recursion theory). --- Fourier series. --- Fourier transform. --- Fractal dimension. --- Frequency domain. --- Gaussian noise. --- Gaussian process. --- Harmonic analysis. --- Harmonic function. --- Heteroclinic orbit. --- Homeomorphism. --- Homoclinic orbit. --- Hyperbolic point. --- Inference. --- Initial condition. --- Instability. --- Integrable system. --- Invariant manifold. --- Iteration. --- Joint probability distribution. --- LTI system theory. --- Limit cycle. --- Linear differential equation. --- Logistic map. --- Marginal distribution. --- Moduli (physics). --- Multiplicative noise. --- Noise (electronics). --- Nonlinear control. --- Nonlinear system. --- Ornstein–Uhlenbeck process. --- Oscillation. --- Parameter space. --- Parameter. --- Partial differential equation. --- Perturbation function. --- Phase plane. --- Phase space. --- Poisson distribution. --- Probability density function. --- Probability distribution. --- Probability theory. --- Probability. --- Production–possibility frontier. --- Relative velocity. --- Scale factor. --- Shear stress. --- Spectral density. --- Spectral gap. --- Standard deviation. --- Stochastic process. --- Stochastic resonance. --- Stochastic. --- Stream function. --- Surface stress. --- Symbolic dynamics. --- The Signal and the Noise. --- Topological conjugacy. --- Transfer function. --- Variance. --- Vorticity.