Concentrated MTA Repair HP reduced biofilm and can cause reparative action at a distance

Quantum entanglement is popularly believed to give rise to spooky action at a distance of a kind that Einstein decisively rejected. Indeed, important recent experiments on systems assigned entangled states have been claimed to refute Einstein by exhibiting such spooky action. After reviewing two considerations in favor of this view I argue that quantum theory can be used to explain puzzling correlations correctly predicted by assignment of entangled quantum states with no such instantaneous action at a distance. We owe both considerations in favor of the view to arguments of John Bell. I present simplified forms of these arguments as well as a game that provides insight into the situation. The argument I give in response turns on a prescriptive view of quantum states that differs both from Dirac’s (as stated in Chapter 2) and Einstein’s.

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LEARNING NAIVE PHYSICS BY VISUAL OBSERVATION: USING QUALITATIVE SPATIAL REPRESENTATIONS AND PROBABILISTIC REASONING

International Journal of Computational Intelligence and Applications ◽

10.1142/s146902680100024x ◽

2001 ◽

Vol 01 (03) ◽

pp. 273-285 ◽

Cited By ~ 1

Author(s):

PAUL A. BOXER

Keyword(s):

Bayesian Network ◽

Probabilistic Reasoning ◽

Autonomous Robots ◽

Visual Observation ◽

Spatial Representations ◽

Physical Behavior ◽

Naive Physics ◽

Action At A Distance ◽

General Physical ◽

Test Scenarios

Autonomous robots are unsuccessful at operating in complex, unconstrained environments. They lack the ability to learn about the physical behavior of different objects through the use of vision. We combine Bayesian networks and qualitative spatial representation to learn general physical behavior by visual observation. We input training scenarios that allow the system to observe and learn normal physical behavior. The position and velocity of the visible objects are represented as qualitative states. Transitions between these states over time are entered as evidence into a Bayesian network. The network provides probabilities of future transitions to produce predictions of future physical behavior. We use test scenarios to determine how well the approach discriminates between normal and abnormal physical behavior and actively predicts future behavior. We examine the ability of the system to learn three naive physical concepts, "no action at a distance", "solidity" and "movement on continuous paths". We conclude that the combination of qualitative spatial representations and Bayesian network techniques is capable of learning these three rules of naive physics.

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Comments on ?quantum theory does not require action at a distance?

Foundations of Physics Letters ◽

10.1007/bf00690074 ◽

1989 ◽

Vol 2 (1) ◽

pp. 9-13 ◽

Cited By ~ 3

Author(s):

Henry P. Stapp

Keyword(s):

Quantum Theory ◽

Action At A Distance

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FORCES BETWEEN ELECTRIC CHARGES IN MOTION: RUTHERFORD SCATTERING, CIRCULAR KEPLERIAN ORBITS, ACTION-AT-A-DISTANCE AND NEWTON'S THIRD LAW IN RELATIVISTIC CLASSICAL ELECTRODYNAMICS

International Journal of Modern Physics A ◽

10.1142/s0217751x08038184 ◽

2008 ◽

Vol 23 (02) ◽

pp. 327-351 ◽

Cited By ~ 1

Author(s):

J. H. FIELD

Keyword(s):

Special Relativity ◽

Small Angle ◽

Classical Electrodynamics ◽

Classical Electromagnetism ◽

Newtonian Gravitation ◽

Keplerian Orbits ◽

Rutherford Scattering ◽

Action At A Distance ◽

Electrodynamic Theory ◽

Third Law

Standard formulae of classical electromagnetism for the forces between electric charges in motion derived from retarded potentials are compared with those obtained from a recently developed relativistic classical electrodynamic theory with an instantaneous intercharge force. Problems discussed include small angle Rutherford scattering, Jackson's recent "torque paradox" and circular Keplerian orbits. Results consistent with special relativity are obtained only with an instantaneous interaction. The impossibility of stable circular motion with retarded fields in either classical electromagnetism or Newtonian gravitation is demonstrated.

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