Search results

Attempts to prove, in this second chapter of the author’s monograph, that with a new research programme, it is possible to build a methodological bridge between economics and all other natural sciences and the scientists should address this challenge. Reviews basic principles that govern nature, including Einstein’s findings along with such luminaries as Copernicus, Newton, Galileo and Jeans. Concludes that the future is safe, as a new generation of scientists is now emerging in the East and the West, and that the new methodology should provide enough space for new roads, ideas and interpretations, which may occur in the future. Closes by saying a new spirit should be initiated in economics and transplanted into natural sciences.

There is a double crisis in modern science and in particular in physics and mechanics. Among others Einstein and Stephane Lupasco, in the 1930s, warned about this crisis. The Quantum Theory cannot be reconciled with the Relativity Theory. Specifically there is a gap (cleavage) between micro – and macro‐physics and mechanics. Parallel or beneath there is also a second crisis derived from a discontinuity (again a cleavage) between classical and modern science, that is between two previous revolutions. A new research programme of a simultaneous equilibrium versus disequilibrium approach, initially applied in economics has now been extended to include natural sciences. It is the question of a new, more comprehensive methodology which is actually a sui generis synthesis between classical and modern heritage. The rigorous application of the new research programme leads to the organisation of an Orientation Table, that is, a methodological map of all possible combinations (systems). The Table shows, without any exaggeration, a few revolutionary results. For instance, with the help of the Table, modern science or the second revolution (Einstein, Bohr, Heisenberg) does not appear contradictory but rather complementary to classical science or the first revolution (Newton, Lavoisier). The Kuhnian thesis to the contrary is disproved and the second crisis is solved. With the help of the Universal Hypothesis of Duality (the basis of the Orientation Table), matter and energy, at the micro – and macro‐level, appear in a double form (the Principle of Duality): stable (equilibrium) particles and unstable (disequilibrium) waves. The strong interactions from modern physics are associated with the law of gravitation (attraction) or stable equilibrium which governs stable matter and energy. The weak interactions are associated with the law of disgravitation (dispersion or repulsion) including entropy or unstable equilibrium which governs unstable matter and energy. In this way the first crisis is also solved.

This study seeks to explain how a cybernetic system, the human brain, creates the cognitive models that are applied by physics to explain particular phenomena of the physical world, namely, the electrostatic force and the annihilation of matter and antimatter.

This study applies findings in cognitive psychology of vision, neuropsychology of the hemispheric mechanisms and quantum mechanics in order to explain how the electrostatic force operates at distance between two charged particles.

In addition to the quantum fields theory, which explains the electrostatic force by photons that carry this force between charged particles (and is related to the left‐hemispheric cognitive mechanism) a dual theory is suggested that explains this force by interchanging of features between particles (and is related to the right‐hemispheric cognitive mechanism).

Like Fidelman's previous studies, this too demonstrates that cybernetic considerations which use cognitive psychological, neuropsychological and physical‐knowledge can obtain testable and applicable physical theories.

This paper aims to show how collective embodiment with physical objects (i.e. props) support young children’s learning through the construction of liminal blends that merge physical, virtual and conceptual resources in a mixed-reality (MR) environment..

Building on Science through Technology Enhanced Play (STEP), we apply the Learning in Embodied Activity Framework to further explore how liminal blends can help us understand learning within MR environments. Twenty-two students from a mixed first- and second-grade classroom participated in a seven-part activity sequence in the STEP environment. The authors applied interaction analysis to analyze how student’s actions performed with the physical objects helped them to construct liminal blends that allowed key concepts to be made visible and shared for collective sensemaking.

The authors found that conceptually productive liminal blends occurred when students constructed connections between the resources in the MR environment and coordinated their embodiment with props to represent new understandings.

This study concludes with the implications for how the design of MR environment and teachers’ facilitation in MR environment supports students in constructing liminal blends and their understanding of complex science phenomena.

A theory of knowledge shows that all four systems of nature are recursive combinatorial‐hamiltonian self‐programmed flow‐wave systems that can be deduced from the usual Conservation Law promoted to the Axiom of Science.

This is a continuation of Parts I and II of the paper. In this part it is suggested that microscopic particles behave similarly to macroscopic objects: Features of two entangled particles, having the same “dimension” (kind of feature), may interchange and migrate from one particle to the other while their wave function collapses. In the particular case of electrically charged particles, like an electron and a proton, the migrating features that are interchanged between the particles, may be the electrical charges (that have the same “dimension”). This implies that each atom of matter has some very small probability to be an atom of antimatter, and it may be annihilated if it collides with an atom of matter. The purpose of this study is to suggest how this hypothesis may be tested empirically.

The cooler are the molecules of gases, the slower they are. Therefore, according to Heisenberg's principle of uncertainty, the probability that gaseous molecules will collide increases when the gas is cooled.

We may expect that when gases are cooled there is a higher than usual probability that gaseous molecules of matter and antimater will collide and will annihilate each other, emitting photons of gamma rays. Such findings has been reported by Molchadzki, but not explained. The same is true regarding other situations in which the probability of collisions of gaseous molecules is higher than the usual, like the colliding of gaseous molecule at the center of an imploding bubble of gas.

If a procedure that increases the number of collisions between gaseous molecules considerably will be developed, it may be that this procedure will be applicable for obtaining clean energy by annihilations of matter and antimatter.

This paper presents a unified framework to model the sintering process of fine powders. The framework is based on classical virtual power principle and its corresponding variational principle. Firstly, the classical models of solid state, viscous and liquid phase sintering are reproduced assuming single matter re‐distribution mechanism and using the virtual power principle as the starting point. Then we demonstrate how to obtain the governing equations for microstructural evolution using the variational principle. These provide a common thread through the existing sintering models. Finally a numerical solution scheme is briefly outlined for computer simulation of microstructural evolution using the variational principle as the starting point. The computer simulation can follow the entire sintering process from powder compact to fully dense solid and deal with fully couple multi‐physics processes involving all the possible underlying matter re‐distribution mechanisms. Several examples are provided to demonstrate the deep insights that can be gained into the sintering process by using the numerical tool.

Discrete element method (DEM) has been extensively used in the laboratory of particulate and multiphase processing at the University of New South Wales (UNSW) to study the fundamentals of particulate matter at a particle scale. This paper briefly reviews the work in the laboratory, which covers the development of simulation techniques and their application to the study of particle packing and flow, transport properties and constitutive relationships of typical static or dynamic particulate systems. It is concluded, through representative comparison between simulated and measured results under different conditions, that DEM, as a major technique for discrete particle simulation, is an effective method for particle scale research of particulate matter.

This paper considers a perspective on particulate matter as being formed from closed loops of waveform energy flow, consistent with observations by de Broglie, Schrödinger and others and supported by recent research findings. It demonstrates that all experimentally verified findings of special relativity may be derived directly from such a model. It further shows a clear form of auto‐adaptive behaviour exhibited by such structures.

A generalised closed‐loop energy flow model is analysed from first principles.

Motion‐dependent time dilation, invariance of the measured speed of light, the Lorentz transformation, mass‐energy equivalence (E=mc²) and speed‐related increase in apparent mass all follow naturally from this structure. Given this view of matter objective invariance of the speed of light relative to all inertial states of motion is an unnecessary and insupportable assumption. A unique objective rest frame (subject to Hubble expansion of space) is identified. All elementary sub‐atomic particles owe their longevity to a non‐destructive state‐change response to energy input, referred to as “motion”. A radically new perspective on time is presented. A possible causal explanation for particle‐antiparticle asymmetry is identified.

Closed timelike curves are not a possibility. Further implications for all fields of physics are very extensive.

There is no conflict between superluminal technologies and causality. Over and above this, possible practical implications are too extensive to be enumerated.

The paper is totally original and of significant potential value in various respects.

The purpose of this paper is to introduce new non‐classical implementations of neural networks (NNs). The developed implementations are performed in the quantum, nano, and optical domains to perform the required neural computing. The various implementations of the new NNs utilizing the introduced architectures are presented, and their extensions for the utilization in the non‐classical neural‐systolic networks are also introduced.

The introduced neural circuits utilize recent findings in the quantum, nano, and optical fields to implement the functionality of the basic NN. This includes the techniques of many‐valued quantum computing (MVQC), carbon nanotubes (CNT), and linear optics. The extensions of implementations to non‐classical neural‐systolic networks using the introduced neural‐systolic architectures are also presented.

Novel NN implementations are introduced in this paper. NN implementation using the general scheme of MVQC is presented. The proposed method uses the many‐valued quantum orthonormal computational basis states to implement such computations. Physical implementation of quantum computing (QC) is performed by controlling the potential to yield specific wavefunction as a result of solving the Schrödinger equation that governs the dynamics in the quantum domain. The CNT‐based implementation of logic NNs is also introduced. New implementations of logic NNs are also introduced that utilize new linear optical circuits which use coherent light beams to perform the functionality of the basic logic multiplexer by utilizing the properties of frequency, polarization, and incident angle. The implementations of non‐classical neural‐systolic networks using the introduced quantum, nano, and optical neural architectures are also presented.

The introduced NN implementations form new important directions in the NN realizations using the newly emerging technologies. Since the new quantum and optical implementations have the advantages of very high‐speed and low‐power consumption, and the nano implementation exists in very compact space where CNT‐based field effect transistor switches reliably using much less power than a silicon‐based device, the introduced implementations for non‐classical neural computation are new and interesting for the design in future technologies that require the optimal design specifications of super‐high speed, minimum power consumption, and minimum size, such as in low‐power control of autonomous robots, adiabatic low‐power very‐large‐scale integration circuit design for signal processing applications, QC, and nanotechnology.