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The “re‐industrialisation” of America is the dominant topic today. It has come about because the United States economy did not live up to its expectations during the decade of the 1970s. As to what has caused such low economic performance, many speculations have been advanced, such as big government, high taxes, monetary maladjustments, the energy shortages, the high prices of energy, etc. However, one group of economists have attributed the dismal economic performance during the 1970s to the phenomenon of the “long‐wave cycles”. This cycle is also called the Kondratieff cycle, and occurs at intervals of forty to sixty years in a socio‐economic system resembling that of capitalism. According to the proponents of this theory since the last part of the eighteenth century, industrial capitalism has exhibited long waves of cyclical fluctuation in income, employment and prices. These economists believe that the “long‐wave cycles” are what have underlined recent United States economic ills.

The paper aims to present an integrated foresight framework and method to support decision-makers who are confronted with today’s complex and rapidly changing world. The method aims at reducing the degree of uncertainty by addressing the inertia or duration of unfolding trends and by placing individual trends in a broader context.

The paper presents a three-layered framework and method for assessing megatrends based on their inertia or duration. It suggests that if long-term trends and key future uncertainties are studied in conjunction at a meta-level and placed in a broader multi-layered framework of trends, it can result in new insights.

The application of the proposed foresight method helps to systematically place a wide range of unrelated trends and key uncertainties in the context of a broader framework of trends, thereby improving the ability to understand the inertia, direction and mutual interaction of these trends.

The elaboration of identified trends and key uncertainties is partly case-specific and subject to interpretation. It is aimed at illustrating the potential use of the framework.

The paper presents a new approach that may, by itself or in combination with existing foresight methods, offer new means for anticipating future developments.

The use of the proposed framework has potential to provide better insight in the complexity of today’s rapid-changing world and the major transitions taking place. It aims to result in sharper foresight by reducing epistemic uncertainty for decision-makers.

The paper demonstrates how megatrends, Kondratieff waves and century-long trends can be placed in an integrated framework and analysed in conjunction.

The discussion in this paper addresses issues that should become part of the current politically popular debate about reindustrializing America. Why is there a perceived need to reindustrialize? Why are innovation and productivity‐faltering? I believe it is because old technologies are now being pushed beyond their level of maximum contribution, and because the radically new technologies of the future have not yet found their proper places in the fabric of society.

Previous research on institutional change has largely ignored its cyclical nature. This paper aims to introduce a four‐phase cyclical model of long‐term institutional change.

The recurrent patterns of the model have been identified from previous technological revolutions and their accompanying surges of development. The model also incorporates generational theory as a driver of institutional change.

The model predicts that a multi‐year institutional crisis is currently underway that has important implications for practitioners. The paper also describes proposed solutions to the current crisis.

The model developed synthesizes disparate institutional theories to build a new explanation for long‐term economic development.

The purpose of this paper is to discuss the integrability studies to the long-short wave equation that is studied in the context of shallow water waves. There are several integration tools that are applied to obtain the soliton and other solutions to the equation. The integration techniques are traveling waves, exp-function method, G′/G-expansion method and several others.

The design of the paper is structured with an introduction to the model. First the traveling wave hypothesis approach leads to the waves of permanent form. This eventually leads to the formulation of other approaches that conforms to the expected results.

The findings are a spectrum of solutions that lead to the clearer understanding of the physical phenomena of long-short waves. There are several constraint conditions that fall out naturally from the solutions. These poses the restrictions for the existence of the soliton solutions.

The results are new and are sharp with Lie symmetry analysis and other advanced integration techniques in place. These lead to the connection between these integration approaches.

IN R. & M. 1679 and AIRCRAFT ENGINEERING, December, 1935, the author gave certain expressions for the stable loads which a stiffened‐skin panel, flat or curved, was capable of carrying without collapse by buckling. As regards the curved panel, it was there implicitly assumed that waving over relatively long lengths was impossible, because of the presence of rigid bulkheads or similar supports at intervals. While this will normally be the case in practice, it may happen that in some part of the structure a long length of panel remains without support other than that given to it by the ordinary frames and stringers. As this will tend to reduce the buckling load, it seems desirable to complete the theory to include the case of buckling in long waves.

The purpose of this paper is to analyze numerically the blowup in finite time of the solutions to a one-dimensional, bidirectional, nonlinear wave model equation for the propagation of small-amplitude waves in shallow water, as a function of the relaxation time, linear and nonlinear drift, power of the nonlinear advection flux, viscosity coefficient, viscous attenuation, and amplitude, smoothness and width of three types of initial conditions.

An implicit, first-order accurate in time, finite difference method valid for semipositive relaxation times has been used to solve the equation in a truncated domain for three different initial conditions, a first-order time derivative initially equal to zero and several constant wave speeds.

The numerical experiments show a very rapid transient from the initial conditions to the formation of a leading propagating wave, whose duration depends strongly on the shape, amplitude and width of the initial data as well as on the coefficients of the bidirectional equation. The blowup times for the triangular conditions have been found to be larger than those for the Gaussian ones, and the latter are larger than those for rectangular conditions, thus indicating that the blowup time decreases as the smoothness of the initial conditions decreases. The blowup time has also been found to decrease as the relaxation time, degree of nonlinearity, linear drift coefficient and amplitude of the initial conditions are increased, and as the width of the initial condition is decreased, but it increases as the viscosity coefficient is increased. No blowup has been observed for relaxation times smaller than one-hundredth, viscosity coefficients larger than ten-thousandths, quadratic and cubic nonlinearities, and initial Gaussian, triangular and rectangular conditions of unity amplitude.

The blowup of a one-dimensional, bidirectional equation that is a model for the propagation of waves in shallow water, longitudinal displacement in homogeneous viscoelastic bars, nerve conduction, nonlinear acoustics and heat transfer in very small devices and/or at very high transfer rates has been determined numerically as a function of the linear and nonlinear drift coefficients, power of the nonlinear drift, viscosity coefficient, viscous attenuation, and amplitude, smoothness and width of the initial conditions for nonzero relaxation times.

The purpose of this paper is to investigate the wave propagation of wave in an infinite poroelastic cylindrical bone. The dynamic behavior of a wet long bone that has been modeled as a piezoelectric hollow cylinder of crystal class 6 is investigated.

An exact closed form solution is presented by employing an analytical procedure. The frequency equation for poroelastic bone is obtained when the boundaries are stress free and is examined numerically.

The study of wave propagation over a continuous medium is of practical importance in the field of engineering, medicine and bio-engineering. Application of the poroelastic materials in medicinal fields such as orthopedics, dental and cardiovascular is well known. In orthopedics, wave propagation over bone is used in monitoring the rate of fracture healing. There are two types of osseous tissue, such as cancellous or trabecular and compact or cortical bone, which are of different materials, with respect to their mechanical behavior.

The frequencies are calculated for poroelastic bone for various values for different values of rotation, angular velocity and density. In wet bone little velocity dispersion was observed, in contrast to the results of earlier studies on wet bone. Large values of attenuation were observed. Such a model would in particular be useful in large-scale parametric studies of bone mechanical response.

The purpose of this paper is to determine the relationship between the number of waves a surfer will catch, the surfer’s characteristics, and the surf conditions; and utilize this relationship to explain wave allocation strategies chosen by surfers.

The study employed a discrete event simulation to model surfers at a well-known surf break in Southern California. Several experimental designs were implemented in the simulation to measure the effect of a surfer’s characteristics and surf conditions on waves caught; and compare different wave allocation strategies.

The number of waves that a surfer will catch is largely dependent upon the surfer’s skill level and the wave allocation strategy used at the surf break. Common wave allocation strategies fail with large crowds.

This study is the first to model the entire lineup at a surf break, providing quantitative insights into why surfers choose different wave allocation strategies.