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About forty years after its discovery, it is still common to read in the literature that quasicrystals (QCs) occupy an intermediate position between amorphous materials and periodic crystals. However, QCs exhibit high-quality diffraction patterns containing a collection of discrete Bragg reflections at variance with amorphous phases. Accordingly, these materials must be properly regarded as long-range ordered materials with a symmetry incompatible with translation invariance. This misleading conceptual status can probably arise from the use of notions borrowed from the amorphous solids framework (such us tunneling states, weak interference effects, variable range hopping, or spin glass) in order to explain certain physical properties observed in QCs. On the other hand, the absence of a general, full-fledged theory of quasiperiodic systems certainly makes it difficult to clearly distinguish the features related to short-range order atomic arrangements from those stemming from long-range order correlations. The contributions collected in this book aim at gaining a deeper understanding on the relationship between the underlying structural order and the resulting physical properties in several illustrative aperiodic systems, including the border line between QCs and related complex metallic alloys, hierarchical superlattices, electrical transmission lines, nucleic acid sequences, photonic quasicrystals, and optical devices based on aperiodic order designs.

nucleic acids --- aperiodic --- quasiperiodic --- fractal --- order --- disorder --- energy structure --- charge transport --- Mg-Zn-Gd alloys --- symmetrical rod phase --- quasicrystal --- morphologies and properties --- quasiperiodic order --- self-similarity --- quasiperiodic photonic micro/nanostructures --- fractal-like photonic micro/nanostructures --- quasiperiodic or fractal-like plasmonic structures --- non-periodic systems --- localization properties --- electrical transmission lines --- quasiperiodicity --- localization --- tight-binding model --- Kubo formula --- low-dimensional systems --- n/a

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The scientific study of complex systems has transformed a wide range of disciplines in recent years, enabling researchers in both the natural and social sciences to model and predict phenomena as diverse as earthquakes, global warming, demographic patterns, financial crises, and the failure of materials. In this book, Didier Sornette boldly applies his varied experience in these areas to propose a simple, powerful, and general theory of how, why, and when stock markets crash. Most attempts to explain market failures seek to pinpoint triggering mechanisms that occur hours, days, or weeks before the collapse. Sornette proposes a radically different view: the underlying cause can be sought months and even years before the abrupt, catastrophic event in the build-up of cooperative speculation, which often translates into an accelerating rise of the market price, otherwise known as a "bubble." Anchoring his sophisticated, step-by-step analysis in leading-edge physical and statistical modeling techniques, he unearths remarkable insights and some predictions--among them, that the "end of the growth era" will occur around 2050. Sornette probes major historical precedents, from the decades-long "tulip mania" in the Netherlands that wilted suddenly in 1637 to the South Sea Bubble that ended with the first huge market crash in England in 1720, to the Great Crash of October 1929 and Black Monday in 1987, to cite just a few. He concludes that most explanations other than cooperative self-organization fail to account for the subtle bubbles by which the markets lay the groundwork for catastrophe. Any investor or investment professional who seeks a genuine understanding of looming financial disasters should read this book. Physicists, geologists, biologists, economists, and others will welcome Why Stock Markets Crash as a highly original "scientific tale," as Sornette aptly puts it, of the exciting and sometimes fearsome--but no longer quite so unfathomable--world of stock markets.

Stocks --- Financial crises --- Prices --- History. --- United States. --- Asia. --- Black Monday. --- Dow Jones Industrial Average. --- Hong Kong. --- Latin America. --- Louis Bachelier. --- Nasdaq index. --- Nasdaq. --- Nikkei. --- Russia. --- South Sea bubble. --- anti-imitation. --- antibubble. --- arbitrage opportunities. --- bubble. --- collapse. --- complex systems. --- computational methods. --- cooperative behavior. --- cooperative speculation. --- crash hazard. --- currency crash. --- derivatives. --- discrete scale invariance. --- drawdown. --- efficient market. --- emergent markets. --- extreme events. --- financial crashes. --- finite-time singularity. --- forward prediction. --- fractals. --- free lunch. --- gold. --- hazard rate. --- hedging. --- herding. --- imitation. --- insurance portfolio. --- log-periodicity. --- market failure. --- natural scientists. --- outlier. --- population dynamics. --- positive feedback. --- power law. --- prediction. --- price-driven model. --- random walk. --- rational agent. --- renormalization group. --- returns. --- risk-driven model. --- risk. --- self-organization. --- self-similarity. --- social network. --- social scientists. --- speculative bubble. --- stock market crash. --- stock market indices. --- stock market prices. --- stock market. --- superhumans. --- sustainability. --- tronics boom. --- tulip mania. --- world economy.

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This book presents the latest findings on one of the most intensely investigated subjects in computational mathematics--the traveling salesman problem. It sounds simple enough: given a set of cities and the cost of travel between each pair of them, the problem challenges you to find the cheapest route by which to visit all the cities and return home to where you began. Though seemingly modest, this exercise has inspired studies by mathematicians, chemists, and physicists. Teachers use it in the classroom. It has practical applications in genetics, telecommunications, and neuroscience. The authors of this book are the same pioneers who for nearly two decades have led the investigation into the traveling salesman problem. They have derived solutions to almost eighty-six thousand cities, yet a general solution to the problem has yet to be discovered. Here they describe the method and computer code they used to solve a broad range of large-scale problems, and along the way they demonstrate the interplay of applied mathematics with increasingly powerful computing platforms. They also give the fascinating history of the problem--how it developed, and why it continues to intrigue us.

Traveling salesman problem. --- TSP (Traveling salesman problem) --- Combinatorial optimization --- Graph theory --- Vehicle routing problem --- AT&T Labs. --- Accuracy and precision. --- Addition. --- Algorithm. --- Analysis of algorithms. --- Applied mathematics. --- Approximation algorithm. --- Approximation. --- Basic solution (linear programming). --- Best, worst and average case. --- Bifurcation theory. --- Big O notation. --- CPLEX. --- CPU time. --- Calculation. --- Chaos theory. --- Column generation. --- Combinatorial optimization. --- Computation. --- Computational resource. --- Computer. --- Connected component (graph theory). --- Connectivity (graph theory). --- Convex hull. --- Cutting-plane method. --- Delaunay triangulation. --- Determinism. --- Disjoint sets. --- Dynamic programming. --- Ear decomposition. --- Engineering. --- Enumeration. --- Equation. --- Estimation. --- Euclidean distance. --- Euclidean space. --- Family of sets. --- For loop. --- Genetic algorithm. --- George Dantzig. --- Georgia Institute of Technology. --- Greedy algorithm. --- Hamiltonian path. --- Hospitality. --- Hypergraph. --- Implementation. --- Instance (computer science). --- Institute. --- Integer. --- Iteration. --- Linear inequality. --- Linear programming. --- Mathematical optimization. --- Mathematics. --- Model of computation. --- Neuroscience. --- Notation. --- Operations research. --- Optimization problem. --- Order by. --- Pairwise. --- Parameter (computer programming). --- Parity (mathematics). --- Percentage. --- Polyhedron. --- Polytope. --- Pricing. --- Princeton University. --- Processing (programming language). --- Project. --- Quantity. --- Reduced cost. --- Requirement. --- Result. --- Rice University. --- Rutgers University. --- Scientific notation. --- Search algorithm. --- Search tree. --- Self-similarity. --- Simplex algorithm. --- Solution set. --- Solver. --- Source code. --- Special case. --- Stochastic. --- Subroutine. --- Subsequence. --- Subset. --- Summation. --- Test set. --- Theorem. --- Theory. --- Time complexity. --- Trade-off. --- Travelling salesman problem. --- Tree (data structure). --- Upper and lower bounds. --- Variable (computer science). --- Variable (mathematics).

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The Special Issue “Radar and Sonar Imaging Processing” is a collection of 21 articles exploring many topics related to remote sensing with radar and sonar sensors. In this editorial, we present short introductions of the published articles. The series of articles in this SI deal with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends while making use of the latest developments in science, including artificial intelligence. It can be said that both radar and sonar imaging and processing still remain a “hot topic” and much research in this area is being conducted worldwide. New techniques and methods for extracting information from radar and sonar sensors and data have been proposed and verified. Some of these will stimulate further research while others have reached maturity and can be considered for industrial implementation and development.

radar --- fuzzy sets theory --- artificial neural network --- game theory --- safe ship trajectory --- computer simulation --- computer decision support --- underwater sonar image --- adaptive denoising --- detection --- adaptive initialization --- synthetic aperture sonar (SAS) --- multireceiver --- numerical evaluation --- numerical transfer function --- imaging algorithm --- X-Band radar --- marine radar current measurement --- quality control --- measurement reliability --- accuracies --- precision --- WaMoS® II --- vessel mounted acoustic Doppler current profiler --- autonomous surface vehicles --- anti-collision --- automotive radar --- target detection --- interferometric inverse synthetic aperture radar (InISAR) --- image registration --- translational motion parameters estimation --- strong scattering centers fusion --- terahertz radar imaging --- side-scan sonar image --- gray scale correction --- Retinex --- image enhancement --- side-scan sonar --- multibeam echo sounder --- initial image matching with constraint --- dense local self-similarity --- superimposition --- quadratic phase error --- SAR --- approximation --- spaceborne real-time SAR imaging --- orbit determination error --- synthetic aperture radar (SAR) --- low frequency --- high-resolution --- large bandwidth --- improved generalized chirp scaling (GCS) --- Lagrange inversion theorem --- range-dependent coupling --- complex Doppler ambiguity --- fast-maneuvering target refocusing --- non-uniform FFT (NUFFT) --- 1D scaled Fourier transform (1D SCFT) --- 3D sonar --- bathymetry --- data reduction --- autonomous navigation --- ground penetrating radar --- underground cavity detection network --- deep convolutional neural network --- automated underground object classification --- phase analysis --- super-resolution --- anti-drone systems --- FMCW radars --- drones detection --- radars calibration --- narrow-band radar --- target classification --- signal reconstruction --- features extraction --- weighted features fusion --- Synthetic Aperture Radar (SAR) --- focusing --- periodically gapped data --- complex deconvolution --- side scan sonar --- bottom tracking --- one-dimensional convolutional neural network --- signal recognition --- real-time processing --- space-borne SAR --- deceptive jamming --- Doppler sensor --- acoustic vector sensor --- road traffic monitoring --- water column image --- gas emissions --- automatic detection --- optical flow --- parallax --- cloud --- earth observation --- geostationary satellite --- meteorological radar --- MSG --- SEVIRI --- sonar --- data fusion --- sensor design --- target tracking --- target imaging --- image understanding --- target recognition