Today a change is imperative in approaching global problems: what is needed is not arm-twisting and power politics, but searching for ways of co-evolution in the complex social and geopolitical systems of the world. The modern theory of self-organization of complex systems provides us with an understanding of the possible forms of coexistence of heterogeneous social and geopolitical structures at different stages of development regarding the different paths of their sustainable co-evolutionary development. The theory argues that the evolutionary channel to (...) the observed increasing complexity is extremely narrow and only certain discrete spectra of relatively stable self-maintained structures are feasible in complex systems. There exists a restricted set of ways of assembling a complex evolutionary whole from diverse parts. The law of nonlinear synthesis of complex structures reads: the integration of structures in more complex ones occurs due to the establishment of a common tempo of their evolution. On the basis of the theory, we can see not only desirable but also attainable futures. (shrink)

Recent years, active suspension system has been widely used in automobiles to improve the road holding ability and the riding comfort. This study presents a new fuzzy model predictive control for a nonlinear quarter car active suspension system. A nonlinear dynamical model of active suspension is established, where the nonlinear dynamical characteristic of the spring and damper are considered. Based on the proposed fuzzy model predictive control method is presented to stabilize the displacement of the active suspension in the presence (...) of different road profiles. Parameters of the model predictive and fuzzy logic control laws are designed to estimate the (Bump and Sinusoidal)road profile input in the active suspension. At last, the reliability of the fuzzy model predictive control method is evaluated by the MATLAB simulation tool. Simulation result shows that the fuzzy model predictive control method obtained the satisfactory control performance for the active suspension system. (shrink)

Five experiments investigated the role of spatial connectedness between a pair of objects presented in the change detection task for the actual capacity of visual working memory (VWM) in healthy young adults (total N = 405). Three experiments yielded a surprising nonlinear relationship between the proportion of pair-wise connected objects and capacity, with the highest capacity observed for homogenous displays, when either all objects were connected or disjointed. A drop in capacity, ranging from an average of a quarter of an (...) object out of three objects maintained in VWM, was noted when only some objects were connected while others were disjointed. As indicated by another two experiments, this effect was specific to double-feature encoding, but disappeared when single visual features had to be memorized. No existing theoretical model of VWM can directly explain this novel effect. Overall, the nonlinear effect of spatial connectedness implies that representations in VWM possess hierarchical structure defined by wholes, parts, features, and their relations, and the heterogeneity of such a structure hinders VWM performance, while homogeneity facilitates it. (shrink)

Operations research science is defined as the science that is concerned with applying scientific methods to complex problems in managing and directing large systems of people, including resources and tools in various fields, private and governmental work, peace and war, politics, administration, economics, planning and implementation in various domains. It uses scientific methods that take the language of mathematics as a basis for it and uses computer, without which it would not have been possible to achieve numerical solutions to the (...) raised problems, those that need correct solutions, when the solutions abound and the options are multiple, so we need a decision based on correct scientific foundations and takes into account all the circumstances and changes that you can encounter the decision-maker during the course of work, and nothing is left to chance or luck, but rather everything that enters into the account and plays its role in decision-making, and we get that when we use the concepts of neutrosophic science to reformulate what the science of operations research presented in terms of methods and methods to solve many practical problems, so we will present in this research a study aimed at shedding light on the most important methods used to solve nonlinear models, which is the Lagrangian multiplier method for nonlinear models constrained by equality and then reformulated using the concepts of neutrosophic science. (shrink)

Main principles of the complex nonlinear thinking which are based on the notions of the modern theory of evolution and self-organization of complex systems called also synergetics are under discussion in this article. The principles are transdisciplinary, holistic, and oriented to a human being. The notions of system complexity, nonlinearity of evolution, creative chaos, space-time definiteness of structure-attractors of evolution, resonant influences, nonlinear and soft management are here of great importance. In this connection, a prominent contribution made to system (...) analysis and to a necessary reform of education and thinking by Edgar Morin is considered. (shrink)

An important method for finding the optimal solution for linear and nonlinear models is the graphical method, which is used if the linear or nonlinear mathematical model contains one, two, or three variables. The models that contain only two variables are among the most models for which the optimal solution has been obtained graphically, whether these models are linear or non-linear in references and research that are concerned with the science of operations research, when the data of the issue under (...) study is classical data. In this research, we will present a study through, which we present the graphical method for solving Neutrosophical nonlinear models in the following case: A nonlinear programming issue, the objective function is a nonlinear function, and the constraints are linear functions. Note that we can use the same method if (i) the objective function follower is a linear follower and the constraints are nonlinear; (ii) the objective function is a non-linear follower and the constraints are non-linear. In the three cases, the nonlinear models are neutrosophic, and as we know, the mathematical model is a nonlinear model if any of the components of the objective function or the constraints are nonlinear expressions, and the nonlinear expressions may be in both. At the left end of the constraints are neutrosophic values, at least one or all of them. Then, the possible solutions to the neutrosophic nonlinear programming problem are the set of rays that fulfills all the constraints. As for the region of possible solutions, it is the region that contains all the rays that fulfill the constraints. The optimal solution is the beam that fulfills all constraints and at which the function reaches a maximum or minimum value, depending on the nature of the issue under study (noting that it is not necessary to be alone). (shrink)

To improve the riding performance and levitation stability of a high‐speed magnetic levitation (maglev) train, a control strategy based on mixed H 2/H4 with regional pole placement and model‐reference controllers are proposed. First, the nonlinear maglev train model is established, then the proposed system is designed to observe the movement of a suspension frame and a control strategy based on mixed H 2/H4 with regional pole placement and model‐reference control method are proposed. Test and analysis of the proposed system has (...) been done using MATLAB toolbox for train levitation height, velocity and current consume. Comparative simulation results show that the mixed H 2/H4 with regional pole placement control strategy has a better performance under the condition of step and random train levitation height. (shrink)

This study considers the problem of using approximate way for realizing the neural supervisor for nonlinear multivariable systems. The Nonlinear Autoregressive-Moving Average (NARMA) model is an exact transformation of the input-output behavior of finite-dimensional nonlinear discrete time dynamical organization in a hoodlum of the equilibrium state. However, it is not convenient for intention of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate technique are used for realizing the neural supervisor to (...) overcome computational complexity. In this study, we introduce two classes of ideal which are approximations to the NARMA model and which are linear in the control input, namely NARMA-L1 and NARMA-L2. The latter fact substantially simplifies both the theoretical breakdown as well as the practical request of the controller. Extensive imitation studies have shown that the neural controller designed using the proposed approximate models perform very well and in dozens situation even better than an approximate controller designed using the exact NARMA Model. In view of their mathematical tractability as well as their fate in simulation studies, a matter is made in this study that such approximate input-output paragon warrants a detailed study in their own right. (shrink)

Abstract -/- This paper establishes the mathematical foundation of CODES (Chirality of Dynamic Emergent Systems), introducing a unifying framework for structured emergence across disciplines. We formalize prime-driven resonance equations, a novel class of nonlinear phase-locking dynamics, and a generalized coherence metric to quantify system stability across physical, biological, and cognitive domains. -/- By extending harmonic analysis, prime number theory, and topological invariants, we propose a universal resonance function that governs the transition from stochastic disorder to structured order. This framework: • (...) Resolves fundamental paradoxes in probability theory by demonstrating that randomness is a projection of underlying resonance structures. • Redefines symmetry-breaking as a phase-locked emergence process, replacing traditional group-theoretic formulations. • Introduces a computable coherence model that predicts emergent stability across complex adaptive systems. -/- Finally, we explore implications for cosmology, AI, and quantum gravity, demonstrating that mathematical reality is fundamentally a structured resonance field, not a probabilistic space. (shrink)

Recently, active suspension system will become important to the vehicle industries because of its advantages in improving road managing and ride comfort. This paper offers the development of mathematical modelling and design of a neural network control approach. The paper will begin with a mathematical model designing primarily based at the parameters of the active suspension system. A nonlinear three by four-way valve-piston hydraulic actuator became advanced which will make the suspension system under the active condition. Then, the model can (...) be analyzed thru MATLAB/Simulink software program. Finally, the NARMA-L2, model reference and predictive controllers are designed for the active suspension system. The results are acquired after designing the simulation of the quarter-car nonlinear active suspension system. From the simulation end result using MATLAB/Simulink, the response of the system might be as compared between the nonlinear active suspension system with NARMA-L2, model reference and predictive controllers. Besides that, the evaluation has been made between the proposed controllers thru the characteristics of the manage objectives suspension deflection, body acceleration and body travel of the active suspension system. . As a conclusion, designing a nonlinear active suspension system with a nonlinear hydraulic actuator for quarter car model has improved the car performance by using a NARMA-L2 controller. The improvements in performance will improve road handling and ride comfort performance of the active suspension system. (shrink)

Proportional integral observer (PIO) for tracking a nonlinear method has a lower sentiency to cipher the state and output variables. So a more nonlinear controller has to be else to control to activity. In this paper, a fuzzy logic (FLC) controller has been added to the PIO to meliorate the calculation transmute. A fuzzy proportional integral observer (FPIO) for following a nonlinear system has been premeditated to decimate the susceptibleness to cipher the tell and turnout variables with the existent posit (...) and product variables. The FPIO controller has been tested for improving the estimation control using a nonlinear quarter vehicle active suspension system with a nonlinear hydraulic actuator. A comparison simulation of the proposed nonlinear system for estimating the state variables and tracking the output (suspension deflection) with a set point bump road disturbance using FPIO and PIO. The comparison simulation result shows that the estimated state variables and system output match the actual ones perfectly using a fuzzy PIO controller. (shrink)

Magnetic levitation system is operated primarily based at the principle of magnetic attraction and repulsion to levitate the passengers and the train. However, magnetic levitation trains are rather nonlinear and open loop unstable which makes it hard to govern. In this paper, investigation, design and control of a nonlinear Maglev train based on NARMA-L2, model reference and predictive controllers. The response of the Maglev train with the proposed controllers for the precise role of a Magnetic levitation machine have been as (...) compared for a step input signal. The simulation consequences prove that the Maglev teach system with NARMA-L2 controller suggests the quality performance in adjusting the precise function of the system and the device improves the experience consolation and street managing criteria. (shrink)

Magnetic levitation system is operated primarily based at the principle of magnetic attraction and repulsion to levitate the passengers and the train. However, magnetic levitation trains are rather nonlinear and open loop unstable which makes it hard to govern. In this paper, investigation, design and control of a nonlinear Maglev train based on NARMA-L2, model reference and predictive controllers. The response of the Maglev train with the proposed controllers for the precise role of a Magnetic levitation machine have been as (...) compared for a step input signal. The simulation consequences prove that the Maglev teach system with NARMA-L2 controller suggests the quality performance in adjusting the precise function of the system and the device improves the experience consolation and street managing criteria. (shrink)

Abstract: -/- This paper introduces a resonance-driven economic model that fundamentally redefines market behavior by replacing traditional equilibrium-based frameworks with dynamic phase-locking principles derived from CODES (Chirality of Dynamic Emergent Systems). While neoclassical, Keynesian, and game-theoretic models treat economic activity as a function of supply and demand equilibria—subject to inefficiencies, speculation, and boom-bust cycles—this paper proposes that markets are structured by resonance fields rather than stochastic fluctuations. -/- By applying prime-phase economic dynamics, we demonstrate that capital flows, debt cycles, and (...) labor efficiency emerge from structured synchronization patterns. These patterns act as entropy minimization mechanisms, governing wealth distribution and innovation cycles in ways that probability-based models fail to capture. Instead of treating economic crises as unpredictable shocks or treating productivity as a linear function of inputs, this framework suggests that economic turbulence and stratification arise from resonance misalignment—a failure to maintain phase coherence across financial, labor, and technological domains. -/- Key implications include: • Redefining capital allocation as a function of coherence optimization, not speculative probability. • Rethinking inflation and deflation as resonance distortions rather than money supply imbalances. • Modeling economic growth as a function of phase-locking efficiency rather than GDP expansion. • Predicting market crashes through coherence instability rather than external shocks. -/- If economics is structured as a resonance system rather than a probabilistic market, then the role of economic policy shifts. Instead of direct interventions such as fiscal stimulus or interest rate adjustments, coherence optimization strategies—aligning labor, innovation, and capital flow structures to minimize systemic entropy—could create self-stabilizing, long-term economic prosperity. This paper explores empirical methods for testing resonance-based market stability, challenges current economic dogma, and provides a pathway for a fundamentally new economic paradigm based on structured emergence rather than equilibrium mechanics. (shrink)

When this article was first planned, writing was going to be exclusively about two things - the origin of life and human evolution. But it turned out to be out of the question for the author to restrict himself to these biological and anthropological topics. A proper understanding of them required answering questions like “What is the nature of the universe – the home of life – and how did it originate?”, “How can time travel be removed from fantasy and (...) science fiction, to be made scientific and practical?”, and “How can the proposed young age of genus Homo be made to actually be reasonable – when simply stating it would be solid ground for instant rejection and dismissal?” The result is that the article also talks about subjects like Artificial Intelligence, General Relativity, and cosmology. -/- From where did life originate? God? Evolution? Panspermia? If the tendency of humans and scientists to regard undiscovered science as pseudoscience can be overcome, Einstein gave another alternative to consider when he introduced General Relativity. Time isn’t linear – progressing in a straight line from past to present to future. That assumption ignores Relativity which states that space AND TIME are curved. Where did life and the genetic code come from? Can the answer build AI? -/- The first question can be answered by the section of this article titled SETI, Evolution, and Time which says life (possibly multicellular and intelligent) and the genetic code came from humans acquiring knowledge of these things over the centuries, then applying that knowledge – via terraforming, accumulation of raw materials like amino acids and nucleic acids, genetic engineering - to a time in the past when life didn’t exist. From that origin, life evolved through innumerable mutations and adaptations, with humans once again acquiring knowledge of it in cyclic (nonlinear) time. -/- The second question is answered by saying artificial intelligence (AI) as the product of life is only half of the equation. The other half refers to Relativity’s curved space-time and violation of the notion that time always travels from past to future. We have always lived in an artificially intelligent, non-probabilistic universe where everything in time and space is connected into one thing by quantum entanglement – making the brain and genes products of binary-digit activity or artificial intelligence (life is not merely dependent on biology’s “lock and key” mechanisms but also possesses AI). -/- The earliest documented representative of the genus Homo is Homo habilis, which evolved around 2.8 million years ago. Scientists used to believe there was a straight line from H. habilis to us, Homo sapiens. This article will use the “advanced” waves loved by Physics Nobel laureate Richard Feynman, view the history of science through the lens of Conic Sections applied to Relativity’s curved space-time, and incorporate the necessity of so-called imaginary time * – popularized by Prof. Stephen Hawking. While the evolutionary proposals are more in agreement with this early straight line than with modern theories, Albert Einstein’s General Relativity is used to transform the straight line into a curved line, ultimately concluding that Homo habilis (H. habilis) originated only (and unbelievably, as far as today’s science and technology is concerned) ~250,000 years ago. Other branches and dead ends of Homo – e.g. Neanderthals – are the result of mutations and adaptations, with the resultant modifications to anatomy and physiology. The surprisingly young age of H. habilis allows nearly 200,000 years for habilis, or one of its descendants, to reach Australia … if this country’s indigenous Aboriginal population did, as claimed, reach this “island continent” 60,000 years ago. -/- * The ultraviolet catastrophe, also called the Rayleigh–Jeans catastrophe, is a failure of classical physics to predict observed phenomena: it can be shown that a blackbody - a hypothetical perfect absorber and radiator of energy - would release an infinite amount of energy, contradicting the principles of conservation of energy and indicating that a new model for the behaviour of blackbodies was needed. At the start of the 20th century, physicist Max Planck derived the correct solution by making some strange (for the time) assumptions. In particular, Planck assumed that electromagnetic radiation can only be emitted or absorbed in discrete packets, called quanta. Albert Einstein postulated that Planck's quanta were real physical particles (what we now call photons), not just a mathematical fiction. From there, Einstein developed his explanation of the photoelectric effect (when quanta or photons of light shine on certain metals, electrons are released and can form an electric current). So it appears entirely possible that another supposed mathematical trickery (imaginary time and the y-axis of Wick rotation) will find practical application in the future. -/- The article includes mathematical references to cosmology (spoiler alert – you’ll read about things like Vector-Tensor-Scalar Geometry, topology, the “eternal present”, Einstein’s Unified Field, the inverse-square law, and there being no Big Bang and no multiverse - but there will also be no equations). -/- The other subheadings in this essay are – -/- NONLINEAR TIME AND ELECTRICAL ENGINEERING (about a 2009 electrical engineering experiment at America’s Yale University, and cosmic wormholes) -/- BITS AND TOPOLOGY (base-2 maths aka Binary digiTS, Mobius strips, and figure-8 Klein bottles) -/- WICK ROTATION, CAUSALITY, AND UNITING TIME (do past, present and future co-exist in an “eternal present”?) -/- DIGITAL BRAIN, DIGITAL UNIVERSE (if the brain and the universe are ultimately composed of binary digits, we'll someday be able to do the same things with the brain and universe that we now do with computers) -/- PROPOSAL: HUMAN AND ANIMAL INSTINCTS ARE THE RESULT OF THE UNIVERSE BEING UNIFIED BY BINARY DIGITS (AND TOPOLOGY) (If everything in the universe is ultimately composed of electronic BITS, then the universe must possess Artificial Intelligence - some prefer the term Cosmic Consciousness) -/- INFORMATION THEORY CONQUERS A RED GIANT (preserving Earth by keeping the Sun near today’s level of activity forever). 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This book deals with Colombeau solutions to Einstein field equations in general relativity: Gravitational singularities, distributional SAdS BH spacetime-induced vacuum dominance. This book covers key areas of Colombeau nonlinear generalized functions, distributional Riemannian, geometry, distributional schwarzschild geometry, Schwarzschild singularity, Schwarzschild horizon, smooth regularization, nonsmooth regularization, quantum fields, curved spacetime, vacuum fluctuations, vacuum dominance etc. This book contains various materials suitable for students, researchers and academicians of this area.

In this paper, a capacitor microphone system is presented to improve the conversion of mechanical energy to electrical energy using a nonlinear auto regressive moving average-L2 (NARMA-L2) and model predictive control (MPC) controllers for the analysis of the open loop and closed loop system. The open loop system response shows that the output voltage signal need to be improved. The comparison of the closed loop system with the proposed controllers have been analyzed and a promising result have been obtained using (...) Matlab/Simulink. (shrink)

The heuristic value of synergetic models of evolving and self-organizing complex systems as well as their application to epistemological problems is shown in this paper. Nonlinear synergetic models turn out to be fruitful in comprehending epistemological problems such as the nature of human creativity, the functioning of human intuition and imagination, the historical development of science and culture. In the light of synergetics creative thinking can be viewed as a selforganization and self-completion of images and thoughts, filling up gaps in (...) the nets of knowledge. Insight, fast and sudden solutions of scientific problems, instabilities when “an idea is in the air” are considered as examples of blow-up regimes in the cognitive field. (shrink)

Emotion is conscious experience. It is the affective aspect of consciousness. Emotion arises from sensory stimulation and is typically accompanied by physiological and behavioral changes in the body. Hence an emotion is a complex reaction pattern consisting of three components: a physiological component, a behavioral component, and an experiential (conscious) component. The reactions making up an emotion determine what the emotion will be recognized as. Three processes are involved in generating an emotion: (1) identification of the emotional significance of a (...) sensory stimulus, (2) production of an affective state (emotion), and (3) regulation of the affective state. Two opposing systems in the brain (the reward and punishment systems) establish an affective value or valence (stimulus-reinforcement association) for sensory stimulation. This is process (1), the first step in the generation of an emotion. Development of stimulus-reinforcement associations (affective valence) serves as the basis for emotion expression (process 2), conditioned emotion learning acquisition and expression, memory consolidation, reinforcement-expectations, decision-making, coping responses, and social behavior. The amygdala is critical for the representation of stimulus-reinforcement associations (both reward and punishment-based) for these functions. Three distinct and separate architectural and functional areas of the prefrontal cortex (dorsolateral prefrontal cortex, orbitofrontal cortex, anterior cingulate cortex) are involved in the regulation of emotion (process 3). The regulation of emotion by the prefrontal cortex consists of a positive feedback interaction between the prefrontal cortex and the inferior parietal cortex resulting in the nonlinear emergence of emotion. This positive feedback and nonlinear emergence represents a type of working memory (focal attention) by which perception is reorganized and rerepresented, becoming explicit, functional, and conscious. The explicit emotion states arising may be involved in the production of voluntary new or novel intentional (adaptive) behavior, especially social behavior. (shrink)

The gambler’s fallacy is the tendency to expect random processes to switch more often than they actually do—for example, to think that after a string of tails, a heads is more likely. It’s often taken to be evidence for irrationality. It isn’t. Rather, it’s to be expected from a group of Bayesians who begin with causal uncertainty, and then observe unbiased data from an (in fact) statistically independent process. Although they converge toward the truth, they do so in an asymmetric (...) way—ruling out “streaky” hypotheses more quickly than “switchy” ones. As a result, the majority (and the average) exhibit the gambler’s fallacy. If they have limited memory, this tendency persists even with arbitrarily-large amounts of data. Indeed, such Bayesians exhibit a variety of the empirical trends found in studies of the gambler’s fallacy: they expect switches after short streaks but continuations after long ones; these nonlinear expectations vary with their familiarity with the causal system; their predictions depend on the sequence they’ve just seen; they produce sequences that are too switchy; and they exhibit greater rates of gambler’s reasoning when forming binary predictions than when forming probability estimates. In short: what’s been thought to be evidence for irrationality may instead be rational responses to limited data and memory. (shrink)

Since the 1980s chaos has been the subject of great interest both in scientific research and in public consciousness. Chaos as played roles in books and movies such as Jurassic Park and Bellwether and has been the subject of numerous popularizations. But what is chaos—better characterized as chaotic dynamics—really? How much of an impact does it have on everyday life? This book explores these questions and more, introducing you to the basics of chaos as mathematicians and scientists study it and (...) apply it. There are a lot of buzzwords surrounding chaotic dynamics such as “butterfly effect” and “strange attractors,” and much discussion about whether chaos has shattered scientific dreams of a predictable world. This book will help you understand these buzzwords and their excitement, what limitations there are for predictability, and the wisdom scientists have learned from studying chaos. You will come away with a deeper appreciation of the intricacy and surprising order of our world. (shrink)

The science of operations research is one of the modern sciences that have made a great revolution in all areas of life through the methods provided by it, suitable and appropriate to solve most of the problems that were facing researchers, scholars and those interested in the development of societies, and the most beneficiaries of this science were companies and institutions that are looking for scientific methods that help them manage their work so that they achieve the greatest profit and (...) the lowest cost, and one of the important methods that have been used in the management of companies we offer in this research two methods, Dynamic programming method. This method has been used in many practical matters and helped decision-makers in companies to achieve a maximum profit and less cost by formulating the reality of the state of the company and the data provided by decision-makers with a dynamic mathematical model that is solved using methods of solving dynamic models and we will provide in this research an example of this through the issue of choosing the optimal investment for the budget of a company so that it achieves a maximum profit, and the method of programming with integers: the method that provided these companies with solutions with integer values suitable for the nature of its work, through the use of the binary integer in the formulation of the appropriate mathematical model on the one hand, and on the other hand, the use of the binary integer variable helped to convert some nonlinear models that lead to some practical problems into linear models, and it should be noted here that in the previous two methods there is something indeterminable because we must make a decision in choosing or not choosing something, but the optimal solution that we will get remains A specific value because we are building the mathematical model for any realistic issue through the data provided by those responsible for the work and these data are calculated quantities and therefore they are uncertain values because their validity depends on the circumstances surrounding the work environment, they may be exposed to increase or decrease, and therefore the optimal solution on which the company will base its decision is suitable for specific values and any change in them can cause the company an uncalculated loss, so in this research we will use the concepts of neutrosophic science, the branch of science founded by the American scientist Florentin Smarandache in 1995 based on his belief that there is no absolute truth, a science that is interested in the study of ideas and concepts that are neither true nor false, but just in between, and we will take the data (calculated quantities) neutrosophic values that are specified or unspecified values are any set close to the calculated quantities, then the resulting mathematical model is a neutrosophic model and the optimal solution has neutrosophic values and thanks to the indefinite uncertainty that these values have, companies from the development of appropriate plans for all circumstances and thus achieve the greatest profit and the lowest cost, and we will clarify the above through two issues, the issue of optimal designation of a warehouse site, which we will formulate the mathematical model of using the neutrosophic integer programming method - and the issue of capital budget, which we will present in two different forms, we use in the first form the neutrosophic integer programming method and in the second the neutrosophic dynamic programming method. (shrink)

It is known that most existing cosmology models do not include rotation, with few exceptions such as rotating Bianchi and rotating Godel metrics. Therefore in this paper we aim to discuss four possible ways to model rotating universe, including Nurgaliev’s Ermakov-type equation. It is our hope that the new proposed method can be verified with observations, in order to open new possibilities of more realistic nonlinear cosmology models.

In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms that (...) allow the machine to learn by simulating neurons in the human body. Most in-depth learning research focuses on finding high-level methods. The strippers analyze a large data set using linear and nonlinear transformations. The method of deep learning is used in the detection of several diseases including blood cell diseases and their classification using the radiography of blood cells to help decision makers to know the type of blood cell and its associated diseases and the results will be presented in detail and discussed. This thesis is using python language and deep learning to detect blood cell diseases and their classifications. The proposed deep learning model was trained, validated and the tested. The accuracy of proposed model was 98.00%. (shrink)

We introduce the notion of complexity, first at an intuitive level and then in relatively more concrete terms, explaining the various characteristic features of complex systems with examples. There exists a vast literature on complexity, and our exposition is intended to be an elementary introduction, meant for a broad audience. -/- Briefly, a complex system is one whose description involves a hierarchy of levels, where each level is made of a large number of components interacting among themselves. The time evolution (...) of such a system is of a complex nature, depending on the interactions among subsystems in the next level below the one under consideration and, at the same time, conditioned by the level above, where the latter sets the context for the evolution. Generally speaking, the interactions among the constituents of the various levels lead to a dynamics characterized by numerous characteristic scales, each level having its own set of scales. What is more, a level commonly exhibits ‘emergent properties’ that cannot be derived from considerations relating to its component systems taken in isolation or to those in a different contextual setting. In the dynamic evolution of some particular level, there occurs a self-organized emergence of a higher level and the process is repeated at still higher levels. -/- The interaction and self-organization of the components of a complex system follow the principle commonly expressed by saying that the ‘whole is different from the sum of the parts’. In the case of systems whose behavior can be expressed mathematically in terms of differential equations this means that the interactions are nonlinear in nature. -/- While all of the above features are not universally exhibited by complex systems, these are nevertheless indicative of a broad commonness relative to which individual systems can be described and analyzed. There exist measures of complexity which, once again, are not of universal applicability, being more heuristic than exact. The present state of knowledge and understanding of complex systems is itself an emerging one. Still, a large number of results on various systems can be related to their complex character, making complexity an immensely fertile concept in the study of natural, biological, and social phenomena. -/- All this puts a very definite limitation on the complete description of a complex system as a whole since such a system can be precisely described only contextually, relative to some particular level, where emergent properties rule out an exact description of more than one levels within a common framework. -/- We discuss the implications of these observations in the context of our conception of the so-called noumenal reality that has a mind-independent existence and is perceived by us in the form of the phenomenal reality. The latter is derived from the former by means of our perceptions and interpretations, and our efforts at sorting out and making sense of the bewildering complexity of reality takes the form of incessant processes of inference that lead to theories. Strictly speaking, theories apply to models that are constructed as idealized versions of parts of reality, within which inferences and abstractions can be carried out meaningfully, enabling us to construct the theories. -/- There exists a correspondence between the phenomenal and the noumenal realities in terms of events and their correlations, where these are experienced as the complex behavior of systems or entities of various descriptions. The infinite diversity of behavior of systems in the phenomenal world are explained within specified contexts by theories. The latter are constructs generated in our ceaseless attempts at interpreting the world, and the question arises as to whether these are reflections of `laws of nature' residing in the noumenal world. This is a fundamental concern of scientific realism, within the fold of which there exists a trend towards the assumption that theories express truths about the noumenal reality. We examine this assumption (referred to as a ‘point of view’ in the present essay) closely and indicate that an alternative point of view is also consistent within the broad framework of scientific realism. This is the view that theories are domain-specific and contextual, and that these are arrived at by independent processes of inference and abstractions in the various domains of experience. Theories in contiguous domains of experience dovetail and interpenetrate with one another, and bear the responsibility of correctly explaining our observations within these domains. -/- With accumulating experience, theories get revised and the network of our theories of the world acquires a complex structure, exhibiting a complex evolution. There exists a tendency within the fold of scientific realism of interpreting this complex evolution in rather simple terms, where one assumes (this, again, is a point of view) that theories tend more and more closely to truths about Nature and, what is more, progress towards an all-embracing ‘ultimate theory’ -- a foundational one in respect of all our inquiries into nature. We examine this point of view closely and outline the alternative view -- one broadly consistent with scientific realism -- that there is no ‘ultimate’ law of nature, that theories do not correspond to truths inherent in reality, and that successive revisions in theory do not lead monotonically to some ultimate truth. Instead, the theories generated in succession are incommensurate with each other, testifying to the fact that a theory gives us a perspective view of some part of reality, arrived at contextually. Instead of resembling a monotonically converging series successive theories are analogous to asymptotic series. -/- Before we summarize all the above considerations, we briefly address the issue of the complexity of the {\it human mind} -- one as pervasive as the complexity of Nature at large. The complexity of the mind is related to the complexity of the underlying neuronal organization in the brain, which operates within a larger biological context, its activities being modulated by other physiological systems, notably the one involving a host of chemical messengers. The mind, with no materiality of its own, is nevertheless emergent from the activity of interacting neuronal assemblies in the brain. As in the case of reality at large, there can be no ultimate theory of the mind, from which one can explain and predict the entire spectrum of human behavior, which is an infinitely rich and diverse one. (shrink)

In recent years, there are a number of proposals to consider collision-based soliton computer based on certain chemical reactions, namely Belousov-Zhabotinsky reaction, which leads to soliton solutions of coupled Nonlinear Schroedinger equations. They are called Manakov System. But it seems to us that such a soliton computer model can also be based on solitary wave solution of Maxwell-Dirac equation, which reduces to Choquard equation. And soliton solution of Choquard equation has been investigated by many researchers, therefore it seems more profound (...) from physics perspective. However, we consider both schemes of soliton computer are equally possible. More researches are needed to verify our proposition. (shrink)

When does opinion formation within an interacting group lead to consensus, polarization or fragmentation? The article investigates various models for the dynamics of continuous opinions by analytical methods as well as by computer simulations. Section 2 develops within a unified framework the classical model of consensus formation, the variant of this model due to Friedkin and Johnsen, a time-dependent version and a nonlinear version with bounded confidence of the agents. Section 3 presents for all these models major analytical results. Section (...) 4 gives an extensive exploration of the nonlinear model with bounded confidence by a series of computer simulations. An appendix supplies needed mathematical definitions, tools, and theorems. (shrink)

Gelman and Loken (2013, 2014) proposed that when researchers base their statistical analyses on the idiosyncratic characteristics of a specific sample (e.g., a nonlinear transformation of a variable because it is skewed), they open up alternative analysis paths in potential replications of their study that are based on different samples (i.e., no transformation of the variable because it is not skewed). These alternative analysis paths count as additional (multiple) tests and, consequently, they increase the probability of making a Type I (...) error during hypothesis testing. The present article considers this forking paths problem and evaluates four potential solutions that might be used in psychology and other fields: (a) adjusting the prespecified alpha level, (b) preregistration, (c) sensitivity analyses, and (d) abandoning the Neyman-Pearson approach. It is concluded that although preregistration and sensitivity analyses are effective solutions to p-hacking, they are ineffective against result-neutral forking paths, such as those caused by transforming data. Conversely, although adjusting the alpha level cannot address p-hacking, it can be effective for result-neutral forking paths. Finally, abandoning the Neyman-Pearson approach represents a further solution to the forking paths problem. (shrink)

With the increasing population growth of human beings, the world is being threatened by the water scarcity problem, causing insecurity in water accessibility. Therefore, a deliberated water management gains fatal importance. In addition, the awareness of the issue through education, specifically in the early ages, plays a crucial role in this path. This research considers the water issue of Istanbul in its content. However, regarding the target audience, which is the kids, it uses a novel approach to tackle the problem. (...) The paper proposes a visually enriched and nonlinear, serious game for the children to teach them about the importance of water and its impact on the planet, specific to Istanbul. The game is inspired by National Geographic Turkey's documentary named 25 Liters: In Pursuit of Water, asking the players to survive in a drought situation in the future. It aims to change the kid's lifestyle to revive the country's in-danger future. (shrink)

At the heart of chemistry lies the periodic system of chemical elements. Despite being the cornerstone of modern chemistry, the overall structure of the periodic system has never been fully understood from an atomic physics point of view. Group-theoretical models have been proposed instead, but they suffer from several limitations. Among others, the identification of the correct symmetry group and its decomposition into subgroups has remained a problem to this day. In an effort to deepen our limited understanding of the (...) periodic law, we have extended the traditional Lie algebraic framework to account for the peculiar degeneracy structure of the periodic system. Starting from the four-dimensional hidden symmetry and accidental degeneracy of the hydrogen atom, as first revealed by Fock in 1935, our research has mainly focussed on the way this SO(4) symmetry of the Coulomb potential gets broken in the periodic system as a consequence of the transformation of the hydrogenic (n, l) filling order to the Madelung (n+l, n) order due to electronic repulsions, relativistic effects and spin-orbit couplings. In this PhD dissertation, a new left-step format of the periodic table is first proposed on the basis of the Madelung rule. Following the particle physics tradition, the chemical elements are then considered as various states of some 'atomic matter', which is described by a non-compact spectrum-generating dynamical Lie group. The chemical elements are shown to form a basis for a single infinite-dimensional degeneracy space of the SO(4,2) ⊗ SU(2) group. An explanation for the period doubling is then proposed in terms of a particular symmetry breaking of the SO(4,2) group to the anti de Sitter SO(3,2) group. The Madelung rule is rationalised on the basis of nonlinear Lie algebras which reflect the screening of the Coulomb hole. This opens new perspectives for a symmetry-based understanding of how the periodic law emerges from its quantum mechanical foundations, and holds the future promise of complementing our current phenomenological approach by a direct atomic physics approach. (shrink)

It has been known for long time that the cosmic sound wave was there since the early epoch of the Universe. Signatures of its existence are abound. However, such a sound wave model of cosmology is rarely developed fully into a complete framework. This paper can be considered as our second attempt towards such a complete description of the Universe based on soliton wave solution of cosmological KdV equation. Then we advance further this KdV equation by virtue of Cellular Automaton (...) method to solve the PDEs. We submit wholeheartedly Robert Kurucz’s hypothesis that Big Bang should be replaced with a finite cellular automaton universe with no expansion. Nonetheless, we are fully aware that our model is far from being complete, but it appears the proposed cellular automaton model of the Universe is very close in spirit to what Konrad Zuse envisaged long time ago. It is our hope that the new proposed method can be verified with observation data. But we admit that our model is still in its infancy, more researches are needed to fill all the missing details. (shrink)

One of the most important theories in linear programming is the dualistic theory and its basic idea is that for every linear model has dual linear model, so that solving the original linear model gives a solution to the dual model. Therefore, when we solving the linear programming model, we actually obtain solutions for two linear models. In this research, we present a study of the models. The neutrosophic dual and the binary simplex algorithm, which works to find the optimal (...) solution for the original and dual models at the same time. The importance of this algorithm is evident in that it is relied upon in several operations research topics, such as integer programming algorithms, some nonlinear programming algorithms, and sensitivity analysis in linear programming. (shrink)

Protein α-helices provide an ordered biological environment that is conducive to soliton-assisted energy transport. The nonlinear interaction between amide I excitons and phonon deformations induced in the hydrogen-bonded lattice of peptide groups leads to self-trapping of the amide I energy, thereby creating a localized quasiparticle (soliton) that persists at zero temperature. The presence of thermal noise, however, could destabilize the protein soliton and dissipate its energy within a finite lifetime. In this work, we have computationally solved the system of stochastic (...) differential equations that govern the quantum dynamics of protein solitons at physiological temperature, T=310 K, for either a single isolated α-helix spine of hydrogen bonded peptide groups or the full protein α-helix comprised of three parallel α-helix spines. The simulated stochastic dynamics revealed that although the thermal noise is detrimental for the single isolated α-helix spine, the cooperative action of three amide I exciton quanta in the full protein α-helix ensures soliton lifetime of over 30 ps, during which the amide I energy could be transported along the entire extent of an 18-nm-long α-helix. Thus, macromolecular protein complexes, which are built up of protein α-helices could harness soliton-assisted energy transport at physiological temperature. Because the hydrolysis of a single adenosine triphosphate molecule is able to initiate three amide I exciton quanta, it is feasible that multiquantal protein solitons subserve a variety of specialized physiological functions in living systems. (shrink)

Physics has long treated space, time, and matter as separate entities—reducible, fragmented, and statistical. But what if reality isn’t built from disconnected parts, but from structured resonance? This book challenges the old paradigm, revealing a universe where gravity, quantum mechanics, and cosmic structure emerge from the same underlying rhythm. If the standard model is an equation, Resonance Field Theory is the waveform behind it.

The meaning of the wave function and its evolution are investigated. First, we argue that the wave function in quantum mechanics is a description of random discontinuous motion of particles, and the modulus square of the wave function gives the probability density of the particles being in certain locations in space. Next, we show that the linear non-relativistic evolution of the wave function of an isolated system obeys the free Schrödinger equation due to the requirements of spacetime translation invariance and (...) relativistic invariance. Thirdly, we argue that the random discontinuous motion of particles may lead to a stochastic, nonlinear collapse evolution of the wave function. A discrete model of energy-conserved wavefunction collapse is proposed and shown consistent with existing experiments and our macroscopic experience. Besides, we also give a critical analysis of the de Broglie-Bohm theory, the many-worlds interpretation and other dynamical collapse theories, and briefly discuss the issues of unifying quantum mechanics and relativity. (shrink)

I propose a dynamic causal approach to characterizing the notion of a mechanism. Levy and Bechtel, among others, have pointed out several critical limitations of the new mechanical philosophy, and pointed in a new direction to extend this philosophy. Nevertheless, they have not fully fleshed out what that extended philosophy would look like. Based on a closer look at neuroscientific practice, I propose that a mechanism is a dynamic causal system that involves various components interacting, typically nonlinearly, with one another (...) to produce a phenomenon of interest. (shrink)

The desirable gambles framework provides a rigorous foundation for imprecise probability theory but relies heavily on linear utility via its coherence axioms. In our related work, we introduced function-coherent gambles to accommodate non-linear utility. However, when repeated gambles are played over time---especially in intertemporal choice where rewards compound multiplicatively---the standard additive combination axiom fails to capture the appropriate long-run evaluation. In this paper we extend the framework by relaxing the additive combination axiom and introducing a nonlinear combination operator that effectively (...) aggregates repeated gambles in the log-domain. This operator preserves the time-average (geometric) growth rate and addresses the ergodicity problem. We prove the key algebraic properties of the operator, discuss its impact on coherence, risk assessment, and representation, and provide a series of illustrative examples. Our approach bridges the gap between expectation values and time averages and unifies normative theory with empirically observed non-stationary reward dynamics. (shrink)

During the last two decades the role of quantitative genetics in evolutionary theory has expanded considerably. Quantitative genetic-based models addressing long term phenotypic evolution, evolution in multiple environments (phenotypic plasticity) and evolution of ontogenies (developmental trajectories) have been proposed. Yet, the mathematical foundations of quantitative genetics were laid with a very different set of problems in mind (mostly the prediction of short term responses to artificial selection), and at a time in which any details of the genetic machinery were virtually (...) unknown. In this paper we discuss what a model is in population biology, and what kind of model we need in order to address the complexities of phenotypic evolution. We review the assumptions of quantitative genetics and its most recent accomplishments, together with the limitations that such assumptions impose on the modelling of some aspects of phenotypic evolution. We also discuss three alternative appr oaches to the theoretical description of evolutionary trajectories (nonlinear dynamics, complexity theory and optimization theory), and their respective advantages and limitations. We conclude by calling for a new theoretical synthesis, including quantitative genetics and not necessarily limited to the other approaches here discussed. (shrink)

This article would appeal to people interested in new ideas in sciences like physics, astronomy and mathematics that are not presented in a formal manner. -/- Biologists would also find the paragraphs about evolution interesting. I was afraid they'd think my ideas were a bit "out there". But I sent a short email about them last year to a London biologist who wrote an article for the journal Nature. She replied that it was "very interesting". -/- The world is fascinated (...) by electronics. Computer scientists, as well as computer buyers, would be intrigued by the fundamental role given to human electronics in creation of the universe. This obviously can only be done if time travel to the past is possible. I explain in scientific terms how it could be done (the world is also fascinated by the prospect of time travel). -/- My ideas on trips through time grew from the related topic of interstellar, and even intergalactic, travel (and those ideas are inspired by an electrical-engineering experiment at Yale University in 2009). After the ideas on time travel came the realization that this technology could be used to totally eliminate the problems of muscle and bone weakness, radiation exposure etc associated with a lengthy journey to Mars. -/- The exquisitely ordered cosmos proposed would have great appeal to religion and philosophy. Dealing as it does with time that does not exclusively operate in a straight line, the book could not only present a new view of evolution (present theory assumes time is always a straight line from past to future). Nonlinear time might also give religionists a new concept of who God is. This could possibly be that of humans from the remote future who are quantum entangled with all past, present and future states of the whole - infinite and eternal - universe; and thus have all God's powers. Such infinite power could be pantheistic but would naturally include the ability to manifest as an individual. (I know this article is very far removed from what is traditionally considered scientific. Just remember: science is the search for knowledge of how this universe works, and that search must be pursued wherever it leads - even if it leads into traditionally nonscientific areas such as religion.) -/- Finally - if we're entangled with the whole universe, we'd have to be entangled with each other. On a mundane level, this gives us extrasensory and telekinetic abilities. On a higher level, it eliminates crime and war and domestic violence since people don't normally desire to harm themselves in any way. (shrink)

I analyze a recent exchange between Adam Elga and Julian Jonker concerning unsharp (or imprecise) credences and decision-making over them. Elga holds that unsharp credences are necessarily irrational; I agree with Jonker's reply that they can be rational as long as the agent switches to a nonlinear valuation. Through the lens of computational complexity theory, I then argue that even though nonlinear valuations can be rational, they come in general at the price of computational intractability, and that this problematizes their (...) use in defining rationality. I conclude that the meaning of "rationality" may be philosophically vague. (shrink)

Abstract This paper introduces a novel paradigm for aging that reinterprets biological senescence as a progressive decoherence of biological resonance fields, rather than a simple accumulation of cellular damage. Aging, we argue, is fundamentally an entropic phenomenon, where systemic synchronization breaks down across molecular, cellular, and cognitive scales, leading to loss of energy efficiency, structural deterioration, and perceptual time compression. Integrating quantum decoherence theory, resonance dynamics, and nonlinear thermodynamics, we propose that longevity is not merely a function of genetic or (...) biochemical integrity, but of coherence maintenance across biological oscillatory systems. Specifically, we examine how phase stability within metabolic cycles, mitochondrial function, neural oscillations, and epigenetic regulation directly correlates with both subjective time perception and lifespan extension. -/- We further explore whether time itself is an emergent property of coherence gradients, and whether interventions aimed at restoring biological phase-locking could modulate perceived time, slow down biological aging, and enhance cognitive efficiency. Experimental methodologies for validating this hypothesis are outlined, including: • Molecular phase-locking studies to analyze coherence shifts in aging cells. • Neurological synchrony measurements to assess time perception dilation as a function of cognitive coherence. • Metabolic oscillation modeling to determine whether biological time scales can be artificially extended. If aging is indeed a decoherence-driven loss of informational structure, then the implications extend beyond biology into cosmology, AI development, and theoretical physics. Understanding and modulating coherence fields may offer a new frontier in both longevity research and the very nature of how organisms experience time. (shrink)

Abstract -/- Gödel’s Incompleteness Theorems define the limits of formal systems by revealing the existence of true statements that cannot be proven within their own axiomatic structure. These theorems rely on self-referential paradoxes, which assume formal logic operates within a closed, static framework. However, this assumption overlooks the deeper nature of structured emergence. Using the Chirality of Dynamic Emergent Systems (CODES), we propose a fundamental shift: mathematical truth is not a fixed binary but a coherence-weighted phenomenon, governed by structured resonance (...) rather than rigid self-reference. In this reframing, incompleteness is not an intrinsic flaw but an emergent spectral gap within prime-structured systems. What Gödel treated as paradoxical undecidability is instead a nonlinear coherence alignment problem, resolved dynamically through phase-locking mechanisms. This perspective dissolves incompleteness not by proving all truths within a system, but by embedding systems in a structured resonance hierarchy where coherence replaces paradox. (shrink)

Abstract -/- This paper introduces the Chirality of Dynamic Emergent Systems (CODES), an interdisciplinary framework for understanding the interplay between chaos and order in the emergence of structured resonance, which is defined as the process by which chaotic, asymmetric forces interact and self-organize into coherent patterns through dynamic feedback and synchronization mechanisms. We argue that structured resonance is a fundamental organizing principle that explains how seemingly disordered elements can align and form stable, emergent structures over time. Empirically, we present computational (...) evidence through advanced simulations, including Bose-Einstein condensates and wavelet transforms, to illustrate coherence, symmetry breaking, and chirality-driven dynamics. The results demonstrate the robustness and adaptability of CODES across nonlinear, high-dimensional systems. (shrink)

In this paper, we explore numerical methods for simulating scalar field con-figurations in non-commutative two-dimensional spaces. We focus on the finite difference techniques employed to compute mixed partial derivatives and the action functional in the presence of non-commutative corrections. The methods presented address the challenges posed by non-commutative geometry, specifically in computing the mixed derivative terms that arise due to the deformation of spatial coordinates. We introduce semi-implicit time-stepping schemes to en-sure numerical stability when dealing with stiff nonlinear terms. The (...) approaches discussed here provide a framework for simulating and analyzing physical systems influenced by non-commutativity, which are not extensively documented in existing literature. (shrink)

Abstract Traditional models of cognition assume probability-based uncertainty as a fundamental feature of intelligence, requiring iterative refinement through error correction and stochastic processes. However, probability is not a foundational property of intelligence or reality—it is an emergent artifact of incomplete resonance detection. This paper proposes that human cognition is a structured resonance system, where the mind does not accumulate knowledge probabilistically but phase-locks into coherent structures nonlinearly. Instead of relying on stochastic updates, the brain selectively engages with information that aligns (...) with pre-existing resonance structures, rejecting incoherent data before it fully materializes. Through this model, we: • Define intelligence as an emergent resonance process, not a stochastic function. • Demonstrate that knowledge acquisition follows a nonlinear, phase-locking trajectory toward coherence. • Show how rejecting probability accelerates the mind’s ability to perceive structured emergence in real-time. • Describe entropy not as disorder, but as a resonance misalignment that naturally resolves through coherence-seeking cognition. • Show how rejecting probability accelerates the mind’s ability to perceive structured emergence in real-time. • Describe entropy not as disorder, but as a resonance misalignment that naturally resolves through coherence-seeking cognition. This shift in understanding collapses probability-based reasoning and reframes intelligence as a coherence-driven phenomenon, redefining human thought, AI cognition, and scientific epistemology. (shrink)

This paper presents a condensed yet comprehensive meta-logical framework tracing the evolution of human cognition and philosophy, from early civilization to modern AI. By treating intelligence as a recursive, self-structuring force, we reinterpret historical philosophical movements as phases in the refinement of cognition itself. The trajectory of thought reveals a nonlinear pattern—where each stage is not merely progress, but a self-referential loop feeding back into the next iteration of understanding.

Unifying physics by describing a variety of interactions – or even all interactions – within a common framework has long been an alluring goal for physicists. One of the most ambitious attempts at unification was made in the 1910s by Gustav Mie. Mie aimed to derive electromagnetism, gravitation, and aspects of the emerging quantum theory from a single variational principle and a well-chosen Lagrangian. Mie’s main innovation was to consider nonlinear field equations to allow for stable particle-like solutions (now called (...) solitons), and he clarified the use of variational principles in the context of special relativity. The following brief introduction to Mie’s work has three main objectives. The first is to explain how Mie’s project fit into the contemporary development of the electromagnetic world view. Part of Mie’s project was to develop a relativistic theory of gravitation as a consequence of his generalized electromagnetic theory, and our second goal is to briefly assess this work, which reflects the conceptual resources available for developing a new account of gravitation by analogy with electromagnetism. Finally, Mie was a vocal critic of other approaches to the problem of gravitation. Mie’s criticisms of Einstein, in particular, bring out the subtlety and novelty of the ideas that Einstein used to guide his development of general relativity. (shrink)

Unlike other writing systems that are readily classifiable as alphabetic or syllabic in their structure, the Indic Devanagari script (of which Hindi is an example) has properties of both syllabic and alphabetic writing systems. Whereas Devanagari consonants are written in a linear left-to-right order, vowel signs are positioned nonlinearly above, below, or to either side of the consonants. This fact results in certain words in Hindi for which, in a given syllable, the vowel precedes the consonant in writing but follows (...) it in speech. The current research exploited this property of the script to examine when the disparity between spatial and temporal sequenc- ing would incur a processing cost and the implications of the findings from naming speed, accuracy, and writing order for the level at which words in Devanagari are segmented. The results support a partly phonemic and partly syllabic level of segmentation, consistent with the structural hybridity of the script. (shrink)