General Theory Research Articles

The Discovery of Accelerating Expansion of Universe 8.8 Billion Years after the Big Bang Vindicates M1 World One Out of the Six Solutions of Einstein’s General Theory of Relativity

This paper gives the mathematical methodology (Tensor mathematics) of describing the surfaces of our Universe in General Theory of Relativity. It expresses the mass energy equivalence formula. It introduces the concept of time dilation, length contraction and mass increment in high speed frame of reference. Minowski space time 4D manifold is illustrated for representing the flat spacetime fabric Reimannian Metric is enumerated. Schwarzschild metric and how mass is accounted for is given.

Mitigating not-invented-here syndrome in consultant knowledge transfer by developing appropriate implementation guidelines

Purpose This study aims to propose a framework for the development of implementation guidelines (IGs) that can help consultants mitigate not-invented-here (NIH) syndrome during a consultant intervention as a specific type of knowledge transfer. Design/methodology/approach The authors adopted a design science research approach for proposing an NIH-mitigating IG development framework. Inspired by findings and rich primary data from two consultant interventions, the authors, through theory building, ground five core principles in the general theory of NIH attitude functions. Finally, the authors revisit two consultant interventions to identify and describe mechanisms that led to the enactment of the principles. Findings The proposed framework provides five principles for developing NIH-mitigating IGs. The present research proposes that successful knowledge transfer and the mitigation of NIH syndrome as a prerequisite for this success are conditioned by adequately developed IGs. Originality/value The originality and value of the present research lie in the proposed NIH-mitigating IG development framework containing a set of principles for IG development as a proactive rather than reactive approach to NIH mitigation. To the best of the authors’ knowledge, this is the first research to address the problematics of mitigating NIH syndrome in consultant knowledge transfer by focusing on developing appropriate IGs. By developing and implementing IGs based on the proposed framework, a more successful transfer of knowledge from consultants to clients should take place, thus, increasing the value that clients receive from consultancy.

Dynamics of high-dimensional quantum systems coupled to a harmonic bath. General theory and implementation via multiconfigurational wave packets and truncated hierarchical equations for the mean-fields.

Modeling the dynamics of a quantum system coupled to a dissipative environment becomes particularly challenging when the system's dimensionality is too high to permit the computation of its eigenstates. This problem is addressed by introducing an eigenstate-free formalism, where the open quantum system is represented as a mixture of high-dimensional, time-dependent wave packets governed by coupled Schrödinger equations, while the environment is described by a multi-component quantum master equation. An efficient computational implementation of this formalism is presented, employing a variational mixed Gaussian/multiconfigurational time-dependent Hartree (G-MCTDH) ansatz for the wave packets and propagating the environment dynamics via hierarchical equations, truncated at the first or second level of the hierarchy. The effectiveness of the proposed methodology is demonstrated on a 61-dimensional model of phonon-driven vibrational relaxation of an adsorbate. G-MCTDH calculations on 4- and 10-dimensional reduced models, combined with truncated hierarchical equations for the mean fields, nearly quantitatively replicate the full-dimensional quantum dynamical results on vibrational relaxation while significantly reducing the computational time. This approach thus offers a promising quantum dynamical method for modeling complex system-bath interactions, where a large number of degrees of freedom must be explicitly considered.

Operationalizing critical success factors of employee ownership using principles of learning management

ABSTRACT The importance of employee-owned (EO) organizations around the world is increasing. Countries, communities and organizations are realizing that passing profits to workers increases wealth at all levels of society. The benefits, widely known, include personal prosperity, organizational profitability and stability, and a host of economic benefits for communities in which EO companies operate. Selling a company to employees, or starting a cooperative organization containing worker owners, is not without risk. New skills are required for the company to reap the rewards inherent in EO organizations, but the method of creating this change varies significantly from one organization to another. Each is unique, but there are some factors that are common to most EO organizations that have achieved a dynamic organizational culture. These factors, which are critical for success, can be isolated using structured research, organized through a lens of general systems theory and operationalized using principles of Learning Management (LM). The result is an organized knowledge transfer plan that maximizes resources and provides the highest probability of a successful transition to a uniquely profitable EO company.

General quartic β-function at three loops

We determine the three-loop MS¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\overline{\ extrm{MS}} $$\\end{document} quartic β-function for the most general renormalisable four-dimensional theories. A general parametrisation of the β-function is compared to known β-functions for specific theories to fix all coefficients. Three-loop β-functions for the cubic coupling and scalar mass terms also follow from the result, which is made available in software packages.

Metric flows with neural networks

Abstract We develop a general theory of flows in the space of Riemannian metrics induced by neural network (NN) gradient descent. This is motivated in part by recent advances in approximating Calabi–Yau metrics with NNs and is enabled by recent advances in understanding flows in the space of NNs. We derive the corresponding metric flow equations, which are governed by a metric neural tangent kernel (NTK), a complicated, non-local object that evolves in time. However, many architectures admit an infinite-width limit in which the kernel becomes fixed and the dynamics simplify. Additional assumptions can induce locality in the flow, which allows for the realization of Perelman’s formulation of Ricci flow that was used to resolve the 3d Poincaré conjecture. We demonstrate that such fixed kernel regimes lead to poor learning of numerical Calabi–Yau metrics, as is expected since the associated NNs do not learn features. Conversely, we demonstrate that well-learned numerical metrics at finite-width exhibit an evolving metric-NTK, associated with feature learning. Our theory of NN metric flows therefore explains why NNs are better at learning Calabi–Yau metrics than fixed kernel methods, such as the Ricci flow.

The geometry of multi-curve interest rate models

We study the problems of consistency and the existence of finite-dimensional realizations for multi-curve interest rate models of Heath–Jarrow–Morton type, generalizing the geometric approach developed by T. Björk and co-authors for the classical single-curve setting. We characterize when a multi-curve interest rate model is consistent with a given parameterized family of forward curves and spreads and when a model can be realized by a finite-dimensional state process. We illustrate the general theory in a number of model classes and examples, providing explicit constructions of finite-dimensional realizations. Based on these theoretical results, we perform the calibration of a three-curve Hull–White model to market data and analyse the stability of the estimated parameters.

Domain embeddings for generating complex descriptions of concepts in Italian language.

In this work, we propose a Distributional Semantic resource enriched with linguistic and lexical information extracted from electronic dictionaries. This resource is designed to bridge the gap between the continuous semantic values represented by distributional vectors and the discrete descriptions provided by general semantics theory. Recently, many researchers have focused on the connection between embeddings and a comprehensive theory of semantics and meaning. This often involves translating the representation of word meanings in Distributional Models into a set of discrete, manually constructed properties, such as semantic primitives or features, using neural decoding techniques. Our approach introduces an alternative strategy based on linguistic data. We have developed a collection of domain-specific co-occurrence matrices derived from two sources: a list of Italian nouns classified into four semantic traits and 20 concrete noun sub-categories and Italian verbs classified by their semantic classes. In these matrices, the co-occurrence values for each word are calculated exclusively with a defined set of words relevant to a particular lexical domain. The resource includes 21 domain-specific matrices, one comprehensive matrix, and a Graphical User Interface. Our model facilitates the generation of reasoned semantic descriptions of concepts by selecting matrices directly associated with concrete conceptual knowledge, such as a matrix based on location nouns and the concept of animal habitats. We assessed the utility of the resource through two experiments, achieving promising outcomes in both the automatic classification of animal nouns and the extraction of animal features.

Understanding the Mechanisms Mediating the Relationship Between Delinquent Peer Association and Adolescent Drug Use in the Greater China Region

Prior research on delinquent peer association and adolescent drug use predominantly examines the direct link between the two factors from the differential association/social learning perspective. The current study, based on survey data among 8,027 secondary school students sampled from three major cities in the Greater China Region, aims to elucidate this relationship further by identifying key mediators derived from several major criminological theories and perspectives, including social learning theory, lifestyle/routine activity theory, general strain theory, and the opportunity perspective. This study finds that significant mediators include pro-drug use attitudes, crime victimization, and drug availability, with pro-drug use attitudes exerting the most substantial influence on adolescent drug use. These results underscore the complexity of the relationship between delinquent peer association and adolescent drug use, advocating for a multifaceted theoretical approach for comprehensive understanding.

A Synergistic Perspective on Multivariate Computation and Causality in Complex Systems.

What does it mean for a complex system to "compute" or perform "computations"? Intuitively, we can understand complex "computation" as occurring when a system's state is a function of multiple inputs (potentially including its own past state). Here, we discuss how computational processes in complex systems can be generally studied using the concept of statistical synergy, which is information about an output that can only be learned when the joint state of all inputs is known. Building on prior work, we show that this approach naturally leads to a link between multivariate information theory and topics in causal inference, specifically, the phenomenon of causal colliders. We begin by showing how Berkson's paradox implies a higher-order, synergistic interaction between multidimensional inputs and outputs. We then discuss how causal structure learning can refine and orient analyses of synergies in empirical data, and when empirical synergies meaningfully reflect computation versus when they may be spurious. We end by proposing that this conceptual link between synergy, causal colliders, and computation can serve as a foundation on which to build a mathematically rich general theory of computation in complex systems.

Exploring the Extremes: The Impact of Radical Right-Wing Populism on Conspiracy Beliefs in Austria

(1) Background: Populist radical right-wing parties and politicians have used conspiracy theories to perpetuate the antagonism between an evil elite conspiring against the good and unknowing people. Yet, less is known about whether and to what extent radical right-wing populism at the individual level is associated with different conspiracy beliefs. This analysis explores how the main components of radical right-wing populism—populist, nativist, and authoritarian attitudes—relate to both a general conspiracy mentality and specific conspiracy theories prevalent in political discourse. (2) Methods: Using data from an original 2023 online survey conducted in Austria, a stronghold of the populist radical right, this study includes new questions on immigration, COVID-19, and climate change, as well as a conspiracy mentality scale. (3) Results: The analyses reveal that all the main components are positively associated with different conspiracy beliefs, albeit to varying degrees. Across models, the strongest predictor is populism, followed by nativism and authoritarianism. Nativism varies the most across different conspiracy beliefs and is particularly associated with the belief in conspiracy theories related to immigration and climate change. (4) Conclusions: The results highlight the prevalence of radical right-wing populist attitudes across various conspiracy beliefs, reflecting how populist radical right-wing actors leverage conspiracy theories in their political discourse.

Continuum Mechanics Applied to the Biomechanics of Motion.

Continuum Mechanics is the discipline that studies the motion and deformation of material bodies, and is at the basis of both Solid Mechanics and Fluid Mechanics. This works aims at highlighting how a basic education in modern Continuum Mechanics can be of fundamental importance not only in the Biomechanics of Tissue, but also in the Biomechanics of Movement. The latter is largely based on Rigid Body Mechanics, which can be considered as a simple particular case of the general theory of Continuum Mechanics. As an example, a straightforward methodology for the extraction of the angular velocity from motion analysis data is illustrated. The method is based on a quantity that is more primitive than the angular velocity: the spin tensor.

Unifying Principles of Generalization: Past, Present, and Future.

Generalization, defined as applying limited experiences to novel situations, represents a cornerstone of human intelligence. Our review traces the evolution and continuity of psychological theories of generalization, from its origins in concept learning (categorizing stimuli) and function learning (learning continuous input-output relationships) to domains such as reinforcement learning and latent structure learning. Historically, there have been fierce debates between approaches based on rule-based mechanisms, which rely on explicit hypotheses about environmental structure, and approaches based on similarity-based mechanisms, which leverage comparisons to prior instances. Each approach has unique advantages: Rules support rapid knowledge transfer, while similarity is computationally simple and flexible. Today, these debates have culminated in the development of hybrid models grounded in Bayesian principles, effectively marrying the precision of rules with the flexibility of similarity. The ongoing success of hybrid models not only bridges past dichotomies but also underscores the importance of integrating both rules and similarity for a comprehensive understanding of human generalization.

Traversable wormholes with electric and magnetic charges in general relativity theory

Traversable wormholes with electric and magnetic charges in general relativity theory

Monte Carlo calculations taking into account the DLP theory to study multilayer adsorption of C2H4 and CF4 on graphite

Physisorption potentials are useful for deducing the properties of adsorption systems. The adsorption behavior is a consequence of the actual potential that describes the interactions among the adsorption system. Determining the actual isotherm is a test for the correctness of a calculated adsorption potential. The physisorption interactions decrease with the film thickness, d, according to a power law as −γ/d3, where γ is the Van der Waals coefficient. In the Dzyaloshinskii, Lifshitz, and Pitaevskii (DLP) theory, γ is a function of d where γ(d) decreases with d. In the present work, the general theory of Van der Waals forces, given by DLP, is used to derive a more exact treatment of interactions among the physisorbed systems. The Monte Carlo method is used to investigate multilayer films using a lattice gas model adsorption isotherm. Critical temperatures are determined for ethylene (C2H4) and tetrafluoromethane (CF4) on graphite. These systems exhibit comparable behavior. Unlike the findings of mean field theory, our data shows that the critical temperature rises gradually as the layer number increases. On the other hand, the comparison with experimental results and measurements has shown that our calculations are more reliable and provide a better approximation in predicting film thickness. Our isotherms appear to be in better agreement with the experimental ones.

Symmetries and Wigner representations of operational theories

Abstract We develop the theory of Wigner representations for general probabilistic theories (GPTs), a large class of operational theories that include both classical and quantum theory. The Wigner representations that we introduce are a natural way to describe the theory in terms of some fixed observables; these observables are often picked to be position and momentum or spin observables. This allows us to introduce symmetries which transform the outcomes of the observables used to construct the Wigner representation; we obtain several results for when these symmetries are well defined or when they uniquely specify the Wigner representation.

Circular vs One-Way Production Processes: Two Different Views on Production and Income Distribution

ABSTRACT This paper examines two distinct representations of production processes: circular production, where commodities function as both inputs and outputs, and one-way production, which starts with factors of production and ends with finished goods. These frameworks offer different views on profits. In circular systems, profits arise from surplus production, while in one-way systems, they appear to emerge from price differences between final goods and inputs. Using Sraffa’s price equations, we analyse the properties of both systems. We demonstrate that while one-way systems seem to allow for profit increases by raising prices, this is an illusion as it ultimately reduces real wages, the true source of profits. Additionally, we show that one-way systems become circular when real wages are fixed. Finally, the paper discusses how this distinction is important in understanding the shift from Walras’ general equilibrium theory to neo-Walrasian formulations. This study highlights the importance of circularity in the functioning of capitalist economies and its implications for the theory of distribution.

거시경제학의 근본적인 문제점: 항등식을 인과성으로 사용

GDP, which only measures the value of the final product, ignores the various production processes that take place in the real world before the final product is produced. In this sense, GDP is not a reflection of the real world, but rather an artificially constructed measure of a ‘fictitious economy’. A bigger problem with GDP is that the identity equation, by which GDP is expressed as the sum of consumer spending, business investment spending, government spending, and net exports, is used in a causal way. Using this identity equation, governments often implement policies that increase spending to stimulate the economy and grow the economy. However, the principle of human behavior that one must first produce in order to consume implies that production is the cause and consumption is the effect. The idea, which implies that consumption is the cause, is thus incorrect because it goes against the principle of human behavior. This idea is based on Keynes's theory. Keynes's theory, as presented in his General Theory, is a misinterpretation of Say's Law of the Market, which states that “when one product is produced, it creates a demand for another product,” as “supply creates its own demand.” Macroeconomics, which was started based on the wrong Keynes' theory, is also a theory that is far from the real world and does not explain the economic problems that are occurring in the real world, such as the financial crisis. Therefore, in order for macroeconomics to properly explain the real world, it is necessary to establish a new macroeconomics. The new macroeconomics should be based on the principles of human behavior and should include the actual production process and the activities of entrepreneurs, who play an important role in the production process. The Austrian Business Cycle Theory, which covers these aspects, can serve as the cornerstone of a new macroeconomic theory.

On the Principle of Relativity of Inertia in Both General and Entangled Relativities

Entangled Relativity is a novel theory of relativity that offers a more economical approach than General Relativity. It successfully recovers both General Relativity and standard quantum field theory within a specific (yet generic) limit. Furthermore, Entangled Relativity precludes the existence of spacetime devoid of the matter that permeates it. Consequently, I argue that Entangled Relativity is not only preferable from the standpoint of Occam’s razor, due to its economical nature, but it also aligns more closely with Einstein’s original vision for a satisfactory theory of relativity.

Factors Affecting the Adoption of Electronic Procurement Systems in Public Institutions in Tanzania: Evidence from Tanzania Prisons in Morogoro Municipal

The study investigated the factors affecting the adoption of electronic procurement systems in public institutions in Tanzania, evidence from Tanzania Prisons in Morogoro Municipal. A survey research design and mixed research approach were utilized. The target population included procurement employees in Tanzania public institutions represented by Kingolwira Prison, Mkonowa Mara Prison, Kihonda Prison, and Remand Prison in Morogoro Municipal Municipality. The study involved 52 respondents. Purposive sampling technique wase used in selection of respondents where all respondents with knowledge on electronic procurement systems were used. Data was gathered through questionnaires with likert scale statements and analysed using descriptive statistics. In addition to that, data deduction techniques whereby conclusions were made by logically reasoning from general principles or theories to specific instances or outcomes based on the available data. User opinions on e- procurement adoption in Tanzanian public institutions highlight significant concerns about technological infrastructure, including hardware availability, software support, and internet reliability. While many acknowledge benefits such as reduced paperwork and enhanced efficiency, opinions vary on its effectiveness in reducing lead times and corruption. Security remains a critical issue, with mixed views on data accessibility and sharing safety. Overall, addressing infrastructure challenges and security concerns is crucial to ensuring successful implementation and broader user acceptance of e- procurement systems.