Comprising the largest population cohort on this planet, Gen Z presents a future-oriented consumer segment driven by climate change and food. This study sought to investigate Gen Zs’ perceptions to-ward plant-based foods and diets, and explore the relationship between attitude components, meal preparation involvement, personal and lifestyle factors, and perceived barriers in adopting a plant-based diet with willingness to adopt green-eating practices. Using cross-sectional data from uni-versity students in Greece, India and UK, various tools were employed to determine the factors influ-encing youths’ consumer behavior toward animal-protein substitutes. PCA indicated the underlying dimensions of students’ viewpoints on plant-based foods, whereas hierarchical and k-means clustering provided the cluster structure. An ordered probit model was estimated to delineate Gen Zs’ willingness to adopt plant-based diets and distinguish among mostly unwilling, somewhat willing and mostly willing youths. Our findings identified two consumer segments, namely proponents and opponents toward plant-based foods and diets, with statistically significant differences in the perceived health benefits of plant-based diets, attachment to animal-based proteins, perceived exclusion of ani-mal-based foods, dissatisfaction with plant-based foods attributes and demand for ensuring adequate protein intake. The ordered probit model estimates showed that there is a rather «homogeneity» in the factors influencing youths’ intention to adopt plant-based diets, with attitude components, meal prep-aration indicators, perceived barriers to eating “green” and personal factors, viz. self-assessed knowledge on healthy eating and physical activity, being strongly associated with students’ willingness to switch to plant-based diets in all three countries. Mapping potential obstacles and enablers in terms of shifting to more green-eating behaviors, our findings could add information to better understand the factors affecting food choice and youths’ transition to a more sustainable lifestyle.

Epithelial–mesenchymal transition (EMT) is defined as a cellular process during which epithelial cells acquire mesenchymal phenotypes and behavior following the downregulation of epithelial features. EMT and its reversed process, the mesenchymal-epithelial transition (MET), and the special form of EMT, the endothelial-mesenchymal transition (EndMT), have been thought as a universal dogma controlling developmental and pathological processes. More than half a century of EMT study has made it a large research field and a mainstream concept. However, discrepancies and disputes over EMT and EMT research have also grown over time. Particularly, neither the epithelial and mesenchymal states/properties nor their regulatory networks nor specific markers have been defined, rendering the EMT, MET and EndMT concepts groundless. Moreover, EMT and MET effects should not be a cause, but rather a consequence of or an accompanying effect during developmental and pathological processes. EMT and MET represented by the change in cell shapes or adhesiveness or symbolized by EMT factors are biased interpretation of the overall change in cellular property and regulatory networks during development and cancer progression. The true meaning of EMT effects in some developmental and pathological processes, such as fibrosis, needs re-evaluation. But the core EMT factors are actually a few components of the regulatory networks of neural stemness, which determines tumorigenicity and pluripotency. The EMT effects in cancer progression and neural crest formation are wrong attribution of the role of neural stemness during cancer progression and the cell-intrinsic property of neural crest cells to the unknown mesenchymal state. It is time to reassess the significance of EMT and its related concepts in scientific research.

The weakness of the dispersion-managed link combined with optical phase conjugation to compensate for optical signal distortion caused by chromatic dispersion and nonlinear Kerr effect of standard single mode fiber is its limited structural flexibility. We propose dispersion map that can simultaneously compensate for the distorted wavelength division multiplexed signal while increasing the configurational flexibility. Each residual dispersion per span (RDPS) in the former half of the proposed link is randomly determined, and in the latter half, the arrangement order of RDPS is the same as or inverted in the former half. We confirm that the dispersion maps in which the RDPS distribution pattern in the latter half is opposite to the arrangement order in the former half are more effective in compensation, and rather, the compensation effect is better than in the dispersion map of the conventional scheme. The notable result of this paper is that the increase of flexibility can be achieved through random arrangement of RDPS in the former half, and the compensation improvement can be achieved by through inverse arrangement in the latter half which make the distribution profile of each half link roughly symmetric with respect to the midway optical phase conjugator.

The last 50 years witnessed the emergence of various so called “hyperpolarization technologies” that allow generating large magnetizations of spin ensembles. This Editorial Essay provides a brief overview of the use of these technologies in various fields, including medicine, chemistry, and quantum sensing. It is concluded that critical questions still need to be addressed to harness benefits of nuclear hyperpolarization in clinical medical imaging while interdisciplinary innovation can unlock potential of novel (yet unexplored) methods. My hope is that this Editorial Essay provides valuable insights into the current state and future directions of spin technologies.

Quantum mechanics could be studied through polynomial algebra, as has been demonstrated by a work (“An approach to first-principles electronic structure calculation by symbolic-numeric computation” by A. Kikuchi). We carry forward the algebraic method of quantum mechanics through algebraic number theory; the basic equations are represented by the multivariate polynomial ideals; the symbolic computations process the ideal and disentangle the eigenstates as the algebraic variety; upon which one canbuild the Galois extension of the number field, in analogy with the univariate polynomial case, to investigate the hierarchy of solutions; the Galois extension is accompanied with the group operations, which permute the eigenstates from one to another, and furnish the quantum system with a non-apparent symmetry. Besides, this sort of algebraic quantum mechanics is an embodiment of the class field theory; some of the important consequences of the latter emerge in quantum mechanics. We shall demonstrate these points through simple models; we will see the use of computational algebra facilitates such sort of analysis, which might often be complicated if we try to solve them manually.

We develop an action principle for producing a single fluid, two-constituent system with dissipation in general relativity. The two constituents in the model are particles and entropy. The particle flux creation rate is taken to be zero, while the entropy creation rate is non-zero. Building on previous work, it is demonstrated that a new term (the proper time derivative of the matter space ``metric'') is required in the Lagrangian in order to produce terms typically associated with bulk and shear viscosity. Equations of motion, entropy creation rate, and energy-momentum-stress tensor are derived. Using an Onsager approach of identifying thermodynamic ``forces'' and ``fluxes'' a model is produced which delivers the same entropy creation rate as the standard, relativistic Navier-Stokes equations. This result is then contrasted with a model generated in the spirit of the action principle, which takes as its starting point a specific Lagrangian and then produces the equations of motion, entropy creation rate, and energy-momentum-stress tensor. Unlike the equations derived from Onsager reasoning, where the analogs of the bulk and shear viscosity coefficients are prescribed ``externally'', we find that the form of the coefficients in the second example are a direct result of the specified Lagrangian. Furthermore, the coefficients are shown to satisfy evolution equations along the fluid worldline; also a product of the specific Lagrangian.

Type II diabetes (T2D) is a multifaceted metabolic disease influenced by various factors (genetic, epigenetic, environmental, and other). An alarming surge in T2D prevalence is estimated, reaching 700 million cases by 2045 worldwide. This review explores the complex interactions of multiple risk factors throughout life and offers a new perspective on T2D. Genetic and epigenetic influences are described in detail. Prenatal factors, such as exposure to undernutrition and maternal overfeeding, induce lasting epigenetic changes, affecting T2D susceptibility. Furthermore, birthweight is a crude proxy for perinatal programming, with low and high birthweights associated with increased T2D risk. Often overlooked, the early postnatal period also significantly contributes to perinatal programming. Neonatal over-nutrition and feeding choices exert lasting effects on DNA methylation and metabolic outcomes later in life. Stress during this period further exacerbates T2D susceptibility. In continuation, childhood behaviors which are influenced by prior periods contribute substantially to T2D risk. Adverse childhood experiences amplify the risk of many diseases, including T2D. Sleep hygiene throughout life plays a role in metabolic health, influencing insulin resistance and appetite regulation. In adulthood, obesity remains a prominent predictor of T2D, with chronic stress contributing to weight gain and unhealthy lifestyle. This review proposes a novel perspective, considering T2D pathophysiology as a nonlinear process governed by numerous factors and their interactions throughout life. The inherent unpredictability suggests a need for personalized interventions tailored to specific risk profiles, emphasizing the importance of understanding gene-environment interactions and embracing a holistic view of T2D pathogenesis.

Physical laws manifest themselves through the amalgamation of mathematical symbols, numbers, functions, geometries, and relationships. These intricate combinations unfold within a mathematical model devised to capture and represent the ``objective reality'' of the system under examination. In this symbiotic relationship between physics and mathematics, the language of mathematics becomes a powerful tool for describing and predicting the behavior of the physical world. The language used and the associated concepts are in a perpetual state of evolution, mirroring the ongoing expansion of the phenomena accessible to our scientific understanding. In this contribution, written in honor of Richard Kerner, we delve into fundamental, at times seemingly elementary, elements of the mathematical language inherent to the physical sciences, guided by the overarching principles of symmetry and group theory. Our focus turns to the captivating realm of spheres, those strikingly symmetric entities that manifest prominently within our geometric landscape. By exploring the interplay between mathematical abstraction and the tangible beauty of symmetry, we seek to deepen our understanding of the underlying structures that govern our interpretation of the physical world.

Although information theory resolves inconsistencies (known under the form of famous enigmas) of the traditional approach of thermostatistics, its place in the corresponding literature is not what it deserves. This is interpreted as being mainly due to epistemological rather than scientific reasons: the subjectivity introduced into physics is perceived as a problem. This paper attempts to expose and clarify where exactly this subjectivity lies: in the representation of the reality and in probabilistic inference. Two aspects which have been integrated into the practice of science for a long time and which should no longer frighten anyone, but which become explicit with information theory.

Landauer’s principle states that the logical irreversibility of an operation, such as erasing one bit, whatever its physical implementation, necessarily implies its thermodynamical irreversibility. In this paper, a very simple counterexample of physical implementation (that uses a two-to-one relation between logic and thermodynamic states) is given that allows to erase one bit in a thermodynamical quasistatic manner (i.e. that may tend to be reversible if slowed down enough).

In a recent article we showed that the analog of the cosmological constant in two spacetime dimensions for a wide variety of integrable quantum field theories has the form ρvac = −m2/2g where m is a physical mass and g is a generalized coupling, where in the free field limit g → 0, ρvac diverges. We speculated that in four spacetime dimensions ρvac takes a similar form ρvac = −m4/2g, but did not support this idea in any specific model. In this article we study this problem for λφ4theory in d spacetime dimensions. We show how to obtain the exact ρvac for the sinh-Gordon theory in the weak coupling limit by using a saddle point approximation. This calculation indicates that the cosmological constant can be well-defined, positive or negative, without spontaneous symmetry breaking. We also show that ρvac satisfies a Callan-Symanzik type of renormalization group equation. For the most interesting case physically, ρvac is positive and can arise from a marginally relevant negative coupling g and the cosmological constant flows to zero at low energies.

The purpose of this article is to address two questions that will aid researchers in understanding FinTech’s inception, development, and potential impact on the stability of the financial system. First, it explains why financial technology is a current phenomenon. While many of the underlying technology for FinTech breakthroughs have been around for some time, it is only recently that financial institutions and entrepreneurs have begun to apply them to financial goods and services. Supply and demand factors in "conventional" financial innovation have been studied, and they have been found to converge, leading to a high rate of innovation. And second, this article explains why FinTech is being covered in greater depth than other types of innovation. This study introduces the concept of "depth" of innovation as a means of answering this question. The more fundamental the innovation, the more it will affect the financial sector. In this paper, we demonstrate that many recent developments in the field of financial technology (FinTech) are truly revolutionary advances, with far-reaching implications for the financial services industry. In addition to the benefits of more adaptability, higher transformational potential might bring increased risk to economic security.

We study and describe possibilities for arities of elementary theories and of their expansions. Links for arities with respect to Boolean algebras, to disjoint unions and to compositions of structures are shown. Arities and aritizabilities are semantically characterized. The dynamics for arities of theories is described.

Based on a measuring system to determine the statistical heterogeneity of individual polygons we propose a method to use polygonal shape patterns as a source of data in order to determine the Shannon entropy of biological organizations. In this research, the term entropy is a particular amount of data related with levels of spatial heterogeneity in a series of different geometrical meshes and sets of random polygons. We propose that this notion of entropy is important to measure levels of information in units of bits, measuring quantities of heterogeneity in geometrical systems. In fact, one important result is that binarization of heterogeneity frequencies yields a supported metric to determine geometrical information from complex configurations. Thirty-five geometric aggregates are tested; biological and non-biological, in order to obtain experimental results of their spatial heterogeneity which is verified with the Shannon entropy parameter defining low particular levels of geometrical information in biological samples. Geometrical aggregates (meshes) include a spectrum of organizations ranging from cell meshes to ecological patterns. Experimental results show that a particular range (0.08 and 0.27) of information is intrinsically associated with low rates of heterogeneity. We conclude it as an intrinsic feature of geometrical organizations in multi-scaling biological systems.

Projects are rarely executed exactly as planned. Often, the actual durations of a project’s activities differ from the planned ones, resulting in costs stemming from the inaccurate estimation of the activities’ completion dates. While monitoring the project at various inspection points is pricy, it can lead to better estimation of the project completion time, hence saving on costs. Nonetheless, identifying the optimal inspection points is a difficult task, as it requires evaluating a large number of the project’s path options, even for small-scale projects. This paper proposes an analytical method for identifying the optimal project inspection points by using Information Theory measures. We search for monitoring (inspection) points that can maximize the information about the estimated project’s duration or completion time. The proposed methodology is based on a simulation-optimization scheme using a Monte Carlo engine that simulates potential activities’ durations. An exhaustive search is performed of all possible control points to find those with the highest expected information gain on the project duration. The proposed algorithm’s complexity is not affected the number of activities, and can address large projects with hundreds or thousands of activities. Numerical experimentation and analysis of various parameters are presented.

Slow-roll inflation may simultaneously solve the horizon problem and generate a near scale-free fluctuation spectrum $P(k)$. These two processes are intimately connected via the initiation and duration of the inflationary phase. But a recent study based on the latest {\it Planck} release suggests that $P(k)$ has a hard cutoff, $k_{\rm min}\not=0$, inconsistent with this conventional picture. Here we demonstrate quantitatively that most---perhaps all---slow-roll inflationary models fail to accommodate this minimum cutoff. We show that the small parameter $\epsilon$ must be $\gtrsim 0.9$ throughout the inflationary period to comply with the data, seriously violating the slow-roll approximation. Models with such an $\epsilon$ predict extremely red spectral indices, at odds with the measured value. We also consider extensions to the basic picture (suggested by several earlier workers) by adding a kinetic-dominated or radiation-dominated phase preceding the slow-roll expansion. Our approach differs from previously published treatments principally because we require these modifications to---not only fit the measured fluctuation spectrum, but to simultaneously also---fix the horizon problem. We show, however, that even such measures preclude a joint resolution of the horizon problem and the missing correlations at large angles.

Learning models of the cerebellum propose that the cerebellum implements an algorithm which makes iterative adjustments to synaptic transmission strength that collectively determine the response to input in learned patterns following training. We propose instead that pattern recognition and control of firing by output cells are separately handled functions which process independently variable data. This can account for the evidence without a machine learning algorithm. The model is a hybrid of physiological arguments and computational methods used to test and quantify the ideas. We argue inter alia that learning operates at the level of functional groups of Purkinje cells defined by their shared climbing fibre input; Golgi cells have several functions and regulation of parallel fibre activity by Golgi cells is not in the expected way; recoding of input to the cerebellum received in the granular layer converts the number of input variables (variables expressed in mossy fibre input to the system) into a much reduced number of functional variables expressed by internal signals traffic; circuits simultaneously execute separate but integrated functions of pattern memory and output coding; they are able to operate separately because the expression of data used in each varies independently of the other; output rates are not learned but controlled by recent relevant input signals in a window opened by pattern memory; the moment-to-moment probability that a Purkinje cell spikes is synchronised across a microzone; a principal function of functional organisation of Purkinje cells into microzones is to increase resolution of rate coded information received by the output cells of the circuit, and to do so in a very short integration window, so that circuit architecture can be explained partly as a device with this function.

To account for the very low mass density associated with Dark Energy and the Cosmological Constant, a new approach to the ground state of empty space is presented. The resulting model for the vacuum state associated with empty space proposes a crystalline-like texture for the chromatic structure of empty space. This vacuum state has the appropriate mass density and predicts acceleration for the Universe expansion. Furthermore, the model predicts that this texture is anisotropic and may lead to measurable changes in the production of electron and positron pairs by gamma rays incident on a solid crystal of low mass density such as graphite.

Komlos conjecture is about the existing of a constant upper bound over the dimension n of the function $K(n)$ defined by $$K(n)=max_{ \{ \overrightarrow{V_1},...,\overrightarrow{V_n} \} \in \{ \overrightarrow{V_i} \in { R}^n \| \overrightarrow{V_i} \| \leq 1 \} ^n } min_{ \{\epsilon_1,...\epsilon_n\} \in \{-1,+1\}^n } \|\sum_{i=0}^{n} \epsilon_i \overrightarrow{V_i}\}\|_{\infty} $$ In this paper, the function $K(n)$ is evaluated first for lower dimensions, $n\leq 5$, where it found that $K(2)=\sqrt{2}$. For higher dimension, the function $f(n)=\sqrt{ n-\lceil\log_2(2^{n-1}/n) \rceil}$ is found to be a lower bound for the function $K(n)$, from where it is concluded that the Komlos conjecture is false i.e., the universal constant $k=max_{n \in N} K(n) $ does not exist because of $$\lim_{n \rightarrow \infty } K(n) \geq \lim_{n \rightarrow \infty } \sqrt{ \log_2(n)-1 }=+\infty$$

This paper aims to suggest an integration of dimensions, especially economic, social, environmental, and politics that are embedded in Sustainable Development Goals (SDGs) within a framework called Umran. This Umranic framework hails from the idea of distinguished Muslim philosopher, historian and sociologist Ibn Khaldun, that is based on Islamic doctrines. As the present integration of the dimensions seems to be problematic, an exploration into the integration within Umranic framework is believed to be potentially a contributive endeavor. Based on an overview of literatures and a content analysis, this paper found that integrating dimensions of SDGs within the Umranic framework appears in the triangle of relationship between God, humans, and environment. This triangle exists in the form of an Islamic economic system. In this system, economic activities of natural resource utilization in various types of ownership undertake the sustainability dimension, that is the environmental protection and the promotion of equitable distribution, followed by the implementation of management of ownership and distribution rights according to Islamic rules. The pre-requisite on the part of the players is the high levels of spirituality. The application of this Islamic economic system followed by its political dimension will guarantee the achievement of SDGs even though it needs adjustment to a number of SDGs’ indicators that are not in accordance to Islamic teachings.

The constraint equations in Maxwell theory are investigated. In analogy with some recent results on the constraints of general relativity it is shown, regardless of the signature and dimension of the ambient space, that the "divergence of a vector field" type constraints can always be put into linear first order hyperbolic form for which global existence and uniqueness of solutions to an initial-boundary value problem is guaranteed.

We studied generalization of a method for extending configurational studies to variables that are not exclusively geographical, in order to allow investigation of generic relationships in the built environment. We observed a number of limitations of the classical approach of configurational studies and we considered how a complex analytical method could be implemented in the study of non-topological variables, such as land use, noise pollution and financial or property rents. In order to do this we established a system of relationships based on a labeled primary graph. Categorization of the labels of the links was performed on a generic variable, specifically, the predominant use of roads. The graph was then contracted using an optimization algorithm, which we describe. The algorithm allows the network to be reduced to a more streamlined system that can better analyze the relationships between the different categories. Application of the method showed that it is faster to identify weaknesses in urban networks, and then take measures to resolve them. The case study concerns the pedestrianization of the Colosseum area in Rome.

The Great Reset has been presented by the World Economic Forum (WEF) in response to the COVID-19 pandemic in 2022 as a model through which a “stakeholder economy” would achieve “resilient, equitable and sustainable” economic, social and environmental goals. A more equitable distribution of resources, better working conditions, and ecological transitions are included in a social, economic and environmental reform agenda. This article raises the question of whether the Great Reset project should be interpreted as a “realistic utopia” and what is its reform potential. In an attempt to answer the question of whether the Great Reset as a realist utopia is consistent with the current state of science and philosophy, the article re-examines the idea of utopia in the light of recent philosophical and scientific approaches, such as critical realism in philosophy, so-cial systems theory in sociology and complexity theory in science. A comparative conceptual analysis is carried out and discussed introducing the idea of a realist utopia in Rawls' theory of justice as fairness. In the final discussion, some doubts are raised about the logical coherence, rigor of scientific theorizing, policy prescriptions, and predictive potential of the Great Reset emerging paradigm. It is concluded that utopian projects of radical reform can become realistic when they offer explanations of the deep structural changes that underlie social and economic evolution, drawing from these explanations the policy implications and prescription that can support struc-tural changes, rather than from assumed long-term effects of exogenous shocks or “black swan” events such as the COVID-19 pandemic.

The many problems faced by the theory of general relativity (GR) have always motivated us to explore the modified theory of GR. Considering the importance of studying the black hole (BH) entropy and its correction in gravity physics, we study the correction of thermodynamic entropy for a kind of spherically symmetric black holes under the generalized Brans-Dicke (GBD) theory of modified gravity. We derive and calculate the entropy and heat capacity. It is found that when the value of event horizon radius~$r_+$~is small, the effect of the entropy correction term on the entropy is very obvious, while for larger values~$r_+$~, the contribution of the correction term on entropy can be almost ignored. In addition, we can observe that as the radius of the event horizon increases, the heat capacity of BH in GBD theory will change from a negative value to a positive value, indicating that there is a phase transition in black holes. Given that studying the structure of geodesic lines is important for exploring the physical characteristics of a strong gravitational field, we also investigate the stability of the geodesic motion of particles in static spherically symmetric BHs within the framework of GBD theory. Concretely, we analyzes the dependence of the innermost stable circular orbit on model parameters. Also, the geodesic deviation equation is also applied to investigate the stable circular orbit of particles in GBD theory. The conditions for the stability of BH solution and the limited range of radial coordinates required to achieve stable circular orbit motion are given. Finally, we show the locations of stable circular orbits, and obtain the angular velocity, the specific energy and angular momentum of the particles which move in circular orbits.

Accurate and efficient determination of excited-state polarizabilities (α) is an open problem both experimentally and computationally. Following our previous work, [Phys. Chem. Chem. Phys. 2023, 25, 2131−2141], where one can employ simple ground-state density-based functions from the information-theoretic approach (ITA) to accurately and efficiently predict the macromolecular polarizabilities, we aim to predict the lowest excited-state polarizabilities in this work. The philosophy is to use density-based functions to depict the excited-state polarizabilities. As a proof-of-principle application, employing 2-(2′-hydroxyphenyl)benzimidazole and its derivatives as model systems, we have verified that either with the ground-state (S0) or excited-state (S1) densities as input, ITA quantities can be strongly correlated with the excited-state polarizabilities. When the transition densities are considered, both S0 and S1 polarizabilities are in good relationships with some ITA quantities. Furthermore, excitation and emission energies can be predicted based on multivariant linear regression equations of ITA quantities.

By defining a constant probabilistic orbit of and iterated functions, the stability dynamics of these functions in possible interactions through connectivity provides the formation of a dynamic fixed point as a metric space between both iterated functions. The presence of a dynamic fixed point identifies qualitatively phases of iteration time lengths and interaction orbits of the event. Qualitative results show that the greater the average distance from one of the functions to the fixed point of the other (all possible solutions), the higher the iteration expression on time (false asymptotic effect) of one of the functions and in the opposite hand, the lower the average distance, the higher orbit’s interactions proximity between iterated functions (stability). This feature reveals asymptotic (well-defined) behavior between functions f and g within a well-defined Lyapunov stability.

A regional organisation (RO) is a group of states that, through the formation of mutual relationships, work together for shared regional goals such as economic growth, social welfare, security, and democracy. The Association of South East Asian Nations (ASEAN) is one such organisation, of interest because of its operative paradoxes. However, current theory to study ROs is both fragmented across the field of study, and inadequate. Taking ROs to be complex adaptive systems, diagnosing ROs requires theory that can to explore their hidden aspects. The metacybernetics framework enables the creation of a critical realism configurative a-priori inquiry approach to theory building, the configurations providing coordinative schemas able to respond to predefined complex modelling needs. To analyse ROs using metacybernetics, we offer a derivative schema, Cultural Agency Theory (CAT). Currently this is limited to exploring modes of information acquisition processes through cognitive style, and until now has had no inherent mechanism to explore social relationships as is required to explore ROs. To enable CAT to explore such relationships, we configure the Tönnies social organisation paradigm for CAT. Mindset Agency Theory (MAT) is a specific elaboration of CAT, and creates an empirical setting for the set of formative traits that de-fine an RO character. A related derivative of CAT is that of Multiple Identity Theory (MIT) which enables organisational pathologies to be explored in terms of identity conflicts. This multifaceted paradigm provides a relatively simple approach to the RO diagnosis, in particular in terms of stability/coherence. This paper is in two parts. In this part 1, the CAT theory will be further developed through the joint configuration of Tönnies social organisation paradigm allowing its pathologies to be diagnosed. In part 2 of the paper, the theory will be applied to ASEAN and the diagnosis will show that it is an inherently incoherent organisation.

A regional organisation (RO) is a group of states that, through the formation of mutual relation-ships, work together for shared regional goals such as economic growth, social welfare, security, and democracy. The Association of South East Asian Nations (ASEAN) is one such organisation, of interest because of its operative paradoxes. However, current theory to study ROs is both fragmented across the field of study, and inadequate. Taking ROs to be complex adaptive systems, diagnosing ROs requires theory that can to explore their hidden aspects. The metacybernetics framework enables the creation of a critical realism configurative a-priori inquiry approach to theory building, the configurations providing coordinative schemas able to respond to predefined complex modelling needs. To analyse ROs using metacybernetics, we offer a derivative schema, Cultural Agency Theory (CAT). Currently this is limited to exploring modes of information acquisition processes through cognitive style, and until now has had no inherent mechanism to explore social relationships as is required to explore ROs. To enable CAT to explore such relationships, we configure the Tönnies social organisation paradigm for CAT. Mindset Agency Theory (MAT) is a specific elaboration of CAT, and creates an empirical setting for the set of formative traits that de-fine an RO character. A related derivative of CAT is that of Multiple Identity Theory (MIT) which enables organisational pathologies to be explored in terms of identity conflicts. Thes multifaceted paradigm provides a relatively simple approach to the RO diagnosis, in particular in terms of stability/coherence. This paper is in two parts. In this part 1, the CAT theory will be further developed through the joint configuration of Tönnies social organisation paradigm allowing its pathologies to be diagnosed. In part 2 of the paper, the theory will be applied to ASEAN and the diagnosis will show that it is an inherently incoherent organisation

This article discuss the estimation of electrical stresses input that is required to determine lifetime degradation of the HV cables installed within overhead transmission lines (OHTL’s). Abort from lightning effects, these electrical stresses are mainly generated due to repetitive switching operation of the transmission line that produces transient overvoltage (TOV) stress and high frequency stress. The transient overvoltage (TOV) due to switching-off the transmission line at the interface points between the cable and OHTL is estimated using artificial neural network (ANN). PSCAD software is used to build the transmission line model for 749 different case in order to build the required database for ANN training. Two different algorithm input to train ANN with one hidden layer and one output layer using different number of nodes are modeled in MATLAB. The results performance is continuously compared and evaluated till acceptable Regression is achieved to insure the error is less than +/-1.5%. The high frequency due to switching-on the transmission line is also recorded and analyzed. The results show that this new method is efficient, accurate and useful as there is no cable monitoring system is available for each HV cable installed within the transmission line.

A groundbreaking integrated predictive model, termed Cyber Forensics Behavioral Analysis (CFBA), has been developed in an environment characterized by rapidly evolving and increasingly sophisticated cyber threats. This model merges Cyber Behavioral Sciences with Digital Forensics to enhance the prediction accuracy and effectiveness of cyber threats originating from specific Autonomous System Numbers (ASNs). It has been observed that traditional cybersecurity strategies, predominantly focused on technical aspects, must be improved in addressing the complex landscape of cyber threats. Consequently, a novel approach has been proposed in this research, combining technical expertise with insights into the behavior of cybercriminals, thereby addressing a significant gap in existing methodologies. A mixed-methods approach has been employed in the study, integrating quantitative and qualitative research methods. This approach has created a comprehensive framework incorporating digital forensics, cybersecurity, computer science, forensic psychology, and the cyber behavioral sciences which incorporates disciplines scuch as cyberpsychology and forensic cyberpsychology. The study is anchored around four key concepts: (1) Forensic Cyberpsychology, which focuses on understanding psychological aspects of cybercriminal behavior; (2) Digital Forensics, involving the collection and analysis of digital evidence from cyber incidents; (3) Predictive Modeling, which utilizes historical data and patterns to anticipate potential cyber threats; and (4) the Cyber Behavioral Analysis Metric (CBAM) and Cyber Behavioral Score (CBS), tools designed for evaluating and scoring ASNs based on their behavior in terms of cybersecurity threat risks. Challenges encountered in the development of this integration have been significant. Initial setbacks included the misalignment of traditional cyber defense methods with the evolving nature of cyber threats and the absence of a holistic approach in pre-existing models. Through the narrative of these challenges and the subsequent development of the CFBA model, the research highlights the necessity for an interdisciplinary approach to cybersecurity. The outcomes of this study are not merely theoretical but provide practical, actionable tools and frameworks that markedly improve the precision of predicting cyber threats, especially from ASNs. The CFBA model represents a significant shift in cybersecurity strategies, highlighting the importance of integrating behavioral insights with technical knowledge. The study emphasizes the need for ongoing research and collaboration in cybersecurity, advocating for an approach that is as comprehensive and multifaceted as the cyber threats it seeks to mitigate. This research has been conducted to contribute significantly to cybersecurity, offering new perspectives and methodologies in a rapidly changing domain.

Solar flares are broadly classified as impulsive or gradual. Ions accelerated in a gradual flare are thought to be accelerated through a shock acceleration mechanism, but the particle acceleration process in an impulsive flare is still largely unexplored. To understand the acceleration process, it is necessary to measure the high-energy gamma-rays and neutrons produced by the impulsive flare. Under such circumstances, on November 7, 2004, a huge X2.0 flare occurred on the solar surface, where ions were accelerated to energies greater than 10 GeV. The accelerated primary protons collided with the solar atmosphere and produced line gamma-rays and neutrons. These particles were received as neutrons and line gamma-rays, respectively. Neutrons of a few GeV, on the other hand, decay to produce secondary protons while traveling 0.06 au in the solar-terrestrial space. These secondary protons arrived at the magnetopause. Although the flux of secondary protons is very low, the effect of collecting secondary protons arriving in a wide region of the magnetosphere (the Funnel or Horn effect) has resulted in significant signals being received by the solar neutron telescope at Mt. Sierra Negra (4,600 m). This information suggests that ions on the solar surface are accelerated to over 10 GeV with an impulsive flare.

This article presents results of the polarization laser studies of the optical and microphysical characteristics of the high-level clouds (HLC). The high-altitude matrix polarization lidar (HAMPL; Tomsk, Russia) is described. HAMPL measures vertical profiles of all elements of the backscattering phase matrix (BSPM) of the HLC. Based on the joint analysis of lidar and radiosonde observations it is shown that the spatial structure of the HLC containing oriented ice crystals is inhomogeneous in the horizontal wind direction. It includes local areas with oriented particles; the sizes of such areas are estimated together with the most probable meteorological conditions of their formation. The shortcomings of the radiosonde observations performed closest to the location of the HAMPL are described. The applicability of the ERA5 reanalysis data of the European Centre for Medium-Range Weather Forecasts for use as an alternative source of information on the vertical profiles of meteorological quantities for the interpretation of HLC lidar sensing data in Western Siberia was checked.

The RHAPS project was launched in 2019 with the major objective to identify specific properties of the fine atmospheric aerosol from combustion sources that are responsible for toxicological effects and can be used as new metrics for health-related outdoor pollution studies. In this paper, we present the overall methodology of RHAPS, and introduce the phenomenology and the first data observed. A comprehensive physico-chemical aerosol characterization has been achieved by means of high-time resolution measurements (e.g. number size distributions, refractory chemical components, elemental composition,) and low-time resolution analyses (e.g. oxidative potential, toxicological assays, chemical composition,…). Preliminary results show a high complexity in the relations observed, the link between air quality and toxicological endpoints being not obvious. We explore data from different points of view: source apportionment of PM1 and the role of source emissions on aerosol toxicity, the oxidative potential as a predictive variable for PM1 toxicity with focus on the secondary organic aerosol possessing redox-active capacity, exposure-response relationships for PM1, and air quality models to forecast PM1 toxicity. We provide a synthesis of results with the outlook to companion papers where data are analyzed in more detail.

We present an analysis of the Dirac equation when the spin symmetry is changed from SU(2) to the quaternion group, $Q_8$, afforded by multiplying one of the $\gamma$-matrices by the imaginary number. The reason for doing this is to introduce a bivector into the spin algebra. This complexifies the Dirac field which separates into two distinct and complementary spaces: one describing polarization and the other coherence. The former describes a 2D structured spin and the latter its helicity, generated by a unit quaternion.

In the theoretical treatment of crystallization it is commonly assumed that relaxation processes of the liquid proceed fast as compared to crystal nucleation and growth processes. Actually, it is supposed that the liquid is located always in the metastable state corresponding to the current values of pressure and temperature. However, near and below the glass transition temperature, Tg, this condition is commonly not fulfilled. In such cases, in the treatment of crystallization, deviations of the state of the liquid from the respective metastable equilibrium state have to be accounted for in determining the kinetic coefficients governing the crystallization kinetics, the thermodynamic driving force of crystallization, and the surface tension of the aggregates of the newly evolving crystal phase including the surface tension of critical clusters affecting considerably the crystal nucleation rate. These factors may considerably influence the course of the overall crystallization process. A theoretical analysis of the resulting effects is given in the present paper by numerical solutions of the J(ohnson)–M(ehl)–A(vrami)–K(olmogorov)–equation employed as the tool to model the overall crystallization kinetics and by analytical estimates of the crystallization peak temperatures in dependence on cooling and heating rates. The results are shown to be in good agreement with experimental data. Possible extensions of the theory to be explored in future analysis are anticipated.

A framework for optimal sensor placement (OSP) for virtual sensing using the modal expansion technique and taking into account uncertainties is presented based on information and utility theory. The OSP maximizes a utility function that quantifies the expected information gained from the data for reducing the uncertainty of quantities of interest (QoI) predicted at the virtual sensing locations. The utility function is extended to make the OSP design robust to uncertainties in structural model and modelling error parameters, resulting in a multidimensional integral of the expected information gain over all possible values of the uncertain parameters and weighted by their assigned probability distributions. Approximate methods are used to compute the multidimensional integral and solve the optimization problem that arises. The Gaussian nature of the response QoI is exploited to derive useful and informative analytical expressions for the utility function. A thorough study of the effect of model, prediction and measurement errors and their uncertainties, as well as the prior uncertainties in the modal coordinates on the selection of the optimal sensor configuration is presented, highlighting the importance of accounting for robustness to errors and other uncertainties.

The Heisenberg {\it ab initio} theory of magnetization is developed to apply for multilayer nanoparticles. The theory is based on distribution and partition functions modification with account the difference between exchange integral and closest neighbour numbers, that change the system of resulting transcendental equation for magnetization and its reversal to form either a paramagnetic type curve or hysteresis loops patterns. The equations are obtained within the Heisenberg partition function construction by Heitler diagonalization of energy matrix via irreducible representations of permutation symmetry group. A combination with the Gauss distribution gives the explicit expression for the partition function in the asymptotic limit] at large spin range in terms of transcendent function. The exchange integral, as a parameter of the equation of state (material equation) is evaluated from Curie temperature value by means of a formula derived within the presented theory. Methods of data processing from the simultaneous solution of the material equation system are proposed. The multi-valued function of hysteresis loop is found by combination of graphical approach and special procedure for elimination of mistaken peaks and prolapses of the patterns. The theory and computation methods are applied to spherical particles with separate surface layers consideration. The contribution of the surface layers, that are specified by number of closest neighbors and exchange integrals into overall magnetization, is studied for two-layer and three-layer models, that are discussed and compared graphically.

Economics has long sought to bridge the principles of microeconomics into the realm of macroeconomics. This paper presents a formal attempt to do so by using a maximum entropy based approach derived from statistical mechanics coupled with subjective game theory and elements from political philosophy. This approach is then applied to income distributions and to the Cobb-Douglas production function, to create a framework for future applications, and to illustrate where past work had made implicit assumptions regarding the system. The paper then explores the consequences of the approach, illustrating self-contradictions in the political philosophy of distributive justice, formally deriving an equation of state for the transactions on the Bitcoin network, and deriving from this the ideal gas law and polytropic process for an economy proving that expansionary monetary policy is not stimulative.

In the case of vascular plants the process of water loss by leafs and water absorption by the root is well known. There is agreement on the passive nature of long-distance moisture movement in the dead cells of the xylem; however, controversy exists focusing on the long-distance water transport principle. Hales (1726) founded a view of bulk flow based on water suction after experiments with cut twigs. The previous doctrine of long-distance water transport within vessel elements and tracheid of the xylem of intact plants – the relevant cohesion theory in text books – was developed mainly by Boehm (1893), Renner (1911) and Dixon (1914) with plant artefacts. Water movement according to this theory is based on an assumed hydrodynamic bulk fluid flow in xylem in continuous water columns (free of water vapour space), under tension, according to the law of Poiseuille (see e.g. Dixon 1914). Physically hydrodynamics is part of fluid mechanics, as a result Poiseuille’s law is usually valid only for hydrodynamic bulk flow in ideal capillaries (Sutera & Skalak, 1993). Besides the basic requirement for transport, according to cohesion theory, the existence of ideal capillaries is not compatible with either: “Because vessel elements and tracheid do not stand as ideal capillaries. …” (Bresinsky et al. 2008, translated from German). Unlike ideal capillaries, the walls of vessel elements and tracheid interact with the transported water. These walls are able to function as a source or as a sink for the transported water because of interaction with the cell walls. With the interaction, vessel elements and tracheid, part of the xylem, can shrink and swell, unlike ideal capillaries. Because the xylem (in woody plants part of the wood) is inconsistent with the basic law of fluid flow, the equation of mass balance (Zimmermann et al. 2004) and cohesion theory are not strictly followed.Many plant physiologists view the cohesion theory as appropriate, however, this theory remains controver­sial, i.e. by Eisenhut (1988), Laschimke (1990) and Hahn (1993). Nultsch (1996) gives doubts referring to the present doctrine of plant water transport. Zimmermann et al. (2004) reject the cohesion theory and conclude: “... that the arguments of the proponents of the Cohesion Theory are completely misleading” (Zimmermann et al. 2004). Hence cohesion theory can be treated as inapplicable and the question arises: how does water transport in fact function? In the following, it is gone into in more detail. A sorption hypothesis of actual water transport, based on empirical fact, shall be addressed in this paper.

We present the real number system as a natural generalization of the natural numbers. First, we prove the co-finite topology, $Cof(\mathbb N)$, is isomorphic to the natural numbers. Then, we generalize these results to describe the continuum $[0,1]$. Then we prove the power set $2^{\mathbb Z}$ contains a subset isomorphic to the non-negative real numbers, with all its defining structure of operations and order. Finally, we provide two different constructions of the entire real number line. We see that the power set $2^{\mathbb N}$ can be given the defining structure of $\mathbb R$. The constructions here provided give simple rules for calculating addition, multiplication, subtraction, division, powers and rational powers of real numbers, and logarithms. The supremum and infimum are explicitly constructed by means of a well defined algorithm that ends in denumerable steps. In section 5 we give evidence our construction of $\mathbb N$ and $\mathbb R$ are canonical; these constructions are as natural as possible. In the same section, we propose a new axiomatic basis for analysis. In the last section we provide a series of graphic representations and physical models that can be used to represent the real number system. We conclude that the system of real numbers is completely defined by the order structure of $\mathbb N$.}

Based on a local causal model of the dynamics of curved discrete spacetime, a causal model of quantum field theory in curved discrete spacetime is described. On the elementary level, space(-time) is assumed to consists of interconnected space points. Each space point is connected to a small discrete set of neighboring space points. Density distribution of the space points and the lengths of the space point connections depend on the distance from the gravitational sources. This leads to curved spacetime in accordance with general relativity. Dynamics of spacetime (i.e., the emergence of space and the propagation of space changes) dynamically assigns "in-connections" and "out-connections" to the affected space points. Emergence and propagation of quantum fields (including particles) are mapped to the emergence and propagation of space changes by utilizing identical paths of in/out-connections. Compatibility with standard quantum field theory (QFT) requests the adjustment of the QFT techniques (e.g., Feynman diagrams, Feynman rules, creation/annihilation operators), which typically apply to three in/out connections, to n > 3 in/out connections. In addition, QFT computation in position space has to be adapted to a curved discrete space-time.

Based on a local causal model of the dynamics of curved discrete spacetime, a causal model of quantum field theory in curved discrete spacetime is described. At the elementary level, space(-time) is assumed to consists of interconnected space points. Each space point is connected to a small discrete set of neighbor space points. Density distribution of the space points and the lengths of the space point connections depend on the distance from the gravitational sources. This leads to curved spacetime in accordance with general relativity. Dynamics of spacetime (i.e., the emergence of space and the propagation of space changes) dynamically assigns "in-connections" and "out-connections" to the affected space points. Emergence and propagation of quantum fields (including particles) are mapped to the emergence and propagation of space changes by utilizing identical paths of in/out-connections. Compatibility with standard quantum field theory (QFT) requests the adjustment of the QFT techniques (e.g., Feynman diagrams, Feynman rules, creation/annihilation operators), which typically apply to three in/out connections, to n > 3 in/out connections. In addition, QFT computation in position space has to be adapted to a curved discrete space-time.

This paper brings to fruition recently found \cite{migdal2023exact} exact reduction of decaying turbulence in the Navier-Stokes equation in $3 + 1$ dimensions to a Number Theory problem of finding the statistical limit of the Euler ensemble. We reformulate the Euler ensemble as a Markov chain and show the equivalence of this formulation to the \textbf{quantum} statistical theory of $N$ fermions on a ring, with an external field related to the random fractions of $\pi$. We find the solution of this system in the turbulent limit $N\to \infty, \nu \to 0$ in terms of a complex trajectory (instanton) providing a saddle point to the path integral over the density of these fermions. This results in an analytic formula for the observable correlation function of vorticity in wavevector space. This is a full solution of decaying turbulence from the first principle without approximations or fitted parameters. The energy spectrum decays as $k^{-\frac{7}{2}}$. We compute resulting integrals in \Mathematica{} and present effective index $n(t) = -t\partial_t \log E $ for the energy decay as a function of time Fig.\ref{fig::NPlot}. The asymptotic value of the effective index in energy decay $n(\infty) = \frac{5}{4}$, but the universal function $n(t)$ is neither constant nor linear.

The rapid increasing rate of soil and water bodies pollution is the main anthropogenic effect caused by the mismanagement of post-consumer plastics. This research evaluated the effectiveness of cattail (Typha Latifolia) fibers (CFs) as bio-adsorbents of microplastic particles (MPPs) from wastewater. The effect of the adsorption environment composition on the adsorption rate was investigated. Batch tests were conducted to evaluate the “spontaneous” adsorption of MPs onto CFs. Five MPPs materials (PVC, PP, LDPE, HDPE, and Nylon 6) were evaluated. An industrial wastewater (PW) and Type II Distilled Water (DW) were employed as adsorption environments. The batch tests results show that CFs are effective in removing MPPs from DW and PW. However, higher removal percentage of MPPs were obtained in PW, ranging from 89% to 100% for PVC, PP, LDPE, and HDPE; while the adsorption of Nylon 6 increased to 29.9%, a removal increased of 50%. These observations indicate that hydrophobic interactions drive the “spontaneous and instantaneous” adsorption process and that adjusting the adsorption environment effectively enhances the MPPs removal rate. This research demonstrates the important role that bio-substrates can play in reducing the environmental pollution as efficient, sustainable, low cost, and reliable adsorbents for the removal of MPPs from wastewaters.

The objective of this research is to analyze metal elements like Na (sodium), Mg (magnesium), Al (aluminum), Si (silicon), Pb (lead), K (potassium), Ca (calcium), and Fe (iron) found in dust particles within two distinct areas from which the sampling has been done. First sampling was taken from the road verge of a highly trafficked road section, while the second sampling was done in a residential garden area 90 m away from the road. Several metal elements have been detected, with a high difference for Silicon Si, which present higher concentrations in the dust sampled from the road verge area. Pb has only been detected in the samples taken from the road verge, which could be explained by residual remnants from old lead gasoline, and wheel weights. Additionally, airborne particulate matter (PM) concentrations have been measured, during the same episode, in comparison between the road verge and the garden area, presenting a substantial difference in the concentration levels, deducing that dense vegetation is protecting and blocking a majority of airborne PM. A literature highlight of health effects of different metal elements and PM concentrations is presented.

This study presents a methodology to reveal traces of viral particles, as aerosol with known chemical and molecular structure, in a sample by means of photon and electron interactions. The method is based on Monte Carlo simulations and on the analysis of photon-electron fluxes-spectra through energy channels counts as a function of different aerosol viral concentrations in the air sample and looking at the peculiar photon/electron interactions with the potential abnormal atomic hydrogen (H), oxygen (O), carbon (C), and phosphorus (P) compositions present in the air sample as a function of living and nonliving matter with PO4 group RNA/DNA strands in a cluster configuration.

It is widely recognized that rapid urbanization and urban change are defining traits of the contemporary era, bringing both daunting challenges and hopeful opportunities. It is therefore critical that we have a clear and actionable model of the nature of urban space and the dynamics of its functions and dysfunctions to guide policy and practice. Yet the field today includes a range of definitions that are often inconsistent and often conflating very different properties of urban land, often expressed in some version of the conflated characterization, “over half of humanity now lives in cities.” In the last several decades, more articulated theoretical models have been advanced, with notable differences and discrepancies as well as partial commonalities. Here we assess the various models, and we formulate a consolidated and “consilient” theoretical model that may help guide policy and practice through an era of increasingly daunting urban challenges. In particular, the model focuses upon the cellular network structure of public and private spaces, and the dynamics of their evolution under human control – a theoretical model we refer to as Place Network Theory.

Which machine-learning model is the best at winning the prisoner’s dilemma? Which models create the best cumulative outcomes? Is there a model that perfectly captures both winning and cumulative points? These are questions generated from a simple 2 x 2 payoff matrix of the prisoner’s dilemma. Imagine you and your partner in crime are caught and sent independently into questioning. You can either collaborate or defect, but you don’t know what your partner will do. If you both collaborate, cumulatively, you’ll each get one year in jail. If you defect and your partner collaborates, you’ll serve no time and they will serve 10 years, and vice versa. If you both defect, you’ll both serve 5 years in jail. Placing AIs against each other to play just one round doesn’t reveal much about their code, strategy, and end goal. So the Reinforcement Learning, Pattern Learning, Tit For Tat, and other models were put up against each other in a 100 round game where their behavior, convergence, and learning were analyzed to reveal the most effective ways strategies to beat the prisoner’s dilemma. All code and data is open sourced here.

We study how abstract representations emerge in a Deep Belief Network (DBN) trained on benchmark datasets. Our analysis targets the principles of learning in the early stages of information processing, starting from the “primordial soup" of the under-sampling regime. As the data is processed by deeper and deeper layers, features are detected and removed, transferring more and more “context-invariant” information to deeper layers. We show that the representation approaches an universal model – the Hierarchical Feature Model (HFM) – determined by the principle of maximal relevance. Relevance quantifies the uncertainty on the model of the data, thus suggesting that “meaning" – i.e. syntactic information – is that part of the data which is not yet captured by a model. Our analysis shows that shallow layers are well described by pairwise Ising models, which provide a representation of the data in terms of generic, low order features. We also show that plasticity increases with depth, in a similar way as it does in the brain. These findings suggest that DBNs are capable of extracting a hierarchy of features from the data which is consistent with the principle of maximal relevance.

While the quantum realm seems hidden, it can also reach examples of infinite energy, especially when a part of space is roughly removed until it disappears, possibly forever. Since it follows that {\it Nothing } can enter a region where the space is missing, the quantum realm, as seen now in affine quantization, will automatically come to help everything else by creating colossal `quantum walls' that will ensure that everything stays out of all black holes. In this article, we show that the expanded quantum realm allows {\it Nothing} to ever fall into a black hole.

Molecular transport and quantum tunneling of H2 and H2O molecules through nanoporous gra-phene is studied using computational modeling and first principles density functional theory. It is demonstrated that molecules with sufficiently high kinetic energies can tunnel through the na-nopores. It is also demonstrated that molecules can be trapped in front of the nanopore or behind it. These investigations help us learn the behavior of molecules in and around nanopores of gra-phene. They also help us learn fundamentals of molecular tunneling. We believe, nanoporous gra-phene can play important roles for gas separation and nanofiltration.

Autonomous search is an ongoing cycle of sensing, statistical estimation and motion control with objective to find and localise targets in a designated search area. Traditionally, the theoretical framework for autonomous search combines the sequential Bayesian estimation with the information theoretic motion control. This paper formulates autonomous search in the framework of possibility theory. Although the possibilistic formulation is slightly more involved than the traditional, it provides means for quantitative modelling and reasoning in the presence of epistemic uncertainty. This feature is demonstrated in the paper in the context of partially known probability of detection, expressed as an interval value. The paper presents an elegant Bayes-like solution to sequential estimation, with the reward function for motion control defined to take into account the epistemic uncertainty. The advantages of the proposed search algorithm are demonstrated by numerical simulations.

This article serves as a preliminary introduction to the design of a new, open-source applied and computational category theory framework, named Categorica, built on top of the Wolfram Language. Categorica allows one to configure and manipulate abstract quivers, categories, groupoids, diagrams, functors and natural transformations, and to perform a vast array of automated abstract algebraic computations using (arbitrary combinations of) the above structures; to manipulate and abstractly reason about arbitrary universal properties, including products, coproducts, pullbacks, pushouts, limits and colimits; and to manipulate, visualize and compute with strict (symmetric) monoidal categories, including full support for automated string diagram rewriting and diagrammatic theorem-proving. In so doing, Categorica combines the capabilities of an abstract computer algebra framework (thus allowing one to compute directly with epimorphisms, monomorphisms, retractions, sections, spans, cospans, fibrations, etc.) with those of a powerful automated theorem-proving system (thus allowing one to convert universal properties and other abstract constructions into (higher-order) equational logic statements that can be reasoned about and proved using standard automated theorem-proving methods, as well as to prove category-theoretic statements directly using purely diagrammatic methods). Internally, Categorica relies upon state-of-the-art graph and hypergraph rewriting algorithms for its automated reasoning capabilities, and is able to convert seamlessly between diagrammatic/combinatorial reasoning on labeled graph representations and symbolic/abstract reasoning on underlying algebraic representations of all category-theoretic concepts. In this first of two articles introducing the design of the framework, we shall focus principally upon its handling of quivers, categories, diagrams, groupoids, functors and natural transformations, including demonstrations of both its algebraic manipulation and theorem-proving capabilities in each case.

The hybrid in-band on-channel (IBOC) transmission system as a digital audio radio scheme could transmit analog FM and digital audio simultaneously. In IBOC systems, broadcasters transmit signals within the allocated channel bands, so the bandwidth allocated for digital audio transmission is a big challenge. In view of the above, the use of cooperative game theory, supported by the use of the bankruptcy game and Shapley's value, is proposed as a strategy to optimize the bandwidth allocation at each node or station, according to the demand in the service, the number of stations and the radio channel conditions in the FM band. The paper proposes a scenario under saturated traffic conditions, in order to evaluate the degree of optimization that the Shapley value can perform under clearly established traffic and channel conditions. The evaluation process yielded a quite favorable result, where it is observed that the use of cooperative game theory supported by the Shapley value can be considered as an excellent alternative when performing bandwidth optimization processes for digital broadcasting over IBOC in FM and with the possibility of being implemented in other digital radio broadcasting systems.

We give a bilocal field theory description of a composite scalar with an extended binding potential, that reduces to the Nambu–Jona–Lasinio (NJL) model in the pointlike limit. This provides a description of the internal dynamics of the bound state and features a static internal wave-function, ϕ(⃗r), in the center-of-mass frame that satisfies a Schr¨odinger-Klein-Gordon equation with eigenvalues m2. We analyze the “coloron” model (single perturbative massive gluon exchange) which yields a UV completion of the NJL model. This has a BCS-like enhancement of its interaction, ∝ Nc the number of colors, and is classically critical with gcritical remarkably close to the NJL quantum critical coupling. Negative eigenvalues for m2 lead to spontaneous symmetry breaking, and the Yukawa coupling of the bound state to constituent fermions is emergent.

Mallios and Zafiris emphasize that adjoint functors or adjunctions are not only "ubiquitous" in category theory but characterize the naturality of their approach to physical geometry. Hence in this paper, the history and theory of adjoint functors is investigated. Where do adjoint functors come from mathematically and how did the concepts develop historically?

In this note we consolidate and give a brief description of several recently published results in ring theory having disproof. These results have been published during 2016 to 2021 in the so called non-predatory reputed mathematical journals indexed in the well known database like Scopus. We have considered results on rings in which each element is a sum of two idempotents appeared in Canad. Math. Bull. (2016), weakly tripotent rings appeared in Bull. Korean Math. Soc. (2018) and Rendiconti Sem. Mat. Univ. Pol. Torino (2021), involution t-clean rings appeared in Eur. J. Pure Appl. Math (2022) and strongly 2-nil clean rings with units of order two appeared in Eur. J. Pure Appl. Math (2023).

The compatibility between the de Sitter Swampland conjecture and Ho\v{r}ava-Lifshitz $F(\bar{R})$ theories with a flat FLRW metric is studied. We first study the standard $f(R)$ theories and show that the only way in which the dS conjecture can be made independent of $R$ is by considering a power law of the form $f(R)\sim R^{\gamma}$. The conjecture and the consistency of the theory puts restrictions on $\gamma$ to be greater but close to $1$. For the $F(\bar{R})$ theories described by its two parameters $\lambda$ and $\mu$ we use the equations of motion to construct the function starting with an ansatz for the scale factor in the Jordan frame of the power law form. By doing a conformal transformation on the three metric to the Einstein frame we can obtain an action of gravity plus a scalar filed by relating the parameters of the theory. The non-projectable and projectable cases are studied and the differences are outlined. The $F(\bar{R})$ function obtained consists of terms of the form $\bar{R}^{\gamma}$ with the possibility of having negative power terms. The dS conjecture leads to inequalities for the $\lambda$ parameter, in both versions it gets restricted to be greater but close to $1/3$. For the general case in which $\mu$ and $\lambda$ are considered as independent, the action contains an extra term but we propose that the conjecture is still applicable. Once again the non-projectable and projectable cases are studied. The $F$ function obtained has the same form as before, the consistency of the theory and the dS conjecture lead to a set of inequalities on both parameters that are studied numerically. In all cases $\lambda$ is restricted by $\mu$ around $1/3$ and we obtain $\lambda\to1/3$ if $\mu\to0$. Finally we consider the $f(R)$ limit $\mu,\lambda\to1$ and we obtain consistent results.

Various formulations of the exact renormalization group can be compared in the perturbative domain, in which we have reliable expressions for regularization-independent (universal) quantities. We consider the renormalization of the $\lambda\phi^4$ theory in three dimensions and make a comparison between the sharp-cutoff regularization method and other more recent methods. The former gives considerably better results, while the other methods are far from optimal in the perturbative domain. In addition, these methods present theoretical problems that are already manifest in the renormalization of mass.

In response to escalating environmental concerns and the surge in eco-friendly sports activities, this study investigates the determinants of sustained intention to participate in plogging, a prac-tice that combines jogging and litter collection. The study seeks to discern the effects of autonomy, competence, and relatedness experiences, as suggested by Self-Determination Theory, on the intent to persist in plogging. Additionally, the study probes the moderating role of eco-friendly attitudes, thereby propelling the confluence of sports and environmental research. The research methodology encompassed surveying plogging participants and analyzing their responses. The validation of these relationships was executed using multi-group structural equation modeling. The results revealed that autonomy and competence did not significantly sway extrinsic motivation, but relatedness surfaced as the most influential factor. This suggests that plogging, primarily viewed as a volunteering activity, serves more as a prosocial behavior that bolsters relationships rather than a means to enhance physical competence. The study also found that the value participants derived from plogging and their intention to continue varied based on their eco-friendly attitudes. The study concludes that voluntary participation and socializing are the core values of plogging, and understanding these values can foster healthier and more sustainable behaviors. The findings offer valuable insights for academic, practical, and policy perspectives in promoting eco-friendly sports activities.

A review on several classical, algebraic models in nuclear structure physics, which use symmetries as an important tool, are presented. After a conceptual introduction to group theory, a selection of models is chosen to illustrate the methods and the power of the usage of symmetries. It enables to describe very involved systems in a greatly simplified manner. Some problems are also discussed, when ignoring basic principles of nature, as the Pauli Exclusion principle. We also show that, nevertheless, occasionally one can rescue these omissions. In a couple of representative models, applications of symmetries are explicitly applied, in order to illustrate how extremely complicate systems can be treated. This contribution is meant bas a review on the use of algebraic models in nuclear physics, leading to a better understanding of the articles in the same special volume.

With a worldwide growing concern for greenhouse gas (GHG) emissions and their impact on human health and the environment, transportation has become a central theme in mitigation, responsible for 14% of human GHG emissions. To build endurance to climate change, transportation services must adapt to the current scenario and act quickly to avert future changes. Deeply rooted changes in socio-technical systems will be necessary to achieve significant CO2 reduction and secure the well-being of future generations. This study's objective is to comprehensively review the current state of carbon mitigation in the transportation sector. This is done through a systematic literature review engrained in the socio-technical transition theory and the structural theory of contingency. Twenty-six review papers covering 2,983 original articles are selected for full-text examination concerning carbon emissions in transportation. Enablers, barriers, benefits, disadvantages and metrics in carbon emissions reduction are identified, and a comprehensive framework is built. Results provide a view of the current sustainability scenario in transportation and allow a better understanding of the factors influencing carbon emission initiatives in transportation and its outcomes.

There has been a disconnect between our understanding of the universe's working at the micro and macro scale - that is, disagreement between quantum mechanics (QM) and general relativity (GR). A theory of vacuum-matter equilibrium is presented from scratch to bridge this gap. It is proposed that gravitons are both quanta of matter and gravitation, as every matter entity is believed to interact with gravitation. The vacuum has an energy density that gives rise to virtual-graviton pairs. Upon collision, a virtual-graviton may get stuck to the matter while a graviton from the matter gets ejected. It is possible as all gravitons are identical in mass and size. Equilibrium is thus established where matter erodes in the vacuum, and the vacuum condenses as matter. The probability of graviton exchange depends on the relative energies of the virtual-graviton and matter entity, as calculated in the inertial frame of reference (IFoR) decided by the state motion of vacuum energy at that place. If the rate of matter-vacuum equilibrium is taken as a constant, it leads to the notion of time and time dilation. The force appearing on a matter entity through collision with virtual-gravitons is calculated, and the expression is a hybrid of Newton's and Einstein's equation. It further helps to answer the queries related to phenomena like the flatness of galaxy rotation curves, misconceptions about relativistic mass and length contraction, the relation between time, gravity, and quantum entanglement (QE), and the composite nature of the universal gravitational constant.

The efficiency of the MOND theory of Mordehai Milgrom might be unrelated to distance, but instead connected to flatness of galaxies and the fact that the large scale distribution of matter is essentially two-dimensional. A combination of the pushing gravity paradigm with essential flatness of large luminous matter clusters leads to an approximate MOND theory which would allow to avoid the dark matter hypothesis.

In this paper, we propose a quantitative definition of emergence from the density matrix framework as a state of knowledge of the system and its generalized probability formulation, in order to detect emergent properties. We propose the use of a descriptor based on the difference of von Neumann entropy, to calculate if subsystems of systems have inner correlations by defining emergent systems in terms of emergent information.

A therapy’s outcome is determined by a tumor’s response to treatment which, in turn, depends on multiple factors such as the severity of the disease and the strength of patient’s immune response. Gold standard cancer therapies are in most cases fragile when sought to break the ties to either tumor kill ratio or patient toxicity. Lately, research has shown that cancer therapy can be at most robust when handling adaptive drug resistance and immune escape patterns developed by evolving tumors. This is due to the stochastic and volatile nature of the interactions, at the tumor environment level, tissue vasculature, and immune landscape, induced by drugs. Herein, we explore the path towards antifragile therapy control, that generates treatment schemes that are not fragile but go beyond robustness. More precisely, we describe a first instantiation of a control-theoretic method to make therapy schemes cope with the systemic variability in the tumor–immune–drug interactions and gain more tumor kill with less patient toxicity. Considering the anti-symmetric interactions within a model of the tumor–immune–drug network, we introduce the antifragile control framework that demonstrates promising results in simulation. We evaluate our control strategy against state-of-the-art therapy schemes on various experiments and discuss the insights we gained on the potential that antifragile control could have in treatment design in clinical settings.

Evolution by natural selection is often viewed as an optimisation process where an organism's phenotypic traits are adapted gradually to improve its fitness. Because of the many different traits with potentially conflicting requirements, among other factors, this optimisation process may appear onerous. Building on recent mathematical work connecting optima and simplicity, we here show that for certain generic phenotype fitness requirements --- those based on physics and engineering principles --- optimal phenotypic shapes will tend to `simple', in the sense of low algorithmic or descriptional complexity. As a result, we argue that adapting to these types of generic fitness requirements will be a much `easier' task for natural selection, compared to a null expectation based on arbitrary optimisation requirements. Further, selection's task may be easier still due to the fact that optimal phenotypes for one set of generic fitness constraints may also be close to optimal for other generic constraints, such that adapting to one constraint yields the other `for free'.

We present a Quantum Space Model (QSM) of the evolution of the universe based on the theory that space consists of energy quanta from which it began. We used the Friedmann equations to trace its history and show that Dark Energy is the energy of space which caused its accelerating expansion.The universe started from a quanta of space which was triggered by quantum fluctuations that caused the Big Bang. It then expanded and cooled undergoing phase transitions to radiation, fundamental particles, and matter. Matter grew into galaxies, and was consolidated by gravity into Black Holes, ending in a Big Crunch and Deep Freeze inside a Black hole at 1.380 trillion years. Fluctuations caused a new Bang to start another cycle in its life. If the Law of Conservation of Energy is universal, then the cosmos is eternal. Our results support the theoretical predictions of a cyclic universe by Steinhardt and associates, as well as Penrose. Space and energy are equivalent as embodied in the Planck energy equation. They are the two most fundamental quantities that govern cosmic evolution. The two principal long range forces are the gravitational force and the space force,which maybe the fifth force in the universe. They provide the clockwork mechanism operating our cyclic universe.

Scientific theories on the functioning and dysfunction of the human brain require a good understanding of both its development — before and after birth, and through maturation to adulthood — and its evolution from the ancestral primate brain. Adopting a complex-systems approach, here we propose that the apparent uniqueness of humans’ cognitive capacities might best be understood as emerging from multiple nested “virtuous cycles.” In particular, we propose that the intimate link that exists between oxygen metabolic loops, cortical expansion, and ultimately cognitive and social demands is a key driver of genetic developmental programs for the human brain. Overall, our proposed evolutionary model makes explicit mechanistic links between metabolism, molecular and cellular brain heterogeneity, and behaviour that may in time provide a clearer understanding of brain developmental trajectories and their disorders.

In this paper, we examine the weak abc conjecture and the strong abc conjecture using some functions. we attempt to discuss the possibilty that the negative consequence of the weak abc conjecture. Namely, we derive that the weak abc conjecture is not true. Additionally, we show that the strong abc conjecture is not true.

Electrically charged particles such as Electrons and Protons carry electric, E, and magnetic, B, fields. In addition to these fields, Quantum Mechanics (QM) endows these particles with an `arcane and spooky' field --- the wavefunction. This wavefunction of QM is not only assumed to be separate but distinct from the electromagnetic field. We herein upend this view by demonstrating otherwise. That is, we demonstrate that the four components of the Dirac wavefunction, can be shown to not only be an intimate, but, a direct function of the electromagnetic field carried by the particle in question. Insofar as unity, depth in our understanding and insight into both Dirac and Maxwell's equations as major pillars of Modern Physics, we believe that this work may very well inch us one-step-closer to the truth.

Formation in soccer is among the most important tactical choices for a successful match.Herein, the simulations of 420000 match-plays have been performed varying the formation, the number of opponents that are actively pressing the team, the speed of the opponents in attempting a pass interception. Dribbling has been neglected. The match-play ends either with a successful series of passes from a central back to the line of the strikers or with the opponents that steal the ball. In this work, I demonstrate that 3-4-3 formation, which is among the most employed formations, relates to the highest probability of success.

With the goal of representing common denominators of aging in different organisms López-Otín et al. in 2013 described nine hallmarks of aging. Since then, this representation has become a major reference point for the biogerontology field. The template for the hallmarks of aging account originated from landmark papers by Hanahan and Weinberg (2000, 2011) defining first six and later ten hallmarks of cancer. Here we assess the strengths and weaknesses of the hallmarks of aging account. As a checklist of diverse major foci of current aging research, it has provided a useful shared overview for biogerontology during a time of transition in the field. It also seems useful in applied biogerontology, to identify interventions (e.g. drugs) that impact multiple symptomatic features of aging. However, while the hallmarks of cancer provide a paradigmatic account of the causes of cancer with profound explanatory power, the hallmarks of aging do not. A worry is that as a non-paradigm the hallmarks of aging have obscured the urgent need to define a genuine paradigm, one that can provide a useful basis for understanding the mechanistic causes of the diverse aging pathologies. We argue that biogerontology must look and move beyond the hallmarks to understand the process of aging.

Living organisms with developed endocrine systems react in a complex way to environmental changes. Changing atmospheric pressure causes different blood pressures or hormone levels; carcinogenic radiation modifies the structure of DNA. Charged particles and ions act as neurotransmitters and block certain types of protein channels and receptors. A high concentration of carbon dioxide has an indirect effect on both blood pressure and neuron activity. The bioelectric nature of living tissues highlights the complexity of the connection between the dynamic physical environment and biological systems. Recent results from studies on the interactions and connections mentioned above are reviewed in this paper.

This paper explores multiple perspectives and proofs regarding the validity of what is considered to be one of the – if not THE - most controversial proofs in the field of mathematics, historical and contemporary applications alike. We consider the various explanations and equivalents of the axiom along with the more widely receptive alternatives. Furthermore, we review the resistance the axiom has encountered in various fields and its potential use in the research and expansion of said fields.

Divergences have become a very useful tool for measuring similarity (or dissimilarity) between probability distributions. Depending on the field of application, a more appropriate measure may be necessary. In this paper we introduce a family of divergences called γ-Divergences. They are based on the convexity property of the functions that generate them. We demonstrate that these divergences verify all the usually required properties, and we extend them to weighted probability distribution. In addition, we define a generalised entropy closely related to the γ-Divergences. Finally, we apply our findings to the analysis of simulated and real time series.

Imagination is more important than knowledge, but if intellect does not provide the needed logical structures, capacities for envisioning new possibilities are overly constrained. The sustainability problems we face today cannot be solved with the same kind of thinking that created them, but clarity on what counts as a new kind of thinking is sorely lacking. This article proposes methodical, model-based ways of heeding Bateson's warning about the negative consequences for the ecology of mind that follow from ignoring the contexts of relationships. Informed by S. L. Star's sense of boundary objects, a sequence of increasingly complex logical types distinguishes and interconnects qualitatively different kinds of thinking in ways that liberate imaginative new possibilities for life. The economy of thought instantiated at each level of complexity is only as meaningful, useful, beautiful, ethical, and efficient as the standards informing local adaptive improvisations. Standards mediating the general and specific, global and local, universally transcendent and embodied particulars enable meaningful negotiations, agreements, and communications. Attending to the differences between levels of discourse sets up new possibilities for creative and imaginative entrepreneurial approaches to viable, feasible, and desirable goals for measuring and managing sustainable development.

This paper addresses the fate of extended space-time symmetries, in particular conformal symmetry and supersymmetry, in two-dimensional Rindler space-time appropriate to a uniformly accelerated non-inertial frame in flat 1+1-dimensional space-time. Generically, in addition to a conformal co-ordinate transformation, the transformation of fields from Minkowski to Rindler space is accompanied by local conformal and Lorentz transformations of the components, which also affect the Bogoliubov transformations between the associated Fock spaces. I construct these transformations for massless scalars and spinors, as well as for the ghost and super-ghost fields necessary in theories with local conformal and supersymmetries, as arising from coupling to 2-D gravity or supergravity. Cancellation of the anomalies in Minkowski and in Rindler space requires theories with the well-known critical spectrum of particles arising in string theory in the limit of infinite strings, and is relevant for the equivalence of Minkowski and Rindler frame theories.

It is shown through three different approaches that, contrary to a long-standing conviction, the orbit of Mercury behaves as required by Newton's equations with a very high precision if one correctly analyzes the situation in the framework of the two-body problem without neglecting the mass of Mercury.

The study of values at European and global level has gained momentum along with the theory of values launched by Schwartz. Values are dormant, hidden, unobservable and impossible to measure directly. They exist somewhere within the human being, manifested by different attitudes, depending on their degree of generality. The paradigm of basic human values implies shared universal values that are encountered in cultures all over the world. The theory of values designed by Schwartz has refined the pool of 19 basic individual values representing principles in individuals and group, further describing the dynamic relationships among them. This study presents practical evidence of the dynamics between individual values, the dynamics theorized by Schwartz in 2012. Following the development of an online questionnaire made up of 46 items with online responses options on a Lickert scale from 1 to 6, where 1 represents less important and 6 represent very important, 220 young people from Western Romania voluntarily responded. By testing the hypothesis assuming the dynamic relationship between the two values through multiple regression analysis, the results demonstrate that in Model 1, which involves a linear relationship, health explains 42% of the variance in security with a F =161,215 significant at p <.01. In Model 2, which involves a curvilinear relationship, health explains 50% of the variance in security version with a F = 35,336 significant at p <.01. The incremental prediction optimization of 8% added by including the squared security accounts for the curve in the regression line, indicating the existence of a curvilinear relationship between security and health. The dynamic relationship demonstrates that upper limit and lower limit aspects of security, significantly influence the health value in a negative way. Normal levels of security trigger a high level of prioritization of health value. The implications of this type of relationship are discussed in explaining the value phenomenon at individual level. The study shows limits due to the selected sample, focusing exclusively on young people with higher education from the Western region of Romania. This sample was the target group of "The National Identity of Romanian Youth" project which designed this research.

The electric field is enormously more powerful than the gravitational field. However, in our normal experience there is no electric field, the electric force is missing. How is it that when you get to larger and larger scales the gravitational field is extremely important whereas the electric field becomes less and less important [1]? This paper proposes a model to explain why gravitation dominates at a larger scale.

In this paper, the elemental construct of an I-shaped fin cooling a heat generating volume is studied through the entropy production perspective. Using the constructal design method framework with entropy production minimization as an objective leads to different optimal shape ratio, different from the ones obtained using the excess of temperature. Moreover, the optimal shape ratio evolution is not necessary the same for local entropy production minimization (excess of entropy production) and global entropy production (entropy produced in the whole area). Finally, an analysis on a possible dimensionless number is introduced for the study of constructal plates.

In this paper, we study the weighted reproducing kernels. We introduce a generalization of weighted reproducing property and extend it to relative reproducing property on Banach spaces. This generalization will develop the parallel computing and it can be used as a base of parallel learning for machines especially in the case that there are non-homogenous weighted hypothesis. This methods formulate learning and estimation problems in a relative reproducing kernel Banach space (RRKBS) of functions defined on the data domain, expanded in terms of a kernel.

Information theory has been developed for seventy years with technological applications that have transformed our societies. The increasing ability to store, transmit, and process information is having a revolutionary impact in most disciplines. The goal of this work is to compare the formal approach to information with Buddhist philosophy. Considering both approaches as compatible and complementary, I argue that information theory can improve our understanding of Buddhist philosophy and vice versa. The resulting synthesis leads to a worldview based on information that overcomes limitations of the currently dominating physics-based worldview.

Lack of physical activity participation for adults with a disability remain a large public health concern. For those with existing, or newly acquired disability, increased sedentary behavior stemming from physical impairments often results in the development of secondary chronic health conditions (e.g., obesity or osteoarthritis) which leads to participation restrictions within major life roles. Without intervention these secondary conditions further increase physical impairment which, in turn, sets these populations up for continuous negative health trajectories over their remaining lifespan. Physical activity can attenuate the development of secondary health conditions and optimize health outcomes within these populations. However, those with disability often do not possess the necessary physical capacity to maintain physically active lifestyles. Therefore, exercise programs specifically designed to increase physical functioning have been identified as a necessary intermediate step to reduce physical limitations prior to adoption of physically active lifestyles. Adoption of exercise program participation remains a difficult task for both the general population and those with disability alike. Based on current rates of physical inactivity, it is clear that traditional health behavior change models do not adequately address the complexity of this issue. This paper highlights some of the limitations within the current health behavior change models as they relate to exercise behavior. Additionally, a novel conceptual framework is presented for the intent of its incorporation within research and health promotion interventions targeting exercise behavior within disability populations.

Starting with BitTorrent and then Bitcoin, decentralized technologies have been on the rise over the last 15+ years, gaining significant momentum in the last 2+ years with the advent of platform ecosystems such as the Blockchain platform Ethereum. New projects have evolved from decentralized games to marketplaces to open funding models to decentralized autonomous organizations. The hype around cryptocurrency and the valuation of innovative projects drove the market cap of cryptocurrencies to over a trillion dollars at one point in 2017. These high valued technologies are now enabling something new: globally scaled, decentralized business models. Despite their valuation and the hype, these new business ecosystems are frail. This is not only because the underlying technology is rapidly evolving, but also because competitive markets see a profit opportunity in exponential cryptocurrency returns. This extracts value from these ecosystems, which could lead to their collapse, if unchecked. In this paper, we explore novel ways for decentralized economies to protect themselves from, and coexist with competitive markets at a global scale utilizing decentralized technologies such as Blockchain.

This study aimed to know the conditioning factors of the transition process to the self-care of women diagnosed with HIV/AIDS. This qualitative study was carried out from June to September 2015 with seven seropositive women, users of a specialized service in sexually transmitted diseases in the municipality of Imperatriz, Maranhão State, Brazil. For the data collection, an individual interview was used, and data analysis was performed by content analysis delineated by Hsieh and Shannon (2005). The resources that influence the self-care in the transition process of women with HIV/AIDS are represented by personal conditioning factors, such as the meaning they attribute to the living with the disease, personal attitudes and cultural beliefs, socioeconomic status, preparation and knowledge about the disease, and by conditioning factors found in the community and society. The transition theory can provide important insights about the resources present in the adaptation process of women diagnosed with HIV so that they can perform their self-care satisfactorily.

The objective of the this study was to reduce the benzo[a]pyrene-induced hepatotoxicity method in herbal medicine products and to give proof that neferine, daidzein, genistein possess antihepa-totoxic effects. B[a]P which classified as a group 1 carcinogen and metabolized to B[a]P-7,8-dihydrodiol-9,10-epoxide (BPDE) causes mutagenic DNA addition products. The reduc-tion of BPDE-DNA adduct formation by B[a]P-7,8-dihydrodiol-9,10-epoxide (BPDE) was derived by benzo[a]pyrene (B[a]P). In HepG2 cells, B[a]P exhibited toxicity and substance treatment of the cells with B[a]P with neferine in lotus and daidzein, genistein in soybean reduced the BPDE-DNA ad-ducts level. The level of B[a]P-metabolites in the substance treatment of the cells was presented that BPDE levels were reduced by neferine in lotus and daidzein, genisten in soybean. These results suggest that neferine in lotus and daidzein, genistein in soybean prevent B[a]P-induced hepato-toxicity for BPDE-DNA adduct formation.

BackgroundThe use of antimicrobials to treat food animals may result in antimicrobial residues in foodstuffs of animal origin. The European Medicines Association (EMA) and World Health Organization (WHO) define safe antimicrobial concentrations in food based on acceptable daily intakes (ADIs). It is unknown if ADI doses of antimicrobials in food could influence the antimicrobial susceptibility of human-associated bacteria. ObjectivesThis aim of this study was to evaluate if the consumption of ADI doses of erythromycin could select for erythromycin resistance in a Galleria mellonella model of Streptococcus pneumoniae infection. Methods A chronic model of S. pneumoniae infection in G. mellonella larvae was used for the experiment. Inoculation of larvae with S. pneumoniae was followed by injections of EMA (0.0875 μg/ml) and WHO (0.012 μg/ml) ADI doses of erythromycin proceeded by isolation of S. pneumoniae colonies on selective agar plates. Minimum inhibitory concentrations (MICs) of resistant colonies were measured, and whole genome sequencing (WGS) was performed followed by variant calling to determine the genetic modifications.   Results Exposure to single doses of both EMA and WHO ADI doses of erythromycin resulted in the emergence of erythromycin resistance in S. pneumoniae. Emergent resistance to erythromycin was associated with a mutation in rplA. Conclusion In our in vivo model, even single dose of erythromycin that are classified as acceptable by the WHO and EMA induced significant increases in erythromycin MICs in S. pneumoniae. These results suggest the need to include the induction of antimicrobial resistance (AMR) as a significant criterion for determining ADIs.

The iron roughneck is an automated equipment utilized for the connection and removal of drilling tools. This paper presents the design of an integrated iron roughneck, providing a detailed introduction to its clamp body structure, along with an analysis of its structural characteristics and performance requirements. The study delves into the integration mode and working characteristics of the clamping mechanism and spin buckle mechanism for the integrated upper clamp body structure of the iron roughneck. Additionally, this paper conducts an in-depth theoretical study on the spin buckle mechanism. Firstly, it analyzes the actual working condition of the spin buckle roller from two perspectives: contact theory and rolling friction theory, determining the structural form of the spin buckle roller. Secondly, it investigates the relative displacement between the spin buckle mechanism and the drilling tool, proposing a design method for the floating device mounted on the spin buckle roller and establishing the kinematic equation of the spin buckle roller under the influence of the floating device. Furthermore, the kinematic equations of the spin buckle roller under the influence of the floating device are established. Finally, a dynamics simulation experiment is performed to simulate the working process of the spin buckle mechanism under actual working conditions, analyzing the dynamics and kinematics of the spin buckle mechanism and obtaining the relevant parameter curves of the spin buckle mechanism and drilling tools. Through data comparison and analysis, the correctness of the theoretical analysis results and the rationality of the performance and structure of the spin buckle mechanism are verified.

This study aims to refine our understanding of evolutionary processes, particularly as they apply to complex organisms, using an innovative graph-based simulation approach. We model the topological evolution of simple (5-node ring graph) and complex (20-node dense random graph) organisms over 10 generations, applying different mutation rates to reflect biological realities. Our results provide intriguing insights into the potentially different evolutionary dynamics at play in simple versus complex organisms. While simple organisms demonstrate high topological flexibility and rapid adaptability, aligning with classical evolutionary models, complex organisms exhibit a surprising degree of structural stability. This stability persists even under mutation rates that would typically drive significant changes in simpler systems. The simulation highlights an important consideration: the intricate, interdependent networks characteristic of complex organisms may create a form of evolutionary buffering. This buffering could modulate the impact of random mutations and natural selection – processes that are cornerstones of evolutionary theory. Our findings suggest that the high degree of complexity in advanced life forms may necessitate a more nuanced view of how evolutionary processes operate across different levels of biological organization. Furthermore, the emergence of new structural motifs in simple organisms, contrasted with the relative conservation in complex topologies, indicates that evolutionary mechanisms may manifest differently across the spectrum of biological complexity. This observation invites a more detailed exploration of how evolutionary principles apply to diverse life forms.These results contribute to the ongoing refinement of evolutionary theory, especially in its application to complex organisms. They suggest that additional mechanisms, such as constrained mutations, epigenetic changes, or higher-order organizational principles, may play significant roles alongside random mutations and natural selection in the evolution of complex life forms.

Several mathematicians and physicists are working all over the globe to get a unified theory. However, most of them are discarding Einstein’s view at the very first step of their theories. This article provides a brief description about this. Also, on the basis of Koga’s theory we point out two reasons which might have caused Einstein’s failure to get a unified theory.

For the better part of a century researchers across disciplines have sought to explain the crystallography of the elemental transition metals: hexagonal close packed, body centered cubic, and face centered cubic in a form similar to that used to rationalize the structure of organic molecules and inorganic complexes. Pauling himself tried with limited success to address the origins of transition metal stability. These early investigators were handicapped, however, by incomplete knowledge regarding the structure of metallic charge density. Here we exploit modern approaches to charge analysis to first comprehensively describe transition metal charge density. Then, we use topological partitioning and quantum mechanically rigorous treatments of kinetic energy to account for the structure of the density as arising from the interactions between metallic tetrahedra. We argue that the crystallography of the early transition metals results from charge transfer from the so called “octahedral” to “tetrahedral holes” while the face centered cubic structure of the late transition metals is a consequence of antibonding interactions that increase octahedral hole kinetic energy.

This review covers some of the central relationships between artificial intelligence, psychology, and economics through the lens of information theory, specifically focusing on formal models of decision-theory. In doing so we look at a particular approach that each field has adopted and how information theory has informed the development of the ideas of each field. A key theme is expected utility theory, its connection to information theory, and the Bayesian approach to decision-making and forms of (bounded) rationality. What emerges from this review is a broadly unified formal perspective derived from three very different starting points that reflect the unique principles of each field. Each of the three approaches reviewed can, in principle at least, be implemented in a computational model in such a way that, with sufficient computational power, they could be compared with human abilities in complex tasks. However, a central critique that can be applied to all three approaches was first put forward by Savage in {\it The Foundations of Statistics} and recently brought to the fore by the economist Binmore: Bayesian approaches to decision-making work in what Savage called `small worlds' but cannot work in `large worlds'. This point, in various different guises, is central to some of the current debates about the power of artificial intelligence and its relationship to human-like learning and decision-making. Recent work on artificial intelligence has gone some way to bridging this gap but significant questions still need to be answered in all three fields in order to make progress on these problems.

Based on the Expected Utility Theory and Regret Theory, the Extended Regret Theory (ERT) is proposed in this paper to study the optimal pricing strategy of retailers in e-commerce environment. Taking the diversity of sales channels and the uncertainty of consumers in e-commerce environment into consideration, author of the paper designs an extended regret utility function which comprehensively considers both pessimistic and optimistic attitudes of decision makers in retailing industry to describe their regret-avoidance behavior. According to the sensitivity analysis, it is found that the optimal retail price decreases as the consumer price sensitivity coefficient increases, yet does not show variation with changes of the consumers pessimism degree. Moreover, the optimal retail price(s) obtained under EUT, ERT and combination of EUT and ERT represent the same.

The managers’ strategic behavior of commercial real estate in a competitive environment is discussed. The means of this research are methods of mathematical and experimental game theory. Illustrates an example of a decision-theoretic game problem with two players engaged in the management of competing shopping centers. The strategies of these players are determined by the costs of the development. Since the number of visitors is constantly and changing the quality of shopping centers, managers actually pull visitors from each other, the game-theoretical formulation of the problem of management of shopping centers corresponds to the zero-sum game. The model example shows that with the help of mathematical modeling it is possible to determine the theoretical expected behavior of agents. The model of the software module created specifically for experimental research is described. The experiments are designed to compare the theoretically predicted behavior with the real actions of people. The novelty is that at significant costs of the Manager for the development and promotion of shopping and entertainment centers, the strategies of managers are resistant to each other's actions, in contrast to changes in the external environment is shown.

The electronic structure and the participation of the simplest azomethine imine (AI) in [3+2] cycloaddition (32CA) reactions have been analysed within the Molecular Electron Density Theory (MEDT) using DFT calculations at the MPWB1K/6-311G(d) level. Electron localisation function (ELF) topological analysis reveals that AI has a pseudoradical structure, while the conceptual DFT reactivity indices characterise this TAC as a moderate electrophile and a good nucleophile. The non-polar 32CA reaction of AI with ethylene takes place through a one-step mechanism with low activation energy, 5.3 kcal/mol-1. A bonding evolution theory (BET) study indicates that this reaction takes place through a non-concerted [2n+2τ] mechanism in which the C–C bond formation is clearly anticipated prior to the C–N one. On the other hand, the polar 32CA reaction of AI with dicyanoethylene takes place through a two-stage one-step mechanism. Now, the more favourable regioisomeric transition state structure (TS) is located 8.5 kcal•mol⁻¹ below the reagents, in complete agreement with the high polar character of the TS. The current MEDT study makes it possible to extend Domingo’s classification of 32CA reactions to a new pra-type of reactivity.

The electron of spin −1/2 is a Dirac fermion of a complex four-component spinor field. Though it is effectively addressed by relativistic quantum field theory, an intuitive form of the fermion still remains lacking and it is often described by the so-called Dirac belt trick. In this novel undertaking, the fermion is examined within the boundary posed by a recently proposed MP model of a hydrogen atom into 4D space-time. Its physicality and transformation to Dirac fermion of four-component spinor is unveiled consistent with Dirac belt trick. The outcomes are compatible with Dirac field theory and other associated features like, SO(3) group to SU(2) transition, quantized Hamiltonian, non-relativistic wave function and Feynman diagrams. The model though speculative could become important towards defining the fundamental state of matter and its field theory subject to further investigations.

The theory of heavy ion double charge exchange (DCE) reactions proceeding by effective rank–2 isotensor interactions is presented. Virtual pion–nucleon charge exchange interactions are investigated as the source for induced isotensor interactions, giving rise to the Majorana DCE (MDCE) reaction mechanism. MDCE is of a generic character, proceeding through pairs of complementary (π±,π∓) reactions in the projectile and target nucleus. The dynamics of the elementary processes is discussed where the excitation of pion–nucleon resonances are of central importance. Investigations of initial and final state ion–ion interactions show that these effects are acting as vertex renormalizations. In closure approximation, well justified by the finite pion mass, the second order transition matrix elements reduce to pion potentials and effective two–body isotensor DCE interactions, giving rise also to two–body correlations in either of the participating nuclei. Connections to neutrinoless Majorana double beta decay (MDBD) are elucidated at various levels of dynamics, from the underlying fundamental electro–weak and QCD scales to the physical scales of nuclear MDBD and MDCE physics. It is pointed out that heavy ion MDCE reactions may also proceed by competing electro–weak charge exchange processes, leading to lepton MDCE by electrons, positrons, and neutrinos.

To meet the calls of the International Labor Organization and National Institutes of Occupational Safety and Health, this paper discusses how to build Occupational, Health, Safety (OSH), and Well-Being competence by expanding education to non-traditional undergraduate disciplines. The authors provide (1) theoretical background on why this would benefit society as a whole, (2) learning theory strategies for teaching OHS and Well-being outside of traditional majors, (3) case studies of how this can occur in undergraduate classes and (4) opportunities and challenges for the future.