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Graph neural network interatomic potentials (GNN-IPs) are gaining significant attention due to their capability of learning from large datasets. Specifically, universal interatomic potentials based on GNN, usually trained with crystalline geometries, often exhibit remarkable extrapolative behavior toward untrained domains, such as surfaces and amorphous configurations. However, the origin of this extrapolation capability is not well understood. This work provides a theoretical explanation of how GNN-IPs extrapolate to untrained geometries. First, we demonstrate that GNN-IPs can capture non-local electrostatic interactions through the message-passing algorithm, as evidenced by tests on toy models and density-functional theory data. We find that GNN-IP models, SevenNet and MACE, accurately predict electrostatic forces in untrained domains, indicating that they have learned the exact functional form of the Coulomb interaction. Based on these results, we suggest that the ability to learn non-local electrostatic interactions, coupled with the embedding nature of GNN-IPs, explains their extrapolation ability. We find that the universal GNN-IP, SevenNet-0, effectively infers non-local Coulomb interactions in untrained domains but fails to extrapolate the non-local forces arising from the kinetic term, which supports the suggested theory. Finally, we address the impact of hyperparameters on the extrapolation performance of universal potentials, such as SevenNet-0 and MACE-MP-0, and discuss the limitations of the extrapolation capabilities. [ABSTRACT FROM AUTHOR]

Despite a large amount of work being devoted to study the phase separation in solids, the underlying physical mechanism responsible for such diffusive first-order phase transitions remains difficult to model outside the spinodal regime, i.e., in the nucleation and growth regime. This work presents an alternative of the classical nucleation theory for modeling phase separation in this regime, even for systems far from the solubility limit, i.e., for high degree of meta-stability where the classical nucleation theory does not hold. This method then allows a direct comparison between simulations and experiments always performed in solids with a high degree of meta-stability. [ABSTRACT FROM AUTHOR]

Stimuli-responsive macromolecules display large conformational changes during their dynamics, sometimes switching between states. Such a multi-stability is useful for the development of soft functional materials. Here, we introduce a mean-field dynamical density functional theory for a model of responsive colloids to study the nonequilibrium dynamics of a colloidal dispersion in time-dependent external fields, with a focus on the coupling of translational and conformational dynamics during their relaxation. Specifically, we consider soft Gaussian particles with a bimodal size distribution between two confining walls with time-dependent (switching-on and off) external gravitational and osmotic fields. We find a rich relaxation behavior of the systems in excellent agreement with particle-based Brownian dynamics computer simulations. In particular, we find time-asymmetric relaxations of integrated observables (wall pressures, mean size, and liquid center-of-mass) for activation/deactivation of external potentials, respectively, which are tunable by the ratio of translational and conformational diffusion time scales. Our work thus paves the way for studying the nonequilibrium relaxation dynamics of complex soft matter with multiple degrees of freedom and hierarchical relaxations. [ABSTRACT FROM AUTHOR]

We establish a list of characterizations of bounded twin-width for hereditary classes of totally ordered graphs: as classes of at most exponential growth studied in enumerative combinatorics, as monadically NIP classes studied in model theory, as classes that do not transduce the class of all graphs studied in finite model theory, and as classes for which model checking first-order logic is fixed-parameter tractable studied in algorithmic graph theory. This has several consequences. First, it allows us to show that every hereditary class of ordered graphs either has at most exponential growth, or has at least factorial growth. This settles a question first asked by Balogh et al. [5] on the growth of hereditary classes of ordered graphs, generalizing the Stanley-Wilf conjecture/Marcus-Tardos theorem. Second, it gives a fixed-parameter approximation algorithm for twin-width on ordered graphs. Third, it yields a full classification of fixed-parameter tractable first-order model checking on hereditary classes of ordered binary structures. Fourth, it provides a model-theoretic characterization of classes with bounded twin-width. Finally, it settles the small conjecture [8] in the case of ordered graphs. [ABSTRACT FROM AUTHOR]

Traditional theories of the nuclear magnetic resonance (NMR) autocorrelation function for intra-molecular dipole pairs assume a single-exponential decay, yet the calculated autocorrelation of realistic systems displays a rich, multi-exponential behavior, resulting in anomalous NMR relaxation dispersion (i.e., frequency dependence). We develop an approach to model and interpret the multi-exponential intra-molecular autocorrelation using simple, physical models within a rigorous statistical mechanical development that encompasses both rotational diffusion and translational diffusion in the same framework. We recast the problem of evaluating the autocorrelation in terms of averaging over a diffusion propagator whose evolution is described by a Fokker–Planck equation. The time-independent part admits an eigenfunction expansion, allowing us to write the propagator as a sum over modes. Each mode has a spatial part that depends on the specified eigenfunction and a temporal part that depends on the corresponding eigenvalue (i.e., correlation time) with a simple, exponential decay. The spatial part is a probability distribution of the dipole pair, analogous to the stationary states of a quantum harmonic oscillator. Drawing inspiration from the idea of inherent structures in liquids, we interpret each of the spatial contributions as a specific molecular mode. These modes can be used to model and predict the NMR dipole–dipole relaxation dispersion of fluids by incorporating phenomena on the molecular level. We validate our statistical mechanical description of the distribution in molecular modes with molecular dynamics simulations interpreted without any relaxation models or adjustable parameters: the most important poles in the Padé–Laplace transform of the simulated autocorrelation agree with the eigenvalues predicted by the theory. [ABSTRACT FROM AUTHOR]

Mixing Gibbs energy and phase equilibria of aqueous solutions of polyglycine were studied theoretically by means of polymer reference interaction site model integral equation theory combined with the Gibbs–Duhem method. In addition to the ordinary liquid–liquid phase separation between dilute and concentrated solutions, the theoretical calculation predicted the coexistence of two coacervate phases, namely, the lower- and higher-density coacervates. The relative thermodynamic stabilities of these two phases change with the polymerization degree of polyglycine. The higher-density coacervate phase was rapidly stabilized by increasing the polymer length, and the lower-density phase became metastable at large polymers. The hydrogen bonds between the peptide chains were strengthened, and water was thermodynamically destabilized in the higher-density coacervate. A possible relation with the formation of amyloid fibril within a liquid droplet is also discussed. [ABSTRACT FROM AUTHOR]

Ferroelectric materials are widely used in actuators, exciters, and memory devices due to their excellent electromechanical properties. However, the instinctive brittleness of ferroelectric materials makes them easy to fracture under external load. Since giant strain gradient can be easily generated near the crack tip, the flexoelectric effect is indispensable in the research of fracture properties of ferroelectric materials. With the combination of time-dependent Ginzburg–Landau theory and phase-field model, the electromechanical behavior of PbTiO 3 in the vicinity of the crack tip is determined in this work. The simulation results demonstrate that the domain structure near the crack tip becomes asymmetric with the flexoelectric effect. The polarization switching-induced toughening, which is characterized by the J -integral, depends on the direction of the crack relative to the original polarization orientation. Furthermore, the longitude flexoelectric coefficient f 11 has more significant impact on the fracture toughness than that of the transverse flexoelectric coefficient f 12 and the shear flexoelectric coefficient f 44. The results of the present work suggest that the flexoelectric effect must be considered in the reliable design of ferroelectric devices. [ABSTRACT FROM AUTHOR]

We give a systematic study of the model theory of generic nilpotent groups and Lie algebras. We show that the Fraïssé limit of 2-nilpotent groups of exponent p studied by Baudisch is 2-dependent and NSOP 1. We prove that the class of c -nilpotent Lie algebras over an arbitrary field, in a language with predicates for a Lazard series, is closed under free amalgamation. We show that for 2 < c , the generic c -nilpotent Lie algebra over F p is strictly NSOP 4 and c -dependent. Via the Lazard correspondence, we obtain the same result for c -nilpotent groups of exponent p , for an odd prime p > c. [ABSTRACT FROM AUTHOR]

This paper provides a literature review of assessment of fit of item response theory models. Various types of fit procedures for item response theory models are reviewed, with a focus on their advantages and disadvantages. Real data examples are used to demonstrate some of the fit procedures. Recommendations are provided for researchers and practitioners who are interested in assessing the fit of item response theory models. [ABSTRACT FROM AUTHOR]

During the micro‐molding of polymer melts, ensuring the viscosity models' accuracy was essential. Existing models had neglected the temperature dependence of microscale factor, rendering them unsuitable for materials with varying temperature sensitivities. This research employed a twin‐bore capillary rheometer and dies of distinct characteristic dimensions as the experimental setup to investigate the viscosity variations across four materials exhibiting diverse temperature sensitivities. A modified MCA viscosity model was established by integrating a microscale factor that accounted for both dimension and temperature dependence into the macroscopic Carreau viscosity model. The traditional MCAc model, which ignored the microscale factor's temperature dependence, offered a comparative reference. These models were subsequently applied to evaluate the influence of coupling effects between viscosity and viscous dissipation on melt temperature, with results compared to experimental data. The results indicated that the MCA model's viscosity forecasts were in closer accord with experimental measurements, maintaining an accuracy within a 16% margin. The models' application to temperature calculations under varying inlet velocities and temperatures confirmed that the MCA model's predictions of the temperature increase along the flow direction were more congruent with experimental outcomes, underscoring the critical importance of incorporating both dimension and temperature dependence when establish microscale viscosity models. [ABSTRACT FROM AUTHOR]

Depending on the developments in technology and information, paper-pencil tests leave their place for computerized adaptive tests (CATs). CAT is widely used in the field of health, mainly in psychiatry. Many item response theory models have been proposed in the literature regarding the use of response time focusing on item difficulty and personal characteristics by ignoring the multidimensional interactions, therefore these results may cause bias in estimates of individual ability levels. The present simulation study was conducted to compare the performance of CAT applications of the effort-moderated item response theory (EM-IRT) model, which is based on response time, and the three-parameter logistic (3PL) model. While simulating CAT with the EM-IRT model and the 3PL model, the hybrid method was used for ability estimation and maximum Fisher information (MFI) was used for item selection. The CAT process proceeded until the standard error of the estimation was <0.3 and <0.5, or all items in the item bank were used. The number of individuals was specified as 1000, while the number of items was changed to 50, 100, and 250. All six scenarios were repeated 1000 times. With the increase in the number of items and the decrease in the standard error as a stopping criterion, consistent results were obtained with true ability levels in both methods. The CAT with the EM-IRT model estimated true ability level slightly lower than CAT with the 3PL model. The EM-IRT model enables measuring the response time that could yield additional data to the physician about the mental and cognitive condition of the patient. The CAT method can be a promising method of telemedicine in the era of the pandemic. [ABSTRACT FROM AUTHOR]

The present study demonstrated the potential applications of reliability models for crash analysis of a large highway network. Specifically, three major outcomes of reliability models were investigated: temporal distributions of crashes, reliability score, and expected number of crashes, using 20-year data (2001–2020) of crashes recorded on the Saskatchewan highway network. A series of reliability models were developed for crashes by crash severity, vehicle involvement, and highway type. First, the temporal distributions of crashes on each segment were fit to a statistical distribution. Second, the reliability scores were used to rank the high crash risk segments. Third, the mean expected crash frequency was used to develop network-wide safety performance functions for total and fatal crashes in urban and rural highway segments using Poisson–Tweedie (PTw) regression models. The developed PTw models showed that the presence of trucks in the traffic composition has a significant effect on crash frequency, especially for urban highway segments. [ABSTRACT FROM AUTHOR]

Comprehensibility (readability) is understood as the ease with which a certain reader can conduct the processes needed to comprehend a certain text in a certain situation. Comprehensibility is a special form of fluency and has been shown to have a considerable influence on comprehension. Based on fluency theory and the four-phase model of interest development, hypotheses are derived regarding the positive influence of comprehensibility on comprehension, interestingness, and interest. A study with N = 302 university students and 15 texts showed substantial effects of comprehensibility on all dependent variables, regardless of which of three instruments was used to assess comprehensibility: one of two comprehensibility questionnaires or the LIX readability formula. The results highlight the importance of fluency for the design of learning materials. [ABSTRACT FROM AUTHOR]

This paper revisits and extends the adjoint theory for glacial isostatic adjustment (GIA) of Crawford et al. (2018). Rotational feedbacks are now incorporated, and the application of the second-order adjoint method is described for the first time. The first-order adjoint method provides an efficient means for computing sensitivity kernels for a chosen objective functional, while the second-order adjoint method provides second-derivative information in the form of Hessian kernels. These latter kernels are required by efficient Newton-type optimization schemes and within methods for quantifying uncertainty for non-linear inverse problems. Most importantly, the entire theory has been reformulated so as to simplify its implementation by others within the GIA community. In particular, the rate-formulation for the GIA forward problem introduced by Crawford et al. (2018) has been replaced with the conventional equations for modelling GIA in laterally heterogeneous earth models. The implementation of the first- and second-order adjoint problems should be relatively easy within both existing and new GIA codes, with only the inclusions of more general force terms being required. [ABSTRACT FROM AUTHOR]

Considering the rapid liquid transport characteristics of bionic dragonfly wings, an experimental investigation into the stability and drag reduction properties of an air film on various textured surfaces is being conducted. The study examines the impact of different wetting gradient textures on the stability and drag reduction properties of air film. Experimental results demonstrate an enhanced fluid transport efficiency, resulting in a maximum drag reduction of 9.1%, attributed to the size effect of the multi‐scale structure of bionic dragonfly wings. Surfaces featuring wetting gradients exhibit increased stability of the air film within the texture and the ability to trap air bubbles. Based on a near‐wall flow two‐phase flow theory model, the simulation considers the morphological changes of the air film at structured interfaces and their influence on near‐wall flow characteristics. The results indicate that the drag reduction effect arise from the slippage effect between the internal vortex in the air film inside the texture and the flow field near the wall surface. The synergistic effect of near‐wall flow fields among multiple texture layers is evident. This interplay across different regions contributes to the sustained drag reduction within the near wall area. [ABSTRACT FROM AUTHOR]

Purpose: This study explores the phenomenon of company-specific plant role models. Following the establishment of distinct lead factories, recent studies imply that multinational companies are now using more detailed plant roles to manage manufacturing networks. While multiple plant role typologies can be found in literature, this is, to our knowledge, the first article to systematically analyze the content of such company-specific plant roles. Design/methodology/approach: We rely on a multiple-case study design of 29 plant role models primarily belonging to multinational companies headquartered in German-speaking countries. Coding is performed to analyze the models for similarities and differences. Findings: The content of company-specific plant role models seems highly dependent on a company's context; hence, there is no one best way to build them. Companies appear to be pursuing different priorities with the application of plant roles, for example, the reorganization of manufacturing networks, the systematic allocation of products or the definition of decision-making autonomy. Compared to the primarily two-dimensional models from theory, companies rely on more dimensions to make their plant roles practical. Similar to models from literature, competence bandwidth, inter-plant knowledge/information flow and location advantage are the most relevant dimensions to differentiate plants from a headquarters' perspective. Practical implications: Plant role models are a powerful management tool that enables delayering the complexity and allows for proactive management of manufacturing networks. Managers fit the content of their plant role models to their company-specific context and the intended application for manufacturing networks. Managers aiming to build company-specific plant roles can use the conceptual framework based on the empirical findings as a benchmark. Originality/value: This study complements prior research on plant roles by acknowledging that companies might develop their own version of plant role models rather than copying the ones from the literature. By doing so, we explore how plant roles look like in a real-world setting. [ABSTRACT FROM AUTHOR]

Piezoelectric bimorph cantilevered beams are frequently employed in energy harvesting applications. The use of macro-fiber composites, which combine piezoelectric fibers with rectangular cross-sections and interdigitated electrodes, has significantly enhanced their performance by enabling operation in the 33-mode of piezoelectricity, thereby increasing conversion efficiency. In this article, the Timoshenko beam theory is applied to overcome the limitations of the Euler-Bernoulli theory in modeling transverse vibrations of harvesters with low slenderness ratios (length to thickness ratios). The mixture rule formulation is applied to determine the equivalent properties of the macro-fiber composite (MFC) structure. The electromechanical properties of a representative volume element (RVE) bounded by two successive interdigitated electrodes are coupled to the overall electro-elastic dynamic model of the structure using the Timoshenko theory. Frequency response functions for the power and tip vibration displacement of the MFC bimorph beam are determined from the model. Experimental data from the literature are used to validate the improved results predicted by the model developed in this article. A comparative analysis between the electromechanical responses predicted using a model based on Timoshenko and a model based on Euler-Bernoulli theory is conducted showing agreement, for harvesters with large slenderness ratios and discrepancies of up to 30% for low slenderness ratios. It has also been shown that the model based on Euler-Bernoulli theory overestimates both the mechanical and the electrical responses for low slenderness ratios as the shear and rotary inertia effects are not negligible in this case. [ABSTRACT FROM AUTHOR]

This paper aims to explore the evolution of the universe in the background of Palatini f(R) gravity. Considering Amendola Gannouji Polarski Tsujikawa (AGPT) f(R) gravity model, we perform a dynamical system analysis within the FLRW universe in order to analyze the impacts of this gravity model on large‐scale structure and dynamics of universe. With the aid of fixed points and eigenvalues, stability properties are analyzed to study long term behavior of universe. For analyzing the feasibility of different phases of universe, the equation of state parameter ωeff was utilized. We found that for the f(R) model under consideration, the results correspond to both of the early as well as the late time epochs for the said f(R) model. [ABSTRACT FROM AUTHOR]

People routinely use facial expressions to communicate successfully and to regulate other’s behaviour, yet modelling the form and meaning of these facial behaviours has proven surprisingly complex. One reason for this difficulty may lie in an over-reliance on the assumptions inherent in existing theories of facial expression – specifically that (1) there is a putative set of facial expressions that signal an internal state of emotion, (2) patterns of facial movement have been empirically linked to the prototypical emotions in this set, and (3) static, non-social, posed images from convenience samples are adequate to validate the first two assumptions. These assumptions have guided the creation of datasets, which are then used to train unrepresentative computational models of facial expression. In this article, we discuss existing theories of facial expression and review how they have shaped current facial expression recognition tools. We then discuss the resources that are available to help researchers build a more ecologically valid model of facial expressions. [ABSTRACT FROM AUTHOR]

ABSTRACT Decentralized periodic event‐triggered control (DPETC) is a method that allows sensors to be placed flexibly while cutting down on their workload and the amount of data they send in a feedback loop, which makes it a good fit for wireless network control systems. In this article, we investigate the control issues of nonlinear switched systems whose switches are determined by the system input and consider their stability by designing a DPETC scheme. Additionally, we model and control a water distribution system with looped pipe network using a switched model and the proposed theory. In this DPETC, at each periodic sampling time, the local event‐triggered mechanism determines events by assessing whether the local sampling error meets the predefined triggering condition. If so, the collected sampling data will be transmitted to a central controller. This controller processes the data to compute the control input, with those nodes without events using the previous updated sampling data. Based on the derived control input, the controller then switches to the appropriate mode following the system's switches. The feasibility of the proposed method is demonstrated through three examples, including a smart water distribution system with looped pipeline. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a new system of equations describing a nonlocal model of viscoelasticity theory. In order to obtain the model we used a new approach to the constitutive relations for the internal energy and stress tensor. Using the modified Cagniard‐de Hoop method we constructed the fundamental solution to this system of equations in the three‐dimensional space. Basing on the derived fundamental solutions, explicit formulae for the solution to the Cauchy problem for this system of equations were presented. For the obtained solution, its mechanical and mathematical aspects and properties have been analyzed for the considered viscoelastic medium. [ABSTRACT FROM AUTHOR]

We are very excited by the recent work of Soto and colleagues (2021; 2022; 2023) integrating the Big 5 model with the growing literature on the determinants of success. We agree that their proposed taxonomy of skills is a good starting point, especially given that it complements the substantive research literature supporting the Big 5. However, we argue that the decision to sharply separate traits from skills does not do justice to the full implications of their model, and that pulling back on the integration between traits and skills obscures the dynamic processes underlying the Big 5. Existing dynamic accounts of personality such as Whole Trait Theory provide a model for understanding both how these skills are included as part of traits and their development as well as a framework for interventions focused on skill development. We hope that discovering the link between skills and traits will warm researchers up to dynamic accounts of the Big 5. [ABSTRACT FROM AUTHOR]

Despite the well-established significance of Black racial identity development in the psychological functioning of African Americans, there is little support within the literature to guide counselors in qualitative assessment of this construct during therapy. This article explores the use of Socratic questioning during counseling as a tool to clarify the essence of what African American clients believe about themselves as racial beings. Integrating nigrescence theory with a four-step model of Socratic questioning, the author describes how Socratic questioning may be used to encourage articulation of the client’s lived experience as a racial being, including discovery of the client’s race-related core and intermediate beliefs and their personal meanings. The article concludes with a discussion of potential barriers to implementation of the approach, as well as implications for future clinical practice. [ABSTRACT FROM AUTHOR]

Collapse risk assessment is an important basis for the prevention and control of geological disasters in mountainous areas. The existing research on collapse hazard is less, and there is still no further advancement in the evaluation of collapse hazard for the traditional indicator assignment method for the diversification of the assignment results of the indicators and the comprehensive evaluation method that cannot consider the ambiguity and randomness of the indicator data at the same time. In this paper, we utilize the respective advantages of the linear programming theory and the cloud model from the prevention and control point of view, and evaluate the collapse samples. Firstly, the weight interval of evaluation index is determined by improved analytic hierarchy process, entropy weight method and coefficient of variation method. Secondly, the linear programming algorithm is used to select the specific weight of each collapse sample when the risk is the largest in the interval. Finally, a comprehensive evaluation model of cloud model is constructed to determine the risk level of collapse. In this paper, 20 collapse samples counted by predecessors in G4217 Wenchuan-Lixian section are taken as research cases. The evaluation results of 20 collapse samples are compared with other evaluation methods and field survey conditions to prove the reliability and rationality of the method. The evaluation results show that 13 of the 20 collapse samples are extremely dangerous, 2 are highly dangerous, 4 are moderately dangerous, and 1 is lowly dangerous. Among them, the extremely dangerous collapse samples account for 65% of the total number of collapses. Compared with other methods, this method is more in line with the actual situation. [ABSTRACT FROM AUTHOR]

This study aims to develop a novel computational model to accurately quantify the interfacial interactions between matrix resin and fillers in polymer-based composites, thereby overcoming the limitations of existing theories and computational models in assessing interfacial interactions, such as limited application scope and unclear boundary conditions. By exploring the dynamic behavior of matrix resin molecular chains, a theoretical model for interfacial interactions was constructed based on molecular chain dynamics theory, and corresponding computational formulas were derived. To validate the model, bisphenol A epoxy resin and hollow glass microspheres were selected as experimental materials, and experimental studies were conducted using dynamic thermomechanical analysis and other methods. The results demonstrate that the proposed molecular chain dynamics model can accurately quantify the interfacial interactions in polymer-based composites, successfully determining the interfacial interaction parameter A value of 0.42 between bisphenol A epoxy resin and hollow glass microspheres, which falls into the category of "ordinary interfacial interaction." This study not only provides a solid theoretical foundation for the optimization design and performance enhancement of composites but also holds broad application prospects in fields such as military aviation, aerospace, naval equipment, and high-end terrestrial equipment, potentially driving advancements in composite material design technology. [ABSTRACT FROM AUTHOR]

AbstractSubsea tunnels are different from mountain tunnels in many aspects. During the construction process using drilling and blasting methods, there are complex environments such as unlimited seawater replenishment and complex geological structures that pose serious challenges to construction safety. In order to more accurately assess the safety of subsea tunnels so as to reduce the probability of disasters, this article proposes the characteristic indicators of “overburden thickness/depth of overlying seawater” (RSR) for subsea tunnels, and combines cloud model theory with Bayesian networks to establish a risk assessment method for subsea tunnel collapse. Taking the Jiaozhou Bay Second subsea tunnel as an example, prior risk reasoning and ex-post risk diagnosis are carried out. The maximum disaster risk section of the tunnel has been determined, and the key influencing factors of the collapse risk of the subsea tunnel have been identified, providing assurance for construction safety. The main contributions of the research results are as follows: (a) analyzed the factors affecting the risk of subsea tunnel; (b) the characteristic indicator for subsea tunnel collapse risk assessment was proposed; and (c) combined the Bayesian network and cloud model, and established the risk assessment method of subsea tunnel by drilling and blasting method. [ABSTRACT FROM AUTHOR]

The Markov chain is a stochastic process in which the future value of a variable is conditionally independent of the past, given its present value. Data with Markovian features are characterized by: frequent observations relative to the expected changes in values, many consecutive same‐category or similar‐value observations at the individual level, and a positive correlation observed between the current and previous values for that variable. In drug development and clinical settings, the data available commonly present Markovian features and are increasingly often modeled using Markov elements or dedicated Markov models. This tutorial presents the main characteristics, evaluations, and applications of various Markov modeling approaches including the discrete‐time Markov models (DTMM), continuous‐time Markov models (CTMM), hidden Markov models, and item‐response theory model with Markov sub‐models. The tutorial has a specific emphasis on the use of DTMM and CTMM for modeling ordered‐categorical data with Markovian features. Although the main body of this tutorial is written in a software‐neutral manner, annotated NONMEM code for all key Markov models is included in the Supplementary Information. [ABSTRACT FROM AUTHOR]

AbstractThe nature of consciousness remains unclear, and academic discussions usually ignore the scientific evidence about anomalous and spiritual experiences suggestive of the mind beyond the brain, mainly because of the lack of a scientific framework that makes sense of these experiences. This manuscript proposes the ‘Pragmatic interactionist’ scientific framework for the mind–brain relationship based on the evidence from scientific studies of spiritual or anomalous experiences, especially near-death, end-of-life, out-of-body, and mediumistic experiences and alleged memories of previous lives. Based on the epistemic principles of an enlarged empirical base and expanded naturalism, the framework’s main components are: interactionist mind–body relationship; the mind exists and functions beyond the brain and survives bodily death; and the brain is a tool and a filter for the mind manifestation. Research proposals to advance and test the framework are: in-depth ‘360 degrees’ studies of the ‘good specimen of the class’, studies on mind-over-brain phenomena, free-will beyond extreme social and biological factors, enhanced mentation with a dysfunctional brain, reports of veridical hallucination, extracerebral memory, and early sharp personality differences between monozygotic twins. The proposed framework is a working hypothesis to enlarge our observational and analytical capacities to foster theories to better understand the human mind. [ABSTRACT FROM AUTHOR]

ABSTRACT The behavior of soft soils distributed in coastal areas usually exhibits obvious time‐dependent behavior after loading. To reasonably describe the stress‐strain relationship of soft soils, this paper establishes a viscoelastic‐viscoplastic small‐strain constitutive model based on the component model and the hardening soil model with small‐strain stiffness (HSS model). First, the Perzyna's viscoplastic flow rule and the modified Hardin–Drnevich model are introduced to derive a one‐dimensional incremental Nishihara constitutive equation. Next, the flexibility coefficient matrix is utilized to extend the one‐dimensional model to three‐dimensional conditions. Then, by combining the HSS elastoplastic theory with the component model, the viscoelastic‐viscoplastic small‐strain constitutive model is subsequently established. To implement the proposed model for numerical analysis, the corresponding UMAT subroutine is developed using Fortran. After comparing the results of numerical simulations with those of existing literature, the reliability of the constitutive model and the program written in this paper is verified. Finally, numerical examples are designed to further analyze the effects of small‐strain parameters and viscoelastic‐viscoplastic parameters on the time‐dependent behavior of soft soils. [ABSTRACT FROM AUTHOR]

Educational tests often have a cluster of items linked by a common stimulus (testlet). In such a design, the dependencies caused between items are called testlet effects. In particular, the directional testlet effect (DTE) refers to a recursive influence whereby responses to earlier items can positively or negatively affect the scores on later items. This study aims to introduce an innovative measurement model to describe DTEs among multiple polytomouslyscored open‐ended items. Through simulations, we found that (1) item and DTE parameters can be accurately recovered in Latent GOLD®, (2) ignoring positive (or negative) DTEs by fitting a standard item response theory model can result in the overestimation (or underestimation) of test reliability, (3) collapsing multiple items of a testlet into a super item is still effective in eliminating DTEs, (4) the popular multidimensional strategy of adding nuisance factors to describe item dependencies fails to account for DTE adequately, and (5) fitting the proposed model for DTE to testlet data involving nuisance factors will observe positive DTEs but will not have a better fit. Moreover, using the proposed model, we demonstrated the coexistence of positive and negative DTEs in a real history exam. [ABSTRACT FROM AUTHOR]

Background: As a major public health problem, cyberbullying has been received widespread attention in recent years. However, most researches on cyberbullying are mainly focused on adolescents and college students, the underlying mechanisms of cyberbullying among graduate students have been relatively less investigated. From the perspectives of the general aggression model and attachment theory, this study aims to explore the relationship between childhood psychological abuse and cyberbullying behavior among graduate students, as well as the mediating roles of negative coping style and trait anxiety. Materials and methods: A total of 482 graduate students were surveyed using measures including the Childhood Psychological Abuse Scale, Simplified Coping Style Questionnaire, Self-Rating Anxiety Scale, and Cyberbullying Behavior Scale. Results: (1) There were significant positive correlations between childhood psychological abuse, negative coping style, trait anxiety, and graduate students' cyberbullying behavior; (2) Childhood psychological abuse could forecast graduate students' cyberbullying behavior through the mediating effects of negative coping style and trait anxiety. This mediation process includes two pathways: the independent mediating effect of negative coping style and the chained mediating effect of negative coping style and trait anxiety. Conclusion: Negative coping style and trait anxiety play mediating roles in the relationship between childhood psychological abuse and cyberbullying behavior among graduate students. [ABSTRACT FROM AUTHOR]

Background: In healthcare research and practice, intervention and implementation fidelity represent the steadfast adherence to core components of research-supported interventions and the strategies employed for their implementation. Evaluating fidelity involves determining whether these core components were delivered as intended. Without fidelity data, the results of complex interventions cannot be meaningfully interpreted. Increasingly, the necessity for firmness and strict adherence by implementers and their organizations has been questioned, with calls for flexibility to accommodate contextual conditions. This shift makes contemporary fidelity a balancing act, requiring researchers to navigate various tensions. This debate paper explores these tensions, drawing on experiences from developing fidelity assessments in two ongoing effectiveness-implementation hybrid trials. Main body: First, given often scarce knowledge about the core components of complex interventions and implementation strategies, decisions about fidelity requirements involve a degree of subjective reasoning. Researchers should make these decisions transparent using theory or logic models. Second, because fidelity is context-dependent and applies to both interventions and implementation strategies, researchers must rethink fidelity concepts with every study while balancing firmness and flexibility. This is particularly crucial for hybrid studies, with their differing emphasis on intervention and implementation fidelity. Third, fidelity concepts typically focus on individual behaviors. However, since organizational and system factors also influence fidelity, there is a growing need to define fidelity criteria at these levels. Finally, as contemporary fidelity concepts prioritize flexible over firm adherence, building, evaluating, and maintaining fidelity in healthcare research has become more complex. This complexity calls for intensified efforts to expand the knowledge base for pragmatic and adaptive fidelity measurement in trial and routine healthcare settings. Conclusion: Contemporary conceptualizations of fidelity place greater demands on how fidelity is examined, necessitating the expansion of fidelity frameworks to include organizational and system levels, the service- and study-specific conceptualizations of intervention and implementation fidelity, and the development of pragmatic approaches for assessing fidelity in research and practice. Continuing to build knowledge on how to balance requirements for firmness and flexibility remains a crucial task within the field of implementation science. [ABSTRACT FROM AUTHOR]

Understanding the mechanism underlying thermostabilization in naturally stable enzymes and enhancing the thermostability of unstable enzymes are crucial aspects in enzyme engineering. Despite the development of various engineering methods, there remains substantial scope for improvement. In this study, a novel concept termed as the "short board" theory is proposed, which conceptualizes proteins as barrels with each component representing a jagged board. Notably, optimizing modifications to the shortest board yields optimal enhancements in terms of thermostability performance. To validate this theory, α‐amylase, an industrial bulk enzyme with multiple domains, is employed as a model enzyme. The existence of "short boards" and their impact on thermostability modification are demonstrated at the domain, residue, and atomic levels through experimental confirmation using domain substitution. Furthermore, a novel thermostable design and prediction model called Zero‐Shot Hamiltonian (ZSH) is established and evaluated on α‐amylase. This coevolutionary approach based on thermostability and deep learning exhibits remarkable success exclusively when applied to enzymes with fixed short boards. The integration of the "short board" theory with the ZSH model presents an innovative tool for enhancing enzymatic thermostability. [ABSTRACT FROM AUTHOR]

Purpose: The effects of glue layers are regarded as the stiffness and damping of laminated circular plates. An energy harvester consisting of a concentrated mass and a piezoelectric laminated circular plate is investigated with the account for the glue layers. Methods: The resonant amplitudes and frequencies are determined via the frequency sweep experiments. To account the adhesive effects, the force surface method is employed to identify the restoring and damping force of the glued laminated plate in a simplified one and half degree-of-freedom system, and the resulting force is fitted by a combination of hyperbolic tangent and trigonometric functions. The model with the nonlinear restoring and damping force is analyzed via the harmonic balance method. The outcomes of the voltage-frequency response curves are supported by the experiment results. Results: The results show that only under small excitation the frequencies can be well predicted by the plate theory model without the glue layers and the differences increase with the excitation. The investigation reveals that the glue layers change mainly the stiffness rather than the damping. Conclusions: The model with the nonlinear restoring and damping force can predict the fundamental resonant amplitudes and frequencies measured by experiments well. [ABSTRACT FROM AUTHOR]

Multidimensional forced‐choice (MFC) items have been found to be useful to reduce response biases in personality assessments. However, conventional scoring methods for the MFC items result in ipsative data, hindering the wider applications of the MFC format. In the last decade, a number of item response theory (IRT) models have been developed, majority of which are for MFC items with binary responses. However, MFC items with polytomous responses are more informative and have many applications. This paper develops a polytomous Rasch ipsative model (pRIM) that can deal with ipsative data and yield estimates that measure construct differentiation—a latent trait that describes the degree to which the personality constructs (e.g., interests) distinguish between each other. The pRIM and its simpler form are applied to a career interests assessment containing four‐category MFC items and the measures of interests differentiation are used for both intra‐ and interpersonal comparisons. Simulations are conducted to examine the recovery of the parameters under various conditions. The results show that the parameters of the pRIM can be well recovered, particularly when a complete linking design and a large sample are used. The implications and application of the pRIM in the personality assessment using MFC items are discussed. [ABSTRACT FROM AUTHOR]

Two first-order logic theories are definitionally equivalent if and only if there is a bijection between their model classes that preserves isomorphisms and ultraproducts (Theorem 2). This is a variant of a prior theorem of van Benthem and Pearce. In Example 2, uncountably many pairs of definitionally inequivalent theories are given such that their model categories are concretely isomorphic via bijections that preserve ultraproducts in the model categories up to isomorphism. Based on these results, we settle several conjectures of Barrett, Glymour and Halvorson. [ABSTRACT FROM AUTHOR]

The supersonic combustor is a critical component of a scramjet, and it is essential to monitor the combustion states within the combustor to ensure the safe and stable operation of the scramjet. Hence, we propose an intelligent combustion state recognition model called the parallel Kolmogorov–Arnold transformer (PKAT). In this model, we construct a Kolmogorov–Arnold linear layer based on Kolmogorov–Arnold theory to enhance the model's ability to approximate flame-stable combustion features. To enable different levels of feature recognition through various backbone networks, we build a parallel structure. The PKAT model performs multi-level and comprehensive recognition of flame combustion features, considering both global and local perspectives. To validate the robustness and generalization capability of the PKAT, we collect data on the stable combustion process of a hydrogen-fueled scramjet engine in a direct-connect supersonic pulse combustion wind tunnel. Experimental results show that the proposed model accurately identifies stable combustion states under different operating conditions, achieving precision, recall, and accuracy rates of 98.31%, 98.36%, and 98.76%, respectively. Furthermore, the PKAT model demonstrates a certain level of generalization capability. When compared to traditional convolutional neural network-based and transformer-based models, the PKAT model exhibits higher recognition performance and robustness in accurately identifying combustion characteristics. [ABSTRACT FROM AUTHOR]

The Hamiltonian cycle and path problems are fundamental in graph theory and useful in modelling real-life problems. Research in this area is directed toward designing better and better algorithms for general problems, but also toward defining new special cases for which exact polynomial-time algorithms exist. In the paper, such new classes of digraphs are proposed. The classes include, among others, quasi-adjoint graphs, which are a superclass of adjoints, directed line graphs, and graphs modelling a DNA sequencing problem. [ABSTRACT FROM AUTHOR]

Team perspective taking is a process of team member empathy, motivation for other people's ideas and feelings, and the ability to understand objectively. It can have positive impacts on teams, but the question of whether team perspective taking positively affects the sense of collective thriving exhibited by the team has not been answered, and the intrinsic mechanism underlying this influence has not been revealed. To explore the impact of team perspective taking on the collective thriving of college student innovation teams, this study constructs a chain mediation model based on theories such as the socially embedded model of thriving. A questionnaire survey was conducted to investigate 225 college student innovation teams. The results show that (1) team perspective taking, team trust, and team reflexivity are positively correlated with collective thriving. (2) Team trust and team reflexivity play separate mediating roles in the influence of team perspective taking on collective thriving. Team trust also plays a chain mediating role, and its mediating path is team perspective taking → team trust → team reflexivity → collective thriving. Team perspective taking not only has a direct effect on the collective thriving of college students' innovation teams but also has an indirect effect through the chain mediating path of team trust and team reflexivity. This study not only further enriches the antecedent literature on collective thriving but also verifies the promoting effect of various resource factors on collective thriving at the team level and provides a theoretical reference for the activation of collective thriving. [ABSTRACT FROM AUTHOR]

This paper is inspired by cutting-edge advancements in chaos theory, fractional calculus, and fixed point theory, which together provide a powerful framework for examining the dynamics of complex systems. At the heart of our research is the fractional-order Dadras–Momeni chaotic system, a pivotal model in chaos theory celebrated for its intricate, multi-scroll dynamics. Leveraging the Atangana–Baleanu fractional derivative, we extend fractional computation to chaotic systems, offering deeper insights into their behavior. To fortify the mathematical foundation of our analysis, we employ the relaxed θ rational contractions in the realm of metric spaces, enabling a more precise exploration of the system's dynamics. A key goal of this work is to simplify the definition of the function class Θ while maintaining the existence and uniqueness of fixed points under θ -relaxed contractions, integrating this framework with the established literature on complete metric spaces. We explore the system's behavior across six distinct cases by varying δ with a fixed fractional order of ℏ = 0.98 . In the first case, a single scroll forms, while successive cases lead to increased scrolls—reaching up to four by the sixth case. Phase portraits and time series analyses reveal a progression in complexity and chaos, with denser, intertwined scrolls as δ increases. This behavior highlights the system's heightened sensitivity to parameter variations, demonstrating how fractional parameters influence the chaotic dynamics. Our results offer meaningful contributions to both the theoretical foundations and practical applications of chaos theory and fractional calculus, advancing the understanding of chaotic systems in new and impacted ways. [ABSTRACT FROM AUTHOR]

According to the infrared patch image (IPI) model theory, the infrared image background has a low rank and the target is sparse. The low-rank model can be used to separate the background and identify the target. However, in a noisy environment, the recognition effect will be affected. The higher the noise, the harder it would be to detect a small target. The residual strong fault and background edges could reduce the detection rate and increase false alarms. The traditional IPI model is adaptable to the background with the lower noise. This paper combines weighted nuclear norm minimization (WNNM) optimization with sparse representation based on the local IPI model. The background details are described more prominently by improving the nuclear norm weighting factor. The target is much easier to detect under the specific bright clouds and ground buildings background with high noise. At the same time, post-processing with image local contrast analysis is performed to compare traditional spatial filtering and local infrared patch image model algorithms. Our method has a good suppression effect on complex noise backgrounds and achieves a higher signal to clutter ratio gain (SCRG). It could also improve the target detection rate and reduce false alarms. [ABSTRACT FROM AUTHOR]

Item response theory models allow estimation of participant and group-mean trait scores from responses to a set of items, but estimates can be biased when participants vary in their response style. We illustrate models fit in gsem that can account for such response style differences by comparing self-report with their ratings of anchoring vignettes—descriptions of other individuals displaying different levels of the trait. Simulation results from standard item response theory, mean bias, random bias, and free-threshold models are illustrated. We show that unbiased estimates can be recovered when the vignettes rated depend on the participants' own self-rating or are even rated by a different sample, substantially broadening their scope of application. [ABSTRACT FROM AUTHOR]

The use of fictional models is extensive and rewarding in modern science. This fact captured the attention of philosophers of science, who are focusing on questions such as the following: is it possible for a fictional model to be explanatory? And, if so, in virtue of what is such a fictional model explanatory? In this paper, I discuss these questions in relation to the realism vs. anti-realism debate in philosophy of science. I focus on work developed by Alisa Bokulich who has argued for the explanatory role played by fictional models, claiming that it can be accommodated by realism in 'a broad sense'. To this end, Bokulich introduced what she called 'an eikonic conception' of explanation, as opposed to the so-called 'ontic' conception. This move, Bokulich claims, allows non-causal explanations to be acceptable to a modified version, as opposed to a 'naïve' brand of realism. Roughly, a fictional model can capture aspects of reality if it manages to act as a proxy for a theory targeting a physical system. As Bokulich explains with the example of James Clerk Maxwell's use of mechanical models, this is due to structural correspondences between a model and a theory at a certain level of abstraction. However, Bokulich does not explain how the model grasps reality. In this paper, I fill this missing piece of the puzzle. While I agree with Bokulich on the explanatory function of fictional models, I shall invoke her reading of Maxwell's work to draw a different conclusion. Specifically, I argue that structural correspondences at various levels form what I call 'a ladder of abstractions' which connects aspects of a target system to the corresponding depths of descriptions. Modifying in these terms the scope of 'representing a system', I suggest that Bokulich's proposed modification of realism is obviated. [ABSTRACT FROM AUTHOR]

Accurate prediction of citywide crowd activity levels (CALs), i.e., the numbers of participants of citywide crowd activities under different venue categories at certain time and locations, is essential for the city management, the personal service applications, and the entrepreneurs in commercial strategic planning. Existing studies have not thoroughly taken into account the complex spatial and temporal interactions among different categories of CALs and their extreme occurrences, leading to lowered adaptivity and accuracy of their models. To address above concerns, we have proposed IE-CALP, a novel spatio-temporal Interactive attention-based and Extreme-aware model for Crowd Activity Level Prediction. The tasks of IE-CALP consist of (a) forecasting the spatial distributions of various CALs at different city regions (spatial CALs), and (b) predicting the number of participants per category of the CALs (categorical CALs). To realize above, we have designed a novel spatial CAL-POI interaction-attentive learning component in IE-CALP to model the spatial interactions across different CAL categories, as well as those among the spatial urban regions and CALs. In addition, IE-CALP incorporate the multi-level trends (e.g., daily and weekly levels of temporal granularity) of CALs through a multi-level temporal feature learning component. Furthermore, to enhance the model adaptivity to extreme CALs (e.g., during extreme urban events or weather conditions), we further take into account the extreme value theory and model the impacts of historical CALs upon the occurrences of extreme CALs. Extensive experiments upon a total of 738,715 CAL records and 246,660 POIs in New York City (NYC), Los Angeles (LA), and Tokyo have further validated the accuracy, adaptivity, and effectiveness of IE-CALP's interaction-attentive and extreme-aware CAL predictions. [ABSTRACT FROM AUTHOR]

This study introduces a holistic analysis framework designed to evaluate and predict the investment risks associated with foreign renewable energy initiatives. This framework aims to reduce the uncertainties inherent in renewable energy projects. To achieve this, we utilize the variable weight matter-element extension model to establish the project's fundamental reliability function. We then refine this model by incorporating evidence theory to assess the project's risk level and derive precise risk index measurements. We utilize the GM model to forecast potential future risks associated with the project. In addition, a case study is presented on the risk assessment and prediction for the Maynak Hydropower Station. Our findings reveals that the project encountered significant investment risks in 2008, 2014, 2020, and 2022. Key risk indicators include political turmoil，policy change，imperfect legislation，cultural risk，exchange rate changes，technical risks and management risks. Furthermore, the investment risk level declined from 2023 to 2027, with our risk measurement outcomes closely aligning with actual conditions, thereby validating the effectiveness and applicability of our model. [ABSTRACT FROM AUTHOR]

David Fabricius is recognized in the history of astronomy for his role in the discoveries of sunspots and the first variable star. As the around 50 letters between them show, he also played a significant role as Kepler's interlocutor when the latter was writing Astronomia Nova. One year before the publication of Astronomia Nova , Fabricius shared with Kepler a new model for Mars that he had developed. The model shocked Kepler because, using the traditional tools of circles and uniform motion, Fabricius had been able to find a model as accurate as Kepler's model involving his first two laws. The official story, based on the reconstruction of Fabricius's model that Apelt made in 1852, asserts that Kepler need not worry because, in fact, he misinterpreted the model. The true model that Fabricius proposed was not predictively accurate. In this paper I offer a new interpretation of Fabricius's model that shows that Kepler did indeed have reason to worry since Fabricius's model was extraordinarily accurate. [ABSTRACT FROM AUTHOR]

In order to solve the problem of difficult simulation of the bolted joint structure of rotors, this study proposes an improved sub-regional thin-layer element method (ISRTL) and applies it to the equivalent simulation of the joint interface in the presence of bolt deviations. The theory introduces the fractal theory and Hertz contact theory to calculate the thin-layer parameter for the region with weak influence of bolt preload. The trend of dynamic response under different loosening deviation conditions is investigated. The experimental study of bolt deviation under axial tension and transverse vibration was carried out using a drum-disk rotor. The frequency and stiffness with bolt loosening position conform to M-type trend. The error of the eigenfrequencies calculated by the proposed method is within 3 % from the experimental results. The results demonstrate that ISRTL method has high accuracy and efficiency in the simulation study for the assembly deviation of rotor bolt connections. [ABSTRACT FROM AUTHOR]

The paper presents a closed-economy stock-flow consistent model aimed at outlining the natural synthesis between two fundamental pillars of the post-Keynesian approach: the supermultiplier (SM) model and the monetary theory of production based on the notion of endogenous money. Such integration allows the defining of the whole economic mechanism describing the financing of autonomous components and investments, as well as the determination of output and saving within a monetary economy of production. Our contribution argues that the endogenous money theory plays a non-ancillary role within the SM approach. By comparing different scenarios describing the financing of autonomous components of demand and investments (bank loans, retained profits, CB, and equity emissions), we point out that the endogenous process of money creation is the only structural mechanism through which the autonomous components can exist and be independent of current income, and Keynesian causality materializes in the long-run. In general, it is the initial finance of investments and autonomous components through endogenous money that allows them to be ex-post founded by household saving. Conversely, the initial finance through the existing stock of wealth, although it does not intact the investments-saving causality, can be considered only a temporary spin-off of the endogenous money process. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) and big data, among other new technologies, have attracted the attention and interest of practitioners and researchers in cognitive cybersecurity regarding the use of AI technologies to protect digital as well as analogue systems. This mixed-method study explores the main determinants of cognitive cybersecurity adoption at the individual level. We propose an integrated model with unified theory of acceptance and use of technology model in combination with trust, word-of-mouth, information security awareness, and habit. We empirically examine the hypotheses using a survey of 267 people from southern Europe. The results obtained from the use of structural equation modelling show that performance expectancy, effort expectancy, and word-of-mouth affect behavioural intention. The behavioural intention and word-of-mouth influences use behaviour. The results were triangulated with field interviews, which supported the findings. This study offers a valuable contribution to software-selling companies that are at the moment, or will in the future be, interested and/or involved in developing cognitive cybersecurity software to be used at an individual level. [ABSTRACT FROM AUTHOR]

When k is a finite field, [J. Becker, J. Denef and L. Lipshitz, Further remarks on the elementary theory of formal power series rings, in Model Theory of Algebra and Arithmetic, Proceedings Karpacz, Poland, Lecture Notes in Mathematics, Vol. 834 (Springer, Berlin, 1979)] observed that the total residue map res : k ((t)) → k , which picks out the constant term of the Laurent series, is definable in the language of rings with a parameter for t. Driven by this observation, we study the theory VF res , ι of valued fields equipped with a linear form res : K → k which restricts to the residue map on the valuation ring. We prove that VF res , ι does not admit a model companion. In addition, we show that (k ((t)) , res) is undecidable whenever k is an infinite field. As a consequence, we get that (ℂ ((t)) , Res 0) is undecidable, where Res 0 : f ↦ Res 0 (f) maps f to its complex residue at 0. [ABSTRACT FROM AUTHOR]