Model Theory Research Articles

Vulnerability to fluctuations in prey and predation landscape in a central place foraging marine predator

IntroductionHuman-induced environmental change is driving a global redistribution of biodiversity, resulting in shifting prey and predation landscapes. These shifting landscapes can lead to changes in behavior, health, and vital rates, with potential implications for population dynamics.MethodsIn the present study, a state-dependent life-history theory model was developed to investigate the individual- and population-level responses of Australian fur seals (Arctocephalus pusillus doriferus) to changes in prey availability and at-sea mortality risk.ResultsRates of pregnancy, pup nursing, and abortion were unaffected by prey availability in the simulated population. Likewise, on-land and at-sea durations were largely unaffected by prey availability, with more pronounced affects for nonreproductive and pregnant females than for lactating females. There was a strong influence of prey availability on the proportion of females that were concurrently pregnant and lactating, largely due to an increase in pup abandonments under low prey availability scenarios. This effect on pup abandonments also had flow on effects for pup recruitment. Increasing at-sea mortality risk resulted in greater offspring losses due to maternal death. The combined impact of prey availability and at-sea mortality risk on the number of simulated female offspring reaching sexual maturity was substantial.DiscussionConsequently, our results suggest high vulnerability of the Australian fur seal population to shifting prey and predation landscapes. These results indicate a need for continued monitoring of Australian fur seal pup production and population dynamics in the face of rapid environmental change.

Psychometric validation of the Danish version of the Major Depression Inventory using data from the Lolland-Falster health study (LOFUS)

Purpose The Major Depression Inventory (MDI) is a widely used self-rating depression scale commonly in primary care in Denmark. It has not been subject to robust psychometric validation in a general population setting. The aim of this study was to evaluate the psychometric measurement properties of the MDI when applied in the general population. Methods We evaluated statistical psychometric validity using modern test theory (confirmatory factor analysis, item response theory models and Rasch measurement theory) testing local independence and differential item function across groups defined by gender, age, education, and chronic disease status. Separate analyses across different strata and across different statistical models were employed. Results Regarding structural validity we consistently identified local dependence for the item two pairs (MDI2,MDI3) and (MDI4,MDI5) across strata. This result was confirmed by bifactor CFA models and item screening. We further identified substantial differential item functioning with respect to age group and with respect to chronic disease. We identified quantified the magnitude of this lack of measurement invariance. Conclusion The MDI is psychometrically valid in homogenous sub populations, but the disclosed evidence of local dependence means that published estimates of its reliability cannot be trusted. The lack of measurement invariance means that the instrument cannot be used to compare individuals or groups unless they are similar in terms of age group and chronic disease status.

Performance evaluation and dimensional optimization design of planar 6R redundant actuation parallel mechanism

Abstract Aiming at the problems of small good workspace, many singular configurations, and limited carrying capacity of non-redundant parallel mechanisms, a full-redundant drive parallel mechanism is designed and developed, and its performance evaluation, good workspace identification, and scale optimization design are studied. First, the kinematics analysis of the planar 6R parallel mechanism is completed. Then, the motion/force transmission performance evaluation index of the mechanism is established, and the singularity analysis of the mechanism is completed. Based on this, the fully redundant driving mode of the mechanism is determined, and the good transmission workspace of the mechanism in this mode is identified. Then, the mapping relationship between the performance and scale of the mechanism is established by using the space model theory, and the scale optimization of the mechanism is completed. Finally, the robot prototype is made according to the optimal scale, and the performance verification is carried out based on the research of dynamics and control strategy. The results show that the fully redundant actuation parallel mechanism obtained by design optimization has high precision and large bearing capacity. The position repeatability and position accuracy are 0.053 mm and 0.635 mm, respectively, and the load weight ratio can reach 15.83%. The research results of this paper complement and improve the performance evaluation and scale optimization system of redundantly actuated parallel mechanisms.

Analysis of a spatio-temporal advection-diffusion model for human behaviors during a catastrophic event

In this work, using the theory of first-order macroscopic crowd models, we introduce a compartmental advection–diffusion model, describing the spatio-temporal dynamics of a population in different human behaviors (alert, panic and control) during a catastrophic event. For this model, we prove the local existence, uniqueness and regularity of a solution, as well as the positivity and [Formula: see text]-boundedness of this solution. Then, in order to study the spatio-temporal propagation of these behavioral reactions within a population during a catastrophic event, we present several numerical simulations for different evacuation scenarios.

Predicting the density and viscosity of deep eutectic solvents at atmospheric and elevated pressures

Deep eutectic solvents (DESs) are promising and sustainable substitutes for organic solvents in various applications. The knowledge of their density and viscosity at different temperatures and pressures is crucial for the corresponding process design. However, most literature primarily focuses on predicting these properties at atmospheric pressure. In this study, we employed the perturbed chain polar statistical associating fluid theory (PCP-SAFT) model and entropy scaling method to predict DESs’ density and viscosity at atmospheric and elevated pressures. 2831 density data points of 38 DESs and 1018 viscosity data points of 31 DESs at different temperatures and pressures were used to evaluate the accuracy of the applied methods. The pure component PCP-SAFT parameters of choline chloride (ChCl) were regressed using density data of ChCl-based DES at various temperatures and pressures. It was found that the PCP-SAFT model can provide satisfactory density predictions for DESs at atmospheric pressure, even without using the system-specific binary interaction parameter (kij=0). However, accurate viscosity prediction at atmospheric pressure for DESs necessitated the inclusion of the binary interaction parameter (kij=aijT+bij) in the PCP-SAFT model. The system-specific coefficients aij andbij, derived from experimental data at atmospheric pressure, were used to predict the density or viscosity of DES at elevated pressures. Accurate predictions for density were observed across the entire pressure range, whereas effective viscosity predictions were confined to a specific pressure range.

Analytical Analysis of Common Fixed Point Results in Fuzzy Cone Metric Spaces

The concept of fuzzy sets was introduced by Zadeh (1965) which marked the beginning of the evolution of fuzzy mathematics. The introduction of uncertainty in the theory of sets in a non-probabilistic manner opened up new possibilities for research in this field. Since then, many authors have explored the theory of fuzzy sets and its applications, leading to successful advancements in various fields such as mathematical programming, model theory, engineering sciences, image processing, and control theory. In this paper, we aim to improve and generalize some common fixed point theorems in fuzzy cone metric spaces, an extension of the well-known results given by Saif Ur Rahman and Hong Xu-Li (2017).

Peridynamic correspondence model with strain gradient elasticity for microstructure dependent size effects

This study presents a peridynamic (PD) correspondence model with strain gradient elasticity (SGE) to capture size effect on strength of nano- and micro-scale structures. The classical elasticity theory lacking a length scale parameter does not account for the microstructure-dependent size effects. Strain Gradient (SG) elasticity is an extension of the classical elasticity with a length scale parameter(s) which can be linked to the microstructure of the material. Peridynamic theory introduces damage into the constitutive relations in a natural way by allowing for interactions of a material point within its horizon which is referred to as the internal length parameter. The correspondence model of the PD theory permits the incorporation of the constitutive relationship of SG theory. Therefore, the present approach combines the effects of PD and SGE length scale parameters on the stiffness and strength of the material. The resulting equations present two length parameters: the horizon of a material point in PD theory and the characteristic length in SGE theory. The PD equation of motion with SGE (PDSG) is free of spatial derivatives and allows for the imposition of classical and nonclassical boundary conditions. The PDSG is first applied to investigate the deformation response of a one-dimensional nanoscale film subjected to a quasi-static tensile load and a dynamic load through an initial constant strain. The static response is compared with the analytical solution for varying ratio of SG length parameter to PD horizon. The dynamic response is compared with a computational solution while satisfying the nonclassical boundary conditions. Subsequently, the PDSG is applied to study the deformation response of a two-dimensional nanoscale film subjected to a quasi-static axial load and a specified tangential end displacement. These two cases are considered under special displacement constraints to compare with the available analytical solutions. Subsequently, a two-dimensional nanoscale film with or without an internal crack is subjected to uniform tensile loading. Finally, crack propagation is simulated under incremental displacement loading. The results capture the analytical predictions and the expected increase in stiffness with increasing ratio of SG length parameter to PD horizon.

Design and construction for theory and method of magnetic-controlled negative pressure GTAW arc model based on multi-physics simulation

Design and construction for theory and method of magnetic-controlled negative pressure GTAW arc model based on multi-physics simulation

How do patients' perceptions and doctors' images impact patient decisions? Deconstructing online physician selection using multimodal data

In the post-pandemic era, medical resources are uneven, and access to healthcare is complicated. Online medical platforms have become a solution to bridge the information gap and reduce hospital pressure. This study uses the stereotype content model and signaling theory to explore the impact of patient perception of patient decision making (PDM) on online medical service platforms. Also, it tests the moderating effect of physician image. We collected information on 12,890 physicians and 746,981 patient reviews from online medical platforms in China. Unsupervised machine learning was used to construct a topic model to extract patients' perceptions of physicians' competence and warmth. Meanwhile, the facial features of physicians, such as age, smile, and glasses, are recognized by convolutional neural networks. Finally, the influence of PDM concern on decision-making and the moderating effect of physician image were analyzed by multiple linear regression. The results of the study showed that (1) patients' perceptions of physicians' competence and warmth had a positive effect on decision-making; (2) physicians' age and wearing glasses enhanced the positive effect of perception on decision-making; and (3) however, physicians' smiles weakened the positive effect of perception on decision-making. This study provides new insights into patients' online physician selection, guides the construction and promotion of medical service platforms, and provides an effective avenue of exploration to alleviate the problem of uneven distribution of offline medical resources.

Measuring maladaptive personality traits with the Structured Clinical Interview for DSM-IV Axis II Screening Questionnaire using a common metrics approach.

The classification of personality disorder (PD) is undergoing a paradigm shift in which categorically defined specific PDs are being replaced by dimensionally defined maladaptive trait domains. To bridge the classificatory approaches, this study attempts to use items from the categorical PD model in DSM-IV to measure the maladaptive trait domains described in DSM-5 Section III/ICD-11. A general population sample comprising 1228 participants completed the Screening Questionnaire of the Structured Clinical Interview for DSM-IV Axis II (SCID-II-SQ), the Personality Inventory for DSM-5 (PID-5), and the anankastia scale of the Personality Inventory for ICD-11 (PiCD). Using item response theory models and a psychometric linking technique, SCID-II-SQ items were evaluated for their contribution to measuring maladaptive trait domains. The best discriminating items were then selected to derive proxy scales. We found that convergent validity of these proxy scales was in a similar range to that of other self-report measures for PD, except for the proxy scale for PiCD anankastia. However, only the proxy scale for negative affectivity showed acceptable reliability that would allow its application in research settings. Future studies should seek to establish a common metric between specific PDs and maladaptive trait domains using self-report measures with higher specificity or semi-structured interviews.

Item Statistics of Multiple Choice Physics Achievement Test Using Classic Test Theory and Item Response Theory

This study examine the comparability of item statistics generated from the frameworks of classical test theory (CTT) and 2-parameter model of item response theory (IRT). A 40-item Physics Achievement Test was developed and administered to 600 senior secondary school two students, who were randomly selected from 12 senior secondary schools in Taraba State, Nigeria. Results showed that item statistics obtained from both frameworks were relatively similar. However, item statistics obtained from IRT 2-parameter model looked balanced than those from CTT. In addition, for item selection process, IRT 2-parameter model retained more items than CTT model. This result implies that test developers and public examining bodies should integrate IRT model into their test development processes. Through IRT model, test constructors would be able to generate stable items than in the CTT model used at present and at the end, the test scores of examinees will be more reliably estimated.

The non-spherical ground state of Proca stars

Spherical Proca Stars (PSs) are regarded as the ground state amongst the family of PSs. In accordance, spherical PSs are thought to have a fundamental branch of stable solutions. In this Letter, we provide energetic, morphological and dynamical evidence that spherical PSs are actually excited states. The ground state is shown to be a family of static, non-spherical, in fact prolate, PSs. The spherical stars in the fundamental branch, albeit stable against spherical perturbations, turn out to succumb to non-spherical dynamics, undergoing an isometry breaking into prolate PSs. We also provide evidence for the dynamical formation of prolate PSs, starting from spherical dilute initial data, via gravitational cooling. Consequently, PSs provide a remarkable example of (possibly compact) relativistic stars, in General Relativity minimally coupled to a simple, physical, field theory model, where staticity plus stability implies non-sphericity.

Estimating crash risk and injury severity considering multiple traffic conflict and crash types: A bivariate extreme value approach

Traffic conflicts are generally considered independent events in existing extreme value theory models to estimate the risk of total or single types of crashes. However, traffic events at a road entity are not necessarily independent interactions and can lead to multiple traffic conflicts with shared common unobserved factors. A comprehensive estimation of crash risks in a road entity needs to consider the correlation of potential traffic conflicts to avoid possible bias in prediction performance and the problem of undetected deficiencies. This study proposes a Bayesian non-stationary bivariate generalised extreme value modelling framework to estimate the severe and non-severe crash risks accounting for the correlation between right-turn and rear-end conflicts at signalised intersections. A deep neural network-based computer vision technique was applied to extract the traffic conflicts from 77 h of video recordings over two right-turn approaches at two signalised intersections in Cairns, Australia. Post encroachment time and modified time to collision were used to characterise right-turn and rear-end conflicts, respectively, while an expected post-collision velocity difference was combined with post encroachment time and modified time to collision for crash risk estimation by injury severity levels. Several covariates were used to address the time-varying heterogeneity of traffic conflict extremes and to estimate the differential crash risks at signal cycles. Results showed a significant correlation between right-turn and rear-end crashes at signal cycle levels, indicating the importance of accounting for the dependency among traffic conflict types. Overall, the bivariate models considering the correlation among traffic conflict types were found to understandably perform better than their univariate counterparts. This study provides a demonstration of a correlated crash risk modelling framework that addresses issues related to the suitable traffic conflict measures, time varying risks (non-stationarity), heterogeneity, and injury severity levels of different crash types.

Predicting Real-World Penny Auction Durations by Integrating Game Theory and Machine Learning

Game theory and machine learning are two widely used techniques for predicting the outcomes of strategic interactions among humans. However, the game theory-based approach often relies on strong rationality and informational assumptions, while the machine learning-based approach typically requires the testing data to come from the same distribution as the training data. Our work studies how to integrate the two techniques to address these weaknesses. We focus on the interactions among real bidders in penny auctions, and develop a three-stage framework to predict the distributions of auction durations, which indicate the numbers of bids and auctioneer revenues. Specifically, we first leverage a pre-trained neural network to encode the descriptions of products in auctions into embeddings. Second, we apply game theory models to make preliminary predictions of auction durations. In particular, we tackle the challenge of accurately inferring parameters in game theory models. Third, we develop a Multi-Branch Mixture Density Network to learn the mapping from product embeddings and game-theoretic predictions to the distributions of actual auction durations. Experiments on real-world penny auction data demonstrate that our framework outperforms both game theory-based and machine learning-based prediction approaches.

Angular Momentum in a Special Nonlinear Elastic Rod

AbstractIn the constrained Cosserat theory of a rod with a rigid cross-section, the balance of angular momentum is satisfied by a restriction on the constitutive equations that requires a second order tensor to be symmetric. The kinematics of the rod are determined by satisfying the balances of linear and director momentum and kinematic constraints. In contrast, the Antman model for a special Cosserat theory of rods proposes constitutive equations directly for the force and mechanical moment applied to the rod and the kinematics are determined by the balances of linear and angular momentum. These two models differ by their treatment of angular momentum. This note poses and answers the question: Are the solutions of these two models identical for the same strain energy?

A large deformation gradient theory for glassy polymers by means of micromorphic regularization

AbstractCold forming of polycarbonate films results in the formation of shear bands in the necking zone. The numerical results obtained from standard viscoplastic material models exhibit mesh size dependency, requiring mathematical regularization. For this purpose, we present in this work a large deformation gradient theory for a viscoplastic isotropic material model published before. We extend our model to a micromorphic model by introducing a new micromorphic variable as an additional degree of freedom along with its first gradient. This variable represents a microequivalent plastic strain. The relation between the macroequivalent plastic strain and the micromorphic variable is accomplished by a micromorphic coupling modulus. This coupling forces proximity between the macro- and microvariables, leading to the targeted regularization effect. The micromorphic model is implemented as a three-dimensional initial boundary value problem in an in-house finite element tool. The analysis is performed for both uniaxial and biaxial specimens. The provided numerical examples show the ability of our model to regularize shear bands within the specimens and address the issue of localization.

How does school management team empowerment relate to teachers' organizational citizenship behavior? A moderated mediation model

PurposePrevious studies have examined the empowerment of individual teachers, while neglecting the fact that such a phenomenon might grow within a team. Building on the crossover model and social exchange theory, the aim of this study is to explore whether team empowerment among school management teams (SMTs), is transmitted to the school level and affects schoolteachers' job satisfaction and thereby schoolteachers' organizational citizenship behavior (OCB). Furthermore, we explored whether those relationships are moderated by team-member exchange (TMX) relationships.Design/methodology/approachData were collected from 86 principals, 357 SMT members and 683 schoolteachers from 86 schools.FindingsResults confirmed the mediating role of schoolteachers' job satisfaction, showing a positive relationship between SMT empowerment and schoolteachers' job satisfaction, and between job satisfaction and OCB. The moderation of TMX and the overall moderated mediation hypotheses were not supported.Research limitations/implicationsThe nature of data collected in the current study precludes any inference concerning the direction of casual links among the study constructs. Therefore, longitudinal studies could be designed, aimed at confirming the direction of links among the variables.Practical implicationsThe findings reinforce the impact of schoolteachers' job satisfaction on achieving OCBs. Hence, SMT members carry the responsibility to cultivate satisfied schoolteachers through schools' support mechanisms and guidance in order to achieve schoolteachers' OCB.Originality/valueThe study identifies SMT empowerment as a key factor that may indirectly encourage schoolteachers to invest in OCBs through positive attitudes of schoolteachers' job satisfaction.

A novel comprehensive framework for surface roughness prediction of integrated robotic belt grinding and burnishing of Inconel 718

Surface roughness serves as a critical metric for assessing surface integrity, directly influencing the service performance of components. Hardening burnishing is a regularly used post-grinding procedure for Inconel 718 that can simultaneously reduce surface roughness and improve surface mechanical characteristics. A novel comprehensive framework is proposed to predict the surface roughness of Inconel 718 processed by the integrated robotic belt grinding and burnishing system developed in this study. Accounting for abrasive grain conditions and material removal rate during grinding, the L-BFGS-B optimization algorithm and image processing are utilized to predict the ground surface roughness first. Building upon this foundation, theoretical models are applied to ascertain the critical burnishing force needed to enter the hardening burnishing stage. Following this, the Expansion Cavity Model and Hertz theory are used to predict the roughness of the hardening burnished surface, which is only applicable when the step-over value exceeds a critical value. The proposed framework not only enhances our comprehension of the mechanisms underlying material surface deformation but also offers a novel avenue for predicting surface roughness during integrated robotic belt grinding and burnishing with high accuracy.

Do Islamic Fintech Leadership and Technology Adoption Predict Sustainable Entrepreneurship Values among Fintech Organizations?

The primary objectives of this paper are to examine if Islamic Fintech leadership (IFL) and technology adoption (TA) can predict Sustainable Entrepreneurship Values (SEV) among Malaysian Fintech organizations. A survey was self-administered to 294 organisations involved in payment, e-wallet, prop-tech, digital bank, blockchain, cryptocurrency, remittance, AI/data, marketplace, crowdfunding, insurtech, wealthtech, Know Your Customer (KYC), and reg-tech services offerings.  Partial Least Square Structural Equation Modelling is used to analyze 121 responses. The results show that IFL has a positive and significant relationship with SEV. TA, however, does not moderate the relationship between IFL and SEV. This paper contributed to developing the extended Technology Acceptance Model and Resource-Based Theory. The SEV model explains the leadership concern for socio-economy, environment, and values by creating a game changer for Islamic digital transformation that enables micro and small enterprises to access faster socio-economic well-being and financial health. 

Mitigating Financial Statement Fraud Perpetrated by Corporate Psychopaths

This paper proposes a fraud mitigation model that focuses on corporate psychopathy's impact on material misstatement of financial statements fraud. Prior research on psychopathy and corporate psychopaths has found that people with these tendencies do not possess the need to rationalize their behavior, therefore negating the rationalization point present in most prior fraud theory models. There is ample prior research on the impact of corporate psychopaths’ effect on corporate culture. There is also an abundance of prior research on fraud theory and how fraud is perpetrated. Drawing from existing research in these areas, this proposed fraud mitigation model identifies and addresses the elements present when corporate psychopaths perpetrate fraud. Board of directors will benefit from this study when they unknowingly hire leaders who exhibit corporate psychopathic traits that can impact financial reporting and internal controls procedures. Other stakeholders and the public interest may benefit from lower risk of financial statement fraud due to fewer corporate psychopaths in leadership positions perpetrating financial statement fraud.