Model Theory Research Articles

A Possibility Evaluation Model for Road Transportation of Hazardous Chemicals Based on Bow-tie Theory and Bayesian Model

This paper collected 1115 road transportation accidents of hazardous chemicals in China from 2013 to 2021, and constructed a total of 120 accident chains, among which the most common accident chain was "impact → rear-end collision → fuel tank damage → leakage", with a total of 195 times. Based on the analysis of historical accident data, the occurrence mechanism of road transportation accidents of hazardous chemicals was discussed. Based on the bow-tie theory, the bow-tie diagram was established to realize the construction of qualitative reasoning bow-tie diagram for multi-disaster coupling accidents in road transportation of hazardous chemicals. The mapping rules between Bow-tie model and Bayesian network were established, and the structure of Bayesian network for road transportation of hazardous chemicals was constructed. The prior probability and conditional probability of Bayesian network nodes are determined by multi-source data, and the real-time accident probability evaluation is realized by combining quantitative and qualitative methods. Finally, a real time evaluation of the possibility of multi-disaster coupling accidents is realized every 30 seconds through a numerical example, which reflects the influence law of multi-disaster coupling scenarios on risks.

Behavioral responses resulting from e-health services and the role of user satisfaction: the case of the online diabetes test

PurposeThe advancement of technologies has made it possible for health-care organizations to provide convenient online services that enable people to manage their health conditions. Although many studies have investigated the adoption and benefits of e-health services, there has been little focus on health-oriented behaviors after adoption, particularly in relation to service quality and user satisfaction.Design/methodology/approachThis paper is based on the SOR model and service quality theories to investigate behavioral responses, including word-of-mouth, intention to use and intention to act. The authors use a partial least squares structural equation modeling analysis with 194 participants and the diabetes risk test survey in Finland.FindingsThe results show that people are willing to engage in health self-management behaviors if they intend to use the e-health service and are satisfied with it. User satisfaction can be enhanced by improving the visual appeal of the website presentation, the quality of the presented information, as well as the usability of the website, all as components of e-health services.Originality/valueThe authors contribute by creating a construct “intention to act,” referring to health-oriented behaviors resulting from e-health service use. In addition, this study is among the first to apply the SOR model to investigate how user satisfaction leads to intention to use, intention to act and word-of-mouth.

Electrical transport properties of Cu2ZnSnSe4 thin films for solar cells applications

In this work we study the electrical transport properties of Cu2ZuSnSe4 (CZTse) thin films. CZTSe thin films were prepared by PVD method; the parameters of deposition as substrate temperature (T,) and mass, (Mx), (Mx = ZnSe, Cu) were varied for a range wide. Conductivity and resistivity measurements as a function of temperature were obtained between 120 and 400 K. It was observed, that high-temperature range above room temperature (>300 K) the carrier transport is thermally activated, with a single activation energy that changes with the variation of T, and Mx. In the low-temperature range (<300 K)), variable range hopping (VRH) was established as a predominant electronic transport mechanism for all samples. Hoppmg parameters were obtained by Difíusinal model and percolation theory.

Identification of Riluzole derivatives as novel calmodulin inhibitors with neuroprotective activity by a joint synthesis, biosensor, and computational guided strategy

The development of new molecules for the treatment of calmodulin related cardiovascular or neurodegenerative diseases is an interesting goal. In this work, we introduce a novel strategy with four main steps: (1) chemical synthesis of target molecules, (2) Förster Resonance Energy Transfer (FRET) biosensor development and in vitro biological assay of new derivatives, (3) Cheminformatics models development and in vivo activity prediction, and (4) Docking studies. This strategy is illustrated with a case study. Firstly, a series of 4-substituted Riluzole derivatives 1–3 were synthetized through a strategy that involves the construction of the 4-bromoriluzole framework and its further functionalization via palladium catalysis or organolithium chemistry. Next, a FRET biosensor for monitoring Ca2+-dependent CaM-ligands interactions has been developed and used for the in vitro assay of Riluzole derivatives. In particular, the best inhibition (80%) was observed for 4-methoxyphenylriluzole 2b. Besides, we trained and validated a new Networks Invariant, Information Fusion, Perturbation Theory, and Machine Learning (NIFPTML) model for predicting probability profiles of in vivo biological activity parameters in different regions of the brain. Next, we used this model to predict the in vivo activity of the compounds experimentally studied in vitro. Last, docking study conducted on Riluzole and its derivatives has provided valuable insights into their binding conformations with the target protein, involving calmodulin and the SK4 channel. This new combined strategy may be useful to reduce assay costs (animals, materials, time, and human resources) in the drug discovery process of calmodulin inhibitors.

Identity in the Digital Age: An Investigation of Malaysian Perspectives on Technology and Privacy

Malaysia is in the process of developing a new identity system to provide citizens and residents with secure and efficient access to digital services. This study aimed to determine the responsiveness of the Malaysian population to new technologies and evaluate their opinions on managing their identity online. The study employed a quantitative research design and collected data through an online questionnaire. A total of 1,014 participants from Malaysia, aged 18 years and above, were included in the study, and the data were analysed using cross-tabulation analysis. The theoretical framework of the study was based on the technology acceptance model, the risk and negative consequences theory of individuals' perceptions, and the organizational trustworthiness theory. The results showed that various demographic characteristics influence individuals' attitudes towards technology adoption and online identity management. Gender, age, ethnicity/race, work status, employment sector, level of education, place of living, household income level, and residence state were all significantly associated with early adoption of emerging technologies, trying out new technologies, and enjoyment of trying out new technologies. Certain demographic factors may also have an impact on people's preferences for specific identity management tools. The study also found significant relationships between various demographic factors and trust levels when it comes to personal data. The study findings have implications for policymakers and practitioners involved in promoting the adoption of new technologies and the management of online identities. The study's findings may assist policymakers in implementing better measures for protecting Malaysians' online identity and privacy. Additionally, the results could also inform future research investigating technology adoption and acceptance among Malaysians.

Effects of metaverse experience on behavioral intention of visitors: moderating role of similarity between virtual and real experience

Purpose This paper aims to examine the impact of metaverse experiences on customers’ offline behavioral intentions: How do customers’ visits to a hospitality business’s virtual property in the metaverse affect their intentions to visit the physical property in the real world? Design/methodology/approach Based on the general learning model and social cognitive theory, this research hypothesizes the positive impact of metaverse experiences on customers’ visit intentions and explores two boundary conditions for positive impact: user–avatar resemblance and servicescape similarity. Two experimental studies were conducted. Findings Metaverse experience has a significant impact on customers’ visit intentions, and this impact is moderated by user–avatar resemblance and servicescape similarity. Research limitations/implications This research addresses the call for empirical studies regarding the effects of metaverse experience on people’s behavioral intentions. Originality/value As one of the earliest empirical studies on the marketing effects of the metaverse, this research provides a basis for future metaverse studies in the hospitality field.

The Influence of ESG Reporting on Competitive Dynamics in Business: Insights from a Game Theoretical Approach

As the basis of ESG rating, ESG information disclosure has gradually moved from a niche investment concept to a mainstream trend in recent years, which plays a key role in the ESG investment process. However, many enterprises still choose not to disclose relevant information for reasons such as controlling costs and reducing negative information output. For enterprises in the same industry with competitive relations, different choices made by both parties may bring about impacts on enterprise competitiveness, financing cost, strategic transformation, and regulation and policy formulation. This paper, from the perspective of enterprises and their competitors in the same industry, uses the game theory model to put forward suggestions for improving enterprises' strategic choices. By establishing a game model to promote the establishment or improvement of ESG management systems within enterprises, enterprises can seek the balance between cooperation and competition in the game, and finally achieve the overall sustainable development in their respective industries.

A pull-out equivalent telescopic layered failure model of carbon fiber bundles in seawater sea-sand cementitious matrix

Based on the excellent mechanical properties and piezoresistive effect of carbon fiber, carbon fiber reinforced cementitious matrix (CFRCM) has been used in the strengthening and self-monitoring research of reinforced concrete (RC) structures. In this study, the assumptions of the telescopic layered model theory of CFRCM were refined. The factors influencing the piezoresistive effect of carbon fibers were subsequently analyzed. Simultaneously, the resistance calculation theory for the pull-out process of CFRCM bundles was established by combining the parallel circuit theory. Based on the above theories, a pull-out equivalent telescopic layered failure model of carbon fiber bundles in the cementitious matrix was developed, considering the trilinear cohesive material law (CML) and the piezoresistive effect. Pull-out tests on carbon fiber bundles in both freshwater standard sand and seawater sea-sand matrices were conducted. This model was successfully used to simulate the piezoresistive effect during the pull-out process of CFRCM bundles with two matrices and different embedded lengths. The number of fiber filaments in each layer, the rupture damage of the fiber filaments during the loading process, and the degree of matrix infiltration into the carbon fibers were calculated. This work lays the foundation for advancing the development of structural strengthening and structural health monitoring.

Every Countable Model of Arithmetic or Set Theory has a Pointwise-Definable End Extension

Abstract According to the math tea argument, there must be real numbers that we cannot describe or define, because there are uncountably many real numbers, but only countably many definitions. And yet, the existence of pointwise-definable models of set theory, in which every individual is definable without parameters, challenges this conclusion. In this article, I introduce a flexible new method for constructing pointwise-definable models of arithmetic and set theory, showing furthermore that every countable model of Zermelo-Fraenkel ZF set theory and of Peano arithmetic PA has a pointwise-definable end extension. In the arithmetic case, I use the universal algorithm and its Σ n generalizations to build a progressively elementary tower making any desired individual a n definable at each stage n, while preserving these definitions through to the limit model, which can thus be arranged to be pointwise definable. A similar method works in set theory, and one can moreover achieve V = L in the extension or indeed any other suitable theory holding in an inner model of the original model, thereby fulfilling the resurrection phenomenon. For example, every countable model of ZF with an inner model with a measurable cardinal has an end extension to a pointwise-definable model of ZFC + V = L[μ].

Linear instability of hairy black holes in Horndeski theory* *Supported in part by the National Key Research and Development Program of China (2020YFC2201503), the National Natural Science Foundation of China (12205254, 12275238, 11675143), the Natural Science Foundation of Zhejiang Province, China (LR21A050001, LY20A050002), the Fundamental Research Funds for the Provincial Universities of Zhejiang Province, China (RF-A2019015), and the Science Foundation

Horndeski theory constitutes the most general model of scalar-tensor theories. It has attracted much attention in recent years in relation with black holes, celestial dynamics, stability analysis, etc. It is important to note that, for certain subclasses of Horndeski models, one can obtain analytic solutions for the background fields. This facilitates the investigation of the corresponding stability problems in detail. In particular, we aim to determine the constraints to the model or theory under which the stability conditions can be satisfied. In this study, we focused on a subclass of Horndeski theory and a set of analytic background solutions. In addition, the odd-parity gravitational perturbation and 2nd-order Lagrangian were investigated. Through careful analysis, the instability was identified within the neighborhood of the event horizon. This allows exclusion of a specific geometry for the model. Such an instability is implanted in the structure of the corresponding Lagrangian and is not erased by simply adding numerical constraints on the coupling parameters. As a starting point of our research, the current study provides insights for further exploration of the Horndeski theory.

Enhanced luminescence of Dy-activated in-situ synthesized LaAlO3/MgO nanocomposites for cool wLED and latent finger printing applications

In the current study, a series of trivalent Dysprosium doped La1-xDyxAlO3/MgO (with x = 0, 1, 3, 5, 7 and 9 mol. %) nanophosphor composites have been synthesized via Pechini sol-gel method. Structural properties were analyzed using XRD, Rietveld refinement and FESEM. The prepared nanophosphors exhibit rhombohedral/face-centered structure. The bandgap values of the nanophosphors were found to be in the range of 5.39–5.75eV. At the sintering temperature of 900 °C, La1-xDyxAlO3/MgO (x = 5 mol.%) nanocomposite exhibit significant enhancement in the white light emission as compared to La1-yDyyAlO3 (y = 5 mol.%). PL intensity of composite further increases with the rise in sintering temperature up to 1200 °C. Dexter's theory and Burshtein model when applied to PL and TRPL profiles unveil the d-d energy transfer mechanism that shifts from donor-acceptor to donor-donor transfer with dopant concentration. Other exemplary colorimetric and luminescence-based parameters such as, CRI, CCT, life-time, energy transfer efficiencies and probabilities indicate the potential suitability of fabricated phosphor for w-LED and imaging applications. The optimized nanophosphor composite, i.e., La1-xDyxAlO3/MgO (x = 5 mol.%) has been explored for Latent Finger Printing and it successfully identified all the levels-1, 2 and 3 features of fingerprint.

Investigation of the lubrication performance of a marine diesel engine crankshaft using a thermo-electrohydrodynamic model

Abstract This study outlines the development of a three-dimensional model for the crankshaft-bearing and a multi-body dynamics model for a four-stroke marine diesel engine. The models are constructed through a simulation approach that integrates the finite element method and multi-body dynamics method. Additionally, the Greenwood/Tripp asperity contact theory and average flow model are incorporated. The investigation also delves into the dynamic coupling between the crankshaft-bearing multi-body system and the mixed lubrication effects, accounting for lubricating oil as a thermo-electrohydrodynamic model and the journal as an elastomer. The study meticulously examines the lubrication characteristics of main bearings in marine diesel engines during normal operational conditions and scrutinizes the impact of various parameters on crankshaft-bearings. The study concludes by offering recommendations and technical support for innovative optimization design and model enhancement of diesel engine crankshaft-bearings.

Characterization of the Edge States in Colloidal Bi2Se3 Platelets.

The remarkable development of colloidal nanocrystals with controlled dimensions and surface chemistry has resulted in vast optoelectronic applications. But can they also form a platform for quantum materials, in which electronic coherence is key? Here, we use colloidal, two-dimensional Bi2Se3 crystals, with precise and uniform thickness and finite lateral dimensions in the 100 nm range, to study the evolution of a topological insulator from three to two dimensions. For a thickness of 4-6 quintuple layers, scanning tunneling spectroscopy shows an 8 nm wide, nonscattering state encircling the platelet. We discuss the nature of this edge state with a low-energy continuum model and ab initio GW-Tight Binding theory. Our results also provide an indication of the maximum density of such states on a device.

Determinants of user acceptance of digital insurance platform service on InsurTech: an empirical study in South Korea

ABSTRACT In recent days, InsurTech services and users are growing rapidly worldwide. InsurTech, a combination of ‘insurance’ and ‘technology’, as an area of Fintech has become an essential innovation strategy of insurance companies. Even if InsurTech services and users are prevalent, there is a lack of empirical research on determinants of user acceptance of InsurTech. The objective of this study is to explore factors determining user acceptance of digital insurance platform services most popular within InsurTech in South Korea. The research model was derived from mainly three theories: the unified theory of acceptance and use of technology (UTAUT), information systems success model (ISSM) and innovation diffusion theory (IDT) with service characteristic factors (system quality, information quality, and service quality) and user characteristic factors (personal innovativeness, self-efficacy, and perceived risk). 249 survey responses from South Korea were analysed. According to the results, information quality exhibited an effect on performance expectancy and effort expectancy whereas service quality was shown to affect only effort expectancy. Furthermore, personal innovativeness affected performance expectancy, effort expectancy, and social influence, self-efficacy exhibited an effect on performance expectancy, and perceived risk affected performance expectancy and effort expectancy.

Adverse childhood experiences among black sexually minoritized men and Black transgender women in Chicago

BackgroundAdverse childhood experiences (ACE) are important predictors of mental health outcomes in adulthood. However, commonly used ACE measures such as the Behavioural Risk Factor Surveillance System (BRFSS) have not been validated among Black sexually minoritized men (SMM) nor transgender women (TW), whom are known to have higher rates of ACE and poorer mental health outcomes. Assessing the psychometric properties of the measure is important for health equity research, as measurements that are not valid for some populations will render uninterpretable results.MethodsData are drawn from the Neighborhoods and Networks (N2) study, a longitudinal cohort of Black SMM and TW living in Southern Chicago. We conducted confirmatory factor analysis, correlation analysis and a two-parameter Item Response Theory (IRT) on the BRFSS ACE measure, an 11-item measure with 8 domains of ACE.ResultsOne hundred forty seven participants (85% cisgender male) completed the BRFSS ACE measurement in the N2 study with age ranges from 16–34. The cohort were from a low socioeconomic background: about 40% of the cohort were housing insecure and made than $10,000 or less annually. They also have a high number of ACEs; 34% had endorsed 4 or more ACE domains. The three-factor structure fit the BRFSS ACE measure best; the measurement consisted of three subscales: of “Household Dysfunction”, “Emotional / Physical”, and “Sexual Abuse” (CFI = 0.975, TLI = 0.967, and RMSEA = 0.051). When the 8 domains of ACE were summed to one score, the total score was is correlated with depressive symptoms and anxiety scores, establishing concurrent validity. Item Response Theory model indicated that the “parental separation” domain had a low discrimination (slope) parameter, suggesting that this domain does not distinguish well between those with and without high ACE.ConclusionsThe BRFFS ACE measure had adequate reliability, a well-replicated structure and some moderate evidence of concurrent validity among Black SMM and TW. The parental separation domain does not discriminate between those with high and low ACE experiences in this population. With changing population demographics and trends in marriage, further examination of this item beyond the current study is warranted to improve health equity research for all.

Quantitative Research on “Blockchain+Supply Chain” Financing Based on Game Theory Modeling

In the 21st century, with globalization and the “Belt and Road” economic activities. As an important financial means, supply chain financing plays a key role in trade transactions between enterprises. Supply chain financing refers to providing financial support and services to different participants in the entire supply chain through financial instruments to meet the financial needs of their production and trade activities. To address the issue of “blockchain+supply chain” financing, specifically in the traditional supply chain, the downstream of the SMEs financing difficulties has been one of the factors plaguing its development. Still, also one of the constraints on the overall supply chain operational efficiency, we use the principles of game theory to establish a game theory model between financial institutions and SMEs and use Matlab software to solve the simulation data. We use the principle of game theory to establish a game theory model between financial institutions and MSMEs, use Matlab software to solve the simulation data and analyze the financial institutions to adopt the “blockchain+supply chain” financing strategy, and MSMEs to adopt the trustworthy strategy so that the two sides can maximize the benefits, and also maximize the benefits for the whole supply side. In addition, the research process and results can provide references for relevant state departments and various social enterprises and organizations.

A Short Note on the Early History of the Spectrum Problem and Finite Model Theory

Finite model theory is currently not one of the hot topics in the philosophy and history of mathematics, not even in the philosophy and history of mathematical logic. The philosophy of mathematics and mathematical logic has concentrated on infinite structures, closely related to foundational issues. In that context, finite models deserved only marginal attention because it was taken for granted that the study of finite structures is trivial compared to the study of infinite structures. In retrospect, research on finite structures turned out to be neither trivial nor irrelevant but had an important impact on theoretical computer science. A closer look at the early history of the spectrum problem shows that the birth of finite model theory has roots in formal logic, at a time when computer science did not yet exist.

Research on the cognitive neural mechanism of privacy empowerment illusion cues regarding comprehensibility and interpretability for privacy disclosures

In the era of artificial intelligence, privacy empowerment illusion has become a crucial means for digital enterprises and platforms to “manipulate” users and create an illusion of control. This topic has also become an urgent and pressing concern for current research. However, the existing studies are limited in terms of their perspectives and methodologies, making it challenging to fully explain why users express concerns about privacy empowerment illusion but repeatedly disclose their personal information. This study combines the associative-propositional evaluation model (APE) and cognitive load theory, using event-related potential (ERP) technology to investigate the underlying mechanisms of how the comprehensibility and interpretability of privacy empowerment illusion cues affect users’ immediate attitudes and privacy disclosure behaviours; these mechanisms are mediated by psychological processing and cognitive load differences. Behavioural research results indicate that in the context of privacy empowerment illusion cues with low comprehensibility, users are more inclined to disclose their private information when faced with high interpretability than they are when faced with low interpretability. EEG results show that in the context of privacy empowerment illusion cues with low comprehensibility, high interpretability induces greater P2 amplitudes than does low interpretability; low interpretability induces greater N2 amplitudes than does high interpretability. This study extends the scopes of the APE model and cognitive load theory in the field of privacy research, providing new insights into privacy attitudes. Doing so offers a valuable framework through which digital enterprises can gain a deeper understanding of users’ genuine privacy attitudes and immediate reactions under privacy empowerment illusion situations. This understanding can help increase user privacy protection and improve their overall online experience, making it highly relevant and beneficial.

A coupled neural field model for the standard consolidation theory

The standard consolidation theory states that short-term memories located in the hippocampus enable the consolidation of long-term memories in the neocortex. In other words, the neocortex slowly learns long-term memories with a transient support of the hippocampus that quickly learns unstable memories. However, it is not clear yet what could be the neurobiological mechanisms underlying these differences in learning rates and memory time-scales. Here, we propose a novel modeling approach of the standard consolidation theory, that focuses on its potential neurobiological mechanisms. In addition to synaptic plasticity and spike frequency adaptation, our model incorporates adult neurogenesis in the dentate gyrus as well as the difference in size between the neocortex and the hippocampus, that we associate with distance-dependent synaptic plasticity. We also take into account the interconnected spatial structure of the involved brain areas, by incorporating the above neurobiological mechanisms in a coupled neural field framework, where each area is represented by a separate neural field with intra- and inter-area connections. To our knowledge, this is the first attempt to apply neural fields to this process. Using numerical simulations and mathematical analysis, we explore the short-term and long-term dynamics of the model upon alternance of phases of hippocampal replay and retrieval cue of an external input. This external input is encodable as a memory pattern in the form of a multiple bump attractor pattern in the individual neural fields. In the model, hippocampal memory patterns become encoded first, before neocortical ones, because of the smaller distances between the bumps of the hippocampal memory patterns. As a result, retrieval of the input pattern in the neocortex at short time-scales necessitates the additional input delivered by the memory pattern of the hippocampus. Neocortical memory patterns progressively consolidate at longer times, up to a point where their retrieval does not need the support of the hippocampus anymore. At longer times, perturbation of the hippocampal neural fields by neurogenesis erases the hippocampus pattern, leading to a final state where the memory pattern is exclusively evoked in the neocortex. Therefore, the dynamics of our model successfully reproduces the main features of the standard consolidation theory. This suggests that neurogenesis in the hippocampus and distance-dependent synaptic plasticity coupled to synaptic depression and spike frequency adaptation, are indeed critical neurobiological processes in memory consolidation.

Multiple salary comparisons, distributive justice, and employee withdrawal.

Salary comparison has well-established implications for employees' attitudes and behaviors at work. Yet how employees process information about simultaneous comparisons, particularly when internal and external comparison information is incongruent, remains controversial. In this article, we draw from the model of dispositional attribution and equity theory to predict how the incongruence of internal and external salary comparisons affects perceptions of distributive justice and subsequent employee withdrawal behavior. We hypothesized that the effect of salary comparisons on perceived distributive justice follows a hierarchically restrictive schema in which a lower salary in comparison to a referent has a greater effect than a higher salary. This further affects employee withdrawal (neglect, turnover intention, and voluntary turnover). We also propose that the effects of salary comparisons are bounded by employees' zero-sum construal of success. Three studies were conducted to test our hypotheses: a quasi-experimental study and two time-lagged field studies. Consistent with our hypotheses, we observed that, when comparison information was incongruent, underpayment compared with others more strongly affected perceived distributive justice than overpayment did. The subsequent impact on perceived distributive justice was negatively related to employee withdrawal. As expected, the effect of incongruent salary comparison information was stronger for employees with lower zero-sum construal of success. The theoretical and practical implications of these findings are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).