Validity Of Model Research Articles

Statistical monitoring applied to data science in classification: continuous validation in predictive models

PurposeThis study aims to analyze the performance of quality indices to continuously validate a predictive model focused on the control chart classification.Design/methodology/approachThe research method used analytical statistical methods to propose a classification model. The project science research concepts were integrated with the statistical process monitoring (SPM) concepts using the modeling methods applied in the data science (DS) area. For the integration development, SPM Phases I and II were associated, generating models with a structured data analysis process, creating a continuous validation approach.FindingsValidation was performed by simulation and analytical techniques applied to the Cohen’s Kappa index, supported by voluntary comparisons in the Matthews correlation coefficient (MCC) and the Youden index, generating prescriptive criteria for the classification. Kappa-based control charts performed well for m = 5 sample amounts and n = 500 sizes when Pe is less than 0.8. The simulations also showed that Kappa control requires fewer samples than the other indices studied.Originality/valueThe main contributions of this study to both theory and practitioners is summarized as follows: (1) it proposes DS and SPM integration; (2) it develops a tool for continuous predictive classification models validation; (3) it compares different indices for model quality, indicating their advantages and disadvantages; (4) it defines sampling criteria and procedure for SPM application considering the technique’s Phases I and II and (5) the validated approach serves as a basis for various analyses, enabling an objective comparison among all alternative designs.

Darcy's law survival from no-slip to perfect-slip flow in porous media

A macroscopic model for perfect-slip flow in porous media is derived in this work, starting from the pore-scale flow problem and making use of an upscaling technique based on the adjoint method and Green's formula. It is shown that the averaged momentum equation has a Darcy form in which the permeability tensor, $\boldsymbol{\mathsf{K}}_{ps}$ , is obtained from an associated adjoint (closure) problem that is to be solved on a (periodic) unit cell representative of the structure. Similarly to the classical permeability tensor, $\boldsymbol{\mathsf{K}}$ , in the no-slip regime, $\boldsymbol{\mathsf{K}}_{ps}$ is intrinsic to the porous medium under consideration and is shown to be symmetric and positive. Integral relationships between $\boldsymbol{\mathsf{K}}_{ps}$ , the partial-slip flow permeability tensor, $\boldsymbol{\mathsf{K}}_{s}$ , and $\boldsymbol{\mathsf{K}}$ are derived. Numerical simulations carried out on two-dimensional model porous structures, together with an approximate analytical solution and an empirical correlation for a particular configuration, confirm the validity of the macroscopic model and the relationship between $\boldsymbol{\mathsf{K}}_{ps}$ and $\boldsymbol{\mathsf{K}}$ .

Examining the Influence of Renewable Energy Consumption, Technological Innovation, and Export Diversification on Economic Growth: Empirical Insights from E-7 Nations

The present research focuses on the endogenous development theory and investigates the relationships between economic growth (dependent variable) and renewable energy consumption, technological innovation, and export diversification (independent variables) in seven emerging economies known as the E-7. Previous studies have examined these factors individually but have not explored their combined impact on the E-7 economies. Therefore, this study contributes to the existing literature on the effects of renewable energy consumption, technological advancement, and export diversification on economic development. This study analyses the dynamic connections among these variables in seven selected emerging countries: Brazil, China, Indonesia, India, Mexico, Russia, and Turkey. Panel data from 1990 to 2022 are utilised, and various methodologies, including panel cointegration, the pooled mean group–autoregressive distributed lag (PMG-ARDL) estimator, and robustness tests, such as the fully modified ordinary least square and dynamic ordinary least square tests, are employed. Empirical inferences are drawn using the Dumitrescu–Hurlin panel causality (DHC) test, and the long-run relationships among the variables are validated using the Westerlund residual cointegration tests. The results from the PMG-ARDL estimator show that renewable energy consumption, technological advancement, and export diversification have a significant and positive impact on economic expansion, confirming the validity of the endogenous growth model in the E-7 countries. The control variable of the financial sector has a positive but insignificant effect on economic growth, while trade openness has a negative and significant effect. The DHC test results indicate a neutral feedback effect of renewable energy consumption on economic growth. The findings also reveal a unidirectional causal relationship between technological innovation and economic growth. Overall, these findings provide valuable insights for economic policymakers in the E-7 countries. By removing barriers to renewable energy consumption, technological innovation, and export diversification, policymakers can promote sustainable economic development.

Development and Optimization of a Micro-Baffle for the Enhancement of Heat Transfer in Film Boiling

This study represents the development and optimization of a micro-baffle design to enhance heat transfer in film boiling. Numerical simulations are performed using an open-source computational fluid dynamics (CFD) model, which incorporates the Lee model for momentum source associated with the phase change, and the Volume of Fluid (VOF) method to capture bubble dynamics. A comparison of the numerical results with the previous numerical and experimental data confirmed the validity of the numerical model. The influence of key design parameters was systematically investigated. The results revealed that a vertical baffle provided the maximum performance. The optimal baffle design achieved a 57.4% improvement in the Nusselt number and a 66.4% increase in critical heat flux (CHF). Furthermore, the proposed design facilitated continuous bubble formation, even with a reduced temperature difference between the heated surface and the subcooled liquid, which is crucial for energy-efficient thermal management in engineering systems. Ultimately, this study demonstrates the potential of micro-baffle designs in controlling bubble dynamics and improving heat transfer in film boiling, thereby aiding the design of efficient thermal systems.

Parametric resonance brain model

The paper introduces a parametric resonance model for characterizing some features of the brain’s electrical activity. This activity is assumed to be a fundamental aspect of brain functionality underpinning functions from basic sensory processing to complex cognitive operations such as memory, reasoning, and emotion. A pivotal element of the proposed parametric model is neuron synchronization which is crucial for generating detectable brain waves. The analysis of the frequency content of brain waves, categorized as delta (0÷4 Hz), theta (4÷7 Hz), alpha (8÷12 Hz), beta (13÷30 Hz), and gamma (30÷100 Hz) reveals, notably, that the mean frequency of each of these brain wave classes is, in sequence, approximately the double of that of the previous one. Based on this observation, the proposed parametric resonance model suggests a cascade of amplification effects. Following the proposed model, in the transition from wakefulness to sleep, the brain wave bands are energized at double frequency by higher frequency neighboring bands; on the contrary, in the sleep to awake transition, brain waves are energized at a half frequency by their lower frequency neighbor waves. Finally, the trend of increasing amplitude values from higher to lower frequencies lends empirical support to the parametric resonant brain model validity.

Study on the Effect of Cracks in Diaphragm Couplings on the Dynamic Characteristics of Shaft System

Diaphragm couplings are prone to developing diaphragm cracks under prolonged high-speed operating conditions, which can lead to degradation in the performance of the transmission system and affect the dynamics of the shafting system. To investigate the effects of diaphragm cracks on the dynamics of couplings and the shafting system, a finite element model of a diaphragm coupling with a crack failure is established using ANSYS finite element software to analyze the time-varying characteristics of the diaphragm coupling’s angular and radial stiffness. A shaft dynamics model of the diaphragm coupling with a crack is developed using Timoshenko beam elements to analyze the impact of different crack lengths and locations on the dynamics of the shafting system. The validity of the dynamic model for a diaphragm coupling with a crack is verified through a constant speed experiment conducted on a rotor test bench. The results indicate that diaphragm crack failure causes a change in the periodicity of the time-varying stiffness of the diaphragm coupling, leading to a distinct 2× component appearing in the frequency domain of the transmission shaft system.

Lattice Boltzmann modeling of forced imbibition dynamics in dual-wetted porous media

Forced imbibition dynamics are critical for enhancing recovery rates in reservoirs, as efficient fluid displacement directly impacts resource extraction. This study employs the Zou-He velocity boundary condition and a modified convective boundary condition (mCBC) within the multi-component Shan-Chen lattice Boltzmann method (LBM), thus facilitating unobstructed flow of multi-component fluids at the outlet while maintaining constant outlet pressure. The model's validity was established through outflow tests of immiscible droplets in channels. Its accuracy was further confirmed by comparing results from forced imbibition dynamics tests in dual-wetted pores with theoretical predictions. A symmetrical porous medium was constructed using the stacking method, achieving dual wettability by fixing the contact angle in the upper region and varying it in the lower region. We performed 20 simulation sets under unfavorable viscosity ratios and varying capillary numbers, focusing on overall displacement efficiency before and after breakthrough, and employing energy balance equations to evaluate the dominant forces. Results reveal that capillary forces predominantly dictate forced imbibition dynamics in low capillary number scenarios. In strongly wetted regions, the invading fluid fully occupies pore spaces; however, in weakly wetted regions, displacement efficiency significantly declines as wettability approaches neutrality, even nearing zero. As capillary numbers increase, viscous forces become more prominent, controlling dynamics and leading to fingering and trapping of defending fluids. In weakly wetted areas, the increasing influence of viscous forces enhances fluid displacement, resulting in significant improvements in overall displacement efficiency compared to conditions dominated by capillary forces.

Deep Learning-Based Reconstruction of 3D Morphology of Geomaterial Particles from Single-View 2D Images.

The morphology of particles formed in different environments contains critical information. Thus, the rapid and effective reconstruction of their three-dimensional (3D) morphology is crucial. This study reconstructs the 3D morphology from two-dimensional (2D) images of particles using artificial intelligence (AI). More than 100,000 particles were sampled from three sources: naturally formed particles (desert sand), manufactured particles (lunar soil simulant), and numerically generated digital particles. A deep learning approach based on a voxel representation of the morphology and multi-dimensional convolutional neural networks was proposed to rapidly upscale and reconstruct particle morphology. The trained model was tested using the three particle types and evaluated using different multi-scale morphological descriptors. The results demonstrated that the statistical properties of the morphological descriptors were consistent for the real 3D particles and those derived from the 2D images and the model. This finding confirms the model's validity and generalizability in upscaling and reconstructing diverse particle samples. This study provides a method for generating 3D numerical representations of geological particles, facilitating in-depth analysis of properties, such as mechanical behavior and transport characteristics, from 2D images.

To Sustainably Ride or Not to Ride: Examining the Green Consumption Intention of Ride-Hailing Services in the Sharing Economy by University Students

An increase in ride-hailing services in the sharing economy can help to reduce the number of vehicles on the road, which will lead to a decrease in air pollution and noise pollution, an improvement in environmental conditions, a decrease in travel costs, and an increase in social benefits to travelers. Hence, there is a great need to examine the consumer’s intention toward usage of ride-hailing services in the sharing economy. The current study aims to examine the green consumption intention of eco-friendly services as an outcome of environmental responsibility and environmental knowledge. It also attempts to examine the serial mediation of green concern, value co-creation, and mediated moderation of social support as an explanatory mechanism of green consumption intention of eco-friendly services. The research design was cross-section and deductive. The respondents of the study were registered university students in Islamabad who were active consumers of major ride-hailing services in Pakistan, i.e., Uber, Careem, Uplift, InDriver, B4U Cabes, and SUVL. A total of 402 responses were gathered using purposive sampling. Partial Least Squares Structural Equation Modeling (PLS-SEM) in Smart PLS is used to evaluate the reliability of measurement instruments and the validity of the research model. The current study results showed that environmental responsibility and knowledge positively and significantly affect motivation to engage in green consumption. Furthermore, environmental concern and value co-creation partially mediate the proposed relationship. In addition, social support also moderates the association between green concern and value co-creation such that it strengthens the connection. The current research findings are an addition to the existing literature and have managerial applications with limitations preceded by future research directions.

Imaging Glucose Metabolism and Dopaminergic Dysfunction in Sheep (Ovis aries) Brain Using Positron Emission Tomography Imaging Reveals Abnormalities in OVT73 Huntington's Disease Sheep.

Huntington's disease (HD) is a neurodegenerative disease that causes cognitive, movement, behavioral, and sleep disturbances, which over time result in progressive disability and eventually death. Clinical translation of novel therapeutics and imaging probes could be accelerated by additional testing in well-characterized large animal models of HD. The major goal of our preliminary cross-sectional study is to demonstrate the feasibility and utility of the unique transgenic sheep model of HD (OVT73) in positron emission tomography (PET) imaging. PET imaging studies were performed in healthy merino sheep (6 year old, n = 3) and OVT73 HD sheep (5.5 year old, n = 3, and 11 year old, n = 3). Region-of-interest and brain atlas labels were defined for regional analyses by using a sheep brain template. [18F]fluorodeoxyglucose ([18F]FDG) was employed to compare the regional brain glucose metabolism and variations in FDG uptake between control and HD sheep. We also used [18F]fluoro-3,4-dihydroxyphenylalanine ([18F]FDOPA) to compare the extent of striatal dysfunction and evaluated the binding potential (BPND) in key brain regions between the groups. Compared with healthy controls and 11 year old HD sheep, the 5.5 year old HD sheep exhibited significantly increased [18F]FDG uptake in several cortical and subcortical brain regions (P < 0.05-0.01). No difference in [18F]FDG uptake was observed between healthy controls and 11 year old HD sheep. Analysis of the [18F]FDOPA BPND parametric maps revealed clusters of reduced binding potential in the 5.5 year old and 11 year old HD sheep compared to the 6 year old control sheep. In this first-of-its-kind study, we showed the usefulness and validity of HD sheep model in imaging cerebral glucose metabolism and dopamine uptake using PET imaging. The identification of discrete patterns of metabolic abnormality using [18F]FDG and decline of [18F]FDOPA uptake may provide a useful means of quantifying early HD-related changes in these models, particularly in the transition from presymptomatic to early symptomatic phases of HD.

The dark side of brand community: the role of brand identification, community identification, brand passion and shopping motivation

PurposeThis paper aims to investigate whether consumers’ identification with a brand community makes them more likely to engage in compulsive buying behavior. Specifically, this research shows that consumers are more likely to experience obsessive passion for brands they identify with if they are also part of brand communities, which, in turn, makes them more likely to engage in compulsive buying behavior.Design/methodology/approachAn online survey (n = 533) among members of the Adorable Representative M.C. for Youth (ARMY) Bangtan Boys (BTS) brand community was conducted. A partial least squares approach was employed to test the validity and reliability of the measurement model as well as to assess the structural equation model.FindingsResults show that brand identification affects harmonious and obsessive passion and that both relationships are moderated by brand community identification. Harmonious passion, in turn, has a positive effect on impulsive buying, whereas obsessive passion has a positive effect on both impulsive and obsessive-compulsive buying. Furthermore, consumer hedonic motivations moderate the relationship between (i) harmonious passion and impulsive buying and (ii) obsessive passion and obsessive-compulsive buying.Originality/valueTo the best of the authors’ knowledge, this work is the first to examine the potential negative impacts brand community identification has on compulsive buying behavior. Besides contributing to research on the negative aspects of brand community identification, by employing a model that distinguishes between two types of passion and compulsive buying, the study provides clarification on relationships suggested by prior studies.

Estimating the individual stillborn rate from easy-to-collect sow data on farm: an application of the bayesian network model

BackgroundA high number of stillborn piglets has a negative impact on production and animal welfare. It is an important contributor to piglet mortality around farrowing and continues to rise with the increase of prolificacy. The objective of this study was to build a predictive model of the stillborn rate.ResultsThis study was performed on two farrow-to-finish farms and one farrow-to-wean farm located in Brittany, France. At each farm, the number of total born (TB), born alive (BA), stillborn piglets (S), the same data at the previous farrowing (TBn− 1, BAn− 1 and Sn− 1), backfat thickness just before farrowing and at previous weaning and parity rank were recorded in our dataset of 3686 farrowings. Bayesian networks were used as an integrated modelling approach to investigate risk factors associated with stillbirth using BayesiaLab® software. Our results suggest the validity of a hybrid model to predict the percentage of stillborn piglets. Three significant risk factors were identified by the model: parity rank (percentage of total mutual information: MI = 64%), Sn− 1 (MI = 25%) and TBn− 1 (MI = 11%). Additionally, backfat thickness just before farrowing was also identified for sows of parity five or more (MI = 0.4%). In practice, under optimal conditions (i.e., low parity rank, less than 8% of stillborn piglets, and a prolificacy lower than 14 piglets at the previous farrowing), our model predicted a stillborn rate almost halved, from 6.5% (mean risk of our dataset) to 3.5% for a sow at the next farrowing. In contrast, in older sows with a backfat thickness less than 15 mm, more than 15% of stillborn and a prolificacy greater than 18 piglets at the previous farrowing, the risk is multiplied by 2.5 from 6.5 to 15.7%.ConclusionOur results highlight the impact of parity, previous prolificacy and stillborn rate on the probability of stillborn. Moreover, the importance of backfat thickness, especially in old sows, must be considered. This information can help farmers classify and manage sows according to their risk of giving birth to stillborn piglets.

Design of experiments optimization of N,N,N-trimethyl chitosan synthesis using N,N-diisopropylethylamine base

This study presents a novel synthesis method of N,N,N-trimethyl chitosan (TMC) by using a non-nucleophilic base and optimizing the solvent system for enhanced scalability, while addressing critical factors such as viscosity management and stirring efficiency. The study objectives also included achieving high N,N,N-trimethylation without O-methylation while minimizing reagent use. Eight bases, three solvent systems, and varying levels of dilution were explored to mitigate viscosity challenges and gas evolution. 1H NMR spectroscopy was used to characterize the TMC products. The integral values of the peaks at 3.3, 3.0, and 2.8 ppm, corresponding to trimethyl, dimethyl, and monomethyl groups, were used to quantify the methylation degrees. The most promising initial results were obtained with N,N-diisopropylethylamine (DIPEA) base, and DMF as solvent. Using 6 eq methyl iodide (MeI) relative to chitosan and DIPEA as base, up to 68 % DTM was achieved. Applying Design of Experiments (DoE), the method was further optimized under diluted conditions, crucial for industrial scalability and viscosity control. Results from a full factorial design (32) revealed that diluted medium effectively prevented viscosity concerns, achieving a notably low viscosity of 5.9 cP in the reaction mixture, a 16-fold decrease in viscosity, compared to initial experiments. It was also established that both the MeI reagent and the base addition are significant factors for the DTM response, with both factors showing quadratic effects. The DoE model demonstrated high significance (R = 0.97), high precision for future prediction (Q2 = 0.87), good model validity (0.84) and excellent reproducibility (0.96). The results mark a notable advancement in TMC synthesis, offering an efficient and practical method with significant implications for industrial applications.

Investigation the Influence of Job Satisfaction as a Mediating Factor in the Relationship Between Transformational Leadership, Knowledge, Knowledge Management, Work Environment and Employee Performance

Objective: This research aims to assess job satisfaction's mediating role between transformational leadership (TL), work environment (WE), knowledge management (KM) practices, and employee performance (EP) by investigating TL's and WE's impact on job satisfaction, and examining how job satisfaction mediates the relationships between TL, KM practices, and EP. Theoretical Framework: The theoretical framework examines key factors affecting employee performance and organizational success. It highlights task and contextual performance, environmental influences, and the role of performance appraisals. Effective human resource practices, knowledge management, and transformational leadership are essential for high performance. Job satisfaction, influenced by knowledge management and leadership, enhances organizational success. Method: This quantitative study investigates the relationships among transformational leadership (TL), work environment (WE), job satisfaction (JS), knowledge management (KM) practices, and employee performance (EP). Data from 411 Thai-speaking participants are analyzed using structural equation modeling (SEM). The study employs validated questionnaires, a 5-point Likert scale, and ADANCO software to assess model fit, reliability, and validity. Results: The sample predominantly comprised females (64.7%) and individuals with bachelor’s degrees (59.12%), with 31.87% employed in companies and 41.12% earning between 30,001 and 50,000 baht. Descriptive analysis revealed strong positive perceptions of KM, TL, WE, JS, and EP, with mean scores between 4.74 and 4.87, underscoring the focus on EP. Structural equation modeling (SEM) identified significant relationships between KM and JS (0.0277), TL and JS (0.0533), WE and JS (0.1720), and JS and EP (0.4721). JS emerged as a key mediator between KM, TL, and WE, accounting for substantial variance in both JS and EP, reflected by R² values of 0.0385 and 0.3283. Although the KM-JS and TL-JS relationships were relatively weak, JS significantly influenced EP. The study advocates for enhancing KM, TL, and WE to improve JS and EP, while recommending future research to investigate moderating factors, longitudinal designs, and cross-cultural contexts. Research Implications: The study reveals critical insights into job satisfaction (JS) as a mediator between transformational leadership (TL), knowledge management (KM), work environment (WE), and employee performance (EP): TL significantly influences KM and WE, while effective KM enhances EP. JS mediates the positive effects of TL, KM, and WE on EP, though moderate correlations suggest other influencing factors. The research emphasizes contextual nuances within Thai organizations, underscoring the complexity of these relationships and the need for further investigation to fully understand their organizational implications. Originality/Value: This study offers innovative insights into the interactions among Knowledge Management (KM), Transformational Leadership (TL), Work Environment (WE), Job Satisfaction (JS), and Employee Performance (EP) in Thai organizations. It identifies JS as a key mediator in the effects of KM, TL, and WE on EP, deepening the understanding of organizational dynamics. Moderate correlations between KM and JS, and TL and JS, suggest additional moderating factors. The pivotal role of JS in determining EP emphasizes the need for organizations to enhance JS to improve performance. The study's focus on Thai organizations highlights cultural and contextual influences, bridging local practices with broader theoretical frameworks. Further investigation is needed to fully understand these complex dynamics.

EFFECTS OF DISAGGREGATED TAX REVENUES ON ECONOMIC GROWTH IN NIGERIA (1995-2023): ARDL BOUND TEST APPROACH

&lt;p&gt;Tax revenue has been a great tool of fiscal policy harnessed toward the economic development of a nation. Its different components have collective effects on the economic growth of a nation. This study examined the effects of disaggregated tax revenue on Nigeria's economic growth from 1995 to 2023. The data was sourced from the Central Bank of Nigeria and the Federal Inland Revenue Service databases. This study examined the effects of disaggregated tax revenue on Nigeria's economic growth from 1995 to 2023. The data was sourced from the Central Bank of Nigeria and the Federal Inland Revenue Service databases. Employing multiple regression analysis within an Autoregressive Distributed Lag (ARDL) model, the study assessed the impact of Value Added Tax (VAT), Companies Income Tax (CIT), Petroleum Profit Tax (PPT) and Personal Income Tax (PIT) on economic growth. The diagnostic tests confirmed the model's validity, with unit root tests showing that all variables, except PIT, achieved stationarity after differencing. The findings revealed that each tax revenue component positively influences economic growth. Based on these results, the study recommends enhancing the legal and regulatory frameworks for businesses, including regular evaluations and updates of tax laws and stronger enforcement mechanisms. It also underscores the need to strengthen anti-corruption efforts, promote property rights, uphold the rule of law, and prioritise good governance to foster public confidence and ensure the effective use of tax revenues for economic development.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;JEL: &lt;/strong&gt;C32, H20, H24, H25&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0785/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Deerminants of watchdog journalism: A global empirical approach

This article introduces and examines a hierarchical model of influences that identifies the variables affecting the watchdog role of journalists at three levels: the societal (press freedom and democracy), the organizational (media ownership), and the individual (editorial autonomy and perceived influences) on a global scale. Using data from 27,567 journalists in 6403 media organizations across 67 countries, the model's validity is confirmed. The findings reveal that variations in journalists’ perception of their role are more pronounced at the societal level compared to the organizational and individual levels. Furthermore, journalists tend to assume a watchdog role more prominently within public media as opposed to private or state-run outlets. Surprisingly, press freedom and democracy have a weak and insignificant impact on watchdog journalism, challenging established norms in the literature, a result that we critically discussed.

Caries Detection and Classification in Photographs Using an Artificial Intelligence-Based Model-An External Validation Study.

This ex vivo diagnostic study aimed to externally validate a freely accessible AI-based model for caries detection, classification, localisation and segmentation using an independent image dataset. It was hypothesised that there would be no difference in diagnostic performance compared to previously published internal validation data. For the independent dataset, 718 dental images representing different stages of carious (n = 535) and noncarious teeth (n = 183) were retrieved from the internet. All photographs were evaluated by the dental team (reference standard) and the AI-based model (test method). Diagnostic performance was statistically determined using cross-tabulations to calculate accuracy (ACC), sensitivity (SE), specificity (SP) and area under the curve (AUC). An overall ACC of 92.0% was achieved for caries detection, with an ACC of 85.5-95.6%, SE of 42.9-93.3%, SP of 82.1-99.4% and AUC of 0.702-0.909 for the classification of caries. Furthermore, 97.0% of the cases were accurately localised. Fully and partially correct segmentation was achieved in 52.9% and 44.1% of the cases, respectively. The validated AI-based model showed promising diagnostic performance in detecting and classifying caries using an independent image dataset. Future studies are needed to investigate the validity, reliability and practicability of AI-based models using dental photographs from different image sources and/or patient groups.

European vulnerable options pricing under sub-mixed fractional jump-diffusion model with stochastic interest rate

With the development of financial markets, the trading of financial derivatives has become more flexible. To meet the demands of investors, over-the-counter (OTC) trading of options has also become increasingly frequent, raising concerns about accurately pricing vulnerable options. This study investigates the pricing problem of European vulnerable options under the sub-mixed fractional jump-diffusion (SMFJ) model. Firstly, the underlying asset price model and the counterparty company value model are established under the SMFJ model with a sub-mixed fractional Vasicek stochastic interest rate. Then, analytical solutions for the European vulnerable options are obtained using the quasi-martingale measure transformation and the risk-neutral pricing method. Additionally, the accuracy of the pricing formula is verified through the Monte Carlo simulation method. Finally, the rationality and validity of the established model are confirmed by numerical simulations, and the influence of key parameters on the pricing models is analyzed.

Does the direct effect of friction increase continuously with absolute temperature?

Constitutive models of fault friction form the basis of physics-based simulations of seismic activity. A generally accepted framework for the slip-rate and state dependence of friction involves a thermally activated process, whereby the probability of slip along microasperities adheres to an Arrhenius law. This model, which has become widely adopted among experimentalists and theoreticians, predicts a continuous increase of the direct effect with absolute temperature, but is it observed experimentally? Leveraging comprehensive laboratory data across diverse hydrothermal, barometric, and lithological conditions, we demonstrate that, contrary to the classical view, the direct effect for a given deformation mechanism remains largely temperature-independent. Instead, the incremental shifts in the direct effect often coincide with the brittle to semi-brittle transition, across which distinct deformation mechanisms operate. These considerations challenge the validity of the classical model. Realistic constitutive laws for rock failure within the lithosphere must incorporate the contributions of multiple deformation mechanisms within active fault zones.

Research on the Alternative Model for Personality Disorders (AMPD) in Iran: A Narrative Literature Review

Background: Many original studies have evaluated the validity and utility of the Alternative Model for Personality Disorders (AMPD) in Iran. However, the present review is a unique attempt to summarize the data in a critical framework to cover gaps in the AMPD research and determine future directions. The review aimed to explore the psychometric evidence for the AMPD, including reliability (alpha coefficient) and validity (construct, convergent, criterion, and incremental types) data in Iran. We also reviewed the overlap between the two AMPD criteria and the associations between the constructs and general psychopathology. Methods: We searched PubMed, PsycNet, Google Scholar, and three national databases for English and Persian records related to the AMPD from January 2013 to 2023. Several keywords and criteria were applied to select studies before summarizing the data. Results: The self-report scales were the first-line measures to assess the AMPD constructs, while interviews were rarely used. The research body provided relative support for both the unidimensional nature of Criterion A measures and the five-factor structure of Criterion B measures. Regarding Criterion B, however, there are still questions about the validity of the disinhibition factor and its clinical utility and generalizability. Conclusion: Although a decade of research on the AMPD in Iran has contributed to improving our knowledge, the current review provided a more comprehensive and clear profile of this model’s validity and generalizability to Iranian culture. We discussed the details of validation studies, limitations, and future considerations.