Rigorous Equations Research Articles

Perception and Trust in Autonomous Vehicles Post Cyber Security Incidents

The integration of Autonomous Vehicles (AVs) into modern systems of transportation brings with it a new and transformative era. Central to the successful realisation of this transformation is the public’s trust in these vehicles and their safety, particularly in the aftermath of cyber security breaches. The following research therefore explores the various factors underpinning this trust in the context of cyber security incidents. A dual-methodological approach was used in the study. Quantitative data was gathered from structured questionnaires distributed to and completed by a cohort of 151 participants and qualitative data, from comprehensive semi-structured interviews with AV technology and cyber security experts. Rigorous Structural Equation Modelling of the quantitative data then allowed for the identification of the key factors influencing public trust from the standpoint of the research participants including the perceived safety of AV technology, the severity of cyber security incidents, the historic cyber security track record of companies and the frequency of successful cyber security breaches. The role of government regulations, though also influential, emerged as less so. The qualitative data, processed via thematic analysis, resonated with the findings from the quantitative data. This highlighted the importance of perceived safety, incident severity, regulatory frameworks and corporate legacy in shaping public trust. Whilst cyber incidents no doubt erode trust in AVs, a combination of technological perception, regulatory scaffolding and corporate history critically impacts this. These insights are instrumental for stakeholders, from policymakers to AV manufacturers, in charting the course of AV assimilation successfully in future.

Probabilistic assessments of running ductile fractures in dense-phase and supercritical CO2 pipelines

Running ductile fracture (RDF) is a severe failure mode of high-pressure pipelines. Dense-phase and supercritical CO2 pipelines are particularly susceptible to RDF due to the unique characteristics of the depressurization process resulting from a fracture of the pipeline. The present study carries out probabilistic analyses of RDF in dense-phase and supercritical CO2 pipelines. The well-known Battelle two-curve method is employed to establish the limit state function for RDF by comparing the arrest pressure with the saturation pressure. The arrest pressure is computed using the Battelle through-wall crack model with the adjustment recently proposed in the literature. The saturation pressure is computed based on the one-dimensional isentropic decompression assumption and a rigorous equation of state. The first-order reliability method is employed to evaluate the probabilities of RDF in hypothetical CO2 pipelines designed per DVN-RP-F104 with representative pipe attributes and initial operating conditions by considering uncertainties in the relevant pipe geometric and material properties. The analysis results indicate that the probability of RDF can vary by several orders of magnitude depending on the pipe attributes and initial operating conditions. Furthermore, the results shed light on the key uncertainties associated with the pipe geometric and material properties that influence the probability of RDF.

Recruitment chatbot acceptance in a company: a mixed method study on human-centered technology acceptance model

This study developed a Human-Centered Technology Acceptance Model (HC-TAM) for recruitment chatbots, integrating aspects of the traditional Technology Acceptance Model (TAM)(Davis in 1989) with a focus on human-centered factors such as transparency, personalization, efficiency, and ethical concerns, alongside the fundamental TAM constructs of perceived ease of use and perceived usefulness. The study shows that the intention to use technology is influenced by their perceptions of its usefulness and ease of use. By extending TAM to include human-centered considerations, this research aimed to capture the diverse factors that significantly influence users’ acceptance of chatbots in the recruitment process. A three-phase study has been carried out, each serving a distinct purpose. (a) Phase 1 focuses on defining primary themes through qualitative interviews with 10 participants, laying the foundation for subsequent research. (b)Building upon this foundation, Phase 2 engages 28 participants in a refined exploration of these themes, ending in a comprehensive landscape of user perspectives. (c) Finally, Phase 3 employs rigorous Structural Equation Modeling for theoretical framework examination, yielding critical constructs and hypotheses. Moreover, Phase 3 encompasses the thorough development of measurement instruments and extensive data collection, involving 146 participants through questionnaires, the study found that the acceptance of recruitment chatbots is significantly enhanced when these systems are designed to be transparent, provide personalized interactions, efficiently fulfill user needs, and address ethical concerns. These findings contribute to the broader understanding of technology acceptance in the context of recruitment, offering valuable insights for developers and designers to create chatbots that are not only technically advanced but also ethically sound, user-friendly, and effectively aligned with human needs and expectations in recruitment settings.

Scattering integral equation formulation for intravascular inclusion biosensing

A dielectric waveguide, inserted into blood vessels, supports its basic mode that is being scattered by a near-field intravascular inclusion. A rigorous integral equation formulation is performed and the electromagnetic response from that inhomogeneity is semi-analytically evaluated. The detectability of the formation, based on spatial distribution of the recorded signal, is estimated by considering various inclusion sizes, locations and textural contrasts. The proposed technique, with its variants and generalizations, provides a generic versatile toolbox to efficiently model biosensor layouts involved in healthcare monitoring and disease screening.

Conservation equations for open-channel flow: effects of bed roughness and secondary currents

AbstractTime-averaged velocity fields in uniform open-channel flows over rough beds may exhibit spatial heterogeneities due to the effects of bed roughness and secondary currents (SCs). The latter typically originate from the turbulence anisotropy and spatial heterogeneity introduced by the solid and mixed corners (i.e., between sidewalls and water surface), but may also appear due to roughness spanwise heterogeneities, e.g., associated with patchy vegetation distributions or streamwise sediment ridges on the channel bed. In this paper, we propose rigorous conservation equations for momentum, kinetic energy and fluid stresses accounting for the contributions of bed roughness and SCs, separately. Particular attention is given to the terms regulating the energy exchanges between roughness-induced and SC-related motions, which are expected to provide information on the physical mechanisms leading to the generation of roughness-induced SCs. The proposed approach is illustrated using a large-eddy simulation of a rough-bed open-channel flow.

The impact of honors education on students’ academic and innovative achievements: a longitudinal study in China (2011–2021)

Honors education has ascended as an integral element within the sphere of global higher education, concentrating on fostering individuals who exhibit creativity and a history of innovative achievements. Despite its widespread adoption, there remains a scarcity of exhaustive longitudinal studies investigating its effects and associated variables. To address this shortcoming, this study deploys rigorous structural equation modeling (SEM) and linear regression analyses to meticulously examine a dataset comprising 319 students, who enrolled over a decade (2011–2021) in a prestigious honors college at a preeminent university in China. The primary objective is to discern the predictive efficacy of Chinese honors education selection criteria on students’ creative and academic accomplishments. This endeavor strives to clarify the complex interplay among students’ creative personalities, academic performance, creative achievements, and standardized college entrance exam scores. The findings emphasize that individuals who exhibit enhanced creative personality traits are predisposed to elevated levels of both innovation and academic attainment (β = 0.170, p = 0.017). Additionally, a significant inverse relationship is observed between general learning aptitude and subsequent academic performance (β = −0.008, p = 0.023), while students pursuing science disciplines demonstrate superior innovation outcomes compared to their liberal arts counterparts (β = 0.125, p = 0.048). Interestingly, neither gender nor general academic prowess exerts significant predictive power over collegiate innovation (β = −0.002, p = 0.134). These empirical insights equip policymakers and scholars with nuanced perspectives on the determinants shaping students’ refined educational experiences, thereby inciting critical discourse concerning the refinement of selection criteria and the imperative of nurturing students’ creative proclivities.

Fluid Focusing Contributes to the BM Vibration Amplification by Boosting the Pressure.

Two hydrodynamic effects are introduced in the standard transmission-line formalism, the focusing of the pressure and fluid velocity fields near the basilar membrane and the viscous damping at the fluid-basilar membrane interface, which significantly affect the cochlear response in the short-wave region. In this region, in which the wavelength is shorter than the cochlear duct height, only a layer of fluid of order of the wavelength is effectively involved in the traveling wave. This has been interpreted [8] as a reduced fluid contribution to the system inertia in the peak region, which is a viewpoint common to the 3-D FEM solutions. In this paper we propose an alternative approach, from a slightly different physical viewpoint. Invoking the fluid flux conservation along the traveling wave propagation direction, we can derive a rigorous propagation equation for the pressure integrated along the vertical axis. Consequently, the relation between the average pressure and the local pressure [4] at the fluid-BM interface can be written. The local pressure is amplified by a factor dependent on the local wavenumber with respect to the average pressure, a phenomenon we refer to as "fluid focusing", which plays a relevant role in the BM total amplification gain. This interpretation of the hydrodynamic boost to the pressure provides a physical justification to the strategy [10] of fitting the BM admittance with a polynomial containing both a conjugated pole and a zero. In the short-wave region, the sharp gradients of the velocity field yield a second important effect, a damping force on the BM motion, proportional to the local wavenumber, which stabilizes active models and shifts the peak of the response towards the base, with respect to the resonant place. This way, the peaked BM response is not that of a proper resonance, corresponding to a sharp maximum of the admittance, but rather a focusing-driven growth toward the resonant place, which is "aborted" before reaching it by the sharply increasing viscous losses. The large values of the wavenumber that ensure strong focusing are ultimately fueled, against viscosity, by the nonlinear OHC mechanism, hence the otherwise puzzling observation of a wide nonlinear gain dynamics with almost level-independent admittance.

Promoting Road Safety for Sustainable Communities: Analysing Driving Anger, Aggressive Driving, and Road Accident Proneness with Partial Least Squares Structural Equation Modelling (PLS-SEM) Approach

Objective: Numerous studies have emphasized the web of factors contributing to a driver’s vulnerability to road accidents. These factors often stem from the interaction between drivers’ conduct, environmental conditions, and vehicle-related aspects. Among these elements, road rage and aggressive driving behavior are particularly noteworthy for their roles in road accidents. In this article, we delve into the connection between road rage, aggressive driving, and their combined impact on the likelihood of road accidents among Malaysian drivers. Theoretical framework: Theoretical materials were based on international scientific publications, reports, and scientific papers. Empirical findings from previous studies were critically reviewed for a more complete and objective presentation of the road accident problem. Methodology: This study used a cross-sectional design to administer self-administered questionnaires to drivers. The survey method made it possible to study the factors influencing susceptibility to traffic accidents quantitatively. The analysis reveals compelling insights using a rigorous structural equation modeling approach. Results and Conclusion: Driving anger and aggressive driving significantly influence the likelihood of road accidents among Malaysian drivers. This study holds significant implications for theoretical understanding and practical intervention strategies to reduce road accident proneness within the Malaysian road user community. The findings provide valuable insights and recommendations to enhance road safety, ultimately contributing to the sustainability of communities through reduced road accidents. Originality/value: The originality and value of the study lie in its in-depth examination of the relationship between driving anger, aggressive driving, and the likelihood of road accidents among Malaysian drivers. It goes beyond existing research by employing a rigorous structural equation modelling approach, drawing from international scientific publications and empirical findings. This comprehensive approach offers fresh insights into the specific context of Malaysia and provides a foundation for practical interventions to reduce road accident proneness, contributing to community sustainability and road safety.

Surrogate Modelling of an Industrial Distillation Column Obtained from Statistical Techniques and Machine Learning

Purpose: To study a case of modeling an industrial distillation system, using the Aspen Plus simulator as the mathematical model and subsequently generating surrogate models using Machine Learning techniques in Matlab. Theoretical Framework: Metamodels are reduced models obtained from data generated by rigorous models, replacing them entirely or partially when the computational codes originating from them require excessively large computational effort to be used feasibly. Method/Design/Approach: The simulation of the process was performed in Aspen Plus. Subsequently, the most important variables were selected, and an experimental design was created using Latin Hypercube Sampling in Matlab, generating points to be used in sensitivity analysis in Aspen Plus. The next step was the construction of metamodels using the Statistics and Machine Learning toolbox in Matlab, employing linear regression and Gaussian process regression models. Finally, a statistical analysis was conducted. Results and Conclusion: The distillation system simulation converged, and the obtained metamodels had good regression indicators, especially the Gaussian process regression models, making them the most suitable for representing the rigorous Aspen Plus model. Research Implications: Understanding the multicomponent distillation process integrated with computational tools and data regression models, leading to a reduction in computational effort. Originality/Value: Development of a tool that enables the simulation and evaluation of a distillation process without the need to acquire software with rigorous equation databases.

Generative design approach to combine architected Voronoi foams with porous collagen scaffolds to create a tunable composite biomaterial

Regenerative biomaterials for musculoskeletal defects must address multi-scale mechanical challenges. Repairing craniomaxillofacial bone defects, which are often large and irregularly shaped, requires close conformal contact between implant and defect margins to aid healing. While mineralized collagen scaffolds can promote mesenchymal stem cell osteogenic differentiation in vitro and bone formation in vivo, their mechanical performance is insufficient for surgical translation. We report a generative design approach to create scaffold-mesh composites by embedding a macro-scale polymeric Voronoi mesh into the mineralized collagen scaffold. The mechanics of architected foam reinforced composites are defined by a rigorous predictive moduli equation. We show biphasic composites localize strain during loading. Further, planar and 3D mesh-scaffold composites can be rapidly shaped to aid conformal fitting. Voronoi-based composites overcome traditional porosity-mechanics relationship limits while enabling rapid shaping of regenerative implants to conformally fit complex defects unique for individual patients. Statement of SignificanceBiomaterial strategies for (craniomaxillofacial) bone regeneration are often limited by the size and complex geometry of the defects. Voronoi structures are open-cell foams with tunable mechanical properties which have primarily been used computationally. We describe generative design strategies to create Voronoi foams via 3D-printing then embed them into an osteogenic mineralized collagen scaffold to form a multi-scale composite biomaterial. Voronoi structures have predictable and tailorable moduli, permit stain localization to defined regions of the composite, and permit conformal fitting to effect margins to aid surgical practicality and improve host-biomaterial interactions. Multi-scale composites based on Voronoi foams represent an adaptable design approach to address significant challenges to large-scale bone repair.

Graph-based approximate message passing iterations

Abstract Approximate message passing (AMP) algorithms have become an important element of high-dimensional statistical inference, mostly due to their adaptability and concentration properties, the state evolution (SE) equations. This is demonstrated by the growing number of new iterations proposed for increasingly complex problems, ranging from multi-layer inference to low-rank matrix estimation with elaborate priors. In this paper, we address the following questions: is there a structure underlying all AMP iterations that unifies them in a common framework? Can we use such a structure to give a modular proof of state evolution equations, adaptable to new AMP iterations without reproducing each time the full argument? We propose an answer to both questions, showing that AMP instances can be generically indexed by an oriented graph. This enables to give a unified interpretation of these iterations, independent from the problem they solve, and a way of composing them arbitrarily. We then show that all AMP iterations indexed by such a graph verify rigorous SE equations, extending the reach of previous proofs and proving a number of recent heuristic derivations of those equations. Our proof naturally includes non-separable functions and we show how existing refinements, such as spatial coupling or matrix-valued variables, can be combined with our framework.

Ab initio model of choice for kinetics of OH-addition to CF2=CFCl

This work presents a thorough resolution for significant differences (ranging from 7.3 to 23.2 times) between theoretical and experimental rate constants for the atmospheric OH-addition to CF2=CFCl, commonly used for manufacturing fluoropolymers, drugs, and fire extinguishers. To correctly describe its kinetic behaviors, it is crucial to use the energy profile calculated at an accurate method CCSD(T)/aug-cc-pVTZ//M06-2X/aug-cc-pVTZ, together with a rigorous stochastic RRKM-based master equation rate model. The model reveals that corrections from hindered rotation and tunneling treatments play a minor role, and CTFE is not a persistent organic pollutant due to its newly-calculated shorter lifetime with OH radicals.

Statistical mechanics of the GENERIC framework under external forcing.

The General Equation for Non-Equilibrium Reversible Irreversible Coupling (generic) framework provides a thermodynamically consistent approach to describe the evolution of coarse-grained variables. This framework states that Markovian dynamic equations governing the evolution of coarse-grained variables have a universal structure that ensures energy conservation (first law) and entropy increase (second law). However, the presence of external time-dependent forces can break the energy conservation law, requiring modifications to the framework's structure. To address this issue, we start from a rigorous and exact transport equation for the average of a set of coarse-grained variables derived from a projection operator technique in the presence of external forces. Under the Markovian approximation, this approach provides the statistical mechanics underpinning of the generic framework under external forcing conditions. By doing so, we can account for the effects of external forcing on the system's evolution while ensuring thermodynamic consistency.

Coherent two-dimensional THz magnetic resonance spectroscopies for molecular magnets: Analysis of Dzyaloshinskii-Moriya interaction.

To investigate the novel quantum dynamic behaviors of magnetic materials that arise from complex spin-spin interactions, it is necessary to probe the magnetic response at a speed greater than the spin-relaxation and dephasing processes. Recently developed two-dimensional (2D) terahertz magnetic resonance (THz-MR) spectroscopy techniques use the magnetic components of laser pulses, and this allows investigation of the details of the ultrafast dynamics of spin systems. For such investigations, quantum treatment-not only of the spin system itself but also of the environment surrounding the spin system-is important. In our method, based on the theory of multidimensional optical spectroscopy, we formulate nonlinear THz-MR spectra using an approach based on the numerically rigorous hierarchical equations of motion. We conduct numerical calculations of both linear (1D) and 2D THz-MR spectra for a linear chiral spin chain. The pitch and direction of chirality (clockwise or anticlockwise) are determined by the strength and signof the Dzyaloshinskii-Moriya interaction (DMI). We show that not only the strength but also the signof the DMI can be evaluated through the use of 2D THz-MR spectroscopic measurements, while 1D measurements allow us to determine only the strength.

Design and Characterization of a Close Compartment Hydrogen Reference Electrode for Electrocatalytic Studies

The reference electrode plays an important role in the determination of the electrocatalytic activity of a given electrode material. The hydrogen reference electrode has several advantages, as it is stable, can be used in the whole range of pH values, and does not contaminate the system. However, its use is not widespread due to certain difficulties related to its construction and operation. In this context, we report the design of a reversible hydrogen electrode (RHE) characterized by its simplicity, reproducibility, portability, stability, and precision. Moreover, rigorous equations for the variation of the RHE potential on the solution concentration, temperature, and pressure were derived as well as for the conversion of a working electrode potential referred to RHE to the standard hydrogen electrode (SHE).

Minimum-Lap-Time Planning of Multibody Vehicle Models via the Articulated-Body Algorithm

Minimum lap-time planning (MLTP) is a well-established problem in the race car industry to provide guidelines for drivers and optimize the vehicle’s setup. In this paper, we tackle the 3D nature of the problem in its full extension, making no simplifying assumptions on the mechanics of the system. We propose a multibody vehicle model, described by rigorous dynamical equations. To effectively handle the resulting complexity, we devised an efficient direct dynamics computational method based on Featherstone’s articulated-body algorithm (ABA). To solve the MLTP, we employed a direct-collocation technique, discretizing the problem so that all information of the 3D track is pre-processed and directly embedded into the discrete problem. This discretization approach turns out to be perfectly compatible with our vehicle model, leading to a solution in accessible computational time frames. The high level of detail of the model makes the proposed approach most useful for in-depth vehicle dynamics analyses on complex tracks. To substantiate the analysis, we provide a comparison with the results obtained by a double-track model on the Nürburgring Nordschleife circuit. Consistently with the average trend defined by the double track, the proposed model features a more dynamically rich behavior, realistically capturing the higher-order effects elicited by the sharp corners and the highly variable slope of the track.

Nonlocal optical potential with core excitation in [formula omitted] and [formula omitted] reactions

We propose a new nonlocal form of the nucleon-nucleus optical potential and demonstrate its reliability. We extend the nonlocal potential to include the excitation of the nuclear core and develop energy-independent proton-Be10 potential reasonably reproducing the experimental data at low energies. We apply the new potential to the study of deuteron stripping and pickup reactions Be10(d,p)11Be and Be11(p,d)10Be using rigorous three-body Faddeev-type equations for transition operators that are solved in the momentum-space partial-wave framework. The achieved description of the experimental data is considerably more successful as compared to previous studies with local potentials. The values of spectroscopic factors consistent with the data are determined, exhibiting only weak energy dependence. The results possibly indicate an increased predicting power of the proposed calculational scheme.

Quantification of interfacial interaction related with adhesive membrane fouling by genetic algorithm back propagation (GABP) neural network

Since adhesive membrane fouling is critically determined by the interfacial interaction between a foulant and a rough membrane surface, efficient quantification of the interfacial interaction is critically important for adhesive membrane fouling mitigation. As a current available method, the advanced extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory involves complicated rigorous thermodynamic equations and massive amounts of computation, restricting its application. To solve this problem, artificial intelligence (AI) visualization technology was used to analyze the existing literature, and the genetic algorithm back propagation (GABP) artificial neural network (ANN) was employed to simplify thermodynamic calculation. The results showed that GABP ANN with 5 neurons could obtain reliable prediction performance in seconds, versus several hours or even days time-consuming by the advanced XDLVO theory. Moreover, the regression coefficient (R) of GABP reached 0.9999, and the error between the prediction results and the simulation results was less than 0.01%, indicating feasibility of the GABP ANN technique for quantification of interfacial interaction related with adhesive membrane fouling. This work provided a novel strategy to efficiently optimize the thermodynamic prediction of adhesive membrane fouling, beneficial for better understanding and control of adhesive membrane fouling.

Quantitative Analysis of Nonequilibrium Phonon Transport Near a Nanoscale Hotspot

Understanding thermal transport by phonons near nanoscale hotspots is critical for many engineering applications, especially for nanoscale thermal measurements and nanoelectronics. Previous studies usually adopted the gray phonon Boltzmann transport equation to consider ballistic phonon transport or the multitemperature model to consider selective phonon excitation. However, nonequilibrium phonon transport near a nanoscale hotspot cannot be fully captured by either method. In this work, we employ the more rigorous nongray phonon Boltzmann transport equation to investigate phonon transport near nanoscale hotspots. We first consider hotspots in a one-dimensional system with two phonon modes to extract the underlying physics. Thermal transport is found to be less efficient near these hotspots, leading to significantly smaller effective thermal conductivity. The mechanism behind this is that different phonon modes have different temperatures and are therefore not in equilibrium. Nonequilibrium is caused by both the selective electron-phonon interaction and ballistic phonon transport. For relatively large hotspots, nonequilibrium is primarily contributed to by the selective excitation effect. When the hotspot size further reduces, the contribution from ballistic phonon transport becomes increasingly more important. Furthermore, we quantitatively study the thermal transport of laser-heated hotspots in Raman experiments and Joule heating in fin field-effect transistors (FETs) using the nongray phonon Boltzmann transport equation. We find that the measured thermal conductivity of single-layer graphene can be significantly underestimated if the nonequilibrium effect is ignored. Additionally, the peak temperature rise in a silicon fin FET is much larger than that calculated by the heat-diffusion equation.

FRACTAL CHARACTERIZATION ON THREE-DIMENSIONAL FRACTUR TORTUOSITY IN COAL BASED ON CT SCANNING

This paper proposed a method for the fractal characterization of the three-dimensional (3D) fracture tortuosity ([Formula: see text] in coal based on CT scanning experiment. The methodology was deduced in detail, and the values of [Formula: see text] of four coal samples were calculated by the rigorous derivation equation established by Feng and Yu. The values of [Formula: see text] by the proposed method fit the relation of [Formula: see text] versus the fractal dimension for 3D fracture number [Formula: see text], and the relation of [Formula: see text] versus the 3D fracture porosity, indicating the rationality and accuracy of the proposed method on estimation of the [Formula: see text]. The results show that the proposed [Formula: see text] can comprehensively character the fractal characteristics of fractures tortuosity in 3D space. It is worth to further study for establishing an analytical fractal equation for fluid mass transfer in 3D fractures of porous media based on the [Formula: see text].