Continuous Component Research Articles

High gain Bi-directional KY converter for low power EV applications

In electric vehicles (EVs), the type of electric motor and converter technology have a significant impact on regulating the operational characteristics of the vehicle. Therefore, in this work, the modified bi-directional KY converter (BKYC) is proposed for EV applications. The main contributions of the proposed converter are high step-up/step-down conversion gain, bi-directional power flow, simplified control structure, continuous current, common ground, low volume, and high efficiency. An inductor on either side of the converter ensures continuous current flow and passive components are arranged to operate in series to offer high step-up/step-down conversion. The charging and discharging operations, steady-state analysis, and design process of the proposed converter are discussed in detail and compared with similar bi-directional converter topologies. Further, the efficiency analysis of the proposed converter is presented and found that the efficacy of 95.51 % in charging operation and 96.52 % in discharging operation of operation. The simulations are carried out using MATLAB/Simulink environment. Further, a prototype of a modified bi-directional KY converter is implemented with a TMS320F28335 processor and validated with theoretical and simulation counterparts.

Adaptive Integral Sliding Mode Control with Chattering Elimination Considering the Actuator Faults and External Disturbances for Trajectory Tracking of 4Y Octocopter Aircraft

This paper presents a control strategy for a 4Y octocopter aircraft that is influenced by multiple actuator faults and external disturbances. The approach relies on a disturbance observer, adaptive type-2 fuzzy sliding mode control scheme, and type-1 fuzzy inference system. The proposed control approach is distinct from other tactics for controlling unmanned aerial vehicles because it can simultaneously compensate for actuator faults and external disturbances. The suggested control technique incorporates adaptive control parameters in both continuous and discontinuous control components. This enables the production of appropriate control signals to manage actuator faults and parametric uncertainties without relying only on the robust discontinuous control approach of sliding mode control. Additionally, a type-1 fuzzy logic system is used to build a fuzzy hitting control law to eliminate the occurrence of chattering phenomena on the integral sliding mode control. In addition, in order to keep the discontinuous control gain in sliding mode control at a small value, a nonlinear disturbance observer is constructed and integrated to mitigate the influence of external disturbances. Moreover, stability analysis of the proposed control method using Lyapunov theory showcases its potential to uphold system tracking performance and minimize tracking errors under specified conditions. The simulation results demonstrate that the proposed control strategy can significantly reduce the chattering effect and provide accurate trajectory tracking in the presence of actuator faults. Furthermore, the efficacy of the recommended control strategy is shown by comparative simulation results of 4Y octocopter under different failing and uncertain settings.

Profiling patterns of patient experiences of access and continuity at team-based primary healthcare clinics (Canada): a latent class analysis

BackgroundAccess to primary healthcare services is a core lever for reducing health inequalities. Population groups living with certain individual social characteristics are disproportionately more likely to experience barriers accessing care. This study identified profiles of access and continuity experiences of patients registered with a family physician working in team-based primary healthcare clinics and explored the associations of these profiles with individual and organizational characteristics.MethodsA cross-sectional e-survey was conducted between September 2022 and April 2023. All registered adult patients with an email address at 104 team-based primary healthcare clinics in Quebec were invited to participate. Latent class analysis was used to identify patient profiles based on nine components of access to care and continuity experiences. Multinomial logistic regression models were fit to analyze each profile’s association with ten characteristics related to individual sociodemographics, perceived heath status, chronic conditions and two related to clinic area and size.ResultsBased on 87,155 patients who reported on their experience, four profiles were identified. “Easy access and continuity” (42% of respondents) was characterized by ease in almost all access and continuity components. Three profiles were characterized by diverging access and/or continuity difficulties. “Challenging booking” (32%) was characterized by patients having to try several times to obtain an appointment at their clinic. “Challenging continuity” (9%) was characterized by patients having to repeat information that should have been in their file. “Access and continuity barriers” (16%) was characterized by difficulties with all access and continuity components. Female gender and poor perceived health significantly increased the risk of belonging to the three profiles associated with difficulties by 1.5. Being a recently arrived immigrant (p = 0.036), having less than a high school education (p = 0.002) and being registered at a large clinic (p < 0.001) were associated with experiencing booking difficulties. Having at least one chronic condition (p = 0.004) or poor perceived mental health (p = 0.048) were associated with experiencing continuity difficulties.ConclusionsThese results highlight individual social and health characteristics associated with increased risk of experiencing healthcare access difficulties, such as immigration status and education level and/or continuity difficulties when having a chronic condition and poor perceived mental health. Facilitating appointment booking for recently arrived immigrants and patients with low education, integrating interprofessional collaboration practices for patients with chronic conditions and improving care coordination and communication for patients with mental health needs are recommended.

On differentiability and mass distributions of typical bivariate copulas

Despite the fact that copulas are commonly considered as analytically smooth/regular objects, derivatives of copulas have to be handled with care. Triggered by a recently published result characterizing multivariate copulas via (d−1)-increasingness of their partial derivative we study the bivariate setting in detail and show that the set of non-differentiability points of a copula may be quite large. We first construct examples of copulas C whose first partial derivative ∂1C(x,y) is pathological in the sense that for almost every x∈(0,1) it does not exist on a dense subset of y∈(0,1), and then show that the family of these copulas is dense. Since in commonly considered subfamilies more regularity might be typical, we then focus on bivariate Extreme Value copulas (EVCs) and show that a topologically typical EVC is not absolutely continuous but has degenerated discrete component, implying that in this class typically ∂1C(x,y) exists in full (0,1)2.Considering that regularity of copulas is closely related to their mass distributions we then study mass distributions of topologically typical copulas and prove the surprising fact that topologically typical bivariate copulas are mutually completely dependent with full support. Furthermore, we use the characterization of EVCs in terms of their associated Pickands dependence measures ϑ on [0,1], show that regularity of ϑ carries over to the corresponding EVC and prove that the subfamily of all EVCs whose absolutely continuous, discrete and singular component has full support is dense in the class of all EVCs.

Design strategy for the prototyping of 3D-printed continuous fiber-reinforced components for solar-powered vehicle

Continuous fiber fused filament fabrication is an advanced 3D printing method that allows designers to produce high-performing lightweight structures, leading toward innovative design philosophies and sustainable production chains. In this work, we proposed a design strategy to manufacture selected components for a solar-powered vehicle, which consists of three stages. Firstly, the prototypes’ CAD models are developed, considering their geometric and manufacturing requirements. Then, a finite element analysis is carried out to ensure optimal fiber reinforcement of prototypes’ critical regions. Lastly, the manufacturing stage involves the slicing process and optimization of the time and cost of the printed part employing Markforged® technology. Adopting the proposed methodology, the experimental campaign investigated the print quality and performance of several prototypes of each component by adjusting printing parameters.

All-optical infrasound sensor based on a Fabry-Perot interferometer

Recent demands for infrasound measurement, whether for detecting violent atmospheric events or evaluating the environmental impact of wind farms, require new acoustic calibration standards in the frequency range below 2Hz. Expanding the frequency bandwidth of microphones remains a limited strategy since they are designed to filter out continuous components. An alternative method for measuring infrasound is proposed, which relies on a Fabry-Perot interferometer. This technique has been studied extensively for static pressure measurements with success. Therefore, adapting a Fabry-Perot refractometer to perform acoustic measurements is not only a technical challenge but also an opportunity to bridge the gap between static pressures and acoustic metrology. As acoustic movement involves both small pressure and temperature variations, it is important to account for their coupled effects in interferometer measurement results. Since the temperature variation field in the measurement system cannot be characterised experimentally, an analytical model has been developed. The chosen theoretical and technical solutions are validated by the good agreement between experimental results obtained with the refractometer carried out and other calibrated sensors in the frequency range from 40mHz to 1.5Hz. These results also highlight the improvements required to bring the device up to the level of an infrasound reference instrument.

Repair alert model when the lifetimes are discretely distributed

This paper deals with the repair alert models. They are used for analyzing lifetime data coming from engineering devices under maintenance management. Repair alert models have been proposed and investigated for continuous component lifetimes. Existing studies are concerned with the lifetimes of items described by continuous distributions. However, discrete lifetimes are also frequently encountered in practice. Examples include operating a piece of equipment in cycles, reporting field failures that are gathered weekly, and the number of pages printed by a device completed before failure. Here, the repair alert models are developed when device lifetimes are discrete. A wide class of discrete distributions, called the telescopic family, is considered for the component lifetimes, and the proposed repair alert model is explained in detail. Furthermore, the problem of estimating parameters is investigated and illustrated by analyzing a real data set.

MULTICOMPONENCE AS A STRUCTURAL PECULIARITY OF MILITARY TERMS IN FOREIGN MASS MEDIA INTO RUSSIAN TRANSLATION

This article delves into the important analysis of the structural peculiarities of multicomponent military terms, a topic of increasing importance due to the need to describe professional objects and concepts, identify complex ideas, and unearth new dimensions of the studied phenomena. The prevalence of multicomponent terminology in foreign mass media resources underscores its significance in the media landscape. The purpose of the article is to explore the structural characteristics of multicomponent military terms extracted from mass media sources, providing a Russian translation. We also seek to identify the primary formulas and constituent components of these terms. By doing so, we hope to contribute to a better understanding of how English military terms can be formed and the development of a terminological dictionary that will include the latest examples of multicomponent military terms. The scientific novelty of the research lies in its focus on a particular and specialized domain of terminological studies, which will help to comprehend the challenges associated with understanding the structural and semantic features of multicomponent military terms, their word formation and constituent components frequently used in their structural models. The results obtained can also serve as a foundation for other fields of terminology.The research methodology is a combination of different research methods, such as the method of continuous sampling, component analysis, and word-formation analysis, which are used to analyze the selected material, and the quantitative approach helps to deal with the numerical data. The systematized examples of multicomponent military terms, categorized into two-, three-, and four-component terms and compound terms with hyphenated spelling, are accompanied by the corresponding translation. The findings of this research will equip translators, researchers, and practitioners with a deeper understanding of the challenges and strategies involved in analyzing the structural models of multicomponent military terms, thereby enhancing their professional capabilities.

Shallow crustal structure of the northern Longmen Shan fault zone revealed by a dense seismic array with ambient noise analysis

The Longmen Shan (LMS) fault zone located in the southwest of China is not only the boundary tectonic zone of the Tibetan Plateau and South China block, but also an important part of the north–south seismic belt of China. To investigate the detailed crustal structure of the LMS fault zone, we deployed a dense seismic array of 151 short-period temporary stations in its northern section from March 16 to April 6, 2023. Continuous vertical component ambient noise waveforms recorded by these stations were cross-correlated for all station pairs, enabling the extraction of Rayleigh wave phase velocity dispersion curves across periods ranging from 0.5 s to 6 s. We then inverted these data to derive the crustal shear wave velocity using direct surface wave tomography. Meanwhile, a linear sub-array consisting of 54 stations and crossing the surface rupture of the 2008 Wenchuan earthquake was used to image the fault structure by applying the Transmitted Surface Wave Reverse Time Migration method (TSW-RTM). The ambient noise tomography results show that strong lateral heterogeneity exists in the shallow crust in the study area, with a high shear velocity in the northwest and a low shear velocity in the southeast. The low shear velocity is generally distributed between the Yingxiu-Beichuan fault (YBF) and the Guanxian-Jiangyou fault (GJF). The results of TSW-RTM indicate that the Wenchuan-Maoxian fault (WMF) and the YBF are both characterized with a steep dip to the northwest. Our results could serve as the important basis for the study of segmentation characteristics of the LMS fault and seismic hazard preparation and mitigation.

RASPA3: A Monte Carlo code for computing adsorption and diffusion in nanoporous materials and thermodynamics properties of fluids.

We present RASPA3, a molecular simulation code for computing adsorption and diffusion in nanoporous materials and thermodynamic and transport properties of fluids. It implements force field based classical Monte Carlo/molecular dynamics in various ensembles. In this article, we introduce the new additions and changes compared to RASPA2. RASPA3 is rewritten from the ground up in C++23 with speed and code readability in mind. Transition-matrix Monte Carlo is added to compute the density of states and free energies. The Monte Carlo code for rigid molecules is based on quaternions, and the atomic positions needed in the energy evaluation are recreated from the center of mass position and quaternion orientation. The expanded ensemble methodology for fractional molecules, with a scaling parameter λ between 0 and 1, now also keeps track of analytic expressions of dU/dλ, allowing independent verification of the chemical potential using thermodynamic integration. The source code is freely available under the MIT license on GitHub. Using this code, we compare four Monte Carlo (MC) insertion/deletion techniques: unbiased Metropolis MC, Configurational-Bias Monte Carlo (CBMC), Continuous Fractional Component MC (CFCMC), and CB/CFCMC. We compare particle distribution shapes, acceptance ratios, accuracy and speed of isotherm computation, enthalpies of adsorption, and chemical potentials, over a wide range of loadings and systems, for the grand canonical ensemble and for the Gibbs ensemble.

Individual differences in decision-making shape how mesolimbic dopamine regulates choice confidence and change-of-mind.

Nucleus accumbens dopamine signaling is an important neural substrate for decision-making. Dominant theories generally discretize and homogenize decision-making, when it is in fact a continuous process, with evaluation and re-evaluation components that extend beyond simple outcome prediction into consideration of past and future value. Extensive work has examined mesolimbic dopamine in the context of reward prediction error, but major gaps persist in our understanding of how dopamine regulates volitional and self-guided decision-making. Moreover, there is little consideration of individual differences in value processing that may shape how dopamine regulates decision-making. Here, using an economic foraging task in mice, we found that dopamine dynamics in the nucleus accumbens core reflected decision confidence during evaluation of decisions, as well as both past and future value during re-evaluation and change-of-mind. Optogenetic manipulations of mesolimbic dopamine release selectively altered evaluation and re-evaluation of decisions in mice whose dopamine dynamics and behavior reflected future value.

Parametric modeling and engineering application of the high-speed continuous beam bridge based on Building Information Modeling.

To improve the informatization and intelligence level of high-speed railway (HSR) bridge construction, a parametric modeling method for continuous beam bridges based on Building Information Modeling (BIM) is proposed in this study. By this method, the parametric families of continuous beam components and key construction machinery are established, and the rapid modeling of overall continuous beam bridge and the simulation of critical construction process are realized as well. Taking the Caoxian-Shangqiu bridge of Xiong'an-Shangqiu HSR as a case study, the parametric modeling method is applied to conduct the engineering application on the prestressed duct layout and rebar clash detection. The results indicate that the modeling efficiencies of HSR continuous beam bridge and construction machinery are significantly increased by the established parametric modeling method. Based on the BIM model of continuous beam bridge, the improvement in the precision of prestressed duct layout and the elimination of rebar clash points can be achieved. The research achievement can guide the visualization of construction disclosure, enhance construction efficiency, and provide reference and technical support for the construction management and control of HSR continuous beam bridges.

Bias correction and ensemble techniques in statistical downscaling model for rainfall prediction using Tweedie-LASSO in West Java, Indonesia

Rainfall is a climate element with high variations in space and time scales, so it is not easy to predict. One way to predict rainfall is statistical downscaling (SD). SD can predict local rainfall based on Global Circulation Model (GCM) data. The Decadal Climate Prediction Project (DCPP), one of the GCMs, originates from adjacent grids and experiences multicollinearity problems. Rainfall as a response variable is Tweedie Compound Poisson Gamma (TCPG) distribution data because it has a discrete component (rainfall events) and a continuous component (rainfall intensity), so SD modelling will be carried out using Tweedie-LASSO. This research aims to compare the performance of bias correction and ensemble methods in SD in predicting rainfall in West Java, Indonesia. Bias correction uses Empirical Quantile Mapping (EQM) with CHIRPS data, and the ensemble method uses a stacking technique with Random Forest (Stacking-RF) due to the varied characteristics of DCPP model sources. Evaluation results using Root Mean Square Error Prediction (RMSEP) and correlation coefficient show that bias correction improves single-model performance but not ensemble models. Besides that, ensemble models outperform single models both before and after bias correction. The combination of bias correction and ensemble modelling can be recommended when conducting SD to enhance the prediction capability of rainfall at stations and other areas.

FUNCTIONS OF PHRASEOLOGICAL UNITS IN UZBEK BUSINESS DISCOURSE

This article explores the functions of phraseological units (PUs) in Uzbek business discourse, shedding light on their role in cultural and linguistic contexts. Phraseological units, which include idioms, collocations, and proverbs, are essential in conveying nuanced meanings, expressing cultural values, and enhancing communication efficacy in business interactions. The research employs a combination of continuous sampling, systematization, component analysis, and discourse analysis methods, supported by a review of both domestic and international literature on phraseology and business communication. Findings reveal that in Uzbek business discourse, PUs serve multiple functions: they reflect cultural values, such as respect and community orientation; facilitate indirect and polite communication; and employ metaphors drawn from traditional contexts like agriculture. Specific examples include idioms and proverbs that emphasize hard work, strategic thinking, and resilience. The study concludes that PUs are integral to effective business communication in Uzbekistan, enhancing rapport, persuasion, and understanding. The ongoing integration of traditional phraseology with modern business practices continues to evolve, underscoring the dynamic nature of Uzbek business discourse.

Strengthening mechanism of TPMS interpenetrating phase composites for bone tissue engineering

Multicomponent functional scaffolds hold great promise as implanted materials with compatible mechanical properties and biological functionalities. Interpenetrating phase composites (IPCs) with biomimetic multiscale porosity were fabricated in this study by additive manufacturing and foaming processes using polymethyl methacrylate (PMMA) and polyurethane foam (PUF), respectively. PMMA creates the macroscopic pores with triply periodic minimal surface (TPMS) structures, while PUF forms microscale porosity interpenetrating within the scaffolds, which has been confirmed by SEM and CT tests. Mechanical testing and finite element analysis (FEA) demonstrated significant enhancements in peak strength, toughness, and energy absorption of the IPCs compared to the scaffold alone, with increases of 134%, 73%, and 236%, respectively. The FEA provided insights into the failure and strengthening mechanisms of the interpenetrating porous structure. The continuous PUF component integrated within the IPCs effectively facilitated stress transfer, impeded crack propagation, and significantly prolonged the stress plateau of the scaffolds. Meanwhile, the PMMA primarily served as the main mechanical load-bearing component, transferring stress to the PUF during the deformation stage, resulting in a highly uniform stress distribution within the scaffolds. This uniform stress distribution creates an environment conducive to effective stress stimulation of the internally growing tissue.

Effect of dissolved KOH and NaCl on the solubility of water in hydrogen: A Monte Carlo simulation study.

Vapor-Liquid Equilibria (VLE) of hydrogen (H2) and aqueous electrolyte (KOH and NaCl) solutions are central to numerous industrial applications such as alkaline electrolysis and underground hydrogen storage. Continuous fractional component Monte Carlo simulations are performed to compute the VLE of H2 and aqueous electrolyte solutions at 298-423K, 10-400bar, 0-8 molKOH/kg water, and 0-6 molNaCl/kg water. The densities and activities of water in aqueous KOH and NaCl solutions are accurately modeled (within 2% deviation from experiments) using the non-polarizable Madrid-2019 Na+/Cl- ion force fields for NaCl and the Madrid-Transport K+ and Delft Force Field of OH- for KOH, combined with the TIP4P/2005 water force field. A free energy correction (independent of pressure, salt type, and salt molality) is applied to the computed infinite dilution excess chemical potentials of H2 and water, resulting in accurate predictions (within 5% of experiments) for the solubilities of H2 in water and the saturated vapor pressures of water for a temperature range of 298-363K. The compositions of water and H2 are computed using an iterative scheme from the liquid phase excess chemical potentials and densities, in which the gas phase fugacities are computed using the GERG-2008 equation of state. For the first time, the VLE of H2 and aqueous KOH/NaCl systems are accurately captured with respect to experiments (i.e., for both the liquid and gas phase compositions) without compromising the liquid phase properties or performing any refitting of force fields.

Supercooled large droplet size distribution effects on airfoil icing: A numerical investigation based on a new coupled Eulerian method

Supercooled large droplets (SLDs) under natural icing conditions have the characteristics of easy deformation in motion and easy splashing on impact, and a bimodal droplet size distribution that has received less attention. The modified form of the Rosin-Rammler function was improved to achieve a more accurate nonlinear fitting of the SLD distribution curve. The droplet size distribution was divided into non-equipartition continuous multiple components. The drag source term of each component was coupled with the overall droplet size distribution, and the Eulerian equations of each component of SLDs were solved simultaneously. A new coupled Eulerian method for non-equipartition continuous multi-size droplets was proposed to simulate the impact characteristics of SLDs, and the SLD collection coefficients were validated. Effects of the ratio between the number of large and small droplet components and the number of all components on the simulation results were investigated to select a better combination based on stable convergence calculation steps and the calculation time. This new method was added to the multi-step icing numerical method, and the accuracy and robustness of the method in icing shape prediction were verified based on the freezing drizzle, median volume diameter &lt; 40 μm (FZDZ, MVD &lt; 40 μm) icing condition. Airfoil icing characteristics based on the bimodal and monomodal distribution were compared, and the icing shapes at the leading edge were similar. Still, the upper and lower limits of the icing shapes with the bimodal distribution were nearer to the trailing edge and the ice layer was thicker there.

A methodical examination of single and multi-attacker flood attacks using RPL-based approaches

The Internet of Things (IoT) constitutes an intricate network of physical entities, ranging from vehicles to home appliances, each ingrained with electronics, software, sensors, and internet connectivity to facilitate data exchange and collection. This novel realm of interconnectivity, while yielding considerable advantages, also invites concerns over cybersecurity, as the vast amount of sensitive data gathered by IoT devices necessitates safeguarding against potential cyber breaches. In this context, the focus of cybersecurity in IoT involves the deployment of diverse technologies, standards, and optimum practices including, but not limited to, encryption, firewalls, and multi-factor authentication. Hence, while IoT contributes significantly to societal advancement, addressing the associated security concerns remains an imperative task. This study therefore delves into an examination of flood attacks, a prevalent form of cyber assault aimed at IoT devices. The study explored the ramifications of such an attack on an IoT system by analyzing network traffic in scenarios of singular and multiple attackers. A benchmark model devoid of an attack was employed for comparative purposes. To circumvent additional stress on the operational system, network packets were mirrored through cloud infrastructure and subsequently relayed to artificial intelligence (AI) and forensic analysis tools for real-time examination. To assure the integral cybersecurity component of continuity within IoT systems, the attacking entities were identified through AI, and forensic tools were employed to conduct real-time data analysis, thereby enabling continuous network monitoring. This study introduces an innovative approach to detecting flood attacks on IoT systems by leveraging a novel AI-based technique that integrates the ’6LoWPAN.Pattern’ feature, previously unexplored in this context. Extensive simulations were conducted to analyze the impact of flood attacks using both single and multiple-attacker scenarios. Our method demonstrated a 99.9% success rate in attacker identification, distinguishing it from existing techniques. This research contributes to the cybersecurity field by enhancing the detection capabilities within IoT networks and offering a robust model against a prevalent form of cyber threats.

Approximations of the Euler–Maruyama Method of Stochastic Differential Equations with Regime Switching

This work focuses on a class of regime-switching diffusion processes with both continuous components and discrete components. Under suitable conditions, we adopt the Euler–Maruyama method to deal with the convergence of numerical solutions of the corresponding stochastic differential equations. More precisely, we first show the convergence rates in the Lp-norm of the stochastic differential equations with regime switching under Lipschitz conditions. Then, we also discuss L1 and L2 convergence under non-Lipschitz conditions.

Scaling limit of the staggered six-vertex model with $U_q\big(\mathfrak{sl}(2)\big)$ invariant boundary conditions

We study the scaling limit of a statistical system, which is a special case of the integrable inhomogeneous six-vertex model. It possesses U_q\big(\mathfrak{sl}(2)\big)Uq(𝔰𝔩(2)) invariance due to the choice of open boundary conditions imposed. An interesting feature of the lattice theory is that the spectrum of scaling dimensions contains a continuous component. By applying the ODE/IQFT correspondence and the method of the Baxter QQ operator the corresponding density of states is obtained. In addition, the partition function appearing in the scaling limit of the lattice model is computed, which may be of interest for the study of nonrational CFTs in the presence of boundaries. As a side result of the research, a simple formula for the matrix elements of the QQ operator for the general, integrable, inhomogeneous six-vertex model was discovered, that has not yet appeared in the literature. It is valid for a certain one parameter family of diagonal open boundary conditions in the sector with the zz-projection of the total spin operator being equal to zero.