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We present a mathematical model for the slow combustion (smoldering) of a two-dimensional sheet of paper. We describe the evolution of the char region, and we investigate the effects of an orthogonal air flow on the shape of the combustion front. The mathematical formulation consists in a set of two nonlinear PDEs for the temperature and the oxygen concentrations coupled with one ODE for the cellulose concentration. The (dimensionless) problem is solved numerically by means of a spectral collocation scheme based on Chebyshev polynomials. Our results show that the Péclet and the Lewis number strongly influence the shape of the ignition front and that the advancement of the combustion front does not occur if advection and diffusion are neglected (zero Péclet and Lewis numbers). In particular we observe that the burning region and the ignition front are strongly influenced by the velocity of the airflow and by the mass and heat transport phenomena due to diffusion and advection. We shall see that the increasing of the ratio between the convective and diffusive characteristic times (Péclet number) and the decreasing of the ratio between the mass and heat diffusive characteristic times (Lewis number) have a "flattening effect" on the combustion front. [ABSTRACT FROM AUTHOR]

In this article, we present a mathematical model and numerical simulation of the coffee-ring effect on porous papers. The numerical method is based on Monte Carlo simulation. The proposed model is simple but can capture the main mechanism of coffee stain formation on porous papers. Several numerical experiments are presented to demonstrate the performance of the proposed algorithm. We can obtain the coffee-ring effect on porous papers as the computer simulation results. [ABSTRACT FROM AUTHOR]

Mathematical modeling is a high-leverage topic; it is critical to students' participation in STEM education and supports civic engagement. Until recently, research on modeling at the elementary level has been underemphasized, particularly research on supports and challenges for teachers who engage in designing authentic modeling tasks. In this study, we employed qualitative case study methods to investigate how elementary teachers designed and implemented authentic mathematical modeling tasks, with an explicit focus on how their tasks evidenced different dimensions of authenticity. We analyzed three cases of teams of elementary teachers as they developed modeling tasks connected to school and community contexts. The three cases were: 1) a student-driven modeling task related to paper and plastic waste in a school cafeteria, 2) a modeling task based on authentic situations at a community-run resource center, and 3) a modeling task focused on designing and monitoring a school community-building art project. Our cases illustrate that elementary teachers can successfully design and implement modeling activities that utilize different entry points and evidence multiple dimensions of authenticity. Furthermore, we found that the specific dimensions of authenticity may vary depending on the design supports and curriculum challenges within each context. [ABSTRACT FROM AUTHOR]

To enhance the quality and efficiency of computer-enabled generation of papers for Test for English Majors Band 8 (TEM-8), a paper generation model supported by sparrow search algorithm-genetic algorithm was studied. First, a simplified test paper generation mathematical model was set up after analyzing and studying types and characteristics of TEM-8 tasks. In the model, quantity, type, difficulty, discrimination degree, scores, exposure, and answering time of test questions were taken into consideration. To enhance the optimizing effect of the genetic algorithm for searching test questions, the traditional genetic algorithm was improved by introducing the sparrow search algorithm into the model to achieve a better crossover rate, variance rate, optimization precision, and speed of the genetic algorithm. A new sparrow search-genetic algorithm (SSA-GA) was designed, and the optimizing effect of SSA-GA was verified to be ideal through optimizing six standard test functions. Then, SSA-GA was applied to conduct experimentation with test paper generation, and comparison with traditional genetic algorithms was also made. The values of best and average fitness of SSA-GA were better than those of the traditional genetic algorithm (GA) in the paper generation. Exposure rate and success rate in TEM-8 paper generation of SSA-GA were higher than those of traditional GA in TEM-8 paper generation. Results showed that the studied SSA-GA could implement test paper generation with higher speed and better quality. [ABSTRACT FROM AUTHOR]

Howard Rachlin's widely influential behavioral economic approach to self‐control and related issues provides the model for this submission. The topic is overconsumption. Current human consumption levels are unsustainable. Explanations typically focus on societal factors, such as the seductive power of advertising and/or misguided tax policies. However, the effectiveness of these factors depends on the degree to which individuals are susceptible to the message: "consume more." Humans are not blank slates. This paper argues that how individuals frame their choices establishes the susceptibility to overconsume. According to economic theory, consumers frame their options as bundles, composed of different combinations of the available items and activities. This leads to maximizing. In experiments, participants tend to frame their options as "either‐or" choices. This leads to the matching law. Mathematical models of concurrent schedule choice procedures show that (1) the matching law implies overconsumption of the most preferred option and (2) that individuals will persist in preferring their favorite option even when doing so reduces overall reward rates. Given that the matching law better describes how individuals choose than does maximizing, the mathematical models of widely used choice procedures help explain why efforts to increase consumption have been more influential than efforts to control consumption. [ABSTRACT FROM AUTHOR]

Due to rapid temperature rise and insulation moisture, bubbles can generate in the oil-paper insulation of oil-immersed power transformers, which can reduce the dielectric strength of oil-paper insulation and even bring about the risk of insulation breakdown. In order to accurately evaluate the conditions of bubble formation, the physical process of bubble formation in oil-paper insulation is studied in this article. Considering the effects of water vaporization, gas dissolution in oil, and moisture migration on bubble formation, a bubble formation prediction model is constructed. Based on Henry’s law, the dissolution equilibrium of gas in oil is taken into consideration and the upper boundary of the initial temperature of bubble effect (ITBE) envelope is obtained in this model. Based on the moisture equilibrium in oil-paper insulation, the bubble formation process caused by the emergence and rapid evaporation of free water is analyzed, and then, the lower boundary of the ITBE envelope is obtained in this model. The model results show that the moisture content of the pressboard and the presence of free water have a great impact on ITBE. Specifically, the higher the moisture content, the lower the ITBE value. In addition, with the further increase of moisture content, the upper and lower boundaries of the ITBE envelope gradually tend to be the same. However, once free water is present on the surface of cellulose, ITBE decreases rapidly to below 120 °C. The model built in this article is of great significance to study the temperature limit of the power transformer. Hence the ITBE envelope can provide an important theoretical reference for reducing the risk of bubble formation during power transformer operation. [ABSTRACT FROM AUTHOR]

The generation and distribution of furfural are significantly affected by moisture content in the insulating paper. However, the diffusion mechanism of furfural under moisture effect is not clear, hence, this study investigates the effect of moisture on the diffusion characteristics of furfural by combining macro experiment and micro molecular dynamics simulation. The simulation results demonstrate that the increased moisture content in paper accelerates the diffusion of furfural from paper to oil, which is also proved by the experimental data. Then, the results of interaction energy analysis indicate that the increase of moisture enhances the van der Waals force between oil and furfural. The present findings are expected to improve the theoretical level of furfural analysis, which will facilitate the aging evaluation of the transformer insulating paper based on furfural. [ABSTRACT FROM AUTHOR]

This article is aimed at quantifying the health condition of the power transformer insulation system through its frequency-domain dielectric characteristic by using the concept of the resistor and fractional calculus. In this regard, the dielectric model of the fractional Poynting–Thomson (PT) is proposed, and a mathematical model for parameter identification of the proposed model is presented. The shuffled frog leaping algorithm (SFLA) is used to realize the parameter identification and the fractional PT model parameters of the oil-paper samples under different insulation health conditions. The influence of moisture and aging on the fractional PT dielectric model parameters is experimentally studied. Results show that, with the increase in the water content within the insulation system, the parameters of the fractional PT model gradually decrease, and there is a strong correlation between the relaxation time and the water content. This facilitates the employment of the fractional PT model parameters to quantify the aging and moisture content of the power transformer insulation system. [ABSTRACT FROM AUTHOR]

Methanol concentration as an aging indicator can assess cellulose aging and estimate cellulose degree of polymerization (DP). Despite the advantages of methanol (MeOH), its major disadvantage is that its concentration in the oil decreases after some time. This point is called the MeOH peak in this article. Therefore, using this indicator when MeOH concentration is reduced leads to incorrect results. When using methanol, the main problem is that whenever the methanol concentration in a transformer is measured, it cannot be identified that the measured concentration belongs to the left or right side of the MeOH peak. If the measured concentration belongs to the right side of the MeOH peak, the estimated DP is incorrect. In this article, an empirical equation is established to estimate the DP value as a function of methanol concentration when methanol concentration belongs to the left side of the MeOH peak. Then, a new index called methanol peak detector index (MPDI) composed of a 2-furfural/MeOH ratio and normalized DP is presented to ensure the validity of the calculated DP value. If it is found that the measured concentration belongs to the left side of the MeOH peak, then the estimated DP by the presented equation is valid. Finally, the application of this method is verified by applying it to measurement data samples indicating the validity of the method. [ABSTRACT FROM AUTHOR]

The space charge effect of transformer insulating paper will distort its internal electric field, and its space charge effect will be more prominent under extremely complex working conditions. At present, the micromechanism of charge transport and electric field distortion characteristics of paperboard are not clear under complex working conditions. So in this article, based on the bipolar carrier transport (BCT) model and the dynamic carrier balance model, the effects of high temperature, aging degree, moisture content, and bent degree on charges accumulation in paperboard are studied under dc high voltage by numerical simulation and the measured data needed for simulation. The results show that the higher temperature strengthens the carrier migration, deepens the injection depth of the charge, and aggravates the distortion of electric field intensity in paperboard. The more extended the aging time of paperboard, the greater the internal trap density and the deeper the trap depth, which lead to charges migration difficultly. Increasing water content in the paperboard will accelerate space charges to reach a steady state, while further increasing it will slow down this process, which is related to the shallow trap getting deeper. When the critical part of paperboard is extruded, many traps are introduced, resulting in charges accumulation seriously. The research results can reference the design of paperboard and the maintenance of transformer insulation system. [ABSTRACT FROM AUTHOR]

The traditional method for transformer moisture diagnosis is to establish empirical equations between feature parameters extracted from frequency domain spectroscopy (FDS) and the transformer’s moisture content. However, the established empirical equation may not be applicable to a novel testing environment, resulting in an unreliable evaluation result. In this regard, it is acknowledged that FDS combined with machine learning is more suitable for estimating moisture content in a variety of test environments. Nonetheless, the accuracy of the estimation results obtained using the existing method is limited by the algorithm’s inability to generalize. To address this issue, we propose an AdaBoost algorithm-enhanced back-propagation neural network (BP_AdaBoost). This study creates a database by extracting feature parameters from the FDS that characterize the insulation states of the prepared samples. Then, using the BP_AdaBoost algorithm and the newly constructed database, the moisture estimation models are trained. Finally, the results of the estimation are discussed in terms of laboratory and field transformers. By comparing the proposed BP_AdaBoost algorithm to other intelligence algorithms, it is demonstrated that it not only performs better in generalization, but also maintains a high level of accuracy. [ABSTRACT FROM AUTHOR]

The imbalance between the prevalence of patients with acute respiratory failure (ARF) and acute-on-chronic respiratory failure and the number of intensive care unit (ICU) beds requires new solutions. The increasing use of non-invasive respiratory tools to support patients at earlier stages of ARF and the increased expertise of non-ICU clinicians in other types of supportive care have led to the development of adult pulmonary intensive care units (PICUs) and pulmonary intermediate care units (PIMCUs). As in other European countries, Italian PICUs and PIMCUs provide an intermediate level of care as the setting designed for managing ARF patients without severe non-pulmonary dysfunction. The PICUs and PIMCUs may also act as step-down units for weaning patients from prolonged mechanical ventilation and for discharging patients still requiring ventilatory support at home. These units may play an important role in the on-going coronavirus disease 2019 pandemic. This position paper promoted by the Italian Thoracic Society (ITS-AIPO) describes the models, facilities, staff, equipment, and operating methods of PICUs and PIMCUs. [ABSTRACT FROM AUTHOR]

The Buck converter is a commonly used voltage regulator (VR) structure that supplies power to the load devices and responds to load transients. In most of the applications, the VR is controlled by voltage or current mode control, and some nonlinear approaches are used to improve the transient response which brings more complexities to the closed loop design. To achieve a fast transient response without over-regulation under a load step transient, this paper proposes a digital single-cycle regulation (SCCR) controller, which comprised a fast path, a slow path, and a neutralization path. Unlike the conventional PID control, the neutralization path of the SCCR controller is used to offset the excessive energy change in the first cycle after a load step occurs, which makes the inductor current reach its new static condition in a shorter period of time. The mathematical model of the SCCR control is established in this paper and a scanning algorithm is proposed for the design of the compensator parameters. Experimental results are presented to verify the improvement of the transient response when compared to the conventional and nonlinear PID control, the recovery time is decreased by 64.3% and 43% for load step-up and step-down when compared with nonlinear PID control. [ABSTRACT FROM AUTHOR]

• Combined effects of extruded brick compositions with paper sludge and expanded perlite were characterized. • The use of additives in bricks has significantly affected their thermo-physical and mechanical properties. • The effects of process parameters on brick properties were investigated with a new mathematical modeling approach. • Fired brick samples showed good thermal insulation performance. • Produced exruded bricks have good potential for energy saving. Lightweight bricks produced with addition of different additive materials such as expanded perlite (EP) and recycling paper sludge (RPS) waste have been accomplished by a pug mill. Porous fired bricks were produced by using organic and inorganic additives such as paper waste and expanded perlite as pore-makers. In the experimental study, the seventeen mixture sets were prepared with Box-Behnken experimental design procedure of two additive ratios and firing temperatures. The brick samples were produced with shaping by extrusion method and firing at 850, 950 and 1050 °C for two hours after drying. Physical characteristics such as bulk density, apparent porosity and water absorption, and also, compressive strength, thermal conductivity and microstructural properties of brick samples were studied. Influences of process parameters on brick properties were investigated with a detailed neuro-regression analysis. In conclusion, the best brick composition (10 % EP + 10 %RPS by weight) in terms of thermal conductivity corresponding to acceptable mechanical properties was optimized. Accordingly, the compressive strength values of all samples are around 10 to 27 MPa. Also, the samples with high additive content (especially 10 %RPS + 5 %EP sample) exhibited the lowest thermal conductivity value (0.432 W/mK) due to the low firing temperature. [ABSTRACT FROM AUTHOR]

I will briefly discuss the history of research-related projects that Mark Burgin and I worked on together. I will then discuss our joint research related to the circle of sense and nonsense. One paper was entitled In a search for deeper meanings: navigating the circle of Sense and Nonsense and in turn articulating logical varieties as knowledge illuminators and the second was entitled In the Circle of Sense and Nonsense, Including A Mathematic Model of Meaning. This research represents a bridge between the media arts and sciences (my artwork) as a means of embodying ideas exploring a particular approach to meaning production and related computation, as well as Burgin's concepts related to logical varieties and mathematical models of meaning. I will refer to the full papers and links because they present a very robust and full articulation of the concepts discussed here. In this paper, I will briefly touch on the areas of research, supply short definitions, and refer to the relevant historical publications. [ABSTRACT FROM AUTHOR]

Aim: To describe the implementation of a trauma‐informed model of care in the Post COVID Respiratory Clinic of a large tertiary referral centre in NSW. Design: Discussion paper. Data Sources: Evidence gathered from a literature search (2008–2022) was used to develop a framework for management of patients presenting to this Post COVID Respiratory Clinic. This paper outlines the personal reflections of the clinic staff as they developed and implemented this framework. Ethical approval was obtained to report the data collected from patient reviews. Discussion: The literature highlights the high prevalence of trauma in patients following COVID‐19 infection, as well as the larger population both during and after the pandemic. This experience of trauma was observed in patients seen within the clinic, indicating a need for specialized care. In response, a trauma‐informed model of care was implemented. Conclusion: Reconceptualizing COVID‐19 as a 'collective trauma' can help healthcare workers understand the needs of post‐COVID patients and enable them to respond empathetically. A trauma‐informed model is complementary to this cohort as it specifically addresses vulnerable populations, many of whom have been further marginalized by the pandemic. Implications for Nursing and Patient Care: Frontline healthcare workers, particularly nurses, are well positioned to implement trauma‐informed care due to their high‐level of patient contact. Adequate allocation of resources and investment in staff is essential to ensure such care can be provided. Impact: The COVID‐19 pandemic has led to adverse physical and mental health outcomes for many.Trauma‐informed care is a way to promote reengagement with the healthcare system in this group.Post COVID patients globally may benefit from this approach, as it aims to build trust and independence. Patient or Public Contribution: Feedback was sought from a patient representative to ensure this paper adequately reflected the experience of the post‐COVID patient. [ABSTRACT FROM AUTHOR]

This article will briefly introduce the traditional disability studies project through the social model of disability and how its inherent theoretical limitations became the impetus to perpetuate a need to adopt critical disability theory (CDT) to expand the intellectual arsenal of the discipline. Being a reflexive inquiry that resists domination that oppresses people with disabilities, CDT's reach produced work in conversation with other areas of critical social thought and inspired this paper to explore how post-colonial work – particularly Homi Bhabha's hybridity theory – can be incorporated into CDT's paradigmatic views of power. This paper concludes by addressing some of the debates and cultural implications that stem from conceptually merging CDT and post-colonial hybridity theory to frame how it can reimagine the possibilities and trajectories of a global disability movement. Points of interest: This article addresses the two main ideas in disability studies, starting with the social model of disability, which helped put forth critical disability theory. Critical disability theory suggests that people with disabilities are controlled by others using the idea of 'impairment' to justify their power. The article suggests that critical disability theory can benefit from an approach called post-colonial hybridity, which combines global North and South ideas to help represent people with disabilities in the Southern part of the world. The article also concludes by exemplifying how mental health and traditional healing practices are combined to support well-being. The authors encourage people studying disability to listen to different voices worldwide to understand how the world is changing. [ABSTRACT FROM AUTHOR]

Radio stations are seriously affected by transmission line reradiation interference, but most of the existing methods for analyzing and solving reradiation interference on transmission lines focus on approximating the physical problem through mathematical models and algorithms, and it is difficult to study the correlation between transmission lines and reradiation interference in depth. This paper introduces the characteristic mode theory to study the influence factors of reradiation interference on transmission lines, which can decompose the surface induced current of transmission lines into a series of mutually orthogonal mode currents. This paper verifies the correctness of applying the MS (mode significance) value of the characteristic mode theory to analyze the reradiation interference through a simple transmission line example. Taking a line with 5 towers as an example, by analyzing the characteristic mode currents of transmission lines with different forwarding angles and linear arrangements, we not only verified that the characteristic mode currents can well characterize the reradiation interference, but also verified that the characteristic currents of different modes have a direct connection with the structure of the line, which can be applied in the process of designing or reconstructing the towers of the transmission lines, to predict the influence of different structural parameters on electromagnetic scattering, so as to optimize the tower design to reduce the reradiation interference effects and thus optimize the tower design to reduce reradiation interference. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Asynchronous temporal Boolean Networks (ATBNs) are more complex in structure and have different linear expressions compared to traditional synchronous Boolean networks. The complexity depends on the number of updated nodes. The main contribution of this paper is to propose results of synchronization and anti-synchronization problems of ATBNs. First, this paper abstracts two Temporal Boolean Networks (TBNs) into a mathematical model, and provides a linear expression of the network by means of the semi-tensor product (STP) tool. Second, based on the asynchronous updating scheme of temporal Boolean networks, we investigate the synchronization (including complete synchronization and anti-synchronization) of ATBNs, and provide two results to guarantee the synchronization and anti-synchronization. Finally, we provide two examples to verify the correctness of our theorems and corollaries. [ABSTRACT FROM AUTHOR]

This research paper explores the realm of fault detection in distributed motors through the vision of the Internet of electrical drives. This paper aims at employing artificial neural networks supported by the data collected by the Internet of distributed devices. Cross-verification of results offers reliable diagnosis of industrial motor faults. The proposed methodology involves the development of a cyber–physical system architecture and mathematical modeling framework for efficient fault detection. The mathematical model is designed to capture the intricate relationships within the cyber–physical system, incorporating the dynamic interactions between distributed motors and their edge controllers. Fast Fourier transform is employed for signal processing, enabling the extraction of meaningful frequency features that serve as indicators of potential faults. The artificial neural network based fault detection system is integrated with the solution, utilizing its ability to learn complex patterns and adapt to varying motor conditions. The effectiveness of the proposed framework and model is demonstrated through experimental results. The experimental setup involves diverse fault scenarios, and the system's performance is evaluated in terms of accuracy, sensitivity, and false positive rates. [ABSTRACT FROM AUTHOR]

Background: People with intellectual disability have diverse needs and experience higher rates of diet‐related chronic disease such as type 2 diabetes compared to people without disability. However, they are infrequently included in development and implementation of interventions to address diet‐related chronic disease. The present study describes the process to plan, develop and refine the Food and Lifestyle Information Program (FLIP) culinary nutrition intervention for adults with mild‐to‐moderate intellectual disability. Methods: The project was initiated by a disability service provider and was guided by the Cook‐Ed™ model and inclusive research principles. Initially the disability service provider and academic research team members co‐designed pre‐program consultation and pilot studies, and draft program resources. Pre‐program consultation explored paid disability support worker (n = 10) perceptions of cooking and food skills, nutrition priorities and optimal program format, which guided further program drafting. Program resources and pilot study design were further developed and refined with co‐researchers with lived experience of intellectual disability who attended a pre‐pilot and then pilot study sessions as remunerated co‐facilitators. Results: Key characteristics of the FLIP intervention arising from pre‐program consultation included providing cooking task instruction in small steps, enabling participant choice in program activities, promoting an inclusive and social atmosphere, and providing paper‐based resources. Conclusions: FLIP intervention co‐design was enabled through ongoing input from the disability service provider and people with lived experience of intellectual disability. Evaluation of FLIP feasibility, acceptability and preliminary effectiveness to improve diet‐related health is underway. Highlights: An academic research team, disability service provider and people with lived experience of intellectual disability co‐designed a culinary nutrition intervention for adults with mild‐to‐moderate intellectual disabilityKey considerations for culinary nutrition programs for people with intellectual disability include providing small group practical instruction, paper‐based Easy Read recipes, providing choice and creating a social and inclusive atmosphere [ABSTRACT FROM AUTHOR]

In his unfinished Ad harmonicon coeleste, François Viète (1540–1603) approaches astronomical models in a purely mathematical way, analyzing the equations involved in them and suggesting new geometrical approaches, usually equivalent but simpler. After dealing with the Copernican planetary models, he develops three different lunar models. The first one describes a model geometrically similar but not identical to the Ptolemaic lunar model. The second is identical to that of Copernicus, but Viète significantly simplifies the calculation methods, and the third one is inspired by Tycho's lunar model. In a previous paper, I analyzed the first model. In this paper, I describe and analyze the second one, leaving for a future work the third one. Extending the ellipse models used by Viète for the outer planets, I also show that every model of epicycle and deferent can be replaced by a planet revolving on a rotating ellipse. [ABSTRACT FROM AUTHOR]

The primary goal of the paper is to monitor the health of the spindle in machine tools to ensure optimal performance and reduce costly downtimes. Spindle health monitoring is essential to detect wear and cracks in spindle bearings, which can be challenging due to their gradual development and hidden locations. The proposed approach combines physics-based modeling and data-driven techniques to monitor spindle health effectively. In Part I and Part II of the paper, mathematical models of bearing faults and spindle imbalance are integrated into the digital model of the spindle. This allows for simulating the operation of the spindle both with and without faults. The integration of fault models enables the generation of vibrations at sensor locations along the spindle shaft. The generated vibration data from the physics-based model are used to train a recurrent neural network-based (RNN) fault detection algorithm. The RNN learns from the labeled vibration spectra to identify different fault conditions. Bayesian optimization is used to automatically tune the hyperparameters governing the accuracy and efficiency of the learning models during the training process. The RNN classifiers are further fine-tuned using a small set of experimentally collected data for the generalization of the model on real-world data. Once the RNN classifier is trained, it can distinguish between different types of damage and identify their specific locations on the spindle assembly. The proposed algorithms achieved an accuracy of 98.43% on experimental data sets that were not used in training the network. [ABSTRACT FROM AUTHOR]

Background: In example‐based learning, examples are often combined with generative activities, such as comparative self‐explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self‐explanations. While static text‐based examples can be compared easily, this is challenging for transient video‐based modelling examples used in complex domains because simultaneous processing of two videos is not feasible. Objectives: To allow for such comparisons, we combined video‐based modelling examples with static representations (i.e., summarizing tables) of the observed optimal and a suboptimal solution of the problem‐solving process. A comparative self‐explanation prompt asked learners to compare the different solution approaches. Our study investigated the impact of video‐based modelling examples versus independent problem‐solving on cognitive load and problem‐solving skill development. Moreover, we investigated the effects of comparative versus sequential self‐explanation prompts, depending on learners' prior knowledge. Methods: In an experiment, 118 automotive apprentices learned a car malfunction diagnosis strategy. Apprentices were divided into three groups: (1) modelling examples with comparative self‐explanation prompts, (2) modelling examples with sequential prompts, and (3) no examples or prompts. Diagnostic knowledge and skills were assessed before and after the intervention. Cognitive load was measured retrospectively. Results and conclusions: Despite no observed effects on cognitive load, modelling examples enhanced diagnostic knowledge and diagnostic skills with scaffolds, though not independent diagnostic skills without scaffolds. The need for more practice opportunities to foster independent diagnostic skills is assumed. Additionally, comparative prompts seem promising for learners with higher prior knowledge. Takeaways: Video‐based modelling examples were more beneficial for learning than practising to apply the diagnostic strategy. Static representations allow for comparisons of video examples and comparative prompts are promising for learners with higher prior knowledge (cf. expertise‐reversal effect). Further research, especially on the effects on cognitive load, is necessary. Lay Description: What is already known about the topic?: Text and video examples that model how to solve a problem are widely used in education.Text examples often include self‐explanation prompts that ask learners to compare several examples.For video examples, such comparison prompts have seldom been investigated, because comparisons are difficult to implement for transient videos. What does this paper add?: This paper shows that video examples combined with static summaries of processes that have been shown in the video example are effective and allow for comparisons of video examples.Such comparisons seem to be more promising for learners with higher prior knowledge. Implications for practice: Practitioners could combine video examples with static summaries of the processes shown in the video examples to allow for comparisons. [ABSTRACT FROM AUTHOR]

Background: Measuring students' self‐regulation skills is essential to understand how they approach their learning tasks in order to identify areas where they might need additional support. Traditionally, self‐report questionnaires and think aloud protocols have been used to measure self‐regulated learning skills (SRL). However, these methods are based on students' interpretation, so they are prone to potential inaccuracy. Recently, there has been a growing interest in utilizing learning analytics (LA) to capture students' self‐regulated learning (SRL) by extracting indicators from their online trace data. Objectives: This paper aims to identify the indicators and metrics employed by previous studies to measure SRL in higher education. Additionally, the study examined how these measurements were validated. Methods: Following the protocol of Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA), this study conducted an analysis of 25 articles, published between 2015 and 2022, and sourced from major databases. Results and Conclusions: The results showed that previous research used a variety of indicators to capture learners' SRL. Most of these indicators are related to time management skills, such as indicators of engagement, regularity, and anti‐procrastination. Furthermore, the study found that the majority of the reviewed studies did not validate the proposed measurements based on any theoretical models. This highlights the importance of fostering closer collaboration between learning analytics and learning science to ensure the extracted indicators accurately represent students' learning processes. Moreover, this collaboration can enhance the validity and reliability of data‐driven approaches, ultimately leading to more meaningful and impactful educational interventions. Lay Description: What is already known about this topic?: Measuring students' self‐regulation skills is essential for understanding their learning approaches and identifying areas requiring further support.Traditionally, questionnaires and interviews have been used to measure learners' self‐regulation; however, these methods rely on students' own views, which can sometimes be unreliable.Recently, there has been more interest in using learning analytics to measure students' self‐regulation based on data extracted from their online activities. What this paper adds?: This paper systematically analyses how previous studies used learning analytics to measure students' self‐regulation in higher education.It examines how these measurements were validated. Implications for practise and/or policy: More collaboration is needed between researcher in learning science and learning analytics is essential to ensure that the metrics and methods developed are not only theoretically sound but also practically relevant. This collaboration ultimately contributes to the design of enhanced learning experiences and outcomes. [ABSTRACT FROM AUTHOR]

This paper introduces a novel three‐phase grid‐tied multilevel inverter (MLI) topology that employs a basic unit per phase, yielding a symmetrical configuration capable of generating five‐level output voltage and an asymmetrical configuration producing seven‐level and nine‐level output voltages. The generalization of the proposed MLI is presented in terms of the number of modules (M) and output levels (L). A comprehensive comparative analysis of the proposed MLI topology against existing configurations is presented for both symmetric and asymmetric cases. The switching devices in the MLI are controlled using the in‐phase disposition level shift PWM (IPD‐LSPWM) technique. The synchronization of the grid‐tied MLI is addressed by considering the uncertainties in grid and load parameters at the point of common coupling (PCC). To achieve synchronization, a PLL‐less grid voltage‐ modulated direct power control (GVM‐DPC) technique is implemented. To mitigate the delay associated with PLL, a GVM‐DPC based on the stationary reference frame (SRF) is applied. This paper also includes mathematical modelling of GVM‐DPC without PLL and the design of an LCL filter. A simulation model of a 15‐kVA, three‐phase, nine‐level grid‐tied MLI is developed in MATLAB/Simulink and tested under both steady‐state and dynamic conditions. The proposed controller's performance is evaluated under the load variations and sudden changes in available power from the distributed generator (DG). Robustness is tested under adverse conditions such as voltage sag/swell at the PCC. Furthermore, the system is implemented in the OPAL‐RT OP4510 real‐time simulator, and the results are validated to confirm the effectiveness and robustness of the proposed grid‐tied MLI. [ABSTRACT FROM AUTHOR]

Motion prediction has gotten much attention in the past few years. It has endless uses either in real life or in virtual life (gaming). The current dynamic motion prediction models, such as the Markov model, depend only on the object motions' history. They ignore the object's direction and speed, which play a key role in dynamic motion prediction. This paper introduces two new probability density functions (PDFs) for elliptic and ellipsoidal regions. Then, it introduces two new motion prediction models based on the new proposed PDFs. This paper proposes new motion detection models that depend not only on the motion's history but also on moving objects' speed and direction (objects' velocity). Moreover, it integrates the proposed models with the Markov model to attain a more precise prediction. Besides, it introduces several applications for the proposed models. [ABSTRACT FROM AUTHOR]

With the rapid development of machine intelligence, an increasing number of websites and servers have been amicably visited or sometimes attached by intelligent machines intensively. Therefore, how to empower a host machine to intelligently distinguish intelligent machines from humans is a challenging work. In this paper, the Mirror Turing Test (MTT) is conceived and implemented. Unlike the standard Turing Test, the tester in the MTT is replaced by a machine instead of a human. Current advancements on deep learning enable machines to recognize subtle differences between genuine and counterfeit works. Sometimes, the ability of machines is even superior to that of humans. Will machines transcend humans in an irreversible trend? Not completely right. The detection of soul in an artwork remains far beyond the capacity of machines. The two sets of MTT based on poetry generated by a machine and a novel imitated by a human were conducted in this paper and neither of them passed the MTT. Poetry is one of the art forms in which authors reveal their souls. Thus, we chose poetry in the MTT experiments on the basis of our soul computing model, thus clearly discriminating machine from human. [ABSTRACT FROM AUTHOR]

This paper presents a method for determining the transmission efficiency of a gear reducer. The proposed method contains an identification theory to derive a dynamical model of motors. Using the identification theory, we propose a method to measure the torque transmission efficiency of the gear reducer. The identification theory is derived from the error between input and output data of the mathematical model of a target plant and actual time series data of the plant by an experiment. The dynamic characteristics of the gear reducer are calculated by identification theory for a system installing the motors. The target plant means a motor or a combined system consisting of the motor and the gear reducer. We discuss the torque constant as one parameter that determines motor characteristics. The torque constant value of the motor can be determined using the identification theory. Then, the torque transmission efficiency of the gear reducer can be decided by the torque constant value. In this paper, we first explain the algorithm of the identification theory, second discuss the results of identifying the motor torque constant, and finally examine the transmission efficiency of the gear reducer in the experiment. [ABSTRACT FROM AUTHOR]

This paper reviews current numerical developments for atmospheric modelling. Numerical atmospheric modelling now looks back to a history of about 70 years after the first successful numerical prediction. Currently, we face new challenges, such as variable and adaptive resolution and ultra-highly resolving global models of 1 km grid length. Large eddy simulation (LES), special applications like the numerical prediction of pollution and atmospheric contaminants belong to the current challenges of numerical developments. While pollution prediction is a standard part of numerical modelling in case of accidents, models currently being developed aim at modelling pollution at all scales from the global to the micro scale. The methods discussed in this paper are spectral elements and other versions of Local-Galerkin (L-Galerkin) methods. Classic numerical methods are also included in the presentation. For example, the rather popular second-order Arakawa C-grid method can be shown to result as a special case of an L-Galerkin method using low-order basis functions. Therefore, developments for Galerkin methods also apply to this classic C-grid method, and this is included in this paper. The new generation of highly parallel computers requires new numerical methods, as some of the classic methods are not well suited for a high degree of parallel computing. It will be shown that some numerical inaccuracies need to be resolved and this indicates a potential for improved results by going to a new generation of numerical methods. The methods considered here are mostly derived from basis functions. Such methods are known under the names of Galerkin, spectral, spectral element, finite element or L-Galerkin methods. Some of these new methods are already used in realistic models. The spectral method, though highly used in the 1990s, is currently replaced by the mentioned local L-Galerkin methods. All methods presented in this review have been tested in idealized numerical situations, the so-called toy models. Waypoints on the way to realistic models and their mathematical problems will be pointed out. Practical problems of informatics will be highlighted. Numerical error traps of some current numerical approaches will be pointed out. These are errors not occurring with highly idealized toy models. Such errors appear when the test situation becomes more realistic. For example, many tests are for regular resolution and results can become worse when the grid becomes irregular. On the sphere no regular grids exist, except for the five derived from Platonic solids. Practical problems beyond mathematics on the way to realistic applications will also be considered. A rather interesting and convenient development is the general availability of computer power. For example, the computational power available on a normal personal computer is comparable to that of a supercomputer in 2005. This means that interesting developments, such as the small sphere atmosphere with a resolution of 1 km and a spherical circumference between 180 and 360 km are available to the normal owner of a personal computer (PC). Besides the mathematical problems of new approaches, we will also consider the informatics challenges of using the new generation of models on mainframe computers and PCs. [ABSTRACT FROM AUTHOR]

This paper develops a new method for analyzing the relationship between a set of points and another single point, the latter of which we call a reference point. This relationship has been discussed in various academic fields, such as geography, criminology, and epidemiology. Analytical methods, however, have not yet been fully developed, which has motivated this paper. Our method reveals how the number of points varies by the distance from a reference point and by direction. It visualizes the spatial pattern of points in relation to a reference point, describes the point pattern using mathematical models, and statistically evaluates the difference between two sets of points. We applied the proposed method to analyze the spatial pattern of the climbers of Mt. Azuma, Japan. The result gave us useful and interesting findings, indicating the method's soundness. [ABSTRACT FROM AUTHOR]

This paper introduces an autonomous robot designed for in-pipe structural health monitoring of oil/gas pipelines. This system employs a 3D Optical Laser Scanning Technical Vision System (TVS) to continuously scan the internal surface of the pipeline. This paper elaborates on the mathematical methodology of 3D laser surface scanning based on dynamic triangulation. This paper presents the mathematical framework governing the combined kinematics of the Mobile Robot (MR) and TVS. It discusses the custom design of the MR, adjusting it to use of robustized mathematics, and incorporating a laser scanner produced using a 3D printer. Both experimental and theoretical approaches are utilized to illustrate the formation of point clouds during surface scanning. This paper details the application of the simple and robust mathematical algorithm RANSAC for the preliminary processing of the measured point clouds. Furthermore, it contributes two distinct and simplified criteria for detecting defects in pipelines, specifically tailored for computer processing. In conclusion, this paper assesses the effectiveness of the proposed mathematical and physical method through experimental tests conducted under varying light conditions. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to discuss heuristics, guided by Parse's (2021a) community model, to understand how health policies emerge from the unique values and beliefs of community constituents. Within this paper, there is a discussion about heuristics, health policy, Parse's humanbecoming paradigm, and policy implications reflected upon with the change concepts of the humanbecoming community model. [ABSTRACT FROM AUTHOR]

Background: Competent clinical reasoning forms the foundation for effective and efficient clinical swallowing examination (CSE) and consequent dysphagia management decisions. While the nature of initial CSEs has been evaluated, it remains unclear how new information gathered by speech–language therapists (SLTs) throughout a patient's acute‐care journey is integrated into their initial clinical reasoning and management processes and used to review and revise initial management recommendations. Aims: To understand how SLTs' clinical reasoning and decision‐making regarding dysphagia assessment and management evolve as patients transition through acute hospital care from referral to discharge. Methods & Procedures: A longitudinal, qualitative approach was employed to gather information from two SLTs who managed six patients at a metropolitan acute‐care hospital. A retrospective 'think‐aloud' protocol was utilized to prompt SLTs regarding their clinical reasoning and decision‐making processes during initial and subsequent CSEs and patient interactions. Three types of concept maps were created based on these interviews: a descriptive concept map, a reasoning map and a hypothesis map. All concept maps were evaluated regarding their overall structure, facts gathered, types of reasoning engaged in (inductive versus deductive), types of hypotheses generated, and the diagnosis and management recommendations made following initial CSE and during subsequent dysphagia management. Outcomes & Results: Initial CSEs involved a rich process of fact‐gathering, that was predominantly led by inductive reasoning (hypothesis generation) and some application of deductive reasoning (hypothesis testing), with the primary aims of determining the presence of dysphagia and identifying the safest diet and fluid recommendations. During follow‐up assessments, SLTs engaged in increasingly more deductive testing of initial hypotheses, including fact‐gathering aimed at determining the tolerance of current diet and fluid recommendations or the suitability for diet and/or fluid upgrade and less inductive reasoning. Consistent with this aim, SLTs' hypotheses were focused primarily on airway protection and medical status during the follow‐up phase. Overall, both initial and follow‐up swallowing assessments were targeted primarily at identifying suitable management recommendations, and less so on identifying and formulating diagnoses. None of the patients presented with adverse respiratory and/or swallowing outcomes during admission and following discharge from speech pathology. Conclusions & Implications: Swallowing assessment and management across the acute‐care journey was observed as a high‐quality, patient‐centred process characterized by iterative cycles of inductive and deductive reasoning. This approach appears to maximize efficiency without compromising the quality of care. The outcomes of this research encourage further investigation and translation to tertiary and post‐professional education contexts as a clear understanding of the processes involved in reaching diagnoses and management recommendations can inform career‐long refinement of clinical skills. WHAT THIS PAPER ADDS: What is already known on the subject: SLTs' clinical reasoning processes during initial CSE employ iterative cycles of inductive and deductive reasoning, reflecting a patient‐centred assessment process. To date it is unknown how SLTs engage in clinical reasoning during follow‐up assessments of swallowing function, how they assess the appropriateness of initial management recommendations and how this relates to patient outcomes. What this paper adds to the existing knowledge: Our longitudinal evaluation of clinical reasoning and decision‐making patterns related to swallowing management in acute care demonstrated that SLTs tailored their processes to each patient's presentation. There was an emphasis on monitoring the suitability of the initial management recommendations and the potential for upgrade of diet or compensatory swallowing strategies. The iterative cycles of inductive and deductive reasoning reflect efficient decision‐making processes that maintain high‐quality clinical care within the acute environment. What are the potential or actual clinical implications of this work?: Employing efficient and high‐quality clinical reasoning is a hallmark of good dysphagia practice in maximizing positive patient outcomes. Developing approaches to understanding and making explicit clinical reasoning processes of experienced clinicians may assist SLTs of all developmental stages to provide high standards of care. [ABSTRACT FROM AUTHOR]

The methodology used for analyzing the survival process should keep in mind heterogeneity in empirical data. Cross-sectional data are more heterogeneous in comparison with birth-cohort data. [ABSTRACT FROM AUTHOR]

In order to fulfill the practical application demands of precisely localizing underwater vehicles using passive electric field localization technology, we propose a scalar-potential-based method for the passive electric field localization of underwater vehicles. This method is grounded on an intelligent differential evolution algorithm and is particularly suited for use in three-layer and stratified oceanic environments. Firstly, based on the potential distribution law of constant current elements in a three-layer parallel stratified ocean environment, the mathematical positioning model is established using the mirror method. Secondly, the differential evolution (DE) algorithm is enhanced with a parameter-adaptive strategy and a boundary mutation processing mechanism to optimize the key objective function in the positioning problem. Additionally, the simulation experiments of the current element in the layered model prove the effectiveness of the proposed positioning method and show that it has no special requirements for the sensor measurement array, but the large range and moderate number of sensors are beneficial to improve the positioning effect. Finally, the laboratory experiments on the positioning method proposed in this paper, involving underwater simulated current elements and underwater vehicle tracks, were carried out successfully. The results indicate that the positioning method proposed in this paper can achieve the performance requirements of independent initial value, strong anti-noise capabilities, rapid positioning speed, easy implementation, and suitability in shallow sea environments. These findings suggest a promising practical application potential for the proposed method. [ABSTRACT FROM AUTHOR]

Active disturbance rejection control (ADRC) is widely used in airborne optoelectronic stabilization platforms due to its minimal reliance on the mathematical model of the controlled object. The extended state observer (ESO) is the core of ADRC, which treats internal parameter variations and external disturbances as total disturbances, observes the disturbances as extended states, and then compensates them into the control loop to eliminate their effects. However, the ESO can only achieve a precise estimation of constant or slowly varying disturbances. When the disturbance is periodically changing, satisfactory results cannot be obtained. In this paper, a generalized high-order extended state observer (GHOESO) is proposed to achieve the precise estimation of known frequency sinusoidal disturbance signals and improve disturbance suppression levels. Through numerical simulations, a traditional ESO and GHOESO are compared in terms of disturbance observation capability and disturbance suppression ability for single and compound disturbances based on our prior knowledge of disturbance frequency. The effectiveness of the proposed GHOESO method is verified. Finally, the algorithm is applied to an airborne optoelectronic stabilization platform for a 1°/1 Hz swing experiment on a space hexapod swing table. The experimental results demonstrate the superiority of the GHOESO proposed in this paper. [ABSTRACT FROM AUTHOR]

This paper explores general coupled dynamic equations on time scales with multiple delays and investigates the existence of periodic solutions using the coincidence degree theory approach. The model studied includes the mathematical models of Nicholson, Mackey–Glass, and Lasota–Wazewska as special cases. Furthermore, we demonstrate that the solutions are not only asymptotically stable but also exponentially synchronized. The presented results significantly extend and complement existing findings in the field. The paper concludes with illustrative examples that highlight the practical implications of our analytical discoveries. [ABSTRACT FROM AUTHOR]

The class of generalized S D D 1 (G S D D 1 ) matrices is a new subclass of H -matrices. In this paper, we focus on the subdirect sum of G S D D 1 matrices, and some sufficient conditions to ensure that the subdirect sum of G S D D 1 matrices with strictly diagonally dominant (S D D) matrices is in the class of G S D D 1 matrices are given. Moreover, corresponding examples are given to illustrate our results. The class of generalized matrices is a new subclass of -matrices. In this paper, we focus on the subdirect sum of matrices, and some sufficient conditions to ensure that the subdirect sum of matrices with strictly diagonally dominant matrices is in the class of matrices are given. Moreover, corresponding examples are given to illustrate our results. [ABSTRACT FROM AUTHOR]

Economic globalization and the rapid development of the Internet make logistics systems more and more diversified, people and enterprises have greatly increased their requirements for logistics systems, and fourth party logistics has received more and more attention from people and related enterprises. In order to further study the routing problem under uncertain stochastic environments, this paper considers the fourth party logistics routing problem from a single manufacturer to multiple distributors with uncertain times and random supplies under the complete information symmetry scenario and symmetric transportation volume decision space. Then, an uncertain stochastic programming model is established with the minimum total cost as its core objective, and the total transportation time, manufacturer's supply, and distributor's demand as constraints. In order to solve the optimal path of the above problems, this paper transforms the uncertain stochastic programming model into a classical mathematical programming model based on the distribution functions of uncertain time and random supply. Finally, two numerical examples are given to verify the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

This paper presents the numerical solution of the heat conduction model with a fractional derivative of the Riemann–Liouville type with respect to the spatial variable. The considered mathematical model assumes the dependence on temperature of the material parameters (such as specific heat, density, and thermal conductivity) of the model. In the paper, the boundary conditions of the first and second types are considered. If the heat flux equal to zero is assumed on the left boundary, then the thermal symmetry is obtained, which results in a simplification of the problem and the possibility of considering only half the area. The numerical examples presented in the paper illustrate the effectiveness and convergence of the discussed computational method. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study is to investigate the pesticide safety behaviours and related factors among cabbage farmers in Kalaw Township, Myanmar. Background: Unsafe chemical pesticide practices affect farmers' health and the environment. Understanding pesticide safety behaviours is necessary for healthcare providers to protect agriculture workers against unwanted adverse health effects. Methods: The cross‐sectional study was conducted among 195 cabbage farmers from March to May 2019. Safety behaviours and factors applied in the PRECEDE–PROCEDE model as a framework were assessed using questionnaires. Bivariate and multivariate logistic regression was applied to identify any associations. Results: Altogether, 72.1% of the farmers had a low level of safety behaviours. Goggles and masks were rarely used before and during pesticide applications. All of the farmers experienced adverse health effects after using pesticides. The attitudes toward pesticide poisoning; support from family, co‐workers and healthcare providers; and the availability of personal protective equipment were significantly associated with safety behaviours. Conclusion: Our data provide novel empirical evidence for an opportunity to design effective nursing interventions to promote pesticide safety behaviours among Myanmar agricultural workers. Nurses should pay more attention to promoting comprehensive interventions to reduce both exposure and health effects among agricultural workers through the involvement of supported stakeholders. Summary statement: What is already known about this topic? Farmers and agricultural workers have extensively used pesticides in all steps of cultivation and face a greater risk of pesticide exposure, which could result in adverse health effects.Owing to the lack of research on community health promotion conducted in Myanmar, the burden of the consequences and adverse effects of pesticides remains a significant health issue. What this paper adds? Findings reveal a clear framework for better understanding and assessing pesticide safety behaviours among agricultural workers and farmers in Myanmar.Findings contribute new knowledge for nursing community health promotion by enhancing understanding of multilevel factors, including international and external factors, associated with safety behaviours among agricultural workers and farmers. The implications of this paper: Nurses and other healthcare professionals should be aware of the importance of preventing adverse health effects among agricultural workers in the community and interventions aimed at promoting safety behaviours should be focused not only on individuals but also on the involvement of social supports—particularly family and co‐workers.Nursing policymakers should consider strengthening the nursing role in the recognition of pesticide risk exposure and health outcomes, management of pesticide poisoning and exposure and prevention of pesticide‐related health conditions both in nursing education and nursing practice.Local authorities and policymakers should focus their attention on health promotion and health services to promote safety behaviours when using pesticides, and treatment and extension services should be provided for cases of suspected pesticide poisoning. [ABSTRACT FROM AUTHOR]

The issues of the evaluation and prediction of the reliability and testability of mining machinery and equipment are becoming particularly relevant, since the safety of technological processes and human life is reaching a new level of realisation due to changes in mining technology. The work is devoted to the development of a logical model for analysing the controllability of mining equipment. The paper presents a model of reliability of the operation of mining equipment on the example of a mine load and passenger hoist. This generalised model is made in the form of a graph of transitions and supplemented with a system of equations. The model allows for the estimation of the reliability of equipment elements and equipment as a whole. A mathematical and logical model for the calculation of the availability and downtime coefficients of various designs of mining equipment systems is proposed. This model became the basis for the methods to calculate the optimal values of diagnostic depth. At these calculated values, the maximum value of availability factor will be obtained. In this paper, an analytical study was carried out and dependences of the readiness factor of parameters of the investigated system such as the intensity of control of technical systems, intensity of failures, etc., were constructed. The paper proposes a mathematical model to assess the reliability of mine hoisting plants through its integration into the method of improving the reliability of mine hoisting plants. [ABSTRACT FROM AUTHOR]

In this paper, we obtain the existence of at least two standing waves (and homoclinic solutions) for a class of time-dependent (and time-independent) discrete nonlinear Schrödinger systems or equations. The novelties of the paper are as follows. (1) Our nonlinearities are composed of three mixed growth terms, i.e., the nonlinearities are composed of sub-linear, asymptotically-linear and super-linear terms. (2) Our nonlinearities may be sign-changing. (3) Our results can also be applied to the cases of concave-convex nonlinear terms. (4) Our results can be applied to a wide range of mathematical models. [ABSTRACT FROM AUTHOR]

In this paper, we consider the Cumulative Capacitated Vehicle Routing Problem (CCVRP), which is used to model many real-world applications, especially in the area of supplying humanitarian aid after a natural disaster. Interestingly, in this study, Unmanned Aerial Vehicles (UAVs) so-called drones are used to assist the trucks in delivering parcels to customers. Each of them travels to different locations to perform specified tasks and meet periodically with the vehicle from which it takes off to swap its battery. In this paper, a mathematical model is formulated which is then tested with small-sized problems using CPLEX software. Due to the difficulty of solving large instances to optimality, we propose a heuristic algorithm based on a well-established type of cluster-first, route-second approach. Then, it is enhanced by some proposed properties. Hereafter, we develop a minimum spanning tree based-lower bound. Finally, extensive computational experiments are carried out by using instances from the literature. They show the good performance of the proposed heuristic algorithm to solve large instances in a very competitive running time. [ABSTRACT FROM AUTHOR]

Introduction: Many Covid‐19 survivors are living with unresolved, relapsing and remitting symptoms and no 'one size' of treatment is likely to be effective for everyone. Supported self‐management for the varied symptoms of Long Covid (LC) is recommended by the National Institute for Health and Care Excellence in the United Kingdom. We aimed to develop a new personalised support intervention for people living with LC using a structured co‐design framework to guide replication and evaluation. Methods: We used the improvement methodology, Experience‐Based Co‐Design, in an accelerated form to harness the collective experiences of people with LC. Incorporating evidence from 'Bridges Self‐Management' (Bridges) an approach in which healthcare professionals (HCPs)are trained to support knowledge, confidence and skills of individuals living with long term conditions. Co‐designed resources are also central to Bridges. Adults who self‐identified as living with or recovered from LC, from England or Wales, aged 18 years and over were recruited, and HCPs, with experience of supporting people with LC. Participants took part in a series of small co‐design group meetings and larger mixed meetings to agree priorities, core principles and generate resources and intervention content. Results: People with LC (n = 28), and HCPs (n = 9) supported co‐design of a book (hard‐copy and digital form) to be used in 1:1 support sessions with a trained HCP. Co‐design stages prioritised stories about physical symptoms first, and psychological and social challenges which followed, nonlinear journeys and reconceptualising stability as progress, rich descriptions of strategies and links to reputable advice and support for navigating healthcare services. Co‐design enabled formulation of eight core intervention principles which underpinned the training and language used by HCPs and fidelity assessments. Conclusion: We have developed a new personalised support intervention, with core principles to be used in one‐to‐one sessions delivered by trained HCPs, with a new co‐designed book as a prompt to build personalised strategies and plans using narratives, ideas, and solutions from other people with LC. Effectiveness and cost effectiveness of the 'LISTEN' intervention will be evaluated in a randomised controlled trial set within the context of the updated Framework for Developing and Evaluating Complex Interventions. Patient and Public Contribution: The LISTEN Public and Patient Involvement (PPI) group comprised seven people living with LC. They all contributed to the design of this study and five members were part of a larger co‐design community described in this paper. They have contributed to this paper by interpreting stages of intervention design and analysis of results. Three members of our PPI group are co‐authors of this paper. [ABSTRACT FROM AUTHOR]

This paper presents a centralized disturbance suppression strategy for distributed drive electric vehicles which is based on model predictive direct motion control. This strategy is capable of addressing issues such as parameter uncertainties and external disturbances in vehicles. Firstly, the paper provides a brief introduction to model predictive direct motion control. Secondly, it analyzes the impact of vehicle parameter uncertainties and external disturbances on the mathematical model. Finally, a centralized disturbance suppression strategy based on a sliding mode observer is proposed. Simulation results demonstrate that this strategy exhibits excellent disturbance rejection capabilities. [ABSTRACT FROM AUTHOR]