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Paper was one of the greatest inventions in ancient China, and it greatly promoted the rapid development of human civilization. Even in today's electronic information age, paper and paper‐derived products are still indispensable to people's daily work and life. However, the traditional paper based on cellulose fibers from plants has some problems. For instance: (1) papermaking consumes a large amount of precious natural resources such as trees; (2) the papermaking industry causes environmental pollution; (3) the traditional paper consisting of organic cellulose fibers is highly flammable and easy to burn; (4) the traditional paper based on cellulose fibers turns to yellow color with time; (5) the lifetime of the traditional paper is relatively short because of the degradation of cellulose fibers. More efforts are needed to investigate and solve these problems facing the traditional paper. In recent years, a new kind of multifunctional fire‐resistant paper based on ultralong hydroxyapatite nanowires has been developed and investigated for various applications, and many research findings have been documented in the literature. This review article provides a comprehensive summary and discussion on recent research advances for this new kind of multifunctional fire‐resistant paper based on ultralong hydroxyapatite nanowires, including the synthesis, properties, applications, and future perspectives. [ABSTRACT FROM AUTHOR]

This paper proposes a new hybrid control strategy to solve the problem of bidirectional wide voltage range regulation in CLLC converters. On the (LLC) side (G2V direction), the SSSA control method is employed for voltage boost, combined with bus voltage and burst control to achieve wide voltage regulation. On the (C) side (V2G direction), the SSSA and full/half‐bridge mode switching control are used to achieve V2G direction wide voltage regulation. This hybrid control strategy also enables high conversion efficiency in both directions without the need for additional components to reduce the converter power density. This is particularly suitable for OBC applications with strict requirements for converter volume and weight. A detailed analysis with mathematical derivation, hybrid control strategy, and converter operation principles is introduced in this paper. The following subchapters supplement the converter voltage gain, soft switching implementation conditions, and design considerations. Finally, the feasibility of the proposed control strategy was verified through an experimental prototype with an input voltage ranging from 340 to 430 V to an output voltage ranging from 225 to 450 V and bidirectional rated power of 6.6/3.3 kW. This prototype achieved a maximum conversion efficiency of 97.7% in the G2V direction and 97.1% in the V2G direction. [ABSTRACT FROM AUTHOR]

This paper proposes a method for detecting the angle of a bearingless motor with less magnetic interference due to the current. Bearingless motors have suspension windings and motor windings that generate leakage flux. Owing to this electromagnetic phenomenon, the signal of the linear Hall‐effect sensor for angle detection is disturbed, and it has to be avoided to place Hall sensors near the winding conventionally. To solve this interference problem, this paper clarifies the ideal combinations between sensor positions and the number of poles and slots of concentrated winding bearingless motors. [ABSTRACT FROM AUTHOR]

In order to solve the huge impact of the digital information age on many technical and industrial fields, a periodic fast search genetic algorithm is proposed. Based on the reconnaissance mission, this paper introduces the common allocation strategy into mission planning, and constructs the mathematical model of multi unmanned aerial vehicle (UAV) cooperative reconnaissance mission planning decision‐making. The proposed periodic fast search genetic algorithm is used to solve the problem of multi UAV cooperative reconnaissance mission planning. In 2020, the industry growth rate of global UAV technology expenditure was as high as 30.6%, and the compound growth rate of UAV in China reached 63.5%, which is enough to see the great prospect of the integrated development of UAV technology and different industries. The experiment evaluates the log verification module of UAV by comparing the two data structures of Merkle tree and linear, and the time and memory overhead of storing and verifying logs, which shows the effectiveness of the log verification scheme in this paper. [ABSTRACT FROM AUTHOR]

A recent paper (Zhang R, Yu X. Traveling waves for a four‐compartment lattice epidemic system with exposed class and standard incidence. Math Meth Appl Sci. 2022; 45: 113‐136) presented a four‐compartment lattice epidemic system with exposed class and standard incidence. The authors studied the existence and non‐existence of traveling wave solutions of this system. However, the limit behavior of R$$ R $$‐component of traveling wave solutions is still open. In this paper, we solve this open problem and establish the boundedness of traveling wave solutions by analysis technique. Meanwhile, we study the non‐existence of traveling wave solutions with non‐positive wave velocity. [ABSTRACT FROM AUTHOR]

Summary: This paper sets out new recommendations for recording structural iron nails. Despite their ubiquity, iron nails have received limited analytical and interpretative attention and recording practices are highly variable. Too often current recording is time‐consuming and costly without providing meaningful information. This paper proposes a new recording methodology, developed through analysis of the Roman structural nail assemblage from the MHI A14 Cambridge‐Huntingdon excavations alongside experiments in nail shaping, with wider context provided by medieval and post‐medieval assemblages from the City of London. This approach includes a new nail typology, recommendations for bulk recording of basic details for whole assemblages (using counts and typologies), alongside detailed recording (shank morphology and further metric data) for certain nail groups. Shank morphology is a particularly important aspect proposed here, being indicative of how nails were used in antiquity. [ABSTRACT FROM AUTHOR]

Extracting balanced geostrophic motions (BM) from sea surface height (SSH) observations obtained by wide‐swath altimetry holds great significance in enhancing our understanding of oceanic dynamic processes at submesoscale wavelength. However, SSH observations derived from wide‐swath altimetry are characterized by high spatial resolution while relatively low temporal resolution, thereby posing challenges to extract the BM from a single SSH snapshot. To address this issue, this paper proposes a deep learning model called the BM‐UBM Network, which takes an instantaneous SSH snapshot as input and outputs the projection corresponding to the BM. Training experiments are conducted both in the Gulf Stream and South China Sea, and three metrics are considered to diagnose model's outputs. The favorable results highlight the potential capability of the BM‐UBM Network to process SSH measurements obtained by wide‐swath altimetry. Plain Language Summary: Oceanic dynamic processes can be classified into two categories: balanced geostrophic motions (BM), including large‐scale circulation, mesoscale and submesoscale eddy turbulence, and unbalanced wave motions (UBM), including barotropic tides, and inertia–gravity waves (IGWs). Both types of motions coexist and have respective contributions to the sea surface height (SSH). How to extract the BM from the total SSH observations obtained by satellite altimetry is the crucial problem to be solved in this paper. To tackle this issue, we propose a deep learning model named the BM‐UBM Network to establish the relationship between the total SSH and the BM component. The BM‐UBM Network can generate SSH estimations for the BM when provided with a well‐resolved SSH snapshot. Key Points: A Deep learning model is developed to extract balanced motions from sea surface height snapshot based on a realistic simulationDiagnostics of three metrics reveal the effectiveness of the model in extracting balanced motionsThe model exhibits remarkable advantages over the Gaussian filter (baseline) in capturing the gradient and Laplacian information [ABSTRACT FROM AUTHOR]

This paper designs a new facial Expression recognition network called a multi‐scale feature Fusion Convolutional neural Network (EFCN). This network is proposed to solve two problems in the facial expression recognition task. First, there are many commonalities between faces of different expression categories, and the recognition task cannot be precisely performed when the commonality is greater than the individuality. Secondly, facial detail features have a significant impact on the final results of expression recognition, while the image detail features extracted by traditional convolutional neural networks are not sufficient. In order to address the above issues, the feature enhancement network (FEN) and the detail information enhancement module (DEM) are designed. The FEN fuses deep and shallow features. Accordingly, the feature map contains richer information, making it easy to identify the samples. The DEM extracts and fuses the features passed by the backbone network with multi‐scale features to enhance the network's ability to extract features from small regions of the face. We validated the proposed method on three datasets, RAF‐DB, CK+, and JAFFE, and achieved 84.50%, 97.86%, and 91.05% accuracy, respectively, and the experimental results showed the effectiveness of the proposed method in this paper. For example, on the JAFFE dataset, the recognition accuracy of this method surpasses the MLT method by 1.87%. [ABSTRACT FROM AUTHOR]

William P. Alston argues in "Expressing" (1965) that there is no important difference between expressing a feeling in language and asserting that one has that feeling. My aims in this paper are (1) to show that Alston's arguments ought to have led him to a different conclusion—that "asserting" and "expressing" individuate speech acts at different levels of analysis (the illocutionary and the locutionary, respectively)—and (2) to argue that this conclusion can solve a problem facing contemporary analyses of expressing: the "no show tell" problem, or the problem of accounting for utterances that report feelings truly without expressing them. Alston's paper made an important contribution 50 years ago, and a reimagining of it can make another important contribution today. [ABSTRACT FROM AUTHOR]

Organizations are confronted with quality failures that must be addressed. Often, statistical methods can be helpful, but the organization lacks an internal statistician. This paper explores the use of a statistical problem‐solving team using Six Sigma professionals as problem‐solving team leaders, trainers, and coaches. A case study methodology is used. The actions and events from the implementation of a statistical problem‐solving team in a global manufacturing organization in the automotive industry through the first decade after implementation are described. Statistical problem‐solving bridges the gap between engineer and statistician using engineers trained to awareness‐level knowledge of statistics and supported by Six Sigma Master Black Belts. The statistical problem‐solving team members need to be highly trained in the three pillars of statistical problem‐solving: Key statistical concepts, key statistical analysis, and the key test method as well as a solid foundation in quality tools. This paper provides a unique view of a global problem‐solving team using both Six Sigma tools and methods and the 8D process as a problem‐solving methodology. [ABSTRACT FROM AUTHOR]

Open math problem solving is critical to help students deepen the understanding and promote transfer of mathematics knowledge. However, the cognitive mechanism for open math problem solving, particularly the role of spatial abilities, has not been paid enough attention. This study recruited 192 junior middle school students (14.30 ± 0.48 years old). Results showed that both spatial visualisation (measured by paper folding) and spatial working memory (measured by spatial 2‐back) significantly associated with open math problem solving with controlled variables including age, sex, nonverbal matrix reasoning, and arithmetic principles. Moreover, spatial working memory was more associated with easy open math problem solving, while spatial visualisation more associated with difficult open math problem solving. These findings suggested that as the difficulty of open math problems increased, the construction of problem space mattered more than retaining and updating problem space in open math problem solving. [ABSTRACT FROM AUTHOR]

The objective of this study is to explore new ways of assessing collaborative problem solving (CPS) processes based on different modalities of audio data and their combination. The data collection took place in an educational lab setting during an experiment with adult teams from professional contexts who collaboratively solved multiple problems as part of a CPS training. From audio data, both verbal (ie, speech) and non‐verbal (ie, pitch) aspects were extracted. Four analysis methods were used, including (a) content analysis; (b) linguistic inquiry and word count; (c) verbal entrainment analysis; and (d) acoustic–prosodic entrainment based on pitch data. Insights are given into the CPS processes of the participating groups using these measures and relevant relationships between some of these measures are further investigated. Based on content analysis, it was found that most of the interactions during the CPS process are task oriented, whereas team‐oriented interactions are less present. Second, three measures of proportion of contribution in CPS were investigated and clear differences in participation patterns between and within teams were found. We suggest that a combination of utterance count and words per sentence could provide valuable insights for quantity and equality of participation. Third, the study explored pronoun use and found that the most frequently used personal pronouns were first‐person singular. Next, the results indicated a relationship between pronoun use and the relative frequency of interactions. Fourth, a rather weak relationship between lexical entrainment measures and the acoustic–prosodic measures were found, suggesting that these measures are indicative of separate communicative aspects in CPS. This study contributes to a better understanding of which type of audio‐based data is most informative to teachers and students as a feedback or assessment tool. This study complements previous research as it focuses on spoken human‐to‐human communication collected in an authentic context. Practitioner notesWhat is already known about this topic Support and guidance systems for learning coaches, teachers and learners are needed to foster the educational quality of collaborative problem solving (CPS) activities.CPS is a complex process and measuring the quality of CPS processes remains challenging.Multimodal learning analytics, focusing on verbal and non‐verbal data sources and using content analysis, linguistic inquiry and word count and verbal and acoustic entrainment measures could be valuable to measure the quality of CPS.What this paper adds The majority of interactions during CPS processes are task oriented or cognitive of nature, whereas team‐oriented interactions are less present.Utterance count and words per sentence should be used in combination, as they are indicative of different aspects.Pronoun use in learners' discourse is related to the types of CPS interactions.Lexical entrainment measures and acoustic–prosodic are indicative of distinctive communicative aspects in CPS.Implications for practice and/or policy Quality indicators of CPS processes should include both verbal and non‐verbal measures of students' interactions.Educational researchers and the (Edtech) industry should further leverage their forces to foster the development of (semi‐)automated systems for measuring the quality of CPS processes.It should be further investigated how quality indicators of CPS processes can be most meaningful to trainers, teachers and learners, for example, through the use of dashboards. [ABSTRACT FROM AUTHOR]

The cascaded H‐bridge (CHB) converter can achieve rich functions, such as active rectification, active power filtering, distributed energy storage, etc. The control of the CHB converter is a multiobjective optimization problem. Finite control set model predictive control (FCS‐MPC) is an effective method developed in recent years to solve this problem. However, because of the large amount of calculation, traditional FCS‐MPC cannot be directly used to control the multilevel CHB converter. It is also difficult to tune the weighting factors in traditional FCS‐MPC. To solve these problems, this paper proposes an improved sequential MPC (IS‐MPC) method for the CHB converter. The proposed method divides the control objectives of the CHB converter into different layers according to their priorities and the control degrees of freedom of each layer can be adjusted according to the system state. Simulation and hardware‐in‐the‐loop (HIL) implementation on a three‐phase 7‐level CHB converter shows that the proposed method can effectively control the ac current and submodule voltage of the CHB converter and reduce the switching loss. Moreover, it significantly reduced the calculation burden of traditional FCS‐MPC, and the use of the weighting factors is also avoided. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Background: Game‐based learning can frame problem‐solving as a sense‐making experience with domain‐specific tasks for school students. However, multiple challenges arise when trying to support learners in such a complex, problem‐oriented learning environment. Objectives and Methods: With an architecture‐themed mathematics learning game, we conducted two mixed‐method studies to explore the impact and design of game‐based mathematical experience on the math problem‐solving performance of middle school students. Results and Conclusions: The study findings suggested a positive impact of game‐based math experience on math problem‐solving for middle school students. Problematization‐oriented game‐based math tasks with structuring features enhanced students' reasoning with problems and channelled it to doing mathematics. Takeaways: The current research findings support the initiative to frame learning as a sense‐making experience with domain‐specific tasks and inform the design of game‐based mathematical experience and learning support. Lay Description: What is already known about this topic: Realistic mathematical practices frame learning as a sense‐making experience.Challenges arise when involving learners in realistic mathematical experiences driven by domain‐specific tasks. What this paper adds: Game‐based simulation of math tasks framed learning as sense‐making experience.Game‐based math experiencing promoted math contextual problem‐solving performance.Structuring features enhanced problematized experiencing with math tasks. Implications for practice and/or policy: Teachers can integrate and facilitate game‐based math experiencing in class.Efforts should be made to make game‐based math tasks meaningful for students. [ABSTRACT FROM AUTHOR]

In this paper, an observer‐based event‐triggered distributed model predictive control method is proposed for a class of nonlinear interconnected systems with bounded disturbances, considering unmeasurable states. First of all, the state observer is constructed. It is proved that the observation error is bounded. Second, distributed model predictive controller is designed by using observed value. Meanwhile, the event‐triggered mechanism is set by using the error between the actual output and the predicted output. The setting of event‐triggered mechanism not only ensures the error between the actual output and the predicted output within a certain range, but also reduces the calculation amounts of solving the optimization problem. The states of each subsystem enter the terminal invariant set by distributed model predictive control, and then are stabilized in the invariant set under the action of output feedback control law. In addition, sufficient conditions are given to ensure the feasibility of the algorithm and the stability of the closed‐loop system. Finally, the numerical example is given, and the simulation results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Variance estimation is an important aspect in statistical inference, especially in the dependent data situations. Resampling methods are ideal for solving this problem since these do not require restrictive distributional assumptions. In this paper, we develop a novel resampling method in the Jackknife family called the stationary jackknife. It can be used to estimate the variance of a statistic in the cases where observations are from a general stationary sequence. Unlike the moving block jackknife, the stationary jackknife computes the jackknife replication by deleting a variable length block and the length has a truncated geometric distribution. Under appropriate assumptions, we can show the stationary jackknife variance estimator is a consistent estimator for the case of the sample mean and, more generally, for a class of nonlinear statistics. Further, the stationary jackknife is shown to provide reasonable variance estimation for a wider range of expected block lengths when compared with the moving block jackknife by simulation. [ABSTRACT FROM AUTHOR]

Laser cladding technology can obtain a cladding layer with good metallurgical bonding with the substrate and excellent performance. In situ growth of hard phase can effectively solve the problem of uneven distribution of reinforcements directly doped with hard particles. In this paper, 45# steel was adopted as the matrix material, WO3, B4C, Al, and Ni60 powder were used to prepare laser cladding and in situ synthesized WC (Tungsten Carbide) hard phase reinforced Ni‐based cladding layers. The effects of different laser cladding parameters, powder particle size, hard phase content on the microstructures and electrochemical properties of in situ synthesized WC hard phase reinforced Ni‐based cladding layer were analyzed. The results revealed that when the (WO3 + B4C + Al) mixed powder content was 25%, the bulk particles of WC phase in the cladding layer were most uniformly distributed in the cladding layer, which enhances the mechanical properties of the cladding layer. When the B4C particle size was 5 μm, the microhardness of the cladding layer was significantly higher than other cladding layers, and the enhancement mechanism of hardness by B4C is due to the Orowan strengthening caused by too small particle size of B4C. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new method to approximate operators resulted from solving the scattering Problem in electromagnetism by dielectrically coated conducting bodies, using integral equations and high order impedance boundary condition. We introduce the variational Problem and we prove its well‐posedness. After discretization, we find that operators arising from the high‐order impedance boundary conditions are not well‐defined. We present the new theoretical approach and highlight its potential through numerical experiments. [ABSTRACT FROM AUTHOR]

This article introduces a special issue on machine learning (ML) applications in geophysical exploration and monitoring. ML techniques have shown promise in streamlining workflows, extracting insights from large datasets, and solving computational problems in geophysics. The special issue includes 17 papers covering a range of geophysical applications, such as seismic data processing, electromagnetic inversion, and well logging. These papers demonstrate the current state of ML applications in geophysics and highlight challenges and potential directions for future research. The hope is that this special issue will serve as a valuable resource for geophysicists interested in ML techniques and their applications in geophysics. [Extracted from the article]

As the central nervous system of modern information warfare, the command‐and‐control network becomes the brain of command and the strategic target of the enemy's primary attack during the operation. In this paper, a method based on edge extension diagram (EED) and binary decision diagram (BDD) is proposed to evaluate the reliability of connectivity within the basic command post of command‐and‐control network, which is solving the problem that the conventional methods failed to model failure probabilities of node links and with low calculation efficiency. First, graph simplification of network topology, extension of nodes under reliable state, construction of path functions, replacement of associated edges, variable sorting, construction of binary decision graphs, and recursive calculation to evaluate the reliability of the connection between the two ends of the command‐and‐control network. Then, further analyze and sort the variable importance of the command‐and‐control network and analyze the sensitivity of the network topology. This paper contributes to the reliability assessment of command‐and‐control network system, the identification and maintenance of key network nodes, and the design of network topology structure. [ABSTRACT FROM AUTHOR]

Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work‐integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal coordination of micro‐level relations. Objectives: The primary aim of this study is to examine the cohesion of teams in learning environments using a learning analytics approach. Method: This study examines teams from higher education who participate in a WIL environment platform working in teams to develop their collaborative problem‐solving skills. Here we show that temporal network motifs can be used as a proxy to measure cohesion. Results and Conclusions: We illustrate three clusters represented by team learning behaviours and found that each cluster has distinctive interactions with learning resources, performance outcomes, temporal network motif group characteristics and emergence over time using learning analytics. Implications: Applying temporal motifs as an analytics‐based measure of cohesion is a starting point for understanding how cohesion develops over time without relying on surveys. We anticipate that the same approaches can be applied in most learning management systems containing trace data of teams and their interactions with learning resources to understand cohesion. Lay Description: What is already known about this topic?: The development of team cohesion has been widely studied for decades in face‐to‐face educational contexts but remains underexplored in online environmentsObtrusive tools, such as questionnaire instruments are still the primary method used to examine team cohesionTeam cohesion is an emergent state that changes over time, representing the synchrony of different behavioural interactionsResearch that explores and examines the temporality of cohesion as it unfolds in team learning is limited What this paper adds?: Underlines how emerging team behaviours are characterised by their engagement, performance and cohesion development using temporal network motifsPresents an analytics‐based measure to examine cohesion using temporal network motifs as a proxyProvides a learning analytics approach for researchers and instructors to evaluate cohesion in online learning environments through online learner trace data The implications of study findings for practitioners: The paper provides insights into distinct teams with emerging learning behaviours, performance associations and cohesion in an online learning platform.The paper provides instructors with a way to monitor and support a team's cohesion over time by examining the way temporal motifs occur.The paper offers a new avenue to understanding learner engagement beyond summarisations [ABSTRACT FROM AUTHOR]

Finding the appropriate machine settings for a given manufacturing process is an important issue in industrial production. A set of minimum and maximum machine settings correspond to the lower and upper quality limits that are specified for the produced product, and by this define the boundaries of all appropriate machine settings. This paper shows that these boundaries are the solution of a multi‐objective optimisation problem, which is called the optimum machine settings problem. However, for most processes there is no mathematical model of the manufacturing process available, which maps the setting parameters on the quality key figures in a way that allows to compute the optimisation problem. In this case, experiments may provide the required empirical data simultaneously while executing the optimisation procedure. Using a case study on heat sealing in industrial packaging, the paper shows, how to develop a design of experiments based on the Normal‐boundary‐intersection method (NBI), and how to generate the Pareto‐frontier by executing test according to this test plan. It addresses the specific limitations inherent in solving an optimisation problem by experiments. The behaviour of the method towards discrete and binary objectives and constraints is discussed. [ABSTRACT FROM AUTHOR]

Background: Real‐world engineering problems are ill‐defined and complex, and solving them may arouse negative epistemic affect (feelings experienced within problem‐solving). These feelings fall into sequenced patterns (affective pathways). Over time, these patterns can alter students' attitudes toward engineering. Meta‐affect (affect or cognition about affect) can shape or reframe affective pathways, changing a student's problem‐solving experience. Purpose/Hypothesis(es): This paper examines epistemic affect and meta‐affect in undergraduate students solving ill‐defined problems called open‐ended modeling problems (OEMPs), addressing two research questions: What epistemic affect and transitions between different affective states do students report? And, how does meta‐affect shape students' affective experiences? Design/Method: We examined 11 retrospective interviews with nine students performed across two semesters in which students completed OEMPs. Using inductive and deductive coding with discourse analysis, we systematically searched for expressions conveying epistemic affect and for transitions in affect; we performed additional deductive coding of the transcripts for meta‐affect and synthesized these results to formulate narratives related to affect and meta‐affect. Results: Together, the expressions, transitions, and meta‐affect suggest different types of student experiences. Depending on their meta‐affect, students either recounted experiences dominated by positive or negative affect, or else they experienced negative emotions as productive. Conclusions: Ill‐defined complex problems elicit a wide range of positive and negative emotions and provide opportunities to practice affective regulation and productive meta‐affect. Viewing the OEMPs as authentic disciplinary experiences and/or the ability to view negative emotions as productive can enable overall positive experiences. Our results provide insight into how instructors can foster positive affective pathways through problem‐scaffolding or their interactions with students. [ABSTRACT FROM AUTHOR]

Background: Despite its obvious relevance to computer science, computational thinking (CT) is transdisciplinary with the potential of impacting one's analytical ability. Although countless efforts have been invested across K‐12 education, there is a paucity of research at the postsecondary level about the extent to which CT can contribute to sustainable learning outcomes. Objectives: The current study examines how a series of Arduino‐based robotics learning activities capture the fuller essence of concepts related to CT. Methods: College students (n = 50) completed a series of six robotics learning activities. Think‐alouds, student reflections and performance scores were used to assess students' CT through a robotics challenge in virtual and physical learning environments. Results and Conclusions: Students verbalized CT concepts related to algorithmic thinking much more than abstraction, problem decomposition and testing and debugging. Students exposed to active learning performed better in a virtual robotics challenge compared to their peers in a traditional‐oriented classroom. Students' scores on the physical robotics challenge increased as a function of the number of references they made to CT concepts during the think‐alouds. It is possible to design pedagogical experiences that tap into various dimensions of CT at incremental levels of complexity through a series of Arduino‐based robotics activities. With the integration of an online simulation, students can visualize and transfer their CT skills between a virtual and physical learning environment, thus leading to more sustainable learning outcomes. Lay Description: What is already known about this topic: Computational thinking (CT) is the conceptual foundation for problem‐solving.CT shifted from unplugged to plugged activities.CT concepts can be fostered through educational robotics. What this paper adds: A multi‐dimensional approach to assessing CT.Applications of CT provide insights into skill transfer.An integrative theoretical approach to study the 'how' and the 'what' of CT. Implications for practice: Educational robotics activities can cater to a fuller range of CT skills.Virtual simulations with constructive feedback are beneficial for students in traditional settings.Mixed learning environments contribute to making links between lectures and labs. [ABSTRACT FROM AUTHOR]

Background: Goal setting has been established in the literature as a critical component of self‐regulated learning and for effective problem‐solving. Yet, surprisingly little attention has been focused on goal‐directed behaviour in digital game‐based learning environments (GBLEs) despite their expanding use in educational contexts. Objectives: The current study examined the impact of goal assignment in a GBLE aligned with curricular objectives and played in a classroom context. Methods: Eighth‐grade students (N = 59) in the experiment were randomly assigned to either a mastery goal condition or a performance goal condition before playing Crystal Island—Outbreak. Goal orientation was measured before gameplay, monitoring judgements assessed during gameplay, and enjoyment was measured after game play. Results and Conclusions: Two important results emerged that contribute to the existing literature on goals and GBLEs. First, assignment to the mastery goal condition resulted in significantly higher enjoyment ratings and monitoring judgements but not game performance while considering the influence of pre‐existing goal‐orientation. Second, self‐reported mastery goal orientation and videogame play frequency predicted enjoyment in the game. Implications: The results suggest that enjoyment can be facilitated by orienting students to adopt mastery goals and that developers should consider integrating mastery‐based instructions in their GBLEs. Moreover, instructional goals can influence students regardless of incoming goal orientations. Lay Description: What is already known about this topic: Goal setting has been understudied in game‐based learning environments.Goal setting is a critical component of developing self‐regulated learning skills. What this paper adds: Evidence that assignment to a mastery goal leads to higher reported enjoyment.Evidence that assignment to a mastery goal leads to higher monitoring judgements.Evidence that incoming goal orientations predict enjoyment in a serious game. Implications for practice and/or policy: Enjoyment can be facilitated by orienting students to adopt mastery goals.Serious game developers should consider integrating mastery‐based instructions.Instructional goals can influence students regardless of incoming goal orientations. [ABSTRACT FROM AUTHOR]

Background: Haptic feedback has been shown to be an effective facilitator of the learning of scientific concepts in a series of studies. However, little is known about the underlying salient learning mechanisms, which are activated when learning from haptic feedback. Objectives: We investigate the learning mechanism in a higher chemistry education setting, in which the students learned about the abstract concept of potential energy in a quantum chemical context. Methods: In this work, we present a mixed‐methods problem‐solving prior to instruction (PS‐I) study with chemistry bachelor students. In an interactive quantum chemistry learning environment, the students explored the energetic profiles of nucleophilic substitution reactions and the corresponding activation barriers experienced as repulsion and attraction. We measured cognitive and affective mechanisms which have been shown to be activated in PS‐I designs, such as knowledge gap awareness, state curiosity, and positive affect as well as the learning outcome quantitatively and the learning trajectories qualitatively. Results and Conclusions: Planned contrasts revealed a small hindering effect of the haptic feedback on the learning outcome. Thematic analysis of the qualitative data lets us attribute this effect to the lack of scaffolding of the haptic feedback and the spontaneous atomic movements in the simulation, which may be interpreted as a visual representation of force in itself. This work highlights the importance of accurate mappings of the haptic feedback unto the target domain and further delivers insight into the prior conceptions of chemistry undergraduate students. Lay Description: What is already known about this topic: Haptic feedback can facilitate learning by grounding abstract concepts in sensory experiences.While previous studies have reported positive affective results, the cognitive results are ambiguous.Moreover, it was frequently reported that the learning of potential energy in a (quantum) chemical context is particularly difficult due to (i) the lack of grounding opportunities and (ii) the diverse previous conceptions. What this paper adds: A learning environment to interact with molecular systems in real‐time is proposed.The concept of activation energy is grounded in sensory experience of pushing and being pulled.The mixed‐methods design allows to explore cognitive and affective variables as well as the specific prior conceptions activated by the environment. Implications for practice and/or policy: We found a small negative effect of the haptic feedback on the learning outcome, potentially due to insufficient introduction of it to the students.The spontaneous movement of the atoms was identified as a more suitable external representation of the force.Future studies should investigate, if explicit introduction of the embodied metaphor can reverse this effect. [ABSTRACT FROM AUTHOR]

Background Study: As interest in programming education continues to grow, more educators are incorporating programming into K‐12 classrooms. There is evidence that programming can help develop essential skills for future societal advancement, known as 21st century skills. However, there has been limited research into which sub‐skills of 21st century skills are fostered through programming and the effect sizes thereof. Objective: This study presented a meta‐analysis to comprehensively understand the influence of programming instruction in K‐12 classrooms on the development of students' 21st century skills in different dimensions of sub‐skills. And further analysed the impact of key elements of programming instruction design on its effectiveness. Methods: A comprehensive meta‐analysis was conducted, covering 74 empirical studies published between 2000 and 2023, involving 136 effect sizes, and moderation analyzes on variables of instructional design. Results: This study indicated that implementing programming instruction in K‐12 schools can help develop students' multiple dimensions of 21st century skills, such as critical thinking, creativity, communication, collaboration, problem‐solving and decision, learning to learn, ICT literacy, and personal and social responsibility. Overall, programming demonstrates a moderate but significant effect on improving 21st century skills (Hedges's g = 0.621, p = 0.000 < 0.01). Furthermore, several best practices were identified to enhance students' 21st century skills, including initiating programming education from kindergarten, limiting the duration of programming interventions to 6 months, adopting interdisciplinary approaches to programming education, utilizing visual programming tools, and selecting appropriate assessment methods. Conclusion: Based on these findings, this study recommended the thoughtful design of programming education to maximize its advantages in various dimensions of 21st century skills. Lay Description: What is already known about this topic: Currently, 21st century skills have become critical skills that students should have.A popular practice in K‐12 schools is to use programming to develop students' 21st century skills, but results are inconsistent and quantitative synthesis of empirical research is lacking.Some factors of programming instruction may influence the effectiveness of programming on students' 21st century competencies. What this paper adds: A meta‐analysis of 74 studies was conducted to provide systematic evidence that programming has a moderate effect on improving K‐12 students' 21st century skills.Programming significantly improves students' eight sub‐skills in the 21st century.Educational level moderated the impact of programming on students' 21st century skills.Instructional duration moderated the impact of programming on students' 21st century skills. The implications of study findings for practitioners: Programming instruction is designed to be well‐planned and to take full advantage of technology to develop students' 21st century skills.Starting programming instruction at a younger age is more beneficial for students' 21st century skill development.Regarding intervention duration, it is noteworthy that interventions lasting within six months are more effective.Integrate programming across disciplines to promote students' multi‐dimensional 21st century skills. [ABSTRACT FROM AUTHOR]

The sigmoid functional response in the predator–prey model was posed in 1977. But its dynamics has not been completely characterized. This paper completes the classification of the global dynamics for the classical predator–prey model with the sigmoid functional response, whose denominator has two different zeros. The dynamical phenomena we obtain here include global stability, the existence of the heteroclinic and homoclinic loops, the consecutive canard explosions via relaxation oscillation, and the canard explosion to a homoclinic loop among others. As we know, the last one is a new dynamical phenomenon, which has never been reported previously. In addition, with the help of geometric singular perturbation theory, we solve the problem of connection between stable and unstable manifolds from different singularities, which has not been well settled in the published literature. [ABSTRACT FROM AUTHOR]

In this paper, the trajectory tracking problem of controlling a constrained quadrotor with unmeasurable system states in an environment with stochastic wind‐gust disturbance is considered. The mathematical model of the quadrotor is divided into the translational system and the rotational system, while only the measurement output of the quadrotor can be accessed. A new output‐based control method is developed for solving this problem. In the translational control system, an output feedback stochastic model predictive control (MPC) algorithm is proposed to generate the optimal control sequence with less conservativeness, by taking into account the information on the distribution of the disturbances and the uncertainty resulting from the attitude tracking error. The closed‐loop probabilistic constraints satisfaction, the recursive feasibility and the stability of the algorithm are further proved. In the rotational system, the active disturbance rejection control (ADRC) method to estimate and compensate for external disturbances is leveraged and robust control for attitude tracking is accomplished. The convergence of the disturbance estimator and the stability proof are provided. Finally, the robustness and effectiveness of the proposed control strategy are verified by an illustrative example. [ABSTRACT FROM AUTHOR]

Variance swaps is a kind of financial instrument that plays an important role in volatility risk management. In this paper, we study the pricing problem of log‐return variance swaps under the double mean reversion DMR (Heston‐CIR) model. Compared with Kim's work, we introduce the square‐root process into the diffusion term of the long‐term mean and present a stochastic approach that greatly simplify the solution of the problem without solving PDEs. An analytical solution and approximate solution are obtained. Some numerical examples show that the exact solution and MC simulation fit well. It is worth mentioning that the difference between the approximate solution and the exact solution is small when the parameters are selected appropriately. By the mean time, the parameter of the long‐term mean has an important impact on the solution, which implies that the introduction of a multi‐factor model is necessary. [ABSTRACT FROM AUTHOR]

Due to advancements in data collection, storage, and processing techniques, machine learning has become a thriving and dominant paradigm. However, one of its main shortcomings is that the classical machine learning paradigm acts in isolation without utilizing the knowledge gained through learning from related tasks in the past. To circumvent this, the concept of Lifelong Machine Learning (LML) has been proposed, with the goal of mimicking how humans learn and acquire cognition. Human learning research has revealed that the brain connects previously learned information while learning new information from a single or small number of examples. Similarly, an LML system continually learns by storing and applying acquired information. Starting with an analysis of how the human brain learns, this paper shows that the LML framework shares a functional structure with the brain when it comes to solving new problems using previously learned information. It also provides a description of the LML framework, emphasizing its similarities to human brain learning. It also provides citation graph generation and scientometric analysis algorithms for the LML literatures, including information about the datasets and evaluation metrics that have been used in the empirical evaluation of LML systems. Finally, it presents outstanding issues and possible future research directions in the field of LML. [ABSTRACT FROM AUTHOR]

In the process of mobile crowdsourced testing, a large number of test reports are generated, which often consist of short text and rich image information. One of the critical issues is how to review these reports efficiently. Researchers have recently proposed clustering, classification, and prioritization techniques to solve this problem. However, existing studies directly use related technologies to text description and segment the text content without further understanding of the text content. By deeply digging into the text information and distinguishing it according to its actual meaning, the sentences described in the text can be categorized into two types: Describing abnormal system behavior and describing reproduction steps. This paper proposes a mobile crowdsourced test report prioritization technique to improve performance. First, we use a TextCNN trained on large‐scale projects to distinguish the text descriptions of reports, then extract features from the text and screenshot information, respectively. Then we apply a clustering technique to gather similar reports. Finally, the inspection order is sampled from the clustering results. To validate our approach, we conduct experiments on six industrial crowdsourced projects. The results show that our method can detect all bugs faster in a limited time than existing prioritization methods, which can improve the bug reports review efficiency. [ABSTRACT FROM AUTHOR]

Abnormal changes in the retinal vessel width usually indicate the presence of certain diseases. This paper presents a novel model to measure the width of retinal vessels. This method firstly employs cubic spline fitting to determine the vessel cross‐sectional direction at the center point of a vessel profile, then uses the extended edge‐searching mode to detect vessel edge points along the vessel cross‐sectional direction, and finally obtains the width value by calculating the distance between the edge point and the center point. The method can accurately locate vessel edge points and successfully solve the problem of central light reflex in blood vessels. Experimental analyses on a publicly available database show that the proposed approach has excellent performance in accuracy with other existing measurement techniques. It provides an effective idea for analyzing morphological changes in blood vessels and can be extended to obtain the shape features of other objects. [ABSTRACT FROM AUTHOR]

The point of departure of this paper is Penrose's definition of conscious action as that in which stimulus and response are linked by a non‐algorithmic relationship, which Penrose defines as 'understanding'. My purpose is to explore the nature of this understanding by means of a two‐step process. The first step is provided by Tononi's Integrated Information Theory of consciousness. This theory provides us with a quantitative measure of conscious states that we need to transform into qualitative meaning. In the second step, we obtain this qualitative meaning with the help of the structuralist theory of mind. From this perspective, meaning originates in the set of qualitative contrasts that define the alternative courses of action that might have been implemented. Work on the analogy between quantitative bits and qualitative binary oppositions does not solve the hard problem of consciousness, but it might help to reformulate it in a new, productive way. [ABSTRACT FROM AUTHOR]

Electromagnetic (EM) parametric modeling has become significant for EM designs of microwave devices. This paper outlines recent advances in hybrid format‐based neuro‐transfer function (TF) techniques for EM parametric modeling of microwave devices. To solve the problem of high‐sensitivity, a novel decomposition approach is discussed to develop a rational‐based neuro‐TF model of EM behavior of microwave devices. To handle the issue of non‐smoothness and discontinuity, a parametric modeling technique incorporating pole‐residue/rational and neural network hybrid transfer function (short for rational/pole‐residue hybrid neuro‐TF) of EM behavior is reviewed. This technique effectively combines rational and residue‐pole formats of the transfer functions. Compared with the residue‐pole‐based neuro‐TF modeling approach and the rational‐based neuro‐TF modeling approach, the rational/pole‐residue hybrid neuro‐TF technique allows for better accuracy in large geometrical changes and high order applications. A parametric modeling method combining neural network and polynomial‐transfer function (neuro‐PTF) is further presented as an advanced version of the rational/pole‐residue hybrid neuro‐TF method. In this approach, the pole–residue‐based transfer function and the polynomial function are used together to describe the EM responses, and can produce more accurate models, especially with large geometrical variables. Following the modeling process, trained models can be used to provide fast and accurate EM response predictions and can subsequently be used for advanced circuit and system design. [ABSTRACT FROM AUTHOR]

Direct electromagnetic (EM) optimization for microwave components design is usually a time‐consuming process. To improve the optimization efficiency, this paper proposes a novel parallel EM optimization technique exploiting improved pole‐residue‐based neuro‐transfer function (neuro‐TF) surrogate and isomorphic orthogonal design of experiment (DOE) sampling strategy. We propose a new sampling method combining isomorphic orthogonal DOE and parallel EM simulations to generate training data for developing the neuro‐TF surrogate. This proposed sampling method can ensure the scattered distribution of data samples in the overall optimization process, thus effectively improving the surrogate accuracy and increasing the optimization speed. We also propose a new pole‐residue tracking technique for order‐changing to solve the discontinuity problem of pole/residues during the neuro‐TF surrogate development. Different from the fixed split ratio in existing pole‐residue tracking technique, the split ratio of poles and residues in the proposed technique is adaptive and determined according to the information of neighboring samples. Therefore, the continuity and smoothness of pole/residues after the splitting are improved, so as the neuro‐TF surrogate accuracy. In addition, the trust region algorithm is exploited during EM optimization to improve the convergence speed. In this way, the proposed EM optimization technique obtains the optimal solution in a shorter time with fewer iterations than the existing techniques. Two examples of EM optimizations of microwave components are used to illustrate the proposed technique. [ABSTRACT FROM AUTHOR]

Background: Providing students with worked out problem solutions is a beneficial instructional technique in STEM disciplines, and studying examples that have been worked out incorrectly may be especially helpful for reducing misconceptions in students with low prior content knowledge. However, past results are inconclusive and the effects of incorrect worked examples alone or in combination with correct examples remains unclear. Objectives: We aim to address whether studying incorrect examples alone or in combination with correct examples can support the reduction of students' fraction misconceptions, operationalized as errors made with high confidence. Methods: After incorrectly solving a sampling problem, 130 students in 4th through 11th grade in the U.S. were randomly assigned to a condition in an online problem set focused on fraction equivalence. Students studied either single‐type worked examples (i.e., correct or incorrect; n = 49) or combination‐type worked examples (correct and incorrect; n = 41) or engaged in a problem‐solving control (n = 50). Results: Studying a combination of correct and incorrect worked examples was as effective as the problem‐solving control with feedback at improving fraction equivalence knowledge and reducing the rate of high‐confidence errors. Students in both the combination condition and the problem‐solving with feedback condition outperformed those who studied either correct or incorrect worked examples alone. Conclusions: Results support the inclusion of a combination of correct and incorrect worked examples when teaching students with low prior content knowledge. Studying a combination of example types within an online tutor helps to reduce misconceptions about fractions, a topic students commonly struggle with. A problem‐solving task with corrective feedback worked equally well. Lay Description: What is already known about this topic: Studying worked examples of mathematical solutions improves student learning.Incorrect examples, either alone or in combination with correct examples, are particularly effective for improving learning for students with low prior knowledge in the target content.Comparing correct and incorrect examples is also effective at improving problem‐solving but this effect may be specific to those with high prior knowledge.Still unknown are the impacts of these different combinations of examples on misconceptions in particular. What this paper adds: We show that studying a combination of correct and incorrect examples reduces math misconceptions.Problem‐solving with corrective feedback within an online tutor also has this effect. Implications for practice and/or policy: Using a combination of example types will help reduce students' misconceptions about fractions. [ABSTRACT FROM AUTHOR]

Background: Collaborative learning can effectively promote the development of higher‐order competencies, where learners collaborate via social interactions to explore and solve complex problems. It has been found that the effective occurrence of collaborative learning requires appropriate external guidance and support. In particular, collaborative interactions in open learning environments are more complex and difficult, which makes it important to provide dynamic interventions for learners according to different collaborative situations. However, the role of facilitators and the characteristics and mechanisms of their interventions have yet to be thoroughly investigated. Objectives: The study aims to uncover the characteristics and patterns of interaction among groups with different collaborative performance and facilitator performance in an open learning environment, and to explore the differentiated role of facilitators in this process. Method: Groups are categorised as high or low based on their collaborative performance and facilitator performance. This study used lag sequential analysis (LSA) and content analysis to explore the interaction patterns of groups with different collaborative performance and facilitator performance. Also, the different roles of facilitators were analysed by comparing the differences in interaction patterns of different collaborative performance groups. Results: The study found that groups with different collaborative performances and facilitator performances showed significant differences in interaction patterns, and the two had crossover effects. There is also variability in the role of facilitators in groups with different collaborative performance profiles. Patterns of transition between different layers of interaction can indicate the level of groups' collaborative engagement. Specific interaction patterns exist that are conducive to enhancing collaborative learning. Conclusions: The results of the study pointed out that groups with different collaborative performance and facilitator performance showed different characteristics of interaction patterns. The role of the facilitator in online collaborative learning is characterised by compensatory and merit‐promoting. High‐quality online collaboration is the result of multiple factors, including learners and facilitators working together. This study has practical implications for the design of instructional interventions for group collaboration in online learning communities. Lay Description: What is already known about this topic: Deep instructional interactions help stimulate group intelligence and promote knowledge creation and deep connections.The facilitation strategies of the instructional implementer in online collaborative learning contexts play an important role in guiding students to engage in interactions and promoting efficient learning.Facilitators need to adopt different intervention strategies for different learners and learning stages to advance collaborative task completion. What this paper adds: Group collaborative performance is closely related to the strength of the connection and the depth of interaction of group members.Roles of facilitator in online collaborative learning can be characterised by strong support, compensation, and merit promotion.High‐quality online collaboration is the result of multifactor interaction between learners and facilitators. Implications for practice and/or policy: Course organisers' rating scale proposed in this study can help screen and train facilitators with excellent attributes.Examining different roles of facilitators can help curriculum designers rationalise the design and organisation of collaborative instruction.When group collaboration is active, learners should be guided through activities for deeper interaction and exploration.When group collaboration is low‐spirited, learners should be encouraged to focus on the stage tasks and explore the tasks step by step. [ABSTRACT FROM AUTHOR]

Background: During the COVID‐19 pandemic, online collaborative problem solving (online CPS) has become one of the most crucial learning methods to develop students' learning performance. However, it remains unclear of the effectiveness of the online CPS method on students' learning performance. Objectives: To explore the overall effect of online CPS methods on students' learning performance and identify the moderating factors that influence this impact, we employed a meta‐analysis approach to analyse the combined effects of 31 articles. Results: The results showed that the online CPS method had a medium impact on students' learning performance, with an overall effect size of 0.526. The moderator analysis indicated that the online CPS method was more effective for (a) college preparatory learners, (b) the discipline of Economics, (c) grouping method of assigned, (d) teacher‐led instruction, (e) study duration of 2 to 4 weeks, (f) group size of 3–5 members, (g) synchronous online environment and (h) cognitive performance. Implications: Based on these findings, we recommend using the online CPS to improve students' cognitive and affective learning performance. To enhance students' social learning performance, instructors should design reasonably to use collaborative scaffolding to engage students purposefully and constructively in online CPS activities. Lay Description: What is already known: During the COVID‐19 pandemic, the online collaborative problem solving (CPS) method is gaining increased popularity.The impact of the online CPS method on students' learning performance has aroused the great interest of scholars.Research on the effectiveness of the online CPS method on students' learning performance is inconsistent. What this paper adds: Research on the influence of the online CPS method on students' learning performance, such as in cognitive, affective and social three‐dimensional learning performance.The online CPS method had a medium positive effect on students' cognitive performance and a moderate to low positive impact on students' affective and social performance.Considering some moderating variables (such as group size, educational level, group method, study duration, discipline, intervention measure and online environment), explore the effectiveness of the online CPS method on students' learning performance. Implications for practice: We recommend using the online CPS method to improve students' cognitive and affective learning performance.To enhance students' social learning performance, instructors should design reasonably to use collaborative scaffolding to engage students purposefully and constructively in online CPS activities. [ABSTRACT FROM AUTHOR]

Background: Flipped classroom (FC) model has become increasingly popular in dental education (DE) with its strengths for students. However, major concerns are lack of interaction, unwillingness to complete the assignments, low engagement during the pre‐class activities because of an unwell‐designed instructional setting of FC. Objectives: The recent study aims to investigate the effects of video‐driven discussions integrated into the flipped classroom (VdDs‐FC) model on dental students' (DSs) learning achievement, practical performance, and higher‐order thinking skills in a restorative dentistry course. Methods: This study adopted a sequential explanatory design from mixed‐methods research. A total of 96 DSs participated in a dentistry faculty of Türkiye. They were randomly divided into two groups: VdDs‐FC group and the conventional flipped classroom (c‐FC) group. Results and conclusions: The results showed that the VdDs‐FC model had significant positive effects on the practical performance of DSs in practical subjects and their problem‐solving and critical thinking skills. However, there was no significant difference between the two groups in learning achievement and creativity. The use of FC in the c‐FC group did not lead to any difference in the students' achievements. Moreover, the qualitative results indicated that the VdDs‐FC model has the potential for enhancing peer learning, practical classroom activities, and higher‐order thinking skills. Implications: This study also includes several instructional implications and suggestions for educators, researchers, and practitioners on use of FC in dentistry. Lay Description: What is already known about this topic: Flipped learning has become a rapidly growing area of dentistry research.Discussion board could be beneficial to increasing dental students' higher order thinking skills, especially problem solving and critical thinking.Video‐driven discussions into flipped classroom provide several opportunities for practical performance in dental education, not for theoretical knowledge. What this paper adds: Video‐driven discussions into flipped classroom model is proposed.We compared two learning environments by including traditional flipped classroom.We found that the integrated model with flipped classroom can have a positive impact on students' achievement.Online discussions usage contributed to higher cognitive, affective, and behavioural learning outcomes.Based on interview data, the proposed model supports peer learning. Implications for practice and/or policy: Dental educators should integrated the digital discussion boards as out‐of‐class activities in the pre‐clinical dental training.From dental educators' perspective, they should be carefully trained in FC design (interaction elements, material design, integration with different methods, etc.).From instructional design perspective, micro videos should have case‐based or problem‐based activities to discuss.From learner perspective, an integration of the flipped classroom with different technologies could have a positive effect on increasing learning. [ABSTRACT FROM AUTHOR]

Background: Computer‐based scaffolding has been intensively used to facilitate students' self‐regulated learning (SRL). However, most previous studies investigated how computer‐based scaffoldings affected the cognitive aspect of SRL, such as knowledge gains and understanding levels. In contrast, more evidence is needed to examine the effects of scaffolding on the metacognitive dimension and efficiency outcome of SRL. Objectives: This study aims to examine the role of computer‐based scaffolding in students' metacognitive monitoring and problem‐solving efficiency. Methods: Seventy‐two medical students completed two clinical reasoning tasks in BioWorld, an intelligent tutoring system (ITS) designed for promoting medical students' diagnostic expertise. During solving the tasks, students were asked to report their confidence judgements about proposed diagnoses. Computer trace data were used to identify task completion time (CT) and students' use of three scaffolding types, that is, conceptual, strategic, and metacognitive. Then we calculated students' metacognitive monitoring accuracy (i.e., calibration) and problem‐solving efficiency. Results and Conclusions: One‐sample t‐test demonstrated that students inaccurately monitored their learning processes and were overconfident in both tasks. Linear mixed‐effects models (LMMs) indicated that the intensive use of metacognitive scaffolding positively predicted students' metacognitive monitoring accuracy. Moreover, strategic scaffolding was negatively related to problem‐solving efficiency, whereas metacognitive scaffolding positively influenced problem‐solving efficiency. Takeaways: This study shows the importance of metacognitive scaffolding in improving the accuracy of metacognitive monitoring and problem‐solving efficiency. Findings from this study provide new insights for instructors and ITS developers to optimise the design of scaffoldings. Lay Description: What is already known about this topic?: Computer‐based scaffolding can facilitate students' knowledge gains and academic performance during self‐regulated learning (SRL).The effects of computer‐based scaffolding on the metacognitive dimension and efficiency outcome of SRL are still in a nascent phase. What this paper adds?: This paper explores how different types of computer‐based scaffolding affect students' metacognitive monitoring and problem‐solving efficiency.Metacognitive scaffolding improved the accuracy of medical students' confidence judgements.Metacognitive scaffolding promoted medical students' diagnostic problem‐solving efficiency.Strategic scaffolding had a negative effect on problem‐solving efficiency. Implications for practice: Instructors could provide more metacognitive scaffoldings to facilitate students' metacognitive monitoring accuracy.The designers of intelligent tutoring systems and instructors should consider the costs associated with using scaffoldings. [ABSTRACT FROM AUTHOR]

Summary: The minimal complexity realization of low‐order positive‐real immittances as resistor–inductor–capacitor (RLC) (or damper‐spring‐inerter) networks is an essential unsolved problem in the theory of network synthesis, and the results can be directly applied to the inerter‐based mechanical systems control. This paper solves the realizability problem of a certain class of biquadratic impedances as any seven‐element series‐parallel RLC network, where the impedance contains a repeated zero and pole of multiplicity two. In contrast to the previous results of this problem, the work in this paper considers the general case and removes the restrictions on the network structures and the number of reactive elements. The final results present a necessary and sufficient condition for the realizability of such an impedance as any seven‐element series‐parallel RLC network. A network synthesis example in suspension control design is presented to illustrate the results of this paper and the applications in inerter‐based mechanical control. [ABSTRACT FROM AUTHOR]

This paper highlights how immersive educational experiences can help students understand the United Nations' Sustainable Development Goals (SDGs) and their relation to leadership. The paper provides an example of how a carefully designed faculty‐led program using original research can cultivate cross‐cultural competencies and build student knowledge and skills to support sustainability. Educators can use this paper as a guide to other immersive experiences to address the SDGs while developing student leadership capacity. [ABSTRACT FROM AUTHOR]

This paper revisits the orientation systems in Situ Rgyalrong (Burmo‐Qiangic, Sino‐Tibetan). These systems reflect heliocentric (e.g., east/west) or topographic (e.g., upriver/downriver) orientation, typically within a frame of absolute reference. While scholars agree that the orientation systems of different Situ dialects are generalisable to a tri‐axial model, the precise semantic values reflected by the three axes have always been controversial. In explaining synchronic semantic divergences among Situ orientation systems from a diachronic perspective, the present work first reveals historical layers within the three axes. Through internal reconstruction, it then identifies the original meanings of the two sets constituting the innovative Axis II. Finally, using typological parallelisms and local topographic features, this paper analyses the Proto‐Situ orientation system as a tri‐axial system of orthogonality, and infers the original meanings of the system's three axes. Importantly, this study shows how the comparative method can be applied to solving semantic problems in languages rich in morphology. [ABSTRACT FROM AUTHOR]

Background: Written reflective practice (WRP) is a teaching tool used across speech–language therapy (SLT) clinical education programmes. The process aims to support the development of reflective skills required for the workplace (e.g., problem‐solving and self‐evaluation). Aims: This cross‐sectional and repeated‐measures study design investigated students' demonstration of breadth of WRP across the clinical education programme. Methods & Procedures: The participants were 77 undergraduate SLT students in their first, second or final professional year of the clinical programme. Participants wrote critical reflections following an interaction with a client/s as part of their clinical education experiences. Formative feedback was provided after each written reflection (WR). In total four WRs per participant were coded for breadth of WRP using a modification of Plack et al.'s coding schema from 2005. This was completed for each of the four time points across the academic year for each professional year. Outcomes & Results: There was a statistically significant association between time (i.e., professional year of the programme) and likelihood of demonstration of breadth of reflection for the lower level reflective element of 'attend' and higher level reflective element of 're‐evaluate'. A positive trend between time and likelihood of demonstration of breadth of reflection was seen for the lower level element of 'reflection‐for‐action'. Final‐professional‐year students exhibited significant enhancements in the higher level elements (e.g., 'premise') compared with first‐ and second‐professional‐year students. Conclusions & Implications: This group of SLT students exhibited significant change in breadth of WRP across the degree programme. This finding has positive implications for facilitating WRP with students and using the current coding framework in clinical programmes. What this paper adds: What is already known on this subject: WRP is one form of reflective practice (RP) used in SLT, allied health, medical and nursing clinical education programmes. Researchers have suggested that RP skills develop over time for students. Previously, studies examining WRP have focused on one off assessment of skill or over a timeframe of 6–10 weeks. Here, we examine SLT students' WRP skills across the degree programme. What this paper adds to existing knowledge: SLT students exhibited significant positive change in breadth of WRP across the degree programme as their clinical experience increased. Our results provide quantitative information in support of using RP as a learning tool throughout clinical education programmes for SLT. What are the potential or actual clinical implications of this work?: This study offers support for educators of SLT students; for example, how educators can assess WRP, and how educators can foster SLT student skill development with formative feedback and reflective questioning. This study also offers support for student SLT, for example, describing how WRP can be part of their individualized learning approach and provide a purposeful examination of self and clinical skill development. [ABSTRACT FROM AUTHOR]

It is well known that accurate estimation of the loop delay between the input and output feedback signals is the key to behavioral modeling and digital predistortion of power amplifier. Nevertheless, most of the traditional loop‐delay compensation algorithms have the disadvantage of high computational complexity. For the purpose of solving this problem, a loop‐delay estimation algorithm based on sliding window has been proposed in this paper, where the first derivative characteristic of the signal is employed to evaluate the correlation between the input and output feedback signals. The simulation and experiment are carried out with different bandwidth signals in this paper. The results show that the proposed algorithm and the traditional cross‐correlation‐based method could align the input and output feedback signals successfully. But in terms of resource consumption, the proposed algorithm could reduce the multiplier nearly by 100% and the adder by approximately 93.2%. [ABSTRACT FROM AUTHOR]

To enact a just and sustainable blue economy, one must consider all the actors involved in its shaping. This paper argues that a quintuple helix approach to stakeholder engagement – involving government, academia, the business community, and civil society – and an inclusive transdisciplinary action research (TAR) methodology are promising avenues with which to do so. Embracing critical pragmatism as a foundational framework, key ideas from three strands of research are consolidated: (1) the recent work on the geographical dimension of socio‐technical sustainability transitions; (2) the literature on just sustainabilities and just transition; and (3) action research and transdisciplinary approaches to problem solving. This allows for the reimagination of a common future for the blue economy that is developed through a different kind of democratic process driven and informed by co‐learning, and shared experiences. By adopting a transdisciplinary action research approach, actors from different disciplines and spheres of experience can gain a better mutual understanding and find commonality through the open door of collaboration. The theoretical argument presented in this paper is illustrated by a vignette of an ongoing TAR project at Southern Connecticut State University, which outlines the challenges and opportunities inherent to implementing a TAR approach. [ABSTRACT FROM AUTHOR]

This paper on a strengths‐based approach (SBA) to practice is based on empirical research with stakeholders involved in an intensive support programme for young people at risk and their parents in Ireland. The Youth Advocate Programme (YAP) model provides wraparound support to respond to their needs by focusing on their competencies and their coping skills and building networks of community‐based supports. The model includes parents or carers in the suite of support offered by advocates. An SBA to practice has been discussed for some time in academic literature and practice guidance. However, it tends to be considered primarily in relation to social work practice, and there is ongoing ambiguity as to what it actually involves in day‐to‐day engagement with individual family members. Insightful, rich accounts of SBAs as part of routine practice provided by young people, parents and practitioners form the basis to this paper and detail how these approaches support the development of hope‐inspiring relationships and promote positive change. Relevant literature and research situates the debate on the experience of using SBA, the wider challenges faced by families, the impact of SBA in practice on those receiving the support service and its potential for use in the wider continuum of children and family services. [ABSTRACT FROM AUTHOR]

Existing methods for nonlinear robust control often use scenario‐based approaches to formulate the control problem as large nonlinear optimization problems. The optimization problems are challenging to solve due to their size, especially if the control problems include time‐varying uncertainty. This paper draws from local reduction methods used in semi‐infinite optimization to solve robust optimal control problems with parametric and time‐varying uncertainty. By iteratively adding interim worst‐case scenarios to the problem, methods based on local reduction provide a way to manage the total number of scenarios. We show that the local reduction method for optimal control problems consists of solving a series of simplified optimal control problems to find worst‐case constraint violations. In particular, we present examples where local reduction methods find worst‐case scenarios that are not on the boundary of the uncertainty set. We also provide bounds on the error if local solvers are used. The proposed approach is illustrated with two case studies with parametric and additive time‐varying uncertainty. In the first case study, the number of scenarios obtained from local reduction is 101, smaller than in the case when all 214+3×192$$ {2}^{14+3\times 192} $$ extreme scenarios are considered. In the second case study, the number of scenarios obtained from the local reduction is two compared to 512 extreme scenarios. Our approach was able to satisfy the constraints both for parametric uncertainty and time‐varying disturbances, whereas approaches from literature either violated the constraints or became computationally expensive. [ABSTRACT FROM AUTHOR]

Most existing domain adaption methods solve the problem of data distribution similarity in single‐source to single‐target domain or multi‐source to single‐target domain adaption, but the more realistic multi‐source to multi‐target domain transfer scenarios are ignored. At the same time, less attention is paid to the similarity of task distribution among domains and the corresponding relationship between coarse‐grained and fine‐grained, which leads to the problem of low classification accuracy. In this paper, a multi‐source to multi‐target domain adaption (MSMTDA) method based on similarity measurement is proposed. Firstly, a cross‐domain similarity measurement mechanism based on the idea of data distribution similarity and task distribution similarity is set up to judge and optimize the distribution difference among source domains and target domains. Secondly, global‐local‐bidirectional alignment is used to solve the problem of poor transfer performance in the existing distributed alignment. Then, the cross‐domain mutual learning strategy is proposed, which reduces classifier discrepancy caused by decision boundaries and distribution difference in multiple domains. Finally, the proposed method is verified on three benchmark datasets in image classification. The experimental results show that the proposed method performs better in both classification accuracy and training time when compared with the conventional method. [ABSTRACT FROM AUTHOR]