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In double‐permeability models, the squirt coefficient representing the fluid mass equation came from mathematical parameterization that was inconsistent with physics, resulting in the prediction of an infinitely large squirt coefficient at an infinitely high frequency. This was a drawback of the models, as an infinitely large squirt flux rate means unrealistic infinite large velocity and kinematic energy (velocity and energy must be bounded). This paper is motivated by solving the problem. At first, when P‐wave compresses a porous rock, the contact of grains (the normal of which is the wave direction) is very compliant, which generates a strong squirt transverse to the wave direction. In contrast, the squirt along the wave direction is relatively small. Based on such a transverse squirt mechanism, a new squirt coefficient is derived, which yields a vanishing value at infinite high frequency. Secondly, the squirt coefficient is put into a previous model to predict velocity and attenuation of ultrasonic P‐wave. Two core samples (Berea sandstone and Boise sandstone) are used for illustration; both the measured velocity and quality factor are well simulated. It is notable that there is an interesting shoulder on the velocity dispersion curves before the asymptotical behaviour of velocity at high frequency. [ABSTRACT FROM AUTHOR]

In this paper, some new algorithms based on the iteratively reweighted least squares (IRLS) method are proposed for sparse recovery problem. There are two important parameters in the IRLS method: a weighted parameter and a regularization parameter. On the one hand, in order to improve the performance of IRLS method, a new way is given to update the weight vector. On the other hand, for the regularization parameter, three new update methods are introduced to avoid the phenomenon that the regularization parameter drops too fast. Then, some improved iteratively reweighted least squares (IIRLS) algorithms are proposed, and their convergence and convergence rate are analyzed. The local convergence of our algorithms is superlinear and approaches a quadratic rate in special cases. Finally, a large number of algorithms are compared in solving the sparse recovery problem, including IRLS methods and IIRLS methods with different weighting parameters and regularization parameters, and certain iterative methods. The experimental results demonstrate that the proposed methods are efficient and promising. [ABSTRACT FROM AUTHOR]

Summary: Nowadays, there is an emerging need for applications based on the Internet of Things (IoT). The sensor nodes present in the IoT network produce data constantly, which directly influences the durability of the network. Therefore, two major challenges while designing IoT systems are network lifetime and energy consumption. Although the ability of IoT applications is huge, there are several limitations such as energy optimization, heterogeneity of devices storage, load balancing, privacy, and security that have to be addressed. These constraints have to be optimized for improving the efficiency of the networks. Hence, the main intention of this paper is to develop the intelligent‐based cluster head selection model for accomplishing green communication in IoT. The two famous algorithms like spotted hyena optimization (SHO) and sun flower optimization (SFO) are integrated to form sun flower‐spotted hyena optimization (SF‐SHO) by utilizing the hybrid meta‐heuristic concept for the optimal cluster head selection. The most significant parameters in IoT networks like delay, distance, energy, temperature, and load are considered for deriving a multi‐objective function to offer optimal clustering. The cluster head of the model is optimally tuned based on the hybrid SF‐SHO, to solve the multi‐objective problem, thus showing the enhanced green communication performance. The proposed model is analyzed and evaluated over different approaches in terms of energy‐specific factors, and the attained results confirm the efficiency of the developed method. [ABSTRACT FROM AUTHOR]

In order to learn the mappings from words to referents, children must integrate co-occurrence information across individually ambiguous pairs of scenes and utterances, a challenge known as crosssituational word learning. In machine learning, recent multimodal neural networks have been shown to learn meaningful visual-linguistic mappings from cross-situational data, as needed to solve problems such as image captioning and visual question answering. These networks are potentially appealing as cognitive models because they can learn from raw visual and linguistic stimuli, something previous cognitive models have not addressed. In this paper, we examine whether recent machine learning approaches can help explain various behavioral phenomena from the psychological literature on crosssituational word learning. We consider two variants of a multimodal neural network architecture and look at seven different phenomena associated with cross-situational word learning and word learning more generally. Our results show that these networks can learn word-referent mappings from a single epoch of training, mimicking the amount of training commonly found in cross-situational word learning experiments. Additionally, these networks capture some, but not all of the phenomena we studied, with all of the failures related to reasoning via mutual exclusivity. These results provide insight into the kinds of phenomena that arise naturally from relatively generic neural network learning algorithms, and which word learning phenomena require additional inductive biases. [ABSTRACT FROM AUTHOR]

Couple and family therapy is distinguished from individual therapy due to its focus on the interactional patterns between family members. However, there is plenty of overlap because of the reciprocal relationship between individual psychopathology and its relational contexts. Many clients seeking individual therapy aim to improve their relationships, and couples and families who have relational difficulties often have at least one partner with some type of psychopathology. This article presents integrative systemic therapy (IST) as a method for integrating individual, couple, and family therapy. IST is a multitheoretical and multisystemic perspective that utilises concepts and interventions from a variety of therapies for a broad variety of presenting concerns and populations, including individuals, couples, and families. In IST, a repetitive pattern of interaction is co‐occurring at two levels – within an individuals' minds (i.e., intrapsychic) and externally in people's interactions with others in their system (i.e., interpersonal) – and they influence each other. Therefore, IST therapists utilise various interventions from individual and couple and family therapy within a case to disentangle problems occurring at various systemic levels. The paper begins with a summary of the theoretical assumptions of IST and introduces basic terms such as sequences. This is followed by specific descriptions of two critical tools, essence and blueprint, which walk therapists through the steps of how to conduct IST and integrate individual, couple, and family therapy. Finally, two case examples are used to demonstrate this process. [ABSTRACT FROM AUTHOR]

This paper deals with a class of Bratu's type, Troesch's, and nonlocal elliptic boundary value problems arising in the heat transfer process. Due to the strong nonlinearity and presence of parameter δ, it is very difficult to solve these problems analytically as well as numerically. By using the Jacobi spectral collocation method, these problems are solved fruitfully. We have shown the numerical as well as theoretical convergence of the suggested scheme. Numerical results are presented through figures and tables, demonstrating the accuracy of the scheme. Results are compared with some known methods to highlight its neglectable error. [ABSTRACT FROM AUTHOR]

In pinhole integral imaging (PII)‐based hologram, each pinhole is regarded as a point light source to emit light rays in different directions to simulate light propagation from the reconstructed 3D information to the computer‐generated hologram (CGH). The PII‐based hologram presents at a working mode similar to resolution‐priority integral imaging (RPII). The depth of field (DOF) is inevitably limited. In this paper, we use twice close‐range capturing to enhance the DOF of this hologram. Twice close‐range capturing can ensure that the virtual objects with different depths are not far from their respective image reference planes, and the detailed information of the back object also can be preserved. Besides, we use a simple ray‐tracing method to solve the occlusion problems. Numerical and optical reconstruction verified that the proposed method can reconstruct clearer 3D images compared with the single capturing method. In addition, the proposed method can present a natural occlusion effect. Thus, the DOF is enhanced. [ABSTRACT FROM AUTHOR]

The study gives definitions of information war (information warfare) and related terms, such as cyberwar and others, indicates the purposes, objects, subject matter, and subjects of the concepts under consideration. The author also considers the features of strategic information warfare conducted by the Russian Federation against Ukraine, the stages in the development of information war, and the classification of its types and methods. The approaches of scientists who studied certain aspects of information warfare were analyzed, based on their work relevant conclusions were drawn and the conceptual basis of the paper was formed. Independently, the definition and characteristics of the concept of cyber warfare inextricably linked with information warfare are given. Methods for solving the problems arising during the information war are introduced, ways of ensuring the information security of the state are provided. Information war in this study is considered as methods and means of presenting information to form the point of view needed by the organizers of information propaganda and the corresponding public opinion in a certain group of people. The author made an in‐depth analysis of the regulatory and legal instruments in force for counterfeiting information warfare and protecting the Ukrainian people from it, pointed out the deficiencies of such documents, and gave recommendations for their further advancement. Recommendations are given to improve the current information awareness among Ukrainians, the directions of the state policy in this field are suggested and ways to ensure the stability of the national information security system of Ukraine are provided. [ABSTRACT FROM AUTHOR]

Visual inspection of photovoltaic modules using electroluminescence (EL) images is a common method of quality inspection. Because human inspection requires a lot of time, object detection algorithm to replace human inspection is a popular research direction in recent years. To solve the problem of low accuracy and slow speed in EL image detection, we propose a YOLO‐based object detection algorithm YOLO‐PV, which achieves 94.55% of AP (average precision) on the photovoltaic module EL image data set, and the interference speed exceeds 35 fps. The improvement of speed and accuracy benefits from the targeted design of the network architecture according to the characteristics of EL image. First, we weaken the backbone's ability to extract deep‐level information so that it can focus on extracting the low‐level defect information. Second, the PAN network is used for feature fusion in the Neck part. But, only the single‐size feature map output is retained, which significantly reduces the amount of calculation. Also, we analyze the impact of data enhancement methods on model overfitting and performance. Finally, we give effective data enhancement methods. The results show that the object detection algorithm in this paper can meet the requirements for high‐precision and real‐time processing on the PV module production line. [ABSTRACT FROM AUTHOR]

In the current paper, a space–time spectral‐Galerkin method is presented for the one‐ and two‐dimensional (1D & 2D) fourth‐order time‐fractional partial integro‐differential equation (TFPIDE) with a weakly singular kernel. In temporal direction, a Petrov‐Galerkin approach is used for discretization. Indeed, eigenfunctions of the first and second kind fractional Sturm‐Liouville problem (FSLP), which called Jacobi polyfractonomials, are used as temporal basis for the trial and test spaces, respectively. Also, spatial discretization is based on the Galerkin approximation with a combination of Legendre polynomials as basis. Fully discrete scheme, give rises to obtaining approximate solution of desired problem via solving a system of linear algebraic equations. Spectral accuracy and efficiency of the considered method are numerically demonstrated by some test problems with smooth and non‐smooth exact solutions in one‐ and two‐dimensional cases. [ABSTRACT FROM AUTHOR]

Adaptive embedding plays an important role in improving the embedding performance of reversible data hiding and it is usually realized by modifying the prediction‐errors discriminately. By extending the skewed histogram shifting technique which uses a pair of extreme predictions to determine whether the target pixel should be predicted or not, this paper realizes another form of adaptive embedding, that is, adaptive prediction‐error generation. Specifically, it is proposed to adaptively determine the pair of extreme predictions according to image content. Each pair of extreme predictions is first evaluated by the introduced distortion per embedding one bit. Then, an efficient mechanism to determine the best pair of extreme predictions for pixels with a given local complexity is designed. With such a mechanism solving the computational problem, it is also proposed to extend the context to obtain more pairs of extreme predictions such that more precise multi‐predictor can be realized. With obtained errors, the best expansion bins are determined to achieve a more comprehensive self‐adaption. Experimental results demonstrate that the proposed scheme achieves better capacity‐distortion performance and outperforms a series of state‐of‐the‐art schemes. [ABSTRACT FROM AUTHOR]

What is the point of doing practical ethics? Is it to find fruitful modes of reasoning so that the people can make up their mind about contested issues? Or is it rather to try to solve those problems once and for all? This article argues that the epistemology of moral disagreement provides good reasons in favor of the former view. In a recent paper, Andrei Poama suggests understanding public policy ethics (EPP) as falling into two broad categories – applied and constructive EPP. The main difference is their reaction to the factum of moral disagreement: proponents of applied EPP explain moral disagreement away, while proponents of constructive EPP take it to be a fundamental characteristic of morality. This article takes Poama's distinction to suggest a path to decide which of the two approaches to EPP is 'the right one', namely to take into account the debate about peer disagreement in epistemology. The article argues that the most promising theory of epistemic peer disagreement – the 'Total Evidence View' – fits constructive EPP quite naturally and that this speaks for constructive against applied approaches to EPP and to practical ethics more generally. [ABSTRACT FROM AUTHOR]

Background: Mixed methods research studies continue to pervade the field of health care, where pragmatism as a research paradigm and patient‐oriented research (POR) as an engagement strategy are combined to strengthen the process and outcomes of the research. Pragmatists use the most appropriate research methods to address issues at hand, where complex social problems need multipronged approaches. As an emerging healthcare research strategy, POR actively engages individuals with lived experience across all stages of the research process. While POR continues to garner attention within mixed‐methods research designs, there is a paucity of literature that considers POR in relation to pragmatism. Objective: As POR grows in popularity within the field of health care, there is a need to explore the theoretical and epistemological alignment with pragmatism and the implications to research. Methods: To address this need, we provide a critical review of the literature to examine the synergies between POR and pragmatism, and argue for the adoption of pragmatism as a paradigm for conducting POR. Main Results: This article begins with a discussion of the philosophical underpinnings informing the pragmatic paradigm. It then identifies key alignments between POR and pragmatism across three intersecting concepts: democratic values, collaborative approaches to problem‐solving and the pursuit of social justice. Discussion and Conclusions: Reflecting on our experiences engaging with patient partners in a mixed‐methods POR study titled READY2Exit, we illustrate the relevance of pragmatism to POR by applying these concepts to practice. Implications and considerations for conducting POR within the pragmatic paradigm are also described. Patient or Public Contribution: This paper provides a critical review of the literature and did not directly involve patients or the public. The authors reflected on their experiences collaborating with five young adult patient partners in the READY2Exit study (case exemplar described in this article) to demonstrate the relevance of the pragmatic paradigm to POR. We acknowledge and thank the young adult patient partners for their contributions to the research, for encouraging us to think critically about patient engagement in research, and for sharing their experiences. [ABSTRACT FROM AUTHOR]

Background: Problem‐solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE‐log data). Therefore, how cognition and affect intertwine and unfold over time in programming problem‐solving activities are rarely investigated. Objectives: In this study, we examined how the theory‐informed measures from multimodal data that we have selected as proxies for cognitive and affective dimensions of learning, are associated with student performance, and in comparison, to prior‐knowledge. Methods: A high‐frequency temporal data was collected with a camera, an electroencephalogram, and an eye‐tracker from 40 computer science students (bachelor and master studies) in the context of a code‐debugging activity. To study the cognitive processes associated with learning we focused on cognitive load theory (CLT) and the human information processing model. In addition, we complemented CLT with the model of affective dynamics in learning to avoid the machine reductionism perspective. Results: Our findings demonstrated that attention, convergent thinking, and frustration were positively correlated with students' successful code‐debugging (i.e., performance), and frequently manifested by high performing participants. Cognitive load, memory load, and boredom were negatively correlated with students' performance, and typically manifested by low performing participants. Implications: Extending the context of analysis in reference to student cognitive processes and affective states, affords educators not just to identify lower performers, but also to understand the potential reasons behind their performance, making our method an important contribution in the confluence of CER and the learning technology communities. In addition, the insights extracted from our analyses allow us to discuss potential avenues for improving learning design and the design of interactive learning systems to support the development of students' problem‐solving skills. Lay Description: What is currently known about the subject matter: ● Problem‐solving interlinks cognitive, affective and metacognitive dimensions of learning. ● In digital settings instructors struggle to distinguish cognitive‐affective states of students. ● Learning technologies require interventions based on cognitive‐affective states of students. What the paper adds: ● When and what cognitive‐affective states are triggered during solving a programming problem. ● What and how measures as proxies for cognitive‐affective states are associated with performance. ● Emphasizes the benefits of augmenting IDE‐log data with sensor data in the context of learning design. Implications of study findings for practitioners: ● Methodology guidelines to identify and model variability in humans' natural behaviours. ● Importance of content and instructions personalization for student engagement and learning. ● Identification of multimodal data proxies for flexible and adaptive multimodal interfaces. [ABSTRACT FROM AUTHOR]

Nowadays, students often practice problem‐solving skills in online learning environments with the help of examples and problems. This requires them to self‐regulate their learning. It is questionable how novices self‐regulate their learning from examples and problems and whether they need support. The present study investigated the open questions (1) to what extent students' (novices) task selections align with instructional design principles and (2) whether informing them about these principles would improve their task selections, learning outcomes, and motivation. Higher education students (N = 150) learned a problem‐solving procedure by fixed sequences of examples and problems (FS‐condition), or by self‐regulated learning (SRL). The SRL participants selected tasks from a database, varying in format, complexity, and cover story, either with (ISRL‐condition) or without (SRL‐condition) watching a video detailing the instructional design principles. Students' task‐selection patterns in both SRL conditions largely corresponded to the principles, although tasks were built up in complexity more often in the ISRL‐condition than in the SRL‐condition. Moreover, there was still room for improvement in students' task selections after solving practice problems. The video instruction helped students to better apply certain principles, but did not enhance learning and motivation. Finally, there were no test performance or motivational differences among conditions. Although these findings might suggest it is relatively 'safe' to allow students to independently start learning new problems‐solving tasks using examples and problems, caution is warranted: It is unclear whether these findings generalize to other student populations, as the students participating in this study have had some experience with similar tasks or learning with examples. Moreover, as there was still room for improvement in students' task selections, follow‐up research should investigate how we can further improve self‐regulated learning from examples and practice problems. Lay Description: What is (not) known about the subject matter: Learning new problem‐solving skills online with examples and problems is becoming more commonInstructional design principles (IDP) detail how to sequence tasks to optimize learning and motivationIt is unclear whether students spontaneously adhere to IDP when they select learning tasksNot much is known about how to support students to make better task selections What is the contribution of this paper: Students received a fixed task sequence (FS‐condition) or selected tasks themselves (SRL)Prior to SRL, SRL‐students watched a video about IDP (ISRL‐condition) or not (SRL‐condition)Results showed that (I)SRL‐students' task‐selections matched quite well with IDPThere were no differences among the FS and (I)SRL conditions in performance or motivation What are the implications of the findings: Students were quite capable of self‐regulating their learning from examples and problemsSRL was even as effective, efficient, and motivating as a fixed task sequenceWatching a video on IDP affected students' task‐selections, but did not enhance learning and motivationFuture research should examine how to further support SRL from examples and problems [ABSTRACT FROM AUTHOR]

Speaker verification models have achieved good results on the single genre data. But the performance degrades when model training and testing are not in the same domain. The adversarial training method is proposed to solve this problem by minimizing domain distribution differences. However, the adversarial training ignores domain‐specific information for the domain‐invariant speaker representations. In this paper, an improved collaborative adversarial network for domain adaptation in speaker verification is performed. Compared to the adversarial training, a collaborative discriminator is newly incorporated that learns domain‐specific information at the lower layers. Further, the projection block is added to the collaborative discriminator. It reduces the noise introduced by the collaborative discriminator. Experiments are conducted in different mismatch scenarios and using different speaker encoders. All the experimental results show that the performance of this method is better than the baseline and previous work using adversarial training. [ABSTRACT FROM AUTHOR]

A large number of NP‐hard graph problems are solvable in XP time when parameterized by some width parameter. Hence, when solving problems on special graph classes, it is helpful to know if the graph class under consideration has bounded width. In this paper we consider maximum‐induced matching width (mim‐width), a particularly general width parameter that has a number of algorithmic applications whenever a decomposition is "quickly computable" for the graph class under consideration. We start by extending the toolkit for proving (un)boundedness of mim‐width of graph classes. By combining our new techniques with known ones we then initiate a systematic study into bounding mim‐width from the perspective of hereditary graph classes, and make a comparison with clique‐width, a more restrictive width parameter that has been well studied. We prove that for a given graph H, the class of H‐free graphs has bounded mim‐width if and only if it has bounded clique‐width. We show that the same is not true for (H1,H2)‐free graphs. We identify several general classes of (H1,H2)‐free graphs having unbounded clique‐width, but bounded mim‐width; moreover, we show that a branch decomposition of constant mim‐width can be found in polynomial time for these classes. Hence, these results have algorithmic implications: when the input is restricted to such a class of (H1,H2)‐free graphs, many problems become polynomial‐time solvable, including classical problems, such as k‐ Colouring and Independent Set, domination‐type problems known as Locally Checkable Vertex Subset and Vertex Partitioning (LC‐VSVP) problems, and distance versions of LC‐VSVP problems, to name just a few. We also prove a number of new results showing that, for certain H1 and H2, the class of (H1,H2)‐free graphs has unbounded mim‐width. Boundedness of clique‐width implies boundedness of mim‐width. By combining our results with the known bounded cases for clique‐width, we present summary theorems of the current state of the art for the boundedness of mim‐width for (H1,H2)‐free graphs. In particular, we classify the mim‐width of (H1,H2)‐free graphs for all pairs (H1,H2) with ∣V(H1)∣+∣V(H2)∣≤8. When H1 and H2 are connected graphs, we classify all pairs (H1,H2) except for one remaining infinite family and a few isolated cases. [ABSTRACT FROM AUTHOR]

In this paper, the Vieta–Fibonacci wavelets as a new family of orthonormal wavelets are generated. An operational matrix concerning fractional integration of these wavelets is extracted. A numerical scheme is established based on these wavelets and their fractional integral matrix together with the collocation technique to solve fractional pantograph equations. The presented method reduces solving the problem under study into solving a system of algebraic equations. Several examples are provided to show the accuracy of the method. [ABSTRACT FROM AUTHOR]

This is Paper 1 in a 27‐paper series on the history of the development of the Woodward‐Hoffmann rules, also known as the Principle of Conservation of Orbital Symmetry. In addition to presenting an outline of this series, this manuscript provides a short overview of the chemical problem eventually solved by the Woodward‐Hoffmann rules. [ABSTRACT FROM AUTHOR]

Computational thinking (CT), which is a cognitive skill used to solve problems with computational solutions, has drawn increasing attention among researchers and practitioners due to the growing recognition of CT competence as a 21st century skill. Collaboration is commonly integrated into CT education to facilitate novice learning, but there is inadequate knowledge regarding the influences of collaboration in CT education. This meta‐analysis examined the overall effects on the cognitive, social and affective competencies of collaborative versus individual problem solving in CT through programming. We identified 33 publications involving 4717 learners, which allowed for 220 effect size comparisons. We found a medium effect size (Hedges' g = 0.562; p < 0.001) in favour of collaborative problem solving on cognitive learning outcomes and a small effect size (Hedges' g = 0.316; p < 0.01) on affective learning outcomes using a random‐effects model. Categorical moderator analysis revealed the moderating effects of educational level, programming environment, study duration, grouping method and group size. The competency model that was generated from the synthesized literature on collaborative computational problem solving yielded insights into the learning design and assessment of relevant activities. Practitioner notesWhat is already known about the topic?Although professional programming usually requires collaboration to accomplish common goals in the work environment, programming is predominantly taught on an individual basis in educational settings.Some intervention studies have reported inconsistent learning outcomes (positive and negative) from integrating collaborative problem solving (CPS) into programming education.There is a need for further scrutiny and exploration of the role of collaboration in the process of learning to program.What does this paper add?Our meta‐analysis showed that CPS is an effective pedagogical tool for developing students' cognitive, affective and social competencies.The moderator analysis revealed that CPS in programming has cognitive benefits irrespective of grouping method, group size and educational levels; however, there is a need for caution in regard to designing collaborative problem‐solving activities for different programming environments and durations.The model generated from the literature synthesis can yield insights into better assessing and designing collaborative problem‐solving activities.Implications for practice and/or policy?Integrating CPS into programming education can prepare students with 21st century skills.Social and affective competencies are crucial to students' learning capacity, which is an issue that needs to be better assessed.Future studies could look more rigorously into the effects of CPS in visual programming and robotics programming among younger age groups, such as primary or middle school students. [ABSTRACT FROM AUTHOR]

This paper investigates the stability of any n degree‐of‐freedom Hencky chain subjected to a full follower force at its tip and under kinematic constraints. We specifically solve this discrete problem and focus on its asymptotic behavior when n tends towards infinity and compare it with its analogous continuous formulation, also referred to as the kinematically constrained Beck's column. The divergence instability load of this non‐conservative discrete system under general kinematic constraints is ruled by the so‐called second‐order work criterion, which involves the symmetric part of the stiffness matrix. The application of the second‐order work criterion to the discrete repetitive system allows to find the exact divergence load pn$p_n$ under kinematic constraints, whatever the size of the discrete system. The critical value pn$p_n$ is obtained as the smallest positive root of explicit transcendent equations for both the generic (an≠0$a_n\ne 0$) and the singular (an=0$a_n=0$) cases, these two cases being illustrated by different values (respectively 2C and C) of the stiffness of the elastic torsion spring at the basis of the discrete system. The corresponding destabilizing kinematic constraint is also calculated. Asymptotic derivations show the convergence of the dimensionless buckling load towards the continuous one, equal to π2, and give the corresponding destabilizing kinematic constraint of the Beck's column. [ABSTRACT FROM AUTHOR]

Summary: Congestion problem in vehicular ad hoc networks (VANETs) is one of the main factors that negatively affect the inter‐vehicle communication (IVC) efficiency of such emerging networks. Decentralized congestion control (DCC) is an effective method for overcoming the congestion problem. However, lower priority packets such as cooperative awareness messages (CAMs) may be encountered with the starvation problem in the DCC approach. This paper proposes FDCC: a traffic‐centric Fuzzy DCC approach for improving CAMs delivery ratio, especially in congested traffic flows. FDDC architecture consists of four fuzzy inference systems (FISs). The inter‐vehicle distance (IVD) and the speed variation are the spatiotemporal fuzzy inputs, which are customized for both single direction and multi‐direction scenarios. Based on the FIS outputs, the FDCC control system, unlike the DCC, provides a way for processing starved CAMs by ignoring unnecessary even‐driven messages. The obtained simulation results through OMNET++ in both single and multi‐direction scenarios show the efficiency of FDCC in terms of the end‐to‐end delay, network throughput, and packet delivery ratio for event‐driven messages as well as essential CAMs. [ABSTRACT FROM AUTHOR]

This paper studies the inhomogeneous nonlinear Schrödinger equations, which may model the propagation of laser beams in nonlinear optics. Using the cross‐constrained variational method, a sharp condition for global existence is derived. Then, by solving a variational problem, the strong instability of solitary waves of this equation is proved. [ABSTRACT FROM AUTHOR]

Electrical resistance tomography (ERT)‐based distributed surface sensing systems, or sensing skins, offer alternative sensing techniques for structural health monitoring, providing capabilities for distributed sensing of, for example, damage, strain, and temperature. Currently, however, the computational techniques utilized for sensing skins are limited to planar surfaces. In this paper, to overcome this limitation, we generalize the ERT‐based surface sensing to nonplanar surfaces covering arbitrarily shaped three‐dimensional structures; we construct a framework in which we reformulate the image reconstruction problem of ERT using techniques of Riemannian geometry, and solve the resulting problem numerically. We test this framework in series of numerical and experimental studies. The results demonstrate the feasibility of the proposed formulation and the applicability of ERT‐based sensing skins to nonplanar geometries. [ABSTRACT FROM AUTHOR]

In order to solve the problem of unstable detection and low detection ability of traditional photoelectric detection target in complex environment, a design method of laser photoelectric detection sensor is proposed. Laser photoelectric detection sensor with active and passive laser detection screen is formed by adding line laser to the traditional photoelectric detection target. According to the characteristics of laser echo energy when the projectile passing through the laser detection screen, the calculation model of the laser echo power received by the photoelectric detector under the random intersection of projectile and target is established, and the signal‐to‐noise ratio calculation function of the system is derived. Through the comparative test, the results show that the detection ability of the laser photoelectric detection sensor is obviously better than that of the traditional photoelectric detection target, especially in the low illumination environment; moreover, the signal‐to‐noise ratio of the laser photoelectric detection sensor still follows the law of decreasing with the increase of detection distance, and it keeps the detection characteristics of photoelectric detection system. By increasing the laser emission power, the signal‐to‐noise ratio of the laser photoelectric detection sensor is improved to a certain extent, and the detection ability of the system is improved. The results verify that the design method and theoretical model of photoelectric detection sensor proposed in this paper are scientific and feasible. [ABSTRACT FROM AUTHOR]

The stochastic block model (SBM) is widely employed as a canonical model for network community detection. Recovering community labels under SBM is not a trivial task, since its theoretical optimization problem is NP‐hard. To solve this problem, numerous statistical methods have been developed in the literature, most of which are, however, not applicable to large‐scale networks. To overcome this limitation, in this paper, we propose a split likelihood (SL) framework, under which we provide a fast converging algorithm, named the SL algorithm, with significant advantages in terms of both community detection accuracy and computational efficiency. Moreover, to deal with networks with hub nodes or those with substantial degrees of variation within communities, we develop a variant of the SL algorithm, named the conditional SL (CSL) algorithm. We present the computational and statistical properties of the proposed algorithm. Then, we demonstrate the superiority of the proposed methods through a large amount of numerical experiments as well as two empirical analyses on real‐world networks. [ABSTRACT FROM AUTHOR]

The traditional approach of fermentation by a free cell system has limitations of low productivity and product separation that need to be addressed for production enhancement and cost effectiveness. One of potential methods to solve the problems is cell immobilization. Microbial cell immobilization allows more efficient up‐scaling by reducing the nonproductive growth phase, improving product yield and simplifying product separation. Furthermore, the emergence of nanomaterials such as carbon nanotubes, graphene, and metal‐based nanomaterials with excellent functional properties provides novel supports for cell immobilization. Nanomaterials have catalytic properties that can provide specific binding site with targeted cells. However, the toxicity of nanomaterials towards cells has hampered its application as it affects the biological system of the cells, which cannot be neglected in any way. This gray area in immobilization is an important concern that needs to be addressed and understood by researchers. This review paper discusses an overview of nanomaterials used for cell immobilization with special focus on its toxicological challenges and how by understanding physicochemical properties of nanomaterials could influence the toxicity and biocompatibility of the cells. [ABSTRACT FROM AUTHOR]

In this paper, we apply the characteristic finite volume method (CFVM) for solving a convection‐diffusion problem on two‐dimensional triangular grids. The finite volume method is used to discretize the equation while the finite element method is applied to estimate the gradient quantities at cell faces. The numerical analysis of the convergence has been implemented for the CFVM in one‐dimension. The approximate L2 norm of the error is derived to determine the errors for the approximate solution. The accuracy of four piecewise linear reconstruction techniques, namely, Frink, Holmes‐Connell, Green‐Gauss, and least‐squares methods are investigated on structured triangular grids. Numerical evidence shows that the least‐squares method is the most accurate of all methods for smooth initial condition problems. For discontinuous initial condition problems, the Frink and the Holmes‐Connell methods give a spurious oscillating solution in the vicinity of the discontinuity upstream of the discontinuity, and the Green‐Gauss and least‐squares methods give a spurious oscillating solution in the vicinity of the discontinuity downstream of the discontinuity. Moreover, the amplitude of the oscillation could be amplified on the finer grid sizes. [ABSTRACT FROM AUTHOR]

In this paper, we consider the nonnegative tensor least squares problem, which arises in the color image restoration. Based on the BB stepsize technique, we design a nonmonotonic descent stepsize and then derive a new gradient projection algorithm to solve this problem. The convergence analysis of the new gradient projected algorithm is given. Some numerical examples show that the new method is feasible and effective. Especially, some simulation experiments in the color image restoration problems illustrate that our algorithm is more effective than the existed algorithms. [ABSTRACT FROM AUTHOR]

Tensor completion is a challenging problem with various applications, especially in recovering incomplete visual data. Considering a color image or gray video as a three‐dimensional tensor, many related models based on the low‐rank prior of the tensor have been proposed. However, the low‐rank prior may not be enough to recover the original tensor from the observed incomplete tensor. In this paper, we propose a tensor completion method to recover color images and gray videos by exploiting both the low‐rank and sparse prior of the observed tensor. Specifically, the tensor completion task can be formulated as a low‐rank minimization problem with a sparse regularizer. The low‐rank property is depicted by the tensor truncated nuclear norm based on tensor singular value decomposition which is a better approximation of tensor tubal rank than tensor nuclear norm. While the sparse regularizer is imposed by a ℓ1‐norm in a discrete cosine transformation domain, which can better employ the local sparse property of the incomplete data. To solve the optimization problem, we employ an alternating direction method of multipliers in which we only need to solve several subproblems which have closed‐form solutions. Substantial experiments on real‐world images and videos show that the proposed method has better performances than the existing state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

In this paper, the inverse problem of initial value identification for homogeneous anomalous diffusion equation with Riemann‐Liouville fractional derivative in time is studied. We prove that this kind of problem is ill‐posed. We analyze the optimal error bound of the problem under the source condition and apply the quasi‐boundary regularization method, fractional Landweber iterative regularization method, and Landweber iterative regularization method to solve this inverse problem. Based on the results of conditional stability, the error estimates between the exact solution and the regular solution are given under the priori and posteriori regularization parameter selection rules. Finally, three examples are given to illustrate the effectiveness and feasibility of these methods. [ABSTRACT FROM AUTHOR]

In this paper, we show the existence of solutions of the convex minimization problems and common fixed problems in CAT(1) spaces under some mild conditions. For this, we propose the new modified the proximal point algorithm. Further, we give some applications for the convex minimization problem and the fixed point problem in CAT(κ) spaces with the bounded positive real number κ. Our results improve and generalize many recent important results in the literature. [ABSTRACT FROM AUTHOR]

The multiplicity of the second‐largest eigenvalue of the adjacency matrix A(G) of a connected graph G, denoted by m(λ2,G), is the number of times of the second‐largest eigenvalue of A(G) appears. In 2019, Jiang, Tidor, Yao, Zhang, and Zhao gave an upper bound on m(λ2,G) for graphs G with bounded degrees, and applied it to solve a longstanding problem on equiangular lines. In this paper, we show that if G is a 3‐connected planar graph or 2‐connected outerplanar graph, then m(λ2,G)≤δ(G), where δ(G) is the minimum degree of G. We further prove that if G is a connected planar graph, then m(λ2,G)≤Δ(G); if G is a connected outerplanar graph, then m(λ2,G)≤max{2,Δ(G)−1}, where Δ(G) is the maximum degree of G. Moreover, these two upper bounds for connected planar graphs and outerplanar graphs, respectively, are best possible. [ABSTRACT FROM AUTHOR]

Purpose: Radiotherapy is one of the main treatments of nasopharyngeal cancer (NPC) and lung cancer. Accurate segmentation of organs at risks (OARs) in CT images is a key step in radiotherapy planning for NPC and lung cancer. However, the segmentation of OARs is influenced by the highly imbalanced size of organs, which often results in very poor segmentation results for small and difficult‐to‐segment organs. In addition, the complex morphological changes and fuzzy boundaries of OARs also pose great challenges to the segmentation task. In this paper, we propose a cross‐layer attention fusion network (CLAF‐CNN) to solve the problem of accurately segmenting OARs. Methods: In CLAF‐CNN, we integrate the spatial attention maps of the adjacent spatial attention modules to make the segmentation targets more accurately focused, so that the network can capture more target‐related features. In this way, the spatial attention modules in the network can be learned and optimized together. In addition, we introduce a new Top‐K exponential logarithmic Dice loss (TELD‐Loss) to solve the imbalance problem in OAR segmentation. The TELD‐Loss further introduces a Top‐K optimization mechanism based on Dice loss and exponential logarithmic loss, which makes the network pay more attention to small organs and difficult‐to‐segment organs, so as to enhance the overall performance of the segmentation model. Results: We validated our framework on the OAR segmentation datasets of the head and neck and lung CT images in the StructSeg 2019 challenge. Experiments show that the CLAF‐CNN outperforms the state‐of‐the‐art attention‐based segmentation methods in the OAR segmentation task with average Dice coefficient of 79.65% for head and neck OARs and 88.39% for lung OARs. Conclusions: This work provides a new network named CLAF‐CNN which contains cross‐layer spatial attention map fusion architecture and TELD‐Loss for OAR segmentation. Results demonstrated that the proposed method could obtain accurate segmentation results for OARs, which has a potential of improving the efficiency of radiotherapy planning for nasopharynx cancer and lung cancer. [ABSTRACT FROM AUTHOR]

The concept developed during the SEMAFLEX project combines knowledge‐based document management with flexible workflow management to achieve ideal support for small‐ and medium‐sized enterprises. This paper focusses on the workflow approach that implements flexibility by deviation on the basis of constraint satisfaction problem solving. Workflow deviations due to unpredictable circumstances or upcoming events are tolerated at runtime, but still, support is maintained and possible succeeding work items are proposed. Procedurally modelled workflows are transformed to declarative constraints, which serve as database for the workflow engine. The described approach is fully implemented, and our experiments demonstrate sufficient runtime performance as well as improvements for practical use. [ABSTRACT FROM AUTHOR]

The traditional fuzzy Petri nets (FPNs) rarely contain the affective features when making reasoning decisions, primarily because the existing affective computing model is not suitable to be described directly in FPNs. In order to solve this problem, this paper introduces an attribute coordinate system and puts forward the affective representation and computing model based on the extraction and integration relationship between the attributes of things, which describes the affective change curve according to the cognition of the thinking subject to the attributes of the decision object. With this new model of affective computing, it is more convenient to utilize a qualitative mapping model and fuzzy qualitative judgment rules to express affective decisions and conveniently describe affective attributes in FPNs. A reasoning decision case illustrates the proposed method's feasibility and advantages. [ABSTRACT FROM AUTHOR]

Modern drug development problems are very complex and require integration of various scientific fields. Traditionally, statistical methods have been the primary tool for design and analysis of clinical trials. Increasingly, pharmacometric approaches using physiology‐based drug and disease models are applied in this context. In this paper, we show that statistics and pharmacometrics have more in common than what keeps them apart, and collectively, the synergy from these two quantitative disciplines can provide greater advances in clinical research and development, resulting in novel and more effective medicines to patients with medical need. [ABSTRACT FROM AUTHOR]

Summary: In multi‐user multiple input multiple output (MU‐MIMO) uplink, the bit error rate (BER) of linear detection schemes, namely, zero forcing (ZF) and minimum mean square error (MMSE) under correlated Rayleigh fading channel deteriorates with increase in spatial correlation and load factor due to the increase in the condition number of the channel matrix. Moreover, the performance gap between ZF and MMSE increases with increase in the antenna number for large load factors. To address this issue, in this paper, truncated singular value decomposition (TSVD), which is a popular method for solving ill‐posed problem, is used in the ZF detection process through proper selection of hard threshold. However, the pseudo‐inverse computed using TSVD is an approximate inverse, which results in interference at the output of the detection process. Therefore, a mathematical expression for the post‐processing signal‐to‐interference‐plus‐noise ratio (SINR) of the substream is derived and subsequently BER is evaluated. Further, the analytical BER is analyzed with respect to the parameters namely, average signal‐to‐noise ratio (SNR) (EsN0), correlation coefficient (ρU,ρB), load factor (β), and number of singular values considered to compute the hard threshold (n) and also validated by Monte Carlo trails. From the simulation results, it is observed that for higher order MU‐MIMO systems and at lower values of EsN0, the performance of TSVD‐based scheme is comparable with that of MMSE by decreasing the truncation parameter (k). Moreover, as the complexity of TSVD‐based ZF using randomized schemes is O(NU2NB+NU2log(k)+NUk2), therefore, the complexity of detection significantly decreases with decrease in k. [ABSTRACT FROM AUTHOR]

The response process of problem‐solving items contains rich information about respondents' behaviours and cognitive process in the digital tasks, while the information extraction is a big challenge. The aim of the study is to use a data‐driven approach to explore the latent states and state transitions underlying problem‐solving process to reflect test‐takers' behavioural patterns, and to investigate how these states and state transitions could be associated with test‐takers' performance. We employed the Hidden Markov Modelling approach to identify test takers' hidden states during the problem‐solving process and compared the frequency of states and/or state transitions between different performance groups. We conducted comparable studies in two problem‐solving items with a focus on the US sample that was collected in PIAAC 2012, and examined the correlation between those frequencies from two items. Latent states and transitions between them underlying the problem‐solving process were identified and found significantly different by performance groups. The groups with correct responses in both items were found more engaged in tasks and more often to use efficient tools to solve problems, while the group with incorrect responses was found more likely to use shorter action sequences and exhibit hesitative behaviours. Consistent behavioural patterns were identified across items. This study demonstrates the value of data‐driven based HMM approach to better understand respondents' behavioural patterns and cognitive transmissions underneath the observable action sequences in complex problem‐solving tasks. Lay Description: What is already known about this topic?: Process data of interactive problem‐solving tasks contains rich information about test‐takers.To extract underlying information from process data is a big challenge. ​ What this paper adds?: The hidden Markov model helps identify latent states underlying problem‐solving process.Different performance groups displayed different behaviour characteristics.A consistent behavioural pattern was observed across problem‐solving items. ​ Implications for practitioners: The use of HMM holds promise in better visualize and understand behaviour patterns in response process.HMM is potential in understanding cognitive transmissions underneath the observable action sequences. ​ [ABSTRACT FROM AUTHOR]

Summary: Although software‐defined networking (SDN) provides a flexible way to provision and control networks, it also makes network debugging and troubleshooting more complex. In SDN, the network is fully managed by software programs that increase flexibility and sophistication but are prone to bugs. Pinpointing those bugs is challenging because they can occur at multiple locations, such as the forwarding plane, the controller OS, and the network services running on top of the controller. Compared to functional bugs, performance bugs are particularly irritating due to their non‐failure semantics. They can lead to performance loss (reduced throughput, increased latency, and wasted resources) while maintaining the network connectivity. The literature reports several tools and techniques to diagnose SDN bugs, but, unfortunately, they are mostly ineffective against performance bugs. In this paper, we propose a novel monitoring and diagnostic framework capable of diagnosing performance bugs in the SDN data plane. The proposed tool works within Open vSwitch (OVS), a popular software switch, albeit it can easily be adapted to any OpenFlow switch. Tracing techniques are used to collect low‐level performance data from monitored switches. Our tool derives adapted performance metrics from kernel and userspace traces, and then displays them in time‐synchronized graphical views. These views provide valuable insights into OVS operation. They also enable practitioners to discover performance‐related issues and analyze their root causes. A few use cases are presented to demonstrate the efficiency of our tool in optimizing OVS performance and diagnosing its performance bugs. [ABSTRACT FROM AUTHOR]

Summary: Shared transportation is a new way of traveling generated by the rapid development of the "Internet +" and the sharing economy. Due to the limited energy carried by shared e‐bikes, the energy problem becomes the primary obstacle restricting its development. At present, one way to solve the energy problem is to use mobile charging vehicles (MCVs). However, how to schedule MCVs to achieve fast response, reduce energy consumption, and improve charging efficiency is crucial. In this paper, we propose a Charging Scheduling scheme based on Dynamic Characteristic of shared e‐bike in Obstacle Space (CSDC‐OS). Firstly, we design two MCV departure mechanisms to solve the problems of low utilization of MCVs and long waiting time for shared e‐bikes. Then, we design the schedulability conditions based on the A‐star algorithm and the dynamic change of e‐bikes to ensure that MCVs can return to the service station in time. Finally, we propose a charging sequence algorithm based on linear skyline query and a selective insertion algorithm to improve the charging efficiency of MCVs. Simulation results show that the CSDC‐OS can improve the response time, mobile consumption, and charging efficiency by more than 8% on average. [ABSTRACT FROM AUTHOR]

Summary: The digitization of objects has given birth to the concept of the Internet of Things (IoT) which is revolutionizing traditional objects by replacing them with intelligent objects such as smart vehicles, smartphones, smart home...etc. In this context, and with the emergence of vehicle networks, is born the need to increase the vehicular resources in order to benefit from several applications facilitating driving and ensuring the drivers safety, even going to think of the automated driving. The use of cloud computing has become the key solution to the lack of resources required to run compute‐intensive applications and the lack of storage space to back up all data related to roads and applications. In addition, we are witnessing the birth of the fog computing paradigm, which brings the functionalities of cloud computing at the edge of the network, thereby solving the latency problem for some time‐sensitive applications and also saving the bandwidth of the network because vehicle requests will not need to cross the entire network to be processed at the cloud level. In this paper, we discuss the different principles of cloud/fog computing and compare the two paradigms. We present a classification of data dissemination schemes in vehicular ad hoc networks (VANETs), vehicular cloud, and vehicular fog computing with their different architectures proposed. We finally present several cloud/fog computing applications. [ABSTRACT FROM AUTHOR]

Magnesium hydride (MgH2) has become a very promising hydrogen storage material because of its high hydrogen storage capacity, good reversibility and low cost. However, high thermodynamic stability and slow kinetic performance of MgH2 limit its practical application. In the past few decades, many alternative methods have been designed to solve this problem. A large number of studies have demonstrated that the use of metal catalyst doping modification, MgH2 nanocrystallization and other methods can greatly improve the hydrogen absorption and dehydrogenation performance of MgH2. Therefore, this paper reviews and summarizes the modification effect of transition metal catalyst doping on the hydrogen storage performance of MgH2, especially the catalysis on the de/rehydrogenation performance of MgH2. In addition, promoting effects of carbon materials, transition metal alloys and compounds on the hydrogen storage performance of MgH2 were also summarized. Finally, the existing problems and challenges of MgH2 as hydrogen storage materials are discussed, and some possible strategies are proposed. [ABSTRACT FROM AUTHOR]

A new image dehazing algorithm based on adaptive sky region is proposed in this paper, which shows good fidelity in sky region and satisfying visual effect in non‐sky region. For robust sky segmentation, we propose a rough‐to‐fine method that can make a balance between efficiency and accuracy. Considering distribution of haze is inconsistent, we divide the input image into three parts and calculate their atmospheric lights respectively. To solve the problem of invalid dark channel prior, we make an improvement for the transmission estimation. Finally, image fusion is taken as a post processing that can solve the problem of partial darkness and ensure a visual pleasing result. The experimental results for both synthetic and natural hazy images demonstrate that our algorithm performs comparable or even better results than the state‐of‐the‐art methods in terms of various measurement indexes, such as the PSNR, SSIM, and so forth. Besides, the proposed algorithm can be also applied in FPGA platform due to the optimized performance. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The failure process in brittle rocks is an important topic in rock mechanics, whose good understanding assists in predicting the strength and deformation characteristics of rocks. Because it is difficult to directly observe microcracks in laboratory tests, a numerical model is a useful tool for investigating microcracking behaviors. However, the mechanism of microcrack evolution is still unclear at the grain scale considering the microscopic heterogeneities. This paper proposes a polygonal universal distinct element code grain‐based model to solve this problem. Compared with other grain‐based models, this model is different in that mineral grains are subdivided into polygon blocks. The grain size, composition, and bond types of the contacts are incorporated, and both inter‐ and intra‐grain cracks are mimicked. Subsequently, micro‐parameters of the blocks and contacts are carefully calibrated according to the laboratory results. Following this, the calibrated model is employed to study the microcracking behaviors of granite in unconfined compression, confined compression, and Brazilian splitting tests. Both the cumulative numbers and locations of microcracks in different grains are recorded, and the types of macroscopic fractures are identified. The modeling results show that tensile cracks dominate the generated microcracks in the low confined compression tests, and the macroscopic fracture pattern is axial splitting. Shear cracks are dominant in the high confined compression tests, and the macroscopic failure pattern is X‐type shear failure. The simulated results are consistent with those observed in the laboratory tests, and thus, may assist in improving rock acoustic emission monitoring and understanding the damage process of rock. [ABSTRACT FROM AUTHOR]

This article aims to study how a thermoelastic medium having a bipolar nature is impacted by diffusion. It employs an analytical method called normal mode analysis to derive the formula for required physical quantities. The paper utilizes Green‐Naghdi theory (G‐N III) along with the three‐phase‐lag (3PHL) model to solve the existing problem. The comparisons are established graphically for different values of the phase‐lag times, the presence and absence of diffusion, and the time parameter with respect to Green‐Naghdi theory and the 3PHL model. [ABSTRACT FROM AUTHOR]

Industry 4.0 is changing data collection, storage, and analysis in industrial processes fundamentally, enabling novel applications such as flexible manufacturing of highly customized products. However, real‐time control of these processes has not yet realized its full potential in using the collected data to drive further development. Indeed, typical industrial control systems are tailored to the plant they need to control, reusing, and adapting to challenge. In the past, the need to solve plant‐specific problems overshadowed the benefits of physically isolating a control system from its plant. We believe that modern virtualization techniques, specifically application containers, present a unique opportunity to decouple control from plants. This separation permits us to fully realize the potential for highly distributed and transferable industrial processes even with real‐time constraints arising from time‐critical subprocesses. This paper explores the challenges and opportunities of shifting industrial control software from dedicated hardware to bare‐metal servers or (edge) cloud computing platforms using off‐the‐shelf technology, that is, technologies commercially available. We present a migration architecture and show, using a specifically developed orchestration tool, that containerized applications can run on shared resources without compromising scheduled execution within given time constraints. Through latency and computational performance experiments, we explore three system setups' limits and summarize lessons learned. [ABSTRACT FROM AUTHOR]

The rapid development of electronic skins has allowed novel multifunctional human–machine interaction interfaces, especially in motion interaction sensors. Although motion sensing is widely used in advanced flexible electronic devices through the integration of single sensing units, the number of electrodes has increased with the increase in integration by the square multiple. This paper presents a self‐powered electronic skin based on the Archimedes spiral structure design, which can detect the multi‐directional movement of the slider without external energy supply. As the rotation angle of the Archimedes spiral increases from 2π to 4π, the maximum resolvable movement direction of the device increases from 24 to 280, and the number of electrodes is kept at 4. Through the exploration of the principle of triboelectricity, the inherent electronegativity of the triboelectric materials is used as the basis for signal discrimination, which not only increases the reliability of the device, but also solves the problem of energy supply during device operation. A reduced number of electrodes and its battery‐free nature enables this electronic skin to be easily integrated into portable electronic devices, such as laptops, smart phones, healthcare devices, etc. [ABSTRACT FROM AUTHOR]

To solve the fabrication problems of traditional precast shear walls caused by too many connections joints, a new type of precast shear wall with unconnected vertically distributed reinforcements and concealed bracings is developed in this paper. Four full‐scale shear walls, including one cast‐in‐place specimen and three precast specimens, were tested under low‐cycle lateral loading conditions to evaluate the seismic performance of the new type of precast shear wall. The test results showed that the loading capacity and energy dissipation of the new type of precast shear wall were comparable to those of the cast‐in‐place specimen; however, the failure mode was similar to the damage mechanism of an infilled wall frame, not the traditional bending‐shear mode of shear walls. Then, a new strut‐and‐tie model considering dowel action was proposed for this new type of precast shear wall. Finally, a parametric study was conducted by finite element analysis to determine a reasonable value of the effective strength coefficient for the strut‐and‐tie model. Good agreement was achieved between the test and model results. [ABSTRACT FROM AUTHOR]

At present, intermittent control is a main method to solve the problem of pumping output voltage with light load of LLC resonant converter, which can not only solve the problem of high pumping output voltage, but also, to a certain extent, improve the efficiency of light load to a certain extent when converter is operating. However, in extremely light‐loading, especially in no‐ loading, with the intermittent cycle increasing and the low‐frequency ripple being introduced, which cannot meet the demand of high‐quality output voltage, and is not conducive to the converter's stable operation. Due to the extremely small power transferred by the converter, in this case, efficiency is not the main factor considered. In this paper, a voltage regulation strategy based on energy feedback is proposed for LLC resonant converter in extremely light‐loading. The output voltage is controlled by adjusting the feedback energy to the source. Compared with the uncontrollable burst off mode of the intermittent control, the proposed control method can effectively improve the output voltage quality due to the controllability in voltage drop mode and the independence from the load. It also can eliminate low frequency ripple and extend battery charging life. The output voltage ripple is minimized by optimizing the duty cycle and the phase shift angle. The correctness and feasibility of the proposed method are verified by experiments. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]