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With heightened uncertainties and risks in the fluctuating business environment, existing studies have concentrated on elucidating how service organizations leverage human resource practices to adapt to and survive such unforeseen and disruptive threats. However, how such practices could serve the strategic objective of cultivating a sustainably thriving workforce across different situations is not well understood. Thriving is a core transitional state that fosters positive behaviors, such as creative customer‐related problem‐solving. Applying social information processing theory, we propose and test a model by exploring how organizations that engage in thriving‐oriented human resource management (HRM) encourage employees to take responsibility and promote constructive change, thereby activating their creative problem‐solving behaviors. Specifically, we theorize and develop measures to promote thriving‐oriented HRM in Study 1. In Study 2, we collected multisource and multi‐wave data from 296 frontline service employees and 45 supervisors in China. Our findings reveal that thriving‐oriented HRM is positively related to felt responsibility for change, which ultimately encourages creative problem‐solving. We also show that the threat imposed by a crisis, that is, the COVID‐19 pandemic, strengthens the positive relationship between thriving‐oriented HRM and felt responsibility for change. Our study contributes to the HRM literature, especially on thriving‐oriented HRM and employee perception, and has practical implications for service organizations in the uncertain context. [ABSTRACT FROM AUTHOR]

We propose a new work design model, SMART work design, that identifies five higher order categories of work characteristics, including stimulating work characteristics (task variety, skill variety, information processing requirements, and problem‐solving requirements), mastery work characteristics (job feedback, feedback from others, and role clarity), autonomous work characteristics (decision‐making autonomy, timing autonomy, and method autonomy), relational work characteristics (social support, task significance, and beneficiary contact), and tolerable work characteristics (low levels of: role overload, work–home conflict, and role conflict). Higher order confirmatory factor analysis of working participants provided initial evidence of this structure (Study 1, N = 1107), which was replicated in an additional dataset (Study 2, time 1, N = 709). To provide further evidence, we examined Study 2 data across three waves (N = 573) to show that each higher order factor at time 1 predicted time 3 job satisfaction either directly or via the theorized time 2 mediators (challenge appraisals, work meaningfulness, fulfillment of relatedness needs, and activated negative affect). In Study 3 (N = 108), employees' scores on specific higher order variables correlated with leader ratings of performance in the expected ways. The SMART work design model provides a unique integrating and multidimensional theory of work design that extends beyond existing models. The model can be used to facilitate the synthesis of research knowledge and guide scholars and practitioners to diagnose and address contemporary work design challenges. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the existence of insensitizing controls for the micropolar fluids in a bounded domain with homogeneous Dirichlet boundary conditions and arbitrarily located internal controller. The study of insensitizing controls is essential to solve a stability problem, which means that we look for controls such that some functionals of the velocity fields (the so‐called sentinels) are insensitive to the small perturbations of initial data. The problem of insensitizing controls is transformed into a suitable controllability problem for a cascade system. Our proof relies on a new global Carleman inequality and the inverse mapping theorem. [ABSTRACT FROM AUTHOR]

This paper aims to recover the initial value and source term simultaneously in the parabolic equations with convective term from measurements at two fixed times t0$$ {t}_0 $$ and T$$ T $$. In particular, we analyze the ill‐posedness of the inverse problem and then apply the Fourier truncated regularization method to solve the inverse problem. A theoretical analysis of the error estimation for the initial value and source term is also given. Finally, we present some numerical examples to verify the validity and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Conceptual engineering is the process of assessing and improving our conceptual repertoire. Some authors have claimed that introducing or revising concepts through conceptual engineering can go as far as expanding the realm of thinkable thoughts and thus enable us to form beliefs, hypotheses, wishes, or desires that we are currently unable to form. If true, this would allow conceptual engineers to contribute to solving stubborn problems – problems that cannot be solved with our current ways of thinking. We call this kind of conceptual engineering heavy‐duty conceptual engineering. As exciting as the idea of heavy‐duty conceptual engineering sounds, it has never been developed or defended. In this paper, we pursue a two‐fold goal. First, to offer a theory of heavy‐duty conceptual engineering that distinguishes it from other kinds of conceptual engineering; second, to show that heavy‐duty conceptual engineering is possible, both in theory and in practice, and to explain how it can be applied in the service of solving stubborn problems. The central idea is that heavy‐duty conceptual engineering can enhance the semantic expressive power of a conceptual system by the use of bootstrapping processes. [ABSTRACT FROM AUTHOR]

The problem of characterization of all graphs where the deletion of an edge results in decrease or increase in the energy is far from completion. To be more exact, we solve this problem for Inverse Sum Indeg energy. We compute the ISI energies of edge deleted graphs of Kn$$ {K}_n $$, Kn,n$$ {K}_{n,n} $$, Kn,n,n$$ {K}_{n,n,n} $$, and star graph, finally we compare the respective energies from the original graphs. We give different graphs where both cases can happen. This serves as partial solutions of the modified version of the hard to crack problem posed by Gutman to characterize all graphs whose energy decreases after deletion of an edge. [ABSTRACT FROM AUTHOR]

With the development of 3D discontinuous deformation analysis (DDA) in precise stress fields and crack propagation problems, it has also demonstrated outstanding capabilities in solving continuous–discontinuous problems. However, currently, 3D DDA modeling primarily focuses on generating rock joint networks and developing 3D cutting algorithms. Correspondingly, 3D geological modeling methods are not yet mature, and establishing 3D models often demands substantial time. The lack of supporting preprocessing modeling methods and corresponding visual operation interfaces significantly hampers the development of 3D DDA. This method builds upon advanced research achievements in unmanned aerial vehicle oblique photography, 3D reconstruction, 3D cutting, computer graphics, and visualization program design. This research establishes a 3D geological entity modeling method for 3D DDA and constructs a comprehensive program using relevant C++ libraries and C language interfaces. In this method, a 3D geological model that incorporates geological elements such as strata and faults is initially established using non‐uniform rational B‐splines (NURBSs) surfaces as the boundary of the solid model. Subsequently, finite element meshing is applied, followed by corresponding topology transformation, resulting in a 3D block system model suitable for 3D DDA calculation. To cater for diverse application scenarios, continuous–discontinuous models integrated with subblocks and models of arbitrary polyhedra can be established. The proposed method has been validated through several typical modeling examples, showing its ability to rapidly and generate 3D high‐precision geological reality models suitable for 3D DDA calculations. Additionally, some techniques used in this method can be extended for modeling other numerical simulation methods, warranting further research. [ABSTRACT FROM AUTHOR]

In this paper we establish for the first time local semiconvexity estimates for fully nonlinear equations and for obstacle problems driven by integro‐differential operators with general kernels. Our proof is based on the Bernstein technique, which we develop for a natural class of nonlocal operators and consider to be of independent interest. In particular, we solve an open problem from Cabré‐Dipierro‐Valdinoci. As an application of our result, we establish optimal regularity estimates and smoothness of the free boundary near regular points for the nonlocal obstacle problem on domains. Finally, we also extend the Bernstein technique to parabolic equations and nonsymmetric operators. [ABSTRACT FROM AUTHOR]

Background Objectives Methods Results and Conclusions Process data captured by computer‐based assessments provide valuable insight into respondents' cognitive processes during problem‐solving tasks. Although previous studies have utilized process data to analyse behavioural patterns or strategies in problem‐solving tasks, the connection between latent cognitive states and their theoretical interpretation in problem solving remains unclear.This research aims to investigate the connections between similar hidden response states and unfold respondents' transition paths in problem‐solving processes. Analysing process data from the 2012 United States Programme for the International Assessment of Adult Competencies (PIAAC), this study seeks to discern patterns in problem solving among participants.The hidden Markov model was first used to uncover the hidden states based on a sequence of observed actions. Next, Gaussian graphical network analysis was employed to analyse the relationships between hidden response states.Results indicated that correct responders had simpler, clearer state relationships, while incorrect responders displayed more complex connections. Respondents who solved the tasks correctly had clearer thoughts about the problem‐solving process, whereas incorrect respondents struggled to understand the problem and failed to figure out solutions. Cognitive state changes during problem solving also varied between groups. The correct groups showed cohesive, logical transitions, in contrast to the emerged isolated, erratic patterns of the incorrect groups. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper investigates a nonlinear two‐player non‐zero‐sum differential game with state and input constraints. To solve this problem, this paper constructs a neural network (NN) framework to approximate the solution of the Hamilton‐Jacobi‐Isaacs (HJI) equation. The adaptive dynamic programming (ADP) method is utilized where each player only needs one critic NN. To solve the issue of state and input saturations, this paper develops a novel constrained system for the differential game, firstly to make the states within the predetermined constraint set. Then, the non‐quadratic expression is used to substitute the traditional quadratic expression for the two‐player non‐zero‐sum differential game, and both of the inputs of the two players are constrained. With these treatments, the control input and the system are more in line with real‐world applications. Moreover, the stability of the system is also analyzed using the Lyapunov theorem. Two numerical examples are presented to illustrate that the critic NN weights estimation errors and the system are uniformly ultimately bounded (UUB), and the state and input constraints can be achieved. [ABSTRACT FROM AUTHOR]

This article is devoted to solving a backward problem for general nonlinear parabolic equations in Sobolev spaces. The problem is hardly solved by computation since it is severely ill‐posed in Hadamard's sense. Using the Fourier transform and the truncation of high‐frequency components, we construct a regularized solution for the problem from the data given inexactly. As usual for ill‐posed problems, the rate of convergence can be obtained under additional smoothness assumptions on the regularity of the exact solution, the so‐called source conditions. By using a source condition in a generalized form, we prove a convergence estimate in a Sobolev space Hq(ℝn)$$ {H}^q\left({\mathrm{\mathbb{R}}}^n\right) $$. Corresponding to different levels of the source condition, the convergence rates are improved gradually. We apply our theory to the backward problem with a convection–diffusion operator and a cubic nonlinearity. Finally, the numerical results are presented to test the validity of the proposed regularization method. [ABSTRACT FROM AUTHOR]

The aim of this paper is twofold. The first goal is to give well‐posedness results for a Robin–transmission problem and a Robin–Dirichlet problem for the Brinkman system in bounded Lipschitz domains in Rn,n≥2$$ {\mathbb{R}}^n,n\ge 2 $$. The Robin–Dirichlet problem appears as a special limit case of the Robin–transmission problem. This aim is achieved by employing the layer potential theoretical methods. The second goal is to provide a well‐posedness result for a Robin–transmission problem and an existence result for the Robin–Dirichlet problem for a Navier–Stokes type system in bounded Lipschitz domains in Rn,n=2,3$$ {\mathbb{R}}^n,n=2,3 $$. Again, the Robin–Dirichlet problem appears as a special limit case of the Robin–transmission problem. This aim is achieved by using the well‐posedness results in the linear case combined with a fixed point argument. In order to illustrate our theoretical results, we also consider a special case of boundary value problems of Robin–Dirichlet type, which models a fluid flow in a porous square cavity. We solve numerically this problem. [ABSTRACT FROM AUTHOR]

The contraction or expansion of a cylindrical cavity in an elastoplastic medium is usually analyzed from a continuum based approach with a plasticity constitutive model. However, localized deformations, which are rooted in the post‐failure softening response of geomaterials, are observed in the form of spiral‐shaped fractures in laboratory tests. An alternative approach based on dislocation theory is introduced in this paper for modeling cavity contraction or expansion. In this model, several equally spaced spiral‐shaped shear fractures initiate and propagate away from the cavity within the linearly elastic medium. The Mohr‐Coulomb criterion and a dilatancy rule are imposed on the shear fractures to constrain the stresses and the displacement jumps. The direction of fracture propagation is determined by minimizing plastic dissipation. The displacement discontinuity method is used to discretize the shear and normal displacement jumps along the fracture and solve the problem numerically. The calculated crack path follows a logarithmic‐like spiral, similar to the slip lines predicted by plasticity theory. The relationship between the pressure and radial displacement at the cavity boundary converge towards the classical elastoplastic solution as the number of fracture branches increases. [ABSTRACT FROM AUTHOR]

Although graph convolutional networks have achieved good performances in skeleton‐graph‐based action recognition, there are still some problems which include the incomplete utilization of skeleton graph features and the lacking of logical adjacency information between nodes in adjacency matrix. In this article, a human action recognition algorithm is proposed based on multiple features from the skeleton graph to solve these problems. More specifically, an improved adjacency matrix is constructed to make full use of the multiple skeleton graph features. These features include local differential features, multi‐scale edge features, features of the original skeleton graph, nodal features, and nodal motion features. Extensive results are conducted on four standard datasets (NTU RGB‐D 60, NTU RGB‐D 120, Kinetics, and Northwestern‐UCLA). The experimental results show that the proposed algorithm outperforms the SOTA action recognition algorithms. [ABSTRACT FROM AUTHOR]

Handwriting is a natural way to communicate and exchange ideas, but converting handwritten diagrams to application‐specific digital formats requires skill and time. Automatic handwritten document conversion can save time, but diagrams and text require different recognition engines. Since accurate segmentation of handwritten diagrams can improve the accuracy of later diagram recognition steps, the authors propose to solve the problem of segmentation of text and non‐text elements of handwritten diagrams using deep semantic segmentation. The model, DeepDP is a flexible U‐net style architecture that can be tuned in complexity to a level appropriate for a particular dataset and diagram type. Experiments on a public hand‐drawn flowchart dataset and a business process diagram dataset show excellent performance, with a per pixel accuracy of 98.6% on the public flowchart datasets and improvement over the 99.3% text stroke accuracy and 96.6% non‐text stroke accuracy obtained by state of the art methods that use online stroke information. On the smaller offline business process diagram dataset, the method obtains a per‐pixel accuracy of 96.9%. [ABSTRACT FROM AUTHOR]

Infrared and visible image fusion involves merging the advantages of infrared and visible images to generate a composite image that encompasses thermal radiation as well as intricate texture details. Infrared and visible image fusion has garnered increasing attention, with numerous fusion methods proposed. However, how to fairly perceive the performance of fused image remains a contentious topic. This paper is dedicated to solving this problem from two perspectives (e.g., subjective and objective aspects). Firstly, an infrared and visible fusion image quality assessment dataset was constructed, including 60 pairs of infrared and visible images captured in various scenes, along with 540 fusion images with different types and degrees of distortions. Additionally, a subjective evaluation dataset of 16,200 subjective scores by 30 participants was further provided for the fused image. Secondly, to overcome the challenging assessment for infrared and visible fusion images without a real reference image, an interesting multi‐domain pseudo‐reference image quality assessment model (MPIQAM) is proposed, by comprehensively considering the thermal radiation information distortion, texture information distortion, and overall naturalness of the fused image. The proposed MPIQAM was compared with 18 mainstream objective metrics, and the experimental findings showcased a commendable level of competitiveness. [ABSTRACT FROM AUTHOR]

In practical production applications, the efficiency and success rate of gesture recognition directly affect the user experience and work efficiency. However, the existing gesture recognition models have the problem of a large number of model parameters and high computational complexity, which makes them unable to meet the needs of end‐to‐end industrial deployment. To solve these problems, this article proposes a gesture recognition model based on YOLOv8. First, FasterNet is adopted as the backbone of YOLOv8, which significantlydecrease the number of parameters and made the model more lightweight. By reducing the number of parameters, the computational complexity of the model can be reduced while maintaining the performance of the model, and the operation efficiency of the model can be improved. Second, recombination convolution ScConv is introduced to replace common convolution operations to further improve the model's efficiency. Recombination convolution can reduce the computation and make up for the loss of precision to some extent. Finally, the MDPIoU loss function is used to optimize target location and prediction, to improve the accuracy of the model. The MDPIoU loss function can better deal with the problem of target boundary frame positioning and prediction so that the model can locate and predict gestures more accurately in gesture recognition tasks. Experiments on a data set containing 10 types of gestures show that the number of parameters and floating point calculations of the improved network model are reduced by 45% and 42.7%, respectively, while the accuracy is unchanged. The improved model can be deployed on edge terminals, providing efficient and accurate gesture recognition. [ABSTRACT FROM AUTHOR]

Pancreas segmentation has great significance in computer‐aided diagnosis of pancreatic diseases. The small size of the pancreas, high variability in shape, and blurred edges make the task of pancreas segmentation challenging. A new model called SEY‐Net is proposed to solve the above problems, which is a one‐stage model with multi‐inputs. SEY‐Net is composed of three main components. Firstly, the edge information extraction (EIE) module is designed to improve the segmentation accuracy of the pancreas boundary. Then, the SE_ResNet50 is selected as the encoder's backbone to fit the size of the pancreas. Finally, the dual cross‐attention is integrated into the skip connection to better focus on the variable shape of the pancreas. The experimental results shows that the proposed method has better performance and outperforms the other existing state‐of‐the‐art pancreas segmentation methods. [ABSTRACT FROM AUTHOR]

On June 1, 1965, R. B. Woodward and Roald Hoffmann published their third communication in the Journal of the American Chemical Society in which they applied orbital symmetry control to explain the mechanism of a wide variety of valence isomerizations that they termed “sigmatropic reactions.” This publication reveals the research trajectory taken by Hoffmann from which this portion of the no‐mechanism problem was solved. Hoffmann used five different quantum chemical tools, all based on either extended Hückel theoretical calculations or frontier molecular orbital theory, in his research. Hoffmann′s laboratory notebooks and his three draft manuscripts along with Woodward′s four subsequent drafts have survived the past 59 years and provide an excellent window into the thinking and manuscript‐writing processes used by these Nobel laureates in February‐April 1965. [ABSTRACT FROM AUTHOR]

ABSTRACT The time domain is the most widely chosen alternative in mechanical fatigue tests to completely represent random events. However, the main disadvantages of this approach are the long time required to complete the tests and the high cost of the complex equipment. On the other hand, fatigue test in the frequency domain is a potential alternative to overcome these disadvantages. That is, it requires less sophisticated equipment, because it uses only simple actuators instead of servo actuators. Moreover, the duration of the fatigue test is reduced, because the total length of the event is replaced by constant repetitions and constant damage. The objective of this work is to propose and develop a methodology that uses the results of structural fatigue as a starting point, and through an optimization problem solved by the genetic algorithm, it determines which loads/displacements caused them in the frequency domain. The purpose is to assist future developments in fatigue tests, supplanting tests in the time domain without losing the correlation in results. [ABSTRACT FROM AUTHOR]

We propose a simple, efficient, and reliable procedure for implicit time stepping, regarding a special case of the viscoplasticity model proposed by Simo and Miehe (1992). The kinematics of this popular model is based on the multiplicative decomposition of the deformation gradient tensor, allowing for a combination of Newtonian viscosity and arbitrary isotropic hyperelasticity. The algorithm is based on approximation of precomputed solutions. Both Lagrangian and Eulerian versions of the algorithm with equivalent properties are available. The proposed numerical scheme is non‐iterative, unconditionally stable, and first order accurate. Moreover, the integration algorithm strictly preserves the inelastic incompressibility constraint, symmetry, positive definiteness, and w‐invariance. The accuracy of stress calculations is verified in a series of numerical tests, including non‐proportional loading and large strain increments. In terms of stress calculation accuracy, the proposed algorithm is equivalent to the implicit Euler method with strict inelastic incompressibility. The algorithm is implemented into MSC.MARC and a demonstration initial‐boundary value problem is solved. [ABSTRACT FROM AUTHOR]

ABSTRACT This article investigates anti‐attack stabilization with passivity problem of uncertain singular semi‐Markov jump systems (singular S‐MJSs) with exogenous disturbance and delay. An ingenious non‐fragile observer‐based neural sliding mode control (SMC) scheme is put forward to solve the problem. First, considering unmeasured states, a distinctive non‐fragile and decoupled observer, which does not contain the control input or any auxiliary sliding mode compensator design as in existing observer‐based SMC approaches, is established such that the disadvantages of sliding mode switching in observers in existing literature can be avoided. Then, “only one sliding surface” design and a new system analysis route are presented, and the derived sliding surface is accessibly designed. Next, a new version of stochastic admissibility and passivity sufficient condition is given, and a related algorithm via an optimization problem is proposed to determine the controller gain and the observer gain by linear matrix inequalities (LMIs). Further, a novel observer‐based anti‐attack neural SMC law, which utilizes a neural network‐based approach to approximate actuator attack, is proposed to stabilize the singular S‐MJSs against actuator attack. Finally, simulation and comparison results are presented, which demonstrate the effectiveness and superiority of our method. [ABSTRACT FROM AUTHOR]

This paper explores the role of measurement as a cognitive technology across human history, emphasizing the coexistence of formal and informal measurement systems. While standardized systems dominate contemporary culture and are well documented across large‐scale societies of the past, this manuscript highlights the less explored domain of informal measurement practices that have been integral to daily life from the past to the present. Through the examination of body‐based measurement systems and proportional heuristics, we demonstrate how these informal strategies were not merely precursors to formal standards but essential adaptive tools for solving everyday problems. Often, these informal solutions come with practical advantages. This manuscript calls for a broader recognition of their significance in cultural and technological evolution. [ABSTRACT FROM AUTHOR]

In order to eliminate the adverse effects caused by power coupling of the isolated three‐port converter (ITPC), this paper proposes a three‐port resonant converter that uses a switch‐controlled‐capacitor (SCC) and an auxiliary inductor, which has resonant parameter compensation capability (RPC‐ITPC). The topology and operational principle of RPC‐ITPC are discussed in detail. To achieve resonant‐type power decoupling, it is usually necessary to ensure that the resonant frequency of the decoupling port resonant tank is consistent with the switching frequency, which puts high demands on the accuracy of the resonant components. To address the sensitivity of resonant‐type power decoupling to the parameters of resonant components, an SCC was adopted to solve the problem. The use of SCC enables the RPC‐ITPC to have resonant parameter compensation capability. In order to further optimize the performance of the RPC‐ITPC, a triple‐phase‐shift (TPS) modulation strategy is proposed to achieve the minimum RMS value of resonant current (MRMS‐TPSMS). Under the MRMS‐TPSMS, the switching devices of the power decoupling port have difficulty achieving ZVS turn‐on. To circumvent this problem, we realize ZVS of the decoupling port switching devices via auxiliary inductor current injection. Finally, a 1 kW experimental prototype was constructed to validate the theoretical propositions presented in this study. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In damage‐level classification, deep learning. models are more likely to focus on regions unrelated to classification targets because of the complexities inherent in real data, such as the diversity of damages (e.g., crack, efflorescence, and corrosion). This causes performance degradation. To solve this problem, it is necessary to handle data complexity and uncertainty. This study proposes a multimodal deep learning model that can focus on damaged regions using text data related to damage in images, such as materials and components. Furthermore, by adjusting the effect of attention maps on damage‐level classification performance based on the confidence calculated when estimating these maps, the proposed method realizes an accurate damage‐level classification. Our contribution is the development of a model with an end‐to‐end multimodal attention mechanism that can simultaneously consider both text and image data and the confidence of the attention map. Finally, experiments using real images validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In addition to considering the influence of a species on other species (centrality), the identification of keystone species should also consider whether it has a unique network position (uniqueness). Clarifying the correlation between species centrality and uniqueness, or whether central species exhibit positional redundancy in food webs, can enhance the understanding of mechanisms stabilizing food webs. However, the findings from analyses utilizing different measures of uniqueness are contentious. In this study, we constructed the food web of the eutrophic Zhangze Lake (northern China) using stable isotopes to estimate the contribution of food sources to consumers. We then calculated trophic field overlap index to assess the uniqueness of species using this quantified food web information. Additionally, we analyzed how the weak interaction and the threshold value under which interactions are considered as weak influence the relationship between species uniqueness and centrality. The findings revealed that, in contrast to the traditional trophic field overlap index, the improved index identified the basal species with the strongest trophic interactions with other species and the filter‐feeding fishes with the fewest interactors as the most unique species, while the basal species were considered the least unique under the traditional index. The ranking results of the traditional index and the centrality showed a significant negative correlation, whereas the improved index displayed a positive correlation, which was caused by the comprehensive consideration of threshold and weak interaction. In addition, based on the data analysis, the suggestion was given for the selection of indices used to identify unique species, and whether central species have positional redundancy was explored. The methodology used in study provides a practical solution for the identification of the most unique species, points out and solves the problems faced in the uniqueness analysis, and advances the understanding of the mechanisms underlying food web robustness. [ABSTRACT FROM AUTHOR]

Sn/Pb perovskite is an  attractive photovoltaic material due to its low toxicity and ideal bandgap. However, the performance of Sn/Pb perovskite solar cells (PSCs) is lower than its Pb‐based counterpart. The main reason originates from the poor crystallinity of Sn/Pb perovskite film. To solve this problem, the crystallization kinetics of Sn/Pb perovskite prepared by the two‐step method is deeply explored and proposed an effective additive of 3‐Hydrazinylpyridine Hydrochloride (3‐HH) to regulate the crystallization process of Sn/Pb perovskite. The results indicate 3‐HH additive promotes fast nucleation, delays the formation and growth of perovskite microcrystals, balances the crystallization rate of Sn/Pb phase perovskite in the initial stage, and then accelerates perovskite microcrystal coalescence in the later stage. Furthermore, the perovskite surface is ameliorated by 3‐HH post‐treatment and a more matched energy level arrangement is attained. Simultaneously, 3‐HH doping and/or post‐treatment passivates perovskite defects and suppresses the oxidation of Sn2+. Benefiting from these effects of 3‐HH, the device with 3‐HH doping and post‐treatment obtains a PCE of 18.329%, which is higher than that of the control device (16.362%). The unencapsulated PSCs with 3‐HH‐modification retain 85% PCE after stored in the glove box for 1500 h, while the control device keeps only 66% PCE. [ABSTRACT FROM AUTHOR]

We present predictive models of the size‐dependent buckling loads of non‐uniform Bernoulli–Euler beams under thermal effects based on the two‐phase local/nonlocal elastic model. The beam ends are assumed to be constrained by elastic springs with translational and rotational stiffness to simulate general boundary conditions. In contrast to most literature in this field, both the bending and thermal deformations of the beams are simultaneously considered to be two‐phase local/nonlocal of two phases, that is, the thermal effect is taken as equivalent to a size‐dependent thermal load. By using the fully equivalent differential form of the local/nonlocal equation with a set of constitutive boundary conditions, the problem is solved numerically with the aid of the generalized differential quadrature method (GDQM). Through conducting validation study, several parametric studies are given for examining the effects of the slope of beams’ thickness variation, nonlocal parameter, and elastically supported conditions on the buckling loads of non‐uniform beams. The results show that constrained stiffness has a drastic influence on the critical bucking loads of the beams. Furthermore, the consideration of the two‐phase thermal load will further reduce the actual buckling load of the beams. [ABSTRACT FROM AUTHOR]

ABSTRACT The recent global trend is the convergence of information and communications technology (ICT). By applying ICT in various fields such as the humanities, new types of products and services are created, and new values that help people's lives can be created. AI can be selected as a representative technology in such convergence ICT. However, applying AI technology to actual production requires ensuring data security. Federated learning (FL) can achieve secure sharing of data, where all parties participate in model training locally and upload it to the server for aggregation. The data never leaves the parties involved, thus solving the problems of data privacy and data silos. However, FL faces issues such as high communication cost, imbalanced performance distribution among participants, and low privacy protection. To achieve a balance between model accuracy, communication cost, fairness, and privacy, this paper proposes a multi‐objective optimization‐based FL algorithm (M‐FedAvg). The multi‐objective optimization problem of maximising the accuracy of the global model, minimising the communication cost, minimising the variance of the accuracy, and minimising the privacy budget is solved by NSGA‐III. The experimental results show that the algorithm proposed can effectively reduce the communication cost of FL and achieve privacy protection for participants without affecting the accuracy of the global model. [ABSTRACT FROM AUTHOR]

Insulators have an extremely important role in transmission lines, and they are important components for ensuring the safe operation of transmission lines. In order to solve the difficult problem of insulator fault detection under complex background, IG‐YOLOv8 insulator fault detection algorithm is proposed in this paper. First, the Wise‐IoU (WIoU) loss function is introduced to mitigate the adverse impact of low‐quality images by employing a dynamic non‐monotonic focusing mechanism, thereby enhancing the detection performance of the entire model. Second, a novel C2f network is constructed by integrating the receptive field coordination attention (RFCA) convolutional module to address the parameter‐sharing issue associated with large convolutional kernels. Additionally, the data set has been reorganized using k‐fold cross‐validation to ensure that each subset undergoes training and testing, consequently reducing generalization errors. Finally, a deformable attention (DA) mechanism is employed to augment the feature extraction capability pertaining to insulator fault region information. In order to evaluate the detection performance of the improved IG‐YOLOv8 algorithm, this study constructed an insulator target detection data set containing four fault types: Normal, Defect, Dirty, and Aging. The experimental results show that the average accuracy of the improved model is increased from 89.7% to 96.9%, and the Recall value of the Aging type insulator is increased from 71.8% to 89.1%. The occurrence of missed detection is greatly reduced, and the accuracy of detection is improved. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The dynamic structure evolution of heterogeneous catalysts during reaction has gained great attention recently. However, controllably manipulating dynamic process and then feeding back catalyst design to extend the lifetime remains challenging. Herein, we proposed an entropy variation strategy to develop a dynamic CuZn−Co/HEOs catalyst, in which the non‐active Co nano‐islands play a crucial role in controlling thermal effect via timely capturing and utilizing reaction heat generated on the adjacent active CuZn alloys, thus solving the deactivation problem of Cu‐based catalysts. Specifically, heat sensitive Co nano‐islands experienced an entropy increasing process of slowly redispersion during the reaction. Under such heat dissipation effect, the CuZn−Co/HEOs catalyst exhibited 95.7 % ethylene selectivity and amazing long‐term stability (>530 h) in the typical exothermic acetylene hydrogenation. Aiming at cultivating it as a catalyst with promising industrial potential, we proposed a simple regeneration approach via an entropy decreasing process. [ABSTRACT FROM AUTHOR]

To address the issue of poor robustness in the model predictive control of grid‐connected inverters due to disturbances in load model parameters, this article developed an ultra‐local model robust predictive controller based on Linear Matrix Inequality (LMI). First, to avoid dependence on model parameters, an ultra‐local model of the system was constructed. Second, in the process of setting the state variable compensation gain, to simplify the complex computational steps of the traditional Lyapunov algorithm, the task of finding the gain that satisfies the Lyapunov stability condition was ingeniously transformed into an optimization problem of solving constrained LMI. Third, the optimized state variables are utilized to design a new cost function predictive model, thereby enhancing the precision of system control. Finally, the effectiveness of the proposed approach has been validated through simulations and experiments. [ABSTRACT FROM AUTHOR]

Although single‐stage inverters are popular for simpler design they face difficulties in shoot‐through mode operation. Insufficient DC voltage regulation and complicated LC network are principal drawbacks of these topologies. A new split source inverter (SSI) can solve problems with single‐stage inverters. In this paper, SSI replaced the voltage source inverter (VSI) of a shunt active power filter (SAPF) which alleviates power quality (PQ) issues in power system. Furthermore, a VSI‐based SAPF faces challenges to maintain consistent voltage across DC‐link capacitor, exactly compensating current generation, and switching loss reduction in inverter. This study examined efficacy of two inverter‐based SAPFs considering a modified synchronous reference frame approach for generating reference current; fuzzy logic controller for regulating DC‐link voltage; and adaptive fuzzy hysteresis current controller for generating switching pulses. Ideal and non‐ideal sources were considered when running the simulations for various load circumstances. The proposed SSI‐based SAPF with an advanced control approach can eradicate source current harmonics to 0.52% and 0.45% under ideal source conditions, and 0.65% and 0.54% under non‐ideal source conditions for non‐linear loads. Similarly, the ripples in the DC‐link voltage are also reduced to 2–3 V for the ideal case and 4–5 V for non‐ideal case. [ABSTRACT FROM AUTHOR]

Background: Functional Communication Disorders (FCDs) are one specific presentation of Functional Neurological Disorder (FND). FND is characterised by neurological symptoms, such as sensory and motor symptoms, which are not explained by neurological disease. Speech and language therapists (SLTs) have expertise in managing communication disorders, including FCDs, though is not known is what clinicians do in practice to treat and manage FCDs. Aim: To explore the clinical practices of SLTs who regularly manage FCDs in the UK, including the assessment and intervention approaches taken. Methods & Procedures: An online survey was developed using Qualtrics software and piloted before dissemination. Participants were experienced SLTs working in the UK who managed at least three FCD referrals a year. The survey was developed with a mix of qualitative and quantitative questions. The survey was disseminated via social media and professional networks. Outcomes & Results: There were 73 completed responses to the survey. Participants reported working with a range of FCDs clinically, with functional stuttering and articulation disorders seen most frequently. SLTs reported working with a wide range of multidisciplinary professionals when managing patients with FCDs, though lack of access to mental health professionals was raised as an issue. SLTs reported using a combination of formal and informal communication assessments. Interventions varied, with a wide range of psychological approaches informing treatment. Lack of specific training, evidence base and negative attitudes around functional neurological disorder (FND) were raised as ongoing issues. Conclusions & Implications: Therapists encountered a wide range of FCDs as part of their clinical practice, though there was a significant disparity in the service and interventions offered. SLTs feel their input can be effective, but lack the resources, training and evidence‐based interventions to provide adequate care. WHAT THIS PAPER ADDS: What is already known on the subject: FCDs are one manifestation of FND and can present as a wide range of communication disorders. SLTs encounter FCDs as part of clinical practice, but report feeling unsure and underprepared to manage these disorders. Consensus recommendations have provided some guidance on how to manage these disorders, though what was not known was what practising SLTs are doing in practice with FCD patients: what assessment, intervention and management strategies they use, and what they feel are the facilitators and barriers to effective management. What this study adds to the existing knowledge: This is the first UK‐wide survey of FCD SLT clinical practice. The survey found that SLTs are seeing a range of FCDs as part of their clinical practice. SLTs reported that they feel their input is effective, that they had confidence in their ability to provide assessment and intervention, and that SLT for FCDs should be routine. SLTs reported using a wide variety of approaches to assessment and intervention. Barriers to effective management included a lack of resources, training, negative staff attitudes towards FND, and lack of research and evidence‐based interventions. What are the practical and clinical implications of this work?: This survey has found that SLTs working across the UK are providing input for patients with FCDs, but frequently reported feeling isolated and lacking clinical peer support. This shows the potential for networking groups to support SLTs to learn and share resources. There is a training need for SLTs and other healthcare professionals to tackle pervasive negative attitudes towards FND. Common themes in intervention approaches were found, but there was variability in the specific approach taken. This requires further research to guide SLTs on the best evidence‐based practice. [ABSTRACT FROM AUTHOR]

Solving mathematical story problems has proven to be a challenge for primary school students with and without developmental disabilities. The present study replicates a behavior analytic study (Neef et al.) by teaching three autistic Chinese students in inclusive education classes to solve addition/subtraction story problems by acquiring an overt precurrent behavior chain. The intervention was effective for all participants by employing a multiple baseline design across behaviors. Additionally, the study extends Neef et al. by conducting maintenance, generalization, and social validity assessments, and expands the teaching format to distance learning (telehealth). The results and limitations are discussed based on Skinner's conceptualization of problem‐solving and its clinical application in teaching complex mathematical skills to students with developmental disabilities. [ABSTRACT FROM AUTHOR]

If C$C$ is a smooth projective curve over an algebraically closed field F$\mathbb {F}$ and G$G$ is a group of automorphisms of C$C$, the canonical representation ofC$C$ is given by the induced F$\mathbb {F}$‐linear action of G$G$ on the vector space H0C,ΩC$H^0\left(C,\Omega _C\right)$ of holomorphic differentials on C$C$. Computing it is still an open problem in general when the cover C→C/G$C \rightarrow C/G$ is wildly ramified. In this paper, we fix a prime power q$q$, we consider the Drinfeld curve, that is, the curve C$C$ given by the equation XYq−XqY−Zq+1=0${XY^q-X^qY-Z^{q+1}=0}$ over F=Fq¯$\mathbb {F}=\hspace{0.83328pt}\overline{\hspace{-0.83328pt}\mathbb {F}_q\hspace{-0.83328pt}}\hspace{0.83328pt}$ together with its standard action by G=SL2Fq${G=SL_2\left(\mathbb {F}_q\right)}$, and decompose H0C,ΩC$H^0\left(C,\Omega _C\right)$ as a direct sum of indecomposable representations of G$G$, thus solving the aforementioned problem in this case. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is a global health concern with high prevalence and mortality. A marine alkaloid, AP‐427, has been reported to show potential for HCC treatment. However, its use is limited by low solubility and high toxicity. We aimed to investigate the preformulation parameters and develop AP‐427 liposomes to improve its clinical suitability. A stability‐indicating HPLC assay was established, and the physicochemical properties of AP‐427 were analyzed. Afterward, AP‐427 liposomes were prepared and characterized, and their cytotoxicity was evaluated. AP‐427 had a low solubility at physiological pH, a LogD of 2.56 ± 0.03, and a basic pKa of 3.24 ± 0.12. An entrapment efficiency of 52.71 ± 3.2% was achieved after optimization. The resulting AP‐427 liposomes were 147.2 ± 3.4 nm and stable up to three months when stored in a pellet form at 4°C. The crystallization of AP‐427 in liposomes became less ordered, and AP‐427 liposomes exhibited a controlled release fitted in Korsmeyer–Peppas model, indicating the release was driven by diffusion. Furthermore, AP‐427 liposomes showed a 3.6 times reduced cytotoxicity against HepG2 cells compared with free AP‐427, potentially enhancing its antitumor efficacy. In conclusion, the precise preformulation parameters advanced the AP‐427 liposomal formulation development, which showed potential for HCC treatment. Practical Applications: The aaptamine derivative AP‐427 has shown cytotoxic effects against hepatocellular carcinoma. However, the low solubility and high toxicity limit its clinical application. The present study aims to prepare liposomal formulation to solve the current problems. Results obtained from this study shed light on challenges related to drug solubility and have paved the way for the development of an effective AP‐427 liposomal formulation with promising application in hepatocellular carcinoma therapy. [ABSTRACT FROM AUTHOR]

This paper proposes a two‐stage beamforming and combining scheme in frequency division duplex (FDD) massive multiple‐input multiple‐output (MIMO) systems with multi‐antenna users. Specifically, the proposed scheme is a two‐stage scheme, where the pre‐beamforming matrix and pre‐combining matrix are designed using the channel covariance matrix (CCM) in the first stage. The problem of the pre‐beamforming matrix and pre‐combining matrix design are formulated as an 0–1 quadratic integer programming problem. To solve this problem, it is further transformed into an 0–1 mixed linear integer programming problem. In the second stage, the sparse code multiple access and multi‐user precoding and combining are adopted to mitigate the inter‐user interference. Different from the previous transmission scheme using CCM, the proposed scheme consider the multi‐antenna user system, and uses the CCM to design both the pre‐beamforming and pre‐combining matrices to sparsify the effective channel matrix, such that the overhead of pilot and feedback can be reduced. Moreover, the sparse code multiple access can help to better reduce the inter‐user interference. Simulation results validate the good performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper provides an overview of current approaches for solving inverse problems in imaging using variational methods and machine learning. A special focus lies on point estimators and their robustness against adversarial perturbations. In this context results of numerical experiments for a one‐dimensional toy problem are provided, showing the robustness of different approaches and empirically verifying theoretical guarantees. Another focus of this review is the exploration of the subspace of data‐consistent solutions through explicit guidance to satisfy specific semantic or textural properties. [ABSTRACT FROM AUTHOR]

Background: Offspring of parents with affective disorders (OAD) are at risk of developing a wide range of mental disorders. Deficits in the rearing environment and high levels of stress are well‐known risk factors for negative outcomes in OAD. Building on prior research, we aim to examine the longitudinal relationships between family dysfunction, stressful life events, and mental health in OAD and control offspring of parents with no affective disorder. In the present study, we hypothesized that high levels of family dysfunction would be associated with more internalizing and externalizing problems across time in OAD than in controls, and that family dysfunction would mediate the relationship between stressful life events in adolescence and poor mental health in adulthood, particularly in OAD. Methods: As part of the TRacking Adolescents' Lives Survey (TRAILS), 2230 participants (51% female, Mage = 11.1 years, SD = 0.6, at baseline) and their parents completed measures across six time points, spanning 15 years. Mental health, family dysfunction, and stressful life events were assessed with the Youth and Adult Self‐Report, Family Assessment Device, and an in‐house measure, respectively. Results: Multi‐group structured equation modeling revealed that family dysfunction was linked to internalizing and externalizing problems in OAD, but not controls, across time. Risk status did not moderate family dysfunction's mediation of the relationship between stressful life events and negative outcomes in adulthood. Conclusions: OAD show high sensitivity to dysfunction in the rearing environment across childhood and adolescence, which supports the use of family based interventions to prevent the development of mental disorders in high‐risk youth. [ABSTRACT FROM AUTHOR]

It is a central tenet of attachment theory that individual differences in attachment representations organize behavior during social interactions. Secure attachment representations also facilitate behavioral synchrony, a key component of adaptive parent–child interactions. Yet, the dynamic neural processes underlying these interactions and the potential role of attachment representations remain largely unknown. A growing body of research indicates that interpersonal neural synchrony (INS) could be a potential neurobiological correlate of high interaction and relationship quality. In this study, we examined whether interpersonal neural and behavioral synchrony during parent–child interaction is associated with parent and child attachment representations. In total, 140 parents (74 mothers and 66 fathers) and their children (age 5–6 years; 60 girls and 80 boys) engaged in cooperative versus individual problem‐solving. INS in frontal and temporal regions was assessed with functional near‐infrared spectroscopy hyperscanning. Attachment representations were ascertained by means of the Adult Attachment Interview in parents and a story‐completion task in children, alongside video‐coded behavioral synchrony. Findings revealed increased INS during cooperative versus individual problem solving across all dyads (훸2(2) = 9.37, p = 0.009). Remarkably, individual differences in attachment representations were associated with INS but not behavioral synchrony (p > 0.159) during cooperation. More specifically, insecure maternal attachment representations were related to higher mother–child INS in frontal regions (훸2(3) = 9.18, p = 0.027). Conversely, secure daughter attachment representations were related to higher daughter–parent INS within temporal regions (훸2(3) = 12.58, p = 0.006). Our data thus provide further indication for INS as a promising correlate to probe the neurobiological underpinnings of attachment representations in the context of early parent–child interactions. Research Highlights: We assessed attachment representations using narrative measures and interpersonal neural synchrony (INS) during parent‐child problem‐solving.Dyads including mothers with insecure attachment representations showed higher INS in left prefrontal regions.Dyads including daughters with secure attachment representations showed higher INS in right temporo‐parietal regions.INS is a promising correlate to probe the neurobiological underpinnings of attachment representations in the context of parent‐child interactions, especially within the mutual prediction framework. [ABSTRACT FROM AUTHOR]

Reflectivity inversion is a key step in reservoir prediction. Conventional sparse‐spike deconvolution assumes that the reflectivity (reflection coefficient series) is sparse and solves for the reflection coefficients by an L1‐norm inversion process. Spectral inversion is an alternative to sparse‐spike deconvolution, which is based on the odd–even decomposition algorithm and can accurately identify thin layers and reduce the wavelet tuning effect without using constraints from logging data, from horizon interpretations or from an initial model of the reflectivity. In seismic processing, an error exists in wavelet extraction because of complex geological structures, resulting in the low accuracy of deconvolution and inversion. Blind deconvolution is an effective method for solving the problem mentioned above, which comprises seismic wavelet and reflectivity sequence, assuming that the wavelets that affect some subsets of the seismic data are approximately the same. Therefore, we combined blind deconvolution with spectral inversion to propose blind spectral inversion. Given an initial wavelet, we can calculate the reflectivity based on spectral inversion and update the wavelet for the next iteration. During the update processing, we add the smoothness of the wavelet amplitude spectrum as a regularization term, thus reducing the wavelet oscillation in the time domain, increasing the similarity between inverted and initial wavelets, and improving the stability of the solution. The blind spectral inversion method inherits the wavelet robustness of blind deconvolution and high resolution of spectral inversion, which is suitable for reflectivity inversion. Applications to synthetic and field seismic datasets demonstrate that the blind spectral inversion method can accurately calculate the reflectivity even when there is an error in wavelet extraction. [ABSTRACT FROM AUTHOR]

The memory conformity effect occurs when people witness a given incident (e.g. a crime) then talk to each other about it, and the statement of one person affects the memory account of the other person with respect to this incident. The aim of this article is to improve the quality of witness testimony by verifying the effectiveness of three methods that aim to reduce memory conformity effect: (1) an extended warning against misinformation; (2) a method based on information about memory functioning and its fallibility and (3) a method consisting in motivating participants to resist influence and demonstrating their individual vulnerability to it. In the presented experiment, the innovative MORI technique was used to study the memory conformity effect. This technique allows a pair of participants to sit beside each other, look at the same screen and see a different version of the same criminal event. In the next stages, the subjects are asked to answer a series of questions about different details, thereby introducing mutual misinformation; then, the participants perform an individual memory test. In the experimental conditions, this test was preceded by one of the three tested methods in each group, with the aim of determining their effectiveness in reducing memory conformity. It turns out that the implementation of an extended warning against misinformation eliminated the memory conformity effect, while the application of two other methods led to a reduction (but not complete elimination) of the studied phenomenon. [ABSTRACT FROM AUTHOR]

The achievement of quantum computational advantage, also known as quantum supremacy, is a major milestone at which a quantum computer can solve a problem significantly faster than the world's most powerful classical computers. Two tasks, boson sampling and random quantum circuit sampling, have experimentally exhibited quantum advantages on photonic and superconducting platforms respectively. Classical benchmarking is essential, yet challenging, because these tasks are intractable for classical computers. This study reviews models, algorithms and large‐scale simulations of these two sampling tasks. These approaches continue to hold substantial significance for research in both current noisy intermediate‐scale quantum (NISQ) systems and future fault‐tolerant quantum computing. [ABSTRACT FROM AUTHOR]

Wheat has been an important part of the human diet for millennia. The increase in demand for wheat grown organically in the United States and globally reflects the growing interest in organic food and food products. A symposium on organic wheat production was held during the annual meeting of the American Society of Agronomy in Baltimore, MD, during 2021. Presenters discussed the state‐of‐the‐science on organic wheat research. Papers were solicited following the symposium for inclusion in this special section. As a result, five papers are included in this special section: four focus on organic wheat research in North America while one discusses results of a European study. Core Ideas: Demand is increasing for wheat grown organically.A need exists for research to solve problems encountered by organic wheat growers.Results of research discussed in five papers can be used to guide future research on organic wheat production. [ABSTRACT FROM AUTHOR]

In teacher professional development (PD), grouping teachers with varying levels of experience can be a productive and empowering way to stimulate the exchange and co‐generation of content and pedagogical knowledge. However, less experienced teachers can face socio‐emotional risks when engaging in collaborative science content reasoning tasks with more experienced colleagues, and these risks may impact the collaborative experience of both parties and the learning environment in teacher PD. This exploratory case study examines the process of productively navigating socio‐emotional risks and interpersonal tensions encountered by a veteran and pre‐service physics teacher during one episode of discussing physics content. We use a single term, comfort‐building, to encapsulate discursive moves that result in increased feelings of comfort and safety by the participants. Comfort‐building includes moves that serve to mitigate social risk, ease tension, and avoid discomfort, as well as those geared toward finding common ground and co‐navigating challenges. These moves can carve out conversational space for teachers to more confidently face risks associated with being accountable to the physics content knowledge and engage in discipline‐based conversations more deeply. The presented case was followed by video‐stimulated individual interviews to determine how consciously the teachers connected their participation to explicit risk and comfort. This case study highlights an affective dimension for consideration in the continued study and facilitation of science teacher PD, especially programs that bring together teachers with a variety of backgrounds and skill sets. [ABSTRACT FROM AUTHOR]

Financial distress prediction (FDP) has attracted high attention from many financial institutions. Utilizing supervised learning‐based methods in FDP, however, is time consuming and labor intensive. Therefore, in this paper, we exploit active‐pSVM method, which combines potential data distribution information and existing expert experience to solve FDP problem. Moreover, with the increasingly popular textual information, we construct several features on our protocol that are based on the Management Discussion and Analysis (MD&A) text information. Using datasets that are collected in different time windows from the listed Chinese companies, we conducted an extensive experiment and were able to confirm a better efficiency of our active‐pSVM, when compared with some common supervised learning‐based methods. Our study also covers the application of MD&A text information on weakly supervised learning model in FDP. [ABSTRACT FROM AUTHOR]

This paper deals with a class of fractional neutral delay systems involving proportional Caputo derivative. Maintaining the finite‐time stability of fractional‐order systems is a major challenge, as their capacity to mimic complex dynamics draws more attention to them. Therefore, the paper presents a novel finite‐time stability criterion based on the Banach fixed‐point theorem. A decomposition formula for proportional Caputo derivative is provided. This formula allows us to derive a new numerical technique for efficiently solving the proposed problem. Finally, extensive numerical results are performed to illustrate and validate the proposed theoretical results. [ABSTRACT FROM AUTHOR]

ABSTRACT The attack detection and data‐driven resilient control problem for heterogeneous nonlinear nonaffine multi‐agent systems (MASs) in the presence of intermittent false data injection (FDI) attacks is investigated in this article. First, an attack detection and isolation mechanism based on the distributed observer are designed to determine the attack signals and isolate the attacked communication links in time. Then, in order to solve the problem of the unknown system model, the dynamic linearization method is used to convert the nonlinear nonaffine MASs into an equivalent linear data model. Further, based on the linear data model, the data‐driven resilient controller with the attack isolation mechanism is designed to achieve the leader‐following tracking control objective. Finally, the simulation result illustrates the performance of the proposed scheme with comparisons. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument have been widely used by scholars around the world to assess the methodological quality of clinical practice guidelines (CPGs). We sought to identify items or domains that are commonly scored low in the assessment, and to systematically review the issues that emerged when evaluators used the AGREE II tool for guideline quality assessment.A systematic search was conducted to identify articles published in medically relevant databases from 2022 to 2023 regarding the use of the AGREE II tool for the assessment of CPGs. We extracted six quality domains and overall quality assessment data of CPGs included in the literature, and processed the data using descriptive statistical analysis, difference analysis, regression analysis, and correlation analysis. A seven‐point Likert scale was used to assess the reporting quality of the included articles.151 relevant publications were identified, including 2081 guidelines published between 1990 and 2022. The results of the regression analysis showed a statistically significant impact of all domains on overall guideline quality (p < 0.001; R2 = 0.777). Domain 1, 2, 3, 4, and 6 scores differed significantly over time (p < 0.001) and were increasing. The score was good for Domain 4 (median 78.00 [IQR: 62.75–89.00]; mean 74.34 [SD 18.85]) and Domain 1 (median 78.00 [IQR: 61.00–90.00]; mean 73.57 [SD 21.12]). Scores were generic for Domain 6 (median 58.33 [IQR: 25.00–83.33]; mean 53.98 [SD 34.13]), Domain 2 (median 53.00 [IQR: 33.30–72.10]; mean 53.30 [SD 24.52]) and Domain 3 (median 51.00 [IQR: 26.02–73.00]; mean 50.44 [SD 27.19]). The score was poor for Domain 5 (median 36.20 [IQR: 20.20–58.32]; mean 40.21 [SD 24.90]). In addition, the quality evaluation results of the included articles showed that 33.1% were evaluated as low and 11.9% as very low.AGREE II tools have facilitated the development of methodological quality for CPGs. Although the quality of CPGs has improved over time, some general low‐quality problems still exist, and solving these problems will be an effective way for developers to upgrade the quality of guidelines. In addition, addressing critical issues in the evaluation of guidelines to present high‐quality study reports would be another way to guide guideline development. [ABSTRACT FROM AUTHOR]