Hydrogels present attractive opportunities as flexible sensors due to their soft nature and tunable physicochemical properties. Despite significant advances, practical application of hydrogel-based sensor is limited by the lack general routes fabricate materials with combination mechanical, conductive, biological Here, a multi-functional hydrogel reported in situ polymerizing acrylamide (AM) N,N'-bis(acryloyl)cystamine (BA) dynamic crosslinked silver-modified polydopamine (PDA)...

Hydrogels have emerged as promising candidates for flexible sensors due to their softness, biocompatibility, and tunable physicochemical properties. However, achieving synchronous satisfaction of conformality, conductivity, diverse biological functions in hydrogel remains a challenge. Here, we proposed multifunctional sensor by incorporating silver-loaded polydopamine nanoparticles (Ag@PDA) into thermally cross-linked methacrylamide chitosan (CSMA) acrylamide network, namely,...

Topological entities based on bulk-boundary correspondence are ubiquitous, from conventional to higher-order topological insulators, where the protected states typically localized at outer boundaries (edges or corners). A less explored scenario involves that inner boundaries, sharing same energy as bulk states. Here, we propose and demonstrate what refer "bulk-hole correspondence''-a relation between robust boundary modes (RBMs) existence of multiple "holes" in singular flatband lattices,...

As a typical model-based evolutionary algorithm, estimation of distribution algorithm (EDA) possesses unique characteristics and has been widely applied in global optimization. However, the commonly used Gaussian EDA (GEDA) usually suffers from premature convergence, which severely limits its search efficiency. This paper first systematically analyzes reasons for deficiency traditional GEDA, then tries to enhance performance by exploiting evolution direction, finally develops new GEDA...

Cooperative coevolution (CC) has shown great potential for solving large-scale optimization problems (LSOPs). However, traditional CC algorithms often waste part of the computation resource (CR) as they equally allocate CR among all subproblems. The recently developed contribution-based improve ones to a certain extent by adaptively allocating according some heuristic rules. Different from existing works, this paper explicitly constructs mathematical model allocation (CRA) problem in and...

5). The majority of studies have been carried out with scaled models dragon fly forewings from the Aeshna Cyanea in either wind tunnels or water channels. In this paper, we study aerodynamics a corrugated airfoil using computational fluid dynamics at low Reynolds number 1000. Structural analysis is also performed commercial software SolidWorks 2009. flow field described by solving incompressible Navier-Stokes equations on an overlapping grid pressure-Poisson method. are discretized space...

Recently, Learning-based image compression has reached comparable performance with traditional codecs(such as JPEG, BPG, WebP). However, computational complexity and rate flexibility are still two major challenges for its practical deployment. To tackle these problems, this paper proposes universal modules named Energy-based Channel Gating(ECG) Bit-rate Modulator(BM), which can be directly embedded into existing end-to-end models. ECG uses dynamic pruning to reduce FLOPs more than 50% in...

Decomposition plays a significant role in cooperative coevolution (CC), which shows great potential large-scale black-box optimization (LSBO). However, current learning-based decomposition algorithms require many fitness evaluations (FEs) to detect variable interdependencies and encounter the difficulty of threshold setting. To address these issues, this study proposes an efficient adaptive differential grouping (EADG) algorithm. Instead homogeneously tackling different types LSBO instances,...

Flexible temperature sensors have been widely used in electronic skins and health monitoring. Body as one of the key physiological signals is crucial for detecting human body's abnormalities, which necessitates high sensitivity, quick responsiveness, stable In this paper, we reported a resistive sensor designed an ultrathin laminated structure with serpentine pattern bioinspired adhesive layer, was fabricated composite poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate)/single-wall...

Abstract By remarkably reducing real fitness evaluations, surrogate-assisted evolutionary algorithms (SAEAs), especially hierarchical SAEAs, have been shown to be effective in solving computationally expensive optimization problems. The success of SAEAs mainly profits from the potential benefit their global surrogate models known as “blessing uncertainty” and high accuracy local models. However, performance leaves room for improvement on high-dimensional problems since now it is still...

Taking "divide-and-conquer" as a basic idea, cooperative coevolution (CC) has shown promising prospect in large scale global optimization. However, its high requirement on the decomposition accuracy can hardly be satisfied practice. Directing against this issue, study proposes bi-hierarchical (BHCC), which tolerate certain degree of error. Besides cooperation among sub-problems conventional CC, BHCC introduces kind between and overall problem. By systematically exploiting excellent...

Higher-order topological semimetals (HOTSMs) represent a novel type of gapless phase, hosting boundary states with dimensions at least two lower than those their bulk geometry. Such nontrivial have been predicted and observed in three-dimensional (3D) systems, representing features the HOTSMs. However, two-dimensional (2D) analogs, represented especially by corner monolayer graphene-like structures, thus far remained only theoretical exploration. Here, we experimentally demonstrate specially...

Weather prediction is of great significance for human daily production activities, global extreme climate prediction, and environmental protection the Earth. However, existing data-based weather methods cannot adequately capture spatial temporal evolution characteristics target region, which makes it difficult to meet practical application requirements in terms efficiency accuracy. Changes involve both strongly correlated continuation relationships, at same time, variables interact with each...

Estimation of distribution algorithm (EDA) is a kind typical model-based evolutionary (EA). Although possessing competitive advantages in theoretical analysis, current EDAs may encounter premature convergence due to the rapid shrinkage search range and relatively low sampling efficiency. Focusing on continuous with Gaussian models, this paper proposes novel probability density estimator which can adaptively enlarge variances thus endow EDA flexible behavior. For estimated density, reflecting...

By taking the idea of divide-and-conquer, cooperative coevolution provides a powerful architecture for large scale optimization problems, but its efficiency depends heavily on decomposition strategy. Existing algorithms either cannot obtain correct results or require number Fitness Evaluations (FEs). To alleviate these limitations, this paper proposes novel algorithm by exploring interdependency from view vectors. It is good at discovering both direct and indirect can significantly reduce...

Estimation of distribution algorithms (EDAs) are a special class model-based evolutionary (EAs). To improve the performance traditional EDAs, many remedies were suggested, which mainly focused on estimating suitable probability model with superior solutions. Different from existing research ideas, this paper tries to enhance EDA by exploiting potential value inferior solutions, where Gaussian is taken as an example. It will be shown that, after simple repair operation, solutions could...

It has been shown that cooperative coevolution (CC) can effectively deal with large scale optimization problems (LSOPs) through a divide-and-conquer strategy. However, its performance is severely restricted by the current context-vector-based sub-solution evaluation method because this requires too many computation resources. To alleviate issue, study proposes an adaptive surrogate model assisted CC framework which adaptively constructs models for different sub-problems fully considering...

Visual object tracking acts as a pivotal component in various emerging video applications. Despite the numerous developments visual tracking, existing deep trackers are still likely to fail when against objects with dramatic variation. These usually do not perform online update or single sub-branch of model, for which they cannot adapt appearance variation objects. Efficient updating methods therefore crucial while previous meta-updater optimizes directly over parameter space, is prone...