Bioinspired MXene-Based Soft Actuators Exhibiting Angle-Independent Structural Color

In nature,many living organisms exhibiting unique structural coloration and soft-bodied actuation have inspired scientists to develop advanced structural colored soft actuators toward biomimetic soft robots.However,it is challenging to simultaneously biomimic the angle-independent structural color and shape-morphing capabilities found in the plum-throated cotinga flying bird.Herein,we report biomimetic MXene-based soft actuators with angle-independent structural color that are fabricated through controlled self-assembly of colloidal SiO_(2) nanoparticles onto highly aligned MXene films followed by vacuum-assisted infiltration of polyvinylidene fluoride into the interstices.The resulting soft actuators are found to exhibit brilliant,angle-independent structural color,as well as ultrafast actuation and recovery speeds(a maximum curvature of 0.52 mm−1 can be achieved within 1.16 s,and a recovery time of~0.24 s)in response to acetone vapor.As proof-of-concept illustrations,structural colored soft actuators are applied to demonstrate a blue gripper-like bird’s claw that can capture the target,artificial green tendrils that can twine around tree branches,and an artificial multicolored butterfly that can flutter its wings upon cyclic exposure to acetone vapor.The strategy is expected to offer new insights into the development of biomimetic multifunctional soft actuators for somatosensory soft robotics and next-generation intelligent machines.

Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance

Genomic selection(GS)is a powerful tool for improving genetic gain in maize breeding.However,its routine application in large-scale breeding pipelines is limited by the high cost of genotyping platforms.Although sequencing-based and array-based genotyping platforms have been used for GS,few studies have compared prediction performance among platforms.In this study,we evaluated the predictabilities of four agronomic traits in 305 maize hybrids derived from 149 parental lines subjected to genotyping by sequencing(GBS),a 40K SNP array,and target sequence capture(TSC)using eight GS models.The GBS marker dataset yielded the highest predictabilities for all traits,followed by TSC and SNP array datasets.We investigated the effect of marker density and statistical models on predictability among genotyping platforms and found that 1K SNPs were sufficient to achieve comparable predictabilities to 10K and all SNPs,and BayesB,GBLUP,and RKHS performed well,while XGBoost performed poorly in most cases.We also selected significant SNP subsets using genome-wide association study(GWAS)analyses in three panels to predict hybrid performance.GWAS facilitated selecting effective SNP subsets for GS and thus reduced genotyping cost,but depended heavily on the GWAS panel.We conclude that there is still room for optimization of the existing SNP array,and using genotyping by target sequencing(GBTS)techniques to integrate a few functional markers identified by GWAS into the 1K SNP array holds great promise of being an effective strategy for developing desirable GS breeding arrays.

A New Partial Task Offloading Method in a Cooperation Mode under Multi-Constraints for Multi-UE

In Multi-access Edge Computing(MEC),to deal with multiple user equipment(UE)’s task offloading problem of parallel relationships under the multi-constraints,this paper proposes a cooperation partial task offloading method(named CPMM),aiming to reduce UE’s energy and computation consumption,while meeting the task completion delay as much as possible.CPMM first studies the task offloading of single-UE and then considers the task offloading ofmulti-UE based on single-UE task offloading.CPMMuses the critical path algorithmto divide the modules into key and non-key modules.According to some constraints of UE-self when offloading tasks,it gives priority to non-key modules for offloading and uses the evaluation decision method to select some appropriate key modules for offloading.Based on fully considering the competition between multiple UEs for communication resources and MEC service resources,CPMM uses the weighted queuing method to alleviate the competition for communication resources and uses the branch decision algorithm to determine the location of module offloading by BS according to the MEC servers’resources.It achieves its goal by selecting reasonable modules to offload and using the cooperation ofUE,MEC,andCloudCenter to determine the execution location of themodules.Extensive experiments demonstrate that CPMM obtains superior performances in task computation consumption reducing around 6%on average,task completion delay reducing around 5%on average,and better task execution success rate than other similar methods.

The Study of Human Resource Development for Chinese Old Generation In the Context of the Aging Population

With the rapid development of the era, the population aging speed is speeding up constantly. Aging population problem has become a common issue in the world. China has been profoundly influenced by the severe aging phenomenon in politics, economy, culture and society. Therefore, how to better promote the development of elderly human resources, promote the development of the senior citizens＇ re-employment, to cope with the challenge of aging turns out to be a pressing issue.

Liquid crystal-templated chiral nanomaterials: from chiral plasmonics to circularly polarized luminescence

Chiral nanomaterials with intrinsic chirality or spatial asymmetry at the nanoscale are currently in the limelight of both fundamental research and diverse important technological applications due to their unprecedented physicochemical characteristics such as intense light-matter interactions, enhanced circular dichroism, and strong circularly polarized luminescence. Herein, we provide a comprehensive overview of the state-of-the-art advances in liquid crystal-templated chiral nanomaterials. The chiroptical properties of chiral nanomaterials are touched, and their fundamental design principles and bottom-up synthesis strategies are discussed. Different chiral functional nanomaterials based on liquid-crystalline soft templates, including chiral plasmonic nanomaterials and chiral luminescent nanomaterials, are systematically introduced, and their underlying mechanisms, properties, and potential applications are emphasized. This review concludes with a perspective on the emerging applications, challenges, and future opportunities of such fascinating chiral nanomaterials. This review can not only deepen our understanding of the fundamentals of soft-matter chirality, but also shine light on the development of advanced chiral functional nanomaterials toward their versatile applications in optics, biology, catalysis, electronics, and beyond.