Programmable gear-based mechanical metamaterials

Elastic properties of classical bulk materials can hardly be changed or adjusted in operando, while such tunable elasticity is highly desired for robots and smart machinery. Although possible in reconfigurable metamaterials, continuous tunability in existing designs is plagued by issues such as structural instability, weak robustness, plastic failure and slow response. Here we report a metamaterial design paradigm using gears with encoded stiffness gradients as the constituent elements and organizing gear clusters for versatile functionalities. The design enables continuously tunable elastic properties while preserving stability and robust manoeuvrability, even under a heavy load. Such gear-based metamaterials enable excellent properties such as continuous modulation of Young’s modulus by two orders of magnitude, shape morphing between ultrasoft and solid states, and fast response. This allows for metamaterial customization and brings fully programmable materials and adaptive robots within reach

A semiparametric spatial dynamic model

Stimulated by the Boston house price data, in this paper, we propose a semiparametric spatial dynamic model, which extends the ordinary spatial autoregressive models to accommodate the effects of some covariates associated with the house price. A profile likelihood based estimation procedure is proposed. The asymptotic normality of the proposed estimators are derived. We also investigate how to identify the parametric/nonparametric components in the proposed semiparametric model. We show how many unknown parameters an unknown bivariate function amounts to, and propose an AIC/BIC of nonparametric version for model selection. Simulation studies are conducted to examine the performance of the proposed methods. The simulation results show our methods work very well. We finally apply the proposed methods to analyze the Boston house price data, which leads to some interesting finding

Effects of habitat differences on the scatter-hoarding behaviour of rodents (Mammalia, Rodentia) in temperate forests

To discover the differences in hoarding strategies of rodents for different seeds in different habitats, we labelled and released three different types of seeds, including Pinus koraiensis, Corylus mandshurica, and Quercus mongolica, in temperate forests of northeastern China and investigated the fate of seeds in four different habitats that included a broad-leaved forest, mixed-forest edge, mixed forest, and artificial larch forest. Our research showed that the hoarding strategy of rodents was found to vary substantially in different habitats. The survival curves of seeds from different habitats showed the same trend, but the rates of consumption in different habitats varied. More than 50% of the seeds in the four habitats were consumed by the tenth day. It took 20 days to consume more than 70% of the seeds. The rate of consumption of P. koraiensis seeds reached 96.70%; 99.09% of the C. mandshurica seeds were consumed, and 93.07% of the Q. mongolica seeds were consumed. The seeds were consumed most quickly in the artificial larch forest. In general, most of the early seeds were quickly devoured. After day 20, the consumption gradually decreased. Rodents found the seeds in the artificial larch forest in a shorter average time than those in the other types of forests. The average earliest discovery time was 1.4 ± 0.9 d (1–3 d). The average earliest discovery time in all the other three habitats exceeded 7 d. The median removal times (MRT) was distributed around the seeds at 14.24 ± 10.53 d (1–60 d). There were significant differences in the MRT among different habitats. It was shortest in the artificial larch forest at 7.67 ± 6.80 d (1–28 d). In contrast, the MRT in the broad-leaved forest was the longest at 17.52 ± 12.91 d (4–60 d). There were significant differences in the MRT between the artificial larch forest and the other habitats. There was less predation of the three types of seeds at the mixed-forest edge, and the most seeds were dispersed. The rates of predation of the P. koraiensis, C. mandshurica, and Q. mongolica seeds were 28.33%, 15.83%, and 44.0%, and 59.17%, 84.17%, and 48.0% of the seeds were dispersed, respectively. The average dispersal distances of all the seeds were less than 6 m, and the longest distance recorded was 18.66 m. The dispersal distances and burial depths differed significantly among the four types of habitats. The distance of seed dispersal was primarily distributed in 1–6 m

A Novel Dnmt3a1 Transcript Inhibits Adipogenesis

DNA (cytosine-5)-methyltransferase 3a (Dnmt3a) is an enzyme that catalyzes the transfer of methyl groups to specific CpG forms in DNA. In mammals, two variant transcripts of Dnmt3a have been successfully identified. To the best of our knowledge, no Dnmt3a transcripts in an avian have been successfully identified. This study was performed to detect different transcripts of Dnmt3a in chickens and to examine whether a novel Dnmt3a transcript named Dnmt3a1 may regulate adipogenesis. In addition to cloning, sequencing, transcript detection, and expression studies, a novel Dnmt3a1 transcript overexpression and knockdown were conducted to explore the potential role of Dnmt3a1 in preadipocyte proliferation and the early stage of adipocyte differentiation. In chicken abdominal fat tissue, we detected a novel Dnmt3a1 transcript that differs from Dnmt3a by lacking 23 amino acids at the exon-1/exon-2 border. Dnmt3a1 mRNA was ubiquitously expressed in a variety of tissues or cells and highly expressed in chicken adipose tissue/cells. The expression of Dnmt3a1 was regulated under different physiological conditions including aging, fasting, and high-fat diet. In addition, overexpression of Dnmt3a1 significantly decreased preadipocyte proliferation and induced cell-cycle arrest while its inhibition increased cell proliferation and S-phase cells. Furthermore, the overexpression of Dnmt3a1 significantly upregulated the mRNA level of cell-cycle-related genes, such as CDKN1A, CDKN1B, CCNB3, CCND2, CCNG2, CDKN2B, and CDK9, or the protein level of CDKN1A, CDKN1B, and CCNG2. Conversely, the knockdown of Dnmt3a1 by siRNA had the opposite effects. Moreover, during early adipocyte differentiation, the overexpression of Dnmt3a1 significantly decreased the mRNA and the protein levels of PPAR-γ, C/EBP-α, ADIPOR1, and STAT3, and the mRNA levels of FAS, LEPR, LPL, PRKAB2, and ATGL. In contrast, their expression was significantly increased after the knockdown of Dnmt3a1. Taken together, we identified a novel transcript of Dnmt3a, and it played a potential role in adipogenesis

On the upper and lower bounds of correlation window size in digital image correlation analysis

Digital Image Correlation (DIC), as a technique based on image processing, has been intensively used for displacement measurement. The setup of DIC analysis starting condition is crucial to the validity of the results. In this paper, the influence of correlation window size (corrsize), one of the parameters that need to be chosen by users for setup, is studied. The results show that DIC is reliable as long as the corrsize is between a lower bound (corssizemin) and an upper bound (corssizemax). The reason why DIC returns high error factor when beyond corssizemax is related to image boundary effect, which is demonstrated by an equation serving as a criterion for corrsize choice. The study in this paper is particularly vital in cases where the Region of Interest (ROI) is close to the image and the real displacement is large

A state-of-the-art review of micron-scale spatially resolved residual stress analysis by FIB-DIC ring-core milling and other techniques

Quantification of residual stress gradients can provide great improvements in understanding the complex interactions between microstructure, mechanical state, mode(s) of failure and structural integrity. Highly focused local probe non-destructive techniques such as X-ray diffraction, electron diffraction or Raman spectroscopy have an established track record in determining spatial variations in the relative changes in residual stress with respect to a reference state for many structural materials. However, the interpretation of these measurements in terms of absolute stress values requires a strain-free sample often difficult to obtain due to the influence of chemistry, microstructure or processing route. With the increasing availability of focused ion beam instruments, a new approach has been developed which is known as the micro-scale ring-core focused ion beam-digital image correlation technique. This technique is becoming the principal tool for quantifying absolute in-plane residual stresses. It can be applied to a broad range of materials: crystalline and amorphous metallic alloys and ceramics, polymers, composites and biomaterials. The precise nano-scale positioning and well-defined gauge volume of this experimental technique make it eminently suitable for spatially resolved analysis, that is, residual stress profiling and mapping. Following a summary of micro-stress evaluation approaches, we focus our attention on focused ion beam-digital image correlation methods and assess the application of micro-scale ring-core methods for spatially resolved residual stress profiling. The sequential ring-core milling focused ion beam-digital image correlation method allows micro- to macro-scale mapping at the step of 10–1000 μm, while the parallel focused ion beam-digital image correlation approach exploits simultaneous milling operation to quantify stress profiles at the micron scale (1–10 μm). Cross-validation against X-ray diffraction results confirms that these approaches represent accurate, reliable and effective residual stress mapping methods. </jats:p