Theoretical Study on Generalized Elastic Laws of Elastic Theory with Different Modulus

In classical elasticity theory with different modulus, the constitutive equations based on the direction of principal stress can only represent the relationship between the principal stress and principal strain in the main stress direction and cannot reflect the stress-strain behavior in other directions, and the mechanical essence of the problem on different modulus in tension and compression cannot be characterized effectively. Therefore, according to the constitutive equations based on the direction of principal stress, the generalized elastic laws were deduced by the rotation formulas of stress and strain under different Cartesian coordinate system, which are constitutive equations with different modulus in tension and compression. With theoretical verification, both the nonlinearity and anisotropy property of bi-modulus materials were revealed by the generalized elastic laws. Furthermore, it can also degenerate to the classical bi-modulus elasticity law, which implies that the constitutive law for material with different modulus in tension and compression is special cases of the obtained results. With respect to the indistinct issues about the shear modulus and the assumption of the ratios between Poisson's ratio and Young's modulus, bimodulus material point under pure shear state was investigated. It is shown that, in the rectangular coordinate system based on the maximum or minimum shear stress direction, the relation between shear stress and shear strain is linear. In other words, the shear modulus keeps invariant;besides, the hypothesis is proved that the ratio of tensile Poisson's ratio to tensile modulus is equal to the ratio of compressive Poisson's ratio to compressive modulus under pure shear state, combining with the geometric relationship of pure shear deformation in differential element

Inferring object properties from human interaction and transferring them to new motions

Humans regularly interact with their surrounding objects. Such interactions often result in strongly correlated motions between humans and the interacting objects. We thus ask: “Is it possible to infer object properties from skeletal motion alone, even without seeing the interacting object itself?” In this paper, we present a fine-grained action recognition method that learns to infer such latent object properties from human interaction motion alone. This inference allows us to disentangle the motion from the object property and transfer object properties to a given motion. We collected a large number of videos and 3D skeletal motions of performing actors using an inertial motion capture device. We analyzed similar actions and learned subtle differences between them to reveal latent properties of the interacting objects. In particular, we learned to identify the interacting object, by estimating its weight, or its spillability. Our results clearly demonstrate that motions and interacting objects are highly correlated and that related object latent properties can be inferred from 3D skeleton sequences alone, leading to new synthesis possibilities for motions involving human interaction

Fatty acid profile, oxidative stability and toxicological safety of bayberry kernel oil

The fatty acid profile, oxidative stability and toxicological safety of bayberry (Myrica rubra Sieb. et Zucc.) kernel oil (BKO) extracted by supercritical carbon dioxide (SC-CO2) and solvent of diethyl ether were assessed. Fatty acid profile was determined by gas chromatography, oxidative stability by placing the sample of 25 g in a blast oven at 50 ± 1 °C to accelerate oxidation and toxicological safety by bacterial reverse mutation (Ames test) and acute oral toxicity in mice. The results demonstrated that in comparison to lard and rapeseed oil, the peroxide values of BKO were higher but the acid values were similar during the incubation test. The Ames test demonstrated no mutagenicity and no obvious acute toxicity were observed, suggesting that the BKO has potential as a novel edible oil

Size and shape evolution of embedded single-crystal αα-Fe nanowires

The size and shape evolution of embedded ferromagnetic αα-Fe nanowires is discussed. The αα-Fe nanowires are formed by pulsed-laser deposition of La0.5Sr0.5FeO3−xLa0.5Sr0.5FeO3−x on single-crystal SrTiO3SrTiO3 (001) substrate in reducing atmosphere. The average diameter of the nanowires increases from d ≈ 4d≈4 to 50 nm as the growth temperature increases from T = 560T=560 to 840 °C. Their in-plane shape evolves from circular to octahedral and square shape with [110] facets dominating as the growth temperature increases. A fitting to a theoretical calculation shows that the circular shape is stable when the diameter of the nanowires is smaller than 8 nm.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87835/2/203110_1.pd

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hot spot regions i n the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re - densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms

A multi-regional, hierarchical-tier mathematical model of the spread and control of COVID-19 epidemics from epicentre to adjacent regions

Epicentres are the focus of COVID-19 research, whereas emerging regions with mainly imported cases due to population movement are often neglected. Classical compartmental models are useful, however, likely oversimplify the complexity when studying epidemics. This study aimed to develop a multi-regional, hierarchical-tier mathematical model for better understanding the complexity and heterogeneity of COVID-19 spread and control. By incorporating the epidemiological and population flow data, we have successfully constructed a multi-regional, hierarchical-tier SLIHR model. With this model, we revealed insight into how COVID-19 was spread from the epicentre Wuhan to other regions in Mainland China based on the large population flow network data. By comprehensive analysis of the effects of different control measures, we identified that Level 1 emergency response, community prevention and application of big data tools significantly correlate with the effectiveness of local epidemic containment across different provinces of China outside the epicentre. In conclusion, our multi-regional, hierarchical-tier SLIHR model revealed insight into how COVID-19 spread from the epicentre Wuhan to other regions of China, and the subsequent control of local epidemics. These findings bear important implications for many other countries and regions to better understand and respond to their local epidemics associated with the ongoing COVID-19 pandemic