Study on Negative Poisson Ratio and Energy Absorption Characteristics of Embedded Arrow Honeycomb Structure

 Impact collision exists widely in people's daily life and threatens people's life safety. Negative Poisson's ratio structure has good mechanical properties. Therefore, it is of great significance to design and study the energy absorption structure with negative Poisson's ratio effect. Based on the traditional symmetrical concave honeycomb structure (SCHS) with negative Poisson's ratio, two modified negative Poisson's ratio honeycomb structures are proposed by adding embedded straight rib arrow structure and embedded curved rib arrow structure, which are respectively called embedded straight rib arrow honeycomb structure (SRAH) and embedded curved rib arrow honeycomb structure (CRAH). Through finite element simulation experiment, the negative Poisson's ratio characteristics of two cellular cells were studied and the influence of structural parameters of the cells on the Poisson's ratio was discussed. ANSYS/LS-DYNA was used to analyze the energy absorption of the proposed three cellular structures at different impact velocities. Numerical simulation results show that the SRHS and CRAH have greater stress platform value, specific energy absorption and impact force efficiency than SCHS, indicating that the SRAH and CRAH exhibited better energy absorption efficiency and impact resistance performance

9-Isopropenyl-4-methyl-2H-thieno[2,3-h]chromen-2-one

The title compound, C15H12O2S, features three fused rings with a dihedral angle of 79.6 (2)° between the isopropenyl group and the thio­phene ring. In the crystal, mol­ecules are connected into a supra­molecular helical chain via C—H⋯O contacts

Properties of inelastic yielding zones generated by in-plane dynamic ruptures—I. Model description and basic results

We discuss results associated with 2-D numerical simulations of in-plane dynamic ruptures on a fault governed by slip-weakening and rate-and-state friction laws with off-fault yielding. The onset of yielding is determined by a Mohr–Coulomb-type criterion whereas the subsequent inelastic response is described by a Duvaut-Lions-type viscoplastic rheology. The study attempts to identify key parameters and conditions that control the spatial distribution and the intensity variation of off-fault yielding zones, the local orientation of the expected microfractures, and scaling relations or correlations among different quantities that can be used to characterize the yielding zones. In this paper, we present example results for crack and pulse ruptures, along with calculations of energy partition and characteristics of the simulated off-fault yielding zones. A companion follow-up paper provides a comprehensive parameter-space study of various examined features. In agreement with previous studies, the location and shape of the off-fault yielding zones depend strongly on the angle ψ of the background maximum compressive stress relative to the fault and the crack versus pulse mode of rupture. Following initial transients associated with nucleation of ruptures, the rate of various energy components (including off-fault dissipation) linearly increases with time for cracks, while approaching a constant level for pulse-like ruptures. The local angle to the fault of the expected microfractures is generally shallower and steeper than ψ in the compressional and extensional quadrants, respectively. The scalar seismic potency density decays logarithmically with increasing fault normal distance, with decay slope and maximum value that are influenced by the operating stress field

Properties of inelastic yielding zones generated by in-plane dynamic ruptures—II. Detailed parameter-space study

We perform a detailed parameter-space study on properties of yielding zones generated by 2-D in-plane dynamic ruptures on a planar fault with different friction laws and parameters, different initial stress conditions, different rock cohesion values, and different contrasts of elasticity and mass density across the fault. The focus is on cases corresponding to large strike-slip faults having high angle (ψ = 45◦) to the maximum compressive background stress. The simulations and analytical scaling results show that for crack-like ruptures (1) the maximum yielding zone thickness T_(max) linearly increases with rupture distance L and the ratio Tmax/L is inversely proportional to (1 + S)^2 with S being the relative strength parameter; (2) the potency density ε^p_0 decays logarithmically with fault normal distance at a rate depending on the stress state and S; (3) increasing rock cohesion reduces T_(max)/L, resulting in faster rupture speed and higher inclination angle Ф of expected microfractures on the extensional side of the fault. For slip pulses in quasi-steady state, T is approximately constant along strike with local values correlating with the maximum slip velocity (or final slip) at a location. For a bimaterial interface with ψ = 45◦, the energy dissipation to yielding contributes to developing macroscopically asymmetric rupture (at the scale of rupture length) with the same preferred propagation direction predicted for purely elastic cases with Coulomb friction. When ψ = 10◦, representative for thrust faulting, the energy dissipation to yielding leads to opposite preferred rupture propagation. In all cases, Ф is higher on average on the compliant side. For both crack and pulse ruptures with ψ = 45◦, T decreases and ε^p_0 increases for conditions representing greater depth. Significant damage asymmetry of the type observed across several large strike-slip faults likely implies persistent macroscopic rupture asymmetry (unilateral cracks, unilateral pulses or asymmetric bilateral pulses). The results on various features of yielding zones expected from this and other studies are summarized in a table along with observations from the field and laboratory experiments

Long SAGE analysis of genes differentially expressed in the midgut and silk gland between the sexes of the silkwormBombyx mori

There are great differences in silk production efficiency and quality between the male and female domestic silkworm (Bombyx mori). Many genes act together but are differentially expressed between the sexes during silk biosynthesis. Two long serial analyses of gene expression (SAGE) libraries were constructed from the midguts and silk glands of both males and females of a sex-limited strain using 5th instar larvae, yielding in total 96,713 and 98,126 SAGE tags, respectively. Among these tags, 202 were analyzed (p < 0.05 and at least a 2.0-fold change between sexes). Overall, 69 genes were then annotated in detail and 15 tags were annotated with expressed sequence tags (ESTs) based only on the NCBI, SilkDB and long-SAGE libraries. Of these genes, only three could be ascribed to sexual disparity as described by microarray-based expression resources of day three of 5th instar in Dazao B. mori microarray database (BmMDB). The other 66 genes were considered the SAGE-extracted genes that are differentially expressed between the sexes of the whole 5th instar larvae. Among the 66 genes and 15 tags, genes (and gene families) sex-specific storage-protein 1 gene (Sp1), low molecular mass 30 kDa lipoprotein 19G1 gene (Lp-c19), serine proteinase family [serine protease precursor gene (Spp) and chymotrypsin-like serine protease gene (Ctlp)], Serpins (Spi1 and Spi2) and Ser1, and the tag 1161 (annotated EST No. BY926524), which are involved in protein digestion in the midgut, synthesis of silk and inhibition of protein disintegration in silk gland, were verified by the remarkable disparities in gene expression between the sexes. The established SAGE library would contribute to the further identification of genes related to sexual disparity in silk protein production efficiency.Key words: Bombyx mori, sexes, silk protein production efficiency, long-SAGE, differentially expressed genes

AFTR: A Robustness Multi-Sensor Fusion Model for 3D Object Detection Based on Adaptive Fusion Transformer.

Multi-modal sensors are the key to ensuring the robust and accurate operation of autonomous driving systems, where LiDAR and cameras are important on-board sensors. However, current fusion methods face challenges due to inconsistent multi-sensor data representations and the misalignment of dynamic scenes. Specifically, current fusion methods either explicitly correlate multi-sensor data features by calibrating parameters, ignoring the feature blurring problems caused by misalignment, or find correlated features between multi-sensor data through global attention, causing rapidly escalating computational costs. On this basis, we propose a transformer-based end-to-end multi-sensor fusion framework named the adaptive fusion transformer (AFTR). The proposed AFTR consists of the adaptive spatial cross-attention (ASCA) mechanism and the spatial temporal self-attention (STSA) mechanism. Specifically, ASCA adaptively associates and interacts with multi-sensor data features in 3D space through learnable local attention, alleviating the problem of the misalignment of geometric information and reducing computational costs, and STSA interacts with cross-temporal information using learnable offsets in deformable attention, mitigating displacements due to dynamic scenes. We show through numerous experiments that the AFTR obtains SOTA performance in the nuScenes 3D object detection task (74.9% NDS and 73.2% mAP) and demonstrates strong robustness to misalignment (only a 0.2% NDS drop with slight noise). At the same time, we demonstrate the effectiveness of the AFTR components through ablation studies. In summary, the proposed AFTR is an accurate, efficient, and robust multi-sensor data fusion framework

Mesh-MLP: An all-MLP Architecture for Mesh Classification and Semantic Segmentation

With the rapid development of geometric deep learning techniques, many mesh-based convolutional operators have been proposed to bridge irregular mesh structures and popular backbone networks. In this paper, we show that while convolutions are helpful, a simple architecture based exclusively on multi-layer perceptrons (MLPs) is competent enough to deal with mesh classification and semantic segmentation. Our new network architecture, named Mesh-MLP, takes mesh vertices equipped with the heat kernel signature (HKS) and dihedral angles as the input, replaces the convolution module of a ResNet with Multi-layer Perceptron (MLP), and utilizes layer normalization (LN) to perform the normalization of the layers. The all-MLP architecture operates in an end-to-end fashion and does not include a pooling module. Extensive experimental results on the mesh classification/segmentation tasks validate the effectiveness of the all-MLP architecture.Comment: 8 pages, 6 figure