Neural Machine Translation with Dynamic Graph Convolutional Decoder

Existing wisdom demonstrates the significance of syntactic knowledge for the improvement of neural machine translation models. However, most previous works merely focus on leveraging the source syntax in the well-known encoder-decoder framework. In sharp contrast, this paper proposes an end-to-end translation architecture from the (graph \& sequence) structural inputs to the (graph \& sequence) outputs, where the target translation and its corresponding syntactic graph are jointly modeled and generated. We propose a customized Dynamic Spatial-Temporal Graph Convolutional Decoder (Dyn-STGCD), which is designed for consuming source feature representations and their syntactic graph, and auto-regressively generating the target syntactic graph and tokens simultaneously. We conduct extensive experiments on five widely acknowledged translation benchmarks, verifying that our proposal achieves consistent improvements over baselines and other syntax-aware variants

The Activation of Macrophage and Upregulation of CD40 Costimulatory Molecule in Lipopolysaccharide-Induced Acute Lung Injury

To study the activation of macrophage and upregulation of costimulatory molecule of CD40 in lipopolysaccharide- (LPS-) induced acute lung injury (ALI) model, and to investigate the pathogenecy of ALI, mice were randomly divided into two groups. ALI model was created by injecting 0.2 mg/kg LPS in phosphate saline (PBS) in trachea. The pathologic changes of mice lungs were observed by HE staining at 24 and 48 hours after LPS treatment, then the alveolar septum damage, abnormal contraction, alveolar space hyperemia, and neutrophils or other inflammatory cells infiltration in the LPS group, but not in the control group, were observed. The expression of CD40 mRNA and CD40 protein molecules were higher in LPS group as compared to the control group by Northern blot and flow cytometry, respectively. Expression of Toll-like receptor-4 (TLR4) in activated macrophage (AMΦ) was higher in LPS group as compared to the control group by RT-PCR. The activation of NF-κB binding to NF-κB consensus oligos increased in LPS group by EMSA in macrophage. The concentrations of TNF-α, MIP-2, and IL-1β cytokines from bronchoalveolar lavage fluid (BALF) were increased significantly in LPS group as compared to the control group by ELISA. The activation of AM and upregulation of costimulatory molecule CD40 induced all kinds of inflammatory cytokines releasing, then led to ALI. Therefore, both of them played vital role in the process of development of ALI

Elastic-viscoplastic self-consistent modeling for finite deformation of polycrystalline materials

Anisotropic 1-site and 2-site self-consistent models are developed to describe the elastic-viscoplastic behavior of polycrystalline materials deformed to finite strains on the basis of rate-dependent crystallographic slip and a generalized Hill-Hutchinson self-consistent approach. The choice of rate-dependent constitutive law at single crystal level implemented in the models is discussed through fitting experimental data and calibrating viscous parameters. It is found that drag-stress type Norton law works well for the 1-site elastic-viscoplastic self-consistent (EVPSC) model while threshold stress type Norton law is suitable for the 2-site EVPSC model to assure that the viscoplastic inter-granular interaction is realistic. Both models have been verified by thoroughly fitting experimental data in literatures. For the 1-site EVPSC model, selected experimental data covers both macroscopic and microscopic mechanical responses of steels during deformation with a large range of strain rate from the quasi-static (10−4s−1) to the dynamic (~104s−1). For the 2-site EVPSC model, in situ neutron diffraction data of nickel-based superalloys with various microstructures was fitted. Both models generally fit the experimental data well. A comparison between the EVPSC and elastic-plastic self-consistent (EPSC) models on the prediction of lattice strains has also been made for both the 1-site and 2-site cases, which verifies the predictability on lattice strains of the newly developed EVPSC models. A validation of the homogenization approach for the EVPSC modeling has been performed, which confirms that the proposed EVPSC models are applicable for cubic structure materials with finite deformations. Our formulation of EVPSC modeling developed in this work shines a spotlight on the way of developing a multi-functional self-consistent model to predict both macroscopic and microscopic deformation behaviors of various polycrystalline materials under different loading rates of 10−4s−1~104s−1

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

YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design

The rapid development and wide utilization of object detection techniques have aroused attention on both accuracy and speed of object detectors. However, the current state-of-the-art object detection works are either accuracy-oriented using a large model but leading to high latency or speed-oriented using a lightweight model but sacrificing accuracy. In this work, we propose YOLObile framework, a real-time object detection on mobile devices via compression-compilation co-design. A novel block-punched pruning scheme is proposed for any kernel size. To improve computational efficiency on mobile devices, a GPU-CPU collaborative scheme is adopted along with advanced compiler-assisted optimizations. Experimental results indicate that our pruning scheme achieves 14$\times$ compression rate of YOLOv4 with 49.0 mAP. Under our YOLObile framework, we achieve 17 FPS inference speed using GPU on Samsung Galaxy S20. By incorporating our proposed GPU-CPU collaborative scheme, the inference speed is increased to 19.1 FPS, and outperforms the original YOLOv4 by 5$\times$ speedup. Source code is at: \url{https://github.com/nightsnack/YOLObile}

Accounting for lattice coherency in a two-phase elastic-plastic self-consistent model for nickel-based superalloys

A 2-site elastic-plastic self-consistent (EPSC) model is developed and implemented in order to account for crystallographic texture development and grain morphology evolution under strong correlations between neighbor grains of different phases, both in space and orientation. Predictions of the model adequately fit the published in situ neutron diffraction data for nickel-based superalloys at ambient and elevated temperatures, in whichγandγ\u27phases exhibit exact cube-cube orientation relationship. Comparison with 2-site model (small strain algorithm, non-rotation scheme) and 1-site model (finite strain algorithm, co-rotation scheme) has been made, and the result shows that the present 2-site model (finite strain algorithm, rotation scheme) leads to better predictions in lattice strain evolution where both rotation of crystal lattice and correlation between inclusions are accounted for, especially when the applied strain is larger than 0.02 for transverse direction and0.05∼0.18for axial direction for the materials studied in this work. Based on a systematic study on the effects of grain-grain interaction and total grain number on the homogenized results, we found that transverse lattice strains ofγ(200) and/orγ\u27(100) are sensitive to the interplay betweenγ-γ\u27interaction and evolution of grain orientation distribution with deformation, while that ofγ(220) andγ\u27(110) are sensitive to the initial crystallographic texture

Prognostic Value of CD44 and Its Isoforms in Advanced Cancer: A Systematic Meta-Analysis With Trial Sequential Analysis

Objective: Cancer stem cell marker CD44 and its variant isoforms (CD44v) may be correlated with tumor growth, metastasis, and chemo-radiotherapy resistance. However, the prognostic power of CD44 and CD44v in advanced cancer remains controversial. Therefore, the purpose of our study was to generalize the prognostic significance of these cancer stem cell markers in advanced cancer patients.Methods: Hazard ratios (HRs) with 95% confidence intervals (95% CIs) were calculated from multivariable analysis to assess the associations among CD44, CD44v6, and CD44v9 positivity and overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), cancer-specific survival (CSS), and recurrence-free survival (RFS). Trial sequential analysis (TSA) was also conducted.Results: We included 15 articles that reported on 1,201 patients with advanced cancer (CD44: nine studies with 796 cases, CD44v6: three studies with 143 cases, and CD44v9: three studies with 262 cases). CD44 expression was slightly linked to worse OS (HR = 2.03, P = 0.027), but there was no correlation between CD44 expression and DFS, RFS, or PFS. Stratified analysis showed that CD44 expression was not correlated with OS at ≥5 years or OS in patients receiving adjuvant therapy. CD44v6 expression was not associated with OS. CD44v9 expression was closely associated with poor 5-years CSS in patients treated with chemo/radiotherapy (HR = 3.62, P < 0.001). However, TSA suggested that additional trials were needed to confirm these conclusions.Conclusions: CD44 or CD44v9 might be novel therapeutic targets for improving the treatment of advanced cancer patients. Additional prospective clinical trials are strongly needed across different cancer types

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