Dynamic Response of Sandwich Tubes with Continuously Density-Graded Aluminum Foam Cores under Internal Explosion Load.

In this paper, the dynamic response of continually density-graded aluminum foam sandwich tubes under internal explosion load was studied. A 3D mesoscopic finite-element model of continually density-graded aluminum foam sandwich tubes was established by the 3D-Voronoi technology. The finite-element results were compared with the existing experimental results, and the rationality of the model was verified. The influences of the core density distribution, the core density gradient, and the core thickness on the blast resistance of the sandwich tubes were analyzed. The results showed that the blast resistance of the sandwich tube with the negative-gradient core is better than that of the sandwich tube with the uniform core. While the blast resistance of the sandwich tube with the positive-gradient core or the middle-hard-gradient core is worse than that of the sandwich tube with the uniform core. For the sandwich tube with the negative-gradient core, the core density gradient increased, and the blast resistance decreased. Increasing the thickness of the core can effectively decrease the deformation of the outer tube of the sandwich tube, but the specific energy absorption of both the whole sandwich tube and its core also decreases.

Recent Progress on Wear-Resistant Materials: Designs, Properties, and Applications.

There has been tremendous interest in the development of different innovative wear-resistant materials, which can help to reduce energy losses resulted from friction and wear by ≈40% over the next 10-15 years. This paper provides a comprehensive review of the recent progress on designs, properties, and applications of wear-resistant materials, starting with an introduction of various advanced technologies for the fabrication of wear-resistant materials and anti-wear structures with their wear mechanisms. Typical strategies of surface engineering and matrix strengthening for the development of wear-resistant materials are then analyzed, focusing on the development of coatings, surface texturing, surface hardening, architecture, and the exploration of matrix compositions, microstructures, and reinforcements. Afterward, the relationship between the wear resistance of a material and its intrinsic properties including hardness, stiffness, strength, and cyclic plasticity is discussed with underlying mechanisms, such as the lattice distortion effect, bonding strength effect, grain size effect, precipitation effect, grain boundary effect, dislocation or twinning effect. A wide range of fundamental applications, specifically in aerospace components, automobile parts, wind turbines, micro-/nano-electromechanical systems, atomic force microscopes, and biomedical devices are highlighted. This review is concluded with prospects on challenges and future directions in this critical field.

CNN Training with Twenty Samples for Crack Detection via Data Augmentation.

The excellent generalization ability of deep learning methods, e.g., convolutional neural networks (CNNs), depends on a large amount of training data, which is difficult to obtain in industrial practices. Data augmentation is regarded commonly as an effective strategy to address this problem. In this paper, we attempt to construct a crack detector based on CNN with twenty images via a two-stage data augmentation method. In detail, nine data augmentation methods are compared for crack detection in the model training, respectively. As a result, the rotation method outperforms these methods for augmentation, and by an in-depth exploration of the rotation method, the performance of the detector is further improved. Furthermore, data augmentation is also applied in the inference process to improve the recall of trained models. The identical object has more chances to be detected in the series of augmented images. This trick is essentially a performance-resource trade-off. For more improvement with limited resources, the greedy algorithm is adopted for searching a better combination of data augmentation. The results show that the crack detectors trained on the small dataset are significantly improved via the proposed two-stage data augmentation. Specifically, using 20 images for training, recall in detecting the cracks achieves 96% and Fext(0.8), which is a variant of F-score for crack detection, achieves 91.18%.

A patient-specific lumped-parameter model of coronary circulation.

A new lumped-parameter model for coronary hemodynamics is developed. This model is developed for the whole coronary network based on CT scans of a patient-specific geometry including the right coronary tree, which is absent in many previous mathematical models. The model adopts the structured tree model boundary conditions similar to the work of Olufsen et al., thus avoiding the necessity of invasive perfusion measurements. In addition, we also incorporated the effects of the head loss at the two inlets of the large coronary arteries for the first time. The head loss could explain the phenomenon of a sudden increase of the resistance at the inlet of coronary vessel. The estimated blood pressure and flow rate results from the model agree well with the clinical measurements. The computed impedances also match the experimental perfusion measurement. The effects of coronary arterial stenosis are considered and the fractional flow reserve and relative flow in the coronary vessels for a stenotic vessel computed in this model show good agreement with published experimental data. It is believed that the approach could be readily translated to clinical practice to facilitate real time clinical diagnosis.

Quasi-static and dynamic experimental studies on the tensile strength and failure pattern of concrete and mortar discs.

As concrete and mortar materials widely used in structural engineering may suffer dynamic loadings, studies on their mechanical properties under different strain rates are of great importance. In this paper, based on splitting tests of Brazilian discs, the tensile strength and failure pattern of concrete and mortar were investigated under quasi-static and dynamic loadings with a strain rate of 1-200 s-1. It is shown that the quasi-static tensile strength of mortar is higher than that of concrete since coarse aggregates weaken the interface bonding strength of the latter. Numerical results confirmed that the plane stress hypothesis lead to a lower value tensile strength for the cylindrical specimens. With the increase of strain rates, dynamic tensile strengths of concrete and mortar significantly increase, and their failure patterns change form a single crack to multiple cracks and even fragment. Furthermore, a relationship between the dynamic increase factor and strain rate was established by using a linear fitting algorithm, which can be conveniently used to calculate the dynamic increase factor of concrete-like materials in engineering applications.

Spherical and cylindrical cavity expansion models based prediction of penetration depths of concrete targets.

The cavity expansion theory is most widely used to predict the depth of penetration of concrete targets. The main purpose of this work is to clarify the differences between the spherical and cylindrical cavity expansion models and their scope of application in predicting the penetration depths of concrete targets. The factors that influence the dynamic cavity expansion process of concrete materials were first examined. Based on numerical results, the relationship between expansion pressure and velocity was established. Then the parameters in the Forrestal's formula were fitted to have a convenient and effective prediction of the penetration depth. Results showed that both the spherical and cylindrical cavity expansion models can accurately predict the depth of penetration when the initial velocity is lower than 800 m/s. However, the prediction accuracy decreases with the increasing of the initial velocity and diameters of the projectiles. Based on our results, it can be concluded that when the initial velocity is higher than the critical velocity, the cylindrical cavity expansion model performs better than the spherical cavity expansion model in predicting the penetration depth, while when the initial velocity is lower than the critical velocity the conclusion is quite the contrary. This work provides a basic principle for selecting the spherical or cylindrical cavity expansion model to predict the penetration depth of concrete targets.

Origin of high strength, low modulus superelasticity in nanowire-shape memory alloy composites.

An open question is the underlying mechanisms for a recent discovered nanocomposite, which composed of shape memory alloy (SMA) matrix with embedded metallic nanowires (NWs), demonstrating novel mechanical properties, such as large quasi-linear elastic strain, low Young's modulus and high yield strength. We use finite element simulations to investigate the interplay between the superelasticity of SMA matrix and the elastic-plastic deformation of embedded NWs. Our results show that stress transfer plays a dominated role in determining the quasi-linear behavior of the nanocomposite. The corresponding microstructure evolution indicate that the transfer is due to the coupling between plastic deformation within the NWs and martensitic transformation in the matrix, i.e., the martensitic transformation of the SMA matrix promotes local plastic deformation nearby, and the high plastic strain region of NWs retains considerable martensite in the surrounding SMA matrix, thus facilitating continues martensitic transformation in subsequent loading. Based on these findings, we propose a general criterion for achieving quasi-linear elasticity.

Lyn deficiency leads to increased microbiota-dependent intestinal inflammation and susceptibility to enteric pathogens.

The Lyn tyrosine kinase governs the development and function of various immune cells, and its dysregulation has been linked to malignancy and autoimmunity. Using models of chemically induced colitis and enteric infection, we show that Lyn plays a critical role in regulating the intestinal microbiota and inflammatory responses as well as protection from enteric pathogens. Lyn(-/-) mice were highly susceptible to dextran sulfate sodium (DSS) colitis, characterized by significant wasting, rectal bleeding, colonic pathology, and enhanced barrier permeability. Increased DSS susceptibility in Lyn(-/-) mice required the presence of T but not B cells and correlated with dysbiosis and increased IFN-γ(+) and/or IL-17(+) colonic T cells. This dysbiosis was characterized by an expansion of segmented filamentous bacteria, associated with altered intestinal production of IL-22 and IgA, and was transmissible to wild-type mice, resulting in increased susceptibility to DSS. Lyn deficiency also resulted in an inability to control infection by the enteric pathogens Salmonella enterica serovar Typhimurium and Citrobacter rodentium. Lyn(-/-) mice exhibited profound cecal inflammation, bacterial dissemination, and morbidity following S. Typhimurium challenge and greater colonic inflammation throughout the course of C. rodentium infection. These results identify Lyn as a key regulator of the mucosal immune system, governing pathophysiology in multiple models of intestinal disease.

Dysregulated hematopoiesis caused by mammary cancer is associated with epigenetic changes and hox gene expression in hematopoietic cells.

Cancer is associated with immune dysfunction characterized by the presence of proinflammatory and immunosuppressive cells and factors that contribute to tumor growth and progression. Here we show that mammary tumor growth is associated with defects in hematopoiesis, leading to myeloproliferative-like disease (leukemoid reaction), anemia, and disruption of the bone marrow stem/progenitor compartment. The defects we characterized included impaired erythropoiesis, leukocytosis, loss of early progenitor cells in the bone marrow, and splenic extramedullary hematopoiesis. We established an in vitro model to dissect interactions between mammary cancers and the hematopoietic system. Investigations in this model revealed that granulocyte colony-stimulating factor (G-CSF) produced by mammary tumors can synergize with FLT3L and granulocyte macrophage CSF (GM-CSF) to expand myeloid progenitors and their progeny in culture. Mammary tumor growth was associated with histone methylation changes within lineage-negative c-Kit-positive hematopoietic cells within the bone marrow of tumor-bearing mice. Similarly, parallel histone methylation patterns occurred in cultured bone marrow cells exposed to mammary tumor-conditioned cell culture media. Notably, changes in histone methylation in these cell populations correlated with dysregulated expression of genes controlling hematopoietic lineage commitment and differentiation, including Hox family genes and members of the Polycomb repressive complex 2 (PRC2) chromatin-remodeling complex. Together, our results show that mammary tumor-secreted factors induce profound perturbations in hematopoiesis and expression of key hematopoietic regulatory genes.

Human dendritic cells engineered to secrete interleukin-18 activate MAGE-A3-specific cytotoxic T lymphocytes in vitro.

Adoptive cell transfer (ACT) involves the administration of tumor specific cytotoxic T lymphocytes (CTLs) into a patient to kill cancer cells. Although a promising cancer therapy, limitations on the generation of activated CTLs have restricted ATC's clinical application. Interleukin-18 (IL-18) is an interferon-γ (IFN-γ) inducing factor that plays an important functional role in regulating CTLs. Here, we attempt to use dendritic cells (DCs) modified with a recombinant adenovirus encoding IL-18 (rAd/IL-18) to improve the generation of activated tumor-specific CTLs. These engineered DCs secrete IL-18, increase the expression of co-stimulatory molecules, and enhance the cytotoxic efficacy of melanoma antigen 3 (MAGE-A3)-specific CTLs in vitro. We show that stimulation of CTLs with rAd/IL-18-loaded DCs increases the specific lysis of MAGE-A3-expressing human breast cancer MCF-7 cells, and at the same time increases the production of activated MAGE-A3-specific CTLs. Our results indicate that transducing DCs with rAd/IL-18 increases both the maturation of DCs and the activation level of MAGE-A3-specific CTLs, greatly enhancing the cytotoxic efficacy of CTLs towards tumor cells.