On the effect of the loading apparatus stiffness on the equilibrium and stability of soft adhesive contacts under shear loads

The interaction between contact area and frictional forces in adhesive soft contacts is receiving much attention in the scientific community due to its implications in many areas of engineering such as surface haptics and bioinspired adhesives. In this work, we consider a soft adhesive sphere that is pressed against a rigid substrate and is sheared by a tangential force where the loads are transferred to the sphere through a normal and a tangential spring, representing the loading apparatus stiffness. We derive a general linear elastic fracture mechanics solution, taking into account also the interaction between modes, by adopting a simple but effective mixed-mode model that has been recently validated against experimental results in similar problems. We discuss how the spring stiffness affects the stability of the equilibrium contact solution, i.e. the transition to separation or to sliding

ActivinA: a new leukemia-promoting factor conferring migratory advantage to B-cell precursor-acute lymphoblastic leukemic cells

B-cell precursor-acute lymphoblastic leukemia modulates the bone marrow (BM) niche to become leukemia-supporting and chemo-protective by reprogramming the stromal microenvironment. New therapies targeting the interplay between leukemia and stroma can help improve disease outcome. We identified ActivinA, a TGF-b family member with a well-described role in promoting several solid malignancies, as a factor favoring leukemia that could represent a new potential target for therapy. ActivinA resulted over-expressed in the leukemic BM and its production was strongly induced in mesenchymal stromal cells after culture with leukemic cells. Moreover, MSCs isolated from BM of leukemic patients showed an intrinsic ability to secrete higher amounts of ActivinA compared to their normal counterparts. The pro-inflammatory leukemic BM microenvironment synergized with leukemic cells to induce stromal-derived ActivinA. Gene expression analysis of ActivinA-treated leukemic cells showed that this protein was able to significantly influence motility-associated pathways. Interestingly, ActivinA promoted random motility and CXCL12-driven migration of leukemic cells, even at suboptimal chemokine concentrations, characterizing the leukemic niche. Conversely, ActivinA severely impaired CXCL12-induced migration of healthy CD34 + cells. This opposite effect can be explained by the ability of ActivinA to increase intracellular calcium only in leukemic cells, boosting cytoskeleton dynamics through a higher rate of actin polymerization. Moreover, by stimulating the invasiveness of the leukemic cells, ActivinA was found to be a leukemia-promoting factor. Importantly, the ability of ActivinA to enhance BM engraftment and the metastatic potential of leukemic cells was confirmed in a xenograft mouse model of the disease. Overall, ActivinA was seen to be a key factor in conferring a migratory advantage to leukemic cells over healthy hematopoiesis within the leukemic niche

Adaptation and Attention for Neural Video Coding

Neural image coding represents now the state-of-The-Art image compression approach. However, a lot of work is still to be done in the video domain. In this work, we propose an end-To-end learned video codec that introduces several architectural novelties as well as training novelties, revolving around the concepts of adaptation and attention. Our codec is organized as an intra-frame codec paired with an inter-frame codec. As one architectural novelty, we propose to train the inter-frame codec model to adapt the motion estimation process based on the resolution of the input video. A second architectural novelty is a new neural block that combines concepts from split-Attention based neural networks and from DenseNets. Finally, we propose to overfit a set of decoder-side multiplicative parameters at inference time. Through ablation studies and comparisons to prior art, we show the benefits of our proposed techniques in terms of coding gains. We compare our codec to VVC/H.266 and RLVC, which represent the state-of-The-Art traditional and end-To-end learned codecs, respectively, and to the top performing end-To-end learned approach in 2021 CLIC competition, E2E_T_OL. Our codec clearly outperforms E2E_T_OL, and compare favorably to VVC and RLVC in some settings.acceptedVersionPeer reviewe

Adaptation and Attention for Neural Video Coding

Neural image coding represents now the state-of-The-Art image compression approach. However, a lot of work is still to be done in the video domain. In this work, we propose an end-To-end learned video codec that introduces several architectural novelties as well as training novelties, revolving around the concepts of adaptation and attention. Our codec is organized as an intra-frame codec paired with an inter-frame codec. As one architectural novelty, we propose to train the inter-frame codec model to adapt the motion estimation process based on the resolution of the input video. A second architectural novelty is a new neural block that combines concepts from split-Attention based neural networks and from DenseNets. Finally, we propose to overfit a set of decoder-side multiplicative parameters at inference time. Through ablation studies and comparisons to prior art, we show the benefits of our proposed techniques in terms of coding gains. We compare our codec to VVC/H.266 and RLVC, which represent the state-of-The-Art traditional and end-To-end learned codecs, respectively, and to the top performing end-To-end learned approach in 2021 CLIC competition, E2E_T_OL. Our codec clearly outperforms E2E_T_OL, and compare favorably to VVC and RLVC in some settings.acceptedVersionPeer reviewe

Learned Enhancement Filters for Image Coding for Machines

Machine-To-Machine (M2M) communication applications and use cases, such as object detection and instance segmentation, are becoming mainstream nowadays. As a consequence, majority of multimedia content is likely to be consumed by machines in the coming years. This opens up new challenges on efficient compression of this type of data. Two main directions are being explored in the literature, one being based on existing traditional codecs, such as the Versatile Video Coding (VVC) standard, that are optimized for human-Targeted use cases, and another based on end-To-end trained neural networks. However, traditional codecs have significant benefits in terms of interoperability, real-Time decoding, and availability of hardware implementations over end-To-end learned codecs. Therefore, in this paper, we propose learned post-processing filters that are targeted for enhancing the performance of machine vision tasks for images reconstructed by the VVC codec. The proposed enhancement filters provide significant improvements on the target tasks compared to VVC coded images. The conducted experiments show that the proposed post-processing filters provide about 45% and 49% Bjontegaard Delta Rate gains over VVC in instance segmentation and object detection tasks, respectively.acceptedVersionPeer reviewe

On the application of fracture mechanics mixed-mode models of sliding with friction and adhesion

As recently suggested in an interesting and stimulating paper by Menga, Carbone and Dini (MCD), applying fracture mechanics energy concepts for the case of a sliding adhesive contact, imposing also the shear stress is constant at the interface and equal to a material constant (as it seems in experiments), leads to a increase of contact area which instead is never observed. We add that the MCD theory also predicts a size effect and hence a distortion of the JKR curve during sliding which is also not observed in experiments. Finally, a simpler example with the pure mode I contact case, leads in the MCD theory to an unbounded contact area, rather than a perhaps more correct limit of the Maugis-Dugdale solution for the adhesive sphere when Tabor parameter is zero, that is DMT's solution. We discuss that the MCD theory does not satisfy equilibrium, and we propose some more correct formulations, although they may be rather academic: recent semi-empirical models, with an appropriate choice of the empirical parameters, seem more promising and robust in modelling actual experiments