ME Design and Freeform Fabrication of Compliant Cellular Materials with Graded Stiffness

Typically, cellular materials are designed for structural applications to provide stiffness or absorb impact via permanent plastic deformation. Alternatively, it is possible to design compliant cellular materials that absorb energy via recoverable elastic deformation, allowing the material to spring back to its original configuration after the load is released. Potential applications include automotive panels or prosthetic applications that require repeated, low-speed impact absorption without permanent deformation. The key is to arrange solid base material in cellular topologies that permit high levels of elastic deformation. To prevent plastic deformation, the topologies are designed for contact between cell walls at predetermined load levels, resulting in customized, graded stiffness profiles. Design techniques are established for synthesizing cellular topologies with customized compliance for static or quasi-static applications. The design techniques account for cell wall contact, large scale deformations, and material nonlinearities. Resulting cellular material designs are fabricated with selective laser sintering, and their properties are experimentally evaluated.Mechanical Engineerin

3D Experimental investigation of the hygro-mechanical behaviour of wood at cellular and sub-cellular scale: detection of local deformations

The swelling/shrinkage of spruce wood samples (Picea Abies) is documented with high resolution XRay Tomography and advanced image analysis tools. We report the reversible moisture-induced global and local deformations at the cellular and sub-cellular scales. In particular, we present sophisticated methods for detecting local deformations in the cell wall. Insight is given on the hygromechanical behaviour of wood cell material and on the role of ultra-cellular components in wood, such as bordered pits and rays

Honeycomb-laminate composite structure

A honeycomb-laminate composite structure was comprised of: (1) a cellular core of a polyquinoxaline foam in a honeycomb structure, and (2) a layer of a noncombustible fibrous material impregnated with a polyimide resin laminated on the cellular core. A process for producing the honeycomb-laminate composite structure and articles containing the honeycomb-laminate composite structure is described

The selectivity and specificity of autophagy in drosophila

Autophagy is a process of cellular self-degradation and is a major pathway for elimination of cytoplasmic material by the lysosomes. Autophagy is responsible for the degradation of damaged organelles and protein aggregates and therefore plays a significant role in cellular homeostasis. Despite the initial belief that autophagy is a nonselective bulk process, there is growing evidence during the last years that sequestration and degradation of cellular material by autophagy can be accomplished in a selective and specific manner. Given the role of autophagy and selective autophagy in several disease related processes such as tumorigenesis, neurodegeneration and infections, it is very important to dissect the molecular mechanisms of selective autophagy, in the context of the system and the organism. An excellent genetically tractable model organism to study autophagy is Drosophila, which appears to have a highly conserved autophagic machinery compared with mammals. However, the mechanisms of selective autophagy in Drosophila have been largely unexplored. The aim of this review is to summarize recent discoveries about the selectivity of autophagy in Drosophila

Deep Q-Learning for Self-Organizing Networks Fault Management and Radio Performance Improvement

We propose an algorithm to automate fault management in an outdoor cellular network using deep reinforcement learning (RL) against wireless impairments. This algorithm enables the cellular network cluster to self-heal by allowing RL to learn how to improve the downlink signal to interference plus noise ratio through exploration and exploitation of various alarm corrective actions. The main contributions of this paper are to 1) introduce a deep RL-based fault handling algorithm which self-organizing networks can implement in a polynomial runtime and 2) show that this fault management method can improve the radio link performance in a realistic network setup. Simulation results show that our proposed algorithm learns an action sequence to clear alarms and improve the performance in the cellular cluster better than existing algorithms, even against the randomness of the network fault occurrences and user movements.Comment: (c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Localized and Cellular Patterns in a Vibrated Granular Layer

We propose a phenomenological model for pattern formation in a vertically vibrated layer of granular material. This model exhibits a variety of stable cellular patterns including standing rolls and squares as well as localized objects (oscillons and worms), similar to recent experimental observations(Umbanhowar et al., 1996). The model is an amplitude equation for the parametrical instability coupled to the mass conservation law. The structure and dynamics of the solutions resemble closely the properties of localized and cellular patterns observed in the experiments.Comment: 4 pages, 4 figures, submitted to Phys. Rev. Let