Living Materials Herald a New Era in Soft Robotics

Living beings have an unsurpassed range of ways to manipulate objects and interact with them. They can make autonomous decisions and can heal themselves. So far, a conventional robot cannot mimic this complexity even remotely. Classical robots are often used to help with lifting and gripping and thus to alleviate the effects of menial tasks. Sensors can render robots responsive, and artificial intelligence aims at enabling autonomous responses. Inanimate soft robots are a step in this direction, but it will only be in combination with living systems that full complexity will be achievable. The field of biohybrid soft robotics provides entirely new concepts to address current challenges, for example the ability to self‐heal, enable a soft touch, or to show situational versatility. Therefore, “living materials” are at the heart of this review. Similarly to biological taxonomy, there is a recent effort for taxonomy of biohybrid soft robotics. Here, an expansion is proposed to take into account not only function and origin of biohybrid soft robotic components, but also the materials. This materials taxonomy key demonstrates visually that materials science will drive the development of the field of soft biohybrid robotics.     

Cell therapy using an array of ultrathin hollow microneedles

Microsystem Technologies - Cell transplantation traditionally employs needles to inject donor cells into tissues to treat certain diseases. However, it is difficult for the current method to...     

Radio planning of energy-aware cellular networks

This paper introduces a joint planning and management optimization approach for cellular networks to limit energy consumption while guaranteeing QoS and minimizing operators Capex and Opex. The modeling framework shows that an effective energy-efficient operation depends on the planning decisions. Conversely, it also shows that planning with energy management operation in view yields more versatile topologies than more traditional models based only on Capex. Results for LTE networks are provided and show that savings up to 65% in energy expenses are possible with slight increases in capital investments.     

New Insights on Plant Cell Elongation: A Role for Acetylcholine

We investigated the effect of auxin and acetylcholine on the expression of the tomato expansin gene LeEXPA2, a specific expansin gene expressed in elongating tomato hypocotyl segments. Since auxin interferes with clathrin-mediated endocytosis, in order to regulate cellular and developmental responses we produced protoplasts from tomato elongating hypocotyls and followed the endocytotic marker, FM4-64, internalization in response to treatments. Tomato protoplasts were observed during auxin and acetylcholine treatments after transient expression of chimerical markers of volume-control related compartments such as vacuoles. Here we describe the contribution of auxin and acetylcholine to LeEXPA2 expression regulation and we support the hypothesis that a possible subcellular target of acetylcholine signal is the vesicular transport, shedding some light on the characterization of this small molecule as local mediator in the plant physiological response.     

Biomechanics of fibrous proteins of the extracellular matrix studied by Brillouin scattering

Brillouin light scattering (BLS) spectroscopy is a technique that is able to detect thermally excited phonons within a material. The speed of propagation of these phonons can be determined from the magnitude of the Brillouin frequency shift between incident and scattered light, thereby providing a measure of the mechanical properties of the material in the gigahertz range. The mechanical properties of the extracellular matrices of biological tissues and their constituent biopolymers are important for normal tissue function and disturbances in these properties are widely implicated in disease. BLS offers the prospect of measuring mechanical properties on a microscopic scale in living tissues, thereby providing insights into structure–function relationships under normal and pathological conditions. In this study, we investigated BLS in collagen and elastin—the fibrous proteins of the extracellular matrix (ECM). Measurements were made on type I collagen in rat tail tendon, type II collagen in articular cartilage and nuchal ligament elastin. The dependence of the BLS spectrum on fibre orientation was investigated in a backscattering geometry using a reflective substrate. Two peaks, a bulk mode arising from phonon propagation along a quasi-radial direction to the fibre axis and a mode parallel to the surface, depending on sample orientation relative to the fibre axis, could be distinguished. The latter peak was fitted to a model of wave propagation through a hexagonally symmetric elastic solid, and the five components of the elasticity tensor were combined to give axial and transverse Young''s, shear and bulk moduli of the fibres. These were 10.2, 8.3, 3.2 and 10.9 GPa, and 6.1, 5.3, 1.9 and 8 GPa for dehydrated type I collagen and elastin, respectively. The former values are close to those previously reported. A microfocused BLS approach was also applied providing selection of single fibres. The moduli of collagen and elastin are much higher than those measured at lower frequency using macroscopic strains, and the difference between them is much less. We therefore believe, like previous investigators, that molecular-scale viscoelastic effects are responsible for the frequency dependence of the fibre biomechanics. Combining BLS with larger-scale mechanical testing methods therefore should, in the future, provide a means of following the evolution of mechanical properties in the formation of the complex structures found in the ECM.     

Neuro-evolutionary approach applied for optimizing the PEMFC performance

A multi-objective optimization strategy, based on stacked neural network–genetic algorithm (SNN–GA) hybrid approach, was applied to study the C/PBI content on a high temperature PEMFC performance. The operating conditions of PEMFC were correlated with power density and electrochemical active surface area for electrodes. The structure of the stack was determined in an optimal form related to the contribution of individual neural networks, after applying an interpolation based procedure. Multi-objective optimization using SNN as model and GA as solving procedure provides optimal working conditions which lead to a high PEMFC performance. Simulation results were in agreement with experimental data, both for model validation and system optimization (the C/PBI content in the range of 17–21%).     

Thermoacoustic Emission from Carbon Nanotubes Imaged by Atomic Force Microscopy

The thermoacoustic effect of isolated single‐wall carbon nanotubes aligned between electrodes is experimentally observed for the first time by imaging the emitted acoustic wave using an atomic force microscopy‐based technique specifically developed for the task. The capability of such a technique for single‐point thermoacoustic measurements is first verified on carbon nanotubes layers with two electrodes for injecting alternate electric current. The technique is then demonstrated to allow the acquisition, simultaneously with the topography, of images reflecting the pressure of the acoustic wave at fixed distance from the sample. Such a capability is used to collect images reflecting the amplitude of acoustic waves generated by isolated nanotubes and nanotube bundles by the thermoacoustic effect.