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In applied biotremology, vibrational signals or cues are exploited to manipulate the target species behaviour. To develop an efficient pest control strategy, other than a detailed investigation into the pest biology and behaviour, the role of the substrate used to transmit the signal is an important feature to be considered, since it may affect vibrations spreading and effective signal transmission and perception. Therefore, we used a multi-disciplinary approach to develop a control technique against the greenhouse whitefly

BACKGROUND Many groups of insects utilize substrate-borne vibrations for intraspecific communication. This characteristic makes them a suitable model for exploring the use of vibrations as a tool for pest control as an alternative to the use of chemicals. Detailed knowledge of species communication is a prerequisite to select the best signals to use. This study explored the use of substrate-borne vibrations for pest control of the brown marmorated stink bug (BMSB), Halyomorpha halys Stal (Heteroptera: Pentatomidae). For this purpose, we first identified the spectral and temporal characteristics that best elicit male responsiveness. Bioassays were conducted with artificial signals that mimicked the natural female calling signal. Second, we used the acquired knowledge to synthesize new signals endowed with different degrees of attractiveness in single- and two-choice bioassays using a wooden custom-made T stand. RESULTS The results from this study showed that males were attracted to female signals along a high range of amplitudes, especially starting from a threshold of 100 μm s-1 , a high pulse repetition time (1 s) and frequency peak corresponding to the first harmonic (76 Hz). This resulted in an "optimal" signal for use to attract males, while the choice test in the T arena showed that this signal elicits searching behavior and attracts BMSB males towards a stimulation point. CONCLUSION We confirm the use of vibrational signals as a strong tool for behavioral manipulation of male BMSB and suggest its possible use in the development of field traps and further management of this pest. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

In applied biotremology, vibrational signals or cues are exploited to manipulate the target species behaviour. To develop an efficient pest control strategy, other than a detailed investigation into the pest biology and behaviour, the role of the substrate used to transmit the signal is an important feature to be considered, since it may affect vibrations spreading and effective signal transmission and perception. Therefore, we used a multi-disciplinary approach to develop a control technique against the greenhouse whitefly,Trialeurodes vaporariorum.First, anad hocvibrational disruptive noise has been developed, based on the acquired knowledge about the mating behaviour and vibrational communication of the mated species. Subsequently, we employed finite-element models to investigate a growing tomato plant response to the aforesaid noise. Modelling how vibrations spread along the plant allowed us to set up a greenhouse experiment to assess the efficacy in terms of insect population of the vibrational treatment, which was administrated through vibrational plates. The green methodology applied in this study represents an innovative, environmentally sound alternative to the usage of synthetic pesticides.

Articular cartilage is a complex connective tissue with the fundamental functions of load bearing, shock absorption and lubrication in joints. However, traumatic events, aging and degenerative pathologies may affect its structural integrity and function, causing pain and long-term disability. Osteoarthritis represents a health issue, which concerns an increasing number of people worldwide. Moreover, it has been observed that this pathology also affects the mechanical behavior of the articular cartilage. To better understand this correlation, the here proposed review analyzes the physiological aspects that influence cartilage microstructure and biomechanics, with a special focus on the pathological changes caused by osteoarthritis. Particularly, the experimental data on human articular cartilage are presented with reference to different techniques adopted for mechanical testing and the related theoretical mechanical models usually applied to articular cartilage are briefly discussed.

Mechanical stimuli are fundamental in the development of organs and tissues, their growth, regeneration or disease. They influence the biochemical signals produced by the cells, and, consequently, the development and spreading of a disease. Moreover, tumour cells are usually characterized by a decrease in the cell mechanical properties that may be directly linked to their metastatic potential. Thus, recently, the experimental and computational study of cell biomechanics is facing a growing interest. Various experimental approaches have been implemented to describe the passive response of cells; however, cell variability and complex experimental procedures may affect the obtained mechanical properties. For this reason, in-silico computational models have been developed through the years, to overcome such limitations, while proposing valuable tools to understand cell mechanical behaviour. This being the case, we propose a combined continuous-tensegrity finite element (FE) model to analyse the mechanical response of a cell and its subcomponents, observing how every part contributes to the overall mechanical behaviour. We modelled both Atomic Force Microscopy (AFM) indentation and micropipette aspiration techniques, as common mechanical tests for cells and elucidated also the role of cell cytoplasm and cytoskeleton in the global cell mechanical response.

Background Obesity has become a global epidemic. Bariatric surgery is considered the most effective therapeutic weapon in terms of weight loss and improvement of quality of life and comorbidities. Laparoscopic sleeve gastrectomy (LSG) is one of the most performed procedures worldwide, although patients carry a nonnegligible risk of developing post-operative GERD and BE. Objectives The aim of this work is the development of computational patient-specific models to analyze the changes induced by bariatric surgery, i.e., the volumetric gastric reduction, the mechanical response of the stomach during an inflation process, and the related elongation strain (ES) distribution at different intragastric pressures. Methods Patient-specific pre- and post-surgical models were extracted from Magnetic Resonance Imaging (MRI) scans of patients with morbid obesity submitted to LSG. Twenty-three patients were analyzed, resulting in forty-six 3D-geometries and related computational analyses. Results A significant difference between the mechanical behavior of pre- and post-surgical stomach subjected to the same internal gastric pressure was observed, that can be correlated to a change in the global stomach stiffness and a minor gastric wall tension, resulting in unusual activations of mechanoreceptors following food intake and satiety variation after LSG. Conclusions Computational patient-specific models may contribute to improve the current knowledge about anatomical and physiological changes induced by LSG, aiming at reducing post-operative complications and improving quality of life in the long run.

Materials that combine the functionalities of both of proteins and graphene are of great interest for the engineering of biosensing, drug delivery, and regenerative devices. Graphene oxide (GO) offers an opportunity to design GO‐protein interactions but the need for harsh reduction processes to enable GO photoexcitation remains a limitation. A disinfector‐assisted low temperature method to reduce GO‐protein materials and fabricate surgical dressings with tuneable photothermal efficiency and bioactive properties for the postoperative treatment of melanoma is reported. The approach harnesses the capacity of 70% ethanol to penetrate the protein shell of microorganisms to infiltrate GO‐protein complexes and reduce GO at low temperature (85 °C) while maintaining the material structure and bioactivity. Both experiments and coarse‐grained simulations are used to describe the reduction process and assess the material properties. In vitro and in vivo validation revealed the capacity of the dressings to prevent tumor recurrence and promote healing after tumor resection.

Due to a widespread number of examples, biological hierarchical structures have been studied for years, founding that surface properties are strictly correlated to the surface roughness. Since friction appears to be a multiscale phenomenon and hierarchy optimizes the macroscopic mechanical properties of bodies, it may be of great interest to develop a model to predict friction of structures with hierarchical surfaces. Thus, we propose an analytical model to describe anisotropic friction, adhesion and wear of hierarchical surfaces. The model describes friction between two generic rough surfaces in contact, sliding one against the other. Then, it has been extended to adhesion, wear and finally to multiple hierarchical levels to obtain the global frictional response.

Supramolecular chemistry offers an exciting opportunity to assemble materials with molecular precision. However, there remains an unmet need to turn molecular self-assembly into functional materials and devices. Harnessing the inherent properties of both disordered proteins and graphene oxide (GO), we report a disordered protein-GO co-assembling system that through a diffusion-reaction process and disorder-to-order transitions generates hierarchically organized materials that exhibit high stability and access to non-equilibrium on demand. We use experimental approaches and molecular dynamics simulations to describe the underlying molecular mechanism of formation and establish key rules for its design and regulation. Through rapid prototyping techniques, we demonstrate the system’s capacity to be controlled with spatio-temporal precision into well-defined capillary-like fluidic microstructures with a high level of biocompatibility and, importantly, the capacity to withstand flow. Our study presents an innovative approach to transform rational supramolecular design into functional engineering with potential widespread use in microfluidic systems and organ-on-a-chip platforms. Self-organising systems have huge potential in device design and fabrication; however, demonstrations of this are limited. Here, the authors report on a combination of disordered proteins and graphene oxide which allows spatio-temporal patterning and demonstrate the fabrication of microfluidic devices.

New possibilities have emerged in recent years, with the development of high-precision fabrication techniques, to exploit microscale surface patterning to modify tribological properties of polymeric materials. However, the effect of surface topography, together with material mechanical parameters, needs to be fully understood to allow the design of surfaces with the desired characteristics. In this paper, we experimentally assess the effect of various types of micropatterned Polydimethylsiloxane surfaces, including anisotropic ones, on macroscopic substrate friction properties. We find that it is possible, through surface patterning, to modify both static and dynamic friction coefficients of the surfaces, demonstrating the possibility of achieving tunability. Additionally, we compare experimental observations with the numerical predictions of a 2D Spring-Block model, deriving the material parameters from tests on the corresponding flat surfaces. We find a good quantitative agreement between calculated and measured trends for various micropattern geometries, demonstrating that the proposed numerical approach can reliably describe patterned surfaces when appropriate material parameters are used. The presented results can further contribute to the description and understanding of the frictional effects of surface patterning, with the aim of achieving surfaces with extreme tunability of tribological properties. Keywords: Friction, Adhesion, Micro-fabrication, Spring-block model

We present a smart robot structure that exploits anisotropic friction to achieve stick-slip locomotion. The robot is made out of three components: a plastic beam, a planar dielectric elastomer actuator and four bristle pads with asymmetric rigid metallic bristles. We show that when the robot is electronically activated at increasing frequency, its structure exploits the resonance condition to reach the maximum locomotion speed. The fundamental frequency of the structure is estimated both analytically and numerically, allowing the range of frequencies in which the top locomotion speed was observed during the experiments to be identified. The locomotion speed of the robot as a function of the actuation frequency is estimated with a frequency response analysis performed on a discretised model of the structure, revealing good agreement with the experimental evidence.

A variety of applications, spanning from structural or biomedical engineering to flexible electronics, require the development of materials able to withstand high load and, at the same time, accommodate high strain before failure. While strength and toughness are often self-excluding properties in man-made materials, they can be efficiently combined by nature, which provides source of inspiration for novel materials design. Herein this paper, we pursue a bio-inspired approach, based on the introduction of a mechanical sink, such as a running knot, to improve the toughness modulus of high-performance polymeric microfibres. These are then enriched with additional smart features, such as a viscoelastic coating, surface roughening or a combination of those, to amplify the beneficial effect of the knot introduction. The role played by all such features on the mechanical performances of the prepared fibre samples, namely load at failure and toughness modulus increase, is then evaluated through a statistical technique, known as correspondence analysis (CA). While this exploratory analysis is widely adopted in biology, ecology, neuroscience or genetics, applications in structural or mechanical engineering are still rare. Here, we show that CA can be a powerful tool for the design of materials provided with enhanced toughness without losing strength.

We consider the mechanical motion of a system of six macroscopic pendula which are connected with springs and arranged in a hexagonal geometry. When the springs are pre-tensioned, the coupling between neighbouring pendula along the longitudinal (L) and the transverse (T) directions are different: identifying the motion along the L and T directions as the two components of a spin-like degree of freedom, we theoretically and experimentally verify that the pre-tensioned springs result in a tunable spin–orbit coupling. We elucidate the structure of such a spin–orbit coupling in the extended two-dimensional honeycomb lattice, making connections to physics of graphene. The experimental frequencies and the oscillation patterns of the eigenmodes for the hexagonal ring of pendula are extracted from a spectral analysis of the motion of the pendula in response to an external excitation and are found to be in good agreement with our theoretical predictions. We anticipate that extending this classical analogue of quantum mechanical spin–orbit coupling to two-dimensional lattices will lead to exciting new topological phenomena in classical mechanics.

Knots are fascinating topological elements, which can be found in both natural and artificial systems. While in most of the cases, knots cannot be loosened without breaking the strand where they are tightened, herein, attention is focused on slip or running knots, which on the contrary can be unfastened without compromising the structural integrity of their hosting material. Two different topologies are considered, involving opposite unfastening mechanisms and their influence on the mechanical properties of natural fibers, as silkworm silk raw and degummed single fibers, is investigated and quantified. Slip knots with optimized shape and size result in a significant enhancement of fibers energy dissipation capability, up to 300–400%, without affecting their load bearing capacity.

Over a century of scientific research on the sliding friction of ice has not been enough to develop an exhaustive explanation for the tribological behavior of frozen water. It has been recognized that ice shows different friction regimes, but a detailed description of all the different phenomena and processes occurring at the interface, including the effect of surface roughness of both the ice and the antagonist material is still missing. In this work the effect of surface morphology on the friction of steel/ice interfaces is studied. Different degrees of random roughness on steel surfaces are introduced and the friction coefficient is measured over a wide range of temperature and sliding velocity. Correlation between the surface roughness and the lubrication regime and friction coefficient is discussed. A theoretical model is developed in order to explain this correlation, and to control the tribological behavior of the system by a proper selection of surface roughness parameters.

Ethylene-propylene-diene terpolymer rubber (EPDM)-based nanocomposites containing carbon black (CB), graphene nanoplatelets (GNPs), and mixtures of the two fillers were prepared. The influence of the relative amounts of the two fillers on the dynamic and static friction coefficients was examined. The static analysis of the coefficient of friction suggests that the partial substitution GNPs into the EPDM/CB blend did not produce a significant variation of the surface grip. The sample comprising EPDM/CB composite and an effective amount of GNPs dispersed in the matrix provides an increase of the thermal conductivity, damping (i. e. shock absorbing properties) and mechanical properties of the nanocomposites. The field-emission scanning electron microscopy and micro tomography analyses showed that the replacement of CB with GNPs reduces the CB aggregation and, hence, improving the percolation of the hybrid fillers and the interface resistance of the composite. The development of thermally conducting elastomeric nanocomposites could envisage their utilization in the processing of rubber blends satisfying the increasing demand to reduce both the duration of the vulcanization process and thus the cost of the vulcanized rubbers., NMP is supported by the European Research Council (ERC StG Ideas 2011 BIHSNAM n. 279985 on “Bio-Inspired hierarchical supernanomaterials”, ERC PoC 2013 KNOTOUGH n. 632277 on “Supertough knotted fibers”, ERC PoC 2015 SILKENE nr. 693670 on “Bionic silk with graphene or other nanomaterials spun by silkworms”), by the European Commission under the Graphene Flagship (WP10 “Nanocomposites”, n. 604391) and by the Provincia Autonoma di Trento (“Graphene Nanocomposites”, n. S116/2012- 242637 and delib. reg. n. 2266). The authors thank MINECO for the partial financial support of this work (project MAT2013-48107-C3). Dr. Manoj Tripathi (Center for Materials and Microsystems, Fondazione Bruno Kessler, Trento e Italy) is gratefully acknowledged for Raman measurements.