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The substantial deformation exhibited by hyperelastic cylindrical shells under pressurization makes them an ideal platform for programmable inflatable structures. If negative pressure is applied, the cylindrical shell will buckle, leading to a sequence of rich deformation modes, all of which are fully recoverable due to the hyperelastic material choice. While the initial buckling event under vacuum is well understood, here, the post-buckling regime is explored and a region in the design space is identified in which a coupled twisting-contraction deformation mode occurs; by carefully controlling the geometry of our homogeneous shells, the proportion of contraction versus twist can be controlled. Additionally, bending as a post-buckling deformation mode can be unlocked by varying the thickness of our shells across the circumference. Since these soft shells can fully recover from substantial deformations caused by buckling, then these instability-driven deformations are harnessed to build soft machines capable of a programmable sequence of movements with a single actuation input.

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Inflatable robots are becoming increasingly popular, especially in applications where safe interactions are a priority. However, designing multifunctional robots that can operate with a single pressure input is challenging. A potential solution is to couple inflatables with passive valves that can harness the flow characteristics to create functionality. In this study, simple, easy to fabricate, lightweight, and inexpensive mechanical valves are presented that harness viscous flow and snapping arch principles. The mechanical valves can be fully integrated on-board, enabling the control of the incoming airflow to realize multifunctional robots that operate with a single pressure input, with no need for electronic components, cables, or wires. By means of three robotic demos and guided by a numerical model, the capabilities of the valves are demonstrated and optimal input profiles are identified to achieve prescribed functionalities. The study enriches the array of available mechanical valves for inflatable robots and enables new strategies to realize multifunctional robots with on-board flow control.

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Kirigami, the Japanese art of paper cutting, has recently enabled the design of stretchable mechanical metamaterials that can be easily realized by embedding arrays of periodic cuts into an elastic sheet. Here, kirigami principles are exploited to design inflatables that can mimic target shapes upon pressurization. The system comprises a kirigami sheet embedded into an unstructured elastomeric membrane. First, it is shown that the inflated shape can be controlled by tuning the geometric parameters of the kirigami pattern. Then, by applying a simple optimization algorithm, the best parameters that enable the kirigami inflatables to transform into a family of target shapes at a given pressure are identified. Furthermore, thanks to the tessellated nature of the kirigami, it is shown that we can selectively manipulate the parameters of the single units to allow the reproduction of features at different scales and ultimately enable a more accurate mimicking of the target.

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People with normal hearing thresholds can nonetheless have difficulty with understanding speech in noisy backgrounds. The origins of such supra-threshold hearing deficits remain largely unclear. Previously we showed that the auditory brainstem response to running speech is modulated by selective attention, evidencing a subcortical mechanism that contributes to speech-in-noise comprehension. We observed, however, significant variation in the magnitude of the brainstem's attentional modulation between the different volunteers. Here we show that this variability relates to the ability of the subjects to understand speech in background noise. In particular, we assessed 43 young human volunteers with normal hearing thresholds for their speech-in-noise comprehension. We also recorded their auditory brainstem responses to running speech when selectively attending to one of two competing voices. To control for potential peripheral hearing deficits, and in particular for cochlear synaptopathy, we further assessed noise exposure, the temporal sensitivity threshold, the middle-ear muscle reflex, and the auditory-brainstem response to clicks in various levels of background noise. These tests did not show evidence for cochlear synaptopathy amongst the volunteers. Furthermore, we found that only the attentional modulation of the brainstem response to speech was significantly related to speech-in-noise comprehension. Our results therefore evidence an impact of top-down modulation of brainstem activity on the variability in speech-in-noise comprehension amongst the subjects.

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Humans are highly skilled at analysing complex acoustic scenes. The segregation of different acoustic streams and the formation of corresponding neural representations is mostly attributed to the auditory cortex. Decoding of selective attention from neuroimaging has therefore focussed on cortical responses to sound. However, the auditory brainstem response to speech is modulated by selective attention as well, as recently shown through measuring the brainstem's response to running speech. Although the response of the auditory brainstem has a smaller magnitude than that of the auditory cortex, it occurs at much higher frequencies and therefore has a higher information rate. Here we develop statistical models for extracting the brainstem response from multi-channel scalp recordings and for analysing the attentional modulation according to the focus of attention. We demonstrate that the attentional modulation of the brainstem response to speech can be employed to decode the attentional focus of a listener from short measurements of 10 s or less in duration. The decoding remains accurate when obtained from three EEG channels only. We further show how out-of-the-box decoding that employs subject-independent models, as well as decoding that is independent of the specific attended speaker is capable of achieving similar accuracy. These results open up new avenues for investigating the neural mechanisms for selective attention in the brainstem and for developing efficient auditory brain-computer interfaces.

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Conventional 3D bioprinting allows fabrication of 3D scaffolds for biomedical applications. In this contribution we present a cryogenic 3D printing method able to produce stable 3D structures by utilising the liquid to solid phase change of a composite hydrogel (CH) ink. This is achieved by rapidly cooling the ink solution below its freezing point using solid carbon dioxide (CO2) in an isopropanol bath. The setup was able to successfully create 3D complex geometrical structures, with an average compressive stiffness of O(1) kPa (0.49 ± 0.04 kPa stress at 30% compressive strain) and therefore mimics the mechanical properties of the softest tissues found in the human body (e.g. brain and lung). The method was further validated by showing that the 3D printed material was well matched to the cast-moulded equivalent in terms of mechanical properties and microstructure. A preliminary biological evaluation on the 3D printed material, coated with collagen type I, poly-L-lysine and gelatine, was performed by seeding human dermal fibroblasts. Cells showed good attachment and viability on the collagen-coated 3D printed CH. This greatly widens the range of applications for the cryogenically 3D printed CH structures, from soft tissue phantoms for surgical training and simulations to mechanobiology and tissue engineering.

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Humans excel at selectively listening to a target speaker in background noise such as competing voices. While the encoding of speech in the auditory cortex is modulated by selective attention, it remains debated whether such modulation occurs already in subcortical auditory structures. Investigating the contribution of the human brainstem to attention has, in particular, been hindered by the tiny amplitude of the brainstem response. Its measurement normally requires a large number of repetitions of the same short sound stimuli, which may lead to a loss of attention and to neural adaptation. Here we develop a mathematical method to measure the auditory brainstem response to running speech, an acoustic stimulus that does not repeat and that has a high ecological validity. We employ this method to assess the brainstem's activity when a subject listens to one of two competing speakers, and show that the brainstem response is consistently modulated by attention.

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