Octopus-Inspired Suction Cups with Embedded Strain Sensors for Object Recognition

The octopus has unique capacities are sources of inspiration in developing soft robotic-enabling technologies. Herein, soft, sensorized, suction cups inspired by the suckers of Octopus vulgaris are presented. The suction cups using direct casting are fabricated, so that materials with different mechanical properties can be combined to optimize sensing and grasping capabilities. The artificial suckers integrate four embedded strain sensors, individually characterized and placed in a 90 degrees configuration along the rim of the suction cup. Based on this arrangement, how well the sensory suction cup can detect 1) the direction and 2) the angle (from 30 degrees to 90 degrees) of a touched inclined surface and 3) the stiffness of a touched flat object (shore hardness between 0010 and D50) both in air and underwater is evaluated. Data processing on neural networks is based using a multilayer perceptron to perform regression on individual properties. The results show a mean absolute error of 0.98 for angles, 0.02 for directions, and 97.9% and 93.5% of accuracy for the material classification in air and underwater, respectively. In view of the results and scalability in manufacturing, the proposed artificial suckers would seem to be highly effective solutions for soft robotics, including blind exploration and object recognition

Multisource energy conversion in plants with soft epicuticular coatings

Living plants have recently been exploited for unusual tasks such as energy conversion and environmental sensing. Yet, using plants as small-scale autonomous energy sources is often impeded by multicable and -electrode installations on the plants. Moreover, insufficient power outputs for steadily driving even low-power electronics made a realization challenging. Here, we show that plants, by a modification of the leaf epicuticular region can be transformed into cable-free, fully plant-enabled integrated devices for multisource energy conversion. In detail, leaf contact electrification caused by wind-induced inter-leaf tangency is magnified by a transparent elastomeric coating on one of two interacting leaves. This enables converting wind energy into harvestable electricity. Further, the same plant is used as an unmatched Marconi-antenna for multi-band radio frequency (RF) energy conversion. This enables the use of the same plant as a complementary multi-energy system with augmented power output if both sources are used simultaneously. In combination, we observed over 1000% enhanced energy accumulation respective to single source harvesting in the specific application case and common plants like ivy could power a commercial sensing platform wirelessly transmitting environmental data. This shows that living plants have potential to autonomously supply application-oriented electronics while maintaining the positive environmental impact by their intrinsic sustainability and benefits such as O-2 production, CO2 fixation, self-repair, and many more

An earthworm-like modular soft robot for locomotion in multi-terrain environments

Robotic locomotion in subterranean environments is still unsolved, and it requires innovative designs and strategies to overcome the challenges of burrowing and moving in unstructured conditions with high pressure and friction at depths of a few centimeters. Inspired by antagonistic muscle contractions and constant volume coelomic chambers observed in earthworms, we designed and developed a modular soft robot based on a peristaltic soft actuator (PSA). The PSA demonstrates two active configurations from a neutral state by switching the input source between positive and negative pressure. PSA generates a longitudinal force for axial penetration and a radial force for anchorage, through bidirectional deformation of the central bellows-like structure, which demonstrates its versatility and ease of control. The performance of PSA depends on the amount and type of fluid confined in an elastomer chamber, generating different forces and displacements. The assembled robot with five PSA modules enabled to perform peristaltic locomotion in different media. The role of friction was also investigated during experimental locomotion tests by attaching passive scales like earthworm setae to the ventral side of the robot. This study proposes a new method for developing a peristaltic earthworm-like soft robot and provides a better understanding of locomotion in different environments

Ultrahigh finesse Fabry-Perot superconducting resonator

We have built a microwave Fabry-Perot resonator made of diamond-machined copper mirrors coated with superconducting niobium. Its damping time (Tc = 130 ms at 51 GHz and 0.8 K) corresponds to a finesse of 4.6 x 109, the highest ever reached for a Fabry-Perot in any frequency range. This result opens novel perspectives for quantum information, decoherence and non-locality studies

Prevalence and socio-demographic predictors of food insecurity in Australia during the COVID-19 pandemic

The COVID-19 pandemic has exacerbated economic vulnerabilities and disrupted theAustralian food supply, with potential implications for food insecurity. This study aims to describe theprevalence and socio-demographic associations of food insecurity in Tasmania, Australia, during theCOVID-19 pandemic. A cross-sectional survey (deployed late May to early June 2020) incorporatedthe U.S. Household Food Security Survey Module: Six-Item Short Form, and fifteen demographicand COVID-related income questions. Survey data (n = 1170) were analyzed using univariate andmultivariate binary logistic regression. The prevalence of food insecurity was 26%. The adjusted oddsof food insecurity were higher among respondents with a disability, from a rural area, and living withdependents. Increasing age, a university education, and income above $80,000/year were protectiveagainst food insecurity. Food insecurity more than doubled with a loss of household income above25% (Adjusted Odds Ratio (AOR): 2.02; 95% CI: 1.11, 3.71; p = 0.022), and the odds further increasedwith loss of income above 75% (AOR: 7.14; 95% CI: 2.01, 24.83; p = 0.002). Our results suggest thatthe prevalence of food insecurity may have increased during the COVID-19 pandemic, particularlyamong economically vulnerable households and people who lost income. Policies that supportdisadvantaged households and ensure adequate employment opportunities are important to supportAustralians throughout and post the COVID-19 pandemic

Iterative simulations to estimate the elastic properties from a series of MRI images followed by MRI-US validation

The modeling of breast deformations is of interest in medical applications such as image-guided biopsy, or image registration for diagnostic purposes. In order to have such information, it is needed to extract the mechanical properties of the tissues. In this work, we propose an iterative technique based on finite element analysis that estimates the elastic modulus of realistic breast phantoms, starting from MRI images acquired in different positions (prone and supine), when deformed only by the gravity force. We validated the method using both a single-modality evaluation in which we simulated the effect of the gravity force to generate four different configurations (prone, supine, lateral, and vertical) and a multi-modality evaluation in which we simulated a series of changes in orientation (prone to supine). Validation is performed, respectively, on surface points and lesions using as ground-truth data from MRI images, and on target lesions inside the breast phantom compared with the actual target segmented from the US image. The use of pre-operative images is limited at the moment to diagnostic purposes. By using our method we can compute patient-specific mechanical properties that allow compensating deformations