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Many studies on acoustic radiation forces, especially those applied to acoustic levitation, focus on characterizing the behaviour of acoustic fields. However, the dynamic response of the levitated objects, particularly those larger than the wavelength limit, remains relatively underexplored. Here, we look to bridge this gap by deriving nonlinear equations of motion for a spherical object trapped under acoustic radiation forces while subject to external excitation. For such a contemporary scenario, the otherwise elemental Gorkov formulation fails to provide accurate results. Using Sparse Identification of Nonlinear Dynamical Systems (SINDy), first, we derive the corresponding nonlinear equation of motion from analytical time series data obtained through the Gorkov formulation and external excitation for acoustically small objects. This approach recovers the governing equation with less than 0.05% error in coefficient values when compared to the analytical solution. Second, we conduct experiments with the TinyLev levitator with external excitation applied via an external actuator to generate the required time series for an acoustically large object. SINDy is applied to reconstruct governing equations from experimental data, allowing for the study of how excitation amplitude affects acoustically large objects. All obtained coefficients change with excitation amplitude, and the coefficients in the dynamic equation of motion should not be treated as constants. Strong velocity-dependent terms emerged, indicating a complex relationship between viscosity and object response, which classical models do not predict. The bifurcation diagram obtained using the SINDy-derived equation of motion shows closer agreement with that obtained experimentally. These results demonstrate that SINDy can recover equations consistent with Gorkov’s formulation and extend beyond it, providing a pathway to derive analytical expressions directly from data for levitating and manipulating objects beyond the Rayleigh limit.

Acoustic metamaterials are structures with exotic acoustic properties, with promising applications in acoustic beam steering, focusing, impedance matching, absorption and isolation. Recent work has shown that the efficiency of many acoustic metamaterials can be enhanced by controlling an additional parameter known as Willis coupling, which is analogous to bianisotropy in electromagnetic metamaterials. The magnitude of Willis coupling in a passive acoustic meta-atom has been shown theoretically to have an upper limit, however the feasibility of reaching this limit has not been experimentally investigated. Here we introduce a meta-atom with Willis coupling which closely approaches this theoretical limit, that is much simpler and less prone to thermo-viscous losses than previously reported structures. We perform two-dimensional experiments to measure the strong Willis coupling, supported by numerical calculations. Our meta-atom geometry is readily modeled analytically, enabling the strength of Willis coupling and its peak frequency to be easily controlled. Willis coupling is an additional degree of freedom, which can enhance acoustic metamaterials, by coupling monopole and dipole excitations. Here, the authors experimentally demonstrate a meta-atom with Willis coupling approaching the theoretical maximum, which is robust to thermo-viscous losses.

Laser Doppler vibrometers (LDVs) have been widely adopted due to their large number of benefits in comparison to traditional contacting vibration transducers. Their high sensitivity, among other unique characteristics, has also led to their use as optical microphones, where the measurement of object vibration in the vicinity of a sound source can act as a microphone. Recent work enabling full correction of LDV measurement in the presence of sensor head vibration unlocks new potential applications, including integration within autonomous vehicles (AVs). In this paper, the common AV challenge of object classification is addressed by presenting and evaluating a novel, non-contact vibro-acoustic object recognition technique. This technique utilises a custom set-up involving a synchronised loudspeaker and scanning LDV to simultaneously remotely solicit and record responses to a periodic chirp excitation in various objects. The 864 recorded signals per object were pre-processed into spectrograms of various forms, which were used to train a ResNet-18 neural network via transfer learning to accurately recognise the objects based only on their vibro-acoustic characteristics. A five-fold cross-validation optimisation approach is described, through which the effects of data set size and pre-processing type on classification accuracy are assessed. A further assessment of the ability of the CNN to classify never-before-seen objects belonging to groups of similar objects on which it has been trained is then described. In both scenarios, the CNN was able to obtain excellent classification accuracy of over 99.7%. The work described here demonstrates the significant promise of such an approach as a viable non-contact object recognition technique suitable for various machine automation tasks, for example, defect detection in production lines or even loose rock identification in underground mines.

Quasi-bound states in the continuum (QBICs) coupling into the propagating spectrum manifest themselves as high-quality factor (Q) modes susceptible to perturbations. This poses a challenge in predicting stable Fano resonances for realistic applications. Besides, where and when the maximum field enhancement occurs in real acoustic devices remains elusive. In this work, we theoretically predict and experimentally demonstrate the existence of a Friedrich-Wintgen BIC in an open acoustic cavity. We provide direct evidence for a QBIC by mapping the pressure field inside the cavity using a Laser Doppler Vibrometer (LDV), which provides the missing field enhancement data. Furthermore, we design a symmetry-reduced BIC and achieve field enhancement by a factor of about three compared to the original cavity. LDV measurements are a promising technique for obtaining high-Q modes’ missing field enhancement data. The presented results facilitate the future applications of BICs in acoustics as high-intensity sound sources, filters, and sensors. The authors demonstrate that laser Doppler vibrometer measurements are a powerful tool for predicting the maximum pressure enhancement of high-Q modes. The results presented enable future applications of acoustic BICs by filling the missing data gap on field enhancement.

Sustainable and affordable energy is one of the most critical issues facing society. Noise is ubiquitous, albeit with a low energy density, making it an almost perfect energy source. Bound states in the continuum overcome this problem through a highly localized energy increase. Here, we present theoretical, numerical, and experimental studies on bound state acoustic harvesters. Under white noise excitation, the bound state harvester outperforms the conventional Helmholtz resonator harvester by a factor of 2.2 in terms of amplitude spectral density of the output voltage and by a factor of 10 in terms of output power. A super-bound state is formed by using pressure coupling in a pseudo-free field environment, further increasing the energy enhancement. This results in a 50-fold increase in output voltage compared to a single bound state harvester. Our findings advance the state-of-the-art in sustainable energy harvesting for low-power devices. The authors present a super-bound state acoustic harvester that outperforms state-of-the-art acoustic energy harvesting systems.

Background Acquiring medical knowledge is a key competency for medical students and a lifelong requirement for physicians. Learning techniques can improve academic success and help students cope with stressors. To support students’ learning process medical faculties should know about learning techniques. The purpose of this study is to analyse the preferred learning techniques of female and male as well as junior and senior medical students and how these learning techniques are related to perceived learning difficulties. Methods In 2019, we conducted an online survey with students of the undergraduate, competency-based curriculum of medicine at Charité – Universitätsmedizin Berlin. We chose ten learning techniques of high, moderate and low utility according to Dunlosky et al. (2013) and we asked medical students to rate their preferred usage of those techniques using a 5-point Likert scale. We applied t-tests to show differences in usage between female and male as well as junior and senior learners. Additionally, we conducted a multiple regression analysis to explore the predictive power of learning techniques regarding perceived difficulties. Results A total of 730 medical students (488 women, 242 men, M age  = 24.85, SD = 4.49) use three techniques the most: ‘highlighting’ (low utility), ‘self-explanation’ (moderate utility) and ‘practice testing’ (high utility). Female students showed a significantly higher usage of low-utility learning techniques (t(404.24) = -7.13, p  < .001) and a higher usage of high-utility learning techniques (t(728) = -2.50, p  < .05) than male students (M = 3.55, SD = .95). Compared to junior students (second to sixth semester; M = 3.65, SD = .71), senior students (seventh semester to final clerkship year; M = 3.52, SD = .73) showed a lower use of low-utility learning techniques (t(603) = 2.15, p  < .05). Usage of low-utility techniques is related to more difficulties (β = .08, t(724) = 2.13, p  < .05). Usage of moderate-utility techniques is related to less learning difficulties (β = -.13, t(599) = -3.21, p  < .01). Conclusions Students use a wide range of low-, moderate- and high-utility learning techniques. The use of learning techniques has an influence on the difficulties perceived by students. Therefore, they could benefit from knowing about and using high-utility learning techniques to facilitate their learning. Faculties should inform their students about effective learning and introduce them to useful learning techniques.

Silk from silkworms and spiders is an exceptionally important natural material, inspiring a range of new products and applications due to its high strength, elasticity, and toughness at low density, as well as its unique conductive and optical properties. Transgenic and recombinant technologies offer great promise for the scaled-up production of new silkworm- and spider-silk-inspired fibres. However, despite considerable effort, producing an artificial silk that recaptures the physico-chemical properties of naturally spun silk has thus far proven elusive. The mechanical, biochemical, and other properties of pre-and post-development fibres accordingly should be determined across scales and structural hierarchies whenever feasible. We have herein reviewed and made recommendations on some of those practices for measuring the bulk fibre properties; skin-core structures; and the primary, secondary, and tertiary structures of silk proteins and the properties of dopes and their proteins. We thereupon examine emerging methodologies and make assessments on how they might be utilized to realize the goal of developing high quality bio-inspired fibres.

Background The qualities of trainees play a key role in entrustment decisions by clinical supervisors for the assignments of professional tasks and levels of supervision. A recent body of qualitative research has shown that in addition to knowledge and skills, a number of personality traits are relevant in the workplace; however, the relevance of these traits has not been investigated empirically. The aim of this study was to analyse the workplace performance of final-year medical students using an Entrustable Professional Activity (EPA) framework in relation to their personality traits. Methods Medical students at the end of their final clerkship year were invited to participate in an online survey-based, cross-sectional field study. In the survey, the workplace performance was captured using a framework consisting of levels of experienced supervision and a defined set of 12 end-of-undergraduate medical training EPAs. The Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism, and openness) of the participating medical students were measured using the Big Five Inventory-SOEP (BFI-S), which consists of 15 items that are rated on a seven-point Likert scale. The data were analysed using descriptive and inferential statistics. Results The study included 880 final-year medical students (mean age: 27.2 years, SD = 3.0; 65% female). The levels of supervision under which the final-year clerkship students carried out the EPAs varied considerably. Significant correlations were found between the levels of experienced supervision and all Big Five dimensions The correlations with the dimensions of extraversion, agreeableness, conscientiousness and openness were positive, and that for the neuroticism dimension was negative (range r  = 0.17 to r  = − 0.23). Multiple regression analyses showed that the combination of the Big Five personality traits accounted for 0.8–7.5% of the variance in supervision levels on individual EPAs. Conclusions Using the BFI-S, we found that the levels of supervision on a set of end-of-undergraduate medical training EPAs were related to the personality traits of final-year medical students. The results of this study confirm the existing body of research on the role of conscientiousness and extraversion in entrustment decision-making and, in particular, add the personality trait of neuroticism as a new and relevant trainee quality to be considered.

A decision model is developed by adopting two control techniques, combining cultural methods and pesticides in a hybrid approach. To control the adverse effects in the long term and to be able to evaluate the extensive use of pesticides on the environment and nearby ecosystems, the novel decision model assumes the use of pesticides only in an emergency situation. We, therefore, formulate a rice-pest-control model by rigorously modelling a rice-pest system and including the decision model and control techniques. The model is then extended to become an optimal control system with an objective function that minimizes the annual losses of rice by controlling insect pest infestations and simultaneously reduce the adverse impacts of pesticides on the environment and nearby ecosystems. This rice-pest-control model is verified by analysis, obtains the necessary conditions for optimality, and confirms our main results numerically. The rice-pest system is verified by stability analysis at equilibrium points and shows transcritical bifurcations indicative of acceptable thresholds for insect pests to demonstrate the pest control strategy.

Eusocial insects like termites and ants use diverse communication methods, including pheromones, sound, and vibrations. Termites, blind and with fewer glands, rely heavily on vibrations for foraging, communication, and predator avoidance. Their appendages detect subtle signals amid noise, though the underlying physiological mechanisms remain largely unknown and understudied. We explore the role of termite legs and antennae as sensory probes. These appendages receive the vibration signals, which are detected by the leg's subgenual organ and the Johnston's organ in the antenna, and which in turn convert these mechanical environmental signals into nerve impulses sent to the nervous system. We compare these appendages in termites and ants, two eusocial, subterranean insect groups that share ecological traits but differ in trophic roles, with ants being major predators of termites. Termite legs and antennae have lower slenderness ratios (legs: 19–35 vs. 48; antennae: 23–32 vs. 61). Wasps and bees fall in between. Assuming similar material properties, termite legs likely have lower stiffness and higher natural frequencies, enhancing vibration sensitivity. The subgenual organ's position near the head may further improve detection. These morphological traits suggest termites could be better adapted for sensing a broader range of vibrations than ants. However, more specimens and species of Isoptera and Formica need to be tested to validate this claim fully. Comparing the legs of termites with ants, we found that termite tibiae amplify lower‐frequency vibrations (~0–2.25 kHz), while ants show an amplification at higher frequencies (1.9–3.1 kHz). This suggests the vibrational sensitivity of termites is better adapted to wood‐borne signals, which corresponds to their food, whereas ants, as generalist foragers, are tuned for diverse terrains, including light structures, such as twigs, leaves, and other plant matter. Considered together, our findings suggest that termite legs may function as an integrated auditory complex. This study investigates how termites use their legs and antennae as vibration‐sensitive sensory organs, comparing them to ants, their eusocial predators. Termite appendages are morphologically adapted to detect lower‐frequency, wood‐borne vibrations, enhancing their foraging and predator avoidance abilities. These findings suggest that termite legs may function as an integrated auditory system, finely tuned to their ecological niche.