Bioinspiration & Biomimetics

Large commercial and military aircraft can operate in a wide range of turbulent conditions, except during extreme weather events such as cyclones. Smaller man-made vehicles, such as micro aerial vehicles (MAVs) and nano aerial vehicles (NAVs), are significantly more sensitive to routine environmental wind fluctuations, making them difficult to control. In contrast, insects exhibit remarkable stability in naturally gusty conditions. Despite this, few studies have systematically investigated the impact of gusts and turbulence on insect flight performance. To address this gap and to gain fundamental insights into insect flight stability under gusty conditions, we examined the flight of freely flying black soldier flies subjected to a discrete head-on aerodynamic gust in a controlled laboratory environment. Flight motions were recorded using two high-speed cameras, and body and wing kinematics were analyzed across 14 distinct cases. In response to the gust, we observed consistent features across the cases: (1) asymmetry in wing stroke amplitude, (2) large changes in body roll angle--up to 160{degrees}--occurring over approximately two wing beats ([~]20 ms) with recovery over [~]9 wing beats, (3) transient pitch-down attitude, and (4) deceleration in the flight direction. These rapid responses, combining passive and active control mechanisms, provide insight into the flight control strategies employed by insects. The findings offer valuable guidance for the design of MAVs and NAVs capable of robustly responding to gusts and unsteady airflow in natural environments.

Despite its ubiquity in natural flows, the effects of turbulence on fish locomotion and behavior remain poorly understood. The prevailing hypothesis is that these effects depend on the spatial and temporal scales of the turbulence relative to the fishs size and swimming speed. But in conventional facilities, turbulence usually increases with mean flow, which forces higher swimming speeds and can leave these relative scales unchanged. We therefore present a novel experimental facility that leverages a jet array to decouple the turbulence from the mean flow and systematically control its scales. This approach allows the ratio of turbulent to fish inertial scales to be varied over an order of magnitude, providing a controlled framework for quantifying fish-turbulence interactions. The facility also supports experiments probing strategies fish may use to cope with turbulence, including collective behaviors. Insights from this work have broader implications for ecological studies and engineering applications, including the design of effective fishways and bio-inspired underwater vehicles.

Body orientation is a key variable in the analysis of insect flight behavior, yet it remains difficult to measure across the full extent of a trajectory in most experimental settings. Although modern tracking systems reliably capture the position and velocity of the center of mass, resolving body yaw orientation typically requires dedicated hardware confined to a small, purpose-built volume, and is impractical for large-scale or long-duration studies. Here, we develop a data-driven estimator that predicts body yaw orientation directly from translational flight trajectory data. We trained a fully connected feed-forward artificial neural network (ANN) on a dataset in which both flight trajectory and body orientation were recorded simultaneously in freely flying Drosophila, using a time-delay embedding of ground velocity, air velocity, and inferred thrust vectors as input features. To improve generalization across arbitrary coordinate frames, we augmented the training data with random rotational transformations. Evaluated on a withheld test set of 3,313 trajectories (101,576 frames), the rotation-augmented model achieved a median mean absolute angular error of 10.51{degrees}, with accurate heading recovery across the full [-{pi}, {pi}) range. The estimator provides a practical tool for recovering body orientation information from existing trajectory datasets in which only center- of-mass motion was recorded, extending the behavioral and computational analysis of insect navigation to previously inaccessible data.

Head rotation is the leading cause of diffuse brain injuries from cycling accidents, with severe, long-term or even fatal consequences. Here, we present a novel helmet safety technology, the Release Layer System (RLS), designed to enhance conventional helmets and reduce the likelihood of such injuries. RLS is located on the outer side of the helmet and thus gets impacted first. The force of the impact activates a rolling mechanism triggering the release of an outer polycarbonate panel, thereby dispersing and transforming a substantial portion of the incident rotational energy. To evaluate the effectiveness of the technology, we conducted oblique impact tests on three popular helmet types, in conventional and RLS-equipped configurations, at three impact locations. RLS-equipped helmets reduced Peak Angular Velocity (PAV) by 57-66%, averaged across impact locations, compared to their conventional counterparts. This corresponds to a 68-86% reduction in the probability of an AIS2+ brain injury, as estimated by the Brain Injury Criterion. The most notable improvement was observed at the pYrot location (front impacts, mid-sagittal plane), with up to 85% PAV reduction. Testing across headforms further demonstrated the effectiveness of the technology in mitigating head rotation irrespective of variations in evaluation setups. This work introduces a novel mechanism for rotational impact mitigation and provides evidence of its potential benefits compared with conventional helmets. As an outer-layer approach, RLS may offer an alternative pathway for managing rotational kinematics in future helmet designs.

A passive device that attaches to the feet, called an exotendon, can reduce the energetic cost of running at moderate speeds, but its efficacy and optimal design parameters at higher speeds are unknown. Identifying optimal parameters at new speeds experimentally would require many experimental trials with different exotendon designs, which is challenging for participants at higher running speeds. We developed a muscle-driven simulation framework to predict the effect of various exotendon designs on the energetic cost of running at an experimentally untested speed (4 m/s). We used these predictions to select four designs, which we evaluated experimentally as users ran at this speed. The framework correctly predicted that an exotendon that reduced energetic cost at 2.7 m/s would also reduce energetic cost at 4 m/s (10% predicted vs. 5.7% measured) and that a short, stiff exotendon and a long, compliant exotendon would not significantly reduce energetic cost. However, exotendon parameters predicted by the simulation to maximize energetic savings did not significantly reduce energetic cost when evaluated experimentally. There was variability between participants in both the magnitude of maximum energy savings and the exotendon condition associated with those savings. In a 5-km time trial performed with and without the exotendon condition that elicited the largest energy savings for each participant during the experiment, we observed a lower average heart rate (-3.9 {+/-} 3.8 beats/min; P=0.03; mean {+/-} standard deviation) and increased cadence (15.9 {+/-} 9.6 steps/min; P=0.002) when participants ran with the exotendon but did not observe a statistically significant difference in finishing time (-13.5 {+/-} 24.6 sec; P=0.3). These results demonstrate exotendons can reduce energetic cost across multiple running speeds and that predictive simulations provide a framework for guiding experiments to evaluate assistive device designs. Author summaryDesigning assistive devices that help people move more efficiently usually requires many experimental trials. These studies can be time-consuming and physically demanding, especially when testing multiple device designs. In this study, we explored whether computer simulations could help guide the design of an assistive device for running called an exotendon. The exotendon is a simple elastic band that connects the feet and can help runners use less energy. Previous experiments showed that the device reduces the energy needed to run at moderate speeds, but it was unclear whether it would also work at faster speeds or which design would lead to energetic savings. We first used simulations of human running to test many possible exotendon designs at a faster speed. These simulations allowed us to identify promising designs before conducting experiments. We then tested a small number of these designs with runners. The experiments confirmed that the exotendon can reduce the energy required to run at faster speeds, although the efficacy of different designs varied between individuals. Our results show that computer simulations can help researchers rapidly evaluate a variety of assistive device ideas and focus experimental testing on the most promising designs.

Understanding how fish navigate complex natural environments requires bridging fine-scale biomechanics with ecological behavior. We investigated the volitional movement and energetics of wild red drum (Sciaenops ocellatus) across laboratory, mesocosm, and field settings. Using flow-respirometry, we quantified metabolic costs and swimming kinematics under ecologically relevant flow conditions shaped by bluff bodies mimicking mangrove roots and oyster mounds. Fish swimming in turbulent wakes exhibited reduced oxygen consumption and altered tailbeat dynamics, especially at high flow speeds. In a large outdoor mesocosm, dual accelerometers revealed a rich behavioral repertoire, including maneuvering and rest, which is not easily observable in confined lab settings. Spectral analysis and clustering identified eight distinct locomotory states, highlighting the limitations of summed acceleration metrics. Field telemetry tracked wild red drum across a 54 km estuarine corridor for a three-year period through an array of 36 acoustic receivers, revealing movement patterns shaped by tidal flow and physical habitats. Hydrodynamic modeling revealed that while laboratory trials demonstrated substantial energetic savings at high flows (approaching 100 cm/s), wild fish were detected predominantly in low-velocity microhabitats (<30 cm/s) near structurally complex features. This mismatch suggests that habitat selection is an adaptive strategy driven by ecological factors such as foraging opportunities, predation refuge, and site fidelity, rather than hydrodynamic efficiency alone. Our multi-scalar approach demonstrates that while flow-structure interactions can reduce locomotor costs for fish, habitat use in the wild reflects broader ecological constraints, offering a framework for integrating biomechanics, physiology, and ecology in conservation-relevant contexts.

Wearable devices for gravity balancing have high potential for impact across domains, including neuromotor rehabilitation and occupational systems. Devices made from compliant mechanisms, optimized to achieve specific compensation moments at target joints, have proven effective, but thus far have solely been optimized towards gravity compensation and not other wearability criteria. In this work, we propose a multi-objective optimization framework, based on particle swarm optimization, to design a soft, gravity balancing shoulder orthosis, while taking into account wearability constraints such as undesired loading directions and device size. Using this custom framework, we pursued multiple stages of orthosis design and optimization, selecting multiple solutions to be translated to real-world prototypes. These solutions were realized via 3D printing with thermoplastic polyurethane and evaluated for mechanical performance on benchtop and in-vivo. In-vivo testing on 6 healthy individuals demonstrated relative reductions in muscle activity for the anterior deltoid and upper trapezius, by 53 % and 71 % respectively when operating the orthosis for static tasks within functional shoulder ranges of motion. Changes in muscle activation were also were observed across other muscles, including the posterior deltoid, as well as in dynamic tasks at different speeds.

Optimizing assistive wearable devices is crucial for their efficacy and user adoption, yet state-of-the-art methods like Human-in-the-Loop Optimization (HILO) and biomechanical modeling face limitations. HILO is time-consuming and often restricted to optimizing control parameters, while inverse dynamics assumes invariant kinematics, which is unreliable for adaptive human-device interaction. Predictive simulation offers a powerful alternative, enabling computational exploration of design spaces. However, existing approaches often lack systematic optimization frameworks and rigorous validation against experimental data. To address this, we developed a Design Optimization Platform that integrates predictive simulations within a two-level optimization structure for personalizing assistive device design. This paper primarily validates the platforms predictive simulations against a publicly available dataset of the passive Biarticular Thigh Exosuit (BATEX), assessing its reliability. Our findings show that the model can sufficiently predict the kinematics and major muscle activations, except for the pelvis tilt and some biarticular muscles. The key finding is that successful identification of personalized optimal BATEX stiffness parameters needs acceptable prediction of metabolic cost trends, not their precise values. Our analysis further reveals that the models accuracy in predicting Vasti muscle activation in the baseline condition is a significant indicator of its success in predicting metabolic cost trends. This demonstrates that accurate prediction of performance trends is more important for effective simulation-based design optimization than perfect biomechanical accuracy, advancing targeted and efficient assistive device development.

Spectral similarity is often judged with a single metric such as RMSE, yet this can be misleading: physically different errors can produce similar scores. This is a critical limitation for computational biomechanics, where spectral agreement underpins both model validation and machine-learning loss design. Here, we develop a multi-metric framework for objective spectral biofidelity and test whether it better captures meaningful disagreement across complex frequency-domain responses. We evaluated 12 complementary similarity metrics, including CORA and ISO/TS 18571, using controlled spectral perturbations that mimic common real-world deviations such as resonance shifts, localized spikes, and broadband tilts. We then applied the framework to an SBI-tuned finite-element middle-ear model to assess convergence with training dataset size and robustness to measurement noise across repeated stochastic runs. No single metric performed reliably across all distortion types. Shape-based metrics tracked resonance morphology but could miss vertical scaling, whereas MaxError remained important for narrowband anomalies that smoother metrics underweighted. CORA and ISO 18571 did not consistently outperform simpler metrics. Rank aggregation using Borda count provided a robust consensus across metrics, enabling objective identification of training-data saturation and noise thresholds beyond which similarity rankings became unstable. These results show that spectral biofidelity cannot be reduced to a single norm. A multi-metric consensus provides a clearer and more physically meaningful basis for comparing experimental and simulated spectra, and offers a more defensible foundation for data-fidelity terms in physics-informed and simulation-based machine learning.

Muscular hydrostats, muscular structures with no rigid skeleton, are ubiquitous within the animal kingdom, from vertebrate tongues to cephalopod arms1,2, but how they perform complex actions remains poorly understood. One model hydrostat studied for its neural control3-7 and biomechanics8-17 is the feeding system (buccal mass) of the sea hare Aplysia (Fig. 1). The buccal mass (Fig. 1b) performs multiple feeding behaviors by coordinating intrinsic muscles to move a grasper (odontophore)18,19. In this paper, we investigated how mechanical reconfiguration from interacting shape-changing elements facilitates large odontophore protractions. During rejection behaviors, mechanical reconfiguration of the odontophore (elongating its shape to a higher aspect ratio) stretches a protractor muscle (I2), allowing I2 to generate stronger protractions12. In biting behaviors, the odontophore has a similar range of motion. However, during biting, the odontophore has a lower aspect ratio throughout protraction, meaning the I2 muscle alone is insufficient to reach observed protractions due to its length/tension property and reduced mechanical advantage9,10,12,18. By combining new analysis of MRI movies of Aplysia feeding12,18 (Fig. 1) with a new biomechanical model for biting and rejection (Fig. 2), we demonstrate two context-dependent mechanical reconfiguration mechanisms that explain the different ways large protractions are produced in biting and rejection (Fig. 3). The mechanisms integrate shape changes, bending and conforming of muscle structures, and shifts in contact interactions. We propose two mechanical subclasses of muscular hydrostats, "constrained" or "unconstrained" (Fig. 4), that may be morphologically similar but employ different control strategies depending on whether mechanical constraints are reliably present. O_FIG O_LINKSMALLFIG WIDTH=150 HEIGHT=200 SRC="FIGDIR/small/715937v1_fig1.gif" ALT="Figure 1"> View larger version (87K): org.highwire.dtl.DTLVardef@1c60cbeorg.highwire.dtl.DTLVardef@16ebd04org.highwire.dtl.DTLVardef@13b65d5org.highwire.dtl.DTLVardef@9aafb0_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1.C_FLOATNO Anatomy and kinematics of the Aplysia feeding system (a1) Adult Aplysia californica searching for food and (a2) feeding on Gracilaria macroalgae ((a1) photo credit: Dr. Jeffrey P. Gill, (a2) modified with permission from Bennington et al. 202514). Gray highlight shows the location of the feeding structure, the buccal mass (b). (b) An anatomical diagram of a midline sagittal view of a buccal mass. During feeding, the odontophore (the internal grasper of the buccal mass) protracts through the tubelike I3 muscle. In the midsagittal plane, the I3 is visible as two longitudinal elements, but is one continuous structure that runs circumferentially around the buccal mass. The inner wall of the distal I3 is shown in dark blue. The dashed white line shows the jaw line, which is used as the reference for both the translation and rotation measurements. (c) Configuration of the buccal mass (left: anatomical diagram; middle: MRI frames) showing (c1) peak retraction and (c2) peak protraction. (right) A diagram of the buccal mass was created to highlight key anatomical landmarks for each frame of the MRI video showing a complete biting sequence (d-e). The same diagrammatic representations of the landmarks are shown in (d) and (e) for the protraction and retraction portions of the biting sequence, respectively (See STAR Methods). The frames shown in (c1) and (c2) correspond to the 0 ms and 3410 ms frames, respectively, and are the same between the middle and right portions of the figure. Key frames referred to in the text: t0: start of the behavioral cycle, t1: peak rotation reached, t2: peak translation reached, t3: rotation plateau ended, t4: end of behavioral cycle. (f) Kinematic measurements were taken using the drawn diagrams for each frame in the sequence. See main text for definitions of variables. All scale bars correspond to 10 mm. C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/715937v1_fig2.gif" ALT="Figure 2"> View larger version (34K): org.highwire.dtl.DTLVardef@1848bb9org.highwire.dtl.DTLVardef@f126a4org.highwire.dtl.DTLVardef@1ffd5forg.highwire.dtl.DTLVardef@336910_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 2.C_FLOATNO Kinetic/Kinematic biomechanical model of the buccal mass (a) Rest geometry of the biomechanical model. The grasper (odontophore) is modeled as a rigid ellipse (magenta with yellow radula). It is connected to the I1/I3 lumen (blue trapezoid) by the hinge muscle (green). The I2 protractor muscle (red) wraps conformally around the odontophore and attaches at the lateral groove. The net force and torque from the I2 on the odontophore are found by performing an instantaneous force balance on a small arc of the ellipse and integrating across the full region of contact between the I2 and the odontophore. The hinge muscle is modeled as a linearly elastic, geometrically exact beam. At each position along the beams midline, a quasistatic force balance is performed (see STAR Methods). (b1) The tension in the I2 is modeled using the length-tension relationship reported in Yu et al. 1999 scaled by a normalized activation level. (b2) The axial and bending stiffness of the beam hinge were calibrated to ex vivo animal data reported in Sutton et al. 2004. Gray region indicates odontophore displacements observed during biting behaviors (Sutton et al. 2004). (c1-c2) To investigate the effects of mechanical reconfiguration on odontophore position at peak protraction, (c1) the aspect ratio of the odontophore ellipse and (c2) the stretch of the lateral groove were added as additional kinematic constraints. (c1) and (c2) show results from the model but do not correspond to any particular behavior or configuration observed in the animal. These constraints impact the biomechanical model via contact forces from the I1/I3 (see STAR Methods). The lateral groove stretch is converted to a depression angle of the dorsal I1/I3 muscle as a proxy for the wrapping of the dorsal I3 around the odontophore observed during in vivo feeding behaviors (Fig 1). (d-e) MRI frames at peak protraction in (d1, with and without overlay) biting (t2) and (e1, with and without overlay) rejection ({tau}2) compared to corresponding frames from the biomechanical model (d2 and e2, respectively). C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=184 SRC="FIGDIR/small/715937v1_fig3.gif" ALT="Figure 3"> View larger version (56K): org.highwire.dtl.DTLVardef@1369a90org.highwire.dtl.DTLVardef@1dda429org.highwire.dtl.DTLVardef@4485d5org.highwire.dtl.DTLVardef@ae6523_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 3.C_FLOATNO Mechanical reconfiguration of the buccal mass (a) Midsagittal kinematics of the buccal mass during a (left) biting and (right) rejection behavior (see also Figs. S1 and S2). Colored circles (diamonds) show data for an individual frame, and the black line shows the two-point moving average of the signal. Vertical dashed lines show concurrent time points in the different kinematic signals (biting: t0: cycle starts, t1: peak rotation, t2: peak translation, t3: rotation plateau ended, t4: cycle ends. Rejection: {tau}0: cycle starts, {tau}1: rotation plateau ends, {tau}2: peak translation, {tau}3: peak rotation, {tau}4: cycle ends). (b) Model configurations for nine different pairs of aspect ratios ({Phi}) and lateral groove stretches ({lambda}LG ) (numbers correspond to the labeled points in (Fig. S6c)). Note that these simulated results from the model do not necessarily correspond to configurations observed in the animal but rather show changes in the systems configuration due to changes in the kinematic parameters. All configurations here were achieved with an I2 activation of AI2 = 65%. (c-d) Sensitivity of the model translation and rotation at peak protraction to lateral groove shortening ({lambda}LG, top row) and aspect ratio change ({Phi}, bottom row) for biting (c) and rejection (d). The y-axis for all panels reports the difference between the model prediction and observed animal value at peak protraction (for translation or rotation) normalized by the range of motion (ROM) for each behavior. For each panel, one kinematic parameter is held fixed (top:{Phi} fixed; bottom:{lambda} LG fixed) at the value observed in the animal at peak protraction, and the other is varied to determine the effect of changing this parameter on the translation and rotation of the odontophore. Vertical dashed lines show the observed value of the varied parameter in the animal at peak protraction. The horizontal dashed line shows 0 difference for reference. The steepness of the difference curve in the vicinity of the vertical dashed line indicates how sensitive the system is to changes in each kinematic parameter near peak protraction. Here, a steeper curve (with a positive or negative slope) indicates greater sensitivity. For biting simulations, AI2 = 15%, and for rejection, AI2 = 90% based on the results of the model validation. Each curve in (c) and (d) is a 1D cross-section of the 2D contour plots shown in Figs. S6-S7. For a complete view of the sensitivity of translation and rotation to lateral groove stretch and aspect ratio across the kinematic configuration space at different I2 activations, see Figs. S6-S7. Note that (c) and (d) use different vertical scales. The smaller scale for the rejection plots was chosen to better show the difference curves for rejection, and it reflects the overall decreased sensitivity to both lateral groove stretch and aspect ratio changes for the rejection behaviors. C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/715937v1_fig4.gif" ALT="Figure 4"> View larger version (36K): org.highwire.dtl.DTLVardef@171f4c6org.highwire.dtl.DTLVardef@7d11a7org.highwire.dtl.DTLVardef@11206e3org.highwire.dtl.DTLVardef@82489c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 4.C_FLOATNO Mechanical reconfiguration facilitates behaviors in a variety of constrained hydrostat systems Combinations of the active shape change of internal structures (cyan), changes to the movement constraints and contact interaction (blue), and bending and conforming of structures (magenta) allow constrained hydrostats to mechanically reconfigure their neuromusculature (purple) to perform various behaviors. This can be seen in various systems across various species. As discussed here, the Aplysia buccal mass uses combinations of these mechanisms in (a) biting and (b) rejection behaviors to protract the buccal mass. (c) The pond snail, Lymnaea, has a morphologically similar buccal mass to Aplysia, but its I1/I3 homolog, the anterior jugalis, sits further posterior to the odontophore35, meaning it may more readily rely on the bending of the anterior jugalis and contact interactions during protraction. (d) The octopus and, more broadly, cephalopod buccal masses contain a beak that lacks a fixed articulation. Instead, by activating the lateral mandibular muscle (LMM), the buccal mass can create a stiff rotation point and may shift the function of the posterior mandibular muscle (PMM) from compressing the buccal mass to opening the beak36,37. (e) The human tongue (and other Type I tongues38) sits within the skull and makes use of contact with the hard palate to push food from the oral cavity into the pharynx27,48. (f) Additionally, by changing how the tongue interacts with the palate and teeth, while maintaining the same internal shape, humans can produce various vowel and consonant sounds39,49,50. This use of contact with the palate and teeth is known in the phonetics community as "bracing." Here, by creating a groove in the middle of the tongue, the phonemes /{varepsilon}/ and /ae/ can be produced. By raising the tongue and creating palatal contact while maintaining that groove, these vowels shift to the fricative consonants /s/ and /{theta}/49. Small insets show which of the mechanical configurations are used in each behavior. C_FIG

Movement is costly, and animals are under strong selective pressure to move efficiently, yet, in patchy, dynamic landscapes, decision-making is inherently uncertain. We quantify the energetic savings achieved by using up-to-date information presented within social cues for reducing movement costs. We use an agent-based model, founded on realistic aeronautical rules and parametrised on the Andean condor (Vultur gryphus), to study movement in patchy landscapes. By explicitly considering altitude, flight results in a sequence of soaring and gliding in the 3D space. We investigate how the cost of movement to an overall goal varies when birds use social information from others that are either fixed in space or moving collectively to the common goal, and under different risk-taking speed strategies, from slow and cautious to fast and risky. The value of social information is operationalised as energetic savings in units of basal metabolic rate. Under low predictability, agents with intermediate risk and high social-information use exhibit lowest movement costs, with up to 41% energy savings over asocial movement. By extending classical aeronautical theory to social and variable environments we demonstrate the adaptive value of social information for efficient movement in patchy, unpredictable landscapes.

In "Experiment-free exoskeleton assistance via learning in simulation", Luo et al. [1] present an ambitious framework for developing exoskeleton controllers through reinforcement learning exclusively in computer simulation. The authors report that a control policy trained on a small dataset from one subject was directly transferred to physical hardware, reducing human metabolic cost during walking, running, and stair climbing by more than any prior device. If confirmed, this would represent a major breakthrough for the field of wearable robotics and their clinical applications. However, a close examination of the published materials casts doubt on these claims. The reported experimental results violate physiological limits on the relationship between mechanical power and muscle energy use during gait2,3,4. The algorithmic claims are surprising and cannot be verified; in contrast with established replicability standards in machine learning5,6, executable code has not been made available. We conclude that the goals of this study have not yet been verifiably achieved and make recommendations for avoiding publication errors of this type in the future.

When honeybee colonies reproduce by fission, several thousand bees and their queen depart the parental nest and temporarily form a dense cluster on a tree branch or other surface while searching for a new nest site. Once the new nest site is selected, the swarm disassembles and flies toward it. How honeybees transition rapidly between dispersed flight and an aggregated cluster remains an open question. Here, we develop an experimental system and three-dimensional imaging pipeline to track individual flying bees together with the evolving morphology of the swarm during formation and dissolution. We report results from a representative swarming event. During assembly, swarms rapidly form low-density clusters before undergoing a slower contraction to a more dense steady state configuration. In contrast, disassembly occurs significantly faster than assembly and is characterized by strongly divergent flight, with bees departing the swarm in all directions. Overall, this method is able to demonstrate the coupled flight and morphological dynamics that underlie honeybee swarm assembly. Because the system is relatively low-cost and low-power, it is readily adaptable for three-dimensional imaging of other biological collectives in naturalistic environments.

Sentinel behaviour occurs when individuals use raised positions to scan for predators while the rest of the group forages. Here, we investigated whether a colonial cooperatively breeding species that forages in large groups, the sociable weaver, Philetairus socius, displays sentinel behaviour. This behaviour has been reported in species with similar ecology, behaviour and foraging habits, (e.g. ground foraging in open habitats where aerial predators are common) and, hence, we expected that it could occur in sociable weavers. On the other hand, sentinel behaviour appears to be less common in species that live in very large groups. We used an experimental set-up consisting of an artificial feeding station and perches to assess occurrence of sentinel related behaviours: (i) perching events > 30s on an elevated position, (ii) head-movements and (iii) alarm calling. Birds were seldom observed perching while others fed, and those that did, perched for periods that were too short to be considered as sentinel behaviour (less than 5s on average). Our results suggest that this behaviour is uncommon or even absent in sociable weavers. We discuss whether other factors such as foraging in very large groups, or interspecific foraging associations might make sentinel behaviour less important in this species.

Radar aeroecology is dedicated to making ecological inference about aerial wildlife from radar-derived information. While producing unique, large-scale datasets describing biological activity in the sky, radar methodologies are largely incapable of relating these to specific species and are thus taxonomically limited. I describe a computational method to increase taxonomic resolution in vertical looking radar data by dividing detected organisms into morphology and movement-based aerial morphotypes. Using the Birdscan MR1 radar target classifier, wing flapping frequency calculation and target size estimation, I demonstrate a nearly 8 fold increase in classification resolution of bird radar data from the Hula Valley Research station, Israel. Furthermore, by relating each species in the regions species pool to its relevant morphotype, I show that most of these newly separated classes are related to small numbers of species (1-10), providing realistic opurtunities to bridge the taxonomy gap in radar data. By using the morphotype approach, radar aeroecologists can start observing and discussing the concept of "Aerodiversity", analogues to widely used biodiversity, a fundamental measure in ecology and conservation sciences. By analitically adressing taxonomy in radar-aeroecology, practitioners will increase the impact and dissemintation of their work and contribute to a better, more complete understanding of the aerial habitat.

Clavicle fractures often exhibit markedly different clinical outcomes: some patients recover acceptable function despite shortening or displacement, whereas others with apparently similar deformity develop persistent pain, functional loss, or poor healing. To explain this distinction, we propose a minimal nonlinear mechanical model for prognostic analysis of clavicle fractures. The model describes the interaction between fracture-related shortening and compensatory shoulder-girdle posture through a reduced equilibrium equation incorporating stiffness, geometric nonlinearity, and shortening-posture coupling. Within this framework, we analyze equilibrium branches, local stability, and the emergence of critical thresholds. We show that post-fracture destabilization can be interpreted as a fold bifurcation, while more complex parameter dependence gives rise to cusp-type structures and multistability. These bifurcation mechanisms provide a mathematical explanation for sudden deterioration after injury or treatment, as well as for strong inter-individual variability. We further introduce an optimization principle based on a utility functional to guide treatment planning. The analysis predicts that the optimal safe correction should lie strictly below the bifurcation threshold, thereby generating a natural safety margin. Although the model is simplified and has not yet been calibrated against patient data, it nevertheless provides a theoretical framework for understanding why fracture prognosis may deteriorate abruptly near critical mechanical conditions and offers a dynamical-systems interpretation of empirical treatment thresholds used in clinical practice.

Animals must continually balance foraging with the risk of predation. In complex natural environments, this means quickly distinguishing between threats and harmless situations. We investigated how site-associated coral reef fishes decide to escape in response to visual cues mimicking predator attacks, using controlled underwater presentations of looming stimuli at varying speeds. We measured escape responses across species and social contexts, comparing them to predator attack speeds observed in the same habitat. Escape responses were highly sensitive to the speed of the looming stimulus, with no responses occurring at low speeds. The speeds triggering escape matched those of predator attacks, whereas cruising swim speeds never triggered a response. Species employed distinct antipredator strategies: Brown Chromis foraged away from shelter with high responsiveness, whereas Bicolor Damselfish remained shelter-dependent with lower escape propensities. Contrary to expectations, the social factors did not affect responses in this study. These findings demonstrate that reef fish are highly sensitive to the approach speed of objects, with species-specific strategies further shaping behaviors. By combining realistic visual threats with natural predator attack data, this study offers insight into how animals make escape decisions in complex, real-world environments.

Collective decision-making in animal groups is often studied using short, trial-based mazes experimental setups that restrict observations to isolated choice events. However, how leadership and decision dynamics unfold over extended periods in symmetric environments remains poorly understood. Here we introduce a novel cyclic three-room Y-shaped environment that enables continuous, and autonomous sequences of collective decisions without experimental reset. We tracked the positions and identities of 20 groups of five AB-strand zebrafish (Danio rerio) during one-hour sessions in which animals freely transitioned between three identical rooms connected by visually isolated identical corridors. We show that this symmetric Y-maze enables the collection of large amounts of data to study decision-making with a few replicates, because habituation occurs after 45 minutes of exploration. After an initial exploration phase, groups reached a stable behavioural regime, generating thousands of decision events per replicate. Collective dynamics were consistent across spatial contexts, indicating that the symmetric architecture does not bias movement patterns, as opposed to traditional mazes. We show that zebrafish leadership is typically shared among shoal members, with leaders often acting as decision-makers. By transforming a classical maze into a self-renewing decision system, this approach enables the study of long-term collective dynamics and spontaneous leadership in controlled yet ecologically relevant conditions. Author summarypresentation

Although predation is a major driver of group living across taxa and the antipredator benefits of grouping are well established, the energetic costs experienced by groups under predation remain largely unexplored. In the current study, we use wild, white mullet (Mugil curema, Valenciennes 1836), to provide the first real-time quantification of the energetic cost of escape in schooling fish using intermittent, closed-loop respirometry. We found that small groups exposed to predators showed a 53.8% increase in their organismal metabolic rate (MO2) as compared to groups without predator exposure. When we evaluated antipredator behaviors such as escape response, group cohesion, and displacement of the group centroid, we found a positive correlation to energetic costs. We then investigated whether escape responses are socially modulated by comparing the energetic costs of escape across solitary individuals, solitary individuals with visual access to a group, and groups. We found that escape frequency and energetic costs to predation were comparable across social contexts, indicating that escape may be an intrinsic survival response independent of cues from group members. Furthermore, we found that fish exposed to predators showed markedly reduced feeding, suggesting that predation constrains energy acquisition in addition to imposing direct energetic costs. Our results provide the first direct quantification of the energetic costs of escape in a schooling fish, offering new insights into the physiological trade-offs underlying collective antipredator defenses.

This study investigates closed kinematic chain biomechanics in cycling with a focus on knee joint loading. Data from 16 cyclists collected on a standardized ergometer were analyzed in OpenSim using inverse dynamics, static optimization, and joint reaction analysis. To keep the pipeline consistent across all subjects, the report summarizes right-knee outputs over a steady-state interval between 120 and 124 s. Peak knee joint moments ranged from 15.79 to 44.85 Nm (mean 30.49 {+/-} 7.66 Nm), while peak resultant knee reaction forces ranged from 1187.61 to 3309.04 N (mean 2317.19 {+/-} 728.19 N). Static optimization showed strong contributions from the rectus femoris and vastus lateralis during power production, with additional stabilization from the biceps femoris long head and gastrocnemius medialis. Mean peak muscle activation was highest for the rectus femoris (0.72 {+/-} 0.19), followed by the biceps femoris long head (0.66 {+/-} 0.20). Mean peak muscle force was highest for the vastus lateralis (1078.1 {+/-} 305.8 N) and rectus femoris (994.1 {+/-} 379.2 N). The results confirm substantial inter-subject variability in knee loading and support the use of personalized training or rehabilitation strategies when cycling is used for performance development or joint recovery.