Swimming Movements Research Articles

Hydrodynamics of cruise swimming and turning maneuvers in Euchaeta antarctica

The hydrodynamic disturbance generated by the adult copepod Euchaeta antarctica during cruise swimming is quantified. Kinematic results are compared to previous results reported for different Euchaeta species. The results reveal a linear relationship between cruise speed and prosome length across Euchaeta species, indicating a size-proportional trend that is indicative of a complicated interaction of species size and environmental factors such as fluid temperature and viscosity. The detailed fluid flow measurements using the tomographic Particle Image Velocimetry (tomo-PIV) technique provide insight into copepod cruise propulsion during turning events in comparison to straight motions. During straight swimming, E. antarctica demonstrates streamlined flow patterns and reduced vorticity in the near-body fluid shear layer, which is beneficial for sustained motion and energy conservation. In contrast, turning maneuvers are characterized by maximum flow velocities reaching 1.5 times greater values than during straight cruising with increased flow field complexity and enhanced vorticity. The viscous dissipation rate generated in the flow disturbance is also greater during turning events, with the total dissipation rate reaching 3.5-3.8×10-8\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\bf3.5-3.8\ imes 10^{-8}$$\\end{document} W compared to 2.6-2.8×10-8\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\bf2.6-2.8\ imes 10^{-8}$$\\end{document} W during straight cruising. The flow disturbance also generates a hydrodynamic cue that prey may sense in order to avoid the predator E. antarctica. For the adult E. antarctica, the hydrodynamic cue extends to a volume that is 11–13 times larger than the copepod exoskeleton volume during the straight swimming motion and 22–25 times larger during the turn events.

Real-Time IMU-Based Kinematics in the Presence of Wireless Data Drop.

Wireless inertial motion capture holds promise for real-time human-machine interfaces and home-based rehabilitation applications. However, wireless data drop can cause significant estimation errors deteriorating performance or even making the system unusable. It is currently unclear how to estimate non-periodic kinematics with wearable inertial measurement units (IMUs) in the presence of wireless data drop (packet loss). We thus propose a novel inference encoder-decoder network model for real-time kinematics during dynamic movement. Twenty-four healthy subjects performed yoga, golf, swimming, dance, and badminton movement activities while wearing IMUs and 10-90% of each IMU's data were randomly removed to determine the effects of data drop on estimation accuracy with and without the proposed model. Results demonstrated a reduction in RMSE of 45.2% to 51.5% in the upper limb kinematic estimation of the proposed model compared to the No Prediction strategy, and a reduction of 19.1% to 31.3% of the proposed model compared with an baseline LSTM model. In addition, the proposed model has significantly less error (p<0.05) than the No Prediction strategy and the baseline LSTM model for 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80% data drop. These results could enable wearable, wireless IMU dynamic motion analysis and assessment with reduced kinematic estimation error in the presence of varying amounts of wireless data drop and thus could further facilitate human-machine interaction and home-based medical assessment and treatment.

The Effect of Parasitization by Trichodinid Ciliates on the Mortality of Cultured Pacific Fat Sleeper larvae (Dormitator latifrons).

Trichodinidae, a prevalent group of protozoan ectoparasites in aquaculture, cause rapid mortality in fish hatcheries. Despite their significance, knowledge about these parasites in farmed fish in South America, especially in native species that are currently being domesticated for aquaculture, remains limited. This study morphologically characterized the Trichodinid species that are infecting Pacific fat sleeper (Dormitator latifrons) larvae and evaluated their impact on larval rearing. Four pairs of broodstock were induced with GnRHA implants and placed in tanks containing 200 L of freshwater, with a water temperature of 28 ± 1.0 °C and a dissolved oxygen level of 4.00 ± 1.23 mg L-1, with partial water exchanges being performed daily. The larvae hatched 7 to 8 h after fertilization and were transferred to tanks containing water with the same quality parameters. Twelve hours post-hatching, the presence of Trichodina was observed. Every 24 h, 60 larvae per tank (n = 180 per treatment) were sedated, and larval wet mounts were prepared, air-dried at room temperature, and impregnated with silver nitrate. Infection parameters and daily mortality were calculated. Trichodina was observed to parasitize the pelvic fins, caudal fins, and heads of fish larvae, which showed lethargy and erratic swimming movements. The Trichodina species showed a daily increase in the infection parameters, and a 58% rate of larval mortality was observed at the fourth day post-hatching (dph) in the infected tanks. In captivity, D. latifrons larvae typically survive up to 7 days post-hatching (dph) before reaching their point of no return due to the lack of adequate diet and feeding regimes. However, our study indicates that Trichodina infestation accelerates mortality, causing infected larvae to die more quickly than uninfected ones.

The motion of a self-propelling two-sphere swimmer in a weakly viscoelastic fluid

We study analytically the propulsion of a force- and torque-free swimmer composed of two counterrotating spheres of differing radii through a viscoelastic fluid described by the Giesekus constitutive model. Our analysis includes both swimmers composed of directly touching spheres and those composed of spheres separated by some finite distance. The propulsion speed of the swimmer is calculated by first expanding the equations of motion and the Giesekus constitutive model as a power series in the Weissenberg number, and then using the Lorentz reciprocal theorem to determine the first-order propulsion speed using the known flow fields for rotating and translating two-sphere geometries at zeroth order. We calculate the relative rotation speeds of the two spheres necessary to maintain the torque-free condition, including an approximate correction for fluid elasticity. The impact of the separation distance between the two spheres, the ratio of their radii, and the value of the Giesekus mobility parameter α on the propulsion speed are all examined; we find that the propulsion speed of the swimmer is maximized for two touching spheres with a radius ratio of approximately 0.7, with a Giesekus mobility parameter of α=0, corresponding to an Oldroyd-B fluid. We also quantify how increased shear-thinning in the fluid, represented by increasing values of α, results in a significant decrease in the swimmer speed. Finally, through calculations of the fluid stresses around the two-sphere swimmer, we demonstrate the development of enhanced hoop stresses around the smaller sphere, which drive the expulsion of stretched fluid behind the smaller sphere and induce motion of the swimmer in the direction of the larger sphere.

Interpreting the Projected Frontal Area in Front Crawl: Determining the Projected Frontal Area of Each Body Segment.

This study aimed to provide evidence for the interpretation of the projected frontal area (PFA) during front crawl. To achieve this goal, we developed a method for calculating the PFA of each body segment using digital human technology and compared the pressure drag under two calculation conditions: a combination of the PFA with and without accounting for the horizontal velocity of each body segment. Twelve competitive male swimmers performed a 15-meter front crawl at 1.20 m·s-1. The three-dimensional positions of the reflective markers attached to the swimmer's body were recorded using an underwater motion-capture system. Based on the body shape of each swimmer obtained from the photogenic body scanner, individual digital human body models were created with the color of the model's vertices divided into eight body segments. The time series of the volumetric swimming motion was reconstructed using inverse kinematics. The PFA of each body segment was then calculated by the automatic processing of a series of parallel frontal images. The pressure drag index, defined as the value excluding the drag coefficient while simultaneously considering the PFA and the horizontal velocity, was calculated under two conditions: the static condition (accounting for only the PFA of each body segment) and the dynamic condition (accounting for the PFA and horizontal velocity of each body segment). Notably, the pressure drag index was higher under the static condition than under the dynamic condition for the humerus, ulna, and hand segments (p < 0.001). The results obtained using our methodology indicate that the PFA of the upper limb segments overestimates their contribution to pressure drag during front crawl under the static condition.

Torque, speed, and power requirements for the design of a lower limb exoskeleton to augment human finned swimming

Abstract The authors seek to design a lower limb exoskeleton to augment human finned swimming; however, data associated with human finned swimming previously did not exist, particularly data that characterizes the active joint torque requirements for human-scale finned swimming motion and the corresponding thrust generation. Since these data are not directly measurable nor easily computed in human subject experiments, the authors instead employed a human-scale robotic platform to characterize the relationship between joint torque, speed, power, and thrust production during flutter kick swimming, specifically at the hip joints. Among the useful insights from this study: (1) the underwater environment can be accurately modeled as a simple viscous load as seen by the hip joints, where viscous coefficient depends on the type of fin; (2) accordingly, for a given fin, movement at any amplitude and frequency is invariant when motion is normalized by amplitude; velocity and torque by the product of amplitude and frequency; and power and thrust by the square of the product of amplitude and frequency; (3) the power-specific thrust is invariant, regardless of fin type, amplitude of motion, and frequency of motion; and 4) the phasing between right and left legs does not have a significant effect on thrust generation (i.e., kicking in-phase and kicking in opposition behave similarly). The authors hope this data will be useful to other researchers interested in developing lower limb exoskeletons to augment underwater human finned swimming.

Swimtrans Net: a multimodal robotic system for swimming action recognition driven via Swin-Transformer.

Currently, using machine learning methods for precise analysis and improvement of swimming techniques holds significant research value and application prospects. The existing machine learning methods have improved the accuracy of action recognition to some extent. However, they still face several challenges such as insufficient data feature extraction, limited model generalization ability, and poor real-time performance. To address these issues, this paper proposes an innovative approach called Swimtrans Net: A multimodal robotic system for swimming action recognition driven via Swin-Transformer. By leveraging the powerful visual data feature extraction capabilities of Swin-Transformer, Swimtrans Net effectively extracts swimming image information. Additionally, to meet the requirements of multimodal tasks, we integrate the CLIP model into the system. Swin-Transformer serves as the image encoder for CLIP, and through fine-tuning the CLIP model, it becomes capable of understanding and interpreting swimming action data, learning relevant features and patterns associated with swimming. Finally, we introduce transfer learning for pre-training to reduce training time and lower computational resources, thereby providing real-time feedback to swimmers. Experimental results show that Swimtrans Net has achieved a 2.94% improvement over the current state-of-the-art methods in swimming motion analysis and prediction, making significant progress. This study introduces an innovative machine learning method that can help coaches and swimmers better understand and improve swimming techniques, ultimately improving swimming performance.

Instrumented bio-inspired cable-driven compliant continuum robot: static modeling and experimental evaluation

Abstract Energy efficiency is inherent for autonomous robotic device. Snakes are well known for their ability to low energy consumption when swimming. However, the swimming know-how is poorly understood. Designing a snake robot inspired by snakes as a tool to find out the swimming energy efficiency crucial point will lead to the development of hyper efficient undulating locomotors. In this article, we introduce a four tendons driven continuum robot made of bio-inspired compliant vertebrae to assess the energy consumption of a planar and a spatial snake motion. The tendon-driven continuum robot constitutes the head–neck part of a locomotor snake robot. A static modeling coupled with an optimization method was implemented to generate bio-inspired motions recorded on snake swimming head. A friction model describing the friction between cables and the disks is investigated and compared to a frictionless model. The proposed prototype is equipped with exteroceptive sensors to record motion and proprioceptive sensors to measure cable forces applied at the tip of the robot. Hence, the work of the forces, thus the energy required to execute a trajectory are computed and analyzed. The energy is introduced as a key criterion to assess the swimming motion of a locomotor snake robot.

Microfluidic measurement of the size and shape of lipid-anchored proteins

The surface of a cell is crowded with membrane proteins. The size, shape, density, and mobility of extracellular surface proteins mediate cell surface accessibility to external molecules, viral particles, and other cells. However, predicting these qualities is not always straightforward, even when protein structures are known. We previously developed an experimental method for measuring flow-driven lateral transport of neutravidin bound to biotinylated lipids in supported lipid bilayers. Here, we use this method to detect hydrodynamic force applied to a series of lipid-anchored proteins with increasing size. We find that the measured force reflects both protein size and shape, making it possible to distinguish these features of intact, folded proteins in their undisturbed orientation and proximity to the lipid membrane. In addition, our results demonstrate that individual proteins are transported large distances by flow forces on the order of femtoNewtons, similar in magnitude to the shear forces resulting from blood circulation or from the swimming motion of microorganisms. Similar protein transport across living cells by hydrodynamic force may contribute to biological flow sensing.

A high-efficiency sharp-interface immersed boundary method based on multi-linear interpolation

The sharp-interface immersed boundary method (IBM) reconstructs the flow locally to achieve the precise identification of solid boundaries and their consequential influences on the fluid dynamics. However, the computational accuracy and efficiency are notably impacted by the diverse interaction between the fluid's Euler grid and the solid's Lagrange mesh. Taking the two-dimensional (2D) case as an example, we analyze the characteristics of various grid cutting classes, with a particular focus on how they reduce the solution speed and computational precision. To address these challenges, we propose a multi-linear interpolation method that enriches flow field information by expanding the interpolation template. Computational results of 2D flow past a stationary cylinder and airfoil, and the takeoff of airfoil takeoff demonstrate that the multi-linear interpolation method increases computational efficiency by up to 20%, while maintaining accuracy. Furthermore, we extend this method to three-dimensional (3D) calculations, enhancing efficiency by about 5% and improving accuracy. Finally, by simulating the full-body motion of a penguin swimming, we showcase the robustness of the method in simulating complex geometric moving boundary problems.

Strategies for improving student swimming skills using training methods and media

Many students find that swimming is a necessary skill, yet many struggle to learn the appropriate form due to inadequate teaching. Learning can happen faster with the right training media, and knowledge of swimming techniques can be improved. Innovative teaching methods and training media are needed to optimise students' mastery of swimming skills. This study is to assess how well proper workout regimens and media can enhance fundamental swimming skills. This study uses an action research design, where three action research cycles are (1) preparation, (2) action, (3) observation, and (4) reflection. If at least 75% of children can perform basic swim movements in a crawling style successfully, then this learning has been successful. This study used a percentage analysis methodology as its analytical method. While at least 75% of students who received a completeness score in swimming during the first cycle showed success in basic crawl style movements, the learning results of students' movements were not in accordance with the success indicators; only 55.55% of students achieved the overall target. The number of students who achieved the goal in the second cycle increased to 32 or 71.11%. At the end of the cycle, 40 students, or 88.89% of students, achieved the overall target. According to the study's findings, the basic swimming ability of adolescent students can be improved by using land exercises and training tools.

Donepezil Nanoemulsion Induces a Torpor-like State with Reduced Toxicity in Nonhibernating Xenopus laevis Tadpoles.

Achieving a reversible decrease of metabolism and other physiological processes in the whole organism, as occurs in animals that experience torpor or hibernation, could contribute to increased survival after serious injury. Using a Bayesian network tool with transcriptomic data and chemical structure similarity assessments, we predicted that the Alzheimer's disease drug donepezil (DNP) could be a promising candidate for a small molecule drug that might induce a torpor-like state. This was confirmed in a screening study with Xenopus laevis tadpoles, a nonhibernator whole animal model. To improve the therapeutic performance of the drug and minimize its toxicity, we encapsulated DNP in a nanoemulsion formulated with low-toxicity materials. This formulation is composed of emulsified droplets <200 nm in diameter that contain 1.250 mM DNP, representing ≥95% encapsulation efficiency. The DNP nanoemulsion induced comparable torpor-like effects to those produced by the free drug in tadpoles, as indicated by reduced swimming motion, cardiac beating frequency, and oxygen consumption, but with an improved biodistribution. Use of the nanoemulsion resulted in a more controlled increase of DNP concentration in the whole organism compared to free DNP, and to a higher concentration in the brain, which reduced DNP toxicity and enabled induction of a longer torpor-like state that was fully reversible. These studies also demonstrate the potential use of Xenopus tadpoles as a high-throughput in vivo screen to assess the efficacy, biodistribution, and toxicity of drug-loaded nanocarriers.

RL-CWtrans Net: multimodal swimming coaching driven via robot vision.

In swimming, the posture and technique of athletes are crucial for improving performance. However, traditional swimming coaches often struggle to capture and analyze athletes' movements in real-time, which limits the effectiveness of coaching. Therefore, this paper proposes RL-CWtrans Net: a robot vision-driven multimodal swimming training system that provides precise and real-time guidance and feedback to swimmers. The system utilizes the Swin-Transformer as a computer vision model to effectively extract the motion and posture features of swimmers. Additionally, with the help of the CLIP model, the system can understand natural language instructions and descriptions related to swimming. By integrating visual and textual features, the system achieves a more comprehensive and accurate information representation. Finally, by employing reinforcement learning to train an intelligent agent, the system can provide personalized guidance and feedback based on multimodal inputs. Experimental results demonstrate significant advancements in accuracy and practicality for this multimodal robot swimming coaching system. The system is capable of capturing real-time movements and providing immediate feedback, thereby enhancing the effectiveness of swimming instruction. This technology holds promise.

A comprehensive review of current practices, challenges, and future perspectives in Koi fish (Cyprinus carpio var. koi) cultivation.

The Koi fish (Cyprinus carpio var. koi) is an ornamental fish with a high selling value because of its attractive colors, color patterns, body shape, and swimming motion. Koi fish is extensively traded in the international fish market because of their popularity among hobbyists from numerous countries worldwide. This review discusses various aspects of Koi fish cultivation, including genetic involvement, selective breeding strategies, and management systems. By examining crucial factors such as water parameters, technological innovations, and evolving cultivation methods, this review explored their influence on the quality of Koi fish. Breakthrough technologies, such as ornamental fish warehousing and recirculation aquaculture systems, enhance breeding efficiency and profitability. Molecular sexing, feed optimization, and color enhancement strategies are central to pursuing superior Koi fish. Reproduction management, disease prevention, and risk reduction during transport underscore ongoing efforts to ensure their survival. Despite notable progress, several challenges remain, including limited genetic studies, gaps in disease research, and unexplored herbal alternatives. The active involvement of hobbyists and breeders in research initiatives is a pivotal force in unlocking the untapped potential. The holistic approaches to enhance production efficiency and improve care standards require further exploration, paving the way for a sustainable future in the evolving management of Koi fish cultivation.

DeformableFishNet: a high-precision lightweight target detector for underwater fish identification

The application of computer vision in fish identification facilitates researchers and managers to better comprehend and safeguard the aquatic ecological environment. Numerous researchers have harnessed deep learning methodologies for studying fish species identification. Nonetheless, this endeavor still encounters challenges such as high computational costs, a substantial number of parameters, and limited practicality. To address these issues, we propose a lightweight network architecture incorporating deformable convolutions, termed DeformableFishNet. Within DeformableFishNet, an efficient global coordinate attention module (EGCA) is introduced alongside a deformable convolution network (EDCN/EC2f), which is grounded in EGCA, to tackle the deformation of fish bodies induced by swimming motions. Additionally, an EC2f-based feature pyramid network (EDBFPN) and an efficient multi-scale decoupling head (EMSD Head) are proposed to extract multi-scale fish features within a lightweight framework. DeformableFishNet was deployed on our freshwater fish dataset, with experimental outcomes illustrating its efficacy, achieving a mean average precision (mAP) of 96.3%. The model comprises 1.7 million parameters and entails 4.7 billion floating-point operations (FLOPs). Furthermore, we validated DeformableFishNet on three public underwater datasets, yielding respective mAPs of 98%, 99.4%, and 83.6%. The experiments show that DeformableFishNet is suitable for underwater identification of various scenes.

On The Preparation Of Training Data For 3D Tracking Of Position And Orientation Of Microswimmers Using Defocusing And Deep Learning

The use of image analysis algorithms based on deep convolutional neural networks (CNNs) is opening new possibilities in experimental techniques for fluid dynamics. In the field of microscopic 3D particle tracking based on defocusing, it has been shown on synthetic images that CNNs can be used to determine not only the depth position but also the orientation of non-spherical microscopic particles or specimens. However, the translation of such approaches to experimental setups is challenging, especially due to the difficulty of obtaining reliable labeled images to train the neural networks. In this work, we propose a method to obtain labeled images of microswimmers from conventional microscopy images, exploiting the properties of the swimming motion at low Reynolds numbers, where inertial effects are negligible. This method allows us to obtain ground truth values of orientation and depth position of a microorganism swimming at a regular pace that can be used as training data for CNNs. The proposed methodology was used to obtain labeled images from experimental videos of the micro-organism Euplotes Vannus. The labeled images were used to train a VGG16 network, providing an estimated uncertainty in the determination of the orientation angles psi, theta, phi, and the depth position Z of 2.4%, 1.4%, 2.3%, and 3.5%, respectively.

Dynamic modeling and simulation of hard-magnetic soft beams interacting with environment via high-order finite elements of ANCF

Hard-magnetic soft (HMS) beams made of soft polymer matrix embedded with hard-magnetic particles can generate large and fast deformation under magnetic stimulation. Dynamic modeling and simulation of HMS beams interacting with complex environment are challenging in terms of computational accuracy and efficiency. This paper presents a method for high-order modeling and efficient computation of HMS beams. The major contribution of the method is a new three-node HMS beam element of absolute nodal coordinate formulation (ANCF), which applies to two material models of nonlinear and linear elasticities (i.e. neoHookean and St. Venant-Kirchhoff) coupled with magnetic energy. To improve the efficiency of the method, the paper presents how to derive the generalized internal forces and their Jacobians via invariant tensors, and how to determine the generalized external forces to model dynamic loads and interactions including gravity, hydrodynamics in fluids, and frictional contact in pipelines. Afterwards, the paper gives both static and dynamic equations with Rayleigh damping and discusses the numerical algorithms. Finally, the paper makes a comparison of static analysis and the experimental observation to validate the accuracy of the proposed modeling method. The paper also discusses the dynamic simulations, including forced vibration, swimming motion, crawling locomotion, and navigating motion to demonstrate the predictive capability and efficacy of the proposed method for dynamic problems.

Biphasic burrowing in Atlantic hagfish (Myxine limosa).

Myxine limosa is a burrowing species of hagfish that occurs in the western north Atlantic in areas with muddy substrate and at depths generally greater than 100 meters. Burrowing of M. limosa has been observed from submersibles, but little is known about the behavior of these animals within the substrate or the biomechanical mechanisms involved. Here we investigated burrowing in M. limosa by observing individuals as they burrowed through transparent gelatin. A photoelastic setup using crossed polarizers allowed us to visualize stress development in the gelatin as the hagfish moved through it. We found that M. limosa created U-shaped burrows in gelatin using a stereotyped, two-phase burrowing behavior. In the first ("Thrash") phase, hagfish drove their head and their anterior body into the substrate using vigorous sinusoidal swimming movements, with their head moving side-to-side. In the second ("Wriggle") phase, swimming movements ceased, with propulsion coming exclusively from the anterior, submerged portion of body. The Wriggle phase involved side-to-side head movements and movements of the submerged part of the body that resembled the "internal concertina" strategy used by caecilians and uropeltid snakes. The entire burrowing process took on average 7.6 minutes to complete and ended with the hagfish's head protruding from the substrate and the rest of its body generally concealed. Understanding the burrowing activities of hagfishes could lead to improved understanding of sediment turnover in marine benthic habitats, new insights into the reproductive behavior of hagfishes, or even inspiration for the design of burrowing robots.

Towards Unusual Rolled Swimming Motion of a Bioinspired Robotic Hammerhead Shark Under Negative Buoyancy

Towards Unusual Rolled Swimming Motion of a Bioinspired Robotic Hammerhead Shark Under Negative Buoyancy

Epidermal club cells in the cardinal tetra (Paracheirodon axelrodi): Presence, distribution, and relationship to antipredator behavior

Epidermal club cells (ECCs) are present in many species of teleost fish. In an attempt to justify their presence in the epidermis of fish, they have been associated with numerous functions. One proposed function is communication with conspecifics during a predation event, as these cells may passively release substances upon rupture, which may occur during predation. We identified the presence and distribution of ECCs in the body skin of adult cardinal tetra, Paracheirodon axelrodi (Schultz, 1956) and analyzed the animal’s behavioral response to conspecific skin extract in a laboratory setting. The identification and distribution of ECCs in the epidermis of the animals were confirmed by conventional histology and immunohistochemistry. Our results demonstrated that: ECCs are present in the skin of the entire body; a high density is observed in the dorsal side from head to tail, in the insertion of the fins and in the epidermis covering them; and ventral distribution is less extensive and more dispersed than dorsal distribution. Treatment of P. axelrodi specimens with skin preparations of conspecifics resulted in behavioral changes in the animals: they showed erratic swimming movements, they showed avoidance of the area of stimulus application and they decreased the time spent moving. Overall, these results allow us to conclude that P. axelrodi possesses ECCs throughout the body, with a greater presence in areas of high exposure to predation events (dorsal area and fins). Animals exposed to conspecific skin extract showed a significant increase in behaviors described as anti-predatory in other species. This supports the hypothesis that ECCs may be the origin of chemical alarm cues that are passively released when skin damage occurs, alerting the rest of the group to the risk of predation.