Fish Schools Research Articles

Vortex phase matching of a self-propelled model of fish with autonomous fin motion

It has been a long-standing problem how schooling fish optimize their motion by exploiting the vortices shed by the others. A recent experimental study showed that a pair of fish reduce energy consumption by matching the phases of their tailbeat according to their distance. In order to elucidate the dynamical mechanism by which fish control the motion of caudal fins via vortex-mediated hydrodynamic interactions, we introduce a new model of a self-propelled swimmer with an active flapping plate. The model incorporates the role of the central pattern generator network that generates rhythmic but noisy activity of the caudal muscle, in addition to hydrodynamic and elastic torques on the fin. For a solitary fish, the model reproduces a linear relation between the swimming speed and tailbeat frequency, as well as the distributions of the speed, tailbeat amplitude, and frequency. For a pair of fish, both the distribution function and energy dissipation rate exhibit periodic patterns as functions of the front-back distance and phase difference of the flapping motion. We show that a pair of fish spontaneously adjust their distance and phase difference via hydrodynamic interaction to reduce energy consumption.

Effects of Different Motion Parameters on the Interaction of Fish School Subsystems.

For a long time, fish school swimming has attracted a great deal of attention in biological systems, as fish schools can have complex hydrodynamic effects on individuals. This work adopted a non-iterative, immersed boundary-lattice Boltzmann method (IB-LBM). A numerical simulation of two-dimensional three-degree-of-freedom self-propelled fish, in side-by-side, staggered, and triangle formations, was conducted by adjusting spacing and motion parameters. A comprehensive analysis of individual speed gains and energy efficiencies in these formations was carried out. Furthermore, an analysis of the hydrodynamic characteristics of fish schools was performed, using instantaneous vorticity profiles and pressure fields. Certain studies have shown that passive interactions between individuals cannot always bring hydrodynamic benefits. The swimming efficiency of side-by-side formations in the same phase gradually increases as the distance decreases, but it also brings certain burdens to individuals when the phases are different. This paper also shows that the roles of passive interactions, spacing, and deflections affect fish school subsystems differently. When the low-pressure areas created by a wake vortex act on one side of an individual's body, the tail-end fish are good at gaining hydrodynamic benefits from it. This effect is not universal, and the degree to which individuals benefit from changes in exercise parameters varies. This study provides a theoretical basis for bioinspired robots, as well as providing certain insights into the mechanism of collective biological movement.

A School of Local Fish on the School Lunch Menu

School cafeterias in the Canary Islands use mainly seafood that is imported from far-away industrial fishing operations, even though there are several nearby fishing fleets. The nearby fleets fish for tuna the traditional way, catching them one by one off of mostly small-scale fishing boats, with the hook and line technique. These boats are eco-friendly, but they tend to export their tuna—several thousand tons each year—to mainland Spain or other countries. So, in 2018, we started a project to supply local tuna and other fish steaks to about a dozen Canary Islands school cafeterias, in an attempt to reduce fish exports and imports. This is good for the environment because it decreases the amount of fuel used to move food from place to place. We hope our work will not only help school kids to eat healthier, but also improve the eating habits and health of the entire local population.

An investigation of Glaucoma Detection in RFI Using Bio-Inspired Multivariable FE with ML Models for Early Diagnosis

To propose a bio-inspired multi-variant feature extraction technique in retinal fundus images to improve glaucoma detection for easy diagnosis. To improve the classification accuracy of glaucoma disease, a machine learning approach is employed based on the features extracted in RFI. Methods: The Fish School Search MOFS (FSS-MOFS) bio-inspired technique is employed to extract the multivariable features from digital RFI and spot the glaucoma variations to maximize the discrimination power and minimize the dimensionality. The Binary Robust Independent Elementary Feature (BRIEF-LD) technique is employed to identify the latent spots in RFI. The PAPILA dataset is utilized for this research study, which includes the clinical records of 244 patients and 488 images of the right and left eye of all the patients under 2 categories (male and female) with results in healthy, glaucoma, and suspect categories. In order to perform deep pixel identification and RFI segmentation, the Densenet-121 architecture is used along with a deep-lab model to incarcerate the built-in fine points of RFI with the help of dilated convolutions. The MATLAB tool is used to assess the suggested bio-inspired technique, and comparative analysis is done against the prevailing glaucoma detection and feature extraction methods such as I-SVM, RFSO, SE-GSO, VGG-Net, and DBN classifiers. Findings: The suggested FSS-MOFS multi-variant feature extraction technique outperforms the prevailing ML methods such as I-SVM, RFSO, SE-GSO, VGG-Net, and DBN classifiers. The result of the comparative study shows 94% accuracy, 96% sensitivity, 97% specificity, 96% F-measure, 96.8% Precision, 97% recall, 95% detection speed, 92.06% TPR, 92.15% TNR, and 8% FPR & FNR. Novelty: The promising result of the FSS-MOFS method boosts the accuracy level of glaucoma detection and classification compared to other classification techniques. The suggested model helps the ophthalmologists identify and diagnose glaucoma in a robust way. FSS-MOFS overcomes the shortcomings of prevailing feature extraction methods.

Guiana dolphins use mangrove margins as a natural barrier to chase fish prey

AbstractThe behavioral plasticity among and within cetacean species can be driven by their prey sources, local adaptations to environmental features, and/or interactions with human activities. One of the tactics displayed by cetaceans is the barrier feeding, in which individuals or groups herd fish schools against natural and non‐natural barriers to restrict movements of their prey. Coastal odontocetes, for example, are known for using shorelines and underwater slopes to trap their prey. Here, we documented two distinct populations of Guiana dolphin using the mangrove margins as a natural barrier to herd and capture fish. The observations took place in the Cananéia estuary, São Paulo State, southeastern Brazil, and in the Paranaguá estuary, Paraná State, southern Brazil. A total of 63 dolphins over eight encounters were observed performing six different events using mangroves as a natural barrier, summing both study areas. These findings not only expand our understanding of the behavior plasticity of the species but also call attention to the importance of the mangrove ecosystem directly to Guiana dolphins and indirectly to the components of their food web.

The marine fish Terapon theraps calling in tropical Australia

Calling by fish of the family Terapontidae, primarily Terapon theraps, is a dominant component of sea noise recorded in northern Australian tropical coastal waters. These fish produce nightly choruses over a few hours at frequencies from 50 Hz to a few kilohertz, with spectral peaks up to 30 dB above background. Choruses are heard over muddy bottoms <30 m depth. The two commonly heard calls range from 73–260 ms in length and comprised 11–21 pulses with repetition rates of 87–121 Hz. Calls were produced by muscle action on a two chambered swim bladder, and differed by muscle contraction rates, damping, and possibly the opening state of a sphincter separating chambers. Swimbladder carrier frequencies varied from 570–1465 Hz. Source levels varied from 141–154 dB re 1 mPa @ 1 m. Heavily damped alarm calls were sometimes heard. Chorusing fish schools were up to 2 km across although they were diffuse and actively calling fish extended beyond this region. A chorus could be detected out to 8 km from its center, well beyond the detection range of an individual call. Choruses may advertise school location during spawning, be used for mate attraction or mediate gamete release in dark turbid waters.

The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots.

Collective behaviour defines the lives of many animal species on the Earth. Underwater swarms span several orders of magnitude in size, from coral larvae and krill to tunas and dolphins. Agent-based algorithms have modelled collective movements of animal groups by use of social forces, which approximate the behaviour of individual animals. But details of how swarming individuals interact with the fluid environment are often under-examined. How do fluid forces shape aquatic swarms? How do fish use their flow-sensing capabilities to coordinate with their schooling mates? We propose viewing underwater collective behaviour from the framework of fluid stigmergy, which considers both physical interactions and information transfer in fluid environments. Understanding the role of hydrodynamics in aquatic collectives requires multi-disciplinary efforts across fluid mechanics, biology and biomimetic robotics. To facilitate future collaborations, we synthesize key studies in these fields.

Fishery Business Analysis (Case Study: FV. Diva Bahari at Kendari Ocean Fishing Port)

Purse seine is a type of fishing gear that has the principle of catching fish by circling a school of fish. Fish caught by purse seine include lemuru, skipjack, and tuna (pelagic fish), which have economic value. One area where the majority of fishermen use purse seines is PPS Kendari. The more fishermen use the purse seine, the more it will affect the income or feasibility of the fishing business. The feasibility status of the business can be identified by conducting a business analysis of the fishing activity. Business analysis begins with participating in a trip to one of the purse seine fishing activities at PPS Kendari in January-May 2020. Carry out business-related recording activities (business capital, maintenance, and income). After the data is obtained, a business analysis will be carried out on the profit value, profit sharing system, R/C ratio, and payback period (PP). Based on the business analysis that has been done, the total cost of fishing activities is Rp. 212,716,600.00, and the company made a profit of Rp. 1,074,353,400.00. profit-sharing system, with each share amounting to Rp. 20,270,818.87. So, it can be said that fishing using purse seines at PPS Kendari is still feasible, with a value of 6.05 and a PP of 0.61 years.

Quantum pure noise-induced transitions: A truly nonclassical limit cycle sensitive to number parity

It is universally accepted that noise may bring order to complex nonequilibrium systems. Most strikingly, entirely new states not seen in the noiseless system can be induced purely by including multiplicative noise-an effect known as pure noise-induced transitions. It was first observed in superfluids in the 1980s. Recent results in complex nonequilibrium systems have also shown how new collective states emerge from such pure noise-induced transitions, such as the foraging behavior of insect colonies, and schooling in fish. Here we report such effects of noise in a quantum-mechanical system without a classical limit. We use a minimal model of a nonlinearly damped oscillator in a fluctuating environment that is analytically tractable, and whose microscopic physics can be understood. When multiplicative environmental noise is included, the system is seen to transition to a limit-cycle state. The noise-induced quantum limit cycle also exhibits other genuinely nonclassical traits, such as Wigner negativity and number-parity sensitive circulation in phase space. Such quantum limit cycles are also conservative. These properties are in stark contrast to those of a widely used limit cycle in the literature, which is dissipative and loses all Wigner negativity. Our results establish the existence of a pure noise-induced transition that is nonclassical and unique to open quantum systems. They illustrate a fundamental difference between quantum and classical noise.

Fish-inspired robotic algorithm: mimicking behaviour and communication of schooling fish.

This study aims to present a novel flocking algorithm for robotic fish that will aid the study of fish in their natural environment. The algorithm, fish-inspired robotic algorithm (FIRA), amalgamates the standard flocking behaviors of attraction, alignment, and repulsion, together with predator avoidance, foraging, general obstacle avoidance, and wandering. The novelty of the FIRA algorithm is the combination of predictive elements to counteract processing delays from sensors and the addition of memory. Furthermore, FIRA is specifically designed to work with an indirect communication method that leads to superior performance in collision avoidance, exploration, foraging, and the emergence of realistic behaviors. By leveraging a high-latency, non-guaranteed communication methodology inspired by stigmergy methods inherent in nature, FIRA successfully addresses some of the obstacles associated with underwater communication. This breakthrough enables the realization of inexpensive, multi-agent swarms while concurrently harnessing the advantages of tetherless communication. FIRA provides a computational light control algorithm for further research with low-cost, low-computing agents. Eventually, FIRA will be used to assimilate robots into a school of biological fish, to study or influence the school. This study endeavors to demonstrate the effectiveness of FIRA by simulating it using a digital twin of a bio-inspired robotic fish. The simulation incorporates the robot's motion and sensors in a realistic, real-time environment with the algorithm used to direct the movements of individual agents. The performance of FIRA was tested against other collective flocking algorithms to determine its effectiveness. From the experiments, it was determined that FIRA outperformed the other algorithms in both collision avoidance and exploration. These experiments establish FIRA as a viable flocking algorithm to mimic fish behavior in robotics.

EAEFA: An Efficient Energy-Aware Task Scheduling in Cloud Environment

The scheduling of tasks in the cloud is a major challenge for improving resource availability and decreasing the total execution time and energy consumption of operations. Due to its simplicity, efficiency, and effectiveness in identifying global optimums, electric fish optimisation (EFO) has recently garnered a lot of interest as a metaheuristic method for solving optimisation issues. In this study, we apply electric fish optimisation (EAEFA) to the problem of cloud task scheduling in an effort to cut down on power usage and turnaround time. The objective is to finish all tasks in the shortest possible time, or makespan, taking into account constraints like resource availability and task dependencies. In the EAEFA approach, a school of electric fish is used to solve a multi-objective optimization problem that represents the scheduling of tasks. Because electric fish are drawn to high-quality solutions and repelled by low-quality ones, the algorithm is able to converge to a global optimum. Experiments validate EAEFA's ability to solve the task scheduling issue in cloud computing. The suggested scheduling strategy was tested on HPC2N and other large-scale simulations of real-world workloads to measure its makespan time, energy efficiency and other performance metrics. Experimental results demonstrate that the proposed EAEFA method improves performance by more than 30% with respect to makespan time and more than 20% with respect to overall energy consumption compared to state-of-the-art methods.

Multi-scale dynamic imaging reveals that cooperative motility behaviors promote efficient predation in bacteria

Many species, such as fish schools or bird flocks, rely on collective motion to forage, prey, or escape predators. Likewise, Myxococcus xanthus forages and moves collectively to prey and feed on other bacterial species. These activities require two distinct motility machines enabling adventurous (A) and social (S) gliding, however when and how these mechanisms are used has remained elusive. Here, we address this long-standing question by applying multiscale semantic cell tracking during predation. We show that: (1) foragers and swarms can comprise A- and S-motile cells, with single cells exchanging frequently between these groups; (2) A-motility is critical to ensure the directional movement of both foragers and swarms; (3) the combined action of A- and S-motile cells within swarms leads to increased predation efficiencies. These results challenge the notion that A- and S-motilities are exclusive to foragers and swarms, and show that these machines act synergistically to enhance predation efficiency.

Spatial extent and isolation of marine artificial structures mediate fish density

Installations of artificial structures in coastal oceans create de facto habitat for marine life. These structures encompass wide varieties of physical characteristics, reflecting their multiple, diverse purposes and creating a need to understand which characteristics maximize fish habitat. Here, we test how physical characteristics – horizontal area, vertical relief, and spatial isolation – relate to fish density from echosounder surveys over artificial structures like concrete pipes, train boxcars, and ships purposely sunk to function as reefs. Echosounder mapping of 31 artificial reef structures and associated fish across a 200 km linear length of the continental shelf of North Carolina, USA, revealed that structures with greater horizontal area and vertical relief host higher fish densities than smaller, shorter structures. Artificial structure spatial arrangement also relates to fish density, as isolated structures are generally associated with greater localized fish densities than structures closer to one another. Patterns in the relationships between fish density and reef characteristics differed for schooling fish, as there was some evidence that reefs of intermediate area exhibited higher schooling fish density. These results suggest that intentional design and spatial arrangement of marine built structures like artificial reefs relates to and can be deliberately incorporated into siting and deployment decisions to enhance their role as fish habitat.

SmrtSwarm: A Novel Swarming Model for Real-World Environments

Drone swarms have gained a lot of popularity in recent times because, as a group, drones can perform highly intelligent tasks. Drone swarms are strongly inspired by the flocking behavior of birds, insects, and schools of fish, where all the members work in a coordinated manner to achieve a common goal. Since each drone is an independent entity, automating the control of a swarm is difficult. Previous works propose various swarming models with either centralized or distributed control. With distributed control, each drone makes its own decisions based on a small set of rules to accomplish swarm behavior, whereas in centralized control, one drone acts as the leader, who knows the final destination and the path to follow; it specifies the trajectories and velocities for the rest of the drones. Almost all the work in the area of swarming models follows Reynolds’ model, which has three basic rules. For GPS-aided settings, state-of-the-art proposals are not mature enough to handle complex environments with obstacles where primarily local decisions are taken. We propose a new set of rules and a game-theoretic method to set the values of the hyperparameters to design robust swarming algorithms for such scenarios. Similarly, the area of realistic swarming in GPS-denied environments is very sparse, and no work simultaneously handles obstacles and ensures that the drones stay in a confined zone and move along with the swarm. Our proposed solution SmrtSwarm solves all of these problems. It is the first comprehensive model that enables swarming in all kinds of decentralized environments regardless of GPS signal availability and obstacles. We achieve this by using a stereo camera and a novel algorithm that quickly identifies drones in depth maps and infers their velocities and identities with reference to itself. We implement our algorithms on the Unity gaming engine and study them using exhaustive simulations. We simulate 15-node swarms and observe cohesive swarming behavior without seeing any collisions or drones drifting apart. We also implement our algorithms on a Beaglebone Black board and show that even in a GPS-denied setting, we can sustain a frame rate of 75 FPS, much more than what is required in practical settings.

ITSASDRONE, an autonomous marine surface drone for fish monitoring around wave energy devices

The ocean energy development is one of the main pillars of the EU Blue Growth strategy. However, while the technological development of devices is growing fast, their potential environmental effects are not well-known. The nascent status of the Marine Renewable Energy (MRE) sector and Wave Energy (WE) in particular, yields many unknowns about its potential environmental pressures and impacts, some of them still far from being completely understood. Wave Energy Converters’ (WECs) operation in the marine environment is still perceived by regulators and stakeholders as a risky activity, particularly for some groups of species and habitats. The SafeWAVE project aims to improve the knowledge on these impacts trough an Environmental Research Demonstration Strategy based on the collection, processing, modelling, analysis and sharing of environmental data collected in WE sites from different European countries where WECs are currently operating (Mutriku power plant and BIMEP in Spain, Aguçadoura in Portugal and SEMREV in France) representing different types of technology, different types of locations and different types of project scales, therefore, different types and/or magnitudes of environmental impacts. As part of SafeWAVE project, environmental monitoring plans relative to electromagnetic fields, acoustics (noise), seafloor integrity and fish communities need to be put in place. In the case of fish communities, generally speaking, any artefact located in the sea may cause an attraction effect on fish communities, especially if it is floating. In the case of Marine Renewable Energy Devices, during the operation phase, in general, the placement of any artefact in the sea can result in an attracting effect on fish communities, especially if it is floating. In order to study this possible effect, fish communities monitoring around the Penguin WEC-2 of WELLO-Oy localized in BiMEP test site with the ITSASDRONE surface drone developed by AZTI was planned. The study was designed to carry out the tunning and conditioning of the ITSASDRONE and to discover the associations between WECs and fish aggregations. Penguin WEC-2 of WELLO was removed from BiMEP test site due to an alarm of leakage. Consequently, we decided to carry out the monitoring work around the HarshLab, a floating laboratory device constructed by Tecnalia and localized also in BiMEP test site. The study allows us to validate the ITSASDRONE as a viable autonomous vehicle for fish school monitoring. It still needs some technological improvement related to navigation system, but in general, the ITSADRONE meets the objectives for which it was conceived and could be an excellent monitoring technique due to its capacity to work remotely and in near shore areas. Schools of unidentified small pelagic fish were observed distributed throughout the water column, predominantly near the bottom in the device area. But, future studies are needed to further explore the association between WECs and fish aggregations. The aim of this communication is to show the work done by an autonomous marine surface drone, ITSASDRONE, in relation to fish monitoring in BiMEP area.

A EUROPEAN ANTIPOPULIST MOVEMENT? THE EMERGENCE AND DIFFUSION OF THE ITALIAN SARDINES AND FINNISH HERRINGS*

This article investigates the emergence and diffusion of antipopulist mobilizations. Resembling the iconic image depicting a school of small fish chasing a big one, the Italian 6000 Sardine and the Finnish Silakkaliike (Herrings) emerged as two movements with antipopulist claims. Although the scholarship on populism is abundant, antipopulism remains mostly neglected, especially its mobilization from below. Drawing on extensive fieldwork including a groundedtheory approach applied to twenty-seven interviews with activists from these two movements, plus the analysis of offline and online organizational documents, this study shows the mechanisms—cognitive, affective and relational—of their national and crossnational diffusion, relating them to the opportunities of the context. Exploring the internal movement dynamics and actors’ perceptions and motivations, this study also contributes to the conceptualization of antipopulism from below, defining the main characteristics and the ideological underpinnings of these two antipopulist movements.

Fish School Behaviour Classification for Optimal Feeding Using Dense Optical Flow

Fish School Behaviour Classification for Optimal Feeding Using Dense Optical Flow

Development of a solution search method using an improved fish school algorithm

The object of research is decision support systems. The subject of research is the decision-making process in management problems using the fish school (FSH) algorithm, an advanced genetic algorithm and evolving artificial neural networks. A solution search method using an improved FSH algorithm is proposed. The study is based on the FSH algorithm for finding a solution on the object state. For training FSH, evolving artificial neural networks are used. The method has the following sequence of actions: – input of initial data; – processing of initial data taking into account the degree of uncertainty; – checking the fitness function of the solution found; – procedure of feeding fish agents (FA); – instinctive-collective FA swimming; – calculation of the center of school gravity; – collective voluntary FA swimming; – changing the FA swimming parameters; – training of FA knowledge bases. The originality of the proposed method lies in the arrangement of FA taking into account the uncertainty of the initial data, improved global and local search procedures taking into account the degree of noise of data about the state of the analysis object. The peculiarity of the proposed method is the use of an improved FA training procedure. The training procedure consists in learning the synaptic weights of the artificial neural network, the type and parameters of the membership function, the architecture of individual elements and the architecture of the artificial neural network as a whole. The use of the method makes it possible to increase the efficiency of data processing at the level of 18–25 % due to the use of additional improved procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes in the interest of solving national security problems

Development of a low-power remote monitoring module for set-net fish school based on WCDMA

Development of a low-power remote monitoring module for set-net fish school based on WCDMA

The Large-Scale Cultivation of Nematodes to Study Their Collective Behaviors.

Animals exhibit dynamic collective behaviors, as observed in flocks of birds, schools of fish, and crowds of humans. The collective behaviors of animals have been investigated in the fields of both biology and physics. In the laboratory, researchers have used various model animals such as the fruit fly and zebrafish for approximately a century, but it has remained a major challenge to study large-scale complex collective behavior orchestrated by these genetically tractable model animals. This paper presents a protocol to create an experimental system of collective behaviors in Caenorhabditis elegans. The propagated worms climb on the lid of the Petri plate and show collective swarming behavior. The system also controls worm interactions and behaviors by changing the humidity and light stimulation. This system allows us to examine the mechanisms underlying collective behaviors by changing environmental conditions and examining the effects of individual-level locomotion on collective behaviors using mutants. Thus, the system is useful for future research in both physics and biology.