Characteristics Of Swarms Research Articles

Spatial and temporal characteristics of laboratory-induced Anopheles coluzzii swarms: Shape, structure, and flight kinematics

Malaria mosquitoes mate in swarms, but how these swarms are formed and maintained remains poorly understood. We characterized three-dimensional spatiotemporal flight kinematics of Anopheles coluzzii males swarming at sunset above a ground marker. The location, shape, and volume of swarms were highly stereotypic, consistent over the complete swarming duration. Swarms have an elliptical cone shape; mean flight kinematics varies spatially within the swarm, but remain rather consistent throughout swarming duration. Using a sensory system-informed model, we show that swarming mosquitoes use visual perception of both the ground marker and sunset horizon to display the swarming behavior. To control their height, swarming individuals maintain an optical angle of the marker ranging from 24° to 55°. Limiting the viewing angle deviation to 4.5% of the maximum value results in the observed elliptical cone swarm shape. We discuss the implications of these finding on malaria mosquito mating success, speciation and for vector control.

CFD Analysis of Aerodynamic Characteristics in a Square-Shaped Swarm Formation of Four Quadcopter UAVs

The aerodynamic behavior of a square-shaped formation of four quadcopter UAVs flying in a swarm is investigated in detail through three-dimensional computer simulations utilizing Computational Fluid Dynamics (CFD) methodology. The swarm configuration comprises four UAVs positioned with two in the upper row and two in the lower row along the same propeller axes. The flow profile generated by the UAV propellers rotating at 10,000 revolutions per minute is analyzed parametrically using the Multiple Reference Frame (MRF) technique. UAVs within the swarm are positioned at 75 cm from the motion centers of adjacent propellers. This distance, the effects of horizontally and vertically positioned UAVs on each other, and the collective behavior of the swarm are thoroughly examined. Pressure, velocity, and turbulent kinetic energy values are meticulously analyzed. This research represents a milestone in understanding the aerodynamic characteristics of UAV swarms and the optimization of swarm performance. The findings highlight effective factors in swarm flights and their consequences for UAVs. Additionally, the article describes the “near-UAV phenomenon”. Furthermore, the methodology developed for CFD simulations provides an approach to analyzing close flight scenarios and evaluating their performance in various swarm configurations. These achievements contribute to the future development of UAV technology.

Hierarchical RNNs with Graph Policy and Attention for Drone Swarm

Abstract In recent years, the drone swarm has experienced remarkable growth, finding applications across diverse domains such as agricultural surveying, disaster rescue, and logistics delivery. However, the rapid expansion of drone swarm usage underscores the necessity for innovative approaches in the field. Traditional algorithms face challenges in adapting to complex tasks, environmental modeling, and computational complexity, highlighting the need for more advanced solutions like multi-agent deep reinforcement learning to enhance efficiency and robustness in drone swarm. Our proposed approach tackles this challenge by embracing temporal and spatial. In terms of the temporal, the proposed approach builds upon historical data, it enhances the predictive capabilities regarding future behaviors. In the spatial, the proposed approach leverage graph theory to model the swarm's features, while attention mechanisms strengthen the relationships between individual drones. The proposed approach addresses the unique characteristics of drone swarms by incorporating temporal dependencies, spatial structures, and attention mechanisms. Extensive experiments validate the effectiveness of the proposed approach.

Self-stabilization of barchan dune chasing

Barchan dunes migrate in swarms, with rich but not fully revealed self-stabilization mechanisms. The interaction between dunes is considered as one of the key reasons for these mechanisms. Contact-type interactions, known as collisions, have been widely studied, while non-contact-type interactions have received less attention. In this paper, a water tunnel experiment was performed to study the non-contact dune chasing. With the aid of numerical simulations, a general model was proposed to interpret the convergence of distance between two dunes chasing each other. The model consists of three factors: inter-dune repulsive vortex, embracing vortex downstream, and difference in dune mass. Then, we reported a scaling law, expressed as the relation between the normalized dune spacing and time, to describe the convergence of dune spacing, and develop a governing equation in the form of area summation to explain the violation of convergence by combining the above-mentioned three factors, both of which were verified experimentally. Our findings could help advance the understanding of the self-stabilization characteristics of dune swarms in nature.

Compact and ordered swarms of unmanned aerial vehicles in cluttered environments.

The globally coordinated motion produced by the classical swarm model is typically generated by simple local interactions at the individual level. Despite the success of these models in interpretation, they cannot guarantee compact and ordered collective motion when applied to the cooperation of unmanned aerial vehicle (UAV) swarms in cluttered environments. Inspired by the behavioral characteristics of biological swarms, a distributed self-organized Reynolds (SOR) swarm model of UAVs is proposed. In this model, a social term is designed to keep the swarm in a collision-free, compact, and ordered collective motion, an obstacle avoidance term is introduced to make the UAV avoid obstacles with a smooth trajectory, and a migration term is added to make the UAV fly in a desired direction. All the behavioral rules for agent interactions are designed with as simple a potential function as possible. And the genetic algorithm is used to optimize the parameters of the model. To evaluate the collective performance, we introduce different metrics such as (a) order, (b) safety, (c) inter-agent distance error, (d) speed range. Through the comparative simulation with the current advanced bio-inspired compact and Vasarhelyi swarm models, the proposed approach can guide the UAV swarm to pass through the dense obstacle environment in a safe and ordered manner as a compact group, and has adaptability to different obstacle densities.

Incorporating hybrid networks into urban transportation infrastructures for improved COVID-19 transmission forecasting

In this study, we focus on exploring the propagation characteristics of particle swarms in social networks and analyze the diffusion process of viruses among populations based on system dynamics. The article mainly discusses three propagation influence mechanisms, including individual attributes, group attributes, and particle swarm attributes, and delves into the modeling of diffusion processes based on network structures. Firstly, we adopt the main roads in the transportation network (hub nodes) as the initial network backbone. On this basis, by introducing branch networks with small-world characteristics and scale-free characteristics, we construct a transportation network that integrates multiple properties. Using this network, we conducted a detailed simulation and analysis of the COVID-19 transmission process and compared and verified it with the infection dynamic data of COVID-19 in Shanghai from March to September 2022. The verification results reveal that our proposed model can significantly improve prediction accuracy. Compared with other existing dynamic models, our model demonstrates excellent performance, possessing high practical application value. This study provides robust theoretical support for the propagation characteristics of particle swarms in social networks and lays the foundation for further research and application in related fields.

Enhancement investigation of mass transfer and mixing performance in the static mixers with three twisted leaves

Abstract The mass transfer and mixing performance in the static mixers with three twisted leaves (TKSM) were investigated by the computational fluid dynamics coupled population balance model. A high-precision and efficient gas-liquid two phase model were evaluated by considering several drag models based on experimental bubble size distributions. The bubble size prediction matched well with experimental data and the mean relative error of Sauter mean diameter (d 32) between the prediction and experiment values is 4.93 %. The drag correction factor considering hindering effect of small bubbles can improve the accuracy of cumulative probability distribution (CPD) prediction by 10.06 %. Bubble breakup capacity is quantized via gas-liquid interfacial area, and an empirical correlation between Eo and bubble aspect ratio (γ) have been proposed to predict morphological characteristics of bubble swarms. The effect of liquid Re on the mass transfer rate is much more significant than that of gas volume fraction (α d). The coefficients of variation profiles show that RL-TKSM has better mixing efficiency compared with LL-TKSM and perfect mixing could be achieved after seven mixing elements. The micro mixing efficiency of RL-TKSM is 1.06–1.14 times that of LL-TKSM, which indicates that RL-TKSM has excellent mixing and mass transfer performances.

Activity characteristics of significant earthquake swarms in the Bohai Rim region

Activity characteristics of significant earthquake swarms in the Bohai Rim region

Periodic activity from fast radio burst FRB180916 explained in the frame of the orbiting asteroid model

ABSTRACT Observation of fast radio bursts (FRBs) are rising very quickly with the advent of specialized instruments and surveys, and it has recently been shown that some of them repeat quasi-periodically. In particular, evidence of a P = 16.35 d period has been reported for FRB 180916.J0158+65. We seek an explanation within the frame of our orbiting asteroid model, whereby FRBs are produced in the plasma wake of asteroids immersed in the wind of a pulsar or a magnetar. We used the data reported by the CHIME/FRB collaboration in order to infer the orbital characteristics of asteroid swarms, and performed parametric studies to explore the possible characteristics of the pulsar, its wind, and of the asteroids, under the constraint that the latter remain dynamically and thermally stable. We found a plausible configuration in which a young pulsar is orbited by a main ∼10−3 M⊙ companion with a period 3P = 49 d, three times longer than the apparent periodicity P. Asteroids responsible for FRBs are located in three dynamical swarms near the L3, L4, and L5 Lagrange points, in a 2:3 orbital resonance akin to the Hildas class of asteroids in the Solar system. In addition, asteroids could be present in the Trojan swarms at the L4 and L5 Lagrange points. Together, these swarms form a carousel that explains the apparent P periodicity and dispersion. We estimated that the presence of at least a few thousand asteroids, of size ∼20 km, is necessary to produce the observed burst rate. We show how radius-to-frequency mapping in the wind and small perturbations by turbulence can suffice to explain downward-drifting sub-pulses, micro-structures, and narrow spectral occupancy.

Human-Collective Collaborative Target Selection

Robotic collectives are composed of hundreds or thousands of distributed robots using local sensing and communication that encompass characteristics of biological spatial swarms, colonies, or a combination of both. Interactions between the individual entities can result in emergent collective behaviors. Human operators in future disaster response or military engagement scenarios are likely to deploy semi-autonomous collectives to gather information and execute tasks within a wide area, while reducing the exposure of personnel to danger. This article presents and evaluates two action selection models in an experiment consisting of a single human operator supervising four simulated collectives. The action selection models have two parts: (1) a best-of- n decision-making model that attempts to choose the highest-quality target from a set of n targets and (2) a quorum sensing task sequencing model that enables autonomous target site occupation. An original biologically inspired insect colony decision model is compared to a bias-reducing model that attempts to reduce environmental bias, which can negatively influence collective best-of- n decisions when poorer-quality targets are easier to evaluate than higher-quality targets. The collective decision-making models are compared in both supervised and unsupervised trials. The bias-reducing model without human supervision is slower than the original model but is 57% more accurate for decisions where evaluating the optimal target is more difficult. Human-collective teams using the bias-reducing model require less operator influence and achieve 25% higher accuracy with difficult decisions compared to the teams using the original model.

Turbulence-induced clustering in compressible active fluids.

We study a novel phase of active polar fluids, which is characterized by the continuous creation and destruction of dense clusters due to self-sustained turbulence. This state arises due to the interplay between self-advection of the aligned swimmers and their defect topology. The typical cluster size is determined by the characteristic vortex size. Our results are obtained by investigating a continuum model of compressible polar active fluids, which incorporates typical experimental observations in bacterial suspensions, in particular a non-monotone dependence of speed on density.

Effects of bubble size on the gas–liquid mass transfer of bubble swarms with Sauter mean diameters of 0.38–4.88 mm in a co‐current upflow bubble column

AbstractBACKGROUNDBubble columns have found a wide range of application in biochemical industry. Mass transfer in the bubble column can be manipulated by adjusting the bubble size. Thus, for the design of bubble columns, it is necessary to investigate the behaviors of different‐sized bubbles. This work attempts to study the global hydrodynamic and mass transfer characteristics of bubble swarms with Sauter mean diameters (d32) of 0.38–4.88 mm, from microbubbles to millimeter‐sized bubbles, in a co‐current bubble column.RESULTSThe specific interfacial areas of the bubble swarms with d32 of 0.38–1.47 (generated by ceramic membrane module) and 1.05–4.88 mm (generated by plate gas distributor) are 250–1100 and 7–270 m−1, respectively. The liquid‐side mass transfer coefficient (kL) of those two kinds of bubbles are (0.45–1.16) × 10−4 and (0.58–7.65) × 10−4 m s−1, respectively.CONCLUSIONDecreasing the bubble size can effectively increase the volumetric mass transfer coefficient (kLa), especially when the bubble size decreases to several micrometers. The major contribution to the mass transfer enhancement results from the increase of the specific interfacial area. Conversely, the kL decreases clearly. It is demonstrated that Higbieʼs and Frosslingʼs equations can approximate the kL of the bubble swarms with d32 > 2 mm and d32 < 2 mm in the bubble column, respectively. © 2020 Society of Chemical Industry

Geochemical Composition of Dolerites as an Indicator of the Distance of a Dike Swarm from the Mantle Plume Center (Case Study of Proterozoic Dike Swarms, Siberian Craton)

Based on investigation of Proterozoic mafic dike swarms of the Siberian Craton, we inferred how the geochemical and isotopic characteristics of dike swarms of dolerites of Large Igneous Provinces depend on their distance from the mantle plume head. It has been found that the dolerite parent melts near the mantle plume head correspond to OIB compositions. At significant distances from the plume, the initial melts of dolerites are generated in the subcontinental lithospheric mantle, which provides a wide range of their compositions differing from typical OIB and do not indicate directly the genetic relationship of these mafic rocks with the mantle plume.

The characteristics of krill swarms in relation to aggregating Antarctic blue whales

We model the presence of rare Antarctic blue whales (Balaenoptera musculus intermedia) in relation to the swarm characteristics of their main prey species, Antarctic krill (Euphausia superba). A combination of visual observations and recent advances in passive acoustic technology were used to locate Antarctic blue whales, whilst simultaneously using active underwater acoustics to characterise the distribution, size, depth, composition and density of krill swarms. Krill swarm characteristics and blue whale presence were examined at a range of spatiotemporal scales to investigate sub meso-scale (i.e., <100 km) foraging behaviour. Results suggest that at all scales, Antarctic blue whales are more likely to be detected within the vicinity of krill swarms with a higher density of krill, those found shallower in the water column, and those of greater vertical height. These findings support hypotheses that as lunge-feeders of extreme size, Antarctic blue whales target shallow, dense krill swarms to maximise their energy intake. As both Antarctic krill and blue whales play a key role in the Southern Ocean ecosystem, the nature of their predator-prey dynamics is an important consideration, not only for the recovery of this endangered species in a changing environment, but for the future management of Antarctic krill fisheries.

Characteristics of micro-earthquake swarms preceding eruptions at Showa crater of Sakurajima volcano, Japan

The Showa crater of Sakurajima, an andesitic volcano in Japan, resumed eruptive activity in June 2006 for the first time in 58 years. Explosive eruptions at the Showa crater have been active since 2009. Micro-earthquake swarms have sometimes been observed in the 1 or 2 h preceding these eruptions since 2012 and have frequently occurred during periods of low eruptive activity. These precursory micro-earthquakes are dominated by high-frequency (5–6 Hz) components and no clear S-wave and are thus classified as BH-type earthquake swarms. The hypocenters of the earthquakes are located in a shallow region (depth of approximately 1 km) near the Showa crater. Prior to the eruptions, the onset of inflation has been observed by extensometers, followed by precursory earthquake swarms 30 min to 1 h later. In the case of insufficient ground contraction, the precursory earthquakes reoccur when the strain reaches the same level it showed just before the eruptions occurred. From the occurrence period and pattern of the precursory earthquakes, it appears they may be generated within a narrow conduit leading to the Showa crater.

An experimental study on the characteristics of ejector-generated bubble swarms

In this study, we report an experimental investigation into the bubble generation characteristics of a venturi-type ejector. A 5-mm-diameter vertically upwards nozzle placed in a 1-m3 water tank was used to generate bubbles at between 2 and 20 L/min airflow rate corresponding to a Reynolds number range of 1.7–17 × 103. High-speed photography and image analysis were used for bubble visualisation and feature extraction. An image processing algorithm was used to obtain bubble velocity profiles and size distribution. It was established that when the nozzle was placed at the ejector’s neck, high bubble velocities result, especially at large Reynolds numbers. Bubble size distributions were created, and size variability is strongly correlated with the gas Reynolds number as well as other liquid properties describing gas flow encountering a quiescent bulk liquid.

Light-Controlled Swarming and Assembly of Colloidal Particles.

Swarms and assemblies are ubiquitous in nature and they can perform complex collective behaviors and cooperative functions that they cannot accomplish individually. In response to light, some colloidal particles (CPs), including light active and passive CPs, can mimic their counterparts in nature and organize into complex structures that exhibit collective functions with remote controllability and high temporospatial precision. In this review, we firstly analyze the structural characteristics of swarms and assemblies of CPs and point out that light-controlled swarming and assembly of CPs are generally achieved by constructing light-responsive interactions between CPs. Then, we summarize in detail the recent advances in light-controlled swarming and assembly of CPs based on the interactions arisen from optical forces, photochemical reactions, photothermal effects, and photoisomerizations, as well as their potential applications. In the end, we also envision some challenges and future prospects of light-controlled swarming and assembly of CPs. With the increasing innovations in mechanisms and control strategies with easy operation, low cost, and arbitrary applicability, light-controlled swarming and assembly of CPs may be employed to manufacture programmable materials and reconfigurable robots for cooperative grasping, collective cargo transportation, and micro- and nanoengineering.

Hilara sp. (Diptera: Empididae; Empidinae): Mating System, Swarm Movements, and Inbreeding Avoidance

In a study spanning parts of nine years, an undescribed species of Hilara Meigen was observed to form mating swarms displaying complex behaviors. Typically, swarms were shaped like a flattened torus rotating rapidly about a horizontal axis. Many swarms also moved up and down and turned slowly back-and-forth about a vertical axis. Both up-and-down and turning movements were random in extent and direction, suggesting that they might arise as random, asymmetric density fluctuations within the swarms themselves. A rotating secondary swarm appeared intermittently inside one end of some primary swarms. Swarm membership changed continually as flies left one swarm to join another and as entire swarms coalesced. At one site the set of all swarms displayed properties not found in the swarms individually: spatial extension, daily dissipation and reconstitution over a period of weeks or months, reproductive potential, and gene flow. Such emergent properties qualify the set as a multicomponent swarm, an object heretofore known only in computer models. Hilara sp. appears to be protandrous, univoltine, and promiscuous. Generally, males paired preferentially with somewhat smaller females, but some small and medium-sized males paired with much larger females. Although males of nearly all known Hilara species present nuptial gifts of prey or other items to females, nuptial gifts were not observed at any time during the present study. Many characteristics of swarms of Hilara sp. can be understood as adaptations that reduce inbreeding.

Modified multiple search cooperative foraging strategy for improved artificial bee colony optimization with robustness analysis

Considering that extending the concept of bees partitioning into subgroups of foragers to the onlooker phase of the cooperative learning artificial bee colony (CLABC) strategy is not only feasible from algorithmic viewpoint but might reflect real behavioral foraging characteristics of bee swarms, this paper studies whether the performance of CLABC can be enhanced by developing a new model for the proposed cooperative foraging scheme. Relying on this idea, we design a modified cooperative learning artificial bee colony algorithm, referred to as mCLABC. The design procedure is built upon the definition of a partitioning scheme of onlookers allowing the generation of subgroups of foragers that might evolve differently by using specific solution search rules. In order to improve the involving of local and global search at both employed and onlooker levels, the multiple search mechanism is further tuned and scheduled according to a random selection strategy defined on the evolving parameters. Moreover, a detailed performance and robustness study of the proposed algorithm dealing with the analysis of the impact of different structural and parametric settings is conducted on benchmark optimization problems. Superior convergence performance, better solution quality, and strong robustness are the main features of the proposed strategy in comparison with recent ABC variants and advanced methods.

Age and Geochemical Characteristics of Major Mafic Dyke Swarms in the Southern Part of the Siberian Craton

Age and Geochemical Characteristics of Major Mafic Dyke Swarms in the Southern Part of the Siberian Craton