Bulletin of the American Physical Society
APS March Meeting 2017
Volume 62, Number 4
Monday–Friday, March 13–17, 2017; New Orleans, Louisiana
Session H14: Collective Dynamics: Fluid Physics of LifeFocus
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Sponsoring Units: GSNP DBIO Chair: Nicholas Ouellette, Stanford University Room: 273 |
Tuesday, March 14, 2017 2:30PM - 3:06PM |
H14.00001: Cilia-based transport networks Invited Speaker: Eberhard Bodenschatz Cerebrospinal fluid conveys many physiologically important signaling factors through the ventricular cavities of the brain. We investigated the transport of cerebrospinal fluid in the third ventricle of the mouse brain and discovered a highly organized pattern of cilia modules, which collectively give rise to a network of fluid flows that allows for precise transport within this ventricle. ~Our work suggests that ciliated epithelia can generate and maintain complex, spatiotemporally regulated flow networks. I shall also show results on how to assemble artificial cilia and cilia carpets. [Preview Abstract] |
Tuesday, March 14, 2017 3:06PM - 3:18PM |
H14.00002: From single cilia to collective waves in human airway ciliated tissues Pietro Cicuta, Maurizio Chioccioli, Luigi Feriani, Nicola Pellicciotta, Jurij Kotar I will present experimental results on activity of motile cilia on various scales: from waveforms on individual cilia to the synchronised motion in cilia carpets of airway cells. Model synthetic experiments have given us an understanding of how cilia could couple with each other through forces transmitted by the fluid, and thus coordinate to beat into well organized waves (previous work is reviewed in Annu. Rev. Condens. Matter Phys. 7, 1-26 (2016)). Working with live imaging of airway human cells at the different scales, we can now test whether the biological system satisfies the ``simple" behavior expected of the fluid flow coupling, or if other factors of mechanical forces transmission need to be accounted for. In general being able to link from the scale of molecular biological activity up to the phenomenology of collective dynamics requires to understand the relevant physical mechanism. This understanding then allows informed diagnostics (and perhaps therapeutic) approaches to a variety of diseases where mucociliary clearance in the airways is compromised. We have started exploring particularly cystic fibrosis, where the rheological properties of the mucus are affected and prevent efficient cilia synchronization. [Preview Abstract] |
Tuesday, March 14, 2017 3:18PM - 3:30PM |
H14.00003: Self mixing of fly larvae during feeding Olga Shishkov, Christopher Johnson, David Hu How do we sustainably feed a growing world population? One solution of increasing interest is the use of black solider fly larvae, pea-sized grubs envisioned to transform hundreds of tons of food waste into a sustainable protein source. Although startups across the world are raising these larvae, a physical understanding of how they should be raised and fed remains missing. In this study, we present experiments measuring their feeding rate as a function of number of larvae. We show that larger groups of larvae have greater mixing which entrains hungry larvae around the food, increasing feeding rate. Feeding of larvae thus differs from feeding of cattle or other livestock which exhibit less self-mixing. [Preview Abstract] |
Tuesday, March 14, 2017 3:30PM - 3:42PM |
H14.00004: Jammed Humans in High-Density Crowd Disasters Arianna Bottinelli, David Sumpter, Jesse Silverberg When people gather in large groups like those found at Black Friday sales events, pilgrimages, heavy metal concerts, and parades, crowd density often becomes exceptionally high. As a consequence, these events can produce tragic outcomes such as stampedes and "crowd crushes". While human collective motion has been studied with active particle simulations, the underlying mechanisms for emergent behavior are less well understood. Here, we use techniques developed to study jammed granular materials to analyze an active matter model inspired by large groups of people gathering at a point of common interest. In the model, a single behavioral rule combined with body-contact interactions are sufficient for the emergence of a self-confined steady state, where particles fluctuate around a stable position. Applying mode analysis to this system, we find evidence for Goldstone modes, soft spots, and stochastic resonance, which may be the preferential mechanisms for dangerous emergent collective motions in crowds. [Preview Abstract] |
Tuesday, March 14, 2017 3:42PM - 3:54PM |
H14.00005: Spatial organization and Synchronization in collec- tive swimming of Hemigrammus bleheri Benjamin Thiria, Ramiro Godoy-Diana, Intesaaf Ashraf, Tung Ha Thanh, Hanae Bradshaw In this work, we study the collective swimming of Hemigrammus bleheri fish using experiments in a shallow swimming channel. We use high-speed video recordings to track the midline kinematics and the spatial organization of fish pairs and triads. Synchronizations are characterized by observance of ''out of phase'' and ''in phase'' configurations. We show that the synchronization state is highly correlated to swimming speed. The increase in synchro- nization led to efficient swimming based on Strouhal number. In case of fish pairs, the collective swimming is 2D and the spatial organization is characterized by two characteristic lengths: the lateral and longitudinal separation distances between fish pairs. For fish triads, different swim- ming patterns or configurations are observed having three dimensional structures. We performed 3D kinematic analysis by employing 3D re- construction using the Direct Linear Transformation (DLT). We show that fish still keep their nearest neighbor distance (NND) constant ir- respective of swimming speeds and configuration. We also point out characteristic angles between neighbors, hence imposing preferred pat- terns. At last we will give some perspectives on spatial organization for larger population. [Preview Abstract] |
Tuesday, March 14, 2017 3:54PM - 4:06PM |
H14.00006: Viscoelasticity promotes collective swimming of sperm Chih-Kuan Tung, Benedict B. Harvey, Alyssa G. Fiore, Florencia Ardon, Susan S. Suarez, Mingming Wu From flocking birds to swarming insects, interactions of organisms large and small lead to the emergence of collective dynamics. Here, we report striking collective swimming of bovine sperm, with sperm orienting in the same direction within each cluster, enabled by the viscoelasticity of the fluid. A long-chain polyacrylamide solution was used as a model viscoelastic fluid such that its rheology can be fine-tuned to mimic that of bovine cervical mucus. In viscoelastic fluid, sperm formed dynamic clusters, and the cluster size increased with elasticity of the polyacrylamide solution. In contrast, sperm swam randomly and individually in Newtonian fluids of similar viscosity. Analysis of the fluid motion surrounding individual swimming sperm indicated that sperm-fluid interaction is facilitated by the elastic component of the fluid. We note that almost all biological fluids (e.g. mucus and blood) are viscoelastic in nature, this finding highlights the importance of fluid elasticity in biological function. We will discuss what the orientation fluctuation within a cluster reveals about the interaction strength. [Preview Abstract] |
Tuesday, March 14, 2017 4:06PM - 4:18PM |
H14.00007: Coarsening dynamics in the Vicsek model Supravat Dey, Nisha Katyal, Dibyendu Das, Sanjay Puri We numerically study the flocking model introduced by Vicsek et al. (1995) in the coarsening regime. At standard self-propulsion speeds, we find two distinct growth laws for the coupled density and velocity fields. The characteristic length scale of the density domains grows as $L_{\rho}(t) \sim t^{1/4}$, while the velocity length scale grows much faster, $viz.$, $L_{v}(t) \sim t^{5/6}$. The spatial fluctuations in the density and velocity ordering are studied by calculating the two-point correlation function and the structure factor, which show deviations from the well-known Porod's law. This is a natural consequence of scattering from irregular morphologies that dynamically arise in the system. In contrast, at lower self-propulsion speeds, the morphology is distinct, and as a result a new set of scaling exponents emerge. Most strikingly, the velocity order follows the density order with $L_{\rho}(t) \sim L_v(t) \sim t^{1/4}$. [Preview Abstract] |
Tuesday, March 14, 2017 4:18PM - 4:30PM |
H14.00008: The Density Functional Theory of Flies: Predicting distributions of interacting active organisms Yunus Kinkhabwala, Juan Valderrama, Itai Cohen, Tomas Arias On October 2$^{\mathrm{nd}}$, 2016, 52 people were crushed in a stampede when a crowd panicked at a religious gathering in Ethiopia. ~The ability to predict the state of a crowd and whether it is susceptible to such transitions could help prevent such catastrophes. While current techniques such as agent based models can predict transitions in emergent behaviors of crowds, the assumptions used to describe the agents are often ad hoc and the simulations are computationally expensive making their application to real-time crowd prediction challenging. ~Here, we pursue an orthogonal approach and ask whether a reduced set of variables, such as the local densities, are sufficient to describe the state of a crowd. Inspired by the theoretical framework of Density Functional Theory, we have developed a system that uses only measurements of local densities to extract two independent crowd behavior functions: (1) preferences for locations and (2) interactions between individuals. With these two functions, we have accurately predicted how a model system of walking \textit{Drosophila melanogaster} distributes itself in an arbitrary 2D environment. In addition, this density-based approach measures properties of the crowd from only observations of the crowd itself without any knowledge of the detailed interactions and thus it can make predictions about the resulting distributions of these flies in arbitrary environments, in real-time. [Preview Abstract] |
Tuesday, March 14, 2017 4:30PM - 4:42PM |
H14.00009: Long-range Acoustic Interactions in Insect Swarms - An Adaptive Gravity Model Dan Gorbonos, Reuven Ianconescu, James G. Puckett, Rui Ni, Nicholas T. Ouellette, Nir S. Gov The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. We consider mating swarms of midges, which are thought to interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our ``adaptive gravity'' model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. Additionally, the adaptive interactions open a new class of equations of motion, which may appear in other biological contexts. [Preview Abstract] |
Tuesday, March 14, 2017 4:42PM - 4:54PM |
H14.00010: A persistent homology approach to collective behavior in insect swarms Michael Sinhuber, Nicholas T. Ouellette Various animals from birds and fish to insects tend to form aggregates, displaying self-organized collective swarming behavior. Due to their frequent occurrence in nature and their implications for engineered, collective systems, these systems have been investigated and modeled thoroughly for decades. Common approaches range from modeling them with coupled differential equations on the individual level up to continuum approaches. We present an alternative, topology-based approach for describing swarming behavior at the macroscale rather than the microscale. We study laboratory swarms of Chironomus riparius, a flying, non-biting midge. To obtain the time-resolved three-dimensional trajectories of individual insects, we use a multi-camera stereoimaging and particle-tracking setup. To investigate the swarming behavior in a topological sense, we employ a persistent homology approach to identify persisting structures and features in the insect swarm that elude a direct, ensemble-averaging approach. We are able to identify features of sub-clusters in the swarm that show behavior distinct from that of the remaining swarm members. The coexistence of sub-swarms with different features resembles some non-biological systems such as active colloids or even thermodynamic systems. [Preview Abstract] |
Tuesday, March 14, 2017 4:54PM - 5:06PM |
H14.00011: Using light gradients to investigate symmetry breaking in fish schools James Puckett, Julia Giannini Theoretical models of social animals successfully reproduce many structures found in nature (e.g. swarms, flocks, mills) using simple interaction rules. However, the interactions between individuals is complex and undoubtedly depends on the environment. Using schools of fish, we use visual perturbations to investigate how individuals negotiate both social and environmental information to reach a consensus. Starting with an unpolarized school of fish, we examine how the symmetry is broken and find that not all fish contribute equally to this decision. [Preview Abstract] |
Tuesday, March 14, 2017 5:06PM - 5:18PM |
H14.00012: Imaging the onset kinetics of the swarming transition using light-controlled bacteria Yi Peng, Yishu Tai, Kechun Zhang, Xiang Cheng Active fluids are a novel class of nonequilibrium soft materials, which are composed of a large number of self-propelled particles. These particles collectively form coherent structures at high densities, as illustrated vividly by the striking patterns of flocking birds, schooling fishes and swarming bacteria. Although the disorder-swarming transition of active fluids has been extensively studied, its very nature is still under heated debate. Here, using an engineered E. coli strain, whose locomotion can be reversibly controlled by light, we experimentally study the onset of the swarming transition of active fluids and explore its kinetic pathway. Particularly, we trigger bacterial swarming using a blue light and image the emergence of the collective structure in concentrated bacterial suspensions. We find a discontinuous jump in the order parameter of the transition and observe a hysteresis in the formation of swarming, which indicate the discontinuous nature. We further investigate the microscopic dynamics in the context of nucleation-and-growth processes and measure the incubation time and the size distribution of nuclei. Our study sheds light on the phase transition of active fluids and the emergent properties of many-body nonequilibrium systems. [Preview Abstract] |
Tuesday, March 14, 2017 5:18PM - 5:30PM |
H14.00013: Pattern-fluid interpretation of chemical turbulence Gerd Schroeder-Turk, Christian Scholz, Klaus Mecke The spontaneous formation of heterogeneous patterns is a hallmark of many nonlinear systems, from biological tissue to evolutionary population dynamics. The standard model for pattern formation in general, and for Turing patterns in chemical reaction-diffusion systems in particular, are deterministic nonlinear partial differential equations where an unstable homogeneous solution gives way to a stable heterogeneous pattern. However, these models fail to fully explain the experimental observation of turbulent patterns with spatio-temporal disorder in chemical systems. Here we introduce a pattern-fluid model as a general concept where turbulence is interpreted as a weakly interacting ensemble obtained by random superposition of stationary solutions to the underlying reaction-diffusion system. The transition from turbulent to stationary patterns is then interpreted as a condensation phenomenon, where the nonlinearity forces one single mode to dominate the ensemble. This model leads to better reproduction of the experimental concentration profiles for the ``stationary phases'' and reproduces the turbulent chemical patterns observed by in Chaos 1, 411, 1991. This abstract represents the work published in PRE 91, 042907, 2015. [Preview Abstract] |
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