arXiv subjects

Jesse L. Silverberg

Publications and source records attributed to Jesse L. Silverberg.

8 recordsLinked to original sources

arXiv2019

Population stability risks and biophysical benefits of cell-cell fusion in macrophage, osteoclast, and giant multinucleated cells

Plant and animal cells are commonly understood as acquiring specialized functions through differentiation and asymmetric division. However, unique capabilities are also acquired when two or more cells fuse together, mixing cytoplasmic and genetic material. Here, we combine imaging experiments with biophysical modeling to perform the first risk-benefit analysis of cell-cell fusion. On one hand, we find fusion introduces an intrinsic instability to the population dynamics. On the other hand, we measure an unusual physiological scaling suggesting these cells grow substantially larger at lower energetic costs. Further analysis of the cytoskeleton finds a size-associated phase separation of F-actin that self-organizes multinucleated cell phenotypes.

physics.bio-ph↗

arXiv2019

Cyber-physical risks of hacked Internet-connected vehicles

The integration of automotive technology with Internet-connectivity promises to both dramatically improve transportation, while simultaneously introducing the potential for new unknown risks. Internet-connected vehicles are like digital data because they can be targeted for malicious hacking. Unlike digital data, however, Internet-connected vehicles are cyber-physical systems that physically interact with each other and their environment. As such, the extension of cybersecurity concerns into the cyber-physical domain introduces new possibilities for self-organized phenomena in traffic flow. Here, we study a scenario envisioned by cybersecurity experts leading to a large number of Internet-connected vehicles being suddenly and simultaneously disabled. We investigate post-hack traffic using agent-based simulations, and discover the critical relevance of percolation for probabilistically predicting the outcomes on a multi-lane road in the immediate aftermath of a vehicle-targeted cyber attack. We develop an analytic percolation-based model to rapidly assess road conditions given the density of disabled vehicles and apply it to study the street network of Manhattan (NY, USA) revealing the city's vulnerability to this particular cyber-physical attack.

cs.CR↗

arXiv2018

Can high-density human collective motion be forecasted by spatiotemporal fluctuations?

Concerts, protests, and sporting events are occurring with increasing frequency and magnitude. The extreme physical conditions common to these events are known to cause injuries and loss-of-life due to the emergence of collective motion such as crowd crush, turbulence, and density waves. Mathematical models of human crowds aimed at enhancing crowd safety by understanding these phenomena are developed with input from a variety of disciplines. However, model validation is challenged by a lack of high-quality empirical data and ethical constraints surrounding human crowd research. Consequently, generalized model-based approach for real-time monitoring/risk-assessment of crowd collective motion remains an open problem. Here, we take a model-free approach to crowd analysis and show that emergent collective motion can be forecasted directly from video data. We use mode analysis methods from material science and concepts from non-equilibrium physics to study footage of a human crowd at an Oasis rock concert. We analyze the attendees positional fluctuations during a period of crowd turbulence to predict the spatial patterns of an emergent human density wave. In addition to predicting spatial patterns of collective motion, we also identify and measure temporal patterns that precede the density wave and forecast its appearance by 1~s. Looking ahead, widening this forecasting window beyond 1~s will enable new computer vision technologies for real-time risk-assessment of emergent human collective motion.

physics.soc-ph↗

arXiv2018

Collective behavior and emergent risks in a model of human- and autonomously-driven vehicles

While much effort has been invested in studies of traffic flow as a physics problem, two emerging trends in technology have broadened the subject for new investigations. The first trend is the development of self-driving vehicles. This highly-anticipated shift from human- to autonomous-drivers is expected to offer substantial benefits for traffic throughput by streamlining large-scale collective behavior. The second trend is the widespread hacking of Internet-connected devices, which as of 2015, includes vehicles. While the first proof-of-concept automobile hack was done at the single-vehicle scale, undesirable collective effects can easily arise if this activity becomes more common. Motivated by these two trends, we explore the phenomena that arise in an active matter model with lanes and lane-changing behavior. Our model incorporates a simplified minimal description of essential differences between human- and autonomous-drivers. We study the emergent collective behavior as the population of vehicles shifts from all-human to all-autonomous. Within the context of our model, we explore a worst-case scenario where Internet-connected autonomous vehicles are disabled simultaneously and \textit{en masse}. Our approach reveals a model-independent role for percolation in interpreting the results. A broad lesson our work highlights is that seemingly minor malicious activity can ultimately have major impacts when magnified through the action of collective behavior.

physics.soc-ph↗

arXiv2017

Sculpting the Vertex: Manipulating the Configuration Space Topography and Topology of Origami Vertices to Design Mechanical Robustness

The geometric, aesthetic, and mathematical elegance of origami is being recognized as a powerful pathway to self-assembly of micro and nano-scale machines with programmable mechanical properties. The typical approach to designing the mechanical response of an ideal origami machine is to include mechanisms where mechanical constraints transform applied forces into a desired motion along a narrow set of degrees of freedom. In fact, to date, most design approaches focus on building up complex mechanisms from simple ones in ways that preserve each individual mechanism's degree of freedom (DOF), with examples ranging from simple robotic arms to homogenous arrays of identical vertices, such as the well-known Miura-ori. However, such approaches typically require tight fabrication tolerances, and often suffer from parasitic compliance. In this work, we demonstrate a technique in which high-degree-of-freedom mechanisms associated with single vertices are heterogeneously combined so that the coupled phase spaces of neighboring vertices are pared down to a controlled range of motions. This approach has the advantage that it produces mechanisms that retain the DOF at each vertex, are robust against fabrication tolerances and parasitic compliance, but nevertheless effectively constrain the range of motion of the entire machine. We demonstrate the utility of this approach by mapping out the configuration space for the modified Miura-ori vertex of degree 6, and show that when strung together, their combined configuration spaces create mechanisms that isolate deformations, constrain the configuration topology of neighboring vertices, or lead to sequential bistable folding throughout the entire origami sheet.

cond-mat.soft↗

arXiv2016

Emergent Structural Mechanisms for High-Density Collective Motion Inspired by Human Crowds

Collective motion of large human crowds often depends on their density. In extreme cases like heavy metal concerts and Black Friday sales events, motion is dominated by physical interactions instead of conventional social norms. Here, we study an active matter model inspired by situations when large groups of people gather at a point of common interest. Our analysis takes an approach developed for jammed granular media and identifies Goldstone modes, soft spots, and stochastic resonance as structurally-driven mechanisms for potentially dangerous emergent collective motion.

physics.soc-ph↗

arXiv2015

Lattice Mechanics of Origami Tessellations

Origami-based design holds promise for developing materials whose mechanical properties are tuned by crease patterns introduced to thin sheets. Although there has been heuristic developments in constructing patterns with desirable qualities, the bridge between origami and physics has yet to be fully developed. To truly consider origami structures as a class of materials, methods akin to solid mechanics need to be developed to understand their long-wavelength behavior. We introduce here a lattice theory for examining the mechanics of origami tessellations in terms of the topology of their crease pattern and the relationship between the folds at each vertex. This formulation provides a general method for associating mechanical properties with periodic folded structures, and allows for a concrete connection between more conventional materials and the mechanical metamaterials constructed using origami-based design.

cond-mat.soft↗

arXiv2013

Collective Motion of Moshers at Heavy Metal Concerts

Human collective behavior can vary from calm to panicked depending on social context. Using videos publicly available online, we study the highly energized collective motion of attendees at heavy metal concerts. We find these extreme social gatherings generate similarly extreme behaviors: a disordered gas-like state called a mosh pit and an ordered vortex-like state called a circle pit. Both phenomena are reproduced in flocking simulations demonstrating that human collective behavior is consistent with the predictions of simplified models.

physics.soc-ph↗