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The formation of congestion on an urban road network is a key issue for the development of sustainable mobility in future smart cities. In this work, we propose a reductionist approach by studying the stationary states of a simple transport model using a random process on a graph, where each node represents a location and the link weights give the transition rates to move from one node to another, representing the mobility demand. Each node has a maximum flow rate and a maximum load capacity, and we assume that the average incoming flow equals the outgoing flow. In the approximation of the single-step process, we are able to analytically characterize the traffic load distribution on the single nodes using a local maximum entropy principle. Our results explain how congested nodes emerge as the total traffic load increases, analogous to a percolation transition where the appearance of a congested node is an independent random event. However, using numerical simulations, we show that in the more realistic case of synchronous dynamics for the nodes, entropic forces introduce correlations among the node states and favor the clustering of empty and congested nodes. Our aim is to highlight the universal properties of congestion formation and, in particular, to understand the role of traffic load fluctuations as a possible precursor of congestion in a transport network.

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Biopolymer networks play a major role as part of the cytoskeleton. They provide stable structures and act as a medium for signal transport. These features encourage the application of such networks as organic computation devices. While research on this topic is not advanced yet, previous results are very promising. The protein actin in particular appears advantageous. It can be arranged to various stable structures and transmit several signals. In this study aster shaped networks were self-assembled via entropic forces by the crowding agent methyl cellulose. These networks are characterised by a regular and uniquely thick bundle structure, but have so far only been accounted in droplets of 100 µm diameter. We report now regular asters in an area of a few mm2 that could be observed even after months. Such stability outside of an organism is striking and underlines the great potential actin aster networks display.

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Living cells are complex systems characterized by fluids crowded by hundreds of different elements, including, in particular, a high density of polymers. They are an excellent and challenging laboratory to study exotic emerging physical phenomena, where entropic forces emerge from the organization processes of many-body interactions. The competition between microscopic and entropic forces may generate complex behaviors, such as phase transitions, which living cells may use to accomplish their functions. In the era of big data, where biological information abounds, but general principles and precise understanding of the microscopic interactions is scarce, entropy methods may offer significant information. In this work, we developed a model where a complex thermodynamic equilibrium resulted from the competition between an effective electrostatic short-range interaction and the entropic forces emerging in a fluid crowded by different sized polymers. The target audience for this article are interdisciplinary researchers in complex systems, particularly in thermodynamics and biophysics modeling.

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To explain the increased transport of nutrients and metabolites and to control the movement of drug molecules through the transporters to the cancer cells, it is important to understand the exact mechanism of their structure and activity, as well as their biological and physical characteristics. We propose a computational model that reproduces the functionality of membrane transporters by quantifying the flow of substrates through the cell membrane. The model identifies the force induced by conformational changes of the transporter due to hydrolysis of ATP, in ABC transporters, or by an electrochemical gradient of ions, in secondary transporters. The transport rate is computed by averaging the velocity generated by the force along the paths followed by the substrates. The results obtained are in accordance with the experiments. The model provides an overall framework for analyzing the membrane transport proteins that regulate the flows of ions, nutrients and other molecules across the cell membranes, and their activities.

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In this review, previous researches that measured intermembrane forces using the Surface Forces Apparatus are recapitulated. Different types of interaction forces are reported between two lipid bilayers including non-specific interactions (e.g., van der Waals, electrostatic, steric hydration, thermal undulation, and hydrophobic) and specific interactions (e.g., ligand-receptor). By measuring absolute distance and interaction forces at the sub-angstrom level and at a few nano-Newtons resolution, respectively, magnitudes, working ranges, and decay lengths of interaction between lipid bilayers are investigated. Utilizing recently developed fluorescence microscopy attachments, simultaneous fluorescence imaging of membrane proteins and lipid phases can be performed during approach/separation cycles of two lipid bilayer deposited surfaces, which can reveal cooperative effects between lipid phases and various types of membrane proteins.

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Macromolecular crowding plays a principal role in a wide range of biological processes including gene expression, chromosomal compaction, and viral infection. However, the impact that crowding has on the dynamics of nucleic acids remains a topic of debate. To address this problem, we use single-molecule fluorescence microscopy and custom particle-tracking algorithms to investigate the impact of varying macromolecular crowding conditions on the transport and conformational dynamics of large DNA molecules. Specifically, we measure the mean-squared center-of-mass displacements, as well as the conformational size, shape, and fluctuations, of individual 115 kbp DNA molecules diffusing through various in vitro solutions of crowding polymers. We determine the role of crowder structure and concentration, as well as ionic conditions, on the diffusion and configurational dynamics of DNA. We find that branched, compact crowders (10 kDa PEG, 420 kDa Ficoll) drive DNA to compact, whereas linear, flexible crowders (10, 500 kDa dextran) cause DNA to elongate. Interestingly, the extent to which DNA mobility is reduced by increasing crowder concentrations appears largely insensitive to crowder structure (branched vs. linear), despite the highly different configurations DNA assumes in each case. We also characterize the role of ionic conditions on crowding-induced DNA dynamics. We show that both DNA diffusion and conformational size exhibit an emergent non-monotonic dependence on salt concentration that is not seen in the absence of crowders.

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The cytoskeleton is a network of interconnected protein filaments, which provide a three-dimensional scaffold for cells. Remodeling of the cytoskeleton is important for key cellular processes, such as cell motility, division, or morphogenesis. This remodeling is traditionally considered to be driven exclusively by processes consuming chemical energy, such as the dynamics of the filaments or the action of molecular motors. Here, we review two mechanisms of cytoskeletal network remodeling that are independent of the consumption of chemical energy. In both cases directed motion of overlapping filaments is driven by entropic forces, which arise from harnessing thermal energy present in solution. Entropic forces are induced either by macromolecular crowding agents or by diffusible crosslinkers confined to the regions where filaments overlap. Both mechanisms increase filament overlap length and lead to the contraction of filament networks. These force-generating mechanisms, together with the chemical energy-dependent mechanisms, need to be considered for the comprehensive quantitative picture of the remodeling of cytoskeletal networks in cells.

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We identify a unique viewpoint on the collective behaviour of intelligent agents. We first develop a highly general abstract model for the possible future lives these agents may encounter as a result of their decisions. In the context of these possibilities, we show that the causal entropic principle, whereby agents follow behavioural rules that maximize their entropy over all paths through the future, predicts many of the observed features of social interactions among both human and animal groups. Our results indicate that agents are often able to maximize their future path entropy by remaining cohesive as a group and that this cohesion leads to collectively intelligent outcomes that depend strongly on the distribution of the number of possible future paths. We derive social interaction rules that are consistent with maximum entropy group behaviour for both discrete and continuous decision spaces. Our analysis further predicts that social interactions are likely to be fundamentally based on Weber's law of response to proportional stimuli, supporting many studies that find a neurological basis for this stimulus-response mechanism and providing a novel basis for the common assumption of linearly additive 'social forces' in simulation studies of collective behaviour.

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The relationship between colloidal building blocks and their assemblies is an active field of research. As a strategy for targeting novel crystal structures, we examine the use of Voronoi particles, which are hard, space-filling particles in the shape of Voronoi cells of a target structure. Although Voronoi particles stabilize their target structure in the limit of high pressure by construction, the thermodynamic assembly of the same structure at moderate pressure, close to the onset of crystallization, is not guaranteed. Indeed, we find that a more symmetric crystal is often preferred due to additional entropic contributions arising from configurational or occupational degeneracy. We characterize the assembly behavior of the Voronoi particles in terms of the symmetries of the building blocks as well as the symmetries of crystal structures and demonstrate how controlling the degeneracies through a modification of particle shape and field-directed assembly can significantly improve the assembly propensity.

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Sinorhizobium meliloti growing on soft agar can exhibit an unusual surface spreading behaviour that differs from other bacterial surface motilities. Bacteria in the colony secrete an exopolysaccharide-rich mucoid fluid that expands outward on the surface, carrying within it a suspension of actively dividing cells. The moving slime disperses the cells in complex and dynamic patterns indicative of simultaneous bacterial growth, swimming and aggregation. We find that while flagellar swimming is required to maintain the cells in suspension, the spreading and the associated pattern formation are primarily driven by the secreted exopolysaccharide EPS II, which creates two entropy-increasing effects: an osmotic flow of water from the agar to the mucoid fluid and a crowding or depletion attraction between the cells. Activation of these physical/chemical phenomena may be a useful function for the high molecular weight EPS II, a galactoglucan whose biosynthesis is tightly regulated by the ExpR/SinI/SinR quorum-sensing system: unlike bacterial colonies that spread via bacterium-generated, physical propulsive forces, S. meliloti under quorum conditions may use EPS II to activate purely entropic forces within its environment, so that it can disperse by passively 'surfing' on those forces.

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