Publications by authors named "Solon A"

We propose a hydrodynamic description of the homogeneous ordered phase of polar flocks. Starting from symmetry principles, we construct the appropriate equation for the dynamics of the Goldstone mode associated with the broken rotational symmetry. We then focus on the two-dimensional case considering both "Malthusian flocks" for which the density field is a fast variable that does not enter the hydrodynamic description and "Vicsek flocks" for which it does.

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We study the stability of the ordered phase of flocking models with a scalar order parameter. Using both the active Ising model and a hydrodynamic description, we show that droplets of particles moving in the direction opposite to that of the ordered phase nucleate and grow. We characterize analytically this self-similar growth and demonstrate that droplets spread ballistically in all directions.

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Article Synopsis
  • Adrenocortical carcinoma (ACC) is a rare and deadly cancer characterized by a specific subtype called CIMP-high, which is associated with abnormal DNA methylation and mutations in β-catenin.
  • Research shows that the differentiation in CIMP-high ACC relies on a complex interaction between β-catenin and certain transcription factors, maintaining its cancerous state throughout its development.
  • Targeting the epigenetic regulator EZH2 can disrupt these interactions, leading to reduced tumor growth and presenting a potential therapeutic approach for treating β-catenin-driven cancers.
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We study numerically the Toner-Tu field theory where the density field is maintained constant, a limit case of "Malthusian" flocks for which the asymptotic scaling of correlation functions in the ordered phase is known exactly. While we confirm these scaling laws, we also show that such constant-density flocks are metastable to the nucleation of a specific defect configuration, and are replaced by a globally disordered phase consisting of asters surrounded by shock lines that constantly evolves and remodels itself. We demonstrate that the main source of disorder lies along shock lines, rendering this active foam fundamentally different from the corresponding equilibrium system.

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We study the one-dimensional active Ising model in which aligning particles undergo diffusion biased by the signs of their spins. The phase diagram obtained varying the density of particles, their hopping rate, and the temperature controlling the alignment shows a homogeneous disordered phase but no homogeneous ordered one, as well as two phases with localized dense structures. In the flocking phase, large ordered aggregates move ballistically and stochastically reverse their direction of motion.

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Mitosis is the cellular process that ensures accurate segregation of the cell's genetic material into two daughter cells. Mitosis is often deregulated in cancer; thus drugs that target mitosis-specific proteins represent attractive targets for anticancer therapy. Numerous inhibitors have been developed against kinesin-5 Eg5, a kinesin essential for bipolar spindle assembly.

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Species composition in high-alpine ecosystems is a useful indicator for monitoring climatic and environmental changes at the upper limits of habitable environments. We used environmental DNA (eDNA) analysis to document the breadth of high-alpine biodiversity present on Earth's highest mountain, Mt. Everest (8,849 m a.

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Mixtures of active and passive particles are predicted to exhibit a variety of nonequilibrium phases. Here we report a dynamic clustering phase in mixtures of colloids and motile bacteria. We show that colloidal clustering results from a balance between bond breaking due to persistent active motion and bond stabilization due to torques that align active particle velocity tangentially to the passive particle surface.

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We study the effect of spatial anisotropy on polar flocks by investigating active q-state clock models in two dimensions. In contrast to the equilibrium case, we find that any amount of anisotropy is asymptotically relevant, drastically altering the phenomenology from that of the rotationally invariant case. All of the well-known physics of the Vicsek model, from giant density fluctuations to microphase separation, is replaced by that of the active Ising model, with short-range correlations and complete phase separation.

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From the aboveground vegetation to the belowground microbes, terrestrial communities differ between the highly divergent alpine (above treeline) and subalpine (below treeline) ecosystems. Yet, much less is known about the partitioning of microbial communities between alpine and subalpine lakes. Our goal was to determine whether the composition of bacterioplankton communities of high-elevation mountain lakes differed across treeline, identify key players in driving the community composition, and identify potential environmental factors that may be driving differences.

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Mitotic kinesins play essential roles during mitotic spindle assembly and in ensuring proper chromosome segregation. Chemical inhibitors of mitotic kinesins are therefore valuable tools to study kinesin function in vitro and in cells. Because cancer is a disease of unregulated cell division, inhibitors also represent potential chemotherapeutic agents.

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Kinesins are regulated in space and time to ensure activation only in the presence of cargo. Kinesin-binding protein (KIFBP), which is mutated in Goldberg-Shprintzen syndrome, binds to and inhibits the catalytic motor heads of 8 of 45 kinesin superfamily members, but the mechanism remains poorly defined. Here, we used cryo–electron microscopy and cross-linking mass spectrometry to determine high-resolution structures of KIFBP alone and in complex with two mitotic kinesins, revealing structural remodeling of kinesin by KIFBP.

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The mitotic spindle, a self-constructed microtubule-based machine, segregates chromosomes during cell division. In mammalian cells, microtubule bundles called kinetochore fibers (k-fibers) connect chromosomes to the spindle poles. Chromosome segregation thus depends on the mechanical integrity of k-fibers.

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Cold, dry, and nutrient-poor, the McMurdo Dry Valleys of Antarctica are among the most extreme terrestrial environments on Earth. Numerous studies have described microbial communities of low elevation soils and streams below glaciers, while less is known about microbial communities in higher elevation soils above glaciers. We characterized microbial life in four landscape features (habitats) of a mountain in Taylor Valley.

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We study the role of noise on the nature of the transition to collective motion in dry active matter. Starting from field theories that predict a continuous transition at the deterministic level, we show that fluctuations induce a density-dependent shift of the onset of order, which in turn changes the nature of the transition into a phase-separation scenario. Our results apply to a range of systems, including models in which particles interact with their "topological" neighbors that have been believed so far to exhibit a continuous onset of order.

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The island species-area relationship (ISAR) is a positive association between the number of species and the area of an isolated, island-like habitat. ISARs are ubiquitous across domains of life, yet the processes generating ISARs remain poorly understood, particularly for microbes. Larger and more productive islands are hypothesized to have more species because they support larger populations of each species and thus reduce the probability of stochastic extinctions in small population sizes.

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We revisit motility-induced phase separation in two models of active particles interacting by pairwise repulsion and uncover new qualitative features: the resulting dense phase contains gas bubbles distributed algebraically up to a typically extremely large cutoff scale. At large enough system size and/or global density, all the gas may be contained inside the bubbles, at which point the system is microphase separated with a finite cutoff bubble scale. We further observe that the ordering is clearly anomalous, with different dynamics for the coarsening of the dense phase and of the gas bubbles.

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Activity and autonomous motion are fundamental in living and engineering systems. This has stimulated the new field of 'active matter' in recent years, which focuses on the physical aspects of propulsion mechanisms, and on motility-induced emergent collective behavior of a larger number of identical agents. The scale of agents ranges from nanomotors and microswimmers, to cells, fish, birds, and people.

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The effects of quenched disorder on a single and many active run-and-tumble particles are studied in one dimension. For a single particle, we consider both the steady-state distribution and the particle's dynamics subject to disorder in three parameters: a bounded external potential, the particle's speed, and its tumbling rate. We show that in the case of a disordered potential, the behavior is like an equilibrium particle diffusing on a random force landscape, implying a dynamics that is logarithmically slow in time.

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Deep convolutional neural networks (CNN) have previously been shown to be useful tools for signal decoding and analysis in a variety of complex domains, such as image processing and speech recognition. By learning from large amounts of data, the representations encoded by these deep networks are often invariant to moderate changes in the underlying feature spaces. Recently, we proposed a CNN architecture that could be applied to electroencephalogram (EEG) decoding and analysis.

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We study the linear response of interacting active Brownian particles in an external potential to simple shear flow. Using a path integral approach, we derive the linear response of any state observable to initiating shear in terms of correlation functions evaluated in the unperturbed system. For systems and observables which are symmetric under exchange of the x and y coordinates, the response formula can be drastically simplified to a form containing only state variables in the corresponding correlation functions (compared to the generic formula containing also time derivatives).

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Although cryoconite holes, sediment-filled melt holes on glacier surfaces, appear small and homogenous, their microbial inhabitants may be spatially partitioned. This partitioning could be particularly important for maintaining biodiversity in holes that remain isolated for many years, such as in Antarctica. We hypothesized that cryoconite holes with greater species richness and biomass should exhibit greater partitioning between the sediments and water, promoting greater biodiversity through spatial niche partitioning.

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P300-based brain-computer interfaces (BCIs) are often trained per-user and per-application space. Training such models requires ground truth knowledge of target and nontarget stimulus categories during model training, which imparts bias into the model. Additionally, not all non-targets are created equal; some may contain visual features that resemble targets or may otherwise be visually salient.

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Here, we review the current state of knowledge concerning high-elevation members of the extremophilic clade (now classified as the genus ). These fungi dominate eukaryotic microbial communities across the highest elevation, soil-like material (tephra) on volcanoes such as Llullaillaco, Socompa, and Saírecabur in the Atacama region of Chile, Argentina, and Bolivia. Recent studies indicate that species are among the most resistant organisms to UV radiation, and a strain of from Volcán Llullaillaco is the first organism that is known to grow during the extreme, diurnal freeze-thaw cycles that occur on a continuous basis at elevations above 6000 m.

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Article Synopsis
  • Brain-computer interfaces (BCIs) allow direct communication with computers through neural signals, typically analyzed using electroencephalogram (EEG) data.
  • Researchers introduced EEGNet, a compact convolutional neural network specifically designed for classifying EEG signals across multiple BCI paradigms.
  • EEGNet outperformed existing methods in generalizing across various paradigms while maintaining high accuracy, even with limited training data, and included techniques for visualizing the learned features.
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