Spontaneous Bending of Hydra Tissue Fragments Driven by Supracellular Actomyosin Bundles

Hydra tissue fragments excised freshly from Hydra body bend spontaneously to some quasi-stable shape in several minutes. We propose that the spontaneous bending is driven mechanically by supracellular actomyosin bundles inherited from parent Hydra. An active-laminated-plate model is constructed, from which we predict that the fragment shape characterized by spontaneous curvature is determined by its anisotropy in contractility and elasticity. The inward bending to endoderm side is ensured by the presence of a soft intermediate matrix (mesoglea) layer. The bending process starts diffusively from the edges and relaxes exponentially to the final quasi-stable shape. Two characteristic time scales are identified from the dissipation due to viscous drag and interlayer frictional sliding, respectively. The former is about 0.01 seconds, but the latter is much larger, about several minutes, consistent with experiments.Comment: 26 pages, 10 figure

“They have it better there” : Chinese Migrant Teachers’ Beliefs, Imaginaries and Ideologies in Cross-national Comparisons

This paper was written in response to a growing need to address the perceptions and experiences of teachers of migrant background. Based on a critical intercultural theoretical perspective, which moves beyond typical ‘culture shock’ and ‘adaptation’ models of understanding and explaining migrants’ experiences, this paper makes use of the concepts of teacher beliefs, ideologies and imaginaries (Holliday, 2010) in considering how Finland-based Chinese migrant teachers perceive the position of being teachers of Chinese in Finland and Australia. Analysis of data from group discussions during a teacher training workshop indicates that these teachers constructed a “utopia” (Australia) and “dystopia” (Finland) Chinese language teaching, and reveals that multiple factors have influenced these migrant teachers’ perceptions and experiences. Findings provide information for e.g. teacher educators and stakeholders to better understand and support migrant teachers from various linguistic and cultural backgrounds.Peer reviewe

Elastic interactions compete with persistent cell motility to drive durotaxis

Many animal cells crawling on elastic substrates exhibit durotaxis and have implications in several biological processes including tissue development, and tumor progression. Here, we introduce a phenomenological model for durotactic migration incorporating both elastic deformation-mediated cell-substrate interactions and the stochasticity of cell migration. Our model is motivated by the key observation in one of the first demonstrations of durotaxis: a single contractile cell at an interface between a softer and a stiffer region of an elastic substrate reorients and migrates towards the stiffer region. We model migrating cells as self-propelling, persistently motile agents that exert contractile, dipolar traction forces on the underlying elastic substrate. The resulting substrate deformations induce elastic interactions with mechanical boundaries, captured by an elastic potential that depends on cell position and orientation relative to the boundary. The potential is attractive or repulsive depending on whether the mechanical boundary condition is clamped or free, which represents the cell being on the softer or stiffer side, respectively, of a confining boundary. The forces and torques from the interactions drive cells to orient perpendicular (parallel) to the boundary and accumulate (deplete) at the clamped (free) boundary, extent of which is determined by elastic potential (A) and motility (Pe). While the elastic interaction drives durotaxis, cell migratory movements such as random reorientation and self-propulsion enable the cell from the attractive potential thereby reducing durotaxis. We define metrics quantifying boundary accumulation and durotaxis and present a phase diagram that identifies three possible regimes: durotaxis, adurotaxis without accumulation and adurotaxis with motility-induced accumulation at a confining boundary.Comment: 14 figures, 28 page

A Diffusion Model for Event Skeleton Generation

Event skeleton generation, aiming to induce an event schema skeleton graph with abstracted event nodes and their temporal relations from a set of event instance graphs, is a critical step in the temporal complex event schema induction task. Existing methods effectively address this task from a graph generation perspective but suffer from noise-sensitive and error accumulation, e.g., the inability to correct errors while generating schema. We, therefore, propose a novel Diffusion Event Graph Model~(DEGM) to address these issues. Our DEGM is the first workable diffusion model for event skeleton generation, where the embedding and rounding techniques with a custom edge-based loss are introduced to transform a discrete event graph into learnable latent representation. Furthermore, we propose a denoising training process to maintain the model's robustness. Consequently, DEGM derives the final schema, where error correction is guaranteed by iteratively refining the latent representation during the schema generation process. Experimental results on three IED bombing datasets demonstrate that our DEGM achieves better results than other state-of-the-art baselines. Our code and data are available at https://github.com/zhufq00/EventSkeletonGeneration