Fluid-driven deformation of a soft granular material

Compressing a porous, fluid-filled material will drive the interstitial fluid out of the pore space, as when squeezing water out of a kitchen sponge. Inversely, injecting fluid into a porous material can deform the solid structure, as when fracturing a shale for natural gas recovery. These poromechanical interactions play an important role in geological and biological systems across a wide range of scales, from the propagation of magma through the Earth's mantle to the transport of fluid through living cells and tissues. The theory of poroelasticity has been largely successful in modeling poromechanical behavior in relatively simple systems, but this continuum theory is fundamentally limited by our understanding of the pore-scale interactions between the fluid and the solid, and these problems are notoriously difficult to study in a laboratory setting. Here, we present a high-resolution measurement of injection-driven poromechanical deformation in a system with granular microsctructure: We inject fluid into a dense, confined monolayer of soft particles and use particle tracking to reveal the dynamics of the multi-scale deformation field. We find that a continuum model based on poroelasticity theory captures certain macroscopic features of the deformation, but the particle-scale deformation field exhibits dramatic departures from smooth, continuum behavior. We observe particle-scale rearrangement and hysteresis, as well as petal-like mesoscale structures that are connected to material failure through spiral shear banding

Multidisciplinary learning through collective performance favors decentralization

Many models of learning in teams assume that team members can share solutions or learn concurrently. However, these assumptions break down in multidisciplinary teams where team members often complete distinct, interrelated pieces of larger tasks. Such contexts make it difficult for individuals to separate the performance effects of their own actions from the actions of interacting neighbors. In this work, we show that individuals can overcome this challenge by learning from network neighbors through mediating artifacts (like collective performance assessments). When neighbors' actions influence collective outcomes, teams with different networks perform relatively similarly to one another. However, varying a team's network can affect performance on tasks that weight individuals' contributions by network properties. Consequently, when individuals innovate (through ``exploring'' searches), dense networks hurt performance slightly by increasing uncertainty. In contrast, dense networks moderately help performance when individuals refine their work (through ``exploiting'' searches) by efficiently finding local optima. We also find that decentralization improves team performance across a battery of 34 tasks. Our results offer design principles for multidisciplinary teams within which other forms of learning prove more difficult.Comment: 11 pages, 8 figures. For SI Appendix, see Ancillary files. For accompanying code, see https://github.com/meluso/multi-disciplinary-learning. For accompanying data, see https://osf.io/kyvtd

Design and performance of a stable first crystal mount for a cryogenically cooled Si monochromator at the Advanced Photon Source

We present a new design for mounting a cryogenically cooled Si crystal which gives greatly improved beam stability. The design has been successfully implemented at the University of Michigan, Howard University, Bell Laboratories-Lucent Technologies Collaborative Access Team (MHATT-CAT) 7ID Beamline of the Advanced Photon Source. Before the installation of the new crystal mount, our Si (lll) cryogenically cooled monochromator was sensitive to the pressure fluctuations of the liquid nitrogen coolant, such that the angle of incidence on the first crystal varied linearly with the applied pressure in the cooling lines, causing beam motion of about 250 μm, 60 m250μm,60m from the source. The key element of the design is a symmetrically positioned cooling manifold which balances the forces caused by pressure fluctuations. With this new mount, the typical beam stability is now about 10 μm, comparable to the source stability. © 2002 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/69891/2/RSINAK-73-3-1511-1.pd

The Extracellular Vesicles of the Helminth Pathogen, Fasciola hepatica: Biogenesis Pathways and Cargo Molecules Involved in Parasite Pathogenesis

Extracellular vesicles (EVs) released by parasites have important roles in establishing and maintaining infection. Analysis of the soluble and vesicular secretions of adult Fasciola hepatica has established a definitive characterization of the total secretome of this zoonotic parasite. Fasciola secretes at least two subpopulations of EVs that differ according to size, cargo molecules and site of release from the parasite. The larger EVs are released from the specialized cells that line the parasite gastrodermus and contain the zymogen of the 37 kDa cathepsin L peptidase that performs a digestive function. The smaller exosome-like vesicle population originate from multivesicular bodies within the tegumental syncytium and carry many previously described immunomodulatory molecules that could be delivered into host cells. By integrating our proteomics data with recently available transcriptomic data sets we have detailed the pathways involved with EV biogenesis in F. hepatica and propose that the small exosome biogenesis occurs via ESCRT-dependent MVB formation in the tegumental syncytium before being shed from the apical plasma membrane. Furthermore, we found that the molecular "machinery" required for EV biogenesis is constitutively expressed across the intramammalian development stages of the parasite. By contrast, the cargo molecules packaged within the EVs are developmentally regulated, most likely to facilitate the parasites migration through host tissue and to counteract host immune attack