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Few techniques are available for studying the nature of forces that drive subcellular dynamics. Here we develop two complementary ones. The first is femtosecond stereotactic laser ablation, which rapidly creates complex cuts of subcellular structures and enables precise dissection of when, where and in what direction forces are generated. The second is an assessment of subcellular fluid flows by comparison of direct flow measurements using microinjected fluorescent nanodiamonds with large-scale fluid-structure simulations of different force transduction models. We apply these techniques to study spindle and centrosome positioning in early Caenorhabditis elegans embryos and to probe the contributions of microtubule pushing, cytoplasmic pulling and cortical pulling upon centrosomal microtubules. Based on our results, we construct a biophysical model to explain the dynamics of centrosomes. We demonstrate that cortical pulling forces provide a general explanation for many behaviours mediated by centrosomes, including pronuclear migration and centration, rotation, metaphase spindle positioning, asymmetric spindle elongation and spindle oscillations. This work establishes methodologies for disentangling the forces responsible for cell biological phenomena. 

Organic trisradicals featuring three-fold symmetry have attracted significant interest because of their unique magnetic properties associated with spin frustration. Herein, we describe the synthesis and characterization of a triangular prism-shaped organic cage for which we have coined the name PrismCage6+ and its trisradical trication—TR3(•+). PrismCage6+ is composed of three 4,4'-bipyridinium dications and two 1,3,5-phenylene units bridged by six methylene groups. In the solid state, PrismCage6+ adopts a highly twisted conformation with close to C3 symmetry as a result of encapsulating one PF6− anion as a guest. PrismCage6+ undergoes stepwise reduction to its mono-, di- and trisradical cations in MeCN on account of strong electronic communication between its 4,4'-bipyridinium units. TR3(•+), which is obtained by reduction of PrismCage6+ employing CoCp2, adopts a triangular prism-shaped conformation with close to C2v symmetry in the solid state. Temperature-dependent continuous-wave and nutation frequency-selective EPR spectra of TR3(•+) in frozen N,N-dimethylformamide indicate its doublet ground state. The doublet-quartet energy gap of TR3(•+) is estimated to be −0.06 kcal mol−1 and the critical temperature of spin-state conversion is found to be ca. 50 K, suggesting that it displays pronounced spin-frustration at the molecular level. To the best of our knowledge, this example is the first organic radical cage to exhibit spin frustration. The trisradical trication of PrismCage6+ opens up new possibilities for fundamental investigations and potential applications in the fields of both organic cages and spin chemistry. 

The manifold scattering transform is a deep feature extractor for data defined on a Riemannian manifold. It is one of the first examples of extending convolutional neural network-like operators to general manifolds. The initial work on this model focused primarily on its theoretical stability and invariance properties but did not provide methods for its numerical implementation except in the case of two-dimensional surfaces with predefined meshes. In this work, we present practical schemes, based on the theory of diffusion maps, for implementing the manifold scattering transform to datasets arising in naturalistic systems, such as single cell genetics, where the data is a high-dimensional point cloud modeled as lying on a low-dimensional manifold. We show that our methods are effective for signal classification and manifold classification tasks. 

Sedimentary beds of alternating red and green colour are commonly interpreted to reflect orbitally‐forced cyclic climatic, syn‐depositional conditions, although colour changes caused by post‐depositional fluids are also documented. Results from IODP Hole U1502A marine sediments in the South China Sea exemplify post‐depositional reducing fluid–rock interactions that locally changed the sediment colour from red to green. Petrographic, rock magnetic and paleomagnetic data on cores show that the red colouration originates from an early, basin‐wide, pervasive diagenetic oxidation event (forming haematite), whereas the green colouration results from subsequent fluid‐driven reduction (forming pyrrhotite‐magnetite). The dense sulfidic stockwork in the basaltic basement underlying these sediments was the likely source of reducing fluids. Drilling deep holes into marine basin basements can thus provide useful information on fluid transfer from the basement to the overlying sedimentary layers.

 

Abstract We select 48 multiflare gamma-ray bursts (GRBs) (including 137 flares) from the Swift/XRT database and estimate the spectral lag with the discrete correlation function. It is found that 89.8% of the flares have positive lags and only 9.5% of the flares show negative lags when fluctuations are taken into account. The median lag of the multiflares (2.75 s) is much greater than that of GRB pulses (0.18 s), which can be explained by the fact that we confirm that multiflare GRBs and multipulse GRBs have similar positive lag–duration correlations. We investigate the origin of the lags by checking the E peak evolution with the two brightest bursts and find the leading models cannot explain all of the multiflare lags and there may be other physical mechanisms. All of the results above reveal that X-ray flares have the same properties as GRB pulses, which further supports the observation that X-ray flares and GRB prompt-emission pulses have the same physical origin. 

In this paper, we propose conjugate energy-based models (CEBMs), a new class of energy-based models that define a joint density over data and latent variables. The joint density of a CEBM decomposes into an intractable distribution over data and a tractable posterior over latent variables. CEBMs have similar use cases as variational autoencoders, in the sense that they learn an unsupervised mapping from data to latent variables. However, these models omit a generator network, which allows them to learn more flexible notions of similarity between data points. Our experiments demonstrate that conjugate EBMs achieve competitive results in terms of image modelling, predictive power of latent space, and out-of-domain detection on a variety of datasets. 

We develop amortized population Gibbs (APG) samplers, a class of scalable methods that frame structured variational inference as adaptive importance sampling. APG samplers construct high-dimensional proposals by iterating over updates to lower-dimensional blocks of variables. We train each conditional proposal by minimizing the inclusive KL divergence with respect to the conditional posterior. To appropriately account for the size of the input data, we develop a new parameterization in terms of neural sufficient statistics. Experiments show that APG samplers can be used to train highly-structured deep generative models in an unsupervised manner, and achieve substantial improvements in inference accuracy relative to standard autoencoding variational methods. 

The present study uses eddy‐resolving numerical simulations to investigate how bed roughness affects flow and turbulence structure around an isolated, partially‐buried mussel (Unio elongatulus) aligned with the incoming flow. The rough‐bed simulations resolve the flow past the exposed part of a gravel bed, whose surface is obtained from a laboratory experiment that also provides some additional data for validation of the numerical model. Results are also discussed for the limiting case of a horizontal smooth bed. Additionally, the effects of varying the level of burial of the mussel inside the substrate and the discharge through the two mussel siphons are investigated via a set of simulations in which the ratio between the median diameter of the (gravel) particles forming the rough bed,d₅₀, and the height of the exposed part of the mussel,h, varies between 0.10 and 0.22. The increase of the bed roughness is associated with a strong amplification of the turbulence kinetic energy in the near‐wake region. Increasing the bed roughness and/or reducinghintensifies the interactions of the eddies generated by the bed particles with the base and tip vortices induced by the active filtering and by the mussel shell, respectively, which, in turn, induces a more rapid dissipation of these vortices. Increasing the bed roughness also reduces the strength of the main downwelling flow region forming in the wake. The strong downwelling near the symmetry plane is the main reason why the symmetric wake shedding mode dominates in the smooth bed simulations with negligible active filtering. By contrast, the anti‐symmetric wake shedding mode dominates in the simulations conduced with a high value of the bed roughness. The mean streamwise drag force coefficient for the emerged part of the shell and the dilution of the excurrent siphon jet increase with increasing bed roughness.

 

Freshwater mussels are bivalve mollusks that inhabit the substrates of rivers. Fully three-dimensional large eddy simulations are used to investigate flow, turbulence and the capacity of the flow to dislocate an isolated, partially-buried, isolated freshwater mussel placed in a ful-ly-developed incoming turbulent open channel flow. The mussel is aligned with the flow di-rection, which corresponds to normal conditions in rivers containing mussel beds. Its sub-mergence depth is about 60% of the mussel height. The paper focuses on quantifying the ef-fect of the active filtering flow through the incurring and excurring siphons. Simulation re-sults are discussed for two limiting cases with no active filtering and with a filtering flow dis-charge that is close to the maximum value recorded for the investigated freshwater mussel species. It is shown that the active filtering increases the turbulent kinetic energy in the wake and slightly decreases the mean streamwise drag acting on the mussel shell. The paper also discusses the main types of large-scale coherent structures generated by partially-burrowed mussels aligned with the flow, how they are affected by the filtered flow and the effects of these eddies on the bed shear stress, sediment entrainment/deposition phenomena and nutri-ent transport