Modeling of the interaction of rigid wheels with dry granular media

We analyze the capabilities of various recently developed techniques, namely Resistive Force Theory (RFT) and continuum plasticity implemented with the Material Point Method (MPM), in capturing dynamics of wheel--dry granular media interactions. We compare results to more conventionally accepted methods of modeling wheel locomotion. While RFT is an empirical force model for arbitrarily-shaped bodies moving through granular media, MPM-based continuum modeling allows the simulation of full granular flow and stress fields. RFT allows for rapid evaluation of interaction forces on arbitrary shaped intruders based on a local surface stress formulation depending on depth, orientation, and movement of surface elements. We perform forced-slip experiments for three different wheel types and three different granular materials, and results are compared with RFT, continuum modeling, and a traditional terramechanics semi-empirical method. Results show that for the range of inputs considered, RFT can be reliably used to predict rigid wheel granular media interactions with accuracy exceeding that of traditional terramechanics methodology in several circumstances. Results also indicate that plasticity-based continuum modeling provides an accurate tool for wheel-soil interaction while providing more information to study the physical processes giving rise to resistive stresses in granular media

Reducing errors by increasing the error rate: MLP Acoustic Modeling for Broadcast News Transcription

We describe some aspects of a Broadcast News recognition system based on hybrid HMM/MLP acoustic modeling. These include the use of novel 'modulation spectrogram' features which are combined with conventional models at the posterior probability level, some experiments with nonlinear segment normalization, and an investigation of the interaction of model size and training set size for an multilayer perceptron (MLP) acoustic classifier. We also report preliminary results of incorporating gender-dependence into this system

Myelinating glia differentiation is regulated by extracellular matrix elasticity

The mechanical properties of living tissues have a significant impact on cell differentiation, but remain unexplored in the context of myelin formation and repair. In the PNS, the extracellular matrix (ECM) incorporates a basal lamina significantly denser than the loosely organized CNS matrix. Inhibition of non-muscle myosin II (NMII) enhances central but impairs peripheral myelination and NMII has been implicated in cellular responses to changes in the elasticity of the ECM. To directly evaluate whether mechanotransduction plays a role in glial cell differentiation, we cultured Schwann cells (SC) and oligodendrocytes (OL) on matrices of variable elastic modulus, mimicking either their native environment or conditions found in injured tissue. We found that a rigid, lesion-like matrix inhibited branching and differentiation of OL in NMII-dependent manner. By contrast, SC developed normally in both soft and stiffer matrices. Although SC differentiation was not significantly affected by changes in matrix stiffness alone, we found that expression of Krox-20 was potentiated on rigid matrices at high laminin concentration. These findings are relevant to the design of biomaterials to promote healing and regeneration in both CNS and PNS, via transplantation of glial progenitors or the implantation of tissue scaffolds

Kernel Approximation Methods for Speech Recognition

International audienceWe study the performance of kernel methods on the acoustic modeling task for automatic speech recognition, and compare their performance to deep neural networks (DNNs). To scale the kernel methods to large data sets, we use the random Fourier feature method of Rahimi and Recht (2007). We propose two novel techniques for improving the performance of kernel acoustic models. First, we propose a simple but effective feature selection method which reduces the number of random features required to attain a fixed level of performance. Second, we present a number of metrics which correlate strongly with speech recognition performance when computed on the heldout set; we attain improved performance by using these metrics to decide when to stop training. Additionally, we show that the linear bottleneck method of Sainath et al. (2013a) improves the performance of our kernel models significantly, in addition to speeding up training and making the models more compact. Leveraging these three methods, the kernel methods attain token error rates between 0.5% better and 0.1% worse than fully-connected DNNs across four speech recognition data sets, including the TIMIT and Broadcast News benchmark tasks

Climatic and geographic predictors of life history variation in Eastern Massasauga (Sistrurus catenatus): A range-wide synthesis

Elucidating how life history traits vary geographically is important to understanding variation in population dynamics. Because many aspects of ectotherm life history are climate-dependent, geographic variation in climate is expected to have a large impact on population dynamics through effects on annual survival, body size, growth rate, age at first reproduction, size-fecundity relationship, and reproductive frequency. The Eastern Massasauga (Sistrurus catenatus) is a small, imperiled North American rattlesnake with a distribution centered on the Great Lakes region, where lake effects strongly influence local conditions. To address Eastern Massasauga life history data gaps, we compiled data from 47 study sites representing 38 counties across the range. We used multimodel inference and general linear models with geographic coordinates and annual climate normals as explanatory variables to clarify patterns of variation in life history traits. We found strong evidence for geographic variation in six of nine life history variables. Adult female snout-vent length and neonate mass increased with increasing mean annual precipitation. Litter size decreased with increasing mean temperature, and the size-fecundity relationship and growth prior to first hibernation both increased with increasing latitude. The proportion of gravid females also increased with increasing latitude, but this relationship may be the result of geographically varying detection bias. Our results provide insights into ectotherm life history variation and fill critical data gaps, which will inform Eastern Massasauga conservation efforts by improving biological realism for models of population viability and climate change

Epigenetic regulator genes direct lineage switching in MLL/AF4 leukaemia

The fusion gene MLL/AF4 defines a high-risk subtype of pro-B acute lymphoblastic leukaemia. Relapse can be associated with a lineage switch from acute lymphoblastic to acute myeloid leukaemia resulting in poor clinical outcomes due to resistance towards chemo- and immuno-therapies. Here we show that the myeloid relapses share oncogene fusion breakpoints with their matched lymphoid presentations and can originate from varying differentiation stages from immature progenitors through to committed B-cell precursors. Lineage switching is linked to substantial changes in chromatin accessibility and rewiring of transcriptional programmes, including alternative splicing. These findings indicate that the execution and maintenance of lymphoid lineage differentiation is impaired. The relapsed myeloid phenotype is recurrently associated with the altered expression, splicing or mutation of chromatin modifiers, including CHD4 coding for the ATPase/helicase of the nucleosome remodelling and deacetylation complex, NuRD. Perturbation of CHD4 alone or in combination with other mutated epigenetic modifiers induces myeloid gene expression in MLL/AF4-positive cell models indicating that lineage switching in MLL/AF4 leukaemia is driven and maintained by disrupted epigenetic regulation