Study of spike and modal stall phenomena in a low-speed axial compressor

This paper presents a study of stall inception mechanisms a in low-speed axial compressor. Previous work has identified two common flow breakdown sequences, the first associated with a short lengthscale disturbance known as a `spike', and the second with a longer lengthscale disturbance known as a `modal oscillation'. In this paper the physical differences between these two mechanisms are illustrated with detailed measurements. Experimental results are also presented which relate the occurrence of the two stalling mechanisms to the operating conditions of the compressor. It is shown that the stability criteria for the two disturbances are different: long lengthscale disturbances are related to a two-dimensional instability of the whole compression system, while short lengthscale disturbances indicate a three-dimensional breakdown of the flow-field associated with high rotor incidence angles. Based on the experimental measurements, a simple model is proposed which explains the type of stall inception pattern observed in a particular compressor. Measurements from a single stage low-speed compressor and from a multistage high-speed compressor are presented in support of the model.

Sequence context analysis in the mouse genome: Single nucleotide polymorphisms and CpG island sequences

A genome-wide view of sequence mutability in mice is still limited, although biologists usually assume the same scenario for mice as for humans. In this study, we examined the sequence context in the local environment of 482,528 mouse single nucleotide po

Active dendrites: Adaptation to spike-based communication

Computational analyses of dendritic computations often assume stationary inputs to neurons, ignoring the pulsatile nature of spike-based communication between neurons and the moment-to-moment fluctuations caused by such spiking inputs. Conversely, circuit computations with spiking neurons are usually formalized without regard to the rich nonlinear nature of dendritic processing. Here we address the computational challenge faced by neurons that compute and represent analogue quantities but communicate with digital spikes, and show that reliable computation of even purely linear functions of inputs can require the interplay of strongly nonlinear subunits within the postsynaptic dendritic tree.Our theory predicts a matching of dendritic nonlinearities and synaptic weight distributions to the joint statistics of presynaptic inputs. This approach suggests normative roles for some puzzling forms of nonlinear dendritic dynamics and plasticity.

Attenuated Salmonella Typhimurium lacking the pathogenicity island-2 type 3 secretion system grow to high bacterial numbers inside phagocytes in mice.

Intracellular replication within specialized vacuoles and cell-to-cell spread in the tissue are essential for the virulence of Salmonella enterica. By observing infection dynamics at the single-cell level in vivo, we have discovered that the Salmonella pathogenicity island 2 (SPI-2) type 3 secretory system (T3SS) is dispensable for growth to high intracellular densities. This challenges the concept that intracellular replication absolutely requires proteins delivered by SPI-2 T3SS, which has been derived largely by inference from in vitro cell experiments and from unrefined measurement of net growth in mouse organs. Furthermore, we infer from our data that the SPI-2 T3SS mediates exit from infected cells, with consequent formation of new infection foci resulting in bacterial spread in the tissues. This suggests a new role for SPI-2 in vivo as a mediator of bacterial spread in the body. In addition, we demonstrate that very similar net growth rates of attenuated salmonellae in organs can be derived from very different underlying intracellular growth dynamics.

Functional requirements for reward-modulated spike-timing-dependent plasticity.

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.

Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.

Inhibitory Synaptic Plasticity - Spike timing dependence and putative network function.

While the plasticity of excitatory synaptic connections in the brain has been widely studied, the plasticity of inhibitory connections is much less understood. Here, we present recent experimental and theoretical □ndings concerning the rules of spike timing-dependent inhibitory plasticity and their putative network function. This is a summary of a workshop at the COSYNE conference 2012.

Detailed measurements of spike formation in an axial compressor

This paper presents new experimental measurements of spike-type stall inception. The measurements were carried out in the single stage Deverson compressor at the Whittle Laboratory. The primary objective was to characterize the flow field in the tip clearance gap during stall inception using sufficient instrumentation to give high spatial and temporal resolution. Measurements were recorded using arrays of unsteady pressure transducers over the rotor tips and hot-wires in the tip gap. Pre-stall ensemble averaged velocity and pressure maps were obtained as well as pressure contours of the stall event. In order to study the transient inception process in greater detail, vector maps were built up from hundreds of stalling events using a triggering system based on the stalling event itself. The results show an embryonic disturbance starting within the blade passage and leading to the formation of a clear spike. The origins of the spike and its relation to the tip leakage vortex are discussed. It has also been shown that before stall the flow in the blade passage which is most likely to stall is generally more unsteady, from revolution to revolution, than the other passages in the annulus. Copyright © 2012 by ASME.

Detailed measurements of spike formation in an axial compressor

This paper presents new experimental measurements of spike-type stall inception. The measurements were carried out in the single stage Deverson compressor at the Whittle Laboratory. The primary objective was to characterize the flow field in the tip clearance gap during stall inception using sufficient instrumentation to give high spatial and temporal resolution. Measurements were recorded using arrays of unsteady pressure transducers over the rotor tips and hot-wires in the tip gap. Prestall ensemble averaged velocity and pressure maps were obtained as well as pressure contours of the stall event. In order to study the transient inception process in greater detail, vector maps were built up from hundreds of stalling events using a triggering system based on the stalling event itself. The results show an embryonic disturbance starting within the blade passage and leading to the formation of a clear spike. The origins of the spike and its relation to the tip leakage vortex are discussed. It has also been shown that before stall, the flow in the blade passage which is most likely to stall is generally more unsteady, from revolution to revolution, than the other passages in the annulus. © 2014 by ASME.