Penetration of the Stigma and Style Elicits a Novel Transcriptome in Pollen Tubes, Pointing to Genes Critical for Growth in a Pistil

Pollen tubes extend through pistil tissues and are guided to ovules where they release sperm for fertilization. Although pollen tubes can germinate and elongate in a synthetic medium, their trajectory is random and their growth rates are slower compared to growth in pistil tissues. Furthermore, interaction with the pistil renders pollen tubes competent to respond to guidance cues secreted by specialized cells within the ovule. The molecular basis for this potentiation of the pollen tube by the pistil remains uncharacterized. Using microarray analysis in Arabidopsis, we show that pollen tubes that have grown through stigma and style tissues of a pistil have a distinct gene expression profile and express a substantially larger fraction of the Arabidopsis genome than pollen grains or pollen tubes grown in vitro. Genes involved in signal transduction, transcription, and pollen tube growth are overrepresented in the subset of the Arabidopsis genome that is enriched in pistil-interacted pollen tubes, suggesting the possibility of a regulatory network that orchestrates gene expression as pollen tubes migrate through the pistil. Reverse genetic analysis of genes induced during pollen tube growth identified seven that had not previously been implicated in pollen tube growth. Two genes are required for pollen tube navigation through the pistil, and five genes are required for optimal pollen tube elongation in vitro. Our studies form the foundation for functional genomic analysis of the interactions between the pollen tube and the pistil, which is an excellent system for elucidation of novel modes of cell–cell interaction

Communication subject to normed channel uncertainties

The transmission of information over a communication channel vastly depends on the level of knowledge that a transmitter and a receiver have about the channel and the interference. The transmission of information subject to insufficient knowledge of communication environment is called communication subject to uncertainties. The goal of this thesis is twofold: (1) To introduce new models for uncertain communication channels; (2) To define, compute, and analyze the performance of communication systems subject to introduced uncertainties from an information theoretic point of view. Various communication scenarios of compound single-input single-output and multiple-input multiple-output Gaussian channels are considered. There are three main contributions of the thesis: (1) The modeling of the channel and the noise uncertainties using Hinfinity and L1 normed liner spaces in frequency domain; (2) In the case of single-input single-output channels, the channel uncertainty is modeled as a subset of H infinity space; while the noise uncertainty is modeled either by a subset of Hinfinity space or by a subset of L1 space. Explicit formulas for the channel capacities, called robust capacities, and the optimal transmitted powers in the form of new water-filling formulas, are derived that explicitly depend on the sizes of the uncertainty sets. Moreover, when the noise uncertainty is modeled by a subset of L1 space, the capacity formula has a game theoretical interpretation, where the transmitter tries to maximize the mutual information, while the noise tries to minimize it. It is shown that a saddle point exists and that the optimal PSD of the transmitter is proportional to the optimal PSD of the noise; (3) In the case of multiple input multiple-output channels, two problems are considered. When the channel uncertainty is described by a subset of Hinfinity space, it is found that the transmission over the strongest singular value of the nominal channel frequency response matrix, representing the partial channel knowledge, is optimal for a large uncertainty set. When the noise uncertainty is described by a subset of L1 space, the optimal power spectral density matrix of the noise is proportional to the optimal power spectral density matrix of the transmitted signal

Distributed Synchronization on Weakly Connected Networks

Distributed synchronization for wireless networks is based on the mutual exchange of the same chirp-signature by nodes. Collisions of these signatures drive the system toward time and (carrier) frequency synchronization using distributed consensus algorithms. This letter investigates the convergence and the asymptotic distortion properties on noisy networks when neighboring clusters of nodes are weakly connected to each other only through a subset of nodes and bridging links. These heavily connected clusters act as macroagents, and the consensus properties of the ensemble depend on the number of bridge links between them. The convergence rate and mean square synchronization deviation are derived as functions of the number of bridge links for different examples of weakly connected noisy networks via the analytic calculation of Laplacian spectra. Our approach facilitates the study of network topology optimization for distributed synchronization

Distributed Synchronization on Weakly Connected Networks

Distributed synchronization for wireless networks is based on the mutual exchange of the same chirp-signature by nodes. Collisions of these signatures drive the system toward time and (carrier) frequency synchronization using distributed consensus algorithms. This letter investigates the convergence and the asymptotic distortion properties on noisy networks when neighboring clusters of nodes are weakly connected to each other only through a subset of nodes and bridging links. These heavily connected clusters act as macroagents, and the consensus properties of the ensemble depend on the number of bridge links between them. The convergence rate and mean square synchronization deviation are derived as functions of the number of bridge links for different examples of weakly connected noisy networks via the analytic calculation of Laplacian spectra. Our approach facilitates the study of network topology optimization for distributed synchronization

Control Over Wireless Communication Channel for Continuous-Time Systems

Abstract-This paper is concerned with the control of one dimensional continuous time linear Gaussian systems over additive white noise wireless fading channels subject to capacity constraints. Necessary and sufficient conditions are derived, for bounded asymptotic and asymptotic observability and stabilizability in the mean square sense, for controlling such systems. For the case of a noiseless time-invariant system controlled over a continuous time additive white Gaussian channel, the sufficient condition for stabilizability and observability states that the capacity of the channel, C a , satisfies, C a > [A] + , where A is the system coefficient and + . It is shown that a separation principle holds between the design of the communication and the control sub-systems, implying that the controller that would be optimal in the absence of the communication channel is also optimal for the problem of the controlling the system over the communication channel