Efficient Beamspace Eigen-Based Direction of Arrival Estimation schemes

The Multiple SIgnal Classification (MUSIC) algorithm developed in the late 70\u27s was the first vector subspace approach used to accurately determine the arrival angles of signal wavefronts impinging upon an array of sensors. As facilitated by the geometry associated with the common uniform linear array of sensors, a root-based formulation was developed to replace the computationally intensive spectral search process and was found to offer an enhanced resolution capability in the presence of two closely-spaced signals. Operation in beamspace, where sectors of space are individually probed via a pre-processor operating on the sensor data, was found to offer both a performance benefit and a reduced computationa1 complexi ty resulting from the reduced data dimension associated with beamspace processing. Little progress, however, has been made in the development of a computationally efficient Root-MUSIC algorithm in a beamspace setting. Two approaches of efficiently arriving at a Root-MUSIC formulation in beamspace are developed and analyzed in this Thesis. In the first approach, a structura1 constraint is placed on the beamforming vectors that can be exploited to yield a reduced order polynomial whose roots provide information on the signal arrival angles. The second approach is considerably more general, and hence, applicable to any vector subspace angle estimation algorithm. In this approach, classical multirate digital signal processing is applied to effectively reduce the dimension of the vectors that span the signal subspace, leading to an efficient beamspace Root-MUSIC (or ESPRIT) algorithm. An auxiliaay, yet important, observation is shown to allow a real-valued eigenanalysis of the beamspace sample covariance matrix to provide a computational savings as well as a performance benefit, particularly in the case of correlated signal scenes. A rigorous theoretical analysis, based upon derived large-sample statistics of the signal subspace eigenvectors, is included to provide insight into the operation of the two algorithmic methodologies employing the real-valued processing enhancement. Numerous simulations are presented to validate the theoretical angle bias and variance expressions as well as to assess the merit of the two beamspace approaches

Allosteric Mechanism of the Circadian Protein Vivid Resolved Through Markov State Model and Machine Learning Analysis

The fungal circadian clock photoreceptor Vivid (VVD) contains a photosensitive allosteric light, oxygen, voltage (LOV) domain that undergoes a large N-terminal conformational change. The mechanism by which a blue-light driven covalent bond formation leads to a global conformational change remains unclear, which hinders the further development of VVD as an optogenetic tool. We answered this question through a novel computational platform integrating Markov state models, machine learning methods, and newly developed community analysis algorithms. Applying this new integrative approach, we provided a quantitative evaluation of the contribution from the covalent bond to the protein global conformational change, and proposed an atomistic allosteric mechanism leading to the discovery of the unexpected importance of A’α/Aβ and previously overlooked Eα/Fα loops in the conformational change. This approach could be applicable to other allosteric proteins in general to provide interpretable atomistic representations of their otherwise elusive allosteric mechanisms

Channel estimation method with improved performance for the UMTS-TDD mode

Channel estimation is an essential building block for UTRA-TDD high performance receivers. Once the performance of the channel estimator algorithm proposed by 3GPP is highly dependent on the time spreading between consecutive multi-path components, a Successive Multi-path channel Estimation Technique (SMET) that improves the time resolution is proposed in this paper. A SMET based maximum likelihood approach for vectorial channel estimation, to include the estimation of the direction-of-arrival, is also proposed. This algorithm solves efficiently the complex problem of DOA estimation of multiple users in a multi path propagation environment even when the number of required DOA's exceeds the number of antenna array elements. Another property of the proposed algorithm is its ability to resolve signals from different users arriving from the same direction. This is due to processing in both time and space dimensions. The performance of these algorithms is assessed by resorting to simulations in multi-path environments using the UMTS-TDD specifications, and also by comparing the rms estimation errors against the Crámer-Rao Bound. The effect of imperfect channel estimation on the performance of RAKE and Hard-Decision Parallel Interference Canceller receivers is also analysed. The results show that a good performance can be achieved with SMET, from low to high values of Eb/n0

Investigation of Atomic Level Patterns in Protein—Small Ligand Interactions

BACKGROUND: Shape complementarity and non-covalent interactions are believed to drive protein-ligand interaction. To date protein-protein, protein-DNA, and protein-RNA interactions were systematically investigated, which is in contrast to interactions with small ligands. We investigate the role of covalent and non-covalent bonds in protein-small ligand interactions using a comprehensive dataset of 2,320 complexes. METHODOLOGY AND PRINCIPAL FINDINGS: We show that protein-ligand interactions are governed by different forces for different ligand types, i.e., protein-organic compound interactions are governed by hydrogen bonds, van der Waals contacts, and covalent bonds; protein-metal ion interactions are dominated by electrostatic force and coordination bonds; protein-anion interactions are established with electrostatic force, hydrogen bonds, and van der Waals contacts; and protein-inorganic cluster interactions are driven by coordination bonds. We extracted several frequently occurring atomic-level patterns concerning these interactions. For instance, 73% of investigated covalent bonds were summarized with just three patterns in which bonds are formed between thiol of Cys and carbon or sulfur atoms of ligands, and nitrogen of Lys and carbon of ligands. Similar patterns were found for the coordination bonds. Hydrogen bonds occur in 67% of protein-organic compound complexes and 66% of them are formed between NH- group of protein residues and oxygen atom of ligands. We quantify relative abundance of specific interaction types and discuss their characteristic features. The extracted protein-organic compound patterns are shown to complement and improve a geometric approach for prediction of binding sites. CONCLUSIONS AND SIGNIFICANCE: We show that for a given type (group) of ligands and type of the interaction force, majority of protein-ligand interactions are repetitive and could be summarized with several simple atomic-level patterns. We summarize and analyze 10 frequently occurring interaction patterns that cover 56% of all considered complexes and we show a practical application for the patterns that concerns interactions with organic compounds

Cross-Talk between the Cellular Redox State and the Circadian System in Neurospora

The circadian system is composed of a number of feedback loops, and multiple feedback loops in the form of oscillators help to maintain stable rhythms. The filamentous fungus Neurospora crassa exhibits a circadian rhythm during asexual spore formation (conidiation banding) and has a major feedback loop that includes the FREQUENCY (FRQ)/WHITE COLLAR (WC) -1 and -2 oscillator (FWO). A mutation in superoxide dismutase (sod)-1, an antioxidant gene, causes a robust and stable circadian rhythm compared with that of wild-type (Wt). However, the mechanisms underlying the functions of reactive oxygen species (ROS) remain unknown. Here, we show that cellular ROS concentrations change in a circadian manner (ROS oscillation), and the amplitudes of ROS oscillation increase with each cycle and then become steady (ROS homeostasis). The ROS oscillation and homeostasis are produced by the ROS-destroying catalases (CATs) and ROS-generating NADPH oxidase (NOX). cat-1 is also induced by illumination, and it reduces ROS levels. Although ROS oscillation persists in the absence of frq, wc-1 or wc-2, its homeostasis is altered. Furthermore, genetic and biochemical evidence reveals that ROS concentration regulates the transcriptional function of WCC and a higher ROS concentration enhances conidiation banding. These findings suggest that the circadian system engages in cross-talk with the cellular redox state via ROS-regulatory factors

A LOV Protein Modulates the Physiological Attributes of Xanthomonas axonopodis pv. citri Relevant for Host Plant Colonization

Recent studies have demonstrated that an appropriate light environment is required for the establishment of efficient vegetal resistance responses in several plant-pathogen interactions. The photoreceptors implicated in such responses are mainly those belonging to the phytochrome family. Data obtained from bacterial genome sequences revealed the presence of photosensory proteins of the BLUF (Blue Light sensing Using FAD), LOV (Light, Oxygen, Voltage) and phytochrome families with no known functions. Xanthomonas axonopodis pv. citri is a Gram-negative bacterium responsible for citrus canker. The in silico analysis of the X. axonopodis pv. citri genome sequence revealed the presence of a gene encoding a putative LOV photoreceptor, in addition to two genes encoding BLUF proteins. This suggests that blue light sensing could play a role in X. axonopodis pv. citri physiology. We obtained the recombinant Xac-LOV protein by expression in Escherichia coli and performed a spectroscopic analysis of the purified protein, which demonstrated that it has a canonical LOV photochemistry. We also constructed a mutant strain of X. axonopodis pv. citri lacking the LOV protein and found that the loss of this protein altered bacterial motility, exopolysaccharide production and biofilm formation. Moreover, we observed that the adhesion of the mutant strain to abiotic and biotic surfaces was significantly diminished compared to the wild-type. Finally, inoculation of orange (Citrus sinensis) leaves with the mutant strain of X. axonopodis pv. citri resulted in marked differences in the development of symptoms in plant tissues relative to the wild-type, suggesting a role for the Xac-LOV protein in the pathogenic process. Altogether, these results suggest the novel involvement of a photosensory system in the regulation of physiological attributes of a phytopathogenic bacterium. A functional blue light receptor in Xanthomonas spp. has been described for the first time, showing an important role in virulence during citrus canker disease

Dual-controlled optogenetic system for the rapid down-regulation of protein levels in mammalian cells

Abstract Optogenetic switches are emerging molecular tools for studying cellular processes as they offer higher spatiotemporal and quantitative precision than classical, chemical-based switches. Light-controllable gene expression systems designed to upregulate protein expression levels meanwhile show performances superior to their chemical-based counterparts. However, systems to reduce protein levels with similar efficiency are lagging behind. Here, we present a novel two-component, blue light-responsive optogenetic OFF switch (‘Blue-OFF’), which enables a rapid and quantitative down-regulation of a protein upon illumination. Blue-OFF combines the first light responsive repressor KRAB-EL222 with the protein degradation module B-LID (blue light-inducible degradation domain) to simultaneously control gene expression and protein stability with a single wavelength. Blue-OFF thus outperforms current optogenetic systems for controlling protein levels. The system is described by a mathematical model which aids in the choice of experimental conditions such as light intensity and illumination regime to obtain the desired outcome. This approach represents an advancement of dual-controlled optogenetic systems in which multiple photosensory modules operate synergistically. As exemplified here for the control of apoptosis in mammalian cell culture, the approach opens up novel perspectives in fundamental research and applications such as tissue engineering