Network reconstruction using knock-out and over-expression data

This paper outlines necessary and sufficient conditions for network reconstruction of linear, time-invariant systems using data from either knock-out or over-expression experiments. These structural system perturbations, which are common in biological experiments, can be formulated as unknown system inputs, allowing the network topology and dynamics to be found. We assume that only partial state measurements are available and propose an algorithm that can reconstruct the network at the level of the measured states using either time-series or steady-state data. A simulated example illustrates how the algorithm successfully reconstructs a network from data. © 2013 EUCA.

Control limitations from distributed sensing: Theory and Extremely Large Telescope application

We investigate performance bounds for feedback control of distributed plants where the controller can be centralized (i.e. it has access to measurements from the whole plant), but sensors only measure differences between neighboring subsystem outputs. Such "distributed sensing" can be a technological necessity in applications where system size exceeds accuracy requirements by many orders of magnitude. We formulate how distributed sensing generally limits feedback performance robust to measurement noise and to model uncertainty, without assuming any controller restrictions (among others, no "distributed control" restriction). A major practical consequence is the necessity to cut down integral action on some modes. We particularize the results to spatially invariant systems and finally illustrate implications of our developments for stabilizing the segmented primary mirror of the European Extremely Large Telescope. © 2013 Elsevier Ltd. All rights reserved.

Identification and characterization of a novel envelope protein in Rana grylio virus

Viral envelope proteins have been proposed to play significant roles in virus infection and assembly. In this study, an envelope protein gene, 53R, was cloned and characterized from Rana grylio virus (RGV), a member of the family Iridoviridae. Database searches found its homologues in all sequenced iricloviruses, and sequence alignment revealed several conserved structural features shared by virus capsid or envelope proteins: a myristoylation site, two predicted transmembrane domains and two invariant cysteine residues. Subsequently, RT-PCR and Western blot detection revealed that the transcripts encoding RGV 53R and the protein itself appeared late during infection of fathead minnow cells and that their appearance was blocked by viral DNA replication inhibitor, indicating that RGV 53R is a late expression gene. Moreover, immunofluorescence localization found an association of 53R with virus factories in RGV-infected cells, and this association was further confirmed by expressing a 53R-GFP fusion protein in pEGFP-N3/53R-transfected cells. Furthermore, detergent extraction and Western blot detection confirmed that RGV 53R was associated with virion membrane. Therefore, the current data suggest that RGV 53R is a novel viral envelope protein and that it may play an important role in virus assembly. This is thought to be the first report on a viral envelope protein that is conserved in all sequenced iridoviruses.

Bioinformatic identification of genes encoding C1q-domain-containing proteins in zebrafish

C1q is the first subcomponent of classical pathway in the complement system and a major link between innate and acquired immunities. The globular (gC1q) domain similar with C1q was also found in many non-complement C1q-domain-containing (C1qDC) proteins which have similar crystal structure to that of the multifunctional tumor necrosis factor (TNF) ligand family, and also have diverse functions. In this study, we identified a total of 52 independent gene sequences encoding C1q-domain-containing proteins through comprehensive searches of zebrafish genome, cDNA and EST databases. In comparison to 31 orthologous genes in human and different numbers in other species, a significant selective pressure was suggested during vertebrate evolution. Domain organization of C1q-domain-containing (C1qDC) proteins mainly includes a leading signal peptide, a collagen-like region of variable length, and a C-terminal C1q domain. There are 11 highly conserved residues within the C1q domain, among which 2 are invariant within the zebrafish gene set. A more extensive database searches also revealed homologous C1qDC proteins in other vertebrates, invertebrates and even bacterium, but no homologous sequences for encoding C1qDC proteins were found in many species that have a more recent evolutionary history with zebrafish. Therefore, further studies on C1q-domain-containing genes among different species will help us understand evolutionary mechanism of innate and acquired immunities.

First principles interatomic potential for tungsten based on Gaussian process regression

An accurate description of atomic interactions, such as that provided by first principles quantum mechanics, is fundamental to realistic prediction of the properties that govern plasticity, fracture or crack propagation in metals. However, the computational complexity associated with modern schemes explicitly based on quantum mechanics limits their applications to systems of a few hundreds of atoms at most. This thesis investigates the application of the Gaussian Approximation Potential (GAP) scheme to atomistic modelling of tungsten - a bcc transition metal which exhibits a brittle-to-ductile transition and whose plasticity behaviour is controlled by the properties of $\frac{1}{2} \langle 111 \rangle$ screw dislocations. We apply Gaussian process regression to interpolate the quantum-mechanical (QM) potential energy surface from a set of points in atomic configuration space. Our training data is based on QM information that is computed directly using density functional theory (DFT). To perform the fitting, we represent atomic environments using a set of rotationally, permutationally and reflection invariant parameters which act as the independent variables in our equations of non-parametric, non-linear regression. We develop a protocol for generating GAP models capable of describing lattice defects in metals by building a series of interatomic potentials for tungsten. We then demonstrate that a GAP potential based on a Smooth Overlap of Atomic Positions (SOAP) covariance function provides a description of the $\frac{1}{2} \langle 111 \rangle$ screw dislocation that is in agreement with the DFT model. We use this potential to simulate the mobility of $\frac{1}{2} \langle 111 \rangle$ screw dislocations by computing the Peierls barrier and model dislocation-vacancy interactions to QM accuracy in a system containing more than 100,000 atoms.

Synchronization of user-generated videos through trajectory correspondence and a refinement procedure

Temporal synchronization of multiple video recordings of the same dynamic event is a critical task in many computer vision applications e.g. novel view synthesis and 3D reconstruction. Typically this information is implied through the time-stamp information embedded in the video streams. User-generated videos shot using consumer grade equipment do not contain this information; hence, there is a need to temporally synchronize signals using the visual information itself. Previous work in this area has either assumed good quality data with relatively simple dynamic content or the availability of precise camera geometry. Our first contribution is a synchronization technique which tries to establish correspondence between feature trajectories across views in a novel way, and specifically targets the kind of complex content found in consumer generated sports recordings, without assuming precise knowledge of fundamental matrices or homographies. We evaluate performance using a number of real video recordings and show that our method is able to synchronize to within 1 sec, which is significantly better than previous approaches. Our second contribution is a robust and unsupervised view-invariant activity recognition descriptor that exploits recurrence plot theory on spatial tiles. The descriptor is individually shown to better characterize the activities from different views under occlusions than state-of-the-art approaches. We combine this descriptor with our proposed synchronization method and show that it can further refine the synchronization index. © 2013 ACM.

Sparse recovery of complex phase-encoded velocity images using iterative thresholding

In this paper we propose a new algorithm for reconstructing phase-encoded velocity images of catalytic reactors from undersampled NMR acquisitions. Previous work on this application has employed total variation and nonlinear conjugate gradients which, although promising, yields unsatisfactory, unphysical visual results. Our approach leverages prior knowledge about the piecewise-smoothness of the phase map and physical constraints imposed by the system under study. We show how iteratively regularizing the real and imaginary parts of the acquired complex image separately in a shift-invariant wavelet domain works to produce a piecewise-smooth velocity map, in general. Using appropriately defined metrics we demonstrate higher fidelity to the ground truth and physical system constraints than previous methods for this specific application. © 2013 IEEE.

Scaling arguments for the fluxes in turbulent miscible fountains

For established axisymmetric turbulent miscible Boussinesq fountains in quiescent uniform environments, expressions are developed for the fluxes of volume, momentum and buoyancy at the outflow from the fountain: the outflow referring to the counterflow at the horizontal plane of the source. The fluxes are expressed in terms of the fountain source conditions and two dimensionless functions of the source Froude number, Fr0: a radial function (relating a horizontal scale of the outflow to the source radius) and a volume flux function (relating the outflow and source volume fluxes). The forms taken by these two functions at low Fr0 and high Fr0 are deduced, thereby providing the outflow fluxes and outflow Froude number solely in terms of the source conditions. For high Fr0, the outflow Froude number, Frout, is shown to be invariant, indicating (by analogy with plumes for which the 'far-field' Froude number is invariant with source Froude number) that the outflow may be regarded as 'far-field' since the fluxes within the fountain have adjusted to attain a balance which is independent of the source conditions. Based on Frout, the fluxes in the plume that forms beyond the fountain outflow are deduced. Finally, from the results of previously published studies, we show that the scalings deduced for fountains are valid for 0.0025 ≲ Fr0 ≲ 1.0 for low Fr0 and Fr0≳ 3.0 for high Fr0. © 2014 Cambridge University Press.

Two cathelicidin genes are present in both rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar)

Further to the previous finding of the rainbow trout rtCATH_1 gene, this paper describes three more cathelicidin genes found in salmonids: two in Atlantic salmon, named asCATH_1 and asCATH_2, and one in rainbow trout, named rtCATH_2. All the three new salmonid cathelicidin genes share the common characteristics of mammalian cathelicidin genes, such as consisting of four exons and possessing a highly conserved preproregion and four invariant cysteines clustered in the C-terminal region of the cathelin-like domain. The asCATH_1 gene is homologous to the rainbow trout rtCATH_1 gene, in that it possesses three repeat motifs of TGGGGGTGGC in exon IV and two cysteine residues in the predicted mature peptide, while the asCATH_2 gene and rtCATH_2 gene are homologues of each other, with 96% nucleotide identity. Salmonid cathelicidins possess the same elastase-sensitive residue, threonine, as hagfish cathelicidins and the rabbit CAP18 molecule. The cleavage site of the four salmonid cathelicidins is within a conserved amino acid motif of QKIRTRR, which is at the beginning of the sequence encoded by exon W. Two 36-residue peptides corresponding to the core part of rtCATH_1 and rtCATH_2 were chemically synthesized and shown to exhibit potent antimicrobial activity. rtCATH_2 was expressed constitutively in gill, head kidney, intestine, skin and spleen, while the expression of rtCATH_1 was inducible in gill, head kidney, and spleen after bacterial challenge. Four cathelicidin genes have now been characterized in salmonids and two were identified in hagfish, confirming that cathelicidin genes evolved early and are likely present in all vertebrates.

Single-electron tunneling depressing synapse for cellular neural networks

In this paper, a cellular neural network with depressing synapses for contrast-invariant pattern classification and synchrony detection is presented, starting from the impulse model of the single-electron tunneling junction. The results of the impulse model and the network are simulated using simulation program with integrated circuit emphasis (SPICE). It is demonstrated that depressing synapses should be an important candidate of robust systems since they exhibit a rapid depression of excitatory postsynaptic potentials for successive presynaptic spikes.

Aharonov-Bohm oscillation and chirality effect in optical activity of single-wall carbon nanotubes

We study the Aharonov-Bohm effect in the optical phenomena of single-wall carbon nanotubes (SWCN) and also their chirality dependence. Especially, we consider the natural optical activity as a proper observable and derive its general expression based on a comprehensive symmetry analysis, which reveals the interplay between the enclosed magnetic flux and the tubule chirality for arbitrary chiral SWCN. A quantitative result for this optical property is given by a gauge invariant tight-binding approximation calculation to stimulate experimental measurements.

Digits speech recognition based on geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems.We observe that this may be true for a recognition tasks based on geometrical learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions via the Hilbert transform. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy, Experiments show method based on ICA and geometrical learning outperforms HMM in different number of train samples.

Continuous speech recognition based on ICA and geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.

Continuous speech recognition based on ICA and geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.