Large scale read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

Regulation, pollution and heterogeneity in Japanese steam power generation companies

In this paper, the random stochastic frontier model is used to estimate the technical efficiency of Japanese steam power generation companies taking into regulation and pollution. The companies are ranked according to their productivity for the period 1976-2003 and homogenous and heterogeneous variables in the cost function are disentangled. Policy implication is derived.

Prefrontal cortex involvement in selective letter generation: A functional magnetic resonance imaging study

Cerebral responses to alternating periods of a control task and a selective letter generation paradigm were investigated with functional Magnetic Resonance Imaging (fMRI). Subjects selectively generated letters from four designated sets of six letters from the English language alphabet, with the instruction that they were not to produce letters in alphabetical order either forward or backward, repeat or alternate letters. Performance during this condition was compared with that of a control condition in which subjects recited the same letters in alphabetical order. Analyses revealed significant and extensive foci of activation in a number of cerebral regions including mid-dorsolateral frontal cortex, inferior frontal gyrus, precuneus, supramarginal gyrus, and cerebellum during the selective letter generation condition. These findings are discussed with respect to recent positron emission tomography (PET) and fMRI studies of verbal working memory and encoding/retrieval in episodic memory.

Generation of spectrum compatible accelerograms

In this paper a new method is presented for generating earthquake accelerograms which have pre-established response spectra. The non-stationary random nature and other salient features of the accelerograms can be taken care of by the procedure developed. The method leads to a sample spectrum which lies above the given spectrum. The generation of records to suit several spectra simultaneously can also be handled by this approach. The method is detailed first. This is followed by several numerical examples.

Floquet generation of Majorana end modes and topological invariants

We show how Majorana end modes can be generated in a one-dimensional system by varying some of the parameters in the Hamiltonian periodically in time. The specific model we consider is a chain containing spinless electrons with a nearest-neighbor hopping amplitude, a p-wave superconducting term, and a chemical potential; this is equivalent to a spin-1/2 chain with anisotropic XY couplings between nearest neighbors and a magnetic field applied in the (z) over cap direction. We show that varying the chemical potential (or magnetic field) periodically in time can produce Majorana modes at the ends of a long chain. We discuss two kinds of periodic driving, periodic delta-function kicks, and a simple harmonic variation with time. We discuss some distinctive features of the end modes such as the inverse participation ratio of their wave functions and their Floquet eigenvalues which are always equal to +/- 1 for time-reversal-symmetric systems. For the case of periodic delta-function kicks, we use the effective Hamiltonian of a system with periodic boundary conditions to define two topological invariants. The first invariant is a well-known winding number, while the second invariant has not appeared in the literature before. The second invariant is more powerful in that it always correctly predicts the numbers of end modes with Floquet eigenvalues equal to + 1 and -1, while the first invariant does not. We find that the number of end modes can become very large as the driving frequency decreases. We show that periodic delta-function kicks in the hopping and superconducting terms can also produce end modes. Finally, we study the effect of electron-phonon interactions (which are relevant at finite temperatures) and a random noise in the chemical potential on the Majorana modes.

Fault-tolerant secret key generation

Mobile nodes observing correlated data communicate using an insecure bidirectional switch to generate a secret key, which must remain concealed from the switch. We are interested in fault-tolerant secret key rates, i.e., the rates of secret key generated even if a subset of nodes drop out before the completion of the communication protocol. We formulate a new notion of fault-tolerant secret key capacity, and present an upper bound on it. This upper bound is shown to be tight when the random variables corresponding to the observations of nodes are exchangeable. Further, it is shown that one round of interaction achieves the fault-tolerant secret key capacity in this case. The upper bound is also tight for the case of a pairwise independent network model consisting of a complete graph, and can be attained by a noninteractive protocol.

Optimal sequential wireless relay placement on a random lattice path

Our work is motivated by impromptu (or ``as-you-go'') deployment of wireless relay nodes along a path, a need that arises in many situations. In this paper, the path is modeled as starting at the origin (where there is the data sink, e.g., the control center), and evolving randomly over a lattice in the positive quadrant. A person walks along the path deploying relay nodes as he goes. At each step, the path can, randomly, either continue in the same direction or take a turn, or come to an end, at which point a data source (e.g., a sensor) has to be placed, that will send packets to the data sink. A decision has to be made at each step whether or not to place a wireless relay node. Assuming that the packet generation rate by the source is very low, and simple link-by-link scheduling, we consider the problem of sequential relay placement so as to minimize the expectation of an end-to-end cost metric (a linear combination of the sum of convex hop costs and the number of relays placed). This impromptu relay placement problem is formulated as a total cost Markov decision process. First, we derive the optimal policy in terms of an optimal placement set and show that this set is characterized by a boundary (with respect to the position of the last placed relay) beyond which it is optimal to place the next relay. Next, based on a simpler one-step-look-ahead characterization of the optimal policy, we propose an algorithm which is proved to converge to the optimal placement set in a finite number of steps and which is faster than value iteration. We show by simulations that the distance threshold based heuristic, usually assumed in the literature, is close to the optimal, provided that the threshold distance is carefully chosen. (C) 2014 Elsevier B.V. All rights reserved.

Computer Simulation Of Random Sphere Packing In An Arbitrarily Shaped Container

Most simulations of random sphere packing concern a cubic or cylindric container with periodic boundary, containers of other shapes are rarely studied. In this paper, a new relaxation algorithm with pre-expanding procedure for random sphere packing in an arbitrarily shaped container is presented. Boundaries of the container are simulated by overlapping spheres which covers the boundary surface of the container. We find 0.4 similar to 0.6 of the overlap rate is a proper value for boundary spheres. The algorithm begins with a random distribution of small internal spheres. Then the expansion and relaxation procedures are performed alternately to increase the packing density. The pre-expanding procedure stops when the packing density of internal spheres reaches a preset value. Following the pre-expanding procedure, the relaxation and shrinking iterations are carried out alternately to reduce the overlaps of internal spheres. The pre-expanding procedure avoids the overflow problem and gives a uniform distribution of initial spheres. Efficiency of the algorithm is increased with the cubic cell background system and double link data structure. Examples show the packing results agree well with both computational and experimental results. Packing density about 0.63 is obtained by the algorithm for random sphere packing in containers of various shapes.

An agent-based multi-scale wind generation model

(EuroPES 2009)

Generation and characterization of monoclonal antibodies against the flounder Paralichthys olivaceus rhabdovirus

Two MAbs (3C7 and 3C9) against flounder Paralichthys olivaceus rhabdovirus (PORV) were generated with hybridoma cell fusion technology and characterized by an indirect enzyme-linked immunosorbent assay, isotype test, Western blot and immunodot analysis and immunofluorescence assay. Isotyping tests demonstrated that both of the two MAbs belonged to IgM subclass. Western blot analysis showed the MAbs reacted with 42, 30, and 22 kDa viral proteins, which were localized within the cytoplasm of PORV-infected grass carp ovary (GCO) cells analyzed by indirect immunofluorescences tests. The MAb 3C7 was also selected at random for detecting virus antigens in the inoculated grass carp tissues by immunohistochemistry assay. Flow cytometry tests showed that at the 36 h postinfection (0.25 PFU/cell), the 23% PORV-infected GCO cells could be distinguished from the uninfected cells with the MAb 3C7. Such MAbs could be useful for diagnosis and potential treatment of viral infection. (C) 2007 Elsevier B.V. All rights reserved.

Efficient Simulation of Freak Waves in Random Oceanic Sea States

Numerical simulations of freak wave generation are studied in random oceanic sea states described by JONSWAP spectrum. The evolution of initial random wave trains is numerically carried out within the framework of the modified four-order nonlinear Schroedinger equation (mNLSE), and some involved influence factors are also discussed. Results show that if the sideband instability is satisfied, a random wave train may evolve into a freak wave train, and simultaneously the setting of the Phillips parameter and enhancement coefficient of JONSWAP spectrum and initial random phases is very important for the formation of freak waves. The way to increase the generation efficiency of freak waves though changing the involved parameters is also presented.

Functional genomic hypothesis generation and experimentation by a robot scientist

King R. D., Whelan, K. E., Jones, F. M., Reiser, P. G. K., Bryant, C. H., Muggleton, S., Kell, D. B. and Oliver, S. G. (2004) Functional genomic hypothesis generation and experimentation by a robot scientist. Nature 427 (6971) p247-252

Numerical Simulations and Coherence Properties of Supercontinuum Generation in Photonic Crystal and Tapered Optical Fibers

Numerical simulations have been used to study broad-band supercontinuum generation in optical fibers with dispersion and nonlinearity characteristics typical and photonic crystal or tapered fibers structures. The simulations include optical shock and Raman nonlinearity terms, with quantum noise taken into account phenomenologically by including in the input field a noise seed of one photon per mode with random phase. For input pulses of 150-fs duration injected in the anomalous dispersion regime, the effect of modulational instability is shown to lead to severe temporal jitter in the output, and associated fluctuations in the spectral amplitude and phase across the generated supercontinuum. The spectral phase fluctuations are quantified by performing multiple simulations and calculating both the standard deviation of the phase and, more rigorously, the degree of first-order coherence as a function of wavelength across the spectrum. By performing simulations over a range of input pulse durations and wavelengths, we can identify the conditions under which coherent supercontinua with a well-defined spectral phase are generated.

Secure Key Generation from OFDM Subcarriers’ Channel Response

The ability to exchange keys between users is vital in any wireless based security system. A key generation technique exploits the randomness of the wireless channel is a promising alternative to existing key distribution techniques, e.g., public key cryptography. In this paper a secure key generation scheme based on the subcarriers’ channel responses in orthogonal frequencydivision multiplexing (OFDM) systems is proposed. We first implement a time-variant multipath channel with its channel impulse response modelled as a wide sense stationary (WSS) uncorrelated scattering random process and demonstrate that each subcarrier’s channel response is also a WSS random process. We then define the X% coherence time as the time required to produce an X% correlation coefficient in the autocorrelation function (ACF) of each channel tap, and find that when all the channel taps have the same Doppler power spectrum, all subcarriers’ channel responses has the same ACF as the channel taps. The subcarrier’s channel response is then sampled every X% coherence time and quantized into key bits. All the key sequences’ randomness is tested using National Institute of Standards and Technology (NIST) statistical test suite and the results indicate that the commonly used sampling interval as 50% coherence time cannot guarantee the randomness of the key sequence.

Generation of replication-proficient influenza virus NS1 point mutants with interferon-hyperinducer phenotype

The NS1 protein of influenza A viruses is the dedicated viral interferon (IFN)-antagonist. Viruses lacking NS1 protein expression cannot multiply in normal cells but are viable in cells deficient in their ability to produce or respond to IFN. Here we report an unbiased mutagenesis approach to identify positions in the influenza A NS1 protein that modulate the IFN response upon infection. A random library of virus ribonucleoproteins containing circa 40 000 point mutants in NS1 were transferred to infectious virus and amplified in MDCK cells unable to respond to interferon. Viruses that activated the interferon (IFN) response were subsequently selected by their ability to induce expression of green-fluorescent protein (GFP) following infection of A549 cells bearing an IFN promoter-dependent GFP gene. Using this approach we isolated individual mutant viruses that replicate to high titers in IFN-compromised cells but, compared to wild type viruses, induced higher levels of IFN in IFN-competent cells and had a reduced capacity to counteract exogenous IFN. Most of these viruses contained not previously reported NS1 mutations within either the RNA-binding domain, the effector domain or the linker region between them. These results indicate that subtle alterations in NS1 can reduce its effectiveness as an IFN antagonist without affecting the intrinsic capacity of the virus to multiply. The general approach reported here may facilitate the generation of replication-proficient, IFN-inducing virus mutants, that potentially could be developed as attenuated vaccines against a variety of viruses.