Interaction of Sesbania mosaic virus movement protein with the coat protein - implications for viral spread

Sesbania mosaic virus (SeMV) is a single-stranded positive-sense RNA plant virus belonging to the genus Sobemovirus. The movement protein (MP) encoded by SeMV ORF1 showed no significant sequence similarity with MPs of other genera, but showed 32% identity with the MP of Southern bean mosaic virus within the Sobemovirus genus. With a view to understanding the mechanism of cell-to-cell movement in sobemoviruses, the SeMV MP gene was cloned, over-expressed in Escherichia coli and purified. Interaction of the recombinant MP with the native virus (NV) was investigated by ELISA and pull-down assays. It was observed that SeMV MP interacted with NV in a concentration- and pH-dependent manner. Analysis of N- and C-terminal deletion mutants of the MP showed that SeMV MP interacts with the NV through the N- terminal 49 amino acid segment. Yeast two-hybrid assays confirmed the in vitro observations, and suggested that SeMV might belong to the class of viruses that require MP and NV/coat protein for cell-to-cell movement.

Interaction of Sesbania Mosaic Virus Movement Protein with VPg and P10: Implication to Specificity of Genome Recognition

Sesbania mosaic virus (SeMV) is a single strand positive-sense RNA plant virus that belongs to the genus Sobemovirus. The mechanism of cell-to-cell movement in sobemoviruses has not been well studied. With a view to identify the viral encoded ancillary proteins of SeMV that may assist in cell-to-cell movement of the virus, all the proteins encoded by SeMV genome were cloned into yeast Matchmaker system 3 and interaction studies were performed. Two proteins namely, viral protein genome linked (VPg) and a 10-kDa protein (P10) c v gft encoded by OFR 2a, were identified as possible interacting partners in addition to the viral coat protein (CP). Further characterization of these interactions revealed that the movement protein (MP) recognizes cognate RNA through interaction with VPg, which is covalently linked to the 59 end of the RNA. Analysis of the deletion mutants delineated the domains of MP involved in the interaction with VPg and P10. This study implicates for the first time that VPg might play an important role in specific recognition of viral genome by MP in SeMV and shed light on the possible role of P10 in the viral movement.

A Generalized Enthalpy Update Scheme for Solidification of a Binary Alloy with Solid Phase Movement

A generalized enthalpy update scheme is presented for evaluating solid and liquid fractions during the solidification of binary alloys, taking solid movement into consideration. A fixed-grid, enthalpy-based method is developed such that the scheme accounts for equilibrium as well as for nonequilibrium solidification phenomena, along with solid phase movement. The effect of solid movement on the solidification interface shape and macrosegregation is highlighted.

Critical behavior at depinning of driven disordered vortex matter in 2H-NbS2

We report unusual jamming in driven ordered vortex flow in 2H-NbS2. Reinitiating movement in these jammed vortices with a higher driving force and halting it thereafter once again with a reduction in drive leads to a critical behavior centered around the depinning threshold via divergences in the lifetimes of transient states, validating the predictions of a recent simulation study Reichhardt and Olson Reichhardt, Phys. Rev. Lett. 103, 168301 (2009)] which also pointed out a correspondence between plastic depinning in vortex matter and the notion of random organization proposed Corte et al., Nat. Phys. 4, 420 (2008)] in the context of sheared colloids undergoing diffusive motion.

Predatory Fish Select for Coordinated Collective Motion in Virtual Prey

Movement in animal groups is highly varied and ranges from seemingly disordered motion in swarms to coordinated aligned motion in flocks and schools. These social interactions are often thought to reduce risk from predators, despite a lack of direct evidence. We investigated risk-related selection for collective motion by allowing real predators ( bluegill sunfish) to hunt mobile virtual prey. By fusing simulated and real animal behavior, we isolated predator effects while controlling for confounding factors. Prey with a tendency to be attracted toward, and to align direction of travel with, near neighbors tended to form mobile coordinated groups and were rarely attacked. These results demonstrate that collective motion could evolve as a response to predation, without prey being able to detect and respond to predators.

Gasification of wood particles in a co-current packed bed: Experiments and model analysis

This study focuses on addressing the propagation front movement in a co-current downdraft gasification system. A detailed single particle modeling analysis extended to the packed bed reactor is used to compare with the experimental measurement as well those available in the literature. This model for biomass gasification systems considered pyrolysis process, gas phase volatile combustion, and heterogeneous char reactions along with gas phase reactions in the packed bed. The pyrolysis kinetics has a critical influence on the gasification process. The propagation front has been shown to increase with air mass flux, attains a peak and then decreases with further increase in air mass flux and finally approaches negative propagation rate. This indicates that front is receding, or no upward movement() bra her it is moving downward towards the char bed. The propagation rate correlates with mass flux as (m) over dot `'(0.883) during the increasing regimes of the front movement The study clearly identifies that bed movement is an important parameter for consideration in a co-current configuration towards establishing the effective bed movement. The study also highlights the importance of surface area to volume ratio of the particles in the packed bed and its influence on the volatile generation. Finally, the gas composition for air gasification under various air mass fluxes is compared with the experimental results. (C) 2016 Elsevier B.V. All rights reserved.

Darwin as a botanist

Charles Darwin on his voyage aboard H. M. S. Beagle contracted a mysterious illness that persisted throughout his life. Despite being ill, he continued his writings. He is remembered as the scientist who putforth the theory that species are changing. A species evolves by the accumulation and preservation of successive slight favourable variations, now known as mutations. In his quest to strengthen his theory on the common origin of all life, and evolution by natural selection, he increasingly turned to plants and carried out experiments at his home-cum-laboratory, focusing on phenomena commonly associated with animals namely, movement. In plant roots, seedlings and climbing plants, he described nyctitropism, geotropism, phototropism and circumnutation. Darwin described the sleep movements in plants in which the petiole hangs down and the leaflets press together in the evening.

Ultrasonic wave characteristics of a monolayer graphene on silicon substrate

The present work deals with an ultrasonic type of wave propagation characteristics of monolayer graphene on silicon (Si) substrate. An atomistic model of a hybrid lattice involving a hexagonal lattice of graphene and surface atoms of diamond lattice of Si is developed to identify the carbon-silicon bond stiffness. Properties of this hybrid lattice model is then mapped into a nonlocal continuum framework. Equivalent force constant due to Si substrate is obtained by minimizing the total potential energy of the system. For this equilibrium configuration, the nonlocal governing equations are derived to analyze the ultrasonic wave dispersion based on spectral analysis. From the present analysis we show that the silicon substrate affects only the flexural wave mode. The frequency band gap of flexural mode is also significantly affected by this substrate. The results also show that, the silicon substrate adds cushioning effect to the graphene and it makes the graphene more stable. The analysis also show that the frequency bang gap relations of in-plane (longitudinal and lateral) and out-of-plane (flexural) wave modes depends not only on the y-direction wavenumber but also on nonlocal scaling parameter. In the nonlocal analysis, at higher values of the y-directional wavenumber, a decrease in the frequency band gap is observed for all the three fundamental wave modes in the graphene-silicon system. The atoms movement in the graphene due to the wave propagation are also captured for all the tree fundamental wave modes. The results presented in this work are qualitatively different from those obtained based on the local analysis and thus, are important for the development of graphene based nanodevices such as strain sensor, mass and pressure sensors, atomic dust detectors and enhancer of surface image resolution that make use of the ultrasonic wave dispersion properties of graphene. (C) 2011 Elsevier Ltd. All rights reserved.

An Optical How Feature and McFIS Based Approach for 3-Dimensional Human Action Recognition

We propose to develop a 3-D optical flow features based human action recognition system. Optical flow based features are employed here since they can capture the apparent movement in object, by design. Moreover, they can represent information hierarchically from local pixel level to global object level. In this work, 3-D optical flow based features a re extracted by combining the 2-1) optical flow based features with the depth flow features obtained from depth camera. In order to develop an action recognition system, we employ a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). The m of McFIS is to find the decision boundary separating different classes based on their respective optical flow based features. McFIS consists of a neuro-fuzzy inference system (cognitive component) and a self-regulatory learning mechanism (meta-cognitive component). During the supervised learning, self-regulatory learning mechanism monitors the knowledge of the current sample with respect to the existing knowledge in the network and controls the learning by deciding on sample deletion, sample learning or sample reserve strategies. The performance of the proposed action recognition system was evaluated on a proprietary data set consisting of eight subjects. The performance evaluation with standard support vector machine classifier and extreme learning machine indicates improved performance of McFIS is recognizing actions based of 3-D optical flow based features.