Asymmetric cell division of granule neuron progenitors in the external granule layer of the mouse cerebellum

The plane of division of granule neuron progenitors (GNPs) was analysed with respect to the pial surface in P0 to P14 cerebellum and the results showed that there was a significant bias towards the plane of cell division being parallel to pial surface across this developmental window. In addition, the distribution of beta-Catenin in anaphase cells was analysed, which showed that there was a significant asymmetry in the distribution of beta-Catenin in dividing GNPs. Further, inhibition of Sonic Hedgehog (Shh) signalling had an effect on plane of cell division. Asymmetric distribution of beta-Catenin was shown to occur towards the source of a localized extracellular cue.

Improved capacity and stability of integrated Li and Mn rich layered-spinel Li1.17Ni0.25Mn1.08O3 cathodes for Li-ion batteries

A Li-rich layered-spinel material with a target composition Li1.17Ni0.25Mn1.08O3 (xLiLi1/3Mn2/3]O-2.(1 - x) LiNi0.5Mn1.5O4, (x = 0.5)) was synthesized by a self-combustion reaction (SCR), characterized by XRD, SEM, TEM, Raman spectroscopy and was studied as a cathode material for Li-ion batteries. The Rietveld refinement results indicated the presence of monoclinic (LiLi1/3Mn2/3]O-2) (52%), spinel (LiNi0.5Mn1.5O4) (39%) and rhombohedral LiNiO2 (9%). The electrochemical performance of this Li-rich integrated cathode material was tested at 30 degrees C and compared to that of high voltage LiNi0.5Mn1.5O4 spinel cathodes. Interestingly, the layered-spinel integrated cathode material exhibits a high specific capacity of about 200 mA h g(-1) at C/10 rate as compared to 180 mA h g(-1) for LiNi0.5Mn1.5O4 in the potential range of 2.4-4.9 V vs. Li anodes in half cells. The layered-spinel integrated cathodes exhibited 92% capacity retention as compared to 82% for LiNi0.5Mn1.5O4 spinel after 80 cycles at 30 degrees C. Also, the integrated cathode material can exhibit 105 mA h g(-1) at 2 C rate as compared to 78 mA h g(-1) for LiNi0.5Mn1.5O4. Thus, the presence of the monoclinic phase in the composite structure helps to stabilize the spinel structure when high specific capacity is required and the electrodes have to work within a wide potential window. Consequently, the Li1.17Ni0.25Mn1.08O3 composite material described herein can be considered as a promising cathode material for Li ion batteries.

Thermal and spectroscopic investigations of glasses in the system PbO-PbCl2-PbBr2

Glass formation has been examined in the system 15PbO.xPbCl(2).(85-x)PbBr2 (where 0 <= x <= 25)where the PbO concentration is kept constant while PbCl2 and PbBr2 concentrations are varied. The glasses have been examined using thermal and spectroscopic techniques. T-8, Delta C-p, refractive index, optical basicity have been found to remain unaffected by the composition which is a curious feature of these glasses. It is found that there is a wide infrared window available for use in the investigated glasses. The IR window extends from 1000 to 1500 cm(-1) and in glasses where PbCl2 is less than 20 mol%, the window extends up to 2260 cm(-1). X-ray photoelectron spectra (XPS) revealed that the 4f(5/2) and 4f(7/2) peaks due to f-level transitions have a constant difference in energies, but with energy and FWHM values that varying sensitively and systematically with composition. The observations are discussed and suitable explanations are provided.

Active dendrites mediate stratified gamma-range coincidence detection in hippocampal model neurons

Hippocampal pyramidal neurons exhibit gamma-phase preference in their spikes, selectively route inputs through gamma frequency multiplexing and are considered part of gamma-bound cell assemblies. How do these neurons exhibit gamma-frequency coincidence detection capabilities, a feature that is essential for the expression of these physiological observations, despite their slow membrane time constant? In this conductance-based modelling study, we developed quantitative metrics for the temporal window of integration/coincidence detection based on the spike-triggered average (STA) of the neuronal compartment. We employed these metrics in conjunction with quantitative measures for spike initiation dynamics to assess the emergence and dependence of coincidence detection and STA spectral selectivity on various ion channel combinations. We found that the presence of resonating conductances (hyperpolarization-activated cyclic nucleotide-gated or T-type calcium), either independently or synergistically when expressed together, led to the emergence of spectral selectivity in the spike initiation dynamics and a significant reduction in the coincidence detection window (CDW). The presence of A-type potassium channels, along with resonating conductances, reduced the STA characteristic frequency and broadened the CDW, but persistent sodium channels sharpened the CDW by strengthening the spectral selectivity in the STA. Finally, in a morphologically precise model endowed with experimentally constrained channel gradients, we found that somatodendritic compartments expressed functional maps of strong theta-frequency selectivity in spike initiation dynamics and gamma-range CDW. Our results reveal the heavy expression of resonating and spike-generating conductances as the mechanism underlying the robust emergence of stratified gamma-range coincidence detection in the dendrites of hippocampal and cortical pyramidal neurons.

Crustal Evolution of Kolli-Massif, Southern India

Southern India is a collage of numerous crustal fragments formed since the Archean (2500 Ma ago) and reworked several times during the geological history. A close look at these terrains provides a window to understand the crustal evolutionary processes experienced by the continental crust in the past, such as crustal growth (formation of crust through addition of new magma) and crustal reworking (modification of an already existing crust). Here we discuss the evolutionary history of such a crustal fragment from the Southern Granulite Terrain (SGT) in peninsular India, namely Kolli-massif. Geology, structural deformation through time, and the implications in crustal assembly of southern India are exponded.

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

Part I: High-Voltage MOS Device Design for Improved Static and RF Performance

In this paper, for the first time, the key design parameters of a shallow trench isolation-based drain-extended MOS transistor are discussed for RF power applications in advanced CMOS technologies. The tradeoff between various dc and RF figures of merit (FoMs) is carefully studied using well-calibrated TCAD simulations. This detailed physical insight is used to optimize the dc and RF behavior, and our work also provides a design window for the improvement of dc as well as RF FoMs, without affecting the breakdown voltage. An improvement of 50% in R-ON and 45% in RF gain is achieved at 1 GHz. Large-signal time-domain analysis is done to explore the output power capability of the device.

Nanoparticle induced miscibility in LCST polymer blends: critically assessing the enthalpic and entropic effects

The use of copolymer and polymer blends widened the possibility of creating materials with multilayered architectures. Hierarchical polymer systems with a wide array of micro and nanostructures are generated by thermally induced phase separation (TIPS) in partially miscible polymer blends. Various parameters like the interaction between the polymers, concentration, solvent/non-solvent ratio, and quenching temperature have to be optimized to obtain these micro/nanophase structures. Alternatively, the addition of nanoparticles is another strategy to design materials with desired hetero-phase structures. The dynamics of the polymer nanocomposite depends on the statistical ordering of polymers around the nanoparticle, which is dependent on the shape of the nanoparticle. The entropic loss due to deformation of polymer chains, like the repulsive interactions due to coiling and the attractive interactions in the case of swelling has been highlighted in this perspective article. The dissipative particle dynamics has been discussed and is correlated with the molecular dynamics simulation in the case of polymer blends. The Cahn Hillard Cook model on variedly shaped immobile fillers has shown difference in the propagation of the composition wave. The nanoparticle shape has a contributing effect on the polymer particle interaction, which can change the miscibility window in the case of these phase separating polymer blends. Quantitative information on the effect of spherical particles on the demixing temperature is well established and further modified to explain the percolation of rod shaped particles in the polymer blends. These models correlate well with the experimental observations in context to the dynamics induced by the nanoparticle in the demixing behavior of the polymer blend. The miscibility of the LCST polymer blend depends on the enthalpic factors like the specific interaction between the components, and the solubility product and the entropic losses occurring due to the formation of any favorable interactions. Hence, it is essential to assess the entropic and enthalpic interactions induced by the nanoparticles independently. The addition of nanoparticles creates heterogeneity in the polymer phase it is localized. This can be observed as an alteration in the relaxation behavior of the polymer. This changes the demixing behavior and the interaction parameter between the polymers. The compositional changes induced due to the incorporation of nanoparticles are also attributed as a reason for the altered demixing temperature. The particle shape anisotropy causes a direction dependent depletion, which changes the phase behavior of the blend. The polymer-grafted nanoparticles with varying grafting density show tremendous variation in the miscibility of the blend. The stretching of the polymer chains grafted on the nanoparticles causes an entropy penalty in the polymer blend. A comparative study on the different shaped particles is not available up to date for understanding these aspects. Hence, we have juxtaposed the various computational studies on nanoparticle dynamics, the shape effect of NPs on homopolymers and also the cases of various polymer blends without nanoparticles to sketch a complete picture on the effect of various particles on the miscibility of LCST blends.

Damage assessment of composite plate structures with material and measurement uncertainty

Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problein in damage assessment. A recently developed C-0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data. (C) 2016 Elsevier Ltd. All rights reserved.