Formative time lags in nitrogen, oxygen and dry air In crossed electric and magnetic fields

Formative time lags in nitrogen, oxygen, and dry air are measured with and without a magnetic field over a range of gas pressures (0.05 ' p ' 20.2 torr 5 kPa to 2 MPa, electric field strengths (1.8xO14 EEs 60xlO V m l) and magnetic field strengths (85xl0-4 < B ' 16x10-2 Tesla). For experiments below the Paschen minimum, the electrodes are designed to ensure that breakdown occurs over longer gaps and for experiments above the Paschen minimum, a coaxial cylindrical system is employed. The experimental technique consists of applying pulse voltages to the gap at various constant values of E/p and B/p and measuring the time lags from which the formative time lags are separated. In the gases studed, formative time lags decrease on application of a magnetic field at a given pressure for conditions below the Paschen minimum. The voltages at which the formative time lags remain the same without and with magnetic fields are determined, and electron molecule collision frequencies (v/p) are determined using the Effective Reduced Electric Field [EREF] concept. With increasing ratio of E/p in crossed fields, v/p decreases in all the three gases. Measurements above the Paschen minimum yield formative time lags which increase on application of a magnetic field. Formative time lags in nitrogen in ExB fields are calculated assuming an average collision frequency of 8.5x109 sec-1 torr 1. It is concluded that the EREF concept can be applied to explain formative time lags in ExB fields.

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

A unified approach to the gauging of space-time and internal symmetries

The properties of the manifold of a Lie groupG, fibered by the cosets of a sub-groupH, are exploited to obtain a geometrical description of gauge theories in space-timeG/H. Gauge potentials and matter fields are pullbacks of equivariant fields onG. Our concept of a connection is more restricted than that in the similar scheme of Ne'eman and Regge, so that its degrees of freedom are just those of a set of gauge potentials forG, onG/H, with no redundant components. The ldquotranslationalrdquo gauge potentials give rise in a natural way to a nonsingular tetrad onG/H. The underlying groupG to be gauged is the groupG of left translations on the manifoldG and is associated with a ldquotrivialrdquo connection, namely the Maurer-Cartan form. Gauge transformations are all those diffeomorphisms onG that preserve the fiber-bundle structure.

Time- and Temperature-Dependent Study in the Three-Component Zinc-Triazolate-Oxybis(benzoate) System: Stabilization of New Topologies

Three new three-dimensional zinc-triazolate-oxybis(benzoate) compounds. [{Zn-3(H2O)(2)}{C12H8O(COO)(2)}(2)-{C2H2N3}(2)]center dot 2H(2)O(I), [Zn-7{C12H8O(COO)(2)}(4){C2H2N3}(6)]center dot H2O, (II), and[{Zn-5(OH)(2)}{C12H8O(COO)(2)}(3){C2H2N3}(2)] (III), synthesized by a hydrothermal reaction of a mixture of Zn(OAc)(2)center dot 2H(2)O, 4,4'-oxybis(benzoic acid), 1,2,4-triazole, NaOH, and water. Compound I has an interpenetrated diamond structure and II and III have pillared-layer related structures. The formation of a hydrated phase (I) at low temperature and a completely dehydrated phase (III) at high temperature suggests the importance of thermodynamic factors in the formation of three compounds. Transformation studies of I in the presence of water shows the formation of a simple Zn-OBA compound, [Zn(OBA)(H2O)] (IV), at 150 and 180 degrees C and compound III at 200 degrees C. The compounds have been characterized by single-crystal X-ray diffraction, powder X-ray diffraction. thermogravimetric analysis, IR, and photoluminescence studies.

Ultrafast Switching Time and Third Order Nonlinear Coefficients of Microwave Treated Single Walled Carbon Nanotube Suspensions

Microwave treated water soluble and amide functionalized single walled carbon nanotubes have been investigated using femtosecond degenerate pump-probe and nonlinear transmission experiments. The time resolved differential transmission using 75 femtosecond pulse with the central wavelength of 790 nm shows a bi-exponential ultrafast photo-bleaching with time constants of 160 fs (130 fs) and 920 fs (300 fs) for water soluble (amide functionalized) nanotubes. Open and closed aperture z-scans show saturation absorption and positive (negative) nonlinear refraction for water soluble (amide functionalized) nanotubes. Two photon absorption coefficient, beta(0) similar to 250 cm/GW (650 cm/GW) and nonlinear index, gamma similar to 15 cm(2)/pW (-30 cm(2)/pW) are obtained from the theoretical fit in the saturation limit to the data for two types of nanotubes.

Time and Energy Complexity of Distributed Computation of a Class of Functions in Wireless Sensor Networks

We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

The fluorescence of Nd3+ in lead borate and bismuth borate glasses with large stimulated emission cross section

The stimulated emission cross section σp for the 1060 nm transition of Nd3+ in lead borate and bismuth borate glasses has been determined from fluorescence measurements. The compositional dependence of σp, which has been evaluated using radiative transition probability, refractive index of the host glass, effective fluorescence linewidth, and position of the band, with PbO/Bi2O3 content is investigated. The σp values of the 1060 nm band of Nd3+ for lead borate and bismuth borate glasses are found to be in the range 2.6–5.7×10−20 cm2 at 298 K and 3.0–6.3×10−20 cm2 at 4.2 K. The σp values are comparatively large suggesting the possible utilization of these materials in laser applications.

Time and Frequency Domain Finite Element Models for Axial Wave Analysis in Hyperelastic Rods

The propagation of axial waves in hyperelastic rods is studied using both time and frequency domain finite element models. The nonlinearity is introduced using the Murnaghan strain energy function and the equations governing the dynamics of the rod are derived assuming linear kinematics. In the time domain, the standard Galerkin finite element method, spectral element method, and Taylor-Galerkin finite element method are considered. A frequency domain formulation based on the Fourier spectral method is also developed. It is found that the time domain spectral element method provides the most efficient numerical tool for the problem considered.

Microstructure and dry sliding wear resistance evaluation of plasma nitrided austenitic stainless steel type AISI 316LN against different sliders

In this work, Plasma Nitriding was carried out at a temperature of 570 degrees C on nuclear grade austenitic stainless steel type AISI 316 LN (316LN SS) in a gas mixture of 20% N-2-80% H-2 to improve the surface hardness and thereby sliding wear resistance. The Plasma Nitride (PN) treated surface has been characterized by Vickers microhardness measurements, Scanning Electron Microscopic (SEM) examination, X-ray Diffraction (XRD) and sliding wear assessment. The average thickness of the PN layer was found to be 70 mu m. Microhardness measurements showed a significant increase in the hardness from 210 HV25g (unnitrided sample) to 1040 HV25g (Plasma Nitrided sample). The XRD reveals that PN layer consists of CrN, Fe4N and Fe3N phases along with austenite phase. The tribological parameters such as the friction coefficient and wear mechanism have been evaluated at ambient conditions for PN treated ring (PN ring) vs. ASTM A453 grade 660 pin (ASTM pin), PN ring vs. Nickel based alloy hard faced pin (Colmonoy pin), PN ring vs. 316LN SS pin and 316LN SS ring vs. 316LN SS pin. The wear tracks have been analyzed by SEM, Energy Dispersive X-ray Analysis (EDX) and Optical Profilometry. The untreated 316LN SS ring vs. 316LN SS pin produced severe wear and was characterized by a combination of delamination and adhesion wear mechanism, whereas wear mechanism of the PN rings reveals mild abrasion and a transfer layer from pin materials. (C) 2012 Elsevier B.V. All rights reserved.

A new approach for understanding ion transport in glasses; example of complex alkali diborate glasses containing lead, bismuth and tellurium oxides

Mechanism of ion transport in glasses continues to be incompletely understood. Several of the theoretical models in vogue fail to rationalize conductivity behaviour when d.c. and a.c. measurements are considered together. While they seem to involve the presence of at least two components in d.c. activation energy, experiments fail to reveal that feature. Further, only minor importance is given to the influence of structure of the glass on the ionic conductivity behaviour. In this paper, we have examined several general aspects of ion transport taking the example of ionically conducting glasses in pseudo binary, yNa(2)B(4)O(7)center dot(1-y) M (a) O (b) (with y = 0 center dot 25-0 center dot 79 and M (a) O (b) = PbO, TeO2 and Bi2O3) system of glasses which have also been recently characterized. Ion transport in them has been studied in detail. We have proposed that non-bridging oxygen (NBO) participation is crucial to the understanding of the observed conductivity behaviour. NBO-BO switching is projected as the first important step in ion transport and alkali ion jump is a subsequent event with a characteristically lower barrier which is, therefore, not observed in any study. All important observations in d.c. and a.c. transport in glasses are found consistent with this model.

Dependence of electron recombination time and light to electricity conversion efficiency on shape of the nanocrystal light sensitizer

Tunability of electron recombination time and light to electricity conversion efficiency to superior values in semiconductor sensitized solar cells via optimized design of nanocrystal light sensitizer shape is discussed here.

Wet and dry spell characteristics of global tropical rainfall

In this study, we analyze satellite-based daily rainfall observations to compare and contrast the wet and dry spell characteristics of tropical rainfall. Defining a wet (dry) spell as the number of consecutive rainy (nonrainy) days, we find that the distributions of wet spells appear to exhibit universality in the following sense. While both ocean and land regions with high seasonal rainfall accumulation (humid regions; e. g., India, Amazon, Pacific Ocean) show a predominance of 2-4 day wet spells, those regions with low seasonal rainfall accumulation (arid regions; e. g., South Atlantic, South Australia) exhibit a wet spell duration distribution that is essentially exponential in nature, with a peak at 1 day. The behavior that we observed for wet spells is reversed for the dry spell characteristics. In other words, the main contribution to the dry part of the season, in terms of the number of nonrainy days, appears to come from 3-4 day dry spells in the arid regions, as opposed to 1 day dry spells in the humid regions. The total rainfall accumulated in each wet spell has also been analyzed, and we find that the major contribution to seasonal rainfall for arid regions comes from 1-5 day wet spells; however, for humid regions, this contribution comes from wet spells of duration as long as 30 days. We also explore the role of chance as well as the influence of organized convection in determining some of the observed features.

Polynomial time and parameterized approximation algorithms for boxicity

The boxicity (cubicity) of a graph G, denoted by box(G) (respectively cub(G)), is the minimum integer k such that G can be represented as the intersection graph of axis parallel boxes (cubes) in ℝ k . The problem of computing boxicity (cubicity) is known to be inapproximable in polynomial time even for graph classes like bipartite, co-bipartite and split graphs, within an O(n 0.5 − ε ) factor for any ε > 0, unless NP = ZPP. We prove that if a graph G on n vertices has a clique on n − k vertices, then box(G) can be computed in time n22O(k2logk) . Using this fact, various FPT approximation algorithms for boxicity are derived. The parameter used is the vertex (or edge) edit distance of the input graph from certain graph families of bounded boxicity - like interval graphs and planar graphs. Using the same fact, we also derive an O(nloglogn√logn√) factor approximation algorithm for computing boxicity, which, to our knowledge, is the first o(n) factor approximation algorithm for the problem. We also present an FPT approximation algorithm for computing the cubicity of graphs, with vertex cover number as the parameter.