Structural Phase Transition of Ytterbium Nitride under High Pressure

The structural and elastic properties of ytterbium nitride (YbN) with NaCl structure have been investigated by using an improved interaction potential model (IIPM). The compound YbN found to undergo from their initial NaCl (B1) phase to body centered tetragonal (BCT) phase at high pressure. The phase transition pressures and associated volume collapses obtained from the potential model developed here show a generally better agreement with available experimental data then others available in the literature. The elastic constants are also reported. This shows that the inclusion of three-body interaction and polarizability effect makes the present model suitable for high pressure studies. Keywords: Rare earth pnictides, three body interaction, phase transition, volume collapse

High Pressure Structural Properties of Rare-earth Antimonide

In the present paper, we have investigated the high-pressure structural phase transition of  rare-earth antimonide. We studied theoretically the structural properties of this compound (DySb) by using the three-body potential model with the effect of electronic polarizability (TBIPEP). These compounds exhibits first order crystallographic phase transition from NaCl (B1) to CsCl (B2) phase at 22.6 GPa respectively. The phase transition pressures and associated volume collapse obtained from present potential model(TBIPEP) show a good agreement with available experimental data. Keywords: High Pressure, Crystal Structure, Volume Collaps

Many people- many perspectives

Generally when thinking or speaking about any theme sometimes it is possible to arrive at a consensus of various viewpoints while sometimes it is not. To look at the world with open eyes everybody has their own perspective

FastRecover: simple and effective fault recovery in a distributed operator-based stream processing engine

Fault tolerance is a key requirement in large-scale distributed stream processing engines (SPEs), especially those that run atop commodity hardware. Currently, fault tolerance in popular distributed SPEs is either inadequate (e.g., those without automatic recovery of operator states) or complex and inefficient (e.g., those with transactional semantics). There are two major considerations in the design of an effective fault tolerance mechanism: the overhead of additional checkpointing operations during normal processing, and the time required to recover and return to normal processing when a failure happens. The main challenge lies in that faster recovery requires higher checkpointing overhead, and vice versa. This thesis presents FastRecover, a novel fault tolerance mechanism for distributed SPEs that strikes a balance between recovery time and checkpointing overhead. Specifically, given an application topology consisting of interconnected operators, and an upper bound on checkpoint overhead, FastRecover computes the optimal expected recovery time, as well as the strategy used for checkpointing and recovery in each operator. The main idea of FastRecover is to compute an optimal partitioning of the streaming operator topology into independent segments; for each segment, FastRecover backs up its input tuples and periodically checkpoints the states of operators therein. During recovery for a particular segment, FastRecover restores each affected operator state in the segment to the latest checkpoint, and replays the inputs of the segment since then. Both checkpointing and recovery utilize the parallel processing capabilities of the distributed SPE. Extensive experiments demonstrate that FastRecover achieves an average of 50% reduction in expected recovery time compared to simple solutions. The experiments also show that the total expected recovery time varies proportionally to the total computational recovery time and recovery latency in tests with simulated failures, and hence is a good measure to optimize

Dimensions Selection Criteria of Stair shaped Slot for Obtaining the Wideband Response of CPDRA

The analysis of a circularly polarised (CP) dielectric resonator antenna (DRA) with the aperture coupled feeding technique is presented in this paper. Until now, the random techniques have been developed for obtaining the CP response in DRA. It is glaringly required to develop a fixed mathematical criterion for the selection of dimensions of the antenna structure. The criterion for selection of the stair-shaped slot dimensions, which is utilised for obtaining the CP response, is defined in this paper. The ranges of slot length ratios are investigated so that a wide CP bandwidth can be obtained. The antenna offers the 10-dB impedance of 58.62% (4.1 GHz - 7.5 GHz) and 3-dB axial ratio bandwidth of 40.86 per cent (4.26GHz - 6.385 GHz)

Impacts of 1.5 °C and 2 °C global warming on regional rainfall and temperature change across India

For a country like India with a primarily agrarian economy, limiting warming to 1.5 °C leads to two key questions: what does the global rise of temperature (1.5 °C and 2.0 °C) mean at the regional scale? and; what are the implications of keeping warming at or below 1.5 °C in particular for agriculture and water resources? Regional level analysis can provide a more segregated picture than a global one based on combined metrics. Details of this study show the distribution of predicted values of changes in regional annual rainfall for the 29 States of India obtained using the 78 General Circulation Model (GCM) models Representative Concentration Pathway (RCP 8.5) and 105 GCM models (RCP 4.5).UK Government’s Department for International Development (DfID

Temperatures and rainfall extremes change under current and future global warming levels across Indian climate zones

This detailed study analyzes the changes in extreme temperature and precipitation events at annual timescales over different climatic zones of India under stringent stabilization targets (RCP4.5) as well as the unmitigated scenario (RCP8.5), estimated from the coupled model inter-comparison project (CMIP5). Annual total precipitation and heavy rainfall-related extreme indices show statistically significant increases in tropical, temperate and semi-arid regions, moving from 1 °C to 3 °C warming level (RCP8.5 scenario). Climate extremes will have far-reaching impacts on social and economic statuses of the respective climate zones. It demands response from national and state action plans on climate change and adaptation in order to create integrated policy decisions

Reference Evapotranspiration Retrievals from a Mesoscale Model Based Weather Variables for Soil Moisture Deficit Estimation

Reference Evapotranspiration (ETo) and soil moisture deficit (SMD) are vital for understanding the hydrological processes, particularly in the context of sustainable water use efficiency in the globe. Precise estimation of ETo and SMD are required for developing appropriate forecasting systems, in hydrological modeling and also in precision agriculture. In this study, the surface temperature downscaled from Weather Research and Forecasting (WRF) model is used to estimate ETo using the boundary conditions that are provided by the European Center for Medium Range Weather Forecast (ECMWF). In order to understand the performance, the Hamon’s method is employed to estimate the ETo using the temperature from meteorological station and WRF derived variables. After estimating the ETo, a range of linear and non-linear models is utilized to retrieve SMD. The performance statistics such as RMSE, %Bias, and Nash Sutcliffe Efficiency (NSE) indicates that the exponential model (RMSE = 0.226; %Bias = −0.077; NSE = 0.616) is efficient for SMD estimation by using the Observed ETo in comparison to the other linear and non-linear models (RMSE range = 0.019–0.667; %Bias range = 2.821–6.894; NSE = 0.013–0.419) used in this study. On the other hand, in the scenario where SMD is estimated using WRF downscaled meteorological variables based ETo, the linear model is found promising (RMSE = 0.017; %Bias = 5.280; NSE = 0.448) as compared to the non-linear models (RMSE range = 0.022–0.707; %Bias range = −0.207–−6.088; NSE range = 0.013–0.149). Our findings also suggest that all the models are performing better during the growing season (RMSE range = 0.024–0.025; %Bias range = −4.982–−3.431; r = 0.245–0.281) than the non−growing season (RMSE range = 0.011–0.12; %Bias range = 33.073–32.701; r = 0.161–0.244) for SMD estimation