A comparison of three methods for downscaling daily precipitation in the Punjab region

Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K-nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue-type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright (C) 2011 John Wiley & Sons, Ltd.

Support Vector Machine Approach to Downscale Precipitation in Climate Change Scenarios

Concern over changes in global climate has increased in recent years with improvement in understanding of atmospheric dynamics and growth in evidence of climate link to long‐term variability in hydrologic records. Climate impact studies rely on climate change information at fine spatial resolution. Towards this, the past decade has witnessed significant progress in development of downscaling models to cascade the climate information provided by General Circulation Models (GCMs) at coarse spatial resolution to the scale relevant for hydrologic studies. While a plethora of downscaling models have been applied successfully to mid‐latitude regions, a few studies are available on tropical regions where the atmosphere is known to have more complex behavior. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling to interpret climate change signals provided by GCMs over tropical regions of India. Climate variables affecting spatio‐temporal variation of precipitation at each meteorological sub‐division of India are identified. Following this, cluster analysis is applied on climate data to identify the wet and dry seasons in each year. The data pertaining to climate variables and precipitation of each meteorological sub‐division is then used to develop SVM based downscaling model for each season. Subsequently, the SVM based downscaling model is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to assess the impact of climate change on hydrological inputs to the meteorological sub‐divisions. The results obtained from the SVM downscaling model are then analyzed to assess the impact of climate change on precipitation over India.

Kinetics of Sulphation of Nickel and Cobalt Ferrites with Na$O, Melt Containing F'e3+ Ions

It has been experimentally established that nickel and cobalt can be extracted from their ferrites with sodium sulphate melt containing femc ions. The kinetics of extraction from synthetic ferrites using a melt of sodium and ferric sulphates of eutectic composition has been studied as a function of the particle size of the ferrite and temperature in the range 900 to 1073 K. The divalent ions in the ferrite exchange with the ferric ion in the melt, leaving a residue of hematite.The rate of reaction conforms to the Crank-Ginstling-Brounshtein diffusion model. The reaction rate is governed by the counter-diffusion of ~ e an~d ~+i ' +(or co2+) ions in the hematite lattice. Analytical expressions for the rate constants have been derived from the experimental data as a function of particle size and temperature. The activation energy for the extraction of nickel from nickel ferrite is 154(+10) kJ mol-' and the corresponding value for cobalt is 142(+10)kJ mol;'. In sulphation roasting of minerals containing nickel, the yield of nickel is generally limited to 75% due to the formation of insoluble ferrites. The use of melts based on sodium sulphate provides a possible route for enhancing the recovery of nickel to approximately 98%.

Physically consistent simulation of mesoscale chemical kinetics: The non-negative FIS-alpha method

Biochemical pathways involving chemical kinetics in medium concentrations (i.e., at mesoscale) of the reacting molecules can be approximated as chemical Langevin equations (CLE) systems. We address the physically consistent non-negative simulation of the CLE sample paths as well as the issue of non-Lipschitz diffusion coefficients when a species approaches depletion and any stiffness due to faster reactions. The non-negative Fully Implicit Stochastic alpha (FIS alpha) method in which stopped reaction channels due to depleted reactants are deleted until a reactant concentration rises again, for non-negativity preservation and in which a positive definite Jacobian is maintained to deal with possible stiffness, is proposed and analysed. The method is illustrated with the computation of active Protein Kinase C response in the Protein Kinase C pathway. (C) 2011 Elsevier Inc. All rights reserved.

Kinetics and chemical analysis of photoinduced interdiffusion in nanolayered Se/As2S3 films

We have studied the kinetics of photoinduced effects in nanolayered Se/As2S3 film by in situ optical absorption measurements, which reveal that photodarkening in these films is followed by photoinduced diffusion. An increase in disorder during photodarkening and its subsequent decrease during photoinduced diffusion were also observed. The observation of photodarkening of Se at room temperature when confined between As2S3 layers suggests that the glass transition temperature of Se shifts to higher energy. The analysis shows that the atoms which take part in photodarkening play a vital role in photoinduced diffusion. The x-ray photoelectron spectroscopy measurements show the atomic movements during photoinduced diffusion. It also shows that some of the As–S bonds are converted into As–Se bonds. Since it is energetically difficult to break an As–S bond to form an As–Se bond, we assume that the new bond formations are taking place by the bond rearrangement mechanism.

Mathematical Model of Viral Kinetics In Vitro Estimates the Number of E2-CD81 Complexes Necessary for Hepatitis C Virus Entry

Interaction between the hepatitis C virus (HCV) envelope protein E2 and the host receptor CD81 is essential for HCV entry into target cells. The number of E2-CD81 complexes necessary for HCV entry has remained difficult to estimate experimentally. Using the recently developed cell culture systems that allow persistent HCV infection in vitro, the dependence of HCV entry and kinetics on CD81 expression has been measured. We reasoned that analysis of the latter experiments using a mathematical model of viral kinetics may yield estimates of the number of E2-CD81 complexes necessary for HCV entry. Here, we constructed a mathematical model of HCV viral kinetics in vitro, in which we accounted explicitly for the dependence of HCV entry on CD81 expression. Model predictions of viral kinetics are in quantitative agreement with experimental observations. Specifically, our model predicts triphasic viral kinetics in vitro, where the first phase is characterized by cell proliferation, the second by the infection of susceptible cells and the third by the growth of cells refractory to infection. By fitting model predictions to the above data, we were able to estimate the threshold number of E2-CD81 complexes necessary for HCV entry into human hepatoma-derived cells. We found that depending on the E2-CD81 binding affinity, between 1 and 13 E2-CD81 complexes are necessary for HCV entry. With this estimate, our model captured data from independent experiments that employed different HCV clones and cells with distinct CD81 expression levels, indicating that the estimate is robust. Our study thus quantifies the molecular requirements of HCV entry and suggests guidelines for intervention strategies that target the E2-CD81 interaction. Further, our model presents a framework for quantitative analyses of cell culture studies now extensively employed to investigate HCV infection.

Kinetics of carbon monoxide oxidation with Sn(0.95)M(0.05)O(2-delta) (M = Cu, Fe, Mn, Co) catalysts

Base metal substituted Sn(0.95)M(0.05)O(2-delta) (M = Cu, Fe, Mn, Co) catalysts were synthesized by the solution combustion method and characterized by XRD, XPS, TEM and BET surface area analysis. The catalytic activities of these materials were investigated by performing CO oxidation. The rates and the apparent activation energies of the reaction for CO oxidation were determined for each catalyst. All the substituted catalysts showed high rates and lower activation energies for the oxidation of CO as compared to unsubstituted SnO(2). The rate was found to be much higher over copper substituted SnO(2) as compared to other studied catalysts. 100% CO conversion was obtained below 225 degrees C over this catalyst. A bifunctional reaction mechanism was developed that accounts for CO adsorption on base metal and support ions and O(2) dissociation on the oxide ion vacancy. The kinetic parameters were determined by fitting the model to the experimental data. The high rates of the CO oxidation reactions at low temperatures were rationalized by the high dissociative chemisorption of adsorbed O(2) over these catalysts.

Differential Reaction Kinetics, Cleavage Complex Formation, and Nonamer Binding Domain Dependence Dictate the Structure-Specific and Sequence-Specific Nuclease Activity of RAGs

During V(D)J recombination, RAG (recombination-activating gene) complex cleaves DNA based on sequence specificity. Besides its physiological function, RAG has been shown to act as a structure-specific nuclease. Recently, we showed that the presence of cytosine within the single-stranded region of heteroduplex DNA is important when RAGs cleave on DNA structures. In the present study, we report that heteroduplex DNA containing a bubble region can be cleaved efficiently when present along with a recombination signal sequence (RSS) in cis or trans configuration. The sequence of the bubble region influences RAG cleavage at RSS when present in cis. We also find that the kinetics of RAG cleavage differs between RSS and bubble, wherein RSS cleavage reaches maximum efficiency faster than bubble cleavage. In addition, unlike RSS, RAG cleavage at bubbles does not lead to cleavage complex formation. Finally, we show that the ``nonamer binding region,'' which regulates RAG cleavage on RSS, is not important during RAG activity in non-B DNA structures. Therefore, in the current study, we identify the possible mechanism by which RAG cleavage is regulated when it acts as a structure-specific nuclease. (C) 2011 Elsevier Ltd. All rights reserved.

Atomic layer deposition of ZrO2 thin films: Study of growth kinetics and dielectric behaviour

Thin films of ZrO2 have been deposited by ALD on Si(100) and SIMOX using two different metalorganic complexes of Zr as precursors. These films are characterized by X-ray diffraction, transmission and scanning electron microscopies, infrared spectroscopy, and electrical measurements. These show that amorphous ZrO2 films of high dielectric quality may be grown on Si(100) starting about 400degreesC. As the growth temperature is raised, the films become crystalline, the phase formed and the microstructure depending on precursor molecular structure. The phase of ZrO2 formed depends also on the relative duration of the precursor and oxygen pulses. XPS and IR spectroscopy show that films grown at low temperatures contain chemically unbound carbon, its extent depending on the precursor. C-V measurements show that films grown on Si(100) have low interface state density, low leakage current, a hysteresis width of only 10-250 mV and a dielectric constant of similar to16-25.

On the role of cloud adjustment time scale in simulating precipitation with Relaxed Arakawa-Schubert convection scheme

The precipitation by Relaxed Arakawa-Schubert cumulus parameterization in a General Circulation Model (GCM) is sensitive to the choice of relaxation parameter or specified cloud adjustment time scale. In the present study, we examine sensitivity of simulated precipitation to the choice of cloud adjustment time scale (tau(adj)) over different parts of the tropics using National Center for Environmental Prediction (NCEP) Seasonal Forecast Model (SFM) during June-September. The results show that a single specified value of tau(adj) performs best only over a particular region and different values are preferred over different parts of the world. To find a relation between tau(adj) and cloud depth (convective activity) we choose six regions over the tropics. Based on the observed relation between outgoing long-wave radiation and tau(adj), we propose a linear cloud-type dependent relaxation parameter to be used in the model. The simulations over most parts of the tropics show improved results due to this newly formulated cloud-type dependent relaxation parameter.

Growth Kinetics of Nanoclusters in Solution

We study the growth kinetics of nanoclusters in solution. There are two generic factors that drive growth: (a) reactions that produce the nanomaterial; and (b) diffusion of the nanomaterial due to chemical-potential gradients. We model the growth kinetics of ZnO nanoparticles via coupled dynamical equations for the relevant order parameters, We study this model both analytically and numerically. We find that there is a crossover in thenanocluster growth law: from L(t) similar to t(1/2) in the reaction-controlled regime to L(t) t(1/3) in the diffusion-controlled regime.