Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

Heat conduction with a phase change in a cylindrical mould

Analytical short time solution of moving boundary in heat conduction in a cylindrical mould under prescribed flux boundary condition has been studied in this paper. Partial differential equations are converted to integro-differential equations. These integro-differential equations which are coupled have been solved analytically for short time by choosing suitable series expansions for the unknown quantitities.

Light scattering in random media with wavelength-scale structures : astronomical and industrial applications

Light scattering, or scattering and absorption of electromagnetic waves, is an important tool in all remote-sensing observations. In astronomy, the light scattered or absorbed by a distant object can be the only source of information. In Solar-system studies, the light-scattering methods are employed when interpreting observations of atmosphereless bodies such as asteroids, atmospheres of planets, and cometary or interplanetary dust. Our Earth is constantly monitored from artificial satellites at different wavelengths. With remote sensing of Earth the light-scattering methods are not the only source of information: there is always the possibility to make in situ measurements. The satellite-based remote sensing is, however, superior in the sense of speed and coverage if only the scattered signal can be reliably interpreted. The optical properties of many industrial products play a key role in their quality. Especially for products such as paint and paper, the ability to obscure the background and to reflect light is of utmost importance. High-grade papers are evaluated based on their brightness, opacity, color, and gloss. In product development, there is a need for computer-based simulation methods that could predict the optical properties and, therefore, could be used in optimizing the quality while reducing the material costs. With paper, for instance, pilot experiments with an actual paper machine can be very time- and resource-consuming. The light-scattering methods presented in this thesis solve rigorously the interaction of light and material with wavelength-scale structures. These methods are computationally demanding, thus the speed and accuracy of the methods play a key role. Different implementations of the discrete-dipole approximation are compared in the thesis and the results provide practical guidelines in choosing a suitable code. In addition, a novel method is presented for the numerical computations of orientation-averaged light-scattering properties of a particle, and the method is compared against existing techniques. Simulation of light scattering for various targets and the possible problems arising from the finite size of the model target are discussed in the thesis. Scattering by single particles and small clusters is considered, as well as scattering in particulate media, and scattering in continuous media with porosity or surface roughness. Various techniques for modeling the scattering media are presented and the results are applied to optimizing the structure of paper. However, the same methods can be applied in light-scattering studies of Solar-system regoliths or cometary dust, or in any remote-sensing problem involving light scattering in random media with wavelength-scale structures.

From ‘Afflicted’ to Activists: Structural Violence and Climate Change Discourse in the States of Pernambuco and Paraíba in Northeast Brazil

This study approaches the problem of poverty in the hinterlands of Northeast Brazil through the concept of structural violence, linking the environmental threats posed by climate change, especially those related to droughts, to the broader social struggles in the region. When discussions about potentials and rights are incorporated into the problematic of poverty, a deeper insight is obtained regarding the various factors behind the phenomenon. It is generally believed that climate change is affecting the already marginalized and poor more than those of higher social standing, and will increasingly do so in the future. The data for this study was collected during a three month field work in the states of Pernambuco and Paraíba in Northeast Brazil. The main methods used were semi-structured interviews and participant observation, including attending seminars concerning climate change on the field. The focus of the work is to compare both layman and expert perceptions on what climate change is about, and question the assumptions about its effects in the future, mainly that of increased numbers of ‘climate refugees’ or people forced to migrate due to changes in climate. The focus on droughts, as opposed to other manifestations of climate change, arises from the fact that droughts are not only phenomena that develop over a longer time span than floods or hurricanes, but is also due to the historical persistence of droughts in the region, and both the institutional and cultural linkages that have evolved around it. The instances of structural violence that are highlighted in this study; the drought industry, land use, and the social and power relations present in the region, including those between the civil society, the state and the private agribusiness sector, all work against a backdrop of symbolic and moral realms of value production, where relations between the different actors are being negotiated anew with the rise of the climate change discourse. The main theoretical framework of the study consists of Johan Galtung’s and Paul Farmer’s theory of structural violence, Ulrich Beck’s theory of the risk society, and James Scott’s theory of everyday peasant resistance.

On infinitesimal σ-fields generated by random processes

It is proved that the infinitesimal look-ahead and look-back σ-fields of a random process disagree at atmost countably many time instants.

Random sequential multilayer deposition of different‐sized k mers on a one dimensional infinite substrate

Kinetics of random sequential, irreversible multilayer deposition of macromolecules of two different sizes on a one dimensional infinite lattice is analyzed at the mean field level. A formal solution for the corresponding rate equation is obtained. The Jamming limits and the distribution of gaps of exact sizes are discussed. In the absence of screening, the jamming limits are shown to be the same for all the layers. A detailed analysis for the components differing by one monomer unit is presented. The small and large time behaviors and the dependence of the individual jamming limits of the k mers and (k−1) mers on k and the rate parameters are analyzed.

Implications of climate change on mitigation potential estimates for forest sector in India

Climate change is projected to impact forest ecosystems, including biodiversity and Net Primary Productivity (NPP). National level carbon forest sector mitigation potential estimates are available for India; however impacts of projected climate change are not included in the mitigation potential estimates. Change in NPP (in gC/m(2)/yr) is taken to represent the impacts of climate change. Long term impacts of climate change (2085) on the NPP of Indian forests are available; however no such regional estimates are available for short and medium terms. The present study based on GCM climatology scenarios projects the short, medium and long term impacts of climate change on forest ecosystems especially on NPP using BIOME4 vegetation model. We estimate that under A2 scenario by the year 2030 the NPP changes by (-5) to 40% across different agro-ecological zones (AEZ). By 2050 it increases by 15% to 59% and by 2070 it increases by 34 to 84%. However, under B2 scenario it increases only by 3 to 25%, 3.5 to 34% and (-2.5) to 38% respectively, in the same time periods. The cumulative mitigation potential is estimated to increase by up to 21% (by nearly 1 GtC) under A2 scenario between the years 2008 and 2108, whereas, under B2 the mitigation potential increases only by 14% (646 MtC). However, cumulative mitigation potential estimates obtained from IBIS-a dynamic global vegetation model suggest much smaller gains, where mitigation potential increases by only 6% and 5% during the period 2008 to 2108.

Computation of restoration of ligand response in the random kinetics of a prostate cancer cell signaling pathway

Mutation and/or dysfunction of signaling proteins in the mitogen activated protein kinase (MAPK) signal transduction pathway are frequently observed in various kinds of human cancer. Consistent with this fact, in the present study, we experimentally observe that the epidermal growth factor (EGF) induced activation profile of MAP kinase signaling is not straightforward dose-dependent in the PC3 prostate cancer cells. To find out what parameters and reactions in the pathway are involved in this departure from the normal dose-dependency, a model-based pathway analysis is performed. The pathway is mathematically modeled with 28 rate equations yielding those many ordinary differential equations (ODE) with kinetic rate constants that have been reported to take random values in the existing literature. This has led to us treating the ODE model of the pathways kinetics as a random differential equations (RDE) system in which the parameters are random variables. We show that our RDE model captures the uncertainty in the kinetic rate constants as seen in the behavior of the experimental data and more importantly, upon simulation, exhibits the abnormal EGF dose-dependency of the activation profile of MAP kinase signaling in PC3 prostate cancer cells. The most likely set of values of the kinetic rate constants obtained from fitting the RDE model into the experimental data is then used in a direct transcription based dynamic optimization method for computing the changes needed in these kinetic rate constant values for the restoration of the normal EGF dose response. The last computation identifies the parameters, i.e., the kinetic rate constants in the RDE model, that are the most sensitive to the change in the EGF dose response behavior in the PC3 prostate cancer cells. The reactions in which these most sensitive parameters participate emerge as candidate drug targets on the signaling pathway. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Fiber Bragg Grating Sensors for Real Time Monitoring of Evacuation Process

Fiber bragg grating (FBG) sensors have been widely used for number of sensing applications like temperature, pressure, acousto-ultrasonic, static and dynamic strain, refractive index change measurements and so on. Present work demonstrates the use of FBG sensors in in-situ measurement of vacuum process with simultaneous leak detection capability. Experiments were conducted in a bell jar vacuum chamber facilitated with conventional Pirani gauge for vacuum measurement. Three different experiments have been conducted to validate the performance of FBG sensor in monitoring vacuum creating process and air bleeding. The preliminary results of FBG sensors in vacuum monitoring have been compared with that of commercial Pirani gauge sensor. This novel technique offers a simple alternative to conventional method for real time monitoring of evacuation process. Proposed FBG based vacuum sensor has potential applications in vacuum systems involving hazardous environment such as chemical and gas plants, automobile industries, aeronautical establishments and leak monitoring in process industries, where the electrical or MEMS based sensors are prone to explosion and corrosion.

Test Application Time Minimization for RAS using Basis Optimization of Column Decoder

Random Access Scan, which addresses individual flip-flops in a design using a memory array like row and column decoder architecture, has recently attracted widespread attention, due to its potential for lower test application time, test data volume and test power dissipation when compared to traditional Serial Scan. This is because typically only a very limited number of random ``care'' bits in a test response need be modified to create the next test vector. Unlike traditional scan, most flip-flops need not be updated. Test application efficiency can be further improved by organizing the access by word instead of by bit. In this paper we present a new decoder structure that takes advantage of basis vectors and linear algebra to further significantly optimize test application in RAS by performing the write operations on multiple bits consecutively. Simulations performed on benchmark circuits show an average of 2-3 times speed up in test write time compared to conventional RAS.

An Efficient Random Walk Strategy for Sampling Based Robot Motion Planners

Sampling based planners have been successful in path planning of robots with many degrees of freedom, but still remains ineffective when the configuration space has a narrow passage. We present a new technique based on a random walk strategy to generate samples in narrow regions quickly, thus improving efficiency of Probabilistic Roadmap Planners. The algorithm substantially reduces instances of collision checking and thereby decreases computational time. The method is powerful even for cases where the structure of the narrow passage is not known, thus giving significant improvement over other known methods.

Pulsed laser deposition of strontium titanate thin films for dynamic random access memory applications

Polycrystalline strontium titanate (SrTiO3) films were prepared by a pulsed laser deposition technique on p-type silicon and platinum-coated silicon substrates. The films exhibited good structural and dielectric properties which were sensitive to the processing conditions. The small signal dielectric constant and dissipation factor at a frequency of 100 kHz were about 225 and 0.03 respectively. The capacitance-voltage (C-V) characteristics in metal-insulator-semiconductor structures exhibited anomalous frequency dispersion behavior and a hysteresis effect. The hysteresis in the C-V curve was found to be about 1 V and of a charge injection type. The density of interface states was about 1.79 x 10(12) cm(-2). The charge storage density was found to be 40 fC mu m(-2) at an applied electric field of 200 kV cm(-1). Studies on current-voltage characteristics indicated an ohmic nature at lower voltages and space charge conduction at higher voltages. The films also exhibited excellent time-dependent dielectric breakdown behavior.

Low electric field, easily reversible electrical set and reset processes in a Ge15Te83Si2 glass for phase change memory applications

We report here an easily reversible set-reset process in a new Ge15Te83Si2 glass that could be a promising candidate for phase change random access memory applications. The I-V characteristics of the studied sample show a comparatively low threshold electric field (E-th) of 7.3 kV/cm. Distinct differences in the type of switching behavior are achieved by means of controlling the on state current. It enables the observation of a threshold type for less than 0.7 mA beyond memory type (set) switching. The set and reset processes have been achieved with a similar magnitude of 1 mA, and with a triangular current pulse for the set process and a short duration rectangular pulse of 10 msec width for the reset operation. Further, a self-resetting effect is seen in this material upon excitation with a saw-tooth/square pulse, and their response of leading and trailing edges are discussed. About 6.5 x 10(4) set-reset cycles have been undertaken without any damage to the device. (C) 2011 American Institute of Physics. doi: 10.1063/1.3574659]

Effect of Melt Convection on The Optimum Thermal Design Of Heat Sinks With Phase Change Material

In this paper, the role of melt convection on the performance of heat sinks with phase change material (PCM) is investigated numerically. The heat sink consists of aluminum plate fins embedded in PCM, and is subjected to heat flux supplied from the bottom. A single-domain enthalpy-based CFD model is developed, which is capable of simulating the phase change process and the associated melt convection. The CFD model is coupled with a genetic algorithm for carrying out the optimization. Two cases are considered, namely, one without melt convection (i.e., conduction heat transfer analysis), and the other with convection. It is found that the geometrical optimizations of heat sinks are different for the two cases, indicating the importance of melt convection in the design of heat sinks with PCMs. In the case of conduction analysis, the optimum width of half fin (i.e., sum of half pitch and half fin thickness) is a constant, which is in good agreement with results reported in the literature. On the other hand, if melt convection is considered, the optimum half fin width depends on the effective thermal diffusivity due to conduction and convection. With melt convection, the optimized design results in a significant improvement of operational time.

Mean first passage time approach to the problem of optimal barrier subdivision for Kramer's escape rate

We consider the effect of subdividing the potential barrier along the reaction coordinate on Kramer's escape rate for a model potential, Using the known supersymmetric potential approach, we show the existence of an optimal number of subdivisions that maximizes the rate, We cast the problem as a mean first passage time problem of a biased random walker and obtain equivalent results, We briefly summarize the results of our investigation on the increase in the escape rate by placing a blow-torch in the unstable part of one of the potential wells. (C) 1999 Elsevier Science B.V. All rights reserved.