Smoothed functional and Quasi-Newton algorithms for routing in multi-stage queueing network with constraints

We consider the problem of optimal routing in a multi-stage network of queues with constraints on queue lengths. We develop three algorithms for probabilistic routing for this problem using only the total end-to-end delays. These algorithms use the smoothed functional (SF) approach to optimize the routing probabilities. In our model all the queues are assumed to have constraints on the average queue length. We also propose a novel quasi-Newton based SF algorithm. Policies like Join Shortest Queue or Least Work Left work only for unconstrained routing. Besides assuming knowledge of the queue length at all the queues. If the only information available is the expected end-to-end delay as with our case such policies cannot be used. We also give simulation results showing the performance of the SF algorithms for this problem.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Mycobacterium tuberculosis mutT1 (Rv2985) and ADPRase (Rv1700) proteins constitute a two-stage mechanism of 8-Oxo-dGTP and 8-Oxo-GTP detoxification and adenosine to cytidine mutation avoidance

Approximately one third of the world population is infected with Mycobacterium tuberculosis, the causative agent of tuberculosis. A better understanding of the pathogen biology is crucial to develop new tools/strategies to tackle its spread and treatment. In the host macrophages, the pathogen is exposed to reactive oxygen species, known to damage dGTP and GTP to 8-oxo-dGTP and 8-oxo-GTP, respectively. Incorporation of the damaged nucleotides in nucleic acids is detrimental to organisms. MutT proteins, belonging to a class of Nudix hydrolases, hydrolyze 8-oxo-G nucleoside triphosphates/diphosphates to the corresponding nucleoside monophosphates and sanitize the nucleotide pool. Mycobacteria possess several MutT proteins. However, a functional homolog of Escherichia coli MutT has not been identified. Here, we characterized MtuMutT1 and Rv1700 proteins of M. tuberculosis. Unlike other MutT proteins, MtuMutT1 converts 8-oxo-dGTP to 8-oxo-dGDP, and 8-oxo-GTP to 8-oxo-GDP. Rv1700 then converts them to the corresponding nucleoside monophosphates. This observation suggests the presence of a two-stage mechanism of 8-oxo-dGTP/8-oxo-GTP detoxification in mycobacteria. MtuMutT1 converts 8-oxo-dGTP to 8-oxo-dGDP with a K-m of similar to 50 mu M and V-max of similar to 0.9 pmol/min per ng of protein, and Rv1700 converts 8-oxo-dGDP to 8-oxo-dGMP with a K-m of similar to 9.5 mu M and V-max of similar to 0.04 pmol/min per ng of protein. Together, MtuMutT1 and Rv1700 offer maximal rescue to E. coli for its MutT deficiency by decreasing A to C mutations (a hallmark of MutT deficiency). We suggest that the concerted action of MtuMutT1 and Rv1700 plays a crucial role in survival of bacteria against oxidative stress.

Crop stage classification of hyperspectral data using unsupervised techniques

The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

Dielectric and electrical conductivity properties of multi-stage spark plasma sintered HA-CaTiO3 composites and comparison with conventionally sintered materials

One of the different issues limiting the wider application of monolithic hydroxyapatite (HA) as an ideal bone replacement material is the lack of reasonably good electrical transport properties. The comprehensive electrical property characterization to evaluate the efficacy of processing parameters in achieving the desired combination of electroactive properties is considered as an important aspect in the development of HA-based bioactive material. In this perspective, the present work reports the temperature (RT-200 degrees C) and frequency (100 Hz-1 MHz) dependent dielectric properties and AC conductivity for a range of HA-CaTiO3 (HA-CT) composites, densified using both conventional pressureless sintering in air as well as spark plasma sintering in vacuum. Importantly, the AC conductivity of spark plasma sintered ceramics similar to upto 10(-5) (Omega cm)(-1)] are found to be considerably higher than the corresponding pressureless sintered ceramics similar to upto 10(-8) (Omega cm)(-1)]. Overall, the results indicate the processing route dependent functional properties of HA-CaTiO3 composites as well as related advantages of spark plasma sintering route. (C) 2013 Elsevier Ltd. All rights reserved.

Reaction dynamics under confinement: an exact path integral treatment of a two-stage model of stochastic gene expression

Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p, r, t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p, r, t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t -> infinity. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.

Simulation study of a two-stage adsorber system

The present study simulates a two-stage silica gel + water adsorption desalination (AD) and chiller system. The adsorber system thermally compresses the low pressure steam generated in the evaporator to the condenser pressure in two stages. Unlike a standalone adsorption chiller unit which operates in a closed cycle the present system is an open cycle wherein the condensed desalinated water is not fed back to the evaporator. The mathematical relations formulated in the current study are based on conservation of mass and energy along with isotherm relation and kinetics for RD-type silica gel + water pair. Various constitutive relations for each component namely the evaporator, adsorber and condenser are integrated in the model. The dynamics of heat exchanger are modeled using LMTD method, and LDF model is used to predict the dynamic characteristic of the adsorber bed. The system performance indicators namely, specific cooling capacity (SCC), specific daily water production (SDWP) and coefficient of performance (COP) are used as objective functions to optimize the system. The novelty of the present work is in introduction of inter-stage pressure as a new parameter for optimizing the two-stage operation of AD chiller system. (C) 2014 Elsevier Ltd. All rights reserved.

Fruit and Seed Volatiles: Multiple Stage Settings, Actors and Props in an Evolutionary Play

Plants emit volatile organic compounds (VOCs) from most parts of their anatomy. Conventionally, the volatiles of leaves, flowers, fruits and seeds have been investigated separately. This review presents an integrated perspective of volatiles produced by fruits and seeds in the context of selection on the whole plant. It suggests that fruit and seed volatiles may only be understood in the light of the chemistry of the whole plant. Fleshy fruit may be viewed as an ecological arena within which several evolutionary games are being played involving fruit VOCs. Fruit odour and colour may be correlated and interact via multimodal signalling in influencing visits by frugivores. The hypothesis of volatile crypsis in the evolution of hard seeds as protection against volatile diffusion and perception by seed predators is reviewed. Current views on the role of volatiles in ant dispersal of seeds or myrmecochory are summarised, especially the suggestion that ants are being manipulated by plants in the form of a sensory trap while providing this service. Plant VOC production is presented as an emergent phenotype that could result from multiple selection pressures acting on various plant parts; the ``plant'' phenotype and VOC profile may receive significant contributions from symbionts within the plant. Viewing the plant as a holobiont would benefit an understanding of the emergent plant phenotype.

EXPERIMENTAL INVESTIGATION OF UNSTEADY FLOW IN A TRANSONIC UNI-STAGE AXIAL COMPRESSOR

Detailed steady and unsteady experimental measurements and analysis were performed on a Single stage Transonic Axial Compressor with asymmetric rotor tip clearance for studying the compressor stall phenomena. The installed compressor had asymmetric tip clearance around the rotor casing varying from about 0.65mm to 1.25mm. A calibrated 5-hole aerodynamic probe was traversed radially at exit of rotor and showed the characteristics of increased flow angle at lower mass flow rates for all the speeds. Mach number distribution and boundary layer effects were also clearly captured. Unsteady measurements for velocity were carried out to study the stall cell behavior using a single component calibrated hotwire probe oriented in axial and tangential directions for choke/free flow and near stall conditions. The hotwire probe was traversed radially across the annulus at inlet to the compressor and showed that the velocity fluctuations were dissimilar when probe was aligned axial and tangential to the flow. Averaged velocities across the annulus showed the reduction in velocity as stall was approached. Axial mean flow velocity decreased across the annulus for all the speeds investigated. Tangential velocity at free flow condition was higher at the tip region due to larger radius. At stall condition, the tangential velocity showed decreased velocities at the tip and slightly increased velocities at the hub section indicating that the flow has breakdown at the tip region of the blade and fluid is accelerated below the blockage zone. The averaged turbulent intensity in axial and tangential flow directions increased from free flow to stall condition for all compressor rated speeds. Fast Fourier Transform (FFT) of the raw signals at stall flow condition showed stall cell and its corresponding frequency of occurrence. The stalling frequency of about half of rotational speed of the rotor along with large tip clearance suggests that modal type stall inception was occurring.

Performance evaluation of a two-stage silica gel plus water adsorption based cooling-cum-desalination system

The first objective of this paper is to show that a single-stage adsorption based cooling-cum-desalination system cannot be used if air cooled heat rejection is used under tropical conditions. This objective is achieved by operating a silica gel + water adsorption chiller first in a single-stage mode and then in a 2-stage mode with 2 beds/stage in each case. The second objective is to improve upon the simulation results obtained earlier by way of empirically describing the thermal wave phenomena during switching of operation of beds between adsorption and desorption and vice versa. Performance indicators, namely, cooling capacity, coefficient of performance and desalinated water output are extracted for various evaporator pressures and half cycle times. The improved simulation model is found to interpret experimental results more closely than the earlier one. Reasons for decline in performance indicators between theoretical and actual scenarios are appraised. (C) 2015 Elsevier Ltd and IIR. All rights reserved.

Part I: Physical Insights Into the Two-Stage Breakdown Characteristics of STI-Type Drain-Extended pMOS Device

In this paper, we study breakdown characteristics in shallow-trench isolation (STI)-type drain-extended MOSFETs (DeMOS) fabricated using a low-power 65-nm triple-well CMOS process with a thin gate oxide. Experimental data of p-type STI-DeMOS device showed distinct two-stage behavior in breakdown characteristics in both OFF-and ON-states, unlike the n-type device, causing a reduction in the breakdown voltage and safe operating area. The first-stage breakdown occurs due to punchthrough in the vertical structure formed by p-well, deep n-well, and p-substrate, whereas the second-stage breakdown occurs due to avalanche breakdown of lateral n-well/p-well junction. The breakdown characteristics are also compared with the STI-DeNMOS device structure. Using the experimental results and advanced TCAD simulations, a complete understanding of breakdown mechanisms is provided in this paper for STI-DeMOS devices in advanced CMOS processes.

Instrumentation and control of a two-stage 4-bed silica gel plus water adsorption cooling cum desalination system

This paper presents the instrumentation and control architecture for a laboratory based two-stage 4-bed silica gel + water adsorption system. The system consists of primarily two fluids: refrigerant (water vapour) and heat transfer fluid (water) flowing through various components. Heat input to the system is simulated using multiple heaters and ambient air is used as the heat sink. The laboratory setup incorporates a real time National Instruments (NI) controller to control several digital and analog valves, heaters, pumps and fans along with simultaneous data acquisition from various flow, pressure and temperature sensors. The paper also presents in detail the various automated and manual tasks required for successful operation of the system. Finally the system pressure and temperature dynamics are reported and its performance evaluated for various cycle times. (C) 2015 Elsevier Ltd. All rights reserved.

Delineation of homogeneous temperature regions: a two-stage clustering approach

Homogeneous temperature regions are necessary for use in hydrometeorological studies. The regions are often delineated by analysing statistics derived from time series of maximum, minimum or mean temperature, rather than attributes influencing temperature. This practice cannot yield meaningful regions in data-sparse areas. Further, independent validation of the delineated regions for homogeneity in temperature is not possible, as temperature records form the basis to arrive at the regions. To address these issues, a two-stage clustering approach is proposed in this study to delineate homogeneous temperature regions. First stage of the approach involves (1) determining correlation structure between observed temperature over the study area and possible predictors (large-scale atmospheric variables) influencing the temperature and (2) using the correlation structure as the basis to delineate sites in the study area into clusters. Second stage of the approach involves analysis on each of the clusters to (1) identify potential predictors (large-scale atmospheric variables) influencing temperature at sites in the cluster and (2) partition the cluster into homogeneous fuzzy temperature regions using the identified potential predictors. Application of the proposed approach to India yielded 28 homogeneous regions that were demonstrated to be effective when compared to an alternate set of 6 regions that were previously delineated over the study area. Intersite cross-correlations of monthly maximum and minimum temperatures in the existing regions were found to be weak and negative for several months, which is undesirable. This problem was not found in the case of regions delineated using the proposed approach. Utility of the proposed regions in arriving at estimates of potential evapotranspiration for ungauged locations in the study area is demonstrated.