Role of water contamination within the GC column of a GasBench II peripheral on the reproducibility of O-18/O-16 ratios in water samples

The GasBench II peripheral along with MAT 253 combination provides a more sensitive platform for the determination of water isotope ratios. Here, we examined the role of adsorbed moisture within the gas chromatography (GC) column of the GasBench II on measurement uncertainties. The uncertainty in O-18/O-16 ratio measurements is determined by several factors, including the presence of water in the GC. The contamination of GC with water originating from samples as water vapour over a longer timeframe is a critical factor in determining the reproducibility of O-18/O-16 ratios in water samples. The shift in isotope ratios observed in the experiment under dry and wet conditions correlates strongly with the retention time of analyte CO2, indicating the effect of accumulated moisture. Two possible methods to circumvent or minimise the effect of adsorbed water on isotope ratios are presented here. The proposed methodology includes either the regular baking of the GC column at a higher temperature (120 degrees C) after analysis of a batch of 32 sample entries or conducting the experiment at a low GC column temperature (22.5 degrees C). The effects of water contamination on long-term reproducibility of reference water, with and without baking protocol, have been described.

Spectral Element Approach to Wave Propagation in Uncertain Composite Beam Structures

This paper presents a study of the wave propagation responses in composite structures in an uncertain environment. Here, the main aim of the work is to quantify the effect of uncertainty in the wave propagation responses at high frequencies. The material properties are considered uncertain and the analysis is performed using Neumann expansion blended with Monte Carlo simulation under the environment of spectral finite element method. The material randomness is included in the conventional wave propagation analysis by different distributions (namely, the normal and the Weibul distribution) and their effect on wave propagation in a composite beam is analyzed. The numerical results presented investigates the effect of material uncertainties on different parameters, namely, wavenumber and group speed, which are relevant in the wave propagation analysis. The effect of the parameters, such as fiber orientation, lay-up sequence, number of layers, and the layer thickness on the uncertain responses due to dynamic impulse load, is thoroughly analyzed. Significant changes are observed in the high frequency responses with the variation in the above parameters, even for a small coefficient of variation. High frequency impact loads are applied and a number of interesting results are presented, which brings out the true effects of uncertainty in the high frequency responses. [DOI: 10.1115/1.4003945]

Potential G-quadruplex formation at breakpoint regions of chromosomal translocations in cancer may explain their fragility

Genetic alterations like point mutations, insertions, deletions, inversions and translocations are frequently found in cancers. Chromosomal translocations are one of the most common genomic aberrations associated with nearly all types of cancers especially leukemia and lymphoma. Recent studies have shown the role of non-B DNA structures in generation of translocations. In the present study, using various bioinformatic tools, we show the propensity of formation of different types of altered DNA structures near translocation breakpoint regions. In particular, we find close association between occurrence of G-quadruplex forming motifs and fragile regions in almost 70% of genes involved in rearrangements in lymphoid cancers. However, such an analysis did not provide any evidence for the occurrence of G-quadruplexes at the close vicinity of translocation breakpoint regions in nonlymphoid cancers. Overall, this study will help in the identification of novel non-B DNA targets that may be responsible for generation of chromosomal translocations in cancer. (C) 2012 Elsevier Inc. All rights reserved.

Monsoon sensitivity to aerosol direct radiative forcing in the community atmosphere model

Aerosol forcing remains a dominant uncertainty in climate studies. The impact of aerosol direct radiative forcing on Indian monsoon is extremely complex and is strongly dependent on the model, aerosol distribution and characteristics specified in the model, modelling strategy employed as well as on spatial and temporal scales. The present study investigates (i) the aerosol direct radiative forcing impact on mean Indian summer monsoon when a combination of quasi-realistic mean annual cycles of scattering and absorbing aerosols derived from an aerosol transport model constrained with satellite observed Aerosol Optical Depth (AOD) is prescribed, (ii) the dominant feedback mechanism behind the simulated impact of all-aerosol direct radiative forcing on monsoon and (iii) the relative impacts of absorbing and scattering aerosols on mean Indian summer monsoon. We have used CAM3, an atmospheric GCM (AGCM) that has a comprehensive treatment of the aerosol-radiation interaction. This AGCM has been used to perform climate simulations with three different representations of aerosol direct radiative forcing due to the total, scattering aerosols and black carbon aerosols. We have also conducted experiments without any aerosol forcing. Aerosol direct impact due to scattering aerosols causes significant reduction in summer monsoon precipitation over India with a tendency for southward shift of Tropical Convergence Zones (TCZs) over the Indian region. Aerosol forcing reduces surface solar absorption over the primary rainbelt region of India and reduces the surface and lower tropospheric temperatures. Concurrent warming of the lower atmosphere over the warm oceanic region in the south reduces the land-ocean temperature contrast and weakens the monsoon overturning circulation and the advection of moisture into the landmass. This increases atmospheric convective stability, and decreases convection, clouds, precipitation and associated latent heat release. Our analysis reveals a defining negative moisture-advection feedback that acts as an internal damping mechanism spinning down the regional hydrological cycle and leading to significant circulation changes in response to external radiative forcing perturbations. When total aerosol loading (both absorbing and scattering aerosols) is prescribed, dust and black carbon aerosols are found to cause significant atmospheric heating over the monsoon region but the aerosol-induced weakening of meridional lower tropospheric temperature gradient (leading to weaker summer monsoon rainfall) more than offsets the increase in summer-time rainfall resulting from the atmospheric heating effect of absorbing aerosols, leading to a net decrease of summer monsoon rainfall. Further, we have carried out climate simulations with globally constant AODs and also with the constant AODs over the extended Indian region replaced by realistic AODs. Regional aerosol radiative forcing perturbations over the Indian region is found to have impact not only over the region of loading but over remote tropical regions as well. This warrants the need to prescribe realistic aerosol properties in strategic regions such as India in order to accurately assess the aerosol impact.

Impacts of climate change on regional water resources

Water is the most important medium through which climate change influences human life. Rising temperatures together with regional changes in precipitation patterns are some of the impacts of climate change that have implications on water availability, frequency and intensity of floods and droughts, soil moisture, water quality, water supply and water demands for irrigation and hydropower generation. In this article we provide an introduction to the emerging field of hydrologic impacts of climate change with a focus on water availability, water quality and irrigation demands. Climate change estimates on regional or local spatial scales are burdened with a considerable amount of uncertainty, stemming from various sources such as climate models, downscaling and hydrological models used in the impact assessments and uncertainty in the downscaling relationships. The present article summarizes the recent advances on uncertainty modeling and regional impacts of climate change for the Mahanadi and Tunga-Bhadra Rivers in India.

Mechanism design for cost optimal PAC learning in the presence of strategic noisy annotators

We consider the problem of Probably Ap-proximate Correct (PAC) learning of a bi-nary classifier from noisy labeled exam-ples acquired from multiple annotators(each characterized by a respective clas-sification noise rate). First, we consider the complete information scenario, where the learner knows the noise rates of all the annotators. For this scenario, we derive sample complexity bound for the Mini-mum Disagreement Algorithm (MDA) on the number of labeled examples to be ob-tained from each annotator. Next, we consider the incomplete information sce-nario, where each annotator is strategic and holds the respective noise rate as a private information. For this scenario, we design a cost optimal procurement auc-tion mechanism along the lines of Myer-son’s optimal auction design framework in a non-trivial manner. This mechanism satisfies incentive compatibility property,thereby facilitating the learner to elicit true noise rates of all the annotators.

Hypersensitivity of hypoxia grown Mycobacterium smegmatis to DNA damaging agents: Implications of the DNA repair deficiencies in attenuation of mycobacteria

Mycobacteria are an important group of pathogenic bacteria. We generated a series of DNA repair deficient strains of Mycobacterium smegmatis, a model organism, to understand the importance of various DNA repair proteins (UvrB, Ung, UdgB, MutY and Fpg) in survival of the pathogenic strains. Here, we compared tolerance of the M. smegmatis strains to genotoxic stress (ROS and RNI) under aerobic, hypoxic and recovery conditions of growth by monitoring their survival. We show an increased susceptibility of mycobacteria to genotoxic stress under hypoxia. UvrB deficiency led to high susceptibility of M. smegmatis to the DNA damaging agents. Ung was second in importance in strains with single deficiencies. Interestingly, we observed that while deficiency of UdgB had only a minor impact on the strain's susceptibility, its combination with Ung deficiency resulted in severe consequences on the strain's survival under genotoxic stress suggesting a strong interdependence of different DNA repair pathways in safeguarding genomic integrity. Our observations reinforce the possibility of targeting DNA repair processes in mycobacteria for therapeutic intervention during active growth and latency phase of the pathogen. High susceptibility of the UvrB, or the Ung/UdgB deficient strains to genotoxic stress may be exploited in generation of attenuated strains of mycobacteria. (C) 2013 Elsevier Ireland Ltd. All rights reserved.

A simulation-based algorithm for optimal pricing policy under demand uncertainty

We propose a simulation-based algorithm for computing the optimal pricing policy for a product under uncertain demand dynamics. We consider a parameterized stochastic differential equation (SDE) model for the uncertain demand dynamics of the product over the planning horizon. In particular, we consider a dynamic model that is an extension of the Bass model. The performance of our algorithm is compared to that of a myopic pricing policy and is shown to give better results. Two significant advantages with our algorithm are as follows: (a) it does not require information on the system model parameters if the SDE system state is known via either a simulation device or real data, and (b) as it works efficiently even for high-dimensional parameters, it uses the efficient smoothed functional gradient estimator.

Damage assessment of composite plate structures with material and measurement uncertainty

Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problein in damage assessment. A recently developed C-0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data. (C) 2016 Elsevier Ltd. All rights reserved.

Climate response to physiological forcing of carbon dioxide simulated by the coupled Community Atmosphere Model (CAM3.1) and Community Land Model (CLM3.0)

Increasing concentrations of atmospheric CO2 decrease stomatal conductance of plants and thus suppress canopy transpiration. The climate response to this CO2-physiological forcing is investigated using the Community Atmosphere Model version 3.1 coupled to Community Land Model version 3.0. In response to the physiological effect of doubling CO2, simulations show a decrease in canopy transpiration of 8%, a mean warming of 0.1K over the land surface, and negligible changes in the hydrological cycle. These climate responses are much smaller than what were found in previous modeling studies. This is largely a result of unrealistic partitioning of evapotranspiration in our model control simulation with a greatly underestimated contribution from canopy transpiration and overestimated contributions from canopy and soil evaporation. This study highlights the importance of a realistic simulation of the hydrological cycle, especially the individual components of evapotranspiration, in reducing the uncertainty in our estimation of climatic response to CO2-physiological forcing. Citation: Cao, L., G. Bala, K. Caldeira, R. Nemani, and G.Ban-Weiss (2009), Climate response to physiological forcing of carbon dioxide simulated by the coupled Community Atmosphere Model (CAM3.1) and Community Land Model (CLM3.0).

M. bovis BCG induced expression of COX-2 involves nitric oxide-dependent and -independent signaling pathways

In a multifaceted immunity to mycobacterial infection, induced expression of cyclooxygenase-2 (COX-2) by Mycobacterium bovis bacillus Calmette-Guerin (BCG) may act as an important influencing factor for the effective host immunity. We here demonstrate that M. bovis BCG-triggered TLR2-dependent signaling leads to COX-2 and PGE2 expression in vitro in macrophages and in vivo in mice. Further, the presence of PGE2 could be demonstrated in sera or cerebrospinal fluid of tuberculosis patients. The induced COX-2 expression in macrophages is dependent on NF-kappa B activation, which is mediated by inducible NO synthase (iNOS)/NO-dependent participation of the members of Notch1-PI-3K signaling cascades as well as iNOS-independent activation of ERK1/2 and p38 MAPKs. Inhibition of iNOS activity abrogated the M. bovis BCG ability to trigger the generation of Notch1 intracellular domain (NICD), a marker for Notch1 signaling activation, as well as activation of the PI-3K signaling cascade. On the contrary, treatment of macrophages with 3-morpholinosydnonimine, a NO donor, resulted in a rapid increase in generation of NICD, activation of PI-3K pathway, as well as the expression of COX-2. Stable expression of NICD in RAW 264.7 macrophages resulted in augmented expression of COX-2. Further, signaling perturbations suggested the involvement of the cross-talk of Notch1 with members with the PI-3K signaling cascade. These results implicate the dichotomous nature of TLR2 signaling during M. bovis BCG-triggered expression of COX-2. In this perspective, we propose the involvement of iNOS/NO as one of the obligatory, early, proximal signaling events during M. bovis BCG-induced COX-2 expression in macrophages.

An adaptive power-system stabiliser which cancels the negative damping torque of a synchronous generator

The paper presents a new criterion for designing a power-system stabiliser, which is that it should cancel the negative damping torque inherent in a synchronous generator and automatic voltage regulator. The method arises from analysis based on the properties of tensor invariance, but it is easily implemented, and leads to the design of an adaptive controller. Extensive computations and simulation have been performed, and laboratory tests have been conducted on a computer-controlled micromachine system. Results are presented illustrating the effectiveness of the adaptive stabiliser.

Interval Data Classification under Partial Information: A Chance-Constraint Approach

This paper presents a Chance-constraint Programming approach for constructing maximum-margin classifiers which are robust to interval-valued uncertainty in training examples. The methodology ensures that uncertain examples are classified correctly with high probability by employing chance-constraints. The main contribution of the paper is to pose the resultant optimization problem as a Second Order Cone Program by using large deviation inequalities, due to Bernstein. Apart from support and mean of the uncertain examples these Bernstein based relaxations make no further assumptions on the underlying uncertainty. Classifiers built using the proposed approach are less conservative, yield higher margins and hence are expected to generalize better than existing methods. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle interval-valued uncertainty than state-of-the-art.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

Evaluation of Moderate-Resolution Imaging Spectroradiometer (MODIS) collection 004 (C004) aerosol retrievals at Kanpur, Indo-Gangetic basin

[1] We have compared the spectral aerosol optical depth (AOD, tau lambda) and aerosol fine mode fraction (AFMF) of Collection 004 (C004) derived from Moderate-Resolution Imaging Spectroradiometer (MODIS) on board National Aeronautics and Space Administration's (NASA) Terra and Aqua platforms with that obtained from Aerosol Robotic Network (AERONET) at Kanpur (26.45 degrees N, 80.35 degrees E), India for the period 2001-2005. The spatially-averaged (0.5 degrees x 0.5 degrees centered at AERONET sunphotometer) MODIS Level-2 aerosol parameters (10 km at nadir) were compared with the temporally averaged AERONET-measured AOD (within +/- 30 minutes of MODIS overpass). We found that MODIS systematically overestimated AOD during the pre-monsoon season (March to June, known to be influenced by dust aerosols). The errors in AOD at 0.66 mu m were correlated with the apparent reflectance at 2.1 mu m (rho*(2.1)) which MODIS C004 uses to estimate the surface reflectance in the visible channels (rho(0.47) = rho*(2.1)/ 4, rho(0.66) = rho*(2.1)/ 2). The large errors in AOD (Delta tau(0.66) > 0.3) are found to be associated with the higher values of rho*(2.1) (0.18 to 0.25), where the uncertainty in the ratios of reflectance is large (Delta rho(0.66) +/- 0.04, Delta rho(0.47) +/- 0.02). This could have resulted in lower surface reflectance, higher aerosol path radiance and thus lead to overestimation in AOD. While MODIS-derived AFMF has binary distribution (1 or 0) with too low (AFMF < 0.2) during dust-loading period, and similar to 1 for the rest of the retrievals, AERONET showed range of values (0.4 to 0.9). The errors in tau(0.66) were also high in the scattering angle range 110 degrees - 140 degrees, where the optical effects of nonspherical dust particles are different from that of spherical particles.