Laboratory notebooks: a cautionary tale

A mathematician tends to have an intense relationship with treatises – one which is more akin to that of a historian than that of her colleagues in the ‘hard’ sciences. A book may be a century or two old and still be relevant as a source of information or inspiration, well-thumbed textbooks from youth might be still consulted decades later, and fierce arguments rage about relative merits of different treatments of the same subject. And much like any book-lover, a mathematician is forever arguing with herself whether she can afford to buy this volume or the other. When the price label is in dollars or euros and the salary paid in rupees, this last dilemma is particularly acute.

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.

Developments in amplitude-comparator techniques for distance relays

The paper reports the development of new amplitude-comparator techniques which allow the instantaneous comparison of the amplitude of the signals derived from primary line quantities. These techniques are used to derive a variety of impedance characteristics. The merits of the new relaying system are: the simple mode of the relay circuitry, the derivation of closed polar characteristics (i.e. quadrilateral) by a single measuring gate and sharp discontinuities in the polar characteristics. Design principles and circuit models in their schematic form are described and, in addition, a comprehensive theoretical basis for comparison is also presented. Dynamic test results are presented for a quadrilateral characteristic of potentially general application.

Markov chain splitting methods in structural reliability integral estimation

Monte Carlo simulation methods involving splitting of Markov chains have been used in evaluation of multi-fold integrals in different application areas. We examine in this paper the performance of these methods in the context of evaluation of reliability integrals from the point of view of characterizing the sampling fluctuations. The methods discussed include the Au-Beck subset simulation, Holmes-Diaconis-Ross method, and generalized splitting algorithm. A few improvisations based on first order reliability method are suggested to select algorithmic parameters of the latter two methods. The bias and sampling variance of the alternative estimators are discussed. Also, an approximation to the sampling distribution of some of these estimators is obtained. Illustrative examples involving component and series system reliability analyses are presented with a view to bring out the relative merits of alternative methods. (C) 2015 Elsevier Ltd. All rights reserved.

Halogen Bonding and Chalcogen Bonding in 4,7-Dibromo-5, 6-dinitro-2,1,3-benzothiadiazole

An organic solid, 4,7-dibromo-5,6-dinitro-2,1,3-benzothiadiazole, has been designed to serve as an illustrative example to quantitatively evaluate the relative merits of halogen and chalcogen bonding in terms of charge density features. The compound displays two polymorphic modifications, one crystallizing in a non-centrosymmetric space group (Z' = 1) and the other in a centrosymmetric space group with two molecules in the asymmetric unit (Z' = 2). Topological analysis based on QTAIM clearly brings out the dominance of the chalcogen bond over the halogen bond along with an indication that halogen bonds are more directional compared to chalcogen bonds. The cohesive energies calculated with the absence of both strong and weak hydrogen bonds as well as stacking interaction are indicative of the stabilities associated with the polymorphic forms.

Stimuli-responsive colorimetric and NIR fluorescence combination probe for selective reporting of cellular hydrogen peroxide

Hydrogen peroxide (H2O2) is a key reactive oxygen species and a messenger in cellular signal transduction apart from playing a vital role in many biological processes in living organisms. In this article, we present phenyl boronic acid-functionalized quinone-cyanine (QCy-BA) in combination with AT-rich DNA (exogenous or endogenous cellular DNA), i.e., QCy-BA subset of DNA as a stimuli-responsive NIR fluorescence probe for measuring in vitro levels of H2O2. In response to cellular H2O2 stimulus, QCy-BA converts into QCy-DT, a one-donor-two-acceptor (D2A) system that exhibits switch-on NIR fluorescence upon binding to the DNA minor groove. Fluorescence studies on the combination probe QCy-BA subset of DNA showed strong NIR fluorescence selectively in the presence of H2O2. Furthermore, glucose oxidase (GOx) assay confirmed the high efficiency of the combination probe QCy-BA subset of DNA for probing H2O2 generated in situ through GOx-mediated glucose oxidation. Quantitative analysis through fluorescence plate reader, flow cytometry and live imaging approaches showed that QCy-BA is a promising probe to detect the normal as well as elevated levels of H2O2 produced by EGF/Nox pathways and post-genotoxic stress in both primary and senescent cells. Overall, QCy-BA, in combination with exogenous or cellular DNA, is a versatile probe to quantify and image H2O2 in normal and disease-associated cells.