Real-time monitoring of critical nodes with minimal number of Phasor Measurement Units

This paper presents a method for placement of Phasor Measurement Units, ensuring the monitoring of vulnerable buses which are obtained based on transient stability analysis of the overall system. Real-time monitoring of phase angles across different nodes, which indicates the proximity to instability, the very purpose will be well defined if the PMUs are placed at buses which are more vulnerable. The issue is to identify the key buses where the PMUs should be placed when the transient stability prediction is taken into account considering various disturbances. Integer Linear Programming technique with equality and inequality constraints is used to find out the optimal placement set with key buses identified from transient stability analysis. Results on IEEE-14 bus system are presented to illustrate the proposed approach.

The Nature of Bond Critical Points in Dinuclear Copper(I) Complexes

Closed-shell contacts between two copper(I) ions are expected to be repulsive. However, such contacts are quite frequent and are well documented. Crystallographic characterization of such contacts in unsupported and bridged multinuclear copper(I) complexes has repeatedly invited debates on the existence of cuprophilicity. Recent developments in the application of Baders theory of atoms-in-molecules (AIM) to systems in which weak hydrogen bonds are involved suggests that the copper(I)copper(I) contacts would benefit from a similar analysis. Thus the nature of electron-density distributions in copper(I) dimers that are unsupported, and those that are bridged, have been examined. A comparison of complexes that are dimers of symmetrical monomers and those that are dimers of two copper(I) monomers with different coordination spheres has also been made. AIM analysis shows that a bond critical point (BCP) between two Cu atoms is present in most cases. The nature of the BCP in terms of the electron density, ?, and its Laplacian is quite similar to the nature of critical points observed in hydrogen bonds in the same systems. The ? is inversely correlated to Cu?Cu distance. It is higher in asymmetrical systems than what is observed in corresponding symmetrical systems. By examining the ratio of the local electron potential-energy density (Vc) to the kinetic energy density (Gc), |Vc|/Gc at the critical point suggests that these interactions are not perfectly ionic but have some shared nature. Thus an analysis of critical points by using AIM theory points to the presence of an attractive metallophilic interaction similar to other well-documented weak interactions like hydrogen bonding.

Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.

Diverse functions of restriction-modification systems in addition to cellular defense

Restriction-modification (R-M) systems are ubiquitous and are often considered primitive immune systems in bacteria. Their diversity and prevalence across the prokaryotic kingdom are an indication of their success as a defense mechanism against invading genomes. However, their cellular defense function does not adequately explain the basis for their immaculate specificity in sequence recognition and nonuniform distribution, ranging from none to too many, in diverse species. The present review deals with new developments which provide insights into the roles of these enzymes in other aspects of cellular function. In this review, emphasis is placed on novel hypotheses and various findings that have not yet been dealt with in a critical review. Emerging studies indicate their role in various cellular processes other than host defense, virulence, and even controlling the rate of evolution of the organism. We also discuss how R-M systems could have successfully evolved and be involved in additional cellular portfolios, thereby increasing the relative fitness of their hosts in the population.

Multiwalled-carbon-nanotube-induced miscibility in near-critical PS/PVME blends: assessment through concentration fluctuations and segmental relaxation

The effects of multiwalled carbon nanotubes (MWNTs) on the concentration fluctuations, interfacial driven elasticity, phase morphology, and local segmental dynamics of chains for near-critical compositions of polystyrene/poly(vinyl to methyl ether) (PS/PVME) blends were systematically investigated using dynamic shear rheology and dielectric spectroscopy. The contribution of the correlation length (xi) of the concentration fluctuations to the evolving stresses was monitored in situ to probe the different stages of demixing in the blends. The classical upturn in the dynamic moduli was taken as the rheological demixing temperature (T-rheo), which was also observed to be in close agreement with those obtained using concentration fluctuation variance, <(delta phi)(2)>, versus temperature curves. Further, Fredrickson and Larson's approach involving the mean-field approximation and the double-reptation self-concentration (DRSC) model was employed to evaluate the spinodal decomposition temperature (T-s). Interestingly, the values of both T-rheo and T-s shifted upward in the blends in the presence of MWNTs, manifesting in molecular-level miscibility. These phenomenal changes were further observed to be a function of the concentration of MWNTs. The evolution of morphology as a function of temperature was studied using polarized optical microscopy (POM). It was observed that PVME, which evolved as an interconnected network during the early stages of demixing, coarsened into a matrix-droplet morphology in the late stages. The preferential wetting of PVME onto MWNTs as a result of physicochemical interactions retained the interconnected network of PVME for longer time scales, as supported by POM and atomic force microscopy (AFM) images. Microscopic heterogeneity in macroscopically miscible systems was studied by dielectric relaxation spectroscopy. The slowing of segmental relaxations in PVME was observed in the presence of both ``frozen'' PS and MWNTs interestingly at temperatures much below the calorimetric glass transition temperature (T-g). This phenomenon was observed to be local rather than global and was addressed by monitoring the evolution of the relaxation spectra near and above the demixing temperature.

Group behaviour in physical, chemical and biological systems

Groups exhibit properties that either are not perceived to exist, or perhaps cannot exist, at the individual level. Such `emergent' properties depend on how individuals interact, both among themselves and with their surroundings. The world of everyday objects consists of material entities. These are, ultimately, groups of elementary particles that organize themselves into atoms and molecules, occupy space, and so on. It turns out that an explanation of even the most commonplace features of this world requires relativistic quantum field theory and the fact that Planck's constant is discrete, not zero. Groups of molecules in solution, in particular polymers ('sols'), can form viscous clusters that behave like elastic solids ('gels'). Sol-gel transitions are examples of cooperative phenomena. Their occurrence is explained by modelling the statistics of inter-unit interactions: the likelihood of either state varies sharply as a critical parameter crosses a threshold value. Group behaviour among cells or organisms is often heritable and therefore can evolve. This permits an additional, typically biological, explanation for it in terms of reproductive advantage, whether of the individual or of the group. There is no general agreement on the appropriate explanatory framework for understanding group-level phenomena in biology.

A critical review of the definition of FRA resonance frequency of transformers as per IEEE Std C57.149-2012

The explanation of resonance given in IEEE Std C57.149-2012 to define resonance during frequency response analysis (FRA) measurements on transformers implicitly uses the conditions prevalent during resonance in a series R-L-C circuit. This dependence is evident from the two assertions made in the definition, viz., resulting in zero net reactive impedance, and, accompanied by a zero value appearing in the phase angle of the frequency response function. These two conditions are satisfied (at resonance) only in a series R-L-C circuit and certainly not in a transformer, as has been assumed in the Standard. This can be proved by considering a ladder-network model. Circuit analysis of this ladder network reveals the origin of this fallacy and proves that, at resonance, neither is the ladder network purely resistive and nor is the phase angle (between input voltage and input current) always zero. Also, during FRA measurements, it is often seen that phase angle does not traverse the conventional cyclic path from +90 degrees to -90 degrees (or vice versa) at all resonant frequencies. This peculiar feature can also be explained using pole-zero maps. Simple derivations, simulations and experimental results on an actual winding are presented. In summary, authors believe that this study dispels existing misconceptions about definition of FRA resonance and provides material for its correction in IEEE Std C57.149-2012. (C) 2014 Elsevier B.V. All rights reserved.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.

Robust Glyoxalase activity of Hsp31, a ThiJ/DJ-1/PfpI Family Member Protein, Is Critical for Oxidative Stress Resistance in Saccharomyces cerevisiae

Methylglyoxal (MG) is a reactive metabolic intermediate generated during various cellular biochemical reactions, including glycolysis. The accumulation of MG indiscriminately modifies proteins, including important cellular antioxidant machinery, leading to severe oxidative stress, which is implicated in multiple neurodegenerative disorders, aging, and cardiac disorders. Although cells possess efficient glyoxalase systems for detoxification, their functions are largely dependent on the glutathione cofactor, the availability of which is self-limiting under oxidative stress. Thus, higher organisms require alternate modes of reducing the MG-mediated toxicity and maintaining redox balance. In this report, we demonstrate that Hsp31 protein, a member of the ThiJ/DJ-1/PfpI family in Saccharomyces cerevisiae, plays an indispensable role in regulating redox homeostasis. Our results show that Hsp31 possesses robust glutathione-independent methylglyoxalase activity and suppresses MG-mediated toxicity and ROS levels as compared with another paralog, Hsp34. On the other hand, glyoxalase-defective mutants of Hsp31 were found highly compromised in regulating the ROS levels. Additionally, Hsp31 maintains cellular glutathione and NADPH levels, thus conferring protection against oxidative stress, and Hsp31 relocalizes to mitochondria to provide cytoprotection to the organelle under oxidative stress conditions. Importantly, human DJ-1, which is implicated in the familial form of Parkinson disease, complements the function of Hsp31 by suppressing methylglyoxal and oxidative stress, thus signifying the importance of these proteins in the maintenance of ROS homeostasis across phylogeny.

Length scales in glass-forming liquids and related systems: a review

The central problem in the study of glass-forming liquids and other glassy systems is the understanding of the complex structural relaxation and rapid growth of relaxation times seen on approaching the glass transition. A central conceptual question is whether one can identify one or more growing length scale(s) associated with this behavior. Given the diversity of molecular glass-formers and a vast body of experimental, computational and theoretical work addressing glassy behavior, a number of ideas and observations pertaining to growing length scales have been presented over the past few decades, but there is as yet no consensus view on this question. In this review, we will summarize the salient results and the state of our understanding of length scales associated with dynamical slow down. After a review of slow dynamics and the glass transition, pertinent theories of the glass transition will be summarized and a survey of ideas relating to length scales in glassy systems will be presented. A number of studies have focused on the emergence of preferred packing arrangements and discussed their role in glassy dynamics. More recently, a central object of attention has been the study of spatially correlated, heterogeneous dynamics and the associated length scale, studied in computer simulations and theoretical analysis such as inhomogeneous mode coupling theory. A number of static length scales have been proposed and studied recently, such as the mosaic length scale discussed in the random first-order transition theory and the related point-to-set correlation length. We will discuss these, elaborating on key results, along with a critical appraisal of the state of the art. Finally we will discuss length scales in driven soft matter, granular fluids and amorphous solids, and give a brief description of length scales in aging systems. Possible relations of these length scales with those in glass-forming liquids will be discussed.

Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk

Complex systems inspired analysis suggests a hypothesis that financial meltdowns are abrupt critical transitions that occur when the system reaches a tipping point. Theoretical and empirical studies on climatic and ecological dynamical systems have shown that approach to tipping points is preceded by a generic phenomenon called critical slowing down, i.e. an increasingly slow response of the system to perturbations. Therefore, it has been suggested that critical slowing down may be used as an early warning signal of imminent critical transitions. Whether financial markets exhibit critical slowing down prior to meltdowns remains unclear. Here, our analysis reveals that three major US (Dow Jones Index, S&P 500 and NASDAQ) and two European markets (DAX and FTSE) did not exhibit critical slowing down prior to major financial crashes over the last century. However, all markets showed strong trends of rising variability, quantified by time series variance and spectral function at low frequencies, prior to crashes. These results suggest that financial crashes are not critical transitions that occur in the vicinity of a tipping point. Using a simple model, we argue that financial crashes are likely to be stochastic transitions which can occur even when the system is far away from the tipping point. Specifically, we show that a gradually increasing strength of stochastic perturbations may have caused to abrupt transitions in the financial markets. Broadly, our results highlight the importance of stochastically driven abrupt transitions in real world scenarios. Our study offers rising variability as a precursor of financial meltdowns albeit with a limitation that they may signal false alarms.

On the issues of resolving a low melting combination as a definite eutectic or an elusive cocrystal: A critical evaluation

Cocrystals and eutectics are different yet related crystalline multi-component adducts with diverse applications in pharmaceutical and materials fields. Recently, they were shown to be alternate products of cocrystallization experiments. Whereas a cocrystal shows distinct diffraction, spectroscopic and thermal signatures as compared to parent components, the hallmark of a eutectic is its low melting nature. However, in certain cases, there can be a problem when one resorts to design a cocrystal and assess its formation vis-A -vis a eutectic. In the absence of a gold standard method to make a cocrystal, it is often difficult to judge how exhaustive should the cocrystallization trials be to ensure the accomplishment of a desired/putative cocrystal. Further, a cocrystal can manifest with intermolecular interactions and/or crystal structure similar to that of its parent compounds such that the conventional diffraction and spectroscopic techniques will be of little help to conclusively infer the formation of cocrystal in the lack of single crystals. Such situations combined with low melting behavior of a combination brings the complication of resolving the combination as a cocrystal or eutectic since now both the adducts share common features. Based on the curious case of Caffeine-Benzoic acid combination, this study aims to unfold the intricate issues related to the design, formation and characterization of cocrystals and eutectics for a way forward. The utility of heteronuclear seeding methodology in establishing a given combination as a cocrystal-forming one or a eutectic-forming one in four known systems is appraised.

Simulation of the Load-Unload Response Ratio and Critical Sensitivity in the Lattice Solid Model

The Load-Unload Response Ratio (LURR) method is an intermediate-term earthquake prediction approach that has shown considerable promise. It involves calculating the ratio of a specified energy release measure during loading and unloading where loading and unloading periods are determined from the earth tide induced perturbations in the Coulomb Failure Stress on optimally oriented faults. In the lead-up to large earthquakes, high LURR values are frequently observed a few months or years prior to the event. These signals may have a similar origin to the observed accelerating seismic moment release (AMR) prior to many large earthquakes or may be due to critical sensitivity of the crust when a large earthquake is imminent. As a first step towards studying the underlying physical mechanism for the LURR observations, numerical studies are conducted using the particle based lattice solid model (LSM) to determine whether LURR observations can be reproduced. The model is initialized as a heterogeneous 2-D block made up of random-sized particles bonded by elastic-brittle links. The system is subjected to uniaxial compression from rigid driving plates on the upper and lower edges of the model. Experiments are conducted using both strain and stress control to load the plates. A sinusoidal stress perturbation is added to the gradual compressional loading to simulate loading and unloading cycles and LURR is calculated. The results reproduce signals similar to those observed in earthquake prediction practice with a high LURR value followed by a sudden drop prior to macroscopic failure of the sample. The results suggest that LURR provides a good predictor for catastrophic failure in elastic-brittle systems and motivate further research to study the underlying physical mechanisms and statistical properties of high LURR values. The results provide encouragement for earthquake prediction research and the use of advanced simulation models to probe the physics of earthquakes.

Expanding adoption of drinking water treatment systems in developing countries: a case study from Tamil Nadu, India

Household-level water treatment and safe storage systems (HWTS) are simple, local, user-friendly, and low cost options to improve drinking water quality at the point of use. However, despite conclusive evidence of the health and economic benefits of HWTS, and promotion efforts in over 50 countries in the past 20 years, implementation outcomes have been slow, reaching only 5-10 million regular users. This study attempts to understand the barriers and drivers affecting HWTS implementation. Using a case study example of a biosand filter program in southern India, system dynamics modelling is shown to be a useful tool to map the inter-relationships of different critical factors and to understand the dissemination dynamics. It is found that the co-existence of expanding quickly and achieving financial sustainability appears to be difficult to achieve under the current program structure.

A systems approach to characterise the dissemination process of household water treatment systems in developing countries

Abstract: Starting in the 1980s, household-level water treatment and safe storage systems (HWTS) have been developed as simple, local, user-friendly, and low cost options to improve drinking water quality at the point of use. However, despite conclusive evidence of the health and economic benefits of HWTS, and promotion efforts in over 50 countries in the past 20 years, implementation outcomes have been slow, reaching only 5-10 million regular users. This study attempts to understand the barriers and drivers affecting HWTS implementation. Although existing literature related to HWTS and innovation diffusion theories proposed ample critical factors and recommendations, there is a lack of holistic and systemic approach to integrate these findings. It is proposed that system dynamics modelling can be a promising tool to map the inter-relationships of different critical factors and to understand the structure of HWTS dissemination process, which may lead to identifying high impact, leveraged mitigation strategies to scale-up HWTS adoption and sustained use.