Taylor series expansion based multidimensional image reconstruction for confocal and 4pi microscopy

We propose and experimentally demonstrate a three-dimensional (3D) image reconstruction methodology based on Taylor series approximation (TSA) in a Bayesian image reconstruction formulation. TSA incorporates the requirement of analyticity in the image domain, and acts as a finite impulse response filter. This technique is validated on images obtained from widefield, confocal laser scanning fluorescence microscopy and two-photon excited 4pi (2PE-4pi) fluorescence microscopy. Studies on simulated 3D objects, mitochondria-tagged yeast cells (labeled with Mitotracker Orange) and mitochondrial networks (tagged with Green fluorescent protein) show a signal-to-background improvement of 40% and resolution enhancement from 360 to 240 nm. This technique can easily be extended to other imaging modalities (single plane illumination microscopy (SPIM), individual molecule localization SPIM, stimulated emission depletion microscopy and its variants).

Assessing resilience and state-transition models with historical records of cheatgrass Bromus tectorum invasion in North American sagebrush-steppe

1. Resilience-based approaches are increasingly being called upon to inform ecosystem management, particularly in arid and semi-arid regions. This requires management frameworks that can assess ecosystem dynamics, both within and between alternative states, at relevant time scales. 2. We analysed long-term vegetation records from two representative sites in the North American sagebrush-steppe ecosystem, spanning nine decades, to determine if empirical patterns were consistent with resilience theory, and to determine if cheatgrass Bromus tectorum invasion led to thresholds as currently envisioned by expert-based state-and-transition models (STM). These data span the entire history of cheatgrass invasion at these sites and provide a unique opportunity to assess the impacts of biotic invasion on ecosystem resilience. 3. We used univariate and multivariate statistical tools to identify unique plant communities and document the magnitude, frequency and directionality of community transitions through time. Community transitions were characterized by 37-47% dissimilarity in species composition, they were not evenly distributed through time, their frequency was not correlated with precipitation, and they could not be readily attributed to fire or grazing. Instead, at both sites, the majority of community transitions occurred within an 8-10year period of increasing cheatgrass density, became infrequent after cheatgrass density peaked, and thereafter transition frequency declined. 4. Greater cheatgrass density, replacement of native species and indication of asymmetry in community transitions suggest that thresholds may have been exceeded in response to cheatgrass invasion at one site (more arid), but not at the other site (less arid). Asymmetry in the direction of community transitions also identified communities that were at-risk' of cheatgrass invasion, as well as potential restoration pathways for recovery of pre-invasion states. 5. Synthesis and applications. These results illustrate the complexities associated with threshold identification, and indicate that criteria describing the frequency, magnitude, directionality and temporal scale of community transitions may provide greater insight into resilience theory and its application for ecosystem management. These criteria are likely to vary across biogeographic regions that are susceptible to cheatgrass invasion, and necessitate more in-depth assessments of thresholds and alternative states, than currently available.

Estimation of Series Capacitance for a Three-Phase Transformer Winding From Its Measured Frequency Response

Recently, authors published a method to indirectly measure series capacitance (C-s) of a single, isolated, uniformly wound transformer winding, from its measured frequency response. The next step was to implement it on an actual three-phase transformer. This task is not as straightforward as it might appear at first glance, since the measured frequency response on a three-phase transformer is influenced by nontested windings and their terminal connections, core, tank, etc. To extract the correct value of C-s from this composite frequency response, the formulation has to be reworked to first identify all significant influences and then include their effects. Initially, the modified method and experimental results on a three-phase transformer (4 MVA, 33 kV/433 V) are presented along with results on the winding considered in isolation (for cross validation). Later, the method is directly implemented on another three-phase unit (3.5 MVA, 13.8 kV/765 V) to show repeatability.

On the unramified principal series of GL(3) over non-archimedean local fields

Let F be a non-archimedean local field and let O be its ring of integers. We give a complete description of the irreducible constituents of the restriction of the unramified principal series representations of GL(3)(F) to GL(3)(O). (C) 2013 Elsevier Inc. All rights reserved.

Predictability of nonstationary time series using wavelet and EMD based ARMA models

Research has been undertaken to ascertain the predictability of non-stationary time series using wavelet and Empirical Mode Decomposition (EMD) based time series models. Methods have been developed in the past to decompose a time series into components. Forecasting of these components combined with random component could yield predictions. Using this ideology, wavelet and EMD analyses have been incorporated separately which decomposes a time series into independent orthogonal components with both time and frequency localizations. The component series are fit with specific auto-regressive models to obtain forecasts which are later combined to obtain the actual predictions. Four non-stationary streamflow sites (USGS data resources) of monthly total volumes and two non-stationary gridded rainfall sites (IMD) of monthly total rainfall are considered for the study. The predictability is checked for six and twelve months ahead forecasts across both the methodologies. Based on performance measures, it is observed that wavelet based method has better prediction capabilities over EMD based method despite some of the limitations of time series methods and the manner in which decomposition takes place. Finally, the study concludes that the wavelet based time series algorithm can be used to model events such as droughts with reasonable accuracy. Also, some modifications that can be made in the model have been discussed that could extend the scope of applicability to other areas in the field of hydrology. (C) 2013 Elesvier B.V. All rights reserved.

New Structural Topologies in a Series of 3d Metal Complexes with Isomeric Phenylenediacetates and 1,3,5-Tris(1-imidazolyl)benzene Ligand: Syntheses, Structures, and Magnetic and Luminescence Properties

In this article we present the syntheses, characterizations, magnetic and luminescence properties of five 3d-metal complexes, Co(tib)(1,2-phda)](n)center dot(H2O)(n) (1), Co-3(tib)(2)(1,3-phda)(3)(H2O)](n)center dot(H2O)(2n) (2), Co-5(tib)(3)(1,4-phda)(5)(H2O)(3)](n)center dot(H2O)(7n) (3), Zn-3(tib)(2)(1,3-phda)(3)](n)center dot(H2O)(4n) (4), and Mn(tib)(2)(H2O)(2)](n)center dot(1,4-phdaH)(2n)center dot(H2O)(4n) (5), obtained from the use of isomeric phenylenediacetates (phda) and the neutral 1,3,5-tris(1-imidazolyl)benzene (tib) ligand. Single crystal X-ray structures showed that 1 constitutes 3,5-connected 2-nodal nets with a double-layered two-dimensional (2D) structure, while 2 forms an interpenetrated 2D network (3,4-connected 3-nodal net). Complex 3 has a complicated three-dimensional structure with 10-nodal 3,4,5-connected nets. Complex 4, although it resembles 2 in stoichiometry and basic building structures, forms a very different overall 2D assembly. In complex 5 the dicarboxylic acid, upon losing only one of the acidic protons, does not take part in coordination; instead it forms a complicated hydrogen bonding network with water molecules. Magnetic susceptibility measurements over a wide range of temperatures revealed that the metal ions exchange very poorly through the tib ligand, but for the Co(II) complexes the effects of nonquenched orbital contributions are prominent. The 3d(10) metal complex 4 showed strong luminescence with lambda(max) = 415 nm (lambda(ex) = 360 nm).

Form and Function of Proteins. Historical Background and the Indian Effort in Macromolecular Crystallography

Global efforts in macromolecular crystallography started in the thirties of the last century. However, definitive results began to emerge only in the late fifties and the early sixties. India has a long tradition in crystallography. The country had a head start in theoretical and computational structural biology, thanks to the efforts of G.N. Ramachandran and his colleagues in the fifties and the sixties. However, macromolecular crystallography got off the ground in India only in the eighties, particularly after the Bangalore group received adequate support from the Department of Science and Technology under their Thrust Area Programme. The Bangalore centre was also identified as a national nucleus for the development of the area in the country. Since then work in the area has spread widely and is being carried out by several groups, mainly led by scientists trained at Bangalore or their descendents, in about thirty institutions in India. In addition to the Department of Science and Technology, the effort is now supported by other agencies like the Department of Biotechnology and the Council of Scientific and Industrial Research. The problems addressed by macromolecular crystallographers in India encompass almost all aspects of modern biology. Indian efforts in macromolecular crystallography have also become an important component of the international efforts in the area.

Type III restriction-modification enzymes: a historical perspective

Restriction endonucleases interact with DNA at specific sites leading to cleavage of DNA. Bacterial DNA is protected from restriction endonuclease cleavage by modifying the DNA using a DNA methyltransferase. Based on their molecular structure, sequence recognition, cleavage position and cofactor requirements, restriction-modification (R-M) systems are classified into four groups. Type III R-M enzymes need to interact with two separate unmethylated DNA sequences in inversely repeated head-to-head orientations for efficient cleavage to occur at a defined location (25-27 bp downstream of one of the recognition sites). Like the Type I R-M enzymes, Type III R-M enzymes possess a sequence-specific ATPase activity for DNA cleavage. ATP hydrolysis is required for the long-distance communication between the sites before cleavage. Different models, based on 1D diffusion and/or 3D-DNA looping, exist to explain how the long-distance interaction between the two recognition sites takes place. Type III R-M systems are found in most sequenced bacteria. Genome sequencing of many pathogenic bacteria also shows the presence of a number of phase-variable Type III R-M systems, which play a role in virulence. A growing number of these enzymes are being subjected to biochemical and genetic studies, which, when combined with ongoing structural analyses, promise to provide details for mechanisms of DNA recognition and catalysis.

Fuzzy Classification of Time Series Data

The problem of classification of time series data is an interesting problem in the field of data mining. Even though several algorithms have been proposed for the problem of time series classification we have developed an innovative algorithm which is computationally fast and accurate in several cases when compared with 1NN classifier. In our method we are calculating the fuzzy membership of each test pattern to be classified to each class. We have experimented with 6 benchmark datasets and compared our method with 1NN classifier.

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives

Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tuberculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, development of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named `distance exponent index (D-x)' (taken x = -4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful prediction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in computer-aided drug design.

Time-Domain Approach to Estimate Series Capacitance of an Isolated Phase Winding of a Transformer

Information available in frequency response data is equivalently available in the time domain as a response due to an impulse excitation. The idea to pursue this equivalence to estimate series capacitance is linked to the well-known fact that under impulse excitation, the line/neutral current in a transformer has three distinct components, of which, the initial capacitive component is the first to manifest, followed by the oscillatory and inductive components. Of these, the capacitive component is temporally well separated from the rest-a crucial feature permitting its direct access and analysis. Further, the winding initially behaves as a pure capacitive network, so the initial component must obviously originate from only the (series and shunt) capacitances. With this logic, it should therefore be possible to estimate series capacitance, just by measuring the initial capacitive component of line current and the total shunt capacitance. The principle of the method and details of its implementation on two actual isolated transformerwindings (uniformly wound) are presented. For implementation, a low-voltage recurrent surge generator, a current probe, and a digital oscilloscope are all that is needed. The method is simple and requires no programming and needs least user intervention, thus paving the way for its widespread use.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

Using long time series of agricultural-derived nitrates for estimating catchment transit times

The estimation of water and solute transit times in catchments is crucial for predicting the response of hydrosystems to external forcings (climatic or anthropogenic). The hydrogeochemical signatures of tracers (either natural or anthropogenic) in streams have been widely used to estimate transit times in catchments as they integrate the various processes at stake. However, most of these tracers are well suited for catchments with mean transit times lower than about 4-5 years. Since the second half of the 20th century, the intensification of agriculture led to a general increase of the nitrogen load in rivers. As nitrate is mainly transported by groundwater in agricultural catchments, this signal can be used to estimate transit times greater than several years, even if nitrate is not a conservative tracer. Conceptual hydrological models can be used to estimate catchment transit times provided their consistency is demonstrated, based on their ability to simulate the stream chemical signatures at various time scales and catchment internal processes such as N storage in groundwater. The objective of this study was to assess if a conceptual lumped model was able to simulate the observed patterns of nitrogen concentration, at various time scales, from seasonal to pluriannual and thus if it was relevant to estimate the nitrogen transit times in headwater catchments. A conceptual lumped model, representing shallow groundwater flow as two parallel linear stores with double porosity, and riparian processes by a constant nitrogen removal function, was applied on two paired agricultural catchments which belong to the Research Observatory ORE AgrHys. The Global Likelihood Uncertainty Estimation (GLUE) approach was used to estimate parameter values and uncertainties. The model performance was assessed on (i) its ability to simulate the contrasted patterns of stream flow and stream nitrate concentrations at seasonal and inter-annual time scales, (ii) its ability to simulate the patterns observed in groundwater at the same temporal scales, and (iii) the consistency of long-term simulations using the calibrated model and the general pattern of the nitrate concentration increase in the region since the beginning of the intensification of agriculture in the 1960s. The simulated nitrate transit times were found more sensitive to climate variability than to parameter uncertainty, and average values were found to be consistent with results from others studies in the same region involving modeling and groundwater dating. This study shows that a simple model can be used to simulate the main dynamics of nitrogen in an intensively polluted catchment and then be used to estimate the transit times of these pollutants in the system which is crucial to guide mitigation plans design and assessment. (C) 2015 Elsevier B.V. All rights reserved.