A Modified Sum-Product Algorithm over Graphs with Isolated Short Cycles

We investigate into the limitations of the sum-product algorithm in the probability domain over graphs with isolated short cycles. By considering the statistical dependency of messages passed in a cycle of length 4, we modify the update equations for the beliefs at the variable and check nodes. We highlight an approximate log domain algebra for the modified variable node update to ensure numerical stability. At higher signal-to-noise ratios (SNR), the performance of decoding over graphs with isolated short cycles using the modified algorithm is improved compared to the original message passing algorithm (MPA).

Simultaneously Uncovering the Patterns of Brain Regions Involved in Different Story Reading Subprocesses

Story understanding involves many perceptual and cognitive subprocesses, from perceiving individual words, to parsing sentences, to understanding the relationships among the story characters. We present an integrated computational model of reading that incorporates these and additional subprocesses, simultaneously discovering their fMRI signatures. Our model predicts the fMRI activity associated with reading arbitrary text passages, well enough to distinguish which of two story segments is being read with 74% accuracy. This approach is the first to simultaneously track diverse reading subprocesses during complex story processing and predict the detailed neural representation of diverse story features, ranging from visual word properties to the mention of different story characters and different actions they perform. We construct brain representation maps that replicate many results from a wide range of classical studies that focus each on one aspect of language processing and offer new insights on which type of information is processed by different areas involved in language processing. Additionally, this approach is promising for studying individual differences: it can be used to create single subject maps that may potentially be used to measure reading comprehension and diagnose reading disorders.

Unusually Short Chalcogen Bonds Involving Organoselenium: Insights into the Se-N Bond Cleavage Mechanism of the Antioxidant Ebselen and Analogues

Structural studies on the polymorphs of the organoselenium antioxidant ebselen and its derivative show the potential of organic selenium to form unusually short Se center dot center dot center dot O chalcogen bonds that lead to conserved supramolecular recognition units. Se center dot center dot center dot O interactions observed in these polymorphs are the shortest such chalcogen bonds known for organoselenium compounds. The FTIR spectral evolution characteristics of this interaction from solution state to solid crystalline state further validates the robustness of this class of supramolecular recognition units. The strength and electronic nature of the Se center dot center dot center dot O chalcogen bonds were explored using high-resolution X-ray charge density analysis and atons-in-molecules (AIM) theoretical analysis. A charge density study unravels the strong electrostatic nature of Se center dot center dot center dot O chalcogen bonding and soft-metal-like behavior of organoselenium. An analysis of the charge density around Se-N and Se-C covalent bonds in conjunction with the Se center dot center dot center dot O chalcogen bonding modes in ebselen and its analogues provides insights into the mechanism of drug action in this class of organoselenium antioxidants. The potential role of the intermolecular Se center dot center dot center dot O chalcogen bonding in forming the intermediate supramolecular assembly that leads to the bond cleavage mechanism has been proposed in terms of electron density topological parameters in a series of molecular complexes of ebselen with reactive oxygen species (ROS).

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Electric field induced short range to long range structural ordering and its influence on the Eu+3 photoluminescence in the lead-free ferroelectric Na1/2Bi1/2TiO3

Eu+3 was incorporated into the lattice of a lead-free ferroelectric Na1/2Bi1/2TiO3 (NBT) as per the nominal formula Na0.5Bi0.5-xEuxTiO3. This system was investigated with regard to the Eu+3 photoluminescence (PL) and structural behaviour as a function of composition and electric field. Electric field was found to irreversibly change the features in the PL spectra and also in the x-ray diffraction patterns below the critical composition x = 0.025. Detailed analysis revealed that below the critical composition, electric field irreversibly suppresses the structural heterogeneity inherent of the host matrix NBT and brings about a long range ferroelectric state with rhombohedral (R3c) distortion. It is shown that the structural disorder on the nano-scale opens a new channel for radiative transition which manifests as a new emission line branching off from the main D-5(0)-> F-7(0) line along with a concomitant change in the relative intensity of the other crystal field induced Stark lines with different J values. The study suggests that Eu+3 luminescence can be used to probe the relative degree of field induced structural ordering in relaxor ferroelectrics and also in high performance piezoelectric alloys where electric field couples very strongly with the lattice and structural degrees of freedom. (C) 2015 AIP Publishing LLC.

A Short Review on Lu-Hf Isotope System in Zircon: Implications for Crustal Evolution

Zircon has been recognized as the unaltered part of the Earth's history which preserves nearly 4 billion year record of earth's evolution. Zircon preserves igneous and metamorphic processes during its formation and remains unaffected by sedimentary processes and crustal recycling. U-Pb and Lu-Hf in zircon work as geochronometer and geochemical tracer respectively. Zircon provide valuable information about the source composition of the rocks and the intrinsic details of an unseen crust-mantle processes. The world wide data of U-Pb and Lu-Hf isotope systems in zircon reveal crustal evolution through geological history. Moreover, the U-Pb age pattern of zircons show distinct peaks attributed to preservation of crustal rocks or mountain building during supercontinent assembly. The histogram of continental crust preservation shows that nearly one-third of continental crust was formed during the Archean, almost 20% was formed during Paleoproterozoic and 14% in last 400 Ma.

DNA Elasticity from Short DNA to Nucleosomal DNA

Active biological processes like transcription, replication, recombination, DNA repair, and DNA packaging encounter bent DNA. Machineries associated with these processes interact with the DNA at short length (<100 base pair) scale. Thus, the study of elasticity of DNA at such length scale is very important. We use fully atomistic molecular dynamics (MD) simulations along with various theoretical methods to determine elastic properties of dsDNA of different lengths and base sequences. We also study DNA elasticity in nucleosome core particle (NCP) both in the presence and the absence of salt. We determine stretch modulus and persistence length of short dsDNA and nucleosomal DNA from contour length distribution and bend angle distribution, respectively. For short dsDNA, we find that stretch modulus increases with ionic strength while persistence length decreases. Calculated values of stretch modulus and persistence length for DNA are in quantitative agreement with available experimental data. The trend is opposite for NCP DNA. We find that the presence of histone core makes the DNA stiffer and thus making the persistence length 3-4 times higher than the bare DNA. Similarly, we also find an increase in the stretch modulus for the NCP DNA. Our study for the first time reports the elastic properties of DNA when it is wrapped around the histone core in NCP. We further show that the WLC model is inadequate to describe DNA elasticity at short length scale. Our results provide a deeper understanding of DNA mechanics and the methods are applicable to most protein-DNA complexes.

A Perspective on Computer Assisted Assessment Techniques for Short Free-Text Answers

Computer Assisted Assessment (CAA) has been existing for several years now. While some forms of CAA do not require sophisticated text understanding (e.g., multiple choice questions), there are also student answers that consist of free text and require analysis of text in the answer. Research towards the latter till date has concentrated on two main sub-tasks: (i) grading of essays, which is done mainly by checking the style, correctness of grammar, and coherence of the essay and (ii) assessment of short free-text answers. In this paper, we present a structured view of relevant research in automated assessment techniques for short free-text answers. We review papers spanning the last 15 years of research with emphasis on recent papers. Our main objectives are two folds. First we present the survey in a structured way by segregating information on dataset, problem formulation, techniques, and evaluation measures. Second we present a discussion on some of the potential future directions in this domain which we hope would be helpful for researchers.

Short-Time Beta Relaxation in Glass-Forming Liquids Is Cooperative in Nature

Temporal relaxation of density fluctuations in supercooled liquids near the glass transition occurs in multiple steps. Using molecular dynamics simulations for three model glass-forming liquids, we show that the short-time beta relaxation is cooperative in nature. Using finite-size scaling analysis, we extract a growing length scale associated with beta relaxation from the observed dependence of the beta relaxation time on the system size. We find, in qualitative agreement with the prediction of the inhomogeneous mode coupling theory, that the temperature dependence of this length scale is the same as that of the length scale that describes the spatial heterogeneity of local dynamics in the long-time alpha-relaxation regime.

Combustion and heat transfer characteristics of nanofluid fuel droplets: A short review

With the pressing need to meet an ever-increasing energy demand, the combustion systems utilizing fossil fuels have been the major contributors to carbon footprint. As the combustion of conventional energy resources continue to produce significant Green House gas (GHG) emissions, there is a strong emphasis to either upgrade or find an energy-efficient eco-friendly alternative to the traditional hydrocarbon fuels. With recent developments in nanotechnology, the ability to manufacture materials with custom tailored properties at nanoscale has led to the discovery of a new class of high energy density fuels containing reactive metallic nanoparticles (NPs). Due to the high reactive interfacial area and enhanced thermal and mass transport properties of nanomaterials, the high heat of formation of these metallic fuels can now be released rapidly, thereby saving on specific fuel consumption and hence reducing GHG emissions. In order to examine the efficacy of nanofuels in energetic formulations, it is imperative to first study their combustion characteristics at the droplet scale that form the fundamental building block for any combustion system utilizing liquid fuel spray. During combustion of such multiphase, multicomponent droplets, the phenomenon of diffusional entrapment of high volatility species leads to its explosive boiling (at the superheat limit) thereby leading to an intense internal pressure build-up. This pressure upsurge causes droplet fragmentation either in form of a microexplosion or droplet puffing followed by atomization (with formation of daughter droplets) featuring disruptive burning. Both these atomization modes represent primary mechanisms for extracting the high oxidation energies of metal NP additives by exposing them to the droplet flame (with daughter droplets acting as carriers of NPs). Atomization also serves as a natural mechanism for uniform distribution and mixing of the base fuel and enhancing burning rates (due to increase in specific surface area through formation of smaller daughter droplets). However, the efficiency of atomization depends on the thermo-physical properties of the base fuel, NP concentration and type. For instance, at dense loading NP agglomeration may lead to shell formation which would sustain the pressure upsurge and hence suppress atomization thereby reducing droplet gasification rate. Contrarily, the NPs may act as nucleation sites and aid boiling and the radiation absorption by NPs (from the flame) may lead to enhanced burning rates. Thus, nanoadditives may have opposing effects on the burning rate depending on the relative dominance of processes occurring at the droplet scale. The fundamental idea in this study is to: First, review different thermo-physical processes that occur globally at the droplet and sub-droplet scale such as surface regression, shell formation due to NP agglomeration, internal boiling, atomization/NP transport to flame zone and flame acoustic interaction that occur at the droplet scale and second, understand how their interaction changes as a function of droplet size, NP type, NP concentration and the type of base fuel. This understanding is crucial for obtaining phenomenological insights on the combustion behavior of novel nanofluid fuels that show great promise for becoming the next-generation fuels. (C) 2016 Elsevier Ltd. All rights reserved.