Developing and testing readability measurements for second language learners

This research constructed a readability measurement for French speakers who view English as a second language. It identified the true cognates, which are the similar words from these two languages, as an indicator of the difficulty of an English text for French people. A multilingual lexical resource is used to detect true cognates in text, and Statistical Language Modelling to predict the predict the readability level. The proposed enhanced statistical language model is making a step in the right direction by improving the accuracy of readability predictions for French speakers by up to 10% compared to state of the art approaches. The outcome of this study could accelerate the learning process for French speakers who are studying English. More importantly, this study also benefits the readability estimation research community, presenting an approach and evaluation at sentence level as well as innovating with the use of cognates as a new text feature.

Fracture process zone size and true fracture energy of concrete using acoustic emission

Acoustic emission (AE) energy, instead of amplitude, associated with each of the event is used to estimate the fracture process zone (FPZ) size. A steep increase in the cumulative AE energy of the events with respect to time is correlated with the formation of FPZ. Based on the AE energy released during these events and the locations of the events, FPZ size is obtained. The size-independent fracture energy is computed using the expressions given in the boundary effect model by least squares method since over-determined system of equations are obtained when data from several specimens are used. Instead of least squares method a different method is suggested in which the transition ligament length, measured from the plot of histograms of AE events plotted over the un-cracked ligament, is used directly to obtain size-independent fracture energy. The fracture energy thus calculated seems to be size-independent.

Rotorcraft parameter estimation using radial basis function neural network

Increased emphasis on rotorcraft performance and perational capabilities has resulted in accurate computation of aerodynamic stability and control parameters. System identification is one such tool in which the model structure and parameters such as aerodynamic stability and control derivatives are derived. In the present work, the rotorcraft aerodynamic parameters are computed using radial basis function neural networks (RBFN) in the presence of both state and measurement noise. The effect of presence of outliers in the data is also considered. RBFN is found to give superior results compared to finite difference derivatives for noisy data. (C) 2010 Elsevier Inc. All rights reserved.

Characterisation of cellulose- and lignin-based materials using x-ray scattering methods

Wood is an important material for the construction and pulping industries. Using x-ray diffraction the microfibril angle of Sitka spruce wood was studied in the first part of this thesis. Sitka spruce (Picea sitchensis [Bong.] Carr.) is native to the west coast of North America, but due to its fast growth rate, it has also been imported to Europe. So far, its nanometre scale properties have not been systematically characterised. In this thesis the microfibril angle of Sitka spruce was shown to depend significantly on the origin of the tree in the first annual rings near the pith. Wood can be further processed to separate lignin from cellulose and hemicelluloses. Solid cellulose can act as a reducer for metal ions and it is also a porous support for nanoparticles. By chemically reducing nickel or copper in the solid cellulose support it is possible to get small nanoparticles on the surfaces of the cellulose fibres. Cellulose supported metal nanoparticles can potentially be used as environmentally friendly catalysts in organic chemistry reactions. In this thesis the size of the nickel and copper containing nanoparticles were studied using anomalous small-angle x-ray scattering and wide-angle x-ray scattering. The anomalous small-angle x-ray scattering experiments showed that the crystallite size of the copper oxide nanoparticles was the same as the size of the nanoparticles, so the nanoparticles were single crystals. The nickel containing nanoparticles were amorphous, but crystallised upon heating. The size of the nanoparticles was observed to be smaller when the reduction of nickel was done in aqueous ammonium hydrate medium compared to reduction made in aqueous solution. Lignin is typically seen as the side-product of wood industries. Lignin is the second most abundant natural polymer on Earth, and it possesses potential to be a useful material for many purposes in addition to being an energy source for the pulp mills. In this thesis, the morphology of several lignins, which were produced by different separation methods from wood, was studied using small-angle and ultra small-angle x-ray scattering. It was shown that the fractal model previously proposed for the lignin structure does not apply to most of the extracted lignin types. The only lignin to which the fractal model could be applied was kraft lignin. In aqueous solutions the average shape of the low molar mass kraft lignin particles was observed to be elongated and flat. The average shape does not necessarily correspond to the shape of the individual particles because of the polydispersity of the fraction and due to selfassociation of the particles. Lignins, and especially lignosulfonate, have many uses as dispersants, binders and emulsion stabilisers. In this thesis work the selfassociation of low molar mass lignosulfonate macromolecules was observed using small-angle x-ray scattering. By taking into account the polydispersity of the studied lignosulfonate fraction, the shape of the lignosulfonate particles was determined to be flat by fitting an oblate ellipsoidal model to the scattering intensity.

A unified construction of space-time codes with optimal rate-diversity tradeoff

The problem of constructing space-time (ST) block codes over a fixed, desired signal constellation is considered. In this situation, there is a tradeoff between the transmission rate as measured in constellation symbols per channel use and the transmit diversity gain achieved by the code. The transmit diversity is a measure of the rate of polynomial decay of pairwise error probability of the code with increase in the signal-to-noise ratio (SNR). In the setting of a quasi-static channel model, let n(t) denote the number of transmit antennas and T the block interval. For any n(t) <= T, a unified construction of (n(t) x T) ST codes is provided here, for a class of signal constellations that includes the familiar pulse-amplitude (PAM), quadrature-amplitude (QAM), and 2(K)-ary phase-shift-keying (PSK) modulations as special cases. The construction is optimal as measured by the rate-diversity tradeoff and can achieve any given integer point on the rate-diversity tradeoff curve. An estimate of the coding gain realized is given. Other results presented here include i) an extension of the optimal unified construction to the multiple fading block case, ii) a version of the optimal unified construction in which the underlying binary block codes are replaced by trellis codes, iii) the providing of a linear dispersion form for the underlying binary block codes, iv) a Gray-mapped version of the unified construction, and v) a generalization of construction of the S-ary case corresponding to constellations of size S-K. Items ii) and iii) are aimed at simplifying the decoding of this class of ST codes.

Dense granular flow down an inclined plane A comparison between the hard particle model and soft particle simulations

The granular flow down an inclined plane is simulated using the discrete element (DE) technique to examine the extent to which the dynamics of an unconfined dense granular flow can be well described by a hard particle model First, we examine the average coordination number for the particles in the flow down an inclined plane using the DE technique using the linear contact model with and without friction, and the Hertzian contact model with friction The simulations show that the average coordination number decreases below 1 for values of the spring stiffness corresponding to real materials, such as sand and glass, even when the angle of inclination is only 10 larger than the angle of repose Additional measures of correlations in the system, such as the fraction of particles with multibody contact, the force ratio (average ratio of the magnitudes of the largest and the second largest force on a particle), and the angle between the two largest forces on the particle, show no evidence of force chains or other correlated motions in the system An analysis of the bond-orientational order parameter indicates that the flow is in the random state, as in event-driven (ED) simulations V Kumaran, J Fluid Mech 632, 107 (2009), J Fluid Mech 632, 145 (2009)] The results of the two simulation techniques for the Bagnold coefficients (ratio of stress and square of the strain rate) and the granular temperature (mean square of the fluctuating velocity) are compared with the theory V Kumaran, J Fluid Mech 632, 107 (2009), J Fluid Mech 632, 145 (2009)] and are found to be in quantitative agreement In addition, we also conduct a comparison of the collision frequency and the distribution of the precollisional relative velocities of particles in contact The strong correlation effects exhibited by these two quantities in event-driven simulations V Kumaran, J Fluid Mech 632, 145 (2009)] are also found in the DE simulations (C) 2010 American Institute of Physics doi 10 1063/1 3504660]

Characterization of Clean and Fouled Rail Track Ballast Subsurface Using Seismic Surface Survey Method: Model and Field Studies

The efficiency of track foundation material gradually decreases due to insufficient lateral confinement, ballast fouling, and loss of shear strength of the subsurface soil under cyclic loading. This paper presents characterization of rail track subsurface to identify ballast fouling and subsurface layers shear wave velocity using seismic survey. Seismic surface wave method of multi-channel analysis of surface wave (MASW) has been carried out in the model track and field track for finding out shear wave velocity of the clean and fouled ballast and track subsurface. The shear wave velocity (SWV) of fouled ballast increases with increase in fouling percentage, and reaches a maximum value and then decreases. This character is similar to typical compaction curve of soil, which is used to define optimum and critical fouling percentage (OFP and CFP). Critical fouling percentage of 15 % is noticed for Coal fouled ballast and 25 % is noticed for clayey sand fouled ballast. Coal fouled ballast reaches the OFP and CFP before clayey sand fouled ballast. Fouling of ballast reduces voids in ballast and there by decreases the drainage. Combined plot of permeability and SWV with percentage of fouling shows that after critical fouling point drainage condition of fouled ballast goes below acceptable limit. Shear wave velocities are measured in the selected location in the Wollongong field track by carrying out similar seismic survey. In-situ samples were collected and degrees of fouling were measured. Field SWV values are more than that of the model track SWV values for the same degree of fouling, which might be due to sleeper's confinement. This article also highlights the ballast gradation widely followed in different countries and presents the comparison of Indian ballast gradation with international gradation standards. Indian ballast contains a coarser particle size when compared to other countries. The upper limit of Indian gradation curve matches with lower limit of ballast gradation curves of America and Australia. The ballast gradation followed by Indian railways is poorly graded and more favorable for the drainage conditions. Indian ballast engineering needs extensive research to improve presents track conditions.

Estimation of Series Capacitance of a Transformer Winding Based on Frequency-Response Data: An Indirect Measurement Approach

A novel procedure to determine the series capacitance of a transformer winding, based on frequency-response measurements, is reported. It is based on converting the measured driving-point impedance magnitude response into a rational function and thereafter exploiting the ratio of a specific coefficient in the numerator and denominator polynomial, which leads to the direct estimation of series capacitance. The theoretical formulations are derived for a mutually coupled ladder-network model, followed by sample calculations. The results obtained are accurate and its feasibility is demonstrated by experiments on model-coil and on actual, single, isolated transformer windings (layered, continuous disc, and interleaved disc). The authors believe that the proposed method is the closest one can get to indirectly measuring series capacitance.

A mixture model approach for formant tracking and the robustness of student's-t distribution

We address the problem of robust formant tracking in continuous speech in the presence of additive noise. We propose a new approach based on mixture modeling of the formant contours. Our approach consists of two main steps: (i) Computation of a pyknogram based on multiband amplitude-modulation/frequency-modulation (AM/FM) decomposition of the input speech; and (ii) Statistical modeling of the pyknogram using mixture models. We experiment with both Gaussian mixture model (GMM) and Student's-t mixture model (tMM) and show that the latter is robust with respect to handling outliers in the pyknogram data, parameter selection, accuracy, and smoothness of the estimated formant contours. Experimental results on simulated data as well as noisy speech data show that the proposed tMM-based approach is also robust to additive noise. We present performance comparisons with a recently developed adaptive filterbank technique proposed in the literature and the classical Burg's spectral estimator technique, which show that the proposed technique is more robust to noise.

Glacial mass balance changes in the Karakoram and Himalaya based on CMIP5 multi-model climate projections

The impact of future climate change on the glaciers in the Karakoram and Himalaya (KH) is investigated using CMIP5 multi-model temperature and precipitation projections, and a relationship between glacial accumulation-area ratio and mass balance developed for the region based on the last 30 to 40 years of observational data. We estimate that the current glacial mass balance (year 2000) for the entire KH region is -6.6 +/- 1 Gta(-1), which decreases about sixfold to -35 +/- 2 Gta(-1) by the 2080s under the high emission scenario of RCP8.5. However, under the low emission scenario of RCP2.6 the glacial mass loss only doubles to -12 +/- 2 Gta(-1) by the 2080s. We also find that 10.6 and 27 % of the glaciers could face `eventual disappearance' by the end of the century under RCP2.6 and RCP8.5 respectively, underscoring the threat to water resources under high emission scenarios.

Residue specific contributions to stability and activity inferred from saturation mutagenesis and deep sequencing

Multiple methods currently exist for rapid construction and screening of single-site saturation mutagenesis (SSM) libraries in which every codon or nucleotide in a DNA fragment is individually randomized. Nucleotide sequences of each library member before and after screening or selection can be obtained through deep sequencing. The relative enrichment of each mutant at each position provides information on its contribution to protein activity or ligand-binding under the conditions of the screen. Such saturation scans have been applied to diverse proteins to delineate hot-spot residues, stability determinants, and for comprehensive fitness estimates. The data have been used to design proteins with enhanced stability, activity and altered specificity relative to wild-type, to test computational predictions of binding affinity, and for protein model discrimination. Future improvements in deep sequencing read lengths and accuracy should allow comprehensive studies of epistatic effects, of combinational variation at multiple sites, and identification of spatially proximate residues.

A constitutive model for transversely isotropic foams, and its application to the indentation of balsa wood

An elastic-plastic constitutive model for transversely isotropic compressible solids (foams) has been developed. A quadratic yield surface with four parameters and one hardening function is proposed. Associated plastic flow is assumed and the yield surface evolves in a self-similar manner calibrated by the uniaxial compressive (or tensile) response of the cellular solid in the axial direction. All material constants in the model (elastic and plastic) can be determined from a combination of a total of four uniaxial and shear tests. The model is used to predict the indentation response of balsa wood to a conical indenter. For the three cone angles considered in this study, very good agreement is found between the experimental measurements and the finite element (FE) predictions of the transversely isotropic cellular solid model. On the other hand, an isotropic foam model is shown to be inadequate to capture the indentation response. © 2005 Elsevier Ltd. All rights reserved.

Intranasal Delivery of Plasma and Platelet Growth Factors Using PRGF-Endoret System Enhances Neurogenesis in a Mouse Model of Alzheimer’s Disease

[EN] Neurodegeneration together with a reduction in neurogenesis are cardinal features of Alzheimer’s disease (AD) induced by a combination of toxic amyloid-β peptide (Aβ) and a loss of trophic factor support. Amelioration of these was assessed with diverse neurotrophins in experimental therapeutic approaches. The aim of this study was to investigate whether intranasal delivery of plasma rich in growth factors (PRGF-Endoret), an autologous pool of morphogens and proteins, could enhance hippocampal neurogenesis and reduce neurodegeneration in an amyloid precursor protein/presenilin-1 (APP/PS1) mouse model. Neurotrophic and neuroprotective actions were firstly evident in primary neuronal cultures, where cell proliferation and survival were augmented by Endoret treatment. Translation of these effects in vivo was assessed in wild type and APP/PS1 mice, where neurogenesis was evaluated using 5-bromodeoxyuridine (BdrU), doublecortin (DCX), and NeuN immunostaining 5 weeks after Endoret administration. The number of BrdU, DCX, and NeuN positive cell was increased after chronic treatment. The number of degenerating neurons, detected with fluoro Jade-B staining was reduced in Endoret-treated APP/PS1 mice at 5 week after intranasal administration. In conclusion, Endoret was able to activate neuronal progenitor cells, enhancing hippocampal neurogenesis, and to reduce Aβ-induced neurodegeneration in a mouse model of AD.

A model of the olfactory bulb and beyond

The olfactory bulb of mammals aids in the discrimination of odors. A mathematical model based on the bulbar anatomy and electrophysiology is described. Simulations of the highly non-linear model produce a 35-60 Hz modulated activity, which is coherent across the bulb. The decision states (for the odor information) in this system can be thought of as stable cycles, rather than as point stable states typical of simpler neuro-computing models. Analysis shows that a group of coupled non-linear oscillators are responsible for the oscillatory activities. The output oscillation pattern of the bulb is determined by the odor input. The model provides a framework in which to understand the transformation between odor input and bulbar output to the olfactory cortex. This model can also be extended to other brain areas such as the hippocampus, thalamus, and neocortex, which show oscillatory neural activities. There is significant correspondence between the model behavior and observed electrophysiology.

It has also been suggested that the olfactory bulb, the first processing center after the sensory cells in the olfactory pathway, plays a role in olfactory adaptation, odor sensitivity enhancement by motivation, and other olfactory psychophysical phenomena. The input from the higher olfactory centers to the inhibitory cells in the bulb are shown to be able to modulate the response, and thus the sensitivity, of the bulb to odor input. It follows that the bulb can decrease its sensitivity to a pre-existing and detected odor (adaptation) while remaining sensitive to new odors, or can increase its sensitivity to discover interesting new odors. Other olfactory psychophysical phenomena such as cross-adaptation are also discussed.

Neural and computational representations of decision variables

These studies explore how, where, and when representations of variables critical to decision-making are represented in the brain. In order to produce a decision, humans must first determine the relevant stimuli, actions, and possible outcomes before applying an algorithm that will select an action from those available. When choosing amongst alternative stimuli, the framework of value-based decision-making proposes that values are assigned to the stimuli and that these values are then compared in an abstract “value space” in order to produce a decision. Despite much progress, in particular regarding the pinpointing of ventromedial prefrontal cortex (vmPFC) as a region that encodes the value, many basic questions remain. In Chapter 2, I show that distributed BOLD signaling in vmPFC represents the value of stimuli under consideration in a manner that is independent of the type of stimulus it is. Thus the open question of whether value is represented in abstraction, a key tenet of value-based decision-making, is confirmed. However, I also show that stimulus-dependent value representations are also present in the brain during decision-making and suggest a potential neural pathway for stimulus-to-value transformations that integrates these two results.

More broadly speaking, there is both neural and behavioral evidence that two distinct control systems are at work during action selection. These two systems compose the “goal-directed system”, which selects actions based on an internal model of the environment, and the “habitual” system, which generates responses based on antecedent stimuli only. Computational characterizations of these two systems imply that they have different informational requirements in terms of input stimuli, actions, and possible outcomes. Associative learning theory predicts that the habitual system should utilize stimulus and action information only, while goal-directed behavior requires that outcomes as well as stimuli and actions be processed. In Chapter 3, I test whether areas of the brain hypothesized to be involved in habitual versus goal-directed control represent the corresponding theorized variables.

The question of whether one or both of these neural systems drives Pavlovian conditioning is less well-studied. Chapter 4 describes an experiment in which subjects were scanned while engaged in a Pavlovian task with a simple non-trivial structure. After comparing a variety of model-based and model-free learning algorithms (thought to underpin goal-directed and habitual decision-making, respectively), it was found that subjects’ reaction times were better explained by a model-based system. In addition, neural signaling of precision, a variable based on a representation of a world model, was found in the amygdala. These data indicate that the influence of model-based representations of the environment can extend even to the most basic learning processes.

Knowledge of the state of hidden variables in an environment is required for optimal inference regarding the abstract decision structure of a given environment and therefore can be crucial to decision-making in a wide range of situations. Inferring the state of an abstract variable requires the generation and manipulation of an internal representation of beliefs over the values of the hidden variable. In Chapter 5, I describe behavioral and neural results regarding the learning strategies employed by human subjects in a hierarchical state-estimation task. In particular, a comprehensive model fit and comparison process pointed to the use of "belief thresholding". This implies that subjects tended to eliminate low-probability hypotheses regarding the state of the environment from their internal model and ceased to update the corresponding variables. Thus, in concert with incremental Bayesian learning, humans explicitly manipulate their internal model of the generative process during hierarchical inference consistent with a serial hypothesis testing strategy.