Semantic and Pragmatic Structures in Chomsky’s Binding Theory

The central question that this paper attempts is to describe the conditions under which the anaphor can be determined grammatically or contextually. The issue at hand is whether anaphoric forms can be distinguished from indexical ones within Binding theory. The syntactic representation of bindees are characterized by the use of indices. But what role does the context play in assigning co-referential or non-coreferential properties to anaphors? Furthermore, ellipses are also context-bound. An elliptical structure is indexical, rather than anaphoric. The study analyzes the syntactic structures of Chomsky’s Binding theory within Bolinger’s (1979) semantic model Meaning and Form. It seeks the support of other semanticists in order to fill possible semantic gaps in Binding theory. Keywords: binding theory, elliptical structures, meaning and form model

Time-Varying Skew in VIX Derivatives Pricing

This paper proposes a new reduced-form model for the pricing of VIX derivatives that includes an independent stochastic jump intensity factor and cojumps in the level and variance of VIX, while allowing the mean of VIX variance to be time varying. I fit the model to daily prices of futures and European options from April 2007 through December 2017. The empirical results indicate that the model significantly outperforms all other nested models and improves on benchmark by 21.6% in sample and 31.2% out of sample. The model more accurately portrays the tail behavior of VIX risk-neutral distribution for both short and long maturities, as it better captures the time-varying skew found to be largely independent of the level of the VIX smile. This paper was accepted by Kay Giesecke, finance.

Monte Carlo Valuation of Corporate Bonds Using Price Data

<p>Corporate debt securities play a large part in financial markets and hence accurate modeling of the prices of these securities is integral. Ericsson and Reneby (2005) state that the corporate bond market in the US doubled between 1995 and 2005 and is now larger than the market for US treasuries. Although the theoretical corporate bond pricing literature is vast, very little empirical research to test the effectiveness of these models has been published. Corporate bond pricing models are split into two families of models. The first, are the structural models which endogenise default by modeling it as an event that may eventuate due to the insolvency of the underlying firm. The second family of models is the newer class of reduced-form models that exogenise default by modeling it as some random process (default intensity). The reduced-form models have been formulated largely due to the empirical failures of the structural family to accurately model prices and spreads. However as Ericsson and Reneby (2005) point out, an inadequate estimation approach may explain the poor performance of the structural models. Structural models are, therefore, the focus of this paper. We, however, do estimate a reduced-form model in order to make a comparison between the two types of model. There are no published papers (to my knowledge) in which both types of model are implemented ...</p>

Monte Carlo Valuation of Corporate Bonds Using Price Data

<p>Corporate debt securities play a large part in financial markets and hence accurate modeling of the prices of these securities is integral. Ericsson and Reneby (2005) state that the corporate bond market in the US doubled between 1995 and 2005 and is now larger than the market for US treasuries. Although the theoretical corporate bond pricing literature is vast, very little empirical research to test the effectiveness of these models has been published. Corporate bond pricing models are split into two families of models. The first, are the structural models which endogenise default by modeling it as an event that may eventuate due to the insolvency of the underlying firm. The second family of models is the newer class of reduced-form models that exogenise default by modeling it as some random process (default intensity). The reduced-form models have been formulated largely due to the empirical failures of the structural family to accurately model prices and spreads. However as Ericsson and Reneby (2005) point out, an inadequate estimation approach may explain the poor performance of the structural models. Structural models are, therefore, the focus of this paper. We, however, do estimate a reduced-form model in order to make a comparison between the two types of model. There are no published papers (to my knowledge) in which both types of model are implemented ...</p>

Physics-informed learning of governing equations from scarce data

Harnessing data to discover the underlying governing laws or equations that describe the behavior of complex physical systems can significantly advance our modeling, simulation and understanding of such systems in various science and engineering disciplines. This work introduces a novel approach called physics-informed neural network with sparse regression to discover governing partial differential equations from scarce and noisy data for nonlinear spatiotemporal systems. In particular, this discovery approach seamlessly integrates the strengths of deep neural networks for rich representation learning, physics embedding, automatic differentiation and sparse regression to approximate the solution of system variables, compute essential derivatives, as well as identify the key derivative terms and parameters that form the structure and explicit expression of the equations. The efficacy and robustness of this method are demonstrated, both numerically and experimentally, on discovering a variety of partial differential equation systems with different levels of data scarcity and noise accounting for different initial/boundary conditions. The resulting computational framework shows the potential for closed-form model discovery in practical applications where large and accurate datasets are intractable to capture.

Urban Stormwater Modeling with Local Inertial Approximation Form of Shallow Water Equations: A Comparative Study

This study focused on the performance and limitations of the local inertial approximation form model (LIM) of the shallow water equations (SWEs) when applied in urban flood modeling. A numerical scheme of the LIM equations was created using finite volume method with a first-order spatiotemporal Roe Riemann solver. A simplified urban stormwater model (SUSM) considering surface and underground dual drainage system was constructed based on LIM and the US Environmental Protection Agency Storm Water Management Model. Moreover, a complete urban stormwater model (USM) based on the SWEs with the same solution algorithm was used as the evaluation benchmark. Numerical results of the SUSM and USM in a highly urbanized area under four rainfall return periods were analyzed and compared. The results reveal that the performance of the SUSM is highly consistent with that of the USM but with an improvement in computational efficiency of approximately 140%. In terms of the accuracy of the model, the SUSM slightly underestimates the water depth and velocity and is less accurate when dealing with supercritical flow in urban stormwater flood modeling. Overall, the SUSM can produce comparable results to USM with higher computational efficiency, which provides a simplified and alternative method for urban flood modeling.

Investigation of Tensile Creep Behavior for High-Density Polyethylene (HDPE) via Experiments and Mathematical Model

Temperatures of −25 °C, +5 °C, and +35 °C were selected to study the creep behavior of high-density polyethylene (HDPE). The ultimate tensile strength of HDPE materials was obtained through uniaxial tensile experiments and the time–strain curves were obtained through creep experiments. When the loaded stress levels were lower than 60% of the ultimate strength, the specimens could maintain a longer time in the stable creep stage and were not prone to necking. In contrast, the specimens necked in a short time. Then, the time hardening form model was applied to simulate the time–strain curve and the parameter values were solved. The parameter values changed exponentially with the stresses, thereby expanding and transforming the time hardening model. The expanded model can easily and accurately predict creep behaviors of the initial and stable creep stages as well as the long-term deformations of HDPE materials. This study would provide a theoretical basis and reference value for engineering applications of HDPE.

“Expletives” as Discourse Markers: Semantic and Pragmatic Considerations in “It” and “There”

This paper explores the syntactic and semantic configurations of expletives “it” and “there.” It attempts to show that expletives are not just syntactic fillers; they are semantic markers and are pragmatically bound NPs that can be co-indexed with covert referents. The study follows a theoretical approach and applies Bolinger’s (1977) Meaning and Form model to the syntactic configurations of expletives. The syntactic structures of expletives are based on the syntactic theories of generativist linguists, namely Chomsky (1986). Chomskyan syntactic theories describe the various formal characteristics of expletives without analyzing their semantic and pragmatic implications. This study premises that Bolinger’s theoretical modal can fill these missing gaps and can provide a conclusive yet not final description of these gaps. The study recognizes expletives as discourse-bound markers and authenticates their contextual and sociological significance.

The modelling of nonlinear distance sensor using piecewise newton polynomial with vertex algorithm

The Sharp GP2Y0A02YK0F is categorized as a nonlinear sensor for distance measurement. This sensor is also categorized as a low-cost sensor. The higher resolution, cheap, high accuracy and easy to install are the advantages. The accuracy level of this sensor depends on the type of the measured object materials, requires an additional device unit and further processing is required since the output is non-linear. The distance determination is not easy for this type of sensor since the characteristic of this sensor fulfills non-injective function. The modelling process is one of methods to convert the output voltage of the sensor to a distance unit. The advantages of polynomial modelling are simple form model, moderate in flexibilities of shape, well known and understood properties, and easy to use for computational matters. The obstacle of polynomial-based modelling is the presence of Runge’s phenomenon. The minimization of Runge’s phenomenon can be done with decreasing the model order. The piecewise Newton polynomials with vertex determination method have been succeeded to generate a nonlinear model and minimize the occurrence of Runge’s phenomenon. The low level of MSE by 0.001 and error percentage of 2.38% has been obtained for the generated model. The low MSE level leads to the high accuracy level of the generated model.