wanyu/IteraTeR_full_sent huggingface dataset:
Original: The microtubule cortical array is a structure consisting of highly aligned microtubules , observed in all growing plant cells, which plays a crucial role in the characteristic plant cell growth by uniaxial expansion along the axis perpendicular to the microtubules.
Revised: The cortical array is a structure consisting of highly aligned microtubules , observed in all growing plant cells, which plays a crucial role in the characteristic plant cell growth by uniaxial expansion along the axis perpendicular to the microtubules.
Edit intent: clarity
Original: The microtubule cortical array is a structure consisting of highly aligned microtubules , observed in all growing plant cells, which plays a crucial role in the characteristic plant cell growth by uniaxial expansion along the axis perpendicular to the microtubules.
Revised: The microtubule cortical array is a structure consisting of highly aligned microtubules which plays a crucial role in the characteristic plant cell growth by uniaxial expansion along the axis perpendicular to the microtubules.
Edit intent: clarity
Original: The microtubule cortical array is a structure consisting of highly aligned microtubules , observed in all growing plant cells, which plays a crucial role in the characteristic plant cell growth by uniaxial expansion along the axis perpendicular to the microtubules. To investigate the orientational ordering of microtubulesin this system, we present both a coarse-grained theoretical model and stochastic particle-based simulations  , and compare the results from these complementary approaches.
Revised: The microtubule cortical array is a structure consisting of highly aligned microtubules , observed in all growing plant cells, which plays a crucial role in the characteristic uniaxial expansion of all growing plant cells. Recent experiments have shown polymerization-driven collisions between the membrane-bound cortical microtubules, suggesting a possible mechanism for their alignment. We present both a coarse-grained theoretical model and stochastic particle-based simulations , and compare the results from these complementary approaches.
Edit intent: meaning-changed
Original:  To investigate the orientational ordering of microtubulesin this system, we present both a coarse-grained theoretical model and stochastic particle-based simulations  , and compare the results from these complementary approaches.
Revised:  To investigate the orientational ordering of microtubulesin this system, we present both a coarse-grained theoretical model and stochastic particle-based simulations of this mechanism , and compare the results from these complementary approaches.
Edit intent: clarity
Original:  Here, we present a simple model that explains the shape and scaling of the distribution of intraday stock price fluctuations (called intraday returns) and verify the model using a large database for several stocks traded on the London Stock Exchange.
Revised:  Here, we present a model that explains the shape and scaling of the distribution of intraday stock price fluctuations (called intraday returns) and verify the model using a large database for several stocks traded on the London Stock Exchange.
Edit intent: clarity
Original:  This enables us to obtain the main result of this article which from the perspective of a utility optimization interpretation of the underlying control problem on a financial market takes the following form. The control  process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Revised:  This enables us to obtain the main result of this article , namely a representation formula for the control process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Edit intent: meaning-changed
Original:  The control  process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Revised:  The control component of its solution. The latter is relevant in the context of securitization of random liabilities arising from exogenous risk, which are optimally hedged by investment in a given financial market with respect to exponential preferences. In a purely stochastic formulation, the control process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Edit intent: meaning-changed
Original:  The control  process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Revised:  The control process of the backward component of the FBSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Edit intent: meaning-changed
Original:  The control  process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Revised:  The control process of the BSDE steers the system into the random liability, and describes its optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Edit intent: coherence
Original:  The control  process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Revised:  The control process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge by investment in a capital market the dynamics of which is described by the forward component.
Edit intent: fluency
Original:  The control  process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Revised:  The control process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in the capital market the dynamics of which is described by the forward component.
Edit intent: fluency
Original:  The control  process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is described by the forward component.
Revised:  The control process of the BSDE steers the system into a random liabilitydepending on a market external uncertainty and this way describes the optimal derivative hedge of the liability by investment in a capital market the dynamics of which is given by the forward component.
Edit intent: clarity
Original:  This delta hedge is described in a key formula in terms of a derivative functional of the solution process and the correlation structure of the internal uncertainty captured by the forward process and the external uncertainty responsible for the market incompleteness  .
Revised:  The representation formula of the main result describes this delta hedge in terms of the derivative of the BSDE's solution process on the one hand, and the correlation structure of the internal uncertainty captured by the forward process and the external uncertainty responsible for the market incompleteness .
Edit intent: meaning-changed
Original:  This delta hedge is described in a key formula in terms of a derivative functional of the solution process and the correlation structure of the internal uncertainty captured by the forward process and the external uncertainty responsible for the market incompleteness  .
Revised:  This delta hedge is described in a key formula in terms of a derivative functional of the solution process and the correlation structure of the internal uncertainty captured by the forward process and the external uncertainty responsible for the market incompleteness on the other hand .
Edit intent: meaning-changed
Original:  The formula largely extends the scope of validity of the results obtained by several authors in the Brownian setting , designed to give a genuinely stochastic representation of the optimal delta hedge in the context of cross hedging insurance derivatives generalizing the derivative hedge in the Black-Scholes model .
Revised:  The formula extends the scope of validity of the results obtained by several authors in the Brownian setting , designed to give a genuinely stochastic representation of the optimal delta hedge in the context of cross hedging insurance derivatives generalizing the derivative hedge in the Black-Scholes model .
Edit intent: clarity
Original:  The formula largely extends the scope of validity of the results obtained by several authors in the Brownian setting , designed to give a genuinely stochastic representation of the optimal delta hedge in the context of cross hedging insurance derivatives generalizing the derivative hedge in the Black-Scholes model .
Revised:  The formula largely extends the scope of validity of the results obtained by several authors in the Brownian setting . It is designed to extend a genuinely stochastic representation of the optimal delta hedge in the context of cross hedging insurance derivatives generalizing the derivative hedge in the Black-Scholes model .
Edit intent: coherence
Original:  The formula largely extends the scope of validity of the results obtained by several authors in the Brownian setting , designed to give a genuinely stochastic representation of the optimal delta hedge in the context of cross hedging insurance derivatives generalizing the derivative hedge in the Black-Scholes model .
Revised:  The formula largely extends the scope of validity of the results obtained by several authors in the Brownian setting , designed to give a genuinely stochastic representation of the optimal replication in cross hedging insurance derivatives generalizing the derivative hedge in the Black-Scholes model .
Edit intent: clarity
Original:  The formula largely extends the scope of validity of the results obtained by several authors in the Brownian setting , designed to give a genuinely stochastic representation of the optimal delta hedge in the context of cross hedging insurance derivatives generalizing the derivative hedge in the Black-Scholes model .
Revised:  The formula largely extends the scope of validity of the results obtained by several authors in the Brownian setting , designed to give a genuinely stochastic representation of the optimal delta hedge in the context of cross hedging insurance derivatives from the classical Black-Scholes model .
Edit intent: clarity
Original:  The formula largely extends the scope of validity of the results obtained by several authors in the Brownian setting , designed to give a genuinely stochastic representation of the optimal delta hedge in the context of cross hedging insurance derivatives generalizing the derivative hedge in the Black-Scholes model . Of course , Malliavin's calculus needed in the Brownian setting is not available in the general local martingale framework .
Revised:  The formula largely extends the scope of validity of the results obtained by several authors in the Brownian setting , designed to give a genuinely stochastic representation of the optimal delta hedge in the context of cross hedging insurance derivatives generalizing the derivative hedge in the Black-Scholes model to incomplete markets on general stochastic bases. In this setting , Malliavin's calculus needed in the Brownian setting is not available in the general local martingale framework .
Edit intent: meaning-changed
Original:  In a purely stochastic formulation, the control process of the backward component of the FBSDE steers the system into the random liability , and describes its optimal derivative hedge by investment in the capital market  the dynamics of which is given by the forward component .
Revised:  In a purely stochastic formulation, the control process of the backward component of the FBSDE steers the system into the random liability and describes its optimal derivative hedge by investment in the capital market the dynamics of which is given by the forward component .
Edit intent: fluency
Original:  In a purely stochastic formulation, the control process of the backward component of the FBSDE steers the system into the random liability , and describes its optimal derivative hedge by investment in the capital market  the dynamics of which is given by the forward component .
Revised:  In a purely stochastic formulation, the control process of the backward component of the FBSDE steers the system into the random liability , and describes its optimal derivative hedge by investment in the capital market , the dynamics of which is given by the forward component .
Edit intent: fluency
Original:  In a purely stochastic formulation, the control process of the backward component of the FBSDE steers the system into the random liability , and describes its optimal derivative hedge by investment in the capital market  the dynamics of which is given by the forward component . The representation formula of the main result describes this delta hedge in terms of the derivative of the BSDE's solution process on the one hand, and the correlation structure of the internal uncertainty captured by the forward process and the external uncertainty responsible for the market incompleteness on the other hand. The formula extends the scope of validity of the results obtained by several authors in the Brownian setting. It is designed to extend a genuinely stochastic representation of the optimal replication in cross hedging insurance derivatives from the classical Black-Scholes model to incomplete markets on general stochastic bases. In this setting, Malliavin's calculus which is required in the Brownian framework is replaced by new tools based on techniques related to a calculus of quadratic covariations of basis martingales .
Revised:  In a purely stochastic formulation, the control process of the backward component of the FBSDE steers the system into the random liability , and describes its optimal derivative hedge by investment in the capital market the dynamics of which is given by the forward component .
Edit intent: meaning-changed
Original: We present  a method for constructing new families of solvable one-dimensional diffusions with linear drift and nonlinear diffusion coefficient functions, whose transition densities are obtainable in analytically closed-form.
Revised: We present new extensions to a method for constructing new families of solvable one-dimensional diffusions with linear drift and nonlinear diffusion coefficient functions, whose transition densities are obtainable in analytically closed-form.
Edit intent: meaning-changed
Original: We present  a method for constructing new families of solvable one-dimensional diffusions with linear drift and nonlinear diffusion coefficient functions, whose transition densities are obtainable in analytically closed-form.
Revised: We present a method for constructing several families of solvable one-dimensional diffusions with linear drift and nonlinear diffusion coefficient functions, whose transition densities are obtainable in analytically closed-form.
Edit intent: meaning-changed
Original:  Our approach is based on  the so-called diffusion canonical transformation method that allows us to uncover new multiparameter diffusions that are mapped onto various simpler underlying diffusions.
Revised:  Our approach is based on the so-called diffusion canonical transformation method that combines smooth monotonic mappings and measure changes via Doob-h transforms. This gives rise to new multi-parameter solvable diffusions that are mapped onto various simpler underlying diffusions.
Edit intent: meaning-changed
Original:  Our approach is based on  the so-called diffusion canonical transformation method that allows us to uncover new multiparameter diffusions that are mapped onto various simpler underlying diffusions. We give a simple rigorous boundary classification and characterization of the newly constructed processes with respect to the martingale property. Specifically, we construct, analyse and classify three new families of nonlinear diffusion models with affine drift that arise from the squared Bessel process (the Bessel family), the CIR process (the confluent hypergeometric family), and the Ornstein-Uhlenbeck diffusion (the OU family) .
Revised:  Our approach is based on the so-called diffusion canonical transformation method that allows us to uncover new multiparameter diffusions that are generally divided into two main classes; the first is specified by having affine (linear) drift with various resulting nonlinear diffusion coefficient functions, while the second class allows for several specifications of a (generally nonlinear) diffusion coefficient with resulting nonlinear drift function. The theory is applicable to diffusions with either singular and/or non-singular endpoints. As part of the results in this paper, we also present a complete boundary classification and martingale characterization of the newly developed diffusion families .
Edit intent: meaning-changed
Original:  Here  we introduce a general formalism that allows to easily write down mean-field equations for any diffusive dynamics on weighted networks , and to recognize the concept of an annealed weighted network , in which such equations become exact.
Revised:  Here , we introduce a general formalism that allows to easily write down mean-field equations for any diffusive dynamics on weighted networks , and to recognize the concept of an annealed weighted network , in which such equations become exact.
Edit intent: fluency
Original:  Here  we introduce a general formalism that allows to easily write down mean-field equations for any diffusive dynamics on weighted networks , and to recognize the concept of an annealed weighted network , in which such equations become exact.
Revised:  Here we introduce a general formalism that allows to easily write down mean-field equations for any diffusive dynamics on weighted networks . We also propose the concept of an annealed weighted network , in which such equations become exact.
Edit intent: coherence
Original:  Here  we introduce a general formalism that allows to easily write down mean-field equations for any diffusive dynamics on weighted networks , and to recognize the concept of an annealed weighted network , in which such equations become exact.
Revised:  Here we introduce a general formalism that allows to easily write down mean-field equations for any diffusive dynamics on weighted networks , and to recognize the concept of annealed weighted networks , in which such equations become exact.
Edit intent: fluency
Original: We use a model of proportionate growth to describe the dynamics of international trade flows. We provide an explanation to the fact that the extensive margin of trade account for a large fraction of the greater exports of large economies, as well as for a number of stylized facts described by the literature on trade networks such as the power-law distribution of connectivity and the fat tails displayed by the distribution of  the growth rates of trade flows.
Revised: We develop a simple theoretical framework for the evolution of weighted network that is consistent with a number of stylized features of real-world data. In our framework, the fat tails displayed by the distribution of the growth rates of trade flows.
Edit intent: clarity
Original:  We provide an explanation to the fact that the extensive margin of trade account for a large fraction of the greater exports of large economies, as well as for a number of stylized facts described by the literature on trade networks such as the power-law distribution of connectivity and the fat tails displayed by the distribution of  the growth rates of trade flows.
Revised:  We provide an explanation to the fact that the extensive margin of trade account for a large fraction of the greater exports of large economies, as well as for a number of stylized facts described by the literature on trade networks such as the power-law distribution of connectivity and the Barabasi-Albert model of network evolution is extended as recently proposed by Stanley and colleagues in their work on complex system dynamics. Our model is verify by means of simulations and real world trade data. We show that the model correctly predicts the intensity and growth distribution of links, the size-variance relationships of the growth of the growth rates of trade flows.
Edit intent: meaning-changed
Original:  We provide an explanation to the fact that the extensive margin of trade account for a large fraction of the greater exports of large economies, as well as for a number of stylized facts described by the literature on trade networks such as the power-law distribution of connectivity and the fat tails displayed by the distribution of  the growth rates of trade flows.
Revised:  We provide an explanation to the fact that the extensive margin of trade account for a large fraction of the greater exports of large economies, as well as for a number of stylized facts described by the literature on trade networks such as the power-law distribution of connectivity and the fat tails displayed by the distribution of link values, the growth rates of trade flows.
Edit intent: meaning-changed
Original:  We provide an explanation to the fact that the extensive margin of trade account for a large fraction of the greater exports of large economies, as well as for a number of stylized facts described by the literature on trade networks such as the power-law distribution of connectivity and the fat tails displayed by the distribution of  the growth rates of trade flows. Hence, such a simple setup is able to capture the dynamics of very different economic variables, from firm size (as shown in the URLanization literature) to international trade flows (as documented here). Furthermore, we provide an additional element to the discussion on the relative ability of different international trade models to adequately match empirical regularities .
Revised:  We provide an explanation to the fact that the extensive margin of trade account for a large fraction of the greater exports of large economies, as well as for a number of stylized facts described by the literature on trade networks such as the power-law distribution of connectivity and the fat tails displayed by the distribution of the relationship between the degree and strength of nodes, as well as the scale-free structure of the network .
Edit intent: meaning-changed