wanyu/IteraTeR_full_sent huggingface dataset:
Original:  The model differs in many respects from previous works on load balancing , in particular by incorporating the call admission process, through random access ; by allowing the differentiation of users based on their priorities ;
Revised:  The model differs in many respects from previous works on load balancing , in particular by incorporating the call admission process, through random access . In specific, the proposed model implements the Physical Random Access Channel used in 3GPP network standards. Furthermore, the proposed model allows the differentiation of users based on their priorities ;
Edit intent: meaning-changed
Original:  The quantitative results illustrate that, for example, as more shared channels are used for load balancing an increase in overall system channel utilization is observed. However, more interestingly, the improvement in blocking probability per shared channel for load balanced users  is maximized at an intermediate number of shared channels  as opposed to the maximum number of these shared resources.
Revised:  The quantitative results illustrate that, for example, cellular network operators can control the manner in which traffic is offloaded between neighboring cells by simply manipulating the length of the random access phase. Our analysis allow to quantitatively determine the blocking probability individual users will experience given a specific length of random access phase. Furthermore, we observe that the improvement in blocking probability per shared channel for load balanced users is maximized at an intermediate number of shared channels as opposed to the maximum number of these shared resources.
Edit intent: meaning-changed
Original:  However, more interestingly, the improvement in blocking probability per shared channel for load balanced users  is maximized at an intermediate number of shared channels  as opposed to the maximum number of these shared resources.
Revised:  However, more interestingly, the improvement in blocking probability per shared channel for load balanced users using DR_{K is maximized at an intermediate number of shared channels as opposed to the maximum number of these shared resources.
Edit intent: meaning-changed
Original:  This occurs because a balance is achieved between the number of users requesting connections and those that are already admitted to the network  .
Revised:  This occurs because a balance is achieved between the number of users requesting connections and those that are already admitted to the network . We also present an extension of our analytical model to a multi-cell network (by means of an approximation) and an application of the proposed load balancing scheme in the context of opportunistic spectrum access .
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Original:  In order to model defaults in a bank's loan/credit business portfolios, we represent its net worth by appropriate Levy processes, and solve explicitly for the double exponential jump diffusion process . In particular, for the spectrally negative case, we generalize the formulation using the scale function, and obtain explicitly the optimal solutions for the exponential jump diffusion process.
Revised:  In order to model defaults in a bank's loan/credit business portfolios, we represent its net worth by appropriate Levy processes, and solve explicitly for the double exponential jump diffusion process and for a general spectrally negative Levy process.
Edit intent: meaning-changed
Original: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% good%DIFDELCMD < {\guillemotright} %%% and the%DIFDELCMD < {\guillemotleft}%%% bad%DIFDELCMD < {\guillemotright} %%%  companies in Russian corporate sector based on their financial statements data (Russian  Standards).
Revised: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% %DIFDELCMD < {\guillemotright} %%% and the%DIFDELCMD < {\guillemotleft}%%% bad%DIFDELCMD < {\guillemotright} %%% companies in Russian corporate sector based on their financial statements data (Russian Standards).
Edit intent: fluency
Original: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% good%DIFDELCMD < {\guillemotright} %%% and the%DIFDELCMD < {\guillemotleft}%%% bad%DIFDELCMD < {\guillemotright} %%%  companies in Russian corporate sector based on their financial statements data (Russian  Standards).
Revised: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% good%DIFDELCMD < {\guillemotright} %%% %DIFDELCMD < {\guillemotleft}%%% bad%DIFDELCMD < {\guillemotright} %%% companies in Russian corporate sector based on their financial statements data (Russian Standards).
Edit intent: coherence
Original: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% good%DIFDELCMD < {\guillemotright} %%% and the%DIFDELCMD < {\guillemotleft}%%% bad%DIFDELCMD < {\guillemotright} %%%  companies in Russian corporate sector based on their financial statements data (Russian  Standards).
Revised: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% good%DIFDELCMD < {\guillemotright} %%% and the%DIFDELCMD < {\guillemotleft}%%% %DIFDELCMD < {\guillemotright} %%% companies in Russian corporate sector based on their financial statements data (Russian Standards).
Edit intent: clarity
Original: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% good%DIFDELCMD < {\guillemotright} %%% and the%DIFDELCMD < {\guillemotleft}%%% bad%DIFDELCMD < {\guillemotright} %%%  companies in Russian corporate sector based on their financial statements data (Russian  Standards).
Revised: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% good%DIFDELCMD < {\guillemotright} %%% and the%DIFDELCMD < {\guillemotleft}%%% bad%DIFDELCMD < {\guillemotright} %%% 'good' and the 'bad' companies in Russian corporate sector based on their financial statements data (Russian Standards).
Edit intent: meaning-changed
Original: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% good%DIFDELCMD < {\guillemotright} %%% and the%DIFDELCMD < {\guillemotleft}%%% bad%DIFDELCMD < {\guillemotright} %%%  companies in Russian corporate sector based on their financial statements data (Russian  Standards).
Revised: The model is aimed to discriminate the %DIFDELCMD < {\guillemotleft}%%% good%DIFDELCMD < {\guillemotright} %%% and the%DIFDELCMD < {\guillemotleft}%%% bad%DIFDELCMD < {\guillemotright} %%% companies in Russian corporate sector based on their financial statements data (Russian Accounting Standards).
Edit intent: fluency
Original:  Furthermore, we define the \alpha re-scaled FTSE100 daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Revised:  Furthermore, we define the alpha re-scaled FTSE100 daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Edit intent: fluency
Original:  Furthermore, we define the \alpha re-scaled FTSE100 daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Revised:  Furthermore, we define the \alpha re-scaled FTSE100 daily index positive returns r(t) ^alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Edit intent: fluency
Original:  Furthermore, we define the \alpha re-scaled FTSE100 daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Revised:  Furthermore, we define the \alpha re-scaled FTSE100 daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Edit intent: fluency
Original:  Furthermore, we define the \alpha re-scaled FTSE100 daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Revised:  Furthermore, we define the \alpha re-scaled FTSE100 daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the alpha positive fluctuations and \alpha negative fluctuations.
Edit intent: fluency
Original:  Furthermore, we define the \alpha re-scaled FTSE100 daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Revised:  Furthermore, we define the \alpha re-scaled FTSE100 daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the \alpha positive fluctuations and alpha negative fluctuations.
Edit intent: fluency
Original:  We use the Kolmogorov-Smirnov statistical test, as a method, to find the values of \alpha that optimize the data collapse of the histogram of the \alpha fluctuations with the Bramwell-Holdsworth-Pinton (BHP) probability density function.
Revised:  We use the Kolmogorov-Smirnov statistical test, as a method, to find the values of alpha that optimize the data collapse of the histogram of the \alpha fluctuations with the Bramwell-Holdsworth-Pinton (BHP) probability density function.
Edit intent: fluency
Original:  We use the Kolmogorov-Smirnov statistical test, as a method, to find the values of \alpha that optimize the data collapse of the histogram of the \alpha fluctuations with the Bramwell-Holdsworth-Pinton (BHP) probability density function.
Revised:  We use the Kolmogorov-Smirnov statistical test, as a method, to find the values of \alpha that optimize the data collapse of the histogram of the alpha fluctuations with the Bramwell-Holdsworth-Pinton (BHP) probability density function.
Edit intent: fluency
Original:  Furthermore, we define the \alpha re-scaled AEX daily index positive returns r(t) ^{\alpha and negative returns (-r(t)) ^{\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Revised:  Furthermore, we define the \alpha re-scaled AEX daily index positive returns r(t) ^\alpha and negative returns (-r(t)) ^{\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Edit intent: fluency
Original:  Furthermore, we define the \alpha re-scaled AEX daily index positive returns r(t) ^{\alpha and negative returns (-r(t)) ^{\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Revised:  Furthermore, we define the \alpha re-scaled AEX daily index positive returns r(t) ^{\alpha and negative returns (-r(t)) ^\alpha that we call, after normalization, the \alpha positive fluctuations and \alpha negative fluctuations.
Edit intent: fluency
Original:  The first scheme is based on a new bipolar random telegraph wave scheme and the second one makes use of the recent noise-based logic which is conjectured to be the brain's method of logic operations [Physics Letters A 373 (2009) 2338-2342 , arXiv:0902.2033 ].
Revised:  The first scheme is based on a new bipolar random telegraph wave scheme and the second one makes use of the recent noise-based logic which is conjectured to be the brain's method of logic operations [Physics Letters A 373 (2009) 2338-2342 ].
Edit intent: coherence
Original:  For binary-valued logic operations, the two simple Boolean schemes presented in this paper use zero (no noise) for the logic Low (L) state. In the random telegraph wave-based scheme, for multi-valued logic operations, additive superpositions of logic states must be avoided, while multiplicative superpositions utilizing hyperspace base vectors can still be utilized. These modifications, while keeping the information richness of multi-valued (noise-based) logic, result in a significant speedup of logic operations for the same signal bandwidth. The logic hyperspace of the first scheme results random telegraph waves with the same statistical properties as the original noise bits. The hyperspace of the second scheme is the same as in the already published version .
Revised:  Error propagation and error removal issues are also addressed .
Edit intent: coherence
Original: We study the valuation partial differential equation for European contingent claims in a general framework of stochastic volatility models . The standard Feynman-Kac theorem cannot be directly applied because the diffusion coefficients may  degenerate on the boundaries of the state space and grow faster than linearly .
Revised: We study the valuation partial differential equation for European contingent claims in a general framework of stochastic volatility models where the standard Feynman-Kac theorem cannot be directly applied because the diffusion coefficients may degenerate on the boundaries of the state space and grow faster than linearly .
Edit intent: clarity
Original:  Sharp results on the existence and uniqueness of classical solutions to the valuation equation are obtained using a combination of probabilistic and analytical techniques. The role of boundary conditions is also discussed .
Revised:  Sharp results on the existence and uniqueness of classical solutions to the valuation equation . It is shown that the value function is the smallest nonnegative classical solution to the valuation equation. Moreover, when the payoff is of strictly sublinear growth, the uniqueness holds among the same class of functions; when the payoff is of linear growth, the uniqueness holds if and only if the asset-price process is a martingale .
Edit intent: meaning-changed
Original: We study the valuation partial differential equation for European contingent claims in a general framework of stochastic volatility models where the standard Feynman-Kac theorem cannot be directly applied because the diffusion coefficients may grow faster than linearly and degenerate on the boundaries of the state space.
Revised: We analyze the valuation partial differential equation for European contingent claims in a general framework of stochastic volatility models where the standard Feynman-Kac theorem cannot be directly applied because the diffusion coefficients may grow faster than linearly and degenerate on the boundaries of the state space.
Edit intent: clarity
Original:  We allow for various types of model behavior ; for example, the volatility process in our model can potentially reach zero and either stay there or instantaneously reflect, and asset-price processes may be strict local martingales under a given risk-neutral measure .
Revised:  We allow for various types of model behavior : the volatility process in our model can potentially reach zero and either stay there or instantaneously reflect, and asset-price processes may be strict local martingales under a given risk-neutral measure .
Edit intent: coherence
Original:  for example, the volatility process in our model can potentially reach zero and either stay there or instantaneously reflect, and asset-price processes may be strict local martingales under a given risk-neutral measure .
Revised:  for example, the volatility process in our model can potentially reach zero and either stay there or instantaneously reflect, and asset-price process may be strict local martingales under a given risk-neutral measure .
Edit intent: fluency
Original:  It is shown that the value function is the smallest nonnegative classical solution to the valuation equation . Moreover, when the payoff is of strictly sublinear growth, the uniqueness holds among the same class of functions ; when the payoff is of linear growth , the uniqueness holds if and only if the asset-price process is a martingale.
Revised:  It is shown that the value function is the smallest nonnegative classical solution to the valuation equation among the functions with at most linear growth if and only if the asset-price process is a martingale.
Edit intent: clarity
Original: We analyze the valuation partial differential equation for European contingent claims in a general framework of stochastic volatility models where the standard Feynman-Kac theorem cannot be directly applied because the diffusion coefficients may grow faster than linearly and degenerate on the boundaries of the state space.
Revised: We analyze the valuation partial differential equation for European contingent claims in a general framework of stochastic volatility models where the diffusion coefficients may grow faster than linearly and degenerate on the boundaries of the state space.
Edit intent: coherence
Original:  We allow for various types of model behavior: the volatility process in our model can potentially reach zero and either stay there or instantaneously reflect, and  asset-price process may be  strict local martingale.
Revised:  We allow for various types of model behavior: the volatility process in our model can potentially reach zero and either stay there or instantaneously reflect, and the asset-price process may be strict local martingale.
Edit intent: fluency
Original:  We allow for various types of model behavior: the volatility process in our model can potentially reach zero and either stay there or instantaneously reflect, and  asset-price process may be  strict local martingale.
Revised:  We allow for various types of model behavior: the volatility process in our model can potentially reach zero and either stay there or instantaneously reflect, and asset-price process may be a strict local martingale.
Edit intent: fluency
Original:  Our main result is a necessary and sufficient condition on the uniqueness of classical solutions to the valuation equation: the value function is the unique nonnegative classical solution to the valuation equation among the functions with at most linear growth if and only if the asset-price is a martingale.
Revised:  Our main result is a necessary and sufficient condition on the uniqueness of classical solutions to the valuation equation: the value function is the unique nonnegative classical solution to the valuation equation among functions with at most linear growth if and only if the asset-price is a martingale.
Edit intent: fluency
Original: We consider the exponential Levy models and we study the conditions under which f-minimal equivalent martingale measure preserves Levy property. Then we give a general formula for optimal strategy in a sense of utility maximization. Finally, we study change-point exponential Levy models, namely we give the conditions for the existence of f-minimal equivalent martingale measure and we obtain a general formula for optimal strategy from point of view of the utility maximization .
Revised: We consider the exponential Levy models with change-point which is a random variable, independent from initial Levy processes. On canonical space with initially enlarged filtration we describe all equivalent martingale measures for change-point exponential Levy models, namely we give the conditions for the existence of f-minimal equivalent martingale measure and we obtain a general formula for optimal strategy from point of view of the utility maximization .
Edit intent: meaning-changed
Original:  Finally, we study change-point exponential Levy models, namely we give the conditions for the existence of f-minimal equivalent martingale measure and we obtain a general formula for optimal strategy from point of view of the utility maximization .
Revised:  Finally, we study change-point model and we give the conditions for the existence of f-minimal equivalent martingale measure and we obtain a general formula for optimal strategy from point of view of the utility maximization .
Edit intent: clarity
Original:  Finally, we study change-point exponential Levy models, namely we give the conditions for the existence of f-minimal equivalent martingale measure and we obtain a general formula for optimal strategy from point of view of the utility maximization .
Revised:  Finally, we study change-point exponential Levy models, namely we give the conditions for the existence of f-minimal equivalent martingale measure . Using the connection between utility maximisation and f-divergence minimisation, we obtain a general formula for optimal strategy from point of view of the utility maximization .
Edit intent: meaning-changed
Original:  Finally, we study change-point exponential Levy models, namely we give the conditions for the existence of f-minimal equivalent martingale measure and we obtain a general formula for optimal strategy from point of view of the utility maximization .
Revised:  Finally, we study change-point exponential Levy models, namely we give the conditions for the existence of f-minimal equivalent martingale measure and we obtain a general formula for optimal strategy in change-point case for initially enlarged filtration and also for progressively enlarged filtration when the utility is exponential .
Edit intent: meaning-changed
Original:  Using the connection between utility maximisation and f-divergence minimisation, we obtain a general formula for optimal strategy in change-point case for initially enlarged filtration and also for progressively enlarged filtration when the utility is exponential .
Revised:  Using the connection between utility maximisation and f-divergence minimisation, we obtain a general formula for optimal strategy in change-point case for initially enlarged filtration and also for progressively enlarged filtration in the case of exponential utility .
Edit intent: clarity
Original: We compute the improved bounds on the copula of a bivariate random vector  when partial information is available, such as the values of the copula on the subset of [0,1]^2, or the value of a functional of the copula, monotone with respect to the concordance order.
Revised: Improved bounds on the copula of a bivariate random vector when partial information is available, such as the values of the copula on the subset of [0,1]^2, or the value of a functional of the copula, monotone with respect to the concordance order.
Edit intent: clarity
Original: We compute the improved bounds on the copula of a bivariate random vector  when partial information is available, such as the values of the copula on the subset of [0,1]^2, or the value of a functional of the copula, monotone with respect to the concordance order.
Revised: We compute the improved bounds on the copula of a bivariate random vector are computed when partial information is available, such as the values of the copula on the subset of [0,1]^2, or the value of a functional of the copula, monotone with respect to the concordance order.
Edit intent: meaning-changed
Original: We compute the improved bounds on the copula of a bivariate random vector  when partial information is available, such as the values of the copula on the subset of [0,1]^2, or the value of a functional of the copula, monotone with respect to the concordance order.
Revised: We compute the improved bounds on the copula of a bivariate random vector when partial information is available, such as the values of the copula on a given subset of [0,1]^2, or the value of a functional of the copula, monotone with respect to the concordance order.
Edit intent: clarity
Original:  Using the NOSC model (Nishinari et. al. PRL, {\bf 95}, 118101 (2005)), which captures the Brownian ratchet mechanism of individual KIF1A along with its biochemical cycle, we systematically derive an analytical expression for the dwell time distribution.  in between two consecutive steps each of which could be forward (+) or backward (-).
Revised:  Using the NOSC model (Nishinari et. al. PRL, {\bf 95}, 118101 (2005)), which captures the Brownian ratchet mechanism of individual KIF1A along with its biochemical cycle, we systematically derive an analytical expression for the dwell time distribution. More detailed information is contained in the probability densities of the "conditional dwell times" \tau_{\pm\pm in between two consecutive steps each of which could be forward (+) or backward (-).
Edit intent: meaning-changed