wanyu/IteraTeR_full_sent huggingface dataset:
Original:   When tested on a set of protein families from PFAM , we found the RLS algorithm to have superior performance compared to PSICOV, a state-of-the-art method for contact prediction  .
Revised:  When tested on a set of protein families from Pfam , we found the RLS algorithm to have superior performance compared to PSICOV, a state-of-the-art method for contact prediction .
Edit intent: fluency
Original:   When tested on a set of protein families from PFAM , we found the RLS algorithm to have superior performance compared to PSICOV, a state-of-the-art method for contact prediction  .
Revised:  When tested on a set of protein families from PFAM , we found the RLS algorithm to have superior performance compared to PSICOV, a state-of-the-art methods for contact prediction .
Edit intent: fluency
Original:   When tested on a set of protein families from PFAM , we found the RLS algorithm to have superior performance compared to PSICOV, a state-of-the-art method for contact prediction  .
Revised:  When tested on a set of protein families from PFAM , we found the RLS algorithm to have superior performance compared to PSICOV, a state-of-the-art method for contact prediction , while at the same time being faster and conceptually simpler .
Edit intent: meaning-changed
Original:  The application to stochastic volatility models include the small-time and, for certain models, the large-strike asymptotics of the Gyongy-Dupire's local volatility function , the final product being asymptotic formulae that can (i) motivate parameterizations of the local volatility surface and (ii) be used to extrapolate local volatilities in a given model.
Revised:  The application to stochastic volatility models include the small-time and, for certain models, the large-strike asymptotics of the Gyongy-Dupire's local volatility function . The final product are asymptotic formulae that can (i) motivate parameterizations of the local volatility surface and (ii) be used to extrapolate local volatilities in a given model.
Edit intent: fluency
Original:  This result includes various earlier existence results on correlated equilibria, noisy stochastic games, and stochastic games with mixtures of constant transition kernels as special cases.
Revised:  This result includes various earlier existence results on correlated equilibria, noisy stochastic games, stochastic games with finite actions and state-independent transitions, and stochastic games with mixtures of constant transition kernels as special cases.
Edit intent: meaning-changed
Original:  Nous pr\'esentons dans ce rapport les diff\'erents \'el\'ements graphique du mod\`ele  .
Revised:  Nous pr\'esentons dans ce rapport les diff\'erents \'el\'ements graphique du mod\`ele et les am\'eliorations qu'il apporte \`a la mod\'elisation de donn\'ees en XML .
Edit intent: meaning-changed
Original:  We presented a mathematical explanation of phenotypic heterogeneity, stochastic phenotype switching , and bet-hedging within isogenic bacterial populations, and thus provided a theoretical framework for the analysis of experiment dataat the cellular or molecular level .
Revised:  It turns out that our model not only provides a clear description of stochastic phenotype switching , and bet-hedging within isogenic bacterial populations, and thus provided a theoretical framework for the analysis of experiment dataat the cellular or molecular level .
Edit intent: meaning-changed
Original:  We presented a mathematical explanation of phenotypic heterogeneity, stochastic phenotype switching , and bet-hedging within isogenic bacterial populations, and thus provided a theoretical framework for the analysis of experiment dataat the cellular or molecular level .
Revised:  We presented a mathematical explanation of phenotypic heterogeneity, stochastic phenotype switching and bet-hedging within isogenic bacterial populations, and thus provided a theoretical framework for the analysis of experiment dataat the cellular or molecular level .
Edit intent: fluency
Original:  We presented a mathematical explanation of phenotypic heterogeneity, stochastic phenotype switching , and bet-hedging within isogenic bacterial populations, and thus provided a theoretical framework for the analysis of experiment dataat the cellular or molecular level .
Revised:  We presented a mathematical explanation of phenotypic heterogeneity, stochastic phenotype switching , and bet-hedging within isogenic bacterial populations, but also provides a deeper insight into the analysis of experiment dataat the cellular or molecular level .
Edit intent: coherence
Original:  We presented a mathematical explanation of phenotypic heterogeneity, stochastic phenotype switching , and bet-hedging within isogenic bacterial populations, and thus provided a theoretical framework for the analysis of experiment dataat the cellular or molecular level .
Revised:  We presented a mathematical explanation of phenotypic heterogeneity, stochastic phenotype switching , and bet-hedging within isogenic bacterial populations, and thus provided a theoretical framework for the analysis of multidimensional experimental data. Moreover, we use some deep mathematical theories to show that our stochastic model and traditional Markov chain models are essentially consistent and reflect the dynamic behavior of the bacterial system at two different time scales .
Edit intent: meaning-changed
Original:  The equation is general in the sense , that it does not depend on the terminal utility , and provides additional analytical insight for some optimal investment problems with known solution. Furthermore when boundary conditions for the optimal strategy can be established independently, it is considerably simpler than the HJB to solve numerically.
Revised:  The equation is general in the sense , that it does not depend on the terminal utility , and provides additional analytical insight for some optimal investment problems with known solutions. Furthermore, when boundary conditions for the optimal strategy can be established independently, it is considerably simpler than the HJB to solve numerically.
Edit intent: fluency
Original: Assuming that the effect is a mathematical function of the cause in a causal relationship, FunChisq, a chi-square test defined on a non-parametric representation of interactions, infers network topology considering both interaction directionality and nonlinearity.
Revised: With the assumption that the effect is a mathematical function of the cause in a causal relationship, FunChisq, a chi-square test defined on a non-parametric representation of interactions, infers network topology considering both interaction directionality and nonlinearity.
Edit intent: fluency
Original:  Counter-intuitively, patterns in those interactions effectively revealed by FunChisq enlist a network inference principle of applying perturbations to a biological system such that it transits between linear and nonlinear working zones, instead of operates only at a linear working zone.
Revised:  Counter-intuitively, patterns in those interactions effectively revealed by FunChisq enlist an experimental design principle essential to network inference -- perturbations to a biological system such that it transits between linear and nonlinear working zones, instead of operates only at a linear working zone.
Edit intent: clarity
Original:  Counter-intuitively, patterns in those interactions effectively revealed by FunChisq enlist a network inference principle of applying perturbations to a biological system such that it transits between linear and nonlinear working zones, instead of operates only at a linear working zone.
Revised:  Counter-intuitively, patterns in those interactions effectively revealed by FunChisq enlist a network inference principle of applying perturbations to a biological system shall make it transits between linear and nonlinear working zones, instead of operates only at a linear working zone.
Edit intent: clarity
Original:  Counter-intuitively, patterns in those interactions effectively revealed by FunChisq enlist a network inference principle of applying perturbations to a biological system such that it transits between linear and nonlinear working zones, instead of operates only at a linear working zone.
Revised:  Counter-intuitively, patterns in those interactions effectively revealed by FunChisq enlist a network inference principle of applying perturbations to a biological system such that it transits between linear and nonlinear working zones, instead of operating only in a linear working zone.
Edit intent: clarity
Original: We study the probabilistic and statistical properties of the variation based realized third and fourth moments of financial returns . The realized moments of the return are unbiased and relative efficient estimators for the actual moments of the return distribution under a martingale condition in the return process.
Revised: We study the probabilistic and statistical properties of the variation based realized third and fourth moments of financial returns as estimators of the actual moments of the return distribution under a martingale condition in the return process.
Edit intent: coherence
Original:  The realized moments of the return are unbiased and relative efficient estimators for the actual moments of the return distribution under a martingale condition in the return process. For the estimation of a stochastic volatility model , we employ a simple method of estimation and a generalized method of moments estimation based on the realized second and third moments . Conditional thin tale property of the return distribution with given quadratic variation of the return is discussed.
Revised:  The realized moments of the return are unbiased and relative efficient estimators for the actual moments of the return distributions. The moment variations are defined under non-parametric assumptions with quadratic variation method but for the computational tractability, we use a square root stochastic volatility model for the derivations of moment conditions for estimations. Using the S\&P 500 index high frequency data, the realized versions of the moment variations is used for the estimation of a stochastic volatility model , we employ a simple method of estimation and a generalized method of moments estimation based on the realized second and third moments . Conditional thin tale property of the return distribution with given quadratic variation of the return is discussed.
Edit intent: meaning-changed
Original:  For the estimation of a stochastic volatility model , we employ a simple method of estimation and a generalized method of moments estimation based on the realized second and third moments . Conditional thin tale property of the return distribution with given quadratic variation of the return is discussed.
Revised:  For the estimation of a stochastic volatility model . We propose a simple estimation method of a stochastic volatility model using the sample averages of the variations and ARMA estimation. In addition, we compare the results with a generalized method of moments estimation based on the realized second and third moments . Conditional thin tale property of the return distribution with given quadratic variation of the return is discussed.
Edit intent: meaning-changed
Original:  For the estimation of a stochastic volatility model , we employ a simple method of estimation and a generalized method of moments estimation based on the realized second and third moments . Conditional thin tale property of the return distribution with given quadratic variation of the return is discussed. We explain the structure of moments variation swaps and analyze the thin tale property of the portfolio return hedged by the third moment variation swap .
Revised:  For the estimation of a stochastic volatility model , we employ a simple method of estimation and a generalized method of moments estimation based on the successive relation between realized moments and their lagged values .
Edit intent: clarity
Original:  We determine the relationship between some of these structures and we show thatthey are not all actuarially fair .
Revised:  We discuss the importance of actuarial fairness, defined as the expected benefits equalling the contributions for each member, and whether actuarial unfairness can be seen as solidarity between members. We show that, with a finite number of members in the fund, the group self-annuitization scheme is not actuarially fair: some members subsidise the other members. The implication is that the members who are subsidising the others may obtain a higher expected benefit by joining a fund with a more favourable membership profile. Since the pooled annuity funds propose different methods of pooling mortality risk, we investigate the connections between them and find that they are genuinely different for a finite heterogeneous membership profile .
Edit intent: meaning-changed
Original:   We discuss the importance of actuarial fairness, defined as the expected benefits equalling the contributions for each member, and whether actuarial unfairness can be seen as solidarity between members.
Revised:  Collectively, the structures are called pooled annuity funds. Since the pooled annuity funds propose different methods of pooling mortality risk, we investigate the connections between them and find that they are genuinely different for a finite heterogeneous membership profile. We discuss the importance of actuarial fairness, defined as the expected benefits equalling the contributions for each member, and whether actuarial unfairness can be seen as solidarity between members.
Edit intent: meaning-changed
Original:   We discuss the importance of actuarial fairness, defined as the expected benefits equalling the contributions for each member, and whether actuarial unfairness can be seen as solidarity between members.
Revised:  We discuss the importance of actuarial fairness, defined as the expected benefits equalling the contributions for each member, in the context of pooling mortality risk and comment on whether actuarial unfairness can be seen as solidarity between members.
Edit intent: meaning-changed
Original: The fundamental concepts of the Unified Growth Theory , the three stages of growth (Malthusian Regime, Post-Malthusian Regime and Modern Growth Regime) are contradicted by data.
Revised: The fundamental concepts of the Unified Growth Theory is a story based firmly on illusions created by hyperbolic distributions. The three stages of growth (Malthusian Regime, Post-Malthusian Regime and Modern Growth Regime) are contradicted by data.
Edit intent: meaning-changed
Original: The fundamental concepts of the Unified Growth Theory , the three stages of growth (Malthusian Regime, Post-Malthusian Regime and Modern Growth Regime) are contradicted by data. The three stages of growth did not exist and the Industrial Revolution had no effect on the world economic growthand on the growth of human population.
Revised: The fundamental concepts of the Unified Growth Theory , the three stages of growth (Malthusian Regime, Post-Malthusian Regime and Modern Growth Regime) did not exist and the Industrial Revolution had no effect on the world economic growthand on the growth of human population.
Edit intent: coherence
Original:  The three stages of growth did not exist and the Industrial Revolution had no effect on the world economic growthand on the growth of human population.
Revised:  The three stages of growth did not exist . The great divergence and the abrupt take-off never happened. All elaborate explanations revolving around these phantom features represent an interesting story but they are scientifically unacceptable and, therefore, they do not explain the economic growth. The Industrial Revolution had no effect on the world economic growthand on the growth of human population.
Edit intent: meaning-changed
Original:  The three stages of growth did not exist and the Industrial Revolution had no effect on the world economic growthand on the growth of human population. Whatever the Unified Growth Theory is describing it is not describing the economic growth and the growth of human population .
Revised:  The three stages of growth did not exist and the Industrial Revolution had no effect on the economic growth. The data clearly indicate that the economic growth was not as complicated and untidy as incorrectly described by the Unified Growth Theory but elegantly simple .
Edit intent: meaning-changed
Original:  The three stages of growth (Malthusian Regime, Post-Malthusian Regime and Modern Growth Regime) did not exist . The great divergence and the abrupt take-off never happened .
Revised:  The three stages of growth (Malthusian Regime, Post-Malthusian Regime and Modern Growth Regime) did not exist and that Industrial Revolution had no influence on the economic growth and on the growth of human population .
Edit intent: meaning-changed
Original: It is well-known that an \R^n-valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any uniformly distributed random variable U  on the unit interval , where Q_k is the quantile function of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Revised: It is well-known that an \R^n-valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any random variable U on the unit interval , where Q_k is the quantile function of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Edit intent: clarity
Original: It is well-known that an \R^n-valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any uniformly distributed random variable U  on the unit interval , where Q_k is the quantile function of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Revised: It is well-known that an \R^n-valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any uniformly distributed random variable U uniformly distributed on the unit interval , where Q_k is the quantile function of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Edit intent: meaning-changed
Original: It is well-known that an \R^n-valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any uniformly distributed random variable U  on the unit interval , where Q_k is the quantile function of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Revised: It is well-known that an \R^n-valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any uniformly distributed random variable U on the unit interval (0,1), where Q_k is the quantile function of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Edit intent: meaning-changed
Original: It is well-known that an \R^n-valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any uniformly distributed random variable U  on the unit interval , where Q_k is the quantile function of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Revised: It is well-known that an \R^n-valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any uniformly distributed random variable U on the unit interval , where Q_k (\cdot) are the quantile functions of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Edit intent: meaning-changed
Original:  Unlike previous studies, our approach avoids making the assumption that the pricing kernel is atomless, and  we overcome one of the major difficulties encountered when one considers general economic equilibrium models in which the pricing kernel is a yet-to-be-determined unknown random variable  .
Revised:  Unlike previous studies, our approach avoids making the assumption that the pricing kernel is atomless, and consequently, we overcome one of the major difficulties encountered when one considers general economic equilibrium models in which the pricing kernel is a yet-to-be-determined unknown random variable .
Edit intent: coherence
Original:  Unlike previous studies, our approach avoids making the assumption that the pricing kernel is atomless, and  we overcome one of the major difficulties encountered when one considers general economic equilibrium models in which the pricing kernel is a yet-to-be-determined unknown random variable  .
Revised:  Unlike previous studies, our approach avoids making the assumption that the pricing kernel is atomless, and we overcome one of the major difficulties encountered when one considers behavioral economic equilibrium models in which the pricing kernel is a yet-to-be-determined unknown random variable .
Edit intent: meaning-changed
Original:  Unlike previous studies, our approach avoids making the assumption that the pricing kernel is atomless, and  we overcome one of the major difficulties encountered when one considers general economic equilibrium models in which the pricing kernel is a yet-to-be-determined unknown random variable  .
Revised:  Unlike previous studies, our approach avoids making the assumption that the pricing kernel is atomless, and we overcome one of the major difficulties encountered when one considers general economic equilibrium models in which the pricing kernel is a yet-to-be-determined unknown random variable . The method is applicable to many other models such as risk sharing model .
Edit intent: meaning-changed
Original: It is well-known that an %DIFDELCMD < \R%%% ^n -valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any random variable U uniformly distributed on the unit interval (0,1), where Q_k(\cdot) are the quantile functions of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Revised: It is well-known that an %DIFDELCMD < \R%%% \mathbb{R -valued random vector (X_1, X_2, \cdots, X_n) is comonotonic if and only if (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) coincide in distribution, for any random variable U uniformly distributed on the unit interval (0,1), where Q_k(\cdot) are the quantile functions of X_k, k=1,2,\cdots, n. It is natural to ask whether (X_1, X_2, \cdots, X_n) and (Q_1(U), Q_2(U),\cdots, Q_n(U)) can coincide almost surely for some special U.
Edit intent: meaning-changed