wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We also compute a power series in the log-moneyness variable for the asymptotic implied volatility , which yields tractable expressions for the  vol skew and convexity , thus being useful for calibration purposes. We also derive formal asymptotics for the small-time moderate deviations regime and a formal saddlepoint approximation for call options in the large deviations regime. This goes to higher order than previous works for rough models, and in particular captures the effect of the mean reversion term. In the large maturity case, the limiting asymptotic smile turns out to be the same as for the standard Heston model ,
Revised:  We also compute a power series in the log-moneyness variable for the asymptotic implied volatility , which yields tractable expressions for the vol skew and convexity . The limiting asymptotic smile in the large-maturity regime is obtained via a stability analysis of the fixed points of the VIE, and is the same as for the standard Heston model ,
Edit intent: meaning-changed
Original:  the limiting asymptotic smile turns out to be the same as for the standard Heston model , for which there is a well known closed-form formula in terms of the SVI parametrization}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to \to _t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to \to  }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Revised:  the limiting asymptotic smile turns out to be the same as for the standard Heston model in \mbox{%DIFAUXCMD \cite{FJ11}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to \to _t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to \to }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Edit intent: meaning-changed
Original:  for which there is a well known closed-form formula in terms of the SVI parametrization}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to \to _t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to \to  }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Revised:  for which there is a well known closed-form formula in terms of the SVI parametrization}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to 1/2 (i.e. H\to _t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to \to }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Edit intent: meaning-changed
Original:  for which there is a well known closed-form formula in terms of the SVI parametrization}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to \to _t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to \to  }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Revised:  for which there is a well known closed-form formula in terms of the SVI parametrization}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to \to 0) whose mgf is also the solution to the Rough Heston VIE with \alpha=1/2, and we show that X^{(1/2)_t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to \to }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Edit intent: meaning-changed
Original:  for which there is a well known closed-form formula in terms of the SVI parametrization}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to \to _t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to \to  }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Revised:  for which there is a well known closed-form formula in terms of the SVI parametrization}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to \to _t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to 0, which leads to a non-flat non-symmetric asymptotic smile in the Edgeworth regime. We also show that the third moment of the log stock price tends to a finite constant as H\to }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Edit intent: meaning-changed
Original:  for which there is a well known closed-form formula in terms of the SVI parametrization}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to \to _t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to \to  }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Revised:  for which there is a well known closed-form formula in terms of the SVI parametrization}\hspace{0pt}%DIFAUXCMD . Finally, using L\'{e}vy's convergence theorem, we show that the log stock price X_t tends weakly to a non-symmetric random variable X^{(1/2)}_t as \alpha }\to \to _t/\sqrt{t} tends weakly to a non-symmetric random variable as t}\to \to 0 (in contrast to the Rough Bergomi model discussed in \mbox{%DIFAUXCMD \cite{FFGS20 }\hspace{0pt}%DIFAUXCMD where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution} .
Edit intent: meaning-changed
Original:  During the active period of the gene, many RNAP molecules transcribe the gene to synthesize the mRNA . The binding event of RNAP to the active state of the gene is an probabilistic process and therefore, introduces noise or fluctuations in the protein levels.
Revised:  During the active period of the gene, many RNAP molecules transcribe the gene to synthesize the mRNAs . The binding event of RNAP to the active state of the gene is an probabilistic process and therefore, introduces noise or fluctuations in the protein levels.
Edit intent: clarity
Original:  During the active period of the gene, many RNAP molecules transcribe the gene to synthesize the mRNA . The binding event of RNAP to the active state of the gene is an probabilistic process and therefore, introduces noise or fluctuations in the protein levels.
Revised:  During the active period of the gene, many RNAP molecules transcribe the gene to synthesize the mRNA . The binding event of RNAP to the active state of the gene is a probabilistic process and therefore, introduces noise or fluctuations in the protein levels.
Edit intent: fluency
Original:  During the active period of the gene, many RNAP molecules transcribe the gene to synthesize the mRNA . The binding event of RNAP to the active state of the gene is an probabilistic process and therefore, introduces noise or fluctuations in the protein levels. The binding event of RNAP to the active state of the gene is an probabilistic process and therefore introduces noise in the protein levels.
Revised:  During the active period of the gene, many RNAP molecules transcribe the gene to synthesize the mRNA . The binding event of RNAP to the active state of the gene is an probabilistic process and therefore, introduces noise or fluctuations in the mRNA and protein levels.
Edit intent: clarity
Original:  The theoretically calculated noise expression of proteins shows excellent agreement with an experimental results. Then , we show that the noise in mRNA level can be sub-Poissonian due to the reinitiation of transcription by RNAP and the mean mRNA level can be increased without increasing the noise.
Revised:  The theoretically calculated noise expression of proteins shows excellent agreement with an experimental result. Then we show that the noise in mRNA level can be sub-Poissonian due to the reinitiation of transcription by RNAP and the mean mRNA level can be increased without increasing the noise.
Edit intent: fluency
Original:  Then , we show that the noise in mRNA level can be sub-Poissonian due to the reinitiation of transcription by RNAP and the mean mRNA level can be increased without increasing the noise.
Revised:  Then , we show that the Fano factor in mRNA levels can be sub-Poissonian due to the reinitiation of transcription by RNAP and the mean mRNA level can be increased without increasing the noise.
Edit intent: meaning-changed
Original:  Then , we show that the noise in mRNA level can be sub-Poissonian due to the reinitiation of transcription by RNAP and the mean mRNA level can be increased without increasing the noise.
Revised:  Then , we show that the noise in mRNA level can be sub-Poissonian due to the reinitiation of transcription by RNAP and the mean mRNA level can be increased without increasing the Fano factor. Our study show that the Fano factor can also be reduced keeping mRNA levels fixed.
Edit intent: meaning-changed
Original: Developing efficient computational methods to change the state of a cell from an undesirable condition, e.g. diseased, into a desirable, e.g. healthy, condition is an important goal of systems biology.
Revised: Developing efficient computational methods to change the state of a cell from an undesirable condition, e.g. diseased, into a desirable, e.g. healthy, condition is an important problem in systems biology.
Edit intent: clarity
Original: This work introduces RadVR, a virtual reality daylighiting analysis tools, that simultaneously allows the analysis of qualitative immersive renderings and the assessment of quantitative data of physically correct daylighting simulations in a 6DOF virtual environment.
Revised: This work introduces RadVR, a virtual reality tool for daylighting analysis that simultaneously combines qualitative assessments through immersive real-time renderings with quantitative physically correct daylighting simulations in a 6DOF virtual environment.
Edit intent: clarity
Original:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year  (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Revised:  perform physically-based daylighting simulations via Radiance, (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Edit intent: clarity
Original:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year  (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Revised:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight in different hours-of-the-year, (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Edit intent: clarity
Original:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year  (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Revised:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) interact with a 9-point-in-time matrix for the nine most representative times of the year (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Edit intent: fluency
Original:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year  (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Revised:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the most representative times of the year (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Edit intent: fluency
Original:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year  (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Revised:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year , and (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Edit intent: coherence
Original:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year  (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality.
Revised:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year (4) visualize, compare, and analyze daylighting simulation results using integrated tools in virtual reality.
Edit intent: fluency
Original:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year  (4) Visualize, compare and analyze daylighting simulation results using integrated tools in virtual reality. By conducting user experiments and comparing the system with a conventional 2D-display daylight analysis tool , Diva4Rhino, the results show that RadVR outperforms Diva4Rhino in spatial understanding tasks, navigation  and sun position analysis  .
Revised:  perform physically-based daylighting simulations powered by the Radianceengine (2) study sunlight penetration in different hours of the year by navigating through time (3) Interact with a 9-point-in-time matrix for the nine most representative times of the year (4) Visualize, compare and analyze daylighting simulation results . With an end-to-end workflow, RadVR integrates with 3D modeling software that is commonly used by building designers. Additionally, by conducting user experiments and comparing the system with a conventional 2D-display daylight analysis tool , Diva4Rhino, the results show that RadVR outperforms Diva4Rhino in spatial understanding tasks, navigation and sun position analysis .
Edit intent: meaning-changed
Original:  By conducting user experiments and comparing the system with a conventional 2D-display daylight analysis tool , Diva4Rhino, the results show that RadVR outperforms Diva4Rhino in spatial understanding tasks, navigation  and sun position analysis  .
Revised:  By conducting user experiments we compare the proposed system with DIVA for Rhino, a Radiance-based tool that uses conventional 2D-displays. The results show that RadVR outperforms Diva4Rhino in spatial understanding tasks, navigation and sun position analysis .
Edit intent: meaning-changed
Original:  By conducting user experiments and comparing the system with a conventional 2D-display daylight analysis tool , Diva4Rhino, the results show that RadVR outperforms Diva4Rhino in spatial understanding tasks, navigation  and sun position analysis  .
Revised:  By conducting user experiments and comparing the system with a conventional 2D-display daylight analysis tool , Diva4Rhino, the results show that RadVR can provide promising assistance in spatial understanding tasks, navigation and sun position analysis .
Edit intent: clarity
Original:  By conducting user experiments and comparing the system with a conventional 2D-display daylight analysis tool , Diva4Rhino, the results show that RadVR outperforms Diva4Rhino in spatial understanding tasks, navigation  and sun position analysis  .
Revised:  By conducting user experiments and comparing the system with a conventional 2D-display daylight analysis tool , Diva4Rhino, the results show that RadVR outperforms Diva4Rhino in spatial understanding tasks, navigation , and sun position analysis .
Edit intent: fluency
Original:  By conducting user experiments and comparing the system with a conventional 2D-display daylight analysis tool , Diva4Rhino, the results show that RadVR outperforms Diva4Rhino in spatial understanding tasks, navigation  and sun position analysis  .
Revised:  By conducting user experiments and comparing the system with a conventional 2D-display daylight analysis tool , Diva4Rhino, the results show that RadVR outperforms Diva4Rhino in spatial understanding tasks, navigation and sun position analysis in virtual reality .
Edit intent: clarity
Original: Surprise-based learning allows agents to adapt quickly in non-stationary stochastic environments . Most existing approaches to surprise-based learning and change point detection assume either implicitly or explicitly a simple, hierarchical generative model of observation sequences that are characterized by stationary periods separated by sudden changes.
Revised: Surprise-based learning allows agents to adapt quickly in non-stationary stochastic environments characterized by stationary periods separated by sudden changes.
Edit intent: clarity
Original:  In this work we show that exact Bayesian inference gives naturally rise to a surprise-modulated trade-off between URLetting and integrating the new observations with the current belief.
Revised:  In this work we show that exact Bayesian inference gives naturally rise to a surprise-modulated trade-off between URLetting old observations and integrating them with the new ones. The modulation depends on a probability ratio, called the "Bayes Factor Surprise" that tests the prior belief against the current belief.
Edit intent: meaning-changed
Original:  We demonstrate that many existing approximate Bayesian approaches also show surprise-based modulation of learning rates, and we derive novel particle filters and variational filters with update rules that exhibit surprise-based modulation. Our derived filters have a constant scaling in observation sequence length and particularly simple update dynamics for any distribution in the exponential family.
Revised:  We demonstrate that in several existing approximate algorithms the Bayes Factor Surprise modulates the rate of adaptation to new observations. We derive three novel surprised-based algorithms, one in the family of particle filters, one in the family of variational learning, and the other in the family of message passing, that are biologically plausible, have constant scaling in observation sequence length and particularly simple update dynamics for any distribution in the exponential family.
Edit intent: meaning-changed
Original:  The  theoretical insight of casting various approaches under the same interpretation of surprise-based learning, as well as the proposed filters, may find useful applications in reinforcement learning in non-stationary environments and in the analysis of animal and human behavior  .
Revised:  The Bayes Factor Surprise is related to but different from Shannon Surprise. In two hypothetical experiments, we make testable predictions for physiological or behavioral indicators that dissociate the Bayes Factor Surprise from Shannon Surprise. The theoretical insight of casting various approaches under the same interpretation of surprise-based learning, as well as the proposed filters, may find useful applications in reinforcement learning in non-stationary environments and in the analysis of animal and human behavior .
Edit intent: meaning-changed
Original:  The  theoretical insight of casting various approaches under the same interpretation of surprise-based learning, as well as the proposed filters, may find useful applications in reinforcement learning in non-stationary environments and in the analysis of animal and human behavior  .
Revised:  The theoretical insight of casting various approaches as surprise-based learning, as well as the proposed filters, may find useful applications in reinforcement learning in non-stationary environments and in the analysis of animal and human behavior .
Edit intent: clarity
Original:  The  theoretical insight of casting various approaches under the same interpretation of surprise-based learning, as well as the proposed filters, may find useful applications in reinforcement learning in non-stationary environments and in the analysis of animal and human behavior  .
Revised:  The theoretical insight of casting various approaches under the same interpretation of surprise-based learning, as well as the proposed filters, may find useful applications in reinforcement learning in non-stationary environments and in the analysis of animal and human behavior , and to reinforcement learning in non-stationary environments .
Edit intent: meaning-changed
Original:  This test has power against generic n-alternatives , and failure to reject the null implies no selection . By contrast, as any omnibus test, we cannot distinguish between a rejection due to genuine selection or to generic mis-specification, when the omitted variable is correlated with the propensity score.
Revised:  This test has power against generic n-alternatives , and failure to reject the null implies no selection , we cannot, as any omnibus test, we cannot distinguish between a rejection due to genuine selection or to generic mis-specification, when the omitted variable is correlated with the propensity score.
Edit intent: coherence