wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Further, we identify a mismatch between academic and industrial sources on tested platform configurations, conclude that function triggers remain insufficiently studied, and list HTTP API gateways and cloud storages as the most used external service integrations.
Revised:  Further, we identify a mismatch between academic and industrial sources on tested platform configurations, conclude that function triggers remain insufficiently studied, and identify HTTP API gateways and cloud storages as the most used external service integrations.
Edit intent: clarity
Original: Cotranslational folding is expected to occur when the folding speed  of the nascent chain is faster than the translation speed of the ribosome, but it is difficult to predict which proteins cotranslationally fold.
Revised: Cotranslational folding depends on the folding speed of the nascent chain is faster than the translation speed of the ribosome, but it is difficult to predict which proteins cotranslationally fold.
Edit intent: clarity
Original: Cotranslational folding is expected to occur when the folding speed  of the nascent chain is faster than the translation speed of the ribosome, but it is difficult to predict which proteins cotranslationally fold.
Revised: Cotranslational folding is expected to occur when the folding speed and stability of the nascent chain is faster than the translation speed of the ribosome, but it is difficult to predict which proteins cotranslationally fold.
Edit intent: meaning-changed
Original: In this work we introduce QuantNet: an architecture that is capable of transferring knowledge over systematic trading strategiesin several financial markets.
Revised: Systematic financial trading strategies account for over 80\% of trade volume in equities and a large chunk of the foreign exchange market. In spite of the availability of data from multiple markets, current approaches in trading rely mainly on learning trading strategies per individual market. In this paper, we take a step towards developing fully end-to-end global trading strategies that leverage systematic trends to produce superior market-specific trading strategies. We introduce QuantNet: an architecture that is capable of transferring knowledge over systematic trading strategiesin several financial markets.
Edit intent: meaning-changed
Original: In this work we introduce QuantNet: an architecture that is capable of transferring knowledge over systematic trading strategiesin several financial markets. By having a system that is able to leverage and share knowledge across them, our aim is two-fold: to circumvent the so-called Backtest Overfitting problem; and to generate higher risk-adjusted returns and fewer drawdowns. To do that, QuantNet exploits a form of modelling called Transfer Learning, where two layers are market-specific and another one is market-agnostic .
Revised: In this work we introduce QuantNet: an architecture that learns market-agnostic .
Edit intent: coherence
Original:  To do that, QuantNet exploits a form of modelling called Transfer Learning, where two layers are market-specific and another one is market-agnostic . This ensures that the transfer occurs across trading strategies, with the market-agnostic layer acting as a vehicle to share knowledge, cross-influence each strategy parameters, and ultimately the trading signal produced. In order to evaluate QuantNet , we compared its performance in relation to the option of not performing transfer learning, that is, using market-specific old-fashioned machine learning.
Revised:  To do that, QuantNet exploits a form of modelling called Transfer Learning, where two layers are market-specific and another one is market-agnostic trends and use these to learn superior market-specific trading strategies. Each market-specific model is composed of an encoder-decoder pair. The encoder transforms market-specific data into an abstract latent representation that is processed by a global model shared by all markets, while the decoder learns a market-specific trading strategy based on both local and global information from the market-specific encoder and the global model. QuantNet , we compared its performance in relation to the option of not performing transfer learning, that is, using market-specific old-fashioned machine learning.
Edit intent: meaning-changed
Original:  In order to evaluate QuantNet , we compared its performance in relation to the option of not performing transfer learning, that is, using market-specific old-fashioned machine learning. In summary, our findings suggest that QuantNet performs better than non transfer-based trading strategies, improving Sharpe ratio in 15\% and Calmar ratio in 41\% across 3103 assets in 58 equity markets across the world.
Revised:  In order to evaluate QuantNet , we compared its performance in relation to the option of not performing transfer learning, that is, using market-specific parameters are free to specialize on the problem at hand, whilst market-agnostic parameters are driven to capture signals from all markets. By integrating over idiosyncratic market data we can learn general transferable dynamics, avoiding the problem of overfitting to produce strategies with superior returns. We evaluate QuantNet on historical data across 3103 assets in 58 global equity markets. Against the top performing baseline, QuantNet yielded 51\% higher Sharpe and 69\% Calmar ratios. In addition we show the benefits of our approach over the non-transfer learning variant, with improvements of 15\% and Calmar ratio in 41\% across 3103 assets in 58 equity markets across the world.
Edit intent: meaning-changed
Original:  In summary, our findings suggest that QuantNet performs better than non transfer-based trading strategies, improving Sharpe ratio in 15\% and Calmar ratio in 41\% across 3103 assets in 58 equity markets across the world.
Revised:  In summary, our findings suggest that QuantNet performs better than non transfer-based trading strategies, improving Sharpe ratio in 15\% and 41\% across 3103 assets in 58 equity markets across the world.
Edit intent: clarity
Original:  In summary, our findings suggest that QuantNet performs better than non transfer-based trading strategies, improving Sharpe ratio in 15\% and Calmar ratio in 41\% across 3103 assets in 58 equity markets across the world. Code coming soon .
Revised:  In summary, our findings suggest that QuantNet performs better than non transfer-based trading strategies, improving Sharpe ratio in 15\% and Calmar ratio in 41\% in Sharpe and Calmar ratios. Code available in appendix .
Edit intent: meaning-changed
Original:  The intervals are centered at the usual  empirical Bayes estimator, but use a larger critical value to account for the effect of shrinkage. We show that in this setting, parametric EBCIs based on the assumption that the means are normally distributed (Morris, 1983) can have coverage substantially below the nominal level when the normality assumption is violated, and we derive a simple rule of thumb for gauging the potential coverage distortion.
Revised:  The intervals are centered at the usual empirical Bayes estimator, but use a critical value accounting for shrinkage. Parametric EBCIs that assume a normal distribution for the means (Morris, 1983) can have coverage substantially below the nominal level when the normality assumption is violated, and we derive a simple rule of thumb for gauging the potential coverage distortion.
Edit intent: clarity
Original:  We show that in this setting, parametric EBCIs based on the assumption that the means are normally distributed (Morris, 1983) can have coverage substantially below the nominal level when the normality assumption is violated, and we derive a simple rule of thumb for gauging the potential coverage distortion.
Revised:  We show that in this setting, parametric EBCIs based on the assumption that the means are normally distributed (Morris, 1983) may substantially undercover when this assumption is violated, and we derive a simple rule of thumb for gauging the potential coverage distortion.
Edit intent: clarity
Original:  If the means are treated as fixed, our EBCIs have an average coverage guarantee: the coverage probability is at least 1- \alpha on average across the n EBCIs for each of the means.
Revised:  If the means are treated as fixed, our EBCIs have an average coverage guarantee: the coverage probability is at least 1 - \alpha on average across the n EBCIs for each of the means.
Edit intent: fluency
Original:  We illustrate our methods with applications to effects of U.S. neighborhoods on intergenerational mobility, and structural changes in factor loadings in a large dynamic factor model for the Eurozone . Our approach generalizes to the construction of intervals with average coverage guarantees in other regularized estimation settings .
Revised:  We illustrate our methods with applications to effects of U.S. neighborhoods on intergenerational mobility, and structural changes in factor loadings in a large dynamic factor model for the Eurozone .
Edit intent: clarity
Original:  In the absence of neither an effective treatment or vaccine and with an incomplete understanding of the epidemiological cycle, predictive mathematical models can help exploring of both COVID-19 transmission and control. In this present study , we consider a new mathematical model on COVID-19 transmission that incorporate lock-down effectand variability in transmission between symptomatic and asymptomatic populations with former being a fast spreader of the disease.
Revised:  In the absence of neither an effective treatment or vaccine and with an incomplete understanding of the epidemiological cycle, predictive mathematical models can help exploring of both COVID-19 transmission in India. To study the effect of social distancing measure, we considered a new mathematical model on COVID-19 transmission that incorporate lock-down effectand variability in transmission between symptomatic and asymptomatic populations with former being a fast spreader of the disease.
Edit intent: meaning-changed
Original:  In this present study , we consider a new mathematical model on COVID-19 transmission that incorporate lock-down effectand variability in transmission between symptomatic and asymptomatic populations with former being a fast spreader of the disease. Using daily COVID-19 notified cases from three states (Maharashtra, Delhi, and Telangana) and overall India, we assess the effect of current 21 days lock-down in terms of reduction cases and deaths.
Revised:  In this present study , we consider a new mathematical model on COVID-19 that incorporates lockdown effect. By validating our model to the data on notified cases from three states (Maharashtra, Delhi, and Telangana) and overall India, we assess the effect of current 21 days lock-down in terms of reduction cases and deaths.
Edit intent: clarity
Original:  Using daily COVID-19 notified cases from three states (Maharashtra, Delhi, and Telangana) and overall India, we assess the effect of current 21 days lock-down in terms of reduction cases and deaths.
Revised:  Using daily COVID-19 notified cases from five different states and overall India, we assess the effect of current 21 days lock-down in terms of reduction cases and deaths.
Edit intent: meaning-changed
Original:  Using daily COVID-19 notified cases from three states (Maharashtra, Delhi, and Telangana) and overall India, we assess the effect of current 21 days lock-down in terms of reduction cases and deaths. Lock-down effect is studied with different lock-down success rate. Our result suggest that 21 days lock-down will have no impact in Maharashtra and overall India. Furthermore, the presence of a higher percentage of COVID-19 super-spreaders will further deteriorate the situation in Maharashtra. However, for Tamil Nadu and Delhi there is some ray of hope as our prediction shows that lock-down will reduce a significant number of cases and deaths. in these two locations . Further extension of lock-down may place Delhi and Tamil Nadu in a comfort zone. Comparing estimated parameter samples for the mentioned four locations, we find a correlation between effect of lockdown and percentage of symptomatic infected in a region .
Revised:  Using daily COVID-19 notified cases from three states (Maharashtra, Delhi, and Telangana) and overall India, we estimated several epidemiologically important parameters as well as the basic reproduction number (R_{0 .
Edit intent: meaning-changed
Original:  Our result suggests that  a higher percentage of symptomatic infected in a region leads to a large number of reduction in notified cases and deaths due to different lock-down scenario .
Revised:  Our result suggests that a higher percentage of symptomatic infection exists in the population. Furthermore, a large scale COVID-19 mass testing is required to reduce community infection. Ensemble model forecast suggested a high rise in the COVID-19 notified cases in most of the locations in the coming days. Furthermore, the trend of the effective reproduction number (R_{t .
Edit intent: meaning-changed
Original: Using a random 10\% sample of tweets authored from 2019-09-01 through 2020-03-25 , we analyze the dynamic behavior of words (1-grams) used on Twitter to describe the ongoing COVID-19 pandemic.
Revised: Using a random 10\% sample of tweets authored from 2019-09-01 through 2020-04-30 , we analyze the dynamic behavior of words (1-grams) used on Twitter to describe the ongoing COVID-19 pandemic.
Edit intent: meaning-changed
Original:  Aggregating countries by dominant language use, we find that volatility in the first dynamic regime is associated with future volatility in new cases of COVID-19 roughly three weeks (average 22.7 \pm 2.17 days) later.
Revised:  Aggregating countries by dominant language use, we find that volatility in the first dynamic regime is associated with future volatility in new cases of COVID-19 roughly three weeks (average 22.49 \pm 2.17 days) later.
Edit intent: meaning-changed
Original:  Aggregating countries by dominant language use, we find that volatility in the first dynamic regime is associated with future volatility in new cases of COVID-19 roughly three weeks (average 22.7 \pm 2.17 days) later.
Revised:  Aggregating countries by dominant language use, we find that volatility in the first dynamic regime is associated with future volatility in new cases of COVID-19 roughly three weeks (average 22.7 \pm 3.26 days) later.
Edit intent: meaning-changed
Original:  Our results suggest that surveillance of change in usage of epidemiology-related words on social media may be useful in forecasting later change in disease case numbers, but we emphasize that our current findings are not causal or necessarily predictive 
Revised:  Our results suggest that surveillance of change in usage of epidemiology-related words on social media may be useful in forecasting later change in disease case numbers, but we emphasize that our current findings are not causal or necessarily predictive .
Edit intent: fluency
Original:  Extending significantly the framework of Schied and Zhang (2018)  , who considered two agents and one asset , we focus our attention on the conditions on the value of transaction cost making the trading profile of the agents, and as a consequence the price trajectory, wildly oscillating and the market unstable.
Revised:  Extending significantly the framework of Schied and Zhang (2018) and Luo and Schied (2020) , who considered two agents and one asset , we focus our attention on the conditions on the value of transaction cost making the trading profile of the agents, and as a consequence the price trajectory, wildly oscillating and the market unstable.
Edit intent: meaning-changed
Original:  Extending significantly the framework of Schied and Zhang (2018)  , who considered two agents and one asset , we focus our attention on the conditions on the value of transaction cost making the trading profile of the agents, and as a consequence the price trajectory, wildly oscillating and the market unstable.
Revised:  Extending significantly the framework of Schied and Zhang (2018) , who considered the one asset case , we focus our attention on the conditions on the value of transaction cost making the trading profile of the agents, and as a consequence the price trajectory, wildly oscillating and the market unstable.
Edit intent: meaning-changed
Original:  We  find that the presence of more assets , the heterogeneity of trading skills (e.g. speed or cost), and a large number of agents make the market more prone to large oscillations and instability.
Revised:  We prove the existence and uniqueness of the corresponding Nash equilibria for the related mean-variance optimization problem. We find that the presence of more assets , the heterogeneity of trading skills (e.g. speed or cost), and a large number of agents make the market more prone to large oscillations and instability.
Edit intent: meaning-changed
Original:  Current camera-based eye tracking systems , however, are fundamentally limited by their bandwidth , forcing a tradeoff between image resolution and framerate, i. e. between latency and update rate .
Revised:  Current camera-based eye tracking systems , however, are fundamentally limited by their bandwidth , forcing a tradeoff between image resolution and framerate, i. e. between latency and power limitations, constraining data acquisition speed to 300 Hz realistically. This obstructs the use of mobile eye trackers to perform, e.g., low latency predictive rendering, or to study quick and subtle eye motions like microsaccades using head-mounted devices in the wild .
Edit intent: meaning-changed
Original:  Here, we propose a hybrid frame-event-based near-eye gaze tracking system offering update rates beyond 10,000 Hz with an accuracy that matches that of high-end desktop-mounted commercial eye trackers when evaluated in the same conditions.
Revised:  Here, we propose a hybrid frame-event-based near-eye gaze tracking system offering update rates beyond 10,000 Hz with an accuracy that matches that of high-end desktop-mounted commercial trackers when evaluated in the same conditions.
Edit intent: fluency
Original:  Using the first hybrid frame-event gaze dataset, which will be made public , we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view ranging from 45 degrees to 98 degrees  .
Revised:  Using the first event-based gaze dataset, which will be made public , we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view ranging from 45 degrees to 98 degrees .
Edit intent: clarity
Original:  Using the first hybrid frame-event gaze dataset, which will be made public , we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view ranging from 45 degrees to 98 degrees  .
Revised:  Using the first hybrid frame-event gaze dataset, available at URL , we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view ranging from 45 degrees to 98 degrees .
Edit intent: meaning-changed
Original:  Using the first hybrid frame-event gaze dataset, which will be made public , we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view ranging from 45 degrees to 98 degrees  .
Revised:  Using the first hybrid frame-event gaze dataset, which will be made public , we demonstrate that our system achieves accuracies of 0.45 degrees--1.75 degrees for fields of view ranging from 45 degrees to 98 degrees .
Edit intent: fluency
Original:  Using the first hybrid frame-event gaze dataset, which will be made public , we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view ranging from 45 degrees to 98 degrees  .
Revised:  Using the first hybrid frame-event gaze dataset, which will be made public , we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view from 45 degrees to 98 degrees .
Edit intent: clarity
Original:  Using the first hybrid frame-event gaze dataset, which will be made public , we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view ranging from 45 degrees to 98 degrees  .
Revised:  Using the first hybrid frame-event gaze dataset, which will be made public , we demonstrate that our system achieves accuracies of 0.45 degrees -- 1.75 degrees for fields of view ranging from 45 degrees to 98 degrees . With this technology, we hope to enable a new generation of ultra-low-latency gaze-contingent rendering and display techniques for virtual and augmented reality .
Edit intent: meaning-changed
Original:  The containment measures are modeled by considering a time-dependent modulation of the bare infectivity \lambda leading to an effective infectivity that decays in time for each infected individual, mimicking for instance the combined effect of  asymptomatic onset of the disease, testing policies and quarantine.
Revised:  The containment measures are modeled by considering a time-dependent modulation of the bare infectivity \lambda leading to effective infectivity that decays in time for each infected individual, mimicking for instance the combined effect of asymptomatic onset of the disease, testing policies and quarantine.
Edit intent: fluency
Original:  The containment measures are modeled by considering a time-dependent modulation of the bare infectivity \lambda leading to an effective infectivity that decays in time for each infected individual, mimicking for instance the combined effect of  asymptomatic onset of the disease, testing policies and quarantine.
Revised:  The containment measures are modeled by considering a time-dependent modulation of the bare infectivity \lambda leading to an effective infectivity that decays in time for each infected individual, mimicking for instance the combined effect of the asymptomatic onset of the disease, testing policies and quarantine.
Edit intent: fluency
Original: Coarse-grained models are simplified representations of systems in terms of fewer particles or sites with respect to more accurate reference descriptions, e. g., atomically-detailed. The definition of the effective interaction sites is commonly based on chemical intuition, and no systematic analysis is usually performed over the many different possible representations to assess the quality of this choice using quantitative metrics .
Revised: In the theoretical modelling of a physical system a crucial step consists in the identification of those degrees of freedom that enable a synthetic, yet informative representation of it. While in some cases this selection can be carried out on the basis of intuition and experience, a straightforward discrimination of the important features from the negligible ones is difficult for many complex systems, most notably heteropolymers and large biomolecules .
Edit intent: clarity
Original:  We employ this method to identify the representations of proteinsthat entail the largest amount of information from the original systems. It is shown that representations with low values of mapping entropy share common features that are intrinsically related to the biological properties of the proteins under examination, thereby establishing a bridge between protein structure, energetics, and function.
Revised:  We employ this method to identify the representations of proteinsthat entail the largest amount of information from the original model; we show that these highly informative representations share common features that are intrinsically related to the biological properties of the proteins under examination, thereby establishing a bridge between protein structure, energetics, and function.
Edit intent: clarity