wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We find that are predictions are in good agreement with the real data from the beginning of the appearance of the COVID-19 , which is not the case for the logistic model that applies only to the few last days.
Revised:  We find that are predictions are in good agreement with the real data from the beginning of the appearance of the COVID-19 ; this is not the case for the logistic model that applies only to the few last days.
Edit intent: coherence
Original:  We find that are predictions are in good agreement with the real data from the beginning of the appearance of the COVID-19 , which is not the case for the logistic model that applies only to the few last days. By inserting the numerical values of the parameters, obtained by analysing the real data , into the differential equation we found the values of the days where the maximum values of the number of infected people by COVID-19 will be reached in Italy and Belgium .
Revised:  We find that are predictions are in good agreement with the real data from the beginning of the appearance of the COVID-19 , which is not the case for the logistic model that only applies to the last few days. We use our differential equation parametrized with experimental data to make several predictions, such as the date when Italy and Belgium will reach a peak number of COVID-19 infected people .
Edit intent: clarity
Original:   We use our differential equation parametrised with experimental data to make several predictions, such as the date when Italy and Belgium will reach a peak number of COVID-19 infected people  .
Revised:  The second part of the work is devoted to modeling the descending phase, i.e. the decrease of the number of people tested positive for COVID-19. Also in this case, we propose a new set of dynamic differential equations that we solved numerically. We use our differential equation parametrised with experimental data to make several predictions, such as the date when Italy and Belgium will reach a peak number of COVID-19 infected people .
Edit intent: meaning-changed
Original:   We use our differential equation parametrised with experimental data to make several predictions, such as the date when Italy and Belgium will reach a peak number of COVID-19 infected people  .
Revised:  We use our differential equation parametrised with experimental data to make several predictions, such as the date when Italy and Belgium will reach a peak number of COVID-19 infected people . We shall see that the descending curves provide valuable information such as the duration of the COVID-19 epidemic in a given Country (and therefore when it will be possible to return to normal life) or how long we will still have to undergo the lockdown measures .
Edit intent: meaning-changed
Original:  We shall see that the descending curves provide valuable information such as the duration of the COVID-19 epidemic in a given Country ( and therefore when it will be possible to return to normal life ) or how long we will still have to undergo the lockdown measures .
Revised:  The descending curves provide valuable information such as the duration of the COVID-19 epidemic in a given Country ( and therefore when it will be possible to return to normal life ) or how long we will still have to undergo the lockdown measures .
Edit intent: coherence
Original:  We shall see that the descending curves provide valuable information such as the duration of the COVID-19 epidemic in a given Country ( and therefore when it will be possible to return to normal life ) or how long we will still have to undergo the lockdown measures .
Revised:  We shall see that the descending curves provide valuable information such as the duration of the COVID-19 epidemic in a given Country and therefore when it will be possible to return to normal life ) or how long we will still have to undergo the lockdown measures .
Edit intent: fluency
Original:  We shall see that the descending curves provide valuable information such as the duration of the COVID-19 epidemic in a given Country ( and therefore when it will be possible to return to normal life ) or how long we will still have to undergo the lockdown measures .
Revised:  We shall see that the descending curves provide valuable information such as the duration of the COVID-19 epidemic in a given Country ( and therefore when it will be possible to return to normal life .
Edit intent: coherence
Original:  This delay model can be put in relation with the so-called SIR model, commonly used in epidemiology, which, instead, is formulated in terms of a set of three ordinary differential equations.
Revised:  This delay model has a higher degree of accuracy than that of the so-called SIR model, commonly used in epidemiology, which, instead, is formulated in terms of a set of three ordinary differential equations.
Edit intent: clarity
Original:  This delay model has a higher degree of accuracy than that of the so-called SIR model, commonly used in epidemiology, which, instead, is formulated in terms of a set of three ordinary differential equations.
Revised:  This delay model has a higher degree of accuracy than that of the so-called SIR model, commonly used in epidemiology, which, instead, is formulated in terms of ordinary differential equations.
Edit intent: clarity
Original:  We apply our model to describe the outbreak of the new virus COVID-19 in Italy, taking into account the containment measures implemented by the government in order to mitigate the spreading of the virus and the social costs for the population.
Revised:  We apply this model to describe the outbreak of the new virus COVID-19 in Italy, taking into account the containment measures implemented by the government in order to mitigate the spreading of the virus and the social costs for the population.
Edit intent: clarity
Original:  We apply our model to describe the outbreak of the new virus COVID-19 in Italy, taking into account the containment measures implemented by the government in order to mitigate the spreading of the virus and the social costs for the population.
Revised:  We apply our model to describe the outbreak of the new infectious disease, Covid-19, in Italy, taking into account the containment measures implemented by the government in order to mitigate the spreading of the virus and the social costs for the population.
Edit intent: clarity
Original:  Our first result is a new parallel batch-dynamic triangle counting algorithm with O(\Delta\Delta+m) amortized work and O(\log^* (\Delta+m)) depth with high probability (w.h.p.) , and O(\Delta+m) space for a batch of \Delta edge insertions or deletions.
Revised:  Our first result is a new parallel batch-dynamic triangle counting algorithm with O(\Delta\Delta+m) amortized work and O(\log^* (\Delta+m)) depth with high probability , and O(\Delta+m) space for a batch of \Delta edge insertions or deletions.
Edit intent: clarity
Original:  Our second result is a simple parallel batch-dynamic k-clique counting algorithm that uses a newly developed parallel k-clique counting algorithm to bootstrap itself, by enumerating smaller cliques, and intersecting them with the batch. Instantiating this idea gives a simple batch-dynamic algorithm running in O(\Delta(m+\Delta)\alpha^{k-4) expected work and O(\log^{k-2} n) depth w.h.p., all in O(m + \Delta) space.
Revised:  Our second result is ) expected work and O(\log^{k-2} n) depth w.h.p., all in O(m + \Delta) space.
Edit intent: coherence
Original:  1)\omega_p{3(\omega_p + 1)}}, (\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right)\right) amortized work , O(\log (\Delta+m)) depth  , and O\left((\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right) space ) expected work and O(\log^{k-2} n) depth with high probability, and O(m + \Delta) space.
Revised:  1)\omega_p{3(\omega_p + 1)}}, (\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right)\right) amortized work and O(\log (\Delta+m)) depth , and O\left((\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right) space ) expected work and O(\log^{k-2} n) depth with high probability, and O(m + \Delta) space.
Edit intent: fluency
Original:  1)\omega_p{3(\omega_p + 1)}}, (\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right)\right) amortized work , O(\log (\Delta+m)) depth  , and O\left((\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right) space ) expected work and O(\log^{k-2} n) depth with high probability, and O(m + \Delta) space.
Revised:  1)\omega_p{3(\omega_p + 1)}}, (\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right)\right) amortized work , O(\log (\Delta+m)) depth with high probability , and O\left((\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right) space ) expected work and O(\log^{k-2} n) depth with high probability, and O(m + \Delta) space.
Edit intent: fluency
Original:  1)\omega_p{3(\omega_p + 1)}}, (\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right)\right) amortized work , O(\log (\Delta+m)) depth  , and O\left((\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right) space ) expected work and O(\log^{k-2} n) depth with high probability, and O(m + \Delta) space.
Revised:  1)\omega_p{3(\omega_p + 1)}}, (\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right)\right) amortized work , O(\log (\Delta+m)) depth , and O\left((\Delta+m)^{2(k + 1)\omega_p{3(\omega_p + 1)}}\right) space . Using a recently developed parallel k-clique counting algorithm, we also obtain a simple batch-dynamic algorithm for k-clique counting on graphs with arboricity \alpha running in O(\Delta(m+\Delta)\alpha^{k-4) expected work and O(\log^{k-2} n) depth with high probability, and O(m + \Delta) space.
Edit intent: meaning-changed
Original:  If d \geq 4, the minimal time horizon can be characterized via the arrival time function of a geometric flow of the unit simplex in  R^d that we call the minimum curvature flow.
Revised:  If d \geq 4, the minimal time horizon can be characterized via the arrival time function of a geometric flow of the unit simplex in \mathbb R^d that we call the minimum curvature flow.
Edit intent: meaning-changed
Original:  Naturally produced droplets from humans (such as those produced by breathing, talking, sneezing, and coughing) include several types of cells (e.g., epithelial cells and cells of the immune system), physiological electrolytes contained in mucous and saliva (e.g. Na+, K+, Cl-), as well as, potentially, several infectious agents (e.g. bacteria, fungi, and viruses).
Revised: Abridged Naturally produced droplets from humans (such as those produced by breathing, talking, sneezing, and coughing) include several types of cells (e.g., epithelial cells and cells of the immune system), physiological electrolytes contained in mucous and saliva (e.g. Na+, K+, Cl-), as well as, potentially, several infectious agents (e.g. bacteria, fungi, and viruses).
Edit intent: meaning-changed
Original:  In response to the novel coronavirus SARS-CoV-2 epidemic, which has become a major public health issue worldwide, we provide a didactic overview of airborne germ transmission as seen from a physics perspective  .
Revised:  In response to the novel coronavirus SARS-CoV-2 epidemic, which has become a major public health issue worldwide, we provide a concise overview of airborne germ transmission as seen from a physics perspective .
Edit intent: meaning-changed
Original:  In response to the novel coronavirus SARS-CoV-2 epidemic, which has become a major public health issue worldwide, we provide a didactic overview of airborne germ transmission as seen from a physics perspective  .
Revised:  In response to the novel coronavirus SARS-CoV-2 epidemic, which has become a major public health issue worldwide, we provide a didactic overview of airborne germ transmission as seen from a physics perspective . We study whether coronavirus aerosols can travel far from the immediate neighborhood and get airborne with the convective currents developed within confined spaces .
Edit intent: meaning-changed
Original:  As an example, a county with 2.8 million population with initial 200  infectious cases is considered , where about 0.15\% people died during the pandemic. Compared with a constant containment strategy, adaptive containment strategies shorten the outbreak length and executing the strictest measures earlier will cause less mortality.
Revised:  As an example, a county with 2.8 million population with initial 200 infectious cases is considered assuming a 4\% mortality rate. We found that compared with a constant containment strategy, adaptive containment strategies shorten the outbreak length and executing the strictest measures earlier will cause less mortality.
Edit intent: meaning-changed
Original:  However, in order to satisfy the needs of its citizens, the strictest containment measures can be only executed for short period.
Revised:  Moreover, the severity of the situation has sparked engagement by both the research and clinical community with the goal of developing effective treatments for the disease. This article proposes a time dynamic prediction model with competing risks for the infected individual and develops a simple tool for policy makers to compare different strategies in terms of when to implement the strictest containment measures can be only executed for short period.
Edit intent: meaning-changed
Original:  However, in order to satisfy the needs of its citizens, the strictest containment measures can be only executed for short period. This article compares two types of containment strategies : a constant containment strategy that could satisfy the needs of citizens for a long period and an adaptive containment strategy whose strict level changes across time.
Revised:  However, in order to satisfy the needs of its citizens, the strictest containment measures and how different treatments can increase or suppress infected cases. Two types of containment strategies : a constant containment strategy that could satisfy the needs of citizens for a long period and an adaptive containment strategy whose strict level changes across time.
Edit intent: meaning-changed
Original:  When to implement the strictest measure is also of interest. A dynamic prediction model is proposed and a simple tool is developed for policy makers to compare different containment strategies. As an example, a region with population 2.8 million and 200 initial infectious cases is considered assuming a 4\% mortality rate .
Revised:  We consider how an effective treatment of the disease can affect the dynamics in a pandemic scenario. For illustration we consider a region with population 2.8 million and 200 initial infectious cases is considered assuming a 4\% mortality rate .
Edit intent: clarity
Original:  As an example, a region with population 2.8 million and 200 initial infectious cases is considered assuming a 4\% mortality rate . We found that compared with a constant containment strategy, adaptive containment strategies shorten the outbreak length and executing the strictest measures early will cause less mortality .
Revised:  As an example, a region with population 2.8 million and 200 initial infectious cases is considered assuming a 4\% mortality rate compared with a 2\% mortality rate if a new drug is available. Our results show compared with a constant containment strategy, adaptive containment strategies shorten the outbreak length and executing the strictest measures early will cause less mortality .
Edit intent: meaning-changed
Original: We analyze the early data on COVID-19 expansion in selected European countries using an analytical parametric model. A description of the time dependence of the disease expansion and a method to evaluate trends of the expansionare proposed.
Revised: We analyze the early data on COVID-19 disease in twenty European countries is analyzed by the least-squares fitting procedure with generic analytic functions. Three regimes of the expansion of the disease expansion and a method to evaluate trends of the expansionare proposed.
Edit intent: meaning-changed
Original:  A description of the time dependence of the disease expansion and a method to evaluate trends of the expansionare proposed. Several features are observed in the data, namely a high predictability of the expansion of disease in Italy and a convergence of the "pushback" parameter towards a limiting value in all the countries where restrictive measures have been adopted.
Revised:  A description of the time dependence of the disease are identified and quantified -- early exponential expansion, damped exponential, and linear expansion. Differences among countries in the early expansion period are quantified. The velocity of the expansion of disease in Italy and a convergence of the "pushback" parameter towards a limiting value in all the countries where restrictive measures have been adopted.
Edit intent: meaning-changed
Original:  Several features are observed in the data, namely a high predictability of the expansion of disease in Italy and a convergence of the "pushback" parameter towards a limiting value in all the countries where restrictive measures have been adopted. Basic predictions for the evolution of the disease expansion are made for selected countries with a stable evolution in the parametric space of the model.
Revised:  Several features are observed in the data, namely a high predictability of the expansion in the evolution of the disease expansion are made for selected countries with a stable evolution in the parametric space of the model.
Edit intent: clarity
Original:  Basic predictions for the evolution of the disease expansion are made for selected countries with a stable evolution in the parametric space of the model.
Revised:  Basic predictions for the exponential regime lies within one standard deviation from the average value for 11 countries. The number of infected individuals at the initial time is excessively high for Italy, 7 standard deviations from the average value. Method for predicting the expansion based on extrapolation in the parametric space of the model.
Edit intent: meaning-changed
Original:  Basic predictions for the evolution of the disease expansion are made for selected countries with a stable evolution in the parametric space of the model. The findings presentedhere should contribute to the understanding of the behavior of the disease expansion and the role of the restrictive measures on the evolution of the expansion .
Revised:  Basic predictions for the evolution of the disease expansion are made for selected countries with a stable evolution in the parametric space is presented. One-week predictions based on extrapolations have average precision of 18\% and 29\% during the later period of the damped exponential expansion for the case of Italy and Czechia, respectively. The method based on extrapolations in the parametric space may provide an elementary method to quantify the impact of restrictive measures on the evolution of the expansion .
Edit intent: meaning-changed
Original:   We use two variations of the SIR model and we include a parameter in this model that accounts for the effects of confinement measures.
Revised:  This early period accounts for unawareness of the epidemiological characteristics of the disease in a new territory, sub-notification of the real numbers of infected people and the timely introduction of social distancing policies to flatten the spread of the disease. We use two variations of the SIR model and we include a parameter in this model that accounts for the effects of confinement measures.
Edit intent: meaning-changed
Original:   We use two variations of the SIR model and we include a parameter in this model that accounts for the effects of confinement measures. We do not calibrate our models parameters, but we estimate all of them based on a clear hierarchical procedure of squared error minimization. The estimated parameters of the ratio between symptomatic and asymptomatic individuals, the proportion of infected individuals that die and the usual epidemiological parameters have a great match with the ones provided by the literature. Our final models provide precise forecasts of the number of infected individuals. We use these models to discuss different scenarios of public policies.
Revised:  We use two variations of the SIR model and we include a parameter in this model that accounts for the effects of social distancing measures. Short and
Edit intent: coherence
Original:  Long terms forecasts show that the confinement policy imposed by the government is able to flatten the pattern of infection of the COVID-19 and we are able to find the optimal date to end the policy .
Revised:  Long terms forecasts show that the social distancing policy imposed by the government is able to flatten the pattern of infection of the COVID-19 and we are able to find the optimal date to end the policy .
Edit intent: meaning-changed
Original:  However, our results  show that if this policy does not last enough time, it is only able to shift the peak of infection into the future keeping the value of the peak in almost the same value  .
Revised:  However, our results show that if this policy does not last enough time, it is only able to shift the peak of infection into the future keeping the value of the peak in almost the same value . Furthermore, our long term simulations forecast the optimal date to end the policy. Finally, we show that the proportion of asymptomatic individuals affects the amplitude of the peak of symptomatic infected, suggesting that it is important to test the population .
Edit intent: meaning-changed
Original: The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial and URLanization 1 . The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees.
Revised: The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial 1 . The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees.
Edit intent: fluency
Original: The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial and URLanization 1 . The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees.
Revised: The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial and URLanization , and URLanization . The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees.
Edit intent: meaning-changed
Original:  The infection duration and number of infected persons are of critical importance for the battle against the pandemic 2,3 . We use the quantitative landscape of the disease spreading in China as a benchmark and utilize infection data from eight countries to estimate the complete evolution of the infection in each of these countries.
Revised:  The infection duration and number of infected persons are of critical importance for the battle against the pandemic . We use the quantitative landscape of the disease spreading in China as a benchmark and utilize infection data from eight countries to estimate the complete evolution of the infection in each of these countries.
Edit intent: coherence