wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We give the first provable algorithms that work regardless of the separation, but only for a constant number of point sources. Surprisingly, we show that when the number of point sources becomes large, there is a phase transition where the sample complexity goes from polynomial to exponential , and we pin down its location to within a universal constant that is independent of the number of point sources.
Revised:  In particular we show that when the number of point sources becomes large, there is a phase transition where the sample complexity goes from polynomial to exponential , and we pin down its location to within a universal constant that is independent of the number of point sources.
Edit intent: coherence
Original:  Surprisingly, we show that when the number of point sources becomes large, there is a phase transition where the sample complexity goes from polynomial to exponential , and we pin down its location to within a universal constant that is independent of the number of point sources.
Revised:  Surprisingly, we show that there is a phase transition where the sample complexity goes from polynomial to exponential , and we pin down its location to within a universal constant that is independent of the number of point sources.
Edit intent: clarity
Original:  Surprisingly, we show that when the number of point sources becomes large, there is a phase transition where the sample complexity goes from polynomial to exponential , and we pin down its location to within a universal constant that is independent of the number of point sources. Thus it is rigorously possible both to break the diffraction limit and yet to prove strong impossibility results depending on the setup. This is the first non-asymptotic statistical foundation for resolution in a model arising from first principles in physics, and helps clarify many omnipresent debates in the optics literature .
Revised:  Surprisingly, we show that when the number of point sources becomes large, there is a phase transition where the sample complexity goes from polynomial to exponential . Surprisingly, we show that this does not occur at the Abbe limit, which has long been presumed to be the true diffraction limit .
Edit intent: meaning-changed
Original:  Here we present the application of different software tools based on transcriptomics data to identify drugs that are potentially able to counteract SARS-CoV-2 infection  and also to provide insights on their mode of action.
Revised:  Here we present the application of computational drug repositioning tools based on transcriptomics data to identify drugs that are potentially able to counteract SARS-CoV-2 infection and also to provide insights on their mode of action.
Edit intent: meaning-changed
Original:  Here we present the application of different software tools based on transcriptomics data to identify drugs that are potentially able to counteract SARS-CoV-2 infection  and also to provide insights on their mode of action.
Revised:  Here we present the application of different software tools based on transcriptomics data to identify drugs that are potentially able to counteract SARS-CoV-2 infection , and also to provide insights on their mode of action.
Edit intent: fluency
Original:  In addition, we found that the DNA Mismatch repair pathway is strongly modulated by drugs with experimental in vitro activity against SARS-CoV-2 infection  .
Revised:  In addition, we found that the DNA Mismatch repair pathway is strongly modulated by drugs with experimental in vitro activity against SARS-CoV-2 infection . Both full results and methods are publicly available .
Edit intent: meaning-changed
Original:  We investigate the first two numerically and produce generating functions which codify the observed patterns , we perform an exploratory data analysis for the third .
Revised:  We investigate the first two numerically and produce generating functions which codify the observed patterns : knot size is uniformly distributed and linearly dependent upon grid size, and the number of components follows a distribution whose mean and variance grow with log_2 of grid size; in particular, for any fixed k, the k-component links grow vanishingly rare as grid size increases. Finally, we observe that the odd moments of writhe vanish, and we perform an exploratory data analysis for the third .
Edit intent: meaning-changed
Original: Calibration of a SIR (Susceptibles-Infected-Recovered) model with official data at international level for the COVID-19 pandemics provides a good example of the difficulties inherent the solution of inverse problems.
Revised: Calibration of a SIR (Susceptibles-Infected-Recovered) model with official international data for the COVID-19 pandemics provides a good example of the difficulties inherent the solution of inverse problems.
Edit intent: clarity
Original:  Together with a physical vision of the model, this is very useful to discuss the uncertainties on the data and how they influence the reliability of calibrated model parameters and, ultimately, of model predictions.
Revised:  Together with a physical vision of the model, the present work addresses numerically the issue of parameters calibration in SIR models, it discusses the uncertainties in the data provided by international authorities, how they influence the reliability of calibrated model parameters and, ultimately, of model predictions.
Edit intent: meaning-changed
Original:  We find that our alternative hypothesis is supported for R&D funded and/or performed by business enterprises while the original Hicks hypothesis holds for R&D funded by the government and R&D performed by universities  .
Revised:  We find that our alternative hypothesis is supported for R&D funded and/or performed by business enterprises while the original Hicks hypothesis holds for R&D funded by the government and R&D performed by universities . Our results reflect that business sector is significantly influenced by market conditions, unlike the government and higher education sectors .
Edit intent: meaning-changed
Original:  Using insights from service communication data, we model the service interactions using self-exciting and mutually exciting bivariate Hawkes processes, so that a correspondence from one party increases the likelihood of a response from the other party soon after. Moreover, our models incorporate both dynamic busyness factors that depend on the agent workload as well as dynamic factors that depend on the inner-mechanics of the interaction.
Revised:  A key observation is that the customer and agent's co-produced service has cross- and self-exciting dynamics within each conversation. The cross-excitation stems from the two parties responding to one another, and the self-excitation captures one party sending follow-ups to their own prior message. We capture this phenomenon by introducing Hawkes process models of the inner-mechanics of the interaction.
Edit intent: coherence
Original:  Moreover, our models incorporate both dynamic busyness factors that depend on the agent workload as well as dynamic factors that depend on the inner-mechanics of the interaction. To understand how well our Hawkes modelsdescribe the message-timestamps, we compare the goodness-of-fit of these models on contact center data from industry .
Revised:  Moreover, our models incorporate both dynamic busyness factors that depend on the agent workload as well as dynamic factors that depend on the services. These models distinguish between the role of the customer and of the agent, reflect the service process's dynamic evolution over time based on its own history, and include additional behavioral and operational aspects, including the agent's number of simultaneous assignments and measures of the amount of information and sentiment each message contains. To evaluate our service co-production models, we apply them to an industry contact center dataset containing nearly 5 million messages .
Edit intent: meaning-changed
Original:  We show that the word-count bivariate Hawkes model, which takes into account the mutual interaction and the amount of information provided by each party, fits the data the best. In addition to a great goodness-of-fit, the Hawkes models allow us to construct explicit expressions for the relationship between the correspondence rates of each party and the conversation progress. These formulae illustrate that the agent is more dominant in pacing the service along in the short term, but that the customer has a more profound effect on the duration of the conversation in the long run .
Revised:  We show that the Hawkes models better represent the service dynamics than do the classic Poisson and phase-type models. Indeed, we find that service interactions are characterized by strong agent-customer dependency and the centrality of the process's cross- and self-excitation attributes .
Edit intent: clarity
Original:  Finally, we use our models to predict the future level of activity within a given conversation, through which we find that the bivariate Hawkes processes that incorporate the amount of information provided by each party or the sentiment expressed by the customer give us the most accurate predictions .
Revised:  Finally, we use the proposed models to improve upon routing algorithms used in contact centers. We show how an activity-based dynamic routing based on predicted information easily computed from our models can outperform well-known and widely used concurrency-based routing rules and substantially reduce customer waiting time, demonstrating how these history-dependent stochastic models can improve operational decision making in practice .
Edit intent: meaning-changed
Original:  We show, by means of numerical simulations, that the proposed models correctly predict the main features of force generation, including the steady-state force-calcium and force-length relationships, the tension-dependent prolongation of twitches  , the force-velocity relationship.
Revised:  We show, by means of numerical simulations, that the proposed models correctly predict the main features of force generation, including the steady-state force-calcium and force-length relationships, the length-dependent prolongation of twitches , the force-velocity relationship.
Edit intent: clarity
Original:  We show, by means of numerical simulations, that the proposed models correctly predict the main features of force generation, including the steady-state force-calcium and force-length relationships, the tension-dependent prolongation of twitches  , the force-velocity relationship.
Revised:  We show, by means of numerical simulations, that the proposed models correctly predict the main features of force generation, including the steady-state force-calcium and force-length relationships, the tension-dependent prolongation of twitches and increase of peak force , the force-velocity relationship.
Edit intent: meaning-changed
Original:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 31 determinant , describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome  .
Revised:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 29 determinants , describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome .
Edit intent: meaning-changed
Original:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 31 determinant , describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome  .
Revised:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 31 determinant , describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome . We show that the true mathematical model of the coronavirus outcome is constituted only of few determinants, but the extent to which each determinant is able to provide an adequate explanation varies between countries due to their heterogeneous socioeconomic structures. To understand the relationship between the socio-economic determinants in the specification of the true model we develop the coronavirus determinants Jointness space. In this space, the potential determinants are linked with each other by their ability to jointly explain the coronavirus outcome. As such the Jointness space can be efficiently implemented for developing socio-economic policies aimed at prevention of future epidemic crises .
Edit intent: meaning-changed
Original:  We show that the true mathematical model of the coronavirus outcome is constituted only of few determinants, but the extent to which each determinant is able to provide an adequate explanation varies between countries due to their heterogeneous socioeconomic structures .
Revised:  We show that the true empirical model behind the coronavirus outcome is constituted only of few determinants, but the extent to which each determinant is able to provide an adequate explanation varies between countries due to their heterogeneous socioeconomic structures .
Edit intent: meaning-changed
Original:  We show that the true mathematical model of the coronavirus outcome is constituted only of few determinants, but the extent to which each determinant is able to provide an adequate explanation varies between countries due to their heterogeneous socioeconomic structures .
Revised:  We show that the true mathematical model of the coronavirus outcome is constituted only of few determinants, but the extent to which each determinant is able to provide a credible explanation varies between countries due to their heterogeneous socioeconomic structures .
Edit intent: clarity
Original:  We show that the true mathematical model of the coronavirus outcome is constituted only of few determinants, but the extent to which each determinant is able to provide an adequate explanation varies between countries due to their heterogeneous socioeconomic structures .
Revised:  We show that the true mathematical model of the coronavirus outcome is constituted only of few determinants, but the extent to which each determinant is able to provide an adequate explanation varies between countries due to their heterogeneous socio-economic characteristics .
Edit intent: clarity
Original:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 29 determinants, describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome .
Revised:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 30 determinants, describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome .
Edit intent: meaning-changed
Original:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 29 determinants, describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome .
Revised:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 29 determinants, describing a diverse set of socio-economic characteristics, in explaining the outcome of the first wave of the coronavirus pandemic .
Edit intent: meaning-changed
Original:  In this space, two determinants are connected with each other if they are able to jointly explain the coronavirus outcome. As constructed, the obtained map acts as a bridge between theoretical investigations and empirical observations, and offers an alternate view for the joint importance of the socio-economic determinants when used for developing policies aimed at preventing future epidemic crises.
Revised:  The obtained map acts as a bridge between theoretical investigations and empirical observations, and offers an alternate view for the joint importance of the socio-economic determinants when used for developing policies aimed at preventing future epidemic crises.
Edit intent: coherence
Original:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 30 determinants, describing a diverse set of socio-economic characteristics, in explaining the outcome of the first wave of the coronavirus pandemic.
Revised:  Here, we leverage Bayesian model averaging techniques and country level data to investigate the potential of 30 determinants, describing a diverse set of socio-economic characteristics, in explaining the outcome of the first wave of the coronavirus pandemic.
Edit intent: coherence
Original:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 30 determinants, describing a diverse set of socio-economic characteristics, in explaining the outcome of the first wave of the coronavirus pandemic.
Revised:  In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 31 determinants, describing a diverse set of socio-economic characteristics, in explaining the outcome of the first wave of the coronavirus pandemic.
Edit intent: meaning-changed
Original:  The obtained map acts as a bridge between theoretical investigations and empirical observations , and offers an alternate view for the joint importance of the socio-economic determinants when used for developing policies aimed at preventing future epidemic crises.
Revised:  The extent to which each determinant is able to provide a credible explanation varies between countries due to their heterogeneous socio-economic characteristics. In this aspect, the obtained Jointness map acts as a bridge between theoretical investigations and empirical observations , and offers an alternate view for the joint importance of the socio-economic determinants when used for developing policies aimed at preventing future epidemic crises.
Edit intent: meaning-changed
Original:  The obtained map acts as a bridge between theoretical investigations and empirical observations , and offers an alternate view for the joint importance of the socio-economic determinants when used for developing policies aimed at preventing future epidemic crises.
Revised:  The obtained map acts as a bridge between theoretical investigations and empirical observations and offers an alternate view for the joint importance of the socio-economic determinants when used for developing policies aimed at preventing future epidemic crises.
Edit intent: fluency
Original:  In the PROMPT Database, our method yields the accuracy of 74.7\% using 4 seconds of speech data and it improves to 79.0 \% when we use 5 minutes of speech data.
Revised:  In the PROMPT Database, our method yields the accuracy of 74.7\% using 4 seconds of speech data and it improves to 80.8 \% when we use 5 minutes of speech data.
Edit intent: meaning-changed
Original:  In the PROMPT Database, our method yields the accuracy of 74.7\% using 4 seconds of speech data and it improves to 79.0 \% when we use 5 minutes of speech data.
Revised:  In the PROMPT Database, our method yields the accuracy of 74.7\% using 4 seconds of speech data and it improves to 79.0 \% when we use all the patient's speech data.
Edit intent: meaning-changed
Original:  Furthermore, we evaluate our method on a three-class classification problem in which we included the Mild Cognitive Impairment (MCI) class and achieved the accuracy of 60.6\%  .
Revised:  Furthermore, we evaluate our method on a three-class classification problem in which we included the Mild Cognitive Impairment (MCI) class and achieved the accuracy of 60.6\% with 40 seconds of speech data .
Edit intent: meaning-changed
Original: After the first infected patient detected in Wuhan, China in December, 2019 with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, the COVID-19 (CO means corona, VI is virus, D is disease, 19 is the year of discovery) disease spread globally due to its high contagious nature and became an ongoing pandemic.
Revised: The lack of recommended drugs or vaccines to deal with the COVID-19 (CO means corona, VI is virus, D is disease, 19 is the year of discovery) disease spread globally due to its high contagious nature and became an ongoing pandemic.
Edit intent: meaning-changed
Original: After the first infected patient detected in Wuhan, China in December, 2019 with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, the COVID-19 (CO means corona, VI is virus, D is disease, 19 is the year of discovery) disease spread globally due to its high contagious nature and became an ongoing pandemic. Also, the lack of vaccines and efficacious drugs to treat infected patients is a great problem to cope this pandemic.
Revised: After the first infected patient detected in Wuhan, China in December, 2019 with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, the COVID-19 is the main concern of this pandemic.
Edit intent: clarity
Original:  In this communication, molecular docking studies of 18 ligands were carried out with the three important proteins of SARS-CoV-2, i.e., RNA-dependent RNA polymerase (RdRp), angiotensin-converting enzyme 2 (ACE2) and spike glycoprotein (SGp).
Revised:  In this communication, molecular docking studies of 18 ligands were carried out with the three therapeutic target proteins of SARS-CoV-2, i.e., RNA-dependent RNA polymerase (RdRp), angiotensin-converting enzyme 2 (ACE2) and spike glycoprotein (SGp).
Edit intent: meaning-changed
Original:  From the obtained results , we observed that all the tested molecules showed better dock score in compared to the hydroxychloroquine claimed to be effective against COVID-19 . Combining the dock score and other medicinal properties, we believe the limonin can be further explored for potential use against COVID-19.
Revised:  The obtained results revealed that the phytochemicals showed better dock score in compared to the hydroxychloroquine claimed to be effective against COVID-19 . Combining the dock score and other medicinal properties, we believe the limonin can be further explored for potential use against COVID-19.
Edit intent: clarity
Original:  From the obtained results , we observed that all the tested molecules showed better dock score in compared to the hydroxychloroquine claimed to be effective against COVID-19 . Combining the dock score and other medicinal properties, we believe the limonin can be further explored for potential use against COVID-19.
Revised:  From the obtained results , we observed that all the tested molecules showed better dock score in compared to the drugs paracetmol and hydroxychloroquine . Combining the dock score and other medicinal properties, we believe the limonin can be further explored for potential use against COVID-19.
Edit intent: clarity
Original:  From the obtained results , we observed that all the tested molecules showed better dock score in compared to the hydroxychloroquine claimed to be effective against COVID-19 . Combining the dock score and other medicinal properties, we believe the limonin can be further explored for potential use against COVID-19.
Revised:  From the obtained results , we observed that all the tested molecules showed better dock score in compared to the hydroxychloroquine claimed to be effective against COVID-19 . Combining the dock score and medicinal properties, we believe the limonin can be further explored for potential use against COVID-19.
Edit intent: coherence