wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Since infinite solutions honour the data, we show a set of cases by considering different situations. The first set of parameters yields initially a reproduction ratio R0 = 3.33 decreasing to 0.95 in April 8, after the lockdown, but increasing to 1.55 after April 27, most probably due to an increase of the contagion in highly populated slums.
Revised:  Since infinite solutions honour the data, we show different cases. In all of them the reproduction ratio R_0 decreases after early lockdown, but increasing to 1.55 after April 27, most probably due to an increase of the contagion in highly populated slums.
Edit intent: clarity
Original:  The first set of parameters yields initially a reproduction ratio R0 = 3.33 decreasing to 0.95 in April 8, after the lockdown, but increasing to 1.55 after April 27, most probably due to an increase of the contagion in highly populated slums.
Revised:  The first set of parameters yields initially a reproduction ratio R0 = 3.33 decreasing to 0.95 in April 8, after the lockdown, but then raises, probably due to an increase of the contagion in highly populated slums.
Edit intent: meaning-changed
Original:  The first set of parameters yields initially a reproduction ratio R0 = 3.33 decreasing to 0.95 in April 8, after the lockdown, but increasing to 1.55 after April 27, most probably due to an increase of the contagion in highly populated slums.
Revised:  The first set of parameters yields initially a reproduction ratio R0 = 3.33 decreasing to 0.95 in April 8, after the lockdown, but increasing to 1.55 after April 27, most probably due to an increase in contagion in highly populated slums.
Edit intent: clarity
Original:  The infection fatality rate (IFR) is 1.88 \% and the predicted number of casualties is 173000 deaths with 9 million people infected at the end of the epidemic. However, keeping R_0 = 0.95 after April 27, would cause only 1881 casualties and 92955 infected individuals. Other cases, assuming the present trend, predict smaller incubation periods (4-5 days) and yield between 20000 and 70000 deaths and IFRs between 0.5 \% and 1.1 \%. We also consider doubling the number of casualties, with a death toll of 44000 individuals and 5.1 million infected individuals. Other choices of parameters also provide a good fit of the data, indicating the uncertainty of the results, which may differ from reported values. The analysis allows us to study how isolation and social distancing measures affect the time evolution of the epidemic .
Revised:  Therefore it is mandatory to reverse this growing trend in R_0 by applying control strategies to avoid a high number of infectious and dead individuals. The model provides an effective procedure to estimate epidemic parameters (fatality rate, transmission probability, infection and incubation periods) and monitor control measures during the epidemic evolution .
Edit intent: coherence
Original:  Second, ROUGE cannot function without a reference summary, which is expensive or impossible to obtain in many cases . Therefore , we introduce a new end-to-end metric system for summary quality assessment by leveraging the semantic similarities of words and/or sentences in deep learning.
Revised:  Second, ROUGE cannot function without a reference summary, which is expensive or impossible to obtain in many cases , is needed. Existing efforts to address the two drawbacks are done separately and have limitations. To holistically address them , we introduce a new end-to-end metric system for summary quality assessment by leveraging the semantic similarities of words and/or sentences in deep learning.
Edit intent: meaning-changed
Original:  Therefore , we introduce a new end-to-end metric system for summary quality assessment by leveraging the semantic similarities of words and/or sentences in deep learning. Models trained in our framework can evaluate a summary directly against the input document , without the need of a reference summary .
Revised:  Therefore , we introduce a new end-to-end metric system for summary quality assessment by leveraging sentence or document embedding and introducing two negative sampling approaches to create training data for this supervised approach .
Edit intent: meaning-changed
Original:  The proposed approach exhibits very promising results on gold-standard datasets and suggests its great potential to future summarization research. The scores from our models have correlation coefficients up to 0.54 with human evaluations on machine generated summaries in TAC2010.
Revised:  The proposed approach exhibits very promising results on several summarization datasets of various domains including news, legislative bills, scientific papers, and patents. When rating machine-generated summaries in TAC2010, our approach outperforms ROUGE in terms of linguistic quality, and achieves a correlation coefficient of up to 0.5702 with human evaluations on machine generated summaries in TAC2010.
Edit intent: meaning-changed
Original:  The scores from our models have correlation coefficients up to 0.54 with human evaluations on machine generated summaries in TAC2010. Its performance is also very close to ROUGE metrics' .
Revised:  The scores from our models have correlation coefficients up to 0.54 with human evaluations in terms of modified pyramid scores. We hope our approach can facilitate summarization research or applications when reference summaries are infeasible or costly to obtain, or when linguistic quality is a focus .
Edit intent: meaning-changed
Original: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ B \succeq 0} \| A -
Revised: We study the problem of testing whether a matrix \mathbf{A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ B \succeq 0} \| A -
Edit intent: meaning-changed
Original: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ B \succeq 0} \| A -
Revised: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| \mathbf{A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ B \succeq 0} \| A -
Edit intent: meaning-changed
Original: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ B \succeq 0} \| A -
Revised: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in Euclidean distance from the PSD cone, i.e. \min _{ B \succeq 0} \| A -
Edit intent: meaning-changed
Original: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ B \succeq 0} \| A -
Revised: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, meaning that \min _{ B \succeq 0} \| A -
Edit intent: coherence
Original: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ B \succeq 0} \| A -
Revised: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ \mathbf{B \succeq 0} \| A -
Edit intent: meaning-changed
Original: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ B \succeq 0} \| A -
Revised: We study the problem of testing whether a matrix A \in R^{n \times n} with bounded entries (\| A \|_\infty \leq 1) is positive semi-definite (PSD), or \epsilon-far in \ell_2^2-distance from the PSD cone, i.e. \min _{ B \succeq 0} \| \mathbf{A -
Edit intent: meaning-changed
Original:  B \|_F^2 = \sum_{i : \lambda_i(A) < 0 \lambda_i^2(A) } > \epsilon n^2  \succeq 0 denotes that \mathbf{B} is PSD} . Our main algorithmic contribution is a non-adaptive tester which distinguishes between these cases using only \tilde{O}(1/\epsilon^4) queries to the entries of A.
Revised:  \mathbf{B \|_F^2 = \sum_{i : \lambda_i(A) < 0 \lambda_i^2(A) } > \epsilon n^2 \succeq 0 denotes that \mathbf{B} is PSD} . Our main algorithmic contribution is a non-adaptive tester which distinguishes between these cases using only \tilde{O}(1/\epsilon^4) queries to the entries of A.
Edit intent: meaning-changed
Original:  B \|_F^2 = \sum_{i : \lambda_i(A) < 0 \lambda_i^2(A) } > \epsilon n^2  \succeq 0 denotes that \mathbf{B} is PSD} . Our main algorithmic contribution is a non-adaptive tester which distinguishes between these cases using only \tilde{O}(1/\epsilon^4) queries to the entries of A.
Revised:  B \|_F^2 \lambda_i^2(A) } > \epsilon n^2 \succeq 0 denotes that \mathbf{B} is PSD} . Our main algorithmic contribution is a non-adaptive tester which distinguishes between these cases using only \tilde{O}(1/\epsilon^4) queries to the entries of A.
Edit intent: clarity
Original:  B \|_F^2 = \sum_{i : \lambda_i(A) < 0 \lambda_i^2(A) } > \epsilon n^2  \succeq 0 denotes that \mathbf{B} is PSD} . Our main algorithmic contribution is a non-adaptive tester which distinguishes between these cases using only \tilde{O}(1/\epsilon^4) queries to the entries of A.
Revised:  B \|_F^2 = \sum_{i : \lambda_i(A) < 0 \lambda_i^2(A) } > \epsilon n^2 , where \mathbf{B \succeq 0 denotes that \mathbf{B} is PSD} . Our main algorithmic contribution is a non-adaptive tester which distinguishes between these cases using only \tilde{O}(1/\epsilon^4) queries to the entries of A.
Edit intent: meaning-changed
Original:  B \|_F^2 = \sum_{i : \lambda_i(A) < 0 \lambda_i^2(A) } > \epsilon n^2  \succeq 0 denotes that \mathbf{B} is PSD} . Our main algorithmic contribution is a non-adaptive tester which distinguishes between these cases using only \tilde{O}(1/\epsilon^4) queries to the entries of A. For the related "\ell_\infty-gap problem", where A is either PSD or has an eigenvalue satisfying \lambda_i(A) <\succeq 0} \|\mathbf{A}} - \epsilon n, our algorithm only requires\|_2 > \epsilon n.
Revised:  B \|_F^2 = \sum_{i : \lambda_i(A) < 0 \lambda_i^2(A) } > \epsilon n^2 \succeq 0 denotes that \mathbf{B} is PSD} . Our main algorithmic contribution is a non-adaptive tester which distinguishes between these cases using only \tilde{O}(1/\epsilon^4) queries to the entries of \mathbf{A "\ell_\infty-gap problem", where A is either PSD or has an eigenvalue satisfying \lambda_i(A) <\succeq 0} \|\mathbf{A}} - \epsilon n, our algorithm only requires\|_2 > \epsilon n.
Edit intent: meaning-changed
Original:  For the related "\ell_\infty-gap problem", where A is either PSD or has an eigenvalue satisfying \lambda_i(A) <\succeq 0} \|\mathbf{A}} - \epsilon n, our algorithm only requires\|_2 > \epsilon n.
Revised:  For the related "\ell_\infty-gap problem", where \mathbf{A is either PSD or has an eigenvalue satisfying \lambda_i(A) <\succeq 0} \|\mathbf{A}} - \epsilon n, our algorithm only requires\|_2 > \epsilon n.
Edit intent: meaning-changed
Original:  For the related "\ell_\infty-gap problem", where A is either PSD or has an eigenvalue satisfying \lambda_i(A) <\succeq 0} \|\mathbf{A}} - \epsilon n, our algorithm only requires\|_2 > \epsilon n.
Revised:  For the related "\ell_\infty-gap problem", where A is either PSD or satisfies \min_{\mathbf{B\succeq 0} \|\mathbf{A}} - \epsilon n, our algorithm only requires\|_2 > \epsilon n.
Edit intent: meaning-changed
Original:  For the related "\ell_\infty-gap problem", where A is either PSD or has an eigenvalue satisfying \lambda_i(A) <\succeq 0} \|\mathbf{A}} - \epsilon n, our algorithm only requires\|_2 > \epsilon n.
Revised:  For the related "\ell_\infty-gap problem", where A is either PSD or has an eigenvalue satisfying \lambda_i(A) <\succeq 0} \|\mathbf{A}} - \mathbf{B\|_2 > \epsilon n.
Edit intent: meaning-changed
Original:  We complement our upper bound for PSD testing with \ell_2^2-gap by giving a \tilde{\Omega}(1/\epsilon^2) lower bound for any non-adaptive algorithm.
Revised:  We complement our upper bound for PSD testing with Euclidean norm distance by giving a \tilde{\Omega}(1/\epsilon^2) lower bound for any non-adaptive algorithm.
Edit intent: meaning-changed
Original:  As an example of the applicability of our construction, we obtain a new \tilde{\Omega}(1/\epsilon^4) sampling lower bound for testing the Schatten-1 norm with a \epsilon  ^{1.5} gap, extending a result of Balcan, Li, Woodruff, and Zhang [SODA'19].
Revised:  As an example of the applicability of our construction, we obtain a new \tilde{\Omega}(1/\epsilon^4) sampling lower bound for testing the Schatten-1 norm with a \epsilon n ^{1.5} gap, extending a result of Balcan, Li, Woodruff, and Zhang [SODA'19].
Edit intent: meaning-changed
Original:  In addition, our hard instance results in new sampling lower bounds for estimating the Ky-Fan Norm, and the cost of  rank-k approximations, i.e. \|A - A_k\|_F^2 = \sum_{i > k \sigma_i^2(A)}  .
Revised:  In addition, it yields new sampling lower bounds for estimating the Ky-Fan Norm, and the cost of rank-k approximations, i.e. \|A - A_k\|_F^2 = \sum_{i > k \sigma_i^2(A)} .
Edit intent: clarity
Original:  In addition, our hard instance results in new sampling lower bounds for estimating the Ky-Fan Norm, and the cost of  rank-k approximations, i.e. \|A - A_k\|_F^2 = \sum_{i > k \sigma_i^2(A)}  .
Revised:  In addition, our hard instance results in new sampling lower bounds for estimating the Ky-Fan Norm, and the cost of the best rank-k approximations, i.e. \|A - A_k\|_F^2 = \sum_{i > k \sigma_i^2(A)} .
Edit intent: clarity
Original:  In addition, our hard instance results in new sampling lower bounds for estimating the Ky-Fan Norm, and the cost of  rank-k approximations, i.e. \|A - A_k\|_F^2 = \sum_{i > k \sigma_i^2(A)}  .
Revised:  In addition, our hard instance results in new sampling lower bounds for estimating the Ky-Fan Norm, and the cost of rank-k \sigma_i^2(A)} .
Edit intent: clarity
Original:  In addition, our hard instance results in new sampling lower bounds for estimating the Ky-Fan Norm, and the cost of  rank-k approximations, i.e. \|A - A_k\|_F^2 = \sum_{i > k \sigma_i^2(A)}  .
Revised:  In addition, our hard instance results in new sampling lower bounds for estimating the Ky-Fan Norm, and the cost of rank-k approximations, i.e. \|A - A_k\|_F^2 = \sum_{i > k \sigma_i^2(A)} approximation .
Edit intent: meaning-changed
Original: We present a family of alchemical perturbation potentials that allow the calculation of hydration free energy of small to medium-sized molecules in a single perturbation step . We also present a general framework to optimize the parameters of the alchemical perturbation potentials based on avoiding first order pseudo phase transitions along the alchemical path.
Revised: We present a family of alchemical perturbation potentials that allow the calculation of hydration free energy of small to medium-sized molecules in a concerted single alchemical coupling step instead of the commonly used sequence of two distinct coupling steps for Lennard-Jones and electrostatic interactions. The perturbation potentials are based on the softplus function of the solute-solvent interaction energy designed to focus sampling near entropic bottlenecks along the alchemical pathway. We present a general framework to optimize the parameters of the alchemical perturbation potentials based on avoiding first order pseudo phase transitions along the alchemical path.
Edit intent: meaning-changed
Original:  We also present a general framework to optimize the parameters of the alchemical perturbation potentials based on avoiding first order pseudo phase transitions along the alchemical path.
Revised:  We also present a general framework to optimize the parameters of the alchemical perturbation potentials of this kind. The optimization procedure is based on the \lambda-function formalism and the maximum-likelihood parameter estimation procedure we developed earlier to avoid the occurrence of multi-modal distributions of the coupling energy along the alchemical path.
Edit intent: meaning-changed
Original:   We illustrate the method for two compounds of increasing size and complexity : ethanol and 1-naphtol .
Revised:  A novel soft-core function applied to the overall solute-solvent interaction energy rather than individual interatomic pair potentials critical for this result is also presented. Because it does not require modifications of core force and energy routines, the soft-core formulation can be easily deployed in molecular dynamics simulation codes. We illustrate the method for two compounds of increasing size and complexity : ethanol and 1-naphtol .
Edit intent: meaning-changed
Original: We consider here an extended SIR model, including several features of the recent COVID-19 outbreak: in particular the infected and recovered individuals can either be detected (+) or undetected (-) and we also integrate an intensive care unit  capacity.
Revised: We consider here an extended SIR model, including several features of the recent COVID-19 outbreak: in particular the infected and recovered individuals can either be detected (+) or undetected (-) and we also integrate an intensive care unit (ICU) capacity.
Edit intent: clarity
Original:  With parametric specification based on literature on COVID-19, we investigate sensitivity of various quantities on  optimal strategies, taking into account the subtle tradeoff between the sanitary and the economic cost of the pandemic, together with the limited capacity level of ICU.
Revised:  With parametric specification based on literature on COVID-19, we investigate the sensitivities of various quantities on optimal strategies, taking into account the subtle tradeoff between the sanitary and the economic cost of the pandemic, together with the limited capacity level of ICU.
Edit intent: clarity
Original:  With parametric specification based on literature on COVID-19, we investigate sensitivity of various quantities on  optimal strategies, taking into account the subtle tradeoff between the sanitary and the economic cost of the pandemic, together with the limited capacity level of ICU.
Revised:  With parametric specification based on literature on COVID-19, we investigate sensitivity of various quantities on the optimal strategies, taking into account the subtle tradeoff between the sanitary and the economic cost of the pandemic, together with the limited capacity level of ICU.
Edit intent: fluency
Original:  With parametric specification based on literature on COVID-19, we investigate sensitivity of various quantities on  optimal strategies, taking into account the subtle tradeoff between the sanitary and the economic cost of the pandemic, together with the limited capacity level of ICU.
Revised:  With parametric specification based on literature on COVID-19, we investigate sensitivity of various quantities on optimal strategies, taking into account the subtle trade-off between the sanitary and the economic cost of the pandemic, together with the limited capacity level of ICU.
Edit intent: fluency
Original:  With parametric specification based on literature on COVID-19, we investigate sensitivity of various quantities on  optimal strategies, taking into account the subtle tradeoff between the sanitary and the economic cost of the pandemic, together with the limited capacity level of ICU.
Revised:  With parametric specification based on literature on COVID-19, we investigate sensitivity of various quantities on optimal strategies, taking into account the subtle tradeoff between the sanitary and the socio-economic cost of the pandemic, together with the limited capacity level of ICU.
Edit intent: clarity
Original:   We also provide optimal intervention measures with increasing ICU capacity, as well as optimization over the effort on detection of infectious and immune individuals  .
Revised:  We also provide optimal intervention measures with increasing ICU capacity, as well as optimization over the effort on detection of infectious and immune individuals . Whenever massive resources are introduced to detect infected individuals, the pressure on social distancing can be released, whereas the impact of detection of immune individuals reveals to be more moderate .
Edit intent: meaning-changed
Original:  To better understand the what impact these genetic variants in immune response genes may have in the differences observed in the immune response to SARS-CoV-2, a quantitative analysis of a dynamical systems model that considers both, the magnitude of viral growth, and the subsequent innate and adaptive response required to achieve control of infection is considered.
Revised:  To better understand what impact these genetic variants in immune response genes may have in the differences observed in the immune response to SARS-CoV-2, a quantitative analysis of a dynamical systems model that considers both, the magnitude of viral growth, and the subsequent innate and adaptive response required to achieve control of infection is considered.
Edit intent: fluency
Original:  In asymptomatic patients  prompt and adequate adaptive immune response quells infection, whereas in those with severe symptoms a slower inadequate adaptive response leads to a runaway cytokine cascade fueled by ongoing viral replication.
Revised:  In asymptomatic patients , prompt and adequate adaptive immune response quells infection, whereas in those with severe symptoms a slower inadequate adaptive response leads to a runaway cytokine cascade fueled by ongoing viral replication.
Edit intent: fluency
Original:  These models involve ratios of evolutionary timescales to branching fractions, assumed uniform throughout a country, and the basic reproduction number, R0 , before and during the national lockdown, for each region of France.
Revised:  These models involve ratios of evolutionary timescales to branching fractions, assumed uniform throughout a country, and the basic reproduction number, R_0 , before and during the national lockdown, for each region of France.
Edit intent: clarity
Original:  The basic reproductive factor was R0 =3.4 +/-0.1 \pm0 before the lockdown and 0.65 +/-0.04 \pm0 (90\% c.l.) during it, both with small regional variations.
Revised:  The basic reproductive factor , averaged over France, was R_0 =3.4 +/-0.1 \pm0 before the lockdown and 0.65 +/-0.04 \pm0 (90\% c.l.) during it, both with small regional variations.
Edit intent: meaning-changed
Original:  The basic reproductive factor was R0 =3.4 +/-0.1 \pm0 before the lockdown and 0.65 +/-0.04 \pm0 (90\% c.l.) during it, both with small regional variations.
Revised:  The basic reproductive factor was R0 =3.4 \pm0 before the lockdown and 0.65 +/-0.04 \pm0 (90\% c.l.) during it, both with small regional variations.
Edit intent: meaning-changed
Original:  The basic reproductive factor was R0 =3.4 +/-0.1 \pm0 before the lockdown and 0.65 +/-0.04 \pm0 (90\% c.l.) during it, both with small regional variations.
Revised:  The basic reproductive factor was R0 =3.4 +/-0.1 \pm0.1 before the lockdown and 0.65 +/-0.04 \pm0 (90\% c.l.) during it, both with small regional variations.
Edit intent: meaning-changed