wanyu/IteraTeR_v2 huggingface dataset:
Original:  We correct a previously published claim that PM is not based on a minimax game.
Revised:  I correct a previously published claim that PM is not based on a minimax game.
Edit intent: fluency
Original: We investigate the changes in the patterns of usage in the Divvy bikeshare system in Chicago from 2016-2018.
Revised: We investigate changes in patterns of usage in the Divvy bikeshare system in Chicago from 2016-2018.
Edit intent: fluency
Original: We investigate the changes in the patterns of usage in the Divvy bikeshare system in Chicago from 2016-2018.
Revised: We investigate the changes in the patterns of usage in the Divvy bikeshare system in Chicago from 2016-2018.
Edit intent: fluency
Original:  We use an iterative testing approach that is augmented by trend testing and a novel temporal false-discovery-rate correction  . Results show stark geographical patterns in clusters that are growing and declining in relative bike-share usage across time and may elucidate latent economic or demographic trends.
Revised:  The method is based on an iterative testing approach that is augmented by trend testing and a novel temporal false-discovery-rate correction . Results show stark geographical patterns in clusters that are growing and declining in relative bike-share usage across time and may elucidate latent economic or demographic trends.
Edit intent: clarity
Original:  We use an iterative testing approach that is augmented by trend testing and a novel temporal false-discovery-rate correction  . Results show stark geographical patterns in clusters that are growing and declining in relative bike-share usage across time and may elucidate latent economic or demographic trends.
Revised:  We use an iterative testing approach that is augmented by trend testing and a novel time-dependent false-discovery-rate correction . Results show stark geographical patterns in clusters that are growing and declining in relative bike-share usage across time and may elucidate latent economic or demographic trends.
Edit intent: clarity
Original:  In addition, we introduce a method of correcting for estimated forgone trips due to full or empty stations in high-activity areas . Results show stark geographical patterns in clusters that are growing and declining in relative bike-share usage across time and may elucidate latent economic or demographic trends.
Revised:  In addition, we introduce a method of correcting for estimated forgone trips due to full or empty stations in high-activity areas . Results show stark geographical patterns in clusters that are growing and declining in relative usage across time and may elucidate latent economic or demographic trends.
Edit intent: clarity
Original:  In addition, we introduce a method of correcting for estimated forgone trips due to full or empty stations in high-activity areas . Results show stark geographical patterns in clusters that are growing and declining in relative bike-share usage across time and may elucidate latent economic or demographic trends.
Revised:  In addition, we introduce a method of correcting for estimated forgone trips due to full or empty stations in high-activity areas . Results show stark geographical patterns in clusters that are growing and declining in relative bike-share usage across time and potentially elucidate latent economic or demographic trends.
Edit intent: clarity
Original: Despite a very effective vaccine , active conflict and community distrust during the ongoing DRC Ebola epidemic are undermining control efforts, including a ring vaccination strategy.
Revised: Despite a very effective vaccine , active conflict and community distrust are undermining control efforts, including a ring vaccination strategy.
Edit intent: clarity
Original:  To assess the impact of vaccination strategies for controlling Ebola epidemics in the context of variable levels of community resistance, we employed an individual-level stochastic transmission model.
Revised:  To assess the impact of vaccination strategies on epidemic control in the context of variable levels of community resistance, we employed an individual-level stochastic transmission model.
Edit intent: clarity
Original:  Our key results are that as levels of inaccessibility increase, there is a qualitative change in the effectiveness of the vaccination strategy.
Edit intent: coherence
Original:  For lower levels of inaccessibility, the probability of epidemic containment increases over time , even if probabilities are lower than they would be otherwise .
Revised:  For lower levels of inaccessibility, the probability of epidemic containment increases over time .
Edit intent: clarity
Original:  Our results underscore the need to enhance community engagement to public health interventions.
Revised:  Our findings underscore the need to enhance community engagement to public health interventions.
Edit intent: clarity
Original: The objective of this technical report is to describe the framework used in Task 1, Acoustic scene classification (ASC) , of the DCASE 2019 challenge.
Revised:  Acoustic scene classification (ASC) , of the DCASE 2019 challenge.
Edit intent: clarity
Original:  Also, in order to improve accuracy, ensemble methods combining different model predictions with different inputs are explored.
Revised:  Also, in order to increase the final accuracy. Even though averaging different model predictions with different inputs are explored.
Edit intent: clarity
Original:  Besides geometric and arithmetic means, ensembles aggregated with the Orness Weighted Averaged (OWA) operator have shown interesting andnovel results.
Revised:  Besides geometric and arithmetic mean plus the Ordered Weighted Averaging (OWA) operator have shown interesting andnovel results.
Edit intent: clarity
Original:  Finally, two numerical experiments are presented to illustrate the efficiency of the theoretical findings.
Revised:  Finally, two numerical experiments are presented to illustrate the theoretical findings.
Edit intent: clarity
Original:  A Crank-Nicolson Galerkin method is applied to the least squares functional with  quadratic stabilizing penalty term.
Revised:  A Crank-Nicolson Galerkin method is applied to the least squares functional with an quadratic stabilizing penalty term.
Edit intent: fluency
Original:  The convergence of finite dimensional regularized approximations to the sought source as measurement noise levels and mesh sizes approach to zero with  appropriate regularization parameter is proved.
Revised:  The convergence of finite dimensional regularized approximations to the sought source as measurement noise levels and mesh sizes approach to zero with an appropriate regularization parameter is proved.
Edit intent: fluency
Original:  Recently , however, practitioners and researchers have also considered Low-Power Wide-Area Networks (LPWAN) like LoRaWAN for such applications.
Revised:  Recently practitioners and researchers have also considered Low-Power Wide-Area Networks (LPWAN) like LoRaWAN for such applications.
Edit intent: coherence
Original:  Recently , however, practitioners and researchers have also considered Low-Power Wide-Area Networks (LPWAN) like LoRaWAN for such applications.
Revised:  Recently , however, practitioners and researchers have considered Low-Power Wide-Area Networks (LPWAN) like LoRaWAN for such applications.
Edit intent: clarity
Original:  Recently , however, practitioners and researchers have also considered Low-Power Wide-Area Networks (LPWAN) like LoRaWAN for such applications.
Revised:  Recently , however, practitioners and researchers have also considered Low-Power Wide-Area Networks (LPWAN) like LoRaWAN for SUN applications.
Edit intent: clarity
Original:  This paper builds over a LoRaWAN model to optimize network parameters while accounting for the interferencefrom other technologies .
Revised:  This paper builds over a LoRaWAN model to optimize network parameters while accounting for inter-technology interference .
Edit intent: clarity
Original:  Our analytic model accounts for the interference LoRaWAN receives from IEEE 802.15.4g networks, which form the bottom layers of Wi-SUN systems.
Revised:  Our analytic model accounts for the interference LoRaWAN receives from IEEE 802.15.4g networks, which forms the bottom layers of Wi-SUN systems.
Edit intent: fluency
Original:  We also derive closed-form equations for the expected reliability of LoRaWAN in such scenarios.
Revised:  We derive closed-form equations for the expected reliability of LoRaWAN in such scenarios.
Edit intent: clarity
Original:  Finally, we propose two optimization algorithms to determine the best LoRaWAN configuration given a targeted minimum reliability level as a restriction.
Revised:  Finally, we propose two optimization algorithms to determine the best LoRaWAN configurations, given a targeted minimum reliability level as a restriction.
Edit intent: fluency
Original:  The first algorithm maximizes communication range given a constraint on the minimum number of users , and the second maximizes the number of users given a minimum communication range  .
Revised:  The first algorithm maximizes communication range given a constraint on the minimum number of users given constraints on the minimum number of users given a minimum communication range .
Edit intent: coherence
Original:  The first algorithm maximizes communication range given a constraint on the minimum number of users , and the second maximizes the number of users given a minimum communication range  .
Revised:  The first algorithm maximizes communication range given a constraint on the minimum number of users , and the second maximizes the number of users , minimum communication range .
Edit intent: fluency
Original:  Remarkably, this gradient calculation achieves computational complexity that scales only linearly with the number of taxa under study.
Revised:  Our gradient calculation achieves computational complexity that scales only linearly with the number of taxa under study.
Edit intent: coherence
Original:  Our method achieves an over 300-fold speed increase over the univariable approach.
Revised:  Our method achieves an over 300-fold speed-increase over the univariable approach.
Edit intent: fluency
Original: Convolutional neural network is a very important model of deep learning.
Revised: Convolutional neural network is an important model in deep learning.
Edit intent: clarity
Original:  It can help avoid the exploding/vanishing gradient problem and improve the generalizability of a neural network if the singular values of the Jacobian of a layer are bounded around 1 in the training process.
Revised:  To avoid exploding/vanishing gradient problem and improve the generalizability of a neural network if the singular values of the Jacobian of a layer are bounded around 1 in the training process.
Edit intent: clarity
Original:  It can help avoid the exploding/vanishing gradient problem and improve the generalizability of a neural network if the singular values of the Jacobian of a layer are bounded around 1 in the training process.
Revised:  It can help avoid the exploding/vanishing gradient problems and to improve the generalizability of a neural network if the singular values of the Jacobian of a layer are bounded around 1 in the training process.
Edit intent: fluency
Original:  It can help avoid the exploding/vanishing gradient problem and improve the generalizability of a neural network if the singular values of the Jacobian of a layer are bounded around 1 in the training process.
Revised:  It can help avoid the exploding/vanishing gradient problem and improve the generalizability of a neural network if the singular values of the transformation matrix corresponding to a convolutional kernel bounded around 1.
Edit intent: clarity
Original:  We propose a new penalty function for a convolutional kernel to let the singular values of the corresponding transformation matrix are bounded around 1.
Revised:  We propose a penalty function that can be used in the optimization of a convolutional neural network to constrain the singular values of the corresponding transformation matrix are bounded around 1.
Edit intent: clarity
Original:  We propose a new penalty function for a convolutional kernel to let the singular values of the corresponding transformation matrix are bounded around 1.
Revised:  We propose a new penalty function for a convolutional kernel to let the singular values of the transformation matrix around 1.
Edit intent: clarity
Original:  We show how to carry out the gradient type methods.
Revised:  We derive an algorithm to carry out the gradient type methods.
Edit intent: clarity
Original:  Building upon the Faber operator series we recently developed for the orthogonal dynamics propagator, and an exact combinatorial algorithm that allows us to compute memory kernels to any desired accuracy from first principles, we demonstrate that the proposed method is effective in computing auto-correlation functions, intermediate scattering functions and other important statistical properties of the observables .
Revised:  Building upon the Faber operator series we recently developed for the orthogonal dynamics propagator, and an exact combinatorial algorithm that allows us to compute memory kernels from first principles, we demonstrate that the proposed method is effective in computing auto-correlation functions, intermediate scattering functions and other important statistical properties of the observables .
Edit intent: clarity
Original:  Building upon the Faber operator series we recently developed for the orthogonal dynamics propagator, and an exact combinatorial algorithm that allows us to compute memory kernels to any desired accuracy from first principles, we demonstrate that the proposed method is effective in computing auto-correlation functions, intermediate scattering functions and other important statistical properties of the observables .
Revised:  Building upon the Faber operator series we recently developed for the orthogonal dynamics propagator, and an exact combinatorial algorithm that allows us to compute memory kernels to any desired accuracy from first principles, we demonstrate that the proposed method is effective in computing auto-correlation functions, intermediate scattering functions and other important statistical properties of the observable .
Edit intent: fluency
Original:  Numerical applications are presented for the Fermi-Pasta-Ulam model, and for random wave propagation in homegeneous media.
Revised:  Numerical applications are presented for the Fermi-Pasta-Ulam model, and for random wave propagation in homogeneous media.
Edit intent: fluency
Original: Motivation: Graph embedding learning which aims to automatically learn low-dimensional node representations has drawn increasing attention in recent years.
Revised:  Graph embedding learning which aims to automatically learn low-dimensional node representations has drawn increasing attention in recent years.
Edit intent: coherence
Original:  To date, most recent graph embedding methods are mainly evaluated on social and information networks and have yet to be comprehensively studied on biomedical networks under systematic experiments and analyses.
Revised:  To date, most recent graph embedding methods are mainly evaluated on social and information networks and have not been comprehensively studied on biomedical networks under systematic experiments and analyses.
Edit intent: clarity
Original:  On the other hand, for a variety of biomedical network analysis tasks, traditional techniques such as matrix factorization (which can be seen as one type of graph embedding methods) have shown promising results, and hence there is a need to systematically evaluate  more recent graph embedding methods (e.g., random walk-based and neural network-based) in terms of their usability and potential to further the state-of-the-art.
Revised:  On the other hand, for a variety of biomedical network analysis tasks, traditional techniques such as matrix factorization have shown promising results, and hence there is a need to systematically evaluate more recent graph embedding methods (e.g., random walk-based and neural network-based) in terms of their usability and potential to further the state-of-the-art.
Edit intent: coherence
Original:  On the other hand, for a variety of biomedical network analysis tasks, traditional techniques such as matrix factorization (which can be seen as one type of graph embedding methods) have shown promising results, and hence there is a need to systematically evaluate  more recent graph embedding methods (e.g., random walk-based and neural network-based) in terms of their usability and potential to further the state-of-the-art.
Revised:  On the other hand, for a variety of biomedical network analysis tasks, traditional techniques such as matrix factorization (which can be seen as one type of graph embedding methods) have shown promising results, and hence there is a need to systematically evaluate the more recent graph embedding methods (e.g., random walk-based and neural network-based) in terms of their usability and potential to further the state-of-the-art.
Edit intent: fluency
Original:  Results: We conduct a systematic comparison of existing graph embedding methods on three important biomedical link prediction tasks: drug-disease association (DDA) prediction, drug-drug interaction (DDI) prediction, protein-protein interaction (PPI) prediction, and one node classification task, i. e., classifying the semantic types of medical terms (nodes).
Revised:  Results: We conduct a systematic comparison on three important biomedical link prediction tasks: drug-disease association (DDA) prediction, drug-drug interaction (DDI) prediction, protein-protein interaction (PPI) prediction, and one node classification task, i. e., classifying the semantic types of medical terms (nodes).
Edit intent: clarity
Original:  Results: We conduct a systematic comparison of existing graph embedding methods on three important biomedical link prediction tasks: drug-disease association (DDA) prediction, drug-drug interaction (DDI) prediction, protein-protein interaction (PPI) prediction, and one node classification task, i. e., classifying the semantic types of medical terms (nodes).
Revised:  Results: We conduct a systematic comparison of existing graph embedding methods on three important biomedical link prediction tasks: drug-disease association prediction, drug-drug interaction (DDI) prediction, protein-protein interaction (PPI) prediction, and one node classification task, i. e., classifying the semantic types of medical terms (nodes).
Edit intent: clarity
Original:  Results: We conduct a systematic comparison of existing graph embedding methods on three important biomedical link prediction tasks: drug-disease association (DDA) prediction, drug-drug interaction (DDI) prediction, protein-protein interaction (PPI) prediction, and one node classification task, i. e., classifying the semantic types of medical terms (nodes).
Revised:  Results: We conduct a systematic comparison of existing graph embedding methods on three important biomedical link prediction tasks: drug-disease association (DDA) prediction, drug-drug interaction prediction, protein-protein interaction (PPI) prediction, and one node classification task, i. e., classifying the semantic types of medical terms (nodes).
Edit intent: fluency
Original:  Results: We conduct a systematic comparison of existing graph embedding methods on three important biomedical link prediction tasks: drug-disease association (DDA) prediction, drug-drug interaction (DDI) prediction, protein-protein interaction (PPI) prediction, and one node classification task, i. e., classifying the semantic types of medical terms (nodes).
Revised:  Results: We conduct a systematic comparison of existing graph embedding methods on three important biomedical link prediction tasks: drug-disease association (DDA) prediction, drug-drug interaction (DDI) prediction, protein-protein interaction prediction, and one node classification task, i. e., classifying the semantic types of medical terms (nodes).
Edit intent: fluency
Original:  Our experimental results demonstrate that the recent graph embedding methods are generally more effective than traditional embedding methods . Besides, compared with two state-of-the-art methods for DDAs and DDIs predictions, graph embedding methods  without using any biological features achieve very competitive performance.
Revised:  Our experimental results demonstrate that the recent graph embedding methods are generally more effective than traditional embedding methods . Besides, compared with two state-of-the-art methods for DDAs and DDIs predictions, graph embedding methods achieve competitive performance without using any biological features achieve very competitive performance.
Edit intent: fluency
Original:  Availability: We develop an easy-to-use Python package with detailed instructions, BioNEV, available URL including all source code and datasets, to facilitate studying various graph embedding methods on biomedical tasks 
Revised:  Availability: We develop an easy-to-use Python package with detailed instructions, BioNEV, including all source code and datasets, to facilitate studying various graph embedding methods on biomedical tasks 
Edit intent: coherence
Original:  Availability: We develop an easy-to-use Python package with detailed instructions, BioNEV, available URL including all source code and datasets, to facilitate studying various graph embedding methods on biomedical tasks 
Revised:  Availability: We develop an easy-to-use Python package with detailed instructions, BioNEV, available URL including all source code and datasets, to facilitate studying various graph embedding methods on biomedical tasks .
Edit intent: fluency
Original: Graph embedding learning which aims to automatically learn low-dimensional node representations  has drawn increasing attention in recent years.
Revised: Graph embedding learning that aims to automatically learn low-dimensional node representations has drawn increasing attention in recent years.
Edit intent: fluency
Original: Graph embedding learning which aims to automatically learn low-dimensional node representations  has drawn increasing attention in recent years.
Revised: Graph embedding learning which aims to automatically learn low-dimensional node representations , has drawn increasing attention in recent years.
Edit intent: fluency
Original:  To date, most recent graph embedding methods are mainly evaluated on social and information networks and have not been comprehensively studied on biomedical networks under systematic experiments and analyses.
Revised:  To date, most recent graph embedding methods are evaluated on social and information networks and have not been comprehensively studied on biomedical networks under systematic experiments and analyses.
Edit intent: coherence
Original:  To date, most recent graph embedding methods are mainly evaluated on social and information networks and have not been comprehensively studied on biomedical networks under systematic experiments and analyses.
Revised:  To date, most recent graph embedding methods are mainly evaluated on social and information networks and are not comprehensively studied on biomedical networks under systematic experiments and analyses.
Edit intent: clarity
Original:  On the other hand, for a variety of biomedical network analysis tasks, traditional techniques such as matrix factorization  have shown promising results, and hence there is a need to systematically evaluate the more recent graph embedding methods (e.g. , random walk-based and neural network-based) in terms of their usability and potential to further the state-of-the-art.
Revised:  On the other hand, for a variety of biomedical network analysis tasks, traditional techniques such as matrix factorization have shown promising results, and hence there is a need to systematically evaluate the more recent graph embedding methods (e.g. random walk-based and neural network-based) in terms of their usability and potential to further the state-of-the-art.
Edit intent: fluency