wanyu/IteraTeR_v2 huggingface dataset:
Original:  Our results indicate that these small drug molecules selectively bind to kinetically active and residues adjoining them on the surface  and inside protein  , and that some prefer hydrophobic over other active sites.
Revised:  Our results indicate that these small drug molecules selectively bind to kinetically active and residues adjoining them on the surface and inside protein pockets , and that some prefer hydrophobic over other active sites.
Edit intent: clarity
Original: We report  results of our study of approved drugs as potential treatments for COVID 19, based on the application of various bioinformatics predictive methods.
Revised: We report the results of our study of approved drugs as potential treatments for COVID 19, based on the application of various bioinformatics predictive methods.
Edit intent: fluency
Original:  In contrast, our approach leverages a generative model to synthesize label maps and gray-scale images that expose a network to a wide range of anatomy and contrast during training.
Revised:  In contrast, our approach leverages a generative model for diverse label maps and gray-scale images that expose a network to a wide range of anatomy and contrast during training.
Edit intent: clarity
Original:  In contrast, our approach leverages a generative model to synthesize label maps and gray-scale images that expose a network to a wide range of anatomy and contrast during training.
Revised:  In contrast, our approach leverages a generative model to synthesize label maps and images that exposes networks to a wide range of anatomy and contrast during training.
Edit intent: clarity
Original:  We demonstrate that this strategy enables robust registration of arbitrary modalities, without the need to retrain for a new modality.
Revised:  We demonstrate that this strategy enables robust registration of arbitrary image contrasts without the need to retrain for a new modality.
Edit intent: clarity
Original:  Our code is integrated with the VoxelMorph library at: URL
Revised:  Our code is available at: URL
Edit intent: clarity
Original: We introduce a learning strategy for contrast-invariant image registration without requiring imaging data .
Revised: We introduce a strategy for learning image registration without requiring imaging data .
Edit intent: clarity
Original:  While classical registration methods accurately estimate the spatial correspondence between images, they solve a costly optimization problem for every  image pair.
Revised:  While classical registration methods accurately estimate the spatial correspondence between images, they solve an optimization problem for every image pair.
Edit intent: clarity
Original:  Learning-based techniques are fast at test time , but can only register images with image contrast and geometric content that are similar to those available during training.
Revised:  Learning-based techniques are fast at test time but limited to registering images with contrasts and geometric content that are similar to those available during training.
Edit intent: clarity
Original:  Learning-based techniques are fast at test time , but can only register images with image contrast and geometric content that are similar to those available during training.
Revised:  Learning-based techniques are fast at test time , but can only register images with image contrast and geometric content similar to those available during training.
Edit intent: fluency
Original:  Learning-based techniques are fast at test time , but can only register images with image contrast and geometric content that are similar to those available during training.
Revised:  Learning-based techniques are fast at test time , but can only register images with image contrast and geometric content that are similar to those seen during training.
Edit intent: clarity
Original:  Our approach leverages a generative model for diverse label maps and images that exposes networks to a wide range of variability during training , forcing them to learn features invariant to image type (contrast).
Revised:  Our approach leverages a generative model for diverse label maps and images that exposes networks to a wide range of variability , forcing them to learn features invariant to image type (contrast).
Edit intent: clarity
Original:  This strategy results in powerful networks trained to generalize to a broad array of real input images .
Revised:  This strategy results in powerful networks that accurately generalize to a broad array of real input images .
Edit intent: clarity
Original:  We present extensive experiments , with a focus on 3D neuroimaging, showing that this strategy enables robust  registration of arbitrary image contrasts without the need to retrain for new modalities .
Revised:  We present extensive experiments with a focus on 3D neuroimaging, showing that this strategy enables robust registration of arbitrary image contrasts without the need to retrain for new modalities .
Edit intent: fluency
Original:  We present extensive experiments , with a focus on 3D neuroimaging, showing that this strategy enables robust  registration of arbitrary image contrasts without the need to retrain for new modalities .
Revised:  We present extensive experiments , with a focus on 3D neuroimaging, showing that this strategy enables robust and accurate registration of arbitrary image contrasts without the need to retrain for new modalities .
Edit intent: clarity
Original:  We demonstrate registration accuracy that most often surpasses the state of the art both within and across modalities , using a single model.
Revised:  We demonstrate registration accuracy surpassing the state of the art both within and across modalities , using a single model.
Edit intent: clarity
Original:  We demonstrate registration accuracy that most often surpasses the state of the art both within and across modalities , using a single model.
Revised:  We demonstrate registration accuracy that most often surpasses the state of the art both within and across contrasts , using a single model.
Edit intent: clarity
Original:  Critically, we show that input labels from which we synthesize images need not be of actual anatomy: training on randomly generated geometric shapes also results in competitive registration performance, albeit slightly less accurate, while alleviating the dependency on real data of any kind.
Revised:  Critically, we show that input labels from which we synthesize images need not be of actual anatomy: training on randomly generated geometric shapes also results in competitive performance, removing the dependency on real data of any kind.
Edit intent: clarity
Original:  Critically, we show that input labels from which we synthesize images need not be of actual anatomy: training on randomly generated geometric shapes also results in competitive registration performance, albeit slightly less accurate, while alleviating the dependency on real data of any kind.
Revised:  Critically, we show that input labels from which we synthesize images need not be of actual anatomy: training on randomly generated geometric shapes also results in competitive registration performance, albeit slightly less accurate, while alleviating the dependency on acquired data of any kind.
Edit intent: clarity
Original:   Our code is available at : URL
Revised:  Our code is available at URL
Edit intent: fluency
Original: Significance: Imaging neural activity in myelinated tissue using optical coherence tomography (OCT) creates exciting possibilities for functional imaging in the peripheral and central nervous systems.
Revised: Significance: Imaging neural activity in myelinated tissue using optical coherence tomography (OCT) creates new possibilities for functional imaging in the peripheral and central nervous systems.
Edit intent: clarity
Original:  There is a gap in understanding of the connection between these two problems and the nature of their online algorithm design.
Revised:  There is a gap in understanding the connection between these two problems and the nature of their online algorithm design.
Edit intent: fluency
Original:  We find that the infinitesimal assumption of the OKP is the key that connects the OTP in the analysis of online algorithms and the construction of worse-case instances.
Revised:  We find that the infinitesimal assumption of the OKP is the key that connects the OTP in the analysis of online algorithms and the construction of worst-case instances.
Edit intent: fluency
Original:  We then present a partitioned memory component structure with new flush policies that better exploits the write memory to minimize the write cost.
Revised:  We then present a partitioned memory component structure with new flush policies to better exploit the write memory to minimize the write cost.
Edit intent: fluency
Original:  Finally , estimates of the relevant rate parameters of the SEIR model are obtained and we demonstrate the robustness of our model predictions under uncertainty of those estimates  .
Revised:  Also , estimates of the relevant rate parameters of the SEIR model are obtained and we demonstrate the robustness of our model predictions under uncertainty of those estimates .
Edit intent: coherence
Original:  (b) a random graph (elimination of mass gatherings  ;
Revised:  (b) a random graph (elimination of mass gatherings ) ;
Edit intent: fluency
Original:  Finally, the social context and utility of this work is identified  .
Revised:  The social context and utility of this work is identified .
Edit intent: coherence
Original: Fake news that manipulates political elections, strikes financial systems and even incites riots , is more viral than real news online, resulting  unstable societies and buffeted democracy.
Revised: Fake news that manipulates political elections, strikes financial systems and even incites riots is more viral than real news online, resulting unstable societies and buffeted democracy.
Edit intent: fluency
Original: Fake news that manipulates political elections, strikes financial systems and even incites riots , is more viral than real news online, resulting  unstable societies and buffeted democracy.
Revised: Fake news that manipulates political elections, strikes financial systems and even incites riots , is more viral than real news online, resulting in unstable societies and buffeted democracy.
Edit intent: fluency
Original:  It is found that the easier contagion of fake news online can be causally explained by more anger it carries.
Revised:  The easier contagion of fake news online can be causally explained by more anger it carries.
Edit intent: coherence
Original:  It is found that the easier contagion of fake news online can be causally explained by more anger it carries.
Revised:  It is found that the easier contagion of fake news online can be causally explained by the greater anger it carries.
Edit intent: clarity
Original:  Offline questionnaires further reveal that anger leads to more incentivized audiences on anxiety management and information sharing and accordingly makes fake news more contagious than real news online.
Revised:  Offline questionnaires reveal that anger leads to more incentivized audiences on anxiety management and information sharing and accordingly makes fake news more contagious than real news online.
Edit intent: clarity
Original:  Offline questionnaires further reveal that anger leads to more incentivized audiences on anxiety management and information sharing and accordingly makes fake news more contagious than real news online.
Revised:  Offline questionnaires further reveal that anger leads to more incentivized audiences in terms of anxiety management and information sharing and accordingly makes fake news more contagious than real news online.
Edit intent: clarity
Original:  Our results suggest that the digital contagion of emotions, in particular the anger, should be comprehensively considered in profiling the online information spread.
Revised:  Our results suggest that the digital contagion of emotions, in particular anger, should be comprehensively considered in profiling the online information spread.
Edit intent: fluency
Original:  Cures like tagging anger in social media could be inspired to slowdown or prevent the contagion of fake news at the very beginning .
Revised:  Cures like tagging anger in social media could be implemented to slow or prevent the contagion of fake news at the very beginning .
Edit intent: clarity
Original:  Cures like tagging anger in social media could be inspired to slowdown or prevent the contagion of fake news at the very beginning .
Revised:  Cures like tagging anger in social media could be inspired to slowdown or prevent the contagion of fake news at the source .
Edit intent: clarity
Original: Fake news that manipulates political elections, strikes financial systems  and even incites riots is more viral than real news online, resulting in unstable societies and buffeted democracy.
Revised: Fake news that manipulates political elections, strikes financial systems , and even incites riots is more viral than real news online, resulting in unstable societies and buffeted democracy.
Edit intent: fluency
Original:  This problem can be viewed as an algebraic generalization of the bipartite matching problem , and was considered by Iwata and Murota (1995).
Revised:  This problem can be viewed as an algebraic generalization of the bipartite matching problem and was considered by Iwata and Murota (1995).
Edit intent: fluency
Original:  One of recent interests on this problem lies in the connection with non-commutative Edmonds' problem by Ivanyos, Qiao, and Subrahamanyam (2018) , and Garg, Gurvits, Oliveiva, and Wigderson (2019), where a result by Iwata and Murota implicitly says that the rank and the non-commutative rank (nc-rank) are the same for this class of symbolic matrices.
Revised:  Recent interests in this problem lie in the connection with non-commutative Edmonds' problem by Ivanyos, Qiao, and Subrahamanyam (2018) , and Garg, Gurvits, Oliveiva, and Wigderson (2019), where a result by Iwata and Murota implicitly says that the rank and the non-commutative rank (nc-rank) are the same for this class of symbolic matrices.
Edit intent: clarity
Original:  One of recent interests on this problem lies in the connection with non-commutative Edmonds' problem by Ivanyos, Qiao, and Subrahamanyam (2018) , and Garg, Gurvits, Oliveiva, and Wigderson (2019), where a result by Iwata and Murota implicitly says that the rank and the non-commutative rank (nc-rank) are the same for this class of symbolic matrices.
Revised:  One of recent interests on this problem lies in the connection with non-commutative Edmonds' problem by Ivanyos, Qiao, and Subrahamanyam (2018) and Garg, Gurvits, Oliveiva, and Wigderson (2019), where a result by Iwata and Murota implicitly says that the rank and the non-commutative rank (nc-rank) are the same for this class of symbolic matrices.
Edit intent: fluency
Original:  One of recent interests on this problem lies in the connection with non-commutative Edmonds' problem by Ivanyos, Qiao, and Subrahamanyam (2018) , and Garg, Gurvits, Oliveiva, and Wigderson (2019), where a result by Iwata and Murota implicitly says that the rank and the non-commutative rank (nc-rank) are the same for this class of symbolic matrices.
Revised:  One of recent interests on this problem lies in the connection with non-commutative Edmonds' problem by Ivanyos, Qiao, and Subrahamanyam (2018) , and Garg, Gurvits, Oliveiva, and Wigderson (2019), where a result by Iwata and Murota implicitly states that the rank and the non-commutative rank (nc-rank) are the same for this class of symbolic matrices.
Edit intent: fluency
Original:  One of recent interests on this problem lies in the connection with non-commutative Edmonds' problem by Ivanyos, Qiao, and Subrahamanyam (2018) , and Garg, Gurvits, Oliveiva, and Wigderson (2019), where a result by Iwata and Murota implicitly says that the rank and the non-commutative rank (nc-rank) are the same for this class of symbolic matrices.
Revised:  One of recent interests on this problem lies in the connection with non-commutative Edmonds' problem by Ivanyos, Qiao, and Subrahamanyam (2018) , and Garg, Gurvits, Oliveiva, and Wigderson (2019), where a result by Iwata and Murota implicitly says that the rank and non-commutative rank (nc-rank) are the same for this class of symbolic matrices.
Edit intent: fluency
Original: We present previously unknown solutions to the 3D Gross-Pitaevskii equation describing atomic Bose-Einstein condensates.
Revised: We present previously unknown solutions to the 3D Gross--Pitaevskii equation describing atomic Bose-Einstein condensates.
Edit intent: fluency
Original: In bounded, polygonal domains \Omega\subset R^2 with Lipschitz boundary \partial\Omega consisting of a finite number of Jordan curves admitting analytic parametrizations, we analyze hp-FEM discretizations of a linear, second order, singularly perturbed reaction diffusion equations on so-called geometric boundary layer meshes.
Revised: In bounded, polygonal domains \Omega\subset R^2 with Lipschitz boundary \partial\Omega consisting of a finite number of Jordan curves admitting analytic parametrizations, we analyze hp-FEM discretizations of linear, second order, singularly perturbed reaction diffusion equations on so-called geometric boundary layer meshes.
Edit intent: fluency
Original:  We prove, under suitable analyticity assumptions on the data, that these hp-FEM afford exponential convergence , in the natural "energy" norm of the problem, as long as the geometric boundary layer mesh can resolve the smallest length scale present in the problem.
Revised:  We prove, under suitable analyticity assumptions on the data, that these hp-FEM afford exponential convergence in the natural "energy" norm of the problem, as long as the geometric boundary layer mesh can resolve the smallest length scale present in the problem.
Edit intent: fluency
Original: We propose a stochastic model for a limit order book with liquidity fluctuations.
Revised: We propose a class of stochastic models for a dynamics of limit order book with liquidity fluctuations.
Edit intent: clarity
Original: Implementing artificial neural networks is commonly achieved via high-level programming languages like Python , and easy-to-use deep learning libraries like Keras.
Revised: Implementing artificial neural networks is commonly achieved via high-level programming languages like Python and easy-to-use deep learning libraries like Keras.
Edit intent: fluency
Original:  As a result, a deep learning practitioner will favor training a neural network model in Python  where these tools are readily available.
Revised:  As a result, a deep learning practitioner will favor training a neural network model in Python , where these tools are readily available.
Edit intent: fluency
Original:  However, many large-scale scientific computation projects are written in Fortran, which makes them difficult to integrate with modern deep learning methods.
Revised:  However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods.
Edit intent: coherence
Original:  The paper describes a number of unique features offered by FKB, such as customizable layers, loss functions, and network ensembles.
Revised:  The paper describes several unique features offered by FKB, such as customizable layers, loss functions, and network ensembles.
Edit intent: fluency
Original:  In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to then be transferred and used in Fortran to assess their emergent behavior , i.e. when fit imperfections are coupled to explicit planetary scale fluid dynamics.
Revised:  In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to be transferred and used in Fortran to assess their emergent behavior , i.e. when fit imperfections are coupled to explicit planetary scale fluid dynamics.
Edit intent: coherence
Original:  In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to then be transferred and used in Fortran to assess their emergent behavior , i.e. when fit imperfections are coupled to explicit planetary scale fluid dynamics.
Revised:  In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to then be transferred and used in Fortran . Such a process allows the model's emergent behavior to be assessed , i.e. when fit imperfections are coupled to explicit planetary scale fluid dynamics.
Edit intent: clarity
Original:  In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to then be transferred and used in Fortran to assess their emergent behavior , i.e. when fit imperfections are coupled to explicit planetary scale fluid dynamics.
Revised:  In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to then be transferred and used in Fortran to assess their emergent behavior , i.e. when fit imperfections are coupled to explicit planetary-scale fluid dynamics.
Edit intent: fluency
Original:  The model emphasizes an approach combining a driven stochastic drive  for each neuron and recurrent inputs resulting from the network activity.
Revised:  The model emphasizes an approach combining a driven stochastic drive for each neuron -- with recurrent inputs resulting from the network activity.
Edit intent: fluency
Original:  After a review of the dynamics of a single HH equation , for both deterministic and stochastic driven case, we proceed to the analysis of the network.
Revised:  After a review of the dynamics of a single HH equation for both the deterministic and the stochastically driven case, we proceed to the analysis of the network.
Edit intent: fluency
Original:  After a review of the dynamics of a single HH equation , for both deterministic and stochastic driven case, we proceed to the analysis of the network.
Revised:  After a review of the dynamics of a single HH equation , for both deterministic and stochastic driven case, we proceed to an analysis of the network.
Edit intent: fluency
Original:  Our numerical analysis highlights emergent properties such as partial synchronization and synchronization , waves of excitability, and oscillations in the gamma-band frequency  .
Revised:  This analysis reveals emergent properties of the system such as partial synchronization and synchronization , waves of excitability, and oscillations in the gamma-band frequency .
Edit intent: clarity
Original:  Finally, we briefly discuss the relationship of this result with the conjecture NP=PSPACE and how this redundancy provide us with a highly efficient compression method for propositional proofs.
Revised:  Finally, we briefly discuss how this redundancy provide us with a highly efficient compression method for propositional proofs.
Edit intent: coherence
Original:  Finally, we briefly discuss the relationship of this result with the conjecture NP=PSPACE and how this redundancy provide us with a highly efficient compression method for propositional proofs.
Revised:  Finally, we briefly discuss the relationship of this result with the conjecture NP=PSPACE and how this redundancy provides us with a highly efficient compression method for propositional proofs.
Edit intent: fluency
Original: Convolutional Neural Networks (CNNs) are the current de-facto approach used for many imaging tasks due to their high learning capacity as well as their architectural qualities.
Revised: Convolutional Neural Networks (CNNs) are the current de-facto models used for many imaging tasks due to their high learning capacity as well as their architectural qualities.
Edit intent: clarity