wanyu/IteraTeR_v2 huggingface dataset:
Original:  Using MDE we are able to discern driving effects in the occipital module between 100-140ms, which coincides with the P100 visually evoked potential, and a driving effect in the interaction of occipital and frontal modules between 120-140ms, suggesting a delayed information processing difference between these modules.
Revised:  Using MDE we are able to discern driving effects in the occipital module between 100-140ms, coinciding with the P100 visually evoked potential, and a driving effect in the interaction of occipital and frontal modules between 120-140ms, suggesting a delayed information processing difference between these modules.
Edit intent: coherence
Original:  Using MDE we are able to discern driving effects in the occipital module between 100-140ms, which coincides with the P100 visually evoked potential, and a driving effect in the interaction of occipital and frontal modules between 120-140ms, suggesting a delayed information processing difference between these modules.
Revised:  Using MDE we are able to discern driving effects in the occipital module between 100-140ms, which coincides with the P100 visually evoked potential, followed by a driving effect in the interaction of occipital and frontal modules between 120-140ms, suggesting a delayed information processing difference between these modules.
Edit intent: clarity
Original:  Using MDE we are able to discern driving effects in the occipital module between 100-140ms, which coincides with the P100 visually evoked potential, and a driving effect in the interaction of occipital and frontal modules between 120-140ms, suggesting a delayed information processing difference between these modules.
Revised:  Using MDE we are able to discern driving effects in the occipital module between 100-140ms, which coincides with the P100 visually evoked potential, and a driving effect in the frontal module between 140-180ms, suggesting that the differences found constitute an information processing difference between these modules.
Edit intent: clarity
Original:  This provides temporally precise information over a heterogeneous population for tasks showing promise in the detection of AD.
Revised:  This provides temporally precise information over a heterogeneous population in promising tasks for the detection of AD.
Edit intent: clarity
Original: We present a data-driven approach to determine the memory kernel and random noise of the generalized Langevin equation .
Revised: We present a data-driven approach to determine the memory kernel and random noise in generalized Langevin equations .
Edit intent: clarity
Original:  To facilitate practical implementations, we parameterize the kernel function in the Laplace domain by a rational function, with coefficients directly linked to the equi- librium statistics of the coarse-grain variables.
Revised:  To facilitate practical implementations, we parameterize the kernel function in the Laplace domain by a rational function, with coefficients directly linked to the equilibrium statistics of the coarse-grain variables.
Edit intent: fluency
Original:  Further, we show that such an approximation can be constructed to arbitrarily high order .
Revised:  We show that such an approximation can be constructed to arbitrarily high order .
Edit intent: coherence
Original:  Within these approximations, the generalized Langevin dynamics can be embedded in an extended stochastic model without  memory.
Revised:  Within these approximations, the generalized Langevin dynamics can be embedded in an extended stochastic model without explicit memory.
Edit intent: clarity
Original:  Here we present evidence of a network effect which biases the digital reputations of the users of P2P networks, showing that P2P networks display exceedingly high levels of reciprocity.
Revised:  Here we present evidence of a network effect which biases digital reputation, revealing that P2P networks display exceedingly high levels of reciprocity.
Edit intent: clarity
Original:  This shows that the crowdsourcing process underpinning digital reputation is significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings.
Revised:  This indicates that the crowdsourcing process underpinning digital reputation is significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings.
Edit intent: clarity
Original:  This shows that the crowdsourcing process underpinning digital reputation is significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings.
Revised:  This shows that the crowdsourcing process underpinning digital reputation can be significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings.
Edit intent: clarity
Original:  We show that the least active users are predominantly responsible for such reciprocity-induced bias, and that this fact can be exploited to suppress the bias itself .
Revised:  We uncover that the least active users are predominantly responsible for such reciprocity-induced bias, and that this fact can be exploited to suppress the bias itself .
Edit intent: clarity
Original: In spreading dynamics in social networks, there exists an optimal set of influencers whose activation can induce a global-scale cascade of information.
Revised: In social networks, there exists an optimal set of influencers whose activation can induce a global-scale cascade of information.
Edit intent: clarity
Original:  Here we address this issue by exploring the collective influence in general threshold models of opinion cascading.
Revised:  Here we address this issue by exploring the collective influence in general threshold models of behavior cascading.
Edit intent: clarity
Original:  Results in both synthetic random graphs and real networks show that the set of spreaders predicted by our method is smaller than those identified by other linearly scalable heuristic approaches.
Revised:  Results in both synthetic random graphs and real networks show that the proposed method can achieve larger collective influence given same number of seeds compared with other linearly scalable heuristic approaches.
Edit intent: clarity
Original:  Recently, a highly scalable method called "Collective Influence (CI)" has been put forward through collective influence maximization.
Revised:  Recently, a scalable method called "Collective Influence (CI)" has been put forward through collective influence maximization.
Edit intent: clarity
Original:  In contrast to previous heuristic methods evaluating nodes' significance separately, CI method inspects the collective influence of multiple spreaders.
Revised:  In contrast to heuristic methods evaluating nodes' significance separately, CI method inspects the collective influence of multiple spreaders.
Edit intent: clarity
Original:  Our consistent results demonstrate that the set of spreaders selected by CI indeed can induce larger scale of information propagation.
Revised:  Our results demonstrate that the set of spreaders selected by CI indeed can induce larger scale of information propagation.
Edit intent: clarity
Original:  Our consistent results demonstrate that the set of spreaders selected by CI indeed can induce larger scale of information propagation.
Revised:  Our consistent results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation.
Edit intent: clarity
Original: In this paper we propose methods to extract geographically relevant information in a multimedia recording using only its audiocomponent .
Revised: In this paper we propose methods to extract geographically relevant information in a multimedia recording using its audio .
Edit intent: clarity
Original:  Using example MEG data, we illustrate some effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to 'decode' different perceptual stimuli or cognitive states over time from dynamic brain activation patterns.
Revised:  Using example MEG data, we illustrate the effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to 'decode' different perceptual stimuli or cognitive states over time from dynamic brain activation patterns.
Edit intent: clarity
Original:  We show that decisions made at both preprocessing (e.g.  dimensionality reduction, subsampling, trial averaging) and decoding (e.g.  classifier selection, cross-validation design) stages of the analysis can significantly affect the results.
Revised:  We show that decisions made at both preprocessing (e.g. , dimensionality reduction, subsampling, trial averaging) and decoding (e.g. classifier selection, cross-validation design) stages of the analysis can significantly affect the results.
Edit intent: fluency
Original:  We show that decisions made at both preprocessing (e.g.  dimensionality reduction, subsampling, trial averaging) and decoding (e.g.  classifier selection, cross-validation design) stages of the analysis can significantly affect the results.
Revised:  We show that decisions made at both preprocessing (e.g. dimensionality reduction, subsampling, trial averaging) and decoding (e.g. , classifier selection, cross-validation design) stages of the analysis can significantly affect the results.
Edit intent: fluency
Original:  From these results, we derive that at every position of an aperiodic uniformly recurrent word start anti-powers of any order We further show that any infinite word avoiding anti-powers of order 3 is ultimately periodic, and that there exist aperiodic words avoiding anti-powers of order 4.
Revised:  As a consequence, we show that every aperiodic uniformly recurrent word start anti-powers of any order We further show that any infinite word avoiding anti-powers of order 3 is ultimately periodic, and that there exist aperiodic words avoiding anti-powers of order 4.
Edit intent: clarity
Original:  We also show that there exist aperiodic recurrent words avoiding anti-powers of order 6, and leave open the question whether there exist aperiodic recurrent words avoiding anti-powers of order k for k=4,5.
Revised:  We also show that there exist aperiodic recurrent words avoiding anti-powers of order 6.
Edit intent: coherence
Original:  As a consequence, we show that  every aperiodic uniformly recurrent word begins in an anti-power of order k, for any choice of k>1.
Revised:  As a consequence, we show that in every aperiodic uniformly recurrent word begins in an anti-power of order k, for any choice of k>1.
Edit intent: clarity
Original:  As a consequence, we show that  every aperiodic uniformly recurrent word begins in an anti-power of order k, for any choice of k>1.
Revised:  As a consequence, we show that every aperiodic uniformly recurrent word , anti-powers of every order begin at every position.
Edit intent: clarity
Original:  We further show that any infinite word avoiding anti-powers of order 3 is ultimately periodic, and that there exist aperiodic words avoiding anti-powers of order 4.
Revised:  We further show that every infinite word avoiding anti-powers of order 3 is ultimately periodic, and that there exist aperiodic words avoiding anti-powers of order 4.
Edit intent: coherence
Original:  We further show that any infinite word avoiding anti-powers of order 3 is ultimately periodic, and that there exist aperiodic words avoiding anti-powers of order 4.
Revised:  We further show that any infinite word avoiding anti-powers of order 3 is ultimately periodic, while there exist aperiodic words avoiding anti-powers of order 4.
Edit intent: coherence
Original:  Unlike spatial interpolation, the interpolated value can be computed using a single simulation run irrespective of the number of parameters in the system.
Edit intent: coherence
Original:  To demonstrate the utility of the interpolation scheme , we solve a discrete parameter queuing network optimization problem by embedding the discrete parameters into  continuous space, and then using a continuous space optimization algorithm to find optimal configurations .
Revised:  To demonstrate the utility of the embedding technique , we solve a discrete parameter queuing network optimization problem by embedding the discrete parameters into continuous space, and then using a continuous space optimization algorithm to find optimal configurations .
Edit intent: clarity
Original:  We propose an algorithm that, given a 3-colorable graph without an induced path on t vertices, computes a coloring with \max %DIFDELCMD < 5,2\ceil{\frac{t-1{2}}-2} %%% \frac{t-1{2}}\rceil}+1} %%% \frac{t-1{2}}\rceil+t^2)m+n) if the input graph has n vertices and m edges.
Revised:  We propose an algorithm that, given a 3-colorable graph without an induced path on t vertices, computes a coloring with \max %DIFDELCMD < 5,2\ceil{\frac{t-1{2}}-2} %%% \{5,2\frac{t-1{2}}\rceil}+1} %%% \frac{t-1{2}}\rceil+t^2)m+n) if the input graph has n vertices and m edges.
Edit intent: fluency
Original:  Finally  the centralities are also computed to reveal the most significance anime.
Revised:  Finally , the centralities are also computed to reveal the most significance anime.
Edit intent: coherence
Original:  Furthermore, by using centralities calculation, we found some anime that are significance to others.
Revised:  Furthermore, by using centralities calculation, we found some anime that are significant to others.
Edit intent: fluency
Original:  In its  most natural formulation, the balance of a social network is thus defined from its simple cycles, cycles which do not visit any vertex more than once.
Revised:  In its most natural formulation, the balance of a social network was thus defined from its simple cycles, cycles which do not visit any vertex more than once.
Edit intent: fluency
Original:  Because of the inherent difficulty associated with finding such cycles on very large networks, social balance has always been studied via other , less-direct means.
Revised:  Because of the inherent difficulty associated with finding such cycles on very large networks, social balance has since then been studied via other , less-direct means.
Edit intent: clarity
Original:  Because of the inherent difficulty associated with finding such cycles on very large networks, social balance has always been studied via other , less-direct means.
Revised:  Because of the inherent difficulty associated with finding such cycles on very large networks, social balance has always been studied via other means.
Edit intent: coherence
Original:  We show that social networks exhibit strong inter-edge correlations favoring balanced situations and we determine the corresponding correlation length \xi.
Revised:  We show that social networks exhibit strong inter-edge correlations favouring balanced situations and we determine the corresponding correlation length \xi.
Edit intent: fluency
Original: This paper studies the problem of optimally extracting nonrenewable natural resource in light of various financial and economical restrictions and constraints.
Revised: This paper studies the problem of optimally extracting nonrenewable natural resource in light of various financial and economic restrictions and constraints.
Edit intent: fluency
Original:  Such a group of smartphones can cooperatively wake up and energy-efficiently send out emergency messages  with their location and position information so as to assist rescue operations.
Revised:  Such a group of smartphones can cooperatively wake up and send out emergency messages with their location and position information so as to assist rescue operations.
Edit intent: clarity
Original:  Such a group of smartphones can cooperatively wake up and energy-efficiently send out emergency messages  with their location and position information so as to assist rescue operations.
Revised:  Such a group of smartphones can cooperatively wake up and energy-efficiently send out emergency messages in an energy-efficient manner with their location and position information so as to assist rescue operations.
Edit intent: clarity
Original:  The aim of this paper is to investigate the empirical adequacy of major such quantum-like models  .
Revised:  The aim of this paper is to investigate the empirical adequacy of major quantum-like models .
Edit intent: clarity
Original:  This strongly suggests that the quantum-like account of the conjunction fallacy fails.
Revised:  This strongly suggests that this quantum-like account of the conjunction fallacy fails.
Edit intent: fluency
Original:  In contrast to existing work, in this paper, we focus on cooperatively offloading data among mobile devices to maximally improve the probability of data delivery from a mobile device to intermittently connected infrastructure within a given time constraint, which is referred to as the cooperative offloading problem.
Revised:  In contrast to existing work, in this paper, we focus on cooperatively offloading data among mobile devices to maximally improve the probability of data delivery from a mobile device to intermittently connected infrastructure within a given time constraint, which is referred to as the cooperative offloading problem.
Edit intent: fluency
Original: In recent years, there have been many computational models exploring how spontaneous neural dynamics arise out of the brain's structural connectome.
Revised: In recent years, there have been many computational simulations of spontaneous neural dynamics arise out of the brain's structural connectome.
Edit intent: clarity
Original:  Here, we explore a very simple neural network model (similar to that used previously to model dynamics at rest) and allow it to control a virtual agent in a very simple environment.
Revised:  Here, we explore a model of spontaneous neural dynamics and allow it to control a virtual agent in a very simple environment.
Edit intent: clarity
Original:  Here, we explore a very simple neural network model (similar to that used previously to model dynamics at rest) and allow it to control a virtual agent in a very simple environment.
Revised:  Here, we explore a very simple neural network model (similar to that used previously to model dynamics at rest) and allow it to control a virtual agent moving in a simple environment.
Edit intent: clarity
Original:  This setup generates interesting brain-environment interactions that suggest the need for homeostatic mechanisms to maintain rich spontaneous dynamics .
Revised:  This setup generates interesting brain-environment interactions that suggest the need for homeostatic mechanisms .
Edit intent: clarity
Original:  Our results suggest complementary functional roles for both balanced local homeostatic plasticity and balanced task-positive task negative activity in maintaining simulated neural dynamics in the face of interactions with the environment.
Revised:  Our results suggest complementary functional roles for both local homeostatic plasticity and balanced task-positive task negative activity in maintaining simulated neural dynamics in the face of interactions with the environment.
Edit intent: fluency
Original:  it also suggests a functional role for macroscopic task negative systems in the brain that may be of relevance to understanding large-scale brain systems such as the default mode network  .
Revised:  it also suggests a functional role for frequently reported macroscopic task-negative patterns of activity (e.g., the default mode network .
Edit intent: clarity
Original:  it also suggests a functional role for macroscopic task negative systems in the brain that may be of relevance to understanding large-scale brain systems such as the default mode network  .
Revised:  it also suggests a functional role for macroscopic task negative systems in the brain that may be of relevance to understanding large-scale brain systems such as the default mode network ) .
Edit intent: fluency
Original:  Deviations from expected input are only forgotten very slowly in power law fashion.
Revised:  Deviations from expected input are only forgotten slowly in power law fashion.
Edit intent: clarity
Original: Deep down in many applications like natural language processing (NLP), vision , and robotics is a form of the k-nearest neighbor search algorithm (kNN) .
Revised: Deep down in many applications like natural language processing , and robotics is a form of the k-nearest neighbor search algorithm (kNN) .
Edit intent: clarity
Original: Deep down in many applications like natural language processing (NLP), vision , and robotics is a form of the k-nearest neighbor search algorithm (kNN) .
Revised: Deep down in many applications like natural language processing (NLP), vision , and robotics is a form of the k-nearest neighbors (kNN) .
Edit intent: clarity
Original:  The NCAM benefits from the higher density and speeds of emerging memory technologies and interfaces.
Revised:  The NCAM benefits from the higher memory bandwidth and density exposed by emerging memory technologies and interfaces.
Edit intent: clarity
Original: The statements `inheritance is not subtyping' and ' mainstream OO languages unnecessarily place restrictions over inheritance'  rippled as mantras through the PL research community for years.
Revised: The statements `inheritance is not subtyping' and ` mainstream OO languages unnecessarily place restrictions over inheritance' rippled as mantras through the PL research community for years.
Edit intent: fluency
Original: The statements `inheritance is not subtyping' and ' mainstream OO languages unnecessarily place restrictions over inheritance'  rippled as mantras through the PL research community for years.
Revised: The statements `inheritance is not subtyping' and ' mainstream OO languages unnecessarily place restrictions over inheritance' have rippled as mantras through the PL research community for years.
Edit intent: fluency
Original:  In spite of that, many mainstream OO developers and OO language designers cannot accept these statements.
Revised:  Many mainstream OO developers and OO language designers cannot accept these statements.
Edit intent: coherence
Original:  In spite of that, many mainstream OO developers and OO language designers cannot accept these statements.
Revised:  In spite of that, many mainstream OO developers and OO language designers however do not accept these statements.
Edit intent: clarity
Original:  In 'nominally-typed' OO languages that they are dearly familiar with, inheritance indeed is subtyping.
Revised:  In nominally-typed OO languages that they are dearly familiar with, inheritance indeed is subtyping.
Edit intent: fluency
Original:  In 'nominally-typed' OO languages that they are dearly familiar with, inheritance indeed is subtyping.
Revised:  In 'nominally-typed' OO languages that these developers and language designers are dearly familiar with, inheritance indeed is subtyping.
Edit intent: clarity
Original:  And they believe inheritance is an inherently nominal notion , not a structural one.
Revised:  And they believe inheritance is an inherently nominal notion not a structural one.
Edit intent: fluency
Original:  Nominally-typed OO languages , such as Java, C#, C++ and Scala, are among the top most-used programming languages today.
Revised:  Nominally-typed OO languages are among the top most-used programming languages today.
Edit intent: coherence
Original:  Nominally-typed OO languages , such as Java, C#, C++ and Scala, are among the top most-used programming languages today.
Revised:  Nominally-typed OO languages , such as Java, C#, C++ and Scala, are among the most used programming languages today.
Edit intent: clarity