wanyu/IteraTeR_v2 huggingface dataset:
Original:  Thus, it is essential to first reduce thermal noise and then correctly identify and remove non-neural artefacts from rs-fMRI signals through proper data processing methods.
Revised:  Thus, it is essential to first reduce thermal noise and then correctly identify and remove non-neural artefacts from rs-fMRI signals through optimized data processing methods.
Edit intent: clarity
Original:  However, existing tools that correct for these effects are tailored for human brain and are not readily transposable to rat data.
Revised:  However, existing tools that correct for these effects have been developed for human brain and are not readily transposable to rat data.
Edit intent: clarity
Original:  Here, we established a data processing pipeline that can robustly remove random and structured noise from rat rs-fMRI data.
Revised:  Therefore, the aim of the present study was to establish a data processing pipeline that can robustly remove random and structured noise from rat rs-fMRI data.
Edit intent: clarity
Original:  We extend their work with an algorithm, Incorporate, to which produces many different core elements.
Revised:  We extend their work with an algorithm, Incorporate, which produces many different core elements.
Edit intent: fluency
Original:  We give an algorithm which produces core vectors that simultaneously maximize SW and fairness.
Revised:  In this setting we give an algorithm which produces core vectors that simultaneously maximize SW and fairness.
Edit intent: clarity
Original: Cancer treatment by cold atmospheric plasma (CAP) offers the possibility to selectively eliminate cancer cells while leaving surrounding, normal cells, unaffected.
Revised: Cold atmospheric plasma (CAP) offers the possibility to selectively eliminate cancer cells while leaving surrounding, normal cells, unaffected.
Edit intent: clarity
Original:  A better insight of this specific apoptosis-inducing mechanism - especially the role of catalase inactivation - could be useful to increase our understanding of possible roles of CAP constituents in cancer treatment .
Revised:  A better insight of this specific apoptosis-inducing mechanism - especially the role of catalase inactivation , can contribute to the understanding of the underlying cause of the anti-cancer effect of CAP .
Edit intent: clarity
Original:  In the present study,  a mathematical model describing the reaction kinetics of the two apoptosis-inducing signaling pathways is developed and used to theoretically investigate their catalase-dependent reactivation.
Revised:  In the present study, a mathematical model to analyze the proposed catalase-dependent reactivation.
Edit intent: clarity
Original: In a previous paper we introduced immediate observation (IO) Petri nets, a class of interest in the study of population protocols (a model of distributed computation), and enzymatic chemical networks.
Revised: In a previous paper we introduced immediate observation (IO) Petri nets, a class of interest in the study of population protocols and enzymatic chemical networks.
Edit intent: clarity
Original:  In the first part of this paper we show that IO Petri nets are globally flat, thus allowing their safety properties to be checked by efficient symbolic model checking tools using acceleration techniques, like FAST.
Revised:  In the first part of this paper we show that IO nets are globally flat, thus allowing their safety properties to be checked by efficient symbolic model checking tools using acceleration techniques, like FAST.
Edit intent: clarity
Original:  In the first part of this paper we show that IO Petri nets are globally flat, thus allowing their safety properties to be checked by efficient symbolic model checking tools using acceleration techniques, like FAST.
Revised:  In the first part of this paper we show that IO Petri nets are globally flat, and so their safety properties to be checked by efficient symbolic model checking tools using acceleration techniques, like FAST.
Edit intent: clarity
Original:  In the first part of this paper we show that IO Petri nets are globally flat, thus allowing their safety properties to be checked by efficient symbolic model checking tools using acceleration techniques, like FAST.
Revised:  In the first part of this paper we show that IO Petri nets are globally flat, thus allowing their safety properties can be checked by efficient symbolic model checking tools using acceleration techniques, like FAST.
Edit intent: clarity
Original:  We show that, while BIO nets are no longer globally flat, and their sets of reachable markings may be non-semilinear, they still are locally flat.
Revised:  We show that, while BIO nets are no longer globally flat, and their sets of reachable markings may be non-semilinear, they are still locally flat.
Edit intent: fluency
Original:  This makes BIO nets the first natural net class with non-semilinear reachability relations for which the reachability problem is provably simpler than for general Petri nets.
Revised:  This makes BIO nets the first natural net class with non-semilinear reachability relation for which the reachability problem is provably simpler than for general Petri nets.
Edit intent: fluency
Original: In this paper, we discuss a quality measure for an aggregation-based coarsening algorithm, named %DIFDELCMD < {\em %%% coarsening based on compatible weighted ma\-tch\-ing , which relies on the interplay between the principle of compatible relaxation and the maximum product matching in weighted graphs.
Revised: In this paper, we discuss a quality measure for an aggregation-based coarsening algorithm, named %DIFDELCMD < {\em %%% coarsening based on compatible weighted matching , which relies on the interplay between the principle of compatible relaxation and the maximum product matching in weighted graphs.
Edit intent: fluency
Original:  The measure we propose is based on a recent general convergence analysis theory applied to the class of multigrid methods employing unsmoothed aggregation.
Revised:  The measure we use is based on a recent general convergence analysis theory applied to the class of multigrid methods employing unsmoothed aggregation.
Edit intent: clarity
Original:  The analysis, as well as the coarsening procedure, is purely algebraic and allows aa posteriori evaluation of the quality of the aggregates  .
Revised:  The analysis, as well as the coarsening procedure, is purely algebraic and allows a posteriori evaluation of the quality of the aggregates .
Edit intent: fluency
Original:  The analysis, as well as the coarsening procedure, is purely algebraic and allows aa posteriori evaluation of the quality of the aggregates  .
Revised:  The analysis, as well as the coarsening procedure, is purely algebraic and allows aan a posteriori evaluation of the quality of the aggregates .
Edit intent: fluency
Original:  The connection between the choice of the aggregates and the compatible relaxation principle is  highlighted, confirming the consistency between available theories for designing effective coarsening procedure in purely algebraic multigrid methods and the effectiveness of the coarsening based on compatible weighted matching.
Revised:  The connection between the choice of the aggregates and the compatible relaxation principle is also highlighted, confirming the consistency between available theories for designing effective coarsening procedure in purely algebraic multigrid methods and the effectiveness of the coarsening based on compatible weighted matching.
Edit intent: coherence
Original:  The measure we use is based on a recent general convergence analysis theory applied to the class of  multigrid methods employing unsmoothed aggregation  .
Revised:  The measure is based on a recent general convergence analysis theory applied to the class of multigrid methods employing unsmoothed aggregation .
Edit intent: coherence
Original:  The measure we use is based on a recent general convergence analysis theory applied to the class of  multigrid methods employing unsmoothed aggregation  .
Revised:  The measure we use is based on a general convergence analysis theory applied to the class of multigrid methods employing unsmoothed aggregation .
Edit intent: clarity
Original:  The connection between the choice of the aggregates and the compatible relaxation principle is also highlighted, confirming the consistency between available theories for designing effective coarsening procedure in purely algebraic multigrid methods and the effectiveness of the coarsening based on compatible weighted matching.
Revised:  The connection between the choice of the aggregates and the compatible relaxation principle is also highlighted, confirming the consistency between available theories for designing effective coarsening procedures in purely algebraic multigrid methods and the effectiveness of the coarsening based on compatible weighted matching.
Edit intent: fluency
Original:  We discuss general methods to obtain aggregates for which good convergence properties are achieved , as well as their application to various test cases.
Revised:  We discuss general methods to obtain aggregates for which good convergence properties are achieved on various test cases.
Edit intent: clarity
Original:  This 2.6B parameter neural network is  trained to minimize perplexity , an automatic metric that we compare against human judgement of multi-turn conversation quality.
Revised:  This 2.6B parameter neural network is simply trained to minimize perplexity , an automatic metric that we compare against human judgement of multi-turn conversation quality.
Edit intent: coherence
Original:  This shows that, in addition to providing a compact latent space representation of audio features, the proposed approach has a relatively high performance over the baseline models.
Revised:  This shows that, in addition to providing a compact latent space representation of audio features, the proposed approach has a higher performance than the baseline models.
Edit intent: clarity
Original:   ] In this paper we  show that if there are c distinct processing times, i.e. p_j's come from a set of size c, then there is a (1-\varepsilon)-approximation that runs in time O(n^{mc^7\varepsilon^{-6}}\log T), where T is the largest deadline.
Revised:  ]). In this paper we show that if there are c distinct processing times, i.e. p_j's come from a set of size c, then there is a (1-\varepsilon)-approximation that runs in time O(n^{mc^7\varepsilon^{-6}}\log T), where T is the largest deadline.
Edit intent: fluency
Original:  For constant m and constant c this yields a PTAS.
Revised:  Therefore, for constant m and constant c this yields a PTAS.
Edit intent: coherence
Original:  As a corollary, we obtain a QPTAS for when p_j's come from a set of size%DIFDELCMD < {\rm %%% Poly (n) and m=%DIFDELCMD < {\rm %DIFDELCMD < %%% Poly (\log n) with (1+\varepsilon)-speed up of machines.
Revised:  %DIFDELCMD < {\rm %%% Poly (n) and m=%DIFDELCMD < {\rm %DIFDELCMD < %%% Poly (\log n) with (1+\varepsilon)-speed up of machines.
Edit intent: coherence
Original:  As a corollary, we obtain a QPTAS for when p_j's come from a set of size%DIFDELCMD < {\rm %%% Poly (n) and m=%DIFDELCMD < {\rm %DIFDELCMD < %%% Poly (\log n) with (1+\varepsilon)-speed up of machines.
Revised:  As a corollary, we obtain a QPTAS for when p_j's come from a set of size%DIFDELCMD < {\rm %%% (n) and m=%DIFDELCMD < {\rm %DIFDELCMD < %%% Poly (\log n) with (1+\varepsilon)-speed up of machines.
Edit intent: fluency
Original:  As a corollary, we obtain a QPTAS for when p_j's come from a set of size%DIFDELCMD < {\rm %%% Poly (n) and m=%DIFDELCMD < {\rm %DIFDELCMD < %%% Poly (\log n) with (1+\varepsilon)-speed up of machines.
Revised:  As a corollary, we obtain a QPTAS for when p_j's come from a set of size%DIFDELCMD < {\rm %%% Poly %DIFDELCMD < {\rm %DIFDELCMD < %%% Poly (\log n) with (1+\varepsilon)-speed up of machines.
Edit intent: coherence
Original:  As a corollary, we obtain a QPTAS for when p_j's come from a set of size%DIFDELCMD < {\rm %%% Poly (n) and m=%DIFDELCMD < {\rm %DIFDELCMD < %%% Poly (\log n) with (1+\varepsilon)-speed up of machines.
Revised:  As a corollary, we obtain a QPTAS for when p_j's come from a set of size%DIFDELCMD < {\rm %%% Poly (n) and m=%DIFDELCMD < {\rm %DIFDELCMD < %%% (\log n) with (1+\varepsilon)-speed up of machines.
Edit intent: fluency
Original:  More specifically, if each value p_j is bounded by%DIFDELCMD < {\rm %%% Poly (n) (but no bound on the number of p_j's) for any \varepsilon>0, there is an algorithm that finds a (1-\varepsilon)-approximate solution on (1+\varepsilon)-speed machines;
Revised:  More specifically, if each value p_j is bounded by%DIFDELCMD < {\rm %%% (n) (but no bound on the number of p_j's) for any \varepsilon>0, there is an algorithm that finds a (1-\varepsilon)-approximate solution on (1+\varepsilon)-speed machines;
Edit intent: fluency
Original:  In accord with the prediction diversity theorem, the collective estimate proved always to be better than the majority of the individual estimates .
Revised:  We find that the collective estimate is better than the majority of the individual estimates .
Edit intent: clarity
Original:  In addition, the poor accuracy of the crowd on some experiments lead us to conjecture that its alleged accuracy is most likely an artifice of selective attention.
Revised:  The poor accuracy of the crowd on some experiments lead us to conjecture that its alleged accuracy is most likely an artifice of selective attention.
Edit intent: coherence
Original: This paper considers a modular grad-div stabilization method for approximating solutions of two multiphysics flow problems: incompressible non-isothermal flows governed by the Boussinesq equations, and magnetohydrodynamics (MHD) .
Revised: This paper considers a modular grad-div stabilization method for approximating solutions of two multiphysics flow problems: incompressible non-isothermal flows .
Edit intent: coherence
Original:  The proposed methods add a minimally intrusive step to an existing Boussinesq /MHD code, with the key idea being that the penalization of the divergence errors, is only in the extra step (i.e. nothing is added to the original equations).
Revised:  The proposed method adds a minimally intrusive step to an existing Boussinesq /MHD code, with the key idea being that the penalization of the divergence errors, is only in the extra step (i.e. nothing is added to the original equations).
Edit intent: fluency
Original:  The proposed methods add a minimally intrusive step to an existing Boussinesq /MHD code, with the key idea being that the penalization of the divergence errors, is only in the extra step (i.e. nothing is added to the original equations).
Revised:  The proposed methods add a minimally intrusive step to an existing Boussinesq code, with the key idea being that the penalization of the divergence errors, is only in the extra step (i.e. nothing is added to the original equations).
Edit intent: clarity
Original:  Tail bounds obtained using central moments are often tighter than the ones obtained using raw moments, but automatically analyzing higher moments is more challenging.
Revised:  Tail bounds obtained using central moments are often tighter than the ones obtained using raw moments, but automatically analyzing central moments is more challenging.
Edit intent: clarity
Original:  This paper presents an analysis for probabilistic programs that automatically derives symbolic over- and under-approximations for variances, as well as higher central moments  .
Revised:  This paper presents an analysis for probabilistic programs that automatically derives symbolic upper and lower bounds on variances, as well as higher central moments .
Edit intent: clarity
Original:  The analysis is proved sound with respect to a trace-based, small-step model that maps programs to Markov chains.
Edit intent: coherence
Original:  The analysis has been implemented using a template-based technique that reduces the inference of polynomial approximations to linear programming.
Revised:  The analysis has been implemented using a template-based technique that reduces the inference of polynomial bounds to linear programming.
Edit intent: clarity
Original:  Experiments with our prototype central-moment analyzer show that, despite the analyzer's over- / under-approximations of various quantities, it obtains tighter tail bounds than a prior system that uses only raw moments, such as expectations.
Revised:  Experiments with our prototype central-moment analyzer show that, despite the analyzer's upper / under-approximations of various quantities, it obtains tighter tail bounds than a prior system that uses only raw moments, such as expectations.
Edit intent: fluency
Original:  Experiments with our prototype central-moment analyzer show that, despite the analyzer's over- / under-approximations of various quantities, it obtains tighter tail bounds than a prior system that uses only raw moments, such as expectations.
Revised:  Experiments with our prototype central-moment analyzer show that, despite the analyzer's over- / lower bounds on various quantities, it obtains tighter tail bounds than a prior system that uses only raw moments, such as expectations.
Edit intent: clarity
Original:  Experiments with our prototype central-moment analyzer show that, despite the analyzer's over- / under-approximations of various quantities, it obtains tighter tail bounds than a prior system that uses only raw moments, such as expectations.
Revised:  Experiments with our prototype central-moment analyzer show that, despite the analyzer's over- / under-approximations of various quantities, it obtains tighter tail bounds than an existing system that uses only raw moments, such as expectations.
Edit intent: clarity
Original:  Most notably, graded monads , indexed by a monoid , model effect systems and parameterised monads , indexed by pairs of pre- and post-conditions , model program logics.
Revised:  Most notably, graded monads ( indexed by a monoid , model effect systems and parameterised monads , indexed by pairs of pre- and post-conditions , model program logics.
Edit intent: fluency
Original:  Most notably, graded monads , indexed by a monoid , model effect systems and parameterised monads , indexed by pairs of pre- and post-conditions , model program logics.
Revised:  Most notably, graded monads , indexed by a monoid ) model effect systems and parameterised monads , indexed by pairs of pre- and post-conditions , model program logics.
Edit intent: fluency
Original:  Most notably, graded monads , indexed by a monoid , model effect systems and parameterised monads , indexed by pairs of pre- and post-conditions , model program logics.
Revised:  Most notably, graded monads , indexed by a monoid , model effect systems and parameterised monads ( indexed by pairs of pre- and post-conditions , model program logics.
Edit intent: fluency
Original:  Most notably, graded monads , indexed by a monoid , model effect systems and parameterised monads , indexed by pairs of pre- and post-conditions , model program logics.
Revised:  Most notably, graded monads , indexed by a monoid , model effect systems and parameterised monads , indexed by pairs of pre- and post-conditions ) model program logics.
Edit intent: fluency
Original: Embedding networks into a fixed dimensional Euclidean feature space, while preserving its essential structural properties is a fundamental task in graph analytics.
Revised: Embedding networks into a fixed dimensional feature space, while preserving its essential structural properties is a fundamental task in graph analytics.
Edit intent: clarity
Original:  These feature vectors , referred to as graph descriptors, are used to measure  pairwise similarity between graphs.
Revised:  These feature vectors (graph descriptors) are used to measure pairwise similarity between graphs.
Edit intent: clarity
Original:  These feature vectors , referred to as graph descriptors, are used to measure  pairwise similarity between graphs.
Revised:  These feature vectors , referred to as graph descriptors, are used to measure the pairwise similarity between graphs.
Edit intent: fluency
Original:  This enables applying data mining algorithms such as classification, clustering, anomaly detection on graph structured data which have numerous applications in multiple domains.
Revised:  This enables applying data mining algorithms (e.g classification, clustering, anomaly detection on graph structured data which have numerous applications in multiple domains.
Edit intent: clarity
Original:  This enables applying data mining algorithms such as classification, clustering, anomaly detection on graph structured data which have numerous applications in multiple domains.
Revised:  This enables applying data mining algorithms such as classification, clustering, or anomaly detection) on graph-structured data which have numerous applications in multiple domains.
Edit intent: coherence
Original:  State-of-the-art algorithms for computing descriptors require the entire graph to be in memory, entailing a huge memory footprint, and thus , do not scale well to increasing sizes of real world networks.
Revised:  State-of-the-art algorithms for computing descriptors require the entire graph to be in memory, entailing a huge memory footprint, and thus do not scale well to increasing sizes of real world networks.
Edit intent: fluency
Original:  State-of-the-art algorithms for computing descriptors require the entire graph to be in memory, entailing a huge memory footprint, and thus , do not scale well to increasing sizes of real world networks.
Revised:  State-of-the-art algorithms for computing descriptors require the entire graph to be in memory, entailing a huge memory footprint, and thus , do not scale well to increasing sizes of real-world networks.
Edit intent: fluency
Original:  In this work, we propose streaming algorithms to efficiently approximate graph descriptors by estimating counts of sub-graphs of order k\leq 4, and thereby devise extensions of two existing graph comparison paradigms: the Graphlet Kernel and NetSimile.
Revised:  In this work, we propose streaming algorithms to efficiently approximate descriptors by estimating counts of sub-graphs of order k\leq 4, and thereby devise extensions of two existing graph comparison paradigms: the Graphlet Kernel and NetSimile.
Edit intent: fluency
Original:  We perform extensive experiments on benchmark real-world networks and demonstrate that our algorithms scale well to massive graphs.
Revised:  We perform extensive experiments on real-world networks and demonstrate that our algorithms scale well to massive graphs.
Edit intent: clarity
Original:  We first consider a public goods game on a uniform hypergraph, showing that it corresponds to the replicator dynamics in the well-mixed limit, and providing an exact theoretical foundation to study cooperation in networked groups.
Revised:  We first consider a public goods game on a uniform hypergraph, showing that it corresponds to the replicator dynamics in the well-mixed limit, providing an exact theoretical foundation to study cooperation in networked groups.
Edit intent: coherence
Original:  We also extend the analysis to heterogeneous hypergraphs that describe interactions of groups of different sizes and characterize the evolution of cooperation in such cases .
Revised:  We also extend the analysis to heterogeneous hypergraphs that describe interactions of groups of different sizes affects the evolution of cooperation in such cases .
Edit intent: clarity
Original:  We also extend the analysis to heterogeneous hypergraphs that describe interactions of groups of different sizes and characterize the evolution of cooperation in such cases .
Revised:  We also extend the analysis to heterogeneous hypergraphs that describe interactions of groups of different sizes and characterize the evolution of cooperation .
Edit intent: clarity