wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Methods: We compare the two most common decomposition models -Parallel Factor Analysis (PARAFAC) and Tucker- in muscle synergy extraction from the three main degrees of freedom (DoF) of the wrist using the first Ninapro database.
Revised:  We compare the two most common decomposition models -Parallel Factor Analysis (PARAFAC) and Tucker- in muscle synergy extraction from the three main degrees of freedom (DoF) of the wrist using the first Ninapro database.
Edit intent: coherence
Original:  Methods: We compare the two most common decomposition models -Parallel Factor Analysis (PARAFAC) and Tucker- in muscle synergy extraction from the three main degrees of freedom (DoF) of the wrist using the first Ninapro database.
Revised:  Methods: We compare the two most widespread tensor decomposition models -- Parallel Factor Analysis (PARAFAC) and Tucker- in muscle synergy extraction from the three main degrees of freedom (DoF) of the wrist using the first Ninapro database.
Edit intent: clarity
Original:  Methods: We compare the two most common decomposition models -Parallel Factor Analysis (PARAFAC) and Tucker- in muscle synergy extraction from the three main degrees of freedom (DoF) of the wrist using the first Ninapro database.
Revised:  Methods: We compare the two most common decomposition models -Parallel Factor Analysis (PARAFAC) and Tucker -- in muscle synergy extraction from the three main degrees of freedom (DoF) of the wrist using the first Ninapro database.
Edit intent: fluency
Original:  Methods: We compare the two most common decomposition models -Parallel Factor Analysis (PARAFAC) and Tucker- in muscle synergy extraction from the three main degrees of freedom (DoF) of the wrist using the first Ninapro database.
Revised:  Methods: We compare the two most common decomposition models -Parallel Factor Analysis (PARAFAC) and Tucker- in muscle synergy analysis of the wrist's three main Degree of Freedoms (DoFs) using the public first Ninapro database.
Edit intent: clarity
Original:  We then utilise the power tensor factorisation to create a novel direct method for shared and task-specific synergy estimation from two biomechanically related tasks by developing a constrained Tucker decomposition method .
Revised:  Furthermore, we proposed a constrained Tucker decomposition (consTD) method for efficient synergy extraction building on the power of tensor decompositions. This method is proposed as a direct novel approach for shared and task-specific synergy estimation from two biomechanically related tasks by developing a constrained Tucker decomposition method .
Edit intent: meaning-changed
Original:  Our approach is compared with the current standard approach of repetitively applying non-negative matrix factorisation (NMF) to a series of the movements. Results: The results show that the constrained Tucker method successfully identified the shared and task-specific synergies for all 3 DoF tensorsdirectly and it was robust to misassignments with regard to task-repetition information unlike NMF, thanks to exploring the multi-way structure of muscle activity.
Revised:  Our approach is compared with the current standard approach of repetitively applying non-negative matrix factorisation (NMF) to a series of movements. The results show that the constrained Tucker method successfully identified the shared and task-specific synergies for all 3 DoF tensorsdirectly and it was robust to misassignments with regard to task-repetition information unlike NMF, thanks to exploring the multi-way structure of muscle activity.
Edit intent: clarity
Original:  Results: The results show that the constrained Tucker method successfully identified the shared and task-specific synergies for all 3 DoF tensorsdirectly and it was robust to misassignments with regard to task-repetition information unlike NMF, thanks to exploring the multi-way structure of muscle activity.
Revised:  Results: The results show that the consTD method is suitable for synergy extraction compared to PARAFAC and Tucker. Moreover, exploiting the multi-way structure of muscle activity, the proposed methods successfully identified shared and task-specific synergies for all 3 DoF tensorsdirectly and it was robust to misassignments with regard to task-repetition information unlike NMF, thanks to exploring the multi-way structure of muscle activity.
Edit intent: meaning-changed
Original:  Results: The results show that the constrained Tucker method successfully identified the shared and task-specific synergies for all 3 DoF tensorsdirectly and it was robust to misassignments with regard to task-repetition information unlike NMF, thanks to exploring the multi-way structure of muscle activity.
Revised:  Results: The results show that the constrained Tucker method successfully identified the shared and task-specific synergies for all three DoFs tensors. These were found to be robust to disarrangement with regard to task-repetition information unlike NMF, thanks to exploring the multi-way structure of muscle activity.
Edit intent: clarity
Original:  Results: The results show that the constrained Tucker method successfully identified the shared and task-specific synergies for all 3 DoF tensorsdirectly and it was robust to misassignments with regard to task-repetition information unlike NMF, thanks to exploring the multi-way structure of muscle activity. Conclusions: We showed the potential of tensor factorisations to study and characterise muscle activity and developed a new direct method for shared and task-specific synergy identificationwith a constrained Tucker decomposition.
Revised:  Results: The results show that the constrained Tucker method successfully identified the shared and task-specific synergies for all 3 DoF tensorsdirectly and it was robust to misassignments with regard to task-repetition information , unlike the commonly used NMF. In summary, we demonstrate how to use tensors to characterise muscle activity and developed a new direct method for shared and task-specific synergy identificationwith a constrained Tucker decomposition.
Edit intent: clarity
Original:  Conclusions: We showed the potential of tensor factorisations to study and characterise muscle activity and developed a new direct method for shared and task-specific synergy identificationwith a constrained Tucker decomposition.
Revised:  Conclusions: We showed the potential of tensor factorisations to study and characterise muscle activity and develop a new consTD method for muscle synergy extraction that could be used for shared and task-specific synergy identificationwith a constrained Tucker decomposition.
Edit intent: clarity
Original:  Conclusions: We showed the potential of tensor factorisations to study and characterise muscle activity and developed a new direct method for shared and task-specific synergy identificationwith a constrained Tucker decomposition. Significance: We expect that this study will pave the way for the development of  muscle activity analysis methods based on higher-order techniques.
Revised:  Conclusions: We showed the potential of tensor factorisations to study and characterise muscle activity and developed a new direct method for shared and task-specific synergies identification. We expect that this study will pave the way for the development of muscle activity analysis methods based on higher-order techniques.
Edit intent: clarity
Original: Many real-world dynamical systems can successfully be analyzed using the temporal network formalism. Empirical temporal networks and dynamic processes that take place in these situations show heterogeneous, non-Markovian, and intrinsically correlated dynamics, making their analysis particularly challenging.
Revised: Many real-world dynamical systems can be successfully analyzed by representing them as networks. Empirically measured networks and dynamic processes that take place in these situations show heterogeneous, non-Markovian, and intrinsically correlated dynamics, making their analysis particularly challenging.
Edit intent: clarity
Original:  Defined as ensembles of random networks with given features constrained to match those of an input (empirical) network, they may  be used to identify statistically significant motifs in empirical temporal networks (i.e. overrepresented w.r.t. the null random networks) and to infer the effects of such motifs on dynamical processes unfolding in the network.
Revised:  Defined as ensembles of random networks with given features constrained to match those of an input (empirical) network, they may for example be used to identify statistically significant motifs in empirical temporal networks (i.e. overrepresented w.r.t. the null random networks) and to infer the effects of such motifs on dynamical processes unfolding in the network.
Edit intent: clarity
Original:  Defined as ensembles of random networks with given features constrained to match those of an input (empirical) network, they may  be used to identify statistically significant motifs in empirical temporal networks (i.e. overrepresented w.r.t. the null random networks) and to infer the effects of such motifs on dynamical processes unfolding in the network.
Revised:  Defined as ensembles of random networks with given features constrained to match those of an input (empirical) network, they may be used to identify important features of empirical networks and their effects on dynamical processes unfolding in the network.
Edit intent: clarity
Original:   However, the effects of most randomization procedures on temporal network characteristics remain poorly understood, rendering their use non-trivial and susceptible to misinterpretation.
Revised:  RRMs are typically implemented as procedures that reshuffle an empirical network, making them very generally applicable. However, the effects of most randomization procedures on temporal network characteristics remain poorly understood, rendering their use non-trivial and susceptible to misinterpretation.
Edit intent: meaning-changed
Original:  We provide a tutorial for the use of MRRMs to analyze an empirical temporal network and we review applications of MRRMs found in literature .
Revised:  We provide two tutorials showing applications of the MRRM framework to empirical temporal networks: 1) to analyze how different features of a network affect other features and 2) to analyze how such features affect a dynamic process in the network. We finally survey applications of MRRMs found in literature .
Edit intent: meaning-changed
Original:  We provide a tutorial for the use of MRRMs to analyze an empirical temporal network and we review applications of MRRMs found in literature . The taxonomy of MRRMs we have developed provides a reference to ease the use of MRRMs, and the theoretical foundations laid here may further serve as a base for the development of a principled and systematic way to generate and apply randomized reference null models for the study of temporal networks .
Revised:  We provide a tutorial for the use of MRRMs to analyze an empirical temporal network and we review applications of MRRMs found in literature .
Edit intent: coherence
Original:   In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, suggesting early warning signals of two majors price collapse that have happened in those periods.
Revised:  Therefore, while the autocorrelation does not display signals of critical slowing down, the standard deviation can be used to anticipate critical or stochastic transitions. In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, suggesting early warning signals of two majors price collapse that have happened in those periods.
Edit intent: meaning-changed
Original:   In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, suggesting early warning signals of two majors price collapse that have happened in those periods.
Revised:  In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, which could have served as early warning signals of two majors price collapse that have happened in those periods.
Edit intent: clarity
Original:   In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, suggesting early warning signals of two majors price collapse that have happened in those periods.
Revised:  In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, suggesting early warning signals of two majors price collapses that have happened in those periods.
Edit intent: fluency
Original:   In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, suggesting early warning signals of two majors price collapse that have happened in those periods.
Revised:  In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, suggesting early warning signals of two majors price collapse that have happened in the following periods. We finally propose a mean-field phenomenological model for the price of crypto-currency to show how the use of the standard deviation of the residuals is a better leading indicator of the collapse in price than the time series' autocorrelation.
Edit intent: meaning-changed
Original:  One hypothesis proposes that rapid action potential onset is caused by the  separation of the axon initial segment, that is the initiation site of action potentials, from the soma, and that this spatial separation also results in ultrafast population encoding.
Revised:  One hypothesis proposes that the sharp action potential onset is caused by the separation of the axon initial segment, that is the initiation site of action potentials, from the soma, and that this spatial separation also results in ultrafast population encoding.
Edit intent: clarity
Original:  One hypothesis proposes that rapid action potential onset is caused by the  separation of the axon initial segment, that is the initiation site of action potentials, from the soma, and that this spatial separation also results in ultrafast population encoding.
Revised:  One hypothesis proposes that rapid action potential onset is caused by the electrotonic separation of the axon initial segment, that is the initiation site of action potentials, from the soma, and that this spatial separation also results in ultrafast population encoding.
Edit intent: meaning-changed
Original:  One hypothesis proposes that rapid action potential onset is caused by the  separation of the axon initial segment, that is the initiation site of action potentials, from the soma, and that this spatial separation also results in ultrafast population encoding.
Revised:  One hypothesis proposes that rapid action potential onset is caused by the separation of the site of action potentials, from the soma, and that this spatial separation also results in ultrafast population encoding.
Edit intent: clarity
Original:  One hypothesis proposes that rapid action potential onset is caused by the  separation of the axon initial segment, that is the initiation site of action potentials, from the soma, and that this spatial separation also results in ultrafast population encoding.
Revised:  One hypothesis proposes that rapid action potential onset is caused by the separation of the axon initial segment, that is the initiation site of action potential initiation from the soma, and that this spatial separation also results in ultrafast population encoding.
Edit intent: clarity
Original:  We find that  the axonal initiation site position is not sufficient to generate an ultrafast response and reproduce the high bandwidth observed in cortical neuron populations .
Revised:  We find that placing the initiation site at different axonal positions has only a weak impact on the linear response function of the model. It fails to generate the axonal initiation site position is not sufficient to generate an ultrafast response and reproduce the high bandwidth observed in cortical neuron populations .
Edit intent: meaning-changed
Original:  In the light of recent experimental evidence about neural activity dependent repositioning of the axon initial segment and the resulting question about the functional properties of this phenomenon , our study predicts that , while it can lead to more rapid action potential onsets in the soma, it does not affect the linear response of a population of neurons.
Revised:  In the light of recent reports of activity-dependent repositioning of the axon initial segment and the resulting question about the functional properties of this phenomenon , our study predicts that , while it can lead to more rapid action potential onsets in the soma, it does not affect the linear response of a population of neurons.
Edit intent: clarity
Original:  In the light of recent experimental evidence about neural activity dependent repositioning of the axon initial segment and the resulting question about the functional properties of this phenomenon , our study predicts that , while it can lead to more rapid action potential onsets in the soma, it does not affect the linear response of a population of neurons.
Revised:  In the light of recent experimental evidence about neural activity dependent repositioning of the axon initial segment , our study predicts that , while it can lead to more rapid action potential onsets in the soma, it does not affect the linear response of a population of neurons.
Edit intent: coherence
Original:  In the light of recent experimental evidence about neural activity dependent repositioning of the axon initial segment and the resulting question about the functional properties of this phenomenon , our study predicts that , while it can lead to more rapid action potential onsets in the soma, it does not affect the linear response of a population of neurons.
Revised:  In the light of recent experimental evidence about neural activity dependent repositioning of the axon initial segment and the resulting question about the functional properties of this phenomenon , our study predicts that a more distal initiation site can lead to more rapid action potential onsets in the soma, it does not affect the linear response of a population of neurons.
Edit intent: meaning-changed
Original:  In the light of recent experimental evidence about neural activity dependent repositioning of the axon initial segment and the resulting question about the functional properties of this phenomenon , our study predicts that , while it can lead to more rapid action potential onsets in the soma, it does not affect the linear response of a population of neurons.
Revised:  In the light of recent experimental evidence about neural activity dependent repositioning of the axon initial segment and the resulting question about the functional properties of this phenomenon , our study predicts that , while it can lead to an increased sharpness of the somatic waveform but it does not affect the linear response of a population of neurons.
Edit intent: meaning-changed
Original:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific  starting point that is independent of such inputs.
Revised:  We assess the potential magnitude of this bias by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific starting point that is independent of such inputs.
Edit intent: clarity
Original:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific  starting point that is independent of such inputs.
Revised:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low- and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific starting point that is independent of such inputs.
Edit intent: fluency
Original:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific  starting point that is independent of such inputs.
Revised:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components ; 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific starting point that is independent of such inputs.
Edit intent: fluency
Original:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific  starting point that is independent of such inputs.
Revised:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific starting point that is independent of such inputs.
Edit intent: coherence
Original:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific  starting point that is independent of such inputs.
Revised:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and 2) a country-specific starting point that is independent of such inputs.
Edit intent: fluency
Original:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific  starting point that is independent of such inputs.
Revised:  We assess the potential magnitude of this problem by decomposing variation in HAZ from 1,406,609 children from 63 low-and middle-income countries into two components : ( 1) a component shaped by environmental inputs, such as poverty, infectious disease, inadequate sanitation, and healthcare access, and ( 2) a country-specific basal starting point that is independent of such inputs.
Edit intent: fluency