wanyu/IteraTeR_v2 huggingface dataset:
Original:  Within a perturbation analysis of the model from the infinite mixing rate, we provide analytical evidence that extinction occurs deterministically at sufficiently large but finite values of the mixing rate for any odd species numbers\ge3 . Further,  we discuss numerical results concerning the trajectories toward such deterministic extinction, including bifurcations, in more general cases .
Revised:  Within a perturbation analysis of the model from the infinite mixing rate, we provide analytical evidence that extinction occurs deterministically at sufficiently large but finite values of the mixing rate for any odd species numbers\ge3 . Further, we discuss numerical results concerning the trajectories toward such deterministic extinction, including global bifurcations caused by changing the mixing rate .
Edit intent: clarity
Original:  We show that a simple transformation of the network's adjacency matrix provides an understanding of ? the origins of occurrence of high multiplicities in the networks spectra.
Revised:  We show that a simple transformation of the network's adjacency matrix provides an understanding of the origins of occurrence of high multiplicities in the networks spectra.
Edit intent: fluency
Original:  Elegant and simple models, such as preferential attachment and link copying , model only rich-gets-richer effects, not aging and decline.
Revised:  Preferential attachment and link copying , model only rich-gets-richer effects, not aging and decline.
Edit intent: clarity
Original:  Elegant and simple models, such as preferential attachment and link copying , model only rich-gets-richer effects, not aging and decline.
Revised:  Elegant and simple models, such as preferential attachment and link copying models, while elegant and simple, only capture rich-gets-richer effects, not aging and decline.
Edit intent: clarity
Original:  We argue that traditional network characterization , or even per-node linking dynamics , are insufficient to judge the faithfulness of models.
Revised:  We argue that traditional characterization of linking dynamics are insufficient to judge the faithfulness of models.
Edit intent: clarity
Original:  We propose a new temporal sketch of an evolving graph, and introduce three new characterizations of a network's temporal dynamics.
Revised:  We propose a new temporal sketch of an evolving graph, and introduce several new characterizations of a network's temporal dynamics.
Edit intent: clarity
Original:  Then we propose a new family of frugal aging models with no per-node parameters and only 2-3 global parameters.
Revised:  Then we propose a new family of frugal aging models with no per-node parameters and only two global parameters.
Edit intent: clarity
Original:  Despite very few parameters, the new model shows remarkably better fit with real data.
Revised:  Despite very few parameters, the new family of models shows remarkably better fit with real data.
Edit intent: clarity
Original:  Estimating parameters of our model for various research communities yields further insights into their comparative dynamics  .
Revised:  Estimating parameters of our model for various research communities yielding further insights into their comparative dynamics .
Edit intent: fluency
Original:  Preferential attachment and link copying models, while elegant and simple , only capture rich-gets-richer effects, not aging and decline.
Revised:  Preferential attachment and link copying models, while enabling elegant analysis , only capture rich-gets-richer effects, not aging and decline.
Edit intent: clarity
Original:  At the closing , we analyze temporal signatures for various research communities yielding further insights into their comparative dynamics.
Revised:  Before concluding , we analyze temporal signatures for various research communities yielding further insights into their comparative dynamics.
Edit intent: clarity
Original:  In this paper we present a comprehensive study of the energy complexity of fundamental problems in wireless networks with four different levels of collision detection : Strong-CD (in which transmitters and listeners detect collisions), Sender-CD (in which transmitters detect collisions, indirectly), Receiver-CD (in which  listeners detect collisions), and No-CD (in which no one detects collisions ).
Revised:  In this paper we study the energy complexity of fundamental problems in wireless networks with four different levels of collision detection : Strong-CD (in which transmitters and listeners detect collisions), Sender-CD (in which transmitters detect collisions, indirectly), Receiver-CD (in which listeners detect collisions), and No-CD (in which no one detects collisions ).
Edit intent: clarity
Original:  We show that the randomized energy complexity of Approximate Counting and Leader Election is \Omega (\log^* n) in Sender-CD and No-CD but \Omega (\log(\log^* n)) in Strong-CD and Receiver-CD, and also provide matching upper bounds.
Revised:  We show that the randomized energy complexity of Approximate Counting and Leader Election is \Omega (\log^* n) in Sender-CD and No-CD but \Omega (\log(\log^* n)) in Receiver-CD, and also provide matching upper bounds.
Edit intent: fluency
Original:  In the deterministic setting, all n devices have unique IDs in the range N%DIFDELCMD < ]%%% . We establish another exponential separation between the deterministic Sender-CD and Receiver-CD models in the opposite direction.
Revised:  In the deterministic setting, all n devices have unique IDs in the range %DIFDELCMD < ]%%% . We establish another exponential separation between the deterministic Sender-CD and Receiver-CD models in the opposite direction.
Edit intent: clarity
Original:  We show that Leader Election can be solved with O (\log\log N) energy in the deterministic Sender-CD model, and give a matching \Omega(\log \log N ) energy lower bound in the Strong-CD model.
Revised:  We show that Leader Election can be solved with O (\log\log N) in Sender-CD model, and give a matching \Omega(\log \log N ) energy lower bound in the Strong-CD model.
Edit intent: clarity
Original: This paper focuses on cognitive radio (CR) internet-of-things (IoT) networks where spectrum sensors are deployed for IoT CR devices, which do not have enough hardware capability to identify an unoccupied spectrum by themselves.
Revised: This paper focuses on cognitive radio (CR) internet- of-things (IoT) networks where spectrum sensors are deployed for IoT CR devices, which do not have enough hardware capability to identify an unoccupied spectrum by themselves.
Edit intent: fluency
Original:  In this sensor-enabled IoT CR network, the CR devices and the sensors are separated.
Revised:  In this sensor- enabled IoT CR network, the CR devices and the sensors are separated.
Edit intent: fluency
Original:  Our scheme improves area spectral efficiency (ASE) compared to  conventional ALOHA and an adaptive transmission scheme which attempts to send data when the sensor measurement is lower than an interference threshold.
Revised:  Our scheme improves area spectral efficiency (ASE) compared to a conventional ALOHA and an adaptive transmission scheme which attempts to send data when the sensor measurement is lower than an interference threshold.
Edit intent: fluency
Original:  We prove the following for the  square G^2 of G. If \omega\le 3, then its chromatic number satisfies \chi(G^2)\le 10 while its stability number satisfies \alpha(G^2)%DIFDELCMD < \ge %%% n/9 unless one of its components is a 10-vertex clique.
Revised:  We prove the following for the chromatic number \chi(G^2) of the square G^2 of G. If \omega\le 3, then its chromatic number satisfies \chi(G^2)\le 10 while its stability number satisfies \alpha(G^2)%DIFDELCMD < \ge %%% n/9 unless one of its components is a 10-vertex clique.
Edit intent: clarity
Original:  We prove the following for the  square G^2 of G. If \omega\le 3, then its chromatic number satisfies \chi(G^2)\le 10 while its stability number satisfies \alpha(G^2)%DIFDELCMD < \ge %%% n/9 unless one of its components is a 10-vertex clique.
Revised:  We prove the following for the square G^2 of G. If \omega\le 3, then \chi(G^2)\le 10 while its stability number satisfies \alpha(G^2)%DIFDELCMD < \ge %%% n/9 unless one of its components is a 10-vertex clique.
Edit intent: clarity
Original:  We prove the following for the  square G^2 of G. If \omega\le 3, then its chromatic number satisfies \chi(G^2)\le 10 while its stability number satisfies \alpha(G^2)%DIFDELCMD < \ge %%% n/9 unless one of its components is a 10-vertex clique.
Revised:  We prove the following for the square G^2 of G. If \omega\le 3, then its chromatic number satisfies \chi(G^2)\le %DIFDELCMD < \ge %%% n/9 unless one of its components is a 10-vertex clique.
Edit intent: clarity
Original:  If \omega \le 4, then \chi(G^2) \le 22 and \alpha(G^2)%DIFDELCMD < \ge %%% n/20.
Revised:  If \omega \le 4, then \chi(G^2) \le %DIFDELCMD < \ge %%% n/20.
Edit intent: coherence
Original:  This work is motivated by a  conjecture of Erdos and Nesetril and provides further evidence for a strengthened form of that conjecture .
Revised:  This work is motivated by a strengthened form of a conjecture of Erdos and Nesetril and provides further evidence for a strengthened form of that conjecture .
Edit intent: fluency
Original:  This work is motivated by a  conjecture of Erdos and Nesetril and provides further evidence for a strengthened form of that conjecture .
Revised:  This work is motivated by a conjecture of Erdos and Nesetril .
Edit intent: clarity
Original:  We prove the following for the chromatic number \chi(G^2) of the square G^2 of G. If \omega \le  3, then \chi(G^2) %DIFDELCMD < \le %%%  10. If \omega%DIFDELCMD < \le %%%  4, then \chi(G^2) %DIFDELCMD < \le %%% 22.
Revised:  We prove the following for the chromatic number \chi(G^2) of the square G^2 of G. If \omega \le 3, then \chi(G^2) %DIFDELCMD < \le %%% 10. %DIFDELCMD < \le %%% 4, then \chi(G^2) %DIFDELCMD < \le %%% 22.
Edit intent: coherence
Original:  We prove the following for the chromatic number \chi(G^2) of the square G^2 of G. If \omega \le  3, then \chi(G^2) %DIFDELCMD < \le %%%  10. If \omega%DIFDELCMD < \le %%%  4, then \chi(G^2) %DIFDELCMD < \le %%% 22.
Revised:  We prove the following for the chromatic number \chi(G^2) of the square G^2 of G. If \omega \le 3, then \chi(G^2) %DIFDELCMD < \le %%% 10. If \omega%DIFDELCMD < \le %%% 4, this implies \chi(G^2) %DIFDELCMD < \le %%% 22.
Edit intent: coherence
Original: This paper concerns the behavior of hyperelastic energies depending on an internal parameter .
Revised: The behavior of hyperelastic energies depending on an internal parameter .
Edit intent: clarity
Original:  Second, two models where the parameter describes the activation of  skeletal muscle tissue are analyzed .
Revised:  Second, two models where the parameter describes the activation of skeletal muscle tissue is presented .
Edit intent: clarity
Original:  In those models, the activation parameter depends on the strain and it is important to consider the derivative of the parameter with respect to the strain in order to capture the proper behavior of the stress .
Revised:  In those models, the activation parameter depends on the strain and it is shown the importance of considering the derivative of the parameter with respect to the strain in order to capture the proper behavior of the stress .
Edit intent: coherence
Original:  In those models, the activation parameter depends on the strain and it is important to consider the derivative of the parameter with respect to the strain in order to capture the proper behavior of the stress .
Revised:  In those models, the activation parameter depends on the strain and it is important to consider the derivative of the parameter with respect to the strain in order to capture the proper stress-strain relations .
Edit intent: clarity
Original: In the Sparse Linear Regression (SLR) problem, given a d \times n matrix M and a d-dimensional vector q, we want to compute a k-sparse  vector \tau such that the error ||M \tau-q|| is minimized.
Revised: In the Sparse Linear Regression (SLR) problem, given a d \times n matrix M and a d-dimensional query q, the goal is to compute a k-sparse vector \tau such that the error ||M \tau-q|| is minimized.
Edit intent: clarity
Original:  In particular, we show that the online variant of all three problems can be solved with query time \tilde O(n^{k-1}) .
Revised:  In particular, we present approximation algorithms for the online variants of the above problems with query time \tilde O(n^{k-1}) .
Edit intent: clarity
Original:  This provides non-trivial improvements over the naive algorithm that exhaustively searches all n%DIFDELCMD < \choose %%%  k subsets B.
Revised:  This provides non-trivial improvements over the naive algorithm that exhaustively searches all %DIFDELCMD < \choose %%% k subsets B.
Edit intent: clarity
Original:  To our knowledge, no method to compute this distribution has been presented in the literature to date.
Revised:  To our knowledge, no method to compute these distributions has been presented in the literature to date.
Edit intent: style
Original:  We show that the joint distribution can be obtained from the solution of a certain system of linear hyperbolic partial differential equations.
Revised:  We show that they can be obtained from the solution of a certain system of linear hyperbolic partial differential equations.
Edit intent: clarity
Original: In recent years, a number of methods have been developed to infer complex demographic histories, especially historical population size changes, from genomic sequence data , and Coalescent Hidden Markov Models have proven to be particularly useful for this type of inference.
Revised: In recent years, a number of methods have been developed to infer complex demographic histories, especially historical population size changes, from genomic sequence data . Coalescent Hidden Markov Models have proven to be particularly useful for this type of inference.
Edit intent: coherence
Original:  Due to the Markovian structure of these models, an essential building block is the joint distribution of local genealogies , or statistics of these genealogies, at two linked loci in populations of variable size.
Revised:  Due to the Markovian structure of these models, an essential building block is the joint distribution of local genealogical trees , or statistics of these genealogies, at two linked loci in populations of variable size.
Edit intent: clarity
Original:  Due to the Markovian structure of these models, an essential building block is the joint distribution of local genealogies , or statistics of these genealogies, at two linked loci in populations of variable size.
Revised:  Due to the Markovian structure of these models, an essential building block is the joint distribution of local genealogies , or statistics of these genealogies, at two neighboring loci in populations of variable size.
Edit intent: clarity
Original:  Here, we present a novel method to compute the marginal and  joint distribution of the total length of the genealogical trees at two linked loci for samples of arbitrary size.
Revised:  Here, we present a novel method to compute the marginal and the joint distribution of the total length of the genealogical trees at two linked loci for samples of arbitrary size.
Edit intent: fluency
Original:  We show that they can be obtained from the solution of a certain system of linear hyperbolic partial differential equations.
Revised:  We show that they can be obtained from the solution of certain hyperbolic systems of partial differential equations.
Edit intent: clarity
Original:  We present a numerical algorithm  based on the Method of Characteristics that can be used to efficiently and accurately solve the system and compute the marginal and the joint distribution .
Revised:  We present a numerical algorithm , based on the Method of Characteristics that can be used to efficiently and accurately solve the system and compute the marginal and the joint distribution .
Edit intent: fluency
Original:  We present a numerical algorithm  based on the Method of Characteristics that can be used to efficiently and accurately solve the system and compute the marginal and the joint distribution .
Revised:  We present a numerical algorithm based on the method of characteristics, that can be used to efficiently and accurately solve the system and compute the marginal and the joint distribution .
Edit intent: fluency
Original:  We present a numerical algorithm  based on the Method of Characteristics that can be used to efficiently and accurately solve the system and compute the marginal and the joint distribution .
Revised:  We present a numerical algorithm based on the Method of Characteristics that can be used to efficiently and accurately solve these systems and compute the marginal and the joint distribution .
Edit intent: clarity
Original:  We present a numerical algorithm  based on the Method of Characteristics that can be used to efficiently and accurately solve the system and compute the marginal and the joint distribution .
Revised:  We present a numerical algorithm based on the Method of Characteristics that can be used to efficiently and accurately solve the system and compute the marginal and the joint distributions .
Edit intent: fluency
Original:  We demonstrate its utility to study  properties of the joint distribution.
Revised:  We demonstrate its utility to study the properties of the joint distribution.
Edit intent: fluency
Original:  We are interested in the convergence time to the equilibrium as a function of this probability, the degree of the network, and the potential of the underlying games  .
Revised:  We are interested in the convergence time to an equilibrium as a function of this probability, the degree of the network, and the potential of the underlying games .
Edit intent: fluency
Original: We address the problem to control a population of noncooperative heterogeneous agents, each with strongly convex cost function depending on the average population state, and all sharing a convex constraint, towards a competitive aggregative equilibrium.
Revised: We address the problem to control a population of noncooperative heterogeneous agents, each with convex cost function depending on the average population state, and all sharing a convex constraint, towards a competitive aggregative equilibrium.
Edit intent: clarity
Original: We address the problem to control a population of noncooperative heterogeneous agents, each with strongly convex cost function depending on the average population state, and all sharing a convex constraint, towards a competitive aggregative equilibrium.
Revised: We address the problem to control a population of noncooperative heterogeneous agents, each with strongly convex cost function depending on the average population state, and all sharing a convex constraint, towards an aggregative equilibrium.
Edit intent: clarity
Original:  We assume an information structure through which a central controller has access to the average population state and can broadcast control signals for steering the decentralized optimal responses of the agents.
Revised:  We assume an information structure through which a central coordinator has access to the average population state and can broadcast control signals for steering the decentralized optimal responses of the agents.
Edit intent: fluency
Original:  We propose a dynamic control law that, based on monotone operator theory arguments, ensures global convergence to an equilibrium independently on the problem data, that are the cost functions and the constraints, local and global, of the agents.
Revised:  We design a dynamic control law that, based on monotone operator theory arguments, ensures global convergence to an equilibrium independently on the problem data, that are the cost functions and the constraints, local and global, of the agents.
Edit intent: clarity
Original:  We propose a dynamic control law that, based on monotone operator theory arguments, ensures global convergence to an equilibrium independently on the problem data, that are the cost functions and the constraints, local and global, of the agents.
Revised:  We propose a dynamic control law that, based on operator theoretic arguments, ensures global convergence to an equilibrium independently on the problem data, that are the cost functions and the constraints, local and global, of the agents.
Edit intent: clarity
Original:  We illustrate the proposed method in two application domains: demand side management and network congestion control  .
Revised:  We illustrate the proposed method in two application domains: network congestion control .
Edit intent: clarity
Original:  Previous work addressing  stance classification task in Twitter has treated each tweet as a separate unit.
Revised:  Previous work addressing the stance classification task in Twitter has treated each tweet as a separate unit.
Edit intent: fluency
Original:  Previous work addressing  stance classification task in Twitter has treated each tweet as a separate unit.
Revised:  Previous work addressing stance classification task has treated each tweet as a separate unit.
Edit intent: clarity
Original:  Here we analyse tweets by virtue of their position in a sequence and test two sequential classifiers, Linear-Chain CRF and Tree CRF, each of which makes different assumptions about the conversation structure.
Revised:  Here we analyse tweets by virtue of their position in a sequence and test two sequential classifiers, Linear-Chain CRF and Tree CRF, each of which makes different assumptions about the conversational structure.
Edit intent: fluency
Original:  By employing a set of rotational invariants  , we analytically reveal the nontrivial topology of  parameter estimation landscape, showing that multiple branches of parameters describe the measurement almost equally well, with only one of them corresponding to the biophysical reality.
Revised:  By employing a set of rotational invariants , we analytically uncover the nontrivial topology of parameter estimation landscape, showing that multiple branches of parameters describe the measurement almost equally well, with only one of them corresponding to the biophysical reality.
Edit intent: clarity
Original:  By employing a set of rotational invariants  , we analytically reveal the nontrivial topology of  parameter estimation landscape, showing that multiple branches of parameters describe the measurement almost equally well, with only one of them corresponding to the biophysical reality.
Revised:  By employing a set of rotational invariants , we analytically reveal the nontrivial topology of the parameter estimation landscape, showing that multiple branches of parameters describe the measurement almost equally well, with only one of them corresponding to the biophysical reality.
Edit intent: fluency
Original:  A comprehensive acquisition shows that the branch choice differs for white and for gray matter .
Revised:  A comprehensive acquisition shows that the branch choice varies across the brain .
Edit intent: clarity
Original:  For this so-called stochastic households model, we provide a method for inferring the model parameters -- governing within-household transmission, recovery, and between-household transmission -- from data of the day upon which each individual became infectious and the household in which each infection occurred .
Revised:  For this so-called stochastic households model, we provide a method for inferring the model parameters---governing within-household transmission, recovery, and between-household transmission -- from data of the day upon which each individual became infectious and the household in which each infection occurred .
Edit intent: fluency