wanyu/IteraTeR_v2 huggingface dataset:
Original:  In theory, the study of the hardness of fitness functions can help understand the ability of evolutionary algorithms (EAs).
Revised:  In theory, the study can help understanding the ability of evolutionary algorithms (EAs).
Edit intent: clarity
Original:  The aim of this paper is to answer the question: what are the easiest and hardest fitness functions with respect to an EA and how will such functions be constructed?
Revised:  The aim of this paper is to answer the question: what are the easiest with respect to an EA and how will such functions be constructed?
Edit intent: clarity
Original:  In the paper , the easiest fitness (and hardest ) fitness functions have been constructed to any given elitist (1+1) EA for maximising any class of fitness functions with the same optima.
Revised:  In the paper , the easiest fitness (and hardest ) fitness functions have been constructed to any given elitist (1+1) EA in maximising a class of fitness functions with the same optima.
Edit intent: fluency
Original:  In terms of the time-fitness landscape, the unimodal functions are the easiest and deceptive functions are the hardest.
Edit intent: coherence
Original:  The paper also reveals that a fitness function , that is easiest to one EA , may become the hardest to another EA, and vice versa.
Revised:  The paper also reveals that a fitness function that is easiest to one EA , may become the hardest to another EA, and vice versa.
Edit intent: fluency
Original:  The paper also reveals that a fitness function , that is easiest to one EA , may become the hardest to another EA, and vice versa.
Revised:  The paper also reveals that a fitness function , that is easiest to one EA may become the hardest to another EA, and vice versa.
Edit intent: fluency
Original:  In theory, the study can help understanding the ability of evolutionary algorithms (EAs) .
Revised:  In theory, the study can help understanding the ability of evolutionary algorithms .
Edit intent: clarity
Original:  The easiest and hardest fitness functions are constructed for an elitist (1+1) EA in maximising a class of fitness functions with the same optima.
Revised:  The easiest and hardest fitness functions are constructed for an elitist (1+1) evolutionary algorithm to maximise a class of fitness functions with the same optima.
Edit intent: clarity
Original:   The paper also reveals that a fitness function that is easiest to one EA may become the hardest to another EA , and vice versa.
Revised:  The paper also reveals that the easiest fitness function to one algorithm may become the hardest to another EA , and vice versa.
Edit intent: clarity
Original:   The paper also reveals that a fitness function that is easiest to one EA may become the hardest to another EA , and vice versa.
Revised:  The paper also reveals that a fitness function that is easiest to one EA may become the hardest to another algorithm , and vice versa.
Edit intent: clarity
Original: Given a set of  terminals, which are points in d-dimensional Euclidean space, the minimum Manhattan network problem (MMN) asks for a minimum-length rectilinear network that connects each pair of terminals by a Manhattan path, that is, a path consisting of axis-parallel segments whose total length equals the pair's Manhattan distance.
Revised: Given a set of terminals, which are points in d-dimensional Euclidean space, the minimum Manhattan network problem (MMN) asks for a minimum-length rectilinear network that connects each pair of terminals by a Manhattan path, that is, a path consisting of axis-parallel segments whose total length equals the pair's Manhattan distance.
Edit intent: fluency
Original:  For d \ge 3, the problem is APX-hard and an approximation algorithm with a ratio of\eps  O(n ^\epsilon)for any \epsilon > 0 is known .
Revised:  For d \ge 3, the problem is APX-hard and an approximation algorithm with a ratio of\eps O(n ^\eps)-approximation .
Edit intent: clarity
Original:  In the generalized minimum Manhattan network problem (GMMN), we are given a set R of n terminal pairs , and the goal is to find a minimum-length rectilinear network such that each pair in R is connected by a Manhattan path.
Revised:  In the generalized minimum Manhattan network problem (GMMN), we are given a set R of n terminal pairs , and the goal is to find a minimum-length rectilinear network such that each pair in R is connected by a Manhattan path.
Edit intent: fluency
Original:  These conditions are weaker than earlier ones invoked to establish kinetic system injectivity, which, in turn, is just one ramication of network concordance.
Revised:  These conditions are weaker than earlier ones invoked to establish kinetic system injectivity, which, in turn, is just one ramification of network concordance.
Edit intent: fluency
Original:  Because the Species Reaction Graph resembles pathway depictions often drawn by biochemists, results here expand the possibility of inferring significant dynamical information directly from standard biochemical reaction diagrams.
Revised:  Because the Species-Reaction Graph resembles pathway depictions often drawn by biochemists, results here expand the possibility of inferring significant dynamical information directly from standard biochemical reaction diagrams.
Edit intent: fluency
Original:  Because the Species Reaction Graph resembles pathway depictions often drawn by biochemists, results here expand the possibility of inferring significant dynamical information directly from standard biochemical reaction diagrams.
Revised:  Because the Species Reaction Graph resembles pathway depictions often drawn by biochemists, results here expand the possibility of inferring signicant dynamical information directly from standard biochemical reaction diagrams.
Edit intent: fluency
Original:  The new result is a modification of a proposition of Diaconis and Stroock from 1991 Annals of Applied Probability 1 (1991), 36-61, Proposition 2%DIFDELCMD < ] %%% inspired by Sinclair's multicommodity flow approach to bounding the second-largest eigenvalue.
Revised:  The new result is a modification of a proposition of Diaconis and Stroock from 1991 %DIFDELCMD < ] %%% inspired by Sinclair's multicommodity flow approach to bounding the second-largest eigenvalue.
Edit intent: coherence
Original: We introduce a new family of Rock-Paper-Scissors type models with Z_N symmetry (N is the number of species) and we show that it has a very rich structure with many completely different phases.
Revised: We introduce a family of Rock-Paper-Scissors type models with Z_N symmetry (N is the number of species) and we show that it has a very rich structure with many completely different phases.
Edit intent: coherence
Original:  We study realizations which lead to the formation of partnership domains, where two or more species coexist, separated by interfaces whose dynamics is controlled by interactions of identical strength between competing species.
Revised:  We study realizations which lead to the formation of domains, where two or more species coexist, separated by interfaces whose dynamics is controlled by interactions of identical strength between competing species.
Edit intent: clarity
Original:  This behavior leads to pattern formation and interface network evolution which are similar , in a statistical sense, to those of several other nonlinear systems  .
Revised:  This behavior leads to pattern formation and interface network evolution and pattern formation similar to the ones of several other nonlinear systems .
Edit intent: clarity
Original:  Such ability is fundamental for living beings to survive: to leverage resources and to avoid the danger.
Revised:  Such ability is fundamental for living beings to survive: to leverage resources and to avoid danger.
Edit intent: fluency
Original:  Consequently, the greater the dynamic range, the greater  the probability of survival.
Revised:  Consequently, the larger is the dynamic range, the greater the probability of survival.
Edit intent: clarity
Original:  Consequently, the greater the dynamic range, the greater  the probability of survival.
Revised:  Consequently, the greater the dynamic range, the greater is the probability of survival.
Edit intent: clarity
Original:  We investigate how  integration of different input signals affects the dynamic range, and in general the collective behavior of a network of excitable units.
Revised:  We investigate how the integration of different input signals affects the dynamic range, and in general the collective behavior of a network of excitable units.
Edit intent: fluency
Original:  By means of numerical simulations and a mean-field approach  we explore the non-equilibrium phase transition in the presence of integration.
Revised:  By means of numerical simulations and a mean-field approach , we explore the non-equilibrium phase transition in the presence of integration.
Edit intent: fluency
Original:  By means of numerical simulations and a mean-field approach  we explore the non-equilibrium phase transition in the presence of integration.
Revised:  By means of numerical simulations and a mean-field approach we explore the nonequilibrium phase transition in the presence of integration.
Edit intent: fluency
Original: We investigate a heterogeneous cellular automaton, where there are two types of agents, conformists and rebels . Each agent has to choose between two actions, 0 and 1. A conformist likes to choose an action that most of her neighbors choose, while in contrast a rebel wants to be different with most of her neighbors.
Revised: We investigate a heterogeneous cellular automaton, where there are two types of agents, conformists and rebels . 
Edit intent: coherence
Original:  A large number of simulations show that in most case agents can reach extraordinarily high degree of coordination.
Revised:  A large number of simulations show that in most cases people can reach an extraordinarily high degree of coordination.
Edit intent: clarity
Original:  Considering that these dynamics are really simple, agents are selfish, myopic, and have very limited information, our findings are rather surprising and exciting .
Revised:  Considering that these dynamics are really simple, agents are selfish, myopic, naive, and local interactions .
Edit intent: clarity
Original:  Phase transition, as well as emergence of many interesting patterns, such as continents, strips, mazes, and wheels, are also observed.
Revised:  Phase transition, as well as emergence of many interesting patterns, is also observed.
Edit intent: coherence
Original:  Simulation shows that  in most cases people can reach an extraordinarily high degree of cooperation, through  selfish, myopic, naive, and local interactions.
Revised:  Simulation shows that in most cases people can reach an extraordinarily high level of cooperation, through selfish, myopic, naive, and local interactions.
Edit intent: clarity
Original:  Simulation shows that  in most cases people can reach an extraordinarily high degree of cooperation, through  selfish, myopic, naive, and local interactions.
Revised:  Simulation shows that in most cases people can reach an extraordinarily high degree of cooperation, through a selfish, myopic, naive, and local interactions.
Edit intent: fluency
Original:  On the computational side, it reveals that calculating reactions free energy and correcting reaction fluxes from infeasible loops are dual problems whose solutions are alternatively inconsistent.
Revised:  On the computational side, it reveals that calculating reactions free energy and searching infeasible loops in flux states are dual problems whose solutions are alternatively inconsistent.
Edit intent: clarity
Original:  The unbiased algorithm also allows to determine the optimal folding temperature and takes by 3--4 orders of magnitude less time steps than those needed to compute folding times.
Revised:  The unbiased algorithm also allows to determine the optimal folding temperature and takes at least 3--4 orders of magnitude less time steps than those needed to compute folding times.
Edit intent: clarity
Original: Identifying the infection sources in a network, including the individuals who started a rumor in a social network, the computers that introduce a virus into a computer network, or the index cases of a contagious disease , plays a critical role in limiting the damage caused by the infection through timely quarantine of the sources.
Revised: Identifying the infection sources in a network, including the index cases that introduce a contagious disease into a population network, the computers that introduce a virus into a computer network, or the index cases of a contagious disease , plays a critical role in limiting the damage caused by the infection through timely quarantine of the sources.
Edit intent: clarity
Original: Identifying the infection sources in a network, including the individuals who started a rumor in a social network, the computers that introduce a virus into a computer network, or the index cases of a contagious disease , plays a critical role in limiting the damage caused by the infection through timely quarantine of the sources.
Revised: Identifying the infection sources in a network, including the individuals who started a rumor in a social network, the servers that inject a computer virus into a computer network, or the index cases of a contagious disease , plays a critical role in limiting the damage caused by the infection through timely quarantine of the sources.
Edit intent: clarity
Original: Identifying the infection sources in a network, including the individuals who started a rumor in a social network, the computers that introduce a virus into a computer network, or the index cases of a contagious disease , plays a critical role in limiting the damage caused by the infection through timely quarantine of the sources.
Revised: Identifying the infection sources in a network, including the individuals who started a rumor in a social network, the computers that introduce a virus into a computer network, or the individuals who started a rumor in a social network , plays a critical role in limiting the damage caused by the infection through timely quarantine of the sources.
Edit intent: clarity
Original:  We consider the problem of estimating the infection sources and the infection regions (subsets of nodes infected by each source) in a network, based only on knowledge of the underlying network connections, and when the number of sources is unknown a priori.
Revised:  We consider the problem of estimating the infection sources and the infection regions (subsets of nodes infected by each source) in a network, based only on knowledge of which nodes are infected and their connections, and when the number of sources is unknown a priori.
Edit intent: clarity
Original:  We derive estimators for the infection sources and their infection regions based on approximations of the infection sequences counts .
Revised:  We derive estimators for the infection sources and their infection regions based on approximations of the infection sequences count .
Edit intent: fluency
Original:  Simulations are conducted on various kinds of networks, including tree networks, small-world networks and real world power grid networks,  to verify the performance of our algorithms.
Revised:  Simulations on various kinds of networks, including tree networks, small-world networks and real world power grid networks, to verify the performance of our algorithms.
Edit intent: clarity
Original: We utilize a coarse-grained  directional dynamic bonding DNA model [ C. Svaneborg, Comp.
Revised: We utilize a coarse-grained DNA model within the directional dynamic bonding DNA model [ C. Svaneborg, Comp.
Edit intent: clarity
Original: We utilize a coarse-grained  directional dynamic bonding DNA model [ C. Svaneborg, Comp.
Revised: We utilize a coarse-grained directional dynamic bonding framework [ C. Svaneborg, Comp.
Edit intent: clarity
Original:  (In Press DOI:10.1016/j.cpc.2012.03.005) ] to study DNA self-assembly and DNA computation .
Revised:  (In Press DOI:10.1016/j.cpc.2012.03.005) ] .
Edit intent: coherence
Original:  In our DNA model, a single nucleotide  is represented by a single interaction site , and complementary sites can hybridize reversibly .
Revised:  In our model, a single nucleotide is represented by a single interaction site , and complementary sites can hybridize reversibly .
Edit intent: clarity
Original:  Along with the dynamic hybridization bonds, angular and dihedral bonds are dynamically introduced and removed to model the collective properties of double helix structure on the DNA zippering dynamics.
Revised:  Along with the dynamic hybridization bonds, angular and dihedral bonds , that model the collective properties of double helix structure on the DNA zippering dynamics.
Edit intent: coherence
Original:  Along with the dynamic hybridization bonds, angular and dihedral bonds are dynamically introduced and removed to model the collective properties of double helix structure on the DNA zippering dynamics.
Revised:  Along with the dynamic hybridization bonds, angular and dihedral bonds are dynamically introduced and removed to model the collective effects of chemical structure on the DNA zippering dynamics.
Edit intent: clarity
Original:  Along with the dynamic hybridization bonds, angular and dihedral bonds are dynamically introduced and removed to model the collective properties of double helix structure on the DNA zippering dynamics.
Revised:  Along with the dynamic hybridization bonds, angular and dihedral bonds are dynamically introduced and removed to model the collective properties of double helix structure on the hybridization dynamics.
Edit intent: clarity
Original:  We use this DNA model to simulate the temperature dependent self-assembly  of DNA tetrahedra at several temperatures, a DNA icosahedron, and also strand displacement operations used in DNA computation.
Revised:  We use the DNA model to simulate the temperature dependent self-assembly of DNA tetrahedra at several temperatures, a DNA icosahedron, and also strand displacement operations used in DNA computation.
Edit intent: fluency
Original:  We use this DNA model to simulate the temperature dependent self-assembly  of DNA tetrahedra at several temperatures, a DNA icosahedron, and also strand displacement operations used in DNA computation.
Revised:  We use this DNA model to perform simulations of the self-assembly of DNA tetrahedra at several temperatures, a DNA icosahedron, and also strand displacement operations used in DNA computation.
Edit intent: clarity
Original:  We use this DNA model to simulate the temperature dependent self-assembly  of DNA tetrahedra at several temperatures, a DNA icosahedron, and also strand displacement operations used in DNA computation.
Revised:  We use this DNA model to simulate the temperature dependent self-assembly of DNA tetrahedra , an icosahedron, as well as strand displacement operations used in DNA computation.
Edit intent: clarity
Original: The problem of monotonicity testing of the boolean hypercube is a classic  well-studied, yet unsolved question in property testing.
Revised: The problem of monotonicity testing of the boolean hypercube is a classic , well-studied, yet unsolved question in property testing.
Edit intent: fluency
Original:  We are given query access to f: \{0,1\}^n \mapsto R \R (for some ordered range R \R ).
Revised:  We are given query access to f: \{0,1\}^n \mapsto R \R (for some ordered range \R ).
Edit intent: fluency
Original:  The boolean hypercube%DIFDELCMD < \cB%%% ^n has a natural partial order  , denoted by \prec (defined by the product of coordinate-wise ordering) .
Revised:  The boolean hypercube%DIFDELCMD < \cB%%% ^n has a natural partial order given by coordinate-wise ordering , denoted by \prec (defined by the product of coordinate-wise ordering) .
Edit intent: clarity
Original:  The boolean hypercube%DIFDELCMD < \cB%%% ^n has a natural partial order  , denoted by \prec (defined by the product of coordinate-wise ordering) .
Revised:  The boolean hypercube%DIFDELCMD < \cB%%% ^n has a natural partial order , denoted by \prec .
Edit intent: coherence
Original:  A function is monotone if  all pairs x \prec y in%DIFDELCMD < \cB%%% ^n , f(x) \leq f(y).
Revised:  A function is monotone if for all pairs x \prec y in%DIFDELCMD < \cB%%% ^n , f(x) \leq f(y).
Edit intent: fluency
Original:  A function is monotone if  all pairs x \prec y in%DIFDELCMD < \cB%%% ^n , f(x) \leq f(y).
Revised:  A function is monotone if all pairs x \prec y %DIFDELCMD < \cB%%% ^n , f(x) \leq f(y).
Edit intent: fluency
Original:  \emph{  It is known that the edge tester using O( \eps n\log| R \R | /%DIFDELCMD < \eps%%% ) samples can distinguish a monotone function from one where \eps_f > \eps.
Revised:  \emph{edge tester It is known that the edge tester using O( \eps n\log| R \R | /%DIFDELCMD < \eps%%% ) samples can distinguish a monotone function from one where \eps_f > \eps.
Edit intent: fluency
Original:  \emph{  It is known that the edge tester using O( \eps n\log| R \R | /%DIFDELCMD < \eps%%% ) samples can distinguish a monotone function from one where \eps_f > \eps.
Revised:  \emph{ It is known that the edge tester using O( \eps n\log| \R | /%DIFDELCMD < \eps%%% ) samples can distinguish a monotone function from one where \eps_f > \eps.
Edit intent: clarity
Original:  \emph{  It is known that the edge tester using O( \eps n\log| R \R | /%DIFDELCMD < \eps%%% ) samples can distinguish a monotone function from one where \eps_f > \eps.
Revised:  \emph{ It is known that the edge tester using O( \eps n\log| R \R | %DIFDELCMD < \eps%%% ) samples can distinguish a monotone function from one where \eps_f > \eps.
Edit intent: fluency
Original:  On the other hand, the best lower bound for monotonicity testing  is \min(| R \R |^2,n).
Revised:  On the other hand, the best lower bound for monotonicity testing is \min(| \R |^2,n).
Edit intent: fluency
Original:  This leaves a quadratic gap in our knowledge, since | R \R | can be 2^n.
Revised:  This leaves a quadratic gap in our knowledge, since | \R | can be 2^n.
Edit intent: coherence
Original:  We prove a very general theorem showing that edge testers work for a class of "bounded-derivative" properties, which contains both monotonicity and Lipschitz.
Revised:  We prove a very general theorem showing that edge testers work for a class of "bounded-derivative" properties, a class containing both monotonicity and Lipschitz.
Edit intent: coherence
Original:  We show an Omega (k) queries lower bound for this problem.
Revised:  We show an \Omega (k) queries lower bound for this problem.
Edit intent: fluency
Original: Let DS_s(n ) be the extremal function of order-s Davenport-Schinzel sequences over an n-letter alphabet .
Revised: Let DS_s(n ) be the extremal function of order-s Davenport-Schinzel sequence, namely a sequence over an n-letter alphabet .
Edit intent: clarity
Original:  Together with existing bounds due to Hart and Sharir, Agarwal, Sharir, and Shor, and Nivasch, we give the following essentially tight bounds on DS_s(n) for all s : DS_s(n) = n, for s=1, 2n-1, for s=2, Theta(n alpha(n)), for s=3, Theta(n 2^{alpha(n)), for s =4, Omega(nalpha(n) 2^{alpha(n)}) and O(nalpha^2(n) 2^{alpha(n)}), for s =5, n 2^{(1 \pm o(1)) alpha^t(n)/t!}, for s}%DIFDELCMD < \geq6 %%% and t = floor (s-2 ) /2 These bounds refute\le  conjectures due to Alon et al. , Nivasch, and Pettie .
Revised:  Together with existing bounds due to Hart and Sharir, Agarwal, Sharir, and Shor, ), for s =4, Omega(nalpha(n) 2^{alpha(n)}) and O(nalpha^2(n) 2^{alpha(n)}), for s =5, n 2^{(1 \pm o(1)) alpha^t(n)/t!}, for s}%DIFDELCMD < \geq6 %%% and t = floor (s-2 ) /2 These bounds refute\le conjectures due to Alon et al. , Nivasch, and Pettie .
Edit intent: coherence