wanyu/IteraTeR_v2 huggingface dataset:
Original:  Here we formally show that for stratified multiple hypothesis testing problems, in which statistical tests can be subdivided naturally, controlling the local False Discovery Rate (lFDR) per stratum  yields the most predictions across the data at any given combined FDR or E-value threshold .
Revised:  Here we formally show that for "stratified" multiple hypothesis testing problems, in which statistical tests can be subdivided naturally, controlling the local False Discovery Rate (lFDR) per stratum yields the most predictions across the data at any given combined FDR or E-value threshold .
Edit intent: fluency
Original:  Here we formally show that for stratified multiple hypothesis testing problems, in which statistical tests can be subdivided naturally, controlling the local False Discovery Rate (lFDR) per stratum  yields the most predictions across the data at any given combined FDR or E-value threshold .
Revised:  Here we formally show that for stratified multiple hypothesis testing problems, controlling the local False Discovery Rate (lFDR) per stratum yields the most predictions across the data at any given combined FDR or E-value threshold .
Edit intent: clarity
Original:  Here we formally show that for stratified multiple hypothesis testing problems, in which statistical tests can be subdivided naturally, controlling the local False Discovery Rate (lFDR) per stratum  yields the most predictions across the data at any given combined FDR or E-value threshold .
Revised:  Here we formally show that for stratified multiple hypothesis testing problems, in which statistical tests can be subdivided naturally, controlling the local False Discovery Rate (lFDR) per stratum yields the most predictions across the data at any given threshold on the FDR or E-value threshold .
Edit intent: clarity
Original:  Here we formally show that for stratified multiple hypothesis testing problems, in which statistical tests can be subdivided naturally, controlling the local False Discovery Rate (lFDR) per stratum  yields the most predictions across the data at any given combined FDR or E-value threshold .
Revised:  Here we formally show that for stratified multiple hypothesis testing problems, in which statistical tests can be subdivided naturally, controlling the local False Discovery Rate (lFDR) per stratum yields the most predictions across the data at any given combined FDR or E-value over all strata combined .
Edit intent: clarity
Original:  however, our tests reveal a small but coherent subset of domain families  biased towards models for specific repetitive patterns, for which FDRs are greatly underestimated due to weaknesses in random sequence models.
Revised:  however, our tests reveal a small but coherent subset of domain families , biased towards models for specific repetitive patterns, for which FDRs are greatly underestimated due to weaknesses in random sequence models.
Edit intent: fluency
Original: Centrality measures, erstwhile popular amongst the sociologists and psychologists, has seen wide and increasing applications across several disciplines of late.
Revised: Centrality measures, erstwhile popular amongst the sociologists and psychologists, have seen wide and increasing applications across several disciplines of late.
Edit intent: fluency
Original: Centrality measures, erstwhile popular amongst the sociologists and psychologists, have seen wide and increasing applications across several disciplines of late.
Revised: Centrality measures, erstwhile popular amongst the sociologists and psychologists, have seen broad and increasing applications across several disciplines of late.
Edit intent: clarity
Original:  In the current paper, we formulate a method to determine the betweenness ordering of k vertices without exactly computing their betweenness indices - which is a daunting task for networks of large size.
Revised:  In the current paper, we propose an efficient heuristic to determine the betweenness ordering of k vertices without exactly computing their betweenness indices - which is a daunting task for networks of large size.
Edit intent: clarity
Original:  In the current paper, we formulate a method to determine the betweenness ordering of k vertices without exactly computing their betweenness indices - which is a daunting task for networks of large size.
Revised:  In the current paper, we formulate a method to determine the betweenness-ordering of k vertices without exactly computing their betweenness indices - which is a daunting task for networks of large size.
Edit intent: fluency
Original:  The method results very efficient ordering even when runs for  linear time in the  number of edges.
Revised:  The method results very efficient ordering even when runs for a linear time in the number of edges.
Edit intent: fluency
Original:  The method results very efficient ordering even when runs for  linear time in the  number of edges.
Revised:  The method results very efficient ordering even when runs for linear time in the terms of the number of edges.
Edit intent: clarity
Original:  We compare our method with the available techniques in the literature and show that our method fares several times better than the currently known techniques.
Revised:  We compare our method with the available techniques in the literature and show that our method produces more efficient ordering than the currently known techniques.
Edit intent: clarity
Original: We find that there is a close relationship between the associated bigraph and the clustering. the imbedding of the bigraph into some space  can identify the clusters .
Revised: We find there is relationship between the associated bigraph and the clustering. the imbedding of the bigraph into some space can identify the clusters .
Edit intent: clarity
Original: We find that there is a close relationship between the associated bigraph and the clustering. the imbedding of the bigraph into some space  can identify the clusters .
Revised: We find that there is a close relationship between the associated bigraph and the clustering. the imbedding of the bigraph into some space , we can identify the clusters .
Edit intent: fluency
Original:  Thus, we propose a new method for network cluster detecting through associated bigraph , of which the physical meaning is clear and the time complexity is acceptable .
Revised:  Thus, we propose a new method for network cluster detecting . And this method , of which the physical meaning is clear and the time complexity is acceptable .
Edit intent: clarity
Original:  The Zachary Network, which presents the structure of a karate club, can be partation into two clusters correctly by this method .
Revised:  The Zachary Network, which presents the structure of a karate club, can be partitioned correctly by these methods .
Edit intent: clarity
Original: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Revised: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% %DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Edit intent: fluency
Original: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Revised: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% \rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Edit intent: coherence
Original: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Revised: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping %DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Edit intent: fluency
Original: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Revised: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% %DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Edit intent: fluency
Original: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Revised: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% %DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Edit intent: fluency
Original: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% \mapsto%DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Revised: =\inf_{\Rho\tau\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% and%DIFDELCMD < \underline %DIFDELCMD < %%% C:=\sup_{\Tau\rho\in\T}%DIFDELCMD < \E[U(\Rho(\tau),\tau)] %%% in continuous time , where U(s,t) is F_{s\vee t-measurable (this is the new feature of our stopping game ), }%DIFDELCMD < \T %%% is the set of stopping times, and%DIFDELCMD < \Rho%%% ,%DIFDELCMD < \Tau%%% :%DIFDELCMD < \T%%% %DIFDELCMD < \T %DIFDELCMD < %%% satisfy certain non-anticipativity conditions.
Edit intent: coherence
Original:  We show that%DIFDELCMD < \bar %%% C=%DIFDELCMD < \underline %DIFDELCMD < %%% C, by converting these problems into a corresponding Dynkin game  .
Revised:  We show that%DIFDELCMD < \bar %%% %DIFDELCMD < \underline %DIFDELCMD < %%% C, by converting these problems into a corresponding Dynkin game .
Edit intent: coherence
Original: This paper presents a queueing-network approach to the analysis and control of mobility-on-demand (MoD) systems for urban personal transportation.
Revised: This paper presents a queueing network approach to the analysis and control of mobility-on-demand (MoD) systems for urban personal transportation.
Edit intent: fluency
Original:  A MoD system consists of a fleet of vehicles providing one-way carsharing service and a team of drivers to rebalance such vehicles.
Revised:  A MoD system consists of a fleet of vehicles providing one-way car sharing service and a team of drivers to rebalance such vehicles.
Edit intent: fluency
Original: %DIFDELCMD < {\bf81}%%% , 5672 (1998) is a restricted model of quantum computing where the input state is the completely-mixed state except for a single pure qubit, and  a single output qubit is measured at the end of the computing.
Revised: %DIFDELCMD < {\bf81}%%% is a restricted model of quantum computing where the input state is the completely-mixed state except for a single pure qubit, and a single output qubit is measured at the end of the computing.
Edit intent: coherence
Original: %DIFDELCMD < {\bf81}%%% , 5672 (1998) is a restricted model of quantum computing where the input state is the completely-mixed state except for a single pure qubit, and  a single output qubit is measured at the end of the computing.
Revised: %DIFDELCMD < {\bf81}%%% , 5672 (1998) is a restricted model of quantum computing where the input state is the completely mixed state except for a single pure qubit, and a single output qubit is measured at the end of the computing.
Edit intent: fluency
Original: %DIFDELCMD < {\bf81}%%% , 5672 (1998) is a restricted model of quantum computing where the input state is the completely-mixed state except for a single pure qubit, and  a single output qubit is measured at the end of the computing.
Revised: %DIFDELCMD < {\bf81}%%% , 5672 (1998) is a restricted model of quantum computing where the input state is the completely-mixed state except for a single clean qubit, and a single output qubit is measured at the end of the computing.
Edit intent: clarity
Original: %DIFDELCMD < {\bf81}%%% , 5672 (1998) is a restricted model of quantum computing where the input state is the completely-mixed state except for a single pure qubit, and  a single output qubit is measured at the end of the computing.
Revised: %DIFDELCMD < {\bf81}%%% , 5672 (1998) is a restricted model of quantum computing where the input state is the completely-mixed state except for a single pure qubit, and only a single output qubit is measured at the end of the computing.
Edit intent: clarity
Original: %DIFDELCMD < {\bf112}%%% , 130502 (2014) that if the output probability distribution of the DQC1 _m model for m%DIFDELCMD < \ge3 %%% can be classically efficiently sampled, then the polynomial hierarchy collapses at the third level .
Revised: %DIFDELCMD < {\bf112}%%% that if the output probability distribution of the DQC1 _m model for m%DIFDELCMD < \ge3 %%% can be classically efficiently sampled, then the polynomial hierarchy collapses at the third level .
Edit intent: coherence
Original: %DIFDELCMD < {\bf112}%%% , 130502 (2014) that if the output probability distribution of the DQC1 _m model for m%DIFDELCMD < \ge3 %%% can be classically efficiently sampled, then the polynomial hierarchy collapses at the third level .
Revised: %DIFDELCMD < {\bf112}%%% , 130502 (2014) that if the output probability distribution of the DQC1 %DIFDELCMD < \ge3 %%% can be classically efficiently sampled, then the polynomial hierarchy collapses at the third level .
Edit intent: clarity
Original:  Two additional measures are proposed to smooth estimates of particle trajectories.
Revised:  Two additional measures are implemented to smooth estimates of particle trajectories.
Edit intent: clarity
Original: Direct detector device (DDD) cameras have revolutionized single particle electron cryomicroscopy (cryo-EM) of protein complexes .
Revised: Direct detector device (DDD) cameras have revolutionized single particle electron cryomicroscopy (cryo-EM) .
Edit intent: clarity
Original:  Two additional measures are implemented to smooth estimates of particle trajectories .
Revised:  To smooth estimates of particle trajectories .
Edit intent: clarity
Original: In several countries , poker games are, probably, the most famous cards games.
Revised: In several countries poker games are, probably, the most famous cards games.
Edit intent: fluency
Original: In several countries , poker games are, probably, the most famous cards games.
Revised: In several countries , poker games are, probably, the most famous card games.
Edit intent: fluency
Original:  Although all variants of poker have their own rules, all of them are characterized by the utilization of money to make sense the challenge.
Revised:  Although each variant of poker has its own rules, all of them are characterized by the utilization of money to make sense the challenge.
Edit intent: clarity
Original: In several countries poker games are, probably, the most famous card games.
Revised: In many countries poker is one of the most popular card games.
Edit intent: clarity
Original:  Although each variant of poker has its own rules, all of them are characterized by the utilization of money to make sense the challenge .
Revised:  Although each variant of poker has its own rules, all involve the use of money to make sense the challenge .
Edit intent: clarity
Original:  Although each variant of poker has its own rules, all of them are characterized by the utilization of money to make sense the challenge .
Revised:  Although each variant of poker has its own rules, all of them are characterized by the utilization of money to make the challenge meaningful .
Edit intent: clarity
Original:  Under this perspective, a poker table can be considered as a psychology lab, where several human behaviors can be observed .
Revised:  Under this perspective, a poker table can be viewed as a psychology lab, where several human behaviors can be observed .
Edit intent: clarity
Original:  Under this perspective, a poker table can be considered as a psychology lab, where several human behaviors can be observed .
Revised:  Under this perspective, a poker table can be considered as a psychology lab, where human behavior can be observed .
Edit intent: clarity
Original:  In this work , we develop a preliminary analysis about the role of rationality in poker games, using the variant Texas Hold'em as reference .
Revised:  In this work , we develop a preliminary analysis of the role of rationality in poker games, using the variant Texas Hold'em as reference .
Edit intent: fluency
Original:  In this work , we develop a preliminary analysis about the role of rationality in poker games, using the variant Texas Hold'em as reference .
Revised:  In this work , we develop a preliminary analysis about the role of rationality in poker games, using a stylized version of Texas Hold'em as reference .
Edit intent: clarity
Original:  In this work , we develop a preliminary analysis about the role of rationality in poker games, using the variant Texas Hold'em as reference .
Revised:  In this work , we develop a preliminary analysis about the role of rationality in poker games, using the variant Texas Hold'em .
Edit intent: clarity
Original:  In particular, we compare the performances of two different kinds of players, i.e., rational players vs irrational players, during a poker tournament.
Revised:  In particular, we compare the performance of two different kinds of players, i.e., rational players vs irrational players, during a poker tournament.
Edit intent: fluency
Original:  In particular, we compare the performances of two different kinds of players, i.e., rational players vs irrational players, during a poker tournament.
Revised:  In particular, we compare the performances of two different kinds of players, i.e., rational vs irrational players, during a poker tournament.
Edit intent: fluency
Original: It is shown that a general scale-invariant, two-component feedback loop can be viewed as a deformed version of a Hamiltonian system.
Revised: It is shown that a general two-component feedback loop can be viewed as a deformed version of a Hamiltonian system.
Edit intent: clarity
Original: It is shown that a general scale-invariant, two-component feedback loop can be viewed as a deformed version of a Hamiltonian system.
Revised: It is shown that a general scale-invariant, two-component feedback loop can be viewed as a deformed Hamiltonian system.
Edit intent: clarity
Original: Empirical data on contacts between individuals in social contexts play an important role in the information of models describing human behavior and how epidemics spread in populations.
Revised: Empirical data on contacts between individuals in social contexts play an important role in providing information for models describing human behavior and how epidemics spread in populations.
Edit intent: clarity
Original:  We then consider the contact network as a potential substrate for infectious disease spread and show that its sparsity tends to prevent outbreaks of fast-spreading epidemics.
Revised:  We consider the contact network as a potential substrate for infectious disease spread and show that its sparsity tends to prevent outbreaks of fast-spreading epidemics.
Edit intent: coherence
Original:  We then consider the contact network as a potential substrate for infectious disease spread and show that its sparsity tends to prevent outbreaks of fast-spreading epidemics.
Revised:  We then consider the contact network as a potential substrate for infectious disease spread and show that its sparsity tends to prevent outbreaks of rapidly spreading epidemics.
Edit intent: fluency
Original:  Linkers (f\sim 50 \%) act as bridges in the \\%DIF > ) act as bridges in the network and have large betweenness centralities.
Revised:  Linkers (f\sim 50 \\%DIF > ) act as bridges in the network and have large betweenness centralities.
Edit intent: fluency
Original:  As such a behavior may be spotted a priori in the offices' organization or from surveys, without the full knowledge of the time-resolved contact network, this result might help the design of efficient, low-cost vaccination or social-distancing strategies.
Revised:  As such a behavior may be spotted a priori in the offices' organization or from surveys, without the full knowledge of the time-resolved contact network, this result might help the design of efficient, low-cost vaccination or social-distancing strategies.
Edit intent: fluency
Original:  As such a behavior may be spotted a priori in the offices' organization or from surveys, without the full knowledge of the time-resolved contact network, this result might help the design of efficient, low-cost vaccination or social-distancing strategies.
Revised:  As such a behavior may be spotted a priori in the offices' organization or from surveys, without the full knowledge of the time-resolved contact network, this result may help the design of efficient, low-cost vaccination or social-distancing strategies.
Edit intent: fluency