wanyu/IteraTeR_full_sent huggingface dataset:
Original: We investigate how and to what extent the Japanese government intervened in the rice futures market in Osaka during the interwar period, from the late 1910s to 1939, using a time-varying AR model .
Revised: We investigate the relationship between market efficiency of rice futures transaction in Osaka and the Japanese government intervened in the rice futures market in Osaka during the interwar period, from the late 1910s to 1939, using a time-varying AR model .
Edit intent: meaning-changed
Original: We investigate how and to what extent the Japanese government intervened in the rice futures market in Osaka during the interwar period, from the late 1910s to 1939, using a time-varying AR model .
Revised: We investigate how and to what extent the Japanese government intervention in rice distributions by directly buying and selling rice during the interwar period, from the late 1910s to 1939, using a time-varying AR model .
Edit intent: meaning-changed
Original: We investigate how and to what extent the Japanese government intervened in the rice futures market in Osaka during the interwar period, from the late 1910s to 1939, using a time-varying AR model .
Revised: We investigate how and to what extent the Japanese government intervened in the rice futures market in Osaka during the interwar period, from the middle 1910s to 1939, using a time-varying AR model .
Edit intent: meaning-changed
Original: We investigate how and to what extent the Japanese government intervened in the rice futures market in Osaka during the interwar period, from the late 1910s to 1939, using a time-varying AR model .
Revised: We investigate how and to what extent the Japanese government intervened in the rice futures market in Osaka during the interwar period, from the late 1910s to 1939, considering the context of "discretion versus rules." We use a time-varying AR model .
Edit intent: meaning-changed
Original: We investigate how and to what extent the Japanese government intervened in the rice futures market in Osaka during the interwar period, from the late 1910s to 1939, using a time-varying AR model .
Revised: We investigate how and to what extent the Japanese government intervened in the rice futures market in Osaka during the interwar period, from the late 1910s to 1939, using a time-varying VAR model to compare market efficiency and the government's actions over time .
Edit intent: meaning-changed
Original: Research of homogeneous ( i.e., single node and edge type) biological networks (BNs) has received significant attention. Graphlets have been proven in homogeneousBN research.Given their popularity, graphlets were extended to their directed or dynamic counterparts, owing to increase in availability of directed or temporal BNs. Given the increasing amounts of available BN data of different types, we generalize current homogeneous graphlets to their heterogeneous counterparts, which encompass different node or edge types and thus allow for analyzing a heterogeneous "network of networks".
Revised: Research of homogeneous ( i.e., conserved) network regions. Existing NA methods are homogeneous, i.e., they can deal only with networks containing nodes and edges of one type. However, due to increasing amounts of available BN data of different types, we generalize current homogeneous graphlets to their heterogeneous counterparts, which encompass different node or edge types and thus allow for analyzing a heterogeneous "network of networks".
Edit intent: clarity
Original:  Given the increasing amounts of available BN data of different types, we generalize current homogeneous graphlets to their heterogeneous counterparts, which encompass different node or edge types and thus allow for analyzing a heterogeneous "network of networks".
Revised:  Given the increasing amounts of heterogeneous real-world network data with nodes and edges of different types, we generalize current homogeneous graphlets to their heterogeneous counterparts, which encompass different node or edge types and thus allow for analyzing a heterogeneous "network of networks".
Edit intent: clarity
Original:  Given the increasing amounts of available BN data of different types, we generalize current homogeneous graphlets to their heterogeneous counterparts, which encompass different node or edge types and thus allow for analyzing a heterogeneous "network of networks". Heterogeneous graphlets will have at least as high impact as homogeneous graphlets have had. We illustrate the usefulness of heterogeneous graphlets in the context of network alignment (NA). While existing NA methods are homogeneous (they can only account for a single node type and a single edge type) , we generalize  a state-of-the-art homogeneous graphlet-based NAmethod into its heterogeneous counterpart.
Revised:  Given the increasing amounts of available BN data of different types, we extend three recent state-of-the-art homogeneous NA methods, WAVE, MAGNA++, and SANA, to allow for heterogeneous NA for the first time. We introduce several algorithmic novelties to achieve this. Namely, these existing NA methods are homogeneous (they can only account for a single node type and a single edge type) , we generalize a state-of-the-art homogeneous graphlet-based NAmethod into its heterogeneous counterpart.
Edit intent: meaning-changed
Original:  While existing NA methods are homogeneous (they can only account for a single node type and a single edge type) , we generalize  a state-of-the-art homogeneous graphlet-based NAmethod into its heterogeneous counterpart.
Revised:  While existing NA methods compute homogeneous graphlet-based node similarities and then find high-scoring alignments with respect to these similarities, while simultaneously maximizing the number of conserved edges. Instead, we generalize homogeneous graphlets to their heterogeneous counterparts, which we then use to develop a new measure of heterogeneous node similarity. Also , we generalize a state-of-the-art homogeneous graphlet-based NAmethod into its heterogeneous counterpart.
Edit intent: meaning-changed
Original:  While existing NA methods are homogeneous (they can only account for a single node type and a single edge type) , we generalize  a state-of-the-art homogeneous graphlet-based NAmethod into its heterogeneous counterpart.
Revised:  While existing NA methods are homogeneous (they can only account for a single node type and a single edge type) , we generalize S^3, a state-of-the-art homogeneous graphlet-based NAmethod into its heterogeneous counterpart.
Edit intent: meaning-changed
Original:  While existing NA methods are homogeneous (they can only account for a single node type and a single edge type) , we generalize  a state-of-the-art homogeneous graphlet-based NAmethod into its heterogeneous counterpart.
Revised:  While existing NA methods are homogeneous (they can only account for a single node type and a single edge type) , we generalize a state-of-the-art measure of edge conservation for homogeneous NA, to its heterogeneous counterpart.
Edit intent: meaning-changed
Original:  Because graphlets are applicable to many other network science problems, we provide an implementation of our heterogeneous graphlet counting approach (available upon request) .
Revised:  Then, we find high-scoring alignments with respect to our heterogeneous node similarity and edge conservation measures. In evaluations on synthetic networks and real-world biological network data, our proposed heterogeneous NA methods lead to higher-quality alignments and better robustness to noise in the data than their homogeneous counterparts .
Edit intent: meaning-changed
Original:  Some popular scheduling policies for such a system (and of interest in this paper) are the discriminatory processor sharing (DPS), discriminatory random order service (DROS), generalized processor sharing (GPS) and weighted fair queueing (WFQ).
Revised:  Some popular scheduling policies for such system are the discriminatory processor sharing (DPS), discriminatory random order service (DROS), generalized processor sharing (GPS) and weighted fair queueing (WFQ).
Edit intent: clarity
Original:  The aim of this paperis to show a certain equivalence between these scheduling policiesfor the special case when the multiclass population have identical and exponential service requirements.
Revised:  In this paper, we propose two classes of policies, namely MPS (multiclass processor sharing) and MROS (multiclass random order service), that generalize the four policies mentioned above. For the special case when the multiclass population have identical and exponential service requirements.
Edit intent: meaning-changed
Original:  The aim of this paperis to show a certain equivalence between these scheduling policiesfor the special case when the multiclass population have identical and exponential service requirements. In fact , we show  the equivalence between two broader classes of policies that generalize the above mentioned four policies.
Revised:  The aim of this paperis to show a certain equivalence between these scheduling policiesfor the special case when the multiclass population have identical and exponential service requirement with parameter \mu , we show the equivalence between two broader classes of policies that generalize the above mentioned four policies.
Edit intent: meaning-changed
Original:  In fact , we show  the equivalence between two broader classes of policies that generalize the above mentioned four policies. We specifically show that the sojourn time distribution for a customer of a particular class in a system with the  DPS (GPS) scheduling policy is a constant multiple of the  waiting time distribution of a customer of the same class in a system with the DROS (respectively WFQ) policy.
Revised:  In fact , we show the sojourn time distribution for a customer of a particular class in a system with the DPS (GPS) scheduling policy is a constant multiple of the waiting time distribution of a customer of the same class in a system with the DROS (respectively WFQ) policy.
Edit intent: coherence
Original:  We specifically show that the sojourn time distribution for a customer of a particular class in a system with the  DPS (GPS) scheduling policy is a constant multiple of the  waiting time distribution of a customer of the same class in a system with the DROS (respectively WFQ) policy.
Revised:  We specifically show that the sojourn time distribution for a class i customer in a system with the MPS policy is a constant multiple of the tail of the waiting time distribution of a class i customer in a system with the DPS (GPS) scheduling policy is a constant multiple of the waiting time distribution of a customer of the same class in a system with the DROS (respectively WFQ) policy.
Edit intent: meaning-changed
Original:  We specifically show that the sojourn time distribution for a customer of a particular class in a system with the  DPS (GPS) scheduling policy is a constant multiple of the  waiting time distribution of a customer of the same class in a system with the DROS (respectively WFQ) policy.
Revised:  We specifically show that the sojourn time distribution for a customer of a particular class in a system with the MROS policy. This result implies that for a class i customer, the tail of the sojourn time distribution in a system with the DPS (GPS) scheduling policy is a constant multiple of the waiting time distribution of a customer of the same class in a system with the DROS (respectively WFQ) policy.
Edit intent: meaning-changed
Original:  We specifically show that the sojourn time distribution for a customer of a particular class in a system with the  DPS (GPS) scheduling policy is a constant multiple of the  waiting time distribution of a customer of the same class in a system with the DROS (respectively WFQ) policy.
Revised:  We specifically show that the sojourn time distribution for a customer of a particular class in a system with the DPS (GPS) scheduling policy is a constant multiple of the tail of the waiting time distribution of a customer of the same class in a system with the DROS (respectively WFQ) policy.
Edit intent: meaning-changed
Original:  We specifically show that the sojourn time distribution for a customer of a particular class in a system with the  DPS (GPS) scheduling policy is a constant multiple of the  waiting time distribution of a customer of the same class in a system with the DROS (respectively WFQ) policy.
Revised:  We specifically show that the sojourn time distribution for a customer of a particular class in a system with the DPS (GPS) scheduling policy is a constant multiple of the waiting time distribution in a system with the DROS (respectively WFQ) policy.
Edit intent: clarity
Original:  The foundation for this joint regression is a recent result by Fissler and Ziegel (2016), who show that the quantile and the ESare jointly elicitable. This joint elicitability allows for M- and Z-estimation of the joint regression parameters.
Revised:  This regression is based on a strictly consistent loss function for the pair quantile and ES, which allows for M- and Z-estimation of the joint regression parameters.
Edit intent: meaning-changed
Original:   This joint regression framework allows for various applications including estimating, forecasting and backtesting Expected Shortfall , which is particularly relevant in light of the upcoming introduction of Expected Shortfall in the Basel Accords.
Revised:  We find that the Z-estimator is numerically unstable and thus, we rely on M-estimation of the model parameters. This joint regression framework allows for various applications including estimating, forecasting and backtesting Expected Shortfall , which is particularly relevant in light of the upcoming introduction of Expected Shortfall in the Basel Accords.
Edit intent: meaning-changed
Original:   This joint regression framework allows for various applications including estimating, forecasting  and backtesting ES, which is particularly relevant in light of the recent introduction of ES in the Basel Accords.
Revised:  Extensive simulations verify the asymptotic properties and analyze the small sample behavior of the M-estimator for different specification functions. This joint regression framework allows for various applications including estimating, forecasting and backtesting ES, which is particularly relevant in light of the recent introduction of ES in the Basel Accords.
Edit intent: meaning-changed
Original:  Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and  Approval Chamberlin--Courant  .
Revised:  Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and the Approval Chamberlin--Courant .
Edit intent: fluency
Original:  Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and  Approval Chamberlin--Courant  .
Revised:  Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and Approval Chamberlin--Courant rule .
Edit intent: clarity
Original:  Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and the Approval Chamberlin--Courant rule.
Revised:  Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and the Approval Chamberlin-Courant rule.
Edit intent: fluency
Original:  We introduce the class of counting rules , provide an axiomatic characterization of this class and, in particular, show that counting rules are consistent . Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and the Approval Chamberlin-Courant rule.
Revised:  We introduce the class of counting rules and provide an axiomatic characterization of this class and, in particular, show that counting rules are consistent . Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and the Approval Chamberlin-Courant rule.
Edit intent: fluency
Original:  We introduce the class of counting rules , provide an axiomatic characterization of this class and, in particular, show that counting rules are consistent . Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and the Approval Chamberlin-Courant rule.
Revised:  We introduce the class of counting rules , provide an axiomatic characterization of this class based on the consistency axiom . Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and the Approval Chamberlin-Courant rule.
Edit intent: clarity
Original:  We introduce the class of counting rules , provide an axiomatic characterization of this class and, in particular, show that counting rules are consistent . Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and the Approval Chamberlin-Courant rule.
Revised:  We introduce the class of counting rules , provide an axiomatic characterization of this class and, in particular, show that counting rules are consistent . Building upon this result, we axiomatically characterize three important consistent multi-winner rules: Proportional Approval Voting, Multi-Winner Approval Voting and the Approval Chamberlin--Courant rule.
Edit intent: fluency
Original: Cells receive signaling molecules by receptors and relay the information via sensory networks so that they can respond properly depending on the type of signals . Recent studies show that cells can extract multi-dimensional information from dynamical concentration patterns of signaling molecules.
Revised: Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signals . Recent studies show that cells can extract multi-dimensional information from dynamical concentration patterns of signaling molecules.
Edit intent: clarity
Original: Cells receive signaling molecules by receptors and relay the information via sensory networks so that they can respond properly depending on the type of signals . Recent studies show that cells can extract multi-dimensional information from dynamical concentration patterns of signaling molecules.
Revised: Cells receive signaling molecules by receptors and relay the information via sensory networks so that they can respond properly depending on the type of signal . Recent studies show that cells can extract multi-dimensional information from dynamical concentration patterns of signaling molecules.
Edit intent: fluency
Original: Cells receive signaling molecules by receptors and relay the information via sensory networks so that they can respond properly depending on the type of signals . Recent studies show that cells can extract multi-dimensional information from dynamical concentration patterns of signaling molecules.
Revised: Cells receive signaling molecules by receptors and relay the information via sensory networks so that they can respond properly depending on the type of signals . Recent studies have shown that cells can extract multi-dimensional information from dynamical concentration patterns of signaling molecules.
Edit intent: clarity
Original:  Here we study how cells generally and optimally process multi-dimensional information embedded in dynamical patterns through biochemical networks. Considering a deterministic limit, we model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output.
Revised:  Here we study how cells generally and optimally process multi-dimensional information embedded in dynamical patterns . We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output.
Edit intent: clarity
Original:  We find that optimal decoders are realized with multiple distinct non-monotonic response functionsand that such optimal decoderscan extract information much more efficiently than typical single-layer linear decoders. We also consider the decorrelation of informationembedded in the dynamical patternsand show that decorrelating decoders converge to the upper bound of the mutual information in the weak noise limit. We explore the biochemical implementations of these decoders using control theory and demonstrate that they can be implemented biochemically through  modification of cascade-type networks, which are prevalent in actual signaling pathways.
Revised:  We find that , when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that they can be implemented biochemically through modification of cascade-type networks, which are prevalent in actual signaling pathways.
Edit intent: coherence
Original: We present a deterministic algorithm that computes\tilde \tilde  the diameter of a directed planar graph with real arc lengths in O(n^{5/3}) time.
Revised: We present an explicit and efficient construction of additively weighted Voronoi diagrams on planar graphs. Let G be a planar graph with n vertices and b sites that lie on a constant number of faces. We show how to preprocess G in\tilde \tilde the diameter of a directed planar graph with real arc lengths in O(n^{5/3}) time.
Edit intent: meaning-changed
Original: We present a deterministic algorithm that computes\tilde \tilde  the diameter of a directed planar graph with real arc lengths in O(n^{5/3}) time.
Revised: We present a deterministic algorithm that computes\tilde O(nb^2) time so that one can compute any additively weighted Voronoi diagram for these sites in\tilde the diameter of a directed planar graph with real arc lengths in O(n^{5/3}) time.
Edit intent: meaning-changed
Original: We present a deterministic algorithm that computes\tilde \tilde  the diameter of a directed planar graph with real arc lengths in O(n^{5/3}) time.
Revised: We present a deterministic algorithm that computes\tilde \tilde O(b) time. We use this construction to compute the diameter of a directed planar graph with real arc lengths in O(n^{5/3}) time.
Edit intent: meaning-changed
Original:  This improves the recent breakthrough result of Cabello (SODA'17), both by improving the running time (from O(n^{11/6})), and by using a deterministic algorithm.
Revised:  This improves the recent breakthrough result of Cabello (SODA'17), both by improving the running time (from O(n^{11/6})), and by providing a deterministic algorithm.
Edit intent: clarity