wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We use scaling to collapse time dependent structure factors at multiple wavenumbers and find the effective dynamic exponent z_{ eff } \approx 3 near the critical point. This value and the form of the structure factor are in excellent agreement with recent theoretical predictions invoking hydrodynamic coupling to the bulk. Our result may have biological relevance since membranes isolated from cells are near miscibility critical points .
Revised:  We use scaling to collapse time dependent structure factors at multiple wavenumbers and find the effective dynamic exponent z_{ eff } \approx 3 as the correlation length of fluctuations exceeds a hydrodynamic length set by the membrane and bulk viscosities .
Edit intent: clarity
Original:  Mechanical RGMs will be introduced, and their relationship to conceptual biological RGMs explained . Exemplars of these biological RGMs and their evolution (e.g. introduction of mutations and recombination-like inversions) will be demonstrated using block diagrams  .
Revised:  Mechanical RGMs will be introduced, and their relationship to conceptual biological RGMs . Exemplars of these biological RGMs and their evolution (e.g. introduction of mutations and recombination-like inversions) will be demonstrated using block diagrams .
Edit intent: clarity
Original:  Mechanical RGMs will be introduced, and their relationship to conceptual biological RGMs explained . Exemplars of these biological RGMs and their evolution (e.g. introduction of mutations and recombination-like inversions) will be demonstrated using block diagrams  .
Revised:  Mechanical RGMs will be introduced, and their relationship to conceptual biological RGMs explained . Exemplars of these biological RGMs and their evolution (e.g. introduction of mutations and recombination-like inversions) will be demonstrated using block diagrams and interconnections with complex networks (called convolution architectures) .
Edit intent: meaning-changed
Original: Recent work of Dupire (2005) and Carr Lee (2010) has highlighted the importance of understanding the Skorokhod embedding originally proposed by Root (1969) for the model-independent hedging of variance options.
Revised: Recent work of Dupire Lee (2010) has highlighted the importance of understanding the Skorokhod embedding originally proposed by Root (1969) for the model-independent hedging of variance options.
Edit intent: coherence
Original: Recent work of Dupire (2005) and Carr Lee (2010) has highlighted the importance of understanding the Skorokhod embedding originally proposed by Root (1969) for the model-independent hedging of variance options.
Revised: Recent work of Dupire (2005) and Carr and Carr and Lee has highlighted the importance of understanding the Skorokhod embedding originally proposed by Root (1969) for the model-independent hedging of variance options.
Edit intent: meaning-changed
Original: Recent work of Dupire (2005) and Carr Lee (2010) has highlighted the importance of understanding the Skorokhod embedding originally proposed by Root (1969) for the model-independent hedging of variance options.
Revised: Recent work of Dupire (2005) and Carr Lee (2010) has highlighted the importance of understanding the Skorokhod embedding originally proposed by Root for the model-independent hedging of variance options.
Edit intent: coherence
Original:  In this work, we prove a characterisation of Root's barrier in terms of the solution to a variational inequality, and we give an alternative proof of the optimality property which has an important consequence for the construction of subhedging strategies in the financial context.
Revised:  In this work, we prove a characterization of Root's barrier in terms of the solution to a variational inequality, and we give an alternative proof of the optimality property which has an important consequence for the construction of subhedging strategies in the financial context.
Edit intent: fluency
Original: Globalization has created an international financial network of countries linked by trade in goods and assets. These linkages allow for more efficient resource allocation across borders, but also create potentially hazardous financial interdependence, such as the great financial distress caused by the 2010 threat of Greece 's default or the 2008 collapse of Lehman Brothers. Increasingly, the tools of network science are being used as a means of articulating in a quantitative way measures of financial interdependence and stability .
Revised: The recent financial crisis of 2008 and the 2011 indebtedness of Greece highlight the importance of understanding the structure of the global financial network .
Edit intent: clarity
Original:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Revised:  In this paper we set out to analyze and characterize this network, as captured by the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Edit intent: clarity
Original:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Revised:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) , in two ways. First, through an adaptation of the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Edit intent: coherence
Original:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Revised:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Edit intent: fluency
Original:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Revised:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust-yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Edit intent: fluency
Original:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Revised:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, a topology found in a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Edit intent: clarity
Original:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Revised:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected.
Edit intent: coherence
Original:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected. Using loss-given-default dynamics [ 3 ], "extinction analysis" simulations show that interdependence increased from 2001 to 2007.
Revised:  In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . We compare these results against four common null-models, generated only from first-order statistics of the empirical data. In addition, we suggest a fifth, log-normal model, which generates networks that seem to match the empirical one more closely. Still, this model does not account for several higher order network statistics, which reenforces the added value of the higher-order analysis. Second, using loss-given-default dynamics [ 3 ], "extinction analysis" simulations show that interdependence increased from 2001 to 2007.
Edit intent: meaning-changed
Original:  Using loss-given-default dynamics [ 3 ], "extinction analysis" simulations show that interdependence increased from 2001 to 2007. Our simulations further indicate that default by a single relatively small country like Greece can be absorbed by the network, but that default in combination with defaults of other PIGS countries (Portugal, Ireland, and Spain) could lead to a massive extinction cascade in the global economy.
Revised:  Using loss-given-default dynamics [ 3 ], we model financial interdependence and potential cascading of financial distress through the network. Preliminary simulations indicate that default by a single relatively small country like Greece can be absorbed by the network, but that default in combination with defaults of other PIGS countries (Portugal, Ireland, and Spain) could lead to a massive extinction cascade in the global economy.
Edit intent: clarity
Original:  Our simulations further indicate that default by a single relatively small country like Greece can be absorbed by the network, but that default in combination with defaults of other PIGS countries (Portugal, Ireland, and Spain) could lead to a massive extinction cascade in the global economy. Adaptations of this approach could form the basis for risk metrics designed to monitor and guide policy formulation for the stability of the global economy.
Revised:  Our simulations further indicate that default by a single relatively small country like Greece can be absorbed by the network, but that default in combination with defaults of other PIGS countries (Portugal, Ireland, and Spain) could lead to a massive extinction cascade in the global economy.
Edit intent: coherence
Original:  In particular, we subject the WTW to a principled set of in silico "knockout experiments ", akin to those carried out in the investigation of food webs, but suitably adapted to this macroeconomic network.
Revised:  In particular, we subject the WTW to a principled set of in silico "knockout experiments ," akin to those carried out in the investigation of food webs, but suitably adapted to this macroeconomic network.
Edit intent: fluency
Original:  Moreover, there is evidence of  sharp change in the structure of the network in the 1960s and 1970s, where the most measures of robustness rapidly increase before resuming a declining trend.
Revised:  Moreover, there is evidence of a sharp change in the structure of the network in the 1960s and 1970s, where the most measures of robustness rapidly increase before resuming a declining trend.
Edit intent: fluency
Original:  In this way we anticipate that knockout experiments like these can play an important role in the evaluation of the stability of economic systems.
Revised:  These analyses depend on a simple model of dynamics that rebalances the trade flow upon network perturbation, the most dramatic of which is node deletion. More subtle and textured forms of perturbation lead to the definition of other measures of node importance as well as vulnerability. We anticipate that experiments and measures like these can play an important role in the evaluation of the stability of economic systems.
Edit intent: meaning-changed
Original:  Except for this very important salt bridge, other three important salt bridges GLU196--ARG156--HIS187 and GLU211--HIS177 are also found to greatly contribute to the structural stability of horse prion protein.
Revised:  Besides this very important salt bridge, other three important salt bridges GLU196--ARG156--HIS187 and GLU211--HIS177 are also found to greatly contribute to the structural stability of horse prion protein.
Edit intent: coherence
Original:  Except for this very important salt bridge, other three important salt bridges GLU196--ARG156--HIS187 and GLU211--HIS177 are also found to greatly contribute to the structural stability of horse prion protein.
Revised:  Except for this very important salt bridge, other four important salt bridges GLU196--ARG156--HIS187 and GLU211--HIS177 are also found to greatly contribute to the structural stability of horse prion protein.
Edit intent: meaning-changed
Original:  Except for this very important salt bridge, other three important salt bridges GLU196--ARG156--HIS187 and GLU211--HIS177 are also found to greatly contribute to the structural stability of horse prion protein.
Revised:  Except for this very important salt bridge, other three important salt bridges GLU196-ARG156-HIS187, ARG156-ASP202 and GLU211-HIS177 are also found to greatly contribute to the structural stability of horse prion protein.
Edit intent: meaning-changed
Original:  To demonstrate the capabilities of the tool set we show the in uence of thread affinity on performance using the well-known OpenMP STREAM triad benchmark, use hardware counter tools to study the performance of a stencil code, and finally show how to detect bandwidth problems on ccNUMA-based compute nodes.
Revised:  To demonstrate the capabilities of the tool set we show the influence of thread affinity on performance using the well-known OpenMP STREAM triad benchmark, use hardware counter tools to study the performance of a stencil code, and finally show how to detect bandwidth problems on ccNUMA-based compute nodes.
Edit intent: fluency
Original:  The model is motivated by {\em  experiments URLanelle motility along a microtubule (MT),  where particles are propelled by molecular motors (dynein and kinesin) along the thirteen protofilaments of the MT . In the model, particles can switch directions of motion due to "tug-of-war" events between counteracting motors.
Revised:  The model is motivated by {\em in vivo experiments URLanelle motility along a microtubule (MT), where particles are propelled by molecular motors (dynein and kinesin) along the thirteen protofilaments of the MT . In the model, particles can switch directions of motion due to "tug-of-war" events between counteracting motors.
Edit intent: meaning-changed
Original:  The model is motivated by {\em  experiments URLanelle motility along a microtubule (MT),  where particles are propelled by molecular motors (dynein and kinesin) along the thirteen protofilaments of the MT . In the model, particles can switch directions of motion due to "tug-of-war" events between counteracting motors.
Revised:  The model is motivated by {\em experiments URLanelle motility along a microtubule (MT), consisting of thirteen protofilaments, where particles are propelled by molecular motors (dynein and kinesin) along the thirteen protofilaments of the MT . In the model, particles can switch directions of motion due to "tug-of-war" events between counteracting motors.
Edit intent: clarity
Original:  The model is motivated by {\em  experiments URLanelle motility along a microtubule (MT),  where particles are propelled by molecular motors (dynein and kinesin) along the thirteen protofilaments of the MT . In the model, particles can switch directions of motion due to "tug-of-war" events between counteracting motors.
Revised:  The model is motivated by {\em experiments URLanelle motility along a microtubule (MT), where particles are propelled by molecular motors (dynein and kinesin) . In the model, particles can switch directions of motion due to "tug-of-war" events between counteracting motors.
Edit intent: clarity
Original:  The model is motivated by {\em  experiments URLanelle motility along a microtubule (MT),  where particles are propelled by molecular motors (dynein and kinesin) along the thirteen protofilaments of the MT . In the model, particles can switch directions of motion due to "tug-of-war" events between counteracting motors.
Revised:  The model is motivated by {\em experiments URLanelle motility along a microtubule (MT), where particles are propelled by molecular motors (dynein and kinesin) along the thirteen protofilaments of the MT . In the URLanelles (particles) can switch directions of motion due to "tug-of-war" events between counteracting motors.
Edit intent: clarity
Original:   In particular, we find a nonlinear scaling of the mean {\em   number of particles accumulated at the tip (%DIFDELCMD < {\em %%% tip size ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Revised:  We show that the ability of lane changes can affect the transport efficiency and the particle-direction change rate obtained from experiments is close to optimal in order to achieve efficient motor URLanelle transport in a living cell. In particular, we find a nonlinear scaling of the mean {\em number of particles accumulated at the tip (%DIFDELCMD < {\em %%% tip size ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Edit intent: meaning-changed
Original:   In particular, we find a nonlinear scaling of the mean {\em   number of particles accumulated at the tip (%DIFDELCMD < {\em %%% tip size ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Revised:  In particular, we find a nonlinear scaling of the mean {\em tip size number of particles accumulated at the tip (%DIFDELCMD < {\em %%% tip size ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Edit intent: meaning-changed
Original:   In particular, we find a nonlinear scaling of the mean {\em   number of particles accumulated at the tip (%DIFDELCMD < {\em %%% tip size ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Revised:  In particular, we find a nonlinear scaling of the mean {\em (the number of particles accumulated at the tip (%DIFDELCMD < {\em %%% tip size ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Edit intent: meaning-changed
Original:   In particular, we find a nonlinear scaling of the mean {\em   number of particles accumulated at the tip (%DIFDELCMD < {\em %%% tip size ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Revised:  In particular, we find a nonlinear scaling of the mean {\em number of particles accumulated at the tip %DIFDELCMD < {\em %%% tip size ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Edit intent: fluency
Original:   In particular, we find a nonlinear scaling of the mean {\em   number of particles accumulated at the tip (%DIFDELCMD < {\em %%% tip size ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Revised:  In particular, we find a nonlinear scaling of the mean {\em number of particles accumulated at the tip (%DIFDELCMD < {\em %%% ) with injection rate and an associated phase transition leading to {\em pulsing states} characterized by periodic filling and emptying of the system .
Edit intent: clarity