wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Here we show that maximizing likelihood over both response functions and noise functions is equivalent to simply identifying maximally informative response functions -- ones that maximize the mutual information I[ R;M ] between predicted responses and corresponding measurements .
Revised:  Here we show that maximizing likelihood over both response functions and noise functions is equivalent to simply identifying maximally informative response functions -- ones that maximize the mutual information I[ R;M ] between observed measurements and predicted representations .
Edit intent: clarity
Original:  We note that experiments of the type considered are unable to distinguish between parametrized response functions lying along certain "diffeomorphic modes" in parameter space . We show how to derive these diffeomorphic modes and observe, fortunately, that such modes typically span a very low-dimensional subspace of parameter space. Therefore, given sufficient data, maximizing mutual information can pinpoint nearly all response function parameters without requiring any model of experimental noise .
Revised:  We note that experiments of the type considered are unable to distinguish between parametrized response functions lying along certain "diffeomorphic modes" in parameter space unconstrained. We term these directions "diffeomorphic modes" and present an equation that allows these modes to be derived systematically. The presence of diffeomorphic modes reflects a fundamental and nontrivial substructure within parameter space, one that is obscured by standard likelihood-based inference .
Edit intent: clarity
Original: PD curve calibration refers to the task of transforming a set of conditional probabilities of default (PDs) to another average PD level that is determined by a change of the underlying unconditional PD.
Revised: PD curve calibration refers to the task of transforming a set of rating grade-level probabilities of default (PDs) to another average PD level that is determined by a change of the underlying unconditional PD.
Edit intent: meaning-changed
Original: PD curve calibration refers to the task of transforming a set of conditional probabilities of default (PDs) to another average PD level that is determined by a change of the underlying unconditional PD.
Revised: PD curve calibration refers to the task of transforming a set of conditional probabilities of default (PDs) to another average PD level that is determined by a change of the underlying portfolio-wide PD.
Edit intent: meaning-changed
Original: PD curve calibration refers to the transformation of a set of rating grade-level probabilities of default (PDs) to another average PD level that is determined by a change of the underlying portfolio-wide PD.
Revised: PD curve calibration refers to the transformation of a set of rating grade level probabilities of default (PDs) to another average PD level that is determined by a change of the underlying portfolio-wide PD.
Edit intent: fluency
Original:  We show that the popular 'scaled PD curve ' approach is theoretically questionable and does not perform well on the test datasets. We identify two calibration approaches that are both theoretically sound and perform much better on the test datasets.
Revised:  We show that the popular 'scaled PD curve ' approach is theoretically questionable and identify an alternative calibration approach ('scaled likelihood ratio') that is both theoretically sound and perform much better on the test datasets.
Edit intent: meaning-changed
Original:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of  consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Revised:  The idea is based on modeling the effects of the pH value on the main driving interactions . We use reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Edit intent: coherence
Original:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of  consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Revised:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transfer its main physical features to the coarse-grained resolution according the principle of consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Edit intent: fluency
Original:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of  consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Revised:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of " consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Edit intent: fluency
Original:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of  consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Revised:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of consistency across the scales ". The coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Edit intent: coherence
Original:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of  consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Revised:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of consistency across the scales . After refining the coarse-grained model is refined by finding a unique set of parameters for the coarse-grained model that,
Edit intent: coherence
Original:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of  consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Revised:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a set of parameters for the coarse-grained model that,
Edit intent: clarity
Original:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of  consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters for the coarse-grained model that,
Revised:  The idea is based on modeling the effects of the pH value on the main driving interactions using reference data from atomistic simulations and experimental databases and transferring its main physical features to the coarse-grained resolution according the principle of consistency across the scales . After refining the coarse-grained model appropriately this was achieved by finding a unique set of parameters that,
Edit intent: coherence
Original:  Brief characterisation of ion transport systems of a yeast cell (Pma1, Ena1, TOK1, Nha1, Trk1, Trk2, non-selective cation conductance) and estimates concerning the number of molecules of each transporter per a cell allow predicting the corresponding ion flows.
Revised:  Brief characterization of main ion transport systems of a yeast cell (Pma1, Ena1, TOK1, Nha1, Trk1, Trk2, non-selective cation conductance) and estimates concerning the number of molecules of each transporter per a cell allow predicting the corresponding ion flows.
Edit intent: clarity
Original:  Brief characterisation of ion transport systems of a yeast cell (Pma1, Ena1, TOK1, Nha1, Trk1, Trk2, non-selective cation conductance) and estimates concerning the number of molecules of each transporter per a cell allow predicting the corresponding ion flows.
Revised:  Brief characterisation of ion transport systems of a yeast cell (Pma1, Ena1, TOK1, Nha1, Trk1, Trk2, non-selective cation conductance) and determining the exact number of molecules of each transporter per a cell allow predicting the corresponding ion flows.
Edit intent: clarity
Original:  Brief characterisation of ion transport systems of a yeast cell (Pma1, Ena1, TOK1, Nha1, Trk1, Trk2, non-selective cation conductance) and estimates concerning the number of molecules of each transporter per a cell allow predicting the corresponding ion flows.
Revised:  Brief characterisation of ion transport systems of a yeast cell (Pma1, Ena1, TOK1, Nha1, Trk1, Trk2, non-selective cation conductance) and estimates concerning the number of molecules of each transporter per a typical cell allow us to predict the corresponding ion flows.
Edit intent: clarity
Original:  Comparison of ion transport in small yeast cell and several animal cell types is provided and importance of cell volume to surface ratio is stressed. Role of cell wall and lipid rafts is discussed in aspect of required increase in spatial and temporary resolution of measurements.
Revised:  Comparison of ion transport in small yeast cell and several animal cell types is provided and importance of cell volume to surface ratio is emphasized. The role of cell wall and lipid rafts is discussed in aspect of required increase in spatial and temporary resolution of measurements.
Edit intent: clarity
Original:  109, 228101, 2012) the elastic properties of DNA were studied by molecular dynamics (MD) simulations . Two important conclusions were made: (i) the computed bending and twisting rigidities of DNA agree well with experimental data , and (ii) for lengths of a few helical turns, DNA dynamics exhibits long-range correlations in qualitative difference from the worm-like rod (WLR) model.
Revised:  109, 228101, 2012) the elastic properties of DNA were studied by molecular dynamics (MD) simulations predict DNA rigidity close to experimental data and confirm one scenario of such breakdown, namely, that for lengths of a few helical turns, DNA dynamics exhibits long-range correlations in qualitative difference from the worm-like rod (WLR) model.
Edit intent: meaning-changed
Original:  Two important conclusions were made: (i) the computed bending and twisting rigidities of DNA agree well with experimental data , and (ii) for lengths of a few helical turns, DNA dynamics exhibits long-range correlations in qualitative difference from the worm-like rod (WLR) model.
Revised:  Two important conclusions were made: (i) the computed bending and twisting rigidities of DNA agree well with experimental data , and (ii) for lengths of a few helical turns, DNA dynamics exhibit long-range correlations in qualitative difference from the worm-like rod (WLR) model.
Edit intent: fluency
Original:  Two important conclusions were made: (i) the computed bending and twisting rigidities of DNA agree well with experimental data , and (ii) for lengths of a few helical turns, DNA dynamics exhibits long-range correlations in qualitative difference from the worm-like rod (WLR) model. Earlier similar studies showed that (i) the current MD forcefields systematically overestimate the DNA rigidity, and (ii) MD trajectories of DNA involve only short-range correlations;
Revised:  Two important conclusions were made: (i) the computed bending and twisting rigidities of DNA agree well with experimental data , and (ii) for lengths of a few helical turns, DNA dynamics exhibits long-range bending and stretching correlations. Earlier studies using similar forcefields concluded that (i) the current MD forcefields systematically overestimate the DNA rigidity, and (ii) MD trajectories of DNA involve only short-range correlations;
Edit intent: clarity
Original:  The combination of these spatio-temporal aspects can be modulated to provide a switch-like response behavior without invoking sophisticated modeling of the signaling process as a sequence of cascade reactions and fine-tuned parameters.
Revised:  The combination of these spatio-temporal aspects can be modulated to provide a robust and high-fidelity response behavior without invoking sophisticated modeling of the signaling process as a sequence of cascade reactions and fine-tuned parameters.
Edit intent: meaning-changed
Original:  Our results also show that the URLanization of the signaling process and the fact that the distributed  events take place in nanoclusters with a finite lifetime regulated by local production is sufficient to obtain a robust and high-fidelity response.
Revised:  Our results show that the URLanization of the signaling process and the fact that the distributed events take place in nanoclusters with a finite lifetime regulated by local production is sufficient to obtain a robust and high-fidelity response.
Edit intent: clarity
Original:  Our results also show that the URLanization of the signaling process and the fact that the distributed  events take place in nanoclusters with a finite lifetime regulated by local production is sufficient to obtain a robust and high-fidelity response.
Revised:  Our results also show that the fact that the distributed events take place in nanoclusters with a finite lifetime regulated by local production is sufficient to obtain a robust and high-fidelity response.
Edit intent: clarity
Original:  Our results also show that the URLanization of the signaling process and the fact that the distributed  events take place in nanoclusters with a finite lifetime regulated by local production is sufficient to obtain a robust and high-fidelity response.
Revised:  Our results also show that the URLanization of the signaling process and the fact that the distributed signaling events take place in nanoclusters with a finite lifetime regulated by local production is sufficient to obtain a robust and high-fidelity response.
Edit intent: fluency
Original: The goal of this study is to make connections between Bollinger Bands and time series models in order to gain a better understanding of the statistical underpinnings of Bollinger Bands. In the first part of the study, we review a popular econometric model called the rolling regression time series model and illustrate an equivalence between the latter and the Bollinger Band methodology.
Revised: The goal of this study is to make connections between Bollinger Bands and time series models in order to gain a better understanding of the statistical underpinnings of the Bollinger Band methodology. We start off by elucidating the rolling regression time series model and illustrate an equivalence between the latter and the Bollinger Band methodology.
Edit intent: clarity
Original:  In the first part of the study, we review a popular econometric model called the rolling regression time series model and illustrate an equivalence between the latter and the Bollinger Band methodology. In the second part of the study, we illustrate the use of Bollinger Bands in pairs trading \mbox{%DIFAUXCMD INV2007 return duration relationship in Bollinger Bands pairs trading.
Revised:  In the first part of the study, we review a popular econometric model called the rolling regression time series model and deriving its explicit relationship to Bollinger Bands. Next we illustrate the use of Bollinger Bands in pairs trading \mbox{%DIFAUXCMD INV2007 return duration relationship in Bollinger Bands pairs trading.
Edit intent: clarity
Original:  In the second part of the study, we illustrate the use of Bollinger Bands in pairs trading \mbox{%DIFAUXCMD INV2007 return duration relationship in Bollinger Bands pairs trading.
Revised:  In the second part of the study, we illustrate the use of Bollinger Bands in pairs trading and prove the existence of a specific return duration relationship in Bollinger Bands pairs trading.
Edit intent: clarity
Original:  In the second part of the study, we illustrate the use of Bollinger Bands in pairs trading \mbox{%DIFAUXCMD INV2007 return duration relationship in Bollinger Bands pairs trading.
Revised:  In the second part of the study, we illustrate the use of Bollinger Bands in pairs trading \mbox{%DIFAUXCMD INV2007 return duration relationship in Bollinger Band pairs trading.
Edit intent: fluency
Original: Then , by viewing Bollinger Bands as an approximation to the random walk plus noise (RWPN) time series model, we are able to modify the Bollinger Band algorithm used in pairs trading and develop a pairs trading variant that we call "Fixed Forecast Maximum Duration  Bands" (FFMDPT).
Revised: Then by viewing the Bollinger Band moving average as an approximation to the random walk plus noise (RWPN) time series model, we are able to modify the Bollinger Band algorithm used in pairs trading and develop a pairs trading variant that we call "Fixed Forecast Maximum Duration Bands" (FFMDPT).
Edit intent: meaning-changed
Original: Then , by viewing Bollinger Bands as an approximation to the random walk plus noise (RWPN) time series model, we are able to modify the Bollinger Band algorithm used in pairs trading and develop a pairs trading variant that we call "Fixed Forecast Maximum Duration  Bands" (FFMDPT).
Revised: Then , by viewing Bollinger Bands as an approximation to the random walk plus noise (RWPN) time series model, we develop a pairs trading variant that we call "Fixed Forecast Maximum Duration Bands" (FFMDPT).
Edit intent: clarity
Original: Then , by viewing Bollinger Bands as an approximation to the random walk plus noise (RWPN) time series model, we are able to modify the Bollinger Band algorithm used in pairs trading and develop a pairs trading variant that we call "Fixed Forecast Maximum Duration  Bands" (FFMDPT).
Revised: Then , by viewing Bollinger Bands as an approximation to the random walk plus noise (RWPN) time series model, we are able to modify the Bollinger Band algorithm used in pairs trading and develop a pairs trading variant that we call "Fixed Forecast Maximum Duration ' Bands" (FFMDPT).
Edit intent: fluency
Original:  We assume that the Brownian motion and jump process are independent, and there exists a  probability density function for the jump times and marks . Under these assumptions, we decompose the global controller-stopper problem into controller-stopper problems with respect to the Brownian filtration, which are determined by a backward induction.
Revised:  We assume that the Brownian motion and jump process are independent, and there exists a probability density function for the jump times and marks given the filtration of the Brownian motion and decompose the global controller-stopper problem into controller-stopper problems with respect to the Brownian filtration, which are determined by a backward induction.
Edit intent: meaning-changed
Original:  To address this technical bottleneck, we have created a series of Gateway shuttle vectors  , which facilitate the assembly of artificial genes and their expression in the budding yeast Saccharomyces cerevisiae.
Revised:  To address this technical bottleneck, we have created a series of Gateway shuttle vectors and an integration vector , which facilitate the assembly of artificial genes and their expression in the budding yeast Saccharomyces cerevisiae.
Edit intent: meaning-changed
Original: Equivalent characterizations of multi-portfolio time consistency are deduced for closed convex and coherent set-valued risk measures on L^p_d  . In the convex case, multi-portfolio time consistency is equivalent to a  condition on the sum of minimal penalty functions.
Revised: Equivalent characterizations of multi-portfolio time consistency are deduced for closed convex and coherent set-valued risk measures on L^p_d (F_T) with image space in the power set of L^p_d(F_t) . In the convex case, multi-portfolio time consistency is equivalent to a condition on the sum of minimal penalty functions.
Edit intent: meaning-changed
Original: Equivalent characterizations of multi-portfolio time consistency are deduced for closed convex and coherent set-valued risk measures on L^p_d  . In the convex case, multi-portfolio time consistency is equivalent to a  condition on the sum of minimal penalty functions.
Revised: Equivalent characterizations of multi-portfolio time consistency are deduced for closed convex and coherent set-valued risk measures on L^p_d . In the convex case, multi-portfolio time consistency is equivalent to a cocycle condition on the sum of minimal penalty functions.
Edit intent: meaning-changed
Original:  As examples, the  set of superhedging portfolios in markets with  transaction costs is shown to have the stability property  and a multi-portfolio time consistent version of the set-valued average value at risk, the composed AV@R, is given and its dual representation deduced.
Revised:  As examples, the set-valued entropic risk measure with constant risk aversion coefficient is shown to satisfy the cocycle condition for its minimal penalty functions, the set of superhedging portfolios in markets with transaction costs is shown to have the stability property and a multi-portfolio time consistent version of the set-valued average value at risk, the composed AV@R, is given and its dual representation deduced.
Edit intent: meaning-changed