wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Additionally, we have validated that the charging of the molecules is of main importance . Furthermore we show the impact of a locally varying salt concentration . Experimental results are shown which indicate a direct influence of compatible solutes on the liquid expanded-liquid condensed phase transition in DPPC monolayers.
Revised:  Additionally, we have validated that the charging of the molecules is of main importance resulting in a well defined hydration sphere. The influence of a varying salt concentration . Experimental results are shown which indicate a direct influence of compatible solutes on the liquid expanded-liquid condensed phase transition in DPPC monolayers.
Edit intent: meaning-changed
Original:  Furthermore we show the impact of a locally varying salt concentration . Experimental results are shown which indicate a direct influence of compatible solutes on the liquid expanded-liquid condensed phase transition in DPPC monolayers. We are able to identify a variation of the local water pressure around the comaptible solutes by numerical calculations as a possible reason for an experimentally observed broadening of the phase transition .
Revised:  Furthermore we show the impact of a locally varying salt concentration is also investigated. Finally we present experimental results of a DPPC monolayer phase transition that validate our numerical findings .
Edit intent: coherence
Original:  The stability result , in particular, implies that in the framework of 4 , the optimal wealth at any given stopping time is stable with respect to changes in the Sharpe ratio and initial wealth.
Revised:  The stability result , in particular, implies that in the framework of \mbox{%DIFAUXCMD MR2438002 , the optimal wealth at any given stopping time is stable with respect to changes in the Sharpe ratio and initial wealth.
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Original:  In this paper we apply the nested sampling algorithm to the problem of protein folding in a  force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations.
Revised:  In this paper we apply the nested sampling algorithm to the problem of protein folding in a Go-type force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations.
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Original:   The topology of the protein molecule emerges as a major determinant of the shape of the energy landscape .
Revised:  We demonstrate the method by conducting folding simulations on a number of small proteins which are commonly used for testing protein folding procedures: protein G, the SH3 domain of Src tyrosine kinase and chymotrypsin inhibitor 2. We compare our results for protein G to those obtained using parallel tempering with the same model. The topology of the protein molecule emerges as a major determinant of the shape of the energy landscape .
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Original:   The topology of the protein molecule emerges as a major determinant of the shape of the energy landscape . The algorithm was tested with protein G. The tertiary structure of the protein was predicted to a reasonably high level of accuracy. The best conformation found had an RMSD of 3.12A from the native structure. Two other proteins, chymotrypsin inhibitor 2 and Src tyrosine kinase SH3 domain, were also tested, with the best conformations found having RMSD 4.75A and 5.33A from their respective native structures .
Revised:  The topology of the protein molecule emerges as a major determinant of the shape of the energy landscape .
Edit intent: coherence
Original:   Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering  .
Revised:  The nested sampling algo- rithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post-processing of the output. Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering .
Edit intent: meaning-changed
Original:  In this paper we apply the nested sampling algorithm  to the problem of protein folding in a Go-type force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations.
Revised:  In this paper we describe a parallel implementation of the nested sampling algorithm to the problem of protein folding in a Go-type force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations.
Edit intent: meaning-changed
Original:  In this paper we apply the nested sampling algorithm  to the problem of protein folding in a Go-type force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations.
Revised:  In this paper we apply the nested sampling algorithm and its application to the problem of protein folding in a Go-type force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations.
Edit intent: meaning-changed
Original:   A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high level description of the potential energy surface for the protein folding simulations.
Revised:  We demonstrate the method by conducting folding simulations on a number of small proteins which are commonly used for testing protein folding procedures: protein G, the SH3 domain of Src tyrosine kinase and chymotrypsin inhibitor 2. A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high level description of the potential energy surface for the protein folding simulations.
Edit intent: meaning-changed
Original:  These charts provide qualitative insights into both the folding process and the nature of the model and force field used . We demonstrate the method by conducting folding simulations on a number of small proteins which are commonly used for testing protein folding procedures: protein G, the SH3 domain of Src tyrosine kinase and chymotrypsin inhibitor 2. We compare our results for protein G to those obtained using parallel tempering with the same model. The topology of the protein molecule emerges as a major determinant of the shape of the energy landscape. The nested sampling algorithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post-processing of the output .
Revised:  These charts provide qualitative insights into both the folding process and the nature of the model and force field used .
Edit intent: coherence
Original:  Given fixed power allocation to the OFDM subcarriers, we observe that a sorted-SNR subcarrier pairing strategy is data-rate optimal, where each relay pairs its incoming and outgoing subcarriers by their SNR order.
Revised:  Given fixed power allocation to the channels, we show that channel pairing over multiple hops can be decomposed into independent pairing problems at each relay, and a sorted-SNR subcarrier pairing strategy is data-rate optimal, where each relay pairs its incoming and outgoing subcarriers by their SNR order.
Edit intent: meaning-changed
Original:  Given fixed power allocation to the OFDM subcarriers, we observe that a sorted-SNR subcarrier pairing strategy is data-rate optimal, where each relay pairs its incoming and outgoing subcarriers by their SNR order.
Revised:  Given fixed power allocation to the OFDM subcarriers, we observe that a sorted-SNR channel pairing strategy is data-rate optimal, where each relay pairs its incoming and outgoing subcarriers by their SNR order.
Edit intent: clarity
Original:  Given fixed power allocation to the OFDM subcarriers, we observe that a sorted-SNR subcarrier pairing strategy is data-rate optimal, where each relay pairs its incoming and outgoing subcarriers by their SNR order.
Revised:  Given fixed power allocation to the OFDM subcarriers, we observe that a sorted-SNR subcarrier pairing strategy is sum-rate optimal, where each relay pairs its incoming and outgoing subcarriers by their SNR order.
Edit intent: clarity
Original:  Given fixed power allocation to the OFDM subcarriers, we observe that a sorted-SNR subcarrier pairing strategy is data-rate optimal, where each relay pairs its incoming and outgoing subcarriers by their SNR order.
Revised:  Given fixed power allocation to the OFDM subcarriers, we observe that a sorted-SNR subcarrier pairing strategy is data-rate optimal, where each relay pairs its incoming and outgoing channels by their SNR order.
Edit intent: clarity
Original:  This separation principle significantly reduces the computational complexity in finding the jointly optimal solution. We further establish the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution , which allows simple implementation of optimal subcarrier pairing at the relays.
Revised:  This separation principle is established by observing the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution , which allows simple implementation of optimal subcarrier pairing at the relays.
Edit intent: clarity
Original:  We further establish the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution , which allows simple implementation of optimal subcarrier pairing at the relays. Simulation results are presented to demonstrate the performance gain of the jointly optimal solution over some suboptimal alternatives  .
Revised:  We further establish the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution . It significantly reduces the computational complexity in finding the jointly optimal solution. The solution for optimizing power allocation is also provided. Numerical results are provided to demonstrate substantial performance gain of the jointly optimal solution over some suboptimal alternatives .
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Original:  Simulation results are presented to demonstrate the performance gain of the jointly optimal solution over some suboptimal alternatives  .
Revised:  Simulation results are presented to demonstrate the performance gain of the jointly optimal solution over some suboptimal alternatives . It is also observed that more gain is obtained from optimal channel pairing than optimal power allocation through judiciously exploiting the variation among multiple channels. Impact of the variation of channel gain, the number of channels, and the number of hops on the performance gain is also studied through numerical examples .
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Original:   The solution for optimizing power allocation  is also provided  . Numerical results are provided to demonstrate substantial performance gain of the jointly optimal solution over some suboptimal alternatives.
Revised:  It follows that the channel pairing problem in joint optimization can be again decomposed into independent pairing problems at each relay based on sorted channel gains. The solution for optimizing power allocation is also provided . Numerical results are provided to demonstrate substantial performance gain of the jointly optimal solution over some suboptimal alternatives.
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Original:  The empirical research of these two points would lead to early warning of economic crisis  .
Revised:  The empirical research of these two points would lead to early warning of economic crisis . Moreover, it is a surprise that the state of economic crisis would be a feasible equilibrium within the framework of the Arrow-Debreu model. That means that we can not understand the origin of economic crisis within the framework of modern economics, for example, the general equilibrium theory .
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Original:  Compared to other proposed non-interactive localization algorithms, the weighted centroid localization (WCL) scheme uses only  received signal strength information, which makes it simple  and robust to variations in the propagation environment.
Revised:  Compared to other proposed non-interactive localization algorithms, the weighted centroid localization (WCL) scheme uses only the received signal strength information, which makes it simple and robust to variations in the propagation environment.
Edit intent: fluency
Original:  Compared to other proposed non-interactive localization algorithms, the weighted centroid localization (WCL) scheme uses only  received signal strength information, which makes it simple  and robust to variations in the propagation environment.
Revised:  Compared to other proposed non-interactive localization algorithms, the weighted centroid localization (WCL) scheme uses only received signal strength information, which makes it simple to implement and robust to variations in the propagation environment.
Edit intent: clarity
Original:  In contrast to prior work, which focused mainly on proposing algorithmic variations and verifying their performance through simulations, in this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance and correlation distance.
Revised:  In this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance and correlation distance.
Edit intent: coherence
Original:  In this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance and correlation distance . Using this analysis, we quantify the robustness of WCL to various physical conditions and provide design guidelines, such as node placement  , for the practical deployment of WCL.
Revised:  In this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance , correlation distance and inaccuracy of sensor node positioning . Using this analysis, we quantify the robustness of WCL to various physical conditions and provide design guidelines, such as node placement , for the practical deployment of WCL.
Edit intent: meaning-changed
Original:  In this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance and correlation distance . Using this analysis, we quantify the robustness of WCL to various physical conditions and provide design guidelines, such as node placement  , for the practical deployment of WCL.
Revised:  In this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance and correlation distance . Using this analysis, we quantify the robustness of WCL to various physical conditions and provide design guidelines, such as node placement and spacing , for the practical deployment of WCL.
Edit intent: clarity
Original: This paper investigates the impact of parameter uncertainty on capital estimate in the well-known extended Loss Given Default (LGD) model with systematic dependence between default and recovery .
Revised: It is a well known fact that recovery rates tend to go down when the number of defaults goes up in economic downturns. We demonstrate how the loss given default model with the well-known extended Loss Given Default (LGD) model with systematic dependence between default and recovery .
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Original: This paper investigates the impact of parameter uncertainty on capital estimate in the well-known extended Loss Given Default (LGD) model with systematic dependence between default and recovery . We demonstrate how the uncertainty can be quantified using the full posterior distribution of model parameters obtained from Bayesian inference via Markov chain Monte Carlo (MCMC).
Revised: This paper investigates the impact of parameter uncertainty on capital estimate in the well-known extended Loss Given Default (LGD) model with systematic dependence between default and recovery dependent via the latent systematic risk factor can be estimated using Bayesian inference methodology and Markov chain Monte Carlo (MCMC).
Edit intent: meaning-changed
Original:  We demonstrate how the uncertainty can be quantified using the full posterior distribution of model parameters obtained from Bayesian inference via Markov chain Monte Carlo (MCMC). Results show that the parameter uncertainty and its impact on capital can be very significant. We have also quantified the effect of diversification for a finite number of borrowers in comparison with the infinitely granular portfolio .
Revised:  We demonstrate how the uncertainty can be quantified using the full posterior distribution of model parameters obtained from Bayesian inference via Markov chain Monte Carlo method. This approach is very convenient for joint estimation of all model parameters and latent systematic factors. Moreover, all relevant uncertainties are easily quantified. Typically available data are annual averages of defaults and recoveries and thus the datasets are small and parameter uncertainty is significant. In this case Bayesian approach is superior to the maximum likelihood method that relies on a large sample limit Gaussian approximation for the parameter uncertainty. As an example, we consider a homogeneous portfolio with one latent factor. However, the approach can be easily extended to deal with non-homogenous portfolios and several latent factors .
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Original:  However, it remains a challenge to combine a classification scheme that describes a protein starting from its  secondary structures and often involves direct human involvement, with an atomary level Physics based approach where a protein is fundamentally viewed as not much more than an ensemble of mutually interacting carbon, hydrogen, oxygen and nitrogen atoms.
Revised:  But it remains a challenge to combine a classification scheme that describes a protein starting from its secondary structures and often involves direct human involvement, with an atomary level Physics based approach where a protein is fundamentally viewed as not much more than an ensemble of mutually interacting carbon, hydrogen, oxygen and nitrogen atoms.
Edit intent: fluency
Original:  However, it remains a challenge to combine a classification scheme that describes a protein starting from its  secondary structures and often involves direct human involvement, with an atomary level Physics based approach where a protein is fundamentally viewed as not much more than an ensemble of mutually interacting carbon, hydrogen, oxygen and nitrogen atoms.
Revised:  However, it remains a challenge to combine a classification scheme that describes a protein starting from its URLanized secondary structures and often involves direct human involvement, with an atomary level Physics based approach where a protein is fundamentally viewed as not much more than an ensemble of mutually interacting carbon, hydrogen, oxygen and nitrogen atoms.
Edit intent: meaning-changed
Original:  However, it remains a challenge to combine a classification scheme that describes a protein starting from its  secondary structures and often involves direct human involvement, with an atomary level Physics based approach where a protein is fundamentally viewed as not much more than an ensemble of mutually interacting carbon, hydrogen, oxygen and nitrogen atoms.
Revised:  However, it remains a challenge to combine a classification scheme that describes a protein starting from its secondary structures and often involves direct human involvement, with an atomary level Physics based approach where a protein is fundamentally nothing more than an ensemble of mutually interacting carbon, hydrogen, oxygen and nitrogen atoms.
Edit intent: clarity
Original:  Here we explain how the geometrical shape of secondary superstructures such as helix-loop-helix motifs, and even entire folded proteins , can be described analytically in terms of a single explicit elementary function that is familiar from nonlinear physical systems where it is known as the kink-soliton.
Revised:  Here we explain how the geometrical shape of entire folded proteins , can be described analytically in terms of a single explicit elementary function that is familiar from nonlinear physical systems where it is known as the kink-soliton.
Edit intent: clarity
Original:  Here we explain how the geometrical shape of secondary superstructures such as helix-loop-helix motifs, and even entire folded proteins , can be described analytically in terms of a single explicit elementary function that is familiar from nonlinear physical systems where it is known as the kink-soliton.
Revised:  Here we explain how the geometrical shape of secondary superstructures such as helix-loop-helix motifs, and even entire folded proteins can be described analytically in terms of a single explicit elementary function that is familiar from nonlinear physical systems where it is known as the kink-soliton.
Edit intent: fluency
Original:  As an example of the feasibility of our approach we describe in detail how the native fold of the myoglobin 1M6C emerges from a combination of kink-solitons with a very high atomary level  accuracy.
Revised:  As an example we describe in detail how the native fold of the myoglobin 1M6C emerges from a combination of kink-solitons with a very high atomary level accuracy.
Edit intent: clarity
Original:  As an example of the feasibility of our approach we describe in detail how the native fold of the myoglobin 1M6C emerges from a combination of kink-solitons with a very high atomary level  accuracy.
Revised:  As an example of the feasibility of our approach we describe in detail how the native fold of the myoglobin 1M6C emerges from a combination of kink-solitons with a very high atomary level accuracy. We also verify that our approach describes longer loops and loops connecting \alpha-helices with \beta-strands, with same overall accuracy.
Edit intent: meaning-changed
Original:  By a technical result on explicit expressions for the comparison theorem, uniqueness theorem and viability on a rectangle of solutions to multidimensional backward stochastic differential equations, some necessary and sufficient conditions are given for the constancy, monotonicity, positivity, homogeneity and translatability properties of multidimensional conditional g-expectation and multidimensional dynamic risk measure ;
Revised:  By a technical result on explicit expressions for the comparison theorem, uniqueness theorem and viability on a rectangle of solutions to multidimensional backward stochastic differential equations, some necessary and sufficient conditions are given for the constancy, monotonicity, positivity, homogeneity and translatability properties of multidimensional conditional g-expectations and multidimensional dynamic risk measure ;
Edit intent: fluency