wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Finally weakening the information own by the agent , and assuming that she only knows a lower-bound  for the terminal value of the interest rate process, we show that the value of the information is finite  .
Revised:  Finally weakening the information own by the agent , and assuming that she only knows a lower-bound or both, a lower and an upper bound, for the terminal value of the interest rate process, we show that the value of the information is finite .
Edit intent: meaning-changed
Original:  Finally weakening the information own by the agent , and assuming that she only knows a lower-bound  for the terminal value of the interest rate process, we show that the value of the information is finite  .
Revised:  Finally weakening the information own by the agent , and assuming that she only knows a lower-bound for the terminal value of the interest rate process, we show that the value of the information is finite . This solves by an analytical proof a conjecture stated in Pikovsky and Karatzas (1996) .
Edit intent: meaning-changed
Original:  In these papers, the authors focus on minimizing regular performance measures, i.e., functions that are non decreasing in the jobs completion time, subject to the constraint that the total rejection cost cannot exceed a predefined upper bound.
Revised:  In these papers, the authors focus on minimizing regular performance measures, i.e., functions that are non-decreasing in the jobs completion time, subject to the constraint that the total rejection cost cannot exceed a predefined upper bound.
Edit intent: fluency
Original:   Finally, we consider two applications of our cache network model : (i) directly mapping to content distribution and (ii) generalization to wireless sensor network by jointly considering content caching and content compression.
Revised:  Numerical evaluations show that our algorithm significant outperforms path replication with traditional caching algorithms over some network topologies. Finally, we consider two applications of our cache network model : (i) directly mapping to content distribution and (ii) generalization to wireless sensor network by jointly considering content caching and content compression.
Edit intent: meaning-changed
Original:   Finally, we consider two applications of our cache network model : (i) directly mapping to content distribution and (ii) generalization to wireless sensor network by jointly considering content caching and content compression. We characterize the tradeoff among caching, compression and communication via a nonlinear non-convex optimization problem. We show that it can be transformed into an equivalent convex problem. The obtained numerical results provide us with insights into how to optimize the performance .
Revised:  Finally, we consider two applications of our cache network model : (i) directly mapping to content distribution .
Edit intent: coherence
Original: Caching algorithms are usually described by the eviction method and analyzed using a metric of hit probability. Since contents have different importance (e.g. popularity), the utility of a high hit probability, and the cost of transmission can vary across contents .
Revised: Edge networks are promising to provide better services to users by provisioning computing and storage resources at the edge of networks. However, due to the uncertainty and diversity of user interests, content popularity, distributed network structure, cache sizes, it is challenging to decide where to place the content, and how long it should be cached .
Edit intent: meaning-changed
Original:  In this paper, we consider timer-based (TTL) policies across a cache network, where contents have differentiated timers over which we optimize. Each content is associated with a utility measured in terms of the corresponding hit probability. We start our analysis from a linear cache network: we propose a utility maximization problem where the objective is to maximize the sum of utilities and a cost minimization problem where the objective is to minimize the content transmission cost across the network .
Revised:  In this paper, we consider timer-based (TTL) policies . We propose provably optimal distributed algorithms that operate at each network cache to maximize the sum of utilities and a cost minimization problem where the objective is to minimize the content transmission cost across the network .
Edit intent: clarity
Original:  We start our analysis from a linear cache network: we propose a utility maximization problem where the objective is to maximize the sum of utilities and a cost minimization problem where the objective is to minimize the content transmission cost across the network . These frameworks enable us to design online algorithms for cache management, for which we prove achieving optimal performance. Informed by the results of our analysis, we formulate a non-convex optimization problem for a general cache network. We show that the duality gap is zero, hence we can develop a distributed iterative primal-dual algorithm for content management in the network. Numerical evaluations show that our algorithm significant outperforms path replication with traditional caching algorithms over some network topologies .
Revised:  We start our analysis from a linear cache network: we propose a utility maximization problem where the objective is to maximize the overall network utility. Our TTL-based optimization model provides theoretical answers to how long each content must be cached, and where it should be placed in the edge network. Extensive evaluations show that our algorithm significant outperforms path replication with traditional caching algorithms over some network topologies .
Edit intent: meaning-changed
Original:  Additionally, there has been a growing interest in the systematic comparison of multiple networks to identify deferentially changed links. Typically, such analyses are focused on the comparison of networks or data from two different conditions. Results: Here, we present an R package for calculating the weighted topological overlap (wTO), that explicitly addresses the sign of wTO values .
Revised:  Here, we present an R package for calculating the weighted topological overlap (wTO), that explicitly addresses the sign of wTO values .
Edit intent: coherence
Original:  Our package also allows the calculation of networks from time series , without replicates. Additionally, our R package incorporates a novel method for calculating a consensus network (CN) from two or more networks .
Revised:  Our package also allows the calculation of networks from time series (without replicates). Since networks from independent datasets (biological repeats or related studies) are not the same due to technical and biological noise in the data, we additionally, incorporated a novel method for calculating a consensus network (CN) from two or more networks .
Edit intent: meaning-changed
Original:  Additionally, our R package incorporates a novel method for calculating a consensus network (CN) from two or more networks . To visualize the resulting networks, the R packagecontains a visualization tool which allows for the direct network manipulation and access of node and link information. When testing the package on a standard laptop computer, we can conduct all calculations for systems of 20,000 genes in under two hours. Conclusion: In this work, we developed an R package that allows the computation of wTO networks, CNs and a visualization tool in the R statistical environment.
Revised:  Additionally, our R package incorporates a novel method for calculating a consensus network (CN) from two or more networks into our R package. We compare our new wTO package to state of art packages and demonstrate the application of the wTO and CN functions using 3 independently derived datasets from healthy human pre-frontal cortex samples. To showcase an example for the time series application we utilized a metagenomics data set. In this work, we developed an R package that allows the computation of wTO networks, CNs and a visualization tool in the R statistical environment.
Edit intent: meaning-changed
Original: If additional information about the distribution of a random variable is available in the form of moment conditions, the weighted kernel density estimator constructed by replacing the uniform weights with the generalised empirical likelihood probabilities provides an improved approximation to the moment constraints.
Revised: Given additional distributional information in the form of moment conditions, the weighted kernel density estimator constructed by replacing the uniform weights with the generalised empirical likelihood probabilities provides an improved approximation to the moment constraints.
Edit intent: clarity
Original: If additional information about the distribution of a random variable is available in the form of moment conditions, the weighted kernel density estimator constructed by replacing the uniform weights with the generalised empirical likelihood probabilities provides an improved approximation to the moment constraints.
Revised: If additional information about the distribution of a random variable is available in the form of moment restrictions, kernel density and distribution function estimators with implied generalised empirical likelihood probabilities provides an improved approximation to the moment constraints.
Edit intent: clarity
Original: If additional information about the distribution of a random variable is available in the form of moment conditions, the weighted kernel density estimator constructed by replacing the uniform weights with the generalised empirical likelihood probabilities provides an improved approximation to the moment constraints. More importantly, a reduction in variance is achieved due to the systematic use of the extra information.
Revised: If additional information about the distribution of a random variable is available in the form of moment conditions, the weighted kernel density estimator constructed by replacing the uniform weights with the generalised empirical likelihood probabilities as weights achieve a reduction in variance is achieved due to the systematic use of the extra information.
Edit intent: clarity
Original:  Same approach can be used to estimate a density or distribution of certain functions of data and, possibly, of the unknown parameters, the latter being replaced by their generalised empirical likelihood estimates. A special case of interest is estimation of densities or distributions of (generalised) residuals in semi-parametric models defined by a finite number of moment restrictions.
Revised:  The particular interest here is the estimation of densities or distributions of (generalised) residuals in semi-parametric models defined by a finite number of moment restrictions.
Edit intent: clarity
Original:  We give conditions under which such estimators are consistent, and describe their asymptotic mean squared error properties . Analytic examples illustrate the situations where re-weighting provides a reduction in variance , and a simulation study is conducted to evaluate small sample performance of the proposed estimators .
Revised:  The paper gives conditions for the consistency and describes the asymptotic mean squared error properties . Analytic examples illustrate the situations where re-weighting provides a reduction in variance , and a simulation study is conducted to evaluate small sample performance of the proposed estimators .
Edit intent: clarity
Original:  We give conditions under which such estimators are consistent, and describe their asymptotic mean squared error properties . Analytic examples illustrate the situations where re-weighting provides a reduction in variance , and a simulation study is conducted to evaluate small sample performance of the proposed estimators .
Revised:  We give conditions under which such estimators are consistent, and describe their asymptotic mean squared error properties of the kernel density and distribution estimators proposed in the paper. A simulation study evaluates the small sample performance of these estimators. Supplements provide analytic examples to illustrate situations where kernel weighting provides a reduction in variance , and a simulation study is conducted to evaluate small sample performance of the proposed estimators .
Edit intent: meaning-changed
Original:  We give conditions under which such estimators are consistent, and describe their asymptotic mean squared error properties . Analytic examples illustrate the situations where re-weighting provides a reduction in variance , and a simulation study is conducted to evaluate small sample performance of the proposed estimators .
Revised:  We give conditions under which such estimators are consistent, and describe their asymptotic mean squared error properties . Analytic examples illustrate the situations where re-weighting provides a reduction in variance together with proofs of the results in the paper .
Edit intent: meaning-changed
Original:  The input to this problem is a set system (X, S ), where X is a set of elements and S is a collection of subsets of X, and an integer k <= \le |X|.
Revised:  The input to this problem is a set system (X, \mathcal{S ), where X is a set of elements and S is a collection of subsets of X, and an integer k <= \le |X|.
Edit intent: meaning-changed
Original:  The input to this problem is a set system (X, S ), where X is a set of elements and S is a collection of subsets of X, and an integer k <= \le |X|.
Revised:  The input to this problem is a set system (X, S ), where X is a set of elements and \mathcal{S is a collection of subsets of X, and an integer k <= \le |X|.
Edit intent: meaning-changed
Original:  The main result of this article is an LP rounding scheme which shows that the integrality gap of the Partial Set Cover LP is at most a constant times that of the Set Cover LP for the same class of geometric objects .
Revised:  The main result of this article is an LP rounding scheme which shows that the integrality gap of the Partial Set Cover LP is at most a constant times that of the Set Cover LP for a certain projection of the set system (X, \mathcal{S .
Edit intent: meaning-changed
Original:  We propose that the Laplace transform of quantum transport (QT) can be used to construct a powerful ensemble of maps from a given complex network to a circle S^1, such that closely-related nodes on the network are grouped into sharply concentrated clusters on S^1.
Revised:  We propose that the Laplace transform of quantum transport (QT) can be used to construct an ensemble of maps from a given complex network to a circle S^1, such that closely-related nodes on the network are grouped into sharply concentrated clusters on S^1.
Edit intent: clarity
Original:  The resulting QT clustering (QTC) algorithm is shown to outperform the state-of-the-art spectral clustering method on synthetic and real data sets containing complex geometric patterns  .
Revised:  The resulting QT clustering (QTC) algorithm is shown to outperform the state-of-the-art spectral clustering method on synthetic and real data sets containing complex geometric patterns and more robust when clusters show strong density variations or heterogeneity in size .
Edit intent: meaning-changed
Original:  The observed phenomenon of QTC can be interpreted as a collective behavior of the microscopic nodes that evolve as macroscopic cluster orbitals in an effective tight-binding model recapitulating the network. 
Revised:  The observed phenomenon of QTC can be interpreted as a collective behavior of the microscopic nodes that evolve as macroscopic cluster orbitals in an effective tight-binding model recapitulating the network. Python source code implementing the algorithm and examples are available at URL
Edit intent: meaning-changed
Original:  We work with a parsimonious parametrization of ordered binary choice regression that quite precisely forecasts future conditional probability distributions of returns , using past indicator and past volatility proxy as predictors.
Revised:  We work with a parsimonious parametrization of ordered binary choice regression that imposes a connection on sign predictability across different quantiles. The model forecasts the future conditional probability distributions of returns , using past indicator and past volatility proxy as predictors.
Edit intent: meaning-changed
Original: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June  2015 to January  2016  and from January  2016 to September  2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Revised: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June /01/ 2015 to January 2016 and from January 2016 to September 2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Edit intent: meaning-changed
Original: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June  2015 to January  2016  and from January  2016 to September  2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Revised: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June 2015 to January /26/ 2016 and from January 2016 to September 2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Edit intent: meaning-changed
Original: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June  2015 to January  2016  and from January  2016 to September  2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Revised: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June 2015 to January 2016 , in which Brazil was under the government of President Dilma Rousseff, and from January 2016 to September 2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Edit intent: meaning-changed
Original: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June  2015 to January  2016  and from January  2016 to September  2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Revised: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June 2015 to January 2016 and from January /27/ 2016 to September 2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Edit intent: meaning-changed
Original: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June  2015 to January  2016  and from January  2016 to September  2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Revised: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June 2015 to January 2016 and from January 2016 to September /08/ 2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Edit intent: meaning-changed
Original: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June  2015 to January  2016  and from January  2016 to September  2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Revised: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June 2015 to January 2016 and from January 2016 to September 2016 which includes the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Edit intent: clarity
Original: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June  2015 to January  2016  and from January  2016 to September  2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Revised: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June 2015 to January 2016 and from January 2016 to September 2016 , corresponding to the government transition from President Dilma Rousseff to President Michel Temer , respectively .
Edit intent: clarity
Original: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June  2015 to January  2016  and from January  2016 to September  2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer , respectively .
Revised: Mutual information minimum spanning trees are used to explore nonlinear dependencies on Brazilian equity network in the periods from June 2015 to January 2016 and from January 2016 to September 2016 , corresponding to the government transition from President Dilma Rousseff to the current President Michel Temer .
Edit intent: clarity
Original: Classical stochastic modelsof protein production usually do not consider several phenomena within the cell such as cell volume growth, cell division or gene replication , furthermore concentrations of RNA-polymerases and ribosomesare in general assumed to be constant.
Revised: In this article, we quantitatively study, through stochastic models, the efects of several intracellular phenomena, such as cell volume growth, cell division or gene replication , furthermore concentrations of RNA-polymerases and ribosomesare in general assumed to be constant.
Edit intent: clarity
Original: Classical stochastic modelsof protein production usually do not consider several phenomena within the cell such as cell volume growth, cell division or gene replication , furthermore concentrations of RNA-polymerases and ribosomesare in general assumed to be constant. In this paper we study the effects induced by all these different aspects on protein variability. Starting from the classical two-stage protein production model, we successively integrate the volume growth, the random partition of compounds at division, the gene replication and the sharing of RNA-polymerases and ribosomes for the production of all types of proteins. Experimental measures are used to determine the numerical values of the parameters of our models. We are then able to investigate the impact of these different phenomena on the variability of a large class of proteins  .
Revised: Classical stochastic modelsof protein production usually do not consider several phenomena within the cell such as cell volume growth, cell division , gene replication as well as fuctuations of available RNA polymerases and ribosomes. These phenomena are indeed rarely considered in classic models of protein production and no relative quantitative comparison among them has been performed. The parameters for a large and representative class of proteins .
Edit intent: coherence