wanyu/IteraTeR_full_sent huggingface dataset:
Original:  In particular, we identify a geometric "egalitarianism" condition on the social network graph that guarantees learning in infinite networks, or learning with high probability in large finite networks, in any equilibrium of the game.
Revised:  In particular, we identify a geometric "egalitarianism" condition on the social network that guarantees learning in infinite networks, or learning with high probability in large finite networks, in any equilibrium of the game.
Edit intent: clarity
Original:  In particular, we identify a geometric "egalitarianism" condition on the social network graph that guarantees learning in infinite networks, or learning with high probability in large finite networks, in any equilibrium of the game. We give examples of non-egalitarian networks with equilibria in which learning fails.
Revised:  In particular, we identify a geometric "egalitarianism" condition on the social network graph that guarantees learning in infinite networks, or learning with high probability in large finite networks, in any equilibrium . We also give examples of non-egalitarian networks with equilibria in which learning fails.
Edit intent: clarity
Original:   Since the minimal martingale measure fails to produce a probability measure in this setting, we construct local risk minimization hedging strategies with respect to a risk neutral measure.
Revised:  More specifically, we implement local risk minimization and a minimum variance hedge approximation based on an extended Girsanov principle that generalizes Duan's (1995) delta hedge. Since the minimal martingale measure fails to produce a probability measure in this setting, we construct local risk minimization hedging strategies with respect to a risk neutral measure.
Edit intent: meaning-changed
Original:   Since the minimal martingale measure fails to produce a probability measure in this setting, we construct local risk minimization hedging strategies with respect to a risk neutral measure. Local risk minimization is investigated in the context of Gaussian driven models, and two other minimum variance hedges are proposed in order to extend Duan's delta hedge.
Revised:  Since the minimal martingale measure fails to produce a probability measure in this setting, we construct local risk minimization hedging strategies with respect to a pricing kernel. These approaches are investigated in the context of Gaussian driven models, and two other minimum variance hedges are proposed in order to extend Duan's delta hedge.
Edit intent: clarity
Original:  Local risk minimization is investigated in the context of Gaussian driven models, and two other minimum variance hedges are proposed in order to extend Duan's delta hedge. These two methods are constructed using local risk minimizing hedges for bivariate diffusion limits of GARCH models. Numerical experiments are carried out in order to compare the different hedging schemes; in particular,  the sensitivity of the hedging strategies with respect to several pricing measures is tested for a special class of non-Gaussian GARCH models for European style options with different moneyness and maturities .
Revised:  Local risk minimization is investigated in the context of non-Gaussian driven models. Furthermore, we analyze these methods for non-Gaussian GARCH diffusion limit processes and link them to the corresponding discrete time counterparts. A detailed numerical analysis based on S the sensitivity of the hedging strategies with respect to several pricing measures is tested for a special class of non-Gaussian GARCH models for European style options with different moneyness and maturities .
Edit intent: clarity
Original:  in particular,  the sensitivity of the hedging strategies with respect to several pricing measures is tested for a special class of non-Gaussian GARCH models for European style options with different moneyness and maturities .
Revised:  in particular, P 500 European Call options is provided to assess the empirical performance of the proposed schemes. We also test the sensitivity of the hedging strategies with respect to several pricing measures is tested for a special class of non-Gaussian GARCH models for European style options with different moneyness and maturities .
Edit intent: meaning-changed
Original:  We further show, that it is smaller than 4/3 as conjectured in literature. This shows a large number of functions appearing in biological networks belong to a class that has a very low average sensitivity, which is even close to a tight lower bound.
Revised:  We further show, that it is smaller than 4/3 This shows that a large number of functions appearing in biological networks belong to a class that has a very low average sensitivity, which is even close to a tight lower bound.
Edit intent: coherence
Original:  The problems involve optimisation of a functional  in which the control features quadratically , while in the state dynamics it appears as a drift perturbation to Brownian paths on Wiener space.
Revised:  The problems involve optimisation of a functional of Brownian paths on Wiener space, with the paths perturbed by a drift involving the control. In addition there is a penalty term in which the control features quadratically , while in the state dynamics it appears as a drift perturbation to Brownian paths on Wiener space.
Edit intent: meaning-changed
Original:  The problems involve optimisation of a functional  in which the control features quadratically , while in the state dynamics it appears as a drift perturbation to Brownian paths on Wiener space. This drift is interpreted as a measure change using the Girsanov theorem, leading to a form of the integration by parts formula in which a directional derivative on Wiener space is computed.
Revised:  The problems involve optimisation of a functional in which the control features quadratically . The drift perturbation is interpreted as a measure change using the Girsanov theorem, leading to a form of the integration by parts formula in which a directional derivative on Wiener space is computed.
Edit intent: clarity
Original:  Instead of relying on an externally URLanization for biological functions, our method connects biological functions together if they are performed by the same genes, as indicated in a compendium of gene annotation data from numerous different biological experiments. Grouping terms by this alternate scheme  provides a new framework with which to describe and predict the functions of experimentally identified sets of genes.
Revised:  Instead of relying on an externally URLanization for biological functions, our method connects biological functions together if they are performed by the same genes, as indicated in a compendium of gene annotation data from numerous different experiments. We show that grouping terms by this alternate scheme provides a new framework with which to describe and predict the functions of experimentally identified sets of genes.
Edit intent: coherence
Original:  We summarize the current knowledge and the state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets . We show how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates.
Revised:  We summarize the current knowledge and the state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The central hit strategy selectively targets central node/edges of the flexible networks of infectious agents or cancer cells to kill them. The network influence strategy works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates.
Edit intent: meaning-changed
Original: From the shape and size analysis of approximately 130 small icosahedral viruses we conclude that there is a typical structural capsid protein, having a mean diameter of 5 nm and a mean thickness of 3 nm, with more than two thirds of the analyzed capsid proteins having thicknesses between 2 nm and 4 nm.
Revised: From the analysis of sizes of approximately 130 small icosahedral viruses we conclude that there is a typical structural capsid protein, having a mean diameter of 5 nm and a mean thickness of 3 nm, with more than two thirds of the analyzed capsid proteins having thicknesses between 2 nm and 4 nm.
Edit intent: clarity
Original: From the shape and size analysis of approximately 130 small icosahedral viruses we conclude that there is a typical structural capsid protein, having a mean diameter of 5 nm and a mean thickness of 3 nm, with more than two thirds of the analyzed capsid proteins having thicknesses between 2 nm and 4 nm.
Revised: From the shape and size analysis of approximately 130 small icosahedral viruses we find that there is a typical structural capsid protein, having a mean diameter of 5 nm and a mean thickness of 3 nm, with more than two thirds of the analyzed capsid proteins having thicknesses between 2 nm and 4 nm.
Edit intent: clarity
Original:  Using such a procedure we performed statistical analysis of a series of virus shapes and we found strong similarities between the capsid elastic properties of even very different viruses. Our findings point to either evolutionary relatedness of most viruses or to evolutionary convergence of the examined properties of viruses.
Revised:  Using such a procedure we performed statistical analysis of a series of virus shapes and we found strong similarities between the capsid elastic properties of even very different viruses.
Edit intent: clarity
Original:  Using self-financed strategy and duplication we are able to derive a Random Partial Differential Equation (RPDE) that any claim whose value depends on firm value and time should satisfy. We solve the RPDE for debt and loan guarantees under the assumption that there are no coupon payment nor dividends prior to the maturity of the debt.
Revised:  Using self-financed strategy and duplication we are able to derive a Random Partial Differential Equation (RPDE) that any claim whose value depends on firm value and time . Under specific final and boundary conditions, we solve the RPDE for debt and loan guarantees under the assumption that there are no coupon payment nor dividends prior to the maturity of the debt.
Edit intent: meaning-changed
Original:  Making use of empirical growth-rate dependences of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the amount and quality of the food it is fed.
Revised:  Making use of empirical growth-rate dependences of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the nutrients it is fed.
Edit intent: clarity
Original:  It should be also mentioned that D. Filiporvi\'{c --convex modules in D. Filipovi\'{c, M. Kupper, N. Vogelpoth, Separation and duality in locally L^0--convex modules, J. Funct.
Revised:  Then, we make use of the advantage of the (\varepsilon,\lambda)--topology and grasp the local property of L^0 --convex modules in D. Filipovi\'{c, M. Kupper, N. Vogelpoth, Separation and duality in locally L^0--convex modules, J. Funct.
Edit intent: meaning-changed
Original:  Filiporvi\'{c --convex modules in D. Filipovi\'{c, M. Kupper, N. Vogelpoth, Separation and duality in locally L^0--convex modules, J. Funct.
Revised:  Filiporvi\'{c --convex D. Filipovi\'{c, M. Kupper, N. Vogelpoth, Separation and duality in locally L^0--convex modules, J. Funct.
Edit intent: fluency
Original:  Filiporvi\'{c --convex modules in D. Filipovi\'{c, M. Kupper, N. Vogelpoth, Separation and duality in locally L^0--convex modules, J. Funct.
Revised:  Filiporvi\'{c --convex modules in , M. Kupper, N. Vogelpoth, Separation and duality in locally L^0--convex modules, J. Funct.
Edit intent: clarity
Original:  Anal. 256 (2009) 3996-4029}%DIFDELCMD < ] %%% (briefly,the FKV paper), where they made some important contributions to the subject and presented some good ideas of financial applications. Unfortunately, there are serious shortcomings in the FKV paper. First, most of the principal results in the FKV paper were based on the premise that the locally L ^{0}--convex topology for every locally L ^{0--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex module may be induced by a family of L^{0 the FKV paper ever gave a proof of this premise, but there was a hole in this proof, in fact, it remains open up to now whether the premise is valid or not.
Revised:  Anal. 256 (2009) 3996-4029}%DIFDELCMD < ] %%% conditional risk measures to prove that every L ^{0}--convex topology for every locally L ^{0--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex module may be induced by a family of L^{0 the FKV paper ever gave a proof of this premise, but there was a hole in this proof, in fact, it remains open up to now whether the premise is valid or not.
Edit intent: coherence
Original:  First, most of the principal results in the FKV paper were based on the premise that the locally L ^{0}--convex topology for every locally L ^{0--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex module may be induced by a family of L^{0 the FKV paper ever gave a proof of this premise, but there was a hole in this proof, in fact, it remains open up to now whether the premise is valid or not.
Revised:  First, most of the principal results in the FKV paper were based on the premise that the locally L ^{0}--convex L ^{0--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex module may be induced by a family of L^{0 the FKV paper ever gave a proof of this premise, but there was a hole in this proof, in fact, it remains open up to now whether the premise is valid or not.
Edit intent: clarity
Original:  First, most of the principal results in the FKV paper were based on the premise that the locally L ^{0}--convex topology for every locally L ^{0--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex module may be induced by a family of L^{0 the FKV paper ever gave a proof of this premise, but there was a hole in this proof, in fact, it remains open up to now whether the premise is valid or not.
Revised:  First, most of the principal results in the FKV paper were based on the premise that the locally L ^{0}--convex topology for every locally L ^{p--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex module may be induced by a family of L^{0 the FKV paper ever gave a proof of this premise, but there was a hole in this proof, in fact, it remains open up to now whether the premise is valid or not.
Edit intent: fluency
Original:  First, most of the principal results in the FKV paper were based on the premise that the locally L ^{0}--convex topology for every locally L ^{0--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex module may be induced by a family of L^{0 the FKV paper ever gave a proof of this premise, but there was a hole in this proof, in fact, it remains open up to now whether the premise is valid or not.
Revised:  First, most of the principal results in the FKV paper were based on the premise that the locally L ^{0}--convex topology for every locally L ^{0--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex L^{p the FKV paper ever gave a proof of this premise, but there was a hole in this proof, in fact, it remains open up to now whether the premise is valid or not.
Edit intent: meaning-changed
Original:  First, most of the principal results in the FKV paper were based on the premise that the locally L ^{0}--convex topology for every locally L ^{0--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex module may be induced by a family of L^{0 the FKV paper ever gave a proof of this premise, but there was a hole in this proof, in fact, it remains open up to now whether the premise is valid or not. In this paper we overcome the difficulty by working with random locally convex modules endowed with the locally L^0 --convex topology rather than locally L^0--convex modules.
Revised:  First, most of the principal results in the FKV paper were based on the premise that the locally L ^{0}--convex topology for every locally L ^{0--conditional risk measure (1\leq p\leq+\infty) can be uniquely extended to an L^{0}} --convex module may be induced by a family of L^{0 the process we find that combining the countable concatenation hull of a set and the local property of conditional risk measures is a very useful analytic skill that may considerably simplify and improve the study of L^{0 --convex topology rather than locally L^0--convex modules.
Edit intent: meaning-changed
Original:  In this paper we overcome the difficulty by working with random locally convex modules endowed with the locally L^0 --convex topology rather than locally L^0--convex modules. Besides, some basic and key results in the FKV paper are also false so that some more interesting and essential things are covered, so we first correct these mistakes and further give a thorough treatment of random convex analysis .
Revised:  In this paper we overcome the difficulty by working with random locally convex modules endowed with the locally L^0 --convex conditional risk measures .
Edit intent: meaning-changed
Original:  Here we propose to overcome these two issues by employing a novel similarity function, DTWMIC , combining a measure taking care of functional interactions of signals (MIC) and a measure identifying horizontal displacements (DTW).
Revised:  Here we propose to overcome these two issues by employing a novel similarity function, Dynamic Time Warping Maximal Information Coefficient (DTW-MIC) , combining a measure taking care of functional interactions of signals (MIC) and a measure identifying horizontal displacements (DTW).
Edit intent: meaning-changed
Original: MicroRNAs (miRNAs) are small RNA molecules composed of 19-22 nt playing important regulatory roles in post-transcriptional gene regulation by inhibiting the translation of the mRNA into proteins or otherwise cleaving the target mRNA. Inferring miRNA targets provides useful information for understanding the roles of miRNA involving in biological processes which may result in diagnosing complex diseases.
Revised: MicroRNAs (miRNAs) are small RNA molecules composed of 19-22 nt , which play important regulatory roles in post-transcriptional gene regulation by inhibiting the translation of the mRNA into proteins or otherwise cleaving the target mRNA. Inferring miRNA targets provides useful information for understanding the roles of miRNA involving in biological processes which may result in diagnosing complex diseases.
Edit intent: clarity
Original: MicroRNAs (miRNAs) are small RNA molecules composed of 19-22 nt playing important regulatory roles in post-transcriptional gene regulation by inhibiting the translation of the mRNA into proteins or otherwise cleaving the target mRNA. Inferring miRNA targets provides useful information for understanding the roles of miRNA involving in biological processes which may result in diagnosing complex diseases.
Revised: MicroRNAs (miRNAs) are small RNA molecules composed of 19-22 nt playing important regulatory roles in post-transcriptional gene regulation by inhibiting the translation of the mRNA into proteins or otherwise cleaving the target mRNA. Inferring miRNA targets provides useful information for understanding the roles of miRNA in biological processes which may result in diagnosing complex diseases.
Edit intent: clarity
Original: MicroRNAs (miRNAs) are small RNA molecules composed of 19-22 nt playing important regulatory roles in post-transcriptional gene regulation by inhibiting the translation of the mRNA into proteins or otherwise cleaving the target mRNA. Inferring miRNA targets provides useful information for understanding the roles of miRNA involving in biological processes which may result in diagnosing complex diseases.
Revised: MicroRNAs (miRNAs) are small RNA molecules composed of 19-22 nt playing important regulatory roles in post-transcriptional gene regulation by inhibiting the translation of the mRNA into proteins or otherwise cleaving the target mRNA. Inferring miRNA targets provides useful information for understanding the roles of miRNA involving in biological processes that are potentially involved in complex diseases.
Edit intent: clarity
Original:   For comparison purposes, we applied the Least Square Regression (LSR), Ridge Regression (RR), LASSO, non-negative LASSO (nLASSO), and the Bayesian approaches to four public data sets which have the known interaction pairs of miRNA and mRNA. Comparing to the point estimate algorithms,  the Bayesian methods are able to infer more known interactions and are more meaningful to provide credible intervals to take into account the uncertainty of the interactions of miRNA and mRNA.
Revised:  These approaches can be used to observe the inferred effects of the miRNAs on the targets by plotting the posterior distributions of those parameters. For comparison purposes, we applied the Least Square Regression (LSR), Ridge Regression (RR), LASSO, non-negative LASSO (nLASSO), and the Bayesian approaches to four public data sets which have the known interaction pairs of miRNA and mRNA. Comparing to the point estimate algorithms, the Bayesian methods are able to infer more known interactions and are more meaningful to provide credible intervals to take into account the uncertainty of the interactions of miRNA and mRNA.
Edit intent: meaning-changed
Original:   For comparison purposes, we applied the Least Square Regression (LSR), Ridge Regression (RR), LASSO, non-negative LASSO (nLASSO), and the Bayesian approaches to four public data sets which have the known interaction pairs of miRNA and mRNA. Comparing to the point estimate algorithms,  the Bayesian methods are able to infer more known interactions and are more meaningful to provide credible intervals to take into account the uncertainty of the interactions of miRNA and mRNA.
Revised:  For comparison purposes, the Least Squares Regression (LSR), Ridge Regression (RR), LASSO, non-negative LASSO (nLASSO), and the Bayesian approaches to four public data sets which have the known interaction pairs of miRNA and mRNA. Comparing to the point estimate algorithms, the Bayesian methods are able to infer more known interactions and are more meaningful to provide credible intervals to take into account the uncertainty of the interactions of miRNA and mRNA.
Edit intent: coherence
Original:   For comparison purposes, we applied the Least Square Regression (LSR), Ridge Regression (RR), LASSO, non-negative LASSO (nLASSO), and the Bayesian approaches to four public data sets which have the known interaction pairs of miRNA and mRNA. Comparing to the point estimate algorithms,  the Bayesian methods are able to infer more known interactions and are more meaningful to provide credible intervals to take into account the uncertainty of the interactions of miRNA and mRNA.
Revised:  For comparison purposes, we applied the Least Square Regression (LSR), Ridge Regression (RR), LASSO, non-negative LASSO (nLASSO), and the proposed Bayesian approaches were applied to four public data sets which have the known interaction pairs of miRNA and mRNA. Comparing to the point estimate algorithms, the Bayesian methods are able to infer more known interactions and are more meaningful to provide credible intervals to take into account the uncertainty of the interactions of miRNA and mRNA.
Edit intent: clarity