wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We provide necessary and sufficient conditions on the assignment on portfolios to guarantee that, for all such evolutions in a  sufficiently volatile market, the actively traded portfolio outperforms the buy-and-hold portfolio in the long run.
Revised:  We provide necessary and sufficient conditions on the assignment on portfolios to guarantee that, for all such evolutions in a diverse and sufficiently volatile market, the actively traded portfolio outperforms the buy-and-hold portfolio in the long run.
Edit intent: clarity
Original:  The vector of proportions of the total market capitalization that belongs to each stock is called the market weights. Consider two portfolios, one is a passive buy-and-hold portfolio representing the entire market , and the other assigns a portfolio vector for each possible value of the market weights and requires trading to maintain this assignment.
Revised:  The vector of proportions of the total market capitalization that belongs to each stock is called the market weight. The market weight defines a buy-and-hold portfolio representing the entire market , and the other assigns a portfolio vector for each possible value of the market weights and requires trading to maintain this assignment.
Edit intent: clarity
Original:  Consider two portfolios, one is a passive buy-and-hold portfolio representing the entire market , and the other assigns a portfolio vector for each possible value of the market weights and requires trading to maintain this assignment.
Revised:  Consider two portfolios, one is a passive buy-and-hold portfolio called the market portfolio whose value represents the performance of the entire stock market. Consider a function that assigns a portfolio vector for each possible value of the market weights and requires trading to maintain this assignment.
Edit intent: meaning-changed
Original:  Consider two portfolios, one is a passive buy-and-hold portfolio representing the entire market , and the other assigns a portfolio vector for each possible value of the market weights and requires trading to maintain this assignment. The evolution of stocks is taken to be any jump process in discrete time, or a path of any continuous semimartingale in continuous time. We do not make any stochastic modeling assumptions on the evolutions. We provide necessary and sufficient conditions on the assignment on portfolios to guarantee that, for all such evolutions in a diverse and sufficiently volatile market, the actively traded portfolio outperforms the buy-and-hold portfolio in the long run .
Revised:  Consider two portfolios, one is a passive buy-and-hold portfolio representing the entire market , and the other assigns a portfolio vector for each possible value of the market weight. Suppose we perform self-financing trading using this portfolio function. We study the problem of characterizing functions such that the resulting portfolio will outperform the market portfolio in the long run .
Edit intent: clarity
Original:  We provide necessary and sufficient conditions on the assignment on portfolios to guarantee that, for all such evolutions in a diverse and sufficiently volatile market, the actively traded portfolio outperforms the buy-and-hold portfolio in the long run . This class of `relative arbitrage' portfolios were discovered by Fernholz and are called functionally generated portfolios.
Revised:  We provide necessary and sufficient conditions on the assignment on portfolios to guarantee that, for all such evolutions in a diverse and sufficiently volatile market, the actively traded portfolio outperforms the buy-and-hold portfolio in the long run under the conditions of diversity and sufficient volatility. No other assumption on the future behavior of stock prices is made.
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Original:  We prove that , in an appropriate sense , a slight generalization of these are the only possible ones. Remarkably, such portfolios correspond to solutions of Monge-Kantorovich optimal transport problems on the unit simplex with a cost function that can be described as log of the partition function. We also show how the presence of microstructure noise in stock price data leads to statistical arbitrage in high-frequency trading .
Revised:  We prove that the only solutions are functionally generated portfolios in the sense of Fernholz. A second characterization is given as the optimal maps of a remarkable optimal transport problem. Both these characterizations follow from a novel property of portfolios called multiplicative cyclical monotonicity. Using this framework we show how the presence of microstructure noise in stock price data leads to statistical arbitrage in high-frequency trading .
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Original:  The  quantile hedging method applied in \mbox{%DIFAUXCMD FL10pt%DIFAUXCMD and \mbox{%DIFAUXCMD FL2 }0pt%DIFAUXCMD } as well as the classical Neyman-Pearson lemma have been generalized.
Revised:  The well known quantile hedging method applied in \mbox{%DIFAUXCMD FL10pt%DIFAUXCMD and \mbox{%DIFAUXCMD FL2 }0pt%DIFAUXCMD } as well as the classical Neyman-Pearson lemma have been generalized.
Edit intent: clarity
Original:  The  quantile hedging method applied in \mbox{%DIFAUXCMD FL10pt%DIFAUXCMD and \mbox{%DIFAUXCMD FL2 }0pt%DIFAUXCMD } as well as the classical Neyman-Pearson lemma have been generalized.
Revised:  The quantile hedging method 0pt%DIFAUXCMD and \mbox{%DIFAUXCMD FL2 }0pt%DIFAUXCMD } as well as the classical Neyman-Pearson lemma have been generalized.
Edit intent: clarity
Original:  The  quantile hedging method applied in \mbox{%DIFAUXCMD FL10pt%DIFAUXCMD and \mbox{%DIFAUXCMD FL2 }0pt%DIFAUXCMD } as well as the classical Neyman-Pearson lemma have been generalized.
Revised:  The quantile hedging method applied in \mbox{%DIFAUXCMD FL10pt%DIFAUXCMD and \mbox{%DIFAUXCMD FL2 }0pt%DIFAUXCMD } as well as the classical Neyman-Pearson lemma are generalized.
Edit intent: clarity
Original:  We derive an analytic expression for the lag-time distribution, which agrees well with existing experimental results for the aggregation of bovine insulin into amyloid fibrils. Our solution provides a way to interpret small-volume experiments on fibril formation, providing insight into the mechanisms at play in early-stage aggregation  .
Revised:  We derive an analytic expression for the lag-time distribution, which agrees well with existing experimental results for the aggregation of bovine insulin . Our expression decomposes the lag time variability into contributions from primary nucleation and autocatalytic growth and reveals how each of these scales with the key kinetic parameters. Our analysis shows that significant lag-time variability can arise from both primary nucleation and from autocatalytic growth and should provide a way to interpret small-volume experiments on fibril formation, providing insight into the mechanisms at play in early-stage aggregation .
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Original:  This allows us to introduce the  concept of extensive and intensive bias, defined as a measurable tendency of the network to prefer either the formation of new links or the reinforcement of existing ones. We discuss the possible economic interpretation in terms of trade margins .
Revised:  This allows us to introduce the concept of extensive and intensive bias, defined as a measurable tendency of the network to prefer either the formation of new links or the reinforcement of link weights, with respect to a reference case where only strengths are enforced. Our findings complement the existing economic literature on (dynamic) intensive and extensive trade margins. More in general, they show that real-world multiplexes can be strongly shaped by layer-specific local constraints .
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Original:  In this paper we approach this challenge with mixed graphical Markov models and higher-order conditional independences . To unlock this methodological framework we derive the parameters for an exact likelihood ratio test and demonstrate its fundamental relevance for higher-order conditioning on continuous expression and discrete genotypes .
Revised:  In this paper we approach this challenge with mixed graphical Markov models and higher-order conditional independences and q-order correlation graphs .
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Original:  The estimation of the eQTL network underlying a well-studied yeast data set using our methodology leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes.
Revised:  Our estimation of the eQTL network underlying a well-studied yeast data set using our methodology leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes.
Edit intent: fluency
Original:  The estimation of the eQTL network underlying a well-studied yeast data set using our methodology leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes.
Revised:  The estimation of the eQTL network underlying a well-studied yeast data set leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes.
Edit intent: clarity
Original: We study the left tail behavior of the logarithm of the distribution function of a sum of dependent positive random variables . Asymptotics are computed under the assumption that the marginal distribution functions decay slowly at zero, meaning that the their logarithms are slowly varying functions.
Revised: We study the left tail behavior of the distribution function of a sum of dependent positive random variables . Asymptotics are computed under the assumption that the marginal distribution functions decay slowly at zero, meaning that the their logarithms are slowly varying functions.
Edit intent: fluency
Original: We study the left tail behavior of the logarithm of the distribution function of a sum of dependent positive random variables . Asymptotics are computed under the assumption that the marginal distribution functions decay slowly at zero, meaning that the their logarithms are slowly varying functions.
Revised: We study the left tail behavior of the logarithm of the distribution function of a sum of dependent positive random variables , with a special focus on the setting of asymptotic independence. Asymptotics at the logarithmic scale are computed under the assumption that the marginal distribution functions decay slowly at zero, meaning that the their logarithms are slowly varying functions.
Edit intent: meaning-changed
Original: We study the left tail behavior of the logarithm of the distribution function of a sum of dependent positive random variables . Asymptotics are computed under the assumption that the marginal distribution functions decay slowly at zero, meaning that the their logarithms are slowly varying functions.
Revised: We study the left tail behavior of the logarithm of the distribution function of a sum of dependent positive random variables . Asymptotics are computed under the assumption that the marginal distribution functions decay slowly at zero, meaning that their logarithms are slowly varying functions.
Edit intent: fluency
Original:  We show that the logarithmic asymptotics of the sum in question depend on a characteristic of the copula of the random variables which we term weak lower tail dependence function , and which is computed explicitly for several families of copulas in this paper.
Revised:  We show that the asymptotics of the sum in question depend on a characteristic of the copula of the random variables which we term weak lower tail dependence function , and which is computed explicitly for several families of copulas in this paper.
Edit intent: clarity
Original:  We show that the logarithmic asymptotics of the sum in question depend on a characteristic of the copula of the random variables which we term weak lower tail dependence function , and which is computed explicitly for several families of copulas in this paper.
Revised:  We show that the logarithmic asymptotics of the sum depend on a characteristic of the copula of the random variables which we term weak lower tail dependence function , and which is computed explicitly for several families of copulas in this paper.
Edit intent: clarity
Original:  We show that the logarithmic asymptotics of the sum in question depend on a characteristic of the copula of the random variables which we term weak lower tail dependence function , and which is computed explicitly for several families of copulas in this paper.
Revised:  We show that the logarithmic asymptotics of the sum in question depend on a characteristic of the copula of the random variables which we term weak lower tail dependence function . We then compute this function explicitly for several families of copulas in this paper.
Edit intent: coherence
Original:  We show that the logarithmic asymptotics of the sum in question depend on a characteristic of the copula of the random variables which we term weak lower tail dependence function , and which is computed explicitly for several families of copulas in this paper. In applications, our results may be used to quantify the diversification of long-only portfolios of financial assets with respect to extreme losses .
Revised:  We show that the logarithmic asymptotics of the sum in question depend on a characteristic of the copula of the random variables which we term weak lower tail dependence function , and which is computed explicitly for several families of copulas , such as the Gaussian copula, the copulas of Gaussian mean-variance mixtures and a class of Archimedean copulas .
Edit intent: meaning-changed
Original: We study the left tail behavior of the distribution function of a sum of dependent positive random variables, with a special focus on the setting of asymptotic independence. Asymptotics at the logarithmic scale are computed under the assumption that the marginal distribution functions decay slowly at zero, meaning that their logarithms are slowly varying functions. This includes parametric families such as log-normal, gamma, Weibull and many distributions from the financial mathematics literature. We show that the asymptotics of the sum depend on a characteristic of the copula of the random variables which we term weak lower tail dependence function.
Revised: We introduce a new functional measure of tail dependence for weakly dependent (asymptotically independent) random vectors, termed weak tail dependence function.
Edit intent: meaning-changed
Original:  We then compute this function explicitly for several families of copulas, such as the Gaussian copula, the copulas of Gaussian mean-variance mixtures and a class of Archimedean copulas.
Revised:  The new measure is defined at the level of copulas and we compute it for several copula families such as the Gaussian copula, the copulas of Gaussian mean-variance mixtures and a class of Archimedean copulas.
Edit intent: clarity
Original:  We then compute this function explicitly for several families of copulas, such as the Gaussian copula, the copulas of Gaussian mean-variance mixtures and a class of Archimedean copulas. As an illustration, we compute the left tail asymptotics for a portfolio of call options in the multidimensional Black-Scholes model .
Revised:  We then compute this function explicitly for several families of copulas, such as the Gaussian copula, the copulas of Gaussian mean-variance mixtures and a class of Gaussian mixture models, certain Archimedean copulas and extreme value copulas. The new measure allows to quantify the tail behavior of certain functionals of weakly dependent random vectors at the log scale .
Edit intent: meaning-changed
Original:  Remarkably, our criterion for the onset of contagion turns out to be isomorphic to a simple rule for the evolution of cooperation on graphs and social networks, supporting recent calls for a methodological rapprochement between finance and ecology.
Revised:  Our criterion for the onset of contagion turns out to be isomorphic to a simple rule for the evolution of cooperation on graphs and social networks, supporting recent calls for a methodological rapprochement between finance and ecology.
Edit intent: coherence
Original:  Remarkably, our criterion for the onset of contagion turns out to be isomorphic to a simple rule for the evolution of cooperation on graphs and social networks, supporting recent calls for a methodological rapprochement between finance and ecology.
Revised:  Remarkably, our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, supporting recent calls for a methodological rapprochement between finance and ecology.
Edit intent: clarity
Original:  Remarkably, our criterion for the onset of contagion turns out to be isomorphic to a simple rule for the evolution of cooperation on graphs and social networks, supporting recent calls for a methodological rapprochement between finance and ecology.
Revised:  Remarkably, our criterion for the onset of contagion turns out to be isomorphic to a simple rule for the evolution of cooperation on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology.
Edit intent: meaning-changed
Original: Motivation In many key applications in the field of metabolomics, such as toxicology or nutrigenomics, it is of interest to profile and detect physiological changes in metabolic pathways .
Revised: Motivation In many key applications in the field of metabolomics, such as toxicology or nutrigenomics, it is of interest to profile and detect physiological changes in metabolic processes, usually represented in the form of pathways. As an alternative, a broader point of view would enable investigators to better understand the relations between entities that exist in different processes. Therefore, relating a possible perturbation to several known processes represents a new approach to this field of study. We propose to use a network representation of metabolism in terms of reactants, enzyme and metabolite .
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Original:  This library provides easy access to the Kyoto Encyclopedia for Genes and Genomes (KEGG) database using its RESTful Application Programming Interfaces (APIs), and methods to enhance manipulation of the information returned from KEGG webservice.
Revised:  This library uses data stored in Kyoto Encyclopedia for Genes and Genomes (KEGG) database using its RESTful Application Programming Interfaces (APIs), and methods to enhance manipulation of the information returned from KEGG webservice.
Edit intent: clarity
Original:  MetaboX includes methods to extract information about a resource of interest (e.g. metabolite, reaction and enzyme) for further processing and storing purposes. MetaboX is modular, thus developers can contribute with alternative implementations or extensions. Each component of the library is designed with minimum dependency on other components. Supplementary information available in Table 1. Availability The MetaboX library is available under the AGPL license on gitHub repository URL
Revised:  MetaboX includes methods to extract information about a resource of interest (e.g. metabolite, reaction and enzyme) and to build reactants networks, bipartite enzyme-metabolite and unipartite enzyme networks. These networks can be exported in different formats for data visualization with standard tools. As a case study, the networks built from a subset of the Glycolysis pathway are described and discussed. Conclusions: The advantages of using such a library imply the ability to model complex systems with few starting information represented by a collection of metabolites KEGG IDs.
Edit intent: meaning-changed
Original: Although the phrase "ontogeny recapitulates phylogeny'' turned out to be incorrect, the search for possible relationships between development and evolution still gathers much attention. Recently, dynamical-systems analysis has proven to be relevant to both development and evolution, and it may therefore provide a link between the two. Using extensive simulations to evolve gene regulation networks that shape morphogenesis, we observed remarkable congruence between development and evolution: Both consisted of the same successive epochs to shape stripes, and good agreement was observed for the ordering as well as the topology of branching of stripes between the two. This congruence is explained by the agreement of bifurcations in dynamical-systems theory between evolution and development, where slowly varying gene-expression levels work as emergent control parameters.
Revised: Although the phrase "ontogeny recapitulates phylogeny'' turned out to be incorrect, the search for possible relationships between phylogeny and ontogeny is one of the most important issues in the field of evolutionary developmental biology. By representing developmental dynamics of spatially located cells with gene expression dynamics with cell-to-cell interaction under external morphogen gradient, evolved are gene regulation networks under mutation and selection with the fitness to approach a prescribed spatial pattern of expressed genes. For most of thousands of numerical evolution experiments, evolution of pattern over generations and development of pattern by an evolved network exhibit remarkable congruence. Here, both the pattern dynamics consist of several epochs to form successive stripe formations between quasi-stationary regimes. In evolution, the regimes are generations needed to hit relevant mutations, while in development, they are due to the emergence of slowly varying expression that controls the pattern change. Successive pattern changes are thus generated, which are regulated by successive combinations of feedback or feedforward regulations under the agreement of bifurcations in dynamical-systems theory between evolution and development, where slowly varying gene-expression levels work as emergent control parameters.
Edit intent: meaning-changed
Original:  This congruence is explained by the agreement of bifurcations in dynamical-systems theory between evolution and development, where slowly varying gene-expression levels work as emergent control parameters. In terms of the gene regulation networks, this congruence is understood as the successive addition of downstream modules, either as feedforward or feedback , while the upstream feedforward network shapes the boundary condition for the downstream dynamics, based on the maternal morphogen gradient.
Revised:  This congruence is explained by the upstream feedforward network shapes the boundary condition for the downstream dynamics, based on the maternal morphogen gradient.
Edit intent: clarity
Original:  In terms of the gene regulation networks, this congruence is understood as the successive addition of downstream modules, either as feedforward or feedback , while the upstream feedforward network shapes the boundary condition for the downstream dynamics, based on the maternal morphogen gradient. Acquisition of a novel developmental mode was due to mutational change in the upstream network to alter the boundary condition .
Revised:  In terms of the gene regulation networks, this congruence is understood as the successive addition of downstream modules, either as feedforward or feedback , while the upstream feedforward network that reads the morphogen gradient. By using a pattern generated by the upstream feedforward network as a boundary condition, downstream networks form later stripe patterns. These epochal changes in development and evolution are represented as same bifurcations in dynamical-systems theory, and this agreement of bifurcations lead to the evolution-development congruences. Violation of the upstream network to alter the boundary condition .
Edit intent: clarity