wanyu/IteraTeR_v2 huggingface dataset:
Original:  The end products can be classified as proof of concept work, private tools and public tools according to their accessibility and state of readiness for scientific work . Based on our findings  we suggest ways in which the current practice of software development in computational neuroscience can be improved along with checklists for developers, reviewers , and scientists to help assess the quality and research readiness of a particular piece of software .
Revised:  The end products can be classified as proof of concept work, private tools and public tools according to their accessibility and state of readiness for scientific work . Based on our findings we suggest ways in which the current practice of software development in computational neuroscience can be improved along with checklists for developers, reviewers , and scientists to help assess the quality whether particular pieces of software are ready for use in research .
Edit intent: clarity
Original:  We use a semi-annealed approach to study the stability of this class of models when coupled in a multiplex network and show that the analytical results are in good agreement with numerical simulations .
Revised:  We use a semi-annealed approximation to study the stability of this class of models when coupled in a multiplex network and show that the analytical results are in good agreement with numerical simulations .
Edit intent: clarity
Original:  We use a semi-annealed approach to study the stability of this class of models when coupled in a multiplex network and show that the analytical results are in good agreement with numerical simulations .
Revised:  We use a semi-annealed approach to study the stability properties of Random Boolean Networks in multiplex (multi-layered) graphs .
Edit intent: clarity
Original:  Our main finding is that the multiplex structure provides a mechanism for the stabilization of the system and of chaotic regimes of individual layers .
Revised:  Our main finding is that the multilevel structure provides a mechanism for the stabilization of the system and of chaotic regimes of individual layers .
Edit intent: clarity
Original:  Empirical research in both human and nonhuman animals reveals that many times foraging choices are context dependent and affected by the foraging choices of others.
Revised:  Empirical research in both human and nonhuman animals reveals that individuals often attend to the foraging choices of others.
Edit intent: clarity
Original:  Here, we analyze foraging choices by a cohort of professional day traders who face the trade-off of trading the same stock multiple times in a row---patch exploitation---or switching to a different stock---patch exploration---with potentially higher returns.
Revised:  Here, we analyze foraging choices of a cohort of professional day traders who face the trade-off of trading the same stock multiple times in a row---patch exploitation---or switching to a different stock---patch exploration---with potentially higher returns.
Edit intent: fluency
Original:  Here, we analyze foraging choices by a cohort of professional day traders who face the trade-off of trading the same stock multiple times in a row---patch exploitation---or switching to a different stock---patch exploration---with potentially higher returns.
Revised:  Here, we analyze foraging choices by a cohort of professional day traders who must choose between trading the same stock multiple times in a row---patch exploitation---or switching to a different stock---patch exploration---with potentially higher returns.
Edit intent: clarity
Original:  Our findings indicate that traders' foraging patterns are characterized by short-term comparative returns that decrease in proportion to patch exploitation and exploration, a novel measure that captures the difference between a trader's resource intake and the competitors' expected intake within a short period of time.
Revised:  We measure the difference between a trader's resource intake and the competitors' expected intake within a short period of time.
Edit intent: clarity
Original:  ABC is a rejection-based method that applies a tolerance of dissimilarity between sets of summary statistics from observed and simulated data.
Revised:  ABC is a rejection-based method that applies a tolerance of dissimilarity between summary statistics from observed and simulated data.
Edit intent: clarity
Original:  ABC gives an exact sampler from the posterior density  in the limit of  zero tolerance.
Revised:  Although several improvements of the algorithm have been proposed, no algorithms are free from approximation introduced by two aspects: 1) the dimensional reduction: sampling is not from the true posterior density given data but from an approximate posterior density given summary statistics; 2) the non-zero tolerance: sampling from the posterior density in the limit of zero tolerance.
Edit intent: coherence
Original:  ABC gives an exact sampler from the posterior density  in the limit of  zero tolerance.
Revised:  ABC gives an exact sampler from the posterior density in the limit of the zero tolerance.
Edit intent: fluency
Original:  However, the choices for summary statistics and metrics of dissimilarity are ambiguous, and acceptance rates decrease with an increasing number of summary statistics .
Revised:  For the first aspect, we can improve the approximation by adding summary statistic, but the increase of the number of summary statistics .
Edit intent: coherence
Original:  We report that kernel ABC (i) avoids the need for tolerance, (ii) upholds the consistency of estimators, and (iii) is tractable for a large number of summary statistics .
Revised:  We report that , in contrast to conventional ABCs, kernel-ABC can incorporate large number of summary statistics .
Edit intent: clarity
Original: Approximate Bayesian Computation (ABC) , which is a likelihood-free approach for Bayesian inferences , is a rejection-based method that applies a tolerance of dissimilarity between summary statistics from observed and simulated data.
Revised: Approximate Bayesian computation (ABC) , which is a likelihood-free approach for Bayesian inferences , is a rejection-based method that applies a tolerance of dissimilarity between summary statistics from observed and simulated data.
Edit intent: fluency
Original: Approximate Bayesian Computation (ABC) , which is a likelihood-free approach for Bayesian inferences , is a rejection-based method that applies a tolerance of dissimilarity between summary statistics from observed and simulated data.
Revised: Approximate Bayesian Computation (ABC) is a likelihood-free approach for Bayesian inferences , is a rejection-based method that applies a tolerance of dissimilarity between summary statistics from observed and simulated data.
Edit intent: coherence
Original: Approximate Bayesian Computation (ABC) , which is a likelihood-free approach for Bayesian inferences , is a rejection-based method that applies a tolerance of dissimilarity between summary statistics from observed and simulated data.
Revised: Approximate Bayesian Computation (ABC) , which is a likelihood-free approach for Bayesian inferences based on a rejection algorithm method that applies a tolerance of dissimilarity between summary statistics from observed and simulated data.
Edit intent: clarity
Original:  Although several improvements of the algorithm have been proposed, no algorithms are free from approximation introduced by two aspects : 1) the dimensional reduction : sampling is not from the true posterior density given data but from an approximate posterior density given summary statistics;
Revised:  Although several improvements to the algorithm have been proposed, no algorithms are free from approximation introduced by two aspects : 1) the dimensional reduction : sampling is not from the true posterior density given data but from an approximate posterior density given summary statistics;
Edit intent: clarity
Original:  Although several improvements of the algorithm have been proposed, no algorithms are free from approximation introduced by two aspects : 1) the dimensional reduction : sampling is not from the true posterior density given data but from an approximate posterior density given summary statistics;
Revised:  Although several improvements of the algorithm have been proposed, none of these improvements avoid the following two sources of approximation : 1) the dimensional reduction : sampling is not from the true posterior density given data but from an approximate posterior density given summary statistics;
Edit intent: clarity
Original:   2) the non-zero tolerance: sampling from the posterior density given summary statistics is achieved only in the limit of the zero tolerance.
Revised:  and 2) the non-zero tolerance: sampling from the posterior density given summary statistics is achieved only in the limit of the zero tolerance.
Edit intent: fluency
Original:   2) the non-zero tolerance: sampling from the posterior density given summary statistics is achieved only in the limit of the zero tolerance.
Revised:  2) non-zero tolerance: sampling from the posterior density given summary statistics is achieved only in the limit of the zero tolerance.
Edit intent: coherence
Original:   2) the non-zero tolerance: sampling from the posterior density given summary statistics is achieved only in the limit of the zero tolerance.
Revised:  2) the non-zero tolerance: sampling from the posterior density given summary statistics is achieved only in the limit of zero tolerance.
Edit intent: coherence
Original:  For the first aspect, we can improve the approximation by adding summary statistic, but the increase of the number of summary statistics could introduce additional variance caused by the low acceptance rate.
Revised:  The first source of approximation can be improved by adding a summary statistic, but the increase of the number of summary statistics could introduce additional variance caused by the low acceptance rate.
Edit intent: clarity
Original:  For the first aspect, we can improve the approximation by adding summary statistic, but the increase of the number of summary statistics could introduce additional variance caused by the low acceptance rate.
Revised:  For the first aspect, we can improve the approximation by adding summary statistic, but an increase in the number of summary statistics could introduce additional variance caused by the low acceptance rate.
Edit intent: clarity
Original:  Consequently, many authors have been concentrated on techniques how to choose informative summary statistics.
Revised:  Consequently, many researchers have attempted to develop techniques to choose informative summary statistics.
Edit intent: clarity
Original:  The aim of this study is to investigate whether a new kernel-based ABC method proposed by Fukumizu et al. ( 2010, arXiv:1009.5736 and 2011, NIPS 24: 1549-1557) is useful for actual complex problems which demand large number of summary statistics, by applying the method to population genetic inferences.
Revised:  The present study evaluated the utility of a kernel-based ABC method proposed by Fukumizu et al. ( 2010, arXiv:1009.5736 and 2011, NIPS 24: 1549-1557) is useful for actual complex problems which demand large number of summary statistics, by applying the method to population genetic inferences.
Edit intent: clarity
Original:  The aim of this study is to investigate whether a new kernel-based ABC method proposed by Fukumizu et al. ( 2010, arXiv:1009.5736 and 2011, NIPS 24: 1549-1557) is useful for actual complex problems which demand large number of summary statistics, by applying the method to population genetic inferences.
Revised:  The aim of this study is to investigate whether a new kernel-based ABC method ( Fukumizu et al. ( 2010, arXiv:1009.5736 and 2011, NIPS 24: 1549-1557) is useful for actual complex problems which demand large number of summary statistics, by applying the method to population genetic inferences.
Edit intent: clarity
Original:  The aim of this study is to investigate whether a new kernel-based ABC method proposed by Fukumizu et al. ( 2010, arXiv:1009.5736 and 2011, NIPS 24: 1549-1557) is useful for actual complex problems which demand large number of summary statistics, by applying the method to population genetic inferences.
Revised:  The aim of this study is to investigate whether a new kernel-based ABC method proposed by Fukumizu et al. 2010, arXiv:1009.5736 and 2011, NIPS 24: 1549-1557) is useful for actual complex problems which demand large number of summary statistics, by applying the method to population genetic inferences.
Edit intent: fluency
Original:  The aim of this study is to investigate whether a new kernel-based ABC method proposed by Fukumizu et al. ( 2010, arXiv:1009.5736 and 2011, NIPS 24: 1549-1557) is useful for actual complex problems which demand large number of summary statistics, by applying the method to population genetic inferences.
Revised:  The aim of this study is to investigate whether a new kernel-based ABC method proposed by Fukumizu et al. ( 2010, arXiv:1009.5736 and 2011, NIPS 24: 1549-1557) for complex problems that demand many summary statistics. Specifically, kernel ABC was applied to population genetic inferences.
Edit intent: coherence
Original:  We report that, in contrast to conventional ABCs, kernel-ABC can incorporate large number of summary statistics with keeping consistency of the posterior estimates without compromising the performance of the inference.
Revised:  We report that, in contrast to conventional ABCs, kernel ABC can incorporate a large number of summary statistics with keeping consistency of the posterior estimates without compromising the performance of the inference.
Edit intent: clarity
Original:  We report that, in contrast to conventional ABCs, kernel-ABC can incorporate large number of summary statistics with keeping consistency of the posterior estimates without compromising the performance of the inference.
Revised:  We report that, in contrast to conventional ABCs, kernel-ABC can incorporate large number of summary statistics while maintaining high performance of the inference.
Edit intent: clarity
Original:  Here we introduce a framework for multi-network analysis based on hypergraph representations.
Revised:  Here we introduce a framework for clustering and community detection in such systems using hypergraph representations.
Edit intent: clarity
Original:  We illustrate our approach with applications for tripartite community detection in folksonomies, for local and global alignment of protein-protein interaction networks between multiple species  and for detecting clusters of overlapping regulatory pathways in directed networks.
Revised:  We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species and for detecting clusters of overlapping regulatory pathways in directed networks.
Edit intent: coherence
Original:  We give a natural construction of a category of \varepsilon-interleavings of these diagrams, and show that if the target category is abelian, so is this category of interleavings.
Revised:  We give a natural construction of a category of interleavings of these diagrams, and show that if the target category is abelian, so is this category of interleavings.
Edit intent: clarity
Original:  Our model has reduced size in terms of number of variable and constraints compared to existing models by a factor of approximately O(n), where n being the number of ports.
Revised:  In particular, our model has reduced size in terms of number of variable and constraints compared to existing models by a factor of approximately O(n), where n being the number of ports.
Edit intent: coherence
Original:  Our model has reduced size in terms of number of variable and constraints compared to existing models by a factor of approximately O(n), where n being the number of ports.
Revised:  Our model has reduced size in terms of the number of variables and constraints compared to existing models by a factor of approximately O(n), where n being the number of ports.
Edit intent: fluency
Original:  The model also permits load/unload time and handle passenger transfer efficiently . Experiments using real world data produced high quality solutions in 12 hours using CPLEX 12.4 with a performance grantee of within 15\% of optimality, on average.
Revised:  The model also handles efficiently load/unload time and handle passenger transfer efficiently . Experiments using real world data produced high quality solutions in 12 hours using CPLEX 12.4 with a performance grantee of within 15\% of optimality, on average.
Edit intent: clarity
Original:  The model also permits load/unload time and handle passenger transfer efficiently . Experiments using real world data produced high quality solutions in 12 hours using CPLEX 12.4 with a performance grantee of within 15\% of optimality, on average.
Revised:  The model also permits load/unload time constraints, crew scheduling and passenger transfers . Experiments using real world data produced high quality solutions in 12 hours using CPLEX 12.4 with a performance grantee of within 15\% of optimality, on average.
Edit intent: clarity
Original:  The model also permits load/unload time and handle passenger transfer efficiently . Experiments using real world data produced high quality solutions in 12 hours using CPLEX 12.4 with a performance grantee of within 15\% of optimality, on average.
Revised:  The model also permits load/unload time and handle passenger transfer efficiently . Experiments using real world data produced high quality solutions in 12 hours using CPLEX 12.4 with a performance guarantee of within 15\% of optimality, on average.
Edit intent: fluency
Original:  In particular, we analyse the dynamics of the model around the so-called `Break Point Date', when behavioural elements are injected into the system and compare it to our empirical benchmark sample.
Edit intent: coherence
Original:  Behavioural patterns are thus embedded into an asset pricing framework  , which allows  to examine their direct impact.
Revised:  Behavioural patterns are injected into an asset pricing framework , which allows to examine their direct impact.
Edit intent: clarity
Original:  Behavioural patterns are thus embedded into an asset pricing framework  , which allows  to examine their direct impact.
Revised:  Behavioural patterns are thus embedded into an asset pricing framework , which allows us to examine their direct impact.
Edit intent: fluency
Original:   ,c} such that no four corners forming a rectangle have the same color.
Revised:  . ,c} such that no four corners forming a rectangle have the same color.
Edit intent: fluency
Original:  We propose a practical secondary sharing scheme based on a combination of geo-location databases and spectrum sensing . Since the DME system performs a safety-of-life function , protection from harmful interference becomes extremely critical.
Revised:  We propose a practical secondary sharing scheme customized to the characteristics of the DME . Since the DME system performs a safety-of-life function , protection from harmful interference becomes extremely critical.
Edit intent: clarity
Original:  We propose a practical secondary sharing scheme based on a combination of geo-location databases and spectrum sensing . Since the DME system performs a safety-of-life function , protection from harmful interference becomes extremely critical.
Revised:  We propose a practical secondary sharing scheme based on a combination of geo-location databases and spectrum sensing . Since the DME system performs a safety-of-life functionality , protection from harmful interference becomes extremely critical.
Edit intent: fluency
Original:  Secondary users estimate the propagation loss and employ an individual interference threshold to control the aggregate interference .
Revised:  The proposed scheme controls aggregate interference by imposing an individual interference threshold to control the aggregate interference .
Edit intent: clarity
Original:  Secondary users estimate the propagation loss and employ an individual interference threshold to control the aggregate interference .
Revised:  Secondary users estimate the propagation loss and employ an individual interference threshold on the secondary users .
Edit intent: clarity
Original:  We examine the feasibility of large scale secondary access in terms of the transmission probability ( of the secondary users ) that keeps the probability of harmful interference below a given limit.
Revised:  We examine the feasibility of large scale secondary access in terms of the transmission probability of the secondary users ) that keeps the probability of harmful interference below a given limit.
Edit intent: fluency
Original:  We examine the feasibility of large scale secondary access in terms of the transmission probability ( of the secondary users ) that keeps the probability of harmful interference below a given limit.
Revised:  We examine the feasibility of large scale secondary access in terms of the transmission probability ( of the secondary users that keeps the probability of harmful interference below a given limit.
Edit intent: fluency
Original:  We propose a cumulant-based approximation of the probability distribution of the aggregate interference in the presence of the above uncertainties.
Edit intent: coherence
Original:  Numerical results show that large scale low-power indoor secondary network is able to operate in adjacent  channels without harming the primary system even with rather limited accuracy in the estimation of the propagation loss.
Revised:  Numerical results show that large number of secondary users are able to operate in adjacent channels without harming the primary system even with rather limited accuracy in the estimation of the propagation loss.
Edit intent: clarity
Original:  Numerical results show that large scale low-power indoor secondary network is able to operate in adjacent  channels without harming the primary system even with rather limited accuracy in the estimation of the propagation loss.
Revised:  Numerical results show that large scale low-power indoor secondary network is able to operate in adjacent channels without harming the primary system even with limited accuracy in the estimation of the propagation loss.
Edit intent: clarity
Original:  To achieve such a design, we apply a multicanonical Monte Carlo  .
Revised:  To achieve such a design, we apply a multicanonical Monte Carlo method .
Edit intent: clarity
Original: Adaptive networks are well-suited to perform decentralized information processing and optimization tasks and to model various types of self organized and complex behavior encountered in nature.
Revised: Adaptive networks are well-suited to perform decentralized information processing and optimization tasks and to model various types of self-organized and complex behavior encountered in nature.
Edit intent: fluency
Original:  The continuous diffusion of information across the network enables agents to adapt their performance in relation to changing data and network conditions;
Revised:  The continuous diffusion of information across the network enables agents to adapt their performance in relation to streaming data and network conditions;
Edit intent: clarity
Original:  it also results in improved adaptation and learning performance relative to non-cooperative networks .
Revised:  it also results in improved adaptation and learning performance relative to non-cooperative agents .
Edit intent: clarity
Original:  Prior reports demonstrate how these can inflate the rate of false effects in published science.
Revised:  Prior reports demonstrate how these incentives inflate the rate of false effects in published science.
Edit intent: clarity
Original:  Further, because of incentives for novelty over replication, published false results then persist in the literature unchallenged .
Revised:  When incentives favor novelty over replication, published false results then persist in the literature unchallenged .
Edit intent: coherence