wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We show using Markov chain Monte Carlo methods that within a simulation estimation framework, a model fitted to sequential infection data accurately captures the timing and extent of cross-protection , and attributes such cross-protection to the correct broad immune components .
Revised:  We show using Markov chain Monte Carlo methods that within a simulation estimation framework, a model fitted to sequential infection data accurately captures the timing and extent of cross-protection . Moreover, the broad immune components .
Edit intent: coherence
Original:  We show using Markov chain Monte Carlo methods that within a simulation estimation framework, a model fitted to sequential infection data accurately captures the timing and extent of cross-protection , and attributes such cross-protection to the correct broad immune components . In addition, sequential infection data enables recovery of the timing and role of each immune component in controlling a primary infection .
Revised:  We show using Markov chain Monte Carlo methods that within a simulation estimation framework, a model fitted to sequential infection data accurately captures the timing and extent of cross-protection , and attributes such cross-protection to the correct broad immune components responsible for such cross-protection can be determined. Such data can also be used to infer the timing and role of each immune component in controlling a primary infection .
Edit intent: meaning-changed
Original:  In addition, sequential infection data enables recovery of the timing and role of each immune component in controlling a primary infection . A major limitation of previous studies using single infection data is that they have produced discrepant estimates of these quantities.
Revised:  In addition, sequential infection data enables recovery of the timing and role of each immune component in controlling a primary infection , even in the absence of serological data. By contrast, single infection data is that they have produced discrepant estimates of these quantities.
Edit intent: meaning-changed
Original:  A major limitation of previous studies using single infection data is that they have produced discrepant estimates of these quantities. This evaluation demonstrates that sequential infection experiments provide richer information for quantifying the contribution of each immune component to cross-protection. This information enhances our understanding of the mechanisms underlying the control and resolution of infection, and generates new insight into how previous exposure influences the time course of a subsequent infection.
Revised:  A major limitation of previous studies using single infection data cannot be used to reliably recover this information. Hence, sequential infection data enhances our understanding of the mechanisms underlying the control and resolution of infection, and generates new insight into how previous exposure influences the time course of a subsequent infection.
Edit intent: clarity
Original:  This allows us to completely characterize the models which prevent arbitrage opportunities . In this respect, we prove two results on the martingale property of stochastic exponentials.
Revised:  This allows us to completely characterize the models which prevent arbitrage opportunities : this boils down to finding a density between a risk-neutral measure \mathbb{Q this respect, we prove two results on the martingale property of stochastic exponentials.
Edit intent: meaning-changed
Original: This paper studies non-identified ill-posed inverse models with estimated operator. Leading examples are the nonparametric IV regression and the functional linear IV regression. We argue that identification of infinite-dimensional parameters is less crucial than identification of finite-dimensional parameters. We show that in the case of identification failures , a very general family of continuously-regularized estimators is consistent for the best approximation of the parameter of interest and obtain L_2 and L_\infty finite-sample risk bounds.
Revised: This paper studies non-identified ill-posed inverse models. The Tikhonov-regularized estimator converges to a well-defined limit equal to the best approximation of the parameter of interest and obtain L_2 and L_\infty finite-sample risk bounds.
Edit intent: meaning-changed
Original:  We show that in the case of identification failures , a very general family of continuously-regularized estimators is consistent for the best approximation of the parameter of interest and obtain L_2 and L_\infty finite-sample risk bounds. This class includes Tikhonov, iterated Tikhonov, spectral cut-off, and Landweber-Fridman as special cases. We show that in many cases the best approximation coincides with the structural parameter and can be a useful and tractable object to infer relation between structural variables otherwise.
Revised:  We show that in the case of identification failures , a very general family of continuously-regularized estimators is consistent for the best approximation of the structural parameter in the orthogonal complement to the null space of the operator. We illustrate that in many cases the best approximation coincides with the structural parameter and can be a useful and tractable object to infer relation between structural variables otherwise.
Edit intent: meaning-changed
Original:  We show that in many cases the best approximation coincides with the structural parameter and can be a useful and tractable object to infer relation between structural variables otherwise. Unlike in the identified case, estimation of the operator may have a non-negligible impact on the estimation accuracy and inference. We develop inferential methods for linear functionals in non-identified models as well as honest uniform confidence sets for the best approximation.
Revised:  We show that in many cases the best approximation coincides with the structural parameter or at least may reasonably approximate it. We characterize the nonasymptotic Hilbert space norm and the uniform norm convergence rates for the best approximation.
Edit intent: meaning-changed
Original:  Lastly, we demonstrate the discontinuity in the asymptotic distribution for extreme cases of identification failures where we observe a degenerate U-statistics asymptotics .
Revised:  Nonidentification has important implications for the large sample distribution of the Tikhonov-regularized estimator, and we document the transition between the Gaussian and the weighted chi-squared limits. The theoretical results are illustrated for the nonparametric IV and the functional linear IV regressions and are further supported by the Monte Carlo experiments .
Edit intent: meaning-changed
Original:  In particular, we show how such strategic reasoning may turn a naive agent into a sophisticated one.
Revised:  We then apply the general results to the case when the agents distort probability and the diffusion process is a geometric Brownian motion. The problem is inherently time-inconsistent as the level of distortion of a same event changes over time. We show how the strategic reasoning may turn a naive agent into a sophisticated one.
Edit intent: meaning-changed
Original:  Finally, when the diffusion process is a geometric Brownian motion we derive stopping strategies of these two types of agent for various parameter specifications of the problem, illustrating rich behaviors beyond the extreme ones such as "never-stopping" or "never-starting".
Revised:  Moreover, we derive stopping strategies of these two types of agent for various parameter specifications of the problem, illustrating rich behaviors beyond the extreme ones such as "never-stopping" or "never-starting".
Edit intent: coherence
Original:  Finally, when the diffusion process is a geometric Brownian motion we derive stopping strategies of these two types of agent for various parameter specifications of the problem, illustrating rich behaviors beyond the extreme ones such as "never-stopping" or "never-starting".
Revised:  Finally, when the diffusion process is a geometric Brownian motion we derive stopping strategies of the two types of agent for various parameter specifications of the problem, illustrating rich behaviors beyond the extreme ones such as "never-stopping" or "never-starting".
Edit intent: clarity
Original:  However, optical microscopy as well as image acquisition and processing suffer from physical and technical prejudices which preclude a correct interpretation of biological observations which reflects in, e.g., medical and pharmacological praxis.
Revised:  However, optical microscopy as well as image acquisition and processing suffer from physical and technical prejudices which preclude a correct interpretation of biological observations which can be reflected in, e.g., medical and pharmacological praxis.
Edit intent: clarity
Original:  Results: We provided a correct set-up of the microscope and, using the approach of information entropy in image processing, we sought a voxel (3D pixel)  which localizes the information about the object.
Revised:  We provided a correct set-up of the microscope and, using the approach of information entropy in image processing, we sought a voxel (3D pixel) which localizes the information about the object.
Edit intent: coherence
Original:  Results: We provided a correct set-up of the microscope and, using the approach of information entropy in image processing, we sought a voxel (3D pixel)  which localizes the information about the object.
Revised:  Results: We provided a correct set-up of the microscope and, using the approach of information entropy in image processing, we sought a voxel (3D pixel) called an electromagnetic centroid which localizes the information about the object.
Edit intent: meaning-changed
Original:  Conclusions: We demonstrate that superresolution down to the Nobelish level can be obtained from commonplace widefield bright-field and fluorescence microscopy and bring new perspectives on co-localization in fluorescent microscopy.
Revised:  We demonstrate that superresolution down to the Nobelish level can be obtained from commonplace widefield bright-field and fluorescence microscopy and bring new perspectives on co-localization in fluorescent microscopy.
Edit intent: coherence
Original: Light microscopy is a standard examination tool in cell biology for study of physico-chemical processes at the intracellular level. However, optical microscopy as well as image acquisition and processing suffer from physical and technical prejudices which preclude a correct interpretation of biological observations which can be reflected in, e.g., medical and pharmacological praxis.
Revised: Light microscopy as well as image acquisition and processing suffer from physical and technical prejudices which preclude a correct interpretation of biological observations which can be reflected in, e.g., medical and pharmacological praxis.
Edit intent: clarity
Original:  Capturing the available information with chain maps on Delaunay complexes, we use persistent homology to quantify the evidence of recurrent behavior , and to recover the eigenspaces of the endomorphism on homology induced by the self-map.
Revised:  Capturing the available information with chain maps on Delaunay complexes, we use persistent homology to quantify the evidence of recurrent behavior . We establish a sampling theorem to recover the eigenspaces of the endomorphism on homology induced by the self-map.
Edit intent: meaning-changed
Original:  Capturing the available information with chain maps on Delaunay complexes, we use persistent homology to quantify the evidence of recurrent behavior , and to recover the eigenspaces of the endomorphism on homology induced by the self-map.
Revised:  Capturing the available information with chain maps on Delaunay complexes, we use persistent homology to quantify the evidence of recurrent behavior , and to recover the eigenspace of the endomorphism on homology induced by the self-map.
Edit intent: fluency
Original:  We  compare PNA against MNA in both a pairwise (native to PNA) and multiple (native to MNA) manner.
Revised:  We evaluate eight prominent PNA and MNA methods, on synthetic and real-world biological networks, using topological and functional alignment quality measures. We compare PNA against MNA in both a pairwise (native to PNA) and multiple (native to MNA) manner.
Edit intent: meaning-changed
Original: A hallmark of living systems is their ability to generate complex spatial patterns at the molecular, cellular, and multicellular levels. Many such systems rely on coupled biochemical and genetic signaling mechanisms that can produce URLanization. Long-range order and patterning can also emerge, however, through purely mechanical interactions. Here, we study the starvation-induced aggregation of gliding Myxococcus xanthus bacteria and show that these cells phase separate by tuning their motility over time.
Revised: Combining high-resolution single cell tracking experiments with numerical simulations, we show that starvation-induced aggregation of gliding Myxococcus xanthus bacteria and show that these cells phase separate by tuning their motility over time.
Edit intent: clarity
Original:  By experimentally varying the density and speed of gliding cells, tracking individual cells in large populations, and comparing to simulations of a model of reversing Active Brownian Particles (ABPs), we show that cell aggregation can be understood with a single phase diagram in terms of  density and a dimensionless inverse rotational Peclet number that characterizes cell motility .
Revised:  The phase separation can be understood with a single phase diagram in terms of density and a dimensionless inverse rotational Peclet number that characterizes cell motility .
Edit intent: clarity
Original:  By experimentally varying the density and speed of gliding cells, tracking individual cells in large populations, and comparing to simulations of a model of reversing Active Brownian Particles (ABPs), we show that cell aggregation can be understood with a single phase diagram in terms of  density and a dimensionless inverse rotational Peclet number that characterizes cell motility .
Revised:  By experimentally varying the density and speed of gliding cells, tracking individual cells in large populations, and comparing to simulations of a model of reversing Active Brownian Particles (ABPs), we show that cell aggregation can be understood in terms of density and a dimensionless inverse rotational Peclet number that characterizes cell motility .
Edit intent: meaning-changed
Original:  By experimentally varying the density and speed of gliding cells, tracking individual cells in large populations, and comparing to simulations of a model of reversing Active Brownian Particles (ABPs), we show that cell aggregation can be understood with a single phase diagram in terms of  density and a dimensionless inverse rotational Peclet number that characterizes cell motility .
Revised:  By experimentally varying the density and speed of gliding cells, tracking individual cells in large populations, and comparing to simulations of a model of reversing Active Brownian Particles (ABPs), we show that cell aggregation can be understood with a single phase diagram in terms of cell density and a dimensionless inverse rotational Peclet number that characterizes cell motility .
Edit intent: fluency
Original:  By experimentally varying the density and speed of gliding cells, tracking individual cells in large populations, and comparing to simulations of a model of reversing Active Brownian Particles (ABPs), we show that cell aggregation can be understood with a single phase diagram in terms of  density and a dimensionless inverse rotational Peclet number that characterizes cell motility .
Revised:  By experimentally varying the density and speed of gliding cells, tracking individual cells in large populations, and comparing to simulations of a model of reversing Active Brownian Particles (ABPs), we show that cell aggregation can be understood with a single phase diagram in terms of density and a dimensionless Peclet number that characterizes cell motility .
Edit intent: clarity
Original:  By experimentally varying the density and speed of gliding cells, tracking individual cells in large populations, and comparing to simulations of a model of reversing Active Brownian Particles (ABPs), we show that cell aggregation can be understood with a single phase diagram in terms of  density and a dimensionless inverse rotational Peclet number that characterizes cell motility . We further track changes in motility of the wild-type during starvation and show that a reduction of the reversal frequencyand an increase in gliding speed change the rotational Peclet number to drive aggregation. Thus, M. xanthus evolved to take advantage of an active-matter phase transition that can be controlled through changes in motility at the individual cell levelwithout complex feedback and chemical communication between cells .
Revised:  By experimentally varying the density and speed of gliding cells, tracking individual cells in large populations, and comparing to simulations of a model of reversing Active Brownian Particles (ABPs), we show that cell aggregation can be understood with a single phase diagram in terms of density and a dimensionless inverse rotational Peclet number that captures cell motility through speed and reversal frequency. Our work suggests that M. xanthus evolved to take advantage of an active-matter phase transition that can be controlled through changes in motility at the individual cell levelwithout complex feedback and chemical communication between cells .
Edit intent: clarity
Original:  Thus, M. xanthus evolved to take advantage of an active-matter phase transition that can be controlled through changes in motility at the individual cell levelwithout complex feedback and chemical communication between cells .
Revised:  Thus, M. xanthus evolved to take advantage of a self-driven non-equilibrium phase transition that can be controlled through changes in motility at the individual cell levelwithout complex feedback and chemical communication between cells .
Edit intent: meaning-changed
Original:   Moreover, we identify the conditions under which a relation between  fluxes and forces holds at the coarse-grained level as it holds at the detailed level.
Revised:  Our results lay the foundations for systematic studies of the thermodynamics of large-scale biochemical reaction networks. Moreover, we identify the conditions under which a relation between fluxes and forces holds at the coarse-grained level as it holds at the detailed level.
Edit intent: meaning-changed
Original:  In doing so, we clarify the speculations and broad claims made in the literature about such a general flux--force relation  .
Revised:  In doing so, we clarify the speculations and broad claims made in the literature about such a general flux--force relation . As a further consequence we show that, in contrast to common belief, the second law of thermodynamics does not require the currents and the forces of biochemical reaction networks to be always aligned .
Edit intent: meaning-changed
Original: We theoretically and empirically study large-scale portfolio allocation problems when transaction costs are taken into account in the optimization problem. We show that transaction costs act on the one hand as a turnover penalization and on the other hand as a regularization, which shrinks the covariance matrix.
Revised: We theoretically and empirically study portfolio optimization under transaction costs and establish a link between turnover penalization and on the other hand as a regularization, which shrinks the covariance matrix.
Edit intent: clarity
Original:  We show that transaction costs act on the one hand as a turnover penalization and on the other hand as a regularization, which shrinks the covariance matrix. As an empirical framework, we propose a flexible econometric setting for portfolio optimization under transaction costs, which incorporates parameter uncertainty and combines predictive distributions of individual models using optimal prediction pooling.
Revised:  We show that transaction costs act on the one hand as a turnover penalization and covariance shrinkage with the penalization governed by transaction costs. We show how the ex ante incorporation of transaction costs shifts optimal portfolios towards regularized versions of efficient allocations. The regulatory effect of transaction costs is studied in an econometric setting incorporating parameter uncertainty and combines predictive distributions of individual models using optimal prediction pooling.
Edit intent: meaning-changed
Original:  As an empirical framework, we propose a flexible econometric setting for portfolio optimization under transaction costs, which incorporates parameter uncertainty and combines predictive distributions of individual models using optimal prediction pooling. We consider predictive distributions resulting from high-frequency based covariance matrix estimates, daily stochastic volatility factor models and regularized rolling window covariance estimates, among others.
Revised:  As an empirical framework, we propose a flexible econometric setting for portfolio optimization under transaction costs, which incorporates parameter uncertainty and optimally combining predictive distributions resulting from high-frequency based covariance matrix estimates, daily stochastic volatility factor models and regularized rolling window covariance estimates, among others.
Edit intent: clarity
Original:  We consider predictive distributions resulting from high-frequency based covariance matrix estimates, daily stochastic volatility factor models and regularized rolling window covariance estimates, among others. Using datacapturing several hundred Nasdaq stocks over more than 10 years , we illustrate that transaction cost regularization (even to small extent) is crucial in order to produce allocations with positive Sharpe ratios.
Revised:  We consider predictive distributions resulting from high-frequency and low-frequency data. In an extensive empirical study , we illustrate that transaction cost regularization (even to small extent) is crucial in order to produce allocations with positive Sharpe ratios.
Edit intent: clarity
Original:  Using datacapturing several hundred Nasdaq stocks over more than 10 years , we illustrate that transaction cost regularization (even to small extent) is crucial in order to produce allocations with positive Sharpe ratios.
Revised:  Using datacapturing several hundred Nasdaq stocks over more than 10 years , we illustrate that turnover penalization is more effective than commonly employed shrinkage methods and is crucial in order to produce allocations with positive Sharpe ratios.
Edit intent: meaning-changed
Original:  Using datacapturing several hundred Nasdaq stocks over more than 10 years , we illustrate that transaction cost regularization (even to small extent) is crucial in order to produce allocations with positive Sharpe ratios. We moreover show that performance differences between individual models decline when transaction costs are considered. Nevertheless, it turns out that adaptive mixtures based on high-frequency and low-frequency information yield the highest performance. Portfolio bootstrap reveals that naive 1/N-allocations and global minimum variance allocations (with and without short sales constraints) are significantly outperformed in terms of Sharpe ratios and utility gains .
Revised:  Using datacapturing several hundred Nasdaq stocks over more than 10 years , we illustrate that transaction cost regularization (even to small extent) is crucial in order to construct empirically well-performing portfolios .
Edit intent: clarity