wanyu/IteraTeR_v2 huggingface dataset:
Original: \ Proc.\ Appl.\ } (  in the limit of infinite population size and for a certain asymptotic parameter regime ), as well as approximations based on heuristicsand  supported by simulations for finite populations.
Revised: \ Proc.\ Appl.\ } ( in the limit of infinite population size and for an asymptotic parameter regime ), as well as approximations based on heuristicsand supported by simulations for finite populations.
Edit intent: clarity
Original:  and it allows to separate this effect from the contribution of epistasis to the mean fitness curve.
Revised:  and it allows to clarify the contribution of epistasis to the mean fitness curve.
Edit intent: clarity
Original:  Mathematically, we first review the `dynamical law of large numbers ' result by Gonz\'{alez Casanova et al. (Stoch.
Revised:  Mathematically, we explain rigorous results in terms of a law of large numbers ' result by Gonz\'{alez Casanova et al. (Stoch.
Edit intent: clarity
Original:  Mathematically, we first review the `dynamical law of large numbers ' result by Gonz\'{alez Casanova et al. (Stoch.
Revised:  Mathematically, we first review the `dynamical law of large numbers lez Casanova et al. (Stoch.
Edit intent: clarity
Original: \ Proc.\ Appl.\ }126 ( 2016), 2211--2252), which applies in the limit of infinite population size and for an asymptotic parameter regime that excludes clonal interference.
Revised: \ Proc.\ Appl.\ } ( 2016), 2211--2252), which applies in the limit of infinite population size and for an asymptotic parameter regime that excludes clonal interference.
Edit intent: clarity
Original: \ Proc.\ Appl.\ }126 ( 2016), 2211--2252), which applies in the limit of infinite population size and for an asymptotic parameter regime that excludes clonal interference.
Revised: \ Proc.\ Appl.\ }126 ( in the limit of infinite population size and for an asymptotic parameter regime that excludes clonal interference.
Edit intent: coherence
Original: \ Proc.\ Appl.\ }126 ( 2016), 2211--2252), which applies in the limit of infinite population size and for an asymptotic parameter regime that excludes clonal interference.
Revised: \ Proc.\ Appl.\ }126 ( 2016), 2211--2252), which applies in the limit of infinite population size and for a certain asymptotic parameter regime that excludes clonal interference.
Edit intent: clarity
Original:  An increasing number of studies highlights the potential of these model membranes when addressing questions in membrane biophysics and cell-biology .
Revised:  An increasing number of studies highlights the potential of these model membranes when addressing questions in membrane biophysics and cell biology .
Edit intent: clarity
Original:  In doing so, many research teams rely on standard protocols for GUV preparation and handling involving the use of sugars .
Revised:  In doing so, many research teams rely on standard protocols for GUV preparation and handling involving the use of sugar solutions .
Edit intent: clarity
Original:  First,  unexpected formation of micron-sized dye-depleted fluid domains was observed upon cooling of GUVs to about 10 K above the lipid main phase transition temperature, TM.
Revised:  First, unexpected formation of micron-sized dye-depleted domains was observed upon cooling of GUVs to about 10 K above the lipid main phase transition temperature, TM.
Edit intent: clarity
Original:  Further cooling of the GUVs down to the immediate vicinity of TM renders the domains hexagonal, and in addition, stripe-like dye-enriched structures around the domains are detected.
Revised:  In addition, upon further cooling of the GUVs down to the immediate vicinity of TM renders the domains hexagonal, and in addition, stripe-like dye-enriched structures around the domains are detected.
Edit intent: clarity
Original:  Further cooling of the GUVs down to the immediate vicinity of TM renders the domains hexagonal, and in addition, stripe-like dye-enriched structures around the domains are detected.
Revised:  Further cooling of the GUVs down to the immediate vicinity of TM , stripe-like dye-enriched structures around the domains are detected.
Edit intent: coherence
Original:  The micron-sized fluid domains in quasi single-component GUVs were observed also when using two other lipids.
Revised:  The micron-sized domains in quasi single-component GUVs were observed also when using two other lipids.
Edit intent: clarity
Original: This paper considers an initial market model, specified by its underlying assets S and its flow of information \mathbb F, and an arbitrary random time \tau which is not an \mathbb F-stopping time.
Revised: This paper considers an initial market model, specified by its underlying assets S and its flow of information \mathbb F, and an arbitrary random time \tau which might not be an \mathbb F-stopping time.
Edit intent: clarity
Original:  At the practical level, this random time might represent the default time of a firm, the death time of an insured, or more generally an occurrence time of an event that might impact the market somehow.
Edit intent: coherence
Original:  Thanks to the deep results of Choulli et al.
Revised:  Thanks to the results of Choulli et al.
Edit intent: clarity
Original:  We study the problem of computing the visibility polygon from a given viewpoint q inside \mathcal {P} where only few working variables can be used.
Revised:  We study the problem of computing the visibility area from a given viewpoint q inside \mathcal {P} where only few working variables can be used.
Edit intent: clarity
Original:  Inquiry. Developing an incrementalized and persistent version of a pipeline is one way to reduce feedback latency, but requires implementation of dependency tracking, cache invalidation, and other complicated and error-prone techniques.
Revised:  Inquiry. Developing an incrementalized and persistent version of a pipeline is one way to reduce feedback latency, but requires dependency tracking, cache invalidation, and other complicated and error-prone techniques.
Edit intent: clarity
Original:  Inquiry. Developing an incrementalized and persistent version of a pipeline is one way to reduce feedback latency, but requires implementation of dependency tracking, cache invalidation, and other complicated and error-prone techniques.
Revised:  Inquiry. Developing an incrementalized and persistent version of a pipeline is one way to reduce feedback latency, but requires implementation of dependency tracking, cache invalidation, and other complicated techniques.
Edit intent: clarity
Original:  Systems for programming incremental and persistent pipelines exist, but do not focus on ease of development, requiring a high degree of boilerplate, increasing development and maintenance effort.
Edit intent: coherence
Original:  Then we carry out a rigorous passage to the limit as the spatial and temporal discretization parameters tend to zero, and show that the sequence of finite element approximations converges towards the unique weak solution of the model at hands.
Revised:  Then we carry out a rigorous passage to the limit as the spatial and temporal discretization parameters tend to zero, and show that the sequence of finite element approximations converges toward the unique weak solution of the model at hands.
Edit intent: fluency
Original:  In doing so, positivity for acute partitions of the computational domain and a priori energy estimates of finite element approximations are established.
Revised:  In doing so, positivity for acute partitions of the computational domain , and hence a priori energy estimates of finite element approximations are established.
Edit intent: coherence
Original:  The key compactness result is obtained via by a Riesz--Fr\'echet--Kolmogorov criterion by perturbation  .
Revised:  The key compactness result is obtained via an adaptation of a Riesz--Fr\'echet--Kolmogorov criterion by perturbation .
Edit intent: clarity
Original: Spiking Neural Networks (SNN) are mathematical models in neuroscience to describe the dynamics among a set of neurons which interact with each other by firing spike signalsto each other.
Revised: Spiking Neural Networks (SNN) are mathematical models in neuroscience to describe the dynamics among a set of neurons that interact with each other by firing spike signalsto each other.
Edit intent: fluency
Original: Interestingly, recent works observed that for an integrate-and-fire model, when configured appropriately (e.g., after the parameters are learned properly), the ]  neurons' firing rate, i.e., converges to an optimal solution of Lasso and certain quadratic optimization problems.
Revised: Interestingly, recent works observed that for an integrate-and-fire model, when configured appropriately (e.g., after the parameters are learned properly), the ] showed that the neurons' firing rate, i.e., converges to an optimal solution of Lasso and certain quadratic optimization problems.
Edit intent: clarity
Original:  In addition, we will compare the objectives and learning signals of brains and machines, leading us to conclude that simply scaling up the current DL algorithms will  not lead to human level mindreading skills.
Revised:  In addition, we will compare the objectives and learning signals of brains and machines, leading us to conclude that simply scaling up the current DL algorithms will most likely not lead to human level mindreading skills.
Edit intent: clarity
Original: The cone-beam tomography consists of integrating a function defined on the three-dimensional space along every ray that starts on a certain scanning curve . Based on Grangeat's formula, Louis [2016, Inverse Problems 32 115005] states reconstruction formulas based on a new generalized Funk-Radon transform on the sphere.
Revised: The cone-beam transform consists of integrating a function defined on the three-dimensional space along every ray that starts on a certain scanning curve . Based on Grangeat's formula, Louis [2016, Inverse Problems 32 115005] states reconstruction formulas based on a new generalized Funk-Radon transform on the sphere.
Edit intent: clarity
Original: The cone-beam tomography consists of integrating a function defined on the three-dimensional space along every ray that starts on a certain scanning curve . Based on Grangeat's formula, Louis [2016, Inverse Problems 32 115005] states reconstruction formulas based on a new generalized Funk-Radon transform on the sphere.
Revised: The cone-beam tomography consists of integrating a function defined on the three-dimensional space along every ray that starts on a certain scanning set . Based on Grangeat's formula, Louis [2016, Inverse Problems 32 115005] states reconstruction formulas based on a new generalized Funk-Radon transform on the sphere.
Edit intent: clarity
Original: The governing equations for electromagneto-thermomechanical systems are well established and thoroughly derived in the literature, but have been limited to small deformations.
Revised: For an accurate description of electromagneto-thermomechanical systems are well established and thoroughly derived in the literature, but have been limited to small deformations.
Edit intent: clarity
Original:  The assumption of small deformations eliminates the distinction between current and initial placement such that electromagnetism and thermomechanics are formulated in the same frame.
Edit intent: coherence
Original:  The approach is similar to its analog in fluid structure interaction, but additionally challenging because the electromagnetic governing equations must also be solved within the solid body while following their own different set of transformation rules.
Revised:  The approach is similar to its analog in fluid structure interaction, but more challenging because the electromagnetic governing equations must also be solved within the solid body while following their own different set of transformation rules.
Edit intent: clarity
Original:  The approach is similar to its analog in fluid structure interaction, but additionally challenging because the electromagnetic governing equations must also be solved within the solid body while following their own different set of transformation rules.
Revised:  The approach is similar to its analog in fluid structure interaction, but additionally challenging because the field equations in electromagnetism must also be solved within the solid body while following their own different set of transformation rules.
Edit intent: clarity
Original:  We further present a mesh-morphing algorithm necessary to accommodate finite deformations to solve the electromagnetic fields outside of the material body.
Revised:  We additionally present a mesh-morphing algorithm necessary to accommodate finite deformations to solve the electromagnetic fields outside of the material body.
Edit intent: clarity
Original:  In contrast to the existing literature, we introduce an analytically tractable model that enables one to connect two layers in a multilayer network by controlling the locality of coupling rather than relying on correlations of topological quantities of different centrality measures, such as degree-degree correlations .
Revised:  In contrast to the existing literature, we introduce an analytically tractable model that enables one to connect two layers in a multilayer network by controlling the locality of coupling .
Edit intent: coherence
Original:  We start by mapping an unassigned "source" node in network A to a randomly chosen "target" node in network B.
Revised:  We start by mapping an unassigned `source' node in network A to a randomly chosen "target" node in network B.
Edit intent: fluency
Original:  We start by mapping an unassigned "source" node in network A to a randomly chosen "target" node in network B.
Revised:  We start by mapping an unassigned "source" node in network A to a randomly chosen `target' node in network B.
Edit intent: fluency
Original:  More specifically, each neighbor of the source node is assigned to the stopping node of a random walk that starts from the target node and has a per-step stopping probability q.
Revised:  More specifically, each neighbor of the source node is assigned to the stopping node of a random walk that starts from the target node and with a per-step stopping probability q.
Edit intent: fluency
Original:  We repeat this process until all nodes in network A have been embedded into network B.
Edit intent: clarity
Original:  The simplicity of the embedding mechanism allows us to calculate key quantities of interest in closed form , making it a useful starting point for more realistic models of network embedding .
Revised:  The simplicity of the model allows us to calculate key quantities of interest in closed form , making it a useful starting point for more realistic models of network embedding .
Edit intent: clarity
Original:  The simplicity of the embedding mechanism allows us to calculate key quantities of interest in closed form , making it a useful starting point for more realistic models of network embedding .
Revised:  The simplicity of the embedding mechanism allows us to calculate key quantities , making it a useful starting point for more realistic models of network embedding .
Edit intent: clarity
Original:  The simplicity of the embedding mechanism allows us to calculate key quantities of interest in closed form , making it a useful starting point for more realistic models of network embedding .
Revised:  The simplicity of the embedding mechanism allows us to calculate key quantities of interest in closed form , making it a useful starting point for more realistic models .
Edit intent: clarity
Original:  For a particular type that we call {\it non-interlaced formulae }, we propose a polynomial time algorithm for their resolution using graphs and matrices.
Revised:  For a particular type that we call {\it non-interlaced formulas }, we propose a polynomial time algorithm for their resolution using graphs and matrices.
Edit intent: fluency
Original:  Thus , standard parallel models predict stochastically independent actual processing timesand therefore total completion times.
Revised:  Thus , standard parallel models assume stochastically independent and identical processing times. Their processing times are equivalent to the statistic known as total completion times.
Edit intent: clarity
Original:  What do standard serial models predict about this statistic?
Revised:  Little is known about what standard serial models predict about this statistic?
Edit intent: clarity
Original: The problem of optimizing sentinel surveillance in networks is to find the nodes where an emerging disease outbreak can be discovered early or reliably.
Revised: The problem of optimizing sentinel surveillance in networks is to identify the nodes to probe such that an emerging disease outbreak can be discovered early or reliably.
Edit intent: clarity
Original:  We investigate three objective measures  quantifying the performance of nodes in sentinel surveillance  the time to detection or extinction, the time to detection, and the frequency of detection.
Revised:  We investigate three objective measures quantifying the performance of nodes in sentinel surveillance -- the time to detection or extinction, the time to detection, and the frequency of detection.
Edit intent: fluency
Original:  As a basis for the comparison, we use the susceptible-infectious-recovered model (SIR) on static and temporal networks of human contacts.
Revised:  As a basis for the comparison, we use the susceptible-infectious-recovered model on static and temporal networks of human contacts.
Edit intent: clarity
Original:   As opposed to other problems in network epidemiology, we find rather similar results for the static and temporal networks.
Revised:  As opposed to other problems in network epidemiology, we draw similar conclusions from the static and temporal networks.
Edit intent: clarity
Original:  Furthermore, we do not find one  network structure that predicts the objective measures---that depends both on the data set and the SIR parameter . .
Revised:  Furthermore, we do not find one type of network structure that predicts the objective measures---that depends both on the data set and the SIR parameter . .
Edit intent: clarity
Original:  Furthermore, we do not find one  network structure that predicts the objective measures---that depends both on the data set and the SIR parameter . .
Revised:  Furthermore, we do not find one network structure that predicts the objective measures -- that depends both on the data set and the SIR parameter . .
Edit intent: fluency
Original:  The analytical form of the proposed solution provides several benefits over purely numerical models, e.g. high variability , existence of low run-time algorithms, extendability to several kinds of boundary conditions, and analytical connection to parameters from communication theory.
Revised:  The analytical form of the proposed solution provides several benefits over purely numerical models, e.g. high flexibility , existence of low run-time algorithms, extendability to several kinds of boundary conditions, and analytical connection to parameters from communication theory.
Edit intent: clarity
Original:  The first contribution of this work is the construction of a reliable linearization scheme that allows us, by choice of scale arguments and stabilization constant , to prove the weak solvability of the microscopic model.
Revised:  The first contribution of this work is the construction of a reliable linearization scheme that allows us, by a suitable choice of scaling arguments and stabilization constant , to prove the weak solvability of the microscopic model.
Edit intent: clarity
Original:  The first contribution of this work is the construction of a reliable linearization scheme that allows us, by choice of scale arguments and stabilization constant , to prove the weak solvability of the microscopic model.
Revised:  The first contribution of this work is the construction of a reliable linearization scheme that allows us, by choice of scale arguments and stabilization constants , to prove the weak solvability of the microscopic model.
Edit intent: fluency
Original:  Asymptotic behaviors of  solution with respect to the microscale parameter are thoroughly investigated in the second step, based on several cases of scalings.
Revised:  Asymptotic behaviors of the microscopic solution with respect to the microscale parameter are thoroughly investigated in the second step, based on several cases of scalings.
Edit intent: fluency
Original:  Asymptotic behaviors of  solution with respect to the microscale parameter are thoroughly investigated in the second step, based on several cases of scalings.
Revised:  Asymptotic behaviors of solution with respect to the microscale parameter are thoroughly investigated in the second theme, based upon several cases of scalings.
Edit intent: clarity
Original:  As an outcome of homogenization for multiscale elliptic problems, we  derive the corresponding macroscopic equation whenever the scaling choices are compatible.
Revised:  As an outcome of homogenization for multiscale elliptic problems, we derive the corresponding macroscopic equation , when the scaling choices are compatible.
Edit intent: coherence
Original:  Moreover, we prove a high-order corrector estimates for the homogenization limit in the energy space H^1 ;
Revised:  Moreover, we prove the high-order corrector estimates for the homogenization limit in the energy space H^1 ;
Edit intent: fluency
Original:  However, a large reduction in floating point (FP) operations in these algorithms can result in significantly reduced FP accuracyof the result .
Revised:  However, a large reduction in floating point (FP) operations in these algorithms can result in poor numeric accuracy .
Edit intent: clarity
Original:  In this paper we  propose several methods for reducing the FP error of these algorithms.
Revised:  In this paper we propose several methods for reducing FP error of these algorithms.
Edit intent: fluency
Original:  Using our methods we can significantly reduce FP error for a given Winograd convolution block size, which allows larger block sizes and reduced computation.
Revised:  Using our methods we can significantly reduce FP error for a given block size, which allows larger block sizes and reduced computation.
Edit intent: clarity
Original: Modern deep neural networks (DNNs) spend a large amount of their execution time computing convolutions.
Revised: Popular deep neural networks (DNNs) spend a large amount of their execution time computing convolutions.
Edit intent: clarity
Original: Modern deep neural networks (DNNs) spend a large amount of their execution time computing convolutions.
Revised: Modern deep neural networks (DNNs) spend the majority of their execution time computing convolutions.
Edit intent: clarity
Original:  Winograd's minimal algorithm for small convolutions can greatly reduce the number of arithmetic operations  .
Revised:  The Winograd family of algorithms can greatly reduce the number of arithmetic operations .
Edit intent: clarity
Original:  However, a large reduction in floating point (FP) operations in these algorithms can result in poor numeric accuracy.
Revised:  However, the performance gain is at the expense of a reduction in floating point (FP) operations in these algorithms can result in poor numeric accuracy.
Edit intent: clarity
Original:  However, a large reduction in floating point (FP) operations in these algorithms can result in poor numeric accuracy.
Revised:  However, a large reduction in floating point (FP) numerical accuracy.
Edit intent: clarity
Original:  In this paper  we analyse the  FP error and prove boundaries on the error .
Revised:  In this paper , we analyse the FP error and prove boundaries on the error .
Edit intent: fluency
Original:  Minimal convolution algorithms depend on the selection of several numericpoints that have a large impact on the accuracy of the result.
Revised:  Minimal convolution algorithms depend on the selection of several numeric that have a large impact on the accuracy of the result.
Edit intent: clarity
Original:  Minimal convolution algorithms depend on the selection of several numericpoints that have a large impact on the accuracy of the result.
Revised:  Minimal convolution algorithms depend on the selection of several numericpoints .
Edit intent: clarity