wanyu/IteraTeR_full_sent huggingface dataset:
Original:   Using white noise calculus we compute explicitly the optimal consumption rate and portfolio in this case and we show that the maximal value is finite as long as  \theta> 0.
Revised:  We allow the stock price dynamics to depend on both a continuous process (Brownian motion) and a jump process (Poisson random measure). We believe that jumps and delays are essential in order to get more realistic financial market models. Using white noise calculus we compute explicitly the optimal consumption rate and portfolio in this case and we show that the maximal value is finite as long as \theta> 0.
Edit intent: meaning-changed
Original:   See e.g. Lachapelle et al LLLL and the references therein.
Revised:  This is because high frequency trading often leads to intensive trading taking place on close to infinitesimal lengths of time, which in the limit corresponds to trading on time sets of measure 0. This may in turn lead to a singular drift in the pricing dynamics. See e.g. Lachapelle et al LLLL and the references therein.
Edit intent: meaning-changed
Original:  The estimation and inference are based on the Neyman-type orthogonal moment conditions , that are relatively insensitive to the estimation of the nuisance parameters.
Revised:  The estimation and inference are based on the Neyman-type orthogonal moment conditions tentatively outlined in Chernozhukov, Hansen and Wuthrich (2018) and thus relatively insensitive to the estimation of the nuisance parameters.
Edit intent: meaning-changed
Original:  We also apply the procedure to reinvestigate two empirical studies: the quantile treatment effect of 401(k) participation on accumulated wealth , and the distributional effect of job-training program participation on trainee earnings .
Revised:  We also apply the procedure to empirically reinvestigate the quantile treatment effect of 401(k) participation on accumulated wealth , and the distributional effect of job-training program participation on trainee earnings .
Edit intent: clarity
Original:  The proposed econometric procedure is based on the Neyman-type orthogonal moment conditions tentatively outlined in Chernozhukov, Hansen and Wuthrich (2018) and  thus relatively insensitive to the estimation of the nuisance parameters.
Revised:  Our proposed econometric procedure is based on the Neyman-type orthogonal moment conditions tentatively outlined in Chernozhukov, Hansen and Wuthrich (2018) and thus relatively insensitive to the estimation of the nuisance parameters.
Edit intent: fluency
Original:  The proposed econometric procedure is based on the Neyman-type orthogonal moment conditions tentatively outlined in Chernozhukov, Hansen and Wuthrich (2018) and  thus relatively insensitive to the estimation of the nuisance parameters.
Revised:  The proposed econometric procedure builds on the Neyman-type orthogonal moment conditions tentatively outlined in Chernozhukov, Hansen and Wuthrich (2018) and thus relatively insensitive to the estimation of the nuisance parameters.
Edit intent: clarity
Original:  The proposed econometric procedure is based on the Neyman-type orthogonal moment conditions tentatively outlined in Chernozhukov, Hansen and Wuthrich (2018) and  thus relatively insensitive to the estimation of the nuisance parameters.
Revised:  The proposed econometric procedure is based on the Neyman-type orthogonal moment conditions of a previous study Chernozhukov, Hansen and Wuthrich (2018) and thus relatively insensitive to the estimation of the nuisance parameters.
Edit intent: meaning-changed
Original:  The proposed econometric procedure is based on the Neyman-type orthogonal moment conditions tentatively outlined in Chernozhukov, Hansen and Wuthrich (2018) and  thus relatively insensitive to the estimation of the nuisance parameters.
Revised:  The proposed econometric procedure is based on the Neyman-type orthogonal moment conditions tentatively outlined in Chernozhukov, Hansen and Wuthrich (2018) and is thus relatively insensitive to the estimation of the nuisance parameters.
Edit intent: fluency
Original:  We find that for realistic parameters based on the UK pensions market, a collectivised fund achieves an approximately 20 \% better return than either an annuity or a personal investment fund . We introduce models of investor preferences over a stream of pension payments in the presence of mortality, incorporating a new concept of adequacy. We find that for risk-averse individuals, pension adequacy plays an important role in determining the optimal fund management strategy. A key issue in the design of collective funds is how to ensure the fund treats all investors fairly. This is a trivial problem in the case that all investors have identical preferences, wealth and mortality, but becomes challenging for heterogeneous funds. We give a strategy for the management of heterogeneous funds in complete markets and prove that it is asymptotically optimal in the absence of systematic longevity risk.
Revised:  We find that for realistic parameters based on the UK pensions market, a collectivised fund achieves an approximately 20 
Edit intent: coherence
Original: A central challenge in industrial microbiological applications is engineering of genetic networks to achieve a target yield or steady state concentration. This is a particularly challenging problem when optimizing under novel reaction conditions where canonical models of metabolic pathways are no longer valid. In these scenarios, the biological systems are entirely represented by data for which no direct methods exist to optimize the reaction output. We introduce a datadriven model discovery approach that leverages Koopman operator theory and time-series expression measurements to discover models that predict untested reaction outcomes. These Koopman models allow us to design control strategies to achieve target steady state concentrations for products of interest. We develop a model of the trypotophan pathway and illustrate this steady stateprogramming framework on this pathway. Tryptophan is an essential amino acid and is a valuable product in industrial microbiology.
Revised: This paper describes the optimal selection of a valuable product in industrial microbiology.
Edit intent: clarity
Original:  Tryptophan is an essential amino acid and is a valuable product in industrial microbiology. We show how Koopman operator theory can thus be used program the steady state of a genetic network in a data-driven context .
Revised:  Tryptophan is an essential amino acid and is a control policy to program the steady state of controlled nonlinear systems with hyperbolic fixed points. This work is motivated by the field of synthetic biology, in which saddle points are common (along with limit cycles), and the aim is to program cells to perform both digital and analog computation, though developing genetic digital computation has been the main focus. We frame the analog computing challenge of generating a steady state input-output function inside living cells. To program the steady state, a data-driven context .
Edit intent: meaning-changed
Original:  We show how Koopman operator theory can thus be used program the steady state of a genetic network in a data-driven context .
Revised:  We show how Koopman operator theory can thus be used program the steady state of a genetic network in a data-driven approach is taken wherein an approximation of the Koopman operator, identified via deep dynamic mode decomposition, is used to describe the dynamics of the system linearly. The new representation of the dynamics are then used to solve an optimization problem for the input which maximizes a direction in state space. Some added structure on the Koopman operator learning process for controlled systems is given for dynamics that are separable in the state and input. Finally, the methods are demonstrated on simulation examples of an incoherent feedforward loop and a combinatorial promoter system, two common network architectures seen in the field of synthetic biology .
Edit intent: meaning-changed
Original: There are abundant cases for using Topological Data Analysis (TDA) in a learning context, but robust topological information commonly comes in the form of a set of persistence diagrams, objects that by nature are uneasy to affix to a generic machine learning framework .
Revised: Robust topological information commonly comes in the form of a set of persistence diagrams, objects that by nature are uneasy to affix to a generic machine learning framework .
Edit intent: coherence
Original: There are abundant cases for using Topological Data Analysis (TDA) in a learning context, but robust topological information commonly comes in the form of a set of persistence diagrams, objects that by nature are uneasy to affix to a generic machine learning framework .
Revised: There are abundant cases for using Topological Data Analysis (TDA) in a learning context, but robust topological information commonly comes in the form of a set of persistence diagrams, finite measures that are in nature uneasy to affix to a generic machine learning framework .
Edit intent: clarity
Original: There are abundant cases for using Topological Data Analysis (TDA) in a learning context, but robust topological information commonly comes in the form of a set of persistence diagrams, objects that by nature are uneasy to affix to a generic machine learning framework .
Revised: There are abundant cases for using Topological Data Analysis (TDA) in a learning context, but robust topological information commonly comes in the form of a set of persistence diagrams, objects that by nature are uneasy to affix to generic machine learning framework .
Edit intent: fluency
Original: There are abundant cases for using Topological Data Analysis (TDA) in a learning context, but robust topological information commonly comes in the form of a set of persistence diagrams, objects that by nature are uneasy to affix to a generic machine learning framework .
Revised: There are abundant cases for using Topological Data Analysis (TDA) in a learning context, but robust topological information commonly comes in the form of a set of persistence diagrams, objects that by nature are uneasy to affix to a generic machine learning frameworks .
Edit intent: fluency
Original:  We introduce a vectorisation method for diagrams that allows to collect information from topological descriptors into a format fit for machine learning tools. Based on a few observations, the method is learned and tailored to discriminate the various important plane regions a diagram is set into.
Revised:  We introduce a learnt, unsupervised measure vectorisation method and use it for reflecting underlying changes in topological behaviour in machine learning contexts. Relying on optimal measure quantisation results the method is learned and tailored to discriminate the various important plane regions a diagram is set into.
Edit intent: meaning-changed
Original:  Based on a few observations, the method is learned and tailored to discriminate the various important plane regions a diagram is set into. With this tool one can automatically augment any sort of machine learning problem with access to a TDA method, enhance performances, construct features reflecting underlying changes in topological behaviour. The proposed methodology comes with only high level tuning parameters such as the encoding budget for topological features. We provide an open-access, ready-to-use implementation and notebook. We showcase the strengths and versatility of our approach on a number of applications .
Revised:  Based on a few observations, the method is learned and tailored to discriminate the various important plane regions where meaningful differences arise. We showcase the strength and robustness of our approach on a number of applications .
Edit intent: clarity
Original:  We showcase the strengths and versatility of our approach on a number of applications . From emulous and modern graph collections to a highly topological synthetic dynamical orbits data, we prove that the method matches or beats the state-of-the-art in encoding persistence diagrams to solve hard problems.
Revised:  We showcase the strengths and versatility of our approach on a number of applications , from emulous and modern graph collections to a highly topological synthetic dynamical orbits data, we prove that the method matches or beats the state-of-the-art in encoding persistence diagrams to solve hard problems.
Edit intent: fluency
Original:  From emulous and modern graph collections to a highly topological synthetic dynamical orbits data, we prove that the method matches or beats the state-of-the-art in encoding persistence diagrams to solve hard problems.
Revised:  From emulous and modern graph collections where the method reaches state-of-the-art performance to a geometric synthetic dynamical orbits data, we prove that the method matches or beats the state-of-the-art in encoding persistence diagrams to solve hard problems.
Edit intent: meaning-changed
Original:  From emulous and modern graph collections to a highly topological synthetic dynamical orbits data, we prove that the method matches or beats the state-of-the-art in encoding persistence diagrams to solve hard problems. We then apply our method in the context of an industrial, difficult time-series regression problem and show the approach to be relevant .
Revised:  From emulous and modern graph collections to a highly topological synthetic dynamical orbits problem. The proposed methodology comes with only high level tuning parameters such as the total measure encoding budget, and we provide a completely open access software .
Edit intent: meaning-changed
Original:  We define the incentive compatibility in this dynamic environment in terms of Bellman equations, which is then simplified by establishing a one-shot deviation principle. Given the optimality of the stopping rule, a sufficient condition for  incentive compatibility is obtained by constructing the state-dependent payment rules in terms of a set of functions parameterized by the allocation rule.
Revised:  This work focuses on the theoretical design regime of the dynamic mechanism design when the agent makes coupled decisions of reporting and stopping. A dynamic incentive compatibility constraint is introduced to guarantee the robustness of the mechanism to the agent's strategic manipulation. A sufficient condition for incentive compatibility is obtained by constructing the state-dependent payment rules in terms of a set of functions parameterized by the allocation rule.
Edit intent: meaning-changed
Original:  Given the optimality of the stopping rule, a sufficient condition for  incentive compatibility is obtained by constructing the state-dependent payment rules in terms of a set of functions parameterized by the allocation rule.
Revised:  Given the optimality of the stopping rule, a sufficient condition for dynamic incentive compatibility is obtained by constructing the state-dependent payment rules in terms of a set of functions parameterized by the allocation rule.
Edit intent: meaning-changed
Original:  A necessary condition is derived from envelope theorem, which explicitly formulates the state-dependent payment rules in terms of allocation rules. A class of monotone environment is considered to characterize the optimal stopping by a threshold rule. The posted-price payment rules are then pinned down  in terms of the allocation rule and the threshold function up to a constant.
Revised:  The payment rules are then pinned down in terms of the allocation rule and the threshold function up to a constant.
Edit intent: coherence
Original:  The posted-price payment rules are then pinned down  in terms of the allocation rule and the threshold function up to a constant. The incentive compatibility constraints restrict the design of the posted-price payment rule by a regular condition .
Revised:  The posted-price payment rules are then pinned down in terms of the allocation rule by deriving a first-order condition. We show cases of relaxations of the principal's mechanism design problem and provide an approach to evaluate the loss of robustness of the dynamic incentive compatibility when the problem solving is relaxed due to analytical intractability. A case study is used to illustrate the theoretical results .
Edit intent: meaning-changed
Original:  This work focuses on the theoretical design regime of the dynamic mechanism design when the agent makes coupled decisions of reporting and stopping. A dynamic incentive compatibility constraint is introduced to guarantee the robustness of the mechanism to the agent's strategic manipulation. A sufficient condition for dynamic incentive compatibility is obtained by constructing the  payment rules in terms of a set of functions parameterized by the allocation rule.
Revised:  We define the incentive compatibility in this dynamic environment in terms of Bellman equations, which is then simplified by establishing a one-shot deviation principle. Given the optimality of the stopping rule, a sufficient condition for dynamic incentive compatibility is obtained by constructing the payment rules in terms of a set of functions parameterized by the allocation rule.
Edit intent: meaning-changed
Original:  The payment rules are then pinned down up to a constant in terms of the allocation rule by deriving a first-order condition.
Revised:  A necessary condition is derived from envelope theorem, which explicitly formulates the state-dependent payment rules in terms of allocation rules. A class of monotone environment is considered to characterize the optimal stopping by a threshold rule. The posted-price payment rules are then pinned down up to a constant in terms of the allocation rule by deriving a first-order condition.
Edit intent: meaning-changed
Original:  The payment rules are then pinned down up to a constant in terms of the allocation rule by deriving a first-order condition. We show cases of relaxations of the principal's mechanism design problem and provide an approach to evaluate the loss of robustness of the dynamic incentive compatibility when the problem solving is relaxed due to analytical intractability. A case study is used to illustrate the theoretical results .
Revised:  The payment rules are then pinned down up to a constant in terms of the allocation rule and the threshold function up to a constant. The incentive compatibility constraints restrict the design of the posted-price payment rule by a regular condition .
Edit intent: meaning-changed
Original:  Here we discuss how capturing the postures of animals over time is a key step in transforming videos into lower dimensional representations of behavior. We envision that the fast-paced development of new deep learning tools will rapidly change the landscape of realizable real-world neuroscience experiments .
Revised:  Here we discuss how capturing the postures of animals - pose estimation - has been rapidly advancing with new deep learning methods. While challenges still remain, we envision that the fast-paced development of new deep learning tools will rapidly change the landscape of realizable real-world neuroscience experiments .
Edit intent: meaning-changed
Original:  Our experimental results showed that NGEMMoutperformed the state-of-art BLAS libraries such as MKL  by an average of 1.4x .
Revised:  Our experimental results showed that NGEMMoutperformed the state-of-art BLAS libraries such as MKL . Our experimental results showed that NGEMM outperformed MKL non-pack and pack version by an average of 1.4x .
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Original:  We show runtime predictions for code on Intel Cascade Lake, AMD Zen, and Marvell Vulcan micro-architectures based on machine models from available documentation and semi-automatic benchmarking.
Revised:  We show runtime predictions for code on Intel Cascade Lake, AMD Zen, and Marvell ThunderX2 micro-architectures based on machine models from available documentation and semi-automatic benchmarking.
Edit intent: meaning-changed
Original:  The proof-of-concept experiments with four wild-type zebrafish embryos render both approaches suitable for automatic staging with average deviations of 0.45 - 0.57 hours .
Revised:  The proof-of-concept experiments with four wild-type zebrafish embryos render both approaches suitable for automatic staging with average deviations of 0.45 - 34 minutes. Moreover, a proof-of-concept evaluation based on simulated 3D+t point cloud data sets shows that average deviations of less than 7 minutes are possible .
Edit intent: meaning-changed
Original:  We verify our methods by collecting user data on twelve subjects for two real-world driving datasets among which one is publicly available (KITTI dataset) and one that we collect ourselves (LISA dataset) with the vehicle being driven in  autonomous mode.
Revised:  We verify our methods by collecting user data on twelve subjects for two real-world driving datasets among which one is publicly available (KITTI dataset) and one that we collect ourselves (LISA dataset) with the vehicle being driven in an autonomous mode.
Edit intent: fluency
Original:  We show that our methods outperform previously reported studies in the context of monitoring driver awareness and detecting hazardous/non-hazardous situations for short time scales of two-seconds. We verify our methods by collecting user data on twelve subjects for two real-world driving datasets among which one is publicly available (KITTI dataset) and one that we collect ourselves (LISA dataset) with the vehicle being driven in an autonomous mode.
Revised:  We show that our methods outperform previously reported studies in the context of monitoring driver awareness and detecting hazardous/non-hazardous situations for short time scales of two seconds. We use EEG and vision data for high resolution temporal classification (two seconds) while additionally also employing PPG and GSR over longer time periods. We evaluate our methods by collecting user data on twelve subjects for two real-world driving datasets among which one is publicly available (KITTI dataset) and one that we collect ourselves (LISA dataset) with the vehicle being driven in an autonomous mode.
Edit intent: meaning-changed
Original:  We verify our methods by collecting user data on twelve subjects for two real-world driving datasets among which one is publicly available (KITTI dataset) and one that we collect ourselves (LISA dataset) with the vehicle being driven in an autonomous mode.
Revised:  We verify our methods by collecting user data on twelve subjects for two real-world driving datasets among which one is publicly available (KITTI dataset) while the other was collected by us (LISA dataset) with the vehicle being driven in an autonomous mode.
Edit intent: clarity
Original:  We verify our methods by collecting user data on twelve subjects for two real-world driving datasets among which one is publicly available (KITTI dataset) and one that we collect ourselves (LISA dataset) with the vehicle being driven in an autonomous mode.This work presents an exhaustive evaluation of multiple sensor modalities on two different datasets for attention monitoring and hazardous events classification .
Revised:  We verify our methods by collecting user data on twelve subjects for two real-world driving datasets among which one is publicly available (KITTI dataset) and one that we collect ourselves (LISA dataset) with the vehicle ... .
Edit intent: coherence
Original:  In this documentation, you will find the following . - A brief introduction to Conjure, - installation instructions, - a description of how to use Conjure through its command line user interface, - a list of Conjure's features, - a description of Conjure's input language Essence, and - a collection of simple demonstrations of Conjure's use.
Revised:  In this documentation, you will find the following : A brief introduction to Conjure, - installation instructions, - a description of how to use Conjure through its command line user interface, - a list of Conjure's features, - a description of Conjure's input language Essence, and - a collection of simple demonstrations of Conjure's use.
Edit intent: fluency