wanyu/IteraTeR_full_sent huggingface dataset:
Original: We empirically verify that the market capitalisations of coins and tokens in the cryptocurrency universe follow power law distributions with significantly different values, with the tail exponent falling between 0.5 and 0.7 for coins, and between 1.0 and 1.3 for tokens.
Revised: We empirically verify that the market capitalisations of coins and tokens in the cryptocurrency universe follow power-law distributions with significantly different values, with the tail exponent falling between 0.5 and 0.7 for coins, and between 1.0 and 1.3 for tokens.
Edit intent: fluency
Original:  in terms of proportional growth and linear versus square-root growth lawof the mean and standard deviation of market capitalisation as a function of time interval . Estimating the main parameters of the model, the theoretical predictions for the power law exponents of coins and tokens distribution are in remarkable agreement with the empirical estimations, given the simplicity of the model in the face of the complexity and non-stationarity of the crypto-currency world .
Revised:  in terms of proportional growth (Gibrat's law) of the coins and tokens . Estimating the main parameters of the model, the theoretical predictions for the power law exponents of coins and tokens distribution are in remarkable agreement with the empirical estimations, given the simplicity of the model in the face of the complexity and non-stationarity of the crypto-currency world .
Edit intent: meaning-changed
Original:  in terms of proportional growth and linear versus square-root growth lawof the mean and standard deviation of market capitalisation as a function of time interval . Estimating the main parameters of the model, the theoretical predictions for the power law exponents of coins and tokens distribution are in remarkable agreement with the empirical estimations, given the simplicity of the model in the face of the complexity and non-stationarity of the crypto-currency world .
Revised:  in terms of proportional growth and linear versus square-root growth lawof the mean and standard deviation of market capitalisation as a function of time interval . Estimating the main parameters of the model, the theoretical predictions for the power-law exponents of coin and token distributions are in remarkable agreement with the empirical estimations, given the simplicity of the model in the face of the complexity and non-stationarity of the crypto-currency world .
Edit intent: fluency
Original:  in terms of proportional growth and linear versus square-root growth lawof the mean and standard deviation of market capitalisation as a function of time interval . Estimating the main parameters of the model, the theoretical predictions for the power law exponents of coins and tokens distribution are in remarkable agreement with the empirical estimations, given the simplicity of the model in the face of the complexity and non-stationarity of the crypto-currency world .
Revised:  in terms of proportional growth and linear versus square-root growth lawof the mean and standard deviation of market capitalisation as a function of time interval . Estimating the main parameters of the model, the theoretical predictions for the power law exponents of coins and tokens distribution are in remarkable agreement with the empirical estimations, given the simplicity of the model .
Edit intent: clarity
Original:  Our results clearly characterizes coins as being "entrenched incumbents" and tokens as an "explosive immature ecosystem", largely due to massive and exuberant Initial Coin Offering activity in the token space.
Revised:  Our results clearly characterize coins as being "entrenched incumbents" and tokens as an "explosive immature ecosystem", largely due to massive and exuberant Initial Coin Offering activity in the token space.
Edit intent: fluency
Original: Designing RNA sequences that fold into specific structures and perform desired biological functions is an emerging field in bioengineering with broad applications from intracellular chemical catalysis to cancer therapy via selective gene silencing.
Revised: Solving the RNA inverse folding problem is a critical prerequisite to RNA design, an emerging field in bioengineering with broad applications from intracellular chemical catalysis to cancer therapy via selective gene silencing.
Edit intent: meaning-changed
Original: Designing RNA sequences that fold into specific structures and perform desired biological functions is an emerging field in bioengineering with broad applications from intracellular chemical catalysis to cancer therapy via selective gene silencing. Effective RNA design requires first solving the inverse folding problem: given a target structure, propose a sequence that folds into that structure.
Revised: Designing RNA sequences that fold into specific structures and perform desired biological functions is an emerging field in bioengineering with broad applications from intracellular chemical catalysis to cancer therapy .
Edit intent: clarity
Original:  Although significant progress has been made in developing computational algorithmsfor this purpose , current approaches are ineffective at designing sequences for complex targets, limiting their utility in real-world applications. However, an alternative that has shown significantly higher performance are human players of the online RNA design game EteRNA . Through many rounds of gameplay, these players have developed a collective library of "human" rules and strategies for RNA design that have proven to be more effective than current computational approaches, especially for complex targets .
Revised:  Although significant progress has been made in developing computational algorithmsfor this purpose , current approaches are ineffective at designing sequences for large or complex targets. On the other hand, human players of the online RNA design game EteRNA . Through many rounds of gameplay, these players have developed a collective library of "human" rules and strategies for RNA design that have proven to be more effective than current computational approaches, especially for complex targets .
Edit intent: clarity
Original:  However, an alternative that has shown significantly higher performance are human players of the online RNA design game EteRNA . Through many rounds of gameplay, these players have developed a collective library of "human" rules and strategies for RNA design that have proven to be more effective than current computational approaches, especially for complex targets . Here, we present an RNA design agent , SentRNA, which consists of a fully-connected neural network trained using the eternasolves dataset, a set of 1.8 x 10^4 player-submitted sequencesacross 724 unique targets.
Revised:  However, an alternative that has shown significantly higher performance are human players of the online RNA design game EteRNA have consistently shown superior performance in this regard, being able to readily design sequences for targets that are challenging for machine algorithms. Here we present a novel approach to the RNA design problem , SentRNA, which consists of a fully-connected neural network trained using the eternasolves dataset, a set of 1.8 x 10^4 player-submitted sequencesacross 724 unique targets.
Edit intent: clarity
Original:  Here, we present an RNA design agent , SentRNA, which consists of a fully-connected neural network trained using the eternasolves dataset, a set of 1.8 x 10^4 player-submitted sequencesacross 724 unique targets.
Revised:  Here, we present an RNA design agent , SentRNA, a design agent consisting of a fully-connected neural network trained using the eternasolves dataset, a set of 1.8 x 10^4 player-submitted sequencesacross 724 unique targets.
Edit intent: clarity
Original:  Here, we present an RNA design agent , SentRNA, which consists of a fully-connected neural network trained using the eternasolves dataset, a set of 1.8 x 10^4 player-submitted sequencesacross 724 unique targets. The agent first predicts an initial sequence for a target using the trained network, and then refines that solution if necessary using a short adaptive walk utilizing a canon of standard design moves. Through this approach, we observe SentRNA can learn and apply human-like design strategies to solve several complex targets previously unsolvable by any computational approach .
Revised:  Here, we present an RNA design agent , SentRNA, which consists of a fully-connected neural network trained end-to-end using human-designed RNA sequences. We show that through this approach, we observe SentRNA can learn and apply human-like design strategies to solve several complex targets previously unsolvable by any computational approach .
Edit intent: clarity
Original:  Through this approach, we observe SentRNA can learn and apply human-like design strategies to solve several complex targets previously unsolvable by any computational approach . We thus demonstrate that incorporating a prior of human design strategies into a computational agent can significantly boost its performance , and suggests a new paradigm for machine-based RNA design.
Revised:  Through this approach, we observe SentRNA can learn and apply human-like design strategies to solve several complex targets previously unsolvable by any machine-based approach and achieve state-of-the-art performance on two separate challenging test sets. Our results demonstrate that incorporating a prior of human design strategies into a computational agent can significantly boost its performance , and suggests a new paradigm for machine-based RNA design.
Edit intent: meaning-changed
Original: State-of-the-art machine learning systems rely on graph-based models, with the distributed training of these models being the norm in AI-powered production pipelines. The performance of these communication-heavy systems depends on the effective overlap of communication and computation.
Revised: State-of-the-art machine learning systems rely on iterative distributed training to tackle the increasing complexity of models and input data. The iteration time in these communication-heavy systems depends on the effective overlap of communication and computation.
Edit intent: clarity
Original:  In this work, we  develop a system for communication scheduling which realizes near-optimal overlap of communication and computation in graph-based models.
Revised:  In this work, we identify a shortcoming in systems with graph representation for computation, such as TensorFlow and PyTorch, that result in high variance in iteration time --- random order of received parameters across workers. We develop a system for communication scheduling which realizes near-optimal overlap of communication and computation in graph-based models.
Edit intent: meaning-changed
Original:  Our system improves the throughput by up to 82\% in inference and 20\% in training, while also reducing straggler effect by up to 2.8x. A part of our implementation is already merged with TensorFlow codebase;
Revised:  TicTac improves the throughput by up to 82\% in inference and 20\% in training, while also reducing straggler effect by up to 2.8x. A part of our implementation is already merged with TensorFlow codebase;
Edit intent: clarity
Original:  While analysis with a standard worm-like chain model suggests that the persistence length of collagen can attain almost any value within the literature range, closer inspection reveals that this modulation of collagen's conformational behaviour is not due to changes in flexibility, but rather arises from the induction of curvature (either intrinsic or induced by interactions with the mica surface).
Revised:  While analysis with a standard worm-like chain model suggests that the persistence length of collagen can attain almost any value within the literature range, closer inspection reveals that this modulation of collagen's conformational behavior is not due to changes in flexibility, but rather arises from the induction of curvature (either intrinsic or induced by interactions with the mica surface).
Edit intent: fluency
Original: Droplets that are driven away from thermal equilibrium by chemical reactions can exhibit rich dynamic behaviors.
Revised: We study the hydrodynamics and shape changes of chemically active droplets. In non-spherical droplets, surface tension generates hydrodynamic flows that drive liquid droplets into a spherical shape. Here we show that spherical droplets that are maintained away from thermodynamic equilibrium by chemical reactions can exhibit rich dynamic behaviors.
Edit intent: meaning-changed
Original: Droplets that are driven away from thermal equilibrium by chemical reactions can exhibit rich dynamic behaviors. When droplet material turns over by chemical reactions a spherical droplet can become unstable and divide spontaneously. We study the effects of hydrodynamic flows in this droplet division.
Revised: Droplets that are driven away from thermal equilibrium by chemical reactions may not remain spherical but can undergo a shape instability which can lead to spontaneous droplet division.
Edit intent: clarity
Original:  We solve the reaction diffusion equations of a phase separating system coupled to hydrodynamic flowsand determine stability diagrams of  droplets as a function of dimensionless viscosity and reaction parameters.
Revised:  In this case chemical activity acts against surface tension and tension-induced hydrodynamic flows. By combining low Reynolds-number hydrodynamics with phase separation dynamics and chemical reaction kinetics we determine stability diagrams of droplets as a function of dimensionless viscosity and reaction parameters.
Edit intent: meaning-changed
Original:  We solve the reaction diffusion equations of a phase separating system coupled to hydrodynamic flowsand determine stability diagrams of  droplets as a function of dimensionless viscosity and reaction parameters.
Revised:  We solve the reaction diffusion equations of a phase separating system coupled to hydrodynamic flowsand determine stability diagrams of spherical droplets as a function of dimensionless viscosity and reaction parameters.
Edit intent: meaning-changed
Original:  We show that hydrodynamics tends to stabilize spherical droplets but that droplet division occurs for sufficiently strong chemical driving, sufficiently large droplet viscosity or sufficiently small surface tension.
Revised:  We determine concentration and flow fields inside and outside the droplets during shape changes and division. Our work shows that hydrodynamic flows tends to stabilize spherical droplets but that droplet division occurs for sufficiently strong chemical driving, sufficiently large droplet viscosity or sufficiently small surface tension.
Edit intent: meaning-changed
Original:  Our work suggests that chemically driven droplet division could be observable in soft colloidal systems with low surface tension such as RNA-protein dropletsin vitro or inside cells .
Revised:  Active droplets could provide simple models for prebiotic protocells that are able to proliferate. Our work captures the key hydrodynamics of droplet division that could be observable in soft colloidal systems with low surface tension such as RNA-protein dropletsin vitro or inside cells .
Edit intent: meaning-changed
Original: In this paper we consider Contact graphs of Paths on a Grid (CPG graphs), i.e. graphs for which there exists a family of interiorly disjoint paths on a grid in one-to-one correspondance with their vertex set such that two vertices are adjacent if and only if the corresponding paths touch at a grid-point.
Revised: In this paper we consider Contact graphs of Paths on a Grid (CPG graphs), i.e. graphs for which there exists a family of interiorly disjoint paths on a grid in one-to-one correspondence with their vertex set such that two vertices are adjacent if and only if the corresponding paths touch at a grid-point.
Edit intent: fluency
Original:  We further investigate the relation between planar graphs and CPG graphs and show that CPG graphs are not necessarily planar and not all planar graphs are CPG . Our class generalizes the well studied class of VCPG graphs .
Revised:  Moreover, we investigate the recognition and 3-colorability problems for B_0-CPG, a subclass of CPG. We further show that CPG graphs are not necessarily planar and not all planar graphs are CPG . Our class generalizes the well studied class of VCPG graphs .
Edit intent: meaning-changed
Original:  Interestingly, no previous authors studied line simplification under these measures in its pure form, namely: for a given \epsilon > 0, choose a minimum size subsequence of the vertices of the input such that the Hausdorff or Fr\'echet distance between the input and output polylines is at most \epsilon .
Revised:  Interestingly, no previous authors studied line simplification under these measures in its pure form, namely: for a given \epsilon > 0, choose a minimum size subsequence of the vertices of the input such that the Hausdorff or Fr\'echet distance between the input and output polylines is at most \epsilon .
Edit intent: fluency
Original:  We analyze how the well-known Douglas-Peucker and Imai-Iri simplification algorithms perform compared to the optimum possible, also in the situation where the algorithms are given a considerably larger error threshold than \epsilon .
Revised:  We analyze how the well-known Douglas-Peucker and Imai-Iri simplification algorithms perform compared to the optimum possible, also in the situation where the algorithms are given a considerably larger error threshold than \epsilon .
Edit intent: fluency
Original:  Interestingly, no previous authors studied line simplification under these measures in its pure form, namely: for a given \epsilon > 0, choose a minimum size subsequence of the vertices of the input such that the Hausdorff or Fr\'echet distance between the input and output polylines is at most \epsilon .
Revised:  Interestingly, no previous authors studied line simplification under these measures in its pure form, namely: for a given \varepsilon > 0, choose a minimum size subsequence of the vertices of the input such that the Hausdorff or Fr\'echet distance between the input and output polylines is at most \epsilon .
Edit intent: clarity
Original:  Interestingly, no previous authors studied line simplification under these measures in its pure form, namely: for a given \epsilon > 0, choose a minimum size subsequence of the vertices of the input such that the Hausdorff or Fr\'echet distance between the input and output polylines is at most \epsilon .
Revised:  Interestingly, no previous authors studied line simplification under these measures in its pure form, namely: for a given \epsilon > 0, choose a minimum size subsequence of the vertices of the input such that the Hausdorff or Fr\'echet distance between the input and output polylines is at most \varepsilon .
Edit intent: clarity
Original:  We analyze how the well-known Douglas-Peucker and Imai-Iri simplification algorithms perform compared to the optimum possible, also in the situation where the algorithms are given a considerably larger error threshold than \epsilon .
Revised:  We analyze how the well-known Douglas-Peucker and Imai-Iri simplification algorithms perform compared to the optimum possible, also in the situation where the algorithms are given a considerably larger error threshold than \varepsilon .
Edit intent: meaning-changed
Original: The occurrence of drug-drug-interactions (DDI) from multiple drug dispensations is a serious problem, both for individuals and health-care systems, since patients with complications due to DDI are likely to re-enter the system at a costlier level.
Revised: The occurrence of drug-drug-interactions (DDI) from multiple drug dispensations is a serious problem, both for individuals and health-care systems, since patients with complications due to DDI are likely to reenter the system at a costlier level.
Edit intent: fluency
Original:  We present a large-scale longitudinal study (18 months) of the DDI phenomenon at the primary- and secondary-care level using electronic health records (EHR) from the city of Blumenau in Southern Brazil (pop. ~ 340,000).
Revised:  We present a large-scale longitudinal study (18 months) of the DDI phenomenon at the primary- and secondary-care level using electronic health records (EHR) from the city of Blumenau in Southern Brazil (pop. \approx 340,000).
Edit intent: clarity
Original:  We found that 181 distinct drug pairs known to interact were dispensed concomitantly to 12 \% of the patients in the city's public health-care system. Further, 4\% of the patients were dispensed DDI combinations, likely to result in major adverse reactions with costs estimated to be larger than previously reported in smaller studies. DDI results are integrated into associative networks for inference and visualization, revealing key medications and interactions involved in the DDI phenomenon. Analysis reveals that women have a 60\% increased risk of DDI as compared to men; the increase becomes 90\% when only major DDI are considered. Furthermore, DDI risk increases substantially with age. Patients aged 70-79 years have a 34\% risk of DDI when they are dispensed two or more drugs concomitantly. Interestingly, a null model demonstrates that age- and women-specific risks from increased polypharmacy fail by far to explain the observed risks of DDI in those populations. This suggests that social and biological factors are at play. These results demonstrate that considerable gender and age biases exist, but that accurate warning systems for known DDI can be devised for health-care systems and public-health policy management, to reduce DDI-related adverse reactions and health-care costs.
Revised:  We found that 181 distinct drug pairs known to interact were dispensed concomitantly to 12 
Edit intent: meaning-changed
Original:  We find  that dynamic cache instantiation has the potential to provide substantial cost reductions in some cases, but that this potential is strongly dependent on the object popularity skew . We also find that selective "Cache on k-th request" cache insertion policies can be even more beneficial in this context than with conventional edge caches  .
Revised:  We find that dynamic cache instantiation has the potential to provide substantial cost reductions in some cases, but that this potential is strongly dependent on the object popularity skew , and that selective cache insertion can be even more beneficial in this context than with conventional edge caches .
Edit intent: clarity
Original:  We also find that selective "Cache on k-th request" cache insertion policies can be even more beneficial in this context than with conventional edge caches  .
Revised:  We also find that selective "Cache on k-th request" cache insertion policies can be even more beneficial in this context than with conventional edge caches . Finally, our contributions also include accurate and easy-to-compute approximations that are shown applicable to LRU caches under time-varying workloads .
Edit intent: meaning-changed
Original:  Here, we address an algorithmic trading problem with collections of heterogeneous agents who aim to perform  statistical arbitrage, where all agents filter the latent states of the world, and their trading actions have permanent and temporary price impact.
Revised:  Here, we address an algorithmic trading problem with collections of heterogeneous agents who aim to perform optimal execution or statistical arbitrage, where all agents filter the latent states of the world, and their trading actions have permanent and temporary price impact.
Edit intent: meaning-changed
Original:  We solve the stochastic game by investigating its mean-field game (MFG) limit, with sub-populations of heterogenous agents, and, using a convex analysis approach, we show that the solution is characterized by a vector-valued forward-backward stochastic differential equation (FBSDE).
Revised:  We solve the stochastic game by investigating its mean-field game (MFG) limit, with sub-populations of heterogeneous agents, and, using a convex analysis approach, we show that the solution is characterized by a vector-valued forward-backward stochastic differential equation (FBSDE).
Edit intent: fluency