wanyu/IteraTeR_v2 huggingface dataset:
Original:  To address this issue, we built a mathematical model of RAS based on data about protein and peptide concentrations in normotensive and hypertensive individuals.
Revised:  In this context, we developed a mathematical model of RAS based on data about protein and peptide concentrations in normotensive and hypertensive individuals.
Edit intent: clarity
Original:  To address this issue, we built a mathematical model of RAS based on data about protein and peptide concentrations in normotensive and hypertensive individuals.
Revised:  To address this issue, we built a mathematical model of RAS based on data regarding protein and peptide concentrations in normotensive and hypertensive individuals.
Edit intent: fluency
Original:  We applied our model to analyze the impact of SARS-CoV-2 infection on the RASsystem , which we modeled through a downregulation of ACE2 related to viral load.
Revised:  We applied our model to analyze the impact of SARS-CoV-2 infection on RAS , which we modeled through a downregulation of ACE2 related to viral load.
Edit intent: clarity
Original: The study presents a neural network , which uses filters based on logistic mapping (LogNNet).
Revised: This study presents a neural network , which uses filters based on logistic mapping (LogNNet).
Edit intent: fluency
Original: The study presents a neural network , which uses filters based on logistic mapping (LogNNet).
Revised: The study presents a neural network which uses filters based on logistic mapping (LogNNet).
Edit intent: fluency
Original:  The most effective MNIST handwritten digit recognition occurs under chaotic behavior of  logistic map.
Revised:  The most effective MNIST handwritten digit recognition occurs under chaotic behavior of the logistic map.
Edit intent: fluency
Original:   An advantage of LogNNet implementation on IoT Devices is the significant savings in used memory (more than 10 times) compared to other neural networks .
Revised:  An advantage of LogNNet implementation on IoT devices is the significant savings in used memory (more than 10 times) compared to other neural networks .
Edit intent: fluency
Original:  The presented network architecture uses an array of weights with a total memory size from 1 kB to 29 kB and achieves a classification accuracy of 80.3-96.3\%  .
Revised:  The presented network architecture uses an array of weights with a total memory size from 1 to 29 kB and achieves a classification accuracy of 80.3-96.3\% .
Edit intent: fluency
Original: In December 2019, a newly discovered SARS-CoV-2 virus  emerged from China and propagated worldwide as a pandemic , resulting in about 35 percent mortality .
Revised: In December 2019, a newly discovered SARS-CoV-2 virus was emerged from China and propagated worldwide as a pandemic , resulting in about 35 percent mortality .
Edit intent: clarity
Original: In December 2019, a newly discovered SARS-CoV-2 virus  emerged from China and propagated worldwide as a pandemic , resulting in about 35 percent mortality .
Revised: In December 2019, a newly discovered SARS-CoV-2 virus emerged from China and propagated worldwide as a pandemic .
Edit intent: coherence
Original:  We present the design of TASM, a tile-aware storage manager, and describe techniques it uses to optimize the physical layout of videos for various query workloads.
Revised:  We present the design of TASM, a tile-based storage manager, and describe techniques it uses to optimize the physical layout of videos for various query workloads.
Edit intent: clarity
Original:  We propose utilizing a feature in modern video codecs called "tiles" to enable spatial random access into encoded videos.
Revised:  We propose utilizing a feature in modern video codecs called "tiles" that enables spatial random access into encoded videos.
Edit intent: fluency
Original:  Layouts picked by TASM speed up individual queries by an average of 51 \% and up to 94\% while maintaining good quality .
Revised:  Layouts picked by TASM speed up individual queries by an average of over 50 \% and up to 94\% while maintaining good quality .
Edit intent: clarity
Original:  Stan is an expressive probabilistic programing language that abstracts the inference and allows users to focus on the modeling.
Revised:  Stan is an expressive probabilistic programming language that abstracts the inference and allows users to focus on the modeling.
Edit intent: fluency
Original:  The resulting code is readable and easily extensible, which makes the modeler's work more transparent and flexible.
Revised:  As a result, Stan code is readable and easily extensible, which makes the modeler's work more transparent and flexible.
Edit intent: clarity
Original:  In this tutorial, we demonstrate with a simple Susceptible-Infected-Recovered (SIR) model how to formulate, fit, and diagnose a compartmental  model in Stan  .
Revised:  In this tutorial, we demonstrate how to formulate, fit, and diagnose a compartmental model in Stan .
Edit intent: coherence
Original:  In this tutorial, we demonstrate with a simple Susceptible-Infected-Recovered (SIR) model how to formulate, fit, and diagnose a compartmental  model in Stan  .
Revised:  In this tutorial, we demonstrate with a simple Susceptible-Infected-Recovered (SIR) model how to formulate, fit, and diagnose a compartmental transmission model in Stan .
Edit intent: clarity
Original:  We also introduce more advanced topics which can  help practitioners fit sophisticated models;
Revised:  We also cover advanced topics which can help practitioners fit sophisticated models;
Edit intent: clarity
Original:  We also introduce more advanced topics which can  help practitioners fit sophisticated models;
Revised:  We also introduce more advanced topics which can further help practitioners fit sophisticated models;
Edit intent: clarity
Original:  notably, how to use simulations to probe our model and our priors, and computational techniques to scale ODE-based models .
Revised:  notably, how to use simulations to probe the model and priors, and computational techniques to scale ODE-based models .
Edit intent: clarity
Original: We present an integer programming model to compute the strong rainbow connection number  src(G)  of any simple graph G. We introduce several enhancements to the proposed model, including a fast heuristic, a novel class of valid inequalities, and a variable elimination scheme.
Revised: We present an integer programming model to compute the strong rainbow connection number , src(G) of any simple graph G. We introduce several enhancements to the proposed model, including a fast heuristic, a novel class of valid inequalities, and a variable elimination scheme.
Edit intent: fluency
Original: We present an integer programming model to compute the strong rainbow connection number  src(G)  of any simple graph G. We introduce several enhancements to the proposed model, including a fast heuristic, a novel class of valid inequalities, and a variable elimination scheme.
Revised: We present an integer programming model to compute the strong rainbow connection number src(G) , of any simple graph G. We introduce several enhancements to the proposed model, including a fast heuristic, a novel class of valid inequalities, and a variable elimination scheme.
Edit intent: fluency
Original: We present an integer programming model to compute the strong rainbow connection number  src(G)  of any simple graph G. We introduce several enhancements to the proposed model, including a fast heuristic, a novel class of valid inequalities, and a variable elimination scheme.
Revised: We present an integer programming model to compute the strong rainbow connection number src(G) of any simple graph G. We introduce several enhancements to the proposed model, including a fast heuristic, and a variable elimination scheme.
Edit intent: coherence
Original:  We evaluate our model with a traditional branch and cut approach as well as an alternative scheme based on iterative lower bound improvement,  which we show to be highly effective in practice.
Revised:  We evaluate our model with a traditional branch and cut approach as well as an alternative scheme based on iterative lower bound improvement, the latter of which we show to be highly effective in practice.
Edit intent: clarity
Original:  This answers a specific case of a question posed by  Baird et al. on the minimum order of 4-cop-win graphs, first appearing in 2011.
Revised:  This answers a question posed by Baird et al. on the minimum order of 4-cop-win graphs, first appearing in 2011.
Edit intent: clarity
Original:  This answers a specific case of a question posed by  Baird et al. on the minimum order of 4-cop-win graphs, first appearing in 2011.
Revised:  This answers a specific case of a question posed by Baird et al. 
Edit intent: coherence
Original:  We also find all 3-cop-win graphs on 11 vertices, narrow down the possible 4-cop-win graphs on 19 vertices and get some progress on finding the minimum order of 3-cop-win planar graphs.
Revised:  We also find all 3-cop-win graphs on 11 vertices, narrow down the possible 4-cop-win graphs on 19 vertices and make some progress on finding the minimum order of 3-cop-win planar graphs.
Edit intent: clarity
Original: Reproducible workflow solutions commonly use high-level technologies that were popular when they were created, providing an immediate solution which is unlikely to be  sustainable in the long term.
Revised: Analysis pipelines commonly use high-level technologies that were popular when they were created, providing an immediate solution which is unlikely to be sustainable in the long term.
Edit intent: clarity
Original: Reproducible workflow solutions commonly use high-level technologies that were popular when they were created, providing an immediate solution which is unlikely to be  sustainable in the long term.
Revised: Reproducible workflow solutions commonly use high-level technologies that are popular when created, but are unlikely to be sustainable in the long term.
Edit intent: clarity
Original:  We therefore introduce a set of criteria  to address this problem and demonstrate their practicality and implementation.
Revised:  A set of criteria to address this problem and demonstrate their practicality and implementation.
Edit intent: coherence
Original:  We therefore introduce a set of criteria  to address this problem and demonstrate their practicality and implementation.
Revised:  We therefore introduce a set of criteria is introduced to address this problem and demonstrate their practicality and implementation.
Edit intent: clarity
Original:  The criteria have been tested in several research publications and can be summarized as: completeness (no dependency beyond a POSIX-compatible operating system, no administrator privileges, no network connection  and storage primarily in plain text);
Revised:  The criteria have been tested in several research publications and can be summarized as: completeness (no dependency beyond a POSIX-compatible operating system, no administrator privileges, no network connection , and storage primarily in plain text);
Edit intent: fluency
Original:  and free-and-open-source software.
Revised:  and free software.
Edit intent: clarity
Original:  As a proof of concept, we have implemented "Maneage" , a solution which stores the project in machine-actionable and human-readable plain-text, enables version-control, cheap archiving, automatic parsing to extract data provenance , and peer-reviewable verification .
Revised:  As a proof of concept, we introduce "Maneage" , a solution which stores the project in machine-actionable and human-readable plain-text, enables version-control, cheap archiving, automatic parsing to extract data provenance , and peer-reviewable verification .
Edit intent: clarity
Original:  As a proof of concept, we have implemented "Maneage" , a solution which stores the project in machine-actionable and human-readable plain-text, enables version-control, cheap archiving, automatic parsing to extract data provenance , and peer-reviewable verification .
Revised:  As a proof of concept, we have implemented "Maneage" (Managing data lineage), enabling cheap archiving, automatic parsing to extract data provenance , and peer-reviewable verification .
Edit intent: clarity
Original:  We show that requiring longevity of a reproducible workflow solution is realistic, without sacrificing immediate or short-term reproducibility and discuss the benefits of the criteria for scientific progress .
Revised:  We show that longevity is a realistic requirement that does not sacrifice immediate or short-term reproducibility and discuss the benefits of the criteria for scientific progress .
Edit intent: clarity
Original:  We show that requiring longevity of a reproducible workflow solution is realistic, without sacrificing immediate or short-term reproducibility and discuss the benefits of the criteria for scientific progress .
Revised:  We show that requiring longevity of a reproducible workflow solution is realistic, without sacrificing immediate or short-term reproducibility . The caveats (with proposed solutions) are then discussed and we conclude with the benefits for the various stakeholders .
Edit intent: coherence
Original: Online community moderators often rely on social signals like whether or not a user has an account or a profile page as clues that users are likely to cause problems.
Revised: Online community moderators often rely on social signals such as whether or not a user has an account or a profile page as clues that users are likely to cause problems.
Edit intent: fluency
Original: Online community moderators often rely on social signals like whether or not a user has an account or a profile page as clues that users are likely to cause problems.
Revised: Online community moderators often rely on social signals like whether or not a user has an account or a profile page as clues that users may cause problems.
Edit intent: clarity
Original:  Reliance on these clues may lead to "over-profiling" bias when moderators focus on these signals but overlook misbehavior by others.
Revised:  Reliance on these clues can lead to overprofiling bias when moderators focus on these signals but overlook misbehavior by others.
Edit intent: clarity
Original:  Reliance on these clues may lead to "over-profiling" bias when moderators focus on these signals but overlook misbehavior by others.
Revised:  Reliance on these clues may lead to "over-profiling" bias when moderators focus on these signals but overlook the misbehavior of others.
Edit intent: fluency
Original:  We analyze moderator behavior in Wikipedia as mediated by a system called RCFilters that displays social signals and algorithmic flags and to estimate the causal effect of being flagged on moderator actions.
Revised:  We analyze moderator behavior in Wikipedia as mediated by RCFilters, a system which displays social signals and algorithmic flags and to estimate the causal effect of being flagged on moderator actions.
Edit intent: clarity
Original:  We analyze moderator behavior in Wikipedia as mediated by a system called RCFilters that displays social signals and algorithmic flags and to estimate the causal effect of being flagged on moderator actions.
Revised:  We analyze moderator behavior in Wikipedia as mediated by a system called RCFilters that displays social signals and algorithmic flags , and estimate the causal effect of being flagged on moderator actions.
Edit intent: coherence
Original:  We show that algorithmically flagged edits are reverted more often, especially edits by established editors with positive social signals, and that flagging decreases the likelihood that moderation actions will be undone.
Revised:  We show that algorithmically flagged edits are reverted more often, especially those by established editors with positive social signals, and that flagging decreases the likelihood that moderation actions will be undone.
Edit intent: clarity
Original:  We find a striking relationship between the negative variation of mobility flows and the net reproduction number , in all Italian regions, between March 11th and March 18th, when the country entered the lockdown.
Revised:  We find a striking relationship between the decrease in mobility flows and the net reproduction number , in all Italian regions, between March 11th and March 18th, when the country entered the lockdown.
Edit intent: clarity
Original:  This observation allows us to quantify the time needed to "switch off " the country mobility (one week) and the time required to bring the net reproduction number below  1 (one week).
Revised:  This observation allows us to quantify the time needed to switch off mobility and bring the net reproduction number below 1 (one week).
Edit intent: clarity
Original:  Our study demonstrates the value of "big " mobility data to the monitoring of key epidemic indicators to inform choices as the epidemics unfolds in the coming months .
Revised:  Our study demonstrates the value of big mobility data to the monitoring of key epidemic indicators to inform choices as the epidemics unfolds in the coming months .
Edit intent: fluency
Original:  Our study demonstrates the value of "big " mobility data to the monitoring of key epidemic indicators to inform choices as the epidemics unfolds in the coming months .
Revised:  Our study demonstrates the value of "big " mobility data to monitor the epidemic and inform control interventions during its unfolding .
Edit intent: clarity
Original: Learned Bloom filters enhance standard Bloom filters by using a learned model for the represented data set.
Revised: Learned Bloom filters enhance standard Bloom filters by using a learned model for the represented set.
Edit intent: clarity
Original:  However, a learned Bloom filter may under-utilize the model by not taking full advantage of the output.
Revised:  However, previous methods for learned Bloom filters do not take full advantage of the output.
Edit intent: clarity
Original:  However, the benefits of novel activation functions have been inconsistent and task-dependent , and therefore the rectified linear unit (ReLU) is still the most commonly used.
Revised:  However, the benefits of novel activation functions have been inconsistent and task dependent , and therefore the rectified linear unit (ReLU) is still the most commonly used.
Edit intent: fluency
Original:  It discovers different activation functions for different architectures, and consistently improves accuracy over ReLU and other recently proposed activation functions by significant margins.
Revised:  It discovers different activation functions for different architectures, consistently improving accuracy over ReLU and other recently proposed activation functions by significant margins.
Edit intent: coherence
Original:  It discovers different activation functions for different architectures, and consistently improves accuracy over ReLU and other recently proposed activation functions by significant margins.
Revised:  It discovers different activation functions for different architectures, and consistently improves accuracy over ReLU and other recently-proposed activation functions by significant margins.
Edit intent: fluency
Original:  Experiments with three different neural network architectures on the  CIFAR-100 image classification dataset show that this approach is effective.
Revised:  Experiments with three different neural network architectures on the CIFAR-100 image classification datasets show that this approach is effective.
Edit intent: fluency
Original:  It discovers both general activation functions and specialized functions for different architectures, consistently improving accuracy over ReLU and other recently-proposed activation functions by significant margins.
Revised:  It discovers both general activation functions and specialized functions for different architectures, consistently improving accuracy over ReLU and other recently proposed activation functions by significant margins.
Edit intent: fluency
Original:  It discovers both general activation functions and specialized functions for different architectures, consistently improving accuracy over ReLU and other recently proposed activation functions by significant margins.
Revised:  It discovers both general activation functions and specialized functions for different architectures, consistently improving accuracy over ReLU and other activation functions by significant margins.
Edit intent: clarity
Original: Millions of sensors, mobile applications and machines are now generating billions of events.
Revised: Millions of sensors, mobile applications and machines now generate billions of events.
Edit intent: clarity
Original:  This has led to specialized many-core key-value stores (KVSs) that can ingest and index these events at high rates (  100 Mops/s /machine) .
Revised:  Specialized many-core key-value stores (KVSs) that can ingest and index these events at high rates ( 100 Mops/s /machine) .
Edit intent: coherence
Original:  This has led to specialized many-core key-value stores (KVSs) that can ingest and index these events at high rates (  100 Mops/s /machine) .
Revised:  This has led to specialized many-core key-value stores (KVSs) can ingest and index these events at high rates ( 100 Mops/s /machine) .
Edit intent: fluency
Original:  This has led to specialized many-core key-value stores (KVSs) that can ingest and index these events at high rates (  100 Mops/s /machine) .
Revised:  This has led to specialized many-core key-value stores (KVSs) that can ingest and index these events at high rates ( over 100 Mops/s /machine) .
Edit intent: clarity
Original:  These systems are efficient if events are generated on the same machine , but, to be practical and cost-effective they must ingest events over the network and scale across cloud resources elastically.
Revised:  These systems are efficient if events are generated on the same machine ; however, to be practical and cost-effective they must ingest events over the network and scale across cloud resources elastically.
Edit intent: fluency
Original:  Hence, Shadowfax can shift load in 17 s to improve cluster throughput by 10 \% with little disruption.
Revised:  Hence, Shadowfax can shift load in 17 s to improve system throughput by 10 \% with little disruption.
Edit intent: clarity
Original:  The oracle model assumes conditional expected marginal profit of any node could be obtained in O(1) time and a (1-1/e) -approximation algorithm is proposed.
Revised:  The oracle model assumes conditional expected marginal profit of any node could be obtained in O(1) time and a (1-1/e) expected approximation policy is proposed.
Edit intent: clarity
Original:  Experimental results on three real-world datasets show efficiencies and superiorities of our algorithm .
Revised:  Experimental results show efficiencies and superiorities of our algorithm .
Edit intent: clarity
Original:  Experimental results on three real-world datasets show efficiencies and superiorities of our algorithm .
Revised:  Experimental results on three real-world datasets show efficiencies and superiorities of our policies .
Edit intent: clarity
Original:  Currently, two main routes of learning exist, including neuroscience-inspired methods , represented by local synaptic plasticity, and machine-learning methods, represented by backpropagation .
Revised:  Currently, two main routes of learning methods exist at present including neuroscience-inspired methods , represented by local synaptic plasticity, and machine-learning methods, represented by backpropagation .
Edit intent: clarity
Original:  Currently, two main routes of learning exist, including neuroscience-inspired methods , represented by local synaptic plasticity, and machine-learning methods, represented by backpropagation .
Revised:  Currently, two main routes of learning exist, including neuroscience-inspired methods and machine learning methods .
Edit intent: clarity
Original:  Both have advantages and complement each other , but neither  can solve all learning problems well.
Revised:  Both have own advantages , but neither can solve all learning problems well.
Edit intent: clarity