wanyu/IteraTeR_v2 huggingface dataset:
Original:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics ;
Revised:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics ,
Edit intent: fluency
Original:  however, its direct application is limited to small-scale systems  of no more than two vehicles because of the exponential-scaling computation complexity.
Revised:  however, its direct application is limited to small-scale systems typically of no more than two vehicles because of the exponential-scaling computation complexity.
Edit intent: clarity
Original:  however, its direct application is limited to small-scale systems  of no more than two vehicles because of the exponential-scaling computation complexity.
Revised:  however, its direct application is limited to small-scale systems of no more than two vehicles because of the exponentially-scaling computation complexity.
Edit intent: fluency
Original:  By assigning vehicle priorities , the sequential path planning (SPP) method  allows multi-vehicle path planning to be done with a computation complexity that scales linearly with the number of vehicles.
Revised:  Previously , the sequential path planning (SPP) method allows multi-vehicle path planning to be done with a computation complexity that scales linearly with the number of vehicles.
Edit intent: coherence
Original:  In this paper, we make SPP more practical by providing three different methods for accounting for disturbances in dynamics and imperfect knowledge of higher-priority vehicles  . Each method has advantages and disadvantages with different assumptions about information sharing.
Revised:  In this paper, we make SPP more practical by providing three different methods to account for disturbances in dynamics and imperfect knowledge of higher-priority vehicles . Each method has advantages and disadvantages with different assumptions about information sharing.
Edit intent: fluency
Original:  In this paper, we make SPP more practical by providing three different methods for accounting for disturbances in dynamics and imperfect knowledge of higher-priority vehicles  . Each method has advantages and disadvantages with different assumptions about information sharing.
Revised:  In this paper, we make SPP more practical by providing three different methods for accounting for disturbances in dynamics and imperfect knowledge of higher-priority vehicles ' states . Each method has advantages and disadvantages with different assumptions about information sharing.
Edit intent: clarity
Original:  In this paper, we make SPP more practical by providing three different methods for accounting for disturbances in dynamics and imperfect knowledge of higher-priority vehicles  . Each method has advantages and disadvantages with different assumptions about information sharing.
Revised:  In this paper, we make SPP more practical by providing three different methods for accounting for disturbances in dynamics and imperfect knowledge of higher-priority vehicles . Each method has different assumptions about information sharing.
Edit intent: coherence
Original: Multi-UAV systems are safety-critical, and guarantees must be made to ensure no undesirable configurations such as collisions occur.
Revised: Multi-UAV systems are safety-critical, and guarantees must be made to ensure no unsafe configurations occur.
Edit intent: clarity
Original:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics, however, its direct application is limited to small-scale systems typically of no more than two vehicles because of the exponentially-scaling computation complexity.
Revised:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems ; however, its direct application is limited to small-scale systems typically of no more than two vehicles because of the exponentially-scaling computation complexity.
Edit intent: coherence
Original:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics, however, its direct application is limited to small-scale systems typically of no more than two vehicles because of the exponentially-scaling computation complexity.
Revised:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics, however, its direct application is limited to small-scale systems of no more than two vehicles because of the exponentially-scaling computation complexity.
Edit intent: clarity
Original:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics, however, its direct application is limited to small-scale systems typically of no more than two vehicles because of the exponentially-scaling computation complexity.
Revised:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics, however, its direct application is limited to small-scale systems typically of no more than two vehicles due to an exponentially-scaling computation complexity.
Edit intent: clarity
Original:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics, however, its direct application is limited to small-scale systems typically of no more than two vehicles because of the exponentially-scaling computation complexity.
Revised:  Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems because it provides safety guarantees and is flexible in terms of system dynamics, however, its direct application is limited to small-scale systems typically of no more than two vehicles because of the exponentially-scaling computational complexity.
Edit intent: fluency
Original:  Previously, the sequential path planning (SPP) method, which assigns strict priorities to vehicles, was proposed , SPP allows multi-vehicle path planning to be done with a linearly-scaling computation complexity.
Revised:  Previously, the sequential path planning (SPP) method, which assigns strict priorities to vehicles, was proposed ; SPP allows multi-vehicle path planning to be done with a linearly-scaling computation complexity.
Edit intent: fluency
Original:  Previously, the sequential path planning (SPP) method, which assigns strict priorities to vehicles, was proposed , SPP allows multi-vehicle path planning to be done with a linearly-scaling computation complexity.
Revised:  Previously, the sequential path planning (SPP) method, which assigns strict priorities to vehicles, was proposed , SPP allows multi-vehicle path planning to be done with a linearly-scaling computational complexity.
Edit intent: fluency
Original:  However, the previous SPP formulation assumed that there are no disturbances in the vehicle dynamics , and that every vehicle has perfect knowledge of the position of higher-priority vehicles  .
Revised:  However, the previous formulation assumed that there are no disturbances in the vehicle dynamics , and that every vehicle has perfect knowledge of the position of higher-priority vehicles .
Edit intent: clarity
Original:  However, the previous SPP formulation assumed that there are no disturbances in the vehicle dynamics , and that every vehicle has perfect knowledge of the position of higher-priority vehicles  .
Revised:  However, the previous SPP formulation assumed that there are no disturbances , and that every vehicle has perfect knowledge of the position of higher-priority vehicles .
Edit intent: clarity
Original:  However, the previous SPP formulation assumed that there are no disturbances in the vehicle dynamics , and that every vehicle has perfect knowledge of the position of higher-priority vehicles  .
Revised:  However, the previous SPP formulation assumed that there are no disturbances in the vehicle dynamics , and that every vehicle has perfect knowledge of higher-priority vehicles .
Edit intent: clarity
Original:  However, the previous SPP formulation assumed that there are no disturbances in the vehicle dynamics , and that every vehicle has perfect knowledge of the position of higher-priority vehicles  .
Revised:  However, the previous SPP formulation assumed that there are no disturbances in the vehicle dynamics , and that every vehicle has perfect knowledge of the position of higher-priority vehicles ' positions .
Edit intent: clarity
Original:  It is shown that an optimal vector in a least-squares sense can be found by solving a convex problem, thus establishing a hidden convexity in Fourier phase retrieval.
Revised:  We show that an optimal vector in a least-squares sense can be found by solving a convex problem, thus establishing a hidden convexity in Fourier phase retrieval.
Edit intent: coherence
Original:  It is also shown that the standard semidefinite relaxation approach yields the optimal cost function value (albeit not necessarily an optimal solution) in this case.
Revised:  We also show that the standard semidefinite relaxation approach yields the optimal cost function value (albeit not necessarily an optimal solution) in this case.
Edit intent: coherence
Original:  We find that increasing the number of binding sites induces noisy oscillations of gene products.
Revised:  We find that increasing the number of binding sites induces regular bursting of gene products.
Edit intent: clarity
Original: We introduce an intuitive mechanism to describe both the emergence of community structure and the evolution of the internal structure of communities in  social networks.
Revised: We introduce an intuitive model that describes both the emergence of community structure and the evolution of the internal structure of communities in social networks.
Edit intent: clarity
Original:  Our idea is based on the simple assumption that each individual can, for every social group to which it belongs, develop connections and introduce new members.
Revised:  Our idea is based on the assumption that each individual can, for every social group to which it belongs, develop connections and introduce new members.
Edit intent: clarity
Original:  First, strong correlations between the number of communities to which a node belong and the number of connections therein;
Revised:  First, strong correlations between the number of communities to which a node belongs and its number of connections therein;
Edit intent: clarity
Original:  This observation is related to the anthropological theory known as Dunbar's number, i.e.  the empirical observation of a maximal number of ties which an average individual can sustain within its social groups.
Revised:  This observation is related to the anthropological theory known as Dunbar's number, i.e. , the empirical observation of a maximal number of ties which an average individual can sustain within its social groups.
Edit intent: fluency
Original:  The second mechanism is based on a recently proposed generalization of preferential attachment to community structure, appropriately called Structural Preferential Attachment (SPA).
Revised:  The second mechanism is based on a recently proposed generalization of preferential attachment to community structure, appropriately called structural preferential attachment (SPA).
Edit intent: fluency
Original:  The combination of these two mechanisms in a single model (SPA+) allows us to reproduce a number of the global statistics of real networks: The distribution of community sizes, of node memberships and of degrees.
Revised:  The combination of these two mechanisms into a single model (SPA+) allows us to reproduce a number of the global statistics of real networks: The distribution of community sizes, of node memberships and of degrees.
Edit intent: clarity
Original:  Such correlations are often present in real networks.
Revised:  We present empirical evidence that support our findings in real complex networks.
Edit intent: clarity
Original:  Applcations to noncommutative noise stability and noncommutative anticoncentration are given . .
Revised:  Applications to noncommutative noise stability and noncommutative anticoncentration are given . .
Edit intent: fluency
Original:  Applcations to noncommutative noise stability and noncommutative anticoncentration are given . .
Revised:  Applcations to noncommutative noise stability and noncommutative anticoncentration are given .
Edit intent: fluency
Original: We introduce a novel tool for analyzing complex network dynamics, allowing for cascades of causally-related events, which we call causal webs (c-webs for short ), to be separated from other activity.
Revised: We introduce a novel tool for analyzing complex network dynamics, allowing for cascades of causally-related events, which we call causal webs (c-webs ), to be separated from other activity.
Edit intent: coherence
Original:  Using this method, we reveal causally-related activity from experimental data with statistics which may support quasicriticality in the brain .
Revised:  Using this method, we reveal causally-related events .
Edit intent: clarity
Original:  We demonstrate applicability to the study of financial risk based on news (6.6M articles), particularly bank distress and government interventions (243 events), where indices can signal the level of bank-stress-related reporting at the entity level, or aggregated at country or European level, while being coupled with explanations.
Revised:  We demonstrate applicability to the study of financial risk based on news (6.6M articles), particularly bank distress and government interventions (243 events), where indices can signal the level of bank-stress-related reporting at the entity level, or aggregated at national or European level, while being coupled with explanations.
Edit intent: fluency
Original:  ~Phys. ~J.~ B 86 (2013) , 455].
Revised:  Phys. J. B 86 (2013) , 455].
Edit intent: fluency
Original:  ~Phys. ~J.~ B 86 (2013) , 455].
Revised:  ~Phys. ~J.~ B 86 (2013) 455].
Edit intent: fluency
Original:  In the present work we apply a slightly adjusted version of the BPD algorithm to the network optimal attack problem, and demonstrate that it has much better performance than a recently proposed Collective Information algorithm [F. Morone and H. A. Makse, Nature 524 (2015) , 63--68] for different types of random networks and real-world network instances.
Revised:  In the present work we apply a slightly adjusted version of the BPD algorithm to the network optimal attack problem, and demonstrate that it has much better performance than a recently proposed Collective Information algorithm [F. Morone and H. A. Makse, Nature 524 (2015) 63--68] for different types of random networks and real-world network instances.
Edit intent: fluency
Original:  In the present work we apply a slightly adjusted version of BPD (with approximately linear time complexity) to the network optimal attack problem, and demonstrate that it has much better performance than a recently proposed Collective Information algorithm [F. Morone and H. A. Makse, Nature 524 (2015) 63--68] for different types of random networks and real-world network instances.
Revised:  In the present work we apply the BPD alrogithm (which has approximately linear time complexity) to the network optimal attack problem, and demonstrate that it has much better performance than a recently proposed Collective Information algorithm [F. Morone and H. A. Makse, Nature 524 (2015) 63--68] for different types of random networks and real-world network instances.
Edit intent: clarity
Original:  RNA-seq data offer insight into gene expression levels and transcriptome structure , enabling us to better understand the regulation of gene expression and fundamental biological processes.
Revised:  RNA-seq data offer insight into gene expression levels and transcriptome structures , enabling us to better understand the regulation of gene expression and fundamental biological processes.
Edit intent: fluency
Original:  Accurate quantification of RNA isoforms from RNA-seq data is a challenging computational task due to the information loss in sequencing experiments.
Revised:  Accurate isoform quantification from RNA-seq data is a challenging computational task due to the information loss in sequencing experiments.
Edit intent: clarity
Original:  Accurate quantification of RNA isoforms from RNA-seq data is a challenging computational task due to the information loss in sequencing experiments.
Revised:  Accurate quantification of RNA isoforms from RNA-seq data is challenging due to the information loss in sequencing experiments.
Edit intent: clarity
Original:  Recent accumulation of multiple RNA-seq data sets from the same biological condition provides new opportunities to improve the isoform quantification accuracy .
Revised:  A recent accumulation of multiple RNA-seq data sets from the same biological condition provides new opportunities to improve the isoform quantification accuracy .
Edit intent: fluency
Original:  Recent accumulation of multiple RNA-seq data sets from the same biological condition provides new opportunities to improve the isoform quantification accuracy .
Revised:  Recent accumulation of multiple RNA-seq data sets from the same tissue or cell type provides new opportunities to improve the isoform quantification accuracy .
Edit intent: clarity
Original:  Recent accumulation of multiple RNA-seq data sets from the same biological condition provides new opportunities to improve the isoform quantification accuracy .
Revised:  Recent accumulation of multiple RNA-seq data sets from the same biological condition provides new opportunities to improve the accuracy of isoform quantification .
Edit intent: clarity
Original:  However, existing statistical or computational methods for multiple RNA-seq samples either pool the samples into one sample or assign equal weights to the samples in estimating isoform abundance.
Revised:  However, existing statistical or computational methods for multiple RNA-seq samples either pool the samples into one sample or assign equal weights to the samples when estimating isoform abundance.
Edit intent: clarity
Original:  These methods ignore the possible heterogeneity in the quality and noise levels of different samples , and could have biased and unrobust estimates.
Revised:  These methods ignore the possible heterogeneity in the quality of different samples , and could have biased and unrobust estimates.
Edit intent: clarity
Original:  These methods ignore the possible heterogeneity in the quality and noise levels of different samples , and could have biased and unrobust estimates.
Revised:  These methods ignore the possible heterogeneity in the quality and noise levels of different samples and could result in biased and unrobust estimates.
Edit intent: clarity
Original:  In this article, we develop a method named "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ)  for more accurate and robust isoform quantification , by integrating multiple RNA-seq samples under a Bayesian framework.
Revised:  In this article, we develop a method , which we call "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ) for more accurate and robust isoform quantification , by integrating multiple RNA-seq samples under a Bayesian framework.
Edit intent: coherence
Original:  In this article, we develop a method named "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ)  for more accurate and robust isoform quantification , by integrating multiple RNA-seq samples under a Bayesian framework.
Revised:  In this article, we develop a method named "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ) , for more accurate and robust isoform quantification , by integrating multiple RNA-seq samples under a Bayesian framework.
Edit intent: fluency
Original:  In this article, we develop a method named "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ)  for more accurate and robust isoform quantification , by integrating multiple RNA-seq samples under a Bayesian framework.
Revised:  In this article, we develop a method named "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ) for more accurate and robust isoform quantification by integrating multiple RNA-seq samples under a Bayesian framework.
Edit intent: fluency
Original:  Our method aims to (1) identify the informative group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples with more weights on the informative group.
Revised:  Our method aims to (1) identify a consistent group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples with more weights on the informative group.
Edit intent: clarity
Original:  Our method aims to (1) identify the informative group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples with more weights on the informative group.
Revised:  Our method aims to (1) identify the informative group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples by allowing for higher weights on the informative group.
Edit intent: clarity
Original:  Our method aims to (1) identify the informative group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples with more weights on the informative group.
Revised:  Our method aims to (1) identify the informative group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples with more weights on the consistent group.
Edit intent: clarity
Original:  We show that MSIQ provides a consistent estimator of isoform abundance, and  demonstrate the accuracy and effectiveness of MSIQ compared to alternative methods through simulation studies on D. melanogaster genes.
Revised:  We show that MSIQ provides a consistent estimator of isoform abundance, and we demonstrate the accuracy and effectiveness of MSIQ compared to alternative methods through simulation studies on D. melanogaster genes.
Edit intent: fluency
Original:  We show that MSIQ provides a consistent estimator of isoform abundance, and  demonstrate the accuracy and effectiveness of MSIQ compared to alternative methods through simulation studies on D. melanogaster genes.
Revised:  We show that MSIQ provides a consistent estimator of isoform abundance, and demonstrate the accuracy and effectiveness of MSIQ compared with alternative methods through simulation studies on D. melanogaster genes.
Edit intent: fluency
Original:  We justify MSIQ's advantages over existing approaches via application studies on real RNA-seq data of human embryonic stem cells and brain tissues .
Revised:  We justify MSIQ's advantages over existing approaches via application studies on real RNA-seq data from human embryonic stem cells and brain tissues .
Edit intent: clarity
Original:  We present a distributed iterative learning control (ILC) approach where each vehicle learns from the experience of its own and its neighbors' previous task repetitions  and adapts its feedforward input to improve performance.
Revised:  We present a distributed iterative learning control (ILC) approach where each vehicle learns from the experience of its own and its neighbors' previous task repetitions , and adapts its feedforward input to improve performance.
Edit intent: fluency