wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Applying this to our scenario where the impact has a clamping nature, the allowed end effector speed on the whole robot workspace would be only 0.13 and 0.16 m/s for the UR10e and KUKA LBR iiwa , respectively. Our measurements reveal that if the task is performed for example 0.8 m away and 0.4 m above the robot base, speeds of 0.16 m/s (UR10e) and 0.20 m/s (KUKA LBR iiwa) can be safely operated, staying within the prescribed force limit. Furthermore, the  force evolution during impact for the UR10e reveals that clamping never occurs .
Revised:  Applying this to our scenario where the impact has a clamping nature, the allowed end effector speed on the whole robot workspace would be only 0.13 and 0.16 m/s for the UR10e and KUKA LBR iiwa ) moving downward against an impact measuring device. First, we empirically show that the force evolution during impact for the UR10e reveals that clamping never occurs .
Edit intent: coherence
Original:  Furthermore, the  force evolution during impact for the UR10e reveals that clamping never occurs .
Revised:  Furthermore, the impact forces can vary by more than 100 percent within the robot workspace. The forces are negatively correlated with the distance from the robot base and the height in the workspace. Second, we present a data-driven model, 3D Collision-Force-Map, predicting impact forces from distance, height, and velocity and demonstrate that it can be trained on a limited number of data points. Third, we analyze the force evolution during impact for the UR10e reveals that clamping never occurs .
Edit intent: meaning-changed
Original:  The formulas relating robot mass, velocity, and impact forces from ISO/TS 15066 are insufficient -- leading both to significant underestimation and overestimation of velocities/forces, and thus to unnecessarily long cycle times or even dangerous applications  .
Revised:  We show that formulas relating robot mass, velocity, and impact forces from ISO/TS 15066 are insufficient -- leading both to significant underestimation and overestimation of velocities/forces, and thus to unnecessarily long cycle times or even dangerous applications .
Edit intent: coherence
Original:  The formulas relating robot mass, velocity, and impact forces from ISO/TS 15066 are insufficient -- leading both to significant underestimation and overestimation of velocities/forces, and thus to unnecessarily long cycle times or even dangerous applications  .
Revised:  The formulas relating robot mass, velocity, and impact forces from ISO/TS 15066 are insufficient -- leading both to significant underestimation and overestimation and thus to unnecessarily long cycle times or even dangerous applications .
Edit intent: clarity
Original:  The formulas relating robot mass, velocity, and impact forces from ISO/TS 15066 are insufficient -- leading both to significant underestimation and overestimation of velocities/forces, and thus to unnecessarily long cycle times or even dangerous applications  .
Revised:  The formulas relating robot mass, velocity, and impact forces from ISO/TS 15066 are insufficient -- leading both to significant underestimation and overestimation of velocities/forces, and thus to unnecessarily long cycle times or even dangerous applications . We propose an empirical method that can be deployed to quickly determine the optimal speed and position where a task can be safely performed with maximum efficiency .
Edit intent: meaning-changed
Original:  Our results demonstrate that the proposed architecture trained on Sentimental LIAR can achieve an accuracy of 70 %DIFDELCMD < \\%%% %DIF < , which is an improvement of ~30\\% over previously reported results for the LIAR benchmark.abstract 
Revised:  Our results demonstrate that the proposed architecture trained on Sentimental LIAR can achieve an accuracy of 70 %DIFDELCMD < \\%%% %DIF < , which is an improvement of ~30\\% over previously reported results for the LIAR benchmark.abstract \%, which is an improvement of ~30\% over previously reported results for the LIAR benchmark.
Edit intent: meaning-changed
Original:  The proposed methodology blends an arbitrary Runge-Kutta scheme and a bound-preserving (BP) first-order approximation using two kinds of limiting techniques. The first one is a predictor-corrector method that belongs to the family of flux-corrected transport (FCT) algorithms.
Revised:  The proposed methodology blends an arbitrary Runge-Kutta scheme and a bound-preserving (BP) and satisfy a semi-discrete maximum principle. Next, we propose a global monolithic convex (GMC) flux limiter which has the structure of a flux-corrected transport (FCT) algorithms.
Edit intent: meaning-changed
Original:  The first one is a predictor-corrector method that belongs to the family of flux-corrected transport (FCT) algorithms. The second approach constrains the antidiffusive part of a high-order target scheme using a new globalized monolithic convex (GMC) limiter. The flux-corrected approximations are BP under the time step restriction of the forward Euler method in the explicit case and without any time step restrictions in the implicit case. The FCT and GMC limiters can be applied to antidiffusive fluxes of intermediate RK stages and/or of the final solution update.
Revised:  The first one is a predictor-corrector method that belongs to the family of flux-corrected transport (FCT) algorithm but is applicable to spatial semi-discretizations and ensures the BP property of the fully discrete scheme for strong stability preserving (SSP) Runge-Kutta time discretizations. To circumvent the order barrier for SSP time integrators, we constrain the intermediate stages and/or of the final solution update.
Edit intent: clarity
Original:  The FCT and GMC limiters can be applied to antidiffusive fluxes of intermediate RK stages and/or of the final solution update. Stagewise limiting ensures the BP property of intermediate cell averages. If the calculation of high-order fluxes involves polynomial reconstructions from BP data, these reconstructions can be constrained using a slope limiter to correct unacceptable input.
Revised:  The FCT and GMC limiters can be applied to antidiffusive fluxes of intermediate RK stages and/or the final stage of a general high-order fluxes involves polynomial reconstructions from BP data, these reconstructions can be constrained using a slope limiter to correct unacceptable input.
Edit intent: clarity
Original:  If the calculation of high-order fluxes involves polynomial reconstructions from BP data, these reconstructions can be constrained using a slope limiter to correct unacceptable input. The BP property of the final solution is guaranteed for all flux-corrected methods . Numerical studies are performed for one-dimensional test problems discretized in space using explicit weighted essentially nonoscillatory (WENO) finite volume schemes .
Revised:  If the calculation of high-order RK method using GMC-type limiters. In this work, our theoretical and numerical studies are restricted to explicit schemes which are provably BP for sufficiently small time steps. The new GMC limiting framework offers the possibility of relaxing the bounds of inequality constraints to achieve higher accuracy at the cost of more stringent time step restrictions. The ability of the presented limiters to preserve global bounds and recognize well-resolved smooth solutions is verified numerically for three representative RK methods combined with weighted essentially nonoscillatory (WENO) finite volume schemes .
Edit intent: clarity
Original:  The BP property of the final solution is guaranteed for all flux-corrected methods . Numerical studies are performed for one-dimensional test problems discretized in space using explicit weighted essentially nonoscillatory (WENO) finite volume schemes .
Revised:  The BP property of the final solution is guaranteed for all flux-corrected methods . Numerical studies are performed for one-dimensional test problems discretized in space using explicit weighted essentially nonoscillatory (WENO) finite volume space discretizations of linear and nonlinear test problems in 1D .
Edit intent: meaning-changed
Original: Motivated by the COVID-19 pandemic, we introduce a mathematical description of the impact of sociality in the spread of infectious diseases by integrating an epidemiological dynamic with a kinetic modeling of population-based contacts.
Revised: Motivated by the COVID-19 pandemic, we introduce a mathematical description of the impact of sociality in the spread of infectious diseases by integrating an epidemiological dynamics with a kinetic modeling of population-based contacts.
Edit intent: fluency
Original:  The kinetic description leads to study the evolution over time of Boltzmann type equations describing the number densities of social contacts of susceptible, infected and recovered individuals, whose proportions are driven by a classical  compartmental model in epidemiology.
Revised:  The kinetic description leads to study the evolution over time of Boltzmann-type equations describing the number densities of social contacts of susceptible, infected and recovered individuals, whose proportions are driven by a classical compartmental model in epidemiology.
Edit intent: fluency
Original:  The kinetic description leads to study the evolution over time of Boltzmann type equations describing the number densities of social contacts of susceptible, infected and recovered individuals, whose proportions are driven by a classical  compartmental model in epidemiology.
Revised:  The kinetic description leads to study the evolution over time of Boltzmann type equations describing the number densities of social contacts of susceptible, infected and recovered individuals, whose proportions are driven by a classical SIR-type compartmental model in epidemiology.
Edit intent: meaning-changed
Original: Contains critical commentary on the exhibitions "Training Humans" and "Making Faces  " by Kate Crawford and Trevor Paglen, and on the accompanying essay "Excavating AI: The politics of images in machine learning training sets . " 
Revised: Two art exhibitions, "Training Humans" and "Making Faces " by Kate Crawford and Trevor Paglen, and on the accompanying essay "Excavating AI: The politics of images in machine learning training sets . " 
Edit intent: meaning-changed
Original: Contains critical commentary on the exhibitions "Training Humans" and "Making Faces  " by Kate Crawford and Trevor Paglen, and on the accompanying essay "Excavating AI: The politics of images in machine learning training sets . " 
Revised: Contains critical commentary on the exhibitions "Training Humans" and "Making Faces , " by Kate Crawford and Trevor Paglen, and on the accompanying essay "Excavating AI: The politics of images in machine learning training sets . " 
Edit intent: fluency
Original: Contains critical commentary on the exhibitions "Training Humans" and "Making Faces  " by Kate Crawford and Trevor Paglen, and on the accompanying essay "Excavating AI: The politics of images in machine learning training sets . " 
Revised: Contains critical commentary on the exhibitions "Training Humans" and "Making Faces " and the accompanying essay "Excavating AI: The politics of images in machine learning training sets . " 
Edit intent: coherence
Original: Contains critical commentary on the exhibitions "Training Humans" and "Making Faces  " by Kate Crawford and Trevor Paglen, and on the accompanying essay "Excavating AI: The politics of images in machine learning training sets . " 
Revised: Contains critical commentary on the exhibitions "Training Humans" and "Making Faces " by Kate Crawford and Trevor Paglen, and on the accompanying essay "Excavating AI: The politics of images in machine learning training sets " 
Edit intent: fluency
Original: Contains critical commentary on the exhibitions "Training Humans" and "Making Faces  " by Kate Crawford and Trevor Paglen, and on the accompanying essay "Excavating AI: The politics of images in machine learning training sets . " 
Revised: Contains critical commentary on the exhibitions "Training Humans" and "Making Faces " by Kate Crawford and Trevor Paglen, and on the accompanying essay "Excavating AI: The politics of images in machine learning training sets . " by Kate Crawford and Trevor Paglen, are making substantial impact on discourse taking place in the social and mass media networks, and some scholarly circles. Critical scrutiny reveals, however, a self-contradictory stance regarding informed consent for the use of facial images, as well as serious flaws in their critique of ML training sets. Our analysis underlines the non-negotiability of informed consent when using human data in artistic and other contexts, and clarifies issues relating to the description of ML training sets.
Edit intent: meaning-changed
Original:  While the explicit Euler method is known to converge to the solution of the rough Bergomi model, the strong rate of convergence is only H. We prove rate H + 1/2 for the weak convergence of the Euler method and, surprisingly, in the case of quadratic payoff functions we obtain rate one.
Revised:  While the explicit Euler method is known to converge to the solution of the rough Bergomi model, its strong rate of convergence is only H. We prove rate H + 1/2 for the weak convergence of the Euler method and, surprisingly, in the case of quadratic payoff functions we obtain rate one.
Edit intent: clarity
Original:  While the explicit Euler method is known to converge to the solution of the rough Bergomi model, the strong rate of convergence is only H. We prove rate H + 1/2 for the weak convergence of the Euler method and, surprisingly, in the case of quadratic payoff functions we obtain rate one.
Revised:  While the explicit Euler method is known to converge to the solution of the rough Bergomi model, the strong rate of convergence is only H. For a simplified rough Bergomi model, we prove rate H + 1/2 for the weak convergence of the Euler method and, surprisingly, in the case of quadratic payoff functions we obtain rate one.
Edit intent: meaning-changed
Original: Trace Reconstruction is the problem of learning an unknown string x from independent traces of x, where traces are generated by independently deleting each bit of x with some deletion probability q. In this paper, we initiate the study of Circular Trace Reconstruction , where the unknown string x is circular and traces are now rotated by a random cyclic shift.
Revised: Trace reconstruction is the problem of learning an unknown string x from independent traces of x, where traces are generated by independently deleting each bit of x with some deletion probability q. In this paper, we initiate the study of Circular Trace Reconstruction , where the unknown string x is circular and traces are now rotated by a random cyclic shift.
Edit intent: fluency
Original: Trace Reconstruction is the problem of learning an unknown string x from independent traces of x, where traces are generated by independently deleting each bit of x with some deletion probability q. In this paper, we initiate the study of Circular Trace Reconstruction , where the unknown string x is circular and traces are now rotated by a random cyclic shift.
Revised: Trace Reconstruction is the problem of learning an unknown string x from independent traces of x, where traces are generated by independently deleting each bit of x with some deletion probability q. In this paper, we initiate the study of Circular trace reconstruction , where the unknown string x is circular and traces are now rotated by a random cyclic shift.
Edit intent: fluency
Original:  For n of this form, this nearly matches  the best known bound of \exp\big(O(n^{1/3})\big) for standard trace reconstruction \big(O)}\big) .
Revised:  For n of this form, this nearly matches what was the best known bound of \exp\big(O(n^{1/3})\big) for standard trace reconstruction \big(O)}\big) .
Edit intent: clarity
Original:  For n of this form, this nearly matches  the best known bound of \exp\big(O(n^{1/3})\big) for standard trace reconstruction \big(O)}\big) .
Revised:  For n of this form, this nearly matches the best known bound of \exp\big(O(n^{1/3})\big) for standard trace reconstruction when this paper was initially released. We note, however, that Chase very recently improved the standard trace reconstruction bound to \exp\big(O)}\big) .
Edit intent: meaning-changed
Original:  For n of this form, this nearly matches  the best known bound of \exp\big(O(n^{1/3})\big) for standard trace reconstruction \big(O)}\big) .
Revised:  For n of this form, this nearly matches the best known bound of \exp\big(O(n^{1/3})\big) for standard trace reconstruction \big(O(n^{1/5)}\big) .
Edit intent: meaning-changed
Original: In wet-lab experiments \mbox{%DIFAUXCMD Nakagaki-Yamada-Toth,Tero-Takagi-etal , the slime mold Physarum polycephalum has demonstrated its ability to solve shortest path problems and to design efficient networks , see Figure \ref{Wet-Lab Experiments For the shortest path problem, a mathematical model for the evolution of the slime was proposed in \mbox{%DIFAUXCMD Tero-Kobayashi-Nakagaki .
Revised: In wet-lab experiments , the slime mold Physarum polycephalum has demonstrated its ability to solve shortest path problems and to design efficient networks , see Figure \ref{Wet-Lab Experiments For the shortest path problem, a mathematical model for the evolution of the slime was proposed in \mbox{%DIFAUXCMD Tero-Kobayashi-Nakagaki .
Edit intent: clarity
Original: In wet-lab experiments \mbox{%DIFAUXCMD Nakagaki-Yamada-Toth,Tero-Takagi-etal , the slime mold Physarum polycephalum has demonstrated its ability to solve shortest path problems and to design efficient networks , see Figure \ref{Wet-Lab Experiments For the shortest path problem, a mathematical model for the evolution of the slime was proposed in \mbox{%DIFAUXCMD Tero-Kobayashi-Nakagaki .
Revised: In wet-lab experiments \mbox{%DIFAUXCMD Nakagaki-Yamada-Toth,Tero-Takagi-etal , the slime mold Physarum polycephalum has demonstrated its ability to solve shortest path problems and to design efficient networks . For the shortest path problem, a mathematical model for the evolution of the slime was proposed in \mbox{%DIFAUXCMD Tero-Kobayashi-Nakagaki .
Edit intent: coherence
Original: In wet-lab experiments \mbox{%DIFAUXCMD Nakagaki-Yamada-Toth,Tero-Takagi-etal , the slime mold Physarum polycephalum has demonstrated its ability to solve shortest path problems and to design efficient networks , see Figure \ref{Wet-Lab Experiments For the shortest path problem, a mathematical model for the evolution of the slime was proposed in \mbox{%DIFAUXCMD Tero-Kobayashi-Nakagaki .
Revised: In wet-lab experiments \mbox{%DIFAUXCMD Nakagaki-Yamada-Toth,Tero-Takagi-etal , the slime mold Physarum polycephalum has demonstrated its ability to solve shortest path problems and to design efficient networks , see Figure \ref{Wet-Lab Experiments For the shortest path problem, a mathematical model for the evolution of the slime is available and it has been shown in computer experiments and through mathematical analysis that the dynamics solves the shortest path problem .
Edit intent: meaning-changed
Original:  By assuming that the conditional location vector from a multivariate Student's t distribution changes over time, we construct a robust filter which is able to overcome several issues that naturally arise when modeling heavy-tailed phenomena and, more in general, vectors of dependent non-Gaussian time series.
Revised:  By assuming that the conditional location vector from a multivariate Student's t distribution changes over time, we construct a robust filter which is able to overcome several issues that naturally arise when modeling heavy-tailed phenomena and, more in general, vectors of dependent non-Gaussian time series.
Edit intent: fluency
Original:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI Disease , BC2GM and JNLPBA datasets, with F1-scores of 92.38 \%, 94.19\%, 87.36 \%, 90.04\%, 84.98 \% and 78.93\%, respectively.
Revised:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI-Disease , BC2GM and JNLPBA datasets, with F1-scores of 92.38 \%, 94.19\%, 87.36 \%, 90.04\%, 84.98 \% and 78.93\%, respectively.
Edit intent: fluency
Original:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI Disease , BC2GM and JNLPBA datasets, with F1-scores of 92.38 \%, 94.19\%, 87.36 \%, 90.04\%, 84.98 \% and 78.93\%, respectively.
Revised:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI Disease , BC2GM and JNLPBA datasets, achieving F1-scores of 92.38 \%, 94.19\%, 87.36 \%, 90.04\%, 84.98 \% and 78.93\%, respectively.
Edit intent: coherence
Original:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI Disease , BC2GM and JNLPBA datasets, with F1-scores of 92.38 \%, 94.19\%, 87.36 \%, 90.04\%, 84.98 \% and 78.93\%, respectively.
Revised:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI Disease , BC2GM and JNLPBA datasets, with F1-scores of 92.92 \%, 94.19\%, 87.36 \%, 90.04\%, 84.98 \% and 78.93\%, respectively.
Edit intent: meaning-changed
Original:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI Disease , BC2GM and JNLPBA datasets, with F1-scores of 92.38 \%, 94.19\%, 87.36 \%, 90.04\%, 84.98 \% and 78.93\%, respectively.
Revised:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI Disease , BC2GM and JNLPBA datasets, with F1-scores of 92.38 \%, 94.19\%, 87.83 \%, 90.04\%, 84.98 \% and 78.93\%, respectively.
Edit intent: meaning-changed
Original:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI Disease , BC2GM and JNLPBA datasets, with F1-scores of 92.38 \%, 94.19\%, 87.36 \%, 90.04\%, 84.98 \% and 78.93\%, respectively.
Revised:  Our method achieves state-of-the-art (SOTA) performance on the BC4CHEMD, BC5CDR-Chem, BC5CDR-Disease, NCBI Disease , BC2GM and JNLPBA datasets, with F1-scores of 92.38 \%, 94.19\%, 87.36 \%, 90.04\%, 85.48 \% and 78.93\%, respectively.
Edit intent: meaning-changed
Original: In the present work, we investigate for the first time with a cut finite element method , a parameterized fourth-order nonlinear geometrical PDE, namely the Cahn-Hilliard system.
Revised: In the present work, we investigate for the first time with a cut finite element method for the parameterized system of second-order equations stemming from the splitting approach of a fourth order nonlinear geometrical PDE, namely the Cahn-Hilliard system.
Edit intent: meaning-changed
Original:  Coding can help boost the service rate region , that is, increase the overall volume of data access requests that can be handled by the system . The goal of this paper is to postulate the service rate region as an important consideration in the design of erasure coded distributed systems.
Revised:  Coding can help boost the service rate region , that is, increase the overall volume of data access requests that the system can handle. This paper aims to postulate the service rate region as an important consideration in the design of erasure coded distributed systems.
Edit intent: clarity
Original:  We highlight several open problems that can be grouped into two broad threads: 1) characterizing the service rate region of a given code and finding the optimal request allocation, and 2 ) designing the underlying erasure code for a given service rate region.
Revised:  We highlight several open problems that can be grouped into two broad threads: 1) characterizing the service rate region of a given code and finding the optimal request allocation, and2 ) designing the underlying erasure code for a given service rate region.
Edit intent: fluency