wanyu/IteraTeR_full_sent huggingface dataset:
Original:  this work presents a centralized database containing the most relevant information on viral fusion proteins, available through a free-to-use web server accessible accessible by the URL URL This server also contains several bioinformatic tools, such as Clustal sequence alignment and Weblogo, and includes a machine learning-based tool capable of predicting the location of fusion peptides (the component of fusion proteins that inserts into the host's cell membrane)
Revised:  this work presents a centralized database containing the most relevant information on viral fusion proteins, available through a free-to-use web server accessible accessible by the URL URL This server also contains several bioinformatic tools, such as Clustal sequence alignment and Weblogo, including as well a machine learning-based tool capable of predicting the location of fusion peptides (the component of fusion proteins that inserts into the host's cell membrane)
Edit intent: clarity
Original:  a binary classification (offensive versus non-offensive language), the level of offense (highly offensive, moderately offensive, and slightly offensive messages), and the identification regarding the target of the discriminatory content (xenophobia, racism, homophobia, sexism, religious intolerance, partyism, apology to the dictatorship, antisemitism, and fat phobia ).
Revised:  a binary classification (offensive versus non-offensive language), the level of offense (highly offensive, moderately offensive, and slightly offensive messages), and the identification regarding the target of the discriminatory content (xenophobia, racism, homophobia, sexism, religious intolerance, partyism, apology to the dictatorship, antisemitism, and fatphobia ).
Edit intent: fluency
Original:  We found that although users are interested in explanations for the road not taken - namely, why the model chose one result and not a well-defined, seemly similar legitimate counterpart - most model interpretations cannot answer these questions.
Revised:  We found that although users are interested in explanations for the road not taken -- namely, why the model chose one result and not a well-defined, seemly similar legitimate counterpart - most model interpretations cannot answer these questions.
Edit intent: fluency
Original:  We found that although users are interested in explanations for the road not taken - namely, why the model chose one result and not a well-defined, seemly similar legitimate counterpart - most model interpretations cannot answer these questions.
Revised:  We found that although users are interested in explanations for the road not taken - namely, why the model chose one result and not a well-defined, seemly similar legitimate counterpart -- most model interpretations cannot answer these questions.
Edit intent: fluency
Original:  Practice and recent evidence suggests that the state-of-the-art (SotA) ASRs struggle with speech variance due to gender, age, speech impairment, race, and accents.
Revised:  Practice and recent evidence suggests that the state-of-the-art (SotA) ASRs struggle with the large variation in speech due to e.g., gender, age, speech impairment, race, and accents.
Edit intent: clarity
Original: In this paper we study consensus-based optimization (CBO), which is a  metaheuristic derivative-free optimization method that can globally minimize nonconvex nonsmooth functions and is amenable to theoretical analysis.
Revised: In this paper we study consensus-based optimization (CBO), which is a multi-agent metaheuristic derivative-free optimization method that can globally minimize nonconvex nonsmooth functions and is amenable to theoretical analysis.
Edit intent: meaning-changed
Original:  Based on an experimentally supported intuition that CBO  performs a gradient descent on the convex envelope of a given objective , we derive a novel technique for proving the convergence to the global minimizer in mean-field law for a rich class of objective functions.
Revised:  Based on an experimentally supported intuition that CBO always performs a gradient descent on the convex envelope of a given objective , we derive a novel technique for proving the convergence to the global minimizer in mean-field law for a rich class of objective functions.
Edit intent: meaning-changed
Original:  Based on an experimentally supported intuition that CBO  performs a gradient descent on the convex envelope of a given objective , we derive a novel technique for proving the convergence to the global minimizer in mean-field law for a rich class of objective functions.
Revised:  Based on an experimentally supported intuition that CBO performs a gradient descent of the squared Euclidean distance to the global minimizer , we derive a novel technique for proving the convergence to the global minimizer in mean-field law for a rich class of objective functions.
Edit intent: meaning-changed
Original:   Furthermore, we improve prior analyses by requiring minimal assumptions about the initialization of the method and by covering objectives that are merely locally Lipschitz continuous.
Revised:  In particular, we prove that CBO performs a convexification of a very large class of optimization problems as the number of optimizing agents goes to infinity. Furthermore, we improve prior analyses by requiring minimal assumptions about the initialization of the method and by covering objectives that are merely locally Lipschitz continuous.
Edit intent: meaning-changed
Original:  This gives rise to the proposed iterative Graph Convolutional Newton's Method (GCNM), which directly includes the forward model into the solution of the inverse problem, while all updates are directly computed by the network on the problem specific mesh.
Revised:  This gives rise to the proposed iterative Graph Convolutional Newton-type Method (GCNM), which directly includes the forward model into the solution of the inverse problem, while all updates are directly computed by the network on the problem specific mesh.
Edit intent: clarity
Original:  This gives rise to the proposed iterative Graph Convolutional Newton's Method (GCNM), which directly includes the forward model into the solution of the inverse problem, while all updates are directly computed by the network on the problem specific mesh.
Revised:  This gives rise to the proposed iterative Graph Convolutional Newton's Method (GCNM), which includes the forward model into the solution of the inverse problem, while all updates are directly computed by the network on the problem specific mesh.
Edit intent: fluency
Original:  This gives rise to the proposed iterative Graph Convolutional Newton's Method (GCNM), which directly includes the forward model into the solution of the inverse problem, while all updates are directly computed by the network on the problem specific mesh.
Revised:  This gives rise to the proposed iterative Graph Convolutional Newton's Method (GCNM), which directly includes the forward model in the solution of the inverse problem, while all updates are directly computed by the network on the problem specific mesh.
Edit intent: fluency
Original:  In this work  we provide a unifying picture on how these known relations, as well as new relations which we derive, stems from a universal autocatalytic network common to all bacteria, facilitating balanced exponential growth of individual cells.
Revised:  In this work , we provide a unifying picture on how these known relations, as well as new relations which we derive, stems from a universal autocatalytic network common to all bacteria, facilitating balanced exponential growth of individual cells.
Edit intent: fluency
Original:  In this work  we provide a unifying picture on how these known relations, as well as new relations which we derive, stems from a universal autocatalytic network common to all bacteria, facilitating balanced exponential growth of individual cells.
Revised:  In this work we provide a unifying picture on how these known relations, as well as new relations that we derive, stems from a universal autocatalytic network common to all bacteria, facilitating balanced exponential growth of individual cells.
Edit intent: fluency
Original:  We show that the core of the cellular autocatalytic network is the transcription--translation machinery -- in itself an autocatalytic network comprising several coupled autocatalytic cycles, including the ribosome, RNA polymerase, and tRNA charging cycles.
Revised:  We show that the core of the cellular autocatalytic network is the transcription -- translation machinery -- in itself an autocatalytic network comprising several coupled autocatalytic cycles, including the ribosome, RNA polymerase, and tRNA charging cycles.
Edit intent: fluency
Original:  We derive two types of growth laws per autocatalytic cycle, one relating growth rate to the relative fraction of the catalyst and its catalysis rate, and the other relating growth rate to all the time--scales in the cycle.
Revised:  We derive two types of growth laws per autocatalytic cycle, one relating growth rate to the relative fraction of the catalyst and its catalysis rate, and the other relating growth rate to all the time scales in the cycle.
Edit intent: fluency
Original:  We also derive a growth law that accounts for the RNA polymerase autocatalytic cycle, which we use to explain how growth rate depends on the inducible expression of the rpoB and rpoC genes, which code for the RpoB and RpoC protein subunits of RNA polymerase, and how the concentration of rifampicin, which targets RNA polymerase, affects growth rate without changing the RNA-to-protein ratio.
Revised:  We also derive a growth law that accounts for the RNA polymerase autocatalytic cycle, which we use to explain how growth rate depends on the inducible expression of the rpoB and rpoC genes, which code for the RpoB and C protein subunits of RNA polymerase, and how the concentration of rifampicin, which targets RNA polymerase, affects growth rate without changing the RNA-to-protein ratio.
Edit intent: coherence
Original:  We find that for EU countries it will take some time to reach this threshold, given that the new, now dominant, mutations, have a significantly higher infection rate  .
Revised:  We find that for EU countries it will take some time to reach this threshold, given that the new, now dominant, mutations, have a significantly higher infection rate . The urgency of accelerating vaccination is increased by early evidence that the new strains also have a higher mortality risk .
Edit intent: meaning-changed
Original:  We argue that in order to build science discovery machines and speed up the scientific discovery process, we should build theoretical and computational frameworks that encapsulate these principles . Building machines that fully incorporate these principles in an automated way might open the doors for many advancements.
Revised:  We argue that building science discovery machines and speed up the scientific discovery process, we should build theoretical and computational frameworks that encapsulate these principles . Building machines that fully incorporate these principles in an automated way might open the doors for many advancements.
Edit intent: coherence
Original:  We argue that in order to build science discovery machines and speed up the scientific discovery process, we should build theoretical and computational frameworks that encapsulate these principles . Building machines that fully incorporate these principles in an automated way might open the doors for many advancements.
Revised:  We argue that in order to build science discovery machines should be guided by these principles as an alternative to the dominant approach of current AI systems that focuses on narrow objectives . Building machines that fully incorporate these principles in an automated way might open the doors for many advancements.
Edit intent: meaning-changed
Original:  This work introduces Distilled Replay, a novel replay strategy for Continual Learning which is able to mitigate URLetting by keeping a very small buffer ( up to 1 pattern per class) of highly informative samples.
Revised:  This work introduces Distilled Replay, a novel replay strategy for Continual Learning which is able to mitigate URLetting by keeping a very small buffer ( 1 pattern per class) of highly informative samples.
Edit intent: clarity
Original:  In particular, we present our emerging HAR projects for healthcare: identification of human activities for intensive care unit (ICU) patients and  Duchenne muscular dystrophy (DMD) patients.
Revised:  In particular, we present our projects to illustrate the system design of HAR applications for healthcare. Our projects include early mobility identification of human activities for intensive care unit (ICU) patients and Duchenne muscular dystrophy (DMD) patients.
Edit intent: meaning-changed
Original:  In particular, we present our emerging HAR projects for healthcare: identification of human activities for intensive care unit (ICU) patients and  Duchenne muscular dystrophy (DMD) patients.
Revised:  In particular, we present our emerging HAR projects for healthcare: identification of human activities for intensive care unit (ICU) patients and gait analysis of Duchenne muscular dystrophy (DMD) patients.
Edit intent: meaning-changed
Original:  This overview paper covers considerations and settings for building a HAR healthcare system, including sensor factors , AI model comparison, and system challenges .
Revised:  This overview paper covers considerations and settings for building a HAR healthcare system, including sensor factors (e.g., type, number, and placement location), AI model selection (e.g., classical machine learning models versus deep learning models), and feature engineering. In addition, we highlight the challenges of such healthcare-oriented HAR systems and propose several research opportunities for both the medical and the computer science community .
Edit intent: meaning-changed
Original:  We show that an implementation of this combination in an existing physics engine (DART) is capable of a 45x single-core speedup over finite-differencing in computing analytical Jacobians for a single timestep, while preserving all the expressiveness of original DART.
Revised:  We show that an implementation of this combination in an existing physics engine (DART) is capable of a 87x single-core speedup over finite-differencing in computing analytical Jacobians for a single timestep, while preserving all the expressiveness of original DART.
Edit intent: meaning-changed
Original: We propose and analyze numerically a new fictitious domain method, based on higher order space-time finite element discretizations, for the simulation of the nonstationary, incompressible Navier--Stokes equations on evolving domains.
Revised: We propose and analyze computationally a new fictitious domain method, based on higher order space-time finite element discretizations, for the simulation of the nonstationary, incompressible Navier--Stokes equations on evolving domains.
Edit intent: clarity
Original: We propose and analyze numerically a new fictitious domain method, based on higher order space-time finite element discretizations, for the simulation of the nonstationary, incompressible Navier--Stokes equations on evolving domains.
Revised: We propose and analyze numerically a new fictitious domain method, based on higher order space-time finite element discretizations, for the simulation of the nonstationary, incompressible Navier-Stokes equations on evolving domains.
Edit intent: fluency
Original:  The  key ingredients of the approach are the weak formulation of Dirichlet boundary conditions by Nitsche's method, the flexible and efficient integration over all types of intersections of cells by moving boundaries and the spatial extension of the discrete physical quantities to the entire computational background mesh including fictitious (ghost) subdomains of fluid flow.
Revised:  The potential of such cut finite element techniques for higher order space-time finite element methods has rarely been studied in the literature so far and deserves further elucidation. The key ingredients of the approach are the weak formulation of Dirichlet boundary conditions by Nitsche's method, the flexible and efficient integration over all types of intersections of cells by moving boundaries and the spatial extension of the discrete physical quantities to the entire computational background mesh including fictitious (ghost) subdomains of fluid flow.
Edit intent: meaning-changed
Original:   To prevent spurious oscillations caused by irregular intersections of mesh cells, a penalization ensuring the stability of the approach and defining implicitly the extension to host domains is added.
Revised:  Thereby, an expensive remeshing and adaptation of the sparse matrix data structure are avoided and the computations are accelerated. To prevent spurious oscillations caused by irregular intersections of mesh cells, a penalization ensuring the stability of the approach and defining implicitly the extension to host domains is added.
Edit intent: meaning-changed
Original:  The convergence and stability properties of the approach are studied, firstly, for a benchmark problem of flow around a stationary obstacle and, secondly, for flow around moving obstacles with arising cut cells and fictitious domains .
Revised:  The parallel implementation of the matrix assembly is described. The optimal order convergence properties of the approach are studied, firstly, for a benchmark problem of flow around a stationary obstacle and, secondly, for flow around moving obstacles with arising cut cells and fictitious domains .
Edit intent: meaning-changed
Original:  The convergence and stability properties of the approach are studied, firstly, for a benchmark problem of flow around a stationary obstacle and, secondly, for flow around moving obstacles with arising cut cells and fictitious domains .
Revised:  The convergence and stability properties of the algorithm are illustrated in a numerical experiment for an evolving domain. The well-known 2d benchmark of flow around a stationary obstacle and, secondly, for flow around moving obstacles with arising cut cells and fictitious domains .
Edit intent: meaning-changed
Original:  The convergence and stability properties of the approach are studied, firstly, for a benchmark problem of flow around a stationary obstacle and, secondly, for flow around moving obstacles with arising cut cells and fictitious domains . The parallel implementation is also addressed .
Revised:  The convergence and stability properties of the approach are studied, firstly, for a benchmark problem of flow around a stationary obstacle and, secondly, for flow around moving obstacles with arising cut cells and fictitious domains are considered further .
Edit intent: clarity
Original: The airborne transmission of disease-causing pathogens like the SARS-CoV-2 virus responsible for the COVID-19 pandemic is known to occur not only through violent expiratory events like coughs or sneezes , but also during activities like singing and even speech.
Revised: Pathogens like the SARS-CoV-2 virus responsible for the COVID-19 pandemic is known to occur not only through violent expiratory events like coughs or sneezes , but also during activities like singing and even speech.
Edit intent: clarity
Original: The airborne transmission of disease-causing pathogens like the SARS-CoV-2 virus responsible for the COVID-19 pandemic is known to occur not only through violent expiratory events like coughs or sneezes , but also during activities like singing and even speech.
Revised: The airborne transmission of disease-causing pathogens like the SARS-CoV-2 are transmitted not only through violent expiratory events like coughs or sneezes , but also during activities like singing and even speech.
Edit intent: clarity
Original: The airborne transmission of disease-causing pathogens like the SARS-CoV-2 virus responsible for the COVID-19 pandemic is known to occur not only through violent expiratory events like coughs or sneezes , but also during activities like singing and even speech.
Revised: The airborne transmission of disease-causing pathogens like the SARS-CoV-2 virus responsible for the COVID-19 pandemic is known to occur not only through violent expiratory events like coughing , but also during activities like singing and even speech.
Edit intent: coherence
Original: The airborne transmission of disease-causing pathogens like the SARS-CoV-2 virus responsible for the COVID-19 pandemic is known to occur not only through violent expiratory events like coughs or sneezes , but also during activities like singing and even speech. We study, using direct numerical simulation (DNS), the transport of virus-laden aerosols generated during human speech. We show that the use of the " top-hat " formulation for steady speech flows can underestimate infection probabilities by a factor of 2-3.
Revised: The airborne transmission of disease-causing pathogens like the SARS-CoV-2 virus responsible for the COVID-19 pandemic is known to occur not only through violent expiratory events like coughs or sneezes , but also through routine activities like breathing/speaking/singing. We perform direct numerical simulations of the turbulent transport of potentially infectious aerosols in short conversations. It is shown that a two-way conversation significantly reduces the aerosol exposure compared to a relative monologue by one person and relative silence of the other. This is because the interaction of the use of the " top-hat " formulation for steady speech flows can underestimate infection probabilities by a factor of 2-3.
Edit intent: meaning-changed
Original:  We show that the use of the " top-hat " formulation for steady speech flows can underestimate infection probabilities by a factor of 2-3. We propose an alternative method of estimating viral ingestion that includes exposure through the eyes and mouth , to provide more realistic estimates of the risk of infection .
Revised:  We show that the use of the " top-hat " effect. Unequal conversation is shown to significantly increase the risk of infection .
Edit intent: coherence
Original:  We propose an alternative method of estimating viral ingestion that includes exposure through the eyes and mouth , to provide more realistic estimates of the risk of infection . This method is then used to determine infection probabilities when two speakers facing each other are engaged in a short conversation. We show that the interaction between the two oppositely-directed speech jetscan increase or decrease infection probabilities, which peak for a height difference between the speakers of about 10cm (30cm) when the axial separationbetween them is 2ft (6ft).
Revised:  We propose an alternative method of estimating viral ingestion that includes exposure through the eyes and mouth , to provide more realistic estimates of the risk of infection to the person who talks less. Interestingly, a small height difference is worse for infection spread, due to reduced interference between the two oppositely-directed speech jetscan increase or decrease infection probabilities, which peak for a height difference between the speakers of about 10cm (30cm) when the axial separationbetween them is 2ft (6ft).
Edit intent: meaning-changed