wanyu/IteraTeR_v2 huggingface dataset:
Original:  We demonstrate our results on several applications which include \mic{several scenarios relevant to the emergence of drug resistance} : the orderings of resistance-conferring mutations in bacteria and the impact of imperfect drug penetration in cancer.
Revised:  We demonstrate our results on \mic{several scenarios relevant to the emergence of drug resistance} : the orderings of resistance-conferring mutations in bacteria and the impact of imperfect drug penetration in cancer.
Edit intent: clarity
Original:  We demonstrate our results on several applications which include \mic{several scenarios relevant to the emergence of drug resistance} : the orderings of resistance-conferring mutations in bacteria and the impact of imperfect drug penetration in cancer.
Revised:  We demonstrate our results on several applications which include \mic{several scenarios relevant to the emergence of drug resistance}, including : the orderings of resistance-conferring mutations in bacteria and the impact of imperfect drug penetration in cancer.
Edit intent: clarity
Original: The fifth generation (5G) technologies enable an emerge type of public cloud environment: Slice as a Service (SlaaS).
Revised: The fifth generation (5G) technologies enable an emerge type of public cloud environment: the Slice-as-a-Service (SlaaS).
Edit intent: fluency
Original:  When the service demand is dense, congestions of slice requests can occur , leading to long waiting time.
Revised:  When the service demand is dense, congestions of slice requests may occur leading to long waiting time.
Edit intent: clarity
Original:  Tenants can therefore behave impatiently to mitigate potential loss caused by congestions .
Revised:  Tenants can therefore behave impatiently to mitigate potential loss .
Edit intent: clarity
Original:  This paper studies the rational strategies of impatient tenants waiting in queue-based slice admission control system, and discusses the benefits of allowing MNO to share its information with the  tenants.
Revised:  This paper studies the rational strategies of impatient tenants waiting in queue-based slice admission control system, and discusses the benefits of allowing MNO to share its information with the upcoming tenants.
Edit intent: clarity
Original:  However, when the service demand will resonably get dense, congestions of slice requests may occur leading to long waiting periods.
Revised:  However, when the service demand will reasonably get dense, congestions of slice requests may occur leading to long waiting periods.
Edit intent: fluency
Original:  IoT is now pervasive---new applications are being deployed in every domain imaginable , leading to a rapid and widespread adoption of device-based interaction and automation.
Revised:  IoT is now pervasive---new applications are being deployed in nearly every conceivable domain , leading to a rapid and widespread adoption of device-based interaction and automation.
Edit intent: clarity
Original:  IoT is now pervasive---new applications are being deployed in every domain imaginable , leading to a rapid and widespread adoption of device-based interaction and automation.
Revised:  IoT is now pervasive---new applications are being deployed in every domain imaginable , leading to adoption of device-based interaction and automation.
Edit intent: clarity
Original:  There is a growing recognition that identifying IoT vulnerabilities requires program-analysis techniques , yet the technical community's understanding of the nature and extent of IoT program analysis remains limited .
Revised:  Program-analysis is crucial in identifying IoT vulnerabilities requires program-analysis techniques , yet the technical community's understanding of the nature and extent of IoT program analysis remains limited .
Edit intent: clarity
Original:  There is a growing recognition that identifying IoT vulnerabilities requires program-analysis techniques , yet the technical community's understanding of the nature and extent of IoT program analysis remains limited .
Revised:  There is a growing recognition that identifying IoT vulnerabilities , yet the technical community's understanding of the nature and extent of IoT program analysis remains limited .
Edit intent: clarity
Original:  There is a growing recognition that identifying IoT vulnerabilities requires program-analysis techniques , yet the technical community's understanding of the nature and extent of IoT program analysis remains limited .
Revised:  There is a growing recognition that identifying IoT vulnerabilities requires program-analysis techniques , yet the application and scope of program analysis in IoT remains largely unexplored by the technical community .
Edit intent: clarity
Original:  In this paper, we study privacy and security issues in IoT that require program-analysis techniques with a focus on attacks identified against these systems and defenses crafted to date . Based on a study of five IoT programming platforms, we identify the key insights resulting from works in both the program analysis and security communities and relate the effectiveness of program-analysis techniques to security and privacy issues.
Revised:  In this paper, we study privacy and security issues in IoT that require program-analysis techniques with an emphasis on identified attacks against these systems and defenses crafted to date . Based on a study of five IoT programming platforms, we identify the key insights resulting from works in both the program analysis and security communities and relate the effectiveness of program-analysis techniques to security and privacy issues.
Edit intent: clarity
Original:  In this paper, we study privacy and security issues in IoT that require program-analysis techniques with a focus on attacks identified against these systems and defenses crafted to date . Based on a study of five IoT programming platforms, we identify the key insights resulting from works in both the program analysis and security communities and relate the effectiveness of program-analysis techniques to security and privacy issues.
Revised:  In this paper, we study privacy and security issues in IoT that require program-analysis techniques with a focus on attacks identified against these systems and defenses implemented so far . Based on a study of five IoT programming platforms, we identify the key insights resulting from works in both the program analysis and security communities and relate the effectiveness of program-analysis techniques to security and privacy issues.
Edit intent: clarity
Original:  In this paper, we study privacy and security issues in IoT that require program-analysis techniques with a focus on attacks identified against these systems and defenses crafted to date . Based on a study of five IoT programming platforms, we identify the key insights resulting from works in both the program analysis and security communities and relate the effectiveness of program-analysis techniques to security and privacy issues.
Revised:  In this paper, we study privacy and security issues in IoT that require program-analysis techniques with a focus on attacks identified against these systems and defenses crafted to date . Based on a study of five IoT programming platforms, we identify the key insights resulting from works in both the program analysis and security communities and relate the efficacy of program-analysis techniques to security and privacy issues.
Edit intent: fluency
Original:  Through these studies and explorations, we highlight key challenges and opportunities in calibrating for the environments in which IoT systems will be used.
Revised:  Through these explorations, we highlight key challenges and opportunities in calibrating for the environments in which IoT systems will be used.
Edit intent: clarity
Original:  IoT is now pervasive---new applications are being deployed in nearly every conceivable domain, leading to adoption of device-based interaction and automation.
Revised:  IoT is now pervasive---new applications are being used in nearly every conceivable domain, leading to adoption of device-based interaction and automation.
Edit intent: clarity
Original:  IoT is now pervasive---new applications are being deployed in nearly every conceivable domain, leading to adoption of device-based interaction and automation.
Revised:  IoT is now pervasive---new applications are being deployed in nearly every conceivable environment, which leads to the adoption of device-based interaction and automation.
Edit intent: clarity
Original:  Program-analysis is crucial in identifying IoT vulnerabilities , yet the application and scope of program analysis in IoT remains largely unexplored by the technical community.
Revised:  However, IoT has also raised issues about the security and privacy of these digitally augmented spaces. Program analysis is crucial in identifying IoT vulnerabilities , yet the application and scope of program analysis in IoT remains largely unexplored by the technical community.
Edit intent: coherence
Original:  Program-analysis is crucial in identifying IoT vulnerabilities , yet the application and scope of program analysis in IoT remains largely unexplored by the technical community.
Revised:  Program-analysis is crucial in identifying those issues , yet the application and scope of program analysis in IoT remains largely unexplored by the technical community.
Edit intent: clarity
Original:  Based on a study of five IoT programming platforms, we identify the key insights resulting from works in both the program analysis and security communities and relate the efficacy of program-analysis techniques to security and privacy issues.
Revised:  Based on a study of five IoT programming platforms, we identify the key insights that result from research efforts in both the program analysis and security communities and relate the efficacy of program-analysis techniques to security and privacy issues.
Edit intent: clarity
Original:  These general results were elucidated from non-equilibrium thermodynamic principles, where active cells play the role of engines to power oscillations in the medium.
Revised:  These general results were elucidated from non-equilibrium thermodynamic principles, where stimulated energy release from active cells drives oscillations in the medium.
Edit intent: clarity
Original:  This unexpected link between adaptation and oscillation is shown to underlie several known examples of dynamical quorum sensing, and as such may also be a source of inadvertent group behaviour in large populations of living organisms.
Revised:  The unexpected link between adaptation and oscillation is shown to underlie several known examples of dynamical quorum sensing, and as such may also be a source of inadvertent group behaviour in large populations of living organisms.
Edit intent: fluency
Original: Reinforcement learning in multi-agent systems has been studied in the fields of economic game theory, artificial intelligence and statistical physics by developing an analytical understanding of the learning dynamics (often in relation to the replicator dynamics of evolutionary game theory).
Revised: Reinforcement learning in multiagent systems has been studied in the fields of economic game theory, artificial intelligence and statistical physics by developing an analytical understanding of the learning dynamics (often in relation to the replicator dynamics of evolutionary game theory).
Edit intent: fluency
Original:  Environmental dynamics, i.e.  changes in the state of an environment affecting the agents' payoffs has received less attention, lacking a universal method to obtain deterministic equations from established multi-state reinforcement learning algorithms.
Revised:  Environmental dynamics, i.e. , changes in the state of an environment affecting the agents' payoffs has received less attention, lacking a universal method to obtain deterministic equations from established multi-state reinforcement learning algorithms.
Edit intent: fluency
Original:  Environmental dynamics, i.e.  changes in the state of an environment affecting the agents' payoffs has received less attention, lacking a universal method to obtain deterministic equations from established multi-state reinforcement learning algorithms.
Revised:  Environmental dynamics, i.e. changes in the state of an environment affecting the agents' payoffs has received less attention, lacking a universal method to obtain deterministic equations from established multistate reinforcement learning algorithms.
Edit intent: fluency
Original:  In this work we present a novel methodology to derive the deterministic limit resulting from an interaction-adaptation time scales separation of a general class of reinforcement learning algorithms, called temporal difference learning.
Revised:  In this work we present a novel methodology to derive the deterministic limit of a general class of reinforcement learning algorithms, called temporal difference learning.
Edit intent: coherence
Original:  This form of learning is equipped to function in more realistic multi-state environments by using the estimated value of future environmental states to adapt the agent's behavior.
Revised:  This form of learning is equipped to function in more realistic multistate environments by using the estimated value of future environmental states to adapt the agent's behavior.
Edit intent: fluency
Original:  Illustrations of their dynamics on two multi-agent, multi-state environments reveal a wide range of different dynamical regimes, such as convergence to fixed points, limit cycles  and even deterministic chaos.
Revised:  Illustrations of their dynamics on two multiagent, multistate environments reveal a wide range of different dynamical regimes, such as convergence to fixed points, limit cycles and even deterministic chaos.
Edit intent: fluency
Original:  Illustrations of their dynamics on two multi-agent, multi-state environments reveal a wide range of different dynamical regimes, such as convergence to fixed points, limit cycles  and even deterministic chaos.
Revised:  Illustrations of their dynamics on two multi-agent, multi-state environments reveal a wide range of different dynamical regimes, such as convergence to fixed points, limit cycles , and even deterministic chaos.
Edit intent: fluency
Original: We consider the problem of warehouse multi- robot automation system in discrete-time and discrete-space configuration with focus on the task allocation and conflict-free path planning.
Revised: We consider the problem of warehouse multi-robot automation system in discrete-time and discrete-space configuration with focus on the task allocation and conflict-free path planning.
Edit intent: fluency
Original:  A semi-complete potential field based local path planning algorithm is then proposed, named the recur- sive excitation/relaxation artificial potential field (RERAPF).
Revised:  A semi-complete potential field based local path planning algorithm is then proposed, named the recursive excitation/relaxation artificial potential field (RERAPF).
Edit intent: fluency
Original:  A mathematical proof is also presented to show the semi- completeness of the RERAPF algorithm.
Revised:  A mathematical proof is also presented to show the semi-completeness of the RERAPF algorithm.
Edit intent: fluency
Original:  Sim- ulation results are also presented for performance evaluation of the proposed path planning algorithm and the overall system.
Revised:  Simulation results are also presented for performance evaluation of the proposed path planning algorithm and the overall system.
Edit intent: fluency
Original:  Standard SSP variants  begin with an empty selection set ( cold-starting ) and perform the selection process once (single-round), over a single candidate set  .
Revised:  Standard SSP variants begin with an empty selection set ( cold-start ) and perform the selection process once (single-round), over a single candidate set .
Edit intent: fluency
Original:  Standard SSP variants  begin with an empty selection set ( cold-starting ) and perform the selection process once (single-round), over a single candidate set  .
Revised:  Standard SSP variants begin with an empty selection set ( cold-starting ) and perform the selection process once over a single candidate set .
Edit intent: clarity
Original:  Each new round has at hand the output of the previous one, i.e. its b selected employees, and tries to update optimally that selection by reassigning each job at most once.
Revised:  Each new round has at hand the output of the previous one, i.e. its b selected employees, and tries to update optimally that set by (re-)assigning each job at most once.
Edit intent: clarity
Original:  We set a rank-based objective of the process over the final job-to-employee assignment and we investigate analytically the optimal cutoff values with respect to the important parameters of the problem.
Revised:  We set a rank-based objective function over the final job-to-employee assignment and we investigate analytically the optimal cutoff values with respect to the important parameters of the problem.
Edit intent: clarity
Original: We present a novel method for the numerical pricing of American options based on Monte Carlo simulation and  optimization of exercise strategies.
Revised: We present a novel method for the numerical pricing of American options based on Monte Carlo simulation and the optimization of exercise strategies.
Edit intent: fluency
Original:  Previous solutions to this problem either explicitly or implicitly determine so-called optimal exercise regions , which consist of points in time and space at which the option is exercised.
Revised:  Previous solutions to this problem either explicitly or implicitly determine so-called optimal exercise regions , which consist of points in time and space at which the option is exercised.
Edit intent: fluency
Original:  Previous solutions to this problem either explicitly or implicitly determine so-called optimal exercise regions , which consist of points in time and space at which the option is exercised.
Revised:  Previous solutions to this problem either explicitly or implicitly determine so-called optimal exercise regions , which consist of points in time and space at which a given option is exercised.
Edit intent: clarity
Original:  In contrast, our method determines exercise rates of randomized exercise strategies.
Revised:  In contrast, our method determines the exercise rates of randomized exercise strategies.
Edit intent: fluency
Original: In recent years deep artificial neural networks (DNNs) have very successfully been employed in numerical simulations for a multitude of computational problems including, for example, object and face recognition, natural language processing, fraud detection, computational advertisement, and numerical approximations of partial differential equations (PDEs).
Revised: In recent years deep artificial neural networks (DNNs) have been successfully employed in numerical simulations for a multitude of computational problems including, for example, object and face recognition, natural language processing, fraud detection, computational advertisement, and numerical approximations of partial differential equations (PDEs).
Edit intent: clarity
Original:  Such numerical simulations indicate that DNNs seem to admit the fundamental flexibility to overcome the curse of dimensionality in the sense that the number of real parameters used to describe the DNN grows at most polynomially in both the reciprocal of the prescribed approximation accuracy \varepsilon > 0 and the dimension d \in N of the function which the DNN aims to approximate in such computational problems.
Revised:  These numerical simulations indicate that DNNs seem to admit the fundamental flexibility to overcome the curse of dimensionality in the sense that the number of real parameters used to describe the DNN grows at most polynomially in both the reciprocal of the prescribed approximation accuracy \varepsilon > 0 and the dimension d \in N of the function which the DNN aims to approximate in such computational problems.
Edit intent: fluency
Original:  Such numerical simulations indicate that DNNs seem to admit the fundamental flexibility to overcome the curse of dimensionality in the sense that the number of real parameters used to describe the DNN grows at most polynomially in both the reciprocal of the prescribed approximation accuracy \varepsilon > 0 and the dimension d \in N of the function which the DNN aims to approximate in such computational problems.
Revised:  Such numerical simulations indicate that DNNs seem to possess the fundamental flexibility to overcome the curse of dimensionality in the sense that the number of real parameters used to describe the DNN grows at most polynomially in both the reciprocal of the prescribed approximation accuracy \varepsilon > 0 and the dimension d \in N of the function which the DNN aims to approximate in such computational problems.
Edit intent: clarity
Original:  There is also a large number of rigorous mathematical approximation results for artificial neural networks in the scientific literature but there are only a few special situations where results in the literature can rigorously explain the success of DNNs when approximating high-dimensional functions .
Revised:  There is also a large number of rigorous mathematical approximation results for artificial neural networks in the scientific literature but there are only a few special situations where results in the literature can rigorously justify the success of DNNs when approximating high-dimensional functions .
Edit intent: fluency
Original:  There is also a large number of rigorous mathematical approximation results for artificial neural networks in the scientific literature but there are only a few special situations where results in the literature can rigorously explain the success of DNNs when approximating high-dimensional functions .
Revised:  There is also a large number of rigorous mathematical approximation results for artificial neural networks in the scientific literature but there are only a few special situations where results in the literature can rigorously explain the success of DNNs in high-dimensional functions .
Edit intent: clarity
Original:  The key contribution of this article is to reveal that DNNs do overcome the curse of dimensionality in the numerical approximation of Kolmogorov PDEs with constant diffusion and nonlinear drift coefficients.
Revised:  The key contribution of this paper is to reveal that DNNs do overcome the curse of dimensionality in the numerical approximation of Kolmogorov PDEs with constant diffusion and nonlinear drift coefficients.
Edit intent: fluency
Original:  We prove that the number of parameters used to describe the employed DNN grows at most polynomially in both the  reciprocal of the prescribed approximation accuracy \varepsilon > 0 and the PDE dimension d \in N . A crucial ingredient in our proof is the fact that the artificial neural network used to approximate the solution of the PDE is indeed a deep artificial neural network with a large number of hidden layers.
Revised:  We prove that the number of parameters used to describe the employed DNN grows at most polynomially in both the PDE dimension d \in N and the reciprocal of the prescribed approximation accuracy \varepsilon > 0 and the PDE dimension d \in N . A crucial ingredient in our proof is the fact that the artificial neural network used to approximate the solution of the PDE is indeed a deep artificial neural network with a large number of hidden layers.
Edit intent: coherence