wanyu/IteraTeR_full_sent huggingface dataset:
Original:  To test the model, we perform experiments with%DIFDELCMD < {\it %%% E. coli strains mutant for recA, sulA and slmA, factors known to affect replication fork dynamics and coupling to cell division. Our validated model of RFstalling based cell division, can reproduce the variability in cell size distribution seen in these mutant strains, and provides a predictive tool to further examine stochastic effects in bacterial cell size regulation .
Revised:  To test the model, we perform experiments with%DIFDELCMD < {\it %%% E. coli predicts an increase in cell size variability with growth rate, consistent with previous experimental reports. We perturb the model to test the effect of increased replication fork (RF) stalling frequency, or uncoupling RF stalling from the cell-division machinery. Indeed, despite ignoring DNA and protein segregation asymmetry, the model can faithfully reproduce quantitative changes in cell size distribution seen in these mutant strains, and provides a predictive tool to further examine stochastic effects in bacterial cell size regulation .
Edit intent: meaning-changed
Original:  Our validated model of RFstalling based cell division, can reproduce the variability in cell size distribution seen in these mutant strains, and provides a predictive tool to further examine stochastic effects in bacterial cell size regulation .
Revised:  Our validated model of RFstalling based cell division, can reproduce the variability in cell size distributions. In our model, multi-fork replication produces multiplicative 'noise' and provides a predictive tool to further examine stochastic effects in bacterial cell size regulation .
Edit intent: meaning-changed
Original:  Our validated model of RFstalling based cell division, can reproduce the variability in cell size distribution seen in these mutant strains, and provides a predictive tool to further examine stochastic effects in bacterial cell size regulation .
Revised:  Our validated model of RFstalling based cell division, can reproduce the variability in cell size distribution seen in these mutant strains, and provides a mechanism linking growth rate and cell size variability .
Edit intent: clarity
Original:  Finally, we formulate a calculus  that is complete for finite support distributions, and that can be compiled to a restricted class of CRNs that at steady state realize those distributions . We illustrate the approach on an example of drug resistance in bacteria .
Revised:  Finally, we formulate a calculus that is complete for finite support distributions, and that can be compiled to a restricted class of CRNs that at steady state realize those distributions .
Edit intent: clarity
Original:  This methodology is suitable for the social sciences since the primary source of uncertainty are the members of the system themselves and presently, no methods are known to fully determine the outcomes in such an environment, which perhaps would require being able to read the minds of everyone involved and to anticipate their actions continously .
Revised:  This methodology is suitable for the social sciences since the primary source of uncertainty are the members of the system themselves and presently, no methods are known to fully determine the outcomes in such an environment, which perhaps would require being able to read the minds of everyone involved and to anticipate their actions continuously .
Edit intent: fluency
Original:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription ' Don't Optimize, Simply Randomize' . 1. Newsvendor Inventory Management Problem 2. School Admissions.
Revised:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription , " Don't Optimize, Simply Randomize' . 1. Newsvendor Inventory Management Problem 2. School Admissions.
Edit intent: fluency
Original:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription ' Don't Optimize, Simply Randomize' . 1. Newsvendor Inventory Management Problem 2. School Admissions.
Revised:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription ' Don't Simply Optimize, Also Randomize, perhaps best described by the term - Randomoptimization" . 1. Newsvendor Inventory Management Problem 2. School Admissions.
Edit intent: meaning-changed
Original:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription, " Don't Simply Optimize, Also Randomize, perhaps best described by the term - Randomoptimization" . 1. Newsvendor Inventory Management Problem 2. School Admissions.
Revised:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription, ' Don't Simply Optimize, Also Randomize, perhaps best described by the term - Randomoptimization" . 1. Newsvendor Inventory Management Problem 2. School Admissions.
Edit intent: fluency
Original:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription, " Don't Simply Optimize, Also Randomize, perhaps best described by the term - Randomoptimization" . 1. Newsvendor Inventory Management Problem 2. School Admissions.
Revised:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription, " Don't Simply Optimize, Also Randomize, perhaps best described by the term - Randoptimization' . 1. Newsvendor Inventory Management Problem 2. School Admissions.
Edit intent: fluency
Original:  This methodology is suitable for the social sciences since the primary source of uncertainty are the members of the system themselves and presently, no methods are known to fully determine the outcomes in such an environment, which perhaps would require being able to read the minds of everyone involved and to anticipate their actions continuously. Admittedly, we are not qualified to recommend whether such an approach is conducive for the natural sciences, unless perhaps, bounds can be established on the levels of uncertainty in a system and it is shown conclusively that a better understanding of the system and hence improved decision making will not alter the outcomes. We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription, ' Don't Simply Optimize, Also Randomize, perhaps best described by the term - Randoptimization '. 1. Newsvendor Inventory Management Problem 2. School Admissions.
Revised:  The example we fully develop is the news-vendor inventory management problem with demand uncertainty with the prescription, " Don't Simply Optimize, Also Randomize, perhaps best described by the term - Randoptimization '. 1. Newsvendor Inventory Management Problem 2. School Admissions.
Edit intent: coherence
Original:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription, ' Don't Simply Optimize, Also Randomize, perhaps best described by the term - Randoptimization '. 1. Newsvendor Inventory Management Problem 2. School Admissions. 3. Journal Submissions. 4. Job Candidate Selection. 5. Stock Picking .
Revised:  We consider a number of examples and develop both the theoretical framework and empirical tests where such an approach might be helpful, with the common prescription, ' Don't Simply Optimize, Also Randomize, perhaps best described by the term - Randoptimization " .
Edit intent: coherence
Original:  The example we fully develop is the news-vendor inventory management problem with demand uncertainty with the prescription, "Don't Simply Optimize, Also Randomize , perhaps best described by the term - Randoptimization"  .
Revised:  The example we develop in greater detail is the news-vendor inventory management problem with demand uncertainty with the prescription, "Don't Simply Optimize, Also Randomize , perhaps best described by the term - Randoptimization" .
Edit intent: clarity
Original:  The example we fully develop is the news-vendor inventory management problem with demand uncertainty with the prescription, "Don't Simply Optimize, Also Randomize , perhaps best described by the term - Randoptimization"  .
Revised:  The example we fully develop is the news-vendor inventory management problem with demand uncertainty . We briefly discuss areas, where such an approach might be helpful, with the common prescription, "Don't Simply Optimize, Also Randomize , perhaps best described by the term - Randoptimization" .
Edit intent: meaning-changed
Original:  The example we fully develop is the news-vendor inventory management problem with demand uncertainty with the prescription, "Don't Simply Optimize, Also Randomize , perhaps best described by the term - Randoptimization"  .
Revised:  The example we fully develop is the news-vendor inventory management problem with demand uncertainty with the prescription, "Don't Simply Optimize, Also Randomize ; perhaps best described by the term - Randoptimization" .
Edit intent: fluency
Original:  The example we fully develop is the news-vendor inventory management problem with demand uncertainty with the prescription, "Don't Simply Optimize, Also Randomize , perhaps best described by the term - Randoptimization"  .
Revised:  The example we fully develop is the news-vendor inventory management problem with demand uncertainty with the prescription, "Don't Simply Optimize, Also Randomize , perhaps best described by the term - Randoptimization" . 1. News-vendor Inventory Management 2. School Admissions 3. Journal Submissions 4. Job Candidate Selection 5. Stock Picking 6. Monetary Policy This methodology is suitable for the social sciences since the primary source of uncertainty are the members of the system themselves and presently, no methods are known to fully determine the outcomes in such an environment, which perhaps would require being able to read the minds of everyone involved and to anticipate their actions continuously. Admittedly, we are not qualified to recommend whether such an approach is conducive for the natural sciences, unless perhaps, bounds can be established on the levels of uncertainty in a system and it is shown conclusively that a better understanding of the system and hence improved decision making will not alter the outcomes .
Edit intent: meaning-changed
Original: In this paper we describe a useful risk management tool to analyse annuity and life insurance portfolios where mortality is modelled stochastically .
Revised: Using an extended version of the credit risk model CreditRisk+, we develop a flexible framework with numerous applications amongst which we find stochastic mortality modelling, forecasting of death causes as well as profit and loss modelling of life insurance and annuity portfolios which can be used in (partial) internal models under Solvency II .
Edit intent: meaning-changed
Original:  We provide various estimation procedures based on publicly available data . The model allows for various other applications, including mortality forecasts . Compared to the Lee-Carter model, we have a more flexible framework, get tighter bounds and can directly extract several sources of uncertainty.
Revised:  We provide various estimation procedures based on publicly available data . Compared to the Lee-Carter model, we have a more flexible framework, get tighter bounds and can directly extract several sources of uncertainty.
Edit intent: clarity
Original: We show from a simple model that a country's technological development can be measured by the logarithm of the number of productsit makes. We show that much of the income gaps among countries are due to differences in technology, as measured by this simple metric. Finally, we show that the so-called Economic Complexity Index (ECI), a recently proposed measure of collective knowhow, is in fact an estimate of this simple metric (with correlation above 0.9) .
Revised: We show from a simple model that a country's products. They argued that this measure explains economic growth better than the conventional variables such as human capital. This paper suggests a simpler measure of production complexity, the logarithm of product diversification, which has a natural foundation in information theory: it measures the information needed to encode the knowledge required to make a country's products. This measure explains well the income differences between countries. It has a basic link with ECI that is strongly supported by the data .
Edit intent: meaning-changed
Original: Several studies assert that the random access procedure of the Long Term Evolution (LTE) cellular standard may not be effective whenever a massive number of synchronous connection attempts are performed by terminals, as may happen in a typical Internet of Things or Smart City scenario.
Revised: Several studies assert that the random access procedure of the Long Term Evolution (LTE) cellular standard may not be effective whenever a massive number of simultaneous connection attempts are performed by terminals, as may happen in a typical Internet of Things or Smart City scenario.
Edit intent: fluency
Original: We present a stochastic framework to study signal transmission in a generic two-step cascade S \rightarrow X \rightarrow Y. Starting from a set of Langevin equations obeying Gaussian noise processes we calculate the variance and covariance associated with the system components .
Revised: We present a stochastic framework to study signal transmission in a generic two-step cascade S \rightarrow X \rightarrow Y. Starting from a set of Langevin equations obeying Gaussian noise processes we calculate the variance and covariance while considering both linear and nonlinear production terms for different biochemical species of the cascade .
Edit intent: meaning-changed
Original: The realised characteristics for Discretisation-Invariant (DI) swaps satisfy the aggregation propertywhen restricted to multivariate processes that are ]  deterministic functions of martingales.
Revised: The realised characteristics for Discretisation-Invariant (DI) swaps satisfy the aggregation propertywhen restricted to multivariate processes that are 2012] deterministic functions of martingales.
Edit intent: fluency
Original: The realised characteristics for Discretisation-Invariant (DI) swaps satisfy the aggregation propertywhen restricted to multivariate processes that are ]  deterministic functions of martingales.
Revised: The realised characteristics for Discretisation-Invariant (DI) swaps satisfy the aggregation propertywhen restricted to multivariate processes that are ] for twice continuously differentiable deterministic functions of martingales.
Edit intent: meaning-changed
Original: The realised characteristics for Discretisation-Invariant (DI) swaps satisfy the aggregation propertywhen restricted to multivariate processes that are ]  deterministic functions of martingales. Hence DI swaps have model-free fair values, in that a no-arbitrage assumption for forward prices is sufficient to derive exact option replication portfolios with neither jump nor discrete monitoring errors.
Revised: The realised characteristics for Discretisation-Invariant (DI) swaps satisfy the aggregation propertywhen restricted to multivariate processes that are ] deterministic functions of a multivariate martingale. They are initially characterised as solutions to a second-order system of PDEs, then those pay-offs based on martingale and log-martingale processes alone form a vector space. Hence there exist an infinite variety of other variance and higher-moment risk premia that are less prone to bias than standard variance swaps because their option replication portfolios with neither jump nor discrete monitoring errors.
Edit intent: meaning-changed
Original:  Hence DI swaps have model-free fair values, in that a no-arbitrage assumption for forward prices is sufficient to derive exact option replication portfolios with neither jump nor discrete monitoring errors. This restriction allows the characterisation of a vector space of DI swaps which provides a great variety of risk premia .
Revised:  Hence DI swaps have model-free fair values, in that a no-arbitrage assumption for forward prices is sufficient to derive exact option replication portfolios have no discrete-monitoring or jump errors .
Edit intent: clarity
Original:   A sub-class consists of pay-offs with fair values that are also free from numerical integration errors over option strikes , where exact pricing and hedging is possible via dynamic trading strategies on a few simple puts and calls.
Revised:  Their fair values are also independent of the monitoring partition. A sub-class consists of pay-offs with fair values that are also free from numerical integration errors over option strikes , where exact pricing and hedging is possible via dynamic trading strategies on a few simple puts and calls.
Edit intent: meaning-changed
Original:   A sub-class consists of pay-offs with fair values that are also free from numerical integration errors over option strikes , where exact pricing and hedging is possible via dynamic trading strategies on a few simple puts and calls.
Revised:  A sub-class consists of pay-offs with fair values that are further free from numerical integration errors over option strikes , where exact pricing and hedging is possible via dynamic trading strategies on a few simple puts and calls.
Edit intent: clarity
Original:   A sub-class consists of pay-offs with fair values that are also free from numerical integration errors over option strikes , where exact pricing and hedging is possible via dynamic trading strategies on a few simple puts and calls.
Revised:  A sub-class consists of pay-offs with fair values that are also free from numerical integration errors over option strikes . Here exact pricing and hedging is possible via dynamic trading strategies on a few simple puts and calls.
Edit intent: coherence
Original:   A sub-class consists of pay-offs with fair values that are also free from numerical integration errors over option strikes , where exact pricing and hedging is possible via dynamic trading strategies on a few simple puts and calls.
Revised:  A sub-class consists of pay-offs with fair values that are also free from numerical integration errors over option strikes , where exact pricing and hedging is possible via dynamic trading strategies on a few vanilla puts and calls.
Edit intent: clarity
Original: The efficiency of intracellular transport of cargo from specific source to target locations is strongly dependent upon molecular motor assisted motion along cytoskeleton filaments, microtubules and actin filaments. Radial transport along microtubules and lateral transport along the filaments of the actin cortex underneath the cell membrane are characteristic for cells with a centrosome. Here we show that this specific URLanization for ballistic transport in conjunction with intermittent diffusion realizes a spatially inhomogeneous intermittent search strategythat is in general optimal for small thicknesses of the actin cortex. We prove optimality in terms of mean first passage times for three different, frequently encountered intracellular transport tasks: i) the narrow escapeproblem (e.g. transport of cargo to a synapse or other specific region of the cell membrane, ii) reaction kinetics enhancement (e.g. binding of a mobile particle with a immobile or mobile target within the cell, iii) the reaction-escape problem (e. g. release of cargo at a synapse after intracellular vesicle pairing.
Revised: We consider random search processes alternating stochastically between diffusion and ballistic motion, in which the distribution function of ballistic motion directions varies from point to point in space. The specific space dependence of the directional distribution together with the switching rates between the two modes of motion establishes a spatially inhomogeneous search strategy. We show that the mean first passage times for three different, frequently encountered intracellular transport tasks: i) the narrow escapeproblem (e.g. transport of cargo to a synapse or other specific region of the cell membrane, ii) reaction kinetics enhancement (e.g. binding of a mobile particle with a immobile or mobile target within the cell, iii) the reaction-escape problem (e. g. release of cargo at a synapse after intracellular vesicle pairing.
Edit intent: meaning-changed
Original:  We prove optimality in terms of mean first passage times for three different, frequently encountered intracellular transport tasks: i) the narrow escapeproblem (e.g. transport of cargo to a synapse or other specific region of the cell membrane, ii) reaction kinetics enhancement (e.g. binding of a mobile particle with a immobile or mobile target within the cell, iii) the reaction-escape problem (e. g. release of cargo at a synapse after intracellular vesicle pairing.
Revised:  We prove optimality in terms of mean first passage times for several standard search problems - narrow escape, reaction partner finding, reaction-escape problem (e. g. release of cargo at a synapse after intracellular vesicle pairing.
Edit intent: clarity
Original:  We prove optimality in terms of mean first passage times for three different, frequently encountered intracellular transport tasks: i) the narrow escapeproblem (e.g. transport of cargo to a synapse or other specific region of the cell membrane, ii) reaction kinetics enhancement (e.g. binding of a mobile particle with a immobile or mobile target within the cell, iii) the reaction-escape problem (e. g. release of cargo at a synapse after intracellular vesicle pairing. The results indicate that living cells realize optimal search strategies for various intracellular transport problems %DIFDELCMD < {\it %%% economically through a spatial URLanization that involves  only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.
Revised:  We prove optimality in terms of mean first passage times for three different, frequently encountered intracellular transport tasks: i) the narrow escapeproblem (e.g. transport of cargo to a synapse or other specific region of the cell membrane, ii) reaction kinetics enhancement (e.g. binding of a mobile particle with a immobile or mobile target within the cell, iii) the reaction-escape - can be minimized with a directional distribution that is reminiscent of the URLanization of the cytoskeleton filaments of cells with a centrosome: radial ballistic transport from center to periphery and back, and ballistic transport in random directions within a concentric shell of thickness \Delta_{\rm opt that living cells realize optimal search strategies for various intracellular transport problems %DIFDELCMD < {\it %%% economically through a spatial URLanization that involves only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.
Edit intent: meaning-changed
Original:  The results indicate that living cells realize optimal search strategies for various intracellular transport problems %DIFDELCMD < {\it %%% economically through a spatial URLanization that involves  only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.
Revised:  The results indicate that living cells realize efficient search strategies for various intracellular transport problems %DIFDELCMD < {\it %%% economically through a spatial URLanization that involves only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.
Edit intent: clarity