wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Revised:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) for distribution of the first passage time of crossing the threshold, which is the distribution of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Edit intent: meaning-changed
Original:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Revised:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for this neuron. The calculation is based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Edit intent: clarity
Original:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Revised:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known PDF p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Edit intent: fluency
Original:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Revised:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for that same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Edit intent: clarity
Original:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and the properties of the feedback line.
Revised:  We have obtained a general relation allowing calculating exactly the probability density function ( pdf ) p(t) of output interspike intervals (ISI) values for a neuronwith feedback based on known pdf p^0(t) for the same neuron without feedback, intensity of the input stream \lambda and properties of the feedback line.
Edit intent: fluency
Original:  In contrast to the Jarque-Bera test that is based on the third and fourth moment, our test relies on the conditional second moments.
Revised:  We derive asymptotic distributions for conditional trimmed mean and variance estimators, and use this to show asymptotic normality of the proposed test statistic. Using financial empirical data, we compare our framework to various statistical tests including the Jarque-Bera test that is based on the third and fourth moment, our test relies on the conditional second moments.
Edit intent: meaning-changed
Original:  We derive asymptotic distributions for conditional trimmed mean and variance estimators, and use this to show asymptotic normality of the proposed teststatistic. Using financial empirical data , we compare our framework to various statistical tests including the Jarque-Bera test that is based on third and fourth moments .
Revised:  Next, we show how to use our framework to construct a powerful statistical normality test. In particular , we compare our framework to various statistical tests including the Jarque-Bera test that is based on third and fourth moments .
Edit intent: clarity
Original:  Using financial empirical data , we compare our framework to various statistical tests including the Jarque-Bera test that is based on third and fourth moments . We show that our methodology outperforms existing methods on market-stock data  .
Revised:  Using financial empirical data , we compare our framework to various statistical tests including the Jarque-Bera test that is based on third and fourth moments , and show that in most considered cases our framework outperforms all others, both on simulated and market-stock data .
Edit intent: clarity
Original:  We construct  goodness-of-fit statistic that has a direct financial interpretation and can be used to assess the impact of fat-tails on central data normality assumption . Next, we show how to use our framework to construct a powerful statistical normality test.
Revised:  We construct a goodness-of-fit statistic that has a direct financial interpretation and can be used to assess the impact of fat-tails on central data normality assumption . Next, we show how to use our framework to construct a powerful statistical normality test.
Edit intent: fluency
Original:  We construct  goodness-of-fit statistic that has a direct financial interpretation and can be used to assess the impact of fat-tails on central data normality assumption . Next, we show how to use our framework to construct a powerful statistical normality test.
Revised:  We construct goodness-of-fit statistic that has a direct interpretation and can be used to assess the impact of fat-tails on central data normality assumption . Next, we show how to use our framework to construct a powerful statistical normality test.
Edit intent: clarity
Original:  We construct  goodness-of-fit statistic that has a direct financial interpretation and can be used to assess the impact of fat-tails on central data normality assumption . Next, we show how to use our framework to construct a powerful statistical normality test.
Revised:  We construct goodness-of-fit statistic that has a direct financial interpretation and can be used to assess the impact of fat-tails on central data conditional dispersion . Next, we show how to use our framework to construct a powerful statistical normality test.
Edit intent: meaning-changed
Original:  We construct  goodness-of-fit statistic that has a direct financial interpretation and can be used to assess the impact of fat-tails on central data normality assumption . Next, we show how to use our framework to construct a powerful statistical normality test.
Revised:  We construct goodness-of-fit statistic that has a direct financial interpretation and can be used to assess the impact of fat-tails on central data normality assumption . Next, we show how to use this framework to construct a powerful statistical normality test.
Edit intent: clarity
Original:  We construct  goodness-of-fit statistic that has a direct financial interpretation and can be used to assess the impact of fat-tails on central data normality assumption . Next, we show how to use our framework to construct a powerful statistical normality test.
Revised:  We construct goodness-of-fit statistic that has a direct financial interpretation and can be used to assess the impact of fat-tails on central data normality assumption . Next, we show how to use our framework to construct a powerful normality test.
Edit intent: clarity
Original:  In particular, we compare our methodology to various popular normality statistical tests, including the Jarque--Bera test that is based on third and fourth moments, and show that in most considered cases our framework outperforms all others, both on simulated and market-stock data.
Revised:  In particular, we compare our methodology to various popular normality tests, including the Jarque--Bera test that is based on third and fourth moments, and show that in most considered cases our framework outperforms all others, both on simulated and market-stock data.
Edit intent: clarity
Original:  In particular, we compare our methodology to various popular normality statistical tests, including the Jarque--Bera test that is based on third and fourth moments, and show that in most considered cases our framework outperforms all others, both on simulated and market-stock data.
Revised:  In particular, we compare our methodology to various popular normality statistical tests, including the Jarque--Bera test that is based on third and fourth moments, and show that in many cases our framework outperforms all others, both on simulated and market-stock data.
Edit intent: clarity
Original:  In particular, we compare our methodology to various popular normality statistical tests, including the Jarque--Bera test that is based on third and fourth moments, and show that in most considered cases our framework outperforms all others, both on simulated and market-stock data.
Revised:  In particular, we compare our methodology to various popular normality statistical tests, including the Jarque--Bera test that is based on third and fourth moments, and show that in most considered cases our framework outperforms all others, both on simulated and market stock data.
Edit intent: fluency
Original: Floating-point arithmetic is the computational foundation of numerical scientific software . Compiler optimizations that affect floating-point arithmetic can have a significant impact on the integrity, reproducibility, and performance of HPC scientific applications.
Revised: Successful HPC software applications are long-lived. When ported across machines and their compilers, these applications often produce different numerical results, many of which are unacceptable. Such variability is also a concern while optimizing the code more aggressively to gain performance. Efficient tools that help locate the program units (files and functions) within which most of the variability occurs are badly needed, both to plan for code ports and to root-cause errors due to variability when they happen in the field . Compiler optimizations that affect floating-point arithmetic can have a significant impact on the integrity, reproducibility, and performance of HPC scientific applications.
Edit intent: meaning-changed
Original: Floating-point arithmetic is the computational foundation of numerical scientific software . Compiler optimizations that affect floating-point arithmetic can have a significant impact on the integrity, reproducibility, and performance of HPC scientific applications. Unfortunately the interplay between the compiler-induced variability and runtime performance from compiler optimizations is not well understood by programmers, a problem that is aggravated by the lack of analysis tools in this domain.
Revised: Floating-point arithmetic is the computational foundation of numerical scientific software . 
Edit intent: coherence
Original:  In this paper, we present a novel set of techniques, as part of a multi-level analysis, that allow programmers to automatically search the space of compiler-induced variabilityand performance using their own inputs and metrics; these techniques allow programmers to pinpoint the root-cause of non-reproducible behavior to function granularity across multiple compilers and platforms using a bisection algorithm. We have demonstrated our methods on real-world code bases. We provide a performance and reproducibility analysis on the MFEM library as well as a study of compiler characterization by attempting to isolate all 1,086 found instances of result variability. The Laghos proxy app is analyzed and a significant divergent floating-point variability is identified in their code base.
Revised:  In this work, we offer an enhanced version of the open-source testing framework FLiT to serve these roles. Key new features of FLiT include a suite of bisection algorithms that help locate the root causes of variability. Another added feature allows an analysis of the tradeoffs between performance and the degree of variability. Our new contributions also include a collection of case studies. Results on the MFEM finite-element library include variability/performance tradeoffs, and the identification of a (hitherto unknown) abnormal level of result-variability even under mild compiler optimizations. Results from studying the Laghos proxy application include identifying a significantly divergent floating-point variability is identified in their code base.
Edit intent: coherence
Original:  The Laghos proxy app is analyzed and a significant divergent floating-point variability is identified in their code base. Our bisect algorithm pinpointed the problematic function with as little as 14 program executions.
Revised:  The Laghos proxy app is analyzed and a significant divergent floating-point result-variability and successful root-causing down to the problematic function with as little as 14 program executions.
Edit intent: clarity
Original:  Furthermore, an evaluation with 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, found that our framework is 100 \% accurate in detecting the file and function location of the injected problem with an average of  15 program executions.
Revised:  Finally, in an evaluation of 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, found that our framework is 100 \% accurate in detecting the file and function location of the injected problem with an average of 15 program executions.
Edit intent: coherence
Original:  Furthermore, an evaluation with 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, found that our framework is 100 \% accurate in detecting the file and function location of the injected problem with an average of  15 program executions.
Revised:  Furthermore, an evaluation with 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, we showed that the FLiT framework has 100 \% accurate in detecting the file and function location of the injected problem with an average of 15 program executions.
Edit intent: clarity
Original:  Furthermore, an evaluation with 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, found that our framework is 100 \% accurate in detecting the file and function location of the injected problem with an average of  15 program executions.
Revised:  Furthermore, an evaluation with 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, found that our framework is 100 precision and recall in discovering the file and function location of the injected problem with an average of 15 program executions.
Edit intent: clarity
Original:  Furthermore, an evaluation with 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, found that our framework is 100 \% accurate in detecting the file and function location of the injected problem with an average of  15 program executions.
Revised:  Furthermore, an evaluation with 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, found that our framework is 100 \% accurate in detecting the file and function locations of the injections all within an average of 15 program executions.
Edit intent: clarity
Original:  Furthermore, an evaluation with 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, found that our framework is 100 \% accurate in detecting the file and function location of the injected problem with an average of  15 program executions.
Revised:  Furthermore, an evaluation with 4,376 controlled injections of floating-point perturbations on the LULESH proxy application, found that our framework is 100 \% accurate in detecting the file and function location of the injected problem with an average of only 15 program executions.
Edit intent: clarity
Original: In here presented what-if analysis we substitute a unified therapy with a ' therapy species', which is the population of heterogeneous therapies evolving accordingly to evolutionary principles.
Revised: In here presented in silico study we suggest a way how to implement the evolutionary principles into anti-cancer therapy design. We hypothesize that instead of its ongoing supervised adaptation, the therapy may be constructed as a self-sustaining evolutionary process in a dynamic fitness landscape established implicitly by evolving cancer cells, microenvironment and the therapy itself. For these purposes, we replace a unified therapy with a ' therapy species', which is the population of heterogeneous therapies evolving accordingly to evolutionary principles.
Edit intent: meaning-changed
Original: In here presented what-if analysis we substitute a unified therapy with a ' therapy species', which is the population of heterogeneous therapies evolving accordingly to evolutionary principles. Each therapy within the species may be, at any time, either free or in the exclusive complex with one cell. The therapy is allowed to create the complex with another cell only after its current host cell has died, playing the role of a catalyst. Regarding therapeutic context, the fitnesses of the therapies reflect their respective cytotoxicities in a way which conforms to evolutionary causation.
Revised: In here presented what-if analysis we substitute a unified therapy with a ' therapy species', which is the population of heterogeneous elementary therapies, and propose a way how to turn the toxicity of the elementary therapy into its fitness in a way which conforms to evolutionary causation.
Edit intent: clarity
Original:  Results of the minimalistic in silico modeling indicate that the resistant cells could bias the evolution of the therapies towards more toxic ones by inhibiting non-efficient therapies. In this way , not only  therapies govern the evolution of different  phenotypes, but variable resistances of cells govern the evolution of  therapies as well  .
Revised:  As a result , not only therapies govern the evolution of different phenotypes, but variable resistances of cells govern the evolution of therapies as well .
Edit intent: coherence
Original:  In this way , not only  therapies govern the evolution of different  phenotypes, but variable resistances of cells govern the evolution of  therapies as well  .
Revised:  In this way , not only therapies govern the evolution of different phenotypes, but variable resistances of cells govern the evolution of therapies as well . We illustrate the approach by the minimalistic ad hoc evolutionary model. Its results indicate that the resistant cells could bias the evolution towards more toxic elementary therapies by inhibiting the less toxic ones .
Edit intent: meaning-changed
Original:  Our approximations are motivated by  extensions of the so-called Normal Power Approximation, used for approximating the cumulative distribution function of a random variable, incorporating not only the skewness but the kurtosis of the random variable in question as well.
Revised:  Our approximations are motivated by that kind of extensions of the so-called Normal Power Approximation, used for approximating the cumulative distribution function of a random variable, incorporating not only the skewness but the kurtosis of the random variable in question as well.
Edit intent: clarity
Original:  Our approximations are motivated by  extensions of the so-called Normal Power Approximation, used for approximating the cumulative distribution function of a random variable, incorporating not only the skewness but the kurtosis of the random variable in question as well.
Revised:  Our approximations are motivated by extensions of the so-called Normal Power Approximation, used for approximating the cumulative distribution function of a random variable, which incorporate not only the skewness but the kurtosis of the random variable in question as well.
Edit intent: coherence
Original:  We review the mathematical models of the regulatory networks involved in EMT, with a particular emphasis on the network motifs (such as coupled feedback loops) that can generate hybrid states that are intermediate between the epithelial and mesenchymal states.
Revised:  We review the mathematical models of the regulatory networks involved in EMT, with a particular emphasis on the network motifs (such as coupled feedback loops) that can generate intermediate hybrid states between the epithelial and mesenchymal states.
Edit intent: clarity
Original: Using ideas from homogenization theory and stability of viscosity solutions, we provide an asymptotic expansion of the value function of a multidimensional utility maximization problem  with small non-linear price impact.
Revised: Using ideas from homogenization theory and stability of viscosity solutions, we provide an asymptotic expansion of the value function of a multidimensional utility maximization problem from consumption with small non-linear price impact.
Edit intent: meaning-changed
Original:  But resources are often allocated to groups, such as families or countries, whose members consume the same bundle but have different preferences. Do fair and efficient allocations exist in such an "economy of families"? We adapt three common notions of fairness: fair-share, no-envy and egalitarian-equivalence , to an economy of families.
Revised:  But resources are often allocated to groups, such as families or countries, whose members consume the same bundle . Families are our lead example: the father, mother and children get to consume the same garden, kitchen, and vacations. We adapt each of the three most popular principles of fairness: fair-share, no-envy and egalitarian-equivalence , to an economy of families.
Edit intent: meaning-changed
Original:  The stronger adaptation --- individual fairness--- requires that each individual in each familyperceives the division as fair ; the weaker one --- family fairness --- requires that the familyas a whole, treated as a single agent with (typically ) incomplete preferences, perceives the division as fair. Individual-fair-share, family-no-envy and family-egalitarian-equivalence are compatible with efficiency under broad conditions. The same holds for individual-no-envy when there are only two families. In contrast, individual-no-envy with three or more families  and individual-egalitarian-equivalence with two or more familiesare typically incompatible with efficiency, unlike the situation in an economy of individuals.
Revised:  For any given criterion of fairness, an allocation is *unanimous-fair* if it is fair according to every individual member of each family, it is *aggregate-fair* if it is fair according to a particular aggregation of all family members' preferences, and it is *collective-fair* if it is fair according to the family's -- typically incomplete -- preferences, that rank a bundle above another bundle if and only if each member of the family ranks the first bundle above the second. While efficiency is generally incompatible with unanimous egalitarian equivalence, and incompatible with unanimous envy-freeness in economies with three or more families and individual-egalitarian-equivalence with two or more familiesare typically incompatible with efficiency, unlike the situation in an economy of individuals.
Edit intent: meaning-changed