wanyu/IteraTeR_v2 huggingface dataset:
Original: I present the phase diagram of spiking neural networks, This phase diagram is useful in three ways, first, it gives us insight about the evolutionary advantage of natural parameters, second, it gives intuition about the parameters that ought to be used in a simulation, and third, it present the robustness of results of a simulation in respect to the parameters.
Revised: In computer simulations of spiking neural networks, This phase diagram is useful in three ways, first, it gives us insight about the evolutionary advantage of natural parameters, second, it gives intuition about the parameters that ought to be used in a simulation, and third, it present the robustness of results of a simulation in respect to the parameters.
Edit intent: clarity
Original:  This  dialogue is the continuation of the previous FAQ "Counterparty Risk, Collateral and Funding FAQ" by Brigo (2011).
Revised:  This dialogue is the continuation of the "Counterparty Risk, Collateral and Funding FAQ" by Brigo (2011).
Edit intent: clarity
Original:  Through questions and answers and  by referring to the growing body of literature on the subject  we present a unified view of valuation (and risk) that takes all such aspects into account .
Revised:  Through questions and answers and by referring to the growing body of literature on the subject , we present a unified view of valuation (and risk) that takes all such aspects into account .
Edit intent: fluency
Original:  The dialogue is in the form of a Q A between a senior expert and a recently hired colleague .
Revised:  The dialogue is in the form of a Q .
Edit intent: clarity
Original:  Similar results for d-dimensional Euclidean space are discussed .
Revised:  Similar results for d-dimensional Euclidean space are conjectured .
Edit intent: clarity
Original: Motivation: Electrospray tandem mass spectrometry (ESI-MS/MS) is commonly used in high-throughput metabolomics.
Revised:  Electrospray tandem mass spectrometry (ESI-MS/MS) is commonly used in high-throughput metabolomics.
Edit intent: coherence
Original:  However, one of the key obstacles to the effective use of this technology is the difficulty in processing measured spectra to accurately and efficiently identify metabolites.
Revised:  However, one of the key obstacles to the effective use of this technology is the difficulty in interpreting measured spectra to accurately and efficiently identify metabolites.
Edit intent: clarity
Original:  Traditional methods for automated metabolite identification compare a target MS or MS/MS spectrum to  spectra in a reference database, ranking likely candidates as those with the closest match.
Revised:  Traditional methods for automated metabolite identification compare the target MS or MS/MS spectrum to spectra in a reference database, ranking likely candidates as those with the closest match.
Edit intent: fluency
Original:  Traditional methods for automated metabolite identification compare a target MS or MS/MS spectrum to  spectra in a reference database, ranking likely candidates as those with the closest match.
Revised:  Traditional methods for automated metabolite identification compare a target MS or MS/MS spectrum to the spectra in a reference database, ranking likely candidates as those with the closest match.
Edit intent: fluency
Original:  Traditional methods for automated metabolite identification compare a target MS or MS/MS spectrum to  spectra in a reference database, ranking likely candidates as those with the closest match.
Revised:  Traditional methods for automated metabolite identification compare a target MS or MS/MS spectrum to spectra in a reference database, ranking candidates based on the closeness of the match.
Edit intent: clarity
Original:  However the limited coverage of available databases has led to  interest in computational methods for predicting reference MS/MS spectra from chemical structures.
Revised:  However the limited coverage of available databases has led to an interest in computational methods for predicting reference MS/MS spectra from chemical structures.
Edit intent: fluency
Original:  This work proposes a probabilistic generative model for the MS/MS fragmentation process, which we call Competitive Fragmentation Modeling (CFM), and a machine learning approach for learning parameters for this model from  data.
Revised:  This work proposes a probabilistic generative model for the MS/MS fragmentation process, which we call Competitive Fragmentation Modeling (CFM), and a machine learning approach for learning parameters for this model from MS/MS data.
Edit intent: clarity
Original:  Results: In the MS/MS spectrum prediction task, this method shows significantly improved Jaccard scores when compared to a full enumeration of all peaks corresponding to substructures of the molecule.
Revised:  In the MS/MS spectrum prediction task, this method shows significantly improved Jaccard scores when compared to a full enumeration of all peaks corresponding to substructures of the molecule.
Edit intent: coherence
Original:  Results: In the MS/MS spectrum prediction task, this method shows significantly improved Jaccard scores when compared to a full enumeration of all peaks corresponding to substructures of the molecule.
Revised:  Results: In the MS/MS spectrum prediction task, CFM shows significantly improved Jaccard scores when compared to a full enumeration of all peaks corresponding to substructures of the molecule.
Edit intent: clarity
Original:  Results: In the MS/MS spectrum prediction task, this method shows significantly improved Jaccard scores when compared to a full enumeration of all peaks corresponding to substructures of the molecule.
Revised:  Results: In the MS/MS spectrum prediction task, this method shows significantly improved performance when compared to a full enumeration of all peaks corresponding to substructures of the molecule.
Edit intent: clarity
Original:  In the metabolite identification task, CFM obtains substantially better rankings for the correct candidate than existing methods  MetFrag and FingerID , on a collection of 1985 tripeptides and 1491 non-peptide metabolites, querying PubChem for candidate structures of the same mass.
Revised:  In the metabolite identification task, CFM obtains substantially better rankings for the correct candidate than existing methods ( MetFrag and FingerID , on a collection of 1985 tripeptides and 1491 non-peptide metabolites, querying PubChem for candidate structures of the same mass.
Edit intent: fluency
Original:  In the wake of the 2007 financial crisis, policy responses by central banks have addressed only financial panic and debt deflation.
Revised:  In the wake of the 2007-08 financial crisis, policy responses by central banks have addressed only financial panic and debt deflation.
Edit intent: clarity
Original:  We prove the existence of strong centerpoints with exact constants for convex polytopes defined by a fixed set of orientations and hyperplanes in R^d . We also prove the existence of strong centerpoints for abstract set systems with bounded intersection.
Revised:  We prove the existence of strong centerpoints with exact constants for convex polytopes defined by a fixed set of orientations . We also prove the existence of strong centerpoints for abstract set systems with bounded intersection.
Edit intent: coherence
Original:  For this, we introduce a notion of comprehensive border bases and border system, and prove their existence even in the cases where they need not correspond to any term order.
Revised:  For this, we introduce a notion of comprehensive border bases and border system, and prove their existence even in the cases where they do not correspond to any term order.
Edit intent: clarity
Original:  We also present algorithms to compute comprehensive border bases and border system.
Revised:  We further present algorithms to compute comprehensive border bases and border system.
Edit intent: clarity
Original: We discuss the following family of problems, parametrized by integers C\geq 2 and D\geq 1: Does a given one-tape non-deterministic q-state Turing machine make at most Cn+D steps on all computations on all inputs of length n, for all n? Assuming a fixed input and tape alphabet, we show that these problems are co-NP-complete and we provide lower and upper complexity bounds.
Revised: We discuss the following family of problems, parameterized by integers C\geq 2 and D\geq 1: Does a given one-tape non-deterministic q-state Turing machine make at most Cn+D steps on all computations on all inputs of length n, for all n? Assuming a fixed input and tape alphabet, we show that these problems are co-NP-complete and we provide lower and upper complexity bounds.
Edit intent: fluency
Original: We discuss the following family of problems, parametrized by integers C\geq 2 and D\geq 1: Does a given one-tape non-deterministic q-state Turing machine make at most Cn+D steps on all computations on all inputs of length n, for all n? Assuming a fixed input and tape alphabet, we show that these problems are co-NP-complete and we provide lower and upper complexity bounds.
Revised: We discuss the following family of problems, parametrized by integers C\geq 2 and D\geq 1: Does a given one-tape non-deterministic q-state Turing machine make at most Cn+D steps on all computations on all inputs of length n, for all n? Assuming a fixed tape and input alphabet, we show that these problems are co-NP-complete and we provide lower and upper complexity bounds.
Edit intent: fluency
Original: We discuss the following family of problems, parametrized by integers C\geq 2 and D\geq 1: Does a given one-tape non-deterministic q-state Turing machine make at most Cn+D steps on all computations on all inputs of length n, for all n? Assuming a fixed input and tape alphabet, we show that these problems are co-NP-complete and we provide lower and upper complexity bounds.
Revised: We discuss the following family of problems, parametrized by integers C\geq 2 and D\geq 1: Does a given one-tape non-deterministic q-state Turing machine make at most Cn+D steps on all computations on all inputs of length n, for all n? Assuming a fixed input and tape alphabet, we show that these problems are co-NP-complete and we provide good non-deterministic and co-non-deterministic lower bounds.
Edit intent: clarity
Original:  For example, within standard 97\% similarity OTUs we are able to successfully resolve up to 20 distinct substrains , all ecologically distinct but with 16S tags differing by as little as 1 nucleotide (99.2\% similarity).
Revised:  For example, within standard 97\% similarity OTUs up to 20 distinct substrains , all ecologically distinct but with 16S tags differing by as little as 1 nucleotide (99.2\% similarity).
Edit intent: clarity
Original:  For example, within standard 97\% similarity OTUs we are able to successfully resolve up to 20 distinct substrains , all ecologically distinct but with 16S tags differing by as little as 1 nucleotide (99.2\% similarity).
Revised:  For example, within standard 97\% similarity OTUs we are able to successfully resolve up to 20 distinct subpopulations , all ecologically distinct but with 16S tags differing by as little as 1 nucleotide (99.2\% similarity).
Edit intent: clarity
Original:  Our findings are numerically verified by the finite-size scaling analysis for critical behaviors and the bimodality coefficient test for discontinuous transitions .
Revised:  Our findings are numerically verified using the finite-size scaling analysis for critical behaviors and the bimodality coefficient test for discontinuous transitions .
Edit intent: fluency
Original:  Our findings are numerically verified by the finite-size scaling analysis for critical behaviors and the bimodality coefficient test for discontinuous transitions .
Revised:  Our findings are numerically verified by the finite-size scaling analysis and the crossings of the bimodality coefficient .
Edit intent: clarity
Original: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for  properties of X^m( q).
Revised: For a real number \beta >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for properties of X^m( q).
Edit intent: clarity
Original: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for  properties of X^m( q).
Revised: For real q >1, Erd\H{os, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for properties of X^m( q).
Edit intent: fluency
Original: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for  properties of X^m( q).
Revised: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for properties of X^m( q).
Edit intent: coherence
Original: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for  properties of X^m( q).
Revised: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, 1,\dots\bigr\} Pisot numbers play a crucial role for properties of X^m( q).
Edit intent: clarity
Original: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for  properties of X^m( q).
Revised: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots,m\}\bigr\} Pisot numbers play a crucial role for properties of X^m( q).
Edit intent: fluency
Original: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for  properties of X^m( q).
Revised: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\}. Pisot numbers play a crucial role for properties of X^m( q).
Edit intent: fluency
Original: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for  properties of X^m( q).
Revised: For real q >1, Erdos, Joos, Jo\'o } and Komornik study distances of the consecutive points in the set X^m( q )= \{a_0+a_1q+\cdots+a_nq^n : n%DIFDELCMD < \geq0%%% ,\ a_i \bigl\{^n a_j \beta^j : n\in\mathbb N,\,a_k} \in\{0, \ldots,m\}\\dots\bigr\} Pisot numbers play a crucial role for the properties of X^m( q).
Edit intent: fluency
Original:  We show that for any non-real \gamma and m<|\gamma|^2 - 1 , the set X^m(\gamma) is not relatively dense in the complex plane.
Revised:  We show that for any non-real \gamma and m<|\gamma|^2 -1 , the set X^m(\gamma) is not relatively dense in the complex plane.
Edit intent: fluency
Original:  For a class of cubic complex Pisot units \gamma and m>|\gamma|^2 - 1 we deduce that X^m(\gamma) is uniformly discrete and relatively dense, i.e.,  is a Delone set.
Revised:  For a class of cubic complex Pisot units \gamma and m>|\gamma|^2 -1 we deduce that X^m(\gamma) is uniformly discrete and relatively dense, i.e., is a Delone set.
Edit intent: fluency
Original:  For a class of cubic complex Pisot units \gamma and m>|\gamma|^2 - 1 we deduce that X^m(\gamma) is uniformly discrete and relatively dense, i.e.,  is a Delone set.
Revised:  For a class of cubic complex Pisot units \gamma and m>|\gamma|^2 - 1 we deduce that X^m(\gamma) is uniformly discrete and relatively dense, i.e., X^m(\gamma) is a Delone set.
Edit intent: fluency
Original:  For the complex root of Y ^3+ Y ^2+ Y - 1 we determine two parameters of the Delone set X^m(\gamma) which are analogous to minimal and maximal distances for the real case X^m( q) .
Revised:  For the complex root of Y ^3+ \gamma ^2+ Y - 1 we determine two parameters of the Delone set X^m(\gamma) which are analogous to minimal and maximal distances for the real case X^m( q) .
Edit intent: fluency
Original: For a real number \beta>1, Erdos, Jo\'o and Komornik study distances of the consecutive points in the set X^m(\beta)=\bigl\{j=0^n a_j \beta^j : n\in\mathbb N,\,a _k \in\{0,1,\dots,m\}\bigr\}.
Revised: For a real number \beta>1, Erdos, Jo\'o and Komornik study distances between consecutive points in the set X^m(\beta)=\bigl\{j=0^n a_j \beta^j : n\in\mathbb N,\,a _k \in\{0,1,\dots,m\}\bigr\}.
Edit intent: clarity
Original:  Following the work of Za\"imi, who considered X^m(\gamma) with \gamma\in \mathbb C\setminus\mathbb R\setminusR } and |\gamma|>1, we show that for any non-real \gamma and m < |\gamma|^2-1, the set X^m(\gamma) is not relatively dense in the complex plane.
Revised:  Following the work of Za\"imi, who considered X^m(\gamma) with \gamma\in \mathbb{C\setminusR } and |\gamma|>1, we show that for any non-real \gamma and m < |\gamma|^2-1, the set X^m(\gamma) is not relatively dense in the complex plane.
Edit intent: clarity
Original:  For a class of cubic complex Pisot units \gamma and m > |\gamma|^2 -1 we deduce that X^m(\gamma) is uniformly discrete and relatively dense, i.e., X^m(\gamma) is a Delone set.
Revised:  Then we focus on complex Pisot units \gamma and m > |\gamma|^2 -1 we deduce that X^m(\gamma) is uniformly discrete and relatively dense, i.e., X^m(\gamma) is a Delone set.
Edit intent: clarity
Original:  For cubic \gamma satisfying \gamma^3+\gamma^2+\gamma-1=0 we determine two parameters of the Delone set X^m(\gamma) which are analogous to minimal and maximal distances for the real case X^m(\beta).
Revised:  Moreover, we present an algorithm for determining two parameters of the Delone set X^m(\gamma) which are analogous to minimal and maximal distances for the real case X^m(\beta).
Edit intent: clarity
Original:  For cubic \gamma satisfying \gamma^3+\gamma^2+\gamma-1=0 we determine two parameters of the Delone set X^m(\gamma) which are analogous to minimal and maximal distances for the real case X^m(\beta).
Revised:  For cubic \gamma satisfying \gamma^3+\gamma^2+\gamma-1=0 we determine two parameters of the Delone set X^m(\gamma) which are analogous to minimal and maximal distances in the real case X^m(\beta).
Edit intent: fluency
Original: Recent experiments have shown that  rod-like bacteria in nutrient-rich media grow in length at an exponential rate .
Revised: Recent experiments have shown that rod-like bacteria in nutrient-rich media often grow at exponential rates .
Edit intent: clarity
Original:  Here, I point out that it is the elongated shape of these bacteria that allows for this behavior.
Revised:  Here, I point out that it is the elongated shapes of these cells that allows for this behavior.
Edit intent: clarity
Original:  Further, I show that when a bacterium's growth is limited by some nutrient -- taken in by the cell through a diffusion-to-capture process -- its growth is suppressed: In three-dimensional geometries , the length L is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Revised:  Further, I show that when growth is limited by some nutrient -- taken in by the cell through a diffusion-to-capture process -- its growth is suppressed: In three-dimensional geometries , the length L is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Edit intent: clarity
Original:  Further, I show that when a bacterium's growth is limited by some nutrient -- taken in by the cell through a diffusion-to-capture process -- its growth is suppressed: In three-dimensional geometries , the length L is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Revised:  Further, I show that when a bacterium's growth is limited by some nutrient -- taken up by the cell through a diffusion-to-capture process -- its growth is suppressed: In three-dimensional geometries , the length L is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Edit intent: fluency
Original:  Further, I show that when a bacterium's growth is limited by some nutrient -- taken in by the cell through a diffusion-to-capture process -- its growth is suppressed: In three-dimensional geometries , the length L is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Revised:  Further, I show that when a bacterium's growth is limited by some nutrient -- taken in by the cell through a diffusion-to-capture process -- cell size is suppressed: In three-dimensional geometries , the length L is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Edit intent: clarity
Original:  Further, I show that when a bacterium's growth is limited by some nutrient -- taken in by the cell through a diffusion-to-capture process -- its growth is suppressed: In three-dimensional geometries , the length L is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Revised:  Further, I show that when a bacterium's growth is limited by some nutrient -- taken in by the cell through a diffusion-to-capture process -- its growth is suppressed: In three dimensions , the length L is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Edit intent: clarity
Original:  Further, I show that when a bacterium's growth is limited by some nutrient -- taken in by the cell through a diffusion-to-capture process -- its growth is suppressed: In three-dimensional geometries , the length L is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Revised:  Further, I show that when a bacterium's growth is limited by some nutrient -- taken in by the cell through a diffusion-to-capture process -- its growth is suppressed: In three-dimensional geometries , the length is bounded by \log L \lesssim t^{1/2}, while in two dimensions the length is bounded by a power-law form .
Edit intent: fluency
Original:  Fits of experimental growth curves to these predicted, sub-exponential forms could allow for direct measures of quantities relating to cellular metabolic rates .
Revised:  Fits of experimental growth curves to these forms would return cellular metabolic rate estimates .
Edit intent: clarity