wanyu/IteraTeR_v2 huggingface dataset:
Original:  These findings are underpinned by simulations of a model based on cell growth and cell cycle.
Revised:  These findings are underpinned by a model based on cell growth and cell cycle.
Edit intent: clarity
Original:  Finally , we numerically show the range of validity of the scale invariance over various characteristic times of the starvation process, revealing the number of multifork replications is crucial for the scale invariance  .
Revised:  Finally , we numerically determine the range of validity of the scale invariance over various characteristic times of the starvation process, revealing the number of multifork replications is crucial for the scale invariance .
Edit intent: clarity
Original:  Our results emphasize the importance of intrinsic cellular cycle processes in this problem, suggesting different distribution trends for bacteria and eukaryotes .
Revised:  Our results , combined with theoretical arguments, suggest the relevance of the multifork replication, which helps retaining information of cell cycle states and may thus result in the scale invariance .
Edit intent: coherence
Original:  Here, by developing a novel microfluidic device and using E. coli, we investigate the response of cell size fluctuations against starvation.
Revised:  Here, by developing a microfluidic device and using E. coli, we investigate the response of cell size fluctuations against starvation.
Edit intent: clarity
Original: In this paper, we consider the optimal subspace expansion problem for the matrix eigenvalue problem Ax=\lambda x:
Revised: Consider the optimal subspace expansion problem for the matrix eigenvalue problem Ax=\lambda x:
Edit intent: clarity
Original:  {\em Which vector w  in the current subspace V, after multiplied by A, provides an optimal subspace expansion for approximating a desired eigenvector x in the sense that x has the smallest angle with the expanded subspace V_w=V+{\rm span}\{Aw\} ?=\argw\in\mathcal{V}\cos\angle(V_w,x)} } Our research motivation is that many iterative methods construct nested subspaces that successively expands V to V_w. Ye ( {\em Linear Algebra Appl. , 428 (2008), pp . 911--918)
Revised:  {\em Which vector w in the current subspace V, after multiplied by A, provides an optimal subspace expansion for approximating a desired eigenvector x in the sense that x has the smallest angle with the expanded subspace V_w=V+{\rm span}\{Aw\} ?=\argw\in\mathcal{V}\cos\angle(V_w,x)} } ? This problem is important as many iterative methods construct nested subspaces that successively expands V to V_w. Ye ( {\em Linear Algebra Appl. , 428 (2008), pp . 911--918)
Edit intent: coherence
Original:  {\em Which vector w  in the current subspace V, after multiplied by A, provides an optimal subspace expansion for approximating a desired eigenvector x in the sense that x has the smallest angle with the expanded subspace V_w=V+{\rm span}\{Aw\} ?=\argw\in\mathcal{V}\cos\angle(V_w,x)} } Our research motivation is that many iterative methods construct nested subspaces that successively expands V to V_w. Ye ( {\em Linear Algebra Appl. , 428 (2008), pp . 911--918)
Revised:  {\em Which vector w in the current subspace V, after multiplied by A, provides an optimal subspace expansion for approximating a desired eigenvector x in the sense that x has the smallest angle with the expanded subspace V_w=V+{\rm span}\{Aw\} ?=\argw\in\mathcal{V}\cos\angle(V_w,x)} } Our research motivation is that many iterative methods construct nested subspaces that successively expand V to V_w. Ye ( {\em Linear Algebra Appl. , 428 (2008), pp . 911--918)
Edit intent: fluency
Original:  {\em Which vector w  in the current subspace V, after multiplied by A, provides an optimal subspace expansion for approximating a desired eigenvector x in the sense that x has the smallest angle with the expanded subspace V_w=V+{\rm span}\{Aw\} ?=\argw\in\mathcal{V}\cos\angle(V_w,x)} } Our research motivation is that many iterative methods construct nested subspaces that successively expands V to V_w. Ye ( {\em Linear Algebra Appl. , 428 (2008), pp . 911--918)
Revised:  {\em Which vector w in the current subspace V, after multiplied by A, provides an optimal subspace expansion for approximating a desired eigenvector x in the sense that x has the smallest angle with the expanded subspace V_w=V+{\rm span}\{Aw\} ?=\argw\in\mathcal{V}\cos\angle(V_w,x)} } Our research motivation is that many iterative methods construct nested subspaces that successively expands V to V_w. Ye ( {\em Linear Algebra Appl. , 428 (2008), p . 911--918)
Edit intent: fluency
Original:  He turns to deriving a maximization characterization of \cos\angle(\mathcal{V}_w,x) for a }{\em   and analysis cannot extend to the non-Hermitian case.
Revised:  He turns to deriving a maximization characterization of \cos\angle(\mathcal{V}_w,x) for a }{\em given and analysis cannot extend to the non-Hermitian case.
Edit intent: fluency
Original:  We study the optimal expansion problem in the general case and derive explicit expressions of the optimal expansion vector w_{opt w_{opt} for and the optimally expanded subspace \mathcal{V}_{w_{opt}} for A general, where P_V is the orthogonal projector onto \mathcal{V}.
Revised:  We study the optimal expansion problem in the general case and derive explicit expressions of w_{opt} for and the optimally expanded subspace \mathcal{V}_{w_{opt}} for A general, where P_V is the orthogonal projector onto \mathcal{V}.
Edit intent: clarity
Original:  To investigate if SARS-CoV-2 can affect early human embryos , we analysed scRNA-seq datasets of human embryos for the SARS-CoV-2 receptors ACE2 and BSG ( CD147 ), the serine protease TMPRSS2 for viral spike protein priming, and the endosomal protease CTSL for spike protein activation via the endosomal route .
Revised:  To investigate if SARS-CoV-2 can affect early human embryos , we analysed scRNA-seq datasets of human embryos for the SARS-CoV-2 receptors ACE2 and BSG ( CD147 ), the serine protease TMPRSS2 , CTSL). We also analyzed the presence of host genes involved in viral replication, the endosomal sorting complexes required for transport (ESCRT) and SARS-Cov-2 interactions .
Edit intent: clarity
Original:  This is a generalization of the main theorem in [Frankl and Graham, European J. Combin.
Revised:  It is also a generalization of the main theorem in [Frankl and Graham, European J. Combin.
Edit intent: coherence
Original: We study the problem of Database Repairs through a rule-based framework that we refer to as Delta Rules.
Revised: We study the problem of database repairs through a rule-based framework that we refer to as Delta Rules.
Edit intent: fluency
Original:  Delta Rules are highly expressive and allow specifying complex, cross-relations repair logic associated with Denial Constraints, Causal Rules, and allowing to capture Database triggers of interest.
Revised:  Delta Rules are highly expressive and allow specifying complex, cross-relations repair logic associated with Denial Constraints, Causal Rules, and allowing to capture Database Triggers of interest.
Edit intent: fluency
Original:  Using the data of two experiments, we compare the dynamical oscillatory model (DOM) with a non-associative oscillatory model (NAOM) made of the superposition of the RW learning curve and oscillations.
Revised:  Using the data of two experiments, we compare the dynamical oscillatory model (DOM) with an oscillatory model made of the superposition of the RW learning curve and oscillations.
Edit intent: clarity
Original:  Not only do data clearly show an oscillatory pattern, but they also favour the DOM over the NAOM , thus pointing out that these oscillations are the manifestation of an associative process.
Revised:  Not only do data clearly show an oscillatory pattern, but they also favor the DOM over the NAOM , thus pointing out that these oscillations are the manifestation of an associative process.
Edit intent: fluency
Original:  Not only do data clearly show an oscillatory pattern, but they also favour the DOM over the NAOM , thus pointing out that these oscillations are the manifestation of an associative process.
Revised:  Not only do data clearly show an oscillatory pattern, but they also favour the DOM over the added oscillation model , thus pointing out that these oscillations are the manifestation of an associative process.
Edit intent: clarity
Original: Age of Information  is a critical metric for several Internet of Things (IoT) applications, where sensors keep track of the environment by sending updates that need to be as fresh as possible.
Revised: Age of Information (AoI) is a critical metric for several Internet of Things (IoT) applications, where sensors keep track of the environment by sending updates that need to be as fresh as possible.
Edit intent: clarity
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: Y :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Edit intent: clarity
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: We introduce a novel class of matrices which are defined by the factorizationY A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Edit intent: clarity
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: We introduce a novel class of matrices which are defined by the factorizationY := X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Edit intent: fluency
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: We introduce a novel class of matrices which are defined by the factorizationY :=A , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Edit intent: fluency
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: We introduce a novel class of matrices which are defined by the factorizationY :=A X A is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Edit intent: clarity
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: We introduce a novel class of matrices which are defined by the factorizationY :=A X , where is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Edit intent: fluency
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA X is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Edit intent: clarity
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column and is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Edit intent: fluency
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX dissociated .
Edit intent: clarity
Original: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and aredissociated .
Revised: We introduce a novel class of matrices which are defined by the factorizationY :=A X , whereA is an m \times n wide sparse binary matrix with a fixed number d nonzeros per column andX is an n \times N sparse real matrix whose columns have at most k nonzeros and are .
Edit intent: fluency
Original:  We define thePSB data model as a particular distribution over this class of matrices, motivated by its implications for community detection, provable binary dictionary learning with real valued sparse coding , and blind combinatorial compressed sensing.
Revised:  We define the as a particular distribution over this class of matrices, motivated by its implications for community detection, provable binary dictionary learning with real valued sparse coding , and blind combinatorial compressed sensing.
Edit intent: clarity
Original:  For data matrices drawn from the PSB data model, we provide computationally efficient factorization algorithms which recover the generating factors with  high probability from as few as N =O%DIFDELCMD < \left(%%% \frac{n{k}\log^2(n)}%DIFDELCMD < \right) %%% data vectors, where k, m and n scale proportionally.
Revised:  For data matrices drawn from the PSB data model, we provide computationally efficient factorization algorithms which recover the generating factors with high probability %DIFDELCMD < \left(%%% \frac{n{k}\log^2(n)}%DIFDELCMD < \right) %%% data vectors, where k, m and n scale proportionally.
Edit intent: clarity
Original:  In this rapidly evolving environment, smart-contract programming languages must allow users to write programs that flexibly manage and transfer assets, while providing strong protection against sophisticated attacks.
Revised:  In the rapidly evolving blockchain environment, smart contract programming languages must allow users to write programs that flexibly manage and transfer assets, while providing strong protection against sophisticated attacks.
Edit intent: clarity
Original:  In this rapidly evolving environment, smart-contract programming languages must allow users to write programs that flexibly manage and transfer assets, while providing strong protection against sophisticated attacks.
Revised:  In this rapidly evolving environment, smart-contract programming languages must allow users to write expressive programs that manage and transfer assets, while providing strong protection against sophisticated attacks.
Edit intent: clarity
Original:  In this rapidly evolving environment, smart-contract programming languages must allow users to write programs that flexibly manage and transfer assets, while providing strong protection against sophisticated attacks.
Revised:  In this rapidly evolving environment, smart-contract programming languages must allow users to write programs that flexibly manage and transfer assets, yet provide strong protection against sophisticated attacks.
Edit intent: coherence
Original:  Move uses novel linear  resource types with  C++11 /Rust-style move semantics as an explicit representation to represent assets such as money.
Revised:  Move uses novel linear resource types with semantics drawing on C++11 /Rust-style move semantics as an explicit representation to represent assets such as money.
Edit intent: clarity
Original:  We present an executable bytecode language with move semantics and show that it satisfies a set of resource safetyguarantees .
Revised:  We present an executable bytecode language with resources and prove that it enjoys resource safety, a conservation property for program values that is analogous to conservation of mass in the physical world .
Edit intent: clarity
Original:  We reduce the lubrication model proposed in [Fai et al  , Active elastohydrodynamics of vesicles in narrow, blind constrictions.
Revised:  We reduce the lubrication model proposed in [Fai et al . , Active elastohydrodynamics of vesicles in narrow, blind constrictions.
Edit intent: fluency
Original:  The key parameters of the model are the ratio of motors that prefer to push toward the head of the dendritic spine to the ratio of motors that prefer to push in the opposite direction.
Revised:  The model's key parameters are the ratio of motors that prefer to push toward the head of the dendritic spine to the ratio of motors that prefer to push in the opposite direction.
Edit intent: clarity
Original:  We perform a numerical bifurcation analysis in these parameters and find that steady-state vesicle velocities appear and disappear through a number of saddle-node bifurcations.
Revised:  We perform a numerical bifurcation analysis in these parameters and find that steady-state vesicle velocities appear and disappear through several saddle-node bifurcations.
Edit intent: fluency
Original:  This  allows us to identify the region of parameter space in which multiple stable velocities exist.
Revised:  This process allows us to identify the region of parameter space in which multiple stable velocities exist.
Edit intent: clarity
Original:  We show by direct calculations that for sufficiently close vesicle-to-spine diameter ratios, there can only be unidirectional motion .
Revised:  We show by direct calculations that there can only be unidirectional motion .
Edit intent: clarity
Original: We focus on scenarios in which multiple rational, non-communicating agents navigate in close proximity, such as unsignalized street intersections.
Revised: We focus on navigation among rational, non-communicating agents navigate in close proximity, such as unsignalized street intersections.
Edit intent: clarity
Original: We focus on scenarios in which multiple rational, non-communicating agents navigate in close proximity, such as unsignalized street intersections.
Revised: We focus on scenarios in which multiple rational, non-communicating agents at unsignalized street intersections.
Edit intent: clarity
Original:  In these situations, decentralized coordination to achieve safe and efficient motion demands nuanced implicit communication between the agents.
Revised:  Following collision-free motion under such settings demands nuanced implicit communication between the agents.
Edit intent: clarity
Original:  In these situations, decentralized coordination to achieve safe and efficient motion demands nuanced implicit communication between the agents.
Revised:  In these situations, decentralized coordination to achieve safe and efficient motion demands nuanced implicit coordination among agents.
Edit intent: clarity
Original:  Often, the spatial structure of such environments constrains multi-agent trajectories to belong to a finite set of modes , each corresponding to a distinct spatiotemporal topology .
Revised:  Often, the structure of these domains constrains multiagent trajectories to belong to a finite set of modes , each corresponding to a distinct spatiotemporal topology .
Edit intent: clarity
Original:  Often, the spatial structure of such environments constrains multi-agent trajectories to belong to a finite set of modes , each corresponding to a distinct spatiotemporal topology .
Revised:  Often, the spatial structure of such environments constrains multi-agent trajectories to belong to a finite set of modes .
Edit intent: clarity
Original:  Our key insight is that empowering agents with a model of this structure can enable effective coordination through implicit communication, realized via intent signals encoded in agents' actions.
Revised:  Our key insight is that empowering agents with a model of these modes can enable effective coordination through implicit communication, realized via intent signals encoded in agents' actions.
Edit intent: clarity
Original:  Our key insight is that empowering agents with a model of this structure can enable effective coordination through implicit communication, realized via intent signals encoded in agents' actions.
Revised:  Our key insight is that empowering agents with a model of this structure can enable effective coordination , realized implicitly via intent signals encoded in agents' actions.
Edit intent: clarity
Original:  In this paper, we do so by representing modes of joint behavior as topological braids.
Revised:  In this paper, we represent modes of joint behavior as topological braids.
Edit intent: coherence
Original:  In this paper, we do so by representing modes of joint behavior as topological braids.
Revised:  In this paper, we do so by representing modes of joint behavior in a compact and interpretable fashion using the formalism of topological braids.
Edit intent: clarity
Original:  We validate our approach with a case study in a four-way unsignalized intersection involving a series of challenging multi-agent scenarios.
Revised:  We validate our approach in a simulated case study featuring challenging multiagent scenarios at a four-way unsignalized intersection involving a series of challenging multi-agent scenarios.
Edit intent: clarity
Original:  Our findings show that our model reduces frequency of collisions by at least 65\% over a set of explicit trajectory prediction baselines , while maintaining comparable  efficiency.
Revised:  Our findings show that our model reduces frequency of collisions by at least 65\% over a set of baselines explicitly reasoning over trajectories , while maintaining comparable efficiency.
Edit intent: clarity
Original: With the increasing sophistication of attacks on cyber-physical systems, deception has emerged as an effective tool to improve system security and safety by obfuscating information or providing misleading information .
Revised: With the increasing sophistication of attacks on cyber-physical systems, deception has emerged as an effective tool to improve system security and safety by obfuscating the attacker's perception .
Edit intent: clarity
Original:  We introduce hypergames on graphs as a model to capture the asymmetrical information with one-sided payoff misperception.
Revised:  We introduce a model called hypergame on graph to capture the asymmetrical information with one-sided payoff misperception.
Edit intent: clarity