wanyu/IteraTeR_full_sent huggingface dataset:
Original:  This algorithm provides an alternate viewpoint on frequency-domain analysis and enables one to quantify the synchronizing timings among signaling pathways for rhythmical calcium oscillations . Numerical results show three types of calcium oscillations of SMCs in mesenteric arterioles: the spontaneous calcium oscillation, the agonist-dependent calcium oscillation, and the agonist-dependent calcium spike.
Revised:  This algorithm provides an alternate viewpoint on frequency-domain analysis and enables one to quantify the synchronizing timings among signaling pathways for rhythmical calcium oscillations . Numerical results show three types of calcium oscillations of SMCs in mesenteric arterioles: the spontaneous calcium oscillation, agonist-dependent calcium oscillation, and the agonist-dependent calcium spike.
Edit intent: fluency
Original:  This algorithm provides an alternate viewpoint on frequency-domain analysis and enables one to quantify the synchronizing timings among signaling pathways for rhythmical calcium oscillations . Numerical results show three types of calcium oscillations of SMCs in mesenteric arterioles: the spontaneous calcium oscillation, the agonist-dependent calcium oscillation, and the agonist-dependent calcium spike.
Revised:  This algorithm provides an alternate viewpoint on frequency-domain analysis and enables one to quantify the synchronizing timings among signaling pathways for rhythmical calcium oscillations . Numerical results show three types of calcium oscillations of SMCs in mesenteric arterioles: the spontaneous calcium oscillation, the agonist-dependent calcium oscillation, and agonist-dependent calcium spike.
Edit intent: fluency
Original:  For the noticeable agonist-dependent types in mesenteric SMCs, we demonstrate the flow of signaling pathways associated with intracellular calcium oscillationsand find the in-phase (out-phase) tendency among cation-cation (cation-anion), which implies the maximization of charge oscillations.
Revised:  For simple single and double SMCs, we demonstrate the flow of signaling pathways associated with intracellular calcium oscillationsand find the in-phase (out-phase) tendency among cation-cation (cation-anion), which implies the maximization of charge oscillations.
Edit intent: meaning-changed
Original:  For the noticeable agonist-dependent types in mesenteric SMCs, we demonstrate the flow of signaling pathways associated with intracellular calcium oscillationsand find the in-phase (out-phase) tendency among cation-cation (cation-anion), which implies the maximization of charge oscillations. For involving intercellular calcium dynamics in finite cell clusters, we observe the window-broadening of the oscillation-frequency spectrum under increasing cell numbers, which hence raises the possibility of synchronized oscillations for vasomotions.
Revised:  For the noticeable agonist-dependent types in mesenteric SMCs, we demonstrate properties of synchronization among complex signals related to calcium oscillations, and show different correlation relations between calcium and voltage signals for various synchronization and resonance conditions. For practical cell clusters, we observe the window-broadening of the oscillation-frequency spectrum under increasing cell numbers, which hence raises the possibility of synchronized oscillations for vasomotions.
Edit intent: clarity
Original:  For involving intercellular calcium dynamics in finite cell clusters, we observe the window-broadening of the oscillation-frequency spectrum under increasing cell numbers, which hence raises the possibility of synchronized oscillations for vasomotions. Our analyses indicate that the rhythm of SMC cluster could (1) correspond to significant enhancements of signal communications among remote cells, (2) respond to calcium sparks against transient stimulations for driving follow-up globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Revised:  For involving intercellular calcium dynamics in finite cell clusters, our analyses indicate that the rhythm of SMC cluster could (1) correspond to significant enhancements of signal communications among remote cells, (2) respond to calcium sparks against transient stimulations for driving follow-up globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Edit intent: coherence
Original:  Our analyses indicate that the rhythm of SMC cluster could (1) correspond to significant enhancements of signal communications among remote cells, (2) respond to calcium sparks against transient stimulations for driving follow-up globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Revised:  Our analyses indicate that the rhythm of SMCs could (1) correspond to significant enhancements of signal communications among remote cells, (2) respond to calcium sparks against transient stimulations for driving follow-up globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Edit intent: clarity
Original:  Our analyses indicate that the rhythm of SMC cluster could (1) correspond to significant enhancements of signal communications among remote cells, (2) respond to calcium sparks against transient stimulations for driving follow-up globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Revised:  Our analyses indicate that the rhythm of SMC cluster could (1) benefit enhancements of signal communications among remote cells, (2) respond to calcium sparks against transient stimulations for driving follow-up globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Edit intent: clarity
Original:  Our analyses indicate that the rhythm of SMC cluster could (1) correspond to significant enhancements of signal communications among remote cells, (2) respond to calcium sparks against transient stimulations for driving follow-up globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Revised:  Our analyses indicate that the rhythm of SMC cluster could (1) correspond to significant enhancements of signal communications among remote cells, (2) respond to a significant calcium peaking against transient stimulations for driving follow-up globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Edit intent: meaning-changed
Original:  Our analyses indicate that the rhythm of SMC cluster could (1) correspond to significant enhancements of signal communications among remote cells, (2) respond to calcium sparks against transient stimulations for driving follow-up globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Revised:  Our analyses indicate that the rhythm of SMC cluster could (1) correspond to significant enhancements of signal communications among remote cells, (2) respond to calcium sparks against transient stimulations for triggering globally-oscillating modes, and (3) characterize the globally-oscillating modes via frog-leap (non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Edit intent: clarity
Original:  However, previous methods usually  used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernels. Only rarely has the hierarchy been used as a second layer of the network connecting the protein network with functional annotations .
Revised:  However, previous methods usually used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model .
Edit intent: clarity
Original:  We evaluate the ability of both methods to predict protein function on yeast, fly, and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA.
Revised:  We evaluate both methods in predicting protein function on yeast, fly, and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA.
Edit intent: clarity
Original:  We evaluate the ability of both methods to predict protein function on yeast, fly, and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA.
Revised:  We evaluate the ability of both methods to predict protein function on yeast, fly, and human datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA.
Edit intent: clarity
Original:  We  find that both BirgRank and AptRank outperform the previous methods, especially when only 10\% of the data are given for training.
Revised:  We design three validation strategies: missing function prediction, de novo function prediction, and guided function prediction to comprehensively evaluate all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially when only 10\% of the data are given for training.
Edit intent: meaning-changed
Original:  AptRank naturally combines protein-protein associations and  function-function relationships into a two-layer network model , and takes full advantage of the hierarchical structure of the Gene Ontology, using directional diffusion without flattening the ontological hierarchy into a similarity kernel.
Revised:  AptRank combines protein-protein associations and function-function relationships into a two-layer network model , and takes full advantage of the hierarchical structure of the Gene Ontology, using directional diffusion without flattening the ontological hierarchy into a similarity kernel.
Edit intent: clarity
Original:  AptRank naturally combines protein-protein associations and  function-function relationships into a two-layer network model , and takes full advantage of the hierarchical structure of the Gene Ontology, using directional diffusion without flattening the ontological hierarchy into a similarity kernel.
Revised:  AptRank naturally combines protein-protein associations and the GO function-function relationships into a two-layer network model , and takes full advantage of the hierarchical structure of the Gene Ontology, using directional diffusion without flattening the ontological hierarchy into a similarity kernel.
Edit intent: meaning-changed
Original:  AptRank naturally combines protein-protein associations and  function-function relationships into a two-layer network model , and takes full advantage of the hierarchical structure of the Gene Ontology, using directional diffusion without flattening the ontological hierarchy into a similarity kernel.
Revised:  AptRank naturally combines protein-protein associations and function-function hierarchy into a two-layer network model , and takes full advantage of the hierarchical structure of the Gene Ontology, using directional diffusion without flattening the ontological hierarchy into a similarity kernel.
Edit intent: clarity
Original:  AptRank naturally combines protein-protein associations and  function-function relationships into a two-layer network model , and takes full advantage of the hierarchical structure of the Gene Ontology, using directional diffusion without flattening the ontological hierarchy into a similarity kernel.
Revised:  AptRank naturally combines protein-protein associations and function-function relationships into a two-layer network model without flattening the ontological hierarchy into a similarity kernel.
Edit intent: coherence
Original:  AptRank naturally combines protein-protein associations and  function-function relationships into a two-layer network model , and takes full advantage of the hierarchical structure of the Gene Ontology, using directional diffusion without flattening the ontological hierarchy into a similarity kernel.
Revised:  AptRank naturally combines protein-protein associations and function-function relationships into a two-layer network model , and takes full advantage of the hierarchical structure of the Gene Ontology, using directional diffusion without flattening the hierarchy into a similarity kernel.
Edit intent: fluency
Original:  First, we establish the inferior limit behavior of a proper lower semicontinuous L ^{0 function on a random locally convex module endowed with the locally L ^{0 topology, which makes perfect the Fenchel-Moreau duality theorem for such functions.
Revised:  First, we establish the inferior limit behavior of a proper lower semicontinuous L ^0--convex function on a random locally convex module endowed with the locally L ^{0 topology, which makes perfect the Fenchel-Moreau duality theorem for such functions.
Edit intent: meaning-changed
Original:  First, we establish the inferior limit behavior of a proper lower semicontinuous L ^{0 function on a random locally convex module endowed with the locally L ^{0 topology, which makes perfect the Fenchel-Moreau duality theorem for such functions.
Revised:  First, we establish the inferior limit behavior of a proper lower semicontinuous L ^{0 function on a random locally convex module endowed with the locally L ^0--convex topology, which makes perfect the Fenchel-Moreau duality theorem for such functions.
Edit intent: meaning-changed
Original:  First, we establish the inferior limit behavior of a proper lower semicontinuous L ^{0 function on a random locally convex module endowed with the locally L ^{0 topology, which makes perfect the Fenchel-Moreau duality theorem for such functions.
Revised:  First, we establish the inferior limit behavior of a proper lower semicontinuous L ^{0 function on a random locally convex module endowed with the locally L ^{0 topology, which makes perfect the Fenchel--Moreau duality theorem for such functions.
Edit intent: clarity
Original:  And then, we establish the elegant relationships among subdifferentiability, Gateaux-differentiability and Frechet-differentiability for a proper L ^{0 function defined on random normed modules.
Revised:  And then, we establish the elegant relationships among subdifferentiability, G\^ateaux--differentiability and Fr\'ech\'et--differentiability for a proper L ^{0 function defined on random normed modules.
Edit intent: meaning-changed
Original:  And then, we establish the elegant relationships among subdifferentiability, Gateaux-differentiability and Frechet-differentiability for a proper L ^{0 function defined on random normed modules.
Revised:  And then, we establish the elegant relationships among subdifferentiability, Gateaux-differentiability and Frechet-differentiability for a proper L ^0--convex function defined on random normed modules.
Edit intent: meaning-changed
Original:  At last, based on the Ekeland's variational principle for a proper lower semicontinuous- \bar{L} ^{0 function, we show that \epsilon-subdifferentials can be approximated by subdifferentials.
Revised:  At last, based on the Ekeland's variational principle for a proper lower semicontinuous \bar{L} ^{0 function, we show that \epsilon-subdifferentials can be approximated by subdifferentials.
Edit intent: fluency
Original:  At last, based on the Ekeland's variational principle for a proper lower semicontinuous- \bar{L} ^{0 function, we show that \epsilon-subdifferentials can be approximated by subdifferentials.
Revised:  At last, based on the Ekeland's variational principle for a proper lower semicontinuous- \bar{L} ^0--valued function, we show that \epsilon-subdifferentials can be approximated by subdifferentials.
Edit intent: clarity
Original:  At last, based on the Ekeland's variational principle for a proper lower semicontinuous- \bar{L} ^{0 function, we show that \epsilon-subdifferentials can be approximated by subdifferentials.
Revised:  At last, based on the Ekeland's variational principle for a proper lower semicontinuous- \bar{L} ^{0 function, we show that \varepsilon--subdifferentials can be approximated by subdifferentials.
Edit intent: meaning-changed
Original:  We would like to emphasize that the success of this paper lies in simultaneously considering the ( \epsilon , \lambda) -topology and the locally L ^{0 topology for a random locally convex module.
Revised:  We would like to emphasize that the success of this paper lies in simultaneously considering the ( \varepsilon , \lambda) -topology and the locally L ^{0 topology for a random locally convex module.
Edit intent: meaning-changed
Original:  We would like to emphasize that the success of this paper lies in simultaneously considering the ( \epsilon , \lambda) -topology and the locally L ^{0 topology for a random locally convex module.
Revised:  We would like to emphasize that the success of this paper lies in simultaneously considering the ( \epsilon , \lambda) -topology and the locally L ^0--convex topology for a random locally convex module.
Edit intent: fluency
Original: Several URLanisms, such as bacteria, algae, or spermatozoa, use flagellum or cilium activity to swim in a fluid . Many URLanisms use rather ample shape deformation, described as amoeboid, to propel themselves , either crawling on a substrate or swimming.
Revised: Several URLanisms, such as bacteria, algae, or spermatozoa, use flagellum or cilium activity to swim in a fluid , while many other URLanisms instead use ample shape deformation, described as amoeboid, to propel themselves , either crawling on a substrate or swimming.
Edit intent: clarity
Original:  Many eukaryotic cells were believed to require an underlying substratum to migrate (crawl) by using ample membrane deformation (like blebbing ). There is now an increasing evidence that a large variety of cells (including those of the immune system) can migrate without the assistance of focal adhesion, and can perform swimming as efficiently as crawling .
Revised:  Many eukaryotic cells were believed to require an underlying substratum to migrate (crawl) by using ample membrane deformation (like blebbing or generation of lamellipodia) but there is now increasing evidence that a large variety of cells (including those of the immune system) can migrate without the assistance of focal adhesion, and can perform swimming as efficiently as crawling .
Edit intent: meaning-changed
Original:  The swimmer exhibits a rich behavior: it can settle into a straight trajectory in the channel , or can navigate from one wall to the other , depending on confinement. Furthermore, the nature of the swimmer is  found to be affected by the confinement: the swimmer can behave  as a pusher at low confinement, and becomes a puller at higher confinement , or vice versa;
Revised:  The swimmer exhibits a rich behavior: it can settle into a straight trajectory in the channel , or can navigate from one wall to the other depending on its confinement. The nature of the swimmer is found to be affected by the confinement: the swimmer can behave as a pusher at low confinement, and becomes a puller at higher confinement , or vice versa;
Edit intent: coherence
Original:  Furthermore, the nature of the swimmer is  found to be affected by the confinement: the swimmer can behave  as a pusher at low confinement, and becomes a puller at higher confinement , or vice versa;
Revised:  Furthermore, the nature of the swimmer is also found to be affected by the confinement: the swimmer can behave as a pusher at low confinement, and becomes a puller at higher confinement , or vice versa;
Edit intent: coherence
Original:  Furthermore, the nature of the swimmer is  found to be affected by the confinement: the swimmer can behave  as a pusher at low confinement, and becomes a puller at higher confinement , or vice versa;
Revised:  Furthermore, the nature of the swimmer is found to be affected by confinement: the swimmer can behave as a pusher at low confinement, and becomes a puller at higher confinement , or vice versa;
Edit intent: fluency
Original:  Furthermore, the nature of the swimmer is  found to be affected by the confinement: the swimmer can behave  as a pusher at low confinement, and becomes a puller at higher confinement , or vice versa;
Revised:  Furthermore, the nature of the swimmer is found to be affected by the confinement: the swimmer can behave , on the average over one swimming cycle, as a pusher at low confinement, and becomes a puller at higher confinement , or vice versa;
Edit intent: meaning-changed
Original:  Furthermore, the nature of the swimmer is  found to be affected by the confinement: the swimmer can behave  as a pusher at low confinement, and becomes a puller at higher confinement , or vice versa; this shows that the swimmernature is not an intrinsic property.
Revised:  Furthermore, the nature of the swimmer is found to be affected by the confinement: the swimmer can behave as a pusher at low confinement, and becomes a puller at higher confinement . The swimmer's nature is thus not an intrinsic property.
Edit intent: coherence
Original:  The scaling of the swimmer velocity V with the force amplitude A is analyzed in details and this shows that at small enough A, V\sim A^2/\eta^2, whereas at large enough A, V is independent of the force and is only fixed by the stroke cycle frequency and the swimmer size.
Revised:  The scaling of the swimmer velocity V with the force amplitude A is analyzed in detail showing that at small enough A, V\sim A^2/\eta^2, whereas at large enough A, V is independent of the force and is only fixed by the stroke cycle frequency and the swimmer size.
Edit intent: coherence
Original:  The scaling of the swimmer velocity V with the force amplitude A is analyzed in details and this shows that at small enough A, V\sim A^2/\eta^2, whereas at large enough A, V is independent of the force and is only fixed by the stroke cycle frequency and the swimmer size.
Revised:  The scaling of the swimmer velocity V with the force amplitude A is analyzed in details and this shows that at small enough A, V\sim A^2/\eta^2, whereas at large enough A, V is independent of the force and is determined solely by the stroke cycle frequency and the swimmer size.
Edit intent: clarity
Original:  The scaling of the swimmer velocity V with the force amplitude A is analyzed in details and this shows that at small enough A, V\sim A^2/\eta^2, whereas at large enough A, V is independent of the force and is only fixed by the stroke cycle frequency and the swimmer size.
Revised:  The scaling of the swimmer velocity V with the force amplitude A is analyzed in details and this shows that at small enough A, V\sim A^2/\eta^2, whereas at large enough A, V is independent of the force and is only fixed by the stroke frequency and swimmer size.
Edit intent: clarity
Original: Eukaryotic cells can detect the direction of a chemoattractant gradient precisely by generating intracellular gradients of signaling molecules that mirror the extracellular gradient ? an ability called directional sensing.
Revised: Eukaryotic cells respond to a chemoattractant gradient precisely by generating intracellular gradients of signaling molecules that mirror the extracellular gradient ? an ability called directional sensing.
Edit intent: clarity
Original: Eukaryotic cells can detect the direction of a chemoattractant gradient precisely by generating intracellular gradients of signaling molecules that mirror the extracellular gradient ? an ability called directional sensing.
Revised: Eukaryotic cells can detect the direction of a chemoattractant gradient by forming intracellular gradients of signaling molecules that mirror the extracellular gradient ? an ability called directional sensing.
Edit intent: clarity