wanyu/IteraTeR_v2 huggingface dataset:
Original:   Thus, this  system works as a  general and accurate framework for discriminating these three cell types, iPSCs, ESC , and SCs . This strategy developed here might also be applied to other biomarker system development .
Revised:  Thus, this system works as a general and accurate framework for discriminating these three cell types, iPSCs, ESCs , and SCs . This strategy developed here might also be applied to other biomarker system development .
Edit intent: fluency
Original:  For this class of constraints, the associated projection operator generally does not have a closed form.
Revised:  For such constraints, the associated projection operator generally does not have a closed form.
Edit intent: clarity
Original:  For this class of constraints, the associated projection operator generally does not have a closed form.
Revised:  For this class of constraints, the associated projection operator generally does not have a simple form.
Edit intent: clarity
Original:  We first give a necessary condition for a polynomial to have an SDR. It implies that some polynomials have no SDR, answering a question of Grenet et al.
Revised:  We first give some sufficient conditions for a polynomial to have an SDR. It implies that some polynomials have no SDR, answering a question of Grenet et al.
Edit intent: clarity
Original:  we show how quantification may  extended to each level of organisation up to the ecological.
Revised:  we show how quantification may be extended to each level of organisation up to the ecological.
Edit intent: fluency
Original:  This is a novel approach compared to the usual technique of adjusting parameters only on the basis of experimental data.
Edit intent: coherence
Original:  We apply this to learn kinetic rates as a form of evolutionary learning, and find parameters which satisfy the objective.
Revised:  We apply this to learn kinetic rates as a form of evolutionary learning, and look for parameters which satisfy the objective.
Edit intent: clarity
Original:  These may be intersected with parameter sets generated from experimental time-series datato further constrain a signal transduction model .
Revised:  This is a novel approach compared to the usual technique of adjusting parameters only on the basis of experimental data .
Edit intent: coherence
Original:  The resulting model is self-regulating , i.e. perturbations in protein concentrations or changes in extracellular signaling will automatically lead to adaptation.
Revised:  The resulting model is self-organizing , i.e. perturbations in protein concentrations or changes in extracellular signaling will automatically lead to adaptation.
Edit intent: clarity
Original:  We find fits with common observations of compensatory or co-regulation of protein expression levels in cellular systems (e. g. PDE3, AC5).
Revised:  We find compensatory or co-regulation of protein expression levels in cellular systems (e. g. PDE3, AC5).
Edit intent: clarity
Original:  We find fits with common observations of compensatory or co-regulation of protein expression levels in cellular systems (e. g. PDE3, AC5).
Revised:  We find fits with common observations of compensatory or co-regulation of protein expression levels .
Edit intent: clarity
Original:  We also show that the evolved networks have qualitatively similar features with real biological networks by standard complex network analysis.
Revised:  We also show that the evolved networks have features qualitatively similar to real biological networks by standard complex network analysis.
Edit intent: fluency
Original: Localization is a fundamental task for both sensor networksand mobile robots .
Revised: Localization is a fundamental task for sensor networks .
Edit intent: clarity
Original:  The result is a framework where the nodes are required to be bi-connected and the communication graph has to be simply rigid.
Revised:  The result is a framework where the nodes are required to be bi-connected and the communication graph has to be rigid.
Edit intent: clarity
Original:  Neural learning architectures hence need a unit, a comparator, able to compare several inputs encoding either internal or external information, like  predictions and sensory readings.
Revised:  Neural learning architectures hence need a unit, a comparator, able to compare several inputs encoding either internal or external information, like for instance predictions and sensory readings.
Edit intent: clarity
Original:  We propose an unsupervised neural circuitry, where the function of input comparison emerge via self-organization only from the interaction of the system with the respective inputs, without external influence or supervision.
Revised:  We propose an unsupervised neural circuitry, where the function of input comparison emerges via self-organization only from the interaction of the system with the respective inputs, without external influence or supervision.
Edit intent: fluency
Original:  Conflicting results have been reported, but in recent studies of vertebrate transcriptomes the hourglass model has been favored.
Revised:  Conflicting results have been reported, but in recent studies of animal transcriptomes the hourglass model has been favored.
Edit intent: clarity
Original:  The basemaps  provide a stable mental framework for analysts to follow developments over searches for different years, which can be animated.
Revised:  The basemaps can provide a stable mental framework for analysts to follow developments over searches for different years, which can be animated.
Edit intent: fluency
Original:  The full flexibility of the advanced search engine of USPTO is available for generating sets of patents  which can thus be visualized and compared.
Revised:  The full flexibility of the advanced search engines of USPTO are available for generating sets of patents which can thus be visualized and compared.
Edit intent: fluency
Original:  In the central nervous system, SWN models have been shown to fit well both anatomical and functional maps at  macroscopic level.
Revised:  In the central nervous system, SWN models have been shown to fit well both anatomical and functional maps at the macroscopic level.
Edit intent: fluency
Original:  However the functional microscopic level, where the nodes of a network are composed by single neuronsrather than brain areas , is still poorly understood.
Revised:  However the functional microscopic level, where the nodes of a network are composed of single neurons , is still poorly understood.
Edit intent: clarity
Original:  At this level  it is not known whether and how these maps  change across different conditions , such as spontaneous activity and sensory stimulation .
Revised:  At this level it is not known whether and how these maps change across different conditions .
Edit intent: clarity
Original:  Then, by using graph-theoretical statistics (transitivity, characteristic path length, small-worldness), we characterized the functional maps topology both during spontaneous activity and sensory stimulation.
Revised:  Then, by using graph-theoretical statistics , we characterized the functional maps topology both during spontaneous activity and sensory stimulation.
Edit intent: clarity
Original:  Then, by using graph-theoretical statistics (transitivity, characteristic path length, small-worldness), we characterized the functional maps topology both during spontaneous activity and sensory stimulation.
Revised:  Then, by using graph-theoretical statistics (transitivity, characteristic path length, small-worldness), we characterized the functional map topology both during spontaneous activity and sensory stimulation.
Edit intent: fluency
Original:  Our main results show that: (i) A SWN organization is present in spikes and LFPs  during spontaneous activity;
Revised:  Our main results show that: (i) spikes and LFPs during spontaneous activity;
Edit intent: clarity
Original:  (ii) After stimulation onsets , while substantial functional map reconfigurations occur both in spike and LFPs, small-worldness is nonetheless preserved (iii) At the LFP level the stimulus triggers a significant increase of inter-area functional connections without modifying the topology of intra-area  connections;
Revised:  (ii) After stimulation onset , while substantial functional map reconfigurations occur both in spike and LFPs, small-worldness is nonetheless preserved (iii) At the LFP level the stimulus triggers a significant increase of inter-area functional connections without modifying the topology of intra-area connections;
Edit intent: clarity
Original:  (ii) After stimulation onsets , while substantial functional map reconfigurations occur both in spike and LFPs, small-worldness is nonetheless preserved (iii) At the LFP level the stimulus triggers a significant increase of inter-area functional connections without modifying the topology of intra-area  connections;
Revised:  (ii) After stimulation onsets , while substantial functional map reconfigurations occur both in spike and LFPs, small-worldness is nonetheless preserved (iii) The stimulus triggers a significant increase of inter-area functional connections without modifying the topology of intra-area connections;
Edit intent: clarity
Original:  (ii) After stimulation onsets , while substantial functional map reconfigurations occur both in spike and LFPs, small-worldness is nonetheless preserved (iii) At the LFP level the stimulus triggers a significant increase of inter-area functional connections without modifying the topology of intra-area  connections;
Revised:  (ii) After stimulation onsets , while substantial functional map reconfigurations occur both in spike and LFPs, small-worldness is nonetheless preserved (iii) At the LFP level the stimulus triggers a significant increase of inter-area functional connections without modifying the topology of intra-area functional connections;
Edit intent: fluency
Original:  Recently, it has been argued that the presence of the law in genomes is an inevitable consequence of the fact that Z = Y/X, which would imply that Z ~ 1/X . Z ~ 1/X  is a very particular case of Menzerath-Altmann law that has been rejected by means of a correlation test between X and Y in genomes, being X the number of chromosomes of a species, Y its genome size in bases and Z the mean chromosome size.
Revised:  Recently, it has been argued that the presence of the law in genomes is an inevitable consequence of the fact that Z = Y/X, which would imply that Z ~ 1/X . Z ~ 1/X . That scaling is a very particular case of Menzerath-Altmann law that has been rejected by means of a correlation test between X and Y in genomes, being X the number of chromosomes of a species, Y its genome size in bases and Z the mean chromosome size.
Edit intent: coherence
Original:  This concentration is identified as an onset of crowding beyond which it is impossible, even in principle, to extract information about hydrodynamic size of the peptide-surfactant complex  ]  .
Revised:  We find that in order to obtain unambiguous information about the hydrodynamic size of the peptide-surfactant complex ] .
Edit intent: coherence
Original:  This concentration is identified as an onset of crowding beyond which it is impossible, even in principle, to extract information about hydrodynamic size of the peptide-surfactant complex  ]  .
Revised:  This concentration is identified as an onset of crowding beyond which it is impossible, even in principle, to extract information about hydrodynamic size of a peptide-surfactant complex ] .
Edit intent: fluency
Original:  The code is validated against XFOIL/ XFLR5, and it is shown that the quality of XFLR5's results would benefit from the mathematically sound surface velocity computation provided by N. Marcov's formula.
Revised:  This code is validated against XFOIL/ XFLR5, and it is shown that the quality of XFLR5's results would benefit from the mathematically sound surface velocity computation provided by N. Marcov's formula.
Edit intent: fluency
Original:  The code is validated against XFOIL/ XFLR5, and it is shown that the quality of XFLR5's results would benefit from the mathematically sound surface velocity computation provided by N. Marcov's formula.
Revised:  The code is validated against XFLR5, and it is shown that the quality of XFLR5's results would benefit from the mathematically sound surface velocity computation provided by N. Marcov's formula.
Edit intent: clarity
Original:  The suitability of our code for co-simulation is demonstrated with a simulation of a tethered wing, i.e, a kite.
Revised:  The suitability of our code for co-simulation is demonstrated with an example of a tethered wing, i.e, a kite.
Edit intent: clarity
Original:  These recommendations are implemented in a C++ library, offered on-line under an open source license by the author .
Revised:  These recommendations are implemented in a C++ library, offered on-line under an open source license .
Edit intent: clarity
Original:  Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism , a high speed-up factor and low power consumption com- pared to conventional computers.
Revised:  Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers.
Edit intent: clarity
Original: In the first part of this paper, we survey the results of three Laplacian matrices called differenceLaplacian matrix, normalizedLaplacian matrix and signlessLaplacian matrix .
Revised: In the first part of this paper, we survey results that are associated with three types of Laplacian matrices:difference, normalized, and signless .
Edit intent: clarity
Original:  We derive eigenvalue and eigenvector formulae for paths and cycles using circulant matrices and give an alternative proof for eigenvalues of adjacency matrix of paths and cycles using Chebyshev polynomials.
Revised:  We derive eigenvalue and eigenvector formulaes for paths and cycles using circulant matrices and give an alternative proof for eigenvalues of adjacency matrix of paths and cycles using Chebyshev polynomials.
Edit intent: fluency
Original:  We derive eigenvalue and eigenvector formulae for paths and cycles using circulant matrices and give an alternative proof for eigenvalues of adjacency matrix of paths and cycles using Chebyshev polynomials.
Revised:  We derive eigenvalue and eigenvector formulae for paths and cycles using circulant matrices and present an alternative proof for eigenvalues of adjacency matrix of paths and cycles using Chebyshev polynomials.
Edit intent: clarity
Original:  We derive eigenvalue and eigenvector formulae for paths and cycles using circulant matrices and give an alternative proof for eigenvalues of adjacency matrix of paths and cycles using Chebyshev polynomials.
Revised:  We derive eigenvalue and eigenvector formulae for paths and cycles using circulant matrices and give an alternative proof for finding eigenvalues of the adjacency matrix of paths and cycles using Chebyshev polynomials.
Edit intent: clarity
Original:  Even each of these results are well knownseparately, we try to summarize all of them, providing uniform proofs in a simple way.
Revised:  Even though each results is separately well known, we unite them, and provide uniform proofs in a simple way.
Edit intent: clarity
Original:  Main part of this paper is to solve the problem of finding graphs, on which spectral clustering methods and normalized cut produce different partitions.
Revised:  Main part of this paper is to solve the problem of finding graphs, on which spectral clustering methods and normalized cuts produce different partitions.
Edit intent: fluency
Original:  First  we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths  and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k}  and weighted path P_{n,k}.
Revised:  First , we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k} and weighted path P_{n,k}.
Edit intent: fluency
Original:  First  we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths  and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k}  and weighted path P_{n,k}.
Revised:  First we derive a formula for a minimum normalized cut for graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k} and weighted path P_{n,k}.
Edit intent: clarity
Original:  First  we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths  and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k}  and weighted path P_{n,k}.
Revised:  First we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double-trees , cycle cross paths and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k} and weighted path P_{n,k}.
Edit intent: fluency
Original:  First  we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths  and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k}  and weighted path P_{n,k}.
Revised:  First we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths , and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k} and weighted path P_{n,k}.
Edit intent: fluency
Original:  First  we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths  and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k}  and weighted path P_{n,k}.
Revised:  First we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths and some complex graphs like lollipop graph LP_{n,m}, roach type graph R_{n,k} and weighted path P_{n,k}.
Edit intent: fluency
Original:  First  we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths  and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k}  and weighted path P_{n,k}.
Revised:  First we derive a formula for a minimum normalized cut of some graph classes such as paths, cycles, complete graphs, double trees , cycle cross paths and some complex graphs such as lollipop graph LP_{n,m}, roach type graph R_{n,k} , and weighted path P_{n,k}.
Edit intent: fluency
Original:  Next we give characteristic polynomials of the normalized Laplacian matrix {\mathcal L}(P_{n,k}) and {\mathcal L}(R_{n,k}).
Revised:  Next , we provide characteristic polynomials of the normalized Laplacian matrix {\mathcal L}(P_{n,k}) and {\mathcal L}(R_{n,k}).
Edit intent: fluency
Original:  Next we give characteristic polynomials of the normalized Laplacian matrix {\mathcal L}(P_{n,k}) and {\mathcal L}(R_{n,k}).
Revised:  Next we give characteristic polynomials of the normalized Laplacian matrices {\mathcal L}(P_{n,k}) and {\mathcal L}(R_{n,k}).
Edit intent: clarity
Original:  Then we give counter example graphs based on R_{n,k}, on which spectral methods and normalized cut produce different clusters.
Revised:  Then , we present counter example graphs based on R_{n,k}, on which spectral methods and normalized cut produce different clusters.
Edit intent: clarity
Original:  Then we give counter example graphs based on R_{n,k}, on which spectral methods and normalized cut produce different clusters.
Revised:  Then we give counter example graphs based on R_{n,k}, on which spectral methods and normalized cuts produce different clusters.
Edit intent: fluency
Original: A fast multipole method (FMM) for asymptotically smooth kernel functions (1/r, 1/r^4, Gauss and Stokes kernels, radial basis functions, etc.) based on a Chebyshev interpolation scheme has been introduced in [Fong and Darve , 2009].
Revised: A fast multipole method (FMM) for asymptotically smooth kernel functions (1/r, 1/r^4, Gauss and Stokes kernels, radial basis functions, etc.) based on a Chebyshev interpolation scheme has been introduced in [Fong et al. , 2009].
Edit intent: clarity
Original:  The method has been extended to oscillatory kernels ( eg. Helmholtz kernel) in [Messner et al., 2011 ].
Revised:  The method has been extended to oscillatory kernels ( e.g., Helmholtz kernel) in [Messner et al., 2011 ].
Edit intent: fluency
Original:  Beside its generality this FMM turned out to be favorable due to its easy implementation and  performance based on intense use of highly optimized BLAS libraries.
Revised:  Beside its generality this FMM turns out to be favorable due to its easy implementation and performance based on intense use of highly optimized BLAS libraries.
Edit intent: fluency
Original:  Beside its generality this FMM turned out to be favorable due to its easy implementation and  performance based on intense use of highly optimized BLAS libraries.
Revised:  Beside its generality this FMM turned out to be favorable due to its easy implementation and performance based on intensive use of highly optimized BLAS libraries.
Edit intent: fluency
Original:  However, a bottleneck has been the precomputation of the  M2L operator and its higher computational intensity compared to other FMM formulations.
Revised:  However, one of its bottlenecks is the precomputation of the M2L operator and its higher computational intensity compared to other FMM formulations.
Edit intent: clarity
Original:  However, a bottleneck has been the precomputation of the  M2L operator and its higher computational intensity compared to other FMM formulations.
Revised:  However, a bottleneck has been the precomputation of the M2L ) operator, and its higher computational intensity compared to other FMM formulations.
Edit intent: fluency
Original:  However, a bottleneck has been the precomputation of the  M2L operator and its higher computational intensity compared to other FMM formulations.
Revised:  However, a bottleneck has been the precomputation of the M2L operator and its higher number of floating point operations (flops) compared to other FMM formulations.
Edit intent: clarity
Original:  Here, we present several optimizations for that operator, which is known to be the most costly FMM operator.
Revised:  Here, we present several optimizations for that operator, which is known to be the costliest FMM operator.
Edit intent: clarity
Original: In this paper we propose a link scheduling algorithm for wireless networks that employ different modes of cooperation at the physical layer (PHY).
Revised: In this work we are concerned with the problem of link scheduling for throughput maximization in wireless networks that employ different modes of cooperation at the physical layer (PHY).
Edit intent: clarity
Original: Natural languages can express some logical propositions that humans  with similar cultural traditions, are able to immediately and correctly compute.
Revised: Natural languages can express some logical propositions that humans , with similar cultural traditions, are able to immediately and correctly compute.
Edit intent: fluency
Original: Natural languages can express some logical propositions that humans , with similar cultural traditions, are able to immediately and correctly compute .
Revised: Natural languages can express some logical propositions that humans are able to immediately and correctly compute .
Edit intent: clarity