wanyu/IteraTeR_v2 huggingface dataset:
Original:  We demonstrate this approach on a range of real-world examples with known community structure, finding that it is able to determine the number of communities correctly in every case.
Revised:  We demonstrate the approach on a range of real-world examples with known community structure, finding that it is able to determine the number of communities correctly in every case.
Edit intent: fluency
Original:  We make the following three contributions: (i) an architecture combining a feed forward module with a recurrent module, where the recurrent module can be run iteratively to improve the performance ;
Revised:  We make the following three contributions: (i) an architecture combining a feed forward module with a recurrent module, where the recurrent module can be run iteratively to improve the performance ,
Edit intent: fluency
Original:  (ii) the model can be trained end-to-end and from scratch, with auxiliary losses incorporated to improve performance ;
Revised:  (ii) the model can be trained end-to-end and from scratch, with auxiliary losses incorporated to improve performance ,
Edit intent: fluency
Original:  Although many text summarization methods have been proposed, developing domain-specific methods for the biomedical texts is a challenging task .
Revised:  Some of the biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text. However, it seems that exploring other measures rather than the frequency for identifying the valuable content of the input document, and considering the correlations existing between concepts can be more useful for this type of summarization .
Edit intent: coherence
Original:  Unlike many existing methods, the system learns to classify the sentences without the need for training data, and selects them for the summary according to the distribution of essential conceptswithin the original text .
Revised:  Unlike many existing methods, the system learns to classify the sentences without the need for training data, and selects them for the summary according to the distribution of these concepts .
Edit intent: clarity
Original:  We show that  the use of critical concepts to represent the sentences as vectors of features, and classifying the sentences based on the distribution of those concepts, will improve the performance of automatic summarization.
Revised:  We show that with the use of critical concepts to represent the sentences as vectors of features, and classifying the sentences based on the distribution of those concepts, will improve the performance of automatic summarization.
Edit intent: coherence
Original:  We show that  the use of critical concepts to represent the sentences as vectors of features, and classifying the sentences based on the distribution of those concepts, will improve the performance of automatic summarization.
Revised:  We show that the use of critical concepts to represent the sentences as vectors of features, and classifying the sentences based on the distribution of those concepts, will improve the performance of summarization.
Edit intent: clarity
Original:  An extensive evaluation is performed on a collection of scientific articles in biomedical domain.
Revised:  An extensive evaluation was performed on a collection of scientific articles in biomedical domain.
Edit intent: clarity
Original:  An extensive evaluation is performed on a collection of scientific articles in biomedical domain.
Revised:  An extensive evaluation is performed on a collection of scientific papers in biomedical domain.
Edit intent: fluency
Original: Automatic text summarization tools help biomedical researchers and clinicians to acquire intended information from various textual resources in shorter time and with less effort . Some of the biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text.
Revised: Automatic text summarization tools help users in biomedical domain to acquire their intended information from various textual resources in shorter time and with less effort . Some of the biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text.
Edit intent: clarity
Original: Automatic text summarization tools help biomedical researchers and clinicians to acquire intended information from various textual resources in shorter time and with less effort . Some of the biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text.
Revised: Automatic text summarization tools help biomedical researchers and clinicians to acquire intended information from various textual resources more efficiently . Some of the biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text.
Edit intent: clarity
Original:  However, it seems that exploring other measures rather than the frequency for identifying the valuable content of the input document, and considering the correlations existing between concepts can be more useful for this type of summarization.
Revised:  However, it seems that exploring other measures rather than the frequency for identifying the valuable content of the input document, and considering the correlations existing between concepts may be more useful for this type of summarization.
Edit intent: coherence
Original:  The input text is mapped to the Unified Medical Language System (UMLS) concepts, and the important ones are selected to be used as the classification features.
Revised:  The input text is mapped to the Unified Medical Language System (UMLS) concepts, then it selects the important ones are selected to be used as the classification features.
Edit intent: coherence
Original:  The input text is mapped to the Unified Medical Language System (UMLS) concepts, and the important ones are selected to be used as the classification features.
Revised:  The input text is mapped to the Unified Medical Language System (UMLS) concepts, and the important ones to be used as the classification features.
Edit intent: coherence
Original:  The input text is mapped to the Unified Medical Language System (UMLS) concepts, and the important ones are selected to be used as the classification features.
Revised:  The input text is mapped to the Unified Medical Language System (UMLS) concepts, and the important ones are selected to be used as classification features.
Edit intent: fluency
Original:  We introduce different feature selection approaches to identify the most important concepts of the text and  select the most informative content according to the distribution of these concepts.
Revised:  We introduce different feature selection approaches to identify the most important concepts of the text and to select the most informative content according to the distribution of these concepts.
Edit intent: fluency
Original:  We show that with the use of an appropriate feature selection approach, our Bayesian biomedical summarizer can improve the performance of summarization.
Revised:  We show that with the use of an appropriate feature selection approach, the Bayesian biomedical summarizer can improve the performance of summarization.
Edit intent: clarity
Original:  An extensive evaluation was performed on a collection of scientific papers in biomedical domain.
Revised:  We perform extensive evaluations on a corpus of scientific papers in biomedical domain.
Edit intent: clarity
Original:  Moreover, the results suggest that using the meaningfulness measure and considering the correlations of concepts in the feature selection step yield a desirable summarization performance .
Revised:  Moreover, the results suggest that using the meaningfulness measure and considering the correlations of concepts in the feature selection step lead to a significant increase in the performance of summarization .
Edit intent: clarity
Original:  When gradients are shallow or noisy, most organisms move by alternating straight motion (runs) with random reorientations (tumbles) .
Revised:  When gradients are shallow or noisy, most organisms move by alternating straight motions (runs) with random reorientations (tumbles) .
Edit intent: fluency
Original:  In an attractant field, motion up the gradient reduces tumble probability, which further boosts drift up the gradient.
Revised:  In an attractant field, motion up the gradient reduces tumbling probability, further boosting drift up the gradient.
Edit intent: clarity
Original:  This positive feedback can drive large fluctuations in the internal state of the organism away from its mean, resulting in long runs in favorable directions but short ones otherwise.
Revised:  Importantly, such positive feedback can drive large fluctuations in the internal state of the organism away from its mean, resulting in long runs in favorable directions but short ones otherwise.
Edit intent: coherence
Original:  We here apply connICA to investigate associations between network-traits derived from task-free FC and cognitive  features that define levels of consciousness.
Revised:  We here apply connICA to investigate associations between network traits derived from task-free FC and cognitive features that define levels of consciousness.
Edit intent: fluency
Original:  The first one represents the functional configuration of an "awake resting" brain, and is associated to the level of arousal.
Revised:  The first one represents the functional configuration it is associated to the level of arousal.
Edit intent: clarity
Original:  The second FC-trait reflects the disconnection of the visual and sensory-motor connectivity patterns and relates to the  ability of communicating with the external environment.
Revised:  The second FC-trait reflects the disconnection of the visual and sensory-motor connectivity patterns . It also relates to the ability of communicating with the external environment.
Edit intent: coherence
Original:  The third FC-trait isolates the connectivity pattern encompassing the fronto-parietal and the default-mode network areas as well as the interaction between left and right hemisphere , which are also associated to the awareness of the self and its surroundings.
Revised:  The third FC-trait isolates the connectivity pattern encompassing the fronto-parietal and the default-mode network areas as well as the interaction between left and right hemispheres , which are also associated to the awareness of the self and its surroundings.
Edit intent: fluency
Original:  Each FC-trait represents a distinct functional process with a role in the degradation of conscious states in functional brain networks, shedding further light on the functional subcircuits that get disrupted in severe brain-damage.
Revised:  Each FC-trait represents a distinct functional process with a role in the degradation of conscious states of functional brain networks, shedding further light on the functional subcircuits that get disrupted in severe brain-damage.
Edit intent: fluency
Original: Many real-world networked systems exhibit a multicore-periphery structure, i.e., multiple cores, each of which contains densely connected elements, surrounded by sparsely connected elements that define the periphery .
Revised: Many real-world networks exhibit a multicores-periphery structure, with densely connected vertices in multiple cores surrounded by a general periphery of sparsely connected vertices .
Edit intent: clarity
Original:  Identification of the multiple-periphery structure can provide a new handle on structures and functions of various complex networks, such as cognitive and biological networks, food webs, social networks, and communication and transportation networks.
Revised:  Identification of the multicores-periphery structure can provide a new handle on structures and functions of various complex networks, such as cognitive and biological networks, food webs, social networks, and communication and transportation networks.
Edit intent: fluency
Original:  Identification of the multiple-periphery structure can provide a new handle on structures and functions of various complex networks, such as cognitive and biological networks, food webs, social networks, and communication and transportation networks.
Revised:  Identification of the multiple-periphery structure can provide a new lens to understand the structures and functions of various complex networks, such as cognitive and biological networks, food webs, social networks, and communication and transportation networks.
Edit intent: clarity
Original:  Herein, we introduce a method to identify the optimal partition of a network into multiple dense cores and a loosely-connected periphery , and test the method on a well-known social network and the technology space network, which are best characterized by multiple-core structures.
Revised:  Herein, we introduce a method to identify the optimal partition of a network into multiple dense cores and a well-known social network and the technology space network, which are best characterized by multiple-core structures.
Edit intent: clarity
Original:  Herein, we introduce a method to identify the optimal partition of a network into multiple dense cores and a loosely-connected periphery , and test the method on a well-known social network and the technology space network, which are best characterized by multiple-core structures.
Revised:  Herein, we introduce a method to identify the optimal partition of a network into multiple dense cores and a loosely-connected periphery , and test the method on a well-known social network and a patent technology network, which are best characterized by multiple-core structures.
Edit intent: clarity
Original: Estimation of the number of species or unobserved classes from a  sample of the underlying population is an ubiquitous problem in statistics.
Revised: Estimation of the number of species or unobserved classes from a random sample of the underlying population is an ubiquitous problem in statistics.
Edit intent: clarity
Original: Estimation of the number of species or unobserved classes from a  sample of the underlying population is an ubiquitous problem in statistics.
Revised: Estimation of the number of species or unobserved classes from a sample of the underlying population is a ubiquitous problem in statistics.
Edit intent: fluency
Original:  New algorithms are required that both take advantage of the scale of the data to account for heterogeneity  but are also sufficiently fast to run in a reasonable amount of time .
Revised:  New algorithms are required that take advantage of the scale of the data to account for heterogeneity but are also sufficiently fast to run in a reasonable amount of time .
Edit intent: clarity
Original:  New algorithms are required that both take advantage of the scale of the data to account for heterogeneity  but are also sufficiently fast to run in a reasonable amount of time .
Revised:  New algorithms are required that both take advantage of the size of the data to account for heterogeneity but are also sufficiently fast to run in a reasonable amount of time .
Edit intent: fluency
Original:  New algorithms are required that both take advantage of the scale of the data to account for heterogeneity  but are also sufficiently fast to run in a reasonable amount of time .
Revised:  New algorithms are required that both take advantage of the scale of the data to account for heterogeneity , but are also sufficiently fast to run in a reasonable amount of time .
Edit intent: fluency
Original:  We present a non-parametric moment based estimator that is both computationally efficient and is sufficiently flexible to account for heterogeneity in the  underlying population.
Revised:  We present a non-parametric moment-based estimator that is both computationally efficient and is sufficiently flexible to account for heterogeneity in the underlying population.
Edit intent: fluency
Original:  This estimator is based on an extension of Chao's moment based lower bound (Chao, 1984), originally developed by Harris (1959) but unattainable due to the lack of efficient algorithms to solve the system of nonlinear equation required for estimation.
Revised:  This estimator is based on an extension of a popular moment-based lower bound (Chao, 1984), originally developed by Harris (1959) but unattainable due to the lack of efficient algorithms to solve the system of nonlinear equation required for estimation.
Edit intent: clarity
Original:  This estimator is based on an extension of Chao's moment based lower bound (Chao, 1984), originally developed by Harris (1959) but unattainable due to the lack of efficient algorithms to solve the system of nonlinear equation required for estimation.
Revised:  This estimator is based on an extension of Chao's moment based lower bound (Chao, 1984), originally developed by Harris (1959) but unattainable due to the lack of economical algorithms to solve the system of nonlinear equation required for estimation.
Edit intent: clarity
Original:  This is in contrast to a directional "activation based" approach which is typical in univariate group level analysis, in which both signal magnitude and sign are taken into account.
Revised:  This is in contrast to a directional "activation based" approach typical in univariate group level analysis, in which both signal magnitude and sign are taken into account.
Edit intent: coherence
Original:  While a directional  MVPA approach implies that individuals share multivariate spatial patterns of activity, in a non-directional approach each individual may have a distinct spatial pattern of activity.
Revised:  While a directional MVPA approach implies that individuals have similar multivariate spatial patterns of activity, in a non-directional approach each individual may have a distinct spatial pattern of activity.
Edit intent: clarity
Original:  Here we show using an experimental dataset that indeed directional and non-directional  MVPA approaches uncover distinct brain regions with some overlap.
Revised:  Here we show using an experimental dataset , we show that directional and non-directional MVPA approaches uncover distinct brain regions with some overlap.
Edit intent: coherence
Original:  Applying FuA to an auditory task, we found higher values in primary auditory regions compared to secondary and control regions.
Revised:  Applying FuA to an auditory task, we find higher values in primary auditory regions compared to secondary and control regions.
Edit intent: fluency
Original:  Applying FuA to an auditory task, we found higher values in primary auditory regions compared to secondary and control regions.
Revised:  Applying FuA to an auditory task, we found higher values in auditory regions compared to secondary and control regions.
Edit intent: clarity
Original:  Our methods are constructive, allowing us to compute low-distortion mappings that are within a 2^{O(n ( \log \log n )^2 /\log n)} factor of optimal in polynomial time and within a n^{O(\log n)} factor of optimal in singly exponential time.
Revised:  Our methods are constructive, allowing us to compute low-distortion mappings that are within a 2^{O(n \log \log n )^2 /\log n)} factor of optimal in polynomial time and within a n^{O(\log n)} factor of optimal in singly exponential time.
Edit intent: fluency
Original:  Our methods are constructive, allowing us to compute low-distortion mappings that are within a 2^{O(n ( \log \log n )^2 /\log n)} factor of optimal in polynomial time and within a n^{O(\log n)} factor of optimal in singly exponential time.
Revised:  Our methods are constructive, allowing us to compute low-distortion mappings that are within a 2^{O(n ( \log \log n /\log n)} factor of optimal in polynomial time and within a n^{O(\log n)} factor of optimal in singly exponential time.
Edit intent: clarity
Original:  Based on these incidents, and the heavy usage of antibiotics in hospitals, it has been assumed that antibiotic resistance evolves in hospital environments.
Revised:  Based on these incidents, and the heavy usage of antibiotics in hospitals, it has been assumed that anti-biotic resistance evolves in hospital environments.
Edit intent: clarity
Original:  We found that the hospital environment has a significant effect upon  evolution of resistance to Cefepime and Ceftazidime but that, for the other antibiotics tested, the hospital is merely a piece of the larger picture.
Revised:  We found that the hospital environment has a significant effect upon the evolution of resistance to Cefepime and Ceftazidime but that, for the other antibiotics tested, the hospital is merely a piece of the larger picture.
Edit intent: fluency
Original:  We found that the hospital environment has a significant effect upon  evolution of resistance to Cefepime and Ceftazidime but that, for the other antibiotics tested, the hospital is merely a piece of the larger picture.
Revised:  We found that the hospital environment has a significant effect upon evolution of resistance ; the hospital is merely a piece of the larger picture.
Edit intent: coherence
Original: Nosocomial outbreaks of bacteria have been documented many times . Based on these incidents, and the heavy usage of antibiotics in hospitals, it has been assumed that anti-biotic resistance evolves in hospital environments.
Revised: Nosocomial outbreaks of bacteria are well-documented . Based on these incidents, and the heavy usage of antibiotics in hospitals, it has been assumed that anti-biotic resistance evolves in hospital environments.
Edit intent: clarity
Original: Nosocomial outbreaks of bacteria have been documented many times . Based on these incidents, and the heavy usage of antibiotics in hospitals, it has been assumed that anti-biotic resistance evolves in hospital environments.
Revised: Nosocomial outbreaks of bacteria have been documented many times . Based on these incidents, and the heavy usage of antibiotics in hospitals, it has been assumed that antibiotic resistance evolves in hospital environments.
Edit intent: clarity
Original:  To test this assumption, we analyzed the resistance phenotypes of bacteria collected  at a community hospital over a 2.5-year period.
Revised:  To test this assumption, we studied resistance phenotypes of bacteria collected at a community hospital over a 2.5-year period.
Edit intent: clarity
Original:  First, to assess dependence of antibiotic resistance on factors other than time, we performed a graphical model analysis .
Revised:  A graphical model analysis .
Edit intent: clarity
Original:  It can inform hospital staff about the effects of various practices and interventions, can be used to help detect clonal outbreaks, and is available free of charge .
Revised:  It can inform hospital staff about the effects of various practices and interventions, can help detect clonal outbreaks, and is available free of charge .
Edit intent: clarity
Original:  The p-values obtained for the other 3 antibiotics (Cefepime, Ceftazidime and Gentamycin ) indicate that particular care should be taken in hospital practices with these antibiotics.
Revised:  The p-values obtained for the other three antibiotics (Cefepime, Ceftazidime and Gentamycin ) indicate that particular care should be taken in hospital practices with these antibiotics.
Edit intent: fluency
Original:  The p-values obtained for the other 3 antibiotics (Cefepime, Ceftazidime and Gentamycin ) indicate that particular care should be taken in hospital practices with these antibiotics.
Revised:  The p-values obtained for the other 3 antibiotics (Cefepime, Ceftazidime and Gentamicin ) indicate that particular care should be taken in hospital practices with these antibiotics.
Edit intent: clarity
Original:  One of the three, Ceftazidime, was significant after accounting for multiple hypotheses, indicating a significant evolution of hospital-based resistance for this drug.
Revised:  One of the three, Ceftazidime, was significant after accounting for multiple hypotheses, indicating a trend of decreased resistance for this drug.
Edit intent: clarity