wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We reveal that neural networks perceive time intervals through the evolution of population state along a stereotypical trajectory, maintain time intervals by line attractors along which the activities of most neurons vary  monotonically with the duration of the maintained interval, and adjust the evolution speed of the statetrajectory for producing or comparing time intervals.
Revised:  We reveal that neural networks perceive time intervals through the evolution of population state along a stereotypical trajectory, maintain time intervals by line attractor along which most neurons vary monotonically with the duration of the maintained interval, and adjust the evolution speed of the statetrajectory for producing or comparing time intervals.
Edit intent: clarity
Original:  We reveal that neural networks perceive time intervals through the evolution of population state along a stereotypical trajectory, maintain time intervals by line attractors along which the activities of most neurons vary  monotonically with the duration of the maintained interval, and adjust the evolution speed of the statetrajectory for producing or comparing time intervals.
Revised:  We reveal that neural networks perceive time intervals through the evolution of population state along a stereotypical trajectory, maintain time intervals by line attractors along which the activities of most neurons vary their activities monotonically with the duration of the maintained interval, and adjust the evolution speed of the statetrajectory for producing or comparing time intervals.
Edit intent: clarity
Original:  We reveal that neural networks perceive time intervals through the evolution of population state along a stereotypical trajectory, maintain time intervals by line attractors along which the activities of most neurons vary  monotonically with the duration of the maintained interval, and adjust the evolution speed of the statetrajectory for producing or comparing time intervals. Spatial information or decision choice preserves the profiles of neuronal activities as functions of time intervals maintained in working memory or flow of time , and is coded in the amplitudes of these profiles. Decision making is combined with time perception through two firing sequences with mutual inhibition.
Revised:  We reveal that neural networks perceive time intervals through the evolution of population state along a stereotypical trajectory, maintain time intervals by line attractors along which the activities of most neurons vary monotonically with the duration of the maintained interval, and produce or compare time intervals by scaling the evolution velocity of population state. Time and non-time information is coded in subspaces orthogonal with each other, which facilitates generalizable decoding of time and non-time information. This is based on the network structure of multiple feedforward sequences that mutually excite or inhibit depending on whether their preferences of non-timing information are similar or not. Strong temporal signal in non-timing tasks arises from high temporal complexity of task, broad input tuning, multi-tasking and timing anticipation.
Edit intent: meaning-changed
Original:  It is not trivial how bacteria can cope with the feast-famine cycle and evolve under such situation, since in the feast period faster growth is beneficial in competition, but faster growth will shorten the feast period.
Revised:  It is not trivial how bacteria can cope with the feast-famine cycle and evolve under such a situation since in the feast period faster growth is beneficial in competition, but faster growth will shorten the feast period.
Edit intent: fluency
Original:  By allowing the model bacteria to evolve growth rate in the feast period with a trade-off with the death rate in the famine period , the bacterial population tends to increase the growth rate and the death rate , even though that tends to decrease the total population size.
Revised:  By allowing the model bacteria to evolve growth rate in the feast period with a trade-off with the growth yield and the death rate , the bacterial population tends to increase the growth rate and the death rate , even though that tends to decrease the total population size.
Edit intent: clarity
Original:  By allowing the model bacteria to evolve growth rate in the feast period with a trade-off with the death rate in the famine period , the bacterial population tends to increase the growth rate and the death rate , even though that tends to decrease the total population size.
Revised:  By allowing the model bacteria to evolve growth rate in the feast period with a trade-off with the death rate in the famine period , the bacterial population tends to increase the growth rate by changing the counterpart of the trade-off , even though that tends to decrease the total population size.
Edit intent: meaning-changed
Original:  One of the likely environmental fluctuations that happen in nature is the repeated cycle of substrate-rich conditions and starvation, called the "feast-famine cycle" . It is not trivial how bacteria can cope with the feast-famine cycle and evolve under such a situation since in the feast period faster growth is beneficial in competition, but faster growth will shorten the feast period. Furthermore, in the famine period, the tolerance to the starvation is needed, which may be negatively correlated with faster growth . We here study possible outcomes of population dynamics and evolution under the feast-famine cycle by a simple stochastic model .
Revised:  One of the likely environmental fluctuations that happen in nature is the repeated cycle of substrate-rich conditions and starvation, called the "feast-famine cycle" , by a simple stochastic model with the trade-off relationship between the growth rate and the growth yield or the death rate .
Edit intent: coherence
Original:  By allowing the model bacteria to evolve growth rate in the feast period with a trade-off with the growth yield and the death rate , the bacterial population tends to increase the growth rate by changing the counterpart of the trade-off , even though that tends to decrease the total population size . Analysis showed that , under the repeated feast-famine cycles, the ratio between the growth rate and the death rate becomes the effective fitness of the population.
Revised:  Under the repeated feast-famine cycle , the bacterial population tends to increase the growth rate by changing the counterpart of the trade-off , even though that tends to decrease the total population size . Analysis showed that , under the repeated feast-famine cycles, the ratio between the growth rate and the death rate becomes the effective fitness of the population.
Edit intent: coherence
Original:  By allowing the model bacteria to evolve growth rate in the feast period with a trade-off with the growth yield and the death rate , the bacterial population tends to increase the growth rate by changing the counterpart of the trade-off , even though that tends to decrease the total population size . Analysis showed that , under the repeated feast-famine cycles, the ratio between the growth rate and the death rate becomes the effective fitness of the population.
Revised:  By allowing the model bacteria to evolve growth rate in the feast period with a trade-off with the growth yield and the death rate , the bacterial population tends to increase the growth rate , even though that tends to decrease the total population size . Analysis showed that , under the repeated feast-famine cycles, the ratio between the growth rate and the death rate becomes the effective fitness of the population.
Edit intent: clarity
Original:  By allowing the model bacteria to evolve growth rate in the feast period with a trade-off with the growth yield and the death rate , the bacterial population tends to increase the growth rate by changing the counterpart of the trade-off , even though that tends to decrease the total population size . Analysis showed that , under the repeated feast-famine cycles, the ratio between the growth rate and the death rate becomes the effective fitness of the population.
Revised:  By allowing the model bacteria to evolve growth rate in the feast period with a trade-off with the growth yield and the death rate , the bacterial population tends to increase the growth rate by changing the counterpart of the trade-off , even though that tends to decrease the total population size due to the trade-off. Analysis of the model shows that the ratio between the growth rate and the death rate becomes the effective fitness of the population.
Edit intent: clarity
Original: Contention at the storage nodes is the main cause of long and variable data access times in distributed storage systems . Offered load on the system must be balanced across the storage nodes in order to minimize contention, and load balance in the system should be robust against the skews and fluctuations in content popularities. Data objects are replicated across multiple nodes in practice to allow for load balancing. However redundancy increases the storage requirement and should be used efficiently. We evaluate load balancing performance of natural storage schemes in which each data object is stored at d different nodes  and each node stores the same number of objects.
Revised: To facilitate load balancing, distributed systems store data redundantly. We evaluate the load balancing performance of natural storage schemes in which each data object is stored at d different nodes and each node stores the same number of objects.
Edit intent: coherence
Original:   We find that  load balance in a system of n nodes improves multiplicatively with d as long as d = o\left(\log(n)\right), and improves exponentially as soon as d = \Theta\left(\log(n)\right).
Revised:  In our model, the load offered for the objects is sampled uniformly at random from all the load vectors with a fixed cumulative value. We find that load balance in a system of n nodes improves multiplicatively with d as long as d = o\left(\log(n)\right), and improves exponentially as soon as d = \Theta\left(\log(n)\right).
Edit intent: meaning-changed
Original:   We find that  load balance in a system of n nodes improves multiplicatively with d as long as d = o\left(\log(n)\right), and improves exponentially as soon as d = \Theta\left(\log(n)\right).
Revised:  We find that the load balance in a system of n nodes improves multiplicatively with d as long as d = o\left(\log(n)\right), and improves exponentially as soon as d = \Theta\left(\log(n)\right).
Edit intent: fluency
Original:   We find that  load balance in a system of n nodes improves multiplicatively with d as long as d = o\left(\log(n)\right), and improves exponentially as soon as d = \Theta\left(\log(n)\right).
Revised:  We find that load balance in a system of n nodes improves multiplicatively with d as long as d = o\left(\log(n)\right), and improves exponentially once d = \Theta\left(\log(n)\right).
Edit intent: clarity
Original:  We show that the load balance in the system improves the same way with d when the service choices are created with XOR's of r objects rather than object replicas , which also reduces the storage overhead multiplicatively by r.
Revised:  We show that the load balance improves in the same way with d when the service choices are created with XOR's of r objects rather than object replicas , which also reduces the storage overhead multiplicatively by r.
Edit intent: clarity
Original:  We show that the load balance in the system improves the same way with d when the service choices are created with XOR's of r objects rather than object replicas , which also reduces the storage overhead multiplicatively by r.
Revised:  We show that the load balance in the system improves the same way with d when the service choices are created with XOR's of r objects rather than object replicas . In such redundancy schemes, storage overhead is reduced multiplicatively by r.
Edit intent: clarity
Original:  However, unlike accessing an object replica, access through a recovery set composed by an XOR'ed object copy requires downloading content from r nodes , which increases the load imbalance in the system additively by r  .
Revised:  However, unlike accessing an object replica, access through a recovery set composed by an XOR'ed object copy requires downloading content from r nodes . At the same time, the load balance increases additively by r .
Edit intent: clarity
Original:  However, unlike accessing an object replica, access through a recovery set composed by an XOR'ed object copy requires downloading content from r nodes , which increases the load imbalance in the system additively by r  .
Revised:  However, unlike accessing an object replica, access through a recovery set composed by an XOR'ed object copy requires downloading content from r nodes , which increases the load imbalance in the system additively by r . We express the system's load balance in terms of the maximal spacing or maximum of d consecutive spacings between the ordered statistics of uniform random variables. Using this connection and the limit results on the maximal d-spacings, we derive our main results .
Edit intent: meaning-changed
Original:  One primary challenge involves clusteringthe data points into classes with interpretable differences. A challenge in clustering high dimensional data is that multimodal signatures that define clusters may only be present in a small but unknown subspace. Discovering the subspace that defines clusters provides low dimensional representations of the data which capture cluster diversity, and provides greater understanding of the system by identifying the key underlying variables.
Revised:  Discovering informative and meaningful features is crucial for clustering, classification, and low dimensional data embedding. Here we propose to construct features based on their ability to discriminate between clusters of the data which capture cluster diversity, and provides greater understanding of the system by identifying the key underlying variables.
Edit intent: clarity
Original:  Discovering the subspace that defines clusters provides low dimensional representations of the data which capture cluster diversity, and provides greater understanding of the system by identifying the key underlying variables. Here, we define a class of problems in which linear separability of clusters is hidden in a low dimensional space.
Revised:  Discovering the subspace that defines clusters provides low dimensional representations of the data points. We define a class of problems in which linear separability of clusters is hidden in a low dimensional space.
Edit intent: clarity
Original:  In this inferred subspace, we find clear signatures of known cell types that eluded classification prior to discovery of the correct low dimensional subspace . This method can be used as a wrapper for existing clustering algorithms to find low dimensional informative subspaces with multimodal signatures within high dimensional data .
Revised:  In this inferred subspace, we find clear signatures of known cell types that eluded classification prior to discovery of the correct low dimensional subspace .
Edit intent: coherence
Original: We investigate the relation between the stationary probability distribution of chemical reaction systems and the convective field derived from the chemical Fokker-Planck equation (CFPE) . This convective field takes into account the drift term of the CFPE and the reaction bias introduced by the diffusion term.
Revised: We investigate the relation between the stationary probability distribution of chemical reaction systems and the convective field derived from the chemical Fokker-Planck equation (CFPE) by comparing predictions of the convective field to the results of stochastic simulations based on Gillespie's algorithm. The convective field takes into account the drift term of the CFPE and the reaction bias introduced by the diffusion term.
Edit intent: meaning-changed
Original:  For one-dimensional systems, fixed points and bifurcations of the convective field correspond to extrema and phenomenological bifurcations of the stationary probability distribution as long as the CFPE is a good approximation to the stochastic dynamics.
Revised:  For one-dimensional systems, fixed points and bifurcations of the convective field correspond to extrema and phenomenological bifurcations of the stationary probability distribution whenever the CFPE is a good approximation to the stochastic dynamics.
Edit intent: clarity
Original:  In contrast, the system-size dependence of the parameter values for a Hopf bifurcation of the convective field is not reflected by the onset of a crater-shaped probability distribution , as the expected crater tends to be washed out for smaller system sizes .
Revised:  In contrast, a Hopf bifurcation of the convective field is not reflected by the onset of a crater-shaped probability distribution , as the expected crater tends to be washed out for smaller system sizes .
Edit intent: clarity
Original:  In contrast, the system-size dependence of the parameter values for a Hopf bifurcation of the convective field is not reflected by the onset of a crater-shaped probability distribution , as the expected crater tends to be washed out for smaller system sizes .
Revised:  In contrast, the system-size dependence of the parameter values for a Hopf bifurcation that occurs in the convective field is not reflected by the onset of a crater-shaped probability distribution , as the expected crater tends to be washed out for smaller system sizes .
Edit intent: clarity
Original:  In contrast, the system-size dependence of the parameter values for a Hopf bifurcation of the convective field is not reflected by the onset of a crater-shaped probability distribution , as the expected crater tends to be washed out for smaller system sizes .
Revised:  In contrast, the system-size dependence of the parameter values for a Hopf bifurcation of the convective field for decreasing system size is not accompanied by the onset of a crater-shaped probability distribution , as the expected crater tends to be washed out for smaller system sizes .
Edit intent: clarity
Original:  In contrast, the system-size dependence of the parameter values for a Hopf bifurcation of the convective field is not reflected by the onset of a crater-shaped probability distribution , as the expected crater tends to be washed out for smaller system sizes .
Revised:  In contrast, the system-size dependence of the parameter values for a Hopf bifurcation of the convective field is not reflected by the onset of a crater-shaped probability distribution ; decreasing system size rather destroys craters and replaces them by local maxima .
Edit intent: meaning-changed
Original:  Using a novel entropy measure - eigen-entropy  , computed from the eigen-centralities (ranks) of different stocks in the correlation-network , we extract information about the "disorder" (or randomness) in the market and its modes.
Revised:  Using the eigen-entropy , computed from the eigen-centralities (ranks) of different stocks in the correlation-network , we extract information about the "disorder" (or randomness) in the market and its modes.
Edit intent: clarity
Original:  Using a novel entropy measure - eigen-entropy  , computed from the eigen-centralities (ranks) of different stocks in the correlation-network , we extract information about the "disorder" (or randomness) in the market and its modes.
Revised:  Using a novel entropy measure - eigen-entropy measure , computed from the eigen-centralities (ranks) of different stocks in the correlation-network , we extract information about the "disorder" (or randomness) in the market and its modes.
Edit intent: coherence
Original:  Using a novel entropy measure - eigen-entropy  , computed from the eigen-centralities (ranks) of different stocks in the correlation-network , we extract information about the "disorder" (or randomness) in the market and its modes.
Revised:  Using a novel entropy measure - eigen-entropy , computed from the eigen-centralities (ranks) of different stocks in the correlation network , we extract information about the "disorder" (or randomness) in the market and its modes.
Edit intent: fluency
Original:  Using a novel entropy measure - eigen-entropy  , computed from the eigen-centralities (ranks) of different stocks in the correlation-network , we extract information about the "disorder" (or randomness) in the market and its modes.
Revised:  Using a novel entropy measure - eigen-entropy , computed from the eigen-centralities (ranks) of different stocks in the correlation-network , we extract information about the "disorder" (or randomness) in the market correlation and its different modes.
Edit intent: meaning-changed
Original:  We choose the US S&P-500 and Japanese Nikkei-225 financial markets, over a 32-year period, and study the evolution of the cross-correlation matrices computed over different short time-intervals or "epochs", and their corresponding eigen-entropies.
Revised:  We choose the US S&P-500 and Japanese Nikkei-225 financial markets, over a 32-year period, and study the evolution of the cross-correlation matrices and their corresponding eigen-entropies.
Edit intent: clarity
Original:  We compare and contrast the empirical results against the numerical results for Wishart orthogonal ensemble (WOE), which has the maximum disorder (randomness) and hence, the highest eigen-entropy .
Revised:  One of the relative entropy measures displays "universal scaling" behavior with respect to the mean market correlation. Further, a functional of the relative entropy measure acts as a good gauge for the "market fragility" (minimum risk of the market portfolio) and the "market fear" (volatility index) .
Edit intent: meaning-changed
Original:  This is achieved by using threads in a warp cooperatively to stream the adjacency and edge label matrices of individual graphs by small square  tiles, which are then staged in registers and the shared memory for later reuse.
Revised:  This is achieved by using threads in a warp cooperatively to stream the adjacency and edge label matrices of individual graphs by small square matrix blocks called tiles, which are then staged in registers and the shared memory for later reuse.
Edit intent: meaning-changed
Original:  The sparsity of the graphs is exploited hierarchically by storing only non-empty tiles of the graphs and non-zero elements within each tile using a coordinate format and bitmaps, respectively. A new partition-based reordering algorithm is proposed for aggregating non-zero elements of the graphs into fewer but denser tiles in order to improve the efficiency of the sparse format.
Revised:  The sparsity of the graphs is exploited hierarchically by storing only non-empty tiles of the graphs and non-zero elements within each tile using bitmaps. We propose a new partition-based reordering algorithm is proposed for aggregating non-zero elements of the graphs into fewer but denser tiles in order to improve the efficiency of the sparse format.
Edit intent: coherence
Original:  A new partition-based reordering algorithm is proposed for aggregating non-zero elements of the graphs into fewer but denser tiles in order to improve the efficiency of the sparse format. We carried out extensive theoretical analyses on the graph tensor product primitives between tiles of various density , and evaluated their performance on synthetic and real-world datasets.
Revised:  A new partition-based reordering algorithm is proposed for aggregating non-zero elements of the graphs into fewer but denser tiles to further exploit sparsity. We carry out extensive theoretical analyses on the graph tensor product primitives between tiles of various density , and evaluated their performance on synthetic and real-world datasets.
Edit intent: meaning-changed