wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Here we show that any conditional distribution P can however be implemented if the master equation dynamics has access to additional "hidden" states , not in X . We investigate how the minimal number of such hidden states needed to implement some P in a thermodynamically reversible manner depends on P. We provide exact results in the special case of conditional distributions that represent single-valued functions.
Revised:  Here we show that any conditional distribution P can however be implemented if the master equation dynamics has access to additional "hidden" states , not in X . We investigate how the minimal number of such hidden states needed to do so. We calculate this cost exactly for the special case of conditional distributions that represent single-valued functions.
Edit intent: clarity
Original:  We provide exact results in the special case of conditional distributions that represent single-valued functions. In the general case, we provide an upper bound on the needed number of hidden states in terms of the nonnegative rank of P.
Revised:  We provide exact results in the special case of conditional distributions that represent single-valued function, and provide an upper bound on the needed number of hidden states in terms of the nonnegative rank of P.
Edit intent: coherence
Original:  In particular, we show that if there are no constraints on what master equation we can construct, then having access to one extra binary degree of freedom ( doubling the total number of states ) is sufficient to carry out any P with zero entropy production.
Revised:  In particular, we show that if there are no constraints on what master equation we can construct, then having access to one extra binary degree of freedom , thus doubling the total number of states ) is sufficient to carry out any P with zero entropy production.
Edit intent: clarity
Original:  In particular, we show that if there are no constraints on what master equation we can construct, then having access to one extra binary degree of freedom ( doubling the total number of states ) is sufficient to carry out any P with zero entropy production.
Revised:  In particular, we show that if there are no constraints on what master equation we can construct, then having access to one extra binary degree of freedom ( doubling the total number of states , is sufficient to carry out any P with zero entropy production.
Edit intent: fluency
Original:  In particular, we show that if there are no constraints on what master equation we can construct, then having access to one extra binary degree of freedom ( doubling the total number of states ) is sufficient to carry out any P with zero entropy production.
Revised:  In particular, we show that if there are no constraints on what master equation we can construct, then having access to one extra binary degree of freedom ( doubling the total number of states ) is sufficient to implement any P with zero entropy production.
Edit intent: clarity
Original:  In particular, we show that if there are no constraints on what master equation we can construct, then having access to one extra binary degree of freedom ( doubling the total number of states ) is sufficient to carry out any P with zero entropy production.
Revised:  In particular, we show that if there are no constraints on what master equation we can construct, then having access to one extra binary degree of freedom ( doubling the total number of states ) is sufficient to carry out any P with a master equation in a thermodynamically reversible way, if there are no constraints on the allowed form of the master equation. (Such constraints can greatly increase the minimal needed number of hidden states.)
Edit intent: meaning-changed
Original:  Our results also imply that for certain P that can be implemented without hidden states, having additional states available permits an implementation that generates less heat . These results can be seen as uncovering and investigating a novel type of cost of the physical resources needed to perform information processing---the size of a system's hidden state space .
Revised:  Our results also imply that for certain P that can be implemented without hidden states, having additional states available permits an implementation that generates less heat .
Edit intent: coherence
Original:  In this paper, we present a novel Partition-Centric Processing Methodology (PCPM)  that drastically reduces the amount of communication with DRAM and achieves high memory bandwidth.
Revised:  In this paper, we present a novel Partition-Centric Processing Methodology (PCPM) to compute PageRank, that drastically reduces the amount of communication with DRAM and achieves high memory bandwidth.
Edit intent: meaning-changed
Original:  Similar to the state of the art Binning with Vertex-centric Gather-Apply-Scatter ( BVGAS) method, PCPM performs partition wise scatter and gather of updates with both phases enjoying full cache line utilization.
Revised:  PCPM uses a Partition-centric abstraction coupled with the Gather-Apply-Scatter ( BVGAS) method, PCPM performs partition wise scatter and gather of updates with both phases enjoying full cache line utilization.
Edit intent: clarity
Original:  Similar to the state of the art Binning with Vertex-centric Gather-Apply-Scatter ( BVGAS) method, PCPM performs partition wise scatter and gather of updates with both phases enjoying full cache line utilization. However, BVGAS suffers from random memory accesses and redundant read/write of update values from nodes to their neighbors. In contrast, PCPM propagates single update from source node to all destinations in a partition, thus decreasing redundancy effectively. We make use of this characteristic to develop a novel bipartite Partition-Node Graph (PNG) data layout for PCPM, that enables streaming memory accesses, with very little generation overhead .
Revised:  Similar to the state of the art Binning with Vertex-centric Gather-Apply-Scatter ( GAS) programming model. By carefully examining how a PCPM based implementation impacts communication characteristics of the algorithm, we propose several system optimizations that improve the execution time substantially. More specifically, we develop (1) a new data layout that significantly reduces communication and random DRAM accesses, and (2) branch avoidance mechanisms to get rid of unpredictable data-dependent branches .
Edit intent: clarity
Original:  We perform detailed analysis of PCPM and provide theoretical bounds on the amount of communication and random DRAM accesses. We experimentally evaluate our approach using 6 large graph datasets and demonstrate an average 2.7x speedup in execution time and 1.7x reduction in communication  , compared to the state of the art .
Revised:  We perform detailed analytical and experimental evaluation of our approach using 6 large graph datasets and demonstrate an average 2.7x speedup in execution time and 1.7x reduction in communication , compared to the state of the art .
Edit intent: clarity
Original:  We experimentally evaluate our approach using 6 large graph datasets and demonstrate an average 2.7x speedup in execution time and 1.7x reduction in communication  , compared to the state of the art .
Revised:  We experimentally evaluate our approach using 6 large graphs and demonstrate an average 2.7x speedup in execution time and 1.7x reduction in communication , compared to the state of the art .
Edit intent: clarity
Original:  We experimentally evaluate our approach using 6 large graph datasets and demonstrate an average 2.7x speedup in execution time and 1.7x reduction in communication  , compared to the state of the art .
Revised:  We experimentally evaluate our approach using 6 large graph datasets and demonstrate an average 2.7x speedup in execution time and 1.7x reduction in communication volume , compared to the state of the art .
Edit intent: clarity
Original:  We experimentally evaluate our approach using 6 large graph datasets and demonstrate an average 2.7x speedup in execution time and 1.7x reduction in communication  , compared to the state of the art .
Revised:  We experimentally evaluate our approach using 6 large graph datasets and demonstrate an average 2.7x speedup in execution time and 1.7x reduction in communication , compared to the state-of-the-art .
Edit intent: fluency
Original:  We also show that unlike the BVGAS implementation , PCPM is able to take advantage of intelligent node labeling that enhances locality in graphs, by further reducing the amount of communication with DRAM . Although we use PageRank as the target application in this paper, our approach can be applied to generic SpMV computation.
Revised:  We also show that unlike other GAS based implementations , PCPM is able to take advantage of intelligent node labeling that enhances locality in graphs, by further reducing the amount of communication with DRAM . Although we use PageRank as the target application in this paper, our approach can be applied to generic SpMV computation.
Edit intent: meaning-changed
Original:  We also show that unlike the BVGAS implementation , PCPM is able to take advantage of intelligent node labeling that enhances locality in graphs, by further reducing the amount of communication with DRAM . Although we use PageRank as the target application in this paper, our approach can be applied to generic SpMV computation.
Revised:  We also show that unlike the BVGAS implementation , PCPM is able to further reduce main memory traffic by taking advantage of intelligent node labeling that enhances locality in graphs, by further reducing the amount of communication with DRAM . Although we use PageRank as the target application in this paper, our approach can be applied to generic SpMV computation.
Edit intent: meaning-changed
Original:  We also show that unlike the BVGAS implementation , PCPM is able to take advantage of intelligent node labeling that enhances locality in graphs, by further reducing the amount of communication with DRAM . Although we use PageRank as the target application in this paper, our approach can be applied to generic SpMV computation.
Revised:  We also show that unlike the BVGAS implementation , PCPM is able to take advantage of intelligent node labeling that enhances locality . Although we use PageRank as the target application in this paper, our approach can be applied to generic SpMV computation.
Edit intent: coherence
Original: Voxel based analysis (VBA) of preclinical magnetic resonance images is widely used in neuroscience.
Revised: While many neuroscience questions aim to understand the human brain, much current knowledge has been gained using animal models, which replicate genetic, structural, and connectivity aspects of the human brain. While voxel-based analysis (VBA) of preclinical magnetic resonance images is widely used in neuroscience.
Edit intent: meaning-changed
Original:  To address the need for quantitative VBA validation we propose a  framework consisting of morphological phantoms, and four quantitative metrics. We address several factors that impact VBA results, including registration parameters, and template construction strategies.
Revised:  To address the need for quantitative VBA validation we propose a framework consisting of morphological phantoms, and four metrics. This addresses several sources that impact VBA results, including registration parameters, and template construction strategies.
Edit intent: clarity
Original:  The travel distance  and its variance of motor are, however, physically constrained by energy consumption, the principle of which has recently been formulated into the thermodynamic uncertainty relation , the product between the heat dissipated from a motor and the squared relative error in the displacement, has a minimal theoretical bound (Q \geq 2 k_B T), which is approached when the time trajectory of the motor is maximally regular for a given amount of free energy input.
Revised:  The travel distance of the motor and its variance of motor are, however, physically constrained by energy consumption, the principle of which has recently been formulated into the thermodynamic uncertainty relation , the product between the heat dissipated from a motor and the squared relative error in the displacement, has a minimal theoretical bound (Q \geq 2 k_B T), which is approached when the time trajectory of the motor is maximally regular for a given amount of free energy input.
Edit intent: fluency
Original:  The travel distance  and its variance of motor are, however, physically constrained by energy consumption, the principle of which has recently been formulated into the thermodynamic uncertainty relation , the product between the heat dissipated from a motor and the squared relative error in the displacement, has a minimal theoretical bound (Q \geq 2 k_B T), which is approached when the time trajectory of the motor is maximally regular for a given amount of free energy input.
Revised:  The travel distance and its variance are, however, physically constrained by energy consumption, the principle of which has recently been formulated into the thermodynamic uncertainty relation , the product between the heat dissipated from a motor and the squared relative error in the displacement, has a minimal theoretical bound (Q \geq 2 k_B T), which is approached when the time trajectory of the motor is maximally regular for a given amount of free energy input.
Edit intent: clarity
Original:  The travel distance  and its variance of motor are, however, physically constrained by energy consumption, the principle of which has recently been formulated into the thermodynamic uncertainty relation , the product between the heat dissipated from a motor and the squared relative error in the displacement, has a minimal theoretical bound (Q \geq 2 k_B T), which is approached when the time trajectory of the motor is maximally regular for a given amount of free energy input.
Revised:  The travel distance and its variance of motor are, however, physically constrained by the free energy being consumed. A recently formulated thermodynamic uncertainty relation , the product between the heat dissipated from a motor and the squared relative error in the displacement, has a minimal theoretical bound (Q \geq 2 k_B T), which is approached when the time trajectory of the motor is maximally regular for a given amount of free energy input.
Edit intent: clarity
Original:  The travel distance  and its variance of motor are, however, physically constrained by energy consumption, the principle of which has recently been formulated into the thermodynamic uncertainty relation , the product between the heat dissipated from a motor and the squared relative error in the displacement, has a minimal theoretical bound (Q \geq 2 k_B T), which is approached when the time trajectory of the motor is maximally regular for a given amount of free energy input.
Revised:  The travel distance and its variance of motor are, however, physically constrained by energy consumption, the principle of which has recently been formulated into the thermodynamic uncertainty relation offers a theoretical framework for the energy-accuracy trade-off relation ubiquitous in biological processes. According to the relation, a measure \mathcal{Q, the product between the heat dissipated from a motor and the squared relative error in the displacement, has a minimal theoretical bound (Q \geq 2 k_B T), which is approached when the time trajectory of the motor is maximally regular for a given amount of free energy input.
Edit intent: meaning-changed
Original:  Here, we use \mathcal{Q} to quantify the transport efficiency of biological motors} . Here, we reinterpret the uncertainty measure (\mathcal{Q) defined in the thermodynamic uncertainty relation such that a motor efficient in cargo transport is characterized with a small \mathcal{Q} . } Analyses on the motility data from several types of molecular motors show that \mathcal{Q} is a nonmonotic function of ATP concentration and load (f).
Revised:  Here, we use \mathcal{Q} to quantify the transport efficiency of biological motors} . ) defined in the thermodynamic uncertainty relation such that a motor efficient in cargo transport is characterized with a small \mathcal{Q} . } Analyses on the motility data from several types of molecular motors show that \mathcal{Q} is a nonmonotic function of ATP concentration and load (f).
Edit intent: clarity
Original:  Here, we use \mathcal{Q} to quantify the transport efficiency of biological motors} . Here, we reinterpret the uncertainty measure (\mathcal{Q) defined in the thermodynamic uncertainty relation such that a motor efficient in cargo transport is characterized with a small \mathcal{Q} . } Analyses on the motility data from several types of molecular motors show that \mathcal{Q} is a nonmonotic function of ATP concentration and load (f).
Revised:  Here, we use \mathcal{Q} to quantify the transport efficiency of biological motors} . Here, we reinterpret the uncertainty measure (\mathcal{Q) defined in the thermodynamic uncertainty relation such that a motor efficient in cargo transport is characterized with a small \mathcal{Q} . } Analyses on the motility data from several types of molecular motors reveal that \mathcal{Q} is a nonmonotic function of ATP concentration and load (f).
Edit intent: fluency
Original:  Here, we use \mathcal{Q} to quantify the transport efficiency of biological motors} . Here, we reinterpret the uncertainty measure (\mathcal{Q) defined in the thermodynamic uncertainty relation such that a motor efficient in cargo transport is characterized with a small \mathcal{Q} . } Analyses on the motility data from several types of molecular motors show that \mathcal{Q} is a nonmonotic function of ATP concentration and load (f).
Revised:  Here, we use \mathcal{Q} to quantify the transport efficiency of biological motors} . Here, we reinterpret the uncertainty measure (\mathcal{Q) defined in the thermodynamic uncertainty relation such that a motor efficient in cargo transport is characterized with a small \mathcal{Q} . } Analyses on the motility data from several types of molecular motors show that \mathcal{Q} is a complex function of ATP concentration and load (f).
Edit intent: clarity
Original:  For kinesin-1, \mathcal{Q} \muM  is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties.
Revised:  For kinesin-1, \mathcal{Q} approaches the theoretical bound at f\approx 4 pN and over a broad range of ATP concentration (1\muM is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties.
Edit intent: meaning-changed
Original:  For kinesin-1, \mathcal{Q} \muM  is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties.
Revised:  For kinesin-1, \mathcal{Q} \muM - 10 mM), and is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties.
Edit intent: meaning-changed
Original:  For kinesin-1, \mathcal{Q} \muM  is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties.
Revised:  For kinesin-1, \mathcal{Q} \muM is locally minimized at [ATP] \approx 200 \muM . In stark contrast, this local minimum vanishes for a mutant that has a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties.
Edit intent: clarity
Original:  For kinesin-1, \mathcal{Q} \muM  is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties.
Revised:  For kinesin-1, \mathcal{Q} \muM is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties.
Edit intent: clarity
Original:  For kinesin-1, \mathcal{Q} \muM  is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties.
Revised:  For kinesin-1, \mathcal{Q} \muM is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the value of \mathcal{Q , which underscores the importance of molecular structure in transport properties.
Edit intent: clarity
Original:  For kinesin-1, \mathcal{Q} \muM  is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure in transport properties. For the biological motors studied here , their value of \mathcal{Q semi-optimized under the cellular condition ([ATP] \approx 1 mM, f=0-1 pN).
Revised:  For kinesin-1, \mathcal{Q} \muM is locally minimized at [ATP] \approx 200 \muM and f\approx 4 pN. Remarkably, for the mutant with a longer neck-linker this local minimum vanishes , and the energetic cost to achieve the same precision as the wild-type increases significantly , which underscores the importance of molecular structure . Transport efficiencies of the biological motors studied here , their value of \mathcal{Q semi-optimized under the cellular condition ([ATP] \approx 1 mM, f=0-1 pN).
Edit intent: clarity
Original:  In this paper we use a novel and reproducible methodology to calibrate a lumped-parameter CV model to left ventricular pressure and volume time series data from rats . Key steps in our methodology include using (1) literature and available data to define a set of nominal parameter values specific to each rat ;
Revised:  In this study we present a novel methodology that is used here to calibrate a lumped-parameter CV model to left ventricular pressure and volume time series data from rats . Key steps in our methodology include using (1) literature and available data to define a set of nominal parameter values specific to each rat ;
Edit intent: clarity