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While evaluating SHIV, we reconsider the trade-off between Off- and On-Policy methods and find that: 1) On-Policy methods are challenging for humans supervisors and 2) performance varies with the expressiveness of the policy class.
Furthermore, the issues of treatment, disposal and handling the large quantity of water produced at steam-based EOR methods are challenging as well as the amount of emission are large used.
This type of pairwise comparison is appropriate for much of the methylation data currently available, but existing methods are challenging to generalize to analysis of more densely sampled sets of dependent cell types.
While new technologies such as optical resonators and nanowire sensors provide the advantage of direct ligand target affinity measurements, these methods are challenging to implement in complex media, at physiological salt, and in a high-throughput fashion.
However, comparative qualitative methods are challenging because of the methodological and organisational difficulties occurring.
However, the practical applications of these methods are challenging because of the exorbitant calculation times required by current methods for contemporary data sizes, the difficulty in correctly modeling the rate heterogeneity in highly diverse taxonomic groups, and the lack of reliable clock calibrations and their uncertainty distributions for most groups of species.
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However, most methods are challenged by small sample size problem since users are usually not so patient to label a large number of training instances in the relevance feedback round.
However, these methods are challenged by restricted selectivity and large amounts of toxic chemicals involved in the process resulting in secondary pollution (He et al. 2015).
The current stem-cell-tracking methods are challenged by limited sensitivity, low cell labeling efficiency, and poor stem cell homing efficiency.
Developing successful drug delivery methods is challenging for any tissue, and the eye is no exception.
SL partners of cancer mutations are of great interest as pharmacological targets; however, identifying them by cell line-based methods is challenging.
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