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The friction model structure enables irreversible transmissions to be simulated, if needed.
This universal model structure enables a single block to be developed independently, without the performances of the remaining blocks being affected.
This model structure enables the structure of the trajectories to be separated into growth parameters, both linear and quadratic, as well as other types of differences in the response probabilities, which we will refer to as nonlinear.
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Thus far in the article we have presented and studied a model structure enabling a human to share control with a neural oscillator to play a virtual percussion instrument.
In addition, the use of the random coefficient modelling structure enabled an assessment of the relationship between the true rate of cartilage loss and initial cartilage volume – an assessment that is plagued by regression to the mean when using only the observed rates of change and initial cartilage volumes in the sample.
Using a mechanical analog parameterization, we derive a force-feedback model structure that enables a human to share control of a virtual percussion instrument with a "robotic" neural oscillator.
The structure enables modelling of the docking interactions to its ligands, for example from focal adhesion kinase, and supports structure-based drug design of inhibitors of the CAS FAK interaction.
In the hybrid model, the centralization in reporting structure enables data scientists to have career progression and growth in a ladder specialized for data scientists, to grow with and be assessed against their peers, and to facilitate and ensure that best practices will be shared across them since they are not each in their own silos.
The authors proposed a model in which G4 DNA structure enables G4 DNA binding proteins to further stabilize the telomere end by binding to G-quadruplex DNA, thereby preventing 5′ to 3′ exonucleolytic resection when the normal protein that blocks telomeric end processing is defective.
Following consideration of some different scenarios for humans and robots interacting in real and virtual environments, we described a simple model structure for enabling a human and a virtual robot, which consisted of a single Large neural oscillator, to share control of a virtual percussion instrument.
2. Evaluation of model structure to enable the identification of candidate variables for reduction analysis.
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