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To ensure that chemotherapy had no inadvertent effect on our ability to distinguish between locoregional disease and liver metastases, we excluded patients who had chemotherapy within 3 months of sample collection, and utilized the same models to compare these two groups.
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A subsequent study utilizing the same model has shown that reductions in fibrosis with 4 weeks of treatment with serelaxin were associated with increases in MMP-13, decreases in TIMP-2, and impaired TGF-β signaling compared with vehicle [ 78].
In the imputation stage, we also utilized the same GMM-model as in our previous study; a 5-component GMM trained on a random 1000 utterance subset of the clean speech training set with a time context of three consecutive Mel-spectral feature frames.
Model 2 utilized the same predictors as Model 1, with the following 3 additional binary variables: CRP ≥ 200 mg/L or extent of consolidation on chest X-ray ≥ 2/3, use of mechanical ventilator/vasopressors, and presence of cancer.
For analyses of fertility treatment, parity and breast feeding, we utilized the same covariates in models except for mother's age at child's birth and mother's tobacco smoking, because they did not change point estimates by more than 10%%.
This barrier fracture length sensitivity analysis was carried out only with the homogenous reservoir case and since this optimum length gave the maximum reservoir performance, we utilized the same length when modeling the other numerical cases.
For the in vitro experiment, we utilized the same 3D culture model to investigate the proteolytic mechanism related to capillary formation.
The perturbed models utilized the same ventricular geometries but slightly adjusted Purkinje structural models; these models were created by applying the texture-mapping procedure with the texture images at a slight offset from the original models.
Both analyses utilized the same covariates as all other models (when controlling for youth reported events, we controlled for youth reported dependent and independent life events, respectively).
This model utilized the same Monte Carlo methodology as that described above and used a random number generator to determine the various journeys made the HCWs (e.g. from Patient A to Patient D; from Patient B to Patient C; etc).
"It was modeled from start to the completion of the piece by me and I utilized the same methods I use in creating any work.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com