Sentence examples for minimize the lack from inspiring English sources

In this section, we evaluate how much the proposed sampling approaches can minimize the lack of data and deliver more informative content.

Its main overall goal is to minimize the lack of engineers, especially in the field of electrical engineering, which is currently existent.

To minimize the lack of generalizability of the results of explanatory RCTs [ 10], some have proposed conducting large pragmatic or practical RCTs with wider selection criteria and more heterogeneous patients [ 11, 12].

MIC50 and NOEC values were aggregated within cogeneric species by using the arithmetic mean to minimize the lack of independence between individual observations [see Supplemental Material, Section 1 and Figure S1 (http://dx.doi.org/10.1289/ehp.1104650)].

Overestimation was greatest for whole grains even though we attempted to minimize the lack of available conversion and processing factors within FAO food balance sheets by removing the major categories of rice, wheat, and other low-fiber grains from the FAO grouping.

Often those phrases seem deliberately chosen to try to soften or minimize the significance of the lack of legal status.

In order to minimize the effects of the lack of knowledge on the experimental study factors, a training session was conducted with all the participants about basic concepts related to SPL and use cases, as well as about the use case template structures used in the experiment.

Therefore, the suggestion of using play and games for the improvement of cognitive flexibility, planning ability, and flexible use of language among children and adolescents with autism can minimize the negative impact that the lack of behavioral repertoire presented by individuals with autism for accomplishing daily tasks at home and school.

To minimize the bias resulting from the lack of randomization, a propensity score will be used.

To minimize the bias resulting from the lack of randomization, we will use a propensity score.

To overcome this problem, gene predictors based on more complex models have been developed that try to minimize the limitations imposed by the lack of predetermined models and incorporate codon bias and start/stop codon patterns of known genes of available whole genomes.