When anyone wishes to support – or defeat – a given position, the sturdiest method is to generate data to predict its consequences.
This phenomenon, referred to as "CO2 fertilization", has been incorporated into vegetation models to predict its consequences for climate change and carbon dynamics (Thompson et al. 2004).
The reconstructed genome-scale metabolic model can be employed as an useful tool for understanding its metabolic capabilities, predicting its physiological consequences in response to various environmental and genetic changes, and developing strategies for systems metabolic engineering to improve its metabolic performance.
Further, the complexity of the legislation makes it difficult for individuals to predict its economic consequences (the Pew survey reported that only 25 percent of poll respondents said they had a very good understanding of how the law would affect them).
The article discusses the application of this chronological framework in understanding and predicting service quality and its consequences.
Numerous studies over the years have confirmed its advantages over the traditional clinic measurement, including a higher reproducibility, lack of placebo and white coat effect, and, most importantly, its superiority in predicting adverse consequences of hypertension.
According to some authors (Swanson et al.; 1986; Canuti et al., 1998; Ermini and Casagli, 2003; Korup, 2004; Dal Sasso et al., 2014), landslide dam behavior can be forecasted and its consequences predicted through geomorphological indexes.
While the bearing stiffness for both mechanisms has been extensively predicted via analysis and its consequences have been observed in experiments, its direct measurement poses several challenges and is not found in the literature.
This cut off point was chosen as 5 kg weight retention represents a substantial shift in weight, and data analyses suggest this cut off point predicts later obesity and its consequences [ 70, 71].
