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The intrinsic uncertainty due to finite data length, colored noise, non-stationary excitations, model order reduction or other operational influences needs to be considered for robust and automated structural health monitoring methods.
Although a changing environment will likely affect many species in temperate forests, the direction and strength of those influences needs to be modeled on a species by species basis as we show that interactions are critical to interpreting demographic patterns, and by extension population dynamics.
Thus, how the linear regression model they used accounts for these influences needs to be explained.
However, whether such regulation is directed towards positive and/or negative influences needs to be investigated in detail separately for both compatible and incompatible interaction.
It can be inferred from the findings of this study that a broad approach to prevention and management of aggression — one that addresses socio-demographic and interpersonal as well as situational and contextual influences — needs to be adopted.
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Knowledge of the factors influencing need perceptions is important for effective planning and implementation of oral health care services in Tanzania.
These environmental influences need to be further investigated.
The different influences need to be quantified for the analysis of monitoring measurements.
These influences need to be carefully considered when designing management approaches.
In order to develop such circuits, a wide variety of influences need to be considered and also compensated if necessary.
Such influences need to be considered when selecting a preference testing method in an animal welfare context.
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CEO of Professional Science Editing for Scientists @ prosciediting.com