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Further epidemiological research to assess the actual prevalence of such pathologies is urgently needed to inform the design of adequate control measures, especially given the impact of mastitis on HIV vertical transmission.
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It is, however, impossible to be certain of adequate control for confounding factors with observational designs.
Poor design and lack of adequate controls also plague even the benchmark studies in the Qigong research field.
The conclusions that can be drawn from these studies are limited by the lack of adequate control groups, and post-treatment complications are likely to be underestimated due to the retrospective design.
Most of the available studies have important limitations, mainly related to small sample sizes, heterogeneity of the patient populations, retrospective study designs and lack of adequate controls (healthy individuals or patients with sepsis but no signs of encephalopathy).
One crucial aspect of clinical trials in palliative care research is the design of an adequate control group condition.
Another important methodological issue is related to the design of an adequate control group.
Despite our meticulous study design, including adequate control of confounding factors, bias may remain because of possible unmeasured or unknown confounders.
The present work deals with the use of a Neuro-Fuzzy Adaptive Inference System (ANFIS) controller designed to ensure adequate control of speed and exhaust temperature for a Heavy Duty Gas Turbine (HDGT) based on Rowen Model equations.
The importance of an appropriate study design that includes adequate control animals cannot be overemphasized when dealing with an infection that is present in many healthy animals.
However, this transition requires detailed knowledge and process understanding of all consecutive unit operations in a continuous manufacturing line to design adequate control strategies.
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