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By aligning data control with data provenance, it would respect a form of data ownership rights.
Other systems enhancing the validity of data are: control of data entry possibilities, repeated reporting of data, where inconsistencies are easier spotted or built in systematic data control with reporting of discrepancies.
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To interpret such data, controls with the disease under study taking an alternative standard regimen (for example, MTX in RA studies) and healthy controls are needed.
However, the likelihood is small since the trials were fully investigator-initiated and data controlled with transparent disclosure of potential conflicts of interest by the respective authors [ 32, 33].
Even a lot of ostensible "lefties" seem to be a bit too complacent in seeing the only problem with centralized data control being when government has it.
The data were structured to distinguish studies with aggregate data (controlled and non-controlled trials) from studies with individual data.
Additional data files and statistical comments: Can the authors provide transcriptional profiling data comparing control with REST KO brains discussed in the manuscript?
The program fits the data for control with very small deviations (χ2 = 0.18).
It also builds relationships between highly structured pieces of data, something that can't easily be done with distributed data controlled by different entities.
This paper addresses the control synthesis problem of networked linear sampled-data control systems (NLSCSs) with band-limited channels.
Moreover, with this approach, it is possible to deal with sampled-data control systems.
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