Sentence examples for autonomous measures from inspiring English sources

Exact(1)

Classifying subjects as "responders" and "non-responders", or classifying single trials as "successful" or "not successful" conditioning based on autonomous measures has proven extremely useful, to exclude erroneous trials or subjects from further analysis (e.g. [28], [51]).

Similar(59)

Even if the focus is on co-operative systems, autonomous system measures have been kept to provide a comparison between all measures during the further process.

Instead, the EU will try to give Ukraine the benefits of the deal unilaterally, in the form of "autonomous trade measures".

We also revealed that the autonomous adaptation measures implemented by stakeholders to mitigate impacts of climatic change often contradict adaptive management planned and implemented by environmental authorities.

To investigate whether circadian oscillation of Nampt mRNA is cell-autonomous, we measured Nampt mRNA levels in WT and AMPKα1/α2−/− mefs after forskolin synchronization.

Over the past decades and even centuries, humans have used various techniques to measure oceans, from buckets that were dragged through the ocean waters to collect samples, to modern autonomous devices that measure the oceans day and night throughout the year and report data by satellite.

A range of instruments was used – including autonomous gliders that measure temperature and water turbulence, and are controlled remotely by someone sitting comfortably onshore – as well as "snowcatchers".

And although in 2012 the Pentagon adopted a 10-year plan not to use fully autonomous AI, the measure allows senior officials to overrule it and does not affect research and development.

Paul Benson, for example, has argued that being autonomous implies a measure of self-worth in that we must be in a position to trust our decision-making capacities to put ourselves in a position of responsibility (Benson 1994; cf. also Grovier 1993, Lehrer 1997, and Westlund 2014).

The better consistency of responses to perturbations, in the real neurons as well as in the model, suggests a paradigm shift away from measuring autonomous dynamics alone towards protocols of controlled perturbations.

In the present study we measured Autonomous Motivation (AM) and Controlled Motivation (CM) as described by SDT (Vansteenkiste et al. 2005; Grolnick and Ryan 1987).

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