Sentence examples for removed classes from inspiring English sources

Since the removed classes R are considered to contain the individuals with infections the parameters a and a P characterize the identification rate of potential cases; it is then rather related to the health policy than to the disease itself (e.g. a is not the mortality rate!).

These are called the susceptible, exposed, infectious and removed classes.

The removed classes both visually and functionally contain more than at least two separate classes, i.e., passenger/cargo ship involve both passenger vessels and general cargo vessels.

The removed classes are, namely (1) general cargo (it is significantly confusing with the container ship and ro-ro cargo), (2) cargo/containership, (3) research/survey vessel, (4) cement carrier, (5) multi purpose offshore vessel, (6) passenger/cargo ship, and (7) cable layer.

(vi) The rate of removal of infectives in class I to the removed class R is proportional to the number of infectives in class I, that is aI t), where a is a positive number.

We assume that the susceptible individuals are not yet infected with HIV but can be infected through sexual contacts with infectives or become aware of the danger of the disease and transfer to the removed class.

(iii) The designer can modify, add or remove classes, attributes or methods in the binary relation and activate step (i) until he obtains a proper class hierarchy or an optimal inheritance graph.

We further explored the signal in sequences by removing classes of rapidly and slowly evolving sites using the slow fast approach of Brinkmann and Philippe (1999) as modified in Sperling et al. (2009).

Since too-rapidly and too-slowly evolving sites may affect phylogenetic analysis [ 64], another dataset (moderate-rate dataset) was constructed by removing classes of rapidly and slowly evolving sites using the slow-fast approach [ 64, 86], in which sites were partitioned into quartiles and only those from the two internal ones were accepted.

For each iteration, the columns of each of 7 microarray data matrices were randomly shuffled to remove class memberships.

We also observed that the EA algorithm was quite effective in removing class III (chimerical) edges for the two 150-bp datasets, and satisfactory in removing the class III edges for the two 36-bp datasets.