Sentence examples for sufficiently heavy from inspiring English sources

The course load is sufficiently heavy that students, particularly during the first year, should not plan a very heavy work schedule.

JK Rowling might have thought she was done with Harry Potter after seven books, none of them pamphlets, but pressure was sufficiently heavy for her to agree to script a series of spin-off flicks.

An S-shaped extinction curve occurs for a rich spray flame under the (SPB c condition, with a sufficiently heavy liquid loading and a sufficiently large water-core size.

The latest adaptation of Grahame's children's classic comes on Sunday night from "Masterpiece Theater," and while the production is ultimately too jaunty to be considered 100percentt safe for someone over 10, it makes a sufficiently heavy investment in the particularities of Grahame's class consciousness.

Air leak in a pneumatic tube conveyor may be negligible for sufficiently heavy parts such as bolts and nuts.

For such samples, classical maximum likelihood methods yield inappropriate distributions for estimating the occurrence probability of exceptional losses because the resulting distributions are not sufficiently heavy tailed.

But these patterns are reversed for traits with sufficiently heavy-tailed initial distributions (e.g., a medical or behavioral disorder for which there is no strongly expressed risk group or a relatively equally distributed ability with significant genetic influence).

However, compared to the body size of bumblebees (workers 40 600 mg, queens up to 850 mg) current transmitters are still sufficiently large and heavy (200 mg) that they have been shown to affect foraging behavior, are likely to affect flight performance and/ or energetics and so might have fitness consequences for bumblebees.

It is unlikely to find sufficiently large "mutually exclusive groups of heavy analgesic use" will exist in the database.

However, given a sufficiently large penalty parameter, the Lasso will also impose heavy shrinkage on large coefficients due to the absence of tails (constant rate of penalization), leading to biased coefficient estimates (see Fig. 2).

The heavy emphasis today on transfer learning reminds us that few companies have sufficiently large datasets to build robust models, let alone balanced models.