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Discover LudwigThe phrase "a sparse bit" is correct and usable in written English.
It can be used to describe a small or minimal amount of something, often in contexts where something is lacking or insufficient.
Example: "The report contained a sparse bit of information on the project's progress, leaving many questions unanswered."
Alternatives: "a small amount" or "a minimal piece".
Exact(1)
However, since we need n fixed bits for each motif to store its bit vector, this is not efficient if there are many sequences, and if a motif occurs only in a small number of sequences, which leads to a sparse bit vector.
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Try shaping yours along your natural arch by plucking, waxing, or threading, then fill in any sparse bits with a brow powder or eyeshadow - up to two shades darker for blonde and light brown eyebrows, auburn or chestnut brown for red eyebrows, and two shades lighter for dark brown and black eyebrows.
Conway and Bromage applied sparse bit array structures to store an implicit, immutable graph representation [ 9].
His preferred sounds are cloudlike, sustained synthesizer chords or sparse bits of piano that well up gradually, then ripple off into the distance.
First proposed 6 years ago, this notion maintains that tiny galaxies, not massive ones, should arise last because it takes gravity so long to assemble the sparse bits of matter in voids.
Sparse bits of information about his personal life can only be gathered from the autobiographies of his contemporaries and their published correspondences (e.g., Quine 1985; Creath 1990) or his obituaries (e.g., Carter 2000; Elgin 1999 (Other Internet Resources), 2000a, 2000b; Elgin et al. 1999; Mitchell 1999; Scheffler 2001; Scholz 2005; Schwartz 1999).
The optimization model for reconstruction of a sparse signal from 1-bit measurements in [3] is min |x|_{1} quad text{s.t.} quad YPhi x ge 0 quad text{and} quad |x|_{2}=1, (4).
These differences are unlikely to be due to collisions as the count vector as implemented in RDKit is a sparse vector of length 4294967296 bits.
The problem of reconstructing a sparse signal from its 1-bit measurements is generally non-convex, and therefore it is a challenge to develop an algorithm that can find a desired solution.
In particular, we first adapt the parity-check matrix according to the bit reliability so that the unreliable bits correspond to a sparse submatrix.
Firstly, the parity-check matrix of polar codes is adjusted such that one of its submatrices corresponding to less reliable bits is in a sparse nature.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com