Universally unique identifiers ('UUIDs') can be sub-optimal for many
  uses-cases because they are not the most character efficient way of encoding
  128 bits of randomness; v1/v2 versions are impractical in many environments,
  as they require access to a unique, stable MAC address; v3/v5 versions require
  a unique seed and produce randomly distributed IDs, which can cause fragmentation
  in many data structures; v4 provides no other information than randomness which
  can cause fragmentation in many data structures. Providing an alternative, 'ULIDs'
  (<https://github.com/ulid/spec>) have 128-bit compatibility with 'UUID', 1.21e+24
  unique 'ULIDs' per millisecond, support standard (text) sorting, canonically encoded
  as a 26 character string, as opposed to the 36 character 'UUID', use 'base32'
  encoding for better efficiency and readability (5 bits per character), are case
  insensitive, have no special characters (i.e. are 'URL' safe) and have a monotonic
  sort order (correctly detects and handles the same millisecond).

A tool to define the rare biosphere. 'ulrb' solves the problem of the 
    definition of rarity by replacing arbitrary thresholds with an unsupervised machine 
    learning algorithm (partitioning around medoids, or k-medoids). This algorithm 
    works for any type of microbiome data, provided there is an abundance table.
    This method also works for non-microbiome data.

A generic reference Bayesian analysis of unidimensional mixture distributions obtained by a location-scale parameterisation of the model is implemented. The including functions simulate and summarize posterior samples for location-scale mixture models using a weakly informative prior. There is no need to define priors for scale-location parameters except two hyperparameters in which are associated with a Dirichlet prior for weights and a simplex.

Plots traced ultrasound tongue imaging data according to a polar coordinate system. 
    There is currently support for plotting means and standard deviations of each category's trace;
    Smoothing Splines Analysis of Variance (SSANOVA) could be implemented as well.  The origin of the 
    polar coordinates may be defined manually or automatically determined based on different 
    algorithms.
    Points for each category can be split into two groups (anterior and posterior) at the point of 
    maximum curvature of each trace. User can specify rays to intersect various parts of the 
    tongue; intersections along these rays serve as input for a pairwise t-test to measure 
    significant contrasts between segments. 
    Currently 'ultrapolaRplot' supports ultrasound tongue imaging trace data from 'UltraTrace' 
    (<https://github.com/SwatPhonLab/UltraTrace>). 'UltraTrace' is capable of importing data from 
    Articulate Instruments AAA.
    'read_textgrid.R' is required for opening TextGrids to determine category and alignment
    information of ultrasound traces.