Contains all the necessary tools to process audio recordings of
             various formats (e.g., WAV, WAC, MP3, ZC), filter noisy files, 
             display audio signals, detect and extract automatically acoustic
             features for further analysis such as classification.

Implements the Bi-objective Lexicographical Classification method and Performance Assessment Ratio at 10% metric for algorithm classification. Constructs matrices representing algorithm performance under multiple criteria, facilitating decision-making in algorithm selection and evaluation. Analyzes and compares algorithm performance based on various metrics to identify the most suitable algorithms for specific tasks. This package includes methods for algorithm classification and evaluation, with examples provided in the documentation. Carvalho (2019) presents a statistical evaluation of algorithmic computational experimentation with infeasible solutions <doi:10.48550/arXiv.1902.00101>. Moreira and Carvalho (2023) analyze power in preprocessing methodologies for datasets with missing values <doi:10.1080/03610918.2023.2234683>.

Provides an integrated data management solution for assets installed via the 'Biobricks.ai' platform. Streamlines the process of loading and interacting with diverse datasets in a consistent manner. A list of bricks is available at <https://status.biobricks.ai>. Documentation for 'Biobricks.ai' is available at <https://docs.biobricks.ai>.

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A toolkit for analysing biochar characterisation and batch
    adsorption experiments. Provides functions to parse structured sample
    identifiers encoding pyrolysis conditions, read raw FTIR and XRD
    instrument output, compute adsorption capacity and removal efficiency,
    fit adsorption isotherms following Langmuir (1918)
    <doi:10.1021/ja02242a004> and Sips (1948) <doi:10.1063/1.1746922>
    among other models, fit adsorption kinetics following Ho and McKay
    (1999) <doi:10.1016/S0032-9592(98)00112-5> and Chien and Clayton
    (1980) <doi:10.2136/sssaj1980.03615995004400020013x> among other
    models, fit batches of samples at once, compute van't Hoff
    thermodynamic parameters, baseline-correct and pick peaks in FTIR
    spectra, deconvolve XRD patterns into a crystallinity index, compute
    BET surface area following Brunauer, Emmett, and Teller (1938)
    <doi:10.1021/ja01269a023>, compute proximate and ultimate analysis
    summaries including directly from a thermogravimetric analysis (TGA)
    curve, compute a smoothed derivative thermogravimetric (DTG) curve
    and pick its decomposition peaks, fit non-isothermal decomposition
    kinetics from multi-heating-rate TGA data following Kissinger (1957)
    <doi:10.1021/ac60131a045>, build correlation matrices with p-values,
    and produce publication-style base-graphics figures including 600
    dpi TIFF export. Built on base R ('stats', 'graphics', 'grDevices') so it has
    no dependency on packages that require external CRAN network access
    to install.