Sample data for <i>Neolamprologus multifasciatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Sample data for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 3 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Sample data for <i>Telmatochromis temporalis</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 4 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 1 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 2 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 5 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

Comparison data 6 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

A list of all facial muscle movements mentioned in the chimpFACS manual [5] and considered in our present study. by Aisha Mahmoud (20623732)

A list of all facial muscle movements mentioned in the catFACS manual [14] and considered in our present study. by Aisha Mahmoud (20623732)

Scope of our collection of pathogen models of metabolism. by Emma M. Glass (13102872)

“…This cladogram was created using the GraPhlAn python tool. (b) Our collection of GENREs represents 9 phyla, 17 classes, 36 orders, 94 genera, and 345 species of pathogens. …”

<i>Spherical Textures</i> and machine-learning classifications of <i>C. elegans</i> germline nuclei. by Oane Gros (20636735)

Automatic classification of germline nuclei provides quantifications of meiotic progression. by Oane Gros (20636735)

Improving the calibration of an integrated CA-What If? digital planning framework by CA What If? (21381170)

“…planning support system (PSS) sub-model to generate and analyse three representative built-up development scenarios. …”

Model fitting to neighborhood-level COVID-19 case data. by Renquan Zhang (13167533)

“…<p>(A), Simulations using model parameters estimated for the period from March 1, 2020 to December 13, 2020. …”

[ relative elevation model data visualization for Data Bloom 2024 ] by Rusmiya Aqid (22189850)

“…<p dir="ltr">This visualization takes the digital elevation model (DEM) of a portion of the Colorado River and transforms it into a relative elevation model (REM); unlike DEM, REM shows the relative height above the river and can more clearly highlight river features. …”

Dataset for the Modeling and Bibliometric Analysis of E-business in Entrepreneurship (1997–2024) by Aggie Moses Zeuse (21460466)

“…These include a summary of Main Information (PNG), a graph of the Annual Scientific Production (PNG), a Thematic Map (PNG) illustrating core research themes, and an analysis of Trend Topics (PNG). For the modeling component, a predictive analysis was conducted using Python to forecast future publication volumes. …”

Dataset for CNN-based Bayesian Calibration of TELEMAC-2D Hydraulic Model by Jose Zevallos (21379988)

“…</li><li>Files starting with <code>y_part</code> are flattened output arrays representing corresponding water depth values.</li></ul></li></ul><p dir="ltr">The <code>.npy</code> files were loaded and processed using the following approach in Python:</p><p dir="ltr"># Load the input and output numpy arrays</p><p dir="ltr">input_path = "..…”

Environmental Census: Modeling Synthetic Biology Ecological Risk with Metagenomic Enzymatic Data and High-Performance Computing by John Docter (22772100)

“…Improved predictive computational tools are necessary to assess the potential establishment risk and environmental location of these escaped engineered microorganisms, assisting their design and management. …”