Indian Institute of Science Bangalore: What does a university look like? by Simon Porter (1364613)

“…Fields of Research with greater than 50% of their output not represented in the network include: Law and Legal Studies (58.06%), Mathematical Sciences (59.19%), and Philosophy and Religious Studies (67.86%)</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…”

Georgia Institute of Technology: What does a university look like? by Simon Porter (1364613)

“…Fields of Research with greater than 50% of their output not represented in the network include: Language, Communication and Culture (51.05%), Economics (51.16%), Philosophy and Religious Studies (54.95%), and History, Heritage and Archaeology (67.09%)</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…”

State University of Campinas: What does a university look like? by Simon Porter (1364613)

“…Fields of Research with greater than 50% of their output not represented in the network include: History, Heritage and Archaeology (59.36%), Language, Communication and Culture (68.41%), Creative Arts and Writing (72.85%), and Philosophy and Religious Studies (77.65%)</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…”

University College London: What does a university look like? by Simon Porter (1364613)

“…Fields of Research with greater than 50% of their output not represented in the network include: Law and Legal Studies (58.72%), History, Heritage and Archaeology (60.62%), Creative Arts and Writing (61.53%), Language, Communication and Culture (62.31%), and Philosophy and Religious Studies (70.32%)</p> <p><strong>Methodology:</strong></p> <p>Graph layout: Batchlayout [1]</p> <p>Clustering: Leiden Algorithm [2]</p> <p>3d Layout: Blender [3]</p> <p>Data: Dimensions [4]</p>…”

archive.zip by Tasneem Fatima (21976946)

“…The structured dataset suggests an intent to train and evaluate deep learning algorithms on real-world image data for practical deployment in grain procurement or quality monitoring systems.…”

Data Sheet 1_Extraction of exact symbolic stationary probability formulas for Markov chains with finite space with application to production lines. Part I: description of methodolo... by Konstantinos S. Boulas (21709982)

“…</p>Results<p>A general algorithm that commences with the Markov chain transition matrix as an input element and forms the state transition diagram. …”

Video 1_Extraction of exact symbolic stationary probability formulas for Markov chains with finite space with application to production lines. Part I: description of methodology.mp... by Konstantinos S. Boulas (21709982)

“…</p>Results<p>A general algorithm that commences with the Markov chain transition matrix as an input element and forms the state transition diagram. …”

DMP4P: Tailoring Daily Meal Plans to Personalized Nutrient Requirements for Chronic Disease Prevention by LEI ZHAO (22266391)

“…</p><p dir="ltr">NHANES original data is uploaded to NHANES_raw_data folder for replay the data generation process only so it is not mandatory for usage.…”

<b>Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies</b> by Marina Diachenko (19739092)

“…<p dir="ltr">The <i>zip</i> file contains the code and data for the analyses/figures described in the paper titled "<b>Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies</b>" published in September in 2024 in Imaging Neuroscience.…”

Supervised Classification of Burned Areas Using Spectral Reflectance and Machine Learning by Baptista Boanha (22424668)

“…<p dir="ltr">This dataset and code package presents a modular framework for supervised classification of burned and unburned land surfaces using satellite-derived spectral reflectance. …”

<b>Force-Position-Speed Planning and Roughness rediction for Robotic Polishing</b> by Ma Haohao (19780875)

“…The improved dung beetle optimization algorithm, back propagation neural network, finite element analysis and response surface method provide a strong guarantee for the selection of robotic polishing process parameters. …”

Non-Conjugate Variational Bayes for Pseudo-Likelihood Mixed Effect Models by Cristian Castiglione (21656583)

“…<p>We propose a unified, yet simple to code, non-conjugate variational Bayes algorithm for posterior approximation of generic Bayesian generalized mixed effect models. …”

High-Dimensional Variable Clustering based on Maxima of a Weakly Dependent Random Process by Alexis Boulin (20659921)

“…A data-driven selection method for the tuning parameter is also proposed. …”

Data Sheet 2_Characterization of the salivary microbiome in healthy individuals under fatigue status.docx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Table 3_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Data Sheet 1_Characterization of the salivary microbiome in healthy individuals under fatigue status.docx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Table 5_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Table 4_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Table 2_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”

Table 1_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

“…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. …”