Supplementary file 2_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm identified globally optimal combinations within 0.2 s for all species, regardless of problem size. …”

Supplementary file 6_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm identified globally optimal combinations within 0.2 s for all species, regardless of problem size. …”

Supplementary file 1_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm identified globally optimal combinations within 0.2 s for all species, regardless of problem size. …”

Supplementary file 4_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm identified globally optimal combinations within 0.2 s for all species, regardless of problem size. …”

Supplementary file 5_Optimising the selection of welfare indicators in farm animals.docx by Jon Day (19128586)

“…The enhanced algorithm identified globally optimal combinations within 0.2 s for all species, regardless of problem size. …”

Data for revision version by Santanu Saha (18277927)

“…This study enhances the well-established min-max method based interactive fuzzy bi-objective optimization algorithm by incorporating the absolute difference function along with the trade-off ratio based autonomized optimization approach. …”

Mechanomics Code - JVT by Carlo Vittorio Cannistraci (5854046)

“…The functions were tested respectively in: MATLAB 2018a or youger, Python 3.9.4, R 4.0.3.…”

A. Explanation of the data points used by EpiFusion; B. the key parameters of the EpiFusion particle filter. by Ciara Judge (20161514)

“…Beta must vary over time and can either be fit using (i) a random walk within the particle filter, (ii) linear splines within the particle filter, (iii) MCMC fitting in epochs by fixing or fitting change times and interval values, or (iv) MCMC fitting the parameters of a logistic function which defines beta over time; C. …”

Echo Peak by Rocco De Marco (14146593)

“…</p><p dir="ltr">For classification, the algorithm iteratively processes the audio in overlapping time windows. …”

High-Dimensional Covariance Regression with Application to Co-Expression QTL Detection by Rakheon Kim (21656910)

“…In this article, we present a new sparse covariance regression framework that models the covariance matrix as a function of subject-level covariates. In the context of co-expression quantitative trait locus (QTL) studies, our method can be used to determine if and how gene co-expressions vary with genetic variations. …”

Examples of model selection methods for the PHMM. by Tianshu Li (1527088)

“…<i>Left panel:</i> LL on validation sets as a function of <i>m</i>. The black curves show the average log-likelihoods (across initial guesses) of all models whose algorithm converged to a solution during training (vertical bars display one standard deviation across 100 different initial guesses for the parameter values). …”

DataSheet1_Application of a risk score model based on glycosylation-related genes in the prognosis and treatment of patients with low-grade glioma.docx by Binbin Zou (11358315)

“…However, the biological function of glycosylation-related genes in LGG remains largely unexplored. …”

Instances and detailed results of the paper <i>Stochastic scheduling on a restricted batching machine</i> by Yasmin Rios Solis (3909469)

“…This function is particularly relevant in manufacturing environments where these machines are present, as meeting due dates is crucial on these bottleneck machines. …”

Finding the most diverse subset of proteins - Genome Informatics 2024 by Amanda Clare (98717)

“…We implemented a grey-box local search algorithm using the structure of the optimised function to guide the search. …”

<b>Fig. 6 |</b> <b>Autonomous microrobot navigation upstream in a flow environment.</b> by Mahmoud Medany (20766911)

“…</b> Schematic of the reward function adjustment to promote microrobot navigation close to the wall, minimizing drag. …”

Seamless integration of legacy robotic systems into a self-driving laboratory via NIMO: a case study on liquid handler automation by Ryo Tamura (1957942)

“…We developed NIMO (formerly NIMS-OS, NIMS Orchestration System), an OS explicitly designed to integrate multiple artificial intelligence (AI) algorithms with diverse exploratory objectives. NIMO provides a framework for integrating AI into robotic experimental systems that are controlled by other OS platforms based on both Python and non-Python languages. …”

Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

“…The analysis was conducted in a Jupyter Notebook environment, using Python and libraries such as Scikit-learn and Pandas. …”

Tree-Enhanced Latent Space Models for Two-Mode Networks by Dan Pu (3714616)

“…In this framework, each node is characterized by a latent embedding vector, reparameterized as the aggregate of intermediate vectors corresponding to nodes within the tree structure. By optimizing the log-likelihood function augmented with a tree-based regularization term, the proposed model facilitates the simultaneous estimation of embedding vectors and the derivation of interpretable community structures. …”

spine_quantification_all_images.xlsx by Ana M Jiménez-García (20396996)

“…It includes a number of neuropsychiatric disturbances including impaired motor activity and coordination, intellectual and cognitive function.</p><p dir="ltr">Results: In the present study, we used a rat early-stage HE model by triple portal vein ligation for 50 days To gain a better understanding of the effect of HE on the brain, artificial intelligence algorithms based on convolutional neuronal networks were implemented for the unbiased quantification of the brain images which were stained by Golgi-Cox immunohistochemistry. …”

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. Microbial community phenotypes and potential functional pathways were predicted using BugBase and PICRUSt2, respectively.…”