Supplementary Material for: Investigating the value of umbilical artery eucapnic pH as a biomarker for adverse neonatal outcomes: A systematic review by figshare admin karger (2628495)

“…However, conventional potential of hydrogen (pH) and base deficit (BD) methods have limitations in neonates. …”

Turkish_native_goat_genotypes by Yalçın YAMAN (20209833)

“…</p><p dir="ltr">Nine heterogeneous machine-learning models—including penalised linear methods, gradient-boosting algorithms, and interaction-sensitive tree ensembles—were applied to examine genotype–phenotype relationships. …”

SBDI Sativa curated 16S GTDB database by Daniel Lundin (11036598)

“…Subsequently, branch lengths for the tree are optimized based on the original alignment of 16S sequences using IQTREE [Nguyen et al. 2015] with a GTR+F+I+G4 model. …”

Imaging platform. by Jiajun Liu (692586)

“…This study proposes a lightweight semantic segmentation model named KAN-GLNet (Kolmogorov–Arnold Network with Global–Local Feature Modulation), based on an enhanced PointNet++ architecture and integrated with an optimized Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, to achieve high-precision segmentation and automatic counting of canola siliques. …”

KAN-GLNet network model. by Jiajun Liu (692586)

“…This study proposes a lightweight semantic segmentation model named KAN-GLNet (Kolmogorov–Arnold Network with Global–Local Feature Modulation), based on an enhanced PointNet++ architecture and integrated with an optimized Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, to achieve high-precision segmentation and automatic counting of canola siliques. …”

Reconstructed canola point cloud samples. by Jiajun Liu (692586)

“…This study proposes a lightweight semantic segmentation model named KAN-GLNet (Kolmogorov–Arnold Network with Global–Local Feature Modulation), based on an enhanced PointNet++ architecture and integrated with an optimized Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, to achieve high-precision segmentation and automatic counting of canola siliques. …”

Training loss and accuracy curves of KAN-GLNet. by Jiajun Liu (692586)

“…This study proposes a lightweight semantic segmentation model named KAN-GLNet (Kolmogorov–Arnold Network with Global–Local Feature Modulation), based on an enhanced PointNet++ architecture and integrated with an optimized Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, to achieve high-precision segmentation and automatic counting of canola siliques. …”

Hardware and software specifications. by Jiajun Liu (692586)

“…This study proposes a lightweight semantic segmentation model named KAN-GLNet (Kolmogorov–Arnold Network with Global–Local Feature Modulation), based on an enhanced PointNet++ architecture and integrated with an optimized Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, to achieve high-precision segmentation and automatic counting of canola siliques. …”

Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples by Derek Lam (11944213)

“…This approach offers a valuable complement to current monitoring strategies and supports broader efforts in environmental health protection. …”

Table 1_Associations of lung function impairment and biological aging with mortality and cardiovascular disease incidence: findings from UK biobank participants.docx by Jiali Chen (5696)

“…PhenoAgeAccel was calculated using algorithms based on clinical biomarkers, and frailty was evaluated according to five established criteria. …”

Pipeline for extraction of parameters for ML and DL. by John Kruper (18809386)

“…<p>(A) Diffusion MRI (dMRI) data from the HBN-POD2 sample is used as input to the algorithm. (B) In the initial step, whole-brain tractography is conducted (C) Major white matter pathways are identified based on the trajectory of the streamlines. …”

Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach by Mar Roca (20435036)

“…We developed a satellite-based workflow to complement <i>in situ</i> seagrass monitoring efforts in the Balearic Islands (Western Mediterranean), reducing field expenses while covering regional spatial scales. …”

Table 1_Artificial intelligence in nursing: an integrative review of clinical and operational impacts.pdf by Salwa Hassanein (20843468)

“…Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …”

Table 2_Artificial intelligence in nursing: an integrative review of clinical and operational impacts.pdf by Salwa Hassanein (20843468)

“…Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …”

Table 3_Artificial intelligence in nursing: an integrative review of clinical and operational impacts.pdf by Salwa Hassanein (20843468)

“…Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …”

Table 1_An interpretable machine learning model for early prediction of Escherichia coli infection in ICU patients.docx by Shu Yang (381226)

“…E. coli infection was identified based on microbiological results and diagnostic codes. Missing data were imputed using the missForest algorithm. …”

Vaccines, Public Health, and the Politics of Immunity: Safety, Debate, and Global Perspectives by Minehli Arakelians Gheshlagh (21983870)

“…</li></ul><p dir="ltr">These visuals complement textual analysis, providing intuitive understanding of complex epidemiological, sociopolitical, and ethical dynamics.…”

Canopy Height Monitoring Data and Model of Hainan Tropical Rainforest National Park by Zixuan Qiu (14013837)

“…</p><p dir="ltr">The data in the folder (Code) includes the training code and prediction code for four machine learning algorithms (BP, CNN, GBDT, RF).…”

Data Sheet 1_Using reinforcement learning in genome assembly: in-depth analysis of a Q-learning assembler.pdf by Kleber Padovani (10198918)

“…We expand upon the previous approach found in the literature to solve this problem by carefully exploring the learning aspects of the proposed intelligent agent, which uses the Q-learning algorithm. We improved the reward system and optimized the exploration of the state space based on pruning and in collaboration with evolutionary computing (>300% improvement). …”

archive.zip by Tasneem Fatima (21976946)

“…The dataset extracted from the archive consists of a large number of labeled images of wheat grains, organized in directories such as <code>wheat_for_cnn</code>, with filenames reflecting numerical categories (e.g., <code>10_1.jpg</code>, <code>100_5.jpg</code>, <code>200_0003.jpg</code>). …”