Table 1_Establishment of reliable identification algorithms for acute heart failure or acute exacerbation of chronic heart failure using clinical data from a medical information da... by Ryusuke Inoue (4617505)

“…The highest sensitivity at 89.53% was observed for Algorithm 9. This algorithm was constructed using a combination of disease codes entered in electronic medical records, DPC, or health insurance claims data, abnormal BNP values in the moderate or high range (≥100 pg/mL), and medications for acute heart failure. …”

The data of LazyAct. by Hongjie Zhang (136127)

MAGPIE: A Machine Learning Approach to Decipher Protein–Protein Interactions in Human Plasma by Emily Hashimoto-Roth (9564009)

Subjects:

MAGPIE: A Machine Learning Approach to Decipher Protein–Protein Interactions in Human Plasma by Emily Hashimoto-Roth (9564009)

Subjects:

Comparison of planning results. by Tianhe Sun (21145341)

“…The model is solved iteratively using the column generation algorithm and strong duality theory. Case studies on a Northeast China power grid demonstrate that, by optimally configuring generation and storage capacity guided by flexibility and other indicators, the proposed method reduces curtailment/load shedding costs and system flexibility insufficiency probability by 45% and 4.3% respectively. …”

Economic parameters of equipment to be built. by Tianhe Sun (21145341)

“…The model is solved iteratively using the column generation algorithm and strong duality theory. Case studies on a Northeast China power grid demonstrate that, by optimally configuring generation and storage capacity guided by flexibility and other indicators, the proposed method reduces curtailment/load shedding costs and system flexibility insufficiency probability by 45% and 4.3% respectively. …”

Results of coordinated ESS planning. by Tianhe Sun (21145341)

“…The model is solved iteratively using the column generation algorithm and strong duality theory. Case studies on a Northeast China power grid demonstrate that, by optimally configuring generation and storage capacity guided by flexibility and other indicators, the proposed method reduces curtailment/load shedding costs and system flexibility insufficiency probability by 45% and 4.3% respectively. …”

Typical daily load curves. by Tianhe Sun (21145341)

“…The model is solved iteratively using the column generation algorithm and strong duality theory. Case studies on a Northeast China power grid demonstrate that, by optimally configuring generation and storage capacity guided by flexibility and other indicators, the proposed method reduces curtailment/load shedding costs and system flexibility insufficiency probability by 45% and 4.3% respectively. …”

Typical daily wind power production curves. by Tianhe Sun (21145341)

“…The model is solved iteratively using the column generation algorithm and strong duality theory. Case studies on a Northeast China power grid demonstrate that, by optimally configuring generation and storage capacity guided by flexibility and other indicators, the proposed method reduces curtailment/load shedding costs and system flexibility insufficiency probability by 45% and 4.3% respectively. …”

Typical daily solar power production curves. by Tianhe Sun (21145341)

“…The model is solved iteratively using the column generation algorithm and strong duality theory. Case studies on a Northeast China power grid demonstrate that, by optimally configuring generation and storage capacity guided by flexibility and other indicators, the proposed method reduces curtailment/load shedding costs and system flexibility insufficiency probability by 45% and 4.3% respectively. …”

Data for "Quantum-enhanced simulated annealing using Rydberg atoms" by Seokho Jeong (20596511)

Consensus network inferred on the healthy individuals (n = 102 samples, p = 151 species) from the liver cirrhosis dataset, followed by CORE-clustering algorithm to identify the mic... by Camille Champion (15238934)

DataSheet1_Average BER evaluation of the uplink OFDM-based NOMA system under SIC and channel estimation error.pdf by Akinbode A. Olawole (20137446)

Code and data for Lambert and Ellner, "SDM meets eDNA: optimal sampling of environmental DNA to estimate species-environment relationships in stream networks", Ecography (2025) by Timothy Lambert (16890087)

“…The code includes: (1) an iterative generalized least squares solution method for estimating model parameters, (2) a genetic algorithm for finding D-optimal sampling designs (i.e., the positioning of samples on a stream network that most accurately estimates species-environment relationships), and (3) generalized additive models for estimating the dependence of estimation accuracy on a stream network's topological and hydrologic properties.…”

Table 1_In Vitro biomechanical study of meniscal properties in patients with severe knee osteoarthritis.xlsx by Yuqi Liu (501183)

“…Quantifying the biomechanical properties of the meniscus is essential for understanding its role in knee joint function and pathology.</p>Methods<p>This study aimed to determine the biomechanical properties of the meniscus in patients with severe KOA using experimental mechanical testing and an inverse finite element analysis (iFEA) model. …”

Table 2_In Vitro biomechanical study of meniscal properties in patients with severe knee osteoarthritis.xlsx by Yuqi Liu (501183)

“…Quantifying the biomechanical properties of the meniscus is essential for understanding its role in knee joint function and pathology.</p>Methods<p>This study aimed to determine the biomechanical properties of the meniscus in patients with severe KOA using experimental mechanical testing and an inverse finite element analysis (iFEA) model. …”

Accuracy of different electrical and optical neural network on Caltech and ETH-80 data sets. by Reyhane Ahmadi (14857363)

Research data for paper: Efficient Event-based Delay Learning in Spiking Neural Networks by Balázs Mészáros (16890225)

“…</li></ol><p dir="ltr">The data was generated and analysed with the code available on GitHub at https://github.com/mbalazs98/deventprop/</p><p dir="ltr">results.py contains all test accuracies shown in figures 4-7. …”

Cellular data inputs and outputs. by Hector Torres (11708207)

Robot polishing experimental platform. by Ma Haohao (22177538)

“…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”