Table 9_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx by Zhu Yang (756364)

“…In this study, we employed bioinformatics methods to identify eight TaAkPHY genes in the Aikang58 wheat variety. …”

Table 4_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx by Zhu Yang (756364)

“…In this study, we employed bioinformatics methods to identify eight TaAkPHY genes in the Aikang58 wheat variety. …”

Table 11_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx by Zhu Yang (756364)

“…In this study, we employed bioinformatics methods to identify eight TaAkPHY genes in the Aikang58 wheat variety. …”

Table 6_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx by Zhu Yang (756364)

“…In this study, we employed bioinformatics methods to identify eight TaAkPHY genes in the Aikang58 wheat variety. …”

Image 2_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif by Zhu Yang (756364)

“…In this study, we employed bioinformatics methods to identify eight TaAkPHY genes in the Aikang58 wheat variety. …”

Table 2_Adverse drug events (ADEs) risk signal mining related to eculizumab based on the FARES database.xlsx by Xi-Feng Wang (6443420)

“…Food and Drug Administration Adverse Event Reporting System (FAERS) database. A total of 461 PTs were identified as satisfying by all four algorithms. …”

Table 1_Adverse drug events (ADEs) risk signal mining related to eculizumab based on the FARES database.docx by Xi-Feng Wang (6443420)

“…Food and Drug Administration Adverse Event Reporting System (FAERS) database. A total of 461 PTs were identified as satisfying by all four algorithms. …”

Design of stiffened panels for stress and buckling via topology optimization: data by Sheng Chu (19655605)

“…To solve the optimization problem, a semi-analytical sensitivity analysis is performed, and the optimization algorithm is outlined. Numerical investigations demonstrate and validate the proposed method.…”

Echo Peak by Rocco De Marco (14146593)

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

Structure of optimized model parameters in the high-dimensional cases. by Kevin J. Wischnewski (21354521)

“…The number and size of the clusters were determined with help of the -means clustering method. Both were set to zero if the absolute mean value of the off-diagonal elements in the correlation matrix (cf. …”

Identify different types of urban renewal implementations at streetscape scale by Xiaotong Wang (20852492)

“…Existing research primarily focuses on detecting pixel-level or object-level changes in urban physical space, often neglecting the semantic complexity inherent in urban renewal. …”

Identification of ferroptosis-related LncRNAs as potential targets for improving immunotherapy in glioblastoma by Zhaochen Wang (12176245)

“…<p>The effect of ferroptosis-related long non-coding RNAs (lncRNAs) in predicting immunotherapy response to glioblastoma (GBM) remains obscure. …”

Supplementary material for the article "Identification of relevant research topics based on pooled bibliometric data of the International Journal of Hydrogen Energy publications fo... by Boris Chigarev (6474086)

“…The study showed the feasibility of merging bibliometric records from the open platforms ScienceDirect and The Lens, which complement each other. The “Fields of Study” data of The Lens was interpreted as system keywords similar to Scopus Index Keywords. …”

Supplementary file 1_An interpretable stacking ensemble model for high-entropy alloy mechanical property prediction.docx by Songpeng Zhao (21563714)

“…Three machine learning algorithms-Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Gradient Boosting (Gradient Boosting)-were integrated into a multi-level stacking ensemble, with Support Vector Regression serving as the meta-learner. …”

Data Sheet 1_Integrated diagnostics and time series sensitivity assessment for growth monitoring of a medicinal plant (Glycyrrhiza uralensis Fisch.) based on unmanned aerial vehicl... by Ao Zhang (372387)

“…Background<p>Water and nitrogen are essential elements prone to deficiency during plant growth. Current water–fertilizer monitoring technologies are unable to meet the demands of large-scale Glycyrrhiza uralensis cultivation. …”

Data Sheet 2_Integrated diagnostics and time series sensitivity assessment for growth monitoring of a medicinal plant (Glycyrrhiza uralensis Fisch.) based on unmanned aerial vehicl... by Ao Zhang (372387)

“…Background<p>Water and nitrogen are essential elements prone to deficiency during plant growth. Current water–fertilizer monitoring technologies are unable to meet the demands of large-scale Glycyrrhiza uralensis cultivation. …”

AI Influence in the Educational Environment by Lev Radman (21381269)

“…The CSV file contains Likert-scale and categorical responses, with a separate README describing each variable and coding scheme.</p><p dir="ltr"><b>Potential reuse</b><br>Researchers can replicate or extend technology-acceptance models in emerging-economy contexts, compare student versus professional cohorts, or conduct secondary analyses on AI self-efficacy and algorithmic trust.…”

Supplementary information files for "Explainable machine learning models for predicting the ultimate bending capacity of slotted perforated cold-formed steel beams under distortion... by L Simwanda (19921680)

“…Utilizing a dataset from 432 non-linear finite element analysis simulations of CFS Lipped channels, ten ML algorithms, including four basic and six ensemble models, were evaluated. …”

Confusion_Matrix_Data.zip by Mohammad Farhad Bulbul (21003494)

“…<p dir="ltr">This research paper proposes a novel approach for human activity recognition using depth video data, focusing on improving accuracy by effectively capturing motion information and utilizing a robust classification method. Here's a breakdown of the key elements:</p><p dir="ltr"><b>. …”

Supporting files for thesis "Deep-learning-based Morphological Modelling: Case Study in Soft Robot Control, Shape Sensing and Deformation" by Yingqi Li (9151304)

“…The algorithm of deep deterministic policy gradient (DDPG) along with domain randomization and offline retraining facilitates fast initialization and stable path following, even under varying tip load, demonstrating its advantages over Jacobian model-based and supervised-learning-based control methods. …”