Table 1_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx حسب Hanlin Yu (17776399)

"…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …"

Table 4_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx حسب Hanlin Yu (17776399)

"…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …"

Table 2_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.xlsx حسب Hanlin Yu (17776399)

"…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …"

Image 1_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.tif حسب Hanlin Yu (17776399)

"…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …"

Image 4_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.tif حسب Hanlin Yu (17776399)

"…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …"

Image 2_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.tiff حسب Hanlin Yu (17776399)

"…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …"

Data Sheet 2_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.csv حسب Hanlin Yu (17776399)

"…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …"

Image 3_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.tiff حسب Hanlin Yu (17776399)

"…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …"

Data Sheet 1_Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.csv حسب Hanlin Yu (17776399)

"…Co-expression modules were then identified in the SD and stroke datasets by weighted gene co-expression network analysis (WGCNA), respectively, and machine learning algorithms (RandomForest, LASSO, and XGBoost) were performed to identify ARL2 as a key diagnostic biomarker with high predictive value (AUC = 0.91). …"

<b>SAFE: </b><b>s</b><b>ensitive </b><b>a</b><b>nnotation </b><b>f</b><b>inding and </b><b>e</b><b>xtraction from multi-type Chinese maps via hybrid intelligence and knowledge grap... حسب jiaxin ren (20482655)

"…<p dir="ltr">Sensitive annotations typically contain key geographic elements or sensitive information vital for geographic information security. …"

Institutions in the Complexity-Relatedness Framework حسب İbrahim Tuğrul Çınar (12058328)

"…<br>Variable construction and filters (5‑year rolling averages, presence matrix, complexity algorithm, relatedness density, normalisation) follow the manuscript.manuscript_numarali</li></ul><p dir="ltr">Variables (grouped overview)</p><ul><li>Identifiers: <code>reg_nuts2</code>, <code>NUTS1</code>, <code>NUTS0</code>, <code>prio_year</code></li><li>Outcomes / initial levels: <code>gdp_c_gr3</code>, <code>gva_c_gr3</code>, <code>totalemp_gr3</code> (3‑year growth rates), <code>lngdp_c</code>, <code>lngva_c</code></li><li>Controls: <code>cap_stock</code>, <code>gfcf</code>, <code>lnhwork</code> (hours worked, log), <code>capdens**</code> (capital intensity variants used in robustness), <code>population density</code> proxy (see manuscript tables)manuscript_numarali</li><li>Composite capability indices & spatial averages:</li><li><ul><li><code>tcrd_mean</code> (CD‑Mean),</li><li><code>fdenseqi_geo</code> (CDQ‑Geo),</li><li><code>tcrd_eqi</code> (CDQ),</li><li><code>_W1</code> / <code>_W0</code> suffixes = within‑NUTS‑1 / within‑country averages.…"

Robust Multi-Model Subset Selection حسب Anthony-Alexander Christidis (6949055)

"…The <a href="https://doi.org/10.1080/10618600.2025.2596057" target="_blank">supplementary material</a> contains all theoretical proofs, additional algorithmic and computational details, and the code and data to reproduce our numerical results.…"

Trust as moral currency: Perspectives of health researchers in sub-Saharan Africa on strategies to promote equitable data sharing حسب Qunita Brown (19751520)

"…High quality data from Africa will afford diversity to global data sets, reducing bias in algorithms built for artificial intelligence technologies in healthcare. …"

<b>Leveraging protected areas for dual goals of biodiversity conservation and zoonotic</b> <b>risk reduction</b> حسب Li Yang (13558573)

"…Supplementary Tables</p><p dir="ltr">The analysis generates several supplementary tables stored in ./3Spatial_result/5sp_tables/<b> (after you run the code)</b>:</p><p dir="ltr">Table S1. Top 30 Countries with the largest key HCN-HZR Areas, their PA Coverage on key HCN-HZR Areas, and economic income level for each country. …"

A Tutorial on the Use of Artificial Intelligence Tools for Facial Emotion Recognition in R حسب Austin Wyman (17559054)

"…Furthermore, we provide an introductory level explanation of the machine learning, deep learning, and computer vision algorithms that underlie most emotion detection programs in order to improve literacy of explainable artificial intelligence in the social and behavioral science literature.…"

Automatic data reduction for the typical astronomer حسب Bradford Holden (21789524)

"…PypeIt has been developed by a small team of astronomers with two leading philosophies: (1) build instrument-agnostic code to serve nearly any spectrograph; (2) implement algorithms that achieve Poisson-level sky-subtraction with minimal systematics to yield precisely calibrated spectra with a meaningful noise model. …"

SPIDER (v2): Synthetic Person Information Dataset for Entity Resolution حسب Praveen Chinnappa (20835779)

"…<p dir="ltr">SPIDER (v2) – Synthetic Person Information Dataset for Entity Resolution provides researchers with ready-to-use data for benchmarking Duplicate or Entity Resolution algorithms. The dataset focuses on person-level fields typical in customer or citizen records. …"

Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis حسب Alan Glanz (22109698)

"…</p><h3><b>2. </b><code><strong>GenosophusV2.txt</strong></code></h3><h3><b>2. …"

From GIS to HBIM and Back: Multiscale Performance and Condition Assessment for Networks of Public Heritage Buildings and Construction Components حسب Teresa Fortunato (21076099)

"…GIS-based inventory approach of networked construction materials, components, and performances is established by unified performance descriptors and diagnostic tests. GIS-BIM data exchange routines by programming codes and algorithms are developed in Python. …"

Figure 1 from PD-1 Blockade Mitigates Surgery-Induced Immunosuppression and Increases the Efficacy of Photodynamic Therapy for Pleural Mesothelioma حسب Gwendolyn M. Cramer (16964052)

"…<b>D,</b> In the AB12 mouse mesothelioma TI model, IL-1Ra protein levels are higher at 4 hours after TI (<i>n</i> = 7) compared with samples of untreated TC (<i>n</i> = 6, Mann–Whitney test <i>P</i> = 0.001).…"