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. …”

Mean squared Error on all unseen data. by Edward Antonian (21453161)

“…The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. Next, we examine the statistical effect of correlated prediction error and propose a method for Generalized Least Squares (GLS) on graphs. …”

Possible graph filter functions. by Edward Antonian (21453161)

“…The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. Next, we examine the statistical effect of correlated prediction error and propose a method for Generalized Least Squares (GLS) on graphs. …”

The notational conventions used in this paper. by Edward Antonian (21453161)

“…The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. Next, we examine the statistical effect of correlated prediction error and propose a method for Generalized Least Squares (GLS) on graphs. …”

Survey Data on NSSI, Stress Response, Emotional Regulation Strategies and gender in Chinese Undergraduates by Yilin Ma (21154754)

“…</p><p dir="ltr"><b>Behavioral sub-questionnaire (AFASM1-12) :</b> Assesses NSSI with or without visible tissue damage</p><p dir="ltr"><b>Functional sub-questionnaire (BFASM1-19):</b> Measures three function types</p><ul><li><i>Automatic negative reinforcement: r</i>efers to engaging in NSSI to relieve or escape from an unpleasant internal state</li><li><i>Social positive reinforcement: </i>refers to engaging in NSSI to create a favorable state or to fulfill social needs</li><li><i>Emotional expression:</i>refers to engaging in NSSI as a means of expressing one’s emotional experiences</li></ul><p dir="ltr"><b>Scale:</b> 5-point Likert scale</p><h3><b>4.Gender</b></h3><ul><li>In this study, males were coded as “1” and females as “2”.</li></ul><p dir="ltr"><b>Usage Notes</b></p><ul><li></li><li>Each row represents one participant; columns include both item‑level and aggregated subscale scores.…”

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. …”

Image 1_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.tif by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 9_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 6_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 3_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 7_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 10_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 2_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 5_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 8_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 4_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 1_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

3D Deformable cell based model. by Roland M. Dries (6620132)

“…(<b>F</b>) Cell model algorithm, shown as pseudo code.</p>…”