Supplementary file 2_The role of α-hydroxybutyrate in modulating sepsis progression: identification of key targets and biomarkers through multi-database data mining, machine learni... حسب Qing Lu (28914)

"…Sepsis-related targets were obtained from the GEO dataset GSE26440, and the intersection of these datasets was analyzed to reveal common targets. Functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning algorithms (L1-LASSO, RF, and SVM) were applied to identify biomarkers. …"

Supplementary file 1_The role of α-hydroxybutyrate in modulating sepsis progression: identification of key targets and biomarkers through multi-database data mining, machine learni... حسب Qing Lu (28914)

"…Sepsis-related targets were obtained from the GEO dataset GSE26440, and the intersection of these datasets was analyzed to reveal common targets. Functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning algorithms (L1-LASSO, RF, and SVM) were applied to identify biomarkers. …"

Desmoke-LAP: Desmoking in Laparoscopic Surgery Dataset حسب Yirou Pan (22560914)

"…<p dir="ltr"><b>This is the publicly available dataset from robot-assisted laparoscopic hysterectomy surgery providing a benchmark for designing and validating smoke removal algorithms. </b> </p><h3><b>Overview</b></h3><p dir="ltr">The dataset contains frames and video clips from 10 robot-assisted laparoscopic hysterectomy procedure videos. …"

An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows حسب Pierre-Alexis DELAROCHE (22092572)

"…Performance Profiling Algorithms Energy Measurement Methodology # Pseudo-algorithmic representation of measurement protocol def capture_energy_metrics(workflow_type: WorkflowEnum, asset_vector: List[PhotoAsset]) -> EnergyProfile: baseline_power = sample_idle_power_draw(duration=30) with PowerMonitoringContext() as pmc: start_timestamp = rdtsc() # Read time-stamp counter if workflow_type == WorkflowEnum.LOCAL: result = execute_local_pipeline(asset_vector) elif workflow_type == WorkflowEnum.CLOUD: result = execute_cloud_pipeline(asset_vector) end_timestamp = rdtsc() energy_profile = EnergyProfile( duration=cycles_to_seconds(end_timestamp - start_timestamp), peak_power=pmc.get_peak_consumption(), average_power=pmc.get_mean_consumption(), total_energy=integrate_power_curve(pmc.get_power_trace()) ) return energy_profile Statistical Analysis Framework Our analytical pipeline employs advanced statistical methodologies including: Variance Decomposition: ANOVA with nested factors for hardware configuration effects Regression Analysis: Generalized Linear Models (GLM) with log-link functions for energy modeling Temporal Analysis: Fourier transform-based frequency domain analysis of power consumption patterns Cluster Analysis: K-means clustering with Euclidean distance metrics for workflow classification Data Validation and Quality Assurance Measurement Uncertainty Quantification All energy measurements incorporate systematic and random error propagation analysis: Instrument Precision: ±0.1W for CPU power, ±0.5W for GPU power Temporal Resolution: 1ms sampling with Nyquist frequency considerations Calibration Protocol: NIST-traceable power standards with periodic recalibration Environmental Controls: Temperature-compensated measurements in climate-controlled facility Outlier Detection Algorithms Statistical outliers are identified using the Interquartile Range (IQR) method with Tukey's fence criteria (Q₁ - 1.5×IQR, Q₃ + 1.5×IQR). …"

<b>dGenhancer v2</b>: A software tool for designing oligonucleotides that can trigger gene-specific Enhancement of Protein Translation. حسب Adam Master (20316450)

"…<br> An excel-based calculator - dGenhancer can be used to search for putative 5’UTR cis-acting elements, which functional activity could be determined by Gibbs energy-dependent secondary structure formation. …"

Table 1_Exploring fecal microbiota signatures associated with immune response and antibiotic impact in NSCLC: insights from metagenomic and machine learning approaches.docx حسب Wenjie Han (1812673)

"…Antibiotic exposure significantly influenced the abundance and functional potential of these key taxa. KEGG-based functional analysis revealed the enrichment of amino acid metabolism pathways in responders. …"

Data Sheet 1_Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review.pdf حسب Catalina Gomez (7057646)

"…We find that current interactions are dominated by simplistic collaboration paradigms, leading to little support for truly interactive functionality. Our taxonomy offers a tool to understand interactivity with AI in decision-making and foster interaction designs for achieving clear communication, trustworthiness, and collaboration.…"

Image 1_Quantitative assessment and Kirschner-wire fixation of an isolated sustentaculum tali fracture in a 7-year-old girl—a case report.tif حسب Fengyong Mao (22100207)

"…Although this investigation offers valuable technical insights, multi-institutional prospective studies are warranted to establish definitive surgical criteria and standardized management algorithms.</p>…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

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

"…With WGCNA and machine-learning algorithms analyses, we found that ARL2 is an important common marker for both diseases.…"

Table 2_Unraveling the role of histone acetylation in sepsis biomarker discovery.docx حسب Feng Cheng (124653)

"…</p>Methods<p>Transcriptomic and single-cell RNA sequencing data were used to identify histone acetylation-related genes. …"

Table 3_Unraveling the role of histone acetylation in sepsis biomarker discovery.docx حسب Feng Cheng (124653)

"…</p>Methods<p>Transcriptomic and single-cell RNA sequencing data were used to identify histone acetylation-related genes. …"