DataSheet7_Integrative analysis of the role of BOLA2B in human pan-cancer.ZIP by Mingxing Liang (11361621)

“…TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.…”

DataSheet6_Integrative analysis of the role of BOLA2B in human pan-cancer.ZIP by Mingxing Liang (11361621)

“…TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.…”

DataSheet1_Integrative analysis of the role of BOLA2B in human pan-cancer.ZIP by Mingxing Liang (11361621)

“…TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.…”

DataSheet2_Integrative analysis of the role of BOLA2B in human pan-cancer.ZIP by Mingxing Liang (11361621)

“…TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.…”

DataSheet11_Integrative analysis of the role of BOLA2B in human pan-cancer.ZIP by Mingxing Liang (11361621)

“…TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.…”

DataSheet8_Integrative analysis of the role of BOLA2B in human pan-cancer.ZIP by Mingxing Liang (11361621)

“…TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.…”

DataSheet9_Integrative analysis of the role of BOLA2B in human pan-cancer.ZIP by Mingxing Liang (11361621)

“…TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.…”

Collaborative research: CyberTraining: Implementation: Medium: Training users, developers, and instructors at the chemistry/physics/materials science interface by Francesco Paesani (5128004)

“…We achieve our aims by providing learners with various backgrounds exposure to state-of-the-art techniques and skills, showing them how to overcome the challenges of complexity by combining theories and algorithms or by unbiased learning of patterns. We will foster community-building among learners, developers, and instructors at different stages of their careers in multiple successive events designed to create a cohesive and sustainable environment where research and educational developments can grow beyond the project's duration. …”

DataSheet1_Spectrally Consistent Mean Dynamic Topography by Combining Mean Sea Surface and Global Geopotential Model Through a Least Squares-Based Approach.pdf by Hongkai Shi (12095411)

“…In this study, we set up a least squares-based (LS) approach to model MDT signal from the altimeter-derived MSS and geoid height using spherical harmonics from GGMs, where MDT is parameterized by Lagrange Basis Functions (LBFs). …”

Patentability of 3D bioprinting technologies by Phoebe Li (4463947)

“…</p><p dir="ltr">(5) <i>In vitro</i> bioprinted (functional or cosmetic) human organs may be patentable.…”

<b>dGenhancer v2</b>: A software tool for designing oligonucleotides that can trigger gene-specific Enhancement of Protein Translation. by 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. …”

Data for Reinforcement Learning-based Congestion Control: A Systematic Evaluation of Fairness, Efficiency and Responsiveness by Luca Giacomoni (4466608)

“…Reinforcement learning (RL)-based congestion control (CC) promises efficient CC in a fast-changing networking landscape, where evolving communication technologies, applications and traffic workloads pose severe challenges to human-derived, static CC algorithms. …”

EMG and data glove dataset for dexterous myoelectric control by Agamemnon Krasoulis (6582983)

“…Scientific Data, 2014" (http://www.nature.com/articles/sdata201453)</div><div><br></div><div>The experiment comprised nine movements including single-finger as well as functional movements. The subjects had to repeat the instructed movements following visual cues (i.e. movies) shown on the screen of a computer monitor.…”

An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows by 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). …”