The evolutionary relationships of Diprotodontia and improving the accuracy of phylogenetic inference from morphological data by Matthew J. Phillips (7907159)

“…A novel simulation study presented here suggests that the inaccuracies in the marsupial algorithmic morphology studies partly stem from functional and body-size correlations among taxa that over-ride phylogenetic signals. …”

<i>DvvGr43a</i> mediates sugar preference of the western corn rootworm without influencing responsiveness to benzoxazinoids. by Ricardo A. R. Machado (10164653)

“…Asterisks indicate functionally characterized receptors. (B) Protein tertiary structure of <i>DvvGr43a</i> as predicted with the Phyre2 algorithm. …”

Data_Sheet_1_Structure and Protein-Protein Interactions of Ice Nucleation Proteins Drive Their Activity.pdf by Susan Hartmann (5849240)

“…Using computational docking of the new INpro model based on rigid-body algorithms we could reproduce a previously proposed homodimer structure of the INpro CRD with an interface along a highly conserved tyrosine ladder and show that the dimer model agrees with our functional data. …”

Video_1_Development of an Improved Rotational Orthosis for Walking With Arm Swing and Active Ankle Control.MP4 by Zaile Mu (8747151)

“…Given the important function of the ankle joint during normal walking, this work aimed to develop an improved rotational orthosis for walking with arm swing, which is called ROWAS II, and especially to develop and evaluate the algorithms for active ankle control. …”

Video2_Framework for Armature-Based 3D Shape Reconstruction of Sensorized Soft Robots in eXtended Reality.MP4 by Elvis I. A. Borges (12472113)

“…This framework has a Robot Operating System (ROS) backbone, allowing for easy integration with existing soft robot control algorithms for intuitive and real-time teleoperation. …”

Video1_Framework for Armature-Based 3D Shape Reconstruction of Sensorized Soft Robots in eXtended Reality.mp4 by Elvis I. A. Borges (12472113)

“…This framework has a Robot Operating System (ROS) backbone, allowing for easy integration with existing soft robot control algorithms for intuitive and real-time teleoperation. …”

Expression vs genomics for predicting dependencies by Broad DepMap (5514062)

“…If you are interested in trying machine learning, the files Features.hdf5 and Target.hdf5 contain the data munged in a convenient form for standard supervised machine learning algorithms.</p><p dir="ltr"><br></p><p dir="ltr">Some large files are in the binary format hdf5 for efficiency in space and read-in. …”

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). …”

Video_6_Attraction, Dynamics, and Phase Transitions in Fire Ant Tower-Building.MOV by Gary K. Nave (8528121)

“…<p>Many insect species, and even some vertebrates, assemble their bodies to form multi-functional materials that combine sensing, computation, and actuation. …”

Video_4_Attraction, Dynamics, and Phase Transitions in Fire Ant Tower-Building.MOV by Gary K. Nave (8528121)

“…<p>Many insect species, and even some vertebrates, assemble their bodies to form multi-functional materials that combine sensing, computation, and actuation. …”

Video_5_Attraction, Dynamics, and Phase Transitions in Fire Ant Tower-Building.MOV by Gary K. Nave (8528121)

“…<p>Many insect species, and even some vertebrates, assemble their bodies to form multi-functional materials that combine sensing, computation, and actuation. …”

Video_2_Attraction, Dynamics, and Phase Transitions in Fire Ant Tower-Building.MOV by Gary K. Nave (8528121)

“…<p>Many insect species, and even some vertebrates, assemble their bodies to form multi-functional materials that combine sensing, computation, and actuation. …”

Video_1_Attraction, Dynamics, and Phase Transitions in Fire Ant Tower-Building.MOV by Gary K. Nave (8528121)

“…<p>Many insect species, and even some vertebrates, assemble their bodies to form multi-functional materials that combine sensing, computation, and actuation. …”

Video_3_Attraction, Dynamics, and Phase Transitions in Fire Ant Tower-Building.MOV by Gary K. Nave (8528121)

“…<p>Many insect species, and even some vertebrates, assemble their bodies to form multi-functional materials that combine sensing, computation, and actuation. …”

Video_7_Attraction, Dynamics, and Phase Transitions in Fire Ant Tower-Building.MOV by Gary K. Nave (8528121)

“…<p>Many insect species, and even some vertebrates, assemble their bodies to form multi-functional materials that combine sensing, computation, and actuation. …”

Data_Sheet_2_Attraction, Dynamics, and Phase Transitions in Fire Ant Tower-Building.zip by Gary K. Nave (8528121)

“…<p>Many insect species, and even some vertebrates, assemble their bodies to form multi-functional materials that combine sensing, computation, and actuation. …”

Data_Sheet_1_Attraction, Dynamics, and Phase Transitions in Fire Ant Tower-Building.pdf by Gary K. Nave (8528121)

“…<p>Many insect species, and even some vertebrates, assemble their bodies to form multi-functional materials that combine sensing, computation, and actuation. …”

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

“…</div><div><br></div><div>Ten able-bodied (Subjects 1-10) and two right-hand transradial amputee participants (Subjects 11-12) are included in the dataset. …”

AP-2α 相关研究 by Ya-Hong Wang (21080642)

“…</p><p dir="ltr"><b>Figure 4 | Comparative transcriptomic analysis of the functional regulation of </b><b><i>VdAP-2α</i></b><b> in </b><b><i>Verticillium dahliae.…”