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1,034 results for “Empirical”
Replication Package for "Improving Programming Education Through SonarQube: A Multiple Empirical Study of How Students Understand Rule Violations, Perceive the Criticality of the Rule, and the Fixing Difficulty"
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An Empirical Study on Snapshot Testing Practices
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Exploring the Impact Mechanism of ChatGPT Applications on University Teachers' Perceived Professional Threats: An Empirical Study Based on Conservation of Resources Theory
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Fit summary of "X-Shooting ULLYSES: Massive Stars at low metallicity IX: Empirical constraints on mass-loss rates and clumping parameters for OB supergiants in the Large Magellanic Cloud"
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The Impact of Trade Barriers in Digital Services on Employment in the Service Sector: Empirical Evidence from China
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Data from: Conventional analysis of trial-by-trial adaptation is biased: empirical and theoretical support using a Bayesian estimator
Research on human motor adaptation has often focused on how people adapt to self-generated or externally-influenced errors. Trial-by-trial adaptation is a person's response to self-generated errors. Externally-influenced errors applied as catch-trial perturbations are used to calculate a person's perturbation adaptation rate. Although these adaptation rates are sometimes compared to one another, we show through simulation and empirical data that the two metrics are distinct. We demonstrate that the trial-by-trial adaptation rate, often calculated as a coefficient in a linear regression, is biased under typical conditions. We tested 12 able-bodied subjects moving a cursor on a screen using a computer mouse. Statistically different adaptation rates arise when sub-sets of trials from different phases of learning are analyzed from within a sequence of movement results. We propose a new approach to identify when a person's learning has stabilized in order to identify steady-state movement trials from which to calculate a more reliable trial-by-trial adaptation rate. Using a Bayesian model of human movement, we show that this analysis approach is more consistent and provides a more confident estimate than alternative approaches. Constraining analyses to steady-state conditions will allow researchers to better decouple the multiple concurrent learning processes that occur while a person makes goal-directed movements. Streamlining this analysis may help broaden the impact of motor adaptation studies, perhaps even enhancing their clinical usefulness.
Supplementary material 1 from: Zhao X, Zhang J, Guo H (2021) Development evaluation of nature reserves under China's forestry department: A spatiotemporal empirical study at the province level. Nature Conservation 44: 81-97. https://doi.org/10.3897/natureconservation.44.65488
Tables S1, S2
The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical datasets
<p class="CxSpFirst">The software program STRUCTURE is one of the most cited tools for determining population structure. To infer the optimal number of clusters from STRUCTURE output, the Δ<i>K</i> method is often applied. However, a recent study relying on simulated microsatellite data suggested that this method has a downward bias in its estimation of <i>K</i> and is sensitive to uneven sampling. If this finding holds for empirical datasets, conclusions about the scale of gene flow may have to be revised for a large number of studies. To determine the impact of method choice, we applied recently described estimators of <i>K</i> to re-estimate genetic structure in 41 empirical microsatellite datasets; 15 from a broad range of taxa and 26 focused on a diverse phylogenetic group, coral. We compared alternative estimates of <i>K</i> (Puechmaille statistics) with traditional (Δ<i>K</i> and posterior probability) estimates and found widespread disagreement of estimators across datasets. Thus, one estimator alone is insufficient for determining the optimal number of clusters regardless of study organism or evenness of sampling scheme. Subsequent analysis of molecular variance (AMOVA) between clustering solutions did not necessarily clarify which solution was best. To better infer population structure, we suggest a combination of visual inspection of STRUCTURE plots and calculation of the alternative estimators at various thresholds in addition to Δ<i>K</i>. Differences between estimators could reveal patterns with important biological implications, such as the potential for more population structure than previously estimated, as was the case for many studies reanalyzed here.</p>
VMTools-RA Empirical Qualitative Evaluation Package
<p>VMTools-RA Empirical Qualitative Evaluation Package</p>
Linking population dynamics models with empirically derived models through phytoplankton primary production
<p>There are alternative methods for estimation of phytoplankton primary production (PP) that are fundamentally different in the calculation approach. The process-oriented PP model is a mechanistic, empirically derived method based on the photosynthesis–light relationships. The population dynamics-based PP calculation, which is a synthetic method, provides a production estimate based on population dynamics of phytoplankton. These alternative methods were here compared with regard to production estimates and linked to enhance the performance of the existing models of population dynamics applied to a wide variety of lakes worldwide in terms of morphometry, nutrient status, and light environments. Estimates of primary production were shown to be sensitive to changes in phytoplankton sinking and zooplankton grazing rates in both methods. Production estimates in the process-oriented PP model were also sensitive to light-associated parameters such as day length. Although the production estimated from the population dynamics-based PP calculation tended to be lower than that from the process-oriented PP model irrespective of lake morphometry, production estimates calculated from both methods with standard parameterization were comparable when production was estimated on an annual timescale. However, it was also shown that the alternative methods could produce different production estimates when estimated on shorter timescales such as cyanobacterial blooms in summer. Cyanobacteria with low mortality due to grazing and sinking losses have been considered as trophic bottlenecks, but there is increasing evidence that their mortality is, to a considerable extent, due to parasitic pathogens. In the case of cyanobacterial blooms, an addition of parasite-related loss term (19–33% of standing stock) resulted in a resolution of the difference in production estimates between the methods. These analyses theoretically support the critical role of parasitism and resolve the bottleneck problem in aquatic ecosystem metabolism.</p>
Data set for EMPIR project MeDDII Paper FMI 73 2020 101729
<p>Data set for EMPIR project MeDDII Paper</p> <p>https://doi.org/10.1016/j.flowmeasinst.2020.101729</p>
Data set for EMPIR project MeDDII Report A2.2.2
<p>Data set for EMPIR project MeDDII Report A2.2.2</p> <p>In-line calibration of in-line pressure sensors</p>
An Exploratory Empirical Study of Trust & Safety Engineering in Open-Source Social Media Platforms
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An Empirical Study Assessing Software Modeling in Alloy
<p>VM for the Formalise Artifact 2023</p>
Empirical study on Visual Attention Characteristics of basketball players of different levels during free-throw shooting original data.
<p>不同水平篮球运动员罚球投篮视觉注意特征实证研究的原始数据,包括注视持续时间、注视次数、瞳孔扩张和扫视幅度。</p>
What rationales drive architectural decisions? An empirical inquiry - Additional material
<p>Contains additional files for the paper "What rationales drive architectural decisions? An empirical inquiry" submitted for review to the ECSA 2023 Research Track.</p>
Empirical Models output - RECCAP2 Program
<p>This data set contains the Empirical models' output data provided under RECCAP2 Program</p>
Data from: Economic uncertainty, geopolitical risk and U.S. energy price risk spillover: An empirical study based on the risk spillover model
<p>This data is mainly used to analyze the risk correlation among economic uncertainly,geopolitical risk and energy price,and can also be applied to the TVP-VAR model to analyze the correlation between different variables using the time-varying parameter model,which has great potential for reuse. The risk relationship between economic uncertainly.At the same time,since it is macroeconomic data,it does not involve any moral and ethical issues.</p>
An Empirical Study on Analyzing the Factors that Affect the Triagement of Change Points
<p>An Empirical Study on Analyzing the Factors that Affect the Triagement of performance Change Points</p>
An Empirical Model for Mercury's Field-Aligned Currents Derived from MESSENGER Magnetometer Data
<p>Companion dataset for manuscript titled "An Empirical Model for Mercury’s Field-Aligned Currents Derived from MESSENGER Magnetometer Data" submitted to <em>JGR: Space Physics</em>.</p> <p>The file MESSENGER_MAG_Disturbance_Indices_v12.txt defines the Mercury disturbance index as a function of MESSENGER orbit number.</p> <p>The file rsuns.txt defines the Mercury’s Heliocentric distance as a function of time.</p> <p>The file merge_magrdr_11083_15120_actidx_kt17res.txt contain the processed MESSENGER magnetometer vectors. This file is further broken into quintiles based on the disturbance index.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.