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621 results for “methodologies”
Adopted Ranking Methodology for Emerging National Importance Technical Institutions: A Correlation Analysis and Dominance of Research Performance Indicators
<p>The article presents the research performance of newly established technical institutes in India. It gives an overview of NTU and NIRF ranking methodologies. This research would help institutions to check their performance and identify ways to strengthen their rank by producing more output with high-impact research work. The article provides appropriate input to the technical institutions under the study to set out practical and pedagogical approaches, and cross-institutional as well as international collaboration to achieve their research goals. The article gives rank to the technical institutes under the study based on their research performance using the NTU ranking methodology.</p>
Data from: Methodological artefacts cause counter-intuitive evolutionary conclusions in a simulation study
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Data supporting: Methodological overview and data-merging approaches in the study of plant-frugivore interactions
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Revisiting the historical scenario of a disease dissemination using genetic data and Approximate Bayesian Computation methodology: the case of Pseudocercospora fijiensis invasion in Africa
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Deliverable [D4.1] Techno-economic sustainability analysis methodology on resources for bio-based products, conversion routes and end-of-life alternative valorisation options
<p>Techno-economic sustainability analysis (TESA) is a methodology framework to evaluate the performance of a process under technical and economic perspective. A process can be divided into three main sections, the resources required for bio-based products, the conversion routes for the production and finally, the end-of-life alternative valorisation options. Consequently, TESA is carried out separately in the three sections and evaluates the likelihood of their different technology scales and applications and their economic feasibility.</p>
Description of full chain Techno-Economic Sustainability Assessment (TESA) methodology
<p>The dataset provides a preliminary description for techno-economic sustainability principles and criteria in relation to SAT-ProBio blueprint.</p>
Data for: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation
<p>Collection of data files used in the paper titled: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation.</p> <p>Additional dataset which covers the noise study CT scans and digital volume correlation noise studies can be found in DOI: <a href="http://www.doi.org/10.5281/zenodo.3352268">10.5281/zenodo.3361832</a></p> <p><strong>Data contains the following:</strong></p> <ul> <li>X-ray CT data for the interrupted direct shear tests of a soil sample containing a Willow plant. The first file is the specimen scanned unloaded, followed by seven incremental shear load steps to 20 mm shear displacement. Files are 8-bit unsigned and 1800x1800x1600px. Voxel resolution is 0.04642 mm. <ol> <li><strong>20180430_HUTCH_1839_DJB_willow_C_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_A_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_B_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_C_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_D_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_E_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_F_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_G_8-bit_1800x1800x1600.raw</strong></li> </ol> </li> <li>Direct shear vs. displacement data is presented in an Excel spreadsheet: <ul> <li><strong>All_load_data_with_reducing_area.xlsx</strong></li> </ul> </li> <li>Normal and shear strain DVC data which has been averaged and plotted against specimen depth is presented in an Excel spreadsheet: <ul> <li><strong>Average_slice_vs_depth_data_all_samples_all_loads3.xlsx</strong></li> </ul> </li> <li>CT scan metadata giving information to the scan settings, voxel resolution, etc. is contained in a .zip file which consists of .xtekct and .XML files generated from the Nikon CT scanner. <ul> <li><strong>CT_Scan_Metadata.zip</strong></li> </ul> </li> <li>Drawings and Solidworks CAD files of the direct shear test rig are contained within the .zip file. There are a number of parts to the assembly. The file SSSB1003-5.SLDASM contains the complete assembly of the direct shear rig and will help identify the part names. The folder CAD_Drawings contains pdf documents of the part drawings. <ul> <li><strong>Direct_Shear_Drawings_Solidworks_Files.zip</strong></li> </ul> </li> <li>Tabulated DVC data taken at 32x32x32px subset size is contained inside a .zip file. These consist of tab separated .dat files from unloaded (data_1.dat) through incremental load steps Load A, Load B... Load G, (data_2.dat, data_3.dat... data_8.dat). The structure of the .dat file contains columns of data with each column number corresponding to the following: (1) x, (2) y (3) z, (4) vx, (5) vy, (6) vz, (7) exx, (8) eyy, (9) ezz, (10) exy, (11) exz, (12) eyz, (13) volumetric strain, (14) is valid. Columns 1-3 are subset positions in mm, 4-6 are displacements in mm, 7-9 are normal strains, 10-12 are shear strains, 13 is volumetric strain and 14 is a binary value indicating if the subset is valid. <ul> <li><strong>DVC_Load_Data_Willow_C.zip</strong></li> </ul> </li> <li>Tabulated DVC data applied to the load step CT data at 32, 48, 64, 96, 128 pixels is presented in the .zip files containing .dat tab separated files. The structure of the .dat files is described in the previous bullet point. These files were used to construct the noise study applied to incrementally loaded CT data by sampling regions away from the shear zone where the strain signals are close to zero. <ul> <li><strong>DVC_Noise_Study_Data_Load_Steps_Willow_C.zip</strong></li> </ul> </li> <li>Processed noise study data which compares the effects of DVC subset size is presented in the .xlsx file. This file contains both the controlled noise experiment data (stationary, magnification and rigid body motion) and noise study data applied to incrementally loaded data using sampled regions away from the shear zone where the strain signals are close to zero. <ul> <li><strong>Willow_C_Processed_Noise_study2.xlsx</strong></li> </ul> </li> <li>Tabulated data which compares the local x displacement vs depth profile from DVC and direct measurement of root position is contained in the following Excel spreadsheet file: <ul> <li><strong>X_Displacement_Root_and_DVC_Comparison_Willow C.xlsx</strong></li> </ul> </li> </ul>
MarTREC Data Set for Report: Developing and Applying an Analysis Methodology to Identify Flow Generation Influences between Vessel and Truck Shipments
<p>Truck activity is logically connected to vessel activity at a port. In turn, vessel activity is also influenced by truck shipments. Although one might expect a direct and straightforward relation between these two types of shipments, that is rarely the case. For instance, many maritime containers carry consolidated cargos that have multiple and different final destinations. Also, different truck capacities, customs clearance and regulations play a critical role in determining the actual relation between these two types of shipments. This project aims at shedding light on the nuances of maritime and roadway flow relations by quantitatively analyzing the linkages between these two types of shipments.</p> <p>The study performed a statistical analysis to determine the probability distributions of vessel and truck activity, and then explore the correlation of each activity with the other. The analysis yielded coefficients that function as explanatory values for specific truck flows.</p> <p>The ultimate purpose of this study is to provide a clearer and quantitative understanding of the relationship between maritime and truck shipments, and by doing so, to provide tools to develop a system for managing trucks that maximizes efficiency for industry, while minimizing industry’s negative impacts on a region.</p> <p>For this purpose, the study selected the Port Freeport as a case study.</p>
Assessing a Multidisciplinary Group of Undergraduate Students Applying the Challenge Based Learning Methodology to Learn Mobile Development
<p>That video presents the paper entitled "Assessing a Multidisciplinary Group of Undergraduate Students Applying the Challenge Based Learning Methodology to Learn Mobile Development" accepted in SBES 2020 conference (Education track).</p>
Amyloid burden quantification depends on PET and MR image processing methodology
<p>The enclosed datasets refer to the work developed at the University Medical Center Groningen and consist of the minimally required PET image data to replicate the results of the study entitled "Amyloid burden quantification depends on PET and MR image processing methodology" which abstract can be found below:</p> <blockquote> <p>Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer’s Disease <em>in-vivo. </em>However, quantification can be affected by the image processing methodology applied. This study’s goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their <em>Native Space </em>and <em>Standard Space</em>; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature.</p> <p>Intensity-related metrics were not meaningfully affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in <em>Native Space</em> avoiding non-rigid spatial transformations. For analyses in <em>Standard Space</em>, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in <em>Native Space,</em> while intensity-based metrics are more robust against differences in image processing pipelines.</p> </blockquote>
Methodology matters for comparing coarse wood and bark decay rates across tree species
<p>1. The importance of wood decay for the global carbon and nutrient cycles is widely recognized. However, relatively little is known about bark decay dynamics, even though bark represents up to 25% of stem dry mass. Moreover, bark presence versus absence can significantly alter wood decay rates. Therefore, it really matters for the fate of carbon whether variation in bark and wood decay rates is coordinated across tree species.</p> <p>2. Answering this question requires advances in methodology to measure both bark and wood mass loss accurately. Decay rates of large logs in the field are often quantified as loss in tissue density, in which case volume depletions of bark and wood can give large underestimations.</p> <p>3. To quantify the real decay rates, we assessed bark mass loss per stem surface area and wood mass loss based on volume-corrected density loss. We further defined the range of actual bark mass loss by considering bark cover loss. Then, we tested the correlation between bark and wood mass loss across 20 temperate tree species during 4 years of decomposition.</p> <p>4. The area-based method generally showed more than 3-fold higher bark mass loss than the density-based method (even higher if considering bark cover loss), and volume-corrected wood mass losses were 1.08-1.12 times higher than density-based mass loss. The deviation of bark mass loss between the two methods was higher for tree species with thicker inner bark. Bark generally decomposed twice as fast as wood across species, and faster decaying bark came with faster decaying wood (R2=0.26, P=0.006).</p> <p>5. We strongly suggest using corrected volume when assessing wood mass loss especially for the species with faster decomposable sapwood and all the wood at advanced decay stages. Further studies of coarse stem decomposition should consider trait "afterlife" effects of inner bark and estimate fraction of stem bark cover to obtain more accurate decay rates. 6. Our new method should benefit our understanding of the in situ dynamics of woody debris decay and monitoring research in different forest ecosystems worldwide, and should aid meta-analyses across diverse studies.</p>
Research Methodology Examples
<p>Αρχεία εργασίας για το βιβλίο μεθοδολογία έρευνάς</p>
Supplementary Video: An End-to-End DNA Taxonomy Methodology for Benthic Biodiversity Survey in the Clarion-Clipperton Zone, Central Pacific Abyss
<p>Supplementary video for the article "<em>An End-to-End DNA Taxonomy Methodology for Benthic Biodiversity Survey in the Clarion-Clipperton Zone, Central Pacific Abyss</em>".</p>
An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology.
<p>The pattern library is available on GitHub through the Joint Global Change Research Institution repository (https://github.com/JGCRI/CMIP5_patterns). GitHub is a web-based version control repository and Internet hosting service which uses git concepts and commands. The purpose of creating this pattern library was to allow for researchers across various fields to be able to efficiently use the statistical patterns generated by the described regression method to examine model response to change in global mean temperature for all the available CMIP5 models (41 models, at present). We also further intend for those patterns to be easy to scale using a scaler generated from a SCM of ones choosing.</p> <p>The pattern library contains patterns, generated by the least squared regression methodology, for the first realization of the 41 CMIP5 climate models. Annual, seasonal, and monthly patterns are provided for surface temperature and precipitation. For temperature patterns, units in Celsius were used as it is the standard temperature units for impact analysis.</p> <p>Included in each netCDF file for each model is:<br> 1. The individual model pattern (2-D);<br> 2. The adjusted R2 between the predictor and dependent terms (2-D);<br> 3. The standard error of the estimated regression coefficient (2-D);<br> 4. A historical climatology based on the 1961-1990 average from each model (2-D), which can be used to construct absolute values at time X;</p> <p>5. The 95th percentile confidence level pattern for model parameters.</p> <p>The patterns from all 41 CMIP5 models range in size (165 kB to 1 MB) due to spatial resolution, but all patterns were kept at the native resolution of the dependent variable and no regridding of input/output variables were done. This was done to retain model specific information, which may have been lost if regridded to a common spatial resolution.</p> <p>All source code used to produce patterns is available in the aforementioned repository. Source code is written in NCAR Command Language (Version 6.3.0; http://dx.doi.org/10.5065/D6WD3XH5).</p>
Patterns in the appropriation of a learning management system by instructors based on Q-methodology: Dataset
<p>Anonymized dataset</p>
Pediatricians' Professional Identities: A Q-Methodology
<p>sipplementary files 1,2,3 for publication of <strong>Pediatricians' Professional Identities</strong></p>
Combined bioinformatics and machine learning methodologies reveal prognosis-related ceRNA network and propose ABCA8, CAT, and CXCL12 as independent protective factors against osteosarcoma
<p><strong>Supplementary Table 1</strong>. Basic traits of the seven microarray datasets from the Gene Expression Omnibus and The Cancer Genome Atlas.</p><p><strong>Supplementary Table 2</strong>. Basic characteristics of the nine differentially expressed circRNAs</p><p><strong>Supplementary Table 3</strong>. Index of concordance (C-index) and variance inflation factor (VIF) of ABCA8, CXCL12, and CAT.</p><p><strong>Supplementary Table 4.</strong> LASSO and cox analysis of ceRNA with coef/se(coef) < 0.01 and P-value of proportional hazards assumption (PH) > 0.05.</p><p><strong>Supplementary Table 5</strong>. Robust rank aggregation analysis of ABCA8, CXCL12, and CAT. LogFC in the four datasets and RRA score of the three RNAs.</p><p><strong>Supplementary Figure 1.</strong> Competitive endogenous RNA in osteosarcoma.</p><p><strong>Supplementary Figure 2.</strong> Protein–protein interaction (PPI) network of genes in the competitive endogenous RNA network</p><p><strong>Supplementary Figure 3.</strong> Proportional hazards assumption (left) and linearity assumption (right).</p><p><strong>Supplementary Figure 4.</strong> Survival analysis for competitive endogenous RNA in osteosarcoma.</p>
Intrusive and Non-Intrusive Uncertainty Quantification Methodologies for Pyrolysis Modeling
<p>This repository contains python scripts and results for uncertainty analysis of Arrhenius equation with kinetic parameters as uncertain. The data set contains folders for each PMMA variant (1,2 and 3) used for uncertainty quantification (UQ) and 'Misc' folder containing miscellaneous files and scripts used in the study. </p> <p>Each PMMA variant folder has further sub-folders for the UQ methods implemented:</p> <ol> <li>Intrusive polynomial chaos (IPC)</li> <li>Monte Carlo (MC)</li> <li>Non-intrusive polynomial chaos (NIPC)</li> </ol> <p>Additionally convergence and comparison for the UQ methods is available in sub-folders of the same name respectively.</p> <p>The python file 'UoWu_noLatex.mplstyle' for plotting style used by us is attached to ease the rerunning of the scripts.</p>
Public funding accountability: a linked open data-based methodology for analysing the scientific productivity and influence of funded projects. Dataset
<p>Tables containing the information about the projects funded by the Spanish AEI and publications acknowledging funding from Funder Registry. Both datasets where used in our publication: <em>Public funding accountability: a linked open data-based methodology for analysing the scientific productivity and influence of funded projects</em>.</p>
Supplementary Materials - Integrating Spatial Analyses and Microbotanical Remains: A Methodological Approach for Investigating Plant Processing Activities and Domestic Spaces at Neolithic Çatalhöyük.
<p><strong>Supplementary Materials I, II, and III - Integrating Spatial Analyses and Microbotanical Remains: A Methodological Approach for Investigating Plant Processing Activities and Domestic Spaces at Neolithic Çatalhöyük.</strong></p> <p> </p> <p><strong>Supplementary I</strong> contains the raw data for the microbotanical analyses on Buildings 80 and 131. It consists of laboratory track sheets and the raw counts of phytoliths and starch grains from each building.</p> <p><strong>Supplementary II</strong> contains: a) A detailed description of all the starch grain typologies encountered in this research along with references from modern reference collections; b) A visual example of each of the phytolith morphotypes identified and c) The variogram and the Kriging error variances.</p> <p><strong>Supplementary III</strong> refers to the R code, building shape files (Mask), and spatial data utilized to produce the Kriging and IDW stipital objects.</p>
ScienceDex guides
Understand access before you commit
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.