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1,855 results for “Framework”
Figure 1 in A simple framework for the exploration of functional biodiversity
Figure 1. – Histogram of maximum body weights of 31,134 species of fishes. The dashed vertical lines indicate –3, –1, 1 and 3 standard deviations in log space and are used as borders between the displayed body size categories, with indicated weight ranges and number of species. Geometric mean body weight is 37.2 g.
Fig. 5 in Orthoceratoid and coleoid cephalopods from the Middle Triassic of Switzerland with an updated taxonomic framework for Triassic Orthoceratoidea
Fig. 5 Camera lucida drawings of Triassic orthoceratoid genera (not to scale) in comparison with Michelinoceras. Phattalungoceras is not shown here, as the only specimen is too poorly preserved to confidently reconstruct its internal structures, although it appears to resemble Pseudotemperoceras. A Michelinoceras michelini, after Barrande (1870; pl. 381; fig. 14); B Trematoceras elegans, after Schindewolf (1933; fig. 5); C Paratrematoceras shevyrevi, after Schastlivceva (1988 pl. 1, fig. 3); D Pseudotemperoceras nyalamense, after Chen (1981; text-fig. 2); E Pseudotemperoceras pulchrum, after Schastlivceva (1988; pl. 1, fig. 5c)
Fig. 6 in Orthoceratoid and coleoid cephalopods from the Middle Triassic of Switzerland with an updated taxonomic framework for Triassic Orthoceratoidea
Fig. 6 Comparison of embryonic shells of selected orthoceratoids. A Trematoceras cf. politum (= T. elegans), Late Triassic, Carnian, after Schindewolf (1933; fig. 5). B Michelinoceras michelini, late Silurian, Ludlow, after Ristedt (1968; fig. 3.1b); C Pseudorthoceras knoxense, Carboniferous, Serpukhovian, after Kröger & Mapes (Kröger & Mapes, 2004; fig. 5.9)
Fig. 7 in Orthoceratoid and coleoid cephalopods from the Middle Triassic of Switzerland with an updated taxonomic framework for Triassic Orthoceratoidea
Fig. 7 Simplified time-scaled phylogeny demonstrating possible relationships of the Trematoceratidae to other orthoceratoids and coleoids. Note that Orthoceras and Michelinoceras are more closely related to coleoids than they are to trematoceratids under this concept. Several groups are omitted here for clarity (e.g., Nautilida, Ammonoida). The questionable Zhuravlevia is here excluded
Fig. 2 in Networks and the ecology of parasite transmission: A framework for wildlife parasitology
Fig. 2. How do we use networks to understand the ecology of parasite transmission? Networks allow us to describe how the behaviour of individuals collectively affects the transmission of parasites within wildlife populations. They provide a flexible framework that enables analysis at three different levels; individual (panel A), dyadic (pair-wise associations) (panel B) and the network (population) level (panel C). Within each level of analysis, there are different metrics and analytical approaches that can be used to explore the ecology of parasite transmission.
Fig. 1 in Networks and the ecology of parasite transmission: A framework for wildlife parasitology
Fig. 1. What is a network? A network in its most elementary form is an adjacency matrix, where row and column labels represent the individuals in the network, and the remaining cells represent the pair-wise associations among individuals in the network (panel A). These associations can be weighted, as below (panel A), where stronger relationships are assigned a higher value (for example, the duration or frequency of contact). They can also be directed, to reflect the direction of the association; in this instance, the direction of possible parasite transmission. In this case, rows represent donor nodes, and columns represent recipient nodes (e.g., in panel A: from node C (donor) to node D (recipient), there is a score of 1). The matrix can be visualised as a network diagram (panel B), consisting of nodes, which represent the epidemiological unit of interest (usually individuals) connected together by a series of edges representing the measure of association (the potential for parasite transmission). In context of understanding the ecology of parasite transmission, edges represent a 'contact' between two hosts that provides an opportunity for parasite transfer. The weighting of edges represents the likelihood of parasite transmission (e.g., the frequency or intensity of contact among hosts). The definition of a contact will depend on the type of parasite considered, and how it is passed from one host to another.
Fig. 1 in Toxoplasma gondii exposure in arctic-nesting geese: A multi-state occupancy framework and comparison of serological assays
Fig. 1. Comparison of seroprevalence estimates for Ross's Geese and Lesser Snow Geese generated by naïve and multi-state occupancy estimators (seroprevalence = Ψ1 × Ψ2).
Towards suitable practices for the integration of social life cycle assessment into the ecodesign framework of hydrogen-related products
<p>The hydrogen sector is envisaged as one of the key enablers of the energy transition that the European Union is facing to accomplish its decarbonization targets. However, regarding the technologies that enable the deployment of a hydrogen economy, a growing concern exists about potential burden-shifting across sustainability<br>dimensions. In this sense, social life cycle assessment arises as a promising methodology to evaluate the social implications of hydrogen technologies along their supply chains. In the context of the European projects eGHOST and SH2E, this study seeks to advance on key methodological aspects of social life cycle assessment when it<br>comes to guiding the ecodesign of two relevant hydrogen-related products: a 5 kW solid oxide electrolysis cell stack for hydrogen production, and a 48 kW proton-exchange membrane fuel cell stack for mobility applications.<br>Based on the social life cycle assessment results for both case studies under alternative approaches, the definition of a product-specific supply chain, making use of appropriate cut-off criteria, was found to be the preferable choice when addressing system boundaries definition. Moreover, performing calculations according to the activity variable approach was found to provide valuable results in terms of social hotspots identification to support subsequent decision-making processes on ecodesign, while the direct calculation approach is foreseen as a complement to ease the interpretation of social scores. It is concluded that advancements in the formalization of<br>such suitable practices could foster the integration of social metrics into the sustainable-by-design framework of hydrogen-related products.</p>
ENTICE Multi-objective optimization framework synthetic evaluation data-sets
<p>This dataset contains synthetic usage data for evaluation of the multi-objective redistribution framework for distributed VMI repositories. </p> <p>The data is stored in a Java object and it should be directly loaded. </p> <p> </p>
Internet of Things from a Business Perspective - The IoT Literature Classification Framework
<p>The Internet of Things (IoT) is an important development in the context of business information systems. The IoT, as a foundation for cyber-physical information systems, has similar potential for revolutionizing business as cloud computing over the last decade. The purpose of the current article is to formulate and apply a framework in order to take a quantitative snapshot of current literature on the IoT from a business perspective. Our results give an overview on important areas and will support future studies in research and practice. </p> <p>This dataset contains the IoT literature classification framework as MS Excel file.</p>
Efficient NAS Benchmark Kernels with C++ Parallel Programming Frameworks for Multi-Cores
<p>Benchmarking is a way to study the performance of new architectures and parallel programming frameworks. Well-established benchmark suites such as the NAS Parallel Benchmarks (NPB) comprise legacy codes that still lack portability to C++ language. As consequence, a set of high-level and easy-to-use C++ parallel programming frameworks cannot be tested in NPB. Our goal is to describe a C++ porting of the NPB kernels and to analyze the performance achieved by different parallel implementations written using the Intel TBB, OpenMP and FastFlow frameworks for Multi-Cores. The experiments show an efficient code porting from Fortran to C++ and a good parallel efficiency on average.</p>
Supplementary data for "Vacancy defect configurations in the metal-organic framework UiO-66: Energetics and electronic structure"
<p>Optimised structures for UiO-66 with various defect configurations in VASP POSCAR format. For naming see the associated paper (DOI:10.1039/c7ta11155j).</p>
ACE gene haplotypes and social networks: Using a biocultural framework to investigate blood pressure variation in African Americans
<p>This dataset contains all processed data used in analyses reported in the manuscript, ACE gene haplotypes and social networks: Using a biocultural framework to investigate blood pressure variation in African Americans. This project is part of a larger study focused on investigating the role of stress, discrimination, genetic variants, and other sociocultural factors in hypertension in African Americans.</p> <p> </p> <p> </p> <p>Variable Names and Descriptions:</p> <p>HHID: Participant Identification number</p> <p>sbp-10: Average of two Systolic Blood Pressure readings without 10 point correction for blood pressure medication (mmHg)</p> <p>sbp: Average of two Systolic Blood Pressure readings with 10 point correction for blood pressure medication (mmHg)</p> <p>dbp-5: Average of two Diastolic Blood Pressure readings without 5 point correction for blood pressure medication (mmHg)</p> <p>dbp: Average of two Diastolic Blood Pressure readings with 5 point correction for blood pressure medication (mmHg)</p> <p>ACE.Genotype: ACE genotype (0= Deletion/Deletion, 1= Insertion/Deletion, 2= Insertion/Insertion)</p> <p>WNK1.Genotype: WNK1 Genotype (0= Deletion/Deletion, 1= Insertion/Deletion, 2= Insertion/Insertion)</p> <p>age: age (years)</p> <p>sex: sex (Male =1, Female = 2)</p> <p>bpmedtake: Whether the participant uses blood pressure medication</p> <p>bmi: Body Mass Index (calculated from height and weight)</p> <p>ALTER GENDER|Answer:Male|Value:0|Count: Number of male alters (social network members)</p> <p>Alter Gender Male: Percentage of alters that are male</p> <p>ALTER GENDER|Answer:Female|Value:1|Count: Number of female alters (social network members)</p> <p>Alter Gender Female: Percentage of alters that are female</p> <p>Closeness_Mean: Average closeness centrality of the network</p> <p>Between_Mean: Average between-ness centrality of the network</p> <p>percentage of family in structural percentage: Percentage of central network positions occupied by family members</p> <p>relationship max close family: The most close (centrally) network member is a family member</p> <p>Average distance: Average distance of individuals in a network</p> <p>Hap B: ACE gene haplotypes</p> <p> </p>
Leaf and wood classification framework for terrestrial LiDAR point clouds: Simulated data validation dataset
<p>Set of 200 3D point clouds used in the validation of "Leaf and wood classification framework for terrestrial LiDAR point clouds". This dataset is a collection of point clouds simulated by a Monte-Carlo ray tracing (librat) using four 3D tree models from the fourth phase RAMI exercise (Widlowski et al, 2015).</p>
Leaf and wood classification framework for terrestrial LiDAR point clouds: Field data validation dataset
<p>Set of 10 3D point clouds used in the validation of "Leaf and wood classification framework for terrestrial LiDAR point clouds". This dataset is a collection of single trees scanned around the globe, from different biomes (both forest and urban areas), using the Riegl VZ-400 terrestrial laser scanner.</p>
Data for "BayesCMD: A Bayesian framework for the analysis of systems biology models of the brain"
<p>Data for the "BayesCMD: A Bayesian framework for the analysis of systems biology models of the brain".</p> <p>All files except 'simulated_hypoxia.csv' contains both input and output data.</p>
Structured feature comparison between container orchestration frameworks
<p>Container orchestration frameworks provide support for management of complex distributed applications. Different frameworks have emerged only recently, and they are in constant evolution as new features are being introduced.</p> <p>This reality makes it difficult for practitioners and researchers to maintain a clear view on the technology space, and hinders selecting the most appropriate framework, assessing the maturity and the lock-in risks for each framework.</p> <p>We present an descriptive feature comparison study of the five most prominent orchestration solutions: Docker Swarm, Kubernetes, and Mesos, combined with Marathon or Aurora, and DC/OS. This study aims at (i) identifying the common and unique features of all frameworks, (ii) comparing these frameworks qualitatively ánd quantitatively with respect to: (ii.a) genericity in terms of supported features and (ii.b) vendor lock-in, (iii) investigating the maturity and stability of the frameworks as well as the pioneering nature of each framework by studying the historical evolution of the frameworks on GitHub</p> <p>The study methodology involves feature variability and commonality analysis, mapping features to common use cases and development history on GitHub, and card sorting for defining a taxonomy of features which is divided into 9 functional aspects and 27 sub-aspects.</p> <p>The result is a comprehensive feature-based overview of the current state of container orchestration frameworks. The published data set contains the data used for answering all research questions (i), (ii) and (iii). This data has been processed both qualitatively as quantitatively. The scientific approach and reproducible methodology allows for continued assessment of container orchestration frameworks.</p> <p>The document format is Microsoft Office Word and is associated with an extended Office template that contains macro's for processing these links automatically (checkLinks creates a simple bibliography, openLinks opens all references in a selected range, deleteLinks delete Links). To activate these Macro's, save the file Normal.dotm in your local user directory that by default contains all Microsoft templates for your user account. For example in Windows, this directory is located in the c:\users\<user name>\AppData\Roaming\Microsoft\Templates</p> <p> </p>
An Insight on the Effect of Azobenzene Functionalities Studied in UiO-66 Framework for Low Energy CO2 Capture and CO2/N2 Membrane Separation
<p>Data supporting journal manuscript. Includes an Excel spreadsheet with all the raw data for the figures in the manuscript, calibrations and calculations. Also includes 3D chemical structures of MOF units, and SEM images of MOF/polymer composite materials.</p> <p><strong>Abstract</strong></p> <p>In this paper, we report a simple approach to study the fundamental aspect of light-responsive metal organic framework (MOF) in UiO-66 topology through a mixed-ligand approach. Apart from change in the structural property, the loading of azobenzene linker inside the framework also affects the CO<sub>2 </sub>light-responsive property and CO<sub>2</sub>/N<sub>2 </sub>selectivity which could help to design future low-energy CO<sub>2 </sub>adsorbents. Further study to incorporate the MOFs into mixed matrix membranes also indicates the benefit of higher azobenzene loading in the MOF to enhance the CO<sub>2</sub>/N<sub>2 </sub>separation performance since it can improve the separation performance which could not be obtained in non-functionalized fillers. </p> <p><strong>Preprint manuscript</strong></p> <p>A Preprint version of the manuscript is available at: <a href="https://doi.org/10.26434/chemrxiv.7568696.v1">https://doi.org/10.26434/chemrxiv.7568696.v1</a> </p> <p><strong>Published article</strong></p> <p>Journal of Materials Chemistry A, 2019, DOI: <a href="https://doi.org/10.1039/C9TA02096A">https://doi.org/10.1039/C9TA02096A</a></p>
A Layer-averaged Nonhydrostatic Dynamical Framework on an Unstructured Mesh for Global and Regional Atmospheric Modeling: Model Description, Baseline Evaluation and Sensitivity Exploration
<p>Selected model output data for supporting this paper.</p> <p>List of Files:</p> <p>2dtracer.tar.gz: correlated tracer test</p> <p>rh3d.tar.gz: 3D Rossby-Haurwitz Wave</p> <p>modon.tar.gz: Colliding Modons</p> <p>jwss.tar.gz: Jablonowski-Williamson Baroclinic Steady State</p> <p>jwbw_1d.tar.gz: 1D data output from Jablonowski-Williamson Baroclinic Wave</p> <p>jwbw_2d.tar.gz: 2D data output from Jablonowski-Williamson Baroclinic Wave</p> <p>dcmip31.tar.gz: DCMIP3-1 nonhydrostatic gravity wave</p> <p>Klemp15.tar.gz: Nonhydrostatic Mountain Waves in Klemp et al. 2015</p> <p>held-suarez.tar.gz: Held-Suarez dry climate (post-processed data for plotting, the raw daily data are too large to upload)</p> <p>jwbwvr.tar.gz: Variable-Resolution modeling of the Jablonowski-Williamson Baroclinic Wave</p> <p> </p> <p>see https://doi.org/10.5281/zenodo.3544795 for a companion work</p> <p>References:</p> <p>Zhang, Y., J. Li, R. Yu, S. Zhang, Z. Liu, J. Huang, and Y. Zhou, 2019: A Layer-Averaged Nonhydrostatic Dynamical Framework on an Unstructured Mesh for Global and Regional Atmospheric Modeling: Model Description, Baseline Evaluation, and Sensitivity Exploration. <em>Journal of Advances in Modeling Earth Systems</em>, <strong>11,</strong> 1685-1714.</p>
Can metal organic frameworks outperform adsorptive removal of harmful phenolic compound 2-chlorophenol by activated carbon?
<p>Dataset supporting publication. High resolution images, and full data set as produced in manuscript figures.</p> <p><strong>Preprint</strong>: <a href="https://doi.org/10.26434/chemrxiv.10320752.v1">https://doi.org/10.26434/chemrxiv.10320752.v1 </a></p> <p><strong>Published article:</strong> <a href="https://doi.org/10.1016/j.cherd.2020.03.017">https://doi.org/10.1016/j.cherd.2020.03.017 </a></p> <p><strong>Abstract:</strong> Removal of persistent organic compounds from aqueous solutions is generally achieved using adsorbent like activated carbon (AC) but it suffers from limited adsorption capacity due to low surface area. This paper describes a pioneering work on the adsorption of an organic pollutant, 2-chlorophenol (2-CP) by two MOFs with high surface area and water stability; MIL-101 and its amino-derivative, MIL-101-NH<sub>2</sub>. Although MOFs have higher surface area than AC, the latter was proven better having the highest equilibrium 2-CP uptake (345 mg.g<sup>-1</sup>), followed by MIL-101 (121 mg.g<sup>-1</sup>) and MIL-101-NH<sub>2</sub> (84 mg.g<sup>-1</sup>). Used MIL-101 could be easily regenerated multiple times by washing with ethanol and even showed improved adsorption capacity after each washing cycle. These results can open the doors to meticulous adsorbent selection for treating 2-CP-contaminated water. </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.