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929 results for “evaluation of impact”
Evaluating Impact of NIRAF Detection for Identifying Parathyroid Glands During Parathyroidectomy
ClinicalTrials.gov study NCT04299425. IPD Sharing: YES. Countries: 1. Publications: 13.
Study of Dabrafenib+Trametinib in the Adjuvant Treatment of Stage III BRAF V600+ Melanoma After Complete Resection to Evaluate the Impact on Pyrexia Related Outcomes
ClinicalTrials.gov study NCT03551626. IPD Sharing: YES. Countries: 23. Publications: 1.
Replication data for impact evaluation of two large-scale forestry incentive programs in Guatemala
Open the record for dataset details and reuse information.
The dataset for the research "Evaluation of Digital Supply Chain Technology’s Impact on Sustainability Under the Moderate Effect of Supply Chain Dynamism: An Empirical Research in the Chinese Energy Supply Chain"
In recent years, the topic of digitalisation and sustainability of supply chains has become increasingly important. In addition, as the environmental dynamism becomes more complex, it is essential to explore how technologies impacts on sustainability under the supply chain dynamism. Hence, there is a study to explore the relationship between technologies and sustainability under the supply chain dynamism in the energy supply chain. In this study, the author collects quantitative data from two Chinese companies, including China Resources Power Zhejiang Company and Hunan HuaDian Changsha Electric Co., Ltd. This is a questionnaire survey and it has 24 questions, including 3 general questions, 5 technologies dimension questions, 12 sustainability dimension questions and 4 supply chain dynamism questions. The author collected data from 30 May 2024 to 6 June May 2024, and there are totally 316 answers.
Evaluation of the impact of imprinted polymer particles on morphology and motility of breast cancer cells by using digital holographic cytometry
<p>Supplemented Videos used in "Evaluation of the impact of imprinted polymer particles on morphology and motility of breast cancer cells by using digital holographic cytometry"</p>
Data from: Using a participatory impact assessment framework to evaluate a community-led mangrove and fisheries conservation approach in West Kalimantan, Indonesia
<ol> <li>Community-based conservation (CBC) has been identified as a solution to biodiversity loss, climate change, and the reduction of rural poverty. The heterogeneity in social and economic inequalities often acts as a barrier to community engagement in resource management and further inhibits the distributional equity of social and ecological outcomes.</li> <li>This study presents a participatory impact assessment (PIA) framework that evaluated the outcomes of a cross-sector community-led conservation initiative. Community members involved in the program identified activities and outcomes for the Conservation Cooperative (CC), ranking the influence of the former on the latter as well as their daily life through multiple focus group discussions (FGDs). Participants were asked to rank the impact of activities on outcomes and the scale of the outcome which was totaled to identify the most impactful program activities and outcomes during the project period.</li> <li>Community members reported improved income, health, education and the creation of a locally-led natural resource management system. Members also reported improved crab harvest rates and reduced mangrove deforestation. Environmental outcomes identified by community members through the PIA were verified through a secondary spatial analysis and mud-crab independent fisheries monitoring.</li> <li>The results support the hypothesis that environmental NGOs need to consider a multi-dimensional view of human well-being, and that cross-sector integrated interventions may be effective at improving multiple outcomes.</li> <li>Future steps should focus on spatial replication of the CC program which will provide further insights by testing for differences in outcomes between villages, how those are impacted by preexisting social and ecological systems, and comparing outcomes between control sites that did not receive interventions.</li> </ol>
Data for: Evaluating the impact of physical frailty during ageing in wild chimpanzees (Pan troglodytes schweinfurthii)
<p>While declining physical performance is an expected consequence of aging, human clinical research has placed increasing emphasis on physical frailty as a predictor of death and disability in the elderly. We examined non-invasive measures approximating frailty in a richly-sampled longitudinal dataset on wild chimpanzees. Using urinary creatinine to assess lean body mass, we demonstrated moderate but significant declines in physical condition with age in both sexes. While older chimpanzees spent less of their day in the trees and feeding, they did not alter activity budgets with respect to travel or resting. There was little evidence that declining lean body mass had negative consequences independent of age. Old chimpanzees with poor lean body mass rested more often but did not otherwise differ in activity. Males, but not females, in poor condition were more likely to exhibit respiratory illness. Poor muscle mass was associated acutely with death in males, but it did not predict future mortality in either sex. While there may be some reasons to suspect biological differences in the susceptibility to frailty in chimpanzees versus humans, our data are consistent with recent reports from humans that lean, physically active individuals can successfully combat frailty.</p>
The Impact of Tool Configuration Spaces on the Evaluation of Configurable Taint Analysis for Android
<p>The data accompanying our ISSTA'2021 submission, <em>Rethinking Android Taint Analysis Evaluations: A Study of the Impact of Tool Configuration Spaces</em></p> <p> </p> <p>Structure:</p> <p><em>results</em>: contains the raw results output by AQL for the runs on Fossdroid and Google Play. Note that we wrote DroidBench results directly to CSV, so there are no "raw" results for them. Instead, see the summaries package. The collection of APKs for both datasets are also in this package.</p> <p><em>summaries</em>: contains CSV summaries of the three replications of our experiments on all three datasets (including examples of Amandroid's nondetermism on non-default configurations).</p> <p><em>datasets</em>: contains our FossDroid classified results and justifications. Please see the README.md in that package for more information.</p> <p><em>diagrams: </em>contains the graphs detailing the FlowDroid and DroidSafe configuration spaces, including their partial orders and disablement relationships.</p> <p><em>violations</em>: contains the records of violations of our partial orders.</p>
Data from: Evaluating the impact of historical climate and early human groups in the Araucaria Forest of Eastern South America
<p>It has been hypothesized that the Araucaria Forest in Southern Brazil underwent expansions in the past, driven either by human groups or by climate fluctuations of the Holocene and Pleistocene. Fossil pollen records of the Paraná Pine (<em>Araucaria angustifolia</em>), a dominant tree in that forest, provide some insights into when those may have occurred. Still, the timing of those expansions has never been estimated. To infer past range shifts and shed light on their main drivers, we employed next-generation DNA sequencing (ddRADseq), machine learning, and a comprehensive database of fossil pollen records in a study of historical demographic inference and paleo-distribution modeling of the Paraná Pine. We found that <em>A. angustifolia</em> comprises two populations expanding at different times: one in the Mantiqueira mountain chain, and the other in the southern Brazilian plateau. The Southern population began to expand during the Last Glacial Period ~70kya, long before human arrival in South America. Still, genetic analyses support that humans later impacted this population, resulting in lower genetic diversity, higher inbreeding, and high levels of gene flow over large distances with a weak pattern of isolation by distance. It is possible this resulted from human influence on seed dispersal and germination on the Southern Brazilian plateau. The Mantiqueira population, in contrast, expanded only recently (~3kya). This timing coincides with Holocene climatic changes and human settlements established further south, although, to date, there is little archeological evidence of human impact in the Mantiqueira. In addition, multitemporal species distribution models built from a combination of present-day and pollen records infer range expansion of the Araucaria Forest during glacial times until the cold humid HS1 event (~16kya), when the forest was most widespread, with no evidence of glacial refugia. The combination of genomic and spatial analyses suggests that both human and climatic controls played a role in the dynamics of the Araucaria Forest.</p>
FIGURE 3 in Evaluation of three pesticides against phytophagous mites and their impact on phytoseiid predators in an eggplant open-field
FIGURE 3: General mean abundance per eggplant leaf (± SE) of Tetranychus urticae (a), Phytoseilus persimilis (b), Polyphagotarsonemus latus (c) and other phytoseiid species (d) in control, fenbutatin oxide (F.O.), acetamiprid (aceta.) and deltamethrin (delta.) treatments.
FIGURE 4 in Evaluation of three pesticides against phytophagous mites and their impact on phytoseiid predators in an eggplant open-field
FIGURE 4: Mean abundance per eggplant leaf (± SE) of Tetranychus urticae (continuous line) and Phytoseiulus persimilis (dotted line) observed during experiments in control (a) treated with water (gray arrows), fenbutatin oxide (b), acetamiprid (c) and deltamethrin (d) (black arrows).
Following Darwin's footsteps: Evaluating the impact of an activity designed for elementary school students to link historically important evolution key concepts on their understanding of natural selection
<p>While several researchers have suggested that evolution should be explored from the initial years of schooling, little information is available on effective resources to enhance elementary school students' level of understanding of evolution by natural selection (LUENS). For the present study, we designed, implemented and evaluated an educational activity planned for fourth graders to explore concepts and conceptual fields that were historically important for the discovery of natural selection. Observation field notes and students' productions were used to analyse how the students explored the proposed activity. Additionally, an evaluation framework consisting of a test, the evaluation criteria and the scoring process was applied in two fourth-grade classes to estimate elementary school students' LUENS before and after engaging in the activity. Our results suggest that our activity allowed students to effectively link all of the key concepts in the classroom and produced a significant increase in their LUENS. These results indicate that our activity had a positive impact on students' understanding of natural selection. They also reveal that additional activities and minor fine-tuning of the present activity are required to further support students' learning about the concept of differential reproduction. We also observed a low level of teleological predictions for both pre- and post-tests. --</p>
Evaluation of the impact of chemical control on the ecology of Rattus norvegicus of an urban community in Salvador, Brazil
<p>dataset of rodent trapping in a pre/post-intervention scheme. Check publication of the same name for details on the study design. File contains complete comprehensive codebook.</p>
Evaluating the impact of filler size and filler content on the stiffness, strength, and toughness of polymer nanocomposites using coarse-grained molecular dynamics: dataset
<div><strong>Abstract:</strong></div> <div>(from [1])</div> <div>Their great versatility makes polymer nanocomposites an important class of engineering materials. In order to gain detailed insights into the nanoscale mechanisms underlying their macroscopic mechanical properties, molecular dynamics (MD) simulations are a valuable tool to complement experimental studies. In this work, we modify the analytical potential functions of an efficient bead-spring model representing a generic polymer nanocomposite to account for the breaking of covalent bonds. We perform uniaxial tensile simulations of double-notched specimens and validate the model using experimental trends for overall stiffness, strength, and toughness. First, we study the effects of sample size, notch geometry, strain rate, temperature, and molar mass for the pure thermoplastic matrix material. Second, we analyze the influence of filler size and filler content on the mechanical behavior of the polymer nanocomposite. With this study, we show that in both the development of new materials and the optimization of established materials, it is possible to gain important preliminary insights into the effects of pertinent material characteristics with a simple MD setup, which can then be further refined by increasing the complexity of the material description and the boundary conditions. </div> <div> </div> <div> </div> <div><strong>Contact:</strong></div> <div>Felix Weber</div> <div>Institute of Applied Mechanics</div> <div>Friedrich-Alexander-Universität Erlangen-Nürnberg</div> <div>Egerlandstr. 5</div> <div>91058 Erlangen</div> <div>Germany</div> <div> </div> <div> </div> <div><strong>Software:</strong></div> <div>All simulations were performed with LAMMPS [2,3] (version 23 June 2022, patch_23Jun2022_update3) </div> <div> </div> <div>Compiler: GNU C++ 11.2.0 with OpenMP not enabled</div> <div>C++ standard: C++11</div> <div> </div> <div>Active compile time flags:</div> <div>-DLAMMPS_GZIP</div> <div>-DLAMMPS_SMALLBIG</div> <div> </div> <div>Installed packages:</div> <div>BPM CLASS2 DPD-BASIC EXTRA-DUMP EXTRA-FIX EXTRA-MOLECULE INTEL KSPACE MANYBODY </div> <div>MC MISC MOLECULE MOLFILE MPIIO NETCDF OPT </div> <div> </div> <div>Moreover, we employ a self-avoiding random walker [4,5] implemented in MATLAB [6] for the initial positioning of the polymer chains and nanoparticles.</div> <div> </div> <div> </div> <div><strong>License:</strong></div> <div>Creative Commons Attribution 4.0 International</div> <div> </div> <div> </div> <div><strong>Context:</strong></div> <div>This dataset contains the results presented in [1] and the necessary data to obtain those.</div> <div> </div> <div> </div> <div><strong>Content:</strong></div> <div>Throughout this data set, LAMMPS lj units are used. The files to reproduce our simulations and their results are structured as follows:</div> <div>- 01_neat: Neat polymer systems</div> <div> - 01_EQU: Equilibration simulations</div> <div> - 02_UT: Uniaxial tensile simulations, including the notch insertion (token "initcrack")</div> <div> - 1.1: Simulations for different sample sizes/numbers of chains (token "chains") at constant molar mass/number of beads per chain</div> <div> - 1.3: Simulations for different widths of the Dirichlet boundary (token "diri")</div> <div> - 2.1: Simulations for different critical bond lengths (token "bondcrit")</div> <div> - 2.2: Simulations for different bond breaking probabilities (token "bondcprob")</div> <div> - 3.1: Simulations for different crack widths (token "crackwidth")</div> <div> - 3.2: Simulations for different crack lengths (token "crackdepth")</div> <div> - 4: Simulations for different strain rates (token "strainrate")</div> <div> - 5: Simulations for different temperatures (token "tem")</div> <div> - 6: Simulations for different molar masses/numbers of beads per chain (token "chain-len")</div> <div>- 02_PNC: Polymer nanocomposite (PNC) systems </div> <div> - 01_EQU: Equilibration simulations</div> <div> - 02_UT: Uniaxial tensile simulations for different filler radii (token "rF") and filler contents/numbers (token "nF"), including the notch insertion (token "initcrack")</div> <div>- parameter_study: Postprocessing of the MD results </div> <div> - parameter_study.xlsx: Overview of the simulations with their respective parameters and statistical analysis of stiffness, strength, and toughness from filtered stress-strain curves (Savitzky-Golay filter applying a linear polynomial and frame length 21)</div> <div> - .csv files of the single sheets of parameter_study.xlsx:</div> <div> - samples.csv: Individual specimens</div> <div> - averages.csv: Statistical analysis of the different samples corresponding to one batch</div> <div> </div> <div>Each simulation directory contains:</div> <div>- LAMMPS input script (*.in) of the simulation</div> <div>- input.prm: Input parameters of the simulation (read by the input script)</div> <div>- LAMMPS data file (*.data, molecular style) of the investigated sample</div> <div>- LAMMPS_out: Resulting LAMMPS data files, log files and simulation results in tabulated form</div> <div> - additional files for the tensile tests: </div> <div> - brokenbonds.dat: Fix print output for fix brokenbondsprint (step time brokenbondsPerStep brokenbondsSum)</div> <div> - stressstrain.dat: Time-averaged data for fix dumpOpt (step v_strain_xx v_OBSstrain_xx v_Piola_xx) with the local strain at the crack tip v_OBSstrain_xx</div> <div> - thermo_out.Dat: Thermodynamic output in condensed tabulated form</div> <div> - thermo_out_SG.Dat: Thermodynamic output in condensed tabulated form, filtered by a Savitzky-Golay filter (linear polynomial, frame length 21)</div> <div> - thermo_out_STD.Dat: Standard deviation between the filtered and unfiltered data</div> <div>- job.out: Simulation log file</div> <div>- meta.info: Meta data of the simulation run</div> <div> </div> <div>Naming convention:</div> <div>- 01_neat: GTPm-[number of chains]_chains-[number of beads per chain]_chain_len-[temperature]_tem-[parameter value]_[parameter]-[sample]</div> <div> - [parameter]: Parameter studied, i.e. diri/bondcrit/bondcprob/crackwidth/crackdepth/strainrate/tem (see above)</div> <div> - [parameter value]: Value of the parameter studied</div> <div> - [sample]: Sample ID</div> <div>- 02_PNC: GTPm_rF-[filler radius]_nF-[number of fillers]_[sample]</div> <div> - [sample]: Sample ID</div> <div> </div> <div>Output quantities (columns of *.Dat files):</div> <div>- Step: time step</div> <div>- Time: time</div> <div>- TotEng: total energy</div> <div>- PotEng: potential energy</div> <div>- KinEng: kinetic energy</div> <div>- E_pair: pair energy</div> <div>- E_bond: bond energy</div> <div>- E_angle: angle energy</div> <div>- E_dihed: dihedral energy</div> <div>- Temp: temperature</div> <div>- Press: hydrostatic pressure</div> <div>- Pxx: xx component of pressure tensor</div> <div>- Pyy: yy component of pressure tensor</div> <div>- Pzz: zz component of pressure tensor</div> <div>- Pxy: xy component of pressure tensor</div> <div>- Pxz: xz component of pressure tensor</div> <div>- Pyz: yz component of pressure tensor</div> <div>- Volume: volume of simulation box</div> <div>- Lx: box length in x direction</div> <div>- Ly: box length in y direction</div> <div>- Lz: box length in z direction</div> <div>- Density: mass density</div> <div>- c_RG: radius of gyration</div> <div>- c_RG[1]: squared radius of gyration tensor (xx component)</div> <div>- c_RG[2]: squared radius of gyration tensor (yy component)</div> <div>- c_RG[3]: squared radius of gyration tensor (zz component)</div> <div>- c_RG[4]: squared radius of gyration tensor (xy component)</div> <div>- c_RG[5]: squared radius of gyration tensor (xz component)</div> <div>- c_RG[6]: squared radius of gyration tensor (yz component)</div> <div>- c_bondave[1]: bond energy averaged over all atoms</div> <div>- c_bondave[2]: bond distance averaged over all atoms</div> <div>- c_bondave[3]: squared bond distance averaged over all atoms</div> <div>- c_angleave[1]: angle energy averaged over all atoms</div> <div>- c_angleave[2]: angle averaged over all atoms degree</div> <div>- c_angleave[3]: cosine of angle</div> <div>- c_angleave[4]: squared cosine of angle</div> <div>- c_MSD[1]: mean squared displacement x-direction</div> <div>- c_MSD[2]: mean squared displacement y-direction</div> <div>- c_MSD[3]: mean squared displacement z-direction</div> <div>- c_MSD[4]: total mean squared displacement</div> <div>- c_COM[1]: x coordinate of center of mass</div> <div>- c_COM[2]: y coordinate of center of mass</div> <div>- c_COM[3]: z coordinate of center of mass</div> <div>- v_strain_xx: xx component of engineering strain tensor </div> <div>- v_strain_yy: yy component of engineering strain tensor </div> <div>- v_strain_zz: zz component of engineering strain tensor </div> <div>- v_vMisesequivstress: von Mises equivalent stress</div> <div>- v_Piola_xx: xx component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_yy: yy component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_zz: zz component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_xy: xy component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_xz: xz component of the virial stress tensor normalized by the initial volume</div> <div>- v_Piola_yz: yz component of the virial stress tensor normalized by the initial volume</div> <div>- v_strain_xy: xy component of engineering strain tensor </div> <div>- v_strain_xz: xz component of engineering strain tensor </div> <div>- v_strain_yz: yz component of engineering strain tensor </div> <div> </div> <div> </div> <div><strong>References:</strong></div> <div>[1] F. Weber, V. Dötschel, P. Steinmann, S. Pfaller, M. Ries, "Evaluating the impact of filler size and filler content on the stiffness, strength, and toughness of polymer nanocomposites using coarse-grained molecular dynamics", Engineering Fracture Mechanics, vol. 307, p. 110270, 2024.</div> <div>[2] S. Plimpton, "Fast parallel algorithms for short-range molecular dynamics", Journal of computational physics, vol. 117, no. 1, pp. 1-19, 1995.</div> <div>[3] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, S. J. Plimpton, "LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales", Computer Physics Communications, vol. 271, p. 108171, 2022.</div> <div>[4] V. Dötschel, S. Pfaller, and M. Ries, "Studying the mechanical behavior of a generic thermoplastic by means of a fast coarse-grained molecular dynamics model", Polymers and Polymer Composites, vol. 31, pp. 1–11, 2023.</div> <div>[5] M. Ries, V. Dötschel, J. Seibert, and S. Pfaller, A self-avoiding random walk algorithm (SARW) for generic thermoplastic polymers and nanocomposites, Zenodo, 2022, https://doi.org/10.5281/zenodo.6245699.</div> <div>[6] The MathWorks, Inc., "Matlab. the language of technical computing", https://de.mathworks.com/help/matlab/.</div> <div> </div> <div> </div> <div><strong>Funding:</strong></div> <div>The authors gratefully acknowledge funding by various sources:</div> <div>The overall research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 377472739/GRK 2423/2-2023. Sebastian Pfaller is furthermore funded by the DFG projects 396414850 (Individual Research Grant 'Identifikation von Interphaseneigenschaften in Nanokompositen') and 505866713 together with the Agence nationale de la recherché (ANR, French Research Agency) – ANR-22-CE92-0049 (Individuel Research Grant 'BIO ART'). In addition, scientific support and HPC resources have been provided by the Erlangen National High Performance Computing Center (NHR@FAU) of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) under the NHR project b136dc. NHR funding is provided by federal and Bavarian state authorities. NHR@FAU hardware is partially funded by the DFG project 440719683.</div>
Raw data for: Evaluating the impact of alyssum flower strips on biological control of key pests in flue-cured tobacco agroecosystems
<p>Flue-cured tobacco, <em>Nicotiana tabacum</em> (L.) is often attacked by various pests such as aphids, whiteflies, and tobacco budworms. Insecticide application has been the primary method in managing these pests in Yunnan province. However, it is necessary to look for more sustainable strategies that can help control pests. In this context, conservation biological control is a highly promising alternative, involving the cultivation or conservation of flowering plants within the agricultural ecosystem to attract and support natural enemies. The objective of this study was to evaluate the potential of alyssum, <em>Lobularia maritima</em> (L.) Desv. in attracting natural enemies and managing pests in flue-cures tobacco cultivation. The study conducted two field experiments over successive years, each with two treatments and three replicates, arranged in a completely randomized design. The treatments were (1) tobacco monoculture, and (2) tobacco intercropped with alyssum flower strips. The population density of natural enemies and pests was monitored weekly throughout the study period. The results showed that the presence of alyssum flowers in the tobacco + alyssum treatment significantly increased the abundance of generalist predators such as syrphids, rove beetles, carabids, <em>Orius</em> sp., and spiders during both experiments. This increase in predator population led to a substantial reduction in tobacco pests, particularly aphids. Intercropping alyssum with tobacco can serve as an effective strategy for managing pests specific to the Nicotiana plant, as well as addressing the limited availability of approved insecticides for this crop. This approach may help to mitigate pest-related issues and reduce the reliance on insecticides in tobacco cultivation, contributing to more sustainable pest management practices.</p>
Dataset for evaluating rooftop photovoltaic solar panels impact on urban temperature at city scale
<p>This dataset contains simulation outputs from the WRF/BEP+BEM v4.3.3 model, evaluating the impact of rooftop photovoltaic solar panels on urban temperatures in five cities: Kolkata, Austin, Sydney, Athens, and Brussels. The model uses one parent domain and two nested domains with resolutions of 18 km, 6 km, and 2 km, focusing on the 2 km resolution. Simulations cover the summer periods of each city, including panel surface temperature and urban state variables data. The dataset represents diverse climate types: tropical wet and dry (Kolkata), Mediterranean (Athens), moderate oceanic<em> </em>(Brussels), and subtropical humid (Sydney and Austin).</p>
Hybrid deep learning framework for evaluating field evapotranspiration considering the impact of soil salinity
<p>Entitled “A novel hybrid deep learning framework for evaluating field evapotranspiration considering the impact of soil salinity” for possible publication in Water Resources Research.</p> <p>Data:</p> <p>The Salinized Farmland Flux Station sites are located in the typical irrigated agricultural area of the arid continental monsoon region in northwest China.In this study, we used data from four flux tower located in saline farmland: two for maize (MZ1, MZ2) and two for sunflower (SF1, SF2).</p> <p>For each site, we collected the following variables at half-hourly temporal resolution: (i) latent heat (<em>LE</em>, W m<sup>-2</sup>) fluxes, serving as a direct measure representing the energy component of <em>ET</em> (mm h<sup>-1</sup>), (ii) net radiation (<em>R<sub>n</sub></em>, W m<sup>-2</sup>), (iii) ground heat flux (<em>G</em>, W m<sup>-2</sup>), (iv) solar irradiance (<em>R<sub>s</sub></em>, W m<sup>-2</sup>), (v) air temperature (<em>T</em><sub>a</sub>, °C), (vi) vapor pressure deficit (<em>VPD</em>, KP<sub>a</sub>), (vii) wind speed (<em>U<sub>s</sub></em>, m s<sup>-1</sup>), (viii) relative humidity (<em>RH,</em> %), and (ix) atmospheric carbon dioxide concentration (<em>C<sub>a</sub></em>, mg m<sup>-3</sup>). During the crop growth period, field in-situ measurements of soil and vegetation data from these farmlands are conducted approximately every 10 days. </p> <p>Code:</p> <p>All the codes were executed in Python. The provided hybrid deep learning model code can be run on Jupyter Notebook.</p>
Evaluating the Impact of Triple Compound Therapy on Relapse Frequency and Quality of Life in Children with Severe Atopic Dermatitis: A Phase II Randomised Clinical Trial
<p>Datasets and analysis from A multi-centre, randomized controlled trial, on pediatric Atopic Dermatitis, conducted at Red Cross and Walter Sisulu Hospitals. The study is entitled Evaluating the Impact of Triple Compound Therapy on Relapse Frequency and Quality of Life in Children with Severe Atopic Dermatitis: A Phase II Randomised Clinical Trial.</p>
Data from Evaluating the impact of climate communication activities by scientists: what is known and necessary?
<p>This dataset contains three text files in RIS format and two pdf files. They represent the analysis for "Evaluating the impact of climate communication activities by scientists: what is known and necessary?" (https://doi.org/10.5194/gc-7-91-2024). </p> <p>There are three stages</p> <ol> <li>The initial search: <ul> <li> <p>The <em>Literature search PE on CC.pdf</em> file provides the initial search terms</p> </li> <li> <p>The <em>Search PE on CC 'Outreach added'.pdf</em> file expands that initial search to include outreach</p> </li> <li>The <em>Initial search (outreach included).ris</em> file contains references to all 819 articles included in the initial search</li> </ul> </li> <li>Excluded first round (based on title and abstract) <ul> <li>The <em>Excluded first round.ris</em> file contains references to all 755 articles excluded in the first round</li> </ul> </li> <li>Included papers <ul> <li>The <em>Included papers.ris </em>file contains references to all 7 articles that were included in the final analysis</li> </ul> </li> </ol>
The dataset of "Evaluation of Digital Supply Chain Technology's Impact on Sustainability Under the Moderate Effect of Supply Chain Dynamism: An Empirical Research in the Chinese Energy Supply Chain"
<p>This dataset involves the data from the questionnaire, which come from the project "Evaluation of Digital Supply Chain Technology’s Impact on Sustainability Under the Moderate Effect of Supply Chain Dynamism: An Empirical Research in the Chinese Energy Supply Chain". It comprises three dimensions questions, technology, sustainability and supply chain dynamism. The datas come from two Chinese energy firms, <span>China Resources Power Zhejiang Company and Hunan HuaDian Changsha Electric Co., Ltd.</span></p>
ScienceDex guides
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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.