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38 results for “Chemical mechanism”
Swiss public's acceptance and sustainability perceptions of food produced with chemical, digital and mechanical weed control measures and the influence of information source on technology perception in agriculture
<p><span>This data was obtained from an online survey conducted with the Swiss public from the two biggest language regions (German and French) in Switzerland. The survey was conducted in February 2023. Participants were recruited through a professional panel provider and quotas were used for age, gender and language region. The final sample contained </span><span>542 respondents. </span><span>In the first part of the survey, respondents provided basic sociodemographic information. In the second part, their sustainability perceptions regarding four different weed management practices (full-surface spraying, hoeing machine, spot spraying and precise spraying) were investigated. Respondents were then assigned to one of five information source groups, in which information on a hoeing and a milking robot was presented, using 5 different information sources (male/female farmer, male/female scientist, no source). Technology perception was assessed using several questions and aspects. Finally, respondents answered several questions assessing their attitudes towards the perception of farmers, food technology neophobia, chemophobia and the importance of naturalness. The survey can be used and adapted to different contents, aiming to investigate public perception of smart farming technologies and the influence of information sources on technology perception. </span></p>
EDGAR v5.0 emissions inventory speciated for the MOZART chemical mechanism
<p>Emission inventories need to be adapted to be used in chemical transport models (CTMs). They usually need ad-hoc preprocessing based on the chemical mechanism used in the CTM, including speciation of non-methane volatile organic compounds (NMVOCs). </p> <p><strong>Here we provide monthly <a href="https://edgar.jrc.ec.europa.eu/index.php/dataset_ap50">EDGAR v5.0 </a> global air pollutant emissions for the year 2015, speciated for the <a href="https://gmd.copernicus.org/articles/3/43/2010/">MOZART</a> chemical mechanism.</strong></p> <p><strong>The dataset is also ready to use in <a href="https://ruc.noaa.gov/wrf/wrf-chem/">WRF-Chem </a>atmospheric model with MOZART-MOSAIC options.</strong></p> <p>Emission files are provided as individual NetCDF files for each pollutant containing anthropogenic sector emissions as individual variables.</p> <p>In the folder you will find:</p> <ul> <li><strong>edgarv5_MOZART_data.tar.gz</strong>: EDGAR v5.0 monthly emissions for the year 2015 (NetCDFformat), speciated for MOZART chemical mechanism. Both total and individual sector emissions are included in each file. </li> <li><strong>edgarv5_MOZART_MOSAIC.inp</strong>: Input file for anthroemiss preprocessing tool for MOZART-MOSAIC options in WRF-Chem.</li> <li><strong>technical_note_EDGARv5_MOZART.pdf </strong>: documentation.</li> </ul> <p>These files are also ready-to be used in <a href="https://www2.acom.ucar.edu/wrf-chem/wrf-chem-tools-community">WRF-Chem anthro-emiss preprocessing tool</a> with the MOZART-MOSAIC options.</p> <p>Accompanying code for preparing the dataset can be found at repository: <a href="https://doi.org/10.5281/zenodo.6145846">https://doi.org/10.5281/zenodo.6145846</a></p> <p>For more detail, please refer to the technical documentation (technical_note_EDGARv5_MOZART.pdf).</p> <p> </p> <p> </p>
Model output from CAABA/MECCA study "Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)"
<p>This dataset includes the main data obtained during the study "Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)" (DOI:10.5194/gmd-2023-102). The updated model code can be found at zenodo.org (DOI:10.5281/zenodo.7944174). The data can be used to replicate the results shown in the manuscript. Contained are results produced by the updated CAABA/MECCA (version 4.7.0) and reference data from CAABA/MECCA version 4.5.5. In version 4.7.0, new biogenic and anthropogenic species are introduced to the model (limonene and long-chained alkanes) with refined multiphase chemistry, while new reaction pathways are added for existing compounds (isoprene, benzene and IEPOX). The output is generated to evaluate model results in terms of temperature- and NOx-dependency.</p>
QM7-X: A comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
<p>Here, we introduce QM7-X, a comprehensive dataset of > 40 physicochemical properties for ~4.2 M equilibrium and non-equilibrium structures of small organic molecules with up to seven non-hydrogen (C, N, O, S, Cl) atoms. To span this fundamentally important region of chemical compound space (CCS), QM7-X includes an exhaustive sampling of (meta-)stable equilibrium structures---comprised of constitutional/structural isomers and stereoisomers, e.g., enantiomers and diastereomers (including cis-trans-and conformational isomers)---as well as 100 non-equilibrium structural variations thereof to reach a total of ~4.2 M molecular structures. Computed at the tightly converged quantum-mechanical PBE0+MBD level of theory, QM7-X contains global (molecular) and local (atom-in-a-molecule) properties ranging from ground state quantities (such as atomization energies and dipole moments) to response quantities (such as polarizability tensors and dispersion coefficients). By providing a systematic, extensive, and tightly converged dataset of quantum-mechanically computed physical and chemical properties, we expect that QM7-X will play a critical role in the development of next-generation machine-learning based models for exploring greater swaths of CCS and performing <em>in silico</em> design of molecules with targeted properties.</p> <p>The dataset is provided in eight HDF5 based files (compressed in .XZ files). One can also find here a README file with technical usage details and examples of how to access the information stored in the dataset (see createDB.py). </p> <p>*The paper explaining the generation of data stored in QM7-X can be found in <em>Sci Data</em> 8, 43 (2021). DOI: 10.1038/s41597-021-00812-2 . arXiv: https://arxiv.org/abs/2006.15139 .</p>
The Pan-Canadian Chemical Library: A Mechanism to Open Academic Chemistry to High-Throughput Virtual Screening
<h1>Pan-Canadian Chemical Library</h1> <p>This Zenodo repository contains the cheap and druglike subset of the Pan-Canadian Chemical Library (PCCL) project. For more information, visit <a href="https://pccl.thesgc.org/" rel="nofollow">https://pccl.thesgc.org</a>.</p> <h2>PCCL library</h2> <p>The PCCL library is splitted by reaction, then by number of heavy atoms. Two types of files are available in zip archives:</p> <ul> <li>The SMILES format files, with the SMILES string and their product name,</li> <li>The CSV format file, with all the information generated during their enumeration: reagents, druglike properties, etc.</li> </ul> <p>Note: Purchasability is defined according to two integers: 1 for products only composed of BB-50 reagents, and 2 for products composed of BB-40 or BB-50 reagents. Read more about the meaning of these reagents groups in the article below.</p> <h2>Citation</h2> <p>If you find the PCCL useful or if you use it, please cite our paper:</p> <p>Bedart, C. <em>et al.</em> The Pan-Canadian Chemical Library: A mechanism to open academic chemistry to high-throughput virtual screening. Scientific Data 11, (2024).<br>doi: <a title="10.1038/s41597-024-03443-5" href="https://www.nature.com/articles/s41597-024-03443-5">10.1038/s41597-024-03443-5</a></p> <p> </p> <p> </p>
Image segmentation masks for curved arrows on molecular images from chemical reaction mechanism images
<p>The dataset presented herein is designed as a ground truth for image segmentation tasks focused on noise extraction in Optical Chemical Structure Recognition (OCSR) processes. It comprises 73 manually extracted and annotated images from real reaction mechanism images, along with 5320 synthetic molecular images generated using RDKit, each featuring computer-drawn curved arrows on random locations on the molecular image pertinent to their respective tasks. Curved arrows are prevalent in chemical reaction mechanism images and significantly impact the accuracy of molecular identity recognition. This dataset aims to enhance OCSR tasks by enabling the pretreatment of molecular images to remove noise, thereby improving molecular recognition accuracy.</p>
Pollen chemical and mechanical defences restrict host-plant use by bees
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Input data for performing chemistry coupled PALM model system 6.0 simulations with different chemical mechanisms
<p>The data presented here comprised of input files that have been used to run chemistry coupled PALM model system 6.0 simulations for the article entitled "Development of an atmospheric chemistry model coupled to the PALM model system 6.0: Implementation and first applications". In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence resolving PALM model system 6.0.</p> <p>List of the input data required for performing chemistry model simulations with different chemical mechanisms is given below. A text file comprised of measured concentrations of NO, NO<sub>2</sub> and O<sub>3</sub> is also added.</p> <ol> <li>Fortran parameter (PARIN) files for four mechanisms and one meteorology-only simulation.</li> <li>Static file</li> <li>Dynamic file</li> <li>Two files (shortwave and longwave input data) for rrtmg radiation model</li> <li>Observation from two air quality stations in Berlin, Germany .</li> <li>PALM model source code revision 4450 (palm_trunk_rev-4450.tar.gz)</li> <li>PALM model source code revision 4601 (palm_trunk_rev-4601.tar.gz)</li> </ol> <p>The PALM model system 6.0 revision 4451 and 4601 (for chemistry flux profiles only) have been used for these simulations. </p>
Tailoring Ti Grade 2 and TNTZ alloy surfaces in a two-step mechanical-chemical modification
<p>This record contains all files generated in the preparation process of the following publication:</p> <p>Agnieszka Kowalczyk, Donata Kuczyńska-Zemła, Agata Sotniczuk, Klaudia Anuszewska and Halina Garbacz,<br> "Tailoring Ti Grade 2 and TNTZ alloy surfaces in a two-step mechanical-chemical modification", submitted to Surface Engineering.</p> <p><br> Designations:<br> Ti alloy - Ti-29Nb-13Ta-4,6Zr alloy (TNTZ)<br> G - sample grinded on #600 grit abrasive paper<br> S_1,2 - sample shot peened with 90-150 µm shots, under pressure of 0.2 MPa<br> S_1,3 - sample shot peened with 90-150 µm shots, under pressure of 0.3 MPa<br> S_1,4 - sample shot peened with 90-150 µm shots, under pressure of 0.4 MPa<br> S_1,5 - sample shot peened with 90-150 µm shots, under pressure of 0.5 MPa<br> S_2,4 - sample shot peened with 150-250 µm shots, under pressure of 0.4 MPa<br> S_2,5 - sample shot peened with 150-250 µm shots, under pressure of 0.5 MPa<br> SE_1,2 - sample shot peened with 90-150 µm shots, under pressure of 0.2 MPa and etched in a solution of 3% hydrofluoric acid (HF)<br> SE_1,3 - sample shot peened with 90-150 µm shots, under pressure of 0.3 MPa and etched in a solution of 3% hydrofluoric acid (HF)<br> SE_1,4 - sample shot peened with 90-150 µm shots, under pressure of 0.4 MPa and etched in a solution of 3% hydrofluoric acid (HF)<br> SE_1,5 - sample shot peened with 90-150 µm shots, under pressure of 0.5 MPa and etched in a solution of 3% hydrofluoric acid (HF)<br> SE_2,4 - sample shot peened with 150-250 µm shots, under pressure of 0.4 MPa and etched in a solution of 3% hydrofluoric acid (HF)<br> SE_2,5 - sample shot peened with 150-250 µm shots, under pressure of 0.5 MPa and etched in a solution of 3% hydrofluoric acid (HF)<br> HV - Vickers hardness<br> SEM - Scanning Electron Microscopy<br> R - roughness<br> W - wettability</p> <p><br> Folders content:<br> Hardness - contains files with data obtained from hardness tests using a Falcon 500 hardness tester with a Vickers indenter at a load of 1.96 N (HV0.2)<br> Roughness - contains files from topography analysis obtained using a Wyko NT9300 optical profilometer for various scan areas<br> SEM - contains images of samples surfaces from Hitachi SU8000 and Hitachi SU70 Scanning Electron Microscopes <br> Wettability - contains files with data obtained from wettability tests using a DataPhysics OCA 25 goniometer with the sessile drop method</p> <p>This research was funded in part by National Science Centre, Poland [Grant no. 2022/45/B/ST5/03398].</p> <p> </p>
Assessing chemical mechanisms underlying the effects of sunflower pollen on a gut pathogen in bumble bees
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Unwanted loss of volatile organic compounds (VOCs) during in situ chemical oxidation sample preservation: Mechanisms and solutions
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Data from: The variation of grain size distribution in rock granular material in seepage process considering the mechanical-hydrological-chemical coupling effect: An experimental research
<p>As a common solid waste in geotechnical engineering, rock granular material should be properly treated and recycled. Rock granular material often coexists with water when it is used as the filling material in geotechnical engineering. Water flowing in rock granular materials is a complex progress with the mechanical-hydrological-chemical (MHC) coupling effect, i. e. the water scours in the gaps and spaces in the rock granular material structure, produces chemical reactions with rock grains, rock grains squeeze each other under the water pressure and compression leading re-breakage and producing secondary rock grains, the fine rock grains are migrated with water and rushed out. In this process, rock grain size distribution (GSD) changes, it affects the physical and mechanical characteristics of the rock granular materials, and even influences the seepage stability of the rock granular materials. To study the variation of GSD in the rock granular material considering the MHC coupling effect after the seepage process, seepage experiments of rock grain samples are carried out and analyzed in this paper. The result is expected to have a positive impact on further studies of the properties of the rock granular material.</p>
STUDY OF PHYSICAL-CHEMICAL AND MECHANICAL PROPERTIES OF NEW DENTAL SEALANTS FORMULATIONS
<p><span><span><span>Data from the tests reported in the article "STUDY OF PHYSICAL-CHEMICAL AND MECHANICAL PROPERTIES OF NEW FORMULATIONS OF DENTAL SEALANTS".</span></span> Revista Cubana de Estomatología<span><span>.</span></span></span></p> <p>Datos de los ensayos reportados en el artículo "ESTUDIO DE PROPIEDADES FÍSICO-QUÍMICAS Y MECÁNICAS DE NUEVAS FORMULACIONES DE SELLANTES DENTALES". Revista Cubana de Estomatología.</p>
Code in support of: Physical and chemical mechanisms that influence the electrical conductivity of lignin-derived biochar
<p>Lignin-derived biochar is a promising, sustainable alternative to petroleum-based carbon powders (e.g., carbon black) for electrode and energy storage applications. Prior studies of these biochars demonstrate that high electrical conductivity and good capacitive behavior are achievable. These studies also show high variability in electrical conductivity between biochars (~10^-2-10^2 S/cm). The underlying mechanisms that lead to desirable electrical properties in these lignin-derived biochars are poorly understood. In this work, we examine the causes of the variation in conductivity of lignin-derived biochar to optimize the electrical conductivity of lignin-derived biochars. To this end, we produced biochar from three different lignins, a whole biomass source (wheat stem), and cellulose at two pyrolysis temperatures (900 C, 1100 C). These biochars have a similar range of conductivities (0.002 to 18.51 S/cm) to what has been reported in the literature. Results from examining the relationship between chemical and physical biochar properties and electrical conductivity indicate that decreases in oxygen content and changes in particle size are associated with increases in electrical conductivity. Lignin isolated with an acidification process yielded biochar with higher electrical conductivity than lignin isolated with sulfate processes. These findings indicate how lignin composition and processing may be further selected and optimized to target specific energy-related applications.</p>
Pore-scale modeling and investigation on thermal-hydro-mechanical-chemical coupled rock dissolution and fracturing process
<p>Attached files include the executable file of the pore-scale multi-field coupled LBM-DEM program written by C language, post-processing programs to record the reactive surface area and reactive temperature written by MATLAB, and the simulation results of rock acid fracturing with 20MPa at the injection hole.</p>
Salivary chemical barrier proteins in Oral Squamous Cell Carcinoma – Alterations in the defense mechanism of the oral cavity
<p>Oral squamous cell carcinoma (OSCC) is one of the most frequent type of head and neck cancers. Despite the genetic and environmental risk factors, OSCC is also associated with microbial infections and/or dysbiosis. The secreted saliva serves as the chemical barrier of the oral cavity and since OSCC can alter the protein composition of saliva, our aim was to analyze the effect of OSCC on the salivary chemical barrier proteins. Publicly available datasets regarding the analysis of salivary proteins from patients with OSCC and controls were collected and examined in order to identify differentially expressed chemical barrier proteins. The network analysis and gene onthology (GO) classification of the differentially expressed chemical barrier proteins were performed, as well. 127 proteins showing different expression pattern between the OSCC and control groups were found. The protein-protein interaction network of up- and down-regulated proteins were constructed and analyzed. The main hub proteins (IL-6, IL-1B, IL-8, TNF, APOA1, APOA2, APOB, APOC3, APOE, and HP) were identified and the enriched GO terms were examined. Our study highlighted the importance of the chemical barrier of saliva in the development of OSCC.</p>
Chemical and Mechanical Angioplasty for Vasospasm (SAVEBRAIN)
ClinicalTrials.gov study NCT05268445. IPD Sharing: NO. Countries: 1. Publications: 0.
Physical and Chemical Study of Atherosclerosis Mechanisms
ClinicalTrials.gov study NCT01700075. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Code in support of: Physical and chemical mechanisms that influence the electrical conductivity of lignin-derived biochar
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Data from: The variation of grain size distribution in rock granular material in seepage process considering the mechanical-hydrological-chemical coupling effect: An experimental research
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OpenNeuro
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