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2,318 results for “Synthesis”
Laccases from Pleurotus ostreatus Applied to the Oxidation of Furfuryl Alcohol for the Synthesis of Key Compounds for Polymer Industry
<p>Laccases are oxidative enzymes with high synthetic potential. In this work, their value in biocatalysis is shown through the green and selective oxidation of furfuryl alcohol into furfural with the aid of mediators. The influence of different parameters, such as pH, enzyme/mediator composition, buffer type, cosolvent tolerance, and reaction times, is investigated. Under the optimal conditions, 20 mol % of TEMPO as mediator and 5.8 U mL<sup>−1</sup> of laccases POXC and POXA1b from <em>Pleurotus ostreatus</em>, quantitative production of furfural is attained after 16 h. POXC laccase stands out for its ability to catalyze the reaction at pH 6.5, whereas POXA1b is notable for its high stability. Furfural conversions reach excellent values (95 %) after 72 h using only 5 mol % of TEMPO at 100 mM. Furthermore, furfuryl alcohol bioamination is achieved by employing the amine transaminase from <em>Chromobacterium violaceum</em>, providing furfuryl amine, a key compound for the polymer industry, through a one-pot sequential approach.</p>
Enzymatic Cascade for the Synthesis of 2,5-Furandicarboxylic Acid in Biphasic and Microaqueous Conditions: 'Media-Agnostic' Biocatalysts for Biorefineries
<p>5-hydroxymethylfurfural (HMF) is produced upon dehydration of C6 sugars in biorefineries. As the product, it remains either in aqueous solutions, or is in situ extracted to an organic medium (biphasic system). For the subsequent oxidation of HMF to 2,5-furandicarboxylic acid (FDCA), ‘media-agnostic’ catalysts that can be efficiently used in different conditions, from aqueous to biphasic, and to organic (microaqueous) media, are of interest. Here, the concept of a one-pot biocatalytic cascade for production of FDCA from HMF was reported, using galactose oxidase (GalOx) for the formation of 2,5-diformylfuran (DFF), followed by the lipase-mediated peracid oxidation of DFF to FDCA. GalOx maintained its catalytic activity upon exposure to a range of organic solvents with only 1 % (v/v) of water. The oxidation of HMF to 2,5-diformylfuran (DFF) was successfully established in ethyl acetate-based biphasic or microaqueous systems. To validate the concept, the reaction was conducted at 5 % (v/v) water, and integrated in a cascade where DFF was subsequently oxidized to FDCA in a reaction catalyzed by <em>Candida antarctica</em> lipase B.</p>
Design of a Green Chemoenzymatic Cascade for Scalable Synthesis of Bio-based Styrene Alternatives
<p>As renewable lignin building blocks, hydroxystyrenes are particularly appealing as either a replacement or addition to styrene-based polymer chemistry. These monomers are obtained by decarboxylation of phenolic acids and often subjected to chemical modifications of their phenolic hydroxy groups to improve polymerization behaviour. Despite efforts, a simple, scalable, and purely (chemo)catalytic synthesis of acetylated hydroxystyrenes remains elusive. We thus propose a custom-made chemoenzymatic route that utilizes a phenolic acid decarboxylase (PAD). Our process development strategy encompasses a computational solvent assessment informing about solubilities and viable reactor operation modes, experimental solvent screening, cascade engineering, heterogenization of biocatalyst, tailoring of acetylation conditions, and reaction upscale in a rotating bed reactor. By this means, we established a clean one-pot two-step process that uses the renewable solvent CPME, bio-based phenolic acid educts and reusable immobilised PAD. The overall chemoenzymatic reaction cascade was demonstrated on a 1 L scale to yield 18.3 g 4-acetoxy-3-methoxystyrene in 96% isolated yield.</p>
BeMAGIC_Synthesis of magnetoelectric nano-objects/nanoparticles
<p>BeMAGIC ITN (GA861145) Synthesis of magnetoelectric nano-objects/nanoparticles by template assisted electrodeposition, lithography and other wet chemistry. Results from UCAM, INRIM, AALTO, TUC, ETHZ and ICN2.</p>
The cell-associated magnesium content is affected in Salmonella mutants defective for SigmaS/RpoS and O-antigen synthesis
<p>In many Gram-negative bacteria, the stress sigma factor of RNA polymerase, σS/RpoS, remodels global gene expression to reshape the physiology of quiescent cells and ensure their survival under non-optimal growth conditions. In the foodborne pathogen <i>Salmonella enterica</i> serovar Typhimurium, σS is also required for biofilm formation and virulence. </p><p>Our recent work has shown that a Δ<i>rpoS</i> mutation reduces the magnesium content of <i>Salmonella</i> (Metaane et al. 2022, PLoS ONE 17(3): e0265511). The O-antigen of LPS is a Mg2+ reservoir that can be used under magnesium deprivation. </p><p>We show here that eventhough the cell-associated magnesium content is affected when <i>Salmonella</i> lacks the entire O-antigen, an effect of the Δ<i>rpoS</i> mutation can be still observed. </p><p>We have also shown that the amount of intracellular free Mg2+ is slightly reduced in the Δ<i>rpoS</i> mutant compared to the wild-type strain (Metaane et al 2023, PLoS ONE 18(9): e0291736). </p><p><strong>This work was supported by the French National Research Agency (ANR-19-CE44-0005-01, PERIOMET project).</strong> </p>
Figures 7-12 in Synthesis Of The Bulgarian Protozoological Investigations Of South Shetland Islands (The Antarctic)
Figures 7-12. Scanning electron photographs of some common interstitial testate amoebae, found in subantarctic region of Chile and on Livingston Island. 7 – Centropyxiella arenaria; 8 – Ogdeniella elegans; 9 – Psammonobiotus linearis; 10 – Pseudocorythion acutum; 11 - Corythionella minima; 12 – Chardezia caudata.
Self-Supported Polymeric Ruthenium Complexes as Olefin Metathesis Catalysts in Synthesis of Heterocyclic Compounds
<p>Data confirming the structure of the new compounds obtained within the project, published in <em>Catalysts</em> <strong>2022</strong>, <em>12</em>(10), 1087; <a href="https://doi.org/10.3390/catal12101087">https://doi.org/10.3390/catal12101087</a></p> <p>The research was performed within MAESTRO project and was funded by National Science Centre, Poland, grant number DEC-2019/34/A/ST4/00372.</p>
Data_Synthesis_Musa_Trials_BLSD: v1.0.0
<p>Companion code and data for the paper "Rank-based data synthesis of heterogeneous trials to identify the effects of climatic factors on the reaction of <em>Musa</em> genotypes to black leaf streak disease".</p>
Raw data of publication: Towards a greener synthesis of dianhydrohexitol esters (Green Chemistry, 2023)
<p>These are the raw data of all graphs shown in the publication:</p> <p>Katrin Städtke, Andreas W. Göpfert, Alexandra Inayat, Towards a greener synthesis of dianhydrohexitol esters, Green Chemistry, 2023</p> <p>DOI: 10.1039/d3gc01795h</p> <p>All raw data file names refer to the respective figures in this publication and its supplementary information file.</p>
Synthesis of National projects on Aviation noise gathered by ANIMA National Focal Points
<p>This bundle gathers synthetic informations on more than hundred projects led at national level in EU countries and their neighbourhood (Switzeland, Ukraine, Serbia...) on aviation noise. This projects are partaking to the EU efforts to update the European Research Roadmap on such aviation noise issues.</p> <p>The bundle has been used for elaboration deliverable ANIMA D6.10 - National Focal Points projects</p>
Anisotropic Gold Nanomaterial Synthesis Using Peptide Facet Specificity and Timed Intervention: Experiment and simulation data, figures, and notebooks for recreating figures
<p><strong>/Data</strong></p> <p>Contains all experimental and simulation data used to generate figures in the manuscript. Each folder is labelled with the relevant technique: atomic force microscopy (AFM), dynamic light scattering (DLS), molecular dynamics (MD), small-angle X-ray scattering (SAXS), scanning electron microscopy (SEM), transmission electron microscopy and selected area electron diffraction (TEM-SAED), and ultraviolet-visible light spectroscopy (UV-Vis). Folders may contain subfolders from different experiments and should be unchanged for the notebooks to point to the correct path when loading data. Any file which contains SI in the filename indicates sample information, which includes sample concentration, delay associated with creating the sample (Delay4 is the relevant column name), unique identification (UID), etc.</p> <p><strong>/Data/AFM</strong></p> <p>Each filename is labelled with the number of delay associated with the sample or No Z2 Control in the case of the control sample. Each sample contains 3 files, the raw AFM data, a processed image, and an excel file with line profile measurements.</p> <p><strong>/Data/DLS</strong></p> <p>Contains exported data from Malvern Nano ZS DLS instrument.</p> <p><strong>/Data/Images</strong></p> <p>Images from the colloidal stability experiment.</p> <p><strong>/Data/MD</strong></p> <p>Molecular dynamics data and some notebooks for processing peptide and facet combinations.</p> <p><strong>/Data/SAXS</strong></p> <p>Reduced SAXS data from time-resolved study of nanoplatelet growth.</p> <p><strong>/Data/SEM</strong></p> <p>SEM images of samples prepared with and without dynamic intervention (control).</p> <p><strong>/Data/TEM_SAED</strong></p> <p>TEM images of samples prepared with and without dynamic intervention (control), and SAED image of a nanoplatelet.</p> <p><strong>/Data/UV-Vis</strong></p> <p>Spectroscopy data from different Z2 variants, the microplate based stability assay, cuvette based stability assay, and the time resolved (kinetics) measurements of particle growth as a result of manual dynamic intervention.</p> <p><strong>/Notebooks</strong></p> <p>This folder contains all of the Jupyter notebooks used to plot data and fit SAXS scattering profiles.</p> <p>See <strong>/Notebooks/environment.yml</strong> for packages necessary to execute the notebooks here and in <strong>/Synthesis_Protocol</strong>. We recommend installing this environment by using:</p> <p> </p> <p>Refer to <a href="https://github.com/SasView/sasmodels">https://github.com/SasView/sasmodels</a> and the first cell of <strong>/Notebooks/SAXS_Fitting.ipynb</strong> for specific instructions on how to complete installation of the sasmodels module (sasmodels will be installed by Pip if you correctly use the shared environment.yml file).</p> <p><strong>/Figures</strong></p> <p>Figures presented in the publication</p>
Raw Data for Ultrashort Electron Wave Packets via Frequency-Comb Synthesis. Aluffi et al, 2023
<p>This compressed files contains all the raw data and the python analysis scripts used to generate the figures in the paper Ultrashort Electron Wave Packets via Frequency-Comb Synthesis, Aluffi et al, 2023. 10.1103/PhysRevApplied.20.034005</p> <p>Preprint available at https://doi.org/10.48550/arXiv.2212.12311</p>
Domain-adaptive Data Synthesis for Large-scale Supermarket Product Recognition
<p><strong>Domain-Adaptive Data Synthesis for Large-Scale Supermarket Product Recognition</strong></p> <p>This repository contains the data synthesis pipeline and synthetic product recognition datasets proposed in [1].</p> <p><strong>Data Synthesis Pipeline:</strong></p> <p>We provide the Blender 3.1 project files and Python source code of our data synthesis pipeline <em>pipeline.zip, </em>accompanied by the<em> </em><a href="https://github.com/taesungp/contrastive-unpaired-translation">FastCUT</a> models used for synthetic-to-real domain translation<em> models.zip</em>. For the synthesis of new shelf images, a product assortment list and product images must be provided in the corresponding directories <em>products/assortment/</em> and <em>products/img/</em>. The pipeline expects product images to follow the naming convention <em>c</em>.png, with <em>c</em> corresponding to a GTIN or generic class label (e.g., 9120050882171.png). The assortment list, <em>assortment.csv</em>, is expected to use the sample format [<em>c, w, d, h</em>], with <em>c</em> being the class label and <em>w, d,</em> and <em>h</em> being the packaging dimensions of the given product in mm (e.g., [4004218143128, 140, 70, 160]). The assortment list to use and the number of images to generate can be specified in <em>generateImages.py </em>(see comments). The rendering process is initiated by either executing <em>load.py</em> from within Blender or within a command-line terminal as a background process. </p> <p><strong>Datasets:</strong></p> <ul> <li><strong>SG3k</strong> - Synthetic GroZi-3.2k (SG3k) dataset, consisting of 10,000 synthetic shelf images with 851,801 instances of 3,234 GroZi-3.2k products. Instance-level bounding boxes and generic class labels are provided for all product instances.</li> <li><strong>SG3kt</strong> - Domain-translated version of SGI3k, utilizing GroZi-3.2k as the target domain. Instance-level bounding boxes and generic class labels are provided for all product instances.</li> <li><strong>SGI3k</strong> - Synthetic GroZi-3.2k (SG3k) dataset, consisting of 10,000 synthetic shelf images with 838,696 instances of 1,063 GroZi-3.2k products. Instance-level bounding boxes and generic class labels are provided for all product instances.</li> <li><strong>SGI3kt</strong> - Domain-translated version of SGI3k, utilizing GroZi-3.2k as the target domain. Instance-level bounding boxes and generic class labels are provided for all product instances.</li> <li><strong>SPS8k</strong> - Synthetic Product Shelves 8k (SPS8k) dataset, comprised of 16,224 synthetic shelf images with 1,981,967 instances of 8,112 supermarket products. Instance-level bounding boxes and GTIN class labels are provided for all product instances.</li> <li><strong>SPS8kt</strong> - Domain-translated version of SPS8k, utilizing SKU110k as the target domain. Instance-level bounding boxes and GTIN class labels for all product instances.</li> </ul> <p>Table 1: Dataset characteristics. </p> <table> <tbody> <tr> <td><strong>Dataset</strong></td> <td><strong>#images</strong></td> <td><strong>#products</strong></td> <td><strong>#instances</strong></td> <td> <strong>labels </strong></td> <td><strong>translation</strong></td> </tr> <tr> <td>SG3k</td> <td>10,000</td> <td>3,234</td> <td>851,801</td> <td>bounding box & generic class¹</td> <td>none</td> </tr> <tr> <td>SG3kt</td> <td>10,000</td> <td>3,234</td> <td>851,801</td> <td>bounding box & generic class¹</td> <td>GroZi-3.2k</td> </tr> <tr> <td>SGI3k</td> <td>10,000</td> <td>1,063</td> <td>838,696</td> <td>bounding box & generic class²</td> <td>none</td> </tr> <tr> <td>SGI3kt</td> <td>10,000</td> <td>1,063</td> <td>838,696</td> <td>bounding box & generic class²</td> <td>GroZi-3.2k</td> </tr> <tr> <td>SPS8k</td> <td>16,224</td> <td>8,112</td> <td>1,981,967</td> <td>bounding box & GTIN</td> <td>none</td> </tr> <tr> <td>SPS8kt</td> <td>16,224</td> <td>8,112</td> <td>1,981,967</td> <td>bounding box & GTIN</td> <td>SKU110k</td> </tr> </tbody> </table> <p> </p> <p><strong>Sample Format</strong></p> <p>A sample consists of an RGB image (i.png) and an accompanying label file (i.txt), which contains the labels for all product instances present in the image. Labels use the YOLO format [c, x, y, w, h].</p> <p>¹SG3k and SG3kt use generic pseudo-GTIN class labels, created by combining the GroZi-3.2k food product category number <em>i</em> (1-27) with the product image index <em>j </em>(j.jpg)<em>, </em>following the convention<em> i0000j </em>(e.g., 13000097).</p> <p>²SGI3k and SGI3kt use the generic GroZi-3.2k class labels from <a href="https://arxiv.org/abs/2003.06800">https://arxiv.org/abs/2003.06800</a>.</p> <p><strong>Download and Use</strong><br>This data may be used for non-commercial research purposes only. If you publish material based on this data, we request that you include a reference to our paper [1].</p> <p>[1] Strohmayer, Julian, and Martin Kampel. "Domain-Adaptive Data Synthesis for Large-Scale Supermarket Product Recognition." <em>International Conference on Computer Analysis of Images and Patterns</em>. Cham: Springer Nature Switzerland, 2023.</p> <p>BibTeX citation:</p> <pre>@inproceedings{strohmayer2023domain, title={Domain-Adaptive Data Synthesis for Large-Scale Supermarket Product Recognition}, author={Strohmayer, Julian and Kampel, Martin}, booktitle={International Conference on Computer Analysis of Images and Patterns}, pages={239--250}, year={2023}, organization={Springer} }</pre>
Cell-free synthesis of infective phages from in vitro assembled phage genomes for efficient phage engineering and production of large phage libraries
<p>Upload of relevant sequencing data for the paper "<strong>Cell-free synthesis of infective phages from <em>in vitro</em> assembled phage genomes for efficient phage engineering and production of large phage libraries"</strong></p>
Synthesis of Tuneable Gold Nanostars: the Role of Adenosine Monophosphate
<p>The seed-mediated growth of gold nanostructures is known to be strongly dependent on the gold seed nanocrystal structure but also in the presence of different additives that may influence the morphology, and therefore the crystalline structure of the final nanoparticle. Among the different additives or capping ligands, biomolecules are an interesting family due to their potential biomedical applications such as drug delivery, bioimaging, biosensing, phototherapy, and antimicrobial activities. Here, we develop a seed-mediated strategy for synthesizing uniform Au nanostars with tuneable optical properties that involve adenosine monophosphate (AMP) as capping ligand. The experimental data reveal the key role of AMP not just providing colloidal stability and directing the reduction of the gold precursor via complexation but also mediating the anisotropic growth of the Au seeds via its selective adsorption on the different crystalline facets of Au nanoparticles. These observations agree with theoretical simulations carried out using molecular dynamics and density functional theory (DFT) calculations. Interestingly, the obtained Au nanostars showed high thermal stability as well as colloidal stability in polar organic solvents, which allowed their direct silica coating via the Stöber method. Importantly, we also explored the mimic enzymatic activity of the resulting gold nanostars and observed a superior catalytic activity compared with other gold nanoparticles reported in the literature.</p>
Data on phenological changes of benthic primary producers from Lake Saint-Pierre (1982-2019), Lake Müggelsee (2000-2021), Limnotron warming experiments and a literature synthesis
<p>This dataset regroup data on phenology of inland water benthic primary producers (macrophytes and periphyton) and includes five major data sources: a literature synthesis, long-term data on phenology from Lake Saint-Pierre (St. Lawrence River, Québec, Canada) and lake Müggelsee (Berlin, Germany), as well as two warming experiments. This data was assembled for a paper in review at Limnology and Oceanography Letters.</p> <p>Additionnal details are provided in the metadata file.</p> <p>Version 2 add some clarifications in the metadata, corrects typos in the pheno_litsearch_InlandLittoral.csv datasheet and added the datasheet pheno_litsearch_raw_responsevar.csv</p>
Upcycling a Plastic Cup: One-Pot Synthesis of Lactate Containing Metal Organic Frameworks from Polylactic Acid
<p>Data supporting publication: <strong>Upcycling a plastic cup: one-pot synthesis of lactate containing metal organic frameworks from polylactic acid</strong>, Benjamin Slater, So-On Wong, Andrew Duckworth, Andrew J. P. White, Matthew R. Hill and Bradley P. Ladewig, Chen. Commun. (2019), DOI: <a href="https://doi.org/10.1039/c9cc02861g">10.1039/c9cc02861g</a>. </p> <p>Includes raw data for XRD spectra for all materials, CIF file and checkCIF file.</p> <p>v2 includes additional high-resolution photos and diagrams supporting the publication</p>
Cross-biome synthesis of source versus sink limits to tree growth
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Data for: An instantaneous voice synthesis neuroprosthesis
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Data from: A global synthesis of how plants respond to climate warming from traits to fitness
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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.