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424 results for “In-situ”
Substantial contribution of in-situ produced bacterial sphingolipids to the sedimentary lipidome
<p><strong>Abstract:</strong> The sedimentary lipid pool comprises a myriad of components with some specific biomarkers used in paleoclimatic and geobiological reconstructions. However, a comprehensive view of the sedimentary lipidome is lacking. Here we conduct an untargeted analysis of the Black Sea sedimentary lipidome using high resolution mass spectrometry. Besides commonly reported phytoplankton-derived fossil lipids originate from oxic surface water, a diverse and abundant set of sphingolipids, accounting for ~20% of the lipidome, was discovered. These sphingolipids are produced in-situ by sedimentary anaerobic bacteria, likely in place of phospholipids due to the deficiency of phosphate in anoxic sediments. Our results suggest that while phytoplankton-derived lipids contribute 50–60% of the sedimentary lipidome, the importance of bacterial lipids, particularly in-situ produced sphingolipids, has been overlooked.</p> <p>Source data:</p> <p>Data 1. Spt_hits.and.backbone_sequences.MAFFT-L-INS-i.msa</p> <p>Data 2. Spt_hits.and.backbone_sequences.MAFFT-L-INS-i.msa.trimAl</p>
In-situ monitoring of the Seine River based on the MeSeine network
<p>In Europe, the management of freshwater ecosystem is governed by the Water Framework Directive (2000/60/CE) and its transposing legislation in France (2006-1772 of December 2006). The good ecological status of water are evaluated using a combination of several indicators such as biological and physico-chemical parameters. The Seine River crosses several important urbanized areas of France, including the Parisian conurbation (9 millions inhabitants). To ensure the good ecological status of the Seine River, the Greater Paris Conurbation Sanitation Authority (SIAAP), has constructed and operated the MeSeine network since 1990. MeSeine constitutes a tool for evaluating the quality of the Seine river and its tributaries (Marne, Oise) in terms of physico-chemistry, bacteriology, micro-contamination and faunal diversity.</p> <p>The MeSeine network extends along 125 km of the Seine River (from Choisy to Méricourt) and over 13 km along the Marne River (frome Champigny to Alfortville). It is structured around tree pillars:</p> <ul> <li>Real time monitoring of the physico-chemical composition of the Seine river using in situ sensor, in particular dissolved oxygen and temperature sensors</li> <li>Sampling and laboratory analysis campaigns to monitor watercourses quality and comply with the quality standards as defined by the Water Framework Directive (good ecological and chemical parameters)</li> <li>Biota monitoring to appreciate the diversity of fish populations, macro-invertebrates and diatoms.</li> </ul> <p>The aim of this work is to provide dissolved oxygen and temperature data of the Seine, generated by the in-situ sensors of the MeSeine network, via the open platform Zenodo.</p>
Supplementary material to: Using UAV-based photogrammetry coupled with in-situ fieldwork and U-Pb geochronology to decipher multi-phase deformation processes: A case study from Sarclet, Inner Moray Firth Basin, UK.
<p>This dataset represents the supplementary material to: Using UAV-based photogrammetry coupled with in-situ fieldwork and U-Pb geochronology to decipher multi-phase deformation processes: A case study from Sarclet, Inner Moray Firth Basin, UK.</p> <p>Appendix A - This appendix represents the 3D Digital Outcrop Modell (DOM) of Sarclet ‘The Haven and The Stack’ locality in 3D PDF format.<br> Appendix B - This appendix represents the 3D Digital Outcrop Modell (DOM) of Sarclet ‘Muiri Geo’ lo-cality in 3D PDF format.<br> Appendix C - This appendix represents the 3D Digital Outcrop Modell (DOM) of Sarclet ‘The Haven and The Stack’ locality in .obj format.<br> Appendix D - This appendix represents the 3D Digital Outcrop Modell (DOM) of Sarclet ‘Muiri Geo’ lo-cality in .obj format.<br> Appendix E - This appendix represents the orthomosaic of Sarclet ‘Muiri Geo’ locality in GeoTiff format.<br> Appendix F - This appendix represents the orthomosaic of Sarclet ‘Muiri Geo’ locality in GeoTiff format.<br> Appendix G - This appendix represents the analytical conditions and geochronology data of the studied samples.</p>
Dataset - In-situ amplification of spin echoes within a kinetic inductance parametric amplifier
<p>Raw data and analysis for arXiv:2211.11333</p> <p> </p>
Videos: The crystallization mechanism of gel-derived SiO2-TiO2 amorphous nanobeads elucidated by high-temperature in-situ experiments
<p>Supplementary materials detailing high-temperature in-situ TEM experiments.</p> <p>Main article available at: <a href="https://doi.org/10.1021/acs.cgd.3c00300">https://doi.org/10.1021/acs.cgd.3c00300</a></p> <p> </p>
In-situ time series collected in the Patagonian fjords.
<p>The dataset included the time series of Conservative temperature, Absolute Salinity, Dissolved Oxygen, and Marine Current published in this manuscript.</p>
Supplementary materials for Detrital garnet geochronology by in-situ U-Pb and Lu-Hf analysis: A case study from the European Alps
<p>Figure S2. Interactive 3D version of Fig.2 from main text, using the same symbology. To open, unzip folder and launch the .xhtml file in any internet browser. Use scroll wheel to zoom, left-click and drag to rotate.</p> <p><br> Table S1. Analytical parameters for garnet U-Pb and Lu-Hf analysis.</p> <p><br> Table S2. Isotopic and trace-element data.</p> <p><br> Table S3. Raman data.</p>
A dataset on in-situ electromagnetic wave integrity control of selective laser fusion printed parts using Machine Learning
<p><strong>DeepSLM Dataset</strong></p> <p>This dataset contains signals from metal parts printed in 3D using SLM (Selective laser melting) technology, produced as part of the DeepSLM project:<em> In-situ monitoring of Selective-Laser-Melted Ti6Al4V Parts Using Eddy Current Testing and Machine Learning</em>.</p> <p><em>Sensor and data collection</em></p> <p>An impedance-based non-destructive testing device is installed on the LPBF coating device. It is in the form of sensors with the following characteristics:</p> <p><em>Spectrum of analysis of the sensors</em></p> <ul> <li>Minimal length: 3-5 mm</li> <li>Minimal width acquisition: 2-3 mm (Without borders effects)</li> <li>Minimal number of layers: 50 layers</li> <li>Signal minimal penetration depth (TiAl<em>6</em>V<em>4</em>/875kHz) = 1.5 mm</li> </ul> <p>The sensors record the signal during printing, while simultaneously sending it to a computer via Bluetooth. The signals are first stored in the database. Next, a dataset is constructed from the extracted signals related to each part, and from the added semi-automatic annotations which describe the porosity of the part and layers.</p> <p><em>Annotations</em></p> <p>In the annotation process, there are 2 different types of labels and a metadata summary for these prints:</p> <p>1. Archimedean porosity measurement for the whole part<br>2. Layer porosity obtained after image processing applied on the resulting metallography images<br>3. Print-related metadata such as print parameters, part dimensions, layer thickness, etc</p> <p>Size: 66 parts<br>Set of printing parameters: 250</p> <p> --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p><strong>Dataset organization</strong></p> <p>The dataset is composed of 7 different printings and is organized as follows:<br>- signals: contains collected signals<br>- metallography: contains porosity extracted by metallography<br>- archimedean: contains porosity extracted by archimedean weighing<br>- metallography-images: contains metallography process images<br>- metadata.csv: contains print metadata (print parameter, part name, strategy, etc.)</p> <p>Each printed part has a unique ID ranging from 0 to 65. Each sub-part has an ID which is the ID of the base part suffixed with the sub-part position: 14_1 is the first sub-part of part 14. This nomenclature is uniform throughout the dataset.</p> <p>The README.md file in the dataset provides more detailed information on the structure of the dataset and the format of each of the files making up the dataset.</p> <p> </p> <p><strong>Relative article</strong></p> <p><a title="https://doi.org/10.1007/978-3-031-47784-3_18" href="https://doi.org/10.1007/978-3-031-47784-3_18" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-47784-3_18</a></p> <p>Sallem, H., Ghorbel, H., Goffinet, E., Cinna, A., Pralong, J., Wicht, J., & Revaz, B. (2023, May). In-Situ Monitoring of Selective Laser Melted Ti–6Al–4V Parts Using Eddy Current Testing and Machine Learning. In <em>Advances In Additive Manufacturing Conference</em> (pp. 139-148). Cham: Springer Nature Switzerland.</p>
Supplementary Information for "In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope"
<p>Supplementary information for the article</p> <p><strong>"In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope"</strong></p> <p>containing the videos of in-situ SEM imaging (mp4 files), raw data/images, and Jupyter notebooks (ipynb files) for data treatment and plots.</p> <p>Link to the publication: <a href="https://doi.org/10.1002/admt.202301632" target="_blank" rel="noopener">https://doi.org/10.1002/admt.202301632</a></p> <p>Link to the preprint: <a href="https://doi.org/10.48550/arXiv.2308.15123" target="_blank" rel="noopener">https://doi.org/10.48550/arXiv.2308.15123</a></p> <p>Explanation of the data files can be found in the <em>Information.pdf</em> file. The <em>Videos</em> folder contains the <em>in-situ </em>SEM image series mentioned in the paper.</p> <p>If there are any questions/bugs, feel free to contact me at the email given on <a href="https://orcid.org/0000-0002-5898-0713" target="_blank" rel="noopener">ORCID.</a></p>
Reformado catalítico de alquitrán proveniente de la gasificación de biomasa con fines energéticos: Estudios DRIFT in-situ
<p>La gasificación es un método termoquímico empleado para la transformación de materiales en compuestos gaseosos con un poder calorífico moderado, el cual puede emplearse para la generación de energía (Garcia Peña et al., 2022). Esta tecnología está adquiriendo un gran interés académico e industrial debido a los beneficios ambientales. En el proceso de gasificación se genera una corriente gaseosa (H2, CO, CO2 y CH4) y compuestos de alquitrán, estos últimos pueden generar baja calidad del gas y problemas operativos en su aplicación (Akbarian et al., 2022). Por lo que la reducción/eliminación del alquitrán de la fase gaseosa es uno de los principales desafíos para el éxito de esta tecnología y su posible aplicación industrial. El reformado catalítico permite la eliminación de alquitrán, presentado ventajas al lograr altas eficiencias, dependiendo de variables como tipo de catalizador, tiempo de residencia y temperatura (Galadima, Masudi, & Muraza, 2022). Este método se considera el más prometedor en aplicaciones a gran escala de la tecnología de gasificación. En este trabajo, inicialmente se estudió el proceso de reformado catalítico a escala laboratorio empleando una cámara DRIFT (Espectroscopia Infrarroja con Reflectancia Difusa) con control de temperatura, presión y flujo de gases. En la cámara se evaluaron 4 catalizadores: Fe/CA catalizador de bajo costo, dolomita (Dol), NiMo soportado en alúmina catalizador descartado de una unidad de hidrodesulfuración (HDS) y residuo de pirolisis (RP) solido obtenido de un proceso de pirólisis (char). Mediante DRIFT in-situ se realizó la adsorción y el seguimiento del reformado de compuestos modelos como tolueno y gas de síntesis con el objetivo de observar intermediarios e interacciones del proceso y posibles reacciones de reformado (Cordoba et al., 2022). Posteriormente, los catalizadores fueron evaluados en el proceso de reformado catalítico acoplado a un sistema de gasificación de residuos biomásicos a escala banco. En este sistema se buscó obtener un gas óptimo para aplicaciones energéticas (Garcia et al., 2022). Para tal fin, se evaluó la gasificacion en modo autotérmico y fluidizado de aserrín de pino con una alimentación de 0.840 kg/h y aguas abajo en el reactor de reformado los 4 catalizadores estudiados a 600°C con un WHSV: 6 h-1. Los resultados del trabajo permitieron identificar especies superficiales, posibles reacciones y el desempeño de los catalizadores durante reformado catalítico mediante los experimentos de DRIFT in-situ. Además, en el proceso de gasificación a escala banco, se observó que todos los catalizadores evaluados en el reactor de reformado aguas abajo presentan una buena actividad catalítica, obteniéndose reducciones de alquitrán > 60%. Los catalizadores en el reformado aumentaron los valores de poder calorífico inferior (LHV) y relación H2/CO, además se obtuvieron diferentes proporciones de H2, CO, CH4 y CO2 que concuerdan con las reacciones y mecanismos evidenciados en los experimentos DRIFT in-situ. Se puede concluir que el reformado catalítico aguas abajo del gasificador mejora la calidad del gas, el cual tiene un potencial para aplicaciones energéticas. Por otro lado, los catalizadores empleados son promisorios ya que son atractivos desde el punto de vista ambiental y económico.</p>
In-situ stress data set of Xianshuihe fault zone, Southwest China.
<p>306 sets of in situ stress data were collected from 48 sites on the Xianshuihe fault zone, used in literature and reports from 1982 to 2022. The detailed data of the in-situ stress include Stress value、Direction、Depth、Longitude、Latitude, Testing method, and the data source. Of these, the in-situ stress measurement methods include hydraulic fracturing, stress relief, acoustic emission, and stress recovery.</p>
Simulation data for paper "Estimation of in-situ stresses and friction properties of rock masses based on natural fractures conductivity: a case study from C0002 well at Nankai Trough zone, offshore Shikoku Island, Japan"
<p>Supplementary files for Dubinya, Tikhotskiy paper entitled "Estimation of in-situ stresses and friction properties of rock masses based on natural fractures conductivity: a case study from C0002 well at Nankai Trough zone, offshore Shikoku Island, Japan" prepared for submission to Journal of Geophysical Research: Solid Earth.</p> <p> </p> <p>File "Initial data on fractures.csv" contains initial data on conductivity of natural fractures, their deoths and spatial orientations</p> <p>Files "Unit N, (un)limited friction" contain results of Monte-Carlo simulations completed based on data from fractures from N-th interval. Friction coefficient is varied either between 0 and 1 (unlimited friction), or 0.4 and 0.6 (limited friction).</p>
Evaluation of a Test Mouthwash and Dentifrice Regimen in an In-situ Model of Dental Erosion
ClinicalTrials.gov study NCT01128972. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Clinical Study to Evaluate Experimental Children's Toothpastes in an In-Situ Caries Model
ClinicalTrials.gov study NCT01607411. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Targeted Intra-Operative Radiotherapy for the Management of Ductal Carcinoma In-Situ of the Breast
ClinicalTrials.gov study NCT00556907. IPD Sharing: Not stated. Countries: 1. Publications: 1.
In-situ and ex-situ conservation priorities and distribution of lentil wild relatives under climate change: A modeling approach
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Data from: A pioneering experimental investigation of a novel in-situ dynamic characterization of the tensile/compression stress-strain mechanism on human plantar soft tissue
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In-situ feeding as a new management tool to conserve orphaned Eurasian lynx (Lynx lynx)
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Dataset from: In-situ bidirectional human-robot value alignment
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Imaging elastodynamic and hydraulic properties of in-situ fractured rock: An experimental investigation exploring effects of dynamic stressing and shearing
<p>We describe laboratory experiments to elucidate the relationship between nonlinear elasticity and permeability evolution in fractured media subjected to local stress perturbations. This study is part of an effort to image fluid pathways and fracture properties using active-source acoustic monitoring during fluid injection and shear of rough fractures. Experiments were conducted with L-shaped samples of Westerly granite fractured in-situ under tri-axial conditions with deionized water subsequently circulated through the resulting fractures. After in-situ fracturing, we separately imposed oscillations of the applied normal stress and pore pressure with amplitudes ranging from 0.2 to 1 MPa and frequencies from 0.1 to 40 Hz. During these dynamic perturbations an array of piezoelectric transducers continuously transmitted ultrasonic pulses across the fracture to monitor the evolving elastic response. We interpret the resulting evolution of elastic wave properties in the context of elastic nonlinearity and relate the estimated nonlinearity parameters to the relative change in permeability of the fractured media. Fracture roughness is then altered in-situ by shearing, with the generation of breccia and wear products. We document the evolution of permeability and fracture contact stiffness as a function of dynamic stressing and shear offset and discuss our findings in relation to fractures in Earth's crust.</p>
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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.