As part of cooperation with Schülerforschungszentrum Hamburg (SFZ), the Cluster UWA offers courses in which pupils in grades 8 to 10 can try to unravel the secrets of lost writings themselves. First, they learn what inks were used in antiquity and the Middle Ages, and make their own inks according to original recipes. The manuscripts produced with these inks are then examined with modern analytical methods under the guidance of our researchers.

This multispectral imaging (MSI) dataset of the prepared ink samples on parchment and papyrus was taken on the 10th of July 2024. Image Processing and analysis of Ink spectra was done during the visit to the SFZ on the 17th of July 2024. Due to time constrains only one of the total of 4 sets of samples was analyzed and processed.

Images in preview are compressed and of lower quality. They are mainly intended to serve as thumbnails. Original hiqh quality TIF images can be found in the Color and PROCESSED folder below (zip file). For information about filenames and folderstructure as well as MSI system related info, please read the "Brief Description of Datasets for Multispectral Imaging Version Q".

148030 Global export shipment records of Msi with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

This record contains example and result data of msiFlow.

msiFlow is a collection of automated workflows for reproducible and scalable multimodal mass spectrometry imaging (MSI) and immunofluorescence microscopy (IFM) data processing and analysis. Using an experimental mouse model for urinary tract infection, induced by uropathogenic E.coli (UPEC), we generated data by

• matrix-assisted laser desorption ionisation mass spectrometry imaging with laser-induced postionisation (MALDI-2 MSI) using the Bruker timsTOFfleX instrument
• transmission-mode MALDI-2 MSI (t-MALDI-2)
• immunofluorescence microscopy (IFM) using the MACSima system from Miltenyi

msiFlow was tested on MALDI-2 MSI, t-MALDI-2 MSI and IFM data of control and UPEC-infected mouse bladder sections. In IFM we used Ly6G and actin for staining neutrophils and the muscle layer. We validated msiFlow on MALDI MSI data of bone marrow (BM)-derived neutrophils. Tentative lipid annotations were validated by MALDI DDA MSI and MALDI MS/MS. All data used and results generated by msiFlow are included in this dataset (besides the intermediate results of the MALDI-2 preprocessing due to data size).

The dataset contains the following zip files:

Detailed knowledge of tissue-specific metabolic profiles of the lung is vital for elucidating the molecular pathological signature of lung aging and exploring potential metabolic targets to improve aging lung function. In this study, a spatially resolved metabolomics approach based on airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI–MSI) was proposed to investigate tissue-specific metabolic disturbances in the lungs of naturally aging mice. This dataset holds considerable potential for exploring the metabolic reprogramming of the aging lung, with important value for understanding the underlying mechanisms of aging-associated lung diseases.

This is the data collection for the nearmsi.shapebackplane bundle. This data set contains data products for 93,397 images obtained by the Multi-Spectral Imager (MSI) of the Near Earth Asteroid Rendezvous (NEAR) mission during the orbital phase at asteroid 433 Eros. The data products include geometric and geophysical information for each pixel. The data products are in the form of backplanes, stored in the FITS image format. There is one backplane file for each MSI image. Each of the MSI backplane files is a 16-band image cube. The bands of the cube contain the information detailed below calculated for the center of each pixel: 1... ...Show More

This data set contains data products for 93,397 images obtained by the Multi-Spectral Imager (MSI) of the Near Earth Asteroid Rendezvous (NEAR) mission during the orbital phase at asteroid 433 Eros. The data products include geometric and geophysical information for each pixel. The data products are in the form of backplanes, stored in the FITS image format. There is one backplane file for each MSI image. Each of the MSI backplane files is a 16-band image cube. The bands of the cube contain the information detailed below calculated for the center of each pixel: 1: Pixel values (I/F) of the original FITS images delivered to the PDS by the NEAR team [Murchie et al., 2001], linearly resampled to rectify the image by squaring the pixels. The original image size is 537 x 244 pixels and the rectified size is 537 x 412 pixels. 2: x coordinate (kilometers) of the intercept with the surface of the asteroid in body-fixed reference frame 3: y coordinate (kilometers) of the intercept with the surface of the asteroid in body-fixed reference frame 4: z coordinate (kilometers) of the intercept with the surface of the asteroid in body-fixed reference frame 5: latitude (planetocentric, degrees) 6: longitude (degrees east) 7: radial distance (kilometers) from the asteroid center of figure 8: solar incidence angle (degrees) 9: emission angle (degrees) 10: solar phase angle (degrees) 11: horizontal pixel scale (kilometers) 12: vertical pixel scale (kilometers) 13: average surface slope relative to gravity (degrees) 14: average elevation relative to gravity (meters) 15: average gravitational acceleration (meters/[s^2]) 16: average gravitational potential (J/kg)

This dataset contains Top-of Atmosphere (TOA) reflectances in cartographic geometry (level 1C) processed data, from the Multispectral Instrument (MSI) aboard the European Space Agency (ESA) Sentinel 2A satellite. Sentinel 2A was launched on 23rd June 2015 and provides multispectral images of the earth’s surface as a continuation and enhancement of the Landsat and SPOT missions. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user in the UK.

CEDA have switched to provide Sentinel 2 data for the UK and Dependencies along with data needed per project basis as of April 2019. Please contact us if you need data outside these areas and we will see what we can do.

Snow and ice are important hydrological resources. Their minimum spatial extent here referred to as annual minimum snow/ice (MSI) cover, plays a very important role as an indicator of long-term changes and baseline capacity for surface water storage. The MSI probability is derived from sequence of seventeen 10-day clear-sky composites corresponding to April, 1 to September, 20 warm period for each year since 2000. Data from Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra satellite for the period since 2000 have been processed with the special technology developed at the Canada Centre for Remote Sensing (CCRS) as described in Trishchenko, 2016; Trishchenko et al., 2016; 2009, 2006, Trishchenko and Ungureanu, 2021, Khlopenkov and Trishchenko, 2008, Luo et al., 2008. The presence of snow or ice is determined for each pixel of the image based on snow/ice scene identification procedure and the probability if computed for the entire warm season as a ratio of number of snow/ice flags to the total number of pixels available (less or equal to 17). The minimum snow and ice extent can be derived from the probability map by applying a certain threshold. New data version V5.0 replaces previous version V4.0 for all data available since 2000. All MSI files were reprocessed for all MODIS input data based on collection 6.1. The output format has not changed since previous version. It is described in Trishchenko (2024). The impact of input data change is small and can be detected only for time interval 2000-2015. Data starting 2016 has been already derived using MODIS collection 6.1 input. The differences between the MSI data based on MODIS Collection 5 (i.e. MSI V4) versus MODIS Collection 6.1 (i.e. MSI V5), on average, are quite small. The region-wide relative difference in the MSI extent varies from -3.97% to +1.75%. The mean value is -0.14%, the median value is 0.18% and standard deviation is 1.83%. As such, we do not expect any sizeable impact of the version change on our previous conclusions regarding trends and climate variations, except for refining the relative values of statistical parameters within the range of a few percents. References: TRISHCHENKO, A.P., 2024: Probability maps of the annual minimum snow and ice (MSI) presence over April,1 to September, 20 period since 2000 derived from MODIS 250m imagery over Canada and neighbouring regions. Data format description. CCRS, NRCan. 4pp.

NEAR EDR volume sets contain a single data set, from one instrument and one mission phase (defined in the phase table in /AAREADME.TXT).

148030 Global import shipment records of Msi with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Spatially resolved lipidomics is pivotal for detecting and interpreting lipidomes within spatial contexts using the mass spectrometry imaging (MSI) technique. However, comprehensive and efficient lipid identification in MSI remains challenging. Herein, we introduce a high-coverage, database-driven approach combined with air-flow-assisted desorption electrospray ionization (AFADESI)-MSI to generate spatial lipid profiles across whole-body mice. Using liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS), we identified 2868 unique lipids in the serum and various organs of mice. Subsequently, we systematically evaluated the distinct ionization properties of the lipids between LC–MS and MSI and created a detailed MSI database containing 14 123 ions. This method enabled the visualization of aberrant fatty acid and phospholipid metabolism across organs in a diabetic mouse model. As a powerful extension incorporated into the MSIannotator tool, our strategy facilitates the rapid and accurate annotation of lipids, providing new research avenues for probing spatially resolved heterogeneous metabolic changes in response to diseases.

NEAR EDR volume sets contain a single data set, from one instrument and one mission phase (defined in the phase table in /AAREADME.TXT).

EarthCARE (Earth Cloud, Aerosol and Radiation Explorer) is the sixth of ESA’s Earth Explorer Mission. It has been developed and is operated in a cooperation mission between ESA and JAXA.

The Multispectral Imager (MSI) onboard of the EarthCARE satellite is a seven-band, push-broom scanner. L1C data (radiance in the visible, near infrared (NIR) and short-wave infrared (SWIR) bands, and brightness temperature in the thermal infrared (TIR) bands) are provided as .ZIP files containing the following files: - Header file in XML format (.HDR) - Data block files in HDF5 format (.h5)

Motorola Solutions stock is expected to experience moderate growth in the near term, supported by increasing demand for its communication and security solutions. However, the company faces risks associated with supply chain disruptions, economic headwinds, and intense competition in the telecommunications sector.

Access Msi import export data of global countries with importers' & exporters' details, shipment date, price, hs code, ports, quantity etc.

Background: The European Space Agency (ESA) has operated medium resolution satellites - Sentinel-2 series (Sentinel-2A and Sentinel-2B) since 2015. The spectral bands and spatial resolution of Sentinel-2 are similar to those of the Landsat series, but Sentinel-2 has a higher revisit frequency and spatial coverage. A combination of Sentinel-2 and Landsat data can provide good spatial and temporal coverage of the Earth's surface and provide useful information to monitor environmental resources over time, such as agricultural production and mining activities. However, the raw remotely sensed data received by these satellites in the solar spectral range do not directly characterise the underlying reflectance of surface objects. The data are modified by the atmosphere, variation of solar and sensor positions as well as surface anisotropic conditions. To make accurate comparisons of imagery acquired at different times, seasons and geographic locations, and detect the change of surface, it is necessary to remove/reduce these effects to ensure the data are consistent and can be compared over time.

What this product offers: This product takes Sentinel-2A imagery captured over the Australian continent and corrects for inconsistencies across land and coastal fringes. The result is accurate and standardised surface reflectance data, which is instrumental in identifying and quantifying environmental change.

The imagery is captured using the Multispectral Instrument (MSI) sensor aboard Sentinel-2A.

This product is a single, cohesive Analysis Ready Data (ARD) package, which allows the analysis of surface reflectance data as is, without the need to apply additional corrections.

It contains two sub-products that provide corrections or attribution information:

• Geoscience Australia Sentinel-2A MSI NBART Collection 3
• Geoscience Australia Sentinel-2A Observation Attributes Collection 3

The resolution is a 10/20/60 m grid based on the ESA Level 1C archive.

Applications: - The development of derivative products to monitor land, inland waterways and coastal features, such as: - urban growth - coastal habitats - mining activities - agricultural activity (e.g. pastoral, irrigated cropping, rain-fed cropping) - water extent - The development of refined information products, such as: - areal units of detected surface water - areal units of deforestation - yield predictions of agricultural parcels - Compliance surveys - Emergency management

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

This dataset is complementary to https://github.com/yaza11/maspim-notebooks.

It contains a

• small test measurement for MSI data (in the "small example" folder)
• a full example for a 5-cm section (from 490 to 495 cm)
  • an MSI measurement, except for the raw data that is linked under the github repo
  • an XRF measurement
  • an X-Ray scan of a 30-cm section covering the 5-cm section

Mass spectrometry imaging (MSI) has emerged as a revolutionary analytical strategy in biomedical research for molecular visualization. By linking the characterization of functional metabolites with tissue architecture, it is now possible to reveal unknown biological functions of tissues. However, due to the complexity and high dimensionality of MSI data, mining bioinformatics-related peaks from batch MSI data sets and achieving complete spatially resolved metabolomics analysis remain a great challenge. Here, we propose novel MSI data processing software, Multi-MSIProcessor (MMP), which integrates the data read-in, MSI visualization, processed data preservation, and biomarker discovery functions. The MMP focuses on the AFADESI-MSI data platform but also supports mzXML and imzmL data input formats for compatibility with data generated by other MSI platforms such as MALDI/SIMS-MSI. MMP enables deep mining of batch MSI data and has flexible adaptability with the source code opened that welcomes new functions and personalized analysis strategies. Using multiple clinical biosamples with complex heterogeneity, we demonstrated that MMP can rapidly establish complete MSI analysis workflows, assess batch sample data quality, screen and annotate differential MS peaks, and obtain abnormal metabolic pathways. MMP provides a novel platform for spatial metabolomics analysis of multiple samples that could meet the diverse analysis requirements of scholars.

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