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Under an atmosphere of argon, to a solution of 3-hexyl-6-methoxy-5,7,8-trimethylchromen-2-one (21.0 mg, 69.4 µmol, 1.00 equiv.) in dichloromethane (1.39 ml), boron tribromide (1 M in DCM, 0.35 ml, 87.0 mg, 347 µmol, 5.00 equiv.) were added dropwise at –78 °C. At this temperature the reaction mixture was stirred for 30 min and then stirred at room temperature over night. The reaction was quenched by addition of saturated NaHCO3 solution, extracted with dichloromethane and washed with distilled water and brine. The combined organic phases were dried over Na2SO4, filtrated and concentrated in vacuo. The crude product was purified by flash column chromatography.

B. Vandecrux (1), A. Kokhanovsky (2), G. Picard (3) and J. Box (1) (1) Geological Survey of Denmark and Greenland (GEUS) Øster Voldgade 10, 1350 Copenhagen, Denmark (2) Max Planck Institute for Chemistry, Mainz 55128, Federal Republic of Germany (3) Institut des Géosciences de l'Environnement, Université de Grenoble, France This algorithm retrieves the snow surface properties using Sentinel-3's OLCI 865nm and 1020 nm bands and the theory developed by A. Kokhanovsky in: Kokhanovsky et al. (2018) On the reflectance spectroscopy of snow Kokhanovsky et al. (2019) Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument Kokhanovsky et al. (2020) The Determination of Snow Albedo from Satellite Measurements Using Fast Atmospheric Correction Technique It includes the ozone retrieval from the OLCI 620 nm band developed in: Kokhanovsky et al. (2020) Retrieval of the total ozone over Antarctica using Sentinel-3 ocean and land colour instrument And the retrieval of impurity load and characteristics from OLCI 400nm and 490nm bands developed in: Kokhanovsky, A. A., et al., 2021a: Retrieval of dust properties from spectral snow reflectance measurements It is also the version that will be converted into a SNAP plug-in.

The software package provides several utilities written in LabView. These utilities don't form independent programs, but rather can be used as a library or controls in other labview programs. The utilities include several new controls (xcontrols), VIs for input and output routines, as well as other 'helper'-functions not provided in the standard LabView environment.

Changes in version 0.1.0 (2022-11-25) Initial version

Server Stream on Sight MR is a collection of software that offloads the rendering process of Mixed Reality (MR) on mobile devices to a server, enabling the display of large-scale 3D models in MR. It allows for the overlay and display of extensive and detailed 3D models in outdoor real-world environments, making it useful for sharing flood risk information and landscape planning outdoors. Multiple mobile devices can connect simultaneously and display MR concurrently by operating several rendering servers in parallel and automatically assigning clients to the appropriate rendering server. This software comprises three components: an Allocating server to assign users, a Rendering server for rendering, and a Client page for display on user devices. Details and source codes for each software component can be accessed from the README.md files in their respective folders and source files within zip files.

Geological Named Entity Recognition

We have reconsidered the evaluation criteria. Instead of 100 random citations, we selected 10 random citations for each regular expression. We decided to examine a fixed quantity of citations per regular expression and not an amount proportional to the number of matches to remove the bias given by the population under consideration. The function to generate the evaluation data is get_random_results in evaluation.py.

This is an archive of CSIB v1 source code. The code is being updated on gitlab: https://gitlab.com/hakasehayashida/canoe-dms

First Release - The Fuzzy Framework for Speed Estimation sourcecode will be added once the paper which is currently under review at the ISPRS International Journal of Geo-Information will be published.

The INL Multi-Robot Control Interface controls many robots through a single user interface. The interface includes a robot display window for each robot showing the robot's condition. More than one window can be used depending on the number of robots. The user interface also includes a robot control window configured to receive commands for sending to the respective robot and a multi-robot common window showing information received from each robot.