3D Gamma-ray and Neutron Mapping in Real-Time with the Localization and Mapping Platform from Unmanned Aerial Systems and Man-Portable Configurations

Nuclear Scene Data Fusion (SDF), implemented in the Localization and Mapping Platform (LAMP) fuses three-dimensional (3D), real-time volumetric reconstructions of radiation sources with contextual information (e.g. LIDAR, camera, etc.) derived from the environment around the detector system. This information, particularly when obtained in real time, may be transformative for applications, including directed search for lost or stolen sources, consequence management after the release of radioactive materials, or contamination avoidance in security-related or emergency response scenarios. 3D reconstructions enabled by SDF localize contamination or hotspots to specific areas or objects, providing higher resolution over larger areas than conventional 2D approaches, and enabling more efficient planning and response, particularly in complex 3D environments. In this work, we present the expansion of these gamma-ray mapping concepts to neutron source localization. Here we integrate LAMP with a custom $Cs_2LiLa(Br,Cl)_6:Ce$ (CLLBC) scintillator detector sensitive to both gamma-rays and neutrons, which we dub Neutron Gamma LAMP (NG-LAMP). NG-LAMP enables simultaneous neutron and gamma-ray mapping with high resolution gamma-ray spectroscopy. We demonstrate the ability to detect and localize surrogate Special Nuclear Materials (SNM) in real-time and in 3D based on neutron signatures alone, which is critical for the detection of heavily shielded SNM, when gamma-ray signatures are attenuated. In this work, we show for the first time the ability to localize, in 3D and realtime, a neutron source in the presence of a strong gamma-ray source, simultaneous and spectroscopic localization of three gamma-ray sources and a neutron source, and finally the localization of a surrogate SNM source based on neutron signatures alone, where gamma-ray data are consistent with background

Optimising cultural practices for grain sorghum in relation to climatic risk at three locations in the United States, using the Sorkam model

The SORKAM model was tested against experimental data, for its suitability to examine the consequences of alternative plant density and row spacing for rainfed grain sorghum in the United States. Simulations were conducted for 2 crop maturities (early and late) and 2 upper limits of plant available water storage (low and high), for each of 4 plant densities (2.5, 5.0, 10.0, and 20.0 plants/m) and 3 row spacings (0.5, 1.0, and 1.5 m), at Temple, Texas, and Manhattan and Garden City, Kansas. Cumulative distribution functions for grain yield were obtained for each combination. Strategies to minimize risk and maximize profit were identified from these functions

Patterns of genetic diversity of the Hawaiian spinner dolphin (Stenella longirostris)

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