Tetraniliprole risk assessment: Unveiling a hidden threat for managing a generalist herbivore.

Insecticide resistance poses a significant challenge in managing generalist herbivores such as the tobacco cutworm (TCW), Spodoptera litura. This study investigates the potential risks associated with using the novel diamide insecticide tetraniliprole to control TCW. A tetraniliprole-resistant strain was developed through twelve generations of laboratory selection, indicating an intermediate risk of resistance development. Field monitoring in China revealed a significant incidence of resistance, particularly in the Nanchang (NC) population (>100-fold). Tetraniliprole showed moderate to high cross-resistance to multiple insecticides and was autosomally inherited with incomplete dominance, controlled by multiple genes, some of which belong to the cytochrome P450 family associated with enhanced detoxification. Life table studies indicated transgenerational hormesis, stimulating TCW female fecundity and increasing population net reproduction rates (R0). These findings suggest a potential for pest resurgence under tetraniliprole use. The integrated risk assessment provides a basis for the sustainable management of TCW using tetraniliprole.

UBES: Unified scatter correction using ultrafast Boltzmann equation solver for conebeam CT.

A semi-analytical solution to the unified Boltzmann equation is constructed to exactly describe the scatter distribution on a flat-panel detector for high-quality conebeam CT (CBCT) imaging. The solver consists of three parts, including the phase space distribution estimator, the effective source constructor and the detector signal extractor. Instead of the tedious Monte Carlo solution, the derived Boltzmann equation solver achieves ultrafast computational capability for scatter signal estimation by combining direct analytical derivation and time-efficient one-dimensional numerical integration over the trajectory along each momentum of the photon phase space distribution. The execution of scatter estimation using the proposed ultrafast Boltzmann equation solver (UBES) for a single projection is finalized in around 0.4 seconds. We compare the performance of the proposed method with the state-of-the-art schemes, including a time-expensive Monte Carlo (MC) method and a conventional kernel-based algorithm using the same dataset, which is acquired from the CBCT scans of a head phantom and an abdominal patient. The evaluation results demonstrate that the proposed UBES method achieves comparable correction accuracy compared with the MC method, while exhibits significant improvements in image quality over learning and kernel-based methods. With the advantages of MC equivalent quality and superfast computational efficiency, the UBES method has the potential to become a standard solution to scatter correction in high-quality CBCT reconstruction.