Design, Synthesis, Antifungal Activity, and 3D-QSAR Study of Novel Quinoxaline-2-Oxyacetate Hydrazide.

Plant pathogenic fungi pose a major threat to global food security, ecosystem services, and human livelihoods. Effective and broad-spectrum fungicides are needed to combat these pathogens. In this study, a novel antifungal 2-oxyacetate hydrazide quinoxaline scaffold as a simple analogue was designed and synthesized. Their antifungal activities were evaluated against Botrytis cinerea (B. cinerea), Altemaria solani (A. solani), Gibberella zeae (G. zeae), Rhizoctonia solani (R. solani), Colletotrichum orbiculare (C. orbiculare), and Alternaria alternata (A. alternata). These results demonstrated that most compounds exhibited remarkable inhibitory activities and possessed better efficacy than ridylbacterin, such as compound 15 (EC50 = 0.87 µg/mL against G. zeae, EC50 = 1.01 µg/mL against C. orbiculare) and compound 1 (EC50 = 1.54 µg/mL against A. alternata, EC50 = 0.20 µg/mL against R. solani). The 3D-QSAR analysis of quinoxaline-2-oxyacetate hydrazide derivatives has provided new insights into the design and optimization of novel antifungal drug molecules based on quinoxaline.

Adaptive autonomous emergency braking model based on weather conditions.

OBJECTIVE: Vehicle active safety systems can improve vehicle security by avoiding collisions. An autonomous emergency braking (AEB) system's safety distance calculation is usually based on normal weather conditions. The AEB system's early warning capabilities decrease during adverse weather conditions. METHODS: A multilayer perceptron (MLP) model is used to obtain data from accident and weather data sets. The MLP model is trained and the severity of accidents is predicted. The severity is used as a parameter to build an adaptive AEB system algorithm that considers adverse weather conditions. RESULTS: The adaptive AEB system algorithm increases safety and reliability under adverse weather conditions. Prescan and a driver-in-the-loop system are used to test the adaptive AEB model. Both tests show that the adaptive AEB model has better performance under adverse weather than the traditional AEB model. CONCLUSIONS: The experimental results demonstrate that the adaptive AEB system can increase the safety distance in rainy weather and avoid collisions under hazy conditions.

Prevalence and subtyping of Cronobacter species in goat milk powder factories in Shaanxi province, China.

Cronobacter spp. are opportunistic pathogens that can cause serious diseases in neonates and infants via consumption of contaminated milk powder. To determine Cronobacter spp. contamination status, 632 samples, including 15 evaporated milk, 45 intermediate powder, 150 finished products, and 422 manufacturing environment samples, were collected from 3 goat milk powder factories in Shaanxi province, China, from July 2013 to April 2014. The recovered Cronobacter isolates were subtyped using pulsed-field gel electrophoresis to trace the potential dissemination routes during the whole production processing. Sixty-seven Cronobacter spp. isolates were recovered. The prevalence rates in manufacturing environment, intermediate powder, and finished products were 92.5, 6.0, and 1.5%, respectively. The predominant species were Cronobacter sakazakii (88.1%); no Cronobacter turicensis, Cronobacter condimenti, or Cronobacter dublinensis were detected. Sixty-seven Cronobacter isolates were grouped in 26 clusters by pulsed-field gel electrophoresis, and substantial genetic similarity was observed among isolates from different sampling sites in the same factory. Isolates in the main clusters were commonly recovered from intermediate powder, floor powder, and shoes. These data indicated that air, powder, and personnel movement were potential routes for Cronobacter dissemination, and manufacturing environment is the key control point for Cronobacter contamination.