Association between preconception and early pregnancy exposure to fine particulate matter and nervous system anomalies: a nested case-control study.

Although several environmental factors may increase the risk of nervous system anomalies, the association between exposure to particulate matter with an aerodynamic diameter of ≤ 2.5 μm (PM) and nervous system anomalies is not completely understood. This study aimed to examine the association between expoure to PM and nervous system anomalies, including specific phenotypes during preconception and early pregnancy and determine the crucial time windows.

Phenylpropanoids and polyacetylenes from the roots of .

Phytochemical investigation of the roots of yielded a new phenylpropanoid, adenophoride () and a new polyacetylene, adenylene () along with four phenylpropanoids and a polyacetylene. The structures were determined by spectroscopic analysis including NMR, MS, UV and IR. Among the isolated compounds, phenylpropanoids including a new compound showed mild α-glucosidase inhibitory activities.

LiZrF protective layer enabled high-voltage LiCoO positive electrode in sulfide all-solid-state batteries.

The application of high-voltage positive electrode materials in sulfide all-solid-state lithium batteries is hindered by the limited oxidation potential of sulfide-based solid-state electrolytes (SSEs). Consequently, surface coating on positive electrode materials is widely applied to alleviate detrimental interfacial reactions. However, most coating layers also react with sulfide-based SSEs, generating electronic conductors and causing gradual interface degradation and capacity fading.

Context-Aware Integrated Navigation System Based on Deep Learning for Seamless Localization.

An integrated navigation system is a promising solution to improve positioning performance by complementing estimated positioning in each sensor, such as a global positioning system (GPS), an inertial measurement unit (IMU), and an odometer sensor. However, under GPS-disabled environments, such as urban canyons or tunnels where the GPS signals are difficult to receive, the positioning performance of the integrated navigation system decreases. Therefore, deep learning-based integrated navigation systems have been proposed to ensure seamless localization under various positioning conditions.