Prenatal Exposure to Polycyclic Aromatic Hydrocarbons and Birth Weight in China

Adverse birth outcomes are a leading cause of mortality in children in China, but the environmental influences of these conditions remain largely unexplained in this population. We aimed to evaluate the levels of polycyclic aromatic hydrocarbons (PAHs) in Chinese pregnant women and their newborns, and to examine the association between levels of PAHs and infant birth weight. We conducted a cross-sectional study including 81 pairs of mothers and newborns from four hospitals in four different cities in China. High Performance Liquid Chromatography was used to measure the concentration of nine PAHs in maternal and cord blood and multiple linear regression analyses were used to evaluate the associations of these PAHs with infant birth weight. Anthracene (ANT) had the highest average concentration and detection rate (geometric mean = 69.54 ng/g and 76.5%, respectively) in maternal serum samples, while fluoranthene (FLT) had the highest concentration and detection rate (geometric mean = 68.4 ng/g and 50.6%, respectively) in the cord blood. Most of the measured PAHs in maternal serum and three PAHs in cord blood were inversely but non-significantly associated with birth weight. The strongest associations were observed for higher concentrations of benzo (a) pyrene (BaP) in maternal serum (230.7 g decrease for levels > median vs. < LOD;p = 0.151) and for ANT in cord blood (153.1 g decrease for levels < median vs. < LOD;p = 0.208). Ant and FLT were the predominant PAHs in the maternal and cord blood serum. Serum concentrations of several measured PAHs were associated with a decreased birth weight, although not significantly, suggesting that further studies with larger sample sizes are needed to validate our findings.

Non-radical activation of persulfate with Bi_(2)O_(3)/BiO_(1.3)I_(0.4)for efficient degradation of propranolol under visible light

Non-radical activation of persulfate(PS)by photocatalysts is an effective approach for removing organic pollutants from aqueous environments.In this study,a novel Bi_(2)O_(3)/BiO_(1.3)I_(0.4)heterojunction was synthesized using a facile solvothermal approach and used for the first time for non-radical activation of PS to degrade propranolol(PRO)in the presence of visible light.The findings found that the degradation rate of PRO in the Bi_(2)O_(3)/BiO_(1.3)I_(0.4)/PS system was significantly increased from 19%to more than 90%within 90 min compared to the Bi_(2)O_(3)/BiO_(1.3)I_(0.4)system.This indicated that the composite system exerted an excellent synergistic effect between the photocatalyst and the persulfate-based oxygenation.Quenching tests and electron paramagnetic resonance demonstrated that the non-radical pathway with singlet oxygen as the active species played a major role in the photocatalytic process.The existence of photo-generated holes during the reaction could also be directly involved in the oxidation of pollutants.Meanwhile,a possible PRO degradation pathway was also proposed.Furthermore,the impacts of pH,humic acid and common anions on the PRO degradation by the Bi_(2)O_(3)/BiO_(1.3)I_(0.4)/PS were explored,and the system’s stability and reusability were also studied.This study exhibits a highly productive catalyst for PS activation via a non-radical pathway and provides a new idea for the degradation of PRO.

Disaster Risk Science:A Geographical Perspective and a Research Framework

In this article,we recall the United Nations’30-year journey in disaster risk reduction strategy and framework,review the latest progress and key scientific and technological questions related to the United Nations disaster risk reduction initiatives,and summarize the framework and contents of disaster risk science research.The object of disaster risk science research is the"disaster system"consisting of hazard,the geographical environment,and exposed units,with features of regionality,interconnectedness,coupling,and complexity.Environmental stability,hazard threat,and socioeconomic vulnerability together determine the way that disasters are formed,establish the spatial extent of disaster impact,and generate the scale of losses.In the formation of a disaster,a conducive environment is the prerequisite,a hazard is the necessary condition,and socioeconomic exposure is the sufficient condition.The geographical environment affects local hazard intensity and therefore can change the pattern of loss distribution.Regional multi-hazard,disaster chain,and disaster compound could induce complex impacts,amplifying or attenuating hazard intensity and changing the scope of affected areas.In the light of research progress,particularly in the context of China,we propose a threelayer disaster risk science disciplinary structure,which contains three pillars(disaster science,disaster technology,and disaster governance),nine core areas,and 27 research fields.Based on these elements,we discuss the frontiers in disaster risk science research.

Ultra-high conductive 3D aluminum photonic crystal as sulfur immobilizer for high-performance lithium-sulfur batteries

The practical application of lithium-sulfur (Li-S) batteries is hampered by the insulative nature of sulfur, sluggish electrochemical kinetics, and large volume variation, which result in capacity-fading at a large current density and poor cycling stability. Herein, a three-dimensional (3D) aluminum photonic crystal encapsulating sulfur (APC@S) composite as a binder-free cathode for Li-S battery is reported. The 3D APC@S cathode can deliver a fantastic capacity of 1,517.8 mAh·g^(−1) at 0.5 C, and retains 712.7 mAh·g^(−1) after 1,500 cycles at 2 C with a decay rate of 0.02% per cycle. Even at a high rate of 5 C, the reversible capacity can still maintain at 680.7 mAh·g^(−1) after 1,000 cycles with a capacity retention of 74.8%. Furthermore, the assembled soft-packaged Li-S battery also exhibits high reversible capacity and stable cycling performance. The excellent electrochemical performance is attributed to the 3D hierarchical and continuously porous structure and high conductive aluminum-wall, which can effectively trap polysulfides, confine the volume expansion on cycling, and accelerate electron/ion transfer. It is expected that this high conductive metal cathode has a great future for the application of energy storage devices.

Morphological residual convolutional neural network(M-RCNN)for intelligent recognition of wear particles from artificial joints

Finding the correct category of wear particles is important to understand the tribological behavior.However,manual identification is tedious and time-consuming.We here propose an automatic morphological residual convolutional neural network(M-RCNN),exploiting the residual knowledge and morphological priors between various particle types.We also employ data augmentation to prevent performance deterioration caused by the extremely imbalanced problem of class distribution.Experimental results indicate that our morphological priors are distinguishable and beneficial to largely boosting overall performance.M-RCNN demonstrates a much higher accuracy(0.940)than the deep residual network(0.845)and support vector machine(0.821).This work provides an effective solution for automatically identifying wear particles and can be a powerful tool to further analyze the failure mechanisms of artificial joints.