Achieving Simplified and Tunable Flexibility in Carborane-Based Emitters for Quantitative Vapochromic VOC Sensing.

Photoluminescence (PL) sensing of volatile organic compounds (VOCs) represents a convenient and economic detection method toward air pollutants. However, tetraphenylethylene (TPE)-based and recent carborane (Cb)-based sensors retained multiple sites that are responsive to VOC stimulation, making quantitative PL sensing rather challenging. Rendering the simplified and tunable flexibility in the PL sensors is key to achieve the quantitative target.

Amorphous NiFe Oxide-based Nanoreactors for Efficient Electrocatalytic Water Oxidation.

Synergy engineering is an important way to enhance the kinetic activity of oxygen-evolution-reaction (OER) electrocatalysts. Here, we fabricated NiFe amorphous nanoreactor (NiFe-ANR) oxide as OER electrocatalysts via a mild self-catalytic reaction. Firstly, the amorphousness helps transform NiFe-ANR into highly active hydroxyhydroxides, and its many fine-grain boundaries increase active sites.

Inference of emission history of neonicotinoid pesticides from marine sediment cores impacted by riverine runoff of a developed agricultural region: The Pearl River Basin, China.

Neonicotinoids (NEOs), as the most-consumed pesticides on a global scale, have posed a serious threat to human health and ecological environment. Information regarding the emission history of NEOs is of great importance to improve the prediction of their environmental loading and biological risk potential. In the present study, contamination levels and compositions of 12 NEOs were identified in 8 sediment cores from the Lingdingyang Estuary, which was impacted by agricultural emissions in riverine runoff of the Pearl River Basin for centuries.

Designing NAZO@BC electrodes for enhanced elimination of hydrophilic organic pollutants in heterogeneous electro-Fenton system: Insights into the detoxification mediated by O and •OH.

Hydrophilic organic pollutants (HLOPs) in effluents of wastewater treatment plants are more prevalent than hydrophobic counterparts, therefore development of upstream processes that can effectively enhance the removal of HLOPs can substantially enhance overall treatment performance. To bridge this gap, 3D electrodes made of biochar-supported Al-ZnO nanoparticles (NAZO@BC) applied in heterogeneous electro-Fenton (EF) system, abbreviated as NBE-EF system, is rationally designed for enhanced elimination of HLOPs in wastewater. Our analysis indicates the NBE-EF system results in an efficient THM elimination, 42.

Crucial roles of 3D-MoO-PBC cocatalytic electrodes in the enhanced degradation of imidacloprid in heterogeneous electro-Fenton system: Degradation mechanisms and toxicity attenuation.

Imidacloprid (IMI), as the most-consumed pesticide, has posed a severe threat to the water ecosystem due to its recalcitrance and inefficient elimination in the traditional wastewater treatment. Herein, a heterogeneous electro-Fenton (EF) system coupled with 3D-MoO-porous biochar (PBC) cocatalytic electrodes, abbreviated as 3D-MPE-EF, is initially applied to promote the elimination of IMI in the agrochemical wastewater from pesticide production. The elimination rate of IMI by 3D-MPE-EF system is 18.

Heterogeneous electro-Fenton using three-dimension NZVI-BC electrodes for degradation of neonicotinoid wastewater.

Neonicotinoids (NEOs), as the most widely used pesticides, pose a serious threat to water ecosystems, especially clothianidin (CLO). However, the degradation behavior of CLO, as a new type of persistent organic pollutant, is rarely studied in wastewater treatment. To bridge this gap, heterogeneous electro-Fenton system using three-dimension electrodes made of biochar-supported zero-valent iron nanoparticle hybrid material (NZVI-BC), abbreviated as 3D-ICE-EF system, is invented and initially applied in CLO wastewater degradation, without the addition of Fenton reagent.

Multicenter Computer-Aided Diagnosis for Lymph Nodes Using Unsupervised Domain-Adaptation Networks Based on Cross-Domain Confounding Representations.

To achieve the robust high-performance computer-aided diagnosis systems for lymph nodes, CT images may be typically collected from multicenter data, which cause the isolated performance of the model based on different data source centers. The variability adaptation problem of lymph node data which is related to the problem of domain adaptation in deep learning differs from the general domain adaptation problem because of the typically larger CT image size and more complex data distributions. Therefore, domain adaptation for this problem needs to consider the shared feature representation and even the conditioning information of each domain so that the adaptation network can capture significant discriminative representations in a domain-invariant space.