Search

In this work, black phosphorus quantum dots (BPQDs) were decorated on hexagonal ZnIn2S4 flower-like microspheres to form zero-dimensional/two-dimensional (0D/2D) structures. Interface interactions between the BPQDs and ZnIn2S4 resulted in optimum effective charge transfer, thereby improving the photocatalytic performance of the material. Thus, the 0.2% BPQD–ZnIn2S4 sample showed 30% higher H2 evolution rates compared to pure ZnIn2S4. This study provides a simple route for the synthesis of photocatalysts. The results obtained herein can pave the way for designing effective catalysts for solar-to-chemical energy conversion and feasible approaches to obtain cheap, clean, and efficient photocatalysts. [ABSTRACT FROM AUTHOR]

Simple Summary: This study recruited 3272 non-small cell lung cancer (NSCLC) cases to analyze the predictive abilities of serum tumor markers (CEA, SCC-Ag, CYFRA 21-1, NSE, ProGRP, TPSA and CA199) for metastasis and clinical stage, and found that tumor marker levels may be indicative of tumor metastasis (intrapulmonary, lymphatic and distant metastasis) and stage. Increased CEA and CA199 provided an accurate prediction of intrapulmonary and distant metastasis. Increased CEA, CYFRA 21-1 and CA199 provided an accurate prediction of lymphatic metastasis and higher tumor stage. Combined detection of serum tumor markers can indicate tumor metastasis and stage in NSCLC patients. Objective: This study aimed to explore the roles of serum tumor markers for metastasis and stage of non-small cell lung cancer (NSCLC). Methods: This study recruited 3272 NSCLC patients admitted to the Tianjin Union Medical Center and the Tianjin Medical University Cancer Institute and Hospital. The predictive abilities of some serum tumor markers (carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC-Ag), cytokeratin-19 fragment (CYFRA 21-1), neuron-specific enolase (NSE), pro-gastrin-releasing peptide (ProGRP), total prostate-specific antigen (TPSA) and carbohydrate antigen 199 (CA199)) for NSCLC metastasis (intrapulmonary, lymphatic and distant metastasis) and clinical stage were analyzed. Results: Tumor markers exhibited different numerical and proportional distributions in NSCLC patients. Elevated CEA, CYFRA 21-1 and CA199 levels were indicative of tumor metastasis and stage. Increased CEA and CA199 provided an accurate prediction of intrapulmonary and distant metastasis with the area under the receiver operator characteristic curve (AUC) of 0.69 both (p < 0.001); Increased CEA, CYFRA 21-1 and CA199 provided an accurate prediction of lymphatic metastasis with the AUC of 0.62 (p < 0.001). Conclusion: Combined detection of serum tumor markers can indicate tumor metastasis and stage in NSCLC patients. [ABSTRACT FROM AUTHOR]

Change detection determines and evaluates changes by comparing bi-temporal images, which is a challenging task in the remote-sensing field. To better exploit the high-level features, deep-learning-based change-detection methods have attracted researchers' attention. Most deep-learning-based methods only explore the spatial–spectral features simultaneously. However, we assume the key spatial-change areas should be more important, and attention should be paid to the specific bands which can best reflect the changes. To achieve this goal, we propose the spatial–spectral joint attention network (SJAN). Compared with traditional methods, SJAN introduces the spatial–spectral attention mechanism to better explore the key changed areas and the key separable bands. To be more specific, a novel spatial-attention module is designed to extract the spatially key regions first. Secondly, the spectral-attention module is developed to adaptively focus on the separable bands of land-cover materials. Finally, a novel objective function is proposed to help the model to measure the similarity of learned spatial–spectral features from both spectrum amplitude and angle perspectives. The proposed SJAN is validated on three benchmark datasets. Comprehensive experiments have been conducted to demonstrate the effectiveness of the proposed SJAN. [ABSTRACT FROM AUTHOR]

Lithium–sulfur batteries (LSBs) are regarded as one of the most promising energy-recycling storage systems due to their high energy density (up to 2600 Wh kg−1), high theoretical specific capacity (as much as 1672 mAh g−1), environmental friendliness, and low cost. Originating from the complicated redox of lithium polysulfide intermediates, Li–S batteries suffer from several problems, restricting their application and commercialization. Such problems include the shuttle effect of polysulfides (Li2Sx (2 < x ≤ 8)), low electronic conductivity of S/Li2S/Li2S2, and large volumetric expansion of S upon lithiation. In this study, a lotus root-like nitrogen-doped carbon nanofiber (NCNF) structure, assembled with vanadium nitride (VN) catalysts, was fabricated as a 3D freestanding current collector for high performance LSBs. The lotus root-like NCNF structure, which had a multichannel porous nanostructure, was able to provide excellent (ionically/electronically) conductive networks, which promoted ion transport and physical confinement of lithium polysulfides. Further, the structure provided good electrolyte penetration, thereby enhancing the interface contact with active S. VN, with its narrow resolved band gap, showed high electrical conductivity, high catalytic effect and polar chemical adsorption of lithium polysulfides, which is ideal for accelerating the reversible redox kinetics of intermediate polysulfides to improve the utilization of S. Tests showed that the VN-decorated multichannel porous carbon nanofiber structure retained a high specific capacity of 1325 mAh g−1 after 100 cycles at 0.1 C, with a low capacity decay of 0.05% per cycle, and demonstrated excellent rate capability. [ABSTRACT FROM AUTHOR]