A Cu(I)-Based MOF with Nonlinear Optical Properties and a Favorable Optical Limit Threshold.

The exploitation of high-performance third-order nonlinear optical (NLO) materials that have a favorable optical limit (OL) threshold is essential due to a rise in the application of ultra-intense lasers. In this study, a Cu-based MOF (denoted as Cu-bpy) was synthesized, and its third-order NLO and OL properties were investigated using the Z-scan technique with the nanosecond laser pulse excitation set at 532 nm. The Cu-bpy exhibits a typical rate of reverse saturable absorption (RSA) with a third-order nonlinear absorption coefficient of 100 cm GW and a favorable OL threshold of 0.

Disentangled Active Learning on Graphs.

Active learning on graphs (ALG) has emerged as a compelling research field due to its capacity to address the challenge of label scarcity. Existing ALG methods incorporate diversity into their query strategies to maximize the gains from node sampling, improving robustness and reducing redundancy in graph learning. However, they often overlook the complex entanglement of latent factors inherent in graph-structured data.

Supervised analysis of alternative polyadenylation from single-cell and spatial transcriptomics data with spvAPA.

Alternative polyadenylation (APA) is an important driver of transcriptome diversity that generates messenger RNA isoforms with distinct 3' ends. The rapid development of single-cell and spatial transcriptomic technologies opened up new opportunities for exploring APA data to discover hidden cell subpopulations invisible in conventional gene expression analysis. However, conventional gene-level analysis tools are not fully applicable to APA data, and commonly used unsupervised dimensionality reduction methods often disregard experimentally derived annotations such as cell type identities.

DFCL: Dual-pathway fusion contrastive learning for blind single-image visible watermark removal.

Digital image watermarking is a prevalent method for image copyright protection. As watermark embedding techniques evolve, research in copyright protection has increasingly extended into watermark removal. Recent advancements in deep learning and generative technologies have led to the development of public watermark removal solutions, addressing issues such as plagiarized, illegal, or outdated watermarks while driving significant improvements in robust watermark embedding.

, a Novel Pestalotioid Fungus Associated with Yellow Rose Branch Canker Disease.

Yellow rose () is a common ornamental shrub species widely cultivated in China. However, canker disease symptoms were discovered during our investigations in Beijing and Xinjiang, China. The fungal isolates were obtained from diseased barks and identified using combined methods of morphology and phylogeny based on a partial region of ITS, LSU, , , and sequences.

Integrated Analysis of Transcriptome and Metabolome in the Brain After Cold Stress of Red Tilapia During Overwintering.

Cold stress during overwintering is considered a bottleneck problem limiting the development of the red tilapia ( spp.) industry, and the regulation mechanism is currently not well understood. In this study, the fish (initial weight: 72.

Structural Elucidation and In Silico-Aided Toxicity Prediction of Forced Degradation Products of Ginsenoside Re Using Ultra-High-Performance Liquid Chromatography Equipped with a Diode Array Detector and Charged Aerosol Detector (UHPLC-DAD-CAD) and Liquid Chromatography Coupled to a High-Resolution Mass Detector (LC-HRMS).

Ginsenoside Re was the major bioactive component found rich in C. A. Meyer, which exerted excellent cardiovascular protection, anti-inflammatory, and anti-oxidation effects.

Exploring the risk factors and clustering patterns of periodontitis in patients with different subtypes of diabetes through machine learning and cluster analysis.

Aim: To analyse the risk factors contributing to the prevalence of periodontitis among clusters of patients with diabetes and to examine the clustering patterns of clinical blood biochemical indicators.

Materials And Methods: Data regarding clinical blood biochemical indicators and periodontitis prevalence among 1804 patients with diabetes were sourced from the National Health and Nutrition Examination Survey (NHANES) database spanning 2009 to 2014. A clinical prediction model for periodontitis risk in patients with diabetes was constructed via the XGBoost machine learning method.

Efficient Organic Light-Emitting Diodes Obtained by Introducing Gadolinium (Gd) Complexes Based on Pyrazolone Derivative Ligands as Hole Trappers.

The utilization of lanthanide (Ln) complexes in the realm of organic light-emitting diodes (OLEDs) has garnered extensive interest, particularly in their role as luminescent materials or electron trappers. A series of gadolinium (Gd) complexes with energy levels of high HOMO/LUMO and different triplet state energies were designed and synthesized by introducing substituents with different electronic effects onto the pyrazolone derivative ligands. Subsequently, these complexes were precisely purified by vacuum sublimation and codoped into the light-emitting layer (EML) of the OLEDs.

The mRNA and protein datasets after cold stress of red tilapia.

The cold stress during overwintering is considered the bottleneck of red tilapia industry. In this study, the water temperature (WT) was reduced by 2 °C per day from 20 °C to 8 °C in the cold (C) group. Then transcriptome of brain(B), gill(G), liver(L) and skin(S) tissues and proteome of G, L and S tissues were performed in C and Normal (N) (WT: 20 °C) group.

Household residential energy choices in green transition: insights from a household survey in rural China.

It has been widely recognized that accelerating green residential energy transition from traditional solid fuels (biomass and coal) to clean and high-efficient energy sources is critical for rural sustainable development. However, little attention has been paid to estimate panel data discrete choice models to analyze the dynamic behavior information of individual households in the process of energy transition. Hence, this paper investigates green residential energy transition using a panel dataset from 3308 rural households in eight provinces of China in 2015 and 2018.

Paclitaxel-Induced Hepatotoxicity in Ovarian Cancer Patients: A Case Report.

Paclitaxel plus carboplatin is the most common regimen for the treatment of ovarian cancer. While generally effective, these chemotherapy agents can cause adverse events such as myelotoxicity, nausea, vomiting, and rarely, hepatotoxicity. Paclitaxel is associated with mild elevations in serum aminotransferase levels, but significant hepatotoxicity is uncommon, particularly in patients without prior liver disease.

Emission characteristics, environmental impacts and health risk assessment of volatile organic compounds from the typical chemical industry in China.

To study the volatile organic compounds (VOCs) emission characteristics of industrial enterprises in China, 6 typical chemical industries in Yuncheng City were selected as research objects, including the modern coal chemical industry (MCC), pharmaceutical industry (PM), pesticide industry (PE), coking industry (CO) and organic chemical industry (OC). The chemical composition of 91 VOCs was quantitatively analyzed. The results showed that the emission concentration of VOCs in the chemical industry ranged from 1.

White Organic Light-Emitting Diodes with External Quantum Efficiency of 20.77% at 10000 cd m and Ultra-High Color Stability by Controlling Exciton Distribution.

Although brightness and efficiency have been continually improved, the inability to achieve superior efficiency, color stability, and low-efficiency roll-off simultaneously in white organic light-emitting diodes (OLEDs) remains a knotty problem restricting the commercial application. In this paper, emission balance for two different horizontal orientation emitting molecules is maintained by using hole transport materials and bipolar host materials to control carriers' recombination and exciton diffusion. Impressively, the obtained devices exhibit extremely stable white emission with small chromaticity coordinates variation of (0.

A CT-based radiomics model for predicting lymph node metastasis in hepatic alveolar echinococcosis patients to support lymph node dissection.

Background: Hepatic alveolar echinococcosis (AE) is a severe zoonotic parasitic disease, and accurate preoperative prediction of lymph node (LN) metastasis in AE patients is crucial for disease management, but it remains an unresolved challenge. The aim of this study was to establish a radiomics model for the preoperative prediction of LN metastasis in hepatic AE patients.

Methods: A total of 100 hepatic AE patients who underwent hepatectomy and hepatoduodenal ligament LN dissection at Qinghai Provincial People's Hospital between January 2016 and August 2023 were included in the study.

Cloud computing load prediction method based on CNN-BiLSTM model under low-carbon background.

With the establishment of the "double carbon" goal, various industries are actively exploring ways to reduce carbon emissions. Cloud data centers, represented by cloud computing, often have the problem of mismatch between load requests and resource supply, resulting in excessive carbon emissions. Based on this, this paper proposes a complete method for cloud computing carbon emission prediction.

Advanced electrochemical membrane technologies for near-complete resource recovery and zero-discharge of urine: Performance optimization and evaluation.

The depletion of nutrient sources in fertilizers demands a paradigm shift in the treatment of nutrient-rich wastewater, such as urine, to enable efficient resource recovery and high-value conversion. This study presented an integrated bipolar membrane electrodialysis (BMED) and hollow fiber membrane (HFM) system for near-complete resource recovery and zero-discharge from urine treatment. Computational simulations and experimental validations demonstrated that a higher voltage (20 V) significantly enhanced energy utilization, while an optimal flow rate of 0.

Crystallinity Control and Strain Release in Wide-Bandgap Perovskite Film via Seed-Induced Growth for Efficient Photovoltaics.

The seed method stands out as a straightforward and efficient approach for fabricating high-performance perovskite solar cells (PSCs). In this study, we propose the utilization of an antisolvent as an additive to induce crystal seeding, thereby facilitating the growth of wide-bandgap perovskite grains. Specifically, we introduce three commonly used antisolvents─ethyl acetate (EA), isopropanol (IPA), and chlorobenzene (CB)─directly into the perovskite precursor solution to generate perovskite seeds, which serve to promote subsequent nucleation.