Unveiling the interactions between biomaterials and heterocyclic dyes: A sustainable approach for wastewater treatment.

The present Review investigates the interactions between biomaterials and heterocyclic dyes, focusing on their potential application in sustainable wastewater treatment. Heterocyclic dyes are widely used in various industries, resulting in their widespread presence in wastewater, posing environmental challenges. This review explores the utilization of biomaterials as adsorbents for the removal of heterocyclic dyes from contaminated water sources. The interactions between biomaterials, such as cellulose, microfibrilated cellulose and lignin and different heterocyclic dyes are examined through reported experimental analysis and characterization techniques. The study evaluates the adsorption capacity, kinetics, and thermodynamics of the biomaterial-dye systems to elucidate the underlying mechanisms and optimize the treatment process. The review highlight the promising potential of biomaterial-based approaches for sustainable wastewater treatment, providing insights for the development of efficient and environmentally friendly dye removal technologies.

Construction of S-Scheme 2D/2D Crystalline Carbon Nitride/BiOIO3 van der Waals Heterojunction for Boosted Photocatalytic Degradation of Antibiotics.

Utilization of semiconductor photocatalyst materials to degrade pollutants for addressing environmental pollution problems has become a research focus in recent years. In this work, a 2D/2D S-scheme crystalline carbon nitride (CCN)/BiOIO3 (BOI) van der Waals heterojunction was successfully constructed for effectively enhancing the degradation efficiency of antibiotic contaminant. The as-synthesized optimal CCN/BOI-3 sample exhibited the highest efficiency of 80% for the photo-degradation of tetracycline (TC, 20 mg/L) after 120 min visible light irradiation, which was significantly higher than that of pure CCN and BOI. The significant improvement in photocatalytic performance is mainly attributed to two aspects: (i) the 2D/2D van der Waals heterojunction can accelerate interface carriers' separation and transfer and afford sufficient active sites; (ii) the S-scheme heterojunction elevated the redox capacity of CCN/BOI, thus providing a driving force for the degradation reaction. The degradation pathways of TC for the CCN/BOI composite were investigated in detail by liquid chromatography-mass spectrometry (LC-MS) analysis. This work provides a design idea for the development of efficient photocatalysts based on the 2D/2D S-scheme van der Waals heterojunctions.

[Analysis of the salt-stress responsive element of the promoter of peanut small GTP binding protein gene AhRabG3f].

To study the molecular mechanism of salt stress response of peanut small GTP binding protein gene AhRabG3f, a 1 914 bp promoter fragment upstream of the start codon of AhRabG3f gene (3f-P) from peanut was cloned. Subsequently, five truncated fragments (3f-P1-3f-P5) with lengths of 1 729, 1 379, 666, 510 and 179 bp were obtained through deletion at the 5' end, respectively. Plant expression vectors where these six promoter fragments were fused with the gus gene were constructed and transformed into tobacco by Agrobacterium-mediated method, respectively. GUS expression in transgenic tobacco and activity analysis were conducted. The gus gene expression can be detected in the transgenic tobacco harboring each promoter segment, among which the driving activity of the full-length promoter 3f-P was the weakest, while the driving activity of the promoter segment 3f-P3 was the strongest. Upon exposure of the transgenic tobacco to salt stress, the GUS activity driven by 3f-P, 3f-P1, 3f-P2 and 3f-P3 was 3.3, 1.2, 1.9 and 1.2 times compared to that of the transgenic plants without salt treatment. This suggests that the AhRabG3f promoter was salt-inducible and there might be positive regulatory elements between 3f-P and 3f-P3 in response to salt stress. The results of GUS activity driven by promoter fragments after salt treatment showed that elements included MYB and GT1 between 1 930 bp and 1 745 bp. Moreover, a TC-rich repeat between 682 bp and 526 bp might be positive cis-elements responsible for salt stress, and an MYC element between 1 395 bp and 682 bp might be a negative cis-element responsible for salt stress. This study may facilitate using the induced promoter to regulate the salt resistance of peanut.

FMixCutMatch for semi-supervised deep learning.

Mixed sample augmentation (MSA) has witnessed great success in the research area of semi-supervised learning (SSL) and is performed by mixing two training samples as an augmentation strategy to effectively smooth the training space. Following the insights on the efficacy of cut-mix in particular, we propose FMixCut, an MSA that combines Fourier space-based data mixing (FMix) and the proposed Fourier space-based data cutting (FCut) for labeled and unlabeled data augmentation. Specifically, for the SSL task, our approach first generates soft pseudo-labels using the model's previous predictions. The model is then trained to penalize the outputs of the FMix-generated samples so that they are consistent with their mixed soft pseudo-labels. In addition, we propose to use FCut, a new Cutout-based data augmentation strategy that adopts the two masked sample pairs from FMix for weighted cross-entropy minimization. Furthermore, by implementing two regularization techniques, namely, batch label distribution entropy maximization and sample confidence entropy minimization, we further boost the training efficiency. Finally, we introduce a dynamic labeled-unlabeled data mixing (DDM) strategy to further accelerate the convergence of the model. Combining the above process, we finally call our SSL approach as "FMixCutMatch", in short FMCmatch. As a result, the proposed FMCmatch achieves state-of-the-art performance on CIFAR-10/100, SVHN and Mini-Imagenet across a variety of SSL conditions with the CNN-13, WRN-28-2 and ResNet-18 networks. In particular, our method achieves a 4.54% test error on CIFAR-10 with 4K labels under the CNN-13 and a 41.25% Top-1 test error on Mini-Imagenet with 10K labels under the ResNet-18. Our codes for reproducing these results are publicly available at https://github.com/biuyq/FMixCutMatch.