Kill two birds with one stone: simultaneous removal of volatile organic compounds and ozone secondary pollution by a novel photocatalytic process.

Volatile organic compounds (VOCs) originating from diverse sources with complex compositions pose threats to both environmental safety and human health. Photocatalytic treatment of VOCs has garnered attention due to its high efficacy at room temperature. However, the intricate photochemical reaction generates ozone (O3), causing secondary pollution. Herein, our work developed a novel "synergistic effect" system for photocatalytic co-treatment of VOCs and O3 secondary pollution. Under the optimized reactor conditions simulated with computational fluid dynamics (CFD), MgO-loaded g-C3N4 composites (MgO/g-C3N4) were synthesized as efficient catalysts for the photocatalytic synergistic treatment process. Density functional theory (DFT) calculations, characterization, and electron paramagnetic resonance (EPR) tests revealed that the addition of MgO reduced the band gap of g-C3N4, and increased O3 molecule adsorption in the composites, efficiently harnessing the synergistic effect of O3 to generate a significant quantity of reactive oxygen radicals, thereby facilitating the removal of VOCs and O3. This study provides new insights for simultaneous elimination of VOCs and O3 secondary pollution by a photocatalytic process.

Nondestructive estimation method of live chicken leg weight based on deep learning.

In the broiler-breeding industry, phenotype determination is critical. Leg weight is a fundamental indicator for breeding, and noninvasive testing technology can reduce damage to animals. This study proposes a broiler leg weight estimation system comprising a weight-estimation model and computed tomography (CT) acquisition equipment. The weight-estimation model can automatically process the scan results of live broiler chickens from the CT acquisition equipment. The weight-estimation model comprises an improved you-only-look-once (YOLOv5) segmentation algorithm and a random forest fitting network. The segmentation head was introduced into the YOLOv5 network, combined with a multiscale attention mechanism and an atrous spatial pyramid pooling architecture, and a new network model, YOLO- measuring chicken leg weight (YOLO-MCLW), was proposed to improve segmentation efficiency and accuracy. Morphological parameters were extracted from the obtained mask image, and a random forest network was used for fitting. The experiments show that the system exhibited an average absolute error of 7.27 g and an average percentage error of 4.82% in tests on 50 individual legs of 25 broiler chickens. The prediction R2 of broiler chicken legs can reaches 88.98%, the segmentation intersection over union result reaches 95.45%, and 37.04 images are processed per second. This system provides technical support for the part determination of broiler chickens in commercial breeding.

A colorimetric platform for sensitively differentiating telomere DNA with different lengths, monitoring G-quadruplex and dsDNA based on silver nanoclusters and unmodified gold nanoparticles.

Human telomere DNA plays a vital role in genome integrity control and carcinogenesis as an indication for extensive cell proliferation. Herein, silver nanoclusters (Ag NCs) templated by polymer and unmodified gold nanoparticles (Au NPs) are designed as a new colorimetric platform for sensitively differentiating telomere DNA with different lengths, monitoring G-quadruplex and dsDNA. Ag NCs can produce the aggregation of Au NPs, so the color of Au NPs changes to blue and the absorption peak moves to 700nm. While the telomere DNA can protect Au NPs from aggregation, the color turns to red again and the absorption band blue shift. Benefiting from the obvious color change, we can differentiate the length of telomere DNA by naked eyes. As the length of telomere DNA is longer, the variation of color becomes more noticeable. The detection limits of telomere DNA containing 10, 22, 40, 64 bases are estimated to be 1.41, 1.21, 0.23 and 0.22nM, respectively. On the other hand, when telomere DNA forms G-quadruplex in the presence of K+, or dsDNA with complementary sequence, both G-quadruplex and dsDNA can protect Au NPs better than the unfolded telomere DNA. Hence, a new colorimetric platform for monitoring structure conversion of DNA is established by Ag NCs-Au NPs system, and to prove this type of application, a selective K+ sensor is developed.