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Controlling nonlinear optical signals electrically offers many opportunities for technological developments. Lanthanide-activated nanoparticles have recently emerged as leading platforms for nonlinear upconversion of infra-red excitation within nanometric volumes. However, manipulation of upconversion emission is restricted to varying percentages of component materials, nanocrystal structure, and optical pumping conditions. Here, we report temporal modulation of anti-Stokes luminescence by coupling upconversion nanoparticles with an electrochemically responsive molecule. By electrically tailoring orbital energy levels of the molecules anchored on nanoparticle surfaces, we demonstrate reversible control of molecular absorption, resulting in dynamic colour editing of anti-Stokes luminescence at single-particle resolution. Moreover, we show that a programmable logic gate array based on opto-electrochemical modulation can be constructed to convert information-encrypted electrical signals into visible patterns with millisecond photonic readout. These findings offer insights into precise control of anti-Stokes luminescence, while enabling a host of applications from low-threshold infrared logic switches to multichannel, high-fidelity photonic circuits. Though upconversion nanoparticles (UCNPs) are attractive for infrared detecting and modulating photonic devices, devising strategies to electrically manipulate upconversion emission remain a challenge. Here, the authors report molecule-assisted opto-electrochemical modulation of UCNP luminescence.

Promoting low-carbon agriculture is vital for climate action and food security. State farms serve as crucial agricultural production bases in China and are essential in reducing China’s carbon emissions and boosting emission efficiency. This study calculates the carbon emissions of state farms across 29 Chinese provinces using the IPCC method from 2010 to 2022. It also evaluates emission efficiency with the Super-Slack-Based Measure (Super-SBM model) and analyzes influencing factors using the Logarithmic Mean Divisia Index (LMDI) method. The findings suggest that the three largest carbon sources are rice planting, chemical fertilizers, and land tillage. Secondly, agricultural carbon emissions in state farms initially surge, stabilize with fluctuations, and ultimately decline, with higher emissions observed in northern and eastern China. Thirdly, the rise of agricultural carbon emission efficiency is driven primarily by technological progress. Lastly, economic development and industry structure promote agricultural carbon emissions, while production efficiency and labor scale reduce them. To reduce carbon emissions from state farms in China and improve agricultural carbon emission efficiency, the following measures can be taken: (1) Improve agricultural production efficiency and reduce carbon emissions in all links; (2) Optimize the agricultural industrial structure and promote the coordinated development of agriculture; (3) Reduce the agricultural labor scale and promote the specialization, professionalization, and high-quality development of agricultural labor; (4) Accelerate agricultural green technology innovation and guide the green transformation of state farms. This study enriches the theoretical foundation of low-carbon agriculture and develops a framework for assessing carbon emissions in Chinese state farms, offering guidance for future research and policy development in sustainable agriculture.

Traditional opera is continuously involved in the construction of placeness because of its close connection with local culture, and the flow of the meaning of placeness has become a hot spot of cultural geography research. This study examines the driving factors and mechanisms of constructing placeness in Huangmei Opera from the perspective of structuration theory. It adopts qualitative research and positivist methodology to analyze the mutual influence and constructive relationship between Huangmei Opera and placeness. The results reveal that under the structural adjustment of the cultural system reform, multiple subjects respond to the impact of the structural adjustment through the action practices of place marketing and leisure participation, combined with the elements of placeness that the city itself possesses. The study confirms that Huangmei Opera, with its local characteristics, is a quintessential example of placeness construction and that Huangmei Opera achieves placeness construction through the interplay of structure, action, and place.

This paper aims to study the spatiotemporal variations in PM2.5 concentrations between 2015 and 2020 in the Fen–Wei Plain. The AOD products of MCD19A2 based on MAIAC were utilized. Besides of AOD, some of its arithmetic values were also introduced to determine the best variable. AOD was determined as the variable for retrieval because of its highest correlation coefficient with PM2.5, reaching up to 0.526**. Several statistical models and SVR have been used and compared for establishing the best retrieval model. Results showed, the determination coefficient r2 of the cubic function was the best (r2 = 0.294**), and the correlation between the predicted and measured values was strong (k = 1.1478, r2 = 0.532**). Both monthly and annual variations of PM2.5 concentrations were researched, which indicated the changing trend was fluctuating. The mean value in 2015 was the largest, reaching up to 38.02 μg/m3, the smallest value of 28.28 μg/m3 appeared in 2019. It can be concluded the influencing mechanism of PM2.5 was complicated, as proven by correlation analysis and gray relational analysis. The influencing factors should be introduced as auxiliary data to promote the retrieval accuracy. With advancements in remote sensing technology, the monitoring efficiency can be effectively improved, which will greatly promote sustainable development.

Optoelectronic effects differentiating absorption of right and left circularly polarized photons in thin films of chiral materials are typically prohibitively small for their direct photocurrent observation. Chiral metasurfaces increase the electronic sensitivity to circular polarization, but their out-of-plane architecture entails manufacturing and performance trade-offs. Here, we show that nanoporous thin films of chiral nanoparticles enable high sensitivity to circular polarization due to light-induced polarization-dependent ion accumulation at nanoparticle interfaces. Self-assembled multilayers of gold nanoparticles modified with l-phenylalanine generate a photocurrent under right-handed circularly polarized light as high as 2.41 times higher than under left-handed circularly polarized light. The strong plasmonic coupling between the multiple nanoparticles producing planar chiroplasmonic modes facilitates the ejection of electrons, whose entrapment at the membrane–electrolyte interface is promoted by a thick layer of enantiopure phenylalanine. Demonstrated detection of light ellipticity with equal sensitivity at all incident angles mimics phenomenological aspects of polarization vision in marine animals. The simplicity of self-assembly and sensitivity of polarization detection found in optoionic membranes opens the door to a family of miniaturized fluidic devices for chiral photonics.Chiral gold nanoparticles coated with enantiomerically pure phenylalanine were assembled into nanoporous membranes, whose ionic conductivity depends on the handedness of the incident circularly polarized light.

Controlling and channeling light emissions from unpolarized quantum dots into specific directions with chiral polarization remains a key challenge in modern photonics. Stacked metasurface designs offer a potential compact solution for chirality and directionality engineering. However, experimental observations of directional chiral radiation from resonant metasurfaces with quantum emitters remain obscure. In this paper, we present experimental observations of unidirectional chiral emission from a twisted bi-layer metasurface via multi-dimensional control, including twist angle, interlayer distance, and lateral displacement between the top and bottom layers, as enabled by doublet alignment lithography (DAL). First, maintaining alignment, the metasurface demonstrates a resonant intrinsic optical chirality with near-unity circular dichroism of 0.94 and reflectance difference of 74%, where a high circular dichroism greater than 0.9 persists across a wide range of angles from −11 to 11 degrees. Second, engineered lateral displacement induces a unidirectional chiral resonance, resulting in unidirectional chiral emission from the quantum dots deposited onto the metasurface. Our bi-layer metasurfaces offer a universal compact platform for efficient radiation manipulation over a wide angular range, promising potential applications in miniaturized lasers, grating couplers, and chiral nanoantennas. Simultaneous control of the direction and polarization of quantum emission using photonic nanostructures is a long-standing challenge in photonics. Here, the authors experimentally demonstrate unidirectional chiral emission from a twisted bilayer metasurface with multi-dimensional control.

Background Gastric cancer is one of the major causes of cancer-related mortality worldwide. Most of patients presenting with inoperable gastric cancers rely on systemic chemotherapy for prolongation of survival. Doxorubicin (DOX) is one of the important agents against gastric cancer. Acquired DOX-resistance severely impedes the chemotherapeutic effect, invariably leading to poor prognosis. Resveratrol (RES) as a kind of phytoalexin has demonstrated anti-tumor functions in breast cancer and myeloid leukemia, but its function and mechanism are still unknown in gastric cancer treatment. Methods CCK8 assay was used to detect the cytotoxicity of DOX and RES to gastric cancer cells. DOX-resistant subclone cell line (SGC7901/DOX) was derived from SGC7901 cells exposed to stepwise increasing concentrations of DOX treatment. We measured the migratory capabilities of SGC7901/DOX cells by Cell scratch test and Transwell assay. SGC7901/DOX cells were treated with DOX, RES, neither or both. Then we analyzed cell survival by CCK8 assay, colony formation by Colony-forming assay, cell apoptosis by Annexin-V-FITC and PI dual staining assay and cell migration by Cell scratch test and Transwell assay. Western blotting was conducted to detect the protein expressions of PTEN/Akt signaling pathway and EMT-related markers. Immunofluorescence was performed to confirm the EMT-related markers expressions. The xenograft model was used to assess the effect of DOX and RES in vivo. The key molecules associated with proliferation, apoptosis and EMT were evaluated by immunohistochemistry in tumor specimens. Results SGC7901/DOX cells acquired drug resistance and enhancive migratory capability. RES enabled SGC7901/DOX cells to regain DOX sensitivity, mitigated the aggressive biological features, promoted cell apoptosis in vitro and inhibited tumor growth in vivo. Mechanistic studies revealed that SGC7901/DOX cells underwent epithelial-mesenchymal transition (EMT) which was induced by Akt activation, and through activating PTEN, RES inhibited the Akt pathway, and then achieved the reversion of EMT. Conclusion RES serves as a novel solution to reverse the DOX-resistance of gastric cancer via preventing EMT by modulating PTEN/Akt signaling pathway. DOX-RES combined treatment provides a promising future for gastric cancer patients to postpone drug resistance and prolong survival.

This study investigates the shear mechanical behavior of soft rock—grout coupled structures through triaxial shear tests and particle flow simulations on sandstone-resin composite specimens under varying normal stresses and immersion times. Key findings include: (1) Intensified hydration damage compromises shear resistance in both rock and interfaces, amplifies deformation, and degrades bearing capacity. (2) Elevated normal stress constrains microcrack coalescence, enhances bearing capacity. Failure modes of specimens—classified as interfacial shear sliding, mixed shear failure, or shear failure occurs exclusively within rock—depending on stress levels and hydration duration. (3) Prolonged immersion reduces energy thresholds for bond rupture, shifting crack propagation from abrupt surges to gradual increments. Weak zones migrate from interfaces to external rock. (4) Increased normal stress raises energy storage limits, suppresses microcrack coalescence, and strengthens weak zones. This study revealing the critical control of hydration damage and stress confinement on energy thresholds at the rock-grout interface, providing a theoretical basis for long-term stability prediction of anchorage structures.

Achieving high-precision anomaly detection with incomplete sensor data is a critical challenge in industrial automation and intelligent manufacturing. This incompleteness often results from sensor failures, environmental interference, occlusions, or acquisition cost constraints. This study explicitly targets both types of incompleteness commonly encountered in industrial multimodal inspection: (i) incomplete sensor data within a given modality, such as partial point cloud loss or image degradation, and (ii) incomplete modalities, where one sensing channel (RGB or 3D) is entirely unavailable. By jointly addressing intra-modal incompleteness and cross-modal absence within a unified cross-distillation framework, our approach enhances anomaly detection robustness under both conditions. First, a teacher–student cross-modal distillation mechanism enables robust feature learning from both RGB and 3D modalities, allowing the student network to accurately detect anomalies even when a modality is missing during inference. Second, a dynamic voxel resolution adjustment with edge-retention strategy alleviates the computational burden of 3D point cloud processing while preserving crucial geometric features. By jointly enhancing robustness to missing modalities and improving computational efficiency, our method offers a resilient and practical solution for anomaly detection in real-world manufacturing scenarios. Extensive experiments demonstrate that the proposed method achieves both high robustness and efficiency across multiple industrial scenarios, establishing new state-of-the-art performance that surpasses existing approaches in both accuracy and speed. This method provides a robust solution for high-precision perception under complex detection conditions, significantly enhancing the feasibility of deploying anomaly detection systems in real industrial environments.

Traditional fossil identification relies on the rich experience and knowledge of paleontologists, and existing intelligent identification methods mainly rely on deep learning to train on a large number of fossil graphic samples to achieve a high degree of precision. In order to solve the above problems and still be able to accurately recognize small samples of rare fossils, we try to use the generative adversarial network (GAN) combined with ResNet50, EfficientNet, and customized CNN architectures, which are applied to the identification of small samples of fossils. First of all, the generator of GAN is fully trained, using it to generate a large number of samples to expand the dataset, enriching the image features extracted by the model, and then through the neural network to analyze the image ion computation, and finally, the best fossil identification model is trained through multiple iterations. Using the method of this paper on the same dataset with a data enhancement method for comparison experiments, the experimental results show that the accuracy rate reaches 93% in the case of epochs 100, higher than the other experimental results, and has a significant advantage in the recognition of fossils with scarce samples. Expanding the dataset using generative adversarial network (GAN) coupled with neural networks to identify small samples of rare fossils.