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In the conventional dual-loop vector control strategy of Voltage Source Converter-based High Voltage Direct Current (VSC-HVDC) systems employed in offshore wind farms, challenges such as complex PI parameter-tuning and slow response speed exist. Furthermore, a single-phase bridge-arm fault in the converter station can lead to a change in system parameters, resulting in the failure of the original control strategy. Hence, this paper proposes a fault-tolerant control strategy for grid-connected offshore wind farms, based on model predictive control (MPC). Firstly, the predictive models for both normal and fault-tolerant states of the grid-side converter station are established based on the system structure of the grid-side converter station and a super-local model. Subsequently, a cost function is constructed using the power error, with the optimization objective set as the value function. This approach allows for accurate prediction of the future switching states of the grid-tied inverter to track the reference power. Finally, a simulation model of the offshore wind power grid system is established in the MATLAB/Simulink (2022a) environment. The results demonstrate that the grid-side converter station can effectively operate in a fault-tolerant manner under the proposed control strategy, thereby enhancing the disturbance resistance and fault-recovery capabilities of the offshore wind VSC-HVDC system. [ABSTRACT FROM AUTHOR]

In this paper, an interesting γ′-carbon 1,6-conjugate addition for phosphine-catalyzed α-succinimide substituted allenoates has been disclosed. A wide array of substrates was found to participate in the reaction, resulting in the production of diverse 4-diarylmethylated 3,4-disubstituted maleimides with satisfactory to outstanding yields. Furthermore, a plausible mechanism for the reaction was proposed by the investigators. [ABSTRACT FROM AUTHOR]

In recent years, asphalt pavement has been subjected to varied environmental conditions during its service life, conditions that predispose it to deformation and cracking. To enhance the performance of asphalt pavement, rock asphalt has been selected as a modifier due to its good compatibility with virgin asphalt binder and its ability to improve the fatigue cracking resistance of asphalt mixtures. Although scholars have conducted some studies on rock asphalt mixtures, research on the fatigue and self-healing performance of these mixtures under conditions such as ultraviolet (UV) aging and freeze–thaw remains limited. This paper presents findings from a study that employs a combined fatigue-healing test to assess the impact of such complex environmental factors on the fatigue and self-healing properties of fine aggregate matrix (FAM) mixtures containing three types of rock asphalts, i.e., Buton, Qingchuan (QC), and Uintaite Modifier (UM). The analysis of fatigue-healing test results, grounded in viscoelastic continuum damage (VECD) theory, indicates that rock asphalt can extend the fatigue life of FAM mixtures, albeit with a concomitant decrease in their self-healing capabilities. The study further reveals that UV aging, freeze–thaw, and UV aging–freeze–thaw conditions all led to a diminution in the fatigue and self-healing properties of FAM mixtures. However, FAM mixtures containing rock asphalt demonstrated greater resilience against these reductions. Atomic force microscope (AFM) results indicate that UV aging reduced the number of bee-structures and enlarged their area, whereas the incorporation of rock asphalt enhanced the uniformity of these structures' distribution, thereby improving the fatigue cracking resistance of FAM mixtures. Fourier transform infrared spectroscopy (FTIR) analysis reveals that while UV aging increased the carbonyl and sulfoxide indices within the asphalt binder, rock asphalt is effective in mitigating this effect to a certain degree, thereby enhancing the aging resistance of FAM mixtures. [ABSTRACT FROM AUTHOR]

Target detection technology based on unmanned aerial vehicle (UAV)-derived aerial imagery has been widely applied in the field of forest fire patrol and rescue. However, due to the specificity of UAV platforms, there are still significant issues to be resolved such as severe omission, low detection accuracy, and poor early warning effectiveness. In light of these issues, this paper proposes an improved YOLOX network for the rapid detection of forest fires in images captured by UAVs. Firstly, to enhance the network's feature-extraction capability in complex fire environments, a multi-level-feature-extraction structure, CSP-ML, is designed to improve the algorithm's detection accuracy for small-target fire areas. Additionally, a CBAM attention mechanism is embedded in the neck network to reduce interference caused by background noise and irrelevant information. Secondly, an adaptive-feature-extraction module is introduced in the YOLOX network's feature fusion part to prevent the loss of important feature information during the fusion process, thus enhancing the network's feature-learning capability. Lastly, the CIoU loss function is used to replace the original loss function, to address issues such as excessive optimization of negative samples and poor gradient-descent direction, thereby strengthening the network's effective recognition of positive samples. Experimental results show that the improved YOLOX network has better detection performance, with mAP@50 and mAP@50_95 increasing by 6.4% and 2.17%, respectively, compared to the traditional YOLOX network. In multi-target flame and small-target flame scenarios, the improved YOLO model achieved a mAP of 96.3%, outperforming deep learning algorithms such as FasterRCNN, SSD, and YOLOv5 by 33.5%, 7.7%, and 7%, respectively. It has a lower omission rate and higher detection accuracy, and it is capable of handling small-target detection tasks in complex fire environments. This can provide support for UAV patrol and rescue applications from a high-altitude perspective. [ABSTRACT FROM AUTHOR]

Focal cerebral ischemia-reperfusion injury is closely related to hyperglycemia and gut microbiota imbalance, while gut microbiota contributes to the regulation of brain function through the gut-brain axis. Previous studies in patients with diabetes have found that 'yam gruel' is a classic medicated diet made from Dioscorea polystachya, increases the content of Bifidobacterium, regulates oxidative stress, and reduces fasting blood glucose levels. The research reported here investigated the effects of 'yam gruel' on the cognitive function of streptozotocin-induced diabetic rats with focal cerebral ischemia-reperfusion injury and explored the mechanism underlying the role of the gut-brain axis in this process. 'Yam gruel' was shown to improve cognitive function as indicated by increased relative content of probiotic bacteria, and short-chain fatty acids in the intestinal tract and cerebral cortex reduced oxidative stress and inflammatory response and promotion of the expression of neurotransmitters and brain-derived neurotrophic factor. Thus, it is concluded that 'yam gruel' has a protective effect on cognitive function via a mechanism related to the gut-brain axis.

In this study, colorimetric indicator nanofiber films based on ethyl cellulose (EC)/gelatin (G) incorporating purple sweet potato anthocyanins (PSPAs) were designed via electrospinning technology for monitoring and maintaining the freshness of pork. The film presented good structural integrity and stability in a humid environment with water vapor permeability (WVP) of 6.07 ± 0.14 × 10−11 g·m−1s−1Pa−1 and water contact angle (WCA) of 81.62 ± 1.43°. When PSPAs were added into the nanofiber films, the antioxidant capacity was significantly improved (p < 0.05) with a DPPH radical scavenging rate of 68.61 ± 1.80%. The nanofiber films showed distinguishable color changes as pH changes and was highly sensitive to volatile ammonia than that of casting films. In the application test, the film color changed from light pink (fresh stage) to light brown (secondary freshness stage) and then to brownish green (spoilage stage), indicating that the nanofiber films can be used to detect the real-time freshness of pork during storage. Meanwhile, it could prolong the shelf life of pork by inhibiting the oxidation degree. Hence, these results suggested that the EC/G/PSPA film has promising future for monitoring freshness and extending shelf life of pork. [ABSTRACT FROM AUTHOR]